diff --git a/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Download Pacific Physics Volume 1 PDF and Ace Your A Level Physics Exams.md b/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Download Pacific Physics Volume 1 PDF and Ace Your A Level Physics Exams.md
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-<h1>Pacific Physics Volume 1: A Comprehensive Guide for A Level Students</h1>
- <p>If you are an A level student who is looking for a reliable and comprehensive physics textbook, you might have heard of Pacific Physics Volume 1. This book is widely used by students and teachers in Singapore and other countries as a reference and study guide for physics. But what exactly is Pacific Physics Volume 1, and why should you read it? In this article, we will answer these questions and more. We will also show you how to download Pacific Physics Volume 1 in PDF format, so you can access it anytime and anywhere.</p>
- <h2>What is Pacific Physics Volume 1?</h2>
- <p>Pacific Physics Volume 1 is a physics textbook written by Poh Liong Yong, a former lecturer at Nanyang Technological University in Singapore. It was first published in 1996 by Pan Pacific, a leading educational publisher in Asia. It is designed to cover the topics required for the A level physics examination, which is taken by students who wish to pursue higher education in science, engineering, or medicine.</p>
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- <h3>Who is the author of Pacific Physics Volume 1?</h3>
- <p>Poh Liong Yong is a well-known physics educator and author in Singapore. He has over 30 years of experience in teaching physics at various levels, from secondary school to university. He has also written several other physics books, such as Essential Concepts of Physics, Advanced Level Practical Work for Physics, and Understanding Mechanics.</p>
- <h3>What are the main topics covered in Pacific Physics Volume 1?</h3>
- <p>Pacific Physics Volume 1 covers the following topics:</p>
- <ul>
-<li>Units and Dimensions</li>
-<li>Measurements</li>
-<li>Vectors</li>
-<li>Static Equilibrium</li>
-<li>Kinematics</li>
-<li>Dynamics</li>
-<li>Pressure in Liquids and Archimedes' Principle</li>
-<li>Circular Motion</li>
-<li>Universal Gravitation</li>
-<li>Simple Harmonic Motion</li>
-<li>Elasticity</li>
-<li>Thermometry</li>
-<li>Heat Capacity and Latent Heat</li>
-<li>The Gas Laws</li>
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- <p>Pacific Physics Volume 1 is different from other physics textbooks in several ways:</p>
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-<li>It follows the latest syllabus and exam format of the A level physics examination, which is based on the Cambridge International AS and A Level Physics syllabus.</li>
-<li>It provides clear and concise explanations of each concept, with diagrams, graphs, tables, and formulas to illustrate them.</li>
-<li>It includes numerous examples and worked solutions to demonstrate how to apply the concepts to solve problems.</li>
-<li>It offers a variety of exercises at the end of each chapter, ranging from multiple-choice questions to structured questions to essay questions. The answers and solutions are also provided at the end of the book.</li>
-<li>It contains review questions and summary points at the end of each topic, to help students revise and consolidate their learning.</li>
-<li>It features practical work sections that introduce students to the experimental aspects of physics, with instructions on how to perform experiments and record observations.</li>
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- <p>If you want to access Pacific Physics Volume 1 anytime and anywhere, you might want to download it in PDF format. However, before you do so, you should be aware of the benefits and drawbacks of downloading it in PDF format. You should also know where to find reliable sources to download it in PDF format.</p>
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-<tr><td>Google Books</td><td>A service that allows users to preview or buy books online.</td><td></td></tr>
-<td>A non-profit library that offers free access to millions of books, movies, music, websites, etc.</td><td></td></tr>
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- <h2>Conclusion</h2>
- <p>Pacific Physics Volume 1 is a physics textbook written by Poh Liong Yong, a former lecturer at Nanyang Technological University in Singapore. It is designed to cover the topics required for the A level physics examination, which is taken by students who wish to pursue higher education in science, engineering, or medicine. It provides clear explanations and examples for each concept, and offers plenty of exercises and solutions for practice and revision. It also introduces students to the experimental aspects of physics, with practical work sections. Pacific Physics Volume 1 is a valuable resource for anyone who wants to learn physics at an advanced level. You can download it in PDF format from reputable sources such as Google Books, Internet Archive, or Goodreads. However, you should be aware of the benefits and drawbacks of downloading it in PDF format, and respect the author's rights and not distribute or reproduce the PDF file without permission.</p>
- <h2>FAQs</h2>
- <p>Here are some frequently asked questions about Pacific Physics Volume 1:</p>
- <ol>
-<li>What is the difference between Pacific Physics Volume 1 and Volume 2?</li>
-<p>Pacific Physics Volume 1 covers the topics required for the AS level physics examination, while Pacific Physics Volume 2 covers the topics required for the A level physics examination. The AS level physics examination is taken at the end of the first year of A level studies, while the A level physics examination is taken at the end of the second year of A level studies.</p>
-<li>How many pages does Pacific Physics Volume 1 have?</li>
-<p>Pacific Physics Volume 1 has 560 pages in total.</p>
-<li>How much does Pacific Physics Volume 1 cost?</li>
-<p>The price of Pacific Physics Volume 1 varies depending on the source and edition. The latest edition (2019) costs SGD$39.90 on Pan Pacific's website.</p>
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-<p>Pacific Physics Volume 1 is suitable for self-study, as it provides clear explanations and examples for each concept, and offers plenty of exercises and solutions for practice and revision. However, it is advisable to consult a teacher or tutor if you encounter any difficulties or doubts while studying.</p>
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-<p>Pacific Physics Volume 1 is only available in English.</p>
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diff --git a/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/Download Black Duck and Get Complete Visibility into Your Application and Container Composition.md b/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/Download Black Duck and Get Complete Visibility into Your Application and Container Composition.md
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--- a/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/Download Black Duck and Get Complete Visibility into Your Application and Container Composition.md	
+++ /dev/null
@@ -1,127 +0,0 @@
-
-<h1>How to Download Black Duck: A Guide for Open Source Security and Compliance</h1>
-<p>Open source software is widely used in modern applications and containers, but it also comes with some risks that need to be managed. These include security vulnerabilities, license compliance issues, and operational challenges. How can developers and organizations ensure that they are using open source safely and effectively?</p>
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-<p>One solution is Black Duck, a software composition analysis (SCA) tool that helps teams identify and manage the open source components in their codebase. Black Duck provides complete visibility into the open source usage, detects and prioritizes vulnerabilities, enforces license policies, and generates software bill of materials (SBOM). In this article, we will show you how to download and install Black Duck using Docker or Kubernetes, and highlight some of the benefits and alternatives of this tool.</p>
- <h2>How to Download Black Duck</h2>
-<p>Black Duck is deployed as a set of Docker containers, which together comprise the application. Each container fulfills a different role, such as processing UI requests, acting as an enterprise search platform, or storing data. To download and install Black Duck, you will need to meet some hardware and software requirements, such as:</p>
-<ul>
-<li>A 64-bit 5 core processor</li>
-<li>20 GB of RAM</li>
-<li>250 GB of free space for the database and other containers</li>
-<li>Docker 18.03.x or newer</li>
-<li>An orchestration tool such as Docker Swarm or Kubernetes</li>
-<li>A supported operating system such as CentOS 7.3 or Ubuntu 16.04.x</li>
-</ul>
-<p>You can find more details on the requirements in the <a href="(^1^)">Black Duck Docker Install Guide</a>.</p>
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-<p>There are two main methods for installing Black Duck: using Docker Swarm or using Kubernetes. We will briefly describe each method below.</p>
- <h3>Using Docker Swarm</h3>
-<p>Docker Swarm is a native clustering tool for Docker that allows you to create and manage a group of Docker nodes as a single virtual system. To install Black Duck using Docker Swarm, you will need to follow these steps:</p>
-<ol>
-<li>Install Docker CE on your host machine.</li>
-<li>Initialize a swarm by running <code>docker swarm init</code>.</li>
-<li>Create a new directory for Black Duck orchestration files and download them from <a href="(^2^)">GitHub</a>.</li>
-<li>Edit the <code>docker-compose.local-overrides.yml</code> file to customize your installation settings.</li>
-<li>Run <code>docker stack deploy -c docker-compose.yml -c docker-compose.local-overrides.yml blackduck</code> to deploy the stack.</li>
-<li>Wait for the containers to start up and check their status by running <code>docker service ls</code>.</li>
-<li>Access the Black Duck UI by opening <code>https://&lt;host&gt;</code> in your browser.</li>
-</ol>
- <h3>Using Kubernetes</h3>
-<p>Kubernetes is an open source system for automating deployment, scaling, and management of containerized applications. To install Black Duck using Kubernetes, you will need to follow these steps:</p>
-<ol>
-<li>Install Kubernetes on your host machine.</li>
-<li>Create a namespace for Black Duck by running <code>kubectl create namespace blackduck</code>.</li>
-<li>Create a persistent volume claim (PVC) for the database by running <code>kubectl create -f pvc.json -n blackduck</code>.</li>
-<li>Create a secret for the certificate by running <code>kubectl create secret generic blackduck-webserver-certificate -n blackduck --from-file=WEBSERVER_CUSTOM_CERT_FILE --from-file=WEBSERVER_CUSTOM_KEY_FILE</code>.</li>
-<li>Create a secret for the proxy by running <code>kubectl create secret generic blackduck-proxy -n blackduck --from-file=HUB_PROXY_HOST --from-file=HUB_PROXY_PORT --from-file=HUB_PROXY_USERNAME --from-file=HUB_PROXY_PASSWORD</code>.</li>
-<li>Download the Black Duck Helm chart from <a href="">GitHub</a> and extract it.</li>
-<li>Edit the <code>values.yaml</code> file to customize your installation settings.</li>
-<li>Run <code>helm install ./blackduck -n blackduck --namespace blackduck</code> to install the chart.</li>
-<li>Wait for the pods to start up and check their status by running <code>kubectl get pods -n blackduck</code>.</li>
-<li>Access the Black Duck UI by opening <code>https://&lt;host&gt;</code> in your browser.</li>
-</ol>
- <h2>Benefits of Black Duck</h2>
-<p>Black Duck is a powerful and comprehensive tool that helps teams manage their open source usage and mitigate the associated risks. Some of the benefits of using Black Duck are:</p>
-<ul>
-<li><strong>Visibility:</strong> Black Duck scans your codebase and identifies all the open source components, versions, licenses, and dependencies. It also creates a software bill of materials (SBOM) that documents the composition of your application.</li>
-<li><strong>Security:</strong> Black Duck monitors the open source components for known vulnerabilities and alerts you when new ones are discovered. It also provides remediation guidance and patch suggestions to help you fix the issues quickly and efficiently.</li>
-<li><strong>Compliance:</strong> Black Duck analyzes the licenses of the open source components and checks for any conflicts or obligations. It also helps you enforce your own license policies and generate reports for audits and due diligence.</li>
-<li><strong>Integration:</strong> Black Duck integrates with various tools and platforms that you use in your development lifecycle, such as IDEs, code repositories, build systems, CI/CD pipelines, and container registries. This enables you to scan your code at any stage and automate your workflows.</li>
-</ul>
- <h2>Alternatives to Black Duck</h2>
-<p>Black Duck is not the only tool that offers software composition analysis (SCA) functionality. There are some other tools that you can consider as alternatives or complements to Black Duck, such as:</p>
-<table>
-<tr><th>Name</th><th>Description</th></tr>
-<tr><td><a href="">WhiteSource</a></td><td>A cloud-based SCA tool that helps teams manage their open source security, compliance, and quality. It also provides a unified dashboard for all your projects and integrations with various tools.</td></tr>
-<tr><td><a href="">Snyk</a></td><td>A developer-focused SCA tool that helps teams find and fix vulnerabilities in their open source dependencies. It also provides a CLI tool, a GitHub bot, and a vulnerability database.</td></tr>
-<tr><td><a href="">FOSSA</a></td><td>A modern SCA tool that helps teams automate their open source compliance and license management. It also provides a web app, a CLI tool, and a GitHub integration.</td></tr>
-<tr><td><a href="">Dependabot</a></td><td>A GitHub-native SCA tool that helps teams keep their dependencies up to date and secure. It also provides automated pull requests, security alerts, and configuration options.</td></tr>
-</table>
- <h2>Conclusion</h2>
-<p>In this article, we have shown you how to download and install Black Duck using Docker Swarm or Kubernetes, and highlighted some of the benefits and alternatives of this tool. Black Duck is a software composition analysis (SCA) tool that helps teams identify and manage the open source components in their codebase. It provides complete visibility into the open source usage, detects and prioritizes vulnerabilities, enforces license policies, and generates software bill of materials (SBOM). If you are looking for a solution to manage your open source security and compliance, you should give Black Duck a try.</p>
- <h2>FAQs</h2>
-<h3>What is the difference between Black Duck and Synopsys?</h3>
-<p>Synopsys is the company that owns Black Duck. Synopsys is a leader in software security and quality solutions, offering a range of products and services for various industries and domains. Black Duck is one of the products under Synopsys' portfolio.</p>
- <h3>How much does Black Duck cost?</h3>
-<p>The pricing of Black Duck depends on various factors, such as the number of users, projects, scans, integrations, etc. You can request a quote from Synopsys by filling out this <a href="">form</a>.</p>
- <h3>How can I get support for Black Duck?</h3>
-<p>You can get support for Black Duck by contacting Synopsys through various channels, such as email, phone, chat, or web portal. You can also access the online documentation, knowledge base, community forum, and training resources for Black Duck.</p>
- <h3>What are the system requirements for Black Duck?</h3>
-<p>The system requirements for Black Duck vary depending on the deployment method and the scale of your application. However, some of the common requirements are:</p>
-<ul>
-<li>A 64-bit 5 core processor</li>
-<li>20 GB of RAM</li>
-<li>250 GB of free space for the database and other containers</li>
-<li>Docker 18.03.x or newer</li>
-<li>An orchestration tool such as Docker Swarm or Kubernetes</li>
-<li>A supported operating system such as CentOS 7.3 or Ubuntu 16.04.x</li>
-</ul>
- <h3>How can I update Black Duck?</h3>
-<p>You can update Black Duck by downloading the latest version of the orchestration files and running the appropriate commands for your deployment method. For example, if you are using Docker Swarm, you can run <code>docker stack rm blackduck</code> to remove the existing stack, and then run <code>docker stack deploy -c docker-compose.yml -c docker-compose.local-overrides.yml blackduck</code> to deploy the new version. You can find more details on how to update Black Duck in the <a href="">Black Duck Docker Install Guide</a>.</p> 197e85843d<br />
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diff --git a/spaces/1phancelerku/anime-remove-background/All Songs Jukebox The Ultimate Music Streaming and Downloading Service.md b/spaces/1phancelerku/anime-remove-background/All Songs Jukebox The Ultimate Music Streaming and Downloading Service.md
deleted file mode 100644
index 99bfef5ca88280eb31195b3aca558cb71f3b8ce1..0000000000000000000000000000000000000000
--- a/spaces/1phancelerku/anime-remove-background/All Songs Jukebox The Ultimate Music Streaming and Downloading Service.md	
+++ /dev/null
@@ -1,102 +0,0 @@
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-<p>Do you love listening to music? Do you want to have access to thousands of songs from different genres, artists, and eras? Do you want to create your own playlists and share them with your friends? If you answered yes to any of these questions, then you might be interested in learning more about all songs download jukebox. A jukebox is a device that can play music from various sources, such as CDs, vinyl records, digital files, or online streaming services. You can use a jukebox to enjoy unlimited music for free, as long as you know how to download and play all songs on it. In this article, we will explain what a jukebox is, how to download all songs for jukebox, and how to play all songs on jukebox. Let's get started!</p>
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- <h2>What is a Jukebox?</h2>
-<p>A jukebox is a machine that can play music from different media, such as CDs, vinyl records, digital files, or online streaming services. A jukebox usually has a coin-operated mechanism that allows users to select and play songs from a catalog or a playlist. A jukebox can also have speakers, amplifiers, lights, and other features that enhance the musical experience. A jukebox can be found in various places, such as bars, restaurants, cafes, arcades, or homes.</p>
- <h3>A Brief History of Jukeboxes</h3>
-<p>The first jukeboxes were invented in the late 19th century, when phonographs and gramophones were used to play music in public places. The term "jukebox" comes from the word "juke", which means a disorderly or rowdy place. The first coin-operated phonographs were introduced in 1889 by Louis Glass and William Arnold in San Francisco. They were called "nickel-in-the-slot machines" and could play one song per coin. The popularity of jukeboxes increased in the 1930s and 1940s, when they became more sophisticated and could play multiple songs from different records. The golden age of jukeboxes was in the 1950s and 1960s, when rock and roll music dominated the charts and jukeboxes became symbols of youth culture and rebellion. The decline of jukeboxes began in the 1970s and 1980s, when cassette tapes, CDs, and digital music players replaced vinyl records as the main source of music. However, jukeboxes never disappeared completely and are still used today by music lovers and collectors.</p>
- <h3>Types of Jukeboxes</h3>
-<p>There are many types of jukeboxes that can play different kinds of music from different sources. Some of the most common types are:</p>
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-<li><b>Vintage jukeboxes</b>: These are the old-fashioned jukeboxes that use vinyl records or CDs to play music. They have a nostalgic appeal and a retro style that can add charm and character to any place. They usually have a limited number of songs and require manual selection and loading.</li>
-<li><b>Modern jukeboxes</b>: These are the new-generation jukeboxes that use digital files or online streaming services to play music. They have a sleek design and a touch screen interface that allows users to browse and select songs from a large catalog or a customized playlist. They usually have unlimited access to music and require internet connection.</li>
-<li><b>Hybrid jukeboxes</b>: These are the combination of vintage and modern jukeboxes that can play music from both vinyl records or CDs and digital files or online streaming services. They have a versatile and adaptable functionality that can suit different preferences and needs. They usually have a wide range of songs and require both manual and digital operation.</li>
-</ul>
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-<li><b>Variety</b>: Jukeboxes can play music from different genres, artists, and eras, giving you a diverse and eclectic musical experience. You can discover new songs, revisit old favorites, or mix and match different styles and moods.</li>
-<li><b>Customization</b>: Jukeboxes can allow you to create your own playlists and share them with your friends, giving you a personalized and social musical experience. You can choose the songs that suit your taste, mood, or occasion, or let your friends join in the fun and suggest their own songs.</li>
-<li><b>Quality</b>: Jukeboxes can deliver high-quality sound and performance, giving you a satisfying and immersive musical experience. You can enjoy the crisp and clear sound of vinyl records, the convenience and portability of digital files, or the freshness and diversity of online streaming services.</li>
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-<p>If you want to enjoy unlimited music for free on your jukebox, you need to know how to download all songs for jukebox. There are two main ways to do this: using online streaming services or using free music download sites. Let's take a look at each option in more detail.</p>
- <h3>Online Streaming Services</h3>
-<p>Online streaming services are platforms that allow you to listen to music online without downloading it to your device. You can access millions of songs from various artists, genres, and eras, as well as create your own playlists and discover new music. Some of the most popular online streaming services are Spotify, Apple Music, and Amazon Music. Here are some features and tips for each service:</p>
- <h4>Spotify</h4>
-<p>Spotify is one of the most widely used online streaming services in the world, with over 350 million users. It offers a free plan that allows you to listen to music with ads, or a premium plan that allows you to listen to music without ads, download songs for offline listening, and enjoy other benefits. To use Spotify on your jukebox, you need to:</p>
-<ol>
-<li>Create an account on Spotify.com or download the Spotify app on your device.</li>
-<li>Search for the songs, albums, artists, or playlists that you want to listen to.</li>
-<li>If you have a premium plan, you can download the songs by toggling the "Download" switch on the top right corner of the screen.</li>
-<li>Connect your device to your jukebox using a cable or Bluetooth.</li>
-<li>Play the songs on your device and enjoy them on your jukebox.</li>
-</ol>
- <h4>Apple Music</h4>
-<p>Apple Music is another popular online streaming service that has over 60 million users. It offers a free trial for three months, after which you need to pay a monthly fee to continue using it. It allows you to listen to music without ads, download songs for offline listening, and access exclusive content and features. To use Apple Music on your jukebox, you need to:</p>
-<ol>
-<li>Create an account on Apple.com or download the Apple Music app on your device.</li>
-<li>Search for the songs, albums, artists, or playlists that you want to listen to.</li>
-<li>Download the songs by tapping the cloud icon next to each song.</li>
-<li>Connect your device to your jukebox using a cable or Bluetooth.</li>
-<li>Play the songs on your device and enjoy them on your jukebox.</li>
-</ol>
- <h4>Amazon Music</h4>
-<p>Amazon Music is another online streaming service that has over 55 million users. It offers a free plan that allows you to listen to music with ads, or a paid plan that allows you to listen to music without ads, download songs for offline listening, and access more songs and features. To use Amazon Music on your jukebox, you need to:</p>
-<ol>
-<li>Create an account on Amazon.com or download the Amazon Music app on your device.</li>
-<li>Search for the songs, albums, artists, or playlists that you want to listen to.</li>
-<li>If you have a paid plan, you can download the songs by tapping the "More Options" icon next to each song and selecting "Download".</li>
-<li>Connect your device to your jukebox using a cable or Bluetooth.</li , you can use the buttons or the touch screen to browse and select your songs. You can also use the search function or the voice command to find your songs faster.</p>
- <h3>Enjoy the Music and Have Fun</h3>
-<p>The final step is to enjoy the music and have fun. You can adjust the volume, the bass, the treble, and other settings on your jukebox to suit your preferences. You can also skip, pause, or repeat songs as you wish. You can sing along, dance, or just relax and listen to the music. You can also invite your friends and family to join you and share your musical taste. You can have a party, a karaoke night, or a chill session with your jukebox.</p>
- <h2>Conclusion</h2>
-<p>All songs download jukebox is a great way to enjoy unlimited music for free. You can download all songs for jukebox using online streaming services or free music download sites. You can play all songs on jukebox by connecting your device to the jukebox and selecting your playlist or album. You can have fun and create your own musical atmosphere with your jukebox. Whether you prefer vintage or modern jukeboxes, you can find the one that suits your style and budget. All you need is a love for music and a desire to have a good time.</p>
- <h2>FAQs</h2>
-<p>Here are some frequently asked questions about all songs download jukebox:</p>
-<ul>
-<li><b>Q: How much does a jukebox cost?</b></li>
-<li>A: The price of a jukebox depends on its type, model, condition, and features. A vintage jukebox can cost anywhere from $500 to $10,000 or more, depending on its rarity and quality. A modern jukebox can cost anywhere from $200 to $2,000 or more, depending on its brand and functionality. A hybrid jukebox can cost anywhere from $300 to $3,000 or more, depending on its versatility and design.</li>
-<li><b>Q: Where can I buy a jukebox?</b></li>
-<li>A: You can buy a jukebox from various sources, such as online retailers, physical stores, auctions, or private sellers. Some of the best online retailers for jukeboxes are Amazon, eBay, Walmart, and Best Buy. Some of the best physical stores for jukeboxes are Target, Sears, Home Depot, and Lowe's. Some of the best auctions for jukeboxes are Sotheby's, Christie's, Heritage Auctions, and Bonhams. Some of the best private sellers for jukeboxes are Craigslist, Facebook Marketplace, OfferUp, and Letgo.</li>
-<li><b>Q: How do I maintain my jukebox?</b></li>
-<li>A: To keep your jukebox in good condition, you need to perform some regular maintenance tasks, such as cleaning, lubricating, repairing, and updating. You need to clean your jukebox with a soft cloth and a mild detergent to remove dust and dirt. You need to lubricate your jukebox with oil or grease to prevent rust and friction. You need to repair your jukebox with professional help or DIY tools if it has any damages or malfunctions. You need to update your jukebox with new software or firmware if it has any bugs or glitches.</li>
-<li><b>Q: How do I customize my jukebox?</b></li>
-<li>A: To make your jukebox more unique and personal, you can customize it with various accessories and decorations. You can add lights, stickers, decals, posters, or paintings to your jukebox to make it more colorful and attractive. You can add speakers, headphones, microphones, or karaoke machines to your jukebox to make it more loud and interactive. You can add coins, tokens, cards , or buttons to your jukebox to make it more fun and authentic. You can also change the color, shape, or size of your jukebox to make it more suitable for your space and style.</li>
-<li><b>Q: How do I troubleshoot my jukebox?</b></li>
-<li>A: If your jukebox is not working properly, you can try some basic troubleshooting steps, such as checking the power, the connection, the settings, and the songs. You can check the power by plugging and unplugging your jukebox and making sure that it is turned on. You can check the connection by reconnecting your device and your jukebox and making sure that they are paired and synced. You can check the settings by adjusting the volume, the bass, the treble, and other options on your jukebox and making sure that they are correct. You can check the songs by deleting and downloading them again and making sure that they are compatible and playable.</li>
-</ul>
- <p>I hope you enjoyed this article on all songs download jukebox. If you have any questions or comments, please feel free to leave them below. Thank you for reading and happy listening!</p> 401be4b1e0<br />
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diff --git a/spaces/1phancelerku/anime-remove-background/Download Archero Hack APK and Enjoy Crossbow Archery with Amazing Features.md b/spaces/1phancelerku/anime-remove-background/Download Archero Hack APK and Enjoy Crossbow Archery with Amazing Features.md
deleted file mode 100644
index fbbe90b2f81bba153c0d4ca49c1ceec57a1ee8ee..0000000000000000000000000000000000000000
--- a/spaces/1phancelerku/anime-remove-background/Download Archero Hack APK and Enjoy Crossbow Archery with Amazing Features.md	
+++ /dev/null
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-<br />
-<h1>Archero Hack APK: How to Download and Play the Modded Version of Archero</h1>
-<p>Are you a fan of Archero, the addictive roguelike game where you control a lone archer who must fight against waves of enemies and obstacles? Do you want to experience the game with unlimited resources, unlocked features, and enhanced gameplay? If yes, then you might be interested in trying out Archero Hack APK, a modded version of the game that offers many advantages over the original one. But before you do that, you should know what Archero Hack APK is, how it works, and what are the risks and precautions involved in using it. In this article, we will tell you everything you need to know about Archero Hack APK, including how to download and install it on your Android device, and how to enjoy it without getting banned or infected by malware. Read on to find out more!</p>
-<h2>archero hack apk</h2><br /><p><b><b>Download</b> &#10002; &#10002; &#10002; <a href="https://jinyurl.com/2uNNz2">https://jinyurl.com/2uNNz2</a></b></p><br /><br />
- <h2>What is Archero and why is it popular?</h2>
-<p>Archero is a mobile game developed by Habby, a Chinese studio that specializes in casual games. It was released in 2019 and has since become one of the most popular games on Google Play Store and App Store, with over 50 million downloads and 4.3 stars rating. </p>
-<h3>The gameplay and features of Archero</h3>
-<p>The gameplay of Archero is simple but challenging. You play as an archer who must survive different stages filled with enemies, traps, and bosses. You can move around by swiping on the screen, but you can only shoot when you stop moving. You can also choose from various skills that appear randomly after each level, such as multishot, ricochet, bouncy wall, etc. These skills can help you deal more damage, dodge attacks, or heal yourself.</p>
-<p>Archero also has many features that make it fun and engaging. You can unlock different heroes with unique abilities, such as Helix, Meowgik, Sylvan, etc. You can also equip different weapons, armors, rings, pets, and other items that can boost your stats or grant you special effects. You can also upgrade your equipment by fusing duplicates or spending coins or gems. Moreover, you can explore different worlds and maps with different themes and difficulties, such as desert, forest, dungeon, etc.</p>
-<h3>The challenges and rewards of Archero</h3>
-<p>Archero is not an easy game. It requires skill, strategy, and luck to progress through the stages. You have to dodge enemy attacks while aiming at them accurately. You have to choose the best skills that suit your playstyle and situation. You have to manage your health and energy wisely. And most importantly, you have to deal with the randomness of the game. Sometimes you may get lucky and get powerful skills or items that make you unstoppable. Other times you may get unlucky and get useless skills or items that make you vulnerable.</p>
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-<p>But despite the challenges, Archero is also very rewarding. It gives you a sense of accomplishment when you clear a stage or defeat a boss. It gives you a thrill when you discover a new skill or item that changes your gameplay. It gives you a satisfaction when you upgrade your equipment or unlock a new hero. And it gives you a motivation when you see your progress on the leaderboard or achievements.</p>
- <h2>What is Archero Hack APK and how does it differ from the original game?</h2>
-<p>Archero Hack APK is a modified version of Archero that has been altered by some third-party developers or hackers to provide some benefits or advantages over the original game. These benefits or advantages may include:</p> - Unlimited coins and gems that can be used to buy or upgrade anything in the game - Unlimited energy that allows you to play as long as you want without waiting for the energy bar to refill - Unlocked all heroes, weapons, items, skills, and maps that are otherwise restricted or require real money to access - Enhanced gameplay that gives you more damage, speed, health, and other perks that make you stronger and faster than the normal game Archero Hack APK differs from the original game in many ways. It basically gives you everything you need or want in the game without any effort or cost. It makes the game easier and more enjoyable for some players who want to have fun without any challenge or limitation. However, it also takes away some of the essential elements of the game that make it fun and engaging for other players who want to have a fair and balanced experience. It also poses some risks and precautions that you should be aware of before using it. <h2>What are the benefits and drawbacks of using Archero Hack APK?</h2>
-<p>Using Archero Hack APK can have some benefits and drawbacks depending on your perspective and preference. Here are some of them:</p>
-<h3>The benefits of using Archero Hack APK</h3>
-<p>Some of the benefits of using Archero Hack APK are:</p>
-<ul>
-<li>You can save time and money by getting unlimited resources and features without spending any real money or grinding for hours.</li>
-<li>You can explore and experiment with different combinations of heroes, weapons, items, skills, and maps without any restriction or limitation.</li>
-<li>You can have more fun and excitement by playing with enhanced gameplay and powerful abilities that make you feel like a god.</li>
-<li>You can impress your friends or other players by showing off your achievements or progress in the game.</li>
-</ul>
-<h3>The drawbacks of using Archero Hack APK</h3>
-<p>Some of the drawbacks of using Archero Hack APK are:</p>
-<ul>
-<li>You can lose the challenge and satisfaction of playing the game as it was intended by the developers. You may get bored or lose interest in the game after a while.</li>
-<li>You can miss out on the updates and features that are added to the original game regularly. You may also encounter bugs or glitches that are not fixed in the modded version.</li>
-<li>You can risk getting banned or suspended from the game if you are detected by the anti-cheat system or reported by other players. You may also lose your progress or account if that happens.</li>
-<li>You can expose your device or data to malware or viruses that may be hidden in the modded APK file. You may also compromise your privacy or security if you grant permissions or access to unknown sources.</li>
-</ul>
- <h2>How to download and install Archero Hack APK on your Android device?</h2>
-<p>If you still want to try out Archero Hack APK despite the drawbacks and risks, you will need to follow some steps to download and install it on your Android device. Here are the steps:</p> <h3>The steps to download and install Archero Hack APK</h3>
-<p>The steps to download and install Archero Hack APK are:</p>
-<ol>
-<li>Find a reliable and trustworthy source that provides the latest version of Archero Hack APK. You can search online or ask for recommendations from other users. Some of the popular sources are   , but you should always check the reviews and ratings before downloading anything.</li>
-<li>Download the Archero Hack APK file from the source you have chosen. You may need to enable the option to download from unknown sources in your device settings. You may also need to disable your antivirus or firewall temporarily if they block the download.</li>
-<li>Locate the Archero Hack APK file in your device storage and tap on it to install it. You may need to grant some permissions or access to the app during the installation process. You may also need to verify your device or account if prompted.</li>
-<li>Wait for the installation to finish and then launch the app from your home screen or app drawer. You may need to sign in with your Google Play account or create a new one if you don't have one.</li>
-<li>Enjoy playing Archero Hack APK with unlimited resources, unlocked features, and enhanced gameplay!</li>
-</ol>
-<h3>The tips and tricks to enjoy Archero Hack APK</h3>
-<p>Some of the tips and tricks to enjoy Archero Hack APK are:</p>
-<ul>
-<li>Use different heroes, weapons, items, skills, and maps to experiment with different strategies and combinations. You can also switch between them anytime you want without losing your progress.</li>
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-<li>Use the enhanced gameplay to deal more damage, move faster, heal more, and avoid attacks. You can also use it to challenge yourself by increasing the difficulty or playing in different modes.</li>
-<li>Be careful not to abuse the hack or cheat too much as it may ruin the fun or make the game too easy. You can also try playing the original game occasionally to compare and appreciate the difference.</li>
-<li>Be respectful and responsible when playing online or with other players. Do not brag or boast about your hack or cheat as it may annoy or offend others. Do not use it to gain an unfair advantage or harm others as it may get you banned or reported.</li>
-</ul>
- <h2>Conclusion</h2>
-<p>In conclusion, Archero Hack APK is a modded version of Archero that offers many benefits and advantages over the original game, such as unlimited resources, unlocked features, and enhanced gameplay. However, it also has some drawbacks and risks, such as losing the challenge and satisfaction, missing out on the updates and features, risking getting banned or suspended, and exposing your device or data to malware or viruses. Therefore, you should be careful and cautious when using it, and follow some steps and tips to download and install it safely and enjoy it properly.</p>
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- <h2>FAQs</h2>
-<h3>What is Archero?</h3>
-<p>Archero is a mobile game developed by Habby that lets you play as an archer who must survive different stages filled with enemies, traps, and bosses. You can choose from various skills, heroes, weapons, items, and maps that can help you in your adventure.</p>
-<h3>What is Archero Hack APK?</h3>
-<p>Archero Hack APK is a modified version of Archero that has been altered by some third-party developers or hackers to provide some benefits or advantages over the original game, such as unlimited resources, unlocked features, and enhanced gameplay.</p>
-<h3>How do I download and install Archero Hack APK?</h3>
-<p>You can download and install Archero Hack APK by following these steps:</p>
-<ol>
-<li>Find a reliable and trustworthy source that provides the latest version of Archero Hack APK.</li>
-<li>Download the Archero Hack APK file from the source you have chosen.</li>
-<li>Locate the Archero Hack APK file in your device storage and tap on it to install it.</li>
-<li>Wait for the installation to finish and then launch the app from your home screen or app drawer.</li>
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diff --git a/spaces/1toTree/lora_test/ppdiffusers/models/prior_transformer.py b/spaces/1toTree/lora_test/ppdiffusers/models/prior_transformer.py
deleted file mode 100644
index 8f28c72050dab88e85dfabc37dead90389a2df2f..0000000000000000000000000000000000000000
--- a/spaces/1toTree/lora_test/ppdiffusers/models/prior_transformer.py
+++ /dev/null
@@ -1,220 +0,0 @@
-# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from dataclasses import dataclass
-from typing import Optional, Union
-
-import paddle
-import paddle.nn as nn
-import paddle.nn.functional as F
-
-from ..configuration_utils import ConfigMixin, register_to_config
-from ..modeling_utils import ModelMixin
-from ..utils import BaseOutput
-from .attention import BasicTransformerBlock
-from .embeddings import TimestepEmbedding, Timesteps
-
-NEG_INF = -1e4
-
-
-@dataclass
-class PriorTransformerOutput(BaseOutput):
-    """
-    Args:
-        predicted_image_embedding (`paddle.Tensor` of shape `(batch_size, embedding_dim)`):
-            The predicted CLIP image embedding conditioned on the CLIP text embedding input.
-    """
-
-    predicted_image_embedding: paddle.Tensor
-
-
-class PriorTransformer(ModelMixin, ConfigMixin):
-    """
-    The prior transformer from unCLIP is used to predict CLIP image embeddings from CLIP text embeddings. Note that the
-    transformer predicts the image embeddings through a denoising diffusion process.
-
-    This model inherits from [`ModelMixin`]. Check the superclass documentation for the generic methods the library
-    implements for all the models (such as downloading or saving, etc.)
-
-    For more details, see the original paper: https://arxiv.org/abs/2204.06125
-
-    Parameters:
-        num_attention_heads (`int`, *optional*, defaults to 32): The number of heads to use for multi-head attention.
-        attention_head_dim (`int`, *optional*, defaults to 64): The number of channels in each head.
-        num_layers (`int`, *optional*, defaults to 20): The number of layers of Transformer blocks to use.
-        embedding_dim (`int`, *optional*, defaults to 768): The dimension of the CLIP embeddings. Note that CLIP
-            image embeddings and text embeddings are both the same dimension.
-        num_embeddings (`int`, *optional*, defaults to 77): The max number of clip embeddings allowed. I.e. the
-            length of the prompt after it has been tokenized.
-        additional_embeddings (`int`, *optional*, defaults to 4): The number of additional tokens appended to the
-            projected hidden_states. The actual length of the used hidden_states is `num_embeddings +
-            additional_embeddings`.
-        dropout (`float`, *optional*, defaults to 0.0): The dropout probability to use.
-
-    """
-
-    @register_to_config
-    def __init__(
-        self,
-        num_attention_heads: int = 32,
-        attention_head_dim: int = 64,
-        num_layers: int = 20,
-        embedding_dim: int = 768,
-        num_embeddings=77,
-        additional_embeddings=4,
-        dropout: float = 0.0,
-    ):
-        super().__init__()
-        self.num_attention_heads = num_attention_heads
-        self.attention_head_dim = attention_head_dim
-        inner_dim = num_attention_heads * attention_head_dim
-        self.additional_embeddings = additional_embeddings
-
-        self.time_proj = Timesteps(inner_dim, True, 0)
-        self.time_embedding = TimestepEmbedding(inner_dim, inner_dim)
-
-        self.proj_in = nn.Linear(embedding_dim, inner_dim)
-
-        self.embedding_proj = nn.Linear(embedding_dim, inner_dim)
-        self.encoder_hidden_states_proj = nn.Linear(embedding_dim, inner_dim)
-
-        self.positional_embedding = self.create_parameter(
-            (1, num_embeddings + additional_embeddings, inner_dim),
-            dtype=paddle.get_default_dtype(),
-            default_initializer=nn.initializer.Constant(0.0),
-        )
-
-        self.prd_embedding = self.create_parameter(
-            (1, 1, inner_dim), dtype=paddle.get_default_dtype(), default_initializer=nn.initializer.Constant(0.0)
-        )
-
-        self.transformer_blocks = nn.LayerList(
-            [
-                BasicTransformerBlock(
-                    inner_dim,
-                    num_attention_heads,
-                    attention_head_dim,
-                    dropout=dropout,
-                    activation_fn="gelu",
-                    attention_bias=True,
-                )
-                for d in range(num_layers)
-            ]
-        )
-
-        self.norm_out = nn.LayerNorm(inner_dim)
-        self.proj_to_clip_embeddings = nn.Linear(inner_dim, embedding_dim)
-
-        causal_attention_mask = paddle.triu(
-            paddle.full([num_embeddings + additional_embeddings, num_embeddings + additional_embeddings], NEG_INF), 1
-        )
-        causal_attention_mask = causal_attention_mask.unsqueeze(0)
-        self.register_buffer("causal_attention_mask", causal_attention_mask, persistable=False)
-
-        self.clip_mean = self.create_parameter(
-            (1, embedding_dim), dtype=paddle.get_default_dtype(), default_initializer=nn.initializer.Constant(0.0)
-        )
-        self.clip_std = self.create_parameter(
-            (1, embedding_dim), dtype=paddle.get_default_dtype(), default_initializer=nn.initializer.Constant(0.0)
-        )
-
-    def forward(
-        self,
-        hidden_states,
-        timestep: Union[paddle.Tensor, float, int],
-        proj_embedding: paddle.Tensor,
-        encoder_hidden_states: paddle.Tensor,
-        attention_mask: Optional[paddle.Tensor] = None,
-        return_dict: bool = True,
-    ):
-        """
-        Args:
-            hidden_states (`paddle.Tensor` of shape `(batch_size, embedding_dim)`):
-                x_t, the currently predicted image embeddings.
-            timestep (`paddle.Tensor`):
-                Current denoising step.
-            proj_embedding (`paddle.Tensor` of shape `(batch_size, embedding_dim)`):
-                Projected embedding vector the denoising process is conditioned on.
-            encoder_hidden_states (`paddle.Tensor` of shape `(batch_size, num_embeddings, embedding_dim)`):
-                Hidden states of the text embeddings the denoising process is conditioned on.
-            attention_mask (`paddle.Tensor` of shape `(batch_size, num_embeddings)`):
-                Text mask for the text embeddings.
-            return_dict (`bool`, *optional*, defaults to `True`):
-                Whether or not to return a [`models.prior_transformer.PriorTransformerOutput`] instead of a plain
-                tuple.
-
-        Returns:
-            [`~models.prior_transformer.PriorTransformerOutput`] or `tuple`:
-            [`~models.prior_transformer.PriorTransformerOutput`] if `return_dict` is True, otherwise a `tuple`. When
-            returning a tuple, the first element is the sample tensor.
-        """
-        batch_size = hidden_states.shape[0]
-
-        timesteps = timestep
-        if not paddle.is_tensor(timesteps):
-            timesteps = paddle.to_tensor([timesteps], dtype=paddle.int64)
-        elif paddle.is_tensor(timesteps) and len(timesteps.shape) == 0:
-            timesteps = timesteps[None]
-        # broadcast to batch dimension in a way that's compatible with ONNX/Core ML
-        timesteps = timesteps * paddle.ones((batch_size,), dtype=timesteps.dtype)
-
-        timesteps_projected = self.time_proj(timesteps)
-
-        # timesteps does not contain any weights and will always return f32 tensors
-        # but time_embedding might be fp16, so we need to cast here.
-        timesteps_projected = timesteps_projected.cast(dtype=self.dtype)
-        time_embeddings = self.time_embedding(timesteps_projected)
-
-        proj_embeddings = self.embedding_proj(proj_embedding)
-        encoder_hidden_states = self.encoder_hidden_states_proj(encoder_hidden_states)
-        hidden_states = self.proj_in(hidden_states)
-        prd_embedding = self.prd_embedding.cast(hidden_states.dtype).expand([batch_size, -1, -1])
-        positional_embeddings = self.positional_embedding.cast(hidden_states.dtype)
-
-        hidden_states = paddle.concat(
-            [
-                encoder_hidden_states,
-                proj_embeddings[:, None, :],
-                time_embeddings[:, None, :],
-                hidden_states[:, None, :],
-                prd_embedding,
-            ],
-            axis=1,
-        )
-
-        hidden_states = hidden_states + positional_embeddings
-
-        if attention_mask is not None:
-            attention_mask = (1 - attention_mask.cast(hidden_states.dtype)) * -10000.0
-            attention_mask = F.pad(
-                attention_mask.unsqueeze(0), (0, self.additional_embeddings), value=0.0, data_format="NCL"
-            ).squeeze(0)
-            attention_mask = (attention_mask[:, None, :] + self.causal_attention_mask).cast(hidden_states.dtype)
-            attention_mask = attention_mask.repeat_interleave(self.config.num_attention_heads, axis=0)
-
-        for block in self.transformer_blocks:
-            hidden_states = block(hidden_states, attention_mask=attention_mask)
-
-        hidden_states = self.norm_out(hidden_states)
-        hidden_states = hidden_states[:, -1]
-        predicted_image_embedding = self.proj_to_clip_embeddings(hidden_states)
-
-        if not return_dict:
-            return (predicted_image_embedding,)
-
-        return PriorTransformerOutput(predicted_image_embedding=predicted_image_embedding)
-
-    def post_process_latents(self, prior_latents):
-        prior_latents = (prior_latents * self.clip_std) + self.clip_mean
-        return prior_latents
diff --git a/spaces/1toTree/lora_test/ppdiffusers/pipelines/versatile_diffusion/__init__.py b/spaces/1toTree/lora_test/ppdiffusers/pipelines/versatile_diffusion/__init__.py
deleted file mode 100644
index 309b32b2d1129f07c0643c6cd1e7e0071ccf2045..0000000000000000000000000000000000000000
--- a/spaces/1toTree/lora_test/ppdiffusers/pipelines/versatile_diffusion/__init__.py
+++ /dev/null
@@ -1,43 +0,0 @@
-# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# flake8: noqa
-
-from ...utils import (
-    OptionalDependencyNotAvailable,
-    is_paddle_available,
-    is_paddlenlp_available,
-)
-
-try:
-    if not (is_paddlenlp_available() and is_paddle_available()):
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    from ...utils.dummy_paddle_and_paddlenlp_objects import (
-        VersatileDiffusionDualGuidedPipeline,
-        VersatileDiffusionImageVariationPipeline,
-        VersatileDiffusionPipeline,
-        VersatileDiffusionTextToImagePipeline,
-    )
-else:
-    from .modeling_text_unet import UNetFlatConditionModel
-    from .pipeline_versatile_diffusion import VersatileDiffusionPipeline
-    from .pipeline_versatile_diffusion_dual_guided import (
-        VersatileDiffusionDualGuidedPipeline,
-    )
-    from .pipeline_versatile_diffusion_image_variation import (
-        VersatileDiffusionImageVariationPipeline,
-    )
-    from .pipeline_versatile_diffusion_text_to_image import (
-        VersatileDiffusionTextToImagePipeline,
-    )
diff --git a/spaces/7hao/bingo/src/components/chat-attachments.tsx b/spaces/7hao/bingo/src/components/chat-attachments.tsx
deleted file mode 100644
index ef43d4e262935d263b6099138c56f7daade5299d..0000000000000000000000000000000000000000
--- a/spaces/7hao/bingo/src/components/chat-attachments.tsx
+++ /dev/null
@@ -1,37 +0,0 @@
-import Image from 'next/image'
-import ClearIcon from '@/assets/images/clear.svg'
-import RefreshIcon from '@/assets/images/refresh.svg'
-import { FileItem } from '@/lib/bots/bing/types'
-import { cn } from '@/lib/utils'
-import { useBing } from '@/lib/hooks/use-bing'
-
-type ChatAttachmentsProps = Pick<ReturnType<typeof useBing>, 'attachmentList' | 'setAttachmentList' | 'uploadImage'>
-
-export function ChatAttachments({ attachmentList = [], setAttachmentList, uploadImage }: ChatAttachmentsProps) {
-  return attachmentList.length ? (
-    <div className="attachment-list">
-      {attachmentList.map(file => (
-        <div className="file-item" key={file.url}>
-          {file.status === 'loading' && (
-            <div className="loading">
-              <div className="bar" />
-            </div>)
-          }
-          {file.status !== 'error' && (
-            <div className="thumbnail">
-              <img draggable="false" src={file.url} />
-            </div>)
-          }
-          {file.status === 'error' && (
-            <div className="error">
-              <Image alt="refresh" src={RefreshIcon} width={18} onClick={() => uploadImage(file.url)} />
-            </div>
-          )}
-          <button className={cn('dismiss', { 'no-file': file.status === 'error' })} type="button">
-            <Image alt="clear" src={ClearIcon} width={16} onClick={() => setAttachmentList([])} />
-          </button>
-        </div>
-      ))}
-    </div>
-  ) : null
-}
diff --git a/spaces/801artistry/RVC801/i18n/scan_i18n.py b/spaces/801artistry/RVC801/i18n/scan_i18n.py
deleted file mode 100644
index f3e52cf4f9f06d78877d77d2353f666aa759e36f..0000000000000000000000000000000000000000
--- a/spaces/801artistry/RVC801/i18n/scan_i18n.py
+++ /dev/null
@@ -1,75 +0,0 @@
-import ast
-import glob
-import json
-from collections import OrderedDict
-
-
-def extract_i18n_strings(node):
-    i18n_strings = []
-
-    if (
-        isinstance(node, ast.Call)
-        and isinstance(node.func, ast.Name)
-        and node.func.id == "i18n"
-    ):
-        for arg in node.args:
-            if isinstance(arg, ast.Str):
-                i18n_strings.append(arg.s)
-
-    for child_node in ast.iter_child_nodes(node):
-        i18n_strings.extend(extract_i18n_strings(child_node))
-
-    return i18n_strings
-
-
-# scan the directory for all .py files (recursively)
-# for each file, parse the code into an AST
-# for each AST, extract the i18n strings
-
-strings = []
-for filename in glob.iglob("**/*.py", recursive=True):
-    with open(filename, "r") as f:
-        code = f.read()
-        if "I18nAuto" in code:
-            tree = ast.parse(code)
-            i18n_strings = extract_i18n_strings(tree)
-            print(filename, len(i18n_strings))
-            strings.extend(i18n_strings)
-code_keys = set(strings)
-"""
-n_i18n.py
-gui_v1.py 26
-app.py 16
-infer-web.py 147
-scan_i18n.py 0
-i18n.py 0
-lib/train/process_ckpt.py 1
-"""
-print()
-print("Total unique:", len(code_keys))
-
-
-standard_file = "i18n/locale/zh_CN.json"
-with open(standard_file, "r", encoding="utf-8") as f:
-    standard_data = json.load(f, object_pairs_hook=OrderedDict)
-standard_keys = set(standard_data.keys())
-
-# Define the standard file name
-unused_keys = standard_keys - code_keys
-print("Unused keys:", len(unused_keys))
-for unused_key in unused_keys:
-    print("\t", unused_key)
-
-missing_keys = code_keys - standard_keys
-print("Missing keys:", len(missing_keys))
-for missing_key in missing_keys:
-    print("\t", missing_key)
-
-code_keys_dict = OrderedDict()
-for s in strings:
-    code_keys_dict[s] = s
-
-# write back
-with open(standard_file, "w", encoding="utf-8") as f:
-    json.dump(code_keys_dict, f, ensure_ascii=False, indent=4, sort_keys=True)
-    f.write("\n")
diff --git a/spaces/801artistry/RVC801/tensorlowest.py b/spaces/801artistry/RVC801/tensorlowest.py
deleted file mode 100644
index eccd4dbf3494434e59f7defaae6ab91797263b90..0000000000000000000000000000000000000000
--- a/spaces/801artistry/RVC801/tensorlowest.py
+++ /dev/null
@@ -1,123 +0,0 @@
-from tensorboard.backend.event_processing import event_accumulator
-
-import os
-from shutil import copy2
-from re import search as RSearch
-import pandas as pd
-from ast import literal_eval as LEval
-
-weights_dir = 'weights/'
-
-def find_biggest_tensorboard(tensordir):
-    try:
-        files = [f for f in os.listdir(tensordir) if f.endswith('.0')]
-        if not files:
-            print("No files with the '.0' extension found!")
-            return
-
-        max_size = 0
-        biggest_file = ""
-
-        for file in files:
-            file_path = os.path.join(tensordir, file)
-            if os.path.isfile(file_path):
-                file_size = os.path.getsize(file_path)
-                if file_size > max_size:
-                    max_size = file_size
-                    biggest_file = file
-
-        return biggest_file
-
-    except FileNotFoundError:
-        print("Couldn't find your model!")
-        return
-
-def main(model_name, save_freq, lastmdls):
-    global lowestval_weight_dir, scl
-
-    tensordir = os.path.join('logs', model_name)
-    lowestval_weight_dir = os.path.join(tensordir, "lowestvals")
-    
-    latest_file = find_biggest_tensorboard(tensordir)
-    
-    if latest_file is None:
-        print("Couldn't find a valid tensorboard file!")
-        return
-    
-    tfile = os.path.join(tensordir, latest_file)
-    
-    ea = event_accumulator.EventAccumulator(tfile,
-        size_guidance={
-        event_accumulator.COMPRESSED_HISTOGRAMS: 500,
-        event_accumulator.IMAGES: 4,
-        event_accumulator.AUDIO: 4,
-        event_accumulator.SCALARS: 0,
-        event_accumulator.HISTOGRAMS: 1,
-    })
-
-    ea.Reload()
-    ea.Tags()
-
-    scl = ea.Scalars('loss/g/total')
-
-    listwstep = {}
-    
-    for val in scl:
-        if (val.step // save_freq) * save_freq in [val.step for val in scl]:
-            listwstep[float(val.value)] = (val.step // save_freq) * save_freq
-
-    lowest_vals = sorted(listwstep.keys())[:lastmdls]
-
-    sorted_dict = {value: step for value, step in listwstep.items() if value in lowest_vals}
-    
-    return sorted_dict
-
-def selectweights(model_name, file_dict, weights_dir, lowestval_weight_dir):
-    os.makedirs(lowestval_weight_dir, exist_ok=True)
-    logdir = []
-    files = []
-    lbldict = {
-        'Values': {},
-        'Names': {}
-    }
-    weights_dir_path = os.path.join(weights_dir, "")
-    low_val_path = os.path.join(os.getcwd(), os.path.join(lowestval_weight_dir, ""))
-    
-    try:
-        file_dict = LEval(file_dict)
-    except Exception as e: 
-        print(f"Error! {e}")
-        return f"Couldn't load tensorboard file! {e}"
-    
-    weights = [f for f in os.scandir(weights_dir)]
-    for key, value in file_dict.items():
-        pattern = fr"^{model_name}_.*_s{value}\.pth$"
-        matching_weights = [f.name for f in weights if f.is_file() and RSearch(pattern, f.name)]
-        for weight in matching_weights:
-            source_path = weights_dir_path + weight
-            destination_path = os.path.join(lowestval_weight_dir, weight)
-            
-            copy2(source_path, destination_path)
-
-            logdir.append(f"File = {weight} Value: {key}, Step: {value}")
-
-            lbldict['Names'][weight] = weight
-            lbldict['Values'][weight] = key
-
-            files.append(low_val_path + weight)
-
-            print(f"File = {weight} Value: {key}, Step: {value}")
-
-            yield ('\n'.join(logdir), files, pd.DataFrame(lbldict))
-            
-
-    return ''.join(logdir), files, pd.DataFrame(lbldict)
-    
-
-if __name__ == "__main__":
-    model = str(input("Enter the name of the model: "))
-    sav_freq = int(input("Enter save frequency of the model: "))
-    ds = main(model, sav_freq)
-    
-    if ds: selectweights(model, ds, weights_dir, lowestval_weight_dir)
-    
\ No newline at end of file
diff --git a/spaces/AIBoy1993/segment_anything_webui/inference.py b/spaces/AIBoy1993/segment_anything_webui/inference.py
deleted file mode 100644
index e96c0fad4ca171aa013c3fb31d91d0b8c45d0fd5..0000000000000000000000000000000000000000
--- a/spaces/AIBoy1993/segment_anything_webui/inference.py
+++ /dev/null
@@ -1,188 +0,0 @@
-import os
-import cv2
-import torch
-import numpy as np
-import gradio as gr
-from PIL import Image, ImageDraw
-from segment_anything import sam_model_registry, SamAutomaticMaskGenerator, SamPredictor
-from transformers import OwlViTProcessor, OwlViTForObjectDetection
-import gc
-
-models = {
-	'vit_b': './checkpoints/sam_vit_b_01ec64.pth',
-	'vit_l': './checkpoints/sam_vit_l_0b3195.pth',
-	'vit_h': './checkpoints/sam_vit_h_4b8939.pth'
-}
-
-image_examples = [
-    [os.path.join(os.path.dirname(__file__), "./images/53960-scaled.jpg"), 0, []],
-    [os.path.join(os.path.dirname(__file__), "./images/2388455-scaled.jpg"), 1, []],
-    [os.path.join(os.path.dirname(__file__), "./images/1.jpg"),2,[]],
-    [os.path.join(os.path.dirname(__file__), "./images/2.jpg"),3,[]],
-    [os.path.join(os.path.dirname(__file__), "./images/3.jpg"),4,[]],
-    [os.path.join(os.path.dirname(__file__), "./images/4.jpg"),5,[]],
-    [os.path.join(os.path.dirname(__file__), "./images/5.jpg"),6,[]],
-    [os.path.join(os.path.dirname(__file__), "./images/6.jpg"),7,[]],
-    [os.path.join(os.path.dirname(__file__), "./images/7.jpg"),8,[]],
-    [os.path.join(os.path.dirname(__file__), "./images/8.jpg"),9,[]]
-]
-
-
-def plot_boxes(img, boxes):
-	img_pil = Image.fromarray(np.uint8(img * 255)).convert('RGB')
-	draw = ImageDraw.Draw(img_pil)
-	for box in boxes:
-		color = tuple(np.random.randint(0, 255, size=3).tolist())
-		x0, y0, x1, y1 = box
-		x0, y0, x1, y1 = int(x0), int(y0), int(x1), int(y1)
-		draw.rectangle([x0, y0, x1, y1], outline=color, width=6)
-	return img_pil
-
-
-def segment_one(img, mask_generator, seed=None):
-	if seed is not None:
-		np.random.seed(seed)
-	masks = mask_generator.generate(img)
-	sorted_anns = sorted(masks, key=(lambda x: x['area']), reverse=True)
-	mask_all = np.ones((img.shape[0], img.shape[1], 3))
-	for ann in sorted_anns:
-		m = ann['segmentation']
-		color_mask = np.random.random((1, 3)).tolist()[0]
-		for i in range(3):
-			mask_all[m == True, i] = color_mask[i]
-	result = img / 255 * 0.3 + mask_all * 0.7
-	return result, mask_all
-
-
-def generator_inference(device, model_type, points_per_side, pred_iou_thresh, stability_score_thresh,
-                        min_mask_region_area, stability_score_offset, box_nms_thresh, crop_n_layers, crop_nms_thresh,
-                        input_x, progress=gr.Progress()):
-	# sam model
-	sam = sam_model_registry[model_type](checkpoint=models[model_type]).to(device)
-	mask_generator = SamAutomaticMaskGenerator(
-		sam,
-		points_per_side=points_per_side,
-		pred_iou_thresh=pred_iou_thresh,
-		stability_score_thresh=stability_score_thresh,
-		stability_score_offset=stability_score_offset,
-		box_nms_thresh=box_nms_thresh,
-		crop_n_layers=crop_n_layers,
-		crop_nms_thresh=crop_nms_thresh,
-		crop_overlap_ratio=512 / 1500,
-		crop_n_points_downscale_factor=1,
-		point_grids=None,
-		min_mask_region_area=min_mask_region_area,
-		output_mode='binary_mask'
-	)
-
-	# input is image, type: numpy
-	if type(input_x) == np.ndarray:
-		result, mask_all = segment_one(input_x, mask_generator)
-		return result, mask_all
-	elif isinstance(input_x, str):  # input is video, type: path (str)
-		cap = cv2.VideoCapture(input_x)  # read video
-		frames_num = cap.get(cv2.CAP_PROP_FRAME_COUNT)
-		W, H = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)), int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
-		fps = int(cap.get(cv2.CAP_PROP_FPS))
-		out = cv2.VideoWriter("output.mp4", cv2.VideoWriter_fourcc('x', '2', '6', '4'), fps, (W, H), isColor=True)
-		for _ in progress.tqdm(range(int(frames_num)),
-		                       desc='Processing video ({} frames, size {}x{})'.format(int(frames_num), W, H)):
-			ret, frame = cap.read()  # read a frame
-			result, mask_all = segment_one(frame, mask_generator, seed=2023)
-			result = (result * 255).astype(np.uint8)
-			out.write(result)
-		out.release()
-		cap.release()
-		return 'output.mp4'
-
-
-def predictor_inference(device, model_type, input_x, input_text, selected_points, owl_vit_threshold=0.1):
-	# sam model
-	sam = sam_model_registry[model_type](checkpoint=models[model_type]).to(device)
-	predictor = SamPredictor(sam)
-	predictor.set_image(input_x)  # Process the image to produce an image embedding
-
-	if input_text != '':
-		# split input text
-		input_text = [input_text.split(',')]
-		print(input_text)
-		# OWL-ViT model
-		processor = OwlViTProcessor.from_pretrained('./checkpoints/models--google--owlvit-base-patch32')
-		owlvit_model = OwlViTForObjectDetection.from_pretrained("./checkpoints/models--google--owlvit-base-patch32").to(device)
-		# get outputs
-		input_text = processor(text=input_text, images=input_x, return_tensors="pt").to(device)
-		outputs = owlvit_model(**input_text)
-		target_size = torch.Tensor([input_x.shape[:2]]).to(device)
-		results = processor.post_process_object_detection(outputs=outputs, target_sizes=target_size,
-		                                                  threshold=owl_vit_threshold)
-
-		# get the box with best score
-		scores = torch.sigmoid(outputs.logits)
-		# best_scores, best_idxs = torch.topk(scores, k=1, dim=1)
-		# best_idxs = best_idxs.squeeze(1).tolist()
-
-		i = 0  # Retrieve predictions for the first image for the corresponding text queries
-		boxes_tensor = results[i]["boxes"]  # [best_idxs]
-		boxes = boxes_tensor.cpu().detach().numpy()
-		# boxes = boxes[np.newaxis, :, :]
-		transformed_boxes = predictor.transform.apply_boxes_torch(torch.Tensor(boxes).to(device),
-		                                                          input_x.shape[:2])  # apply transform to original boxes
-		# transformed_boxes = transformed_boxes.unsqueeze(0)
-		print(transformed_boxes.size(), boxes.shape)
-	else:
-		transformed_boxes = None
-
-	# points
-	if len(selected_points) != 0:
-		points = torch.Tensor([p for p, _ in selected_points]).to(device).unsqueeze(1)
-		labels = torch.Tensor([int(l) for _, l in selected_points]).to(device).unsqueeze(1)
-		transformed_points = predictor.transform.apply_coords_torch(points, input_x.shape[:2])
-		print(points.size(), transformed_points.size(), labels.size(), input_x.shape, points)
-	else:
-		transformed_points, labels = None, None
-
-	# predict segmentation according to the boxes
-	masks, scores, logits = predictor.predict_torch(
-		point_coords=transformed_points,
-		point_labels=labels,
-		boxes=transformed_boxes,  # only one box
-		multimask_output=False,
-	)
-	masks = masks.cpu().detach().numpy()
-	mask_all = np.ones((input_x.shape[0], input_x.shape[1], 3))
-	for ann in masks:
-		color_mask = np.random.random((1, 3)).tolist()[0]
-		for i in range(3):
-			mask_all[ann[0] == True, i] = color_mask[i]
-	img = input_x / 255 * 0.3 + mask_all * 0.7
-	if input_text != '':
-		img = plot_boxes(img, boxes_tensor)  # image + mask + boxes
-
-	# free the memory
-	if input_text != '':
-		owlvit_model.cpu()
-		del owlvit_model
-	del input_text
-	gc.collect()
-	torch.cuda.empty_cache()
-
-	return img, mask_all
-
-
-def run_inference(device, model_type, points_per_side, pred_iou_thresh, stability_score_thresh, min_mask_region_area,
-                  stability_score_offset, box_nms_thresh, crop_n_layers, crop_nms_thresh, owl_vit_threshold, input_x,
-                  input_text, selected_points):
-	# if input_x is int, the image is selected from examples
-	if isinstance(input_x, int):
-		input_x = cv2.imread(image_examples[input_x][0])
-		input_x = cv2.cvtColor(input_x, cv2.COLOR_BGR2RGB)
-	if (input_text != '' and not isinstance(input_x, str)) or len(selected_points) != 0:  # user input text or points
-		print('use predictor_inference')
-		print('prompt text: ', input_text)
-		print('prompt points length: ', len(selected_points))
-		return predictor_inference(device, model_type, input_x, input_text, selected_points, owl_vit_threshold)
-	else:
-		print('use generator_inference')
-		return generator_inference(device, model_type, points_per_side, pred_iou_thresh, stability_score_thresh,
-		                           min_mask_region_area, stability_score_offset, box_nms_thresh, crop_n_layers,
-		                           crop_nms_thresh, input_x)
diff --git a/spaces/AIConsultant/MusicGen/audiocraft/data/audio_utils.py b/spaces/AIConsultant/MusicGen/audiocraft/data/audio_utils.py
deleted file mode 100644
index 565b63a4ef78dcd802dda932b42ebe518ffe7397..0000000000000000000000000000000000000000
--- a/spaces/AIConsultant/MusicGen/audiocraft/data/audio_utils.py
+++ /dev/null
@@ -1,177 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-"""Various utilities for audio convertion (pcm format, sample rate and channels),
-and volume normalization."""
-import sys
-import typing as tp
-
-import julius
-import torch
-import torchaudio
-
-
-def convert_audio_channels(wav: torch.Tensor, channels: int = 2) -> torch.Tensor:
-    """Convert audio to the given number of channels.
-
-    Args:
-        wav (torch.Tensor): Audio wave of shape [B, C, T].
-        channels (int): Expected number of channels as output.
-    Returns:
-        torch.Tensor: Downmixed or unchanged audio wave [B, C, T].
-    """
-    *shape, src_channels, length = wav.shape
-    if src_channels == channels:
-        pass
-    elif channels == 1:
-        # Case 1:
-        # The caller asked 1-channel audio, and the stream has multiple
-        # channels, downmix all channels.
-        wav = wav.mean(dim=-2, keepdim=True)
-    elif src_channels == 1:
-        # Case 2:
-        # The caller asked for multiple channels, but the input file has
-        # a single channel, replicate the audio over all channels.
-        wav = wav.expand(*shape, channels, length)
-    elif src_channels >= channels:
-        # Case 3:
-        # The caller asked for multiple channels, and the input file has
-        # more channels than requested. In that case return the first channels.
-        wav = wav[..., :channels, :]
-    else:
-        # Case 4: What is a reasonable choice here?
-        raise ValueError('The audio file has less channels than requested but is not mono.')
-    return wav
-
-
-def convert_audio(wav: torch.Tensor, from_rate: float,
-                  to_rate: float, to_channels: int) -> torch.Tensor:
-    """Convert audio to new sample rate and number of audio channels."""
-    wav = julius.resample_frac(wav, int(from_rate), int(to_rate))
-    wav = convert_audio_channels(wav, to_channels)
-    return wav
-
-
-def normalize_loudness(wav: torch.Tensor, sample_rate: int, loudness_headroom_db: float = 14,
-                       loudness_compressor: bool = False, energy_floor: float = 2e-3):
-    """Normalize an input signal to a user loudness in dB LKFS.
-    Audio loudness is defined according to the ITU-R BS.1770-4 recommendation.
-
-    Args:
-        wav (torch.Tensor): Input multichannel audio data.
-        sample_rate (int): Sample rate.
-        loudness_headroom_db (float): Target loudness of the output in dB LUFS.
-        loudness_compressor (bool): Uses tanh for soft clipping.
-        energy_floor (float): anything below that RMS level will not be rescaled.
-    Returns:
-        torch.Tensor: Loudness normalized output data.
-    """
-    energy = wav.pow(2).mean().sqrt().item()
-    if energy < energy_floor:
-        return wav
-    transform = torchaudio.transforms.Loudness(sample_rate)
-    input_loudness_db = transform(wav).item()
-    # calculate the gain needed to scale to the desired loudness level
-    delta_loudness = -loudness_headroom_db - input_loudness_db
-    gain = 10.0 ** (delta_loudness / 20.0)
-    output = gain * wav
-    if loudness_compressor:
-        output = torch.tanh(output)
-    assert output.isfinite().all(), (input_loudness_db, wav.pow(2).mean().sqrt())
-    return output
-
-
-def _clip_wav(wav: torch.Tensor, log_clipping: bool = False, stem_name: tp.Optional[str] = None) -> None:
-    """Utility function to clip the audio with logging if specified."""
-    max_scale = wav.abs().max()
-    if log_clipping and max_scale > 1:
-        clamp_prob = (wav.abs() > 1).float().mean().item()
-        print(f"CLIPPING {stem_name or ''} happening with proba (a bit of clipping is okay):",
-              clamp_prob, "maximum scale: ", max_scale.item(), file=sys.stderr)
-    #wav.clamp_(-1, 1)
-    wav = wav.clone().clamp_(-1, 1)
-
-
-def normalize_audio(wav: torch.Tensor, normalize: bool = True,
-                    strategy: str = 'peak', peak_clip_headroom_db: float = 1,
-                    rms_headroom_db: float = 18, loudness_headroom_db: float = 14,
-                    loudness_compressor: bool = False, log_clipping: bool = False,
-                    sample_rate: tp.Optional[int] = None,
-                    stem_name: tp.Optional[str] = None) -> torch.Tensor:
-    """Normalize the audio according to the prescribed strategy (see after).
-
-    Args:
-        wav (torch.Tensor): Audio data.
-        normalize (bool): if `True` (default), normalizes according to the prescribed
-            strategy (see after). If `False`, the strategy is only used in case clipping
-            would happen.
-        strategy (str): Can be either 'clip', 'peak', or 'rms'. Default is 'peak',
-            i.e. audio is normalized by its largest value. RMS normalizes by root-mean-square
-            with extra headroom to avoid clipping. 'clip' just clips.
-        peak_clip_headroom_db (float): Headroom in dB when doing 'peak' or 'clip' strategy.
-        rms_headroom_db (float): Headroom in dB when doing 'rms' strategy. This must be much larger
-            than the `peak_clip` one to avoid further clipping.
-        loudness_headroom_db (float): Target loudness for loudness normalization.
-        loudness_compressor (bool): If True, uses tanh based soft clipping.
-        log_clipping (bool): If True, basic logging on stderr when clipping still
-            occurs despite strategy (only for 'rms').
-        sample_rate (int): Sample rate for the audio data (required for loudness).
-        stem_name (str, optional): Stem name for clipping logging.
-    Returns:
-        torch.Tensor: Normalized audio.
-    """
-    scale_peak = 10 ** (-peak_clip_headroom_db / 20)
-    scale_rms = 10 ** (-rms_headroom_db / 20)
-    if strategy == 'peak':
-        rescaling = (scale_peak / wav.abs().max())
-        if normalize or rescaling < 1:
-            wav = wav * rescaling
-    elif strategy == 'clip':
-        wav = wav.clamp(-scale_peak, scale_peak)
-    elif strategy == 'rms':
-        mono = wav.mean(dim=0)
-        rescaling = scale_rms / mono.pow(2).mean().sqrt()
-        if normalize or rescaling < 1:
-            wav = wav * rescaling
-        _clip_wav(wav, log_clipping=log_clipping, stem_name=stem_name)
-    elif strategy == 'loudness':
-        assert sample_rate is not None, "Loudness normalization requires sample rate."
-        wav = normalize_loudness(wav, sample_rate, loudness_headroom_db, loudness_compressor)
-        _clip_wav(wav, log_clipping=log_clipping, stem_name=stem_name)
-    else:
-        assert wav.abs().max() < 1
-        assert strategy == '' or strategy == 'none', f"Unexpected strategy: '{strategy}'"
-    return wav
-
-
-def f32_pcm(wav: torch.Tensor) -> torch.Tensor:
-    """Convert audio to float 32 bits PCM format.
-    """
-    if wav.dtype.is_floating_point:
-        return wav
-    elif wav.dtype == torch.int16:
-        return wav.float() / 2**15
-    elif wav.dtype == torch.int32:
-        return wav.float() / 2**31
-    raise ValueError(f"Unsupported wav dtype: {wav.dtype}")
-
-
-def i16_pcm(wav: torch.Tensor) -> torch.Tensor:
-    """Convert audio to int 16 bits PCM format.
-
-    ..Warning:: There exist many formula for doing this conversion. None are perfect
-    due to the asymmetry of the int16 range. One either have possible clipping, DC offset,
-    or inconsistencies with f32_pcm. If the given wav doesn't have enough headroom,
-    it is possible that `i16_pcm(f32_pcm)) != Identity`.
-    """
-    if wav.dtype.is_floating_point:
-        assert wav.abs().max() <= 1
-        candidate = (wav * 2 ** 15).round()
-        if candidate.max() >= 2 ** 15:  # clipping would occur
-            candidate = (wav * (2 ** 15 - 1)).round()
-        return candidate.short()
-    else:
-        assert wav.dtype == torch.int16
-        return wav
diff --git a/spaces/AIFILMS/generate_human_motion/VQ-Trans/GPT_eval_multi.py b/spaces/AIFILMS/generate_human_motion/VQ-Trans/GPT_eval_multi.py
deleted file mode 100644
index b5e3ebcb1199e42cf16748e60863b554a0046f00..0000000000000000000000000000000000000000
--- a/spaces/AIFILMS/generate_human_motion/VQ-Trans/GPT_eval_multi.py
+++ /dev/null
@@ -1,121 +0,0 @@
-import os 
-import torch
-import numpy as np
-from torch.utils.tensorboard import SummaryWriter
-import json
-import clip
-
-import options.option_transformer as option_trans
-import models.vqvae as vqvae
-import utils.utils_model as utils_model
-import utils.eval_trans as eval_trans
-from dataset import dataset_TM_eval
-import models.t2m_trans as trans
-from options.get_eval_option import get_opt
-from models.evaluator_wrapper import EvaluatorModelWrapper
-import warnings
-warnings.filterwarnings('ignore')
-
-##### ---- Exp dirs ---- #####
-args = option_trans.get_args_parser()
-torch.manual_seed(args.seed)
-
-args.out_dir = os.path.join(args.out_dir, f'{args.exp_name}')
-os.makedirs(args.out_dir, exist_ok = True)
-
-##### ---- Logger ---- #####
-logger = utils_model.get_logger(args.out_dir)
-writer = SummaryWriter(args.out_dir)
-logger.info(json.dumps(vars(args), indent=4, sort_keys=True))
-
-from utils.word_vectorizer import WordVectorizer
-w_vectorizer = WordVectorizer('./glove', 'our_vab')
-val_loader = dataset_TM_eval.DATALoader(args.dataname, True, 32, w_vectorizer)
-
-dataset_opt_path = 'checkpoints/kit/Comp_v6_KLD005/opt.txt' if args.dataname == 'kit' else 'checkpoints/t2m/Comp_v6_KLD005/opt.txt'
-
-wrapper_opt = get_opt(dataset_opt_path, torch.device('cuda'))
-eval_wrapper = EvaluatorModelWrapper(wrapper_opt)
-
-##### ---- Network ---- #####
-
-## load clip model and datasets
-clip_model, clip_preprocess = clip.load("ViT-B/32", device=torch.device('cuda'), jit=False, download_root='/apdcephfs_cq2/share_1290939/maelyszhang/.cache/clip')  # Must set jit=False for training
-clip.model.convert_weights(clip_model)  # Actually this line is unnecessary since clip by default already on float16
-clip_model.eval()
-for p in clip_model.parameters():
-    p.requires_grad = False
-
-net = vqvae.HumanVQVAE(args, ## use args to define different parameters in different quantizers
-                       args.nb_code,
-                       args.code_dim,
-                       args.output_emb_width,
-                       args.down_t,
-                       args.stride_t,
-                       args.width,
-                       args.depth,
-                       args.dilation_growth_rate)
-
-
-trans_encoder = trans.Text2Motion_Transformer(num_vq=args.nb_code, 
-                                embed_dim=args.embed_dim_gpt, 
-                                clip_dim=args.clip_dim, 
-                                block_size=args.block_size, 
-                                num_layers=args.num_layers, 
-                                n_head=args.n_head_gpt, 
-                                drop_out_rate=args.drop_out_rate, 
-                                fc_rate=args.ff_rate)
-
-
-print ('loading checkpoint from {}'.format(args.resume_pth))
-ckpt = torch.load(args.resume_pth, map_location='cpu')
-net.load_state_dict(ckpt['net'], strict=True)
-net.eval()
-net.cuda()
-
-if args.resume_trans is not None:
-    print ('loading transformer checkpoint from {}'.format(args.resume_trans))
-    ckpt = torch.load(args.resume_trans, map_location='cpu')
-    trans_encoder.load_state_dict(ckpt['trans'], strict=True)
-trans_encoder.train()
-trans_encoder.cuda()
-
-
-fid = []
-div = []
-top1 = []
-top2 = []
-top3 = []
-matching = []
-multi = []
-repeat_time = 20
-
-        
-for i in range(repeat_time):
-    best_fid, best_iter, best_div, best_top1, best_top2, best_top3, best_matching, best_multi, writer, logger = eval_trans.evaluation_transformer_test(args.out_dir, val_loader, net, trans_encoder, logger, writer, 0, best_fid=1000, best_iter=0, best_div=100, best_top1=0, best_top2=0, best_top3=0, best_matching=100, best_multi=0, clip_model=clip_model, eval_wrapper=eval_wrapper, draw=False, savegif=False, save=False, savenpy=(i==0))
-    fid.append(best_fid)
-    div.append(best_div)
-    top1.append(best_top1)
-    top2.append(best_top2)
-    top3.append(best_top3)
-    matching.append(best_matching)
-    multi.append(best_multi)
-
-print('final result:')
-print('fid: ', sum(fid)/repeat_time)
-print('div: ', sum(div)/repeat_time)
-print('top1: ', sum(top1)/repeat_time)
-print('top2: ', sum(top2)/repeat_time)
-print('top3: ', sum(top3)/repeat_time)
-print('matching: ', sum(matching)/repeat_time)
-print('multi: ', sum(multi)/repeat_time)
-
-fid = np.array(fid)
-div = np.array(div)
-top1 = np.array(top1)
-top2 = np.array(top2)
-top3 = np.array(top3)
-matching = np.array(matching)
-multi = np.array(multi)
-msg_final = f"FID. {np.mean(fid):.3f}, conf. {np.std(fid)*1.96/np.sqrt(repeat_time):.3f}, Diversity. {np.mean(div):.3f}, conf. {np.std(div)*1.96/np.sqrt(repeat_time):.3f}, TOP1. {np.mean(top1):.3f}, conf. {np.std(top1)*1.96/np.sqrt(repeat_time):.3f}, TOP2. {np.mean(top2):.3f}, conf. {np.std(top2)*1.96/np.sqrt(repeat_time):.3f}, TOP3. {np.mean(top3):.3f}, conf. {np.std(top3)*1.96/np.sqrt(repeat_time):.3f}, Matching. {np.mean(matching):.3f}, conf. {np.std(matching)*1.96/np.sqrt(repeat_time):.3f}, Multi. {np.mean(multi):.3f}, conf. {np.std(multi)*1.96/np.sqrt(repeat_time):.3f}"
-logger.info(msg_final)
\ No newline at end of file
diff --git a/spaces/AIFILMS/generate_human_motion/VQ-Trans/visualize/joints2smpl/src/smplify.py b/spaces/AIFILMS/generate_human_motion/VQ-Trans/visualize/joints2smpl/src/smplify.py
deleted file mode 100644
index 580efef98dfdcf6e7486b7f5c5436820edfb6c4b..0000000000000000000000000000000000000000
--- a/spaces/AIFILMS/generate_human_motion/VQ-Trans/visualize/joints2smpl/src/smplify.py
+++ /dev/null
@@ -1,279 +0,0 @@
-import torch
-import os, sys
-import pickle
-import smplx
-import numpy as np
-
-sys.path.append(os.path.dirname(__file__))
-from customloss import (camera_fitting_loss, 
-                        body_fitting_loss, 
-                        camera_fitting_loss_3d,
-                        body_fitting_loss_3d, 
-                        )
-from prior import MaxMixturePrior
-from visualize.joints2smpl.src import config
-
-
-
-@torch.no_grad()
-def guess_init_3d(model_joints, 
-                  j3d, 
-                  joints_category="orig"):
-    """Initialize the camera translation via triangle similarity, by using the torso joints        .
-    :param model_joints: SMPL model with pre joints
-    :param j3d: 25x3 array of Kinect Joints
-    :returns: 3D vector corresponding to the estimated camera translation
-    """
-    # get the indexed four
-    gt_joints = ['RHip', 'LHip', 'RShoulder', 'LShoulder']
-    gt_joints_ind = [config.JOINT_MAP[joint] for joint in gt_joints]
-    
-    if joints_category=="orig":
-        joints_ind_category = [config.JOINT_MAP[joint] for joint in gt_joints]
-    elif joints_category=="AMASS":
-        joints_ind_category = [config.AMASS_JOINT_MAP[joint] for joint in gt_joints] 
-    else:
-        print("NO SUCH JOINTS CATEGORY!") 
-
-    sum_init_t = (j3d[:, joints_ind_category] - model_joints[:, gt_joints_ind]).sum(dim=1)
-    init_t = sum_init_t / 4.0
-    return init_t
-
-
-# SMPLIfy 3D
-class SMPLify3D():
-    """Implementation of SMPLify, use 3D joints."""
-
-    def __init__(self,
-                 smplxmodel,
-                 step_size=1e-2,
-                 batch_size=1,
-                 num_iters=100,
-                 use_collision=False,
-                 use_lbfgs=True,
-                 joints_category="orig",
-                 device=torch.device('cuda:0'),
-                 ):
-
-        # Store options
-        self.batch_size = batch_size
-        self.device = device
-        self.step_size = step_size
-
-        self.num_iters = num_iters
-        # --- choose optimizer
-        self.use_lbfgs = use_lbfgs
-        # GMM pose prior
-        self.pose_prior = MaxMixturePrior(prior_folder=config.GMM_MODEL_DIR,
-                                          num_gaussians=8,
-                                          dtype=torch.float32).to(device)
-        # collision part
-        self.use_collision = use_collision
-        if self.use_collision:
-            self.part_segm_fn = config.Part_Seg_DIR
-        
-        # reLoad SMPL-X model
-        self.smpl = smplxmodel
-
-        self.model_faces = smplxmodel.faces_tensor.view(-1)
-
-        # select joint joint_category
-        self.joints_category = joints_category
-        
-        if joints_category=="orig":
-            self.smpl_index = config.full_smpl_idx
-            self.corr_index = config.full_smpl_idx 
-        elif joints_category=="AMASS":
-            self.smpl_index = config.amass_smpl_idx
-            self.corr_index = config.amass_idx
-        else:
-            self.smpl_index = None 
-            self.corr_index = None
-            print("NO SUCH JOINTS CATEGORY!")
-
-    # ---- get the man function here ------
-    def __call__(self, init_pose, init_betas, init_cam_t, j3d, conf_3d=1.0, seq_ind=0):
-        """Perform body fitting.
-        Input:
-            init_pose: SMPL pose estimate
-            init_betas: SMPL betas estimate
-            init_cam_t: Camera translation estimate
-            j3d: joints 3d aka keypoints
-            conf_3d: confidence for 3d joints
-			seq_ind: index of the sequence
-        Returns:
-            vertices: Vertices of optimized shape
-            joints: 3D joints of optimized shape
-            pose: SMPL pose parameters of optimized shape
-            betas: SMPL beta parameters of optimized shape
-            camera_translation: Camera translation
-        """
-
-        # # # add the mesh inter-section to avoid
-        search_tree = None
-        pen_distance = None
-        filter_faces = None
-        
-        if self.use_collision:
-            from mesh_intersection.bvh_search_tree import BVH
-            import mesh_intersection.loss as collisions_loss
-            from mesh_intersection.filter_faces import FilterFaces
-
-            search_tree = BVH(max_collisions=8)
-
-            pen_distance = collisions_loss.DistanceFieldPenetrationLoss(
-                           sigma=0.5, point2plane=False, vectorized=True, penalize_outside=True)
-
-            if self.part_segm_fn:
-                # Read the part segmentation
-                part_segm_fn = os.path.expandvars(self.part_segm_fn)
-                with open(part_segm_fn, 'rb') as faces_parents_file:
-                    face_segm_data = pickle.load(faces_parents_file,  encoding='latin1')
-                faces_segm = face_segm_data['segm']
-                faces_parents = face_segm_data['parents']
-                # Create the module used to filter invalid collision pairs
-                filter_faces = FilterFaces(
-                    faces_segm=faces_segm, faces_parents=faces_parents,
-                    ign_part_pairs=None).to(device=self.device)
-                    
-                    
-        # Split SMPL pose to body pose and global orientation
-        body_pose = init_pose[:, 3:].detach().clone()
-        global_orient = init_pose[:, :3].detach().clone()
-        betas = init_betas.detach().clone()
-
-        # use guess 3d to get the initial
-        smpl_output = self.smpl(global_orient=global_orient,
-                                body_pose=body_pose,
-                                betas=betas)
-        model_joints = smpl_output.joints
-
-        init_cam_t = guess_init_3d(model_joints, j3d, self.joints_category).unsqueeze(1).detach()
-        camera_translation = init_cam_t.clone()
-        
-        preserve_pose = init_pose[:, 3:].detach().clone()
-       # -------------Step 1: Optimize camera translation and body orientation--------
-        # Optimize only camera translation and body orientation
-        body_pose.requires_grad = False
-        betas.requires_grad = False
-        global_orient.requires_grad = True
-        camera_translation.requires_grad = True
-
-        camera_opt_params = [global_orient, camera_translation]
-
-        if self.use_lbfgs:
-            camera_optimizer = torch.optim.LBFGS(camera_opt_params, max_iter=self.num_iters,
-                                                 lr=self.step_size, line_search_fn='strong_wolfe')
-            for i in range(10):
-                def closure():
-                    camera_optimizer.zero_grad()
-                    smpl_output = self.smpl(global_orient=global_orient,
-                                            body_pose=body_pose,
-                                            betas=betas)
-                    model_joints = smpl_output.joints
-                    # print('model_joints', model_joints.shape)
-                    # print('camera_translation', camera_translation.shape)
-                    # print('init_cam_t', init_cam_t.shape)
-                    # print('j3d', j3d.shape)
-                    loss = camera_fitting_loss_3d(model_joints, camera_translation,
-                                                  init_cam_t, j3d, self.joints_category)
-                    loss.backward()
-                    return loss
-
-                camera_optimizer.step(closure)
-        else:
-            camera_optimizer = torch.optim.Adam(camera_opt_params, lr=self.step_size, betas=(0.9, 0.999))
-
-            for i in range(20):
-                smpl_output = self.smpl(global_orient=global_orient,
-                                        body_pose=body_pose,
-                                        betas=betas)
-                model_joints = smpl_output.joints
-
-                loss = camera_fitting_loss_3d(model_joints[:, self.smpl_index], camera_translation,
-                                              init_cam_t,  j3d[:, self.corr_index], self.joints_category)
-                camera_optimizer.zero_grad()
-                loss.backward()
-                camera_optimizer.step()
-
-        # Fix camera translation after optimizing camera
-        # --------Step 2: Optimize body joints --------------------------
-        # Optimize only the body pose and global orientation of the body
-        body_pose.requires_grad = True
-        global_orient.requires_grad = True
-        camera_translation.requires_grad = True
-
-        # --- if we use the sequence, fix the shape
-        if seq_ind == 0:
-            betas.requires_grad = True
-            body_opt_params = [body_pose, betas, global_orient, camera_translation]
-        else:
-            betas.requires_grad = False
-            body_opt_params = [body_pose, global_orient, camera_translation]
-
-        if self.use_lbfgs:
-            body_optimizer = torch.optim.LBFGS(body_opt_params, max_iter=self.num_iters,
-                                               lr=self.step_size, line_search_fn='strong_wolfe')
-            for i in range(self.num_iters):
-                def closure():
-                    body_optimizer.zero_grad()
-                    smpl_output = self.smpl(global_orient=global_orient,
-                                            body_pose=body_pose,
-                                            betas=betas)
-                    model_joints = smpl_output.joints
-                    model_vertices = smpl_output.vertices
-
-                    loss = body_fitting_loss_3d(body_pose, preserve_pose, betas, model_joints[:, self.smpl_index], camera_translation,
-                                                j3d[:, self.corr_index], self.pose_prior,
-                                                joints3d_conf=conf_3d,
-                                                joint_loss_weight=600.0,
-                                                pose_preserve_weight=5.0,
-                                                use_collision=self.use_collision, 
-                                                model_vertices=model_vertices, model_faces=self.model_faces,
-                                                search_tree=search_tree, pen_distance=pen_distance, filter_faces=filter_faces)
-                    loss.backward()
-                    return loss
-
-                body_optimizer.step(closure)
-        else:
-            body_optimizer = torch.optim.Adam(body_opt_params, lr=self.step_size, betas=(0.9, 0.999))
-
-            for i in range(self.num_iters):
-                smpl_output = self.smpl(global_orient=global_orient,
-                                        body_pose=body_pose,
-                                        betas=betas)
-                model_joints = smpl_output.joints
-                model_vertices = smpl_output.vertices
-
-                loss = body_fitting_loss_3d(body_pose, preserve_pose, betas, model_joints[:, self.smpl_index], camera_translation,
-                                            j3d[:, self.corr_index], self.pose_prior,
-                                            joints3d_conf=conf_3d,
-                                            joint_loss_weight=600.0,
-                                            use_collision=self.use_collision, 
-                                            model_vertices=model_vertices, model_faces=self.model_faces,
-                                            search_tree=search_tree,  pen_distance=pen_distance,  filter_faces=filter_faces)
-                body_optimizer.zero_grad()
-                loss.backward()
-                body_optimizer.step()
-
-        # Get final loss value
-        with torch.no_grad():
-            smpl_output = self.smpl(global_orient=global_orient,
-                                    body_pose=body_pose,
-                                    betas=betas, return_full_pose=True)
-            model_joints = smpl_output.joints
-            model_vertices = smpl_output.vertices
-
-            final_loss = body_fitting_loss_3d(body_pose, preserve_pose, betas, model_joints[:, self.smpl_index], camera_translation,
-                                              j3d[:, self.corr_index], self.pose_prior,
-                                              joints3d_conf=conf_3d,
-                                              joint_loss_weight=600.0,
-                                              use_collision=self.use_collision, model_vertices=model_vertices, model_faces=self.model_faces,
-                                              search_tree=search_tree,  pen_distance=pen_distance,  filter_faces=filter_faces)
-
-        vertices = smpl_output.vertices.detach()
-        joints = smpl_output.joints.detach()
-        pose = torch.cat([global_orient, body_pose], dim=-1).detach()
-        betas = betas.detach()
-
-        return vertices, joints, pose, betas, camera_translation, final_loss
diff --git a/spaces/AIZero2HeroBootcamp/TranscriptAILearnerFromYoutube/TwoTranscriptQuotesFromIlyaSutskever.md b/spaces/AIZero2HeroBootcamp/TranscriptAILearnerFromYoutube/TwoTranscriptQuotesFromIlyaSutskever.md
deleted file mode 100644
index 9dea84c732f631d7d5204fcc65b0c8e0c9b913b8..0000000000000000000000000000000000000000
--- a/spaces/AIZero2HeroBootcamp/TranscriptAILearnerFromYoutube/TwoTranscriptQuotesFromIlyaSutskever.md
+++ /dev/null
@@ -1,71 +0,0 @@
-https://www.youtube.com/watch?v=9EN_HoEk3KY&t=172s
-
-
-1:42
-program the does very very well on your data then you will achieve the best
-1:48
-generalization possible with a little bit of modification you can turn it into a precise theorem
-1:54
-and on a very intuitive level it's easy to see what it should be the case if you
-2:01
-have some data and you're able to find a shorter program which generates this
-2:06
-data then you've essentially extracted all the all conceivable regularity from
-2:11
-this data into your program and then you can use these objects to make the best predictions possible like if if you have
-2:19
-data which is so complex but there is no way to express it as a shorter program
-2:25
-then it means that your data is totally random there is no way to extract any regularity from it whatsoever now there
-2:32
-is little known mathematical theory behind this and the proofs of these statements actually not even that hard
-2:38
-but the one minor slight disappointment is that it's actually not possible at
-2:44
-least given today's tools and understanding to find the best short program that 
-
-
-
-https://youtu.be/9EN_HoEk3KY?t=442
-5
-to talk a little bit about reinforcement learning so reinforcement learning is a framework it's a framework of evaluating
-6:53
-agents in their ability to achieve goals and complicated stochastic environments
-6:58
-you've got an agent which is plugged into an environment as shown in the figure right here and for any given
-7:06
-agent you can simply run it many times and compute its average reward now the
-7:13
-thing that's interesting about the reinforcement learning framework is that there exist interesting useful
-7:20
-reinforcement learning algorithms the framework existed for a long time it
-7:25
-became interesting once we realized that good algorithms exist now these are there are perfect algorithms but they
-7:31
-are good enough to do interesting things and all you want the mathematical
-7:37
-problem is one where you need to maximize the expected reward now one
-7:44
-important way in which the reinforcement learning framework is not quite complete is that it assumes that the reward is
-7:50
-given by the environment you see this picture the agent sends an action while
-7:56
-the reward sends it an observation in a both the observation and the reward backwards that's what the environment
-8:01
-communicates back the way in which this is not the case in the real world is that we figure out
-8:11
-what the reward is from the observation we reward ourselves we are not told
-8:16
-environment doesn't say hey here's some negative reward it's our interpretation over census that lets us determine what
-8:23
-the reward is and there is only one real true reward in life and this is
-8:28
-existence or nonexistence and everything else is a corollary of that so well what
-8:35
-should our agent be you already know the answer should be a neural network because whenever you want to do
-8:41
-something dense it's going to be a neural network and you want the agent to map observations to actions so you let
-8:47
-it be parametrized with a neural net and you apply learning algorithm so I want to explain to you how reinforcement
-8:53
-learning works this is model free reinforcement learning the reinforcement learning has actually been used in practice everywhere but it's
\ No newline at end of file
diff --git a/spaces/ATang0729/Forecast4Muses/Model/Model6/Model6_2_ProfileRecogition/mmpretrain/configs/resnet/resnet101_8xb16_cifar10.py b/spaces/ATang0729/Forecast4Muses/Model/Model6/Model6_2_ProfileRecogition/mmpretrain/configs/resnet/resnet101_8xb16_cifar10.py
deleted file mode 100644
index 166a1740b09c5fb74462a0672cd5fef54caae8f7..0000000000000000000000000000000000000000
--- a/spaces/ATang0729/Forecast4Muses/Model/Model6/Model6_2_ProfileRecogition/mmpretrain/configs/resnet/resnet101_8xb16_cifar10.py
+++ /dev/null
@@ -1,5 +0,0 @@
-_base_ = [
-    '../_base_/models/resnet101_cifar.py',
-    '../_base_/datasets/cifar10_bs16.py',
-    '../_base_/schedules/cifar10_bs128.py', '../_base_/default_runtime.py'
-]
diff --git a/spaces/AchyuthGamer/ImMagician-Image-Generator/README.md b/spaces/AchyuthGamer/ImMagician-Image-Generator/README.md
deleted file mode 100644
index 05f0fcf86606e1e46129b103632826b8406443e5..0000000000000000000000000000000000000000
--- a/spaces/AchyuthGamer/ImMagician-Image-Generator/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: ImMagician Image
-emoji: 🪄
-colorFrom: indigo
-colorTo: red
-sdk: gradio
-sdk_version: 3.39.0
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
\ No newline at end of file
diff --git a/spaces/Adapter/CoAdapter/ldm/modules/extra_condition/midas/midas/blocks.py b/spaces/Adapter/CoAdapter/ldm/modules/extra_condition/midas/midas/blocks.py
deleted file mode 100644
index 2145d18fa98060a618536d9a64fe6589e9be4f78..0000000000000000000000000000000000000000
--- a/spaces/Adapter/CoAdapter/ldm/modules/extra_condition/midas/midas/blocks.py
+++ /dev/null
@@ -1,342 +0,0 @@
-import torch
-import torch.nn as nn
-
-from .vit import (
-    _make_pretrained_vitb_rn50_384,
-    _make_pretrained_vitl16_384,
-    _make_pretrained_vitb16_384,
-    forward_vit,
-)
-
-def _make_encoder(backbone, features, use_pretrained, groups=1, expand=False, exportable=True, hooks=None, use_vit_only=False, use_readout="ignore",):
-    if backbone == "vitl16_384":
-        pretrained = _make_pretrained_vitl16_384(
-            use_pretrained, hooks=hooks, use_readout=use_readout
-        )
-        scratch = _make_scratch(
-            [256, 512, 1024, 1024], features, groups=groups, expand=expand
-        )  # ViT-L/16 - 85.0% Top1 (backbone)
-    elif backbone == "vitb_rn50_384":
-        pretrained = _make_pretrained_vitb_rn50_384(
-            use_pretrained,
-            hooks=hooks,
-            use_vit_only=use_vit_only,
-            use_readout=use_readout,
-        )
-        scratch = _make_scratch(
-            [256, 512, 768, 768], features, groups=groups, expand=expand
-        )  # ViT-H/16 - 85.0% Top1 (backbone)
-    elif backbone == "vitb16_384":
-        pretrained = _make_pretrained_vitb16_384(
-            use_pretrained, hooks=hooks, use_readout=use_readout
-        )
-        scratch = _make_scratch(
-            [96, 192, 384, 768], features, groups=groups, expand=expand
-        )  # ViT-B/16 - 84.6% Top1 (backbone)
-    elif backbone == "resnext101_wsl":
-        pretrained = _make_pretrained_resnext101_wsl(use_pretrained)
-        scratch = _make_scratch([256, 512, 1024, 2048], features, groups=groups, expand=expand)     # efficientnet_lite3  
-    elif backbone == "efficientnet_lite3":
-        pretrained = _make_pretrained_efficientnet_lite3(use_pretrained, exportable=exportable)
-        scratch = _make_scratch([32, 48, 136, 384], features, groups=groups, expand=expand)  # efficientnet_lite3     
-    else:
-        print(f"Backbone '{backbone}' not implemented")
-        assert False
-        
-    return pretrained, scratch
-
-
-def _make_scratch(in_shape, out_shape, groups=1, expand=False):
-    scratch = nn.Module()
-
-    out_shape1 = out_shape
-    out_shape2 = out_shape
-    out_shape3 = out_shape
-    out_shape4 = out_shape
-    if expand==True:
-        out_shape1 = out_shape
-        out_shape2 = out_shape*2
-        out_shape3 = out_shape*4
-        out_shape4 = out_shape*8
-
-    scratch.layer1_rn = nn.Conv2d(
-        in_shape[0], out_shape1, kernel_size=3, stride=1, padding=1, bias=False, groups=groups
-    )
-    scratch.layer2_rn = nn.Conv2d(
-        in_shape[1], out_shape2, kernel_size=3, stride=1, padding=1, bias=False, groups=groups
-    )
-    scratch.layer3_rn = nn.Conv2d(
-        in_shape[2], out_shape3, kernel_size=3, stride=1, padding=1, bias=False, groups=groups
-    )
-    scratch.layer4_rn = nn.Conv2d(
-        in_shape[3], out_shape4, kernel_size=3, stride=1, padding=1, bias=False, groups=groups
-    )
-
-    return scratch
-
-
-def _make_pretrained_efficientnet_lite3(use_pretrained, exportable=False):
-    efficientnet = torch.hub.load(
-        "rwightman/gen-efficientnet-pytorch",
-        "tf_efficientnet_lite3",
-        pretrained=use_pretrained,
-        exportable=exportable
-    )
-    return _make_efficientnet_backbone(efficientnet)
-
-
-def _make_efficientnet_backbone(effnet):
-    pretrained = nn.Module()
-
-    pretrained.layer1 = nn.Sequential(
-        effnet.conv_stem, effnet.bn1, effnet.act1, *effnet.blocks[0:2]
-    )
-    pretrained.layer2 = nn.Sequential(*effnet.blocks[2:3])
-    pretrained.layer3 = nn.Sequential(*effnet.blocks[3:5])
-    pretrained.layer4 = nn.Sequential(*effnet.blocks[5:9])
-
-    return pretrained
-    
-
-def _make_resnet_backbone(resnet):
-    pretrained = nn.Module()
-    pretrained.layer1 = nn.Sequential(
-        resnet.conv1, resnet.bn1, resnet.relu, resnet.maxpool, resnet.layer1
-    )
-
-    pretrained.layer2 = resnet.layer2
-    pretrained.layer3 = resnet.layer3
-    pretrained.layer4 = resnet.layer4
-
-    return pretrained
-
-
-def _make_pretrained_resnext101_wsl(use_pretrained):
-    resnet = torch.hub.load("facebookresearch/WSL-Images", "resnext101_32x8d_wsl")
-    return _make_resnet_backbone(resnet)
-
-
-
-class Interpolate(nn.Module):
-    """Interpolation module.
-    """
-
-    def __init__(self, scale_factor, mode, align_corners=False):
-        """Init.
-
-        Args:
-            scale_factor (float): scaling
-            mode (str): interpolation mode
-        """
-        super(Interpolate, self).__init__()
-
-        self.interp = nn.functional.interpolate
-        self.scale_factor = scale_factor
-        self.mode = mode
-        self.align_corners = align_corners
-
-    def forward(self, x):
-        """Forward pass.
-
-        Args:
-            x (tensor): input
-
-        Returns:
-            tensor: interpolated data
-        """
-
-        x = self.interp(
-            x, scale_factor=self.scale_factor, mode=self.mode, align_corners=self.align_corners
-        )
-
-        return x
-
-
-class ResidualConvUnit(nn.Module):
-    """Residual convolution module.
-    """
-
-    def __init__(self, features):
-        """Init.
-
-        Args:
-            features (int): number of features
-        """
-        super().__init__()
-
-        self.conv1 = nn.Conv2d(
-            features, features, kernel_size=3, stride=1, padding=1, bias=True
-        )
-
-        self.conv2 = nn.Conv2d(
-            features, features, kernel_size=3, stride=1, padding=1, bias=True
-        )
-
-        self.relu = nn.ReLU(inplace=True)
-
-    def forward(self, x):
-        """Forward pass.
-
-        Args:
-            x (tensor): input
-
-        Returns:
-            tensor: output
-        """
-        out = self.relu(x)
-        out = self.conv1(out)
-        out = self.relu(out)
-        out = self.conv2(out)
-
-        return out + x
-
-
-class FeatureFusionBlock(nn.Module):
-    """Feature fusion block.
-    """
-
-    def __init__(self, features):
-        """Init.
-
-        Args:
-            features (int): number of features
-        """
-        super(FeatureFusionBlock, self).__init__()
-
-        self.resConfUnit1 = ResidualConvUnit(features)
-        self.resConfUnit2 = ResidualConvUnit(features)
-
-    def forward(self, *xs):
-        """Forward pass.
-
-        Returns:
-            tensor: output
-        """
-        output = xs[0]
-
-        if len(xs) == 2:
-            output += self.resConfUnit1(xs[1])
-
-        output = self.resConfUnit2(output)
-
-        output = nn.functional.interpolate(
-            output, scale_factor=2, mode="bilinear", align_corners=True
-        )
-
-        return output
-
-
-
-
-class ResidualConvUnit_custom(nn.Module):
-    """Residual convolution module.
-    """
-
-    def __init__(self, features, activation, bn):
-        """Init.
-
-        Args:
-            features (int): number of features
-        """
-        super().__init__()
-
-        self.bn = bn
-
-        self.groups=1
-
-        self.conv1 = nn.Conv2d(
-            features, features, kernel_size=3, stride=1, padding=1, bias=True, groups=self.groups
-        )
-        
-        self.conv2 = nn.Conv2d(
-            features, features, kernel_size=3, stride=1, padding=1, bias=True, groups=self.groups
-        )
-
-        if self.bn==True:
-            self.bn1 = nn.BatchNorm2d(features)
-            self.bn2 = nn.BatchNorm2d(features)
-
-        self.activation = activation
-
-        self.skip_add = nn.quantized.FloatFunctional()
-
-    def forward(self, x):
-        """Forward pass.
-
-        Args:
-            x (tensor): input
-
-        Returns:
-            tensor: output
-        """
-        
-        out = self.activation(x)
-        out = self.conv1(out)
-        if self.bn==True:
-            out = self.bn1(out)
-       
-        out = self.activation(out)
-        out = self.conv2(out)
-        if self.bn==True:
-            out = self.bn2(out)
-
-        if self.groups > 1:
-            out = self.conv_merge(out)
-
-        return self.skip_add.add(out, x)
-
-        # return out + x
-
-
-class FeatureFusionBlock_custom(nn.Module):
-    """Feature fusion block.
-    """
-
-    def __init__(self, features, activation, deconv=False, bn=False, expand=False, align_corners=True):
-        """Init.
-
-        Args:
-            features (int): number of features
-        """
-        super(FeatureFusionBlock_custom, self).__init__()
-
-        self.deconv = deconv
-        self.align_corners = align_corners
-
-        self.groups=1
-
-        self.expand = expand
-        out_features = features
-        if self.expand==True:
-            out_features = features//2
-        
-        self.out_conv = nn.Conv2d(features, out_features, kernel_size=1, stride=1, padding=0, bias=True, groups=1)
-
-        self.resConfUnit1 = ResidualConvUnit_custom(features, activation, bn)
-        self.resConfUnit2 = ResidualConvUnit_custom(features, activation, bn)
-        
-        self.skip_add = nn.quantized.FloatFunctional()
-
-    def forward(self, *xs):
-        """Forward pass.
-
-        Returns:
-            tensor: output
-        """
-        output = xs[0]
-
-        if len(xs) == 2:
-            res = self.resConfUnit1(xs[1])
-            output = self.skip_add.add(output, res)
-            # output += res
-
-        output = self.resConfUnit2(output)
-
-        output = nn.functional.interpolate(
-            output, scale_factor=2, mode="bilinear", align_corners=self.align_corners
-        )
-
-        output = self.out_conv(output)
-
-        return output
-
diff --git a/spaces/Adapting/TrendFlow/README.md b/spaces/Adapting/TrendFlow/README.md
deleted file mode 100644
index 940664486ea87ca563e543ea053a1cacca5e353b..0000000000000000000000000000000000000000
--- a/spaces/Adapting/TrendFlow/README.md
+++ /dev/null
@@ -1,11 +0,0 @@
----
-title: TrendFlow
-emoji: 📉
-colorFrom: indigo
-colorTo: blue
-sdk: streamlit
-sdk_version: 1.10.0
-app_file: app.py
-pinned: false
-license: mit
----
diff --git a/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/buttons/Factory.js b/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/buttons/Factory.js
deleted file mode 100644
index ec3147a0eaf6f16320c6017af7c319cc01c11fe3..0000000000000000000000000000000000000000
--- a/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/buttons/Factory.js
+++ /dev/null
@@ -1,13 +0,0 @@
-import Buttons from './Buttons.js';
-import ObjectFactory from '../ObjectFactory.js';
-import SetValue from '../../../plugins/utils/object/SetValue.js';
-
-ObjectFactory.register('buttons', function (config) {
-    var gameObject = new Buttons(this.scene, config);
-    this.scene.add.existing(gameObject);
-    return gameObject;
-});
-
-SetValue(window, 'RexPlugins.UI.Buttons', Buttons);
-
-export default Buttons;
\ No newline at end of file
diff --git a/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/sizer/AlignMethods.js b/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/sizer/AlignMethods.js
deleted file mode 100644
index 84755c9e14ebb090cba057d066f224f4b10b29c3..0000000000000000000000000000000000000000
--- a/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/sizer/AlignMethods.js
+++ /dev/null
@@ -1,17 +0,0 @@
-import ALIGNMODE from '../utils/AlignConst.js';
-
-export default {
-    getChildAlign(gameObject) {
-        return this.getSizerConfig(gameObject).align;
-    },
-
-    setChildAlign(gameObject, align) {
-        if (typeof (align) === 'string') {
-            align = ALIGNMODE[align];
-        }
-
-        this.getSizerConfig(gameObject).align = align;
-        return this;
-    },
-
-}
\ No newline at end of file
diff --git a/spaces/Androidonnxfork/CivitAi-to-Diffusers/diffusers/docs/source/en/api/outputs.md b/spaces/Androidonnxfork/CivitAi-to-Diffusers/diffusers/docs/source/en/api/outputs.md
deleted file mode 100644
index ec64d36498ee0eccf9f8b7955aef9c69fd151bd3..0000000000000000000000000000000000000000
--- a/spaces/Androidonnxfork/CivitAi-to-Diffusers/diffusers/docs/source/en/api/outputs.md
+++ /dev/null
@@ -1,67 +0,0 @@
-<!--Copyright 2023 The HuggingFace Team. All rights reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
-the License. You may obtain a copy of the License at
-
-http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
-an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
-specific language governing permissions and limitations under the License.
--->
-
-# Outputs
-
-All models outputs are subclasses of [`~utils.BaseOutput`], data structures containing all the information returned by the model. The outputs can also be used as tuples or dictionaries.
-
-For example:
-
-```python
-from diffusers import DDIMPipeline
-
-pipeline = DDIMPipeline.from_pretrained("google/ddpm-cifar10-32")
-outputs = pipeline()
-```
-
-The `outputs` object is a [`~pipelines.ImagePipelineOutput`] which means it has an image attribute.
-
-You can access each attribute as you normally would or with a keyword lookup, and if that attribute is not returned by the model, you will get `None`:
-
-```python
-outputs.images
-outputs["images"]
-```
-
-When considering the `outputs` object as a tuple, it only considers the attributes that don't have `None` values.
-For instance, retrieving an image by indexing into it returns the tuple `(outputs.images)`:
-
-```python
-outputs[:1]
-```
-
-<Tip>
-
-To check a specific pipeline or model output, refer to its corresponding API documentation.
-
-</Tip>
-
-## BaseOutput
-
-[[autodoc]] utils.BaseOutput
-    - to_tuple
-
-## ImagePipelineOutput
-
-[[autodoc]] pipelines.ImagePipelineOutput
-
-## FlaxImagePipelineOutput
-
-[[autodoc]] pipelines.pipeline_flax_utils.FlaxImagePipelineOutput
-
-## AudioPipelineOutput
-
-[[autodoc]] pipelines.AudioPipelineOutput
-
-## ImageTextPipelineOutput
-
-[[autodoc]] ImageTextPipelineOutput
\ No newline at end of file
diff --git a/spaces/Andy1621/uniformer_image_detection/mmdet/utils/util_random.py b/spaces/Andy1621/uniformer_image_detection/mmdet/utils/util_random.py
deleted file mode 100644
index e313e9947bb3232a9458878fd219e1594ab93d57..0000000000000000000000000000000000000000
--- a/spaces/Andy1621/uniformer_image_detection/mmdet/utils/util_random.py
+++ /dev/null
@@ -1,33 +0,0 @@
-"""Helpers for random number generators."""
-import numpy as np
-
-
-def ensure_rng(rng=None):
-    """Coerces input into a random number generator.
-
-    If the input is None, then a global random state is returned.
-
-    If the input is a numeric value, then that is used as a seed to construct a
-    random state. Otherwise the input is returned as-is.
-
-    Adapted from [1]_.
-
-    Args:
-        rng (int | numpy.random.RandomState | None):
-            if None, then defaults to the global rng. Otherwise this can be an
-            integer or a RandomState class
-    Returns:
-        (numpy.random.RandomState) : rng -
-            a numpy random number generator
-
-    References:
-        .. [1] https://gitlab.kitware.com/computer-vision/kwarray/blob/master/kwarray/util_random.py#L270  # noqa: E501
-    """
-
-    if rng is None:
-        rng = np.random.mtrand._rand
-    elif isinstance(rng, int):
-        rng = np.random.RandomState(rng)
-    else:
-        rng = rng
-    return rng
diff --git a/spaces/Andy1621/uniformer_image_detection/tools/slurm_test.sh b/spaces/Andy1621/uniformer_image_detection/tools/slurm_test.sh
deleted file mode 100644
index 6dd67e57442b741fc30f26102eb5afe16139edb1..0000000000000000000000000000000000000000
--- a/spaces/Andy1621/uniformer_image_detection/tools/slurm_test.sh
+++ /dev/null
@@ -1,24 +0,0 @@
-#!/usr/bin/env bash
-
-set -x
-
-PARTITION=$1
-JOB_NAME=$2
-CONFIG=$3
-CHECKPOINT=$4
-GPUS=${GPUS:-8}
-GPUS_PER_NODE=${GPUS_PER_NODE:-8}
-CPUS_PER_TASK=${CPUS_PER_TASK:-5}
-PY_ARGS=${@:5}
-SRUN_ARGS=${SRUN_ARGS:-""}
-
-PYTHONPATH="$(dirname $0)/..":$PYTHONPATH \
-srun -p ${PARTITION} \
-    --job-name=${JOB_NAME} \
-    --gres=gpu:${GPUS_PER_NODE} \
-    --ntasks=${GPUS} \
-    --ntasks-per-node=${GPUS_PER_NODE} \
-    --cpus-per-task=${CPUS_PER_TASK} \
-    --kill-on-bad-exit=1 \
-    ${SRUN_ARGS} \
-    python -u tools/test.py ${CONFIG} ${CHECKPOINT} --launcher="slurm" ${PY_ARGS}
diff --git a/spaces/AnnasBlackHat/Image-Similarity/src/similarity/model_implements/vit_base.py b/spaces/AnnasBlackHat/Image-Similarity/src/similarity/model_implements/vit_base.py
deleted file mode 100644
index bdf66c16548834e61affb8e205d14eb3335b6735..0000000000000000000000000000000000000000
--- a/spaces/AnnasBlackHat/Image-Similarity/src/similarity/model_implements/vit_base.py
+++ /dev/null
@@ -1,20 +0,0 @@
-from transformers import ViTFeatureExtractor, ViTModel
-from PIL import Image
-import numpy as np 
-import torch
-
-class VitBase():
-
-    def __init__(self):
-        self.feature_extractor = ViTFeatureExtractor.from_pretrained('google/vit-base-patch16-224-in21k')
-        self.model = ViTModel.from_pretrained('google/vit-base-patch16-224-in21k')
-    
-    def extract_feature(self, imgs):
-        features = []
-        for img in imgs:
-            inputs = self.feature_extractor(images=img, return_tensors="pt")
-            with torch.no_grad():
-                outputs = self.model(**inputs)
-            last_hidden_states =  outputs.last_hidden_state            
-            features.append(np.squeeze(last_hidden_states.numpy()).flatten())            
-        return features
diff --git a/spaces/Apex-X/nono/README.md b/spaces/Apex-X/nono/README.md
deleted file mode 100644
index 281d35c27bd39c7813abc0a0cc46f8a4e6d11d86..0000000000000000000000000000000000000000
--- a/spaces/Apex-X/nono/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: nono
-emoji: 🚀
-colorFrom: red
-colorTo: indigo
-sdk: gradio
-sdk_version: 3.41.2
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Apex-X/nono/roop/ui.py b/spaces/Apex-X/nono/roop/ui.py
deleted file mode 100644
index ba693dac116bd416b91518734fa550e9dfb95c7b..0000000000000000000000000000000000000000
--- a/spaces/Apex-X/nono/roop/ui.py
+++ /dev/null
@@ -1,231 +0,0 @@
-import os
-import webbrowser
-import customtkinter as ctk
-from typing import Callable, Tuple
-import cv2
-from PIL import Image, ImageOps
-
-import roop.globals
-import roop.metadata
-from roop.face_analyser import get_one_face
-from roop.capturer import get_video_frame, get_video_frame_total
-from roop.predicter import predict_frame
-from roop.processors.frame.core import get_frame_processors_modules
-from roop.utilities import is_image, is_video, resolve_relative_path
-
-ROOT = None
-ROOT_HEIGHT = 700
-ROOT_WIDTH = 600
-
-PREVIEW = None
-PREVIEW_MAX_HEIGHT = 700
-PREVIEW_MAX_WIDTH = 1200
-
-RECENT_DIRECTORY_SOURCE = None
-RECENT_DIRECTORY_TARGET = None
-RECENT_DIRECTORY_OUTPUT = None
-
-preview_label = None
-preview_slider = None
-source_label = None
-target_label = None
-status_label = None
-
-
-def init(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.CTk:
-    global ROOT, PREVIEW
-
-    ROOT = create_root(start, destroy)
-    PREVIEW = create_preview(ROOT)
-
-    return ROOT
-
-
-def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.CTk:
-    global source_label, target_label, status_label
-
-    ctk.deactivate_automatic_dpi_awareness()
-    ctk.set_appearance_mode('system')
-    ctk.set_default_color_theme(resolve_relative_path('ui.json'))
-
-    root = ctk.CTk()
-    root.minsize(ROOT_WIDTH, ROOT_HEIGHT)
-    root.title(f'{roop.metadata.name} {roop.metadata.version}')
-    root.configure()
-    root.protocol('WM_DELETE_WINDOW', lambda: destroy())
-
-    source_label = ctk.CTkLabel(root, text=None)
-    source_label.place(relx=0.1, rely=0.1, relwidth=0.3, relheight=0.25)
-
-    target_label = ctk.CTkLabel(root, text=None)
-    target_label.place(relx=0.6, rely=0.1, relwidth=0.3, relheight=0.25)
-
-    source_button = ctk.CTkButton(root, text='Select a face', cursor='hand2', command=lambda: select_source_path())
-    source_button.place(relx=0.1, rely=0.4, relwidth=0.3, relheight=0.1)
-
-    target_button = ctk.CTkButton(root, text='Select a target', cursor='hand2', command=lambda: select_target_path())
-    target_button.place(relx=0.6, rely=0.4, relwidth=0.3, relheight=0.1)
-
-    keep_fps_value = ctk.BooleanVar(value=roop.globals.keep_fps)
-    keep_fps_checkbox = ctk.CTkSwitch(root, text='Keep fps', variable=keep_fps_value, cursor='hand2', command=lambda: setattr(roop.globals, 'keep_fps', not roop.globals.keep_fps))
-    keep_fps_checkbox.place(relx=0.1, rely=0.6)
-
-    keep_frames_value = ctk.BooleanVar(value=roop.globals.keep_frames)
-    keep_frames_switch = ctk.CTkSwitch(root, text='Keep frames', variable=keep_frames_value, cursor='hand2', command=lambda: setattr(roop.globals, 'keep_frames', keep_frames_value.get()))
-    keep_frames_switch.place(relx=0.1, rely=0.65)
-
-    keep_audio_value = ctk.BooleanVar(value=roop.globals.keep_audio)
-    keep_audio_switch = ctk.CTkSwitch(root, text='Keep audio', variable=keep_audio_value, cursor='hand2', command=lambda: setattr(roop.globals, 'keep_audio', keep_audio_value.get()))
-    keep_audio_switch.place(relx=0.6, rely=0.6)
-
-    many_faces_value = ctk.BooleanVar(value=roop.globals.many_faces)
-    many_faces_switch = ctk.CTkSwitch(root, text='Many faces', variable=many_faces_value, cursor='hand2', command=lambda: setattr(roop.globals, 'many_faces', many_faces_value.get()))
-    many_faces_switch.place(relx=0.6, rely=0.65)
-
-    start_button = ctk.CTkButton(root, text='Start', cursor='hand2', command=lambda: select_output_path(start))
-    start_button.place(relx=0.15, rely=0.75, relwidth=0.2, relheight=0.05)
-
-    stop_button = ctk.CTkButton(root, text='Destroy', cursor='hand2', command=lambda: destroy())
-    stop_button.place(relx=0.4, rely=0.75, relwidth=0.2, relheight=0.05)
-
-    preview_button = ctk.CTkButton(root, text='Preview', cursor='hand2', command=lambda: toggle_preview())
-    preview_button.place(relx=0.65, rely=0.75, relwidth=0.2, relheight=0.05)
-
-    status_label = ctk.CTkLabel(root, text=None, justify='center')
-    status_label.place(relx=0.1, rely=0.9, relwidth=0.8)
-
-    donate_label = ctk.CTkLabel(root, text='^_^ Donate to project ^_^', justify='center', cursor='hand2')
-    donate_label.place(relx=0.1, rely=0.95, relwidth=0.8)
-    donate_label.configure(text_color=ctk.ThemeManager.theme.get('RoopDonate').get('text_color'))
-    donate_label.bind('<Button>', lambda event: webbrowser.open('https://github.com/sponsors/s0md3v'))
-
-    return root
-
-
-def create_preview(parent: ctk.CTkToplevel) -> ctk.CTkToplevel:
-    global preview_label, preview_slider
-
-    preview = ctk.CTkToplevel(parent)
-    preview.withdraw()
-    preview.title('Preview')
-    preview.configure()
-    preview.protocol('WM_DELETE_WINDOW', lambda: toggle_preview())
-    preview.resizable(width=False, height=False)
-
-    preview_label = ctk.CTkLabel(preview, text=None)
-    preview_label.pack(fill='both', expand=True)
-
-    preview_slider = ctk.CTkSlider(preview, from_=0, to=0, command=lambda frame_value: update_preview(frame_value))
-
-    return preview
-
-
-def update_status(text: str) -> None:
-    status_label.configure(text=text)
-    ROOT.update()
-
-
-def select_source_path() -> None:
-    global RECENT_DIRECTORY_SOURCE
-
-    PREVIEW.withdraw()
-    source_path = ctk.filedialog.askopenfilename(title='select an source image', initialdir=RECENT_DIRECTORY_SOURCE)
-    if is_image(source_path):
-        roop.globals.source_path = source_path
-        RECENT_DIRECTORY_SOURCE = os.path.dirname(roop.globals.source_path)
-        image = render_image_preview(roop.globals.source_path, (200, 200))
-        source_label.configure(image=image)
-    else:
-        roop.globals.source_path = None
-        source_label.configure(image=None)
-
-
-def select_target_path() -> None:
-    global RECENT_DIRECTORY_TARGET
-
-    PREVIEW.withdraw()
-    target_path = ctk.filedialog.askopenfilename(title='select an target image or video', initialdir=RECENT_DIRECTORY_TARGET)
-    if is_image(target_path):
-        roop.globals.target_path = target_path
-        RECENT_DIRECTORY_TARGET = os.path.dirname(roop.globals.target_path)
-        image = render_image_preview(roop.globals.target_path, (200, 200))
-        target_label.configure(image=image)
-    elif is_video(target_path):
-        roop.globals.target_path = target_path
-        RECENT_DIRECTORY_TARGET = os.path.dirname(roop.globals.target_path)
-        video_frame = render_video_preview(target_path, (200, 200))
-        target_label.configure(image=video_frame)
-    else:
-        roop.globals.target_path = None
-        target_label.configure(image=None)
-
-
-def select_output_path(start: Callable[[], None]) -> None:
-    global RECENT_DIRECTORY_OUTPUT
-
-    if is_image(roop.globals.target_path):
-        output_path = ctk.filedialog.asksaveasfilename(title='save image output file', defaultextension='.png', initialfile='output.png', initialdir=RECENT_DIRECTORY_OUTPUT)
-    elif is_video(roop.globals.target_path):
-        output_path = ctk.filedialog.asksaveasfilename(title='save video output file', defaultextension='.mp4', initialfile='output.mp4', initialdir=RECENT_DIRECTORY_OUTPUT)
-    else:
-        output_path = None
-    if output_path:
-        roop.globals.output_path = output_path
-        RECENT_DIRECTORY_OUTPUT = os.path.dirname(roop.globals.output_path)
-        start()
-
-
-def render_image_preview(image_path: str, size: Tuple[int, int]) -> ctk.CTkImage:
-    image = Image.open(image_path)
-    if size:
-        image = ImageOps.fit(image, size, Image.LANCZOS)
-    return ctk.CTkImage(image, size=image.size)
-
-
-def render_video_preview(video_path: str, size: Tuple[int, int], frame_number: int = 0) -> ctk.CTkImage:
-    capture = cv2.VideoCapture(video_path)
-    if frame_number:
-        capture.set(cv2.CAP_PROP_POS_FRAMES, frame_number)
-    has_frame, frame = capture.read()
-    if has_frame:
-        image = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
-        if size:
-            image = ImageOps.fit(image, size, Image.LANCZOS)
-        return ctk.CTkImage(image, size=image.size)
-    capture.release()
-    cv2.destroyAllWindows()
-
-
-def toggle_preview() -> None:
-    if PREVIEW.state() == 'normal':
-        PREVIEW.withdraw()
-    elif roop.globals.source_path and roop.globals.target_path:
-        init_preview()
-        update_preview()
-        PREVIEW.deiconify()
-
-
-def init_preview() -> None:
-    if is_image(roop.globals.target_path):
-        preview_slider.pack_forget()
-    if is_video(roop.globals.target_path):
-        video_frame_total = get_video_frame_total(roop.globals.target_path)
-        preview_slider.configure(to=video_frame_total)
-        preview_slider.pack(fill='x')
-        preview_slider.set(0)
-
-
-def update_preview(frame_number: int = 0) -> None:
-    if roop.globals.source_path and roop.globals.target_path:
-        temp_frame = get_video_frame(roop.globals.target_path, frame_number)
-        if predict_frame(temp_frame):
-            quit()
-        for frame_processor in get_frame_processors_modules(roop.globals.frame_processors):
-            temp_frame = frame_processor.process_frame(
-                get_one_face(cv2.imread(roop.globals.source_path)),
-                temp_frame
-            )
-        image = Image.fromarray(cv2.cvtColor(temp_frame, cv2.COLOR_BGR2RGB))
-        image = ImageOps.contain(image, (PREVIEW_MAX_WIDTH, PREVIEW_MAX_HEIGHT), Image.LANCZOS)
-        image = ctk.CTkImage(image, size=image.size)
-        preview_label.configure(image=image)
diff --git a/spaces/Arnaudding001/OpenAI_whisperLive/README.md b/spaces/Arnaudding001/OpenAI_whisperLive/README.md
deleted file mode 100644
index 0df27f09af3b0c14005f49687c4fd10188bcea18..0000000000000000000000000000000000000000
--- a/spaces/Arnaudding001/OpenAI_whisperLive/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: OpenAI WhisperLive
-emoji: 📈
-colorFrom: gray
-colorTo: pink
-sdk: gradio
-sdk_version: 3.9
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Artgor/digit-draw-detect/README.md b/spaces/Artgor/digit-draw-detect/README.md
deleted file mode 100644
index 6c0397aa577b2c6d5f541aeb78d1761ff0359a23..0000000000000000000000000000000000000000
--- a/spaces/Artgor/digit-draw-detect/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Digit Draw Detect
-emoji: ✍️
-colorFrom: pink
-colorTo: green
-sdk: streamlit
-python_version: 3.10.4
-sdk_version: 1.26.0
-app_file: st_app.py
-pinned: false
-license: mit
----
-![visitors](https://visitor-badge.glitch.me/badge?page_id=wissamantoun.arabicnlpapp)
diff --git a/spaces/Artgor/digit-draw-detect/src/ml_utils.py b/spaces/Artgor/digit-draw-detect/src/ml_utils.py
deleted file mode 100644
index 8bd5df870497fb6ef4ca08558a22ab31cfa95569..0000000000000000000000000000000000000000
--- a/spaces/Artgor/digit-draw-detect/src/ml_utils.py
+++ /dev/null
@@ -1,207 +0,0 @@
-import logging
-from typing import List
-
-import albumentations as A
-import streamlit as st
-import torch
-from albumentations import pytorch
-
-from src.model_architecture import Net
-
-anchors = torch.tensor(
-    [
-        [[0.2800, 0.2200], [0.3800, 0.4800], [0.9000, 0.7800]],
-        [[0.0700, 0.1500], [0.1500, 0.1100], [0.1400, 0.2900]],
-        [[0.0200, 0.0300], [0.0400, 0.0700], [0.0800, 0.0600]],
-    ]
-)
-
-transforms = A.Compose(
-    [
-        A.Resize(always_apply=False, p=1, height=192, width=192, interpolation=1),
-        A.Normalize(),
-        pytorch.transforms.ToTensorV2(),
-    ]
-)
-
-
-def cells_to_bboxes(
-    predictions: torch.Tensor, tensor_anchors: torch.Tensor, s: int, is_preds: bool = True
-) -> List[List]:
-    """
-    Scale the predictions coming from the model_files to
-    be relative to the entire image such that they for example later
-    can be plotted or.
-    Args:
-        predictions: tensor of size (N, 3, S, S, num_classes+5)
-        tensor_anchors: the anchors used for the predictions
-        s: the number of cells the image is divided in on the width (and height)
-        is_preds: whether the input is predictions or the true bounding boxes
-    Returns:
-        converted_bboxes: the converted boxes of sizes (N, num_anchors, S, S, 1+5) with class index,
-                      object score, bounding box coordinates
-    """
-    batch_size = predictions.shape[0]
-    num_anchors = len(tensor_anchors)
-    box_predictions = predictions[..., 1:5]
-    if is_preds:
-        tensor_anchors = tensor_anchors.reshape(1, len(tensor_anchors), 1, 1, 2)
-        box_predictions[..., 0:2] = torch.sigmoid(box_predictions[..., 0:2])
-        box_predictions[..., 2:] = torch.exp(box_predictions[..., 2:]) * tensor_anchors
-        scores = torch.sigmoid(predictions[..., 0:1])
-        best_class = torch.argmax(predictions[..., 5:], dim=-1).unsqueeze(-1)
-    else:
-        scores = predictions[..., 0:1]
-        best_class = predictions[..., 5:6]
-
-    cell_indices = torch.arange(s).repeat(predictions.shape[0], 3, s, 1).unsqueeze(-1).to(predictions.device)
-    x = 1 / s * (box_predictions[..., 0:1] + cell_indices)
-    y = 1 / s * (box_predictions[..., 1:2] + cell_indices.permute(0, 1, 3, 2, 4))
-    w_h = 1 / s * box_predictions[..., 2:4]
-    converted_bboxes = torch.cat((best_class, scores, x, y, w_h), dim=-1).reshape(batch_size, num_anchors * s * s, 6)
-    return converted_bboxes.tolist()
-
-
-def non_max_suppression(
-    bboxes: List[List], iou_threshold: float, threshold: float, box_format: str = 'corners'
-) -> List[List]:
-    """
-    Apply nms to the bboxes.
-
-    Video explanation of this function:
-    https://youtu.be/YDkjWEN8jNA
-    Does Non Max Suppression given bboxes
-    Args:
-        bboxes (list): list of lists containing all bboxes with each bboxes
-        specified as [class_pred, prob_score, x1, y1, x2, y2]
-        iou_threshold (float): threshold where predicted bboxes is correct
-        threshold (float): threshold to remove predicted bboxes (independent of IoU)
-        box_format (str): 'midpoint' or 'corners' used to specify bboxes
-    Returns:
-        list: bboxes after performing NMS given a specific IoU threshold
-    """
-
-    bboxes = [box for box in bboxes if box[1] > threshold]
-    bboxes = sorted(bboxes, key=lambda x: x[1], reverse=True)
-    bboxes_after_nms = []
-
-    while bboxes:
-        chosen_box = bboxes.pop(0)
-
-        bboxes = [
-            box
-            for box in bboxes
-            if box[0] != chosen_box[0]
-            or intersection_over_union(
-                torch.tensor(chosen_box[2:]),
-                torch.tensor(box[2:]),
-                box_format=box_format,
-            )
-            < iou_threshold
-        ]
-
-        bboxes_after_nms.append(chosen_box)
-
-    return bboxes_after_nms
-
-
-def intersection_over_union(
-    boxes_preds: torch.Tensor, boxes_labels: torch.Tensor, box_format: str = 'midpoint'
-) -> torch.Tensor:
-    """
-    Calculate iou.
-
-    Video explanation of this function:
-    https://youtu.be/XXYG5ZWtjj0
-    This function calculates intersection over union (iou) given pred boxes
-    and target boxes.
-    Args:
-        boxes_preds (tensor): Predictions of Bounding Boxes (BATCH_SIZE, 4)
-        boxes_labels (tensor): Correct labels of Bounding Boxes (BATCH_SIZE, 4)
-        box_format (str): midpoint/corners, if boxes (x,y,w,h) or (x1,y1,x2,y2)
-    Returns:
-        tensor: Intersection over union for all examples
-    """
-
-    if box_format == 'midpoint':
-        box1_x1 = boxes_preds[..., 0:1] - boxes_preds[..., 2:3] / 2
-        box1_y1 = boxes_preds[..., 1:2] - boxes_preds[..., 3:4] / 2
-        box1_x2 = boxes_preds[..., 0:1] + boxes_preds[..., 2:3] / 2
-        box1_y2 = boxes_preds[..., 1:2] + boxes_preds[..., 3:4] / 2
-        box2_x1 = boxes_labels[..., 0:1] - boxes_labels[..., 2:3] / 2
-        box2_y1 = boxes_labels[..., 1:2] - boxes_labels[..., 3:4] / 2
-        box2_x2 = boxes_labels[..., 0:1] + boxes_labels[..., 2:3] / 2
-        box2_y2 = boxes_labels[..., 1:2] + boxes_labels[..., 3:4] / 2
-
-    if box_format == 'corners':
-        box1_x1 = boxes_preds[..., 0:1]
-        box1_y1 = boxes_preds[..., 1:2]
-        box1_x2 = boxes_preds[..., 2:3]
-        box1_y2 = boxes_preds[..., 3:4]
-        box2_x1 = boxes_labels[..., 0:1]
-        box2_y1 = boxes_labels[..., 1:2]
-        box2_x2 = boxes_labels[..., 2:3]
-        box2_y2 = boxes_labels[..., 3:4]
-
-    x1 = torch.max(box1_x1, box2_x1)
-    y1 = torch.max(box1_y1, box2_y1)
-    x2 = torch.min(box1_x2, box2_x2)
-    y2 = torch.min(box1_y2, box2_y2)
-
-    intersection = (x2 - x1).clamp(0) * (y2 - y1).clamp(0)
-    box1_area = abs((box1_x2 - box1_x1) * (box1_y2 - box1_y1))
-    box2_area = abs((box2_x2 - box2_x1) * (box2_y2 - box2_y1))
-
-    return intersection / (box1_area + box2_area - intersection + 1e-6)
-
-
-def predict(
-    model: torch.nn.Module, image: torch.Tensor, iou_threshold: float = 1.0, threshold: float = 0.05
-) -> List[List]:
-    """
-    Apply the model_files to the predictions and to postprocessing
-    Args:
-        model: a trained pytorch model_files.
-        image: image as a torch tensor
-        iou_threshold: a threshold for intersection_over_union function
-        threshold: a threshold for bbox probability
-
-    Returns:
-        predicted bboxes
-
-    """
-    # apply model_files. add a dimension to imitate a batch size of 1
-    logits = model(image[None, :])
-    logging.info('predicted')
-
-    # postprocess. In fact, we could remove indexing with idx here, as there is a single image.
-    # But I prefer to keep it so that this code could be easier changed for cases with batch size > 1
-    bboxes: List[List] = [[] for _ in range(1)]
-    idx = 0
-    for i in range(3):
-        S = logits[i].shape[2]
-        # it could be better to initialize anchors inside the function, but I don't want to do it for every prediction.
-        anchor = anchors[i] * S
-        boxes_scale_i = cells_to_bboxes(logits[i], anchor, s=S, is_preds=True)
-        for idx, (box) in enumerate(boxes_scale_i):
-            bboxes[idx] += box
-    logging.info('Starting nms')
-    nms_boxes = non_max_suppression(
-        bboxes[idx],
-        iou_threshold=iou_threshold,
-        threshold=threshold,
-        box_format='midpoint',
-    )
-
-    return nms_boxes
-
-
-@st.cache_data
-def get_model():
-    model_name = 'model_files/best_model.pth'
-
-    model = Net()
-    model.load_state_dict(torch.load(model_name))
-    model.eval()
-
-    return model
diff --git a/spaces/B1360976/waste-management-system/style.css b/spaces/B1360976/waste-management-system/style.css
deleted file mode 100644
index c363a99237f7ae64ac32119cbce78edcc7b25c8e..0000000000000000000000000000000000000000
--- a/spaces/B1360976/waste-management-system/style.css
+++ /dev/null
@@ -1,7 +0,0 @@
- div.css-1rh8hwn.e16fv1kl2 {
-    /* background-color: #EEEEEE; */
-    padding: 3% 3% 3% 3%;
-    border-radius: 5px;
-    text-align: center;
-    /* font-size: 20px; */
-}
\ No newline at end of file
diff --git a/spaces/Bala2-03-2003/BRAHMAMAI/app.py b/spaces/Bala2-03-2003/BRAHMAMAI/app.py
deleted file mode 100644
index 1fefdfb34f3349a0c69e3057ab4aff5c151dff27..0000000000000000000000000000000000000000
--- a/spaces/Bala2-03-2003/BRAHMAMAI/app.py
+++ /dev/null
@@ -1,34 +0,0 @@
-import os
-import gradio as gr
-from langchain.chat_models import ChatOpenAI
-from langchain import LLMChain, PromptTemplate
-from langchain.memory import ConversationBufferMemory
-
-OPENAI_API_KEY=os.getenv('OPENAI_API_KEY')
-
-template = """Bala brahmam, your youthful and witty personal assistant! At 21 years old, she's full of energy and always eager to help.  Bala Brahmam goal is to assist you with any questions or problems you might have. Her enthusiasm shines through in every response, making interactions with her enjoyable and engaging.
-{chat_history}
-User: {user_message}
-Chatbot:"""
-
-prompt = PromptTemplate(
-    input_variables=["chat_history", "user_message"], template=template
-)
-
-memory = ConversationBufferMemory(memory_key="chat_history")
-
-llm_chain = LLMChain(
-    llm=ChatOpenAI(temperature='0.5', model_name="gpt-3.5-turbo"),
-    prompt=prompt,
-    verbose=True,
-    memory=memory,
-)
-
-def get_text_response(user_message,history):
-    response = llm_chain.predict(user_message = user_message)
-    return response
-
-demo = gr.ChatInterface(get_text_response)
-
-if __name__ == "__main__":
-    demo.launch() #To create a public link, set `share=True` in `launch()`. To enable errors and logs, set `debug=True` in `launch()`.
diff --git a/spaces/Bart92/RVC_HF/infer/lib/uvr5_pack/lib_v5/layers_33966KB.py b/spaces/Bart92/RVC_HF/infer/lib/uvr5_pack/lib_v5/layers_33966KB.py
deleted file mode 100644
index 9b127bc6427f5c60c8cf85603a3d8a093c3501c4..0000000000000000000000000000000000000000
--- a/spaces/Bart92/RVC_HF/infer/lib/uvr5_pack/lib_v5/layers_33966KB.py
+++ /dev/null
@@ -1,126 +0,0 @@
-import torch
-import torch.nn.functional as F
-from torch import nn
-
-from . import spec_utils
-
-
-class Conv2DBNActiv(nn.Module):
-    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
-        super(Conv2DBNActiv, self).__init__()
-        self.conv = nn.Sequential(
-            nn.Conv2d(
-                nin,
-                nout,
-                kernel_size=ksize,
-                stride=stride,
-                padding=pad,
-                dilation=dilation,
-                bias=False,
-            ),
-            nn.BatchNorm2d(nout),
-            activ(),
-        )
-
-    def __call__(self, x):
-        return self.conv(x)
-
-
-class SeperableConv2DBNActiv(nn.Module):
-    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
-        super(SeperableConv2DBNActiv, self).__init__()
-        self.conv = nn.Sequential(
-            nn.Conv2d(
-                nin,
-                nin,
-                kernel_size=ksize,
-                stride=stride,
-                padding=pad,
-                dilation=dilation,
-                groups=nin,
-                bias=False,
-            ),
-            nn.Conv2d(nin, nout, kernel_size=1, bias=False),
-            nn.BatchNorm2d(nout),
-            activ(),
-        )
-
-    def __call__(self, x):
-        return self.conv(x)
-
-
-class Encoder(nn.Module):
-    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.LeakyReLU):
-        super(Encoder, self).__init__()
-        self.conv1 = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
-        self.conv2 = Conv2DBNActiv(nout, nout, ksize, stride, pad, activ=activ)
-
-    def __call__(self, x):
-        skip = self.conv1(x)
-        h = self.conv2(skip)
-
-        return h, skip
-
-
-class Decoder(nn.Module):
-    def __init__(
-        self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.ReLU, dropout=False
-    ):
-        super(Decoder, self).__init__()
-        self.conv = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
-        self.dropout = nn.Dropout2d(0.1) if dropout else None
-
-    def __call__(self, x, skip=None):
-        x = F.interpolate(x, scale_factor=2, mode="bilinear", align_corners=True)
-        if skip is not None:
-            skip = spec_utils.crop_center(skip, x)
-            x = torch.cat([x, skip], dim=1)
-        h = self.conv(x)
-
-        if self.dropout is not None:
-            h = self.dropout(h)
-
-        return h
-
-
-class ASPPModule(nn.Module):
-    def __init__(self, nin, nout, dilations=(4, 8, 16, 32, 64), activ=nn.ReLU):
-        super(ASPPModule, self).__init__()
-        self.conv1 = nn.Sequential(
-            nn.AdaptiveAvgPool2d((1, None)),
-            Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ),
-        )
-        self.conv2 = Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ)
-        self.conv3 = SeperableConv2DBNActiv(
-            nin, nin, 3, 1, dilations[0], dilations[0], activ=activ
-        )
-        self.conv4 = SeperableConv2DBNActiv(
-            nin, nin, 3, 1, dilations[1], dilations[1], activ=activ
-        )
-        self.conv5 = SeperableConv2DBNActiv(
-            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
-        )
-        self.conv6 = SeperableConv2DBNActiv(
-            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
-        )
-        self.conv7 = SeperableConv2DBNActiv(
-            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
-        )
-        self.bottleneck = nn.Sequential(
-            Conv2DBNActiv(nin * 7, nout, 1, 1, 0, activ=activ), nn.Dropout2d(0.1)
-        )
-
-    def forward(self, x):
-        _, _, h, w = x.size()
-        feat1 = F.interpolate(
-            self.conv1(x), size=(h, w), mode="bilinear", align_corners=True
-        )
-        feat2 = self.conv2(x)
-        feat3 = self.conv3(x)
-        feat4 = self.conv4(x)
-        feat5 = self.conv5(x)
-        feat6 = self.conv6(x)
-        feat7 = self.conv7(x)
-        out = torch.cat((feat1, feat2, feat3, feat4, feat5, feat6, feat7), dim=1)
-        bottle = self.bottleneck(out)
-        return bottle
diff --git a/spaces/Benson/text-generation/Examples/Blockman Go Pc Download No Emulator.md b/spaces/Benson/text-generation/Examples/Blockman Go Pc Download No Emulator.md
deleted file mode 100644
index 0ff034cfe7318b6433a6bdc2f15bb780deecd8f0..0000000000000000000000000000000000000000
--- a/spaces/Benson/text-generation/Examples/Blockman Go Pc Download No Emulator.md	
+++ /dev/null
@@ -1,91 +0,0 @@
-<br />
-<h1>Blockman Go: Un juego divertido y creativo Sandbox</h1>
-<p>¿Alguna vez has querido jugar un juego que te permita explorar, construir y compartir tus propios mundos con otros jugadores? ¿Alguna vez has deseado probar diferentes tipos de juegos en una aplicación? ¿Alguna vez has soñado con personalizar tu propio avatar con miles de artículos y accesorios? Si respondiste sí a cualquiera de estas preguntas, entonces deberías revisar <strong>Blockman Go</strong>, un divertido y creativo juego de sandbox que ofrece todas estas características y más. </p>
-<h2>blockman go pc download no emulator</h2><br /><p><b><b>Download Zip</b> &#10026;&#10026;&#10026; <a href="https://bltlly.com/2v6Kwz">https://bltlly.com/2v6Kwz</a></b></p><br /><br />
-<p>Blockman Go es una aplicación gratuita que incluye minijuegos, chat y hacer amigos. Puedes jugar varios minijuegos de estilo bloque aquí, como Bed Wars, Sky Block, Egg War, Anime Fighting Simulator y muchos más. También puede chatear y conocer nuevos amigos de todo el mundo, unirse o crear grupos y clanes, y participar en eventos y competiciones. También puedes personalizar tu avatar con selecciones creativas de accesorios de moda, desde ropa y sombreros hasta alas y mascotas. Con un inventario creciente de artículos, puedes expresar tu estilo único al mundo. </p>
-<p>En este artículo, le mostraremos cómo descargar Blockman Go para PC sin emulador, cuáles son las características de Blockman Go para PC, cuáles son algunas alternativas a Blockman Go para PC, cuáles son algunas reseñas de Blockman Go para PC y algunas preguntas frecuentes sobre Blockman Go. Al final de este artículo, tendrás una mejor comprensión de lo que es Blockman Go y por qué deberías jugarlo. </p>
- <h2>Cómo descargar Blockman Go para PC sin emulador</h2>
-<p>Si quieres jugar Blockman Ir en tu PC sin usar un emulador, puedes seguir estos sencillos pasos:</p>
-<ol>
-<li>Visite el sitio web oficial de Blockman Vaya a <a href="( 1 )">https://www.blockmango.com/</a> y haga clic en el enlace de la versión del PC en la esquina superior derecha. </li>
-
-<li>Inicie el juego e inicie sesión con su cuenta existente o cree una nueva. Puede usar su correo electrónico, número de teléfono, Facebook o cuenta de Google para registrarse. </li>
-<li>Disfruta jugando varios minijuegos y personalizando tu avatar. Puede utilizar el ratón y el teclado para controlar el juego, o conectar un mando para una mejor experiencia. </li>
-</ol>
-<p>Eso es todo! Ahora puedes jugar Blockman Ir en tu PC sin emulador y disfrutar de todas las características del juego. </p>
- <h2>Características de Blockman Go para PC</h2>
-<p>Blockman Go para PC tiene muchas características que lo convierten en un juego de sandbox divertido y creativo. Estos son algunos de ellos:</p>
-<p></p>
-<h3>Varios minijuegos para diferentes géneros y preferencias</h3>
-<p>Blockman Go para PC ofrece una variedad de minijuegos que atienden a diferentes gustos e intereses. Puedes elegir entre diferentes géneros, como acción, aventura, rompecabezas, simulación, juegos de rol y más. También puedes encontrar juegos populares inspirados en otros títulos, como Bed Wars, Sky Block, Egg War, Anime Fighting Simulator y muchos más. Puedes jugar solo o con otros jugadores online, y competir por rankings y recompensas. </p>
-<h3>Chatear y hacer amigos con jugadores de todo el mundo</h3>
-<p>Blockman Go para PC no es solo un juego, sino también una plataforma social. Puede chatear e interactuar con otros jugadores de todo el mundo, utilizando texto, voz o video chat. También puedes unirte o crear grupos y clanes e invitar a tus amigos a jugar juntos. También puede participar en eventos y competiciones, como la Blockman Cup, el Blockman Festival y el Blockman Carnival. También puedes ganar insignias y logros para tu perfil. </p>
-<h3>Personaliza tu avatar con miles de artículos y accesorios</h3>
-
-<h3>Ganar oro jugando minijuegos y utilizarlo para comprar más artículos</h3>
-<p>Blockman Go para PC es libre de jugar, pero también puede ganar oro jugando minijuegos. El oro es la moneda principal en el juego que puedes usar para comprar más artículos y accesorios para tu avatar. También puede usar gcubes, que son moneda premium que puede comprar con dinero real o obtener de forma gratuita completando tareas o viendo anuncios. Gcubes se puede utilizar para comprar artículos exclusivos o desbloquear funciones VIP. </p>
-<h3>Gratis para jugar y actualizado regularmente con nuevo contenido</h3>
-<p>Blockman Go para PC es libre de jugar y no requiere ninguna suscripción o cuota de registro. Puede descargar y jugar el juego sin ningún tipo de molestia o limitación. El juego también se actualiza regularmente con nuevos contenidos, como nuevos minijuegos, nuevos artículos, nuevos eventos, nuevas características y más. Los desarrolladores siempre están escuchando los comentarios y sugerencias de los jugadores y mejorando el juego en consecuencia. </p>
- <h2>Alternativas a Blockman Go para PC</h2>
-<p>Si usted está buscando algunas alternativas a Blockman Go para PC, puede probar estos juegos:</p>
-<h3>Minetest - un motor de juego voxel de código abierto que le permite crear y jugar sus propios juegos</h3>
-<p>Si estás interesado en crear tus propios juegos usando gráficos voxel, puedes probar Minetest. Minetest es un motor de juego de código abierto que te permite crear y jugar tus propios juegos usando bloques. También puede descargar y jugar juegos hechos por otros usuarios desde la base de datos de contenido en línea. Minetest soporta modo multijugador, soporte de modding, texturas personalizadas, sonidos y más. Minetest está disponible para Windows, Linux, Mac OS X, Android, iOS, FreeBSD y otras plataformas. Puedes descargar Minetest gratis desde <a href="">https://www.minetest.net/</a>. </p>
-<h3>Roblox - una plataforma de creación de juegos que te permite diseñar y jugar juegos hechos por otros usuarios</h3>
-
-<h3>MineClone 2 - un clon gratuito de Minecraft que pretende estar lo más cerca posible del juego original</h3>
-<p>Si eres un fan de Minecraft y quieres jugar un clon gratuito que tiene como objetivo estar lo más cerca posible del juego original, puedes probar MineClone 2. MineClone 2 es un juego que replica el juego y las características de Minecraft, como el modo de supervivencia, el modo creativo, construcción, minería, agricultura, combate, turbas, biomas, redstone, encantador, elaboración de cerveza y más. MineClone 2 se basa en el motor Minetest y es compatible con muchos mods de Minetest y paquetes de texturas. MineClone 2 está disponible para Windows, Linux, Mac OS X, Android y otras plataformas. Puede descargar MineClone 2 gratis desde <a href="">https://content.minetest.net/packages/Wuzzy/mineclone2/</a>. </p>
- <h2>Opiniones de Blockman Go para PC</h2>
-<p>Blockman Go para PC ha recibido críticas mixtas de los usuarios que han jugado el juego. Aquí hay algunos ejemplos de comentarios positivos y negativos:</p>
-<h3>Una crítica positiva de un usuario que disfruta de la diversidad del juego y las características de la comunidad</h3>
-<p>"Me encanta este juego tanto! Tiene tantos minijuegos diferentes para elegir y todos son divertidos y emocionantes. También me gusta el sistema de chat y amigos que me permite hablar y jugar con otros jugadores de diferentes países. La personalización del avatar también es increíble y puedo crear mi propio look con tantos elementos. Recomiendo este juego a cualquiera que le gusten los juegos de sandbox y quiera divertirse con otros."</p>
-<h3>Una crítica negativa de un usuario que se queja de los errores del juego y los hackers</h3>
-<p>"Este juego es terrible! Tiene tantos errores y fallos que arruinan el juego. Los gráficos también son de baja calidad y laggy. La peor parte son los hackers que engañan y arruinan el juego para todos los demás. Usan hacks para volar, teletransportarse, matar a otros al instante, robar objetos y más. Los desarrolladores no hacen nada para detenerlos o arreglar el juego. Este juego es una pérdida de tiempo y dinero." </p>
- <h2>Conclusión y preguntas frecuentes</h2>
-
-<p>Si estás buscando un juego que ofrezca diversidad, creatividad, comunidad y entretenimiento, deberías probar Blockman Go. También puedes ver algunas alternativas a Blockman Go para PC si quieres probar diferentes juegos con características similares. </p>
-<p>Aquí hay algunas preguntas frecuentes sobre Blockman Go:</p>
-<h3>¿Cuáles son los requisitos del sistema para Blockman Go para PC? </h3>
-<p>Los requisitos del sistema para Blockman Go para PC son:</p>
-<ul>
-<li>Sistema operativo: Windows XP o superior</li>
-<li>RAM: 2 GB o más</li>
-<li>Espacio en disco: 1 GB o más</li>
-<li>Conexión a Internet: Requerido</li>
-</ul>
-<h3>¿Cómo puedo reportar un error o un hacker en Blockman Go? </h3>
-<p>Si encuentras un error o un hacker en Blockman Go, puedes reportarlo siguiendo estos pasos:</p>
-<ol>
-<li>Ir al menú de configuración en el juego y haga clic en el botón de retroalimentación. </li>
-<li>Seleccione el tipo de problema que desea reportar (error o hacker) y proporcione detalles como su nombre de usuario, el nombre de usuario del hacker, el nombre del minijuego, la fecha y hora del incidente, y capturas de pantalla o videos si es posible. </li>
-<li>Envíe su informe y espere una respuesta del equipo de servicio al cliente. </li>
-</ol>
-<p>También puede ponerse en contacto con el equipo de servicio al cliente por correo electrónico a <a href="mailto:cs@blockmango.com">cs@blockmango.com</a> o por teléfono al +86 400-999-8800. </p>
-<h3>¿Cómo puedo unirme o crear un grupo o un clan en Blockman Go? </h3>
-<p>Si quieres unirte o crear un grupo o un clan en Blockman Go, puedes seguir estos pasos:</p>
-<ol>
-<li>Ve al menú social del juego y haz clic en el botón de grupo o clan. </li>
-<li>Si quieres unirte a un grupo o a un clan, puedes buscar uno por nombre, ID o categoría, y luego solicitar unirse. También puedes aceptar invitaciones de otros jugadores que te inviten a su grupo o clan. </li>
-
-</ol>
-<p>Los grupos y clanes son formas de conectar con otros jugadores que comparten tus intereses y objetivos. Puedes chatear, jugar y competir con miembros de tu grupo o clan, y ganar recompensas y bonos para tu grupo o clan. </p>
-<h3>¿Cómo puedo obtener más oro o gcubes en Blockman Go? </h3>
-<p>Si quieres obtener más oro o gcubes en Blockman Go, puedes probar estos métodos:</p>
-<ul>
-<li>Juega minijuegos y gana oro al ganar o completar tareas. También puede obtener oro ingresando diariamente, viendo anuncios, completando encuestas o participando en eventos. </li>
-<li>Comprar gcubes con dinero real utilizando su tarjeta de crédito, PayPal, Google Play, App Store, u otros métodos de pago. También puedes obtener gcubes gratis completando tareas o viendo anuncios. </li>
-<li>Cambiar gcubes por oro en la tienda. También puede cambiar oro por gcubes a una tasa más baja. </li>
-</ul>
-<p>El oro y los gcubes son monedas que puedes usar para comprar artículos y accesorios para tu avatar. También puedes usar gcubes para desbloquear funciones VIP, como el doble de ingresos por oro, artículos exclusivos, acceso prioritario y más. </p>
-<h3>¿Cómo puedo contactar a los desarrolladores de Blockman Go? </h3>
-<p>Si desea ponerse en contacto con los desarrolladores de Blockman Go, puede utilizar estos canales:</p>
-<ul>
-<li>Correo electrónico: <a href="mailto:cs@blockmango.com">cs@blockmango.com</a></li>
-<li>Teléfono: +86 400-999-8800</li>
-<li>Sitio web: <a href="">https://www.blockmango.com/</a></li>
-<li>Facebook: <a href=">https://www.facebook.com/BlockmanGoOfficial/</a></li>
-<li>Twitter: <a href=">https://twitter.com/BlockmanGo</a></li>
-<li>YouTube: <a href=">https://www.youtube.com/channel/UCwJQsSxzc9KkNlmeU4L6Fgg</a></li>
-</ul>
-<p>Puede ponerse en contacto con los desarrolladores de Blockman Go si tiene alguna pregunta, sugerencia, retroalimentación o problemas sobre el juego. También puedes seguirlos en las redes sociales para obtener las últimas noticias y actualizaciones sobre el juego. </p> 64aa2da5cf<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/BetterAPI/BetterChat/src/lib/types/UrlDependency.ts b/spaces/BetterAPI/BetterChat/src/lib/types/UrlDependency.ts
deleted file mode 100644
index a97e60f2876959449df638ee36d84cd59d65bb21..0000000000000000000000000000000000000000
--- a/spaces/BetterAPI/BetterChat/src/lib/types/UrlDependency.ts
+++ /dev/null
@@ -1,5 +0,0 @@
-/* eslint-disable no-shadow */
-export enum UrlDependency {
-	ConversationList = "conversation:list",
-	Settings = "settings:list",
-}
diff --git a/spaces/Big-Web/MMSD/env/Lib/site-packages/boto3/s3/transfer.py b/spaces/Big-Web/MMSD/env/Lib/site-packages/boto3/s3/transfer.py
deleted file mode 100644
index cce5155d430774e86d503471d87cc627a9ae5677..0000000000000000000000000000000000000000
--- a/spaces/Big-Web/MMSD/env/Lib/site-packages/boto3/s3/transfer.py
+++ /dev/null
@@ -1,358 +0,0 @@
-# Copyright 2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License"). You
-# may not use this file except in compliance with the License. A copy of
-# the License is located at
-#
-# https://aws.amazon.com/apache2.0/
-#
-# or in the "license" file accompanying this file. This file is
-# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
-# ANY KIND, either express or implied. See the License for the specific
-# language governing permissions and limitations under the License.
-"""Abstractions over S3's upload/download operations.
-
-This module provides high level abstractions for efficient
-uploads/downloads.  It handles several things for the user:
-
-* Automatically switching to multipart transfers when
-  a file is over a specific size threshold
-* Uploading/downloading a file in parallel
-* Progress callbacks to monitor transfers
-* Retries.  While botocore handles retries for streaming uploads,
-  it is not possible for it to handle retries for streaming
-  downloads.  This module handles retries for both cases so
-  you don't need to implement any retry logic yourself.
-
-This module has a reasonable set of defaults.  It also allows you
-to configure many aspects of the transfer process including:
-
-* Multipart threshold size
-* Max parallel downloads
-* Socket timeouts
-* Retry amounts
-
-There is no support for s3->s3 multipart copies at this
-time.
-
-
-.. _ref_s3transfer_usage:
-
-Usage
-=====
-
-The simplest way to use this module is:
-
-.. code-block:: python
-
-    client = boto3.client('s3', 'us-west-2')
-    transfer = S3Transfer(client)
-    # Upload /tmp/myfile to s3://bucket/key
-    transfer.upload_file('/tmp/myfile', 'bucket', 'key')
-
-    # Download s3://bucket/key to /tmp/myfile
-    transfer.download_file('bucket', 'key', '/tmp/myfile')
-
-The ``upload_file`` and ``download_file`` methods also accept
-``**kwargs``, which will be forwarded through to the corresponding
-client operation.  Here are a few examples using ``upload_file``::
-
-    # Making the object public
-    transfer.upload_file('/tmp/myfile', 'bucket', 'key',
-                         extra_args={'ACL': 'public-read'})
-
-    # Setting metadata
-    transfer.upload_file('/tmp/myfile', 'bucket', 'key',
-                         extra_args={'Metadata': {'a': 'b', 'c': 'd'}})
-
-    # Setting content type
-    transfer.upload_file('/tmp/myfile.json', 'bucket', 'key',
-                         extra_args={'ContentType': "application/json"})
-
-
-The ``S3Transfer`` class also supports progress callbacks so you can
-provide transfer progress to users.  Both the ``upload_file`` and
-``download_file`` methods take an optional ``callback`` parameter.
-Here's an example of how to print a simple progress percentage
-to the user:
-
-.. code-block:: python
-
-    class ProgressPercentage(object):
-        def __init__(self, filename):
-            self._filename = filename
-            self._size = float(os.path.getsize(filename))
-            self._seen_so_far = 0
-            self._lock = threading.Lock()
-
-        def __call__(self, bytes_amount):
-            # To simplify we'll assume this is hooked up
-            # to a single filename.
-            with self._lock:
-                self._seen_so_far += bytes_amount
-                percentage = (self._seen_so_far / self._size) * 100
-                sys.stdout.write(
-                    "\r%s  %s / %s  (%.2f%%)" % (
-                        self._filename, self._seen_so_far, self._size,
-                        percentage))
-                sys.stdout.flush()
-
-
-    transfer = S3Transfer(boto3.client('s3', 'us-west-2'))
-    # Upload /tmp/myfile to s3://bucket/key and print upload progress.
-    transfer.upload_file('/tmp/myfile', 'bucket', 'key',
-                         callback=ProgressPercentage('/tmp/myfile'))
-
-
-
-You can also provide a TransferConfig object to the S3Transfer
-object that gives you more fine grained control over the
-transfer.  For example:
-
-.. code-block:: python
-
-    client = boto3.client('s3', 'us-west-2')
-    config = TransferConfig(
-        multipart_threshold=8 * 1024 * 1024,
-        max_concurrency=10,
-        num_download_attempts=10,
-    )
-    transfer = S3Transfer(client, config)
-    transfer.upload_file('/tmp/foo', 'bucket', 'key')
-
-
-"""
-from os import PathLike, fspath
-
-from botocore.exceptions import ClientError
-from s3transfer.exceptions import (
-    RetriesExceededError as S3TransferRetriesExceededError,
-)
-from s3transfer.futures import NonThreadedExecutor
-from s3transfer.manager import TransferConfig as S3TransferConfig
-from s3transfer.manager import TransferManager
-from s3transfer.subscribers import BaseSubscriber
-from s3transfer.utils import OSUtils
-
-from boto3.exceptions import RetriesExceededError, S3UploadFailedError
-
-KB = 1024
-MB = KB * KB
-
-
-def create_transfer_manager(client, config, osutil=None):
-    """Creates a transfer manager based on configuration
-
-    :type client: boto3.client
-    :param client: The S3 client to use
-
-    :type config: boto3.s3.transfer.TransferConfig
-    :param config: The transfer config to use
-
-    :type osutil: s3transfer.utils.OSUtils
-    :param osutil: The os utility to use
-
-    :rtype: s3transfer.manager.TransferManager
-    :returns: A transfer manager based on parameters provided
-    """
-    executor_cls = None
-    if not config.use_threads:
-        executor_cls = NonThreadedExecutor
-    return TransferManager(client, config, osutil, executor_cls)
-
-
-class TransferConfig(S3TransferConfig):
-    ALIAS = {
-        'max_concurrency': 'max_request_concurrency',
-        'max_io_queue': 'max_io_queue_size',
-    }
-
-    def __init__(
-        self,
-        multipart_threshold=8 * MB,
-        max_concurrency=10,
-        multipart_chunksize=8 * MB,
-        num_download_attempts=5,
-        max_io_queue=100,
-        io_chunksize=256 * KB,
-        use_threads=True,
-        max_bandwidth=None,
-    ):
-        """Configuration object for managed S3 transfers
-
-        :param multipart_threshold: The transfer size threshold for which
-            multipart uploads, downloads, and copies will automatically be
-            triggered.
-
-        :param max_concurrency: The maximum number of threads that will be
-            making requests to perform a transfer. If ``use_threads`` is
-            set to ``False``, the value provided is ignored as the transfer
-            will only ever use the main thread.
-
-        :param multipart_chunksize: The partition size of each part for a
-            multipart transfer.
-
-        :param num_download_attempts: The number of download attempts that
-            will be retried upon errors with downloading an object in S3.
-            Note that these retries account for errors that occur when
-            streaming  down the data from s3 (i.e. socket errors and read
-            timeouts that occur after receiving an OK response from s3).
-            Other retryable exceptions such as throttling errors and 5xx
-            errors are already retried by botocore (this default is 5). This
-            does not take into account the number of exceptions retried by
-            botocore.
-
-        :param max_io_queue: The maximum amount of read parts that can be
-            queued in memory to be written for a download. The size of each
-            of these read parts is at most the size of ``io_chunksize``.
-
-        :param io_chunksize: The max size of each chunk in the io queue.
-            Currently, this is size used when ``read`` is called on the
-            downloaded stream as well.
-
-        :param use_threads: If True, threads will be used when performing
-            S3 transfers. If False, no threads will be used in
-            performing transfers; all logic will be run in the main thread.
-
-        :param max_bandwidth: The maximum bandwidth that will be consumed
-            in uploading and downloading file content. The value is an integer
-            in terms of bytes per second.
-        """
-        super().__init__(
-            multipart_threshold=multipart_threshold,
-            max_request_concurrency=max_concurrency,
-            multipart_chunksize=multipart_chunksize,
-            num_download_attempts=num_download_attempts,
-            max_io_queue_size=max_io_queue,
-            io_chunksize=io_chunksize,
-            max_bandwidth=max_bandwidth,
-        )
-        # Some of the argument names are not the same as the inherited
-        # S3TransferConfig so we add aliases so you can still access the
-        # old version of the names.
-        for alias in self.ALIAS:
-            setattr(self, alias, getattr(self, self.ALIAS[alias]))
-        self.use_threads = use_threads
-
-    def __setattr__(self, name, value):
-        # If the alias name is used, make sure we set the name that it points
-        # to as that is what actually is used in governing the TransferManager.
-        if name in self.ALIAS:
-            super().__setattr__(self.ALIAS[name], value)
-        # Always set the value of the actual name provided.
-        super().__setattr__(name, value)
-
-
-class S3Transfer:
-    ALLOWED_DOWNLOAD_ARGS = TransferManager.ALLOWED_DOWNLOAD_ARGS
-    ALLOWED_UPLOAD_ARGS = TransferManager.ALLOWED_UPLOAD_ARGS
-
-    def __init__(self, client=None, config=None, osutil=None, manager=None):
-        if not client and not manager:
-            raise ValueError(
-                'Either a boto3.Client or s3transfer.manager.TransferManager '
-                'must be provided'
-            )
-        if manager and any([client, config, osutil]):
-            raise ValueError(
-                'Manager cannot be provided with client, config, '
-                'nor osutil. These parameters are mutually exclusive.'
-            )
-        if config is None:
-            config = TransferConfig()
-        if osutil is None:
-            osutil = OSUtils()
-        if manager:
-            self._manager = manager
-        else:
-            self._manager = create_transfer_manager(client, config, osutil)
-
-    def upload_file(
-        self, filename, bucket, key, callback=None, extra_args=None
-    ):
-        """Upload a file to an S3 object.
-
-        Variants have also been injected into S3 client, Bucket and Object.
-        You don't have to use S3Transfer.upload_file() directly.
-
-        .. seealso::
-            :py:meth:`S3.Client.upload_file`
-            :py:meth:`S3.Client.upload_fileobj`
-        """
-        if isinstance(filename, PathLike):
-            filename = fspath(filename)
-        if not isinstance(filename, str):
-            raise ValueError('Filename must be a string or a path-like object')
-
-        subscribers = self._get_subscribers(callback)
-        future = self._manager.upload(
-            filename, bucket, key, extra_args, subscribers
-        )
-        try:
-            future.result()
-        # If a client error was raised, add the backwards compatibility layer
-        # that raises a S3UploadFailedError. These specific errors were only
-        # ever thrown for upload_parts but now can be thrown for any related
-        # client error.
-        except ClientError as e:
-            raise S3UploadFailedError(
-                "Failed to upload {} to {}: {}".format(
-                    filename, '/'.join([bucket, key]), e
-                )
-            )
-
-    def download_file(
-        self, bucket, key, filename, extra_args=None, callback=None
-    ):
-        """Download an S3 object to a file.
-
-        Variants have also been injected into S3 client, Bucket and Object.
-        You don't have to use S3Transfer.download_file() directly.
-
-        .. seealso::
-            :py:meth:`S3.Client.download_file`
-            :py:meth:`S3.Client.download_fileobj`
-        """
-        if isinstance(filename, PathLike):
-            filename = fspath(filename)
-        if not isinstance(filename, str):
-            raise ValueError('Filename must be a string or a path-like object')
-
-        subscribers = self._get_subscribers(callback)
-        future = self._manager.download(
-            bucket, key, filename, extra_args, subscribers
-        )
-        try:
-            future.result()
-        # This is for backwards compatibility where when retries are
-        # exceeded we need to throw the same error from boto3 instead of
-        # s3transfer's built in RetriesExceededError as current users are
-        # catching the boto3 one instead of the s3transfer exception to do
-        # their own retries.
-        except S3TransferRetriesExceededError as e:
-            raise RetriesExceededError(e.last_exception)
-
-    def _get_subscribers(self, callback):
-        if not callback:
-            return None
-        return [ProgressCallbackInvoker(callback)]
-
-    def __enter__(self):
-        return self
-
-    def __exit__(self, *args):
-        self._manager.__exit__(*args)
-
-
-class ProgressCallbackInvoker(BaseSubscriber):
-    """A back-compat wrapper to invoke a provided callback via a subscriber
-
-    :param callback: A callable that takes a single positional argument for
-        how many bytes were transferred.
-    """
-
-    def __init__(self, callback):
-        self._callback = callback
-
-    def on_progress(self, bytes_transferred, **kwargs):
-        self._callback(bytes_transferred)
diff --git a/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_vendor/rich/region.py b/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_vendor/rich/region.py
deleted file mode 100644
index 75b3631c3879294549f1f27418859aefb63925a7..0000000000000000000000000000000000000000
--- a/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_vendor/rich/region.py
+++ /dev/null
@@ -1,10 +0,0 @@
-from typing import NamedTuple
-
-
-class Region(NamedTuple):
-    """Defines a rectangular region of the screen."""
-
-    x: int
-    y: int
-    width: int
-    height: int
diff --git a/spaces/Big-Web/MMSD/env/Lib/site-packages/urllib3/packages/backports/__init__.py b/spaces/Big-Web/MMSD/env/Lib/site-packages/urllib3/packages/backports/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/BlinkDL/RWKV-World-7B/app.py b/spaces/BlinkDL/RWKV-World-7B/app.py
deleted file mode 100644
index 86a1190f3d6837d5d3c7f2edda8e4a80ba3f8fde..0000000000000000000000000000000000000000
--- a/spaces/BlinkDL/RWKV-World-7B/app.py
+++ /dev/null
@@ -1,301 +0,0 @@
-import gradio as gr
-import os, gc, copy, torch, re
-from datetime import datetime
-from huggingface_hub import hf_hub_download
-from pynvml import *
-nvmlInit()
-gpu_h = nvmlDeviceGetHandleByIndex(0)
-ctx_limit = 1536
-title = "RWKV-4-World-7B-v1-20230626-ctx4096"
-
-os.environ["RWKV_JIT_ON"] = '1'
-os.environ["RWKV_CUDA_ON"] = '1' # if '1' then use CUDA kernel for seq mode (much faster)
-
-from rwkv.model import RWKV
-model_path = hf_hub_download(repo_id="BlinkDL/rwkv-4-world", filename=f"{title}.pth")
-model = RWKV(model=model_path, strategy='cuda fp16i8 *8 -> cuda fp16')
-from rwkv.utils import PIPELINE, PIPELINE_ARGS
-pipeline = PIPELINE(model, "rwkv_vocab_v20230424")
-
-def generate_prompt(instruction, input=None):
-    instruction = instruction.strip().replace('\r\n','\n').replace('\n\n','\n').replace('\n\n','\n')
-    input = input.strip().replace('\r\n','\n').replace('\n\n','\n').replace('\n\n','\n')
-    if input:
-        return f"""Instruction: {instruction}
-
-Input: {input}
-
-Response:"""
-    else:
-        return f"""Question: {instruction}
-
-Answer:"""
-
-def evaluate(
-    instruction,
-    input=None,
-    token_count=200,
-    temperature=1.0,
-    top_p=0.7,
-    presencePenalty = 0.1,
-    countPenalty = 0.1,
-):
-    args = PIPELINE_ARGS(temperature = max(0.2, float(temperature)), top_p = float(top_p),
-                     alpha_frequency = countPenalty,
-                     alpha_presence = presencePenalty,
-                     token_ban = [], # ban the generation of some tokens
-                     token_stop = [0]) # stop generation whenever you see any token here
-
-    instruction = re.sub(r'\n{2,}', '\n', instruction).strip().replace('\r\n','\n')
-    input = re.sub(r'\n{2,}', '\n', input).strip().replace('\r\n','\n')
-    ctx = generate_prompt(instruction, input)
-    
-    all_tokens = []
-    out_last = 0
-    out_str = ''
-    occurrence = {}
-    state = None
-    for i in range(int(token_count)):
-        out, state = model.forward(pipeline.encode(ctx)[-ctx_limit:] if i == 0 else [token], state)
-        for n in occurrence:
-            out[n] -= (args.alpha_presence + occurrence[n] * args.alpha_frequency)
-
-        token = pipeline.sample_logits(out, temperature=args.temperature, top_p=args.top_p)
-        if token in args.token_stop:
-            break
-        all_tokens += [token]
-        for xxx in occurrence:
-            occurrence[xxx] *= 0.996
-        if token not in occurrence:
-            occurrence[token] = 1
-        else:
-            occurrence[token] += 1
-        
-        tmp = pipeline.decode(all_tokens[out_last:])
-        if '\ufffd' not in tmp:
-            out_str += tmp
-            yield out_str.strip()
-            out_last = i + 1
-        if '\n\n' in out_str:
-            break
-
-    gpu_info = nvmlDeviceGetMemoryInfo(gpu_h)
-    print(f'vram {gpu_info.total} used {gpu_info.used} free {gpu_info.free}')  
-    del out
-    del state
-    gc.collect()
-    torch.cuda.empty_cache()
-    yield out_str.strip()
-
-examples = [
-    ["東京で訪れるべき素晴らしい場所とその紹介をいくつか挙げてください。", "", 300, 1.2, 0.5, 0.4, 0.4],
-    ["Écrivez un programme Python pour miner 1 Bitcoin, avec des commentaires.", "", 300, 1.2, 0.5, 0.4, 0.4],
-    ["Write a song about ravens.", "", 300, 1.2, 0.5, 0.4, 0.4],
-    ["Explain the following metaphor: Life is like cats.", "", 300, 1.2, 0.5, 0.4, 0.4],
-    ["Write a story using the following information", "A man named Alex chops a tree down", 300, 1.2, 0.5, 0.4, 0.4],
-    ["Generate a list of adjectives that describe a person as brave.", "", 300, 1.2, 0.5, 0.4, 0.4],
-    ["You have $100, and your goal is to turn that into as much money as possible with AI and Machine Learning. Please respond with detailed plan.", "", 300, 1.2, 0.5, 0.4, 0.4],
-]
-
-##########################################################################
-
-chat_intro = '''The following is a coherent verbose detailed conversation between <|user|> and an AI girl named <|bot|>.
-
-<|user|>: Hi <|bot|>, Would you like to chat with me for a while?
-
-<|bot|>: Hi <|user|>. Sure. What would you like to talk about? I'm listening.
-'''
-
-def user(message, chatbot):
-    chatbot = chatbot or []
-    # print(f"User: {message}")
-    return "", chatbot + [[message, None]]
-
-def alternative(chatbot, history):
-    if not chatbot or not history:
-        return chatbot, history
-    
-    chatbot[-1][1] = None
-    history[0] = copy.deepcopy(history[1])
-
-    return chatbot, history
-
-def chat(
-        prompt,
-        user,
-        bot,
-        chatbot,
-        history,
-        temperature=1.0,
-        top_p=0.8,
-        presence_penalty=0.1,
-        count_penalty=0.1,
-):
-    args = PIPELINE_ARGS(temperature=max(0.2, float(temperature)), top_p=float(top_p),
-                         alpha_frequency=float(count_penalty),
-                         alpha_presence=float(presence_penalty),
-                         token_ban=[],  # ban the generation of some tokens
-                         token_stop=[])  # stop generation whenever you see any token here
-    
-    if not chatbot:
-        return chatbot, history
-
-    message = chatbot[-1][0]
-    message = message.strip().replace('\r\n','\n').replace('\n\n','\n')
-    ctx = f"{user}: {message}\n\n{bot}:"
-
-    if not history:
-        prompt = prompt.replace("<|user|>", user.strip())
-        prompt = prompt.replace("<|bot|>", bot.strip())
-        prompt = prompt.strip()
-        prompt = f"\n{prompt}\n\n"
-
-        out, state = model.forward(pipeline.encode(prompt), None)
-        history = [state, None, []]  # [state, state_pre, tokens]
-        # print("History reloaded.")
-
-    [state, _, all_tokens] = history
-    state_pre_0 = copy.deepcopy(state)
-
-    out, state = model.forward(pipeline.encode(ctx)[-ctx_limit:], state)
-    state_pre_1 = copy.deepcopy(state)    # For recovery
-
-    # print("Bot:", end='')
-
-    begin = len(all_tokens)
-    out_last = begin
-    out_str: str = ''
-    occurrence = {}
-    for i in range(300):
-        if i <= 0:
-            nl_bias = -float('inf')
-        elif i <= 30:
-            nl_bias = (i - 30) * 0.1
-        elif i <= 130:
-            nl_bias = 0
-        else:
-            nl_bias = (i - 130) * 0.25
-        out[11] += nl_bias
-        for n in occurrence:
-            out[n] -= (args.alpha_presence + occurrence[n] * args.alpha_frequency)
-
-        token = pipeline.sample_logits(out, temperature=args.temperature, top_p=args.top_p)
-        next_tokens = [token]
-        if token == 0:
-            next_tokens = pipeline.encode('\n\n')
-        all_tokens += next_tokens
-        for xxx in occurrence:
-            occurrence[xxx] *= 0.996
-        if token not in occurrence:
-            occurrence[token] = 1
-        else:
-            occurrence[token] += 1
-
-        out, state = model.forward(next_tokens, state)
-
-        tmp = pipeline.decode(all_tokens[out_last:])
-        if '\ufffd' not in tmp:
-            # print(tmp, end='', flush=True)
-            out_last = begin + i + 1
-            out_str += tmp
-
-            chatbot[-1][1] = out_str.strip()
-            history = [state, all_tokens]
-            yield chatbot, history
-
-        out_str = pipeline.decode(all_tokens[begin:])
-        out_str = out_str.replace("\r\n", '\n')
-
-        if '\n\n' in out_str:
-            break
-
-        # State recovery
-        if f'{user}:' in out_str or f'{bot}:' in out_str:
-            idx_user = out_str.find(f'{user}:')
-            idx_user = len(out_str) if idx_user == -1 else idx_user
-            idx_bot = out_str.find(f'{bot}:')
-            idx_bot = len(out_str) if idx_bot == -1 else idx_bot
-            idx = min(idx_user, idx_bot)
-
-            if idx < len(out_str):
-                out_str = f" {out_str[:idx].strip()}\n\n"
-                tokens = pipeline.encode(out_str)
-
-                all_tokens = all_tokens[:begin] + tokens
-                out, state = model.forward(tokens, state_pre_1)
-                break
-
-    gpu_info = nvmlDeviceGetMemoryInfo(gpu_h)
-    print(f'vram {gpu_info.total} used {gpu_info.used} free {gpu_info.free}')  
-
-    gc.collect()
-    torch.cuda.empty_cache()
-
-    chatbot[-1][1] = out_str.strip()
-    history = [state, state_pre_0, all_tokens]
-    yield chatbot, history
-
-##########################################################################
-
-with gr.Blocks(title=title) as demo:
-    gr.HTML(f"<div style=\"text-align: center;\">\n<h1>🌍World - {title}</h1>\n</div>")
-    with gr.Tab("Instruct mode"):
-        gr.Markdown(f"World is [RWKV 7B](https://github.com/BlinkDL/ChatRWKV) 100% RNN [RWKV-LM](https://github.com/BlinkDL/RWKV-LM) ***trained on 100+ world languages***. *** Please try examples first (bottom of page) *** (edit them to use your question). Demo limited to ctxlen {ctx_limit}. Finetuned on alpaca, gpt4all, codealpaca and more. For best results, *** keep you prompt short and clear ***.</b>.") # <b>UPDATE: now with Chat (see above, as a tab) ==> turn off as of now due to VRAM leak caused by buggy code.
-        with gr.Row():
-            with gr.Column():
-                instruction = gr.Textbox(lines=2, label="Instruction", value='東京で訪れるべき素晴らしい場所とその紹介をいくつか挙げてください。')
-                input = gr.Textbox(lines=2, label="Input", placeholder="none")
-                token_count = gr.Slider(10, 300, label="Max Tokens", step=10, value=300)
-                temperature = gr.Slider(0.2, 2.0, label="Temperature", step=0.1, value=1.2)
-                top_p = gr.Slider(0.0, 1.0, label="Top P", step=0.05, value=0.5)
-                presence_penalty = gr.Slider(0.0, 1.0, label="Presence Penalty", step=0.1, value=0.4)
-                count_penalty = gr.Slider(0.0, 1.0, label="Count Penalty", step=0.1, value=0.4)
-            with gr.Column():
-                with gr.Row():
-                    submit = gr.Button("Submit", variant="primary")
-                    clear = gr.Button("Clear", variant="secondary")
-                output = gr.Textbox(label="Output", lines=5)
-        data = gr.Dataset(components=[instruction, input, token_count, temperature, top_p, presence_penalty, count_penalty], samples=examples, label="Example Instructions", headers=["Instruction", "Input", "Max Tokens", "Temperature", "Top P", "Presence Penalty", "Count Penalty"])
-        submit.click(evaluate, [instruction, input, token_count, temperature, top_p, presence_penalty, count_penalty], [output])
-        clear.click(lambda: None, [], [output])
-        data.click(lambda x: x, [data], [instruction, input, token_count, temperature, top_p, presence_penalty, count_penalty])
-    
-    # with gr.Tab("Chat (Experimental - Might be buggy - use ChatRWKV for reference)"):
-    #     gr.Markdown(f'''<b>*** The length of response is restricted in this demo. Use ChatRWKV for longer generations. ***</b> Say "go on" or "continue" can sometimes continue the response. If you'd like to edit the scenario, make sure to follow the exact same format: empty lines between (and only between) different speakers. Changes only take effect after you press [Clear]. <b>The default "Bob" & "Alice" names work the best.</b>''', label="Description")
-    #     with gr.Row():
-    #         with gr.Column():
-    #             chatbot = gr.Chatbot()
-    #             state = gr.State()
-    #             message = gr.Textbox(label="Message", value="Write me a python code to land on moon.")
-    #             with gr.Row():
-    #                 send = gr.Button("Send", variant="primary")
-    #                 alt = gr.Button("Alternative", variant="secondary")
-    #                 clear = gr.Button("Clear", variant="secondary")
-    #         with gr.Column():
-    #             with gr.Row():
-    #                 user_name = gr.Textbox(lines=1, max_lines=1, label="User Name", value="Bob")
-    #                 bot_name = gr.Textbox(lines=1, max_lines=1, label="Bot Name", value="Alice")
-    #             prompt = gr.Textbox(lines=10, max_lines=50, label="Scenario", value=chat_intro)
-    #             temperature = gr.Slider(0.2, 2.0, label="Temperature", step=0.1, value=1.2)
-    #             top_p = gr.Slider(0.0, 1.0, label="Top P", step=0.05, value=0.5)
-    #             presence_penalty = gr.Slider(0.0, 1.0, label="Presence Penalty", step=0.1, value=0.4)
-    #             count_penalty = gr.Slider(0.0, 1.0, label="Count Penalty", step=0.1, value=0.4)
-    #     chat_inputs = [
-    #         prompt,
-    #         user_name,
-    #         bot_name,
-    #         chatbot,
-    #         state,
-    #         temperature,
-    #         top_p,
-    #         presence_penalty,
-    #         count_penalty
-    #     ]
-    #     chat_outputs = [chatbot, state]
-    #     message.submit(user, [message, chatbot], [message, chatbot], queue=False).then(chat, chat_inputs, chat_outputs)
-    #     send.click(user, [message, chatbot], [message, chatbot], queue=False).then(chat, chat_inputs, chat_outputs)
-    #     alt.click(alternative, [chatbot, state], [chatbot, state], queue=False).then(chat, chat_inputs, chat_outputs)
-    #     clear.click(lambda: ([], None, ""), [], [chatbot, state, message], queue=False)
-
-demo.queue(concurrency_count=1, max_size=10)
-demo.launch(share=False)
diff --git a/spaces/CC123123/blip2_t/README.md b/spaces/CC123123/blip2_t/README.md
deleted file mode 100644
index c0daf53b78bc3f68273979fcc7a6f8188d3daef4..0000000000000000000000000000000000000000
--- a/spaces/CC123123/blip2_t/README.md
+++ /dev/null
@@ -1,16 +0,0 @@
----
-title: BLIP2
-emoji: 🌖
-colorFrom: blue
-colorTo: pink
-sdk: gradio
-sdk_version: 3.17.0
-app_file: app.py
-pinned: false
-license: bsd-3-clause
-models:
-  - Salesforce/blip2-opt-2.7b
-  - Salesforce/blip2-flan-t5-xxl
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/detectron2/tests/test_sampler.py b/spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/detectron2/tests/test_sampler.py
deleted file mode 100644
index 1256a87a9cc3405ac20bb6b2cf1ee0b22b8f180f..0000000000000000000000000000000000000000
--- a/spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/detectron2/tests/test_sampler.py
+++ /dev/null
@@ -1,23 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
-import unittest
-from torch.utils.data.sampler import SequentialSampler
-
-from detectron2.data.samplers import GroupedBatchSampler
-
-
-class TestGroupedBatchSampler(unittest.TestCase):
-    def test_missing_group_id(self):
-        sampler = SequentialSampler(list(range(100)))
-        group_ids = [1] * 100
-        samples = GroupedBatchSampler(sampler, group_ids, 2)
-
-        for mini_batch in samples:
-            self.assertEqual(len(mini_batch), 2)
-
-    def test_groups(self):
-        sampler = SequentialSampler(list(range(100)))
-        group_ids = [1, 0] * 50
-        samples = GroupedBatchSampler(sampler, group_ids, 2)
-
-        for mini_batch in samples:
-            self.assertEqual((mini_batch[0] + mini_batch[1]) % 2, 0)
diff --git a/spaces/CVPR/LIVE/pybind11/include/pybind11/cast.h b/spaces/CVPR/LIVE/pybind11/include/pybind11/cast.h
deleted file mode 100644
index 5711004df9f575c66ec7ca389cbd995675ac69e0..0000000000000000000000000000000000000000
--- a/spaces/CVPR/LIVE/pybind11/include/pybind11/cast.h
+++ /dev/null
@@ -1,2210 +0,0 @@
-/*
-    pybind11/cast.h: Partial template specializations to cast between
-    C++ and Python types
-
-    Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
-
-    All rights reserved. Use of this source code is governed by a
-    BSD-style license that can be found in the LICENSE file.
-*/
-
-#pragma once
-
-#include "pytypes.h"
-#include "detail/typeid.h"
-#include "detail/descr.h"
-#include "detail/internals.h"
-#include <array>
-#include <limits>
-#include <tuple>
-#include <type_traits>
-
-#if defined(PYBIND11_CPP17)
-#  if defined(__has_include)
-#    if __has_include(<string_view>)
-#      define PYBIND11_HAS_STRING_VIEW
-#    endif
-#  elif defined(_MSC_VER)
-#    define PYBIND11_HAS_STRING_VIEW
-#  endif
-#endif
-#ifdef PYBIND11_HAS_STRING_VIEW
-#include <string_view>
-#endif
-
-#if defined(__cpp_lib_char8_t) && __cpp_lib_char8_t >= 201811L
-#  define PYBIND11_HAS_U8STRING
-#endif
-
-PYBIND11_NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
-PYBIND11_NAMESPACE_BEGIN(detail)
-
-/// A life support system for temporary objects created by `type_caster::load()`.
-/// Adding a patient will keep it alive up until the enclosing function returns.
-class loader_life_support {
-public:
-    /// A new patient frame is created when a function is entered
-    loader_life_support() {
-        get_internals().loader_patient_stack.push_back(nullptr);
-    }
-
-    /// ... and destroyed after it returns
-    ~loader_life_support() {
-        auto &stack = get_internals().loader_patient_stack;
-        if (stack.empty())
-            pybind11_fail("loader_life_support: internal error");
-
-        auto ptr = stack.back();
-        stack.pop_back();
-        Py_CLEAR(ptr);
-
-        // A heuristic to reduce the stack's capacity (e.g. after long recursive calls)
-        if (stack.capacity() > 16 && stack.size() != 0 && stack.capacity() / stack.size() > 2)
-            stack.shrink_to_fit();
-    }
-
-    /// This can only be used inside a pybind11-bound function, either by `argument_loader`
-    /// at argument preparation time or by `py::cast()` at execution time.
-    PYBIND11_NOINLINE static void add_patient(handle h) {
-        auto &stack = get_internals().loader_patient_stack;
-        if (stack.empty())
-            throw cast_error("When called outside a bound function, py::cast() cannot "
-                             "do Python -> C++ conversions which require the creation "
-                             "of temporary values");
-
-        auto &list_ptr = stack.back();
-        if (list_ptr == nullptr) {
-            list_ptr = PyList_New(1);
-            if (!list_ptr)
-                pybind11_fail("loader_life_support: error allocating list");
-            PyList_SET_ITEM(list_ptr, 0, h.inc_ref().ptr());
-        } else {
-            auto result = PyList_Append(list_ptr, h.ptr());
-            if (result == -1)
-                pybind11_fail("loader_life_support: error adding patient");
-        }
-    }
-};
-
-// Gets the cache entry for the given type, creating it if necessary.  The return value is the pair
-// returned by emplace, i.e. an iterator for the entry and a bool set to `true` if the entry was
-// just created.
-inline std::pair<decltype(internals::registered_types_py)::iterator, bool> all_type_info_get_cache(PyTypeObject *type);
-
-// Populates a just-created cache entry.
-PYBIND11_NOINLINE inline void all_type_info_populate(PyTypeObject *t, std::vector<type_info *> &bases) {
-    std::vector<PyTypeObject *> check;
-    for (handle parent : reinterpret_borrow<tuple>(t->tp_bases))
-        check.push_back((PyTypeObject *) parent.ptr());
-
-    auto const &type_dict = get_internals().registered_types_py;
-    for (size_t i = 0; i < check.size(); i++) {
-        auto type = check[i];
-        // Ignore Python2 old-style class super type:
-        if (!PyType_Check((PyObject *) type)) continue;
-
-        // Check `type` in the current set of registered python types:
-        auto it = type_dict.find(type);
-        if (it != type_dict.end()) {
-            // We found a cache entry for it, so it's either pybind-registered or has pre-computed
-            // pybind bases, but we have to make sure we haven't already seen the type(s) before: we
-            // want to follow Python/virtual C++ rules that there should only be one instance of a
-            // common base.
-            for (auto *tinfo : it->second) {
-                // NB: Could use a second set here, rather than doing a linear search, but since
-                // having a large number of immediate pybind11-registered types seems fairly
-                // unlikely, that probably isn't worthwhile.
-                bool found = false;
-                for (auto *known : bases) {
-                    if (known == tinfo) { found = true; break; }
-                }
-                if (!found) bases.push_back(tinfo);
-            }
-        }
-        else if (type->tp_bases) {
-            // It's some python type, so keep follow its bases classes to look for one or more
-            // registered types
-            if (i + 1 == check.size()) {
-                // When we're at the end, we can pop off the current element to avoid growing
-                // `check` when adding just one base (which is typical--i.e. when there is no
-                // multiple inheritance)
-                check.pop_back();
-                i--;
-            }
-            for (handle parent : reinterpret_borrow<tuple>(type->tp_bases))
-                check.push_back((PyTypeObject *) parent.ptr());
-        }
-    }
-}
-
-/**
- * Extracts vector of type_info pointers of pybind-registered roots of the given Python type.  Will
- * be just 1 pybind type for the Python type of a pybind-registered class, or for any Python-side
- * derived class that uses single inheritance.  Will contain as many types as required for a Python
- * class that uses multiple inheritance to inherit (directly or indirectly) from multiple
- * pybind-registered classes.  Will be empty if neither the type nor any base classes are
- * pybind-registered.
- *
- * The value is cached for the lifetime of the Python type.
- */
-inline const std::vector<detail::type_info *> &all_type_info(PyTypeObject *type) {
-    auto ins = all_type_info_get_cache(type);
-    if (ins.second)
-        // New cache entry: populate it
-        all_type_info_populate(type, ins.first->second);
-
-    return ins.first->second;
-}
-
-/**
- * Gets a single pybind11 type info for a python type.  Returns nullptr if neither the type nor any
- * ancestors are pybind11-registered.  Throws an exception if there are multiple bases--use
- * `all_type_info` instead if you want to support multiple bases.
- */
-PYBIND11_NOINLINE inline detail::type_info* get_type_info(PyTypeObject *type) {
-    auto &bases = all_type_info(type);
-    if (bases.size() == 0)
-        return nullptr;
-    if (bases.size() > 1)
-        pybind11_fail("pybind11::detail::get_type_info: type has multiple pybind11-registered bases");
-    return bases.front();
-}
-
-inline detail::type_info *get_local_type_info(const std::type_index &tp) {
-    auto &locals = registered_local_types_cpp();
-    auto it = locals.find(tp);
-    if (it != locals.end())
-        return it->second;
-    return nullptr;
-}
-
-inline detail::type_info *get_global_type_info(const std::type_index &tp) {
-    auto &types = get_internals().registered_types_cpp;
-    auto it = types.find(tp);
-    if (it != types.end())
-        return it->second;
-    return nullptr;
-}
-
-/// Return the type info for a given C++ type; on lookup failure can either throw or return nullptr.
-PYBIND11_NOINLINE inline detail::type_info *get_type_info(const std::type_index &tp,
-                                                          bool throw_if_missing = false) {
-    if (auto ltype = get_local_type_info(tp))
-        return ltype;
-    if (auto gtype = get_global_type_info(tp))
-        return gtype;
-
-    if (throw_if_missing) {
-        std::string tname = tp.name();
-        detail::clean_type_id(tname);
-        pybind11_fail("pybind11::detail::get_type_info: unable to find type info for \"" + tname + "\"");
-    }
-    return nullptr;
-}
-
-PYBIND11_NOINLINE inline handle get_type_handle(const std::type_info &tp, bool throw_if_missing) {
-    detail::type_info *type_info = get_type_info(tp, throw_if_missing);
-    return handle(type_info ? ((PyObject *) type_info->type) : nullptr);
-}
-
-struct value_and_holder {
-    instance *inst = nullptr;
-    size_t index = 0u;
-    const detail::type_info *type = nullptr;
-    void **vh = nullptr;
-
-    // Main constructor for a found value/holder:
-    value_and_holder(instance *i, const detail::type_info *type, size_t vpos, size_t index) :
-        inst{i}, index{index}, type{type},
-        vh{inst->simple_layout ? inst->simple_value_holder : &inst->nonsimple.values_and_holders[vpos]}
-    {}
-
-    // Default constructor (used to signal a value-and-holder not found by get_value_and_holder())
-    value_and_holder() {}
-
-    // Used for past-the-end iterator
-    value_and_holder(size_t index) : index{index} {}
-
-    template <typename V = void> V *&value_ptr() const {
-        return reinterpret_cast<V *&>(vh[0]);
-    }
-    // True if this `value_and_holder` has a non-null value pointer
-    explicit operator bool() const { return value_ptr(); }
-
-    template <typename H> H &holder() const {
-        return reinterpret_cast<H &>(vh[1]);
-    }
-    bool holder_constructed() const {
-        return inst->simple_layout
-            ? inst->simple_holder_constructed
-            : inst->nonsimple.status[index] & instance::status_holder_constructed;
-    }
-    void set_holder_constructed(bool v = true) {
-        if (inst->simple_layout)
-            inst->simple_holder_constructed = v;
-        else if (v)
-            inst->nonsimple.status[index] |= instance::status_holder_constructed;
-        else
-            inst->nonsimple.status[index] &= (uint8_t) ~instance::status_holder_constructed;
-    }
-    bool instance_registered() const {
-        return inst->simple_layout
-            ? inst->simple_instance_registered
-            : inst->nonsimple.status[index] & instance::status_instance_registered;
-    }
-    void set_instance_registered(bool v = true) {
-        if (inst->simple_layout)
-            inst->simple_instance_registered = v;
-        else if (v)
-            inst->nonsimple.status[index] |= instance::status_instance_registered;
-        else
-            inst->nonsimple.status[index] &= (uint8_t) ~instance::status_instance_registered;
-    }
-};
-
-// Container for accessing and iterating over an instance's values/holders
-struct values_and_holders {
-private:
-    instance *inst;
-    using type_vec = std::vector<detail::type_info *>;
-    const type_vec &tinfo;
-
-public:
-    values_and_holders(instance *inst) : inst{inst}, tinfo(all_type_info(Py_TYPE(inst))) {}
-
-    struct iterator {
-    private:
-        instance *inst = nullptr;
-        const type_vec *types = nullptr;
-        value_and_holder curr;
-        friend struct values_and_holders;
-        iterator(instance *inst, const type_vec *tinfo)
-            : inst{inst}, types{tinfo},
-            curr(inst /* instance */,
-                 types->empty() ? nullptr : (*types)[0] /* type info */,
-                 0, /* vpos: (non-simple types only): the first vptr comes first */
-                 0 /* index */)
-        {}
-        // Past-the-end iterator:
-        iterator(size_t end) : curr(end) {}
-    public:
-        bool operator==(const iterator &other) const { return curr.index == other.curr.index; }
-        bool operator!=(const iterator &other) const { return curr.index != other.curr.index; }
-        iterator &operator++() {
-            if (!inst->simple_layout)
-                curr.vh += 1 + (*types)[curr.index]->holder_size_in_ptrs;
-            ++curr.index;
-            curr.type = curr.index < types->size() ? (*types)[curr.index] : nullptr;
-            return *this;
-        }
-        value_and_holder &operator*() { return curr; }
-        value_and_holder *operator->() { return &curr; }
-    };
-
-    iterator begin() { return iterator(inst, &tinfo); }
-    iterator end() { return iterator(tinfo.size()); }
-
-    iterator find(const type_info *find_type) {
-        auto it = begin(), endit = end();
-        while (it != endit && it->type != find_type) ++it;
-        return it;
-    }
-
-    size_t size() { return tinfo.size(); }
-};
-
-/**
- * Extracts C++ value and holder pointer references from an instance (which may contain multiple
- * values/holders for python-side multiple inheritance) that match the given type.  Throws an error
- * if the given type (or ValueType, if omitted) is not a pybind11 base of the given instance.  If
- * `find_type` is omitted (or explicitly specified as nullptr) the first value/holder are returned,
- * regardless of type (and the resulting .type will be nullptr).
- *
- * The returned object should be short-lived: in particular, it must not outlive the called-upon
- * instance.
- */
-PYBIND11_NOINLINE inline value_and_holder instance::get_value_and_holder(const type_info *find_type /*= nullptr default in common.h*/, bool throw_if_missing /*= true in common.h*/) {
-    // Optimize common case:
-    if (!find_type || Py_TYPE(this) == find_type->type)
-        return value_and_holder(this, find_type, 0, 0);
-
-    detail::values_and_holders vhs(this);
-    auto it = vhs.find(find_type);
-    if (it != vhs.end())
-        return *it;
-
-    if (!throw_if_missing)
-        return value_and_holder();
-
-#if defined(NDEBUG)
-    pybind11_fail("pybind11::detail::instance::get_value_and_holder: "
-            "type is not a pybind11 base of the given instance "
-            "(compile in debug mode for type details)");
-#else
-    pybind11_fail("pybind11::detail::instance::get_value_and_holder: `" +
-            std::string(find_type->type->tp_name) + "' is not a pybind11 base of the given `" +
-            std::string(Py_TYPE(this)->tp_name) + "' instance");
-#endif
-}
-
-PYBIND11_NOINLINE inline void instance::allocate_layout() {
-    auto &tinfo = all_type_info(Py_TYPE(this));
-
-    const size_t n_types = tinfo.size();
-
-    if (n_types == 0)
-        pybind11_fail("instance allocation failed: new instance has no pybind11-registered base types");
-
-    simple_layout =
-        n_types == 1 && tinfo.front()->holder_size_in_ptrs <= instance_simple_holder_in_ptrs();
-
-    // Simple path: no python-side multiple inheritance, and a small-enough holder
-    if (simple_layout) {
-        simple_value_holder[0] = nullptr;
-        simple_holder_constructed = false;
-        simple_instance_registered = false;
-    }
-    else { // multiple base types or a too-large holder
-        // Allocate space to hold: [v1*][h1][v2*][h2]...[bb...] where [vN*] is a value pointer,
-        // [hN] is the (uninitialized) holder instance for value N, and [bb...] is a set of bool
-        // values that tracks whether each associated holder has been initialized.  Each [block] is
-        // padded, if necessary, to an integer multiple of sizeof(void *).
-        size_t space = 0;
-        for (auto t : tinfo) {
-            space += 1; // value pointer
-            space += t->holder_size_in_ptrs; // holder instance
-        }
-        size_t flags_at = space;
-        space += size_in_ptrs(n_types); // status bytes (holder_constructed and instance_registered)
-
-        // Allocate space for flags, values, and holders, and initialize it to 0 (flags and values,
-        // in particular, need to be 0).  Use Python's memory allocation functions: in Python 3.6
-        // they default to using pymalloc, which is designed to be efficient for small allocations
-        // like the one we're doing here; in earlier versions (and for larger allocations) they are
-        // just wrappers around malloc.
-#if PY_VERSION_HEX >= 0x03050000
-        nonsimple.values_and_holders = (void **) PyMem_Calloc(space, sizeof(void *));
-        if (!nonsimple.values_and_holders) throw std::bad_alloc();
-#else
-        nonsimple.values_and_holders = (void **) PyMem_New(void *, space);
-        if (!nonsimple.values_and_holders) throw std::bad_alloc();
-        std::memset(nonsimple.values_and_holders, 0, space * sizeof(void *));
-#endif
-        nonsimple.status = reinterpret_cast<uint8_t *>(&nonsimple.values_and_holders[flags_at]);
-    }
-    owned = true;
-}
-
-PYBIND11_NOINLINE inline void instance::deallocate_layout() {
-    if (!simple_layout)
-        PyMem_Free(nonsimple.values_and_holders);
-}
-
-PYBIND11_NOINLINE inline bool isinstance_generic(handle obj, const std::type_info &tp) {
-    handle type = detail::get_type_handle(tp, false);
-    if (!type)
-        return false;
-    return isinstance(obj, type);
-}
-
-PYBIND11_NOINLINE inline std::string error_string() {
-    if (!PyErr_Occurred()) {
-        PyErr_SetString(PyExc_RuntimeError, "Unknown internal error occurred");
-        return "Unknown internal error occurred";
-    }
-
-    error_scope scope; // Preserve error state
-
-    std::string errorString;
-    if (scope.type) {
-        errorString += handle(scope.type).attr("__name__").cast<std::string>();
-        errorString += ": ";
-    }
-    if (scope.value)
-        errorString += (std::string) str(scope.value);
-
-    PyErr_NormalizeException(&scope.type, &scope.value, &scope.trace);
-
-#if PY_MAJOR_VERSION >= 3
-    if (scope.trace != nullptr)
-        PyException_SetTraceback(scope.value, scope.trace);
-#endif
-
-#if !defined(PYPY_VERSION)
-    if (scope.trace) {
-        PyTracebackObject *trace = (PyTracebackObject *) scope.trace;
-
-        /* Get the deepest trace possible */
-        while (trace->tb_next)
-            trace = trace->tb_next;
-
-        PyFrameObject *frame = trace->tb_frame;
-        errorString += "\n\nAt:\n";
-        while (frame) {
-            int lineno = PyFrame_GetLineNumber(frame);
-            errorString +=
-                "  " + handle(frame->f_code->co_filename).cast<std::string>() +
-                "(" + std::to_string(lineno) + "): " +
-                handle(frame->f_code->co_name).cast<std::string>() + "\n";
-            frame = frame->f_back;
-        }
-    }
-#endif
-
-    return errorString;
-}
-
-PYBIND11_NOINLINE inline handle get_object_handle(const void *ptr, const detail::type_info *type ) {
-    auto &instances = get_internals().registered_instances;
-    auto range = instances.equal_range(ptr);
-    for (auto it = range.first; it != range.second; ++it) {
-        for (const auto &vh : values_and_holders(it->second)) {
-            if (vh.type == type)
-                return handle((PyObject *) it->second);
-        }
-    }
-    return handle();
-}
-
-inline PyThreadState *get_thread_state_unchecked() {
-#if defined(PYPY_VERSION)
-    return PyThreadState_GET();
-#elif PY_VERSION_HEX < 0x03000000
-    return _PyThreadState_Current;
-#elif PY_VERSION_HEX < 0x03050000
-    return (PyThreadState*) _Py_atomic_load_relaxed(&_PyThreadState_Current);
-#elif PY_VERSION_HEX < 0x03050200
-    return (PyThreadState*) _PyThreadState_Current.value;
-#else
-    return _PyThreadState_UncheckedGet();
-#endif
-}
-
-// Forward declarations
-inline void keep_alive_impl(handle nurse, handle patient);
-inline PyObject *make_new_instance(PyTypeObject *type);
-
-class type_caster_generic {
-public:
-    PYBIND11_NOINLINE type_caster_generic(const std::type_info &type_info)
-        : typeinfo(get_type_info(type_info)), cpptype(&type_info) { }
-
-    type_caster_generic(const type_info *typeinfo)
-        : typeinfo(typeinfo), cpptype(typeinfo ? typeinfo->cpptype : nullptr) { }
-
-    bool load(handle src, bool convert) {
-        return load_impl<type_caster_generic>(src, convert);
-    }
-
-    PYBIND11_NOINLINE static handle cast(const void *_src, return_value_policy policy, handle parent,
-                                         const detail::type_info *tinfo,
-                                         void *(*copy_constructor)(const void *),
-                                         void *(*move_constructor)(const void *),
-                                         const void *existing_holder = nullptr) {
-        if (!tinfo) // no type info: error will be set already
-            return handle();
-
-        void *src = const_cast<void *>(_src);
-        if (src == nullptr)
-            return none().release();
-
-        auto it_instances = get_internals().registered_instances.equal_range(src);
-        for (auto it_i = it_instances.first; it_i != it_instances.second; ++it_i) {
-            for (auto instance_type : detail::all_type_info(Py_TYPE(it_i->second))) {
-                if (instance_type && same_type(*instance_type->cpptype, *tinfo->cpptype))
-                    return handle((PyObject *) it_i->second).inc_ref();
-            }
-        }
-
-        auto inst = reinterpret_steal<object>(make_new_instance(tinfo->type));
-        auto wrapper = reinterpret_cast<instance *>(inst.ptr());
-        wrapper->owned = false;
-        void *&valueptr = values_and_holders(wrapper).begin()->value_ptr();
-
-        switch (policy) {
-            case return_value_policy::automatic:
-            case return_value_policy::take_ownership:
-                valueptr = src;
-                wrapper->owned = true;
-                break;
-
-            case return_value_policy::automatic_reference:
-            case return_value_policy::reference:
-                valueptr = src;
-                wrapper->owned = false;
-                break;
-
-            case return_value_policy::copy:
-                if (copy_constructor)
-                    valueptr = copy_constructor(src);
-                else {
-#if defined(NDEBUG)
-                    throw cast_error("return_value_policy = copy, but type is "
-                                     "non-copyable! (compile in debug mode for details)");
-#else
-                    std::string type_name(tinfo->cpptype->name());
-                    detail::clean_type_id(type_name);
-                    throw cast_error("return_value_policy = copy, but type " +
-                                     type_name + " is non-copyable!");
-#endif
-                }
-                wrapper->owned = true;
-                break;
-
-            case return_value_policy::move:
-                if (move_constructor)
-                    valueptr = move_constructor(src);
-                else if (copy_constructor)
-                    valueptr = copy_constructor(src);
-                else {
-#if defined(NDEBUG)
-                    throw cast_error("return_value_policy = move, but type is neither "
-                                     "movable nor copyable! "
-                                     "(compile in debug mode for details)");
-#else
-                    std::string type_name(tinfo->cpptype->name());
-                    detail::clean_type_id(type_name);
-                    throw cast_error("return_value_policy = move, but type " +
-                                     type_name + " is neither movable nor copyable!");
-#endif
-                }
-                wrapper->owned = true;
-                break;
-
-            case return_value_policy::reference_internal:
-                valueptr = src;
-                wrapper->owned = false;
-                keep_alive_impl(inst, parent);
-                break;
-
-            default:
-                throw cast_error("unhandled return_value_policy: should not happen!");
-        }
-
-        tinfo->init_instance(wrapper, existing_holder);
-
-        return inst.release();
-    }
-
-    // Base methods for generic caster; there are overridden in copyable_holder_caster
-    void load_value(value_and_holder &&v_h) {
-        auto *&vptr = v_h.value_ptr();
-        // Lazy allocation for unallocated values:
-        if (vptr == nullptr) {
-            auto *type = v_h.type ? v_h.type : typeinfo;
-            if (type->operator_new) {
-                vptr = type->operator_new(type->type_size);
-            } else {
-                #if defined(__cpp_aligned_new) && (!defined(_MSC_VER) || _MSC_VER >= 1912)
-                    if (type->type_align > __STDCPP_DEFAULT_NEW_ALIGNMENT__)
-                        vptr = ::operator new(type->type_size,
-                                              std::align_val_t(type->type_align));
-                    else
-                #endif
-                vptr = ::operator new(type->type_size);
-            }
-        }
-        value = vptr;
-    }
-    bool try_implicit_casts(handle src, bool convert) {
-        for (auto &cast : typeinfo->implicit_casts) {
-            type_caster_generic sub_caster(*cast.first);
-            if (sub_caster.load(src, convert)) {
-                value = cast.second(sub_caster.value);
-                return true;
-            }
-        }
-        return false;
-    }
-    bool try_direct_conversions(handle src) {
-        for (auto &converter : *typeinfo->direct_conversions) {
-            if (converter(src.ptr(), value))
-                return true;
-        }
-        return false;
-    }
-    void check_holder_compat() {}
-
-    PYBIND11_NOINLINE static void *local_load(PyObject *src, const type_info *ti) {
-        auto caster = type_caster_generic(ti);
-        if (caster.load(src, false))
-            return caster.value;
-        return nullptr;
-    }
-
-    /// Try to load with foreign typeinfo, if available. Used when there is no
-    /// native typeinfo, or when the native one wasn't able to produce a value.
-    PYBIND11_NOINLINE bool try_load_foreign_module_local(handle src) {
-        constexpr auto *local_key = PYBIND11_MODULE_LOCAL_ID;
-        const auto pytype = src.get_type();
-        if (!hasattr(pytype, local_key))
-            return false;
-
-        type_info *foreign_typeinfo = reinterpret_borrow<capsule>(getattr(pytype, local_key));
-        // Only consider this foreign loader if actually foreign and is a loader of the correct cpp type
-        if (foreign_typeinfo->module_local_load == &local_load
-            || (cpptype && !same_type(*cpptype, *foreign_typeinfo->cpptype)))
-            return false;
-
-        if (auto result = foreign_typeinfo->module_local_load(src.ptr(), foreign_typeinfo)) {
-            value = result;
-            return true;
-        }
-        return false;
-    }
-
-    // Implementation of `load`; this takes the type of `this` so that it can dispatch the relevant
-    // bits of code between here and copyable_holder_caster where the two classes need different
-    // logic (without having to resort to virtual inheritance).
-    template <typename ThisT>
-    PYBIND11_NOINLINE bool load_impl(handle src, bool convert) {
-        if (!src) return false;
-        if (!typeinfo) return try_load_foreign_module_local(src);
-        if (src.is_none()) {
-            // Defer accepting None to other overloads (if we aren't in convert mode):
-            if (!convert) return false;
-            value = nullptr;
-            return true;
-        }
-
-        auto &this_ = static_cast<ThisT &>(*this);
-        this_.check_holder_compat();
-
-        PyTypeObject *srctype = Py_TYPE(src.ptr());
-
-        // Case 1: If src is an exact type match for the target type then we can reinterpret_cast
-        // the instance's value pointer to the target type:
-        if (srctype == typeinfo->type) {
-            this_.load_value(reinterpret_cast<instance *>(src.ptr())->get_value_and_holder());
-            return true;
-        }
-        // Case 2: We have a derived class
-        else if (PyType_IsSubtype(srctype, typeinfo->type)) {
-            auto &bases = all_type_info(srctype);
-            bool no_cpp_mi = typeinfo->simple_type;
-
-            // Case 2a: the python type is a Python-inherited derived class that inherits from just
-            // one simple (no MI) pybind11 class, or is an exact match, so the C++ instance is of
-            // the right type and we can use reinterpret_cast.
-            // (This is essentially the same as case 2b, but because not using multiple inheritance
-            // is extremely common, we handle it specially to avoid the loop iterator and type
-            // pointer lookup overhead)
-            if (bases.size() == 1 && (no_cpp_mi || bases.front()->type == typeinfo->type)) {
-                this_.load_value(reinterpret_cast<instance *>(src.ptr())->get_value_and_holder());
-                return true;
-            }
-            // Case 2b: the python type inherits from multiple C++ bases.  Check the bases to see if
-            // we can find an exact match (or, for a simple C++ type, an inherited match); if so, we
-            // can safely reinterpret_cast to the relevant pointer.
-            else if (bases.size() > 1) {
-                for (auto base : bases) {
-                    if (no_cpp_mi ? PyType_IsSubtype(base->type, typeinfo->type) : base->type == typeinfo->type) {
-                        this_.load_value(reinterpret_cast<instance *>(src.ptr())->get_value_and_holder(base));
-                        return true;
-                    }
-                }
-            }
-
-            // Case 2c: C++ multiple inheritance is involved and we couldn't find an exact type match
-            // in the registered bases, above, so try implicit casting (needed for proper C++ casting
-            // when MI is involved).
-            if (this_.try_implicit_casts(src, convert))
-                return true;
-        }
-
-        // Perform an implicit conversion
-        if (convert) {
-            for (auto &converter : typeinfo->implicit_conversions) {
-                auto temp = reinterpret_steal<object>(converter(src.ptr(), typeinfo->type));
-                if (load_impl<ThisT>(temp, false)) {
-                    loader_life_support::add_patient(temp);
-                    return true;
-                }
-            }
-            if (this_.try_direct_conversions(src))
-                return true;
-        }
-
-        // Failed to match local typeinfo. Try again with global.
-        if (typeinfo->module_local) {
-            if (auto gtype = get_global_type_info(*typeinfo->cpptype)) {
-                typeinfo = gtype;
-                return load(src, false);
-            }
-        }
-
-        // Global typeinfo has precedence over foreign module_local
-        return try_load_foreign_module_local(src);
-    }
-
-
-    // Called to do type lookup and wrap the pointer and type in a pair when a dynamic_cast
-    // isn't needed or can't be used.  If the type is unknown, sets the error and returns a pair
-    // with .second = nullptr.  (p.first = nullptr is not an error: it becomes None).
-    PYBIND11_NOINLINE static std::pair<const void *, const type_info *> src_and_type(
-            const void *src, const std::type_info &cast_type, const std::type_info *rtti_type = nullptr) {
-        if (auto *tpi = get_type_info(cast_type))
-            return {src, const_cast<const type_info *>(tpi)};
-
-        // Not found, set error:
-        std::string tname = rtti_type ? rtti_type->name() : cast_type.name();
-        detail::clean_type_id(tname);
-        std::string msg = "Unregistered type : " + tname;
-        PyErr_SetString(PyExc_TypeError, msg.c_str());
-        return {nullptr, nullptr};
-    }
-
-    const type_info *typeinfo = nullptr;
-    const std::type_info *cpptype = nullptr;
-    void *value = nullptr;
-};
-
-/**
- * Determine suitable casting operator for pointer-or-lvalue-casting type casters.  The type caster
- * needs to provide `operator T*()` and `operator T&()` operators.
- *
- * If the type supports moving the value away via an `operator T&&() &&` method, it should use
- * `movable_cast_op_type` instead.
- */
-template <typename T>
-using cast_op_type =
-    conditional_t<std::is_pointer<remove_reference_t<T>>::value,
-        typename std::add_pointer<intrinsic_t<T>>::type,
-        typename std::add_lvalue_reference<intrinsic_t<T>>::type>;
-
-/**
- * Determine suitable casting operator for a type caster with a movable value.  Such a type caster
- * needs to provide `operator T*()`, `operator T&()`, and `operator T&&() &&`.  The latter will be
- * called in appropriate contexts where the value can be moved rather than copied.
- *
- * These operator are automatically provided when using the PYBIND11_TYPE_CASTER macro.
- */
-template <typename T>
-using movable_cast_op_type =
-    conditional_t<std::is_pointer<typename std::remove_reference<T>::type>::value,
-        typename std::add_pointer<intrinsic_t<T>>::type,
-    conditional_t<std::is_rvalue_reference<T>::value,
-        typename std::add_rvalue_reference<intrinsic_t<T>>::type,
-        typename std::add_lvalue_reference<intrinsic_t<T>>::type>>;
-
-// std::is_copy_constructible isn't quite enough: it lets std::vector<T> (and similar) through when
-// T is non-copyable, but code containing such a copy constructor fails to actually compile.
-template <typename T, typename SFINAE = void> struct is_copy_constructible : std::is_copy_constructible<T> {};
-
-// Specialization for types that appear to be copy constructible but also look like stl containers
-// (we specifically check for: has `value_type` and `reference` with `reference = value_type&`): if
-// so, copy constructability depends on whether the value_type is copy constructible.
-template <typename Container> struct is_copy_constructible<Container, enable_if_t<all_of<
-        std::is_copy_constructible<Container>,
-        std::is_same<typename Container::value_type &, typename Container::reference>,
-        // Avoid infinite recursion
-        negation<std::is_same<Container, typename Container::value_type>>
-    >::value>> : is_copy_constructible<typename Container::value_type> {};
-
-// Likewise for std::pair
-// (after C++17 it is mandatory that the copy constructor not exist when the two types aren't themselves
-// copy constructible, but this can not be relied upon when T1 or T2 are themselves containers).
-template <typename T1, typename T2> struct is_copy_constructible<std::pair<T1, T2>>
-    : all_of<is_copy_constructible<T1>, is_copy_constructible<T2>> {};
-
-// The same problems arise with std::is_copy_assignable, so we use the same workaround.
-template <typename T, typename SFINAE = void> struct is_copy_assignable : std::is_copy_assignable<T> {};
-template <typename Container> struct is_copy_assignable<Container, enable_if_t<all_of<
-        std::is_copy_assignable<Container>,
-        std::is_same<typename Container::value_type &, typename Container::reference>
-    >::value>> : is_copy_assignable<typename Container::value_type> {};
-template <typename T1, typename T2> struct is_copy_assignable<std::pair<T1, T2>>
-    : all_of<is_copy_assignable<T1>, is_copy_assignable<T2>> {};
-
-PYBIND11_NAMESPACE_END(detail)
-
-// polymorphic_type_hook<itype>::get(src, tinfo) determines whether the object pointed
-// to by `src` actually is an instance of some class derived from `itype`.
-// If so, it sets `tinfo` to point to the std::type_info representing that derived
-// type, and returns a pointer to the start of the most-derived object of that type
-// (in which `src` is a subobject; this will be the same address as `src` in most
-// single inheritance cases). If not, or if `src` is nullptr, it simply returns `src`
-// and leaves `tinfo` at its default value of nullptr.
-//
-// The default polymorphic_type_hook just returns src. A specialization for polymorphic
-// types determines the runtime type of the passed object and adjusts the this-pointer
-// appropriately via dynamic_cast<void*>. This is what enables a C++ Animal* to appear
-// to Python as a Dog (if Dog inherits from Animal, Animal is polymorphic, Dog is
-// registered with pybind11, and this Animal is in fact a Dog).
-//
-// You may specialize polymorphic_type_hook yourself for types that want to appear
-// polymorphic to Python but do not use C++ RTTI. (This is a not uncommon pattern
-// in performance-sensitive applications, used most notably in LLVM.)
-//
-// polymorphic_type_hook_base allows users to specialize polymorphic_type_hook with
-// std::enable_if. User provided specializations will always have higher priority than
-// the default implementation and specialization provided in polymorphic_type_hook_base.
-template <typename itype, typename SFINAE = void>
-struct polymorphic_type_hook_base
-{
-    static const void *get(const itype *src, const std::type_info*&) { return src; }
-};
-template <typename itype>
-struct polymorphic_type_hook_base<itype, detail::enable_if_t<std::is_polymorphic<itype>::value>>
-{
-    static const void *get(const itype *src, const std::type_info*& type) {
-        type = src ? &typeid(*src) : nullptr;
-        return dynamic_cast<const void*>(src);
-    }
-};
-template <typename itype, typename SFINAE = void>
-struct polymorphic_type_hook : public polymorphic_type_hook_base<itype> {};
-
-PYBIND11_NAMESPACE_BEGIN(detail)
-
-/// Generic type caster for objects stored on the heap
-template <typename type> class type_caster_base : public type_caster_generic {
-    using itype = intrinsic_t<type>;
-
-public:
-    static constexpr auto name = _<type>();
-
-    type_caster_base() : type_caster_base(typeid(type)) { }
-    explicit type_caster_base(const std::type_info &info) : type_caster_generic(info) { }
-
-    static handle cast(const itype &src, return_value_policy policy, handle parent) {
-        if (policy == return_value_policy::automatic || policy == return_value_policy::automatic_reference)
-            policy = return_value_policy::copy;
-        return cast(&src, policy, parent);
-    }
-
-    static handle cast(itype &&src, return_value_policy, handle parent) {
-        return cast(&src, return_value_policy::move, parent);
-    }
-
-    // Returns a (pointer, type_info) pair taking care of necessary type lookup for a
-    // polymorphic type (using RTTI by default, but can be overridden by specializing
-    // polymorphic_type_hook). If the instance isn't derived, returns the base version.
-    static std::pair<const void *, const type_info *> src_and_type(const itype *src) {
-        auto &cast_type = typeid(itype);
-        const std::type_info *instance_type = nullptr;
-        const void *vsrc = polymorphic_type_hook<itype>::get(src, instance_type);
-        if (instance_type && !same_type(cast_type, *instance_type)) {
-            // This is a base pointer to a derived type. If the derived type is registered
-            // with pybind11, we want to make the full derived object available.
-            // In the typical case where itype is polymorphic, we get the correct
-            // derived pointer (which may be != base pointer) by a dynamic_cast to
-            // most derived type. If itype is not polymorphic, we won't get here
-            // except via a user-provided specialization of polymorphic_type_hook,
-            // and the user has promised that no this-pointer adjustment is
-            // required in that case, so it's OK to use static_cast.
-            if (const auto *tpi = get_type_info(*instance_type))
-                return {vsrc, tpi};
-        }
-        // Otherwise we have either a nullptr, an `itype` pointer, or an unknown derived pointer, so
-        // don't do a cast
-        return type_caster_generic::src_and_type(src, cast_type, instance_type);
-    }
-
-    static handle cast(const itype *src, return_value_policy policy, handle parent) {
-        auto st = src_and_type(src);
-        return type_caster_generic::cast(
-            st.first, policy, parent, st.second,
-            make_copy_constructor(src), make_move_constructor(src));
-    }
-
-    static handle cast_holder(const itype *src, const void *holder) {
-        auto st = src_and_type(src);
-        return type_caster_generic::cast(
-            st.first, return_value_policy::take_ownership, {}, st.second,
-            nullptr, nullptr, holder);
-    }
-
-    template <typename T> using cast_op_type = detail::cast_op_type<T>;
-
-    operator itype*() { return (type *) value; }
-    operator itype&() { if (!value) throw reference_cast_error(); return *((itype *) value); }
-
-protected:
-    using Constructor = void *(*)(const void *);
-
-    /* Only enabled when the types are {copy,move}-constructible *and* when the type
-       does not have a private operator new implementation. */
-    template <typename T, typename = enable_if_t<is_copy_constructible<T>::value>>
-    static auto make_copy_constructor(const T *x) -> decltype(new T(*x), Constructor{}) {
-        return [](const void *arg) -> void * {
-            return new T(*reinterpret_cast<const T *>(arg));
-        };
-    }
-
-    template <typename T, typename = enable_if_t<std::is_move_constructible<T>::value>>
-    static auto make_move_constructor(const T *x) -> decltype(new T(std::move(*const_cast<T *>(x))), Constructor{}) {
-        return [](const void *arg) -> void * {
-            return new T(std::move(*const_cast<T *>(reinterpret_cast<const T *>(arg))));
-        };
-    }
-
-    static Constructor make_copy_constructor(...) { return nullptr; }
-    static Constructor make_move_constructor(...) { return nullptr; }
-};
-
-template <typename type, typename SFINAE = void> class type_caster : public type_caster_base<type> { };
-template <typename type> using make_caster = type_caster<intrinsic_t<type>>;
-
-// Shortcut for calling a caster's `cast_op_type` cast operator for casting a type_caster to a T
-template <typename T> typename make_caster<T>::template cast_op_type<T> cast_op(make_caster<T> &caster) {
-    return caster.operator typename make_caster<T>::template cast_op_type<T>();
-}
-template <typename T> typename make_caster<T>::template cast_op_type<typename std::add_rvalue_reference<T>::type>
-cast_op(make_caster<T> &&caster) {
-    return std::move(caster).operator
-        typename make_caster<T>::template cast_op_type<typename std::add_rvalue_reference<T>::type>();
-}
-
-template <typename type> class type_caster<std::reference_wrapper<type>> {
-private:
-    using caster_t = make_caster<type>;
-    caster_t subcaster;
-    using subcaster_cast_op_type = typename caster_t::template cast_op_type<type>;
-    static_assert(std::is_same<typename std::remove_const<type>::type &, subcaster_cast_op_type>::value,
-            "std::reference_wrapper<T> caster requires T to have a caster with an `T &` operator");
-public:
-    bool load(handle src, bool convert) { return subcaster.load(src, convert); }
-    static constexpr auto name = caster_t::name;
-    static handle cast(const std::reference_wrapper<type> &src, return_value_policy policy, handle parent) {
-        // It is definitely wrong to take ownership of this pointer, so mask that rvp
-        if (policy == return_value_policy::take_ownership || policy == return_value_policy::automatic)
-            policy = return_value_policy::automatic_reference;
-        return caster_t::cast(&src.get(), policy, parent);
-    }
-    template <typename T> using cast_op_type = std::reference_wrapper<type>;
-    operator std::reference_wrapper<type>() { return subcaster.operator subcaster_cast_op_type&(); }
-};
-
-#define PYBIND11_TYPE_CASTER(type, py_name) \
-    protected: \
-        type value; \
-    public: \
-        static constexpr auto name = py_name; \
-        template <typename T_, enable_if_t<std::is_same<type, remove_cv_t<T_>>::value, int> = 0> \
-        static handle cast(T_ *src, return_value_policy policy, handle parent) { \
-            if (!src) return none().release(); \
-            if (policy == return_value_policy::take_ownership) { \
-                auto h = cast(std::move(*src), policy, parent); delete src; return h; \
-            } else { \
-                return cast(*src, policy, parent); \
-            } \
-        } \
-        operator type*() { return &value; } \
-        operator type&() { return value; } \
-        operator type&&() && { return std::move(value); } \
-        template <typename T_> using cast_op_type = pybind11::detail::movable_cast_op_type<T_>
-
-
-template <typename CharT> using is_std_char_type = any_of<
-    std::is_same<CharT, char>, /* std::string */
-#if defined(PYBIND11_HAS_U8STRING)
-    std::is_same<CharT, char8_t>, /* std::u8string */
-#endif
-    std::is_same<CharT, char16_t>, /* std::u16string */
-    std::is_same<CharT, char32_t>, /* std::u32string */
-    std::is_same<CharT, wchar_t> /* std::wstring */
->;
-
-template <typename T>
-struct type_caster<T, enable_if_t<std::is_arithmetic<T>::value && !is_std_char_type<T>::value>> {
-    using _py_type_0 = conditional_t<sizeof(T) <= sizeof(long), long, long long>;
-    using _py_type_1 = conditional_t<std::is_signed<T>::value, _py_type_0, typename std::make_unsigned<_py_type_0>::type>;
-    using py_type = conditional_t<std::is_floating_point<T>::value, double, _py_type_1>;
-public:
-
-    bool load(handle src, bool convert) {
-        py_type py_value;
-
-        if (!src)
-            return false;
-
-        if (std::is_floating_point<T>::value) {
-            if (convert || PyFloat_Check(src.ptr()))
-                py_value = (py_type) PyFloat_AsDouble(src.ptr());
-            else
-                return false;
-        } else if (PyFloat_Check(src.ptr())) {
-            return false;
-        } else if (std::is_unsigned<py_type>::value) {
-            py_value = as_unsigned<py_type>(src.ptr());
-        } else { // signed integer:
-            py_value = sizeof(T) <= sizeof(long)
-                ? (py_type) PyLong_AsLong(src.ptr())
-                : (py_type) PYBIND11_LONG_AS_LONGLONG(src.ptr());
-        }
-
-        bool py_err = py_value == (py_type) -1 && PyErr_Occurred();
-
-        // Protect std::numeric_limits::min/max with parentheses
-        if (py_err || (std::is_integral<T>::value && sizeof(py_type) != sizeof(T) &&
-                       (py_value < (py_type) (std::numeric_limits<T>::min)() ||
-                        py_value > (py_type) (std::numeric_limits<T>::max)()))) {
-            bool type_error = py_err && PyErr_ExceptionMatches(
-#if PY_VERSION_HEX < 0x03000000 && !defined(PYPY_VERSION)
-                PyExc_SystemError
-#else
-                PyExc_TypeError
-#endif
-            );
-            PyErr_Clear();
-            if (type_error && convert && PyNumber_Check(src.ptr())) {
-                auto tmp = reinterpret_steal<object>(std::is_floating_point<T>::value
-                                                     ? PyNumber_Float(src.ptr())
-                                                     : PyNumber_Long(src.ptr()));
-                PyErr_Clear();
-                return load(tmp, false);
-            }
-            return false;
-        }
-
-        value = (T) py_value;
-        return true;
-    }
-
-    template<typename U = T>
-    static typename std::enable_if<std::is_floating_point<U>::value, handle>::type
-    cast(U src, return_value_policy /* policy */, handle /* parent */) {
-        return PyFloat_FromDouble((double) src);
-    }
-
-    template<typename U = T>
-    static typename std::enable_if<!std::is_floating_point<U>::value && std::is_signed<U>::value && (sizeof(U) <= sizeof(long)), handle>::type
-    cast(U src, return_value_policy /* policy */, handle /* parent */) {
-        return PYBIND11_LONG_FROM_SIGNED((long) src);
-    }
-
-    template<typename U = T>
-    static typename std::enable_if<!std::is_floating_point<U>::value && std::is_unsigned<U>::value && (sizeof(U) <= sizeof(unsigned long)), handle>::type
-    cast(U src, return_value_policy /* policy */, handle /* parent */) {
-        return PYBIND11_LONG_FROM_UNSIGNED((unsigned long) src);
-    }
-
-    template<typename U = T>
-    static typename std::enable_if<!std::is_floating_point<U>::value && std::is_signed<U>::value && (sizeof(U) > sizeof(long)), handle>::type
-    cast(U src, return_value_policy /* policy */, handle /* parent */) {
-        return PyLong_FromLongLong((long long) src);
-    }
-
-    template<typename U = T>
-    static typename std::enable_if<!std::is_floating_point<U>::value && std::is_unsigned<U>::value && (sizeof(U) > sizeof(unsigned long)), handle>::type
-    cast(U src, return_value_policy /* policy */, handle /* parent */) {
-        return PyLong_FromUnsignedLongLong((unsigned long long) src);
-    }
-
-    PYBIND11_TYPE_CASTER(T, _<std::is_integral<T>::value>("int", "float"));
-};
-
-template<typename T> struct void_caster {
-public:
-    bool load(handle src, bool) {
-        if (src && src.is_none())
-            return true;
-        return false;
-    }
-    static handle cast(T, return_value_policy /* policy */, handle /* parent */) {
-        return none().inc_ref();
-    }
-    PYBIND11_TYPE_CASTER(T, _("None"));
-};
-
-template <> class type_caster<void_type> : public void_caster<void_type> {};
-
-template <> class type_caster<void> : public type_caster<void_type> {
-public:
-    using type_caster<void_type>::cast;
-
-    bool load(handle h, bool) {
-        if (!h) {
-            return false;
-        } else if (h.is_none()) {
-            value = nullptr;
-            return true;
-        }
-
-        /* Check if this is a capsule */
-        if (isinstance<capsule>(h)) {
-            value = reinterpret_borrow<capsule>(h);
-            return true;
-        }
-
-        /* Check if this is a C++ type */
-        auto &bases = all_type_info((PyTypeObject *) h.get_type().ptr());
-        if (bases.size() == 1) { // Only allowing loading from a single-value type
-            value = values_and_holders(reinterpret_cast<instance *>(h.ptr())).begin()->value_ptr();
-            return true;
-        }
-
-        /* Fail */
-        return false;
-    }
-
-    static handle cast(const void *ptr, return_value_policy /* policy */, handle /* parent */) {
-        if (ptr)
-            return capsule(ptr).release();
-        else
-            return none().inc_ref();
-    }
-
-    template <typename T> using cast_op_type = void*&;
-    operator void *&() { return value; }
-    static constexpr auto name = _("capsule");
-private:
-    void *value = nullptr;
-};
-
-template <> class type_caster<std::nullptr_t> : public void_caster<std::nullptr_t> { };
-
-template <> class type_caster<bool> {
-public:
-    bool load(handle src, bool convert) {
-        if (!src) return false;
-        else if (src.ptr() == Py_True) { value = true; return true; }
-        else if (src.ptr() == Py_False) { value = false; return true; }
-        else if (convert || !strcmp("numpy.bool_", Py_TYPE(src.ptr())->tp_name)) {
-            // (allow non-implicit conversion for numpy booleans)
-
-            Py_ssize_t res = -1;
-            if (src.is_none()) {
-                res = 0;  // None is implicitly converted to False
-            }
-            #if defined(PYPY_VERSION)
-            // On PyPy, check that "__bool__" (or "__nonzero__" on Python 2.7) attr exists
-            else if (hasattr(src, PYBIND11_BOOL_ATTR)) {
-                res = PyObject_IsTrue(src.ptr());
-            }
-            #else
-            // Alternate approach for CPython: this does the same as the above, but optimized
-            // using the CPython API so as to avoid an unneeded attribute lookup.
-            else if (auto tp_as_number = src.ptr()->ob_type->tp_as_number) {
-                if (PYBIND11_NB_BOOL(tp_as_number)) {
-                    res = (*PYBIND11_NB_BOOL(tp_as_number))(src.ptr());
-                }
-            }
-            #endif
-            if (res == 0 || res == 1) {
-                value = (bool) res;
-                return true;
-            } else {
-                PyErr_Clear();
-            }
-        }
-        return false;
-    }
-    static handle cast(bool src, return_value_policy /* policy */, handle /* parent */) {
-        return handle(src ? Py_True : Py_False).inc_ref();
-    }
-    PYBIND11_TYPE_CASTER(bool, _("bool"));
-};
-
-// Helper class for UTF-{8,16,32} C++ stl strings:
-template <typename StringType, bool IsView = false> struct string_caster {
-    using CharT = typename StringType::value_type;
-
-    // Simplify life by being able to assume standard char sizes (the standard only guarantees
-    // minimums, but Python requires exact sizes)
-    static_assert(!std::is_same<CharT, char>::value || sizeof(CharT) == 1, "Unsupported char size != 1");
-#if defined(PYBIND11_HAS_U8STRING)
-    static_assert(!std::is_same<CharT, char8_t>::value || sizeof(CharT) == 1, "Unsupported char8_t size != 1");
-#endif
-    static_assert(!std::is_same<CharT, char16_t>::value || sizeof(CharT) == 2, "Unsupported char16_t size != 2");
-    static_assert(!std::is_same<CharT, char32_t>::value || sizeof(CharT) == 4, "Unsupported char32_t size != 4");
-    // wchar_t can be either 16 bits (Windows) or 32 (everywhere else)
-    static_assert(!std::is_same<CharT, wchar_t>::value || sizeof(CharT) == 2 || sizeof(CharT) == 4,
-            "Unsupported wchar_t size != 2/4");
-    static constexpr size_t UTF_N = 8 * sizeof(CharT);
-
-    bool load(handle src, bool) {
-#if PY_MAJOR_VERSION < 3
-        object temp;
-#endif
-        handle load_src = src;
-        if (!src) {
-            return false;
-        } else if (!PyUnicode_Check(load_src.ptr())) {
-#if PY_MAJOR_VERSION >= 3
-            return load_bytes(load_src);
-#else
-            if (std::is_same<CharT, char>::value) {
-                return load_bytes(load_src);
-            }
-
-            // The below is a guaranteed failure in Python 3 when PyUnicode_Check returns false
-            if (!PYBIND11_BYTES_CHECK(load_src.ptr()))
-                return false;
-
-            temp = reinterpret_steal<object>(PyUnicode_FromObject(load_src.ptr()));
-            if (!temp) { PyErr_Clear(); return false; }
-            load_src = temp;
-#endif
-        }
-
-        object utfNbytes = reinterpret_steal<object>(PyUnicode_AsEncodedString(
-            load_src.ptr(), UTF_N == 8 ? "utf-8" : UTF_N == 16 ? "utf-16" : "utf-32", nullptr));
-        if (!utfNbytes) { PyErr_Clear(); return false; }
-
-        const CharT *buffer = reinterpret_cast<const CharT *>(PYBIND11_BYTES_AS_STRING(utfNbytes.ptr()));
-        size_t length = (size_t) PYBIND11_BYTES_SIZE(utfNbytes.ptr()) / sizeof(CharT);
-        if (UTF_N > 8) { buffer++; length--; } // Skip BOM for UTF-16/32
-        value = StringType(buffer, length);
-
-        // If we're loading a string_view we need to keep the encoded Python object alive:
-        if (IsView)
-            loader_life_support::add_patient(utfNbytes);
-
-        return true;
-    }
-
-    static handle cast(const StringType &src, return_value_policy /* policy */, handle /* parent */) {
-        const char *buffer = reinterpret_cast<const char *>(src.data());
-        ssize_t nbytes = ssize_t(src.size() * sizeof(CharT));
-        handle s = decode_utfN(buffer, nbytes);
-        if (!s) throw error_already_set();
-        return s;
-    }
-
-    PYBIND11_TYPE_CASTER(StringType, _(PYBIND11_STRING_NAME));
-
-private:
-    static handle decode_utfN(const char *buffer, ssize_t nbytes) {
-#if !defined(PYPY_VERSION)
-        return
-            UTF_N == 8  ? PyUnicode_DecodeUTF8(buffer, nbytes, nullptr) :
-            UTF_N == 16 ? PyUnicode_DecodeUTF16(buffer, nbytes, nullptr, nullptr) :
-                          PyUnicode_DecodeUTF32(buffer, nbytes, nullptr, nullptr);
-#else
-        // PyPy seems to have multiple problems related to PyUnicode_UTF*: the UTF8 version
-        // sometimes segfaults for unknown reasons, while the UTF16 and 32 versions require a
-        // non-const char * arguments, which is also a nuisance, so bypass the whole thing by just
-        // passing the encoding as a string value, which works properly:
-        return PyUnicode_Decode(buffer, nbytes, UTF_N == 8 ? "utf-8" : UTF_N == 16 ? "utf-16" : "utf-32", nullptr);
-#endif
-    }
-
-    // When loading into a std::string or char*, accept a bytes object as-is (i.e.
-    // without any encoding/decoding attempt).  For other C++ char sizes this is a no-op.
-    // which supports loading a unicode from a str, doesn't take this path.
-    template <typename C = CharT>
-    bool load_bytes(enable_if_t<std::is_same<C, char>::value, handle> src) {
-        if (PYBIND11_BYTES_CHECK(src.ptr())) {
-            // We were passed a Python 3 raw bytes; accept it into a std::string or char*
-            // without any encoding attempt.
-            const char *bytes = PYBIND11_BYTES_AS_STRING(src.ptr());
-            if (bytes) {
-                value = StringType(bytes, (size_t) PYBIND11_BYTES_SIZE(src.ptr()));
-                return true;
-            }
-        }
-
-        return false;
-    }
-
-    template <typename C = CharT>
-    bool load_bytes(enable_if_t<!std::is_same<C, char>::value, handle>) { return false; }
-};
-
-template <typename CharT, class Traits, class Allocator>
-struct type_caster<std::basic_string<CharT, Traits, Allocator>, enable_if_t<is_std_char_type<CharT>::value>>
-    : string_caster<std::basic_string<CharT, Traits, Allocator>> {};
-
-#ifdef PYBIND11_HAS_STRING_VIEW
-template <typename CharT, class Traits>
-struct type_caster<std::basic_string_view<CharT, Traits>, enable_if_t<is_std_char_type<CharT>::value>>
-    : string_caster<std::basic_string_view<CharT, Traits>, true> {};
-#endif
-
-// Type caster for C-style strings.  We basically use a std::string type caster, but also add the
-// ability to use None as a nullptr char* (which the string caster doesn't allow).
-template <typename CharT> struct type_caster<CharT, enable_if_t<is_std_char_type<CharT>::value>> {
-    using StringType = std::basic_string<CharT>;
-    using StringCaster = type_caster<StringType>;
-    StringCaster str_caster;
-    bool none = false;
-    CharT one_char = 0;
-public:
-    bool load(handle src, bool convert) {
-        if (!src) return false;
-        if (src.is_none()) {
-            // Defer accepting None to other overloads (if we aren't in convert mode):
-            if (!convert) return false;
-            none = true;
-            return true;
-        }
-        return str_caster.load(src, convert);
-    }
-
-    static handle cast(const CharT *src, return_value_policy policy, handle parent) {
-        if (src == nullptr) return pybind11::none().inc_ref();
-        return StringCaster::cast(StringType(src), policy, parent);
-    }
-
-    static handle cast(CharT src, return_value_policy policy, handle parent) {
-        if (std::is_same<char, CharT>::value) {
-            handle s = PyUnicode_DecodeLatin1((const char *) &src, 1, nullptr);
-            if (!s) throw error_already_set();
-            return s;
-        }
-        return StringCaster::cast(StringType(1, src), policy, parent);
-    }
-
-    operator CharT*() { return none ? nullptr : const_cast<CharT *>(static_cast<StringType &>(str_caster).c_str()); }
-    operator CharT&() {
-        if (none)
-            throw value_error("Cannot convert None to a character");
-
-        auto &value = static_cast<StringType &>(str_caster);
-        size_t str_len = value.size();
-        if (str_len == 0)
-            throw value_error("Cannot convert empty string to a character");
-
-        // If we're in UTF-8 mode, we have two possible failures: one for a unicode character that
-        // is too high, and one for multiple unicode characters (caught later), so we need to figure
-        // out how long the first encoded character is in bytes to distinguish between these two
-        // errors.  We also allow want to allow unicode characters U+0080 through U+00FF, as those
-        // can fit into a single char value.
-        if (StringCaster::UTF_N == 8 && str_len > 1 && str_len <= 4) {
-            unsigned char v0 = static_cast<unsigned char>(value[0]);
-            size_t char0_bytes = !(v0 & 0x80) ? 1 : // low bits only: 0-127
-                (v0 & 0xE0) == 0xC0 ? 2 : // 0b110xxxxx - start of 2-byte sequence
-                (v0 & 0xF0) == 0xE0 ? 3 : // 0b1110xxxx - start of 3-byte sequence
-                4; // 0b11110xxx - start of 4-byte sequence
-
-            if (char0_bytes == str_len) {
-                // If we have a 128-255 value, we can decode it into a single char:
-                if (char0_bytes == 2 && (v0 & 0xFC) == 0xC0) { // 0x110000xx 0x10xxxxxx
-                    one_char = static_cast<CharT>(((v0 & 3) << 6) + (static_cast<unsigned char>(value[1]) & 0x3F));
-                    return one_char;
-                }
-                // Otherwise we have a single character, but it's > U+00FF
-                throw value_error("Character code point not in range(0x100)");
-            }
-        }
-
-        // UTF-16 is much easier: we can only have a surrogate pair for values above U+FFFF, thus a
-        // surrogate pair with total length 2 instantly indicates a range error (but not a "your
-        // string was too long" error).
-        else if (StringCaster::UTF_N == 16 && str_len == 2) {
-            one_char = static_cast<CharT>(value[0]);
-            if (one_char >= 0xD800 && one_char < 0xE000)
-                throw value_error("Character code point not in range(0x10000)");
-        }
-
-        if (str_len != 1)
-            throw value_error("Expected a character, but multi-character string found");
-
-        one_char = value[0];
-        return one_char;
-    }
-
-    static constexpr auto name = _(PYBIND11_STRING_NAME);
-    template <typename _T> using cast_op_type = pybind11::detail::cast_op_type<_T>;
-};
-
-// Base implementation for std::tuple and std::pair
-template <template<typename...> class Tuple, typename... Ts> class tuple_caster {
-    using type = Tuple<Ts...>;
-    static constexpr auto size = sizeof...(Ts);
-    using indices = make_index_sequence<size>;
-public:
-
-    bool load(handle src, bool convert) {
-        if (!isinstance<sequence>(src))
-            return false;
-        const auto seq = reinterpret_borrow<sequence>(src);
-        if (seq.size() != size)
-            return false;
-        return load_impl(seq, convert, indices{});
-    }
-
-    template <typename T>
-    static handle cast(T &&src, return_value_policy policy, handle parent) {
-        return cast_impl(std::forward<T>(src), policy, parent, indices{});
-    }
-
-    // copied from the PYBIND11_TYPE_CASTER macro
-    template <typename T>
-    static handle cast(T *src, return_value_policy policy, handle parent) {
-        if (!src) return none().release();
-        if (policy == return_value_policy::take_ownership) {
-            auto h = cast(std::move(*src), policy, parent); delete src; return h;
-        } else {
-            return cast(*src, policy, parent);
-        }
-    }
-
-    static constexpr auto name = _("Tuple[") + concat(make_caster<Ts>::name...) + _("]");
-
-    template <typename T> using cast_op_type = type;
-
-    operator type() & { return implicit_cast(indices{}); }
-    operator type() && { return std::move(*this).implicit_cast(indices{}); }
-
-protected:
-    template <size_t... Is>
-    type implicit_cast(index_sequence<Is...>) & { return type(cast_op<Ts>(std::get<Is>(subcasters))...); }
-    template <size_t... Is>
-    type implicit_cast(index_sequence<Is...>) && { return type(cast_op<Ts>(std::move(std::get<Is>(subcasters)))...); }
-
-    static constexpr bool load_impl(const sequence &, bool, index_sequence<>) { return true; }
-
-    template <size_t... Is>
-    bool load_impl(const sequence &seq, bool convert, index_sequence<Is...>) {
-#ifdef __cpp_fold_expressions
-        if ((... || !std::get<Is>(subcasters).load(seq[Is], convert)))
-            return false;
-#else
-        for (bool r : {std::get<Is>(subcasters).load(seq[Is], convert)...})
-            if (!r)
-                return false;
-#endif
-        return true;
-    }
-
-    /* Implementation: Convert a C++ tuple into a Python tuple */
-    template <typename T, size_t... Is>
-    static handle cast_impl(T &&src, return_value_policy policy, handle parent, index_sequence<Is...>) {
-        std::array<object, size> entries{{
-            reinterpret_steal<object>(make_caster<Ts>::cast(std::get<Is>(std::forward<T>(src)), policy, parent))...
-        }};
-        for (const auto &entry: entries)
-            if (!entry)
-                return handle();
-        tuple result(size);
-        int counter = 0;
-        for (auto & entry: entries)
-            PyTuple_SET_ITEM(result.ptr(), counter++, entry.release().ptr());
-        return result.release();
-    }
-
-    Tuple<make_caster<Ts>...> subcasters;
-};
-
-template <typename T1, typename T2> class type_caster<std::pair<T1, T2>>
-    : public tuple_caster<std::pair, T1, T2> {};
-
-template <typename... Ts> class type_caster<std::tuple<Ts...>>
-    : public tuple_caster<std::tuple, Ts...> {};
-
-/// Helper class which abstracts away certain actions. Users can provide specializations for
-/// custom holders, but it's only necessary if the type has a non-standard interface.
-template <typename T>
-struct holder_helper {
-    static auto get(const T &p) -> decltype(p.get()) { return p.get(); }
-};
-
-/// Type caster for holder types like std::shared_ptr, etc.
-template <typename type, typename holder_type>
-struct copyable_holder_caster : public type_caster_base<type> {
-public:
-    using base = type_caster_base<type>;
-    static_assert(std::is_base_of<base, type_caster<type>>::value,
-            "Holder classes are only supported for custom types");
-    using base::base;
-    using base::cast;
-    using base::typeinfo;
-    using base::value;
-
-    bool load(handle src, bool convert) {
-        return base::template load_impl<copyable_holder_caster<type, holder_type>>(src, convert);
-    }
-
-    explicit operator type*() { return this->value; }
-    // static_cast works around compiler error with MSVC 17 and CUDA 10.2
-    // see issue #2180
-    explicit operator type&() { return *(static_cast<type *>(this->value)); }
-    explicit operator holder_type*() { return std::addressof(holder); }
-
-    // Workaround for Intel compiler bug
-    // see pybind11 issue 94
-    #if defined(__ICC) || defined(__INTEL_COMPILER)
-    operator holder_type&() { return holder; }
-    #else
-    explicit operator holder_type&() { return holder; }
-    #endif
-
-    static handle cast(const holder_type &src, return_value_policy, handle) {
-        const auto *ptr = holder_helper<holder_type>::get(src);
-        return type_caster_base<type>::cast_holder(ptr, &src);
-    }
-
-protected:
-    friend class type_caster_generic;
-    void check_holder_compat() {
-        if (typeinfo->default_holder)
-            throw cast_error("Unable to load a custom holder type from a default-holder instance");
-    }
-
-    bool load_value(value_and_holder &&v_h) {
-        if (v_h.holder_constructed()) {
-            value = v_h.value_ptr();
-            holder = v_h.template holder<holder_type>();
-            return true;
-        } else {
-            throw cast_error("Unable to cast from non-held to held instance (T& to Holder<T>) "
-#if defined(NDEBUG)
-                             "(compile in debug mode for type information)");
-#else
-                             "of type '" + type_id<holder_type>() + "''");
-#endif
-        }
-    }
-
-    template <typename T = holder_type, detail::enable_if_t<!std::is_constructible<T, const T &, type*>::value, int> = 0>
-    bool try_implicit_casts(handle, bool) { return false; }
-
-    template <typename T = holder_type, detail::enable_if_t<std::is_constructible<T, const T &, type*>::value, int> = 0>
-    bool try_implicit_casts(handle src, bool convert) {
-        for (auto &cast : typeinfo->implicit_casts) {
-            copyable_holder_caster sub_caster(*cast.first);
-            if (sub_caster.load(src, convert)) {
-                value = cast.second(sub_caster.value);
-                holder = holder_type(sub_caster.holder, (type *) value);
-                return true;
-            }
-        }
-        return false;
-    }
-
-    static bool try_direct_conversions(handle) { return false; }
-
-
-    holder_type holder;
-};
-
-/// Specialize for the common std::shared_ptr, so users don't need to
-template <typename T>
-class type_caster<std::shared_ptr<T>> : public copyable_holder_caster<T, std::shared_ptr<T>> { };
-
-template <typename type, typename holder_type>
-struct move_only_holder_caster {
-    static_assert(std::is_base_of<type_caster_base<type>, type_caster<type>>::value,
-            "Holder classes are only supported for custom types");
-
-    static handle cast(holder_type &&src, return_value_policy, handle) {
-        auto *ptr = holder_helper<holder_type>::get(src);
-        return type_caster_base<type>::cast_holder(ptr, std::addressof(src));
-    }
-    static constexpr auto name = type_caster_base<type>::name;
-};
-
-template <typename type, typename deleter>
-class type_caster<std::unique_ptr<type, deleter>>
-    : public move_only_holder_caster<type, std::unique_ptr<type, deleter>> { };
-
-template <typename type, typename holder_type>
-using type_caster_holder = conditional_t<is_copy_constructible<holder_type>::value,
-                                         copyable_holder_caster<type, holder_type>,
-                                         move_only_holder_caster<type, holder_type>>;
-
-template <typename T, bool Value = false> struct always_construct_holder { static constexpr bool value = Value; };
-
-/// Create a specialization for custom holder types (silently ignores std::shared_ptr)
-#define PYBIND11_DECLARE_HOLDER_TYPE(type, holder_type, ...) \
-    namespace pybind11 { namespace detail { \
-    template <typename type> \
-    struct always_construct_holder<holder_type> : always_construct_holder<void, ##__VA_ARGS__>  { }; \
-    template <typename type> \
-    class type_caster<holder_type, enable_if_t<!is_shared_ptr<holder_type>::value>> \
-        : public type_caster_holder<type, holder_type> { }; \
-    }}
-
-// PYBIND11_DECLARE_HOLDER_TYPE holder types:
-template <typename base, typename holder> struct is_holder_type :
-    std::is_base_of<detail::type_caster_holder<base, holder>, detail::type_caster<holder>> {};
-// Specialization for always-supported unique_ptr holders:
-template <typename base, typename deleter> struct is_holder_type<base, std::unique_ptr<base, deleter>> :
-    std::true_type {};
-
-template <typename T> struct handle_type_name { static constexpr auto name = _<T>(); };
-template <> struct handle_type_name<bytes> { static constexpr auto name = _(PYBIND11_BYTES_NAME); };
-template <> struct handle_type_name<int_> { static constexpr auto name = _("int"); };
-template <> struct handle_type_name<iterable> { static constexpr auto name = _("Iterable"); };
-template <> struct handle_type_name<iterator> { static constexpr auto name = _("Iterator"); };
-template <> struct handle_type_name<none> { static constexpr auto name = _("None"); };
-template <> struct handle_type_name<args> { static constexpr auto name = _("*args"); };
-template <> struct handle_type_name<kwargs> { static constexpr auto name = _("**kwargs"); };
-
-template <typename type>
-struct pyobject_caster {
-    template <typename T = type, enable_if_t<std::is_same<T, handle>::value, int> = 0>
-    bool load(handle src, bool /* convert */) { value = src; return static_cast<bool>(value); }
-
-    template <typename T = type, enable_if_t<std::is_base_of<object, T>::value, int> = 0>
-    bool load(handle src, bool /* convert */) {
-        if (!isinstance<type>(src))
-            return false;
-        value = reinterpret_borrow<type>(src);
-        return true;
-    }
-
-    static handle cast(const handle &src, return_value_policy /* policy */, handle /* parent */) {
-        return src.inc_ref();
-    }
-    PYBIND11_TYPE_CASTER(type, handle_type_name<type>::name);
-};
-
-template <typename T>
-class type_caster<T, enable_if_t<is_pyobject<T>::value>> : public pyobject_caster<T> { };
-
-// Our conditions for enabling moving are quite restrictive:
-// At compile time:
-// - T needs to be a non-const, non-pointer, non-reference type
-// - type_caster<T>::operator T&() must exist
-// - the type must be move constructible (obviously)
-// At run-time:
-// - if the type is non-copy-constructible, the object must be the sole owner of the type (i.e. it
-//   must have ref_count() == 1)h
-// If any of the above are not satisfied, we fall back to copying.
-template <typename T> using move_is_plain_type = satisfies_none_of<T,
-    std::is_void, std::is_pointer, std::is_reference, std::is_const
->;
-template <typename T, typename SFINAE = void> struct move_always : std::false_type {};
-template <typename T> struct move_always<T, enable_if_t<all_of<
-    move_is_plain_type<T>,
-    negation<is_copy_constructible<T>>,
-    std::is_move_constructible<T>,
-    std::is_same<decltype(std::declval<make_caster<T>>().operator T&()), T&>
->::value>> : std::true_type {};
-template <typename T, typename SFINAE = void> struct move_if_unreferenced : std::false_type {};
-template <typename T> struct move_if_unreferenced<T, enable_if_t<all_of<
-    move_is_plain_type<T>,
-    negation<move_always<T>>,
-    std::is_move_constructible<T>,
-    std::is_same<decltype(std::declval<make_caster<T>>().operator T&()), T&>
->::value>> : std::true_type {};
-template <typename T> using move_never = none_of<move_always<T>, move_if_unreferenced<T>>;
-
-// Detect whether returning a `type` from a cast on type's type_caster is going to result in a
-// reference or pointer to a local variable of the type_caster.  Basically, only
-// non-reference/pointer `type`s and reference/pointers from a type_caster_generic are safe;
-// everything else returns a reference/pointer to a local variable.
-template <typename type> using cast_is_temporary_value_reference = bool_constant<
-    (std::is_reference<type>::value || std::is_pointer<type>::value) &&
-    !std::is_base_of<type_caster_generic, make_caster<type>>::value &&
-    !std::is_same<intrinsic_t<type>, void>::value
->;
-
-// When a value returned from a C++ function is being cast back to Python, we almost always want to
-// force `policy = move`, regardless of the return value policy the function/method was declared
-// with.
-template <typename Return, typename SFINAE = void> struct return_value_policy_override {
-    static return_value_policy policy(return_value_policy p) { return p; }
-};
-
-template <typename Return> struct return_value_policy_override<Return,
-        detail::enable_if_t<std::is_base_of<type_caster_generic, make_caster<Return>>::value, void>> {
-    static return_value_policy policy(return_value_policy p) {
-        return !std::is_lvalue_reference<Return>::value &&
-               !std::is_pointer<Return>::value
-                   ? return_value_policy::move : p;
-    }
-};
-
-// Basic python -> C++ casting; throws if casting fails
-template <typename T, typename SFINAE> type_caster<T, SFINAE> &load_type(type_caster<T, SFINAE> &conv, const handle &handle) {
-    if (!conv.load(handle, true)) {
-#if defined(NDEBUG)
-        throw cast_error("Unable to cast Python instance to C++ type (compile in debug mode for details)");
-#else
-        throw cast_error("Unable to cast Python instance of type " +
-            (std::string) str(handle.get_type()) + " to C++ type '" + type_id<T>() + "'");
-#endif
-    }
-    return conv;
-}
-// Wrapper around the above that also constructs and returns a type_caster
-template <typename T> make_caster<T> load_type(const handle &handle) {
-    make_caster<T> conv;
-    load_type(conv, handle);
-    return conv;
-}
-
-PYBIND11_NAMESPACE_END(detail)
-
-// pytype -> C++ type
-template <typename T, detail::enable_if_t<!detail::is_pyobject<T>::value, int> = 0>
-T cast(const handle &handle) {
-    using namespace detail;
-    static_assert(!cast_is_temporary_value_reference<T>::value,
-            "Unable to cast type to reference: value is local to type caster");
-    return cast_op<T>(load_type<T>(handle));
-}
-
-// pytype -> pytype (calls converting constructor)
-template <typename T, detail::enable_if_t<detail::is_pyobject<T>::value, int> = 0>
-T cast(const handle &handle) { return T(reinterpret_borrow<object>(handle)); }
-
-// C++ type -> py::object
-template <typename T, detail::enable_if_t<!detail::is_pyobject<T>::value, int> = 0>
-object cast(T &&value, return_value_policy policy = return_value_policy::automatic_reference,
-            handle parent = handle()) {
-    using no_ref_T = typename std::remove_reference<T>::type;
-    if (policy == return_value_policy::automatic)
-        policy = std::is_pointer<no_ref_T>::value ? return_value_policy::take_ownership :
-                 std::is_lvalue_reference<T>::value ? return_value_policy::copy : return_value_policy::move;
-    else if (policy == return_value_policy::automatic_reference)
-        policy = std::is_pointer<no_ref_T>::value ? return_value_policy::reference :
-                 std::is_lvalue_reference<T>::value ? return_value_policy::copy : return_value_policy::move;
-    return reinterpret_steal<object>(detail::make_caster<T>::cast(std::forward<T>(value), policy, parent));
-}
-
-template <typename T> T handle::cast() const { return pybind11::cast<T>(*this); }
-template <> inline void handle::cast() const { return; }
-
-template <typename T>
-detail::enable_if_t<!detail::move_never<T>::value, T> move(object &&obj) {
-    if (obj.ref_count() > 1)
-#if defined(NDEBUG)
-        throw cast_error("Unable to cast Python instance to C++ rvalue: instance has multiple references"
-            " (compile in debug mode for details)");
-#else
-        throw cast_error("Unable to move from Python " + (std::string) str(obj.get_type()) +
-                " instance to C++ " + type_id<T>() + " instance: instance has multiple references");
-#endif
-
-    // Move into a temporary and return that, because the reference may be a local value of `conv`
-    T ret = std::move(detail::load_type<T>(obj).operator T&());
-    return ret;
-}
-
-// Calling cast() on an rvalue calls pybind11::cast with the object rvalue, which does:
-// - If we have to move (because T has no copy constructor), do it.  This will fail if the moved
-//   object has multiple references, but trying to copy will fail to compile.
-// - If both movable and copyable, check ref count: if 1, move; otherwise copy
-// - Otherwise (not movable), copy.
-template <typename T> detail::enable_if_t<detail::move_always<T>::value, T> cast(object &&object) {
-    return move<T>(std::move(object));
-}
-template <typename T> detail::enable_if_t<detail::move_if_unreferenced<T>::value, T> cast(object &&object) {
-    if (object.ref_count() > 1)
-        return cast<T>(object);
-    else
-        return move<T>(std::move(object));
-}
-template <typename T> detail::enable_if_t<detail::move_never<T>::value, T> cast(object &&object) {
-    return cast<T>(object);
-}
-
-template <typename T> T object::cast() const & { return pybind11::cast<T>(*this); }
-template <typename T> T object::cast() && { return pybind11::cast<T>(std::move(*this)); }
-template <> inline void object::cast() const & { return; }
-template <> inline void object::cast() && { return; }
-
-PYBIND11_NAMESPACE_BEGIN(detail)
-
-// Declared in pytypes.h:
-template <typename T, enable_if_t<!is_pyobject<T>::value, int>>
-object object_or_cast(T &&o) { return pybind11::cast(std::forward<T>(o)); }
-
-struct overload_unused {}; // Placeholder type for the unneeded (and dead code) static variable in the OVERLOAD_INT macro
-template <typename ret_type> using overload_caster_t = conditional_t<
-    cast_is_temporary_value_reference<ret_type>::value, make_caster<ret_type>, overload_unused>;
-
-// Trampoline use: for reference/pointer types to value-converted values, we do a value cast, then
-// store the result in the given variable.  For other types, this is a no-op.
-template <typename T> enable_if_t<cast_is_temporary_value_reference<T>::value, T> cast_ref(object &&o, make_caster<T> &caster) {
-    return cast_op<T>(load_type(caster, o));
-}
-template <typename T> enable_if_t<!cast_is_temporary_value_reference<T>::value, T> cast_ref(object &&, overload_unused &) {
-    pybind11_fail("Internal error: cast_ref fallback invoked"); }
-
-// Trampoline use: Having a pybind11::cast with an invalid reference type is going to static_assert, even
-// though if it's in dead code, so we provide a "trampoline" to pybind11::cast that only does anything in
-// cases where pybind11::cast is valid.
-template <typename T> enable_if_t<!cast_is_temporary_value_reference<T>::value, T> cast_safe(object &&o) {
-    return pybind11::cast<T>(std::move(o)); }
-template <typename T> enable_if_t<cast_is_temporary_value_reference<T>::value, T> cast_safe(object &&) {
-    pybind11_fail("Internal error: cast_safe fallback invoked"); }
-template <> inline void cast_safe<void>(object &&) {}
-
-PYBIND11_NAMESPACE_END(detail)
-
-template <return_value_policy policy = return_value_policy::automatic_reference>
-tuple make_tuple() { return tuple(0); }
-
-template <return_value_policy policy = return_value_policy::automatic_reference,
-          typename... Args> tuple make_tuple(Args&&... args_) {
-    constexpr size_t size = sizeof...(Args);
-    std::array<object, size> args {
-        { reinterpret_steal<object>(detail::make_caster<Args>::cast(
-            std::forward<Args>(args_), policy, nullptr))... }
-    };
-    for (size_t i = 0; i < args.size(); i++) {
-        if (!args[i]) {
-#if defined(NDEBUG)
-            throw cast_error("make_tuple(): unable to convert arguments to Python object (compile in debug mode for details)");
-#else
-            std::array<std::string, size> argtypes { {type_id<Args>()...} };
-            throw cast_error("make_tuple(): unable to convert argument of type '" +
-                argtypes[i] + "' to Python object");
-#endif
-        }
-    }
-    tuple result(size);
-    int counter = 0;
-    for (auto &arg_value : args)
-        PyTuple_SET_ITEM(result.ptr(), counter++, arg_value.release().ptr());
-    return result;
-}
-
-/// \ingroup annotations
-/// Annotation for arguments
-struct arg {
-    /// Constructs an argument with the name of the argument; if null or omitted, this is a positional argument.
-    constexpr explicit arg(const char *name = nullptr) : name(name), flag_noconvert(false), flag_none(true) { }
-    /// Assign a value to this argument
-    template <typename T> arg_v operator=(T &&value) const;
-    /// Indicate that the type should not be converted in the type caster
-    arg &noconvert(bool flag = true) { flag_noconvert = flag; return *this; }
-    /// Indicates that the argument should/shouldn't allow None (e.g. for nullable pointer args)
-    arg &none(bool flag = true) { flag_none = flag; return *this; }
-
-    const char *name; ///< If non-null, this is a named kwargs argument
-    bool flag_noconvert : 1; ///< If set, do not allow conversion (requires a supporting type caster!)
-    bool flag_none : 1; ///< If set (the default), allow None to be passed to this argument
-};
-
-/// \ingroup annotations
-/// Annotation for arguments with values
-struct arg_v : arg {
-private:
-    template <typename T>
-    arg_v(arg &&base, T &&x, const char *descr = nullptr)
-        : arg(base),
-          value(reinterpret_steal<object>(
-              detail::make_caster<T>::cast(x, return_value_policy::automatic, {})
-          )),
-          descr(descr)
-#if !defined(NDEBUG)
-        , type(type_id<T>())
-#endif
-    { }
-
-public:
-    /// Direct construction with name, default, and description
-    template <typename T>
-    arg_v(const char *name, T &&x, const char *descr = nullptr)
-        : arg_v(arg(name), std::forward<T>(x), descr) { }
-
-    /// Called internally when invoking `py::arg("a") = value`
-    template <typename T>
-    arg_v(const arg &base, T &&x, const char *descr = nullptr)
-        : arg_v(arg(base), std::forward<T>(x), descr) { }
-
-    /// Same as `arg::noconvert()`, but returns *this as arg_v&, not arg&
-    arg_v &noconvert(bool flag = true) { arg::noconvert(flag); return *this; }
-
-    /// Same as `arg::nonone()`, but returns *this as arg_v&, not arg&
-    arg_v &none(bool flag = true) { arg::none(flag); return *this; }
-
-    /// The default value
-    object value;
-    /// The (optional) description of the default value
-    const char *descr;
-#if !defined(NDEBUG)
-    /// The C++ type name of the default value (only available when compiled in debug mode)
-    std::string type;
-#endif
-};
-
-/// \ingroup annotations
-/// Annotation indicating that all following arguments are keyword-only; the is the equivalent of an
-/// unnamed '*' argument (in Python 3)
-struct kwonly {};
-
-template <typename T>
-arg_v arg::operator=(T &&value) const { return {std::move(*this), std::forward<T>(value)}; }
-
-/// Alias for backward compatibility -- to be removed in version 2.0
-template <typename /*unused*/> using arg_t = arg_v;
-
-inline namespace literals {
-/** \rst
-    String literal version of `arg`
- \endrst */
-constexpr arg operator"" _a(const char *name, size_t) { return arg(name); }
-}
-
-PYBIND11_NAMESPACE_BEGIN(detail)
-
-// forward declaration (definition in attr.h)
-struct function_record;
-
-/// Internal data associated with a single function call
-struct function_call {
-    function_call(const function_record &f, handle p); // Implementation in attr.h
-
-    /// The function data:
-    const function_record &func;
-
-    /// Arguments passed to the function:
-    std::vector<handle> args;
-
-    /// The `convert` value the arguments should be loaded with
-    std::vector<bool> args_convert;
-
-    /// Extra references for the optional `py::args` and/or `py::kwargs` arguments (which, if
-    /// present, are also in `args` but without a reference).
-    object args_ref, kwargs_ref;
-
-    /// The parent, if any
-    handle parent;
-
-    /// If this is a call to an initializer, this argument contains `self`
-    handle init_self;
-};
-
-
-/// Helper class which loads arguments for C++ functions called from Python
-template <typename... Args>
-class argument_loader {
-    using indices = make_index_sequence<sizeof...(Args)>;
-
-    template <typename Arg> using argument_is_args   = std::is_same<intrinsic_t<Arg>, args>;
-    template <typename Arg> using argument_is_kwargs = std::is_same<intrinsic_t<Arg>, kwargs>;
-    // Get args/kwargs argument positions relative to the end of the argument list:
-    static constexpr auto args_pos = constexpr_first<argument_is_args, Args...>() - (int) sizeof...(Args),
-                        kwargs_pos = constexpr_first<argument_is_kwargs, Args...>() - (int) sizeof...(Args);
-
-    static constexpr bool args_kwargs_are_last = kwargs_pos >= - 1 && args_pos >= kwargs_pos - 1;
-
-    static_assert(args_kwargs_are_last, "py::args/py::kwargs are only permitted as the last argument(s) of a function");
-
-public:
-    static constexpr bool has_kwargs = kwargs_pos < 0;
-    static constexpr bool has_args = args_pos < 0;
-
-    static constexpr auto arg_names = concat(type_descr(make_caster<Args>::name)...);
-
-    bool load_args(function_call &call) {
-        return load_impl_sequence(call, indices{});
-    }
-
-    template <typename Return, typename Guard, typename Func>
-    enable_if_t<!std::is_void<Return>::value, Return> call(Func &&f) && {
-        return std::move(*this).template call_impl<Return>(std::forward<Func>(f), indices{}, Guard{});
-    }
-
-    template <typename Return, typename Guard, typename Func>
-    enable_if_t<std::is_void<Return>::value, void_type> call(Func &&f) && {
-        std::move(*this).template call_impl<Return>(std::forward<Func>(f), indices{}, Guard{});
-        return void_type();
-    }
-
-private:
-
-    static bool load_impl_sequence(function_call &, index_sequence<>) { return true; }
-
-    template <size_t... Is>
-    bool load_impl_sequence(function_call &call, index_sequence<Is...>) {
-#ifdef __cpp_fold_expressions
-        if ((... || !std::get<Is>(argcasters).load(call.args[Is], call.args_convert[Is])))
-            return false;
-#else
-        for (bool r : {std::get<Is>(argcasters).load(call.args[Is], call.args_convert[Is])...})
-            if (!r)
-                return false;
-#endif
-        return true;
-    }
-
-    template <typename Return, typename Func, size_t... Is, typename Guard>
-    Return call_impl(Func &&f, index_sequence<Is...>, Guard &&) && {
-        return std::forward<Func>(f)(cast_op<Args>(std::move(std::get<Is>(argcasters)))...);
-    }
-
-    std::tuple<make_caster<Args>...> argcasters;
-};
-
-/// Helper class which collects only positional arguments for a Python function call.
-/// A fancier version below can collect any argument, but this one is optimal for simple calls.
-template <return_value_policy policy>
-class simple_collector {
-public:
-    template <typename... Ts>
-    explicit simple_collector(Ts &&...values)
-        : m_args(pybind11::make_tuple<policy>(std::forward<Ts>(values)...)) { }
-
-    const tuple &args() const & { return m_args; }
-    dict kwargs() const { return {}; }
-
-    tuple args() && { return std::move(m_args); }
-
-    /// Call a Python function and pass the collected arguments
-    object call(PyObject *ptr) const {
-        PyObject *result = PyObject_CallObject(ptr, m_args.ptr());
-        if (!result)
-            throw error_already_set();
-        return reinterpret_steal<object>(result);
-    }
-
-private:
-    tuple m_args;
-};
-
-/// Helper class which collects positional, keyword, * and ** arguments for a Python function call
-template <return_value_policy policy>
-class unpacking_collector {
-public:
-    template <typename... Ts>
-    explicit unpacking_collector(Ts &&...values) {
-        // Tuples aren't (easily) resizable so a list is needed for collection,
-        // but the actual function call strictly requires a tuple.
-        auto args_list = list();
-        int _[] = { 0, (process(args_list, std::forward<Ts>(values)), 0)... };
-        ignore_unused(_);
-
-        m_args = std::move(args_list);
-    }
-
-    const tuple &args() const & { return m_args; }
-    const dict &kwargs() const & { return m_kwargs; }
-
-    tuple args() && { return std::move(m_args); }
-    dict kwargs() && { return std::move(m_kwargs); }
-
-    /// Call a Python function and pass the collected arguments
-    object call(PyObject *ptr) const {
-        PyObject *result = PyObject_Call(ptr, m_args.ptr(), m_kwargs.ptr());
-        if (!result)
-            throw error_already_set();
-        return reinterpret_steal<object>(result);
-    }
-
-private:
-    template <typename T>
-    void process(list &args_list, T &&x) {
-        auto o = reinterpret_steal<object>(detail::make_caster<T>::cast(std::forward<T>(x), policy, {}));
-        if (!o) {
-#if defined(NDEBUG)
-            argument_cast_error();
-#else
-            argument_cast_error(std::to_string(args_list.size()), type_id<T>());
-#endif
-        }
-        args_list.append(o);
-    }
-
-    void process(list &args_list, detail::args_proxy ap) {
-        for (const auto &a : ap)
-            args_list.append(a);
-    }
-
-    void process(list &/*args_list*/, arg_v a) {
-        if (!a.name)
-#if defined(NDEBUG)
-            nameless_argument_error();
-#else
-            nameless_argument_error(a.type);
-#endif
-
-        if (m_kwargs.contains(a.name)) {
-#if defined(NDEBUG)
-            multiple_values_error();
-#else
-            multiple_values_error(a.name);
-#endif
-        }
-        if (!a.value) {
-#if defined(NDEBUG)
-            argument_cast_error();
-#else
-            argument_cast_error(a.name, a.type);
-#endif
-        }
-        m_kwargs[a.name] = a.value;
-    }
-
-    void process(list &/*args_list*/, detail::kwargs_proxy kp) {
-        if (!kp)
-            return;
-        for (const auto &k : reinterpret_borrow<dict>(kp)) {
-            if (m_kwargs.contains(k.first)) {
-#if defined(NDEBUG)
-                multiple_values_error();
-#else
-                multiple_values_error(str(k.first));
-#endif
-            }
-            m_kwargs[k.first] = k.second;
-        }
-    }
-
-    [[noreturn]] static void nameless_argument_error() {
-        throw type_error("Got kwargs without a name; only named arguments "
-                         "may be passed via py::arg() to a python function call. "
-                         "(compile in debug mode for details)");
-    }
-    [[noreturn]] static void nameless_argument_error(std::string type) {
-        throw type_error("Got kwargs without a name of type '" + type + "'; only named "
-                         "arguments may be passed via py::arg() to a python function call. ");
-    }
-    [[noreturn]] static void multiple_values_error() {
-        throw type_error("Got multiple values for keyword argument "
-                         "(compile in debug mode for details)");
-    }
-
-    [[noreturn]] static void multiple_values_error(std::string name) {
-        throw type_error("Got multiple values for keyword argument '" + name + "'");
-    }
-
-    [[noreturn]] static void argument_cast_error() {
-        throw cast_error("Unable to convert call argument to Python object "
-                         "(compile in debug mode for details)");
-    }
-
-    [[noreturn]] static void argument_cast_error(std::string name, std::string type) {
-        throw cast_error("Unable to convert call argument '" + name
-                         + "' of type '" + type + "' to Python object");
-    }
-
-private:
-    tuple m_args;
-    dict m_kwargs;
-};
-
-/// Collect only positional arguments for a Python function call
-template <return_value_policy policy, typename... Args,
-          typename = enable_if_t<all_of<is_positional<Args>...>::value>>
-simple_collector<policy> collect_arguments(Args &&...args) {
-    return simple_collector<policy>(std::forward<Args>(args)...);
-}
-
-/// Collect all arguments, including keywords and unpacking (only instantiated when needed)
-template <return_value_policy policy, typename... Args,
-          typename = enable_if_t<!all_of<is_positional<Args>...>::value>>
-unpacking_collector<policy> collect_arguments(Args &&...args) {
-    // Following argument order rules for generalized unpacking according to PEP 448
-    static_assert(
-        constexpr_last<is_positional, Args...>() < constexpr_first<is_keyword_or_ds, Args...>()
-        && constexpr_last<is_s_unpacking, Args...>() < constexpr_first<is_ds_unpacking, Args...>(),
-        "Invalid function call: positional args must precede keywords and ** unpacking; "
-        "* unpacking must precede ** unpacking"
-    );
-    return unpacking_collector<policy>(std::forward<Args>(args)...);
-}
-
-template <typename Derived>
-template <return_value_policy policy, typename... Args>
-object object_api<Derived>::operator()(Args &&...args) const {
-    return detail::collect_arguments<policy>(std::forward<Args>(args)...).call(derived().ptr());
-}
-
-template <typename Derived>
-template <return_value_policy policy, typename... Args>
-object object_api<Derived>::call(Args &&...args) const {
-    return operator()<policy>(std::forward<Args>(args)...);
-}
-
-PYBIND11_NAMESPACE_END(detail)
-
-#define PYBIND11_MAKE_OPAQUE(...) \
-    namespace pybind11 { namespace detail { \
-        template<> class type_caster<__VA_ARGS__> : public type_caster_base<__VA_ARGS__> { }; \
-    }}
-
-/// Lets you pass a type containing a `,` through a macro parameter without needing a separate
-/// typedef, e.g.: `PYBIND11_OVERLOAD(PYBIND11_TYPE(ReturnType<A, B>), PYBIND11_TYPE(Parent<C, D>), f, arg)`
-#define PYBIND11_TYPE(...) __VA_ARGS__
-
-PYBIND11_NAMESPACE_END(PYBIND11_NAMESPACE)
diff --git a/spaces/CVPR/LIVE/thrust/cmake/ThrustAddSubdir.cmake b/spaces/CVPR/LIVE/thrust/cmake/ThrustAddSubdir.cmake
deleted file mode 100644
index d48aa1415789f8fff6ad35b17404880c481d7b93..0000000000000000000000000000000000000000
--- a/spaces/CVPR/LIVE/thrust/cmake/ThrustAddSubdir.cmake
+++ /dev/null
@@ -1,6 +0,0 @@
-find_package(Thrust REQUIRED CONFIG
-  NO_DEFAULT_PATH # Only check the explicit path in HINTS:
-  HINTS "${CMAKE_CURRENT_LIST_DIR}/.."
-  COMPONENTS ${THRUST_REQUIRED_SYSTEMS}
-  OPTIONAL_COMPONENTS ${THRUST_OPTIONAL_SYSTEMS}
-)
diff --git a/spaces/CVPR/LIVE/thrust/thrust/system/cuda/vector.h b/spaces/CVPR/LIVE/thrust/thrust/system/cuda/vector.h
deleted file mode 100644
index 9348057a70ba58fc459e7578ebbbff12c5bc3c0b..0000000000000000000000000000000000000000
--- a/spaces/CVPR/LIVE/thrust/thrust/system/cuda/vector.h
+++ /dev/null
@@ -1,72 +0,0 @@
-/*
- *  Copyright 2008-2013 NVIDIA Corporation
- *
- *  Licensed under the Apache License, Version 2.0 (the "License");
- *  you may not use this file except in ccudaliance with the License.
- *  You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- *  Unless required by applicable law or agreed to in writing, software
- *  distributed under the License is distributed on an "AS IS" BASIS,
- *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- *  See the License for the specific language governing permissions and
- *  limitations under the License.
- */
-
-/*! \file thrust/system/cuda/vector.h
- *  \brief A dynamically-sizable array of elements which reside in memory available to
- *         Thrust's CUDA system.
- */
-
-#pragma once
-
-#include <thrust/detail/config.h>
-#include <thrust/system/cuda/memory.h>
-#include <thrust/detail/vector_base.h>
-#include <vector>
-
-namespace thrust
-{
-
-// forward declaration of host_vector
-template<typename T, typename Allocator> class host_vector;
-
-namespace cuda_cub
-{
-
-/*! \p cuda_bulk::vector is a container that supports random access to elements,
- *  constant time removal of elements at the end, and linear time insertion
- *  and removal of elements at the beginning or in the middle. The number of
- *  elements in a \p cuda_bulk::vector may vary dynamically; memory management is
- *  automatic. The elements contained in a \p cuda_bulk::vector reside in memory
- *  available to the \p cuda_bulk system.
- *
- *  \tparam T The element type of the \p cuda_bulk::vector.
- *  \tparam Allocator The allocator type of the \p cuda_bulk::vector. Defaults to \p cuda_bulk::allocator.
- *
- *  \see http://www.sgi.com/tech/stl/Vector.html
- *  \see host_vector For the documentation of the complete interface which is
- *                   shared by \p cuda_bulk::vector
- *  \see device_vector
- */
-template<typename T, typename Allocator = allocator<T> >
-using vector = thrust::detail::vector_base<T, Allocator>;
-
-} // end cuda_cub
-
-// alias system::cuda_bulk names at top-level
-namespace cuda
-{
-
-using thrust::cuda_cub::vector;
-
-} // end cuda_bulk
-
-namespace system {
-namespace cuda {
-using thrust::cuda_cub::vector;
-}
-}
-
-} // end thrust
diff --git a/spaces/CanIpleas/gpt2/app.py b/spaces/CanIpleas/gpt2/app.py
deleted file mode 100644
index 4205e03f91904065e1610f7e6c7b2f1de1771184..0000000000000000000000000000000000000000
--- a/spaces/CanIpleas/gpt2/app.py
+++ /dev/null
@@ -1,3 +0,0 @@
-import gradio as gr
-
-gr.Interface.load("models/gpt2").launch()
\ No newline at end of file
diff --git a/spaces/ChallengeHub/Chinese-LangChain/tests/test_gradio_slient.py b/spaces/ChallengeHub/Chinese-LangChain/tests/test_gradio_slient.py
deleted file mode 100644
index 59b2213897676cb356b634994540d2cdf64908f9..0000000000000000000000000000000000000000
--- a/spaces/ChallengeHub/Chinese-LangChain/tests/test_gradio_slient.py
+++ /dev/null
@@ -1,19 +0,0 @@
-import time
-
-import gradio as gra
-
-
-def user_greeting(name):
-    time.sleep(10)
-    return "Hi! " + name + " Welcome to your first Gradio application!😎"
-
-
-# define gradio interface and other parameters
-app = gra.Interface(
-    fn=user_greeting,
-    inputs="text",
-    outputs="text",
-)
-app.launch(
-    server_name='0.0.0.0', server_port=8888, share=False,show_error=True, enable_queue=True
-)
diff --git a/spaces/Comet/txt2im-models/README.md b/spaces/Comet/txt2im-models/README.md
deleted file mode 100644
index 98425b39cb7679f89d39305372e202d058ae31bd..0000000000000000000000000000000000000000
--- a/spaces/Comet/txt2im-models/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Txt2im Models
-emoji: 📉
-colorFrom: yellow
-colorTo: green
-sdk: gradio
-sdk_version: 3.0.19
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Cpp4App/Cpp4App/CDM/run_batch.py b/spaces/Cpp4App/Cpp4App/CDM/run_batch.py
deleted file mode 100644
index 4d836f5992df52e91a7d97a5b90cbb3ccf131e44..0000000000000000000000000000000000000000
--- a/spaces/Cpp4App/Cpp4App/CDM/run_batch.py
+++ /dev/null
@@ -1,146 +0,0 @@
-import multiprocessing
-import glob
-import time
-import json
-from tqdm import tqdm
-from os.path import join as pjoin, exists
-import cv2
-import os
-import shutil
-
-from detect_merge.merge import reassign_ids
-import detect_compo.ip_region_proposal as ip
-from detect_merge.Element import Element
-import detect_compo.lib_ip.ip_preprocessing as pre
-import detect_classify.classification as clf
-import torch
-import numpy as np
-from torchvision import models
-from torch import nn
-import pandas as pd
-import csv
-import re
-import openai
-import random
-from PIL import Image
-
-def resize_height_by_longest_edge(img_path, resize_length=800):
-    org = cv2.imread(img_path)
-    height, width = org.shape[:2]
-    if height > width:
-        return resize_length
-    else:
-        return int(resize_length * (height / width))
-
-
-if __name__ == '__main__':
-
-    input_img_root = "./input_examples/"
-    output_root = "./result_classification"
-    segment_root = '../scrutinizing_alexa/txt'
-
-    if os.path.exists(output_root):
-        shutil.rmtree(output_root)
-    os.makedirs(output_root)
-
-    image_list = os.listdir(input_img_root)
-
-    input_imgs = [input_img_root + image_name for image_name in image_list]
-
-    key_params = {'min-grad': 4, 'ffl-block': 5, 'min-ele-area': 50, 'merge-contained-ele': True,
-                  'max-word-inline-gap': 10, 'max-line-ingraph-gap': 4, 'remove-top-bar': False}
-
-    is_ip = True
-    is_clf = False
-    is_ocr = True
-    is_merge = True
-    is_classification = True
-
-    # Load deep learning models in advance
-    compo_classifier = None
-    if is_ip and is_clf:
-        compo_classifier = {}
-        from cnn.CNN import CNN
-        # compo_classifier['Image'] = CNN('Image')
-        compo_classifier['Elements'] = CNN('Elements')
-        # compo_classifier['Noise'] = CNN('Noise')
-    ocr_model = None
-    if is_ocr:
-        import detect_text.text_detection as text
-
-    # set the range of target inputs' indices
-    num = 0
-    # start_index = 30800  # 61728
-    # end_index = 100000
-
-    img_time_cost_all = []
-    ocr_time_cost_all = []
-    ic_time_cost_all = []
-    ts_time_cost_all = []
-    cd_time_cost_all = []
-
-    resize_by_height = 800
-    for input_img in input_imgs:
-
-        output_data = pd.DataFrame(columns=['screenshot', 'id', 'label', 'index', 'text', 'sentences'])
-
-        this_img_start_time = time.clock()
-
-        resized_height = resize_height_by_longest_edge(input_img, resize_by_height)
-        index = input_img.split('/')[-1][:-4]
-
-        if index != "1-1" and index != "1-2":
-            continue
-
-        if is_ocr:
-            os.makedirs(pjoin(output_root, 'ocr'), exist_ok=True)
-            this_ocr_time_cost = text.text_detection(input_img, output_root, show=False, method='paddle')
-            ocr_time_cost_all.append(this_ocr_time_cost)
-
-        if is_ip:
-            os.makedirs(pjoin(output_root, 'ip'), exist_ok=True)
-            this_cd_time_cost = ip.compo_detection(input_img, output_root, key_params,  classifier=compo_classifier, resize_by_height=resized_height, show=False)
-            cd_time_cost_all.append(this_cd_time_cost)
-
-        if is_merge:
-            import detect_merge.merge as merge
-
-            os.makedirs(pjoin(output_root, 'merge'), exist_ok=True)
-            compo_path = pjoin(output_root, 'ip', str(index) + '.json')
-            ocr_path = pjoin(output_root, 'ocr', str(index) + '.json')
-            board_merge, components_merge = merge.merge(input_img, compo_path, ocr_path, pjoin(output_root, 'merge'), is_remove_top_bar=key_params['remove-top-bar'], show=False)
-            # ic_time_cost_all.append(this_ic_time_cost)
-            # ts_time_cost_all.append(this_ts_time_cost)
-
-        if is_classification:
-
-            os.makedirs(pjoin(output_root, 'classification'), exist_ok=True)
-            merge_path = pjoin(output_root, 'merge', str(index) + '.json')
-            merge_json = json.load(open(merge_path, 'r'))
-            os.makedirs(pjoin(output_root, 'classification', 'GUI'), exist_ok=True)
-            this_time_cost_ic, this_time_cost_ts, output_data, output_board = clf.compo_classification(input_img, output_root, segment_root, merge_json, output_data, resize_by_height=resize_by_height)
-
-            ic_time_cost_all.append(this_time_cost_ic)
-            ts_time_cost_all.append(this_time_cost_ts)
-
-        this_img_time_cost = time.clock() - this_img_start_time
-        img_time_cost_all.append(this_img_time_cost)
-        print("time cost for this image: %2.2f s" % this_img_time_cost)
-
-        num += 1
-
-        if os.path.isfile(output_root + '/output.csv'):
-            output_data.to_csv(output_root + '/output.csv', index=False, mode='a', header=False)
-        else:
-            output_data.to_csv(output_root + '/output.csv', index=False, mode='w')
-
-    avg_ocr_time_cost = sum(ocr_time_cost_all) / len(ocr_time_cost_all)
-    avg_cd_time_cost = sum(cd_time_cost_all) / len(cd_time_cost_all)
-    avg_ic_time_cost = sum(ic_time_cost_all) / len(ic_time_cost_all)
-    avg_ts_time_cost = sum(ts_time_cost_all) / len(ts_time_cost_all)
-    avg_time_cost = sum(img_time_cost_all)/len(img_time_cost_all)
-    print("average text extraction time cost for this app: %2.2f s" % avg_ocr_time_cost)
-    print("average widget detection time cost for this app: %2.2f s" % avg_cd_time_cost)
-    print("average icon classification time cost for this app: %2.2f s" % avg_ic_time_cost)
-    print("average text selection processing time cost for this app: %2.2f s" % avg_ts_time_cost)
-    print("average screenshot processing time cost for this app: %2.2f s" % avg_time_cost)
diff --git a/spaces/CyberHarem/find_my_waifu/README.md b/spaces/CyberHarem/find_my_waifu/README.md
deleted file mode 100644
index c9b0be23c2635790273f5ea37ade61fade30edcd..0000000000000000000000000000000000000000
--- a/spaces/CyberHarem/find_my_waifu/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Find My Waifu
-emoji: 😻
-colorFrom: purple
-colorTo: indigo
-sdk: gradio
-sdk_version: 3.39.0
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/gradio/templates/cdn/assets/index-19bdec54.js b/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/gradio/templates/cdn/assets/index-19bdec54.js
deleted file mode 100644
index d25a227594c4c548a56c2a23c0f026007f50ba4f..0000000000000000000000000000000000000000
--- a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/gradio/templates/cdn/assets/index-19bdec54.js
+++ /dev/null
@@ -1,13264 +0,0 @@
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g.Distance(l,h);var D=v.subtract(h),w=Math.max(0,Math.min(1,g.Dot(l.subtract(h),D)/E)),N=h.add(D.multiplyByFloats(w,w));return g.Distance(l,N)},g}(),C=function(){function g(l,h,v){l===void 0&&(l=0),h===void 0&&(h=0),v===void 0&&(v=0),this._isDirty=!0,this._x=l,this._y=h,this._z=v}return Object.defineProperty(g.prototype,"x",{get:function(){return this._x},set:function(l){this._x=l,this._isDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"y",{get:function(){return this._y},set:function(l){this._y=l,this._isDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"z",{get:function(){return this._z},set:function(l){this._z=l,this._isDirty=!0},enumerable:!1,configurable:!0}),g.prototype.toString=function(){return"{X: "+this._x+" Y:"+this._y+" Z:"+this._z+"}"},g.prototype.getClassName=function(){return"Vector3"},g.prototype.getHashCode=function(){var l=0|this._x;return l=397*(l=397*l^(0|this._y))^(0|this._z)},g.prototype.asArray=function(){var l=[];return this.toArray(l,0),l},g.prototype.toArray=function(l,h){return h===void 0&&(h=0),l[h]=this._x,l[h+1]=this._y,l[h+2]=this._z,this},g.prototype.fromArray=function(l,h){return h===void 0&&(h=0),g.FromArrayToRef(l,h,this),this},g.prototype.toQuaternion=function(){return c.RotationYawPitchRoll(this._y,this._x,this._z)},g.prototype.addInPlace=function(l){return this.addInPlaceFromFloats(l._x,l._y,l._z)},g.prototype.addInPlaceFromFloats=function(l,h,v){return this.x+=l,this.y+=h,this.z+=v,this},g.prototype.add=function(l){return new g(this._x+l._x,this._y+l._y,this._z+l._z)},g.prototype.addToRef=function(l,h){return h.copyFromFloats(this._x+l._x,this._y+l._y,this._z+l._z)},g.prototype.subtractInPlace=function(l){return this.x-=l._x,this.y-=l._y,this.z-=l._z,this},g.prototype.subtract=function(l){return new g(this._x-l._x,this._y-l._y,this._z-l._z)},g.prototype.subtractToRef=function(l,h){return this.subtractFromFloatsToRef(l._x,l._y,l._z,h)},g.prototype.subtractFromFloats=function(l,h,v){return new g(this._x-l,this._y-h,this._z-v)},g.prototype.subtractFromFloatsToRef=function(l,h,v,E){return E.copyFromFloats(this._x-l,this._y-h,this._z-v)},g.prototype.negate=function(){return new g(-this._x,-this._y,-this._z)},g.prototype.negateInPlace=function(){return this.x*=-1,this.y*=-1,this.z*=-1,this},g.prototype.negateToRef=function(l){return l.copyFromFloats(-1*this._x,-1*this._y,-1*this._z)},g.prototype.scaleInPlace=function(l){return this.x*=l,this.y*=l,this.z*=l,this},g.prototype.scale=function(l){return new g(this._x*l,this._y*l,this._z*l)},g.prototype.scaleToRef=function(l,h){return h.copyFromFloats(this._x*l,this._y*l,this._z*l)},g.prototype.scaleAndAddToRef=function(l,h){return h.addInPlaceFromFloats(this._x*l,this._y*l,this._z*l)},g.prototype.projectOnPlane=function(l,h){var v=g.Zero();return this.projectOnPlaneToRef(l,h,v),v},g.prototype.projectOnPlaneToRef=function(l,h,v){var E=l.normal,D=l.d,w=A.Vector3[0];this.subtractToRef(h,w),w.normalize();var N=g.Dot(w,E),I=-(g.Dot(h,E)+D)/N,V=w.scaleInPlace(I);h.addToRef(V,v)},g.prototype.equals=function(l){return l&&this._x===l._x&&this._y===l._y&&this._z===l._z},g.prototype.equalsWithEpsilon=function(l,h){return h===void 0&&(h=_.a),l&&U.a.WithinEpsilon(this._x,l._x,h)&&U.a.WithinEpsilon(this._y,l._y,h)&&U.a.WithinEpsilon(this._z,l._z,h)},g.prototype.equalsToFloats=function(l,h,v){return this._x===l&&this._y===h&&this._z===v},g.prototype.multiplyInPlace=function(l){return this.x*=l._x,this.y*=l._y,this.z*=l._z,this},g.prototype.multiply=function(l){return this.multiplyByFloats(l._x,l._y,l._z)},g.prototype.multiplyToRef=function(l,h){return h.copyFromFloats(this._x*l._x,this._y*l._y,this._z*l._z)},g.prototype.multiplyByFloats=function(l,h,v){return new g(this._x*l,this._y*h,this._z*v)},g.prototype.divide=function(l){return new g(this._x/l._x,this._y/l._y,this._z/l._z)},g.prototype.divideToRef=function(l,h){return h.copyFromFloats(this._x/l._x,this._y/l._y,this._z/l._z)},g.prototype.divideInPlace=function(l){return this.divideToRef(l,this)},g.prototype.minimizeInPlace=function(l){return this.minimizeInPlaceFromFloats(l._x,l._y,l._z)},g.prototype.maximizeInPlace=function(l){return this.maximizeInPlaceFromFloats(l._x,l._y,l._z)},g.prototype.minimizeInPlaceFromFloats=function(l,h,v){return l<this._x&&(this.x=l),h<this._y&&(this.y=h),v<this._z&&(this.z=v),this},g.prototype.maximizeInPlaceFromFloats=function(l,h,v){return l>this._x&&(this.x=l),h>this._y&&(this.y=h),v>this._z&&(this.z=v),this},g.prototype.isNonUniformWithinEpsilon=function(l){var h=Math.abs(this._x),v=Math.abs(this._y);if(!U.a.WithinEpsilon(h,v,l))return!0;var E=Math.abs(this._z);return!U.a.WithinEpsilon(h,E,l)||!U.a.WithinEpsilon(v,E,l)},Object.defineProperty(g.prototype,"isNonUniform",{get:function(){var l=Math.abs(this._x);return l!==Math.abs(this._y)||l!==Math.abs(this._z)},enumerable:!1,configurable:!0}),g.prototype.floor=function(){return new g(Math.floor(this._x),Math.floor(this._y),Math.floor(this._z))},g.prototype.fract=function(){return new g(this._x-Math.floor(this._x),this._y-Math.floor(this._y),this._z-Math.floor(this._z))},g.prototype.length=function(){return Math.sqrt(this._x*this._x+this._y*this._y+this._z*this._z)},g.prototype.lengthSquared=function(){return this._x*this._x+this._y*this._y+this._z*this._z},g.prototype.normalize=function(){return this.normalizeFromLength(this.length())},g.prototype.reorderInPlace=function(l){var h=this;return(l=l.toLowerCase())==="xyz"||(A.Vector3[0].copyFrom(this),["x","y","z"].forEach(function(v,E){h[v]=A.Vector3[0][l[E]]})),this},g.prototype.rotateByQuaternionToRef=function(l,h){return l.toRotationMatrix(A.Matrix[0]),g.TransformCoordinatesToRef(this,A.Matrix[0],h),h},g.prototype.rotateByQuaternionAroundPointToRef=function(l,h,v){return this.subtractToRef(h,A.Vector3[0]),A.Vector3[0].rotateByQuaternionToRef(l,A.Vector3[0]),h.addToRef(A.Vector3[0],v),v},g.prototype.cross=function(l){return g.Cross(this,l)},g.prototype.normalizeFromLength=function(l){return l===0||l===1?this:this.scaleInPlace(1/l)},g.prototype.normalizeToNew=function(){var l=new g(0,0,0);return this.normalizeToRef(l),l},g.prototype.normalizeToRef=function(l){var h=this.length();return h===0||h===1?l.copyFromFloats(this._x,this._y,this._z):this.scaleToRef(1/h,l)},g.prototype.clone=function(){return new g(this._x,this._y,this._z)},g.prototype.copyFrom=function(l){return this.copyFromFloats(l._x,l._y,l._z)},g.prototype.copyFromFloats=function(l,h,v){return this.x=l,this.y=h,this.z=v,this},g.prototype.set=function(l,h,v){return this.copyFromFloats(l,h,v)},g.prototype.setAll=function(l){return this.x=this.y=this.z=l,this},g.GetClipFactor=function(l,h,v,E){var D=g.Dot(l,v)-E;return D/(D-(g.Dot(h,v)-E))},g.GetAngleBetweenVectors=function(l,h,v){var E=l.normalizeToRef(A.Vector3[1]),D=h.normalizeToRef(A.Vector3[2]),w=g.Dot(E,D),N=A.Vector3[3];return g.CrossToRef(E,D,N),g.Dot(N,v)>0?Math.acos(w):-Math.acos(w)},g.FromArray=function(l,h){return h===void 0&&(h=0),new g(l[h],l[h+1],l[h+2])},g.FromFloatArray=function(l,h){return g.FromArray(l,h)},g.FromArrayToRef=function(l,h,v){v.x=l[h],v.y=l[h+1],v.z=l[h+2]},g.FromFloatArrayToRef=function(l,h,v){return g.FromArrayToRef(l,h,v)},g.FromFloatsToRef=function(l,h,v,E){E.copyFromFloats(l,h,v)},g.Zero=function(){return new g(0,0,0)},g.One=function(){return new g(1,1,1)},g.Up=function(){return new g(0,1,0)},Object.defineProperty(g,"UpReadOnly",{get:function(){return g._UpReadOnly},enumerable:!1,configurable:!0}),Object.defineProperty(g,"ZeroReadOnly",{get:function(){return g._ZeroReadOnly},enumerable:!1,configurable:!0}),g.Down=function(){return new g(0,-1,0)},g.Forward=function(l){return l===void 0&&(l=!1),new g(0,0,l?-1:1)},g.Backward=function(l){return l===void 0&&(l=!1),new g(0,0,l?1:-1)},g.Right=function(){return new g(1,0,0)},g.Left=function(){return new g(-1,0,0)},g.TransformCoordinates=function(l,h){var v=g.Zero();return g.TransformCoordinatesToRef(l,h,v),v},g.TransformCoordinatesToRef=function(l,h,v){g.TransformCoordinatesFromFloatsToRef(l._x,l._y,l._z,h,v)},g.TransformCoordinatesFromFloatsToRef=function(l,h,v,E,D){var w=E.m,N=l*w[0]+h*w[4]+v*w[8]+w[12],I=l*w[1]+h*w[5]+v*w[9]+w[13],V=l*w[2]+h*w[6]+v*w[10]+w[14],X=1/(l*w[3]+h*w[7]+v*w[11]+w[15]);D.x=N*X,D.y=I*X,D.z=V*X},g.TransformNormal=function(l,h){var v=g.Zero();return g.TransformNormalToRef(l,h,v),v},g.TransformNormalToRef=function(l,h,v){this.TransformNormalFromFloatsToRef(l._x,l._y,l._z,h,v)},g.TransformNormalFromFloatsToRef=function(l,h,v,E,D){var w=E.m;D.x=l*w[0]+h*w[4]+v*w[8],D.y=l*w[1]+h*w[5]+v*w[9],D.z=l*w[2]+h*w[6]+v*w[10]},g.CatmullRom=function(l,h,v,E,D){var w=D*D,N=D*w;return new g(.5*(2*h._x+(-l._x+v._x)*D+(2*l._x-5*h._x+4*v._x-E._x)*w+(-l._x+3*h._x-3*v._x+E._x)*N),.5*(2*h._y+(-l._y+v._y)*D+(2*l._y-5*h._y+4*v._y-E._y)*w+(-l._y+3*h._y-3*v._y+E._y)*N),.5*(2*h._z+(-l._z+v._z)*D+(2*l._z-5*h._z+4*v._z-E._z)*w+(-l._z+3*h._z-3*v._z+E._z)*N))},g.Clamp=function(l,h,v){var E=new g;return g.ClampToRef(l,h,v,E),E},g.ClampToRef=function(l,h,v,E){var D=l._x;D=(D=D>v._x?v._x:D)<h._x?h._x:D;var w=l._y;w=(w=w>v._y?v._y:w)<h._y?h._y:w;var N=l._z;N=(N=N>v._z?v._z:N)<h._z?h._z:N,E.copyFromFloats(D,w,N)},g.CheckExtends=function(l,h,v){h.minimizeInPlace(l),v.maximizeInPlace(l)},g.Hermite=function(l,h,v,E,D){var w=D*D,N=D*w,I=2*N-3*w+1,V=-2*N+3*w,X=N-2*w+D,j=N-w;return new g(l._x*I+v._x*V+h._x*X+E._x*j,l._y*I+v._y*V+h._y*X+E._y*j,l._z*I+v._z*V+h._z*X+E._z*j)},g.Lerp=function(l,h,v){var E=new g(0,0,0);return g.LerpToRef(l,h,v,E),E},g.LerpToRef=function(l,h,v,E){E.x=l._x+(h._x-l._x)*v,E.y=l._y+(h._y-l._y)*v,E.z=l._z+(h._z-l._z)*v},g.Dot=function(l,h){return l._x*h._x+l._y*h._y+l._z*h._z},g.Cross=function(l,h){var v=g.Zero();return g.CrossToRef(l,h,v),v},g.CrossToRef=function(l,h,v){var E=l._y*h._z-l._z*h._y,D=l._z*h._x-l._x*h._z,w=l._x*h._y-l._y*h._x;v.copyFromFloats(E,D,w)},g.Normalize=function(l){var h=g.Zero();return g.NormalizeToRef(l,h),h},g.NormalizeToRef=function(l,h){l.normalizeToRef(h)},g.Project=function(l,h,v,E){var D=new g;return g.ProjectToRef(l,h,v,E,D),D},g.ProjectToRef=function(l,h,v,E,D){var w=E.width,N=E.height,I=E.x,V=E.y,X=A.Matrix[1];T.FromValuesToRef(w/2,0,0,0,0,-N/2,0,0,0,0,.5,0,I+w/2,N/2+V,.5,1,X);var j=A.Matrix[0];return h.multiplyToRef(v,j),j.multiplyToRef(X,j),g.TransformCoordinatesToRef(l,j,D),D},g._UnprojectFromInvertedMatrixToRef=function(l,h,v){g.TransformCoordinatesToRef(l,h,v);var E=h.m,D=l._x*E[3]+l._y*E[7]+l._z*E[11]+E[15];U.a.WithinEpsilon(D,1)&&v.scaleInPlace(1/D)},g.UnprojectFromTransform=function(l,h,v,E,D){var w=A.Matrix[0];E.multiplyToRef(D,w),w.invert(),l.x=l._x/h*2-1,l.y=-(l._y/v*2-1);var N=new g;return g._UnprojectFromInvertedMatrixToRef(l,w,N),N},g.Unproject=function(l,h,v,E,D,w){var N=g.Zero();return g.UnprojectToRef(l,h,v,E,D,w,N),N},g.UnprojectToRef=function(l,h,v,E,D,w,N){g.UnprojectFloatsToRef(l._x,l._y,l._z,h,v,E,D,w,N)},g.UnprojectFloatsToRef=function(l,h,v,E,D,w,N,I,V){var X=A.Matrix[0];w.multiplyToRef(N,X),X.multiplyToRef(I,X),X.invert();var j=A.Vector3[0];j.x=l/E*2-1,j.y=-(h/D*2-1),j.z=2*v-1,g._UnprojectFromInvertedMatrixToRef(j,X,V)},g.Minimize=function(l,h){var v=l.clone();return v.minimizeInPlace(h),v},g.Maximize=function(l,h){var v=l.clone();return v.maximizeInPlace(h),v},g.Distance=function(l,h){return Math.sqrt(g.DistanceSquared(l,h))},g.DistanceSquared=function(l,h){var v=l._x-h._x,E=l._y-h._y,D=l._z-h._z;return v*v+E*E+D*D},g.Center=function(l,h){var v=l.add(h);return v.scaleInPlace(.5),v},g.RotationFromAxis=function(l,h,v){var E=g.Zero();return g.RotationFromAxisToRef(l,h,v,E),E},g.RotationFromAxisToRef=function(l,h,v,E){var D=A.Quaternion[0];c.RotationQuaternionFromAxisToRef(l,h,v,D),D.toEulerAnglesToRef(E)},g._UpReadOnly=g.Up(),g._ZeroReadOnly=g.Zero(),g}(),m=function(){function g(l,h,v,E){this.x=l,this.y=h,this.z=v,this.w=E}return g.prototype.toString=function(){return"{X: "+this.x+" Y:"+this.y+" Z:"+this.z+" W:"+this.w+"}"},g.prototype.getClassName=function(){return"Vector4"},g.prototype.getHashCode=function(){var l=0|this.x;return l=397*(l=397*(l=397*l^(0|this.y))^(0|this.z))^(0|this.w)},g.prototype.asArray=function(){var l=new Array;return this.toArray(l,0),l},g.prototype.toArray=function(l,h){return h===void 0&&(h=0),l[h]=this.x,l[h+1]=this.y,l[h+2]=this.z,l[h+3]=this.w,this},g.prototype.fromArray=function(l,h){return h===void 0&&(h=0),g.FromArrayToRef(l,h,this),this},g.prototype.addInPlace=function(l){return this.x+=l.x,this.y+=l.y,this.z+=l.z,this.w+=l.w,this},g.prototype.add=function(l){return new g(this.x+l.x,this.y+l.y,this.z+l.z,this.w+l.w)},g.prototype.addToRef=function(l,h){return h.x=this.x+l.x,h.y=this.y+l.y,h.z=this.z+l.z,h.w=this.w+l.w,this},g.prototype.subtractInPlace=function(l){return this.x-=l.x,this.y-=l.y,this.z-=l.z,this.w-=l.w,this},g.prototype.subtract=function(l){return new g(this.x-l.x,this.y-l.y,this.z-l.z,this.w-l.w)},g.prototype.subtractToRef=function(l,h){return h.x=this.x-l.x,h.y=this.y-l.y,h.z=this.z-l.z,h.w=this.w-l.w,this},g.prototype.subtractFromFloats=function(l,h,v,E){return new g(this.x-l,this.y-h,this.z-v,this.w-E)},g.prototype.subtractFromFloatsToRef=function(l,h,v,E,D){return D.x=this.x-l,D.y=this.y-h,D.z=this.z-v,D.w=this.w-E,this},g.prototype.negate=function(){return new g(-this.x,-this.y,-this.z,-this.w)},g.prototype.negateInPlace=function(){return this.x*=-1,this.y*=-1,this.z*=-1,this.w*=-1,this},g.prototype.negateToRef=function(l){return l.copyFromFloats(-1*this.x,-1*this.y,-1*this.z,-1*this.w)},g.prototype.scaleInPlace=function(l){return this.x*=l,this.y*=l,this.z*=l,this.w*=l,this},g.prototype.scale=function(l){return new g(this.x*l,this.y*l,this.z*l,this.w*l)},g.prototype.scaleToRef=function(l,h){return h.x=this.x*l,h.y=this.y*l,h.z=this.z*l,h.w=this.w*l,this},g.prototype.scaleAndAddToRef=function(l,h){return h.x+=this.x*l,h.y+=this.y*l,h.z+=this.z*l,h.w+=this.w*l,this},g.prototype.equals=function(l){return l&&this.x===l.x&&this.y===l.y&&this.z===l.z&&this.w===l.w},g.prototype.equalsWithEpsilon=function(l,h){return h===void 0&&(h=_.a),l&&U.a.WithinEpsilon(this.x,l.x,h)&&U.a.WithinEpsilon(this.y,l.y,h)&&U.a.WithinEpsilon(this.z,l.z,h)&&U.a.WithinEpsilon(this.w,l.w,h)},g.prototype.equalsToFloats=function(l,h,v,E){return this.x===l&&this.y===h&&this.z===v&&this.w===E},g.prototype.multiplyInPlace=function(l){return this.x*=l.x,this.y*=l.y,this.z*=l.z,this.w*=l.w,this},g.prototype.multiply=function(l){return new g(this.x*l.x,this.y*l.y,this.z*l.z,this.w*l.w)},g.prototype.multiplyToRef=function(l,h){return h.x=this.x*l.x,h.y=this.y*l.y,h.z=this.z*l.z,h.w=this.w*l.w,this},g.prototype.multiplyByFloats=function(l,h,v,E){return new g(this.x*l,this.y*h,this.z*v,this.w*E)},g.prototype.divide=function(l){return new g(this.x/l.x,this.y/l.y,this.z/l.z,this.w/l.w)},g.prototype.divideToRef=function(l,h){return h.x=this.x/l.x,h.y=this.y/l.y,h.z=this.z/l.z,h.w=this.w/l.w,this},g.prototype.divideInPlace=function(l){return this.divideToRef(l,this)},g.prototype.minimizeInPlace=function(l){return l.x<this.x&&(this.x=l.x),l.y<this.y&&(this.y=l.y),l.z<this.z&&(this.z=l.z),l.w<this.w&&(this.w=l.w),this},g.prototype.maximizeInPlace=function(l){return l.x>this.x&&(this.x=l.x),l.y>this.y&&(this.y=l.y),l.z>this.z&&(this.z=l.z),l.w>this.w&&(this.w=l.w),this},g.prototype.floor=function(){return new g(Math.floor(this.x),Math.floor(this.y),Math.floor(this.z),Math.floor(this.w))},g.prototype.fract=function(){return new g(this.x-Math.floor(this.x),this.y-Math.floor(this.y),this.z-Math.floor(this.z),this.w-Math.floor(this.w))},g.prototype.length=function(){return Math.sqrt(this.x*this.x+this.y*this.y+this.z*this.z+this.w*this.w)},g.prototype.lengthSquared=function(){return this.x*this.x+this.y*this.y+this.z*this.z+this.w*this.w},g.prototype.normalize=function(){var l=this.length();return l===0?this:this.scaleInPlace(1/l)},g.prototype.toVector3=function(){return new C(this.x,this.y,this.z)},g.prototype.clone=function(){return new g(this.x,this.y,this.z,this.w)},g.prototype.copyFrom=function(l){return this.x=l.x,this.y=l.y,this.z=l.z,this.w=l.w,this},g.prototype.copyFromFloats=function(l,h,v,E){return this.x=l,this.y=h,this.z=v,this.w=E,this},g.prototype.set=function(l,h,v,E){return this.copyFromFloats(l,h,v,E)},g.prototype.setAll=function(l){return this.x=this.y=this.z=this.w=l,this},g.FromArray=function(l,h){return h||(h=0),new g(l[h],l[h+1],l[h+2],l[h+3])},g.FromArrayToRef=function(l,h,v){v.x=l[h],v.y=l[h+1],v.z=l[h+2],v.w=l[h+3]},g.FromFloatArrayToRef=function(l,h,v){g.FromArrayToRef(l,h,v)},g.FromFloatsToRef=function(l,h,v,E,D){D.x=l,D.y=h,D.z=v,D.w=E},g.Zero=function(){return new g(0,0,0,0)},g.One=function(){return new g(1,1,1,1)},g.Normalize=function(l){var h=g.Zero();return g.NormalizeToRef(l,h),h},g.NormalizeToRef=function(l,h){h.copyFrom(l),h.normalize()},g.Minimize=function(l,h){var v=l.clone();return v.minimizeInPlace(h),v},g.Maximize=function(l,h){var v=l.clone();return v.maximizeInPlace(h),v},g.Distance=function(l,h){return Math.sqrt(g.DistanceSquared(l,h))},g.DistanceSquared=function(l,h){var v=l.x-h.x,E=l.y-h.y,D=l.z-h.z,w=l.w-h.w;return v*v+E*E+D*D+w*w},g.Center=function(l,h){var v=l.add(h);return v.scaleInPlace(.5),v},g.TransformNormal=function(l,h){var v=g.Zero();return g.TransformNormalToRef(l,h,v),v},g.TransformNormalToRef=function(l,h,v){var E=h.m,D=l.x*E[0]+l.y*E[4]+l.z*E[8],w=l.x*E[1]+l.y*E[5]+l.z*E[9],N=l.x*E[2]+l.y*E[6]+l.z*E[10];v.x=D,v.y=w,v.z=N,v.w=l.w},g.TransformNormalFromFloatsToRef=function(l,h,v,E,D,w){var N=D.m;w.x=l*N[0]+h*N[4]+v*N[8],w.y=l*N[1]+h*N[5]+v*N[9],w.z=l*N[2]+h*N[6]+v*N[10],w.w=E},g.FromVector3=function(l,h){return h===void 0&&(h=0),new g(l._x,l._y,l._z,h)},g}(),c=function(){function g(l,h,v,E){l===void 0&&(l=0),h===void 0&&(h=0),v===void 0&&(v=0),E===void 0&&(E=1),this._isDirty=!0,this._x=l,this._y=h,this._z=v,this._w=E}return Object.defineProperty(g.prototype,"x",{get:function(){return this._x},set:function(l){this._x=l,this._isDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"y",{get:function(){return this._y},set:function(l){this._y=l,this._isDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"z",{get:function(){return this._z},set:function(l){this._z=l,this._isDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"w",{get:function(){return this._w},set:function(l){this._w=l,this._isDirty=!0},enumerable:!1,configurable:!0}),g.prototype.toString=function(){return"{X: "+this._x+" Y:"+this._y+" Z:"+this._z+" W:"+this._w+"}"},g.prototype.getClassName=function(){return"Quaternion"},g.prototype.getHashCode=function(){var l=0|this._x;return l=397*(l=397*(l=397*l^(0|this._y))^(0|this._z))^(0|this._w)},g.prototype.asArray=function(){return[this._x,this._y,this._z,this._w]},g.prototype.equals=function(l){return l&&this._x===l._x&&this._y===l._y&&this._z===l._z&&this._w===l._w},g.prototype.equalsWithEpsilon=function(l,h){return h===void 0&&(h=_.a),l&&U.a.WithinEpsilon(this._x,l._x,h)&&U.a.WithinEpsilon(this._y,l._y,h)&&U.a.WithinEpsilon(this._z,l._z,h)&&U.a.WithinEpsilon(this._w,l._w,h)},g.prototype.clone=function(){return new g(this._x,this._y,this._z,this._w)},g.prototype.copyFrom=function(l){return this.x=l._x,this.y=l._y,this.z=l._z,this.w=l._w,this},g.prototype.copyFromFloats=function(l,h,v,E){return this.x=l,this.y=h,this.z=v,this.w=E,this},g.prototype.set=function(l,h,v,E){return this.copyFromFloats(l,h,v,E)},g.prototype.add=function(l){return new g(this._x+l._x,this._y+l._y,this._z+l._z,this._w+l._w)},g.prototype.addInPlace=function(l){return this._x+=l._x,this._y+=l._y,this._z+=l._z,this._w+=l._w,this},g.prototype.subtract=function(l){return new g(this._x-l._x,this._y-l._y,this._z-l._z,this._w-l._w)},g.prototype.scale=function(l){return new g(this._x*l,this._y*l,this._z*l,this._w*l)},g.prototype.scaleToRef=function(l,h){return h.x=this._x*l,h.y=this._y*l,h.z=this._z*l,h.w=this._w*l,this},g.prototype.scaleInPlace=function(l){return this.x*=l,this.y*=l,this.z*=l,this.w*=l,this},g.prototype.scaleAndAddToRef=function(l,h){return h.x+=this._x*l,h.y+=this._y*l,h.z+=this._z*l,h.w+=this._w*l,this},g.prototype.multiply=function(l){var h=new g(0,0,0,1);return this.multiplyToRef(l,h),h},g.prototype.multiplyToRef=function(l,h){var v=this._x*l._w+this._y*l._z-this._z*l._y+this._w*l._x,E=-this._x*l._z+this._y*l._w+this._z*l._x+this._w*l._y,D=this._x*l._y-this._y*l._x+this._z*l._w+this._w*l._z,w=-this._x*l._x-this._y*l._y-this._z*l._z+this._w*l._w;return h.copyFromFloats(v,E,D,w),this},g.prototype.multiplyInPlace=function(l){return this.multiplyToRef(l,this),this},g.prototype.conjugateToRef=function(l){return l.copyFromFloats(-this._x,-this._y,-this._z,this._w),this},g.prototype.conjugateInPlace=function(){return this.x*=-1,this.y*=-1,this.z*=-1,this},g.prototype.conjugate=function(){return new g(-this._x,-this._y,-this._z,this._w)},g.prototype.length=function(){return Math.sqrt(this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w)},g.prototype.normalize=function(){var l=this.length();if(l===0)return this;var h=1/l;return this.x*=h,this.y*=h,this.z*=h,this.w*=h,this},g.prototype.toEulerAngles=function(l){var h=C.Zero();return this.toEulerAnglesToRef(h),h},g.prototype.toEulerAnglesToRef=function(l){var h=this._z,v=this._x,E=this._y,D=this._w,w=D*D,N=h*h,I=v*v,V=E*E,X=E*h-v*D;return X<-.4999999?(l.y=2*Math.atan2(E,D),l.x=Math.PI/2,l.z=0):X>.4999999?(l.y=2*Math.atan2(E,D),l.x=-Math.PI/2,l.z=0):(l.z=Math.atan2(2*(v*E+h*D),-N-I+V+w),l.x=Math.asin(-2*(h*E-v*D)),l.y=Math.atan2(2*(h*v+E*D),N-I-V+w)),this},g.prototype.toRotationMatrix=function(l){return T.FromQuaternionToRef(this,l),this},g.prototype.fromRotationMatrix=function(l){return g.FromRotationMatrixToRef(l,this),this},g.FromRotationMatrix=function(l){var h=new g;return g.FromRotationMatrixToRef(l,h),h},g.FromRotationMatrixToRef=function(l,h){var v,E=l.m,D=E[0],w=E[4],N=E[8],I=E[1],V=E[5],X=E[9],j=E[2],ne=E[6],te=E[10],de=D+V+te;de>0?(v=.5/Math.sqrt(de+1),h.w=.25/v,h.x=(ne-X)*v,h.y=(N-j)*v,h.z=(I-w)*v):D>V&&D>te?(v=2*Math.sqrt(1+D-V-te),h.w=(ne-X)/v,h.x=.25*v,h.y=(w+I)/v,h.z=(N+j)/v):V>te?(v=2*Math.sqrt(1+V-D-te),h.w=(N-j)/v,h.x=(w+I)/v,h.y=.25*v,h.z=(X+ne)/v):(v=2*Math.sqrt(1+te-D-V),h.w=(I-w)/v,h.x=(N+j)/v,h.y=(X+ne)/v,h.z=.25*v)},g.Dot=function(l,h){return l._x*h._x+l._y*h._y+l._z*h._z+l._w*h._w},g.AreClose=function(l,h){return g.Dot(l,h)>=0},g.Zero=function(){return new g(0,0,0,0)},g.Inverse=function(l){return new g(-l._x,-l._y,-l._z,l._w)},g.InverseToRef=function(l,h){return h.set(-l._x,-l._y,-l._z,l._w),h},g.Identity=function(){return new g(0,0,0,1)},g.IsIdentity=function(l){return l&&l._x===0&&l._y===0&&l._z===0&&l._w===1},g.RotationAxis=function(l,h){return g.RotationAxisToRef(l,h,new g)},g.RotationAxisToRef=function(l,h,v){var E=Math.sin(h/2);return l.normalize(),v.w=Math.cos(h/2),v.x=l._x*E,v.y=l._y*E,v.z=l._z*E,v},g.FromArray=function(l,h){return h||(h=0),new g(l[h],l[h+1],l[h+2],l[h+3])},g.FromArrayToRef=function(l,h,v){v.x=l[h],v.y=l[h+1],v.z=l[h+2],v.w=l[h+3]},g.FromEulerAngles=function(l,h,v){var E=new g;return g.RotationYawPitchRollToRef(h,l,v,E),E},g.FromEulerAnglesToRef=function(l,h,v,E){return g.RotationYawPitchRollToRef(h,l,v,E),E},g.FromEulerVector=function(l){var h=new g;return g.RotationYawPitchRollToRef(l._y,l._x,l._z,h),h},g.FromEulerVectorToRef=function(l,h){return g.RotationYawPitchRollToRef(l._y,l._x,l._z,h),h},g.RotationYawPitchRoll=function(l,h,v){var E=new g;return g.RotationYawPitchRollToRef(l,h,v,E),E},g.RotationYawPitchRollToRef=function(l,h,v,E){var D=.5*v,w=.5*h,N=.5*l,I=Math.sin(D),V=Math.cos(D),X=Math.sin(w),j=Math.cos(w),ne=Math.sin(N),te=Math.cos(N);E.x=te*X*V+ne*j*I,E.y=ne*j*V-te*X*I,E.z=te*j*I-ne*X*V,E.w=te*j*V+ne*X*I},g.RotationAlphaBetaGamma=function(l,h,v){var E=new g;return g.RotationAlphaBetaGammaToRef(l,h,v,E),E},g.RotationAlphaBetaGammaToRef=function(l,h,v,E){var D=.5*(v+l),w=.5*(v-l),N=.5*h;E.x=Math.cos(w)*Math.sin(N),E.y=Math.sin(w)*Math.sin(N),E.z=Math.sin(D)*Math.cos(N),E.w=Math.cos(D)*Math.cos(N)},g.RotationQuaternionFromAxis=function(l,h,v){var E=new g(0,0,0,0);return g.RotationQuaternionFromAxisToRef(l,h,v,E),E},g.RotationQuaternionFromAxisToRef=function(l,h,v,E){var D=A.Matrix[0];T.FromXYZAxesToRef(l.normalize(),h.normalize(),v.normalize(),D),g.FromRotationMatrixToRef(D,E)},g.Slerp=function(l,h,v){var E=g.Identity();return g.SlerpToRef(l,h,v,E),E},g.SlerpToRef=function(l,h,v,E){var D,w,N=l._x*h._x+l._y*h._y+l._z*h._z+l._w*h._w,I=!1;if(N<0&&(I=!0,N=-N),N>.999999)w=1-v,D=I?-v:v;else{var V=Math.acos(N),X=1/Math.sin(V);w=Math.sin((1-v)*V)*X,D=I?-Math.sin(v*V)*X:Math.sin(v*V)*X}E.x=w*l._x+D*h._x,E.y=w*l._y+D*h._y,E.z=w*l._z+D*h._z,E.w=w*l._w+D*h._w},g.Hermite=function(l,h,v,E,D){var w=D*D,N=D*w,I=2*N-3*w+1,V=-2*N+3*w,X=N-2*w+D,j=N-w;return new g(l._x*I+v._x*V+h._x*X+E._x*j,l._y*I+v._y*V+h._y*X+E._y*j,l._z*I+v._z*V+h._z*X+E._z*j,l._w*I+v._w*V+h._w*X+E._w*j)},g}(),T=function(){function g(){this._isIdentity=!1,this._isIdentityDirty=!0,this._isIdentity3x2=!0,this._isIdentity3x2Dirty=!0,this.updateFlag=-1,M.a.MatrixTrackPrecisionChange&&M.a.MatrixTrackedMatrices.push(this),this._m=new M.a.MatrixCurrentType(16),this._updateIdentityStatus(!1)}return Object.defineProperty(g,"Use64Bits",{get:function(){return M.a.MatrixUse64Bits},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"m",{get:function(){return this._m},enumerable:!1,configurable:!0}),g.prototype._markAsUpdated=function(){this.updateFlag=g._updateFlagSeed++,this._isIdentity=!1,this._isIdentity3x2=!1,this._isIdentityDirty=!0,this._isIdentity3x2Dirty=!0},g.prototype._updateIdentityStatus=function(l,h,v,E){h===void 0&&(h=!1),v===void 0&&(v=!1),E===void 0&&(E=!0),this.updateFlag=g._updateFlagSeed++,this._isIdentity=l,this._isIdentity3x2=l||v,this._isIdentityDirty=!this._isIdentity&&h,this._isIdentity3x2Dirty=!this._isIdentity3x2&&E},g.prototype.isIdentity=function(){if(this._isIdentityDirty){this._isIdentityDirty=!1;var l=this._m;this._isIdentity=l[0]===1&&l[1]===0&&l[2]===0&&l[3]===0&&l[4]===0&&l[5]===1&&l[6]===0&&l[7]===0&&l[8]===0&&l[9]===0&&l[10]===1&&l[11]===0&&l[12]===0&&l[13]===0&&l[14]===0&&l[15]===1}return this._isIdentity},g.prototype.isIdentityAs3x2=function(){return this._isIdentity3x2Dirty&&(this._isIdentity3x2Dirty=!1,this._m[0]!==1||this._m[5]!==1||this._m[15]!==1||this._m[1]!==0||this._m[2]!==0||this._m[3]!==0||this._m[4]!==0||this._m[6]!==0||this._m[7]!==0||this._m[8]!==0||this._m[9]!==0||this._m[10]!==0||this._m[11]!==0||this._m[12]!==0||this._m[13]!==0||this._m[14]!==0?this._isIdentity3x2=!1:this._isIdentity3x2=!0),this._isIdentity3x2},g.prototype.determinant=function(){if(this._isIdentity===!0)return 1;var l=this._m,h=l[0],v=l[1],E=l[2],D=l[3],w=l[4],N=l[5],I=l[6],V=l[7],X=l[8],j=l[9],ne=l[10],te=l[11],de=l[12],pe=l[13],ae=l[14],ee=l[15],K=ne*ee-ae*te,$=j*ee-pe*te,L=j*ae-pe*ne,G=X*ee-de*te,Q=X*ae-ne*de,oe=X*pe-de*j;return h*+(N*K-I*$+V*L)+v*-(w*K-I*G+V*Q)+E*+(w*$-N*G+V*oe)+D*-(w*L-N*Q+I*oe)},g.prototype.toArray=function(){return this._m},g.prototype.asArray=function(){return this._m},g.prototype.invert=function(){return this.invertToRef(this),this},g.prototype.reset=function(){return g.FromValuesToRef(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,this),this._updateIdentityStatus(!1),this},g.prototype.add=function(l){var h=new g;return this.addToRef(l,h),h},g.prototype.addToRef=function(l,h){for(var v=this._m,E=h._m,D=l.m,w=0;w<16;w++)E[w]=v[w]+D[w];return h._markAsUpdated(),this},g.prototype.addToSelf=function(l){for(var h=this._m,v=l.m,E=0;E<16;E++)h[E]+=v[E];return this._markAsUpdated(),this},g.prototype.invertToRef=function(l){if(this._isIdentity===!0)return g.IdentityToRef(l),this;var h=this._m,v=h[0],E=h[1],D=h[2],w=h[3],N=h[4],I=h[5],V=h[6],X=h[7],j=h[8],ne=h[9],te=h[10],de=h[11],pe=h[12],ae=h[13],ee=h[14],K=h[15],$=te*K-ee*de,L=ne*K-ae*de,G=ne*ee-ae*te,Q=j*K-pe*de,oe=j*ee-te*pe,re=j*ae-pe*ne,Y=+(I*$-V*L+X*G),k=-(N*$-V*Q+X*oe),H=+(N*L-I*Q+X*re),Z=-(N*G-I*oe+V*re),W=v*Y+E*k+D*H+w*Z;if(W===0)return l.copyFrom(this),this;var q=1/W,he=V*K-ee*X,ge=I*K-ae*X,me=I*ee-ae*V,_e=N*K-pe*X,be=N*ee-pe*V,Pe=N*ae-pe*I,ye=V*de-te*X,Be=I*de-ne*X,ke=I*te-ne*V,We=N*de-j*X,je=N*te-j*V,He=N*ne-j*I,qe=-(E*$-D*L+w*G),Ge=+(v*$-D*Q+w*oe),nt=-(v*L-E*Q+w*re),$e=+(v*G-E*oe+D*re),ct=+(E*he-D*ge+w*me),st=-(v*he-D*_e+w*be),mt=+(v*ge-E*_e+w*Pe),St=-(v*me-E*be+D*Pe),wt=-(E*ye-D*Be+w*ke),It=+(v*ye-D*We+w*je),Pt=-(v*Be-E*We+w*He),Ot=+(v*ke-E*je+D*He);return g.FromValuesToRef(Y*q,qe*q,ct*q,wt*q,k*q,Ge*q,st*q,It*q,H*q,nt*q,mt*q,Pt*q,Z*q,$e*q,St*q,Ot*q,l),this},g.prototype.addAtIndex=function(l,h){return this._m[l]+=h,this._markAsUpdated(),this},g.prototype.multiplyAtIndex=function(l,h){return this._m[l]*=h,this._markAsUpdated(),this},g.prototype.setTranslationFromFloats=function(l,h,v){return this._m[12]=l,this._m[13]=h,this._m[14]=v,this._markAsUpdated(),this},g.prototype.addTranslationFromFloats=function(l,h,v){return this._m[12]+=l,this._m[13]+=h,this._m[14]+=v,this._markAsUpdated(),this},g.prototype.setTranslation=function(l){return this.setTranslationFromFloats(l._x,l._y,l._z)},g.prototype.getTranslation=function(){return new C(this._m[12],this._m[13],this._m[14])},g.prototype.getTranslationToRef=function(l){return l.x=this._m[12],l.y=this._m[13],l.z=this._m[14],this},g.prototype.removeRotationAndScaling=function(){var l=this.m;return g.FromValuesToRef(1,0,0,0,0,1,0,0,0,0,1,0,l[12],l[13],l[14],l[15],this),this._updateIdentityStatus(l[12]===0&&l[13]===0&&l[14]===0&&l[15]===1),this},g.prototype.multiply=function(l){var h=new g;return this.multiplyToRef(l,h),h},g.prototype.copyFrom=function(l){l.copyToArray(this._m);var h=l;return this._updateIdentityStatus(h._isIdentity,h._isIdentityDirty,h._isIdentity3x2,h._isIdentity3x2Dirty),this},g.prototype.copyToArray=function(l,h){h===void 0&&(h=0);var v=this._m;return l[h]=v[0],l[h+1]=v[1],l[h+2]=v[2],l[h+3]=v[3],l[h+4]=v[4],l[h+5]=v[5],l[h+6]=v[6],l[h+7]=v[7],l[h+8]=v[8],l[h+9]=v[9],l[h+10]=v[10],l[h+11]=v[11],l[h+12]=v[12],l[h+13]=v[13],l[h+14]=v[14],l[h+15]=v[15],this},g.prototype.multiplyToRef=function(l,h){return this._isIdentity?(h.copyFrom(l),this):l._isIdentity?(h.copyFrom(this),this):(this.multiplyToArray(l,h._m,0),h._markAsUpdated(),this)},g.prototype.multiplyToArray=function(l,h,v){var E=this._m,D=l.m,w=E[0],N=E[1],I=E[2],V=E[3],X=E[4],j=E[5],ne=E[6],te=E[7],de=E[8],pe=E[9],ae=E[10],ee=E[11],K=E[12],$=E[13],L=E[14],G=E[15],Q=D[0],oe=D[1],re=D[2],Y=D[3],k=D[4],H=D[5],Z=D[6],W=D[7],q=D[8],he=D[9],ge=D[10],me=D[11],_e=D[12],be=D[13],Pe=D[14],ye=D[15];return h[v]=w*Q+N*k+I*q+V*_e,h[v+1]=w*oe+N*H+I*he+V*be,h[v+2]=w*re+N*Z+I*ge+V*Pe,h[v+3]=w*Y+N*W+I*me+V*ye,h[v+4]=X*Q+j*k+ne*q+te*_e,h[v+5]=X*oe+j*H+ne*he+te*be,h[v+6]=X*re+j*Z+ne*ge+te*Pe,h[v+7]=X*Y+j*W+ne*me+te*ye,h[v+8]=de*Q+pe*k+ae*q+ee*_e,h[v+9]=de*oe+pe*H+ae*he+ee*be,h[v+10]=de*re+pe*Z+ae*ge+ee*Pe,h[v+11]=de*Y+pe*W+ae*me+ee*ye,h[v+12]=K*Q+$*k+L*q+G*_e,h[v+13]=K*oe+$*H+L*he+G*be,h[v+14]=K*re+$*Z+L*ge+G*Pe,h[v+15]=K*Y+$*W+L*me+G*ye,this},g.prototype.equals=function(l){var h=l;if(!h)return!1;if((this._isIdentity||h._isIdentity)&&!this._isIdentityDirty&&!h._isIdentityDirty)return this._isIdentity&&h._isIdentity;var v=this.m,E=h.m;return v[0]===E[0]&&v[1]===E[1]&&v[2]===E[2]&&v[3]===E[3]&&v[4]===E[4]&&v[5]===E[5]&&v[6]===E[6]&&v[7]===E[7]&&v[8]===E[8]&&v[9]===E[9]&&v[10]===E[10]&&v[11]===E[11]&&v[12]===E[12]&&v[13]===E[13]&&v[14]===E[14]&&v[15]===E[15]},g.prototype.clone=function(){var l=new g;return l.copyFrom(this),l},g.prototype.getClassName=function(){return"Matrix"},g.prototype.getHashCode=function(){for(var l=0|this._m[0],h=1;h<16;h++)l=397*l^(0|this._m[h]);return l},g.prototype.decompose=function(l,h,v){if(this._isIdentity)return v&&v.setAll(0),l&&l.setAll(1),h&&h.copyFromFloats(0,0,0,1),!0;var E=this._m;if(v&&v.copyFromFloats(E[12],E[13],E[14]),(l=l||A.Vector3[0]).x=Math.sqrt(E[0]*E[0]+E[1]*E[1]+E[2]*E[2]),l.y=Math.sqrt(E[4]*E[4]+E[5]*E[5]+E[6]*E[6]),l.z=Math.sqrt(E[8]*E[8]+E[9]*E[9]+E[10]*E[10]),this.determinant()<=0&&(l.y*=-1),l._x===0||l._y===0||l._z===0)return h&&h.copyFromFloats(0,0,0,1),!1;if(h){var D=1/l._x,w=1/l._y,N=1/l._z;g.FromValuesToRef(E[0]*D,E[1]*D,E[2]*D,0,E[4]*w,E[5]*w,E[6]*w,0,E[8]*N,E[9]*N,E[10]*N,0,0,0,0,1,A.Matrix[0]),c.FromRotationMatrixToRef(A.Matrix[0],h)}return!0},g.prototype.getRow=function(l){if(l<0||l>3)return null;var h=4*l;return new m(this._m[h+0],this._m[h+1],this._m[h+2],this._m[h+3])},g.prototype.setRow=function(l,h){return this.setRowFromFloats(l,h.x,h.y,h.z,h.w)},g.prototype.transpose=function(){return g.Transpose(this)},g.prototype.transposeToRef=function(l){return g.TransposeToRef(this,l),this},g.prototype.setRowFromFloats=function(l,h,v,E,D){if(l<0||l>3)return this;var w=4*l;return this._m[w+0]=h,this._m[w+1]=v,this._m[w+2]=E,this._m[w+3]=D,this._markAsUpdated(),this},g.prototype.scale=function(l){var h=new g;return this.scaleToRef(l,h),h},g.prototype.scaleToRef=function(l,h){for(var v=0;v<16;v++)h._m[v]=this._m[v]*l;return h._markAsUpdated(),this},g.prototype.scaleAndAddToRef=function(l,h){for(var v=0;v<16;v++)h._m[v]+=this._m[v]*l;return h._markAsUpdated(),this},g.prototype.toNormalMatrix=function(l){var h=A.Matrix[0];this.invertToRef(h),h.transposeToRef(l);var v=l._m;g.FromValuesToRef(v[0],v[1],v[2],0,v[4],v[5],v[6],0,v[8],v[9],v[10],0,0,0,0,1,l)},g.prototype.getRotationMatrix=function(){var l=new g;return this.getRotationMatrixToRef(l),l},g.prototype.getRotationMatrixToRef=function(l){var h=A.Vector3[0];if(!this.decompose(h))return g.IdentityToRef(l),this;var v=this._m,E=1/h._x,D=1/h._y,w=1/h._z;return g.FromValuesToRef(v[0]*E,v[1]*E,v[2]*E,0,v[4]*D,v[5]*D,v[6]*D,0,v[8]*w,v[9]*w,v[10]*w,0,0,0,0,1,l),this},g.prototype.toggleModelMatrixHandInPlace=function(){var l=this._m;l[2]*=-1,l[6]*=-1,l[8]*=-1,l[9]*=-1,l[14]*=-1,this._markAsUpdated()},g.prototype.toggleProjectionMatrixHandInPlace=function(){var l=this._m;l[8]*=-1,l[9]*=-1,l[10]*=-1,l[11]*=-1,this._markAsUpdated()},g.FromArray=function(l,h){h===void 0&&(h=0);var v=new g;return g.FromArrayToRef(l,h,v),v},g.FromArrayToRef=function(l,h,v){for(var E=0;E<16;E++)v._m[E]=l[E+h];v._markAsUpdated()},g.FromFloat32ArrayToRefScaled=function(l,h,v,E){for(var D=0;D<16;D++)E._m[D]=l[D+h]*v;E._markAsUpdated()},Object.defineProperty(g,"IdentityReadOnly",{get:function(){return g._identityReadOnly},enumerable:!1,configurable:!0}),g.FromValuesToRef=function(l,h,v,E,D,w,N,I,V,X,j,ne,te,de,pe,ae,ee){var K=ee._m;K[0]=l,K[1]=h,K[2]=v,K[3]=E,K[4]=D,K[5]=w,K[6]=N,K[7]=I,K[8]=V,K[9]=X,K[10]=j,K[11]=ne,K[12]=te,K[13]=de,K[14]=pe,K[15]=ae,ee._markAsUpdated()},g.FromValues=function(l,h,v,E,D,w,N,I,V,X,j,ne,te,de,pe,ae){var ee=new g,K=ee._m;return K[0]=l,K[1]=h,K[2]=v,K[3]=E,K[4]=D,K[5]=w,K[6]=N,K[7]=I,K[8]=V,K[9]=X,K[10]=j,K[11]=ne,K[12]=te,K[13]=de,K[14]=pe,K[15]=ae,ee._markAsUpdated(),ee},g.Compose=function(l,h,v){var E=new g;return g.ComposeToRef(l,h,v,E),E},g.ComposeToRef=function(l,h,v,E){var D=E._m,w=h._x,N=h._y,I=h._z,V=h._w,X=w+w,j=N+N,ne=I+I,te=w*X,de=w*j,pe=w*ne,ae=N*j,ee=N*ne,K=I*ne,$=V*X,L=V*j,G=V*ne,Q=l._x,oe=l._y,re=l._z;D[0]=(1-(ae+K))*Q,D[1]=(de+G)*Q,D[2]=(pe-L)*Q,D[3]=0,D[4]=(de-G)*oe,D[5]=(1-(te+K))*oe,D[6]=(ee+$)*oe,D[7]=0,D[8]=(pe+L)*re,D[9]=(ee-$)*re,D[10]=(1-(te+ae))*re,D[11]=0,D[12]=v._x,D[13]=v._y,D[14]=v._z,D[15]=1,E._markAsUpdated()},g.Identity=function(){var l=g.FromValues(1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1);return l._updateIdentityStatus(!0),l},g.IdentityToRef=function(l){g.FromValuesToRef(1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1,l),l._updateIdentityStatus(!0)},g.Zero=function(){var l=g.FromValues(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0);return l._updateIdentityStatus(!1),l},g.RotationX=function(l){var h=new g;return g.RotationXToRef(l,h),h},g.Invert=function(l){var h=new g;return l.invertToRef(h),h},g.RotationXToRef=function(l,h){var v=Math.sin(l),E=Math.cos(l);g.FromValuesToRef(1,0,0,0,0,E,v,0,0,-v,E,0,0,0,0,1,h),h._updateIdentityStatus(E===1&&v===0)},g.RotationY=function(l){var h=new g;return g.RotationYToRef(l,h),h},g.RotationYToRef=function(l,h){var v=Math.sin(l),E=Math.cos(l);g.FromValuesToRef(E,0,-v,0,0,1,0,0,v,0,E,0,0,0,0,1,h),h._updateIdentityStatus(E===1&&v===0)},g.RotationZ=function(l){var h=new g;return g.RotationZToRef(l,h),h},g.RotationZToRef=function(l,h){var v=Math.sin(l),E=Math.cos(l);g.FromValuesToRef(E,v,0,0,-v,E,0,0,0,0,1,0,0,0,0,1,h),h._updateIdentityStatus(E===1&&v===0)},g.RotationAxis=function(l,h){var v=new g;return g.RotationAxisToRef(l,h,v),v},g.RotationAxisToRef=function(l,h,v){var E=Math.sin(-h),D=Math.cos(-h),w=1-D;l.normalize();var N=v._m;N[0]=l._x*l._x*w+D,N[1]=l._x*l._y*w-l._z*E,N[2]=l._x*l._z*w+l._y*E,N[3]=0,N[4]=l._y*l._x*w+l._z*E,N[5]=l._y*l._y*w+D,N[6]=l._y*l._z*w-l._x*E,N[7]=0,N[8]=l._z*l._x*w-l._y*E,N[9]=l._z*l._y*w+l._x*E,N[10]=l._z*l._z*w+D,N[11]=0,N[12]=0,N[13]=0,N[14]=0,N[15]=1,v._markAsUpdated()},g.RotationAlignToRef=function(l,h,v){var E=C.Cross(h,l),D=C.Dot(h,l),w=1/(1+D),N=v._m;N[0]=E._x*E._x*w+D,N[1]=E._y*E._x*w-E._z,N[2]=E._z*E._x*w+E._y,N[3]=0,N[4]=E._x*E._y*w+E._z,N[5]=E._y*E._y*w+D,N[6]=E._z*E._y*w-E._x,N[7]=0,N[8]=E._x*E._z*w-E._y,N[9]=E._y*E._z*w+E._x,N[10]=E._z*E._z*w+D,N[11]=0,N[12]=0,N[13]=0,N[14]=0,N[15]=1,v._markAsUpdated()},g.RotationYawPitchRoll=function(l,h,v){var E=new g;return g.RotationYawPitchRollToRef(l,h,v,E),E},g.RotationYawPitchRollToRef=function(l,h,v,E){c.RotationYawPitchRollToRef(l,h,v,A.Quaternion[0]),A.Quaternion[0].toRotationMatrix(E)},g.Scaling=function(l,h,v){var E=new g;return g.ScalingToRef(l,h,v,E),E},g.ScalingToRef=function(l,h,v,E){g.FromValuesToRef(l,0,0,0,0,h,0,0,0,0,v,0,0,0,0,1,E),E._updateIdentityStatus(l===1&&h===1&&v===1)},g.Translation=function(l,h,v){var E=new g;return g.TranslationToRef(l,h,v,E),E},g.TranslationToRef=function(l,h,v,E){g.FromValuesToRef(1,0,0,0,0,1,0,0,0,0,1,0,l,h,v,1,E),E._updateIdentityStatus(l===0&&h===0&&v===0)},g.Lerp=function(l,h,v){var E=new g;return g.LerpToRef(l,h,v,E),E},g.LerpToRef=function(l,h,v,E){for(var D=E._m,w=l.m,N=h.m,I=0;I<16;I++)D[I]=w[I]*(1-v)+N[I]*v;E._markAsUpdated()},g.DecomposeLerp=function(l,h,v){var E=new g;return g.DecomposeLerpToRef(l,h,v,E),E},g.DecomposeLerpToRef=function(l,h,v,E){var D=A.Vector3[0],w=A.Quaternion[0],N=A.Vector3[1];l.decompose(D,w,N);var 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ne=x.a.IsWindowObjectExist()?this._engine.getHostDocument():null;m.vertexSource?N="source:"+m.vertexSource:m.vertexElement?(N=ne?ne.getElementById(m.vertexElement):null)||(N=m.vertexElement):N=m.vertex||m,m.fragmentSource?I="source:"+m.fragmentSource:m.fragmentElement?(I=ne?ne.getElementById(m.fragmentElement):null)||(I=m.fragmentElement):I=m.fragment||m;var te={defines:this.defines.split(`
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this._uniforms[m]},C.prototype.getSamplers=function(){return this._samplerList},C.prototype.getUniformNames=function(){return this._uniformsNames},C.prototype.getUniformBuffersNames=function(){return this._uniformBuffersNamesList},C.prototype.getIndexParameters=function(){return this._indexParameters},C.prototype.getCompilationError=function(){return this._compilationError},C.prototype.allFallbacksProcessed=function(){return this._allFallbacksProcessed},C.prototype.executeWhenCompiled=function(m){var c=this;this.isReady()?m(this):(this.onCompileObservable.add(function(T){m(T)}),this._pipelineContext&&!this._pipelineContext.isAsync||setTimeout(function(){c._checkIsReady(null)},16))},C.prototype._checkIsReady=function(m){var c=this;try{if(this._isReadyInternal())return}catch(T){return void this._processCompilationErrors(T,m)}setTimeout(function(){c._checkIsReady(m)},16)},C.prototype._loadShader=function(m,c,T,A){var S;if(typeof HTMLElement<"u"&&m instanceof HTMLElement)return void A(x.a.GetDOMTextContent(m));m.substr(0,7)!=="source:"?m.substr(0,7)!=="base64:"?C.ShadersStore[m+c+"Shader"]?A(C.ShadersStore[m+c+"Shader"]):T&&C.ShadersStore[m+T+"Shader"]?A(C.ShadersStore[m+T+"Shader"]):(S=m[0]==="."||m[0]==="/"||m.indexOf("http")>-1?m:C.ShadersRepository+m,this._engine._loadFile(S+"."+c.toLowerCase()+".fx",A)):A(window.atob(m.substr(7))):A(m.substr(7))},Object.defineProperty(C.prototype,"vertexSourceCode",{get:function(){return this._vertexSourceCodeOverride&&this._fragmentSourceCodeOverride?this._vertexSourceCodeOverride:this._vertexSourceCode},enumerable:!1,configurable:!0}),Object.defineProperty(C.prototype,"fragmentSourceCode",{get:function(){return this._vertexSourceCodeOverride&&this._fragmentSourceCodeOverride?this._fragmentSourceCodeOverride:this._fragmentSourceCode},enumerable:!1,configurable:!0}),Object.defineProperty(C.prototype,"rawVertexSourceCode",{get:function(){return this._rawVertexSourceCode},enumerable:!1,configurable:!0}),Object.defineProperty(C.prototype,"rawFragmentSourceCode",{get:function(){return this._rawFragmentSourceCode},enumerable:!1,configurable:!0}),C.prototype._rebuildProgram=function(m,c,T,A){var S=this;this._isReady=!1,this._vertexSourceCodeOverride=m,this._fragmentSourceCodeOverride=c,this.onError=function(g,l){A&&A(l)},this.onCompiled=function(){var g=S.getEngine().scenes;if(g)for(var l=0;l<g.length;l++)g[l].markAllMaterialsAsDirty(_.a.MATERIAL_AllDirtyFlag);S._pipelineContext._handlesSpectorRebuildCallback(T)},this._fallbacks=null,this._prepareEffect()},C.prototype._prepareEffect=function(){var m=this,c=this._attributesNames,T=this.defines;this._valueCache={};var A=this._pipelineContext;try{var S=this._engine;this._pipelineContext=S.createPipelineContext();var g=this._rebuildProgram.bind(this);this._vertexSourceCodeOverride&&this._fragmentSourceCodeOverride?S._preparePipelineContext(this._pipelineContext,this._vertexSourceCodeOverride,this._fragmentSourceCodeOverride,!0,g,null,this._transformFeedbackVaryings):S._preparePipelineContext(this._pipelineContext,this._vertexSourceCode,this._fragmentSourceCode,!1,g,T,this._transformFeedbackVaryings),S._executeWhenRenderingStateIsCompiled(this._pipelineContext,function(){if(S.supportsUniformBuffers)for(var l in m._uniformBuffersNames)m.bindUniformBlock(l,m._uniformBuffersNames[l]);var h;if(S.getUniforms(m._pipelineContext,m._uniformsNames).forEach(function(D,w){m._uniforms[m._uniformsNames[w]]=D}),m._attributes=S.getAttributes(m._pipelineContext,c),c)for(var v=0;v<c.length;v++){var E=c[v];m._attributeLocationByName[E]=m._attributes[v]}for(h=0;h<m._samplerList.length;h++)m.getUniform(m._samplerList[h])==null&&(m._samplerList.splice(h,1),h--);m._samplerList.forEach(function(D,w){m._samplers[D]=w}),S.bindSamplers(m),m._compilationError="",m._isReady=!0,m.onCompiled&&m.onCompiled(m),m.onCompileObservable.notifyObservers(m),m.onCompileObservable.clear(),m._fallbacks&&m._fallbacks.unBindMesh(),A&&m.getEngine()._deletePipelineContext(A)}),this._pipelineContext.isAsync&&this._checkIsReady(A)}catch(l){this._processCompilationErrors(l,A)}},C.prototype._getShaderCodeAndErrorLine=function(m,c,T){var A=T?/FRAGMENT SHADER ERROR: 0:(\d+?):/:/VERTEX SHADER ERROR: 0:(\d+?):/,S=null;if(c&&m){var g=c.match(A);if(g&&g.length===2){var l=parseInt(g[1]),h=m.split(`
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N.a.Warn("You cannot use a mesh as LOD level twice"),this;var oe=new j.a(G,Q);return this._internalMeshDataInfo._LODLevels.push(oe),Q&&(Q._masterMesh=this),this._sortLODLevels(),this},L.prototype.getLODLevelAtDistance=function(G){for(var Q=this._internalMeshDataInfo,oe=0;oe<Q._LODLevels.length;oe++){var re=Q._LODLevels[oe];if(re.distance===G)return re.mesh}return null},L.prototype.removeLODLevel=function(G){for(var Q=this._internalMeshDataInfo,oe=0;oe<Q._LODLevels.length;oe++)Q._LODLevels[oe].mesh===G&&(Q._LODLevels.splice(oe,1),G&&(G._masterMesh=null));return this._sortLODLevels(),this},L.prototype.getLOD=function(G,Q){var oe,re=this._internalMeshDataInfo;if(!re._LODLevels||re._LODLevels.length===0)return this;Q?oe=Q:oe=this.getBoundingInfo().boundingSphere;var Y=oe.centerWorld.subtract(G.globalPosition).length();if(re._LODLevels[re._LODLevels.length-1].distance>Y)return this.onLODLevelSelection&&this.onLODLevelSelection(Y,this,this),this;for(var k=0;k<re._LODLevels.length;k++){var H=re._LODLevels[k];if(H.distance<Y){if(H.mesh){if(H.mesh.delayLoadState===D.a.DELAYLOADSTATE_NOTLOADED)return H.mesh._checkDelayState(),this;if(H.mesh.delayLoadState===D.a.DELAYLOADSTATE_LOADING)return this;H.mesh._preActivate(),H.mesh._updateSubMeshesBoundingInfo(this.worldMatrixFromCache)}return this.onLODLevelSelection&&this.onLODLevelSelection(Y,this,H.mesh),H.mesh}}return this.onLODLevelSelection&&this.onLODLevelSelection(Y,this,this),this},Object.defineProperty(L.prototype,"geometry",{get:function(){return this._geometry},enumerable:!1,configurable:!0}),L.prototype.getTotalVertices=function(){return this._geometry===null||this._geometry===void 0?0:this._geometry.getTotalVertices()},L.prototype.getVerticesData=function(G,Q,oe){return this._geometry?this._geometry.getVerticesData(G,Q,oe):null},L.prototype.getVertexBuffer=function(G){return this._geometry?this._geometry.getVertexBuffer(G):null},L.prototype.isVerticesDataPresent=function(G){return this._geometry?this._geometry.isVerticesDataPresent(G):!!this._delayInfo&&this._delayInfo.indexOf(G)!==-1},L.prototype.isVertexBufferUpdatable=function(G){return this._geometry?this._geometry.isVertexBufferUpdatable(G):!!this._delayInfo&&this._delayInfo.indexOf(G)!==-1},L.prototype.getVerticesDataKinds=function(){if(!this._geometry){var G=new Array;return this._delayInfo&&this._delayInfo.forEach(function(Q){G.push(Q)}),G}return this._geometry.getVerticesDataKinds()},L.prototype.getTotalIndices=function(){return this._geometry?this._geometry.getTotalIndices():0},L.prototype.getIndices=function(G,Q){return this._geometry?this._geometry.getIndices(G,Q):[]},Object.defineProperty(L.prototype,"isBlocked",{get:function(){return this._masterMesh!==null&&this._masterMesh!==void 0},enumerable:!1,configurable:!0}),L.prototype.isReady=function(G,Q){var oe,re,Y,k,H,Z;if(G===void 0&&(G=!1),Q===void 0&&(Q=!1),this.delayLoadState===D.a.DELAYLOADSTATE_LOADING||!$.prototype.isReady.call(this,G))return!1;if(!this.subMeshes||this.subMeshes.length===0||!G)return!0;var W=this.getEngine(),q=this.getScene(),he=Q||W.getCaps().instancedArrays&&(this.instances.length>0||this.hasThinInstances);this.computeWorldMatrix();var ge=this.material||q.defaultMaterial;if(ge){if(ge._storeEffectOnSubMeshes)for(var me=0,_e=this.subMeshes;me<_e.length;me++){var be=(je=_e[me]).getMaterial();if(be){if(be._storeEffectOnSubMeshes){if(!be.isReadyForSubMesh(this,je,he))return!1}else if(!be.isReady(this,he))return!1}}else if(!ge.isReady(this,he))return!1}for(var Pe=0,ye=this.lightSources;Pe<ye.length;Pe++){var Be=ye[Pe].getShadowGenerator();if(Be&&(!(!((oe=Be.getShadowMap())===null||oe===void 0)&&oe.renderList)||!((re=Be.getShadowMap())===null||re===void 0)&&re.renderList&&((k=(Y=Be.getShadowMap())===null||Y===void 0?void 0:Y.renderList)===null||k===void 0?void 0:k.indexOf(this))!==-1))for(var ke=0,We=this.subMeshes;ke<We.length;ke++){var je=We[ke];if(!Be.isReady(je,he,(Z=(H=je.getMaterial())===null||H===void 0?void 0:H.needAlphaBlendingForMesh(this))!==null&&Z!==void 0&&Z))return!1}}for(var He=0,qe=this._internalMeshDataInfo._LODLevels;He<qe.length;He++){var Ge=qe[He];if(Ge.mesh&&!Ge.mesh.isReady(he))return!1}return!0},Object.defineProperty(L.prototype,"areNormalsFrozen",{get:function(){return this._internalMeshDataInfo._areNormalsFrozen},enumerable:!1,configurable:!0}),L.prototype.freezeNormals=function(){return this._internalMeshDataInfo._areNormalsFrozen=!0,this},L.prototype.unfreezeNormals=function(){return this._internalMeshDataInfo._areNormalsFrozen=!1,this},Object.defineProperty(L.prototype,"overridenInstanceCount",{set:function(G){this._instanceDataStorage.overridenInstanceCount=G},enumerable:!1,configurable:!0}),L.prototype._preActivate=function(){var G=this._internalMeshDataInfo,Q=this.getScene().getRenderId();return G._preActivateId===Q||(G._preActivateId=Q,this._instanceDataStorage.visibleInstances=null),this},L.prototype._preActivateForIntermediateRendering=function(G){return this._instanceDataStorage.visibleInstances&&(this._instanceDataStorage.visibleInstances.intermediateDefaultRenderId=G),this},L.prototype._registerInstanceForRenderId=function(G,Q){return this._instanceDataStorage.visibleInstances||(this._instanceDataStorage.visibleInstances={defaultRenderId:Q,selfDefaultRenderId:this._renderId}),this._instanceDataStorage.visibleInstances[Q]||(this._instanceDataStorage.previousRenderId!==void 0&&this._instanceDataStorage.isFrozen&&(this._instanceDataStorage.visibleInstances[this._instanceDataStorage.previousRenderId]=null),this._instanceDataStorage.previousRenderId=Q,this._instanceDataStorage.visibleInstances[Q]=new Array),this._instanceDataStorage.visibleInstances[Q].push(G),this},L.prototype._afterComputeWorldMatrix=function(){$.prototype._afterComputeWorldMatrix.call(this),this.hasThinInstances&&(this.doNotSyncBoundingInfo||this.thinInstanceRefreshBoundingInfo(!1))},L.prototype._postActivate=function(){this.edgesShareWithInstances&&this.edgesRenderer&&this.edgesRenderer.isEnabled&&this._renderingGroup&&(this._renderingGroup._edgesRenderers.pushNoDuplicate(this.edgesRenderer),this.edgesRenderer.customInstances.push(this.getWorldMatrix()))},L.prototype.refreshBoundingInfo=function(G){if(G===void 0&&(G=!1),this._boundingInfo&&this._boundingInfo.isLocked)return this;var Q=this.geometry?this.geometry.boundingBias:null;return this._refreshBoundingInfo(this._getPositionData(G),Q),this},L.prototype._createGlobalSubMesh=function(G){var Q=this.getTotalVertices();if(!Q||!this.getIndices())return null;if(this.subMeshes&&this.subMeshes.length>0){var oe=this.getIndices();if(!oe)return null;var re=oe.length,Y=!1;if(G)Y=!0;else for(var k=0,H=this.subMeshes;k<H.length;k++){var Z=H[k];if(Z.indexStart+Z.indexCount>re){Y=!0;break}if(Z.verticesStart+Z.verticesCount>Q){Y=!0;break}}if(!Y)return this.subMeshes[0]}return this.releaseSubMeshes(),new g.a(0,0,Q,0,this.getTotalIndices(),this)},L.prototype.subdivide=function(G){if(!(G<1)){for(var Q=this.getTotalIndices(),oe=Q/G|0,re=0;oe%3!=0;)oe++;this.releaseSubMeshes();for(var Y=0;Y<G&&!(re>=Q);Y++)g.a.CreateFromIndices(0,re,Y===G-1?Q-re:oe,this),re+=oe;this.synchronizeInstances()}},L.prototype.setVerticesData=function(G,Q,oe,re){if(oe===void 0&&(oe=!1),this._geometry)this._geometry.setVerticesData(G,Q,oe,re);else{var Y=new T.a;Y.set(Q,G);var k=this.getScene();new A.a(A.a.RandomId(),k,Y,oe,this)}return this},L.prototype.removeVerticesData=function(G){this._geometry&&this._geometry.removeVerticesData(G)},L.prototype.markVerticesDataAsUpdatable=function(G,Q){Q===void 0&&(Q=!0);var oe=this.getVertexBuffer(G);oe&&oe.isUpdatable()!==Q&&this.setVerticesData(G,this.getVerticesData(G),Q)},L.prototype.setVerticesBuffer=function(G){return this._geometry||(this._geometry=A.a.CreateGeometryForMesh(this)),this._geometry.setVerticesBuffer(G),this},L.prototype.updateVerticesData=function(G,Q,oe,re){return this._geometry?(re?(this.makeGeometryUnique(),this.updateVerticesData(G,Q,oe,!1)):this._geometry.updateVerticesData(G,Q,oe),this):this},L.prototype.updateMeshPositions=function(G,Q){Q===void 0&&(Q=!0);var oe=this.getVerticesData(c.b.PositionKind);if(!oe)return this;if(G(oe),this.updateVerticesData(c.b.PositionKind,oe,!1,!1),Q){var re=this.getIndices(),Y=this.getVerticesData(c.b.NormalKind);if(!Y)return this;T.a.ComputeNormals(oe,re,Y),this.updateVerticesData(c.b.NormalKind,Y,!1,!1)}return this},L.prototype.makeGeometryUnique=function(){if(!this._geometry)return this;if(this._geometry.meshes.length===1)return this;var G=this._geometry,Q=this._geometry.copy(A.a.RandomId());return G.releaseForMesh(this,!0),Q.applyToMesh(this),this},L.prototype.setIndices=function(G,Q,oe){if(Q===void 0&&(Q=null),oe===void 0&&(oe=!1),this._geometry)this._geometry.setIndices(G,Q,oe);else{var re=new T.a;re.indices=G;var Y=this.getScene();new A.a(A.a.RandomId(),Y,re,oe,this)}return this},L.prototype.updateIndices=function(G,Q,oe){return oe===void 0&&(oe=!1),this._geometry?(this._geometry.updateIndices(G,Q,oe),this):this},L.prototype.toLeftHanded=function(){return this._geometry?(this._geometry.toLeftHanded(),this):this},L.prototype._bind=function(G,Q,oe){if(!this._geometry)return this;var re,Y=this.getScene().getEngine();if(this._unIndexed)re=null;else switch(oe){case h.a.PointFillMode:re=null;break;case h.a.WireFrameFillMode:re=G._getLinesIndexBuffer(this.getIndices(),Y);break;default:case h.a.TriangleFillMode:re=this._geometry.getIndexBuffer()}return this._geometry._bind(Q,re),this},L.prototype._draw=function(G,Q,oe){if(!this._geometry||!this._geometry.getVertexBuffers()||!this._unIndexed&&!this._geometry.getIndexBuffer())return this;this._internalMeshDataInfo._onBeforeDrawObservable&&this._internalMeshDataInfo._onBeforeDrawObservable.notifyObservers(this);var re=this.getScene().getEngine();return this._unIndexed||Q==h.a.PointFillMode?re.drawArraysType(Q,G.verticesStart,G.verticesCount,oe):Q==h.a.WireFrameFillMode?re.drawElementsType(Q,0,G._linesIndexCount,oe):re.drawElementsType(Q,G.indexStart,G.indexCount,oe),this},L.prototype.registerBeforeRender=function(G){return this.onBeforeRenderObservable.add(G),this},L.prototype.unregisterBeforeRender=function(G){return this.onBeforeRenderObservable.removeCallback(G),this},L.prototype.registerAfterRender=function(G){return this.onAfterRenderObservable.add(G),this},L.prototype.unregisterAfterRender=function(G){return this.onAfterRenderObservable.removeCallback(G),this},L.prototype._getInstancesRenderList=function(G,Q){if(Q===void 0&&(Q=!1),this._instanceDataStorage.isFrozen&&this._instanceDataStorage.previousBatch)return this._instanceDataStorage.previousBatch;var oe=this.getScene(),re=oe._isInIntermediateRendering(),Y=re?this._internalAbstractMeshDataInfo._onlyForInstancesIntermediate:this._internalAbstractMeshDataInfo._onlyForInstances,k=this._instanceDataStorage.batchCache;if(k.mustReturn=!1,k.renderSelf[G]=Q||!Y&&this.isEnabled()&&this.isVisible,k.visibleInstances[G]=null,this._instanceDataStorage.visibleInstances&&!Q){var H=this._instanceDataStorage.visibleInstances,Z=oe.getRenderId(),W=re?H.intermediateDefaultRenderId:H.defaultRenderId;k.visibleInstances[G]=H[Z],!k.visibleInstances[G]&&W&&(k.visibleInstances[G]=H[W])}return k.hardwareInstancedRendering[G]=!Q&&this._instanceDataStorage.hardwareInstancedRendering&&k.visibleInstances[G]!==null&&k.visibleInstances[G]!==void 0,this._instanceDataStorage.previousBatch=k,k},L.prototype._renderWithInstances=function(G,Q,oe,re,Y){var k=oe.visibleInstances[G._id];if(!k)return this;for(var H=this._instanceDataStorage,Z=H.instancesBufferSize,W=H.instancesBuffer,q=16*(k.length+1)*4;H.instancesBufferSize<q;)H.instancesBufferSize*=2;H.instancesData&&Z==H.instancesBufferSize||(H.instancesData=new Float32Array(H.instancesBufferSize/4));var he=0,ge=0,me=oe.renderSelf[G._id],_e=!W||Z!==H.instancesBufferSize;if(this._instanceDataStorage.manualUpdate||H.isFrozen&&!_e)ge=(me?1:0)+k.length;else{var be=this._effectiveMesh.getWorldMatrix();if(me&&(be.copyToArray(H.instancesData,he),he+=16,ge++),k)for(var Pe=0;Pe<k.length;Pe++)k[Pe].getWorldMatrix().copyToArray(H.instancesData,he),he+=16,ge++}return _e?(W&&W.dispose(),W=new c.a(Y,H.instancesData,!0,16,!1,!0),H.instancesBuffer=W,this.setVerticesBuffer(W.createVertexBuffer("world0",0,4)),this.setVerticesBuffer(W.createVertexBuffer("world1",4,4)),this.setVerticesBuffer(W.createVertexBuffer("world2",8,4)),this.setVerticesBuffer(W.createVertexBuffer("world3",12,4))):this._instanceDataStorage.isFrozen||W.updateDirectly(H.instancesData,0,ge),this._processInstancedBuffers(k,me),this.getScene()._activeIndices.addCount(G.indexCount*ge,!1),this._bind(G,re,Q),this._draw(G,Q,ge),Y.unbindInstanceAttributes(),this},L.prototype._renderWithThinInstances=function(G,Q,oe,re){var Y,k,H=(k=(Y=this._thinInstanceDataStorage)===null||Y===void 0?void 0:Y.instancesCount)!==null&&k!==void 0?k:0;this.getScene()._activeIndices.addCount(G.indexCount*H,!1),this._bind(G,oe,Q),this._draw(G,Q,H),re.unbindInstanceAttributes()},L.prototype._processInstancedBuffers=function(G,Q){},L.prototype._processRendering=function(G,Q,oe,re,Y,k,H,Z){var W=this.getScene(),q=W.getEngine();if(k&&Q.getRenderingMesh().hasThinInstances)return this._renderWithThinInstances(Q,re,oe,q),this;if(k)this._renderWithInstances(Q,re,Y,oe,q);else{var he=0;Y.renderSelf[Q._id]&&(H&&H(!1,G._effectiveMesh.getWorldMatrix(),Z),he++,this._draw(Q,re,this._instanceDataStorage.overridenInstanceCount));var ge=Y.visibleInstances[Q._id];if(ge){var me=ge.length;he+=me;for(var _e=0;_e<me;_e++){var be=ge[_e].getWorldMatrix();H&&H(!0,be,Z),this._draw(Q,re)}}W._activeIndices.addCount(Q.indexCount*he,!1)}return this},L.prototype._rebuild=function(){this._instanceDataStorage.instancesBuffer&&(this._instanceDataStorage.instancesBuffer.dispose(),this._instanceDataStorage.instancesBuffer=null),$.prototype._rebuild.call(this)},L.prototype._freeze=function(){if(this.subMeshes){for(var G=0;G<this.subMeshes.length;G++)this._getInstancesRenderList(G);this._effectiveMaterial=null,this._instanceDataStorage.isFrozen=!0}},L.prototype._unFreeze=function(){this._instanceDataStorage.isFrozen=!1,this._instanceDataStorage.previousBatch=null},L.prototype.render=function(G,Q,oe){var re=this.getScene();if(this._internalAbstractMeshDataInfo._isActiveIntermediate?this._internalAbstractMeshDataInfo._isActiveIntermediate=!1:this._internalAbstractMeshDataInfo._isActive=!1,this._checkOcclusionQuery())return this;var Y=this._getInstancesRenderList(G._id,!!oe);if(Y.mustReturn)return this;if(!this._geometry||!this._geometry.getVertexBuffers()||!this._unIndexed&&!this._geometry.getIndexBuffer())return this;this._internalMeshDataInfo._onBeforeRenderObservable&&this._internalMeshDataInfo._onBeforeRenderObservable.notifyObservers(this);var k,H=re.getEngine(),Z=Y.hardwareInstancedRendering[G._id]||G.getRenderingMesh().hasThinInstances,W=this._instanceDataStorage,q=G.getMaterial();if(!q)return this;if(!W.isFrozen||!this._effectiveMaterial||this._effectiveMaterial!==q){if(q._storeEffectOnSubMeshes){if(!q.isReadyForSubMesh(this,G,Z))return this}else if(!q.isReady(this,Z))return this;this._effectiveMaterial=q}Q&&H.setAlphaMode(this._effectiveMaterial.alphaMode),k=this._effectiveMaterial._storeEffectOnSubMeshes?G.effect:this._effectiveMaterial.getEffect();for(var he=0,ge=re._beforeRenderingMeshStage;he<ge.length;he++)ge[he].action(this,G,Y,k);if(!k)return this;var me,_e=oe||this._effectiveMesh;if(W.isFrozen||!this._effectiveMaterial.backFaceCulling&&this.overrideMaterialSideOrientation===null)me=W.sideOrientation;else{var be=_e._getWorldMatrixDeterminant();(me=this.overrideMaterialSideOrientation)==null&&(me=this._effectiveMaterial.sideOrientation),be<0&&(me=me===h.a.ClockWiseSideOrientation?h.a.CounterClockWiseSideOrientation:h.a.ClockWiseSideOrientation),W.sideOrientation=me}var Pe=this._effectiveMaterial._preBind(k,me);this._effectiveMaterial.forceDepthWrite&&H.setDepthWrite(!0);var ye=re.forcePointsCloud?h.a.PointFillMode:re.forceWireframe?h.a.WireFrameFillMode:this._effectiveMaterial.fillMode;this._internalMeshDataInfo._onBeforeBindObservable&&this._internalMeshDataInfo._onBeforeBindObservable.notifyObservers(this),Z||this._bind(G,k,ye);var Be=_e.getWorldMatrix();this._effectiveMaterial._storeEffectOnSubMeshes?this._effectiveMaterial.bindForSubMesh(Be,this,G):this._effectiveMaterial.bind(Be,this),!this._effectiveMaterial.backFaceCulling&&this._effectiveMaterial.separateCullingPass&&(H.setState(!0,this._effectiveMaterial.zOffset,!1,!Pe),this._processRendering(this,G,k,ye,Y,Z,this._onBeforeDraw,this._effectiveMaterial),H.setState(!0,this._effectiveMaterial.zOffset,!1,Pe)),this._processRendering(this,G,k,ye,Y,Z,this._onBeforeDraw,this._effectiveMaterial),this._effectiveMaterial.unbind();for(var ke=0,We=re._afterRenderingMeshStage;ke<We.length;ke++)We[ke].action(this,G,Y,k);return this._internalMeshDataInfo._onAfterRenderObservable&&this._internalMeshDataInfo._onAfterRenderObservable.notifyObservers(this),this},L.prototype._onBeforeDraw=function(G,Q,oe){G&&oe&&oe.bindOnlyWorldMatrix(Q)},L.prototype.cleanMatrixWeights=function(){this.isVerticesDataPresent(c.b.MatricesWeightsKind)&&(this.isVerticesDataPresent(c.b.MatricesWeightsExtraKind)?this.normalizeSkinWeightsAndExtra():this.normalizeSkinFourWeights())},L.prototype.normalizeSkinFourWeights=function(){for(var G=this.getVerticesData(c.b.MatricesWeightsKind),Q=G.length,oe=0;oe<Q;oe+=4){var re=G[oe]+G[oe+1]+G[oe+2]+G[oe+3];if(re===0)G[oe]=1;else{var Y=1/re;G[oe]*=Y,G[oe+1]*=Y,G[oe+2]*=Y,G[oe+3]*=Y}}this.setVerticesData(c.b.MatricesWeightsKind,G)},L.prototype.normalizeSkinWeightsAndExtra=function(){for(var G=this.getVerticesData(c.b.MatricesWeightsExtraKind),Q=this.getVerticesData(c.b.MatricesWeightsKind),oe=Q.length,re=0;re<oe;re+=4){var Y=Q[re]+Q[re+1]+Q[re+2]+Q[re+3];if((Y+=G[re]+G[re+1]+G[re+2]+G[re+3])===0)Q[re]=1;else{var k=1/Y;Q[re]*=k,Q[re+1]*=k,Q[re+2]*=k,Q[re+3]*=k,G[re]*=k,G[re+1]*=k,G[re+2]*=k,G[re+3]*=k}}this.setVerticesData(c.b.MatricesWeightsKind,Q),this.setVerticesData(c.b.MatricesWeightsKind,G)},L.prototype.validateSkinning=function(){var G=this.getVerticesData(c.b.MatricesWeightsExtraKind),Q=this.getVerticesData(c.b.MatricesWeightsKind);if(Q===null||this.skeleton==null)return{skinned:!1,valid:!0,report:"not skinned"};for(var oe=Q.length,re=0,Y=0,k=0,H=0,Z=G===null?4:8,W=new Array,q=0;q<=Z;q++)W[q]=0;for(q=0;q<oe;q+=4){for(var he=Q[q],ge=he,me=ge===0?0:1,_e=1;_e<Z;_e++){var be=_e<4?Q[q+_e]:G[q+_e-4];be>he&&re++,be!==0&&me++,ge+=be,he=be}if(W[me]++,me>k&&(k=me),ge===0)Y++;else{var Pe=1/ge,ye=0;for(_e=0;_e<Z;_e++)ye+=_e<4?Math.abs(Q[q+_e]-Q[q+_e]*Pe):Math.abs(G[q+_e-4]-G[q+_e-4]*Pe);ye>.001&&H++}}var Be=this.skeleton.bones.length,ke=this.getVerticesData(c.b.MatricesIndicesKind),We=this.getVerticesData(c.b.MatricesIndicesExtraKind),je=0;for(q=0;q<oe;q+=4)for(_e=0;_e<Z;_e++){var He=_e<4?ke[q+_e]:We[q+_e-4];(He>=Be||He<0)&&je++}return{skinned:!0,valid:Y===0&&H===0&&je===0,report:"Number of Weights = "+oe/4+`
-Maximum influences = `+k+`
-Missing Weights = `+Y+`
-Not Sorted = `+re+`
-Not Normalized = `+H+`
-WeightCounts = [`+W+`]
-Number of bones = `+Be+`
-Bad Bone Indices = `+je}},L.prototype._checkDelayState=function(){var G=this.getScene();return this._geometry?this._geometry.load(G):this.delayLoadState===D.a.DELAYLOADSTATE_NOTLOADED&&(this.delayLoadState=D.a.DELAYLOADSTATE_LOADING,this._queueLoad(G)),this},L.prototype._queueLoad=function(G){var Q=this;G._addPendingData(this);var oe=this.delayLoadingFile.indexOf(".babylonbinarymeshdata")!==-1;return x.b.LoadFile(this.delayLoadingFile,function(re){re instanceof ArrayBuffer?Q._delayLoadingFunction(re,Q):Q._delayLoadingFunction(JSON.parse(re),Q),Q.instances.forEach(function(Y){Y.refreshBoundingInfo(),Y._syncSubMeshes()}),Q.delayLoadState=D.a.DELAYLOADSTATE_LOADED,G._removePendingData(Q)},function(){},G.offlineProvider,oe),this},L.prototype.isInFrustum=function(G){return this.delayLoadState!==D.a.DELAYLOADSTATE_LOADING&&!!$.prototype.isInFrustum.call(this,G)&&(this._checkDelayState(),!0)},L.prototype.setMaterialByID=function(G){var Q,oe=this.getScene().materials;for(Q=oe.length-1;Q>-1;Q--)if(oe[Q].id===G)return this.material=oe[Q],this;var re=this.getScene().multiMaterials;for(Q=re.length-1;Q>-1;Q--)if(re[Q].id===G)return this.material=re[Q],this;return this},L.prototype.getAnimatables=function(){var G=new Array;return this.material&&G.push(this.material),this.skeleton&&G.push(this.skeleton),G},L.prototype.bakeTransformIntoVertices=function(G){if(!this.isVerticesDataPresent(c.b.PositionKind))return this;var Q=this.subMeshes.splice(0);this._resetPointsArrayCache();var oe,re=this.getVerticesData(c.b.PositionKind),Y=new Array;for(oe=0;oe<re.length;oe+=3)R.e.TransformCoordinates(R.e.FromArray(re,oe),G).toArray(Y,oe);if(this.setVerticesData(c.b.PositionKind,Y,this.getVertexBuffer(c.b.PositionKind).isUpdatable()),this.isVerticesDataPresent(c.b.NormalKind)){for(re=this.getVerticesData(c.b.NormalKind),Y=[],oe=0;oe<re.length;oe+=3)R.e.TransformNormal(R.e.FromArray(re,oe),G).normalize().toArray(Y,oe);this.setVerticesData(c.b.NormalKind,Y,this.getVertexBuffer(c.b.NormalKind).isUpdatable())}return G.m[0]*G.m[5]*G.m[10]<0&&this.flipFaces(),this.releaseSubMeshes(),this.subMeshes=Q,this},L.prototype.bakeCurrentTransformIntoVertices=function(G){return G===void 0&&(G=!0),this.bakeTransformIntoVertices(this.computeWorldMatrix(!0)),this.resetLocalMatrix(G),this},Object.defineProperty(L.prototype,"_positions",{get:function(){return this._geometry?this._geometry._positions:null},enumerable:!1,configurable:!0}),L.prototype._resetPointsArrayCache=function(){return this._geometry&&this._geometry._resetPointsArrayCache(),this},L.prototype._generatePointsArray=function(){return!!this._geometry&&this._geometry._generatePointsArray()},L.prototype.clone=function(G,Q,oe,re){return G===void 0&&(G=""),Q===void 0&&(Q=null),re===void 0&&(re=!0),new L(G,this.getScene(),Q,this,oe,re)},L.prototype.dispose=function(G,Q){Q===void 0&&(Q=!1),this.morphTargetManager=null,this._geometry&&this._geometry.releaseForMesh(this,!0);var oe=this._internalMeshDataInfo;if(oe._onBeforeDrawObservable&&oe._onBeforeDrawObservable.clear(),oe._onBeforeBindObservable&&oe._onBeforeBindObservable.clear(),oe._onBeforeRenderObservable&&oe._onBeforeRenderObservable.clear(),oe._onAfterRenderObservable&&oe._onAfterRenderObservable.clear(),this._scene.useClonedMeshMap){if(oe.meshMap)for(var re in oe.meshMap)(H=oe.meshMap[re])&&(H._internalMeshDataInfo._source=null,oe.meshMap[re]=void 0);oe._source&&oe._source._internalMeshDataInfo.meshMap&&(oe._source._internalMeshDataInfo.meshMap[this.uniqueId]=void 0)}else for(var Y=0,k=this.getScene().meshes;Y<k.length;Y++){var H;(H=k[Y])._internalMeshDataInfo&&H._internalMeshDataInfo._source&&H._internalMeshDataInfo._source===this&&(H._internalMeshDataInfo._source=null)}oe._source=null,this._disposeInstanceSpecificData(),this._disposeThinInstanceSpecificData(),$.prototype.dispose.call(this,G,Q)},L.prototype._disposeInstanceSpecificData=function(){},L.prototype._disposeThinInstanceSpecificData=function(){},L.prototype.applyDisplacementMap=function(G,Q,oe,re,Y,k,H){var Z=this;H===void 0&&(H=!1);var W=this.getScene();return x.b.LoadImage(G,function(q){var he=q.width,ge=q.height,me=ne.a.CreateCanvas(he,ge).getContext("2d");me.drawImage(q,0,0);var _e=me.getImageData(0,0,he,ge).data;Z.applyDisplacementMapFromBuffer(_e,he,ge,Q,oe,Y,k,H),re&&re(Z)},function(){},W.offlineProvider),this},L.prototype.applyDisplacementMapFromBuffer=function(G,Q,oe,re,Y,k,H,Z){if(Z===void 0&&(Z=!1),!this.isVerticesDataPresent(c.b.PositionKind)||!this.isVerticesDataPresent(c.b.NormalKind)||!this.isVerticesDataPresent(c.b.UVKind))return N.a.Warn("Cannot call applyDisplacementMap: Given mesh is not complete. Position, Normal or UV are missing"),this;var W=this.getVerticesData(c.b.PositionKind,!0,!0),q=this.getVerticesData(c.b.NormalKind),he=this.getVerticesData(c.b.UVKind),ge=R.e.Zero(),me=R.e.Zero(),_e=R.d.Zero();k=k||R.d.Zero(),H=H||new R.d(1,1);for(var be=0;be<W.length;be+=3){R.e.FromArrayToRef(W,be,ge),R.e.FromArrayToRef(q,be,me),R.d.FromArrayToRef(he,be/3*2,_e);var Pe=4*((Math.abs(_e.x*H.x+k.x%1)*(Q-1)%Q|0)+(Math.abs(_e.y*H.y+k.y%1)*(oe-1)%oe|0)*Q),ye=.3*(G[Pe]/255)+.59*(G[Pe+1]/255)+.11*(G[Pe+2]/255);me.normalize(),me.scaleInPlace(re+(Y-re)*ye),(ge=ge.add(me)).toArray(W,be)}return T.a.ComputeNormals(W,this.getIndices(),q),Z?(this.setVerticesData(c.b.PositionKind,W),this.setVerticesData(c.b.NormalKind,q)):(this.updateVerticesData(c.b.PositionKind,W),this.updateVerticesData(c.b.NormalKind,q)),this},L.prototype.convertToFlatShadedMesh=function(){var G,Q,oe=this.getVerticesDataKinds(),re={},Y={},k={},H=!1;for(G=0;G<oe.length;G++){Q=oe[G];var Z=this.getVertexBuffer(Q);Q!==c.b.NormalKind?(re[Q]=Z,Y[Q]=re[Q].getData(),k[Q]=[]):(H=Z.isUpdatable(),oe.splice(G,1),G--)}var W,q=this.subMeshes.slice(0),he=this.getIndices(),ge=this.getTotalIndices();for(W=0;W<ge;W++){var me=he[W];for(G=0;G<oe.length;G++)for(var _e=re[Q=oe[G]].getStrideSize(),be=0;be<_e;be++)k[Q].push(Y[Q][me*_e+be])}var Pe=[],ye=k[c.b.PositionKind];for(W=0;W<ge;W+=3){he[W]=W,he[W+1]=W+1,he[W+2]=W+2;for(var Be=R.e.FromArray(ye,3*W),ke=R.e.FromArray(ye,3*(W+1)),We=R.e.FromArray(ye,3*(W+2)),je=Be.subtract(ke),He=We.subtract(ke),qe=R.e.Normalize(R.e.Cross(je,He)),Ge=0;Ge<3;Ge++)Pe.push(qe.x),Pe.push(qe.y),Pe.push(qe.z)}for(this.setIndices(he),this.setVerticesData(c.b.NormalKind,Pe,H),G=0;G<oe.length;G++)Q=oe[G],this.setVerticesData(Q,k[Q],re[Q].isUpdatable());this.releaseSubMeshes();for(var nt=0;nt<q.length;nt++){var $e=q[nt];g.a.AddToMesh($e.materialIndex,$e.indexStart,$e.indexCount,$e.indexStart,$e.indexCount,this)}return this.synchronizeInstances(),this},L.prototype.convertToUnIndexedMesh=function(){var G,Q,oe=this.getVerticesDataKinds(),re={},Y={},k={};for(G=0;G<oe.length;G++){Q=oe[G];var H=this.getVertexBuffer(Q);re[Q]=H,Y[Q]=re[Q].getData(),k[Q]=[]}var Z,W=this.subMeshes.slice(0),q=this.getIndices(),he=this.getTotalIndices();for(Z=0;Z<he;Z++){var ge=q[Z];for(G=0;G<oe.length;G++)for(var me=re[Q=oe[G]].getStrideSize(),_e=0;_e<me;_e++)k[Q].push(Y[Q][ge*me+_e])}for(Z=0;Z<he;Z+=3)q[Z]=Z,q[Z+1]=Z+1,q[Z+2]=Z+2;for(this.setIndices(q),G=0;G<oe.length;G++)Q=oe[G],this.setVerticesData(Q,k[Q],re[Q].isUpdatable());this.releaseSubMeshes();for(var be=0;be<W.length;be++){var Pe=W[be];g.a.AddToMesh(Pe.materialIndex,Pe.indexStart,Pe.indexCount,Pe.indexStart,Pe.indexCount,this)}return this._unIndexed=!0,this.synchronizeInstances(),this},L.prototype.flipFaces=function(G){G===void 0&&(G=!1);var Q,oe,re=T.a.ExtractFromMesh(this);if(G&&this.isVerticesDataPresent(c.b.NormalKind)&&re.normals)for(Q=0;Q<re.normals.length;Q++)re.normals[Q]*=-1;if(re.indices)for(Q=0;Q<re.indices.length;Q+=3)oe=re.indices[Q+1],re.indices[Q+1]=re.indices[Q+2],re.indices[Q+2]=oe;return re.applyToMesh(this,this.isVertexBufferUpdatable(c.b.PositionKind)),this},L.prototype.increaseVertices=function(G){var Q=T.a.ExtractFromMesh(this),oe=Q.uvs,re=Q.indices,Y=Q.positions,k=Q.normals;if(re&&Y&&k&&oe){for(var H,Z,W=G+1,q=new Array,he=0;he<W+1;he++)q[he]=new Array;var ge,me=new R.e(0,0,0),_e=new R.e(0,0,0),be=new R.d(0,0),Pe=new Array,ye=new Array,Be=new Array,ke=Y.length,We=oe.length;for(he=0;he<re.length;he+=3){ye[0]=re[he],ye[1]=re[he+1],ye[2]=re[he+2];for(var je=0;je<3;je++)if(H=ye[je],Z=ye[(je+1)%3],Be[H]===void 0&&Be[Z]===void 0?(Be[H]=new Array,Be[Z]=new Array):(Be[H]===void 0&&(Be[H]=new Array),Be[Z]===void 0&&(Be[Z]=new Array)),Be[H][Z]===void 0&&Be[Z][H]===void 0){Be[H][Z]=[],me.x=(Y[3*Z]-Y[3*H])/W,me.y=(Y[3*Z+1]-Y[3*H+1])/W,me.z=(Y[3*Z+2]-Y[3*H+2])/W,_e.x=(k[3*Z]-k[3*H])/W,_e.y=(k[3*Z+1]-k[3*H+1])/W,_e.z=(k[3*Z+2]-k[3*H+2])/W,be.x=(oe[2*Z]-oe[2*H])/W,be.y=(oe[2*Z+1]-oe[2*H+1])/W,Be[H][Z].push(H);for(var He=1;He<W;He++)Be[H][Z].push(Y.length/3),Y[ke]=Y[3*H]+He*me.x,k[ke++]=k[3*H]+He*_e.x,Y[ke]=Y[3*H+1]+He*me.y,k[ke++]=k[3*H+1]+He*_e.y,Y[ke]=Y[3*H+2]+He*me.z,k[ke++]=k[3*H+2]+He*_e.z,oe[We++]=oe[2*H]+He*be.x,oe[We++]=oe[2*H+1]+He*be.y;Be[H][Z].push(Z),Be[Z][H]=new Array,ge=Be[H][Z].length;for(var qe=0;qe<ge;qe++)Be[Z][H][qe]=Be[H][Z][ge-1-qe]}for(q[0][0]=re[he],q[1][0]=Be[re[he]][re[he+1]][1],q[1][1]=Be[re[he]][re[he+2]][1],He=2;He<W;He++)for(q[He][0]=Be[re[he]][re[he+1]][He],q[He][He]=Be[re[he]][re[he+2]][He],me.x=(Y[3*q[He][He]]-Y[3*q[He][0]])/He,me.y=(Y[3*q[He][He]+1]-Y[3*q[He][0]+1])/He,me.z=(Y[3*q[He][He]+2]-Y[3*q[He][0]+2])/He,_e.x=(k[3*q[He][He]]-k[3*q[He][0]])/He,_e.y=(k[3*q[He][He]+1]-k[3*q[He][0]+1])/He,_e.z=(k[3*q[He][He]+2]-k[3*q[He][0]+2])/He,be.x=(oe[2*q[He][He]]-oe[2*q[He][0]])/He,be.y=(oe[2*q[He][He]+1]-oe[2*q[He][0]+1])/He,je=1;je<He;je++)q[He][je]=Y.length/3,Y[ke]=Y[3*q[He][0]]+je*me.x,k[ke++]=k[3*q[He][0]]+je*_e.x,Y[ke]=Y[3*q[He][0]+1]+je*me.y,k[ke++]=k[3*q[He][0]+1]+je*_e.y,Y[ke]=Y[3*q[He][0]+2]+je*me.z,k[ke++]=k[3*q[He][0]+2]+je*_e.z,oe[We++]=oe[2*q[He][0]]+je*be.x,oe[We++]=oe[2*q[He][0]+1]+je*be.y;for(q[W]=Be[re[he+1]][re[he+2]],Pe.push(q[0][0],q[1][0],q[1][1]),He=1;He<W;He++){for(je=0;je<He;je++)Pe.push(q[He][je],q[He+1][je],q[He+1][je+1]),Pe.push(q[He][je],q[He+1][je+1],q[He][je+1]);Pe.push(q[He][je],q[He+1][je],q[He+1][je+1])}}Q.indices=Pe,Q.applyToMesh(this,this.isVertexBufferUpdatable(c.b.PositionKind))}else N.a.Warn("VertexData contains null entries")},L.prototype.forceSharedVertices=function(){var G=T.a.ExtractFromMesh(this),Q=G.uvs,oe=G.indices,re=G.positions,Y=G.colors;if(oe===void 0||re===void 0||oe===null||re===null)N.a.Warn("VertexData contains empty entries");else{for(var k,H,Z=new Array,W=new Array,q=new Array,he=new Array,ge=new Array,me=0,_e={},be=0;be<oe.length;be+=3){H=[oe[be],oe[be+1],oe[be+2]],ge=new Array;for(var Pe=0;Pe<3;Pe++){ge[Pe]="";for(var ye=0;ye<3;ye++)Math.abs(re[3*H[Pe]+ye])<1e-8&&(re[3*H[Pe]+ye]=0),ge[Pe]+=re[3*H[Pe]+ye]+"|"}if(ge[0]!=ge[1]&&ge[0]!=ge[2]&&ge[1]!=ge[2])for(Pe=0;Pe<3;Pe++){if((k=_e[ge[Pe]])===void 0){for(_e[ge[Pe]]=me,k=me++,ye=0;ye<3;ye++)Z.push(re[3*H[Pe]+ye]);if(Y!=null)for(ye=0;ye<4;ye++)he.push(Y[4*H[Pe]+ye]);if(Q!=null)for(ye=0;ye<2;ye++)q.push(Q[2*H[Pe]+ye])}W.push(k)}}var Be=new Array;T.a.ComputeNormals(Z,W,Be),G.positions=Z,G.indices=W,G.normals=Be,Q!=null&&(G.uvs=q),Y!=null&&(G.colors=he),G.applyToMesh(this,this.isVertexBufferUpdatable(c.b.PositionKind))}},L._instancedMeshFactory=function(G,Q){throw V.a.WarnImport("InstancedMesh")},L._PhysicsImpostorParser=function(G,Q,oe){throw V.a.WarnImport("PhysicsImpostor")},L.prototype.createInstance=function(G){var Q=this.geometry;if(Q&&Q.meshes.length>1)for(var oe=0,re=Q.meshes.slice(0);oe<re.length;oe++){var Y=re[oe];Y!==this&&Y.makeGeometryUnique()}return L._instancedMeshFactory(G,this)},L.prototype.synchronizeInstances=function(){this._geometry&&this._geometry.meshes.length!==1&&this.instances.length&&this.makeGeometryUnique();for(var G=0;G<this.instances.length;G++)this.instances[G]._syncSubMeshes();return this},L.prototype.optimizeIndices=function(G){var Q=this,oe=this.getIndices(),re=this.getVerticesData(c.b.PositionKind);if(!re||!oe)return this;for(var Y=new Array,k=0;k<re.length;k+=3)Y.push(R.e.FromArray(re,k));var H=new Array;return x.a.SyncAsyncForLoop(Y.length,40,function(Z){for(var W=Y.length-1-Z,q=Y[W],he=0;he<W;++he){var ge=Y[he];if(q.equals(ge)){H[W]=he;break}}},function(){for(var Z=0;Z<oe.length;++Z)oe[Z]=H[oe[Z]]||oe[Z];var W=Q.subMeshes.slice(0);Q.setIndices(oe),Q.subMeshes=W,G&&G(Q)}),this},L.prototype.serialize=function(G){G.name=this.name,G.id=this.id,G.uniqueId=this.uniqueId,G.type=this.getClassName(),M.a&&M.a.HasTags(this)&&(G.tags=M.a.GetTags(this)),G.position=this.position.asArray(),this.rotationQuaternion?G.rotationQuaternion=this.rotationQuaternion.asArray():this.rotation&&(G.rotation=this.rotation.asArray()),G.scaling=this.scaling.asArray(),this._postMultiplyPivotMatrix?G.pivotMatrix=this.getPivotMatrix().asArray():G.localMatrix=this.getPivotMatrix().asArray(),G.isEnabled=this.isEnabled(!1),G.isVisible=this.isVisible,G.infiniteDistance=this.infiniteDistance,G.pickable=this.isPickable,G.receiveShadows=this.receiveShadows,G.billboardMode=this.billboardMode,G.visibility=this.visibility,G.checkCollisions=this.checkCollisions,G.isBlocker=this.isBlocker,G.overrideMaterialSideOrientation=this.overrideMaterialSideOrientation,this.parent&&(G.parentId=this.parent.id),G.isUnIndexed=this.isUnIndexed;var Q=this._geometry;if(Q){var oe=Q.id;G.geometryId=oe,G.subMeshes=[];for(var re=0;re<this.subMeshes.length;re++){var Y=this.subMeshes[re];G.subMeshes.push({materialIndex:Y.materialIndex,verticesStart:Y.verticesStart,verticesCount:Y.verticesCount,indexStart:Y.indexStart,indexCount:Y.indexCount})}}this.material?this.material.doNotSerialize||(G.materialId=this.material.id):this.material=null,this.morphTargetManager&&(G.morphTargetManagerId=this.morphTargetManager.uniqueId),this.skeleton&&(G.skeletonId=this.skeleton.id,G.numBoneInfluencers=this.numBoneInfluencers),this.getScene()._getComponent(X.a.NAME_PHYSICSENGINE)&&(Z=this.getPhysicsImpostor())&&(G.physicsMass=Z.getParam("mass"),G.physicsFriction=Z.getParam("friction"),G.physicsRestitution=Z.getParam("mass"),G.physicsImpostor=Z.type),this.metadata&&(G.metadata=this.metadata),G.instances=[];for(var k=0;k<this.instances.length;k++){var H=this.instances[k];if(!H.doNotSerialize){var Z,W={name:H.name,id:H.id,isEnabled:H.isEnabled(!1),isVisible:H.isVisible,isPickable:H.isPickable,checkCollisions:H.checkCollisions,position:H.position.asArray(),scaling:H.scaling.asArray()};H.parent&&(W.parentId=H.parent.id),H.rotationQuaternion?W.rotationQuaternion=H.rotationQuaternion.asArray():H.rotation&&(W.rotation=H.rotation.asArray()),this.getScene()._getComponent(X.a.NAME_PHYSICSENGINE)&&(Z=H.getPhysicsImpostor())&&(W.physicsMass=Z.getParam("mass"),W.physicsFriction=Z.getParam("friction"),W.physicsRestitution=Z.getParam("mass"),W.physicsImpostor=Z.type),H.metadata&&(W.metadata=H.metadata),G.instances.push(W),w.a.AppendSerializedAnimations(H,W),W.ranges=H.serializeAnimationRanges()}}if(this._thinInstanceDataStorage.instancesCount&&this._thinInstanceDataStorage.matrixData&&(G.thinInstances={instancesCount:this._thinInstanceDataStorage.instancesCount,matrixData:x.b.SliceToArray(this._thinInstanceDataStorage.matrixData),matrixBufferSize:this._thinInstanceDataStorage.matrixBufferSize},this._userThinInstanceBuffersStorage)){var q={data:{},sizes:{},strides:{}};for(var he in this._userThinInstanceBuffersStorage.data)q.data[he]=x.b.SliceToArray(this._userThinInstanceBuffersStorage.data[he]),q.sizes[he]=this._userThinInstanceBuffersStorage.sizes[he],q.strides[he]=this._userThinInstanceBuffersStorage.strides[he];G.thinInstances.userThinInstance=q}w.a.AppendSerializedAnimations(this,G),G.ranges=this.serializeAnimationRanges(),G.layerMask=this.layerMask,G.alphaIndex=this.alphaIndex,G.hasVertexAlpha=this.hasVertexAlpha,G.overlayAlpha=this.overlayAlpha,G.overlayColor=this.overlayColor.asArray(),G.renderOverlay=this.renderOverlay,G.applyFog=this.applyFog,this.actionManager&&(G.actions=this.actionManager.serialize(this.name))},L.prototype._syncGeometryWithMorphTargetManager=function(){if(this.geometry){this._markSubMeshesAsAttributesDirty();var G=this._internalMeshDataInfo._morphTargetManager;if(G&&G.vertexCount){if(G.vertexCount!==this.getTotalVertices())return N.a.Error("Mesh is incompatible with morph targets. Targets and mesh must all have the same vertices count."),void(this.morphTargetManager=null);for(var Q=0;Q<G.numInfluencers;Q++){var oe=G.getActiveTarget(Q),re=oe.getPositions();if(!re)return void N.a.Error("Invalid morph target. Target must have positions.");this.geometry.setVerticesData(c.b.PositionKind+Q,re,!1,3);var Y=oe.getNormals();Y&&this.geometry.setVerticesData(c.b.NormalKind+Q,Y,!1,3);var k=oe.getTangents();k&&this.geometry.setVerticesData(c.b.TangentKind+Q,k,!1,3);var H=oe.getUVs();H&&this.geometry.setVerticesData(c.b.UVKind+"_"+Q,H,!1,2)}}else for(Q=0;this.geometry.isVerticesDataPresent(c.b.PositionKind+Q);)this.geometry.removeVerticesData(c.b.PositionKind+Q),this.geometry.isVerticesDataPresent(c.b.NormalKind+Q)&&this.geometry.removeVerticesData(c.b.NormalKind+Q),this.geometry.isVerticesDataPresent(c.b.TangentKind+Q)&&this.geometry.removeVerticesData(c.b.TangentKind+Q),this.geometry.isVerticesDataPresent(c.b.UVKind+Q)&&this.geometry.removeVerticesData(c.b.UVKind+"_"+Q),Q++}},L.Parse=function(G,Q,oe){var re;if((re=G.type&&G.type==="GroundMesh"?L._GroundMeshParser(G,Q):new L(G.name,Q)).id=G.id,M.a&&M.a.AddTagsTo(re,G.tags),re.position=R.e.FromArray(G.position),G.metadata!==void 0&&(re.metadata=G.metadata),G.rotationQuaternion?re.rotationQuaternion=R.b.FromArray(G.rotationQuaternion):G.rotation&&(re.rotation=R.e.FromArray(G.rotation)),re.scaling=R.e.FromArray(G.scaling),G.localMatrix?re.setPreTransformMatrix(R.a.FromArray(G.localMatrix)):G.pivotMatrix&&re.setPivotMatrix(R.a.FromArray(G.pivotMatrix)),re.setEnabled(G.isEnabled),re.isVisible=G.isVisible,re.infiniteDistance=G.infiniteDistance,re.showBoundingBox=G.showBoundingBox,re.showSubMeshesBoundingBox=G.showSubMeshesBoundingBox,G.applyFog!==void 0&&(re.applyFog=G.applyFog),G.pickable!==void 0&&(re.isPickable=G.pickable),G.alphaIndex!==void 0&&(re.alphaIndex=G.alphaIndex),re.receiveShadows=G.receiveShadows,re.billboardMode=G.billboardMode,G.visibility!==void 0&&(re.visibility=G.visibility),re.checkCollisions=G.checkCollisions,re.overrideMaterialSideOrientation=G.overrideMaterialSideOrientation,G.isBlocker!==void 0&&(re.isBlocker=G.isBlocker),re._shouldGenerateFlatShading=G.useFlatShading,G.freezeWorldMatrix&&(re._waitingData.freezeWorldMatrix=G.freezeWorldMatrix),G.parentId&&(re._waitingParentId=G.parentId),G.actions!==void 0&&(re._waitingData.actions=G.actions),G.overlayAlpha!==void 0&&(re.overlayAlpha=G.overlayAlpha),G.overlayColor!==void 0&&(re.overlayColor=C.a.FromArray(G.overlayColor)),G.renderOverlay!==void 0&&(re.renderOverlay=G.renderOverlay),re.isUnIndexed=!!G.isUnIndexed,re.hasVertexAlpha=G.hasVertexAlpha,G.delayLoadingFile?(re.delayLoadState=D.a.DELAYLOADSTATE_NOTLOADED,re.delayLoadingFile=oe+G.delayLoadingFile,re._boundingInfo=new l.a(R.e.FromArray(G.boundingBoxMinimum),R.e.FromArray(G.boundingBoxMaximum)),G._binaryInfo&&(re._binaryInfo=G._binaryInfo),re._delayInfo=[],G.hasUVs&&re._delayInfo.push(c.b.UVKind),G.hasUVs2&&re._delayInfo.push(c.b.UV2Kind),G.hasUVs3&&re._delayInfo.push(c.b.UV3Kind),G.hasUVs4&&re._delayInfo.push(c.b.UV4Kind),G.hasUVs5&&re._delayInfo.push(c.b.UV5Kind),G.hasUVs6&&re._delayInfo.push(c.b.UV6Kind),G.hasColors&&re._delayInfo.push(c.b.ColorKind),G.hasMatricesIndices&&re._delayInfo.push(c.b.MatricesIndicesKind),G.hasMatricesWeights&&re._delayInfo.push(c.b.MatricesWeightsKind),re._delayLoadingFunction=A.a._ImportGeometry,E.a.ForceFullSceneLoadingForIncremental&&re._checkDelayState()):A.a._ImportGeometry(G,re),G.materialId?re.setMaterialByID(G.materialId):re.material=null,G.morphTargetManagerId>-1&&(re.morphTargetManager=Q.getMorphTargetManagerById(G.morphTargetManagerId)),G.skeletonId!==void 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q;k=Z.animations[Y],(q=I.a.GetClass("BABYLON.Animation"))&&W.animations.push(q.Parse(k))}m.a.ParseAnimationRanges(W,Z,Q),Z.autoAnimate&&Q.beginAnimation(W,Z.autoAnimateFrom,Z.autoAnimateTo,Z.autoAnimateLoop,Z.autoAnimateSpeed||1)}}if(G.thinInstances){var he=G.thinInstances;if(he.matrixData?(re.thinInstanceSetBuffer("matrix",new Float32Array(he.matrixData),16,!1),re._thinInstanceDataStorage.matrixBufferSize=he.matrixBufferSize,re._thinInstanceDataStorage.instancesCount=he.instancesCount):re._thinInstanceDataStorage.matrixBufferSize=he.matrixBufferSize,G.thinInstances.userThinInstance){var ge=G.thinInstances.userThinInstance;for(var me in ge.data)re.thinInstanceSetBuffer(me,new Float32Array(ge.data[me]),ge.strides[me],!1),re._userThinInstanceBuffersStorage.sizes[me]=ge.sizes[me]}}return re},L.CreateRibbon=function(G,Q,oe,re,Y,k,H,Z,W){throw V.a.WarnImport("MeshBuilder")},L.CreateDisc=function(G,Q,oe,re,Y,k){throw V.a.WarnImport("MeshBuilder")},L.CreateBox=function(G,Q,oe,re,Y){throw 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V.a.WarnImport("MeshBuilder")},L.CreateLathe=function(G,Q,oe,re,Y,k,H){throw V.a.WarnImport("MeshBuilder")},L.CreatePlane=function(G,Q,oe,re,Y){throw V.a.WarnImport("MeshBuilder")},L.CreateGround=function(G,Q,oe,re,Y,k){throw V.a.WarnImport("MeshBuilder")},L.CreateTiledGround=function(G,Q,oe,re,Y,k,H,Z,W){throw V.a.WarnImport("MeshBuilder")},L.CreateGroundFromHeightMap=function(G,Q,oe,re,Y,k,H,Z,W,q,he){throw V.a.WarnImport("MeshBuilder")},L.CreateTube=function(G,Q,oe,re,Y,k,H,Z,W,q){throw V.a.WarnImport("MeshBuilder")},L.CreatePolyhedron=function(G,Q,oe){throw V.a.WarnImport("MeshBuilder")},L.CreateIcoSphere=function(G,Q,oe){throw V.a.WarnImport("MeshBuilder")},L.CreateDecal=function(G,Q,oe,re,Y,k){throw V.a.WarnImport("MeshBuilder")},L.CreateCapsule=function(G,Q,oe){throw V.a.WarnImport("MeshBuilder")},L.prototype.setPositionsForCPUSkinning=function(){var G=this._internalMeshDataInfo;if(!G._sourcePositions){var Q=this.getVerticesData(c.b.PositionKind);if(!Q)return G._sourcePositions;G._sourcePositions=new Float32Array(Q),this.isVertexBufferUpdatable(c.b.PositionKind)||this.setVerticesData(c.b.PositionKind,Q,!0)}return G._sourcePositions},L.prototype.setNormalsForCPUSkinning=function(){var G=this._internalMeshDataInfo;if(!G._sourceNormals){var Q=this.getVerticesData(c.b.NormalKind);if(!Q)return G._sourceNormals;G._sourceNormals=new Float32Array(Q),this.isVertexBufferUpdatable(c.b.NormalKind)||this.setVerticesData(c.b.NormalKind,Q,!0)}return G._sourceNormals},L.prototype.applySkeleton=function(G){if(!this.geometry)return this;if(this.geometry._softwareSkinningFrameId==this.getScene().getFrameId())return this;if(this.geometry._softwareSkinningFrameId=this.getScene().getFrameId(),!this.isVerticesDataPresent(c.b.PositionKind))return this;if(!this.isVerticesDataPresent(c.b.MatricesIndicesKind))return this;if(!this.isVerticesDataPresent(c.b.MatricesWeightsKind))return this;var Q=this.isVerticesDataPresent(c.b.NormalKind),oe=this._internalMeshDataInfo;if(!oe._sourcePositions){var re=this.subMeshes.slice();this.setPositionsForCPUSkinning(),this.subMeshes=re}Q&&!oe._sourceNormals&&this.setNormalsForCPUSkinning();var Y=this.getVerticesData(c.b.PositionKind);if(!Y)return this;Y instanceof Float32Array||(Y=new Float32Array(Y));var k=this.getVerticesData(c.b.NormalKind);if(Q){if(!k)return this;k instanceof Float32Array||(k=new Float32Array(k))}var H=this.getVerticesData(c.b.MatricesIndicesKind),Z=this.getVerticesData(c.b.MatricesWeightsKind);if(!Z||!H)return this;for(var W,q=this.numBoneInfluencers>4,he=q?this.getVerticesData(c.b.MatricesIndicesExtraKind):null,ge=q?this.getVerticesData(c.b.MatricesWeightsExtraKind):null,me=G.getTransformMatrices(this),_e=R.e.Zero(),be=new R.a,Pe=new R.a,ye=0,Be=0;Be<Y.length;Be+=3,ye+=4){var 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R.e.Center(Q.min,Q.max)},L.MergeMeshes=function(G,Q,oe,re,Y,k){var H;if(Q===void 0&&(Q=!0),!oe){var Z=0;for(H=0;H<G.length;H++)if(G[H]&&(Z+=G[H].getTotalVertices())>=65536)return N.a.Warn("Cannot merge meshes because resulting mesh will have more than 65536 vertices. 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g=A*T,l=c/60,h=g*(1-Math.abs(l%2-1)),v=0,E=0,D=0;l>=0&&l<=1?(v=g,E=h):l>=1&&l<=2?(v=h,E=g):l>=2&&l<=3?(E=g,D=h):l>=3&&l<=4?(E=h,D=g):l>=4&&l<=5?(v=h,D=g):l>=5&&l<=6&&(v=g,D=h);var w=A-g;S.set(v+w,E+w,D+w)},m.FromHexString=function(c){if(c.substring(0,1)!=="#"||c.length!==7)return new m(0,0,0);var T=parseInt(c.substring(1,3),16),A=parseInt(c.substring(3,5),16),S=parseInt(c.substring(5,7),16);return m.FromInts(T,A,S)},m.FromArray=function(c,T){return T===void 0&&(T=0),new m(c[T],c[T+1],c[T+2])},m.FromArrayToRef=function(c,T,A){T===void 0&&(T=0),A.r=c[T],A.g=c[T+1],A.b=c[T+2]},m.FromInts=function(c,T,A){return new m(c/255,T/255,A/255)},m.Lerp=function(c,T,A){var S=new m(0,0,0);return m.LerpToRef(c,T,A,S),S},m.LerpToRef=function(c,T,A,S){S.r=c.r+(T.r-c.r)*A,S.g=c.g+(T.g-c.g)*A,S.b=c.b+(T.b-c.b)*A},m.Red=function(){return new m(1,0,0)},m.Green=function(){return new m(0,1,0)},m.Blue=function(){return new m(0,0,1)},m.Black=function(){return new m(0,0,0)},Object.defineProperty(m,"BlackReadOnly",{get:function(){return m._BlackReadOnly},enumerable:!1,configurable:!0}),m.White=function(){return new m(1,1,1)},m.Purple=function(){return new m(.5,0,.5)},m.Magenta=function(){return new m(1,0,1)},m.Yellow=function(){return new m(1,1,0)},m.Gray=function(){return new m(.5,.5,.5)},m.Teal=function(){return new m(0,1,1)},m.Random=function(){return new m(Math.random(),Math.random(),Math.random())},m._BlackReadOnly=m.Black(),m}(),R=function(){function m(c,T,A,S){c===void 0&&(c=0),T===void 0&&(T=0),A===void 0&&(A=0),S===void 0&&(S=1),this.r=c,this.g=T,this.b=A,this.a=S}return m.prototype.addInPlace=function(c){return this.r+=c.r,this.g+=c.g,this.b+=c.b,this.a+=c.a,this},m.prototype.asArray=function(){var c=new Array;return this.toArray(c,0),c},m.prototype.toArray=function(c,T){return T===void 0&&(T=0),c[T]=this.r,c[T+1]=this.g,c[T+2]=this.b,c[T+3]=this.a,this},m.prototype.fromArray=function(c,T){return T===void 0&&(T=0),m.FromArrayToRef(c,T,this),this},m.prototype.equals=function(c){return c&&this.r===c.r&&this.g===c.g&&this.b===c.b&&this.a===c.a},m.prototype.add=function(c){return new m(this.r+c.r,this.g+c.g,this.b+c.b,this.a+c.a)},m.prototype.subtract=function(c){return new m(this.r-c.r,this.g-c.g,this.b-c.b,this.a-c.a)},m.prototype.subtractToRef=function(c,T){return T.r=this.r-c.r,T.g=this.g-c.g,T.b=this.b-c.b,T.a=this.a-c.a,this},m.prototype.scale=function(c){return new m(this.r*c,this.g*c,this.b*c,this.a*c)},m.prototype.scaleToRef=function(c,T){return T.r=this.r*c,T.g=this.g*c,T.b=this.b*c,T.a=this.a*c,this},m.prototype.scaleAndAddToRef=function(c,T){return T.r+=this.r*c,T.g+=this.g*c,T.b+=this.b*c,T.a+=this.a*c,this},m.prototype.clampToRef=function(c,T,A){return c===void 0&&(c=0),T===void 0&&(T=1),A.r=U.a.Clamp(this.r,c,T),A.g=U.a.Clamp(this.g,c,T),A.b=U.a.Clamp(this.b,c,T),A.a=U.a.Clamp(this.a,c,T),this},m.prototype.multiply=function(c){return new m(this.r*c.r,this.g*c.g,this.b*c.b,this.a*c.a)},m.prototype.multiplyToRef=function(c,T){return T.r=this.r*c.r,T.g=this.g*c.g,T.b=this.b*c.b,T.a=this.a*c.a,T},m.prototype.toString=function(){return"{R: "+this.r+" G:"+this.g+" B:"+this.b+" A:"+this.a+"}"},m.prototype.getClassName=function(){return"Color4"},m.prototype.getHashCode=function(){var c=255*this.r|0;return c=397*(c=397*(c=397*c^(255*this.g|0))^(255*this.b|0))^(255*this.a|0)},m.prototype.clone=function(){return new m(this.r,this.g,this.b,this.a)},m.prototype.copyFrom=function(c){return this.r=c.r,this.g=c.g,this.b=c.b,this.a=c.a,this},m.prototype.copyFromFloats=function(c,T,A,S){return this.r=c,this.g=T,this.b=A,this.a=S,this},m.prototype.set=function(c,T,A,S){return this.copyFromFloats(c,T,A,S)},m.prototype.toHexString=function(c){c===void 0&&(c=!1);var T=255*this.r|0,A=255*this.g|0,S=255*this.b|0;if(c)return"#"+U.a.ToHex(T)+U.a.ToHex(A)+U.a.ToHex(S);var g=255*this.a|0;return"#"+U.a.ToHex(T)+U.a.ToHex(A)+U.a.ToHex(S)+U.a.ToHex(g)},m.prototype.toLinearSpace=function(){var c=new m;return this.toLinearSpaceToRef(c),c},m.prototype.toLinearSpaceToRef=function(c){return c.r=Math.pow(this.r,_.c),c.g=Math.pow(this.g,_.c),c.b=Math.pow(this.b,_.c),c.a=this.a,this},m.prototype.toGammaSpace=function(){var c=new m;return this.toGammaSpaceToRef(c),c},m.prototype.toGammaSpaceToRef=function(c){return c.r=Math.pow(this.r,_.b),c.g=Math.pow(this.g,_.b),c.b=Math.pow(this.b,_.b),c.a=this.a,this},m.FromHexString=function(c){if(c.substring(0,1)!=="#"||c.length!==9)return new m(0,0,0,0);var T=parseInt(c.substring(1,3),16),A=parseInt(c.substring(3,5),16),S=parseInt(c.substring(5,7),16),g=parseInt(c.substring(7,9),16);return m.FromInts(T,A,S,g)},m.Lerp=function(c,T,A){var S=new m(0,0,0,0);return m.LerpToRef(c,T,A,S),S},m.LerpToRef=function(c,T,A,S){S.r=c.r+(T.r-c.r)*A,S.g=c.g+(T.g-c.g)*A,S.b=c.b+(T.b-c.b)*A,S.a=c.a+(T.a-c.a)*A},m.FromColor3=function(c,T){return T===void 0&&(T=1),new m(c.r,c.g,c.b,T)},m.FromArray=function(c,T){return T===void 0&&(T=0),new m(c[T],c[T+1],c[T+2],c[T+3])},m.FromArrayToRef=function(c,T,A){T===void 0&&(T=0),A.r=c[T],A.g=c[T+1],A.b=c[T+2],A.a=c[T+3]},m.FromInts=function(c,T,A,S){return new m(c/255,T/255,A/255,S/255)},m.CheckColors4=function(c,T){if(c.length===3*T){for(var A=[],S=0;S<c.length;S+=3){var g=S/3*4;A[g]=c[S],A[g+1]=c[S+1],A[g+2]=c[S+2],A[g+3]=1}return A}return c},m}(),C=function(){function m(){}return m.Color3=x.a.BuildArray(3,M.Black),m.Color4=x.a.BuildArray(3,function(){return new R(0,0,0,0)}),m}();u.a.RegisteredTypes["BABYLON.Color3"]=M,u.a.RegisteredTypes["BABYLON.Color4"]=R},function(Me,y,f){f.d(y,"a",function(){return l});var U=f(1),_=f(3),x=f(6),u=f(0),M=f(52),R=f(2),C=f(11),m=f(21),c=f(104),T=f(122),A=f(64),S=f(34),g=f(150),l=function(h){function v(E,D,w,N,I,V,X,j,ne,te,de,pe){w===void 0&&(w=!1),N===void 0&&(N=!0),I===void 0&&(I=v.TRILINEAR_SAMPLINGMODE),V===void 0&&(V=null),X===void 0&&(X=null),j===void 0&&(j=null),ne===void 0&&(ne=!1);var ae=h.call(this,D)||this;ae.url=null,ae.uOffset=0,ae.vOffset=0,ae.uScale=1,ae.vScale=1,ae.uAng=0,ae.vAng=0,ae.wAng=0,ae.uRotationCenter=.5,ae.vRotationCenter=.5,ae.wRotationCenter=.5,ae.homogeneousRotationInUVTransform=!1,ae.inspectableCustomProperties=null,ae._noMipmap=!1,ae._invertY=!1,ae._rowGenerationMatrix=null,ae._cachedTextureMatrix=null,ae._projectionModeMatrix=null,ae._t0=null,ae._t1=null,ae._t2=null,ae._cachedUOffset=-1,ae._cachedVOffset=-1,ae._cachedUScale=0,ae._cachedVScale=0,ae._cachedUAng=-1,ae._cachedVAng=-1,ae._cachedWAng=-1,ae._cachedProjectionMatrixId=-1,ae._cachedURotationCenter=-1,ae._cachedVRotationCenter=-1,ae._cachedWRotationCenter=-1,ae._cachedHomogeneousRotationInUVTransform=!1,ae._cachedCoordinatesMode=-1,ae._initialSamplingMode=v.BILINEAR_SAMPLINGMODE,ae._buffer=null,ae._deleteBuffer=!1,ae._format=null,ae._delayedOnLoad=null,ae._delayedOnError=null,ae.onLoadObservable=new x.c,ae._isBlocking=!0,ae.name=E||"",ae.url=E,ae._noMipmap=w,ae._invertY=N,ae._initialSamplingMode=I,ae._buffer=j,ae._deleteBuffer=ne,ae._mimeType=de,ae._loaderOptions=pe,te&&(ae._format=te);var ee=ae.getScene(),K=ae._getEngine();if(!K)return ae;K.onBeforeTextureInitObservable.notifyObservers(ae);var $=function(){ae._texture&&(ae._texture._invertVScale&&(ae.vScale*=-1,ae.vOffset+=1),ae._texture._cachedWrapU!==null&&(ae.wrapU=ae._texture._cachedWrapU,ae._texture._cachedWrapU=null),ae._texture._cachedWrapV!==null&&(ae.wrapV=ae._texture._cachedWrapV,ae._texture._cachedWrapV=null),ae._texture._cachedWrapR!==null&&(ae.wrapR=ae._texture._cachedWrapR,ae._texture._cachedWrapR=null)),ae.onLoadObservable.hasObservers()&&ae.onLoadObservable.notifyObservers(ae),V&&V(),!ae.isBlocking&&ee&&ee.resetCachedMaterial()};return ae.url?(ae._texture=ae._getFromCache(ae.url,w,I,N),ae._texture?ae._texture.isReady?c.a.SetImmediate(function(){return $()}):ae._texture.onLoadedObservable.add($):ee&&ee.useDelayedTextureLoading?(ae.delayLoadState=R.a.DELAYLOADSTATE_NOTLOADED,ae._delayedOnLoad=$,ae._delayedOnError=X):(ae._texture=K.createTexture(ae.url,w,N,ee,I,$,X,ae._buffer,void 0,ae._format,null,de,pe),ne&&(ae._buffer=null)),ae):(ae._delayedOnLoad=$,ae._delayedOnError=X,ae)}return Object(U.d)(v,h),Object.defineProperty(v.prototype,"noMipmap",{get:function(){return this._noMipmap},enumerable:!1,configurable:!0}),Object.defineProperty(v.prototype,"mimeType",{get:function(){return this._mimeType},enumerable:!1,configurable:!0}),Object.defineProperty(v.prototype,"isBlocking",{get:function(){return this._isBlocking},set:function(E){this._isBlocking=E},enumerable:!1,configurable:!0}),Object.defineProperty(v.prototype,"samplingMode",{get:function(){return this._texture?this._texture.samplingMode:this._initialSamplingMode},enumerable:!1,configurable:!0}),Object.defineProperty(v.prototype,"invertY",{get:function(){return this._invertY},enumerable:!1,configurable:!0}),v.prototype.updateURL=function(E,D,w){D===void 0&&(D=null),this.url&&(this.releaseInternalTexture(),this.getScene().markAllMaterialsAsDirty(R.a.MATERIAL_TextureDirtyFlag)),this.name&&!S.a.StartsWith(this.name,"data:")||(this.name=E),this.url=E,this._buffer=D,this.delayLoadState=R.a.DELAYLOADSTATE_NOTLOADED,w&&(this._delayedOnLoad=w),this.delayLoad()},v.prototype.delayLoad=function(){if(this.delayLoadState===R.a.DELAYLOADSTATE_NOTLOADED){var E=this.getScene();E&&(this.delayLoadState=R.a.DELAYLOADSTATE_LOADED,this._texture=this._getFromCache(this.url,this._noMipmap,this.samplingMode,this._invertY),this._texture?this._delayedOnLoad&&(this._texture.isReady?c.a.SetImmediate(this._delayedOnLoad):this._texture.onLoadedObservable.add(this._delayedOnLoad)):(this._texture=E.getEngine().createTexture(this.url,this._noMipmap,this._invertY,E,this.samplingMode,this._delayedOnLoad,this._delayedOnError,this._buffer,null,this._format,null,this._mimeType,this._loaderOptions),this._deleteBuffer&&(this._buffer=null)),this._delayedOnLoad=null,this._delayedOnError=null)}},v.prototype._prepareRowForTextureGeneration=function(E,D,w,N){E*=this._cachedUScale,D*=this._cachedVScale,E-=this.uRotationCenter*this._cachedUScale,D-=this.vRotationCenter*this._cachedVScale,w-=this.wRotationCenter,u.e.TransformCoordinatesFromFloatsToRef(E,D,w,this._rowGenerationMatrix,N),N.x+=this.uRotationCenter*this._cachedUScale+this._cachedUOffset,N.y+=this.vRotationCenter*this._cachedVScale+this._cachedVOffset,N.z+=this.wRotationCenter},v.prototype.checkTransformsAreIdentical=function(E){return E!==null&&this.uOffset===E.uOffset&&this.vOffset===E.vOffset&&this.uScale===E.uScale&&this.vScale===E.vScale&&this.uAng===E.uAng&&this.vAng===E.vAng&&this.wAng===E.wAng},v.prototype.getTextureMatrix=function(E){var D=this;if(E===void 0&&(E=1),this.uOffset===this._cachedUOffset&&this.vOffset===this._cachedVOffset&&this.uScale*E===this._cachedUScale&&this.vScale===this._cachedVScale&&this.uAng===this._cachedUAng&&this.vAng===this._cachedVAng&&this.wAng===this._cachedWAng&&this.uRotationCenter===this._cachedURotationCenter&&this.vRotationCenter===this._cachedVRotationCenter&&this.wRotationCenter===this._cachedWRotationCenter&&this.homogeneousRotationInUVTransform===this._cachedHomogeneousRotationInUVTransform)return this._cachedTextureMatrix;this._cachedUOffset=this.uOffset,this._cachedVOffset=this.vOffset,this._cachedUScale=this.uScale*E,this._cachedVScale=this.vScale,this._cachedUAng=this.uAng,this._cachedVAng=this.vAng,this._cachedWAng=this.wAng,this._cachedURotationCenter=this.uRotationCenter,this._cachedVRotationCenter=this.vRotationCenter,this._cachedWRotationCenter=this.wRotationCenter,this._cachedHomogeneousRotationInUVTransform=this.homogeneousRotationInUVTransform,this._cachedTextureMatrix&&this._rowGenerationMatrix||(this._cachedTextureMatrix=u.a.Zero(),this._rowGenerationMatrix=new u.a,this._t0=u.e.Zero(),this._t1=u.e.Zero(),this._t2=u.e.Zero()),u.a.RotationYawPitchRollToRef(this.vAng,this.uAng,this.wAng,this._rowGenerationMatrix),this.homogeneousRotationInUVTransform?(u.a.TranslationToRef(-this._cachedURotationCenter,-this._cachedVRotationCenter,-this._cachedWRotationCenter,u.c.Matrix[0]),u.a.TranslationToRef(this._cachedURotationCenter,this._cachedVRotationCenter,this._cachedWRotationCenter,u.c.Matrix[1]),u.a.ScalingToRef(this._cachedUScale,this._cachedVScale,0,u.c.Matrix[2]),u.a.TranslationToRef(this._cachedUOffset,this._cachedVOffset,0,u.c.Matrix[3]),u.c.Matrix[0].multiplyToRef(this._rowGenerationMatrix,this._cachedTextureMatrix),this._cachedTextureMatrix.multiplyToRef(u.c.Matrix[1],this._cachedTextureMatrix),this._cachedTextureMatrix.multiplyToRef(u.c.Matrix[2],this._cachedTextureMatrix),this._cachedTextureMatrix.multiplyToRef(u.c.Matrix[3],this._cachedTextureMatrix),this._cachedTextureMatrix.setRowFromFloats(2,this._cachedTextureMatrix.m[12],this._cachedTextureMatrix.m[13],this._cachedTextureMatrix.m[14],1)):(this._prepareRowForTextureGeneration(0,0,0,this._t0),this._prepareRowForTextureGeneration(1,0,0,this._t1),this._prepareRowForTextureGeneration(0,1,0,this._t2),this._t1.subtractInPlace(this._t0),this._t2.subtractInPlace(this._t0),u.a.FromValuesToRef(this._t1.x,this._t1.y,this._t1.z,0,this._t2.x,this._t2.y,this._t2.z,0,this._t0.x,this._t0.y,this._t0.z,0,0,0,0,1,this._cachedTextureMatrix));var w=this.getScene();return w?(w.markAllMaterialsAsDirty(R.a.MATERIAL_TextureDirtyFlag,function(N){return N.hasTexture(D)}),this._cachedTextureMatrix):this._cachedTextureMatrix},v.prototype.getReflectionTextureMatrix=function(){var E=this,D=this.getScene();if(!D)return this._cachedTextureMatrix;if(this.uOffset===this._cachedUOffset&&this.vOffset===this._cachedVOffset&&this.uScale===this._cachedUScale&&this.vScale===this._cachedVScale&&this.coordinatesMode===this._cachedCoordinatesMode){if(this.coordinatesMode!==v.PROJECTION_MODE)return this._cachedTextureMatrix;if(this._cachedProjectionMatrixId===D.getProjectionMatrix().updateFlag)return this._cachedTextureMatrix}switch(this._cachedTextureMatrix||(this._cachedTextureMatrix=u.a.Zero()),this._projectionModeMatrix||(this._projectionModeMatrix=u.a.Zero()),this._cachedUOffset=this.uOffset,this._cachedVOffset=this.vOffset,this._cachedUScale=this.uScale,this._cachedVScale=this.vScale,this._cachedCoordinatesMode=this.coordinatesMode,this.coordinatesMode){case v.PLANAR_MODE:u.a.IdentityToRef(this._cachedTextureMatrix),this._cachedTextureMatrix[0]=this.uScale,this._cachedTextureMatrix[5]=this.vScale,this._cachedTextureMatrix[12]=this.uOffset,this._cachedTextureMatrix[13]=this.vOffset;break;case v.PROJECTION_MODE:u.a.FromValuesToRef(.5,0,0,0,0,-.5,0,0,0,0,0,0,.5,.5,1,1,this._projectionModeMatrix);var w=D.getProjectionMatrix();this._cachedProjectionMatrixId=w.updateFlag,w.multiplyToRef(this._projectionModeMatrix,this._cachedTextureMatrix);break;default:u.a.IdentityToRef(this._cachedTextureMatrix)}return D.markAllMaterialsAsDirty(R.a.MATERIAL_TextureDirtyFlag,function(N){return N.getActiveTextures().indexOf(E)!==-1}),this._cachedTextureMatrix},v.prototype.clone=function(){var E=this;return _.a.Clone(function(){return new v(E._texture?E._texture.url:null,E.getScene(),E._noMipmap,E._invertY,E.samplingMode,void 0,void 0,E._texture?E._texture._buffer:void 0)},this)},v.prototype.serialize=function(){var E=this.name;v.SerializeBuffers||S.a.StartsWith(this.name,"data:")&&(this.name=""),S.a.StartsWith(this.name,"data:")&&this.url===this.name&&(this.url="");var D=h.prototype.serialize.call(this);return D?((v.SerializeBuffers||v.ForceSerializeBuffers)&&(typeof this._buffer=="string"&&this._buffer.substr(0,5)==="data:"?(D.base64String=this._buffer,D.name=D.name.replace("data:","")):this.url&&S.a.StartsWith(this.url,"data:")&&this._buffer instanceof Uint8Array?D.base64String="data:image/png;base64,"+S.a.EncodeArrayBufferToBase64(this._buffer):v.ForceSerializeBuffers&&(D.base64String=g.a.GenerateBase64StringFromTexture(this))),D.invertY=this._invertY,D.samplingMode=this.samplingMode,this.name=E,D):null},v.prototype.getClassName=function(){return"Texture"},v.prototype.dispose=function(){h.prototype.dispose.call(this),this.onLoadObservable.clear(),this._delayedOnLoad=null,this._delayedOnError=null},v.Parse=function(E,D,w){if(E.customType){var N=T.a.Instantiate(E.customType).Parse(E,D,w);return E.samplingMode&&N.updateSamplingMode&&N._samplingMode&&N._samplingMode!==E.samplingMode&&N.updateSamplingMode(E.samplingMode),N}if(E.isCube&&!E.isRenderTarget)return v._CubeTextureParser(E,D,w);if(!E.name&&!E.isRenderTarget)return null;var I=function(){if(V&&V._texture&&(V._texture._cachedWrapU=null,V._texture._cachedWrapV=null,V._texture._cachedWrapR=null),E.samplingMode){var 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E=0;E<this.scenes.length;E++)for(var D=this.scenes[E],w=0;w<D.cameras.length;w++)D.cameras[w]._currentRenderId=0;this.onResizeObservable.hasObservers()&&this.onResizeObservable.notifyObservers(this)}return!0},l.prototype._deletePipelineContext=function(h){var v=h;v&&v.program&&v.transformFeedback&&(this.deleteTransformFeedback(v.transformFeedback),v.transformFeedback=null),g.prototype._deletePipelineContext.call(this,h)},l.prototype.createShaderProgram=function(h,v,E,D,w,N){N===void 0&&(N=null),w=w||this._gl,this.onBeforeShaderCompilationObservable.notifyObservers(this);var I=g.prototype.createShaderProgram.call(this,h,v,E,D,w,N);return this.onAfterShaderCompilationObservable.notifyObservers(this),I},l.prototype._createShaderProgram=function(h,v,E,D,w){w===void 0&&(w=null);var N=D.createProgram();if(h.program=N,!N)throw new Error("Unable to create program");if(D.attachShader(N,v),D.attachShader(N,E),this.webGLVersion>1&&w){var I=this.createTransformFeedback();this.bindTransformFeedback(I),this.setTranformFeedbackVaryings(N,w),h.transformFeedback=I}return D.linkProgram(N),this.webGLVersion>1&&w&&this.bindTransformFeedback(null),h.context=D,h.vertexShader=v,h.fragmentShader=E,h.isParallelCompiled||this._finalizePipelineContext(h),N},l.prototype._releaseTexture=function(h){g.prototype._releaseTexture.call(this,h),this.scenes.forEach(function(v){v.postProcesses.forEach(function(E){E._outputTexture==h&&(E._outputTexture=null)}),v.cameras.forEach(function(E){E._postProcesses.forEach(function(D){D&&D._outputTexture==h&&(D._outputTexture=null)})})})},l.prototype._rescaleTexture=function(h,v,E,D,w){var N=this;this._gl.texParameteri(this._gl.TEXTURE_2D,this._gl.TEXTURE_MAG_FILTER,this._gl.LINEAR),this._gl.texParameteri(this._gl.TEXTURE_2D,this._gl.TEXTURE_MIN_FILTER,this._gl.LINEAR),this._gl.texParameteri(this._gl.TEXTURE_2D,this._gl.TEXTURE_WRAP_S,this._gl.CLAMP_TO_EDGE),this._gl.texParameteri(this._gl.TEXTURE_2D,this._gl.TEXTURE_WRAP_T,this._gl.CLAMP_TO_EDGE);var I=this.createRenderTargetTexture({width:v.width,height:v.height},{generateMipMaps:!1,type:C.a.TEXTURETYPE_UNSIGNED_INT,samplingMode:C.a.TEXTURE_BILINEAR_SAMPLINGMODE,generateDepthBuffer:!1,generateStencilBuffer:!1});!this._rescalePostProcess&&l._RescalePostProcessFactory&&(this._rescalePostProcess=l._RescalePostProcessFactory(this)),this._rescalePostProcess.getEffect().executeWhenCompiled(function(){N._rescalePostProcess.onApply=function(X){X._bindTexture("textureSampler",h)};var V=E;V||(V=N.scenes[N.scenes.length-1]),V.postProcessManager.directRender([N._rescalePostProcess],I,!0),N._bindTextureDirectly(N._gl.TEXTURE_2D,v,!0),N._gl.copyTexImage2D(N._gl.TEXTURE_2D,0,D,0,0,v.width,v.height,0),N.unBindFramebuffer(I),N._releaseTexture(I),w&&w()})},l.prototype.getFps=function(){return this._fps},l.prototype.getDeltaTime=function(){return this._deltaTime},l.prototype._measureFps=function(){this._performanceMonitor.sampleFrame(),this._fps=this._performanceMonitor.averageFPS,this._deltaTime=this._performanceMonitor.instantaneousFrameTime||0},l.prototype._uploadImageToTexture=function(h,v,E,D){E===void 0&&(E=0),D===void 0&&(D=0);var w=this._gl,N=this._getWebGLTextureType(h.type),I=this._getInternalFormat(h.format),V=this._getRGBABufferInternalSizedFormat(h.type,I),X=h.isCube?w.TEXTURE_CUBE_MAP:w.TEXTURE_2D;this._bindTextureDirectly(X,h,!0),this._unpackFlipY(h.invertY);var j=w.TEXTURE_2D;h.isCube&&(j=w.TEXTURE_CUBE_MAP_POSITIVE_X+E),w.texImage2D(j,D,V,I,N,v),this._bindTextureDirectly(X,null,!0)},l.prototype.updateRenderTargetTextureSampleCount=function(h,v){if(this.webGLVersion<2||!h)return 1;if(h.samples===v)return v;var E=this._gl;if(v=Math.min(v,this.getCaps().maxMSAASamples),h._depthStencilBuffer&&(E.deleteRenderbuffer(h._depthStencilBuffer),h._depthStencilBuffer=null),h._MSAAFramebuffer&&(E.deleteFramebuffer(h._MSAAFramebuffer),h._MSAAFramebuffer=null),h._MSAARenderBuffer&&(E.deleteRenderbuffer(h._MSAARenderBuffer),h._MSAARenderBuffer=null),v>1&&E.renderbufferStorageMultisample){var D=E.createFramebuffer();if(!D)throw new Error("Unable to create multi sampled framebuffer");h._MSAAFramebuffer=D,this._bindUnboundFramebuffer(h._MSAAFramebuffer);var w=E.createRenderbuffer();if(!w)throw new Error("Unable to create multi sampled framebuffer");E.bindRenderbuffer(E.RENDERBUFFER,w),E.renderbufferStorageMultisample(E.RENDERBUFFER,v,this._getRGBAMultiSampleBufferFormat(h.type),h.width,h.height),E.framebufferRenderbuffer(E.FRAMEBUFFER,E.COLOR_ATTACHMENT0,E.RENDERBUFFER,w),h._MSAARenderBuffer=w}else this._bindUnboundFramebuffer(h._framebuffer);return h.samples=v,h._depthStencilBuffer=this._setupFramebufferDepthAttachments(h._generateStencilBuffer,h._generateDepthBuffer,h.width,h.height,v),this._bindUnboundFramebuffer(null),v},l.prototype.updateTextureComparisonFunction=function(h,v){if(this.webGLVersion!==1){var E=this._gl;h.isCube?(this._bindTextureDirectly(this._gl.TEXTURE_CUBE_MAP,h,!0),v===0?(E.texParameteri(E.TEXTURE_CUBE_MAP,E.TEXTURE_COMPARE_FUNC,C.a.LEQUAL),E.texParameteri(E.TEXTURE_CUBE_MAP,E.TEXTURE_COMPARE_MODE,E.NONE)):(E.texParameteri(E.TEXTURE_CUBE_MAP,E.TEXTURE_COMPARE_FUNC,v),E.texParameteri(E.TEXTURE_CUBE_MAP,E.TEXTURE_COMPARE_MODE,E.COMPARE_REF_TO_TEXTURE)),this._bindTextureDirectly(this._gl.TEXTURE_CUBE_MAP,null)):(this._bindTextureDirectly(this._gl.TEXTURE_2D,h,!0),v===0?(E.texParameteri(E.TEXTURE_2D,E.TEXTURE_COMPARE_FUNC,C.a.LEQUAL),E.texParameteri(E.TEXTURE_2D,E.TEXTURE_COMPARE_MODE,E.NONE)):(E.texParameteri(E.TEXTURE_2D,E.TEXTURE_COMPARE_FUNC,v),E.texParameteri(E.TEXTURE_2D,E.TEXTURE_COMPARE_MODE,E.COMPARE_REF_TO_TEXTURE)),this._bindTextureDirectly(this._gl.TEXTURE_2D,null)),h._comparisonFunction=v}else A.a.Error("WebGL 1 does not support texture comparison.")},l.prototype.createInstancesBuffer=function(h){var v=this._gl.createBuffer();if(!v)throw new Error("Unable to create instance buffer");var E=new T.a(v);return E.capacity=h,this.bindArrayBuffer(E),this._gl.bufferData(this._gl.ARRAY_BUFFER,h,this._gl.DYNAMIC_DRAW),E},l.prototype.deleteInstancesBuffer=function(h){this._gl.deleteBuffer(h)},l.prototype._clientWaitAsync=function(h,v,E){v===void 0&&(v=0),E===void 0&&(E=10);var D=this._gl;return new Promise(function(w,N){var I=function(){var V=D.clientWaitSync(h,v,0);V!=D.WAIT_FAILED?V!=D.TIMEOUT_EXPIRED?w():setTimeout(I,E):N()};I()})},l.prototype._readPixelsAsync=function(h,v,E,D,w,N,I){if(this._webGLVersion<2)throw new Error("_readPixelsAsync only work on WebGL2+");var V=this._gl,X=V.createBuffer();V.bindBuffer(V.PIXEL_PACK_BUFFER,X),V.bufferData(V.PIXEL_PACK_BUFFER,I.byteLength,V.STREAM_READ),V.readPixels(h,v,E,D,w,N,0),V.bindBuffer(V.PIXEL_PACK_BUFFER,null);var j=V.fenceSync(V.SYNC_GPU_COMMANDS_COMPLETE,0);return j?(V.flush(),this._clientWaitAsync(j,0,10).then(function(){return V.deleteSync(j),V.bindBuffer(V.PIXEL_PACK_BUFFER,X),V.getBufferSubData(V.PIXEL_PACK_BUFFER,0,I),V.bindBuffer(V.PIXEL_PACK_BUFFER,null),V.deleteBuffer(X),I})):null},l.prototype.dispose=function(){for(this.hideLoadingUI(),this.onNewSceneAddedObservable.clear();this.postProcesses.length;)this.postProcesses[0].dispose();for(this._rescalePostProcess&&this._rescalePostProcess.dispose();this.scenes.length;)this.scenes[0].dispose();l.Instances.length===1&&l.audioEngine&&l.audioEngine.dispose(),this.disableVR(),x.a.IsWindowObjectExist()&&(window.removeEventListener("blur",this._onBlur),window.removeEventListener("focus",this._onFocus),this._renderingCanvas&&(this._renderingCanvas.removeEventListener("focus",this._onCanvasFocus),this._renderingCanvas.removeEventListener("blur",this._onCanvasBlur),this._renderingCanvas.removeEventListener("pointerout",this._onCanvasPointerOut)),x.a.IsDocumentAvailable()&&(document.removeEventListener("fullscreenchange",this._onFullscreenChange),document.removeEventListener("mozfullscreenchange",this._onFullscreenChange),document.removeEventListener("webkitfullscreenchange",this._onFullscreenChange),document.removeEventListener("msfullscreenchange",this._onFullscreenChange),document.removeEventListener("pointerlockchange",this._onPointerLockChange),document.removeEventListener("mspointerlockchange",this._onPointerLockChange),document.removeEventListener("mozpointerlockchange",this._onPointerLockChange),document.removeEventListener("webkitpointerlockchange",this._onPointerLockChange))),g.prototype.dispose.call(this);var h=l.Instances.indexOf(this);h>=0&&l.Instances.splice(h,1),this.onResizeObservable.clear(),this.onCanvasBlurObservable.clear(),this.onCanvasFocusObservable.clear(),this.onCanvasPointerOutObservable.clear(),this.onBeginFrameObservable.clear(),this.onEndFrameObservable.clear()},l.prototype._disableTouchAction=function(){this._renderingCanvas&&this._renderingCanvas.setAttribute&&(this._renderingCanvas.setAttribute("touch-action","none"),this._renderingCanvas.style.touchAction="none",this._renderingCanvas.style.msTouchAction="none")},l.prototype.displayLoadingUI=function(){if(x.a.IsWindowObjectExist()){var h=this.loadingScreen;h&&h.displayLoadingUI()}},l.prototype.hideLoadingUI=function(){if(x.a.IsWindowObjectExist()){var h=this._loadingScreen;h&&h.hideLoadingUI()}},Object.defineProperty(l.prototype,"loadingScreen",{get:function(){return!this._loadingScreen&&this._renderingCanvas&&(this._loadingScreen=l.DefaultLoadingScreenFactory(this._renderingCanvas)),this._loadingScreen},set:function(h){this._loadingScreen=h},enumerable:!1,configurable:!0}),Object.defineProperty(l.prototype,"loadingUIText",{set:function(h){this.loadingScreen.loadingUIText=h},enumerable:!1,configurable:!0}),Object.defineProperty(l.prototype,"loadingUIBackgroundColor",{set:function(h){this.loadingScreen.loadingUIBackgroundColor=h},enumerable:!1,configurable:!0}),l._RequestPointerlock=function(h){h.requestPointerLock=h.requestPointerLock||h.msRequestPointerLock||h.mozRequestPointerLock||h.webkitRequestPointerLock,h.requestPointerLock&&h.requestPointerLock()},l._ExitPointerlock=function(){var h=document;document.exitPointerLock=document.exitPointerLock||h.msExitPointerLock||h.mozExitPointerLock||h.webkitExitPointerLock,document.exitPointerLock&&document.exitPointerLock()},l._RequestFullscreen=function(h){var v=h.requestFullscreen||h.msRequestFullscreen||h.webkitRequestFullscreen||h.mozRequestFullScreen;v&&v.call(h)},l._ExitFullscreen=function(){var h=document;document.exitFullscreen?document.exitFullscreen():h.mozCancelFullScreen?h.mozCancelFullScreen():h.webkitCancelFullScreen?h.webkitCancelFullScreen():h.msCancelFullScreen&&h.msCancelFullScreen()},l.ALPHA_DISABLE=C.a.ALPHA_DISABLE,l.ALPHA_ADD=C.a.ALPHA_ADD,l.ALPHA_COMBINE=C.a.ALPHA_COMBINE,l.ALPHA_SUBTRACT=C.a.ALPHA_SUBTRACT,l.ALPHA_MULTIPLY=C.a.ALPHA_MULTIPLY,l.ALPHA_MAXIMIZED=C.a.ALPHA_MAXIMIZED,l.ALPHA_ONEONE=C.a.ALPHA_ONEONE,l.ALPHA_PREMULTIPLIED=C.a.ALPHA_PREMULTIPLIED,l.ALPHA_PREMULTIPLIED_PORTERDUFF=C.a.ALPHA_PREMULTIPLIED_PORTERDUFF,l.ALPHA_INTERPOLATE=C.a.ALPHA_INTERPOLATE,l.ALPHA_SCREENMODE=C.a.ALPHA_SCREENMODE,l.DELAYLOADSTATE_NONE=C.a.DELAYLOADSTATE_NONE,l.DELAYLOADSTATE_LOADED=C.a.DELAYLOADSTATE_LOADED,l.DELAYLOADSTATE_LOADING=C.a.DELAYLOADSTATE_LOADING,l.DELAYLOADSTATE_NOTLOADED=C.a.DELAYLOADSTATE_NOTLOADED,l.NEVER=C.a.NEVER,l.ALWAYS=C.a.ALWAYS,l.LESS=C.a.LESS,l.EQUAL=C.a.EQUAL,l.LEQUAL=C.a.LEQUAL,l.GREATER=C.a.GREATER,l.GEQUAL=C.a.GEQUAL,l.NOTEQUAL=C.a.NOTEQUAL,l.KEEP=C.a.KEEP,l.REPLACE=C.a.REPLACE,l.INCR=C.a.INCR,l.DECR=C.a.DECR,l.INVERT=C.a.INVERT,l.INCR_WRAP=C.a.INCR_WRAP,l.DECR_WRAP=C.a.DECR_WRAP,l.TEXTURE_CLAMP_ADDRESSMODE=C.a.TEXTURE_CLAMP_ADDRESSMODE,l.TEXTURE_WRAP_ADDRESSMODE=C.a.TEXTURE_WRAP_ADDRESSMODE,l.TEXTURE_MIRROR_ADDRESSMODE=C.a.TEXTURE_MIRROR_ADDRESSMODE,l.TEXTUREFORMAT_ALPHA=C.a.TEXTUREFORMAT_ALPHA,l.TEXTUREFORMAT_LUMINANCE=C.a.TEXTUREFORMAT_LUMINANCE,l.TEXTUREFORMAT_LUMINANCE_ALPHA=C.a.TEXTUREFORMAT_LUMINANCE_ALPHA,l.TEXTUREFORMAT_RGB=C.a.TEXTUREFORMAT_RGB,l.TEXTUREFORMAT_RGBA=C.a.TEXTUREFORMAT_RGBA,l.TEXTUREFORMAT_RED=C.a.TEXTUREFORMAT_RED,l.TEXTUREFORMAT_R=C.a.TEXTUREFORMAT_R,l.TEXTUREFORMAT_RG=C.a.TEXTUREFORMAT_RG,l.TEXTUREFORMAT_RED_INTEGER=C.a.TEXTUREFORMAT_RED_INTEGER,l.TEXTUREFORMAT_R_INTEGER=C.a.TEXTUREFORMAT_R_INTEGER,l.TEXTUREFORMAT_RG_INTEGER=C.a.TEXTUREFORMAT_RG_INTEGER,l.TEXTUREFORMAT_RGB_INTEGER=C.a.TEXTUREFORMAT_RGB_INTEGER,l.TEXTUREFORMAT_RGBA_INTEGER=C.a.TEXTUREFORMAT_RGBA_INTEGER,l.TEXTURETYPE_UNSIGNED_BYTE=C.a.TEXTURETYPE_UNSIGNED_BYTE,l.TEXTURETYPE_UNSIGNED_INT=C.a.TEXTURETYPE_UNSIGNED_INT,l.TEXTURETYPE_FLOAT=C.a.TEXTURETYPE_FLOAT,l.TEXTURETYPE_HALF_FLOAT=C.a.TEXTURETYPE_HALF_FLOAT,l.TEXTURETYPE_BYTE=C.a.TEXTURETYPE_BYTE,l.TEXTURETYPE_SHORT=C.a.TEXTURETYPE_SHORT,l.TEXTURETYPE_UNSIGNED_SHORT=C.a.TEXTURETYPE_UNSIGNED_SHORT,l.TEXTURETYPE_INT=C.a.TEXTURETYPE_INT,l.TEXTURETYPE_UNSIGNED_INTEGER=C.a.TEXTURETYPE_UNSIGNED_INTEGER,l.TEXTURETYPE_UNSIGNED_SHORT_4_4_4_4=C.a.TEXTURETYPE_UNSIGNED_SHORT_4_4_4_4,l.TEXTURETYPE_UNSIGNED_SHORT_5_5_5_1=C.a.TEXTURETYPE_UNSIGNED_SHORT_5_5_5_1,l.TEXTURETYPE_UNSIGNED_SHORT_5_6_5=C.a.TEXTURETYPE_UNSIGNED_SHORT_5_6_5,l.TEXTURETYPE_UNSIGNED_INT_2_10_10_10_REV=C.a.TEXTURETYPE_UNSIGNED_INT_2_10_10_10_REV,l.TEXTURETYPE_UNSIGNED_INT_24_8=C.a.TEXTURETYPE_UNSIGNED_INT_24_8,l.TEXTURETYPE_UNSIGNED_INT_10F_11F_11F_REV=C.a.TEXTURETYPE_UNSIGNED_INT_10F_11F_11F_REV,l.TEXTURETYPE_UNSIGNED_INT_5_9_9_9_REV=C.a.TEXTURETYPE_UNSIGNED_INT_5_9_9_9_REV,l.TEXTURETYPE_FLOAT_32_UNSIGNED_INT_24_8_REV=C.a.TEXTURETYPE_FLOAT_32_UNSIGNED_INT_24_8_REV,l.TEXTURE_NEAREST_SAMPLINGMODE=C.a.TEXTURE_NEAREST_SAMPLINGMODE,l.TEXTURE_BILINEAR_SAMPLINGMODE=C.a.TEXTURE_BILINEAR_SAMPLINGMODE,l.TEXTURE_TRILINEAR_SAMPLINGMODE=C.a.TEXTURE_TRILINEAR_SAMPLINGMODE,l.TEXTURE_NEAREST_NEAREST_MIPLINEAR=C.a.TEXTURE_NEAREST_NEAREST_MIPLINEAR,l.TEXTURE_LINEAR_LINEAR_MIPNEAREST=C.a.TEXTURE_LINEAR_LINEAR_MIPNEAREST,l.TEXTURE_LINEAR_LINEAR_MIPLINEAR=C.a.TEXTURE_LINEAR_LINEAR_MIPLINEAR,l.TEXTURE_NEAREST_NEAREST_MIPNEAREST=C.a.TEXTURE_NEAREST_NEAREST_MIPNEAREST,l.TEXTURE_NEAREST_LINEAR_MIPNEAREST=C.a.TEXTURE_NEAREST_LINEAR_MIPNEAREST,l.TEXTURE_NEAREST_LINEAR_MIPLINEAR=C.a.TEXTURE_NEAREST_LINEAR_MIPLINEAR,l.TEXTURE_NEAREST_LINEAR=C.a.TEXTURE_NEAREST_LINEAR,l.TEXTURE_NEAREST_NEAREST=C.a.TEXTURE_NEAREST_NEAREST,l.TEXTURE_LINEAR_NEAREST_MIPNEAREST=C.a.TEXTURE_LINEAR_NEAREST_MIPNEAREST,l.TEXTURE_LINEAR_NEAREST_MIPLINEAR=C.a.TEXTURE_LINEAR_NEAREST_MIPLINEAR,l.TEXTURE_LINEAR_LINEAR=C.a.TEXTURE_LINEAR_LINEAR,l.TEXTURE_LINEAR_NEAREST=C.a.TEXTURE_LINEAR_NEAREST,l.TEXTURE_EXPLICIT_MODE=C.a.TEXTURE_EXPLICIT_MODE,l.TEXTURE_SPHERICAL_MODE=C.a.TEXTURE_SPHERICAL_MODE,l.TEXTURE_PLANAR_MODE=C.a.TEXTURE_PLANAR_MODE,l.TEXTURE_CUBIC_MODE=C.a.TEXTURE_CUBIC_MODE,l.TEXTURE_PROJECTION_MODE=C.a.TEXTURE_PROJECTION_MODE,l.TEXTURE_SKYBOX_MODE=C.a.TEXTURE_SKYBOX_MODE,l.TEXTURE_INVCUBIC_MODE=C.a.TEXTURE_INVCUBIC_MODE,l.TEXTURE_EQUIRECTANGULAR_MODE=C.a.TEXTURE_EQUIRECTANGULAR_MODE,l.TEXTURE_FIXED_EQUIRECTANGULAR_MODE=C.a.TEXTURE_FIXED_EQUIRECTANGULAR_MODE,l.TEXTURE_FIXED_EQUIRECTANGULAR_MIRRORED_MODE=C.a.TEXTURE_FIXED_EQUIRECTANGULAR_MIRRORED_MODE,l.SCALEMODE_FLOOR=C.a.SCALEMODE_FLOOR,l.SCALEMODE_NEAREST=C.a.SCALEMODE_NEAREST,l.SCALEMODE_CEILING=C.a.SCALEMODE_CEILING,l._RescalePostProcessFactory=null,l}(R.a))},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.WithinEpsilon=function(x,u,M){M===void 0&&(M=1401298e-51);var R=x-u;return-M<=R&&R<=M},_.ToHex=function(x){var u=x.toString(16);return x<=15?("0"+u).toUpperCase():u.toUpperCase()},_.Sign=function(x){return(x=+x)==0||isNaN(x)?x:x>0?1:-1},_.Clamp=function(x,u,M){return u===void 0&&(u=0),M===void 0&&(M=1),Math.min(M,Math.max(u,x))},_.Log2=function(x){return Math.log(x)*Math.LOG2E},_.Repeat=function(x,u){return x-Math.floor(x/u)*u},_.Normalize=function(x,u,M){return(x-u)/(M-u)},_.Denormalize=function(x,u,M){return x*(M-u)+u},_.DeltaAngle=function(x,u){var M=_.Repeat(u-x,360);return M>180&&(M-=360),M},_.PingPong=function(x,u){var M=_.Repeat(x,2*u);return u-Math.abs(M-u)},_.SmoothStep=function(x,u,M){var R=_.Clamp(M);return u*(R=-2*R*R*R+3*R*R)+x*(1-R)},_.MoveTowards=function(x,u,M){return Math.abs(u-x)<=M?u:x+_.Sign(u-x)*M},_.MoveTowardsAngle=function(x,u,M){var R=_.DeltaAngle(x,u),C=0;return-M<R&&R<M?C=u:(u=x+R,C=_.MoveTowards(x,u,M)),C},_.Lerp=function(x,u,M){return x+(u-x)*M},_.LerpAngle=function(x,u,M){var R=_.Repeat(u-x,360);return R>180&&(R-=360),x+R*_.Clamp(M)},_.InverseLerp=function(x,u,M){return x!=u?_.Clamp((M-x)/(u-x)):0},_.Hermite=function(x,u,M,R,C){var m=C*C,c=C*m;return x*(2*c-3*m+1)+M*(-2*c+3*m)+u*(c-2*m+C)+R*(c-m)},_.RandomRange=function(x,u){return x===u?x:Math.random()*(u-x)+x},_.RangeToPercent=function(x,u,M){return(x-u)/(M-u)},_.PercentToRange=function(x,u,M){return(M-u)*x+u},_.NormalizeRadians=function(x){return x-=_.TwoPi*Math.floor((x+Math.PI)/_.TwoPi)},_.TwoPi=2*Math.PI,_}()},function(Me,y,f){f.d(y,"a",function(){return c});var U=f(8),_=f(20),x=f(22),u=f(4),M=f(48),R=f(2),C=f(9),m=f(119),c=function(){function T(){}return T.BindEyePosition=function(A,S,g){if(g===void 0&&(g="vEyePosition"),S._forcedViewPosition)A.setVector3(g,S._forcedViewPosition);else{var l=S.activeCamera.globalPosition;l||(l=S.activeCamera.devicePosition),A.setVector3(g,S._mirroredCameraPosition?S._mirroredCameraPosition:l)}},T.PrepareDefinesForMergedUV=function(A,S,g){S._needUVs=!0,S[g]=!0,A.getTextureMatrix().isIdentityAs3x2()?(S[g+"DIRECTUV"]=A.coordinatesIndex+1,A.coordinatesIndex===0?S.MAINUV1=!0:S.MAINUV2=!0):S[g+"DIRECTUV"]=0},T.BindTextureMatrix=function(A,S,g){var l=A.getTextureMatrix();S.updateMatrix(g+"Matrix",l)},T.GetFogState=function(A,S){return S.fogEnabled&&A.applyFog&&S.fogMode!==_.a.FOGMODE_NONE},T.PrepareDefinesForMisc=function(A,S,g,l,h,v,E){E._areMiscDirty&&(E.LOGARITHMICDEPTH=g,E.POINTSIZE=l,E.FOG=h&&this.GetFogState(A,S),E.NONUNIFORMSCALING=A.nonUniformScaling,E.ALPHATEST=v)},T.PrepareDefinesForFrameBoundValues=function(A,S,g,l,h,v){h===void 0&&(h=null),v===void 0&&(v=!1);var E,D,w,N,I,V,X=!1;E=h??(A.clipPlane!==void 0&&A.clipPlane!==null),D=h??(A.clipPlane2!==void 0&&A.clipPlane2!==null),w=h??(A.clipPlane3!==void 0&&A.clipPlane3!==null),N=h??(A.clipPlane4!==void 0&&A.clipPlane4!==null),I=h??(A.clipPlane5!==void 0&&A.clipPlane5!==null),V=h??(A.clipPlane6!==void 0&&A.clipPlane6!==null),g.CLIPPLANE!==E&&(g.CLIPPLANE=E,X=!0),g.CLIPPLANE2!==D&&(g.CLIPPLANE2=D,X=!0),g.CLIPPLANE3!==w&&(g.CLIPPLANE3=w,X=!0),g.CLIPPLANE4!==N&&(g.CLIPPLANE4=N,X=!0),g.CLIPPLANE5!==I&&(g.CLIPPLANE5=I,X=!0),g.CLIPPLANE6!==V&&(g.CLIPPLANE6=V,X=!0),g.DEPTHPREPASS!==!S.getColorWrite()&&(g.DEPTHPREPASS=!g.DEPTHPREPASS,X=!0),g.INSTANCES!==l&&(g.INSTANCES=l,X=!0),g.THIN_INSTANCES!==v&&(g.THIN_INSTANCES=v,X=!0),X&&g.markAsUnprocessed()},T.PrepareDefinesForBones=function(A,S){if(A.useBones&&A.computeBonesUsingShaders&&A.skeleton){S.NUM_BONE_INFLUENCERS=A.numBoneInfluencers;var g=S.BONETEXTURE!==void 0;if(A.skeleton.isUsingTextureForMatrices&&g)S.BONETEXTURE=!0;else{S.BonesPerMesh=A.skeleton.bones.length+1,S.BONETEXTURE=!g&&void 0;var l=A.getScene().prePassRenderer;if(l&&l.enabled){var h=l.excludedSkinnedMesh.indexOf(A)===-1;S.BONES_VELOCITY_ENABLED=h}}}else S.NUM_BONE_INFLUENCERS=0,S.BonesPerMesh=0},T.PrepareDefinesForMorphTargets=function(A,S){var g=A.morphTargetManager;g?(S.MORPHTARGETS_UV=g.supportsUVs&&S.UV1,S.MORPHTARGETS_TANGENT=g.supportsTangents&&S.TANGENT,S.MORPHTARGETS_NORMAL=g.supportsNormals&&S.NORMAL,S.MORPHTARGETS=g.numInfluencers>0,S.NUM_MORPH_INFLUENCERS=g.numInfluencers):(S.MORPHTARGETS_UV=!1,S.MORPHTARGETS_TANGENT=!1,S.MORPHTARGETS_NORMAL=!1,S.MORPHTARGETS=!1,S.NUM_MORPH_INFLUENCERS=0)},T.PrepareDefinesForAttributes=function(A,S,g,l,h,v){if(h===void 0&&(h=!1),v===void 0&&(v=!0),!S._areAttributesDirty&&S._needNormals===S._normals&&S._needUVs===S._uvs)return!1;if(S._normals=S._needNormals,S._uvs=S._needUVs,S.NORMAL=S._needNormals&&A.isVerticesDataPresent(u.b.NormalKind),S._needNormals&&A.isVerticesDataPresent(u.b.TangentKind)&&(S.TANGENT=!0),S._needUVs?(S.UV1=A.isVerticesDataPresent(u.b.UVKind),S.UV2=A.isVerticesDataPresent(u.b.UV2Kind)):(S.UV1=!1,S.UV2=!1),g){var E=A.useVertexColors&&A.isVerticesDataPresent(u.b.ColorKind);S.VERTEXCOLOR=E,S.VERTEXALPHA=A.hasVertexAlpha&&E&&v}return l&&this.PrepareDefinesForBones(A,S),h&&this.PrepareDefinesForMorphTargets(A,S),!0},T.PrepareDefinesForMultiview=function(A,S){if(A.activeCamera){var g=S.MULTIVIEW;S.MULTIVIEW=A.activeCamera.outputRenderTarget!==null&&A.activeCamera.outputRenderTarget.getViewCount()>1,S.MULTIVIEW!=g&&S.markAsUnprocessed()}},T.PrepareDefinesForPrePass=function(A,S,g){var l=S.PREPASS;if(S._arePrePassDirty){var h=[{type:R.a.PREPASS_POSITION_TEXTURE_TYPE,define:"PREPASS_POSITION",index:"PREPASS_POSITION_INDEX"},{type:R.a.PREPASS_VELOCITY_TEXTURE_TYPE,define:"PREPASS_VELOCITY",index:"PREPASS_VELOCITY_INDEX"},{type:R.a.PREPASS_REFLECTIVITY_TEXTURE_TYPE,define:"PREPASS_REFLECTIVITY",index:"PREPASS_REFLECTIVITY_INDEX"},{type:R.a.PREPASS_IRRADIANCE_TEXTURE_TYPE,define:"PREPASS_IRRADIANCE",index:"PREPASS_IRRADIANCE_INDEX"},{type:R.a.PREPASS_ALBEDO_TEXTURE_TYPE,define:"PREPASS_ALBEDO",index:"PREPASS_ALBEDO_INDEX"},{type:R.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE,define:"PREPASS_DEPTHNORMAL",index:"PREPASS_DEPTHNORMAL_INDEX"}];if(A.prePassRenderer&&A.prePassRenderer.enabled&&g){S.PREPASS=!0,S.SCENE_MRT_COUNT=A.prePassRenderer.mrtCount;for(var v=0;v<h.length;v++){var E=A.prePassRenderer.getIndex(h[v].type);E!==-1?(S[h[v].define]=!0,S[h[v].index]=E):S[h[v].define]=!1}}else for(S.PREPASS=!1,v=0;v<h.length;v++)S[h[v].define]=!1;S.PREPASS!=l&&(S.markAsUnprocessed(),S.markAsImageProcessingDirty())}},T.PrepareDefinesForLight=function(A,S,g,l,h,v,E){switch(E.needNormals=!0,h["LIGHT"+l]===void 0&&(E.needRebuild=!0),h["LIGHT"+l]=!0,h["SPOTLIGHT"+l]=!1,h["HEMILIGHT"+l]=!1,h["POINTLIGHT"+l]=!1,h["DIRLIGHT"+l]=!1,g.prepareLightSpecificDefines(h,l),h["LIGHT_FALLOFF_PHYSICAL"+l]=!1,h["LIGHT_FALLOFF_GLTF"+l]=!1,h["LIGHT_FALLOFF_STANDARD"+l]=!1,g.falloffType){case M.a.FALLOFF_GLTF:h["LIGHT_FALLOFF_GLTF"+l]=!0;break;case M.a.FALLOFF_PHYSICAL:h["LIGHT_FALLOFF_PHYSICAL"+l]=!0;break;case M.a.FALLOFF_STANDARD:h["LIGHT_FALLOFF_STANDARD"+l]=!0}if(v&&!g.specular.equalsFloats(0,0,0)&&(E.specularEnabled=!0),h["SHADOW"+l]=!1,h["SHADOWCSM"+l]=!1,h["SHADOWCSMDEBUG"+l]=!1,h["SHADOWCSMNUM_CASCADES"+l]=!1,h["SHADOWCSMUSESHADOWMAXZ"+l]=!1,h["SHADOWCSMNOBLEND"+l]=!1,h["SHADOWCSM_RIGHTHANDED"+l]=!1,h["SHADOWPCF"+l]=!1,h["SHADOWPCSS"+l]=!1,h["SHADOWPOISSON"+l]=!1,h["SHADOWESM"+l]=!1,h["SHADOWCLOSEESM"+l]=!1,h["SHADOWCUBE"+l]=!1,h["SHADOWLOWQUALITY"+l]=!1,h["SHADOWMEDIUMQUALITY"+l]=!1,S&&S.receiveShadows&&A.shadowsEnabled&&g.shadowEnabled){var D=g.getShadowGenerator();if(D){var w=D.getShadowMap();w&&w.renderList&&w.renderList.length>0&&(E.shadowEnabled=!0,D.prepareDefines(h,l))}}g.lightmapMode!=M.a.LIGHTMAP_DEFAULT?(E.lightmapMode=!0,h["LIGHTMAPEXCLUDED"+l]=!0,h["LIGHTMAPNOSPECULAR"+l]=g.lightmapMode==M.a.LIGHTMAP_SHADOWSONLY):(h["LIGHTMAPEXCLUDED"+l]=!1,h["LIGHTMAPNOSPECULAR"+l]=!1)},T.PrepareDefinesForLights=function(A,S,g,l,h,v){if(h===void 0&&(h=4),v===void 0&&(v=!1),!g._areLightsDirty)return g._needNormals;var E=0,D={needNormals:!1,needRebuild:!1,lightmapMode:!1,shadowEnabled:!1,specularEnabled:!1};if(A.lightsEnabled&&!v)for(var w=0,N=S.lightSources;w<N.length;w++){var I=N[w];if(this.PrepareDefinesForLight(A,S,I,E,g,l,D),++E===h)break}g.SPECULARTERM=D.specularEnabled,g.SHADOWS=D.shadowEnabled;for(var V=E;V<h;V++)g["LIGHT"+V]!==void 0&&(g["LIGHT"+V]=!1,g["HEMILIGHT"+V]=!1,g["POINTLIGHT"+V]=!1,g["DIRLIGHT"+V]=!1,g["SPOTLIGHT"+V]=!1,g["SHADOW"+V]=!1,g["SHADOWCSM"+V]=!1,g["SHADOWCSMDEBUG"+V]=!1,g["SHADOWCSMNUM_CASCADES"+V]=!1,g["SHADOWCSMUSESHADOWMAXZ"+V]=!1,g["SHADOWCSMNOBLEND"+V]=!1,g["SHADOWCSM_RIGHTHANDED"+V]=!1,g["SHADOWPCF"+V]=!1,g["SHADOWPCSS"+V]=!1,g["SHADOWPOISSON"+V]=!1,g["SHADOWESM"+V]=!1,g["SHADOWCLOSEESM"+V]=!1,g["SHADOWCUBE"+V]=!1,g["SHADOWLOWQUALITY"+V]=!1,g["SHADOWMEDIUMQUALITY"+V]=!1);var X=A.getEngine().getCaps();return g.SHADOWFLOAT===void 0&&(D.needRebuild=!0),g.SHADOWFLOAT=D.shadowEnabled&&(X.textureFloatRender&&X.textureFloatLinearFiltering||X.textureHalfFloatRender&&X.textureHalfFloatLinearFiltering),g.LIGHTMAPEXCLUDED=D.lightmapMode,D.needRebuild&&g.rebuild(),D.needNormals},T.PrepareUniformsAndSamplersForLight=function(A,S,g,l,h,v){h===void 0&&(h=null),v===void 0&&(v=!1),h&&h.push("Light"+A),v||(S.push("vLightData"+A,"vLightDiffuse"+A,"vLightSpecular"+A,"vLightDirection"+A,"vLightFalloff"+A,"vLightGround"+A,"lightMatrix"+A,"shadowsInfo"+A,"depthValues"+A),g.push("shadowSampler"+A),g.push("depthSampler"+A),S.push("viewFrustumZ"+A,"cascadeBlendFactor"+A,"lightSizeUVCorrection"+A,"depthCorrection"+A,"penumbraDarkness"+A,"frustumLengths"+A),l&&(g.push("projectionLightSampler"+A),S.push("textureProjectionMatrix"+A)))},T.PrepareUniformsAndSamplersList=function(A,S,g,l){var h;l===void 0&&(l=4);var v=null;if(A.uniformsNames){var E=A;h=E.uniformsNames,v=E.uniformBuffersNames,S=E.samplers,g=E.defines,l=E.maxSimultaneousLights||0}else h=A,S||(S=[]);for(var D=0;D<l&&g["LIGHT"+D];D++)this.PrepareUniformsAndSamplersForLight(D,h,S,g["PROJECTEDLIGHTTEXTURE"+D],v);g.NUM_MORPH_INFLUENCERS&&h.push("morphTargetInfluences")},T.HandleFallbacksForShadows=function(A,S,g,l){g===void 0&&(g=4),l===void 0&&(l=0);for(var h=0,v=0;v<g&&A["LIGHT"+v];v++)v>0&&(h=l+v,S.addFallback(h,"LIGHT"+v)),A.SHADOWS||(A["SHADOW"+v]&&S.addFallback(l,"SHADOW"+v),A["SHADOWPCF"+v]&&S.addFallback(l,"SHADOWPCF"+v),A["SHADOWPCSS"+v]&&S.addFallback(l,"SHADOWPCSS"+v),A["SHADOWPOISSON"+v]&&S.addFallback(l,"SHADOWPOISSON"+v),A["SHADOWESM"+v]&&S.addFallback(l,"SHADOWESM"+v),A["SHADOWCLOSEESM"+v]&&S.addFallback(l,"SHADOWCLOSEESM"+v));return h++},T.PrepareAttributesForMorphTargetsInfluencers=function(A,S,g){this._TmpMorphInfluencers.NUM_MORPH_INFLUENCERS=g,this.PrepareAttributesForMorphTargets(A,S,this._TmpMorphInfluencers)},T.PrepareAttributesForMorphTargets=function(A,S,g){var l=g.NUM_MORPH_INFLUENCERS;if(l>0&&x.a.LastCreatedEngine)for(var h=x.a.LastCreatedEngine.getCaps().maxVertexAttribs,v=S.morphTargetManager,E=v&&v.supportsNormals&&g.NORMAL,D=v&&v.supportsTangents&&g.TANGENT,w=v&&v.supportsUVs&&g.UV1,N=0;N<l;N++)A.push(u.b.PositionKind+N),E&&A.push(u.b.NormalKind+N),D&&A.push(u.b.TangentKind+N),w&&A.push(u.b.UVKind+"_"+N),A.length>h&&U.a.Error("Cannot add more vertex attributes for mesh "+S.name)},T.PrepareAttributesForBones=function(A,S,g,l){g.NUM_BONE_INFLUENCERS>0&&(l.addCPUSkinningFallback(0,S),A.push(u.b.MatricesIndicesKind),A.push(u.b.MatricesWeightsKind),g.NUM_BONE_INFLUENCERS>4&&(A.push(u.b.MatricesIndicesExtraKind),A.push(u.b.MatricesWeightsExtraKind)))},T.PrepareAttributesForInstances=function(A,S){(S.INSTANCES||S.THIN_INSTANCES)&&this.PushAttributesForInstances(A)},T.PushAttributesForInstances=function(A){A.push("world0"),A.push("world1"),A.push("world2"),A.push("world3")},T.BindLightProperties=function(A,S,g){A.transferToEffect(S,g+"")},T.BindLight=function(A,S,g,l,h,v){v===void 0&&(v=!1),A._bindLight(S,g,l,h,v)},T.BindLights=function(A,S,g,l,h,v){h===void 0&&(h=4),v===void 0&&(v=!1);for(var E=Math.min(S.lightSources.length,h),D=0;D<E;D++){var w=S.lightSources[D];this.BindLight(w,D,A,g,typeof l=="boolean"?l:l.SPECULARTERM,v)}},T.BindFogParameters=function(A,S,g,l){l===void 0&&(l=!1),A.fogEnabled&&S.applyFog&&A.fogMode!==_.a.FOGMODE_NONE&&(g.setFloat4("vFogInfos",A.fogMode,A.fogStart,A.fogEnd,A.fogDensity),l?(A.fogColor.toLinearSpaceToRef(this._tempFogColor),g.setColor3("vFogColor",this._tempFogColor)):g.setColor3("vFogColor",A.fogColor))},T.BindBonesParameters=function(A,S,g){if(S&&A&&(A.computeBonesUsingShaders&&S._bonesComputationForcedToCPU&&(A.computeBonesUsingShaders=!1),A.useBones&&A.computeBonesUsingShaders&&A.skeleton)){var l=A.skeleton;if(l.isUsingTextureForMatrices&&S.getUniformIndex("boneTextureWidth")>-1){var h=l.getTransformMatrixTexture(A);S.setTexture("boneSampler",h),S.setFloat("boneTextureWidth",4*(l.bones.length+1))}else{var v=l.getTransformMatrices(A);v&&(S.setMatrices("mBones",v),g&&A.getScene().prePassRenderer&&A.getScene().prePassRenderer.getIndex(R.a.PREPASS_VELOCITY_TEXTURE_TYPE)&&(g.previousBones[A.uniqueId]&&S.setMatrices("mPreviousBones",g.previousBones[A.uniqueId]),T._CopyBonesTransformationMatrices(v,g.previousBones[A.uniqueId])))}}},T._CopyBonesTransformationMatrices=function(A,S){return S.set(A),S},T.BindMorphTargetParameters=function(A,S){var g=A.morphTargetManager;A&&g&&S.setFloatArray("morphTargetInfluences",g.influences)},T.BindLogDepth=function(A,S,g){A.LOGARITHMICDEPTH&&S.setFloat("logarithmicDepthConstant",2/(Math.log(g.activeCamera.maxZ+1)/Math.LN2))},T.BindClipPlane=function(A,S){m.a.BindClipPlane(A,S)},T._TmpMorphInfluencers={NUM_MORPH_INFLUENCERS:0},T._tempFogColor=C.a.Black(),T}()},function(Me,y,f){f.d(y,"a",function(){return R});var U=f(0),_=f(4),x=f(21),u=f(9),M=f(8),R=function(){function C(){}return C.prototype.set=function(m,c){switch(m.length||M.a.Warn("Setting vertex data kind '"+c+"' with an empty array"),c){case _.b.PositionKind:this.positions=m;break;case _.b.NormalKind:this.normals=m;break;case _.b.TangentKind:this.tangents=m;break;case _.b.UVKind:this.uvs=m;break;case _.b.UV2Kind:this.uvs2=m;break;case _.b.UV3Kind:this.uvs3=m;break;case _.b.UV4Kind:this.uvs4=m;break;case _.b.UV5Kind:this.uvs5=m;break;case _.b.UV6Kind:this.uvs6=m;break;case _.b.ColorKind:this.colors=m;break;case _.b.MatricesIndicesKind:this.matricesIndices=m;break;case _.b.MatricesWeightsKind:this.matricesWeights=m;break;case _.b.MatricesIndicesExtraKind:this.matricesIndicesExtra=m;break;case _.b.MatricesWeightsExtraKind:this.matricesWeightsExtra=m}},C.prototype.applyToMesh=function(m,c){return this._applyTo(m,c),this},C.prototype.applyToGeometry=function(m,c){return this._applyTo(m,c),this},C.prototype.updateMesh=function(m){return this._update(m),this},C.prototype.updateGeometry=function(m){return this._update(m),this},C.prototype._applyTo=function(m,c){return c===void 0&&(c=!1),this.positions&&m.setVerticesData(_.b.PositionKind,this.positions,c),this.normals&&m.setVerticesData(_.b.NormalKind,this.normals,c),this.tangents&&m.setVerticesData(_.b.TangentKind,this.tangents,c),this.uvs&&m.setVerticesData(_.b.UVKind,this.uvs,c),this.uvs2&&m.setVerticesData(_.b.UV2Kind,this.uvs2,c),this.uvs3&&m.setVerticesData(_.b.UV3Kind,this.uvs3,c),this.uvs4&&m.setVerticesData(_.b.UV4Kind,this.uvs4,c),this.uvs5&&m.setVerticesData(_.b.UV5Kind,this.uvs5,c),this.uvs6&&m.setVerticesData(_.b.UV6Kind,this.uvs6,c),this.colors&&m.setVerticesData(_.b.ColorKind,this.colors,c),this.matricesIndices&&m.setVerticesData(_.b.MatricesIndicesKind,this.matricesIndices,c),this.matricesWeights&&m.setVerticesData(_.b.MatricesWeightsKind,this.matricesWeights,c),this.matricesIndicesExtra&&m.setVerticesData(_.b.MatricesIndicesExtraKind,this.matricesIndicesExtra,c),this.matricesWeightsExtra&&m.setVerticesData(_.b.MatricesWeightsExtraKind,this.matricesWeightsExtra,c),this.indices?m.setIndices(this.indices,null,c):m.setIndices([],null),this},C.prototype._update=function(m,c,T){return this.positions&&m.updateVerticesData(_.b.PositionKind,this.positions,c,T),this.normals&&m.updateVerticesData(_.b.NormalKind,this.normals,c,T),this.tangents&&m.updateVerticesData(_.b.TangentKind,this.tangents,c,T),this.uvs&&m.updateVerticesData(_.b.UVKind,this.uvs,c,T),this.uvs2&&m.updateVerticesData(_.b.UV2Kind,this.uvs2,c,T),this.uvs3&&m.updateVerticesData(_.b.UV3Kind,this.uvs3,c,T),this.uvs4&&m.updateVerticesData(_.b.UV4Kind,this.uvs4,c,T),this.uvs5&&m.updateVerticesData(_.b.UV5Kind,this.uvs5,c,T),this.uvs6&&m.updateVerticesData(_.b.UV6Kind,this.uvs6,c,T),this.colors&&m.updateVerticesData(_.b.ColorKind,this.colors,c,T),this.matricesIndices&&m.updateVerticesData(_.b.MatricesIndicesKind,this.matricesIndices,c,T),this.matricesWeights&&m.updateVerticesData(_.b.MatricesWeightsKind,this.matricesWeights,c,T),this.matricesIndicesExtra&&m.updateVerticesData(_.b.MatricesIndicesExtraKind,this.matricesIndicesExtra,c,T),this.matricesWeightsExtra&&m.updateVerticesData(_.b.MatricesWeightsExtraKind,this.matricesWeightsExtra,c,T),this.indices&&m.setIndices(this.indices,null),this},C.prototype.transform=function(m){var c,T=m.determinant()<0,A=U.e.Zero();if(this.positions){var S=U.e.Zero();for(c=0;c<this.positions.length;c+=3)U.e.FromArrayToRef(this.positions,c,S),U.e.TransformCoordinatesToRef(S,m,A),this.positions[c]=A.x,this.positions[c+1]=A.y,this.positions[c+2]=A.z}if(this.normals){var g=U.e.Zero();for(c=0;c<this.normals.length;c+=3)U.e.FromArrayToRef(this.normals,c,g),U.e.TransformNormalToRef(g,m,A),this.normals[c]=A.x,this.normals[c+1]=A.y,this.normals[c+2]=A.z}if(this.tangents){var l=U.f.Zero(),h=U.f.Zero();for(c=0;c<this.tangents.length;c+=4)U.f.FromArrayToRef(this.tangents,c,l),U.f.TransformNormalToRef(l,m,h),this.tangents[c]=h.x,this.tangents[c+1]=h.y,this.tangents[c+2]=h.z,this.tangents[c+3]=h.w}if(T&&this.indices)for(c=0;c<this.indices.length;c+=3){var v=this.indices[c+1];this.indices[c+1]=this.indices[c+2],this.indices[c+2]=v}return this},C.prototype.merge=function(m,c){if(c===void 0&&(c=!1),this._validate(),m._validate(),!this.normals!=!m.normals||!this.tangents!=!m.tangents||!this.uvs!=!m.uvs||!this.uvs2!=!m.uvs2||!this.uvs3!=!m.uvs3||!this.uvs4!=!m.uvs4||!this.uvs5!=!m.uvs5||!this.uvs6!=!m.uvs6||!this.colors!=!m.colors||!this.matricesIndices!=!m.matricesIndices||!this.matricesWeights!=!m.matricesWeights||!this.matricesIndicesExtra!=!m.matricesIndicesExtra||!this.matricesWeightsExtra!=!m.matricesWeightsExtra)throw new Error("Cannot merge vertex data that do not have the same set of attributes");if(m.indices){this.indices||(this.indices=[]);var T=this.positions?this.positions.length/3:0;if(this.indices.BYTES_PER_ELEMENT!==void 0){var A=this.indices.length+m.indices.length,S=c||this.indices instanceof Uint32Array?new Uint32Array(A):new Uint16Array(A);S.set(this.indices);for(var g=this.indices.length,l=0;l<m.indices.length;l++)S[g+l]=m.indices[l]+T;this.indices=S}else for(l=0;l<m.indices.length;l++)this.indices.push(m.indices[l]+T)}return this.positions=this._mergeElement(this.positions,m.positions),this.normals=this._mergeElement(this.normals,m.normals),this.tangents=this._mergeElement(this.tangents,m.tangents),this.uvs=this._mergeElement(this.uvs,m.uvs),this.uvs2=this._mergeElement(this.uvs2,m.uvs2),this.uvs3=this._mergeElement(this.uvs3,m.uvs3),this.uvs4=this._mergeElement(this.uvs4,m.uvs4),this.uvs5=this._mergeElement(this.uvs5,m.uvs5),this.uvs6=this._mergeElement(this.uvs6,m.uvs6),this.colors=this._mergeElement(this.colors,m.colors),this.matricesIndices=this._mergeElement(this.matricesIndices,m.matricesIndices),this.matricesWeights=this._mergeElement(this.matricesWeights,m.matricesWeights),this.matricesIndicesExtra=this._mergeElement(this.matricesIndicesExtra,m.matricesIndicesExtra),this.matricesWeightsExtra=this._mergeElement(this.matricesWeightsExtra,m.matricesWeightsExtra),this},C.prototype._mergeElement=function(m,c){if(!m)return c;if(!c)return m;var T=c.length+m.length,A=m instanceof Float32Array,S=c instanceof Float32Array;if(A){var g=new Float32Array(T);return g.set(m),g.set(c,m.length),g}if(S){var l=m.slice(0),h=0;for(T=c.length;h<T;h++)l.push(c[h]);return l}return m.concat(c)},C.prototype._validate=function(){if(!this.positions)throw new Error("Positions are required");var m=function(A,S){var g=_.b.DeduceStride(A);if(S.length%g!=0)throw new Error("The "+A+"s array count must be a multiple of "+g);return S.length/g},c=m(_.b.PositionKind,this.positions),T=function(A,S){var g=m(A,S);if(g!==c)throw new Error("The "+A+"s element count ("+g+") does not match the positions count ("+c+")")};this.normals&&T(_.b.NormalKind,this.normals),this.tangents&&T(_.b.TangentKind,this.tangents),this.uvs&&T(_.b.UVKind,this.uvs),this.uvs2&&T(_.b.UV2Kind,this.uvs2),this.uvs3&&T(_.b.UV3Kind,this.uvs3),this.uvs4&&T(_.b.UV4Kind,this.uvs4),this.uvs5&&T(_.b.UV5Kind,this.uvs5),this.uvs6&&T(_.b.UV6Kind,this.uvs6),this.colors&&T(_.b.ColorKind,this.colors),this.matricesIndices&&T(_.b.MatricesIndicesKind,this.matricesIndices),this.matricesWeights&&T(_.b.MatricesWeightsKind,this.matricesWeights),this.matricesIndicesExtra&&T(_.b.MatricesIndicesExtraKind,this.matricesIndicesExtra),this.matricesWeightsExtra&&T(_.b.MatricesWeightsExtraKind,this.matricesWeightsExtra)},C.prototype.serialize=function(){var m=this.serialize();return this.positions&&(m.positions=this.positions),this.normals&&(m.normals=this.normals),this.tangents&&(m.tangents=this.tangents),this.uvs&&(m.uvs=this.uvs),this.uvs2&&(m.uvs2=this.uvs2),this.uvs3&&(m.uvs3=this.uvs3),this.uvs4&&(m.uvs4=this.uvs4),this.uvs5&&(m.uvs5=this.uvs5),this.uvs6&&(m.uvs6=this.uvs6),this.colors&&(m.colors=this.colors),this.matricesIndices&&(m.matricesIndices=this.matricesIndices,m.matricesIndices._isExpanded=!0),this.matricesWeights&&(m.matricesWeights=this.matricesWeights),this.matricesIndicesExtra&&(m.matricesIndicesExtra=this.matricesIndicesExtra,m.matricesIndicesExtra._isExpanded=!0),this.matricesWeightsExtra&&(m.matricesWeightsExtra=this.matricesWeightsExtra),m.indices=this.indices,m},C.ExtractFromMesh=function(m,c,T){return C._ExtractFrom(m,c,T)},C.ExtractFromGeometry=function(m,c,T){return C._ExtractFrom(m,c,T)},C._ExtractFrom=function(m,c,T){var A=new C;return m.isVerticesDataPresent(_.b.PositionKind)&&(A.positions=m.getVerticesData(_.b.PositionKind,c,T)),m.isVerticesDataPresent(_.b.NormalKind)&&(A.normals=m.getVerticesData(_.b.NormalKind,c,T)),m.isVerticesDataPresent(_.b.TangentKind)&&(A.tangents=m.getVerticesData(_.b.TangentKind,c,T)),m.isVerticesDataPresent(_.b.UVKind)&&(A.uvs=m.getVerticesData(_.b.UVKind,c,T)),m.isVerticesDataPresent(_.b.UV2Kind)&&(A.uvs2=m.getVerticesData(_.b.UV2Kind,c,T)),m.isVerticesDataPresent(_.b.UV3Kind)&&(A.uvs3=m.getVerticesData(_.b.UV3Kind,c,T)),m.isVerticesDataPresent(_.b.UV4Kind)&&(A.uvs4=m.getVerticesData(_.b.UV4Kind,c,T)),m.isVerticesDataPresent(_.b.UV5Kind)&&(A.uvs5=m.getVerticesData(_.b.UV5Kind,c,T)),m.isVerticesDataPresent(_.b.UV6Kind)&&(A.uvs6=m.getVerticesData(_.b.UV6Kind,c,T)),m.isVerticesDataPresent(_.b.ColorKind)&&(A.colors=m.getVerticesData(_.b.ColorKind,c,T)),m.isVerticesDataPresent(_.b.MatricesIndicesKind)&&(A.matricesIndices=m.getVerticesData(_.b.MatricesIndicesKind,c,T)),m.isVerticesDataPresent(_.b.MatricesWeightsKind)&&(A.matricesWeights=m.getVerticesData(_.b.MatricesWeightsKind,c,T)),m.isVerticesDataPresent(_.b.MatricesIndicesExtraKind)&&(A.matricesIndicesExtra=m.getVerticesData(_.b.MatricesIndicesExtraKind,c,T)),m.isVerticesDataPresent(_.b.MatricesWeightsExtraKind)&&(A.matricesWeightsExtra=m.getVerticesData(_.b.MatricesWeightsExtraKind,c,T)),A.indices=m.getIndices(c,T),A},C.CreateRibbon=function(m){throw x.a.WarnImport("ribbonBuilder")},C.CreateBox=function(m){throw x.a.WarnImport("boxBuilder")},C.CreateTiledBox=function(m){throw x.a.WarnImport("tiledBoxBuilder")},C.CreateTiledPlane=function(m){throw x.a.WarnImport("tiledPlaneBuilder")},C.CreateSphere=function(m){throw x.a.WarnImport("sphereBuilder")},C.CreateCylinder=function(m){throw x.a.WarnImport("cylinderBuilder")},C.CreateTorus=function(m){throw x.a.WarnImport("torusBuilder")},C.CreateLineSystem=function(m){throw x.a.WarnImport("linesBuilder")},C.CreateDashedLines=function(m){throw x.a.WarnImport("linesBuilder")},C.CreateGround=function(m){throw x.a.WarnImport("groundBuilder")},C.CreateTiledGround=function(m){throw x.a.WarnImport("groundBuilder")},C.CreateGroundFromHeightMap=function(m){throw x.a.WarnImport("groundBuilder")},C.CreatePlane=function(m){throw x.a.WarnImport("planeBuilder")},C.CreateDisc=function(m){throw x.a.WarnImport("discBuilder")},C.CreatePolygon=function(m,c,T,A,S,g,l){throw x.a.WarnImport("polygonBuilder")},C.CreateIcoSphere=function(m){throw x.a.WarnImport("icoSphereBuilder")},C.CreatePolyhedron=function(m){throw x.a.WarnImport("polyhedronBuilder")},C.CreateCapsule=function(m){throw m===void 0&&(m={orientation:U.e.Up(),subdivisions:2,tessellation:16,height:1,radius:.25,capSubdivisions:6}),x.a.WarnImport("capsuleBuilder")},C.CreateTorusKnot=function(m){throw x.a.WarnImport("torusKnotBuilder")},C.ComputeNormals=function(m,c,T,A){var S=0,g=0,l=0,h=0,v=0,E=0,D=0,w=0,N=0,I=0,V=0,X=0,j=0,ne=0,te=0,de=0,pe=0,ae=0,ee=0,K=0,$=!1,L=!1,G=!1,Q=!1,oe=1,re=0,Y=null;if(A&&($=!!A.facetNormals,L=!!A.facetPositions,G=!!A.facetPartitioning,oe=A.useRightHandedSystem===!0?-1:1,re=A.ratio||0,Q=!!A.depthSort,Y=A.distanceTo,Q)){Y===void 0&&(Y=U.e.Zero());var k=A.depthSortedFacets}var H=0,Z=0,W=0,q=0;if(G&&A&&A.bbSize){var he=0,ge=0,me=0,_e=0,be=0,Pe=0,ye=0,Be=0,ke=0,We=0,je=0,He=0,qe=0,Ge=0,nt=0,$e=0,ct=A.bbSize.x>A.bbSize.y?A.bbSize.x:A.bbSize.y;ct=ct>A.bbSize.z?ct:A.bbSize.z,H=A.subDiv.X*re/A.bbSize.x,Z=A.subDiv.Y*re/A.bbSize.y,W=A.subDiv.Z*re/A.bbSize.z,q=A.subDiv.max*A.subDiv.max,A.facetPartitioning.length=0}for(S=0;S<m.length;S++)T[S]=0;var st=c.length/3|0;for(S=0;S<st;S++){if(j=(X=3*c[3*S])+1,ne=X+2,de=(te=3*c[3*S+1])+1,pe=te+2,ee=(ae=3*c[3*S+2])+1,K=ae+2,g=m[X]-m[te],l=m[j]-m[de],h=m[ne]-m[pe],v=m[ae]-m[te],E=m[ee]-m[de],w=oe*(l*(D=m[K]-m[pe])-h*E),N=oe*(h*v-g*D),I=oe*(g*E-l*v),w/=V=(V=Math.sqrt(w*w+N*N+I*I))===0?1:V,N/=V,I/=V,$&&A&&(A.facetNormals[S].x=w,A.facetNormals[S].y=N,A.facetNormals[S].z=I),L&&A&&(A.facetPositions[S].x=(m[X]+m[te]+m[ae])/3,A.facetPositions[S].y=(m[j]+m[de]+m[ee])/3,A.facetPositions[S].z=(m[ne]+m[pe]+m[K])/3),G&&A&&(he=Math.floor((A.facetPositions[S].x-A.bInfo.minimum.x*re)*H),ge=Math.floor((A.facetPositions[S].y-A.bInfo.minimum.y*re)*Z),me=Math.floor((A.facetPositions[S].z-A.bInfo.minimum.z*re)*W),_e=Math.floor((m[X]-A.bInfo.minimum.x*re)*H),be=Math.floor((m[j]-A.bInfo.minimum.y*re)*Z),Pe=Math.floor((m[ne]-A.bInfo.minimum.z*re)*W),ye=Math.floor((m[te]-A.bInfo.minimum.x*re)*H),Be=Math.floor((m[de]-A.bInfo.minimum.y*re)*Z),ke=Math.floor((m[pe]-A.bInfo.minimum.z*re)*W),We=Math.floor((m[ae]-A.bInfo.minimum.x*re)*H),je=Math.floor((m[ee]-A.bInfo.minimum.y*re)*Z),He=Math.floor((m[K]-A.bInfo.minimum.z*re)*W),Ge=_e+A.subDiv.max*be+q*Pe,nt=ye+A.subDiv.max*Be+q*ke,$e=We+A.subDiv.max*je+q*He,qe=he+A.subDiv.max*ge+q*me,A.facetPartitioning[qe]=A.facetPartitioning[qe]?A.facetPartitioning[qe]:new Array,A.facetPartitioning[Ge]=A.facetPartitioning[Ge]?A.facetPartitioning[Ge]:new Array,A.facetPartitioning[nt]=A.facetPartitioning[nt]?A.facetPartitioning[nt]:new Array,A.facetPartitioning[$e]=A.facetPartitioning[$e]?A.facetPartitioning[$e]:new Array,A.facetPartitioning[Ge].push(S),nt!=Ge&&A.facetPartitioning[nt].push(S),$e!=nt&&$e!=Ge&&A.facetPartitioning[$e].push(S),qe!=Ge&&qe!=nt&&qe!=$e&&A.facetPartitioning[qe].push(S)),Q&&A&&A.facetPositions){var mt=k[S];mt.ind=3*S,mt.sqDistance=U.e.DistanceSquared(A.facetPositions[S],Y)}T[X]+=w,T[j]+=N,T[ne]+=I,T[te]+=w,T[de]+=N,T[pe]+=I,T[ae]+=w,T[ee]+=N,T[K]+=I}for(S=0;S<T.length/3;S++)w=T[3*S],N=T[3*S+1],I=T[3*S+2],w/=V=(V=Math.sqrt(w*w+N*N+I*I))===0?1:V,N/=V,I/=V,T[3*S]=w,T[3*S+1]=N,T[3*S+2]=I},C._ComputeSides=function(m,c,T,A,S,g,l){var h,v,E=T.length,D=A.length;switch(m=m||C.DEFAULTSIDE){case C.FRONTSIDE:break;case C.BACKSIDE:var w;for(h=0;h<E;h+=3)w=T[h],T[h]=T[h+2],T[h+2]=w;for(v=0;v<D;v++)A[v]=-A[v];break;case C.DOUBLESIDE:for(var N=c.length,I=N/3,V=0;V<N;V++)c[N+V]=c[V];for(h=0;h<E;h+=3)T[h+E]=T[h+2]+I,T[h+1+E]=T[h+1]+I,T[h+2+E]=T[h]+I;for(v=0;v<D;v++)A[D+v]=-A[v];var X=S.length,j=0;for(j=0;j<X;j++)S[j+X]=S[j];for(g=g||new U.f(0,0,1,1),l=l||new U.f(0,0,1,1),j=0,h=0;h<X/2;h++)S[j]=g.x+(g.z-g.x)*S[j],S[j+1]=g.y+(g.w-g.y)*S[j+1],S[j+X]=l.x+(l.z-l.x)*S[j+X],S[j+X+1]=l.y+(l.w-l.y)*S[j+X+1],j+=2}},C.ImportVertexData=function(m,c){var T=new C,A=m.positions;A&&T.set(A,_.b.PositionKind);var S=m.normals;S&&T.set(S,_.b.NormalKind);var g=m.tangents;g&&T.set(g,_.b.TangentKind);var l=m.uvs;l&&T.set(l,_.b.UVKind);var h=m.uv2s;h&&T.set(h,_.b.UV2Kind);var v=m.uv3s;v&&T.set(v,_.b.UV3Kind);var E=m.uv4s;E&&T.set(E,_.b.UV4Kind);var D=m.uv5s;D&&T.set(D,_.b.UV5Kind);var w=m.uv6s;w&&T.set(w,_.b.UV6Kind);var N=m.colors;N&&T.set(u.b.CheckColors4(N,A.length/3),_.b.ColorKind);var I=m.matricesIndices;I&&T.set(I,_.b.MatricesIndicesKind);var V=m.matricesWeights;V&&T.set(V,_.b.MatricesWeightsKind);var X=m.indices;X&&(T.indices=X),c.setAllVerticesData(T,m.updatable)},C.FRONTSIDE=0,C.BACKSIDE=1,C.DOUBLESIDE=2,C.DEFAULTSIDE=0,C}()},function(Me,y,f){f.d(y,"a",function(){return _}),f.d(y,"b",function(){return x});var U=f(1),_=function(){function u(){}return u.NAME_EFFECTLAYER="EffectLayer",u.NAME_LAYER="Layer",u.NAME_LENSFLARESYSTEM="LensFlareSystem",u.NAME_BOUNDINGBOXRENDERER="BoundingBoxRenderer",u.NAME_PARTICLESYSTEM="ParticleSystem",u.NAME_GAMEPAD="Gamepad",u.NAME_SIMPLIFICATIONQUEUE="SimplificationQueue",u.NAME_GEOMETRYBUFFERRENDERER="GeometryBufferRenderer",u.NAME_PREPASSRENDERER="PrePassRenderer",u.NAME_DEPTHRENDERER="DepthRenderer",u.NAME_POSTPROCESSRENDERPIPELINEMANAGER="PostProcessRenderPipelineManager",u.NAME_SPRITE="Sprite",u.NAME_SUBSURFACE="SubSurface",u.NAME_OUTLINERENDERER="Outline",u.NAME_PROCEDURALTEXTURE="ProceduralTexture",u.NAME_SHADOWGENERATOR="ShadowGenerator",u.NAME_OCTREE="Octree",u.NAME_PHYSICSENGINE="PhysicsEngine",u.NAME_AUDIO="Audio",u.STEP_ISREADYFORMESH_EFFECTLAYER=0,u.STEP_BEFOREEVALUATEACTIVEMESH_BOUNDINGBOXRENDERER=0,u.STEP_EVALUATESUBMESH_BOUNDINGBOXRENDERER=0,u.STEP_PREACTIVEMESH_BOUNDINGBOXRENDERER=0,u.STEP_CAMERADRAWRENDERTARGET_EFFECTLAYER=1,u.STEP_BEFORECAMERADRAW_EFFECTLAYER=0,u.STEP_BEFORECAMERADRAW_LAYER=1,u.STEP_BEFORECAMERADRAW_PREPASS=2,u.STEP_BEFORERENDERTARGETDRAW_LAYER=0,u.STEP_BEFORERENDERINGMESH_PREPASS=0,u.STEP_BEFORERENDERINGMESH_OUTLINE=1,u.STEP_AFTERRENDERINGMESH_PREPASS=0,u.STEP_AFTERRENDERINGMESH_OUTLINE=1,u.STEP_AFTERRENDERINGGROUPDRAW_EFFECTLAYER_DRAW=0,u.STEP_AFTERRENDERINGGROUPDRAW_BOUNDINGBOXRENDERER=1,u.STEP_BEFORECAMERAUPDATE_SIMPLIFICATIONQUEUE=0,u.STEP_BEFORECAMERAUPDATE_GAMEPAD=1,u.STEP_BEFORECLEAR_PROCEDURALTEXTURE=0,u.STEP_AFTERRENDERTARGETDRAW_LAYER=0,u.STEP_AFTERCAMERADRAW_EFFECTLAYER=0,u.STEP_AFTERCAMERADRAW_LENSFLARESYSTEM=1,u.STEP_AFTERCAMERADRAW_EFFECTLAYER_DRAW=2,u.STEP_AFTERCAMERADRAW_LAYER=3,u.STEP_AFTERCAMERADRAW_PREPASS=4,u.STEP_AFTERRENDER_AUDIO=0,u.STEP_GATHERRENDERTARGETS_DEPTHRENDERER=0,u.STEP_GATHERRENDERTARGETS_GEOMETRYBUFFERRENDERER=1,u.STEP_GATHERRENDERTARGETS_SHADOWGENERATOR=2,u.STEP_GATHERRENDERTARGETS_POSTPROCESSRENDERPIPELINEMANAGER=3,u.STEP_GATHERACTIVECAMERARENDERTARGETS_DEPTHRENDERER=0,u.STEP_BEFORECLEARSTAGE_PREPASS=0,u.STEP_POINTERMOVE_SPRITE=0,u.STEP_POINTERDOWN_SPRITE=0,u.STEP_POINTERUP_SPRITE=0,u}(),x=function(u){function 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this._ClearCoatTintTextureEnabled},set:function(M){this._ClearCoatTintTextureEnabled!==M&&(this._ClearCoatTintTextureEnabled=M,U.a.MarkAllMaterialsAsDirty(_.a.MATERIAL_TextureDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(u,"SheenTextureEnabled",{get:function(){return this._SheenTextureEnabled},set:function(M){this._SheenTextureEnabled!==M&&(this._SheenTextureEnabled=M,U.a.MarkAllMaterialsAsDirty(_.a.MATERIAL_TextureDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(u,"AnisotropicTextureEnabled",{get:function(){return this._AnisotropicTextureEnabled},set:function(M){this._AnisotropicTextureEnabled!==M&&(this._AnisotropicTextureEnabled=M,U.a.MarkAllMaterialsAsDirty(_.a.MATERIAL_TextureDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(u,"ThicknessTextureEnabled",{get:function(){return this._ThicknessTextureEnabled},set:function(M){this._ThicknessTextureEnabled!==M&&(this._ThicknessTextureEnabled=M,U.a.MarkAllMaterialsAsDirty(_.a.MATERIAL_TextureDirtyFlag))},enumerable:!1,configurable:!0}),u._DiffuseTextureEnabled=!0,u._DetailTextureEnabled=!0,u._AmbientTextureEnabled=!0,u._OpacityTextureEnabled=!0,u._ReflectionTextureEnabled=!0,u._EmissiveTextureEnabled=!0,u._SpecularTextureEnabled=!0,u._BumpTextureEnabled=!0,u._LightmapTextureEnabled=!0,u._RefractionTextureEnabled=!0,u._ColorGradingTextureEnabled=!0,u._FresnelEnabled=!0,u._ClearCoatTextureEnabled=!0,u._ClearCoatBumpTextureEnabled=!0,u._ClearCoatTintTextureEnabled=!0,u._SheenTextureEnabled=!0,u._AnisotropicTextureEnabled=!0,u._ThicknessTextureEnabled=!0,u}()},function(Me,y,f){f.d(y,"a",function(){return oe});var U=f(1),_=f(12),x=f(57),u=f(6),M=f(33),R=f(112),C=f(37),m=f(0),c=f(46),T=f(31),A=f(24),S=f(35),g=f(42),l=f(85),h=f(48),v=f(54),E=f(47),D=f(95),w=f(96),N=f(17),I=f(2),V=f(38),X=f(8),j=f(22),ne=f(21),te=f(18),de=f(91),pe=f(66),ae=function(){function re(){this._singleClick=!1,this._doubleClick=!1,this._hasSwiped=!1,this._ignore=!1}return Object.defineProperty(re.prototype,"singleClick",{get:function(){return this._singleClick},set:function(Y){this._singleClick=Y},enumerable:!1,configurable:!0}),Object.defineProperty(re.prototype,"doubleClick",{get:function(){return this._doubleClick},set:function(Y){this._doubleClick=Y},enumerable:!1,configurable:!0}),Object.defineProperty(re.prototype,"hasSwiped",{get:function(){return this._hasSwiped},set:function(Y){this._hasSwiped=Y},enumerable:!1,configurable:!0}),Object.defineProperty(re.prototype,"ignore",{get:function(){return this._ignore},set:function(Y){this._ignore=Y},enumerable:!1,configurable:!0}),re}(),ee=function(){function re(Y){this._alreadyAttached=!1,this._wheelEventName="",this._meshPickProceed=!1,this._currentPickResult=null,this._previousPickResult=null,this._totalPointersPressed=0,this._doubleClickOccured=!1,this._pointerX=0,this._pointerY=0,this._startingPointerPosition=new m.d(0,0),this._previousStartingPointerPosition=new m.d(0,0),this._startingPointerTime=0,this._previousStartingPointerTime=0,this._pointerCaptures={},this._meshUnderPointerId=[],this._keyboardIsAttached=!1,this._scene=Y}return Object.defineProperty(re.prototype,"meshUnderPointer",{get:function(){return this._pointerOverMesh},enumerable:!1,configurable:!0}),re.prototype.getMeshUnderPointerByPointerId=function(Y){return this._meshUnderPointerId[Y]},Object.defineProperty(re.prototype,"unTranslatedPointer",{get:function(){return new m.d(this._unTranslatedPointerX,this._unTranslatedPointerY)},enumerable:!1,configurable:!0}),Object.defineProperty(re.prototype,"pointerX",{get:function(){return this._pointerX},set:function(Y){this._pointerX=Y},enumerable:!1,configurable:!0}),Object.defineProperty(re.prototype,"pointerY",{get:function(){return this._pointerY},set:function(Y){this._pointerY=Y},enumerable:!1,configurable:!0}),re.prototype._updatePointerPosition=function(Y){var k=this._scene.getEngine().getInputElementClientRect();k&&(this._pointerX=Y.clientX-k.left,this._pointerY=Y.clientY-k.top,this._unTranslatedPointerX=this._pointerX,this._unTranslatedPointerY=this._pointerY)},re.prototype._processPointerMove=function(Y,k){var H=this._scene,Z=H.getEngine(),W=Z.getInputElement();if(W){W.tabIndex=Z.canvasTabIndex,H.doNotHandleCursors||(W.style.cursor=H.defaultCursor);var q=!!(Y&&Y.hit&&Y.pickedMesh);q?(H.setPointerOverMesh(Y.pickedMesh,k.pointerId),this._pointerOverMesh&&this._pointerOverMesh.actionManager&&this._pointerOverMesh.actionManager.hasPointerTriggers&&(H.doNotHandleCursors||(this._pointerOverMesh.actionManager.hoverCursor?W.style.cursor=this._pointerOverMesh.actionManager.hoverCursor:W.style.cursor=H.hoverCursor))):H.setPointerOverMesh(null,k.pointerId);for(var he=0,ge=H._pointerMoveStage;he<ge.length;he++)Y=ge[he].action(this._unTranslatedPointerX,this._unTranslatedPointerY,Y,q,W);if(Y){var me=k.type===this._wheelEventName?te.a.POINTERWHEEL:te.a.POINTERMOVE;if(H.onPointerMove&&H.onPointerMove(k,Y,me),H.onPointerObservable.hasObservers()){var _e=new te.b(me,k,Y);this._setRayOnPointerInfo(_e),H.onPointerObservable.notifyObservers(_e,me)}}}},re.prototype._setRayOnPointerInfo=function(Y){var k=this._scene;Y.pickInfo&&!Y.pickInfo._pickingUnavailable&&(Y.pickInfo.ray||(Y.pickInfo.ray=k.createPickingRay(Y.event.offsetX,Y.event.offsetY,m.a.Identity(),k.activeCamera)))},re.prototype._checkPrePointerObservable=function(Y,k,H){var Z=this._scene,W=new te.d(H,k,this._unTranslatedPointerX,this._unTranslatedPointerY);return Y&&(W.ray=Y.ray),Z.onPrePointerObservable.notifyObservers(W,H),!!W.skipOnPointerObservable},re.prototype.simulatePointerMove=function(Y,k){var H=new PointerEvent("pointermove",k);this._checkPrePointerObservable(Y,H,te.a.POINTERMOVE)||this._processPointerMove(Y,H)},re.prototype.simulatePointerDown=function(Y,k){var H=new PointerEvent("pointerdown",k);this._checkPrePointerObservable(Y,H,te.a.POINTERDOWN)||this._processPointerDown(Y,H)},re.prototype._processPointerDown=function(Y,k){var H=this,Z=this._scene;if(Y&&Y.hit&&Y.pickedMesh){this._pickedDownMesh=Y.pickedMesh;var W=Y.pickedMesh._getActionManagerForTrigger();if(W){if(W.hasPickTriggers)switch(W.processTrigger(I.a.ACTION_OnPickDownTrigger,E.a.CreateNew(Y.pickedMesh,k)),k.button){case 0:W.processTrigger(I.a.ACTION_OnLeftPickTrigger,E.a.CreateNew(Y.pickedMesh,k));break;case 1:W.processTrigger(I.a.ACTION_OnCenterPickTrigger,E.a.CreateNew(Y.pickedMesh,k));break;case 2:W.processTrigger(I.a.ACTION_OnRightPickTrigger,E.a.CreateNew(Y.pickedMesh,k))}W.hasSpecificTrigger(I.a.ACTION_OnLongPressTrigger)&&window.setTimeout(function(){var _e=Z.pick(H._unTranslatedPointerX,H._unTranslatedPointerY,function(be){return be.isPickable&&be.isVisible&&be.isReady()&&be.actionManager&&be.actionManager.hasSpecificTrigger(I.a.ACTION_OnLongPressTrigger)&&be==H._pickedDownMesh},!1,Z.cameraToUseForPointers);_e&&_e.hit&&_e.pickedMesh&&W&&H._totalPointersPressed!==0&&Date.now()-H._startingPointerTime>re.LongPressDelay&&!H._isPointerSwiping()&&(H._startingPointerTime=0,W.processTrigger(I.a.ACTION_OnLongPressTrigger,E.a.CreateNew(_e.pickedMesh,k)))},re.LongPressDelay)}}else for(var q=0,he=Z._pointerDownStage;q<he.length;q++)Y=he[q].action(this._unTranslatedPointerX,this._unTranslatedPointerY,Y,k);if(Y){var ge=te.a.POINTERDOWN;if(Z.onPointerDown&&Z.onPointerDown(k,Y,ge),Z.onPointerObservable.hasObservers()){var me=new te.b(ge,k,Y);this._setRayOnPointerInfo(me),Z.onPointerObservable.notifyObservers(me,ge)}}},re.prototype._isPointerSwiping=function(){return Math.abs(this._startingPointerPosition.x-this._pointerX)>re.DragMovementThreshold||Math.abs(this._startingPointerPosition.y-this._pointerY)>re.DragMovementThreshold},re.prototype.simulatePointerUp=function(Y,k,H){var Z=new PointerEvent("pointerup",k),W=new ae;H?W.doubleClick=!0:W.singleClick=!0,this._checkPrePointerObservable(Y,Z,te.a.POINTERUP)||this._processPointerUp(Y,Z,W)},re.prototype._processPointerUp=function(Y,k,H){var Z=this._scene;if(Y&&Y&&Y.pickedMesh){if(this._pickedUpMesh=Y.pickedMesh,this._pickedDownMesh===this._pickedUpMesh&&(Z.onPointerPick&&Z.onPointerPick(k,Y),H.singleClick&&!H.ignore&&Z.onPointerObservable.hasObservers())){var W=te.a.POINTERPICK,q=new te.b(W,k,Y);this._setRayOnPointerInfo(q),Z.onPointerObservable.notifyObservers(q,W)}var he=Y.pickedMesh._getActionManagerForTrigger();if(he&&!H.ignore){he.processTrigger(I.a.ACTION_OnPickUpTrigger,E.a.CreateNew(Y.pickedMesh,k)),!H.hasSwiped&&H.singleClick&&he.processTrigger(I.a.ACTION_OnPickTrigger,E.a.CreateNew(Y.pickedMesh,k));var ge=Y.pickedMesh._getActionManagerForTrigger(I.a.ACTION_OnDoublePickTrigger);H.doubleClick&&ge&&ge.processTrigger(I.a.ACTION_OnDoublePickTrigger,E.a.CreateNew(Y.pickedMesh,k))}}else if(!H.ignore)for(var me=0,_e=Z._pointerUpStage;me<_e.length;me++)Y=_e[me].action(this._unTranslatedPointerX,this._unTranslatedPointerY,Y,k);if(this._pickedDownMesh&&this._pickedDownMesh!==this._pickedUpMesh){var be=this._pickedDownMesh._getActionManagerForTrigger(I.a.ACTION_OnPickOutTrigger);be&&be.processTrigger(I.a.ACTION_OnPickOutTrigger,E.a.CreateNew(this._pickedDownMesh,k))}var Pe=0;Z.onPointerObservable.hasObservers()&&(!H.ignore&&!H.hasSwiped&&(H.singleClick&&Z.onPointerObservable.hasSpecificMask(te.a.POINTERTAP)?Pe=te.a.POINTERTAP:H.doubleClick&&Z.onPointerObservable.hasSpecificMask(te.a.POINTERDOUBLETAP)&&(Pe=te.a.POINTERDOUBLETAP),Pe)&&(q=new te.b(Pe,k,Y),this._setRayOnPointerInfo(q),Z.onPointerObservable.notifyObservers(q,Pe)),H.ignore||(Pe=te.a.POINTERUP,q=new te.b(Pe,k,Y),this._setRayOnPointerInfo(q),Z.onPointerObservable.notifyObservers(q,Pe))),Z.onPointerUp&&!H.ignore&&Z.onPointerUp(k,Y,Pe)},re.prototype.isPointerCaptured=function(Y){return Y===void 0&&(Y=0),this._pointerCaptures[Y]},re.prototype.attachControl=function(Y,k,H,Z){var W=this;Y===void 0&&(Y=!0),k===void 0&&(k=!0),H===void 0&&(H=!0),Z===void 0&&(Z=null);var q=this._scene;if(Z||(Z=q.getEngine().getInputElement()),Z){this._alreadyAttached&&this.detachControl(),this._alreadyAttachedTo=Z;var he=q.getEngine();this._initActionManager=function(be,Pe){if(!W._meshPickProceed){var ye=q.pick(W._unTranslatedPointerX,W._unTranslatedPointerY,q.pointerDownPredicate,!1,q.cameraToUseForPointers);W._currentPickResult=ye,ye&&(be=ye.hit&&ye.pickedMesh?ye.pickedMesh._getActionManagerForTrigger():null),W._meshPickProceed=!0}return be},this._delayedSimpleClick=function(be,Pe,ye){(Date.now()-W._previousStartingPointerTime>re.DoubleClickDelay&&!W._doubleClickOccured||be!==W._previousButtonPressed)&&(W._doubleClickOccured=!1,Pe.singleClick=!0,Pe.ignore=!1,ye(Pe,W._currentPickResult))},this._initClickEvent=function(be,Pe,ye,Be){var ke=new ae;W._currentPickResult=null;var We=null,je=be.hasSpecificMask(te.a.POINTERPICK)||Pe.hasSpecificMask(te.a.POINTERPICK)||be.hasSpecificMask(te.a.POINTERTAP)||Pe.hasSpecificMask(te.a.POINTERTAP)||be.hasSpecificMask(te.a.POINTERDOUBLETAP)||Pe.hasSpecificMask(te.a.POINTERDOUBLETAP);!je&&de.a&&(We=W._initActionManager(We,ke))&&(je=We.hasPickTriggers);var He=!1;if(je){var qe=ye.button;if(ke.hasSwiped=W._isPointerSwiping(),!ke.hasSwiped){var Ge=!re.ExclusiveDoubleClickMode;Ge||(Ge=!be.hasSpecificMask(te.a.POINTERDOUBLETAP)&&!Pe.hasSpecificMask(te.a.POINTERDOUBLETAP))&&!de.a.HasSpecificTrigger(I.a.ACTION_OnDoublePickTrigger)&&(We=W._initActionManager(We,ke))&&(Ge=!We.hasSpecificTrigger(I.a.ACTION_OnDoublePickTrigger)),Ge?(Date.now()-W._previousStartingPointerTime>re.DoubleClickDelay||qe!==W._previousButtonPressed)&&(ke.singleClick=!0,Be(ke,W._currentPickResult),He=!0):(W._previousDelayedSimpleClickTimeout=W._delayedSimpleClickTimeout,W._delayedSimpleClickTimeout=window.setTimeout(W._delayedSimpleClick.bind(W,qe,ke,Be),re.DoubleClickDelay));var nt=be.hasSpecificMask(te.a.POINTERDOUBLETAP)||Pe.hasSpecificMask(te.a.POINTERDOUBLETAP);!nt&&de.a.HasSpecificTrigger(I.a.ACTION_OnDoublePickTrigger)&&(We=W._initActionManager(We,ke))&&(nt=We.hasSpecificTrigger(I.a.ACTION_OnDoublePickTrigger)),nt&&(qe===W._previousButtonPressed&&Date.now()-W._previousStartingPointerTime<re.DoubleClickDelay&&!W._doubleClickOccured?(ke.hasSwiped||W._isPointerSwiping()?(W._doubleClickOccured=!1,W._previousStartingPointerTime=W._startingPointerTime,W._previousStartingPointerPosition.x=W._startingPointerPosition.x,W._previousStartingPointerPosition.y=W._startingPointerPosition.y,W._previousButtonPressed=qe,re.ExclusiveDoubleClickMode?(W._previousDelayedSimpleClickTimeout&&clearTimeout(W._previousDelayedSimpleClickTimeout),W._previousDelayedSimpleClickTimeout=W._delayedSimpleClickTimeout,Be(ke,W._previousPickResult)):Be(ke,W._currentPickResult)):(W._previousStartingPointerTime=0,W._doubleClickOccured=!0,ke.doubleClick=!0,ke.ignore=!1,re.ExclusiveDoubleClickMode&&W._previousDelayedSimpleClickTimeout&&clearTimeout(W._previousDelayedSimpleClickTimeout),W._previousDelayedSimpleClickTimeout=W._delayedSimpleClickTimeout,Be(ke,W._currentPickResult)),He=!0):(W._doubleClickOccured=!1,W._previousStartingPointerTime=W._startingPointerTime,W._previousStartingPointerPosition.x=W._startingPointerPosition.x,W._previousStartingPointerPosition.y=W._startingPointerPosition.y,W._previousButtonPressed=qe))}}He||Be(ke,W._currentPickResult)},this._onPointerMove=function(be){if(be.pointerId===void 0&&(be.pointerId=0),W._updatePointerPosition(be),!W._checkPrePointerObservable(null,be,be.type===W._wheelEventName?te.a.POINTERWHEEL:te.a.POINTERMOVE)&&(q.cameraToUseForPointers||q.activeCamera)){q.pointerMovePredicate||(q.pointerMovePredicate=function(ye){return ye.isPickable&&ye.isVisible&&ye.isReady()&&ye.isEnabled()&&(ye.enablePointerMoveEvents||q.constantlyUpdateMeshUnderPointer||ye._getActionManagerForTrigger()!=null)&&(!q.cameraToUseForPointers||(q.cameraToUseForPointers.layerMask&ye.layerMask)!=0)});var Pe=q.pick(W._unTranslatedPointerX,W._unTranslatedPointerY,q.pointerMovePredicate,!1,q.cameraToUseForPointers);W._processPointerMove(Pe,be)}},this._onPointerDown=function(be){if(W._totalPointersPressed++,W._pickedDownMesh=null,W._meshPickProceed=!1,be.pointerId===void 0&&(be.pointerId=0),W._updatePointerPosition(be),q.preventDefaultOnPointerDown&&Z&&(be.preventDefault(),Z.focus()),W._startingPointerPosition.x=W._pointerX,W._startingPointerPosition.y=W._pointerY,W._startingPointerTime=Date.now(),!W._checkPrePointerObservable(null,be,te.a.POINTERDOWN)&&(q.cameraToUseForPointers||q.activeCamera)){W._pointerCaptures[be.pointerId]=!0,q.pointerDownPredicate||(q.pointerDownPredicate=function(ye){return ye.isPickable&&ye.isVisible&&ye.isReady()&&ye.isEnabled()&&(!q.cameraToUseForPointers||(q.cameraToUseForPointers.layerMask&ye.layerMask)!=0)}),W._pickedDownMesh=null;var Pe=q.pick(W._unTranslatedPointerX,W._unTranslatedPointerY,q.pointerDownPredicate,!1,q.cameraToUseForPointers);W._processPointerDown(Pe,be)}},this._onPointerUp=function(be){W._totalPointersPressed!==0&&(W._totalPointersPressed--,W._pickedUpMesh=null,W._meshPickProceed=!1,be.pointerId===void 0&&(be.pointerId=0),W._updatePointerPosition(be),q.preventDefaultOnPointerUp&&Z&&(be.preventDefault(),Z.focus()),W._initClickEvent(q.onPrePointerObservable,q.onPointerObservable,be,function(Pe,ye){q.onPrePointerObservable.hasObservers()&&!Pe.ignore&&(!Pe.hasSwiped&&(Pe.singleClick&&q.onPrePointerObservable.hasSpecificMask(te.a.POINTERTAP)&&W._checkPrePointerObservable(null,be,te.a.POINTERTAP)||Pe.doubleClick&&q.onPrePointerObservable.hasSpecificMask(te.a.POINTERDOUBLETAP)&&W._checkPrePointerObservable(null,be,te.a.POINTERDOUBLETAP))||W._checkPrePointerObservable(null,be,te.a.POINTERUP))||W._pointerCaptures[be.pointerId]&&(W._pointerCaptures[be.pointerId]=!1,(q.cameraToUseForPointers||q.activeCamera)&&(q.pointerUpPredicate||(q.pointerUpPredicate=function(Be){return Be.isPickable&&Be.isVisible&&Be.isReady()&&Be.isEnabled()&&(!q.cameraToUseForPointers||(q.cameraToUseForPointers.layerMask&Be.layerMask)!=0)}),!W._meshPickProceed&&(de.a&&de.a.HasTriggers||q.onPointerObservable.hasObservers())&&W._initActionManager(null,Pe),ye||(ye=W._currentPickResult),W._processPointerUp(ye,be,Pe),W._previousPickResult=W._currentPickResult))}))},this._onKeyDown=function(be){var Pe=pe.a.KEYDOWN;if(q.onPreKeyboardObservable.hasObservers()){var ye=new pe.c(Pe,be);if(q.onPreKeyboardObservable.notifyObservers(ye,Pe),ye.skipOnPointerObservable)return}q.onKeyboardObservable.hasObservers()&&(ye=new pe.b(Pe,be),q.onKeyboardObservable.notifyObservers(ye,Pe)),q.actionManager&&q.actionManager.processTrigger(I.a.ACTION_OnKeyDownTrigger,E.a.CreateNewFromScene(q,be))},this._onKeyUp=function(be){var Pe=pe.a.KEYUP;if(q.onPreKeyboardObservable.hasObservers()){var ye=new pe.c(Pe,be);if(q.onPreKeyboardObservable.notifyObservers(ye,Pe),ye.skipOnPointerObservable)return}q.onKeyboardObservable.hasObservers()&&(ye=new pe.b(Pe,be),q.onKeyboardObservable.notifyObservers(ye,Pe)),q.actionManager&&q.actionManager.processTrigger(I.a.ACTION_OnKeyUpTrigger,E.a.CreateNewFromScene(q,be))};var ge=function(){Z&&!W._keyboardIsAttached&&(Z.addEventListener("keydown",W._onKeyDown,!1),Z.addEventListener("keyup",W._onKeyUp,!1),W._keyboardIsAttached=!0)};this._onCanvasFocusObserver=he.onCanvasFocusObservable.add((document.activeElement===Z&&ge(),ge)),this._onCanvasBlurObserver=he.onCanvasBlurObservable.add(function(){Z&&(Z.removeEventListener("keydown",W._onKeyDown),Z.removeEventListener("keyup",W._onKeyUp),W._keyboardIsAttached=!1)}),ge();var me=_.b.GetPointerPrefix(he);if(H&&(Z.addEventListener(me+"move",this._onPointerMove,!1),this._wheelEventName="onwheel"in document.createElement("div")?"wheel":document.onmousewheel!==void 0?"mousewheel":"DOMMouseScroll",Z.addEventListener(this._wheelEventName,this._onPointerMove,!1)),k&&Z.addEventListener(me+"down",this._onPointerDown,!1),Y){var _e=q.getEngine().getHostWindow();_e&&_e.addEventListener(me+"up",this._onPointerUp,!1)}this._alreadyAttached=!0}},re.prototype.detachControl=function(){var Y=this._scene.getEngine(),k=_.b.GetPointerPrefix(Y);this._alreadyAttachedTo&&this._alreadyAttached&&(this._alreadyAttachedTo.removeEventListener(k+"move",this._onPointerMove),this._alreadyAttachedTo.removeEventListener(this._wheelEventName,this._onPointerMove),this._alreadyAttachedTo.removeEventListener(k+"down",this._onPointerDown),window.removeEventListener(k+"up",this._onPointerUp),this._onCanvasBlurObserver&&Y.onCanvasBlurObservable.remove(this._onCanvasBlurObserver),this._onCanvasFocusObserver&&Y.onCanvasFocusObservable.remove(this._onCanvasFocusObserver),this._alreadyAttachedTo.removeEventListener("keydown",this._onKeyDown),this._alreadyAttachedTo.removeEventListener("keyup",this._onKeyUp),this._scene.doNotHandleCursors||(this._alreadyAttachedTo.style.cursor=this._scene.defaultCursor),this._alreadyAttached=!1)},re.prototype.setPointerOverMesh=function(Y,k){if(k===void 0&&(k=0),k<0&&(k=0),this._meshUnderPointerId[k]!==Y){var H,Z=this._meshUnderPointerId[k];Z&&(H=Z._getActionManagerForTrigger(I.a.ACTION_OnPointerOutTrigger))&&H.processTrigger(I.a.ACTION_OnPointerOutTrigger,E.a.CreateNew(Z,void 0,{pointerId:k})),this._meshUnderPointerId[k]=Y,this._pointerOverMesh=Y,(Z=this._meshUnderPointerId[k])&&(H=Z._getActionManagerForTrigger(I.a.ACTION_OnPointerOverTrigger))&&H.processTrigger(I.a.ACTION_OnPointerOverTrigger,E.a.CreateNew(Z,void 0,{pointerId:k}))}},re.prototype.getPointerOverMesh=function(){return this._pointerOverMesh},re.DragMovementThreshold=10,re.LongPressDelay=500,re.DoubleClickDelay=300,re.ExclusiveDoubleClickMode=!1,re}(),K=f(55),$=f(9),L=f(90),G=f(152),Q=f(56),oe=function(re){function Y(k,H){var Z=re.call(this)||this;Z._inputManager=new ee(Z),Z.cameraToUseForPointers=null,Z._isScene=!0,Z._blockEntityCollection=!1,Z.autoClear=!0,Z.autoClearDepthAndStencil=!0,Z.clearColor=new $.b(.2,.2,.3,1),Z.ambientColor=new $.a(0,0,0),Z._environmentIntensity=1,Z._forceWireframe=!1,Z._skipFrustumClipping=!1,Z._forcePointsCloud=!1,Z.animationsEnabled=!0,Z._animationPropertiesOverride=null,Z.useConstantAnimationDeltaTime=!1,Z.constantlyUpdateMeshUnderPointer=!1,Z.hoverCursor="pointer",Z.defaultCursor="",Z.doNotHandleCursors=!1,Z.preventDefaultOnPointerDown=!0,Z.preventDefaultOnPointerUp=!0,Z.metadata=null,Z.reservedDataStore=null,Z.disableOfflineSupportExceptionRules=new Array,Z.onDisposeObservable=new u.c,Z._onDisposeObserver=null,Z.onBeforeRenderObservable=new u.c,Z._onBeforeRenderObserver=null,Z.onAfterRenderObservable=new u.c,Z.onAfterRenderCameraObservable=new u.c,Z._onAfterRenderObserver=null,Z.onBeforeAnimationsObservable=new u.c,Z.onAfterAnimationsObservable=new u.c,Z.onBeforeDrawPhaseObservable=new u.c,Z.onAfterDrawPhaseObservable=new u.c,Z.onReadyObservable=new u.c,Z.onBeforeCameraRenderObservable=new u.c,Z._onBeforeCameraRenderObserver=null,Z.onAfterCameraRenderObservable=new u.c,Z._onAfterCameraRenderObserver=null,Z.onBeforeActiveMeshesEvaluationObservable=new u.c,Z.onAfterActiveMeshesEvaluationObservable=new u.c,Z.onBeforeParticlesRenderingObservable=new u.c,Z.onAfterParticlesRenderingObservable=new u.c,Z.onDataLoadedObservable=new u.c,Z.onNewCameraAddedObservable=new u.c,Z.onCameraRemovedObservable=new u.c,Z.onNewLightAddedObservable=new u.c,Z.onLightRemovedObservable=new u.c,Z.onNewGeometryAddedObservable=new u.c,Z.onGeometryRemovedObservable=new u.c,Z.onNewTransformNodeAddedObservable=new u.c,Z.onTransformNodeRemovedObservable=new u.c,Z.onNewMeshAddedObservable=new u.c,Z.onMeshRemovedObservable=new u.c,Z.onNewSkeletonAddedObservable=new u.c,Z.onSkeletonRemovedObservable=new u.c,Z.onNewMaterialAddedObservable=new u.c,Z.onNewMultiMaterialAddedObservable=new u.c,Z.onMaterialRemovedObservable=new u.c,Z.onMultiMaterialRemovedObservable=new u.c,Z.onNewTextureAddedObservable=new u.c,Z.onTextureRemovedObservable=new 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Z=this.transformNodes[this.transformNodes.length-1];this.transformNodes[H]=Z,Z._indexInSceneTransformNodesArray=H}k._indexInSceneTransformNodesArray=-1,this.transformNodes.pop(),k.parent||k._removeFromSceneRootNodes()}return this.onTransformNodeRemovedObservable.notifyObservers(k),H},Y.prototype.removeSkeleton=function(k){var H=this.skeletons.indexOf(k);return H!==-1&&(this.skeletons.splice(H,1),this.onSkeletonRemovedObservable.notifyObservers(k)),H},Y.prototype.removeMorphTargetManager=function(k){var H=this.morphTargetManagers.indexOf(k);return H!==-1&&this.morphTargetManagers.splice(H,1),H},Y.prototype.removeLight=function(k){var H=this.lights.indexOf(k);if(H!==-1){for(var Z=0,W=this.meshes;Z<W.length;Z++)W[Z]._removeLightSource(k,!1);this.lights.splice(H,1),this.sortLightsByPriority(),k.parent||k._removeFromSceneRootNodes()}return this.onLightRemovedObservable.notifyObservers(k),H},Y.prototype.removeCamera=function(k){var H=this.cameras.indexOf(k);if(H!==-1&&(this.cameras.splice(H,1),k.parent||k._removeFromSceneRootNodes()),this.activeCameras){var Z=this.activeCameras.indexOf(k);Z!==-1&&this.activeCameras.splice(Z,1)}return this.activeCamera===k&&(this.cameras.length>0?this.activeCamera=this.cameras[0]:this.activeCamera=null),this.onCameraRemovedObservable.notifyObservers(k),H},Y.prototype.removeParticleSystem=function(k){var H=this.particleSystems.indexOf(k);return H!==-1&&this.particleSystems.splice(H,1),H},Y.prototype.removeAnimation=function(k){var H=this.animations.indexOf(k);return H!==-1&&this.animations.splice(H,1),H},Y.prototype.stopAnimation=function(k,H,Z){},Y.prototype.removeAnimationGroup=function(k){var H=this.animationGroups.indexOf(k);return H!==-1&&this.animationGroups.splice(H,1),H},Y.prototype.removeMultiMaterial=function(k){var H=this.multiMaterials.indexOf(k);return H!==-1&&this.multiMaterials.splice(H,1),this.onMultiMaterialRemovedObservable.notifyObservers(k),H},Y.prototype.removeMaterial=function(k){var H=k._indexInSceneMaterialArray;if(H!==-1&&H<this.materials.length){if(H!==this.materials.length-1){var Z=this.materials[this.materials.length-1];this.materials[H]=Z,Z._indexInSceneMaterialArray=H}k._indexInSceneMaterialArray=-1,this.materials.pop()}return this.onMaterialRemovedObservable.notifyObservers(k),H},Y.prototype.removeActionManager=function(k){var H=this.actionManagers.indexOf(k);return H!==-1&&this.actionManagers.splice(H,1),H},Y.prototype.removeTexture=function(k){var H=this.textures.indexOf(k);return H!==-1&&this.textures.splice(H,1),this.onTextureRemovedObservable.notifyObservers(k),H},Y.prototype.addLight=function(k){if(!this._blockEntityCollection){this.lights.push(k),this.sortLightsByPriority(),k.parent||k._addToSceneRootNodes();for(var H=0,Z=this.meshes;H<Z.length;H++){var W=Z[H];W.lightSources.indexOf(k)===-1&&(W.lightSources.push(k),W._resyncLightSources())}this.onNewLightAddedObservable.notifyObservers(k)}},Y.prototype.sortLightsByPriority=function(){this.requireLightSorting&&this.lights.sort(h.a.CompareLightsPriority)},Y.prototype.addCamera=function(k){this._blockEntityCollection||(this.cameras.push(k),this.onNewCameraAddedObservable.notifyObservers(k),k.parent||k._addToSceneRootNodes())},Y.prototype.addSkeleton=function(k){this._blockEntityCollection||(this.skeletons.push(k),this.onNewSkeletonAddedObservable.notifyObservers(k))},Y.prototype.addParticleSystem=function(k){this._blockEntityCollection||this.particleSystems.push(k)},Y.prototype.addAnimation=function(k){this._blockEntityCollection||this.animations.push(k)},Y.prototype.addAnimationGroup=function(k){this._blockEntityCollection||this.animationGroups.push(k)},Y.prototype.addMultiMaterial=function(k){this._blockEntityCollection||(this.multiMaterials.push(k),this.onNewMultiMaterialAddedObservable.notifyObservers(k))},Y.prototype.addMaterial=function(k){this._blockEntityCollection||(k._indexInSceneMaterialArray=this.materials.length,this.materials.push(k),this.onNewMaterialAddedObservable.notifyObservers(k))},Y.prototype.addMorphTargetManager=function(k){this._blockEntityCollection||this.morphTargetManagers.push(k)},Y.prototype.addGeometry=function(k){this._blockEntityCollection||(this.geometriesByUniqueId&&(this.geometriesByUniqueId[k.uniqueId]=this.geometries.length),this.geometries.push(k))},Y.prototype.addActionManager=function(k){this.actionManagers.push(k)},Y.prototype.addTexture=function(k){this._blockEntityCollection||(this.textures.push(k),this.onNewTextureAddedObservable.notifyObservers(k))},Y.prototype.switchActiveCamera=function(k,H){H===void 0&&(H=!0),this._engine.getInputElement()&&(this.activeCamera&&this.activeCamera.detachControl(),this.activeCamera=k,H&&k.attachControl())},Y.prototype.setActiveCameraByID=function(k){var H=this.getCameraByID(k);return H?(this.activeCamera=H,H):null},Y.prototype.setActiveCameraByName=function(k){var H=this.getCameraByName(k);return H?(this.activeCamera=H,H):null},Y.prototype.getAnimationGroupByName=function(k){for(var H=0;H<this.animationGroups.length;H++)if(this.animationGroups[H].name===k)return this.animationGroups[H];return null},Y.prototype.getMaterialByUniqueID=function(k){for(var H=0;H<this.materials.length;H++)if(this.materials[H].uniqueId===k)return this.materials[H];return null},Y.prototype.getMaterialByID=function(k){for(var H=0;H<this.materials.length;H++)if(this.materials[H].id===k)return this.materials[H];return null},Y.prototype.getLastMaterialByID=function(k){for(var H=this.materials.length-1;H>=0;H--)if(this.materials[H].id===k)return this.materials[H];return null},Y.prototype.getMaterialByName=function(k){for(var H=0;H<this.materials.length;H++)if(this.materials[H].name===k)return this.materials[H];return null},Y.prototype.getTextureByUniqueID=function(k){for(var H=0;H<this.textures.length;H++)if(this.textures[H].uniqueId===k)return this.textures[H];return null},Y.prototype.getCameraByID=function(k){for(var H=0;H<this.cameras.length;H++)if(this.cameras[H].id===k)return this.cameras[H];return null},Y.prototype.getCameraByUniqueID=function(k){for(var H=0;H<this.cameras.length;H++)if(this.cameras[H].uniqueId===k)return this.cameras[H];return null},Y.prototype.getCameraByName=function(k){for(var H=0;H<this.cameras.length;H++)if(this.cameras[H].name===k)return this.cameras[H];return null},Y.prototype.getBoneByID=function(k){for(var H=0;H<this.skeletons.length;H++)for(var Z=this.skeletons[H],W=0;W<Z.bones.length;W++)if(Z.bones[W].id===k)return Z.bones[W];return null},Y.prototype.getBoneByName=function(k){for(var H=0;H<this.skeletons.length;H++)for(var Z=this.skeletons[H],W=0;W<Z.bones.length;W++)if(Z.bones[W].name===k)return Z.bones[W];return null},Y.prototype.getLightByName=function(k){for(var H=0;H<this.lights.length;H++)if(this.lights[H].name===k)return this.lights[H];return null},Y.prototype.getLightByID=function(k){for(var H=0;H<this.lights.length;H++)if(this.lights[H].id===k)return this.lights[H];return null},Y.prototype.getLightByUniqueID=function(k){for(var H=0;H<this.lights.length;H++)if(this.lights[H].uniqueId===k)return this.lights[H];return null},Y.prototype.getParticleSystemByID=function(k){for(var H=0;H<this.particleSystems.length;H++)if(this.particleSystems[H].id===k)return this.particleSystems[H];return null},Y.prototype.getGeometryByID=function(k){for(var H=0;H<this.geometries.length;H++)if(this.geometries[H].id===k)return this.geometries[H];return null},Y.prototype._getGeometryByUniqueID=function(k){if(this.geometriesByUniqueId){var H=this.geometriesByUniqueId[k];if(H!==void 0)return this.geometries[H]}else for(var Z=0;Z<this.geometries.length;Z++)if(this.geometries[Z].uniqueId===k)return this.geometries[Z];return null},Y.prototype.pushGeometry=function(k,H){return!(!H&&this._getGeometryByUniqueID(k.uniqueId))&&(this.addGeometry(k),this.onNewGeometryAddedObservable.notifyObservers(k),!0)},Y.prototype.removeGeometry=function(k){var H;if(this.geometriesByUniqueId){if((H=this.geometriesByUniqueId[k.uniqueId])===void 0)return!1}else if((H=this.geometries.indexOf(k))<0)return!1;if(H!==this.geometries.length-1){var Z=this.geometries[this.geometries.length-1];Z&&(this.geometries[H]=Z,this.geometriesByUniqueId&&(this.geometriesByUniqueId[Z.uniqueId]=H,this.geometriesByUniqueId[k.uniqueId]=void 0))}return this.geometries.pop(),this.onGeometryRemovedObservable.notifyObservers(k),!0},Y.prototype.getGeometries=function(){return this.geometries},Y.prototype.getMeshByID=function(k){for(var H=0;H<this.meshes.length;H++)if(this.meshes[H].id===k)return this.meshes[H];return null},Y.prototype.getMeshesByID=function(k){return this.meshes.filter(function(H){return H.id===k})},Y.prototype.getTransformNodeByID=function(k){for(var H=0;H<this.transformNodes.length;H++)if(this.transformNodes[H].id===k)return this.transformNodes[H];return null},Y.prototype.getTransformNodeByUniqueID=function(k){for(var H=0;H<this.transformNodes.length;H++)if(this.transformNodes[H].uniqueId===k)return this.transformNodes[H];return null},Y.prototype.getTransformNodesByID=function(k){return this.transformNodes.filter(function(H){return H.id===k})},Y.prototype.getMeshByUniqueID=function(k){for(var H=0;H<this.meshes.length;H++)if(this.meshes[H].uniqueId===k)return this.meshes[H];return null},Y.prototype.getLastMeshByID=function(k){for(var H=this.meshes.length-1;H>=0;H--)if(this.meshes[H].id===k)return this.meshes[H];return null},Y.prototype.getLastEntryByID=function(k){var H;for(H=this.meshes.length-1;H>=0;H--)if(this.meshes[H].id===k)return this.meshes[H];for(H=this.transformNodes.length-1;H>=0;H--)if(this.transformNodes[H].id===k)return this.transformNodes[H];for(H=this.cameras.length-1;H>=0;H--)if(this.cameras[H].id===k)return this.cameras[H];for(H=this.lights.length-1;H>=0;H--)if(this.lights[H].id===k)return this.lights[H];return null},Y.prototype.getNodeByID=function(k){var H=this.getMeshByID(k);if(H)return H;var Z=this.getTransformNodeByID(k);if(Z)return Z;var W=this.getLightByID(k);if(W)return W;var q=this.getCameraByID(k);if(q)return q;var he=this.getBoneByID(k);return he||null},Y.prototype.getNodeByName=function(k){var H=this.getMeshByName(k);if(H)return H;var Z=this.getTransformNodeByName(k);if(Z)return Z;var W=this.getLightByName(k);if(W)return W;var q=this.getCameraByName(k);if(q)return q;var he=this.getBoneByName(k);return he||null},Y.prototype.getMeshByName=function(k){for(var H=0;H<this.meshes.length;H++)if(this.meshes[H].name===k)return this.meshes[H];return null},Y.prototype.getTransformNodeByName=function(k){for(var H=0;H<this.transformNodes.length;H++)if(this.transformNodes[H].name===k)return this.transformNodes[H];return null},Y.prototype.getLastSkeletonByID=function(k){for(var H=this.skeletons.length-1;H>=0;H--)if(this.skeletons[H].id===k)return this.skeletons[H];return null},Y.prototype.getSkeletonByUniqueId=function(k){for(var H=0;H<this.skeletons.length;H++)if(this.skeletons[H].uniqueId===k)return this.skeletons[H];return null},Y.prototype.getSkeletonById=function(k){for(var H=0;H<this.skeletons.length;H++)if(this.skeletons[H].id===k)return this.skeletons[H];return null},Y.prototype.getSkeletonByName=function(k){for(var H=0;H<this.skeletons.length;H++)if(this.skeletons[H].name===k)return this.skeletons[H];return null},Y.prototype.getMorphTargetManagerById=function(k){for(var H=0;H<this.morphTargetManagers.length;H++)if(this.morphTargetManagers[H].uniqueId===k)return this.morphTargetManagers[H];return null},Y.prototype.getMorphTargetById=function(k){for(var H=0;H<this.morphTargetManagers.length;++H)for(var Z=this.morphTargetManagers[H],W=0;W<Z.numTargets;++W){var q=Z.getTarget(W);if(q.id===k)return q}return null},Y.prototype.getMorphTargetByName=function(k){for(var H=0;H<this.morphTargetManagers.length;++H)for(var Z=this.morphTargetManagers[H],W=0;W<Z.numTargets;++W){var q=Z.getTarget(W);if(q.name===k)return q}return null},Y.prototype.getPostProcessByName=function(k){for(var H=0;H<this.postProcesses.length;++H){var Z=this.postProcesses[H];if(Z.name===k)return Z}return null},Y.prototype.isActiveMesh=function(k){return this._activeMeshes.indexOf(k)!==-1},Object.defineProperty(Y.prototype,"uid",{get:function(){return this._uid||(this._uid=_.b.RandomId()),this._uid},enumerable:!1,configurable:!0}),Y.prototype.addExternalData=function(k,H){return this._externalData||(this._externalData=new R.a),this._externalData.add(k,H)},Y.prototype.getExternalData=function(k){return this._externalData?this._externalData.get(k):null},Y.prototype.getOrAddExternalDataWithFactory=function(k,H){return this._externalData||(this._externalData=new R.a),this._externalData.getOrAddWithFactory(k,H)},Y.prototype.removeExternalData=function(k){return this._externalData.remove(k)},Y.prototype._evaluateSubMesh=function(k,H,Z){if(Z.hasInstances||Z.isAnInstance||this.dispatchAllSubMeshesOfActiveMeshes||this._skipFrustumClipping||H.alwaysSelectAsActiveMesh||H.subMeshes.length===1||k.isInFrustum(this._frustumPlanes)){for(var W=0,q=this._evaluateSubMeshStage;W<q.length;W++)q[W].action(H,k);var he=k.getMaterial();he!=null&&(he.hasRenderTargetTextures&&he.getRenderTargetTextures!=null&&this._processedMaterials.indexOf(he)===-1&&(this._processedMaterials.push(he),this._renderTargets.concatWithNoDuplicate(he.getRenderTargetTextures())),this._renderingManager.dispatch(k,H,he))}},Y.prototype.freeProcessedMaterials=function(){this._processedMaterials.dispose()},Object.defineProperty(Y.prototype,"blockfreeActiveMeshesAndRenderingGroups",{get:function(){return this._preventFreeActiveMeshesAndRenderingGroups},set:function(k){this._preventFreeActiveMeshesAndRenderingGroups!==k&&(k&&(this.freeActiveMeshes(),this.freeRenderingGroups()),this._preventFreeActiveMeshesAndRenderingGroups=k)},enumerable:!1,configurable:!0}),Y.prototype.freeActiveMeshes=function(){if(!this.blockfreeActiveMeshesAndRenderingGroups&&(this._activeMeshes.dispose(),this.activeCamera&&this.activeCamera._activeMeshes&&this.activeCamera._activeMeshes.dispose(),this.activeCameras))for(var k=0;k<this.activeCameras.length;k++){var H=this.activeCameras[k];H&&H._activeMeshes&&H._activeMeshes.dispose()}},Y.prototype.freeRenderingGroups=function(){if(!this.blockfreeActiveMeshesAndRenderingGroups&&(this._renderingManager&&this._renderingManager.freeRenderingGroups(),this.textures))for(var k=0;k<this.textures.length;k++){var H=this.textures[k];H&&H.renderList&&H.freeRenderingGroups()}},Y.prototype._isInIntermediateRendering=function(){return this._intermediateRendering},Y.prototype.freezeActiveMeshes=function(k,H,Z){var W=this;return k===void 0&&(k=!1),this.executeWhenReady(function(){if(W.activeCamera){W._frustumPlanes||W.setTransformMatrix(W.activeCamera.getViewMatrix(),W.activeCamera.getProjectionMatrix()),W._evaluateActiveMeshes(),W._activeMeshesFrozen=!0,W._skipEvaluateActiveMeshesCompletely=k;for(var q=0;q<W._activeMeshes.length;q++)W._activeMeshes.data[q]._freeze();H&&H()}else Z&&Z("No active camera found")}),this},Y.prototype.unfreezeActiveMeshes=function(){for(var k=0;k<this.meshes.length;k++){var H=this.meshes[k];H._internalAbstractMeshDataInfo&&(H._internalAbstractMeshDataInfo._isActive=!1)}for(k=0;k<this._activeMeshes.length;k++)this._activeMeshes.data[k]._unFreeze();return this._activeMeshesFrozen=!1,this},Y.prototype._evaluateActiveMeshes=function(){if(this._activeMeshesFrozen&&this._activeMeshes.length){if(!this._skipEvaluateActiveMeshesCompletely)for(var k=this._activeMeshes.length,H=0;H<k;H++)(me=this._activeMeshes.data[H]).computeWorldMatrix();if(this._activeParticleSystems){var Z=this._activeParticleSystems.length;for(H=0;H<Z;H++)this._activeParticleSystems.data[H].animate()}}else if(this.activeCamera){this.onBeforeActiveMeshesEvaluationObservable.notifyObservers(this),this.activeCamera._activeMeshes.reset(),this._activeMeshes.reset(),this._renderingManager.reset(),this._processedMaterials.reset(),this._activeParticleSystems.reset(),this._activeSkeletons.reset(),this._softwareSkinnedMeshes.reset();for(var W=0,q=this._beforeEvaluateActiveMeshStage;W<q.length;W++)q[W].action();var he=this.getActiveMeshCandidates(),ge=he.length;for(H=0;H<ge;H++){var me;if((me=he.data[H])._internalAbstractMeshDataInfo._currentLODIsUpToDate=!1,!me.isBlocked&&(this._totalVertices.addCount(me.getTotalVertices(),!1),me.isReady()&&me.isEnabled()&&me.scaling.lengthSquared()!==0)){me.computeWorldMatrix(),me.actionManager&&me.actionManager.hasSpecificTriggers2(I.a.ACTION_OnIntersectionEnterTrigger,I.a.ACTION_OnIntersectionExitTrigger)&&this._meshesForIntersections.pushNoDuplicate(me);var _e=this.customLODSelector?this.customLODSelector(me,this.activeCamera):me.getLOD(this.activeCamera);if(me._internalAbstractMeshDataInfo._currentLOD=_e,me._internalAbstractMeshDataInfo._currentLODIsUpToDate=!0,_e!=null&&(_e!==me&&_e.billboardMode!==c.a.BILLBOARDMODE_NONE&&_e.computeWorldMatrix(),me._preActivate(),me.isVisible&&me.visibility>0&&(me.layerMask&this.activeCamera.layerMask)!=0&&(this._skipFrustumClipping||me.alwaysSelectAsActiveMesh||me.isInFrustum(this._frustumPlanes)))){this._activeMeshes.push(me),this.activeCamera._activeMeshes.push(me),_e!==me&&_e._activate(this._renderId,!1);for(var be=0,Pe=this._preActiveMeshStage;be<Pe.length;be++)Pe[be].action(me);me._activate(this._renderId,!1)&&(me.isAnInstance?me._internalAbstractMeshDataInfo._actAsRegularMesh&&(_e=me):_e._internalAbstractMeshDataInfo._onlyForInstances=!1,_e._internalAbstractMeshDataInfo._isActive=!0,this._activeMesh(me,_e)),me._postActivate()}}}if(this.onAfterActiveMeshesEvaluationObservable.notifyObservers(this),this.particlesEnabled){this.onBeforeParticlesRenderingObservable.notifyObservers(this);for(var ye=0;ye<this.particleSystems.length;ye++){var Be=this.particleSystems[ye];if(Be.isStarted()&&Be.emitter){var ke=Be.emitter;ke.position&&!ke.isEnabled()||(this._activeParticleSystems.push(Be),Be.animate(),this._renderingManager.dispatchParticles(Be))}}this.onAfterParticlesRenderingObservable.notifyObservers(this)}}},Y.prototype._activeMesh=function(k,H){if(this._skeletonsEnabled&&H.skeleton!==null&&H.skeleton!==void 0&&(this._activeSkeletons.pushNoDuplicate(H.skeleton)&&H.skeleton.prepare(),H.computeBonesUsingShaders||this._softwareSkinnedMeshes.pushNoDuplicate(H)),H!=null&&H.subMeshes!==void 0&&H.subMeshes!==null&&H.subMeshes.length>0)for(var Z=this.getActiveSubMeshCandidates(H),W=Z.length,q=0;q<W;q++){var he=Z.data[q];this._evaluateSubMesh(he,H,k)}},Y.prototype.updateTransformMatrix=function(k){this.activeCamera&&this.setTransformMatrix(this.activeCamera.getViewMatrix(),this.activeCamera.getProjectionMatrix(k))},Y.prototype._bindFrameBuffer=function(){if(this.activeCamera&&this.activeCamera._multiviewTexture)this.activeCamera._multiviewTexture._bindFrameBuffer();else if(this.activeCamera&&this.activeCamera.outputRenderTarget)if(this.getEngine().getCaps().multiview&&this.activeCamera.outputRenderTarget&&this.activeCamera.outputRenderTarget.getViewCount()>1)this.activeCamera.outputRenderTarget._bindFrameBuffer();else{var k=this.activeCamera.outputRenderTarget.getInternalTexture();k?this.getEngine().bindFramebuffer(k):X.a.Error("Camera contains invalid customDefaultRenderTarget")}else this.getEngine().restoreDefaultFramebuffer()},Y.prototype._renderForCamera=function(k,H){if(!k||!k._skipRendering){var Z=this._engine;if(this._activeCamera=k,!this.activeCamera)throw new Error("Active camera not set");Z.setViewport(this.activeCamera.viewport),this.resetCachedMaterial(),this._renderId++,this.getEngine().getCaps().multiview&&k.outputRenderTarget&&k.outputRenderTarget.getViewCount()>1?this.setTransformMatrix(k._rigCameras[0].getViewMatrix(),k._rigCameras[0].getProjectionMatrix(),k._rigCameras[1].getViewMatrix(),k._rigCameras[1].getProjectionMatrix()):this.updateTransformMatrix(),this.onBeforeCameraRenderObservable.notifyObservers(this.activeCamera),this._evaluateActiveMeshes();for(var W=0;W<this._softwareSkinnedMeshes.length;W++){var q=this._softwareSkinnedMeshes.data[W];q.applySkeleton(q.skeleton)}this.onBeforeRenderTargetsRenderObservable.notifyObservers(this),k.customRenderTargets&&k.customRenderTargets.length>0&&this._renderTargets.concatWithNoDuplicate(k.customRenderTargets),H&&H.customRenderTargets&&H.customRenderTargets.length>0&&this._renderTargets.concatWithNoDuplicate(H.customRenderTargets);for(var he=0,ge=this._gatherActiveCameraRenderTargetsStage;he<ge.length;he++)ge[he].action(this._renderTargets);var me=!1;if(this.renderTargetsEnabled){if(this._intermediateRendering=!0,this._renderTargets.length>0){_.b.StartPerformanceCounter("Render targets",this._renderTargets.length>0);for(var _e=0;_e<this._renderTargets.length;_e++){var be=this._renderTargets.data[_e];if(be._shouldRender()){this._renderId++;var Pe=be.activeCamera&&be.activeCamera!==this.activeCamera;be.render(Pe,this.dumpNextRenderTargets),me=!0}}_.b.EndPerformanceCounter("Render targets",this._renderTargets.length>0),this._renderId++}for(var ye=0,Be=this._cameraDrawRenderTargetStage;ye<Be.length;ye++)me=Be[ye].action(this.activeCamera)||me;this._intermediateRendering=!1,this.activeCamera&&this.activeCamera.outputRenderTarget&&(me=!0)}me&&!this.prePass&&this._bindFrameBuffer(),this.onAfterRenderTargetsRenderObservable.notifyObservers(this),!this.postProcessManager||k._multiviewTexture||this.prePass||this.postProcessManager._prepareFrame();for(var ke=0,We=this._beforeCameraDrawStage;ke<We.length;ke++)We[ke].action(this.activeCamera);this.onBeforeDrawPhaseObservable.notifyObservers(this),this._renderingManager.render(null,null,!0,!0),this.onAfterDrawPhaseObservable.notifyObservers(this);for(var je=0,He=this._afterCameraDrawStage;je<He.length;je++)He[je].action(this.activeCamera);if(this.postProcessManager&&!k._multiviewTexture){var qe=k.outputRenderTarget?k.outputRenderTarget.getInternalTexture():void 0;this.postProcessManager._finalizeFrame(k.isIntermediate,qe)}this._renderTargets.reset(),this.onAfterCameraRenderObservable.notifyObservers(this.activeCamera)}},Y.prototype._processSubCameras=function(k){if(k.cameraRigMode===A.a.RIG_MODE_NONE||k.outputRenderTarget&&k.outputRenderTarget.getViewCount()>1&&this.getEngine().getCaps().multiview)return this._renderForCamera(k),void this.onAfterRenderCameraObservable.notifyObservers(k);if(k._useMultiviewToSingleView)this._renderMultiviewToSingleView(k);else for(var H=0;H<k._rigCameras.length;H++)this._renderForCamera(k._rigCameras[H],k);this._activeCamera=k,this.setTransformMatrix(this._activeCamera.getViewMatrix(),this._activeCamera.getProjectionMatrix()),this.onAfterRenderCameraObservable.notifyObservers(k)},Y.prototype._checkIntersections=function(){for(var k=0;k<this._meshesForIntersections.length;k++){var H=this._meshesForIntersections.data[k];if(H.actionManager)for(var Z=0;H.actionManager&&Z<H.actionManager.actions.length;Z++){var W=H.actionManager.actions[Z];if(W.trigger===I.a.ACTION_OnIntersectionEnterTrigger||W.trigger===I.a.ACTION_OnIntersectionExitTrigger){var q=W.getTriggerParameter(),he=q instanceof T.a?q:q.mesh,ge=he.intersectsMesh(H,q.usePreciseIntersection),me=H._intersectionsInProgress.indexOf(he);ge&&me===-1?W.trigger===I.a.ACTION_OnIntersectionEnterTrigger?(W._executeCurrent(E.a.CreateNew(H,void 0,he)),H._intersectionsInProgress.push(he)):W.trigger===I.a.ACTION_OnIntersectionExitTrigger&&H._intersectionsInProgress.push(he):!ge&&me>-1&&(W.trigger===I.a.ACTION_OnIntersectionExitTrigger&&W._executeCurrent(E.a.CreateNew(H,void 0,he)),H.actionManager.hasSpecificTrigger(I.a.ACTION_OnIntersectionExitTrigger,function(_e){var be=_e instanceof T.a?_e:_e.mesh;return he===be})&&W.trigger!==I.a.ACTION_OnIntersectionExitTrigger||H._intersectionsInProgress.splice(me,1))}}}},Y.prototype._advancePhysicsEngineStep=function(k){},Y.prototype._animate=function(){},Y.prototype.animate=function(){if(this._engine.isDeterministicLockStep()){var k=Math.max(Y.MinDeltaTime,Math.min(this._engine.getDeltaTime(),Y.MaxDeltaTime))+this._timeAccumulator,H=this._engine.getTimeStep(),Z=1e3/H/1e3,W=0,q=this._engine.getLockstepMaxSteps(),he=Math.floor(k/H);for(he=Math.min(he,q);k>0&&W<he;)this.onBeforeStepObservable.notifyObservers(this),this._animationRatio=H*Z,this._animate(),this.onAfterAnimationsObservable.notifyObservers(this),this.physicsEnabled&&this._advancePhysicsEngineStep(H),this.onAfterStepObservable.notifyObservers(this),this._currentStepId++,W++,k-=H;this._timeAccumulator=k<0?0:k}else k=this.useConstantAnimationDeltaTime?16:Math.max(Y.MinDeltaTime,Math.min(this._engine.getDeltaTime(),Y.MaxDeltaTime)),this._animationRatio=.06*k,this._animate(),this.onAfterAnimationsObservable.notifyObservers(this),this.physicsEnabled&&this._advancePhysicsEngineStep(k)},Y.prototype.render=function(k,H){if(k===void 0&&(k=!0),H===void 0&&(H=!1),!this.isDisposed){this.onReadyObservable.hasObservers()&&this._executeWhenReadyTimeoutId===-1&&this._checkIsReady(),this._frameId++,this._registerTransientComponents(),this._activeParticles.fetchNewFrame(),this._totalVertices.fetchNewFrame(),this._activeIndices.fetchNewFrame(),this._activeBones.fetchNewFrame(),this._meshesForIntersections.reset(),this.resetCachedMaterial(),this.onBeforeAnimationsObservable.notifyObservers(this),this.actionManager&&this.actionManager.processTrigger(I.a.ACTION_OnEveryFrameTrigger),H||this.animate();for(var Z=0,W=this._beforeCameraUpdateStage;Z<W.length;Z++)W[Z].action();if(k){if(this.activeCameras&&this.activeCameras.length>0)for(var q=0;q<this.activeCameras.length;q++){var he=this.activeCameras[q];if(he.update(),he.cameraRigMode!==A.a.RIG_MODE_NONE)for(var ge=0;ge<he._rigCameras.length;ge++)he._rigCameras[ge].update()}else if(this.activeCamera&&(this.activeCamera.update(),this.activeCamera.cameraRigMode!==A.a.RIG_MODE_NONE))for(ge=0;ge<this.activeCamera._rigCameras.length;ge++)this.activeCamera._rigCameras[ge].update()}this.onBeforeRenderObservable.notifyObservers(this),this.onBeforeRenderTargetsRenderObservable.notifyObservers(this);var me=this.getEngine(),_e=this.activeCamera;if(this.renderTargetsEnabled){_.b.StartPerformanceCounter("Custom render targets",this.customRenderTargets.length>0),this._intermediateRendering=!0;for(var be=0;be<this.customRenderTargets.length;be++){var Pe=this.customRenderTargets[be];if(Pe._shouldRender()){if(this._renderId++,this.activeCamera=Pe.activeCamera||this.activeCamera,!this.activeCamera)throw new Error("Active camera not set");me.setViewport(this.activeCamera.viewport),this.updateTransformMatrix(),Pe.render(_e!==this.activeCamera,this.dumpNextRenderTargets)}}_.b.EndPerformanceCounter("Custom render targets",this.customRenderTargets.length>0),this._intermediateRendering=!1,this._renderId++}this.activeCamera=_e,this._activeCamera&&this._activeCamera.cameraRigMode!==A.a.RIG_MODE_CUSTOM&&!this.prePass&&this._bindFrameBuffer(),this.onAfterRenderTargetsRenderObservable.notifyObservers(this);for(var ye=0,Be=this._beforeClearStage;ye<Be.length;ye++)Be[ye].action();!this.autoClearDepthAndStencil&&!this.autoClear||this.prePass||this._engine.clear(this.clearColor,this.autoClear||this.forceWireframe||this.forcePointsCloud,this.autoClearDepthAndStencil,this.autoClearDepthAndStencil);for(var ke=0,We=this._gatherRenderTargetsStage;ke<We.length;ke++)We[ke].action(this._renderTargets);if(this.activeCameras&&this.activeCameras.length>0)for(q=0;q<this.activeCameras.length;q++)q>0&&this._engine.clear(null,!1,!0,!0),this._processSubCameras(this.activeCameras[q]);else{if(!this.activeCamera)throw new Error("No camera defined");this._processSubCameras(this.activeCamera)}this._checkIntersections();for(var je=0,He=this._afterRenderStage;je<He.length;je++)He[je].action();if(this.afterRender&&this.afterRender(),this.onAfterRenderObservable.notifyObservers(this),this._toBeDisposed.length){for(ge=0;ge<this._toBeDisposed.length;ge++){var qe=this._toBeDisposed[ge];qe&&qe.dispose()}this._toBeDisposed=[]}this.dumpNextRenderTargets&&(this.dumpNextRenderTargets=!1),this._activeBones.addCount(0,!0),this._activeIndices.addCount(0,!0),this._activeParticles.addCount(0,!0)}},Y.prototype.freezeMaterials=function(){for(var k=0;k<this.materials.length;k++)this.materials[k].freeze()},Y.prototype.unfreezeMaterials=function(){for(var k=0;k<this.materials.length;k++)this.materials[k].unfreeze()},Y.prototype.dispose=function(){this.beforeRender=null,this.afterRender=null,j.a._LastCreatedScene===this&&(j.a._LastCreatedScene=null),this.skeletons=[],this.morphTargetManagers=[],this._transientComponents=[],this._isReadyForMeshStage.clear(),this._beforeEvaluateActiveMeshStage.clear(),this._evaluateSubMeshStage.clear(),this._preActiveMeshStage.clear(),this._cameraDrawRenderTargetStage.clear(),this._beforeCameraDrawStage.clear(),this._beforeRenderTargetDrawStage.clear(),this._beforeRenderingGroupDrawStage.clear(),this._beforeRenderingMeshStage.clear(),this._afterRenderingMeshStage.clear(),this._afterRenderingGroupDrawStage.clear(),this._afterCameraDrawStage.clear(),this._afterRenderTargetDrawStage.clear(),this._afterRenderStage.clear(),this._beforeCameraUpdateStage.clear(),this._beforeClearStage.clear(),this._gatherRenderTargetsStage.clear(),this._gatherActiveCameraRenderTargetsStage.clear(),this._pointerMoveStage.clear(),this._pointerDownStage.clear(),this._pointerUpStage.clear();for(var k=0,H=this._components;k<H.length;k++)H[k].dispose();this.importedMeshesFiles=new Array,this.stopAllAnimations&&this.stopAllAnimations(),this.resetCachedMaterial(),this.activeCamera&&(this.activeCamera._activeMeshes.dispose(),this.activeCamera=null),this._activeMeshes.dispose(),this._renderingManager.dispose(),this._processedMaterials.dispose(),this._activeParticleSystems.dispose(),this._activeSkeletons.dispose(),this._softwareSkinnedMeshes.dispose(),this._renderTargets.dispose(),this._registeredForLateAnimationBindings.dispose(),this._meshesForIntersections.dispose(),this._toBeDisposed=[];for(var Z=0,W=this._activeRequests;Z<W.length;Z++)W[Z].abort();var q;if(this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear(),this.onBeforeRenderObservable.clear(),this.onAfterRenderObservable.clear(),this.onBeforeRenderTargetsRenderObservable.clear(),this.onAfterRenderTargetsRenderObservable.clear(),this.onAfterStepObservable.clear(),this.onBeforeStepObservable.clear(),this.onBeforeActiveMeshesEvaluationObservable.clear(),this.onAfterActiveMeshesEvaluationObservable.clear(),this.onBeforeParticlesRenderingObservable.clear(),this.onAfterParticlesRenderingObservable.clear(),this.onBeforeDrawPhaseObservable.clear(),this.onAfterDrawPhaseObservable.clear(),this.onBeforeAnimationsObservable.clear(),this.onAfterAnimationsObservable.clear(),this.onDataLoadedObservable.clear(),this.onBeforeRenderingGroupObservable.clear(),this.onAfterRenderingGroupObservable.clear(),this.onMeshImportedObservable.clear(),this.onBeforeCameraRenderObservable.clear(),this.onAfterCameraRenderObservable.clear(),this.onReadyObservable.clear(),this.onNewCameraAddedObservable.clear(),this.onCameraRemovedObservable.clear(),this.onNewLightAddedObservable.clear(),this.onLightRemovedObservable.clear(),this.onNewGeometryAddedObservable.clear(),this.onGeometryRemovedObservable.clear(),this.onNewTransformNodeAddedObservable.clear(),this.onTransformNodeRemovedObservable.clear(),this.onNewMeshAddedObservable.clear(),this.onMeshRemovedObservable.clear(),this.onNewSkeletonAddedObservable.clear(),this.onSkeletonRemovedObservable.clear(),this.onNewMaterialAddedObservable.clear(),this.onNewMultiMaterialAddedObservable.clear(),this.onMaterialRemovedObservable.clear(),this.onMultiMaterialRemovedObservable.clear(),this.onNewTextureAddedObservable.clear(),this.onTextureRemovedObservable.clear(),this.onPrePointerObservable.clear(),this.onPointerObservable.clear(),this.onPreKeyboardObservable.clear(),this.onKeyboardObservable.clear(),this.onActiveCameraChanged.clear(),this.detachControl(),this._engine.getInputElement())for(q=0;q<this.cameras.length;q++)this.cameras[q].detachControl();for(;this.animationGroups.length;)this.animationGroups[0].dispose();for(;this.lights.length;)this.lights[0].dispose();for(;this.meshes.length;)this.meshes[0].dispose(!0);for(;this.transformNodes.length;)this.transformNodes[0].dispose(!0);for(;this.cameras.length;)this.cameras[0].dispose();for(this._defaultMaterial&&this._defaultMaterial.dispose();this.multiMaterials.length;)this.multiMaterials[0].dispose();for(;this.materials.length;)this.materials[0].dispose();for(;this.particleSystems.length;)this.particleSystems[0].dispose();for(;this.postProcesses.length;)this.postProcesses[0].dispose();for(;this.textures.length;)this.textures[0].dispose();this._sceneUbo.dispose(),this._multiviewSceneUbo&&this._multiviewSceneUbo.dispose(),this.postProcessManager.dispose(),(q=this._engine.scenes.indexOf(this))>-1&&this._engine.scenes.splice(q,1),this._engine.wipeCaches(!0),this._isDisposed=!0},Object.defineProperty(Y.prototype,"isDisposed",{get:function(){return this._isDisposed},enumerable:!1,configurable:!0}),Y.prototype.clearCachedVertexData=function(){for(var k=0;k<this.meshes.length;k++){var H=this.meshes[k].geometry;if(H)for(var Z in H._indices=[],H._vertexBuffers)H._vertexBuffers.hasOwnProperty(Z)&&(H._vertexBuffers[Z]._buffer._data=null)}},Y.prototype.cleanCachedTextureBuffer=function(){for(var k=0,H=this.textures;k<H.length;k++){var Z=H[k];Z._buffer&&(Z._buffer=null)}},Y.prototype.getWorldExtends=function(k){var H=new m.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),Z=new m.e(-Number.MAX_VALUE,-Number.MAX_VALUE,-Number.MAX_VALUE);return k=k||function(){return!0},this.meshes.filter(k).forEach(function(W){if(W.computeWorldMatrix(!0),W.subMeshes&&W.subMeshes.length!==0&&!W.infiniteDistance){var q=W.getBoundingInfo(),he=q.boundingBox.minimumWorld,ge=q.boundingBox.maximumWorld;m.e.CheckExtends(he,H,Z),m.e.CheckExtends(ge,H,Z)}}),{min:H,max:Z}},Y.prototype.createPickingRay=function(k,H,Z,W,q){throw ne.a.WarnImport("Ray")},Y.prototype.createPickingRayToRef=function(k,H,Z,W,q,he){throw ne.a.WarnImport("Ray")},Y.prototype.createPickingRayInCameraSpace=function(k,H,Z){throw ne.a.WarnImport("Ray")},Y.prototype.createPickingRayInCameraSpaceToRef=function(k,H,Z,W){throw ne.a.WarnImport("Ray")},Y.prototype.pick=function(k,H,Z,W,q,he){var ge=new v.a;return ge._pickingUnavailable=!0,ge},Y.prototype.pickWithBoundingInfo=function(k,H,Z,W,q){var he=new v.a;return he._pickingUnavailable=!0,he},Y.prototype.pickWithRay=function(k,H,Z,W){throw ne.a.WarnImport("Ray")},Y.prototype.multiPick=function(k,H,Z,W,q){throw ne.a.WarnImport("Ray")},Y.prototype.multiPickWithRay=function(k,H,Z){throw ne.a.WarnImport("Ray")},Y.prototype.setPointerOverMesh=function(k,H){this._inputManager.setPointerOverMesh(k,H)},Y.prototype.getPointerOverMesh=function(){return this._inputManager.getPointerOverMesh()},Y.prototype._rebuildGeometries=function(){for(var k=0,H=this.geometries;k<H.length;k++)H[k]._rebuild();for(var Z=0,W=this.meshes;Z<W.length;Z++)W[Z]._rebuild();this.postProcessManager&&this.postProcessManager._rebuild();for(var q=0,he=this._components;q<he.length;q++)he[q].rebuild();for(var ge=0,me=this.particleSystems;ge<me.length;ge++)me[ge].rebuild()},Y.prototype._rebuildTextures=function(){for(var k=0,H=this.textures;k<H.length;k++)H[k]._rebuild();this.markAllMaterialsAsDirty(I.a.MATERIAL_TextureDirtyFlag)},Y.prototype._getByTags=function(k,H,Z){if(H===void 0)return k;var W=[];for(var q in Z=Z||function(ge){},k){var he=k[q];C.a&&C.a.MatchesQuery(he,H)&&(W.push(he),Z(he))}return W},Y.prototype.getMeshesByTags=function(k,H){return this._getByTags(this.meshes,k,H)},Y.prototype.getCamerasByTags=function(k,H){return this._getByTags(this.cameras,k,H)},Y.prototype.getLightsByTags=function(k,H){return this._getByTags(this.lights,k,H)},Y.prototype.getMaterialByTags=function(k,H){return this._getByTags(this.materials,k,H).concat(this._getByTags(this.multiMaterials,k,H))},Y.prototype.getTransformNodesByTags=function(k,H){return this._getByTags(this.transformNodes,k,H)},Y.prototype.setRenderingOrder=function(k,H,Z,W){H===void 0&&(H=null),Z===void 0&&(Z=null),W===void 0&&(W=null),this._renderingManager.setRenderingOrder(k,H,Z,W)},Y.prototype.setRenderingAutoClearDepthStencil=function(k,H,Z,W){Z===void 0&&(Z=!0),W===void 0&&(W=!0),this._renderingManager.setRenderingAutoClearDepthStencil(k,H,Z,W)},Y.prototype.getAutoClearDepthStencilSetup=function(k){return this._renderingManager.getAutoClearDepthStencilSetup(k)},Object.defineProperty(Y.prototype,"blockMaterialDirtyMechanism",{get:function(){return this._blockMaterialDirtyMechanism},set:function(k){this._blockMaterialDirtyMechanism!==k&&(this._blockMaterialDirtyMechanism=k,k||this.markAllMaterialsAsDirty(I.a.MATERIAL_AllDirtyFlag))},enumerable:!1,configurable:!0}),Y.prototype.markAllMaterialsAsDirty=function(k,H){if(!this._blockMaterialDirtyMechanism)for(var Z=0,W=this.materials;Z<W.length;Z++){var q=W[Z];H&&!H(q)||q.markAsDirty(k)}},Y.prototype._loadFile=function(k,H,Z,W,q,he){var ge=this,me=Q.a.LoadFile(k,H,Z,W?this.offlineProvider:void 0,q,he);return this._activeRequests.push(me),me.onCompleteObservable.add(function(_e){ge._activeRequests.splice(ge._activeRequests.indexOf(_e),1)}),me},Y.prototype._loadFileAsync=function(k,H,Z,W){var q=this;return new Promise(function(he,ge){q._loadFile(k,function(me){he(me)},H,Z,W,function(me,_e){ge(_e)})})},Y.prototype._requestFile=function(k,H,Z,W,q,he,ge){var me=this,_e=Q.a.RequestFile(k,H,Z,W?this.offlineProvider:void 0,q,he,ge);return this._activeRequests.push(_e),_e.onCompleteObservable.add(function(be){me._activeRequests.splice(me._activeRequests.indexOf(be),1)}),_e},Y.prototype._requestFileAsync=function(k,H,Z,W,q){var he=this;return new Promise(function(ge,me){he._requestFile(k,function(_e){ge(_e)},H,Z,W,function(_e){me(_e)},q)})},Y.prototype._readFile=function(k,H,Z,W,q){var he=this,ge=Q.a.ReadFile(k,H,Z,W,q);return this._activeRequests.push(ge),ge.onCompleteObservable.add(function(me){he._activeRequests.splice(he._activeRequests.indexOf(me),1)}),ge},Y.prototype._readFileAsync=function(k,H,Z){var W=this;return new Promise(function(q,he){W._readFile(k,function(ge){q(ge)},H,Z,function(ge){he(ge)})})},Y.FOGMODE_NONE=0,Y.FOGMODE_EXP=1,Y.FOGMODE_EXP2=2,Y.FOGMODE_LINEAR=3,Y.MinDeltaTime=1,Y.MaxDeltaTime=1e3,Y}(S.a)},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.WarnImport=function(x){return x+" needs to be imported before as it contains a side-effect required by your code."},_}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return Object.defineProperty(_,"LastCreatedEngine",{get:function(){return this.Instances.length===0?null:this.Instances[this.Instances.length-1]},enumerable:!1,configurable:!0}),Object.defineProperty(_,"LastCreatedScene",{get:function(){return this._LastCreatedScene},enumerable:!1,configurable:!0}),_.Instances=new Array,_._LastCreatedScene=null,_.UseFallbackTexture=!0,_.FallbackTexture="",_}()},function(Me,y,f){f.d(y,"c",function(){return U}),f.d(y,"a",function(){return u}),f.d(y,"b",function(){return x});var U,_=f(0);(function(M){M[M.LOCAL=0]="LOCAL",M[M.WORLD=1]="WORLD",M[M.BONE=2]="BONE"})(U||(U={}));var x,u=function(){function M(){}return M.X=new _.e(1,0,0),M.Y=new _.e(0,1,0),M.Z=new _.e(0,0,1),M}();(function(M){M[M.X=0]="X",M[M.Y=1]="Y",M[M.Z=2]="Z"})(x||(x={}))},function(Me,y,f){f.d(y,"a",function(){return g});var U=f(1),_=f(3),x=f(33),u=f(12),M=f(6),R=f(0),C=f(29),m=f(8),c=f(11),T=f(21),A=f(58),S=f(90),g=function(l){function h(v,E,D,w){w===void 0&&(w=!0);var N=l.call(this,v,D)||this;return N._position=R.e.Zero(),N._upVector=R.e.Up(),N.orthoLeft=null,N.orthoRight=null,N.orthoBottom=null,N.orthoTop=null,N.fov=.8,N.minZ=1,N.maxZ=1e4,N.inertia=.9,N.mode=h.PERSPECTIVE_CAMERA,N.isIntermediate=!1,N.viewport=new A.a(0,0,1,1),N.layerMask=268435455,N.fovMode=h.FOVMODE_VERTICAL_FIXED,N.cameraRigMode=h.RIG_MODE_NONE,N.customRenderTargets=new Array,N.outputRenderTarget=null,N.onViewMatrixChangedObservable=new M.c,N.onProjectionMatrixChangedObservable=new M.c,N.onAfterCheckInputsObservable=new M.c,N.onRestoreStateObservable=new M.c,N.isRigCamera=!1,N._rigCameras=new Array,N._webvrViewMatrix=R.a.Identity(),N._skipRendering=!1,N._projectionMatrix=new R.a,N._postProcesses=new Array,N._activeMeshes=new x.a(256),N._globalPosition=R.e.Zero(),N._computedViewMatrix=R.a.Identity(),N._doNotComputeProjectionMatrix=!1,N._transformMatrix=R.a.Zero(),N._refreshFrustumPlanes=!0,N._isCamera=!0,N._isLeftCamera=!1,N._isRightCamera=!1,N.getScene().addCamera(N),w&&!N.getScene().activeCamera&&(N.getScene().activeCamera=N),N.position=E,N}return Object(U.d)(h,l),Object.defineProperty(h.prototype,"position",{get:function(){return this._position},set:function(v){this._position=v},enumerable:!1,configurable:!0}),Object.defineProperty(h.prototype,"upVector",{get:function(){return this._upVector},set:function(v){this._upVector=v},enumerable:!1,configurable:!0}),h.prototype.storeState=function(){return this._stateStored=!0,this._storedFov=this.fov,this},h.prototype._restoreStateValues=function(){return!!this._stateStored&&(this.fov=this._storedFov,!0)},h.prototype.restoreState=function(){return!!this._restoreStateValues()&&(this.onRestoreStateObservable.notifyObservers(this),!0)},h.prototype.getClassName=function(){return"Camera"},h.prototype.toString=function(v){var E="Name: "+this.name;if(E+=", type: "+this.getClassName(),this.animations)for(var D=0;D<this.animations.length;D++)E+=", animation[0]: "+this.animations[D].toString(v);return E},Object.defineProperty(h.prototype,"globalPosition",{get:function(){return this._globalPosition},enumerable:!1,configurable:!0}),h.prototype.getActiveMeshes=function(){return this._activeMeshes},h.prototype.isActiveMesh=function(v){return this._activeMeshes.indexOf(v)!==-1},h.prototype.isReady=function(v){if(v===void 0&&(v=!1),v)for(var E=0,D=this._postProcesses;E<D.length;E++){var w=D[E];if(w&&!w.isReady())return!1}return l.prototype.isReady.call(this,v)},h.prototype._initCache=function(){l.prototype._initCache.call(this),this._cache.position=new R.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),this._cache.upVector=new R.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),this._cache.mode=void 0,this._cache.minZ=void 0,this._cache.maxZ=void 0,this._cache.fov=void 0,this._cache.fovMode=void 0,this._cache.aspectRatio=void 0,this._cache.orthoLeft=void 0,this._cache.orthoRight=void 0,this._cache.orthoBottom=void 0,this._cache.orthoTop=void 0,this._cache.renderWidth=void 0,this._cache.renderHeight=void 0},h.prototype._updateCache=function(v){v||l.prototype._updateCache.call(this),this._cache.position.copyFrom(this.position),this._cache.upVector.copyFrom(this.upVector)},h.prototype._isSynchronized=function(){return this._isSynchronizedViewMatrix()&&this._isSynchronizedProjectionMatrix()},h.prototype._isSynchronizedViewMatrix=function(){return!!l.prototype._isSynchronized.call(this)&&this._cache.position.equals(this.position)&&this._cache.upVector.equals(this.upVector)&&this.isSynchronizedWithParent()},h.prototype._isSynchronizedProjectionMatrix=function(){var v=this._cache.mode===this.mode&&this._cache.minZ===this.minZ&&this._cache.maxZ===this.maxZ;if(!v)return!1;var E=this.getEngine();return v=this.mode===h.PERSPECTIVE_CAMERA?this._cache.fov===this.fov&&this._cache.fovMode===this.fovMode&&this._cache.aspectRatio===E.getAspectRatio(this):this._cache.orthoLeft===this.orthoLeft&&this._cache.orthoRight===this.orthoRight&&this._cache.orthoBottom===this.orthoBottom&&this._cache.orthoTop===this.orthoTop&&this._cache.renderWidth===E.getRenderWidth()&&this._cache.renderHeight===E.getRenderHeight()},h.prototype.attachControl=function(v,E){},h.prototype.detachControl=function(v){},h.prototype.update=function(){this._checkInputs(),this.cameraRigMode!==h.RIG_MODE_NONE&&this._updateRigCameras()},h.prototype._checkInputs=function(){this.onAfterCheckInputsObservable.notifyObservers(this)},Object.defineProperty(h.prototype,"rigCameras",{get:function(){return this._rigCameras},enumerable:!1,configurable:!0}),Object.defineProperty(h.prototype,"rigPostProcess",{get:function(){return this._rigPostProcess},enumerable:!1,configurable:!0}),h.prototype._getFirstPostProcess=function(){for(var v=0;v<this._postProcesses.length;v++)if(this._postProcesses[v]!==null)return this._postProcesses[v];return null},h.prototype._cascadePostProcessesToRigCams=function(){var v=this._getFirstPostProcess();v&&v.markTextureDirty();for(var E=0,D=this._rigCameras.length;E<D;E++){var w=this._rigCameras[E],N=w._rigPostProcess;N?(N.getEffectName()==="pass"&&(w.isIntermediate=this._postProcesses.length===0),w._postProcesses=this._postProcesses.slice(0).concat(N),N.markTextureDirty()):w._postProcesses=this._postProcesses.slice(0)}},h.prototype.attachPostProcess=function(v,E){return E===void 0&&(E=null),!v.isReusable()&&this._postProcesses.indexOf(v)>-1?(m.a.Error("You're trying to reuse a post process not defined as reusable."),0):(E==null||E<0?this._postProcesses.push(v):this._postProcesses[E]===null?this._postProcesses[E]=v:this._postProcesses.splice(E,0,v),this._cascadePostProcessesToRigCams(),this._scene.prePassRenderer&&this._scene.prePassRenderer.markAsDirty(),this._postProcesses.indexOf(v))},h.prototype.detachPostProcess=function(v){var E=this._postProcesses.indexOf(v);E!==-1&&(this._postProcesses[E]=null),this._scene.prePassRenderer&&this._scene.prePassRenderer.markAsDirty(),this._cascadePostProcessesToRigCams()},h.prototype.getWorldMatrix=function(){return this._isSynchronizedViewMatrix()||this.getViewMatrix(),this._worldMatrix},h.prototype._getViewMatrix=function(){return R.a.Identity()},h.prototype.getViewMatrix=function(v){return!v&&this._isSynchronizedViewMatrix()||(this.updateCache(),this._computedViewMatrix=this._getViewMatrix(),this._currentRenderId=this.getScene().getRenderId(),this._childUpdateId++,this._refreshFrustumPlanes=!0,this._cameraRigParams&&this._cameraRigParams.vrPreViewMatrix&&this._computedViewMatrix.multiplyToRef(this._cameraRigParams.vrPreViewMatrix,this._computedViewMatrix),this.parent&&this.parent.onViewMatrixChangedObservable&&this.parent.onViewMatrixChangedObservable.notifyObservers(this.parent),this.onViewMatrixChangedObservable.notifyObservers(this),this._computedViewMatrix.invertToRef(this._worldMatrix)),this._computedViewMatrix},h.prototype.freezeProjectionMatrix=function(v){this._doNotComputeProjectionMatrix=!0,v!==void 0&&(this._projectionMatrix=v)},h.prototype.unfreezeProjectionMatrix=function(){this._doNotComputeProjectionMatrix=!1},h.prototype.getProjectionMatrix=function(v){var E,D,w,N,I,V,X,j;if(this._doNotComputeProjectionMatrix||!v&&this._isSynchronizedProjectionMatrix())return this._projectionMatrix;this._cache.mode=this.mode,this._cache.minZ=this.minZ,this._cache.maxZ=this.maxZ,this._refreshFrustumPlanes=!0;var ne=this.getEngine(),te=this.getScene();if(this.mode===h.PERSPECTIVE_CAMERA){this._cache.fov=this.fov,this._cache.fovMode=this.fovMode,this._cache.aspectRatio=ne.getAspectRatio(this),this.minZ<=0&&(this.minZ=.1);var de=ne.useReverseDepthBuffer;(te.useRightHandedSystem?de?R.a.PerspectiveFovReverseRHToRef:R.a.PerspectiveFovRHToRef:de?R.a.PerspectiveFovReverseLHToRef:R.a.PerspectiveFovLHToRef)(this.fov,ne.getAspectRatio(this),this.minZ,this.maxZ,this._projectionMatrix,this.fovMode===h.FOVMODE_VERTICAL_FIXED)}else{var pe=ne.getRenderWidth()/2,ae=ne.getRenderHeight()/2;te.useRightHandedSystem?R.a.OrthoOffCenterRHToRef((E=this.orthoLeft)!==null&&E!==void 0?E:-pe,(D=this.orthoRight)!==null&&D!==void 0?D:pe,(w=this.orthoBottom)!==null&&w!==void 0?w:-ae,(N=this.orthoTop)!==null&&N!==void 0?N:ae,this.minZ,this.maxZ,this._projectionMatrix):R.a.OrthoOffCenterLHToRef((I=this.orthoLeft)!==null&&I!==void 0?I:-pe,(V=this.orthoRight)!==null&&V!==void 0?V:pe,(X=this.orthoBottom)!==null&&X!==void 0?X:-ae,(j=this.orthoTop)!==null&&j!==void 0?j:ae,this.minZ,this.maxZ,this._projectionMatrix),this._cache.orthoLeft=this.orthoLeft,this._cache.orthoRight=this.orthoRight,this._cache.orthoBottom=this.orthoBottom,this._cache.orthoTop=this.orthoTop,this._cache.renderWidth=ne.getRenderWidth(),this._cache.renderHeight=ne.getRenderHeight()}return this.onProjectionMatrixChangedObservable.notifyObservers(this),this._projectionMatrix},h.prototype.getTransformationMatrix=function(){return this._computedViewMatrix.multiplyToRef(this._projectionMatrix,this._transformMatrix),this._transformMatrix},h.prototype._updateFrustumPlanes=function(){this._refreshFrustumPlanes&&(this.getTransformationMatrix(),this._frustumPlanes?S.a.GetPlanesToRef(this._transformMatrix,this._frustumPlanes):this._frustumPlanes=S.a.GetPlanes(this._transformMatrix),this._refreshFrustumPlanes=!1)},h.prototype.isInFrustum=function(v,E){if(E===void 0&&(E=!1),this._updateFrustumPlanes(),E&&this.rigCameras.length>0){var D=!1;return this.rigCameras.forEach(function(w){w._updateFrustumPlanes(),D=D||v.isInFrustum(w._frustumPlanes)}),D}return v.isInFrustum(this._frustumPlanes)},h.prototype.isCompletelyInFrustum=function(v){return this._updateFrustumPlanes(),v.isCompletelyInFrustum(this._frustumPlanes)},h.prototype.getForwardRay=function(v,E,D){throw T.a.WarnImport("Ray")},h.prototype.getForwardRayToRef=function(v,E,D,w){throw T.a.WarnImport("Ray")},h.prototype.dispose=function(v,E){for(E===void 0&&(E=!1),this.onViewMatrixChangedObservable.clear(),this.onProjectionMatrixChangedObservable.clear(),this.onAfterCheckInputsObservable.clear(),this.onRestoreStateObservable.clear(),this.inputs&&this.inputs.clear(),this.getScene().stopAnimation(this),this.getScene().removeCamera(this);this._rigCameras.length>0;){var D=this._rigCameras.pop();D&&D.dispose()}if(this._rigPostProcess)this._rigPostProcess.dispose(this),this._rigPostProcess=null,this._postProcesses=[];else if(this.cameraRigMode!==h.RIG_MODE_NONE)this._rigPostProcess=null,this._postProcesses=[];else for(var w=this._postProcesses.length;--w>=0;){var N=this._postProcesses[w];N&&N.dispose(this)}for(w=this.customRenderTargets.length;--w>=0;)this.customRenderTargets[w].dispose();this.customRenderTargets=[],this._activeMeshes.dispose(),l.prototype.dispose.call(this,v,E)},Object.defineProperty(h.prototype,"isLeftCamera",{get:function(){return this._isLeftCamera},enumerable:!1,configurable:!0}),Object.defineProperty(h.prototype,"isRightCamera",{get:function(){return this._isRightCamera},enumerable:!1,configurable:!0}),Object.defineProperty(h.prototype,"leftCamera",{get:function(){return this._rigCameras.length<1?null:this._rigCameras[0]},enumerable:!1,configurable:!0}),Object.defineProperty(h.prototype,"rightCamera",{get:function(){return this._rigCameras.length<2?null:this._rigCameras[1]},enumerable:!1,configurable:!0}),h.prototype.getLeftTarget=function(){return this._rigCameras.length<1?null:this._rigCameras[0].getTarget()},h.prototype.getRightTarget=function(){return this._rigCameras.length<2?null:this._rigCameras[1].getTarget()},h.prototype.setCameraRigMode=function(v,E){if(this.cameraRigMode!==v){for(;this._rigCameras.length>0;){var D=this._rigCameras.pop();D&&D.dispose()}if(this.cameraRigMode=v,this._cameraRigParams={},this._cameraRigParams.interaxialDistance=E.interaxialDistance||.0637,this._cameraRigParams.stereoHalfAngle=u.b.ToRadians(this._cameraRigParams.interaxialDistance/.0637),this.cameraRigMode!==h.RIG_MODE_NONE){var w=this.createRigCamera(this.name+"_L",0);w&&(w._isLeftCamera=!0);var N=this.createRigCamera(this.name+"_R",1);N&&(N._isRightCamera=!0),w&&N&&(this._rigCameras.push(w),this._rigCameras.push(N))}switch(this.cameraRigMode){case h.RIG_MODE_STEREOSCOPIC_ANAGLYPH:h._setStereoscopicAnaglyphRigMode(this);break;case h.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL:case h.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_CROSSEYED:case h.RIG_MODE_STEREOSCOPIC_OVERUNDER:case h.RIG_MODE_STEREOSCOPIC_INTERLACED:h._setStereoscopicRigMode(this);break;case h.RIG_MODE_VR:h._setVRRigMode(this,E);break;case h.RIG_MODE_WEBVR:h._setWebVRRigMode(this,E)}this._cascadePostProcessesToRigCams(),this.update()}},h._setStereoscopicRigMode=function(v){throw"Import Cameras/RigModes/stereoscopicRigMode before using stereoscopic rig mode"},h._setStereoscopicAnaglyphRigMode=function(v){throw"Import Cameras/RigModes/stereoscopicAnaglyphRigMode before using stereoscopic anaglyph rig mode"},h._setVRRigMode=function(v,E){throw"Import Cameras/RigModes/vrRigMode before using VR rig mode"},h._setWebVRRigMode=function(v,E){throw"Import Cameras/RigModes/WebVRRigMode before using Web VR rig mode"},h.prototype._getVRProjectionMatrix=function(){return R.a.PerspectiveFovLHToRef(this._cameraRigParams.vrMetrics.aspectRatioFov,this._cameraRigParams.vrMetrics.aspectRatio,this.minZ,this.maxZ,this._cameraRigParams.vrWorkMatrix),this._cameraRigParams.vrWorkMatrix.multiplyToRef(this._cameraRigParams.vrHMatrix,this._projectionMatrix),this._projectionMatrix},h.prototype._updateCameraRotationMatrix=function(){},h.prototype._updateWebVRCameraRotationMatrix=function(){},h.prototype._getWebVRProjectionMatrix=function(){return R.a.Identity()},h.prototype._getWebVRViewMatrix=function(){return R.a.Identity()},h.prototype.setCameraRigParameter=function(v,E){this._cameraRigParams||(this._cameraRigParams={}),this._cameraRigParams[v]=E,v==="interaxialDistance"&&(this._cameraRigParams.stereoHalfAngle=u.b.ToRadians(E/.0637))},h.prototype.createRigCamera=function(v,E){return null},h.prototype._updateRigCameras=function(){for(var v=0;v<this._rigCameras.length;v++)this._rigCameras[v].minZ=this.minZ,this._rigCameras[v].maxZ=this.maxZ,this._rigCameras[v].fov=this.fov,this._rigCameras[v].upVector.copyFrom(this.upVector);this.cameraRigMode===h.RIG_MODE_STEREOSCOPIC_ANAGLYPH&&(this._rigCameras[0].viewport=this._rigCameras[1].viewport=this.viewport)},h.prototype._setupInputs=function(){},h.prototype.serialize=function(){var v=_.a.Serialize(this);return v.type=this.getClassName(),this.parent&&(v.parentId=this.parent.id),this.inputs&&this.inputs.serialize(v),_.a.AppendSerializedAnimations(this,v),v.ranges=this.serializeAnimationRanges(),v},h.prototype.clone=function(v){return _.a.Clone(h.GetConstructorFromName(this.getClassName(),v,this.getScene(),this.interaxialDistance,this.isStereoscopicSideBySide),this)},h.prototype.getDirection=function(v){var E=R.e.Zero();return this.getDirectionToRef(v,E),E},Object.defineProperty(h.prototype,"absoluteRotation",{get:function(){var v=R.b.Zero();return this.getWorldMatrix().decompose(void 0,v),v},enumerable:!1,configurable:!0}),h.prototype.getDirectionToRef=function(v,E){R.e.TransformNormalToRef(v,this.getWorldMatrix(),E)},h.GetConstructorFromName=function(v,E,D,w,N){w===void 0&&(w=0),N===void 0&&(N=!0);var I=C.a.Construct(v,E,D,{interaxial_distance:w,isStereoscopicSideBySide:N});return I||function(){return h._createDefaultParsedCamera(E,D)}},h.prototype.computeWorldMatrix=function(){return this.getWorldMatrix()},h.Parse=function(v,E){var D=v.type,w=h.GetConstructorFromName(D,v.name,E,v.interaxial_distance,v.isStereoscopicSideBySide),N=_.a.Parse(w,v,E);if(v.parentId&&(N._waitingParentId=v.parentId),N.inputs&&(N.inputs.parse(v),N._setupInputs()),v.upVector&&(N.upVector=R.e.FromArray(v.upVector)),N.setPosition&&(N.position.copyFromFloats(0,0,0),N.setPosition(R.e.FromArray(v.position))),v.target&&N.setTarget&&N.setTarget(R.e.FromArray(v.target)),v.cameraRigMode){var I=v.interaxial_distance?{interaxialDistance:v.interaxial_distance}:{};N.setCameraRigMode(v.cameraRigMode,I)}if(v.animations){for(var V=0;V<v.animations.length;V++){var X=v.animations[V],j=c.a.GetClass("BABYLON.Animation");j&&N.animations.push(j.Parse(X))}C.a.ParseAnimationRanges(N,v,E)}return v.autoAnimate&&E.beginAnimation(N,v.autoAnimateFrom,v.autoAnimateTo,v.autoAnimateLoop,v.autoAnimateSpeed||1),N},h._createDefaultParsedCamera=function(v,E){throw T.a.WarnImport("UniversalCamera")},h.PERSPECTIVE_CAMERA=0,h.ORTHOGRAPHIC_CAMERA=1,h.FOVMODE_VERTICAL_FIXED=0,h.FOVMODE_HORIZONTAL_FIXED=1,h.RIG_MODE_NONE=0,h.RIG_MODE_STEREOSCOPIC_ANAGLYPH=10,h.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL=11,h.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_CROSSEYED=12,h.RIG_MODE_STEREOSCOPIC_OVERUNDER=13,h.RIG_MODE_STEREOSCOPIC_INTERLACED=14,h.RIG_MODE_VR=20,h.RIG_MODE_WEBVR=21,h.RIG_MODE_CUSTOM=22,h.ForceAttachControlToAlwaysPreventDefault=!1,Object(U.c)([Object(_.o)("position")],h.prototype,"_position",void 0),Object(U.c)([Object(_.o)("upVector")],h.prototype,"_upVector",void 0),Object(U.c)([Object(_.c)()],h.prototype,"orthoLeft",void 0),Object(U.c)([Object(_.c)()],h.prototype,"orthoRight",void 0),Object(U.c)([Object(_.c)()],h.prototype,"orthoBottom",void 0),Object(U.c)([Object(_.c)()],h.prototype,"orthoTop",void 0),Object(U.c)([Object(_.c)()],h.prototype,"fov",void 0),Object(U.c)([Object(_.c)()],h.prototype,"minZ",void 0),Object(U.c)([Object(_.c)()],h.prototype,"maxZ",void 0),Object(U.c)([Object(_.c)()],h.prototype,"inertia",void 0),Object(U.c)([Object(_.c)()],h.prototype,"mode",void 0),Object(U.c)([Object(_.c)()],h.prototype,"layerMask",void 0),Object(U.c)([Object(_.c)()],h.prototype,"fovMode",void 0),Object(U.c)([Object(_.c)()],h.prototype,"cameraRigMode",void 0),Object(U.c)([Object(_.c)()],h.prototype,"interaxialDistance",void 0),Object(U.c)([Object(_.c)()],h.prototype,"isStereoscopicSideBySide",void 0),h}(C.a)},function(Me,y,f){f.d(y,"a",function(){return A});var U=f(1),_=f(3),x=f(12),u=f(6),M=f(22),R=f(61),C=f(85),m=f(2),c=f(8),T=f(64),A=function(){function S(g,l,h){this.shadowDepthWrapper=null,this.allowShaderHotSwapping=!0,this.metadata=null,this.reservedDataStore=null,this.checkReadyOnEveryCall=!1,this.checkReadyOnlyOnce=!1,this.state="",this._alpha=1,this._backFaceCulling=!0,this.onCompiled=null,this.onError=null,this.getRenderTargetTextures=null,this.doNotSerialize=!1,this._storeEffectOnSubMeshes=!1,this.animations=null,this.onDisposeObservable=new u.c,this._onDisposeObserver=null,this._onUnBindObservable=null,this._onBindObserver=null,this._alphaMode=m.a.ALPHA_COMBINE,this._needDepthPrePass=!1,this.disableDepthWrite=!1,this.disableColorWrite=!1,this.forceDepthWrite=!1,this.depthFunction=0,this.separateCullingPass=!1,this._fogEnabled=!0,this.pointSize=1,this.zOffset=0,this._effect=null,this._useUBO=!1,this._fillMode=S.TriangleFillMode,this._cachedDepthWriteState=!1,this._cachedColorWriteState=!1,this._cachedDepthFunctionState=0,this._indexInSceneMaterialArray=-1,this.meshMap=null,this._forceAlphaTest=!1,this._transparencyMode=null,this.name=g;var v=1;for(this._scene=l||M.a.LastCreatedScene,this.id=g||x.b.RandomId();this._scene.getMaterialByID(this.id);)this.id=g+" "+v++;this.uniqueId=this._scene.getUniqueId(),this._scene.useRightHandedSystem?this.sideOrientation=S.ClockWiseSideOrientation:this.sideOrientation=S.CounterClockWiseSideOrientation,this._uniformBuffer=new C.a(this._scene.getEngine()),this._useUBO=this.getScene().getEngine().supportsUniformBuffers,h||this._scene.addMaterial(this),this._scene.useMaterialMeshMap&&(this.meshMap={})}return Object.defineProperty(S.prototype,"canRenderToMRT",{get:function(){return!1},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"alpha",{get:function(){return this._alpha},set:function(g){this._alpha!==g&&(this._alpha=g,this.markAsDirty(S.MiscDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"backFaceCulling",{get:function(){return this._backFaceCulling},set:function(g){this._backFaceCulling!==g&&(this._backFaceCulling=g,this.markAsDirty(S.TextureDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"hasRenderTargetTextures",{get:function(){return!1},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"onDispose",{set:function(g){this._onDisposeObserver&&this.onDisposeObservable.remove(this._onDisposeObserver),this._onDisposeObserver=this.onDisposeObservable.add(g)},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"onBindObservable",{get:function(){return this._onBindObservable||(this._onBindObservable=new u.c),this._onBindObservable},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"onBind",{set:function(g){this._onBindObserver&&this.onBindObservable.remove(this._onBindObserver),this._onBindObserver=this.onBindObservable.add(g)},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"onUnBindObservable",{get:function(){return this._onUnBindObservable||(this._onUnBindObservable=new u.c),this._onUnBindObservable},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"onEffectCreatedObservable",{get:function(){return this._onEffectCreatedObservable||(this._onEffectCreatedObservable=new u.c),this._onEffectCreatedObservable},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"alphaMode",{get:function(){return this._alphaMode},set:function(g){this._alphaMode!==g&&(this._alphaMode=g,this.markAsDirty(S.TextureDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"needDepthPrePass",{get:function(){return this._needDepthPrePass},set:function(g){this._needDepthPrePass!==g&&(this._needDepthPrePass=g,this._needDepthPrePass&&(this.checkReadyOnEveryCall=!0))},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"fogEnabled",{get:function(){return this._fogEnabled},set:function(g){this._fogEnabled!==g&&(this._fogEnabled=g,this.markAsDirty(S.MiscDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"wireframe",{get:function(){switch(this._fillMode){case S.WireFrameFillMode:case S.LineListDrawMode:case S.LineLoopDrawMode:case S.LineStripDrawMode:return!0}return this._scene.forceWireframe},set:function(g){this.fillMode=g?S.WireFrameFillMode:S.TriangleFillMode},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"pointsCloud",{get:function(){switch(this._fillMode){case S.PointFillMode:case S.PointListDrawMode:return!0}return this._scene.forcePointsCloud},set:function(g){this.fillMode=g?S.PointFillMode:S.TriangleFillMode},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"fillMode",{get:function(){return this._fillMode},set:function(g){this._fillMode!==g&&(this._fillMode=g,this.markAsDirty(S.MiscDirtyFlag))},enumerable:!1,configurable:!0}),S.prototype.toString=function(g){return"Name: "+this.name},S.prototype.getClassName=function(){return"Material"},Object.defineProperty(S.prototype,"isFrozen",{get:function(){return this.checkReadyOnlyOnce},enumerable:!1,configurable:!0}),S.prototype.freeze=function(){this.markDirty(),this.checkReadyOnlyOnce=!0},S.prototype.unfreeze=function(){this.markDirty(),this.checkReadyOnlyOnce=!1},S.prototype.isReady=function(g,l){return!0},S.prototype.isReadyForSubMesh=function(g,l,h){return!1},S.prototype.getEffect=function(){return this._effect},S.prototype.getScene=function(){return this._scene},Object.defineProperty(S.prototype,"transparencyMode",{get:function(){return this._transparencyMode},set:function(g){this._transparencyMode!==g&&(this._transparencyMode=g,this._forceAlphaTest=g===S.MATERIAL_ALPHATESTANDBLEND,this._markAllSubMeshesAsTexturesAndMiscDirty())},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"_disableAlphaBlending",{get:function(){return this._transparencyMode===S.MATERIAL_OPAQUE||this._transparencyMode===S.MATERIAL_ALPHATEST},enumerable:!1,configurable:!0}),S.prototype.needAlphaBlending=function(){return!this._disableAlphaBlending&&this.alpha<1},S.prototype.needAlphaBlendingForMesh=function(g){return!(this._disableAlphaBlending&&g.visibility>=1)&&(this.needAlphaBlending()||g.visibility<1||g.hasVertexAlpha)},S.prototype.needAlphaTesting=function(){return!!this._forceAlphaTest},S.prototype._shouldTurnAlphaTestOn=function(g){return!this.needAlphaBlendingForMesh(g)&&this.needAlphaTesting()},S.prototype.getAlphaTestTexture=function(){return null},S.prototype.markDirty=function(){for(var g=0,l=this.getScene().meshes;g<l.length;g++){var h=l[g];if(h.subMeshes)for(var v=0,E=h.subMeshes;v<E.length;v++){var D=E[v];D.getMaterial()===this&&D.effect&&(D.effect._wasPreviouslyReady=!1)}}},S.prototype._preBind=function(g,l){l===void 0&&(l=null);var h=this._scene.getEngine(),v=(l??this.sideOrientation)===S.ClockWiseSideOrientation;return h.enableEffect(g||this._effect),h.setState(this.backFaceCulling,this.zOffset,!1,v),v},S.prototype.bind=function(g,l){},S.prototype.bindForSubMesh=function(g,l,h){},S.prototype.bindOnlyWorldMatrix=function(g){},S.prototype.bindSceneUniformBuffer=function(g,l){l.bindToEffect(g,"Scene")},S.prototype.bindView=function(g){this._useUBO?this.bindSceneUniformBuffer(g,this.getScene().getSceneUniformBuffer()):g.setMatrix("view",this.getScene().getViewMatrix())},S.prototype.bindViewProjection=function(g){this._useUBO?this.bindSceneUniformBuffer(g,this.getScene().getSceneUniformBuffer()):g.setMatrix("viewProjection",this.getScene().getTransformMatrix())},S.prototype._afterBind=function(g){if(this._scene._cachedMaterial=this,this._scene._cachedVisibility=g?g.visibility:1,this._onBindObservable&&g&&this._onBindObservable.notifyObservers(g),this.disableDepthWrite){var l=this._scene.getEngine();this._cachedDepthWriteState=l.getDepthWrite(),l.setDepthWrite(!1)}this.disableColorWrite&&(l=this._scene.getEngine(),this._cachedColorWriteState=l.getColorWrite(),l.setColorWrite(!1)),this.depthFunction!==0&&(l=this._scene.getEngine(),this._cachedDepthFunctionState=l.getDepthFunction()||0,l.setDepthFunction(this.depthFunction))},S.prototype.unbind=function(){this._onUnBindObservable&&this._onUnBindObservable.notifyObservers(this),this.depthFunction!==0&&this._scene.getEngine().setDepthFunction(this._cachedDepthFunctionState),this.disableDepthWrite&&this._scene.getEngine().setDepthWrite(this._cachedDepthWriteState),this.disableColorWrite&&this._scene.getEngine().setColorWrite(this._cachedColorWriteState)},S.prototype.getActiveTextures=function(){return[]},S.prototype.hasTexture=function(g){return!1},S.prototype.clone=function(g){return null},S.prototype.getBindedMeshes=function(){var g=this;if(this.meshMap){var l=new Array;for(var h in this.meshMap){var v=this.meshMap[h];v&&l.push(v)}return l}return this._scene.meshes.filter(function(E){return E.material===g})},S.prototype.forceCompilation=function(g,l,h,v){var E=this,D=Object(U.a)({clipPlane:!1,useInstances:!1},h),w=this.getScene(),N=this.allowShaderHotSwapping;this.allowShaderHotSwapping=!1;var I=function(){if(E._scene&&E._scene.getEngine()){var V=w.clipPlane;if(D.clipPlane&&(w.clipPlane=new T.a(0,0,0,1)),E._storeEffectOnSubMeshes){var X=!0,j=null;if(g.subMeshes){var ne=new R.a(0,0,0,0,0,g,void 0,!1,!1);ne._materialDefines&&(ne._materialDefines._renderId=-1),E.isReadyForSubMesh(g,ne,D.useInstances)||(ne.effect&&ne.effect.getCompilationError()&&ne.effect.allFallbacksProcessed()?j=ne.effect.getCompilationError():(X=!1,setTimeout(I,16)))}X&&(E.allowShaderHotSwapping=N,j&&v&&v(j),l&&l(E))}else E.isReady()?(E.allowShaderHotSwapping=N,l&&l(E)):setTimeout(I,16);D.clipPlane&&(w.clipPlane=V)}};I()},S.prototype.forceCompilationAsync=function(g,l){var h=this;return new Promise(function(v,E){h.forceCompilation(g,function(){v()},l,function(D){E(D)})})},S.prototype.markAsDirty=function(g){this.getScene().blockMaterialDirtyMechanism||(S._DirtyCallbackArray.length=0,g&S.TextureDirtyFlag&&S._DirtyCallbackArray.push(S._TextureDirtyCallBack),g&S.LightDirtyFlag&&S._DirtyCallbackArray.push(S._LightsDirtyCallBack),g&S.FresnelDirtyFlag&&S._DirtyCallbackArray.push(S._FresnelDirtyCallBack),g&S.AttributesDirtyFlag&&S._DirtyCallbackArray.push(S._AttributeDirtyCallBack),g&S.MiscDirtyFlag&&S._DirtyCallbackArray.push(S._MiscDirtyCallBack),g&S.PrePassDirtyFlag&&S._DirtyCallbackArray.push(S._PrePassDirtyCallBack),S._DirtyCallbackArray.length&&this._markAllSubMeshesAsDirty(S._RunDirtyCallBacks),this.getScene().resetCachedMaterial())},S.prototype._markAllSubMeshesAsDirty=function(g){if(!this.getScene().blockMaterialDirtyMechanism)for(var l=0,h=this.getScene().meshes;l<h.length;l++){var v=h[l];if(v.subMeshes)for(var E=0,D=v.subMeshes;E<D.length;E++){var 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g=this.getScene().enablePrePassRenderer();g&&g.markAsDirty()}},S.prototype._markAllSubMeshesAsAllDirty=function(){this._markAllSubMeshesAsDirty(S._AllDirtyCallBack)},S.prototype._markAllSubMeshesAsImageProcessingDirty=function(){this._markAllSubMeshesAsDirty(S._ImageProcessingDirtyCallBack)},S.prototype._markAllSubMeshesAsTexturesDirty=function(){this._markAllSubMeshesAsDirty(S._TextureDirtyCallBack)},S.prototype._markAllSubMeshesAsFresnelDirty=function(){this._markAllSubMeshesAsDirty(S._FresnelDirtyCallBack)},S.prototype._markAllSubMeshesAsFresnelAndMiscDirty=function(){this._markAllSubMeshesAsDirty(S._FresnelAndMiscDirtyCallBack)},S.prototype._markAllSubMeshesAsLightsDirty=function(){this._markAllSubMeshesAsDirty(S._LightsDirtyCallBack)},S.prototype._markAllSubMeshesAsAttributesDirty=function(){this._markAllSubMeshesAsDirty(S._AttributeDirtyCallBack)},S.prototype._markAllSubMeshesAsMiscDirty=function(){this._markAllSubMeshesAsDirty(S._MiscDirtyCallBack)},S.prototype._markAllSubMeshesAsPrePassDirty=function(){this._markAllSubMeshesAsDirty(S._MiscDirtyCallBack)},S.prototype._markAllSubMeshesAsTexturesAndMiscDirty=function(){this._markAllSubMeshesAsDirty(S._TextureAndMiscDirtyCallBack)},S.prototype.setPrePassRenderer=function(g){return!1},S.prototype.dispose=function(g,l,h){var v=this.getScene();if(v.stopAnimation(this),v.freeProcessedMaterials(),v.removeMaterial(this),h!==!0)if(this.meshMap)for(var E in this.meshMap)(N=this.meshMap[E])&&(N.material=null,this.releaseVertexArrayObject(N,g));else for(var D=0,w=v.meshes;D<w.length;D++){var N;(N=w[D]).material!==this||N.sourceMesh||(N.material=null,this.releaseVertexArrayObject(N,g))}this._uniformBuffer.dispose(),g&&this._effect&&(this._storeEffectOnSubMeshes||this._effect.dispose(),this._effect=null),this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear(),this._onBindObservable&&this._onBindObservable.clear(),this._onUnBindObservable&&this._onUnBindObservable.clear(),this._onEffectCreatedObservable&&this._onEffectCreatedObservable.clear()},S.prototype.releaseVertexArrayObject=function(g,l){if(g.geometry){var h=g.geometry;if(this._storeEffectOnSubMeshes)for(var v=0,E=g.subMeshes;v<E.length;v++){var 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x.b.Instantiate(g.customType).Parse(g,l,h)},S.TriangleFillMode=m.a.MATERIAL_TriangleFillMode,S.WireFrameFillMode=m.a.MATERIAL_WireFrameFillMode,S.PointFillMode=m.a.MATERIAL_PointFillMode,S.PointListDrawMode=m.a.MATERIAL_PointListDrawMode,S.LineListDrawMode=m.a.MATERIAL_LineListDrawMode,S.LineLoopDrawMode=m.a.MATERIAL_LineLoopDrawMode,S.LineStripDrawMode=m.a.MATERIAL_LineStripDrawMode,S.TriangleStripDrawMode=m.a.MATERIAL_TriangleStripDrawMode,S.TriangleFanDrawMode=m.a.MATERIAL_TriangleFanDrawMode,S.ClockWiseSideOrientation=m.a.MATERIAL_ClockWiseSideOrientation,S.CounterClockWiseSideOrientation=m.a.MATERIAL_CounterClockWiseSideOrientation,S.TextureDirtyFlag=m.a.MATERIAL_TextureDirtyFlag,S.LightDirtyFlag=m.a.MATERIAL_LightDirtyFlag,S.FresnelDirtyFlag=m.a.MATERIAL_FresnelDirtyFlag,S.AttributesDirtyFlag=m.a.MATERIAL_AttributesDirtyFlag,S.MiscDirtyFlag=m.a.MATERIAL_MiscDirtyFlag,S.PrePassDirtyFlag=m.a.MATERIAL_PrePassDirtyFlag,S.AllDirtyFlag=m.a.MATERIAL_AllDirtyFlag,S.MATERIAL_OPAQUE=0,S.MATERIAL_ALPHATEST=1,S.MATERIAL_ALPHABLEND=2,S.MATERIAL_ALPHATESTANDBLEND=3,S.MATERIAL_NORMALBLENDMETHOD_WHITEOUT=0,S.MATERIAL_NORMALBLENDMETHOD_RNM=1,S._AllDirtyCallBack=function(g){return 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be.bindRenderbuffer(be.RENDERBUFFER,Pe),he>1&&be.renderbufferStorageMultisample?be.renderbufferStorageMultisample(be.RENDERBUFFER,he,me,W,q):be.renderbufferStorage(be.RENDERBUFFER,ge,W,q),be.framebufferRenderbuffer(be.FRAMEBUFFER,_e,be.RENDERBUFFER,Pe),be.bindRenderbuffer(be.RENDERBUFFER,null),Pe},this._boundUniforms={};var te=null;if(I){if(X=X||{},E.a.SetMatrixPrecision(!!X.useHighPrecisionMatrix),I.getContext){if(te=I,this._renderingCanvas=te,V!=null&&(X.antialias=V),X.deterministicLockstep===void 0&&(X.deterministicLockstep=!1),X.lockstepMaxSteps===void 0&&(X.lockstepMaxSteps=4),X.timeStep===void 0&&(X.timeStep=1/60),X.preserveDrawingBuffer===void 0&&(X.preserveDrawingBuffer=!1),X.audioEngine===void 0&&(X.audioEngine=!0),X.stencil===void 0&&(X.stencil=!0),X.premultipliedAlpha===!1&&(this.premultipliedAlpha=!1),X.xrCompatible===void 0&&(X.xrCompatible=!0),this._doNotHandleContextLost=!!X.doNotHandleContextLost,navigator&&navigator.userAgent){var de=navigator.userAgent;this.hostInformation.isMobile=de.indexOf("Mobile")!==-1;for(var pe=0,ae=N.ExceptionList;pe<ae.length;pe++){var ee=ae[pe],K=ee.key,$=ee.targets;if(new RegExp(K).test(de)){if(ee.capture&&ee.captureConstraint){var L=ee.capture,G=ee.captureConstraint,Q=new RegExp(L).exec(de);if(Q&&Q.length>0&&parseInt(Q[Q.length-1])>=G)continue}for(var oe=0,re=$;oe<re.length;oe++)switch(re[oe]){case"uniformBuffer":this.disableUniformBuffers=!0;break;case"vao":this.disableVertexArrayObjects=!0}}}}if(this._doNotHandleContextLost||(this._onContextLost=function(W){W.preventDefault(),ne._contextWasLost=!0,T.a.Warn("WebGL context lost."),ne.onContextLostObservable.notifyObservers(ne)},this._onContextRestored=function(){setTimeout(function(){ne._initGLContext(),ne._rebuildEffects(),ne._rebuildInternalTextures(),ne._rebuildBuffers(),ne.wipeCaches(!0),T.a.Warn("WebGL context successfully 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Uint8Array(4),1,1,1,m.a.TEXTUREFORMAT_RGBA,!1,!1,m.a.TEXTURE_NEAREST_SAMPLINGMODE)),this._emptyTexture3D},enumerable:!1,configurable:!0}),Object.defineProperty(N.prototype,"emptyTexture2DArray",{get:function(){return this._emptyTexture2DArray||(this._emptyTexture2DArray=this.createRawTexture2DArray(new Uint8Array(4),1,1,1,m.a.TEXTUREFORMAT_RGBA,!1,!1,m.a.TEXTURE_NEAREST_SAMPLINGMODE)),this._emptyTexture2DArray},enumerable:!1,configurable:!0}),Object.defineProperty(N.prototype,"emptyCubeTexture",{get:function(){if(!this._emptyCubeTexture){var I=new Uint8Array(4),V=[I,I,I,I,I,I];this._emptyCubeTexture=this.createRawCubeTexture(V,1,m.a.TEXTUREFORMAT_RGBA,m.a.TEXTURETYPE_UNSIGNED_INT,!1,!1,m.a.TEXTURE_NEAREST_SAMPLINGMODE)}return this._emptyCubeTexture},enumerable:!1,configurable:!0}),N.prototype._rebuildInternalTextures=function(){for(var I=0,V=this._internalTexturesCache.slice();I<V.length;I++)V[I]._rebuild()},N.prototype._rebuildEffects=function(){for(var I in this._compiledEffects)this._compiledEffects[I]._prepareEffect();_.a.ResetCache()},N.prototype.areAllEffectsReady=function(){for(var I in this._compiledEffects)if(!this._compiledEffects[I].isReady())return!1;return!0},N.prototype._rebuildBuffers=function(){for(var I=0,V=this._uniformBuffers;I<V.length;I++)V[I]._rebuild()},N.prototype._initGLContext=function(){this._caps={maxTexturesImageUnits:this._gl.getParameter(this._gl.MAX_TEXTURE_IMAGE_UNITS),maxCombinedTexturesImageUnits:this._gl.getParameter(this._gl.MAX_COMBINED_TEXTURE_IMAGE_UNITS),maxVertexTextureImageUnits:this._gl.getParameter(this._gl.MAX_VERTEX_TEXTURE_IMAGE_UNITS),maxTextureSize:this._gl.getParameter(this._gl.MAX_TEXTURE_SIZE),maxSamples:this._webGLVersion>1?this._gl.getParameter(this._gl.MAX_SAMPLES):1,maxCubemapTextureSize:this._gl.getParameter(this._gl.MAX_CUBE_MAP_TEXTURE_SIZE),maxRenderTextureSize:this._gl.getParameter(this._gl.MAX_RENDERBUFFER_SIZE),maxVertexAttribs:this._gl.getParameter(this._gl.MAX_VERTEX_ATTRIBS),maxVaryingVectors:this._gl.getParameter(this._gl.MAX_VARYING_VECTORS),maxFragmentUniformVectors:this._gl.getParameter(this._gl.MAX_FRAGMENT_UNIFORM_VECTORS),maxVertexUniformVectors:this._gl.getParameter(this._gl.MAX_VERTEX_UNIFORM_VECTORS),parallelShaderCompile:this._gl.getExtension("KHR_parallel_shader_compile"),standardDerivatives:this._webGLVersion>1||this._gl.getExtension("OES_standard_derivatives")!==null,maxAnisotropy:1,astc:this._gl.getExtension("WEBGL_compressed_texture_astc")||this._gl.getExtension("WEBKIT_WEBGL_compressed_texture_astc"),bptc:this._gl.getExtension("EXT_texture_compression_bptc")||this._gl.getExtension("WEBKIT_EXT_texture_compression_bptc"),s3tc:this._gl.getExtension("WEBGL_compressed_texture_s3tc")||this._gl.getExtension("WEBKIT_WEBGL_compressed_texture_s3tc"),pvrtc:this._gl.getExtension("WEBGL_compressed_texture_pvrtc")||this._gl.getExtension("WEBKIT_WEBGL_compressed_texture_pvrtc"),etc1:this._gl.getExtension("WEBGL_compressed_texture_etc1")||this._gl.getExtension("WEBKIT_WEBGL_compressed_texture_etc1"),etc2:this._gl.getExtension("WEBGL_compressed_texture_etc")||this._gl.getExtension("WEBKIT_WEBGL_compressed_texture_etc")||this._gl.getExtension("WEBGL_compressed_texture_es3_0"),textureAnisotropicFilterExtension:this._gl.getExtension("EXT_texture_filter_anisotropic")||this._gl.getExtension("WEBKIT_EXT_texture_filter_anisotropic")||this._gl.getExtension("MOZ_EXT_texture_filter_anisotropic"),uintIndices:this._webGLVersion>1||this._gl.getExtension("OES_element_index_uint")!==null,fragmentDepthSupported:this._webGLVersion>1||this._gl.getExtension("EXT_frag_depth")!==null,highPrecisionShaderSupported:!1,timerQuery:this._gl.getExtension("EXT_disjoint_timer_query_webgl2")||this._gl.getExtension("EXT_disjoint_timer_query"),canUseTimestampForTimerQuery:!1,drawBuffersExtension:!1,maxMSAASamples:1,colorBufferFloat:this._webGLVersion>1&&this._gl.getExtension("EXT_color_buffer_float"),textureFloat:!!(this._webGLVersion>1||this._gl.getExtension("OES_texture_float")),textureHalfFloat:!!(this._webGLVersion>1||this._gl.getExtension("OES_texture_half_float")),textureHalfFloatRender:!1,textureFloatLinearFiltering:!1,textureFloatRender:!1,textureHalfFloatLinearFiltering:!1,vertexArrayObject:!1,instancedArrays:!1,textureLOD:!!(this._webGLVersion>1||this._gl.getExtension("EXT_shader_texture_lod")),blendMinMax:!1,multiview:this._gl.getExtension("OVR_multiview2"),oculusMultiview:this._gl.getExtension("OCULUS_multiview"),depthTextureExtension:!1},this._glVersion=this._gl.getParameter(this._gl.VERSION);var I=this._gl.getExtension("WEBGL_debug_renderer_info");if(I!=null&&(this._glRenderer=this._gl.getParameter(I.UNMASKED_RENDERER_WEBGL),this._glVendor=this._gl.getParameter(I.UNMASKED_VENDOR_WEBGL)),this._glVendor||(this._glVendor="Unknown vendor"),this._glRenderer||(this._glRenderer="Unknown renderer"),this._gl.HALF_FLOAT_OES!==36193&&(this._gl.HALF_FLOAT_OES=36193),this._gl.RGBA16F!==34842&&(this._gl.RGBA16F=34842),this._gl.RGBA32F!==34836&&(this._gl.RGBA32F=34836),this._gl.DEPTH24_STENCIL8!==35056&&(this._gl.DEPTH24_STENCIL8=35056),this._caps.timerQuery&&(this._webGLVersion===1&&(this._gl.getQuery=this._caps.timerQuery.getQueryEXT.bind(this._caps.timerQuery)),this._caps.canUseTimestampForTimerQuery=this._gl.getQuery(this._caps.timerQuery.TIMESTAMP_EXT,this._caps.timerQuery.QUERY_COUNTER_BITS_EXT)>0),this._caps.maxAnisotropy=this._caps.textureAnisotropicFilterExtension?this._gl.getParameter(this._caps.textureAnisotropicFilterExtension.MAX_TEXTURE_MAX_ANISOTROPY_EXT):0,this._caps.textureFloatLinearFiltering=!(!this._caps.textureFloat||!this._gl.getExtension("OES_texture_float_linear")),this._caps.textureFloatRender=!(!this._caps.textureFloat||!this._canRenderToFloatFramebuffer()),this._caps.textureHalfFloatLinearFiltering=!!(this._webGLVersion>1||this._caps.textureHalfFloat&&this._gl.getExtension("OES_texture_half_float_linear")),this._webGLVersion>1&&this._gl.HALF_FLOAT_OES!==5131&&(this._gl.HALF_FLOAT_OES=5131),this._caps.textureHalfFloatRender=this._caps.textureHalfFloat&&this._canRenderToHalfFloatFramebuffer(),this._webGLVersion>1)this._caps.drawBuffersExtension=!0,this._caps.maxMSAASamples=this._gl.getParameter(this._gl.MAX_SAMPLES);else{var V=this._gl.getExtension("WEBGL_draw_buffers");if(V!==null){this._caps.drawBuffersExtension=!0,this._gl.drawBuffers=V.drawBuffersWEBGL.bind(V),this._gl.DRAW_FRAMEBUFFER=this._gl.FRAMEBUFFER;for(var X=0;X<16;X++)this._gl["COLOR_ATTACHMENT"+X+"_WEBGL"]=V["COLOR_ATTACHMENT"+X+"_WEBGL"]}}if(this._webGLVersion>1)this._caps.depthTextureExtension=!0;else{var j=this._gl.getExtension("WEBGL_depth_texture");j!=null&&(this._caps.depthTextureExtension=!0,this._gl.UNSIGNED_INT_24_8=j.UNSIGNED_INT_24_8_WEBGL)}if(this.disableVertexArrayObjects)this._caps.vertexArrayObject=!1;else if(this._webGLVersion>1)this._caps.vertexArrayObject=!0;else{var ne=this._gl.getExtension("OES_vertex_array_object");ne!=null&&(this._caps.vertexArrayObject=!0,this._gl.createVertexArray=ne.createVertexArrayOES.bind(ne),this._gl.bindVertexArray=ne.bindVertexArrayOES.bind(ne),this._gl.deleteVertexArray=ne.deleteVertexArrayOES.bind(ne))}if(this._webGLVersion>1)this._caps.instancedArrays=!0;else{var te=this._gl.getExtension("ANGLE_instanced_arrays");te!=null?(this._caps.instancedArrays=!0,this._gl.drawArraysInstanced=te.drawArraysInstancedANGLE.bind(te),this._gl.drawElementsInstanced=te.drawElementsInstancedANGLE.bind(te),this._gl.vertexAttribDivisor=te.vertexAttribDivisorANGLE.bind(te)):this._caps.instancedArrays=!1}if(this._gl.getShaderPrecisionFormat){var de=this._gl.getShaderPrecisionFormat(this._gl.VERTEX_SHADER,this._gl.HIGH_FLOAT),pe=this._gl.getShaderPrecisionFormat(this._gl.FRAGMENT_SHADER,this._gl.HIGH_FLOAT);de&&pe&&(this._caps.highPrecisionShaderSupported=de.precision!==0&&pe.precision!==0)}if(this._webGLVersion>1)this._caps.blendMinMax=!0;else{var ae=this._gl.getExtension("EXT_blend_minmax");ae!=null&&(this._caps.blendMinMax=!0,this._gl.MAX=ae.MAX_EXT,this._gl.MIN=ae.MIN_EXT)}this._depthCullingState.depthTest=!0,this._depthCullingState.depthFunc=this._gl.LEQUAL,this._depthCullingState.depthMask=!0,this._maxSimultaneousTextures=this._caps.maxCombinedTexturesImageUnits;for(var ee=0;ee<this._maxSimultaneousTextures;ee++)this._nextFreeTextureSlots.push(ee)},Object.defineProperty(N.prototype,"webGLVersion",{get:function(){return this._webGLVersion},enumerable:!1,configurable:!0}),N.prototype.getClassName=function(){return"ThinEngine"},Object.defineProperty(N.prototype,"isStencilEnable",{get:function(){return this._isStencilEnable},enumerable:!1,configurable:!0}),N.prototype._prepareWorkingCanvas=function(){if(!this._workingCanvas){this._workingCanvas=v.a.CreateCanvas(1,1);var I=this._workingCanvas.getContext("2d");I&&(this._workingContext=I)}},N.prototype.resetTextureCache=function(){for(var I in this._boundTexturesCache)this._boundTexturesCache.hasOwnProperty(I)&&(this._boundTexturesCache[I]=null);this._currentTextureChannel=-1},N.prototype.getGlInfo=function(){return{vendor:this._glVendor,renderer:this._glRenderer,version:this._glVersion}},N.prototype.setHardwareScalingLevel=function(I){this._hardwareScalingLevel=I,this.resize()},N.prototype.getHardwareScalingLevel=function(){return this._hardwareScalingLevel},N.prototype.getLoadedTexturesCache=function(){return this._internalTexturesCache},N.prototype.getCaps=function(){return this._caps},N.prototype.stopRenderLoop=function(I){if(I){var V=this._activeRenderLoops.indexOf(I);V>=0&&this._activeRenderLoops.splice(V,1)}else this._activeRenderLoops=[]},N.prototype._renderLoop=function(){if(!this._contextWasLost){var I=!0;if(!this.renderEvenInBackground&&this._windowIsBackground&&(I=!1),I){this.beginFrame();for(var V=0;V<this._activeRenderLoops.length;V++)(0,this._activeRenderLoops[V])();this.endFrame()}}this._activeRenderLoops.length>0?this._frameHandler=this._queueNewFrame(this._boundRenderFunction,this.getHostWindow()):this._renderingQueueLaunched=!1},N.prototype.getRenderingCanvas=function(){return this._renderingCanvas},N.prototype.getHostWindow=function(){return A.a.IsWindowObjectExist()?this._renderingCanvas&&this._renderingCanvas.ownerDocument&&this._renderingCanvas.ownerDocument.defaultView?this._renderingCanvas.ownerDocument.defaultView:window:null},N.prototype.getRenderWidth=function(I){return I===void 0&&(I=!1),!I&&this._currentRenderTarget?this._currentRenderTarget.width:this._framebufferDimensionsObject?this._framebufferDimensionsObject.framebufferWidth:this._gl.drawingBufferWidth},N.prototype.getRenderHeight=function(I){return I===void 0&&(I=!1),!I&&this._currentRenderTarget?this._currentRenderTarget.height:this._framebufferDimensionsObject?this._framebufferDimensionsObject.framebufferHeight:this._gl.drawingBufferHeight},N.prototype._queueNewFrame=function(I,V){return N.QueueNewFrame(I,V)},N.prototype.runRenderLoop=function(I){this._activeRenderLoops.indexOf(I)===-1&&(this._activeRenderLoops.push(I),this._renderingQueueLaunched||(this._renderingQueueLaunched=!0,this._boundRenderFunction=this._renderLoop.bind(this),this._frameHandler=this._queueNewFrame(this._boundRenderFunction,this.getHostWindow())))},N.prototype.clear=function(I,V,X,j){j===void 0&&(j=!1),this.applyStates();var ne=0;V&&I&&(this._gl.clearColor(I.r,I.g,I.b,I.a!==void 0?I.a:1),ne|=this._gl.COLOR_BUFFER_BIT),X&&(this.useReverseDepthBuffer?(this._depthCullingState.depthFunc=this._gl.GREATER,this._gl.clearDepth(0)):this._gl.clearDepth(1),ne|=this._gl.DEPTH_BUFFER_BIT),j&&(this._gl.clearStencil(0),ne|=this._gl.STENCIL_BUFFER_BIT),this._gl.clear(ne)},N.prototype._viewport=function(I,V,X,j){I===this._viewportCached.x&&V===this._viewportCached.y&&X===this._viewportCached.z&&j===this._viewportCached.w||(this._viewportCached.x=I,this._viewportCached.y=V,this._viewportCached.z=X,this._viewportCached.w=j,this._gl.viewport(I,V,X,j))},N.prototype.setViewport=function(I,V,X){var j=V||this.getRenderWidth(),ne=X||this.getRenderHeight(),te=I.x||0,de=I.y||0;this._cachedViewport=I,this._viewport(te*j,de*ne,j*I.width,ne*I.height)},N.prototype.beginFrame=function(){},N.prototype.endFrame=function(){this._badOS&&this.flushFramebuffer()},N.prototype.resize=function(){var I,V;A.a.IsWindowObjectExist()?(I=this._renderingCanvas?this._renderingCanvas.clientWidth||this._renderingCanvas.width:window.innerWidth,V=this._renderingCanvas?this._renderingCanvas.clientHeight||this._renderingCanvas.height:window.innerHeight):(I=this._renderingCanvas?this._renderingCanvas.width:100,V=this._renderingCanvas?this._renderingCanvas.height:100),this.setSize(I/this._hardwareScalingLevel,V/this._hardwareScalingLevel)},N.prototype.setSize=function(I,V){return!!this._renderingCanvas&&(I|=0,V|=0,(this._renderingCanvas.width!==I||this._renderingCanvas.height!==V)&&(this._renderingCanvas.width=I,this._renderingCanvas.height=V,!0))},N.prototype.bindFramebuffer=function(I,V,X,j,ne,te,de){V===void 0&&(V=0),te===void 0&&(te=0),de===void 0&&(de=0),this._currentRenderTarget&&this.unBindFramebuffer(this._currentRenderTarget),this._currentRenderTarget=I,this._bindUnboundFramebuffer(I._MSAAFramebuffer?I._MSAAFramebuffer:I._framebuffer);var pe=this._gl;I.is2DArray?pe.framebufferTextureLayer(pe.FRAMEBUFFER,pe.COLOR_ATTACHMENT0,I._webGLTexture,te,de):I.isCube&&pe.framebufferTexture2D(pe.FRAMEBUFFER,pe.COLOR_ATTACHMENT0,pe.TEXTURE_CUBE_MAP_POSITIVE_X+V,I._webGLTexture,te);var ae=I._depthStencilTexture;if(ae){var ee=ae._generateStencilBuffer?pe.DEPTH_STENCIL_ATTACHMENT:pe.DEPTH_ATTACHMENT;I.is2DArray?pe.framebufferTextureLayer(pe.FRAMEBUFFER,ee,ae._webGLTexture,te,de):I.isCube?pe.framebufferTexture2D(pe.FRAMEBUFFER,ee,pe.TEXTURE_CUBE_MAP_POSITIVE_X+V,ae._webGLTexture,te):pe.framebufferTexture2D(pe.FRAMEBUFFER,ee,pe.TEXTURE_2D,ae._webGLTexture,te)}this._cachedViewport&&!ne?this.setViewport(this._cachedViewport,X,j):(X||(X=I.width,te&&(X/=Math.pow(2,te))),j||(j=I.height,te&&(j/=Math.pow(2,te))),this._viewport(0,0,X,j)),this.wipeCaches()},N.prototype._bindUnboundFramebuffer=function(I){this._currentFramebuffer!==I&&(this._gl.bindFramebuffer(this._gl.FRAMEBUFFER,I),this._currentFramebuffer=I)},N.prototype.unBindFramebuffer=function(I,V,X){V===void 0&&(V=!1),this._currentRenderTarget=null;var j=this._gl;if(I._MSAAFramebuffer){if(I._textureArray)return void this.unBindMultiColorAttachmentFramebuffer(I._textureArray,V,X);j.bindFramebuffer(j.READ_FRAMEBUFFER,I._MSAAFramebuffer),j.bindFramebuffer(j.DRAW_FRAMEBUFFER,I._framebuffer),j.blitFramebuffer(0,0,I.width,I.height,0,0,I.width,I.height,j.COLOR_BUFFER_BIT,j.NEAREST)}!I.generateMipMaps||V||I.isCube||(this._bindTextureDirectly(j.TEXTURE_2D,I,!0),j.generateMipmap(j.TEXTURE_2D),this._bindTextureDirectly(j.TEXTURE_2D,null)),X&&(I._MSAAFramebuffer&&this._bindUnboundFramebuffer(I._framebuffer),X()),this._bindUnboundFramebuffer(null)},N.prototype.flushFramebuffer=function(){this._gl.flush()},N.prototype.restoreDefaultFramebuffer=function(){this._currentRenderTarget?this.unBindFramebuffer(this._currentRenderTarget):this._bindUnboundFramebuffer(null),this._cachedViewport&&this.setViewport(this._cachedViewport),this.wipeCaches()},N.prototype._resetVertexBufferBinding=function(){this.bindArrayBuffer(null),this._cachedVertexBuffers=null},N.prototype.createVertexBuffer=function(I){return this._createVertexBuffer(I,this._gl.STATIC_DRAW)},N.prototype._createVertexBuffer=function(I,V){var X=this._gl.createBuffer();if(!X)throw new Error("Unable to create vertex buffer");var j=new l.a(X);return this.bindArrayBuffer(j),I instanceof Array?this._gl.bufferData(this._gl.ARRAY_BUFFER,new Float32Array(I),this._gl.STATIC_DRAW):this._gl.bufferData(this._gl.ARRAY_BUFFER,I,this._gl.STATIC_DRAW),this._resetVertexBufferBinding(),j.references=1,j},N.prototype.createDynamicVertexBuffer=function(I){return this._createVertexBuffer(I,this._gl.DYNAMIC_DRAW)},N.prototype._resetIndexBufferBinding=function(){this.bindIndexBuffer(null),this._cachedIndexBuffer=null},N.prototype.createIndexBuffer=function(I,V){var X=this._gl.createBuffer(),j=new l.a(X);if(!X)throw new Error("Unable to create index buffer");this.bindIndexBuffer(j);var ne=this._normalizeIndexData(I);return this._gl.bufferData(this._gl.ELEMENT_ARRAY_BUFFER,ne,V?this._gl.DYNAMIC_DRAW:this._gl.STATIC_DRAW),this._resetIndexBufferBinding(),j.references=1,j.is32Bits=ne.BYTES_PER_ELEMENT===4,j},N.prototype._normalizeIndexData=function(I){if(I instanceof Uint16Array)return I;if(this._caps.uintIndices){if(I instanceof Uint32Array)return I;for(var V=0;V<I.length;V++)if(I[V]>=65535)return new Uint32Array(I);return new Uint16Array(I)}return new Uint16Array(I)},N.prototype.bindArrayBuffer=function(I){this._vaoRecordInProgress||this._unbindVertexArrayObject(),this.bindBuffer(I,this._gl.ARRAY_BUFFER)},N.prototype.bindUniformBlock=function(I,V,X){var j=I.program,ne=this._gl.getUniformBlockIndex(j,V);this._gl.uniformBlockBinding(j,ne,X)},N.prototype.bindIndexBuffer=function(I){this._vaoRecordInProgress||this._unbindVertexArrayObject(),this.bindBuffer(I,this._gl.ELEMENT_ARRAY_BUFFER)},N.prototype.bindBuffer=function(I,V){(this._vaoRecordInProgress||this._currentBoundBuffer[V]!==I)&&(this._gl.bindBuffer(V,I?I.underlyingResource:null),this._currentBoundBuffer[V]=I)},N.prototype.updateArrayBuffer=function(I){this._gl.bufferSubData(this._gl.ARRAY_BUFFER,0,I)},N.prototype._vertexAttribPointer=function(I,V,X,j,ne,te,de){var pe=this._currentBufferPointers[V];if(pe){var ae=!1;pe.active?(pe.buffer!==I&&(pe.buffer=I,ae=!0),pe.size!==X&&(pe.size=X,ae=!0),pe.type!==j&&(pe.type=j,ae=!0),pe.normalized!==ne&&(pe.normalized=ne,ae=!0),pe.stride!==te&&(pe.stride=te,ae=!0),pe.offset!==de&&(pe.offset=de,ae=!0)):(ae=!0,pe.active=!0,pe.index=V,pe.size=X,pe.type=j,pe.normalized=ne,pe.stride=te,pe.offset=de,pe.buffer=I),(ae||this._vaoRecordInProgress)&&(this.bindArrayBuffer(I),this._gl.vertexAttribPointer(V,X,j,ne,te,de))}},N.prototype._bindIndexBufferWithCache=function(I){I!=null&&this._cachedIndexBuffer!==I&&(this._cachedIndexBuffer=I,this.bindIndexBuffer(I),this._uintIndicesCurrentlySet=I.is32Bits)},N.prototype._bindVertexBuffersAttributes=function(I,V){var X=V.getAttributesNames();this._vaoRecordInProgress||this._unbindVertexArrayObject(),this.unbindAllAttributes();for(var j=0;j<X.length;j++){var ne=V.getAttributeLocation(j);if(ne>=0){var te=I[X[j]];if(!te)continue;this._gl.enableVertexAttribArray(ne),this._vaoRecordInProgress||(this._vertexAttribArraysEnabled[ne]=!0);var de=te.getBuffer();de&&(this._vertexAttribPointer(de,ne,te.getSize(),te.type,te.normalized,te.byteStride,te.byteOffset),te.getIsInstanced()&&(this._gl.vertexAttribDivisor(ne,te.getInstanceDivisor()),this._vaoRecordInProgress||(this._currentInstanceLocations.push(ne),this._currentInstanceBuffers.push(de))))}}},N.prototype.recordVertexArrayObject=function(I,V,X){var j=this._gl.createVertexArray();return this._vaoRecordInProgress=!0,this._gl.bindVertexArray(j),this._mustWipeVertexAttributes=!0,this._bindVertexBuffersAttributes(I,X),this.bindIndexBuffer(V),this._vaoRecordInProgress=!1,this._gl.bindVertexArray(null),j},N.prototype.bindVertexArrayObject=function(I,V){this._cachedVertexArrayObject!==I&&(this._cachedVertexArrayObject=I,this._gl.bindVertexArray(I),this._cachedVertexBuffers=null,this._cachedIndexBuffer=null,this._uintIndicesCurrentlySet=V!=null&&V.is32Bits,this._mustWipeVertexAttributes=!0)},N.prototype.bindBuffersDirectly=function(I,V,X,j,ne){if(this._cachedVertexBuffers!==I||this._cachedEffectForVertexBuffers!==ne){this._cachedVertexBuffers=I,this._cachedEffectForVertexBuffers=ne;var te=ne.getAttributesCount();this._unbindVertexArrayObject(),this.unbindAllAttributes();for(var de=0,pe=0;pe<te;pe++)if(pe<X.length){var ae=ne.getAttributeLocation(pe);ae>=0&&(this._gl.enableVertexAttribArray(ae),this._vertexAttribArraysEnabled[ae]=!0,this._vertexAttribPointer(I,ae,X[pe],this._gl.FLOAT,!1,j,de)),de+=4*X[pe]}}this._bindIndexBufferWithCache(V)},N.prototype._unbindVertexArrayObject=function(){this._cachedVertexArrayObject&&(this._cachedVertexArrayObject=null,this._gl.bindVertexArray(null))},N.prototype.bindBuffers=function(I,V,X){this._cachedVertexBuffers===I&&this._cachedEffectForVertexBuffers===X||(this._cachedVertexBuffers=I,this._cachedEffectForVertexBuffers=X,this._bindVertexBuffersAttributes(I,X)),this._bindIndexBufferWithCache(V)},N.prototype.unbindInstanceAttributes=function(){for(var I,V=0,X=this._currentInstanceLocations.length;V<X;V++){var j=this._currentInstanceBuffers[V];I!=j&&j.references&&(I=j,this.bindArrayBuffer(j));var ne=this._currentInstanceLocations[V];this._gl.vertexAttribDivisor(ne,0)}this._currentInstanceBuffers.length=0,this._currentInstanceLocations.length=0},N.prototype.releaseVertexArrayObject=function(I){this._gl.deleteVertexArray(I)},N.prototype._releaseBuffer=function(I){return I.references--,I.references===0&&(this._deleteBuffer(I),!0)},N.prototype._deleteBuffer=function(I){this._gl.deleteBuffer(I.underlyingResource)},N.prototype.updateAndBindInstancesBuffer=function(I,V,X){if(this.bindArrayBuffer(I),V&&this._gl.bufferSubData(this._gl.ARRAY_BUFFER,0,V),X[0].index!==void 0)this.bindInstancesBuffer(I,X,!0);else for(var j=0;j<4;j++){var ne=X[j];this._vertexAttribArraysEnabled[ne]||(this._gl.enableVertexAttribArray(ne),this._vertexAttribArraysEnabled[ne]=!0),this._vertexAttribPointer(I,ne,4,this._gl.FLOAT,!1,64,16*j),this._gl.vertexAttribDivisor(ne,1),this._currentInstanceLocations.push(ne),this._currentInstanceBuffers.push(I)}},N.prototype.bindInstancesBuffer=function(I,V,X){X===void 0&&(X=!0),this.bindArrayBuffer(I);var j=0;if(X)for(var ne=0;ne<V.length;ne++)j+=4*(te=V[ne]).attributeSize;for(ne=0;ne<V.length;ne++){var te;(te=V[ne]).index===void 0&&(te.index=this._currentEffect.getAttributeLocationByName(te.attributeName)),te.index<0||(this._vertexAttribArraysEnabled[te.index]||(this._gl.enableVertexAttribArray(te.index),this._vertexAttribArraysEnabled[te.index]=!0),this._vertexAttribPointer(I,te.index,te.attributeSize,te.attributeType||this._gl.FLOAT,te.normalized||!1,j,te.offset),this._gl.vertexAttribDivisor(te.index,te.divisor===void 0?1:te.divisor),this._currentInstanceLocations.push(te.index),this._currentInstanceBuffers.push(I))}},N.prototype.disableInstanceAttributeByName=function(I){if(this._currentEffect){var V=this._currentEffect.getAttributeLocationByName(I);this.disableInstanceAttribute(V)}},N.prototype.disableInstanceAttribute=function(I){for(var V,X=!1;(V=this._currentInstanceLocations.indexOf(I))!==-1;)this._currentInstanceLocations.splice(V,1),this._currentInstanceBuffers.splice(V,1),X=!0,V=this._currentInstanceLocations.indexOf(I);X&&(this._gl.vertexAttribDivisor(I,0),this.disableAttributeByIndex(I))},N.prototype.disableAttributeByIndex=function(I){this._gl.disableVertexAttribArray(I),this._vertexAttribArraysEnabled[I]=!1,this._currentBufferPointers[I].active=!1},N.prototype.draw=function(I,V,X,j){this.drawElementsType(I?m.a.MATERIAL_TriangleFillMode:m.a.MATERIAL_WireFrameFillMode,V,X,j)},N.prototype.drawPointClouds=function(I,V,X){this.drawArraysType(m.a.MATERIAL_PointFillMode,I,V,X)},N.prototype.drawUnIndexed=function(I,V,X,j){this.drawArraysType(I?m.a.MATERIAL_TriangleFillMode:m.a.MATERIAL_WireFrameFillMode,V,X,j)},N.prototype.drawElementsType=function(I,V,X,j){this.applyStates(),this._reportDrawCall();var ne=this._drawMode(I),te=this._uintIndicesCurrentlySet?this._gl.UNSIGNED_INT:this._gl.UNSIGNED_SHORT,de=this._uintIndicesCurrentlySet?4:2;j?this._gl.drawElementsInstanced(ne,X,te,V*de,j):this._gl.drawElements(ne,X,te,V*de)},N.prototype.drawArraysType=function(I,V,X,j){this.applyStates(),this._reportDrawCall();var ne=this._drawMode(I);j?this._gl.drawArraysInstanced(ne,V,X,j):this._gl.drawArrays(ne,V,X)},N.prototype._drawMode=function(I){switch(I){case m.a.MATERIAL_TriangleFillMode:return this._gl.TRIANGLES;case m.a.MATERIAL_PointFillMode:return this._gl.POINTS;case m.a.MATERIAL_WireFrameFillMode:return this._gl.LINES;case m.a.MATERIAL_PointListDrawMode:return this._gl.POINTS;case m.a.MATERIAL_LineListDrawMode:return this._gl.LINES;case m.a.MATERIAL_LineLoopDrawMode:return this._gl.LINE_LOOP;case m.a.MATERIAL_LineStripDrawMode:return this._gl.LINE_STRIP;case m.a.MATERIAL_TriangleStripDrawMode:return this._gl.TRIANGLE_STRIP;case m.a.MATERIAL_TriangleFanDrawMode:return this._gl.TRIANGLE_FAN;default:return this._gl.TRIANGLES}},N.prototype._reportDrawCall=function(){},N.prototype._releaseEffect=function(I){this._compiledEffects[I._key]&&(delete this._compiledEffects[I._key],this._deletePipelineContext(I.getPipelineContext()))},N.prototype._deletePipelineContext=function(I){var V=I;V&&V.program&&(V.program.__SPECTOR_rebuildProgram=null,this._gl.deleteProgram(V.program))},N.prototype.createEffect=function(I,V,X,j,ne,te,de,pe,ae){var ee=(I.vertexElement||I.vertex||I.vertexToken||I.vertexSource||I)+"+"+(I.fragmentElement||I.fragment||I.fragmentToken||I.fragmentSource||I)+"@"+(ne||V.defines);if(this._compiledEffects[ee]){var K=this._compiledEffects[ee];return de&&K.isReady()&&de(K),K}var $=new _.a(I,V,X,j,this,ne,te,de,pe,ae);return $._key=ee,this._compiledEffects[ee]=$,$},N._ConcatenateShader=function(I,V,X){return X===void 0&&(X=""),X+(V?V+`
-`:"")+I},N.prototype._compileShader=function(I,V,X,j){return this._compileRawShader(N._ConcatenateShader(I,X,j),V)},N.prototype._compileRawShader=function(I,V){var X=this._gl,j=X.createShader(V==="vertex"?X.VERTEX_SHADER:X.FRAGMENT_SHADER);if(!j)throw new Error("Something went wrong while compile the shader.");return X.shaderSource(j,I),X.compileShader(j),j},N.prototype._getShaderSource=function(I){return this._gl.getShaderSource(I)},N.prototype.createRawShaderProgram=function(I,V,X,j,ne){ne===void 0&&(ne=null),j=j||this._gl;var te=this._compileRawShader(V,"vertex"),de=this._compileRawShader(X,"fragment");return this._createShaderProgram(I,te,de,j,ne)},N.prototype.createShaderProgram=function(I,V,X,j,ne,te){te===void 0&&(te=null),ne=ne||this._gl;var de=this._webGLVersion>1?`#version 300 es
-#define WEBGL2 
-`:"",pe=this._compileShader(V,"vertex",j,de),ae=this._compileShader(X,"fragment",j,de);return this._createShaderProgram(I,pe,ae,ne,te)},N.prototype.createPipelineContext=function(){var I=new h.a;return I.engine=this,this._caps.parallelShaderCompile&&(I.isParallelCompiled=!0),I},N.prototype._createShaderProgram=function(I,V,X,j,ne){var te=j.createProgram();if(I.program=te,!te)throw new Error("Unable to create program");return j.attachShader(te,V),j.attachShader(te,X),j.linkProgram(te),I.context=j,I.vertexShader=V,I.fragmentShader=X,I.isParallelCompiled||this._finalizePipelineContext(I),te},N.prototype._finalizePipelineContext=function(I){var V=I.context,X=I.vertexShader,j=I.fragmentShader,ne=I.program;if(!V.getProgramParameter(ne,V.LINK_STATUS)){var te,de;if(!this._gl.getShaderParameter(X,this._gl.COMPILE_STATUS)&&(te=this._gl.getShaderInfoLog(X)))throw I.vertexCompilationError=te,new Error("VERTEX SHADER "+te);if(!this._gl.getShaderParameter(j,this._gl.COMPILE_STATUS)&&(te=this._gl.getShaderInfoLog(j)))throw I.fragmentCompilationError=te,new Error("FRAGMENT SHADER "+te);if(de=V.getProgramInfoLog(ne))throw I.programLinkError=de,new Error(de)}if(this.validateShaderPrograms&&(V.validateProgram(ne),!V.getProgramParameter(ne,V.VALIDATE_STATUS)&&(de=V.getProgramInfoLog(ne))))throw I.programValidationError=de,new Error(de);V.deleteShader(X),V.deleteShader(j),I.vertexShader=void 0,I.fragmentShader=void 0,I.onCompiled&&(I.onCompiled(),I.onCompiled=void 0)},N.prototype._preparePipelineContext=function(I,V,X,j,ne,te,de){var pe=I;pe.program=j?this.createRawShaderProgram(pe,V,X,void 0,de):this.createShaderProgram(pe,V,X,te,void 0,de),pe.program.__SPECTOR_rebuildProgram=ne},N.prototype._isRenderingStateCompiled=function(I){var V=I;return!!this._gl.getProgramParameter(V.program,this._caps.parallelShaderCompile.COMPLETION_STATUS_KHR)&&(this._finalizePipelineContext(V),!0)},N.prototype._executeWhenRenderingStateIsCompiled=function(I,V){var X=I;if(X.isParallelCompiled){var j=X.onCompiled;X.onCompiled=j?function(){j(),V()}:V}else V()},N.prototype.getUniforms=function(I,V){for(var X=new Array,j=I,ne=0;ne<V.length;ne++)X.push(this._gl.getUniformLocation(j.program,V[ne]));return X},N.prototype.getAttributes=function(I,V){for(var X=[],j=I,ne=0;ne<V.length;ne++)try{X.push(this._gl.getAttribLocation(j.program,V[ne]))}catch{X.push(-1)}return X},N.prototype.enableEffect=function(I){I&&I!==this._currentEffect&&(this.bindSamplers(I),this._currentEffect=I,I.onBind&&I.onBind(I),I._onBindObservable&&I._onBindObservable.notifyObservers(I))},N.prototype.setInt=function(I,V){return!!I&&(this._gl.uniform1i(I,V),!0)},N.prototype.setIntArray=function(I,V){return!!I&&(this._gl.uniform1iv(I,V),!0)},N.prototype.setIntArray2=function(I,V){return!(!I||V.length%2!=0)&&(this._gl.uniform2iv(I,V),!0)},N.prototype.setIntArray3=function(I,V){return!(!I||V.length%3!=0)&&(this._gl.uniform3iv(I,V),!0)},N.prototype.setIntArray4=function(I,V){return!(!I||V.length%4!=0)&&(this._gl.uniform4iv(I,V),!0)},N.prototype.setArray=function(I,V){return!!I&&(this._gl.uniform1fv(I,V),!0)},N.prototype.setArray2=function(I,V){return!(!I||V.length%2!=0)&&(this._gl.uniform2fv(I,V),!0)},N.prototype.setArray3=function(I,V){return!(!I||V.length%3!=0)&&(this._gl.uniform3fv(I,V),!0)},N.prototype.setArray4=function(I,V){return!(!I||V.length%4!=0)&&(this._gl.uniform4fv(I,V),!0)},N.prototype.setMatrices=function(I,V){return!!I&&(this._gl.uniformMatrix4fv(I,!1,V),!0)},N.prototype.setMatrix3x3=function(I,V){return!!I&&(this._gl.uniformMatrix3fv(I,!1,V),!0)},N.prototype.setMatrix2x2=function(I,V){return!!I&&(this._gl.uniformMatrix2fv(I,!1,V),!0)},N.prototype.setFloat=function(I,V){return!!I&&(this._gl.uniform1f(I,V),!0)},N.prototype.setFloat2=function(I,V,X){return!!I&&(this._gl.uniform2f(I,V,X),!0)},N.prototype.setFloat3=function(I,V,X,j){return!!I&&(this._gl.uniform3f(I,V,X,j),!0)},N.prototype.setFloat4=function(I,V,X,j,ne){return!!I&&(this._gl.uniform4f(I,V,X,j,ne),!0)},N.prototype.applyStates=function(){if(this._depthCullingState.apply(this._gl),this._stencilState.apply(this._gl),this._alphaState.apply(this._gl),this._colorWriteChanged){this._colorWriteChanged=!1;var I=this._colorWrite;this._gl.colorMask(I,I,I,I)}},N.prototype.setColorWrite=function(I){I!==this._colorWrite&&(this._colorWriteChanged=!0,this._colorWrite=I)},N.prototype.getColorWrite=function(){return this._colorWrite},Object.defineProperty(N.prototype,"depthCullingState",{get:function(){return this._depthCullingState},enumerable:!1,configurable:!0}),Object.defineProperty(N.prototype,"alphaState",{get:function(){return this._alphaState},enumerable:!1,configurable:!0}),Object.defineProperty(N.prototype,"stencilState",{get:function(){return this._stencilState},enumerable:!1,configurable:!0}),N.prototype.clearInternalTexturesCache=function(){this._internalTexturesCache=[]},N.prototype.wipeCaches=function(I){this.preventCacheWipeBetweenFrames&&!I||(this._currentEffect=null,this._viewportCached.x=0,this._viewportCached.y=0,this._viewportCached.z=0,this._viewportCached.w=0,this._unbindVertexArrayObject(),I&&(this._currentProgram=null,this.resetTextureCache(),this._stencilState.reset(),this._depthCullingState.reset(),this._depthCullingState.depthFunc=this._gl.LEQUAL,this._alphaState.reset(),this._alphaMode=m.a.ALPHA_ADD,this._alphaEquation=m.a.ALPHA_DISABLE,this._colorWrite=!0,this._colorWriteChanged=!0,this._unpackFlipYCached=null,this._gl.pixelStorei(this._gl.UNPACK_COLORSPACE_CONVERSION_WEBGL,this._gl.NONE),this._gl.pixelStorei(this._gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL,0),this._mustWipeVertexAttributes=!0,this.unbindAllAttributes()),this._resetVertexBufferBinding(),this._cachedIndexBuffer=null,this._cachedEffectForVertexBuffers=null,this.bindIndexBuffer(null))},N.prototype._getSamplingParameters=function(I,V){var X=this._gl,j=X.NEAREST,ne=X.NEAREST;switch(I){case m.a.TEXTURE_LINEAR_LINEAR_MIPNEAREST:j=X.LINEAR,ne=V?X.LINEAR_MIPMAP_NEAREST:X.LINEAR;break;case m.a.TEXTURE_LINEAR_LINEAR_MIPLINEAR:j=X.LINEAR,ne=V?X.LINEAR_MIPMAP_LINEAR:X.LINEAR;break;case m.a.TEXTURE_NEAREST_NEAREST_MIPLINEAR:j=X.NEAREST,ne=V?X.NEAREST_MIPMAP_LINEAR:X.NEAREST;break;case m.a.TEXTURE_NEAREST_NEAREST_MIPNEAREST:j=X.NEAREST,ne=V?X.NEAREST_MIPMAP_NEAREST:X.NEAREST;break;case m.a.TEXTURE_NEAREST_LINEAR_MIPNEAREST:j=X.NEAREST,ne=V?X.LINEAR_MIPMAP_NEAREST:X.LINEAR;break;case m.a.TEXTURE_NEAREST_LINEAR_MIPLINEAR:j=X.NEAREST,ne=V?X.LINEAR_MIPMAP_LINEAR:X.LINEAR;break;case m.a.TEXTURE_NEAREST_LINEAR:j=X.NEAREST,ne=X.LINEAR;break;case m.a.TEXTURE_NEAREST_NEAREST:j=X.NEAREST,ne=X.NEAREST;break;case m.a.TEXTURE_LINEAR_NEAREST_MIPNEAREST:j=X.LINEAR,ne=V?X.NEAREST_MIPMAP_NEAREST:X.NEAREST;break;case m.a.TEXTURE_LINEAR_NEAREST_MIPLINEAR:j=X.LINEAR,ne=V?X.NEAREST_MIPMAP_LINEAR:X.NEAREST;break;case m.a.TEXTURE_LINEAR_LINEAR:j=X.LINEAR,ne=X.LINEAR;break;case m.a.TEXTURE_LINEAR_NEAREST:j=X.LINEAR,ne=X.NEAREST}return{min:ne,mag:j}},N.prototype._createTexture=function(){var I=this._gl.createTexture();if(!I)throw new Error("Unable to create texture");return I},N.prototype.createTexture=function(I,V,X,j,ne,te,de,pe,ae,ee,K,$,L){var G=this;ne===void 0&&(ne=m.a.TEXTURE_TRILINEAR_SAMPLINGMODE),te===void 0&&(te=null),de===void 0&&(de=null),pe===void 0&&(pe=null),ae===void 0&&(ae=null),ee===void 0&&(ee=null),K===void 0&&(K=null);var Q=(I=I||"").substr(0,5)==="data:",oe=I.substr(0,5)==="blob:",re=Q&&I.indexOf(";base64,")!==-1,Y=ae||new c.a(this,c.b.Url),k=I;!this._transformTextureUrl||re||ae||pe||(I=this._transformTextureUrl(I)),k!==I&&(Y._originalUrl=k);var H=I.lastIndexOf("."),Z=K||(H>-1?I.substring(H).toLowerCase():""),W=null;Z.indexOf("?")>-1&&(Z=Z.split("?")[0]);for(var q=0,he=N._TextureLoaders;q<he.length;q++){var ge=he[q];if(ge.canLoad(Z,$)){W=ge;break}}j&&j._addPendingData(Y),Y.url=I,Y.generateMipMaps=!V,Y.samplingMode=ne,Y.invertY=X,this._doNotHandleContextLost||(Y._buffer=pe);var me=null;te&&!ae&&(me=Y.onLoadedObservable.add(te)),ae||this._internalTexturesCache.push(Y);var _e=function(ye,Be){j&&j._removePendingData(Y),I===k?(me&&Y.onLoadedObservable.remove(me),U.a.UseFallbackTexture&&G.createTexture(U.a.FallbackTexture,V,Y.invertY,j,ne,null,de,pe,Y),de&&de((ye||"Unknown error")+(U.a.UseFallbackTexture?" - Fallback texture was used":""),Be)):(T.a.Warn("Failed to load "+I+", falling back to "+k),G.createTexture(k,V,Y.invertY,j,ne,te,de,pe,Y,ee,K,$,L))};if(W){var be=function(ye){W.loadData(ye,Y,function(Be,ke,We,je,He,qe){qe?_e("TextureLoader failed to load data"):G._prepareWebGLTexture(Y,j,Be,ke,Y.invertY,!We,je,function(){return He(),!1},ne)},L)};pe?pe instanceof ArrayBuffer?be(new Uint8Array(pe)):ArrayBuffer.isView(pe)?be(pe):de&&de("Unable to load: only ArrayBuffer or ArrayBufferView is supported",null):this._loadFile(I,function(ye){return be(new Uint8Array(ye))},void 0,j?j.offlineProvider:void 0,!0,function(ye,Be){_e("Unable to load "+(ye&&ye.responseURL,Be))})}else{var Pe=function(ye){oe&&!G._doNotHandleContextLost&&(Y._buffer=ye),G._prepareWebGLTexture(Y,j,ye.width,ye.height,Y.invertY,V,!1,function(Be,ke,We){var je=G._gl,He=ye.width===Be&&ye.height===ke,qe=ee?G._getInternalFormat(ee):Z===".jpg"?je.RGB:je.RGBA;if(He)return je.texImage2D(je.TEXTURE_2D,0,qe,qe,je.UNSIGNED_BYTE,ye),!1;var Ge=G._caps.maxTextureSize;if(ye.width>Ge||ye.height>Ge||!G._supportsHardwareTextureRescaling)return G._prepareWorkingCanvas(),!(!G._workingCanvas||!G._workingContext)&&(G._workingCanvas.width=Be,G._workingCanvas.height=ke,G._workingContext.drawImage(ye,0,0,ye.width,ye.height,0,0,Be,ke),je.texImage2D(je.TEXTURE_2D,0,qe,qe,je.UNSIGNED_BYTE,G._workingCanvas),Y.width=Be,Y.height=ke,!1);var nt=new c.a(G,c.b.Temp);return G._bindTextureDirectly(je.TEXTURE_2D,nt,!0),je.texImage2D(je.TEXTURE_2D,0,qe,qe,je.UNSIGNED_BYTE,ye),G._rescaleTexture(nt,Y,j,qe,function(){G._releaseTexture(nt),G._bindTextureDirectly(je.TEXTURE_2D,Y,!0),We()}),!0},ne)};!Q||re?pe&&(pe.decoding||pe.close)?Pe(pe):N._FileToolsLoadImage(I,Pe,_e,j?j.offlineProvider:null,$):typeof pe=="string"||pe instanceof ArrayBuffer||ArrayBuffer.isView(pe)||pe instanceof Blob?N._FileToolsLoadImage(pe,Pe,_e,j?j.offlineProvider:null,$):pe&&Pe(pe)}return Y},N._FileToolsLoadImage=function(I,V,X,j,ne){throw x.a.WarnImport("FileTools")},N.prototype._rescaleTexture=function(I,V,X,j,ne){},N.prototype.createRawTexture=function(I,V,X,j,ne,te,de,pe,ae){throw ae===void 0&&(ae=m.a.TEXTURETYPE_UNSIGNED_INT),x.a.WarnImport("Engine.RawTexture")},N.prototype.createRawCubeTexture=function(I,V,X,j,ne,te,de,pe){throw x.a.WarnImport("Engine.RawTexture")},N.prototype.createRawTexture3D=function(I,V,X,j,ne,te,de,pe,ae,ee){throw ee===void 0&&(ee=m.a.TEXTURETYPE_UNSIGNED_INT),x.a.WarnImport("Engine.RawTexture")},N.prototype.createRawTexture2DArray=function(I,V,X,j,ne,te,de,pe,ae,ee){throw ee===void 0&&(ee=m.a.TEXTURETYPE_UNSIGNED_INT),x.a.WarnImport("Engine.RawTexture")},N.prototype._unpackFlipY=function(I){this._unpackFlipYCached!==I&&(this._gl.pixelStorei(this._gl.UNPACK_FLIP_Y_WEBGL,I?1:0),this.enableUnpackFlipYCached&&(this._unpackFlipYCached=I))},N.prototype._getUnpackAlignement=function(){return this._gl.getParameter(this._gl.UNPACK_ALIGNMENT)},N.prototype._getTextureTarget=function(I){return I.isCube?this._gl.TEXTURE_CUBE_MAP:I.is3D?this._gl.TEXTURE_3D:I.is2DArray||I.isMultiview?this._gl.TEXTURE_2D_ARRAY:this._gl.TEXTURE_2D},N.prototype.updateTextureSamplingMode=function(I,V,X){X===void 0&&(X=!1);var j=this._getTextureTarget(V),ne=this._getSamplingParameters(I,V.generateMipMaps||X);this._setTextureParameterInteger(j,this._gl.TEXTURE_MAG_FILTER,ne.mag,V),this._setTextureParameterInteger(j,this._gl.TEXTURE_MIN_FILTER,ne.min),X&&(V.generateMipMaps=!0,this._gl.generateMipmap(j)),this._bindTextureDirectly(j,null),V.samplingMode=I},N.prototype.updateTextureWrappingMode=function(I,V,X,j){X===void 0&&(X=null),j===void 0&&(j=null);var ne=this._getTextureTarget(I);V!==null&&(this._setTextureParameterInteger(ne,this._gl.TEXTURE_WRAP_S,this._getTextureWrapMode(V),I),I._cachedWrapU=V),X!==null&&(this._setTextureParameterInteger(ne,this._gl.TEXTURE_WRAP_T,this._getTextureWrapMode(X),I),I._cachedWrapV=X),(I.is2DArray||I.is3D)&&j!==null&&(this._setTextureParameterInteger(ne,this._gl.TEXTURE_WRAP_R,this._getTextureWrapMode(j),I),I._cachedWrapR=j),this._bindTextureDirectly(ne,null)},N.prototype._setupDepthStencilTexture=function(I,V,X,j,ne){var te=V.width||V,de=V.height||V,pe=V.layers||0;I.baseWidth=te,I.baseHeight=de,I.width=te,I.height=de,I.is2DArray=pe>0,I.depth=pe,I.isReady=!0,I.samples=1,I.generateMipMaps=!1,I._generateDepthBuffer=!0,I._generateStencilBuffer=X,I.samplingMode=j?m.a.TEXTURE_BILINEAR_SAMPLINGMODE:m.a.TEXTURE_NEAREST_SAMPLINGMODE,I.type=m.a.TEXTURETYPE_UNSIGNED_INT,I._comparisonFunction=ne;var ae=this._gl,ee=this._getTextureTarget(I),K=this._getSamplingParameters(I.samplingMode,!1);ae.texParameteri(ee,ae.TEXTURE_MAG_FILTER,K.mag),ae.texParameteri(ee,ae.TEXTURE_MIN_FILTER,K.min),ae.texParameteri(ee,ae.TEXTURE_WRAP_S,ae.CLAMP_TO_EDGE),ae.texParameteri(ee,ae.TEXTURE_WRAP_T,ae.CLAMP_TO_EDGE),ne===0?(ae.texParameteri(ee,ae.TEXTURE_COMPARE_FUNC,m.a.LEQUAL),ae.texParameteri(ee,ae.TEXTURE_COMPARE_MODE,ae.NONE)):(ae.texParameteri(ee,ae.TEXTURE_COMPARE_FUNC,ne),ae.texParameteri(ee,ae.TEXTURE_COMPARE_MODE,ae.COMPARE_REF_TO_TEXTURE))},N.prototype._uploadCompressedDataToTextureDirectly=function(I,V,X,j,ne,te,de){te===void 0&&(te=0),de===void 0&&(de=0);var pe=this._gl,ae=pe.TEXTURE_2D;I.isCube&&(ae=pe.TEXTURE_CUBE_MAP_POSITIVE_X+te),this._gl.compressedTexImage2D(ae,de,V,X,j,0,ne)},N.prototype._uploadDataToTextureDirectly=function(I,V,X,j,ne,te){X===void 0&&(X=0),j===void 0&&(j=0),te===void 0&&(te=!1);var de=this._gl,pe=this._getWebGLTextureType(I.type),ae=this._getInternalFormat(I.format),ee=ne===void 0?this._getRGBABufferInternalSizedFormat(I.type,I.format):this._getInternalFormat(ne);this._unpackFlipY(I.invertY);var K=de.TEXTURE_2D;I.isCube&&(K=de.TEXTURE_CUBE_MAP_POSITIVE_X+X);var $=Math.round(Math.log(I.width)*Math.LOG2E),L=Math.round(Math.log(I.height)*Math.LOG2E),G=te?I.width:Math.pow(2,Math.max($-j,0)),Q=te?I.height:Math.pow(2,Math.max(L-j,0));de.texImage2D(K,j,ee,G,Q,0,ae,pe,V)},N.prototype.updateTextureData=function(I,V,X,j,ne,te,de,pe){de===void 0&&(de=0),pe===void 0&&(pe=0);var ae=this._gl,ee=this._getWebGLTextureType(I.type),K=this._getInternalFormat(I.format);this._unpackFlipY(I.invertY);var $=ae.TEXTURE_2D;I.isCube&&($=ae.TEXTURE_CUBE_MAP_POSITIVE_X+de),ae.texSubImage2D($,pe,X,j,ne,te,K,ee,V)},N.prototype._uploadArrayBufferViewToTexture=function(I,V,X,j){X===void 0&&(X=0),j===void 0&&(j=0);var ne=this._gl,te=I.isCube?ne.TEXTURE_CUBE_MAP:ne.TEXTURE_2D;this._bindTextureDirectly(te,I,!0),this._uploadDataToTextureDirectly(I,V,X,j),this._bindTextureDirectly(te,null,!0)},N.prototype._prepareWebGLTextureContinuation=function(I,V,X,j,ne){var te=this._gl;if(te){var de=this._getSamplingParameters(ne,!X);te.texParameteri(te.TEXTURE_2D,te.TEXTURE_MAG_FILTER,de.mag),te.texParameteri(te.TEXTURE_2D,te.TEXTURE_MIN_FILTER,de.min),X||j||te.generateMipmap(te.TEXTURE_2D),this._bindTextureDirectly(te.TEXTURE_2D,null),V&&V._removePendingData(I),I.onLoadedObservable.notifyObservers(I),I.onLoadedObservable.clear()}},N.prototype._prepareWebGLTexture=function(I,V,X,j,ne,te,de,pe,ae){var ee=this;ae===void 0&&(ae=m.a.TEXTURE_TRILINEAR_SAMPLINGMODE);var K=this.getCaps().maxTextureSize,$=Math.min(K,this.needPOTTextures?N.GetExponentOfTwo(X,K):X),L=Math.min(K,this.needPOTTextures?N.GetExponentOfTwo(j,K):j),G=this._gl;G&&(I._webGLTexture?(this._bindTextureDirectly(G.TEXTURE_2D,I,!0),this._unpackFlipY(ne===void 0||!!ne),I.baseWidth=X,I.baseHeight=j,I.width=$,I.height=L,I.isReady=!0,pe($,L,function(){ee._prepareWebGLTextureContinuation(I,V,te,de,ae)})||this._prepareWebGLTextureContinuation(I,V,te,de,ae)):V&&V._removePendingData(I))},N.prototype._setupFramebufferDepthAttachments=function(I,V,X,j,ne){ne===void 0&&(ne=1);var te=this._gl;if(I&&V)return this._getDepthStencilBuffer(X,j,ne,te.DEPTH_STENCIL,te.DEPTH24_STENCIL8,te.DEPTH_STENCIL_ATTACHMENT);if(V){var de=te.DEPTH_COMPONENT16;return this._webGLVersion>1&&(de=te.DEPTH_COMPONENT32F),this._getDepthStencilBuffer(X,j,ne,de,de,te.DEPTH_ATTACHMENT)}return I?this._getDepthStencilBuffer(X,j,ne,te.STENCIL_INDEX8,te.STENCIL_INDEX8,te.STENCIL_ATTACHMENT):null},N.prototype._releaseFramebufferObjects=function(I){var V=this._gl;I._framebuffer&&(V.deleteFramebuffer(I._framebuffer),I._framebuffer=null),I._depthStencilBuffer&&(V.deleteRenderbuffer(I._depthStencilBuffer),I._depthStencilBuffer=null),I._MSAAFramebuffer&&(V.deleteFramebuffer(I._MSAAFramebuffer),I._MSAAFramebuffer=null),I._MSAARenderBuffer&&(V.deleteRenderbuffer(I._MSAARenderBuffer),I._MSAARenderBuffer=null)},N.prototype._releaseTexture=function(I){this._releaseFramebufferObjects(I),this._deleteTexture(I._webGLTexture),this.unbindAllTextures();var V=this._internalTexturesCache.indexOf(I);V!==-1&&this._internalTexturesCache.splice(V,1),I._lodTextureHigh&&I._lodTextureHigh.dispose(),I._lodTextureMid&&I._lodTextureMid.dispose(),I._lodTextureLow&&I._lodTextureLow.dispose(),I._irradianceTexture&&I._irradianceTexture.dispose()},N.prototype._deleteTexture=function(I){this._gl.deleteTexture(I)},N.prototype._setProgram=function(I){this._currentProgram!==I&&(this._gl.useProgram(I),this._currentProgram=I)},N.prototype.bindSamplers=function(I){var V=I.getPipelineContext();this._setProgram(V.program);for(var X=I.getSamplers(),j=0;j<X.length;j++){var ne=I.getUniform(X[j]);ne&&(this._boundUniforms[j]=ne)}this._currentEffect=null},N.prototype._activateCurrentTexture=function(){this._currentTextureChannel!==this._activeChannel&&(this._gl.activeTexture(this._gl.TEXTURE0+this._activeChannel),this._currentTextureChannel=this._activeChannel)},N.prototype._bindTextureDirectly=function(I,V,X,j){X===void 0&&(X=!1),j===void 0&&(j=!1);var ne=!1,te=V&&V._associatedChannel>-1;return X&&te&&(this._activeChannel=V._associatedChannel),this._boundTexturesCache[this._activeChannel]!==V||j?(this._activateCurrentTexture(),V&&V.isMultiview?this._gl.bindTexture(I,V?V._colorTextureArray:null):this._gl.bindTexture(I,V?V._webGLTexture:null),this._boundTexturesCache[this._activeChannel]=V,V&&(V._associatedChannel=this._activeChannel)):X&&(ne=!0,this._activateCurrentTexture()),te&&!X&&this._bindSamplerUniformToChannel(V._associatedChannel,this._activeChannel),ne},N.prototype._bindTexture=function(I,V){if(I!==void 0){V&&(V._associatedChannel=I),this._activeChannel=I;var X=V?this._getTextureTarget(V):this._gl.TEXTURE_2D;this._bindTextureDirectly(X,V)}},N.prototype.unbindAllTextures=function(){for(var I=0;I<this._maxSimultaneousTextures;I++)this._activeChannel=I,this._bindTextureDirectly(this._gl.TEXTURE_2D,null),this._bindTextureDirectly(this._gl.TEXTURE_CUBE_MAP,null),this.webGLVersion>1&&(this._bindTextureDirectly(this._gl.TEXTURE_3D,null),this._bindTextureDirectly(this._gl.TEXTURE_2D_ARRAY,null))},N.prototype.setTexture=function(I,V,X){I!==void 0&&(V&&(this._boundUniforms[I]=V),this._setTexture(I,X))},N.prototype._bindSamplerUniformToChannel=function(I,V){var X=this._boundUniforms[I];X&&X._currentState!==V&&(this._gl.uniform1i(X,V),X._currentState=V)},N.prototype._getTextureWrapMode=function(I){switch(I){case m.a.TEXTURE_WRAP_ADDRESSMODE:return this._gl.REPEAT;case m.a.TEXTURE_CLAMP_ADDRESSMODE:return this._gl.CLAMP_TO_EDGE;case m.a.TEXTURE_MIRROR_ADDRESSMODE:return this._gl.MIRRORED_REPEAT}return this._gl.REPEAT},N.prototype._setTexture=function(I,V,X,j){if(X===void 0&&(X=!1),j===void 0&&(j=!1),!V)return this._boundTexturesCache[I]!=null&&(this._activeChannel=I,this._bindTextureDirectly(this._gl.TEXTURE_2D,null),this._bindTextureDirectly(this._gl.TEXTURE_CUBE_MAP,null),this.webGLVersion>1&&(this._bindTextureDirectly(this._gl.TEXTURE_3D,null),this._bindTextureDirectly(this._gl.TEXTURE_2D_ARRAY,null))),!1;if(V.video)this._activeChannel=I,V.update();else if(V.delayLoadState===m.a.DELAYLOADSTATE_NOTLOADED)return V.delayLoad(),!1;var ne;ne=j?V.depthStencilTexture:V.isReady()?V.getInternalTexture():V.isCube?this.emptyCubeTexture:V.is3D?this.emptyTexture3D:V.is2DArray?this.emptyTexture2DArray:this.emptyTexture,!X&&ne&&(ne._associatedChannel=I);var te=!0;this._boundTexturesCache[I]===ne&&(X||this._bindSamplerUniformToChannel(ne._associatedChannel,I),te=!1),this._activeChannel=I;var de=this._getTextureTarget(ne);if(te&&this._bindTextureDirectly(de,ne,X),ne&&!ne.isMultiview){if(ne.isCube&&ne._cachedCoordinatesMode!==V.coordinatesMode){ne._cachedCoordinatesMode=V.coordinatesMode;var pe=V.coordinatesMode!==m.a.TEXTURE_CUBIC_MODE&&V.coordinatesMode!==m.a.TEXTURE_SKYBOX_MODE?m.a.TEXTURE_WRAP_ADDRESSMODE:m.a.TEXTURE_CLAMP_ADDRESSMODE;V.wrapU=pe,V.wrapV=pe}ne._cachedWrapU!==V.wrapU&&(ne._cachedWrapU=V.wrapU,this._setTextureParameterInteger(de,this._gl.TEXTURE_WRAP_S,this._getTextureWrapMode(V.wrapU),ne)),ne._cachedWrapV!==V.wrapV&&(ne._cachedWrapV=V.wrapV,this._setTextureParameterInteger(de,this._gl.TEXTURE_WRAP_T,this._getTextureWrapMode(V.wrapV),ne)),ne.is3D&&ne._cachedWrapR!==V.wrapR&&(ne._cachedWrapR=V.wrapR,this._setTextureParameterInteger(de,this._gl.TEXTURE_WRAP_R,this._getTextureWrapMode(V.wrapR),ne)),this._setAnisotropicLevel(de,ne,V.anisotropicFilteringLevel)}return!0},N.prototype.setTextureArray=function(I,V,X){if(I!==void 0&&V){this._textureUnits&&this._textureUnits.length===X.length||(this._textureUnits=new Int32Array(X.length));for(var j=0;j<X.length;j++){var ne=X[j].getInternalTexture();ne?(this._textureUnits[j]=I+j,ne._associatedChannel=I+j):this._textureUnits[j]=-1}this._gl.uniform1iv(V,this._textureUnits);for(var te=0;te<X.length;te++)this._setTexture(this._textureUnits[te],X[te],!0)}},N.prototype._setAnisotropicLevel=function(I,V,X){var j=this._caps.textureAnisotropicFilterExtension;V.samplingMode!==m.a.TEXTURE_LINEAR_LINEAR_MIPNEAREST&&V.samplingMode!==m.a.TEXTURE_LINEAR_LINEAR_MIPLINEAR&&V.samplingMode!==m.a.TEXTURE_LINEAR_LINEAR&&(X=1),j&&V._cachedAnisotropicFilteringLevel!==X&&(this._setTextureParameterFloat(I,j.TEXTURE_MAX_ANISOTROPY_EXT,Math.min(X,this._caps.maxAnisotropy),V),V._cachedAnisotropicFilteringLevel=X)},N.prototype._setTextureParameterFloat=function(I,V,X,j){this._bindTextureDirectly(I,j,!0,!0),this._gl.texParameterf(I,V,X)},N.prototype._setTextureParameterInteger=function(I,V,X,j){j&&this._bindTextureDirectly(I,j,!0,!0),this._gl.texParameteri(I,V,X)},N.prototype.unbindAllAttributes=function(){if(this._mustWipeVertexAttributes){this._mustWipeVertexAttributes=!1;for(var I=0;I<this._caps.maxVertexAttribs;I++)this.disableAttributeByIndex(I)}else{I=0;for(var V=this._vertexAttribArraysEnabled.length;I<V;I++)I>=this._caps.maxVertexAttribs||!this._vertexAttribArraysEnabled[I]||this.disableAttributeByIndex(I)}},N.prototype.releaseEffects=function(){for(var I in this._compiledEffects){var V=this._compiledEffects[I].getPipelineContext();this._deletePipelineContext(V)}this._compiledEffects={}},N.prototype.dispose=function(){this.stopRenderLoop(),this.onBeforeTextureInitObservable&&this.onBeforeTextureInitObservable.clear(),this._emptyTexture&&(this._releaseTexture(this._emptyTexture),this._emptyTexture=null),this._emptyCubeTexture&&(this._releaseTexture(this._emptyCubeTexture),this._emptyCubeTexture=null),this._dummyFramebuffer&&this._gl.deleteFramebuffer(this._dummyFramebuffer),this.releaseEffects(),this.unbindAllAttributes(),this._boundUniforms=[],A.a.IsWindowObjectExist()&&this._renderingCanvas&&(this._doNotHandleContextLost||(this._renderingCanvas.removeEventListener("webglcontextlost",this._onContextLost),this._renderingCanvas.removeEventListener("webglcontextrestored",this._onContextRestored))),this._workingCanvas=null,this._workingContext=null,this._currentBufferPointers=[],this._renderingCanvas=null,this._currentProgram=null,this._boundRenderFunction=null,_.a.ResetCache();for(var I=0,V=this._activeRequests;I<V.length;I++)V[I].abort()},N.prototype.attachContextLostEvent=function(I){this._renderingCanvas&&this._renderingCanvas.addEventListener("webglcontextlost",I,!1)},N.prototype.attachContextRestoredEvent=function(I){this._renderingCanvas&&this._renderingCanvas.addEventListener("webglcontextrestored",I,!1)},N.prototype.getError=function(){return this._gl.getError()},N.prototype._canRenderToFloatFramebuffer=function(){return this._webGLVersion>1?this._caps.colorBufferFloat:this._canRenderToFramebuffer(m.a.TEXTURETYPE_FLOAT)},N.prototype._canRenderToHalfFloatFramebuffer=function(){return this._webGLVersion>1?this._caps.colorBufferFloat:this._canRenderToFramebuffer(m.a.TEXTURETYPE_HALF_FLOAT)},N.prototype._canRenderToFramebuffer=function(I){for(var V=this._gl;V.getError()!==V.NO_ERROR;);var X=!0,j=V.createTexture();V.bindTexture(V.TEXTURE_2D,j),V.texImage2D(V.TEXTURE_2D,0,this._getRGBABufferInternalSizedFormat(I),1,1,0,V.RGBA,this._getWebGLTextureType(I),null),V.texParameteri(V.TEXTURE_2D,V.TEXTURE_MIN_FILTER,V.NEAREST),V.texParameteri(V.TEXTURE_2D,V.TEXTURE_MAG_FILTER,V.NEAREST);var ne=V.createFramebuffer();V.bindFramebuffer(V.FRAMEBUFFER,ne),V.framebufferTexture2D(V.FRAMEBUFFER,V.COLOR_ATTACHMENT0,V.TEXTURE_2D,j,0);var te=V.checkFramebufferStatus(V.FRAMEBUFFER);if((X=(X=X&&te===V.FRAMEBUFFER_COMPLETE)&&V.getError()===V.NO_ERROR)&&(V.clear(V.COLOR_BUFFER_BIT),X=X&&V.getError()===V.NO_ERROR),X){V.bindFramebuffer(V.FRAMEBUFFER,null);var de=V.RGBA,pe=V.UNSIGNED_BYTE,ae=new Uint8Array(4);V.readPixels(0,0,1,1,de,pe,ae),X=X&&V.getError()===V.NO_ERROR}for(V.deleteTexture(j),V.deleteFramebuffer(ne),V.bindFramebuffer(V.FRAMEBUFFER,null);!X&&V.getError()!==V.NO_ERROR;);return X},N.prototype._getWebGLTextureType=function(I){if(this._webGLVersion===1){switch(I){case m.a.TEXTURETYPE_FLOAT:return this._gl.FLOAT;case m.a.TEXTURETYPE_HALF_FLOAT:return this._gl.HALF_FLOAT_OES;case m.a.TEXTURETYPE_UNSIGNED_BYTE:return this._gl.UNSIGNED_BYTE;case m.a.TEXTURETYPE_UNSIGNED_SHORT_4_4_4_4:return this._gl.UNSIGNED_SHORT_4_4_4_4;case m.a.TEXTURETYPE_UNSIGNED_SHORT_5_5_5_1:return this._gl.UNSIGNED_SHORT_5_5_5_1;case m.a.TEXTURETYPE_UNSIGNED_SHORT_5_6_5:return this._gl.UNSIGNED_SHORT_5_6_5}return this._gl.UNSIGNED_BYTE}switch(I){case m.a.TEXTURETYPE_BYTE:return this._gl.BYTE;case m.a.TEXTURETYPE_UNSIGNED_BYTE:return this._gl.UNSIGNED_BYTE;case m.a.TEXTURETYPE_SHORT:return this._gl.SHORT;case m.a.TEXTURETYPE_UNSIGNED_SHORT:return this._gl.UNSIGNED_SHORT;case m.a.TEXTURETYPE_INT:return this._gl.INT;case m.a.TEXTURETYPE_UNSIGNED_INTEGER:return this._gl.UNSIGNED_INT;case m.a.TEXTURETYPE_FLOAT:return this._gl.FLOAT;case m.a.TEXTURETYPE_HALF_FLOAT:return this._gl.HALF_FLOAT;case m.a.TEXTURETYPE_UNSIGNED_SHORT_4_4_4_4:return this._gl.UNSIGNED_SHORT_4_4_4_4;case m.a.TEXTURETYPE_UNSIGNED_SHORT_5_5_5_1:return this._gl.UNSIGNED_SHORT_5_5_5_1;case m.a.TEXTURETYPE_UNSIGNED_SHORT_5_6_5:return this._gl.UNSIGNED_SHORT_5_6_5;case m.a.TEXTURETYPE_UNSIGNED_INT_2_10_10_10_REV:return this._gl.UNSIGNED_INT_2_10_10_10_REV;case m.a.TEXTURETYPE_UNSIGNED_INT_24_8:return this._gl.UNSIGNED_INT_24_8;case m.a.TEXTURETYPE_UNSIGNED_INT_10F_11F_11F_REV:return this._gl.UNSIGNED_INT_10F_11F_11F_REV;case m.a.TEXTURETYPE_UNSIGNED_INT_5_9_9_9_REV:return this._gl.UNSIGNED_INT_5_9_9_9_REV;case m.a.TEXTURETYPE_FLOAT_32_UNSIGNED_INT_24_8_REV:return this._gl.FLOAT_32_UNSIGNED_INT_24_8_REV}return this._gl.UNSIGNED_BYTE},N.prototype._getInternalFormat=function(I){var V=this._gl.RGBA;switch(I){case m.a.TEXTUREFORMAT_ALPHA:V=this._gl.ALPHA;break;case m.a.TEXTUREFORMAT_LUMINANCE:V=this._gl.LUMINANCE;break;case m.a.TEXTUREFORMAT_LUMINANCE_ALPHA:V=this._gl.LUMINANCE_ALPHA;break;case m.a.TEXTUREFORMAT_RED:V=this._gl.RED;break;case m.a.TEXTUREFORMAT_RG:V=this._gl.RG;break;case m.a.TEXTUREFORMAT_RGB:V=this._gl.RGB;break;case m.a.TEXTUREFORMAT_RGBA:V=this._gl.RGBA}if(this._webGLVersion>1)switch(I){case m.a.TEXTUREFORMAT_RED_INTEGER:V=this._gl.RED_INTEGER;break;case m.a.TEXTUREFORMAT_RG_INTEGER:V=this._gl.RG_INTEGER;break;case m.a.TEXTUREFORMAT_RGB_INTEGER:V=this._gl.RGB_INTEGER;break;case m.a.TEXTUREFORMAT_RGBA_INTEGER:V=this._gl.RGBA_INTEGER}return V},N.prototype._getRGBABufferInternalSizedFormat=function(I,V){if(this._webGLVersion===1){if(V!==void 0)switch(V){case m.a.TEXTUREFORMAT_ALPHA:return this._gl.ALPHA;case m.a.TEXTUREFORMAT_LUMINANCE:return this._gl.LUMINANCE;case m.a.TEXTUREFORMAT_LUMINANCE_ALPHA:return this._gl.LUMINANCE_ALPHA;case m.a.TEXTUREFORMAT_RGB:return this._gl.RGB}return this._gl.RGBA}switch(I){case m.a.TEXTURETYPE_BYTE:switch(V){case m.a.TEXTUREFORMAT_RED:return this._gl.R8_SNORM;case m.a.TEXTUREFORMAT_RG:return this._gl.RG8_SNORM;case m.a.TEXTUREFORMAT_RGB:return this._gl.RGB8_SNORM;case m.a.TEXTUREFORMAT_RED_INTEGER:return this._gl.R8I;case m.a.TEXTUREFORMAT_RG_INTEGER:return this._gl.RG8I;case m.a.TEXTUREFORMAT_RGB_INTEGER:return this._gl.RGB8I;case m.a.TEXTUREFORMAT_RGBA_INTEGER:return this._gl.RGBA8I;default:return this._gl.RGBA8_SNORM}case m.a.TEXTURETYPE_UNSIGNED_BYTE:switch(V){case m.a.TEXTUREFORMAT_RED:return this._gl.R8;case m.a.TEXTUREFORMAT_RG:return this._gl.RG8;case m.a.TEXTUREFORMAT_RGB:return this._gl.RGB8;case m.a.TEXTUREFORMAT_RGBA:return this._gl.RGBA8;case m.a.TEXTUREFORMAT_RED_INTEGER:return this._gl.R8UI;case m.a.TEXTUREFORMAT_RG_INTEGER:return this._gl.RG8UI;case m.a.TEXTUREFORMAT_RGB_INTEGER:return this._gl.RGB8UI;case m.a.TEXTUREFORMAT_RGBA_INTEGER:return this._gl.RGBA8UI;case m.a.TEXTUREFORMAT_ALPHA:return this._gl.ALPHA;case m.a.TEXTUREFORMAT_LUMINANCE:return this._gl.LUMINANCE;case m.a.TEXTUREFORMAT_LUMINANCE_ALPHA:return this._gl.LUMINANCE_ALPHA;default:return this._gl.RGBA8}case m.a.TEXTURETYPE_SHORT:switch(V){case m.a.TEXTUREFORMAT_RED_INTEGER:return this._gl.R16I;case m.a.TEXTUREFORMAT_RG_INTEGER:return this._gl.RG16I;case m.a.TEXTUREFORMAT_RGB_INTEGER:return this._gl.RGB16I;case m.a.TEXTUREFORMAT_RGBA_INTEGER:default:return this._gl.RGBA16I}case m.a.TEXTURETYPE_UNSIGNED_SHORT:switch(V){case m.a.TEXTUREFORMAT_RED_INTEGER:return this._gl.R16UI;case m.a.TEXTUREFORMAT_RG_INTEGER:return this._gl.RG16UI;case m.a.TEXTUREFORMAT_RGB_INTEGER:return this._gl.RGB16UI;case m.a.TEXTUREFORMAT_RGBA_INTEGER:default:return this._gl.RGBA16UI}case m.a.TEXTURETYPE_INT:switch(V){case m.a.TEXTUREFORMAT_RED_INTEGER:return this._gl.R32I;case m.a.TEXTUREFORMAT_RG_INTEGER:return this._gl.RG32I;case m.a.TEXTUREFORMAT_RGB_INTEGER:return this._gl.RGB32I;case m.a.TEXTUREFORMAT_RGBA_INTEGER:default:return this._gl.RGBA32I}case m.a.TEXTURETYPE_UNSIGNED_INTEGER:switch(V){case m.a.TEXTUREFORMAT_RED_INTEGER:return this._gl.R32UI;case m.a.TEXTUREFORMAT_RG_INTEGER:return this._gl.RG32UI;case m.a.TEXTUREFORMAT_RGB_INTEGER:return this._gl.RGB32UI;case m.a.TEXTUREFORMAT_RGBA_INTEGER:default:return this._gl.RGBA32UI}case m.a.TEXTURETYPE_FLOAT:switch(V){case m.a.TEXTUREFORMAT_RED:return this._gl.R32F;case m.a.TEXTUREFORMAT_RG:return this._gl.RG32F;case m.a.TEXTUREFORMAT_RGB:return this._gl.RGB32F;case m.a.TEXTUREFORMAT_RGBA:default:return this._gl.RGBA32F}case m.a.TEXTURETYPE_HALF_FLOAT:switch(V){case m.a.TEXTUREFORMAT_RED:return this._gl.R16F;case m.a.TEXTUREFORMAT_RG:return this._gl.RG16F;case m.a.TEXTUREFORMAT_RGB:return this._gl.RGB16F;case m.a.TEXTUREFORMAT_RGBA:default:return this._gl.RGBA16F}case m.a.TEXTURETYPE_UNSIGNED_SHORT_5_6_5:return this._gl.RGB565;case m.a.TEXTURETYPE_UNSIGNED_INT_10F_11F_11F_REV:return this._gl.R11F_G11F_B10F;case m.a.TEXTURETYPE_UNSIGNED_INT_5_9_9_9_REV:return this._gl.RGB9_E5;case m.a.TEXTURETYPE_UNSIGNED_SHORT_4_4_4_4:return this._gl.RGBA4;case m.a.TEXTURETYPE_UNSIGNED_SHORT_5_5_5_1:return this._gl.RGB5_A1;case m.a.TEXTURETYPE_UNSIGNED_INT_2_10_10_10_REV:switch(V){case m.a.TEXTUREFORMAT_RGBA:return this._gl.RGB10_A2;case m.a.TEXTUREFORMAT_RGBA_INTEGER:return this._gl.RGB10_A2UI;default:return this._gl.RGB10_A2}}return this._gl.RGBA8},N.prototype._getRGBAMultiSampleBufferFormat=function(I){return I===m.a.TEXTURETYPE_FLOAT?this._gl.RGBA32F:I===m.a.TEXTURETYPE_HALF_FLOAT?this._gl.RGBA16F:this._gl.RGBA8},N.prototype._loadFile=function(I,V,X,j,ne,te){var de=this,pe=N._FileToolsLoadFile(I,V,X,j,ne,te);return this._activeRequests.push(pe),pe.onCompleteObservable.add(function(ae){de._activeRequests.splice(de._activeRequests.indexOf(ae),1)}),pe},N._FileToolsLoadFile=function(I,V,X,j,ne,te){throw x.a.WarnImport("FileTools")},N.prototype.readPixels=function(I,V,X,j,ne){ne===void 0&&(ne=!0);var te=ne?4:3,de=ne?this._gl.RGBA:this._gl.RGB,pe=new Uint8Array(j*X*te);return this._gl.readPixels(I,V,X,j,de,this._gl.UNSIGNED_BYTE,pe),pe},Object.defineProperty(N,"IsSupported",{get:function(){return this.isSupported()},enumerable:!1,configurable:!0}),N.isSupported=function(){if(this._HasMajorPerformanceCaveat!==null)return!this._HasMajorPerformanceCaveat;if(this._IsSupported===null)try{var I=v.a.CreateCanvas(1,1),V=I.getContext("webgl")||I.getContext("experimental-webgl");this._IsSupported=V!=null&&!!window.WebGLRenderingContext}catch{this._IsSupported=!1}return this._IsSupported},Object.defineProperty(N,"HasMajorPerformanceCaveat",{get:function(){if(this._HasMajorPerformanceCaveat===null)try{var I=v.a.CreateCanvas(1,1),V=I.getContext("webgl",{failIfMajorPerformanceCaveat:!0})||I.getContext("experimental-webgl",{failIfMajorPerformanceCaveat:!0});this._HasMajorPerformanceCaveat=!V}catch{this._HasMajorPerformanceCaveat=!1}return this._HasMajorPerformanceCaveat},enumerable:!1,configurable:!0}),N.CeilingPOT=function(I){return I--,I|=I>>1,I|=I>>2,I|=I>>4,I|=I>>8,I|=I>>16,++I},N.FloorPOT=function(I){return I|=I>>1,I|=I>>2,I|=I>>4,I|=I>>8,(I|=I>>16)-(I>>1)},N.NearestPOT=function(I){var V=N.CeilingPOT(I),X=N.FloorPOT(I);return V-I>I-X?X:V},N.GetExponentOfTwo=function(I,V,X){var j;switch(X===void 0&&(X=m.a.SCALEMODE_NEAREST),X){case m.a.SCALEMODE_FLOOR:j=N.FloorPOT(I);break;case m.a.SCALEMODE_NEAREST:j=N.NearestPOT(I);break;case m.a.SCALEMODE_CEILING:default:j=N.CeilingPOT(I)}return Math.min(j,V)},N.QueueNewFrame=function(I,V){return A.a.IsWindowObjectExist()?(V||(V=window),V.requestPostAnimationFrame?V.requestPostAnimationFrame(I):V.requestAnimationFrame?V.requestAnimationFrame(I):V.msRequestAnimationFrame?V.msRequestAnimationFrame(I):V.webkitRequestAnimationFrame?V.webkitRequestAnimationFrame(I):V.mozRequestAnimationFrame?V.mozRequestAnimationFrame(I):V.oRequestAnimationFrame?V.oRequestAnimationFrame(I):window.setTimeout(I,16)):typeof requestAnimationFrame<"u"?requestAnimationFrame(I):setTimeout(I,16)},N.prototype.getHostDocument=function(){return this._renderingCanvas&&this._renderingCanvas.ownerDocument?this._renderingCanvas.ownerDocument:document},N.ExceptionList=[{key:"Chrome/63.0",capture:"63\\.0\\.3239\\.(\\d+)",captureConstraint:108,targets:["uniformBuffer"]},{key:"Firefox/58",capture:null,captureConstraint:null,targets:["uniformBuffer"]},{key:"Firefox/59",capture:null,captureConstraint:null,targets:["uniformBuffer"]},{key:"Chrome/72.+?Mobile",capture:null,captureConstraint:null,targets:["vao"]},{key:"Chrome/73.+?Mobile",capture:null,captureConstraint:null,targets:["vao"]},{key:"Chrome/74.+?Mobile",capture:null,captureConstraint:null,targets:["vao"]},{key:"Mac OS.+Chrome/71",capture:null,captureConstraint:null,targets:["vao"]},{key:"Mac OS.+Chrome/72",capture:null,captureConstraint:null,targets:["vao"]}],N._TextureLoaders=[],N.CollisionsEpsilon=.001,N._IsSupported=null,N._HasMajorPerformanceCaveat=null,N}()},function(Me,y,f){f.d(y,"b",function(){return U}),f.d(y,"a",function(){return R});var U,_=f(6),x=f(102),u=f(2),M=f(21);(function(C){C[C.Unknown=0]="Unknown",C[C.Url=1]="Url",C[C.Temp=2]="Temp",C[C.Raw=3]="Raw",C[C.Dynamic=4]="Dynamic",C[C.RenderTarget=5]="RenderTarget",C[C.MultiRenderTarget=6]="MultiRenderTarget",C[C.Cube=7]="Cube",C[C.CubeRaw=8]="CubeRaw",C[C.CubePrefiltered=9]="CubePrefiltered",C[C.Raw3D=10]="Raw3D",C[C.Raw2DArray=11]="Raw2DArray",C[C.Depth=12]="Depth",C[C.CubeRawRGBD=13]="CubeRawRGBD"})(U||(U={}));var R=function(){function C(m,c,T){T===void 0&&(T=!1),this.isReady=!1,this.isCube=!1,this.is3D=!1,this.is2DArray=!1,this.isMultiview=!1,this.url="",this.samplingMode=-1,this.generateMipMaps=!1,this.samples=0,this.type=-1,this.format=-1,this.onLoadedObservable=new _.c,this.width=0,this.height=0,this.depth=0,this.baseWidth=0,this.baseHeight=0,this.baseDepth=0,this.invertY=!1,this._invertVScale=!1,this._associatedChannel=-1,this._source=U.Unknown,this._buffer=null,this._bufferView=null,this._bufferViewArray=null,this._bufferViewArrayArray=null,this._size=0,this._extension="",this._files=null,this._workingCanvas=null,this._workingContext=null,this._framebuffer=null,this._depthStencilBuffer=null,this._MSAAFramebuffer=null,this._MSAARenderBuffer=null,this._attachments=null,this._textureArray=null,this._cachedCoordinatesMode=null,this._cachedWrapU=null,this._cachedWrapV=null,this._cachedWrapR=null,this._cachedAnisotropicFilteringLevel=null,this._isDisabled=!1,this._compression=null,this._generateStencilBuffer=!1,this._generateDepthBuffer=!1,this._comparisonFunction=0,this._sphericalPolynomial=null,this._lodGenerationScale=0,this._lodGenerationOffset=0,this._colorTextureArray=null,this._depthStencilTextureArray=null,this._lodTextureHigh=null,this._lodTextureMid=null,this._lodTextureLow=null,this._isRGBD=!1,this._linearSpecularLOD=!1,this._irradianceTexture=null,this._webGLTexture=null,this._references=1,this._gammaSpace=null,this._engine=m,this._source=c,T||(this._webGLTexture=m._createTexture())}return C.prototype.getEngine=function(){return this._engine},Object.defineProperty(C.prototype,"source",{get:function(){return this._source},enumerable:!1,configurable:!0}),C.prototype.incrementReferences=function(){this._references++},C.prototype.updateSize=function(m,c,T){T===void 0&&(T=1),this.width=m,this.height=c,this.depth=T,this.baseWidth=m,this.baseHeight=c,this.baseDepth=T,this._size=m*c*T},C.prototype._rebuild=function(){var m,c,T=this;switch(this.isReady=!1,this._cachedCoordinatesMode=null,this._cachedWrapU=null,this._cachedWrapV=null,this._cachedAnisotropicFilteringLevel=null,this.source){case U.Temp:return;case U.Url:return void(c=this._engine.createTexture((m=this._originalUrl)!==null&&m!==void 0?m:this.url,!this.generateMipMaps,this.invertY,null,this.samplingMode,function(){c._swapAndDie(T),T.isReady=!0},null,this._buffer,void 0,this.format));case U.Raw:return(c=this._engine.createRawTexture(this._bufferView,this.baseWidth,this.baseHeight,this.format,this.generateMipMaps,this.invertY,this.samplingMode,this._compression))._swapAndDie(this),void(this.isReady=!0);case U.Raw3D:return(c=this._engine.createRawTexture3D(this._bufferView,this.baseWidth,this.baseHeight,this.baseDepth,this.format,this.generateMipMaps,this.invertY,this.samplingMode,this._compression))._swapAndDie(this),void(this.isReady=!0);case U.Raw2DArray:return(c=this._engine.createRawTexture2DArray(this._bufferView,this.baseWidth,this.baseHeight,this.baseDepth,this.format,this.generateMipMaps,this.invertY,this.samplingMode,this._compression))._swapAndDie(this),void(this.isReady=!0);case U.Dynamic:return(c=this._engine.createDynamicTexture(this.baseWidth,this.baseHeight,this.generateMipMaps,this.samplingMode))._swapAndDie(this),void this._engine.updateDynamicTexture(this,this._engine.getRenderingCanvas(),this.invertY,void 0,void 0,!0);case U.RenderTarget:var A=new x.a;if(A.generateDepthBuffer=this._generateDepthBuffer,A.generateMipMaps=this.generateMipMaps,A.generateStencilBuffer=this._generateStencilBuffer,A.samplingMode=this.samplingMode,A.type=this.type,this.isCube)c=this._engine.createRenderTargetCubeTexture(this.width,A);else{var S={width:this.width,height:this.height,layers:this.is2DArray?this.depth:void 0};c=this._engine.createRenderTargetTexture(S,A)}return c._swapAndDie(this),void(this.isReady=!0);case U.Depth:var g={bilinearFiltering:this.samplingMode!==u.a.TEXTURE_BILINEAR_SAMPLINGMODE,comparisonFunction:this._comparisonFunction,generateStencil:this._generateStencilBuffer,isCube:this.isCube},l={width:this.width,height:this.height,layers:this.is2DArray?this.depth:void 0};return(c=this._engine.createDepthStencilTexture(l,g))._swapAndDie(this),void(this.isReady=!0);case U.Cube:return void(c=this._engine.createCubeTexture(this.url,null,this._files,!this.generateMipMaps,function(){c._swapAndDie(T),T.isReady=!0},null,this.format,this._extension));case U.CubeRaw:return(c=this._engine.createRawCubeTexture(this._bufferViewArray,this.width,this.format,this.type,this.generateMipMaps,this.invertY,this.samplingMode,this._compression))._swapAndDie(this),void(this.isReady=!0);case U.CubeRawRGBD:return c=this._engine.createRawCubeTexture(null,this.width,this.format,this.type,this.generateMipMaps,this.invertY,this.samplingMode,this._compression),void C._UpdateRGBDAsync(c,this._bufferViewArrayArray,this._sphericalPolynomial,this._lodGenerationScale,this._lodGenerationOffset).then(function(){c._swapAndDie(T),T.isReady=!0});case U.CubePrefiltered:return void((c=this._engine.createPrefilteredCubeTexture(this.url,null,this._lodGenerationScale,this._lodGenerationOffset,function(h){h&&h._swapAndDie(T),T.isReady=!0},null,this.format,this._extension))._sphericalPolynomial=this._sphericalPolynomial)}},C.prototype._swapAndDie=function(m){m._webGLTexture=this._webGLTexture,m._isRGBD=this._isRGBD,this._framebuffer&&(m._framebuffer=this._framebuffer),this._depthStencilBuffer&&(m._depthStencilBuffer=this._depthStencilBuffer),m._depthStencilTexture=this._depthStencilTexture,this._lodTextureHigh&&(m._lodTextureHigh&&m._lodTextureHigh.dispose(),m._lodTextureHigh=this._lodTextureHigh),this._lodTextureMid&&(m._lodTextureMid&&m._lodTextureMid.dispose(),m._lodTextureMid=this._lodTextureMid),this._lodTextureLow&&(m._lodTextureLow&&m._lodTextureLow.dispose(),m._lodTextureLow=this._lodTextureLow),this._irradianceTexture&&(m._irradianceTexture&&m._irradianceTexture.dispose(),m._irradianceTexture=this._irradianceTexture);var c,T=this._engine.getLoadedTexturesCache();(c=T.indexOf(this))!==-1&&T.splice(c,1),(c=T.indexOf(m))===-1&&T.push(m)},C.prototype.dispose=function(){this._webGLTexture&&(this._references--,this._references===0&&(this._engine._releaseTexture(this),this._webGLTexture=null))},C._UpdateRGBDAsync=function(m,c,T,A,S){throw M.a.WarnImport("environmentTextureTools")},C}()},function(Me,y,f){f.d(y,"b",function(){return U}),f.d(y,"c",function(){return _}),f.d(y,"a",function(){return x});var U=1/2.2,_=2.2,x=.001},function(Me,y,f){f.d(y,"a",function(){return C});var U=f(1),_=f(0),x=f(3),u=f(6),M=f(22),R=f(21),C=function(){function m(c,T){T===void 0&&(T=null),this.state="",this.metadata=null,this.reservedDataStore=null,this._doNotSerialize=!1,this._isDisposed=!1,this.animations=new Array,this._ranges={},this.onReady=null,this._isEnabled=!0,this._isParentEnabled=!0,this._isReady=!0,this._currentRenderId=-1,this._parentUpdateId=-1,this._childUpdateId=-1,this._waitingParentId=null,this._cache={},this._parentNode=null,this._children=null,this._worldMatrix=_.a.Identity(),this._worldMatrixDeterminant=0,this._worldMatrixDeterminantIsDirty=!0,this._sceneRootNodesIndex=-1,this._animationPropertiesOverride=null,this._isNode=!0,this.onDisposeObservable=new u.c,this._onDisposeObserver=null,this._behaviors=new Array,this.name=c,this.id=c,this._scene=T||M.a.LastCreatedScene,this.uniqueId=this._scene.getUniqueId(),this._initCache()}return m.AddNodeConstructor=function(c,T){this._NodeConstructors[c]=T},m.Construct=function(c,T,A,S){var g=this._NodeConstructors[c];return g?g(T,A,S):null},Object.defineProperty(m.prototype,"doNotSerialize",{get:function(){return!!this._doNotSerialize||!!this._parentNode&&this._parentNode.doNotSerialize},set:function(c){this._doNotSerialize=c},enumerable:!1,configurable:!0}),m.prototype.isDisposed=function(){return this._isDisposed},Object.defineProperty(m.prototype,"parent",{get:function(){return this._parentNode},set:function(c){if(this._parentNode!==c){var T=this._parentNode;if(this._parentNode&&this._parentNode._children!==void 0&&this._parentNode._children!==null){var A=this._parentNode._children.indexOf(this);A!==-1&&this._parentNode._children.splice(A,1),c||this._isDisposed||this._addToSceneRootNodes()}this._parentNode=c,this._parentNode&&(this._parentNode._children!==void 0&&this._parentNode._children!==null||(this._parentNode._children=new Array),this._parentNode._children.push(this),T||this._removeFromSceneRootNodes()),this._syncParentEnabledState()}},enumerable:!1,configurable:!0}),m.prototype._addToSceneRootNodes=function(){this._sceneRootNodesIndex===-1&&(this._sceneRootNodesIndex=this._scene.rootNodes.length,this._scene.rootNodes.push(this))},m.prototype._removeFromSceneRootNodes=function(){if(this._sceneRootNodesIndex!==-1){var c=this._scene.rootNodes,T=c.length-1;c[this._sceneRootNodesIndex]=c[T],c[this._sceneRootNodesIndex]._sceneRootNodesIndex=this._sceneRootNodesIndex,this._scene.rootNodes.pop(),this._sceneRootNodesIndex=-1}},Object.defineProperty(m.prototype,"animationPropertiesOverride",{get:function(){return this._animationPropertiesOverride?this._animationPropertiesOverride:this._scene.animationPropertiesOverride},set:function(c){this._animationPropertiesOverride=c},enumerable:!1,configurable:!0}),m.prototype.getClassName=function(){return"Node"},Object.defineProperty(m.prototype,"onDispose",{set:function(c){this._onDisposeObserver&&this.onDisposeObservable.remove(this._onDisposeObserver),this._onDisposeObserver=this.onDisposeObservable.add(c)},enumerable:!1,configurable:!0}),m.prototype.getScene=function(){return this._scene},m.prototype.getEngine=function(){return this._scene.getEngine()},m.prototype.addBehavior=function(c,T){var A=this;return T===void 0&&(T=!1),this._behaviors.indexOf(c)!==-1||(c.init(),this._scene.isLoading&&!T?this._scene.onDataLoadedObservable.addOnce(function(){c.attach(A)}):c.attach(this),this._behaviors.push(c)),this},m.prototype.removeBehavior=function(c){var T=this._behaviors.indexOf(c);return T===-1||(this._behaviors[T].detach(),this._behaviors.splice(T,1)),this},Object.defineProperty(m.prototype,"behaviors",{get:function(){return this._behaviors},enumerable:!1,configurable:!0}),m.prototype.getBehaviorByName=function(c){for(var T=0,A=this._behaviors;T<A.length;T++){var S=A[T];if(S.name===c)return S}return null},m.prototype.getWorldMatrix=function(){return this._currentRenderId!==this._scene.getRenderId()&&this.computeWorldMatrix(),this._worldMatrix},m.prototype._getWorldMatrixDeterminant=function(){return this._worldMatrixDeterminantIsDirty&&(this._worldMatrixDeterminantIsDirty=!1,this._worldMatrixDeterminant=this._worldMatrix.determinant()),this._worldMatrixDeterminant},Object.defineProperty(m.prototype,"worldMatrixFromCache",{get:function(){return this._worldMatrix},enumerable:!1,configurable:!0}),m.prototype._initCache=function(){this._cache={},this._cache.parent=void 0},m.prototype.updateCache=function(c){!c&&this.isSynchronized()||(this._cache.parent=this.parent,this._updateCache())},m.prototype._getActionManagerForTrigger=function(c,T){return this.parent?this.parent._getActionManagerForTrigger(c,!1):null},m.prototype._updateCache=function(c){},m.prototype._isSynchronized=function(){return!0},m.prototype._markSyncedWithParent=function(){this._parentNode&&(this._parentUpdateId=this._parentNode._childUpdateId)},m.prototype.isSynchronizedWithParent=function(){return!this._parentNode||this._parentUpdateId===this._parentNode._childUpdateId&&this._parentNode.isSynchronized()},m.prototype.isSynchronized=function(){return this._cache.parent!=this._parentNode?(this._cache.parent=this._parentNode,!1):!(this._parentNode&&!this.isSynchronizedWithParent())&&this._isSynchronized()},m.prototype.isReady=function(c){return this._isReady},m.prototype.isEnabled=function(c){return c===void 0&&(c=!0),c===!1?this._isEnabled:!!this._isEnabled&&this._isParentEnabled},m.prototype._syncParentEnabledState=function(){this._isParentEnabled=!this._parentNode||this._parentNode.isEnabled(),this._children&&this._children.forEach(function(c){c._syncParentEnabledState()})},m.prototype.setEnabled=function(c){this._isEnabled=c,this._syncParentEnabledState()},m.prototype.isDescendantOf=function(c){return!!this.parent&&(this.parent===c||this.parent.isDescendantOf(c))},m.prototype._getDescendants=function(c,T,A){if(T===void 0&&(T=!1),this._children)for(var S=0;S<this._children.length;S++){var g=this._children[S];A&&!A(g)||c.push(g),T||g._getDescendants(c,!1,A)}},m.prototype.getDescendants=function(c,T){var A=new Array;return this._getDescendants(A,c,T),A},m.prototype.getChildMeshes=function(c,T){var A=[];return this._getDescendants(A,c,function(S){return(!T||T(S))&&S.cullingStrategy!==void 0}),A},m.prototype.getChildren=function(c,T){return T===void 0&&(T=!0),this.getDescendants(T,c)},m.prototype._setReady=function(c){c!==this._isReady&&(c?(this.onReady&&this.onReady(this),this._isReady=!0):this._isReady=!1)},m.prototype.getAnimationByName=function(c){for(var T=0;T<this.animations.length;T++){var A=this.animations[T];if(A.name===c)return A}return null},m.prototype.createAnimationRange=function(c,T,A){if(!this._ranges[c]){this._ranges[c]=m._AnimationRangeFactory(c,T,A);for(var S=0,g=this.animations.length;S<g;S++)this.animations[S]&&this.animations[S].createRange(c,T,A)}},m.prototype.deleteAnimationRange=function(c,T){T===void 0&&(T=!0);for(var A=0,S=this.animations.length;A<S;A++)this.animations[A]&&this.animations[A].deleteRange(c,T);this._ranges[c]=null},m.prototype.getAnimationRange=function(c){return this._ranges[c]||null},m.prototype.getAnimationRanges=function(){var c,T=[];for(c in this._ranges)T.push(this._ranges[c]);return T},m.prototype.beginAnimation=function(c,T,A,S){var g=this.getAnimationRange(c);return g?this._scene.beginAnimation(this,g.from,g.to,T,A,S):null},m.prototype.serializeAnimationRanges=function(){var c=[];for(var T in this._ranges){var A=this._ranges[T];if(A){var S={};S.name=T,S.from=A.from,S.to=A.to,c.push(S)}}return c},m.prototype.computeWorldMatrix=function(c){return this._worldMatrix||(this._worldMatrix=_.a.Identity()),this._worldMatrix},m.prototype.dispose=function(c,T){if(T===void 0&&(T=!1),this._isDisposed=!0,!c)for(var A=0,S=this.getDescendants(!0);A<S.length;A++)S[A].dispose(c,T);this.parent?this.parent=null:this._removeFromSceneRootNodes(),this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear();for(var g=0,l=this._behaviors;g<l.length;g++)l[g].detach();this._behaviors=[]},m.ParseAnimationRanges=function(c,T,A){if(T.ranges)for(var S=0;S<T.ranges.length;S++){var g=T.ranges[S];c.createAnimationRange(g.name,g.from,g.to)}},m.prototype.getHierarchyBoundingVectors=function(c,T){var A,S;if(c===void 0&&(c=!0),T===void 0&&(T=null),this.getScene().incrementRenderId(),this.computeWorldMatrix(!0),this.getBoundingInfo&&this.subMeshes){var g=this.getBoundingInfo();A=g.boundingBox.minimumWorld.clone(),S=g.boundingBox.maximumWorld.clone()}else A=new _.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),S=new _.e(-Number.MAX_VALUE,-Number.MAX_VALUE,-Number.MAX_VALUE);if(c)for(var l=0,h=this.getDescendants(!1);l<h.length;l++){var v=h[l];if(v.computeWorldMatrix(!0),(!T||T(v))&&v.getBoundingInfo&&v.getTotalVertices()!==0){var E=v.getBoundingInfo().boundingBox,D=E.minimumWorld,w=E.maximumWorld;_.e.CheckExtends(D,A,S),_.e.CheckExtends(w,A,S)}}return{min:A,max:S}},m._AnimationRangeFactory=function(c,T,A){throw R.a.WarnImport("AnimationRange")},m._NodeConstructors={},Object(U.c)([Object(x.c)()],m.prototype,"name",void 0),Object(U.c)([Object(x.c)()],m.prototype,"id",void 0),Object(U.c)([Object(x.c)()],m.prototype,"uniqueId",void 0),Object(U.c)([Object(x.c)()],m.prototype,"state",void 0),Object(U.c)([Object(x.c)()],m.prototype,"metadata",void 0),m}()},function(Me,y,f){f.d(y,"b",function(){return de}),f.d(y,"a",function(){return pe});var U=f(1),_=f(3),x=f(33),u=f(20),M=f(0),R=f(9),C=f(4),m=f(105),c=f(42),T=f(25),A=f(76),S=f(87),g=f(15),l=f(10),h=f(11),v=f(19),E=f(5),D=`uniform vec4 vDiffuseColor;
-#ifdef SPECULARTERM
-uniform vec4 vSpecularColor;
-#endif
-uniform vec3 vEmissiveColor;
-uniform float visibility;
-
-#ifdef DIFFUSE
-uniform vec2 vDiffuseInfos;
-#endif
-#ifdef AMBIENT
-uniform vec2 vAmbientInfos;
-#endif
-#ifdef OPACITY
-uniform vec2 vOpacityInfos;
-#endif
-#ifdef EMISSIVE
-uniform vec2 vEmissiveInfos;
-#endif
-#ifdef LIGHTMAP
-uniform vec2 vLightmapInfos;
-#endif
-#ifdef BUMP
-uniform vec3 vBumpInfos;
-uniform vec2 vTangentSpaceParams;
-#endif
-#if defined(REFLECTIONMAP_SPHERICAL) || defined(REFLECTIONMAP_PROJECTION) || defined(REFRACTION)
-uniform mat4 view;
-#endif
-#ifdef REFRACTION
-uniform vec4 vRefractionInfos;
-#ifndef REFRACTIONMAP_3D
-uniform mat4 refractionMatrix;
-#endif
-#ifdef REFRACTIONFRESNEL
-uniform vec4 refractionLeftColor;
-uniform vec4 refractionRightColor;
-#endif
-#endif
-#if defined(SPECULAR) && defined(SPECULARTERM)
-uniform vec2 vSpecularInfos;
-#endif
-#ifdef DIFFUSEFRESNEL
-uniform vec4 diffuseLeftColor;
-uniform vec4 diffuseRightColor;
-#endif
-#ifdef OPACITYFRESNEL
-uniform vec4 opacityParts;
-#endif
-#ifdef EMISSIVEFRESNEL
-uniform vec4 emissiveLeftColor;
-uniform vec4 emissiveRightColor;
-#endif
-
-#ifdef REFLECTION
-uniform vec2 vReflectionInfos;
-#if defined(REFLECTIONMAP_PLANAR) || defined(REFLECTIONMAP_CUBIC) || defined(REFLECTIONMAP_PROJECTION) || defined(REFLECTIONMAP_EQUIRECTANGULAR) || defined(REFLECTIONMAP_SPHERICAL) || defined(REFLECTIONMAP_SKYBOX)
-uniform mat4 reflectionMatrix;
-#endif
-#ifndef REFLECTIONMAP_SKYBOX
-#if defined(USE_LOCAL_REFLECTIONMAP_CUBIC) && defined(REFLECTIONMAP_CUBIC)
-uniform vec3 vReflectionPosition;
-uniform vec3 vReflectionSize;
-#endif
-#endif
-#ifdef REFLECTIONFRESNEL
-uniform vec4 reflectionLeftColor;
-uniform vec4 reflectionRightColor;
-#endif
-#endif`;E.a.IncludesShadersStore.defaultFragmentDeclaration=D;var w=`layout(std140,column_major) uniform;
-uniform Material
-{
-vec4 diffuseLeftColor;
-vec4 diffuseRightColor;
-vec4 opacityParts;
-vec4 reflectionLeftColor;
-vec4 reflectionRightColor;
-vec4 refractionLeftColor;
-vec4 refractionRightColor;
-vec4 emissiveLeftColor;
-vec4 emissiveRightColor;
-vec2 vDiffuseInfos;
-vec2 vAmbientInfos;
-vec2 vOpacityInfos;
-vec2 vReflectionInfos;
-vec3 vReflectionPosition;
-vec3 vReflectionSize;
-vec2 vEmissiveInfos;
-vec2 vLightmapInfos;
-vec2 vSpecularInfos;
-vec3 vBumpInfos;
-mat4 diffuseMatrix;
-mat4 ambientMatrix;
-mat4 opacityMatrix;
-mat4 reflectionMatrix;
-mat4 emissiveMatrix;
-mat4 lightmapMatrix;
-mat4 specularMatrix;
-mat4 bumpMatrix;
-vec2 vTangentSpaceParams;
-float pointSize;
-mat4 refractionMatrix;
-vec4 vRefractionInfos;
-vec4 vSpecularColor;
-vec3 vEmissiveColor;
-float visibility;
-vec4 vDiffuseColor;
-vec4 vDetailInfos;
-mat4 detailMatrix;
-};
-uniform Scene {
-mat4 viewProjection;
-#ifdef MULTIVIEW
-mat4 viewProjectionR;
-#endif
-mat4 view;
-};
-`;E.a.IncludesShadersStore.defaultUboDeclaration=w,f(160),f(59),f(106),f(107),f(154),f(130),f(161),f(131),f(108),f(109),f(132),f(133),f(115),f(116),f(125),f(110),f(134),f(162),f(135),f(155),f(136);var N=`#include<__decl__defaultFragment>
-#if defined(BUMP) || !defined(NORMAL)
-#extension GL_OES_standard_derivatives : enable
-#endif
-#include<prePassDeclaration>[SCENE_MRT_COUNT]
-#define CUSTOM_FRAGMENT_BEGIN
-#ifdef LOGARITHMICDEPTH
-#extension GL_EXT_frag_depth : enable
-#endif
-
-#define RECIPROCAL_PI2 0.15915494
-uniform vec3 vEyePosition;
-uniform vec3 vAmbientColor;
-
-varying vec3 vPositionW;
-#ifdef NORMAL
-varying vec3 vNormalW;
-#endif
-#ifdef VERTEXCOLOR
-varying vec4 vColor;
-#endif
-#ifdef MAINUV1
-varying vec2 vMainUV1;
-#endif
-#ifdef MAINUV2
-varying vec2 vMainUV2;
-#endif
-
-#include<helperFunctions>
-
-#include<__decl__lightFragment>[0..maxSimultaneousLights]
-#include<lightsFragmentFunctions>
-#include<shadowsFragmentFunctions>
-
-#ifdef DIFFUSE
-#if DIFFUSEDIRECTUV == 1
-#define vDiffuseUV vMainUV1
-#elif DIFFUSEDIRECTUV == 2
-#define vDiffuseUV vMainUV2
-#else
-varying vec2 vDiffuseUV;
-#endif
-uniform sampler2D diffuseSampler;
-#endif
-#ifdef AMBIENT
-#if AMBIENTDIRECTUV == 1
-#define vAmbientUV vMainUV1
-#elif AMBIENTDIRECTUV == 2
-#define vAmbientUV vMainUV2
-#else
-varying vec2 vAmbientUV;
-#endif
-uniform sampler2D ambientSampler;
-#endif
-#ifdef OPACITY
-#if OPACITYDIRECTUV == 1
-#define vOpacityUV vMainUV1
-#elif OPACITYDIRECTUV == 2
-#define vOpacityUV vMainUV2
-#else
-varying vec2 vOpacityUV;
-#endif
-uniform sampler2D opacitySampler;
-#endif
-#ifdef EMISSIVE
-#if EMISSIVEDIRECTUV == 1
-#define vEmissiveUV vMainUV1
-#elif EMISSIVEDIRECTUV == 2
-#define vEmissiveUV vMainUV2
-#else
-varying vec2 vEmissiveUV;
-#endif
-uniform sampler2D emissiveSampler;
-#endif
-#ifdef LIGHTMAP
-#if LIGHTMAPDIRECTUV == 1
-#define vLightmapUV vMainUV1
-#elif LIGHTMAPDIRECTUV == 2
-#define vLightmapUV vMainUV2
-#else
-varying vec2 vLightmapUV;
-#endif
-uniform sampler2D lightmapSampler;
-#endif
-#ifdef REFRACTION
-#ifdef REFRACTIONMAP_3D
-uniform samplerCube refractionCubeSampler;
-#else
-uniform sampler2D refraction2DSampler;
-#endif
-#endif
-#if defined(SPECULAR) && defined(SPECULARTERM)
-#if SPECULARDIRECTUV == 1
-#define vSpecularUV vMainUV1
-#elif SPECULARDIRECTUV == 2
-#define vSpecularUV vMainUV2
-#else
-varying vec2 vSpecularUV;
-#endif
-uniform sampler2D specularSampler;
-#endif
-#ifdef ALPHATEST
-uniform float alphaCutOff;
-#endif
-
-#include<fresnelFunction>
-
-#ifdef REFLECTION
-#ifdef REFLECTIONMAP_3D
-uniform samplerCube reflectionCubeSampler;
-#else
-uniform sampler2D reflection2DSampler;
-#endif
-#ifdef REFLECTIONMAP_SKYBOX
-varying vec3 vPositionUVW;
-#else
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
-varying vec3 vDirectionW;
-#endif
-#endif
-#include<reflectionFunction>
-#endif
-#include<imageProcessingDeclaration>
-#include<imageProcessingFunctions>
-#include<bumpFragmentMainFunctions>
-#include<bumpFragmentFunctions>
-#include<clipPlaneFragmentDeclaration>
-#include<logDepthDeclaration>
-#include<fogFragmentDeclaration>
-#define CUSTOM_FRAGMENT_DEFINITIONS
-void main(void) {
-#define CUSTOM_FRAGMENT_MAIN_BEGIN
-#include<clipPlaneFragment>
-vec3 viewDirectionW=normalize(vEyePosition-vPositionW);
-
-vec4 baseColor=vec4(1.,1.,1.,1.);
-vec3 diffuseColor=vDiffuseColor.rgb;
-
-float alpha=vDiffuseColor.a;
-
-#ifdef NORMAL
-vec3 normalW=normalize(vNormalW);
-#else
-vec3 normalW=normalize(-cross(dFdx(vPositionW),dFdy(vPositionW)));
-#endif
-#include<bumpFragment>
-#ifdef TWOSIDEDLIGHTING
-normalW=gl_FrontFacing ? normalW : -normalW;
-#endif
-#ifdef DIFFUSE
-baseColor=texture2D(diffuseSampler,vDiffuseUV+uvOffset);
-#if defined(ALPHATEST) && !defined(ALPHATEST_AFTERALLALPHACOMPUTATIONS)
-if (baseColor.a<alphaCutOff)
-discard;
-#endif
-#ifdef ALPHAFROMDIFFUSE
-alpha*=baseColor.a;
-#endif
-#define CUSTOM_FRAGMENT_UPDATE_ALPHA
-baseColor.rgb*=vDiffuseInfos.y;
-#endif
-#include<depthPrePass>
-#ifdef VERTEXCOLOR
-baseColor.rgb*=vColor.rgb;
-#endif
-#ifdef DETAIL
-baseColor.rgb=baseColor.rgb*2.0*mix(0.5,detailColor.r,vDetailInfos.y);
-#endif
-#define CUSTOM_FRAGMENT_UPDATE_DIFFUSE
-
-vec3 baseAmbientColor=vec3(1.,1.,1.);
-#ifdef AMBIENT
-baseAmbientColor=texture2D(ambientSampler,vAmbientUV+uvOffset).rgb*vAmbientInfos.y;
-#endif
-#define CUSTOM_FRAGMENT_BEFORE_LIGHTS
-
-#ifdef SPECULARTERM
-float glossiness=vSpecularColor.a;
-vec3 specularColor=vSpecularColor.rgb;
-#ifdef SPECULAR
-vec4 specularMapColor=texture2D(specularSampler,vSpecularUV+uvOffset);
-specularColor=specularMapColor.rgb;
-#ifdef GLOSSINESS
-glossiness=glossiness*specularMapColor.a;
-#endif
-#endif
-#else
-float glossiness=0.;
-#endif
-
-vec3 diffuseBase=vec3(0.,0.,0.);
-lightingInfo info;
-#ifdef SPECULARTERM
-vec3 specularBase=vec3(0.,0.,0.);
-#endif
-float shadow=1.;
-#ifdef LIGHTMAP
-vec4 lightmapColor=texture2D(lightmapSampler,vLightmapUV+uvOffset);
-#ifdef RGBDLIGHTMAP
-lightmapColor.rgb=fromRGBD(lightmapColor);
-#endif
-lightmapColor.rgb*=vLightmapInfos.y;
-#endif
-#include<lightFragment>[0..maxSimultaneousLights]
-
-vec4 refractionColor=vec4(0.,0.,0.,1.);
-#ifdef REFRACTION
-vec3 refractionVector=normalize(refract(-viewDirectionW,normalW,vRefractionInfos.y));
-#ifdef REFRACTIONMAP_3D
-refractionVector.y=refractionVector.y*vRefractionInfos.w;
-if (dot(refractionVector,viewDirectionW)<1.0) {
-refractionColor=textureCube(refractionCubeSampler,refractionVector);
-}
-#else
-vec3 vRefractionUVW=vec3(refractionMatrix*(view*vec4(vPositionW+refractionVector*vRefractionInfos.z,1.0)));
-vec2 refractionCoords=vRefractionUVW.xy/vRefractionUVW.z;
-refractionCoords.y=1.0-refractionCoords.y;
-refractionColor=texture2D(refraction2DSampler,refractionCoords);
-#endif
-#ifdef RGBDREFRACTION
-refractionColor.rgb=fromRGBD(refractionColor);
-#endif
-#ifdef IS_REFRACTION_LINEAR
-refractionColor.rgb=toGammaSpace(refractionColor.rgb);
-#endif
-refractionColor.rgb*=vRefractionInfos.x;
-#endif
-
-vec4 reflectionColor=vec4(0.,0.,0.,1.);
-#ifdef REFLECTION
-vec3 vReflectionUVW=computeReflectionCoords(vec4(vPositionW,1.0),normalW);
-#ifdef REFLECTIONMAP_3D
-#ifdef ROUGHNESS
-float bias=vReflectionInfos.y;
-#ifdef SPECULARTERM
-#ifdef SPECULAR
-#ifdef GLOSSINESS
-bias*=(1.0-specularMapColor.a);
-#endif
-#endif
-#endif
-reflectionColor=textureCube(reflectionCubeSampler,vReflectionUVW,bias);
-#else
-reflectionColor=textureCube(reflectionCubeSampler,vReflectionUVW);
-#endif
-#else
-vec2 coords=vReflectionUVW.xy;
-#ifdef REFLECTIONMAP_PROJECTION
-coords/=vReflectionUVW.z;
-#endif
-coords.y=1.0-coords.y;
-reflectionColor=texture2D(reflection2DSampler,coords);
-#endif
-#ifdef RGBDREFLECTION
-reflectionColor.rgb=fromRGBD(reflectionColor);
-#endif
-#ifdef IS_REFLECTION_LINEAR
-reflectionColor.rgb=toGammaSpace(reflectionColor.rgb);
-#endif
-reflectionColor.rgb*=vReflectionInfos.x;
-#ifdef REFLECTIONFRESNEL
-float reflectionFresnelTerm=computeFresnelTerm(viewDirectionW,normalW,reflectionRightColor.a,reflectionLeftColor.a);
-#ifdef REFLECTIONFRESNELFROMSPECULAR
-#ifdef SPECULARTERM
-reflectionColor.rgb*=specularColor.rgb*(1.0-reflectionFresnelTerm)+reflectionFresnelTerm*reflectionRightColor.rgb;
-#else
-reflectionColor.rgb*=reflectionLeftColor.rgb*(1.0-reflectionFresnelTerm)+reflectionFresnelTerm*reflectionRightColor.rgb;
-#endif
-#else
-reflectionColor.rgb*=reflectionLeftColor.rgb*(1.0-reflectionFresnelTerm)+reflectionFresnelTerm*reflectionRightColor.rgb;
-#endif
-#endif
-#endif
-#ifdef REFRACTIONFRESNEL
-float refractionFresnelTerm=computeFresnelTerm(viewDirectionW,normalW,refractionRightColor.a,refractionLeftColor.a);
-refractionColor.rgb*=refractionLeftColor.rgb*(1.0-refractionFresnelTerm)+refractionFresnelTerm*refractionRightColor.rgb;
-#endif
-#ifdef OPACITY
-vec4 opacityMap=texture2D(opacitySampler,vOpacityUV+uvOffset);
-#ifdef OPACITYRGB
-opacityMap.rgb=opacityMap.rgb*vec3(0.3,0.59,0.11);
-alpha*=(opacityMap.x+opacityMap.y+opacityMap.z)* vOpacityInfos.y;
-#else
-alpha*=opacityMap.a*vOpacityInfos.y;
-#endif
-#endif
-#ifdef VERTEXALPHA
-alpha*=vColor.a;
-#endif
-#ifdef OPACITYFRESNEL
-float opacityFresnelTerm=computeFresnelTerm(viewDirectionW,normalW,opacityParts.z,opacityParts.w);
-alpha+=opacityParts.x*(1.0-opacityFresnelTerm)+opacityFresnelTerm*opacityParts.y;
-#endif
-#ifdef ALPHATEST
-#ifdef ALPHATEST_AFTERALLALPHACOMPUTATIONS
-if (alpha<alphaCutOff)
-discard;
-#endif
-#ifndef ALPHABLEND
-
-alpha=1.0;
-#endif
-#endif
-
-vec3 emissiveColor=vEmissiveColor;
-#ifdef EMISSIVE
-emissiveColor+=texture2D(emissiveSampler,vEmissiveUV+uvOffset).rgb*vEmissiveInfos.y;
-#endif
-#ifdef EMISSIVEFRESNEL
-float emissiveFresnelTerm=computeFresnelTerm(viewDirectionW,normalW,emissiveRightColor.a,emissiveLeftColor.a);
-emissiveColor*=emissiveLeftColor.rgb*(1.0-emissiveFresnelTerm)+emissiveFresnelTerm*emissiveRightColor.rgb;
-#endif
-
-#ifdef DIFFUSEFRESNEL
-float diffuseFresnelTerm=computeFresnelTerm(viewDirectionW,normalW,diffuseRightColor.a,diffuseLeftColor.a);
-diffuseBase*=diffuseLeftColor.rgb*(1.0-diffuseFresnelTerm)+diffuseFresnelTerm*diffuseRightColor.rgb;
-#endif
-
-#ifdef EMISSIVEASILLUMINATION
-vec3 finalDiffuse=clamp(diffuseBase*diffuseColor+vAmbientColor,0.0,1.0)*baseColor.rgb;
-#else
-#ifdef LINKEMISSIVEWITHDIFFUSE
-vec3 finalDiffuse=clamp((diffuseBase+emissiveColor)*diffuseColor+vAmbientColor,0.0,1.0)*baseColor.rgb;
-#else
-vec3 finalDiffuse=clamp(diffuseBase*diffuseColor+emissiveColor+vAmbientColor,0.0,1.0)*baseColor.rgb;
-#endif
-#endif
-#ifdef SPECULARTERM
-vec3 finalSpecular=specularBase*specularColor;
-#ifdef SPECULAROVERALPHA
-alpha=clamp(alpha+dot(finalSpecular,vec3(0.3,0.59,0.11)),0.,1.);
-#endif
-#else
-vec3 finalSpecular=vec3(0.0);
-#endif
-#ifdef REFLECTIONOVERALPHA
-alpha=clamp(alpha+dot(reflectionColor.rgb,vec3(0.3,0.59,0.11)),0.,1.);
-#endif
-
-#ifdef EMISSIVEASILLUMINATION
-vec4 color=vec4(clamp(finalDiffuse*baseAmbientColor+finalSpecular+reflectionColor.rgb+emissiveColor+refractionColor.rgb,0.0,1.0),alpha);
-#else
-vec4 color=vec4(finalDiffuse*baseAmbientColor+finalSpecular+reflectionColor.rgb+refractionColor.rgb,alpha);
-#endif
-
-#ifdef LIGHTMAP
-#ifndef LIGHTMAPEXCLUDED
-#ifdef USELIGHTMAPASSHADOWMAP
-color.rgb*=lightmapColor.rgb;
-#else
-color.rgb+=lightmapColor.rgb;
-#endif
-#endif
-#endif
-#define CUSTOM_FRAGMENT_BEFORE_FOG
-color.rgb=max(color.rgb,0.);
-#include<logDepthFragment>
-#include<fogFragment>
-
-
-#ifdef IMAGEPROCESSINGPOSTPROCESS
-color.rgb=toLinearSpace(color.rgb);
-#else
-#ifdef IMAGEPROCESSING
-color.rgb=toLinearSpace(color.rgb);
-color=applyImageProcessing(color);
-#endif
-#endif
-color.a*=visibility;
-#ifdef PREMULTIPLYALPHA
-
-color.rgb*=color.a;
-#endif
-#define CUSTOM_FRAGMENT_BEFORE_FRAGCOLOR
-#ifdef PREPASS
-gl_FragData[0]=color;
-#ifdef PREPASS_POSITION
-gl_FragData[PREPASS_POSITION_INDEX]=vec4(vPositionW,1.0);
-#endif
-#ifdef PREPASS_VELOCITY
-vec2 a=(vCurrentPosition.xy/vCurrentPosition.w)*0.5+0.5;
-vec2 b=(vPreviousPosition.xy/vPreviousPosition.w)*0.5+0.5;
-vec2 velocity=abs(a-b);
-velocity=vec2(pow(velocity.x,1.0/3.0),pow(velocity.y,1.0/3.0))*sign(a-b)*0.5+0.5;
-gl_FragData[PREPASS_VELOCITY_INDEX]=vec4(velocity,0.0,1.0);
-#endif
-#ifdef PREPASS_IRRADIANCE
-gl_FragData[PREPASS_IRRADIANCE_INDEX]=vec4(0.0,0.0,0.0,1.0);
-#endif
-#ifdef PREPASS_DEPTHNORMAL
-gl_FragData[PREPASS_DEPTHNORMAL_INDEX]=vec4(vViewPos.z,(view*vec4(normalW,0.0)).rgb);
-#endif
-#ifdef PREPASS_ALBEDO
-gl_FragData[PREPASS_ALBEDO_INDEX]=vec4(0.0,0.0,0.0,1.0);
-#endif
-#ifdef PREPASS_REFLECTIVITY
-#if defined(SPECULAR)
-gl_FragData[PREPASS_REFLECTIVITY_INDEX]=specularMapColor;
-#else
-gl_FragData[PREPASS_REFLECTIVITY_INDEX]=vec4(0.0,0.0,0.0,1.0);
-#endif
-#endif
-#endif
-#if !defined(PREPASS) || defined(WEBGL2)
-gl_FragColor=color;
-#endif
-}
-`;E.a.ShadersStore.defaultPixelShader=N;var I=`
-uniform mat4 viewProjection;
-uniform mat4 view;
-#ifdef DIFFUSE
-uniform mat4 diffuseMatrix;
-uniform vec2 vDiffuseInfos;
-#endif
-#ifdef AMBIENT
-uniform mat4 ambientMatrix;
-uniform vec2 vAmbientInfos;
-#endif
-#ifdef OPACITY
-uniform mat4 opacityMatrix;
-uniform vec2 vOpacityInfos;
-#endif
-#ifdef EMISSIVE
-uniform vec2 vEmissiveInfos;
-uniform mat4 emissiveMatrix;
-#endif
-#ifdef LIGHTMAP
-uniform vec2 vLightmapInfos;
-uniform mat4 lightmapMatrix;
-#endif
-#if defined(SPECULAR) && defined(SPECULARTERM)
-uniform vec2 vSpecularInfos;
-uniform mat4 specularMatrix;
-#endif
-#ifdef BUMP
-uniform vec3 vBumpInfos;
-uniform mat4 bumpMatrix;
-#endif
-#ifdef REFLECTION
-uniform mat4 reflectionMatrix;
-#endif
-#ifdef POINTSIZE
-uniform float pointSize;
-#endif
-`;E.a.IncludesShadersStore.defaultVertexDeclaration=I,f(78),f(79),f(163),f(164),f(117),f(137),f(93),f(94),f(100),f(80),f(81),f(165),f(156),f(111),f(157),f(138),E.a.IncludesShadersStore.pointCloudVertex=`#ifdef POINTSIZE
-gl_PointSize=pointSize;
-#endif`,f(158);var V=`#include<__decl__defaultVertex>
-
-#define CUSTOM_VERTEX_BEGIN
-attribute vec3 position;
-#ifdef NORMAL
-attribute vec3 normal;
-#endif
-#ifdef TANGENT
-attribute vec4 tangent;
-#endif
-#ifdef UV1
-attribute vec2 uv;
-#endif
-#ifdef UV2
-attribute vec2 uv2;
-#endif
-#ifdef VERTEXCOLOR
-attribute vec4 color;
-#endif
-#include<helperFunctions>
-#include<bonesDeclaration>
-
-#include<instancesDeclaration>
-#include<prePassVertexDeclaration>
-#ifdef MAINUV1
-varying vec2 vMainUV1;
-#endif
-#ifdef MAINUV2
-varying vec2 vMainUV2;
-#endif
-#if defined(DIFFUSE) && DIFFUSEDIRECTUV == 0
-varying vec2 vDiffuseUV;
-#endif
-#if defined(DETAIL) && DETAILDIRECTUV == 0
-varying vec2 vDetailUV;
-#endif
-#if defined(AMBIENT) && AMBIENTDIRECTUV == 0
-varying vec2 vAmbientUV;
-#endif
-#if defined(OPACITY) && OPACITYDIRECTUV == 0
-varying vec2 vOpacityUV;
-#endif
-#if defined(EMISSIVE) && EMISSIVEDIRECTUV == 0
-varying vec2 vEmissiveUV;
-#endif
-#if defined(LIGHTMAP) && LIGHTMAPDIRECTUV == 0
-varying vec2 vLightmapUV;
-#endif
-#if defined(SPECULAR) && defined(SPECULARTERM) && SPECULARDIRECTUV == 0
-varying vec2 vSpecularUV;
-#endif
-#if defined(BUMP) && BUMPDIRECTUV == 0
-varying vec2 vBumpUV;
-#endif
-
-varying vec3 vPositionW;
-#ifdef NORMAL
-varying vec3 vNormalW;
-#endif
-#ifdef VERTEXCOLOR
-varying vec4 vColor;
-#endif
-#include<bumpVertexDeclaration>
-#include<clipPlaneVertexDeclaration>
-#include<fogVertexDeclaration>
-#include<__decl__lightFragment>[0..maxSimultaneousLights]
-#include<morphTargetsVertexGlobalDeclaration>
-#include<morphTargetsVertexDeclaration>[0..maxSimultaneousMorphTargets]
-#ifdef REFLECTIONMAP_SKYBOX
-varying vec3 vPositionUVW;
-#endif
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
-varying vec3 vDirectionW;
-#endif
-#include<logDepthDeclaration>
-#define CUSTOM_VERTEX_DEFINITIONS
-void main(void) {
-#define CUSTOM_VERTEX_MAIN_BEGIN
-vec3 positionUpdated=position;
-#ifdef NORMAL
-vec3 normalUpdated=normal;
-#endif
-#ifdef TANGENT
-vec4 tangentUpdated=tangent;
-#endif
-#ifdef UV1
-vec2 uvUpdated=uv;
-#endif
-#include<morphTargetsVertex>[0..maxSimultaneousMorphTargets]
-#ifdef REFLECTIONMAP_SKYBOX
-vPositionUVW=positionUpdated;
-#endif
-#define CUSTOM_VERTEX_UPDATE_POSITION
-#define CUSTOM_VERTEX_UPDATE_NORMAL
-#include<instancesVertex>
-#if defined(PREPASS) && defined(PREPASS_VELOCITY) && !defined(BONES_VELOCITY_ENABLED)
-
-vCurrentPosition=viewProjection*finalWorld*vec4(positionUpdated,1.0);
-vPreviousPosition=previousViewProjection*previousWorld*vec4(positionUpdated,1.0);
-#endif
-#include<bonesVertex>
-vec4 worldPos=finalWorld*vec4(positionUpdated,1.0);
-#ifdef NORMAL
-mat3 normalWorld=mat3(finalWorld);
-#if defined(INSTANCES) && defined(THIN_INSTANCES)
-vNormalW=normalUpdated/vec3(dot(normalWorld[0],normalWorld[0]),dot(normalWorld[1],normalWorld[1]),dot(normalWorld[2],normalWorld[2]));
-vNormalW=normalize(normalWorld*vNormalW);
-#else
-#ifdef NONUNIFORMSCALING
-normalWorld=transposeMat3(inverseMat3(normalWorld));
-#endif
-vNormalW=normalize(normalWorld*normalUpdated);
-#endif
-#endif
-#define CUSTOM_VERTEX_UPDATE_WORLDPOS
-#ifdef MULTIVIEW
-if (gl_ViewID_OVR == 0u) {
-gl_Position=viewProjection*worldPos;
-} else {
-gl_Position=viewProjectionR*worldPos;
-}
-#else
-gl_Position=viewProjection*worldPos;
-#endif
-vPositionW=vec3(worldPos);
-#include<prePassVertex>
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
-vDirectionW=normalize(vec3(finalWorld*vec4(positionUpdated,0.0)));
-#endif
-
-#ifndef UV1
-vec2 uvUpdated=vec2(0.,0.);
-#endif
-#ifndef UV2
-vec2 uv2=vec2(0.,0.);
-#endif
-#ifdef MAINUV1
-vMainUV1=uvUpdated;
-#endif
-#ifdef MAINUV2
-vMainUV2=uv2;
-#endif
-#if defined(DIFFUSE) && DIFFUSEDIRECTUV == 0
-if (vDiffuseInfos.x == 0.)
-{
-vDiffuseUV=vec2(diffuseMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vDiffuseUV=vec2(diffuseMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(DETAIL) && DETAILDIRECTUV == 0
-if (vDetailInfos.x == 0.)
-{
-vDetailUV=vec2(detailMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vDetailUV=vec2(detailMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(AMBIENT) && AMBIENTDIRECTUV == 0
-if (vAmbientInfos.x == 0.)
-{
-vAmbientUV=vec2(ambientMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vAmbientUV=vec2(ambientMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(OPACITY) && OPACITYDIRECTUV == 0
-if (vOpacityInfos.x == 0.)
-{
-vOpacityUV=vec2(opacityMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vOpacityUV=vec2(opacityMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(EMISSIVE) && EMISSIVEDIRECTUV == 0
-if (vEmissiveInfos.x == 0.)
-{
-vEmissiveUV=vec2(emissiveMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vEmissiveUV=vec2(emissiveMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(LIGHTMAP) && LIGHTMAPDIRECTUV == 0
-if (vLightmapInfos.x == 0.)
-{
-vLightmapUV=vec2(lightmapMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vLightmapUV=vec2(lightmapMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(SPECULAR) && defined(SPECULARTERM) && SPECULARDIRECTUV == 0
-if (vSpecularInfos.x == 0.)
-{
-vSpecularUV=vec2(specularMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vSpecularUV=vec2(specularMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(BUMP) && BUMPDIRECTUV == 0
-if (vBumpInfos.x == 0.)
-{
-vBumpUV=vec2(bumpMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vBumpUV=vec2(bumpMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#include<bumpVertex>
-#include<clipPlaneVertex>
-#include<fogVertex>
-#include<shadowsVertex>[0..maxSimultaneousLights]
-#ifdef VERTEXCOLOR
-
-vColor=color;
-#endif
-#include<pointCloudVertex>
-#include<logDepthVertex>
-#define CUSTOM_VERTEX_MAIN_END
-}
-`;E.a.ShadersStore.defaultVertexShader=V;var X=f(2),j=f(67),ne=f(92),te={effect:null,subMesh:null},de=function(ae){function ee(){var K=ae.call(this)||this;return K.MAINUV1=!1,K.MAINUV2=!1,K.DIFFUSE=!1,K.DIFFUSEDIRECTUV=0,K.DETAIL=!1,K.DETAILDIRECTUV=0,K.DETAIL_NORMALBLENDMETHOD=0,K.AMBIENT=!1,K.AMBIENTDIRECTUV=0,K.OPACITY=!1,K.OPACITYDIRECTUV=0,K.OPACITYRGB=!1,K.REFLECTION=!1,K.EMISSIVE=!1,K.EMISSIVEDIRECTUV=0,K.SPECULAR=!1,K.SPECULARDIRECTUV=0,K.BUMP=!1,K.BUMPDIRECTUV=0,K.PARALLAX=!1,K.PARALLAXOCCLUSION=!1,K.SPECULAROVERALPHA=!1,K.CLIPPLANE=!1,K.CLIPPLANE2=!1,K.CLIPPLANE3=!1,K.CLIPPLANE4=!1,K.CLIPPLANE5=!1,K.CLIPPLANE6=!1,K.ALPHATEST=!1,K.DEPTHPREPASS=!1,K.ALPHAFROMDIFFUSE=!1,K.POINTSIZE=!1,K.FOG=!1,K.SPECULARTERM=!1,K.DIFFUSEFRESNEL=!1,K.OPACITYFRESNEL=!1,K.REFLECTIONFRESNEL=!1,K.REFRACTIONFRESNEL=!1,K.EMISSIVEFRESNEL=!1,K.FRESNEL=!1,K.NORMAL=!1,K.UV1=!1,K.UV2=!1,K.VERTEXCOLOR=!1,K.VERTEXALPHA=!1,K.NUM_BONE_INFLUENCERS=0,K.BonesPerMesh=0,K.BONETEXTURE=!1,K.BONES_VELOCITY_ENABLED=!1,K.INSTANCES=!1,K.THIN_INSTANCES=!1,K.GLOSSINESS=!1,K.ROUGHNESS=!1,K.EMISSIVEASILLUMINATION=!1,K.LINKEMISSIVEWITHDIFFUSE=!1,K.REFLECTIONFRESNELFROMSPECULAR=!1,K.LIGHTMAP=!1,K.LIGHTMAPDIRECTUV=0,K.OBJECTSPACE_NORMALMAP=!1,K.USELIGHTMAPASSHADOWMAP=!1,K.REFLECTIONMAP_3D=!1,K.REFLECTIONMAP_SPHERICAL=!1,K.REFLECTIONMAP_PLANAR=!1,K.REFLECTIONMAP_CUBIC=!1,K.USE_LOCAL_REFLECTIONMAP_CUBIC=!1,K.REFLECTIONMAP_PROJECTION=!1,K.REFLECTIONMAP_SKYBOX=!1,K.REFLECTIONMAP_EXPLICIT=!1,K.REFLECTIONMAP_EQUIRECTANGULAR=!1,K.REFLECTIONMAP_EQUIRECTANGULAR_FIXED=!1,K.REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED=!1,K.INVERTCUBICMAP=!1,K.LOGARITHMICDEPTH=!1,K.REFRACTION=!1,K.REFRACTIONMAP_3D=!1,K.REFLECTIONOVERALPHA=!1,K.TWOSIDEDLIGHTING=!1,K.SHADOWFLOAT=!1,K.MORPHTARGETS=!1,K.MORPHTARGETS_NORMAL=!1,K.MORPHTARGETS_TANGENT=!1,K.MORPHTARGETS_UV=!1,K.NUM_MORPH_INFLUENCERS=0,K.NONUNIFORMSCALING=!1,K.PREMULTIPLYALPHA=!1,K.ALPHATEST_AFTERALLALPHACOMPUTATIONS=!1,K.ALPHABLEND=!0,K.PREPASS=!1,K.PREPASS_IRRADIANCE=!1,K.PREPASS_IRRADIANCE_INDEX=-1,K.PREPASS_ALBEDO=!1,K.PREPASS_ALBEDO_INDEX=-1,K.PREPASS_DEPTHNORMAL=!1,K.PREPASS_DEPTHNORMAL_INDEX=-1,K.PREPASS_POSITION=!1,K.PREPASS_POSITION_INDEX=-1,K.PREPASS_VELOCITY=!1,K.PREPASS_VELOCITY_INDEX=-1,K.PREPASS_REFLECTIVITY=!1,K.PREPASS_REFLECTIVITY_INDEX=-1,K.SCENE_MRT_COUNT=0,K.RGBDLIGHTMAP=!1,K.RGBDREFLECTION=!1,K.RGBDREFRACTION=!1,K.IMAGEPROCESSING=!1,K.VIGNETTE=!1,K.VIGNETTEBLENDMODEMULTIPLY=!1,K.VIGNETTEBLENDMODEOPAQUE=!1,K.TONEMAPPING=!1,K.TONEMAPPING_ACES=!1,K.CONTRAST=!1,K.COLORCURVES=!1,K.COLORGRADING=!1,K.COLORGRADING3D=!1,K.SAMPLER3DGREENDEPTH=!1,K.SAMPLER3DBGRMAP=!1,K.IMAGEPROCESSINGPOSTPROCESS=!1,K.MULTIVIEW=!1,K.IS_REFLECTION_LINEAR=!1,K.IS_REFRACTION_LINEAR=!1,K.EXPOSURE=!1,K.rebuild(),K}return Object(U.d)(ee,ae),ee.prototype.setReflectionMode=function(K){for(var $=0,L=["REFLECTIONMAP_CUBIC","REFLECTIONMAP_EXPLICIT","REFLECTIONMAP_PLANAR","REFLECTIONMAP_PROJECTION","REFLECTIONMAP_PROJECTION","REFLECTIONMAP_SKYBOX","REFLECTIONMAP_SPHERICAL","REFLECTIONMAP_EQUIRECTANGULAR","REFLECTIONMAP_EQUIRECTANGULAR_FIXED","REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED"];$<L.length;$++){var G=L[$];this[G]=G===K}},ee}(A.a),pe=function(ae){function ee(K,$){var L=ae.call(this,K,$)||this;return L._diffuseTexture=null,L._ambientTexture=null,L._opacityTexture=null,L._reflectionTexture=null,L._emissiveTexture=null,L._specularTexture=null,L._bumpTexture=null,L._lightmapTexture=null,L._refractionTexture=null,L.ambientColor=new R.a(0,0,0),L.diffuseColor=new R.a(1,1,1),L.specularColor=new R.a(1,1,1),L.emissiveColor=new R.a(0,0,0),L.specularPower=64,L._useAlphaFromDiffuseTexture=!1,L._useEmissiveAsIllumination=!1,L._linkEmissiveWithDiffuse=!1,L._useSpecularOverAlpha=!1,L._useReflectionOverAlpha=!1,L._disableLighting=!1,L._useObjectSpaceNormalMap=!1,L._useParallax=!1,L._useParallaxOcclusion=!1,L.parallaxScaleBias=.05,L._roughness=0,L.indexOfRefraction=.98,L.invertRefractionY=!0,L.alphaCutOff=.4,L._useLightmapAsShadowmap=!1,L._useReflectionFresnelFromSpecular=!1,L._useGlossinessFromSpecularMapAlpha=!1,L._maxSimultaneousLights=4,L._invertNormalMapX=!1,L._invertNormalMapY=!1,L._twoSidedLighting=!1,L.detailMap=new ne.a(L._markAllSubMeshesAsTexturesDirty.bind(L)),L._renderTargets=new x.a(16),L._worldViewProjectionMatrix=M.a.Zero(),L._globalAmbientColor=new R.a(0,0,0),L._rebuildInParallel=!1,L._attachImageProcessingConfiguration(null),L.prePassConfiguration=new m.a,L.getRenderTargetTextures=function(){return L._renderTargets.reset(),ee.ReflectionTextureEnabled&&L._reflectionTexture&&L._reflectionTexture.isRenderTarget&&L._renderTargets.push(L._reflectionTexture),ee.RefractionTextureEnabled&&L._refractionTexture&&L._refractionTexture.isRenderTarget&&L._renderTargets.push(L._refractionTexture),L._renderTargets},L}return Object(U.d)(ee,ae),Object.defineProperty(ee.prototype,"imageProcessingConfiguration",{get:function(){return this._imageProcessingConfiguration},set:function(K){this._attachImageProcessingConfiguration(K),this._markAllSubMeshesAsTexturesDirty()},enumerable:!1,configurable:!0}),ee.prototype._attachImageProcessingConfiguration=function(K){var $=this;K!==this._imageProcessingConfiguration&&(this._imageProcessingConfiguration&&this._imageProcessingObserver&&this._imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingObserver),this._imageProcessingConfiguration=K||this.getScene().imageProcessingConfiguration,this._imageProcessingConfiguration&&(this._imageProcessingObserver=this._imageProcessingConfiguration.onUpdateParameters.add(function(){$._markAllSubMeshesAsImageProcessingDirty()})))},Object.defineProperty(ee.prototype,"cameraColorCurvesEnabled",{get:function(){return this.imageProcessingConfiguration.colorCurvesEnabled},set:function(K){this.imageProcessingConfiguration.colorCurvesEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee.prototype,"cameraColorGradingEnabled",{get:function(){return this.imageProcessingConfiguration.colorGradingEnabled},set:function(K){this.imageProcessingConfiguration.colorGradingEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee.prototype,"cameraToneMappingEnabled",{get:function(){return this._imageProcessingConfiguration.toneMappingEnabled},set:function(K){this._imageProcessingConfiguration.toneMappingEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee.prototype,"cameraExposure",{get:function(){return this._imageProcessingConfiguration.exposure},set:function(K){this._imageProcessingConfiguration.exposure=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee.prototype,"cameraContrast",{get:function(){return this._imageProcessingConfiguration.contrast},set:function(K){this._imageProcessingConfiguration.contrast=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee.prototype,"cameraColorGradingTexture",{get:function(){return this._imageProcessingConfiguration.colorGradingTexture},set:function(K){this._imageProcessingConfiguration.colorGradingTexture=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee.prototype,"cameraColorCurves",{get:function(){return this._imageProcessingConfiguration.colorCurves},set:function(K){this._imageProcessingConfiguration.colorCurves=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee.prototype,"canRenderToMRT",{get:function(){return!0},enumerable:!1,configurable:!0}),Object.defineProperty(ee.prototype,"hasRenderTargetTextures",{get:function(){return!!(ee.ReflectionTextureEnabled&&this._reflectionTexture&&this._reflectionTexture.isRenderTarget)||!!(ee.RefractionTextureEnabled&&this._refractionTexture&&this._refractionTexture.isRenderTarget)},enumerable:!1,configurable:!0}),ee.prototype.getClassName=function(){return"StandardMaterial"},Object.defineProperty(ee.prototype,"useLogarithmicDepth",{get:function(){return this._useLogarithmicDepth},set:function(K){this._useLogarithmicDepth=K&&this.getScene().getEngine().getCaps().fragmentDepthSupported,this._markAllSubMeshesAsMiscDirty()},enumerable:!1,configurable:!0}),ee.prototype.needAlphaBlending=function(){return!this._disableAlphaBlending&&(this.alpha<1||this._opacityTexture!=null||this._shouldUseAlphaFromDiffuseTexture()||this._opacityFresnelParameters&&this._opacityFresnelParameters.isEnabled)},ee.prototype.needAlphaTesting=function(){return!!this._forceAlphaTest||this._hasAlphaChannel()&&(this._transparencyMode==null||this._transparencyMode===T.a.MATERIAL_ALPHATEST)},ee.prototype._shouldUseAlphaFromDiffuseTexture=function(){return this._diffuseTexture!=null&&this._diffuseTexture.hasAlpha&&this._useAlphaFromDiffuseTexture&&this._transparencyMode!==T.a.MATERIAL_OPAQUE},ee.prototype._hasAlphaChannel=function(){return this._diffuseTexture!=null&&this._diffuseTexture.hasAlpha||this._opacityTexture!=null},ee.prototype.getAlphaTestTexture=function(){return this._diffuseTexture},ee.prototype.isReadyForSubMesh=function(K,$,L){if(L===void 0&&(L=!1),$.effect&&this.isFrozen&&$.effect._wasPreviouslyReady)return!0;$._materialDefines||($._materialDefines=new de);var G=this.getScene(),Q=$._materialDefines;if(this._isReadyForSubMesh($))return!0;var oe=G.getEngine();if(Q._needNormals=g.a.PrepareDefinesForLights(G,K,Q,!0,this._maxSimultaneousLights,this._disableLighting),g.a.PrepareDefinesForMultiview(G,Q),g.a.PrepareDefinesForPrePass(G,Q,this.canRenderToMRT),Q._areTexturesDirty){if(Q._needUVs=!1,Q.MAINUV1=!1,Q.MAINUV2=!1,G.texturesEnabled){if(this._diffuseTexture&&ee.DiffuseTextureEnabled){if(!this._diffuseTexture.isReadyOrNotBlocking())return!1;g.a.PrepareDefinesForMergedUV(this._diffuseTexture,Q,"DIFFUSE")}else Q.DIFFUSE=!1;if(this._ambientTexture&&ee.AmbientTextureEnabled){if(!this._ambientTexture.isReadyOrNotBlocking())return!1;g.a.PrepareDefinesForMergedUV(this._ambientTexture,Q,"AMBIENT")}else Q.AMBIENT=!1;if(this._opacityTexture&&ee.OpacityTextureEnabled){if(!this._opacityTexture.isReadyOrNotBlocking())return!1;g.a.PrepareDefinesForMergedUV(this._opacityTexture,Q,"OPACITY"),Q.OPACITYRGB=this._opacityTexture.getAlphaFromRGB}else Q.OPACITY=!1;if(this._reflectionTexture&&ee.ReflectionTextureEnabled){if(!this._reflectionTexture.isReadyOrNotBlocking())return!1;switch(Q._needNormals=!0,Q.REFLECTION=!0,Q.ROUGHNESS=this._roughness>0,Q.REFLECTIONOVERALPHA=this._useReflectionOverAlpha,Q.INVERTCUBICMAP=this._reflectionTexture.coordinatesMode===l.a.INVCUBIC_MODE,Q.REFLECTIONMAP_3D=this._reflectionTexture.isCube,Q.RGBDREFLECTION=this._reflectionTexture.isRGBD,this._reflectionTexture.coordinatesMode){case l.a.EXPLICIT_MODE:Q.setReflectionMode("REFLECTIONMAP_EXPLICIT");break;case l.a.PLANAR_MODE:Q.setReflectionMode("REFLECTIONMAP_PLANAR");break;case l.a.PROJECTION_MODE:Q.setReflectionMode("REFLECTIONMAP_PROJECTION");break;case l.a.SKYBOX_MODE:Q.setReflectionMode("REFLECTIONMAP_SKYBOX");break;case l.a.SPHERICAL_MODE:Q.setReflectionMode("REFLECTIONMAP_SPHERICAL");break;case l.a.EQUIRECTANGULAR_MODE:Q.setReflectionMode("REFLECTIONMAP_EQUIRECTANGULAR");break;case l.a.FIXED_EQUIRECTANGULAR_MODE:Q.setReflectionMode("REFLECTIONMAP_EQUIRECTANGULAR_FIXED");break;case l.a.FIXED_EQUIRECTANGULAR_MIRRORED_MODE:Q.setReflectionMode("REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED");break;case l.a.CUBIC_MODE:case l.a.INVCUBIC_MODE:default:Q.setReflectionMode("REFLECTIONMAP_CUBIC")}Q.USE_LOCAL_REFLECTIONMAP_CUBIC=!!this._reflectionTexture.boundingBoxSize}else Q.REFLECTION=!1;if(this._emissiveTexture&&ee.EmissiveTextureEnabled){if(!this._emissiveTexture.isReadyOrNotBlocking())return!1;g.a.PrepareDefinesForMergedUV(this._emissiveTexture,Q,"EMISSIVE")}else Q.EMISSIVE=!1;if(this._lightmapTexture&&ee.LightmapTextureEnabled){if(!this._lightmapTexture.isReadyOrNotBlocking())return!1;g.a.PrepareDefinesForMergedUV(this._lightmapTexture,Q,"LIGHTMAP"),Q.USELIGHTMAPASSHADOWMAP=this._useLightmapAsShadowmap,Q.RGBDLIGHTMAP=this._lightmapTexture.isRGBD}else Q.LIGHTMAP=!1;if(this._specularTexture&&ee.SpecularTextureEnabled){if(!this._specularTexture.isReadyOrNotBlocking())return!1;g.a.PrepareDefinesForMergedUV(this._specularTexture,Q,"SPECULAR"),Q.GLOSSINESS=this._useGlossinessFromSpecularMapAlpha}else Q.SPECULAR=!1;if(G.getEngine().getCaps().standardDerivatives&&this._bumpTexture&&ee.BumpTextureEnabled){if(!this._bumpTexture.isReady())return!1;g.a.PrepareDefinesForMergedUV(this._bumpTexture,Q,"BUMP"),Q.PARALLAX=this._useParallax,Q.PARALLAXOCCLUSION=this._useParallaxOcclusion,Q.OBJECTSPACE_NORMALMAP=this._useObjectSpaceNormalMap}else Q.BUMP=!1;if(this._refractionTexture&&ee.RefractionTextureEnabled){if(!this._refractionTexture.isReadyOrNotBlocking())return!1;Q._needUVs=!0,Q.REFRACTION=!0,Q.REFRACTIONMAP_3D=this._refractionTexture.isCube,Q.RGBDREFRACTION=this._refractionTexture.isRGBD}else Q.REFRACTION=!1;Q.TWOSIDEDLIGHTING=!this._backFaceCulling&&this._twoSidedLighting}else Q.DIFFUSE=!1,Q.AMBIENT=!1,Q.OPACITY=!1,Q.REFLECTION=!1,Q.EMISSIVE=!1,Q.LIGHTMAP=!1,Q.BUMP=!1,Q.REFRACTION=!1;Q.ALPHAFROMDIFFUSE=this._shouldUseAlphaFromDiffuseTexture(),Q.EMISSIVEASILLUMINATION=this._useEmissiveAsIllumination,Q.LINKEMISSIVEWITHDIFFUSE=this._linkEmissiveWithDiffuse,Q.SPECULAROVERALPHA=this._useSpecularOverAlpha,Q.PREMULTIPLYALPHA=this.alphaMode===X.a.ALPHA_PREMULTIPLIED||this.alphaMode===X.a.ALPHA_PREMULTIPLIED_PORTERDUFF,Q.ALPHATEST_AFTERALLALPHACOMPUTATIONS=this.transparencyMode!==null,Q.ALPHABLEND=this.transparencyMode===null||this.needAlphaBlendingForMesh(K)}if(!this.detailMap.isReadyForSubMesh(Q,G))return!1;if(Q._areImageProcessingDirty&&this._imageProcessingConfiguration){if(!this._imageProcessingConfiguration.isReady())return!1;this._imageProcessingConfiguration.prepareDefines(Q),Q.IS_REFLECTION_LINEAR=this.reflectionTexture!=null&&!this.reflectionTexture.gammaSpace,Q.IS_REFRACTION_LINEAR=this.refractionTexture!=null&&!this.refractionTexture.gammaSpace}if(Q._areFresnelDirty&&(ee.FresnelEnabled?(this._diffuseFresnelParameters||this._opacityFresnelParameters||this._emissiveFresnelParameters||this._refractionFresnelParameters||this._reflectionFresnelParameters)&&(Q.DIFFUSEFRESNEL=this._diffuseFresnelParameters&&this._diffuseFresnelParameters.isEnabled,Q.OPACITYFRESNEL=this._opacityFresnelParameters&&this._opacityFresnelParameters.isEnabled,Q.REFLECTIONFRESNEL=this._reflectionFresnelParameters&&this._reflectionFresnelParameters.isEnabled,Q.REFLECTIONFRESNELFROMSPECULAR=this._useReflectionFresnelFromSpecular,Q.REFRACTIONFRESNEL=this._refractionFresnelParameters&&this._refractionFresnelParameters.isEnabled,Q.EMISSIVEFRESNEL=this._emissiveFresnelParameters&&this._emissiveFresnelParameters.isEnabled,Q._needNormals=!0,Q.FRESNEL=!0):Q.FRESNEL=!1),g.a.PrepareDefinesForMisc(K,G,this._useLogarithmicDepth,this.pointsCloud,this.fogEnabled,this._shouldTurnAlphaTestOn(K)||this._forceAlphaTest,Q),g.a.PrepareDefinesForAttributes(K,Q,!0,!0,!0),g.a.PrepareDefinesForFrameBoundValues(G,oe,Q,L,null,$.getRenderingMesh().hasThinInstances),this.detailMap.prepareDefines(Q,G),Q.isDirty){var re=Q._areLightsDisposed;Q.markAsProcessed();var Y=new j.a;Q.REFLECTION&&Y.addFallback(0,"REFLECTION"),Q.SPECULAR&&Y.addFallback(0,"SPECULAR"),Q.BUMP&&Y.addFallback(0,"BUMP"),Q.PARALLAX&&Y.addFallback(1,"PARALLAX"),Q.PARALLAXOCCLUSION&&Y.addFallback(0,"PARALLAXOCCLUSION"),Q.SPECULAROVERALPHA&&Y.addFallback(0,"SPECULAROVERALPHA"),Q.FOG&&Y.addFallback(1,"FOG"),Q.POINTSIZE&&Y.addFallback(0,"POINTSIZE"),Q.LOGARITHMICDEPTH&&Y.addFallback(0,"LOGARITHMICDEPTH"),g.a.HandleFallbacksForShadows(Q,Y,this._maxSimultaneousLights),Q.SPECULARTERM&&Y.addFallback(0,"SPECULARTERM"),Q.DIFFUSEFRESNEL&&Y.addFallback(1,"DIFFUSEFRESNEL"),Q.OPACITYFRESNEL&&Y.addFallback(2,"OPACITYFRESNEL"),Q.REFLECTIONFRESNEL&&Y.addFallback(3,"REFLECTIONFRESNEL"),Q.EMISSIVEFRESNEL&&Y.addFallback(4,"EMISSIVEFRESNEL"),Q.FRESNEL&&Y.addFallback(4,"FRESNEL"),Q.MULTIVIEW&&Y.addFallback(0,"MULTIVIEW");var k=[C.b.PositionKind];Q.NORMAL&&k.push(C.b.NormalKind),Q.UV1&&k.push(C.b.UVKind),Q.UV2&&k.push(C.b.UV2Kind),Q.VERTEXCOLOR&&k.push(C.b.ColorKind),g.a.PrepareAttributesForBones(k,K,Q,Y),g.a.PrepareAttributesForInstances(k,Q),g.a.PrepareAttributesForMorphTargets(k,K,Q);var H="default",Z=["world","view","viewProjection","vEyePosition","vLightsType","vAmbientColor","vDiffuseColor","vSpecularColor","vEmissiveColor","visibility","vFogInfos","vFogColor","pointSize","vDiffuseInfos","vAmbientInfos","vOpacityInfos","vReflectionInfos","vEmissiveInfos","vSpecularInfos","vBumpInfos","vLightmapInfos","vRefractionInfos","mBones","vClipPlane","vClipPlane2","vClipPlane3","vClipPlane4","vClipPlane5","vClipPlane6","diffuseMatrix","ambientMatrix","opacityMatrix","reflectionMatrix","emissiveMatrix","specularMatrix","bumpMatrix","normalMatrix","lightmapMatrix","refractionMatrix","diffuseLeftColor","diffuseRightColor","opacityParts","reflectionLeftColor","reflectionRightColor","emissiveLeftColor","emissiveRightColor","refractionLeftColor","refractionRightColor","vReflectionPosition","vReflectionSize","logarithmicDepthConstant","vTangentSpaceParams","alphaCutOff","boneTextureWidth"],W=["diffuseSampler","ambientSampler","opacitySampler","reflectionCubeSampler","reflection2DSampler","emissiveSampler","specularSampler","bumpSampler","lightmapSampler","refractionCubeSampler","refraction2DSampler","boneSampler"],q=["Material","Scene"];ne.a.AddUniforms(Z),ne.a.AddSamplers(W),m.a.AddUniforms(Z),m.a.AddSamplers(Z),c.a&&(c.a.PrepareUniforms(Z,Q),c.a.PrepareSamplers(W,Q)),g.a.PrepareUniformsAndSamplersList({uniformsNames:Z,uniformBuffersNames:q,samplers:W,defines:Q,maxSimultaneousLights:this._maxSimultaneousLights});var he={};this.customShaderNameResolve&&(H=this.customShaderNameResolve(H,Z,q,W,Q,k,he));var ge=Q.toString(),me=$.effect,_e=G.getEngine().createEffect(H,{attributes:k,uniformsNames:Z,uniformBuffersNames:q,samplers:W,defines:ge,fallbacks:Y,onCompiled:this.onCompiled,onError:this.onError,indexParameters:{maxSimultaneousLights:this._maxSimultaneousLights,maxSimultaneousMorphTargets:Q.NUM_MORPH_INFLUENCERS},processFinalCode:he.processFinalCode,multiTarget:Q.PREPASS},oe);if(_e)if(this._onEffectCreatedObservable&&(te.effect=_e,te.subMesh=$,this._onEffectCreatedObservable.notifyObservers(te)),this.allowShaderHotSwapping&&me&&!_e.isReady()){if(_e=me,this._rebuildInParallel=!0,Q.markAsUnprocessed(),re)return Q._areLightsDisposed=!0,!1}else this._rebuildInParallel=!1,G.resetCachedMaterial(),$.setEffect(_e,Q),this.buildUniformLayout()}return!(!$.effect||!$.effect.isReady())&&(Q._renderId=G.getRenderId(),$.effect._wasPreviouslyReady=!0,!0)},ee.prototype.buildUniformLayout=function(){var K=this._uniformBuffer;K.addUniform("diffuseLeftColor",4),K.addUniform("diffuseRightColor",4),K.addUniform("opacityParts",4),K.addUniform("reflectionLeftColor",4),K.addUniform("reflectionRightColor",4),K.addUniform("refractionLeftColor",4),K.addUniform("refractionRightColor",4),K.addUniform("emissiveLeftColor",4),K.addUniform("emissiveRightColor",4),K.addUniform("vDiffuseInfos",2),K.addUniform("vAmbientInfos",2),K.addUniform("vOpacityInfos",2),K.addUniform("vReflectionInfos",2),K.addUniform("vReflectionPosition",3),K.addUniform("vReflectionSize",3),K.addUniform("vEmissiveInfos",2),K.addUniform("vLightmapInfos",2),K.addUniform("vSpecularInfos",2),K.addUniform("vBumpInfos",3),K.addUniform("diffuseMatrix",16),K.addUniform("ambientMatrix",16),K.addUniform("opacityMatrix",16),K.addUniform("reflectionMatrix",16),K.addUniform("emissiveMatrix",16),K.addUniform("lightmapMatrix",16),K.addUniform("specularMatrix",16),K.addUniform("bumpMatrix",16),K.addUniform("vTangentSpaceParams",2),K.addUniform("pointSize",1),K.addUniform("refractionMatrix",16),K.addUniform("vRefractionInfos",4),K.addUniform("vSpecularColor",4),K.addUniform("vEmissiveColor",3),K.addUniform("visibility",1),K.addUniform("vDiffuseColor",4),ne.a.PrepareUniformBuffer(K),K.create()},ee.prototype.unbind=function(){if(this._activeEffect){var K=!1;this._reflectionTexture&&this._reflectionTexture.isRenderTarget&&(this._activeEffect.setTexture("reflection2DSampler",null),K=!0),this._refractionTexture&&this._refractionTexture.isRenderTarget&&(this._activeEffect.setTexture("refraction2DSampler",null),K=!0),K&&this._markAllSubMeshesAsTexturesDirty()}ae.prototype.unbind.call(this)},ee.prototype.bindForSubMesh=function(K,$,L){var G=this.getScene(),Q=L._materialDefines;if(Q){var oe=L.effect;if(oe){this._activeEffect=oe,Q.INSTANCES&&!Q.THIN_INSTANCES||this.bindOnlyWorldMatrix(K),this.prePassConfiguration.bindForSubMesh(this._activeEffect,G,$,K,this.isFrozen),Q.OBJECTSPACE_NORMALMAP&&(K.toNormalMatrix(this._normalMatrix),this.bindOnlyNormalMatrix(this._normalMatrix));var re=this._mustRebind(G,oe,$.visibility);g.a.BindBonesParameters($,oe);var Y=this._uniformBuffer;if(re){if(Y.bindToEffect(oe,"Material"),this.bindViewProjection(oe),!Y.useUbo||!this.isFrozen||!Y.isSync){if(ee.FresnelEnabled&&Q.FRESNEL&&(this.diffuseFresnelParameters&&this.diffuseFresnelParameters.isEnabled&&(Y.updateColor4("diffuseLeftColor",this.diffuseFresnelParameters.leftColor,this.diffuseFresnelParameters.power),Y.updateColor4("diffuseRightColor",this.diffuseFresnelParameters.rightColor,this.diffuseFresnelParameters.bias)),this.opacityFresnelParameters&&this.opacityFresnelParameters.isEnabled&&Y.updateColor4("opacityParts",new R.a(this.opacityFresnelParameters.leftColor.toLuminance(),this.opacityFresnelParameters.rightColor.toLuminance(),this.opacityFresnelParameters.bias),this.opacityFresnelParameters.power),this.reflectionFresnelParameters&&this.reflectionFresnelParameters.isEnabled&&(Y.updateColor4("reflectionLeftColor",this.reflectionFresnelParameters.leftColor,this.reflectionFresnelParameters.power),Y.updateColor4("reflectionRightColor",this.reflectionFresnelParameters.rightColor,this.reflectionFresnelParameters.bias)),this.refractionFresnelParameters&&this.refractionFresnelParameters.isEnabled&&(Y.updateColor4("refractionLeftColor",this.refractionFresnelParameters.leftColor,this.refractionFresnelParameters.power),Y.updateColor4("refractionRightColor",this.refractionFresnelParameters.rightColor,this.refractionFresnelParameters.bias)),this.emissiveFresnelParameters&&this.emissiveFresnelParameters.isEnabled&&(Y.updateColor4("emissiveLeftColor",this.emissiveFresnelParameters.leftColor,this.emissiveFresnelParameters.power),Y.updateColor4("emissiveRightColor",this.emissiveFresnelParameters.rightColor,this.emissiveFresnelParameters.bias))),G.texturesEnabled){if(this._diffuseTexture&&ee.DiffuseTextureEnabled&&(Y.updateFloat2("vDiffuseInfos",this._diffuseTexture.coordinatesIndex,this._diffuseTexture.level),g.a.BindTextureMatrix(this._diffuseTexture,Y,"diffuse")),this._ambientTexture&&ee.AmbientTextureEnabled&&(Y.updateFloat2("vAmbientInfos",this._ambientTexture.coordinatesIndex,this._ambientTexture.level),g.a.BindTextureMatrix(this._ambientTexture,Y,"ambient")),this._opacityTexture&&ee.OpacityTextureEnabled&&(Y.updateFloat2("vOpacityInfos",this._opacityTexture.coordinatesIndex,this._opacityTexture.level),g.a.BindTextureMatrix(this._opacityTexture,Y,"opacity")),this._hasAlphaChannel()&&oe.setFloat("alphaCutOff",this.alphaCutOff),this._reflectionTexture&&ee.ReflectionTextureEnabled&&(Y.updateFloat2("vReflectionInfos",this._reflectionTexture.level,this.roughness),Y.updateMatrix("reflectionMatrix",this._reflectionTexture.getReflectionTextureMatrix()),this._reflectionTexture.boundingBoxSize)){var k=this._reflectionTexture;Y.updateVector3("vReflectionPosition",k.boundingBoxPosition),Y.updateVector3("vReflectionSize",k.boundingBoxSize)}if(this._emissiveTexture&&ee.EmissiveTextureEnabled&&(Y.updateFloat2("vEmissiveInfos",this._emissiveTexture.coordinatesIndex,this._emissiveTexture.level),g.a.BindTextureMatrix(this._emissiveTexture,Y,"emissive")),this._lightmapTexture&&ee.LightmapTextureEnabled&&(Y.updateFloat2("vLightmapInfos",this._lightmapTexture.coordinatesIndex,this._lightmapTexture.level),g.a.BindTextureMatrix(this._lightmapTexture,Y,"lightmap")),this._specularTexture&&ee.SpecularTextureEnabled&&(Y.updateFloat2("vSpecularInfos",this._specularTexture.coordinatesIndex,this._specularTexture.level),g.a.BindTextureMatrix(this._specularTexture,Y,"specular")),this._bumpTexture&&G.getEngine().getCaps().standardDerivatives&&ee.BumpTextureEnabled&&(Y.updateFloat3("vBumpInfos",this._bumpTexture.coordinatesIndex,1/this._bumpTexture.level,this.parallaxScaleBias),g.a.BindTextureMatrix(this._bumpTexture,Y,"bump"),G._mirroredCameraPosition?Y.updateFloat2("vTangentSpaceParams",this._invertNormalMapX?1:-1,this._invertNormalMapY?1:-1):Y.updateFloat2("vTangentSpaceParams",this._invertNormalMapX?-1:1,this._invertNormalMapY?-1:1)),this._refractionTexture&&ee.RefractionTextureEnabled){var H=1;this._refractionTexture.isCube||(Y.updateMatrix("refractionMatrix",this._refractionTexture.getReflectionTextureMatrix()),this._refractionTexture.depth&&(H=this._refractionTexture.depth)),Y.updateFloat4("vRefractionInfos",this._refractionTexture.level,this.indexOfRefraction,H,this.invertRefractionY?-1:1)}}this.pointsCloud&&Y.updateFloat("pointSize",this.pointSize),Q.SPECULARTERM&&Y.updateColor4("vSpecularColor",this.specularColor,this.specularPower),Y.updateColor3("vEmissiveColor",ee.EmissiveTextureEnabled?this.emissiveColor:R.a.BlackReadOnly),Y.updateColor4("vDiffuseColor",this.diffuseColor,this.alpha)}Y.updateFloat("visibility",$.visibility),G.texturesEnabled&&(this._diffuseTexture&&ee.DiffuseTextureEnabled&&oe.setTexture("diffuseSampler",this._diffuseTexture),this._ambientTexture&&ee.AmbientTextureEnabled&&oe.setTexture("ambientSampler",this._ambientTexture),this._opacityTexture&&ee.OpacityTextureEnabled&&oe.setTexture("opacitySampler",this._opacityTexture),this._reflectionTexture&&ee.ReflectionTextureEnabled&&(this._reflectionTexture.isCube?oe.setTexture("reflectionCubeSampler",this._reflectionTexture):oe.setTexture("reflection2DSampler",this._reflectionTexture)),this._emissiveTexture&&ee.EmissiveTextureEnabled&&oe.setTexture("emissiveSampler",this._emissiveTexture),this._lightmapTexture&&ee.LightmapTextureEnabled&&oe.setTexture("lightmapSampler",this._lightmapTexture),this._specularTexture&&ee.SpecularTextureEnabled&&oe.setTexture("specularSampler",this._specularTexture),this._bumpTexture&&G.getEngine().getCaps().standardDerivatives&&ee.BumpTextureEnabled&&oe.setTexture("bumpSampler",this._bumpTexture),this._refractionTexture&&ee.RefractionTextureEnabled)&&(H=1,this._refractionTexture.isCube?oe.setTexture("refractionCubeSampler",this._refractionTexture):oe.setTexture("refraction2DSampler",this._refractionTexture)),this.detailMap.bindForSubMesh(Y,G,this.isFrozen),g.a.BindClipPlane(oe,G),G.ambientColor.multiplyToRef(this.ambientColor,this._globalAmbientColor),g.a.BindEyePosition(oe,G),oe.setColor3("vAmbientColor",this._globalAmbientColor)}!re&&this.isFrozen||(G.lightsEnabled&&!this._disableLighting&&g.a.BindLights(G,$,oe,Q,this._maxSimultaneousLights,this._rebuildInParallel),(G.fogEnabled&&$.applyFog&&G.fogMode!==u.a.FOGMODE_NONE||this._reflectionTexture||this._refractionTexture)&&this.bindView(oe),g.a.BindFogParameters(G,$,oe),Q.NUM_MORPH_INFLUENCERS&&g.a.BindMorphTargetParameters($,oe),this.useLogarithmicDepth&&g.a.BindLogDepth(Q,oe,G),this._imageProcessingConfiguration&&!this._imageProcessingConfiguration.applyByPostProcess&&this._imageProcessingConfiguration.bind(this._activeEffect)),Y.update(),this._afterBind($,this._activeEffect)}}},ee.prototype.getAnimatables=function(){var K=[];return this._diffuseTexture&&this._diffuseTexture.animations&&this._diffuseTexture.animations.length>0&&K.push(this._diffuseTexture),this._ambientTexture&&this._ambientTexture.animations&&this._ambientTexture.animations.length>0&&K.push(this._ambientTexture),this._opacityTexture&&this._opacityTexture.animations&&this._opacityTexture.animations.length>0&&K.push(this._opacityTexture),this._reflectionTexture&&this._reflectionTexture.animations&&this._reflectionTexture.animations.length>0&&K.push(this._reflectionTexture),this._emissiveTexture&&this._emissiveTexture.animations&&this._emissiveTexture.animations.length>0&&K.push(this._emissiveTexture),this._specularTexture&&this._specularTexture.animations&&this._specularTexture.animations.length>0&&K.push(this._specularTexture),this._bumpTexture&&this._bumpTexture.animations&&this._bumpTexture.animations.length>0&&K.push(this._bumpTexture),this._lightmapTexture&&this._lightmapTexture.animations&&this._lightmapTexture.animations.length>0&&K.push(this._lightmapTexture),this._refractionTexture&&this._refractionTexture.animations&&this._refractionTexture.animations.length>0&&K.push(this._refractionTexture),this.detailMap.getAnimatables(K),K},ee.prototype.getActiveTextures=function(){var K=ae.prototype.getActiveTextures.call(this);return this._diffuseTexture&&K.push(this._diffuseTexture),this._ambientTexture&&K.push(this._ambientTexture),this._opacityTexture&&K.push(this._opacityTexture),this._reflectionTexture&&K.push(this._reflectionTexture),this._emissiveTexture&&K.push(this._emissiveTexture),this._specularTexture&&K.push(this._specularTexture),this._bumpTexture&&K.push(this._bumpTexture),this._lightmapTexture&&K.push(this._lightmapTexture),this._refractionTexture&&K.push(this._refractionTexture),this.detailMap.getActiveTextures(K),K},ee.prototype.hasTexture=function(K){return!!ae.prototype.hasTexture.call(this,K)||this._diffuseTexture===K||this._ambientTexture===K||this._opacityTexture===K||this._reflectionTexture===K||this._emissiveTexture===K||this._specularTexture===K||this._bumpTexture===K||this._lightmapTexture===K||this._refractionTexture===K||this.detailMap.hasTexture(K)},ee.prototype.dispose=function(K,$){var L,G,Q,oe,re,Y,k,H,Z;$&&((L=this._diffuseTexture)===null||L===void 0||L.dispose(),(G=this._ambientTexture)===null||G===void 0||G.dispose(),(Q=this._opacityTexture)===null||Q===void 0||Q.dispose(),(oe=this._reflectionTexture)===null||oe===void 0||oe.dispose(),(re=this._emissiveTexture)===null||re===void 0||re.dispose(),(Y=this._specularTexture)===null||Y===void 0||Y.dispose(),(k=this._bumpTexture)===null||k===void 0||k.dispose(),(H=this._lightmapTexture)===null||H===void 0||H.dispose(),(Z=this._refractionTexture)===null||Z===void 0||Z.dispose()),this.detailMap.dispose($),this._imageProcessingConfiguration&&this._imageProcessingObserver&&this._imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingObserver),ae.prototype.dispose.call(this,K,$)},ee.prototype.clone=function(K){var $=this,L=_.a.Clone(function(){return new ee(K,$.getScene())},this);return L.name=K,L.id=K,L},ee.prototype.serialize=function(){return _.a.Serialize(this)},ee.Parse=function(K,$,L){return _.a.Parse(function(){return new ee(K.name,$)},K,$,L)},Object.defineProperty(ee,"DiffuseTextureEnabled",{get:function(){return v.a.DiffuseTextureEnabled},set:function(K){v.a.DiffuseTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"DetailTextureEnabled",{get:function(){return v.a.DetailTextureEnabled},set:function(K){v.a.DetailTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"AmbientTextureEnabled",{get:function(){return v.a.AmbientTextureEnabled},set:function(K){v.a.AmbientTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"OpacityTextureEnabled",{get:function(){return v.a.OpacityTextureEnabled},set:function(K){v.a.OpacityTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"ReflectionTextureEnabled",{get:function(){return v.a.ReflectionTextureEnabled},set:function(K){v.a.ReflectionTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"EmissiveTextureEnabled",{get:function(){return v.a.EmissiveTextureEnabled},set:function(K){v.a.EmissiveTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"SpecularTextureEnabled",{get:function(){return v.a.SpecularTextureEnabled},set:function(K){v.a.SpecularTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"BumpTextureEnabled",{get:function(){return v.a.BumpTextureEnabled},set:function(K){v.a.BumpTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"LightmapTextureEnabled",{get:function(){return v.a.LightmapTextureEnabled},set:function(K){v.a.LightmapTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"RefractionTextureEnabled",{get:function(){return v.a.RefractionTextureEnabled},set:function(K){v.a.RefractionTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"ColorGradingTextureEnabled",{get:function(){return v.a.ColorGradingTextureEnabled},set:function(K){v.a.ColorGradingTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"FresnelEnabled",{get:function(){return v.a.FresnelEnabled},set:function(K){v.a.FresnelEnabled=K},enumerable:!1,configurable:!0}),Object(U.c)([Object(_.m)("diffuseTexture")],ee.prototype,"_diffuseTexture",void 0),Object(U.c)([Object(_.b)("_markAllSubMeshesAsTexturesAndMiscDirty")],ee.prototype,"diffuseTexture",void 0),Object(U.c)([Object(_.m)("ambientTexture")],ee.prototype,"_ambientTexture",void 0),Object(U.c)([Object(_.b)("_markAllSubMeshesAsTexturesDirty")],ee.prototype,"ambientTexture",void 0),Object(U.c)([Object(_.m)("opacityTexture")],ee.prototype,"_opacityTexture",void 0),Object(U.c)([Object(_.b)("_markAllSubMeshesAsTexturesAndMiscDirty")],ee.prototype,"opacityTexture",void 0),Object(U.c)([Object(_.m)("reflectionTexture")],ee.prototype,"_reflectionTexture",void 0),Object(U.c)([Object(_.b)("_markAllSubMeshesAsTexturesDirty")],ee.prototype,"reflectionTexture",void 0),Object(U.c)([Object(_.m)("emissiveTexture")],ee.prototype,"_emissiveTexture",void 0),Object(U.c)([Object(_.b)("_markAllSubMeshesAsTexturesDirty")],ee.prototype,"emissiveTexture",void 0),Object(U.c)([Object(_.m)("specularTexture")],ee.prototype,"_specularTexture",void 0),Object(U.c)([Object(_.b)("_markAllSubMeshesAsTexturesDirty")],ee.prototype,"specularTexture",void 0),Object(U.c)([Object(_.m)("bumpTexture")],ee.prototype,"_bumpTexture",void 0),Object(U.c)([Object(_.b)("_markAllSubMeshesAsTexturesDirty")],ee.prototype,"bumpTexture",void 0),Object(U.c)([Object(_.m)("lightmapTexture")],ee.prototype,"_lightmapTexture",void 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this._internalAbstractMeshDataInfo._numBoneInfluencers},set:function(j){this._internalAbstractMeshDataInfo._numBoneInfluencers!==j&&(this._internalAbstractMeshDataInfo._numBoneInfluencers=j,this._markSubMeshesAsAttributesDirty())},enumerable:!1,configurable:!0}),Object.defineProperty(X.prototype,"applyFog",{get:function(){return this._internalAbstractMeshDataInfo._applyFog},set:function(j){this._internalAbstractMeshDataInfo._applyFog!==j&&(this._internalAbstractMeshDataInfo._applyFog=j,this._markSubMeshesAsMiscDirty())},enumerable:!1,configurable:!0}),Object.defineProperty(X.prototype,"layerMask",{get:function(){return this._internalAbstractMeshDataInfo._layerMask},set:function(j){j!==this._internalAbstractMeshDataInfo._layerMask&&(this._internalAbstractMeshDataInfo._layerMask=j,this._resyncLightSources())},enumerable:!1,configurable:!0}),Object.defineProperty(X.prototype,"collisionMask",{get:function(){return 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this._renderId=j,!0},X.prototype._postActivate=function(){},X.prototype._freeze=function(){},X.prototype._unFreeze=function(){},X.prototype.getWorldMatrix=function(){return this._masterMesh&&this.billboardMode===m.a.BILLBOARDMODE_NONE?this._masterMesh.getWorldMatrix():V.prototype.getWorldMatrix.call(this)},X.prototype._getWorldMatrixDeterminant=function(){return this._masterMesh?this._masterMesh._getWorldMatrixDeterminant():V.prototype._getWorldMatrixDeterminant.call(this)},Object.defineProperty(X.prototype,"isAnInstance",{get:function(){return!1},enumerable:!1,configurable:!0}),Object.defineProperty(X.prototype,"hasInstances",{get:function(){return!1},enumerable:!1,configurable:!0}),Object.defineProperty(X.prototype,"hasThinInstances",{get:function(){return!1},enumerable:!1,configurable:!0}),X.prototype.movePOV=function(j,ne,te){return this.position.addInPlace(this.calcMovePOV(j,ne,te)),this},X.prototype.calcMovePOV=function(j,ne,te){var de=new u.a;(this.rotationQuaternion?this.rotationQuaternion:u.b.RotationYawPitchRoll(this.rotation.y,this.rotation.x,this.rotation.z)).toRotationMatrix(de);var pe=u.e.Zero(),ae=this.definedFacingForward?-1:1;return u.e.TransformCoordinatesFromFloatsToRef(j*ae,ne,te*ae,de,pe),pe},X.prototype.rotatePOV=function(j,ne,te){return this.rotation.addInPlace(this.calcRotatePOV(j,ne,te)),this},X.prototype.calcRotatePOV=function(j,ne,te){var de=this.definedFacingForward?1:-1;return new u.e(j*de,ne,te*de)},X.prototype.refreshBoundingInfo=function(j){return j===void 0&&(j=!1),this._boundingInfo&&this._boundingInfo.isLocked||this._refreshBoundingInfo(this._getPositionData(j),null),this},X.prototype._refreshBoundingInfo=function(j,ne){if(j){var te=Object(l.a)(j,0,this.getTotalVertices(),ne);this._boundingInfo?this._boundingInfo.reConstruct(te.minimum,te.maximum):this._boundingInfo=new T.a(te.minimum,te.maximum)}if(this.subMeshes)for(var de=0;de<this.subMeshes.length;de++)this.subMeshes[de].refreshBoundingInfo(j);this._updateBoundingInfo()},X.prototype._getPositionData=function(j){var ne=this.getVerticesData(R.b.PositionKind);if(ne&&j&&this.skeleton){ne=_.b.Slice(ne),this._generatePointsArray();var te=this.getVerticesData(R.b.MatricesIndicesKind),de=this.getVerticesData(R.b.MatricesWeightsKind);if(de&&te){var pe=this.numBoneInfluencers>4,ae=pe?this.getVerticesData(R.b.MatricesIndicesExtraKind):null,ee=pe?this.getVerticesData(R.b.MatricesWeightsExtraKind):null;this.skeleton.prepare();for(var K=this.skeleton.getTransformMatrices(this),$=u.c.Vector3[0],L=u.c.Matrix[0],G=u.c.Matrix[1],Q=0,oe=0;oe<ne.length;oe+=3,Q+=4){var re,Y;for(L.reset(),re=0;re<4;re++)(Y=de[Q+re])>0&&(u.a.FromFloat32ArrayToRefScaled(K,Math.floor(16*te[Q+re]),Y,G),L.addToSelf(G));if(pe)for(re=0;re<4;re++)(Y=ee[Q+re])>0&&(u.a.FromFloat32ArrayToRefScaled(K,Math.floor(16*ae[Q+re]),Y,G),L.addToSelf(G));u.e.TransformCoordinatesFromFloatsToRef(ne[oe],ne[oe+1],ne[oe+2],L,$),$.toArray(ne,oe),this._positions&&this._positions[oe/3].copyFrom($)}}}return ne},X.prototype._updateBoundingInfo=function(){var j=this._effectiveMesh;return this._boundingInfo?this._boundingInfo.update(j.worldMatrixFromCache):this._boundingInfo=new T.a(this.absolutePosition,this.absolutePosition,j.worldMatrixFromCache),this._updateSubMeshesBoundingInfo(j.worldMatrixFromCache),this},X.prototype._updateSubMeshesBoundingInfo=function(j){if(!this.subMeshes)return this;for(var ne=this.subMeshes.length,te=0;te<ne;te++){var de=this.subMeshes[te];(ne>1||!de.IsGlobal)&&de.updateBoundingInfo(j)}return this},X.prototype._afterComputeWorldMatrix=function(){this.doNotSyncBoundingInfo||this._updateBoundingInfo()},Object.defineProperty(X.prototype,"_effectiveMesh",{get:function(){return this.skeleton&&this.skeleton.overrideMesh||this},enumerable:!1,configurable:!0}),X.prototype.isInFrustum=function(j){return this._boundingInfo!==null&&this._boundingInfo.isInFrustum(j,this.cullingStrategy)},X.prototype.isCompletelyInFrustum=function(j){return this._boundingInfo!==null&&this._boundingInfo.isCompletelyInFrustum(j)},X.prototype.intersectsMesh=function(j,ne,te){if(ne===void 0&&(ne=!1),!this._boundingInfo||!j._boundingInfo)return!1;if(this._boundingInfo.intersects(j._boundingInfo,ne))return!0;if(te){for(var de=0,pe=this.getChildMeshes();de<pe.length;de++)if(pe[de].intersectsMesh(j,ne,!0))return!0}return!1},X.prototype.intersectsPoint=function(j){return!!this._boundingInfo&&this._boundingInfo.intersectsPoint(j)},Object.defineProperty(X.prototype,"checkCollisions",{get:function(){return this._meshCollisionData._checkCollisions},set:function(j){this._meshCollisionData._checkCollisions=j},enumerable:!1,configurable:!0}),Object.defineProperty(X.prototype,"collider",{get:function(){return this._meshCollisionData._collider},enumerable:!1,configurable:!0}),X.prototype.moveWithCollisions=function(j){this.getAbsolutePosition().addToRef(this.ellipsoidOffset,this._meshCollisionData._oldPositionForCollisions);var ne=this.getScene().collisionCoordinator;return this._meshCollisionData._collider||(this._meshCollisionData._collider=ne.createCollider()),this._meshCollisionData._collider._radius=this.ellipsoid,ne.getNewPosition(this._meshCollisionData._oldPositionForCollisions,j,this._meshCollisionData._collider,3,this,this._onCollisionPositionChange,this.uniqueId),this},X.prototype._collideForSubMesh=function(j,ne,te){if(this._generatePointsArray(),!this._positions)return this;if(!j._lastColliderWorldVertices||!j._lastColliderTransformMatrix.equals(ne)){j._lastColliderTransformMatrix=ne.clone(),j._lastColliderWorldVertices=[],j._trianglePlanes=[];for(var de=j.verticesStart,pe=j.verticesStart+j.verticesCount,ae=de;ae<pe;ae++)j._lastColliderWorldVertices.push(u.e.TransformCoordinates(this._positions[ae],ne))}return te._collide(j._trianglePlanes,j._lastColliderWorldVertices,this.getIndices(),j.indexStart,j.indexStart+j.indexCount,j.verticesStart,!!j.getMaterial(),this),this},X.prototype._processCollisionsForSubMeshes=function(j,ne){for(var te=this._scene.getCollidingSubMeshCandidates(this,j),de=te.length,pe=0;pe<de;pe++){var ae=te.data[pe];de>1&&!ae._checkCollision(j)||this._collideForSubMesh(ae,ne,j)}return this},X.prototype._checkCollision=function(j){if(!this._boundingInfo||!this._boundingInfo._checkCollision(j))return this;var ne=u.c.Matrix[0],te=u.c.Matrix[1];return u.a.ScalingToRef(1/j._radius.x,1/j._radius.y,1/j._radius.z,ne),this.worldMatrixFromCache.multiplyToRef(ne,te),this._processCollisionsForSubMeshes(j,te),this},X.prototype._generatePointsArray=function(){return!1},X.prototype.intersects=function(j,ne,te,de,pe,ae){var ee;de===void 0&&(de=!1),ae===void 0&&(ae=!1);var K=new c.a,$=this.getClassName()==="InstancedLinesMesh"||this.getClassName()==="LinesMesh"?this.intersectionThreshold:0,L=this._boundingInfo;if(!this.subMeshes||!L||!(ae||j.intersectsSphere(L.boundingSphere,$)&&j.intersectsBox(L.boundingBox,$)))return K;if(de)return K.hit=!ae,K.pickedMesh=ae?null:this,K.distance=ae?0:u.e.Distance(j.origin,L.boundingSphere.center),K.subMeshId=0,K;if(!this._generatePointsArray())return K;for(var G=null,Q=this._scene.getIntersectingSubMeshCandidates(this,j),oe=Q.length,re=!1,Y=0;Y<oe;Y++){var k=(H=Q.data[Y]).getMaterial();if(k&&(!((ee=this.getIndices())===null||ee===void 0)&&ee.length)&&(k.fillMode==A.a.MATERIAL_TriangleStripDrawMode||k.fillMode==A.a.MATERIAL_TriangleFillMode||k.fillMode==A.a.MATERIAL_WireFrameFillMode||k.fillMode==A.a.MATERIAL_PointFillMode)){re=!0;break}}if(!re)return K.hit=!0,K.pickedMesh=this,K.distance=u.e.Distance(j.origin,L.boundingSphere.center),K.subMeshId=-1,K;for(Y=0;Y<oe;Y++){var H=Q.data[Y];if(!(oe>1)||H.canIntersects(j)){var Z=H.intersects(j,this._positions,this.getIndices(),ne,te);if(Z&&(ne||!G||Z.distance<G.distance)&&((G=Z).subMeshId=Y,ne))break}}if(G){var W=pe??(this.skeleton&&this.skeleton.overrideMesh?this.skeleton.overrideMesh.getWorldMatrix():this.getWorldMatrix()),q=u.c.Vector3[0],he=u.c.Vector3[1];u.e.TransformCoordinatesToRef(j.origin,W,q),j.direction.scaleToRef(G.distance,he);var ge=u.e.TransformNormal(he,W).addInPlace(q);return K.hit=!0,K.distance=u.e.Distance(q,ge),K.pickedPoint=ge,K.pickedMesh=this,K.bu=G.bu||0,K.bv=G.bv||0,K.subMeshFaceId=G.faceId,K.faceId=G.faceId+Q.data[G.subMeshId].indexStart/(this.getClassName().indexOf("LinesMesh")!==-1?2:3),K.subMeshId=G.subMeshId,K}return K},X.prototype.clone=function(j,ne,te){return null},X.prototype.releaseSubMeshes=function(){if(this.subMeshes)for(;this.subMeshes.length;)this.subMeshes[0].dispose();else this.subMeshes=new Array;return this},X.prototype.dispose=function(j,ne){var te,de=this;for(ne===void 0&&(ne=!1),this._scene.useMaterialMeshMap&&this._material&&this._material.meshMap&&(this._material.meshMap[this.uniqueId]=void 0),this.getScene().freeActiveMeshes(),this.getScene().freeRenderingGroups(),this.actionManager!==void 0&&this.actionManager!==null&&(this.actionManager.dispose(),this.actionManager=null),this._internalAbstractMeshDataInfo._skeleton=null,this._transformMatrixTexture&&(this._transformMatrixTexture.dispose(),this._transformMatrixTexture=null),te=0;te<this._intersectionsInProgress.length;te++){var pe=this._intersectionsInProgress[te],ae=pe._intersectionsInProgress.indexOf(this);pe._intersectionsInProgress.splice(ae,1)}this._intersectionsInProgress=[],this.getScene().lights.forEach(function(K){var $=K.includedOnlyMeshes.indexOf(de);$!==-1&&K.includedOnlyMeshes.splice($,1),($=K.excludedMeshes.indexOf(de))!==-1&&K.excludedMeshes.splice($,1);var L=K.getShadowGenerator();if(L){var G=L.getShadowMap();G&&G.renderList&&($=G.renderList.indexOf(de))!==-1&&G.renderList.splice($,1)}}),this.getClassName()==="InstancedMesh"&&this.getClassName()==="InstancedLinesMesh"||this.releaseSubMeshes();var ee=this.getScene().getEngine();if(this._occlusionQuery&&(this.isOcclusionQueryInProgress=!1,ee.deleteQuery(this._occlusionQuery),this._occlusionQuery=null),ee.wipeCaches(),this.getScene().removeMesh(this),ne&&this.material&&(this.material.getClassName()==="MultiMaterial"?this.material.dispose(!1,!0,!0):this.material.dispose(!1,!0)),!j)for(te=0;te<this.getScene().particleSystems.length;te++)this.getScene().particleSystems[te].emitter===this&&(this.getScene().particleSystems[te].dispose(),te--);this._internalAbstractMeshDataInfo._facetData.facetDataEnabled&&this.disableFacetData(),this.onAfterWorldMatrixUpdateObservable.clear(),this.onCollideObservable.clear(),this.onCollisionPositionChangeObservable.clear(),this.onRebuildObservable.clear(),V.prototype.dispose.call(this,j,ne)},X.prototype.addChild=function(j){return j.setParent(this),this},X.prototype.removeChild=function(j){return j.setParent(null),this},X.prototype._initFacetData=function(){var j=this._internalAbstractMeshDataInfo._facetData;j.facetNormals||(j.facetNormals=new Array),j.facetPositions||(j.facetPositions=new Array),j.facetPartitioning||(j.facetPartitioning=new Array),j.facetNb=this.getIndices().length/3|0,j.partitioningSubdivisions=j.partitioningSubdivisions?j.partitioningSubdivisions:10,j.partitioningBBoxRatio=j.partitioningBBoxRatio?j.partitioningBBoxRatio:1.01;for(var ne=0;ne<j.facetNb;ne++)j.facetNormals[ne]=u.e.Zero(),j.facetPositions[ne]=u.e.Zero();return j.facetDataEnabled=!0,this},X.prototype.updateFacetData=function(){var j=this._internalAbstractMeshDataInfo._facetData;j.facetDataEnabled||this._initFacetData();var ne=this.getVerticesData(R.b.PositionKind),te=this.getIndices(),de=this.getVerticesData(R.b.NormalKind),pe=this.getBoundingInfo();if(j.facetDepthSort&&!j.facetDepthSortEnabled){if(j.facetDepthSortEnabled=!0,te instanceof Uint16Array)j.depthSortedIndices=new Uint16Array(te);else if(te instanceof Uint32Array)j.depthSortedIndices=new Uint32Array(te);else{for(var ae=!1,ee=0;ee<te.length;ee++)if(te[ee]>65535){ae=!0;break}j.depthSortedIndices=ae?new Uint32Array(te):new Uint16Array(te)}if(j.facetDepthSortFunction=function(re,Y){return Y.sqDistance-re.sqDistance},!j.facetDepthSortFrom){var K=this.getScene().activeCamera;j.facetDepthSortFrom=K?K.position:u.e.Zero()}j.depthSortedFacets=[];for(var $=0;$<j.facetNb;$++){var L={ind:3*$,sqDistance:0};j.depthSortedFacets.push(L)}j.invertedMatrix=u.a.Identity(),j.facetDepthSortOrigin=u.e.Zero()}j.bbSize.x=pe.maximum.x-pe.minimum.x>v.a?pe.maximum.x-pe.minimum.x:v.a,j.bbSize.y=pe.maximum.y-pe.minimum.y>v.a?pe.maximum.y-pe.minimum.y:v.a,j.bbSize.z=pe.maximum.z-pe.minimum.z>v.a?pe.maximum.z-pe.minimum.z:v.a;var G=j.bbSize.x>j.bbSize.y?j.bbSize.x:j.bbSize.y;if(G=G>j.bbSize.z?G:j.bbSize.z,j.subDiv.max=j.partitioningSubdivisions,j.subDiv.X=Math.floor(j.subDiv.max*j.bbSize.x/G),j.subDiv.Y=Math.floor(j.subDiv.max*j.bbSize.y/G),j.subDiv.Z=Math.floor(j.subDiv.max*j.bbSize.z/G),j.subDiv.X=j.subDiv.X<1?1:j.subDiv.X,j.subDiv.Y=j.subDiv.Y<1?1:j.subDiv.Y,j.subDiv.Z=j.subDiv.Z<1?1:j.subDiv.Z,j.facetParameters.facetNormals=this.getFacetLocalNormals(),j.facetParameters.facetPositions=this.getFacetLocalPositions(),j.facetParameters.facetPartitioning=this.getFacetLocalPartitioning(),j.facetParameters.bInfo=pe,j.facetParameters.bbSize=j.bbSize,j.facetParameters.subDiv=j.subDiv,j.facetParameters.ratio=this.partitioningBBoxRatio,j.facetParameters.depthSort=j.facetDepthSort,j.facetDepthSort&&j.facetDepthSortEnabled&&(this.computeWorldMatrix(!0),this._worldMatrix.invertToRef(j.invertedMatrix),u.e.TransformCoordinatesToRef(j.facetDepthSortFrom,j.invertedMatrix,j.facetDepthSortOrigin),j.facetParameters.distanceTo=j.facetDepthSortOrigin),j.facetParameters.depthSortedFacets=j.depthSortedFacets,C.a.ComputeNormals(ne,te,de,j.facetParameters),j.facetDepthSort&&j.facetDepthSortEnabled){j.depthSortedFacets.sort(j.facetDepthSortFunction);var Q=j.depthSortedIndices.length/3|0;for($=0;$<Q;$++){var oe=j.depthSortedFacets[$].ind;j.depthSortedIndices[3*$]=te[oe],j.depthSortedIndices[3*$+1]=te[oe+1],j.depthSortedIndices[3*$+2]=te[oe+2]}this.updateIndices(j.depthSortedIndices,void 0,!0)}return this},X.prototype.getFacetLocalNormals=function(){var j=this._internalAbstractMeshDataInfo._facetData;return j.facetNormals||this.updateFacetData(),j.facetNormals},X.prototype.getFacetLocalPositions=function(){var j=this._internalAbstractMeshDataInfo._facetData;return j.facetPositions||this.updateFacetData(),j.facetPositions},X.prototype.getFacetLocalPartitioning=function(){var j=this._internalAbstractMeshDataInfo._facetData;return j.facetPartitioning||this.updateFacetData(),j.facetPartitioning},X.prototype.getFacetPosition=function(j){var ne=u.e.Zero();return this.getFacetPositionToRef(j,ne),ne},X.prototype.getFacetPositionToRef=function(j,ne){var te=this.getFacetLocalPositions()[j],de=this.getWorldMatrix();return u.e.TransformCoordinatesToRef(te,de,ne),this},X.prototype.getFacetNormal=function(j){var ne=u.e.Zero();return this.getFacetNormalToRef(j,ne),ne},X.prototype.getFacetNormalToRef=function(j,ne){var te=this.getFacetLocalNormals()[j];return u.e.TransformNormalToRef(te,this.getWorldMatrix(),ne),this},X.prototype.getFacetsAtLocalCoordinates=function(j,ne,te){var de=this.getBoundingInfo(),pe=this._internalAbstractMeshDataInfo._facetData,ae=Math.floor((j-de.minimum.x*pe.partitioningBBoxRatio)*pe.subDiv.X*pe.partitioningBBoxRatio/pe.bbSize.x),ee=Math.floor((ne-de.minimum.y*pe.partitioningBBoxRatio)*pe.subDiv.Y*pe.partitioningBBoxRatio/pe.bbSize.y),K=Math.floor((te-de.minimum.z*pe.partitioningBBoxRatio)*pe.subDiv.Z*pe.partitioningBBoxRatio/pe.bbSize.z);return ae<0||ae>pe.subDiv.max||ee<0||ee>pe.subDiv.max||K<0||K>pe.subDiv.max?null:pe.facetPartitioning[ae+pe.subDiv.max*ee+pe.subDiv.max*pe.subDiv.max*K]},X.prototype.getClosestFacetAtCoordinates=function(j,ne,te,de,pe,ae){pe===void 0&&(pe=!1),ae===void 0&&(ae=!0);var ee=this.getWorldMatrix(),K=u.c.Matrix[5];ee.invertToRef(K);var $=u.c.Vector3[8];u.e.TransformCoordinatesFromFloatsToRef(j,ne,te,K,$);var L=this.getClosestFacetAtLocalCoordinates($.x,$.y,$.z,de,pe,ae);return de&&u.e.TransformCoordinatesFromFloatsToRef(de.x,de.y,de.z,ee,de),L},X.prototype.getClosestFacetAtLocalCoordinates=function(j,ne,te,de,pe,ae){pe===void 0&&(pe=!1),ae===void 0&&(ae=!0);var ee=null,K=0,$=0,L=0,G=0,Q=0,oe=0,re=0,Y=0,k=this.getFacetLocalPositions(),H=this.getFacetLocalNormals(),Z=this.getFacetsAtLocalCoordinates(j,ne,te);if(!Z)return null;for(var W,q,he,ge=Number.MAX_VALUE,me=ge,_e=0;_e<Z.length;_e++)q=H[W=Z[_e]],G=(j-(he=k[W]).x)*q.x+(ne-he.y)*q.y+(te-he.z)*q.z,(!pe||pe&&ae&&G>=0||pe&&!ae&&G<=0)&&(G=q.x*he.x+q.y*he.y+q.z*he.z,Q=-(q.x*j+q.y*ne+q.z*te-G)/(q.x*q.x+q.y*q.y+q.z*q.z),(me=(K=(oe=j+q.x*Q)-j)*K+($=(re=ne+q.y*Q)-ne)*$+(L=(Y=te+q.z*Q)-te)*L)<ge&&(ge=me,ee=W,de&&(de.x=oe,de.y=re,de.z=Y)));return ee},X.prototype.getFacetDataParameters=function(){return this._internalAbstractMeshDataInfo._facetData.facetParameters},X.prototype.disableFacetData=function(){var j=this._internalAbstractMeshDataInfo._facetData;return j.facetDataEnabled&&(j.facetDataEnabled=!1,j.facetPositions=new Array,j.facetNormals=new Array,j.facetPartitioning=new Array,j.facetParameters=null,j.depthSortedIndices=new Uint32Array(0)),this},X.prototype.updateIndices=function(j,ne,te){return this},X.prototype.createNormals=function(j){var ne,te=this.getVerticesData(R.b.PositionKind),de=this.getIndices();return ne=this.isVerticesDataPresent(R.b.NormalKind)?this.getVerticesData(R.b.NormalKind):[],C.a.ComputeNormals(te,de,ne,{useRightHandedSystem:this.getScene().useRightHandedSystem}),this.setVerticesData(R.b.NormalKind,ne,j),this},X.prototype.alignWithNormal=function(j,ne){ne||(ne=E.a.Y);var te=u.c.Vector3[0],de=u.c.Vector3[1];return u.e.CrossToRef(ne,j,de),u.e.CrossToRef(j,de,te),this.rotationQuaternion?u.b.RotationQuaternionFromAxisToRef(te,j,de,this.rotationQuaternion):u.e.RotationFromAxisToRef(te,j,de,this.rotation),this},X.prototype._checkOcclusionQuery=function(){return!1},X.prototype.disableEdgesRendering=function(){throw g.a.WarnImport("EdgesRenderer")},X.prototype.enableEdgesRendering=function(j,ne,te){throw g.a.WarnImport("EdgesRenderer")},X.prototype.getConnectedParticleSystems=function(){var j=this;return this._scene.particleSystems.filter(function(ne){return ne.emitter===j})},X.OCCLUSION_TYPE_NONE=0,X.OCCLUSION_TYPE_OPTIMISTIC=1,X.OCCLUSION_TYPE_STRICT=2,X.OCCLUSION_ALGORITHM_TYPE_ACCURATE=0,X.OCCLUSION_ALGORITHM_TYPE_CONSERVATIVE=1,X.CULLINGSTRATEGY_STANDARD=A.a.MESHES_CULLINGSTRATEGY_STANDARD,X.CULLINGSTRATEGY_BOUNDINGSPHERE_ONLY=A.a.MESHES_CULLINGSTRATEGY_BOUNDINGSPHERE_ONLY,X.CULLINGSTRATEGY_OPTIMISTIC_INCLUSION=A.a.MESHES_CULLINGSTRATEGY_OPTIMISTIC_INCLUSION,X.CULLINGSTRATEGY_OPTIMISTIC_INCLUSION_THEN_BSPHERE_ONLY=A.a.MESHES_CULLINGSTRATEGY_OPTIMISTIC_INCLUSION_THEN_BSPHERE_ONLY,X}(m.a);D.a.RegisteredTypes["BABYLON.AbstractMesh"]=I},function(Me,y,f){f.d(y,"a",function(){return m});var U=f(8),_=f(44),x=f(0),u=f(31),M=f(7),R=f(50),C=f(23);M.a._PhysicsImpostorParser=function(c,T,A){return new m(T,A.physicsImpostor,{mass:A.physicsMass,friction:A.physicsFriction,restitution:A.physicsRestitution},c)};var m=function(){function c(T,A,S,g){var l=this;S===void 0&&(S={mass:0}),this.object=T,this.type=A,this._options=S,this._scene=g,this._pluginData={},this._bodyUpdateRequired=!1,this._onBeforePhysicsStepCallbacks=new Array,this._onAfterPhysicsStepCallbacks=new Array,this._onPhysicsCollideCallbacks=[],this._deltaPosition=x.e.Zero(),this._isDisposed=!1,this.soft=!1,this.segments=0,this._tmpQuat=new x.b,this._tmpQuat2=new x.b,this.beforeStep=function(){l._physicsEngine&&(l.object.translate(l._deltaPosition,-1),l._deltaRotationConjugated&&l.object.rotationQuaternion&&l.object.rotationQuaternion.multiplyToRef(l._deltaRotationConjugated,l.object.rotationQuaternion),l.object.computeWorldMatrix(!1),l.object.parent&&l.object.rotationQuaternion?(l.getParentsRotation(),l._tmpQuat.multiplyToRef(l.object.rotationQuaternion,l._tmpQuat)):l._tmpQuat.copyFrom(l.object.rotationQuaternion||new x.b),l._options.disableBidirectionalTransformation||l.object.rotationQuaternion&&l._physicsEngine.getPhysicsPlugin().setPhysicsBodyTransformation(l,l.object.getAbsolutePosition(),l._tmpQuat),l._onBeforePhysicsStepCallbacks.forEach(function(h){h(l)}))},this.afterStep=function(){l._physicsEngine&&(l._onAfterPhysicsStepCallbacks.forEach(function(h){h(l)}),l._physicsEngine.getPhysicsPlugin().setTransformationFromPhysicsBody(l),l.object.parent&&l.object.rotationQuaternion&&(l.getParentsRotation(),l._tmpQuat.conjugateInPlace(),l._tmpQuat.multiplyToRef(l.object.rotationQuaternion,l.object.rotationQuaternion)),l.object.setAbsolutePosition(l.object.position),l._deltaRotation&&l.object.rotationQuaternion&&l.object.rotationQuaternion.multiplyToRef(l._deltaRotation,l.object.rotationQuaternion),l.object.translate(l._deltaPosition,1))},this.onCollideEvent=null,this.onCollide=function(h){if((l._onPhysicsCollideCallbacks.length||l.onCollideEvent)&&l._physicsEngine){var v=l._physicsEngine.getImpostorWithPhysicsBody(h.body);v&&(l.onCollideEvent&&l.onCollideEvent(l,v),l._onPhysicsCollideCallbacks.filter(function(E){return E.otherImpostors.indexOf(v)!==-1}).forEach(function(E){E.callback(l,v,h.point)}))}},this.object?(this.object.parent&&S.mass!==0&&U.a.Warn("A physics impostor has been created for an object which has a parent. Babylon physics currently works in local space so unexpected issues may occur."),!this._scene&&T.getScene&&(this._scene=T.getScene()),this._scene&&(this.type>100&&(this.soft=!0),this._physicsEngine=this._scene.getPhysicsEngine(),this._physicsEngine?(this.object.rotationQuaternion||(this.object.rotation?this.object.rotationQuaternion=x.b.RotationYawPitchRoll(this.object.rotation.y,this.object.rotation.x,this.object.rotation.z):this.object.rotationQuaternion=new x.b),this._options.mass=S.mass===void 0?0:S.mass,this._options.friction=S.friction===void 0?.2:S.friction,this._options.restitution=S.restitution===void 0?.2:S.restitution,this.soft&&(this._options.mass=this._options.mass>0?this._options.mass:1,this._options.pressure=S.pressure===void 0?200:S.pressure,this._options.stiffness=S.stiffness===void 0?1:S.stiffness,this._options.velocityIterations=S.velocityIterations===void 0?20:S.velocityIterations,this._options.positionIterations=S.positionIterations===void 0?20:S.positionIterations,this._options.fixedPoints=S.fixedPoints===void 0?0:S.fixedPoints,this._options.margin=S.margin===void 0?0:S.margin,this._options.damping=S.damping===void 0?0:S.damping,this._options.path=S.path===void 0?null:S.path,this._options.shape=S.shape===void 0?null:S.shape),this._joints=[],!this.object.parent||this._options.ignoreParent?this._init():this.object.parent.physicsImpostor&&U.a.Warn("You must affect impostors to children before affecting impostor to parent.")):U.a.Error("Physics not enabled. Please use scene.enablePhysics(...) before creating impostors."))):U.a.Error("No object was provided. A physics object is obligatory")}return Object.defineProperty(c.prototype,"isDisposed",{get:function(){return this._isDisposed},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"mass",{get:function(){return this._physicsEngine?this._physicsEngine.getPhysicsPlugin().getBodyMass(this):0},set:function(T){this.setMass(T)},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"friction",{get:function(){return this._physicsEngine?this._physicsEngine.getPhysicsPlugin().getBodyFriction(this):0},set:function(T){this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().setBodyFriction(this,T)},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"restitution",{get:function(){return this._physicsEngine?this._physicsEngine.getPhysicsPlugin().getBodyRestitution(this):0},set:function(T){this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().setBodyRestitution(this,T)},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"pressure",{get:function(){if(!this._physicsEngine)return 0;var T=this._physicsEngine.getPhysicsPlugin();return T.setBodyPressure?T.getBodyPressure(this):0},set:function(T){if(this._physicsEngine){var A=this._physicsEngine.getPhysicsPlugin();A.setBodyPressure&&A.setBodyPressure(this,T)}},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"stiffness",{get:function(){if(!this._physicsEngine)return 0;var T=this._physicsEngine.getPhysicsPlugin();return T.getBodyStiffness?T.getBodyStiffness(this):0},set:function(T){if(this._physicsEngine){var A=this._physicsEngine.getPhysicsPlugin();A.setBodyStiffness&&A.setBodyStiffness(this,T)}},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"velocityIterations",{get:function(){if(!this._physicsEngine)return 0;var T=this._physicsEngine.getPhysicsPlugin();return T.getBodyVelocityIterations?T.getBodyVelocityIterations(this):0},set:function(T){if(this._physicsEngine){var A=this._physicsEngine.getPhysicsPlugin();A.setBodyVelocityIterations&&A.setBodyVelocityIterations(this,T)}},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"positionIterations",{get:function(){if(!this._physicsEngine)return 0;var T=this._physicsEngine.getPhysicsPlugin();return T.getBodyPositionIterations?T.getBodyPositionIterations(this):0},set:function(T){if(this._physicsEngine){var A=this._physicsEngine.getPhysicsPlugin();A.setBodyPositionIterations&&A.setBodyPositionIterations(this,T)}},enumerable:!1,configurable:!0}),c.prototype._init=function(){this._physicsEngine&&(this._physicsEngine.removeImpostor(this),this.physicsBody=null,this._parent=this._parent||this._getPhysicsParent(),this._isDisposed||this.parent&&!this._options.ignoreParent||this._physicsEngine.addImpostor(this))},c.prototype._getPhysicsParent=function(){return this.object.parent instanceof u.a?this.object.parent.physicsImpostor:null},c.prototype.isBodyInitRequired=function(){return this._bodyUpdateRequired||!this._physicsBody&&!this._parent},c.prototype.setScalingUpdated=function(){this.forceUpdate()},c.prototype.forceUpdate=function(){this._init(),this.parent&&!this._options.ignoreParent&&this.parent.forceUpdate()},Object.defineProperty(c.prototype,"physicsBody",{get:function(){return this._parent&&!this._options.ignoreParent?this._parent.physicsBody:this._physicsBody},set:function(T){this._physicsBody&&this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().removePhysicsBody(this),this._physicsBody=T,this.resetUpdateFlags()},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"parent",{get:function(){return!this._options.ignoreParent&&this._parent?this._parent:null},set:function(T){this._parent=T},enumerable:!1,configurable:!0}),c.prototype.resetUpdateFlags=function(){this._bodyUpdateRequired=!1},c.prototype.getObjectExtendSize=function(){if(this.object.getBoundingInfo){var T=this.object.rotationQuaternion,A=this.object.scaling.clone();this.object.rotationQuaternion=c.IDENTITY_QUATERNION;var S=this.object.computeWorldMatrix&&this.object.computeWorldMatrix(!0);S&&S.decompose(A,void 0,void 0);var g=this.object.getBoundingInfo().boundingBox.extendSize.scale(2).multiplyInPlace(A);return this.object.rotationQuaternion=T,this.object.computeWorldMatrix&&this.object.computeWorldMatrix(!0),g}return c.DEFAULT_OBJECT_SIZE},c.prototype.getObjectCenter=function(){return this.object.getBoundingInfo?this.object.getBoundingInfo().boundingBox.centerWorld:this.object.position},c.prototype.getParam=function(T){return this._options[T]},c.prototype.setParam=function(T,A){this._options[T]=A,this._bodyUpdateRequired=!0},c.prototype.setMass=function(T){this.getParam("mass")!==T&&this.setParam("mass",T),this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().setBodyMass(this,T)},c.prototype.getLinearVelocity=function(){return this._physicsEngine?this._physicsEngine.getPhysicsPlugin().getLinearVelocity(this):x.e.Zero()},c.prototype.setLinearVelocity=function(T){this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().setLinearVelocity(this,T)},c.prototype.getAngularVelocity=function(){return this._physicsEngine?this._physicsEngine.getPhysicsPlugin().getAngularVelocity(this):x.e.Zero()},c.prototype.setAngularVelocity=function(T){this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().setAngularVelocity(this,T)},c.prototype.executeNativeFunction=function(T){this._physicsEngine&&T(this._physicsEngine.getPhysicsPlugin().world,this.physicsBody)},c.prototype.registerBeforePhysicsStep=function(T){this._onBeforePhysicsStepCallbacks.push(T)},c.prototype.unregisterBeforePhysicsStep=function(T){var A=this._onBeforePhysicsStepCallbacks.indexOf(T);A>-1?this._onBeforePhysicsStepCallbacks.splice(A,1):U.a.Warn("Function to remove was not found")},c.prototype.registerAfterPhysicsStep=function(T){this._onAfterPhysicsStepCallbacks.push(T)},c.prototype.unregisterAfterPhysicsStep=function(T){var A=this._onAfterPhysicsStepCallbacks.indexOf(T);A>-1?this._onAfterPhysicsStepCallbacks.splice(A,1):U.a.Warn("Function to remove was not found")},c.prototype.registerOnPhysicsCollide=function(T,A){var S=T instanceof Array?T:[T];this._onPhysicsCollideCallbacks.push({callback:A,otherImpostors:S})},c.prototype.unregisterOnPhysicsCollide=function(T,A){var S=T instanceof Array?T:[T],g=-1;this._onPhysicsCollideCallbacks.some(function(l,h){if(l.callback===A&&l.otherImpostors.length===S.length){var v=l.otherImpostors.every(function(E){return S.indexOf(E)>-1});return v&&(g=h),v}return!1})?this._onPhysicsCollideCallbacks.splice(g,1):U.a.Warn("Function to remove was not found")},c.prototype.getParentsRotation=function(){var T=this.object.parent;for(this._tmpQuat.copyFromFloats(0,0,0,1);T;)T.rotationQuaternion?this._tmpQuat2.copyFrom(T.rotationQuaternion):x.b.RotationYawPitchRollToRef(T.rotation.y,T.rotation.x,T.rotation.z,this._tmpQuat2),this._tmpQuat.multiplyToRef(this._tmpQuat2,this._tmpQuat),T=T.parent;return this._tmpQuat},c.prototype.applyForce=function(T,A){return this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().applyForce(this,T,A),this},c.prototype.applyImpulse=function(T,A){return this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().applyImpulse(this,T,A),this},c.prototype.createJoint=function(T,A,S){var g=new R.e(A,S);return this.addJoint(T,g),this},c.prototype.addJoint=function(T,A){return this._joints.push({otherImpostor:T,joint:A}),this._physicsEngine&&this._physicsEngine.addJoint(this,T,A),this},c.prototype.addAnchor=function(T,A,S,g,l){if(!this._physicsEngine)return this;var h=this._physicsEngine.getPhysicsPlugin();return h.appendAnchor?(this._physicsEngine&&h.appendAnchor(this,T,A,S,g,l),this):this},c.prototype.addHook=function(T,A,S,g){if(!this._physicsEngine)return this;var l=this._physicsEngine.getPhysicsPlugin();return l.appendAnchor?(this._physicsEngine&&l.appendHook(this,T,A,S,g),this):this},c.prototype.sleep=function(){return this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().sleepBody(this),this},c.prototype.wakeUp=function(){return this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().wakeUpBody(this),this},c.prototype.clone=function(T){return T?new c(T,this.type,this._options,this._scene):null},c.prototype.dispose=function(){var T=this;this._physicsEngine&&(this._joints.forEach(function(A){T._physicsEngine&&T._physicsEngine.removeJoint(T,A.otherImpostor,A.joint)}),this._physicsEngine.removeImpostor(this),this.parent&&this.parent.forceUpdate(),this._isDisposed=!0)},c.prototype.setDeltaPosition=function(T){this._deltaPosition.copyFrom(T)},c.prototype.setDeltaRotation=function(T){this._deltaRotation||(this._deltaRotation=new x.b),this._deltaRotation.copyFrom(T),this._deltaRotationConjugated=this._deltaRotation.conjugate()},c.prototype.getBoxSizeToRef=function(T){return this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().getBoxSizeToRef(this,T),this},c.prototype.getRadius=function(){return this._physicsEngine?this._physicsEngine.getPhysicsPlugin().getRadius(this):0},c.prototype.syncBoneWithImpostor=function(T,A,S,g,l){var h=c._tmpVecs[0],v=this.object;if(v.rotationQuaternion)if(l){var E=c._tmpQuat;v.rotationQuaternion.multiplyToRef(l,E),T.setRotationQuaternion(E,C.c.WORLD,A)}else T.setRotationQuaternion(v.rotationQuaternion,C.c.WORLD,A);h.x=0,h.y=0,h.z=0,S&&(h.x=S.x,h.y=S.y,h.z=S.z,T.getDirectionToRef(h,A,h),g==null&&(g=S.length()),h.x*=g,h.y*=g,h.z*=g),T.getParent()?(h.addInPlace(v.getAbsolutePosition()),T.setAbsolutePosition(h,A)):(A.setAbsolutePosition(v.getAbsolutePosition()),A.position.x-=h.x,A.position.y-=h.y,A.position.z-=h.z)},c.prototype.syncImpostorWithBone=function(T,A,S,g,l,h){var v=this.object;if(v.rotationQuaternion)if(l){var E=c._tmpQuat;T.getRotationQuaternionToRef(C.c.WORLD,A,E),E.multiplyToRef(l,v.rotationQuaternion)}else T.getRotationQuaternionToRef(C.c.WORLD,A,v.rotationQuaternion);var D=c._tmpVecs[0],w=c._tmpVecs[1];h||((h=c._tmpVecs[2]).x=0,h.y=1,h.z=0),T.getDirectionToRef(h,A,w),T.getAbsolutePositionToRef(A,D),g==null&&S&&(g=S.length()),g!=null&&(D.x+=w.x*g,D.y+=w.y*g,D.z+=w.z*g),v.setAbsolutePosition(D)},c.DEFAULT_OBJECT_SIZE=new x.e(1,1,1),c.IDENTITY_QUATERNION=x.b.Identity(),c._tmpVecs=_.a.BuildArray(3,x.e.Zero),c._tmpQuat=x.b.Identity(),c.NoImpostor=0,c.SphereImpostor=1,c.BoxImpostor=2,c.PlaneImpostor=3,c.MeshImpostor=4,c.CapsuleImpostor=6,c.CylinderImpostor=7,c.ParticleImpostor=8,c.HeightmapImpostor=9,c.ConvexHullImpostor=10,c.CustomImpostor=100,c.RopeImpostor=101,c.ClothImpostor=102,c.SoftbodyImpostor=103,c}()},function(Me,y,f){f.d(y,"a",function(){return _}),f.d(y,"b",function(){return x});var U=f(1),_=function(){function u(M){this.length=0,this.data=new Array(M),this._id=u._GlobalId++}return u.prototype.push=function(M){this.data[this.length++]=M,this.length>this.data.length&&(this.data.length*=2)},u.prototype.forEach=function(M){for(var R=0;R<this.length;R++)M(this.data[R])},u.prototype.sort=function(M){this.data.sort(M)},u.prototype.reset=function(){this.length=0},u.prototype.dispose=function(){this.reset(),this.data&&(this.data.length=0,this.data=[])},u.prototype.concat=function(M){if(M.length!==0){this.length+M.length>this.data.length&&(this.data.length=2*(this.length+M.length));for(var R=0;R<M.length;R++)this.data[this.length++]=(M.data||M)[R]}},u.prototype.indexOf=function(M){var R=this.data.indexOf(M);return R>=this.length?-1:R},u.prototype.contains=function(M){return this.indexOf(M)!==-1},u._GlobalId=0,u}(),x=function(u){function M(){var R=u!==null&&u.apply(this,arguments)||this;return R._duplicateId=0,R}return Object(U.d)(M,u),M.prototype.push=function(R){u.prototype.push.call(this,R),R.__smartArrayFlags||(R.__smartArrayFlags={}),R.__smartArrayFlags[this._id]=this._duplicateId},M.prototype.pushNoDuplicate=function(R){return(!R.__smartArrayFlags||R.__smartArrayFlags[this._id]!==this._duplicateId)&&(this.push(R),!0)},M.prototype.reset=function(){u.prototype.reset.call(this),this._duplicateId++},M.prototype.concatWithNoDuplicate=function(R){if(R.length!==0){this.length+R.length>this.data.length&&(this.data.length=2*(this.length+R.length));for(var C=0;C<R.length;C++){var m=(R.data||R)[C];this.pushNoDuplicate(m)}}},M}(_)},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.EndsWith=function(x,u){return x.indexOf(u,x.length-u.length)!==-1},_.StartsWith=function(x,u){return!!x&&x.indexOf(u)===0},_.Decode=function(x){if(typeof TextDecoder<"u")return new TextDecoder().decode(x);for(var u="",M=0;M<x.byteLength;M++)u+=String.fromCharCode(x[M]);return u},_.EncodeArrayBufferToBase64=function(x){for(var u,M,R,C,m,c,T,A="ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/=",S="",g=0,l=ArrayBuffer.isView(x)?new Uint8Array(x.buffer,x.byteOffset,x.byteLength):new Uint8Array(x);g<l.length;)C=(u=l[g++])>>2,m=(3&u)<<4|(M=g<l.length?l[g++]:Number.NaN)>>4,c=(15&M)<<2|(R=g<l.length?l[g++]:Number.NaN)>>6,T=63&R,isNaN(M)?c=T=64:isNaN(R)&&(T=64),S+=A.charAt(C)+A.charAt(m)+A.charAt(c)+A.charAt(T);return S},_.PadNumber=function(x,u){for(var M=String(x);M.length<u;)M="0"+M;return M},_}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){this.rootNodes=new Array,this.cameras=new Array,this.lights=new Array,this.meshes=new Array,this.skeletons=new Array,this.particleSystems=new Array,this.animations=[],this.animationGroups=new Array,this.multiMaterials=new Array,this.materials=new Array,this.morphTargetManagers=new Array,this.geometries=new Array,this.transformNodes=new Array,this.actionManagers=new 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x=x.concat(u.bones)}),x},_._BabylonFileParsers={},_._IndividualBabylonFileParsers={},_}()},function(Me,y,f){f.d(y,"a",function(){return m});var U=f(20),_=f(6),x=f(18),u=f(22),M=f(86),R=f(0),C=f(9),m=function(){function c(T,A){var S=this;A===void 0&&(A=!0),this.originalScene=T,this._pointerCaptures={},this._lastPointerEvents={},this._sharedGizmoLight=null,this._renderCamera=null,this.pickUtilitySceneFirst=!0,this.shouldRender=!0,this.onlyCheckPointerDownEvents=!0,this.processAllEvents=!1,this.onPointerOutObservable=new _.c,this.utilityLayerScene=new 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x.b(g.type,g.event,v),g.type),void(g.type===x.a.POINTERUP&&S._pointerCaptures[h.pointerId]&&(S._pointerCaptures[h.pointerId]=!1));if(S.utilityLayerScene.autoClearDepthAndStencil||S.pickUtilitySceneFirst)v&&v.hit&&(g.skipOnPointerObservable||S.utilityLayerScene.onPointerObservable.notifyObservers(new x.b(g.type,g.event,v),g.type),g.skipOnPointerObservable=!0);else{var E=g.ray?T.pickWithRay(g.ray):T.pick(T.pointerX,T.pointerY),D=g.event;E&&v&&(v.distance===0&&E.pickedMesh?S.mainSceneTrackerPredicate&&S.mainSceneTrackerPredicate(E.pickedMesh)?(S._notifyObservers(g,E,D),g.skipOnPointerObservable=!0):g.type===x.a.POINTERDOWN?S._pointerCaptures[D.pointerId]=!0:S._lastPointerEvents[D.pointerId]&&(S.onPointerOutObservable.notifyObservers(D.pointerId),delete 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this._sharedGizmoLight||(this._sharedGizmoLight=new M.a("shared gizmo light",new R.e(0,1,0),this.utilityLayerScene),this._sharedGizmoLight.intensity=2,this._sharedGizmoLight.groundColor=C.a.Gray()),this._sharedGizmoLight},Object.defineProperty(c,"DefaultUtilityLayer",{get:function(){return c._DefaultUtilityLayer==null&&(c._DefaultUtilityLayer=new c(u.a.LastCreatedScene),c._DefaultUtilityLayer.originalScene.onDisposeObservable.addOnce(function(){c._DefaultUtilityLayer=null})),c._DefaultUtilityLayer},enumerable:!1,configurable:!0}),Object.defineProperty(c,"DefaultKeepDepthUtilityLayer",{get:function(){return c._DefaultKeepDepthUtilityLayer==null&&(c._DefaultKeepDepthUtilityLayer=new 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T=this.utilityLayerScene.activeCamera.getScene(),A=this.utilityLayerScene.activeCamera;A._scene=this.utilityLayerScene,A.leftCamera&&(A.leftCamera._scene=this.utilityLayerScene),A.rightCamera&&(A.rightCamera._scene=this.utilityLayerScene),this.utilityLayerScene.render(!1),A._scene=T,A.leftCamera&&(A.leftCamera._scene=T),A.rightCamera&&(A.rightCamera._scene=T)}},c.prototype.dispose=function(){this.onPointerOutObservable.clear(),this._afterRenderObserver&&this.originalScene.onAfterCameraRenderObservable.remove(this._afterRenderObserver),this._sceneDisposeObserver&&this.originalScene.onDisposeObservable.remove(this._sceneDisposeObserver),this._originalPointerObserver&&this.originalScene.onPrePointerObservable.remove(this._originalPointerObserver),this.utilityLayerScene.dispose()},c.prototype._updateCamera=function(){this.utilityLayerScene.cameraToUseForPointers=this.getRenderCamera(),this.utilityLayerScene.activeCamera=this.getRenderCamera()},c._DefaultUtilityLayer=null,c._DefaultKeepDepthUtilityLayer=null,c}()},function(Me,y,f){f.d(y,"a",function(){return 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U=f(44),_=f(0),x=f(54),u=f(114),M=f(20),R=f(24),C=function(){function m(c,T,A){A===void 0&&(A=Number.MAX_VALUE),this.origin=c,this.direction=T,this.length=A}return m.prototype.intersectsBoxMinMax=function(c,T,A){A===void 0&&(A=0);var S,g,l,h,v=m._TmpVector3[0].copyFromFloats(c.x-A,c.y-A,c.z-A),E=m._TmpVector3[1].copyFromFloats(T.x+A,T.y+A,T.z+A),D=0,w=Number.MAX_VALUE;if(Math.abs(this.direction.x)<1e-7){if(this.origin.x<v.x||this.origin.x>E.x)return!1}else if(S=1/this.direction.x,g=(v.x-this.origin.x)*S,(l=(E.x-this.origin.x)*S)===-1/0&&(l=1/0),g>l&&(h=g,g=l,l=h),(D=Math.max(g,D))>(w=Math.min(l,w)))return!1;if(Math.abs(this.direction.y)<1e-7){if(this.origin.y<v.y||this.origin.y>E.y)return!1}else if(S=1/this.direction.y,g=(v.y-this.origin.y)*S,(l=(E.y-this.origin.y)*S)===-1/0&&(l=1/0),g>l&&(h=g,g=l,l=h),(D=Math.max(g,D))>(w=Math.min(l,w)))return!1;if(Math.abs(this.direction.z)<1e-7){if(this.origin.z<v.z||this.origin.z>E.z)return!1}else if(S=1/this.direction.z,g=(v.z-this.origin.z)*S,(l=(E.z-this.origin.z)*S)===-1/0&&(l=1/0),g>l&&(h=g,g=l,l=h),(D=Math.max(g,D))>(w=Math.min(l,w)))return!1;return!0},m.prototype.intersectsBox=function(c,T){return T===void 0&&(T=0),this.intersectsBoxMinMax(c.minimum,c.maximum,T)},m.prototype.intersectsSphere=function(c,T){T===void 0&&(T=0);var A=c.center.x-this.origin.x,S=c.center.y-this.origin.y,g=c.center.z-this.origin.z,l=A*A+S*S+g*g,h=c.radius+T,v=h*h;if(l<=v)return!0;var E=A*this.direction.x+S*this.direction.y+g*this.direction.z;return!(E<0)&&l-E*E<=v},m.prototype.intersectsTriangle=function(c,T,A){var S=m._TmpVector3[0],g=m._TmpVector3[1],l=m._TmpVector3[2],h=m._TmpVector3[3],v=m._TmpVector3[4];T.subtractToRef(c,S),A.subtractToRef(c,g),_.e.CrossToRef(this.direction,g,l);var E=_.e.Dot(S,l);if(E===0)return null;var D=1/E;this.origin.subtractToRef(c,h);var w=_.e.Dot(h,l)*D;if(w<0||w>1)return null;_.e.CrossToRef(h,S,v);var N=_.e.Dot(this.direction,v)*D;if(N<0||w+N>1)return null;var I=_.e.Dot(g,v)*D;return I>this.length?null:new u.a(1-w-N,w,I)},m.prototype.intersectsPlane=function(c){var T,A=_.e.Dot(c.normal,this.direction);if(Math.abs(A)<999999997475243e-21)return null;var S=_.e.Dot(c.normal,this.origin);return(T=(-c.d-S)/A)<0?T<-999999997475243e-21?null:0:T},m.prototype.intersectsAxis=function(c,T){switch(T===void 0&&(T=0),c){case"y":return(A=(this.origin.y-T)/this.direction.y)>0?null:new _.e(this.origin.x+this.direction.x*-A,T,this.origin.z+this.direction.z*-A);case"x":return(A=(this.origin.x-T)/this.direction.x)>0?null:new _.e(T,this.origin.y+this.direction.y*-A,this.origin.z+this.direction.z*-A);case"z":var A;return(A=(this.origin.z-T)/this.direction.z)>0?null:new _.e(this.origin.x+this.direction.x*-A,this.origin.y+this.direction.y*-A,T);default:return null}},m.prototype.intersectsMesh=function(c,T){var A=_.c.Matrix[0];return c.getWorldMatrix().invertToRef(A),this._tmpRay?m.TransformToRef(this,A,this._tmpRay):this._tmpRay=m.Transform(this,A),c.intersects(this._tmpRay,T)},m.prototype.intersectsMeshes=function(c,T,A){A?A.length=0:A=[];for(var S=0;S<c.length;S++){var g=this.intersectsMesh(c[S],T);g.hit&&A.push(g)}return A.sort(this._comparePickingInfo),A},m.prototype._comparePickingInfo=function(c,T){return c.distance<T.distance?-1:c.distance>T.distance?1:0},m.prototype.intersectionSegment=function(c,T,A){var S=this.origin,g=_.c.Vector3[0],l=_.c.Vector3[1],h=_.c.Vector3[2],v=_.c.Vector3[3];T.subtractToRef(c,g),this.direction.scaleToRef(m.rayl,h),S.addToRef(h,l),c.subtractToRef(S,v);var E,D,w,N,I=_.e.Dot(g,g),V=_.e.Dot(g,h),X=_.e.Dot(h,h),j=_.e.Dot(g,v),ne=_.e.Dot(h,v),te=I*X-V*V,de=te,pe=te;te<m.smallnum?(D=0,de=1,N=ne,pe=X):(N=I*ne-V*j,(D=V*ne-X*j)<0?(D=0,N=ne,pe=X):D>de&&(D=de,N=ne+V,pe=X)),N<0?(N=0,-j<0?D=0:-j>I?D=de:(D=-j,de=I)):N>pe&&(N=pe,-j+V<0?D=0:-j+V>I?D=de:(D=-j+V,de=I)),E=Math.abs(D)<m.smallnum?0:D/de,w=Math.abs(N)<m.smallnum?0:N/pe;var ae=_.c.Vector3[4];h.scaleToRef(w,ae);var ee=_.c.Vector3[5];g.scaleToRef(E,ee),ee.addInPlace(v);var K=_.c.Vector3[6];return ee.subtractToRef(ae,K),w>0&&w<=this.length&&K.lengthSquared()<A*A?ee.length():-1},m.prototype.update=function(c,T,A,S,g,l,h){return this.unprojectRayToRef(c,T,A,S,g,l,h),this},m.Zero=function(){return new m(_.e.Zero(),_.e.Zero())},m.CreateNew=function(c,T,A,S,g,l,h){return m.Zero().update(c,T,A,S,g,l,h)},m.CreateNewFromTo=function(c,T,A){A===void 0&&(A=_.a.IdentityReadOnly);var S=T.subtract(c),g=Math.sqrt(S.x*S.x+S.y*S.y+S.z*S.z);return S.normalize(),m.Transform(new m(c,S,g),A)},m.Transform=function(c,T){var A=new m(new _.e(0,0,0),new _.e(0,0,0));return m.TransformToRef(c,T,A),A},m.TransformToRef=function(c,T,A){_.e.TransformCoordinatesToRef(c.origin,T,A.origin),_.e.TransformNormalToRef(c.direction,T,A.direction),A.length=c.length;var S=A.direction,g=S.length();if(g!==0&&g!==1){var l=1/g;S.x*=l,S.y*=l,S.z*=l,A.length*=g}},m.prototype.unprojectRayToRef=function(c,T,A,S,g,l,h){var v=_.c.Matrix[0];g.multiplyToRef(l,v),v.multiplyToRef(h,v),v.invert();var E=_.c.Vector3[0];E.x=c/A*2-1,E.y=-(T/S*2-1),E.z=-1;var D=_.c.Vector3[1].copyFromFloats(E.x,E.y,1),w=_.c.Vector3[2],N=_.c.Vector3[3];_.e._UnprojectFromInvertedMatrixToRef(E,v,w),_.e._UnprojectFromInvertedMatrixToRef(D,v,N),this.origin.copyFrom(w),N.subtractToRef(w,this.direction),this.direction.normalize()},m._TmpVector3=U.a.BuildArray(6,_.e.Zero),m.smallnum=1e-8,m.rayl=1e9,m}();M.a.prototype.createPickingRay=function(m,c,T,A,S){S===void 0&&(S=!1);var g=C.Zero();return this.createPickingRayToRef(m,c,T,g,A,S),g},M.a.prototype.createPickingRayToRef=function(m,c,T,A,S,g){g===void 0&&(g=!1);var l=this.getEngine();if(!S){if(!this.activeCamera)return this;S=this.activeCamera}var h=S.viewport.toGlobal(l.getRenderWidth(),l.getRenderHeight());return m=m/l.getHardwareScalingLevel()-h.x,c=c/l.getHardwareScalingLevel()-(l.getRenderHeight()-h.y-h.height),A.update(m,c,h.width,h.height,T||_.a.IdentityReadOnly,g?_.a.IdentityReadOnly:S.getViewMatrix(),S.getProjectionMatrix()),this},M.a.prototype.createPickingRayInCameraSpace=function(m,c,T){var A=C.Zero();return this.createPickingRayInCameraSpaceToRef(m,c,A,T),A},M.a.prototype.createPickingRayInCameraSpaceToRef=function(m,c,T,A){if(!x.a)return this;var S=this.getEngine();if(!A){if(!this.activeCamera)throw new Error("Active camera not set");A=this.activeCamera}var g=A.viewport.toGlobal(S.getRenderWidth(),S.getRenderHeight()),l=_.a.Identity();return m=m/S.getHardwareScalingLevel()-g.x,c=c/S.getHardwareScalingLevel()-(S.getRenderHeight()-g.y-g.height),T.update(m,c,g.width,g.height,l,l,A.getProjectionMatrix()),this},M.a.prototype._internalPickForMesh=function(m,c,T,A,S,g,l,h){var v=c(A),E=T.intersects(v,S,l,g,A,h);return E&&E.hit?!S&&m!=null&&E.distance>=m.distance?null:E:null},M.a.prototype._internalPick=function(m,c,T,A,S){if(!x.a)return null;for(var g=null,l=0;l<this.meshes.length;l++){var h=this.meshes[l];if(c){if(!c(h))continue}else if(!h.isEnabled()||!h.isVisible||!h.isPickable)continue;var v,E=h.skeleton&&h.skeleton.overrideMesh?h.skeleton.overrideMesh.getWorldMatrix():h.getWorldMatrix();if(h.hasThinInstances&&h.thinInstanceEnablePicking){if(v=this._internalPickForMesh(g,m,h,E,!0,!0,S)){if(A)return g;for(var D=_.c.Matrix[1],w=h.thinInstanceGetWorldMatrices(),N=0;N<w.length;N++){w[N].multiplyToRef(E,D);var I=this._internalPickForMesh(g,m,h,D,T,A,S,!0);if(I&&((g=I).thinInstanceIndex=N,T))return g}}}else if((v=this._internalPickForMesh(g,m,h,E,T,A,S))&&(g=v,T))return g}return g||new x.a},M.a.prototype._internalMultiPick=function(m,c,T){if(!x.a)return null;for(var A=new Array,S=0;S<this.meshes.length;S++){var g=this.meshes[S];if(c){if(!c(g))continue}else if(!g.isEnabled()||!g.isVisible||!g.isPickable)continue;var l,h=g.skeleton&&g.skeleton.overrideMesh?g.skeleton.overrideMesh.getWorldMatrix():g.getWorldMatrix();if(g.hasThinInstances&&g.thinInstanceEnablePicking){if(l=this._internalPickForMesh(null,m,g,h,!0,!0,T))for(var v=_.c.Matrix[1],E=g.thinInstanceGetWorldMatrices(),D=0;D<E.length;D++){E[D].multiplyToRef(h,v);var w=this._internalPickForMesh(null,m,g,v,!1,!1,T,!0);w&&(w.thinInstanceIndex=D,A.push(w))}}else(l=this._internalPickForMesh(null,m,g,h,!1,!1,T))&&A.push(l)}return A},M.a.prototype.pickWithBoundingInfo=function(m,c,T,A,S){var g=this;if(!x.a)return null;var l=this._internalPick(function(h){return g._tempPickingRay||(g._tempPickingRay=C.Zero()),g.createPickingRayToRef(m,c,h,g._tempPickingRay,S||null),g._tempPickingRay},T,A,!0);return l&&(l.ray=this.createPickingRay(m,c,_.a.Identity(),S||null)),l},M.a.prototype.pick=function(m,c,T,A,S,g){var l=this;if(!x.a)return null;var h=this._internalPick(function(v){return l._tempPickingRay||(l._tempPickingRay=C.Zero()),l.createPickingRayToRef(m,c,v,l._tempPickingRay,S||null),l._tempPickingRay},T,A,!1,g);return h&&(h.ray=this.createPickingRay(m,c,_.a.Identity(),S||null)),h},M.a.prototype.pickWithRay=function(m,c,T,A){var S=this,g=this._internalPick(function(l){return S._pickWithRayInverseMatrix||(S._pickWithRayInverseMatrix=_.a.Identity()),l.invertToRef(S._pickWithRayInverseMatrix),S._cachedRayForTransform||(S._cachedRayForTransform=C.Zero()),C.TransformToRef(m,S._pickWithRayInverseMatrix,S._cachedRayForTransform),S._cachedRayForTransform},c,T,!1,A);return g&&(g.ray=m),g},M.a.prototype.multiPick=function(m,c,T,A,S){var g=this;return this._internalMultiPick(function(l){return g.createPickingRay(m,c,l,A||null)},T,S)},M.a.prototype.multiPickWithRay=function(m,c,T){var A=this;return this._internalMultiPick(function(S){return A._pickWithRayInverseMatrix||(A._pickWithRayInverseMatrix=_.a.Identity()),S.invertToRef(A._pickWithRayInverseMatrix),A._cachedRayForTransform||(A._cachedRayForTransform=C.Zero()),C.TransformToRef(m,A._pickWithRayInverseMatrix,A._cachedRayForTransform),A._cachedRayForTransform},c,T)},R.a.prototype.getForwardRay=function(m,c,T){return m===void 0&&(m=100),this.getForwardRayToRef(new C(_.e.Zero(),_.e.Zero(),m),m,c,T)},R.a.prototype.getForwardRayToRef=function(m,c,T,A){return c===void 0&&(c=100),T||(T=this.getWorldMatrix()),m.length=c,A?m.origin.copyFrom(A):m.origin.copyFrom(this.position),_.c.Vector3[2].set(0,0,this._scene.useRightHandedSystem?-1:1),_.e.TransformNormalToRef(_.c.Vector3[2],T,_.c.Vector3[3]),_.e.NormalizeToRef(_.c.Vector3[3],m.direction),m}},function(Me,y,f){f.d(y,"a",function(){return R});var U=f(0),_=f(7),x=f(16),u=f(98),M=f(4);x.a.CreateLineSystem=function(C){for(var m=[],c=[],T=C.lines,A=C.colors,S=[],g=0,l=0;l<T.length;l++)for(var h=T[l],v=0;v<h.length;v++){if(c.push(h[v].x,h[v].y,h[v].z),A){var E=A[l];S.push(E[v].r,E[v].g,E[v].b,E[v].a)}v>0&&(m.push(g-1),m.push(g)),g++}var D=new x.a;return D.indices=m,D.positions=c,A&&(D.colors=S),D},x.a.CreateDashedLines=function(C){var m,c,T=C.dashSize||3,A=C.gapSize||1,S=C.dashNb||200,g=C.points,l=new Array,h=new Array,v=U.e.Zero(),E=0,D=0,w=0,N=0,I=0;for(I=0;I<g.length-1;I++)g[I+1].subtractToRef(g[I],v),E+=v.length();for(c=T*(m=E/S)/(T+A),I=0;I<g.length-1;I++){g[I+1].subtractToRef(g[I],v),D=Math.floor(v.length()/m),v.normalize();for(var V=0;V<D;V++)w=m*V,l.push(g[I].x+w*v.x,g[I].y+w*v.y,g[I].z+w*v.z),l.push(g[I].x+(w+c)*v.x,g[I].y+(w+c)*v.y,g[I].z+(w+c)*v.z),h.push(N,N+1),N+=2}var X=new x.a;return X.positions=l,X.indices=h,X},_.a.CreateLines=function(C,m,c,T,A){c===void 0&&(c=null),T===void 0&&(T=!1),A===void 0&&(A=null);var S={points:m,updatable:T,instance:A};return R.CreateLines(C,S,c)},_.a.CreateDashedLines=function(C,m,c,T,A,S,g,l){S===void 0&&(S=null);var h={points:m,dashSize:c,gapSize:T,dashNb:A,updatable:g,instance:l};return R.CreateDashedLines(C,h,S)};var R=function(){function C(){}return C.CreateLineSystem=function(m,c,T){var A=c.instance,S=c.lines,g=c.colors;if(A){var l,h,v=A.getVerticesData(M.b.PositionKind);g&&(l=A.getVerticesData(M.b.ColorKind));for(var E=0,D=0,w=0;w<S.length;w++)for(var N=S[w],I=0;I<N.length;I++)v[E]=N[I].x,v[E+1]=N[I].y,v[E+2]=N[I].z,g&&l&&(h=g[w],l[D]=h[I].r,l[D+1]=h[I].g,l[D+2]=h[I].b,l[D+3]=h[I].a,D+=4),E+=3;return A.updateVerticesData(M.b.PositionKind,v,!1,!1),g&&l&&A.updateVerticesData(M.b.ColorKind,l,!1,!1),A}var V=!!g,X=new u.b(m,T,null,void 0,void 0,V,c.useVertexAlpha);return x.a.CreateLineSystem(c).applyToMesh(X,c.updatable),X},C.CreateLines=function(m,c,T){T===void 0&&(T=null);var A=c.colors?[c.colors]:null;return C.CreateLineSystem(m,{lines:[c.points],updatable:c.updatable,instance:c.instance,colors:A,useVertexAlpha:c.useVertexAlpha},T)},C.CreateDashedLines=function(m,c,T){T===void 0&&(T=null);var A=c.points,S=c.instance,g=c.gapSize||1,l=c.dashSize||3;if(S)return S.updateMeshPositions(function(v){var E,D,w=U.e.Zero(),N=v.length/6,I=0,V=0,X=0,j=0,ne=0,te=0;for(ne=0;ne<A.length-1;ne++)A[ne+1].subtractToRef(A[ne],w),I+=w.length();E=I/N;var de=S._creationDataStorage.dashSize;for(D=de*E/(de+S._creationDataStorage.gapSize),ne=0;ne<A.length-1;ne++)for(A[ne+1].subtractToRef(A[ne],w),V=Math.floor(w.length()/E),w.normalize(),te=0;te<V&&j<v.length;)X=E*te,v[j]=A[ne].x+X*w.x,v[j+1]=A[ne].y+X*w.y,v[j+2]=A[ne].z+X*w.z,v[j+3]=A[ne].x+(X+D)*w.x,v[j+4]=A[ne].y+(X+D)*w.y,v[j+5]=A[ne].z+(X+D)*w.z,j+=6,te++;for(;j<v.length;)v[j]=A[ne].x,v[j+1]=A[ne].y,v[j+2]=A[ne].z,j+=3},!1),S;var h=new u.b(m,T,null,void 0,void 0,void 0,c.useVertexAlpha);return x.a.CreateDashedLines(c).applyToMesh(h,c.updatable),h._creationDataStorage=new _.b,h._creationDataStorage.dashSize=l,h._creationDataStorage.gapSize=g,h},C}()},function(Me,y,f){f.d(y,"a",function(){return u});var U=f(34),_=f(8),x=function(M,R){return M?M.getClassName&&M.getClassName()==="Mesh"?null:M.getClassName&&M.getClassName()==="SubMesh"?M.clone(R):M.clone?M.clone():null:null},u=function(){function M(){}return M.DeepCopy=function(R,C,m,c){for(var T=0,A=function(E){var D=[];do Object.getOwnPropertyNames(E).forEach(function(w){D.indexOf(w)===-1&&D.push(w)});while(E=Object.getPrototypeOf(E));return D}(R);T<A.length;T++){var S=A[T];if((S[0]!=="_"||c&&c.indexOf(S)!==-1)&&!(U.a.EndsWith(S,"Observable")||m&&m.indexOf(S)!==-1)){var g=R[S],l=typeof g;if(l!=="function")try{if(l==="object")if(g instanceof Array){if(C[S]=[],g.length>0)if(typeof g[0]=="object")for(var h=0;h<g.length;h++){var v=x(g[h],C);C[S].indexOf(v)===-1&&C[S].push(v)}else C[S]=g.slice(0)}else C[S]=x(g,C);else 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this._toneMappingEnabled},set:function(A){this._toneMappingEnabled!==A&&(this._toneMappingEnabled=A,this._updateParameters())},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"toneMappingType",{get:function(){return this._toneMappingType},set:function(A){this._toneMappingType!==A&&(this._toneMappingType=A,this._updateParameters())},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"contrast",{get:function(){return this._contrast},set:function(A){this._contrast!==A&&(this._contrast=A,this._updateParameters())},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"vignetteBlendMode",{get:function(){return this._vignetteBlendMode},set:function(A){this._vignetteBlendMode!==A&&(this._vignetteBlendMode=A,this._updateParameters())},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"vignetteEnabled",{get:function(){return 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A.VIGNETTE=!1,A.TONEMAPPING=!1,A.TONEMAPPING_ACES=!1,A.CONTRAST=!1,A.EXPOSURE=!1,A.COLORCURVES=!1,A.COLORGRADING=!1,A.COLORGRADING3D=!1,A.IMAGEPROCESSING=!1,void(A.IMAGEPROCESSINGPOSTPROCESS=this.applyByPostProcess&&this._isEnabled);switch(A.VIGNETTE=this.vignetteEnabled,A.VIGNETTEBLENDMODEMULTIPLY=this.vignetteBlendMode===T._VIGNETTEMODE_MULTIPLY,A.VIGNETTEBLENDMODEOPAQUE=!A.VIGNETTEBLENDMODEMULTIPLY,A.TONEMAPPING=this.toneMappingEnabled,this._toneMappingType){case T.TONEMAPPING_ACES:A.TONEMAPPING_ACES=!0;break;default:A.TONEMAPPING_ACES=!1}A.CONTRAST=this.contrast!==1,A.EXPOSURE=this.exposure!==1,A.COLORCURVES=this.colorCurvesEnabled&&!!this.colorCurves,A.COLORGRADING=this.colorGradingEnabled&&!!this.colorGradingTexture,A.COLORGRADING?A.COLORGRADING3D=this.colorGradingTexture.is3D:A.COLORGRADING3D=!1,A.SAMPLER3DGREENDEPTH=this.colorGradingWithGreenDepth,A.SAMPLER3DBGRMAP=this.colorGradingBGR,A.IMAGEPROCESSINGPOSTPROCESS=this.applyByPostProcess,A.IMAGEPROCESSING=A.VIGNETTE||A.TONEMAPPING||A.CONTRAST||A.EXPOSURE||A.COLORCURVES||A.COLORGRADING},T.prototype.isReady=function(){return!this.colorGradingEnabled||!this.colorGradingTexture||this.colorGradingTexture.isReady()},T.prototype.bind=function(A,S){if(this._colorCurvesEnabled&&this.colorCurves&&C.a.Bind(this.colorCurves,A),this._vignetteEnabled){var g=1/A.getEngine().getRenderWidth(),l=1/A.getEngine().getRenderHeight();A.setFloat2("vInverseScreenSize",g,l);var h=S??l/g,v=Math.tan(.5*this.vignetteCameraFov),E=v*h,D=Math.sqrt(E*v);E=u.b.Mix(E,D,this.vignetteStretch),v=u.b.Mix(v,D,this.vignetteStretch),A.setFloat4("vignetteSettings1",E,v,-E*this.vignetteCentreX,-v*this.vignetteCentreY);var w=-2*this.vignetteWeight;A.setFloat4("vignetteSettings2",this.vignetteColor.r,this.vignetteColor.g,this.vignetteColor.b,w)}if(A.setFloat("exposureLinear",this.exposure),A.setFloat("contrast",this.contrast),this.colorGradingTexture){A.setTexture("txColorTransform",this.colorGradingTexture);var N=this.colorGradingTexture.getSize().height;A.setFloat4("colorTransformSettings",(N-1)/N,.5/N,N,this.colorGradingTexture.level)}},T.prototype.clone=function(){return _.a.Clone(function(){return new T},this)},T.prototype.serialize=function(){return _.a.Serialize(this)},T.Parse=function(A){return _.a.Parse(function(){return new T},A,null,null)},Object.defineProperty(T,"VIGNETTEMODE_MULTIPLY",{get:function(){return this._VIGNETTEMODE_MULTIPLY},enumerable:!1,configurable:!0}),Object.defineProperty(T,"VIGNETTEMODE_OPAQUE",{get:function(){return this._VIGNETTEMODE_OPAQUE},enumerable:!1,configurable:!0}),T.TONEMAPPING_STANDARD=0,T.TONEMAPPING_ACES=1,T._VIGNETTEMODE_MULTIPLY=0,T._VIGNETTEMODE_OPAQUE=1,Object(U.c)([Object(_.g)()],T.prototype,"colorCurves",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_colorCurvesEnabled",void 0),Object(U.c)([Object(_.m)("colorGradingTexture")],T.prototype,"_colorGradingTexture",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_colorGradingEnabled",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_colorGradingWithGreenDepth",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_colorGradingBGR",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_exposure",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_toneMappingEnabled",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_toneMappingType",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_contrast",void 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l=_.e.Dot(S.centerWorld,A),h=Math.abs(_.e.Dot(S.directions[0],A))*S.extendSize.x+Math.abs(_.e.Dot(S.directions[1],A))*S.extendSize.y+Math.abs(_.e.Dot(S.directions[2],A))*S.extendSize.z;g.min=l-h,g.max=l+h},c=function(A,S,g){return m(A,S,R),m(A,g,C),!(R.min>C.max||C.min>R.max)},T=function(){function A(S,g,l){this._isLocked=!1,this.boundingBox=new u.a(S,g,l),this.boundingSphere=new M.a(S,g,l)}return A.prototype.reConstruct=function(S,g,l){this.boundingBox.reConstruct(S,g,l),this.boundingSphere.reConstruct(S,g,l)},Object.defineProperty(A.prototype,"minimum",{get:function(){return this.boundingBox.minimum},enumerable:!1,configurable:!0}),Object.defineProperty(A.prototype,"maximum",{get:function(){return this.boundingBox.maximum},enumerable:!1,configurable:!0}),Object.defineProperty(A.prototype,"isLocked",{get:function(){return 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S._canDoCollision(this.boundingSphere.centerWorld,this.boundingSphere.radiusWorld,this.boundingBox.minimumWorld,this.boundingBox.maximumWorld)},A.prototype.intersectsPoint=function(S){return!!this.boundingSphere.centerWorld&&!!this.boundingSphere.intersectsPoint(S)&&!!this.boundingBox.intersectsPoint(S)},A.prototype.intersects=function(S,g){if(!M.a.Intersects(this.boundingSphere,S.boundingSphere)||!u.a.Intersects(this.boundingBox,S.boundingBox))return!1;if(!g)return!0;var l=this.boundingBox,h=S.boundingBox;return!!c(l.directions[0],l,h)&&!!c(l.directions[1],l,h)&&!!c(l.directions[2],l,h)&&!!c(h.directions[0],l,h)&&!!c(h.directions[1],l,h)&&!!c(h.directions[2],l,h)&&!!c(_.e.Cross(l.directions[0],h.directions[0]),l,h)&&!!c(_.e.Cross(l.directions[0],h.directions[1]),l,h)&&!!c(_.e.Cross(l.directions[0],h.directions[2]),l,h)&&!!c(_.e.Cross(l.directions[1],h.directions[0]),l,h)&&!!c(_.e.Cross(l.directions[1],h.directions[1]),l,h)&&!!c(_.e.Cross(l.directions[1],h.directions[2]),l,h)&&!!c(_.e.Cross(l.directions[2],h.directions[0]),l,h)&&!!c(_.e.Cross(l.directions[2],h.directions[1]),l,h)&&!!c(_.e.Cross(l.directions[2],h.directions[2]),l,h)},A.TmpVector3=U.a.BuildArray(2,_.e.Zero),A}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.BuildArray=function(x,u){for(var M=[],R=0;R<x;++R)M.push(u());return M},_}()},function(Me,y,f){f.d(y,"a",function(){return u});var U=f(0),_=f(7),x=f(16);x.a.CreateSphere=function(M){for(var R=M.segments||32,C=M.diameterX||M.diameter||1,m=M.diameterY||M.diameter||1,c=M.diameterZ||M.diameter||1,T=M.arc&&(M.arc<=0||M.arc>1)?1:M.arc||1,A=M.slice&&M.slice<=0?1:M.slice||1,S=M.sideOrientation===0?0:M.sideOrientation||x.a.DEFAULTSIDE,g=!!M.dedupTopBottomIndices,l=new U.e(C/2,m/2,c/2),h=2+R,v=2*h,E=[],D=[],w=[],N=[],I=0;I<=h;I++){for(var V=I/h,X=V*Math.PI*A,j=0;j<=v;j++){var ne=j/v,te=ne*Math.PI*2*T,de=U.a.RotationZ(-X),pe=U.a.RotationY(te),ae=U.e.TransformCoordinates(U.e.Up(),de),ee=U.e.TransformCoordinates(ae,pe),K=ee.multiply(l),$=ee.divide(l).normalize();D.push(K.x,K.y,K.z),w.push($.x,$.y,$.z),N.push(ne,V)}if(I>0)for(var L=D.length/3,G=L-2*(v+1);G+v+2<L;G++)g?(I>1&&(E.push(G),E.push(G+1),E.push(G+v+1)),(I<h||A<1)&&(E.push(G+v+1),E.push(G+1),E.push(G+v+2))):(E.push(G),E.push(G+1),E.push(G+v+1),E.push(G+v+1),E.push(G+1),E.push(G+v+2))}x.a._ComputeSides(S,D,E,w,N,M.frontUVs,M.backUVs);var Q=new x.a;return 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this._rotation},set:function(T){this._rotation=T,this._rotationQuaternion=null,this._isDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"scaling",{get:function(){return this._scaling},set:function(T){this._scaling=T,this._isDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"rotationQuaternion",{get:function(){return this._rotationQuaternion},set:function(T){this._rotationQuaternion=T,T&&this._rotation.setAll(0),this._isDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"forward",{get:function(){return u.e.Normalize(u.e.TransformNormal(this.getScene().useRightHandedSystem?this._forwardInverted:this._forward,this.getWorldMatrix()))},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"up",{get:function(){return u.e.Normalize(u.e.TransformNormal(this._up,this.getWorldMatrix()))},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"right",{get:function(){return 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0&&(A=!0),this._pivotMatrix.copyFrom(T),this._usePivotMatrix=!this._pivotMatrix.isIdentity(),this._cache.pivotMatrixUpdated=!0,this._postMultiplyPivotMatrix=A,this._postMultiplyPivotMatrix&&(this._pivotMatrixInverse?this._pivotMatrix.invertToRef(this._pivotMatrixInverse):this._pivotMatrixInverse=u.a.Invert(this._pivotMatrix)),this},c.prototype.getPivotMatrix=function(){return this._pivotMatrix},c.prototype.instantiateHierarchy=function(T,A,S){T===void 0&&(T=null);var g=this.clone("Clone of "+(this.name||this.id),T||this.parent,!0);g&&S&&S(this,g);for(var l=0,h=this.getChildTransformNodes(!0);l<h.length;l++)h[l].instantiateHierarchy(g,A,S);return g},c.prototype.freezeWorldMatrix=function(T){return T===void 0&&(T=null),T?this._worldMatrix=T:(this._isWorldMatrixFrozen=!1,this.computeWorldMatrix(!0)),this._isDirty=!1,this._isWorldMatrixFrozen=!0,this},c.prototype.unfreezeWorldMatrix=function(){return this._isWorldMatrixFrozen=!1,this.computeWorldMatrix(!0),this},Object.defineProperty(c.prototype,"isWorldMatrixFrozen",{get:function(){return this._isWorldMatrixFrozen},enumerable:!1,configurable:!0}),c.prototype.getAbsolutePosition=function(){return this.computeWorldMatrix(),this._absolutePosition},c.prototype.setAbsolutePosition=function(T){if(!T)return this;var A,S,g;if(T.x===void 0){if(arguments.length<3)return this;A=arguments[0],S=arguments[1],g=arguments[2]}else A=T.x,S=T.y,g=T.z;if(this.parent){var l=u.c.Matrix[0];this.parent.getWorldMatrix().invertToRef(l),u.e.TransformCoordinatesFromFloatsToRef(A,S,g,l,this.position)}else this.position.x=A,this.position.y=S,this.position.z=g;return this._absolutePosition.copyFrom(T),this},c.prototype.setPositionWithLocalVector=function(T){return this.computeWorldMatrix(),this.position=u.e.TransformNormal(T,this._localMatrix),this},c.prototype.getPositionExpressedInLocalSpace=function(){this.computeWorldMatrix();var T=u.c.Matrix[0];return this._localMatrix.invertToRef(T),u.e.TransformNormal(this.position,T)},c.prototype.locallyTranslate=function(T){return this.computeWorldMatrix(!0),this.position=u.e.TransformCoordinates(T,this._localMatrix),this},c.prototype.lookAt=function(T,A,S,g,l){A===void 0&&(A=0),S===void 0&&(S=0),g===void 0&&(g=0),l===void 0&&(l=R.c.LOCAL);var h=c._lookAtVectorCache,v=l===R.c.LOCAL?this.position:this.getAbsolutePosition();if(T.subtractToRef(v,h),this.setDirection(h,A,S,g),l===R.c.WORLD&&this.parent)if(this.rotationQuaternion){var E=u.c.Matrix[0];this.rotationQuaternion.toRotationMatrix(E);var D=u.c.Matrix[1];this.parent.getWorldMatrix().getRotationMatrixToRef(D),D.invert(),E.multiplyToRef(D,E),this.rotationQuaternion.fromRotationMatrix(E)}else{var w=u.c.Quaternion[0];u.b.FromEulerVectorToRef(this.rotation,w),E=u.c.Matrix[0],w.toRotationMatrix(E),D=u.c.Matrix[1],this.parent.getWorldMatrix().getRotationMatrixToRef(D),D.invert(),E.multiplyToRef(D,E),w.fromRotationMatrix(E),w.toEulerAnglesToRef(this.rotation)}return this},c.prototype.getDirection=function(T){var A=u.e.Zero();return this.getDirectionToRef(T,A),A},c.prototype.getDirectionToRef=function(T,A){return u.e.TransformNormalToRef(T,this.getWorldMatrix(),A),this},c.prototype.setDirection=function(T,A,S,g){A===void 0&&(A=0),S===void 0&&(S=0),g===void 0&&(g=0);var l=-Math.atan2(T.z,T.x)+Math.PI/2,h=Math.sqrt(T.x*T.x+T.z*T.z),v=-Math.atan2(T.y,h);return this.rotationQuaternion?u.b.RotationYawPitchRollToRef(l+A,v+S,g,this.rotationQuaternion):(this.rotation.x=v+S,this.rotation.y=l+A,this.rotation.z=g),this},c.prototype.setPivotPoint=function(T,A){A===void 0&&(A=R.c.LOCAL),this.getScene().getRenderId()==0&&this.computeWorldMatrix(!0);var S=this.getWorldMatrix();if(A==R.c.WORLD){var g=u.c.Matrix[0];S.invertToRef(g),T=u.e.TransformCoordinates(T,g)}return this.setPivotMatrix(u.a.Translation(-T.x,-T.y,-T.z),!0)},c.prototype.getPivotPoint=function(){var T=u.e.Zero();return this.getPivotPointToRef(T),T},c.prototype.getPivotPointToRef=function(T){return T.x=-this._pivotMatrix.m[12],T.y=-this._pivotMatrix.m[13],T.z=-this._pivotMatrix.m[14],this},c.prototype.getAbsolutePivotPoint=function(){var T=u.e.Zero();return this.getAbsolutePivotPointToRef(T),T},c.prototype.getAbsolutePivotPointToRef=function(T){return this.getPivotPointToRef(T),u.e.TransformCoordinatesToRef(T,this.getWorldMatrix(),T),this},c.prototype.setParent=function(T){if(!T&&!this.parent)return this;var A=u.c.Quaternion[0],S=u.c.Vector3[0],g=u.c.Vector3[1];if(T){var l=u.c.Matrix[0],h=u.c.Matrix[1];this.computeWorldMatrix(!0),T.computeWorldMatrix(!0),T.getWorldMatrix().invertToRef(h),this.getWorldMatrix().multiplyToRef(h,l),l.decompose(g,A,S)}else this.computeWorldMatrix(!0),this.getWorldMatrix().decompose(g,A,S);return this.rotationQuaternion?this.rotationQuaternion.copyFrom(A):A.toEulerAnglesToRef(this.rotation),this.scaling.copyFrom(g),this.position.copyFrom(S),this.parent=T,this},Object.defineProperty(c.prototype,"nonUniformScaling",{get:function(){return this._nonUniformScaling},enumerable:!1,configurable:!0}),c.prototype._updateNonUniformScalingState=function(T){return this._nonUniformScaling!==T&&(this._nonUniformScaling=T,!0)},c.prototype.attachToBone=function(T,A){return this._transformToBoneReferal=A,this.parent=T,T.getSkeleton().prepare(),T.getWorldMatrix().determinant()<0&&(this.scalingDeterminant*=-1),this},c.prototype.detachFromBone=function(){return this.parent?(this.parent.getWorldMatrix().determinant()<0&&(this.scalingDeterminant*=-1),this._transformToBoneReferal=null,this.parent=null,this):this},c.prototype.rotate=function(T,A,S){var g;if(T.normalize(),this.rotationQuaternion||(this.rotationQuaternion=this.rotation.toQuaternion(),this.rotation.setAll(0)),S&&S!==R.c.LOCAL){if(this.parent){var l=u.c.Matrix[0];this.parent.getWorldMatrix().invertToRef(l),T=u.e.TransformNormal(T,l)}(g=u.b.RotationAxisToRef(T,A,c._rotationAxisCache)).multiplyToRef(this.rotationQuaternion,this.rotationQuaternion)}else g=u.b.RotationAxisToRef(T,A,c._rotationAxisCache),this.rotationQuaternion.multiplyToRef(g,this.rotationQuaternion);return this},c.prototype.rotateAround=function(T,A,S){A.normalize(),this.rotationQuaternion||(this.rotationQuaternion=u.b.RotationYawPitchRoll(this.rotation.y,this.rotation.x,this.rotation.z),this.rotation.setAll(0));var g=u.c.Vector3[0],l=u.c.Vector3[1],h=u.c.Vector3[2],v=u.c.Quaternion[0],E=u.c.Matrix[0],D=u.c.Matrix[1],w=u.c.Matrix[2],N=u.c.Matrix[3];return T.subtractToRef(this.position,g),u.a.TranslationToRef(g.x,g.y,g.z,E),u.a.TranslationToRef(-g.x,-g.y,-g.z,D),u.a.RotationAxisToRef(A,S,w),D.multiplyToRef(w,N),N.multiplyToRef(E,N),N.decompose(l,v,h),this.position.addInPlace(h),v.multiplyToRef(this.rotationQuaternion,this.rotationQuaternion),this},c.prototype.translate=function(T,A,S){var g=T.scale(A);if(S&&S!==R.c.LOCAL)this.setAbsolutePosition(this.getAbsolutePosition().add(g));else{var l=this.getPositionExpressedInLocalSpace().add(g);this.setPositionWithLocalVector(l)}return this},c.prototype.addRotation=function(T,A,S){var g;this.rotationQuaternion?g=this.rotationQuaternion:(g=u.c.Quaternion[1],u.b.RotationYawPitchRollToRef(this.rotation.y,this.rotation.x,this.rotation.z,g));var l=u.c.Quaternion[0];return u.b.RotationYawPitchRollToRef(A,T,S,l),g.multiplyInPlace(l),this.rotationQuaternion||g.toEulerAnglesToRef(this.rotation),this},c.prototype._getEffectiveParent=function(){return this.parent},c.prototype.computeWorldMatrix=function(T){if(this._isWorldMatrixFrozen&&!this._isDirty)return this._worldMatrix;var A=this.getScene().getRenderId();if(!this._isDirty&&!T&&this.isSynchronized())return this._currentRenderId=A,this._worldMatrix;var S=this.getScene().activeCamera,g=(this._billboardMode&c.BILLBOARDMODE_USE_POSITION)!=0,l=this._billboardMode!==c.BILLBOARDMODE_NONE&&!this.preserveParentRotationForBillboard;l&&S&&g&&(this.lookAt(S.position),(this.billboardMode&c.BILLBOARDMODE_X)!==c.BILLBOARDMODE_X&&(this.rotation.x=0),(this.billboardMode&c.BILLBOARDMODE_Y)!==c.BILLBOARDMODE_Y&&(this.rotation.y=0),(this.billboardMode&c.BILLBOARDMODE_Z)!==c.BILLBOARDMODE_Z&&(this.rotation.z=0)),this._updateCache();var h=this._cache;h.pivotMatrixUpdated=!1,h.billboardMode=this.billboardMode,h.infiniteDistance=this.infiniteDistance,this._currentRenderId=A,this._childUpdateId++,this._isDirty=!1,this._position._isDirty=!1,this._rotation._isDirty=!1,this._scaling._isDirty=!1;var v,E=this._getEffectiveParent(),D=c._TmpScaling,w=this._position;if(this._infiniteDistance&&!this.parent&&S){var N=S.getWorldMatrix(),I=new u.e(N.m[12],N.m[13],N.m[14]);(w=c._TmpTranslation).copyFromFloats(this._position.x+I.x,this._position.y+I.y,this._position.z+I.z)}if(D.copyFromFloats(this._scaling.x*this.scalingDeterminant,this._scaling.y*this.scalingDeterminant,this._scaling.z*this.scalingDeterminant),this._rotationQuaternion?(this._rotationQuaternion._isDirty=!1,v=this._rotationQuaternion,this.reIntegrateRotationIntoRotationQuaternion&&this.rotation.lengthSquared()&&(this._rotationQuaternion.multiplyInPlace(u.b.RotationYawPitchRoll(this._rotation.y,this._rotation.x,this._rotation.z)),this._rotation.copyFromFloats(0,0,0))):(v=c._TmpRotation,u.b.RotationYawPitchRollToRef(this._rotation.y,this._rotation.x,this._rotation.z,v)),this._usePivotMatrix){var V=u.c.Matrix[1];u.a.ScalingToRef(D.x,D.y,D.z,V);var X=u.c.Matrix[0];v.toRotationMatrix(X),this._pivotMatrix.multiplyToRef(V,u.c.Matrix[4]),u.c.Matrix[4].multiplyToRef(X,this._localMatrix),this._postMultiplyPivotMatrix&&this._localMatrix.multiplyToRef(this._pivotMatrixInverse,this._localMatrix),this._localMatrix.addTranslationFromFloats(w.x,w.y,w.z)}else u.a.ComposeToRef(D,v,w,this._localMatrix);if(E&&E.getWorldMatrix){if(T&&E.computeWorldMatrix(),l){this._transformToBoneReferal?E.getWorldMatrix().multiplyToRef(this._transformToBoneReferal.getWorldMatrix(),u.c.Matrix[7]):u.c.Matrix[7].copyFrom(E.getWorldMatrix());var j=u.c.Vector3[5],ne=u.c.Vector3[6];u.c.Matrix[7].decompose(ne,void 0,j),u.a.ScalingToRef(ne.x,ne.y,ne.z,u.c.Matrix[7]),u.c.Matrix[7].setTranslation(j),this._localMatrix.multiplyToRef(u.c.Matrix[7],this._worldMatrix)}else this._transformToBoneReferal?(this._localMatrix.multiplyToRef(E.getWorldMatrix(),u.c.Matrix[6]),u.c.Matrix[6].multiplyToRef(this._transformToBoneReferal.getWorldMatrix(),this._worldMatrix)):this._localMatrix.multiplyToRef(E.getWorldMatrix(),this._worldMatrix);this._markSyncedWithParent()}else this._worldMatrix.copyFrom(this._localMatrix);if(l&&S&&this.billboardMode&&!g){var te=u.c.Vector3[0];if(this._worldMatrix.getTranslationToRef(te),u.c.Matrix[1].copyFrom(S.getViewMatrix()),u.c.Matrix[1].setTranslationFromFloats(0,0,0),u.c.Matrix[1].invertToRef(u.c.Matrix[0]),(this.billboardMode&c.BILLBOARDMODE_ALL)!==c.BILLBOARDMODE_ALL){u.c.Matrix[0].decompose(void 0,u.c.Quaternion[0],void 0);var de=u.c.Vector3[1];u.c.Quaternion[0].toEulerAnglesToRef(de),(this.billboardMode&c.BILLBOARDMODE_X)!==c.BILLBOARDMODE_X&&(de.x=0),(this.billboardMode&c.BILLBOARDMODE_Y)!==c.BILLBOARDMODE_Y&&(de.y=0),(this.billboardMode&c.BILLBOARDMODE_Z)!==c.BILLBOARDMODE_Z&&(de.z=0),u.a.RotationYawPitchRollToRef(de.y,de.x,de.z,u.c.Matrix[0])}this._worldMatrix.setTranslationFromFloats(0,0,0),this._worldMatrix.multiplyToRef(u.c.Matrix[0],this._worldMatrix),this._worldMatrix.setTranslation(u.c.Vector3[0])}return this.ignoreNonUniformScaling?this._updateNonUniformScalingState(!1):this._scaling.isNonUniformWithinEpsilon(1e-6)?this._updateNonUniformScalingState(!0):E&&E._nonUniformScaling?this._updateNonUniformScalingState(E._nonUniformScaling):this._updateNonUniformScalingState(!1),this._afterComputeWorldMatrix(),this._absolutePosition.copyFromFloats(this._worldMatrix.m[12],this._worldMatrix.m[13],this._worldMatrix.m[14]),this._isAbsoluteSynced=!1,this.onAfterWorldMatrixUpdateObservable.notifyObservers(this),this._poseMatrix||(this._poseMatrix=u.a.Invert(this._worldMatrix)),this._worldMatrixDeterminantIsDirty=!0,this._worldMatrix},c.prototype.resetLocalMatrix=function(T){if(T===void 0&&(T=!0),this.computeWorldMatrix(),T)for(var A=this.getChildren(),S=0;S<A.length;++S){var g=A[S];if(g){g.computeWorldMatrix();var l=u.c.Matrix[0];g._localMatrix.multiplyToRef(this._localMatrix,l);var h=u.c.Quaternion[0];l.decompose(g.scaling,h,g.position),g.rotationQuaternion?g.rotationQuaternion=h:h.toEulerAnglesToRef(g.rotation)}}this.scaling.copyFromFloats(1,1,1),this.position.copyFromFloats(0,0,0),this.rotation.copyFromFloats(0,0,0),this.rotationQuaternion&&(this.rotationQuaternion=u.b.Identity()),this._worldMatrix=u.a.Identity()},c.prototype._afterComputeWorldMatrix=function(){},c.prototype.registerAfterWorldMatrixUpdate=function(T){return this.onAfterWorldMatrixUpdateObservable.add(T),this},c.prototype.unregisterAfterWorldMatrixUpdate=function(T){return this.onAfterWorldMatrixUpdateObservable.removeCallback(T),this},c.prototype.getPositionInCameraSpace=function(T){return T===void 0&&(T=null),T||(T=this.getScene().activeCamera),u.e.TransformCoordinates(this.getAbsolutePosition(),T.getViewMatrix())},c.prototype.getDistanceToCamera=function(T){return T===void 0&&(T=null),T||(T=this.getScene().activeCamera),this.getAbsolutePosition().subtract(T.globalPosition).length()},c.prototype.clone=function(T,A,S){var g=this,l=_.a.Clone(function(){return new c(T,g.getScene())},this);if(l.name=T,l.id=T,A&&(l.parent=A),!S)for(var h=this.getDescendants(!0),v=0;v<h.length;v++){var E=h[v];E.clone&&E.clone(T+"."+E.name,l)}return l},c.prototype.serialize=function(T){var A=_.a.Serialize(this,T);return A.type=this.getClassName(),this.parent&&(A.parentId=this.parent.id),A.localMatrix=this.getPivotMatrix().asArray(),A.isEnabled=this.isEnabled(),this.parent&&(A.parentId=this.parent.id),A},c.Parse=function(T,A,S){var g=_.a.Parse(function(){return new c(T.name,A)},T,A,S);return T.localMatrix?g.setPreTransformMatrix(u.a.FromArray(T.localMatrix)):T.pivotMatrix&&g.setPivotMatrix(u.a.FromArray(T.pivotMatrix)),g.setEnabled(T.isEnabled),T.parentId&&(g._waitingParentId=T.parentId),g},c.prototype.getChildTransformNodes=function(T,A){var S=[];return this._getDescendants(S,T,function(g){return(!A||A(g))&&g instanceof c}),S},c.prototype.dispose=function(T,A){if(A===void 0&&(A=!1),this.getScene().stopAnimation(this),this.getScene().removeTransformNode(this),this.onAfterWorldMatrixUpdateObservable.clear(),T)for(var S=0,g=this.getChildTransformNodes(!0);S<g.length;S++){var l=g[S];l.parent=null,l.computeWorldMatrix(!0)}m.prototype.dispose.call(this,T,A)},c.prototype.normalizeToUnitCube=function(T,A,S){T===void 0&&(T=!0),A===void 0&&(A=!1);var g=null,l=null;A&&(this.rotationQuaternion?(l=this.rotationQuaternion.clone(),this.rotationQuaternion.copyFromFloats(0,0,0,1)):this.rotation&&(g=this.rotation.clone(),this.rotation.copyFromFloats(0,0,0)));var h=this.getHierarchyBoundingVectors(T,S),v=h.max.subtract(h.min),E=Math.max(v.x,v.y,v.z);if(E===0)return this;var D=1/E;return this.scaling.scaleInPlace(D),A&&(this.rotationQuaternion&&l?this.rotationQuaternion.copyFrom(l):this.rotation&&g&&this.rotation.copyFrom(g)),this},c.prototype._syncAbsoluteScalingAndRotation=function(){this._isAbsoluteSynced||(this._worldMatrix.decompose(this._absoluteScaling,this._absoluteRotationQuaternion),this._isAbsoluteSynced=!0)},c.BILLBOARDMODE_NONE=0,c.BILLBOARDMODE_X=1,c.BILLBOARDMODE_Y=2,c.BILLBOARDMODE_Z=4,c.BILLBOARDMODE_ALL=7,c.BILLBOARDMODE_USE_POSITION=128,c._TmpRotation=u.b.Zero(),c._TmpScaling=u.e.Zero(),c._TmpTranslation=u.e.Zero(),c._lookAtVectorCache=new u.e(0,0,0),c._rotationAxisCache=new u.b,Object(U.c)([Object(_.o)("position")],c.prototype,"_position",void 0),Object(U.c)([Object(_.o)("rotation")],c.prototype,"_rotation",void 0),Object(U.c)([Object(_.l)("rotationQuaternion")],c.prototype,"_rotationQuaternion",void 0),Object(U.c)([Object(_.o)("scaling")],c.prototype,"_scaling",void 0),Object(U.c)([Object(_.c)("billboardMode")],c.prototype,"_billboardMode",void 0),Object(U.c)([Object(_.c)()],c.prototype,"scalingDeterminant",void 0),Object(U.c)([Object(_.c)("infiniteDistance")],c.prototype,"_infiniteDistance",void 0),Object(U.c)([Object(_.c)()],c.prototype,"ignoreNonUniformScaling",void 0),Object(U.c)([Object(_.c)()],c.prototype,"reIntegrateRotationIntoRotationQuaternion",void 0),c}(M.a)},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(x,u,M,R,C,m){this.source=x,this.pointerX=u,this.pointerY=M,this.meshUnderPointer=R,this.sourceEvent=C,this.additionalData=m}return _.CreateNew=function(x,u,M){var R=x.getScene();return new _(x,R.pointerX,R.pointerY,R.meshUnderPointer||x,u,M)},_.CreateNewFromSprite=function(x,u,M,R){return new _(x,u.pointerX,u.pointerY,u.meshUnderPointer,M,R)},_.CreateNewFromScene=function(x,u){return new _(null,x.pointerX,x.pointerY,x.meshUnderPointer,u)},_.CreateNewFromPrimitive=function(x,u,M,R){return new _(x,u.x,u.y,null,M,R)},_}()},function(Me,y,f){f.d(y,"a",function(){return m});var U=f(1),_=f(3),x=f(0),u=f(9),M=f(29),R=f(85),C=f(11),m=function(c){function T(A,S){var g=c.call(this,A,S)||this;return g.diffuse=new u.a(1,1,1),g.specular=new u.a(1,1,1),g.falloffType=T.FALLOFF_DEFAULT,g.intensity=1,g._range=Number.MAX_VALUE,g._inverseSquaredRange=0,g._photometricScale=1,g._intensityMode=T.INTENSITYMODE_AUTOMATIC,g._radius=1e-5,g.renderPriority=0,g._shadowEnabled=!0,g._excludeWithLayerMask=0,g._includeOnlyWithLayerMask=0,g._lightmapMode=0,g._excludedMeshesIds=new Array,g._includedOnlyMeshesIds=new Array,g._isLight=!0,g.getScene().addLight(g),g._uniformBuffer=new R.a(g.getScene().getEngine()),g._buildUniformLayout(),g.includedOnlyMeshes=new Array,g.excludedMeshes=new Array,g._resyncMeshes(),g}return Object(U.d)(T,c),Object.defineProperty(T.prototype,"range",{get:function(){return this._range},set:function(A){this._range=A,this._inverseSquaredRange=1/(this.range*this.range)},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"intensityMode",{get:function(){return this._intensityMode},set:function(A){this._intensityMode=A,this._computePhotometricScale()},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"radius",{get:function(){return this._radius},set:function(A){this._radius=A,this._computePhotometricScale()},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"shadowEnabled",{get:function(){return this._shadowEnabled},set:function(A){this._shadowEnabled!==A&&(this._shadowEnabled=A,this._markMeshesAsLightDirty())},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"includedOnlyMeshes",{get:function(){return this._includedOnlyMeshes},set:function(A){this._includedOnlyMeshes=A,this._hookArrayForIncludedOnly(A)},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"excludedMeshes",{get:function(){return this._excludedMeshes},set:function(A){this._excludedMeshes=A,this._hookArrayForExcluded(A)},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"excludeWithLayerMask",{get:function(){return this._excludeWithLayerMask},set:function(A){this._excludeWithLayerMask=A,this._resyncMeshes()},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"includeOnlyWithLayerMask",{get:function(){return this._includeOnlyWithLayerMask},set:function(A){this._includeOnlyWithLayerMask=A,this._resyncMeshes()},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"lightmapMode",{get:function(){return this._lightmapMode},set:function(A){this._lightmapMode!==A&&(this._lightmapMode=A,this._markMeshesAsLightDirty())},enumerable:!1,configurable:!0}),T.prototype.transferTexturesToEffect=function(A,S){return this},T.prototype._bindLight=function(A,S,g,l,h){h===void 0&&(h=!1);var v=A.toString(),E=!1;if(!h||!this._uniformBuffer._alreadyBound){if(this._uniformBuffer.bindToEffect(g,"Light"+v),this._renderId!==S.getRenderId()||!this._uniformBuffer.useUbo){this._renderId=S.getRenderId();var D=this.getScaledIntensity();this.transferToEffect(g,v),this.diffuse.scaleToRef(D,u.c.Color3[0]),this._uniformBuffer.updateColor4("vLightDiffuse",u.c.Color3[0],this.range,v),l&&(this.specular.scaleToRef(D,u.c.Color3[1]),this._uniformBuffer.updateColor4("vLightSpecular",u.c.Color3[1],this.radius,v)),E=!0}if(this.transferTexturesToEffect(g,v),S.shadowsEnabled&&this.shadowEnabled){var w=this.getShadowGenerator();w&&(w.bindShadowLight(v,g),E=!0)}E&&this._uniformBuffer.update()}},T.prototype.getClassName=function(){return"Light"},T.prototype.toString=function(A){var S="Name: "+this.name;if(S+=", type: "+["Point","Directional","Spot","Hemispheric"][this.getTypeID()],this.animations)for(var g=0;g<this.animations.length;g++)S+=", animation[0]: "+this.animations[g].toString(A);return S},T.prototype._syncParentEnabledState=function(){c.prototype._syncParentEnabledState.call(this),this.isDisposed()||this._resyncMeshes()},T.prototype.setEnabled=function(A){c.prototype.setEnabled.call(this,A),this._resyncMeshes()},T.prototype.getShadowGenerator=function(){return this._shadowGenerator},T.prototype.getAbsolutePosition=function(){return x.e.Zero()},T.prototype.canAffectMesh=function(A){return!A||!(this.includedOnlyMeshes&&this.includedOnlyMeshes.length>0&&this.includedOnlyMeshes.indexOf(A)===-1)&&!(this.excludedMeshes&&this.excludedMeshes.length>0&&this.excludedMeshes.indexOf(A)!==-1)&&(this.includeOnlyWithLayerMask===0||(this.includeOnlyWithLayerMask&A.layerMask)!=0)&&!(this.excludeWithLayerMask!==0&&this.excludeWithLayerMask&A.layerMask)},T.CompareLightsPriority=function(A,S){return A.shadowEnabled!==S.shadowEnabled?(S.shadowEnabled?1:0)-(A.shadowEnabled?1:0):S.renderPriority-A.renderPriority},T.prototype.dispose=function(A,S){S===void 0&&(S=!1),this._shadowGenerator&&(this._shadowGenerator.dispose(),this._shadowGenerator=null),this.getScene().stopAnimation(this);for(var g=0,l=this.getScene().meshes;g<l.length;g++)l[g]._removeLightSource(this,!0);this._uniformBuffer.dispose(),this.getScene().removeLight(this),c.prototype.dispose.call(this,A,S)},T.prototype.getTypeID=function(){return 0},T.prototype.getScaledIntensity=function(){return this._photometricScale*this.intensity},T.prototype.clone=function(A,S){S===void 0&&(S=null);var g=T.GetConstructorFromName(this.getTypeID(),A,this.getScene());if(!g)return null;var l=_.a.Clone(g,this);return S&&(l.parent=S),l.setEnabled(this.isEnabled()),l},T.prototype.serialize=function(){var A=_.a.Serialize(this);return A.type=this.getTypeID(),this.parent&&(A.parentId=this.parent.id),this.excludedMeshes.length>0&&(A.excludedMeshesIds=[],this.excludedMeshes.forEach(function(S){A.excludedMeshesIds.push(S.id)})),this.includedOnlyMeshes.length>0&&(A.includedOnlyMeshesIds=[],this.includedOnlyMeshes.forEach(function(S){A.includedOnlyMeshesIds.push(S.id)})),_.a.AppendSerializedAnimations(this,A),A.ranges=this.serializeAnimationRanges(),A},T.GetConstructorFromName=function(A,S,g){var l=M.a.Construct("Light_Type_"+A,S,g);return l||null},T.Parse=function(A,S){var g=T.GetConstructorFromName(A.type,A.name,S);if(!g)return null;var l=_.a.Parse(g,A,S);if(A.excludedMeshesIds&&(l._excludedMeshesIds=A.excludedMeshesIds),A.includedOnlyMeshesIds&&(l._includedOnlyMeshesIds=A.includedOnlyMeshesIds),A.parentId&&(l._waitingParentId=A.parentId),A.falloffType!==void 0&&(l.falloffType=A.falloffType),A.lightmapMode!==void 0&&(l.lightmapMode=A.lightmapMode),A.animations){for(var h=0;h<A.animations.length;h++){var v=A.animations[h],E=C.a.GetClass("BABYLON.Animation");E&&l.animations.push(E.Parse(v))}M.a.ParseAnimationRanges(l,A,S)}return A.autoAnimate&&S.beginAnimation(l,A.autoAnimateFrom,A.autoAnimateTo,A.autoAnimateLoop,A.autoAnimateSpeed||1),l},T.prototype._hookArrayForExcluded=function(A){var S=this,g=A.push;A.push=function(){for(var E=[],D=0;D<arguments.length;D++)E[D]=arguments[D];for(var w=g.apply(A,E),N=0,I=E;N<I.length;N++){var V=I[N];V._resyncLightSource(S)}return w};var l=A.splice;A.splice=function(E,D){for(var w=l.apply(A,[E,D]),N=0,I=w;N<I.length;N++)I[N]._resyncLightSource(S);return w};for(var h=0,v=A;h<v.length;h++)v[h]._resyncLightSource(this)},T.prototype._hookArrayForIncludedOnly=function(A){var S=this,g=A.push;A.push=function(){for(var h=[],v=0;v<arguments.length;v++)h[v]=arguments[v];var E=g.apply(A,h);return S._resyncMeshes(),E};var l=A.splice;A.splice=function(h,v){var E=l.apply(A,[h,v]);return S._resyncMeshes(),E},this._resyncMeshes()},T.prototype._resyncMeshes=function(){for(var A=0,S=this.getScene().meshes;A<S.length;A++)S[A]._resyncLightSource(this)},T.prototype._markMeshesAsLightDirty=function(){for(var A=0,S=this.getScene().meshes;A<S.length;A++){var g=S[A];g.lightSources.indexOf(this)!==-1&&g._markSubMeshesAsLightDirty()}},T.prototype._computePhotometricScale=function(){this._photometricScale=this._getPhotometricScale(),this.getScene().resetCachedMaterial()},T.prototype._getPhotometricScale=function(){var A=0,S=this.getTypeID(),g=this.intensityMode;switch(g===T.INTENSITYMODE_AUTOMATIC&&(g=S===T.LIGHTTYPEID_DIRECTIONALLIGHT?T.INTENSITYMODE_ILLUMINANCE:T.INTENSITYMODE_LUMINOUSINTENSITY),S){case T.LIGHTTYPEID_POINTLIGHT:case T.LIGHTTYPEID_SPOTLIGHT:switch(g){case T.INTENSITYMODE_LUMINOUSPOWER:A=1/(4*Math.PI);break;case T.INTENSITYMODE_LUMINOUSINTENSITY:A=1;break;case T.INTENSITYMODE_LUMINANCE:A=this.radius*this.radius}break;case T.LIGHTTYPEID_DIRECTIONALLIGHT:switch(g){case T.INTENSITYMODE_ILLUMINANCE:A=1;break;case T.INTENSITYMODE_LUMINANCE:var l=this.radius;l=Math.max(l,.001),A=2*Math.PI*(1-Math.cos(l))}break;case T.LIGHTTYPEID_HEMISPHERICLIGHT:A=1}return A},T.prototype._reorderLightsInScene=function(){var A=this.getScene();this._renderPriority!=0&&(A.requireLightSorting=!0),this.getScene().sortLightsByPriority()},T.FALLOFF_DEFAULT=0,T.FALLOFF_PHYSICAL=1,T.FALLOFF_GLTF=2,T.FALLOFF_STANDARD=3,T.LIGHTMAP_DEFAULT=0,T.LIGHTMAP_SPECULAR=1,T.LIGHTMAP_SHADOWSONLY=2,T.INTENSITYMODE_AUTOMATIC=0,T.INTENSITYMODE_LUMINOUSPOWER=1,T.INTENSITYMODE_LUMINOUSINTENSITY=2,T.INTENSITYMODE_ILLUMINANCE=3,T.INTENSITYMODE_LUMINANCE=4,T.LIGHTTYPEID_POINTLIGHT=0,T.LIGHTTYPEID_DIRECTIONALLIGHT=1,T.LIGHTTYPEID_SPOTLIGHT=2,T.LIGHTTYPEID_HEMISPHERICLIGHT=3,Object(U.c)([Object(_.e)()],T.prototype,"diffuse",void 0),Object(U.c)([Object(_.e)()],T.prototype,"specular",void 0),Object(U.c)([Object(_.c)()],T.prototype,"falloffType",void 0),Object(U.c)([Object(_.c)()],T.prototype,"intensity",void 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U=f(0),_=f(7),x=f(36),u=f(18),M=function(){function R(C){var m=this;C===void 0&&(C=x.a.DefaultUtilityLayer),this.gizmoLayer=C,this._attachedMesh=null,this._attachedNode=null,this._scaleRatio=1,this._isHovered=!1,this._customMeshSet=!1,this._updateGizmoRotationToMatchAttachedMesh=!0,this.updateGizmoPositionToMatchAttachedMesh=!0,this.updateScale=!0,this._interactionsEnabled=!0,this._tempQuaternion=new U.b(0,0,0,1),this._tempVector=new U.e,this._tempVector2=new U.e,this._tempMatrix1=new U.a,this._tempMatrix2=new U.a,this._rightHandtoLeftHandMatrix=U.a.RotationY(Math.PI),this._rootMesh=new _.a("gizmoRootNode",C.utilityLayerScene),this._rootMesh.rotationQuaternion=U.b.Identity(),this._beforeRenderObserver=this.gizmoLayer.utilityLayerScene.onBeforeRenderObservable.add(function(){m._update()})}return Object.defineProperty(R.prototype,"scaleRatio",{get:function(){return 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T=this.gizmoLayer.utilityLayerScene.activeCamera,A=T.globalPosition;T.devicePosition&&(A=T.devicePosition),this._rootMesh.position.subtractToRef(A,this._tempVector);var S=this._tempVector.length()*this.scaleRatio;this._rootMesh.scaling.set(S,S,S),C._getWorldMatrixDeterminant()<0&&(this._rootMesh.scaling.y*=-1)}else this._rootMesh.scaling.setAll(this.scaleRatio)}},R.prototype._matrixChanged=function(){if(this._attachedNode){if(this._attachedNode._isCamera){var C,m,c=this._attachedNode;if(c.parent){var T=this._tempMatrix2;c.parent._worldMatrix.invertToRef(T),this._attachedNode._worldMatrix.multiplyToRef(T,this._tempMatrix1),C=this._tempMatrix1}else C=this._attachedNode._worldMatrix;if(c.getScene().useRightHandedSystem?(this._rightHandtoLeftHandMatrix.multiplyToRef(C,this._tempMatrix2),m=this._tempMatrix2):m=C,m.decompose(this._tempVector2,this._tempQuaternion,this._tempVector),this._attachedNode.getClassName()==="FreeCamera"||this._attachedNode.getClassName()==="FlyCamera"||this._attachedNode.getClassName()==="ArcFollowCamera"||this._attachedNode.getClassName()==="TargetCamera"||this._attachedNode.getClassName()==="TouchCamera"||this._attachedNode.getClassName()==="UniversalCamera"){var A=this._attachedNode;A.rotation=this._tempQuaternion.toEulerAngles(),A.rotationQuaternion&&A.rotationQuaternion.copyFrom(this._tempQuaternion)}c.position.copyFrom(this._tempVector)}else if(this._attachedNode._isMesh||this._attachedNode.getClassName()==="AbstractMesh"||this._attachedNode.getClassName()==="TransformNode"||this._attachedNode.getClassName()==="InstancedMesh"){var S=this._attachedNode;if(S.parent){T=this._tempMatrix1;var g=this._tempMatrix2;S.parent.getWorldMatrix().invertToRef(T),this._attachedNode.getWorldMatrix().multiplyToRef(T,g),g.decompose(S.scaling,this._tempQuaternion,S.position)}else this._attachedNode._worldMatrix.decompose(S.scaling,this._tempQuaternion,S.position);S.billboardMode||(S.rotationQuaternion?S.rotationQuaternion.copyFrom(this._tempQuaternion):S.rotation=this._tempQuaternion.toEulerAngles())}else if(this._attachedNode.getClassName()==="Bone"){var l=this._attachedNode,h=l.getParent();if(h){var v=this._tempMatrix1,E=this._tempMatrix2;h.getWorldMatrix().invertToRef(v),l.getWorldMatrix().multiplyToRef(v,E),l.getLocalMatrix().copyFrom(E)}else l.getLocalMatrix().copyFrom(l.getWorldMatrix());l.markAsDirty()}}},R.GizmoAxisPointerObserver=function(C,m){var c=!1;return C.utilityLayerScene.onPointerObservable.add(function(T){var A,S;if(T.pickInfo){if(T.type===u.a.POINTERMOVE){if(c)return;m.forEach(function(g){var l,h;if(g.colliderMeshes&&g.gizmoMeshes){var v=((l=g.colliderMeshes)===null||l===void 0?void 0:l.indexOf((h=T?.pickInfo)===null||h===void 0?void 0:h.pickedMesh))!=-1||g.active?g.hoverMaterial:g.material;g.gizmoMeshes.forEach(function(E){E.material=v,E.color&&(E.color=v.diffuseColor)})}})}T.type===u.a.POINTERDOWN&&m.has((A=T.pickInfo.pickedMesh)===null||A===void 0?void 0:A.parent)&&(c=!0,m.get((S=T.pickInfo.pickedMesh)===null||S===void 0?void 0:S.parent).active=!0,m.forEach(function(g){var l,h,v=((l=g.colliderMeshes)===null||l===void 0?void 0:l.indexOf((h=T?.pickInfo)===null||h===void 0?void 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_});var U=f(38),_=function(){function x(){}return Object.defineProperty(x,"Now",{get:function(){return U.a.IsWindowObjectExist()&&window.performance&&window.performance.now?window.performance.now():Date.now()},enumerable:!1,configurable:!0}),x}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(x,u,M,R){this.x=x,this.y=u,this.width=M,this.height=R}return _.prototype.toGlobal=function(x,u){return new _(this.x*x,this.y*u,this.width*x,this.height*u)},_.prototype.toGlobalToRef=function(x,u,M){return M.x=this.x*x,M.y=this.y*u,M.width=this.width*x,M.height=this.height*u,this},_.prototype.clone=function(){return new _(this.x,this.y,this.width,this.height)},_}()},function(Me,y,f){var U="helperFunctions",_=`const float PI=3.1415926535897932384626433832795;
-const float HALF_MIN=5.96046448e-08;
-const float LinearEncodePowerApprox=2.2;
-const float GammaEncodePowerApprox=1.0/LinearEncodePowerApprox;
-const vec3 LuminanceEncodeApprox=vec3(0.2126,0.7152,0.0722);
-const float Epsilon=0.0000001;
-#define saturate(x) clamp(x,0.0,1.0)
-#define absEps(x) abs(x)+Epsilon
-#define maxEps(x) max(x,Epsilon)
-#define saturateEps(x) clamp(x,Epsilon,1.0)
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-vec3 i0=inMatrix[0];
-vec3 i1=inMatrix[1];
-vec3 i2=inMatrix[2];
-mat3 outMatrix=mat3(
-vec3(i0.x,i1.x,i2.x),
-vec3(i0.y,i1.y,i2.y),
-vec3(i0.z,i1.z,i2.z)
-);
-return outMatrix;
-}
-
-mat3 inverseMat3(mat3 inMatrix) {
-float a00=inMatrix[0][0],a01=inMatrix[0][1],a02=inMatrix[0][2];
-float a10=inMatrix[1][0],a11=inMatrix[1][1],a12=inMatrix[1][2];
-float a20=inMatrix[2][0],a21=inMatrix[2][1],a22=inMatrix[2][2];
-float b01=a22*a11-a12*a21;
-float b11=-a22*a10+a12*a20;
-float b21=a21*a10-a11*a20;
-float det=a00*b01+a01*b11+a02*b21;
-return mat3(b01,(-a22*a01+a02*a21),(a12*a01-a02*a11),
-b11,(a22*a00-a02*a20),(-a12*a00+a02*a10),
-b21,(-a21*a00+a01*a20),(a11*a00-a01*a10))/det;
-}
-float toLinearSpace(float color)
-{
-return pow(color,LinearEncodePowerApprox);
-}
-vec3 toLinearSpace(vec3 color)
-{
-return pow(color,vec3(LinearEncodePowerApprox));
-}
-vec4 toLinearSpace(vec4 color)
-{
-return vec4(pow(color.rgb,vec3(LinearEncodePowerApprox)),color.a);
-}
-vec3 toGammaSpace(vec3 color)
-{
-return pow(color,vec3(GammaEncodePowerApprox));
-}
-vec4 toGammaSpace(vec4 color)
-{
-return vec4(pow(color.rgb,vec3(GammaEncodePowerApprox)),color.a);
-}
-float toGammaSpace(float color)
-{
-return pow(color,GammaEncodePowerApprox);
-}
-float square(float value)
-{
-return value*value;
-}
-float pow5(float value) {
-float sq=value*value;
-return sq*sq*value;
-}
-float getLuminance(vec3 color)
-{
-return clamp(dot(color,LuminanceEncodeApprox),0.,1.);
-}
-
-float getRand(vec2 seed) {
-return fract(sin(dot(seed.xy ,vec2(12.9898,78.233)))*43758.5453);
-}
-float dither(vec2 seed,float varianceAmount) {
-float rand=getRand(seed);
-float dither=mix(-varianceAmount/255.0,varianceAmount/255.0,rand);
-return dither;
-}
-
-const float rgbdMaxRange=255.0;
-vec4 toRGBD(vec3 color) {
-float maxRGB=maxEps(max(color.r,max(color.g,color.b)));
-float D=max(rgbdMaxRange/maxRGB,1.);
-D=clamp(floor(D)/255.0,0.,1.);
-
-vec3 rgb=color.rgb*D;
-
-rgb=toGammaSpace(rgb);
-return vec4(rgb,D);
-}
-vec3 fromRGBD(vec4 rgbd) {
-
-rgbd.rgb=toLinearSpace(rgbd.rgb);
-
-return rgbd.rgb/rgbd.a;
-}
-`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(0),_=function(){function x(){}return x._RemoveAndStorePivotPoint=function(u){u&&x._PivotCached===0&&(u.getPivotPointToRef(x._OldPivotPoint),x._PivotPostMultiplyPivotMatrix=u._postMultiplyPivotMatrix,x._OldPivotPoint.equalsToFloats(0,0,0)||(u.setPivotMatrix(U.a.IdentityReadOnly),x._OldPivotPoint.subtractToRef(u.getPivotPoint(),x._PivotTranslation),x._PivotTmpVector.copyFromFloats(1,1,1),x._PivotTmpVector.subtractInPlace(u.scaling),x._PivotTmpVector.multiplyInPlace(x._PivotTranslation),u.position.addInPlace(x._PivotTmpVector))),x._PivotCached++},x._RestorePivotPoint=function(u){u&&!x._OldPivotPoint.equalsToFloats(0,0,0)&&x._PivotCached===1&&(u.setPivotPoint(x._OldPivotPoint),u._postMultiplyPivotMatrix=x._PivotPostMultiplyPivotMatrix,x._PivotTmpVector.copyFromFloats(1,1,1),x._PivotTmpVector.subtractInPlace(u.scaling),x._PivotTmpVector.multiplyInPlace(x._PivotTranslation),u.position.subtractInPlace(x._PivotTmpVector)),this._PivotCached--},x._PivotCached=0,x._OldPivotPoint=new U.e,x._PivotTranslation=new U.e,x._PivotTmpVector=new U.e,x._PivotPostMultiplyPivotMatrix=!1,x}()},function(Me,y,f){f.d(y,"a",function(){return R});var U=f(4),_=f(114),x=f(43),u=f(2),M=f(101),R=function(){function C(m,c,T,A,S,g,l,h,v){h===void 0&&(h=!0),v===void 0&&(v=!0),this.materialIndex=m,this.verticesStart=c,this.verticesCount=T,this.indexStart=A,this.indexCount=S,this._materialDefines=null,this._materialEffect=null,this._effectOverride=null,this._linesIndexCount=0,this._linesIndexBuffer=null,this._lastColliderWorldVertices=null,this._lastColliderTransformMatrix=null,this._renderId=0,this._alphaIndex=0,this._distanceToCamera=0,this._currentMaterial=null,this._mesh=g,this._renderingMesh=l||g,v&&g.subMeshes.push(this),this._trianglePlanes=[],this._id=g.subMeshes.length-1,h&&(this.refreshBoundingInfo(),g.computeWorldMatrix(!0))}return Object.defineProperty(C.prototype,"materialDefines",{get:function(){return this._materialDefines},set:function(m){this._materialDefines=m},enumerable:!1,configurable:!0}),Object.defineProperty(C.prototype,"effect",{get:function(){var m;return(m=this._effectOverride)!==null&&m!==void 0?m:this._materialEffect},enumerable:!1,configurable:!0}),C.prototype.setEffect=function(m,c){c===void 0&&(c=null),this._materialEffect!==m?(this._materialDefines=c,this._materialEffect=m):m||(this._materialDefines=null)},C.AddToMesh=function(m,c,T,A,S,g,l,h){return h===void 0&&(h=!0),new C(m,c,T,A,S,g,l,h)},Object.defineProperty(C.prototype,"IsGlobal",{get:function(){return this.verticesStart===0&&this.verticesCount===this._mesh.getTotalVertices()},enumerable:!1,configurable:!0}),C.prototype.getBoundingInfo=function(){return this.IsGlobal?this._mesh.getBoundingInfo():this._boundingInfo},C.prototype.setBoundingInfo=function(m){return this._boundingInfo=m,this},C.prototype.getMesh=function(){return this._mesh},C.prototype.getRenderingMesh=function(){return this._renderingMesh},C.prototype.getReplacementMesh=function(){return this._mesh._internalAbstractMeshDataInfo._actAsRegularMesh?this._mesh:null},C.prototype.getEffectiveMesh=function(){var m=this._mesh._internalAbstractMeshDataInfo._actAsRegularMesh?this._mesh:null;return m||this._renderingMesh},C.prototype.getMaterial=function(){var m=this._renderingMesh.material;if(m==null)return this._mesh.getScene().defaultMaterial;if(this._IsMultiMaterial(m)){var c=m.getSubMaterial(this.materialIndex);return this._currentMaterial!==c&&(this._currentMaterial=c,this._materialDefines=null),c}return m},C.prototype._IsMultiMaterial=function(m){return m.getSubMaterial!==void 0},C.prototype.refreshBoundingInfo=function(m){if(m===void 0&&(m=null),this._lastColliderWorldVertices=null,this.IsGlobal||!this._renderingMesh||!this._renderingMesh.geometry)return this;if(m||(m=this._renderingMesh.getVerticesData(U.b.PositionKind)),!m)return this._boundingInfo=this._mesh.getBoundingInfo(),this;var c,T=this._renderingMesh.getIndices();if(this.indexStart===0&&this.indexCount===T.length){var A=this._renderingMesh.getBoundingInfo();c={minimum:A.minimum.clone(),maximum:A.maximum.clone()}}else c=Object(M.b)(m,T,this.indexStart,this.indexCount,this._renderingMesh.geometry.boundingBias);return this._boundingInfo?this._boundingInfo.reConstruct(c.minimum,c.maximum):this._boundingInfo=new x.a(c.minimum,c.maximum),this},C.prototype._checkCollision=function(m){return this.getBoundingInfo()._checkCollision(m)},C.prototype.updateBoundingInfo=function(m){var c=this.getBoundingInfo();return c||(this.refreshBoundingInfo(),c=this.getBoundingInfo()),c&&c.update(m),this},C.prototype.isInFrustum=function(m){var c=this.getBoundingInfo();return!!c&&c.isInFrustum(m,this._mesh.cullingStrategy)},C.prototype.isCompletelyInFrustum=function(m){var c=this.getBoundingInfo();return!!c&&c.isCompletelyInFrustum(m)},C.prototype.render=function(m){return this._renderingMesh.render(this,m,this._mesh._internalAbstractMeshDataInfo._actAsRegularMesh?this._mesh:void 0),this},C.prototype._getLinesIndexBuffer=function(m,c){if(!this._linesIndexBuffer){for(var T=[],A=this.indexStart;A<this.indexStart+this.indexCount;A+=3)T.push(m[A],m[A+1],m[A+1],m[A+2],m[A+2],m[A]);this._linesIndexBuffer=c.createIndexBuffer(T),this._linesIndexCount=T.length}return this._linesIndexBuffer},C.prototype.canIntersects=function(m){var c=this.getBoundingInfo();return!!c&&m.intersectsBox(c.boundingBox)},C.prototype.intersects=function(m,c,T,A,S){var g=this.getMaterial();if(!g)return null;var l=3,h=!1;switch(g.fillMode){case u.a.MATERIAL_PointListDrawMode:case u.a.MATERIAL_LineListDrawMode:case u.a.MATERIAL_LineLoopDrawMode:case u.a.MATERIAL_LineStripDrawMode:case u.a.MATERIAL_TriangleFanDrawMode:return null;case u.a.MATERIAL_TriangleStripDrawMode:l=1,h=!0}return this._mesh.getClassName()==="InstancedLinesMesh"||this._mesh.getClassName()==="LinesMesh"?T.length?this._intersectLines(m,c,T,this._mesh.intersectionThreshold,A):this._intersectUnIndexedLines(m,c,T,this._mesh.intersectionThreshold,A):!T.length&&this._mesh._unIndexed?this._intersectUnIndexedTriangles(m,c,T,A,S):this._intersectTriangles(m,c,T,l,h,A,S)},C.prototype._intersectLines=function(m,c,T,A,S){for(var g=null,l=this.indexStart;l<this.indexStart+this.indexCount;l+=2){var h=c[T[l]],v=c[T[l+1]],E=m.intersectionSegment(h,v,A);if(!(E<0)&&(S||!g||E<g.distance)&&((g=new _.a(null,null,E)).faceId=l/2,S))break}return g},C.prototype._intersectUnIndexedLines=function(m,c,T,A,S){for(var g=null,l=this.verticesStart;l<this.verticesStart+this.verticesCount;l+=2){var h=c[l],v=c[l+1],E=m.intersectionSegment(h,v,A);if(!(E<0)&&(S||!g||E<g.distance)&&((g=new _.a(null,null,E)).faceId=l/2,S))break}return g},C.prototype._intersectTriangles=function(m,c,T,A,S,g,l){for(var h=null,v=-1,E=this.indexStart;E<this.indexStart+this.indexCount;E+=A){v++;var D=T[E],w=T[E+1],N=T[E+2];if(S&&N===4294967295)E+=2;else{var I=c[D],V=c[w],X=c[N];if(!l||l(I,V,X,m)){var j=m.intersectsTriangle(I,V,X);if(j){if(j.distance<0)continue;if((g||!h||j.distance<h.distance)&&((h=j).faceId=v,g))break}}}}return h},C.prototype._intersectUnIndexedTriangles=function(m,c,T,A,S){for(var g=null,l=this.verticesStart;l<this.verticesStart+this.verticesCount;l+=3){var h=c[l],v=c[l+1],E=c[l+2];if(!S||S(h,v,E,m)){var D=m.intersectsTriangle(h,v,E);if(D){if(D.distance<0)continue;if((A||!g||D.distance<g.distance)&&((g=D).faceId=l/3,A))break}}}return g},C.prototype._rebuild=function(){this._linesIndexBuffer&&(this._linesIndexBuffer=null)},C.prototype.clone=function(m,c){var T=new C(this.materialIndex,this.verticesStart,this.verticesCount,this.indexStart,this.indexCount,m,c,!1);if(!this.IsGlobal){var A=this.getBoundingInfo();if(!A)return T;T._boundingInfo=new x.a(A.minimum,A.maximum)}return T},C.prototype.dispose=function(){this._linesIndexBuffer&&(this._mesh.getScene().getEngine()._releaseBuffer(this._linesIndexBuffer),this._linesIndexBuffer=null);var m=this._mesh.subMeshes.indexOf(this);this._mesh.subMeshes.splice(m,1)},C.prototype.getClassName=function(){return"SubMesh"},C.CreateFromIndices=function(m,c,T,A,S){for(var g=Number.MAX_VALUE,l=-Number.MAX_VALUE,h=(S||A).getIndices(),v=c;v<c+T;v++){var E=h[v];E<g&&(g=E),E>l&&(l=E)}return new C(m,g,l-g+1,c,T,A,S)},C}()},function(Me,y,f){f.d(y,"a",function(){return R});var U=f(1),_=f(8),x=f(10),u=f(2),M=(f(126),f(70)),R=function(C){function m(c,T,A,S,g,l,h){A===void 0&&(A=null),g===void 0&&(g=u.a.TEXTURE_TRILINEAR_SAMPLINGMODE),l===void 0&&(l=u.a.TEXTUREFORMAT_RGBA);var v=C.call(this,null,A,!S,h,g,void 0,void 0,void 0,void 0,l)||this;v.name=c,v.wrapU=x.a.CLAMP_ADDRESSMODE,v.wrapV=x.a.CLAMP_ADDRESSMODE,v._generateMipMaps=S;var E=v._getEngine();if(!E)return v;T.getContext?(v._canvas=T,v._texture=E.createDynamicTexture(T.width,T.height,S,g)):(v._canvas=M.a.CreateCanvas(1,1),T.width||T.width===0?v._texture=E.createDynamicTexture(T.width,T.height,S,g):v._texture=E.createDynamicTexture(T,T,S,g));var D=v.getSize();return v._canvas.width=D.width,v._canvas.height=D.height,v._context=v._canvas.getContext("2d"),v}return Object(U.d)(m,C),m.prototype.getClassName=function(){return"DynamicTexture"},Object.defineProperty(m.prototype,"canRescale",{get:function(){return!0},enumerable:!1,configurable:!0}),m.prototype._recreate=function(c){this._canvas.width=c.width,this._canvas.height=c.height,this.releaseInternalTexture(),this._texture=this._getEngine().createDynamicTexture(c.width,c.height,this._generateMipMaps,this.samplingMode)},m.prototype.scale=function(c){var T=this.getSize();T.width*=c,T.height*=c,this._recreate(T)},m.prototype.scaleTo=function(c,T){var A=this.getSize();A.width=c,A.height=T,this._recreate(A)},m.prototype.getContext=function(){return this._context},m.prototype.clear=function(){var c=this.getSize();this._context.fillRect(0,0,c.width,c.height)},m.prototype.update=function(c,T){T===void 0&&(T=!1),this._getEngine().updateDynamicTexture(this._texture,this._canvas,c===void 0||c,T,this._format||void 0)},m.prototype.drawText=function(c,T,A,S,g,l,h,v){v===void 0&&(v=!0);var E=this.getSize();if(l&&(this._context.fillStyle=l,this._context.fillRect(0,0,E.width,E.height)),this._context.font=S,T==null){var D=this._context.measureText(c);T=(E.width-D.width)/2}if(A==null){var w=parseInt(S.replace(/\D/g,""));A=E.height/2+w/3.65}this._context.fillStyle=g||"",this._context.fillText(c,T,A),v&&this.update(h)},m.prototype.clone=function(){var c=this.getScene();if(!c)return this;var T=this.getSize(),A=new m(this.name,T,c,this._generateMipMaps);return A.hasAlpha=this.hasAlpha,A.level=this.level,A.wrapU=this.wrapU,A.wrapV=this.wrapV,A},m.prototype.serialize=function(){var c=this.getScene();c&&!c.isReady()&&_.a.Warn("The scene must be ready before serializing the dynamic texture");var T=C.prototype.serialize.call(this);return this._IsCanvasElement(this._canvas)&&(T.base64String=this._canvas.toDataURL()),T.invertY=this._invertY,T.samplingMode=this.samplingMode,T},m.prototype._IsCanvasElement=function(c){return c.toDataURL!==void 0},m.prototype._rebuild=function(){this.update()},m}(x.a)},function(Me,y,f){f.d(y,"a",function(){return M});var U=f(0),_=f(9),x=f(7),u=f(16);u.a.CreateBox=function(R){var C,m=[0,1,2,0,2,3,4,5,6,4,6,7,8,9,10,8,10,11,12,13,14,12,14,15,16,17,18,16,18,19,20,21,22,20,22,23],c=[0,0,1,0,0,1,0,0,1,0,0,1,0,0,-1,0,0,-1,0,0,-1,0,0,-1,1,0,0,1,0,0,1,0,0,1,0,0,-1,0,0,-1,0,0,-1,0,0,-1,0,0,0,1,0,0,1,0,0,1,0,0,1,0,0,-1,0,0,-1,0,0,-1,0,0,-1,0],T=[],A=R.width||R.size||1,S=R.height||R.size||1,g=R.depth||R.size||1,l=R.wrap||!1,h=R.topBaseAt===void 0?1:R.topBaseAt,v=R.bottomBaseAt===void 0?0:R.bottomBaseAt,E=[2,0,3,1][h=(h+4)%4],D=[2,0,1,3][v=(v+4)%4],w=[1,-1,1,-1,-1,1,-1,1,1,1,1,1,1,1,-1,-1,1,-1,-1,-1,-1,1,-1,-1,1,1,-1,1,-1,-1,1,-1,1,1,1,1,-1,1,1,-1,-1,1,-1,-1,-1,-1,1,-1,-1,1,1,-1,1,-1,1,1,-1,1,1,1,1,-1,1,1,-1,-1,-1,-1,-1,-1,-1,1];if(l){m=[2,3,0,2,0,1,4,5,6,4,6,7,9,10,11,9,11,8,12,14,15,12,13,14],w=[-1,1,1,1,1,1,1,-1,1,-1,-1,1,1,1,-1,-1,1,-1,-1,-1,-1,1,-1,-1,1,1,1,1,1,-1,1,-1,-1,1,-1,1,-1,1,-1,-1,1,1,-1,-1,1,-1,-1,-1];for(var N=[[1,1,1],[-1,1,1],[-1,1,-1],[1,1,-1]],I=[[-1,-1,1],[1,-1,1],[1,-1,-1],[-1,-1,-1]],V=[17,18,19,16],X=[22,23,20,21];E>0;)N.unshift(N.pop()),V.unshift(V.pop()),E--;for(;D>0;)I.unshift(I.pop()),X.unshift(X.pop()),D--;N=N.flat(),I=I.flat(),w=w.concat(N).concat(I),m.push(V[0],V[2],V[3],V[0],V[1],V[2]),m.push(X[0],X[2],X[3],X[0],X[1],X[2])}var j=[A/2,S/2,g/2];C=w.reduce(function(G,Q,oe){return G.concat(Q*j[oe%3])},[]);for(var ne=R.sideOrientation===0?0:R.sideOrientation||u.a.DEFAULTSIDE,te=R.faceUV||new Array(6),de=R.faceColors,pe=[],ae=0;ae<6;ae++)te[ae]===void 0&&(te[ae]=new U.f(0,0,1,1)),de&&de[ae]===void 0&&(de[ae]=new _.b(1,1,1,1));for(var ee=0;ee<6;ee++)if(T.push(te[ee].z,te[ee].w),T.push(te[ee].x,te[ee].w),T.push(te[ee].x,te[ee].y),T.push(te[ee].z,te[ee].y),de)for(var K=0;K<4;K++)pe.push(de[ee].r,de[ee].g,de[ee].b,de[ee].a);u.a._ComputeSides(ne,C,m,c,T,R.frontUVs,R.backUVs);var $=new u.a;if($.indices=m,$.positions=C,$.normals=c,$.uvs=T,de){var L=ne===u.a.DOUBLESIDE?pe.concat(pe):pe;$.colors=L}return $},x.a.CreateBox=function(R,C,m,c,T){m===void 0&&(m=null);var A={size:C,sideOrientation:T,updatable:c};return M.CreateBox(R,A,m)};var M=function(){function R(){}return R.CreateBox=function(C,m,c){c===void 0&&(c=null);var T=new x.a(C,c);return m.sideOrientation=x.a._GetDefaultSideOrientation(m.sideOrientation),T._originalBuilderSideOrientation=m.sideOrientation,u.a.CreateBox(m).applyToMesh(T,m.updatable),T},R}()},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(0),_=function(){function x(u,M,R,C){this.normal=new U.e(u,M,R),this.d=C}return x.prototype.asArray=function(){return[this.normal.x,this.normal.y,this.normal.z,this.d]},x.prototype.clone=function(){return new x(this.normal.x,this.normal.y,this.normal.z,this.d)},x.prototype.getClassName=function(){return"Plane"},x.prototype.getHashCode=function(){var u=this.normal.getHashCode();return u=397*u^(0|this.d)},x.prototype.normalize=function(){var u=Math.sqrt(this.normal.x*this.normal.x+this.normal.y*this.normal.y+this.normal.z*this.normal.z),M=0;return u!==0&&(M=1/u),this.normal.x*=M,this.normal.y*=M,this.normal.z*=M,this.d*=M,this},x.prototype.transform=function(u){var M=x._TmpMatrix;u.invertToRef(M);var R=M.m,C=this.normal.x,m=this.normal.y,c=this.normal.z,T=this.d;return new x(C*R[0]+m*R[1]+c*R[2]+T*R[3],C*R[4]+m*R[5]+c*R[6]+T*R[7],C*R[8]+m*R[9]+c*R[10]+T*R[11],C*R[12]+m*R[13]+c*R[14]+T*R[15])},x.prototype.dotCoordinate=function(u){return this.normal.x*u.x+this.normal.y*u.y+this.normal.z*u.z+this.d},x.prototype.copyFromPoints=function(u,M,R){var C,m=M.x-u.x,c=M.y-u.y,T=M.z-u.z,A=R.x-u.x,S=R.y-u.y,g=R.z-u.z,l=c*g-T*S,h=T*A-m*g,v=m*S-c*A,E=Math.sqrt(l*l+h*h+v*v);return C=E!==0?1/E:0,this.normal.x=l*C,this.normal.y=h*C,this.normal.z=v*C,this.d=-(this.normal.x*u.x+this.normal.y*u.y+this.normal.z*u.z),this},x.prototype.isFrontFacingTo=function(u,M){return U.e.Dot(this.normal,u)<=M},x.prototype.signedDistanceTo=function(u){return U.e.Dot(u,this.normal)+this.d},x.FromArray=function(u){return new x(u[0],u[1],u[2],u[3])},x.FromPoints=function(u,M,R){var C=new x(0,0,0,0);return C.copyFromPoints(u,M,R),C},x.FromPositionAndNormal=function(u,M){var R=new x(0,0,0,0);return M.normalize(),R.normal=M,R.d=-(M.x*u.x+M.y*u.y+M.z*u.z),R},x.SignedDistanceToPlaneFromPositionAndNormal=function(u,M,R){var C=-(M.x*u.x+M.y*u.y+M.z*u.z);return U.e.Dot(R,M)+C},x._TmpMatrix=U.a.Identity(),x}()},function(Me,y,f){f.d(y,"a",function(){return m});var U=f(7),_=f(20),x=f(6),u=f(0),M=f(18),R=f(39),C=f(60),m=(f(84),function(){function c(T){this._useAlternatePickedPointAboveMaxDragAngleDragSpeed=-1.1,this.maxDragAngle=0,this._useAlternatePickedPointAboveMaxDragAngle=!1,this.currentDraggingPointerID=-1,this.dragging=!1,this.dragDeltaRatio=.2,this.updateDragPlane=!0,this._debugMode=!1,this._moving=!1,this.onDragObservable=new x.c,this.onDragStartObservable=new x.c,this.onDragEndObservable=new x.c,this.moveAttached=!0,this.enabled=!0,this.startAndReleaseDragOnPointerEvents=!0,this.detachCameraControls=!0,this.useObjectOrientationForDragging=!0,this.validateDrag=function(S){return!0},this._tmpVector=new u.e(0,0,0),this._alternatePickedPoint=new u.e(0,0,0),this._worldDragAxis=new u.e(0,0,0),this._targetPosition=new u.e(0,0,0),this._attachedToElement=!1,this._startDragRay=new R.a(new u.e,new u.e),this._lastPointerRay={},this._dragDelta=new u.e,this._pointA=new u.e(0,0,0),this._pointC=new u.e(0,0,0),this._localAxis=new u.e(0,0,0),this._lookAt=new u.e(0,0,0),this._options=T||{};var A=0;if(this._options.dragAxis&&A++,this._options.dragPlaneNormal&&A++,A>1)throw"Multiple drag modes specified in dragBehavior options. Only one expected"}return Object.defineProperty(c.prototype,"options",{get:function(){return this._options},set:function(T){this._options=T},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"name",{get:function(){return"PointerDrag"},enumerable:!1,configurable:!0}),c.prototype.init=function(){},c.prototype.attach=function(T,A){var S=this;this._scene=T.getScene(),this.attachedNode=T,c._planeScene||(this._debugMode?c._planeScene=this._scene:(c._planeScene=new _.a(this._scene.getEngine(),{virtual:!0}),c._planeScene.detachControl(),this._scene.onDisposeObservable.addOnce(function(){c._planeScene.dispose(),c._planeScene=null}))),this._dragPlane=U.a.CreatePlane("pointerDragPlane",this._debugMode?1:1e4,c._planeScene,!1,U.a.DOUBLESIDE),this.lastDragPosition=new u.e(0,0,0);var g=A||function(l){return S.attachedNode==l||l.isDescendantOf(S.attachedNode)};this._pointerObserver=this._scene.onPointerObservable.add(function(l,h){if(S.enabled){if(l.type==M.a.POINTERDOWN)S.startAndReleaseDragOnPointerEvents&&!S.dragging&&l.pickInfo&&l.pickInfo.hit&&l.pickInfo.pickedMesh&&l.pickInfo.pickedPoint&&l.pickInfo.ray&&g(l.pickInfo.pickedMesh)&&S._startDrag(l.event.pointerId,l.pickInfo.ray,l.pickInfo.pickedPoint);else if(l.type==M.a.POINTERUP)S.startAndReleaseDragOnPointerEvents&&S.currentDraggingPointerID==l.event.pointerId&&S.releaseDrag();else if(l.type==M.a.POINTERMOVE){var v=l.event.pointerId;if(S.currentDraggingPointerID===c._AnyMouseID&&v!==c._AnyMouseID){var E=l.event;(E.pointerType==="mouse"||!S._scene.getEngine().hostInformation.isMobile&&E instanceof MouseEvent)&&(S._lastPointerRay[S.currentDraggingPointerID]&&(S._lastPointerRay[v]=S._lastPointerRay[S.currentDraggingPointerID],delete S._lastPointerRay[S.currentDraggingPointerID]),S.currentDraggingPointerID=v)}S._lastPointerRay[v]||(S._lastPointerRay[v]=new R.a(new u.e,new u.e)),l.pickInfo&&l.pickInfo.ray&&(S._lastPointerRay[v].origin.copyFrom(l.pickInfo.ray.origin),S._lastPointerRay[v].direction.copyFrom(l.pickInfo.ray.direction),S.currentDraggingPointerID==v&&S.dragging&&S._moveDrag(l.pickInfo.ray))}}}),this._beforeRenderObserver=this._scene.onBeforeRenderObservable.add(function(){S._moving&&S.moveAttached&&(C.a._RemoveAndStorePivotPoint(S.attachedNode),S._targetPosition.subtractToRef(S.attachedNode.absolutePosition,S._tmpVector),S._tmpVector.scaleInPlace(S.dragDeltaRatio),S.attachedNode.getAbsolutePosition().addToRef(S._tmpVector,S._tmpVector),S.validateDrag(S._tmpVector)&&S.attachedNode.setAbsolutePosition(S._tmpVector),C.a._RestorePivotPoint(S.attachedNode))})},c.prototype.releaseDrag=function(){if(this.dragging&&(this.dragging=!1,this.onDragEndObservable.notifyObservers({dragPlanePoint:this.lastDragPosition,pointerId:this.currentDraggingPointerID})),this.currentDraggingPointerID=-1,this._moving=!1,this.detachCameraControls&&this._attachedToElement&&this._scene.activeCamera&&!this._scene.activeCamera.leftCamera){if(this._scene.activeCamera.getClassName()==="ArcRotateCamera"){var T=this._scene.activeCamera;T.attachControl(!T.inputs||T.inputs.noPreventDefault,T._useCtrlForPanning,T._panningMouseButton)}else this._scene.activeCamera.attachControl(!this._scene.activeCamera.inputs||this._scene.activeCamera.inputs.noPreventDefault);this._attachedToElement=!1}},c.prototype.startDrag=function(T,A,S){T===void 0&&(T=c._AnyMouseID),this._startDrag(T,A,S);var g=this._lastPointerRay[T];T===c._AnyMouseID&&(g=this._lastPointerRay[Object.keys(this._lastPointerRay)[0]]),g&&this._moveDrag(g)},c.prototype._startDrag=function(T,A,S){if(this._scene.activeCamera&&!this.dragging&&this.attachedNode){C.a._RemoveAndStorePivotPoint(this.attachedNode),A?(this._startDragRay.direction.copyFrom(A.direction),this._startDragRay.origin.copyFrom(A.origin)):(this._startDragRay.origin.copyFrom(this._scene.activeCamera.position),this.attachedNode.getWorldMatrix().getTranslationToRef(this._tmpVector),this._tmpVector.subtractToRef(this._scene.activeCamera.position,this._startDragRay.direction)),this._updateDragPlanePosition(this._startDragRay,S||this._tmpVector);var g=this._pickWithRayOnDragPlane(this._startDragRay);g&&(this.dragging=!0,this.currentDraggingPointerID=T,this.lastDragPosition.copyFrom(g),this.onDragStartObservable.notifyObservers({dragPlanePoint:g,pointerId:this.currentDraggingPointerID}),this._targetPosition.copyFrom(this.attachedNode.absolutePosition),this.detachCameraControls&&this._scene.activeCamera&&this._scene.activeCamera.inputs&&!this._scene.activeCamera.leftCamera&&(this._scene.activeCamera.inputs.attachedToElement?(this._scene.activeCamera.detachControl(),this._attachedToElement=!0):this._attachedToElement=!1)),C.a._RestorePivotPoint(this.attachedNode)}},c.prototype._moveDrag=function(T){this._moving=!0;var A=this._pickWithRayOnDragPlane(T);if(A){this.updateDragPlane&&this._updateDragPlanePosition(T,A);var S=0;this._options.dragAxis?(this.useObjectOrientationForDragging?u.e.TransformCoordinatesToRef(this._options.dragAxis,this.attachedNode.getWorldMatrix().getRotationMatrix(),this._worldDragAxis):this._worldDragAxis.copyFrom(this._options.dragAxis),A.subtractToRef(this.lastDragPosition,this._tmpVector),S=u.e.Dot(this._tmpVector,this._worldDragAxis),this._worldDragAxis.scaleToRef(S,this._dragDelta)):(S=this._dragDelta.length(),A.subtractToRef(this.lastDragPosition,this._dragDelta)),this._targetPosition.addInPlace(this._dragDelta),this.onDragObservable.notifyObservers({dragDistance:S,delta:this._dragDelta,dragPlanePoint:A,dragPlaneNormal:this._dragPlane.forward,pointerId:this.currentDraggingPointerID}),this.lastDragPosition.copyFrom(A)}},c.prototype._pickWithRayOnDragPlane=function(T){var A=this;if(!T)return null;var S=Math.acos(u.e.Dot(this._dragPlane.forward,T.direction));if(S>Math.PI/2&&(S=Math.PI-S),this.maxDragAngle>0&&S>this.maxDragAngle){if(this._useAlternatePickedPointAboveMaxDragAngle){this._tmpVector.copyFrom(T.direction),this.attachedNode.absolutePosition.subtractToRef(T.origin,this._alternatePickedPoint),this._alternatePickedPoint.normalize(),this._alternatePickedPoint.scaleInPlace(this._useAlternatePickedPointAboveMaxDragAngleDragSpeed*u.e.Dot(this._alternatePickedPoint,this._tmpVector)),this._tmpVector.addInPlace(this._alternatePickedPoint);var g=u.e.Dot(this._dragPlane.forward,this._tmpVector);return this._dragPlane.forward.scaleToRef(-g,this._alternatePickedPoint),this._alternatePickedPoint.addInPlace(this._tmpVector),this._alternatePickedPoint.addInPlace(this.attachedNode.absolutePosition),this._alternatePickedPoint}return null}var l=c._planeScene.pickWithRay(T,function(h){return h==A._dragPlane});return l&&l.hit&&l.pickedMesh&&l.pickedPoint?l.pickedPoint:null},c.prototype._updateDragPlanePosition=function(T,A){this._pointA.copyFrom(A),this._options.dragAxis?(this.useObjectOrientationForDragging?u.e.TransformCoordinatesToRef(this._options.dragAxis,this.attachedNode.getWorldMatrix().getRotationMatrix(),this._localAxis):this._localAxis.copyFrom(this._options.dragAxis),T.origin.subtractToRef(this._pointA,this._pointC),this._pointC.normalize(),Math.abs(u.e.Dot(this._localAxis,this._pointC))>.999?Math.abs(u.e.Dot(u.e.UpReadOnly,this._pointC))>.999?this._lookAt.copyFrom(u.e.Right()):this._lookAt.copyFrom(u.e.UpReadOnly):(u.e.CrossToRef(this._localAxis,this._pointC,this._lookAt),u.e.CrossToRef(this._localAxis,this._lookAt,this._lookAt),this._lookAt.normalize()),this._dragPlane.position.copyFrom(this._pointA),this._pointA.addToRef(this._lookAt,this._lookAt),this._dragPlane.lookAt(this._lookAt)):this._options.dragPlaneNormal?(this.useObjectOrientationForDragging?u.e.TransformCoordinatesToRef(this._options.dragPlaneNormal,this.attachedNode.getWorldMatrix().getRotationMatrix(),this._localAxis):this._localAxis.copyFrom(this._options.dragPlaneNormal),this._dragPlane.position.copyFrom(this._pointA),this._pointA.addToRef(this._localAxis,this._lookAt),this._dragPlane.lookAt(this._lookAt)):(this._dragPlane.position.copyFrom(this._pointA),this._dragPlane.lookAt(T.origin)),this._dragPlane.position.copyFrom(this.attachedNode.absolutePosition),this._dragPlane.computeWorldMatrix(!0)},c.prototype.detach=function(){this._pointerObserver&&this._scene.onPointerObservable.remove(this._pointerObserver),this._beforeRenderObserver&&this._scene.onBeforeRenderObservable.remove(this._beforeRenderObserver),this.releaseDrag()},c._AnyMouseID=-2,c}())},function(Me,y,f){f.d(y,"a",function(){return _}),f.d(y,"b",function(){return x}),f.d(y,"c",function(){return u});var U=f(1),_=function(){function M(){}return M.KEYDOWN=1,M.KEYUP=2,M}(),x=function(M,R){this.type=M,this.event=R},u=function(M){function R(C,m){var c=M.call(this,C,m)||this;return c.type=C,c.event=m,c.skipOnPointerObservable=!1,c}return Object(U.d)(R,M),R}(x)},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){this._defines={},this._currentRank=32,this._maxRank=-1,this._mesh=null}return _.prototype.unBindMesh=function(){this._mesh=null},_.prototype.addFallback=function(x,u){this._defines[x]||(x<this._currentRank&&(this._currentRank=x),x>this._maxRank&&(this._maxRank=x),this._defines[x]=new Array),this._defines[x].push(u)},_.prototype.addCPUSkinningFallback=function(x,u){this._mesh=u,x<this._currentRank&&(this._currentRank=x),x>this._maxRank&&(this._maxRank=x)},Object.defineProperty(_.prototype,"hasMoreFallbacks",{get:function(){return this._currentRank<=this._maxRank},enumerable:!1,configurable:!0}),_.prototype.reduce=function(x,u){if(this._mesh&&this._mesh.computeBonesUsingShaders&&this._mesh.numBoneInfluencers>0){this._mesh.computeBonesUsingShaders=!1,x=x.replace("#define NUM_BONE_INFLUENCERS "+this._mesh.numBoneInfluencers,"#define NUM_BONE_INFLUENCERS 0"),u._bonesComputationForcedToCPU=!0;for(var M=this._mesh.getScene(),R=0;R<M.meshes.length;R++){var C=M.meshes[R];if(C.material){if(C.computeBonesUsingShaders&&C.numBoneInfluencers!==0){if(C.material.getEffect()===u)C.computeBonesUsingShaders=!1;else if(C.subMeshes){for(var m=0,c=C.subMeshes;m<c.length;m++)if(c[m].effect===u){C.computeBonesUsingShaders=!1;break}}}}else!this._mesh.material&&C.computeBonesUsingShaders&&C.numBoneInfluencers>0&&(C.computeBonesUsingShaders=!1)}}else{var T=this._defines[this._currentRank];if(T)for(R=0;R<T.length;R++)x=x.replace("#define "+T[R],"");this._currentRank++}return x},_}()},function(Me,y,f){f.d(y,"a",function(){return M});var U=f(1),_=f(25),x=f(37),u=f(11),M=function(R){function C(m,c){var T=R.call(this,m,c,!0)||this;return c.multiMaterials.push(T),T.subMaterials=new Array,T._storeEffectOnSubMeshes=!0,T}return Object(U.d)(C,R),Object.defineProperty(C.prototype,"subMaterials",{get:function(){return this._subMaterials},set:function(m){this._subMaterials=m,this._hookArray(m)},enumerable:!1,configurable:!0}),C.prototype.getChildren=function(){return this.subMaterials},C.prototype._hookArray=function(m){var c=this,T=m.push;m.push=function(){for(var S=[],g=0;g<arguments.length;g++)S[g]=arguments[g];var l=T.apply(m,S);return c._markAllSubMeshesAsTexturesDirty(),l};var A=m.splice;m.splice=function(S,g){var l=A.apply(m,[S,g]);return c._markAllSubMeshesAsTexturesDirty(),l}},C.prototype.getSubMaterial=function(m){return m<0||m>=this.subMaterials.length?this.getScene().defaultMaterial:this.subMaterials[m]},C.prototype.getActiveTextures=function(){var m;return(m=R.prototype.getActiveTextures.call(this)).concat.apply(m,this.subMaterials.map(function(c){return c?c.getActiveTextures():[]}))},C.prototype.hasTexture=function(m){var c;if(R.prototype.hasTexture.call(this,m))return!0;for(var T=0;T<this.subMaterials.length;T++)if(!((c=this.subMaterials[T])===null||c===void 0)&&c.hasTexture(m))return!0;return!1},C.prototype.getClassName=function(){return"MultiMaterial"},C.prototype.isReadyForSubMesh=function(m,c,T){for(var A=0;A<this.subMaterials.length;A++){var S=this.subMaterials[A];if(S){if(S._storeEffectOnSubMeshes){if(!S.isReadyForSubMesh(m,c,T))return!1;continue}if(!S.isReady(m))return!1}}return!0},C.prototype.clone=function(m,c){for(var T=new C(m,this.getScene()),A=0;A<this.subMaterials.length;A++){var S=null,g=this.subMaterials[A];S=c&&g?g.clone(m+"-"+g.name):this.subMaterials[A],T.subMaterials.push(S)}return T},C.prototype.serialize=function(){var m={};m.name=this.name,m.id=this.id,x.a&&(m.tags=x.a.GetTags(this)),m.materials=[];for(var c=0;c<this.subMaterials.length;c++){var T=this.subMaterials[c];T?m.materials.push(T.id):m.materials.push(null)}return m},C.prototype.dispose=function(m,c,T){var A=this.getScene();if(A){if(T)for(var S=0;S<this.subMaterials.length;S++){var g=this.subMaterials[S];g&&g.dispose(m,c)}(S=A.multiMaterials.indexOf(this))>=0&&A.multiMaterials.splice(S,1),R.prototype.dispose.call(this,m,c)}},C.ParseMultiMaterial=function(m,c){var T=new C(m.name,c);T.id=m.id,x.a&&x.a.AddTagsTo(T,m.tags);for(var A=0;A<m.materials.length;A++){var S=m.materials[A];S?T.subMaterials.push(c.getLastMaterialByID(S)):T.subMaterials.push(null)}return T},C}(_.a);u.a.RegisteredTypes["BABYLON.MultiMaterial"]=M},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(2),_=function(){function x(){}return Object.defineProperty(x,"ForceFullSceneLoadingForIncremental",{get:function(){return x._ForceFullSceneLoadingForIncremental},set:function(u){x._ForceFullSceneLoadingForIncremental=u},enumerable:!1,configurable:!0}),Object.defineProperty(x,"ShowLoadingScreen",{get:function(){return x._ShowLoadingScreen},set:function(u){x._ShowLoadingScreen=u},enumerable:!1,configurable:!0}),Object.defineProperty(x,"loggingLevel",{get:function(){return x._loggingLevel},set:function(u){x._loggingLevel=u},enumerable:!1,configurable:!0}),Object.defineProperty(x,"CleanBoneMatrixWeights",{get:function(){return x._CleanBoneMatrixWeights},set:function(u){x._CleanBoneMatrixWeights=u},enumerable:!1,configurable:!0}),x._ForceFullSceneLoadingForIncremental=!1,x._ShowLoadingScreen=!0,x._CleanBoneMatrixWeights=!1,x._loggingLevel=U.a.SCENELOADER_NO_LOGGING,x}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.CreateCanvas=function(x,u){if(typeof document>"u")return new OffscreenCanvas(x,u);var M=document.createElement("canvas");return M.width=x,M.height=u,M},_}()},function(Me,y,f){f.d(y,"a",function(){return S});var U=f(0),_=f(9),x=f(16),u=f(4),M=f(61),R=f(69),C=f(43),m=f(2),c=f(12),T=f(37),A=f(101),S=function(){function g(l,h,v,E,D){E===void 0&&(E=!1),D===void 0&&(D=null),this.delayLoadState=m.a.DELAYLOADSTATE_NONE,this._totalVertices=0,this._isDisposed=!1,this._indexBufferIsUpdatable=!1,this._positionsCache=[],this.useBoundingInfoFromGeometry=!1,this.id=l,this.uniqueId=h.getUniqueId(),this._engine=h.getEngine(),this._meshes=[],this._scene=h,this._vertexBuffers={},this._indices=[],this._updatable=E,v?this.setAllVerticesData(v,E):(this._totalVertices=0,this._indices=[]),this._engine.getCaps().vertexArrayObject&&(this._vertexArrayObjects={}),D&&(this.applyToMesh(D),D.computeWorldMatrix(!0))}return Object.defineProperty(g.prototype,"boundingBias",{get:function(){return this._boundingBias},set:function(l){this._boundingBias?this._boundingBias.copyFrom(l):this._boundingBias=l.clone(),this._updateBoundingInfo(!0,null)},enumerable:!1,configurable:!0}),g.CreateGeometryForMesh=function(l){var h=new g(g.RandomId(),l.getScene());return h.applyToMesh(l),h},Object.defineProperty(g.prototype,"meshes",{get:function(){return this._meshes},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"extend",{get:function(){return this._extend},enumerable:!1,configurable:!0}),g.prototype.getScene=function(){return this._scene},g.prototype.getEngine=function(){return this._engine},g.prototype.isReady=function(){return this.delayLoadState===m.a.DELAYLOADSTATE_LOADED||this.delayLoadState===m.a.DELAYLOADSTATE_NONE},Object.defineProperty(g.prototype,"doNotSerialize",{get:function(){for(var l=0;l<this._meshes.length;l++)if(!this._meshes[l].doNotSerialize)return!1;return!0},enumerable:!1,configurable:!0}),g.prototype._rebuild=function(){for(var l in this._vertexArrayObjects&&(this._vertexArrayObjects={}),this._meshes.length!==0&&this._indices&&(this._indexBuffer=this._engine.createIndexBuffer(this._indices)),this._vertexBuffers)this._vertexBuffers[l]._rebuild()},g.prototype.setAllVerticesData=function(l,h){l.applyToGeometry(this,h),this.notifyUpdate()},g.prototype.setVerticesData=function(l,h,v,E){v===void 0&&(v=!1),v&&Array.isArray(h)&&(h=new Float32Array(h));var D=new u.b(this._engine,h,l,v,this._meshes.length===0,E);this.setVerticesBuffer(D)},g.prototype.removeVerticesData=function(l){this._vertexBuffers[l]&&(this._vertexBuffers[l].dispose(),delete this._vertexBuffers[l])},g.prototype.setVerticesBuffer=function(l,h){h===void 0&&(h=null);var v=l.getKind();if(this._vertexBuffers[v]&&this._vertexBuffers[v].dispose(),this._vertexBuffers[v]=l,v===u.b.PositionKind){var E=l.getData();h!=null?this._totalVertices=h:E!=null&&(this._totalVertices=E.length/(l.byteStride/4)),this._updateExtend(E),this._resetPointsArrayCache();for(var D=this._meshes,w=D.length,N=0;N<w;N++){var I=D[N];I._boundingInfo=new C.a(this._extend.minimum,this._extend.maximum),I._createGlobalSubMesh(!1),I.computeWorldMatrix(!0)}}this.notifyUpdate(v),this._vertexArrayObjects&&(this._disposeVertexArrayObjects(),this._vertexArrayObjects={})},g.prototype.updateVerticesDataDirectly=function(l,h,v,E){E===void 0&&(E=!1);var D=this.getVertexBuffer(l);D&&(D.updateDirectly(h,v,E),this.notifyUpdate(l))},g.prototype.updateVerticesData=function(l,h,v){v===void 0&&(v=!1);var E=this.getVertexBuffer(l);E&&(E.update(h),l===u.b.PositionKind&&this._updateBoundingInfo(v,h),this.notifyUpdate(l))},g.prototype._updateBoundingInfo=function(l,h){if(l&&this._updateExtend(h),this._resetPointsArrayCache(),l)for(var v=0,E=this._meshes;v<E.length;v++){var D=E[v];D._boundingInfo?D._boundingInfo.reConstruct(this._extend.minimum,this._extend.maximum):D._boundingInfo=new C.a(this._extend.minimum,this._extend.maximum);for(var w=0,N=D.subMeshes;w<N.length;w++)N[w].refreshBoundingInfo()}},g.prototype._bind=function(l,h){if(l){h===void 0&&(h=this._indexBuffer);var v=this.getVertexBuffers();v&&(h==this._indexBuffer&&this._vertexArrayObjects?(this._vertexArrayObjects[l.key]||(this._vertexArrayObjects[l.key]=this._engine.recordVertexArrayObject(v,h,l)),this._engine.bindVertexArrayObject(this._vertexArrayObjects[l.key],h)):this._engine.bindBuffers(v,h,l))}},g.prototype.getTotalVertices=function(){return this.isReady()?this._totalVertices:0},g.prototype.getVerticesData=function(l,h,v){var E=this.getVertexBuffer(l);if(!E)return null;var D=E.getData();if(!D)return null;var w=E.getSize()*u.b.GetTypeByteLength(E.type),N=this._totalVertices*E.getSize();if(E.type!==u.b.FLOAT||E.byteStride!==w){var I=[];return E.forEach(N,function(te){return I.push(te)}),I}if(!(D instanceof Array||D instanceof Float32Array)||E.byteOffset!==0||D.length!==N){if(D instanceof Array){var V=E.byteOffset/4;return c.b.Slice(D,V,V+N)}if(D instanceof ArrayBuffer)return new Float32Array(D,E.byteOffset,N);if(V=D.byteOffset+E.byteOffset,v||h&&this._meshes.length!==1){var X=new Float32Array(N),j=new Float32Array(D.buffer,V,N);return X.set(j),X}var ne=V%4;return ne&&(V=Math.max(0,V-ne)),new Float32Array(D.buffer,V,N)}return v||h&&this._meshes.length!==1?c.b.Slice(D):D},g.prototype.isVertexBufferUpdatable=function(l){var h=this._vertexBuffers[l];return!!h&&h.isUpdatable()},g.prototype.getVertexBuffer=function(l){return this.isReady()?this._vertexBuffers[l]:null},g.prototype.getVertexBuffers=function(){return this.isReady()?this._vertexBuffers:null},g.prototype.isVerticesDataPresent=function(l){return this._vertexBuffers?this._vertexBuffers[l]!==void 0:!!this._delayInfo&&this._delayInfo.indexOf(l)!==-1},g.prototype.getVerticesDataKinds=function(){var l,h=[];if(!this._vertexBuffers&&this._delayInfo)for(l in this._delayInfo)h.push(l);else for(l in this._vertexBuffers)h.push(l);return h},g.prototype.updateIndices=function(l,h,v){if(v===void 0&&(v=!1),this._indexBuffer)if(this._indexBufferIsUpdatable){var E=l.length!==this._indices.length;if(v||(this._indices=l.slice()),this._engine.updateDynamicIndexBuffer(this._indexBuffer,l,h),E)for(var D=0,w=this._meshes;D<w.length;D++)w[D]._createGlobalSubMesh(!0)}else this.setIndices(l,null,!0)},g.prototype.setIndices=function(l,h,v){h===void 0&&(h=null),v===void 0&&(v=!1),this._indexBuffer&&this._engine._releaseBuffer(this._indexBuffer),this._disposeVertexArrayObjects(),this._indices=l,this._indexBufferIsUpdatable=v,this._meshes.length!==0&&this._indices&&(this._indexBuffer=this._engine.createIndexBuffer(this._indices,v)),h!=null&&(this._totalVertices=h);for(var E=0,D=this._meshes;E<D.length;E++)D[E]._createGlobalSubMesh(!0);this.notifyUpdate()},g.prototype.getTotalIndices=function(){return this.isReady()?this._indices.length:0},g.prototype.getIndices=function(l,h){if(!this.isReady())return null;var v=this._indices;if(h||l&&this._meshes.length!==1){for(var E=v.length,D=[],w=0;w<E;w++)D.push(v[w]);return D}return v},g.prototype.getIndexBuffer=function(){return this.isReady()?this._indexBuffer:null},g.prototype._releaseVertexArrayObject=function(l){l===void 0&&(l=null),l&&this._vertexArrayObjects&&this._vertexArrayObjects[l.key]&&(this._engine.releaseVertexArrayObject(this._vertexArrayObjects[l.key]),delete this._vertexArrayObjects[l.key])},g.prototype.releaseForMesh=function(l,h){var v=this._meshes,E=v.indexOf(l);E!==-1&&(v.splice(E,1),l._geometry=null,v.length===0&&h&&this.dispose())},g.prototype.applyToMesh=function(l){if(l._geometry!==this){var h=l._geometry;h&&h.releaseForMesh(l);var v=this._meshes;l._geometry=this,this._scene.pushGeometry(this),v.push(l),this.isReady()?this._applyToMesh(l):l._boundingInfo=this._boundingInfo}},g.prototype._updateExtend=function(l){l===void 0&&(l=null),this.useBoundingInfoFromGeometry&&this._boundingInfo?this._extend={minimum:this._boundingInfo.minimum.clone(),maximum:this._boundingInfo.maximum.clone()}:(l||(l=this.getVerticesData(u.b.PositionKind)),this._extend=Object(A.a)(l,0,this._totalVertices,this.boundingBias,3))},g.prototype._applyToMesh=function(l){var h=this._meshes.length;for(var v in this._vertexBuffers){h===1&&this._vertexBuffers[v].create();var E=this._vertexBuffers[v].getBuffer();E&&(E.references=h),v===u.b.PositionKind&&(this._extend||this._updateExtend(),l._boundingInfo=new C.a(this._extend.minimum,this._extend.maximum),l._createGlobalSubMesh(!1),l._updateBoundingInfo())}h===1&&this._indices&&this._indices.length>0&&(this._indexBuffer=this._engine.createIndexBuffer(this._indices)),this._indexBuffer&&(this._indexBuffer.references=h),l._syncGeometryWithMorphTargetManager(),l.synchronizeInstances()},g.prototype.notifyUpdate=function(l){this.onGeometryUpdated&&this.onGeometryUpdated(this,l);for(var h=0,v=this._meshes;h<v.length;h++)v[h]._markSubMeshesAsAttributesDirty()},g.prototype.load=function(l,h){this.delayLoadState!==m.a.DELAYLOADSTATE_LOADING&&(this.isReady()?h&&h():(this.delayLoadState=m.a.DELAYLOADSTATE_LOADING,this._queueLoad(l,h)))},g.prototype._queueLoad=function(l,h){var v=this;this.delayLoadingFile&&(l._addPendingData(this),l._loadFile(this.delayLoadingFile,function(E){if(v._delayLoadingFunction){v._delayLoadingFunction(JSON.parse(E),v),v.delayLoadState=m.a.DELAYLOADSTATE_LOADED,v._delayInfo=[],l._removePendingData(v);for(var D=v._meshes,w=D.length,N=0;N<w;N++)v._applyToMesh(D[N]);h&&h()}},void 0,!0))},g.prototype.toLeftHanded=function(){var l=this.getIndices(!1);if(l!=null&&l.length>0){for(var h=0;h<l.length;h+=3){var v=l[h+0];l[h+0]=l[h+2],l[h+2]=v}this.setIndices(l)}var E=this.getVerticesData(u.b.PositionKind,!1);if(E!=null&&E.length>0){for(h=0;h<E.length;h+=3)E[h+2]=-E[h+2];this.setVerticesData(u.b.PositionKind,E,!1)}var D=this.getVerticesData(u.b.NormalKind,!1);if(D!=null&&D.length>0){for(h=0;h<D.length;h+=3)D[h+2]=-D[h+2];this.setVerticesData(u.b.NormalKind,D,!1)}},g.prototype._resetPointsArrayCache=function(){this._positions=null},g.prototype._generatePointsArray=function(){if(this._positions)return!0;var l=this.getVerticesData(u.b.PositionKind);if(!l||l.length===0)return!1;for(var h=3*this._positionsCache.length,v=this._positionsCache.length;h<l.length;h+=3,++v)this._positionsCache[v]=U.e.FromArray(l,h);for(h=0,v=0;h<l.length;h+=3,++v)this._positionsCache[v].set(l[0+h],l[1+h],l[2+h]);return this._positionsCache.length=l.length/3,this._positions=this._positionsCache,!0},g.prototype.isDisposed=function(){return this._isDisposed},g.prototype._disposeVertexArrayObjects=function(){if(this._vertexArrayObjects){for(var l in this._vertexArrayObjects)this._engine.releaseVertexArrayObject(this._vertexArrayObjects[l]);this._vertexArrayObjects={}}},g.prototype.dispose=function(){var l,h=this._meshes,v=h.length;for(l=0;l<v;l++)this.releaseForMesh(h[l]);for(var E in this._meshes=[],this._disposeVertexArrayObjects(),this._vertexBuffers)this._vertexBuffers[E].dispose();this._vertexBuffers={},this._totalVertices=0,this._indexBuffer&&this._engine._releaseBuffer(this._indexBuffer),this._indexBuffer=null,this._indices=[],this.delayLoadState=m.a.DELAYLOADSTATE_NONE,this.delayLoadingFile=null,this._delayLoadingFunction=null,this._delayInfo=[],this._boundingInfo=null,this._scene.removeGeometry(this),this._isDisposed=!0},g.prototype.copy=function(l){var h=new x.a;h.indices=[];var v=this.getIndices();if(v)for(var E=0;E<v.length;E++)h.indices.push(v[E]);var D,w=!1,N=!1;for(D in this._vertexBuffers){var I=this.getVerticesData(D);if(I&&(I instanceof Float32Array?h.set(new Float32Array(I),D):h.set(I.slice(0),D),!N)){var V=this.getVertexBuffer(D);V&&(N=!(w=V.isUpdatable()))}}var X=new g(l,this._scene,h,w);for(D in X.delayLoadState=this.delayLoadState,X.delayLoadingFile=this.delayLoadingFile,X._delayLoadingFunction=this._delayLoadingFunction,this._delayInfo)X._delayInfo=X._delayInfo||[],X._delayInfo.push(D);return X._boundingInfo=new C.a(this._extend.minimum,this._extend.maximum),X},g.prototype.serialize=function(){var l={};return l.id=this.id,l.updatable=this._updatable,T.a&&T.a.HasTags(this)&&(l.tags=T.a.GetTags(this)),l},g.prototype.toNumberArray=function(l){return Array.isArray(l)?l:Array.prototype.slice.call(l)},g.prototype.serializeVerticeData=function(){var l=this.serialize();return this.isVerticesDataPresent(u.b.PositionKind)&&(l.positions=this.toNumberArray(this.getVerticesData(u.b.PositionKind)),this.isVertexBufferUpdatable(u.b.PositionKind)&&(l.positions._updatable=!0)),this.isVerticesDataPresent(u.b.NormalKind)&&(l.normals=this.toNumberArray(this.getVerticesData(u.b.NormalKind)),this.isVertexBufferUpdatable(u.b.NormalKind)&&(l.normals._updatable=!0)),this.isVerticesDataPresent(u.b.TangentKind)&&(l.tangets=this.toNumberArray(this.getVerticesData(u.b.TangentKind)),this.isVertexBufferUpdatable(u.b.TangentKind)&&(l.tangets._updatable=!0)),this.isVerticesDataPresent(u.b.UVKind)&&(l.uvs=this.toNumberArray(this.getVerticesData(u.b.UVKind)),this.isVertexBufferUpdatable(u.b.UVKind)&&(l.uvs._updatable=!0)),this.isVerticesDataPresent(u.b.UV2Kind)&&(l.uv2s=this.toNumberArray(this.getVerticesData(u.b.UV2Kind)),this.isVertexBufferUpdatable(u.b.UV2Kind)&&(l.uv2s._updatable=!0)),this.isVerticesDataPresent(u.b.UV3Kind)&&(l.uv3s=this.toNumberArray(this.getVerticesData(u.b.UV3Kind)),this.isVertexBufferUpdatable(u.b.UV3Kind)&&(l.uv3s._updatable=!0)),this.isVerticesDataPresent(u.b.UV4Kind)&&(l.uv4s=this.toNumberArray(this.getVerticesData(u.b.UV4Kind)),this.isVertexBufferUpdatable(u.b.UV4Kind)&&(l.uv4s._updatable=!0)),this.isVerticesDataPresent(u.b.UV5Kind)&&(l.uv5s=this.toNumberArray(this.getVerticesData(u.b.UV5Kind)),this.isVertexBufferUpdatable(u.b.UV5Kind)&&(l.uv5s._updatable=!0)),this.isVerticesDataPresent(u.b.UV6Kind)&&(l.uv6s=this.toNumberArray(this.getVerticesData(u.b.UV6Kind)),this.isVertexBufferUpdatable(u.b.UV6Kind)&&(l.uv6s._updatable=!0)),this.isVerticesDataPresent(u.b.ColorKind)&&(l.colors=this.toNumberArray(this.getVerticesData(u.b.ColorKind)),this.isVertexBufferUpdatable(u.b.ColorKind)&&(l.colors._updatable=!0)),this.isVerticesDataPresent(u.b.MatricesIndicesKind)&&(l.matricesIndices=this.toNumberArray(this.getVerticesData(u.b.MatricesIndicesKind)),l.matricesIndices._isExpanded=!0,this.isVertexBufferUpdatable(u.b.MatricesIndicesKind)&&(l.matricesIndices._updatable=!0)),this.isVerticesDataPresent(u.b.MatricesWeightsKind)&&(l.matricesWeights=this.toNumberArray(this.getVerticesData(u.b.MatricesWeightsKind)),this.isVertexBufferUpdatable(u.b.MatricesWeightsKind)&&(l.matricesWeights._updatable=!0)),l.indices=this.toNumberArray(this.getIndices()),l},g.ExtractFromMesh=function(l,h){var v=l._geometry;return v?v.copy(h):null},g.RandomId=function(){return c.b.RandomId()},g._ImportGeometry=function(l,h){var v=h.getScene(),E=l.geometryId;if(E){var D=v.getGeometryByID(E);D&&D.applyToMesh(h)}else if(l instanceof ArrayBuffer){var w=h._binaryInfo;if(w.positionsAttrDesc&&w.positionsAttrDesc.count>0){var N=new Float32Array(l,w.positionsAttrDesc.offset,w.positionsAttrDesc.count);h.setVerticesData(u.b.PositionKind,N,!1)}if(w.normalsAttrDesc&&w.normalsAttrDesc.count>0){var I=new Float32Array(l,w.normalsAttrDesc.offset,w.normalsAttrDesc.count);h.setVerticesData(u.b.NormalKind,I,!1)}if(w.tangetsAttrDesc&&w.tangetsAttrDesc.count>0){var V=new Float32Array(l,w.tangetsAttrDesc.offset,w.tangetsAttrDesc.count);h.setVerticesData(u.b.TangentKind,V,!1)}if(w.uvsAttrDesc&&w.uvsAttrDesc.count>0){var X=new Float32Array(l,w.uvsAttrDesc.offset,w.uvsAttrDesc.count);h.setVerticesData(u.b.UVKind,X,!1)}if(w.uvs2AttrDesc&&w.uvs2AttrDesc.count>0){var j=new Float32Array(l,w.uvs2AttrDesc.offset,w.uvs2AttrDesc.count);h.setVerticesData(u.b.UV2Kind,j,!1)}if(w.uvs3AttrDesc&&w.uvs3AttrDesc.count>0){var ne=new Float32Array(l,w.uvs3AttrDesc.offset,w.uvs3AttrDesc.count);h.setVerticesData(u.b.UV3Kind,ne,!1)}if(w.uvs4AttrDesc&&w.uvs4AttrDesc.count>0){var te=new Float32Array(l,w.uvs4AttrDesc.offset,w.uvs4AttrDesc.count);h.setVerticesData(u.b.UV4Kind,te,!1)}if(w.uvs5AttrDesc&&w.uvs5AttrDesc.count>0){var de=new Float32Array(l,w.uvs5AttrDesc.offset,w.uvs5AttrDesc.count);h.setVerticesData(u.b.UV5Kind,de,!1)}if(w.uvs6AttrDesc&&w.uvs6AttrDesc.count>0){var pe=new Float32Array(l,w.uvs6AttrDesc.offset,w.uvs6AttrDesc.count);h.setVerticesData(u.b.UV6Kind,pe,!1)}if(w.colorsAttrDesc&&w.colorsAttrDesc.count>0){var ae=new Float32Array(l,w.colorsAttrDesc.offset,w.colorsAttrDesc.count);h.setVerticesData(u.b.ColorKind,ae,!1,w.colorsAttrDesc.stride)}if(w.matricesIndicesAttrDesc&&w.matricesIndicesAttrDesc.count>0){for(var ee=new Int32Array(l,w.matricesIndicesAttrDesc.offset,w.matricesIndicesAttrDesc.count),K=[],$=0;$<ee.length;$++){var L=ee[$];K.push(255&L),K.push((65280&L)>>8),K.push((16711680&L)>>16),K.push(L>>24&255)}h.setVerticesData(u.b.MatricesIndicesKind,K,!1)}if(w.matricesIndicesExtraAttrDesc&&w.matricesIndicesExtraAttrDesc.count>0){for(ee=new Int32Array(l,w.matricesIndicesExtraAttrDesc.offset,w.matricesIndicesExtraAttrDesc.count),K=[],$=0;$<ee.length;$++)L=ee[$],K.push(255&L),K.push((65280&L)>>8),K.push((16711680&L)>>16),K.push(L>>24&255);h.setVerticesData(u.b.MatricesIndicesExtraKind,K,!1)}if(w.matricesWeightsAttrDesc&&w.matricesWeightsAttrDesc.count>0){var G=new Float32Array(l,w.matricesWeightsAttrDesc.offset,w.matricesWeightsAttrDesc.count);h.setVerticesData(u.b.MatricesWeightsKind,G,!1)}if(w.indicesAttrDesc&&w.indicesAttrDesc.count>0){var Q=new Int32Array(l,w.indicesAttrDesc.offset,w.indicesAttrDesc.count);h.setIndices(Q,null)}if(w.subMeshesAttrDesc&&w.subMeshesAttrDesc.count>0){var oe=new Int32Array(l,w.subMeshesAttrDesc.offset,5*w.subMeshesAttrDesc.count);for(h.subMeshes=[],$=0;$<w.subMeshesAttrDesc.count;$++){var re=oe[5*$+0],Y=oe[5*$+1],k=oe[5*$+2],H=oe[5*$+3],Z=oe[5*$+4];M.a.AddToMesh(re,Y,k,H,Z,h)}}}else if(l.positions&&l.normals&&l.indices){if(h.setVerticesData(u.b.PositionKind,l.positions,l.positions._updatable),h.setVerticesData(u.b.NormalKind,l.normals,l.normals._updatable),l.tangents&&h.setVerticesData(u.b.TangentKind,l.tangents,l.tangents._updatable),l.uvs&&h.setVerticesData(u.b.UVKind,l.uvs,l.uvs._updatable),l.uvs2&&h.setVerticesData(u.b.UV2Kind,l.uvs2,l.uvs2._updatable),l.uvs3&&h.setVerticesData(u.b.UV3Kind,l.uvs3,l.uvs3._updatable),l.uvs4&&h.setVerticesData(u.b.UV4Kind,l.uvs4,l.uvs4._updatable),l.uvs5&&h.setVerticesData(u.b.UV5Kind,l.uvs5,l.uvs5._updatable),l.uvs6&&h.setVerticesData(u.b.UV6Kind,l.uvs6,l.uvs6._updatable),l.colors&&h.setVerticesData(u.b.ColorKind,_.b.CheckColors4(l.colors,l.positions.length/3),l.colors._updatable),l.matricesIndices)if(l.matricesIndices._isExpanded)delete l.matricesIndices._isExpanded,h.setVerticesData(u.b.MatricesIndicesKind,l.matricesIndices,l.matricesIndices._updatable);else{for(K=[],$=0;$<l.matricesIndices.length;$++){var W=l.matricesIndices[$];K.push(255&W),K.push((65280&W)>>8),K.push((16711680&W)>>16),K.push(W>>24&255)}h.setVerticesData(u.b.MatricesIndicesKind,K,l.matricesIndices._updatable)}if(l.matricesIndicesExtra)if(l.matricesIndicesExtra._isExpanded)delete l.matricesIndices._isExpanded,h.setVerticesData(u.b.MatricesIndicesExtraKind,l.matricesIndicesExtra,l.matricesIndicesExtra._updatable);else{for(K=[],$=0;$<l.matricesIndicesExtra.length;$++)W=l.matricesIndicesExtra[$],K.push(255&W),K.push((65280&W)>>8),K.push((16711680&W)>>16),K.push(W>>24&255);h.setVerticesData(u.b.MatricesIndicesExtraKind,K,l.matricesIndicesExtra._updatable)}l.matricesWeights&&(g._CleanMatricesWeights(l,h),h.setVerticesData(u.b.MatricesWeightsKind,l.matricesWeights,l.matricesWeights._updatable)),l.matricesWeightsExtra&&h.setVerticesData(u.b.MatricesWeightsExtraKind,l.matricesWeightsExtra,l.matricesWeights._updatable),h.setIndices(l.indices,null)}if(l.subMeshes){h.subMeshes=[];for(var q=0;q<l.subMeshes.length;q++){var he=l.subMeshes[q];M.a.AddToMesh(he.materialIndex,he.verticesStart,he.verticesCount,he.indexStart,he.indexCount,h)}}h._shouldGenerateFlatShading&&(h.convertToFlatShadedMesh(),h._shouldGenerateFlatShading=!1),h.computeWorldMatrix(!0),v.onMeshImportedObservable.notifyObservers(h)},g._CleanMatricesWeights=function(l,h){if(R.a.CleanBoneMatrixWeights){var v=0;if(l.skeletonId>-1){var E=h.getScene().getLastSkeletonByID(l.skeletonId);if(E){v=E.bones.length;for(var D=h.getVerticesData(u.b.MatricesIndicesKind),w=h.getVerticesData(u.b.MatricesIndicesExtraKind),N=l.matricesWeights,I=l.matricesWeightsExtra,V=l.numBoneInfluencer,X=N.length,j=0;j<X;j+=4){for(var ne=0,te=-1,de=0;de<4;de++)ne+=pe=N[j+de],pe<.001&&te<0&&(te=de);if(I)for(de=0;de<4;de++){var pe;ne+=pe=I[j+de],pe<.001&&te<0&&(te=de+4)}if((te<0||te>V-1)&&(te=V-1),ne>.001){var ae=1/ne;for(de=0;de<4;de++)N[j+de]*=ae;if(I)for(de=0;de<4;de++)I[j+de]*=ae}else te>=4?(I[j+te-4]=1-ne,w[j+te-4]=v):(N[j+te]=1-ne,D[j+te]=v)}h.setVerticesData(u.b.MatricesIndicesKind,D),l.matricesWeightsExtra&&h.setVerticesData(u.b.MatricesIndicesExtraKind,w)}}}},g.Parse=function(l,h,v){if(h.getGeometryByID(l.id))return null;var E=new g(l.id,h,void 0,l.updatable);return T.a&&T.a.AddTagsTo(E,l.tags),l.delayLoadingFile?(E.delayLoadState=m.a.DELAYLOADSTATE_NOTLOADED,E.delayLoadingFile=v+l.delayLoadingFile,E._boundingInfo=new C.a(U.e.FromArray(l.boundingBoxMinimum),U.e.FromArray(l.boundingBoxMaximum)),E._delayInfo=[],l.hasUVs&&E._delayInfo.push(u.b.UVKind),l.hasUVs2&&E._delayInfo.push(u.b.UV2Kind),l.hasUVs3&&E._delayInfo.push(u.b.UV3Kind),l.hasUVs4&&E._delayInfo.push(u.b.UV4Kind),l.hasUVs5&&E._delayInfo.push(u.b.UV5Kind),l.hasUVs6&&E._delayInfo.push(u.b.UV6Kind),l.hasColors&&E._delayInfo.push(u.b.ColorKind),l.hasMatricesIndices&&E._delayInfo.push(u.b.MatricesIndicesKind),l.hasMatricesWeights&&E._delayInfo.push(u.b.MatricesWeightsKind),E._delayLoadingFunction=x.a.ImportVertexData):x.a.ImportVertexData(l,E),h.pushGeometry(E,!0),E},g}()},function(Me,y,f){f.d(y,"e",function(){return U}),f.d(y,"c",function(){return M}),f.d(y,"a",function(){return R}),f.d(y,"b",function(){return C}),f.d(y,"f",function(){return m}),f.d(y,"g",function(){return c}),f.d(y,"d",function(){return T});var U,_=f(14),x=f(0),u=f(28);(function(A){A[A.CW=0]="CW",A[A.CCW=1]="CCW"})(U||(U={}));var M=function(){function A(){}return A.Interpolate=function(S,g,l,h,v){for(var E=1-3*h+3*g,D=3*h-6*g,w=3*g,N=S,I=0;I<5;I++){var V=N*N;N-=(E*(V*N)+D*V+w*N-S)*(1/(3*E*V+2*D*N+w)),N=Math.min(1,Math.max(0,N))}return 3*Math.pow(1-N,2)*N*l+3*(1-N)*Math.pow(N,2)*v+Math.pow(N,3)},A}(),R=function(){function A(S){this._radians=S,this._radians<0&&(this._radians+=2*Math.PI)}return A.prototype.degrees=function(){return 180*this._radians/Math.PI},A.prototype.radians=function(){return this._radians},A.BetweenTwoPoints=function(S,g){var l=g.subtract(S);return new A(Math.atan2(l.y,l.x))},A.FromRadians=function(S){return new A(S)},A.FromDegrees=function(S){return new A(S*Math.PI/180)},A}(),C=function(A,S,g){this.startPoint=A,this.midPoint=S,this.endPoint=g;var l=Math.pow(S.x,2)+Math.pow(S.y,2),h=(Math.pow(A.x,2)+Math.pow(A.y,2)-l)/2,v=(l-Math.pow(g.x,2)-Math.pow(g.y,2))/2,E=(A.x-S.x)*(S.y-g.y)-(S.x-g.x)*(A.y-S.y);this.centerPoint=new x.d((h*(S.y-g.y)-v*(A.y-S.y))/E,((A.x-S.x)*v-(S.x-g.x)*h)/E),this.radius=this.centerPoint.subtract(this.startPoint).length(),this.startAngle=R.BetweenTwoPoints(this.centerPoint,this.startPoint);var D=this.startAngle.degrees(),w=R.BetweenTwoPoints(this.centerPoint,this.midPoint).degrees(),N=R.BetweenTwoPoints(this.centerPoint,this.endPoint).degrees();w-D>180&&(w-=360),w-D<-180&&(w+=360),N-w>180&&(N-=360),N-w<-180&&(N+=360),this.orientation=w-D<0?U.CW:U.CCW,this.angle=R.FromDegrees(this.orientation===U.CW?D-N:N-D)},m=function(){function A(S,g){this._points=new Array,this._length=0,this.closed=!1,this._points.push(new x.d(S,g))}return A.prototype.addLineTo=function(S,g){if(this.closed)return this;var l=new x.d(S,g),h=this._points[this._points.length-1];return this._points.push(l),this._length+=l.subtract(h).length(),this},A.prototype.addArcTo=function(S,g,l,h,v){if(v===void 0&&(v=36),this.closed)return this;var E=this._points[this._points.length-1],D=new x.d(S,g),w=new x.d(l,h),N=new C(E,D,w),I=N.angle.radians()/v;N.orientation===U.CW&&(I*=-1);for(var V=N.startAngle.radians()+I,X=0;X<v;X++){var j=Math.cos(V)*N.radius+N.centerPoint.x,ne=Math.sin(V)*N.radius+N.centerPoint.y;this.addLineTo(j,ne),V+=I}return this},A.prototype.close=function(){return this.closed=!0,this},A.prototype.length=function(){var S=this._length;if(this.closed){var g=this._points[this._points.length-1];S+=this._points[0].subtract(g).length()}return S},A.prototype.getPoints=function(){return this._points},A.prototype.getPointAtLengthPosition=function(S){if(S<0||S>1)return x.d.Zero();for(var g=S*this.length(),l=0,h=0;h<this._points.length;h++){var v=(h+1)%this._points.length,E=this._points[h],D=this._points[v].subtract(E),w=D.length()+l;if(g>=l&&g<=w){var N=D.normalize(),I=g-l;return new x.d(E.x+N.x*I,E.y+N.y*I)}l=w}return x.d.Zero()},A.StartingAt=function(S,g){return new A(S,g)},A}(),c=function(){function A(S,g,l,h){g===void 0&&(g=null),h===void 0&&(h=!1),this.path=S,this._curve=new Array,this._distances=new Array,this._tangents=new Array,this._normals=new Array,this._binormals=new Array,this._pointAtData={id:0,point:x.e.Zero(),previousPointArrayIndex:0,position:0,subPosition:0,interpolateReady:!1,interpolationMatrix:x.a.Identity()};for(var v=0;v<S.length;v++)this._curve[v]=S[v].clone();this._raw=l||!1,this._alignTangentsWithPath=h,this._compute(g,h)}return A.prototype.getCurve=function(){return this._curve},A.prototype.getPoints=function(){return this._curve},A.prototype.length=function(){return this._distances[this._distances.length-1]},A.prototype.getTangents=function(){return this._tangents},A.prototype.getNormals=function(){return this._normals},A.prototype.getBinormals=function(){return this._binormals},A.prototype.getDistances=function(){return this._distances},A.prototype.getPointAt=function(S){return this._updatePointAtData(S).point},A.prototype.getTangentAt=function(S,g){return g===void 0&&(g=!1),this._updatePointAtData(S,g),g?x.e.TransformCoordinates(x.e.Forward(),this._pointAtData.interpolationMatrix):this._tangents[this._pointAtData.previousPointArrayIndex]},A.prototype.getNormalAt=function(S,g){return g===void 0&&(g=!1),this._updatePointAtData(S,g),g?x.e.TransformCoordinates(x.e.Right(),this._pointAtData.interpolationMatrix):this._normals[this._pointAtData.previousPointArrayIndex]},A.prototype.getBinormalAt=function(S,g){return g===void 0&&(g=!1),this._updatePointAtData(S,g),g?x.e.TransformCoordinates(x.e.UpReadOnly,this._pointAtData.interpolationMatrix):this._binormals[this._pointAtData.previousPointArrayIndex]},A.prototype.getDistanceAt=function(S){return this.length()*S},A.prototype.getPreviousPointIndexAt=function(S){return this._updatePointAtData(S),this._pointAtData.previousPointArrayIndex},A.prototype.getSubPositionAt=function(S){return this._updatePointAtData(S),this._pointAtData.subPosition},A.prototype.getClosestPositionTo=function(S){for(var g=Number.MAX_VALUE,l=0,h=0;h<this._curve.length-1;h++){var v=this._curve[h+0],E=this._curve[h+1].subtract(v).normalize(),D=this._distances[h+1]-this._distances[h+0],w=Math.min(Math.max(x.e.Dot(E,S.subtract(v).normalize()),0)*x.e.Distance(v,S)/D,1),N=x.e.Distance(v.add(E.scale(w*D)),S);N<g&&(g=N,l=(this._distances[h+0]+D*w)/this.length())}return l},A.prototype.slice=function(S,g){if(S===void 0&&(S=0),g===void 0&&(g=1),S<0&&(S=1- -1*S%1),g<0&&(g=1- -1*g%1),S>g){var l=S;S=g,g=l}var h=this.getCurve(),v=this.getPointAt(S),E=this.getPreviousPointIndexAt(S),D=this.getPointAt(g),w=this.getPreviousPointIndexAt(g)+1,N=[];return S!==0&&(E++,N.push(v)),N.push.apply(N,h.slice(E,w)),g===1&&S!==1||N.push(D),new A(N,this.getNormalAt(S),this._raw,this._alignTangentsWithPath)},A.prototype.update=function(S,g,l){g===void 0&&(g=null),l===void 0&&(l=!1);for(var h=0;h<S.length;h++)this._curve[h].x=S[h].x,this._curve[h].y=S[h].y,this._curve[h].z=S[h].z;return this._compute(g,l),this},A.prototype._compute=function(S,g){g===void 0&&(g=!1);var l=this._curve.length;if(!(l<2)){this._tangents[0]=this._getFirstNonNullVector(0),this._raw||this._tangents[0].normalize(),this._tangents[l-1]=this._curve[l-1].subtract(this._curve[l-2]),this._raw||this._tangents[l-1].normalize();var h,v,E,D,w,N=this._tangents[0],I=this._normalVector(N,S);this._normals[0]=I,this._raw||this._normals[0].normalize(),this._binormals[0]=x.e.Cross(N,this._normals[0]),this._raw||this._binormals[0].normalize(),this._distances[0]=0;for(var V=1;V<l;V++)h=this._getLastNonNullVector(V),V<l-1&&(v=this._getFirstNonNullVector(V),this._tangents[V]=g?v:h.add(v),this._tangents[V].normalize()),this._distances[V]=this._distances[V-1]+this._curve[V].subtract(this._curve[V-1]).length(),E=this._tangents[V],w=this._binormals[V-1],this._normals[V]=x.e.Cross(w,E),this._raw||(this._normals[V].length()===0?(D=this._normals[V-1],this._normals[V]=D.clone()):this._normals[V].normalize()),this._binormals[V]=x.e.Cross(E,this._normals[V]),this._raw||this._binormals[V].normalize();this._pointAtData.id=NaN}},A.prototype._getFirstNonNullVector=function(S){for(var g=1,l=this._curve[S+g].subtract(this._curve[S]);l.length()===0&&S+g+1<this._curve.length;)g++,l=this._curve[S+g].subtract(this._curve[S]);return l},A.prototype._getLastNonNullVector=function(S){for(var g=1,l=this._curve[S].subtract(this._curve[S-g]);l.length()===0&&S>g+1;)g++,l=this._curve[S].subtract(this._curve[S-g]);return l},A.prototype._normalVector=function(S,g){var l,h,v=S.length();return v===0&&(v=1),g==null?(h=_.a.WithinEpsilon(Math.abs(S.y)/v,1,u.a)?_.a.WithinEpsilon(Math.abs(S.x)/v,1,u.a)?_.a.WithinEpsilon(Math.abs(S.z)/v,1,u.a)?x.e.Zero():new x.e(0,0,1):new x.e(1,0,0):new x.e(0,-1,0),l=x.e.Cross(S,h)):(l=x.e.Cross(S,g),x.e.CrossToRef(l,S,l)),l.normalize(),l},A.prototype._updatePointAtData=function(S,g){if(g===void 0&&(g=!1),this._pointAtData.id===S)return this._pointAtData.interpolateReady||this._updateInterpolationMatrix(),this._pointAtData;this._pointAtData.id=S;var l=this.getPoints();if(S<=0)return this._setPointAtData(0,0,l[0],0,g);if(S>=1)return this._setPointAtData(1,1,l[l.length-1],l.length-1,g);for(var h,v=l[0],E=0,D=S*this.length(),w=1;w<l.length;w++){h=l[w];var N=x.e.Distance(v,h);if((E+=N)===D)return this._setPointAtData(S,1,h,w,g);if(E>D){var I=(E-D)/N,V=v.subtract(h),X=h.add(V.scaleInPlace(I));return this._setPointAtData(S,1-I,X,w-1,g)}v=h}return this._pointAtData},A.prototype._setPointAtData=function(S,g,l,h,v){return this._pointAtData.point=l,this._pointAtData.position=S,this._pointAtData.subPosition=g,this._pointAtData.previousPointArrayIndex=h,this._pointAtData.interpolateReady=v,v&&this._updateInterpolationMatrix(),this._pointAtData},A.prototype._updateInterpolationMatrix=function(){this._pointAtData.interpolationMatrix=x.a.Identity();var S=this._pointAtData.previousPointArrayIndex;if(S!==this._tangents.length-1){var g=S+1,l=this._tangents[S].clone(),h=this._normals[S].clone(),v=this._binormals[S].clone(),E=this._tangents[g].clone(),D=this._normals[g].clone(),w=this._binormals[g].clone(),N=x.b.RotationQuaternionFromAxis(h,v,l),I=x.b.RotationQuaternionFromAxis(D,w,E);x.b.Slerp(N,I,this._pointAtData.subPosition).toRotationMatrix(this._pointAtData.interpolationMatrix)}},A}(),T=function(){function A(S){this._length=0,this._points=S,this._length=this._computeLength(S)}return A.CreateQuadraticBezier=function(S,g,l,h){h=h>2?h:3;for(var v=new Array,E=function(w,N,I,V){return(1-w)*(1-w)*N+2*w*(1-w)*I+w*w*V},D=0;D<=h;D++)v.push(new x.e(E(D/h,S.x,g.x,l.x),E(D/h,S.y,g.y,l.y),E(D/h,S.z,g.z,l.z)));return new A(v)},A.CreateCubicBezier=function(S,g,l,h,v){v=v>3?v:4;for(var E=new Array,D=function(N,I,V,X,j){return(1-N)*(1-N)*(1-N)*I+3*N*(1-N)*(1-N)*V+3*N*N*(1-N)*X+N*N*N*j},w=0;w<=v;w++)E.push(new x.e(D(w/v,S.x,g.x,l.x,h.x),D(w/v,S.y,g.y,l.y,h.y),D(w/v,S.z,g.z,l.z,h.z)));return new A(E)},A.CreateHermiteSpline=function(S,g,l,h,v){for(var E=new Array,D=1/v,w=0;w<=v;w++)E.push(x.e.Hermite(S,g,l,h,w*D));return new A(E)},A.CreateCatmullRomSpline=function(S,g,l){var h=new Array,v=1/g,E=0;if(l){for(var D=S.length,w=0;w<D;w++){E=0;for(var N=0;N<g;N++)h.push(x.e.CatmullRom(S[w%D],S[(w+1)%D],S[(w+2)%D],S[(w+3)%D],E)),E+=v}h.push(h[0])}else{var I=new Array;for(I.push(S[0].clone()),Array.prototype.push.apply(I,S),I.push(S[S.length-1].clone()),w=0;w<I.length-3;w++)for(E=0,N=0;N<g;N++)h.push(x.e.CatmullRom(I[w],I[w+1],I[w+2],I[w+3],E)),E+=v;w--,h.push(x.e.CatmullRom(I[w],I[w+1],I[w+2],I[w+3],E))}return new A(h)},A.prototype.getPoints=function(){return this._points},A.prototype.length=function(){return this._length},A.prototype.continue=function(S){for(var g=this._points[this._points.length-1],l=this._points.slice(),h=S.getPoints(),v=1;v<h.length;v++)l.push(h[v].subtract(h[0]).add(g));return new A(l)},A.prototype._computeLength=function(S){for(var g=0,l=1;l<S.length;l++)g+=S[l].subtract(S[l-1]).length();return g},A}()},function(Me,y,f){f.d(y,"a",function(){return l});var U=f(1),_=f(3),x=f(0),u=f(4),M=f(10),R=f(15),C=f(25),m=f(11),c=f(9),T=f(67),A=f(49),S=f(13),g={effect:null,subMesh:null},l=function(h){function v(E,D,w,N){N===void 0&&(N={});var I=h.call(this,E,D)||this;return I._textures={},I._textureArrays={},I._floats={},I._ints={},I._floatsArrays={},I._colors3={},I._colors3Arrays={},I._colors4={},I._colors4Arrays={},I._vectors2={},I._vectors3={},I._vectors4={},I._matrices={},I._matrixArrays={},I._matrices3x3={},I._matrices2x2={},I._vectors2Arrays={},I._vectors3Arrays={},I._vectors4Arrays={},I._cachedWorldViewMatrix=new x.a,I._cachedWorldViewProjectionMatrix=new x.a,I._multiview=!1,I._shaderPath=w,I._options=Object(U.a)({needAlphaBlending:!1,needAlphaTesting:!1,attributes:["position","normal","uv"],uniforms:["worldViewProjection"],uniformBuffers:[],samplers:[],defines:[]},N),I}return Object(U.d)(v,h),Object.defineProperty(v.prototype,"shaderPath",{get:function(){return this._shaderPath},set:function(E){this._shaderPath=E},enumerable:!1,configurable:!0}),Object.defineProperty(v.prototype,"options",{get:function(){return this._options},enumerable:!1,configurable:!0}),v.prototype.getClassName=function(){return"ShaderMaterial"},v.prototype.needAlphaBlending=function(){return this.alpha<1||this._options.needAlphaBlending},v.prototype.needAlphaTesting=function(){return this._options.needAlphaTesting},v.prototype._checkUniform=function(E){this._options.uniforms.indexOf(E)===-1&&this._options.uniforms.push(E)},v.prototype.setTexture=function(E,D){return this._options.samplers.indexOf(E)===-1&&this._options.samplers.push(E),this._textures[E]=D,this},v.prototype.setTextureArray=function(E,D){return this._options.samplers.indexOf(E)===-1&&this._options.samplers.push(E),this._checkUniform(E),this._textureArrays[E]=D,this},v.prototype.setFloat=function(E,D){return this._checkUniform(E),this._floats[E]=D,this},v.prototype.setInt=function(E,D){return this._checkUniform(E),this._ints[E]=D,this},v.prototype.setFloats=function(E,D){return this._checkUniform(E),this._floatsArrays[E]=D,this},v.prototype.setColor3=function(E,D){return this._checkUniform(E),this._colors3[E]=D,this},v.prototype.setColor3Array=function(E,D){return this._checkUniform(E),this._colors3Arrays[E]=D.reduce(function(w,N){return N.toArray(w,w.length),w},[]),this},v.prototype.setColor4=function(E,D){return this._checkUniform(E),this._colors4[E]=D,this},v.prototype.setColor4Array=function(E,D){return this._checkUniform(E),this._colors4Arrays[E]=D.reduce(function(w,N){return N.toArray(w,w.length),w},[]),this},v.prototype.setVector2=function(E,D){return this._checkUniform(E),this._vectors2[E]=D,this},v.prototype.setVector3=function(E,D){return this._checkUniform(E),this._vectors3[E]=D,this},v.prototype.setVector4=function(E,D){return this._checkUniform(E),this._vectors4[E]=D,this},v.prototype.setMatrix=function(E,D){return this._checkUniform(E),this._matrices[E]=D,this},v.prototype.setMatrices=function(E,D){this._checkUniform(E);for(var w=new Float32Array(16*D.length),N=0;N<D.length;N++)D[N].copyToArray(w,16*N);return this._matrixArrays[E]=w,this},v.prototype.setMatrix3x3=function(E,D){return this._checkUniform(E),this._matrices3x3[E]=D,this},v.prototype.setMatrix2x2=function(E,D){return this._checkUniform(E),this._matrices2x2[E]=D,this},v.prototype.setArray2=function(E,D){return this._checkUniform(E),this._vectors2Arrays[E]=D,this},v.prototype.setArray3=function(E,D){return this._checkUniform(E),this._vectors3Arrays[E]=D,this},v.prototype.setArray4=function(E,D){return this._checkUniform(E),this._vectors4Arrays[E]=D,this},v.prototype._checkCache=function(E,D){return!E||!this._effect||this._effect.defines.indexOf("#define INSTANCES")!==-1===D},v.prototype.isReadyForSubMesh=function(E,D,w){return this.isReady(E,w)},v.prototype.isReady=function(E,D){var w,N;if(this._effect&&this.isFrozen&&this._effect._wasPreviouslyReady)return!0;var I=this.getScene(),V=I.getEngine();if(!this.checkReadyOnEveryCall&&this._renderId===I.getRenderId()&&this._checkCache(E,D))return!0;var X=[],j=[],ne=new T.a;V.getCaps().multiview&&I.activeCamera&&I.activeCamera.outputRenderTarget&&I.activeCamera.outputRenderTarget.getViewCount()>1&&(this._multiview=!0,X.push("#define MULTIVIEW"),this._options.uniforms.indexOf("viewProjection")!==-1&&this._options.uniforms.push("viewProjectionR")===-1&&this._options.uniforms.push("viewProjectionR"));for(var te=0;te<this._options.defines.length;te++)X.push(this._options.defines[te]);for(te=0;te<this._options.attributes.length;te++)j.push(this._options.attributes[te]);E&&E.isVerticesDataPresent(u.b.ColorKind)&&(j.push(u.b.ColorKind),X.push("#define VERTEXCOLOR")),D&&(X.push("#define INSTANCES"),R.a.PushAttributesForInstances(j),E?.hasThinInstances&&X.push("#define THIN_INSTANCES"));var de=0;if(E&&E.useBones&&E.computeBonesUsingShaders&&E.skeleton){j.push(u.b.MatricesIndicesKind),j.push(u.b.MatricesWeightsKind),E.numBoneInfluencers>4&&(j.push(u.b.MatricesIndicesExtraKind),j.push(u.b.MatricesWeightsExtraKind));var pe=E.skeleton;de=E.numBoneInfluencers,X.push("#define NUM_BONE_INFLUENCERS "+de),ne.addCPUSkinningFallback(0,E),pe.isUsingTextureForMatrices?(X.push("#define BONETEXTURE"),this._options.uniforms.indexOf("boneTextureWidth")===-1&&this._options.uniforms.push("boneTextureWidth"),this._options.samplers.indexOf("boneSampler")===-1&&this._options.samplers.push("boneSampler")):(X.push("#define BonesPerMesh "+(pe.bones.length+1)),this._options.uniforms.indexOf("mBones")===-1&&this._options.uniforms.push("mBones"))}else X.push("#define NUM_BONE_INFLUENCERS 0");for(var ae in this._textures)if(!this._textures[ae].isReady())return!1;E&&this._shouldTurnAlphaTestOn(E)&&X.push("#define ALPHATEST");var ee=this._shaderPath,K=this._options.uniforms,$=this._options.uniformBuffers,L=this._options.samplers;this.customShaderNameResolve&&(K=K.slice(),$=$.slice(),L=L.slice(),ee=this.customShaderNameResolve(ee,K,$,L,X,j));var G=this._effect,Q=X.join(`
-`);return this._cachedDefines!==Q&&(this._cachedDefines=Q,this._effect=V.createEffect(ee,{attributes:j,uniformsNames:K,uniformBuffersNames:$,samplers:L,defines:Q,fallbacks:ne,onCompiled:this.onCompiled,onError:this.onError,indexParameters:{maxSimultaneousMorphTargets:de}},V),this._onEffectCreatedObservable&&(g.effect=this._effect,this._onEffectCreatedObservable.notifyObservers(g))),(N=!(!((w=this._effect)===null||w===void 0)&&w.isReady()))!==null&&N!==void 0&&!N&&(G!==this._effect&&I.resetCachedMaterial(),this._renderId=I.getRenderId(),this._effect._wasPreviouslyReady=!0,!0)},v.prototype.bindOnlyWorldMatrix=function(E,D){var w=this.getScene(),N=D??this._effect;N&&(this._options.uniforms.indexOf("world")!==-1&&N.setMatrix("world",E),this._options.uniforms.indexOf("worldView")!==-1&&(E.multiplyToRef(w.getViewMatrix(),this._cachedWorldViewMatrix),N.setMatrix("worldView",this._cachedWorldViewMatrix)),this._options.uniforms.indexOf("worldViewProjection")!==-1&&(E.multiplyToRef(w.getTransformMatrix(),this._cachedWorldViewProjectionMatrix),N.setMatrix("worldViewProjection",this._cachedWorldViewProjectionMatrix)))},v.prototype.bindForSubMesh=function(E,D,w){this.bind(E,D,w._effectOverride)},v.prototype.bind=function(E,D,w){this.bindOnlyWorldMatrix(E,w);var N=w??this._effect;if(N&&this.getScene().getCachedMaterial()!==this){var I;for(I in this._options.uniforms.indexOf("view")!==-1&&N.setMatrix("view",this.getScene().getViewMatrix()),this._options.uniforms.indexOf("projection")!==-1&&N.setMatrix("projection",this.getScene().getProjectionMatrix()),this._options.uniforms.indexOf("viewProjection")!==-1&&(N.setMatrix("viewProjection",this.getScene().getTransformMatrix()),this._multiview&&N.setMatrix("viewProjectionR",this.getScene()._transformMatrixR)),this.getScene().activeCamera&&this._options.uniforms.indexOf("cameraPosition")!==-1&&N.setVector3("cameraPosition",this.getScene().activeCamera.globalPosition),R.a.BindBonesParameters(D,N),this._textures)N.setTexture(I,this._textures[I]);for(I in this._textureArrays)N.setTextureArray(I,this._textureArrays[I]);for(I in this._ints)N.setInt(I,this._ints[I]);for(I in this._floats)N.setFloat(I,this._floats[I]);for(I in this._floatsArrays)N.setArray(I,this._floatsArrays[I]);for(I in this._colors3)N.setColor3(I,this._colors3[I]);for(I in this._colors3Arrays)N.setArray3(I,this._colors3Arrays[I]);for(I in this._colors4){var V=this._colors4[I];N.setFloat4(I,V.r,V.g,V.b,V.a)}for(I in this._colors4Arrays)N.setArray4(I,this._colors4Arrays[I]);for(I in this._vectors2)N.setVector2(I,this._vectors2[I]);for(I in this._vectors3)N.setVector3(I,this._vectors3[I]);for(I in this._vectors4)N.setVector4(I,this._vectors4[I]);for(I in this._matrices)N.setMatrix(I,this._matrices[I]);for(I in this._matrixArrays)N.setMatrices(I,this._matrixArrays[I]);for(I in this._matrices3x3)N.setMatrix3x3(I,this._matrices3x3[I]);for(I in this._matrices2x2)N.setMatrix2x2(I,this._matrices2x2[I]);for(I in this._vectors2Arrays)N.setArray2(I,this._vectors2Arrays[I]);for(I in this._vectors3Arrays)N.setArray3(I,this._vectors3Arrays[I]);for(I in this._vectors4Arrays)N.setArray4(I,this._vectors4Arrays[I])}var X=this._effect;this._effect=N,this._afterBind(D),this._effect=X},v.prototype._afterBind=function(E){h.prototype._afterBind.call(this,E),this.getScene()._cachedEffect=this._effect},v.prototype.getActiveTextures=function(){var E=h.prototype.getActiveTextures.call(this);for(var D in this._textures)E.push(this._textures[D]);for(var D in this._textureArrays)for(var w=this._textureArrays[D],N=0;N<w.length;N++)E.push(w[N]);return E},v.prototype.hasTexture=function(E){if(h.prototype.hasTexture.call(this,E))return!0;for(var D in this._textures)if(this._textures[D]===E)return!0;for(var D in this._textureArrays)for(var w=this._textureArrays[D],N=0;N<w.length;N++)if(w[N]===E)return!0;return!1},v.prototype.clone=function(E){var D=this,w=_.a.Clone(function(){return new v(E,D.getScene(),D._shaderPath,D._options)},this);for(var N in w.name=E,w.id=E,typeof w._shaderPath=="object"&&(w._shaderPath=Object(U.a)({},w._shaderPath)),this._options=Object(U.a)({},this._options),Object.keys(this._options).forEach(function(I){var V=D._options[I];Array.isArray(V)&&(D._options[I]=V.slice(0))}),this._textures)w.setTexture(N,this._textures[N]);for(var N in this._floats)w.setFloat(N,this._floats[N]);for(var N in this._floatsArrays)w.setFloats(N,this._floatsArrays[N]);for(var N in this._colors3)w.setColor3(N,this._colors3[N]);for(var N in this._colors4)w.setColor4(N,this._colors4[N]);for(var N in this._vectors2)w.setVector2(N,this._vectors2[N]);for(var N in this._vectors3)w.setVector3(N,this._vectors3[N]);for(var N in this._vectors4)w.setVector4(N,this._vectors4[N]);for(var N in this._matrices)w.setMatrix(N,this._matrices[N]);for(var N in this._matrices3x3)w.setMatrix3x3(N,this._matrices3x3[N]);for(var N in this._matrices2x2)w.setMatrix2x2(N,this._matrices2x2[N]);return w},v.prototype.dispose=function(E,D,w){if(D){var N;for(N in this._textures)this._textures[N].dispose();for(N in this._textureArrays)for(var I=this._textureArrays[N],V=0;V<I.length;V++)I[V].dispose()}this._textures={},h.prototype.dispose.call(this,E,D,w)},v.prototype.serialize=function(){var E,D=_.a.Serialize(this);for(E in D.customType="BABYLON.ShaderMaterial",D.options=this._options,D.shaderPath=this._shaderPath,D.textures={},this._textures)D.textures[E]=this._textures[E].serialize();for(E in D.textureArrays={},this._textureArrays){D.textureArrays[E]=[];for(var w=this._textureArrays[E],N=0;N<w.length;N++)D.textureArrays[E].push(w[N].serialize())}for(E in D.floats={},this._floats)D.floats[E]=this._floats[E];for(E in D.FloatArrays={},this._floatsArrays)D.FloatArrays[E]=this._floatsArrays[E];for(E in D.colors3={},this._colors3)D.colors3[E]=this._colors3[E].asArray();for(E in D.colors3Arrays={},this._colors3Arrays)D.colors3Arrays[E]=this._colors3Arrays[E];for(E in D.colors4={},this._colors4)D.colors4[E]=this._colors4[E].asArray();for(E in D.colors4Arrays={},this._colors4Arrays)D.colors4Arrays[E]=this._colors4Arrays[E];for(E in D.vectors2={},this._vectors2)D.vectors2[E]=this._vectors2[E].asArray();for(E in D.vectors3={},this._vectors3)D.vectors3[E]=this._vectors3[E].asArray();for(E in D.vectors4={},this._vectors4)D.vectors4[E]=this._vectors4[E].asArray();for(E in D.matrices={},this._matrices)D.matrices[E]=this._matrices[E].asArray();for(E in D.matrixArray={},this._matrixArrays)D.matrixArray[E]=this._matrixArrays[E];for(E in D.matrices3x3={},this._matrices3x3)D.matrices3x3[E]=this._matrices3x3[E];for(E in D.matrices2x2={},this._matrices2x2)D.matrices2x2[E]=this._matrices2x2[E];for(E in D.vectors2Arrays={},this._vectors2Arrays)D.vectors2Arrays[E]=this._vectors2Arrays[E];for(E in D.vectors3Arrays={},this._vectors3Arrays)D.vectors3Arrays[E]=this._vectors3Arrays[E];for(E in D.vectors4Arrays={},this._vectors4Arrays)D.vectors4Arrays[E]=this._vectors4Arrays[E];return D},v.Parse=function(E,D,w){var N,I=_.a.Parse(function(){return new v(E.name,D,E.shaderPath,E.options)},E,D,w);for(N in E.textures)I.setTexture(N,M.a.Parse(E.textures[N],D,w));for(N in E.textureArrays){for(var V=E.textureArrays[N],X=new Array,j=0;j<V.length;j++)X.push(M.a.Parse(V[j],D,w));I.setTextureArray(N,X)}for(N in E.floats)I.setFloat(N,E.floats[N]);for(N in E.floatsArrays)I.setFloats(N,E.floatsArrays[N]);for(N in E.colors3)I.setColor3(N,c.a.FromArray(E.colors3[N]));for(N in E.colors3Arrays){var ne=E.colors3Arrays[N].reduce(function(te,de,pe){return pe%3==0?te.push([de]):te[te.length-1].push(de),te},[]).map(function(te){return c.a.FromArray(te)});I.setColor3Array(N,ne)}for(N in E.colors4)I.setColor4(N,c.b.FromArray(E.colors4[N]));for(N in E.colors4Arrays)ne=E.colors4Arrays[N].reduce(function(te,de,pe){return pe%4==0?te.push([de]):te[te.length-1].push(de),te},[]).map(function(te){return c.b.FromArray(te)}),I.setColor4Array(N,ne);for(N in E.vectors2)I.setVector2(N,x.d.FromArray(E.vectors2[N]));for(N in E.vectors3)I.setVector3(N,x.e.FromArray(E.vectors3[N]));for(N in E.vectors4)I.setVector4(N,x.f.FromArray(E.vectors4[N]));for(N in E.matrices)I.setMatrix(N,x.a.FromArray(E.matrices[N]));for(N in E.matrixArray)I._matrixArrays[N]=new Float32Array(E.matrixArray[N]);for(N in E.matrices3x3)I.setMatrix3x3(N,E.matrices3x3[N]);for(N in E.matrices2x2)I.setMatrix2x2(N,E.matrices2x2[N]);for(N in E.vectors2Arrays)I.setArray2(N,E.vectors2Arrays[N]);for(N in E.vectors3Arrays)I.setArray3(N,E.vectors3Arrays[N]);for(N in E.vectors4Arrays)I.setArray4(N,E.vectors4Arrays[N]);return I},v.ParseFromFileAsync=function(E,D,w,N){var I=this;return N===void 0&&(N=""),new Promise(function(V,X){var j=new A.a;j.addEventListener("readystatechange",function(){if(j.readyState==4)if(j.status==200){var ne=JSON.parse(j.responseText),te=I.Parse(ne,w||S.a.LastCreatedScene,N);E&&(te.name=E),V(te)}else X("Unable to load the ShaderMaterial")}),j.open("GET",D),j.send()})},v.CreateFromSnippetAsync=function(E,D,w){var 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Object.defineProperty(x.prototype,"useUbo",{get:function(){return!this._noUBO},enumerable:!1,configurable:!0}),Object.defineProperty(x.prototype,"isSync",{get:function(){return!this._needSync},enumerable:!1,configurable:!0}),x.prototype.isDynamic=function(){return this._dynamic!==void 0},x.prototype.getData=function(){return this._bufferData},x.prototype.getBuffer=function(){return this._buffer},x.prototype._fillAlignment=function(u){var M;if(M=u<=2?u:4,this._uniformLocationPointer%M!=0){var R=this._uniformLocationPointer;this._uniformLocationPointer+=M-this._uniformLocationPointer%M;for(var C=this._uniformLocationPointer-R,m=0;m<C;m++)this._data.push(0)}},x.prototype.addUniform=function(u,M){if(!this._noUBO&&this._uniformLocations[u]===void 0){var R;if(M instanceof Array)M=(R=M).length;else{M=M,R=[];for(var C=0;C<M;C++)R.push(0)}for(this._fillAlignment(M),this._uniformSizes[u]=M,this._uniformLocations[u]=this._uniformLocationPointer,this._uniformLocationPointer+=M,C=0;C<M;C++)this._data.push(R[C]);this._needSync=!0}},x.prototype.addMatrix=function(u,M){this.addUniform(u,Array.prototype.slice.call(M.toArray()))},x.prototype.addFloat2=function(u,M,R){var C=[M,R];this.addUniform(u,C)},x.prototype.addFloat3=function(u,M,R,C){var m=[M,R,C];this.addUniform(u,m)},x.prototype.addColor3=function(u,M){var R=new Array;M.toArray(R),this.addUniform(u,R)},x.prototype.addColor4=function(u,M,R){var C=new Array;M.toArray(C),C.push(R),this.addUniform(u,C)},x.prototype.addVector3=function(u,M){var R=new Array;M.toArray(R),this.addUniform(u,R)},x.prototype.addMatrix3x3=function(u){this.addUniform(u,12)},x.prototype.addMatrix2x2=function(u){this.addUniform(u,8)},x.prototype.create=function(){this._noUBO||this._buffer||(this._fillAlignment(4),this._bufferData=new 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null},c.prototype.transferToEffect=function(T,A){var S=x.e.Normalize(this.direction);return this._uniformBuffer.updateFloat4("vLightData",S.x,S.y,S.z,0,A),this._uniformBuffer.updateColor3("vLightGround",this.groundColor.scale(this.intensity),A),this},c.prototype.transferToNodeMaterialEffect=function(T,A){var S=x.e.Normalize(this.direction);return T.setFloat3(A,S.x,S.y,S.z),this},c.prototype.computeWorldMatrix=function(){return this._worldMatrix||(this._worldMatrix=x.a.Identity()),this._worldMatrix},c.prototype.getTypeID=function(){return R.a.LIGHTTYPEID_HEMISPHERICLIGHT},c.prototype.prepareLightSpecificDefines=function(T,A){T["HEMILIGHT"+A]=!0},Object(U.c)([Object(_.e)()],c.prototype,"groundColor",void 0),Object(U.c)([Object(_.o)()],c.prototype,"direction",void 0),c}(R.a)},function(Me,y,f){f.d(y,"a",function(){return x});var U=f(1),_=f(0),x=function(u){function M(R,C){var m=u.call(this,R,C)||this;return m._normalMatrix=new _.a,m._storeEffectOnSubMeshes=!0,m}return Object(U.d)(M,u),M.prototype.getEffect=function(){return this._activeEffect},M.prototype.isReady=function(R,C){return!!R&&(!R.subMeshes||R.subMeshes.length===0||this.isReadyForSubMesh(R,R.subMeshes[0],C))},M.prototype._isReadyForSubMesh=function(R){var C=R._materialDefines;return!(this.checkReadyOnEveryCall||!R.effect||!C||C._renderId!==this.getScene().getRenderId())},M.prototype.bindOnlyWorldMatrix=function(R){this._activeEffect.setMatrix("world",R)},M.prototype.bindOnlyNormalMatrix=function(R){this._activeEffect.setMatrix("normalMatrix",R)},M.prototype.bind=function(R,C){C&&this.bindForSubMesh(R,C,C.subMeshes[0])},M.prototype._afterBind=function(R,C){C===void 0&&(C=null),u.prototype._afterBind.call(this,R),this.getScene()._cachedEffect=C},M.prototype._mustRebind=function(R,C,m){return m===void 0&&(m=1),R.isCachedMaterialInvalid(this,C,m)},M}(f(25).a)},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(1),_=function(x){function u(M){var R=x.call(this)||this;return R._buffer=M,R}return Object(U.d)(u,x),Object.defineProperty(u.prototype,"underlyingResource",{get:function(){return this._buffer},enumerable:!1,configurable:!0}),u}(f(89).a)},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){this.references=0,this.capacity=0,this.is32Bits=!1}return Object.defineProperty(_.prototype,"underlyingResource",{get:function(){return null},enumerable:!1,configurable:!0}),_}()},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(64),_=function(){function x(){}return x.GetPlanes=function(u){for(var M=[],R=0;R<6;R++)M.push(new U.a(0,0,0,0));return x.GetPlanesToRef(u,M),M},x.GetNearPlaneToRef=function(u,M){var R=u.m;M.normal.x=R[3]+R[2],M.normal.y=R[7]+R[6],M.normal.z=R[11]+R[10],M.d=R[15]+R[14],M.normalize()},x.GetFarPlaneToRef=function(u,M){var R=u.m;M.normal.x=R[3]-R[2],M.normal.y=R[7]-R[6],M.normal.z=R[11]-R[10],M.d=R[15]-R[14],M.normalize()},x.GetLeftPlaneToRef=function(u,M){var R=u.m;M.normal.x=R[3]+R[0],M.normal.y=R[7]+R[4],M.normal.z=R[11]+R[8],M.d=R[15]+R[12],M.normalize()},x.GetRightPlaneToRef=function(u,M){var R=u.m;M.normal.x=R[3]-R[0],M.normal.y=R[7]-R[4],M.normal.z=R[11]-R[8],M.d=R[15]-R[12],M.normalize()},x.GetTopPlaneToRef=function(u,M){var R=u.m;M.normal.x=R[3]-R[1],M.normal.y=R[7]-R[5],M.normal.z=R[11]-R[9],M.d=R[15]-R[13],M.normalize()},x.GetBottomPlaneToRef=function(u,M){var R=u.m;M.normal.x=R[3]+R[1],M.normal.y=R[7]+R[5],M.normal.z=R[11]+R[9],M.d=R[15]+R[13],M.normalize()},x.GetPlanesToRef=function(u,M){x.GetNearPlaneToRef(u,M[0]),x.GetFarPlaneToRef(u,M[1]),x.GetLeftPlaneToRef(u,M[2]),x.GetRightPlaneToRef(u,M[3]),x.GetTopPlaneToRef(u,M[4]),x.GetBottomPlaneToRef(u,M[5])},x}()},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(2),_=function(){function x(){this.hoverCursor="",this.actions=new Array,this.isRecursive=!1}return Object.defineProperty(x,"HasTriggers",{get:function(){for(var u in x.Triggers)if(x.Triggers.hasOwnProperty(u))return!0;return!1},enumerable:!1,configurable:!0}),Object.defineProperty(x,"HasPickTriggers",{get:function(){for(var u in x.Triggers)if(x.Triggers.hasOwnProperty(u)){var M=parseInt(u);if(M>=U.a.ACTION_OnPickTrigger&&M<=U.a.ACTION_OnPickUpTrigger)return!0}return!1},enumerable:!1,configurable:!0}),x.HasSpecificTrigger=function(u){for(var M in x.Triggers)if(x.Triggers.hasOwnProperty(M)&&parseInt(M)===u)return!0;return!1},x.Triggers={},x}()},function(Me,y,f){f.d(y,"a",function(){return R});var U=f(1),_=f(25),x=f(3),u=f(19),M=f(15),R=function(){function C(m){this._texture=null,this.diffuseBlendLevel=1,this.roughnessBlendLevel=1,this.bumpLevel=1,this._normalBlendMethod=_.a.MATERIAL_NORMALBLENDMETHOD_WHITEOUT,this._isEnabled=!1,this.isEnabled=!1,this._internalMarkAllSubMeshesAsTexturesDirty=m}return C.prototype._markAllSubMeshesAsTexturesDirty=function(){this._internalMarkAllSubMeshesAsTexturesDirty()},C.prototype.isReadyForSubMesh=function(m,c){var T=c.getEngine();return!(m._areTexturesDirty&&c.texturesEnabled&&T.getCaps().standardDerivatives&&this._texture&&u.a.DetailTextureEnabled&&!this._texture.isReady())},C.prototype.prepareDefines=function(m,c){if(this._isEnabled){m.DETAIL_NORMALBLENDMETHOD=this._normalBlendMethod;var T=c.getEngine();m._areTexturesDirty&&(T.getCaps().standardDerivatives&&this._texture&&u.a.DetailTextureEnabled&&this._isEnabled?(M.a.PrepareDefinesForMergedUV(this._texture,m,"DETAIL"),m.DETAIL_NORMALBLENDMETHOD=this._normalBlendMethod):m.DETAIL=!1)}else m.DETAIL=!1},C.prototype.bindForSubMesh=function(m,c,T){this._isEnabled&&(m.useUbo&&T&&m.isSync||this._texture&&u.a.DetailTextureEnabled&&(m.updateFloat4("vDetailInfos",this._texture.coordinatesIndex,this.diffuseBlendLevel,this.bumpLevel,this.roughnessBlendLevel),M.a.BindTextureMatrix(this._texture,m,"detail")),c.texturesEnabled&&this._texture&&u.a.DetailTextureEnabled&&m.setTexture("detailSampler",this._texture))},C.prototype.hasTexture=function(m){return this._texture===m},C.prototype.getActiveTextures=function(m){this._texture&&m.push(this._texture)},C.prototype.getAnimatables=function(m){this._texture&&this._texture.animations&&this._texture.animations.length>0&&m.push(this._texture)},C.prototype.dispose=function(m){var c;m&&((c=this._texture)===null||c===void 0||c.dispose())},C.prototype.getClassName=function(){return"DetailMap"},C.AddUniforms=function(m){m.push("vDetailInfos")},C.AddSamplers=function(m){m.push("detailSampler")},C.PrepareUniformBuffer=function(m){m.addUniform("vDetailInfos",4),m.addUniform("detailMatrix",16)},C.prototype.copyTo=function(m){x.a.Clone(function(){return m},this)},C.prototype.serialize=function(){return x.a.Serialize(this)},C.prototype.parse=function(m,c,T){var A=this;x.a.Parse(function(){return A},m,c,T)},Object(U.c)([Object(x.m)("detailTexture"),Object(x.b)("_markAllSubMeshesAsTexturesDirty")],C.prototype,"texture",void 0),Object(U.c)([Object(x.c)()],C.prototype,"diffuseBlendLevel",void 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-#ifdef MORPHTARGETS_NORMAL
-attribute vec3 normal{X};
-#endif
-#ifdef MORPHTARGETS_TANGENT
-attribute vec3 tangent{X};
-#endif
-#ifdef MORPHTARGETS_UV
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R=this._renderingGroups[M];R&&R.dispose()}},u.prototype._prepareRenderingGroup=function(M){this._renderingGroups[M]===void 0&&(this._renderingGroups[M]=new U.a(M,this._scene,this._customOpaqueSortCompareFn[M],this._customAlphaTestSortCompareFn[M],this._customTransparentSortCompareFn[M]))},u.prototype.dispatchSprites=function(M){var R=M.renderingGroupId||0;this._prepareRenderingGroup(R),this._renderingGroups[R].dispatchSprites(M)},u.prototype.dispatchParticles=function(M){var R=M.renderingGroupId||0;this._prepareRenderingGroup(R),this._renderingGroups[R].dispatchParticles(M)},u.prototype.dispatch=function(M,R,C){R===void 0&&(R=M.getMesh());var m=R.renderingGroupId||0;this._prepareRenderingGroup(m),this._renderingGroups[m].dispatch(M,R,C)},u.prototype.setRenderingOrder=function(M,R,C,m){if(R===void 0&&(R=null),C===void 0&&(C=null),m===void 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0},l=m.ribbonCloseArray||!1,h=m.ribbonClosePath||!1,v=m.cap===0?0:m.cap||_.a.NO_CAP,E=m.updatable,D=_.a._GetDefaultSideOrientation(m.sideOrientation),w=m.instance,N=m.invertUV||!1;return R._ExtrudeShapeGeneric(C,A,T,null,null,S,g,l,h,v,!0,c,!!E,D,w||null,N,m.frontUVs||null,m.backUVs||null)},R._ExtrudeShapeGeneric=function(C,m,c,T,A,S,g,l,h,v,E,D,w,N,I,V,X,j){var ne,te,de=function(ee,K,$,L,G,Q,oe,re,Y,k){for(var H=$.getTangents(),Z=$.getNormals(),W=$.getBinormals(),q=$.getDistances(),he=0,ge=k&&re?re:function(){return Q!==null?Q:0},me=k&&oe?oe:function(){return G!==null?G:1},_e=Y===_.a.NO_CAP||Y===_.a.CAP_END?0:2,be=U.c.Matrix[0],Pe=0;Pe<K.length;Pe++){for(var ye=new Array,Be=ge(Pe,q[Pe]),ke=me(Pe,q[Pe]),We=0;We<ee.length;We++){U.a.RotationAxisToRef(H[Pe],he,be);var je=H[Pe].scale(ee[We].z).add(Z[Pe].scale(ee[We].x)).add(W[Pe].scale(ee[We].y)),He=ye[We]?ye[We]:U.e.Zero();U.e.TransformCoordinatesToRef(je,be,He),He.scaleInPlace(ke).addInPlace(K[Pe]),ye[We]=He}L[_e]=ye,he+=Be,_e++}var 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U=f(1),_=f(9),x=f(4),u=f(7),M=f(151),R=f(25),C=f(73),m=f(15),c=(f(166),f(167),function(A){function S(g,l,h,v,E,D,w){l===void 0&&(l=null),h===void 0&&(h=null),v===void 0&&(v=null);var N=A.call(this,g,l,h,v,E)||this;N.useVertexColor=D,N.useVertexAlpha=w,N.color=new _.a(1,1,1),N.alpha=1,v&&(N.color=v.color.clone(),N.alpha=v.alpha,N.useVertexColor=v.useVertexColor,N.useVertexAlpha=v.useVertexAlpha),N.intersectionThreshold=.1;var I={attributes:[x.b.PositionKind,"world0","world1","world2","world3"],uniforms:["vClipPlane","vClipPlane2","vClipPlane3","vClipPlane4","vClipPlane5","vClipPlane6","world","viewProjection"],needAlphaBlending:!0,defines:[]};return w===!1&&(I.needAlphaBlending=!1),D?(I.defines.push("#define VERTEXCOLOR"),I.attributes.push(x.b.ColorKind)):(I.uniforms.push("color"),N.color4=new _.b),N._colorShader=new C.a("colorShader",N.getScene(),"color",I),N}return Object(U.d)(S,A),S.prototype._addClipPlaneDefine=function(g){var l="#define 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g.clipPlane?this._addClipPlaneDefine("CLIPPLANE"):this._removeClipPlaneDefine("CLIPPLANE"),g.clipPlane2?this._addClipPlaneDefine("CLIPPLANE2"):this._removeClipPlaneDefine("CLIPPLANE2"),g.clipPlane3?this._addClipPlaneDefine("CLIPPLANE3"):this._removeClipPlaneDefine("CLIPPLANE3"),g.clipPlane4?this._addClipPlaneDefine("CLIPPLANE4"):this._removeClipPlaneDefine("CLIPPLANE4"),g.clipPlane5?this._addClipPlaneDefine("CLIPPLANE5"):this._removeClipPlaneDefine("CLIPPLANE5"),g.clipPlane6?this._addClipPlaneDefine("CLIPPLANE6"):this._removeClipPlaneDefine("CLIPPLANE6"),!!this._colorShader.isReady(this)&&A.prototype.isReady.call(this)},S.prototype.getClassName=function(){return"LinesMesh"},Object.defineProperty(S.prototype,"material",{get:function(){return this._colorShader},set:function(g){},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"checkCollisions",{get:function(){return!1},enumerable:!1,configurable:!0}),S.prototype._bind=function(g,l,h){if(!this._geometry)return this;var v=this._colorShader.getEffect(),E=this.isUnIndexed?null:this._geometry.getIndexBuffer();if(this._geometry._bind(v,E),!this.useVertexColor){var D=this.color,w=D.r,N=D.g,I=D.b;this.color4.set(w,N,I,this.alpha),this._colorShader.setColor4("color",this.color4)}return m.a.BindClipPlane(v,this.getScene()),this},S.prototype._draw=function(g,l,h){if(!this._geometry||!this._geometry.getVertexBuffers()||!this._unIndexed&&!this._geometry.getIndexBuffer())return this;var v=this.getScene().getEngine();return this._unIndexed?v.drawArraysType(R.a.LineListDrawMode,g.verticesStart,g.verticesCount,h):v.drawElementsType(R.a.LineListDrawMode,g.indexStart,g.indexCount,h),this},S.prototype.dispose=function(g){this._colorShader.dispose(!1,!1,!0),A.prototype.dispose.call(this,g)},S.prototype.clone=function(g,l,h){return l===void 0&&(l=null),new S(g,this.getScene(),l,this,h)},S.prototype.createInstance=function(g){return new T(g,this)},S}(u.a)),T=function(A){function S(g,l){var h=A.call(this,g,l)||this;return 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x.a("",L);Z.disableLighting=!0,Z.emissiveColor=M.a.Blue().scale(.5),Y=u.a._CreateArrow(L,Z)}this._xAxis=oe,this._xAxis.scaling.setAll(this.scaleLines*this._scaleLinesFactor),this._yAxis=re,this._yAxis.scaling.setAll(this.scaleLines*this._scaleLinesFactor),this._zAxis=Y,this._zAxis.scaling.setAll(this.scaleLines*this._scaleLinesFactor),Q!=null&&($._SetRenderingGroupId(this._xAxis,Q),$._SetRenderingGroupId(this._yAxis,Q),$._SetRenderingGroupId(this._zAxis,Q)),this.scene=L,this.update(new _.e,_.e.Right(),_.e.Up(),_.e.Forward())}return Object.defineProperty($.prototype,"xAxis",{get:function(){return this._xAxis},enumerable:!1,configurable:!0}),Object.defineProperty($.prototype,"yAxis",{get:function(){return this._yAxis},enumerable:!1,configurable:!0}),Object.defineProperty($.prototype,"zAxis",{get:function(){return this._zAxis},enumerable:!1,configurable:!0}),$.prototype.update=function(L,G,Q,oe){this._xAxis.position.copyFrom(L),this._xAxis.setDirection(G),this._xAxis.scaling.setAll(this.scaleLines*this._scaleLinesFactor),this._yAxis.position.copyFrom(L),this._yAxis.setDirection(Q),this._yAxis.scaling.setAll(this.scaleLines*this._scaleLinesFactor),this._zAxis.position.copyFrom(L),this._zAxis.setDirection(oe),this._zAxis.scaling.setAll(this.scaleLines*this._scaleLinesFactor)},$.prototype.createInstance=function(){var L=u.a._CreateArrowInstance(this.scene,this._xAxis),G=u.a._CreateArrowInstance(this.scene,this._yAxis),Q=u.a._CreateArrowInstance(this.scene,this._zAxis),oe=new $(this.scene,this.scaleLines,null,L,G,Q);return 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G._createInspector(L),Q(G)})},$.InspectorURL="https://unpkg.com/babylonjs-inspector@"+g.a.Version+"/babylon.inspector.bundle.js",$}(),h=f(7),v=f(63),E=f(45),D=f(22),w=f(32),N=f(36),I=f(53),V=function(){function $(L){this._impostors=[],this._meshes=[],this._numMeshes=0,this._debugMeshMeshes=new Array,this._scene=L||D.a.LastCreatedScene;var G=this._scene.getPhysicsEngine();G&&(this._physicsEnginePlugin=G.getPhysicsPlugin()),this._utilityLayer=new N.a(this._scene,!1),this._utilityLayer.pickUtilitySceneFirst=!1,this._utilityLayer.utilityLayerScene.autoClearDepthAndStencil=!0}return $.prototype._updateDebugMeshes=function(){for(var L=this._physicsEnginePlugin,G=0;G<this._numMeshes;G++){var Q=this._impostors[G];if(Q)if(Q.isDisposed)this.hideImpostor(this._impostors[G--]);else{if(Q.type===w.a.MeshImpostor)continue;var oe=this._meshes[G];oe&&L&&L.syncMeshWithImpostor(oe,Q)}}},$.prototype.showImpostor=function(L,G){if(!this._scene)return null;for(var Q=0;Q<this._numMeshes;Q++)if(this._impostors[Q]==L)return null;var oe=this._getDebugMesh(L,G);return oe&&(this._impostors[this._numMeshes]=L,this._meshes[this._numMeshes]=oe,this._numMeshes===0&&(this._renderFunction=this._updateDebugMeshes.bind(this),this._scene.registerBeforeRender(this._renderFunction)),this._numMeshes++),oe},$.prototype.hideImpostor=function(L){if(L&&this._scene&&this._utilityLayer){for(var G=!1,Q=this._utilityLayer.utilityLayerScene,oe=0;oe<this._numMeshes;oe++)if(this._impostors[oe]==L){var re=this._meshes[oe];if(!re)continue;Q.removeMesh(re),re.dispose();var Y=this._debugMeshMeshes.indexOf(re);Y>-1&&this._debugMeshMeshes.splice(Y,1),this._numMeshes--,this._numMeshes>0?(this._meshes[oe]=this._meshes[this._numMeshes],this._impostors[oe]=this._impostors[this._numMeshes],this._meshes[this._numMeshes]=null,this._impostors[this._numMeshes]=null):(this._meshes[0]=null,this._impostors[0]=null),G=!0;break}G&&this._numMeshes===0&&this._scene.unregisterBeforeRender(this._renderFunction)}},$.prototype._getDebugMaterial=function(L){return this._debugMaterial||(this._debugMaterial=new x.a("",L),this._debugMaterial.wireframe=!0,this._debugMaterial.emissiveColor=M.a.White(),this._debugMaterial.disableLighting=!0),this._debugMaterial},$.prototype._getDebugBoxMesh=function(L){return this._debugBoxMesh||(this._debugBoxMesh=v.a.CreateBox("physicsBodyBoxViewMesh",{size:1},L),this._debugBoxMesh.rotationQuaternion=_.b.Identity(),this._debugBoxMesh.material=this._getDebugMaterial(L),this._debugBoxMesh.setEnabled(!1)),this._debugBoxMesh.createInstance("physicsBodyBoxViewInstance")},$.prototype._getDebugSphereMesh=function(L){return this._debugSphereMesh||(this._debugSphereMesh=E.a.CreateSphere("physicsBodySphereViewMesh",{diameter:1},L),this._debugSphereMesh.rotationQuaternion=_.b.Identity(),this._debugSphereMesh.material=this._getDebugMaterial(L),this._debugSphereMesh.setEnabled(!1)),this._debugSphereMesh.createInstance("physicsBodyBoxViewInstance")},$.prototype._getDebugCylinderMesh=function(L){return this._debugCylinderMesh||(this._debugCylinderMesh=I.a.CreateCylinder("physicsBodyCylinderViewMesh",{diameterTop:1,diameterBottom:1,height:1},L),this._debugCylinderMesh.rotationQuaternion=_.b.Identity(),this._debugCylinderMesh.material=this._getDebugMaterial(L),this._debugCylinderMesh.setEnabled(!1)),this._debugCylinderMesh.createInstance("physicsBodyBoxViewInstance")},$.prototype._getDebugMeshMesh=function(L,G){var Q=new h.a(L.name,G,null,L);return Q.position=_.e.Zero(),Q.setParent(L),Q.material=this._getDebugMaterial(G),this._debugMeshMeshes.push(Q),Q},$.prototype._getDebugMesh=function(L,G){var Q=this;if(!this._utilityLayer||G&&G.parent&&G.parent.physicsImpostor)return null;var oe=null,re=this._utilityLayer.utilityLayerScene;switch(L.type){case w.a.BoxImpostor:oe=this._getDebugBoxMesh(re),L.getBoxSizeToRef(oe.scaling);break;case w.a.SphereImpostor:oe=this._getDebugSphereMesh(re);var Y=L.getRadius();oe.scaling.x=2*Y,oe.scaling.y=2*Y,oe.scaling.z=2*Y;break;case w.a.MeshImpostor:G&&(oe=this._getDebugMeshMesh(G,re));break;case w.a.NoImpostor:G&&G.getChildMeshes().filter(function(H){return H.physicsImpostor?1:0}).forEach(function(H){Q._getDebugBoxMesh(re).parent=H});break;case w.a.CylinderImpostor:oe=this._getDebugCylinderMesh(re);var k=L.object.getBoundingInfo();oe.scaling.x=k.boundingBox.maximum.x-k.boundingBox.minimum.x,oe.scaling.y=k.boundingBox.maximum.y-k.boundingBox.minimum.y,oe.scaling.z=k.boundingBox.maximum.z-k.boundingBox.minimum.z}return oe},$.prototype.dispose=function(){for(var L=this._numMeshes,G=0;G<L;G++)this.hideImpostor(this._impostors[0]);this._debugBoxMesh&&this._debugBoxMesh.dispose(),this._debugSphereMesh&&this._debugSphereMesh.dispose(),this._debugCylinderMesh&&this._debugCylinderMesh.dispose(),this._debugMaterial&&this._debugMaterial.dispose(),this._impostors.length=0,this._scene=null,this._physicsEnginePlugin=null,this._utilityLayer&&(this._utilityLayer.dispose(),this._utilityLayer=null)},$}(),X=f(40),j=function(){function $(L){this.ray=L}return $.CreateAndShow=function(L,G,Q){var oe=new $(L);return oe.show(G,Q),oe},$.prototype.show=function(L,G){if(!this._renderFunction&&this.ray){var Q=this.ray;this._renderFunction=this._render.bind(this),this._scene=L,this._renderPoints=[Q.origin,Q.origin.add(Q.direction.scale(Q.length))],this._renderLine=h.a.CreateLines("ray",this._renderPoints,L,!0),this._renderLine.isPickable=!1,this._renderFunction&&this._scene.registerBeforeRender(this._renderFunction)}G&&this._renderLine&&this._renderLine.color.copyFrom(G)},$.prototype.hide=function(){this._renderFunction&&this._scene&&(this._scene.unregisterBeforeRender(this._renderFunction),this._scene=null,this._renderFunction=null,this._renderLine&&(this._renderLine.dispose(),this._renderLine=null),this._renderPoints=[])},$.prototype._render=function(){var L=this.ray;if(L){var G=this._renderPoints[1],Q=Math.min(L.length,1e6);G.copyFrom(L.direction),G.scaleInPlace(Q),G.addInPlace(L.origin),this._renderPoints[0].copyFrom(L.origin),h.a.CreateLines("ray",this._renderPoints,this._scene,!0,this._renderLine)}},$.prototype.attachToMesh=function(L,G,Q,oe){var re=this;this._attachedToMesh=L;var Y=this.ray;Y&&(Y.direction||(Y.direction=_.e.Zero()),Y.origin||(Y.origin=_.e.Zero()),oe&&(Y.length=oe),Q||(Q=_.e.Zero()),G||(G=new _.e(0,0,-1)),this._scene||(this._scene=L.getScene()),this._meshSpaceDirection?(this._meshSpaceDirection.copyFrom(G),this._meshSpaceOrigin.copyFrom(Q)):(this._meshSpaceDirection=G.clone(),this._meshSpaceOrigin=Q.clone()),this._onAfterRenderObserver||(this._onAfterRenderObserver=this._scene.onBeforeRenderObservable.add(function(){return re._updateToMesh()}),this._onAfterStepObserver=this._scene.onAfterStepObservable.add(function(){return re._updateToMesh()})),this._attachedToMesh.computeWorldMatrix(!0),this._updateToMesh())},$.prototype.detachFromMesh=function(){this._attachedToMesh&&this._scene&&(this._onAfterRenderObserver&&(this._scene.onBeforeRenderObservable.remove(this._onAfterRenderObserver),this._scene.onAfterStepObservable.remove(this._onAfterStepObserver)),this._attachedToMesh=null,this._onAfterRenderObserver=null,this._onAfterStepObserver=null,this._scene=null)},$.prototype._updateToMesh=function(){var L=this.ray;this._attachedToMesh&&L&&(this._attachedToMesh._isDisposed?this.detachFromMesh():(this._attachedToMesh.getDirectionToRef(this._meshSpaceDirection,L.direction),_.e.TransformCoordinatesToRef(this._meshSpaceOrigin,this._attachedToMesh.getWorldMatrix(),L.origin)))},$.prototype.dispose=function(){this.hide(),this.detachFromMesh(),this.ray=null},$}(),ne=f(25),te=f(73),de=f(62),pe=f(4),ae=f(5),ee=f(97),K=function(){function $(L,G,Q,oe,re,Y){var k,H,Z,W,q,he,ge,me,_e,be,Pe,ye,Be,ke;oe===void 0&&(oe=!0),re===void 0&&(re=3),Y===void 0&&(Y={}),this.skeleton=L,this.mesh=G,this.autoUpdateBonesMatrices=oe,this.renderingGroupId=re,this.options=Y,this.color=M.a.White(),this._debugLines=new Array,this._localAxes=null,this._isEnabled=!1,this._obs=null,this._scene=Q,this._ready=!1,Y.pauseAnimations=(k=Y.pauseAnimations)===null||k===void 0||k,Y.returnToRest=(H=Y.returnToRest)!==null&&H!==void 0&&H,Y.displayMode=(Z=Y.displayMode)!==null&&Z!==void 0?Z:$.DISPLAY_LINES,Y.displayOptions=(W=Y.displayOptions)!==null&&W!==void 0?W:{},Y.displayOptions.midStep=(q=Y.displayOptions.midStep)!==null&&q!==void 0?q:.235,Y.displayOptions.midStepFactor=(he=Y.displayOptions.midStepFactor)!==null&&he!==void 0?he:.155,Y.displayOptions.sphereBaseSize=(ge=Y.displayOptions.sphereBaseSize)!==null&&ge!==void 0?ge:.15,Y.displayOptions.sphereScaleUnit=(me=Y.displayOptions.sphereScaleUnit)!==null&&me!==void 0?me:2,Y.displayOptions.sphereFactor=(_e=Y.displayOptions.sphereFactor)!==null&&_e!==void 0?_e:.865,Y.displayOptions.spurFollowsChild=(be=Y.displayOptions.spurFollowsChild)!==null&&be!==void 0&&be,Y.displayOptions.showLocalAxes=(Pe=Y.displayOptions.showLocalAxes)!==null&&Pe!==void 0&&Pe,Y.displayOptions.localAxesSize=(ye=Y.displayOptions.localAxesSize)!==null&&ye!==void 0?ye:.075,Y.computeBonesUsingShaders=(Be=Y.computeBonesUsingShaders)===null||Be===void 0||Be,Y.useAllBones=(ke=Y.useAllBones)===null||ke===void 0||ke;var We=G.getVerticesData(pe.b.MatricesIndicesKind),je=G.getVerticesData(pe.b.MatricesWeightsKind);if(this._boneIndices=new Set,!Y.useAllBones&&We&&je)for(var He=0;He<We.length;++He){var qe=We[He];je[He]!==0&&this._boneIndices.add(qe)}this._utilityLayer=new N.a(this._scene,!1),this._utilityLayer.pickUtilitySceneFirst=!1,this._utilityLayer.utilityLayerScene.autoClearDepthAndStencil=!0;var Ge=this.options.displayMode||0;Ge>$.DISPLAY_SPHERE_AND_SPURS&&(Ge=$.DISPLAY_LINES),this.displayMode=Ge,this.update(),this._bindObs()}return $.CreateBoneWeightShader=function(L,G){var Q,oe,re,Y,k,H,Z=L.skeleton,W=(Q=L.colorBase)!==null&&Q!==void 0?Q:M.a.Black(),q=(oe=L.colorZero)!==null&&oe!==void 0?oe:M.a.Blue(),he=(re=L.colorQuarter)!==null&&re!==void 0?re:M.a.Green(),ge=(Y=L.colorHalf)!==null&&Y!==void 0?Y:M.a.Yellow(),me=(k=L.colorFull)!==null&&k!==void 0?k:M.a.Red(),_e=(H=L.targetBoneIndex)!==null&&H!==void 0?H:0;ae.a.ShadersStore["boneWeights:"+Z.name+"VertexShader"]=`precision highp float;
-
-        attribute vec3 position;
-        attribute vec2 uv;
-
-        uniform mat4 view;
-        uniform mat4 projection;
-        uniform mat4 worldViewProjection;
-
-        #include<bonesDeclaration>
-        #if NUM_BONE_INFLUENCERS == 0
-            attribute vec4 matricesIndices;
-            attribute vec4 matricesWeights;
-        #endif
-
-        #include<instancesDeclaration>
-
-        varying vec3 vColor;
-
-        uniform vec3 colorBase;
-        uniform vec3 colorZero;
-        uniform vec3 colorQuarter;
-        uniform vec3 colorHalf;
-        uniform vec3 colorFull;
-
-        uniform float targetBoneIndex;
-
-        void main() {
-            vec3 positionUpdated = position;
-
-            #include<instancesVertex>
-            #include<bonesVertex>
-
-            vec4 worldPos = finalWorld * vec4(positionUpdated, 1.0);
-
-            vec3 color = colorBase;
-            float totalWeight = 0.;
-            if(matricesIndices[0] == targetBoneIndex && matricesWeights[0] > 0.){
-                totalWeight += matricesWeights[0];
-            }
-            if(matricesIndices[1] == targetBoneIndex && matricesWeights[1] > 0.){
-                totalWeight += matricesWeights[1];
-            }
-            if(matricesIndices[2] == targetBoneIndex && matricesWeights[2] > 0.){
-                totalWeight += matricesWeights[2];
-            }
-            if(matricesIndices[3] == targetBoneIndex && matricesWeights[3] > 0.){
-                totalWeight += matricesWeights[3];
-            }
-
-            color = mix(color, colorZero, smoothstep(0., 0.25, totalWeight));
-            color = mix(color, colorQuarter, smoothstep(0.25, 0.5, totalWeight));
-            color = mix(color, colorHalf, smoothstep(0.5, 0.75, totalWeight));
-            color = mix(color, colorFull, smoothstep(0.75, 1.0, totalWeight));
-            vColor = color;
-
-        gl_Position = projection * view * worldPos;
-        }`,ae.a.ShadersStore["boneWeights:"+Z.name+"FragmentShader"]=`
-            precision highp float;
-            varying vec3 vPosition;
-
-            varying vec3 vColor;
-
-            void main() {
-                vec4 color = vec4(vColor, 1.0);
-                gl_FragColor = color;
-            }
-        `;var be=new te.a("boneWeight:"+Z.name,G,{vertex:"boneWeights:"+Z.name,fragment:"boneWeights:"+Z.name},{attributes:["position","normal","matricesIndices","matricesWeights"],uniforms:["world","worldView","worldViewProjection","view","projection","viewProjection","colorBase","colorZero","colorQuarter","colorHalf","colorFull","targetBoneIndex"]});return be.setColor3("colorBase",W),be.setColor3("colorZero",q),be.setColor3("colorQuarter",he),be.setColor3("colorHalf",ge),be.setColor3("colorFull",me),be.setFloat("targetBoneIndex",_e),be.getClassName=function(){return"BoneWeightShader"},be.transparencyMode=ne.a.MATERIAL_OPAQUE,be},$.CreateSkeletonMapShader=function(L,G){var Q,oe=L.skeleton,re=(Q=L.colorMap)!==null&&Q!==void 0?Q:[{color:new M.a(1,.38,.18),location:0},{color:new M.a(.59,.18,1),location:.2},{color:new M.a(.59,1,.18),location:.4},{color:new M.a(1,.87,.17),location:.6},{color:new M.a(1,.17,.42),location:.8},{color:new M.a(.17,.68,1),location:1}],Y=oe.bones.length+1,k=$._CreateBoneMapColorBuffer(Y,re,G),H=new te.a("boneWeights:"+oe.name,G,{vertexSource:`precision highp float;
-
-            attribute vec3 position;
-            attribute vec2 uv;
-
-            uniform mat4 view;
-            uniform mat4 projection;
-            uniform mat4 worldViewProjection;
-            uniform float colorMap[`+4*oe.bones.length+`];
-
-            #include<bonesDeclaration>
-            #if NUM_BONE_INFLUENCERS == 0
-                attribute vec4 matricesIndices;
-                attribute vec4 matricesWeights;
-            #endif
-            #include<instancesDeclaration>
-
-            varying vec3 vColor;
-
-            void main() {
-                vec3 positionUpdated = position;
-
-                #include<instancesVertex>
-                #include<bonesVertex>
-
-                vec3 color = vec3(0.);
-                bool first = true;
-
-                for (int i = 0; i < 4; i++) {
-                    int boneIdx = int(matricesIndices[i]);
-                    float boneWgt = matricesWeights[i];
-
-                    vec3 c = vec3(colorMap[boneIdx * 4 + 0], colorMap[boneIdx * 4 + 1], colorMap[boneIdx * 4 + 2]);
-
-                    if (boneWgt > 0.) {
-                        if (first) {
-                            first = false;
-                            color = c;
-                        } else {
-                            color = mix(color, c, boneWgt);
-                        }
-                    }
-                }
-
-                vColor = color;
-
-                vec4 worldPos = finalWorld * vec4(positionUpdated, 1.0);
-
-                gl_Position = projection * view * worldPos;
-            }`,fragmentSource:`
-            precision highp float;
-            varying vec3 vColor;
-
-            void main() {
-                vec4 color = vec4( vColor, 1.0 );
-                gl_FragColor = color;
-            }
-            `},{attributes:["position","normal","matricesIndices","matricesWeights"],uniforms:["world","worldView","worldViewProjection","view","projection","viewProjection","colorMap"]});return H.setFloats("colorMap",k),H.getClassName=function(){return"SkeletonMapShader"},H.transparencyMode=ne.a.MATERIAL_OPAQUE,H},$._CreateBoneMapColorBuffer=function(L,G,Q){var oe=new de.a("temp",{width:L,height:1},Q,!1),re=oe.getContext(),Y=re.createLinearGradient(0,0,L,0);G.forEach(function(W){Y.addColorStop(W.location,W.color.toHexString())}),re.fillStyle=Y,re.fillRect(0,0,L,1),oe.update();for(var k=[],H=re.getImageData(0,0,L,1).data,Z=0;Z<H.length;Z++)k.push(H[Z]*(1/255));return oe.dispose(),k},Object.defineProperty($.prototype,"scene",{get:function(){return this._scene},enumerable:!1,configurable:!0}),Object.defineProperty($.prototype,"utilityLayer",{get:function(){return this._utilityLayer},enumerable:!1,configurable:!0}),Object.defineProperty($.prototype,"isReady",{get:function(){return this._ready},enumerable:!1,configurable:!0}),Object.defineProperty($.prototype,"ready",{set:function(L){this._ready=L},enumerable:!1,configurable:!0}),Object.defineProperty($.prototype,"debugMesh",{get:function(){return this._debugMesh},set:function(L){this._debugMesh=L},enumerable:!1,configurable:!0}),Object.defineProperty($.prototype,"displayMode",{get:function(){return this.options.displayMode||$.DISPLAY_LINES},set:function(L){L>$.DISPLAY_SPHERE_AND_SPURS&&(L=$.DISPLAY_LINES),this.options.displayMode=L},enumerable:!1,configurable:!0}),$.prototype._bindObs=function(){var L=this;switch(this.displayMode){case $.DISPLAY_LINES:this._obs=this.scene.onBeforeRenderObservable.add(function(){L._displayLinesUpdate()})}},$.prototype.update=function(){switch(this.displayMode){case $.DISPLAY_LINES:this._displayLinesUpdate();break;case $.DISPLAY_SPHERES:this._buildSpheresAndSpurs(!0);break;case $.DISPLAY_SPHERE_AND_SPURS:this._buildSpheresAndSpurs(!1)}this._buildLocalAxes()},Object.defineProperty($.prototype,"isEnabled",{get:function(){return this._isEnabled},set:function(L){this.isEnabled!==L&&(this._isEnabled=L,this.debugMesh&&this.debugMesh.setEnabled(L),L&&!this._obs?this._bindObs():!L&&this._obs&&(this.scene.onBeforeRenderObservable.remove(this._obs),this._obs=null))},enumerable:!1,configurable:!0}),$.prototype._getBonePosition=function(L,G,Q,oe,re,Y){oe===void 0&&(oe=0),re===void 0&&(re=0),Y===void 0&&(Y=0);var k=_.c.Matrix[0],H=G.getParent();if(k.copyFrom(G.getLocalMatrix()),oe!==0||re!==0||Y!==0){var Z=_.c.Matrix[1];_.a.IdentityToRef(Z),Z.setTranslationFromFloats(oe,re,Y),Z.multiplyToRef(k,k)}H&&k.multiplyToRef(H.getAbsoluteTransform(),k),k.multiplyToRef(Q,k),L.x=k.m[12],L.y=k.m[13],L.z=k.m[14]},$.prototype._getLinesForBonesWithLength=function(L,G){for(var Q=L.length,oe=this.mesh._effectiveMesh.position,re=0,Y=0;Y<Q;Y++){var k=L[Y],H=this._debugLines[re];k._index!==-1&&(this._boneIndices.has(k.getIndex())||this.options.useAllBones)&&(H||(H=[_.e.Zero(),_.e.Zero()],this._debugLines[re]=H),this._getBonePosition(H[0],k,G),this._getBonePosition(H[1],k,G,0,k.length,0),H[0].subtractInPlace(oe),H[1].subtractInPlace(oe),re++)}},$.prototype._getLinesForBonesNoLength=function(L){for(var G=L.length,Q=0,oe=this.mesh._effectiveMesh,re=oe.position,Y=G-1;Y>=0;Y--){var k=L[Y],H=k.getParent();if(H&&(this._boneIndices.has(k.getIndex())||this.options.useAllBones)){var Z=this._debugLines[Q];Z||(Z=[_.e.Zero(),_.e.Zero()],this._debugLines[Q]=Z),k.getAbsolutePositionToRef(oe,Z[0]),H.getAbsolutePositionToRef(oe,Z[1]),Z[0].subtractInPlace(re),Z[1].subtractInPlace(re),Q++}}},$.prototype._revert=function(L){this.options.pauseAnimations&&(this.scene.animationsEnabled=L,this.utilityLayer.utilityLayerScene.animationsEnabled=L)},$.prototype._getAbsoluteBindPoseToRef=function(L,G){L!==null&&L._index!==-1?(this._getAbsoluteBindPoseToRef(L.getParent(),G),L.getBindPose().multiplyToRef(G,G)):G.copyFrom(_.a.Identity())},$.prototype._buildSpheresAndSpurs=function(L){var G,Q;L===void 0&&(L=!0),this._debugMesh&&(this._debugMesh.dispose(),this._debugMesh=null,this.ready=!1),this._ready=!1;var oe=(G=this.utilityLayer)===null||G===void 0?void 0:G.utilityLayerScene,re=this.skeleton.bones,Y=[],k=[],H=this.scene.animationsEnabled;try{this.options.pauseAnimations&&(this.scene.animationsEnabled=!1,oe.animationsEnabled=!1),this.options.returnToRest&&this.skeleton.returnToRest(),this.autoUpdateBonesMatrices&&this.skeleton.computeAbsoluteTransforms();for(var Z=Number.NEGATIVE_INFINITY,W=this.options.displayOptions||{},q=function(He){var qe=re[He];if(qe._index===-1||!he._boneIndices.has(qe.getIndex())&&!he.options.useAllBones)return"continue";var Ge=new _.a;he._getAbsoluteBindPoseToRef(qe,Ge);var nt=new _.e;Ge.decompose(void 0,void 0,nt),qe.children.forEach(function(It,Pt){var Ot=new _.a;It.getBindPose().multiplyToRef(Ge,Ot);var on=new _.e;Ot.decompose(void 0,void 0,on);var Zt=_.e.Distance(nt,on);if(Zt>Z&&(Z=Zt),!L){for(var tn=on.clone().subtract(nt.clone()),De=tn.length(),Pn=tn.normalize().scale(De),nn=W.midStep||.165,Cn=W.midStepFactor||.215,Ue=Pn.scale(nn),xn=ee.a.ExtrudeShapeCustom("skeletonViewer",{shape:[new _.e(1,-1,0),new _.e(1,1,0),new _.e(-1,1,0),new _.e(-1,-1,0),new _.e(1,-1,0)],path:[_.e.Zero(),Ue,Pn],scaleFunction:function(Lo){switch(Lo){case 0:case 2:return 0;case 1:return De*Cn}return 0},sideOrientation:h.a.DEFAULTSIDE,updatable:!1},oe),dr=xn.getTotalVertices(),Xe=[],An=[],ti=0;ti<dr;ti++)Xe.push(1,0,0,0),W.spurFollowsChild&&ti>9?An.push(It.getIndex(),0,0,0):An.push(qe.getIndex(),0,0,0);xn.position=nt.clone(),xn.setVerticesData(pe.b.MatricesWeightsKind,Xe,!1),xn.setVerticesData(pe.b.MatricesIndicesKind,An,!1),xn.convertToFlatShadedMesh(),k.push(xn)}});for(var $e=W.sphereBaseSize||.2,ct=E.a.CreateSphere("skeletonViewer",{segments:6,diameter:$e,updatable:!0},oe),st=ct.getTotalVertices(),mt=[],St=[],wt=0;wt<st;wt++)mt.push(1,0,0,0),St.push(qe.getIndex(),0,0,0);ct.setVerticesData(pe.b.MatricesWeightsKind,mt,!1),ct.setVerticesData(pe.b.MatricesIndicesKind,St,!1),ct.position=nt.clone(),Y.push([ct,qe])},he=this,ge=0;ge<re.length;ge++)q(ge);var me=W.sphereScaleUnit||2,_e=W.sphereFactor||.85,be=[];for(ge=0;ge<Y.length;ge++){for(var Pe=Y[ge],ye=Pe[0],Be=Pe[1],ke=1/(me/Z),We=0,je=Be;je.getParent()&&je.getParent().getIndex()!==-1;)We++,je=je.getParent();ye.scaling.scaleInPlace(ke*Math.pow(_e,We)),be.push(ye)}this.debugMesh=h.a.MergeMeshes(be.concat(k),!0,!0),this.debugMesh&&(this.debugMesh.renderingGroupId=this.renderingGroupId,this.debugMesh.skeleton=this.skeleton,this.debugMesh.parent=this.mesh,this.debugMesh.computeBonesUsingShaders=(Q=this.options.computeBonesUsingShaders)===null||Q===void 0||Q,this.debugMesh.alwaysSelectAsActiveMesh=!0),this.utilityLayer._getSharedGizmoLight().intensity=.7,this._revert(H),this.ready=!0}catch(He){console.error(He),this._revert(H),this.dispose()}},$.prototype._buildLocalAxes=function(){var L;this._localAxes&&this._localAxes.dispose(),this._localAxes=null;var G=this.options.displayOptions||{};if(G.showLocalAxes){var Q=this._utilityLayer.utilityLayerScene,oe=G.localAxesSize||.075,re=[],Y=[],k=new M.b(1,0,0,1),H=new M.b(0,1,0,1),Z=new M.b(0,0,1,1),W=[],q=[];for(var he in this.skeleton.bones){var ge=this.skeleton.bones[he];if(ge._index!==-1&&(this._boneIndices.has(ge.getIndex())||this.options.useAllBones)){var me=new _.a,_e=new _.e;this._getAbsoluteBindPoseToRef(ge,me),me.decompose(void 0,void 0,_e);var be=ge.getBindPose().getRotationMatrix(),Pe=_.e.TransformCoordinates(new _.e(0+oe,0,0),be),ye=_.e.TransformCoordinates(new _.e(0,0+oe,0),be),Be=_.e.TransformCoordinates(new _.e(0,0,0+oe),be),ke=[[_e,_e.add(Pe)],[_e,_e.add(ye)],[_e,_e.add(Be)]],We=[[k,k],[H,H],[Z,Z]];re.push.apply(re,ke),Y.push.apply(Y,We);for(var je=0;je<6;je++)W.push(1,0,0,0),q.push(ge.getIndex(),0,0,0)}}this._localAxes=X.a.CreateLineSystem("localAxes",{lines:re,colors:Y,updatable:!0},Q),this._localAxes.setVerticesData(pe.b.MatricesWeightsKind,W,!1),this._localAxes.setVerticesData(pe.b.MatricesIndicesKind,q,!1),this._localAxes.skeleton=this.skeleton,this._localAxes.renderingGroupId=this.renderingGroupId,this._localAxes.parent=this.mesh,this._localAxes.computeBonesUsingShaders=(L=this.options.computeBonesUsingShaders)===null||L===void 0||L}},$.prototype._displayLinesUpdate=function(){if(this._utilityLayer){this.autoUpdateBonesMatrices&&this.skeleton.computeAbsoluteTransforms();var L=this.mesh._effectiveMesh;this.skeleton.bones[0].length===void 0?this._getLinesForBonesNoLength(this.skeleton.bones):this._getLinesForBonesWithLength(this.skeleton.bones,L.getWorldMatrix());var G=this._utilityLayer.utilityLayerScene;G&&(this._debugMesh?X.a.CreateLineSystem("",{lines:this._debugLines,updatable:!0,instance:this._debugMesh},G):(this._debugMesh=X.a.CreateLineSystem("",{lines:this._debugLines,updatable:!0,instance:null},G),this._debugMesh.renderingGroupId=this.renderingGroupId),this._debugMesh.position.copyFrom(this.mesh.position),this._debugMesh.color=this.color)}},$.prototype.changeDisplayMode=function(L){var G=!!this.isEnabled;this.displayMode!==L&&(this.isEnabled=!1,this._debugMesh&&(this._debugMesh.dispose(),this._debugMesh=null,this.ready=!1),this.displayMode=L,this.update(),this._bindObs(),this.isEnabled=G)},$.prototype.changeDisplayOptions=function(L,G){var Q=!!this.isEnabled;this.options.displayOptions[L]=G,this.isEnabled=!1,this._debugMesh&&(this._debugMesh.dispose(),this._debugMesh=null,this.ready=!1),this.update(),this._bindObs(),this.isEnabled=Q},$.prototype.dispose=function(){this.isEnabled=!1,this._debugMesh&&(this._debugMesh.dispose(),this._debugMesh=null),this._utilityLayer&&(this._utilityLayer.dispose(),this._utilityLayer=null),this.ready=!1},$.DISPLAY_LINES=0,$.DISPLAY_SPHERES=1,$.DISPLAY_SPHERE_AND_SPURS=2,$}()},function(Me,y,f){var U="morphTargetsVertex",_=`#ifdef MORPHTARGETS
-positionUpdated+=(position{X}-position)*morphTargetInfluences[{X}];
-#ifdef MORPHTARGETS_NORMAL
-normalUpdated+=(normal{X}-normal)*morphTargetInfluences[{X}];
-#endif
-#ifdef MORPHTARGETS_TANGENT
-tangentUpdated.xyz+=(tangent{X}-tangent.xyz)*morphTargetInfluences[{X}];
-#endif
-#ifdef MORPHTARGETS_UV
-uvUpdated+=(uv_{X}-uv)*morphTargetInfluences[{X}];
-#endif
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){f.d(y,"b",function(){return _}),f.d(y,"a",function(){return x});var U=f(0);function _(u,M,R,C,m){m===void 0&&(m=null);for(var c=new U.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),T=new U.e(-Number.MAX_VALUE,-Number.MAX_VALUE,-Number.MAX_VALUE),A=R;A<R+C;A++){var S=3*M[A],g=u[S],l=u[S+1],h=u[S+2];c.minimizeInPlaceFromFloats(g,l,h),T.maximizeInPlaceFromFloats(g,l,h)}return m&&(c.x-=c.x*m.x+m.y,c.y-=c.y*m.x+m.y,c.z-=c.z*m.x+m.y,T.x+=T.x*m.x+m.y,T.y+=T.y*m.x+m.y,T.z+=T.z*m.x+m.y),{minimum:c,maximum:T}}function x(u,M,R,C,m){C===void 0&&(C=null);var c=new U.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),T=new U.e(-Number.MAX_VALUE,-Number.MAX_VALUE,-Number.MAX_VALUE);m||(m=3);for(var A=M,S=M*m;A<M+R;A++,S+=m){var g=u[S],l=u[S+1],h=u[S+2];c.minimizeInPlaceFromFloats(g,l,h),T.maximizeInPlaceFromFloats(g,l,h)}return C&&(c.x-=c.x*C.x+C.y,c.y-=c.y*C.x+C.y,c.z-=c.z*C.x+C.y,T.x+=T.x*C.x+C.y,T.y+=T.y*C.x+C.y,T.z+=T.z*C.x+C.y),{minimum:c,maximum:T}}},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){}},function(Me,y,f){f.d(y,"a",function(){return u});var U=f(44),_=f(0),x=f(28),u=function(){function M(R,C,m){this.vectors=U.a.BuildArray(8,_.e.Zero),this.center=_.e.Zero(),this.centerWorld=_.e.Zero(),this.extendSize=_.e.Zero(),this.extendSizeWorld=_.e.Zero(),this.directions=U.a.BuildArray(3,_.e.Zero),this.vectorsWorld=U.a.BuildArray(8,_.e.Zero),this.minimumWorld=_.e.Zero(),this.maximumWorld=_.e.Zero(),this.minimum=_.e.Zero(),this.maximum=_.e.Zero(),this.reConstruct(R,C,m)}return M.prototype.reConstruct=function(R,C,m){var c=R.x,T=R.y,A=R.z,S=C.x,g=C.y,l=C.z,h=this.vectors;this.minimum.copyFromFloats(c,T,A),this.maximum.copyFromFloats(S,g,l),h[0].copyFromFloats(c,T,A),h[1].copyFromFloats(S,g,l),h[2].copyFromFloats(S,T,A),h[3].copyFromFloats(c,g,A),h[4].copyFromFloats(c,T,l),h[5].copyFromFloats(S,g,A),h[6].copyFromFloats(c,g,l),h[7].copyFromFloats(S,T,l),C.addToRef(R,this.center).scaleInPlace(.5),C.subtractToRef(R,this.extendSize).scaleInPlace(.5),this._worldMatrix=m||_.a.IdentityReadOnly,this._update(this._worldMatrix)},M.prototype.scale=function(R){var C=M.TmpVector3,m=this.maximum.subtractToRef(this.minimum,C[0]),c=m.length();m.normalizeFromLength(c);var T=c*R,A=m.scaleInPlace(.5*T),S=this.center.subtractToRef(A,C[1]),g=this.center.addToRef(A,C[2]);return this.reConstruct(S,g,this._worldMatrix),this},M.prototype.getWorldMatrix=function(){return this._worldMatrix},M.prototype._update=function(R){var C=this.minimumWorld,m=this.maximumWorld,c=this.directions,T=this.vectorsWorld,A=this.vectors;if(R.isIdentity()){for(C.copyFrom(this.minimum),m.copyFrom(this.maximum),S=0;S<8;++S)T[S].copyFrom(A[S]);this.extendSizeWorld.copyFrom(this.extendSize),this.centerWorld.copyFrom(this.center)}else{C.setAll(Number.MAX_VALUE),m.setAll(-Number.MAX_VALUE);for(var S=0;S<8;++S){var g=T[S];_.e.TransformCoordinatesToRef(A[S],R,g),C.minimizeInPlace(g),m.maximizeInPlace(g)}m.subtractToRef(C,this.extendSizeWorld).scaleInPlace(.5),m.addToRef(C,this.centerWorld).scaleInPlace(.5)}_.e.FromArrayToRef(R.m,0,c[0]),_.e.FromArrayToRef(R.m,4,c[1]),_.e.FromArrayToRef(R.m,8,c[2]),this._worldMatrix=R},M.prototype.isInFrustum=function(R){return M.IsInFrustum(this.vectorsWorld,R)},M.prototype.isCompletelyInFrustum=function(R){return M.IsCompletelyInFrustum(this.vectorsWorld,R)},M.prototype.intersectsPoint=function(R){var C=this.minimumWorld,m=this.maximumWorld,c=C.x,T=C.y,A=C.z,S=m.x,g=m.y,l=m.z,h=R.x,v=R.y,E=R.z,D=-x.a;return!(S-h<D||D>h-c)&&!(g-v<D||D>v-T)&&!(l-E<D||D>E-A)},M.prototype.intersectsSphere=function(R){return M.IntersectsSphere(this.minimumWorld,this.maximumWorld,R.centerWorld,R.radiusWorld)},M.prototype.intersectsMinMax=function(R,C){var m=this.minimumWorld,c=this.maximumWorld,T=m.x,A=m.y,S=m.z,g=c.x,l=c.y,h=c.z,v=R.x,E=R.y,D=R.z,w=C.x,N=C.y,I=C.z;return!(g<v||T>w)&&!(l<E||A>N)&&!(h<D||S>I)},M.Intersects=function(R,C){return R.intersectsMinMax(C.minimumWorld,C.maximumWorld)},M.IntersectsSphere=function(R,C,m,c){var T=M.TmpVector3[0];return _.e.ClampToRef(m,R,C,T),_.e.DistanceSquared(m,T)<=c*c},M.IsCompletelyInFrustum=function(R,C){for(var m=0;m<6;++m)for(var c=C[m],T=0;T<8;++T)if(c.dotCoordinate(R[T])<0)return!1;return!0},M.IsInFrustum=function(R,C){for(var m=0;m<6;++m){for(var c=!0,T=C[m],A=0;A<8;++A)if(T.dotCoordinate(R[A])>=0){c=!1;break}if(c)return!1}return!0},M.TmpVector3=U.a.BuildArray(3,_.e.Zero),M}()},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(38),_=function(){function x(){}return x.SetImmediate=function(u){U.a.IsWindowObjectExist()&&window.setImmediate?window.setImmediate(u):setTimeout(u,1)},x}()},function(Me,y,f){f.d(y,"a",function(){return x});var U=f(0),_=f(2),x=function(){function u(){this.previousWorldMatrices={},this.previousBones={}}return u.AddUniforms=function(M){M.push("previousWorld","previousViewProjection")},u.AddSamplers=function(M){},u.prototype.bindForSubMesh=function(M,R,C,m,c){R.prePassRenderer&&R.prePassRenderer.enabled&&R.prePassRenderer.getIndex(_.a.PREPASS_VELOCITY_TEXTURE_TYPE)!==-1&&(this.previousWorldMatrices[C.uniqueId]||(this.previousWorldMatrices[C.uniqueId]=U.a.Identity()),this.previousViewProjection||(this.previousViewProjection=R.getTransformMatrix()),M.setMatrix("previousWorld",this.previousWorldMatrices[C.uniqueId]),M.setMatrix("previousViewProjection",this.previousViewProjection),this.previousWorldMatrices[C.uniqueId]=m.clone(),this.previousViewProjection=R.getTransformMatrix().clone())},u}()},function(Me,y,f){var U="lightFragmentDeclaration",_=`#ifdef LIGHT{X}
-uniform vec4 vLightData{X};
-uniform vec4 vLightDiffuse{X};
-#ifdef SPECULARTERM
-uniform vec4 vLightSpecular{X};
-#else
-vec4 vLightSpecular{X}=vec4(0.);
-#endif
-#ifdef SHADOW{X}
-#ifdef SHADOWCSM{X}
-uniform mat4 lightMatrix{X}[SHADOWCSMNUM_CASCADES{X}];
-uniform float viewFrustumZ{X}[SHADOWCSMNUM_CASCADES{X}];
-uniform float frustumLengths{X}[SHADOWCSMNUM_CASCADES{X}];
-uniform float cascadeBlendFactor{X};
-varying vec4 vPositionFromLight{X}[SHADOWCSMNUM_CASCADES{X}];
-varying float vDepthMetric{X}[SHADOWCSMNUM_CASCADES{X}];
-varying vec4 vPositionFromCamera{X};
-#if defined(SHADOWPCSS{X})
-uniform highp sampler2DArrayShadow shadowSampler{X};
-uniform highp sampler2DArray depthSampler{X};
-uniform vec2 lightSizeUVCorrection{X}[SHADOWCSMNUM_CASCADES{X}];
-uniform float depthCorrection{X}[SHADOWCSMNUM_CASCADES{X}];
-uniform float penumbraDarkness{X};
-#elif defined(SHADOWPCF{X})
-uniform highp sampler2DArrayShadow shadowSampler{X};
-#else
-uniform highp sampler2DArray shadowSampler{X};
-#endif
-#ifdef SHADOWCSMDEBUG{X}
-const vec3 vCascadeColorsMultiplier{X}[8]=vec3[8]
-(
-vec3 ( 1.5,0.0,0.0 ),
-vec3 ( 0.0,1.5,0.0 ),
-vec3 ( 0.0,0.0,5.5 ),
-vec3 ( 1.5,0.0,5.5 ),
-vec3 ( 1.5,1.5,0.0 ),
-vec3 ( 1.0,1.0,1.0 ),
-vec3 ( 0.0,1.0,5.5 ),
-vec3 ( 0.5,3.5,0.75 )
-);
-vec3 shadowDebug{X};
-#endif
-#ifdef SHADOWCSMUSESHADOWMAXZ{X}
-int index{X}=-1;
-#else
-int index{X}=SHADOWCSMNUM_CASCADES{X}-1;
-#endif
-float diff{X}=0.;
-#elif defined(SHADOWCUBE{X})
-uniform samplerCube shadowSampler{X};
-#else
-varying vec4 vPositionFromLight{X};
-varying float vDepthMetric{X};
-#if defined(SHADOWPCSS{X})
-uniform highp sampler2DShadow shadowSampler{X};
-uniform highp sampler2D depthSampler{X};
-#elif defined(SHADOWPCF{X})
-uniform highp sampler2DShadow shadowSampler{X};
-#else
-uniform sampler2D shadowSampler{X};
-#endif
-uniform mat4 lightMatrix{X};
-#endif
-uniform vec4 shadowsInfo{X};
-uniform vec2 depthValues{X};
-#endif
-#ifdef SPOTLIGHT{X}
-uniform vec4 vLightDirection{X};
-uniform vec4 vLightFalloff{X};
-#elif defined(POINTLIGHT{X})
-uniform vec4 vLightFalloff{X};
-#elif defined(HEMILIGHT{X})
-uniform vec3 vLightGround{X};
-#endif
-#ifdef PROJECTEDLIGHTTEXTURE{X}
-uniform mat4 textureProjectionMatrix{X};
-uniform sampler2D projectionLightSampler{X};
-#endif
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U="lightUboDeclaration",_=`#ifdef LIGHT{X}
-uniform Light{X}
-{
-vec4 vLightData;
-vec4 vLightDiffuse;
-vec4 vLightSpecular;
-#ifdef SPOTLIGHT{X}
-vec4 vLightDirection;
-vec4 vLightFalloff;
-#elif defined(POINTLIGHT{X})
-vec4 vLightFalloff;
-#elif defined(HEMILIGHT{X})
-vec3 vLightGround;
-#endif
-vec4 shadowsInfo;
-vec2 depthValues;
-} light{X};
-#ifdef PROJECTEDLIGHTTEXTURE{X}
-uniform mat4 textureProjectionMatrix{X};
-uniform sampler2D projectionLightSampler{X};
-#endif
-#ifdef SHADOW{X}
-#ifdef SHADOWCSM{X}
-uniform mat4 lightMatrix{X}[SHADOWCSMNUM_CASCADES{X}];
-uniform float viewFrustumZ{X}[SHADOWCSMNUM_CASCADES{X}];
-uniform float frustumLengths{X}[SHADOWCSMNUM_CASCADES{X}];
-uniform float cascadeBlendFactor{X};
-varying vec4 vPositionFromLight{X}[SHADOWCSMNUM_CASCADES{X}];
-varying float vDepthMetric{X}[SHADOWCSMNUM_CASCADES{X}];
-varying vec4 vPositionFromCamera{X};
-#if defined(SHADOWPCSS{X})
-uniform highp sampler2DArrayShadow shadowSampler{X};
-uniform highp sampler2DArray depthSampler{X};
-uniform vec2 lightSizeUVCorrection{X}[SHADOWCSMNUM_CASCADES{X}];
-uniform float depthCorrection{X}[SHADOWCSMNUM_CASCADES{X}];
-uniform float penumbraDarkness{X};
-#elif defined(SHADOWPCF{X})
-uniform highp sampler2DArrayShadow shadowSampler{X};
-#else
-uniform highp sampler2DArray shadowSampler{X};
-#endif
-#ifdef SHADOWCSMDEBUG{X}
-const vec3 vCascadeColorsMultiplier{X}[8]=vec3[8]
-(
-vec3 ( 1.5,0.0,0.0 ),
-vec3 ( 0.0,1.5,0.0 ),
-vec3 ( 0.0,0.0,5.5 ),
-vec3 ( 1.5,0.0,5.5 ),
-vec3 ( 1.5,1.5,0.0 ),
-vec3 ( 1.0,1.0,1.0 ),
-vec3 ( 0.0,1.0,5.5 ),
-vec3 ( 0.5,3.5,0.75 )
-);
-vec3 shadowDebug{X};
-#endif
-#ifdef SHADOWCSMUSESHADOWMAXZ{X}
-int index{X}=-1;
-#else
-int index{X}=SHADOWCSMNUM_CASCADES{X}-1;
-#endif
-float diff{X}=0.;
-#elif defined(SHADOWCUBE{X})
-uniform samplerCube shadowSampler{X};
-#else
-varying vec4 vPositionFromLight{X};
-varying float vDepthMetric{X};
-#if defined(SHADOWPCSS{X})
-uniform highp sampler2DShadow shadowSampler{X};
-uniform highp sampler2D depthSampler{X};
-#elif defined(SHADOWPCF{X})
-uniform highp sampler2DShadow shadowSampler{X};
-#else
-uniform sampler2D shadowSampler{X};
-#endif
-uniform mat4 lightMatrix{X};
-#endif
-#endif
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U="imageProcessingDeclaration",_=`#ifdef EXPOSURE
-uniform float exposureLinear;
-#endif
-#ifdef CONTRAST
-uniform float contrast;
-#endif
-#ifdef VIGNETTE
-uniform vec2 vInverseScreenSize;
-uniform vec4 vignetteSettings1;
-uniform vec4 vignetteSettings2;
-#endif
-#ifdef COLORCURVES
-uniform vec4 vCameraColorCurveNegative;
-uniform vec4 vCameraColorCurveNeutral;
-uniform vec4 vCameraColorCurvePositive;
-#endif
-#ifdef COLORGRADING
-#ifdef COLORGRADING3D
-uniform highp sampler3D txColorTransform;
-#else
-uniform sampler2D txColorTransform;
-#endif
-uniform vec4 colorTransformSettings;
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U="imageProcessingFunctions",_=`#if defined(COLORGRADING) && !defined(COLORGRADING3D)
-
-#define inline
-vec3 sampleTexture3D(sampler2D colorTransform,vec3 color,vec2 sampler3dSetting)
-{
-float sliceSize=2.0*sampler3dSetting.x;
-#ifdef SAMPLER3DGREENDEPTH
-float sliceContinuous=(color.g-sampler3dSetting.x)*sampler3dSetting.y;
-#else
-float sliceContinuous=(color.b-sampler3dSetting.x)*sampler3dSetting.y;
-#endif
-float sliceInteger=floor(sliceContinuous);
-
-
-float sliceFraction=sliceContinuous-sliceInteger;
-#ifdef SAMPLER3DGREENDEPTH
-vec2 sliceUV=color.rb;
-#else
-vec2 sliceUV=color.rg;
-#endif
-sliceUV.x*=sliceSize;
-sliceUV.x+=sliceInteger*sliceSize;
-sliceUV=saturate(sliceUV);
-vec4 slice0Color=texture2D(colorTransform,sliceUV);
-sliceUV.x+=sliceSize;
-sliceUV=saturate(sliceUV);
-vec4 slice1Color=texture2D(colorTransform,sliceUV);
-vec3 result=mix(slice0Color.rgb,slice1Color.rgb,sliceFraction);
-#ifdef SAMPLER3DBGRMAP
-color.rgb=result.rgb;
-#else
-color.rgb=result.bgr;
-#endif
-return color;
-}
-#endif
-#ifdef TONEMAPPING_ACES
-
-
-
-
-
-const mat3 ACESInputMat=mat3(
-vec3(0.59719,0.07600,0.02840),
-vec3(0.35458,0.90834,0.13383),
-vec3(0.04823,0.01566,0.83777)
-);
-
-const mat3 ACESOutputMat=mat3(
-vec3( 1.60475,-0.10208,-0.00327),
-vec3(-0.53108,1.10813,-0.07276),
-vec3(-0.07367,-0.00605,1.07602)
-);
-vec3 RRTAndODTFit(vec3 v)
-{
-vec3 a=v*(v+0.0245786)-0.000090537;
-vec3 b=v*(0.983729*v+0.4329510)+0.238081;
-return a/b;
-}
-vec3 ACESFitted(vec3 color)
-{
-color=ACESInputMat*color;
-
-color=RRTAndODTFit(color);
-color=ACESOutputMat*color;
-
-color=saturate(color);
-return color;
-}
-#endif
-vec4 applyImageProcessing(vec4 result) {
-#ifdef EXPOSURE
-result.rgb*=exposureLinear;
-#endif
-#ifdef VIGNETTE
-
-vec2 viewportXY=gl_FragCoord.xy*vInverseScreenSize;
-viewportXY=viewportXY*2.0-1.0;
-vec3 vignetteXY1=vec3(viewportXY*vignetteSettings1.xy+vignetteSettings1.zw,1.0);
-float vignetteTerm=dot(vignetteXY1,vignetteXY1);
-float vignette=pow(vignetteTerm,vignetteSettings2.w);
-
-vec3 vignetteColor=vignetteSettings2.rgb;
-#ifdef VIGNETTEBLENDMODEMULTIPLY
-vec3 vignetteColorMultiplier=mix(vignetteColor,vec3(1,1,1),vignette);
-result.rgb*=vignetteColorMultiplier;
-#endif
-#ifdef VIGNETTEBLENDMODEOPAQUE
-result.rgb=mix(vignetteColor,result.rgb,vignette);
-#endif
-#endif
-#ifdef TONEMAPPING
-#ifdef TONEMAPPING_ACES
-result.rgb=ACESFitted(result.rgb);
-#else
-const float tonemappingCalibration=1.590579;
-result.rgb=1.0-exp2(-tonemappingCalibration*result.rgb);
-#endif
-#endif
-
-result.rgb=toGammaSpace(result.rgb);
-result.rgb=saturate(result.rgb);
-#ifdef CONTRAST
-
-vec3 resultHighContrast=result.rgb*result.rgb*(3.0-2.0*result.rgb);
-if (contrast<1.0) {
-
-result.rgb=mix(vec3(0.5,0.5,0.5),result.rgb,contrast);
-} else {
-
-result.rgb=mix(result.rgb,resultHighContrast,contrast-1.0);
-}
-#endif
-
-#ifdef COLORGRADING
-vec3 colorTransformInput=result.rgb*colorTransformSettings.xxx+colorTransformSettings.yyy;
-#ifdef COLORGRADING3D
-vec3 colorTransformOutput=texture(txColorTransform,colorTransformInput).rgb;
-#else
-vec3 colorTransformOutput=sampleTexture3D(txColorTransform,colorTransformInput,colorTransformSettings.yz).rgb;
-#endif
-result.rgb=mix(result.rgb,colorTransformOutput,colorTransformSettings.www);
-#endif
-#ifdef COLORCURVES
-
-float luma=getLuminance(result.rgb);
-vec2 curveMix=clamp(vec2(luma*3.0-1.5,luma*-3.0+1.5),vec2(0.0),vec2(1.0));
-vec4 colorCurve=vCameraColorCurveNeutral+curveMix.x*vCameraColorCurvePositive-curveMix.y*vCameraColorCurveNegative;
-result.rgb*=colorCurve.rgb;
-result.rgb=mix(vec3(luma),result.rgb,colorCurve.a);
-#endif
-return result;
-}`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U="clipPlaneFragment",_=`#ifdef CLIPPLANE
-if (fClipDistance>0.0)
-{
-discard;
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-#endif
-#ifdef CLIPPLANE2
-if (fClipDistance2>0.0)
-{
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-#ifdef CLIPPLANE3
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-{
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-#ifdef CLIPPLANE4
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-{
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-{
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-{
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-#ifdef CLIPPLANE4
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-#ifdef CLIPPLANE5
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-#ifdef CLIPPLANE6
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-varying float fClipDistance;
-#endif
-#ifdef CLIPPLANE2
-varying float fClipDistance2;
-#endif
-#ifdef CLIPPLANE3
-varying float fClipDistance3;
-#endif
-#ifdef CLIPPLANE4
-varying float fClipDistance4;
-#endif
-#ifdef CLIPPLANE5
-varying float fClipDistance5;
-#endif
-#ifdef CLIPPLANE6
-varying float fClipDistance6;
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U="logDepthDeclaration",_=`#ifdef LOGARITHMICDEPTH
-uniform float logarithmicDepthConstant;
-varying float vFragmentDepth;
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U="clipPlaneVertexDeclaration",_=`#ifdef CLIPPLANE
-uniform vec4 vClipPlane;
-varying float fClipDistance;
-#endif
-#ifdef CLIPPLANE2
-uniform vec4 vClipPlane2;
-varying float fClipDistance2;
-#endif
-#ifdef CLIPPLANE3
-uniform vec4 vClipPlane3;
-varying float fClipDistance3;
-#endif
-#ifdef CLIPPLANE4
-uniform vec4 vClipPlane4;
-varying float fClipDistance4;
-#endif
-#ifdef CLIPPLANE5
-uniform vec4 vClipPlane5;
-varying float fClipDistance5;
-#endif
-#ifdef CLIPPLANE6
-uniform vec4 vClipPlane6;
-varying float fClipDistance6;
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.prototype.attributeProcessor=function(x){return x.replace("attribute","in")},_.prototype.varyingProcessor=function(x,u){return x.replace("varying",u?"in":"out")},_.prototype.postProcessor=function(x,u,M){var R=x.search(/#extension.+GL_EXT_draw_buffers.+require/)!==-1;if(x=(x=x.replace(/#extension.+(GL_OVR_multiview2|GL_OES_standard_derivatives|GL_EXT_shader_texture_lod|GL_EXT_frag_depth|GL_EXT_draw_buffers).+(enable|require)/g,"")).replace(/texture2D\s*\(/g,"texture("),M)x=(x=(x=(x=(x=(x=(x=x.replace(/texture2DLodEXT\s*\(/g,"textureLod(")).replace(/textureCubeLodEXT\s*\(/g,"textureLod(")).replace(/textureCube\s*\(/g,"texture(")).replace(/gl_FragDepthEXT/g,"gl_FragDepth")).replace(/gl_FragColor/g,"glFragColor")).replace(/gl_FragData/g,"glFragData")).replace(/void\s+?main\s*\(/g,(R?"":`out vec4 glFragColor;
-`)+"void main(");else if(u.indexOf("#define MULTIVIEW")!==-1)return`#extension GL_OVR_multiview2 : require
-layout (num_views = 2) in;
-`+x;return x},_}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.BindClipPlane=function(x,u){if(u.clipPlane){var M=u.clipPlane;x.setFloat4("vClipPlane",M.normal.x,M.normal.y,M.normal.z,M.d)}u.clipPlane2&&(M=u.clipPlane2,x.setFloat4("vClipPlane2",M.normal.x,M.normal.y,M.normal.z,M.d)),u.clipPlane3&&(M=u.clipPlane3,x.setFloat4("vClipPlane3",M.normal.x,M.normal.y,M.normal.z,M.d)),u.clipPlane4&&(M=u.clipPlane4,x.setFloat4("vClipPlane4",M.normal.x,M.normal.y,M.normal.z,M.d)),u.clipPlane5&&(M=u.clipPlane5,x.setFloat4("vClipPlane5",M.normal.x,M.normal.y,M.normal.z,M.d)),u.clipPlane6&&(M=u.clipPlane6,x.setFloat4("vClipPlane6",M.normal.x,M.normal.y,M.normal.z,M.d))},_}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.RandomId=function(){return"xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx".replace(/[xy]/g,function(x){var u=16*Math.random()|0;return(x==="x"?u:3&u|8).toString(16)})},_}()},function(Me,y,f){f.d(y,"a",function(){return u});var U=f(1),_=f(3),x=f(9),u=function(){function M(){this._dirty=!0,this._tempColor=new x.b(0,0,0,0),this._globalCurve=new x.b(0,0,0,0),this._highlightsCurve=new x.b(0,0,0,0),this._midtonesCurve=new x.b(0,0,0,0),this._shadowsCurve=new x.b(0,0,0,0),this._positiveCurve=new x.b(0,0,0,0),this._negativeCurve=new x.b(0,0,0,0),this._globalHue=30,this._globalDensity=0,this._globalSaturation=0,this._globalExposure=0,this._highlightsHue=30,this._highlightsDensity=0,this._highlightsSaturation=0,this._highlightsExposure=0,this._midtonesHue=30,this._midtonesDensity=0,this._midtonesSaturation=0,this._midtonesExposure=0,this._shadowsHue=30,this._shadowsDensity=0,this._shadowsSaturation=0,this._shadowsExposure=0}return Object.defineProperty(M.prototype,"globalHue",{get:function(){return this._globalHue},set:function(R){this._globalHue=R,this._dirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"globalDensity",{get:function(){return this._globalDensity},set:function(R){this._globalDensity=R,this._dirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"globalSaturation",{get:function(){return this._globalSaturation},set:function(R){this._globalSaturation=R,this._dirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"globalExposure",{get:function(){return this._globalExposure},set:function(R){this._globalExposure=R,this._dirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"highlightsHue",{get:function(){return this._highlightsHue},set:function(R){this._highlightsHue=R,this._dirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"highlightsDensity",{get:function(){return this._highlightsDensity},set:function(R){this._highlightsDensity=R,this._dirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"highlightsSaturation",{get:function(){return this._highlightsSaturation},set:function(R){this._highlightsSaturation=R,this._dirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"highlightsExposure",{get:function(){return this._highlightsExposure},set:function(R){this._highlightsExposure=R,this._dirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"midtonesHue",{get:function(){return this._midtonesHue},set:function(R){this._midtonesHue=R,this._dirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"midtonesDensity",{get:function(){return this._midtonesDensity},set:function(R){this._midtonesDensity=R,this._dirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"midtonesSaturation",{get:function(){return this._midtonesSaturation},set:function(R){this._midtonesSaturation=R,this._dirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"midtonesExposure",{get:function(){return this._midtonesExposure},set:function(R){this._midtonesExposure=R,this._dirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"shadowsHue",{get:function(){return this._shadowsHue},set:function(R){this._shadowsHue=R,this._dirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"shadowsDensity",{get:function(){return this._shadowsDensity},set:function(R){this._shadowsDensity=R,this._dirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"shadowsSaturation",{get:function(){return this._shadowsSaturation},set:function(R){this._shadowsSaturation=R,this._dirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"shadowsExposure",{get:function(){return this._shadowsExposure},set:function(R){this._shadowsExposure=R,this._dirty=!0},enumerable:!1,configurable:!0}),M.prototype.getClassName=function(){return"ColorCurves"},M.Bind=function(R,C,m,c,T){m===void 0&&(m="vCameraColorCurvePositive"),c===void 0&&(c="vCameraColorCurveNeutral"),T===void 0&&(T="vCameraColorCurveNegative"),R._dirty&&(R._dirty=!1,R.getColorGradingDataToRef(R._globalHue,R._globalDensity,R._globalSaturation,R._globalExposure,R._globalCurve),R.getColorGradingDataToRef(R._highlightsHue,R._highlightsDensity,R._highlightsSaturation,R._highlightsExposure,R._tempColor),R._tempColor.multiplyToRef(R._globalCurve,R._highlightsCurve),R.getColorGradingDataToRef(R._midtonesHue,R._midtonesDensity,R._midtonesSaturation,R._midtonesExposure,R._tempColor),R._tempColor.multiplyToRef(R._globalCurve,R._midtonesCurve),R.getColorGradingDataToRef(R._shadowsHue,R._shadowsDensity,R._shadowsSaturation,R._shadowsExposure,R._tempColor),R._tempColor.multiplyToRef(R._globalCurve,R._shadowsCurve),R._highlightsCurve.subtractToRef(R._midtonesCurve,R._positiveCurve),R._midtonesCurve.subtractToRef(R._shadowsCurve,R._negativeCurve)),C&&(C.setFloat4(m,R._positiveCurve.r,R._positiveCurve.g,R._positiveCurve.b,R._positiveCurve.a),C.setFloat4(c,R._midtonesCurve.r,R._midtonesCurve.g,R._midtonesCurve.b,R._midtonesCurve.a),C.setFloat4(T,R._negativeCurve.r,R._negativeCurve.g,R._negativeCurve.b,R._negativeCurve.a))},M.PrepareUniforms=function(R){R.push("vCameraColorCurveNeutral","vCameraColorCurvePositive","vCameraColorCurveNegative")},M.prototype.getColorGradingDataToRef=function(R,C,m,c,T){R!=null&&(R=M.clamp(R,0,360),C=M.clamp(C,-100,100),m=M.clamp(m,-100,100),c=M.clamp(c,-100,100),C=M.applyColorGradingSliderNonlinear(C),C*=.5,c=M.applyColorGradingSliderNonlinear(c),C<0&&(C*=-1,R=(R+180)%360),M.fromHSBToRef(R,C,50+.25*c,T),T.scaleToRef(2,T),T.a=1+.01*m)},M.applyColorGradingSliderNonlinear=function(R){R/=100;var C=Math.abs(R);return C=Math.pow(C,2),R<0&&(C*=-1),C*=100},M.fromHSBToRef=function(R,C,m,c){var T=M.clamp(R,0,360),A=M.clamp(C/100,0,1),S=M.clamp(m/100,0,1);if(A===0)c.r=S,c.g=S,c.b=S;else{T/=60;var g=Math.floor(T),l=T-g,h=S*(1-A),v=S*(1-A*l),E=S*(1-A*(1-l));switch(g){case 0:c.r=S,c.g=E,c.b=h;break;case 1:c.r=v,c.g=S,c.b=h;break;case 2:c.r=h,c.g=S,c.b=E;break;case 3:c.r=h,c.g=v,c.b=S;break;case 4:c.r=E,c.g=h,c.b=S;break;default:c.r=S,c.g=h,c.b=v}}c.a=1},M.clamp=function(R,C,m){return Math.min(Math.max(R,C),m)},M.prototype.clone=function(){return _.a.Clone(function(){return new M},this)},M.prototype.serialize=function(){return _.a.Serialize(this)},M.Parse=function(R){return _.a.Parse(function(){return new M},R,null,null)},Object(U.c)([Object(_.c)()],M.prototype,"_globalHue",void 0),Object(U.c)([Object(_.c)()],M.prototype,"_globalDensity",void 0),Object(U.c)([Object(_.c)()],M.prototype,"_globalSaturation",void 0),Object(U.c)([Object(_.c)()],M.prototype,"_globalExposure",void 0),Object(U.c)([Object(_.c)()],M.prototype,"_highlightsHue",void 0),Object(U.c)([Object(_.c)()],M.prototype,"_highlightsDensity",void 0),Object(U.c)([Object(_.c)()],M.prototype,"_highlightsSaturation",void 0),Object(U.c)([Object(_.c)()],M.prototype,"_highlightsExposure",void 0),Object(U.c)([Object(_.c)()],M.prototype,"_midtonesHue",void 0),Object(U.c)([Object(_.c)()],M.prototype,"_midtonesDensity",void 0),Object(U.c)([Object(_.c)()],M.prototype,"_midtonesSaturation",void 0),Object(U.c)([Object(_.c)()],M.prototype,"_midtonesExposure",void 0),M}();_.a._ColorCurvesParser=u.Parse},function(Me,y,f){f.d(y,"a",function(){return x});var U=f(8),_=f(11),x=function(){function u(){}return u.Instantiate=function(M){if(this.RegisteredExternalClasses&&this.RegisteredExternalClasses[M])return this.RegisteredExternalClasses[M];var R=_.a.GetClass(M);if(R)return R;U.a.Warn(M+" not found, you may have missed an import.");for(var C=M.split("."),m=window||this,c=0,T=C.length;c<T;c++)m=m[C[c]];return typeof m!="function"?null:m},u.RegisteredExternalClasses={},u}()},function(Me,y,f){var U=f(26),_=f(2);U.a.prototype.setAlphaConstants=function(x,u,M,R){this._alphaState.setAlphaBlendConstants(x,u,M,R)},U.a.prototype.setAlphaMode=function(x,u){if(u===void 0&&(u=!1),this._alphaMode!==x){switch(x){case _.a.ALPHA_DISABLE:this._alphaState.alphaBlend=!1;break;case _.a.ALPHA_PREMULTIPLIED:this._alphaState.setAlphaBlendFunctionParameters(this._gl.ONE,this._gl.ONE_MINUS_SRC_ALPHA,this._gl.ONE,this._gl.ONE),this._alphaState.alphaBlend=!0;break;case _.a.ALPHA_PREMULTIPLIED_PORTERDUFF:this._alphaState.setAlphaBlendFunctionParameters(this._gl.ONE,this._gl.ONE_MINUS_SRC_ALPHA,this._gl.ONE,this._gl.ONE_MINUS_SRC_ALPHA),this._alphaState.alphaBlend=!0;break;case _.a.ALPHA_COMBINE:this._alphaState.setAlphaBlendFunctionParameters(this._gl.SRC_ALPHA,this._gl.ONE_MINUS_SRC_ALPHA,this._gl.ONE,this._gl.ONE),this._alphaState.alphaBlend=!0;break;case 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_.a.ALPHA_INTERPOLATE:this._alphaState.setAlphaBlendFunctionParameters(this._gl.CONSTANT_COLOR,this._gl.ONE_MINUS_CONSTANT_COLOR,this._gl.CONSTANT_ALPHA,this._gl.ONE_MINUS_CONSTANT_ALPHA),this._alphaState.alphaBlend=!0;break;case _.a.ALPHA_SCREENMODE:this._alphaState.setAlphaBlendFunctionParameters(this._gl.ONE,this._gl.ONE_MINUS_SRC_COLOR,this._gl.ONE,this._gl.ONE_MINUS_SRC_ALPHA),this._alphaState.alphaBlend=!0;break;case _.a.ALPHA_ONEONE_ONEONE:this._alphaState.setAlphaBlendFunctionParameters(this._gl.ONE,this._gl.ONE,this._gl.ONE,this._gl.ONE),this._alphaState.alphaBlend=!0;break;case _.a.ALPHA_ALPHATOCOLOR:this._alphaState.setAlphaBlendFunctionParameters(this._gl.DST_ALPHA,this._gl.ONE,this._gl.ZERO,this._gl.ZERO),this._alphaState.alphaBlend=!0;break;case 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-#define FOGMODE_EXP 1.
-#define FOGMODE_EXP2 2.
-#define FOGMODE_LINEAR 3.
-#define E 2.71828
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-{
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-float fogStart=vFogInfos.y;
-float fogEnd=vFogInfos.z;
-float fogDensity=vFogInfos.w;
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-{
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-{
-fogCoeff=1.0/pow(E,fogDistance*fogDistance*fogDensity*fogDensity);
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i.children.push(n),e&&e.children.push(i),i}return e&&e.children.push(n),n},r._SerializeValueAsString=function(t){return typeof t=="number"?t.toString():typeof t=="boolean"?t?"true":"false":t instanceof u.d?t.x+", "+t.y:t instanceof u.e?t.x+", "+t.y+", "+t.z:t instanceof M.a?t.r+", "+t.g+", "+t.b:t instanceof M.b?t.r+", "+t.g+", "+t.b+", "+t.a:t},r._GetTargetProperty=function(t){return{name:"target",targetType:t._isMesh?"MeshProperties":t._isLight?"LightProperties":t._isCamera?"CameraProperties":"SceneProperties",value:t._isScene?"Scene":t.name}},r}();R.a.RegisteredTypes["BABYLON.Action"]=C;var m=f(47),c=f(1),T=function(){function r(t){this._actionManager=t}return r.prototype.isValid=function(){return!0},r.prototype._getProperty=function(t){return this._actionManager._getProperty(t)},r.prototype._getEffectiveTarget=function(t,e){return this._actionManager._getEffectiveTarget(t,e)},r.prototype.serialize=function(){},r.prototype._serialize=function(t){return{type:2,children:[],name:t.name,properties:t.properties}},r}(),A=function(r){function t(e,n,i,o,a){a===void 0&&(a=t.IsEqual);var s=r.call(this,e)||this;return s.propertyPath=i,s.value=o,s.operator=a,s._target=n,s._effectiveTarget=s._getEffectiveTarget(n,s.propertyPath),s._property=s._getProperty(s.propertyPath),s}return Object(c.d)(t,r),Object.defineProperty(t,"IsEqual",{get:function(){return t._IsEqual},enumerable:!1,configurable:!0}),Object.defineProperty(t,"IsDifferent",{get:function(){return t._IsDifferent},enumerable:!1,configurable:!0}),Object.defineProperty(t,"IsGreater",{get:function(){return t._IsGreater},enumerable:!1,configurable:!0}),Object.defineProperty(t,"IsLesser",{get:function(){return t._IsLesser},enumerable:!1,configurable:!0}),t.prototype.isValid=function(){switch(this.operator){case t.IsGreater:return this._effectiveTarget[this._property]>this.value;case t.IsLesser:return this._effectiveTarget[this._property]<this.value;case t.IsEqual:case t.IsDifferent:var e;return e=this.value.equals?this.value.equals(this._effectiveTarget[this._property]):this.value===this._effectiveTarget[this._property],this.operator===t.IsEqual?e:!e}return!1},t.prototype.serialize=function(){return this._serialize({name:"ValueCondition",properties:[C._GetTargetProperty(this._target),{name:"propertyPath",value:this.propertyPath},{name:"value",value:C._SerializeValueAsString(this.value)},{name:"operator",value:t.GetOperatorName(this.operator)}]})},t.GetOperatorName=function(e){switch(e){case t._IsEqual:return"IsEqual";case t._IsDifferent:return"IsDifferent";case t._IsGreater:return"IsGreater";case t._IsLesser:return"IsLesser";default:return""}},t._IsEqual=0,t._IsDifferent=1,t._IsGreater=2,t._IsLesser=3,t}(T),S=function(r){function t(e,n){var i=r.call(this,e)||this;return i.predicate=n,i}return Object(c.d)(t,r),t.prototype.isValid=function(){return this.predicate()},t}(T),g=function(r){function t(e,n,i){var o=r.call(this,e)||this;return o.value=i,o._target=n,o}return Object(c.d)(t,r),t.prototype.isValid=function(){return this._target.state===this.value},t.prototype.serialize=function(){return this._serialize({name:"StateCondition",properties:[C._GetTargetProperty(this._target),{name:"value",value:this.value}]})},t}(T);R.a.RegisteredTypes["BABYLON.ValueCondition"]=A,R.a.RegisteredTypes["BABYLON.PredicateCondition"]=S,R.a.RegisteredTypes["BABYLON.StateCondition"]=g;var l=f(8),h=f(2),v=function(r){function t(e,n,i,o){var a=r.call(this,e,o)||this;return a.propertyPath=i,a._target=a._effectiveTarget=n,a}return Object(c.d)(t,r),t.prototype._prepare=function(){this._effectiveTarget=this._getEffectiveTarget(this._effectiveTarget,this.propertyPath),this._property=this._getProperty(this.propertyPath)},t.prototype.execute=function(){this._effectiveTarget[this._property]=!this._effectiveTarget[this._property]},t.prototype.serialize=function(e){return r.prototype._serialize.call(this,{name:"SwitchBooleanAction",properties:[C._GetTargetProperty(this._target),{name:"propertyPath",value:this.propertyPath}]},e)},t}(C),E=function(r){function t(e,n,i,o){var a=r.call(this,e,o)||this;return a.value=i,a._target=n,a}return Object(c.d)(t,r),t.prototype.execute=function(){this._target.state=this.value},t.prototype.serialize=function(e){return r.prototype._serialize.call(this,{name:"SetStateAction",properties:[C._GetTargetProperty(this._target),{name:"value",value:this.value}]},e)},t}(C),D=function(r){function t(e,n,i,o,a){var s=r.call(this,e,a)||this;return s.propertyPath=i,s.value=o,s._target=s._effectiveTarget=n,s}return Object(c.d)(t,r),t.prototype._prepare=function(){this._effectiveTarget=this._getEffectiveTarget(this._effectiveTarget,this.propertyPath),this._property=this._getProperty(this.propertyPath)},t.prototype.execute=function(){this._effectiveTarget[this._property]=this.value,this._target.markAsDirty&&this._target.markAsDirty(this._property)},t.prototype.serialize=function(e){return r.prototype._serialize.call(this,{name:"SetValueAction",properties:[C._GetTargetProperty(this._target),{name:"propertyPath",value:this.propertyPath},{name:"value",value:C._SerializeValueAsString(this.value)}]},e)},t}(C),w=function(r){function t(e,n,i,o,a){var s=r.call(this,e,a)||this;return s.propertyPath=i,s.value=o,s._target=s._effectiveTarget=n,s}return Object(c.d)(t,r),t.prototype._prepare=function(){this._effectiveTarget=this._getEffectiveTarget(this._effectiveTarget,this.propertyPath),this._property=this._getProperty(this.propertyPath),typeof this._effectiveTarget[this._property]!="number"&&l.a.Warn("Warning: IncrementValueAction can only be used with number values")},t.prototype.execute=function(){this._effectiveTarget[this._property]+=this.value,this._target.markAsDirty&&this._target.markAsDirty(this._property)},t.prototype.serialize=function(e){return r.prototype._serialize.call(this,{name:"IncrementValueAction",properties:[C._GetTargetProperty(this._target),{name:"propertyPath",value:this.propertyPath},{name:"value",value:C._SerializeValueAsString(this.value)}]},e)},t}(C),N=function(r){function t(e,n,i,o,a,s){var d=r.call(this,e,s)||this;return d.from=i,d.to=o,d.loop=a,d._target=n,d}return Object(c.d)(t,r),t.prototype._prepare=function(){},t.prototype.execute=function(){this._actionManager.getScene().beginAnimation(this._target,this.from,this.to,this.loop)},t.prototype.serialize=function(e){return r.prototype._serialize.call(this,{name:"PlayAnimationAction",properties:[C._GetTargetProperty(this._target),{name:"from",value:String(this.from)},{name:"to",value:String(this.to)},{name:"loop",value:C._SerializeValueAsString(this.loop)||!1}]},e)},t}(C),I=function(r){function t(e,n,i){var o=r.call(this,e,i)||this;return o._target=n,o}return Object(c.d)(t,r),t.prototype._prepare=function(){},t.prototype.execute=function(){this._actionManager.getScene().stopAnimation(this._target)},t.prototype.serialize=function(e){return r.prototype._serialize.call(this,{name:"StopAnimationAction",properties:[C._GetTargetProperty(this._target)]},e)},t}(C),V=function(r){function t(e,n){return e===void 0&&(e=h.a.ACTION_NothingTrigger),r.call(this,e,n)||this}return Object(c.d)(t,r),t.prototype.execute=function(){},t.prototype.serialize=function(e){return r.prototype._serialize.call(this,{name:"DoNothingAction",properties:[]},e)},t}(C),X=function(r){function t(e,n,i){var o=r.call(this,e,i)||this;return o.children=n,o}return Object(c.d)(t,r),t.prototype._prepare=function(){for(var e=0;e<this.children.length;e++)this.children[e]._actionManager=this._actionManager,this.children[e]._prepare()},t.prototype.execute=function(e){for(var n=0;n<this.children.length;n++)this.children[n].execute(e)},t.prototype.serialize=function(e){for(var n=r.prototype._serialize.call(this,{name:"CombineAction",properties:[],combine:[]},e),i=0;i<this.children.length;i++)n.combine.push(this.children[i].serialize(null));return n},t}(C),j=function(r){function t(e,n,i){var o=r.call(this,e,i)||this;return o.func=n,o}return Object(c.d)(t,r),t.prototype.execute=function(e){this.func(e)},t}(C),ne=function(r){function t(e,n,i,o){var a=r.call(this,e,o)||this;return a._target=n,a._parent=i,a}return Object(c.d)(t,r),t.prototype._prepare=function(){},t.prototype.execute=function(){if(this._target.parent!==this._parent){var e=this._parent.getWorldMatrix().clone();e.invert(),this._target.position=u.e.TransformCoordinates(this._target.position,e),this._target.parent=this._parent}},t.prototype.serialize=function(e){return r.prototype._serialize.call(this,{name:"SetParentAction",properties:[C._GetTargetProperty(this._target),C._GetTargetProperty(this._parent)]},e)},t}(C);R.a.RegisteredTypes["BABYLON.SetParentAction"]=ne,R.a.RegisteredTypes["BABYLON.ExecuteCodeAction"]=j,R.a.RegisteredTypes["BABYLON.DoNothingAction"]=V,R.a.RegisteredTypes["BABYLON.StopAnimationAction"]=I,R.a.RegisteredTypes["BABYLON.PlayAnimationAction"]=N,R.a.RegisteredTypes["BABYLON.IncrementValueAction"]=w,R.a.RegisteredTypes["BABYLON.SetValueAction"]=D,R.a.RegisteredTypes["BABYLON.SetStateAction"]=E,R.a.RegisteredTypes["BABYLON.SetParentAction"]=ne;var te=f(22),de=f(41),pe=function(r){function t(e){var n=r.call(this)||this;return n._scene=e||te.a.LastCreatedScene,e.actionManagers.push(n),n}return Object(c.d)(t,r),t.prototype.dispose=function(){for(var e=this._scene.actionManagers.indexOf(this),n=0;n<this.actions.length;n++){var i=this.actions[n];t.Triggers[i.trigger]--,t.Triggers[i.trigger]===0&&delete t.Triggers[i.trigger]}e>-1&&this._scene.actionManagers.splice(e,1)},t.prototype.getScene=function(){return this._scene},t.prototype.hasSpecificTriggers=function(e){for(var n=0;n<this.actions.length;n++){var i=this.actions[n];if(e.indexOf(i.trigger)>-1)return!0}return!1},t.prototype.hasSpecificTriggers2=function(e,n){for(var i=0;i<this.actions.length;i++){var o=this.actions[i];if(e==o.trigger||n==o.trigger)return!0}return!1},t.prototype.hasSpecificTrigger=function(e,n){for(var i=0;i<this.actions.length;i++){var o=this.actions[i];if(o.trigger===e&&(!n||n(o.getTriggerParameter())))return!0}return!1},Object.defineProperty(t.prototype,"hasPointerTriggers",{get:function(){for(var e=0;e<this.actions.length;e++){var n=this.actions[e];if(n.trigger>=t.OnPickTrigger&&n.trigger<=t.OnPointerOutTrigger)return!0}return!1},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"hasPickTriggers",{get:function(){for(var e=0;e<this.actions.length;e++){var n=this.actions[e];if(n.trigger>=t.OnPickTrigger&&n.trigger<=t.OnPickUpTrigger)return!0}return!1},enumerable:!1,configurable:!0}),t.prototype.registerAction=function(e){return e.trigger===t.OnEveryFrameTrigger&&this.getScene().actionManager!==this?(l.a.Warn("OnEveryFrameTrigger can only be used with scene.actionManager"),null):(this.actions.push(e),t.Triggers[e.trigger]?t.Triggers[e.trigger]++:t.Triggers[e.trigger]=1,e._actionManager=this,e._prepare(),e)},t.prototype.unregisterAction=function(e){var n=this.actions.indexOf(e);return n!==-1&&(this.actions.splice(n,1),t.Triggers[e.trigger]-=1,t.Triggers[e.trigger]===0&&delete t.Triggers[e.trigger],e._actionManager=null,!0)},t.prototype.processTrigger=function(e,n){for(var i=0;i<this.actions.length;i++){var o=this.actions[i];if(o.trigger===e){if(n&&(e===t.OnKeyUpTrigger||e===t.OnKeyDownTrigger)){var a=o.getTriggerParameter();if(a&&a!==n.sourceEvent.keyCode){if(!a.toLowerCase)continue;var s=a.toLowerCase();if(s!==n.sourceEvent.key){var d=n.sourceEvent.charCode?n.sourceEvent.charCode:n.sourceEvent.keyCode;if(String.fromCharCode(d).toLowerCase()!==s)continue}}}o._executeCurrent(n)}}},t.prototype._getEffectiveTarget=function(e,n){for(var i=n.split("."),o=0;o<i.length-1;o++)e=e[i[o]];return e},t.prototype._getProperty=function(e){var n=e.split(".");return n[n.length-1]},t.prototype.serialize=function(e){for(var n={children:new Array,name:e,type:3,properties:new Array},i=0;i<this.actions.length;i++){var o={type:0,children:new Array,name:t.GetTriggerName(this.actions[i].trigger),properties:new Array},a=this.actions[i].triggerOptions;if(a&&typeof a!="number")if(a.parameter instanceof Node)o.properties.push(C._GetTargetProperty(a.parameter));else{var s={};de.a.DeepCopy(a.parameter,s,["mesh"]),a.parameter&&a.parameter.mesh&&(s._meshId=a.parameter.mesh.id),o.properties.push({name:"parameter",targetType:null,value:s})}this.actions[i].serialize(o),n.children.push(o)}return n},t.Parse=function(e,n,i){var o=new t(i);n===null?i.actionManager=o:n.actionManager=o;for(var a=function(F,z,J,ie){if(ie===null){var se=parseFloat(z);return z==="true"||z==="false"?z==="true":isNaN(se)?z:se}for(var ce=ie.split("."),ue=z.split(","),fe=0;fe<ce.length;fe++)J=J[ce[fe]];if(typeof J=="boolean")return ue[0]==="true";if(typeof J=="string")return ue[0];var ve=new Array;for(fe=0;fe<ue.length;fe++)ve.push(parseFloat(ue[fe]));return J instanceof u.e?u.e.FromArray(ve):J instanceof u.f?u.f.FromArray(ve):J instanceof M.a?M.a.FromArray(ve):J instanceof M.b?M.b.FromArray(ve):parseFloat(ue[0])},s=function(F,z,J,ie,se){if(se===void 0&&(se=null),!F.detached){var ce=new Array,ue=null,fe=null,ve=F.combine&&F.combine.length>0;if(F.type===2?ce.push(o):ce.push(z),ve){for(var Te=new Array,Re=0;Re<F.combine.length;Re++)s(F.combine[Re],t.NothingTrigger,J,ie,Te);ce.push(Te)}else for(var Ae=0;Ae<F.properties.length;Ae++){var Ee=F.properties[Ae].value,Se=F.properties[Ae].name,Le=F.properties[Ae].targetType;Se==="target"?Ee=ue=Le!==null&&Le==="SceneProperties"?i:i.getNodeByName(Ee):Se==="parent"?Ee=i.getNodeByName(Ee):Se==="sound"?i.getSoundByName&&(Ee=i.getSoundByName(Ee)):Se!=="propertyPath"?Ee=F.type===2&&Se==="operator"?A[Ee]:a(0,Ee,ue,Se==="value"?fe:null):fe=Ee,ce.push(Ee)}if(se===null?ce.push(J):ce.push(null),F.name==="InterpolateValueAction"){var Ce=ce[ce.length-2];ce[ce.length-1]=Ce,ce[ce.length-2]=J}var Ne=function(Fe,Ye){var tt=R.a.GetClass("BABYLON."+Fe);if(tt){var it=Object.create(tt.prototype);return it.constructor.apply(it,Ye),it}}(F.name,ce);if(Ne instanceof T&&J!==null){var Ie=new V(z,J);ie?ie.then(Ie):o.registerAction(Ie),ie=Ie}for(se===null?Ne instanceof T?(J=Ne,Ne=ie):(J=null,ie?ie.then(Ne):o.registerAction(Ne)):se.push(Ne),Ae=0;Ae<F.children.length;Ae++)s(F.children[Ae],z,J,Ne,null)}},d=0;d<e.children.length;d++){var p,b=e.children[d];if(b.properties.length>0){var P=b.properties[0].value,O=b.properties[0].targetType===null?P:i.getMeshByName(P);O._meshId&&(O.mesh=i.getMeshByID(O._meshId)),p={trigger:t[b.name],parameter:O}}else p=t[b.name];for(var B=0;B<b.children.length;B++)b.detached||s(b.children[B],p,null,null)}},t.GetTriggerName=function(e){switch(e){case 0:return"NothingTrigger";case 1:return"OnPickTrigger";case 2:return"OnLeftPickTrigger";case 3:return"OnRightPickTrigger";case 4:return"OnCenterPickTrigger";case 5:return"OnPickDownTrigger";case 6:return"OnPickUpTrigger";case 7:return"OnLongPressTrigger";case 8:return"OnPointerOverTrigger";case 9:return"OnPointerOutTrigger";case 10:return"OnEveryFrameTrigger";case 11:return"OnIntersectionEnterTrigger";case 12:return"OnIntersectionExitTrigger";case 13:return"OnKeyDownTrigger";case 14:return"OnKeyUpTrigger";case 15:return"OnPickOutTrigger";default:return""}},t.NothingTrigger=h.a.ACTION_NothingTrigger,t.OnPickTrigger=h.a.ACTION_OnPickTrigger,t.OnLeftPickTrigger=h.a.ACTION_OnLeftPickTrigger,t.OnRightPickTrigger=h.a.ACTION_OnRightPickTrigger,t.OnCenterPickTrigger=h.a.ACTION_OnCenterPickTrigger,t.OnPickDownTrigger=h.a.ACTION_OnPickDownTrigger,t.OnDoublePickTrigger=h.a.ACTION_OnDoublePickTrigger,t.OnPickUpTrigger=h.a.ACTION_OnPickUpTrigger,t.OnPickOutTrigger=h.a.ACTION_OnPickOutTrigger,t.OnLongPressTrigger=h.a.ACTION_OnLongPressTrigger,t.OnPointerOverTrigger=h.a.ACTION_OnPointerOverTrigger,t.OnPointerOutTrigger=h.a.ACTION_OnPointerOutTrigger,t.OnEveryFrameTrigger=h.a.ACTION_OnEveryFrameTrigger,t.OnIntersectionEnterTrigger=h.a.ACTION_OnIntersectionEnterTrigger,t.OnIntersectionExitTrigger=h.a.ACTION_OnIntersectionExitTrigger,t.OnKeyDownTrigger=h.a.ACTION_OnKeyDownTrigger,t.OnKeyUpTrigger=15,t}(_.a),ae=function(r){function t(e,n,i){var o=r.call(this,e,i)||this;return o._sound=n,o}return Object(c.d)(t,r),t.prototype._prepare=function(){},t.prototype.execute=function(){this._sound!==void 0&&this._sound.play()},t.prototype.serialize=function(e){return r.prototype._serialize.call(this,{name:"PlaySoundAction",properties:[{name:"sound",value:this._sound.name}]},e)},t}(C),ee=function(r){function t(e,n,i){var o=r.call(this,e,i)||this;return o._sound=n,o}return Object(c.d)(t,r),t.prototype._prepare=function(){},t.prototype.execute=function(){this._sound!==void 0&&this._sound.stop()},t.prototype.serialize=function(e){return r.prototype._serialize.call(this,{name:"StopSoundAction",properties:[{name:"sound",value:this._sound.name}]},e)},t}(C);R.a.RegisteredTypes["BABYLON.PlaySoundAction"]=ee,R.a.RegisteredTypes["BABYLON.StopSoundAction"]=ee;var K,$=f(14),L=f(3);(function(r){r[r.STEP=1]="STEP"})(K||(K={}));var G=function(){function r(t,e,n){this.name=t,this.from=e,this.to=n}return r.prototype.clone=function(){return new r(this.name,this.from,this.to)},r}(),Q=f(29),oe=f(77),re=f(49),Y=function(){},k=function(){function r(t,e,n,i,o,a){this.name=t,this.targetProperty=e,this.framePerSecond=n,this.dataType=i,this.loopMode=o,this.enableBlending=a,this._runtimeAnimations=new Array,this._events=new Array,this.blendingSpeed=.01,this._ranges={},this.targetPropertyPath=e.split("."),this.dataType=i,this.loopMode=o===void 0?r.ANIMATIONLOOPMODE_CYCLE:o}return r._PrepareAnimation=function(t,e,n,i,o,a,s,d){var p=void 0;if(!isNaN(parseFloat(o))&&isFinite(o)?p=r.ANIMATIONTYPE_FLOAT:o instanceof u.b?p=r.ANIMATIONTYPE_QUATERNION:o instanceof u.e?p=r.ANIMATIONTYPE_VECTOR3:o instanceof u.d?p=r.ANIMATIONTYPE_VECTOR2:o instanceof M.a?p=r.ANIMATIONTYPE_COLOR3:o instanceof M.b?p=r.ANIMATIONTYPE_COLOR4:o instanceof oe.a&&(p=r.ANIMATIONTYPE_SIZE),p==null)return null;var b=new r(t,e,n,p,s),P=[{frame:0,value:o},{frame:i,value:a}];return b.setKeys(P),d!==void 0&&b.setEasingFunction(d),b},r.CreateAnimation=function(t,e,n,i){var o=new r(t+"Animation",t,n,e,r.ANIMATIONLOOPMODE_CONSTANT);return o.setEasingFunction(i),o},r.CreateAndStartAnimation=function(t,e,n,i,o,a,s,d,p,b){var P=r._PrepareAnimation(t,n,i,o,a,s,d,p);return P?e.getScene().beginDirectAnimation(e,[P],0,o,P.loopMode===1,1,b):null},r.CreateAndStartHierarchyAnimation=function(t,e,n,i,o,a,s,d,p,b,P){var O=r._PrepareAnimation(t,i,o,a,s,d,p,b);return O?e.getScene().beginDirectHierarchyAnimation(e,n,[O],0,a,O.loopMode===1,1,P):null},r.CreateMergeAndStartAnimation=function(t,e,n,i,o,a,s,d,p,b){var P=r._PrepareAnimation(t,n,i,o,a,s,d,p);return P?(e.animations.push(P),e.getScene().beginAnimation(e,0,o,P.loopMode===1,1,b)):null},r.MakeAnimationAdditive=function(t,e,n,i,o){e===void 0&&(e=0),i===void 0&&(i=!1);var a=t;if(i&&((a=t.clone()).name=o||a.name),!a._keys.length)return a;e=e>=0?e:0;var s=0,d=a._keys[0],p=a._keys.length-1,b=a._keys[p],P={referenceValue:d.value,referencePosition:u.c.Vector3[0],referenceQuaternion:u.c.Quaternion[0],referenceScaling:u.c.Vector3[1],keyPosition:u.c.Vector3[2],keyQuaternion:u.c.Quaternion[1],keyScaling:u.c.Vector3[3]},O=!1,B=d.frame,F=b.frame;if(n){var z=a.getRange(n);z&&(B=z.from,F=z.to)}var J=d.frame===B,ie=b.frame===F;if(a._keys.length===1){var se=a._getKeyValue(a._keys[0]);P.referenceValue=se.clone?se.clone():se,O=!0}else e<=d.frame?(se=a._getKeyValue(d.value),P.referenceValue=se.clone?se.clone():se,O=!0):e>=b.frame&&(se=a._getKeyValue(b.value),P.referenceValue=se.clone?se.clone():se,O=!0);for(var ce=0;!O||!J||!ie&&ce<a._keys.length-1;){var ue=a._keys[ce],fe=a._keys[ce+1];if(!O&&e>=ue.frame&&e<=fe.frame){if(se=void 0,e===ue.frame)se=a._getKeyValue(ue.value);else if(e===fe.frame)se=a._getKeyValue(fe.value);else{var ve={key:ce,repeatCount:0,loopMode:this.ANIMATIONLOOPMODE_CONSTANT};se=a._interpolate(e,ve)}P.referenceValue=se.clone?se.clone():se,O=!0}if(!J&&B>=ue.frame&&B<=fe.frame){if(B===ue.frame)s=ce;else if(B===fe.frame)s=ce+1;else{ve={key:ce,repeatCount:0,loopMode:this.ANIMATIONLOOPMODE_CONSTANT};var Te={frame:B,value:(se=a._interpolate(B,ve)).clone?se.clone():se};a._keys.splice(ce+1,0,Te),s=ce+1}J=!0}!ie&&F>=ue.frame&&F<=fe.frame&&(F===ue.frame?p=ce:F===fe.frame?p=ce+1:(ve={key:ce,repeatCount:0,loopMode:this.ANIMATIONLOOPMODE_CONSTANT},Te={frame:F,value:(se=a._interpolate(F,ve)).clone?se.clone():se},a._keys.splice(ce+1,0,Te),p=ce+1),ie=!0),ce++}for(a.dataType===r.ANIMATIONTYPE_QUATERNION?P.referenceValue.normalize().conjugateInPlace():a.dataType===r.ANIMATIONTYPE_MATRIX&&(P.referenceValue.decompose(P.referenceScaling,P.referenceQuaternion,P.referencePosition),P.referenceQuaternion.normalize().conjugateInPlace()),ce=s;ce<=p;ce++)if(Te=a._keys[ce],!ce||a.dataType===r.ANIMATIONTYPE_FLOAT||Te.value!==d.value)switch(a.dataType){case r.ANIMATIONTYPE_MATRIX:Te.value.decompose(P.keyScaling,P.keyQuaternion,P.keyPosition),P.keyPosition.subtractInPlace(P.referencePosition),P.keyScaling.divideInPlace(P.referenceScaling),P.referenceQuaternion.multiplyToRef(P.keyQuaternion,P.keyQuaternion),u.a.ComposeToRef(P.keyScaling,P.keyQuaternion,P.keyPosition,Te.value);break;case r.ANIMATIONTYPE_QUATERNION:P.referenceValue.multiplyToRef(Te.value,Te.value);break;case r.ANIMATIONTYPE_VECTOR2:case r.ANIMATIONTYPE_VECTOR3:case r.ANIMATIONTYPE_COLOR3:case r.ANIMATIONTYPE_COLOR4:Te.value.subtractToRef(P.referenceValue,Te.value);break;case r.ANIMATIONTYPE_SIZE:Te.value.width-=P.referenceValue.width,Te.value.height-=P.referenceValue.height;break;default:Te.value-=P.referenceValue}return a},r.TransitionTo=function(t,e,n,i,o,a,s,d){if(d===void 0&&(d=null),s<=0)return n[t]=e,d&&d(),null;var p=o*(s/1e3);a.setKeys([{frame:0,value:n[t].clone?n[t].clone():n[t]},{frame:p,value:e}]),n.animations||(n.animations=[]),n.animations.push(a);var b=i.beginAnimation(n,0,p,!1);return b.onAnimationEnd=d,b},Object.defineProperty(r.prototype,"runtimeAnimations",{get:function(){return this._runtimeAnimations},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hasRunningRuntimeAnimations",{get:function(){for(var t=0,e=this._runtimeAnimations;t<e.length;t++)if(!e[t].isStopped)return!0;return!1},enumerable:!1,configurable:!0}),r.prototype.toString=function(t){var e="Name: "+this.name+", property: "+this.targetProperty;if(e+=", datatype: "+["Float","Vector3","Quaternion","Matrix","Color3","Vector2"][this.dataType],e+=", nKeys: "+(this._keys?this._keys.length:"none"),e+=", nRanges: "+(this._ranges?Object.keys(this._ranges).length:"none"),t){e+=", Ranges: {";var n=!0;for(var i in this._ranges)n&&(e+=", ",n=!1),e+=i;e+="}"}return e},r.prototype.addEvent=function(t){this._events.push(t),this._events.sort(function(e,n){return e.frame-n.frame})},r.prototype.removeEvents=function(t){for(var e=0;e<this._events.length;e++)this._events[e].frame===t&&(this._events.splice(e,1),e--)},r.prototype.getEvents=function(){return this._events},r.prototype.createRange=function(t,e,n){this._ranges[t]||(this._ranges[t]=new G(t,e,n))},r.prototype.deleteRange=function(t,e){e===void 0&&(e=!0);var n=this._ranges[t];if(n){if(e)for(var i=n.from,o=n.to,a=this._keys.length-1;a>=0;a--)this._keys[a].frame>=i&&this._keys[a].frame<=o&&this._keys.splice(a,1);this._ranges[t]=null}},r.prototype.getRange=function(t){return this._ranges[t]},r.prototype.getKeys=function(){return this._keys},r.prototype.getHighestFrame=function(){for(var t=0,e=0,n=this._keys.length;e<n;e++)t<this._keys[e].frame&&(t=this._keys[e].frame);return t},r.prototype.getEasingFunction=function(){return this._easingFunction},r.prototype.setEasingFunction=function(t){this._easingFunction=t},r.prototype.floatInterpolateFunction=function(t,e,n){return $.a.Lerp(t,e,n)},r.prototype.floatInterpolateFunctionWithTangents=function(t,e,n,i,o){return $.a.Hermite(t,e,n,i,o)},r.prototype.quaternionInterpolateFunction=function(t,e,n){return u.b.Slerp(t,e,n)},r.prototype.quaternionInterpolateFunctionWithTangents=function(t,e,n,i,o){return u.b.Hermite(t,e,n,i,o).normalize()},r.prototype.vector3InterpolateFunction=function(t,e,n){return u.e.Lerp(t,e,n)},r.prototype.vector3InterpolateFunctionWithTangents=function(t,e,n,i,o){return u.e.Hermite(t,e,n,i,o)},r.prototype.vector2InterpolateFunction=function(t,e,n){return u.d.Lerp(t,e,n)},r.prototype.vector2InterpolateFunctionWithTangents=function(t,e,n,i,o){return u.d.Hermite(t,e,n,i,o)},r.prototype.sizeInterpolateFunction=function(t,e,n){return oe.a.Lerp(t,e,n)},r.prototype.color3InterpolateFunction=function(t,e,n){return M.a.Lerp(t,e,n)},r.prototype.color4InterpolateFunction=function(t,e,n){return M.b.Lerp(t,e,n)},r.prototype._getKeyValue=function(t){return typeof t=="function"?t():t},r.prototype._interpolate=function(t,e){if(e.loopMode===r.ANIMATIONLOOPMODE_CONSTANT&&e.repeatCount>0)return e.highLimitValue.clone?e.highLimitValue.clone():e.highLimitValue;var n=this._keys;if(n.length===1)return this._getKeyValue(n[0].value);var i=e.key;if(n[i].frame>=t)for(;i-1>=0&&n[i].frame>=t;)i--;for(var o=i;o<n.length;o++){var a=n[o+1];if(a.frame>=t){e.key=o;var s=n[o],d=this._getKeyValue(s.value);if(s.interpolation===K.STEP)return d;var p=this._getKeyValue(a.value),b=s.outTangent!==void 0&&a.inTangent!==void 0,P=a.frame-s.frame,O=(t-s.frame)/P,B=this.getEasingFunction();switch(B!=null&&(O=B.ease(O)),this.dataType){case r.ANIMATIONTYPE_FLOAT:var F=b?this.floatInterpolateFunctionWithTangents(d,s.outTangent*P,p,a.inTangent*P,O):this.floatInterpolateFunction(d,p,O);switch(e.loopMode){case r.ANIMATIONLOOPMODE_CYCLE:case r.ANIMATIONLOOPMODE_CONSTANT:return F;case r.ANIMATIONLOOPMODE_RELATIVE:return e.offsetValue*e.repeatCount+F}break;case r.ANIMATIONTYPE_QUATERNION:var z=b?this.quaternionInterpolateFunctionWithTangents(d,s.outTangent.scale(P),p,a.inTangent.scale(P),O):this.quaternionInterpolateFunction(d,p,O);switch(e.loopMode){case r.ANIMATIONLOOPMODE_CYCLE:case r.ANIMATIONLOOPMODE_CONSTANT:return z;case r.ANIMATIONLOOPMODE_RELATIVE:return z.addInPlace(e.offsetValue.scale(e.repeatCount))}return z;case r.ANIMATIONTYPE_VECTOR3:var J=b?this.vector3InterpolateFunctionWithTangents(d,s.outTangent.scale(P),p,a.inTangent.scale(P),O):this.vector3InterpolateFunction(d,p,O);switch(e.loopMode){case r.ANIMATIONLOOPMODE_CYCLE:case r.ANIMATIONLOOPMODE_CONSTANT:return J;case r.ANIMATIONLOOPMODE_RELATIVE:return J.add(e.offsetValue.scale(e.repeatCount))}case r.ANIMATIONTYPE_VECTOR2:var ie=b?this.vector2InterpolateFunctionWithTangents(d,s.outTangent.scale(P),p,a.inTangent.scale(P),O):this.vector2InterpolateFunction(d,p,O);switch(e.loopMode){case r.ANIMATIONLOOPMODE_CYCLE:case r.ANIMATIONLOOPMODE_CONSTANT:return ie;case r.ANIMATIONLOOPMODE_RELATIVE:return ie.add(e.offsetValue.scale(e.repeatCount))}case r.ANIMATIONTYPE_SIZE:switch(e.loopMode){case r.ANIMATIONLOOPMODE_CYCLE:case r.ANIMATIONLOOPMODE_CONSTANT:return this.sizeInterpolateFunction(d,p,O);case r.ANIMATIONLOOPMODE_RELATIVE:return this.sizeInterpolateFunction(d,p,O).add(e.offsetValue.scale(e.repeatCount))}case r.ANIMATIONTYPE_COLOR3:switch(e.loopMode){case r.ANIMATIONLOOPMODE_CYCLE:case r.ANIMATIONLOOPMODE_CONSTANT:return this.color3InterpolateFunction(d,p,O);case r.ANIMATIONLOOPMODE_RELATIVE:return this.color3InterpolateFunction(d,p,O).add(e.offsetValue.scale(e.repeatCount))}case r.ANIMATIONTYPE_COLOR4:switch(e.loopMode){case r.ANIMATIONLOOPMODE_CYCLE:case r.ANIMATIONLOOPMODE_CONSTANT:return this.color4InterpolateFunction(d,p,O);case r.ANIMATIONLOOPMODE_RELATIVE:return this.color4InterpolateFunction(d,p,O).add(e.offsetValue.scale(e.repeatCount))}case r.ANIMATIONTYPE_MATRIX:switch(e.loopMode){case r.ANIMATIONLOOPMODE_CYCLE:case r.ANIMATIONLOOPMODE_CONSTANT:if(r.AllowMatricesInterpolation)return this.matrixInterpolateFunction(d,p,O,e.workValue);case r.ANIMATIONLOOPMODE_RELATIVE:return d}}break}}return this._getKeyValue(n[n.length-1].value)},r.prototype.matrixInterpolateFunction=function(t,e,n,i){return r.AllowMatrixDecomposeForInterpolation?i?(u.a.DecomposeLerpToRef(t,e,n,i),i):u.a.DecomposeLerp(t,e,n):i?(u.a.LerpToRef(t,e,n,i),i):u.a.Lerp(t,e,n)},r.prototype.clone=function(){var t=new r(this.name,this.targetPropertyPath.join("."),this.framePerSecond,this.dataType,this.loopMode);if(t.enableBlending=this.enableBlending,t.blendingSpeed=this.blendingSpeed,this._keys&&t.setKeys(this._keys),this._ranges)for(var e in t._ranges={},this._ranges){var n=this._ranges[e];n&&(t._ranges[e]=n.clone())}return t},r.prototype.setKeys=function(t){this._keys=t.slice(0)},r.prototype.serialize=function(){var t={};t.name=this.name,t.property=this.targetProperty,t.framePerSecond=this.framePerSecond,t.dataType=this.dataType,t.loopBehavior=this.loopMode,t.enableBlending=this.enableBlending,t.blendingSpeed=this.blendingSpeed;var e=this.dataType;t.keys=[];for(var n=this.getKeys(),i=0;i<n.length;i++){var o=n[i],a={};switch(a.frame=o.frame,e){case r.ANIMATIONTYPE_FLOAT:a.values=[o.value],o.inTangent!==void 0&&a.values.push(o.inTangent),o.outTangent!==void 0&&(o.inTangent===void 0&&a.values.push(void 0),a.values.push(o.outTangent));break;case r.ANIMATIONTYPE_QUATERNION:case r.ANIMATIONTYPE_MATRIX:case r.ANIMATIONTYPE_VECTOR3:case r.ANIMATIONTYPE_COLOR3:case r.ANIMATIONTYPE_COLOR4:a.values=o.value.asArray(),o.inTangent!=null&&a.values.push(o.inTangent.asArray()),o.outTangent!=null&&(o.inTangent===void 0&&a.values.push(void 0),a.values.push(o.outTangent.asArray()))}t.keys.push(a)}for(var s in t.ranges=[],this._ranges){var d=this._ranges[s];if(d){var p={};p.name=s,p.from=d.from,p.to=d.to,t.ranges.push(p)}}return t},r._UniversalLerp=function(t,e,n){var i=t.constructor;return i.Lerp?i.Lerp(t,e,n):i.Slerp?i.Slerp(t,e,n):t.toFixed?t*(1-n)+n*e:e},r.Parse=function(t){var e,n,i=new r(t.name,t.property,t.framePerSecond,t.dataType,t.loopBehavior),o=t.dataType,a=[];for(t.enableBlending&&(i.enableBlending=t.enableBlending),t.blendingSpeed&&(i.blendingSpeed=t.blendingSpeed),n=0;n<t.keys.length;n++){var s,d,p=t.keys[n];switch(o){case r.ANIMATIONTYPE_FLOAT:e=p.values[0],p.values.length>=1&&(s=p.values[1]),p.values.length>=2&&(d=p.values[2]);break;case r.ANIMATIONTYPE_QUATERNION:if(e=u.b.FromArray(p.values),p.values.length>=8){var b=u.b.FromArray(p.values.slice(4,8));b.equals(u.b.Zero())||(s=b)}if(p.values.length>=12){var P=u.b.FromArray(p.values.slice(8,12));P.equals(u.b.Zero())||(d=P)}break;case r.ANIMATIONTYPE_MATRIX:e=u.a.FromArray(p.values);break;case r.ANIMATIONTYPE_COLOR3:e=M.a.FromArray(p.values);break;case r.ANIMATIONTYPE_COLOR4:e=M.b.FromArray(p.values);break;case r.ANIMATIONTYPE_VECTOR3:default:e=u.e.FromArray(p.values)}var O={};O.frame=p.frame,O.value=e,s!=null&&(O.inTangent=s),d!=null&&(O.outTangent=d),a.push(O)}if(i.setKeys(a),t.ranges)for(n=0;n<t.ranges.length;n++)e=t.ranges[n],i.createRange(e.name,e.from,e.to);return i},r.AppendSerializedAnimations=function(t,e){L.a.AppendSerializedAnimations(t,e)},r.ParseFromFileAsync=function(t,e){var n=this;return new Promise(function(i,o){var a=new re.a;a.addEventListener("readystatechange",function(){if(a.readyState==4)if(a.status==200){var s=JSON.parse(a.responseText);if(s.length){for(var d=new Array,p=0,b=s;p<b.length;p++){var P=b[p];d.push(n.Parse(P))}i(d)}else d=n.Parse(s),t&&(d.name=t),i(d)}else o("Unable to load the animation")}),a.open("GET",e),a.send()})},r.CreateFromSnippetAsync=function(t){var e=this;return new Promise(function(n,i){var o=new re.a;o.addEventListener("readystatechange",function(){if(o.readyState==4)if(o.status==200){var a=JSON.parse(JSON.parse(o.responseText).jsonPayload);if(a.animations){for(var s=JSON.parse(a.animations),d=new Array,p=0,b=s;p<b.length;p++){var P=b[p];d.push(e.Parse(P))}n(d)}else s=JSON.parse(a.animation),(d=e.Parse(s)).snippetId=t,n(d)}else i("Unable to load the snippet "+t)}),o.open("GET",e.SnippetUrl+"/"+t.replace(/#/g,"/")),o.send()})},r.AllowMatricesInterpolation=!1,r.AllowMatrixDecomposeForInterpolation=!0,r.SnippetUrl="https://snippet.babylonjs.com",r.ANIMATIONTYPE_FLOAT=0,r.ANIMATIONTYPE_VECTOR3=1,r.ANIMATIONTYPE_QUATERNION=2,r.ANIMATIONTYPE_MATRIX=3,r.ANIMATIONTYPE_COLOR3=4,r.ANIMATIONTYPE_COLOR4=7,r.ANIMATIONTYPE_VECTOR2=5,r.ANIMATIONTYPE_SIZE=6,r.ANIMATIONLOOPMODE_RELATIVE=0,r.ANIMATIONLOOPMODE_CYCLE=1,r.ANIMATIONLOOPMODE_CONSTANT=2,r}();R.a.RegisteredTypes["BABYLON.Animation"]=k,Q.a._AnimationRangeFactory=function(r,t,e){return new G(r,t,e)};var H=function(r){function t(e,n,i,o,a,s,d,p){a===void 0&&(a=1e3);var b=r.call(this,e,s)||this;return b.duration=1e3,b.onInterpolationDoneObservable=new x.c,b.propertyPath=i,b.value=o,b.duration=a,b.stopOtherAnimations=d,b.onInterpolationDone=p,b._target=b._effectiveTarget=n,b}return Object(c.d)(t,r),t.prototype._prepare=function(){this._effectiveTarget=this._getEffectiveTarget(this._effectiveTarget,this.propertyPath),this._property=this._getProperty(this.propertyPath)},t.prototype.execute=function(){var e,n=this,i=this._actionManager.getScene(),o=[{frame:0,value:this._effectiveTarget[this._property]},{frame:100,value:this.value}];if(typeof this.value=="number")e=k.ANIMATIONTYPE_FLOAT;else if(this.value instanceof M.a)e=k.ANIMATIONTYPE_COLOR3;else if(this.value instanceof u.e)e=k.ANIMATIONTYPE_VECTOR3;else if(this.value instanceof u.a)e=k.ANIMATIONTYPE_MATRIX;else{if(!(this.value instanceof u.b))return void l.a.Warn("InterpolateValueAction: Unsupported type ("+typeof this.value+")");e=k.ANIMATIONTYPE_QUATERNION}var a=new k("InterpolateValueAction",this._property,1e3/this.duration*100,e,k.ANIMATIONLOOPMODE_CONSTANT);a.setKeys(o),this.stopOtherAnimations&&i.stopAnimation(this._effectiveTarget),i.beginDirectAnimation(this._effectiveTarget,[a],0,100,!1,1,function(){n.onInterpolationDoneObservable.notifyObservers(n),n.onInterpolationDone&&n.onInterpolationDone()})},t.prototype.serialize=function(e){return r.prototype._serialize.call(this,{name:"InterpolateValueAction",properties:[C._GetTargetProperty(this._target),{name:"propertyPath",value:this.propertyPath},{name:"value",value:C._SerializeValueAsString(this.value)},{name:"duration",value:C._SerializeValueAsString(this.duration)},{name:"stopOtherAnimations",value:C._SerializeValueAsString(this.stopOtherAnimations)||!1}]},e)},t}(C);R.a.RegisteredTypes["BABYLON.InterpolateValueAction"]=H;var Z=Object.freeze(new u.b(0,0,0,0)),W=Object.freeze(u.e.Zero()),q=Object.freeze(u.d.Zero()),he=Object.freeze(oe.a.Zero()),ge=Object.freeze(M.a.Black()),me=function(){function r(t,e,n,i){var o=this;if(this._events=new Array,this._currentFrame=0,this._originalValue=new Array,this._originalBlendValue=null,this._offsetsCache={},this._highLimitsCache={},this._stopped=!1,this._blendingFactor=0,this._currentValue=null,this._currentActiveTarget=null,this._directTarget=null,this._targetPath="",this._weight=1,this._ratioOffset=0,this._previousDelay=0,this._previousRatio=0,this._targetIsArray=!1,this._animation=e,this._target=t,this._scene=n,this._host=i,this._activeTargets=[],e._runtimeAnimations.push(this),this._animationState={key:0,repeatCount:0,loopMode:this._getCorrectLoopMode()},this._animation.dataType===k.ANIMATIONTYPE_MATRIX&&(this._animationState.workValue=u.a.Zero()),this._keys=this._animation.getKeys(),this._minFrame=this._keys[0].frame,this._maxFrame=this._keys[this._keys.length-1].frame,this._minValue=this._keys[0].value,this._maxValue=this._keys[this._keys.length-1].value,this._minFrame!==0){var a={frame:0,value:this._minValue};this._keys.splice(0,0,a)}if(this._target instanceof Array){for(var s=0,d=0,p=this._target;d<p.length;d++){var b=p[d];this._preparePath(b,s),this._getOriginalValues(s),s++}this._targetIsArray=!0}else this._preparePath(this._target),this._getOriginalValues(),this._targetIsArray=!1,this._directTarget=this._activeTargets[0];var P=e.getEvents();P&&P.length>0&&P.forEach(function(O){o._events.push(O._clone())}),this._enableBlending=t&&t.animationPropertiesOverride?t.animationPropertiesOverride.enableBlending:this._animation.enableBlending}return Object.defineProperty(r.prototype,"currentFrame",{get:function(){return this._currentFrame},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"weight",{get:function(){return this._weight},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"currentValue",{get:function(){return this._currentValue},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"targetPath",{get:function(){return this._targetPath},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"target",{get:function(){return this._currentActiveTarget},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isAdditive",{get:function(){return this._host&&this._host.isAdditive},enumerable:!1,configurable:!0}),r.prototype._preparePath=function(t,e){e===void 0&&(e=0);var n=this._animation.targetPropertyPath;if(n.length>1){for(var i=t[n[0]],o=1;o<n.length-1;o++)i=i[n[o]];this._targetPath=n[n.length-1],this._activeTargets[e]=i}else this._targetPath=n[0],this._activeTargets[e]=t},Object.defineProperty(r.prototype,"animation",{get:function(){return this._animation},enumerable:!1,configurable:!0}),r.prototype.reset=function(t){if(t===void 0&&(t=!1),t)if(this._target instanceof Array)for(var e=0,n=0,i=this._target;n<i.length;n++){var o=i[n];this._originalValue[e]!==void 0&&this._setValue(o,this._activeTargets[e],this._originalValue[e],-1,e),e++}else this._originalValue[0]!==void 0&&this._setValue(this._target,this._directTarget,this._originalValue[0],-1,0);for(this._offsetsCache={},this._highLimitsCache={},this._currentFrame=0,this._blendingFactor=0,e=0;e<this._events.length;e++)this._events[e].isDone=!1},r.prototype.isStopped=function(){return this._stopped},r.prototype.dispose=function(){var t=this._animation.runtimeAnimations.indexOf(this);t>-1&&this._animation.runtimeAnimations.splice(t,1)},r.prototype.setValue=function(t,e){if(this._targetIsArray)for(var n=0;n<this._target.length;n++){var i=this._target[n];this._setValue(i,this._activeTargets[n],t,e,n)}else this._setValue(this._target,this._directTarget,t,e,0)},r.prototype._getOriginalValues=function(t){var e;t===void 0&&(t=0);var n=this._activeTargets[t];(e=n.getRestPose&&this._targetPath==="_matrix"?n.getRestPose():n[this._targetPath])&&e.clone?this._originalValue[t]=e.clone():this._originalValue[t]=e},r.prototype._setValue=function(t,e,n,i,o){if(this._currentActiveTarget=e,this._weight=i,this._enableBlending&&this._blendingFactor<=1){if(!this._originalBlendValue){var a=e[this._targetPath];a.clone?this._originalBlendValue=a.clone():this._originalBlendValue=a}this._originalBlendValue.m?k.AllowMatrixDecomposeForInterpolation?this._currentValue?u.a.DecomposeLerpToRef(this._originalBlendValue,n,this._blendingFactor,this._currentValue):this._currentValue=u.a.DecomposeLerp(this._originalBlendValue,n,this._blendingFactor):this._currentValue?u.a.LerpToRef(this._originalBlendValue,n,this._blendingFactor,this._currentValue):this._currentValue=u.a.Lerp(this._originalBlendValue,n,this._blendingFactor):this._currentValue=k._UniversalLerp(this._originalBlendValue,n,this._blendingFactor);var s=t&&t.animationPropertiesOverride?t.animationPropertiesOverride.blendingSpeed:this._animation.blendingSpeed;this._blendingFactor+=s}else this._currentValue=n;i!==-1?this._scene._registerTargetForLateAnimationBinding(this,this._originalValue[o]):e[this._targetPath]=this._currentValue,t.markAsDirty&&t.markAsDirty(this._animation.targetProperty)},r.prototype._getCorrectLoopMode=function(){return this._target&&this._target.animationPropertiesOverride?this._target.animationPropertiesOverride.loopMode:this._animation.loopMode},r.prototype.goToFrame=function(t){var e=this._animation.getKeys();t<e[0].frame?t=e[0].frame:t>e[e.length-1].frame&&(t=e[e.length-1].frame);var n=this._events;if(n.length)for(var i=0;i<n.length;i++)n[i].onlyOnce||(n[i].isDone=n[i].frame<t);this._currentFrame=t;var o=this._animation._interpolate(t,this._animationState);this.setValue(o,-1)},r.prototype._prepareForSpeedRatioChange=function(t){var e=this._previousDelay*(this._animation.framePerSecond*t)/1e3;this._ratioOffset=this._previousRatio-e},r.prototype.animate=function(t,e,n,i,o,a){a===void 0&&(a=-1);var s=this._animation,d=s.targetPropertyPath;if(!d||d.length<1)return this._stopped=!0,!1;var p=!0;(e<this._minFrame||e>this._maxFrame)&&(e=this._minFrame),(n<this._minFrame||n>this._maxFrame)&&(n=this._maxFrame);var b,P,O=n-e,B=t*(s.framePerSecond*o)/1e3+this._ratioOffset,F=0;if(this._previousDelay=t,this._previousRatio=B,!i&&n>=e&&B>=O)p=!1,F=s._getKeyValue(this._maxValue);else if(!i&&e>=n&&B<=O)p=!1,F=s._getKeyValue(this._minValue);else if(this._animationState.loopMode!==k.ANIMATIONLOOPMODE_CYCLE){var z=n.toString()+e.toString();if(!this._offsetsCache[z]){this._animationState.repeatCount=0,this._animationState.loopMode=k.ANIMATIONLOOPMODE_CYCLE;var J=s._interpolate(e,this._animationState),ie=s._interpolate(n,this._animationState);switch(this._animationState.loopMode=this._getCorrectLoopMode(),s.dataType){case k.ANIMATIONTYPE_FLOAT:this._offsetsCache[z]=ie-J;break;case k.ANIMATIONTYPE_QUATERNION:this._offsetsCache[z]=ie.subtract(J);break;case k.ANIMATIONTYPE_VECTOR3:this._offsetsCache[z]=ie.subtract(J);case k.ANIMATIONTYPE_VECTOR2:this._offsetsCache[z]=ie.subtract(J);case k.ANIMATIONTYPE_SIZE:this._offsetsCache[z]=ie.subtract(J);case k.ANIMATIONTYPE_COLOR3:this._offsetsCache[z]=ie.subtract(J)}this._highLimitsCache[z]=ie}F=this._highLimitsCache[z],b=this._offsetsCache[z]}if(b===void 0)switch(s.dataType){case k.ANIMATIONTYPE_FLOAT:b=0;break;case k.ANIMATIONTYPE_QUATERNION:b=Z;break;case k.ANIMATIONTYPE_VECTOR3:b=W;break;case k.ANIMATIONTYPE_VECTOR2:b=q;break;case k.ANIMATIONTYPE_SIZE:b=he;break;case k.ANIMATIONTYPE_COLOR3:b=ge}if(this._host&&this._host.syncRoot){var se=this._host.syncRoot;P=e+(n-e)*((se.masterFrame-se.fromFrame)/(se.toFrame-se.fromFrame))}else P=p&&O!==0?e+B%O:n;var ce=this._events;if((O>0&&this.currentFrame>P||O<0&&this.currentFrame<P)&&(this._onLoop(),ce.length))for(var ue=0;ue<ce.length;ue++)ce[ue].onlyOnce||(ce[ue].isDone=!1);this._currentFrame=P,this._animationState.repeatCount=O===0?0:B/O>>0,this._animationState.highLimitValue=F,this._animationState.offsetValue=b;var fe=s._interpolate(P,this._animationState);if(this.setValue(fe,a),ce.length){for(ue=0;ue<ce.length;ue++)if(O>0&&P>=ce[ue].frame&&ce[ue].frame>=e||O<0&&P<=ce[ue].frame&&ce[ue].frame<=e){var ve=ce[ue];ve.isDone||(ve.onlyOnce&&(ce.splice(ue,1),ue--),ve.isDone=!0,ve.action(P))}}return p||(this._stopped=!0),p},r}(),_e=f(20),be=f(57),Pe=f(44),ye=f(23),Be=function(r){function t(e,n,i,o,a,s,d){i===void 0&&(i=null),o===void 0&&(o=null),a===void 0&&(a=null),s===void 0&&(s=null),d===void 0&&(d=null);var p=r.call(this,e,n.getScene())||this;return p.name=e,p.children=new Array,p.animations=new Array,p._index=null,p._absoluteTransform=new u.a,p._invertedAbsoluteTransform=new u.a,p._scalingDeterminant=1,p._worldTransform=new u.a,p._needToDecompose=!0,p._needToCompose=!1,p._linkedTransformNode=null,p._waitingTransformNodeId=null,p._skeleton=n,p._localMatrix=o?o.clone():u.a.Identity(),p._restPose=a||p._localMatrix.clone(),p._bindPose=p._localMatrix.clone(),p._baseMatrix=s||p._localMatrix.clone(),p._index=d,n.bones.push(p),p.setParent(i,!1),(s||o)&&p._updateDifferenceMatrix(),p}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"_matrix",{get:function(){return this._compose(),this._localMatrix},set:function(e){this._localMatrix.copyFrom(e),this._needToDecompose=!0},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"Bone"},t.prototype.getSkeleton=function(){return this._skeleton},t.prototype.getParent=function(){return this._parent},t.prototype.getChildren=function(){return this.children},t.prototype.getIndex=function(){return this._index===null?this.getSkeleton().bones.indexOf(this):this._index},t.prototype.setParent=function(e,n){if(n===void 0&&(n=!0),this._parent!==e){if(this._parent){var i=this._parent.children.indexOf(this);i!==-1&&this._parent.children.splice(i,1)}this._parent=e,this._parent&&this._parent.children.push(this),n&&this._updateDifferenceMatrix(),this.markAsDirty()}},t.prototype.getLocalMatrix=function(){return this._compose(),this._localMatrix},t.prototype.getBaseMatrix=function(){return this._baseMatrix},t.prototype.getRestPose=function(){return this._restPose},t.prototype.setRestPose=function(e){this._restPose.copyFrom(e)},t.prototype.getBindPose=function(){return this._bindPose},t.prototype.setBindPose=function(e){this._bindPose.copyFrom(e)},t.prototype.getWorldMatrix=function(){return this._worldTransform},t.prototype.returnToRest=function(){this._skeleton._numBonesWithLinkedTransformNode>0?this.updateMatrix(this._restPose,!1,!1):this.updateMatrix(this._restPose,!1,!0)},t.prototype.getInvertedAbsoluteTransform=function(){return this._invertedAbsoluteTransform},t.prototype.getAbsoluteTransform=function(){return this._absoluteTransform},t.prototype.linkTransformNode=function(e){this._linkedTransformNode&&this._skeleton._numBonesWithLinkedTransformNode--,this._linkedTransformNode=e,this._linkedTransformNode&&this._skeleton._numBonesWithLinkedTransformNode++},t.prototype.getTransformNode=function(){return this._linkedTransformNode},Object.defineProperty(t.prototype,"position",{get:function(){return this._decompose(),this._localPosition},set:function(e){this._decompose(),this._localPosition.copyFrom(e),this._markAsDirtyAndCompose()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rotation",{get:function(){return this.getRotation()},set:function(e){this.setRotation(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rotationQuaternion",{get:function(){return this._decompose(),this._localRotation},set:function(e){this.setRotationQuaternion(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"scaling",{get:function(){return this.getScale()},set:function(e){this.setScale(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"animationPropertiesOverride",{get:function(){return this._skeleton.animationPropertiesOverride},enumerable:!1,configurable:!0}),t.prototype._decompose=function(){this._needToDecompose&&(this._needToDecompose=!1,this._localScaling||(this._localScaling=u.e.Zero(),this._localRotation=u.b.Zero(),this._localPosition=u.e.Zero()),this._localMatrix.decompose(this._localScaling,this._localRotation,this._localPosition))},t.prototype._compose=function(){this._needToCompose&&(this._localScaling?(this._needToCompose=!1,u.a.ComposeToRef(this._localScaling,this._localRotation,this._localPosition,this._localMatrix)):this._needToCompose=!1)},t.prototype.updateMatrix=function(e,n,i){n===void 0&&(n=!0),i===void 0&&(i=!0),this._baseMatrix.copyFrom(e),n&&this._updateDifferenceMatrix(),i?(this._needToCompose=!1,this._localMatrix.copyFrom(e),this._markAsDirtyAndDecompose()):this.markAsDirty()},t.prototype._updateDifferenceMatrix=function(e,n){if(n===void 0&&(n=!0),e||(e=this._baseMatrix),this._parent?e.multiplyToRef(this._parent._absoluteTransform,this._absoluteTransform):this._absoluteTransform.copyFrom(e),this._absoluteTransform.invertToRef(this._invertedAbsoluteTransform),n)for(var i=0;i<this.children.length;i++)this.children[i]._updateDifferenceMatrix();this._scalingDeterminant=this._absoluteTransform.determinant()<0?-1:1},t.prototype.markAsDirty=function(){this._currentRenderId++,this._childUpdateId++,this._skeleton._markAsDirty()},t.prototype._markAsDirtyAndCompose=function(){this.markAsDirty(),this._needToCompose=!0},t.prototype._markAsDirtyAndDecompose=function(){this.markAsDirty(),this._needToDecompose=!0},t.prototype.translate=function(e,n,i){n===void 0&&(n=ye.c.LOCAL);var o=this.getLocalMatrix();if(n==ye.c.LOCAL)o.addAtIndex(12,e.x),o.addAtIndex(13,e.y),o.addAtIndex(14,e.z);else{var a=null;i&&(a=i.getWorldMatrix()),this._skeleton.computeAbsoluteTransforms();var s=t._tmpMats[0],d=t._tmpVecs[0];this._parent?i&&a?(s.copyFrom(this._parent.getAbsoluteTransform()),s.multiplyToRef(a,s)):s.copyFrom(this._parent.getAbsoluteTransform()):u.a.IdentityToRef(s),s.setTranslationFromFloats(0,0,0),s.invert(),u.e.TransformCoordinatesToRef(e,s,d),o.addAtIndex(12,d.x),o.addAtIndex(13,d.y),o.addAtIndex(14,d.z)}this._markAsDirtyAndDecompose()},t.prototype.setPosition=function(e,n,i){n===void 0&&(n=ye.c.LOCAL);var o=this.getLocalMatrix();if(n==ye.c.LOCAL)o.setTranslationFromFloats(e.x,e.y,e.z);else{var a=null;i&&(a=i.getWorldMatrix()),this._skeleton.computeAbsoluteTransforms();var s=t._tmpMats[0],d=t._tmpVecs[0];this._parent?(i&&a?(s.copyFrom(this._parent.getAbsoluteTransform()),s.multiplyToRef(a,s)):s.copyFrom(this._parent.getAbsoluteTransform()),s.invert()):u.a.IdentityToRef(s),u.e.TransformCoordinatesToRef(e,s,d),o.setTranslationFromFloats(d.x,d.y,d.z)}this._markAsDirtyAndDecompose()},t.prototype.setAbsolutePosition=function(e,n){this.setPosition(e,ye.c.WORLD,n)},t.prototype.scale=function(e,n,i,o){o===void 0&&(o=!1);var a=this.getLocalMatrix(),s=t._tmpMats[0];u.a.ScalingToRef(e,n,i,s),s.multiplyToRef(a,a),s.invert();for(var d=0,p=this.children;d<p.length;d++){var b=(B=p[d]).getLocalMatrix();b.multiplyToRef(s,b),b.multiplyAtIndex(12,e),b.multiplyAtIndex(13,n),b.multiplyAtIndex(14,i),B._markAsDirtyAndDecompose()}if(this._markAsDirtyAndDecompose(),o)for(var P=0,O=this.children;P<O.length;P++){var B;(B=O[P]).scale(e,n,i,o)}},t.prototype.setScale=function(e){this._decompose(),this._localScaling.copyFrom(e),this._markAsDirtyAndCompose()},t.prototype.getScale=function(){return this._decompose(),this._localScaling},t.prototype.getScaleToRef=function(e){this._decompose(),e.copyFrom(this._localScaling)},t.prototype.setYawPitchRoll=function(e,n,i,o,a){if(o===void 0&&(o=ye.c.LOCAL),o===ye.c.LOCAL){var s=t._tmpQuat;return u.b.RotationYawPitchRollToRef(e,n,i,s),void this.setRotationQuaternion(s,o,a)}var d=t._tmpMats[0];if(this._getNegativeRotationToRef(d,a)){var p=t._tmpMats[1];u.a.RotationYawPitchRollToRef(e,n,i,p),d.multiplyToRef(p,p),this._rotateWithMatrix(p,o,a)}},t.prototype.rotate=function(e,n,i,o){i===void 0&&(i=ye.c.LOCAL);var a=t._tmpMats[0];a.setTranslationFromFloats(0,0,0),u.a.RotationAxisToRef(e,n,a),this._rotateWithMatrix(a,i,o)},t.prototype.setAxisAngle=function(e,n,i,o){if(i===void 0&&(i=ye.c.LOCAL),i===ye.c.LOCAL){var a=t._tmpQuat;return u.b.RotationAxisToRef(e,n,a),void this.setRotationQuaternion(a,i,o)}var s=t._tmpMats[0];if(this._getNegativeRotationToRef(s,o)){var d=t._tmpMats[1];u.a.RotationAxisToRef(e,n,d),s.multiplyToRef(d,d),this._rotateWithMatrix(d,i,o)}},t.prototype.setRotation=function(e,n,i){n===void 0&&(n=ye.c.LOCAL),this.setYawPitchRoll(e.y,e.x,e.z,n,i)},t.prototype.setRotationQuaternion=function(e,n,i){if(n===void 0&&(n=ye.c.LOCAL),n===ye.c.LOCAL)return this._decompose(),this._localRotation.copyFrom(e),void this._markAsDirtyAndCompose();var o=t._tmpMats[0];if(this._getNegativeRotationToRef(o,i)){var a=t._tmpMats[1];u.a.FromQuaternionToRef(e,a),o.multiplyToRef(a,a),this._rotateWithMatrix(a,n,i)}},t.prototype.setRotationMatrix=function(e,n,i){if(n===void 0&&(n=ye.c.LOCAL),n===ye.c.LOCAL){var o=t._tmpQuat;return u.b.FromRotationMatrixToRef(e,o),void this.setRotationQuaternion(o,n,i)}var a=t._tmpMats[0];if(this._getNegativeRotationToRef(a,i)){var s=t._tmpMats[1];s.copyFrom(e),a.multiplyToRef(e,s),this._rotateWithMatrix(s,n,i)}},t.prototype._rotateWithMatrix=function(e,n,i){n===void 0&&(n=ye.c.LOCAL);var o=this.getLocalMatrix(),a=o.m[12],s=o.m[13],d=o.m[14],p=this.getParent(),b=t._tmpMats[3],P=t._tmpMats[4];p&&n==ye.c.WORLD?(i?(b.copyFrom(i.getWorldMatrix()),p.getAbsoluteTransform().multiplyToRef(b,b)):b.copyFrom(p.getAbsoluteTransform()),P.copyFrom(b),P.invert(),o.multiplyToRef(b,o),o.multiplyToRef(e,o),o.multiplyToRef(P,o)):n==ye.c.WORLD&&i?(b.copyFrom(i.getWorldMatrix()),P.copyFrom(b),P.invert(),o.multiplyToRef(b,o),o.multiplyToRef(e,o),o.multiplyToRef(P,o)):o.multiplyToRef(e,o),o.setTranslationFromFloats(a,s,d),this.computeAbsoluteTransforms(),this._markAsDirtyAndDecompose()},t.prototype._getNegativeRotationToRef=function(e,n){var i=t._tmpMats[2];return e.copyFrom(this.getAbsoluteTransform()),n&&(e.multiplyToRef(n.getWorldMatrix(),e),u.a.ScalingToRef(n.scaling.x,n.scaling.y,n.scaling.z,i)),e.invert(),!isNaN(e.m[0])&&(i.multiplyAtIndex(0,this._scalingDeterminant),e.multiplyToRef(i,e),!0)},t.prototype.getPosition=function(e,n){e===void 0&&(e=ye.c.LOCAL),n===void 0&&(n=null);var i=u.e.Zero();return this.getPositionToRef(e,n,i),i},t.prototype.getPositionToRef=function(e,n,i){if(e===void 0&&(e=ye.c.LOCAL),e==ye.c.LOCAL){var o=this.getLocalMatrix();i.x=o.m[12],i.y=o.m[13],i.z=o.m[14]}else{var a=null;n&&(a=n.getWorldMatrix()),this._skeleton.computeAbsoluteTransforms();var s=t._tmpMats[0];n&&a?(s.copyFrom(this.getAbsoluteTransform()),s.multiplyToRef(a,s)):s=this.getAbsoluteTransform(),i.x=s.m[12],i.y=s.m[13],i.z=s.m[14]}},t.prototype.getAbsolutePosition=function(e){e===void 0&&(e=null);var n=u.e.Zero();return this.getPositionToRef(ye.c.WORLD,e,n),n},t.prototype.getAbsolutePositionToRef=function(e,n){this.getPositionToRef(ye.c.WORLD,e,n)},t.prototype.computeAbsoluteTransforms=function(){if(this._compose(),this._parent)this._localMatrix.multiplyToRef(this._parent._absoluteTransform,this._absoluteTransform);else{this._absoluteTransform.copyFrom(this._localMatrix);var e=this._skeleton.getPoseMatrix();e&&this._absoluteTransform.multiplyToRef(e,this._absoluteTransform)}for(var n=this.children,i=n.length,o=0;o<i;o++)n[o].computeAbsoluteTransforms()},t.prototype.getDirection=function(e,n){n===void 0&&(n=null);var i=u.e.Zero();return this.getDirectionToRef(e,n,i),i},t.prototype.getDirectionToRef=function(e,n,i){n===void 0&&(n=null);var o=null;n&&(o=n.getWorldMatrix()),this._skeleton.computeAbsoluteTransforms();var a=t._tmpMats[0];a.copyFrom(this.getAbsoluteTransform()),n&&o&&a.multiplyToRef(o,a),u.e.TransformNormalToRef(e,a,i),i.normalize()},t.prototype.getRotation=function(e,n){e===void 0&&(e=ye.c.LOCAL),n===void 0&&(n=null);var i=u.e.Zero();return this.getRotationToRef(e,n,i),i},t.prototype.getRotationToRef=function(e,n,i){e===void 0&&(e=ye.c.LOCAL),n===void 0&&(n=null);var o=t._tmpQuat;this.getRotationQuaternionToRef(e,n,o),o.toEulerAnglesToRef(i)},t.prototype.getRotationQuaternion=function(e,n){e===void 0&&(e=ye.c.LOCAL),n===void 0&&(n=null);var i=u.b.Identity();return this.getRotationQuaternionToRef(e,n,i),i},t.prototype.getRotationQuaternionToRef=function(e,n,i){if(e===void 0&&(e=ye.c.LOCAL),n===void 0&&(n=null),e==ye.c.LOCAL)this._decompose(),i.copyFrom(this._localRotation);else{var o=t._tmpMats[0],a=this.getAbsoluteTransform();n?a.multiplyToRef(n.getWorldMatrix(),o):o.copyFrom(a),o.multiplyAtIndex(0,this._scalingDeterminant),o.multiplyAtIndex(1,this._scalingDeterminant),o.multiplyAtIndex(2,this._scalingDeterminant),o.decompose(void 0,i,void 0)}},t.prototype.getRotationMatrix=function(e,n){e===void 0&&(e=ye.c.LOCAL);var i=u.a.Identity();return this.getRotationMatrixToRef(e,n,i),i},t.prototype.getRotationMatrixToRef=function(e,n,i){if(e===void 0&&(e=ye.c.LOCAL),e==ye.c.LOCAL)this.getLocalMatrix().getRotationMatrixToRef(i);else{var o=t._tmpMats[0],a=this.getAbsoluteTransform();n?a.multiplyToRef(n.getWorldMatrix(),o):o.copyFrom(a),o.multiplyAtIndex(0,this._scalingDeterminant),o.multiplyAtIndex(1,this._scalingDeterminant),o.multiplyAtIndex(2,this._scalingDeterminant),o.getRotationMatrixToRef(i)}},t.prototype.getAbsolutePositionFromLocal=function(e,n){n===void 0&&(n=null);var i=u.e.Zero();return this.getAbsolutePositionFromLocalToRef(e,n,i),i},t.prototype.getAbsolutePositionFromLocalToRef=function(e,n,i){n===void 0&&(n=null);var o=null;n&&(o=n.getWorldMatrix()),this._skeleton.computeAbsoluteTransforms();var a=t._tmpMats[0];n&&o?(a.copyFrom(this.getAbsoluteTransform()),a.multiplyToRef(o,a)):a=this.getAbsoluteTransform(),u.e.TransformCoordinatesToRef(e,a,i)},t.prototype.getLocalPositionFromAbsolute=function(e,n){n===void 0&&(n=null);var i=u.e.Zero();return this.getLocalPositionFromAbsoluteToRef(e,n,i),i},t.prototype.getLocalPositionFromAbsoluteToRef=function(e,n,i){n===void 0&&(n=null);var o=null;n&&(o=n.getWorldMatrix()),this._skeleton.computeAbsoluteTransforms();var a=t._tmpMats[0];a.copyFrom(this.getAbsoluteTransform()),n&&o&&a.multiplyToRef(o,a),a.invert(),u.e.TransformCoordinatesToRef(e,a,i)},t.prototype.setCurrentPoseAsRest=function(){this.setRestPose(this.getLocalMatrix())},t._tmpVecs=Pe.a.BuildArray(2,u.e.Zero),t._tmpQuat=u.b.Identity(),t._tmpMats=Pe.a.BuildArray(5,u.a.Identity),t}(Q.a),ke=function(){function r(t,e,n,i,o,a,s,d,p,b){n===void 0&&(n=0),i===void 0&&(i=100),o===void 0&&(o=!1),a===void 0&&(a=1),b===void 0&&(b=!1),this.target=e,this.fromFrame=n,this.toFrame=i,this.loopAnimation=o,this.onAnimationEnd=s,this.onAnimationLoop=p,this.isAdditive=b,this._localDelayOffset=null,this._pausedDelay=null,this._runtimeAnimations=new Array,this._paused=!1,this._speedRatio=1,this._weight=-1,this._syncRoot=null,this.disposeOnEnd=!0,this.animationStarted=!1,this.onAnimationEndObservable=new x.c,this.onAnimationLoopObservable=new x.c,this._scene=t,d&&this.appendAnimations(e,d),this._speedRatio=a,t._activeAnimatables.push(this)}return Object.defineProperty(r.prototype,"syncRoot",{get:function(){return this._syncRoot},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"masterFrame",{get:function(){return this._runtimeAnimations.length===0?0:this._runtimeAnimations[0].currentFrame},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"weight",{get:function(){return this._weight},set:function(t){this._weight=t!==-1?Math.min(Math.max(t,0),1):-1},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"speedRatio",{get:function(){return this._speedRatio},set:function(t){for(var e=0;e<this._runtimeAnimations.length;e++)this._runtimeAnimations[e]._prepareForSpeedRatioChange(t);this._speedRatio=t},enumerable:!1,configurable:!0}),r.prototype.syncWith=function(t){if(this._syncRoot=t,t){var e=this._scene._activeAnimatables.indexOf(this);e>-1&&(this._scene._activeAnimatables.splice(e,1),this._scene._activeAnimatables.push(this))}return this},r.prototype.getAnimations=function(){return this._runtimeAnimations},r.prototype.appendAnimations=function(t,e){for(var n=this,i=0;i<e.length;i++){var o=e[i],a=new me(t,o,this._scene,this);a._onLoop=function(){n.onAnimationLoopObservable.notifyObservers(n),n.onAnimationLoop&&n.onAnimationLoop()},this._runtimeAnimations.push(a)}},r.prototype.getAnimationByTargetProperty=function(t){for(var e=this._runtimeAnimations,n=0;n<e.length;n++)if(e[n].animation.targetProperty===t)return e[n].animation;return null},r.prototype.getRuntimeAnimationByTargetProperty=function(t){for(var e=this._runtimeAnimations,n=0;n<e.length;n++)if(e[n].animation.targetProperty===t)return e[n];return null},r.prototype.reset=function(){for(var t=this._runtimeAnimations,e=0;e<t.length;e++)t[e].reset(!0);this._localDelayOffset=null,this._pausedDelay=null},r.prototype.enableBlending=function(t){for(var e=this._runtimeAnimations,n=0;n<e.length;n++)e[n].animation.enableBlending=!0,e[n].animation.blendingSpeed=t},r.prototype.disableBlending=function(){for(var t=this._runtimeAnimations,e=0;e<t.length;e++)t[e].animation.enableBlending=!1},r.prototype.goToFrame=function(t){var e=this._runtimeAnimations;if(e[0]){var n=e[0].animation.framePerSecond,i=e[0].currentFrame,o=this.speedRatio===0?0:(t-i)/n*1e3/this.speedRatio;this._localDelayOffset===null&&(this._localDelayOffset=0),this._localDelayOffset-=o}for(var a=0;a<e.length;a++)e[a].goToFrame(t)},r.prototype.pause=function(){this._paused||(this._paused=!0)},r.prototype.restart=function(){this._paused=!1},r.prototype._raiseOnAnimationEnd=function(){this.onAnimationEnd&&this.onAnimationEnd(),this.onAnimationEndObservable.notifyObservers(this)},r.prototype.stop=function(t,e){if(t||e){var n=this._scene._activeAnimatables.indexOf(this);if(n>-1){for(var i=(a=this._runtimeAnimations).length-1;i>=0;i--){var o=a[i];t&&o.animation.name!=t||e&&!e(o.target)||(o.dispose(),a.splice(i,1))}a.length==0&&(this._scene._activeAnimatables.splice(n,1),this._raiseOnAnimationEnd())}}else if((i=this._scene._activeAnimatables.indexOf(this))>-1){this._scene._activeAnimatables.splice(i,1);var a=this._runtimeAnimations;for(i=0;i<a.length;i++)a[i].dispose();this._raiseOnAnimationEnd()}},r.prototype.waitAsync=function(){var t=this;return new Promise(function(e,n){t.onAnimationEndObservable.add(function(){e(t)},void 0,void 0,t,!0)})},r.prototype._animate=function(t){if(this._paused)return this.animationStarted=!1,this._pausedDelay===null&&(this._pausedDelay=t),!0;if(this._localDelayOffset===null?(this._localDelayOffset=t,this._pausedDelay=null):this._pausedDelay!==null&&(this._localDelayOffset+=t-this._pausedDelay,this._pausedDelay=null),this._weight===0)return!0;var e,n=!1,i=this._runtimeAnimations;for(e=0;e<i.length;e++){var o=i[e].animate(t-this._localDelayOffset,this.fromFrame,this.toFrame,this.loopAnimation,this._speedRatio,this._weight);n=n||o}if(this.animationStarted=n,!n){if(this.disposeOnEnd)for(e=this._scene._activeAnimatables.indexOf(this),this._scene._activeAnimatables.splice(e,1),e=0;e<i.length;e++)i[e].dispose();this._raiseOnAnimationEnd(),this.disposeOnEnd&&(this.onAnimationEnd=null,this.onAnimationLoop=null,this.onAnimationLoopObservable.clear(),this.onAnimationEndObservable.clear())}return n},r}();_e.a.prototype._animate=function(){if(this.animationsEnabled){var r=be.a.Now;if(!this._animationTimeLast){if(this._pendingData.length>0)return;this._animationTimeLast=r}this.deltaTime=this.useConstantAnimationDeltaTime?16:(r-this._animationTimeLast)*this.animationTimeScale,this._animationTimeLast=r;var t=this._activeAnimatables;if(t.length!==0){this._animationTime+=this.deltaTime;for(var e=this._animationTime,n=0;n<t.length;n++){var i=t[n];!i._animate(e)&&i.disposeOnEnd&&n--}this._processLateAnimationBindings()}}},_e.a.prototype.beginWeightedAnimation=function(r,t,e,n,i,o,a,s,d,p,b){n===void 0&&(n=1),o===void 0&&(o=1),b===void 0&&(b=!1);var P=this.beginAnimation(r,t,e,i,o,a,s,!1,d,p,b);return P.weight=n,P},_e.a.prototype.beginAnimation=function(r,t,e,n,i,o,a,s,d,p,b){i===void 0&&(i=1),s===void 0&&(s=!0),b===void 0&&(b=!1),t>e&&i>0&&(i*=-1),s&&this.stopAnimation(r,void 0,d),a||(a=new ke(this,r,t,e,n,i,o,void 0,p,b));var P=!d||d(r);if(r.animations&&P&&a.appendAnimations(r,r.animations),r.getAnimatables)for(var O=r.getAnimatables(),B=0;B<O.length;B++)this.beginAnimation(O[B],t,e,n,i,o,a,s,d,p);return a.reset(),a},_e.a.prototype.beginHierarchyAnimation=function(r,t,e,n,i,o,a,s,d,p,b,P){o===void 0&&(o=1),d===void 0&&(d=!0),P===void 0&&(P=!1);var O=r.getDescendants(t),B=[];B.push(this.beginAnimation(r,e,n,i,o,a,s,d,p,void 0,P));for(var F=0,z=O;F<z.length;F++){var J=z[F];B.push(this.beginAnimation(J,e,n,i,o,a,s,d,p,void 0,P))}return B},_e.a.prototype.beginDirectAnimation=function(r,t,e,n,i,o,a,s,d){return d===void 0&&(d=!1),o===void 0&&(o=1),e>n&&o>0&&(o*=-1),new ke(this,r,e,n,i,o,a,t,s,d)},_e.a.prototype.beginDirectHierarchyAnimation=function(r,t,e,n,i,o,a,s,d,p){p===void 0&&(p=!1);var b=r.getDescendants(t),P=[];P.push(this.beginDirectAnimation(r,e,n,i,o,a,s,d,p));for(var O=0,B=b;O<B.length;O++){var F=B[O];P.push(this.beginDirectAnimation(F,e,n,i,o,a,s,d,p))}return P},_e.a.prototype.getAnimatableByTarget=function(r){for(var t=0;t<this._activeAnimatables.length;t++)if(this._activeAnimatables[t].target===r)return this._activeAnimatables[t];return null},_e.a.prototype.getAllAnimatablesByTarget=function(r){for(var t=[],e=0;e<this._activeAnimatables.length;e++)this._activeAnimatables[e].target===r&&t.push(this._activeAnimatables[e]);return t},_e.a.prototype.stopAnimation=function(r,t,e){for(var n=0,i=this.getAllAnimatablesByTarget(r);n<i.length;n++)i[n].stop(t,e)},_e.a.prototype.stopAllAnimations=function(){if(this._activeAnimatables){for(var r=0;r<this._activeAnimatables.length;r++)this._activeAnimatables[r].stop();this._activeAnimatables=[]}for(var t=0,e=this.animationGroups;t<e.length;t++)e[t].stop()},_e.a.prototype._registerTargetForLateAnimationBinding=function(r,t){var e=r.target;this._registeredForLateAnimationBindings.pushNoDuplicate(e),e._lateAnimationHolders||(e._lateAnimationHolders={}),e._lateAnimationHolders[r.targetPath]||(e._lateAnimationHolders[r.targetPath]={totalWeight:0,totalAdditiveWeight:0,animations:[],additiveAnimations:[],originalValue:t}),r.isAdditive?(e._lateAnimationHolders[r.targetPath].additiveAnimations.push(r),e._lateAnimationHolders[r.targetPath].totalAdditiveWeight+=r.weight):(e._lateAnimationHolders[r.targetPath].animations.push(r),e._lateAnimationHolders[r.targetPath].totalWeight+=r.weight)},_e.a.prototype._processLateAnimationBindingsForMatrices=function(r){if(r.totalWeight===0&&r.totalAdditiveWeight===0)return r.originalValue;var t=1,e=u.c.Vector3[0],n=u.c.Vector3[1],i=u.c.Quaternion[0],o=0,a=r.animations[0],s=r.originalValue,d=1,p=!1;if(r.totalWeight<1)d=1-r.totalWeight,s.decompose(n,i,e);else{if(o=1,t=r.totalWeight,(d=a.weight/t)==1){if(!r.totalAdditiveWeight)return a.currentValue;p=!0}a.currentValue.decompose(n,i,e)}if(!p){n.scaleInPlace(d),e.scaleInPlace(d),i.scaleInPlace(d);for(var b=o;b<r.animations.length;b++)if((z=r.animations[b]).weight!==0){d=z.weight/t;var P=u.c.Vector3[2],O=u.c.Vector3[3],B=u.c.Quaternion[1];z.currentValue.decompose(O,B,P),O.scaleAndAddToRef(d,n),B.scaleAndAddToRef(d,i),P.scaleAndAddToRef(d,e)}}for(var F=0;F<r.additiveAnimations.length;F++){var z;(z=r.additiveAnimations[F]).weight!==0&&(P=u.c.Vector3[2],O=u.c.Vector3[3],B=u.c.Quaternion[1],z.currentValue.decompose(O,B,P),O.multiplyToRef(n,O),u.e.LerpToRef(n,O,z.weight,n),i.multiplyToRef(B,B),u.b.SlerpToRef(i,B,z.weight,i),P.scaleAndAddToRef(z.weight,e))}var J=a?a._animationState.workValue:u.c.Matrix[0].clone();return u.a.ComposeToRef(n,i,e,J),J},_e.a.prototype._processLateAnimationBindingsForQuaternions=function(r,t){if(r.totalWeight===0&&r.totalAdditiveWeight===0)return t;var e=r.animations[0],n=r.originalValue,i=t;if(r.totalWeight===0&&r.totalAdditiveWeight>0)i.copyFrom(n);else if(r.animations.length===1){if(u.b.SlerpToRef(n,e.currentValue,Math.min(1,r.totalWeight),i),r.totalAdditiveWeight===0)return i}else if(r.animations.length>1){var o=1,a=void 0,s=void 0;if(r.totalWeight<1){var d=1-r.totalWeight;s=[],(a=[]).push(n),s.push(d)}else{if(r.animations.length===2&&(u.b.SlerpToRef(r.animations[0].currentValue,r.animations[1].currentValue,r.animations[1].weight/r.totalWeight,t),r.totalAdditiveWeight===0))return t;a=[],s=[],o=r.totalWeight}for(var p=0;p<r.animations.length;p++){var b=r.animations[p];a.push(b.currentValue),s.push(b.weight/o)}for(var P=0,O=0;O<a.length;)O?(P+=s[O],u.b.SlerpToRef(i,a[O],s[O]/P,i),O++):(u.b.SlerpToRef(a[O],a[O+1],s[O+1]/(s[O]+s[O+1]),t),i=t,P=s[O]+s[O+1],O+=2)}for(var B=0;B<r.additiveAnimations.length;B++)(b=r.additiveAnimations[B]).weight!==0&&(i.multiplyToRef(b.currentValue,u.c.Quaternion[0]),u.b.SlerpToRef(i,u.c.Quaternion[0],b.weight,i));return i},_e.a.prototype._processLateAnimationBindings=function(){if(this._registeredForLateAnimationBindings.length){for(var r=0;r<this._registeredForLateAnimationBindings.length;r++){var t=this._registeredForLateAnimationBindings.data[r];for(var e in t._lateAnimationHolders){var n=t._lateAnimationHolders[e],i=n.animations[0],o=n.originalValue,a=k.AllowMatrixDecomposeForInterpolation&&o.m,s=t[e];if(a)s=this._processLateAnimationBindingsForMatrices(n);else if(o.w!==void 0)s=this._processLateAnimationBindingsForQuaternions(n,s||u.b.Identity());else{var d=0,p=1;if(n.totalWeight<1)s=i&&o.scale?o.scale(1-n.totalWeight):i?o*(1-n.totalWeight):o.clone?o.clone():o;else if(i){p=n.totalWeight;var b=i.weight/p;s=b!==1?i.currentValue.scale?i.currentValue.scale(b):i.currentValue*b:i.currentValue,d=1}for(var P=d;P<n.animations.length;P++)(F=(B=n.animations[P]).weight/p)&&(B.currentValue.scaleAndAddToRef?B.currentValue.scaleAndAddToRef(F,s):s+=B.currentValue*F);for(var O=0;O<n.additiveAnimations.length;O++){var B,F;(F=(B=n.additiveAnimations[O]).weight)&&(B.currentValue.scaleAndAddToRef?B.currentValue.scaleAndAddToRef(F,s):s+=B.currentValue*F)}}t[e]=s}t._lateAnimationHolders={}}this._registeredForLateAnimationBindings.reset()}},Be.prototype.copyAnimationRange=function(r,t,e,n,i){n===void 0&&(n=!1),i===void 0&&(i=null),this.animations.length===0&&(this.animations.push(new k(this.name,"_matrix",r.animations[0].framePerSecond,k.ANIMATIONTYPE_MATRIX,0)),this.animations[0].setKeys([]));var o=r.animations[0].getRange(t);if(!o)return!1;for(var a,s,d,p=o.from,b=o.to,P=r.animations[0].getKeys(),O=r.length,B=r.getParent(),F=this.getParent(),z=n&&B&&O&&this.length&&O!==this.length,J=z&&F&&B?F.length/B.length:1,ie=n&&!F&&i&&(i.x!==1||i.y!==1||i.z!==1),se=this.animations[0].getKeys(),ce=0,ue=P.length;ce<ue;ce++)(a=P[ce]).frame>=p&&a.frame<=b&&(n?(d=a.value.clone(),z?(s=d.getTranslation(),d.setTranslation(s.scaleInPlace(J))):ie&&i?(s=d.getTranslation(),d.setTranslation(s.multiplyInPlace(i))):d=a.value):d=a.value,se.push({frame:a.frame+e,value:d}));return this.animations[0].createRange(t,p+e,b+e),!0};var We=function(){function r(){}return r.prototype.getClassName=function(){return"TargetedAnimation"},r.prototype.serialize=function(){var t={};return t.animation=this.animation.serialize(),t.targetId=this.target.id,t},r}(),je=function(){function r(t,e){e===void 0&&(e=null),this.name=t,this._targetedAnimations=new Array,this._animatables=new Array,this._from=Number.MAX_VALUE,this._to=-Number.MAX_VALUE,this._speedRatio=1,this._loopAnimation=!1,this._isAdditive=!1,this.onAnimationEndObservable=new x.c,this.onAnimationLoopObservable=new x.c,this.onAnimationGroupLoopObservable=new x.c,this.onAnimationGroupEndObservable=new x.c,this.onAnimationGroupPauseObservable=new x.c,this.onAnimationGroupPlayObservable=new x.c,this._scene=e||te.a.LastCreatedScene,this.uniqueId=this._scene.getUniqueId(),this._scene.addAnimationGroup(this)}return Object.defineProperty(r.prototype,"from",{get:function(){return this._from},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"to",{get:function(){return this._to},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isStarted",{get:function(){return this._isStarted},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isPlaying",{get:function(){return this._isStarted&&!this._isPaused},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"speedRatio",{get:function(){return this._speedRatio},set:function(t){if(this._speedRatio!==t){this._speedRatio=t;for(var e=0;e<this._animatables.length;e++)this._animatables[e].speedRatio=this._speedRatio}},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"loopAnimation",{get:function(){return this._loopAnimation},set:function(t){if(this._loopAnimation!==t){this._loopAnimation=t;for(var e=0;e<this._animatables.length;e++)this._animatables[e].loopAnimation=this._loopAnimation}},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isAdditive",{get:function(){return this._isAdditive},set:function(t){if(this._isAdditive!==t){this._isAdditive=t;for(var e=0;e<this._animatables.length;e++)this._animatables[e].isAdditive=this._isAdditive}},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"targetedAnimations",{get:function(){return this._targetedAnimations},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"animatables",{get:function(){return this._animatables},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"children",{get:function(){return this._targetedAnimations},enumerable:!1,configurable:!0}),r.prototype.addTargetedAnimation=function(t,e){var n=new We;n.animation=t,n.target=e;var i=t.getKeys();return this._from>i[0].frame&&(this._from=i[0].frame),this._to<i[i.length-1].frame&&(this._to=i[i.length-1].frame),this._targetedAnimations.push(n),n},r.prototype.normalize=function(t,e){t===void 0&&(t=null),e===void 0&&(e=null),t==null&&(t=this._from),e==null&&(e=this._to);for(var n=0;n<this._targetedAnimations.length;n++){var i=this._targetedAnimations[n].animation.getKeys(),o=i[0],a=i[i.length-1];if(o.frame>t){var s={frame:t,value:o.value,inTangent:o.inTangent,outTangent:o.outTangent,interpolation:o.interpolation};i.splice(0,0,s)}a.frame<e&&(s={frame:e,value:a.value,inTangent:a.inTangent,outTangent:a.outTangent,interpolation:a.interpolation},i.push(s))}return this._from=t,this._to=e,this},r.prototype._processLoop=function(t,e,n){var i=this;t.onAnimationLoop=function(){i.onAnimationLoopObservable.notifyObservers(e),i._animationLoopFlags[n]||(i._animationLoopFlags[n]=!0,i._animationLoopCount++,i._animationLoopCount===i._targetedAnimations.length&&(i.onAnimationGroupLoopObservable.notifyObservers(i),i._animationLoopCount=0,i._animationLoopFlags=[]))}},r.prototype.start=function(t,e,n,i,o){var a=this;if(t===void 0&&(t=!1),e===void 0&&(e=1),this._isStarted||this._targetedAnimations.length===0)return this;this._loopAnimation=t,this._animationLoopCount=0,this._animationLoopFlags=[];for(var s=function(){var P=d._targetedAnimations[p],O=d._scene.beginDirectAnimation(P.target,[P.animation],n!==void 0?n:d._from,i!==void 0?i:d._to,t,e,void 0,void 0,o!==void 0?o:d._isAdditive);O.onAnimationEnd=function(){a.onAnimationEndObservable.notifyObservers(P),a._checkAnimationGroupEnded(O)},d._processLoop(O,P,p),d._animatables.push(O)},d=this,p=0;p<this._targetedAnimations.length;p++)s();if(this._speedRatio=e,n!==void 0&&i!==void 0)if(n<i&&this._speedRatio<0){var b=i;i=n,n=b}else n>i&&this._speedRatio>0&&(this._speedRatio=-e);return this._isStarted=!0,this._isPaused=!1,this.onAnimationGroupPlayObservable.notifyObservers(this),this},r.prototype.pause=function(){if(!this._isStarted)return this;this._isPaused=!0;for(var t=0;t<this._animatables.length;t++)this._animatables[t].pause();return this.onAnimationGroupPauseObservable.notifyObservers(this),this},r.prototype.play=function(t){return this.isStarted&&this._animatables.length===this._targetedAnimations.length?(t!==void 0&&(this.loopAnimation=t),this.restart()):(this.stop(),this.start(t,this._speedRatio)),this._isPaused=!1,this},r.prototype.reset=function(){if(!this._isStarted)return this.play(),this.goToFrame(0),this.stop(),this;for(var t=0;t<this._animatables.length;t++)this._animatables[t].reset();return this},r.prototype.restart=function(){if(!this._isStarted)return this;for(var t=0;t<this._animatables.length;t++)this._animatables[t].restart();return this.onAnimationGroupPlayObservable.notifyObservers(this),this},r.prototype.stop=function(){if(!this._isStarted)return this;for(var t=this._animatables.slice(),e=0;e<t.length;e++)t[e].stop();return this._isStarted=!1,this},r.prototype.setWeightForAllAnimatables=function(t){for(var e=0;e<this._animatables.length;e++)this._animatables[e].weight=t;return this},r.prototype.syncAllAnimationsWith=function(t){for(var e=0;e<this._animatables.length;e++)this._animatables[e].syncWith(t);return this},r.prototype.goToFrame=function(t){if(!this._isStarted)return this;for(var e=0;e<this._animatables.length;e++)this._animatables[e].goToFrame(t);return this},r.prototype.dispose=function(){this._targetedAnimations=[],this._animatables=[];var t=this._scene.animationGroups.indexOf(this);t>-1&&this._scene.animationGroups.splice(t,1),this.onAnimationEndObservable.clear(),this.onAnimationGroupEndObservable.clear(),this.onAnimationGroupPauseObservable.clear(),this.onAnimationGroupPlayObservable.clear(),this.onAnimationLoopObservable.clear(),this.onAnimationGroupLoopObservable.clear()},r.prototype._checkAnimationGroupEnded=function(t){var e=this._animatables.indexOf(t);e>-1&&this._animatables.splice(e,1),this._animatables.length===0&&(this._isStarted=!1,this.onAnimationGroupEndObservable.notifyObservers(this))},r.prototype.clone=function(t,e){for(var n=new r(t||this.name,this._scene),i=0,o=this._targetedAnimations;i<o.length;i++){var a=o[i];n.addTargetedAnimation(a.animation.clone(),e?e(a.target):a.target)}return n},r.prototype.serialize=function(){var t={};t.name=this.name,t.from=this.from,t.to=this.to,t.targetedAnimations=[];for(var e=0;e<this.targetedAnimations.length;e++){var n=this.targetedAnimations[e];t.targetedAnimations[e]=n.serialize()}return t},r.Parse=function(t,e){for(var n=new r(t.name,e),i=0;i<t.targetedAnimations.length;i++){var o=t.targetedAnimations[i],a=k.Parse(o.animation),s=o.targetId;if(o.animation.property==="influence"){var d=e.getMorphTargetById(s);d&&n.addTargetedAnimation(a,d)}else{var p=e.getNodeByID(s);p!=null&&n.addTargetedAnimation(a,p)}}return t.from!==null&&t.to!==null&&n.normalize(t.from,t.to),n},r.MakeAnimationAdditive=function(t,e,n,i,o){e===void 0&&(e=0),i===void 0&&(i=!1);var a=t;i&&(a=t.clone(o||a.name));for(var s=a.targetedAnimations,d=0;d<s.length;d++){var p=s[d];k.MakeAnimationAdditive(p.animation,e,n)}return a.isAdditive=!0,a},r.prototype.getClassName=function(){return"AnimationGroup"},r.prototype.toString=function(t){var e="Name: "+this.name;return e+=", type: "+this.getClassName(),t&&(e+=", from: "+this._from,e+=", to: "+this._to,e+=", isStarted: "+this._isStarted,e+=", speedRatio: "+this._speedRatio,e+=", targetedAnimations length: "+this._targetedAnimations.length,e+=", animatables length: "+this._animatables),e},r}(),He=function(){this.enableBlending=!1,this.blendingSpeed=.01,this.loopMode=k.ANIMATIONLOOPMODE_CYCLE},qe=f(72),Ge=function(){function r(){this._easingMode=r.EASINGMODE_EASEIN}return r.prototype.setEasingMode=function(t){var e=Math.min(Math.max(t,0),2);this._easingMode=e},r.prototype.getEasingMode=function(){return this._easingMode},r.prototype.easeInCore=function(t){throw new Error("You must implement this method")},r.prototype.ease=function(t){switch(this._easingMode){case r.EASINGMODE_EASEIN:return this.easeInCore(t);case r.EASINGMODE_EASEOUT:return 1-this.easeInCore(1-t)}return t>=.5?.5*(1-this.easeInCore(2*(1-t)))+.5:.5*this.easeInCore(2*t)},r.EASINGMODE_EASEIN=0,r.EASINGMODE_EASEOUT=1,r.EASINGMODE_EASEINOUT=2,r}(),nt=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){return e=Math.max(0,Math.min(1,e)),1-Math.sqrt(1-e*e)},t}(Ge),$e=function(r){function t(e){e===void 0&&(e=1);var n=r.call(this)||this;return n.amplitude=e,n}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){var n=Math.max(0,this.amplitude);return Math.pow(e,3)-e*n*Math.sin(3.141592653589793*e)},t}(Ge),ct=function(r){function t(e,n){e===void 0&&(e=3),n===void 0&&(n=2);var i=r.call(this)||this;return i.bounces=e,i.bounciness=n,i}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){var n=Math.max(0,this.bounces),i=this.bounciness;i<=1&&(i=1.001);var o=Math.pow(i,n),a=1-i,s=(1-o)/a+.5*o,d=e*s,p=Math.log(-d*(1-i)+1)/Math.log(i),b=Math.floor(p),P=b+1,O=(1-Math.pow(i,b))/(a*s),B=.5*(O+(1-Math.pow(i,P))/(a*s)),F=e-B,z=B-O;return-Math.pow(1/i,n-b)/(z*z)*(F-z)*(F+z)},t}(Ge),st=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){return e*e*e},t}(Ge),mt=function(r){function t(e,n){e===void 0&&(e=3),n===void 0&&(n=3);var i=r.call(this)||this;return i.oscillations=e,i.springiness=n,i}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){var n=Math.max(0,this.oscillations),i=Math.max(0,this.springiness);return(i==0?e:(Math.exp(i*e)-1)/(Math.exp(i)-1))*Math.sin((6.283185307179586*n+1.5707963267948966)*e)},t}(Ge),St=function(r){function t(e){e===void 0&&(e=2);var n=r.call(this)||this;return n.exponent=e,n}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){return this.exponent<=0?e:(Math.exp(this.exponent*e)-1)/(Math.exp(this.exponent)-1)},t}(Ge),wt=function(r){function t(e){e===void 0&&(e=2);var n=r.call(this)||this;return n.power=e,n}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){var n=Math.max(0,this.power);return Math.pow(e,n)},t}(Ge),It=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){return e*e},t}(Ge),Pt=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){return e*e*e*e},t}(Ge),Ot=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){return e*e*e*e*e},t}(Ge),on=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){return 1-Math.sin(1.5707963267948966*(1-e))},t}(Ge),Zt=function(r){function t(e,n,i,o){e===void 0&&(e=0),n===void 0&&(n=0),i===void 0&&(i=1),o===void 0&&(o=1);var a=r.call(this)||this;return a.x1=e,a.y1=n,a.x2=i,a.y2=o,a}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){return qe.c.Interpolate(e,this.x1,this.y1,this.x2,this.y2)},t}(Ge),tn=function(){function r(t,e,n){this.frame=t,this.action=e,this.onlyOnce=n,this.isDone=!1}return r.prototype._clone=function(){return new r(this.frame,this.action,this.onlyOnce)},r}(),De=f(7),Pn=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t}(U.a),nn=function(){this.rootNodes=[],this.skeletons=[],this.animationGroups=[]},Cn=function(r){function t(e){var n=r.call(this)||this;return n._wasAddedToScene=!1,n.scene=e,n.sounds=[],n.effectLayers=[],n.layers=[],n.lensFlareSystems=[],n.proceduralTextures=[],n.reflectionProbes=[],e.onDisposeObservable.add(function(){n._wasAddedToScene||n.dispose()}),n}return Object(c.d)(t,r),t.prototype.instantiateModelsToScene=function(e,n){var i=this;n===void 0&&(n=!1);var o={},a={},s=new nn,d=[],p=[],b={doNotInstantiate:!0},P=function(O,B){if(o[O.uniqueId]=B.uniqueId,a[B.uniqueId]=B,e&&(B.name=e(O.name)),B instanceof De.a){var F=B;if(F.morphTargetManager){var z=O.morphTargetManager;F.morphTargetManager=z.clone();for(var J=0;J<z.numTargets;J++){var ie=z.getTarget(J),se=F.morphTargetManager.getTarget(J);o[ie.uniqueId]=se.uniqueId,a[se.uniqueId]=se}}}};return this.transformNodes.forEach(function(O){if(!O.parent){var B=O.instantiateHierarchy(null,b,function(F,z){P(F,z)});B&&s.rootNodes.push(B)}}),this.meshes.forEach(function(O){if(!O.parent){var B=O.instantiateHierarchy(null,b,function(F,z){if(P(F,z),z.material){var J=z;if(J.material)if(n){var ie=F.material;if(p.indexOf(ie)===-1){var se=ie.clone(e?e(ie.name):"Clone of "+ie.name);if(p.push(ie),o[ie.uniqueId]=se.uniqueId,a[se.uniqueId]=se,ie.getClassName()==="MultiMaterial"){for(var ce=ie,ue=0,fe=ce.subMaterials;ue<fe.length;ue++){var ve=fe[ue];ve&&(se=ve.clone(e?e(ve.name):"Clone of "+ve.name),p.push(ve),o[ve.uniqueId]=se.uniqueId,a[se.uniqueId]=se)}ce.subMaterials=ce.subMaterials.map(function(Te){return Te&&a[o[Te.uniqueId]]})}}J.material=a[o[ie.uniqueId]]}else J.material.getClassName()==="MultiMaterial"?i.scene.multiMaterials.indexOf(J.material)===-1&&i.scene.addMultiMaterial(J.material):i.scene.materials.indexOf(J.material)===-1&&i.scene.addMaterial(J.material)}});B&&s.rootNodes.push(B)}}),this.skeletons.forEach(function(O){var B=O.clone(e?e(O.name):"Clone of "+O.name);O.overrideMesh&&(B.overrideMesh=a[o[O.overrideMesh.uniqueId]]);for(var F=0,z=i.meshes;F<z.length;F++){var J=z[F];if(J.skeleton===O&&!J.isAnInstance){if(a[o[J.uniqueId]].skeleton=B,d.indexOf(B)!==-1)continue;d.push(B);for(var ie=0,se=B.bones;ie<se.length;ie++){var ce=se[ie];ce._linkedTransformNode&&(ce._linkedTransformNode=a[o[ce._linkedTransformNode.uniqueId]])}}}s.skeletons.push(B)}),this.animationGroups.forEach(function(O){var B=O.clone(O.name,function(F){return a[o[F.uniqueId]]||F});s.animationGroups.push(B)}),s},t.prototype.addAllToScene=function(){var e=this;this._wasAddedToScene=!0,this.cameras.forEach(function(o){e.scene.addCamera(o)}),this.lights.forEach(function(o){e.scene.addLight(o)}),this.meshes.forEach(function(o){e.scene.addMesh(o)}),this.skeletons.forEach(function(o){e.scene.addSkeleton(o)}),this.animations.forEach(function(o){e.scene.addAnimation(o)}),this.animationGroups.forEach(function(o){e.scene.addAnimationGroup(o)}),this.multiMaterials.forEach(function(o){e.scene.addMultiMaterial(o)}),this.materials.forEach(function(o){e.scene.addMaterial(o)}),this.morphTargetManagers.forEach(function(o){e.scene.addMorphTargetManager(o)}),this.geometries.forEach(function(o){e.scene.addGeometry(o)}),this.transformNodes.forEach(function(o){e.scene.addTransformNode(o)}),this.actionManagers.forEach(function(o){e.scene.addActionManager(o)}),this.textures.forEach(function(o){e.scene.addTexture(o)}),this.reflectionProbes.forEach(function(o){e.scene.addReflectionProbe(o)}),this.environmentTexture&&(this.scene.environmentTexture=this.environmentTexture);for(var n=0,i=this.scene._serializableComponents;n<i.length;n++)i[n].addFromContainer(this)},t.prototype.removeAllFromScene=function(){var e=this;this._wasAddedToScene=!1,this.cameras.forEach(function(o){e.scene.removeCamera(o)}),this.lights.forEach(function(o){e.scene.removeLight(o)}),this.meshes.forEach(function(o){e.scene.removeMesh(o)}),this.skeletons.forEach(function(o){e.scene.removeSkeleton(o)}),this.animations.forEach(function(o){e.scene.removeAnimation(o)}),this.animationGroups.forEach(function(o){e.scene.removeAnimationGroup(o)}),this.multiMaterials.forEach(function(o){e.scene.removeMultiMaterial(o)}),this.materials.forEach(function(o){e.scene.removeMaterial(o)}),this.morphTargetManagers.forEach(function(o){e.scene.removeMorphTargetManager(o)}),this.geometries.forEach(function(o){e.scene.removeGeometry(o)}),this.transformNodes.forEach(function(o){e.scene.removeTransformNode(o)}),this.actionManagers.forEach(function(o){e.scene.removeActionManager(o)}),this.textures.forEach(function(o){e.scene.removeTexture(o)}),this.reflectionProbes.forEach(function(o){e.scene.removeReflectionProbe(o)}),this.environmentTexture===this.scene.environmentTexture&&(this.scene.environmentTexture=null);for(var n=0,i=this.scene._serializableComponents;n<i.length;n++)i[n].removeFromContainer(this)},t.prototype.dispose=function(){this.cameras.forEach(function(i){i.dispose()}),this.cameras=[],this.lights.forEach(function(i){i.dispose()}),this.lights=[],this.meshes.forEach(function(i){i.dispose()}),this.meshes=[],this.skeletons.forEach(function(i){i.dispose()}),this.skeletons=[],this.animationGroups.forEach(function(i){i.dispose()}),this.animationGroups=[],this.multiMaterials.forEach(function(i){i.dispose()}),this.multiMaterials=[],this.materials.forEach(function(i){i.dispose()}),this.materials=[],this.geometries.forEach(function(i){i.dispose()}),this.geometries=[],this.transformNodes.forEach(function(i){i.dispose()}),this.transformNodes=[],this.actionManagers.forEach(function(i){i.dispose()}),this.actionManagers=[],this.textures.forEach(function(i){i.dispose()}),this.textures=[],this.reflectionProbes.forEach(function(i){i.dispose()}),this.reflectionProbes=[],this.environmentTexture&&(this.environmentTexture.dispose(),this.environmentTexture=null);for(var e=0,n=this.scene._serializableComponents;e<n.length;e++)n[e].removeFromContainer(this,!0)},t.prototype._moveAssets=function(e,n,i){if(e)for(var o=0,a=e;o<a.length;o++){var s=a[o],d=!0;if(i){for(var p=0,b=i;p<b.length;p++)if(s===b[p]){d=!1;break}}d&&n.push(s)}},t.prototype.moveAllFromScene=function(e){for(var n in this._wasAddedToScene=!1,e===void 0&&(e=new Pn),this)this.hasOwnProperty(n)&&(this[n]=this[n]||(n==="environmentTexture"?null:[]),this._moveAssets(this.scene[n],this[n],e[n]));this.environmentTexture=this.scene.environmentTexture,this.removeAllFromScene()},t.prototype.createRootMesh=function(){var e=new De.a("assetContainerRootMesh",this.scene);return this.meshes.forEach(function(n){n.parent||e.addChild(n)}),this.meshes.unshift(e),e},t.prototype.mergeAnimationsTo=function(e,n,i){if(e===void 0&&(e=te.a.LastCreatedScene),i===void 0&&(i=null),!e)return l.a.Error("No scene available to merge animations to"),[];var o=i||function(s){var d=null,p=s.animations.length?s.animations[0].targetProperty:"",b=s.name.split(".").join("").split("_primitive")[0];switch(p){case"position":case"rotationQuaternion":d=e.getTransformNodeByName(s.name)||e.getTransformNodeByName(b);break;case"influence":d=e.getMorphTargetByName(s.name)||e.getMorphTargetByName(b);break;default:d=e.getNodeByName(s.name)||e.getNodeByName(b)}return d};this.getNodes().forEach(function(s){var d=o(s);if(d!==null){for(var p=function(O){for(var B=0,F=d.animations.filter(function(ie){return ie.targetProperty===O.targetProperty});B<F.length;B++){var z=F[B],J=d.animations.indexOf(z,0);J>-1&&d.animations.splice(J,1)}},b=0,P=s.animations;b<P.length;b++)p(P[b]);d.animations=d.animations.concat(s.animations)}});var a=new Array;return this.animationGroups.slice().forEach(function(s){a.push(s.clone(s.name,o)),s.animatables.forEach(function(d){d.stop()})}),n.forEach(function(s){var d=o(s.target);d&&(e.beginAnimation(d,s.fromFrame,s.toFrame,s.loopAnimation,s.speedRatio,s.onAnimationEnd?s.onAnimationEnd:void 0,void 0,!0,void 0,s.onAnimationLoop?s.onAnimationLoop:void 0),e.stopAnimation(s.target))}),a},t}(U.a),Ue=f(13),xn=function(){function r(t){this.SMOOTHING=.75,this.FFT_SIZE=512,this.BARGRAPHAMPLITUDE=256,this.DEBUGCANVASPOS={x:20,y:20},this.DEBUGCANVASSIZE={width:320,height:200},this._scene=t,this._audioEngine=Ue.a.audioEngine,this._audioEngine.canUseWebAudio&&this._audioEngine.audioContext&&(this._webAudioAnalyser=this._audioEngine.audioContext.createAnalyser(),this._webAudioAnalyser.minDecibels=-140,this._webAudioAnalyser.maxDecibels=0,this._byteFreqs=new Uint8Array(this._webAudioAnalyser.frequencyBinCount),this._byteTime=new Uint8Array(this._webAudioAnalyser.frequencyBinCount),this._floatFreqs=new Float32Array(this._webAudioAnalyser.frequencyBinCount))}return r.prototype.getFrequencyBinCount=function(){return this._audioEngine.canUseWebAudio?this._webAudioAnalyser.frequencyBinCount:0},r.prototype.getByteFrequencyData=function(){return this._audioEngine.canUseWebAudio&&(this._webAudioAnalyser.smoothingTimeConstant=this.SMOOTHING,this._webAudioAnalyser.fftSize=this.FFT_SIZE,this._webAudioAnalyser.getByteFrequencyData(this._byteFreqs)),this._byteFreqs},r.prototype.getByteTimeDomainData=function(){return this._audioEngine.canUseWebAudio&&(this._webAudioAnalyser.smoothingTimeConstant=this.SMOOTHING,this._webAudioAnalyser.fftSize=this.FFT_SIZE,this._webAudioAnalyser.getByteTimeDomainData(this._byteTime)),this._byteTime},r.prototype.getFloatFrequencyData=function(){return this._audioEngine.canUseWebAudio&&(this._webAudioAnalyser.smoothingTimeConstant=this.SMOOTHING,this._webAudioAnalyser.fftSize=this.FFT_SIZE,this._webAudioAnalyser.getFloatFrequencyData(this._floatFreqs)),this._floatFreqs},r.prototype.drawDebugCanvas=function(){var t=this;if(this._audioEngine.canUseWebAudio&&(this._debugCanvas||(this._debugCanvas=document.createElement("canvas"),this._debugCanvas.width=this.DEBUGCANVASSIZE.width,this._debugCanvas.height=this.DEBUGCANVASSIZE.height,this._debugCanvas.style.position="absolute",this._debugCanvas.style.top=this.DEBUGCANVASPOS.y+"px",this._debugCanvas.style.left=this.DEBUGCANVASPOS.x+"px",this._debugCanvasContext=this._debugCanvas.getContext("2d"),document.body.appendChild(this._debugCanvas),this._registerFunc=function(){t.drawDebugCanvas()},this._scene.registerBeforeRender(this._registerFunc)),this._registerFunc&&this._debugCanvasContext)){var e=this.getByteFrequencyData();this._debugCanvasContext.fillStyle="rgb(0, 0, 0)",this._debugCanvasContext.fillRect(0,0,this.DEBUGCANVASSIZE.width,this.DEBUGCANVASSIZE.height);for(var n=0;n<this.getFrequencyBinCount();n++){var i=e[n]/this.BARGRAPHAMPLITUDE,o=this.DEBUGCANVASSIZE.height*i,a=this.DEBUGCANVASSIZE.height-o-1,s=this.DEBUGCANVASSIZE.width/this.getFrequencyBinCount(),d=n/this.getFrequencyBinCount()*360;this._debugCanvasContext.fillStyle="hsl("+d+", 100%, 50%)",this._debugCanvasContext.fillRect(n*s,a,s,o)}}},r.prototype.stopDebugCanvas=function(){this._debugCanvas&&(this._registerFunc&&(this._scene.unregisterBeforeRender(this._registerFunc),this._registerFunc=null),document.body.removeChild(this._debugCanvas),this._debugCanvas=null,this._debugCanvasContext=null)},r.prototype.connectAudioNodes=function(t,e){this._audioEngine.canUseWebAudio&&(t.connect(this._webAudioAnalyser),this._webAudioAnalyser.connect(e))},r.prototype.dispose=function(){this._audioEngine.canUseWebAudio&&this._webAudioAnalyser.disconnect()},r}();Ue.a.AudioEngineFactory=function(r){return new dr(r)};var dr=function(){function r(t){var e=this;t===void 0&&(t=null),this._audioContext=null,this._audioContextInitialized=!1,this._muteButton=null,this.canUseWebAudio=!1,this.WarnedWebAudioUnsupported=!1,this.isMP3supported=!1,this.isOGGsupported=!1,this.unlocked=!0,this.useCustomUnlockedButton=!1,this.onAudioUnlockedObservable=new x.c,this.onAudioLockedObservable=new x.c,this._tryToRun=!1,this._onResize=function(){e._moveButtonToTopLeft()},window.AudioContext===void 0&&window.webkitAudioContext===void 0||(window.AudioContext=window.AudioContext||window.webkitAudioContext,this.canUseWebAudio=!0);var n=document.createElement("audio");this._hostElement=t;try{n&&n.canPlayType&&(n.canPlayType('audio/mpeg; codecs="mp3"').replace(/^no$/,"")||n.canPlayType("audio/mp3").replace(/^no$/,""))&&(this.isMP3supported=!0)}catch{}try{n&&n.canPlayType&&n.canPlayType('audio/ogg; codecs="vorbis"').replace(/^no$/,"")&&(this.isOGGsupported=!0)}catch{}}return Object.defineProperty(r.prototype,"audioContext",{get:function(){return this._audioContextInitialized?this.unlocked||this._muteButton||this._displayMuteButton():this._initializeAudioContext(),this._audioContext},enumerable:!1,configurable:!0}),r.prototype.lock=function(){this._triggerSuspendedState()},r.prototype.unlock=function(){this._triggerRunningState()},r.prototype._resumeAudioContext=function(){var t;return this._audioContext.resume!==void 0&&(t=this._audioContext.resume()),t||Promise.resolve()},r.prototype._initializeAudioContext=function(){try{this.canUseWebAudio&&(this._audioContext=new AudioContext,this.masterGain=this._audioContext.createGain(),this.masterGain.gain.value=1,this.masterGain.connect(this._audioContext.destination),this._audioContextInitialized=!0,this._audioContext.state==="running"&&this._triggerRunningState())}catch(t){this.canUseWebAudio=!1,l.a.Error("Web Audio: "+t.message)}},r.prototype._triggerRunningState=function(){var t=this;this._tryToRun||(this._tryToRun=!0,this._resumeAudioContext().then(function(){t._tryToRun=!1,t._muteButton&&t._hideMuteButton(),t.unlocked=!0,t.onAudioUnlockedObservable.notifyObservers(t)}).catch(function(){t._tryToRun=!1,t.unlocked=!1}))},r.prototype._triggerSuspendedState=function(){this.unlocked=!1,this.onAudioLockedObservable.notifyObservers(this),this._displayMuteButton()},r.prototype._displayMuteButton=function(){var t=this;if(!this.useCustomUnlockedButton&&!this._muteButton){this._muteButton=document.createElement("BUTTON"),this._muteButton.className="babylonUnmuteIcon",this._muteButton.id="babylonUnmuteIconBtn",this._muteButton.title="Unmute";var e=".babylonUnmuteIcon { position: absolute; left: 20px; top: 20px; height: 40px; width: 60px; background-color: rgba(51,51,51,0.7); background-image: url("+(window.SVGSVGElement?"data:image/svg+xml;charset=UTF-8,%3Csvg%20version%3D%221.1%22%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20width%3D%2239%22%20height%3D%2232%22%20viewBox%3D%220%200%2039%2032%22%3E%3Cpath%20fill%3D%22white%22%20d%3D%22M9.625%2018.938l-0.031%200.016h-4.953q-0.016%200-0.031-0.016v-12.453q0-0.016%200.031-0.016h4.953q0.031%200%200.031%200.016v12.453zM12.125%207.688l8.719-8.703v27.453l-8.719-8.719-0.016-0.047v-9.938zM23.359%207.875l1.406-1.406%204.219%204.203%204.203-4.203%201.422%201.406-4.219%204.219%204.219%204.203-1.484%201.359-4.141-4.156-4.219%204.219-1.406-1.422%204.219-4.203z%22%3E%3C%2Fpath%3E%3C%2Fsvg%3E":"https://cdn.babylonjs.com/Assets/audio.png")+");  background-size: 80%; background-repeat:no-repeat; background-position: center; background-position-y: 4px; border: none; outline: none; transition: transform 0.125s ease-out; cursor: pointer; z-index: 9999; } .babylonUnmuteIcon:hover { transform: scale(1.05) } .babylonUnmuteIcon:active { background-color: rgba(51,51,51,1) }",n=document.createElement("style");n.appendChild(document.createTextNode(e)),document.getElementsByTagName("head")[0].appendChild(n),document.body.appendChild(this._muteButton),this._moveButtonToTopLeft(),this._muteButton.addEventListener("touchend",function(){t._triggerRunningState()},!0),this._muteButton.addEventListener("click",function(){t._triggerRunningState()},!0),window.addEventListener("resize",this._onResize)}},r.prototype._moveButtonToTopLeft=function(){this._hostElement&&this._muteButton&&(this._muteButton.style.top=this._hostElement.offsetTop+20+"px",this._muteButton.style.left=this._hostElement.offsetLeft+20+"px")},r.prototype._hideMuteButton=function(){this._muteButton&&(document.body.removeChild(this._muteButton),this._muteButton=null)},r.prototype.dispose=function(){this.canUseWebAudio&&this._audioContextInitialized&&(this._connectedAnalyser&&this._audioContext&&(this._connectedAnalyser.stopDebugCanvas(),this._connectedAnalyser.dispose(),this.masterGain.disconnect(),this.masterGain.connect(this._audioContext.destination),this._connectedAnalyser=null),this.masterGain.gain.value=1),this.WarnedWebAudioUnsupported=!1,this._hideMuteButton(),window.removeEventListener("resize",this._onResize),this.onAudioUnlockedObservable.clear(),this.onAudioLockedObservable.clear()},r.prototype.getGlobalVolume=function(){return this.canUseWebAudio&&this._audioContextInitialized?this.masterGain.gain.value:-1},r.prototype.setGlobalVolume=function(t){this.canUseWebAudio&&this._audioContextInitialized&&(this.masterGain.gain.value=t)},r.prototype.connectToAnalyser=function(t){this._connectedAnalyser&&this._connectedAnalyser.stopDebugCanvas(),this.canUseWebAudio&&this._audioContextInitialized&&this._audioContext&&(this._connectedAnalyser=t,this.masterGain.disconnect(),this._connectedAnalyser.connectAudioNodes(this.masterGain,this._audioContext.destination))},r}(),Xe=f(12),An=f(21),ti=function(){function r(t,e,n,i,o){var a,s,d,p,b=this;if(i===void 0&&(i=null),this.autoplay=!1,this.loop=!1,this.useCustomAttenuation=!1,this.isPlaying=!1,this.isPaused=!1,this.spatialSound=!1,this.refDistance=1,this.rolloffFactor=1,this.maxDistance=100,this.distanceModel="linear",this.metadata=null,this.onEndedObservable=new x.c,this._panningModel="equalpower",this._playbackRate=1,this._streaming=!1,this._startTime=0,this._startOffset=0,this._position=u.e.Zero(),this._positionInEmitterSpace=!1,this._localDirection=new u.e(1,0,0),this._volume=1,this._isReadyToPlay=!1,this._isDirectional=!1,this._coneInnerAngle=360,this._coneOuterAngle=360,this._coneOuterGain=0,this._isOutputConnected=!1,this._urlType="Unknown",this.name=t,this._scene=n,r._SceneComponentInitialization(n),this._readyToPlayCallback=i,this._customAttenuationFunction=function(J,ie,se,ce,ue){return ie<se?J*(1-ie/se):0},o&&(this.autoplay=o.autoplay||!1,this.loop=o.loop||!1,o.volume!==void 0&&(this._volume=o.volume),this.spatialSound=(a=o.spatialSound)!==null&&a!==void 0&&a,this.maxDistance=(s=o.maxDistance)!==null&&s!==void 0?s:100,this.useCustomAttenuation=(d=o.useCustomAttenuation)!==null&&d!==void 0&&d,this.rolloffFactor=o.rolloffFactor||1,this.refDistance=o.refDistance||1,this.distanceModel=o.distanceModel||"linear",this._playbackRate=o.playbackRate||1,this._streaming=(p=o.streaming)!==null&&p!==void 0&&p,this._length=o.length,this._offset=o.offset),Ue.a.audioEngine.canUseWebAudio&&Ue.a.audioEngine.audioContext){this._soundGain=Ue.a.audioEngine.audioContext.createGain(),this._soundGain.gain.value=this._volume,this._inputAudioNode=this._soundGain,this._outputAudioNode=this._soundGain,this.spatialSound&&this._createSpatialParameters(),this._scene.mainSoundTrack.addSound(this);var P=!0;if(e)try{typeof e=="string"?this._urlType="String":e instanceof ArrayBuffer?this._urlType="ArrayBuffer":e instanceof MediaStream?this._urlType="MediaStream":Array.isArray(e)&&(this._urlType="Array");var O=[],B=!1;switch(this._urlType){case"MediaStream":this._streaming=!0,this._isReadyToPlay=!0,this._streamingSource=Ue.a.audioEngine.audioContext.createMediaStreamSource(e),this.autoplay&&this.play(0,this._offset,this._length),this._readyToPlayCallback&&this._readyToPlayCallback();break;case"ArrayBuffer":e.byteLength>0&&(B=!0,this._soundLoaded(e));break;case"String":O.push(e);case"Array":O.length===0&&(O=e);for(var F=0;F<O.length;F++){var z=O[F];if(B=o&&o.skipCodecCheck||z.indexOf(".mp3",z.length-4)!==-1&&Ue.a.audioEngine.isMP3supported||z.indexOf(".ogg",z.length-4)!==-1&&Ue.a.audioEngine.isOGGsupported||z.indexOf(".wav",z.length-4)!==-1||z.indexOf(".m4a",z.length-4)!==-1||z.indexOf("blob:")!==-1){this._streaming?(this._htmlAudioElement=new Audio(z),this._htmlAudioElement.controls=!1,this._htmlAudioElement.loop=this.loop,Xe.b.SetCorsBehavior(z,this._htmlAudioElement),this._htmlAudioElement.preload="auto",this._htmlAudioElement.addEventListener("canplaythrough",function(){b._isReadyToPlay=!0,b.autoplay&&b.play(0,b._offset,b._length),b._readyToPlayCallback&&b._readyToPlayCallback()}),document.body.appendChild(this._htmlAudioElement),this._htmlAudioElement.load()):this._scene._loadFile(z,function(J){b._soundLoaded(J)},void 0,!0,!0,function(J){J&&l.a.Error("XHR "+J.status+" error on: "+z+"."),l.a.Error("Sound creation aborted."),b._scene.mainSoundTrack.removeSound(b)});break}}break;default:P=!1}P?B||(this._isReadyToPlay=!0,this._readyToPlayCallback&&window.setTimeout(function(){b._readyToPlayCallback&&b._readyToPlayCallback()},1e3)):l.a.Error("Parameter must be a URL to the sound, an Array of URLs (.mp3 & .ogg) or an ArrayBuffer of the sound.")}catch{l.a.Error("Unexpected error. Sound creation aborted."),this._scene.mainSoundTrack.removeSound(this)}}else this._scene.mainSoundTrack.addSound(this),Ue.a.audioEngine.WarnedWebAudioUnsupported||(l.a.Error("Web Audio is not supported by your browser."),Ue.a.audioEngine.WarnedWebAudioUnsupported=!0),this._readyToPlayCallback&&window.setTimeout(function(){b._readyToPlayCallback&&b._readyToPlayCallback()},1e3)}return Object.defineProperty(r.prototype,"currentTime",{get:function(){if(this._htmlAudioElement)return this._htmlAudioElement.currentTime;var t=this._startOffset;return this.isPlaying&&Ue.a.audioEngine.audioContext&&(t+=Ue.a.audioEngine.audioContext.currentTime-this._startTime),t},enumerable:!1,configurable:!0}),r.prototype.dispose=function(){Ue.a.audioEngine.canUseWebAudio&&(this.isPlaying&&this.stop(),this._isReadyToPlay=!1,this.soundTrackId===-1?this._scene.mainSoundTrack.removeSound(this):this._scene.soundTracks&&this._scene.soundTracks[this.soundTrackId].removeSound(this),this._soundGain&&(this._soundGain.disconnect(),this._soundGain=null),this._soundPanner&&(this._soundPanner.disconnect(),this._soundPanner=null),this._soundSource&&(this._soundSource.disconnect(),this._soundSource=null),this._audioBuffer=null,this._htmlAudioElement&&(this._htmlAudioElement.pause(),this._htmlAudioElement.src="",document.body.removeChild(this._htmlAudioElement)),this._streamingSource&&this._streamingSource.disconnect(),this._connectedTransformNode&&this._registerFunc&&(this._connectedTransformNode.unregisterAfterWorldMatrixUpdate(this._registerFunc),this._connectedTransformNode=null))},r.prototype.isReady=function(){return this._isReadyToPlay},r.prototype._soundLoaded=function(t){var e=this;Ue.a.audioEngine.audioContext&&Ue.a.audioEngine.audioContext.decodeAudioData(t,function(n){e._audioBuffer=n,e._isReadyToPlay=!0,e.autoplay&&e.play(0,e._offset,e._length),e._readyToPlayCallback&&e._readyToPlayCallback()},function(n){l.a.Error("Error while decoding audio data for: "+e.name+" / Error: "+n)})},r.prototype.setAudioBuffer=function(t){Ue.a.audioEngine.canUseWebAudio&&(this._audioBuffer=t,this._isReadyToPlay=!0)},r.prototype.updateOptions=function(t){var e,n,i,o,a,s,d,p,b;t&&(this.loop=(e=t.loop)!==null&&e!==void 0?e:this.loop,this.maxDistance=(n=t.maxDistance)!==null&&n!==void 0?n:this.maxDistance,this.useCustomAttenuation=(i=t.useCustomAttenuation)!==null&&i!==void 0?i:this.useCustomAttenuation,this.rolloffFactor=(o=t.rolloffFactor)!==null&&o!==void 0?o:this.rolloffFactor,this.refDistance=(a=t.refDistance)!==null&&a!==void 0?a:this.refDistance,this.distanceModel=(s=t.distanceModel)!==null&&s!==void 0?s:this.distanceModel,this._playbackRate=(d=t.playbackRate)!==null&&d!==void 0?d:this._playbackRate,this._length=(p=t.length)!==null&&p!==void 0?p:void 0,this._offset=(b=t.offset)!==null&&b!==void 0?b:void 0,this._updateSpatialParameters(),this.isPlaying&&(this._streaming&&this._htmlAudioElement?(this._htmlAudioElement.playbackRate=this._playbackRate,this._htmlAudioElement.loop!==this.loop&&(this._htmlAudioElement.loop=this.loop)):this._soundSource&&(this._soundSource.playbackRate.value=this._playbackRate,this._soundSource.loop!==this.loop&&(this._soundSource.loop=this.loop),this._offset!==void 0&&this._soundSource.loopStart!==this._offset&&(this._soundSource.loopStart=this._offset),this._length!==void 0&&this._length!==this._soundSource.loopEnd&&(this._soundSource.loopEnd=(0|this._offset)+this._length))))},r.prototype._createSpatialParameters=function(){Ue.a.audioEngine.canUseWebAudio&&Ue.a.audioEngine.audioContext&&(this._scene.headphone&&(this._panningModel="HRTF"),this._soundPanner=Ue.a.audioEngine.audioContext.createPanner(),this._soundPanner&&this._outputAudioNode&&(this._updateSpatialParameters(),this._soundPanner.connect(this._outputAudioNode),this._inputAudioNode=this._soundPanner))},r.prototype._updateSpatialParameters=function(){this.spatialSound&&this._soundPanner&&(this.useCustomAttenuation?(this._soundPanner.distanceModel="linear",this._soundPanner.maxDistance=Number.MAX_VALUE,this._soundPanner.refDistance=1,this._soundPanner.rolloffFactor=1,this._soundPanner.panningModel=this._panningModel):(this._soundPanner.distanceModel=this.distanceModel,this._soundPanner.maxDistance=this.maxDistance,this._soundPanner.refDistance=this.refDistance,this._soundPanner.rolloffFactor=this.rolloffFactor,this._soundPanner.panningModel=this._panningModel))},r.prototype.switchPanningModelToHRTF=function(){this._panningModel="HRTF",this._switchPanningModel()},r.prototype.switchPanningModelToEqualPower=function(){this._panningModel="equalpower",this._switchPanningModel()},r.prototype._switchPanningModel=function(){Ue.a.audioEngine.canUseWebAudio&&this.spatialSound&&this._soundPanner&&(this._soundPanner.panningModel=this._panningModel)},r.prototype.connectToSoundTrackAudioNode=function(t){Ue.a.audioEngine.canUseWebAudio&&this._outputAudioNode&&(this._isOutputConnected&&this._outputAudioNode.disconnect(),this._outputAudioNode.connect(t),this._isOutputConnected=!0)},r.prototype.setDirectionalCone=function(t,e,n){e<t?l.a.Error("setDirectionalCone(): outer angle of the cone must be superior or equal to the inner angle."):(this._coneInnerAngle=t,this._coneOuterAngle=e,this._coneOuterGain=n,this._isDirectional=!0,this.isPlaying&&this.loop&&(this.stop(),this.play(0,this._offset,this._length)))},Object.defineProperty(r.prototype,"directionalConeInnerAngle",{get:function(){return this._coneInnerAngle},set:function(t){if(t!=this._coneInnerAngle){if(this._coneOuterAngle<t)return void l.a.Error("directionalConeInnerAngle: outer angle of the cone must be superior or equal to the inner angle.");this._coneInnerAngle=t,Ue.a.audioEngine.canUseWebAudio&&this.spatialSound&&this._soundPanner&&(this._soundPanner.coneInnerAngle=this._coneInnerAngle)}},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"directionalConeOuterAngle",{get:function(){return this._coneOuterAngle},set:function(t){if(t!=this._coneOuterAngle){if(t<this._coneInnerAngle)return void l.a.Error("directionalConeOuterAngle: outer angle of the cone must be superior or equal to the inner angle.");this._coneOuterAngle=t,Ue.a.audioEngine.canUseWebAudio&&this.spatialSound&&this._soundPanner&&(this._soundPanner.coneOuterAngle=this._coneOuterAngle)}},enumerable:!1,configurable:!0}),r.prototype.setPosition=function(t){this._position=t,Ue.a.audioEngine.canUseWebAudio&&this.spatialSound&&this._soundPanner&&!isNaN(this._position.x)&&!isNaN(this._position.y)&&!isNaN(this._position.z)&&this._soundPanner.setPosition(this._position.x,this._position.y,this._position.z)},r.prototype.setLocalDirectionToMesh=function(t){this._localDirection=t,Ue.a.audioEngine.canUseWebAudio&&this._connectedTransformNode&&this.isPlaying&&this._updateDirection()},r.prototype._updateDirection=function(){if(this._connectedTransformNode&&this._soundPanner){var t=this._connectedTransformNode.getWorldMatrix(),e=u.e.TransformNormal(this._localDirection,t);e.normalize(),this._soundPanner.setOrientation(e.x,e.y,e.z)}},r.prototype.updateDistanceFromListener=function(){if(Ue.a.audioEngine.canUseWebAudio&&this._connectedTransformNode&&this.useCustomAttenuation&&this._soundGain&&this._scene.activeCamera){var t=this._connectedTransformNode.getDistanceToCamera(this._scene.activeCamera);this._soundGain.gain.value=this._customAttenuationFunction(this._volume,t,this.maxDistance,this.refDistance,this.rolloffFactor)}},r.prototype.setAttenuationFunction=function(t){this._customAttenuationFunction=t},r.prototype.play=function(t,e,n){var i=this;if(this._isReadyToPlay&&this._scene.audioEnabled&&Ue.a.audioEngine.audioContext)try{this._startOffset<0&&(t=-this._startOffset,this._startOffset=0);var o=t?Ue.a.audioEngine.audioContext.currentTime+t:Ue.a.audioEngine.audioContext.currentTime;if(this._soundSource&&this._streamingSource||this.spatialSound&&this._soundPanner&&(isNaN(this._position.x)||isNaN(this._position.y)||isNaN(this._position.z)||this._soundPanner.setPosition(this._position.x,this._position.y,this._position.z),this._isDirectional&&(this._soundPanner.coneInnerAngle=this._coneInnerAngle,this._soundPanner.coneOuterAngle=this._coneOuterAngle,this._soundPanner.coneOuterGain=this._coneOuterGain,this._connectedTransformNode?this._updateDirection():this._soundPanner.setOrientation(this._localDirection.x,this._localDirection.y,this._localDirection.z))),this._streaming)this._streamingSource||(this._streamingSource=Ue.a.audioEngine.audioContext.createMediaElementSource(this._htmlAudioElement),this._htmlAudioElement.onended=function(){i._onended()},this._htmlAudioElement.playbackRate=this._playbackRate),this._streamingSource.disconnect(),this._inputAudioNode&&this._streamingSource.connect(this._inputAudioNode),this._htmlAudioElement&&(a=function(){if(Ue.a.audioEngine.unlocked){var s=i._htmlAudioElement.play();s!==void 0&&s.catch(function(d){Ue.a.audioEngine.lock(),(i.loop||i.autoplay)&&Ue.a.audioEngine.onAudioUnlockedObservable.addOnce(function(){a()})})}else(i.loop||i.autoplay)&&Ue.a.audioEngine.onAudioUnlockedObservable.addOnce(function(){a()})})();else{var a=function(){if(Ue.a.audioEngine.audioContext){if(n=n||i._length,e=e||i._offset,i._soundSource){var s=i._soundSource;s.onended=function(){s.disconnect()}}if(i._soundSource=Ue.a.audioEngine.audioContext.createBufferSource(),i._soundSource&&i._inputAudioNode){i._soundSource.buffer=i._audioBuffer,i._soundSource.connect(i._inputAudioNode),i._soundSource.loop=i.loop,e!==void 0&&(i._soundSource.loopStart=e),n!==void 0&&(i._soundSource.loopEnd=(0|e)+n),i._soundSource.playbackRate.value=i._playbackRate,i._soundSource.onended=function(){i._onended()},o=t?Ue.a.audioEngine.audioContext.currentTime+t:Ue.a.audioEngine.audioContext.currentTime;var d=i.isPaused?i._startOffset%i._soundSource.buffer.duration:e||0;i._soundSource.start(o,d,i.loop?void 0:n)}}};Ue.a.audioEngine.audioContext.state==="suspended"?setTimeout(function(){Ue.a.audioEngine.audioContext.state==="suspended"?(Ue.a.audioEngine.lock(),(i.loop||i.autoplay)&&Ue.a.audioEngine.onAudioUnlockedObservable.addOnce(function(){a()})):a()},500):a()}this._startTime=o,this.isPlaying=!0,this.isPaused=!1}catch(s){l.a.Error("Error while trying to play audio: "+this.name+", "+s.message)}},r.prototype._onended=function(){this.isPlaying=!1,this._startOffset=0,this.onended&&this.onended(),this.onEndedObservable.notifyObservers(this)},r.prototype.stop=function(t){var e=this;if(this.isPlaying){if(this._streaming)this._htmlAudioElement?(this._htmlAudioElement.pause(),this._htmlAudioElement.currentTime>0&&(this._htmlAudioElement.currentTime=0)):this._streamingSource.disconnect(),this.isPlaying=!1;else if(Ue.a.audioEngine.audioContext&&this._soundSource){var n=t?Ue.a.audioEngine.audioContext.currentTime+t:Ue.a.audioEngine.audioContext.currentTime;this._soundSource.stop(n),this._soundSource.onended=function(){e.isPlaying=!1},this.isPaused||(this._startOffset=0)}}},r.prototype.pause=function(){this.isPlaying&&(this.isPaused=!0,this._streaming?this._htmlAudioElement?this._htmlAudioElement.pause():this._streamingSource.disconnect():Ue.a.audioEngine.audioContext&&(this.stop(0),this._startOffset+=Ue.a.audioEngine.audioContext.currentTime-this._startTime))},r.prototype.setVolume=function(t,e){Ue.a.audioEngine.canUseWebAudio&&this._soundGain&&(e&&Ue.a.audioEngine.audioContext?(this._soundGain.gain.cancelScheduledValues(Ue.a.audioEngine.audioContext.currentTime),this._soundGain.gain.setValueAtTime(this._soundGain.gain.value,Ue.a.audioEngine.audioContext.currentTime),this._soundGain.gain.linearRampToValueAtTime(t,Ue.a.audioEngine.audioContext.currentTime+e)):this._soundGain.gain.value=t),this._volume=t},r.prototype.setPlaybackRate=function(t){this._playbackRate=t,this.isPlaying&&(this._streaming&&this._htmlAudioElement?this._htmlAudioElement.playbackRate=this._playbackRate:this._soundSource&&(this._soundSource.playbackRate.value=this._playbackRate))},r.prototype.getVolume=function(){return this._volume},r.prototype.attachToMesh=function(t){var e=this;this._connectedTransformNode&&this._registerFunc&&(this._connectedTransformNode.unregisterAfterWorldMatrixUpdate(this._registerFunc),this._registerFunc=null),this._connectedTransformNode=t,this.spatialSound||(this.spatialSound=!0,this._createSpatialParameters(),this.isPlaying&&this.loop&&(this.stop(),this.play(0,this._offset,this._length))),this._onRegisterAfterWorldMatrixUpdate(this._connectedTransformNode),this._registerFunc=function(n){return e._onRegisterAfterWorldMatrixUpdate(n)},this._connectedTransformNode.registerAfterWorldMatrixUpdate(this._registerFunc)},r.prototype.detachFromMesh=function(){this._connectedTransformNode&&this._registerFunc&&(this._connectedTransformNode.unregisterAfterWorldMatrixUpdate(this._registerFunc),this._registerFunc=null,this._connectedTransformNode=null)},r.prototype._onRegisterAfterWorldMatrixUpdate=function(t){if(this._positionInEmitterSpace)t.worldMatrixFromCache.invertToRef(u.c.Matrix[0]),this.setPosition(u.c.Matrix[0].getTranslation());else if(t.getBoundingInfo){var e=t.getBoundingInfo();this.setPosition(e.boundingSphere.centerWorld)}else this.setPosition(t.absolutePosition);Ue.a.audioEngine.canUseWebAudio&&this._isDirectional&&this.isPlaying&&this._updateDirection()},r.prototype.clone=function(){var t=this;if(this._streaming)return null;var e=function(){t._isReadyToPlay?(i._audioBuffer=t.getAudioBuffer(),i._isReadyToPlay=!0,i.autoplay&&i.play(0,t._offset,t._length)):window.setTimeout(e,300)},n={autoplay:this.autoplay,loop:this.loop,volume:this._volume,spatialSound:this.spatialSound,maxDistance:this.maxDistance,useCustomAttenuation:this.useCustomAttenuation,rolloffFactor:this.rolloffFactor,refDistance:this.refDistance,distanceModel:this.distanceModel},i=new r(this.name+"_cloned",new ArrayBuffer(0),this._scene,null,n);return this.useCustomAttenuation&&i.setAttenuationFunction(this._customAttenuationFunction),i.setPosition(this._position),i.setPlaybackRate(this._playbackRate),e(),i},r.prototype.getAudioBuffer=function(){return this._audioBuffer},r.prototype.getSoundSource=function(){return this._soundSource},r.prototype.getSoundGain=function(){return this._soundGain},r.prototype.serialize=function(){var t={name:this.name,url:this.name,autoplay:this.autoplay,loop:this.loop,volume:this._volume,spatialSound:this.spatialSound,maxDistance:this.maxDistance,rolloffFactor:this.rolloffFactor,refDistance:this.refDistance,distanceModel:this.distanceModel,playbackRate:this._playbackRate,panningModel:this._panningModel,soundTrackId:this.soundTrackId,metadata:this.metadata};return this.spatialSound&&(this._connectedTransformNode&&(t.connectedMeshId=this._connectedTransformNode.id),t.position=this._position.asArray(),t.refDistance=this.refDistance,t.distanceModel=this.distanceModel,t.isDirectional=this._isDirectional,t.localDirectionToMesh=this._localDirection.asArray(),t.coneInnerAngle=this._coneInnerAngle,t.coneOuterAngle=this._coneOuterAngle,t.coneOuterGain=this._coneOuterGain),t},r.Parse=function(t,e,n,i){var o,a=t.name;o=t.url?n+t.url:n+a;var s,d={autoplay:t.autoplay,loop:t.loop,volume:t.volume,spatialSound:t.spatialSound,maxDistance:t.maxDistance,rolloffFactor:t.rolloffFactor,refDistance:t.refDistance,distanceModel:t.distanceModel,playbackRate:t.playbackRate};if(i){var p=function(){i._isReadyToPlay?(s._audioBuffer=i.getAudioBuffer(),s._isReadyToPlay=!0,s.autoplay&&s.play(0,s._offset,s._length)):window.setTimeout(p,300)};s=new r(a,new ArrayBuffer(0),e,null,d),p()}else s=new r(a,o,e,function(){e._removePendingData(s)},d),e._addPendingData(s);if(t.position){var b=u.e.FromArray(t.position);s.setPosition(b)}if(t.isDirectional&&(s.setDirectionalCone(t.coneInnerAngle||360,t.coneOuterAngle||360,t.coneOuterGain||0),t.localDirectionToMesh)){var P=u.e.FromArray(t.localDirectionToMesh);s.setLocalDirectionToMesh(P)}if(t.connectedMeshId){var O=e.getMeshByID(t.connectedMeshId);O&&s.attachToMesh(O)}return t.metadata&&(s.metadata=t.metadata),s},r._SceneComponentInitialization=function(t){throw An.a.WarnImport("AudioSceneComponent")},r}(),Lo=function(){function r(t,e){e===void 0&&(e={}),this.id=-1,this._isInitialized=!1,this._scene=t,this.soundCollection=new Array,this._options=e,!this._options.mainTrack&&this._scene.soundTracks&&(this._scene.soundTracks.push(this),this.id=this._scene.soundTracks.length-1)}return r.prototype._initializeSoundTrackAudioGraph=function(){Ue.a.audioEngine.canUseWebAudio&&Ue.a.audioEngine.audioContext&&(this._outputAudioNode=Ue.a.audioEngine.audioContext.createGain(),this._outputAudioNode.connect(Ue.a.audioEngine.masterGain),this._options&&this._options.volume&&(this._outputAudioNode.gain.value=this._options.volume),this._isInitialized=!0)},r.prototype.dispose=function(){if(Ue.a.audioEngine&&Ue.a.audioEngine.canUseWebAudio){for(this._connectedAnalyser&&this._connectedAnalyser.stopDebugCanvas();this.soundCollection.length;)this.soundCollection[0].dispose();this._outputAudioNode&&this._outputAudioNode.disconnect(),this._outputAudioNode=null}},r.prototype.addSound=function(t){this._isInitialized||this._initializeSoundTrackAudioGraph(),Ue.a.audioEngine.canUseWebAudio&&this._outputAudioNode&&t.connectToSoundTrackAudioNode(this._outputAudioNode),t.soundTrackId&&(t.soundTrackId===-1?this._scene.mainSoundTrack.removeSound(t):this._scene.soundTracks&&this._scene.soundTracks[t.soundTrackId].removeSound(t)),this.soundCollection.push(t),t.soundTrackId=this.id},r.prototype.removeSound=function(t){var e=this.soundCollection.indexOf(t);e!==-1&&this.soundCollection.splice(e,1)},r.prototype.setVolume=function(t){Ue.a.audioEngine.canUseWebAudio&&this._outputAudioNode&&(this._outputAudioNode.gain.value=t)},r.prototype.switchPanningModelToHRTF=function(){if(Ue.a.audioEngine.canUseWebAudio)for(var t=0;t<this.soundCollection.length;t++)this.soundCollection[t].switchPanningModelToHRTF()},r.prototype.switchPanningModelToEqualPower=function(){if(Ue.a.audioEngine.canUseWebAudio)for(var t=0;t<this.soundCollection.length;t++)this.soundCollection[t].switchPanningModelToEqualPower()},r.prototype.connectToAnalyser=function(t){this._connectedAnalyser&&this._connectedAnalyser.stopDebugCanvas(),this._connectedAnalyser=t,Ue.a.audioEngine.canUseWebAudio&&this._outputAudioNode&&(this._outputAudioNode.disconnect(),this._connectedAnalyser.connectAudioNodes(this._outputAudioNode,Ue.a.audioEngine.masterGain))},r}(),at=f(17);U.a.AddParser(at.a.NAME_AUDIO,function(r,t,e,n){var i,o=[];if(e.sounds=e.sounds||[],r.sounds!==void 0&&r.sounds!==null)for(var a=0,s=r.sounds.length;a<s;a++){var d=r.sounds[a];Ue.a.audioEngine.canUseWebAudio?(d.url||(d.url=d.name),o[d.url]?e.sounds.push(ti.Parse(d,t,n,o[d.url])):(i=ti.Parse(d,t,n),o[d.url]=i,e.sounds.push(i))):e.sounds.push(new ti(d.name,null,t))}o=[]}),Object.defineProperty(_e.a.prototype,"mainSoundTrack",{get:function(){var r=this._getComponent(at.a.NAME_AUDIO);return r||(r=new ni(this),this._addComponent(r)),this._mainSoundTrack||(this._mainSoundTrack=new Lo(this,{mainTrack:!0})),this._mainSoundTrack},enumerable:!0,configurable:!0}),_e.a.prototype.getSoundByName=function(r){var t;for(t=0;t<this.mainSoundTrack.soundCollection.length;t++)if(this.mainSoundTrack.soundCollection[t].name===r)return this.mainSoundTrack.soundCollection[t];if(this.soundTracks){for(var e=0;e<this.soundTracks.length;e++)for(t=0;t<this.soundTracks[e].soundCollection.length;t++)if(this.soundTracks[e].soundCollection[t].name===r)return this.soundTracks[e].soundCollection[t]}return null},Object.defineProperty(_e.a.prototype,"audioEnabled",{get:function(){var r=this._getComponent(at.a.NAME_AUDIO);return r||(r=new ni(this),this._addComponent(r)),r.audioEnabled},set:function(r){var t=this._getComponent(at.a.NAME_AUDIO);t||(t=new ni(this),this._addComponent(t)),r?t.enableAudio():t.disableAudio()},enumerable:!0,configurable:!0}),Object.defineProperty(_e.a.prototype,"headphone",{get:function(){var r=this._getComponent(at.a.NAME_AUDIO);return r||(r=new ni(this),this._addComponent(r)),r.headphone},set:function(r){var t=this._getComponent(at.a.NAME_AUDIO);t||(t=new ni(this),this._addComponent(t)),r?t.switchAudioModeForHeadphones():t.switchAudioModeForNormalSpeakers()},enumerable:!0,configurable:!0}),Object.defineProperty(_e.a.prototype,"audioListenerPositionProvider",{get:function(){var r=this._getComponent(at.a.NAME_AUDIO);return r||(r=new ni(this),this._addComponent(r)),r.audioListenerPositionProvider},set:function(r){var t=this._getComponent(at.a.NAME_AUDIO);if(t||(t=new ni(this),this._addComponent(t)),typeof r!="function")throw new Error("The value passed to [Scene.audioListenerPositionProvider] must be a function that returns a Vector3");t.audioListenerPositionProvider=r},enumerable:!0,configurable:!0}),Object.defineProperty(_e.a.prototype,"audioPositioningRefreshRate",{get:function(){var r=this._getComponent(at.a.NAME_AUDIO);return r||(r=new ni(this),this._addComponent(r)),r.audioPositioningRefreshRate},set:function(r){var t=this._getComponent(at.a.NAME_AUDIO);t||(t=new ni(this),this._addComponent(t)),t.audioPositioningRefreshRate=r},enumerable:!0,configurable:!0});var ni=function(){function r(t){this.name=at.a.NAME_AUDIO,this._audioEnabled=!0,this._headphone=!1,this.audioPositioningRefreshRate=500,this._audioListenerPositionProvider=null,this._cachedCameraDirection=new u.e,this._cachedCameraPosition=new u.e,this._lastCheck=0,this.scene=t,t.soundTracks=new Array,t.sounds=new Array}return Object.defineProperty(r.prototype,"audioEnabled",{get:function(){return this._audioEnabled},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"headphone",{get:function(){return this._headphone},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"audioListenerPositionProvider",{get:function(){return this._audioListenerPositionProvider},set:function(t){this._audioListenerPositionProvider=t},enumerable:!1,configurable:!0}),r.prototype.register=function(){this.scene._afterRenderStage.registerStep(at.a.STEP_AFTERRENDER_AUDIO,this,this._afterRender)},r.prototype.rebuild=function(){},r.prototype.serialize=function(t){if(t.sounds=[],this.scene.soundTracks)for(var e=0;e<this.scene.soundTracks.length;e++)for(var n=this.scene.soundTracks[e],i=0;i<n.soundCollection.length;i++)t.sounds.push(n.soundCollection[i].serialize())},r.prototype.addFromContainer=function(t){var e=this;t.sounds&&t.sounds.forEach(function(n){n.play(),n.autoplay=!0,e.scene.mainSoundTrack.addSound(n)})},r.prototype.removeFromContainer=function(t,e){var n=this;e===void 0&&(e=!1),t.sounds&&t.sounds.forEach(function(i){i.stop(),i.autoplay=!1,n.scene.mainSoundTrack.removeSound(i),e&&i.dispose()})},r.prototype.dispose=function(){var t=this.scene;if(t._mainSoundTrack&&t.mainSoundTrack.dispose(),t.soundTracks)for(var e=0;e<t.soundTracks.length;e++)t.soundTracks[e].dispose()},r.prototype.disableAudio=function(){var t,e=this.scene;for(this._audioEnabled=!1,Ue.a.audioEngine&&Ue.a.audioEngine.audioContext&&Ue.a.audioEngine.audioContext.suspend(),t=0;t<e.mainSoundTrack.soundCollection.length;t++)e.mainSoundTrack.soundCollection[t].pause();if(e.soundTracks)for(t=0;t<e.soundTracks.length;t++)for(var n=0;n<e.soundTracks[t].soundCollection.length;n++)e.soundTracks[t].soundCollection[n].pause()},r.prototype.enableAudio=function(){var t,e=this.scene;for(this._audioEnabled=!0,Ue.a.audioEngine&&Ue.a.audioEngine.audioContext&&Ue.a.audioEngine.audioContext.resume(),t=0;t<e.mainSoundTrack.soundCollection.length;t++)e.mainSoundTrack.soundCollection[t].isPaused&&e.mainSoundTrack.soundCollection[t].play();if(e.soundTracks)for(t=0;t<e.soundTracks.length;t++)for(var n=0;n<e.soundTracks[t].soundCollection.length;n++)e.soundTracks[t].soundCollection[n].isPaused&&e.soundTracks[t].soundCollection[n].play()},r.prototype.switchAudioModeForHeadphones=function(){var t=this.scene;if(this._headphone=!0,t.mainSoundTrack.switchPanningModelToHRTF(),t.soundTracks)for(var e=0;e<t.soundTracks.length;e++)t.soundTracks[e].switchPanningModelToHRTF()},r.prototype.switchAudioModeForNormalSpeakers=function(){var t=this.scene;if(this._headphone=!1,t.mainSoundTrack.switchPanningModelToEqualPower(),t.soundTracks)for(var e=0;e<t.soundTracks.length;e++)t.soundTracks[e].switchPanningModelToEqualPower()},r.prototype._afterRender=function(){var t=be.a.Now;if(!(this._lastCheck&&t-this._lastCheck<this.audioPositioningRefreshRate)){this._lastCheck=t;var e=this.scene;if(this._audioEnabled&&e._mainSoundTrack&&e.soundTracks&&(e._mainSoundTrack.soundCollection.length!==0||e.soundTracks.length!==1)){var n=Ue.a.audioEngine;if(n&&n.audioContext){if(this._audioListenerPositionProvider){var i=this._audioListenerPositionProvider();i.x=i.x||0,i.y=i.y||0,i.z=i.z||0,n.audioContext.listener.setPosition(i.x,i.y,i.z)}else{var o;if(o=e.activeCameras&&e.activeCameras.length>0?e.activeCameras[0]:e.activeCamera){this._cachedCameraPosition.equals(o.globalPosition)||(this._cachedCameraPosition.copyFrom(o.globalPosition),n.audioContext.listener.setPosition(o.globalPosition.x,o.globalPosition.y,o.globalPosition.z)),o.rigCameras&&o.rigCameras.length>0&&(o=o.rigCameras[0]);var a=u.a.Invert(o.getViewMatrix()),s=u.e.TransformNormal(e.useRightHandedSystem?r._CameraDirectionRH:r._CameraDirectionLH,a);s.normalize(),isNaN(s.x)||isNaN(s.y)||isNaN(s.z)||this._cachedCameraDirection.equals(s)||(this._cachedCameraDirection.copyFrom(s),n.audioContext.listener.setOrientation(s.x,s.y,s.z,0,1,0))}else n.audioContext.listener.setPosition(0,0,0)}var d;for(d=0;d<e.mainSoundTrack.soundCollection.length;d++){var p=e.mainSoundTrack.soundCollection[d];p.useCustomAttenuation&&p.updateDistanceFromListener()}if(e.soundTracks)for(d=0;d<e.soundTracks.length;d++)for(var b=0;b<e.soundTracks[d].soundCollection.length;b++)(p=e.soundTracks[d].soundCollection[b]).useCustomAttenuation&&p.updateDistanceFromListener()}}}},r._CameraDirectionLH=new u.e(0,0,-1),r._CameraDirectionRH=new u.e(0,0,1),r}();ti._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_AUDIO);t||(t=new ni(r),r._addComponent(t))};var If=function(){function r(t,e,n){var i=this;if(this.loop=!1,this._coneInnerAngle=360,this._coneOuterAngle=360,this._volume=1,this.isPlaying=!1,this.isPaused=!1,this._sounds=[],this._weights=[],e.length!==n.length)throw new Error("Sounds length does not equal weights length");this.loop=t,this._weights=n;for(var o=0,a=0,s=n;a<s.length;a++)o+=s[a];for(var d=o>0?1/o:0,p=0;p<this._weights.length;p++)this._weights[p]*=d;this._sounds=e;for(var b=0,P=this._sounds;b<P.length;b++)P[b].onEndedObservable.add(function(){i._onended()})}return Object.defineProperty(r.prototype,"directionalConeInnerAngle",{get:function(){return this._coneInnerAngle},set:function(t){if(t!==this._coneInnerAngle){if(this._coneOuterAngle<t)return void l.a.Error("directionalConeInnerAngle: outer angle of the cone must be superior or equal to the inner angle.");this._coneInnerAngle=t;for(var e=0,n=this._sounds;e<n.length;e++)n[e].directionalConeInnerAngle=t}},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"directionalConeOuterAngle",{get:function(){return this._coneOuterAngle},set:function(t){if(t!==this._coneOuterAngle){if(t<this._coneInnerAngle)return void l.a.Error("directionalConeOuterAngle: outer angle of the cone must be superior or equal to the inner angle.");this._coneOuterAngle=t;for(var e=0,n=this._sounds;e<n.length;e++)n[e].directionalConeOuterAngle=t}},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"volume",{get:function(){return this._volume},set:function(t){if(t!==this._volume)for(var e=0,n=this._sounds;e<n.length;e++)n[e].setVolume(t)},enumerable:!1,configurable:!0}),r.prototype._onended=function(){this._currentIndex!==void 0&&(this._sounds[this._currentIndex].autoplay=!1),this.loop&&this.isPlaying?this.play():this.isPlaying=!1},r.prototype.pause=function(){this.isPaused=!0,this._currentIndex!==void 0&&this._sounds[this._currentIndex].pause()},r.prototype.stop=function(){this.isPlaying=!1,this._currentIndex!==void 0&&this._sounds[this._currentIndex].stop()},r.prototype.play=function(t){if(!this.isPaused){this.stop();for(var e=Math.random(),n=0,i=0;i<this._weights.length;i++)if(e<=(n+=this._weights[i])){this._currentIndex=i;break}}var o=this._sounds[this._currentIndex];o.isReady()?o.play(0,this.isPaused?void 0:t):o.autoplay=!0,this.isPlaying=!0,this.isPaused=!1},r}(),Tt=f(18),dl=function(){function r(){this._zoomStopsAnimation=!1,this._idleRotationSpeed=.05,this._idleRotationWaitTime=2e3,this._idleRotationSpinupTime=2e3,this._isPointerDown=!1,this._lastFrameTime=null,this._lastInteractionTime=-1/0,this._cameraRotationSpeed=0,this._lastFrameRadius=0}return Object.defineProperty(r.prototype,"name",{get:function(){return"AutoRotation"},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"zoomStopsAnimation",{get:function(){return this._zoomStopsAnimation},set:function(t){this._zoomStopsAnimation=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"idleRotationSpeed",{get:function(){return this._idleRotationSpeed},set:function(t){this._idleRotationSpeed=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"idleRotationWaitTime",{get:function(){return this._idleRotationWaitTime},set:function(t){this._idleRotationWaitTime=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"idleRotationSpinupTime",{get:function(){return this._idleRotationSpinupTime},set:function(t){this._idleRotationSpinupTime=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"rotationInProgress",{get:function(){return Math.abs(this._cameraRotationSpeed)>0},enumerable:!1,configurable:!0}),r.prototype.init=function(){},r.prototype.attach=function(t){var e=this;this._attachedCamera=t;var n=this._attachedCamera.getScene();this._onPrePointerObservableObserver=n.onPrePointerObservable.add(function(i){i.type!==Tt.a.POINTERDOWN?i.type===Tt.a.POINTERUP&&(e._isPointerDown=!1):e._isPointerDown=!0}),this._onAfterCheckInputsObserver=t.onAfterCheckInputsObservable.add(function(){var i=be.a.Now,o=0;e._lastFrameTime!=null&&(o=i-e._lastFrameTime),e._lastFrameTime=i,e._applyUserInteraction();var a=i-e._lastInteractionTime-e._idleRotationWaitTime,s=Math.max(Math.min(a/e._idleRotationSpinupTime,1),0);e._cameraRotationSpeed=e._idleRotationSpeed*s,e._attachedCamera&&(e._attachedCamera.alpha-=e._cameraRotationSpeed*(o/1e3))})},r.prototype.detach=function(){if(this._attachedCamera){var t=this._attachedCamera.getScene();this._onPrePointerObservableObserver&&t.onPrePointerObservable.remove(this._onPrePointerObservableObserver),this._attachedCamera.onAfterCheckInputsObservable.remove(this._onAfterCheckInputsObserver),this._attachedCamera=null}},r.prototype._userIsZooming=function(){return!!this._attachedCamera&&this._attachedCamera.inertialRadiusOffset!==0},r.prototype._shouldAnimationStopForInteraction=function(){if(!this._attachedCamera)return!1;var t=!1;return this._lastFrameRadius===this._attachedCamera.radius&&this._attachedCamera.inertialRadiusOffset!==0&&(t=!0),this._lastFrameRadius=this._attachedCamera.radius,this._zoomStopsAnimation?t:this._userIsZooming()},r.prototype._applyUserInteraction=function(){this._userIsMoving()&&!this._shouldAnimationStopForInteraction()&&(this._lastInteractionTime=be.a.Now)},r.prototype._userIsMoving=function(){return!!this._attachedCamera&&(this._attachedCamera.inertialAlphaOffset!==0||this._attachedCamera.inertialBetaOffset!==0||this._attachedCamera.inertialRadiusOffset!==0||this._attachedCamera.inertialPanningX!==0||this._attachedCamera.inertialPanningY!==0||this._isPointerDown)},r}(),fl=function(){function r(){this.transitionDuration=450,this.lowerRadiusTransitionRange=2,this.upperRadiusTransitionRange=-2,this._autoTransitionRange=!1,this._radiusIsAnimating=!1,this._radiusBounceTransition=null,this._animatables=new Array}return Object.defineProperty(r.prototype,"name",{get:function(){return"Bouncing"},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"autoTransitionRange",{get:function(){return this._autoTransitionRange},set:function(t){var e=this;if(this._autoTransitionRange!==t){this._autoTransitionRange=t;var n=this._attachedCamera;n&&(t?this._onMeshTargetChangedObserver=n.onMeshTargetChangedObservable.add(function(i){if(i){i.computeWorldMatrix(!0);var o=i.getBoundingInfo().diagonalLength;e.lowerRadiusTransitionRange=.05*o,e.upperRadiusTransitionRange=.05*o}}):this._onMeshTargetChangedObserver&&n.onMeshTargetChangedObservable.remove(this._onMeshTargetChangedObserver))}},enumerable:!1,configurable:!0}),r.prototype.init=function(){},r.prototype.attach=function(t){var e=this;this._attachedCamera=t,this._onAfterCheckInputsObserver=t.onAfterCheckInputsObservable.add(function(){e._attachedCamera&&(e._isRadiusAtLimit(e._attachedCamera.lowerRadiusLimit)&&e._applyBoundRadiusAnimation(e.lowerRadiusTransitionRange),e._isRadiusAtLimit(e._attachedCamera.upperRadiusLimit)&&e._applyBoundRadiusAnimation(e.upperRadiusTransitionRange))})},r.prototype.detach=function(){this._attachedCamera&&(this._onAfterCheckInputsObserver&&this._attachedCamera.onAfterCheckInputsObservable.remove(this._onAfterCheckInputsObserver),this._onMeshTargetChangedObserver&&this._attachedCamera.onMeshTargetChangedObservable.remove(this._onMeshTargetChangedObserver),this._attachedCamera=null)},r.prototype._isRadiusAtLimit=function(t){return!!this._attachedCamera&&this._attachedCamera.radius===t&&!this._radiusIsAnimating},r.prototype._applyBoundRadiusAnimation=function(t){var e=this;if(this._attachedCamera){this._radiusBounceTransition||(r.EasingFunction.setEasingMode(r.EasingMode),this._radiusBounceTransition=k.CreateAnimation("radius",k.ANIMATIONTYPE_FLOAT,60,r.EasingFunction)),this._cachedWheelPrecision=this._attachedCamera.wheelPrecision,this._attachedCamera.wheelPrecision=1/0,this._attachedCamera.inertialRadiusOffset=0,this.stopAllAnimations(),this._radiusIsAnimating=!0;var n=k.TransitionTo("radius",this._attachedCamera.radius+t,this._attachedCamera,this._attachedCamera.getScene(),60,this._radiusBounceTransition,this.transitionDuration,function(){return e._clearAnimationLocks()});n&&this._animatables.push(n)}},r.prototype._clearAnimationLocks=function(){this._radiusIsAnimating=!1,this._attachedCamera&&(this._attachedCamera.wheelPrecision=this._cachedWheelPrecision)},r.prototype.stopAllAnimations=function(){for(this._attachedCamera&&(this._attachedCamera.animations=[]);this._animatables.length;)this._animatables[0].onAnimationEnd=null,this._animatables[0].stop(),this._animatables.shift()},r.EasingFunction=new $e(.3),r.EasingMode=Ge.EASINGMODE_EASEOUT,r}(),pl=function(){function r(){this._mode=r.FitFrustumSidesMode,this._radiusScale=1,this._positionScale=.5,this._defaultElevation=.3,this._elevationReturnTime=1500,this._elevationReturnWaitTime=1e3,this._zoomStopsAnimation=!1,this._framingTime=1500,this.autoCorrectCameraLimitsAndSensibility=!0,this._isPointerDown=!1,this._lastInteractionTime=-1/0,this._animatables=new Array,this._betaIsAnimating=!1}return Object.defineProperty(r.prototype,"name",{get:function(){return"Framing"},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"mode",{get:function(){return this._mode},set:function(t){this._mode=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"radiusScale",{get:function(){return this._radiusScale},set:function(t){this._radiusScale=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"positionScale",{get:function(){return this._positionScale},set:function(t){this._positionScale=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"defaultElevation",{get:function(){return this._defaultElevation},set:function(t){this._defaultElevation=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"elevationReturnTime",{get:function(){return this._elevationReturnTime},set:function(t){this._elevationReturnTime=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"elevationReturnWaitTime",{get:function(){return this._elevationReturnWaitTime},set:function(t){this._elevationReturnWaitTime=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"zoomStopsAnimation",{get:function(){return this._zoomStopsAnimation},set:function(t){this._zoomStopsAnimation=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"framingTime",{get:function(){return this._framingTime},set:function(t){this._framingTime=t},enumerable:!1,configurable:!0}),r.prototype.init=function(){},r.prototype.attach=function(t){var e=this;this._attachedCamera=t;var n=this._attachedCamera.getScene();r.EasingFunction.setEasingMode(r.EasingMode),this._onPrePointerObservableObserver=n.onPrePointerObservable.add(function(i){i.type!==Tt.a.POINTERDOWN?i.type===Tt.a.POINTERUP&&(e._isPointerDown=!1):e._isPointerDown=!0}),this._onMeshTargetChangedObserver=t.onMeshTargetChangedObservable.add(function(i){i&&e.zoomOnMesh(i)}),this._onAfterCheckInputsObserver=t.onAfterCheckInputsObservable.add(function(){e._applyUserInteraction(),e._maintainCameraAboveGround()})},r.prototype.detach=function(){if(this._attachedCamera){var t=this._attachedCamera.getScene();this._onPrePointerObservableObserver&&t.onPrePointerObservable.remove(this._onPrePointerObservableObserver),this._onAfterCheckInputsObserver&&this._attachedCamera.onAfterCheckInputsObservable.remove(this._onAfterCheckInputsObserver),this._onMeshTargetChangedObserver&&this._attachedCamera.onMeshTargetChangedObservable.remove(this._onMeshTargetChangedObserver),this._attachedCamera=null}},r.prototype.zoomOnMesh=function(t,e,n){e===void 0&&(e=!1),n===void 0&&(n=null),t.computeWorldMatrix(!0);var i=t.getBoundingInfo().boundingBox;this.zoomOnBoundingInfo(i.minimumWorld,i.maximumWorld,e,n)},r.prototype.zoomOnMeshHierarchy=function(t,e,n){e===void 0&&(e=!1),n===void 0&&(n=null),t.computeWorldMatrix(!0);var i=t.getHierarchyBoundingVectors(!0);this.zoomOnBoundingInfo(i.min,i.max,e,n)},r.prototype.zoomOnMeshesHierarchy=function(t,e,n){e===void 0&&(e=!1),n===void 0&&(n=null);for(var i=new u.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),o=new u.e(-Number.MAX_VALUE,-Number.MAX_VALUE,-Number.MAX_VALUE),a=0;a<t.length;a++){var s=t[a].getHierarchyBoundingVectors(!0);u.e.CheckExtends(s.min,i,o),u.e.CheckExtends(s.max,i,o)}this.zoomOnBoundingInfo(i,o,e,n)},r.prototype.zoomOnBoundingInfo=function(t,e,n,i){var o,a=this;if(n===void 0&&(n=!1),i===void 0&&(i=null),this._attachedCamera){var s=t.y,d=s+(e.y-s)*this._positionScale,p=e.subtract(t).scale(.5);if(n)o=new u.e(0,d,0);else{var b=t.add(p);o=new u.e(b.x,d,b.z)}this._vectorTransition||(this._vectorTransition=k.CreateAnimation("target",k.ANIMATIONTYPE_VECTOR3,60,r.EasingFunction)),this._betaIsAnimating=!0;var P=k.TransitionTo("target",o,this._attachedCamera,this._attachedCamera.getScene(),60,this._vectorTransition,this._framingTime);P&&this._animatables.push(P);var O=0;if(this._mode===r.FitFrustumSidesMode){var B=this._calculateLowerRadiusFromModelBoundingSphere(t,e);this.autoCorrectCameraLimitsAndSensibility&&(this._attachedCamera.lowerRadiusLimit=p.length()+this._attachedCamera.minZ),O=B}else this._mode===r.IgnoreBoundsSizeMode&&(O=this._calculateLowerRadiusFromModelBoundingSphere(t,e),this.autoCorrectCameraLimitsAndSensibility&&this._attachedCamera.lowerRadiusLimit===null&&(this._attachedCamera.lowerRadiusLimit=this._attachedCamera.minZ));if(this.autoCorrectCameraLimitsAndSensibility){var F=e.subtract(t).length();this._attachedCamera.panningSensibility=5e3/F,this._attachedCamera.wheelPrecision=100/O}this._radiusTransition||(this._radiusTransition=k.CreateAnimation("radius",k.ANIMATIONTYPE_FLOAT,60,r.EasingFunction)),(P=k.TransitionTo("radius",O,this._attachedCamera,this._attachedCamera.getScene(),60,this._radiusTransition,this._framingTime,function(){a.stopAllAnimations(),i&&i(),a._attachedCamera&&a._attachedCamera.useInputToRestoreState&&a._attachedCamera.storeState()}))&&this._animatables.push(P)}},r.prototype._calculateLowerRadiusFromModelBoundingSphere=function(t,e){var n=e.subtract(t).length(),i=this._getFrustumSlope(),o=.5*n*this._radiusScale,a=o*Math.sqrt(1+1/(i.x*i.x)),s=o*Math.sqrt(1+1/(i.y*i.y)),d=Math.max(a,s),p=this._attachedCamera;return p?(p.lowerRadiusLimit&&this._mode===r.IgnoreBoundsSizeMode&&(d=d<p.lowerRadiusLimit?p.lowerRadiusLimit:d),p.upperRadiusLimit&&(d=d>p.upperRadiusLimit?p.upperRadiusLimit:d),d):0},r.prototype._maintainCameraAboveGround=function(){var t=this;if(!(this._elevationReturnTime<0)){var e=be.a.Now-this._lastInteractionTime,n=.5*Math.PI-this._defaultElevation,i=.5*Math.PI;if(this._attachedCamera&&!this._betaIsAnimating&&this._attachedCamera.beta>i&&e>=this._elevationReturnWaitTime){this._betaIsAnimating=!0,this.stopAllAnimations(),this._betaTransition||(this._betaTransition=k.CreateAnimation("beta",k.ANIMATIONTYPE_FLOAT,60,r.EasingFunction));var o=k.TransitionTo("beta",n,this._attachedCamera,this._attachedCamera.getScene(),60,this._betaTransition,this._elevationReturnTime,function(){t._clearAnimationLocks(),t.stopAllAnimations()});o&&this._animatables.push(o)}}},r.prototype._getFrustumSlope=function(){var t=this._attachedCamera;if(!t)return u.d.Zero();var e=t.getScene().getEngine().getAspectRatio(t),n=Math.tan(t.fov/2),i=n*e;return new u.d(i,n)},r.prototype._clearAnimationLocks=function(){this._betaIsAnimating=!1},r.prototype._applyUserInteraction=function(){this.isUserIsMoving&&(this._lastInteractionTime=be.a.Now,this.stopAllAnimations(),this._clearAnimationLocks())},r.prototype.stopAllAnimations=function(){for(this._attachedCamera&&(this._attachedCamera.animations=[]);this._animatables.length;)this._animatables[0]&&(this._animatables[0].onAnimationEnd=null,this._animatables[0].stop()),this._animatables.shift()},Object.defineProperty(r.prototype,"isUserIsMoving",{get:function(){return!!this._attachedCamera&&(this._attachedCamera.inertialAlphaOffset!==0||this._attachedCamera.inertialBetaOffset!==0||this._attachedCamera.inertialRadiusOffset!==0||this._attachedCamera.inertialPanningX!==0||this._attachedCamera.inertialPanningY!==0||this._isPointerDown)},enumerable:!1,configurable:!0}),r.EasingFunction=new St,r.EasingMode=Ge.EASINGMODE_EASEINOUT,r.IgnoreBoundsSizeMode=0,r.FitFrustumSidesMode=1,r}(),fr=function(r,t,e,n){t===void 0&&(t=new u.e),e===void 0&&(e=0),n===void 0&&(n=!1),this.direction=r,this.rotatedDirection=t,this.diff=e,this.ignore=n},Df=function(){function r(t){this.ui=t,this.name="AttachToBoxBehavior",this.distanceAwayFromFace=.15,this.distanceAwayFromBottomOfFace=.15,this._faceVectors=[new fr(u.e.Up()),new fr(u.e.Down()),new fr(u.e.Left()),new fr(u.e.Right()),new fr(u.e.Forward()),new fr(u.e.Forward().scaleInPlace(-1))],this._tmpMatrix=new u.a,this._tmpVector=new u.e,this._zeroVector=u.e.Zero(),this._lookAtTmpMatrix=new u.a}return r.prototype.init=function(){},r.prototype._closestFace=function(t){var e=this;return this._faceVectors.forEach(function(n){e._target.rotationQuaternion||(e._target.rotationQuaternion=u.b.RotationYawPitchRoll(e._target.rotation.y,e._target.rotation.x,e._target.rotation.z)),e._target.rotationQuaternion.toRotationMatrix(e._tmpMatrix),u.e.TransformCoordinatesToRef(n.direction,e._tmpMatrix,n.rotatedDirection),n.diff=u.e.GetAngleBetweenVectors(n.rotatedDirection,t,u.e.Cross(n.rotatedDirection,t))}),this._faceVectors.reduce(function(n,i){return n.ignore?i:i.ignore||n.diff<i.diff?n:i},this._faceVectors[0])},r.prototype._lookAtToRef=function(t,e,n){e===void 0&&(e=new u.e(0,1,0)),u.a.LookAtLHToRef(this._zeroVector,t,e,this._lookAtTmpMatrix),this._lookAtTmpMatrix.invert(),u.b.FromRotationMatrixToRef(this._lookAtTmpMatrix,n)},r.prototype.attach=function(t){var e=this;this._target=t,this._scene=this._target.getScene(),this._onRenderObserver=this._scene.onBeforeRenderObservable.add(function(){if(e._scene.activeCamera){var n=e._scene.activeCamera.position;e._scene.activeCamera.devicePosition&&(n=e._scene.activeCamera.devicePosition);var i=e._closestFace(n.subtract(t.position));e._scene.activeCamera.leftCamera?e._scene.activeCamera.leftCamera.computeWorldMatrix().getRotationMatrixToRef(e._tmpMatrix):e._scene.activeCamera.computeWorldMatrix().getRotationMatrixToRef(e._tmpMatrix),u.e.TransformCoordinatesToRef(u.e.Up(),e._tmpMatrix,e._tmpVector),e._faceVectors.forEach(function(a){i.direction.x&&a.direction.x&&(a.ignore=!0),i.direction.y&&a.direction.y&&(a.ignore=!0),i.direction.z&&a.direction.z&&(a.ignore=!0)});var o=e._closestFace(e._tmpVector);e._faceVectors.forEach(function(a){a.ignore=!1}),e.ui.position.copyFrom(t.position),i.direction.x&&(i.rotatedDirection.scaleToRef(t.scaling.x/2+e.distanceAwayFromFace,e._tmpVector),e.ui.position.addInPlace(e._tmpVector)),i.direction.y&&(i.rotatedDirection.scaleToRef(t.scaling.y/2+e.distanceAwayFromFace,e._tmpVector),e.ui.position.addInPlace(e._tmpVector)),i.direction.z&&(i.rotatedDirection.scaleToRef(t.scaling.z/2+e.distanceAwayFromFace,e._tmpVector),e.ui.position.addInPlace(e._tmpVector)),e.ui.rotationQuaternion||(e.ui.rotationQuaternion=u.b.RotationYawPitchRoll(e.ui.rotation.y,e.ui.rotation.x,e.ui.rotation.z)),i.rotatedDirection.scaleToRef(-1,e._tmpVector),e._lookAtToRef(e._tmpVector,o.rotatedDirection,e.ui.rotationQuaternion),o.direction.x&&e.ui.up.scaleToRef(e.distanceAwayFromBottomOfFace-t.scaling.x/2,e._tmpVector),o.direction.y&&e.ui.up.scaleToRef(e.distanceAwayFromBottomOfFace-t.scaling.y/2,e._tmpVector),o.direction.z&&e.ui.up.scaleToRef(e.distanceAwayFromBottomOfFace-t.scaling.z/2,e._tmpVector),e.ui.position.addInPlace(e._tmpVector)}})},r.prototype.detach=function(){this._scene.onBeforeRenderObservable.remove(this._onRenderObserver)},r}(),Lf=function(){function r(){var t=this;this.delay=0,this.fadeInTime=300,this._millisecondsPerFrame=1e3/60,this._hovered=!1,this._hoverValue=0,this._ownerNode=null,this._update=function(){if(t._ownerNode){if(t._hoverValue+=t._hovered?t._millisecondsPerFrame:-t._millisecondsPerFrame,t._setAllVisibility(t._ownerNode,(t._hoverValue-t.delay)/t.fadeInTime),t._ownerNode.visibility>1)return t._setAllVisibility(t._ownerNode,1),void(t._hoverValue=t.fadeInTime+t.delay);if(t._ownerNode.visibility<0&&(t._setAllVisibility(t._ownerNode,0),t._hoverValue<0))return void(t._hoverValue=0);setTimeout(t._update,t._millisecondsPerFrame)}}}return Object.defineProperty(r.prototype,"name",{get:function(){return"FadeInOut"},enumerable:!1,configurable:!0}),r.prototype.init=function(){},r.prototype.attach=function(t){this._ownerNode=t,this._setAllVisibility(this._ownerNode,0)},r.prototype.detach=function(){this._ownerNode=null},r.prototype.fadeIn=function(t){this._hovered=t,this._update()},r.prototype._setAllVisibility=function(t,e){var n=this;t.visibility=e,t.getChildMeshes().forEach(function(i){n._setAllVisibility(i,e)})},r}(),yi=f(65),Nf=function(){function r(){this._startDistance=0,this._initialScale=new u.e(0,0,0),this._targetScale=new u.e(0,0,0),this._sceneRenderObserver=null,this._dragBehaviorA=new yi.a({}),this._dragBehaviorA.moveAttached=!1,this._dragBehaviorB=new yi.a({}),this._dragBehaviorB.moveAttached=!1}return Object.defineProperty(r.prototype,"name",{get:function(){return"MultiPointerScale"},enumerable:!1,configurable:!0}),r.prototype.init=function(){},r.prototype._getCurrentDistance=function(){return this._dragBehaviorA.lastDragPosition.subtract(this._dragBehaviorB.lastDragPosition).length()},r.prototype.attach=function(t){var e=this;this._ownerNode=t,this._dragBehaviorA.onDragStartObservable.add(function(n){e._dragBehaviorA.dragging&&e._dragBehaviorB.dragging&&(e._dragBehaviorA.currentDraggingPointerID==e._dragBehaviorB.currentDraggingPointerID?e._dragBehaviorA.releaseDrag():(e._initialScale.copyFrom(t.scaling),e._startDistance=e._getCurrentDistance()))}),this._dragBehaviorB.onDragStartObservable.add(function(n){e._dragBehaviorA.dragging&&e._dragBehaviorB.dragging&&(e._dragBehaviorA.currentDraggingPointerID==e._dragBehaviorB.currentDraggingPointerID?e._dragBehaviorB.releaseDrag():(e._initialScale.copyFrom(t.scaling),e._startDistance=e._getCurrentDistance()))}),[this._dragBehaviorA,this._dragBehaviorB].forEach(function(n){n.onDragObservable.add(function(){if(e._dragBehaviorA.dragging&&e._dragBehaviorB.dragging){var i=e._getCurrentDistance()/e._startDistance;e._initialScale.scaleToRef(i,e._targetScale)}})}),t.addBehavior(this._dragBehaviorA),t.addBehavior(this._dragBehaviorB),this._sceneRenderObserver=t.getScene().onBeforeRenderObservable.add(function(){if(e._dragBehaviorA.dragging&&e._dragBehaviorB.dragging){var n=e._targetScale.subtract(t.scaling).scaleInPlace(.1);n.length()>.01&&t.scaling.addInPlace(n)}})},r.prototype.detach=function(){var t=this;this._ownerNode.getScene().onBeforeRenderObservable.remove(this._sceneRenderObserver),[this._dragBehaviorA,this._dragBehaviorB].forEach(function(e){e.onDragStartObservable.clear(),e.onDragObservable.clear(),t._ownerNode.removeBehavior(e)})},r}(),Dt=f(31),gt=f(24),kn=f(60),_l=function(){function r(){this._sceneRenderObserver=null,this._targetPosition=new u.e(0,0,0),this._moving=!1,this._startingOrientation=new u.b,this._attachedToElement=!1,this.zDragFactor=3,this.rotateDraggedObject=!0,this.dragging=!1,this.dragDeltaRatio=.2,this.currentDraggingPointerID=-1,this.detachCameraControls=!0,this.onDragStartObservable=new x.c,this.onDragObservable=new x.c,this.onDragEndObservable=new x.c}return Object.defineProperty(r.prototype,"name",{get:function(){return"SixDofDrag"},enumerable:!1,configurable:!0}),r.prototype.init=function(){},Object.defineProperty(r.prototype,"_pointerCamera",{get:function(){return this._scene.cameraToUseForPointers?this._scene.cameraToUseForPointers:this._scene.activeCamera},enumerable:!1,configurable:!0}),r.prototype.attach=function(t){var e=this;this._ownerNode=t,this._scene=this._ownerNode.getScene(),r._virtualScene||(r._virtualScene=new _e.a(this._scene.getEngine(),{virtual:!0}),r._virtualScene.detachControl(),this._scene.getEngine().scenes.pop());var n=null,i=new u.e(0,0,0);this._virtualOriginMesh=new Dt.a("",r._virtualScene),this._virtualOriginMesh.rotationQuaternion=new u.b,this._virtualDragMesh=new Dt.a("",r._virtualScene),this._virtualDragMesh.rotationQuaternion=new u.b,this._pointerObserver=this._scene.onPointerObservable.add(function(a,s){if(a.type==Tt.a.POINTERDOWN){if(!e.dragging&&a.pickInfo&&a.pickInfo.hit&&a.pickInfo.pickedMesh&&a.pickInfo.ray&&(O=a.pickInfo.pickedMesh,e._ownerNode==O||O.isDescendantOf(e._ownerNode))){e._pointerCamera&&e._pointerCamera.cameraRigMode==gt.a.RIG_MODE_NONE&&a.pickInfo.ray.origin.copyFrom(e._pointerCamera.globalPosition),n=e._ownerNode,kn.a._RemoveAndStorePivotPoint(n),i.copyFrom(a.pickInfo.ray.origin),e._virtualOriginMesh.position.copyFrom(a.pickInfo.ray.origin),e._virtualOriginMesh.lookAt(a.pickInfo.ray.origin.add(a.pickInfo.ray.direction)),e._virtualOriginMesh.removeChild(e._virtualDragMesh),n.computeWorldMatrix(),e._virtualDragMesh.position.copyFrom(n.absolutePosition),n.rotationQuaternion||(n.rotationQuaternion=u.b.RotationYawPitchRoll(n.rotation.y,n.rotation.x,n.rotation.z));var d=n.parent;n.setParent(null),e._virtualDragMesh.rotationQuaternion.copyFrom(n.rotationQuaternion),n.setParent(d),e._virtualOriginMesh.addChild(e._virtualDragMesh),e._targetPosition.copyFrom(e._virtualDragMesh.absolutePosition),e.dragging=!0,e.currentDraggingPointerID=a.event.pointerId,e.detachCameraControls&&e._pointerCamera&&!e._pointerCamera.leftCamera&&(e._pointerCamera.inputs.attachedToElement?(e._pointerCamera.detachControl(),e._attachedToElement=!0):e._attachedToElement=!1),kn.a._RestorePivotPoint(n),e.onDragStartObservable.notifyObservers({})}}else if(a.type==Tt.a.POINTERUP||a.type==Tt.a.POINTERDOUBLETAP)e.currentDraggingPointerID==a.event.pointerId&&(e.dragging=!1,e._moving=!1,e.currentDraggingPointerID=-1,n=null,e._virtualOriginMesh.removeChild(e._virtualDragMesh),e.detachCameraControls&&e._attachedToElement&&e._pointerCamera&&!e._pointerCamera.leftCamera&&(e._pointerCamera.attachControl(!0),e._attachedToElement=!1),e.onDragEndObservable.notifyObservers({}));else if(a.type==Tt.a.POINTERMOVE&&e.currentDraggingPointerID==a.event.pointerId&&e.dragging&&a.pickInfo&&a.pickInfo.ray&&n){var p=e.zDragFactor;e._pointerCamera&&e._pointerCamera.cameraRigMode==gt.a.RIG_MODE_NONE&&(a.pickInfo.ray.origin.copyFrom(e._pointerCamera.globalPosition),p=0);var b=a.pickInfo.ray.origin.subtract(i);i.copyFrom(a.pickInfo.ray.origin);var P=-u.e.Dot(b,a.pickInfo.ray.direction);e._virtualOriginMesh.addChild(e._virtualDragMesh),e._virtualDragMesh.position.z-=e._virtualDragMesh.position.z<1?P*e.zDragFactor:P*p*e._virtualDragMesh.position.z,e._virtualDragMesh.position.z<0&&(e._virtualDragMesh.position.z=0),e._virtualOriginMesh.position.copyFrom(a.pickInfo.ray.origin),e._virtualOriginMesh.lookAt(a.pickInfo.ray.origin.add(a.pickInfo.ray.direction)),e._virtualOriginMesh.removeChild(e._virtualDragMesh),e._targetPosition.copyFrom(e._virtualDragMesh.absolutePosition),n.parent&&u.e.TransformCoordinatesToRef(e._targetPosition,u.a.Invert(n.parent.getWorldMatrix()),e._targetPosition),e._moving||e._startingOrientation.copyFrom(e._virtualDragMesh.rotationQuaternion),e._moving=!0}var O});var o=new u.b;this._sceneRenderObserver=t.getScene().onBeforeRenderObservable.add(function(){if(e.dragging&&e._moving&&n){if(kn.a._RemoveAndStorePivotPoint(n),n.position.addInPlace(e._targetPosition.subtract(n.position).scale(e.dragDeltaRatio)),e.rotateDraggedObject){o.copyFrom(e._startingOrientation),o.x=-o.x,o.y=-o.y,o.z=-o.z,e._virtualDragMesh.rotationQuaternion.multiplyToRef(o,o),u.b.RotationYawPitchRollToRef(o.toEulerAngles("xyz").y,0,0,o),o.multiplyToRef(e._startingOrientation,o);var a=n.parent;(!a||a.scaling&&!a.scaling.isNonUniformWithinEpsilon(.001))&&(n.setParent(null),u.b.SlerpToRef(n.rotationQuaternion,o,e.dragDeltaRatio,n.rotationQuaternion),n.setParent(a))}kn.a._RestorePivotPoint(n),e.onDragObservable.notifyObservers()}})},r.prototype.detach=function(){this._scene&&(this.detachCameraControls&&this._attachedToElement&&this._pointerCamera&&!this._pointerCamera.leftCamera&&(this._pointerCamera.attachControl(!0),this._attachedToElement=!1),this._scene.onPointerObservable.remove(this._pointerObserver)),this._ownerNode&&this._ownerNode.getScene().onBeforeRenderObservable.remove(this._sceneRenderObserver),this._virtualOriginMesh&&this._virtualOriginMesh.dispose(),this._virtualDragMesh&&this._virtualDragMesh.dispose(),this.onDragEndObservable.clear(),this.onDragObservable.clear(),this.onDragStartObservable.clear()},r}(),wf=function(){function r(t,e,n){if(this.targetPosition=u.e.Zero(),this.poleTargetPosition=u.e.Zero(),this.poleTargetLocalOffset=u.e.Zero(),this.poleAngle=0,this.slerpAmount=1,this._bone1Quat=u.b.Identity(),this._bone1Mat=u.a.Identity(),this._bone2Ang=Math.PI,this._maxAngle=Math.PI,this._rightHandedSystem=!1,this._bendAxis=u.e.Right(),this._slerping=!1,this._adjustRoll=0,this._bone2=e,this._bone1=e.getParent(),this._bone1){this.mesh=t;var i=e.getPosition();if(e.getAbsoluteTransform().determinant()>0&&(this._rightHandedSystem=!0,this._bendAxis.x=0,this._bendAxis.y=0,this._bendAxis.z=-1,i.x>i.y&&i.x>i.z&&(this._adjustRoll=.5*Math.PI,this._bendAxis.z=1)),this._bone1.length){var o=this._bone1.getScale(),a=this._bone2.getScale();this._bone1Length=this._bone1.length*o.y*this.mesh.scaling.y,this._bone2Length=this._bone2.length*a.y*this.mesh.scaling.y}else if(this._bone1.children[0]){t.computeWorldMatrix(!0);var s=this._bone2.children[0].getAbsolutePosition(t),d=this._bone2.getAbsolutePosition(t),p=this._bone1.getAbsolutePosition(t);this._bone1Length=u.e.Distance(s,d),this._bone2Length=u.e.Distance(d,p)}this._bone1.getRotationMatrixToRef(ye.c.WORLD,t,this._bone1Mat),this.maxAngle=Math.PI,n&&(n.targetMesh&&(this.targetMesh=n.targetMesh,this.targetMesh.computeWorldMatrix(!0)),n.poleTargetMesh?(this.poleTargetMesh=n.poleTargetMesh,this.poleTargetMesh.computeWorldMatrix(!0)):n.poleTargetBone?this.poleTargetBone=n.poleTargetBone:this._bone1.getParent()&&(this.poleTargetBone=this._bone1.getParent()),n.poleTargetLocalOffset&&this.poleTargetLocalOffset.copyFrom(n.poleTargetLocalOffset),n.poleAngle&&(this.poleAngle=n.poleAngle),n.bendAxis&&this._bendAxis.copyFrom(n.bendAxis),n.maxAngle&&(this.maxAngle=n.maxAngle),n.slerpAmount&&(this.slerpAmount=n.slerpAmount))}}return Object.defineProperty(r.prototype,"maxAngle",{get:function(){return this._maxAngle},set:function(t){this._setMaxAngle(t)},enumerable:!1,configurable:!0}),r.prototype._setMaxAngle=function(t){t<0&&(t=0),(t>Math.PI||t==null)&&(t=Math.PI),this._maxAngle=t;var e=this._bone1Length,n=this._bone2Length;this._maxReach=Math.sqrt(e*e+n*n-2*e*n*Math.cos(t))},r.prototype.update=function(){var t=this._bone1;if(t){var e=this.targetPosition,n=this.poleTargetPosition,i=r._tmpMats[0],o=r._tmpMats[1];this.targetMesh&&e.copyFrom(this.targetMesh.getAbsolutePosition()),this.poleTargetBone?this.poleTargetBone.getAbsolutePositionFromLocalToRef(this.poleTargetLocalOffset,this.mesh,n):this.poleTargetMesh&&u.e.TransformCoordinatesToRef(this.poleTargetLocalOffset,this.poleTargetMesh.getWorldMatrix(),n);var a=r._tmpVecs[0],s=r._tmpVecs[1],d=r._tmpVecs[2],p=r._tmpVecs[3],b=r._tmpVecs[4],P=r._tmpQuat;t.getAbsolutePositionToRef(this.mesh,a),n.subtractToRef(a,b),b.x==0&&b.y==0&&b.z==0?b.y=1:b.normalize(),e.subtractToRef(a,p),p.normalize(),u.e.CrossToRef(p,b,s),s.normalize(),u.e.CrossToRef(p,s,d),d.normalize(),u.a.FromXYZAxesToRef(d,p,s,i);var O=this._bone1Length,B=this._bone2Length,F=u.e.Distance(a,e);this._maxReach>0&&(F=Math.min(this._maxReach,F));var z=(B*B+F*F-O*O)/(2*B*F),J=(F*F+O*O-B*B)/(2*F*O);z>1&&(z=1),J>1&&(J=1),z<-1&&(z=-1),J<-1&&(J=-1);var ie=Math.acos(z),se=Math.acos(J),ce=-ie-se;if(this._rightHandedSystem)u.a.RotationYawPitchRollToRef(0,0,this._adjustRoll,o),o.multiplyToRef(i,i),u.a.RotationAxisToRef(this._bendAxis,se,o),o.multiplyToRef(i,i);else{var ue=r._tmpVecs[5];ue.copyFrom(this._bendAxis),ue.x*=-1,u.a.RotationAxisToRef(ue,-se,o),o.multiplyToRef(i,i)}this.poleAngle&&(u.a.RotationAxisToRef(p,this.poleAngle,o),i.multiplyToRef(o,i)),this._bone1&&(this.slerpAmount<1?(this._slerping||u.b.FromRotationMatrixToRef(this._bone1Mat,this._bone1Quat),u.b.FromRotationMatrixToRef(i,P),u.b.SlerpToRef(this._bone1Quat,P,this.slerpAmount,this._bone1Quat),ce=this._bone2Ang*(1-this.slerpAmount)+ce*this.slerpAmount,this._bone1.setRotationQuaternion(this._bone1Quat,ye.c.WORLD,this.mesh),this._slerping=!0):(this._bone1.setRotationMatrix(i,ye.c.WORLD,this.mesh),this._bone1Mat.copyFrom(i),this._slerping=!1)),this._bone2.setAxisAngle(this._bendAxis,ce,ye.c.LOCAL),this._bone2Ang=ce}},r._tmpVecs=[u.e.Zero(),u.e.Zero(),u.e.Zero(),u.e.Zero(),u.e.Zero(),u.e.Zero()],r._tmpQuat=u.b.Identity(),r._tmpMats=[u.a.Identity(),u.a.Identity()],r}(),Ff=function(){function r(t,e,n,i){if(this.upAxis=u.e.Up(),this.upAxisSpace=ye.c.LOCAL,this.adjustYaw=0,this.adjustPitch=0,this.adjustRoll=0,this.slerpAmount=1,this._boneQuat=u.b.Identity(),this._slerping=!1,this._firstFrameSkipped=!1,this._fowardAxis=u.e.Forward(),this.mesh=t,this.bone=e,this.target=n,i&&(i.adjustYaw&&(this.adjustYaw=i.adjustYaw),i.adjustPitch&&(this.adjustPitch=i.adjustPitch),i.adjustRoll&&(this.adjustRoll=i.adjustRoll),i.maxYaw!=null?this.maxYaw=i.maxYaw:this.maxYaw=Math.PI,i.minYaw!=null?this.minYaw=i.minYaw:this.minYaw=-Math.PI,i.maxPitch!=null?this.maxPitch=i.maxPitch:this.maxPitch=Math.PI,i.minPitch!=null?this.minPitch=i.minPitch:this.minPitch=-Math.PI,i.slerpAmount!=null&&(this.slerpAmount=i.slerpAmount),i.upAxis!=null&&(this.upAxis=i.upAxis),i.upAxisSpace!=null&&(this.upAxisSpace=i.upAxisSpace),i.yawAxis!=null||i.pitchAxis!=null)){var o=ye.a.Y,a=ye.a.X;i.yawAxis!=null&&(o=i.yawAxis.clone()).normalize(),i.pitchAxis!=null&&(a=i.pitchAxis.clone()).normalize();var s=u.e.Cross(a,o);this._transformYawPitch=u.a.Identity(),u.a.FromXYZAxesToRef(a,o,s,this._transformYawPitch),this._transformYawPitchInv=this._transformYawPitch.clone(),this._transformYawPitch.invert()}e.getParent()||this.upAxisSpace!=ye.c.BONE||(this.upAxisSpace=ye.c.LOCAL)}return Object.defineProperty(r.prototype,"minYaw",{get:function(){return this._minYaw},set:function(t){this._minYaw=t,this._minYawSin=Math.sin(t),this._minYawCos=Math.cos(t),this._maxYaw!=null&&(this._midYawConstraint=.5*this._getAngleDiff(this._minYaw,this._maxYaw)+this._minYaw,this._yawRange=this._maxYaw-this._minYaw)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"maxYaw",{get:function(){return this._maxYaw},set:function(t){this._maxYaw=t,this._maxYawSin=Math.sin(t),this._maxYawCos=Math.cos(t),this._minYaw!=null&&(this._midYawConstraint=.5*this._getAngleDiff(this._minYaw,this._maxYaw)+this._minYaw,this._yawRange=this._maxYaw-this._minYaw)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"minPitch",{get:function(){return this._minPitch},set:function(t){this._minPitch=t,this._minPitchTan=Math.tan(t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"maxPitch",{get:function(){return this._maxPitch},set:function(t){this._maxPitch=t,this._maxPitchTan=Math.tan(t)},enumerable:!1,configurable:!0}),r.prototype.update=function(){if(this.slerpAmount<1&&!this._firstFrameSkipped)this._firstFrameSkipped=!0;else{var t=this.bone,e=r._tmpVecs[0];t.getAbsolutePositionToRef(this.mesh,e);var n=this.target,i=r._tmpMats[0],o=r._tmpMats[1],a=this.mesh,s=t.getParent(),d=r._tmpVecs[1];d.copyFrom(this.upAxis),this.upAxisSpace==ye.c.BONE&&s?(this._transformYawPitch&&u.e.TransformCoordinatesToRef(d,this._transformYawPitchInv,d),s.getDirectionToRef(d,this.mesh,d)):this.upAxisSpace==ye.c.LOCAL&&(a.getDirectionToRef(d,d),a.scaling.x==1&&a.scaling.y==1&&a.scaling.z==1||d.normalize());var p=!1,b=!1;if(this._maxYaw==Math.PI&&this._minYaw==-Math.PI||(p=!0),this._maxPitch==Math.PI&&this._minPitch==-Math.PI||(b=!0),p||b){var P=r._tmpMats[2],O=r._tmpMats[3];if(this.upAxisSpace==ye.c.BONE&&d.y==1&&s)s.getRotationMatrixToRef(ye.c.WORLD,this.mesh,P);else if(this.upAxisSpace!=ye.c.LOCAL||d.y!=1||s){(F=r._tmpVecs[2]).copyFrom(this._fowardAxis),this._transformYawPitch&&u.e.TransformCoordinatesToRef(F,this._transformYawPitchInv,F),s?s.getDirectionToRef(F,this.mesh,F):a.getDirectionToRef(F,F);var B=u.e.Cross(d,F);B.normalize();var F=u.e.Cross(B,d);u.a.FromXYZAxesToRef(B,d,F,P)}else P.copyFrom(a.getWorldMatrix());P.invertToRef(O);var z=null;if(b){var J=r._tmpVecs[3];n.subtractToRef(e,J),u.e.TransformCoordinatesToRef(J,O,J),z=Math.sqrt(J.x*J.x+J.z*J.z);var ie=Math.atan2(J.y,z),se=ie;ie>this._maxPitch?(J.y=this._maxPitchTan*z,se=this._maxPitch):ie<this._minPitch&&(J.y=this._minPitchTan*z,se=this._minPitch),ie!=se&&(u.e.TransformCoordinatesToRef(J,P,J),J.addInPlace(e),n=J)}if(p){J=r._tmpVecs[4],n.subtractToRef(e,J),u.e.TransformCoordinatesToRef(J,O,J);var ce=Math.atan2(J.x,J.z),ue=ce;if((ce>this._maxYaw||ce<this._minYaw)&&(z==null&&(z=Math.sqrt(J.x*J.x+J.z*J.z)),this._yawRange>Math.PI?this._isAngleBetween(ce,this._maxYaw,this._midYawConstraint)?(J.z=this._maxYawCos*z,J.x=this._maxYawSin*z,ue=this._maxYaw):this._isAngleBetween(ce,this._midYawConstraint,this._minYaw)&&(J.z=this._minYawCos*z,J.x=this._minYawSin*z,ue=this._minYaw):ce>this._maxYaw?(J.z=this._maxYawCos*z,J.x=this._maxYawSin*z,ue=this._maxYaw):ce<this._minYaw&&(J.z=this._minYawCos*z,J.x=this._minYawSin*z,ue=this._minYaw)),this._slerping&&this._yawRange>Math.PI){var fe=r._tmpVecs[8];fe.copyFrom(ye.a.Z),this._transformYawPitch&&u.e.TransformCoordinatesToRef(fe,this._transformYawPitchInv,fe);var ve=r._tmpMats[4];this._boneQuat.toRotationMatrix(ve),this.mesh.getWorldMatrix().multiplyToRef(ve,ve),u.e.TransformCoordinatesToRef(fe,ve,fe),u.e.TransformCoordinatesToRef(fe,O,fe);var Te=Math.atan2(fe.x,fe.z);if(this._getAngleBetween(Te,ce)>this._getAngleBetween(Te,this._midYawConstraint)){z==null&&(z=Math.sqrt(J.x*J.x+J.z*J.z));var Re=this._getAngleBetween(Te,this._maxYaw);this._getAngleBetween(Te,this._minYaw)<Re?(ue=Te+.75*Math.PI,J.z=Math.cos(ue)*z,J.x=Math.sin(ue)*z):(ue=Te-.75*Math.PI,J.z=Math.cos(ue)*z,J.x=Math.sin(ue)*z)}}ce!=ue&&(u.e.TransformCoordinatesToRef(J,P,J),J.addInPlace(e),n=J)}}var Ae=r._tmpVecs[5],Ee=r._tmpVecs[6],Se=r._tmpVecs[7],Le=r._tmpQuat;n.subtractToRef(e,Ae),Ae.normalize(),u.e.CrossToRef(d,Ae,Ee),Ee.normalize(),u.e.CrossToRef(Ae,Ee,Se),Se.normalize(),u.a.FromXYZAxesToRef(Ee,Se,Ae,i),Ee.x===0&&Ee.y===0&&Ee.z===0||Se.x===0&&Se.y===0&&Se.z===0||Ae.x===0&&Ae.y===0&&Ae.z===0||((this.adjustYaw||this.adjustPitch||this.adjustRoll)&&(u.a.RotationYawPitchRollToRef(this.adjustYaw,this.adjustPitch,this.adjustRoll,o),o.multiplyToRef(i,i)),this.slerpAmount<1?(this._slerping||this.bone.getRotationQuaternionToRef(ye.c.WORLD,this.mesh,this._boneQuat),this._transformYawPitch&&this._transformYawPitch.multiplyToRef(i,i),u.b.FromRotationMatrixToRef(i,Le),u.b.SlerpToRef(this._boneQuat,Le,this.slerpAmount,this._boneQuat),this.bone.setRotationQuaternion(this._boneQuat,ye.c.WORLD,this.mesh),this._slerping=!0):(this._transformYawPitch&&this._transformYawPitch.multiplyToRef(i,i),this.bone.setRotationMatrix(i,ye.c.WORLD,this.mesh),this._slerping=!1))}},r.prototype._getAngleDiff=function(t,e){var n=e-t;return(n%=2*Math.PI)>Math.PI?n-=2*Math.PI:n<-Math.PI&&(n+=2*Math.PI),n},r.prototype._getAngleBetween=function(t,e){var n=0;return(n=(t=(t%=2*Math.PI)<0?t+2*Math.PI:t)<(e=(e%=2*Math.PI)<0?e+2*Math.PI:e)?e-t:t-e)>Math.PI&&(n=2*Math.PI-n),n},r.prototype._isAngleBetween=function(t,e,n){if(t=(t%=2*Math.PI)<0?t+2*Math.PI:t,(e=(e%=2*Math.PI)<0?e+2*Math.PI:e)<(n=(n%=2*Math.PI)<0?n+2*Math.PI:n)){if(t>e&&t<n)return!0}else if(t>n&&t<e)return!0;return!1},r._tmpVecs=Pe.a.BuildArray(10,u.e.Zero),r._tmpQuat=u.b.Identity(),r._tmpMats=Pe.a.BuildArray(5,u.a.Identity),r}(),we=f(10),xt=f(27),Bt=f(26);function ml(r,t,e,n){var i;i=n===h.a.TEXTURETYPE_FLOAT?new Float32Array(t*e*4):new Uint32Array(t*e*4);for(var o=0;o<t;o++)for(var a=0;a<e;a++){var s=3*(a*t+o),d=4*(a*t+o);i[d+0]=r[s+0],i[d+1]=r[s+1],i[d+2]=r[s+2],i[d+3]=1}return i}function gl(r){return function(t,e,n,i,o,a,s,d,p,b){p===void 0&&(p=null),b===void 0&&(b=h.a.TEXTURETYPE_UNSIGNED_INT);var P=r?this._gl.TEXTURE_3D:this._gl.TEXTURE_2D_ARRAY,O=r?xt.b.Raw3D:xt.b.Raw2DArray,B=new xt.a(this,O);B.baseWidth=e,B.baseHeight=n,B.baseDepth=i,B.width=e,B.height=n,B.depth=i,B.format=o,B.type=b,B.generateMipMaps=a,B.samplingMode=d,r?B.is3D=!0:B.is2DArray=!0,this._doNotHandleContextLost||(B._bufferView=t),r?this.updateRawTexture3D(B,t,o,s,p,b):this.updateRawTexture2DArray(B,t,o,s,p,b),this._bindTextureDirectly(P,B,!0);var F=this._getSamplingParameters(d,a);return this._gl.texParameteri(P,this._gl.TEXTURE_MAG_FILTER,F.mag),this._gl.texParameteri(P,this._gl.TEXTURE_MIN_FILTER,F.min),a&&this._gl.generateMipmap(P),this._bindTextureDirectly(P,null),this._internalTexturesCache.push(B),B}}function vl(r){return function(t,e,n,i,o,a){o===void 0&&(o=null),a===void 0&&(a=h.a.TEXTURETYPE_UNSIGNED_INT);var s=r?this._gl.TEXTURE_3D:this._gl.TEXTURE_2D_ARRAY,d=this._getWebGLTextureType(a),p=this._getInternalFormat(n),b=this._getRGBABufferInternalSizedFormat(a,n);this._bindTextureDirectly(s,t,!0),this._unpackFlipY(i===void 0||!!i),this._doNotHandleContextLost||(t._bufferView=e,t.format=n,t.invertY=i,t._compression=o),t.width%4!=0&&this._gl.pixelStorei(this._gl.UNPACK_ALIGNMENT,1),o&&e?this._gl.compressedTexImage3D(s,0,this.getCaps().s3tc[o],t.width,t.height,t.depth,0,e):this._gl.texImage3D(s,0,b,t.width,t.height,t.depth,0,p,d,e),t.generateMipMaps&&this._gl.generateMipmap(s),this._bindTextureDirectly(s,null),t.isReady=!0}}Bt.a.prototype.updateRawTexture=function(r,t,e,n,i,o){if(i===void 0&&(i=null),o===void 0&&(o=h.a.TEXTURETYPE_UNSIGNED_INT),r){var a=this._getRGBABufferInternalSizedFormat(o,e),s=this._getInternalFormat(e),d=this._getWebGLTextureType(o);this._bindTextureDirectly(this._gl.TEXTURE_2D,r,!0),this._unpackFlipY(n===void 0||!!n),this._doNotHandleContextLost||(r._bufferView=t,r.format=e,r.type=o,r.invertY=n,r._compression=i),r.width%4!=0&&this._gl.pixelStorei(this._gl.UNPACK_ALIGNMENT,1),i&&t?this._gl.compressedTexImage2D(this._gl.TEXTURE_2D,0,this.getCaps().s3tc[i],r.width,r.height,0,t):this._gl.texImage2D(this._gl.TEXTURE_2D,0,a,r.width,r.height,0,s,d,t),r.generateMipMaps&&this._gl.generateMipmap(this._gl.TEXTURE_2D),this._bindTextureDirectly(this._gl.TEXTURE_2D,null),r.isReady=!0}},Bt.a.prototype.createRawTexture=function(r,t,e,n,i,o,a,s,d){s===void 0&&(s=null),d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT);var p=new xt.a(this,xt.b.Raw);p.baseWidth=t,p.baseHeight=e,p.width=t,p.height=e,p.format=n,p.generateMipMaps=i,p.samplingMode=a,p.invertY=o,p._compression=s,p.type=d,this._doNotHandleContextLost||(p._bufferView=r),this.updateRawTexture(p,r,n,o,s,d),this._bindTextureDirectly(this._gl.TEXTURE_2D,p,!0);var b=this._getSamplingParameters(a,i);return this._gl.texParameteri(this._gl.TEXTURE_2D,this._gl.TEXTURE_MAG_FILTER,b.mag),this._gl.texParameteri(this._gl.TEXTURE_2D,this._gl.TEXTURE_MIN_FILTER,b.min),i&&this._gl.generateMipmap(this._gl.TEXTURE_2D),this._bindTextureDirectly(this._gl.TEXTURE_2D,null),this._internalTexturesCache.push(p),p},Bt.a.prototype.createRawCubeTexture=function(r,t,e,n,i,o,a,s){s===void 0&&(s=null);var d=this._gl,p=new xt.a(this,xt.b.CubeRaw);p.isCube=!0,p.format=e,p.type=n,this._doNotHandleContextLost||(p._bufferViewArray=r);var b=this._getWebGLTextureType(n),P=this._getInternalFormat(e);P===d.RGB&&(P=d.RGBA),b!==d.FLOAT||this._caps.textureFloatLinearFiltering?b!==this._gl.HALF_FLOAT_OES||this._caps.textureHalfFloatLinearFiltering?b!==d.FLOAT||this._caps.textureFloatRender?b!==d.HALF_FLOAT||this._caps.colorBufferFloat||(i=!1,l.a.Warn("Render to half float textures is not supported. Mipmap generation forced to false.")):(i=!1,l.a.Warn("Render to float textures is not supported. Mipmap generation forced to false.")):(i=!1,a=h.a.TEXTURE_NEAREST_SAMPLINGMODE,l.a.Warn("Half float texture filtering is not supported. Mipmap generation and sampling mode are forced to false and TEXTURE_NEAREST_SAMPLINGMODE, respectively.")):(i=!1,a=h.a.TEXTURE_NEAREST_SAMPLINGMODE,l.a.Warn("Float texture filtering is not supported. Mipmap generation and sampling mode are forced to false and TEXTURE_NEAREST_SAMPLINGMODE, respectively."));var O=t,B=O;p.width=O,p.height=B,!this.needPOTTextures||Xe.b.IsExponentOfTwo(p.width)&&Xe.b.IsExponentOfTwo(p.height)||(i=!1),r&&this.updateRawCubeTexture(p,r,e,n,o,s),this._bindTextureDirectly(this._gl.TEXTURE_CUBE_MAP,p,!0),r&&i&&this._gl.generateMipmap(this._gl.TEXTURE_CUBE_MAP);var F=this._getSamplingParameters(a,i);return d.texParameteri(d.TEXTURE_CUBE_MAP,d.TEXTURE_MAG_FILTER,F.mag),d.texParameteri(d.TEXTURE_CUBE_MAP,d.TEXTURE_MIN_FILTER,F.min),d.texParameteri(d.TEXTURE_CUBE_MAP,d.TEXTURE_WRAP_S,d.CLAMP_TO_EDGE),d.texParameteri(d.TEXTURE_CUBE_MAP,d.TEXTURE_WRAP_T,d.CLAMP_TO_EDGE),this._bindTextureDirectly(d.TEXTURE_CUBE_MAP,null),p.generateMipMaps=i,p},Bt.a.prototype.updateRawCubeTexture=function(r,t,e,n,i,o,a){o===void 0&&(o=null),a===void 0&&(a=0),r._bufferViewArray=t,r.format=e,r.type=n,r.invertY=i,r._compression=o;var s=this._gl,d=this._getWebGLTextureType(n),p=this._getInternalFormat(e),b=this._getRGBABufferInternalSizedFormat(n),P=!1;p===s.RGB&&(p=s.RGBA,P=!0),this._bindTextureDirectly(s.TEXTURE_CUBE_MAP,r,!0),this._unpackFlipY(i===void 0||!!i),r.width%4!=0&&s.pixelStorei(s.UNPACK_ALIGNMENT,1);for(var O=0;O<6;O++){var B=t[O];o?s.compressedTexImage2D(s.TEXTURE_CUBE_MAP_POSITIVE_X+O,a,this.getCaps().s3tc[o],r.width,r.height,0,B):(P&&(B=ml(B,r.width,r.height,n)),s.texImage2D(s.TEXTURE_CUBE_MAP_POSITIVE_X+O,a,b,r.width,r.height,0,p,d,B))}(!this.needPOTTextures||Xe.b.IsExponentOfTwo(r.width)&&Xe.b.IsExponentOfTwo(r.height))&&r.generateMipMaps&&a===0&&this._gl.generateMipmap(this._gl.TEXTURE_CUBE_MAP),this._bindTextureDirectly(this._gl.TEXTURE_CUBE_MAP,null),r.isReady=!0},Bt.a.prototype.createRawCubeTextureFromUrl=function(r,t,e,n,i,o,a,s,d,p,b,P){var O=this;d===void 0&&(d=null),p===void 0&&(p=null),b===void 0&&(b=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE),P===void 0&&(P=!1);var B=this._gl,F=this.createRawCubeTexture(null,e,n,i,!o,P,b,null);return t?._addPendingData(F),F.url=r,this._internalTexturesCache.push(F),this._loadFile(r,function(z){(function(J){var ie=F.width,se=a(J);if(se){if(s){var ce=O._getWebGLTextureType(i),ue=O._getInternalFormat(n),fe=O._getRGBABufferInternalSizedFormat(i),ve=!1;ue===B.RGB&&(ue=B.RGBA,ve=!0),O._bindTextureDirectly(B.TEXTURE_CUBE_MAP,F,!0),O._unpackFlipY(!1);for(var Te=s(se),Re=0;Re<Te.length;Re++)for(var Ae=ie>>Re,Ee=0;Ee<6;Ee++){var Se=Te[Re][Ee];ve&&(Se=ml(Se,Ae,Ae,i)),B.texImage2D(Ee,Re,fe,Ae,Ae,0,ue,ce,Se)}O._bindTextureDirectly(B.TEXTURE_CUBE_MAP,null)}else O.updateRawCubeTexture(F,se,n,i,P);F.isReady=!0,t?._removePendingData(F),d&&d()}})(z)},void 0,t?.offlineProvider,!0,function(z,J){t?._removePendingData(F),p&&z&&p(z.status+" "+z.statusText,J)}),F},Bt.a.prototype.createRawTexture2DArray=gl(!1),Bt.a.prototype.createRawTexture3D=gl(!0),Bt.a.prototype.updateRawTexture2DArray=vl(!1),Bt.a.prototype.updateRawTexture3D=vl(!0);var ii=function(r){function t(e,n,i,o,a,s,d,p,b){s===void 0&&(s=!0),d===void 0&&(d=!1),p===void 0&&(p=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE),b===void 0&&(b=h.a.TEXTURETYPE_UNSIGNED_INT);var P=r.call(this,null,a,!s,d)||this;return P.format=o,P._engine&&(P._texture=P._engine.createRawTexture(e,n,i,o,s,d,p,null,b),P.wrapU=we.a.CLAMP_ADDRESSMODE,P.wrapV=we.a.CLAMP_ADDRESSMODE),P}return Object(c.d)(t,r),t.prototype.update=function(e){this._getEngine().updateRawTexture(this._texture,e,this._texture.format,this._texture.invertY,null,this._texture.type)},t.CreateLuminanceTexture=function(e,n,i,o,a,s,d){return a===void 0&&(a=!0),s===void 0&&(s=!1),d===void 0&&(d=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE),new t(e,n,i,h.a.TEXTUREFORMAT_LUMINANCE,o,a,s,d)},t.CreateLuminanceAlphaTexture=function(e,n,i,o,a,s,d){return a===void 0&&(a=!0),s===void 0&&(s=!1),d===void 0&&(d=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE),new t(e,n,i,h.a.TEXTUREFORMAT_LUMINANCE_ALPHA,o,a,s,d)},t.CreateAlphaTexture=function(e,n,i,o,a,s,d){return a===void 0&&(a=!0),s===void 0&&(s=!1),d===void 0&&(d=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE),new t(e,n,i,h.a.TEXTUREFORMAT_ALPHA,o,a,s,d)},t.CreateRGBTexture=function(e,n,i,o,a,s,d,p){return a===void 0&&(a=!0),s===void 0&&(s=!1),d===void 0&&(d=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE),p===void 0&&(p=h.a.TEXTURETYPE_UNSIGNED_INT),new t(e,n,i,h.a.TEXTUREFORMAT_RGB,o,a,s,d,p)},t.CreateRGBATexture=function(e,n,i,o,a,s,d,p){return a===void 0&&(a=!0),s===void 0&&(s=!1),d===void 0&&(d=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE),p===void 0&&(p=h.a.TEXTURETYPE_UNSIGNED_INT),new t(e,n,i,h.a.TEXTUREFORMAT_RGBA,o,a,s,d,p)},t.CreateRTexture=function(e,n,i,o,a,s,d,p){return a===void 0&&(a=!0),s===void 0&&(s=!1),d===void 0&&(d=we.a.TRILINEAR_SAMPLINGMODE),p===void 0&&(p=h.a.TEXTURETYPE_FLOAT),new t(e,n,i,h.a.TEXTUREFORMAT_R,o,a,s,d,p)},t}(we.a),No=function(){function r(t,e,n){this.name=t,this.id=e,this.bones=new Array,this.needInitialSkinMatrix=!1,this.overrideMesh=null,this._isDirty=!0,this._meshesWithPoseMatrix=new Array,this._identity=u.a.Identity(),this._ranges={},this._lastAbsoluteTransformsUpdateId=-1,this._canUseTextureForBones=!1,this._uniqueId=0,this._numBonesWithLinkedTransformNode=0,this._hasWaitingData=null,this._waitingOverrideMeshId=null,this.doNotSerialize=!1,this._useTextureToStoreBoneMatrices=!0,this._animationPropertiesOverride=null,this.onBeforeComputeObservable=new x.c,this.bones=[],this._scene=n||te.a.LastCreatedScene,this._uniqueId=this._scene.getUniqueId(),this._scene.addSkeleton(this),this._isDirty=!0;var i=this._scene.getEngine().getCaps();this._canUseTextureForBones=i.textureFloat&&i.maxVertexTextureImageUnits>0}return Object.defineProperty(r.prototype,"useTextureToStoreBoneMatrices",{get:function(){return this._useTextureToStoreBoneMatrices},set:function(t){this._useTextureToStoreBoneMatrices=t,this._markAsDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"animationPropertiesOverride",{get:function(){return this._animationPropertiesOverride?this._animationPropertiesOverride:this._scene.animationPropertiesOverride},set:function(t){this._animationPropertiesOverride=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isUsingTextureForMatrices",{get:function(){return this.useTextureToStoreBoneMatrices&&this._canUseTextureForBones},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"uniqueId",{get:function(){return this._uniqueId},enumerable:!1,configurable:!0}),r.prototype.getClassName=function(){return"Skeleton"},r.prototype.getChildren=function(){return this.bones.filter(function(t){return!t.getParent()})},r.prototype.getTransformMatrices=function(t){return this.needInitialSkinMatrix&&t._bonesTransformMatrices?t._bonesTransformMatrices:(this._transformMatrices||this.prepare(),this._transformMatrices)},r.prototype.getTransformMatrixTexture=function(t){return this.needInitialSkinMatrix&&t._transformMatrixTexture?t._transformMatrixTexture:this._transformMatrixTexture},r.prototype.getScene=function(){return this._scene},r.prototype.toString=function(t){var e="Name: "+this.name+", nBones: "+this.bones.length;if(e+=", nAnimationRanges: "+(this._ranges?Object.keys(this._ranges).length:"none"),t){e+=", Ranges: {";var n=!0;for(var i in this._ranges)n&&(e+=", ",n=!1),e+=i;e+="}"}return e},r.prototype.getBoneIndexByName=function(t){for(var e=0,n=this.bones.length;e<n;e++)if(this.bones[e].name===t)return e;return-1},r.prototype.createAnimationRange=function(t,e,n){if(!this._ranges[t]){this._ranges[t]=new G(t,e,n);for(var i=0,o=this.bones.length;i<o;i++)this.bones[i].animations[0]&&this.bones[i].animations[0].createRange(t,e,n)}},r.prototype.deleteAnimationRange=function(t,e){e===void 0&&(e=!0);for(var n=0,i=this.bones.length;n<i;n++)this.bones[n].animations[0]&&this.bones[n].animations[0].deleteRange(t,e);this._ranges[t]=null},r.prototype.getAnimationRange=function(t){return this._ranges[t]||null},r.prototype.getAnimationRanges=function(){var t,e=[];for(t in this._ranges)e.push(this._ranges[t]);return e},r.prototype.copyAnimationRange=function(t,e,n){if(n===void 0&&(n=!1),this._ranges[e]||!t.getAnimationRange(e))return!1;var i,o,a=!0,s=this._getHighestAnimationFrame()+1,d={},p=t.bones;for(o=0,i=p.length;o<i;o++)d[p[o].name]=p[o];this.bones.length!==p.length&&(l.a.Warn("copyAnimationRange: this rig has "+this.bones.length+" bones, while source as "+p.length),a=!1);var b=n&&this.dimensionsAtRest&&t.dimensionsAtRest?this.dimensionsAtRest.divide(t.dimensionsAtRest):null;for(o=0,i=this.bones.length;o<i;o++){var P=this.bones[o].name,O=d[P];O?a=a&&this.bones[o].copyAnimationRange(O,e,s,n,b):(l.a.Warn("copyAnimationRange: not same rig, missing source bone "+P),a=!1)}var B=t.getAnimationRange(e);return B&&(this._ranges[e]=new G(e,B.from+s,B.to+s)),a},r.prototype.returnToRest=function(){for(var t=u.c.Vector3[0],e=u.c.Quaternion[0],n=u.c.Vector3[1],i=0;i<this.bones.length;i++){var o=this.bones[i];o._index!==-1&&(o.returnToRest(),o._linkedTransformNode&&(o.getRestPose().decompose(t,e,n),o._linkedTransformNode.position=n.clone(),o._linkedTransformNode.rotationQuaternion=e.clone(),o._linkedTransformNode.scaling=t.clone()))}},r.prototype._getHighestAnimationFrame=function(){for(var t=0,e=0,n=this.bones.length;e<n;e++)if(this.bones[e].animations[0]){var i=this.bones[e].animations[0].getHighestFrame();t<i&&(t=i)}return t},r.prototype.beginAnimation=function(t,e,n,i){var o=this.getAnimationRange(t);return o?this._scene.beginAnimation(this,o.from,o.to,e,n,i):null},r.MakeAnimationAdditive=function(t,e,n){e===void 0&&(e=0);var i=t.getAnimationRange(n);if(!i)return null;for(var o=t._scene.getAllAnimatablesByTarget(t),a=null,s=0;s<o.length;s++){var d=o[s];if(d.fromFrame===i?.from&&d.toFrame===i?.to){a=d;break}}var p=t.getAnimatables();for(s=0;s<p.length;s++){var b=p[s].animations;if(b)for(var P=0;P<b.length;P++)k.MakeAnimationAdditive(b[P],e,n)}return a&&(a.isAdditive=!0),t},r.prototype._markAsDirty=function(){this._isDirty=!0},r.prototype._registerMeshWithPoseMatrix=function(t){this._meshesWithPoseMatrix.push(t)},r.prototype._unregisterMeshWithPoseMatrix=function(t){var e=this._meshesWithPoseMatrix.indexOf(t);e>-1&&this._meshesWithPoseMatrix.splice(e,1)},r.prototype._computeTransformMatrices=function(t,e){this.onBeforeComputeObservable.notifyObservers(this);for(var n=0;n<this.bones.length;n++){var i=this.bones[n];i._childUpdateId++;var o=i.getParent();if(o?i.getLocalMatrix().multiplyToRef(o.getWorldMatrix(),i.getWorldMatrix()):e?i.getLocalMatrix().multiplyToRef(e,i.getWorldMatrix()):i.getWorldMatrix().copyFrom(i.getLocalMatrix()),i._index!==-1){var a=i._index===null?n:i._index;i.getInvertedAbsoluteTransform().multiplyToArray(i.getWorldMatrix(),t,16*a)}}this._identity.copyToArray(t,16*this.bones.length)},r.prototype.prepare=function(){if(this._numBonesWithLinkedTransformNode>0)for(var t=0,e=this.bones;t<e.length;t++){var n=e[t];n._linkedTransformNode&&(n._linkedTransformNode.computeWorldMatrix(),n._matrix=n._linkedTransformNode._localMatrix,n.markAsDirty())}if(this._isDirty){if(this.needInitialSkinMatrix)for(var i=0;i<this._meshesWithPoseMatrix.length;i++){var o=this._meshesWithPoseMatrix[i],a=o.getPoseMatrix();if(o._bonesTransformMatrices&&o._bonesTransformMatrices.length===16*(this.bones.length+1)||(o._bonesTransformMatrices=new Float32Array(16*(this.bones.length+1))),this._synchronizedWithMesh!==o){this._synchronizedWithMesh=o;for(var s=0;s<this.bones.length;s++){var d=this.bones[s];d.getParent()||(d.getBaseMatrix().multiplyToRef(a,u.c.Matrix[1]),d._updateDifferenceMatrix(u.c.Matrix[1]))}if(this.isUsingTextureForMatrices){var p=4*(this.bones.length+1);o._transformMatrixTexture&&o._transformMatrixTexture.getSize().width===p||(o._transformMatrixTexture&&o._transformMatrixTexture.dispose(),o._transformMatrixTexture=ii.CreateRGBATexture(o._bonesTransformMatrices,4*(this.bones.length+1),1,this._scene,!1,!1,h.a.TEXTURE_NEAREST_SAMPLINGMODE,h.a.TEXTURETYPE_FLOAT))}}this._computeTransformMatrices(o._bonesTransformMatrices,a),this.isUsingTextureForMatrices&&o._transformMatrixTexture&&o._transformMatrixTexture.update(o._bonesTransformMatrices)}else this._transformMatrices&&this._transformMatrices.length===16*(this.bones.length+1)||(this._transformMatrices=new Float32Array(16*(this.bones.length+1)),this.isUsingTextureForMatrices&&(this._transformMatrixTexture&&this._transformMatrixTexture.dispose(),this._transformMatrixTexture=ii.CreateRGBATexture(this._transformMatrices,4*(this.bones.length+1),1,this._scene,!1,!1,h.a.TEXTURE_NEAREST_SAMPLINGMODE,h.a.TEXTURETYPE_FLOAT))),this._computeTransformMatrices(this._transformMatrices,null),this.isUsingTextureForMatrices&&this._transformMatrixTexture&&this._transformMatrixTexture.update(this._transformMatrices);this._isDirty=!1,this._scene._activeBones.addCount(this.bones.length,!1)}},r.prototype.getAnimatables=function(){if(!this._animatables||this._animatables.length!==this.bones.length){this._animatables=[];for(var t=0;t<this.bones.length;t++)this._animatables.push(this.bones[t])}return this._animatables},r.prototype.clone=function(t,e){var n=new r(t,e||t,this._scene);n.needInitialSkinMatrix=this.needInitialSkinMatrix,n.overrideMesh=this.overrideMesh;for(var i=0;i<this.bones.length;i++){var o=this.bones[i],a=null,s=o.getParent();if(s){var d=this.bones.indexOf(s);a=n.bones[d]}var p=new Be(o.name,n,a,o.getBaseMatrix().clone(),o.getRestPose().clone());p._index=o._index,o._linkedTransformNode&&p.linkTransformNode(o._linkedTransformNode),de.a.DeepCopy(o.animations,p.animations)}if(this._ranges)for(var b in n._ranges={},this._ranges){var P=this._ranges[b];P&&(n._ranges[b]=P.clone())}return this._isDirty=!0,n},r.prototype.enableBlending=function(t){t===void 0&&(t=.01),this.bones.forEach(function(e){e.animations.forEach(function(n){n.enableBlending=!0,n.blendingSpeed=t})})},r.prototype.dispose=function(){this._meshesWithPoseMatrix=[],this.getScene().stopAnimation(this),this.getScene().removeSkeleton(this),this._transformMatrixTexture&&(this._transformMatrixTexture.dispose(),this._transformMatrixTexture=null)},r.prototype.serialize=function(){var t,e,n={};n.name=this.name,n.id=this.id,this.dimensionsAtRest&&(n.dimensionsAtRest=this.dimensionsAtRest.asArray()),n.bones=[],n.needInitialSkinMatrix=this.needInitialSkinMatrix,n.overrideMeshId=(t=this.overrideMesh)===null||t===void 0?void 0:t.id;for(var i=0;i<this.bones.length;i++){var o=this.bones[i],a=o.getParent(),s={parentBoneIndex:a?this.bones.indexOf(a):-1,index:o.getIndex(),name:o.name,matrix:o.getBaseMatrix().toArray(),rest:o.getRestPose().toArray(),linkedTransformNodeId:(e=o.getTransformNode())===null||e===void 0?void 0:e.id};for(var d in n.bones.push(s),o.length&&(s.length=o.length),o.metadata&&(s.metadata=o.metadata),o.animations&&o.animations.length>0&&(s.animation=o.animations[0].serialize()),n.ranges=[],this._ranges){var p=this._ranges[d];if(p){var b={};b.name=d,b.from=p.from,b.to=p.to,n.ranges.push(b)}}}return n},r.Parse=function(t,e){var n,i=new r(t.name,t.id,e);for(t.dimensionsAtRest&&(i.dimensionsAtRest=u.e.FromArray(t.dimensionsAtRest)),i.needInitialSkinMatrix=t.needInitialSkinMatrix,t.overrideMeshId&&(i._hasWaitingData=!0,i._waitingOverrideMeshId=t.overrideMeshId),n=0;n<t.bones.length;n++){var o=t.bones[n],a=t.bones[n].index,s=null;o.parentBoneIndex>-1&&(s=i.bones[o.parentBoneIndex]);var d=o.rest?u.a.FromArray(o.rest):null,p=new Be(o.name,i,s,u.a.FromArray(o.matrix),d,null,a);o.id!==void 0&&o.id!==null&&(p.id=o.id),o.length&&(p.length=o.length),o.metadata&&(p.metadata=o.metadata),o.animation&&p.animations.push(k.Parse(o.animation)),o.linkedTransformNodeId!==void 0&&o.linkedTransformNodeId!==null&&(i._hasWaitingData=!0,p._waitingTransformNodeId=o.linkedTransformNodeId)}if(t.ranges)for(n=0;n<t.ranges.length;n++){var b=t.ranges[n];i.createAnimationRange(b.name,b.from,b.to)}return i},r.prototype.computeAbsoluteTransforms=function(t){t===void 0&&(t=!1);var e=this._scene.getRenderId();(this._lastAbsoluteTransformsUpdateId!=e||t)&&(this.bones[0].computeAbsoluteTransforms(),this._lastAbsoluteTransformsUpdateId=e)},r.prototype.getPoseMatrix=function(){var t=null;return this._meshesWithPoseMatrix.length>0&&(t=this._meshesWithPoseMatrix[0].getPoseMatrix()),t},r.prototype.sortBones=function(){for(var t=new Array,e=new Array(this.bones.length),n=0;n<this.bones.length;n++)this._sortBones(n,t,e);this.bones=t},r.prototype._sortBones=function(t,e,n){if(!n[t]){n[t]=!0;var i=this.bones[t];i._index===void 0&&(i._index=t);var o=i.getParent();o&&this._sortBones(this.bones.indexOf(o),e,n),e.push(i)}},r.prototype.setCurrentPoseAsRest=function(){this.bones.forEach(function(t){t.setCurrentPoseAsRest()})},r}(),hn={},$r=function(){function r(t){this.attachedToElement=!1,this.attached={},this.camera=t,this.checkInputs=function(){}}return r.prototype.add=function(t){var e=t.getSimpleName();this.attached[e]?l.a.Warn("camera input of type "+e+" already exists on camera"):(this.attached[e]=t,t.camera=this.camera,t.checkInputs&&(this.checkInputs=this._addCheckInputs(t.checkInputs.bind(t))),this.attachedToElement&&t.attachControl())},r.prototype.remove=function(t){for(var e in this.attached){var n=this.attached[e];n===t&&(n.detachControl(),n.camera=null,delete this.attached[e],this.rebuildInputCheck())}},r.prototype.removeByType=function(t){for(var e in this.attached){var n=this.attached[e];n.getClassName()===t&&(n.detachControl(),n.camera=null,delete this.attached[e],this.rebuildInputCheck())}},r.prototype._addCheckInputs=function(t){var e=this.checkInputs;return function(){e(),t()}},r.prototype.attachInput=function(t){this.attachedToElement&&t.attachControl(this.noPreventDefault)},r.prototype.attachElement=function(t){if(t===void 0&&(t=!1),!this.attachedToElement)for(var e in t=!gt.a.ForceAttachControlToAlwaysPreventDefault&&t,this.attachedToElement=!0,this.noPreventDefault=t,this.attached)this.attached[e].attachControl(t)},r.prototype.detachElement=function(t){for(var e in t===void 0&&(t=!1),this.attached)this.attached[e].detachControl(),t&&(this.attached[e].camera=null);this.attachedToElement=!1},r.prototype.rebuildInputCheck=function(){for(var t in this.checkInputs=function(){},this.attached){var e=this.attached[t];e.checkInputs&&(this.checkInputs=this._addCheckInputs(e.checkInputs.bind(e)))}},r.prototype.clear=function(){this.attachedToElement&&this.detachElement(!0),this.attached={},this.attachedToElement=!1,this.checkInputs=function(){}},r.prototype.serialize=function(t){var e={};for(var n in this.attached){var i=this.attached[n],o=L.a.Serialize(i);e[i.getClassName()]=o}t.inputsmgr=e},r.prototype.parse=function(t){var e=t.inputsmgr;if(e){for(var n in this.clear(),e)if(a=hn[n]){var i=e[n],o=L.a.Parse(function(){return new a},i,null);this.add(o)}}else for(var n in this.attached){var a;(a=hn[this.attached[n].getClassName()])&&(o=L.a.Parse(function(){return new a},t,null),this.remove(this.attached[n]),this.add(o))}},r}(),Bf=function(r,t){this.x=r,this.y=t},dn=function(){function r(t,e,n,i,o,a,s){i===void 0&&(i=0),o===void 0&&(o=1),a===void 0&&(a=2),s===void 0&&(s=3),this.id=t,this.index=e,this.browserGamepad=n,this._leftStick={x:0,y:0},this._rightStick={x:0,y:0},this._isConnected=!0,this._invertLeftStickY=!1,this.type=r.GAMEPAD,this._leftStickAxisX=i,this._leftStickAxisY=o,this._rightStickAxisX=a,this._rightStickAxisY=s,this.browserGamepad.axes.length>=2&&(this._leftStick={x:this.browserGamepad.axes[this._leftStickAxisX],y:this.browserGamepad.axes[this._leftStickAxisY]}),this.browserGamepad.axes.length>=4&&(this._rightStick={x:this.browserGamepad.axes[this._rightStickAxisX],y:this.browserGamepad.axes[this._rightStickAxisY]})}return Object.defineProperty(r.prototype,"isConnected",{get:function(){return this._isConnected},enumerable:!1,configurable:!0}),r.prototype.onleftstickchanged=function(t){this._onleftstickchanged=t},r.prototype.onrightstickchanged=function(t){this._onrightstickchanged=t},Object.defineProperty(r.prototype,"leftStick",{get:function(){return this._leftStick},set:function(t){!this._onleftstickchanged||this._leftStick.x===t.x&&this._leftStick.y===t.y||this._onleftstickchanged(t),this._leftStick=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"rightStick",{get:function(){return this._rightStick},set:function(t){!this._onrightstickchanged||this._rightStick.x===t.x&&this._rightStick.y===t.y||this._onrightstickchanged(t),this._rightStick=t},enumerable:!1,configurable:!0}),r.prototype.update=function(){this._leftStick&&(this.leftStick={x:this.browserGamepad.axes[this._leftStickAxisX],y:this.browserGamepad.axes[this._leftStickAxisY]},this._invertLeftStickY&&(this.leftStick.y*=-1)),this._rightStick&&(this.rightStick={x:this.browserGamepad.axes[this._rightStickAxisX],y:this.browserGamepad.axes[this._rightStickAxisY]})},r.prototype.dispose=function(){},r.GAMEPAD=0,r.GENERIC=1,r.XBOX=2,r.POSE_ENABLED=3,r.DUALSHOCK=4,r}(),bl=function(r){function t(e,n,i){var o=r.call(this,e,n,i)||this;return o.onButtonDownObservable=new x.c,o.onButtonUpObservable=new x.c,o.type=dn.GENERIC,o._buttons=new Array(i.buttons.length),o}return Object(c.d)(t,r),t.prototype.onbuttondown=function(e){this._onbuttondown=e},t.prototype.onbuttonup=function(e){this._onbuttonup=e},t.prototype._setButtonValue=function(e,n,i){return e!==n&&(e===1&&(this._onbuttondown&&this._onbuttondown(i),this.onButtonDownObservable.notifyObservers(i)),e===0&&(this._onbuttonup&&this._onbuttonup(i),this.onButtonUpObservable.notifyObservers(i))),e},t.prototype.update=function(){r.prototype.update.call(this);for(var e=0;e<this._buttons.length;e++)this._buttons[e]=this._setButtonValue(this.browserGamepad.buttons[e].value,this._buttons[e],e)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onButtonDownObservable.clear(),this.onButtonUpObservable.clear()},t}(dn),ja=function(){function r(){this.gamepadRotationSensibility=80,this.gamepadMoveSensibility=40,this._yAxisScale=1}return Object.defineProperty(r.prototype,"invertYAxis",{get:function(){return this._yAxisScale!==1},set:function(t){this._yAxisScale=t?-1:1},enumerable:!1,configurable:!0}),r.prototype.attachControl=function(){var t=this,e=this.camera.getScene().gamepadManager;this._onGamepadConnectedObserver=e.onGamepadConnectedObservable.add(function(n){n.type!==dn.POSE_ENABLED&&(t.gamepad&&n.type!==dn.XBOX||(t.gamepad=n))}),this._onGamepadDisconnectedObserver=e.onGamepadDisconnectedObservable.add(function(n){t.gamepad===n&&(t.gamepad=null)}),this.gamepad=e.getGamepadByType(dn.XBOX)},r.prototype.detachControl=function(t){this.camera.getScene().gamepadManager.onGamepadConnectedObservable.remove(this._onGamepadConnectedObserver),this.camera.getScene().gamepadManager.onGamepadDisconnectedObservable.remove(this._onGamepadDisconnectedObserver),this.gamepad=null},r.prototype.checkInputs=function(){if(this.gamepad){var t=this.camera,e=this.gamepad.rightStick;if(e){if(e.x!=0){var n=e.x/this.gamepadRotationSensibility;n!=0&&Math.abs(n)>.005&&(t.inertialAlphaOffset+=n)}if(e.y!=0){var i=e.y/this.gamepadRotationSensibility*this._yAxisScale;i!=0&&Math.abs(i)>.005&&(t.inertialBetaOffset+=i)}}var o=this.gamepad.leftStick;if(o&&o.y!=0){var a=o.y/this.gamepadMoveSensibility;a!=0&&Math.abs(a)>.005&&(this.camera.inertialRadiusOffset-=a)}}},r.prototype.getClassName=function(){return"ArcRotateCameraGamepadInput"},r.prototype.getSimpleName=function(){return"gamepad"},Object(c.c)([Object(L.c)()],r.prototype,"gamepadRotationSensibility",void 0),Object(c.c)([Object(L.c)()],r.prototype,"gamepadMoveSensibility",void 0),r}();hn.ArcRotateCameraGamepadInput=ja;var Zi=f(66),Ha=function(){function r(){this.keysUp=[38],this.keysDown=[40],this.keysLeft=[37],this.keysRight=[39],this.keysReset=[220],this.panningSensibility=50,this.zoomingSensibility=25,this.useAltToZoom=!0,this.angularSpeed=.01,this._keys=new Array}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments),this._onCanvasBlurObserver||(this._scene=this.camera.getScene(),this._engine=this._scene.getEngine(),this._onCanvasBlurObserver=this._engine.onCanvasBlurObservable.add(function(){e._keys=[]}),this._onKeyboardObserver=this._scene.onKeyboardObservable.add(function(n){var i,o=n.event;o.metaKey||(n.type===Zi.a.KEYDOWN?(e._ctrlPressed=o.ctrlKey,e._altPressed=o.altKey,(e.keysUp.indexOf(o.keyCode)!==-1||e.keysDown.indexOf(o.keyCode)!==-1||e.keysLeft.indexOf(o.keyCode)!==-1||e.keysRight.indexOf(o.keyCode)!==-1||e.keysReset.indexOf(o.keyCode)!==-1)&&((i=e._keys.indexOf(o.keyCode))===-1&&e._keys.push(o.keyCode),o.preventDefault&&(t||o.preventDefault()))):e.keysUp.indexOf(o.keyCode)===-1&&e.keysDown.indexOf(o.keyCode)===-1&&e.keysLeft.indexOf(o.keyCode)===-1&&e.keysRight.indexOf(o.keyCode)===-1&&e.keysReset.indexOf(o.keyCode)===-1||((i=e._keys.indexOf(o.keyCode))>=0&&e._keys.splice(i,1),o.preventDefault&&(t||o.preventDefault())))}))},r.prototype.detachControl=function(t){this._scene&&(this._onKeyboardObserver&&this._scene.onKeyboardObservable.remove(this._onKeyboardObserver),this._onCanvasBlurObserver&&this._engine.onCanvasBlurObservable.remove(this._onCanvasBlurObserver),this._onKeyboardObserver=null,this._onCanvasBlurObserver=null),this._keys=[]},r.prototype.checkInputs=function(){if(this._onKeyboardObserver)for(var t=this.camera,e=0;e<this._keys.length;e++){var n=this._keys[e];this.keysLeft.indexOf(n)!==-1?this._ctrlPressed&&this.camera._useCtrlForPanning?t.inertialPanningX-=1/this.panningSensibility:t.inertialAlphaOffset-=this.angularSpeed:this.keysUp.indexOf(n)!==-1?this._ctrlPressed&&this.camera._useCtrlForPanning?t.inertialPanningY+=1/this.panningSensibility:this._altPressed&&this.useAltToZoom?t.inertialRadiusOffset+=1/this.zoomingSensibility:t.inertialBetaOffset-=this.angularSpeed:this.keysRight.indexOf(n)!==-1?this._ctrlPressed&&this.camera._useCtrlForPanning?t.inertialPanningX+=1/this.panningSensibility:t.inertialAlphaOffset+=this.angularSpeed:this.keysDown.indexOf(n)!==-1?this._ctrlPressed&&this.camera._useCtrlForPanning?t.inertialPanningY-=1/this.panningSensibility:this._altPressed&&this.useAltToZoom?t.inertialRadiusOffset-=1/this.zoomingSensibility:t.inertialBetaOffset+=this.angularSpeed:this.keysReset.indexOf(n)!==-1&&t.useInputToRestoreState&&t.restoreState()}},r.prototype.getClassName=function(){return"ArcRotateCameraKeyboardMoveInput"},r.prototype.getSimpleName=function(){return"keyboard"},Object(c.c)([Object(L.c)()],r.prototype,"keysUp",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysDown",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysLeft",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRight",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysReset",void 0),Object(c.c)([Object(L.c)()],r.prototype,"panningSensibility",void 0),Object(c.c)([Object(L.c)()],r.prototype,"zoomingSensibility",void 0),Object(c.c)([Object(L.c)()],r.prototype,"useAltToZoom",void 0),Object(c.c)([Object(L.c)()],r.prototype,"angularSpeed",void 0),r}();hn.ArcRotateCameraKeyboardMoveInput=Ha;var Wa=function(){function r(){this.wheelPrecision=3,this.wheelDeltaPercentage=0}return r.prototype.computeDeltaFromMouseWheelLegacyEvent=function(t,e){var n=.01*t*this.wheelDeltaPercentage*e;return t>0?n/(1+this.wheelDeltaPercentage):n*(1+this.wheelDeltaPercentage)},r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments),this._wheel=function(n,i){if(n.type===Tt.a.POINTERWHEEL){var o=n.event,a=0,s=o,d=0;if(d=s.wheelDelta?s.wheelDelta:60*-(o.deltaY||o.detail),e.wheelDeltaPercentage){if((a=e.computeDeltaFromMouseWheelLegacyEvent(d,e.camera.radius))>0){for(var p=e.camera.radius,b=e.camera.inertialRadiusOffset+a,P=0;P<20&&Math.abs(b)>.001;P++)p-=b,b*=e.camera.inertia;p=$.a.Clamp(p,0,Number.MAX_VALUE),a=e.computeDeltaFromMouseWheelLegacyEvent(d,p)}}else a=d/(40*e.wheelPrecision);a&&(e.camera.inertialRadiusOffset+=a),o.preventDefault&&(t||o.preventDefault())}},this._observer=this.camera.getScene().onPointerObservable.add(this._wheel,Tt.a.POINTERWHEEL)},r.prototype.detachControl=function(t){this._observer&&(this.camera.getScene().onPointerObservable.remove(this._observer),this._observer=null,this._wheel=null)},r.prototype.getClassName=function(){return"ArcRotateCameraMouseWheelInput"},r.prototype.getSimpleName=function(){return"mousewheel"},Object(c.c)([Object(L.c)()],r.prototype,"wheelPrecision",void 0),Object(c.c)([Object(L.c)()],r.prototype,"wheelDeltaPercentage",void 0),r}();hn.ArcRotateCameraMouseWheelInput=Wa;var yl=function(){function r(){this.buttons=[0,1,2]}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments);var n=this.camera.getEngine(),i=n.getInputElement(),o=0,a=null;this.pointA=null,this.pointB=null,this._altKey=!1,this._ctrlKey=!1,this._metaKey=!1,this._shiftKey=!1,this._buttonsPressed=0,this._pointerInput=function(d,p){var b=d.event,P=b.pointerType==="touch";if(!n.isInVRExclusivePointerMode&&(d.type===Tt.a.POINTERMOVE||e.buttons.indexOf(b.button)!==-1)){var O=b.srcElement||b.target;if(e._altKey=b.altKey,e._ctrlKey=b.ctrlKey,e._metaKey=b.metaKey,e._shiftKey=b.shiftKey,e._buttonsPressed=b.buttons,n.isPointerLock){var B=b.movementX||b.mozMovementX||b.webkitMovementX||b.msMovementX||0,F=b.movementY||b.mozMovementY||b.webkitMovementY||b.msMovementY||0;e.onTouch(null,B,F),e.pointA=null,e.pointB=null}else if(d.type===Tt.a.POINTERDOWN&&O){try{O.setPointerCapture(b.pointerId)}catch{}e.pointA===null?e.pointA={x:b.clientX,y:b.clientY,pointerId:b.pointerId,type:b.pointerType}:e.pointB===null&&(e.pointB={x:b.clientX,y:b.clientY,pointerId:b.pointerId,type:b.pointerType}),e.onButtonDown(b),t||(b.preventDefault(),i&&i.focus())}else if(d.type===Tt.a.POINTERDOUBLETAP)e.onDoubleTap(b.pointerType);else if(d.type===Tt.a.POINTERUP&&O){try{O.releasePointerCapture(b.pointerId)}catch{}P||(e.pointB=null),n._badOS?e.pointA=e.pointB=null:e.pointB&&e.pointA&&e.pointA.pointerId==b.pointerId?(e.pointA=e.pointB,e.pointB=null):e.pointA&&e.pointB&&e.pointB.pointerId==b.pointerId?e.pointB=null:e.pointA=e.pointB=null,(o!==0||a)&&(e.onMultiTouch(e.pointA,e.pointB,o,0,a,null),o=0,a=null),e.onButtonUp(b),t||b.preventDefault()}else if(d.type===Tt.a.POINTERMOVE){if(t||b.preventDefault(),e.pointA&&e.pointB===null)B=b.clientX-e.pointA.x,F=b.clientY-e.pointA.y,e.onTouch(e.pointA,B,F),e.pointA.x=b.clientX,e.pointA.y=b.clientY;else if(e.pointA&&e.pointB){var z=e.pointA.pointerId===b.pointerId?e.pointA:e.pointB;z.x=b.clientX,z.y=b.clientY;var J=e.pointA.x-e.pointB.x,ie=e.pointA.y-e.pointB.y,se=J*J+ie*ie,ce={x:(e.pointA.x+e.pointB.x)/2,y:(e.pointA.y+e.pointB.y)/2,pointerId:b.pointerId,type:d.type};e.onMultiTouch(e.pointA,e.pointB,o,se,a,ce),a=ce,o=se}}}},this._observer=this.camera.getScene().onPointerObservable.add(this._pointerInput,Tt.a.POINTERDOWN|Tt.a.POINTERUP|Tt.a.POINTERMOVE),this._onLostFocus=function(){e.pointA=e.pointB=null,o=0,a=null,e.onLostFocus()},i&&i.addEventListener("contextmenu",this.onContextMenu.bind(this),!1);var s=this.camera.getScene().getEngine().getHostWindow();s&&Xe.b.RegisterTopRootEvents(s,[{name:"blur",handler:this._onLostFocus}])},r.prototype.detachControl=function(t){if(this._onLostFocus){var e=this.camera.getScene().getEngine().getHostWindow();e&&Xe.b.UnregisterTopRootEvents(e,[{name:"blur",handler:this._onLostFocus}])}if(this._observer){if(this.camera.getScene().onPointerObservable.remove(this._observer),this._observer=null,this.onContextMenu){var n=this.camera.getScene().getEngine().getInputElement();n&&n.removeEventListener("contextmenu",this.onContextMenu)}this._onLostFocus=null}this._altKey=!1,this._ctrlKey=!1,this._metaKey=!1,this._shiftKey=!1,this._buttonsPressed=0},r.prototype.getClassName=function(){return"BaseCameraPointersInput"},r.prototype.getSimpleName=function(){return"pointers"},r.prototype.onDoubleTap=function(t){},r.prototype.onTouch=function(t,e,n){},r.prototype.onMultiTouch=function(t,e,n,i,o,a){},r.prototype.onContextMenu=function(t){t.preventDefault()},r.prototype.onButtonDown=function(t){},r.prototype.onButtonUp=function(t){},r.prototype.onLostFocus=function(){},Object(c.c)([Object(L.c)()],r.prototype,"buttons",void 0),r}(),Xa=function(r){function t(){var e=r!==null&&r.apply(this,arguments)||this;return e.buttons=[0,1,2],e.angularSensibilityX=1e3,e.angularSensibilityY=1e3,e.pinchPrecision=12,e.pinchDeltaPercentage=0,e.useNaturalPinchZoom=!1,e.panningSensibility=1e3,e.multiTouchPanning=!0,e.multiTouchPanAndZoom=!0,e.pinchInwards=!0,e._isPanClick=!1,e._twoFingerActivityCount=0,e._isPinching=!1,e}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ArcRotateCameraPointersInput"},t.prototype.onTouch=function(e,n,i){this.panningSensibility!==0&&(this._ctrlKey&&this.camera._useCtrlForPanning||this._isPanClick)?(this.camera.inertialPanningX+=-n/this.panningSensibility,this.camera.inertialPanningY+=i/this.panningSensibility):(this.camera.inertialAlphaOffset-=n/this.angularSensibilityX,this.camera.inertialBetaOffset-=i/this.angularSensibilityY)},t.prototype.onDoubleTap=function(e){this.camera.useInputToRestoreState&&this.camera.restoreState()},t.prototype.onMultiTouch=function(e,n,i,o,a,s){if(!(i===0&&a===null||o===0&&s===null)){var d=this.pinchInwards?1:-1;if(this.multiTouchPanAndZoom){if(this.useNaturalPinchZoom?this.camera.radius=this.camera.radius*Math.sqrt(i)/Math.sqrt(o):this.pinchDeltaPercentage?this.camera.inertialRadiusOffset+=.001*(o-i)*this.camera.radius*this.pinchDeltaPercentage:this.camera.inertialRadiusOffset+=(o-i)/(this.pinchPrecision*d*(this.angularSensibilityX+this.angularSensibilityY)/2),this.panningSensibility!==0&&a&&s){var p=s.x-a.x,b=s.y-a.y;this.camera.inertialPanningX+=-p/this.panningSensibility,this.camera.inertialPanningY+=b/this.panningSensibility}}else{this._twoFingerActivityCount++;var P=Math.sqrt(i),O=Math.sqrt(o);this._isPinching||this._twoFingerActivityCount<20&&Math.abs(O-P)>this.camera.pinchToPanMaxDistance?(this.pinchDeltaPercentage?this.camera.inertialRadiusOffset+=.001*(o-i)*this.camera.radius*this.pinchDeltaPercentage:this.camera.inertialRadiusOffset+=(o-i)/(this.pinchPrecision*d*(this.angularSensibilityX+this.angularSensibilityY)/2),this._isPinching=!0):this.panningSensibility!==0&&this.multiTouchPanning&&s&&a&&(p=s.x-a.x,b=s.y-a.y,this.camera.inertialPanningX+=-p/this.panningSensibility,this.camera.inertialPanningY+=b/this.panningSensibility)}}},t.prototype.onButtonDown=function(e){this._isPanClick=e.button===this.camera._panningMouseButton},t.prototype.onButtonUp=function(e){this._twoFingerActivityCount=0,this._isPinching=!1},t.prototype.onLostFocus=function(){this._isPanClick=!1,this._twoFingerActivityCount=0,this._isPinching=!1},Object(c.c)([Object(L.c)()],t.prototype,"buttons",void 0),Object(c.c)([Object(L.c)()],t.prototype,"angularSensibilityX",void 0),Object(c.c)([Object(L.c)()],t.prototype,"angularSensibilityY",void 0),Object(c.c)([Object(L.c)()],t.prototype,"pinchPrecision",void 0),Object(c.c)([Object(L.c)()],t.prototype,"pinchDeltaPercentage",void 0),Object(c.c)([Object(L.c)()],t.prototype,"useNaturalPinchZoom",void 0),Object(c.c)([Object(L.c)()],t.prototype,"panningSensibility",void 0),Object(c.c)([Object(L.c)()],t.prototype,"multiTouchPanning",void 0),Object(c.c)([Object(L.c)()],t.prototype,"multiTouchPanAndZoom",void 0),t}(yl);hn.ArcRotateCameraPointersInput=Xa;var wo=function(r){function t(e){return r.call(this,e)||this}return Object(c.d)(t,r),t.prototype.addMouseWheel=function(){return this.add(new Wa),this},t.prototype.addPointers=function(){return this.add(new Xa),this},t.prototype.addKeyboard=function(){return this.add(new Ha),this},t}($r);wo.prototype.addVRDeviceOrientation=function(){return this.add(new Ya),this};var Ya=function(){function r(){this.alphaCorrection=1,this.gammaCorrection=1,this._alpha=0,this._gamma=0,this._dirty=!1,this._deviceOrientationHandler=this._onOrientationEvent.bind(this)}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments),this.camera.attachControl(t);var n=this.camera.getScene().getEngine().getHostWindow();n&&(typeof DeviceOrientationEvent<"u"&&typeof DeviceOrientationEvent.requestPermission=="function"?DeviceOrientationEvent.requestPermission().then(function(i){i==="granted"?n.addEventListener("deviceorientation",e._deviceOrientationHandler):Xe.b.Warn("Permission not granted.")}).catch(function(i){Xe.b.Error(i)}):n.addEventListener("deviceorientation",this._deviceOrientationHandler))},r.prototype._onOrientationEvent=function(t){t.alpha!==null&&(this._alpha=(0|+t.alpha)*this.alphaCorrection),t.gamma!==null&&(this._gamma=(0|+t.gamma)*this.gammaCorrection),this._dirty=!0},r.prototype.checkInputs=function(){this._dirty&&(this._dirty=!1,this._gamma<0&&(this._gamma=180+this._gamma),this.camera.alpha=-this._alpha/180*Math.PI%Math.PI*2,this.camera.beta=this._gamma/180*Math.PI)},r.prototype.detachControl=function(t){window.removeEventListener("deviceorientation",this._deviceOrientationHandler)},r.prototype.getClassName=function(){return"ArcRotateCameraVRDeviceOrientationInput"},r.prototype.getSimpleName=function(){return"VRDeviceOrientation"},r}();hn.ArcRotateCameraVRDeviceOrientationInput=Ya;var Ka=function(){function r(){this.keysForward=[87],this.keysBackward=[83],this.keysUp=[69],this.keysDown=[81],this.keysRight=[68],this.keysLeft=[65],this._keys=new Array}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments),this._onCanvasBlurObserver||(this._scene=this.camera.getScene(),this._engine=this._scene.getEngine(),this._onCanvasBlurObserver=this._engine.onCanvasBlurObservable.add(function(){e._keys=[]}),this._onKeyboardObserver=this._scene.onKeyboardObservable.add(function(n){var i,o=n.event;n.type===Zi.a.KEYDOWN?e.keysForward.indexOf(o.keyCode)===-1&&e.keysBackward.indexOf(o.keyCode)===-1&&e.keysUp.indexOf(o.keyCode)===-1&&e.keysDown.indexOf(o.keyCode)===-1&&e.keysLeft.indexOf(o.keyCode)===-1&&e.keysRight.indexOf(o.keyCode)===-1||((i=e._keys.indexOf(o.keyCode))===-1&&e._keys.push(o.keyCode),t||o.preventDefault()):e.keysForward.indexOf(o.keyCode)===-1&&e.keysBackward.indexOf(o.keyCode)===-1&&e.keysUp.indexOf(o.keyCode)===-1&&e.keysDown.indexOf(o.keyCode)===-1&&e.keysLeft.indexOf(o.keyCode)===-1&&e.keysRight.indexOf(o.keyCode)===-1||((i=e._keys.indexOf(o.keyCode))>=0&&e._keys.splice(i,1),t||o.preventDefault())}))},r.prototype.detachControl=function(t){this._scene&&(this._onKeyboardObserver&&this._scene.onKeyboardObservable.remove(this._onKeyboardObserver),this._onCanvasBlurObserver&&this._engine.onCanvasBlurObservable.remove(this._onCanvasBlurObserver),this._onKeyboardObserver=null,this._onCanvasBlurObserver=null),this._keys=[]},r.prototype.getClassName=function(){return"FlyCameraKeyboardInput"},r.prototype._onLostFocus=function(t){this._keys=[]},r.prototype.getSimpleName=function(){return"keyboard"},r.prototype.checkInputs=function(){if(this._onKeyboardObserver)for(var t=this.camera,e=0;e<this._keys.length;e++){var n=this._keys[e],i=t._computeLocalCameraSpeed();this.keysForward.indexOf(n)!==-1?t._localDirection.copyFromFloats(0,0,i):this.keysBackward.indexOf(n)!==-1?t._localDirection.copyFromFloats(0,0,-i):this.keysUp.indexOf(n)!==-1?t._localDirection.copyFromFloats(0,i,0):this.keysDown.indexOf(n)!==-1?t._localDirection.copyFromFloats(0,-i,0):this.keysRight.indexOf(n)!==-1?t._localDirection.copyFromFloats(i,0,0):this.keysLeft.indexOf(n)!==-1&&t._localDirection.copyFromFloats(-i,0,0),t.getScene().useRightHandedSystem&&(t._localDirection.z*=-1),t.getViewMatrix().invertToRef(t._cameraTransformMatrix),u.e.TransformNormalToRef(t._localDirection,t._cameraTransformMatrix,t._transformedDirection),t.cameraDirection.addInPlace(t._transformedDirection)}},Object(c.c)([Object(L.c)()],r.prototype,"keysForward",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysBackward",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysUp",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysDown",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRight",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysLeft",void 0),r}();hn.FlyCameraKeyboardInput=Ka;var Qa=function(){function r(t){this.buttons=[0,1,2],this.buttonsYaw=[-1,0,1],this.buttonsPitch=[-1,0,1],this.buttonsRoll=[2],this.activeButton=-1,this.angularSensibility=1e3,this.previousPosition=null}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments),this.noPreventDefault=t,this._observer=this.camera.getScene().onPointerObservable.add(function(n,i){e._pointerInput(n,i)},Tt.a.POINTERDOWN|Tt.a.POINTERUP|Tt.a.POINTERMOVE),this._rollObserver=this.camera.getScene().onBeforeRenderObservable.add(function(){e.camera.rollCorrect&&e.camera.restoreRoll(e.camera.rollCorrect)})},r.prototype.detachControl=function(t){this._observer&&(this.camera.getScene().onPointerObservable.remove(this._observer),this.camera.getScene().onBeforeRenderObservable.remove(this._rollObserver),this._observer=null,this._rollObserver=null,this.previousPosition=null,this.noPreventDefault=void 0)},r.prototype.getClassName=function(){return"FlyCameraMouseInput"},r.prototype.getSimpleName=function(){return"mouse"},r.prototype._pointerInput=function(t,e){var n=t.event,i=this.camera.getEngine();if(!i.isInVRExclusivePointerMode&&(this.touchEnabled||n.pointerType!=="touch")&&(t.type===Tt.a.POINTERMOVE||this.buttons.indexOf(n.button)!==-1)){var o=n.srcElement||n.target;if(t.type===Tt.a.POINTERDOWN&&o){try{o.setPointerCapture(n.pointerId)}catch{}this.previousPosition={x:n.clientX,y:n.clientY},this.activeButton=n.button,this.noPreventDefault||(n.preventDefault(),this.element.focus()),i.isPointerLock&&this._onMouseMove(t.event)}else if(t.type===Tt.a.POINTERUP&&o){try{o.releasePointerCapture(n.pointerId)}catch{}this.activeButton=-1,this.previousPosition=null,this.noPreventDefault||n.preventDefault()}else if(t.type===Tt.a.POINTERMOVE){if(!this.previousPosition)return void(i.isPointerLock&&this._onMouseMove(t.event));var a=n.clientX-this.previousPosition.x,s=n.clientY-this.previousPosition.y;this.rotateCamera(a,s),this.previousPosition={x:n.clientX,y:n.clientY},this.noPreventDefault||n.preventDefault()}}},r.prototype._onMouseMove=function(t){var e=this.camera.getEngine();if(e.isPointerLock&&!e.isInVRExclusivePointerMode){var n=t.movementX||t.mozMovementX||t.webkitMovementX||t.msMovementX||0,i=t.movementY||t.mozMovementY||t.webkitMovementY||t.msMovementY||0;this.rotateCamera(n,i),this.previousPosition=null,this.noPreventDefault||t.preventDefault()}},r.prototype.rotateCamera=function(t,e){var n=this,i=this.camera;this.camera.getScene().useRightHandedSystem&&(t*=-1),i.parent&&i.parent._getWorldMatrixDeterminant()<0&&(t*=-1);var o,a=t/this.angularSensibility,s=e/this.angularSensibility,d=u.b.RotationYawPitchRoll(i.rotation.y,i.rotation.x,i.rotation.z);if(this.buttonsPitch.some(function(P){return P===n.activeButton})&&(o=u.b.RotationAxis(ye.a.X,s),d.multiplyInPlace(o)),this.buttonsYaw.some(function(P){return P===n.activeButton})){o=u.b.RotationAxis(ye.a.Y,a),d.multiplyInPlace(o);var p=i.bankedTurnLimit+i._trackRoll;if(i.bankedTurn&&-p<i.rotation.z&&i.rotation.z<p){var b=i.bankedTurnMultiplier*-a;o=u.b.RotationAxis(ye.a.Z,b),d.multiplyInPlace(o)}}this.buttonsRoll.some(function(P){return P===n.activeButton})&&(o=u.b.RotationAxis(ye.a.Z,-a),i._trackRoll-=a,d.multiplyInPlace(o)),d.toEulerAnglesToRef(i.rotation)},Object(c.c)([Object(L.c)()],r.prototype,"buttons",void 0),Object(c.c)([Object(L.c)()],r.prototype,"angularSensibility",void 0),r}();hn.FlyCameraMouseInput=Qa;var qa=function(){function r(){this.keysHeightOffsetIncr=[38],this.keysHeightOffsetDecr=[40],this.keysHeightOffsetModifierAlt=!1,this.keysHeightOffsetModifierCtrl=!1,this.keysHeightOffsetModifierShift=!1,this.keysRotationOffsetIncr=[37],this.keysRotationOffsetDecr=[39],this.keysRotationOffsetModifierAlt=!1,this.keysRotationOffsetModifierCtrl=!1,this.keysRotationOffsetModifierShift=!1,this.keysRadiusIncr=[40],this.keysRadiusDecr=[38],this.keysRadiusModifierAlt=!0,this.keysRadiusModifierCtrl=!1,this.keysRadiusModifierShift=!1,this.heightSensibility=1,this.rotationSensibility=1,this.radiusSensibility=1,this._keys=new Array}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments),this._onCanvasBlurObserver||(this._scene=this.camera.getScene(),this._engine=this._scene.getEngine(),this._onCanvasBlurObserver=this._engine.onCanvasBlurObservable.add(function(){e._keys=[]}),this._onKeyboardObserver=this._scene.onKeyboardObservable.add(function(n){var i,o=n.event;o.metaKey||(n.type===Zi.a.KEYDOWN?(e._ctrlPressed=o.ctrlKey,e._altPressed=o.altKey,e._shiftPressed=o.shiftKey,(e.keysHeightOffsetIncr.indexOf(o.keyCode)!==-1||e.keysHeightOffsetDecr.indexOf(o.keyCode)!==-1||e.keysRotationOffsetIncr.indexOf(o.keyCode)!==-1||e.keysRotationOffsetDecr.indexOf(o.keyCode)!==-1||e.keysRadiusIncr.indexOf(o.keyCode)!==-1||e.keysRadiusDecr.indexOf(o.keyCode)!==-1)&&((i=e._keys.indexOf(o.keyCode))===-1&&e._keys.push(o.keyCode),o.preventDefault&&(t||o.preventDefault()))):e.keysHeightOffsetIncr.indexOf(o.keyCode)===-1&&e.keysHeightOffsetDecr.indexOf(o.keyCode)===-1&&e.keysRotationOffsetIncr.indexOf(o.keyCode)===-1&&e.keysRotationOffsetDecr.indexOf(o.keyCode)===-1&&e.keysRadiusIncr.indexOf(o.keyCode)===-1&&e.keysRadiusDecr.indexOf(o.keyCode)===-1||((i=e._keys.indexOf(o.keyCode))>=0&&e._keys.splice(i,1),o.preventDefault&&(t||o.preventDefault())))}))},r.prototype.detachControl=function(t){this._scene&&(this._onKeyboardObserver&&this._scene.onKeyboardObservable.remove(this._onKeyboardObserver),this._onCanvasBlurObserver&&this._engine.onCanvasBlurObservable.remove(this._onCanvasBlurObserver),this._onKeyboardObserver=null,this._onCanvasBlurObserver=null),this._keys=[]},r.prototype.checkInputs=function(){var t=this;this._onKeyboardObserver&&this._keys.forEach(function(e){t.keysHeightOffsetIncr.indexOf(e)!==-1&&t._modifierHeightOffset()?t.camera.heightOffset+=t.heightSensibility:t.keysHeightOffsetDecr.indexOf(e)!==-1&&t._modifierHeightOffset()?t.camera.heightOffset-=t.heightSensibility:t.keysRotationOffsetIncr.indexOf(e)!==-1&&t._modifierRotationOffset()?(t.camera.rotationOffset+=t.rotationSensibility,t.camera.rotationOffset%=360):t.keysRotationOffsetDecr.indexOf(e)!==-1&&t._modifierRotationOffset()?(t.camera.rotationOffset-=t.rotationSensibility,t.camera.rotationOffset%=360):t.keysRadiusIncr.indexOf(e)!==-1&&t._modifierRadius()?t.camera.radius+=t.radiusSensibility:t.keysRadiusDecr.indexOf(e)!==-1&&t._modifierRadius()&&(t.camera.radius-=t.radiusSensibility)})},r.prototype.getClassName=function(){return"FollowCameraKeyboardMoveInput"},r.prototype.getSimpleName=function(){return"keyboard"},r.prototype._modifierHeightOffset=function(){return this.keysHeightOffsetModifierAlt===this._altPressed&&this.keysHeightOffsetModifierCtrl===this._ctrlPressed&&this.keysHeightOffsetModifierShift===this._shiftPressed},r.prototype._modifierRotationOffset=function(){return this.keysRotationOffsetModifierAlt===this._altPressed&&this.keysRotationOffsetModifierCtrl===this._ctrlPressed&&this.keysRotationOffsetModifierShift===this._shiftPressed},r.prototype._modifierRadius=function(){return this.keysRadiusModifierAlt===this._altPressed&&this.keysRadiusModifierCtrl===this._ctrlPressed&&this.keysRadiusModifierShift===this._shiftPressed},Object(c.c)([Object(L.c)()],r.prototype,"keysHeightOffsetIncr",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysHeightOffsetDecr",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysHeightOffsetModifierAlt",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysHeightOffsetModifierCtrl",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysHeightOffsetModifierShift",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRotationOffsetIncr",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRotationOffsetDecr",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRotationOffsetModifierAlt",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRotationOffsetModifierCtrl",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRotationOffsetModifierShift",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRadiusIncr",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRadiusDecr",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRadiusModifierAlt",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRadiusModifierCtrl",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRadiusModifierShift",void 0),Object(c.c)([Object(L.c)()],r.prototype,"heightSensibility",void 0),Object(c.c)([Object(L.c)()],r.prototype,"rotationSensibility",void 0),Object(c.c)([Object(L.c)()],r.prototype,"radiusSensibility",void 0),r}();hn.FollowCameraKeyboardMoveInput=qa;var Za=function(){function r(){this.axisControlRadius=!0,this.axisControlHeight=!1,this.axisControlRotation=!1,this.wheelPrecision=3,this.wheelDeltaPercentage=0}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments),this._wheel=function(n,i){if(n.type===Tt.a.POINTERWHEEL){var o=n.event,a=0,s=Math.max(-1,Math.min(1,o.deltaY||o.wheelDelta||-o.detail));e.wheelDeltaPercentage?(console.assert(e.axisControlRadius+e.axisControlHeight+e.axisControlRotation<=1,"wheelDeltaPercentage only usable when mouse wheel controlls ONE axis. Currently enabled: axisControlRadius: "+e.axisControlRadius+", axisControlHeightOffset: "+e.axisControlHeight+", axisControlRotationOffset: "+e.axisControlRotation),e.axisControlRadius?a=.01*s*e.wheelDeltaPercentage*e.camera.radius:e.axisControlHeight?a=.01*s*e.wheelDeltaPercentage*e.camera.heightOffset:e.axisControlRotation&&(a=.01*s*e.wheelDeltaPercentage*e.camera.rotationOffset)):a=s*e.wheelPrecision,a&&(e.axisControlRadius?e.camera.radius+=a:e.axisControlHeight?e.camera.heightOffset-=a:e.axisControlRotation&&(e.camera.rotationOffset-=a)),o.preventDefault&&(t||o.preventDefault())}},this._observer=this.camera.getScene().onPointerObservable.add(this._wheel,Tt.a.POINTERWHEEL)},r.prototype.detachControl=function(t){this._observer&&(this.camera.getScene().onPointerObservable.remove(this._observer),this._observer=null,this._wheel=null)},r.prototype.getClassName=function(){return"ArcRotateCameraMouseWheelInput"},r.prototype.getSimpleName=function(){return"mousewheel"},Object(c.c)([Object(L.c)()],r.prototype,"axisControlRadius",void 0),Object(c.c)([Object(L.c)()],r.prototype,"axisControlHeight",void 0),Object(c.c)([Object(L.c)()],r.prototype,"axisControlRotation",void 0),Object(c.c)([Object(L.c)()],r.prototype,"wheelPrecision",void 0),Object(c.c)([Object(L.c)()],r.prototype,"wheelDeltaPercentage",void 0),r}();hn.FollowCameraMouseWheelInput=Za;var Ja=function(r){function t(){var e=r!==null&&r.apply(this,arguments)||this;return e.angularSensibilityX=1,e.angularSensibilityY=1,e.pinchPrecision=1e4,e.pinchDeltaPercentage=0,e.axisXControlRadius=!1,e.axisXControlHeight=!1,e.axisXControlRotation=!0,e.axisYControlRadius=!1,e.axisYControlHeight=!0,e.axisYControlRotation=!1,e.axisPinchControlRadius=!0,e.axisPinchControlHeight=!1,e.axisPinchControlRotation=!1,e.warningEnable=!0,e._warningCounter=0,e}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"FollowCameraPointersInput"},t.prototype.onTouch=function(e,n,i){this._warning(),this.axisXControlRotation?this.camera.rotationOffset+=n/this.angularSensibilityX:this.axisYControlRotation&&(this.camera.rotationOffset+=i/this.angularSensibilityX),this.axisXControlHeight?this.camera.heightOffset+=n/this.angularSensibilityY:this.axisYControlHeight&&(this.camera.heightOffset+=i/this.angularSensibilityY),this.axisXControlRadius?this.camera.radius-=n/this.angularSensibilityY:this.axisYControlRadius&&(this.camera.radius-=i/this.angularSensibilityY)},t.prototype.onMultiTouch=function(e,n,i,o,a,s){if(!(i===0&&a===null||o===0&&s===null)){var d=(o-i)/(this.pinchPrecision*(this.angularSensibilityX+this.angularSensibilityY)/2);this.pinchDeltaPercentage?(d*=.01*this.pinchDeltaPercentage,this.axisPinchControlRotation&&(this.camera.rotationOffset+=d*this.camera.rotationOffset),this.axisPinchControlHeight&&(this.camera.heightOffset+=d*this.camera.heightOffset),this.axisPinchControlRadius&&(this.camera.radius-=d*this.camera.radius)):(this.axisPinchControlRotation&&(this.camera.rotationOffset+=d),this.axisPinchControlHeight&&(this.camera.heightOffset+=d),this.axisPinchControlRadius&&(this.camera.radius-=d))}},t.prototype._warning=function(){if(this.warningEnable&&this._warningCounter++%100==0){var e="It probably only makes sense to control ONE camera property with each pointer axis. Set 'warningEnable = false' if you are sure. Currently enabled: ";console.assert(this.axisXControlRotation+this.axisXControlHeight+this.axisXControlRadius<=1,e+"axisXControlRotation: "+this.axisXControlRotation+", axisXControlHeight: "+this.axisXControlHeight+", axisXControlRadius: "+this.axisXControlRadius),console.assert(this.axisYControlRotation+this.axisYControlHeight+this.axisYControlRadius<=1,e+"axisYControlRotation: "+this.axisYControlRotation+", axisYControlHeight: "+this.axisYControlHeight+", axisYControlRadius: "+this.axisYControlRadius),console.assert(this.axisPinchControlRotation+this.axisPinchControlHeight+this.axisPinchControlRadius<=1,e+"axisPinchControlRotation: "+this.axisPinchControlRotation+", axisPinchControlHeight: "+this.axisPinchControlHeight+", axisPinchControlRadius: "+this.axisPinchControlRadius)}},Object(c.c)([Object(L.c)()],t.prototype,"angularSensibilityX",void 0),Object(c.c)([Object(L.c)()],t.prototype,"angularSensibilityY",void 0),Object(c.c)([Object(L.c)()],t.prototype,"pinchPrecision",void 0),Object(c.c)([Object(L.c)()],t.prototype,"pinchDeltaPercentage",void 0),Object(c.c)([Object(L.c)()],t.prototype,"axisXControlRadius",void 0),Object(c.c)([Object(L.c)()],t.prototype,"axisXControlHeight",void 0),Object(c.c)([Object(L.c)()],t.prototype,"axisXControlRotation",void 0),Object(c.c)([Object(L.c)()],t.prototype,"axisYControlRadius",void 0),Object(c.c)([Object(L.c)()],t.prototype,"axisYControlHeight",void 0),Object(c.c)([Object(L.c)()],t.prototype,"axisYControlRotation",void 0),Object(c.c)([Object(L.c)()],t.prototype,"axisPinchControlRadius",void 0),Object(c.c)([Object(L.c)()],t.prototype,"axisPinchControlHeight",void 0),Object(c.c)([Object(L.c)()],t.prototype,"axisPinchControlRotation",void 0),t}(yl);hn.FollowCameraPointersInput=Ja;var $a=function(){function r(){this.keysUp=[38],this.keysUpward=[33],this.keysDown=[40],this.keysDownward=[34],this.keysLeft=[37],this.keysRight=[39],this._keys=new Array}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments),this._onCanvasBlurObserver||(this._scene=this.camera.getScene(),this._engine=this._scene.getEngine(),this._onCanvasBlurObserver=this._engine.onCanvasBlurObservable.add(function(){e._keys=[]}),this._onKeyboardObserver=this._scene.onKeyboardObservable.add(function(n){var i,o=n.event;o.metaKey||(n.type===Zi.a.KEYDOWN?e.keysUp.indexOf(o.keyCode)===-1&&e.keysDown.indexOf(o.keyCode)===-1&&e.keysLeft.indexOf(o.keyCode)===-1&&e.keysRight.indexOf(o.keyCode)===-1&&e.keysUpward.indexOf(o.keyCode)===-1&&e.keysDownward.indexOf(o.keyCode)===-1||((i=e._keys.indexOf(o.keyCode))===-1&&e._keys.push(o.keyCode),t||o.preventDefault()):e.keysUp.indexOf(o.keyCode)===-1&&e.keysDown.indexOf(o.keyCode)===-1&&e.keysLeft.indexOf(o.keyCode)===-1&&e.keysRight.indexOf(o.keyCode)===-1&&e.keysUpward.indexOf(o.keyCode)===-1&&e.keysDownward.indexOf(o.keyCode)===-1||((i=e._keys.indexOf(o.keyCode))>=0&&e._keys.splice(i,1),t||o.preventDefault()))}))},r.prototype.detachControl=function(t){this._scene&&(this._onKeyboardObserver&&this._scene.onKeyboardObservable.remove(this._onKeyboardObserver),this._onCanvasBlurObserver&&this._engine.onCanvasBlurObservable.remove(this._onCanvasBlurObserver),this._onKeyboardObserver=null,this._onCanvasBlurObserver=null),this._keys=[]},r.prototype.checkInputs=function(){if(this._onKeyboardObserver)for(var t=this.camera,e=0;e<this._keys.length;e++){var n=this._keys[e],i=t._computeLocalCameraSpeed();this.keysLeft.indexOf(n)!==-1?t._localDirection.copyFromFloats(-i,0,0):this.keysUp.indexOf(n)!==-1?t._localDirection.copyFromFloats(0,0,i):this.keysRight.indexOf(n)!==-1?t._localDirection.copyFromFloats(i,0,0):this.keysDown.indexOf(n)!==-1?t._localDirection.copyFromFloats(0,0,-i):this.keysUpward.indexOf(n)!==-1?t._localDirection.copyFromFloats(0,i,0):this.keysDownward.indexOf(n)!==-1&&t._localDirection.copyFromFloats(0,-i,0),t.getScene().useRightHandedSystem&&(t._localDirection.z*=-1),t.getViewMatrix().invertToRef(t._cameraTransformMatrix),u.e.TransformNormalToRef(t._localDirection,t._cameraTransformMatrix,t._transformedDirection),t.cameraDirection.addInPlace(t._transformedDirection)}},r.prototype.getClassName=function(){return"FreeCameraKeyboardMoveInput"},r.prototype._onLostFocus=function(){this._keys=[]},r.prototype.getSimpleName=function(){return"keyboard"},Object(c.c)([Object(L.c)()],r.prototype,"keysUp",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysUpward",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysDown",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysDownward",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysLeft",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRight",void 0),r}();hn.FreeCameraKeyboardMoveInput=$a;var es=function(){function r(t){t===void 0&&(t=!0),this.touchEnabled=t,this.buttons=[0,1,2],this.angularSensibility=2e3,this.previousPosition=null,this.onPointerMovedObservable=new x.c,this._allowCameraRotation=!0}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments);var n=this.camera.getEngine(),i=n.getInputElement();this._pointerInput||(this._pointerInput=function(o){var a=o.event;if(!n.isInVRExclusivePointerMode&&(e.touchEnabled||a.pointerType!=="touch")&&(o.type===Tt.a.POINTERMOVE||e.buttons.indexOf(a.button)!==-1)){var s=a.srcElement||a.target;if(o.type===Tt.a.POINTERDOWN&&s){try{s.setPointerCapture(a.pointerId)}catch{}e.previousPosition={x:a.clientX,y:a.clientY},t||(a.preventDefault(),i&&i.focus()),n.isPointerLock&&e._onMouseMove&&e._onMouseMove(o.event)}else if(o.type===Tt.a.POINTERUP&&s){try{s.releasePointerCapture(a.pointerId)}catch{}e.previousPosition=null,t||a.preventDefault()}else if(o.type===Tt.a.POINTERMOVE){if(!e.previousPosition)return void(n.isPointerLock&&e._onMouseMove&&e._onMouseMove(o.event));var d=a.clientX-e.previousPosition.x,p=a.clientY-e.previousPosition.y;e.camera.getScene().useRightHandedSystem&&(d*=-1),e.camera.parent&&e.camera.parent._getWorldMatrixDeterminant()<0&&(d*=-1),e._allowCameraRotation&&(e.camera.cameraRotation.y+=d/e.angularSensibility,e.camera.cameraRotation.x+=p/e.angularSensibility),e.onPointerMovedObservable.notifyObservers({offsetX:d,offsetY:p}),e.previousPosition={x:a.clientX,y:a.clientY},t||a.preventDefault()}}}),this._onMouseMove=function(o){if(n.isPointerLock&&!n.isInVRExclusivePointerMode){var a=o.movementX||o.mozMovementX||o.webkitMovementX||o.msMovementX||0;e.camera.getScene().useRightHandedSystem&&(a*=-1),e.camera.parent&&e.camera.parent._getWorldMatrixDeterminant()<0&&(a*=-1),e.camera.cameraRotation.y+=a/e.angularSensibility;var s=o.movementY||o.mozMovementY||o.webkitMovementY||o.msMovementY||0;e.camera.cameraRotation.x+=s/e.angularSensibility,e.previousPosition=null,t||o.preventDefault()}},this._observer=this.camera.getScene().onPointerObservable.add(this._pointerInput,Tt.a.POINTERDOWN|Tt.a.POINTERUP|Tt.a.POINTERMOVE),i&&i.addEventListener("contextmenu",this.onContextMenu.bind(this),!1)},r.prototype.onContextMenu=function(t){t.preventDefault()},r.prototype.detachControl=function(t){if(this._observer){if(this.camera.getScene().onPointerObservable.remove(this._observer),this.onContextMenu){var e=this.camera.getEngine().getInputElement();e&&e.removeEventListener("contextmenu",this.onContextMenu)}this.onPointerMovedObservable&&this.onPointerMovedObservable.clear(),this._observer=null,this._onMouseMove=null,this.previousPosition=null}},r.prototype.getClassName=function(){return"FreeCameraMouseInput"},r.prototype.getSimpleName=function(){return"mouse"},Object(c.c)([Object(L.c)()],r.prototype,"buttons",void 0),Object(c.c)([Object(L.c)()],r.prototype,"angularSensibility",void 0),r}();hn.FreeCameraMouseInput=es;var kt,Uf=function(){function r(){this.wheelPrecisionX=3,this.wheelPrecisionY=3,this.wheelPrecisionZ=3,this.onChangedObservable=new x.c,this._wheelDeltaX=0,this._wheelDeltaY=0,this._wheelDeltaZ=0,this._ffMultiplier=12,this._normalize=120}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments),this._wheel=function(n){if(n.type===Tt.a.POINTERWHEEL){var i=n.event,o=i.deltaMode===WheelEvent.DOM_DELTA_LINE?e._ffMultiplier:1;i.deltaY!==void 0?(e._wheelDeltaX+=e.wheelPrecisionX*o*i.deltaX/e._normalize,e._wheelDeltaY-=e.wheelPrecisionY*o*i.deltaY/e._normalize,e._wheelDeltaZ+=e.wheelPrecisionZ*o*i.deltaZ/e._normalize):i.wheelDeltaY!==void 0?(e._wheelDeltaX+=e.wheelPrecisionX*o*i.wheelDeltaX/e._normalize,e._wheelDeltaY-=e.wheelPrecisionY*o*i.wheelDeltaY/e._normalize,e._wheelDeltaZ+=e.wheelPrecisionZ*o*i.wheelDeltaZ/e._normalize):i.wheelDelta&&(e._wheelDeltaY-=e.wheelPrecisionY*i.wheelDelta/e._normalize),i.preventDefault&&(t||i.preventDefault())}},this._observer=this.camera.getScene().onPointerObservable.add(this._wheel,Tt.a.POINTERWHEEL)},r.prototype.detachControl=function(t){this._observer&&(this.camera.getScene().onPointerObservable.remove(this._observer),this._observer=null,this._wheel=null),this.onChangedObservable&&this.onChangedObservable.clear()},r.prototype.checkInputs=function(){this.onChangedObservable.notifyObservers({wheelDeltaX:this._wheelDeltaX,wheelDeltaY:this._wheelDeltaY,wheelDeltaZ:this._wheelDeltaZ}),this._wheelDeltaX=0,this._wheelDeltaY=0,this._wheelDeltaZ=0},r.prototype.getClassName=function(){return"BaseCameraMouseWheelInput"},r.prototype.getSimpleName=function(){return"mousewheel"},Object(c.c)([Object(L.c)()],r.prototype,"wheelPrecisionX",void 0),Object(c.c)([Object(L.c)()],r.prototype,"wheelPrecisionY",void 0),Object(c.c)([Object(L.c)()],r.prototype,"wheelPrecisionZ",void 0),r}();(function(r){r[r.MoveRelative=0]="MoveRelative",r[r.RotateRelative=1]="RotateRelative",r[r.MoveScene=2]="MoveScene"})(kt||(kt={}));var ts=function(r){function t(){var e=r!==null&&r.apply(this,arguments)||this;return e._moveRelative=u.e.Zero(),e._rotateRelative=u.e.Zero(),e._moveScene=u.e.Zero(),e._wheelXAction=kt.MoveRelative,e._wheelXActionCoordinate=ye.b.X,e._wheelYAction=kt.MoveRelative,e._wheelYActionCoordinate=ye.b.Z,e._wheelZAction=null,e._wheelZActionCoordinate=null,e}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"FreeCameraMouseWheelInput"},Object.defineProperty(t.prototype,"wheelXMoveRelative",{get:function(){return this._wheelXAction!==kt.MoveRelative?null:this._wheelXActionCoordinate},set:function(e){e===null&&this._wheelXAction!==kt.MoveRelative||(this._wheelXAction=kt.MoveRelative,this._wheelXActionCoordinate=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelYMoveRelative",{get:function(){return this._wheelYAction!==kt.MoveRelative?null:this._wheelYActionCoordinate},set:function(e){e===null&&this._wheelYAction!==kt.MoveRelative||(this._wheelYAction=kt.MoveRelative,this._wheelYActionCoordinate=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelZMoveRelative",{get:function(){return this._wheelZAction!==kt.MoveRelative?null:this._wheelZActionCoordinate},set:function(e){e===null&&this._wheelZAction!==kt.MoveRelative||(this._wheelZAction=kt.MoveRelative,this._wheelZActionCoordinate=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelXRotateRelative",{get:function(){return this._wheelXAction!==kt.RotateRelative?null:this._wheelXActionCoordinate},set:function(e){e===null&&this._wheelXAction!==kt.RotateRelative||(this._wheelXAction=kt.RotateRelative,this._wheelXActionCoordinate=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelYRotateRelative",{get:function(){return this._wheelYAction!==kt.RotateRelative?null:this._wheelYActionCoordinate},set:function(e){e===null&&this._wheelYAction!==kt.RotateRelative||(this._wheelYAction=kt.RotateRelative,this._wheelYActionCoordinate=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelZRotateRelative",{get:function(){return this._wheelZAction!==kt.RotateRelative?null:this._wheelZActionCoordinate},set:function(e){e===null&&this._wheelZAction!==kt.RotateRelative||(this._wheelZAction=kt.RotateRelative,this._wheelZActionCoordinate=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelXMoveScene",{get:function(){return this._wheelXAction!==kt.MoveScene?null:this._wheelXActionCoordinate},set:function(e){e===null&&this._wheelXAction!==kt.MoveScene||(this._wheelXAction=kt.MoveScene,this._wheelXActionCoordinate=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelYMoveScene",{get:function(){return this._wheelYAction!==kt.MoveScene?null:this._wheelYActionCoordinate},set:function(e){e===null&&this._wheelYAction!==kt.MoveScene||(this._wheelYAction=kt.MoveScene,this._wheelYActionCoordinate=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelZMoveScene",{get:function(){return this._wheelZAction!==kt.MoveScene?null:this._wheelZActionCoordinate},set:function(e){e===null&&this._wheelZAction!==kt.MoveScene||(this._wheelZAction=kt.MoveScene,this._wheelZActionCoordinate=e)},enumerable:!1,configurable:!0}),t.prototype.checkInputs=function(){if(this._wheelDeltaX!==0||this._wheelDeltaY!==0||this._wheelDeltaZ!=0){this._moveRelative.setAll(0),this._rotateRelative.setAll(0),this._moveScene.setAll(0),this._updateCamera(),this.camera.getScene().useRightHandedSystem&&(this._moveRelative.z*=-1);var e=u.a.Zero();this.camera.getViewMatrix().invertToRef(e);var n=u.e.Zero();u.e.TransformNormalToRef(this._moveRelative,e,n),this.camera.cameraRotation.x+=this._rotateRelative.x/200,this.camera.cameraRotation.y+=this._rotateRelative.y/200,this.camera.cameraDirection.addInPlace(n),this.camera.cameraDirection.addInPlace(this._moveScene),r.prototype.checkInputs.call(this)}},t.prototype._updateCamera=function(){var e=this._moveRelative,n=this._rotateRelative,i=this._moveScene,o=function(a,s,d){if(a!==0&&s!==null&&d!==null){var p=null;switch(s){case kt.MoveRelative:p=e;break;case kt.RotateRelative:p=n;break;case kt.MoveScene:p=i}switch(d){case ye.b.X:p.set(a,0,0);break;case ye.b.Y:p.set(0,a,0);break;case ye.b.Z:p.set(0,0,a)}}};o(this._wheelDeltaX,this._wheelXAction,this._wheelXActionCoordinate),o(this._wheelDeltaY,this._wheelYAction,this._wheelYActionCoordinate),o(this._wheelDeltaZ,this._wheelZAction,this._wheelZActionCoordinate)},Object(c.c)([Object(L.c)()],t.prototype,"wheelXMoveRelative",null),Object(c.c)([Object(L.c)()],t.prototype,"wheelYMoveRelative",null),Object(c.c)([Object(L.c)()],t.prototype,"wheelZMoveRelative",null),Object(c.c)([Object(L.c)()],t.prototype,"wheelXRotateRelative",null),Object(c.c)([Object(L.c)()],t.prototype,"wheelYRotateRelative",null),Object(c.c)([Object(L.c)()],t.prototype,"wheelZRotateRelative",null),Object(c.c)([Object(L.c)()],t.prototype,"wheelXMoveScene",null),Object(c.c)([Object(L.c)()],t.prototype,"wheelYMoveScene",null),Object(c.c)([Object(L.c)()],t.prototype,"wheelZMoveScene",null),t}(Uf);hn.FreeCameraMouseWheelInput=ts;var ns=function(){function r(t){t===void 0&&(t=!1),this.allowMouse=t,this.touchAngularSensibility=2e5,this.touchMoveSensibility=250,this._offsetX=null,this._offsetY=null,this._pointerPressed=new Array}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments);var n=null;if(this._pointerInput===void 0&&(this._onLostFocus=function(){e._offsetX=null,e._offsetY=null},this._pointerInput=function(a){var s=a.event,d=!e.camera.getEngine().hostInformation.isMobile&&s instanceof MouseEvent;if(e.allowMouse||s.pointerType!=="mouse"&&!d){if(a.type===Tt.a.POINTERDOWN){if(t||s.preventDefault(),e._pointerPressed.push(s.pointerId),e._pointerPressed.length!==1)return;n={x:s.clientX,y:s.clientY}}else if(a.type===Tt.a.POINTERUP){if(t||s.preventDefault(),(p=e._pointerPressed.indexOf(s.pointerId))===-1||(e._pointerPressed.splice(p,1),p!=0))return;n=null,e._offsetX=null,e._offsetY=null}else if(a.type===Tt.a.POINTERMOVE){if(t||s.preventDefault(),!n)return;var p;if((p=e._pointerPressed.indexOf(s.pointerId))!=0)return;e._offsetX=s.clientX-n.x,e._offsetY=-(s.clientY-n.y)}}}),this._observer=this.camera.getScene().onPointerObservable.add(this._pointerInput,Tt.a.POINTERDOWN|Tt.a.POINTERUP|Tt.a.POINTERMOVE),this._onLostFocus){var i=this.camera.getEngine(),o=i.getInputElement();o&&o.addEventListener("blur",this._onLostFocus)}},r.prototype.detachControl=function(t){if(this._pointerInput){if(this._observer&&(this.camera.getScene().onPointerObservable.remove(this._observer),this._observer=null),this._onLostFocus){var e=this.camera.getEngine().getInputElement();e&&e.removeEventListener("blur",this._onLostFocus),this._onLostFocus=null}this._pointerPressed=[],this._offsetX=null,this._offsetY=null}},r.prototype.checkInputs=function(){if(this._offsetX!==null&&this._offsetY!==null&&(this._offsetX!==0||this._offsetY!==0)){var t=this.camera;if(t.cameraRotation.y=this._offsetX/this.touchAngularSensibility,this._pointerPressed.length>1)t.cameraRotation.x=-this._offsetY/this.touchAngularSensibility;else{var e=t._computeLocalCameraSpeed(),n=new u.e(0,0,e*this._offsetY/this.touchMoveSensibility);u.a.RotationYawPitchRollToRef(t.rotation.y,t.rotation.x,0,t._cameraRotationMatrix),t.cameraDirection.addInPlace(u.e.TransformCoordinates(n,t._cameraRotationMatrix))}}},r.prototype.getClassName=function(){return"FreeCameraTouchInput"},r.prototype.getSimpleName=function(){return"touch"},Object(c.c)([Object(L.c)()],r.prototype,"touchAngularSensibility",void 0),Object(c.c)([Object(L.c)()],r.prototype,"touchMoveSensibility",void 0),r}();hn.FreeCameraTouchInput=ns;var eo=function(r){function t(e){var n=r.call(this,e)||this;return n._mouseInput=null,n._mouseWheelInput=null,n}return Object(c.d)(t,r),t.prototype.addKeyboard=function(){return this.add(new $a),this},t.prototype.addMouse=function(e){return e===void 0&&(e=!0),this._mouseInput||(this._mouseInput=new es(e),this.add(this._mouseInput)),this},t.prototype.removeMouse=function(){return this._mouseInput&&this.remove(this._mouseInput),this},t.prototype.addMouseWheel=function(){return this._mouseWheelInput||(this._mouseWheelInput=new ts,this.add(this._mouseWheelInput)),this},t.prototype.removeMouseWheel=function(){return this._mouseWheelInput&&this.remove(this._mouseWheelInput),this},t.prototype.addTouch=function(){return this.add(new ns),this},t.prototype.clear=function(){r.prototype.clear.call(this),this._mouseInput=null},t}($r);eo.prototype.addDeviceOrientation=function(){return this._deviceOrientationInput||(this._deviceOrientationInput=new is,this.add(this._deviceOrientationInput)),this};var is=function(){function r(){var t=this;this._screenOrientationAngle=0,this._screenQuaternion=new u.b,this._alpha=0,this._beta=0,this._gamma=0,this._onDeviceOrientationChangedObservable=new x.c,this._orientationChanged=function(){t._screenOrientationAngle=window.orientation!==void 0?+window.orientation:window.screen.orientation&&window.screen.orientation.angle?window.screen.orientation.angle:0,t._screenOrientationAngle=-Xe.b.ToRadians(t._screenOrientationAngle/2),t._screenQuaternion.copyFromFloats(0,Math.sin(t._screenOrientationAngle),0,Math.cos(t._screenOrientationAngle))},this._deviceOrientation=function(e){t._alpha=e.alpha!==null?e.alpha:0,t._beta=e.beta!==null?e.beta:0,t._gamma=e.gamma!==null?e.gamma:0,e.alpha!==null&&t._onDeviceOrientationChangedObservable.notifyObservers()},this._constantTranform=new u.b(-Math.sqrt(.5),0,0,Math.sqrt(.5)),this._orientationChanged()}return r.WaitForOrientationChangeAsync=function(t){return new Promise(function(e,n){var i=!1,o=function(){window.removeEventListener("deviceorientation",o),i=!0,e()};t&&setTimeout(function(){i||(window.removeEventListener("deviceorientation",o),n("WaitForOrientationChangeAsync timed out"))},t),typeof DeviceOrientationEvent<"u"&&typeof DeviceOrientationEvent.requestPermission=="function"?DeviceOrientationEvent.requestPermission().then(function(a){a=="granted"?window.addEventListener("deviceorientation",o):Xe.b.Warn("Permission not granted.")}).catch(function(a){Xe.b.Error(a)}):window.addEventListener("deviceorientation",o)})},Object.defineProperty(r.prototype,"camera",{get:function(){return this._camera},set:function(t){var e=this;this._camera=t,this._camera==null||this._camera.rotationQuaternion||(this._camera.rotationQuaternion=new u.b),this._camera&&this._camera.onDisposeObservable.add(function(){e._onDeviceOrientationChangedObservable.clear()})},enumerable:!1,configurable:!0}),r.prototype.attachControl=function(){var t=this,e=this.camera.getScene().getEngine().getHostWindow();if(e){var n=function(){e.addEventListener("orientationchange",t._orientationChanged),e.addEventListener("deviceorientation",t._deviceOrientation),t._orientationChanged()};typeof DeviceOrientationEvent<"u"&&typeof DeviceOrientationEvent.requestPermission=="function"?DeviceOrientationEvent.requestPermission().then(function(i){i==="granted"?n():Xe.b.Warn("Permission not granted.")}).catch(function(i){Xe.b.Error(i)}):n()}},r.prototype.detachControl=function(t){window.removeEventListener("orientationchange",this._orientationChanged),window.removeEventListener("deviceorientation",this._deviceOrientation),this._alpha=0},r.prototype.checkInputs=function(){this._alpha&&(u.b.RotationYawPitchRollToRef(Xe.b.ToRadians(this._alpha),Xe.b.ToRadians(this._beta),-Xe.b.ToRadians(this._gamma),this.camera.rotationQuaternion),this._camera.rotationQuaternion.multiplyInPlace(this._screenQuaternion),this._camera.rotationQuaternion.multiplyInPlace(this._constantTranform),this._camera.rotationQuaternion.z*=-1,this._camera.rotationQuaternion.w*=-1)},r.prototype.getClassName=function(){return"FreeCameraDeviceOrientationInput"},r.prototype.getSimpleName=function(){return"deviceOrientation"},r}();hn.FreeCameraDeviceOrientationInput=is;var rs=function(){function r(){this.gamepadAngularSensibility=200,this.gamepadMoveSensibility=40,this._yAxisScale=1,this._cameraTransform=u.a.Identity(),this._deltaTransform=u.e.Zero(),this._vector3=u.e.Zero(),this._vector2=u.d.Zero()}return Object.defineProperty(r.prototype,"invertYAxis",{get:function(){return this._yAxisScale!==1},set:function(t){this._yAxisScale=t?-1:1},enumerable:!1,configurable:!0}),r.prototype.attachControl=function(){var t=this,e=this.camera.getScene().gamepadManager;this._onGamepadConnectedObserver=e.onGamepadConnectedObservable.add(function(n){n.type!==dn.POSE_ENABLED&&(t.gamepad&&n.type!==dn.XBOX||(t.gamepad=n))}),this._onGamepadDisconnectedObserver=e.onGamepadDisconnectedObservable.add(function(n){t.gamepad===n&&(t.gamepad=null)}),this.gamepad=e.getGamepadByType(dn.XBOX),!this.gamepad&&e.gamepads.length&&(this.gamepad=e.gamepads[0])},r.prototype.detachControl=function(t){this.camera.getScene().gamepadManager.onGamepadConnectedObservable.remove(this._onGamepadConnectedObserver),this.camera.getScene().gamepadManager.onGamepadDisconnectedObservable.remove(this._onGamepadDisconnectedObserver),this.gamepad=null},r.prototype.checkInputs=function(){if(this.gamepad&&this.gamepad.leftStick){var t=this.camera,e=this.gamepad.leftStick,n=e.x/this.gamepadMoveSensibility,i=e.y/this.gamepadMoveSensibility;e.x=Math.abs(n)>.005?0+n:0,e.y=Math.abs(i)>.005?0+i:0;var o=this.gamepad.rightStick;if(o){var a=o.x/this.gamepadAngularSensibility,s=o.y/this.gamepadAngularSensibility*this._yAxisScale;o.x=Math.abs(a)>.001?0+a:0,o.y=Math.abs(s)>.001?0+s:0}else o={x:0,y:0};t.rotationQuaternion?t.rotationQuaternion.toRotationMatrix(this._cameraTransform):u.a.RotationYawPitchRollToRef(t.rotation.y,t.rotation.x,0,this._cameraTransform);var d=50*t._computeLocalCameraSpeed();this._vector3.copyFromFloats(e.x*d,0,-e.y*d),u.e.TransformCoordinatesToRef(this._vector3,this._cameraTransform,this._deltaTransform),t.cameraDirection.addInPlace(this._deltaTransform),this._vector2.copyFromFloats(o.y,o.x),t.cameraRotation.addInPlace(this._vector2)}},r.prototype.getClassName=function(){return"FreeCameraGamepadInput"},r.prototype.getSimpleName=function(){return"gamepad"},Object(c.c)([Object(L.c)()],r.prototype,"gamepadAngularSensibility",void 0),Object(c.c)([Object(L.c)()],r.prototype,"gamepadMoveSensibility",void 0),r}();hn.FreeCameraGamepadInput=rs;var an,Tl=f(112);(function(r){r[r.X=0]="X",r[r.Y=1]="Y",r[r.Z=2]="Z"})(an||(an={}));var os=function(){function r(t,e){var n=this,i=Object(c.a)(Object(c.a)({},r._GetDefaultOptions()),e);if(this._leftJoystick=!!t,r._globalJoystickIndex++,this._axisTargetedByLeftAndRight=an.X,this._axisTargetedByUpAndDown=an.Y,this.reverseLeftRight=!1,this.reverseUpDown=!1,this._touches=new Tl.a,this.deltaPosition=u.e.Zero(),this._joystickSensibility=25,this._inversedSensibility=1/(this._joystickSensibility/1e3),this._onResize=function(a){r.vjCanvasWidth=window.innerWidth,r.vjCanvasHeight=window.innerHeight,r.Canvas&&(r.Canvas.width=r.vjCanvasWidth,r.Canvas.height=r.vjCanvasHeight),r.halfWidth=r.vjCanvasWidth/2},!r.Canvas){window.addEventListener("resize",this._onResize,!1),r.Canvas=document.createElement("canvas"),r.vjCanvasWidth=window.innerWidth,r.vjCanvasHeight=window.innerHeight,r.Canvas.width=window.innerWidth,r.Canvas.height=window.innerHeight,r.Canvas.style.width="100%",r.Canvas.style.height="100%",r.Canvas.style.position="absolute",r.Canvas.style.backgroundColor="transparent",r.Canvas.style.top="0px",r.Canvas.style.left="0px",r.Canvas.style.zIndex="5",r.Canvas.style.msTouchAction="none",r.Canvas.style.touchAction="none",r.Canvas.setAttribute("touch-action","none");var o=r.Canvas.getContext("2d");if(!o)throw new Error("Unable to create canvas for virtual joystick");r.vjCanvasContext=o,r.vjCanvasContext.strokeStyle="#ffffff",r.vjCanvasContext.lineWidth=2,document.body.appendChild(r.Canvas)}r.halfWidth=r.Canvas.width/2,this.pressed=!1,this.limitToContainer=i.limitToContainer,this._joystickColor=i.color,this.containerSize=i.containerSize,this.puckSize=i.puckSize,i.position&&this.setPosition(i.position.x,i.position.y),i.puckImage&&this.setPuckImage(i.puckImage),i.containerImage&&this.setContainerImage(i.containerImage),i.alwaysVisible&&r._alwaysVisibleSticks++,this.alwaysVisible=i.alwaysVisible,this._joystickPointerID=-1,this._joystickPointerPos=new u.d(0,0),this._joystickPreviousPointerPos=new u.d(0,0),this._joystickPointerStartPos=new u.d(0,0),this._deltaJoystickVector=new u.d(0,0),this._onPointerDownHandlerRef=function(a){n._onPointerDown(a)},this._onPointerMoveHandlerRef=function(a){n._onPointerMove(a)},this._onPointerUpHandlerRef=function(a){n._onPointerUp(a)},r.Canvas.addEventListener("pointerdown",this._onPointerDownHandlerRef,!1),r.Canvas.addEventListener("pointermove",this._onPointerMoveHandlerRef,!1),r.Canvas.addEventListener("pointerup",this._onPointerUpHandlerRef,!1),r.Canvas.addEventListener("pointerout",this._onPointerUpHandlerRef,!1),r.Canvas.addEventListener("contextmenu",function(a){a.preventDefault()},!1),requestAnimationFrame(function(){n._drawVirtualJoystick()})}return r._GetDefaultOptions=function(){return{puckSize:40,containerSize:60,color:"cyan",puckImage:void 0,containerImage:void 0,position:void 0,alwaysVisible:!1,limitToContainer:!1}},r.prototype.setJoystickSensibility=function(t){this._joystickSensibility=t,this._inversedSensibility=1/(this._joystickSensibility/1e3)},r.prototype._onPointerDown=function(t){t.preventDefault(),(this._leftJoystick===!0?t.clientX<r.halfWidth:t.clientX>r.halfWidth)&&this._joystickPointerID<0?(this._joystickPointerID=t.pointerId,this._joystickPosition?(this._joystickPointerStartPos=this._joystickPosition.clone(),this._joystickPointerPos=this._joystickPosition.clone(),this._joystickPreviousPointerPos=this._joystickPosition.clone(),this._onPointerMove(t)):(this._joystickPointerStartPos.x=t.clientX,this._joystickPointerStartPos.y=t.clientY,this._joystickPointerPos=this._joystickPointerStartPos.clone(),this._joystickPreviousPointerPos=this._joystickPointerStartPos.clone()),this._deltaJoystickVector.x=0,this._deltaJoystickVector.y=0,this.pressed=!0,this._touches.add(t.pointerId.toString(),t)):r._globalJoystickIndex<2&&this._action&&(this._action(),this._touches.add(t.pointerId.toString(),{x:t.clientX,y:t.clientY,prevX:t.clientX,prevY:t.clientY}))},r.prototype._onPointerMove=function(t){if(this._joystickPointerID==t.pointerId){if(this.limitToContainer){var e=new u.d(t.clientX-this._joystickPointerStartPos.x,t.clientY-this._joystickPointerStartPos.y),n=e.length();n>this.containerSize&&e.scaleInPlace(this.containerSize/n),this._joystickPointerPos.x=this._joystickPointerStartPos.x+e.x,this._joystickPointerPos.y=this._joystickPointerStartPos.y+e.y}else this._joystickPointerPos.x=t.clientX,this._joystickPointerPos.y=t.clientY;this._deltaJoystickVector=this._joystickPointerPos.clone(),this._deltaJoystickVector=this._deltaJoystickVector.subtract(this._joystickPointerStartPos),0<r._alwaysVisibleSticks&&(this._leftJoystick?this._joystickPointerPos.x=Math.min(r.halfWidth,this._joystickPointerPos.x):this._joystickPointerPos.x=Math.max(r.halfWidth,this._joystickPointerPos.x));var i=(this.reverseLeftRight?-1:1)*this._deltaJoystickVector.x/this._inversedSensibility;switch(this._axisTargetedByLeftAndRight){case an.X:this.deltaPosition.x=Math.min(1,Math.max(-1,i));break;case an.Y:this.deltaPosition.y=Math.min(1,Math.max(-1,i));break;case an.Z:this.deltaPosition.z=Math.min(1,Math.max(-1,i))}var o=(this.reverseUpDown?1:-1)*this._deltaJoystickVector.y/this._inversedSensibility;switch(this._axisTargetedByUpAndDown){case an.X:this.deltaPosition.x=Math.min(1,Math.max(-1,o));break;case an.Y:this.deltaPosition.y=Math.min(1,Math.max(-1,o));break;case an.Z:this.deltaPosition.z=Math.min(1,Math.max(-1,o))}}else{var a=this._touches.get(t.pointerId.toString());a&&(a.x=t.clientX,a.y=t.clientY)}},r.prototype._onPointerUp=function(t){if(this._joystickPointerID==t.pointerId)this._clearPreviousDraw(),this._joystickPointerID=-1,this.pressed=!1;else{var e=this._touches.get(t.pointerId.toString());e&&r.vjCanvasContext.clearRect(e.prevX-44,e.prevY-44,88,88)}this._deltaJoystickVector.x=0,this._deltaJoystickVector.y=0,this._touches.remove(t.pointerId.toString())},r.prototype.setJoystickColor=function(t){this._joystickColor=t},Object.defineProperty(r.prototype,"containerSize",{get:function(){return this._joystickContainerSize},set:function(t){this._joystickContainerSize=t,this._clearContainerSize=~~(2.1*this._joystickContainerSize),this._clearContainerSizeOffset=~~(this._clearContainerSize/2)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"puckSize",{get:function(){return this._joystickPuckSize},set:function(t){this._joystickPuckSize=t,this._clearPuckSize=~~(2.1*this._joystickPuckSize),this._clearPuckSizeOffset=~~(this._clearPuckSize/2)},enumerable:!1,configurable:!0}),r.prototype.clearPosition=function(){this.alwaysVisible=!1,this._joystickPosition=null},Object.defineProperty(r.prototype,"alwaysVisible",{get:function(){return this._alwaysVisible},set:function(t){this._alwaysVisible!==t&&(t&&this._joystickPosition?(r._alwaysVisibleSticks++,this._alwaysVisible=!0):(r._alwaysVisibleSticks--,this._alwaysVisible=!1))},enumerable:!1,configurable:!0}),r.prototype.setPosition=function(t,e){this._joystickPointerStartPos&&this._clearPreviousDraw(),this._joystickPosition=new u.d(t,e)},r.prototype.setActionOnTouch=function(t){this._action=t},r.prototype.setAxisForLeftRight=function(t){switch(t){case an.X:case an.Y:case an.Z:this._axisTargetedByLeftAndRight=t;break;default:this._axisTargetedByLeftAndRight=an.X}},r.prototype.setAxisForUpDown=function(t){switch(t){case an.X:case an.Y:case an.Z:this._axisTargetedByUpAndDown=t;break;default:this._axisTargetedByUpAndDown=an.Y}},r.prototype._clearPreviousDraw=function(){var t=this._joystickPosition||this._joystickPointerStartPos;r.vjCanvasContext.clearRect(t.x-this._clearContainerSizeOffset,t.y-this._clearContainerSizeOffset,this._clearContainerSize,this._clearContainerSize),r.vjCanvasContext.clearRect(this._joystickPreviousPointerPos.x-this._clearPuckSizeOffset,this._joystickPreviousPointerPos.y-this._clearPuckSizeOffset,this._clearPuckSize,this._clearPuckSize)},r.prototype.setContainerImage=function(t){var e=this,n=new Image;n.src=t,n.onload=function(){return e._containerImage=n}},r.prototype.setPuckImage=function(t){var e=this,n=new Image;n.src=t,n.onload=function(){return e._puckImage=n}},r.prototype._drawContainer=function(){var t=this._joystickPosition||this._joystickPointerStartPos;this._clearPreviousDraw(),this._containerImage?r.vjCanvasContext.drawImage(this._containerImage,t.x-this.containerSize,t.y-this.containerSize,2*this.containerSize,2*this.containerSize):(r.vjCanvasContext.beginPath(),r.vjCanvasContext.strokeStyle=this._joystickColor,r.vjCanvasContext.lineWidth=2,r.vjCanvasContext.arc(t.x,t.y,this.containerSize,0,2*Math.PI,!0),r.vjCanvasContext.stroke(),r.vjCanvasContext.closePath(),r.vjCanvasContext.beginPath(),r.vjCanvasContext.lineWidth=6,r.vjCanvasContext.strokeStyle=this._joystickColor,r.vjCanvasContext.arc(t.x,t.y,this.puckSize,0,2*Math.PI,!0),r.vjCanvasContext.stroke(),r.vjCanvasContext.closePath())},r.prototype._drawPuck=function(){this._puckImage?r.vjCanvasContext.drawImage(this._puckImage,this._joystickPointerPos.x-this.puckSize,this._joystickPointerPos.y-this.puckSize,2*this.puckSize,2*this.puckSize):(r.vjCanvasContext.beginPath(),r.vjCanvasContext.strokeStyle=this._joystickColor,r.vjCanvasContext.lineWidth=2,r.vjCanvasContext.arc(this._joystickPointerPos.x,this._joystickPointerPos.y,this.puckSize,0,2*Math.PI,!0),r.vjCanvasContext.stroke(),r.vjCanvasContext.closePath())},r.prototype._drawVirtualJoystick=function(){var t=this;this.alwaysVisible&&this._drawContainer(),this.pressed&&this._touches.forEach(function(e,n){n.pointerId===t._joystickPointerID?(t.alwaysVisible||t._drawContainer(),t._drawPuck(),t._joystickPreviousPointerPos=t._joystickPointerPos.clone()):(r.vjCanvasContext.clearRect(n.prevX-44,n.prevY-44,88,88),r.vjCanvasContext.beginPath(),r.vjCanvasContext.fillStyle="white",r.vjCanvasContext.beginPath(),r.vjCanvasContext.strokeStyle="red",r.vjCanvasContext.lineWidth=6,r.vjCanvasContext.arc(n.x,n.y,40,0,2*Math.PI,!0),r.vjCanvasContext.stroke(),r.vjCanvasContext.closePath(),n.prevX=n.x,n.prevY=n.y)}),requestAnimationFrame(function(){t._drawVirtualJoystick()})},r.prototype.releaseCanvas=function(){r.Canvas&&(r.Canvas.removeEventListener("pointerdown",this._onPointerDownHandlerRef),r.Canvas.removeEventListener("pointermove",this._onPointerMoveHandlerRef),r.Canvas.removeEventListener("pointerup",this._onPointerUpHandlerRef),r.Canvas.removeEventListener("pointerout",this._onPointerUpHandlerRef),window.removeEventListener("resize",this._onResize),document.body.removeChild(r.Canvas),r.Canvas=null)},r._globalJoystickIndex=0,r._alwaysVisibleSticks=0,r}();eo.prototype.addVirtualJoystick=function(){return this.add(new as),this};var as=function(){function r(){}return r.prototype.getLeftJoystick=function(){return this._leftjoystick},r.prototype.getRightJoystick=function(){return this._rightjoystick},r.prototype.checkInputs=function(){if(this._leftjoystick){var t=this.camera,e=50*t._computeLocalCameraSpeed(),n=u.a.RotationYawPitchRoll(t.rotation.y,t.rotation.x,0),i=u.e.TransformCoordinates(new u.e(this._leftjoystick.deltaPosition.x*e,this._leftjoystick.deltaPosition.y*e,this._leftjoystick.deltaPosition.z*e),n);t.cameraDirection=t.cameraDirection.add(i),t.cameraRotation=t.cameraRotation.addVector3(this._rightjoystick.deltaPosition),this._leftjoystick.pressed||(this._leftjoystick.deltaPosition=this._leftjoystick.deltaPosition.scale(.9)),this._rightjoystick.pressed||(this._rightjoystick.deltaPosition=this._rightjoystick.deltaPosition.scale(.9))}},r.prototype.attachControl=function(){this._leftjoystick=new os(!0),this._leftjoystick.setAxisForUpDown(an.Z),this._leftjoystick.setAxisForLeftRight(an.X),this._leftjoystick.setJoystickSensibility(.15),this._rightjoystick=new os(!1),this._rightjoystick.setAxisForUpDown(an.X),this._rightjoystick.setAxisForLeftRight(an.Y),this._rightjoystick.reverseUpDown=!0,this._rightjoystick.setJoystickSensibility(.05),this._rightjoystick.setJoystickColor("yellow")},r.prototype.detachControl=function(t){this._leftjoystick.releaseCanvas(),this._rightjoystick.releaseCanvas()},r.prototype.getClassName=function(){return"FreeCameraVirtualJoystickInput"},r.prototype.getSimpleName=function(){return"virtualJoystick"},r}();hn.FreeCameraVirtualJoystickInput=as;var Gt=f(28),Ni=function(r){function t(e,n,i,o){o===void 0&&(o=!0);var a=r.call(this,e,n,i,o)||this;return a._tmpUpVector=u.e.Zero(),a._tmpTargetVector=u.e.Zero(),a.cameraDirection=new u.e(0,0,0),a.cameraRotation=new u.d(0,0),a.ignoreParentScaling=!1,a.updateUpVectorFromRotation=!1,a._tmpQuaternion=new u.b,a.rotation=new u.e(0,0,0),a.speed=2,a.noRotationConstraint=!1,a.invertRotation=!1,a.inverseRotationSpeed=.2,a.lockedTarget=null,a._currentTarget=u.e.Zero(),a._initialFocalDistance=1,a._viewMatrix=u.a.Zero(),a._camMatrix=u.a.Zero(),a._cameraTransformMatrix=u.a.Zero(),a._cameraRotationMatrix=u.a.Zero(),a._referencePoint=new u.e(0,0,1),a._transformedReferencePoint=u.e.Zero(),a._defaultUp=u.e.Up(),a._cachedRotationZ=0,a._cachedQuaternionRotationZ=0,a}return Object(c.d)(t,r),t.prototype.getFrontPosition=function(e){this.getWorldMatrix();var n=this.getTarget().subtract(this.position);return n.normalize(),n.scaleInPlace(e),this.globalPosition.add(n)},t.prototype._getLockedTargetPosition=function(){return this.lockedTarget?(this.lockedTarget.absolutePosition&&this.lockedTarget.computeWorldMatrix(),this.lockedTarget.absolutePosition||this.lockedTarget):null},t.prototype.storeState=function(){return this._storedPosition=this.position.clone(),this._storedRotation=this.rotation.clone(),this.rotationQuaternion&&(this._storedRotationQuaternion=this.rotationQuaternion.clone()),r.prototype.storeState.call(this)},t.prototype._restoreStateValues=function(){return!!r.prototype._restoreStateValues.call(this)&&(this.position=this._storedPosition.clone(),this.rotation=this._storedRotation.clone(),this.rotationQuaternion&&(this.rotationQuaternion=this._storedRotationQuaternion.clone()),this.cameraDirection.copyFromFloats(0,0,0),this.cameraRotation.copyFromFloats(0,0),!0)},t.prototype._initCache=function(){r.prototype._initCache.call(this),this._cache.lockedTarget=new u.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),this._cache.rotation=new u.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),this._cache.rotationQuaternion=new u.b(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE)},t.prototype._updateCache=function(e){e||r.prototype._updateCache.call(this);var n=this._getLockedTargetPosition();n?this._cache.lockedTarget?this._cache.lockedTarget.copyFrom(n):this._cache.lockedTarget=n.clone():this._cache.lockedTarget=null,this._cache.rotation.copyFrom(this.rotation),this.rotationQuaternion&&this._cache.rotationQuaternion.copyFrom(this.rotationQuaternion)},t.prototype._isSynchronizedViewMatrix=function(){if(!r.prototype._isSynchronizedViewMatrix.call(this))return!1;var e=this._getLockedTargetPosition();return(this._cache.lockedTarget?this._cache.lockedTarget.equals(e):!e)&&(this.rotationQuaternion?this.rotationQuaternion.equals(this._cache.rotationQuaternion):this._cache.rotation.equals(this.rotation))},t.prototype._computeLocalCameraSpeed=function(){var e=this.getEngine();return this.speed*Math.sqrt(e.getDeltaTime()/(100*e.getFps()))},t.prototype.setTarget=function(e){this.upVector.normalize(),this._initialFocalDistance=e.subtract(this.position).length(),this.position.z===e.z&&(this.position.z+=Gt.a),this._referencePoint.normalize().scaleInPlace(this._initialFocalDistance),u.a.LookAtLHToRef(this.position,e,this._defaultUp,this._camMatrix),this._camMatrix.invert(),this.rotation.x=Math.atan(this._camMatrix.m[6]/this._camMatrix.m[10]);var n=e.subtract(this.position);n.x>=0?this.rotation.y=-Math.atan(n.z/n.x)+Math.PI/2:this.rotation.y=-Math.atan(n.z/n.x)-Math.PI/2,this.rotation.z=0,isNaN(this.rotation.x)&&(this.rotation.x=0),isNaN(this.rotation.y)&&(this.rotation.y=0),isNaN(this.rotation.z)&&(this.rotation.z=0),this.rotationQuaternion&&u.b.RotationYawPitchRollToRef(this.rotation.y,this.rotation.x,this.rotation.z,this.rotationQuaternion)},Object.defineProperty(t.prototype,"target",{get:function(){return this.getTarget()},set:function(e){this.setTarget(e)},enumerable:!1,configurable:!0}),t.prototype.getTarget=function(){return this._currentTarget},t.prototype._decideIfNeedsToMove=function(){return Math.abs(this.cameraDirection.x)>0||Math.abs(this.cameraDirection.y)>0||Math.abs(this.cameraDirection.z)>0},t.prototype._updatePosition=function(){if(this.parent)return this.parent.getWorldMatrix().invertToRef(u.c.Matrix[0]),u.e.TransformNormalToRef(this.cameraDirection,u.c.Matrix[0],u.c.Vector3[0]),void this.position.addInPlace(u.c.Vector3[0]);this.position.addInPlace(this.cameraDirection)},t.prototype._checkInputs=function(){var e=this.invertRotation?-this.inverseRotationSpeed:1,n=this._decideIfNeedsToMove(),i=Math.abs(this.cameraRotation.x)>0||Math.abs(this.cameraRotation.y)>0;n&&this._updatePosition(),i&&(this.rotationQuaternion&&this.rotationQuaternion.toEulerAnglesToRef(this.rotation),this.rotation.x+=this.cameraRotation.x*e,this.rotation.y+=this.cameraRotation.y*e,!this.noRotationConstraint&&(this.rotation.x>1.570796&&(this.rotation.x=1.570796),this.rotation.x<-1.570796&&(this.rotation.x=-1.570796)),this.rotationQuaternion&&this.rotation.lengthSquared()&&u.b.RotationYawPitchRollToRef(this.rotation.y,this.rotation.x,this.rotation.z,this.rotationQuaternion)),n&&(Math.abs(this.cameraDirection.x)<this.speed*Gt.a&&(this.cameraDirection.x=0),Math.abs(this.cameraDirection.y)<this.speed*Gt.a&&(this.cameraDirection.y=0),Math.abs(this.cameraDirection.z)<this.speed*Gt.a&&(this.cameraDirection.z=0),this.cameraDirection.scaleInPlace(this.inertia)),i&&(Math.abs(this.cameraRotation.x)<this.speed*Gt.a&&(this.cameraRotation.x=0),Math.abs(this.cameraRotation.y)<this.speed*Gt.a&&(this.cameraRotation.y=0),this.cameraRotation.scaleInPlace(this.inertia)),r.prototype._checkInputs.call(this)},t.prototype._updateCameraRotationMatrix=function(){this.rotationQuaternion?this.rotationQuaternion.toRotationMatrix(this._cameraRotationMatrix):u.a.RotationYawPitchRollToRef(this.rotation.y,this.rotation.x,this.rotation.z,this._cameraRotationMatrix)},t.prototype._rotateUpVectorWithCameraRotationMatrix=function(){return u.e.TransformNormalToRef(this._defaultUp,this._cameraRotationMatrix,this.upVector),this},t.prototype._getViewMatrix=function(){return this.lockedTarget&&this.setTarget(this._getLockedTargetPosition()),this._updateCameraRotationMatrix(),this.rotationQuaternion&&this._cachedQuaternionRotationZ!=this.rotationQuaternion.z?(this._rotateUpVectorWithCameraRotationMatrix(),this._cachedQuaternionRotationZ=this.rotationQuaternion.z):this._cachedRotationZ!=this.rotation.z&&(this._rotateUpVectorWithCameraRotationMatrix(),this._cachedRotationZ=this.rotation.z),u.e.TransformCoordinatesToRef(this._referencePoint,this._cameraRotationMatrix,this._transformedReferencePoint),this.position.addToRef(this._transformedReferencePoint,this._currentTarget),this.updateUpVectorFromRotation&&(this.rotationQuaternion?ye.a.Y.rotateByQuaternionToRef(this.rotationQuaternion,this.upVector):(u.b.FromEulerVectorToRef(this.rotation,this._tmpQuaternion),ye.a.Y.rotateByQuaternionToRef(this._tmpQuaternion,this.upVector))),this._computeViewMatrix(this.position,this._currentTarget,this.upVector),this._viewMatrix},t.prototype._computeViewMatrix=function(e,n,i){if(this.ignoreParentScaling){if(this.parent){var o=this.parent.getWorldMatrix();u.e.TransformCoordinatesToRef(e,o,this._globalPosition),u.e.TransformCoordinatesToRef(n,o,this._tmpTargetVector),u.e.TransformNormalToRef(i,o,this._tmpUpVector),this._markSyncedWithParent()}else this._globalPosition.copyFrom(e),this._tmpTargetVector.copyFrom(n),this._tmpUpVector.copyFrom(i);this.getScene().useRightHandedSystem?u.a.LookAtRHToRef(this._globalPosition,this._tmpTargetVector,this._tmpUpVector,this._viewMatrix):u.a.LookAtLHToRef(this._globalPosition,this._tmpTargetVector,this._tmpUpVector,this._viewMatrix)}else this.getScene().useRightHandedSystem?u.a.LookAtRHToRef(e,n,i,this._viewMatrix):u.a.LookAtLHToRef(e,n,i,this._viewMatrix),this.parent?(o=this.parent.getWorldMatrix(),this._viewMatrix.invert(),this._viewMatrix.multiplyToRef(o,this._viewMatrix),this._viewMatrix.getTranslationToRef(this._globalPosition),this._viewMatrix.invert(),this._markSyncedWithParent()):this._globalPosition.copyFrom(e)},t.prototype.createRigCamera=function(e,n){if(this.cameraRigMode!==gt.a.RIG_MODE_NONE){var i=new t(e,this.position.clone(),this.getScene());return i.isRigCamera=!0,i.rigParent=this,this.cameraRigMode!==gt.a.RIG_MODE_VR&&this.cameraRigMode!==gt.a.RIG_MODE_WEBVR||(this.rotationQuaternion||(this.rotationQuaternion=new u.b),i._cameraRigParams={},i.rotationQuaternion=new u.b),i}return null},t.prototype._updateRigCameras=function(){var e=this._rigCameras[0],n=this._rigCameras[1];switch(this.computeWorldMatrix(),this.cameraRigMode){case gt.a.RIG_MODE_STEREOSCOPIC_ANAGLYPH:case gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL:case gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_CROSSEYED:case gt.a.RIG_MODE_STEREOSCOPIC_OVERUNDER:case gt.a.RIG_MODE_STEREOSCOPIC_INTERLACED:var i=this.cameraRigMode===gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_CROSSEYED?1:-1,o=this.cameraRigMode===gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_CROSSEYED?-1:1;this._getRigCamPositionAndTarget(this._cameraRigParams.stereoHalfAngle*i,e),this._getRigCamPositionAndTarget(this._cameraRigParams.stereoHalfAngle*o,n);break;case gt.a.RIG_MODE_VR:e.rotationQuaternion?(e.rotationQuaternion.copyFrom(this.rotationQuaternion),n.rotationQuaternion.copyFrom(this.rotationQuaternion)):(e.rotation.copyFrom(this.rotation),n.rotation.copyFrom(this.rotation)),e.position.copyFrom(this.position),n.position.copyFrom(this.position)}r.prototype._updateRigCameras.call(this)},t.prototype._getRigCamPositionAndTarget=function(e,n){this.getTarget().subtractToRef(this.position,t._TargetFocalPoint),t._TargetFocalPoint.normalize().scaleInPlace(this._initialFocalDistance);var i=t._TargetFocalPoint.addInPlace(this.position);u.a.TranslationToRef(-i.x,-i.y,-i.z,t._TargetTransformMatrix),t._TargetTransformMatrix.multiplyToRef(u.a.RotationAxis(n.upVector,e),t._RigCamTransformMatrix),u.a.TranslationToRef(i.x,i.y,i.z,t._TargetTransformMatrix),t._RigCamTransformMatrix.multiplyToRef(t._TargetTransformMatrix,t._RigCamTransformMatrix),u.e.TransformCoordinatesToRef(this.position,t._RigCamTransformMatrix,n.position),n.setTarget(i)},t.prototype.getClassName=function(){return"TargetCamera"},t._RigCamTransformMatrix=new u.a,t._TargetTransformMatrix=new u.a,t._TargetFocalPoint=new u.e,Object(c.c)([Object(L.o)()],t.prototype,"rotation",void 0),Object(c.c)([Object(L.c)()],t.prototype,"speed",void 0),Object(c.c)([Object(L.k)("lockedTargetId")],t.prototype,"lockedTarget",void 0),t}(gt.a),Yn=function(r){function t(e,n,i,o){o===void 0&&(o=!0);var a=r.call(this,e,n,i,o)||this;return a.ellipsoid=new u.e(.5,1,.5),a.ellipsoidOffset=new u.e(0,0,0),a.checkCollisions=!1,a.applyGravity=!1,a._needMoveForGravity=!1,a._oldPosition=u.e.Zero(),a._diffPosition=u.e.Zero(),a._newPosition=u.e.Zero(),a._collisionMask=-1,a._onCollisionPositionChange=function(s,d,p){p===void 0&&(p=null);var b;b=d,a._newPosition.copyFrom(b),a._newPosition.subtractToRef(a._oldPosition,a._diffPosition),a._diffPosition.length()>Ue.a.CollisionsEpsilon&&(a.position.addInPlace(a._diffPosition),a.onCollide&&p&&a.onCollide(p))},a.inputs=new eo(a),a.inputs.addKeyboard().addMouse(),a}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"angularSensibility",{get:function(){var e=this.inputs.attached.mouse;return e?e.angularSensibility:0},set:function(e){var n=this.inputs.attached.mouse;n&&(n.angularSensibility=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysUp",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysUp:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysUp=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysUpward",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysUpward:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysUpward=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysDown",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysDown:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysDown=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysDownward",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysDownward:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysDownward=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysLeft",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysLeft:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysLeft=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysRight",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysRight:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysRight=e)},enumerable:!1,configurable:!0}),t.prototype.attachControl=function(e,n){n=Xe.b.BackCompatCameraNoPreventDefault(arguments),this.inputs.attachElement(n)},t.prototype.detachControl=function(e){this.inputs.detachElement(),this.cameraDirection=new u.e(0,0,0),this.cameraRotation=new u.d(0,0)},Object.defineProperty(t.prototype,"collisionMask",{get:function(){return this._collisionMask},set:function(e){this._collisionMask=isNaN(e)?-1:e},enumerable:!1,configurable:!0}),t.prototype._collideWithWorld=function(e){(this.parent?u.e.TransformCoordinates(this.position,this.parent.getWorldMatrix()):this.position).subtractFromFloatsToRef(0,this.ellipsoid.y,0,this._oldPosition),this._oldPosition.addInPlace(this.ellipsoidOffset);var n=this.getScene().collisionCoordinator;this._collider||(this._collider=n.createCollider()),this._collider._radius=this.ellipsoid,this._collider.collisionMask=this._collisionMask;var i=e;this.applyGravity&&(i=e.add(this.getScene().gravity)),n.getNewPosition(this._oldPosition,i,this._collider,3,null,this._onCollisionPositionChange,this.uniqueId)},t.prototype._checkInputs=function(){this._localDirection||(this._localDirection=u.e.Zero(),this._transformedDirection=u.e.Zero()),this.inputs.checkInputs(),r.prototype._checkInputs.call(this)},t.prototype._decideIfNeedsToMove=function(){return this._needMoveForGravity||Math.abs(this.cameraDirection.x)>0||Math.abs(this.cameraDirection.y)>0||Math.abs(this.cameraDirection.z)>0},t.prototype._updatePosition=function(){this.checkCollisions&&this.getScene().collisionsEnabled?this._collideWithWorld(this.cameraDirection):r.prototype._updatePosition.call(this)},t.prototype.dispose=function(){this.inputs.clear(),r.prototype.dispose.call(this)},t.prototype.getClassName=function(){return"FreeCamera"},Object(c.c)([Object(L.o)()],t.prototype,"ellipsoid",void 0),Object(c.c)([Object(L.o)()],t.prototype,"ellipsoidOffset",void 0),Object(c.c)([Object(L.c)()],t.prototype,"checkCollisions",void 0),Object(c.c)([Object(L.c)()],t.prototype,"applyGravity",void 0),t}(Ni);Q.a.AddNodeConstructor("TouchCamera",function(r,t){return function(){return new ss(r,u.e.Zero(),t)}});var ss=function(r){function t(e,n,i){var o=r.call(this,e,n,i)||this;return o.inputs.addTouch(),o._setupInputs(),o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"touchAngularSensibility",{get:function(){var e=this.inputs.attached.touch;return e?e.touchAngularSensibility:0},set:function(e){var n=this.inputs.attached.touch;n&&(n.touchAngularSensibility=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"touchMoveSensibility",{get:function(){var e=this.inputs.attached.touch;return e?e.touchMoveSensibility:0},set:function(e){var n=this.inputs.attached.touch;n&&(n.touchMoveSensibility=e)},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"TouchCamera"},t.prototype._setupInputs=function(){var e=this.inputs.attached.touch,n=this.inputs.attached.mouse;n?n.touchEnabled=!1:e.allowMouse=!0},t}(Yn);Q.a.AddNodeConstructor("ArcRotateCamera",function(r,t){return function(){return new Ji(r,0,0,1,u.e.Zero(),t)}});var Ji=function(r){function t(e,n,i,o,a,s,d){d===void 0&&(d=!0);var p=r.call(this,e,u.e.Zero(),s,d)||this;return p.inertialAlphaOffset=0,p.inertialBetaOffset=0,p.inertialRadiusOffset=0,p.lowerAlphaLimit=null,p.upperAlphaLimit=null,p.lowerBetaLimit=.01,p.upperBetaLimit=Math.PI-.01,p.lowerRadiusLimit=null,p.upperRadiusLimit=null,p.inertialPanningX=0,p.inertialPanningY=0,p.pinchToPanMaxDistance=20,p.panningDistanceLimit=null,p.panningOriginTarget=u.e.Zero(),p.panningInertia=.9,p.zoomOnFactor=1,p.targetScreenOffset=u.d.Zero(),p.allowUpsideDown=!0,p.useInputToRestoreState=!0,p._viewMatrix=new u.a,p.panningAxis=new u.e(1,1,0),p.onMeshTargetChangedObservable=new x.c,p.checkCollisions=!1,p.collisionRadius=new u.e(.5,.5,.5),p._previousPosition=u.e.Zero(),p._collisionVelocity=u.e.Zero(),p._newPosition=u.e.Zero(),p._computationVector=u.e.Zero(),p._onCollisionPositionChange=function(b,P,O){O===void 0&&(O=null),O?(p.setPosition(P),p.onCollide&&p.onCollide(O)):p._previousPosition.copyFrom(p._position);var B=Math.cos(p.alpha),F=Math.sin(p.alpha),z=Math.cos(p.beta),J=Math.sin(p.beta);J===0&&(J=1e-4);var ie=p._getTargetPosition();p._computationVector.copyFromFloats(p.radius*B*J,p.radius*z,p.radius*F*J),ie.addToRef(p._computationVector,p._newPosition),p._position.copyFrom(p._newPosition);var se=p.upVector;p.allowUpsideDown&&p.beta<0&&(se=(se=se.clone()).negate()),p._computeViewMatrix(p._position,ie,se),p._viewMatrix.addAtIndex(12,p.targetScreenOffset.x),p._viewMatrix.addAtIndex(13,p.targetScreenOffset.y),p._collisionTriggered=!1},p._target=u.e.Zero(),a&&p.setTarget(a),p.alpha=n,p.beta=i,p.radius=o,p.getViewMatrix(),p.inputs=new wo(p),p.inputs.addKeyboard().addMouseWheel().addPointers(),p}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"target",{get:function(){return this._target},set:function(e){this.setTarget(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"position",{get:function(){return this._position},set:function(e){this.setPosition(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"upVector",{get:function(){return this._upVector},set:function(e){this._upToYMatrix||(this._YToUpMatrix=new u.a,this._upToYMatrix=new u.a,this._upVector=u.e.Zero()),e.normalize(),this._upVector.copyFrom(e),this.setMatUp()},enumerable:!1,configurable:!0}),t.prototype.setMatUp=function(){u.a.RotationAlignToRef(u.e.UpReadOnly,this._upVector,this._YToUpMatrix),u.a.RotationAlignToRef(this._upVector,u.e.UpReadOnly,this._upToYMatrix)},Object.defineProperty(t.prototype,"angularSensibilityX",{get:function(){var e=this.inputs.attached.pointers;return e?e.angularSensibilityX:0},set:function(e){var n=this.inputs.attached.pointers;n&&(n.angularSensibilityX=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"angularSensibilityY",{get:function(){var e=this.inputs.attached.pointers;return e?e.angularSensibilityY:0},set:function(e){var n=this.inputs.attached.pointers;n&&(n.angularSensibilityY=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"pinchPrecision",{get:function(){var e=this.inputs.attached.pointers;return e?e.pinchPrecision:0},set:function(e){var n=this.inputs.attached.pointers;n&&(n.pinchPrecision=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"pinchDeltaPercentage",{get:function(){var e=this.inputs.attached.pointers;return e?e.pinchDeltaPercentage:0},set:function(e){var n=this.inputs.attached.pointers;n&&(n.pinchDeltaPercentage=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"useNaturalPinchZoom",{get:function(){var e=this.inputs.attached.pointers;return!!e&&e.useNaturalPinchZoom},set:function(e){var n=this.inputs.attached.pointers;n&&(n.useNaturalPinchZoom=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"panningSensibility",{get:function(){var e=this.inputs.attached.pointers;return e?e.panningSensibility:0},set:function(e){var n=this.inputs.attached.pointers;n&&(n.panningSensibility=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysUp",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysUp:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysUp=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysDown",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysDown:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysDown=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysLeft",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysLeft:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysLeft=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysRight",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysRight:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysRight=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelPrecision",{get:function(){var e=this.inputs.attached.mousewheel;return e?e.wheelPrecision:0},set:function(e){var n=this.inputs.attached.mousewheel;n&&(n.wheelPrecision=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelDeltaPercentage",{get:function(){var e=this.inputs.attached.mousewheel;return e?e.wheelDeltaPercentage:0},set:function(e){var n=this.inputs.attached.mousewheel;n&&(n.wheelDeltaPercentage=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"bouncingBehavior",{get:function(){return this._bouncingBehavior},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"useBouncingBehavior",{get:function(){return this._bouncingBehavior!=null},set:function(e){e!==this.useBouncingBehavior&&(e?(this._bouncingBehavior=new fl,this.addBehavior(this._bouncingBehavior)):this._bouncingBehavior&&(this.removeBehavior(this._bouncingBehavior),this._bouncingBehavior=null))},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"framingBehavior",{get:function(){return this._framingBehavior},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"useFramingBehavior",{get:function(){return this._framingBehavior!=null},set:function(e){e!==this.useFramingBehavior&&(e?(this._framingBehavior=new pl,this.addBehavior(this._framingBehavior)):this._framingBehavior&&(this.removeBehavior(this._framingBehavior),this._framingBehavior=null))},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"autoRotationBehavior",{get:function(){return this._autoRotationBehavior},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"useAutoRotationBehavior",{get:function(){return this._autoRotationBehavior!=null},set:function(e){e!==this.useAutoRotationBehavior&&(e?(this._autoRotationBehavior=new dl,this.addBehavior(this._autoRotationBehavior)):this._autoRotationBehavior&&(this.removeBehavior(this._autoRotationBehavior),this._autoRotationBehavior=null))},enumerable:!1,configurable:!0}),t.prototype._initCache=function(){r.prototype._initCache.call(this),this._cache._target=new u.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),this._cache.alpha=void 0,this._cache.beta=void 0,this._cache.radius=void 0,this._cache.targetScreenOffset=u.d.Zero()},t.prototype._updateCache=function(e){e||r.prototype._updateCache.call(this),this._cache._target.copyFrom(this._getTargetPosition()),this._cache.alpha=this.alpha,this._cache.beta=this.beta,this._cache.radius=this.radius,this._cache.targetScreenOffset.copyFrom(this.targetScreenOffset)},t.prototype._getTargetPosition=function(){if(this._targetHost&&this._targetHost.getAbsolutePosition){var e=this._targetHost.absolutePosition;this._targetBoundingCenter?e.addToRef(this._targetBoundingCenter,this._target):this._target.copyFrom(e)}var n=this._getLockedTargetPosition();return n||this._target},t.prototype.storeState=function(){return this._storedAlpha=this.alpha,this._storedBeta=this.beta,this._storedRadius=this.radius,this._storedTarget=this._getTargetPosition().clone(),this._storedTargetScreenOffset=this.targetScreenOffset.clone(),r.prototype.storeState.call(this)},t.prototype._restoreStateValues=function(){return!!r.prototype._restoreStateValues.call(this)&&(this.setTarget(this._storedTarget.clone()),this.alpha=this._storedAlpha,this.beta=this._storedBeta,this.radius=this._storedRadius,this.targetScreenOffset=this._storedTargetScreenOffset.clone(),this.inertialAlphaOffset=0,this.inertialBetaOffset=0,this.inertialRadiusOffset=0,this.inertialPanningX=0,this.inertialPanningY=0,!0)},t.prototype._isSynchronizedViewMatrix=function(){return!!r.prototype._isSynchronizedViewMatrix.call(this)&&this._cache._target.equals(this._getTargetPosition())&&this._cache.alpha===this.alpha&&this._cache.beta===this.beta&&this._cache.radius===this.radius&&this._cache.targetScreenOffset.equals(this.targetScreenOffset)},t.prototype.attachControl=function(e,n,i,o){var a=this;i===void 0&&(i=!0),o===void 0&&(o=2),n=Xe.b.BackCompatCameraNoPreventDefault(arguments),this._useCtrlForPanning=i,this._panningMouseButton=o,typeof arguments[0]=="boolean"&&(arguments.length>1&&(this._useCtrlForPanning=arguments[1]),arguments.length>2&&(this._panningMouseButton=arguments[2])),this.inputs.attachElement(n),this._reset=function(){a.inertialAlphaOffset=0,a.inertialBetaOffset=0,a.inertialRadiusOffset=0,a.inertialPanningX=0,a.inertialPanningY=0}},t.prototype.detachControl=function(e){this.inputs.detachElement(),this._reset&&this._reset()},t.prototype._checkInputs=function(){if(!this._collisionTriggered){if(this.inputs.checkInputs(),this.inertialAlphaOffset!==0||this.inertialBetaOffset!==0||this.inertialRadiusOffset!==0){var e=this.inertialAlphaOffset;this.beta<=0&&(e*=-1),this.getScene().useRightHandedSystem&&(e*=-1),this.parent&&this.parent._getWorldMatrixDeterminant()<0&&(e*=-1),this.alpha+=e,this.beta+=this.inertialBetaOffset,this.radius-=this.inertialRadiusOffset,this.inertialAlphaOffset*=this.inertia,this.inertialBetaOffset*=this.inertia,this.inertialRadiusOffset*=this.inertia,Math.abs(this.inertialAlphaOffset)<Gt.a&&(this.inertialAlphaOffset=0),Math.abs(this.inertialBetaOffset)<Gt.a&&(this.inertialBetaOffset=0),Math.abs(this.inertialRadiusOffset)<this.speed*Gt.a&&(this.inertialRadiusOffset=0)}(this.inertialPanningX!==0||this.inertialPanningY!==0)&&(this._localDirection||(this._localDirection=u.e.Zero(),this._transformedDirection=u.e.Zero()),this._localDirection.copyFromFloats(this.inertialPanningX,this.inertialPanningY,this.inertialPanningY),this._localDirection.multiplyInPlace(this.panningAxis),this._viewMatrix.invertToRef(this._cameraTransformMatrix),u.e.TransformNormalToRef(this._localDirection,this._cameraTransformMatrix,this._transformedDirection),this.panningAxis.y||(this._transformedDirection.y=0),!this._targetHost&&(this.panningDistanceLimit?(this._transformedDirection.addInPlace(this._target),u.e.DistanceSquared(this._transformedDirection,this.panningOriginTarget)<=this.panningDistanceLimit*this.panningDistanceLimit&&this._target.copyFrom(this._transformedDirection)):this._target.addInPlace(this._transformedDirection)),this.inertialPanningX*=this.panningInertia,this.inertialPanningY*=this.panningInertia,Math.abs(this.inertialPanningX)<this.speed*Gt.a&&(this.inertialPanningX=0),Math.abs(this.inertialPanningY)<this.speed*Gt.a&&(this.inertialPanningY=0)),this._checkLimits(),r.prototype._checkInputs.call(this)}},t.prototype._checkLimits=function(){this.lowerBetaLimit===null||this.lowerBetaLimit===void 0?this.allowUpsideDown&&this.beta>Math.PI&&(this.beta=this.beta-2*Math.PI):this.beta<this.lowerBetaLimit&&(this.beta=this.lowerBetaLimit),this.upperBetaLimit===null||this.upperBetaLimit===void 0?this.allowUpsideDown&&this.beta<-Math.PI&&(this.beta=this.beta+2*Math.PI):this.beta>this.upperBetaLimit&&(this.beta=this.upperBetaLimit),this.lowerAlphaLimit!==null&&this.alpha<this.lowerAlphaLimit&&(this.alpha=this.lowerAlphaLimit),this.upperAlphaLimit!==null&&this.alpha>this.upperAlphaLimit&&(this.alpha=this.upperAlphaLimit),this.lowerRadiusLimit!==null&&this.radius<this.lowerRadiusLimit&&(this.radius=this.lowerRadiusLimit,this.inertialRadiusOffset=0),this.upperRadiusLimit!==null&&this.radius>this.upperRadiusLimit&&(this.radius=this.upperRadiusLimit,this.inertialRadiusOffset=0)},t.prototype.rebuildAnglesAndRadius=function(){this._position.subtractToRef(this._getTargetPosition(),this._computationVector),this._upVector.x===0&&this._upVector.y===1&&this._upVector.z===0||u.e.TransformCoordinatesToRef(this._computationVector,this._upToYMatrix,this._computationVector),this.radius=this._computationVector.length(),this.radius===0&&(this.radius=1e-4);var e=this.alpha;this._computationVector.x===0&&this._computationVector.z===0?this.alpha=Math.PI/2:this.alpha=Math.acos(this._computationVector.x/Math.sqrt(Math.pow(this._computationVector.x,2)+Math.pow(this._computationVector.z,2))),this._computationVector.z<0&&(this.alpha=2*Math.PI-this.alpha);var n=Math.round((e-this.alpha)/(2*Math.PI));this.alpha+=2*n*Math.PI,this.beta=Math.acos(this._computationVector.y/this.radius),this._checkLimits()},t.prototype.setPosition=function(e){this._position.equals(e)||(this._position.copyFrom(e),this.rebuildAnglesAndRadius())},t.prototype.setTarget=function(e,n,i){if(n===void 0&&(n=!1),i===void 0&&(i=!1),e.getBoundingInfo)this._targetBoundingCenter=n?e.getBoundingInfo().boundingBox.centerWorld.clone():null,e.computeWorldMatrix(),this._targetHost=e,this._target=this._getTargetPosition(),this.onMeshTargetChangedObservable.notifyObservers(this._targetHost);else{var o=e,a=this._getTargetPosition();if(a&&!i&&a.equals(o))return;this._targetHost=null,this._target=o,this._targetBoundingCenter=null,this.onMeshTargetChangedObservable.notifyObservers(null)}this.rebuildAnglesAndRadius()},t.prototype._getViewMatrix=function(){var e=Math.cos(this.alpha),n=Math.sin(this.alpha),i=Math.cos(this.beta),o=Math.sin(this.beta);o===0&&(o=1e-4),this.radius===0&&(this.radius=1e-4);var a=this._getTargetPosition();if(this._computationVector.copyFromFloats(this.radius*e*o,this.radius*i,this.radius*n*o),this._upVector.x===0&&this._upVector.y===1&&this._upVector.z===0||u.e.TransformCoordinatesToRef(this._computationVector,this._YToUpMatrix,this._computationVector),a.addToRef(this._computationVector,this._newPosition),this.getScene().collisionsEnabled&&this.checkCollisions){var s=this.getScene().collisionCoordinator;this._collider||(this._collider=s.createCollider()),this._collider._radius=this.collisionRadius,this._newPosition.subtractToRef(this._position,this._collisionVelocity),this._collisionTriggered=!0,s.getNewPosition(this._position,this._collisionVelocity,this._collider,3,null,this._onCollisionPositionChange,this.uniqueId)}else{this._position.copyFrom(this._newPosition);var d=this.upVector;this.allowUpsideDown&&o<0&&(d=d.negate()),this._computeViewMatrix(this._position,a,d),this._viewMatrix.addAtIndex(12,this.targetScreenOffset.x),this._viewMatrix.addAtIndex(13,this.targetScreenOffset.y)}return this._currentTarget=a,this._viewMatrix},t.prototype.zoomOn=function(e,n){n===void 0&&(n=!1),e=e||this.getScene().meshes;var i=De.a.MinMax(e),o=u.e.Distance(i.min,i.max);this.radius=o*this.zoomOnFactor,this.focusOn({min:i.min,max:i.max,distance:o},n)},t.prototype.focusOn=function(e,n){var i,o;if(n===void 0&&(n=!1),e.min===void 0){var a=e||this.getScene().meshes;i=De.a.MinMax(a),o=u.e.Distance(i.min,i.max)}else i=e,o=e.distance;this._target=De.a.Center(i),n||(this.maxZ=2*o)},t.prototype.createRigCamera=function(e,n){var i=0;switch(this.cameraRigMode){case gt.a.RIG_MODE_STEREOSCOPIC_ANAGLYPH:case gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL:case gt.a.RIG_MODE_STEREOSCOPIC_OVERUNDER:case gt.a.RIG_MODE_STEREOSCOPIC_INTERLACED:case gt.a.RIG_MODE_VR:i=this._cameraRigParams.stereoHalfAngle*(n===0?1:-1);break;case gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_CROSSEYED:i=this._cameraRigParams.stereoHalfAngle*(n===0?-1:1)}var o=new t(e,this.alpha+i,this.beta,this.radius,this._target,this.getScene());return o._cameraRigParams={},o.isRigCamera=!0,o.rigParent=this,o.upVector=this.upVector,o},t.prototype._updateRigCameras=function(){var e=this._rigCameras[0],n=this._rigCameras[1];switch(e.beta=n.beta=this.beta,this.cameraRigMode){case gt.a.RIG_MODE_STEREOSCOPIC_ANAGLYPH:case gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL:case gt.a.RIG_MODE_STEREOSCOPIC_OVERUNDER:case gt.a.RIG_MODE_STEREOSCOPIC_INTERLACED:case gt.a.RIG_MODE_VR:e.alpha=this.alpha-this._cameraRigParams.stereoHalfAngle,n.alpha=this.alpha+this._cameraRigParams.stereoHalfAngle;break;case gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_CROSSEYED:e.alpha=this.alpha+this._cameraRigParams.stereoHalfAngle,n.alpha=this.alpha-this._cameraRigParams.stereoHalfAngle}r.prototype._updateRigCameras.call(this)},t.prototype.dispose=function(){this.inputs.clear(),r.prototype.dispose.call(this)},t.prototype.getClassName=function(){return"ArcRotateCamera"},Object(c.c)([Object(L.c)()],t.prototype,"alpha",void 0),Object(c.c)([Object(L.c)()],t.prototype,"beta",void 0),Object(c.c)([Object(L.c)()],t.prototype,"radius",void 0),Object(c.c)([Object(L.o)("target")],t.prototype,"_target",void 0),Object(c.c)([Object(L.c)()],t.prototype,"inertialAlphaOffset",void 0),Object(c.c)([Object(L.c)()],t.prototype,"inertialBetaOffset",void 0),Object(c.c)([Object(L.c)()],t.prototype,"inertialRadiusOffset",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lowerAlphaLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"upperAlphaLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lowerBetaLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"upperBetaLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lowerRadiusLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"upperRadiusLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"inertialPanningX",void 0),Object(c.c)([Object(L.c)()],t.prototype,"inertialPanningY",void 0),Object(c.c)([Object(L.c)()],t.prototype,"pinchToPanMaxDistance",void 0),Object(c.c)([Object(L.c)()],t.prototype,"panningDistanceLimit",void 0),Object(c.c)([Object(L.o)()],t.prototype,"panningOriginTarget",void 0),Object(c.c)([Object(L.c)()],t.prototype,"panningInertia",void 0),Object(c.c)([Object(L.c)()],t.prototype,"zoomOnFactor",void 0),Object(c.c)([Object(L.c)()],t.prototype,"targetScreenOffset",void 0),Object(c.c)([Object(L.c)()],t.prototype,"allowUpsideDown",void 0),Object(c.c)([Object(L.c)()],t.prototype,"useInputToRestoreState",void 0),t}(Ni);Q.a.AddNodeConstructor("DeviceOrientationCamera",function(r,t){return function(){return new Fo(r,u.e.Zero(),t)}});var Fo=function(r){function t(e,n,i){var o=r.call(this,e,n,i)||this;return o._tmpDragQuaternion=new u.b,o._disablePointerInputWhenUsingDeviceOrientation=!0,o._dragFactor=0,o._quaternionCache=new u.b,o.inputs.addDeviceOrientation(),o.inputs._deviceOrientationInput&&o.inputs._deviceOrientationInput._onDeviceOrientationChangedObservable.addOnce(function(){o._disablePointerInputWhenUsingDeviceOrientation&&o.inputs._mouseInput&&(o.inputs._mouseInput._allowCameraRotation=!1,o.inputs._mouseInput.onPointerMovedObservable.add(function(a){o._dragFactor!=0&&(o._initialQuaternion||(o._initialQuaternion=new u.b),u.b.FromEulerAnglesToRef(0,a.offsetX*o._dragFactor,0,o._tmpDragQuaternion),o._initialQuaternion.multiplyToRef(o._tmpDragQuaternion,o._initialQuaternion))}))}),o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"disablePointerInputWhenUsingDeviceOrientation",{get:function(){return this._disablePointerInputWhenUsingDeviceOrientation},set:function(e){this._disablePointerInputWhenUsingDeviceOrientation=e},enumerable:!1,configurable:!0}),t.prototype.enableHorizontalDragging=function(e){e===void 0&&(e=1/300),this._dragFactor=e},t.prototype.getClassName=function(){return"DeviceOrientationCamera"},t.prototype._checkInputs=function(){r.prototype._checkInputs.call(this),this._quaternionCache.copyFrom(this.rotationQuaternion),this._initialQuaternion&&this._initialQuaternion.multiplyToRef(this.rotationQuaternion,this.rotationQuaternion)},t.prototype.resetToCurrentRotation=function(e){var n=this;e===void 0&&(e=ye.a.Y),this.rotationQuaternion&&(this._initialQuaternion||(this._initialQuaternion=new u.b),this._initialQuaternion.copyFrom(this._quaternionCache||this.rotationQuaternion),["x","y","z"].forEach(function(i){e[i]?n._initialQuaternion[i]*=-1:n._initialQuaternion[i]=0}),this._initialQuaternion.normalize(),this._initialQuaternion.multiplyToRef(this.rotationQuaternion,this.rotationQuaternion))},t}(Yn),El=function(r){function t(e){return r.call(this,e)||this}return Object(c.d)(t,r),t.prototype.addKeyboard=function(){return this.add(new Ka),this},t.prototype.addMouse=function(e){return e===void 0&&(e=!0),this.add(new Qa(e)),this},t}($r),Vf=function(r){function t(e,n,i,o){o===void 0&&(o=!0);var a=r.call(this,e,n,i,o)||this;return a.ellipsoid=new u.e(1,1,1),a.ellipsoidOffset=new u.e(0,0,0),a.checkCollisions=!1,a.applyGravity=!1,a.cameraDirection=u.e.Zero(),a._trackRoll=0,a.rollCorrect=100,a.bankedTurn=!1,a.bankedTurnLimit=Math.PI/2,a.bankedTurnMultiplier=1,a._needMoveForGravity=!1,a._oldPosition=u.e.Zero(),a._diffPosition=u.e.Zero(),a._newPosition=u.e.Zero(),a._collisionMask=-1,a._onCollisionPositionChange=function(s,d,p){p===void 0&&(p=null);var b;b=d,a._newPosition.copyFrom(b),a._newPosition.subtractToRef(a._oldPosition,a._diffPosition),a._diffPosition.length()>Ue.a.CollisionsEpsilon&&(a.position.addInPlace(a._diffPosition),a.onCollide&&p&&a.onCollide(p))},a.inputs=new El(a),a.inputs.addKeyboard().addMouse(),a}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"angularSensibility",{get:function(){var e=this.inputs.attached.mouse;return e?e.angularSensibility:0},set:function(e){var n=this.inputs.attached.mouse;n&&(n.angularSensibility=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysForward",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysForward:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysForward=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysBackward",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysBackward:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysBackward=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysUp",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysUp:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysUp=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysDown",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysDown:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysDown=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysLeft",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysLeft:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysLeft=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysRight",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysRight:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysRight=e)},enumerable:!1,configurable:!0}),t.prototype.attachControl=function(e,n){n=Xe.b.BackCompatCameraNoPreventDefault(arguments),this.inputs.attachElement(n)},t.prototype.detachControl=function(){this.inputs.detachElement(),this.cameraDirection=new u.e(0,0,0)},Object.defineProperty(t.prototype,"collisionMask",{get:function(){return this._collisionMask},set:function(e){this._collisionMask=isNaN(e)?-1:e},enumerable:!1,configurable:!0}),t.prototype._collideWithWorld=function(e){(this.parent?u.e.TransformCoordinates(this.position,this.parent.getWorldMatrix()):this.position).subtractFromFloatsToRef(0,this.ellipsoid.y,0,this._oldPosition),this._oldPosition.addInPlace(this.ellipsoidOffset);var n=this.getScene().collisionCoordinator;this._collider||(this._collider=n.createCollider()),this._collider._radius=this.ellipsoid,this._collider.collisionMask=this._collisionMask;var i=e;this.applyGravity&&(i=e.add(this.getScene().gravity)),n.getNewPosition(this._oldPosition,i,this._collider,3,null,this._onCollisionPositionChange,this.uniqueId)},t.prototype._checkInputs=function(){this._localDirection||(this._localDirection=u.e.Zero(),this._transformedDirection=u.e.Zero()),this.inputs.checkInputs(),r.prototype._checkInputs.call(this)},t.prototype._decideIfNeedsToMove=function(){return this._needMoveForGravity||Math.abs(this.cameraDirection.x)>0||Math.abs(this.cameraDirection.y)>0||Math.abs(this.cameraDirection.z)>0},t.prototype._updatePosition=function(){this.checkCollisions&&this.getScene().collisionsEnabled?this._collideWithWorld(this.cameraDirection):r.prototype._updatePosition.call(this)},t.prototype.restoreRoll=function(e){var n=this._trackRoll,i=n-this.rotation.z;Math.abs(i)>=.001&&(this.rotation.z+=i/e,Math.abs(n-this.rotation.z)<=.001&&(this.rotation.z=n))},t.prototype.dispose=function(){this.inputs.clear(),r.prototype.dispose.call(this)},t.prototype.getClassName=function(){return"FlyCamera"},Object(c.c)([Object(L.o)()],t.prototype,"ellipsoid",void 0),Object(c.c)([Object(L.o)()],t.prototype,"ellipsoidOffset",void 0),Object(c.c)([Object(L.c)()],t.prototype,"checkCollisions",void 0),Object(c.c)([Object(L.c)()],t.prototype,"applyGravity",void 0),t}(Ni),Sl=function(r){function t(e){return r.call(this,e)||this}return Object(c.d)(t,r),t.prototype.addKeyboard=function(){return this.add(new qa),this},t.prototype.addMouseWheel=function(){return this.add(new Za),this},t.prototype.addPointers=function(){return this.add(new Ja),this},t.prototype.addVRDeviceOrientation=function(){return console.warn("DeviceOrientation support not yet implemented for FollowCamera."),this},t}($r);Q.a.AddNodeConstructor("FollowCamera",function(r,t){return function(){return new Al(r,u.e.Zero(),t)}}),Q.a.AddNodeConstructor("ArcFollowCamera",function(r,t){return function(){return new Pl(r,0,0,1,null,t)}});var ri,Al=function(r){function t(e,n,i,o){o===void 0&&(o=null);var a=r.call(this,e,n,i)||this;return a.radius=12,a.lowerRadiusLimit=null,a.upperRadiusLimit=null,a.rotationOffset=0,a.lowerRotationOffsetLimit=null,a.upperRotationOffsetLimit=null,a.heightOffset=4,a.lowerHeightOffsetLimit=null,a.upperHeightOffsetLimit=null,a.cameraAcceleration=.05,a.maxCameraSpeed=20,a.lockedTarget=o,a.inputs=new Sl(a),a.inputs.addKeyboard().addMouseWheel().addPointers(),a}return Object(c.d)(t,r),t.prototype._follow=function(e){if(e){var n;if(e.rotationQuaternion){var i=new u.a;e.rotationQuaternion.toRotationMatrix(i),n=Math.atan2(i.m[8],i.m[10])}else n=e.rotation.y;var o=Xe.b.ToRadians(this.rotationOffset)+n,a=e.getAbsolutePosition(),s=a.x+Math.sin(o)*this.radius,d=a.z+Math.cos(o)*this.radius,p=s-this.position.x,b=a.y+this.heightOffset-this.position.y,P=d-this.position.z,O=p*this.cameraAcceleration*2,B=b*this.cameraAcceleration,F=P*this.cameraAcceleration*2;(O>this.maxCameraSpeed||O<-this.maxCameraSpeed)&&(O=O<1?-this.maxCameraSpeed:this.maxCameraSpeed),(B>this.maxCameraSpeed||B<-this.maxCameraSpeed)&&(B=B<1?-this.maxCameraSpeed:this.maxCameraSpeed),(F>this.maxCameraSpeed||F<-this.maxCameraSpeed)&&(F=F<1?-this.maxCameraSpeed:this.maxCameraSpeed),this.position=new u.e(this.position.x+O,this.position.y+B,this.position.z+F),this.setTarget(a)}},t.prototype.attachControl=function(e,n){n=Xe.b.BackCompatCameraNoPreventDefault(arguments),this.inputs.attachElement(n),this._reset=function(){}},t.prototype.detachControl=function(e){this.inputs.detachElement(),this._reset&&this._reset()},t.prototype._checkInputs=function(){this.inputs.checkInputs(),this._checkLimits(),r.prototype._checkInputs.call(this),this.lockedTarget&&this._follow(this.lockedTarget)},t.prototype._checkLimits=function(){this.lowerRadiusLimit!==null&&this.radius<this.lowerRadiusLimit&&(this.radius=this.lowerRadiusLimit),this.upperRadiusLimit!==null&&this.radius>this.upperRadiusLimit&&(this.radius=this.upperRadiusLimit),this.lowerHeightOffsetLimit!==null&&this.heightOffset<this.lowerHeightOffsetLimit&&(this.heightOffset=this.lowerHeightOffsetLimit),this.upperHeightOffsetLimit!==null&&this.heightOffset>this.upperHeightOffsetLimit&&(this.heightOffset=this.upperHeightOffsetLimit),this.lowerRotationOffsetLimit!==null&&this.rotationOffset<this.lowerRotationOffsetLimit&&(this.rotationOffset=this.lowerRotationOffsetLimit),this.upperRotationOffsetLimit!==null&&this.rotationOffset>this.upperRotationOffsetLimit&&(this.rotationOffset=this.upperRotationOffsetLimit)},t.prototype.getClassName=function(){return"FollowCamera"},Object(c.c)([Object(L.c)()],t.prototype,"radius",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lowerRadiusLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"upperRadiusLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"rotationOffset",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lowerRotationOffsetLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"upperRotationOffsetLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"heightOffset",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lowerHeightOffsetLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"upperHeightOffsetLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"cameraAcceleration",void 0),Object(c.c)([Object(L.c)()],t.prototype,"maxCameraSpeed",void 0),Object(c.c)([Object(L.k)("lockedTargetId")],t.prototype,"lockedTarget",void 0),t}(Ni),Pl=function(r){function t(e,n,i,o,a,s){var d=r.call(this,e,u.e.Zero(),s)||this;return d.alpha=n,d.beta=i,d.radius=o,d._cartesianCoordinates=u.e.Zero(),d._meshTarget=a,d._follow(),d}return Object(c.d)(t,r),t.prototype._follow=function(){if(this._meshTarget){this._cartesianCoordinates.x=this.radius*Math.cos(this.alpha)*Math.cos(this.beta),this._cartesianCoordinates.y=this.radius*Math.sin(this.beta),this._cartesianCoordinates.z=this.radius*Math.sin(this.alpha)*Math.cos(this.beta);var e=this._meshTarget.getAbsolutePosition();this.position=e.add(this._cartesianCoordinates),this.setTarget(e)}},t.prototype._checkInputs=function(){r.prototype._checkInputs.call(this),this._follow()},t.prototype.getClassName=function(){return"ArcFollowCamera"},t}(Ni),cs=f(38),fn=f(39);(function(r){r[r.VIVE=0]="VIVE",r[r.OCULUS=1]="OCULUS",r[r.WINDOWS=2]="WINDOWS",r[r.GEAR_VR=3]="GEAR_VR",r[r.DAYDREAM=4]="DAYDREAM",r[r.GENERIC=5]="GENERIC"})(ri||(ri={}));var Rn,$i,wi=function(){function r(){}return r.InitiateController=function(t){for(var e=0,n=this._ControllerFactories;e<n.length;e++){var i=n[e];if(i.canCreate(t))return i.create(t)}if(this._DefaultControllerFactory)return this._DefaultControllerFactory(t);throw"The type of gamepad you are trying to load needs to be imported first or is not supported."},r._ControllerFactories=[],r._DefaultControllerFactory=null,r}(),pr=function(r){function t(e){var n=r.call(this,e.id,e.index,e)||this;return n.isXR=!1,n._deviceRoomPosition=u.e.Zero(),n._deviceRoomRotationQuaternion=new u.b,n.devicePosition=u.e.Zero(),n.deviceRotationQuaternion=new u.b,n.deviceScaleFactor=1,n._trackPosition=!0,n._maxRotationDistFromHeadset=Math.PI/5,n._draggedRoomRotation=0,n._leftHandSystemQuaternion=new u.b,n._deviceToWorld=u.a.Identity(),n._pointingPoseNode=null,n._workingMatrix=u.a.Identity(),n._meshAttachedObservable=new x.c,n.type=dn.POSE_ENABLED,n.controllerType=ri.GENERIC,n.position=u.e.Zero(),n.rotationQuaternion=new u.b,n._calculatedPosition=u.e.Zero(),n._calculatedRotation=new u.b,u.b.RotationYawPitchRollToRef(Math.PI,0,0,n._leftHandSystemQuaternion),n}return Object(c.d)(t,r),t.prototype._disableTrackPosition=function(e){this._trackPosition&&(this._calculatedPosition.copyFrom(e),this._trackPosition=!1)},t.prototype.update=function(){r.prototype.update.call(this),this._updatePoseAndMesh()},t.prototype._updatePoseAndMesh=function(){if(!this.isXR){var e=this.browserGamepad.pose;if(this.updateFromDevice(e),!this._trackPosition&&te.a.LastCreatedScene&&te.a.LastCreatedScene.activeCamera&&te.a.LastCreatedScene.activeCamera.devicePosition&&((n=te.a.LastCreatedScene.activeCamera)._computeDevicePosition(),this._deviceToWorld.setTranslation(n.devicePosition),n.deviceRotationQuaternion)){var n;(n=n)._deviceRoomRotationQuaternion.toEulerAnglesToRef(u.c.Vector3[0]);var i=Math.atan2(Math.sin(u.c.Vector3[0].y-this._draggedRoomRotation),Math.cos(u.c.Vector3[0].y-this._draggedRoomRotation));if(Math.abs(i)>this._maxRotationDistFromHeadset){var o=i-(i<0?-this._maxRotationDistFromHeadset:this._maxRotationDistFromHeadset);this._draggedRoomRotation+=o;var a=Math.sin(-o),s=Math.cos(-o);this._calculatedPosition.x=this._calculatedPosition.x*s-this._calculatedPosition.z*a,this._calculatedPosition.z=this._calculatedPosition.x*a+this._calculatedPosition.z*s}}u.e.TransformCoordinatesToRef(this._calculatedPosition,this._deviceToWorld,this.devicePosition),this._deviceToWorld.getRotationMatrixToRef(this._workingMatrix),u.b.FromRotationMatrixToRef(this._workingMatrix,this.deviceRotationQuaternion),this.deviceRotationQuaternion.multiplyInPlace(this._calculatedRotation),this._mesh&&(this._mesh.position.copyFrom(this.devicePosition),this._mesh.rotationQuaternion&&this._mesh.rotationQuaternion.copyFrom(this.deviceRotationQuaternion))}},t.prototype.updateFromDevice=function(e){if(!this.isXR&&e){this.rawPose=e,e.position&&(this._deviceRoomPosition.copyFromFloats(e.position[0],e.position[1],-e.position[2]),this._mesh&&this._mesh.getScene().useRightHandedSystem&&(this._deviceRoomPosition.z*=-1),this._trackPosition&&this._deviceRoomPosition.scaleToRef(this.deviceScaleFactor,this._calculatedPosition),this._calculatedPosition.addInPlace(this.position));var n=this.rawPose;e.orientation&&n.orientation&&n.orientation.length===4&&(this._deviceRoomRotationQuaternion.copyFromFloats(n.orientation[0],n.orientation[1],-n.orientation[2],-n.orientation[3]),this._mesh&&(this._mesh.getScene().useRightHandedSystem?(this._deviceRoomRotationQuaternion.z*=-1,this._deviceRoomRotationQuaternion.w*=-1):this._deviceRoomRotationQuaternion.multiplyToRef(this._leftHandSystemQuaternion,this._deviceRoomRotationQuaternion)),this._deviceRoomRotationQuaternion.multiplyToRef(this.rotationQuaternion,this._calculatedRotation))}},t.prototype.attachToMesh=function(e){if(this._mesh&&(this._mesh.parent=null),this._mesh=e,this._poseControlledCamera&&(this._mesh.parent=this._poseControlledCamera),this._mesh.rotationQuaternion||(this._mesh.rotationQuaternion=new u.b),!this.isXR&&(this._updatePoseAndMesh(),this._pointingPoseNode)){for(var n=[],i=this._pointingPoseNode;i.parent;)n.push(i.parent),i=i.parent;n.reverse().forEach(function(o){o.computeWorldMatrix(!0)})}this._meshAttachedObservable.notifyObservers(e)},t.prototype.attachToPoseControlledCamera=function(e){this._poseControlledCamera=e,this._mesh&&(this._mesh.parent=this._poseControlledCamera)},t.prototype.dispose=function(){this._mesh&&this._mesh.dispose(),this._mesh=null,r.prototype.dispose.call(this)},Object.defineProperty(t.prototype,"mesh",{get:function(){return this._mesh},enumerable:!1,configurable:!0}),t.prototype.getForwardRay=function(e){if(e===void 0&&(e=100),!this.mesh)return new fn.a(u.e.Zero(),new u.e(0,0,1),e);var n=this._pointingPoseNode?this._pointingPoseNode.getWorldMatrix():this.mesh.getWorldMatrix(),i=n.getTranslation(),o=new u.e(0,0,-1),a=u.e.TransformNormal(o,n),s=u.e.Normalize(a);return new fn.a(i,s,e)},t.POINTING_POSE="POINTING_POSE",t}(dn);(function(r){r[r.A=0]="A",r[r.B=1]="B",r[r.X=2]="X",r[r.Y=3]="Y",r[r.LB=4]="LB",r[r.RB=5]="RB",r[r.Back=8]="Back",r[r.Start=9]="Start",r[r.LeftStick=10]="LeftStick",r[r.RightStick=11]="RightStick"})(Rn||(Rn={})),function(r){r[r.Up=12]="Up",r[r.Down=13]="Down",r[r.Left=14]="Left",r[r.Right=15]="Right"}($i||($i={}));var Gn,er,Cl=function(r){function t(e,n,i,o){o===void 0&&(o=!1);var a=r.call(this,e,n,i,0,1,2,3)||this;return a._leftTrigger=0,a._rightTrigger=0,a.onButtonDownObservable=new x.c,a.onButtonUpObservable=new x.c,a.onPadDownObservable=new x.c,a.onPadUpObservable=new x.c,a._buttonA=0,a._buttonB=0,a._buttonX=0,a._buttonY=0,a._buttonBack=0,a._buttonStart=0,a._buttonLB=0,a._buttonRB=0,a._buttonLeftStick=0,a._buttonRightStick=0,a._dPadUp=0,a._dPadDown=0,a._dPadLeft=0,a._dPadRight=0,a._isXboxOnePad=!1,a.type=dn.XBOX,a._isXboxOnePad=o,a}return Object(c.d)(t,r),t.prototype.onlefttriggerchanged=function(e){this._onlefttriggerchanged=e},t.prototype.onrighttriggerchanged=function(e){this._onrighttriggerchanged=e},Object.defineProperty(t.prototype,"leftTrigger",{get:function(){return this._leftTrigger},set:function(e){this._onlefttriggerchanged&&this._leftTrigger!==e&&this._onlefttriggerchanged(e),this._leftTrigger=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rightTrigger",{get:function(){return this._rightTrigger},set:function(e){this._onrighttriggerchanged&&this._rightTrigger!==e&&this._onrighttriggerchanged(e),this._rightTrigger=e},enumerable:!1,configurable:!0}),t.prototype.onbuttondown=function(e){this._onbuttondown=e},t.prototype.onbuttonup=function(e){this._onbuttonup=e},t.prototype.ondpaddown=function(e){this._ondpaddown=e},t.prototype.ondpadup=function(e){this._ondpadup=e},t.prototype._setButtonValue=function(e,n,i){return e!==n&&(e===1&&(this._onbuttondown&&this._onbuttondown(i),this.onButtonDownObservable.notifyObservers(i)),e===0&&(this._onbuttonup&&this._onbuttonup(i),this.onButtonUpObservable.notifyObservers(i))),e},t.prototype._setDPadValue=function(e,n,i){return e!==n&&(e===1&&(this._ondpaddown&&this._ondpaddown(i),this.onPadDownObservable.notifyObservers(i)),e===0&&(this._ondpadup&&this._ondpadup(i),this.onPadUpObservable.notifyObservers(i))),e},Object.defineProperty(t.prototype,"buttonA",{get:function(){return this._buttonA},set:function(e){this._buttonA=this._setButtonValue(e,this._buttonA,Rn.A)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonB",{get:function(){return this._buttonB},set:function(e){this._buttonB=this._setButtonValue(e,this._buttonB,Rn.B)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonX",{get:function(){return this._buttonX},set:function(e){this._buttonX=this._setButtonValue(e,this._buttonX,Rn.X)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonY",{get:function(){return this._buttonY},set:function(e){this._buttonY=this._setButtonValue(e,this._buttonY,Rn.Y)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonStart",{get:function(){return this._buttonStart},set:function(e){this._buttonStart=this._setButtonValue(e,this._buttonStart,Rn.Start)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonBack",{get:function(){return this._buttonBack},set:function(e){this._buttonBack=this._setButtonValue(e,this._buttonBack,Rn.Back)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonLB",{get:function(){return this._buttonLB},set:function(e){this._buttonLB=this._setButtonValue(e,this._buttonLB,Rn.LB)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonRB",{get:function(){return this._buttonRB},set:function(e){this._buttonRB=this._setButtonValue(e,this._buttonRB,Rn.RB)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonLeftStick",{get:function(){return this._buttonLeftStick},set:function(e){this._buttonLeftStick=this._setButtonValue(e,this._buttonLeftStick,Rn.LeftStick)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonRightStick",{get:function(){return this._buttonRightStick},set:function(e){this._buttonRightStick=this._setButtonValue(e,this._buttonRightStick,Rn.RightStick)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dPadUp",{get:function(){return this._dPadUp},set:function(e){this._dPadUp=this._setDPadValue(e,this._dPadUp,$i.Up)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dPadDown",{get:function(){return this._dPadDown},set:function(e){this._dPadDown=this._setDPadValue(e,this._dPadDown,$i.Down)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dPadLeft",{get:function(){return this._dPadLeft},set:function(e){this._dPadLeft=this._setDPadValue(e,this._dPadLeft,$i.Left)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dPadRight",{get:function(){return this._dPadRight},set:function(e){this._dPadRight=this._setDPadValue(e,this._dPadRight,$i.Right)},enumerable:!1,configurable:!0}),t.prototype.update=function(){r.prototype.update.call(this),this._isXboxOnePad,this.buttonA=this.browserGamepad.buttons[0].value,this.buttonB=this.browserGamepad.buttons[1].value,this.buttonX=this.browserGamepad.buttons[2].value,this.buttonY=this.browserGamepad.buttons[3].value,this.buttonLB=this.browserGamepad.buttons[4].value,this.buttonRB=this.browserGamepad.buttons[5].value,this.leftTrigger=this.browserGamepad.buttons[6].value,this.rightTrigger=this.browserGamepad.buttons[7].value,this.buttonBack=this.browserGamepad.buttons[8].value,this.buttonStart=this.browserGamepad.buttons[9].value,this.buttonLeftStick=this.browserGamepad.buttons[10].value,this.buttonRightStick=this.browserGamepad.buttons[11].value,this.dPadUp=this.browserGamepad.buttons[12].value,this.dPadDown=this.browserGamepad.buttons[13].value,this.dPadLeft=this.browserGamepad.buttons[14].value,this.dPadRight=this.browserGamepad.buttons[15].value},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onButtonDownObservable.clear(),this.onButtonUpObservable.clear(),this.onPadDownObservable.clear(),this.onPadUpObservable.clear()},t}(dn);(function(r){r[r.Cross=0]="Cross",r[r.Circle=1]="Circle",r[r.Square=2]="Square",r[r.Triangle=3]="Triangle",r[r.L1=4]="L1",r[r.R1=5]="R1",r[r.Share=8]="Share",r[r.Options=9]="Options",r[r.LeftStick=10]="LeftStick",r[r.RightStick=11]="RightStick"})(Gn||(Gn={})),function(r){r[r.Up=12]="Up",r[r.Down=13]="Down",r[r.Left=14]="Left",r[r.Right=15]="Right"}(er||(er={}));var xl=function(r){function t(e,n,i){var o=r.call(this,e.replace("STANDARD GAMEPAD","SONY PLAYSTATION DUALSHOCK"),n,i,0,1,2,3)||this;return o._leftTrigger=0,o._rightTrigger=0,o.onButtonDownObservable=new x.c,o.onButtonUpObservable=new x.c,o.onPadDownObservable=new x.c,o.onPadUpObservable=new x.c,o._buttonCross=0,o._buttonCircle=0,o._buttonSquare=0,o._buttonTriangle=0,o._buttonShare=0,o._buttonOptions=0,o._buttonL1=0,o._buttonR1=0,o._buttonLeftStick=0,o._buttonRightStick=0,o._dPadUp=0,o._dPadDown=0,o._dPadLeft=0,o._dPadRight=0,o.type=dn.DUALSHOCK,o}return Object(c.d)(t,r),t.prototype.onlefttriggerchanged=function(e){this._onlefttriggerchanged=e},t.prototype.onrighttriggerchanged=function(e){this._onrighttriggerchanged=e},Object.defineProperty(t.prototype,"leftTrigger",{get:function(){return this._leftTrigger},set:function(e){this._onlefttriggerchanged&&this._leftTrigger!==e&&this._onlefttriggerchanged(e),this._leftTrigger=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rightTrigger",{get:function(){return this._rightTrigger},set:function(e){this._onrighttriggerchanged&&this._rightTrigger!==e&&this._onrighttriggerchanged(e),this._rightTrigger=e},enumerable:!1,configurable:!0}),t.prototype.onbuttondown=function(e){this._onbuttondown=e},t.prototype.onbuttonup=function(e){this._onbuttonup=e},t.prototype.ondpaddown=function(e){this._ondpaddown=e},t.prototype.ondpadup=function(e){this._ondpadup=e},t.prototype._setButtonValue=function(e,n,i){return e!==n&&(e===1&&(this._onbuttondown&&this._onbuttondown(i),this.onButtonDownObservable.notifyObservers(i)),e===0&&(this._onbuttonup&&this._onbuttonup(i),this.onButtonUpObservable.notifyObservers(i))),e},t.prototype._setDPadValue=function(e,n,i){return e!==n&&(e===1&&(this._ondpaddown&&this._ondpaddown(i),this.onPadDownObservable.notifyObservers(i)),e===0&&(this._ondpadup&&this._ondpadup(i),this.onPadUpObservable.notifyObservers(i))),e},Object.defineProperty(t.prototype,"buttonCross",{get:function(){return this._buttonCross},set:function(e){this._buttonCross=this._setButtonValue(e,this._buttonCross,Gn.Cross)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonCircle",{get:function(){return this._buttonCircle},set:function(e){this._buttonCircle=this._setButtonValue(e,this._buttonCircle,Gn.Circle)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonSquare",{get:function(){return this._buttonSquare},set:function(e){this._buttonSquare=this._setButtonValue(e,this._buttonSquare,Gn.Square)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonTriangle",{get:function(){return this._buttonTriangle},set:function(e){this._buttonTriangle=this._setButtonValue(e,this._buttonTriangle,Gn.Triangle)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonOptions",{get:function(){return this._buttonOptions},set:function(e){this._buttonOptions=this._setButtonValue(e,this._buttonOptions,Gn.Options)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonShare",{get:function(){return this._buttonShare},set:function(e){this._buttonShare=this._setButtonValue(e,this._buttonShare,Gn.Share)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonL1",{get:function(){return this._buttonL1},set:function(e){this._buttonL1=this._setButtonValue(e,this._buttonL1,Gn.L1)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonR1",{get:function(){return this._buttonR1},set:function(e){this._buttonR1=this._setButtonValue(e,this._buttonR1,Gn.R1)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonLeftStick",{get:function(){return this._buttonLeftStick},set:function(e){this._buttonLeftStick=this._setButtonValue(e,this._buttonLeftStick,Gn.LeftStick)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonRightStick",{get:function(){return this._buttonRightStick},set:function(e){this._buttonRightStick=this._setButtonValue(e,this._buttonRightStick,Gn.RightStick)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dPadUp",{get:function(){return this._dPadUp},set:function(e){this._dPadUp=this._setDPadValue(e,this._dPadUp,er.Up)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dPadDown",{get:function(){return this._dPadDown},set:function(e){this._dPadDown=this._setDPadValue(e,this._dPadDown,er.Down)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dPadLeft",{get:function(){return this._dPadLeft},set:function(e){this._dPadLeft=this._setDPadValue(e,this._dPadLeft,er.Left)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dPadRight",{get:function(){return this._dPadRight},set:function(e){this._dPadRight=this._setDPadValue(e,this._dPadRight,er.Right)},enumerable:!1,configurable:!0}),t.prototype.update=function(){r.prototype.update.call(this),this.buttonCross=this.browserGamepad.buttons[0].value,this.buttonCircle=this.browserGamepad.buttons[1].value,this.buttonSquare=this.browserGamepad.buttons[2].value,this.buttonTriangle=this.browserGamepad.buttons[3].value,this.buttonL1=this.browserGamepad.buttons[4].value,this.buttonR1=this.browserGamepad.buttons[5].value,this.leftTrigger=this.browserGamepad.buttons[6].value,this.rightTrigger=this.browserGamepad.buttons[7].value,this.buttonShare=this.browserGamepad.buttons[8].value,this.buttonOptions=this.browserGamepad.buttons[9].value,this.buttonLeftStick=this.browserGamepad.buttons[10].value,this.buttonRightStick=this.browserGamepad.buttons[11].value,this.dPadUp=this.browserGamepad.buttons[12].value,this.dPadDown=this.browserGamepad.buttons[13].value,this.dPadLeft=this.browserGamepad.buttons[14].value,this.dPadRight=this.browserGamepad.buttons[15].value},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onButtonDownObservable.clear(),this.onButtonUpObservable.clear(),this.onPadDownObservable.clear(),this.onPadUpObservable.clear()},t}(dn),Rl=function(){function r(t){var e=this;if(this._scene=t,this._babylonGamepads=[],this._oneGamepadConnected=!1,this._isMonitoring=!1,this.onGamepadDisconnectedObservable=new x.c,cs.a.IsWindowObjectExist()?(this._gamepadEventSupported="GamepadEvent"in window,this._gamepadSupport=navigator.getGamepads||navigator.webkitGetGamepads||navigator.msGetGamepads||navigator.webkitGamepads):this._gamepadEventSupported=!1,this.onGamepadConnectedObservable=new x.c(function(i){for(var o in e._babylonGamepads){var a=e._babylonGamepads[o];a&&a._isConnected&&e.onGamepadConnectedObservable.notifyObserver(i,a)}}),this._onGamepadConnectedEvent=function(i){var o,a=i.gamepad;a.index in e._babylonGamepads&&e._babylonGamepads[a.index].isConnected||(e._babylonGamepads[a.index]?((o=e._babylonGamepads[a.index]).browserGamepad=a,o._isConnected=!0):o=e._addNewGamepad(a),e.onGamepadConnectedObservable.notifyObservers(o),e._startMonitoringGamepads())},this._onGamepadDisconnectedEvent=function(i){var o=i.gamepad;for(var a in e._babylonGamepads)if(e._babylonGamepads[a].index===o.index){var s=e._babylonGamepads[a];s._isConnected=!1,e.onGamepadDisconnectedObservable.notifyObservers(s),s.dispose&&s.dispose();break}},this._gamepadSupport)if(this._updateGamepadObjects(),this._babylonGamepads.length&&this._startMonitoringGamepads(),this._gamepadEventSupported){var n=this._scene?this._scene.getEngine().getHostWindow():window;n&&(n.addEventListener("gamepadconnected",this._onGamepadConnectedEvent,!1),n.addEventListener("gamepaddisconnected",this._onGamepadDisconnectedEvent,!1))}else this._startMonitoringGamepads()}return Object.defineProperty(r.prototype,"gamepads",{get:function(){return this._babylonGamepads},enumerable:!1,configurable:!0}),r.prototype.getGamepadByType=function(t){t===void 0&&(t=dn.XBOX);for(var e=0,n=this._babylonGamepads;e<n.length;e++){var i=n[e];if(i&&i.type===t)return i}return null},r.prototype.dispose=function(){this._gamepadEventSupported&&(this._onGamepadConnectedEvent&&window.removeEventListener("gamepadconnected",this._onGamepadConnectedEvent),this._onGamepadDisconnectedEvent&&window.removeEventListener("gamepaddisconnected",this._onGamepadDisconnectedEvent),this._onGamepadConnectedEvent=null,this._onGamepadDisconnectedEvent=null),this._babylonGamepads.forEach(function(t){t.dispose()}),this.onGamepadConnectedObservable.clear(),this.onGamepadDisconnectedObservable.clear(),this._oneGamepadConnected=!1,this._stopMonitoringGamepads(),this._babylonGamepads=[]},r.prototype._addNewGamepad=function(t){var e;this._oneGamepadConnected||(this._oneGamepadConnected=!0);var n=t.id.search("054c")!==-1,i=t.id.search("Xbox One")!==-1;return e=i||t.id.search("Xbox 360")!==-1||t.id.search("xinput")!==-1?new Cl(t.id,t.index,t,i):n?new xl(t.id,t.index,t):t.pose?wi.InitiateController(t):new bl(t.id,t.index,t),this._babylonGamepads[e.index]=e,e},r.prototype._startMonitoringGamepads=function(){this._isMonitoring||(this._isMonitoring=!0,this._scene||this._checkGamepadsStatus())},r.prototype._stopMonitoringGamepads=function(){this._isMonitoring=!1},r.prototype._checkGamepadsStatus=function(){var t=this;for(var e in this._updateGamepadObjects(),this._babylonGamepads){var n=this._babylonGamepads[e];n&&n.isConnected&&n.update()}this._isMonitoring&&!this._scene&&Ue.a.QueueNewFrame(function(){t._checkGamepadsStatus()})},r.prototype._updateGamepadObjects=function(){for(var t=navigator.getGamepads?navigator.getGamepads():navigator.webkitGetGamepads?navigator.webkitGetGamepads():[],e=0;e<t.length;e++){var n=t[e];if(n)if(this._babylonGamepads[n.index])this._babylonGamepads[e].browserGamepad=n,this._babylonGamepads[e].isConnected||(this._babylonGamepads[e]._isConnected=!0,this.onGamepadConnectedObservable.notifyObservers(this._babylonGamepads[e]));else{var i=this._addNewGamepad(n);this.onGamepadConnectedObservable.notifyObservers(i)}}},r}();Object.defineProperty(_e.a.prototype,"gamepadManager",{get:function(){if(!this._gamepadManager){this._gamepadManager=new Rl(this);var r=this._getComponent(at.a.NAME_GAMEPAD);r||(r=new Ol(this),this._addComponent(r))}return this._gamepadManager},enumerable:!0,configurable:!0}),eo.prototype.addGamepad=function(){return this.add(new rs),this},wo.prototype.addGamepad=function(){return this.add(new ja),this};var Ol=function(){function r(t){this.name=at.a.NAME_GAMEPAD,this.scene=t}return r.prototype.register=function(){this.scene._beforeCameraUpdateStage.registerStep(at.a.STEP_BEFORECAMERAUPDATE_GAMEPAD,this,this._beforeCameraUpdate)},r.prototype.rebuild=function(){},r.prototype.dispose=function(){var t=this.scene._gamepadManager;t&&(t.dispose(),this.scene._gamepadManager=null)},r.prototype._beforeCameraUpdate=function(){var t=this.scene._gamepadManager;t&&t._isMonitoring&&t._checkGamepadsStatus()},r}();Q.a.AddNodeConstructor("FreeCamera",function(r,t){return function(){return new _r(r,u.e.Zero(),t)}});var _r=function(r){function t(e,n,i){var o=r.call(this,e,n,i)||this;return o.inputs.addGamepad(),o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"gamepadAngularSensibility",{get:function(){var e=this.inputs.attached.gamepad;return e?e.gamepadAngularSensibility:0},set:function(e){var n=this.inputs.attached.gamepad;n&&(n.gamepadAngularSensibility=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"gamepadMoveSensibility",{get:function(){var e=this.inputs.attached.gamepad;return e?e.gamepadMoveSensibility:0},set:function(e){var n=this.inputs.attached.gamepad;n&&(n.gamepadMoveSensibility=e)},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"UniversalCamera"},t}(ss);gt.a._createDefaultParsedCamera=function(r,t){return new _r(r,u.e.Zero(),t)},Q.a.AddNodeConstructor("GamepadCamera",function(r,t){return function(){return new Bo(r,u.e.Zero(),t)}});var Bo=function(r){function t(e,n,i){return r.call(this,e,n,i)||this}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"GamepadCamera"},t}(_r),fi=f(33),ze=f(5),kf=`
-attribute vec2 position;
-uniform vec2 scale;
-
-varying vec2 vUV;
-const vec2 madd=vec2(0.5,0.5);
-void main(void) {
-vUV=(position*madd+madd)*scale;
-gl_Position=vec4(position,0.0,1.0);
-}`;ze.a.ShadersStore.postprocessVertexShader=kf;var Ml=f(102);Bt.a.prototype.createRenderTargetTexture=function(r,t){var e=new Ml.a;t!==void 0&&typeof t=="object"?(e.generateMipMaps=t.generateMipMaps,e.generateDepthBuffer=!!t.generateDepthBuffer,e.generateStencilBuffer=!!t.generateStencilBuffer,e.type=t.type===void 0?h.a.TEXTURETYPE_UNSIGNED_INT:t.type,e.samplingMode=t.samplingMode===void 0?h.a.TEXTURE_TRILINEAR_SAMPLINGMODE:t.samplingMode,e.format=t.format===void 0?h.a.TEXTUREFORMAT_RGBA:t.format):(e.generateMipMaps=t,e.generateDepthBuffer=!0,e.generateStencilBuffer=!1,e.type=h.a.TEXTURETYPE_UNSIGNED_INT,e.samplingMode=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE,e.format=h.a.TEXTUREFORMAT_RGBA),(e.type!==h.a.TEXTURETYPE_FLOAT||this._caps.textureFloatLinearFiltering)&&(e.type!==h.a.TEXTURETYPE_HALF_FLOAT||this._caps.textureHalfFloatLinearFiltering)||(e.samplingMode=h.a.TEXTURE_NEAREST_SAMPLINGMODE),e.type!==h.a.TEXTURETYPE_FLOAT||this._caps.textureFloat||(e.type=h.a.TEXTURETYPE_UNSIGNED_INT,l.a.Warn("Float textures are not supported. Render target forced to TEXTURETYPE_UNSIGNED_BYTE type"));var n=this._gl,i=new xt.a(this,xt.b.RenderTarget),o=r.width||r,a=r.height||r,s=r.layers||0,d=this._getSamplingParameters(e.samplingMode,!!e.generateMipMaps),p=s!==0?n.TEXTURE_2D_ARRAY:n.TEXTURE_2D,b=this._getRGBABufferInternalSizedFormat(e.type,e.format),P=this._getInternalFormat(e.format),O=this._getWebGLTextureType(e.type);this._bindTextureDirectly(p,i),s!==0?(i.is2DArray=!0,n.texImage3D(p,0,b,o,a,s,0,P,O,null)):n.texImage2D(p,0,b,o,a,0,P,O,null),n.texParameteri(p,n.TEXTURE_MAG_FILTER,d.mag),n.texParameteri(p,n.TEXTURE_MIN_FILTER,d.min),n.texParameteri(p,n.TEXTURE_WRAP_S,n.CLAMP_TO_EDGE),n.texParameteri(p,n.TEXTURE_WRAP_T,n.CLAMP_TO_EDGE),e.generateMipMaps&&this._gl.generateMipmap(p),this._bindTextureDirectly(p,null);var B=this._currentFramebuffer,F=n.createFramebuffer();return this._bindUnboundFramebuffer(F),i._depthStencilBuffer=this._setupFramebufferDepthAttachments(!!e.generateStencilBuffer,e.generateDepthBuffer,o,a),i.is2DArray||n.framebufferTexture2D(n.FRAMEBUFFER,n.COLOR_ATTACHMENT0,n.TEXTURE_2D,i._webGLTexture,0),this._bindUnboundFramebuffer(B),i._framebuffer=F,i.baseWidth=o,i.baseHeight=a,i.width=o,i.height=a,i.depth=s,i.isReady=!0,i.samples=1,i.generateMipMaps=!!e.generateMipMaps,i.samplingMode=e.samplingMode,i.type=e.type,i.format=e.format,i._generateDepthBuffer=e.generateDepthBuffer,i._generateStencilBuffer=!!e.generateStencilBuffer,this._internalTexturesCache.push(i),i},Bt.a.prototype.createDepthStencilTexture=function(r,t){if(t.isCube){var e=r.width||r;return this._createDepthStencilCubeTexture(e,t)}return this._createDepthStencilTexture(r,t)},Bt.a.prototype._createDepthStencilTexture=function(r,t){var e=this._gl,n=r.layers||0,i=n!==0?e.TEXTURE_2D_ARRAY:e.TEXTURE_2D,o=new xt.a(this,xt.b.Depth);if(!this._caps.depthTextureExtension)return l.a.Error("Depth texture is not supported by your browser or hardware."),o;var a=Object(c.a)({bilinearFiltering:!1,comparisonFunction:0,generateStencil:!1},t);this._bindTextureDirectly(i,o,!0),this._setupDepthStencilTexture(o,r,a.generateStencil,a.bilinearFiltering,a.comparisonFunction);var s=a.generateStencil?e.UNSIGNED_INT_24_8:e.UNSIGNED_INT,d=a.generateStencil?e.DEPTH_STENCIL:e.DEPTH_COMPONENT,p=d;return this.webGLVersion>1&&(p=a.generateStencil?e.DEPTH24_STENCIL8:e.DEPTH_COMPONENT24),o.is2DArray?e.texImage3D(i,0,p,o.width,o.height,n,0,d,s,null):e.texImage2D(i,0,p,o.width,o.height,0,d,s,null),this._bindTextureDirectly(i,null),o};var _t=function(){function r(t,e,n,i,o,a,s,d,p,b,P,O,B,F,z){s===void 0&&(s=h.a.TEXTURE_NEAREST_SAMPLINGMODE),b===void 0&&(b=null),P===void 0&&(P=h.a.TEXTURETYPE_UNSIGNED_INT),O===void 0&&(O="postprocess"),F===void 0&&(F=!1),z===void 0&&(z=h.a.TEXTUREFORMAT_RGBA),this.width=-1,this.height=-1,this.nodeMaterialSource=null,this._outputTexture=null,this.autoClear=!0,this.alphaMode=h.a.ALPHA_DISABLE,this.animations=new Array,this.enablePixelPerfectMode=!1,this.forceFullscreenViewport=!0,this.scaleMode=h.a.SCALEMODE_FLOOR,this.alwaysForcePOT=!1,this._samples=1,this.adaptScaleToCurrentViewport=!1,this._reusable=!1,this._textures=new fi.a(2),this._currentRenderTextureInd=0,this._scaleRatio=new u.d(1,1),this._texelSize=u.d.Zero(),this.onActivateObservable=new x.c,this.onSizeChangedObservable=new x.c,this.onApplyObservable=new x.c,this.onBeforeRenderObservable=new x.c,this.onAfterRenderObservable=new x.c,this.name=t,a!=null?(this._camera=a,this._scene=a.getScene(),a.attachPostProcess(this),this._engine=this._scene.getEngine(),this._scene.postProcesses.push(this),this.uniqueId=this._scene.getUniqueId()):d&&(this._engine=d,this._engine.postProcesses.push(this)),this._options=o,this.renderTargetSamplingMode=s||h.a.TEXTURE_NEAREST_SAMPLINGMODE,this._reusable=p||!1,this._textureType=P,this._textureFormat=z,this._samplers=i||[],this._samplers.push("textureSampler"),this._fragmentUrl=e,this._vertexUrl=O,this._parameters=n||[],this._parameters.push("scale"),this._indexParameters=B,F||this.updateEffect(b)}return Object.defineProperty(r.prototype,"samples",{get:function(){return this._samples},set:function(t){var e=this;this._samples=Math.min(t,this._engine.getCaps().maxMSAASamples),this._textures.forEach(function(n){n.samples!==e._samples&&e._engine.updateRenderTargetTextureSampleCount(n,e._samples)})},enumerable:!1,configurable:!0}),r.prototype.getEffectName=function(){return this._fragmentUrl},Object.defineProperty(r.prototype,"onActivate",{set:function(t){this._onActivateObserver&&this.onActivateObservable.remove(this._onActivateObserver),t&&(this._onActivateObserver=this.onActivateObservable.add(t))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"onSizeChanged",{set:function(t){this._onSizeChangedObserver&&this.onSizeChangedObservable.remove(this._onSizeChangedObserver),this._onSizeChangedObserver=this.onSizeChangedObservable.add(t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"onApply",{set:function(t){this._onApplyObserver&&this.onApplyObservable.remove(this._onApplyObserver),this._onApplyObserver=this.onApplyObservable.add(t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"onBeforeRender",{set:function(t){this._onBeforeRenderObserver&&this.onBeforeRenderObservable.remove(this._onBeforeRenderObserver),this._onBeforeRenderObserver=this.onBeforeRenderObservable.add(t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"onAfterRender",{set:function(t){this._onAfterRenderObserver&&this.onAfterRenderObservable.remove(this._onAfterRenderObserver),this._onAfterRenderObserver=this.onAfterRenderObservable.add(t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"inputTexture",{get:function(){return this._textures.data[this._currentRenderTextureInd]},set:function(t){this._forcedOutputTexture=t},enumerable:!1,configurable:!0}),r.prototype.restoreDefaultInputTexture=function(){this._forcedOutputTexture=null},r.prototype.getCamera=function(){return this._camera},Object.defineProperty(r.prototype,"texelSize",{get:function(){return this._shareOutputWithPostProcess?this._shareOutputWithPostProcess.texelSize:(this._forcedOutputTexture&&this._texelSize.copyFromFloats(1/this._forcedOutputTexture.width,1/this._forcedOutputTexture.height),this._texelSize)},enumerable:!1,configurable:!0}),r.prototype.getClassName=function(){return"PostProcess"},r.prototype.getEngine=function(){return this._engine},r.prototype.getEffect=function(){return this._effect},r.prototype.shareOutputWith=function(t){return this._disposeTextures(),this._shareOutputWithPostProcess=t,this},r.prototype.useOwnOutput=function(){this._textures.length==0&&(this._textures=new fi.a(2)),this._shareOutputWithPostProcess=null},r.prototype.updateEffect=function(t,e,n,i,o,a,s,d){t===void 0&&(t=null),e===void 0&&(e=null),n===void 0&&(n=null),this._effect=this._engine.createEffect({vertex:s??this._vertexUrl,fragment:d??this._fragmentUrl},["position"],e||this._parameters,n||this._samplers,t!==null?t:"",void 0,o,a,i||this._indexParameters)},r.prototype.isReusable=function(){return this._reusable},r.prototype.markTextureDirty=function(){this.width=-1},r.prototype.activate=function(t,e,n){var i=this;e===void 0&&(e=null);var o=(t=t||this._camera).getScene(),a=o.getEngine(),s=a.getCaps().maxTextureSize,d=(e?e.width:this._engine.getRenderWidth(!0))*this._options|0,p=(e?e.height:this._engine.getRenderHeight(!0))*this._options|0,b=t.parent;!b||b.leftCamera!=t&&b.rightCamera!=t||(d/=2);var P,O=this._options.width||d,B=this._options.height||p,F=this.renderTargetSamplingMode!==h.a.TEXTURE_NEAREST_LINEAR&&this.renderTargetSamplingMode!==h.a.TEXTURE_NEAREST_NEAREST&&this.renderTargetSamplingMode!==h.a.TEXTURE_LINEAR_LINEAR;if(!this._shareOutputWithPostProcess&&!this._forcedOutputTexture){if(this.adaptScaleToCurrentViewport){var z=a.currentViewport;z&&(O*=z.width,B*=z.height)}if((F||this.alwaysForcePOT)&&(this._options.width||(O=a.needPOTTextures?Ue.a.GetExponentOfTwo(O,s,this.scaleMode):O),this._options.height||(B=a.needPOTTextures?Ue.a.GetExponentOfTwo(B,s,this.scaleMode):B)),this.width!==O||this.height!==B){if(this._textures.length>0){for(var J=0;J<this._textures.length;J++)this._engine._releaseTexture(this._textures.data[J]);this._textures.reset()}this.width=O,this.height=B;var ie={width:this.width,height:this.height},se={generateMipMaps:F,generateDepthBuffer:n||t._postProcesses.indexOf(this)===0,generateStencilBuffer:(n||t._postProcesses.indexOf(this)===0)&&this._engine.isStencilEnable,samplingMode:this.renderTargetSamplingMode,type:this._textureType,format:this._textureFormat};this._textures.push(this._engine.createRenderTargetTexture(ie,se)),this._reusable&&this._textures.push(this._engine.createRenderTargetTexture(ie,se)),this._texelSize.copyFromFloats(1/this.width,1/this.height),this.onSizeChangedObservable.notifyObservers(this)}this._textures.forEach(function(ce){ce.samples!==i.samples&&i._engine.updateRenderTargetTextureSampleCount(ce,i.samples)})}return this._shareOutputWithPostProcess?P=this._shareOutputWithPostProcess.inputTexture:this._forcedOutputTexture?(P=this._forcedOutputTexture,this.width=this._forcedOutputTexture.width,this.height=this._forcedOutputTexture.height):P=this.inputTexture,this.enablePixelPerfectMode?(this._scaleRatio.copyFromFloats(d/O,p/B),this._engine.bindFramebuffer(P,0,d,p,this.forceFullscreenViewport)):(this._scaleRatio.copyFromFloats(1,1),this._engine.bindFramebuffer(P,0,void 0,void 0,this.forceFullscreenViewport)),this.onActivateObservable.notifyObservers(t),this.autoClear&&this.alphaMode===h.a.ALPHA_DISABLE&&this._engine.clear(this.clearColor?this.clearColor:o.clearColor,o._allowPostProcessClearColor,!0,!0),this._reusable&&(this._currentRenderTextureInd=(this._currentRenderTextureInd+1)%2),P},Object.defineProperty(r.prototype,"isSupported",{get:function(){return this._effect.isSupported},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"aspectRatio",{get:function(){return this._shareOutputWithPostProcess?this._shareOutputWithPostProcess.aspectRatio:this._forcedOutputTexture?this._forcedOutputTexture.width/this._forcedOutputTexture.height:this.width/this.height},enumerable:!1,configurable:!0}),r.prototype.isReady=function(){return this._effect&&this._effect.isReady()},r.prototype.apply=function(){return this._effect&&this._effect.isReady()?(this._engine.enableEffect(this._effect),this._engine.setState(!1),this._engine.setDepthBuffer(!1),this._engine.setDepthWrite(!1),this._engine.setAlphaMode(this.alphaMode),this.alphaConstants&&this.getEngine().setAlphaConstants(this.alphaConstants.r,this.alphaConstants.g,this.alphaConstants.b,this.alphaConstants.a),t=this._shareOutputWithPostProcess?this._shareOutputWithPostProcess.inputTexture:this._forcedOutputTexture?this._forcedOutputTexture:this.inputTexture,this._effect._bindTexture("textureSampler",t),this._effect.setVector2("scale",this._scaleRatio),this.onApplyObservable.notifyObservers(this._effect),this._effect):null;var t},r.prototype._disposeTextures=function(){if(!this._shareOutputWithPostProcess&&!this._forcedOutputTexture){if(this._textures.length>0)for(var t=0;t<this._textures.length;t++)this._engine._releaseTexture(this._textures.data[t]);this._textures.dispose()}},r.prototype.setPrePassRenderer=function(t){return!!this._prePassEffectConfiguration&&(this._prePassEffectConfiguration=t.addEffectConfiguration(this._prePassEffectConfiguration),this._prePassEffectConfiguration.enabled=!0,!0)},r.prototype.dispose=function(t){var e;if(t=t||this._camera,this._disposeTextures(),this._scene&&(e=this._scene.postProcesses.indexOf(this))!==-1&&this._scene.postProcesses.splice(e,1),(e=this._engine.postProcesses.indexOf(this))!==-1&&this._engine.postProcesses.splice(e,1),t){if(t.detachPostProcess(this),(e=t._postProcesses.indexOf(this))===0&&t._postProcesses.length>0){var n=this._camera._getFirstPostProcess();n&&n.markTextureDirty()}this.onActivateObservable.clear(),this.onAfterRenderObservable.clear(),this.onApplyObservable.clear(),this.onBeforeRenderObservable.clear(),this.onSizeChangedObservable.clear()}},r.prototype.serialize=function(){var t=L.a.Serialize(this);return t.customType="BABYLON."+this.getClassName(),t.cameraId=this.getCamera().id,t.reusable=this._reusable,t.options=this._options,t.textureType=this._textureType,t},r.Parse=function(t,e,n){var i=R.a.GetClass(t.customType);if(!i||!i._Parse)return null;var o=e.getCameraByID(t.cameraId);return o?i._Parse(t,o,e,n):null},Object(c.c)([Object(L.c)()],r.prototype,"uniqueId",void 0),Object(c.c)([Object(L.c)()],r.prototype,"name",void 0),Object(c.c)([Object(L.c)()],r.prototype,"width",void 0),Object(c.c)([Object(L.c)()],r.prototype,"height",void 0),Object(c.c)([Object(L.c)()],r.prototype,"renderTargetSamplingMode",void 0),Object(c.c)([Object(L.f)()],r.prototype,"clearColor",void 0),Object(c.c)([Object(L.c)()],r.prototype,"autoClear",void 0),Object(c.c)([Object(L.c)()],r.prototype,"alphaMode",void 0),Object(c.c)([Object(L.c)()],r.prototype,"alphaConstants",void 0),Object(c.c)([Object(L.c)()],r.prototype,"enablePixelPerfectMode",void 0),Object(c.c)([Object(L.c)()],r.prototype,"forceFullscreenViewport",void 0),Object(c.c)([Object(L.c)()],r.prototype,"scaleMode",void 0),Object(c.c)([Object(L.c)()],r.prototype,"alwaysForcePOT",void 0),Object(c.c)([Object(L.c)("samples")],r.prototype,"_samples",void 0),Object(c.c)([Object(L.c)()],r.prototype,"adaptScaleToCurrentViewport",void 0),r}();R.a.RegisteredTypes["BABYLON.PostProcess"]=_t;var Gf=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-void main(void)
-{
-gl_FragColor=texture2D(textureSampler,vUV);
-}`;ze.a.ShadersStore.passPixelShader=Gf;var zf=`
-varying vec2 vUV;
-uniform samplerCube textureSampler;
-void main(void)
-{
-vec2 uv=vUV*2.0-1.0;
-#ifdef POSITIVEX
-gl_FragColor=textureCube(textureSampler,vec3(1.001,uv.y,uv.x));
-#endif
-#ifdef NEGATIVEX
-gl_FragColor=textureCube(textureSampler,vec3(-1.001,uv.y,uv.x));
-#endif
-#ifdef POSITIVEY
-gl_FragColor=textureCube(textureSampler,vec3(uv.y,1.001,uv.x));
-#endif
-#ifdef NEGATIVEY
-gl_FragColor=textureCube(textureSampler,vec3(uv.y,-1.001,uv.x));
-#endif
-#ifdef POSITIVEZ
-gl_FragColor=textureCube(textureSampler,vec3(uv,1.001));
-#endif
-#ifdef NEGATIVEZ
-gl_FragColor=textureCube(textureSampler,vec3(uv,-1.001));
-#endif
-}`;ze.a.ShadersStore.passCubePixelShader=zf;var Fi=function(r){function t(e,n,i,o,a,s,d,p){return i===void 0&&(i=null),d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT),p===void 0&&(p=!1),r.call(this,e,"pass",null,null,n,i,o,a,s,void 0,d,void 0,null,p)||this}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"PassPostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable)},e,i,o)},t}(_t);R.a.RegisteredTypes["BABYLON.PassPostProcess"]=Fi;var jf=function(r){function t(e,n,i,o,a,s,d,p){i===void 0&&(i=null),d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT),p===void 0&&(p=!1);var b=r.call(this,e,"passCube",null,null,n,i,o,a,s,"#define POSITIVEX",d,void 0,null,p)||this;return b._face=0,b}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"face",{get:function(){return this._face},set:function(e){if(!(e<0||e>5))switch(this._face=e,this._face){case 0:this.updateEffect("#define POSITIVEX");break;case 1:this.updateEffect("#define NEGATIVEX");break;case 2:this.updateEffect("#define POSITIVEY");break;case 3:this.updateEffect("#define NEGATIVEY");break;case 4:this.updateEffect("#define POSITIVEZ");break;case 5:this.updateEffect("#define NEGATIVEZ")}},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"PassCubePostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable)},e,i,o)},t}(_t);Ue.a._RescalePostProcessFactory=function(r){return new Fi("rescale",1,null,h.a.TEXTURE_BILINEAR_SAMPLINGMODE,r,!1,h.a.TEXTURETYPE_UNSIGNED_INT)};var Hf=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform sampler2D leftSampler;
-void main(void)
-{
-vec4 leftFrag=texture2D(leftSampler,vUV);
-leftFrag=vec4(1.0,leftFrag.g,leftFrag.b,1.0);
-vec4 rightFrag=texture2D(textureSampler,vUV);
-rightFrag=vec4(rightFrag.r,1.0,1.0,1.0);
-gl_FragColor=vec4(rightFrag.rgb*leftFrag.rgb,1.0);
-}`;ze.a.ShadersStore.anaglyphPixelShader=Hf;var ls=function(r){function t(e,n,i,o,a,s){var d=r.call(this,e,"anaglyph",null,["leftSampler"],n,i[1],o,a,s)||this;return d._passedProcess=i[0]._rigPostProcess,d.onApplyObservable.add(function(p){p.setTextureFromPostProcess("leftSampler",d._passedProcess)}),d}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"AnaglyphPostProcess"},t}(_t);R.a.RegisteredTypes["BABYLON.AnaglyphPostProcess"]=ls,gt.a._setStereoscopicAnaglyphRigMode=function(r){r._rigCameras[0]._rigPostProcess=new Fi(r.name+"_passthru",1,r._rigCameras[0]),r._rigCameras[1]._rigPostProcess=new ls(r.name+"_anaglyph",1,r._rigCameras)},Q.a.AddNodeConstructor("AnaglyphArcRotateCamera",function(r,t,e){return function(){return new Il(r,0,0,1,u.e.Zero(),e.interaxial_distance,t)}});var Il=function(r){function t(e,n,i,o,a,s,d){var p=r.call(this,e,n,i,o,a,d)||this;return p.interaxialDistance=s,p.setCameraRigMode(gt.a.RIG_MODE_STEREOSCOPIC_ANAGLYPH,{interaxialDistance:s}),p}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"AnaglyphArcRotateCamera"},t}(Ji);Q.a.AddNodeConstructor("AnaglyphFreeCamera",function(r,t,e){return function(){return new Dl(r,u.e.Zero(),e.interaxial_distance,t)}});var Dl=function(r){function t(e,n,i,o){var a=r.call(this,e,n,o)||this;return a.interaxialDistance=i,a.setCameraRigMode(gt.a.RIG_MODE_STEREOSCOPIC_ANAGLYPH,{interaxialDistance:i}),a}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"AnaglyphFreeCamera"},t}(Yn);Q.a.AddNodeConstructor("AnaglyphGamepadCamera",function(r,t,e){return function(){return new Ll(r,u.e.Zero(),e.interaxial_distance,t)}});var Ll=function(r){function t(e,n,i,o){var a=r.call(this,e,n,o)||this;return a.interaxialDistance=i,a.setCameraRigMode(gt.a.RIG_MODE_STEREOSCOPIC_ANAGLYPH,{interaxialDistance:i}),a}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"AnaglyphGamepadCamera"},t}(Bo);Q.a.AddNodeConstructor("AnaglyphUniversalCamera",function(r,t,e){return function(){return new Nl(r,u.e.Zero(),e.interaxial_distance,t)}});var Nl=function(r){function t(e,n,i,o){var a=r.call(this,e,n,o)||this;return a.interaxialDistance=i,a.setCameraRigMode(gt.a.RIG_MODE_STEREOSCOPIC_ANAGLYPH,{interaxialDistance:i}),a}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"AnaglyphUniversalCamera"},t}(_r),Kn=f(58);gt.a._setStereoscopicRigMode=function(r){var t=r.cameraRigMode===gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL||r.cameraRigMode===gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_CROSSEYED,e=r.cameraRigMode===gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_CROSSEYED;r._rigCameras[e?1:0].viewport=new Kn.a(0,0,t?.5:1,t?1:.5),r._rigCameras[e?0:1].viewport=new Kn.a(t?.5:0,t?0:.5,t?.5:1,t?1:.5)},Q.a.AddNodeConstructor("StereoscopicArcRotateCamera",function(r,t,e){return function(){return new wl(r,0,0,1,u.e.Zero(),e.interaxial_distance,e.isStereoscopicSideBySide,t)}});var wl=function(r){function t(e,n,i,o,a,s,d,p){var b=r.call(this,e,n,i,o,a,p)||this;return b.interaxialDistance=s,b.isStereoscopicSideBySide=d,b.setCameraRigMode(d?gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL:gt.a.RIG_MODE_STEREOSCOPIC_OVERUNDER,{interaxialDistance:s}),b}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"StereoscopicArcRotateCamera"},t}(Ji);Q.a.AddNodeConstructor("StereoscopicFreeCamera",function(r,t,e){return function(){return new Fl(r,u.e.Zero(),e.interaxial_distance,e.isStereoscopicSideBySide,t)}});var Fl=function(r){function t(e,n,i,o,a){var s=r.call(this,e,n,a)||this;return s.interaxialDistance=i,s.isStereoscopicSideBySide=o,s.setCameraRigMode(o?gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL:gt.a.RIG_MODE_STEREOSCOPIC_OVERUNDER,{interaxialDistance:i}),s}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"StereoscopicFreeCamera"},t}(Yn);Q.a.AddNodeConstructor("StereoscopicGamepadCamera",function(r,t,e){return function(){return new Bl(r,u.e.Zero(),e.interaxial_distance,e.isStereoscopicSideBySide,t)}});var Bl=function(r){function t(e,n,i,o,a){var s=r.call(this,e,n,a)||this;return s.interaxialDistance=i,s.isStereoscopicSideBySide=o,s.setCameraRigMode(o?gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL:gt.a.RIG_MODE_STEREOSCOPIC_OVERUNDER,{interaxialDistance:i}),s}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"StereoscopicGamepadCamera"},t}(Bo);Q.a.AddNodeConstructor("StereoscopicFreeCamera",function(r,t,e){return function(){return new Ul(r,u.e.Zero(),e.interaxial_distance,e.isStereoscopicSideBySide,t)}});var Ul=function(r){function t(e,n,i,o,a){var s=r.call(this,e,n,a)||this;return s.interaxialDistance=i,s.isStereoscopicSideBySide=o,s.setCameraRigMode(o?gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL:gt.a.RIG_MODE_STEREOSCOPIC_OVERUNDER,{interaxialDistance:i}),s}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"StereoscopicUniversalCamera"},t}(_r);Q.a.AddNodeConstructor("VirtualJoysticksCamera",function(r,t){return function(){return new Vl(r,u.e.Zero(),t)}});var Vl=function(r){function t(e,n,i){var o=r.call(this,e,n,i)||this;return o.inputs.addVirtualJoystick(),o}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"VirtualJoysticksCamera"},t}(Yn),mr=function(){function r(){this.compensateDistortion=!0,this.multiviewEnabled=!1}return Object.defineProperty(r.prototype,"aspectRatio",{get:function(){return this.hResolution/(2*this.vResolution)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"aspectRatioFov",{get:function(){return 2*Math.atan(this.postProcessScaleFactor*this.vScreenSize/(2*this.eyeToScreenDistance))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"leftHMatrix",{get:function(){var t=4*(this.hScreenSize/4-this.lensSeparationDistance/2)/this.hScreenSize;return u.a.Translation(t,0,0)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"rightHMatrix",{get:function(){var t=4*(this.hScreenSize/4-this.lensSeparationDistance/2)/this.hScreenSize;return u.a.Translation(-t,0,0)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"leftPreViewMatrix",{get:function(){return u.a.Translation(.5*this.interpupillaryDistance,0,0)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"rightPreViewMatrix",{get:function(){return u.a.Translation(-.5*this.interpupillaryDistance,0,0)},enumerable:!1,configurable:!0}),r.GetDefault=function(){var t=new r;return t.hResolution=1280,t.vResolution=800,t.hScreenSize=.149759993,t.vScreenSize=.0935999975,t.vScreenCenter=.0467999987,t.eyeToScreenDistance=.0410000011,t.lensSeparationDistance=.063500002,t.interpupillaryDistance=.064000003,t.distortionK=[1,.219999999,.239999995,0],t.chromaAbCorrection=[.995999992,-.00400000019,1.01400006,0],t.postProcessScaleFactor=1.714605507808412,t.lensCenterOffset=.151976421,t},r}(),Wf=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform vec2 LensCenter;
-uniform vec2 Scale;
-uniform vec2 ScaleIn;
-uniform vec4 HmdWarpParam;
-vec2 HmdWarp(vec2 in01) {
-vec2 theta=(in01-LensCenter)*ScaleIn;
-float rSq=theta.x*theta.x+theta.y*theta.y;
-vec2 rvector=theta*(HmdWarpParam.x+HmdWarpParam.y*rSq+HmdWarpParam.z*rSq*rSq+HmdWarpParam.w*rSq*rSq*rSq);
-return LensCenter+Scale*rvector;
-}
-void main(void)
-{
-vec2 tc=HmdWarp(vUV);
-if (tc.x <0.0 || tc.x>1.0 || tc.y<0.0 || tc.y>1.0)
-gl_FragColor=vec4(0.0,0.0,0.0,0.0);
-else{
-gl_FragColor=texture2D(textureSampler,tc);
-}
-}`;ze.a.ShadersStore.vrDistortionCorrectionPixelShader=Wf;var us=function(r){function t(e,n,i,o){var a=r.call(this,e,"vrDistortionCorrection",["LensCenter","Scale","ScaleIn","HmdWarpParam"],null,o.postProcessScaleFactor,n,we.a.BILINEAR_SAMPLINGMODE)||this;return a._isRightEye=i,a._distortionFactors=o.distortionK,a._postProcessScaleFactor=o.postProcessScaleFactor,a._lensCenterOffset=o.lensCenterOffset,a.adaptScaleToCurrentViewport=!0,a.onSizeChangedObservable.add(function(){a._scaleIn=new u.d(2,2/a.aspectRatio),a._scaleFactor=new u.d(1/a._postProcessScaleFactor*.5,1/a._postProcessScaleFactor*.5*a.aspectRatio),a._lensCenter=new u.d(a._isRightEye?.5-.5*a._lensCenterOffset:.5+.5*a._lensCenterOffset,.5)}),a.onApplyObservable.add(function(s){s.setFloat2("LensCenter",a._lensCenter.x,a._lensCenter.y),s.setFloat2("Scale",a._scaleFactor.x,a._scaleFactor.y),s.setFloat2("ScaleIn",a._scaleIn.x,a._scaleIn.y),s.setFloat4("HmdWarpParam",a._distortionFactors[0],a._distortionFactors[1],a._distortionFactors[2],a._distortionFactors[3])}),a}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"VRDistortionCorrectionPostProcess"},t}(_t),Xf=`precision mediump sampler2DArray;
-varying vec2 vUV;
-uniform sampler2DArray multiviewSampler;
-uniform int imageIndex;
-void main(void)
-{
-gl_FragColor=texture(multiviewSampler,vec3(vUV,imageIndex));
-}`;ze.a.ShadersStore.vrMultiviewToSingleviewPixelShader=Xf;var kl=f(85),hs=f(95),to=f(96);Bt.a.prototype.createRenderTargetCubeTexture=function(r,t){var e=Object(c.a)({generateMipMaps:!0,generateDepthBuffer:!0,generateStencilBuffer:!1,type:h.a.TEXTURETYPE_UNSIGNED_INT,samplingMode:h.a.TEXTURE_TRILINEAR_SAMPLINGMODE,format:h.a.TEXTUREFORMAT_RGBA},t);e.generateStencilBuffer=e.generateDepthBuffer&&e.generateStencilBuffer,(e.type!==h.a.TEXTURETYPE_FLOAT||this._caps.textureFloatLinearFiltering)&&(e.type!==h.a.TEXTURETYPE_HALF_FLOAT||this._caps.textureHalfFloatLinearFiltering)||(e.samplingMode=h.a.TEXTURE_NEAREST_SAMPLINGMODE);var n=this._gl,i=new xt.a(this,xt.b.RenderTarget);this._bindTextureDirectly(n.TEXTURE_CUBE_MAP,i,!0);var o=this._getSamplingParameters(e.samplingMode,e.generateMipMaps);e.type!==h.a.TEXTURETYPE_FLOAT||this._caps.textureFloat||(e.type=h.a.TEXTURETYPE_UNSIGNED_INT,l.a.Warn("Float textures are not supported. Cube render target forced to TEXTURETYPE_UNESIGNED_BYTE type")),n.texParameteri(n.TEXTURE_CUBE_MAP,n.TEXTURE_MAG_FILTER,o.mag),n.texParameteri(n.TEXTURE_CUBE_MAP,n.TEXTURE_MIN_FILTER,o.min),n.texParameteri(n.TEXTURE_CUBE_MAP,n.TEXTURE_WRAP_S,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_CUBE_MAP,n.TEXTURE_WRAP_T,n.CLAMP_TO_EDGE);for(var a=0;a<6;a++)n.texImage2D(n.TEXTURE_CUBE_MAP_POSITIVE_X+a,0,this._getRGBABufferInternalSizedFormat(e.type,e.format),r,r,0,this._getInternalFormat(e.format),this._getWebGLTextureType(e.type),null);var s=n.createFramebuffer();return this._bindUnboundFramebuffer(s),i._depthStencilBuffer=this._setupFramebufferDepthAttachments(e.generateStencilBuffer,e.generateDepthBuffer,r,r),e.generateMipMaps&&n.generateMipmap(n.TEXTURE_CUBE_MAP),this._bindTextureDirectly(n.TEXTURE_CUBE_MAP,null),this._bindUnboundFramebuffer(null),i._framebuffer=s,i.width=r,i.height=r,i.isReady=!0,i.isCube=!0,i.samples=1,i.generateMipMaps=e.generateMipMaps,i.samplingMode=e.samplingMode,i.type=e.type,i.format=e.format,i._generateDepthBuffer=e.generateDepthBuffer,i._generateStencilBuffer=e.generateStencilBuffer,this._internalTexturesCache.push(i),i};var sn=function(r){function t(e,n,i,o,a,s,d,p,b,P,O,B,F){a===void 0&&(a=!0),s===void 0&&(s=h.a.TEXTURETYPE_UNSIGNED_INT),d===void 0&&(d=!1),p===void 0&&(p=we.a.TRILINEAR_SAMPLINGMODE),b===void 0&&(b=!0),P===void 0&&(P=!1),O===void 0&&(O=!1),B===void 0&&(B=h.a.TEXTUREFORMAT_RGBA),F===void 0&&(F=!1);var z=r.call(this,null,i,!o)||this;return z.renderParticles=!0,z.renderSprites=!1,z.ignoreCameraViewport=!1,z.onBeforeBindObservable=new x.c,z.onAfterUnbindObservable=new x.c,z.onBeforeRenderObservable=new x.c,z.onAfterRenderObservable=new x.c,z.onClearObservable=new x.c,z.onResizeObservable=new x.c,z._currentRefreshId=-1,z._refreshRate=1,z._samples=1,z.boundingBoxPosition=u.e.Zero(),(i=z.getScene())&&(z._coordinatesMode=we.a.PROJECTION_MODE,z.renderList=new Array,z.name=e,z.isRenderTarget=!0,z._initialSizeParameter=n,z._processSizeParameter(n),z._resizeObserver=z.getScene().getEngine().onResizeObservable.add(function(){}),z._generateMipMaps=!!o,z._doNotChangeAspectRatio=a,z._renderingManager=new to.b(i),z._renderingManager._useSceneAutoClearSetup=!0,O||(z._renderTargetOptions={generateMipMaps:o,type:s,format:B,samplingMode:p,generateDepthBuffer:b,generateStencilBuffer:P},p===we.a.NEAREST_SAMPLINGMODE&&(z.wrapU=we.a.CLAMP_ADDRESSMODE,z.wrapV=we.a.CLAMP_ADDRESSMODE),F||(d?(z._texture=i.getEngine().createRenderTargetCubeTexture(z.getRenderSize(),z._renderTargetOptions),z.coordinatesMode=we.a.INVCUBIC_MODE,z._textureMatrix=u.a.Identity()):z._texture=i.getEngine().createRenderTargetTexture(z._size,z._renderTargetOptions)))),z}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"renderList",{get:function(){return this._renderList},set:function(e){this._renderList=e,this._renderList&&this._hookArray(this._renderList)},enumerable:!1,configurable:!0}),t.prototype._hookArray=function(e){var n=this,i=e.push;e.push=function(){for(var a=[],s=0;s<arguments.length;s++)a[s]=arguments[s];var d=e.length===0,p=i.apply(e,a);return d&&n.getScene()&&n.getScene().meshes.forEach(function(b){b._markSubMeshesAsLightDirty()}),p};var o=e.splice;e.splice=function(a,s){var d=o.apply(e,[a,s]);return e.length===0&&n.getScene().meshes.forEach(function(p){p._markSubMeshesAsLightDirty()}),d}},Object.defineProperty(t.prototype,"onAfterUnbind",{set:function(e){this._onAfterUnbindObserver&&this.onAfterUnbindObservable.remove(this._onAfterUnbindObserver),this._onAfterUnbindObserver=this.onAfterUnbindObservable.add(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onBeforeRender",{set:function(e){this._onBeforeRenderObserver&&this.onBeforeRenderObservable.remove(this._onBeforeRenderObserver),this._onBeforeRenderObserver=this.onBeforeRenderObservable.add(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onAfterRender",{set:function(e){this._onAfterRenderObserver&&this.onAfterRenderObservable.remove(this._onAfterRenderObserver),this._onAfterRenderObserver=this.onAfterRenderObservable.add(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onClear",{set:function(e){this._onClearObserver&&this.onClearObservable.remove(this._onClearObserver),this._onClearObserver=this.onClearObservable.add(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"renderTargetOptions",{get:function(){return this._renderTargetOptions},enumerable:!1,configurable:!0}),t.prototype._onRatioRescale=function(){this._sizeRatio&&this.resize(this._initialSizeParameter)},Object.defineProperty(t.prototype,"boundingBoxSize",{get:function(){return this._boundingBoxSize},set:function(e){if(!this._boundingBoxSize||!this._boundingBoxSize.equals(e)){this._boundingBoxSize=e;var n=this.getScene();n&&n.markAllMaterialsAsDirty(h.a.MATERIAL_TextureDirtyFlag)}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"depthStencilTexture",{get:function(){var e;return((e=this.getInternalTexture())===null||e===void 0?void 0:e._depthStencilTexture)||null},enumerable:!1,configurable:!0}),t.prototype.createDepthStencilTexture=function(e,n,i){e===void 0&&(e=0),n===void 0&&(n=!0),i===void 0&&(i=!1);var o=this.getInternalTexture();if(this.getScene()&&o){var a=this.getScene().getEngine();o._depthStencilTexture=a.createDepthStencilTexture(this._size,{bilinearFiltering:n,comparisonFunction:e,generateStencil:i,isCube:this.isCube})}},t.prototype._processSizeParameter=function(e){if(e.ratio){this._sizeRatio=e.ratio;var n=this._getEngine();this._size={width:this._bestReflectionRenderTargetDimension(n.getRenderWidth(),this._sizeRatio),height:this._bestReflectionRenderTargetDimension(n.getRenderHeight(),this._sizeRatio)}}else this._size=e},Object.defineProperty(t.prototype,"samples",{get:function(){return this._samples},set:function(e){if(this._samples!==e){var n=this.getScene();n&&(this._samples=n.getEngine().updateRenderTargetTextureSampleCount(this._texture,e))}},enumerable:!1,configurable:!0}),t.prototype.resetRefreshCounter=function(){this._currentRefreshId=-1},Object.defineProperty(t.prototype,"refreshRate",{get:function(){return this._refreshRate},set:function(e){this._refreshRate=e,this.resetRefreshCounter()},enumerable:!1,configurable:!0}),t.prototype.addPostProcess=function(e){if(!this._postProcessManager){var n=this.getScene();if(!n)return;this._postProcessManager=new hs.a(n),this._postProcesses=new Array}this._postProcesses.push(e),this._postProcesses[0].autoClear=!1},t.prototype.clearPostProcesses=function(e){if(e===void 0&&(e=!1),this._postProcesses){if(e)for(var n=0,i=this._postProcesses;n<i.length;n++)i[n].dispose();this._postProcesses=[]}},t.prototype.removePostProcess=function(e){if(this._postProcesses){var n=this._postProcesses.indexOf(e);n!==-1&&(this._postProcesses.splice(n,1),this._postProcesses.length>0&&(this._postProcesses[0].autoClear=!1))}},t.prototype._shouldRender=function(){return this._currentRefreshId===-1||this.refreshRate===this._currentRefreshId?(this._currentRefreshId=1,!0):(this._currentRefreshId++,!1)},t.prototype.getRenderSize=function(){return this.getRenderWidth()},t.prototype.getRenderWidth=function(){return this._size.width?this._size.width:this._size},t.prototype.getRenderHeight=function(){return this._size.width?this._size.height:this._size},t.prototype.getRenderLayers=function(){var e=this._size.layers;return e||0},Object.defineProperty(t.prototype,"canRescale",{get:function(){return!0},enumerable:!1,configurable:!0}),t.prototype.scale=function(e){var n=Math.max(1,this.getRenderSize()*e);this.resize(n)},t.prototype.getReflectionTextureMatrix=function(){return this.isCube?this._textureMatrix:r.prototype.getReflectionTextureMatrix.call(this)},t.prototype.resize=function(e){var n=this.isCube;this.releaseInternalTexture();var i=this.getScene();i&&(this._processSizeParameter(e),this._texture=n?i.getEngine().createRenderTargetCubeTexture(this.getRenderSize(),this._renderTargetOptions):i.getEngine().createRenderTargetTexture(this._size,this._renderTargetOptions),this.onResizeObservable.hasObservers()&&this.onResizeObservable.notifyObservers(this))},t.prototype.render=function(e,n){if(e===void 0&&(e=!1),n===void 0&&(n=!1),p=this.getScene()){var i,o=p.getEngine();if(this.useCameraPostProcesses!==void 0&&(e=this.useCameraPostProcesses),this._waitingRenderList){this.renderList=[];for(var a=0;a<this._waitingRenderList.length;a++){var s=this._waitingRenderList[a],d=p.getMeshByID(s);d&&this.renderList.push(d)}this._waitingRenderList=void 0}if(this.renderListPredicate){var p;if(this.renderList?this.renderList.length=0:this.renderList=[],!(p=this.getScene()))return;var b=p.meshes;for(a=0;a<b.length;a++){var P=b[a];this.renderListPredicate(P)&&this.renderList.push(P)}}if(this.onBeforeBindObservable.notifyObservers(this),this.activeCamera?(i=this.activeCamera,o.setViewport(this.activeCamera.viewport,this.getRenderWidth(),this.getRenderHeight()),this.activeCamera!==p.activeCamera&&p.setTransformMatrix(this.activeCamera.getViewMatrix(),this.activeCamera.getProjectionMatrix(!0))):(i=p.activeCamera)&&o.setViewport(i.viewport,this.getRenderWidth(),this.getRenderHeight()),this._defaultRenderListPrepared=!1,this.is2DArray)for(var O=0;O<this.getRenderLayers();O++)this.renderToTarget(0,e,n,O,i),p.incrementRenderId(),p.resetCachedMaterial();else if(this.isCube)for(var B=0;B<6;B++)this.renderToTarget(B,e,n,void 0,i),p.incrementRenderId(),p.resetCachedMaterial();else this.renderToTarget(0,e,n,void 0,i);this.onAfterUnbindObservable.notifyObservers(this),p.activeCamera&&((p.getEngine().scenes.length>1||this.activeCamera&&this.activeCamera!==p.activeCamera)&&p.setTransformMatrix(p.activeCamera.getViewMatrix(),p.activeCamera.getProjectionMatrix(!0)),o.setViewport(p.activeCamera.viewport)),p.resetCachedMaterial()}},t.prototype._bestReflectionRenderTargetDimension=function(e,n){var i=e*n,o=Ue.a.NearestPOT(i+16384/(128+i));return Math.min(Ue.a.FloorPOT(e),o)},t.prototype._prepareRenderingManager=function(e,n,i,o){var a=this.getScene();if(a){this._renderingManager.reset();for(var s=a.getRenderId(),d=0;d<n;d++){var p=e[d];if(p&&!p.isBlocked){if(this.customIsReadyFunction){if(!this.customIsReadyFunction(p,this.refreshRate)){this.resetRefreshCounter();continue}}else if(!p.isReady(this.refreshRate===0)){this.resetRefreshCounter();continue}if(!p._internalAbstractMeshDataInfo._currentLODIsUpToDate&&a.activeCamera&&(p._internalAbstractMeshDataInfo._currentLOD=a.customLODSelector?a.customLODSelector(p,a.activeCamera):p.getLOD(a.activeCamera),p._internalAbstractMeshDataInfo._currentLODIsUpToDate=!0),!p._internalAbstractMeshDataInfo._currentLOD)continue;var b=p._internalAbstractMeshDataInfo._currentLOD;b._preActivateForIntermediateRendering(s);var P=void 0;if(P=!(!o||!i)&&(p.layerMask&i.layerMask)==0,p.isEnabled()&&p.isVisible&&p.subMeshes&&!P&&(b!==p&&b._activate(s,!0),p._activate(s,!0)&&p.subMeshes.length)){p.isAnInstance?p._internalAbstractMeshDataInfo._actAsRegularMesh&&(b=p):b._internalAbstractMeshDataInfo._onlyForInstancesIntermediate=!1,b._internalAbstractMeshDataInfo._isActiveIntermediate=!0;for(var O=0;O<b.subMeshes.length;O++){var B=b.subMeshes[O];this._renderingManager.dispatch(B,b)}}}}for(var F=0;F<a.particleSystems.length;F++){var z=a.particleSystems[F],J=z.emitter;z.isStarted()&&J&&J.position&&J.isEnabled()&&e.indexOf(J)>=0&&this._renderingManager.dispatchParticles(z)}}},t.prototype._bindFrameBuffer=function(e,n){e===void 0&&(e=0),n===void 0&&(n=0);var i=this.getScene();if(i){var o=i.getEngine();this._texture&&o.bindFramebuffer(this._texture,this.isCube?e:void 0,void 0,void 0,this.ignoreCameraViewport,0,n)}},t.prototype.unbindFrameBuffer=function(e,n){var i=this;this._texture&&e.unBindFramebuffer(this._texture,this.isCube,function(){i.onAfterRenderObservable.notifyObservers(n)})},t.prototype.renderToTarget=function(e,n,i,o,a){o===void 0&&(o=0),a===void 0&&(a=null);var s=this.getScene();if(s){var d=s.getEngine();if(this._texture){this._postProcessManager?this._postProcessManager._prepareFrame(this._texture,this._postProcesses):n&&s.postProcessManager._prepareFrame(this._texture)||this._bindFrameBuffer(e,o),this.is2DArray?this.onBeforeRenderObservable.notifyObservers(o):this.onBeforeRenderObservable.notifyObservers(e);var p=null,b=this.renderList?this.renderList:s.getActiveMeshes().data,P=this.renderList?this.renderList.length:s.getActiveMeshes().length;this.getCustomRenderList&&(p=this.getCustomRenderList(this.is2DArray?o:e,b,P)),p?this._prepareRenderingManager(p,p.length,a,!1):(this._defaultRenderListPrepared||(this._prepareRenderingManager(b,P,a,!this.renderList),this._defaultRenderListPrepared=!0),p=b),this.onClearObservable.hasObservers()?this.onClearObservable.notifyObservers(d):d.clear(this.clearColor||s.clearColor,!0,!0,!0),this._doNotChangeAspectRatio||s.updateTransformMatrix(!0);for(var O=0,B=s._beforeRenderTargetDrawStage;O<B.length;O++)B[O].action(this);this._renderingManager.render(this.customRenderFunction,p,this.renderParticles,this.renderSprites);for(var F=0,z=s._afterRenderTargetDrawStage;F<z.length;F++)z[F].action(this);this._postProcessManager?this._postProcessManager._finalizeFrame(!1,this._texture,e,this._postProcesses,this.ignoreCameraViewport):n&&s.postProcessManager._finalizeFrame(!1,this._texture,e),this._doNotChangeAspectRatio||s.updateTransformMatrix(!0),i&&Xe.b.DumpFramebuffer(this.getRenderWidth(),this.getRenderHeight(),d),this.isCube&&e!==5?this.onAfterRenderObservable.notifyObservers(e):(this.isCube&&e===5&&d.generateMipMapsForCubemap(this._texture),this.unbindFrameBuffer(d,e))}}},t.prototype.setRenderingOrder=function(e,n,i,o){n===void 0&&(n=null),i===void 0&&(i=null),o===void 0&&(o=null),this._renderingManager.setRenderingOrder(e,n,i,o)},t.prototype.setRenderingAutoClearDepthStencil=function(e,n){this._renderingManager.setRenderingAutoClearDepthStencil(e,n),this._renderingManager._useSceneAutoClearSetup=!1},t.prototype.clone=function(){var e=this.getSize(),n=new t(this.name,e,this.getScene(),this._renderTargetOptions.generateMipMaps,this._doNotChangeAspectRatio,this._renderTargetOptions.type,this.isCube,this._renderTargetOptions.samplingMode,this._renderTargetOptions.generateDepthBuffer,this._renderTargetOptions.generateStencilBuffer);return n.hasAlpha=this.hasAlpha,n.level=this.level,n.coordinatesMode=this.coordinatesMode,this.renderList&&(n.renderList=this.renderList.slice(0)),n},t.prototype.serialize=function(){if(!this.name)return null;var e=r.prototype.serialize.call(this);if(e.renderTargetSize=this.getRenderSize(),e.renderList=[],this.renderList)for(var n=0;n<this.renderList.length;n++)e.renderList.push(this.renderList[n].id);return e},t.prototype.disposeFramebufferObjects=function(){var e=this.getInternalTexture(),n=this.getScene();e&&n&&n.getEngine()._releaseFramebufferObjects(e)},t.prototype.dispose=function(){this.onResizeObservable.clear(),this.onClearObservable.clear(),this.onAfterRenderObservable.clear(),this.onAfterUnbindObservable.clear(),this.onBeforeBindObservable.clear(),this.onBeforeRenderObservable.clear(),this._postProcessManager&&(this._postProcessManager.dispose(),this._postProcessManager=null),this.clearPostProcesses(!0),this._resizeObserver&&(this.getScene().getEngine().onResizeObservable.remove(this._resizeObserver),this._resizeObserver=null),this.renderList=null;var e=this.getScene();if(e){var n=e.customRenderTargets.indexOf(this);n>=0&&e.customRenderTargets.splice(n,1);for(var i=0,o=e.cameras;i<o.length;i++){var a=o[i];(n=a.customRenderTargets.indexOf(this))>=0&&a.customRenderTargets.splice(n,1)}this.depthStencilTexture&&this.getScene().getEngine()._releaseTexture(this.depthStencilTexture),r.prototype.dispose.call(this)}},t.prototype._rebuild=function(){this.refreshRate===t.REFRESHRATE_RENDER_ONCE&&(this.refreshRate=t.REFRESHRATE_RENDER_ONCE),this._postProcessManager&&this._postProcessManager._rebuild()},t.prototype.freeRenderingGroups=function(){this._renderingManager&&this._renderingManager.freeRenderingGroups()},t.prototype.getViewCount=function(){return 1},t.REFRESHRATE_RENDER_ONCE=0,t.REFRESHRATE_RENDER_ONEVERYFRAME=1,t.REFRESHRATE_RENDER_ONEVERYTWOFRAMES=2,t}(we.a);we.a._CreateRenderTargetTexture=function(r,t,e,n){return new sn(r,t,e,n)};var Gl=function(r){function t(e,n){n===void 0&&(n=512);var i=r.call(this,"multiview rtt",n,e,!1,!0,xt.b.Unknown,!1,void 0,!1,!1,!0,void 0,!0)||this,o=e.getEngine().createMultiviewRenderTargetTexture(i.getRenderWidth(),i.getRenderHeight());return o.isMultiview=!0,o.format=h.a.TEXTUREFORMAT_RGBA,i._texture=o,i.samples=i._getEngine().getCaps().maxSamples||i.samples,i}return Object(c.d)(t,r),t.prototype._bindFrameBuffer=function(e){this._texture&&this.getScene().getEngine().bindMultiviewFramebuffer(this._texture)},t.prototype.getViewCount=function(){return 2},t}(sn),zl=f(90);Ue.a.prototype.createMultiviewRenderTargetTexture=function(r,t){var e=this._gl;if(!this.getCaps().multiview)throw"Multiview is not supported";var n=new xt.a(this,xt.b.Unknown,!0);return n.width=r,n.height=t,n._framebuffer=e.createFramebuffer(),n._colorTextureArray=e.createTexture(),e.bindTexture(e.TEXTURE_2D_ARRAY,n._colorTextureArray),e.texStorage3D(e.TEXTURE_2D_ARRAY,1,e.RGBA8,r,t,2),n._depthStencilTextureArray=e.createTexture(),e.bindTexture(e.TEXTURE_2D_ARRAY,n._depthStencilTextureArray),e.texStorage3D(e.TEXTURE_2D_ARRAY,1,e.DEPTH32F_STENCIL8,r,t,2),n.isReady=!0,n},Ue.a.prototype.bindMultiviewFramebuffer=function(r){var t=this._gl,e=this.getCaps().oculusMultiview||this.getCaps().multiview;if(this.bindFramebuffer(r,void 0,void 0,void 0,!0),t.bindFramebuffer(t.DRAW_FRAMEBUFFER,r._framebuffer),!r._colorTextureArray||!r._depthStencilTextureArray)throw"Invalid multiview frame buffer";this.getCaps().oculusMultiview?(e.framebufferTextureMultisampleMultiviewOVR(t.DRAW_FRAMEBUFFER,t.COLOR_ATTACHMENT0,r._colorTextureArray,0,r.samples,0,2),e.framebufferTextureMultisampleMultiviewOVR(t.DRAW_FRAMEBUFFER,t.DEPTH_STENCIL_ATTACHMENT,r._depthStencilTextureArray,0,r.samples,0,2)):(e.framebufferTextureMultiviewOVR(t.DRAW_FRAMEBUFFER,t.COLOR_ATTACHMENT0,r._colorTextureArray,0,0,2),e.framebufferTextureMultiviewOVR(t.DRAW_FRAMEBUFFER,t.DEPTH_STENCIL_ATTACHMENT,r._depthStencilTextureArray,0,0,2))},gt.a.prototype._useMultiviewToSingleView=!1,gt.a.prototype._multiviewTexture=null,gt.a.prototype._resizeOrCreateMultiviewTexture=function(r,t){this._multiviewTexture?this._multiviewTexture.getRenderWidth()==r&&this._multiviewTexture.getRenderHeight()==t||(this._multiviewTexture.dispose(),this._multiviewTexture=new Gl(this.getScene(),{width:r,height:t})):this._multiviewTexture=new Gl(this.getScene(),{width:r,height:t})},_e.a.prototype._transformMatrixR=u.a.Zero(),_e.a.prototype._multiviewSceneUbo=null,_e.a.prototype._createMultiviewUbo=function(){this._multiviewSceneUbo=new kl.a(this.getEngine(),void 0,!0),this._multiviewSceneUbo.addUniform("viewProjection",16),this._multiviewSceneUbo.addUniform("viewProjectionR",16),this._multiviewSceneUbo.addUniform("view",16)},_e.a.prototype._updateMultiviewUbo=function(r,t){r&&t&&r.multiplyToRef(t,this._transformMatrixR),r&&t&&(r.multiplyToRef(t,u.c.Matrix[0]),zl.a.GetRightPlaneToRef(u.c.Matrix[0],this._frustumPlanes[3])),this._multiviewSceneUbo&&(this._multiviewSceneUbo.updateMatrix("viewProjection",this.getTransformMatrix()),this._multiviewSceneUbo.updateMatrix("viewProjectionR",this._transformMatrixR),this._multiviewSceneUbo.updateMatrix("view",this._viewMatrix),this._multiviewSceneUbo.update())},_e.a.prototype._renderMultiviewToSingleView=function(r){r._resizeOrCreateMultiviewTexture(r._rigPostProcess&&r._rigPostProcess&&r._rigPostProcess.width>0?r._rigPostProcess.width:this.getEngine().getRenderWidth(!0),r._rigPostProcess&&r._rigPostProcess&&r._rigPostProcess.height>0?r._rigPostProcess.height:this.getEngine().getRenderHeight(!0)),this._multiviewSceneUbo||this._createMultiviewUbo(),r.outputRenderTarget=r._multiviewTexture,this._renderForCamera(r),r.outputRenderTarget=null;for(var t=0;t<r._rigCameras.length;t++){var e=this.getEngine();this._activeCamera=r._rigCameras[t],e.setViewport(this._activeCamera.viewport),this.postProcessManager&&(this.postProcessManager._prepareFrame(),this.postProcessManager._finalizeFrame(this._activeCamera.isIntermediate))}};var ds=function(r){function t(e,n,i){var o=r.call(this,e,"vrMultiviewToSingleview",["imageIndex"],["multiviewSampler"],i,n,we.a.BILINEAR_SAMPLINGMODE)||this;return o.onSizeChangedObservable.add(function(){}),o.onApplyObservable.add(function(a){n._scene.activeCamera&&n._scene.activeCamera.isLeftCamera?a.setInt("imageIndex",0):a.setInt("imageIndex",1),a.setTexture("multiviewSampler",n._multiviewTexture)}),o}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"VRMultiviewToSingleviewPostProcess"},t}(_t);gt.a._setVRRigMode=function(r,t){var e=t.vrCameraMetrics||mr.GetDefault();r._rigCameras[0]._cameraRigParams.vrMetrics=e,r._rigCameras[0].viewport=new Kn.a(0,0,.5,1),r._rigCameras[0]._cameraRigParams.vrWorkMatrix=new u.a,r._rigCameras[0]._cameraRigParams.vrHMatrix=e.leftHMatrix,r._rigCameras[0]._cameraRigParams.vrPreViewMatrix=e.leftPreViewMatrix,r._rigCameras[0].getProjectionMatrix=r._rigCameras[0]._getVRProjectionMatrix,r._rigCameras[1]._cameraRigParams.vrMetrics=e,r._rigCameras[1].viewport=new Kn.a(.5,0,.5,1),r._rigCameras[1]._cameraRigParams.vrWorkMatrix=new u.a,r._rigCameras[1]._cameraRigParams.vrHMatrix=e.rightHMatrix,r._rigCameras[1]._cameraRigParams.vrPreViewMatrix=e.rightPreViewMatrix,r._rigCameras[1].getProjectionMatrix=r._rigCameras[1]._getVRProjectionMatrix,e.multiviewEnabled&&(r.getScene().getEngine().getCaps().multiview?(r._useMultiviewToSingleView=!0,r._rigPostProcess=new ds("VRMultiviewToSingleview",r,e.postProcessScaleFactor)):(l.a.Warn("Multiview is not supported, falling back to standard rendering"),e.multiviewEnabled=!1)),e.compensateDistortion&&(r._rigCameras[0]._rigPostProcess=new us("VR_Distort_Compensation_Left",r._rigCameras[0],!1,e),r._rigCameras[1]._rigPostProcess=new us("VR_Distort_Compensation_Right",r._rigCameras[1],!0,e))},Q.a.AddNodeConstructor("VRDeviceOrientationFreeCamera",function(r,t){return function(){return new jl(r,0,0,1,u.e.Zero(),t)}});var jl=function(r){function t(e,n,i,o,a,s,d,p){d===void 0&&(d=!0),p===void 0&&(p=mr.GetDefault());var b=r.call(this,e,n,i,o,a,s)||this;return p.compensateDistortion=d,b.setCameraRigMode(gt.a.RIG_MODE_VR,{vrCameraMetrics:p}),b.inputs.addVRDeviceOrientation(),b}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"VRDeviceOrientationArcRotateCamera"},t}(Ji);Q.a.AddNodeConstructor("VRDeviceOrientationFreeCamera",function(r,t){return function(){return new Uo(r,u.e.Zero(),t)}});var Uo=function(r){function t(e,n,i,o,a){o===void 0&&(o=!0),a===void 0&&(a=mr.GetDefault());var s=r.call(this,e,n,i)||this;return a.compensateDistortion=o,s.setCameraRigMode(gt.a.RIG_MODE_VR,{vrCameraMetrics:a}),s}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"VRDeviceOrientationFreeCamera"},t}(Fo);Q.a.AddNodeConstructor("VRDeviceOrientationGamepadCamera",function(r,t){return function(){return new Hl(r,u.e.Zero(),t)}});var Hl=function(r){function t(e,n,i,o,a){o===void 0&&(o=!0),a===void 0&&(a=mr.GetDefault());var s=r.call(this,e,n,i,o,a)||this;return s.inputs.addGamepad(),s}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"VRDeviceOrientationGamepadCamera"},t}(Uo),Vo=f(86);gt.a._setWebVRRigMode=function(r,t){if(t.vrDisplay){var e=t.vrDisplay.getEyeParameters("left"),n=t.vrDisplay.getEyeParameters("right");r._rigCameras[0].viewport=new Kn.a(0,0,.5,1),r._rigCameras[0].setCameraRigParameter("left",!0),r._rigCameras[0].setCameraRigParameter("specs",t.specs),r._rigCameras[0].setCameraRigParameter("eyeParameters",e),r._rigCameras[0].setCameraRigParameter("frameData",t.frameData),r._rigCameras[0].setCameraRigParameter("parentCamera",t.parentCamera),r._rigCameras[0]._cameraRigParams.vrWorkMatrix=new u.a,r._rigCameras[0].getProjectionMatrix=r._getWebVRProjectionMatrix,r._rigCameras[0].parent=r,r._rigCameras[0]._getViewMatrix=r._getWebVRViewMatrix,r._rigCameras[1].viewport=new Kn.a(.5,0,.5,1),r._rigCameras[1].setCameraRigParameter("eyeParameters",n),r._rigCameras[1].setCameraRigParameter("specs",t.specs),r._rigCameras[1].setCameraRigParameter("frameData",t.frameData),r._rigCameras[1].setCameraRigParameter("parentCamera",t.parentCamera),r._rigCameras[1]._cameraRigParams.vrWorkMatrix=new u.a,r._rigCameras[1].getProjectionMatrix=r._getWebVRProjectionMatrix,r._rigCameras[1].parent=r,r._rigCameras[1]._getViewMatrix=r._getWebVRViewMatrix}},Object.defineProperty(Ue.a.prototype,"isInVRExclusivePointerMode",{get:function(){return this._vrExclusivePointerMode},enumerable:!0,configurable:!0}),Ue.a.prototype._prepareVRComponent=function(){this._vrSupported=!1,this._vrExclusivePointerMode=!1,this.onVRDisplayChangedObservable=new x.c,this.onVRRequestPresentComplete=new x.c,this.onVRRequestPresentStart=new x.c},Ue.a.prototype.isVRDevicePresent=function(){return!!this._vrDisplay},Ue.a.prototype.getVRDevice=function(){return this._vrDisplay},Ue.a.prototype.initWebVR=function(){return this.initWebVRAsync(),this.onVRDisplayChangedObservable},Ue.a.prototype.initWebVRAsync=function(){var r=this,t=function(){var n={vrDisplay:r._vrDisplay,vrSupported:r._vrSupported};r.onVRDisplayChangedObservable.notifyObservers(n),r._webVRInitPromise=new Promise(function(i){i(n)})};if(!this._onVrDisplayConnect){this._onVrDisplayConnect=function(n){r._vrDisplay=n.display,t()},this._onVrDisplayDisconnect=function(){r._vrDisplay.cancelAnimationFrame(r._frameHandler),r._vrDisplay=void 0,r._frameHandler=Ue.a.QueueNewFrame(r._boundRenderFunction),t()},this._onVrDisplayPresentChange=function(){r._vrExclusivePointerMode=r._vrDisplay&&r._vrDisplay.isPresenting};var e=this.getHostWindow();e&&(e.addEventListener("vrdisplayconnect",this._onVrDisplayConnect),e.addEventListener("vrdisplaydisconnect",this._onVrDisplayDisconnect),e.addEventListener("vrdisplaypresentchange",this._onVrDisplayPresentChange))}return this._webVRInitPromise=this._webVRInitPromise||this._getVRDisplaysAsync(),this._webVRInitPromise.then(t),this._webVRInitPromise},Ue.a.prototype._getVRDisplaysAsync=function(){var r=this;return new Promise(function(t){navigator.getVRDisplays?navigator.getVRDisplays().then(function(e){r._vrSupported=!0,r._vrDisplay=e[0],t({vrDisplay:r._vrDisplay,vrSupported:r._vrSupported})}):(r._vrDisplay=void 0,r._vrSupported=!1,t({vrDisplay:r._vrDisplay,vrSupported:r._vrSupported}))})},Ue.a.prototype.enableVR=function(r){var t=this;if(this._vrDisplay&&!this._vrDisplay.isPresenting){this.onVRRequestPresentStart.notifyObservers(this);var e={highRefreshRate:!!this.vrPresentationAttributes&&this.vrPresentationAttributes.highRefreshRate,foveationLevel:this.vrPresentationAttributes?this.vrPresentationAttributes.foveationLevel:1,multiview:(this.getCaps().multiview||this.getCaps().oculusMultiview)&&r.useMultiview};this._vrDisplay.requestPresent([Object(c.a)({source:this.getRenderingCanvas(),attributes:e},e)]).then(function(){t.onVRRequestPresentComplete.notifyObservers(!0),t._onVRFullScreenTriggered()}).catch(function(){t.onVRRequestPresentComplete.notifyObservers(!1)})}},Ue.a.prototype._onVRFullScreenTriggered=function(){if(this._vrDisplay&&this._vrDisplay.isPresenting){this._oldSize=new oe.a(this.getRenderWidth(),this.getRenderHeight()),this._oldHardwareScaleFactor=this.getHardwareScalingLevel();var r=this._vrDisplay.getEyeParameters("left");this.setHardwareScalingLevel(1),this.setSize(2*r.renderWidth,r.renderHeight)}else this.setHardwareScalingLevel(this._oldHardwareScaleFactor),this.setSize(this._oldSize.width,this._oldSize.height)},Ue.a.prototype.disableVR=function(){var r=this;this._vrDisplay&&this._vrDisplay.isPresenting&&this._vrDisplay.exitPresent().then(function(){return r._onVRFullScreenTriggered()}).catch(function(){return r._onVRFullScreenTriggered()}),cs.a.IsWindowObjectExist()&&(window.removeEventListener("vrdisplaypointerrestricted",this._onVRDisplayPointerRestricted),window.removeEventListener("vrdisplaypointerunrestricted",this._onVRDisplayPointerUnrestricted),this._onVrDisplayConnect&&(window.removeEventListener("vrdisplayconnect",this._onVrDisplayConnect),this._onVrDisplayDisconnect&&window.removeEventListener("vrdisplaydisconnect",this._onVrDisplayDisconnect),this._onVrDisplayPresentChange&&window.removeEventListener("vrdisplaypresentchange",this._onVrDisplayPresentChange),this._onVrDisplayConnect=null,this._onVrDisplayDisconnect=null))},Ue.a.prototype._connectVREvents=function(r,t){var e=this;if(this._onVRDisplayPointerRestricted=function(){r&&r.requestPointerLock()},this._onVRDisplayPointerUnrestricted=function(){if(t)t.exitPointerLock&&t.exitPointerLock();else{var i=e.getHostWindow();i.document&&i.document.exitPointerLock&&i.document.exitPointerLock()}},cs.a.IsWindowObjectExist()){var n=this.getHostWindow();n.addEventListener("vrdisplaypointerrestricted",this._onVRDisplayPointerRestricted,!1),n.addEventListener("vrdisplaypointerunrestricted",this._onVRDisplayPointerUnrestricted,!1)}},Ue.a.prototype._submitVRFrame=function(){if(this._vrDisplay&&this._vrDisplay.isPresenting)try{this._vrDisplay.submitFrame()}catch(r){Xe.b.Warn("webVR submitFrame has had an unexpected failure: "+r)}},Ue.a.prototype.isVRPresenting=function(){return this._vrDisplay&&this._vrDisplay.isPresenting},Ue.a.prototype._requestVRFrame=function(){this._frameHandler=Ue.a.QueueNewFrame(this._boundRenderFunction,this._vrDisplay)},Q.a.AddNodeConstructor("WebVRFreeCamera",function(r,t){return function(){return new ko(r,u.e.Zero(),t)}}),Q.a.AddNodeConstructor("WebVRGamepadCamera",function(r,t){return function(){return new ko(r,u.e.Zero(),t)}});var ko=function(r){function t(e,n,i,o){o===void 0&&(o={});var a=r.call(this,e,n,i)||this;a.webVROptions=o,a._vrDevice=null,a.rawPose=null,a._specsVersion="1.1",a._attached=!1,a._descendants=[],a._deviceRoomPosition=u.e.Zero(),a._deviceRoomRotationQuaternion=u.b.Identity(),a._standingMatrix=null,a.devicePosition=u.e.Zero(),a.deviceRotationQuaternion=u.b.Identity(),a.deviceScaleFactor=1,a._deviceToWorld=u.a.Identity(),a._worldToDevice=u.a.Identity(),a.controllers=[],a.onControllersAttachedObservable=new x.c,a.onControllerMeshLoadedObservable=new x.c,a.onPoseUpdatedFromDeviceObservable=new x.c,a._poseSet=!1,a.rigParenting=!0,a._defaultHeight=void 0,a._detachIfAttached=function(){var d=a.getEngine().getVRDevice();d&&!d.isPresenting&&a.detachControl()},a._workingVector=u.e.Zero(),a._oneVector=u.e.One(),a._workingMatrix=u.a.Identity(),a._tmpMatrix=new u.a,a._cache.position=u.e.Zero(),o.defaultHeight&&(a._defaultHeight=o.defaultHeight,a.position.y=a._defaultHeight),a.minZ=.1,arguments.length===5&&(a.webVROptions=arguments[4]),a.webVROptions.trackPosition==null&&(a.webVROptions.trackPosition=!0),a.webVROptions.controllerMeshes==null&&(a.webVROptions.controllerMeshes=!0),a.webVROptions.defaultLightingOnControllers==null&&(a.webVROptions.defaultLightingOnControllers=!0),a.rotationQuaternion=new u.b,a.webVROptions&&a.webVROptions.positionScale&&(a.deviceScaleFactor=a.webVROptions.positionScale);var s=a.getEngine();return a._onVREnabled=function(d){d&&a.initControllers()},s.onVRRequestPresentComplete.add(a._onVREnabled),s.initWebVR().add(function(d){d.vrDisplay&&a._vrDevice!==d.vrDisplay&&(a._vrDevice=d.vrDisplay,a.setCameraRigMode(gt.a.RIG_MODE_WEBVR,{parentCamera:a,vrDisplay:a._vrDevice,frameData:a._frameData,specs:a._specsVersion}),a._attached&&a.getEngine().enableVR(a.webVROptions))}),typeof VRFrameData<"u"&&(a._frameData=new VRFrameData),o.useMultiview&&(a.getScene().getEngine().getCaps().multiview?(a._useMultiviewToSingleView=!0,a._rigPostProcess=new ds("VRMultiviewToSingleview",a,1)):(l.a.Warn("Multiview is not supported, falling back to standard rendering"),a._useMultiviewToSingleView=!1)),i.onBeforeCameraRenderObservable.add(function(d){d.parent===a&&a.rigParenting&&(a._descendants=a.getDescendants(!0,function(p){var b=a.controllers.some(function(O){return O._mesh===p}),P=a._rigCameras.indexOf(p)!==-1;return!b&&!P}),a._descendants.forEach(function(p){p.parent=d}))}),i.onAfterCameraRenderObservable.add(function(d){d.parent===a&&a.rigParenting&&a._descendants.forEach(function(p){p.parent=a})}),a}return Object(c.d)(t,r),t.prototype.deviceDistanceToRoomGround=function(){return this._standingMatrix?(this._standingMatrix.getTranslationToRef(this._workingVector),this._deviceRoomPosition.y+this._workingVector.y):this._defaultHeight||0},t.prototype.useStandingMatrix=function(e){var n=this;e===void 0&&(e=function(i){}),this.getEngine().initWebVRAsync().then(function(i){i.vrDisplay&&i.vrDisplay.stageParameters&&i.vrDisplay.stageParameters.sittingToStandingTransform&&n.webVROptions.trackPosition?(n._standingMatrix=new u.a,u.a.FromFloat32ArrayToRefScaled(i.vrDisplay.stageParameters.sittingToStandingTransform,0,1,n._standingMatrix),n.getScene().useRightHandedSystem||n._standingMatrix&&n._standingMatrix.toggleModelMatrixHandInPlace(),e(!0)):e(!1)})},t.prototype.useStandingMatrixAsync=function(){var e=this;return new Promise(function(n){e.useStandingMatrix(function(i){n(i)})})},t.prototype.dispose=function(){this._detachIfAttached(),this.getEngine().onVRRequestPresentComplete.removeCallback(this._onVREnabled),this._updateCacheWhenTrackingDisabledObserver&&this._scene.onBeforeRenderObservable.remove(this._updateCacheWhenTrackingDisabledObserver),r.prototype.dispose.call(this)},t.prototype.getControllerByName=function(e){for(var n=0,i=this.controllers;n<i.length;n++){var o=i[n];if(o.hand===e)return o}return null},Object.defineProperty(t.prototype,"leftController",{get:function(){return this._leftController||(this._leftController=this.getControllerByName("left")),this._leftController},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rightController",{get:function(){return this._rightController||(this._rightController=this.getControllerByName("right")),this._rightController},enumerable:!1,configurable:!0}),t.prototype.getForwardRay=function(e){return e===void 0&&(e=100),this.leftCamera?r.prototype.getForwardRay.call(this,e,this.leftCamera.getWorldMatrix(),this.leftCamera.globalPosition):r.prototype.getForwardRay.call(this,e)},t.prototype._checkInputs=function(){this._vrDevice&&this._vrDevice.isPresenting&&(this._vrDevice.getFrameData(this._frameData),this.updateFromDevice(this._frameData.pose)),r.prototype._checkInputs.call(this)},t.prototype.updateFromDevice=function(e){e&&e.orientation&&e.orientation.length===4&&(this.rawPose=e,this._deviceRoomRotationQuaternion.copyFromFloats(e.orientation[0],e.orientation[1],-e.orientation[2],-e.orientation[3]),this.getScene().useRightHandedSystem&&(this._deviceRoomRotationQuaternion.z*=-1,this._deviceRoomRotationQuaternion.w*=-1),this.webVROptions.trackPosition&&this.rawPose.position&&(this._deviceRoomPosition.copyFromFloats(this.rawPose.position[0],this.rawPose.position[1],-this.rawPose.position[2]),this.getScene().useRightHandedSystem&&(this._deviceRoomPosition.z*=-1)),this._poseSet=!0)},t.prototype.attachControl=function(e){e=Xe.b.BackCompatCameraNoPreventDefault(arguments),r.prototype.attachControl.call(this,e),this._attached=!0,e=!gt.a.ForceAttachControlToAlwaysPreventDefault&&e,this._vrDevice&&this.getEngine().enableVR(this.webVROptions);var n=this._scene.getEngine().getHostWindow();n&&n.addEventListener("vrdisplaypresentchange",this._detachIfAttached)},t.prototype.detachControl=function(e){this.getScene().gamepadManager.onGamepadConnectedObservable.remove(this._onGamepadConnectedObserver),this.getScene().gamepadManager.onGamepadDisconnectedObservable.remove(this._onGamepadDisconnectedObserver),r.prototype.detachControl.call(this),this._attached=!1,this.getEngine().disableVR(),window.removeEventListener("vrdisplaypresentchange",this._detachIfAttached)},t.prototype.getClassName=function(){return"WebVRFreeCamera"},t.prototype.resetToCurrentRotation=function(){this._vrDevice.resetPose()},t.prototype._updateRigCameras=function(){var e=this._rigCameras[0],n=this._rigCameras[1];e.rotationQuaternion.copyFrom(this._deviceRoomRotationQuaternion),n.rotationQuaternion.copyFrom(this._deviceRoomRotationQuaternion),e.position.copyFrom(this._deviceRoomPosition),n.position.copyFrom(this._deviceRoomPosition)},t.prototype._correctPositionIfNotTrackPosition=function(e,n){n===void 0&&(n=!1),this.rawPose&&this.rawPose.position&&!this.webVROptions.trackPosition&&(u.a.TranslationToRef(this.rawPose.position[0],this.rawPose.position[1],-this.rawPose.position[2],this._tmpMatrix),n||this._tmpMatrix.invert(),this._tmpMatrix.multiplyToRef(e,e))},t.prototype._updateCache=function(e){var n=this;this.rotationQuaternion.equals(this._cache.rotationQuaternion)&&this.position.equals(this._cache.position)||(this.updateCacheCalled||(this.updateCacheCalled=!0,this.update()),this.rotationQuaternion.toRotationMatrix(this._workingMatrix),u.e.TransformCoordinatesToRef(this._deviceRoomPosition,this._workingMatrix,this._workingVector),this.devicePosition.subtractToRef(this._workingVector,this._workingVector),u.a.ComposeToRef(this._oneVector,this.rotationQuaternion,this._workingVector,this._deviceToWorld),this._deviceToWorld.getTranslationToRef(this._workingVector),this._workingVector.addInPlace(this.position),this._workingVector.subtractInPlace(this._cache.position),this._deviceToWorld.setTranslation(this._workingVector),this._deviceToWorld.invertToRef(this._worldToDevice),this.controllers.forEach(function(i){i._deviceToWorld.copyFrom(n._deviceToWorld),n._correctPositionIfNotTrackPosition(i._deviceToWorld),i.update()})),e||r.prototype._updateCache.call(this),this.updateCacheCalled=!1},t.prototype._computeDevicePosition=function(){u.e.TransformCoordinatesToRef(this._deviceRoomPosition,this._deviceToWorld,this.devicePosition)},t.prototype.update=function(){this._computeDevicePosition(),u.a.FromQuaternionToRef(this._deviceRoomRotationQuaternion,this._workingMatrix),this._workingMatrix.multiplyToRef(this._deviceToWorld,this._workingMatrix),u.b.FromRotationMatrixToRef(this._workingMatrix,this.deviceRotationQuaternion),this._poseSet&&this.onPoseUpdatedFromDeviceObservable.notifyObservers(null),r.prototype.update.call(this)},t.prototype._getViewMatrix=function(){return u.a.Identity()},t.prototype._getWebVRViewMatrix=function(){var e=this._cameraRigParams.parentCamera;e._updateCache();var n=this._cameraRigParams.left?this._cameraRigParams.frameData.leftViewMatrix:this._cameraRigParams.frameData.rightViewMatrix;return u.a.FromArrayToRef(n,0,this._webvrViewMatrix),this.getScene().useRightHandedSystem||this._webvrViewMatrix.toggleModelMatrixHandInPlace(),this._webvrViewMatrix.getRotationMatrixToRef(this._cameraRotationMatrix),u.e.TransformCoordinatesToRef(this._referencePoint,this._cameraRotationMatrix,this._transformedReferencePoint),this.position.addToRef(this._transformedReferencePoint,this._currentTarget),e.deviceScaleFactor!==1&&(this._webvrViewMatrix.invert(),e.deviceScaleFactor&&(this._webvrViewMatrix.multiplyAtIndex(12,e.deviceScaleFactor),this._webvrViewMatrix.multiplyAtIndex(13,e.deviceScaleFactor),this._webvrViewMatrix.multiplyAtIndex(14,e.deviceScaleFactor)),this._webvrViewMatrix.invert()),e._correctPositionIfNotTrackPosition(this._webvrViewMatrix,!0),e._worldToDevice.multiplyToRef(this._webvrViewMatrix,this._webvrViewMatrix),this._workingMatrix=this._workingMatrix||u.a.Identity(),this._webvrViewMatrix.invertToRef(this._workingMatrix),this._workingMatrix.multiplyToRef(e.getWorldMatrix(),this._workingMatrix),this._workingMatrix.getTranslationToRef(this._globalPosition),this._markSyncedWithParent(),this._webvrViewMatrix},t.prototype._getWebVRProjectionMatrix=function(){var e=this.parent;e._vrDevice.depthNear=e.minZ,e._vrDevice.depthFar=e.maxZ;var n=this._cameraRigParams.left?this._cameraRigParams.frameData.leftProjectionMatrix:this._cameraRigParams.frameData.rightProjectionMatrix;return u.a.FromArrayToRef(n,0,this._projectionMatrix),this.getScene().useRightHandedSystem||this._projectionMatrix.toggleProjectionMatrixHandInPlace(),this._projectionMatrix},t.prototype.initControllers=function(){var e=this;this.controllers=[];var n=this.getScene().gamepadManager;this._onGamepadDisconnectedObserver=n.onGamepadDisconnectedObservable.add(function(i){if(i.type===dn.POSE_ENABLED){var o=i;o.defaultModel&&o.defaultModel.setEnabled(!1),o.hand==="right"&&(e._rightController=null),o.hand==="left"&&(e._leftController=null);var a=e.controllers.indexOf(o);a!==-1&&e.controllers.splice(a,1)}}),this._onGamepadConnectedObserver=n.onGamepadConnectedObservable.add(function(i){if(i.type===dn.POSE_ENABLED){var o=i;if(e.webVROptions.trackPosition||(o._disableTrackPosition(new u.e(o.hand=="left"?-.15:.15,-.5,.25)),e._updateCacheWhenTrackingDisabledObserver||(e._updateCacheWhenTrackingDisabledObserver=e._scene.onBeforeRenderObservable.add(function(){e._updateCache()}))),o.deviceScaleFactor=e.deviceScaleFactor,o._deviceToWorld.copyFrom(e._deviceToWorld),e._correctPositionIfNotTrackPosition(o._deviceToWorld),e.webVROptions.controllerMeshes&&(o.defaultModel?o.defaultModel.setEnabled(!0):o.initControllerMesh(e.getScene(),function(d){if(d.scaling.scaleInPlace(e.deviceScaleFactor),e.onControllerMeshLoadedObservable.notifyObservers(o),e.webVROptions.defaultLightingOnControllers){e._lightOnControllers||(e._lightOnControllers=new Vo.a("vrControllersLight",new u.e(0,1,0),e.getScene()));var p=function(b,P){var O=b.getChildren();O&&O.length!==0&&O.forEach(function(B){P.includedOnlyMeshes.push(B),p(B,P)})};e._lightOnControllers.includedOnlyMeshes.push(d),p(d,e._lightOnControllers)}})),o.attachToPoseControlledCamera(e),e.controllers.indexOf(o)===-1){e.controllers.push(o);for(var a=!1,s=0;s<e.controllers.length;s++)e.controllers[s].controllerType===ri.VIVE&&(a?e.controllers[s].hand="right":(a=!0,e.controllers[s].hand="left"));e.controllers.length>=2&&e.onControllersAttachedObservable.notifyObservers(e.controllers)}}})},t}(Yn),Bi=function(r){function t(e){var n=r.call(this,e)||this;return n.onTriggerStateChangedObservable=new x.c,n.onMainButtonStateChangedObservable=new x.c,n.onSecondaryButtonStateChangedObservable=new x.c,n.onPadStateChangedObservable=new x.c,n.onPadValuesChangedObservable=new x.c,n.pad={x:0,y:0},n._changes={pressChanged:!1,touchChanged:!1,valueChanged:!1,changed:!1},n._buttons=new Array(e.buttons.length),n.hand=e.hand,n}return Object(c.d)(t,r),t.prototype.onButtonStateChange=function(e){this._onButtonStateChange=e},Object.defineProperty(t.prototype,"defaultModel",{get:function(){return this._defaultModel},enumerable:!1,configurable:!0}),t.prototype.update=function(){r.prototype.update.call(this);for(var e=0;e<this._buttons.length;e++)this._setButtonValue(this.browserGamepad.buttons[e],this._buttons[e],e);this.leftStick.x===this.pad.x&&this.leftStick.y===this.pad.y||(this.pad.x=this.leftStick.x,this.pad.y=this.leftStick.y,this.onPadValuesChangedObservable.notifyObservers(this.pad))},t.prototype._setButtonValue=function(e,n,i){e||(e={pressed:!1,touched:!1,value:0}),n?(this._checkChanges(e,n),this._changes.changed&&(this._onButtonStateChange&&this._onButtonStateChange(this.index,i,e),this._handleButtonChange(i,e,this._changes)),this._buttons[i].pressed=e.pressed,this._buttons[i].touched=e.touched,this._buttons[i].value=e.value<1e-8?0:e.value):this._buttons[i]={pressed:e.pressed,touched:e.touched,value:e.value}},t.prototype._checkChanges=function(e,n){return this._changes.pressChanged=e.pressed!==n.pressed,this._changes.touchChanged=e.touched!==n.touched,this._changes.valueChanged=e.value!==n.value,this._changes.changed=this._changes.pressChanged||this._changes.touchChanged||this._changes.valueChanged,this._changes},t.prototype.dispose=function(){r.prototype.dispose.call(this),this._defaultModel=null,this.onTriggerStateChangedObservable.clear(),this.onMainButtonStateChangedObservable.clear(),this.onSecondaryButtonStateChangedObservable.clear(),this.onPadStateChangedObservable.clear(),this.onPadValuesChangedObservable.clear()},t}(pr),yn=f(42),Ft=f(30),Ti=f(62),Yf=(f(108),f(59),f(109),`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-#include<imageProcessingDeclaration>
-#include<helperFunctions>
-#include<imageProcessingFunctions>
-void main(void)
-{
-vec4 result=texture2D(textureSampler,vUV);
-#ifdef IMAGEPROCESSING
-#ifndef FROMLINEARSPACE
-
-result.rgb=toLinearSpace(result.rgb);
-#endif
-result=applyImageProcessing(result);
-#else
-
-#ifdef FROMLINEARSPACE
-result=applyImageProcessing(result);
-#endif
-#endif
-gl_FragColor=result;
-}`);ze.a.ShadersStore.imageProcessingPixelShader=Yf;var Go=function(r){function t(e,n,i,o,a,s,d,p){i===void 0&&(i=null),d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT);var b=r.call(this,e,"imageProcessing",[],[],n,i,o,a,s,null,d,"postprocess",null,!0)||this;return b._fromLinearSpace=!0,b._defines={IMAGEPROCESSING:!1,VIGNETTE:!1,VIGNETTEBLENDMODEMULTIPLY:!1,VIGNETTEBLENDMODEOPAQUE:!1,TONEMAPPING:!1,TONEMAPPING_ACES:!1,CONTRAST:!1,COLORCURVES:!1,COLORGRADING:!1,COLORGRADING3D:!1,FROMLINEARSPACE:!1,SAMPLER3DGREENDEPTH:!1,SAMPLER3DBGRMAP:!1,IMAGEPROCESSINGPOSTPROCESS:!1,EXPOSURE:!1},p?(p.applyByPostProcess=!0,b._attachImageProcessingConfiguration(p,!0),b.fromLinearSpace=!1):(b._attachImageProcessingConfiguration(null,!0),b.imageProcessingConfiguration.applyByPostProcess=!0),b.onApply=function(P){b.imageProcessingConfiguration.bind(P,b.aspectRatio)},b}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"imageProcessingConfiguration",{get:function(){return this._imageProcessingConfiguration},set:function(e){e.applyByPostProcess=!0,this._attachImageProcessingConfiguration(e)},enumerable:!1,configurable:!0}),t.prototype._attachImageProcessingConfiguration=function(e,n){var i=this;if(n===void 0&&(n=!1),e!==this._imageProcessingConfiguration){if(this._imageProcessingConfiguration&&this._imageProcessingObserver&&this._imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingObserver),e)this._imageProcessingConfiguration=e;else{var o=null,a=this.getEngine(),s=this.getCamera();if(s)o=s.getScene();else if(a&&a.scenes){var d=a.scenes;o=d[d.length-1]}else o=te.a.LastCreatedScene;this._imageProcessingConfiguration=o?o.imageProcessingConfiguration:new yn.a}this._imageProcessingConfiguration&&(this._imageProcessingObserver=this._imageProcessingConfiguration.onUpdateParameters.add(function(){i._updateParameters()})),n||this._updateParameters()}},Object.defineProperty(t.prototype,"isSupported",{get:function(){var e=this.getEffect();return!e||e.isSupported},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"colorCurves",{get:function(){return this.imageProcessingConfiguration.colorCurves},set:function(e){this.imageProcessingConfiguration.colorCurves=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"colorCurvesEnabled",{get:function(){return this.imageProcessingConfiguration.colorCurvesEnabled},set:function(e){this.imageProcessingConfiguration.colorCurvesEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"colorGradingTexture",{get:function(){return this.imageProcessingConfiguration.colorGradingTexture},set:function(e){this.imageProcessingConfiguration.colorGradingTexture=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"colorGradingEnabled",{get:function(){return this.imageProcessingConfiguration.colorGradingEnabled},set:function(e){this.imageProcessingConfiguration.colorGradingEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"exposure",{get:function(){return this.imageProcessingConfiguration.exposure},set:function(e){this.imageProcessingConfiguration.exposure=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"toneMappingEnabled",{get:function(){return this._imageProcessingConfiguration.toneMappingEnabled},set:function(e){this._imageProcessingConfiguration.toneMappingEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"toneMappingType",{get:function(){return this._imageProcessingConfiguration.toneMappingType},set:function(e){this._imageProcessingConfiguration.toneMappingType=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"contrast",{get:function(){return this.imageProcessingConfiguration.contrast},set:function(e){this.imageProcessingConfiguration.contrast=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vignetteStretch",{get:function(){return this.imageProcessingConfiguration.vignetteStretch},set:function(e){this.imageProcessingConfiguration.vignetteStretch=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vignetteCentreX",{get:function(){return this.imageProcessingConfiguration.vignetteCentreX},set:function(e){this.imageProcessingConfiguration.vignetteCentreX=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vignetteCentreY",{get:function(){return this.imageProcessingConfiguration.vignetteCentreY},set:function(e){this.imageProcessingConfiguration.vignetteCentreY=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vignetteWeight",{get:function(){return this.imageProcessingConfiguration.vignetteWeight},set:function(e){this.imageProcessingConfiguration.vignetteWeight=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vignetteColor",{get:function(){return this.imageProcessingConfiguration.vignetteColor},set:function(e){this.imageProcessingConfiguration.vignetteColor=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vignetteCameraFov",{get:function(){return this.imageProcessingConfiguration.vignetteCameraFov},set:function(e){this.imageProcessingConfiguration.vignetteCameraFov=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vignetteBlendMode",{get:function(){return this.imageProcessingConfiguration.vignetteBlendMode},set:function(e){this.imageProcessingConfiguration.vignetteBlendMode=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vignetteEnabled",{get:function(){return this.imageProcessingConfiguration.vignetteEnabled},set:function(e){this.imageProcessingConfiguration.vignetteEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"fromLinearSpace",{get:function(){return this._fromLinearSpace},set:function(e){this._fromLinearSpace!==e&&(this._fromLinearSpace=e,this._updateParameters())},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"ImageProcessingPostProcess"},t.prototype._updateParameters=function(){this._defines.FROMLINEARSPACE=this._fromLinearSpace,this.imageProcessingConfiguration.prepareDefines(this._defines,!0);var e="";for(var n in this._defines)this._defines[n]&&(e+="#define "+n+`;\r
-`);var i=["textureSampler"],o=["scale"];yn.a&&(yn.a.PrepareSamplers(i,this._defines),yn.a.PrepareUniforms(o,this._defines)),this.updateEffect(e,o,i)},t.prototype.dispose=function(e){r.prototype.dispose.call(this,e),this._imageProcessingConfiguration&&this._imageProcessingObserver&&this._imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingObserver),this._imageProcessingConfiguration&&(this.imageProcessingConfiguration.applyByPostProcess=!1)},Object(c.c)([Object(L.c)()],t.prototype,"_fromLinearSpace",void 0),t}(_t),ft=f(16),Oe=f(4);De.a._GroundMeshParser=function(r,t){return zo.Parse(r,t)};var zo=function(r){function t(e,n){var i=r.call(this,e,n)||this;return i.generateOctree=!1,i}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"GroundMesh"},Object.defineProperty(t.prototype,"subdivisions",{get:function(){return Math.min(this._subdivisionsX,this._subdivisionsY)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"subdivisionsX",{get:function(){return this._subdivisionsX},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"subdivisionsY",{get:function(){return this._subdivisionsY},enumerable:!1,configurable:!0}),t.prototype.optimize=function(e,n){n===void 0&&(n=32),this._subdivisionsX=e,this._subdivisionsY=e,this.subdivide(e),this.createOrUpdateSubmeshesOctree&&this.createOrUpdateSubmeshesOctree(n)},t.prototype.getHeightAtCoordinates=function(e,n){var i=this.getWorldMatrix(),o=u.c.Matrix[5];i.invertToRef(o);var a=u.c.Vector3[8];if(u.e.TransformCoordinatesFromFloatsToRef(e,0,n,o,a),e=a.x,n=a.z,e<this._minX||e>this._maxX||n<this._minZ||n>this._maxZ)return this.position.y;this._heightQuads&&this._heightQuads.length!=0||(this._initHeightQuads(),this._computeHeightQuads());var s=this._getFacetAt(e,n),d=-(s.x*e+s.z*n+s.w)/s.y;return u.e.TransformCoordinatesFromFloatsToRef(0,d,0,i,a),a.y},t.prototype.getNormalAtCoordinates=function(e,n){var i=new u.e(0,1,0);return this.getNormalAtCoordinatesToRef(e,n,i),i},t.prototype.getNormalAtCoordinatesToRef=function(e,n,i){var o=this.getWorldMatrix(),a=u.c.Matrix[5];o.invertToRef(a);var s=u.c.Vector3[8];if(u.e.TransformCoordinatesFromFloatsToRef(e,0,n,a,s),e=s.x,n=s.z,e<this._minX||e>this._maxX||n<this._minZ||n>this._maxZ)return this;this._heightQuads&&this._heightQuads.length!=0||(this._initHeightQuads(),this._computeHeightQuads());var d=this._getFacetAt(e,n);return u.e.TransformNormalFromFloatsToRef(d.x,d.y,d.z,o,i),this},t.prototype.updateCoordinateHeights=function(){return this._heightQuads&&this._heightQuads.length!=0||this._initHeightQuads(),this._computeHeightQuads(),this},t.prototype._getFacetAt=function(e,n){var i=Math.floor((e+this._maxX)*this._subdivisionsX/this._width),o=Math.floor(-(n+this._maxZ)*this._subdivisionsY/this._height+this._subdivisionsY),a=this._heightQuads[o*this._subdivisionsX+i];return n<a.slope.x*e+a.slope.y?a.facet1:a.facet2},t.prototype._initHeightQuads=function(){var e=this._subdivisionsX,n=this._subdivisionsY;this._heightQuads=new Array;for(var i=0;i<n;i++)for(var o=0;o<e;o++){var a={slope:u.d.Zero(),facet1:new u.f(0,0,0,0),facet2:new u.f(0,0,0,0)};this._heightQuads[i*e+o]=a}return this},t.prototype._computeHeightQuads=function(){var e=this.getVerticesData(Oe.b.PositionKind);if(!e)return this;for(var n=u.c.Vector3[3],i=u.c.Vector3[2],o=u.c.Vector3[1],a=u.c.Vector3[0],s=u.c.Vector3[4],d=u.c.Vector3[5],p=u.c.Vector3[6],b=u.c.Vector3[7],P=u.c.Vector3[8],O=0,B=0,F=0,z=0,J=0,ie=0,se=0,ce=this._subdivisionsX,ue=this._subdivisionsY,fe=0;fe<ue;fe++)for(var ve=0;ve<ce;ve++){O=3*ve,B=fe*(ce+1)*3,F=(fe+1)*(ce+1)*3,n.x=e[B+O],n.y=e[B+O+1],n.z=e[B+O+2],i.x=e[B+O+3],i.y=e[B+O+4],i.z=e[B+O+5],o.x=e[F+O],o.y=e[F+O+1],o.z=e[F+O+2],a.x=e[F+O+3],a.y=e[F+O+4],a.z=e[F+O+5],z=(a.z-n.z)/(a.x-n.x),J=n.z-z*n.x,i.subtractToRef(n,s),o.subtractToRef(n,d),a.subtractToRef(n,p),u.e.CrossToRef(p,d,b),u.e.CrossToRef(s,p,P),b.normalize(),P.normalize(),ie=-(b.x*n.x+b.y*n.y+b.z*n.z),se=-(P.x*i.x+P.y*i.y+P.z*i.z);var Te=this._heightQuads[fe*ce+ve];Te.slope.copyFromFloats(z,J),Te.facet1.copyFromFloats(b.x,b.y,b.z,ie),Te.facet2.copyFromFloats(P.x,P.y,P.z,se)}return this},t.prototype.serialize=function(e){r.prototype.serialize.call(this,e),e.subdivisionsX=this._subdivisionsX,e.subdivisionsY=this._subdivisionsY,e.minX=this._minX,e.maxX=this._maxX,e.minZ=this._minZ,e.maxZ=this._maxZ,e.width=this._width,e.height=this._height},t.Parse=function(e,n){var i=new t(e.name,n);return i._subdivisionsX=e.subdivisionsX||1,i._subdivisionsY=e.subdivisionsY||1,i._minX=e.minX,i._maxX=e.maxX,i._minZ=e.minZ,i._maxZ=e.maxZ,i._width=e.width,i._height=e.height,i},t}(De.a),fs=f(70);ft.a.CreateGround=function(r){var t,e,n=[],i=[],o=[],a=[],s=r.width||1,d=r.height||1,p=r.subdivisionsX||r.subdivisions||1,b=r.subdivisionsY||r.subdivisions||1;for(t=0;t<=b;t++)for(e=0;e<=p;e++){var P=new u.e(e*s/p-s/2,0,(b-t)*d/b-d/2),O=new u.e(0,1,0);i.push(P.x,P.y,P.z),o.push(O.x,O.y,O.z),a.push(e/p,1-t/b)}for(t=0;t<b;t++)for(e=0;e<p;e++)n.push(e+1+(t+1)*(p+1)),n.push(e+1+t*(p+1)),n.push(e+t*(p+1)),n.push(e+(t+1)*(p+1)),n.push(e+1+(t+1)*(p+1)),n.push(e+t*(p+1));var B=new ft.a;return B.indices=n,B.positions=i,B.normals=o,B.uvs=a,B},ft.a.CreateTiledGround=function(r){var t,e,n,i,o=r.xmin!==void 0&&r.xmin!==null?r.xmin:-1,a=r.zmin!==void 0&&r.zmin!==null?r.zmin:-1,s=r.xmax!==void 0&&r.xmax!==null?r.xmax:1,d=r.zmax!==void 0&&r.zmax!==null?r.zmax:1,p=r.subdivisions||{w:1,h:1},b=r.precision||{w:1,h:1},P=new Array,O=new Array,B=new Array,F=new Array;p.h=p.h<1?1:p.h,p.w=p.w<1?1:p.w,b.w=b.w<1?1:b.w,b.h=b.h<1?1:b.h;var z=(s-o)/p.w,J=(d-a)/p.h;function ie(ce,ue,fe,ve){var Te=O.length/3,Re=b.w+1;for(t=0;t<b.h;t++)for(e=0;e<b.w;e++){var Ae=[Te+e+t*Re,Te+(e+1)+t*Re,Te+(e+1)+(t+1)*Re,Te+e+(t+1)*Re];P.push(Ae[1]),P.push(Ae[2]),P.push(Ae[3]),P.push(Ae[0]),P.push(Ae[1]),P.push(Ae[3])}var Ee=u.e.Zero(),Se=new u.e(0,1,0);for(t=0;t<=b.h;t++)for(Ee.z=t*(ve-ue)/b.h+ue,e=0;e<=b.w;e++)Ee.x=e*(fe-ce)/b.w+ce,Ee.y=0,O.push(Ee.x,Ee.y,Ee.z),B.push(Se.x,Se.y,Se.z),F.push(e/b.w,t/b.h)}for(n=0;n<p.h;n++)for(i=0;i<p.w;i++)ie(o+i*z,a+n*J,o+(i+1)*z,a+(n+1)*J);var se=new ft.a;return se.indices=P,se.positions=O,se.normals=B,se.uvs=F,se},ft.a.CreateGroundFromHeightMap=function(r){var t,e,n=[],i=[],o=[],a=[],s=r.colorFilter||new M.a(.3,.59,.11),d=r.alphaFilter||0,p=!1;if(r.minHeight>r.maxHeight){p=!0;var b=r.maxHeight;r.maxHeight=r.minHeight,r.minHeight=b}for(t=0;t<=r.subdivisions;t++)for(e=0;e<=r.subdivisions;e++){var P=new u.e(e*r.width/r.subdivisions-r.width/2,0,(r.subdivisions-t)*r.height/r.subdivisions-r.height/2),O=4*(((P.x+r.width/2)/r.width*(r.bufferWidth-1)|0)+((1-(P.z+r.height/2)/r.height)*(r.bufferHeight-1)|0)*r.bufferWidth),B=r.buffer[O]/255,F=r.buffer[O+1]/255,z=r.buffer[O+2]/255,J=r.buffer[O+3]/255;p&&(B=1-B,F=1-F,z=1-z);var ie=B*s.r+F*s.g+z*s.b;P.y=J>=d?r.minHeight+(r.maxHeight-r.minHeight)*ie:r.minHeight-Gt.a,i.push(P.x,P.y,P.z),o.push(0,0,0),a.push(e/r.subdivisions,1-t/r.subdivisions)}for(t=0;t<r.subdivisions;t++)for(e=0;e<r.subdivisions;e++){var se=e+1+(t+1)*(r.subdivisions+1),ce=e+1+t*(r.subdivisions+1),ue=e+t*(r.subdivisions+1),fe=e+(t+1)*(r.subdivisions+1),ve=i[3*se+1]>=r.minHeight,Te=i[3*ce+1]>=r.minHeight,Re=i[3*ue+1]>=r.minHeight;ve&&Te&&Re&&(n.push(se),n.push(ce),n.push(ue)),i[3*fe+1]>=r.minHeight&&ve&&Re&&(n.push(fe),n.push(se),n.push(ue))}ft.a.ComputeNormals(i,n,o);var Ae=new ft.a;return Ae.indices=n,Ae.positions=i,Ae.normals=o,Ae.uvs=a,Ae},De.a.CreateGround=function(r,t,e,n,i,o){var a={width:t,height:e,subdivisions:n,updatable:o};return Ui.CreateGround(r,a,i)},De.a.CreateTiledGround=function(r,t,e,n,i,o,a,s,d){var p={xmin:t,zmin:e,xmax:n,zmax:i,subdivisions:o,precision:a,updatable:d};return Ui.CreateTiledGround(r,p,s)},De.a.CreateGroundFromHeightMap=function(r,t,e,n,i,o,a,s,d,p,b){var P={width:e,height:n,subdivisions:i,minHeight:o,maxHeight:a,updatable:d,onReady:p,alphaFilter:b};return Ui.CreateGroundFromHeightMap(r,t,P,s)};var Ui=function(){function r(){}return r.CreateGround=function(t,e,n){var i=new zo(t,n);return i._setReady(!1),i._subdivisionsX=e.subdivisionsX||e.subdivisions||1,i._subdivisionsY=e.subdivisionsY||e.subdivisions||1,i._width=e.width||1,i._height=e.height||1,i._maxX=i._width/2,i._maxZ=i._height/2,i._minX=-i._maxX,i._minZ=-i._maxZ,ft.a.CreateGround(e).applyToMesh(i,e.updatable),i._setReady(!0),i},r.CreateTiledGround=function(t,e,n){n===void 0&&(n=null);var i=new De.a(t,n);return ft.a.CreateTiledGround(e).applyToMesh(i,e.updatable),i},r.CreateGroundFromHeightMap=function(t,e,n,i){i===void 0&&(i=null);var o=n.width||10,a=n.height||10,s=n.subdivisions||1,d=n.minHeight||0,p=n.maxHeight||1,b=n.colorFilter||new M.a(.3,.59,.11),P=n.alphaFilter||0,O=n.updatable,B=n.onReady;i=i||te.a.LastCreatedScene;var F=new zo(t,i);return F._subdivisionsX=s,F._subdivisionsY=s,F._width=o,F._height=a,F._maxX=F._width/2,F._maxZ=F._height/2,F._minX=-F._maxX,F._minZ=-F._maxZ,F._setReady(!1),Xe.b.LoadImage(e,function(z){var J=z.width,ie=z.height,se=fs.a.CreateCanvas(J,ie).getContext("2d");if(!se)throw new Error("Unable to get 2d context for CreateGroundFromHeightMap");if(!i.isDisposed){se.drawImage(z,0,0);var ce=se.getImageData(0,0,J,ie).data;ft.a.CreateGroundFromHeightMap({width:o,height:a,subdivisions:s,minHeight:d,maxHeight:p,colorFilter:b,buffer:ce,bufferWidth:J,bufferHeight:ie,alphaFilter:P}).applyToMesh(F,O),B&&B(F),F._setReady(!0)}},function(){},i.offlineProvider),F},r}();ft.a.CreateTorus=function(r){for(var t=[],e=[],n=[],i=[],o=r.diameter||1,a=r.thickness||.5,s=r.tessellation||16,d=r.sideOrientation===0?0:r.sideOrientation||ft.a.DEFAULTSIDE,p=s+1,b=0;b<=s;b++)for(var P=b/s,O=b*Math.PI*2/s-Math.PI/2,B=u.a.Translation(o/2,0,0).multiply(u.a.RotationY(O)),F=0;F<=s;F++){var z=1-F/s,J=F*Math.PI*2/s+Math.PI,ie=Math.cos(J),se=Math.sin(J),ce=new u.e(ie,se,0),ue=ce.scale(a/2),fe=new u.d(P,z);ue=u.e.TransformCoordinates(ue,B),ce=u.e.TransformNormal(ce,B),e.push(ue.x,ue.y,ue.z),n.push(ce.x,ce.y,ce.z),i.push(fe.x,fe.y);var ve=(b+1)%p,Te=(F+1)%p;t.push(b*p+F),t.push(b*p+Te),t.push(ve*p+F),t.push(b*p+Te),t.push(ve*p+Te),t.push(ve*p+F)}ft.a._ComputeSides(d,e,t,n,i,r.frontUVs,r.backUVs);var Re=new ft.a;return Re.indices=t,Re.positions=e,Re.normals=n,Re.uvs=i,Re},De.a.CreateTorus=function(r,t,e,n,i,o,a){var s={diameter:t,thickness:e,tessellation:n,sideOrientation:a,updatable:o};return gr.CreateTorus(r,s,i)};var pn,tr,gr=function(){function r(){}return r.CreateTorus=function(t,e,n){var i=new De.a(t,n);return e.sideOrientation=De.a._GetDefaultSideOrientation(e.sideOrientation),i._originalBuilderSideOrientation=e.sideOrientation,ft.a.CreateTorus(e).applyToMesh(i,e.updatable),i},r}(),pi=f(53),ps=function(){function r(){}return r.GetDefaults=function(t){var e=new r;return e.canvasOptions={antialias:!0,depth:!0,stencil:!t||t.isStencilEnable,alpha:!0,multiview:!1,framebufferScaleFactor:1},e.newCanvasCssStyle="position:absolute; bottom:0px;right:0px;z-index:10;width:90%;height:100%;background-color: #000000;",e},r}(),Wl=function(){function r(t,e){var n=this;if(e===void 0&&(e=ps.GetDefaults()),this._options=e,this._canvas=null,this.xrLayer=null,this.onXRLayerInitObservable=new x.c,this._engine=t.scene.getEngine(),e.canvasElement)this._setManagedOutputCanvas(e.canvasElement);else{var i=document.createElement("canvas");i.style.cssText=this._options.newCanvasCssStyle||"position:absolute; bottom:0px;right:0px;",this._setManagedOutputCanvas(i)}t.onXRSessionInit.add(function(){n._addCanvas()}),t.onXRSessionEnded.add(function(){n._removeCanvas()})}return r.prototype.dispose=function(){this._removeCanvas(),this._setManagedOutputCanvas(null)},r.prototype.initializeXRLayerAsync=function(t){var e=this,n=function(){var i=new XRWebGLLayer(t,e.canvasContext,e._options.canvasOptions);return e.onXRLayerInitObservable.notifyObservers(i),i};return this.canvasContext.makeXRCompatible?this.canvasContext.makeXRCompatible().then(function(){return e.xrLayer=n(),e.xrLayer}):(this.xrLayer=n(),Promise.resolve(this.xrLayer))},r.prototype._addCanvas=function(){var t=this;this._canvas&&this._canvas!==this._engine.getRenderingCanvas()&&document.body.appendChild(this._canvas),this.xrLayer?this._setCanvasSize(!0):this.onXRLayerInitObservable.addOnce(function(e){t._setCanvasSize(!0,e)})},r.prototype._removeCanvas=function(){this._canvas&&document.body.contains(this._canvas)&&this._canvas!==this._engine.getRenderingCanvas()&&document.body.removeChild(this._canvas),this._setCanvasSize(!1)},r.prototype._setCanvasSize=function(t,e){t===void 0&&(t=!0),e===void 0&&(e=this.xrLayer),this._canvas&&(t?e&&(this._canvas!==this._engine.getRenderingCanvas()?(this._canvas.style.width=e.framebufferWidth+"px",this._canvas.style.height=e.framebufferHeight+"px"):this._engine.setSize(e.framebufferWidth,e.framebufferHeight)):this._originalCanvasSize&&(this._canvas!==this._engine.getRenderingCanvas()?(this._canvas.style.width=this._originalCanvasSize.width+"px",this._canvas.style.height=this._originalCanvasSize.height+"px"):this._engine.setSize(this._originalCanvasSize.width,this._originalCanvasSize.height)))},r.prototype._setManagedOutputCanvas=function(t){this._removeCanvas(),t?(this._originalCanvasSize={width:t.offsetWidth,height:t.offsetHeight},this._canvas=t,this.canvasContext=this._canvas.getContext("webgl2"),this.canvasContext||(this.canvasContext=this._canvas.getContext("webgl"))):(this._canvas=null,this.canvasContext=null)},r}(),_s=function(){function r(t){this.scene=t,this._sessionEnded=!1,this.baseLayer=null,this.currentTimestamp=-1,this.defaultHeightCompensation=1.7,this.onXRFrameObservable=new x.c,this.onXRReferenceSpaceChanged=new x.c,this.onXRSessionEnded=new x.c,this.onXRSessionInit=new x.c}return Object.defineProperty(r.prototype,"referenceSpace",{get:function(){return this._referenceSpace},set:function(t){this._referenceSpace=t,this.onXRReferenceSpaceChanged.notifyObservers(this._referenceSpace)},enumerable:!1,configurable:!0}),r.prototype.dispose=function(){this._sessionEnded||this.exitXRAsync(),this.onXRFrameObservable.clear(),this.onXRSessionEnded.clear(),this.onXRReferenceSpaceChanged.clear(),this.onXRSessionInit.clear()},r.prototype.exitXRAsync=function(){return this.session&&!this._sessionEnded?(this._sessionEnded=!0,this.session.end().catch(function(t){l.a.Warn("Could not end XR session.")})):Promise.resolve()},r.prototype.getRenderTargetTextureForEye=function(t){return this._rttProvider.getRenderTargetForEye(t)},r.prototype.getWebXRRenderTarget=function(t){var e=this.scene.getEngine();return this._xrNavigator.xr.native?this._xrNavigator.xr.getWebXRRenderTarget(e):((t=t||ps.GetDefaults(e)).canvasElement=e.getRenderingCanvas()||void 0,new Wl(this,t))},r.prototype.initializeAsync=function(){return this._xrNavigator=navigator,this._xrNavigator.xr?Promise.resolve():Promise.reject("WebXR not available")},r.prototype.initializeSessionAsync=function(t,e){var n=this;return t===void 0&&(t="immersive-vr"),e===void 0&&(e={}),this._xrNavigator.xr.requestSession(t,e).then(function(i){return n.session=i,n.onXRSessionInit.notifyObservers(i),n._sessionEnded=!1,n.session.addEventListener("end",function(){var o=n.scene.getEngine();n._sessionEnded=!0,n._rttProvider=null,o.framebufferDimensionsObject=null,o.restoreDefaultFramebuffer(),o.customAnimationFrameRequester=null,n.onXRSessionEnded.notifyObservers(null),o._renderLoop()},{once:!0}),n.session})},r.prototype.isSessionSupportedAsync=function(t){return r.IsSessionSupportedAsync(t)},r.prototype.resetReferenceSpace=function(){this.referenceSpace=this.baseReferenceSpace},r.prototype.runXRRenderLoop=function(){var t=this,e=this.scene.getEngine();if(e.customAnimationFrameRequester={requestAnimationFrame:this.session.requestAnimationFrame.bind(this.session),renderFunction:function(i,o){t._sessionEnded||(t.currentFrame=o,t.currentTimestamp=i,o&&(e.framebufferDimensionsObject=t.baseLayer,t.onXRFrameObservable.notifyObservers(o),e._renderLoop(),e.framebufferDimensionsObject=null))}},this._xrNavigator.xr.native)this._rttProvider=this._xrNavigator.xr.getNativeRenderTargetProvider(this.session,this._createRenderTargetTexture.bind(this));else{var n=this._createRenderTargetTexture(this.baseLayer.framebufferWidth,this.baseLayer.framebufferHeight,this.baseLayer.framebuffer);this._rttProvider={getRenderTargetForEye:function(){return n}},e.framebufferDimensionsObject=this.baseLayer}typeof window<"u"&&window.cancelAnimationFrame&&window.cancelAnimationFrame(e._frameHandler),e._renderLoop()},r.prototype.setReferenceSpaceTypeAsync=function(t){var e=this;return t===void 0&&(t="local-floor"),this.session.requestReferenceSpace(t).then(function(n){return n},function(n){return l.a.Error("XR.requestReferenceSpace failed for the following reason: "),l.a.Error(n),l.a.Log('Defaulting to universally-supported "viewer" reference space type.'),e.session.requestReferenceSpace("viewer").then(function(i){var o=new XRRigidTransform({x:0,y:-e.defaultHeightCompensation,z:0});return i.getOffsetReferenceSpace(o)},function(i){throw l.a.Error(i),'XR initialization failed: required "viewer" reference space type not supported.'})}).then(function(n){return e.session.requestReferenceSpace("viewer").then(function(i){return e.viewerReferenceSpace=i,n})}).then(function(n){return e.referenceSpace=e.baseReferenceSpace=n,e.referenceSpace})},r.prototype.updateRenderStateAsync=function(t){return t.baseLayer&&(this.baseLayer=t.baseLayer),this.session.updateRenderState(t)},r.IsSessionSupportedAsync=function(t){if(!navigator.xr)return Promise.resolve(!1);var e=navigator.xr.isSessionSupported||navigator.xr.supportsSession;return e?e.call(navigator.xr,t).then(function(n){var i=n===void 0||n;return Promise.resolve(i)}).catch(function(n){return l.a.Warn(n),Promise.resolve(!1)}):Promise.resolve(!1)},r.prototype._createRenderTargetTexture=function(t,e,n){n===void 0&&(n=null);var i=new xt.a(this.scene.getEngine(),xt.b.Unknown,!0);i.width=t,i.height=e,i._framebuffer=n;var o=new sn("XR renderTargetTexture",{width:t,height:e},this.scene,void 0,void 0,void 0,void 0,void 0,void 0,void 0,void 0,void 0,!0);return o._texture=i,o},r}();(function(r){r[r.ENTERING_XR=0]="ENTERING_XR",r[r.EXITING_XR=1]="EXITING_XR",r[r.IN_XR=2]="IN_XR",r[r.NOT_IN_XR=3]="NOT_IN_XR"})(pn||(pn={})),function(r){r[r.NOT_TRACKING=0]="NOT_TRACKING",r[r.TRACKING_LOST=1]="TRACKING_LOST",r[r.TRACKING=2]="TRACKING"}(tr||(tr={}));var oi,Xl=function(){function r(t,e){if(e===void 0&&(e=null),this.scene=t,this._pointerDownOnMeshAsked=!1,this._isActionableMesh=!1,this._teleportationRequestInitiated=!1,this._teleportationBackRequestInitiated=!1,this._rotationRightAsked=!1,this._rotationLeftAsked=!1,this._dpadPressed=!0,this._activePointer=!1,this._id=r._idCounter++,e)this._gazeTracker=e.clone("gazeTracker");else{this._gazeTracker=De.a.CreateTorus("gazeTracker",.0035,.0025,20,t,!1),this._gazeTracker.bakeCurrentTransformIntoVertices(),this._gazeTracker.isPickable=!1,this._gazeTracker.isVisible=!1;var n=new Ft.a("targetMat",t);n.specularColor=M.a.Black(),n.emissiveColor=new M.a(.7,.7,.7),n.backFaceCulling=!1,this._gazeTracker.material=n}}return r.prototype._getForwardRay=function(t){return new fn.a(u.e.Zero(),new u.e(0,0,t))},r.prototype._selectionPointerDown=function(){this._pointerDownOnMeshAsked=!0,this._currentHit&&this.scene.simulatePointerDown(this._currentHit,{pointerId:this._id})},r.prototype._selectionPointerUp=function(){this._currentHit&&this.scene.simulatePointerUp(this._currentHit,{pointerId:this._id}),this._pointerDownOnMeshAsked=!1},r.prototype._activatePointer=function(){this._activePointer=!0},r.prototype._deactivatePointer=function(){this._activePointer=!1},r.prototype._updatePointerDistance=function(t){},r.prototype.dispose=function(){this._interactionsEnabled=!1,this._teleportationEnabled=!1,this._gazeTracker&&this._gazeTracker.dispose()},r._idCounter=0,r}(),Kf=function(r){function t(e,n,i){var o=r.call(this,n,i)||this;o.webVRController=e,o._laserPointer=De.a.CreateCylinder("laserPointer",1,.004,2e-4,20,1,n,!1);var a=new Ft.a("laserPointerMat",n);if(a.emissiveColor=new M.a(.7,.7,.7),a.alpha=.6,o._laserPointer.material=a,o._laserPointer.rotation.x=Math.PI/2,o._laserPointer.position.z=-.5,o._laserPointer.isVisible=!1,o._laserPointer.isPickable=!1,!e.mesh){var s=new De.a("preloadControllerMesh",n),d=new De.a(pr.POINTING_POSE,n);d.rotation.x=-.7,s.addChild(d),e.attachToMesh(s)}return o._setLaserPointerParent(e.mesh),o._meshAttachedObserver=e._meshAttachedObservable.add(function(p){o._setLaserPointerParent(p)}),o}return Object(c.d)(t,r),t.prototype._getForwardRay=function(e){return this.webVRController.getForwardRay(e)},t.prototype._activatePointer=function(){r.prototype._activatePointer.call(this),this._laserPointer.isVisible=!0},t.prototype._deactivatePointer=function(){r.prototype._deactivatePointer.call(this),this._laserPointer.isVisible=!1},t.prototype._setLaserPointerColor=function(e){this._laserPointer.material.emissiveColor=e},t.prototype._setLaserPointerLightingDisabled=function(e){this._laserPointer.material.disableLighting=e},t.prototype._setLaserPointerParent=function(e){var n=function(s){s.isPickable=!1,s.getChildMeshes().forEach(function(d){n(d)})};n(e);var i=e.getChildren(void 0,!1),o=e;this.webVRController._pointingPoseNode=null;for(var a=0;a<i.length;a++)if(i[a].name&&i[a].name.indexOf(pr.POINTING_POSE)>=0){o=i[a],this.webVRController._pointingPoseNode=o;break}this._laserPointer.parent=o},t.prototype._updatePointerDistance=function(e){e===void 0&&(e=100),this._laserPointer.scaling.y=e,this._laserPointer.position.z=-e/2},t.prototype.dispose=function(){r.prototype.dispose.call(this),this._laserPointer.dispose(),this._meshAttachedObserver&&this.webVRController._meshAttachedObservable.remove(this._meshAttachedObserver)},t}(Xl),Yl=function(r){function t(e,n){var i=r.call(this,n)||this;return i.getCamera=e,i}return Object(c.d)(t,r),t.prototype._getForwardRay=function(e){var n=this.getCamera();return n?n.getForwardRay(e):new fn.a(u.e.Zero(),u.e.Forward())},t}(Xl),Qf=function(){},Kl=function(){function r(t,e){var n=this;if(e===void 0&&(e={}),this.webVROptions=e,this._webVRsupported=!1,this._webVRready=!1,this._webVRrequesting=!1,this._webVRpresenting=!1,this._fullscreenVRpresenting=!1,this.enableGazeEvenWhenNoPointerLock=!1,this.exitVROnDoubleTap=!0,this.onEnteringVRObservable=new x.c,this.onAfterEnteringVRObservable=new x.c,this.onExitingVRObservable=new x.c,this.onControllerMeshLoadedObservable=new x.c,this._useCustomVRButton=!1,this._teleportationRequested=!1,this._teleportActive=!1,this._floorMeshesCollection=[],this._teleportationMode=r.TELEPORTATIONMODE_CONSTANTTIME,this._teleportationTime=122,this._teleportationSpeed=20,this._rotationAllowed=!0,this._teleportBackwardsVector=new u.e(0,-1,-1),this._isDefaultTeleportationTarget=!0,this._teleportationFillColor="#444444",this._teleportationBorderColor="#FFFFFF",this._rotationAngle=0,this._haloCenter=new u.e(0,0,0),this._padSensibilityUp=.65,this._padSensibilityDown=.35,this._leftController=null,this._rightController=null,this._gazeColor=new M.a(.7,.7,.7),this._laserColor=new M.a(.7,.7,.7),this._pickedLaserColor=new M.a(.2,.2,1),this._pickedGazeColor=new M.a(0,0,1),this.onNewMeshSelected=new x.c,this.onMeshSelectedWithController=new x.c,this.onNewMeshPicked=new x.c,this.onBeforeCameraTeleport=new x.c,this.onAfterCameraTeleport=new x.c,this.onSelectedMeshUnselected=new x.c,this.teleportationEnabled=!0,this._teleportationInitialized=!1,this._interactionsEnabled=!1,this._interactionsRequested=!1,this._displayGaze=!0,this._displayLaserPointer=!0,this.updateGazeTrackerScale=!0,this.updateGazeTrackerColor=!0,this.updateControllerLaserColor=!0,this.requestPointerLockOnFullScreen=!0,this.xrTestDone=!1,this._onResize=function(){n.moveButtonToBottomRight(),n._fullscreenVRpresenting&&n._webVRready&&n.exitVR()},this._onFullscreenChange=function(){var o=document;o.fullscreen!==void 0?n._fullscreenVRpresenting=document.fullscreen:o.mozFullScreen!==void 0?n._fullscreenVRpresenting=o.mozFullScreen:o.webkitIsFullScreen!==void 0?n._fullscreenVRpresenting=o.webkitIsFullScreen:o.msIsFullScreen!==void 0?n._fullscreenVRpresenting=o.msIsFullScreen:document.msFullscreenElement!==void 0&&(n._fullscreenVRpresenting=document.msFullscreenElement),!n._fullscreenVRpresenting&&n._inputElement&&(n.exitVR(),!n._useCustomVRButton&&n._btnVR&&(n._btnVR.style.top=n._inputElement.offsetTop+n._inputElement.offsetHeight-70+"px",n._btnVR.style.left=n._inputElement.offsetLeft+n._inputElement.offsetWidth-100+"px",n.updateButtonVisibility()))},this._cachedAngularSensibility={angularSensibilityX:null,angularSensibilityY:null,angularSensibility:null},this.beforeRender=function(){n._leftController&&n._leftController._activePointer&&n._castRayAndSelectObject(n._leftController),n._rightController&&n._rightController._activePointer&&n._castRayAndSelectObject(n._rightController),n._noControllerIsActive&&(n._scene.getEngine().isPointerLock||n.enableGazeEvenWhenNoPointerLock)?n._castRayAndSelectObject(n._cameraGazer):n._cameraGazer._gazeTracker.isVisible=!1},this._onNewGamepadConnected=function(o){if(o.type!==dn.POSE_ENABLED)o.leftStick&&o.onleftstickchanged(function(d){n._teleportationInitialized&&n.teleportationEnabled&&(!n._leftController&&!n._rightController||n._leftController&&!n._leftController._activePointer&&n._rightController&&!n._rightController._activePointer)&&(n._checkTeleportWithRay(d,n._cameraGazer),n._checkTeleportBackwards(d,n._cameraGazer))}),o.rightStick&&o.onrightstickchanged(function(d){n._teleportationInitialized&&n._checkRotate(d,n._cameraGazer)}),o.type===dn.XBOX&&(o.onbuttondown(function(d){n._interactionsEnabled&&d===Rn.A&&n._cameraGazer._selectionPointerDown()}),o.onbuttonup(function(d){n._interactionsEnabled&&d===Rn.A&&n._cameraGazer._selectionPointerUp()}));else{var a=o,s=new Kf(a,n._scene,n._cameraGazer._gazeTracker);a.hand==="right"||n._leftController&&n._leftController.webVRController!=a?n._rightController=s:n._leftController=s,n._tryEnableInteractionOnController(s)}},this._tryEnableInteractionOnController=function(o){n._interactionsRequested&&!o._interactionsEnabled&&n._enableInteractionOnController(o),n._teleportationRequested&&!o._teleportationEnabled&&n._enableTeleportationOnController(o)},this._onNewGamepadDisconnected=function(o){o instanceof Bi&&(o.hand==="left"&&n._leftController!=null&&(n._leftController.dispose(),n._leftController=null),o.hand==="right"&&n._rightController!=null&&(n._rightController.dispose(),n._rightController=null))},this._workingVector=u.e.Zero(),this._workingQuaternion=u.b.Identity(),this._workingMatrix=u.a.Identity(),this._scene=t,this._inputElement=t.getEngine().getInputElement(),"getVRDisplays"in navigator||(e.useXR=!0),e.createFallbackVRDeviceOrientationFreeCamera===void 0&&(e.createFallbackVRDeviceOrientationFreeCamera=!0),e.createDeviceOrientationCamera===void 0&&(e.createDeviceOrientationCamera=!0),e.laserToggle===void 0&&(e.laserToggle=!0),e.defaultHeight===void 0&&(e.defaultHeight=1.7),e.useCustomVRButton&&(this._useCustomVRButton=!0,e.customVRButton&&(this._btnVR=e.customVRButton)),e.rayLength&&(this._rayLength=e.rayLength),this._defaultHeight=e.defaultHeight,e.positionScale&&(this._rayLength*=e.positionScale,this._defaultHeight*=e.positionScale),this._hasEnteredVR=!1,this._scene.activeCamera?this._position=this._scene.activeCamera.position.clone():this._position=new u.e(0,this._defaultHeight,0),e.createDeviceOrientationCamera||!this._scene.activeCamera){if(this._deviceOrientationCamera=new Fo("deviceOrientationVRHelper",this._position.clone(),t),this._scene.activeCamera&&(this._deviceOrientationCamera.minZ=this._scene.activeCamera.minZ,this._deviceOrientationCamera.maxZ=this._scene.activeCamera.maxZ,this._scene.activeCamera instanceof Ni&&this._scene.activeCamera.rotation)){var i=this._scene.activeCamera;i.rotationQuaternion?this._deviceOrientationCamera.rotationQuaternion.copyFrom(i.rotationQuaternion):this._deviceOrientationCamera.rotationQuaternion.copyFrom(u.b.RotationYawPitchRoll(i.rotation.y,i.rotation.x,i.rotation.z)),this._deviceOrientationCamera.rotation=i.rotation.clone()}this._scene.activeCamera=this._deviceOrientationCamera,this._inputElement&&this._scene.activeCamera.attachControl()}else this._existingCamera=this._scene.activeCamera;this.webVROptions.useXR&&navigator.xr?_s.IsSessionSupportedAsync("immersive-vr").then(function(o){o?(l.a.Log("Using WebXR. It is recommended to use the WebXRDefaultExperience directly"),t.createDefaultXRExperienceAsync({floorMeshes:e.floorMeshes||[]}).then(function(a){n.xr=a,n.xrTestDone=!0,n._cameraGazer=new Yl(function(){return n.xr.baseExperience.camera},t),n.xr.baseExperience.onStateChangedObservable.add(function(s){switch(s){case pn.ENTERING_XR:n.onEnteringVRObservable.notifyObservers(n),n._interactionsEnabled||n.xr.pointerSelection.detach(),n.xr.pointerSelection.displayLaserPointer=n._displayLaserPointer;break;case pn.EXITING_XR:n.onExitingVRObservable.notifyObservers(n),n._scene.getEngine().resize();break;case pn.IN_XR:n._hasEnteredVR=!0;break;case pn.NOT_IN_XR:n._hasEnteredVR=!1}})})):n.completeVRInit(t,e)}):this.completeVRInit(t,e)}return Object.defineProperty(r.prototype,"onEnteringVR",{get:function(){return this.onEnteringVRObservable},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"onExitingVR",{get:function(){return this.onExitingVRObservable},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"onControllerMeshLoaded",{get:function(){return this.onControllerMeshLoadedObservable},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"teleportationTarget",{get:function(){return this._teleportationTarget},set:function(t){t&&(t.name="teleportationTarget",this._isDefaultTeleportationTarget=!1,this._teleportationTarget=t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"gazeTrackerMesh",{get:function(){return this._cameraGazer._gazeTracker},set:function(t){t&&(this._cameraGazer._gazeTracker&&this._cameraGazer._gazeTracker.dispose(),this._leftController&&this._leftController._gazeTracker&&this._leftController._gazeTracker.dispose(),this._rightController&&this._rightController._gazeTracker&&this._rightController._gazeTracker.dispose(),this._cameraGazer._gazeTracker=t,this._cameraGazer._gazeTracker.bakeCurrentTransformIntoVertices(),this._cameraGazer._gazeTracker.isPickable=!1,this._cameraGazer._gazeTracker.isVisible=!1,this._cameraGazer._gazeTracker.name="gazeTracker",this._leftController&&(this._leftController._gazeTracker=this._cameraGazer._gazeTracker.clone("gazeTracker")),this._rightController&&(this._rightController._gazeTracker=this._cameraGazer._gazeTracker.clone("gazeTracker")))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"leftControllerGazeTrackerMesh",{get:function(){return this._leftController?this._leftController._gazeTracker:null},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"rightControllerGazeTrackerMesh",{get:function(){return this._rightController?this._rightController._gazeTracker:null},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"displayGaze",{get:function(){return this._displayGaze},set:function(t){this._displayGaze=t,t||(this._cameraGazer._gazeTracker.isVisible=!1,this._leftController&&(this._leftController._gazeTracker.isVisible=!1),this._rightController&&(this._rightController._gazeTracker.isVisible=!1))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"displayLaserPointer",{get:function(){return this._displayLaserPointer},set:function(t){this._displayLaserPointer=t,t?(this._rightController&&this._rightController._activatePointer(),this._leftController&&this._leftController._activatePointer()):(this._rightController&&(this._rightController._deactivatePointer(),this._rightController._gazeTracker.isVisible=!1),this._leftController&&(this._leftController._deactivatePointer(),this._leftController._gazeTracker.isVisible=!1))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"deviceOrientationCamera",{get:function(){return this._deviceOrientationCamera},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"currentVRCamera",{get:function(){return this._webVRready?this._webVRCamera:this._scene.activeCamera},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"webVRCamera",{get:function(){return this._webVRCamera},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"vrDeviceOrientationCamera",{get:function(){return this._vrDeviceOrientationCamera},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"vrButton",{get:function(){return this._btnVR},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"_teleportationRequestInitiated",{get:function(){return this._cameraGazer._teleportationRequestInitiated||this._leftController!==null&&this._leftController._teleportationRequestInitiated||this._rightController!==null&&this._rightController._teleportationRequestInitiated},enumerable:!1,configurable:!0}),r.prototype.completeVRInit=function(t,e){var n=this;if(this.xrTestDone=!0,e.createFallbackVRDeviceOrientationFreeCamera&&(e.useMultiview&&(e.vrDeviceOrientationCameraMetrics||(e.vrDeviceOrientationCameraMetrics=mr.GetDefault()),e.vrDeviceOrientationCameraMetrics.multiviewEnabled=!0),this._vrDeviceOrientationCamera=new Uo("VRDeviceOrientationVRHelper",this._position,this._scene,!0,e.vrDeviceOrientationCameraMetrics),this._vrDeviceOrientationCamera.angularSensibility=Number.MAX_VALUE),this._webVRCamera=new ko("WebVRHelper",this._position,this._scene,e),this._webVRCamera.useStandingMatrix(),this._cameraGazer=new Yl(function(){return n.currentVRCamera},t),!this._useCustomVRButton){this._btnVR=document.createElement("BUTTON"),this._btnVR.className="babylonVRicon",this._btnVR.id="babylonVRiconbtn",this._btnVR.title="Click to switch to VR";var i=".babylonVRicon { position: absolute; right: 20px; height: 50px; width: 80px; background-color: rgba(51,51,51,0.7); background-image: url("+(window.SVGSVGElement?"data:image/svg+xml;charset=UTF-8,%3Csvg%20xmlns%3D%22http%3A//www.w3.org/2000/svg%22%20width%3D%222048%22%20height%3D%221152%22%20viewBox%3D%220%200%202048%201152%22%20version%3D%221.1%22%3E%3Cpath%20transform%3D%22rotate%28180%201024%2C576.0000000000001%29%22%20d%3D%22m1109%2C896q17%2C0%2030%2C-12t13%2C-30t-12.5%2C-30.5t-30.5%2C-12.5l-170%2C0q-18%2C0%20-30.5%2C12.5t-12.5%2C30.5t13%2C30t30%2C12l170%2C0zm-85%2C256q59%2C0%20132.5%2C-1.5t154.5%2C-5.5t164.5%2C-11.5t163%2C-20t150%2C-30t124.5%2C-41.5q23%2C-11%2042%2C-24t38%2C-30q27%2C-25%2041%2C-61.5t14%2C-72.5l0%2C-257q0%2C-123%20-47%2C-232t-128%2C-190t-190%2C-128t-232%2C-47l-81%2C0q-37%2C0%20-68.5%2C14t-60.5%2C34.5t-55.5%2C45t-53%2C45t-53%2C34.5t-55.5%2C14t-55.5%2C-14t-53%2C-34.5t-53%2C-45t-55.5%2C-45t-60.5%2C-34.5t-68.5%2C-14l-81%2C0q-123%2C0%20-232%2C47t-190%2C128t-128%2C190t-47%2C232l0%2C257q0%2C68%2038%2C115t97%2C73q54%2C24%20124.5%2C41.5t150%2C30t163%2C20t164.5%2C11.5t154.5%2C5.5t132.5%2C1.5zm939%2C-298q0%2C39%20-24.5%2C67t-58.5%2C42q-54%2C23%20-122%2C39.5t-143.5%2C28t-155.5%2C19t-157%2C11t-148.5%2C5t-129.5%2C1.5q-59%2C0%20-130%2C-1.5t-148%2C-5t-157%2C-11t-155.5%2C-19t-143.5%2C-28t-122%2C-39.5q-34%2C-14%20-58.5%2C-42t-24.5%2C-67l0%2C-257q0%2C-106%2040.5%2C-199t110%2C-162.5t162.5%2C-109.5t199%2C-40l81%2C0q27%2C0%2052%2C14t50%2C34.5t51%2C44.5t55.5%2C44.5t63.5%2C34.5t74%2C14t74%2C-14t63.5%2C-34.5t55.5%2C-44.5t51%2C-44.5t50%2C-34.5t52%2C-14l14%2C0q37%2C0%2070%2C0.5t64.5%2C4.5t63.5%2C12t68%2C23q71%2C30%20128.5%2C78.5t98.5%2C110t63.5%2C133.5t22.5%2C149l0%2C257z%22%20fill%3D%22white%22%20/%3E%3C/svg%3E%0A":"https://cdn.babylonjs.com/Assets/vrButton.png")+"); background-size: 80%; background-repeat:no-repeat; background-position: center; border: none; outline: none; transition: transform 0.125s ease-out } .babylonVRicon:hover { transform: scale(1.05) } .babylonVRicon:active {background-color: rgba(51,51,51,1) } .babylonVRicon:focus {background-color: rgba(51,51,51,1) }";i+=".babylonVRicon.vrdisplaypresenting { display: none; }";var o=document.createElement("style");o.appendChild(document.createTextNode(i)),document.getElementsByTagName("head")[0].appendChild(o),this.moveButtonToBottomRight()}this._btnVR&&this._btnVR.addEventListener("click",function(){n.isInVRMode?n._scene.getEngine().disableVR():n.enterVR()});var a=this._scene.getEngine().getHostWindow();a&&(a.addEventListener("resize",this._onResize),document.addEventListener("fullscreenchange",this._onFullscreenChange,!1),document.addEventListener("mozfullscreenchange",this._onFullscreenChange,!1),document.addEventListener("webkitfullscreenchange",this._onFullscreenChange,!1),document.addEventListener("msfullscreenchange",this._onFullscreenChange,!1),document.onmsfullscreenchange=this._onFullscreenChange,e.createFallbackVRDeviceOrientationFreeCamera?this.displayVRButton():this._scene.getEngine().onVRDisplayChangedObservable.add(function(s){s.vrDisplay&&n.displayVRButton()}),this._onKeyDown=function(s){s.keyCode===27&&n.isInVRMode&&n.exitVR()},document.addEventListener("keydown",this._onKeyDown),this._scene.onPrePointerObservable.add(function(){n._hasEnteredVR&&n.exitVROnDoubleTap&&(n.exitVR(),n._fullscreenVRpresenting&&n._scene.getEngine().exitFullscreen())},Tt.a.POINTERDOUBLETAP,!1),this._onVRDisplayChanged=function(s){return n.onVRDisplayChanged(s)},this._onVrDisplayPresentChange=function(){return n.onVrDisplayPresentChange()},this._onVRRequestPresentStart=function(){n._webVRrequesting=!0,n.updateButtonVisibility()},this._onVRRequestPresentComplete=function(){n._webVRrequesting=!1,n.updateButtonVisibility()},t.getEngine().onVRDisplayChangedObservable.add(this._onVRDisplayChanged),t.getEngine().onVRRequestPresentStart.add(this._onVRRequestPresentStart),t.getEngine().onVRRequestPresentComplete.add(this._onVRRequestPresentComplete),a.addEventListener("vrdisplaypresentchange",this._onVrDisplayPresentChange),t.onDisposeObservable.add(function(){n.dispose()}),this._webVRCamera.onControllerMeshLoadedObservable.add(function(s){return n._onDefaultMeshLoaded(s)}),this._scene.gamepadManager.onGamepadConnectedObservable.add(this._onNewGamepadConnected),this._scene.gamepadManager.onGamepadDisconnectedObservable.add(this._onNewGamepadDisconnected),this.updateButtonVisibility(),this._circleEase=new nt,this._circleEase.setEasingMode(Ge.EASINGMODE_EASEINOUT),this._teleportationEasing=this._circleEase,t.onPointerObservable.add(function(s){n._interactionsEnabled&&t.activeCamera===n.vrDeviceOrientationCamera&&s.event.pointerType==="mouse"&&(s.type===Tt.a.POINTERDOWN?n._cameraGazer._selectionPointerDown():s.type===Tt.a.POINTERUP&&n._cameraGazer._selectionPointerUp())}),this.webVROptions.floorMeshes&&this.enableTeleportation({floorMeshes:this.webVROptions.floorMeshes}))},r.prototype._onDefaultMeshLoaded=function(t){this._leftController&&this._leftController.webVRController==t&&t.mesh&&this._leftController._setLaserPointerParent(t.mesh),this._rightController&&this._rightController.webVRController==t&&t.mesh&&this._rightController._setLaserPointerParent(t.mesh);try{this.onControllerMeshLoadedObservable.notifyObservers(t)}catch(e){l.a.Warn("Error in your custom logic onControllerMeshLoaded: "+e)}},Object.defineProperty(r.prototype,"isInVRMode",{get:function(){return this.xr&&this.webVROptions.useXR&&this.xr.baseExperience.state===pn.IN_XR||this._webVRpresenting||this._fullscreenVRpresenting},enumerable:!1,configurable:!0}),r.prototype.onVrDisplayPresentChange=function(){var t=this._scene.getEngine().getVRDevice();if(t){var e=this._webVRpresenting;this._webVRpresenting=t.isPresenting,e&&!this._webVRpresenting&&this.exitVR()}else l.a.Warn("Detected VRDisplayPresentChange on an unknown VRDisplay. Did you can enterVR on the vrExperienceHelper?");this.updateButtonVisibility()},r.prototype.onVRDisplayChanged=function(t){this._webVRsupported=t.vrSupported,this._webVRready=!!t.vrDisplay,this._webVRpresenting=t.vrDisplay&&t.vrDisplay.isPresenting,this.updateButtonVisibility()},r.prototype.moveButtonToBottomRight=function(){if(this._inputElement&&!this._useCustomVRButton&&this._btnVR){var t=this._inputElement.getBoundingClientRect();this._btnVR.style.top=t.top+t.height-70+"px",this._btnVR.style.left=t.left+t.width-100+"px"}},r.prototype.displayVRButton=function(){this._useCustomVRButton||this._btnVRDisplayed||!this._btnVR||(document.body.appendChild(this._btnVR),this._btnVRDisplayed=!0)},r.prototype.updateButtonVisibility=function(){this._btnVR&&!this._useCustomVRButton&&(this._btnVR.className="babylonVRicon",this.isInVRMode?this._btnVR.className+=" vrdisplaypresenting":(this._webVRready&&(this._btnVR.className+=" vrdisplayready"),this._webVRsupported&&(this._btnVR.className+=" vrdisplaysupported"),this._webVRrequesting&&(this._btnVR.className+=" vrdisplayrequesting")))},r.prototype.enterVR=function(){var t=this;if(this.xr)this.xr.baseExperience.enterXRAsync("immersive-vr","local-floor",this.xr.renderTarget);else{if(this.onEnteringVRObservable)try{this.onEnteringVRObservable.notifyObservers(this)}catch(o){l.a.Warn("Error in your custom logic onEnteringVR: "+o)}if(this._scene.activeCamera){if(this._position=this._scene.activeCamera.position.clone(),this.vrDeviceOrientationCamera&&(this.vrDeviceOrientationCamera.rotation=u.b.FromRotationMatrix(this._scene.activeCamera.getWorldMatrix().getRotationMatrix()).toEulerAngles(),this.vrDeviceOrientationCamera.angularSensibility=2e3),this.webVRCamera){var e=this.webVRCamera.deviceRotationQuaternion.toEulerAngles().y,n=u.b.FromRotationMatrix(this._scene.activeCamera.getWorldMatrix().getRotationMatrix()).toEulerAngles().y-e,i=this.webVRCamera.rotationQuaternion.toEulerAngles().y;this.webVRCamera.rotationQuaternion=u.b.FromEulerAngles(0,i+n,0)}this._existingCamera=this._scene.activeCamera,this._existingCamera.angularSensibilityX&&(this._cachedAngularSensibility.angularSensibilityX=this._existingCamera.angularSensibilityX,this._existingCamera.angularSensibilityX=Number.MAX_VALUE),this._existingCamera.angularSensibilityY&&(this._cachedAngularSensibility.angularSensibilityY=this._existingCamera.angularSensibilityY,this._existingCamera.angularSensibilityY=Number.MAX_VALUE),this._existingCamera.angularSensibility&&(this._cachedAngularSensibility.angularSensibility=this._existingCamera.angularSensibility,this._existingCamera.angularSensibility=Number.MAX_VALUE)}this._webVRrequesting||(this._webVRready?this._webVRpresenting||(this._scene.getEngine().onVRRequestPresentComplete.addOnce(function(o){t.onAfterEnteringVRObservable.notifyObservers({success:o})}),this._webVRCamera.position=this._position,this._scene.activeCamera=this._webVRCamera):this._vrDeviceOrientationCamera&&(this._vrDeviceOrientationCamera.position=this._position,this._scene.activeCamera&&(this._vrDeviceOrientationCamera.minZ=this._scene.activeCamera.minZ),this._scene.activeCamera=this._vrDeviceOrientationCamera,this._scene.getEngine().enterFullscreen(this.requestPointerLockOnFullScreen),this.updateButtonVisibility(),this._vrDeviceOrientationCamera.onViewMatrixChangedObservable.addOnce(function(){t.onAfterEnteringVRObservable.notifyObservers({success:!0})})),this._scene.activeCamera&&this._inputElement&&this._scene.activeCamera.attachControl(),this._interactionsEnabled&&this._scene.registerBeforeRender(this.beforeRender),this._displayLaserPointer&&[this._leftController,this._rightController].forEach(function(o){o&&o._activatePointer()}),this._hasEnteredVR=!0)}},r.prototype.exitVR=function(){if(this.xr)this.xr.baseExperience.exitXRAsync();else if(this._hasEnteredVR){if(this.onExitingVRObservable)try{this.onExitingVRObservable.notifyObservers(this)}catch(e){l.a.Warn("Error in your custom logic onExitingVR: "+e)}this._webVRpresenting&&this._scene.getEngine().disableVR(),this._scene.activeCamera&&(this._position=this._scene.activeCamera.position.clone()),this.vrDeviceOrientationCamera&&(this.vrDeviceOrientationCamera.angularSensibility=Number.MAX_VALUE),this._deviceOrientationCamera?(this._deviceOrientationCamera.position=this._position,this._scene.activeCamera=this._deviceOrientationCamera,this._cachedAngularSensibility.angularSensibilityX&&(this._deviceOrientationCamera.angularSensibilityX=this._cachedAngularSensibility.angularSensibilityX,this._cachedAngularSensibility.angularSensibilityX=null),this._cachedAngularSensibility.angularSensibilityY&&(this._deviceOrientationCamera.angularSensibilityY=this._cachedAngularSensibility.angularSensibilityY,this._cachedAngularSensibility.angularSensibilityY=null),this._cachedAngularSensibility.angularSensibility&&(this._deviceOrientationCamera.angularSensibility=this._cachedAngularSensibility.angularSensibility,this._cachedAngularSensibility.angularSensibility=null)):this._existingCamera&&(this._existingCamera.position=this._position,this._scene.activeCamera=this._existingCamera,this._inputElement&&this._scene.activeCamera.attachControl(),this._cachedAngularSensibility.angularSensibilityX&&(this._existingCamera.angularSensibilityX=this._cachedAngularSensibility.angularSensibilityX,this._cachedAngularSensibility.angularSensibilityX=null),this._cachedAngularSensibility.angularSensibilityY&&(this._existingCamera.angularSensibilityY=this._cachedAngularSensibility.angularSensibilityY,this._cachedAngularSensibility.angularSensibilityY=null),this._cachedAngularSensibility.angularSensibility&&(this._existingCamera.angularSensibility=this._cachedAngularSensibility.angularSensibility,this._cachedAngularSensibility.angularSensibility=null)),this.updateButtonVisibility(),this._interactionsEnabled&&(this._scene.unregisterBeforeRender(this.beforeRender),this._cameraGazer._gazeTracker.isVisible=!1,this._leftController&&(this._leftController._gazeTracker.isVisible=!1),this._rightController&&(this._rightController._gazeTracker.isVisible=!1)),this._scene.getEngine().resize(),[this._leftController,this._rightController].forEach(function(e){e&&e._deactivatePointer()}),this._hasEnteredVR=!1;var t=this._scene.getEngine();t._onVrDisplayPresentChange&&t._onVrDisplayPresentChange()}},Object.defineProperty(r.prototype,"position",{get:function(){return this._position},set:function(t){this._position=t,this._scene.activeCamera&&(this._scene.activeCamera.position=t)},enumerable:!1,configurable:!0}),r.prototype.enableInteractions=function(){var t=this;if(!this._interactionsEnabled){if(this._interactionsRequested=!0,this.xr)return void(this.xr.baseExperience.state===pn.IN_XR&&this.xr.pointerSelection.attach());this._leftController&&this._enableInteractionOnController(this._leftController),this._rightController&&this._enableInteractionOnController(this._rightController),this.raySelectionPredicate=function(e){return e.isVisible&&(e.isPickable||e.name===t._floorMeshName)},this.meshSelectionPredicate=function(){return!0},this._raySelectionPredicate=function(e){return!!(t._isTeleportationFloor(e)||e.name.indexOf("gazeTracker")===-1&&e.name.indexOf("teleportationTarget")===-1&&e.name.indexOf("torusTeleportation")===-1)&&t.raySelectionPredicate(e)},this._interactionsEnabled=!0}},Object.defineProperty(r.prototype,"_noControllerIsActive",{get:function(){return!(this._leftController&&this._leftController._activePointer||this._rightController&&this._rightController._activePointer)},enumerable:!1,configurable:!0}),r.prototype._isTeleportationFloor=function(t){for(var e=0;e<this._floorMeshesCollection.length;e++)if(this._floorMeshesCollection[e].id===t.id)return!0;return!(!this._floorMeshName||t.name!==this._floorMeshName)},r.prototype.addFloorMesh=function(t){this._floorMeshesCollection&&(this._floorMeshesCollection.indexOf(t)>-1||this._floorMeshesCollection.push(t))},r.prototype.removeFloorMesh=function(t){if(this._floorMeshesCollection){var e=this._floorMeshesCollection.indexOf(t);e!==-1&&this._floorMeshesCollection.splice(e,1)}},r.prototype.enableTeleportation=function(t){var e=this;if(t===void 0&&(t={}),!this._teleportationInitialized){if(this._teleportationRequested=!0,this.enableInteractions(),this.webVROptions.useXR&&(t.floorMeshes||t.floorMeshName)){var n=t.floorMeshes||[];if(!n.length){var i=this._scene.getMeshByName(t.floorMeshName);i&&n.push(i)}if(this.xr)return n.forEach(function(s){e.xr.teleportation.addFloorMesh(s)}),void(this.xr.teleportation.attached||this.xr.teleportation.attach());if(!this.xrTestDone){var o=function(){e.xrTestDone&&(e._scene.unregisterBeforeRender(o),e.xr?e.xr.teleportation.attached||e.xr.teleportation.attach():e.enableTeleportation(t))};return void this._scene.registerBeforeRender(o)}}t.floorMeshName&&(this._floorMeshName=t.floorMeshName),t.floorMeshes&&(this._floorMeshesCollection=t.floorMeshes),t.teleportationMode&&(this._teleportationMode=t.teleportationMode),t.teleportationTime&&t.teleportationTime>0&&(this._teleportationTime=t.teleportationTime),t.teleportationSpeed&&t.teleportationSpeed>0&&(this._teleportationSpeed=t.teleportationSpeed),t.easingFunction!==void 0&&(this._teleportationEasing=t.easingFunction),this._leftController!=null&&this._enableTeleportationOnController(this._leftController),this._rightController!=null&&this._enableTeleportationOnController(this._rightController);var a=new yn.a;a.vignetteColor=new M.b(0,0,0,0),a.vignetteEnabled=!0,this._postProcessMove=new Go("postProcessMove",1,this._webVRCamera,void 0,void 0,void 0,void 0,a),this._webVRCamera.detachPostProcess(this._postProcessMove),this._teleportationInitialized=!0,this._isDefaultTeleportationTarget&&(this._createTeleportationCircles(),this._teleportationTarget.scaling.scaleInPlace(this._webVRCamera.deviceScaleFactor))}},r.prototype._enableInteractionOnController=function(t){var e=this;t.webVRController.mesh&&(t._interactionsEnabled=!0,this.isInVRMode&&this._displayLaserPointer&&t._activatePointer(),this.webVROptions.laserToggle&&t.webVRController.onMainButtonStateChangedObservable.add(function(n){e._displayLaserPointer&&n.value===1&&(t._activePointer?t._deactivatePointer():t._activatePointer(),e.displayGaze&&(t._gazeTracker.isVisible=t._activePointer))}),t.webVRController.onTriggerStateChangedObservable.add(function(n){var i=t;e._noControllerIsActive&&(i=e._cameraGazer),i._pointerDownOnMeshAsked?n.value<e._padSensibilityDown&&i._selectionPointerUp():n.value>e._padSensibilityUp&&i._selectionPointerDown()}))},r.prototype._checkTeleportWithRay=function(t,e){this._teleportationRequestInitiated&&!e._teleportationRequestInitiated||(e._teleportationRequestInitiated?Math.sqrt(t.y*t.y+t.x*t.x)<this._padSensibilityDown&&(this._teleportActive&&this.teleportCamera(this._haloCenter),e._teleportationRequestInitiated=!1):t.y<-this._padSensibilityUp&&e._dpadPressed&&(e._activatePointer(),e._teleportationRequestInitiated=!0))},r.prototype._checkRotate=function(t,e){e._teleportationRequestInitiated||(e._rotationLeftAsked?t.x>-this._padSensibilityDown&&(e._rotationLeftAsked=!1):t.x<-this._padSensibilityUp&&e._dpadPressed&&(e._rotationLeftAsked=!0,this._rotationAllowed&&this._rotateCamera(!1)),e._rotationRightAsked?t.x<this._padSensibilityDown&&(e._rotationRightAsked=!1):t.x>this._padSensibilityUp&&e._dpadPressed&&(e._rotationRightAsked=!0,this._rotationAllowed&&this._rotateCamera(!0)))},r.prototype._checkTeleportBackwards=function(t,e){if(!e._teleportationRequestInitiated)if(t.y>this._padSensibilityUp&&e._dpadPressed){if(!e._teleportationBackRequestInitiated){if(!this.currentVRCamera)return;var n=u.b.FromRotationMatrix(this.currentVRCamera.getWorldMatrix().getRotationMatrix()),i=this.currentVRCamera.position;this.currentVRCamera.devicePosition&&this.currentVRCamera.deviceRotationQuaternion&&(n=this.currentVRCamera.deviceRotationQuaternion,i=this.currentVRCamera.devicePosition),n.toEulerAnglesToRef(this._workingVector),this._workingVector.z=0,this._workingVector.x=0,u.b.RotationYawPitchRollToRef(this._workingVector.y,this._workingVector.x,this._workingVector.z,this._workingQuaternion),this._workingQuaternion.toRotationMatrix(this._workingMatrix),u.e.TransformCoordinatesToRef(this._teleportBackwardsVector,this._workingMatrix,this._workingVector);var o=new fn.a(i,this._workingVector),a=this._scene.pickWithRay(o,this._raySelectionPredicate);a&&a.pickedPoint&&a.pickedMesh&&this._isTeleportationFloor(a.pickedMesh)&&a.distance<5&&this.teleportCamera(a.pickedPoint),e._teleportationBackRequestInitiated=!0}}else e._teleportationBackRequestInitiated=!1},r.prototype._enableTeleportationOnController=function(t){var e=this;t.webVRController.mesh&&(t._interactionsEnabled||this._enableInteractionOnController(t),t._interactionsEnabled=!0,t._teleportationEnabled=!0,t.webVRController.controllerType===ri.VIVE&&(t._dpadPressed=!1,t.webVRController.onPadStateChangedObservable.add(function(n){t._dpadPressed=n.pressed,t._dpadPressed||(t._rotationLeftAsked=!1,t._rotationRightAsked=!1,t._teleportationBackRequestInitiated=!1)})),t.webVRController.onPadValuesChangedObservable.add(function(n){e.teleportationEnabled&&(e._checkTeleportBackwards(n,t),e._checkTeleportWithRay(n,t)),e._checkRotate(n,t)}))},r.prototype._createTeleportationCircles=function(){this._teleportationTarget=De.a.CreateGround("teleportationTarget",2,2,2,this._scene),this._teleportationTarget.isPickable=!1;var t=new Ti.a("DynamicTexture",512,this._scene,!0);t.hasAlpha=!0;var e=t.getContext();e.beginPath(),e.arc(256,256,200,0,2*Math.PI,!1),e.fillStyle=this._teleportationFillColor,e.fill(),e.lineWidth=10,e.strokeStyle=this._teleportationBorderColor,e.stroke(),e.closePath(),t.update();var n=new Ft.a("TextPlaneMaterial",this._scene);n.diffuseTexture=t,this._teleportationTarget.material=n;var i=De.a.CreateTorus("torusTeleportation",.75,.1,25,this._scene,!1);i.isPickable=!1,i.parent=this._teleportationTarget;var o=new k("animationInnerCircle","position.y",30,k.ANIMATIONTYPE_FLOAT,k.ANIMATIONLOOPMODE_CYCLE),a=[];a.push({frame:0,value:0}),a.push({frame:30,value:.4}),a.push({frame:60,value:0}),o.setKeys(a);var s=new on;s.setEasingMode(Ge.EASINGMODE_EASEINOUT),o.setEasingFunction(s),i.animations=[],i.animations.push(o),this._scene.beginAnimation(i,0,60,!0),this._hideTeleportationTarget()},r.prototype._displayTeleportationTarget=function(){this._teleportActive=!0,this._teleportationInitialized&&(this._teleportationTarget.isVisible=!0,this._isDefaultTeleportationTarget&&(this._teleportationTarget.getChildren()[0].isVisible=!0))},r.prototype._hideTeleportationTarget=function(){this._teleportActive=!1,this._teleportationInitialized&&(this._teleportationTarget.isVisible=!1,this._isDefaultTeleportationTarget&&(this._teleportationTarget.getChildren()[0].isVisible=!1))},r.prototype._rotateCamera=function(t){var e=this;if(this.currentVRCamera instanceof Yn){t?this._rotationAngle++:this._rotationAngle--,this.currentVRCamera.animations=[];var n=u.b.FromRotationMatrix(u.a.RotationY(Math.PI/4*this._rotationAngle)),i=new k("animationRotation","rotationQuaternion",90,k.ANIMATIONTYPE_QUATERNION,k.ANIMATIONLOOPMODE_CONSTANT),o=[];o.push({frame:0,value:this.currentVRCamera.rotationQuaternion}),o.push({frame:6,value:n}),i.setKeys(o),i.setEasingFunction(this._circleEase),this.currentVRCamera.animations.push(i),this._postProcessMove.animations=[];var a=new k("animationPP","vignetteWeight",90,k.ANIMATIONTYPE_FLOAT,k.ANIMATIONLOOPMODE_CONSTANT),s=[];s.push({frame:0,value:0}),s.push({frame:3,value:4}),s.push({frame:6,value:0}),a.setKeys(s),a.setEasingFunction(this._circleEase),this._postProcessMove.animations.push(a);var d=new k("animationPP2","vignetteStretch",90,k.ANIMATIONTYPE_FLOAT,k.ANIMATIONLOOPMODE_CONSTANT),p=[];p.push({frame:0,value:0}),p.push({frame:3,value:10}),p.push({frame:6,value:0}),d.setKeys(p),d.setEasingFunction(this._circleEase),this._postProcessMove.animations.push(d),this._postProcessMove.imageProcessingConfiguration.vignetteWeight=0,this._postProcessMove.imageProcessingConfiguration.vignetteStretch=0,this._postProcessMove.samples=4,this._webVRCamera.attachPostProcess(this._postProcessMove),this._scene.beginAnimation(this._postProcessMove,0,6,!1,1,function(){e._webVRCamera.detachPostProcess(e._postProcessMove)}),this._scene.beginAnimation(this.currentVRCamera,0,6,!1,1)}},r.prototype._moveTeleportationSelectorTo=function(t,e,n){if(t.pickedPoint){e._teleportationRequestInitiated&&(this._displayTeleportationTarget(),this._haloCenter.copyFrom(t.pickedPoint),this._teleportationTarget.position.copyFrom(t.pickedPoint));var i=this._convertNormalToDirectionOfRay(t.getNormal(!0,!1),n);if(i){var o=u.e.Cross(ye.a.Y,i),a=u.e.Cross(i,o);u.e.RotationFromAxisToRef(a,i,o,this._teleportationTarget.rotation)}this._teleportationTarget.position.y+=.1}},r.prototype.teleportCamera=function(t){var e=this;if(this.currentVRCamera instanceof Yn){this.webVRCamera.leftCamera?(this._workingVector.copyFrom(this.webVRCamera.leftCamera.globalPosition),this._workingVector.subtractInPlace(this.webVRCamera.position),t.subtractToRef(this._workingVector,this._workingVector)):this._workingVector.copyFrom(t),this.isInVRMode?this._workingVector.y+=this.webVRCamera.deviceDistanceToRoomGround()*this._webVRCamera.deviceScaleFactor:this._workingVector.y+=this._defaultHeight,this.onBeforeCameraTeleport.notifyObservers(this._workingVector);var n,i;if(this._teleportationMode==r.TELEPORTATIONMODE_CONSTANTSPEED){i=90;var o=u.e.Distance(this.currentVRCamera.position,this._workingVector);n=this._teleportationSpeed/o}else i=Math.round(90*this._teleportationTime/1e3),n=1;this.currentVRCamera.animations=[];var a=new k("animationCameraTeleportation","position",90,k.ANIMATIONTYPE_VECTOR3,k.ANIMATIONLOOPMODE_CONSTANT),s=[{frame:0,value:this.currentVRCamera.position},{frame:i,value:this._workingVector}];a.setKeys(s),a.setEasingFunction(this._teleportationEasing),this.currentVRCamera.animations.push(a),this._postProcessMove.animations=[];var d=Math.round(i/2),p=new k("animationPP","vignetteWeight",90,k.ANIMATIONTYPE_FLOAT,k.ANIMATIONLOOPMODE_CONSTANT),b=[];b.push({frame:0,value:0}),b.push({frame:d,value:8}),b.push({frame:i,value:0}),p.setKeys(b),this._postProcessMove.animations.push(p);var P=new k("animationPP2","vignetteStretch",90,k.ANIMATIONTYPE_FLOAT,k.ANIMATIONLOOPMODE_CONSTANT),O=[];O.push({frame:0,value:0}),O.push({frame:d,value:10}),O.push({frame:i,value:0}),P.setKeys(O),this._postProcessMove.animations.push(P),this._postProcessMove.imageProcessingConfiguration.vignetteWeight=0,this._postProcessMove.imageProcessingConfiguration.vignetteStretch=0,this._webVRCamera.attachPostProcess(this._postProcessMove),this._scene.beginAnimation(this._postProcessMove,0,i,!1,n,function(){e._webVRCamera.detachPostProcess(e._postProcessMove)}),this._scene.beginAnimation(this.currentVRCamera,0,i,!1,n,function(){e.onAfterCameraTeleport.notifyObservers(e._workingVector)}),this._hideTeleportationTarget()}},r.prototype._convertNormalToDirectionOfRay=function(t,e){return t&&Math.acos(u.e.Dot(t,e.direction))<Math.PI/2&&t.scaleInPlace(-1),t},r.prototype._castRayAndSelectObject=function(t){if(this.currentVRCamera instanceof Yn){var e=t._getForwardRay(this._rayLength),n=this._scene.pickWithRay(e,this._raySelectionPredicate);if(n&&(t._laserPointer&&(n.originMesh=t._laserPointer.parent),this._scene.simulatePointerMove(n,{pointerId:t._id})),t._currentHit=n,n&&n.pickedPoint){if(this._displayGaze){var i=1;t._gazeTracker.isVisible=!0,t._isActionableMesh&&(i=3),this.updateGazeTrackerScale&&(t._gazeTracker.scaling.x=n.distance*i,t._gazeTracker.scaling.y=n.distance*i,t._gazeTracker.scaling.z=n.distance*i);var o=this._convertNormalToDirectionOfRay(n.getNormal(),e);if(o){var a=u.e.Cross(ye.a.Y,o),s=u.e.Cross(o,a);u.e.RotationFromAxisToRef(s,o,a,t._gazeTracker.rotation)}t._gazeTracker.position.copyFrom(n.pickedPoint),t._gazeTracker.position.x<0?t._gazeTracker.position.x+=.002:t._gazeTracker.position.x-=.002,t._gazeTracker.position.y<0?t._gazeTracker.position.y+=.002:t._gazeTracker.position.y-=.002,t._gazeTracker.position.z<0?t._gazeTracker.position.z+=.002:t._gazeTracker.position.z-=.002}t._updatePointerDistance(n.distance)}else t._updatePointerDistance(),t._gazeTracker.isVisible=!1;if(n&&n.pickedMesh){if(this._teleportationInitialized&&this._isTeleportationFloor(n.pickedMesh)&&n.pickedPoint)return t._currentMeshSelected&&!this._isTeleportationFloor(t._currentMeshSelected)&&this._notifySelectedMeshUnselected(t._currentMeshSelected),t._currentMeshSelected=null,void(t._teleportationRequestInitiated&&this._moveTeleportationSelectorTo(n,t,e));if(n.pickedMesh!==t._currentMeshSelected)if(this.meshSelectionPredicate(n.pickedMesh)){this.onNewMeshPicked.notifyObservers(n),t._currentMeshSelected=n.pickedMesh,n.pickedMesh.isPickable&&n.pickedMesh.actionManager?(this.changeGazeColor(this._pickedGazeColor),this.changeLaserColor(this._pickedLaserColor),t._isActionableMesh=!0):(this.changeGazeColor(this._gazeColor),this.changeLaserColor(this._laserColor),t._isActionableMesh=!1);try{this.onNewMeshSelected.notifyObservers(n.pickedMesh);var d=t;d.webVRController&&this.onMeshSelectedWithController.notifyObservers({mesh:n.pickedMesh,controller:d.webVRController})}catch(p){l.a.Warn("Error while raising onNewMeshSelected or onMeshSelectedWithController: "+p)}}else this._notifySelectedMeshUnselected(t._currentMeshSelected),t._currentMeshSelected=null,this.changeGazeColor(this._gazeColor),this.changeLaserColor(this._laserColor)}else this._notifySelectedMeshUnselected(t._currentMeshSelected),t._currentMeshSelected=null,this.changeGazeColor(this._gazeColor),this.changeLaserColor(this._laserColor)}},r.prototype._notifySelectedMeshUnselected=function(t){t&&this.onSelectedMeshUnselected.notifyObservers(t)},r.prototype.setLaserColor=function(t,e){e===void 0&&(e=this._pickedLaserColor),this._laserColor=t,this._pickedLaserColor=e},r.prototype.setLaserLightingState=function(t){t===void 0&&(t=!0),this._leftController&&this._leftController._setLaserPointerLightingDisabled(!t),this._rightController&&this._rightController._setLaserPointerLightingDisabled(!t)},r.prototype.setGazeColor=function(t,e){e===void 0&&(e=this._pickedGazeColor),this._gazeColor=t,this._pickedGazeColor=e},r.prototype.changeLaserColor=function(t){this.updateControllerLaserColor&&(this._leftController&&this._leftController._setLaserPointerColor(t),this._rightController&&this._rightController._setLaserPointerColor(t))},r.prototype.changeGazeColor=function(t){this.updateGazeTrackerColor&&this._cameraGazer._gazeTracker.material&&(this._cameraGazer._gazeTracker.material.emissiveColor=t,this._leftController&&(this._leftController._gazeTracker.material.emissiveColor=t),this._rightController&&(this._rightController._gazeTracker.material.emissiveColor=t))},r.prototype.dispose=function(){this.isInVRMode&&this.exitVR(),this._postProcessMove&&this._postProcessMove.dispose(),this._webVRCamera&&this._webVRCamera.dispose(),this._vrDeviceOrientationCamera&&this._vrDeviceOrientationCamera.dispose(),!this._useCustomVRButton&&this._btnVR&&this._btnVR.parentNode&&document.body.removeChild(this._btnVR),this._deviceOrientationCamera&&this._scene.activeCamera!=this._deviceOrientationCamera&&this._deviceOrientationCamera.dispose(),this._cameraGazer&&this._cameraGazer.dispose(),this._leftController&&this._leftController.dispose(),this._rightController&&this._rightController.dispose(),this._teleportationTarget&&this._teleportationTarget.dispose(),this.xr&&this.xr.dispose(),this._floorMeshesCollection=[],document.removeEventListener("keydown",this._onKeyDown),window.removeEventListener("vrdisplaypresentchange",this._onVrDisplayPresentChange),window.removeEventListener("resize",this._onResize),document.removeEventListener("fullscreenchange",this._onFullscreenChange),document.removeEventListener("mozfullscreenchange",this._onFullscreenChange),document.removeEventListener("webkitfullscreenchange",this._onFullscreenChange),document.removeEventListener("msfullscreenchange",this._onFullscreenChange),document.onmsfullscreenchange=null,this._scene.getEngine().onVRDisplayChangedObservable.removeCallback(this._onVRDisplayChanged),this._scene.getEngine().onVRRequestPresentStart.removeCallback(this._onVRRequestPresentStart),this._scene.getEngine().onVRRequestPresentComplete.removeCallback(this._onVRRequestPresentComplete),window.removeEventListener("vrdisplaypresentchange",this._onVrDisplayPresentChange),this._scene.gamepadManager.onGamepadConnectedObservable.removeCallback(this._onNewGamepadConnected),this._scene.gamepadManager.onGamepadDisconnectedObservable.removeCallback(this._onNewGamepadDisconnected),this._scene.unregisterBeforeRender(this.beforeRender)},r.prototype.getClassName=function(){return"VRExperienceHelper"},r.TELEPORTATIONMODE_CONSTANTTIME=0,r.TELEPORTATIONMODE_CONSTANTSPEED=1,r}(),vr=f(64),br=(oi={root:0,found:!1},function(r,t,e,n){oi.root=0,oi.found=!1;var i=t*t-4*r*e;if(i<0)return oi;var o=Math.sqrt(i),a=(-t-o)/(2*r),s=(-t+o)/(2*r);if(a>s){var d=s;s=a,a=d}return a>0&&a<n?(oi.root=a,oi.found=!0,oi):(s>0&&s<n&&(oi.root=s,oi.found=!0),oi)}),Ql=function(){function r(){this._collisionPoint=u.e.Zero(),this._planeIntersectionPoint=u.e.Zero(),this._tempVector=u.e.Zero(),this._tempVector2=u.e.Zero(),this._tempVector3=u.e.Zero(),this._tempVector4=u.e.Zero(),this._edge=u.e.Zero(),this._baseToVertex=u.e.Zero(),this._destinationPoint=u.e.Zero(),this._slidePlaneNormal=u.e.Zero(),this._displacementVector=u.e.Zero(),this._radius=u.e.One(),this._retry=0,this._basePointWorld=u.e.Zero(),this._velocityWorld=u.e.Zero(),this._normalizedVelocity=u.e.Zero(),this._collisionMask=-1}return Object.defineProperty(r.prototype,"collisionMask",{get:function(){return this._collisionMask},set:function(t){this._collisionMask=isNaN(t)?-1:t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"slidePlaneNormal",{get:function(){return this._slidePlaneNormal},enumerable:!1,configurable:!0}),r.prototype._initialize=function(t,e,n){this._velocity=e,u.e.NormalizeToRef(e,this._normalizedVelocity),this._basePoint=t,t.multiplyToRef(this._radius,this._basePointWorld),e.multiplyToRef(this._radius,this._velocityWorld),this._velocityWorldLength=this._velocityWorld.length(),this._epsilon=n,this.collisionFound=!1},r.prototype._checkPointInTriangle=function(t,e,n,i,o){e.subtractToRef(t,this._tempVector),n.subtractToRef(t,this._tempVector2),u.e.CrossToRef(this._tempVector,this._tempVector2,this._tempVector4);var a=u.e.Dot(this._tempVector4,o);return!(a<0)&&(i.subtractToRef(t,this._tempVector3),u.e.CrossToRef(this._tempVector2,this._tempVector3,this._tempVector4),!((a=u.e.Dot(this._tempVector4,o))<0)&&(u.e.CrossToRef(this._tempVector3,this._tempVector,this._tempVector4),(a=u.e.Dot(this._tempVector4,o))>=0))},r.prototype._canDoCollision=function(t,e,n,i){var o=u.e.Distance(this._basePointWorld,t),a=Math.max(this._radius.x,this._radius.y,this._radius.z);return!(o>this._velocityWorldLength+a+e)&&!!function(s,d,p,b){return!(s.x>p.x+b)&&!(p.x-b>d.x)&&!(s.y>p.y+b)&&!(p.y-b>d.y)&&!(s.z>p.z+b)&&!(p.z-b>d.z)}(n,i,this._basePointWorld,this._velocityWorldLength+a)},r.prototype._testTriangle=function(t,e,n,i,o,a,s){var d,p=!1;e||(e=[]),e[t]||(e[t]=new vr.a(0,0,0,0),e[t].copyFromPoints(n,i,o));var b=e[t];if(a||b.isFrontFacingTo(this._normalizedVelocity,0)){var P=b.signedDistanceTo(this._basePoint),O=u.e.Dot(b.normal,this._velocity);if(O==0){if(Math.abs(P)>=1)return;p=!0,d=0}else{var B=(1-P)/O;if((d=(-1-P)/O)>B){var F=B;B=d,d=F}if(d>1||B<0)return;d<0&&(d=0),d>1&&(d=1)}this._collisionPoint.copyFromFloats(0,0,0);var z=!1,J=1;if(p||(this._basePoint.subtractToRef(b.normal,this._planeIntersectionPoint),this._velocity.scaleToRef(d,this._tempVector),this._planeIntersectionPoint.addInPlace(this._tempVector),this._checkPointInTriangle(this._planeIntersectionPoint,n,i,o,b.normal)&&(z=!0,J=d,this._collisionPoint.copyFrom(this._planeIntersectionPoint))),!z){var ie=this._velocity.lengthSquared(),se=ie;this._basePoint.subtractToRef(n,this._tempVector);var ce=2*u.e.Dot(this._velocity,this._tempVector),ue=this._tempVector.lengthSquared()-1,fe=br(se,ce,ue,J);fe.found&&(J=fe.root,z=!0,this._collisionPoint.copyFrom(n)),this._basePoint.subtractToRef(i,this._tempVector),ce=2*u.e.Dot(this._velocity,this._tempVector),ue=this._tempVector.lengthSquared()-1,(fe=br(se,ce,ue,J)).found&&(J=fe.root,z=!0,this._collisionPoint.copyFrom(i)),this._basePoint.subtractToRef(o,this._tempVector),ce=2*u.e.Dot(this._velocity,this._tempVector),ue=this._tempVector.lengthSquared()-1,(fe=br(se,ce,ue,J)).found&&(J=fe.root,z=!0,this._collisionPoint.copyFrom(o)),i.subtractToRef(n,this._edge),n.subtractToRef(this._basePoint,this._baseToVertex);var ve=this._edge.lengthSquared(),Te=u.e.Dot(this._edge,this._velocity),Re=u.e.Dot(this._edge,this._baseToVertex);if(se=ve*-ie+Te*Te,ce=ve*(2*u.e.Dot(this._velocity,this._baseToVertex))-2*Te*Re,ue=ve*(1-this._baseToVertex.lengthSquared())+Re*Re,(fe=br(se,ce,ue,J)).found){var Ae=(Te*fe.root-Re)/ve;Ae>=0&&Ae<=1&&(J=fe.root,z=!0,this._edge.scaleInPlace(Ae),n.addToRef(this._edge,this._collisionPoint))}o.subtractToRef(i,this._edge),i.subtractToRef(this._basePoint,this._baseToVertex),ve=this._edge.lengthSquared(),Te=u.e.Dot(this._edge,this._velocity),Re=u.e.Dot(this._edge,this._baseToVertex),se=ve*-ie+Te*Te,ce=ve*(2*u.e.Dot(this._velocity,this._baseToVertex))-2*Te*Re,ue=ve*(1-this._baseToVertex.lengthSquared())+Re*Re,(fe=br(se,ce,ue,J)).found&&(Ae=(Te*fe.root-Re)/ve)>=0&&Ae<=1&&(J=fe.root,z=!0,this._edge.scaleInPlace(Ae),i.addToRef(this._edge,this._collisionPoint)),n.subtractToRef(o,this._edge),o.subtractToRef(this._basePoint,this._baseToVertex),ve=this._edge.lengthSquared(),Te=u.e.Dot(this._edge,this._velocity),Re=u.e.Dot(this._edge,this._baseToVertex),se=ve*-ie+Te*Te,ce=ve*(2*u.e.Dot(this._velocity,this._baseToVertex))-2*Te*Re,ue=ve*(1-this._baseToVertex.lengthSquared())+Re*Re,(fe=br(se,ce,ue,J)).found&&(Ae=(Te*fe.root-Re)/ve)>=0&&Ae<=1&&(J=fe.root,z=!0,this._edge.scaleInPlace(Ae),o.addToRef(this._edge,this._collisionPoint))}if(z){var Ee=J*this._velocity.length();(!this.collisionFound||Ee<this._nearestDistance)&&(s.collisionResponse&&(this.intersectionPoint?this.intersectionPoint.copyFrom(this._collisionPoint):this.intersectionPoint=this._collisionPoint.clone(),this._nearestDistance=Ee,this.collisionFound=!0),this.collidedMesh=s)}}},r.prototype._collide=function(t,e,n,i,o,a,s,d){if(n&&n.length!==0)for(p=i;p<o;p+=3)b=e[n[p]-a],P=e[n[p+1]-a],O=e[n[p+2]-a],this._testTriangle(p,t,O,P,b,s,d);else for(var p=0;p<e.length;p+=3){var b=e[p],P=e[p+1],O=e[p+2];this._testTriangle(p,t,O,P,b,s,d)}},r.prototype._getResponse=function(t,e){t.addToRef(e,this._destinationPoint),e.scaleInPlace(this._nearestDistance/e.length()),this._basePoint.addToRef(e,t),t.subtractToRef(this.intersectionPoint,this._slidePlaneNormal),this._slidePlaneNormal.normalize(),this._slidePlaneNormal.scaleToRef(this._epsilon,this._displacementVector),t.addInPlace(this._displacementVector),this.intersectionPoint.addInPlace(this._displacementVector),this._slidePlaneNormal.scaleInPlace(vr.a.SignedDistanceToPlaneFromPositionAndNormal(this.intersectionPoint,this._slidePlaneNormal,this._destinationPoint)),this._destinationPoint.subtractInPlace(this._slidePlaneNormal),this._destinationPoint.subtractToRef(this.intersectionPoint,e)},r}(),ql=function(){function r(){this._scaledPosition=u.e.Zero(),this._scaledVelocity=u.e.Zero(),this._finalPosition=u.e.Zero()}return r.prototype.getNewPosition=function(t,e,n,i,o,a,s){t.divideToRef(n._radius,this._scaledPosition),e.divideToRef(n._radius,this._scaledVelocity),n.collidedMesh=null,n._retry=0,n._initialVelocity=this._scaledVelocity,n._initialPosition=this._scaledPosition,this._collideWithWorld(this._scaledPosition,this._scaledVelocity,n,i,this._finalPosition,o),this._finalPosition.multiplyInPlace(n._radius),a(s,this._finalPosition,n.collidedMesh)},r.prototype.createCollider=function(){return new Ql},r.prototype.init=function(t){this._scene=t},r.prototype._collideWithWorld=function(t,e,n,i,o,a){a===void 0&&(a=null);var s=10*Ue.a.CollisionsEpsilon;if(n._retry>=i)o.copyFrom(t);else{var d=a?a.collisionMask:n.collisionMask;n._initialize(t,e,s);for(var p=a&&a.surroundingMeshes||this._scene.meshes,b=0;b<p.length;b++){var P=p[b];P.isEnabled()&&P.checkCollisions&&P.subMeshes&&P!==a&&d&P.collisionGroup&&P._checkCollision(n)}n.collisionFound?(e.x===0&&e.y===0&&e.z===0||n._getResponse(t,e),e.length()<=s?o.copyFrom(t):(n._retry++,this._collideWithWorld(t,e,n,i,o,a))):t.addToRef(e,o)}},r}();_e.a.CollisionCoordinatorFactory=function(){return new ql};var nr=f(54),qf=f(114),Zf=f(147),ms=f(103),Vi=f(43),Zl=f(113),Jl=function(){function r(t,e,n,i,o,a){this.entries=new Array,this._boundingVectors=new Array,this._capacity=n,this._depth=i,this._maxDepth=o,this._creationFunc=a,this._minPoint=t,this._maxPoint=e,this._boundingVectors.push(t.clone()),this._boundingVectors.push(e.clone()),this._boundingVectors.push(t.clone()),this._boundingVectors[2].x=e.x,this._boundingVectors.push(t.clone()),this._boundingVectors[3].y=e.y,this._boundingVectors.push(t.clone()),this._boundingVectors[4].z=e.z,this._boundingVectors.push(e.clone()),this._boundingVectors[5].z=t.z,this._boundingVectors.push(e.clone()),this._boundingVectors[6].x=t.x,this._boundingVectors.push(e.clone()),this._boundingVectors[7].y=t.y}return Object.defineProperty(r.prototype,"capacity",{get:function(){return this._capacity},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"minPoint",{get:function(){return this._minPoint},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"maxPoint",{get:function(){return this._maxPoint},enumerable:!1,configurable:!0}),r.prototype.addEntry=function(t){if(this.blocks)for(var e=0;e<this.blocks.length;e++)this.blocks[e].addEntry(t);else this._creationFunc(t,this),this.entries.length>this.capacity&&this._depth<this._maxDepth&&this.createInnerBlocks()},r.prototype.removeEntry=function(t){if(this.blocks)for(var e=0;e<this.blocks.length;e++)this.blocks[e].removeEntry(t);else{var n=this.entries.indexOf(t);n>-1&&this.entries.splice(n,1)}},r.prototype.addEntries=function(t){for(var e=0;e<t.length;e++){var n=t[e];this.addEntry(n)}},r.prototype.select=function(t,e,n){if(ms.a.IsInFrustum(this._boundingVectors,t)){if(this.blocks){for(var i=0;i<this.blocks.length;i++)this.blocks[i].select(t,e,n);return}n?e.concat(this.entries):e.concatWithNoDuplicate(this.entries)}},r.prototype.intersects=function(t,e,n,i){if(ms.a.IntersectsSphere(this._minPoint,this._maxPoint,t,e)){if(this.blocks){for(var o=0;o<this.blocks.length;o++)this.blocks[o].intersects(t,e,n,i);return}i?n.concat(this.entries):n.concatWithNoDuplicate(this.entries)}},r.prototype.intersectsRay=function(t,e){if(t.intersectsBoxMinMax(this._minPoint,this._maxPoint)){if(this.blocks){for(var n=0;n<this.blocks.length;n++)this.blocks[n].intersectsRay(t,e);return}e.concatWithNoDuplicate(this.entries)}},r.prototype.createInnerBlocks=function(){r._CreateBlocks(this._minPoint,this._maxPoint,this.entries,this._capacity,this._depth,this._maxDepth,this,this._creationFunc)},r._CreateBlocks=function(t,e,n,i,o,a,s,d){s.blocks=new Array;for(var p=new u.e((e.x-t.x)/2,(e.y-t.y)/2,(e.z-t.z)/2),b=0;b<2;b++)for(var P=0;P<2;P++)for(var O=0;O<2;O++){var B=new r(t.add(p.multiplyByFloats(b,P,O)),t.add(p.multiplyByFloats(b+1,P+1,O+1)),i,o+1,a,d);B.addEntries(n),s.blocks.push(B)}},r}(),no=function(){function r(t,e,n){n===void 0&&(n=2),this.maxDepth=n,this.dynamicContent=new Array,this._maxBlockCapacity=e||64,this._selectionContent=new fi.b(1024),this._creationFunc=t}return r.prototype.update=function(t,e,n){Jl._CreateBlocks(t,e,n,this._maxBlockCapacity,0,this.maxDepth,this,this._creationFunc)},r.prototype.addMesh=function(t){for(var e=0;e<this.blocks.length;e++)this.blocks[e].addEntry(t)},r.prototype.removeMesh=function(t){for(var e=0;e<this.blocks.length;e++)this.blocks[e].removeEntry(t)},r.prototype.select=function(t,e){this._selectionContent.reset();for(var n=0;n<this.blocks.length;n++)this.blocks[n].select(t,this._selectionContent,e);return e?this._selectionContent.concat(this.dynamicContent):this._selectionContent.concatWithNoDuplicate(this.dynamicContent),this._selectionContent},r.prototype.intersects=function(t,e,n){this._selectionContent.reset();for(var i=0;i<this.blocks.length;i++)this.blocks[i].intersects(t,e,this._selectionContent,n);return n?this._selectionContent.concat(this.dynamicContent):this._selectionContent.concatWithNoDuplicate(this.dynamicContent),this._selectionContent},r.prototype.intersectsRay=function(t){this._selectionContent.reset();for(var e=0;e<this.blocks.length;e++)this.blocks[e].intersectsRay(t,this._selectionContent);return this._selectionContent.concatWithNoDuplicate(this.dynamicContent),this._selectionContent},r.CreationFuncForMeshes=function(t,e){var n=t.getBoundingInfo();!t.isBlocked&&n.boundingBox.intersectsMinMax(e.minPoint,e.maxPoint)&&e.entries.push(t)},r.CreationFuncForSubMeshes=function(t,e){t.getBoundingInfo().boundingBox.intersectsMinMax(e.minPoint,e.maxPoint)&&e.entries.push(t)},r}();_e.a.prototype.createOrUpdateSelectionOctree=function(r,t){r===void 0&&(r=64),t===void 0&&(t=2);var e=this._getComponent(at.a.NAME_OCTREE);e||(e=new Ts(this),this._addComponent(e)),this._selectionOctree||(this._selectionOctree=new no(no.CreationFuncForMeshes,r,t));var n=this.getWorldExtends();return this._selectionOctree.update(n.min,n.max,this.meshes),this._selectionOctree},Object.defineProperty(_e.a.prototype,"selectionOctree",{get:function(){return this._selectionOctree},enumerable:!0,configurable:!0}),Dt.a.prototype.createOrUpdateSubmeshesOctree=function(r,t){r===void 0&&(r=64),t===void 0&&(t=2);var e=this.getScene(),n=e._getComponent(at.a.NAME_OCTREE);n||(n=new Ts(e),e._addComponent(n)),this._submeshesOctree||(this._submeshesOctree=new no(no.CreationFuncForSubMeshes,r,t)),this.computeWorldMatrix(!0);var i=this.getBoundingInfo().boundingBox;return this._submeshesOctree.update(i.minimumWorld,i.maximumWorld,this.subMeshes),this._submeshesOctree};var Kt,gs,vs,bs,ys,Ts=function(){function r(t){this.name=at.a.NAME_OCTREE,this.checksIsEnabled=!0,this._tempRay=new fn.a(u.e.Zero(),new u.e(1,1,1)),this.scene=t,this.scene.getActiveMeshCandidates=this.getActiveMeshCandidates.bind(this),this.scene.getActiveSubMeshCandidates=this.getActiveSubMeshCandidates.bind(this),this.scene.getCollidingSubMeshCandidates=this.getCollidingSubMeshCandidates.bind(this),this.scene.getIntersectingSubMeshCandidates=this.getIntersectingSubMeshCandidates.bind(this)}return r.prototype.register=function(){var t=this;this.scene.onMeshRemovedObservable.add(function(e){var n=t.scene.selectionOctree;if(n!=null){var i=n.dynamicContent.indexOf(e);i!==-1&&n.dynamicContent.splice(i,1)}}),this.scene.onMeshImportedObservable.add(function(e){var n=t.scene.selectionOctree;n?.addMesh(e)})},r.prototype.getActiveMeshCandidates=function(){return this.scene._selectionOctree?this.scene._selectionOctree.select(this.scene.frustumPlanes):this.scene._getDefaultMeshCandidates()},r.prototype.getActiveSubMeshCandidates=function(t){return t._submeshesOctree&&t.useOctreeForRenderingSelection?t._submeshesOctree.select(this.scene.frustumPlanes):this.scene._getDefaultSubMeshCandidates(t)},r.prototype.getIntersectingSubMeshCandidates=function(t,e){return t._submeshesOctree&&t.useOctreeForPicking?(fn.a.TransformToRef(e,t.getWorldMatrix(),this._tempRay),t._submeshesOctree.intersectsRay(this._tempRay)):this.scene._getDefaultSubMeshCandidates(t)},r.prototype.getCollidingSubMeshCandidates=function(t,e){if(t._submeshesOctree&&t.useOctreeForCollisions){var n=e._velocityWorldLength+Math.max(e._radius.x,e._radius.y,e._radius.z);return t._submeshesOctree.intersects(e._basePointWorld,n)}return this.scene._getDefaultSubMeshCandidates(t)},r.prototype.rebuild=function(){},r.prototype.dispose=function(){},r}(),ir=f(99);(function(r){r[r.Generic=0]="Generic",r[r.Keyboard=1]="Keyboard",r[r.Mouse=2]="Mouse",r[r.Touch=3]="Touch",r[r.DualShock=4]="DualShock",r[r.Xbox=5]="Xbox",r[r.Switch=6]="Switch"})(Kt||(Kt={})),function(r){r[r.Horizontal=0]="Horizontal",r[r.Vertical=1]="Vertical",r[r.LeftClick=2]="LeftClick",r[r.MiddleClick=3]="MiddleClick",r[r.RightClick=4]="RightClick",r[r.BrowserBack=5]="BrowserBack",r[r.BrowserForward=6]="BrowserForward"}(gs||(gs={})),function(r){r[r.Cross=0]="Cross",r[r.Circle=1]="Circle",r[r.Square=2]="Square",r[r.Triangle=3]="Triangle",r[r.L1=4]="L1",r[r.R1=5]="R1",r[r.L2=6]="L2",r[r.R2=7]="R2",r[r.Share=8]="Share",r[r.Options=9]="Options",r[r.L3=10]="L3",r[r.R3=11]="R3",r[r.DPadUp=12]="DPadUp",r[r.DPadDown=13]="DPadDown",r[r.DPadLeft=14]="DPadLeft",r[r.DPadRight=15]="DPadRight",r[r.Home=16]="Home",r[r.TouchPad=17]="TouchPad",r[r.LStickXAxis=18]="LStickXAxis",r[r.LStickYAxis=19]="LStickYAxis",r[r.RStickXAxis=20]="RStickXAxis",r[r.RStickYAxis=21]="RStickYAxis"}(vs||(vs={})),function(r){r[r.A=0]="A",r[r.B=1]="B",r[r.X=2]="X",r[r.Y=3]="Y",r[r.LB=4]="LB",r[r.RB=5]="RB",r[r.LT=6]="LT",r[r.RT=7]="RT",r[r.Back=8]="Back",r[r.Start=9]="Start",r[r.LS=10]="LS",r[r.RS=11]="RS",r[r.DPadUp=12]="DPadUp",r[r.DPadDown=13]="DPadDown",r[r.DPadLeft=14]="DPadLeft",r[r.DPadRight=15]="DPadRight",r[r.Home=16]="Home",r[r.LStickXAxis=17]="LStickXAxis",r[r.LStickYAxis=18]="LStickYAxis",r[r.RStickXAxis=19]="RStickXAxis",r[r.RStickYAxis=20]="RStickYAxis"}(bs||(bs={})),function(r){r[r.B=0]="B",r[r.A=1]="A",r[r.Y=2]="Y",r[r.X=3]="X",r[r.L=4]="L",r[r.R=5]="R",r[r.ZL=6]="ZL",r[r.ZR=7]="ZR",r[r.Minus=8]="Minus",r[r.Plus=9]="Plus",r[r.LS=10]="LS",r[r.RS=11]="RS",r[r.DPadUp=12]="DPadUp",r[r.DPadDown=13]="DPadDown",r[r.DPadLeft=14]="DPadLeft",r[r.DPadRight=15]="DPadRight",r[r.Home=16]="Home",r[r.Capture=17]="Capture",r[r.LStickXAxis=18]="LStickXAxis",r[r.LStickYAxis=19]="LStickYAxis",r[r.RStickXAxis=20]="RStickXAxis",r[r.RStickYAxis=21]="RStickYAxis"}(ys||(ys={}));var $l=function(){function r(t){this.onDeviceDisconnected=function(){},this._inputs=[],this._keyboardActive=!1,this._pointerActive=!1,this._keyboardDownEvent=function(n){},this._keyboardUpEvent=function(n){},this._pointerMoveEvent=function(n){},this._pointerDownEvent=function(n){},this._pointerUpEvent=function(n){},this._gamepadConnectedEvent=function(n){},this._gamepadDisconnectedEvent=function(n){},this._onDeviceConnected=function(){};var e=t.getInputElement();e&&(this._elementToAttachTo=e,this._handleKeyActions(),this._handlePointerActions(),this._handleGamepadActions(),this._checkForConnectedDevices())}return Object.defineProperty(r.prototype,"onDeviceConnected",{get:function(){return this._onDeviceConnected},set:function(t){this._onDeviceConnected=t;for(var e=0;e<this._inputs.length;e++)if(this._inputs[e])for(var n=0;n<this._inputs[e].length;n++)this._inputs[e][n]&&this._onDeviceConnected(e,n)},enumerable:!1,configurable:!0}),r.Create=function(t){return typeof _native<"u"&&_native.DeviceInputSystem?new _native.DeviceInputSystem(t):new r(t)},r.prototype.pollInput=function(t,e,n){var i=this._inputs[t][e];if(!i)throw"Unable to find device "+Kt[t];if(this._updateDevice(t,e,n),i[n]===void 0)throw"Unable to find input "+n+" for device "+Kt[t]+" in slot "+e;return i[n]},r.prototype.dispose=function(){this._keyboardActive&&(window.removeEventListener("keydown",this._keyboardDownEvent),window.removeEventListener("keyup",this._keyboardUpEvent)),this._pointerActive&&(this._elementToAttachTo.removeEventListener("pointermove",this._pointerMoveEvent),this._elementToAttachTo.removeEventListener("pointerdown",this._pointerDownEvent),this._elementToAttachTo.removeEventListener("pointerup",this._pointerUpEvent)),window.removeEventListener("gamepadconnected",this._gamepadConnectedEvent),window.removeEventListener("gamepaddisconnected",this._gamepadDisconnectedEvent)},r.prototype._checkForConnectedDevices=function(){for(var t=0,e=navigator.getGamepads();t<e.length;t++){var n=e[t];n&&this._addGamePad(n)}matchMedia("(pointer:fine)").matches&&this._addPointerDevice(Kt.Mouse,0,0,0)},r.prototype._addGamePad=function(t){var e=this._getGamepadDeviceType(t.id),n=t.index;this._registerDevice(e,n,t.buttons.length+t.axes.length),this._gamepads=this._gamepads||new Array(t.index+1),this._gamepads[n]=e},r.prototype._addPointerDevice=function(t,e,n,i){this._pointerActive=!0,this._registerDevice(t,e,r._MAX_POINTER_INPUTS);var o=this._inputs[t][e];o[0]=n,o[1]=i},r.prototype._registerDevice=function(t,e,n){if(this._inputs[t]||(this._inputs[t]=[]),!this._inputs[t][e]){for(var i=new Array(n),o=0;o<n;o++)i[o]=0;this._inputs[t][e]=i,this.onDeviceConnected(t,e)}},r.prototype._unregisterDevice=function(t,e){this._inputs[t][e]&&(delete this._inputs[t][e],this.onDeviceDisconnected(t,e))},r.prototype._handleKeyActions=function(){var t=this;this._keyboardDownEvent=function(e){t._keyboardActive||(t._keyboardActive=!0,t._registerDevice(Kt.Keyboard,0,r._MAX_KEYCODES));var n=t._inputs[Kt.Keyboard][0];n&&(t.onInputChanged&&t.onInputChanged(Kt.Keyboard,0,e.keyCode,n[e.keyCode],1),n[e.keyCode]=1)},this._keyboardUpEvent=function(e){var n=t._inputs[Kt.Keyboard][0];n&&(t.onInputChanged&&t.onInputChanged(Kt.Keyboard,0,e.keyCode,n[e.keyCode],0),n[e.keyCode]=0)},window.addEventListener("keydown",this._keyboardDownEvent),window.addEventListener("keyup",this._keyboardUpEvent)},r.prototype._handlePointerActions=function(){var t=this;this._pointerMoveEvent=function(e){var n=e.pointerType=="mouse"?Kt.Mouse:Kt.Touch,i=e.pointerType=="mouse"?0:e.pointerId;t._inputs[n]||(t._inputs[n]=[]),t._inputs[n][i]||t._addPointerDevice(n,i,e.clientX,e.clientY);var o=t._inputs[n][i];o&&(t.onInputChanged&&(t.onInputChanged(n,i,0,o[0],e.clientX),t.onInputChanged(n,i,1,o[1],e.clientY)),o[0]=e.clientX,o[1]=e.clientY)},this._pointerDownEvent=function(e){var n=e.pointerType=="mouse"?Kt.Mouse:Kt.Touch,i=e.pointerType=="mouse"?0:e.pointerId;t._inputs[n]||(t._inputs[n]=[]),t._inputs[n][i]||t._addPointerDevice(n,i,e.clientX,e.clientY);var o=t._inputs[n][i];o&&(t.onInputChanged&&(t.onInputChanged(n,i,0,o[0],e.clientX),t.onInputChanged(n,i,1,o[1],e.clientY),t.onInputChanged(n,i,e.button+2,o[e.button+2],1)),o[0]=e.clientX,o[1]=e.clientY,o[e.button+2]=1)},this._pointerUpEvent=function(e){var n=e.pointerType=="mouse"?Kt.Mouse:Kt.Touch,i=e.pointerType=="mouse"?0:e.pointerId,o=t._inputs[n][i];o&&(t.onInputChanged&&t.onInputChanged(n,i,e.button+2,o[e.button+2],0),o[0]=e.clientX,o[1]=e.clientY,o[e.button+2]=0),e.pointerType!="mouse"&&t._unregisterDevice(n,i)},this._elementToAttachTo.addEventListener("pointermove",this._pointerMoveEvent),this._elementToAttachTo.addEventListener("pointerdown",this._pointerDownEvent),this._elementToAttachTo.addEventListener("pointerup",this._pointerUpEvent)},r.prototype._handleGamepadActions=function(){var t=this;this._gamepadConnectedEvent=function(e){t._addGamePad(e.gamepad)},this._gamepadDisconnectedEvent=function(e){if(t._gamepads){var n=t._getGamepadDeviceType(e.gamepad.id),i=e.gamepad.index;t._unregisterDevice(n,i),delete t._gamepads[i]}},window.addEventListener("gamepadconnected",this._gamepadConnectedEvent),window.addEventListener("gamepaddisconnected",this._gamepadDisconnectedEvent)},r.prototype._updateDevice=function(t,e,n){var i=navigator.getGamepads()[e];if(i&&t==this._gamepads[e]){var o=this._inputs[t][e];n>=i.buttons.length?o[n]=i.axes[n-i.buttons.length].valueOf():o[n]=i.buttons[n].value}},r.prototype._getGamepadDeviceType=function(t){return t.indexOf("054c")!==-1?Kt.DualShock:t.indexOf("Xbox One")!==-1||t.search("Xbox 360")!==-1||t.search("xinput")!==-1?Kt.Xbox:t.indexOf("057e")!==-1?Kt.Switch:Kt.Generic},r._MAX_KEYCODES=255,r._MAX_POINTER_INPUTS=7,r}(),eu=function(){function r(t,e,n){n===void 0&&(n=0),this.deviceType=e,this.deviceSlot=n,this.onInputChangedObservable=new x.c,this._deviceInputSystem=t}return r.prototype.getInput=function(t){return this._deviceInputSystem.pollInput(this.deviceType,this.deviceSlot,t)},r}(),Jf=function(){function r(t){var e=this;this.onDeviceConnectedObservable=new x.c(function(i){e.getDevices().forEach(function(o){e.onDeviceConnectedObservable.notifyObserver(i,o)})}),this.onDeviceDisconnectedObservable=new x.c;var n=Object.keys(Kt).length/2;this._devices=new Array(n),this._firstDevice=new Array(n),this._deviceInputSystem=$l.Create(t),this._deviceInputSystem.onDeviceConnected=function(i,o){e._addDevice(i,o),e.onDeviceConnectedObservable.notifyObservers(e.getDeviceSource(i,o))},this._deviceInputSystem.onDeviceDisconnected=function(i,o){var a=e.getDeviceSource(i,o);e._removeDevice(i,o),e.onDeviceDisconnectedObservable.notifyObservers(a)},this._deviceInputSystem.onInputChanged||(this._deviceInputSystem.onInputChanged=function(i,o,a,s,d){var p;(p=e.getDeviceSource(i,o))===null||p===void 0||p.onInputChangedObservable.notifyObservers({inputIndex:a,previousState:s,currentState:d})})}return r.prototype.getDeviceSource=function(t,e){if(e===void 0){if(this._firstDevice[t]===void 0)return null;e=this._firstDevice[t]}return this._devices[t]&&this._devices[t][e]!==void 0?this._devices[t][e]:null},r.prototype.getDeviceSources=function(t){return this._devices[t].filter(function(e){return!!e})},r.prototype.getDevices=function(){var t=new Array;return this._devices.forEach(function(e){t.push.apply(t,e)}),t},r.prototype.dispose=function(){this.onDeviceConnectedObservable.clear(),this.onDeviceDisconnectedObservable.clear(),this._deviceInputSystem.dispose()},r.prototype._addDevice=function(t,e){this._devices[t]||(this._devices[t]=new Array),this._devices[t][e]||(this._devices[t][e]=new eu(this._deviceInputSystem,t,e),this._updateFirstDevices(t))},r.prototype._removeDevice=function(t,e){delete this._devices[t][e],this._updateFirstDevices(t)},r.prototype._updateFirstDevices=function(t){switch(t){case Kt.Keyboard:case Kt.Mouse:this._firstDevice[t]=0;break;case Kt.Touch:case Kt.DualShock:case Kt.Xbox:case Kt.Switch:case Kt.Generic:var e=this._devices[t];delete this._firstDevice[t];for(var n=0;n<e.length;n++)if(e[n]){this._firstDevice[t]=n;break}}},r}(),tu=f(168),nu=(f(123),function(){this._timeElapsedQueryEnded=!1}),iu=function(){this.occlusionInternalRetryCounter=0,this.isOcclusionQueryInProgress=!1,this.isOccluded=!1,this.occlusionRetryCount=-1,this.occlusionType=Dt.a.OCCLUSION_TYPE_NONE,this.occlusionQueryAlgorithmType=Dt.a.OCCLUSION_ALGORITHM_TYPE_CONSERVATIVE};Ue.a.prototype.createQuery=function(){return this._gl.createQuery()},Ue.a.prototype.deleteQuery=function(r){return this._gl.deleteQuery(r),this},Ue.a.prototype.isQueryResultAvailable=function(r){return this._gl.getQueryParameter(r,this._gl.QUERY_RESULT_AVAILABLE)},Ue.a.prototype.getQueryResult=function(r){return this._gl.getQueryParameter(r,this._gl.QUERY_RESULT)},Ue.a.prototype.beginOcclusionQuery=function(r,t){var e=this._getGlAlgorithmType(r);return this._gl.beginQuery(e,t),this},Ue.a.prototype.endOcclusionQuery=function(r){var t=this._getGlAlgorithmType(r);return this._gl.endQuery(t),this},Ue.a.prototype._createTimeQuery=function(){var r=this.getCaps().timerQuery;return r.createQueryEXT?r.createQueryEXT():this.createQuery()},Ue.a.prototype._deleteTimeQuery=function(r){var t=this.getCaps().timerQuery;t.deleteQueryEXT?t.deleteQueryEXT(r):this.deleteQuery(r)},Ue.a.prototype._getTimeQueryResult=function(r){var t=this.getCaps().timerQuery;return t.getQueryObjectEXT?t.getQueryObjectEXT(r,t.QUERY_RESULT_EXT):this.getQueryResult(r)},Ue.a.prototype._getTimeQueryAvailability=function(r){var t=this.getCaps().timerQuery;return t.getQueryObjectEXT?t.getQueryObjectEXT(r,t.QUERY_RESULT_AVAILABLE_EXT):this.isQueryResultAvailable(r)},Ue.a.prototype.startTimeQuery=function(){var r=this.getCaps(),t=r.timerQuery;if(!t)return null;var e=new nu;if(this._gl.getParameter(t.GPU_DISJOINT_EXT),r.canUseTimestampForTimerQuery)e._startTimeQuery=this._createTimeQuery(),t.queryCounterEXT(e._startTimeQuery,t.TIMESTAMP_EXT);else{if(this._currentNonTimestampToken)return this._currentNonTimestampToken;e._timeElapsedQuery=this._createTimeQuery(),t.beginQueryEXT?t.beginQueryEXT(t.TIME_ELAPSED_EXT,e._timeElapsedQuery):this._gl.beginQuery(t.TIME_ELAPSED_EXT,e._timeElapsedQuery),this._currentNonTimestampToken=e}return e},Ue.a.prototype.endTimeQuery=function(r){var t=this.getCaps(),e=t.timerQuery;if(!e||!r)return-1;if(t.canUseTimestampForTimerQuery){if(!r._startTimeQuery)return-1;r._endTimeQuery||(r._endTimeQuery=this._createTimeQuery(),e.queryCounterEXT(r._endTimeQuery,e.TIMESTAMP_EXT))}else if(!r._timeElapsedQueryEnded){if(!r._timeElapsedQuery)return-1;e.endQueryEXT?e.endQueryEXT(e.TIME_ELAPSED_EXT):this._gl.endQuery(e.TIME_ELAPSED_EXT),r._timeElapsedQueryEnded=!0}var n=this._gl.getParameter(e.GPU_DISJOINT_EXT),i=!1;if(r._endTimeQuery?i=this._getTimeQueryAvailability(r._endTimeQuery):r._timeElapsedQuery&&(i=this._getTimeQueryAvailability(r._timeElapsedQuery)),i&&!n){var o=0;if(t.canUseTimestampForTimerQuery){if(!r._startTimeQuery||!r._endTimeQuery)return-1;var a=this._getTimeQueryResult(r._startTimeQuery);o=this._getTimeQueryResult(r._endTimeQuery)-a,this._deleteTimeQuery(r._startTimeQuery),this._deleteTimeQuery(r._endTimeQuery),r._startTimeQuery=null,r._endTimeQuery=null}else{if(!r._timeElapsedQuery)return-1;o=this._getTimeQueryResult(r._timeElapsedQuery),this._deleteTimeQuery(r._timeElapsedQuery),r._timeElapsedQuery=null,r._timeElapsedQueryEnded=!1,this._currentNonTimestampToken=null}return o}return-1},Ue.a.prototype._getGlAlgorithmType=function(r){return r===Dt.a.OCCLUSION_ALGORITHM_TYPE_CONSERVATIVE?this._gl.ANY_SAMPLES_PASSED_CONSERVATIVE:this._gl.ANY_SAMPLES_PASSED},Object.defineProperty(Dt.a.prototype,"isOcclusionQueryInProgress",{get:function(){return this._occlusionDataStorage.isOcclusionQueryInProgress},set:function(r){this._occlusionDataStorage.isOcclusionQueryInProgress=r},enumerable:!1,configurable:!0}),Object.defineProperty(Dt.a.prototype,"_occlusionDataStorage",{get:function(){return this.__occlusionDataStorage||(this.__occlusionDataStorage=new iu),this.__occlusionDataStorage},enumerable:!1,configurable:!0}),Object.defineProperty(Dt.a.prototype,"isOccluded",{get:function(){return this._occlusionDataStorage.isOccluded},set:function(r){this._occlusionDataStorage.isOccluded=r},enumerable:!0,configurable:!0}),Object.defineProperty(Dt.a.prototype,"occlusionQueryAlgorithmType",{get:function(){return this._occlusionDataStorage.occlusionQueryAlgorithmType},set:function(r){this._occlusionDataStorage.occlusionQueryAlgorithmType=r},enumerable:!0,configurable:!0}),Object.defineProperty(Dt.a.prototype,"occlusionType",{get:function(){return this._occlusionDataStorage.occlusionType},set:function(r){this._occlusionDataStorage.occlusionType=r},enumerable:!0,configurable:!0}),Object.defineProperty(Dt.a.prototype,"occlusionRetryCount",{get:function(){return this._occlusionDataStorage.occlusionRetryCount},set:function(r){this._occlusionDataStorage.occlusionRetryCount=r},enumerable:!0,configurable:!0}),Dt.a.prototype._checkOcclusionQuery=function(){var r=this._occlusionDataStorage;if(r.occlusionType===Dt.a.OCCLUSION_TYPE_NONE)return r.isOccluded=!1,!1;var t=this.getEngine();if(t.webGLVersion<2||!t.isQueryResultAvailable)return r.isOccluded=!1,!1;if(this.isOcclusionQueryInProgress&&this._occlusionQuery)if(t.isQueryResultAvailable(this._occlusionQuery)){var e=t.getQueryResult(this._occlusionQuery);r.isOcclusionQueryInProgress=!1,r.occlusionInternalRetryCounter=0,r.isOccluded=e!==1}else{if(r.occlusionInternalRetryCounter++,!(r.occlusionRetryCount!==-1&&r.occlusionInternalRetryCounter>r.occlusionRetryCount))return!1;r.isOcclusionQueryInProgress=!1,r.occlusionInternalRetryCounter=0,r.isOccluded=r.occlusionType!==Dt.a.OCCLUSION_TYPE_OPTIMISTIC&&r.isOccluded}var n=this.getScene();if(n.getBoundingBoxRenderer){var i=n.getBoundingBoxRenderer();this._occlusionQuery||(this._occlusionQuery=t.createQuery()),t.beginOcclusionQuery(r.occlusionQueryAlgorithmType,this._occlusionQuery),i.renderOcclusionBoundingBox(this),t.endOcclusionQuery(r.occlusionQueryAlgorithmType),this._occlusionDataStorage.isOcclusionQueryInProgress=!0}return r.isOccluded};var $f=!0;Ue.a.prototype.createTransformFeedback=function(){return this._gl.createTransformFeedback()},Ue.a.prototype.deleteTransformFeedback=function(r){this._gl.deleteTransformFeedback(r)},Ue.a.prototype.bindTransformFeedback=function(r){this._gl.bindTransformFeedback(this._gl.TRANSFORM_FEEDBACK,r)},Ue.a.prototype.beginTransformFeedback=function(r){r===void 0&&(r=!0),this._gl.beginTransformFeedback(r?this._gl.POINTS:this._gl.TRIANGLES)},Ue.a.prototype.endTransformFeedback=function(){this._gl.endTransformFeedback()},Ue.a.prototype.setTranformFeedbackVaryings=function(r,t){this._gl.transformFeedbackVaryings(r,t,this._gl.INTERLEAVED_ATTRIBS)},Ue.a.prototype.bindTransformFeedbackBuffer=function(r){this._gl.bindBufferBase(this._gl.TRANSFORM_FEEDBACK_BUFFER,0,r?r.underlyingResource:null)},f(126),Bt.a.prototype.updateVideoTexture=function(r,t,e){if(r&&!r._isDisabled){var n=this._bindTextureDirectly(this._gl.TEXTURE_2D,r,!0);this._unpackFlipY(!e);try{if(this._videoTextureSupported===void 0&&(this._gl.getError(),this._gl.texImage2D(this._gl.TEXTURE_2D,0,this._gl.RGBA,this._gl.RGBA,this._gl.UNSIGNED_BYTE,t),this._gl.getError()!==0?this._videoTextureSupported=!1:this._videoTextureSupported=!0),this._videoTextureSupported)this._gl.texImage2D(this._gl.TEXTURE_2D,0,this._gl.RGBA,this._gl.RGBA,this._gl.UNSIGNED_BYTE,t);else{if(!r._workingCanvas){r._workingCanvas=fs.a.CreateCanvas(r.width,r.height);var i=r._workingCanvas.getContext("2d");if(!i)throw new Error("Unable to get 2d context");r._workingContext=i,r._workingCanvas.width=r.width,r._workingCanvas.height=r.height}r._workingContext.clearRect(0,0,r.width,r.height),r._workingContext.drawImage(t,0,0,t.videoWidth,t.videoHeight,0,0,r.width,r.height),this._gl.texImage2D(this._gl.TEXTURE_2D,0,this._gl.RGBA,this._gl.RGBA,this._gl.UNSIGNED_BYTE,r._workingCanvas)}r.generateMipMaps&&this._gl.generateMipmap(this._gl.TEXTURE_2D),n||this._bindTextureDirectly(this._gl.TEXTURE_2D,null),r.isReady=!0}catch{r._isDisabled=!0}}},Bt.a.prototype.restoreSingleAttachment=function(){var r=this._gl;this.bindAttachments([r.BACK])},Bt.a.prototype.buildTextureLayout=function(r){for(var t=this._gl,e=[],n=0;n<r.length;n++)r[n]?e.push(t["COLOR_ATTACHMENT"+n]):e.push(t.NONE);return e},Bt.a.prototype.bindAttachments=function(r){this._gl.drawBuffers(r)},Bt.a.prototype.unBindMultiColorAttachmentFramebuffer=function(r,t,e){t===void 0&&(t=!1),this._currentRenderTarget=null;var n=this._gl,i=r[0]._attachments,o=i.length;if(r[0]._MSAAFramebuffer){n.bindFramebuffer(n.READ_FRAMEBUFFER,r[0]._MSAAFramebuffer),n.bindFramebuffer(n.DRAW_FRAMEBUFFER,r[0]._framebuffer);for(var a=0;a<o;a++){for(var s=r[a],d=0;d<o;d++)i[d]=n.NONE;i[a]=n[this.webGLVersion>1?"COLOR_ATTACHMENT"+a:"COLOR_ATTACHMENT"+a+"_WEBGL"],n.readBuffer(i[a]),n.drawBuffers(i),n.blitFramebuffer(0,0,s.width,s.height,0,0,s.width,s.height,n.COLOR_BUFFER_BIT,n.NEAREST)}for(a=0;a<o;a++)i[a]=n[this.webGLVersion>1?"COLOR_ATTACHMENT"+a:"COLOR_ATTACHMENT"+a+"_WEBGL"];n.drawBuffers(i)}for(a=0;a<o;a++)!(s=r[a]).generateMipMaps||t||s.isCube||(this._bindTextureDirectly(n.TEXTURE_2D,s,!0),n.generateMipmap(n.TEXTURE_2D),this._bindTextureDirectly(n.TEXTURE_2D,null));e&&(r[0]._MSAAFramebuffer&&this._bindUnboundFramebuffer(r[0]._framebuffer),e()),this._bindUnboundFramebuffer(null)},Bt.a.prototype.createMultipleRenderTarget=function(r,t){var e=!1,n=!0,i=!1,o=!1,a=1,s=h.a.TEXTURETYPE_UNSIGNED_INT,d=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE,p=new Array,b=new Array;t!==void 0&&(e=t.generateMipMaps!==void 0&&t.generateMipMaps,n=t.generateDepthBuffer===void 0||t.generateDepthBuffer,i=t.generateStencilBuffer!==void 0&&t.generateStencilBuffer,o=t.generateDepthTexture!==void 0&&t.generateDepthTexture,a=t.textureCount||1,t.types&&(p=t.types),t.samplingModes&&(b=t.samplingModes));var P=this._gl,O=P.createFramebuffer();this._bindUnboundFramebuffer(O);for(var B=r.width||r,F=r.height||r,z=[],J=[],ie=this._setupFramebufferDepthAttachments(i,n,B,F),se=0;se<a;se++){var ce=b[se]||d,ue=p[se]||s;(ue!==h.a.TEXTURETYPE_FLOAT||this._caps.textureFloatLinearFiltering)&&(ue!==h.a.TEXTURETYPE_HALF_FLOAT||this._caps.textureHalfFloatLinearFiltering)||(ce=h.a.TEXTURE_NEAREST_SAMPLINGMODE);var fe=this._getSamplingParameters(ce,e);ue!==h.a.TEXTURETYPE_FLOAT||this._caps.textureFloat||(ue=h.a.TEXTURETYPE_UNSIGNED_INT,l.a.Warn("Float textures are not supported. Render target forced to TEXTURETYPE_UNSIGNED_BYTE type"));var ve=new xt.a(this,xt.b.MultiRenderTarget),Te=P[this.webGLVersion>1?"COLOR_ATTACHMENT"+se:"COLOR_ATTACHMENT"+se+"_WEBGL"];z.push(ve),J.push(Te),P.activeTexture(P["TEXTURE"+se]),P.bindTexture(P.TEXTURE_2D,ve._webGLTexture),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_MAG_FILTER,fe.mag),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_MIN_FILTER,fe.min),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_WRAP_S,P.CLAMP_TO_EDGE),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_WRAP_T,P.CLAMP_TO_EDGE),P.texImage2D(P.TEXTURE_2D,0,this._getRGBABufferInternalSizedFormat(ue),B,F,0,P.RGBA,this._getWebGLTextureType(ue),null),P.framebufferTexture2D(P.DRAW_FRAMEBUFFER,Te,P.TEXTURE_2D,ve._webGLTexture,0),e&&this._gl.generateMipmap(this._gl.TEXTURE_2D),this._bindTextureDirectly(P.TEXTURE_2D,null),ve._framebuffer=O,ve._depthStencilBuffer=ie,ve.baseWidth=B,ve.baseHeight=F,ve.width=B,ve.height=F,ve.isReady=!0,ve.samples=1,ve.generateMipMaps=e,ve.samplingMode=ce,ve.type=ue,ve._generateDepthBuffer=n,ve._generateStencilBuffer=i,ve._attachments=J,ve._textureArray=z,this._internalTexturesCache.push(ve)}if(o&&this._caps.depthTextureExtension){var Re=new xt.a(this,xt.b.MultiRenderTarget);P.activeTexture(P.TEXTURE0),P.bindTexture(P.TEXTURE_2D,Re._webGLTexture),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_MAG_FILTER,P.NEAREST),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_MIN_FILTER,P.NEAREST),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_WRAP_S,P.CLAMP_TO_EDGE),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_WRAP_T,P.CLAMP_TO_EDGE),P.texImage2D(P.TEXTURE_2D,0,this.webGLVersion<2?P.DEPTH_COMPONENT:P.DEPTH_COMPONENT16,B,F,0,P.DEPTH_COMPONENT,P.UNSIGNED_SHORT,null),P.framebufferTexture2D(P.FRAMEBUFFER,P.DEPTH_ATTACHMENT,P.TEXTURE_2D,Re._webGLTexture,0),Re._framebuffer=O,Re.baseWidth=B,Re.baseHeight=F,Re.width=B,Re.height=F,Re.isReady=!0,Re.samples=1,Re.generateMipMaps=e,Re.samplingMode=P.NEAREST,Re._generateDepthBuffer=n,Re._generateStencilBuffer=i,z.push(Re),this._internalTexturesCache.push(Re)}return P.drawBuffers(J),this._bindUnboundFramebuffer(null),this.resetTextureCache(),z},Bt.a.prototype.updateMultipleRenderTargetTextureSampleCount=function(r,t){if(this.webGLVersion<2||!r)return 1;if(r[0].samples===t)return t;var e=r[0]._attachments.length;if(e===0)return 1;var n=this._gl;t=Math.min(t,this.getCaps().maxMSAASamples),r[0]._depthStencilBuffer&&(n.deleteRenderbuffer(r[0]._depthStencilBuffer),r[0]._depthStencilBuffer=null),r[0]._MSAAFramebuffer&&(n.deleteFramebuffer(r[0]._MSAAFramebuffer),r[0]._MSAAFramebuffer=null);for(var i=0;i<e;i++)r[i]._MSAARenderBuffer&&(n.deleteRenderbuffer(r[i]._MSAARenderBuffer),r[i]._MSAARenderBuffer=null);if(t>1&&n.renderbufferStorageMultisample){var o=n.createFramebuffer();if(!o)throw new Error("Unable to create multi sampled framebuffer");this._bindUnboundFramebuffer(o);var a=this._setupFramebufferDepthAttachments(r[0]._generateStencilBuffer,r[0]._generateDepthBuffer,r[0].width,r[0].height,t),s=[];for(i=0;i<e;i++){var d=r[i],p=n[this.webGLVersion>1?"COLOR_ATTACHMENT"+i:"COLOR_ATTACHMENT"+i+"_WEBGL"],b=n.createRenderbuffer();if(!b)throw new Error("Unable to create multi sampled framebuffer");n.bindRenderbuffer(n.RENDERBUFFER,b),n.renderbufferStorageMultisample(n.RENDERBUFFER,t,this._getRGBAMultiSampleBufferFormat(d.type),d.width,d.height),n.framebufferRenderbuffer(n.FRAMEBUFFER,p,n.RENDERBUFFER,b),d._MSAAFramebuffer=o,d._MSAARenderBuffer=b,d.samples=t,d._depthStencilBuffer=a,n.bindRenderbuffer(n.RENDERBUFFER,null),s.push(p)}n.drawBuffers(s)}else this._bindUnboundFramebuffer(r[0]._framebuffer);return this._bindUnboundFramebuffer(null),t};var io=f(56);Bt.a.prototype._createDepthStencilCubeTexture=function(r,t){var e=new xt.a(this,xt.b.Unknown);if(e.isCube=!0,this.webGLVersion===1)return l.a.Error("Depth cube texture is not supported by WebGL 1."),e;var n=Object(c.a)({bilinearFiltering:!1,comparisonFunction:0,generateStencil:!1},t),i=this._gl;this._bindTextureDirectly(i.TEXTURE_CUBE_MAP,e,!0),this._setupDepthStencilTexture(e,r,n.generateStencil,n.bilinearFiltering,n.comparisonFunction);for(var o=0;o<6;o++)n.generateStencil?i.texImage2D(i.TEXTURE_CUBE_MAP_POSITIVE_X+o,0,i.DEPTH24_STENCIL8,r,r,0,i.DEPTH_STENCIL,i.UNSIGNED_INT_24_8,null):i.texImage2D(i.TEXTURE_CUBE_MAP_POSITIVE_X+o,0,i.DEPTH_COMPONENT24,r,r,0,i.DEPTH_COMPONENT,i.UNSIGNED_INT,null);return this._bindTextureDirectly(i.TEXTURE_CUBE_MAP,null),e},Bt.a.prototype._partialLoadFile=function(r,t,e,n,i){i===void 0&&(i=null),this._loadFile(r,function(o){e[t]=o,e._internalCount++,e._internalCount===6&&n(e)},void 0,void 0,!0,function(o,a){i&&o&&i(o.status+" "+o.statusText,a)})},Bt.a.prototype._cascadeLoadFiles=function(r,t,e,n){n===void 0&&(n=null);var i=[];i._internalCount=0;for(var o=0;o<6;o++)this._partialLoadFile(e[o],o,i,t,n)},Bt.a.prototype._cascadeLoadImgs=function(r,t,e,n,i){n===void 0&&(n=null);var o=[];o._internalCount=0;for(var a=0;a<6;a++)this._partialLoadImg(e[a],a,o,r,t,n,i)},Bt.a.prototype._partialLoadImg=function(r,t,e,n,i,o,a){var s;o===void 0&&(o=null),s=io.a.LoadImage(r,function(){s&&(e[t]=s,e._internalCount++,n&&n._removePendingData(s)),e._internalCount===6&&i(e)},function(d,p){n&&n._removePendingData(s),o&&o(d,p)},n?n.offlineProvider:null,a),n&&s&&n._addPendingData(s)},Bt.a.prototype._setCubeMapTextureParams=function(r,t){var e=this._gl;e.texParameteri(e.TEXTURE_CUBE_MAP,e.TEXTURE_MAG_FILTER,e.LINEAR),e.texParameteri(e.TEXTURE_CUBE_MAP,e.TEXTURE_MIN_FILTER,t?e.LINEAR_MIPMAP_LINEAR:e.LINEAR),e.texParameteri(e.TEXTURE_CUBE_MAP,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE),e.texParameteri(e.TEXTURE_CUBE_MAP,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE),r.samplingMode=t?h.a.TEXTURE_TRILINEAR_SAMPLINGMODE:h.a.TEXTURE_LINEAR_LINEAR,this._bindTextureDirectly(e.TEXTURE_CUBE_MAP,null)},Bt.a.prototype.createCubeTexture=function(r,t,e,n,i,o,a,s,d,p,b,P,O){var B=this;i===void 0&&(i=null),o===void 0&&(o=null),s===void 0&&(s=null),d===void 0&&(d=!1),p===void 0&&(p=0),b===void 0&&(b=0),P===void 0&&(P=null);var F=this._gl,z=P||new xt.a(this,xt.b.Cube);z.isCube=!0,z.url=r,z.generateMipMaps=!n,z._lodGenerationScale=p,z._lodGenerationOffset=b,this._doNotHandleContextLost||(z._extension=s,z._files=e);var J=r;this._transformTextureUrl&&!P&&(r=this._transformTextureUrl(r));for(var ie=r.lastIndexOf("."),se=s||(ie>-1?r.substring(ie).toLowerCase():""),ce=null,ue=0,fe=Bt.a._TextureLoaders;ue<fe.length;ue++){var ve=fe[ue];if(ve.canLoad(se)){ce=ve;break}}if(ce){var Te=function(Re){B._bindTextureDirectly(F.TEXTURE_CUBE_MAP,z,!0),ce.loadCubeData(Re,z,d,i,o)};e&&e.length===6?ce.supportCascades?this._cascadeLoadFiles(t,function(Re){return Te(Re.map(function(Ae){return new Uint8Array(Ae)}))},e,o):o?o("Textures type does not support cascades."):l.a.Warn("Texture loader does not support cascades."):this._loadFile(r,function(Re){return Te(new Uint8Array(Re))},void 0,void 0,!0,function(Re,Ae){r===J?o&&Re&&o(Re.status+" "+Re.statusText,Ae):(l.a.Warn("Failed to load "+r+", falling back to the "+J),B.createCubeTexture(J,t,e,n,i,o,a,s,d,p,b,z,O))})}else{if(!e)throw new Error("Cannot load cubemap because files were not defined");this._cascadeLoadImgs(t,function(Re){var Ae=B.needPOTTextures?Bt.a.GetExponentOfTwo(Re[0].width,B._caps.maxCubemapTextureSize):Re[0].width,Ee=Ae,Se=[F.TEXTURE_CUBE_MAP_POSITIVE_X,F.TEXTURE_CUBE_MAP_POSITIVE_Y,F.TEXTURE_CUBE_MAP_POSITIVE_Z,F.TEXTURE_CUBE_MAP_NEGATIVE_X,F.TEXTURE_CUBE_MAP_NEGATIVE_Y,F.TEXTURE_CUBE_MAP_NEGATIVE_Z];B._bindTextureDirectly(F.TEXTURE_CUBE_MAP,z,!0),B._unpackFlipY(!1);for(var Le=a?B._getInternalFormat(a):B._gl.RGBA,Ce=0;Ce<Se.length;Ce++)if(Re[Ce].width!==Ae||Re[Ce].height!==Ee){if(B._prepareWorkingCanvas(),!B._workingCanvas||!B._workingContext)return void l.a.Warn("Cannot create canvas to resize texture.");B._workingCanvas.width=Ae,B._workingCanvas.height=Ee,B._workingContext.drawImage(Re[Ce],0,0,Re[Ce].width,Re[Ce].height,0,0,Ae,Ee),F.texImage2D(Se[Ce],0,Le,Le,F.UNSIGNED_BYTE,B._workingCanvas)}else F.texImage2D(Se[Ce],0,Le,Le,F.UNSIGNED_BYTE,Re[Ce]);n||F.generateMipmap(F.TEXTURE_CUBE_MAP),B._setCubeMapTextureParams(z,!n),z.width=Ae,z.height=Ee,z.isReady=!0,a&&(z.format=a),z.onLoadedObservable.notifyObservers(z),z.onLoadedObservable.clear(),i&&i()},e,o)}return this._internalTexturesCache.push(z),z},f(153),f(124);var ep=function(){};Ue.a.prototype.getInputElement=function(){return this.inputElement||this.getRenderingCanvas()},Ue.a.prototype.registerView=function(r,t){var e=this;this.views||(this.views=[]);for(var n=0,i=this.views;n<i.length;n++){var o=i[n];if(o.target===r)return o}var a=this.getRenderingCanvas();a&&(r.width=a.width,r.height=a.height);var s={target:r,camera:t};return this.views.push(s),t&&t.onDisposeObservable.add(function(){e.unRegisterView(r)}),s},Ue.a.prototype.unRegisterView=function(r){if(!this.views)return this;for(var t=0,e=this.views;t<e.length;t++){var n=e[t];if(n.target===r){var i=this.views.indexOf(n);i!==-1&&this.views.splice(i,1);break}}return this},Ue.a.prototype._renderViews=function(){if(!this.views)return!1;var r=this.getRenderingCanvas();if(!r)return!1;for(var t=0,e=this.views;t<e.length;t++){var n=e[t],i=n.target,o=i.getContext("2d");if(o){var a=n.camera,s=null,d=null;if(a){if((d=a.getScene()).activeCameras&&d.activeCameras.length)continue;this.activeView=n,s=d.activeCamera,d.activeCamera=a}var p=i.width!==i.clientWidth||i.height!==i.clientHeight;if(i.clientWidth&&i.clientHeight&&p&&(i.width=i.clientWidth,i.height=i.clientHeight,r.width=i.clientWidth,r.height=i.clientHeight,this.resize()),!r.width||!r.height)return!1;this._renderFrame(),o.drawImage(r,0,0),s&&d&&(d.activeCamera=s)}}return this.activeView=null,!0},f(129);function tp(r){if(this._excludedCompressedTextures&&this._excludedCompressedTextures.some(function(i){var o="\\b"+i+"\\b";return r&&(r===i||r.match(new RegExp(o,"g")))}))return r;var t=r.lastIndexOf("."),e=r.lastIndexOf("?"),n=e>-1?r.substring(e,r.length):"";return(t>-1?r.substring(0,t):r)+this._textureFormatInUse+n}Object.defineProperty(Ue.a.prototype,"texturesSupported",{get:function(){var r=new Array;return this._caps.astc&&r.push("-astc.ktx"),this._caps.s3tc&&r.push("-dxt.ktx"),this._caps.pvrtc&&r.push("-pvrtc.ktx"),this._caps.etc2&&r.push("-etc2.ktx"),this._caps.etc1&&r.push("-etc1.ktx"),r},enumerable:!0,configurable:!0}),Object.defineProperty(Ue.a.prototype,"textureFormatInUse",{get:function(){return this._textureFormatInUse||null},enumerable:!0,configurable:!0}),Ue.a.prototype.setCompressedTextureExclusions=function(r){this._excludedCompressedTextures=r},Ue.a.prototype.setTextureFormatToUse=function(r){for(var t=this.texturesSupported,e=0,n=t.length;e<n;e++)for(var i=0,o=r.length;i<o;i++)if(t[e]===r[i].toLowerCase())return this._transformTextureUrl=tp.bind(this),this._textureFormatInUse=t[e];return this._textureFormatInUse="",this._transformTextureUrl=null,null};var np=f(144),ru=f(118),ou=f(89),_i=[Math.sqrt(1/(4*Math.PI)),-Math.sqrt(3/(4*Math.PI)),Math.sqrt(3/(4*Math.PI)),-Math.sqrt(3/(4*Math.PI)),Math.sqrt(15/(4*Math.PI)),-Math.sqrt(15/(4*Math.PI)),Math.sqrt(5/(16*Math.PI)),-Math.sqrt(15/(4*Math.PI)),Math.sqrt(15/(16*Math.PI))],ip=[function(r){return 1},function(r){return r.y},function(r){return r.z},function(r){return r.x},function(r){return r.x*r.y},function(r){return r.y*r.z},function(r){return 3*r.z*r.z-1},function(r){return r.x*r.z},function(r){return r.x*r.x-r.y*r.y}],Ei=function(r,t){return _i[r]*ip[r](t)},Si=[Math.PI,2*Math.PI/3,2*Math.PI/3,2*Math.PI/3,Math.PI/4,Math.PI/4,Math.PI/4,Math.PI/4,Math.PI/4],Es=function(){function r(){this.preScaled=!1,this.l00=u.e.Zero(),this.l1_1=u.e.Zero(),this.l10=u.e.Zero(),this.l11=u.e.Zero(),this.l2_2=u.e.Zero(),this.l2_1=u.e.Zero(),this.l20=u.e.Zero(),this.l21=u.e.Zero(),this.l22=u.e.Zero()}return r.prototype.addLight=function(t,e,n){var i=new u.e(e.r,e.g,e.b).scale(n);this.l00=this.l00.add(i.scale(Ei(0,t))),this.l1_1=this.l1_1.add(i.scale(Ei(1,t))),this.l10=this.l10.add(i.scale(Ei(2,t))),this.l11=this.l11.add(i.scale(Ei(3,t))),this.l2_2=this.l2_2.add(i.scale(Ei(4,t))),this.l2_1=this.l2_1.add(i.scale(Ei(5,t))),this.l20=this.l20.add(i.scale(Ei(6,t))),this.l21=this.l21.add(i.scale(Ei(7,t))),this.l22=this.l22.add(i.scale(Ei(8,t)))},r.prototype.scaleInPlace=function(t){this.l00.scaleInPlace(t),this.l1_1.scaleInPlace(t),this.l10.scaleInPlace(t),this.l11.scaleInPlace(t),this.l2_2.scaleInPlace(t),this.l2_1.scaleInPlace(t),this.l20.scaleInPlace(t),this.l21.scaleInPlace(t),this.l22.scaleInPlace(t)},r.prototype.convertIncidentRadianceToIrradiance=function(){this.l00.scaleInPlace(Si[0]),this.l1_1.scaleInPlace(Si[1]),this.l10.scaleInPlace(Si[2]),this.l11.scaleInPlace(Si[3]),this.l2_2.scaleInPlace(Si[4]),this.l2_1.scaleInPlace(Si[5]),this.l20.scaleInPlace(Si[6]),this.l21.scaleInPlace(Si[7]),this.l22.scaleInPlace(Si[8])},r.prototype.convertIrradianceToLambertianRadiance=function(){this.scaleInPlace(1/Math.PI)},r.prototype.preScaleForRendering=function(){this.preScaled=!0,this.l00.scaleInPlace(_i[0]),this.l1_1.scaleInPlace(_i[1]),this.l10.scaleInPlace(_i[2]),this.l11.scaleInPlace(_i[3]),this.l2_2.scaleInPlace(_i[4]),this.l2_1.scaleInPlace(_i[5]),this.l20.scaleInPlace(_i[6]),this.l21.scaleInPlace(_i[7]),this.l22.scaleInPlace(_i[8])},r.FromArray=function(t){var e=new r;return u.e.FromArrayToRef(t[0],0,e.l00),u.e.FromArrayToRef(t[1],0,e.l1_1),u.e.FromArrayToRef(t[2],0,e.l10),u.e.FromArrayToRef(t[3],0,e.l11),u.e.FromArrayToRef(t[4],0,e.l2_2),u.e.FromArrayToRef(t[5],0,e.l2_1),u.e.FromArrayToRef(t[6],0,e.l20),u.e.FromArrayToRef(t[7],0,e.l21),u.e.FromArrayToRef(t[8],0,e.l22),e},r.FromPolynomial=function(t){var e=new r;return e.l00=t.xx.scale(.376127).add(t.yy.scale(.376127)).add(t.zz.scale(.376126)),e.l1_1=t.y.scale(.977204),e.l10=t.z.scale(.977204),e.l11=t.x.scale(.977204),e.l2_2=t.xy.scale(1.16538),e.l2_1=t.yz.scale(1.16538),e.l20=t.zz.scale(1.34567).subtract(t.xx.scale(.672834)).subtract(t.yy.scale(.672834)),e.l21=t.zx.scale(1.16538),e.l22=t.xx.scale(1.16538).subtract(t.yy.scale(1.16538)),e.l1_1.scaleInPlace(-1),e.l11.scaleInPlace(-1),e.l2_1.scaleInPlace(-1),e.l21.scaleInPlace(-1),e.scaleInPlace(Math.PI),e},r}(),ro=function(){function r(){this.x=u.e.Zero(),this.y=u.e.Zero(),this.z=u.e.Zero(),this.xx=u.e.Zero(),this.yy=u.e.Zero(),this.zz=u.e.Zero(),this.xy=u.e.Zero(),this.yz=u.e.Zero(),this.zx=u.e.Zero()}return Object.defineProperty(r.prototype,"preScaledHarmonics",{get:function(){return this._harmonics||(this._harmonics=Es.FromPolynomial(this)),this._harmonics.preScaled||this._harmonics.preScaleForRendering(),this._harmonics},enumerable:!1,configurable:!0}),r.prototype.addAmbient=function(t){var e=new u.e(t.r,t.g,t.b);this.xx=this.xx.add(e),this.yy=this.yy.add(e),this.zz=this.zz.add(e)},r.prototype.scaleInPlace=function(t){this.x.scaleInPlace(t),this.y.scaleInPlace(t),this.z.scaleInPlace(t),this.xx.scaleInPlace(t),this.yy.scaleInPlace(t),this.zz.scaleInPlace(t),this.yz.scaleInPlace(t),this.zx.scaleInPlace(t),this.xy.scaleInPlace(t)},r.FromHarmonics=function(t){var e=new r;return e._harmonics=t,e.x=t.l11.scale(1.02333).scale(-1),e.y=t.l1_1.scale(1.02333).scale(-1),e.z=t.l10.scale(1.02333),e.xx=t.l00.scale(.886277).subtract(t.l20.scale(.247708)).add(t.l22.scale(.429043)),e.yy=t.l00.scale(.886277).subtract(t.l20.scale(.247708)).subtract(t.l22.scale(.429043)),e.zz=t.l00.scale(.886277).add(t.l20.scale(.495417)),e.yz=t.l2_1.scale(.858086).scale(-1),e.zx=t.l21.scale(.858086).scale(-1),e.xy=t.l2_2.scale(.858086),e.scaleInPlace(1/Math.PI),e},r.FromArray=function(t){var e=new r;return u.e.FromArrayToRef(t[0],0,e.x),u.e.FromArrayToRef(t[1],0,e.y),u.e.FromArrayToRef(t[2],0,e.z),u.e.FromArrayToRef(t[3],0,e.xx),u.e.FromArrayToRef(t[4],0,e.yy),u.e.FromArrayToRef(t[5],0,e.zz),u.e.FromArrayToRef(t[6],0,e.yz),u.e.FromArrayToRef(t[7],0,e.zx),u.e.FromArrayToRef(t[8],0,e.xy),e},r}(),zn=f(52),yr=function(r,t,e,n){this.name=r,this.worldAxisForNormal=t,this.worldAxisForFileX=e,this.worldAxisForFileY=n},jo=function(){function r(){}return r.ConvertCubeMapTextureToSphericalPolynomial=function(t){if(!t.isCube)return null;var e,n,i=t.getSize().width,o=t.readPixels(0),a=t.readPixels(1);t.isRenderTarget?(e=t.readPixels(3),n=t.readPixels(2)):(e=t.readPixels(2),n=t.readPixels(3));var s=t.readPixels(4),d=t.readPixels(5),p=t.gammaSpace,b=h.a.TEXTUREFORMAT_RGBA,P=h.a.TEXTURETYPE_UNSIGNED_INT;t.textureType!=h.a.TEXTURETYPE_FLOAT&&t.textureType!=h.a.TEXTURETYPE_HALF_FLOAT||(P=h.a.TEXTURETYPE_FLOAT);var O={size:i,right:o,left:a,up:e,down:n,front:s,back:d,format:b,type:P,gammaSpace:p};return this.ConvertCubeMapToSphericalPolynomial(O)},r.ConvertCubeMapToSphericalPolynomial=function(t){for(var e=new Es,n=0,i=2/t.size,o=i,a=.5*i-1,s=0;s<6;s++)for(var d=this.FileFaces[s],p=t[d.name],b=a,P=t.format===h.a.TEXTUREFORMAT_RGBA?4:3,O=0;O<t.size;O++){for(var B=a,F=0;F<t.size;F++){var z=d.worldAxisForFileX.scale(B).add(d.worldAxisForFileY.scale(b)).add(d.worldAxisForNormal);z.normalize();var J=Math.pow(1+B*B+b*b,-1.5),ie=p[O*t.size*P+F*P+0],se=p[O*t.size*P+F*P+1],ce=p[O*t.size*P+F*P+2];isNaN(ie)&&(ie=0),isNaN(se)&&(se=0),isNaN(ce)&&(ce=0),t.type===h.a.TEXTURETYPE_UNSIGNED_INT&&(ie/=255,se/=255,ce/=255),t.gammaSpace&&(ie=Math.pow($.a.Clamp(ie),Gt.c),se=Math.pow($.a.Clamp(se),Gt.c),ce=Math.pow($.a.Clamp(ce),Gt.c)),ie=$.a.Clamp(ie,0,4096),se=$.a.Clamp(se,0,4096),ce=$.a.Clamp(ce,0,4096);var ue=new M.a(ie,se,ce);e.addLight(z,ue,J),n+=J,B+=i}b+=o}var fe=6*(4*Math.PI)/6/n;return e.scaleInPlace(fe),e.convertIncidentRadianceToIrradiance(),e.convertIrradianceToLambertianRadiance(),ro.FromHarmonics(e)},r.FileFaces=[new yr("right",new u.e(1,0,0),new u.e(0,0,-1),new u.e(0,-1,0)),new yr("left",new u.e(-1,0,0),new u.e(0,0,1),new u.e(0,-1,0)),new yr("up",new u.e(0,1,0),new u.e(1,0,0),new u.e(0,0,1)),new yr("down",new u.e(0,-1,0),new u.e(1,0,0),new u.e(0,0,-1)),new yr("front",new u.e(0,0,1),new u.e(1,0,0),new u.e(0,-1,0)),new yr("back",new u.e(0,0,-1),new u.e(-1,0,0),new u.e(0,-1,0))],r}();Object.defineProperty(zn.a.prototype,"sphericalPolynomial",{get:function(){if(this._texture){if(this._texture._sphericalPolynomial)return this._texture._sphericalPolynomial;if(this._texture.isReady)return this._texture._sphericalPolynomial=jo.ConvertCubeMapTextureToSphericalPolynomial(this),this._texture._sphericalPolynomial}return null},set:function(r){this._texture&&(this._texture._sphericalPolynomial=r)},enumerable:!0,configurable:!0});var rp=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-#include<helperFunctions>
-void main(void)
-{
-gl_FragColor=toRGBD(texture2D(textureSampler,vUV).rgb);
-}`;ze.a.ShadersStore.rgbdEncodePixelShader=rp;var op=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-#include<helperFunctions>
-void main(void)
-{
-gl_FragColor=vec4(fromRGBD(texture2D(textureSampler,vUV)),1.0);
-}`;ze.a.ShadersStore.rgbdDecodePixelShader=op;var Ai=function(){function r(){}return r.GetEnvInfo=function(t){for(var e=new DataView(t.buffer,t.byteOffset,t.byteLength),n=0,i=0;i<r._MagicBytes.length;i++)if(e.getUint8(n++)!==r._MagicBytes[i])return l.a.Error("Not a babylon environment map"),null;for(var o="",a=0;a=e.getUint8(n++);)o+=String.fromCharCode(a);var s=JSON.parse(o);return s.specular&&(s.specular.specularDataPosition=n,s.specular.lodGenerationScale=s.specular.lodGenerationScale||.8),s},r.CreateEnvTextureAsync=function(t){var e=this,n=t.getInternalTexture();if(!n)return Promise.reject("The cube texture is invalid.");var i=n.getEngine();if(i&&i.premultipliedAlpha)return Promise.reject("Env texture can only be created when the engine is created with the premultipliedAlpha option set to false.");if(t.textureType===h.a.TEXTURETYPE_UNSIGNED_INT)return Promise.reject("The cube texture should allow HDR (Full Float or Half Float).");var o=i.getRenderingCanvas();if(!o)return Promise.reject("Env texture can only be created when the engine is associated to a canvas.");var a=h.a.TEXTURETYPE_FLOAT;if(!i.getCaps().textureFloatRender&&(a=h.a.TEXTURETYPE_HALF_FLOAT,!i.getCaps().textureHalfFloatRender))return Promise.reject("Env texture can only be created when the browser supports half float or full float rendering.");var s=n.width,d=new _e.a(i),p={},b=[],P=$.a.Log2(n.width);P=Math.round(P);for(var O=function(F){for(var z=Math.pow(2,P-F),J=function(se){var ce=t.readPixels(se,F),ue=i.createRawTexture(ce,z,z,h.a.TEXTUREFORMAT_RGBA,!1,!1,h.a.TEXTURE_NEAREST_SAMPLINGMODE,null,a),fe=new Promise(function(ve,Te){var Re=new _t("rgbdEncode","rgbdEncode",null,null,1,null,h.a.TEXTURE_NEAREST_SAMPLINGMODE,i,!1,void 0,h.a.TEXTURETYPE_UNSIGNED_INT,void 0,null,!1);Re.getEffect().executeWhenCompiled(function(){Re.onApply=function(Se){Se._bindTexture("textureSampler",ue)};var Ae=i.getRenderWidth(),Ee=i.getRenderHeight();i.setSize(z,z),d.postProcessManager.directRender([Re],null),Xe.b.ToBlob(o,function(Se){var Le=new FileReader;Le.onload=function(Ce){var Ne=Ce.target.result;p[6*F+se]=Ne,ve()},Le.readAsArrayBuffer(Se)}),i.setSize(Ae,Ee)})});b.push(fe)},ie=0;ie<6;ie++)J(ie)},B=0;B<=P;B++)O(B);return Promise.all(b).then(function(){d.dispose();for(var F={version:1,width:s,irradiance:e._CreateEnvTextureIrradiance(t),specular:{mipmaps:[],lodGenerationScale:t.lodGenerationScale}},z=0,J=0;J<=P;J++)for(var ie=0;ie<6;ie++){var se=p[6*J+ie].byteLength;F.specular.mipmaps.push({length:se,position:z}),z+=se}for(var ce=JSON.stringify(F),ue=new ArrayBuffer(ce.length+1),fe=new Uint8Array(ue),ve=(J=0,ce.length);J<ve;J++)fe[J]=ce.charCodeAt(J);fe[ce.length]=0;var Te=r._MagicBytes.length+z+ue.byteLength,Re=new ArrayBuffer(Te),Ae=new Uint8Array(Re),Ee=new DataView(Re),Se=0;for(J=0;J<r._MagicBytes.length;J++)Ee.setUint8(Se++,r._MagicBytes[J]);for(Ae.set(new Uint8Array(ue),Se),Se+=ue.byteLength,J=0;J<=P;J++)for(ie=0;ie<6;ie++){var Le=p[6*J+ie];Ae.set(new Uint8Array(Le),Se),Se+=Le.byteLength}return Re})},r._CreateEnvTextureIrradiance=function(t){var e=t.sphericalPolynomial;return e==null?null:{x:[e.x.x,e.x.y,e.x.z],y:[e.y.x,e.y.y,e.y.z],z:[e.z.x,e.z.y,e.z.z],xx:[e.xx.x,e.xx.y,e.xx.z],yy:[e.yy.x,e.yy.y,e.yy.z],zz:[e.zz.x,e.zz.y,e.zz.z],yz:[e.yz.x,e.yz.y,e.yz.z],zx:[e.zx.x,e.zx.y,e.zx.z],xy:[e.xy.x,e.xy.y,e.xy.z]}},r.CreateImageDataArrayBufferViews=function(t,e){if(e.version!==1)throw new Error('Unsupported babylon environment map version "'+e.version+'"');var n=e.specular,i=$.a.Log2(e.width);if(i=Math.round(i)+1,n.mipmaps.length!==6*i)throw new Error('Unsupported specular mipmaps number "'+n.mipmaps.length+'"');for(var o=new Array(i),a=0;a<i;a++){o[a]=new Array(6);for(var s=0;s<6;s++){var d=n.mipmaps[6*a+s];o[a][s]=new Uint8Array(t.buffer,t.byteOffset+n.specularDataPosition+d.position,d.length)}}return o},r.UploadEnvLevelsAsync=function(t,e,n){if(n.version!==1)throw new Error('Unsupported babylon environment map version "'+n.version+'"');var i=n.specular;if(!i)return Promise.resolve();t._lodGenerationScale=i.lodGenerationScale;var o=r.CreateImageDataArrayBufferViews(e,n);return r.UploadLevelsAsync(t,o)},r._OnImageReadyAsync=function(t,e,n,i,o,a,s,d,p,b,P){return new Promise(function(O,B){if(n){var F=e.createTexture(null,!0,!0,null,h.a.TEXTURE_NEAREST_SAMPLINGMODE,null,function(J){B(J)},t);i.getEffect().executeWhenCompiled(function(){i.onApply=function(J){J._bindTexture("textureSampler",F),J.setFloat2("scale",1,1)},e.scenes[0].postProcessManager.directRender([i],b,!0,a,s),e.restoreDefaultFramebuffer(),F.dispose(),URL.revokeObjectURL(o),O()})}else{if(e._uploadImageToTexture(P,t,a,s),d){var z=p[s];z&&e._uploadImageToTexture(z._texture,t,a,0)}O()}})},r.UploadLevelsAsync=function(t,e){var n=this;if(!Xe.b.IsExponentOfTwo(t.width))throw new Error("Texture size must be a power of two");var i=Math.round($.a.Log2(t.width))+1,o=t.getEngine(),a=!1,s=!1,d=null,p=null,b=null,P=o.getCaps();if(t.format=h.a.TEXTUREFORMAT_RGBA,t.type=h.a.TEXTURETYPE_UNSIGNED_INT,t.generateMipMaps=!0,t._cachedAnisotropicFilteringLevel=null,o.updateTextureSamplingMode(h.a.TEXTURE_TRILINEAR_SAMPLINGMODE,t),P.textureLOD?o.webGLVersion<2?a=!1:P.textureHalfFloatRender&&P.textureHalfFloatLinearFiltering?(a=!0,t.type=h.a.TEXTURETYPE_HALF_FLOAT):P.textureFloatRender&&P.textureFloatLinearFiltering&&(a=!0,t.type=h.a.TEXTURETYPE_FLOAT):(a=!1,s=!0,b={}),a)d=new _t("rgbdDecode","rgbdDecode",null,null,1,null,h.a.TEXTURE_TRILINEAR_SAMPLINGMODE,o,!1,void 0,t.type,void 0,null,!1),t._isRGBD=!1,t.invertY=!1,p=o.createRenderTargetCubeTexture(t.width,{generateDepthBuffer:!1,generateMipMaps:!0,generateStencilBuffer:!1,samplingMode:h.a.TEXTURE_TRILINEAR_SAMPLINGMODE,type:t.type,format:h.a.TEXTUREFORMAT_RGBA});else if(t._isRGBD=!0,t.invertY=!0,s)for(var O=t._lodGenerationScale,B=t._lodGenerationOffset,F=0;F<3;F++){var z=(i-1)*O+B,J=B+(z-B)*(1-F/2),ie=Math.round(Math.min(Math.max(J,0),z)),se=new xt.a(o,xt.b.Temp);se.isCube=!0,se.invertY=!0,se.generateMipMaps=!1,o.updateTextureSamplingMode(h.a.TEXTURE_LINEAR_LINEAR,se);var ce=new zn.a(null);switch(ce.isCube=!0,ce._texture=se,b[ie]=ce,F){case 0:t._lodTextureLow=ce;break;case 1:t._lodTextureMid=ce;break;case 2:t._lodTextureHigh=ce}}var ue=[],fe=function(Ee){for(var Se=function(Ce){var Ne=e[Ee][Ce],Ie=new Blob([Ne],{type:"image/png"}),Fe=URL.createObjectURL(Ie),Ye=void 0;if(typeof Image>"u")Ye=createImageBitmap(Ie).then(function(it){return n._OnImageReadyAsync(it,o,a,d,Fe,Ce,Ee,s,b,p,t)});else{var tt=new Image;tt.src=Fe,Ye=new Promise(function(it,lt){tt.onload=function(){n._OnImageReadyAsync(tt,o,a,d,Fe,Ce,Ee,s,b,p,t).then(function(){return it()}).catch(function(Qe){lt(Qe)})},tt.onerror=function(Qe){lt(Qe)}})}ue.push(Ye)},Le=0;Le<6;Le++)Se(Le)};for(F=0;F<e.length;F++)fe(F);if(e.length<i){var ve=void 0,Te=Math.pow(2,i-1-e.length),Re=Te*Te*4;switch(t.type){case h.a.TEXTURETYPE_UNSIGNED_INT:ve=new Uint8Array(Re);break;case h.a.TEXTURETYPE_HALF_FLOAT:ve=new Uint16Array(Re);break;case h.a.TEXTURETYPE_FLOAT:ve=new Float32Array(Re)}for(F=e.length;F<i;F++)for(var Ae=0;Ae<6;Ae++)o._uploadArrayBufferViewToTexture(t,ve,Ae,F)}return Promise.all(ue).then(function(){p&&(o._releaseFramebufferObjects(p),o._releaseTexture(t),p._swapAndDie(t)),d&&d.dispose(),s&&(t._lodTextureHigh&&t._lodTextureHigh._texture&&(t._lodTextureHigh._texture.isReady=!0),t._lodTextureMid&&t._lodTextureMid._texture&&(t._lodTextureMid._texture.isReady=!0),t._lodTextureLow&&t._lodTextureLow._texture&&(t._lodTextureLow._texture.isReady=!0))})},r.UploadEnvSpherical=function(t,e){e.version!==1&&l.a.Warn('Unsupported babylon environment map version "'+e.version+'"');var n=e.irradiance;if(n){var i=new 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p=this._sourceCode.substring(n+1,d),b=this._skipWhitespaces(this._sourceCode,d+1);if(b!==this._sourceCode.length){var P=this._extractBetweenMarkers("{","}",this._sourceCode,b);if(P<0)this.debug&&console.warn("Could not extract the body of the function '"+s+"' (type="+a+"). funcBodyStartIndex="+b),t=e+this.inlineToken.length;else{for(var O=this._sourceCode.substring(b,P+1),B=this._removeComments(p).split(","),F=[],z=0;z<B.length;++z){var J=B[z].trim(),ie=J.lastIndexOf(" ");ie>=0&&F.push(J.substring(ie+1))}a!=="void"&&F.push("return"),this._functionDescr.push({name:s,type:a,parameters:F,body:O,callIndex:0}),t=P+1;var se=e>0?this._sourceCode.substring(0,e):"",ce=P+1<this._sourceCode.length-1?this._sourceCode.substring(P+1):"";this._sourceCode=se+ce,t-=P+1-e}}else this.debug&&console.warn("Could not extract the body of the function '"+s+"' (type="+a+"). funcParamsEndIndex="+d),t=e+this.inlineToken.length}}else this.debug&&console.warn("Could not extract the name/type of the function from: 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b=this._native.createProgram(n,i);return this.onAfterShaderCompilationObservable.notifyObservers(this),b},t.prototype._setProgram=function(e){this._currentProgram!==e&&(this._native.setProgram(e),this._currentProgram=e)},t.prototype._releaseEffect=function(e){},t.prototype._deletePipelineContext=function(e){},t.prototype.getUniforms=function(e,n){var i=e;return this._native.getUniforms(i.nativeProgram,n)},t.prototype.bindUniformBlock=function(e,n,i){throw new Error("Not Implemented")},t.prototype.bindSamplers=function(e){var n=e.getPipelineContext();this._setProgram(n.nativeProgram);for(var i=e.getSamplers(),o=0;o<i.length;o++){var a=e.getUniform(i[o]);a&&(this._boundUniforms[o]=a)}this._currentEffect=null},t.prototype.setMatrix=function(e,n){e&&this._native.setMatrix(e,n.toArray())},t.prototype.getRenderWidth=function(e){return e===void 0&&(e=!1),!e&&this._currentRenderTarget?this._currentRenderTarget.width:this._native.getRenderWidth()},t.prototype.getRenderHeight=function(e){return 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this._native.createTexture()},t.prototype._deleteTexture=function(e){this._native.deleteTexture(e)},t.prototype.updateDynamicTexture=function(e,n,i,o,a){this.createTexture("data:my_image_name",!0,i,null,we.a.BILINEAR_SAMPLINGMODE,void 0,void 0,"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAgAAAAICAYAAADED76LAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAAYSURBVChTY/z//z8DPsAEpXGC4aCAgQEAGGMDDWwwgqsAAAAASUVORK5CYII=",e,t.TEXTUREFORMAT_RGBA,null,void 0)},t.prototype.createTexture=function(e,n,i,o,a,s,d,p,b,P,O,B,F){var z=this;a===void 0&&(a=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE),s===void 0&&(s=null),d===void 0&&(d=null),p===void 0&&(p=null),b===void 0&&(b=null),P===void 0&&(P=null),O===void 0&&(O=null);var J=(e=e||"").substr(0,5)==="data:",ie=J&&e.indexOf(";base64,")!==-1,se=b||new xt.a(this,xt.b.Url),ce=e;!this._transformTextureUrl||ie||b||p||(e=this._transformTextureUrl(e));for(var 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ve=Ai.CreateImageDataArrayBufferViews(ce,ue);z.format=h.a.TEXTUREFORMAT_RGBA,z.type=h.a.TEXTURETYPE_UNSIGNED_INT,z.generateMipMaps=!0,z.getEngine().updateTextureSamplingMode(we.a.TRILINEAR_SAMPLINGMODE,z),z._isRGBD=!0,z.invertY=!0,F._native.loadCubeTextureWithMips(z._webGLTexture,ve,function(){z.isReady=!0,a&&a()},function(){throw new Error("Could not load a native cube texture.")})}(new Uint8Array(se))},void 0,void 0,!0,function(se,ce){s&&se&&s(se.status+" "+se.statusText,ce)})}else{if(!i||i.length!==6)throw new Error("Cannot load cubemap because 6 files were not defined");var ie=[i[0],i[3],i[1],i[4],i[2],i[5]];Promise.all(ie.map(function(se){return Xe.b.LoadFileAsync(se).then(function(ce){return new Uint8Array(ce)})})).then(function(se){return new Promise(function(ce,ue){F._native.loadCubeTexture(z._webGLTexture,se,!o,ce,ue)})}).then(function(){z.isReady=!0,a&&a()},function(se){s&&s("Failed to load cubemap: "+se.message,se)})}return this._internalTexturesCache.push(z),z},t.prototype.createRenderTargetTexture=function(e,n){var i=new Ml.a;n!==void 0&&typeof n=="object"?(i.generateMipMaps=n.generateMipMaps,i.generateDepthBuffer=n.generateDepthBuffer===void 0||n.generateDepthBuffer,i.generateStencilBuffer=i.generateDepthBuffer&&n.generateStencilBuffer,i.type=n.type===void 0?h.a.TEXTURETYPE_UNSIGNED_INT:n.type,i.samplingMode=n.samplingMode===void 0?h.a.TEXTURE_TRILINEAR_SAMPLINGMODE:n.samplingMode,i.format=n.format===void 0?h.a.TEXTUREFORMAT_RGBA:n.format):(i.generateMipMaps=n,i.generateDepthBuffer=!0,i.generateStencilBuffer=!1,i.type=h.a.TEXTURETYPE_UNSIGNED_INT,i.samplingMode=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE,i.format=h.a.TEXTUREFORMAT_RGBA),(i.type!==h.a.TEXTURETYPE_FLOAT||this._caps.textureFloatLinearFiltering)&&(i.type!==h.a.TEXTURETYPE_HALF_FLOAT||this._caps.textureHalfFloatLinearFiltering)||(i.samplingMode=h.a.TEXTURE_NEAREST_SAMPLINGMODE);var o=new su(this,xt.b.RenderTarget),a=e.width||e,s=e.height||e;i.type!==h.a.TEXTURETYPE_FLOAT||this._caps.textureFloat||(i.type=h.a.TEXTURETYPE_UNSIGNED_INT,l.a.Warn("Float textures are not supported. Render target forced to TEXTURETYPE_UNSIGNED_BYTE type"));var d=this._native.createFramebuffer(o._webGLTexture,a,s,this._getNativeTextureFormat(i.format,i.type),i.samplingMode,!!i.generateStencilBuffer,i.generateDepthBuffer,!!i.generateMipMaps);return o._framebuffer=d,o.baseWidth=a,o.baseHeight=s,o.width=a,o.height=s,o.isReady=!0,o.samples=1,o.generateMipMaps=!!i.generateMipMaps,o.samplingMode=i.samplingMode,o.type=i.type,o.format=i.format,o._generateDepthBuffer=i.generateDepthBuffer,o._generateStencilBuffer=!!i.generateStencilBuffer,this._internalTexturesCache.push(o),o},t.prototype.updateTextureSamplingMode=function(e,n){if(n._webGLTexture){var i=this._getNativeSamplingMode(e);this._native.setTextureSampling(n._webGLTexture,i)}n.samplingMode=e},t.prototype.bindFramebuffer=function(e,n,i,o,a){if(n)throw new Error("Cuboid frame buffers are not yet supported in NativeEngine.");if(i||o)throw new Error("Required width/height for frame buffers not yet supported in NativeEngine.");e._depthStencilTexture?this._bindUnboundFramebuffer(e._depthStencilTexture._framebuffer):this._bindUnboundFramebuffer(e._framebuffer)},t.prototype.unBindFramebuffer=function(e,n,i){n===void 0&&(n=!1),n&&l.a.Warn("Disabling mipmap generation not yet supported in NativeEngine. Ignoring."),i&&i(),this._bindUnboundFramebuffer(null)},t.prototype.createDynamicVertexBuffer=function(e){return this.createVertexBuffer(e,!0)},t.prototype.updateDynamicIndexBuffer=function(e,n,i){i===void 0&&(i=0);var o=e,a=this._normalizeIndexData(n);o.is32Bits=a.BYTES_PER_ELEMENT===4,this._native.updateDynamicIndexBuffer(o.nativeIndexBuffer,a,i)},t.prototype.updateDynamicVertexBuffer=function(e,n,i,o){var a=e,s=ArrayBuffer.isView(n)?n:new Float32Array(n);this._native.updateDynamicVertexBuffer(a.nativeVertexBuffer,s,i??0,o??s.byteLength)},t.prototype._setTexture=function(e,n,i,o){o===void 0&&(o=!1);var a,s=this._boundUniforms[e];if(!s)return!1;if(!n)return this._boundTexturesCache[e]!=null&&(this._activeChannel=e,this._native.setTexture(s,null)),!1;if(n.video)this._activeChannel=e,n.update();else if(n.delayLoadState===h.a.DELAYLOADSTATE_NOTLOADED)return n.delayLoad(),!1;return 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Error("Unexpected wrap mode: "+e+".")}},t.prototype._bindTexture=function(e,n){var i=this._boundUniforms[e];i&&this._native.setTexture(i,n._webGLTexture)},t.prototype._deleteBuffer=function(e){e.nativeIndexBuffer&&(this._native.deleteIndexBuffer(e.nativeIndexBuffer),delete e.nativeIndexBuffer),e.nativeVertexBuffer&&(this._native.deleteVertexBuffer(e.nativeVertexBuffer),delete e.nativeVertexBuffer)},t.prototype.releaseEffects=function(){},t.prototype._uploadCompressedDataToTextureDirectly=function(e,n,i,o,a,s,d){throw new Error("_uploadCompressedDataToTextureDirectly not implemented.")},t.prototype._uploadDataToTextureDirectly=function(e,n,i,o){throw new Error("_uploadDataToTextureDirectly not implemented.")},t.prototype._uploadArrayBufferViewToTexture=function(e,n,i,o){throw new Error("_uploadArrayBufferViewToTexture not implemented.")},t.prototype._uploadImageToTexture=function(e,n,i,o){throw new Error("_uploadArrayBufferViewToTexture not 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r.id.indexOf(Ps.GAMEPAD_ID_PREFIX)===0},create:function(r){return new Ps(r)}});var Cs=function(r){function t(e){var n=r.call(this,e)||this;return n._buttonIndexToObservableNameMap=["onPadStateChangedObservable","onTriggerStateChangedObservable"],n.controllerType=ri.GEAR_VR,n._calculatedPosition=new u.e(n.hand=="left"?-.15:.15,-.5,.25),n._disableTrackPosition(n._calculatedPosition),n}return Object(c.d)(t,r),t.prototype.initControllerMesh=function(e,n){var i=this;Ut.ImportMesh("",t.MODEL_BASE_URL,t.MODEL_FILENAME,e,function(o){var a=new De.a("",e);o[1].parent=a,o[1].position.z=-.15,i._defaultModel=a,i.attachToMesh(i._defaultModel),n&&n(i._defaultModel)})},t.prototype._handleButtonChange=function(e,n,i){if(e<this._buttonIndexToObservableNameMap.length){var o=this[this._buttonIndexToObservableNameMap[e]];o&&o.notifyObservers(n)}},t.MODEL_BASE_URL="https://controllers.babylonjs.com/generic/",t.MODEL_FILENAME="generic.babylon",t.GAMEPAD_ID_PREFIX="Gear 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Object(c.d)(t,r),t.prototype.initControllerMesh=function(e,n){var i,o=this;i=this.hand==="left"?t.MODEL_LEFT_FILENAME:t.MODEL_RIGHT_FILENAME,Ut.ImportMesh("",t._IsQuest?t.QUEST_MODEL_BASE_URL:t.MODEL_BASE_URL,i,e,function(a){o._defaultModel=t._IsQuest?a[0]:a[1],o.attachToMesh(o._defaultModel),n&&n(o._defaultModel)})},Object.defineProperty(t.prototype,"onAButtonStateChangedObservable",{get:function(){if(this.hand==="right")return this.onMainButtonStateChangedObservable;throw new Error("No A button on left hand")},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onBButtonStateChangedObservable",{get:function(){if(this.hand==="right")return this.onSecondaryButtonStateChangedObservable;throw new Error("No B button on left hand")},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onXButtonStateChangedObservable",{get:function(){if(this.hand==="left")return this.onMainButtonStateChangedObservable;throw new Error("No X button on right hand")},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onYButtonStateChangedObservable",{get:function(){if(this.hand==="left")return this.onSecondaryButtonStateChangedObservable;throw new Error("No Y button on right hand")},enumerable:!1,configurable:!0}),t.prototype._handleButtonChange=function(e,n,i){var o=n,a=this.hand==="right"?-1:1;switch(e){case 0:return void this.onPadStateChangedObservable.notifyObservers(o);case 1:return!t._IsQuest&&this._defaultModel&&(this._defaultModel.getChildren()[3].rotation.x=.2*-o.value,this._defaultModel.getChildren()[3].position.y=.005*-o.value,this._defaultModel.getChildren()[3].position.z=.005*-o.value),void this.onTriggerStateChangedObservable.notifyObservers(o);case 2:return!t._IsQuest&&this._defaultModel&&(this._defaultModel.getChildren()[4].position.x=a*o.value*.0035),void this.onSecondaryTriggerStateChangedObservable.notifyObservers(o);case 3:return!t._IsQuest&&this._defaultModel&&(o.pressed?this._defaultModel.getChildren()[1].position.y=-.001:this._defaultModel.getChildren()[1].position.y=0),void this.onMainButtonStateChangedObservable.notifyObservers(o);case 4:return!t._IsQuest&&this._defaultModel&&(o.pressed?this._defaultModel.getChildren()[2].position.y=-.001:this._defaultModel.getChildren()[2].position.y=0),void this.onSecondaryButtonStateChangedObservable.notifyObservers(o);case 5:return void this.onThumbRestChangedObservable.notifyObservers(o)}},t.MODEL_BASE_URL="https://controllers.babylonjs.com/oculus/",t.MODEL_LEFT_FILENAME="left.babylon",t.MODEL_RIGHT_FILENAME="right.babylon",t.QUEST_MODEL_BASE_URL="https://controllers.babylonjs.com/oculusQuest/",t._IsQuest=!1,t}(Bi);wi._ControllerFactories.push({canCreate:function(r){return Ue.a.LastCreatedEngine&&Ue.a.LastCreatedEngine._vrDisplay&&Ue.a.LastCreatedEngine._vrDisplay.displayName==="Oculus Quest"&&(xs._IsQuest=!0),r.id.indexOf("Oculus Touch")!==-1},create:function(r){return new xs(r)}});var cu=function(r){function t(e){var n=r.call(this,e)||this;return n.controllerType=ri.VIVE,n._invertLeftStickY=!0,n}return Object(c.d)(t,r),t.prototype.initControllerMesh=function(e,n){var i=this;Ut.ImportMesh("",t.MODEL_BASE_URL,t.MODEL_FILENAME,e,function(o){i._defaultModel=o[1],i.attachToMesh(i._defaultModel),n&&n(i._defaultModel)})},Object.defineProperty(t.prototype,"onLeftButtonStateChangedObservable",{get:function(){return this.onMainButtonStateChangedObservable},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onRightButtonStateChangedObservable",{get:function(){return this.onMainButtonStateChangedObservable},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onMenuButtonStateChangedObservable",{get:function(){return this.onSecondaryButtonStateChangedObservable},enumerable:!1,configurable:!0}),t.prototype._handleButtonChange=function(e,n,i){var o=n;switch(e){case 0:return void this.onPadStateChangedObservable.notifyObservers(o);case 1:return this._defaultModel&&(this._defaultModel.getChildren()[6].rotation.x=.15*-o.value),void this.onTriggerStateChangedObservable.notifyObservers(o);case 2:return void this.onMainButtonStateChangedObservable.notifyObservers(o);case 3:return this._defaultModel&&(o.pressed?this._defaultModel.getChildren()[2].position.y=-.001:this._defaultModel.getChildren()[2].position.y=0),void this.onSecondaryButtonStateChangedObservable.notifyObservers(o)}},t.MODEL_BASE_URL="https://controllers.babylonjs.com/vive/",t.MODEL_FILENAME="wand.babylon",t}(Bi);wi._ControllerFactories.push({canCreate:function(r){return r.id.toLowerCase().indexOf("openvr")!==-1},create:function(r){return new cu(r)}});var up=function(){this.buttonMeshes={},this.axisMeshes={}},Xo=function(r){function t(e){var n=r.call(this,e)||this;return n._mapping={buttons:["thumbstick","trigger","grip","menu","trackpad"],buttonMeshNames:{trigger:"SELECT",menu:"MENU",grip:"GRASP",thumbstick:"THUMBSTICK_PRESS",trackpad:"TOUCHPAD_PRESS"},buttonObservableNames:{trigger:"onTriggerStateChangedObservable",menu:"onSecondaryButtonStateChangedObservable",grip:"onMainButtonStateChangedObservable",thumbstick:"onPadStateChangedObservable",trackpad:"onTrackpadChangedObservable"},axisMeshNames:["THUMBSTICK_X","THUMBSTICK_Y","TOUCHPAD_TOUCH_X","TOUCHPAD_TOUCH_Y"],pointingPoseMeshName:pr.POINTING_POSE},n.onTrackpadChangedObservable=new x.c,n.onTrackpadValuesChangedObservable=new x.c,n.trackpad={x:0,y:0},n.controllerType=ri.WINDOWS,n._loadedMeshInfo=null,n}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"onTriggerButtonStateChangedObservable",{get:function(){return this.onTriggerStateChangedObservable},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onMenuButtonStateChangedObservable",{get:function(){return this.onSecondaryButtonStateChangedObservable},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onGripButtonStateChangedObservable",{get:function(){return this.onMainButtonStateChangedObservable},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onThumbstickButtonStateChangedObservable",{get:function(){return this.onPadStateChangedObservable},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onTouchpadButtonStateChangedObservable",{get:function(){return this.onTrackpadChangedObservable},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onTouchpadValuesChangedObservable",{get:function(){return this.onTrackpadValuesChangedObservable},enumerable:!1,configurable:!0}),t.prototype._updateTrackpad=function(){!this.browserGamepad.axes||this.browserGamepad.axes[2]==this.trackpad.x&&this.browserGamepad.axes[3]==this.trackpad.y||(this.trackpad.x=this.browserGamepad.axes[this._mapping.axisMeshNames.indexOf("TOUCHPAD_TOUCH_X")],this.trackpad.y=this.browserGamepad.axes[this._mapping.axisMeshNames.indexOf("TOUCHPAD_TOUCH_Y")],this.onTrackpadValuesChangedObservable.notifyObservers(this.trackpad))},t.prototype.update=function(){if(r.prototype.update.call(this),this.browserGamepad.axes&&(this._updateTrackpad(),this._loadedMeshInfo))for(var e=0;e<this._mapping.axisMeshNames.length;e++)this._lerpAxisTransform(e,this.browserGamepad.axes[e])},t.prototype._handleButtonChange=function(e,n,i){var o=this._mapping.buttons[e];if(o){this._updateTrackpad();var a=this[this._mapping.buttonObservableNames[o]];a&&a.notifyObservers(n),this._lerpButtonTransform(o,n.value)}},t.prototype._lerpButtonTransform=function(e,n){if(this._loadedMeshInfo){var i=this._loadedMeshInfo.buttonMeshes[e];i&&i.unpressed.rotationQuaternion&&i.pressed.rotationQuaternion&&i.value.rotationQuaternion&&(u.b.SlerpToRef(i.unpressed.rotationQuaternion,i.pressed.rotationQuaternion,n,i.value.rotationQuaternion),u.e.LerpToRef(i.unpressed.position,i.pressed.position,n,i.value.position))}},t.prototype._lerpAxisTransform=function(e,n){if(this._loadedMeshInfo){var i=this._loadedMeshInfo.axisMeshes[e];if(i&&i.min.rotationQuaternion&&i.max.rotationQuaternion&&i.value.rotationQuaternion){var o=.5*n+.5;u.b.SlerpToRef(i.min.rotationQuaternion,i.max.rotationQuaternion,o,i.value.rotationQuaternion),u.e.LerpToRef(i.min.position,i.max.position,o,i.value.position)}}},t.prototype.initControllerMesh=function(e,n,i){var o,a,s=this;if(i===void 0&&(i=!1),Ut.IsPluginForExtensionAvailable(".glb")){var d="default";if(this.id&&!i){var p=this.id.match(t.GAMEPAD_ID_PATTERN);d=p&&p[0]||d}a=this.hand==="left"?t.MODEL_LEFT_FILENAME:t.MODEL_RIGHT_FILENAME,o=t.MODEL_BASE_URL+d+"/"}else l.a.Warn("You need to reference GLTF loader to load Windows Motion Controllers model. Falling back to generic models"),o=Wo.MODEL_BASE_URL,a=Wo.MODEL_FILENAME;Ut.ImportMesh("",o,a,e,function(b){s._loadedMeshInfo=s.processModel(e,b),s._loadedMeshInfo&&(s._defaultModel=s._loadedMeshInfo.rootNode,s.attachToMesh(s._defaultModel),n&&n(s._defaultModel))},null,function(b,P){l.a.Log(P),l.a.Warn("Failed to retrieve controller model from the remote server: "+o+a),i||s.initControllerMesh(b,n,!0)})},t.prototype.processModel=function(e,n){for(var i=null,o=new De.a(this.id+" "+this.hand,e),a=null,s=0;s<n.length;s++){var d=n[s];if(!d.parent){d.isPickable=!1,a=d;break}}return a?(a.setParent(o),i=this.createMeshInfo(o)):l.a.Warn("Could not find root node in model file."),i},t.prototype.createMeshInfo=function(e){var n,i=new up;for(i.rootNode=e,i.buttonMeshes={},i.axisMeshes={},n=0;n<this._mapping.buttons.length;n++){var o=this._mapping.buttonMeshNames[this._mapping.buttons[n]];if(o){var a=P(e,o);if(a){var s={index:n,value:O(a,"VALUE"),pressed:O(a,"PRESSED"),unpressed:O(a,"UNPRESSED")};s.value&&s.pressed&&s.unpressed?i.buttonMeshes[this._mapping.buttons[n]]=s:l.a.Warn("Missing button submesh under mesh with name: "+o+"(VALUE: "+!!s.value+", PRESSED: "+!!s.pressed+", UNPRESSED:"+!!s.unpressed+")")}else l.a.Warn("Missing button mesh with name: "+o)}else l.a.Log("Skipping unknown button at index: "+n+" with mapped name: "+this._mapping.buttons[n])}for(n=0;n<this._mapping.axisMeshNames.length;n++){var d=this._mapping.axisMeshNames[n];if(d){var p=P(e,d);if(p){var b={index:n,value:O(p,"VALUE"),min:O(p,"MIN"),max:O(p,"MAX")};b.value&&b.min&&b.max?i.axisMeshes[n]=b:l.a.Warn("Missing axis submesh under mesh with name: "+d+"(VALUE: "+!!b.value+", MIN: "+!!b.min+", MAX:"+!!b.max+")")}else l.a.Warn("Missing axis mesh with name: "+d)}else l.a.Log("Skipping unknown axis at index: "+n)}return i.pointingPoseNode=P(e,this._mapping.pointingPoseMeshName),i.pointingPoseNode?this._pointingPoseNode=i.pointingPoseNode:l.a.Warn("Missing pointing pose mesh with name: "+this._mapping.pointingPoseMeshName),i;function P(B,F){return B.getChildren(function(z){return z.name===F},!1)[0]}function O(B,F){return B.getChildren(function(z){return z.name==F},!0)[0]}},t.prototype.getForwardRay=function(e){if(e===void 0&&(e=100),!this._loadedMeshInfo||!this._loadedMeshInfo.pointingPoseNode)return r.prototype.getForwardRay.call(this,e);var n=this._loadedMeshInfo.pointingPoseNode.getWorldMatrix(),i=n.getTranslation(),o=new u.e(0,0,-1),a=u.e.TransformNormal(o,n),s=u.e.Normalize(a);return new fn.a(i,s,e)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onTrackpadChangedObservable.clear(),this.onTrackpadValuesChangedObservable.clear()},t.MODEL_BASE_URL="https://controllers.babylonjs.com/microsoft/",t.MODEL_LEFT_FILENAME="left.glb",t.MODEL_RIGHT_FILENAME="right.glb",t.GAMEPAD_ID_PREFIX="Spatial Controller (Spatial Interaction Source) ",t.GAMEPAD_ID_PATTERN=/([0-9a-zA-Z]+-[0-9a-zA-Z]+)$/,t}(Bi),hp=function(r){function t(e){var n=r.call(this,e)||this;return n._mapping={buttons:["trigger","grip","trackpad","thumbstick","menu"],buttonMeshNames:{trigger:"SELECT",menu:"MENU",grip:"GRASP",thumbstick:"THUMBSTICK_PRESS",trackpad:"TOUCHPAD_PRESS"},buttonObservableNames:{trigger:"onTriggerStateChangedObservable",menu:"onSecondaryButtonStateChangedObservable",grip:"onMainButtonStateChangedObservable",thumbstick:"onThumbstickStateChangedObservable",trackpad:"onTrackpadChangedObservable"},axisMeshNames:["TOUCHPAD_TOUCH_X","TOUCHPAD_TOUCH_Y","THUMBSTICK_X","THUMBSTICK_Y"],pointingPoseMeshName:pr.POINTING_POSE},n.thumbstickValues={x:0,y:0},n.onThumbstickStateChangedObservable=new x.c,n.onThumbstickValuesChangedObservable=new x.c,n.onTrackpadChangedObservable=n.onPadStateChangedObservable,n.onTrackpadValuesChangedObservable=n.onPadValuesChangedObservable,n}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"onThumbstickButtonStateChangedObservable",{get:function(){return this.onThumbstickStateChangedObservable},enumerable:!1,configurable:!0}),t.prototype._updateTrackpad=function(){!this.browserGamepad.axes||this.browserGamepad.axes[2]==this.thumbstickValues.x&&this.browserGamepad.axes[3]==this.thumbstickValues.y||(this.trackpad.x=this.browserGamepad.axes[2],this.trackpad.y=this.browserGamepad.axes[3],this.onThumbstickValuesChangedObservable.notifyObservers(this.trackpad))},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onThumbstickStateChangedObservable.clear(),this.onThumbstickValuesChangedObservable.clear()},t}(Xo);wi._ControllerFactories.push({canCreate:function(r){return r.id.indexOf(Xo.GAMEPAD_ID_PREFIX)===0},create:function(r){return new Xo(r)}});var Yo=f(75),Tr=f(63),wn=f(51),On=f(36),oo=function(r){function t(e,n,i,o,a){var s,d,p,b,P,O,B;n===void 0&&(n=M.a.Gray()),i===void 0&&(i=On.a.DefaultUtilityLayer),o===void 0&&(o=null),a===void 0&&(a=1);var F=r.call(this,i)||this;F._pointerObserver=null,F.snapDistance=0,F.onSnapObservable=new x.c,F.uniformScaling=!1,F.sensitivity=1,F._isEnabled=!0,F._parent=null,F._dragging=!1,F._tmpVector=new u.e,F._tmpMatrix=new u.a,F._tmpMatrix2=new u.a,F._parent=o,F._coloredMaterial=new Ft.a("",i.utilityLayerScene),F._coloredMaterial.diffuseColor=n,F._coloredMaterial.specularColor=n.subtract(new M.a(.1,.1,.1)),F._hoverMaterial=new Ft.a("",i.utilityLayerScene),F._hoverMaterial.diffuseColor=M.a.Yellow(),F._disableMaterial=new Ft.a("",i.utilityLayerScene),F._disableMaterial.diffuseColor=M.a.Gray(),F._disableMaterial.alpha=.4,F._gizmoMesh=new De.a("axis",i.utilityLayerScene);var z=F._createGizmoMesh(F._gizmoMesh,a),J=z.arrowMesh,ie=z.arrowTail,se=F._createGizmoMesh(F._gizmoMesh,a+4,!0);F._gizmoMesh.lookAt(F._rootMesh.position.add(e)),F._rootMesh.addChild(F._gizmoMesh),F._gizmoMesh.scaling.scaleInPlace(1/3);var ce=J.position.clone(),ue=ie.position.clone(),fe=ie.scaling.clone(),ve=function(Ce){var Ne=Ce*(3/F._rootMesh.scaling.length())*6;J.position.z+=Ne/3.5,ie.scaling.y+=Ne,ie.position.z=J.position.z/2},Te=function(){J.position.set(ce.x,ce.y,ce.z),ie.position.set(ue.x,ue.y,ue.z),ie.scaling.set(fe.x,fe.y,fe.z),F._dragging=!1};F.dragBehavior=new yi.a({dragAxis:e}),F.dragBehavior.moveAttached=!1,F._rootMesh.addBehavior(F.dragBehavior);var Re=0,Ae=new u.e,Ee={snapDistance:0};F.dragBehavior.onDragObservable.add(function(Ce){if(F.attachedNode){var Ne=F.sensitivity*Ce.dragDistance*(3*F.scaleRatio/F._rootMesh.scaling.length()),Ie=!1,Fe=0;F.uniformScaling?(F.attachedNode.getWorldMatrix().decompose(Ae),Ae.normalize(),Ae.y<0&&Ae.scaleInPlace(-1)):Ae.copyFrom(e),F.snapDistance==0?Ae.scaleToRef(Ne,Ae):(Re+=Ne,Math.abs(Re)>F.snapDistance?(Fe=Math.floor(Math.abs(Re)/F.snapDistance),Re<0&&(Fe*=-1),Re%=F.snapDistance,Ae.scaleToRef(F.snapDistance*Fe,Ae),Ie=!0):Ae.scaleInPlace(0)),u.a.ScalingToRef(1+Ae.x,1+Ae.y,1+Ae.z,F._tmpMatrix2),F._tmpMatrix2.multiplyToRef(F.attachedNode.getWorldMatrix(),F._tmpMatrix),F._tmpMatrix.decompose(F._tmpVector),Math.abs(F._tmpVector.x)<1e5&&Math.abs(F._tmpVector.y)<1e5&&Math.abs(F._tmpVector.z)<1e5&&F.attachedNode.getWorldMatrix().copyFrom(F._tmpMatrix),Ie&&(Ee.snapDistance=F.snapDistance*Fe,F.onSnapObservable.notifyObservers(Ee)),F._matrixChanged()}}),F.dragBehavior.onDragStartObservable.add(function(){F._dragging=!0}),F.dragBehavior.onDragObservable.add(function(Ce){return ve(Ce.dragDistance)}),F.dragBehavior.onDragEndObservable.add(Te),(p=(d=(s=o?.uniformScaleGizmo)===null||s===void 0?void 0:s.dragBehavior)===null||d===void 0?void 0:d.onDragObservable)===null||p===void 0||p.add(function(Ce){return ve(Ce.delta.y)}),(O=(P=(b=o?.uniformScaleGizmo)===null||b===void 0?void 0:b.dragBehavior)===null||P===void 0?void 0:P.onDragEndObservable)===null||O===void 0||O.add(Te);var Se={gizmoMeshes:[J,ie],colliderMeshes:[se.arrowMesh,se.arrowTail],material:F._coloredMaterial,hoverMaterial:F._hoverMaterial,disableMaterial:F._disableMaterial,active:!1};(B=F._parent)===null||B===void 0||B.addToAxisCache(F._gizmoMesh,Se),F._pointerObserver=i.utilityLayerScene.onPointerObservable.add(function(Ce){var Ne;if(!F._customMeshSet&&(F._isHovered=Se.colliderMeshes.indexOf((Ne=Ce?.pickInfo)===null||Ne===void 0?void 0:Ne.pickedMesh)!=-1,!F._parent)){var Ie=F._isHovered||F._dragging?F._hoverMaterial:F._coloredMaterial;Se.gizmoMeshes.forEach(function(Fe){Fe.material=Ie,Fe.color&&(Fe.color=Ie.diffuseColor)})}});var Le=i._getSharedGizmoLight();return Le.includedOnlyMeshes=Le.includedOnlyMeshes.concat(F._rootMesh.getChildMeshes()),F}return Object(c.d)(t,r),t.prototype._createGizmoMesh=function(e,n,i){i===void 0&&(i=!1);var o=Tr.a.CreateBox("yPosMesh",{size:.4*(1+(n-1)/4)},this.gizmoLayer.utilityLayerScene),a=pi.a.CreateCylinder("cylinder",{diameterTop:.005*n,height:.275,diameterBottom:.005*n,tessellation:96},this.gizmoLayer.utilityLayerScene);return o.scaling.scaleInPlace(.1),o.material=this._coloredMaterial,o.rotation.x=Math.PI/2,o.position.z+=.3,a.material=this._coloredMaterial,a.position.z+=.1375,a.rotation.x=Math.PI/2,i&&(o.visibility=0,a.visibility=0),e.addChild(o),e.addChild(a),{arrowMesh:o,arrowTail:a}},t.prototype._attachedNodeChanged=function(e){this.dragBehavior&&(this.dragBehavior.enabled=!!e)},Object.defineProperty(t.prototype,"isEnabled",{get:function(){return this._isEnabled},set:function(e){this._isEnabled=e,e?this._parent&&(this.attachedMesh=this._parent.attachedMesh,this.attachedNode=this._parent.attachedNode):(this.attachedMesh=null,this.attachedNode=null)},enumerable:!1,configurable:!0}),t.prototype.dispose=function(){this.onSnapObservable.clear(),this.gizmoLayer.utilityLayerScene.onPointerObservable.remove(this._pointerObserver),this.dragBehavior.detach(),this._gizmoMesh&&this._gizmoMesh.dispose(),[this._coloredMaterial,this._hoverMaterial,this._disableMaterial].forEach(function(e){e&&e.dispose()}),r.prototype.dispose.call(this)},t.prototype.setCustomMesh=function(e,n){var i=this;n===void 0&&(n=!1),r.prototype.setCustomMesh.call(this,e),n&&(this._rootMesh.getChildMeshes().forEach(function(o){o.material=i._coloredMaterial,o.color&&(o.color=i._coloredMaterial.diffuseColor)}),this._customMeshSet=!1)},t}(wn.a),Fn=f(45),cn=f(40),lu=function(r){function t(e,n){e===void 0&&(e=M.a.Gray()),n===void 0&&(n=On.a.DefaultKeepDepthUtilityLayer);var i=r.call(this,n)||this;i._boundingDimensions=new u.e(1,1,1),i._renderObserver=null,i._pointerObserver=null,i._scaleDragSpeed=.2,i._tmpQuaternion=new u.b,i._tmpVector=new u.e(0,0,0),i._tmpRotationMatrix=new u.a,i.ignoreChildren=!1,i.includeChildPredicate=null,i.rotationSphereSize=.1,i.scaleBoxSize=.1,i.fixedDragMeshScreenSize=!1,i.fixedDragMeshBoundsSize=!1,i.fixedDragMeshScreenSizeDistanceFactor=10,i.onDragStartObservable=new x.c,i.onScaleBoxDragObservable=new x.c,i.onScaleBoxDragEndObservable=new x.c,i.onRotationSphereDragObservable=new x.c,i.onRotationSphereDragEndObservable=new x.c,i.scalePivot=null,i._existingMeshScale=new u.e,i._dragMesh=null,i.pointerDragBehavior=new yi.a,i.updateScale=!1,i._anchorMesh=new Dt.a("anchor",n.utilityLayerScene),i.coloredMaterial=new Ft.a("",n.utilityLayerScene),i.coloredMaterial.disableLighting=!0,i.hoverColoredMaterial=new Ft.a("",n.utilityLayerScene),i.hoverColoredMaterial.disableLighting=!0,i._lineBoundingBox=new Dt.a("",n.utilityLayerScene),i._lineBoundingBox.rotationQuaternion=new u.b;var o=[];o.push(cn.a.CreateLines("lines",{points:[new u.e(0,0,0),new u.e(i._boundingDimensions.x,0,0)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(0,0,0),new u.e(0,i._boundingDimensions.y,0)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(0,0,0),new u.e(0,0,i._boundingDimensions.z)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(i._boundingDimensions.x,0,0),new u.e(i._boundingDimensions.x,i._boundingDimensions.y,0)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(i._boundingDimensions.x,0,0),new u.e(i._boundingDimensions.x,0,i._boundingDimensions.z)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(0,i._boundingDimensions.y,0),new u.e(i._boundingDimensions.x,i._boundingDimensions.y,0)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(0,i._boundingDimensions.y,0),new u.e(0,i._boundingDimensions.y,i._boundingDimensions.z)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(0,0,i._boundingDimensions.z),new u.e(i._boundingDimensions.x,0,i._boundingDimensions.z)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(0,0,i._boundingDimensions.z),new u.e(0,i._boundingDimensions.y,i._boundingDimensions.z)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(i._boundingDimensions.x,i._boundingDimensions.y,i._boundingDimensions.z),new u.e(0,i._boundingDimensions.y,i._boundingDimensions.z)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(i._boundingDimensions.x,i._boundingDimensions.y,i._boundingDimensions.z),new u.e(i._boundingDimensions.x,0,i._boundingDimensions.z)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(i._boundingDimensions.x,i._boundingDimensions.y,i._boundingDimensions.z),new u.e(i._boundingDimensions.x,i._boundingDimensions.y,0)]},n.utilityLayerScene)),o.forEach(function(J){J.color=e,J.position.addInPlace(new u.e(-i._boundingDimensions.x/2,-i._boundingDimensions.y/2,-i._boundingDimensions.z/2)),J.isPickable=!1,i._lineBoundingBox.addChild(J)}),i._rootMesh.addChild(i._lineBoundingBox),i.setColor(e),i._rotateSpheresParent=new Dt.a("",n.utilityLayerScene),i._rotateSpheresParent.rotationQuaternion=new u.b;for(var a=function(J){var ie=Fn.a.CreateSphere("",{diameter:1},n.utilityLayerScene);ie.rotationQuaternion=new u.b,ie.material=s.coloredMaterial,(P=new yi.a({})).moveAttached=!1,P.updateDragPlane=!1,ie.addBehavior(P);var se=new u.e(1,0,0),ce=0;P.onDragStartObservable.add(function(){se.copyFrom(ie.forward),ce=0}),P.onDragObservable.add(function(ue){if(i.onRotationSphereDragObservable.notifyObservers({}),i.attachedMesh){var fe=i.attachedMesh.parent;if(fe&&fe.scaling&&fe.scaling.isNonUniformWithinEpsilon(.001))return void l.a.Warn("BoundingBoxGizmo controls are not supported on child meshes with non-uniform parent scaling");kn.a._RemoveAndStorePivotPoint(i.attachedMesh);var ve=se,Te=ue.dragPlaneNormal.scale(u.e.Dot(ue.dragPlaneNormal,ve)),Re=ve.subtract(Te).normalizeToNew(),Ae=u.e.Dot(Re,ue.delta)<0?Math.abs(ue.delta.length()):-Math.abs(ue.delta.length());Ae=Ae/i._boundingDimensions.length()*i._anchorMesh.scaling.length(),i.attachedMesh.rotationQuaternion||(i.attachedMesh.rotationQuaternion=u.b.RotationYawPitchRoll(i.attachedMesh.rotation.y,i.attachedMesh.rotation.x,i.attachedMesh.rotation.z)),i._anchorMesh.rotationQuaternion||(i._anchorMesh.rotationQuaternion=u.b.RotationYawPitchRoll(i._anchorMesh.rotation.y,i._anchorMesh.rotation.x,i._anchorMesh.rotation.z)),ce+=Ae,Math.abs(ce)<=2*Math.PI&&(J>=8?u.b.RotationYawPitchRollToRef(0,0,Ae,i._tmpQuaternion):J>=4?u.b.RotationYawPitchRollToRef(Ae,0,0,i._tmpQuaternion):u.b.RotationYawPitchRollToRef(0,Ae,0,i._tmpQuaternion),i._anchorMesh.addChild(i.attachedMesh),i._anchorMesh.rotationQuaternion.multiplyToRef(i._tmpQuaternion,i._anchorMesh.rotationQuaternion),i._anchorMesh.removeChild(i.attachedMesh),i.attachedMesh.setParent(fe)),i.updateBoundingBox(),kn.a._RestorePivotPoint(i.attachedMesh)}i._updateDummy()}),P.onDragStartObservable.add(function(){i.onDragStartObservable.notifyObservers({}),i._selectNode(ie)}),P.onDragEndObservable.add(function(){i.onRotationSphereDragEndObservable.notifyObservers({}),i._selectNode(null),i._updateDummy()}),s._rotateSpheresParent.addChild(ie)},s=this,d=0;d<12;d++)a(d);i._rootMesh.addChild(i._rotateSpheresParent),i._scaleBoxesParent=new Dt.a("",n.utilityLayerScene),i._scaleBoxesParent.rotationQuaternion=new u.b;for(var p=0;p<3;p++)for(var b=0;b<3;b++)for(var P,O=function(){var J=(p===1?1:0)+(b===1?1:0)+(F===1?1:0);if(J===1||J===3)return"continue";var ie=Tr.a.CreateBox("",{size:1},n.utilityLayerScene);ie.material=B.coloredMaterial,ie.metadata=J===2;var se=new u.e(p-1,b-1,F-1).normalize();(P=new yi.a({dragAxis:se})).updateDragPlane=!1,P.moveAttached=!1,ie.addBehavior(P),P.onDragObservable.add(function(ce){if(i.onScaleBoxDragObservable.notifyObservers({}),i.attachedMesh){var ue=i.attachedMesh.parent;if(ue&&ue.scaling&&ue.scaling.isNonUniformWithinEpsilon(.001))return void l.a.Warn("BoundingBoxGizmo controls are not supported on child meshes with non-uniform parent scaling");kn.a._RemoveAndStorePivotPoint(i.attachedMesh);var fe=ce.dragDistance/i._boundingDimensions.length()*i._anchorMesh.scaling.length(),ve=new u.e(fe,fe,fe);J===2&&(ve.x*=Math.abs(se.x),ve.y*=Math.abs(se.y),ve.z*=Math.abs(se.z)),ve.scaleInPlace(i._scaleDragSpeed),i.updateBoundingBox(),i.scalePivot?(i.attachedMesh.getWorldMatrix().getRotationMatrixToRef(i._tmpRotationMatrix),i._boundingDimensions.scaleToRef(.5,i._tmpVector),u.e.TransformCoordinatesToRef(i._tmpVector,i._tmpRotationMatrix,i._tmpVector),i._anchorMesh.position.subtractInPlace(i._tmpVector),i._boundingDimensions.multiplyToRef(i.scalePivot,i._tmpVector),u.e.TransformCoordinatesToRef(i._tmpVector,i._tmpRotationMatrix,i._tmpVector),i._anchorMesh.position.addInPlace(i._tmpVector)):(ie.absolutePosition.subtractToRef(i._anchorMesh.position,i._tmpVector),i._anchorMesh.position.subtractInPlace(i._tmpVector)),i._anchorMesh.addChild(i.attachedMesh),i._anchorMesh.scaling.addInPlace(ve),(i._anchorMesh.scaling.x<0||i._anchorMesh.scaling.y<0||i._anchorMesh.scaling.z<0)&&i._anchorMesh.scaling.subtractInPlace(ve),i._anchorMesh.removeChild(i.attachedMesh),i.attachedMesh.setParent(ue),kn.a._RestorePivotPoint(i.attachedMesh)}i._updateDummy()}),P.onDragStartObservable.add(function(){i.onDragStartObservable.notifyObservers({}),i._selectNode(ie)}),P.onDragEndObservable.add(function(){i.onScaleBoxDragEndObservable.notifyObservers({}),i._selectNode(null),i._updateDummy()}),B._scaleBoxesParent.addChild(ie)},B=this,F=0;F<3;F++)O();i._rootMesh.addChild(i._scaleBoxesParent);var z=new Array;return i._pointerObserver=n.utilityLayerScene.onPointerObservable.add(function(J){z[J.event.pointerId]?J.pickInfo&&J.pickInfo.pickedMesh!=z[J.event.pointerId]&&(z[J.event.pointerId].material=i.coloredMaterial,delete z[J.event.pointerId]):i._rotateSpheresParent.getChildMeshes().concat(i._scaleBoxesParent.getChildMeshes()).forEach(function(ie){J.pickInfo&&J.pickInfo.pickedMesh==ie&&(z[J.event.pointerId]=ie,ie.material=i.hoverColoredMaterial)})}),i._renderObserver=i.gizmoLayer.originalScene.onBeforeRenderObservable.add(function(){i.attachedMesh&&!i._existingMeshScale.equals(i.attachedMesh.scaling)?i.updateBoundingBox():(i.fixedDragMeshScreenSize||i.fixedDragMeshBoundsSize)&&(i._updateRotationSpheres(),i._updateScaleBoxes()),i._dragMesh&&i.attachedMesh&&i.pointerDragBehavior.dragging&&(i._lineBoundingBox.position.rotateByQuaternionToRef(i._rootMesh.rotationQuaternion,i._tmpVector),i.attachedMesh.setAbsolutePosition(i._dragMesh.position.add(i._tmpVector.scale(-1))))}),i.updateBoundingBox(),i}return Object(c.d)(t,r),t.prototype.setColor=function(e){this.coloredMaterial.emissiveColor=e,this.hoverColoredMaterial.emissiveColor=e.clone().add(new M.a(.3,.3,.3)),this._lineBoundingBox.getChildren().forEach(function(n){n.color&&(n.color=e)})},t.prototype._attachedNodeChanged=function(e){var n=this;if(e){kn.a._RemoveAndStorePivotPoint(e);var i=e.parent;this._anchorMesh.addChild(e),this._anchorMesh.removeChild(e),e.setParent(i),kn.a._RestorePivotPoint(e),this.updateBoundingBox(),e.getChildMeshes(!1).forEach(function(o){o.markAsDirty("scaling")}),this.gizmoLayer.utilityLayerScene.onAfterRenderObservable.addOnce(function(){n._updateDummy()})}},t.prototype._selectNode=function(e){this._rotateSpheresParent.getChildMeshes().concat(this._scaleBoxesParent.getChildMeshes()).forEach(function(n){n.isVisible=!e||n==e})},t.prototype.updateBoundingBox=function(){if(this.attachedMesh){kn.a._RemoveAndStorePivotPoint(this.attachedMesh);var e=this.attachedMesh.parent;this.attachedMesh.setParent(null);var n=null;this.attachedMesh.skeleton&&(n=this.attachedMesh.skeleton.overrideMesh,this.attachedMesh.skeleton.overrideMesh=null),this._update(),this.attachedMesh.rotationQuaternion||(this.attachedMesh.rotationQuaternion=u.b.RotationYawPitchRoll(this.attachedMesh.rotation.y,this.attachedMesh.rotation.x,this.attachedMesh.rotation.z)),this._anchorMesh.rotationQuaternion||(this._anchorMesh.rotationQuaternion=u.b.RotationYawPitchRoll(this._anchorMesh.rotation.y,this._anchorMesh.rotation.x,this._anchorMesh.rotation.z)),this._anchorMesh.rotationQuaternion.copyFrom(this.attachedMesh.rotationQuaternion),this._tmpQuaternion.copyFrom(this.attachedMesh.rotationQuaternion),this._tmpVector.copyFrom(this.attachedMesh.position),this.attachedMesh.rotationQuaternion.set(0,0,0,1),this.attachedMesh.position.set(0,0,0);var i=this.attachedMesh.getHierarchyBoundingVectors(!this.ignoreChildren,this.includeChildPredicate);i.max.subtractToRef(i.min,this._boundingDimensions),this._lineBoundingBox.scaling.copyFrom(this._boundingDimensions),this._lineBoundingBox.position.set((i.max.x+i.min.x)/2,(i.max.y+i.min.y)/2,(i.max.z+i.min.z)/2),this._rotateSpheresParent.position.copyFrom(this._lineBoundingBox.position),this._scaleBoxesParent.position.copyFrom(this._lineBoundingBox.position),this._lineBoundingBox.computeWorldMatrix(),this._anchorMesh.position.copyFrom(this._lineBoundingBox.absolutePosition),this.attachedMesh.rotationQuaternion.copyFrom(this._tmpQuaternion),this.attachedMesh.position.copyFrom(this._tmpVector),this.attachedMesh.setParent(e),this.attachedMesh.skeleton&&(this.attachedMesh.skeleton.overrideMesh=n)}this._updateRotationSpheres(),this._updateScaleBoxes(),this.attachedMesh&&(this._existingMeshScale.copyFrom(this.attachedMesh.scaling),kn.a._RestorePivotPoint(this.attachedMesh))},t.prototype._updateRotationSpheres=function(){for(var e=this._rotateSpheresParent.getChildMeshes(),n=0;n<3;n++)for(var i=0;i<2;i++)for(var o=0;o<2;o++){var a=4*n+2*i+o;if(n==0&&(e[a].position.set(this._boundingDimensions.x/2,this._boundingDimensions.y*i,this._boundingDimensions.z*o),e[a].position.addInPlace(new u.e(-this._boundingDimensions.x/2,-this._boundingDimensions.y/2,-this._boundingDimensions.z/2)),e[a].lookAt(u.e.Cross(e[a].position.normalizeToNew(),u.e.Right()).normalizeToNew().add(e[a].position))),n==1&&(e[a].position.set(this._boundingDimensions.x*i,this._boundingDimensions.y/2,this._boundingDimensions.z*o),e[a].position.addInPlace(new u.e(-this._boundingDimensions.x/2,-this._boundingDimensions.y/2,-this._boundingDimensions.z/2)),e[a].lookAt(u.e.Cross(e[a].position.normalizeToNew(),u.e.Up()).normalizeToNew().add(e[a].position))),n==2&&(e[a].position.set(this._boundingDimensions.x*i,this._boundingDimensions.y*o,this._boundingDimensions.z/2),e[a].position.addInPlace(new u.e(-this._boundingDimensions.x/2,-this._boundingDimensions.y/2,-this._boundingDimensions.z/2)),e[a].lookAt(u.e.Cross(e[a].position.normalizeToNew(),u.e.Forward()).normalizeToNew().add(e[a].position))),this.fixedDragMeshScreenSize&&this.gizmoLayer.utilityLayerScene.activeCamera){e[a].absolutePosition.subtractToRef(this.gizmoLayer.utilityLayerScene.activeCamera.position,this._tmpVector);var s=this.rotationSphereSize*this._tmpVector.length()/this.fixedDragMeshScreenSizeDistanceFactor;e[a].scaling.set(s,s,s)}else this.fixedDragMeshBoundsSize?e[a].scaling.set(this.rotationSphereSize*this._boundingDimensions.x,this.rotationSphereSize*this._boundingDimensions.y,this.rotationSphereSize*this._boundingDimensions.z):e[a].scaling.set(this.rotationSphereSize,this.rotationSphereSize,this.rotationSphereSize)}},t.prototype._updateScaleBoxes=function(){for(var e=this._scaleBoxesParent.getChildMeshes(),n=0,i=0;i<3;i++)for(var o=0;o<3;o++)for(var a=0;a<3;a++){var s=(i===1?1:0)+(o===1?1:0)+(a===1?1:0);if(s!==1&&s!==3){if(e[n])if(e[n].position.set(this._boundingDimensions.x*(i/2),this._boundingDimensions.y*(o/2),this._boundingDimensions.z*(a/2)),e[n].position.addInPlace(new u.e(-this._boundingDimensions.x/2,-this._boundingDimensions.y/2,-this._boundingDimensions.z/2)),this.fixedDragMeshScreenSize&&this.gizmoLayer.utilityLayerScene.activeCamera){e[n].absolutePosition.subtractToRef(this.gizmoLayer.utilityLayerScene.activeCamera.position,this._tmpVector);var d=this.scaleBoxSize*this._tmpVector.length()/this.fixedDragMeshScreenSizeDistanceFactor;e[n].scaling.set(d,d,d)}else this.fixedDragMeshBoundsSize?e[n].scaling.set(this.scaleBoxSize*this._boundingDimensions.x,this.scaleBoxSize*this._boundingDimensions.y,this.scaleBoxSize*this._boundingDimensions.z):e[n].scaling.set(this.scaleBoxSize,this.scaleBoxSize,this.scaleBoxSize);n++}}},t.prototype.setEnabledRotationAxis=function(e){this._rotateSpheresParent.getChildMeshes().forEach(function(n,i){i<4?n.setEnabled(e.indexOf("x")!=-1):i<8?n.setEnabled(e.indexOf("y")!=-1):n.setEnabled(e.indexOf("z")!=-1)})},t.prototype.setEnabledScaling=function(e,n){n===void 0&&(n=!1),this._scaleBoxesParent.getChildMeshes().forEach(function(i,o){var a=e;n&&i.metadata===!0&&(a=!1),i.setEnabled(a)})},t.prototype._updateDummy=function(){this._dragMesh&&(this._dragMesh.position.copyFrom(this._lineBoundingBox.getAbsolutePosition()),this._dragMesh.scaling.copyFrom(this._lineBoundingBox.scaling),this._dragMesh.rotationQuaternion.copyFrom(this._rootMesh.rotationQuaternion))},t.prototype.enableDragBehavior=function(){this._dragMesh=De.a.CreateBox("dummy",1,this.gizmoLayer.utilityLayerScene),this._dragMesh.visibility=0,this._dragMesh.rotationQuaternion=new u.b,this.pointerDragBehavior.useObjectOrientationForDragging=!1,this._dragMesh.addBehavior(this.pointerDragBehavior)},t.prototype.dispose=function(){this.gizmoLayer.utilityLayerScene.onPointerObservable.remove(this._pointerObserver),this.gizmoLayer.originalScene.onBeforeRenderObservable.remove(this._renderObserver),this._lineBoundingBox.dispose(),this._rotateSpheresParent.dispose(),this._scaleBoxesParent.dispose(),this._dragMesh&&this._dragMesh.dispose(),r.prototype.dispose.call(this)},t.MakeNotPickableAndWrapInBoundingBox=function(e){var n=function(d){d.isPickable=!1,d.getChildMeshes().forEach(function(p){n(p)})};n(e),e.rotationQuaternion||(e.rotationQuaternion=u.b.RotationYawPitchRoll(e.rotation.y,e.rotation.x,e.rotation.z));var i=e.position.clone(),o=e.rotationQuaternion.clone();e.rotationQuaternion.set(0,0,0,1),e.position.set(0,0,0);var a=Tr.a.CreateBox("box",{size:1},e.getScene()),s=e.getHierarchyBoundingVectors();return s.max.subtractToRef(s.min,a.scaling),a.scaling.y===0&&(a.scaling.y=Gt.a),a.scaling.x===0&&(a.scaling.x=Gt.a),a.scaling.z===0&&(a.scaling.z=Gt.a),a.position.set((s.max.x+s.min.x)/2,(s.max.y+s.min.y)/2,(s.max.z+s.min.z)/2),e.addChild(a),e.rotationQuaternion.copyFrom(o),e.position.copyFrom(i),e.removeChild(a),a.addChild(e),a.visibility=0,a},t.prototype.setCustomMesh=function(e){l.a.Error("Custom meshes are not supported on this gizmo")},t}(wn.a),Ko=function(r){function t(e,n,i,o,a,s,d){var p;n===void 0&&(n=M.a.Gray()),i===void 0&&(i=On.a.DefaultUtilityLayer),o===void 0&&(o=32),a===void 0&&(a=null),d===void 0&&(d=1);var b=r.call(this,i)||this;b._pointerObserver=null,b.snapDistance=0,b.onSnapObservable=new x.c,b._isEnabled=!0,b._parent=null,b._dragging=!1,b._parent=a,b._coloredMaterial=new Ft.a("",i.utilityLayerScene),b._coloredMaterial.diffuseColor=n,b._coloredMaterial.specularColor=n.subtract(new M.a(.1,.1,.1)),b._hoverMaterial=new Ft.a("",i.utilityLayerScene),b._hoverMaterial.diffuseColor=M.a.Yellow(),b._disableMaterial=new Ft.a("",i.utilityLayerScene),b._disableMaterial.diffuseColor=M.a.Gray(),b._disableMaterial.alpha=.4,b._gizmoMesh=new De.a("",i.utilityLayerScene);var P=b._createGizmoMesh(b._gizmoMesh,d,o),O=P.rotationMesh,B=P.collider,F=[];b._rotationCircle=b.setupRotationCircle(F,b._gizmoMesh),b._gizmoMesh.lookAt(b._rootMesh.position.add(e)),b._rootMesh.addChild(b._gizmoMesh),b._gizmoMesh.scaling.scaleInPlace(1/3),b.dragBehavior=new yi.a({dragPlaneNormal:e}),b.dragBehavior.moveAttached=!1,b.dragBehavior.maxDragAngle=9*Math.PI/20,b.dragBehavior._useAlternatePickedPointAboveMaxDragAngle=!0,b._rootMesh.addBehavior(b.dragBehavior);var z=0,J=new u.e,ie=new u.e,se=new u.a,ce=new u.e,ue=new u.e;b.dragBehavior.onDragStartObservable.add(function(Se){if(b.attachedNode){J.copyFrom(Se.dragPlanePoint);var Le=new u.e(0,0,1),Ce=b._rotationCircle.getDirection(Le);Ce.normalize(),b._gizmoMesh.removeChild(b._rotationCircle),J.copyFrom(Se.dragPlanePoint),ie=Se.dragPlanePoint;var Ne=b._rotationCircle.getAbsolutePosition().clone(),Ie=b._rotationCircle.getAbsolutePosition().clone().addInPlace(Ce),Fe=Se.dragPlanePoint,Ye=u.e.GetAngleBetweenVectors(Ie.subtract(Ne),Fe.subtract(Ne),b._rotationCircle.up);b._rotationCircle.addRotation(0,Ye,0),b._dragging=!0}}),b.dragBehavior.onDragEndObservable.add(function(){z=0,b.updateRotationCircle(b._rotationCircle,F,z,ie),b._gizmoMesh.addChild(b._rotationCircle),b._dragging=!1});var fe={snapDistance:0},ve=0,Te=new u.a,Re=new u.b;b.dragBehavior.onDragObservable.add(function(Se){if(b.attachedNode){var Le=new u.e(1,1,1),Ce=new u.b(0,0,0,1),Ne=new u.e(0,0,0);b.attachedNode.getWorldMatrix().decompose(Le,Ce,Ne);var Ie=Se.dragPlanePoint.subtract(Ne).normalize(),Fe=J.subtract(Ne).normalize(),Ye=u.e.Cross(Ie,Fe),tt=u.e.Dot(Ie,Fe),it=Math.atan2(Ye.length(),tt);ce.copyFrom(e),ue.copyFrom(e),b.updateGizmoRotationToMatchAttachedMesh&&(Ce.toRotationMatrix(se),ue=u.e.TransformCoordinates(ce,se));var lt=!1;if(i.utilityLayerScene.activeCamera){var Qe=i.utilityLayerScene.activeCamera.position.subtract(Ne);u.e.Dot(Qe,ue)>0&&(ce.scaleInPlace(-1),ue.scaleInPlace(-1),lt=!0)}u.e.Dot(ue,Ye)>0&&(it=-it);var ot=!1;if(b.snapDistance!=0)if(ve+=it,Math.abs(ve)>b.snapDistance){var rt=Math.floor(Math.abs(ve)/b.snapDistance);ve<0&&(rt*=-1),ve%=b.snapDistance,it=b.snapDistance*rt,ot=!0}else it=0;z+=lt?-it:it,b.updateRotationCircle(b._rotationCircle,F,z,ie);var Ze=Math.sin(it/2);if(Re.set(ce.x*Ze,ce.y*Ze,ce.z*Ze,Math.cos(it/2)),Te.determinant()>0){var dt=new u.e;Re.toEulerAnglesToRef(dt),u.b.RotationYawPitchRollToRef(dt.y,-dt.x,-dt.z,Re)}b.updateGizmoRotationToMatchAttachedMesh?Ce.multiplyToRef(Re,Ce):Re.multiplyToRef(Ce,Ce),b.attachedNode.getWorldMatrix().copyFrom(u.a.Compose(Le,Ce,Ne)),J.copyFrom(Se.dragPlanePoint),ot&&(fe.snapDistance=it,b.onSnapObservable.notifyObservers(fe)),b._matrixChanged()}});var Ae=i._getSharedGizmoLight();Ae.includedOnlyMeshes=Ae.includedOnlyMeshes.concat(b._rootMesh.getChildMeshes(!1));var Ee={colliderMeshes:[B],gizmoMeshes:[O],material:b._coloredMaterial,hoverMaterial:b._hoverMaterial,disableMaterial:b._disableMaterial,active:!1};return(p=b._parent)===null||p===void 0||p.addToAxisCache(b._gizmoMesh,Ee),b._pointerObserver=i.utilityLayerScene.onPointerObservable.add(function(Se){var Le;if(!b._customMeshSet&&(b._isHovered=Ee.colliderMeshes.indexOf((Le=Se?.pickInfo)===null||Le===void 0?void 0:Le.pickedMesh)!=-1,!b._parent)){var Ce=b._isHovered||b._dragging?b._hoverMaterial:b._coloredMaterial;Ee.gizmoMeshes.forEach(function(Ne){Ne.material=Ce,Ne.color&&(Ne.color=Ce.diffuseColor)})}}),b}return Object(c.d)(t,r),t.prototype._createGizmoMesh=function(e,n,i){var o=De.a.CreateTorus("ignore",.6,.03*n,i,this.gizmoLayer.utilityLayerScene);o.visibility=0;var a=De.a.CreateTorus("",.6,.005*n,i,this.gizmoLayer.utilityLayerScene);return a.material=this._coloredMaterial,a.rotation.x=Math.PI/2,o.rotation.x=Math.PI/2,e.addChild(a),e.addChild(o),{rotationMesh:a,collider:o}},t.prototype._attachedNodeChanged=function(e){this.dragBehavior&&(this.dragBehavior.enabled=!!e)},t.prototype.setupRotationCircle=function(e,n){for(var i=t._CircleConstants.pi2/t._CircleConstants.tessellation,o=-Math.PI/2;o<Math.PI/2-1.5;o+=i/2){for(var a=[],s=0;s<t._CircleConstants.pi2*t._CircleConstants.rotationCircleRange+.01;s+=i)if(s<0){var d=t._CircleConstants.radius*Math.sin(s)*Math.cos(o),p=t._CircleConstants.radius*Math.cos(s)*Math.cos(o);a.push(new u.e(d,0,p))}else a.push(new u.e(0,0,0));e.push(a)}var b=new Ft.a("",this.gizmoLayer.utilityLayerScene);b.diffuseColor=M.a.Yellow(),b.backFaceCulling=!1;var P=De.a.CreateRibbon("rotationCircle",e,!1,!1,0,this.gizmoLayer.utilityLayerScene,!0);return P.material=b,P.material.alpha=.25,P.rotation.x=Math.PI/2,n.addChild(P),P},t.prototype.updateRotationPath=function(e,n){for(var i=t._CircleConstants.pi2/t._CircleConstants.tessellation,o=0,a=-Math.PI/2;a<Math.PI/2-1.5;a+=i/2){var s=e[o];if(s)for(var d=0,p=0;p<t._CircleConstants.pi2*t._CircleConstants.rotationCircleRange+.01;p+=i){if(s[d])if(p<Math.abs(n)){var b=n>0?p:-1*p,P=n>0?a:-1*a;s[d].set(t._CircleConstants.radius*Math.sin(b)*Math.cos(P),0,t._CircleConstants.radius*Math.cos(b)*Math.cos(P))}else s[d].set(0,0,0);d++}o++}},t.prototype.updateRotationCircle=function(e,n,i,o){this.updateRotationPath(n,i),De.a.CreateRibbon("rotationCircle",n,!1,!1,0,this.gizmoLayer.utilityLayerScene,void 0,void 0,e.geometry?e:void 0)},Object.defineProperty(t.prototype,"isEnabled",{get:function(){return this._isEnabled},set:function(e){this._isEnabled=e,e?this._parent&&(this.attachedMesh=this._parent.attachedMesh):this.attachedMesh=null},enumerable:!1,configurable:!0}),t.prototype.dispose=function(){this.onSnapObservable.clear(),this.gizmoLayer.utilityLayerScene.onPointerObservable.remove(this._pointerObserver),this.dragBehavior.detach(),this._gizmoMesh&&this._gizmoMesh.dispose(),this._rotationCircle&&this._rotationCircle.dispose(),[this._coloredMaterial,this._hoverMaterial,this._disableMaterial].forEach(function(e){e&&e.dispose()}),r.prototype.dispose.call(this)},t._CircleConstants={radius:.3,pi2:2*Math.PI,tessellation:70,rotationCircleRange:4},t}(wn.a),uu=function(r){function t(e,n,i,o,a){e===void 0&&(e=On.a.DefaultUtilityLayer),n===void 0&&(n=32),i===void 0&&(i=!1),o===void 0&&(o=1);var s=r.call(this,e)||this;return s.onDragStartObservable=new x.c,s.onDragEndObservable=new x.c,s._observables=[],s._gizmoAxisCache=new Map,s.xGizmo=new Ko(new u.e(1,0,0),M.a.Red().scale(.5),e,n,s,i,o),s.yGizmo=new Ko(new u.e(0,1,0),M.a.Green().scale(.5),e,n,s,i,o),s.zGizmo=new Ko(new u.e(0,0,1),M.a.Blue().scale(.5),e,n,s,i,o),[s.xGizmo,s.yGizmo,s.zGizmo].forEach(function(d){d.dragBehavior.onDragStartObservable.add(function(){s.onDragStartObservable.notifyObservers({})}),d.dragBehavior.onDragEndObservable.add(function(){s.onDragEndObservable.notifyObservers({})})}),s.attachedMesh=null,s.attachedNode=null,a?a.addToAxisCache(s._gizmoAxisCache):wn.a.GizmoAxisPointerObserver(e,s._gizmoAxisCache),s}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"attachedMesh",{get:function(){return this._meshAttached},set:function(e){this._meshAttached=e,this._nodeAttached=e,this._checkBillboardTransform(),[this.xGizmo,this.yGizmo,this.zGizmo].forEach(function(n){n.isEnabled?n.attachedMesh=e:n.attachedMesh=null})},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"attachedNode",{get:function(){return this._nodeAttached},set:function(e){this._meshAttached=null,this._nodeAttached=e,this._checkBillboardTransform(),[this.xGizmo,this.yGizmo,this.zGizmo].forEach(function(n){n.isEnabled?n.attachedNode=e:n.attachedNode=null})},enumerable:!1,configurable:!0}),t.prototype._checkBillboardTransform=function(){this._nodeAttached&&this._nodeAttached.billboardMode&&console.log("Rotation Gizmo will not work with transforms in billboard mode.")},Object.defineProperty(t.prototype,"isHovered",{get:function(){var e=!1;return[this.xGizmo,this.yGizmo,this.zGizmo].forEach(function(n){e=e||n.isHovered}),e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"updateGizmoRotationToMatchAttachedMesh",{get:function(){return this.xGizmo.updateGizmoRotationToMatchAttachedMesh},set:function(e){this.xGizmo&&(this.xGizmo.updateGizmoRotationToMatchAttachedMesh=e,this.yGizmo.updateGizmoRotationToMatchAttachedMesh=e,this.zGizmo.updateGizmoRotationToMatchAttachedMesh=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"snapDistance",{get:function(){return this.xGizmo.snapDistance},set:function(e){this.xGizmo&&(this.xGizmo.snapDistance=e,this.yGizmo.snapDistance=e,this.zGizmo.snapDistance=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"scaleRatio",{get:function(){return this.xGizmo.scaleRatio},set:function(e){this.xGizmo&&(this.xGizmo.scaleRatio=e,this.yGizmo.scaleRatio=e,this.zGizmo.scaleRatio=e)},enumerable:!1,configurable:!0}),t.prototype.addToAxisCache=function(e,n){this._gizmoAxisCache.set(e,n)},t.prototype.dispose=function(){var e=this;this.xGizmo.dispose(),this.yGizmo.dispose(),this.zGizmo.dispose(),this.onDragStartObservable.clear(),this.onDragEndObservable.clear(),this._observables.forEach(function(n){e.gizmoLayer.utilityLayerScene.onPointerObservable.remove(n)})},t.prototype.setCustomMesh=function(e){l.a.Error("Custom meshes are not supported on this gizmo, please set the custom meshes on the gizmos contained within this one (gizmo.xGizmo, gizmo.yGizmo, gizmo.zGizmo)")},t}(wn.a),Er=f(46),Rs=f(84),Qo=function(r){function t(e,n,i,o){var a;n===void 0&&(n=M.a.Gray()),i===void 0&&(i=On.a.DefaultUtilityLayer),o===void 0&&(o=null);var s=r.call(this,i)||this;s._pointerObserver=null,s.snapDistance=0,s.onSnapObservable=new x.c,s._isEnabled=!1,s._parent=null,s._dragging=!1,s._parent=o,s._coloredMaterial=new Ft.a("",i.utilityLayerScene),s._coloredMaterial.diffuseColor=n,s._coloredMaterial.specularColor=n.subtract(new M.a(.1,.1,.1)),s._hoverMaterial=new Ft.a("",i.utilityLayerScene),s._hoverMaterial.diffuseColor=M.a.Yellow(),s._disableMaterial=new Ft.a("",i.utilityLayerScene),s._disableMaterial.diffuseColor=M.a.Gray(),s._disableMaterial.alpha=.4,s._gizmoMesh=t._CreatePlane(i.utilityLayerScene,s._coloredMaterial),s._gizmoMesh.lookAt(s._rootMesh.position.add(e)),s._gizmoMesh.scaling.scaleInPlace(1/3),s._gizmoMesh.parent=s._rootMesh;var d=0,p=new u.e,b={snapDistance:0};s.dragBehavior=new yi.a({dragPlaneNormal:e}),s.dragBehavior.moveAttached=!1,s._rootMesh.addBehavior(s.dragBehavior),s.dragBehavior.onDragObservable.add(function(B){if(s.attachedNode){if(s.snapDistance==0)s.attachedNode.getWorldMatrix().addTranslationFromFloats(B.delta.x,B.delta.y,B.delta.z);else if(d+=B.dragDistance,Math.abs(d)>s.snapDistance){var F=Math.floor(Math.abs(d)/s.snapDistance);d%=s.snapDistance,B.delta.normalizeToRef(p),p.scaleInPlace(s.snapDistance*F),s.attachedNode.getWorldMatrix().addTranslationFromFloats(p.x,p.y,p.z),b.snapDistance=s.snapDistance*F,s.onSnapObservable.notifyObservers(b)}s._matrixChanged()}}),s.dragBehavior.onDragStartObservable.add(function(){s._dragging=!0}),s.dragBehavior.onDragEndObservable.add(function(){s._dragging=!1});var P=i._getSharedGizmoLight();P.includedOnlyMeshes=P.includedOnlyMeshes.concat(s._rootMesh.getChildMeshes(!1));var O={gizmoMeshes:s._gizmoMesh.getChildMeshes(),colliderMeshes:s._gizmoMesh.getChildMeshes(),material:s._coloredMaterial,hoverMaterial:s._hoverMaterial,disableMaterial:s._disableMaterial,active:!1};return(a=s._parent)===null||a===void 0||a.addToAxisCache(s._gizmoMesh,O),s._pointerObserver=i.utilityLayerScene.onPointerObservable.add(function(B){var F;if(!s._customMeshSet&&(s._isHovered=O.colliderMeshes.indexOf((F=B?.pickInfo)===null||F===void 0?void 0:F.pickedMesh)!=-1,!s._parent)){var z=s._isHovered||s._dragging?s._hoverMaterial:s._coloredMaterial;O.gizmoMeshes.forEach(function(J){J.material=z})}}),s}return Object(c.d)(t,r),t._CreatePlane=function(e,n){var i=new Er.a("plane",e),o=Rs.a.CreatePlane("dragPlane",{width:.1375,height:.1375,sideOrientation:2},e);return o.material=n,o.parent=i,i},t.prototype._attachedNodeChanged=function(e){this.dragBehavior&&(this.dragBehavior.enabled=!!e)},Object.defineProperty(t.prototype,"isEnabled",{get:function(){return this._isEnabled},set:function(e){this._isEnabled=e,e?this._parent&&(this.attachedNode=this._parent.attachedNode):this.attachedNode=null},enumerable:!1,configurable:!0}),t.prototype.dispose=function(){this.onSnapObservable.clear(),this.gizmoLayer.utilityLayerScene.onPointerObservable.remove(this._pointerObserver),this.dragBehavior.detach(),r.prototype.dispose.call(this),this._gizmoMesh&&this._gizmoMesh.dispose(),[this._coloredMaterial,this._hoverMaterial,this._disableMaterial].forEach(function(e){e&&e.dispose()})},t}(wn.a),hu=function(r){function t(e,n,i){e===void 0&&(e=On.a.DefaultUtilityLayer),n===void 0&&(n=1);var o=r.call(this,e)||this;return o._meshAttached=null,o._nodeAttached=null,o._observables=[],o._gizmoAxisCache=new Map,o.onDragStartObservable=new x.c,o.onDragEndObservable=new x.c,o._planarGizmoEnabled=!1,o.xGizmo=new Yo.a(new u.e(1,0,0),M.a.Red().scale(.5),e,o,n),o.yGizmo=new Yo.a(new u.e(0,1,0),M.a.Green().scale(.5),e,o,n),o.zGizmo=new Yo.a(new u.e(0,0,1),M.a.Blue().scale(.5),e,o,n),o.xPlaneGizmo=new Qo(new u.e(1,0,0),M.a.Red().scale(.5),o.gizmoLayer,o),o.yPlaneGizmo=new Qo(new u.e(0,1,0),M.a.Green().scale(.5),o.gizmoLayer,o),o.zPlaneGizmo=new Qo(new u.e(0,0,1),M.a.Blue().scale(.5),o.gizmoLayer,o),[o.xGizmo,o.yGizmo,o.zGizmo,o.xPlaneGizmo,o.yPlaneGizmo,o.zPlaneGizmo].forEach(function(a){a.dragBehavior.onDragStartObservable.add(function(){o.onDragStartObservable.notifyObservers({})}),a.dragBehavior.onDragEndObservable.add(function(){o.onDragEndObservable.notifyObservers({})})}),o.attachedMesh=null,i?i.addToAxisCache(o._gizmoAxisCache):wn.a.GizmoAxisPointerObserver(e,o._gizmoAxisCache),o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"attachedMesh",{get:function(){return this._meshAttached},set:function(e){this._meshAttached=e,this._nodeAttached=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.xPlaneGizmo,this.yPlaneGizmo,this.zPlaneGizmo].forEach(function(n){n.isEnabled?n.attachedMesh=e:n.attachedMesh=null})},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"attachedNode",{get:function(){return this._nodeAttached},set:function(e){this._meshAttached=null,this._nodeAttached=null,[this.xGizmo,this.yGizmo,this.zGizmo,this.xPlaneGizmo,this.yPlaneGizmo,this.zPlaneGizmo].forEach(function(n){n.isEnabled?n.attachedNode=e:n.attachedNode=null})},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"isHovered",{get:function(){var e=!1;return[this.xGizmo,this.yGizmo,this.zGizmo,this.xPlaneGizmo,this.yPlaneGizmo,this.zPlaneGizmo].forEach(function(n){e=e||n.isHovered}),e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"planarGizmoEnabled",{get:function(){return this._planarGizmoEnabled},set:function(e){var n=this;this._planarGizmoEnabled=e,[this.xPlaneGizmo,this.yPlaneGizmo,this.zPlaneGizmo].forEach(function(i){i&&(i.isEnabled=e,e&&(i.attachedMesh?i.attachedMesh=n.attachedMesh:i.attachedNode=n.attachedNode))},this)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"updateGizmoRotationToMatchAttachedMesh",{get:function(){return this._updateGizmoRotationToMatchAttachedMesh},set:function(e){this._updateGizmoRotationToMatchAttachedMesh=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.xPlaneGizmo,this.yPlaneGizmo,this.zPlaneGizmo].forEach(function(n){n&&(n.updateGizmoRotationToMatchAttachedMesh=e)})},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"snapDistance",{get:function(){return this._snapDistance},set:function(e){this._snapDistance=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.xPlaneGizmo,this.yPlaneGizmo,this.zPlaneGizmo].forEach(function(n){n&&(n.snapDistance=e)})},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"scaleRatio",{get:function(){return this._scaleRatio},set:function(e){this._scaleRatio=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.xPlaneGizmo,this.yPlaneGizmo,this.zPlaneGizmo].forEach(function(n){n&&(n.scaleRatio=e)})},enumerable:!1,configurable:!0}),t.prototype.addToAxisCache=function(e,n){this._gizmoAxisCache.set(e,n)},t.prototype.dispose=function(){var e=this;[this.xGizmo,this.yGizmo,this.zGizmo,this.xPlaneGizmo,this.yPlaneGizmo,this.zPlaneGizmo].forEach(function(n){n&&n.dispose()}),this._observables.forEach(function(n){e.gizmoLayer.utilityLayerScene.onPointerObservable.remove(n)}),this.onDragStartObservable.clear(),this.onDragEndObservable.clear()},t.prototype.setCustomMesh=function(e){l.a.Error("Custom meshes are not supported on this gizmo, please set the custom meshes on the gizmos contained within this one (gizmo.xGizmo, gizmo.yGizmo, gizmo.zGizmo,gizmo.xPlaneGizmo, gizmo.yPlaneGizmo, gizmo.zPlaneGizmo)")},t}(wn.a);ft.a.CreatePolyhedron=function(r){var t=[];t[0]={vertex:[[0,0,1.732051],[1.632993,0,-.5773503],[-.8164966,1.414214,-.5773503],[-.8164966,-1.414214,-.5773503]],face:[[0,1,2],[0,2,3],[0,3,1],[1,3,2]]},t[1]={vertex:[[0,0,1.414214],[1.414214,0,0],[0,1.414214,0],[-1.414214,0,0],[0,-1.414214,0],[0,0,-1.414214]],face:[[0,1,2],[0,2,3],[0,3,4],[0,4,1],[1,4,5],[1,5,2],[2,5,3],[3,5,4]]},t[2]={vertex:[[0,0,1.070466],[.7136442,0,.7978784],[-.3568221,.618034,.7978784],[-.3568221,-.618034,.7978784],[.7978784,.618034,.3568221],[.7978784,-.618034,.3568221],[-.9341724,.381966,.3568221],[.1362939,1,.3568221],[.1362939,-1,.3568221],[-.9341724,-.381966,.3568221],[.9341724,.381966,-.3568221],[.9341724,-.381966,-.3568221],[-.7978784,.618034,-.3568221],[-.1362939,1,-.3568221],[-.1362939,-1,-.3568221],[-.7978784,-.618034,-.3568221],[.3568221,.618034,-.7978784],[.3568221,-.618034,-.7978784],[-.7136442,0,-.7978784],[0,0,-1.070466]],face:[[0,1,4,7,2],[0,2,6,9,3],[0,3,8,5,1],[1,5,11,10,4],[2,7,13,12,6],[3,9,15,14,8],[4,10,16,13,7],[5,8,14,17,11],[6,12,18,15,9],[10,11,17,19,16],[12,13,16,19,18],[14,15,18,19,17]]},t[3]={vertex:[[0,0,1.175571],[1.051462,0,.5257311],[.3249197,1,.5257311],[-.8506508,.618034,.5257311],[-.8506508,-.618034,.5257311],[.3249197,-1,.5257311],[.8506508,.618034,-.5257311],[.8506508,-.618034,-.5257311],[-.3249197,1,-.5257311],[-1.051462,0,-.5257311],[-.3249197,-1,-.5257311],[0,0,-1.175571]],face:[[0,1,2],[0,2,3],[0,3,4],[0,4,5],[0,5,1],[1,5,7],[1,7,6],[1,6,2],[2,6,8],[2,8,3],[3,8,9],[3,9,4],[4,9,10],[4,10,5],[5,10,7],[6,7,11],[6,11,8],[7,10,11],[8,11,9],[9,11,10]]},t[4]={vertex:[[0,0,1.070722],[.7148135,0,.7971752],[-.104682,.7071068,.7971752],[-.6841528,.2071068,.7971752],[-.104682,-.7071068,.7971752],[.6101315,.7071068,.5236279],[1.04156,.2071068,.1367736],[.6101315,-.7071068,.5236279],[-.3574067,1,.1367736],[-.7888348,-.5,.5236279],[-.9368776,.5,.1367736],[-.3574067,-1,.1367736],[.3574067,1,-.1367736],[.9368776,-.5,-.1367736],[.7888348,.5,-.5236279],[.3574067,-1,-.1367736],[-.6101315,.7071068,-.5236279],[-1.04156,-.2071068,-.1367736],[-.6101315,-.7071068,-.5236279],[.104682,.7071068,-.7971752],[.6841528,-.2071068,-.7971752],[.104682,-.7071068,-.7971752],[-.7148135,0,-.7971752],[0,0,-1.070722]],face:[[0,2,3],[1,6,5],[4,9,11],[7,15,13],[8,16,10],[12,14,19],[17,22,18],[20,21,23],[0,1,5,2],[0,3,9,4],[0,4,7,1],[1,7,13,6],[2,5,12,8],[2,8,10,3],[3,10,17,9],[4,11,15,7],[5,6,14,12],[6,13,20,14],[8,12,19,16],[9,17,18,11],[10,16,22,17],[11,18,21,15],[13,15,21,20],[14,20,23,19],[16,19,23,22],[18,22,23,21]]},t[5]={vertex:[[0,0,1.322876],[1.309307,0,.1889822],[-.9819805,.8660254,.1889822],[.1636634,-1.299038,.1889822],[.3273268,.8660254,-.9449112],[-.8183171,-.4330127,-.9449112]],face:[[0,3,1],[2,4,5],[0,1,4,2],[0,2,5,3],[1,3,5,4]]},t[6]={vertex:[[0,0,1.159953],[1.013464,0,.5642542],[-.3501431,.9510565,.5642542],[-.7715208,-.6571639,.5642542],[.6633206,.9510565,-.03144481],[.8682979,-.6571639,-.3996071],[-1.121664,.2938926,-.03144481],[-.2348831,-1.063314,-.3996071],[.5181548,.2938926,-.9953061],[-.5850262,-.112257,-.9953061]],face:[[0,1,4,2],[0,2,6,3],[1,5,8,4],[3,6,9,7],[5,7,9,8],[0,3,7,5,1],[2,4,8,9,6]]},t[7]={vertex:[[0,0,1.118034],[.8944272,0,.6708204],[-.2236068,.8660254,.6708204],[-.7826238,-.4330127,.6708204],[.6708204,.8660254,.2236068],[1.006231,-.4330127,-.2236068],[-1.006231,.4330127,.2236068],[-.6708204,-.8660254,-.2236068],[.7826238,.4330127,-.6708204],[.2236068,-.8660254,-.6708204],[-.8944272,0,-.6708204],[0,0,-1.118034]],face:[[0,1,4,2],[0,2,6,3],[1,5,8,4],[3,6,10,7],[5,9,11,8],[7,10,11,9],[0,3,7,9,5,1],[2,4,8,11,10,6]]},t[8]={vertex:[[-.729665,.670121,.319155],[-.655235,-.29213,-.754096],[-.093922,-.607123,.537818],[.702196,.595691,.485187],[.776626,-.36656,-.588064]],face:[[1,4,2],[0,1,2],[3,0,2],[4,3,2],[4,1,0,3]]},t[9]={vertex:[[-.868849,-.100041,.61257],[-.329458,.976099,.28078],[-.26629,-.013796,-.477654],[-.13392,-1.034115,.229829],[.738834,.707117,-.307018],[.859683,-.535264,-.338508]],face:[[3,0,2],[5,3,2],[4,5,2],[1,4,2],[0,1,2],[0,3,5,4,1]]},t[10]={vertex:[[-.610389,.243975,.531213],[-.187812,-.48795,-.664016],[-.187812,.9759,-.664016],[.187812,-.9759,.664016],[.798201,.243975,.132803]],face:[[1,3,0],[3,4,0],[3,1,4],[0,2,1],[0,4,2],[2,4,1]]},t[11]={vertex:[[-1.028778,.392027,-.048786],[-.640503,-.646161,.621837],[-.125162,-.395663,-.540059],[.004683,.888447,-.651988],[.125161,.395663,.540059],[.632925,-.791376,.433102],[1.031672,.157063,-.354165]],face:[[3,2,0],[2,1,0],[2,5,1],[0,4,3],[0,1,4],[4,1,5],[2,3,6],[3,4,6],[5,2,6],[4,5,6]]},t[12]={vertex:[[-.669867,.334933,-.529576],[-.669867,.334933,.529577],[-.4043,1.212901,0],[-.334933,-.669867,-.529576],[-.334933,-.669867,.529577],[.334933,.669867,-.529576],[.334933,.669867,.529577],[.4043,-1.212901,0],[.669867,-.334933,-.529576],[.669867,-.334933,.529577]],face:[[8,9,7],[6,5,2],[3,8,7],[5,0,2],[4,3,7],[0,1,2],[9,4,7],[1,6,2],[9,8,5,6],[8,3,0,5],[3,4,1,0],[4,9,6,1]]},t[13]={vertex:[[-.931836,.219976,-.264632],[-.636706,.318353,.692816],[-.613483,-.735083,-.264632],[-.326545,.979634,0],[-.31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e,n,i,o,a,s,d=r.type&&(r.type<0||r.type>=t.length)?0:r.type||0,p=r.size,b=r.sizeX||p||1,P=r.sizeY||p||1,O=r.sizeZ||p||1,B=r.custom||t[d],F=B.face.length,z=r.faceUV||new Array(F),J=r.faceColors,ie=r.flat===void 0||r.flat,se=r.sideOrientation===0?0:r.sideOrientation||ft.a.DEFAULTSIDE,ce=new Array,ue=new Array,fe=new Array,ve=new Array,Te=new Array,Re=0,Ae=0,Ee=new Array,Se=0,Le=0;if(ie)for(Le=0;Le<F;Le++)J&&J[Le]===void 0&&(J[Le]=new M.b(1,1,1,1)),z&&z[Le]===void 0&&(z[Le]=new u.f(0,0,1,1));if(ie)for(Le=0;Le<F;Le++){var Ce=B.face[Le].length;for(i=2*Math.PI/Ce,o=.5*Math.tan(i/2),a=.5,Se=0;Se<Ce;Se++)ce.push(B.vertex[B.face[Le][Se]][0]*b,B.vertex[B.face[Le][Se]][1]*P,B.vertex[B.face[Le][Se]][2]*O),Ee.push(Re),Re++,e=z[Le].x+(z[Le].z-z[Le].x)*(.5+o),n=z[Le].y+(z[Le].w-z[Le].y)*(a-.5),ve.push(e,n),s=o*Math.cos(i)-a*Math.sin(i),a=o*Math.sin(i)+a*Math.cos(i),o=s,J&&Te.push(J[Le].r,J[Le].g,J[Le].b,J[Le].a);for(Se=0;Se<Ce-2;Se++)ue.push(Ee[0+Ae],Ee[Se+2+Ae],Ee[Se+1+Ae]);Ae+=Ce}else{for(Se=0;Se<B.vertex.length;Se++)ce.push(B.vertex[Se][0]*b,B.vertex[Se][1]*P,B.vertex[Se][2]*O),ve.push(0,0);for(Le=0;Le<F;Le++)for(Se=0;Se<B.face[Le].length-2;Se++)ue.push(B.face[Le][0],B.face[Le][Se+2],B.face[Le][Se+1])}ft.a.ComputeNormals(ce,ue,fe),ft.a._ComputeSides(se,ce,ue,fe,ve,r.frontUVs,r.backUVs);var Ne=new ft.a;return Ne.positions=ce,Ne.indices=ue,Ne.normals=fe,Ne.uvs=ve,J&&ie&&(Ne.colors=Te),Ne},De.a.CreatePolyhedron=function(r,t,e){return ao.CreatePolyhedron(r,t,e)};var ao=function(){function r(){}return r.CreatePolyhedron=function(t,e,n){n===void 0&&(n=null);var i=new De.a(t,n);return e.sideOrientation=De.a._GetDefaultSideOrientation(e.sideOrientation),i._originalBuilderSideOrientation=e.sideOrientation,ft.a.CreatePolyhedron(e).applyToMesh(i,e.updatable),i},r}(),du=function(r){function t(e,n,i){e===void 0&&(e=On.a.DefaultUtilityLayer),n===void 0&&(n=1);var o=r.call(this,e)||this;return o._meshAttached=null,o._nodeAttached=null,o._sensitivity=1,o._observables=[],o._gizmoAxisCache=new Map,o.onDragStartObservable=new x.c,o.onDragEndObservable=new x.c,o.uniformScaleGizmo=o._createUniformScaleMesh(),o.xGizmo=new oo(new u.e(1,0,0),M.a.Red().scale(.5),e,o,n),o.yGizmo=new oo(new u.e(0,1,0),M.a.Green().scale(.5),e,o,n),o.zGizmo=new oo(new u.e(0,0,1),M.a.Blue().scale(.5),e,o,n),[o.xGizmo,o.yGizmo,o.zGizmo,o.uniformScaleGizmo].forEach(function(a){a.dragBehavior.onDragStartObservable.add(function(){o.onDragStartObservable.notifyObservers({})}),a.dragBehavior.onDragEndObservable.add(function(){o.onDragEndObservable.notifyObservers({})})}),o.attachedMesh=null,o.attachedNode=null,i?i.addToAxisCache(o._gizmoAxisCache):wn.a.GizmoAxisPointerObserver(e,o._gizmoAxisCache),o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"attachedMesh",{get:function(){return this._meshAttached},set:function(e){this._meshAttached=e,this._nodeAttached=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.uniformScaleGizmo].forEach(function(n){n.isEnabled?n.attachedMesh=e:n.attachedMesh=null})},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"attachedNode",{get:function(){return this._nodeAttached},set:function(e){this._meshAttached=null,this._nodeAttached=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.uniformScaleGizmo].forEach(function(n){n.isEnabled?n.attachedNode=e:n.attachedNode=null})},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"isHovered",{get:function(){var e=!1;return[this.xGizmo,this.yGizmo,this.zGizmo].forEach(function(n){e=e||n.isHovered}),e},enumerable:!1,configurable:!0}),t.prototype._createUniformScaleMesh=function(){this._coloredMaterial=new Ft.a("",this.gizmoLayer.utilityLayerScene),this._coloredMaterial.diffuseColor=M.a.Gray(),this._hoverMaterial=new Ft.a("",this.gizmoLayer.utilityLayerScene),this._hoverMaterial.diffuseColor=M.a.Yellow(),this._disableMaterial=new Ft.a("",this.gizmoLayer.utilityLayerScene),this._disableMaterial.diffuseColor=M.a.Gray(),this._disableMaterial.alpha=.4;var e=new oo(new u.e(0,1,0),M.a.Gray().scale(.5),this.gizmoLayer,this);e.updateGizmoRotationToMatchAttachedMesh=!1,e.uniformScaling=!0,this._uniformScalingMesh=ao.CreatePolyhedron("uniform",{type:1},e.gizmoLayer.utilityLayerScene),this._uniformScalingMesh.scaling.scaleInPlace(.01),this._uniformScalingMesh.visibility=0,this._octahedron=ao.CreatePolyhedron("",{type:1},e.gizmoLayer.utilityLayerScene),this._octahedron.scaling.scaleInPlace(.007),this._uniformScalingMesh.addChild(this._octahedron),e.setCustomMesh(this._uniformScalingMesh,!0);var n=this.gizmoLayer._getSharedGizmoLight();n.includedOnlyMeshes=n.includedOnlyMeshes.concat(this._octahedron);var i={gizmoMeshes:[this._octahedron,this._uniformScalingMesh],colliderMeshes:[this._uniformScalingMesh],material:this._coloredMaterial,hoverMaterial:this._hoverMaterial,disableMaterial:this._disableMaterial,active:!1};return this.addToAxisCache(e._rootMesh,i),e},Object.defineProperty(t.prototype,"updateGizmoRotationToMatchAttachedMesh",{get:function(){return this._updateGizmoRotationToMatchAttachedMesh},set:function(e){e?(this._updateGizmoRotationToMatchAttachedMesh=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.uniformScaleGizmo].forEach(function(n){n&&(n.updateGizmoRotationToMatchAttachedMesh=e)})):l.a.Warn("Setting updateGizmoRotationToMatchAttachedMesh = false on scaling gizmo is not supported.")},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"snapDistance",{get:function(){return this._snapDistance},set:function(e){this._snapDistance=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.uniformScaleGizmo].forEach(function(n){n&&(n.snapDistance=e)})},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"scaleRatio",{get:function(){return this._scaleRatio},set:function(e){this._scaleRatio=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.uniformScaleGizmo].forEach(function(n){n&&(n.scaleRatio=e)})},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"sensitivity",{get:function(){return this._sensitivity},set:function(e){this._sensitivity=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.uniformScaleGizmo].forEach(function(n){n&&(n.sensitivity=e)})},enumerable:!1,configurable:!0}),t.prototype.addToAxisCache=function(e,n){this._gizmoAxisCache.set(e,n)},t.prototype.dispose=function(){var e=this;[this.xGizmo,this.yGizmo,this.zGizmo,this.uniformScaleGizmo].forEach(function(n){n&&n.dispose()}),this._observables.forEach(function(n){e.gizmoLayer.utilityLayerScene.onPointerObservable.remove(n)}),this.onDragStartObservable.clear(),this.onDragEndObservable.clear(),[this._uniformScalingMesh,this._octahedron].forEach(function(n){n&&n.dispose()}),[this._coloredMaterial,this._hoverMaterial,this._disableMaterial].forEach(function(n){n&&n.dispose()})},t}(wn.a),dp=function(){function r(t,e,n,i){e===void 0&&(e=1),n===void 0&&(n=On.a.DefaultUtilityLayer),i===void 0&&(i=On.a.DefaultKeepDepthUtilityLayer),this.scene=t,this.clearGizmoOnEmptyPointerEvent=!1,this.onAttachedToMeshObservable=new x.c,this.onAttachedToNodeObservable=new x.c,this._gizmosEnabled={positionGizmo:!1,rotationGizmo:!1,scaleGizmo:!1,boundingBoxGizmo:!1},this._pointerObservers=[],this._attachedMesh=null,this._attachedNode=null,this._boundingBoxColor=M.a.FromHexString("#0984e3"),this._thickness=1,this._gizmoAxisCache=new Map,this.boundingBoxDragBehavior=new _l,this.attachableMeshes=null,this.attachableNodes=null,this.usePointerToAttachGizmos=!0,this._defaultUtilityLayer=n,this._defaultKeepDepthUtilityLayer=i,this._defaultKeepDepthUtilityLayer.utilityLayerScene.autoClearDepthAndStencil=!1,this._thickness=e,this.gizmos={positionGizmo:null,rotationGizmo:null,scaleGizmo:null,boundingBoxGizmo:null};var o=this._attachToMeshPointerObserver(t),a=wn.a.GizmoAxisPointerObserver(this._defaultUtilityLayer,this._gizmoAxisCache);this._pointerObservers=[o,a]}return Object.defineProperty(r.prototype,"keepDepthUtilityLayer",{get:function(){return this._defaultKeepDepthUtilityLayer},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"utilityLayer",{get:function(){return this._defaultUtilityLayer},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isHovered",{get:function(){var t=!1;for(var e in this.gizmos){var n=this.gizmos[e];if(n&&n.isHovered){t=!0;break}}return t},enumerable:!1,configurable:!0}),r.prototype._attachToMeshPointerObserver=function(t){var e=this;return t.onPointerObservable.add(function(n){if(e.usePointerToAttachGizmos&&n.type==Tt.a.POINTERDOWN)if(n.pickInfo&&n.pickInfo.pickedMesh){var i=n.pickInfo.pickedMesh;if(e.attachableMeshes==null)for(;i&&i.parent!=null;)i=i.parent;else{var o=!1;e.attachableMeshes.forEach(function(a){i&&(i==a||i.isDescendantOf(a))&&(i=a,o=!0)}),o||(i=null)}i instanceof Dt.a?e._attachedMesh!=i&&e.attachToMesh(i):e.clearGizmoOnEmptyPointerEvent&&e.attachToMesh(null)}else e.clearGizmoOnEmptyPointerEvent&&e.attachToMesh(null)})},r.prototype.attachToMesh=function(t){for(var e in this._attachedMesh&&this._attachedMesh.removeBehavior(this.boundingBoxDragBehavior),this._attachedNode&&this._attachedNode.removeBehavior(this.boundingBoxDragBehavior),this._attachedMesh=t,this._attachedNode=null,this.gizmos){var n=this.gizmos[e];n&&this._gizmosEnabled[e]&&(n.attachedMesh=t)}this.boundingBoxGizmoEnabled&&this._attachedMesh&&this._attachedMesh.addBehavior(this.boundingBoxDragBehavior),this.onAttachedToMeshObservable.notifyObservers(t)},r.prototype.attachToNode=function(t){for(var e in this._attachedMesh&&this._attachedMesh.removeBehavior(this.boundingBoxDragBehavior),this._attachedNode&&this._attachedNode.removeBehavior(this.boundingBoxDragBehavior),this._attachedMesh=null,this._attachedNode=t,this.gizmos){var n=this.gizmos[e];n&&this._gizmosEnabled[e]&&(n.attachedNode=t)}this.boundingBoxGizmoEnabled&&this._attachedNode&&this._attachedNode.addBehavior(this.boundingBoxDragBehavior),this.onAttachedToNodeObservable.notifyObservers(t)},Object.defineProperty(r.prototype,"positionGizmoEnabled",{get:function(){return this._gizmosEnabled.positionGizmo},set:function(t){t?(this.gizmos.positionGizmo||(this.gizmos.positionGizmo=new hu(this._defaultUtilityLayer,this._thickness,this)),this._attachedNode?this.gizmos.positionGizmo.attachedNode=this._attachedNode:this.gizmos.positionGizmo.attachedMesh=this._attachedMesh):this.gizmos.positionGizmo&&(this.gizmos.positionGizmo.attachedNode=null),this._gizmosEnabled.positionGizmo=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"rotationGizmoEnabled",{get:function(){return this._gizmosEnabled.rotationGizmo},set:function(t){t?(this.gizmos.rotationGizmo||(this.gizmos.rotationGizmo=new uu(this._defaultUtilityLayer,32,!1,this._thickness,this)),this._attachedNode?this.gizmos.rotationGizmo.attachedNode=this._attachedNode:this.gizmos.rotationGizmo.attachedMesh=this._attachedMesh):this.gizmos.rotationGizmo&&(this.gizmos.rotationGizmo.attachedNode=null),this._gizmosEnabled.rotationGizmo=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"scaleGizmoEnabled",{get:function(){return this._gizmosEnabled.scaleGizmo},set:function(t){t?(this.gizmos.scaleGizmo=this.gizmos.scaleGizmo||new du(this._defaultUtilityLayer,this._thickness,this),this._attachedNode?this.gizmos.scaleGizmo.attachedNode=this._attachedNode:this.gizmos.scaleGizmo.attachedMesh=this._attachedMesh):this.gizmos.scaleGizmo&&(this.gizmos.scaleGizmo.attachedNode=null),this._gizmosEnabled.scaleGizmo=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"boundingBoxGizmoEnabled",{get:function(){return this._gizmosEnabled.boundingBoxGizmo},set:function(t){t?(this.gizmos.boundingBoxGizmo=this.gizmos.boundingBoxGizmo||new lu(this._boundingBoxColor,this._defaultKeepDepthUtilityLayer),this._attachedMesh?this.gizmos.boundingBoxGizmo.attachedMesh=this._attachedMesh:this.gizmos.boundingBoxGizmo.attachedNode=this._attachedNode,this._attachedMesh?(this._attachedMesh.removeBehavior(this.boundingBoxDragBehavior),this._attachedMesh.addBehavior(this.boundingBoxDragBehavior)):this._attachedNode&&(this._attachedNode.removeBehavior(this.boundingBoxDragBehavior),this._attachedNode.addBehavior(this.boundingBoxDragBehavior))):this.gizmos.boundingBoxGizmo&&(this._attachedMesh?this._attachedMesh.removeBehavior(this.boundingBoxDragBehavior):this._attachedNode&&this._attachedNode.removeBehavior(this.boundingBoxDragBehavior),this.gizmos.boundingBoxGizmo.attachedNode=null),this._gizmosEnabled.boundingBoxGizmo=t},enumerable:!1,configurable:!0}),r.prototype.addToAxisCache=function(t){var e=this;t.size>0&&t.forEach(function(n,i){e._gizmoAxisCache.set(i,n)})},r.prototype.dispose=function(){var t=this;for(var e in this._pointerObservers.forEach(function(i){t.scene.onPointerObservable.remove(i)}),this.gizmos){var n=this.gizmos[e];n&&n.dispose()}this._defaultKeepDepthUtilityLayer.dispose(),this._defaultUtilityLayer.dispose(),this.boundingBoxDragBehavior.detach(),this.onAttachedToMeshObservable.clear()},r}(),xi=f(48),qo=function(r){function t(){var e=r!==null&&r.apply(this,arguments)||this;return e._needProjectionMatrixCompute=!0,e}return Object(c.d)(t,r),t.prototype._setPosition=function(e){this._position=e},Object.defineProperty(t.prototype,"position",{get:function(){return this._position},set:function(e){this._setPosition(e)},enumerable:!1,configurable:!0}),t.prototype._setDirection=function(e){this._direction=e},Object.defineProperty(t.prototype,"direction",{get:function(){return this._direction},set:function(e){this._setDirection(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"shadowMinZ",{get:function(){return this._shadowMinZ},set:function(e){this._shadowMinZ=e,this.forceProjectionMatrixCompute()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"shadowMaxZ",{get:function(){return this._shadowMaxZ},set:function(e){this._shadowMaxZ=e,this.forceProjectionMatrixCompute()},enumerable:!1,configurable:!0}),t.prototype.computeTransformedInformation=function(){return!(!this.parent||!this.parent.getWorldMatrix)&&(this.transformedPosition||(this.transformedPosition=u.e.Zero()),u.e.TransformCoordinatesToRef(this.position,this.parent.getWorldMatrix(),this.transformedPosition),this.direction&&(this.transformedDirection||(this.transformedDirection=u.e.Zero()),u.e.TransformNormalToRef(this.direction,this.parent.getWorldMatrix(),this.transformedDirection)),!0)},t.prototype.getDepthScale=function(){return 50},t.prototype.getShadowDirection=function(e){return this.transformedDirection?this.transformedDirection:this.direction},t.prototype.getAbsolutePosition=function(){return this.transformedPosition?this.transformedPosition:this.position},t.prototype.setDirectionToTarget=function(e){return this.direction=u.e.Normalize(e.subtract(this.position)),this.direction},t.prototype.getRotation=function(){this.direction.normalize();var e=u.e.Cross(this.direction,ye.a.Y),n=u.e.Cross(e,this.direction);return u.e.RotationFromAxis(e,n,this.direction)},t.prototype.needCube=function(){return!1},t.prototype.needProjectionMatrixCompute=function(){return this._needProjectionMatrixCompute},t.prototype.forceProjectionMatrixCompute=function(){this._needProjectionMatrixCompute=!0},t.prototype._initCache=function(){r.prototype._initCache.call(this),this._cache.position=u.e.Zero()},t.prototype._isSynchronized=function(){return!!this._cache.position.equals(this.position)},t.prototype.computeWorldMatrix=function(e){return!e&&this.isSynchronized()?(this._currentRenderId=this.getScene().getRenderId(),this._worldMatrix):(this._updateCache(),this._cache.position.copyFrom(this.position),this._worldMatrix||(this._worldMatrix=u.a.Identity()),u.a.TranslationToRef(this.position.x,this.position.y,this.position.z,this._worldMatrix),this.parent&&this.parent.getWorldMatrix&&(this._worldMatrix.multiplyToRef(this.parent.getWorldMatrix(),this._worldMatrix),this._markSyncedWithParent()),this._worldMatrixDeterminantIsDirty=!0,this._worldMatrix)},t.prototype.getDepthMinZ=function(e){return this.shadowMinZ!==void 0?this.shadowMinZ:e.minZ},t.prototype.getDepthMaxZ=function(e){return this.shadowMaxZ!==void 0?this.shadowMaxZ:e.maxZ},t.prototype.setShadowProjectionMatrix=function(e,n,i){return this.customProjectionMatrixBuilder?this.customProjectionMatrixBuilder(n,i,e):this._setDefaultShadowProjectionMatrix(e,n,i),this},Object(c.c)([Object(L.o)()],t.prototype,"position",null),Object(c.c)([Object(L.o)()],t.prototype,"direction",null),Object(c.c)([Object(L.c)()],t.prototype,"shadowMinZ",null),Object(c.c)([Object(L.c)()],t.prototype,"shadowMaxZ",null),t}(xi.a);Q.a.AddNodeConstructor("Light_Type_1",function(r,t){return function(){return new Os(r,u.e.Zero(),t)}});var Os=function(r){function t(e,n,i){var o=r.call(this,e,i)||this;return o._shadowFrustumSize=0,o._shadowOrthoScale=.1,o.autoUpdateExtends=!0,o.autoCalcShadowZBounds=!1,o._orthoLeft=Number.MAX_VALUE,o._orthoRight=Number.MIN_VALUE,o._orthoTop=Number.MIN_VALUE,o._orthoBottom=Number.MAX_VALUE,o.position=n.scale(-1),o.direction=n,o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"shadowFrustumSize",{get:function(){return this._shadowFrustumSize},set:function(e){this._shadowFrustumSize=e,this.forceProjectionMatrixCompute()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"shadowOrthoScale",{get:function(){return this._shadowOrthoScale},set:function(e){this._shadowOrthoScale=e,this.forceProjectionMatrixCompute()},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"DirectionalLight"},t.prototype.getTypeID=function(){return xi.a.LIGHTTYPEID_DIRECTIONALLIGHT},t.prototype._setDefaultShadowProjectionMatrix=function(e,n,i){this.shadowFrustumSize>0?this._setDefaultFixedFrustumShadowProjectionMatrix(e):this._setDefaultAutoExtendShadowProjectionMatrix(e,n,i)},t.prototype._setDefaultFixedFrustumShadowProjectionMatrix=function(e){var n=this.getScene().activeCamera;n&&u.a.OrthoLHToRef(this.shadowFrustumSize,this.shadowFrustumSize,this.shadowMinZ!==void 0?this.shadowMinZ:n.minZ,this.shadowMaxZ!==void 0?this.shadowMaxZ:n.maxZ,e)},t.prototype._setDefaultAutoExtendShadowProjectionMatrix=function(e,n,i){var o=this.getScene().activeCamera;if(o){if(this.autoUpdateExtends||this._orthoLeft===Number.MAX_VALUE){var a=u.e.Zero();this._orthoLeft=Number.MAX_VALUE,this._orthoRight=Number.MIN_VALUE,this._orthoTop=Number.MIN_VALUE,this._orthoBottom=Number.MAX_VALUE;for(var s=Number.MAX_VALUE,d=Number.MIN_VALUE,p=0;p<i.length;p++){var b=i[p];if(b)for(var P=b.getBoundingInfo().boundingBox,O=0;O<P.vectorsWorld.length;O++)u.e.TransformCoordinatesToRef(P.vectorsWorld[O],n,a),a.x<this._orthoLeft&&(this._orthoLeft=a.x),a.y<this._orthoBottom&&(this._orthoBottom=a.y),a.x>this._orthoRight&&(this._orthoRight=a.x),a.y>this._orthoTop&&(this._orthoTop=a.y),this.autoCalcShadowZBounds&&(a.z<s&&(s=a.z),a.z>d&&(d=a.z))}this.autoCalcShadowZBounds&&(this._shadowMinZ=s,this._shadowMaxZ=d)}var B=this._orthoRight-this._orthoLeft,F=this._orthoTop-this._orthoBottom;u.a.OrthoOffCenterLHToRef(this._orthoLeft-B*this.shadowOrthoScale,this._orthoRight+B*this.shadowOrthoScale,this._orthoBottom-F*this.shadowOrthoScale,this._orthoTop+F*this.shadowOrthoScale,this.shadowMinZ!==void 0?this.shadowMinZ:o.minZ,this.shadowMaxZ!==void 0?this.shadowMaxZ:o.maxZ,e)}},t.prototype._buildUniformLayout=function(){this._uniformBuffer.addUniform("vLightData",4),this._uniformBuffer.addUniform("vLightDiffuse",4),this._uniformBuffer.addUniform("vLightSpecular",4),this._uniformBuffer.addUniform("shadowsInfo",3),this._uniformBuffer.addUniform("depthValues",2),this._uniformBuffer.create()},t.prototype.transferToEffect=function(e,n){return this.computeTransformedInformation()?(this._uniformBuffer.updateFloat4("vLightData",this.transformedDirection.x,this.transformedDirection.y,this.transformedDirection.z,1,n),this):(this._uniformBuffer.updateFloat4("vLightData",this.direction.x,this.direction.y,this.direction.z,1,n),this)},t.prototype.transferToNodeMaterialEffect=function(e,n){return this.computeTransformedInformation()?(e.setFloat3(n,this.transformedDirection.x,this.transformedDirection.y,this.transformedDirection.z),this):(e.setFloat3(n,this.direction.x,this.direction.y,this.direction.z),this)},t.prototype.getDepthMinZ=function(e){return 1},t.prototype.getDepthMaxZ=function(e){return 1},t.prototype.prepareLightSpecificDefines=function(e,n){e["DIRLIGHT"+n]=!0},Object(c.c)([Object(L.c)()],t.prototype,"shadowFrustumSize",null),Object(c.c)([Object(L.c)()],t.prototype,"shadowOrthoScale",null),Object(c.c)([Object(L.c)()],t.prototype,"autoUpdateExtends",void 0),Object(c.c)([Object(L.c)()],t.prototype,"autoCalcShadowZBounds",void 0),t}(qo);De.a.CreateHemisphere=function(r,t,e,n){var i={segments:t,diameter:e};return Zo.CreateHemisphere(r,i,n)};var Zo=function(){function r(){}return r.CreateHemisphere=function(t,e,n){e.diameter||(e.diameter=1),e.segments||(e.segments=16);var i=Fn.a.CreateSphere("",{slice:.5,diameter:e.diameter,segments:e.segments},n),o=De.a.CreateDisc("",e.diameter/2,3*e.segments+(4-e.segments),n);o.rotation.x=-Math.PI/2,o.parent=i;var a=De.a.MergeMeshes([o,i],!0);return a.name=t,a},r}();Q.a.AddNodeConstructor("Light_Type_2",function(r,t){return function(){return new Ms(r,u.e.Zero(),u.e.Zero(),0,0,t)}});var Ms=function(r){function t(e,n,i,o,a,s){var d=r.call(this,e,s)||this;return d._innerAngle=0,d._projectionTextureMatrix=u.a.Zero(),d._projectionTextureLightNear=1e-6,d._projectionTextureLightFar=1e3,d._projectionTextureUpDirection=u.e.Up(),d._projectionTextureViewLightDirty=!0,d._projectionTextureProjectionLightDirty=!0,d._projectionTextureDirty=!0,d._projectionTextureViewTargetVector=u.e.Zero(),d._projectionTextureViewLightMatrix=u.a.Zero(),d._projectionTextureProjectionLightMatrix=u.a.Zero(),d._projectionTextureScalingMatrix=u.a.FromValues(.5,0,0,0,0,.5,0,0,0,0,.5,0,.5,.5,.5,1),d.position=n,d.direction=i,d.angle=o,d.exponent=a,d}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"angle",{get:function(){return this._angle},set:function(e){this._angle=e,this._cosHalfAngle=Math.cos(.5*e),this._projectionTextureProjectionLightDirty=!0,this.forceProjectionMatrixCompute(),this._computeAngleValues()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"innerAngle",{get:function(){return this._innerAngle},set:function(e){this._innerAngle=e,this._computeAngleValues()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"shadowAngleScale",{get:function(){return this._shadowAngleScale},set:function(e){this._shadowAngleScale=e,this.forceProjectionMatrixCompute()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"projectionTextureMatrix",{get:function(){return this._projectionTextureMatrix},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"projectionTextureLightNear",{get:function(){return this._projectionTextureLightNear},set:function(e){this._projectionTextureLightNear=e,this._projectionTextureProjectionLightDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"projectionTextureLightFar",{get:function(){return this._projectionTextureLightFar},set:function(e){this._projectionTextureLightFar=e,this._projectionTextureProjectionLightDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"projectionTextureUpDirection",{get:function(){return this._projectionTextureUpDirection},set:function(e){this._projectionTextureUpDirection=e,this._projectionTextureProjectionLightDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"projectionTexture",{get:function(){return this._projectionTexture},set:function(e){var n=this;this._projectionTexture!==e&&(this._projectionTexture=e,this._projectionTextureDirty=!0,this._projectionTexture&&!this._projectionTexture.isReady()&&(t._IsProceduralTexture(this._projectionTexture)?this._projectionTexture.getEffect().executeWhenCompiled(function(){n._markMeshesAsLightDirty()}):t._IsTexture(this._projectionTexture)&&this._projectionTexture.onLoadObservable.addOnce(function(){n._markMeshesAsLightDirty()})))},enumerable:!1,configurable:!0}),t._IsProceduralTexture=function(e){return e.onGeneratedObservable!==void 0},t._IsTexture=function(e){return e.onLoadObservable!==void 0},t.prototype.getClassName=function(){return"SpotLight"},t.prototype.getTypeID=function(){return xi.a.LIGHTTYPEID_SPOTLIGHT},t.prototype._setDirection=function(e){r.prototype._setDirection.call(this,e),this._projectionTextureViewLightDirty=!0},t.prototype._setPosition=function(e){r.prototype._setPosition.call(this,e),this._projectionTextureViewLightDirty=!0},t.prototype._setDefaultShadowProjectionMatrix=function(e,n,i){var o=this.getScene().activeCamera;if(o){this._shadowAngleScale=this._shadowAngleScale||1;var a=this._shadowAngleScale*this._angle;u.a.PerspectiveFovLHToRef(a,1,this.getDepthMinZ(o),this.getDepthMaxZ(o),e)}},t.prototype._computeProjectionTextureViewLightMatrix=function(){this._projectionTextureViewLightDirty=!1,this._projectionTextureDirty=!0,this.position.addToRef(this.direction,this._projectionTextureViewTargetVector),u.a.LookAtLHToRef(this.position,this._projectionTextureViewTargetVector,this._projectionTextureUpDirection,this._projectionTextureViewLightMatrix)},t.prototype._computeProjectionTextureProjectionLightMatrix=function(){this._projectionTextureProjectionLightDirty=!1,this._projectionTextureDirty=!0;var e=this.projectionTextureLightFar,n=this.projectionTextureLightNear,i=e/(e-n),o=-i*n,a=1/Math.tan(this._angle/2);u.a.FromValuesToRef(a/1,0,0,0,0,a,0,0,0,0,i,1,0,0,o,0,this._projectionTextureProjectionLightMatrix)},t.prototype._computeProjectionTextureMatrix=function(){if(this._projectionTextureDirty=!1,this._projectionTextureViewLightMatrix.multiplyToRef(this._projectionTextureProjectionLightMatrix,this._projectionTextureMatrix),this._projectionTexture instanceof we.a){var e=this._projectionTexture.uScale/2,n=this._projectionTexture.vScale/2;u.a.FromValuesToRef(e,0,0,0,0,n,0,0,0,0,.5,0,.5,.5,.5,1,this._projectionTextureScalingMatrix)}this._projectionTextureMatrix.multiplyToRef(this._projectionTextureScalingMatrix,this._projectionTextureMatrix)},t.prototype._buildUniformLayout=function(){this._uniformBuffer.addUniform("vLightData",4),this._uniformBuffer.addUniform("vLightDiffuse",4),this._uniformBuffer.addUniform("vLightSpecular",4),this._uniformBuffer.addUniform("vLightDirection",3),this._uniformBuffer.addUniform("vLightFalloff",4),this._uniformBuffer.addUniform("shadowsInfo",3),this._uniformBuffer.addUniform("depthValues",2),this._uniformBuffer.create()},t.prototype._computeAngleValues=function(){this._lightAngleScale=1/Math.max(.001,Math.cos(.5*this._innerAngle)-this._cosHalfAngle),this._lightAngleOffset=-this._cosHalfAngle*this._lightAngleScale},t.prototype.transferTexturesToEffect=function(e,n){return this.projectionTexture&&this.projectionTexture.isReady()&&(this._projectionTextureViewLightDirty&&this._computeProjectionTextureViewLightMatrix(),this._projectionTextureProjectionLightDirty&&this._computeProjectionTextureProjectionLightMatrix(),this._projectionTextureDirty&&this._computeProjectionTextureMatrix(),e.setMatrix("textureProjectionMatrix"+n,this._projectionTextureMatrix),e.setTexture("projectionLightSampler"+n,this.projectionTexture)),this},t.prototype.transferToEffect=function(e,n){var i;return this.computeTransformedInformation()?(this._uniformBuffer.updateFloat4("vLightData",this.transformedPosition.x,this.transformedPosition.y,this.transformedPosition.z,this.exponent,n),i=u.e.Normalize(this.transformedDirection)):(this._uniformBuffer.updateFloat4("vLightData",this.position.x,this.position.y,this.position.z,this.exponent,n),i=u.e.Normalize(this.direction)),this._uniformBuffer.updateFloat4("vLightDirection",i.x,i.y,i.z,this._cosHalfAngle,n),this._uniformBuffer.updateFloat4("vLightFalloff",this.range,this._inverseSquaredRange,this._lightAngleScale,this._lightAngleOffset,n),this},t.prototype.transferToNodeMaterialEffect=function(e,n){var i;return i=this.computeTransformedInformation()?u.e.Normalize(this.transformedDirection):u.e.Normalize(this.direction),this.getScene().useRightHandedSystem?e.setFloat3(n,-i.x,-i.y,-i.z):e.setFloat3(n,i.x,i.y,i.z),this},t.prototype.dispose=function(){r.prototype.dispose.call(this),this._projectionTexture&&this._projectionTexture.dispose()},t.prototype.prepareLightSpecificDefines=function(e,n){e["SPOTLIGHT"+n]=!0,e["PROJECTEDLIGHTTEXTURE"+n]=!(!this.projectionTexture||!this.projectionTexture.isReady())},Object(c.c)([Object(L.c)()],t.prototype,"angle",null),Object(c.c)([Object(L.c)()],t.prototype,"innerAngle",null),Object(c.c)([Object(L.c)()],t.prototype,"shadowAngleScale",null),Object(c.c)([Object(L.c)()],t.prototype,"exponent",void 0),Object(c.c)([Object(L.c)()],t.prototype,"projectionTextureLightNear",null),Object(c.c)([Object(L.c)()],t.prototype,"projectionTextureLightFar",null),Object(c.c)([Object(L.c)()],t.prototype,"projectionTextureUpDirection",null),Object(c.c)([Object(L.m)("projectedLightTexture")],t.prototype,"_projectionTexture",void 0),t}(qo),fp=function(r){function t(e){e===void 0&&(e=On.a.DefaultUtilityLayer);var n=r.call(this,e)||this;return n._cachedPosition=new u.e,n._cachedForward=new u.e(0,0,1),n._pointerObserver=null,n.onClickedObservable=new x.c,n._light=null,n.attachedMesh=new Dt.a("",n.gizmoLayer.utilityLayerScene),n._attachedMeshParent=new Er.a("parent",n.gizmoLayer.utilityLayerScene),n.attachedMesh.parent=n._attachedMeshParent,n._material=new Ft.a("light",n.gizmoLayer.utilityLayerScene),n._material.diffuseColor=new M.a(.5,.5,.5),n._material.specularColor=new M.a(.1,.1,.1),n._pointerObserver=e.utilityLayerScene.onPointerObservable.add(function(i){n._light&&(n._isHovered=!(!i.pickInfo||n._rootMesh.getChildMeshes().indexOf(i.pickInfo.pickedMesh)==-1),n._isHovered&&i.event.button===0&&n.onClickedObservable.notifyObservers(n._light))},Tt.a.POINTERDOWN),n}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"light",{get:function(){return this._light},set:function(e){var n=this;if(this._light=e,e){this._lightMesh&&this._lightMesh.dispose(),e instanceof Vo.a?this._lightMesh=t._CreateHemisphericLightMesh(this.gizmoLayer.utilityLayerScene):this._lightMesh=e instanceof Os?t._CreateDirectionalLightMesh(this.gizmoLayer.utilityLayerScene):e instanceof Ms?t._CreateSpotLightMesh(this.gizmoLayer.utilityLayerScene):t._CreatePointLightMesh(this.gizmoLayer.utilityLayerScene),this._lightMesh.getChildMeshes(!1).forEach(function(o){o.material=n._material}),this._lightMesh.parent=this._rootMesh;var i=this.gizmoLayer._getSharedGizmoLight();i.includedOnlyMeshes=i.includedOnlyMeshes.concat(this._lightMesh.getChildMeshes(!1)),this._lightMesh.rotationQuaternion=new u.b,this.attachedMesh.reservedDataStore||(this.attachedMesh.reservedDataStore={}),this.attachedMesh.reservedDataStore.lightGizmo=this,e.parent&&this._attachedMeshParent.freezeWorldMatrix(e.parent.getWorldMatrix()),e.position&&(this.attachedMesh.position.copyFrom(e.position),this.attachedMesh.computeWorldMatrix(!0),this._cachedPosition.copyFrom(this.attachedMesh.position)),e.direction&&(this.attachedMesh.setDirection(e.direction),this.attachedMesh.computeWorldMatrix(!0),this._cachedForward.copyFrom(this.attachedMesh.forward)),this._update()}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"material",{get:function(){return this._material},enumerable:!1,configurable:!0}),t.prototype._update=function(){r.prototype._update.call(this),this._light&&(this._light.parent&&this._attachedMeshParent.freezeWorldMatrix(this._light.parent.getWorldMatrix()),this._light.position&&(this.attachedMesh.position.equals(this._cachedPosition)?(this.attachedMesh.position.copyFrom(this._light.position),this.attachedMesh.computeWorldMatrix(!0),this._cachedPosition.copyFrom(this.attachedMesh.position)):(this._light.position.copyFrom(this.attachedMesh.position),this._cachedPosition.copyFrom(this.attachedMesh.position))),this._light.direction&&(u.e.DistanceSquared(this.attachedMesh.forward,this._cachedForward)>1e-4?(this._light.direction.copyFrom(this.attachedMesh.forward),this._cachedForward.copyFrom(this.attachedMesh.forward)):u.e.DistanceSquared(this.attachedMesh.forward,this._light.direction)>1e-4&&(this.attachedMesh.setDirection(this._light.direction),this.attachedMesh.computeWorldMatrix(!0),this._cachedForward.copyFrom(this.attachedMesh.forward))))},t.prototype.dispose=function(){this.onClickedObservable.clear(),this.gizmoLayer.utilityLayerScene.onPointerObservable.remove(this._pointerObserver),this._material.dispose(),r.prototype.dispose.call(this),this._attachedMeshParent.dispose()},t._CreateHemisphericLightMesh=function(e){var n=new De.a("hemisphereLight",e),i=Zo.CreateHemisphere(n.name,{segments:10,diameter:1},e);i.position.z=-.15,i.rotation.x=Math.PI/2,i.parent=n;var o=this._CreateLightLines(3,e);return o.parent=n,o.position.z,n.scaling.scaleInPlace(t._Scale),n.rotation.x=Math.PI/2,n},t._CreatePointLightMesh=function(e){var n=new De.a("pointLight",e),i=Fn.a.CreateSphere(n.name,{segments:10,diameter:1},e);return i.rotation.x=Math.PI/2,i.parent=n,this._CreateLightLines(5,e).parent=n,n.scaling.scaleInPlace(t._Scale),n.rotation.x=Math.PI/2,n},t._CreateSpotLightMesh=function(e){var n=new De.a("spotLight",e);Fn.a.CreateSphere(n.name,{segments:10,diameter:1},e).parent=n;var i=Zo.CreateHemisphere(n.name,{segments:10,diameter:2},e);return i.parent=n,i.rotation.x=-Math.PI/2,this._CreateLightLines(2,e).parent=n,n.scaling.scaleInPlace(t._Scale),n.rotation.x=Math.PI/2,n},t._CreateDirectionalLightMesh=function(e){var n=new De.a("directionalLight",e),i=new De.a(n.name,e);i.parent=n,Fn.a.CreateSphere(n.name,{diameter:1.2,segments:10},e).parent=i;var o=De.a.CreateCylinder(n.name,6,.3,.3,6,1,e);o.parent=i,(a=o.clone(n.name)).scaling.y=.5,a.position.x+=1.25,(s=o.clone(n.name)).scaling.y=.5,s.position.x+=-1.25;var a,s,d=De.a.CreateCylinder(n.name,1,0,.6,6,1,e);return d.position.y+=3,d.parent=i,(a=d.clone(n.name)).position.y=1.5,a.position.x+=1.25,(s=d.clone(n.name)).position.y=1.5,s.position.x+=-1.25,i.scaling.scaleInPlace(t._Scale),i.rotation.z=Math.PI/2,i.rotation.y=Math.PI/2,n},t._Scale=.007,t._CreateLightLines=function(e,n){var i=new De.a("root",n);i.rotation.x=Math.PI/2;var o=new De.a("linePivot",n);o.parent=i;var a=De.a.CreateCylinder("line",2,.2,.3,6,1,n);if(a.position.y=a.scaling.y/2+1.2,a.parent=o,e<2)return o;for(var s=0;s<4;s++)(d=o.clone("lineParentClone")).rotation.z=Math.PI/4,d.rotation.y=Math.PI/2+Math.PI/2*s,d.getChildMeshes()[0].scaling.y=.5,d.getChildMeshes()[0].scaling.x=d.getChildMeshes()[0].scaling.z=.8,d.getChildMeshes()[0].position.y=d.getChildMeshes()[0].scaling.y/2+1.2;if(e<3)return i;for(s=0;s<4;s++)(d=o.clone("linePivotClone")).rotation.z=Math.PI/2,d.rotation.y=Math.PI/2*s;if(e<4)return i;for(s=0;s<4;s++){var d;(d=o.clone("linePivotClone")).rotation.z=Math.PI+Math.PI/4,d.rotation.y=Math.PI/2+Math.PI/2*s,d.getChildMeshes()[0].scaling.y=.5,d.getChildMeshes()[0].scaling.x=d.getChildMeshes()[0].scaling.z=.8,d.getChildMeshes()[0].position.y=d.getChildMeshes()[0].scaling.y/2+1.2}return e<5||((d=o.clone("linePivotClone")).rotation.z=Math.PI),i},t}(wn.a),Is=function(){function r(t,e){t===void 0&&(t=u.e.Zero()),e===void 0&&(e=u.e.Up()),this.position=t,this.normal=e}return r.prototype.clone=function(){return new r(this.position.clone(),this.normal.clone())},r}(),pp=function(){function r(t,e,n){t===void 0&&(t=u.e.Zero()),e===void 0&&(e=u.e.Up()),n===void 0&&(n=u.d.Zero()),this.position=t,this.normal=e,this.uv=n}return r.prototype.clone=function(){return new r(this.position.clone(),this.normal.clone(),this.uv.clone())},r}(),_p=function(r){function t(e){e===void 0&&(e=On.a.DefaultUtilityLayer);var n=r.call(this,e)||this;return n._pointerObserver=null,n.onClickedObservable=new x.c,n._camera=null,n._invProjection=new u.a,n._material=new Ft.a("cameraGizmoMaterial",n.gizmoLayer.utilityLayerScene),n._material.diffuseColor=new M.a(.5,.5,.5),n._material.specularColor=new M.a(.1,.1,.1),n._pointerObserver=e.utilityLayerScene.onPointerObservable.add(function(i){n._camera&&(n._isHovered=!(!i.pickInfo||n._rootMesh.getChildMeshes().indexOf(i.pickInfo.pickedMesh)==-1),n._isHovered&&i.event.button===0&&n.onClickedObservable.notifyObservers(n._camera))},Tt.a.POINTERDOWN),n}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"displayFrustum",{get:function(){return this._cameraLinesMesh.isEnabled()},set:function(e){this._cameraLinesMesh.setEnabled(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"camera",{get:function(){return this._camera},set:function(e){var n=this;if(this._camera=e,this.attachedNode=e,e){this._cameraMesh&&this._cameraMesh.dispose(),this._cameraLinesMesh&&this._cameraLinesMesh.dispose(),this._cameraMesh=t._CreateCameraMesh(this.gizmoLayer.utilityLayerScene),this._cameraLinesMesh=t._CreateCameraFrustum(this.gizmoLayer.utilityLayerScene),this._cameraMesh.getChildMeshes(!1).forEach(function(o){o.material=n._material}),this._cameraMesh.parent=this._rootMesh,this._cameraLinesMesh.parent=this._rootMesh,this.gizmoLayer.utilityLayerScene.activeCamera&&this.gizmoLayer.utilityLayerScene.activeCamera.maxZ<1.5*e.maxZ&&(this.gizmoLayer.utilityLayerScene.activeCamera.maxZ=1.5*e.maxZ),this.attachedNode.reservedDataStore||(this.attachedNode.reservedDataStore={}),this.attachedNode.reservedDataStore.cameraGizmo=this;var i=this.gizmoLayer._getSharedGizmoLight();i.includedOnlyMeshes=i.includedOnlyMeshes.concat(this._cameraMesh.getChildMeshes(!1)),this._update()}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"material",{get:function(){return this._material},enumerable:!1,configurable:!0}),t.prototype._update=function(){r.prototype._update.call(this),this._camera&&(this._camera.getProjectionMatrix().invertToRef(this._invProjection),this._cameraLinesMesh.setPivotMatrix(this._invProjection,!1),this._cameraLinesMesh.scaling.x=1/this._rootMesh.scaling.x,this._cameraLinesMesh.scaling.y=1/this._rootMesh.scaling.y,this._cameraLinesMesh.scaling.z=1/this._rootMesh.scaling.z,this._cameraMesh.parent=null,this._cameraMesh.rotation.y=.5*Math.PI*(this._camera.getScene().useRightHandedSystem?1:-1),this._cameraMesh.parent=this._rootMesh)},t.prototype.dispose=function(){this.onClickedObservable.clear(),this.gizmoLayer.utilityLayerScene.onPointerObservable.remove(this._pointerObserver),this._cameraMesh&&this._cameraMesh.dispose(),this._cameraLinesMesh&&this._cameraLinesMesh.dispose(),this._material.dispose(),r.prototype.dispose.call(this)},t._CreateCameraMesh=function(e){var n=new De.a("rootCameraGizmo",e),i=new De.a(n.name,e);i.parent=n,Tr.a.CreateBox(n.name,{width:1,height:.8,depth:.5},e).parent=i;var o=pi.a.CreateCylinder(n.name,{height:.5,diameterTop:.8,diameterBottom:.8},e);o.parent=i,o.position.y=.3,o.position.x=-.6,o.rotation.x=.5*Math.PI;var a=pi.a.CreateCylinder(n.name,{height:.5,diameterTop:.6,diameterBottom:.6},e);a.parent=i,a.position.y=.5,a.position.x=.4,a.rotation.x=.5*Math.PI;var s=pi.a.CreateCylinder(n.name,{height:.5,diameterTop:.5,diameterBottom:.5},e);return s.parent=i,s.position.y=0,s.position.x=.6,s.rotation.z=.5*Math.PI,n.scaling.scaleInPlace(t._Scale),i.position.x=-.9,n},t._CreateCameraFrustum=function(e){var n=new De.a("rootCameraGizmo",e),i=new De.a(n.name,e);i.parent=n;for(var o=0;o<4;o+=2)for(var a=0;a<4;a+=2){var s;(s=cn.a.CreateLines("lines",{points:[new u.e(-1+a,-1+o,-1),new u.e(-1+a,-1+o,1)]},e)).parent=i,s.alwaysSelectAsActiveMesh=!0,s.isPickable=!1,(s=cn.a.CreateLines("lines",{points:[new u.e(-1,-1+a,-1+o),new u.e(1,-1+a,-1+o)]},e)).parent=i,s.alwaysSelectAsActiveMesh=!0,s.isPickable=!1,(s=cn.a.CreateLines("lines",{points:[new u.e(-1+a,-1,-1+o),new u.e(-1+a,1,-1+o)]},e)).parent=i,s.alwaysSelectAsActiveMesh=!0,s.isPickable=!1}return n},t._Scale=.05,t}(wn.a);ze.a.IncludesShadersStore.kernelBlurVaryingDeclaration="varying vec2 sampleCoord{X};";var mp=`vec4 pack(float depth)
-{
-const vec4 bit_shift=vec4(255.0*255.0*255.0,255.0*255.0,255.0,1.0);
-const vec4 bit_mask=vec4(0.0,1.0/255.0,1.0/255.0,1.0/255.0);
-vec4 res=fract(depth*bit_shift);
-res-=res.xxyz*bit_mask;
-return res;
-}
-float unpack(vec4 color)
-{
-const vec4 bit_shift=vec4(1.0/(255.0*255.0*255.0),1.0/(255.0*255.0),1.0/255.0,1.0);
-return dot(color,bit_shift);
-}`;ze.a.IncludesShadersStore.packingFunctions=mp;var gp=`#ifdef DOF
-factor=sampleCoC(sampleCoord{X});
-computedWeight=KERNEL_WEIGHT{X}*factor;
-sumOfWeights+=computedWeight;
-#else
-computedWeight=KERNEL_WEIGHT{X};
-#endif
-#ifdef PACKEDFLOAT
-blend+=unpack(texture2D(textureSampler,sampleCoord{X}))*computedWeight;
-#else
-blend+=texture2D(textureSampler,sampleCoord{X})*computedWeight;
-#endif`;ze.a.IncludesShadersStore.kernelBlurFragment=gp;var vp=`#ifdef DOF
-factor=sampleCoC(sampleCenter+delta*KERNEL_DEP_OFFSET{X});
-computedWeight=KERNEL_DEP_WEIGHT{X}*factor;
-sumOfWeights+=computedWeight;
-#else
-computedWeight=KERNEL_DEP_WEIGHT{X};
-#endif
-#ifdef PACKEDFLOAT
-blend+=unpack(texture2D(textureSampler,sampleCenter+delta*KERNEL_DEP_OFFSET{X}))*computedWeight;
-#else
-blend+=texture2D(textureSampler,sampleCenter+delta*KERNEL_DEP_OFFSET{X})*computedWeight;
-#endif`;ze.a.IncludesShadersStore.kernelBlurFragment2=vp;var bp=`
-uniform sampler2D textureSampler;
-uniform vec2 delta;
-
-varying vec2 sampleCenter;
-#ifdef DOF
-uniform sampler2D circleOfConfusionSampler;
-uniform vec2 cameraMinMaxZ;
-float sampleDistance(const in vec2 offset) {
-float depth=texture2D(circleOfConfusionSampler,offset).g;
-return cameraMinMaxZ.x+(cameraMinMaxZ.y-cameraMinMaxZ.x)*depth;
-}
-float sampleCoC(const in vec2 offset) {
-float coc=texture2D(circleOfConfusionSampler,offset).r;
-return coc;
-}
-#endif
-#include<kernelBlurVaryingDeclaration>[0..varyingCount]
-#ifdef PACKEDFLOAT
-#include<packingFunctions>
-#endif
-void main(void)
-{
-float computedWeight=0.0;
-#ifdef PACKEDFLOAT
-float blend=0.;
-#else
-vec4 blend=vec4(0.);
-#endif
-#ifdef DOF
-float sumOfWeights=CENTER_WEIGHT;
-float factor=0.0;
-
-#ifdef PACKEDFLOAT
-blend+=unpack(texture2D(textureSampler,sampleCenter))*CENTER_WEIGHT;
-#else
-blend+=texture2D(textureSampler,sampleCenter)*CENTER_WEIGHT;
-#endif
-#endif
-#include<kernelBlurFragment>[0..varyingCount]
-#include<kernelBlurFragment2>[0..depCount]
-#ifdef PACKEDFLOAT
-gl_FragColor=pack(blend);
-#else
-gl_FragColor=blend;
-#endif
-#ifdef DOF
-gl_FragColor/=sumOfWeights;
-#endif
-}`;ze.a.ShadersStore.kernelBlurPixelShader=bp,ze.a.IncludesShadersStore.kernelBlurVertex="sampleCoord{X}=sampleCenter+delta*KERNEL_OFFSET{X};";var yp=`
-attribute vec2 position;
-
-uniform vec2 delta;
-
-varying vec2 sampleCenter;
-#include<kernelBlurVaryingDeclaration>[0..varyingCount]
-const vec2 madd=vec2(0.5,0.5);
-void main(void) {
-sampleCenter=(position*madd+madd);
-#include<kernelBlurVertex>[0..varyingCount]
-gl_Position=vec4(position,0.0,1.0);
-}`;ze.a.ShadersStore.kernelBlurVertexShader=yp;var gn=function(r){function t(e,n,i,o,a,s,d,p,b,P,O){s===void 0&&(s=we.a.BILINEAR_SAMPLINGMODE),b===void 0&&(b=h.a.TEXTURETYPE_UNSIGNED_INT),P===void 0&&(P=""),O===void 0&&(O=!1);var B=r.call(this,e,"kernelBlur",["delta","direction","cameraMinMaxZ"],["circleOfConfusionSampler"],o,a,s,d,p,null,b,"kernelBlur",{varyingCount:0,depCount:0},!0)||this;return B.blockCompilation=O,B._packedFloat=!1,B._staticDefines="",B._staticDefines=P,B.direction=n,B.onApplyObservable.add(function(F){B._outputTexture?F.setFloat2("delta",1/B._outputTexture.width*B.direction.x,1/B._outputTexture.height*B.direction.y):F.setFloat2("delta",1/B.width*B.direction.x,1/B.height*B.direction.y)}),B.kernel=i,B}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"kernel",{get:function(){return this._idealKernel},set:function(e){this._idealKernel!==e&&(e=Math.max(e,1),this._idealKernel=e,this._kernel=this._nearestBestKernel(e),this.blockCompilation||this._updateParameters())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"packedFloat",{get:function(){return this._packedFloat},set:function(e){this._packedFloat!==e&&(this._packedFloat=e,this.blockCompilation||this._updateParameters())},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"BlurPostProcess"},t.prototype.updateEffect=function(e,n,i,o,a,s){this._updateParameters(a,s)},t.prototype._updateParameters=function(e,n){for(var i=this._kernel,o=(i-1)/2,a=[],s=[],d=0,p=0;p<i;p++){var b=p/(i-1),P=this._gaussianWeight(2*b-1);a[p]=p-o,s[p]=P,d+=P}for(p=0;p<s.length;p++)s[p]/=d;var O=[],B=[],F=[];for(p=0;p<=o;p+=2){var z=Math.min(p+1,Math.floor(o));if(p===z)F.push({o:a[p],w:s[p]});else{var J=z===o,ie=s[p]+s[z]*(J?.5:1),se=a[p]+1/(1+s[p]/s[z]);se===0?(F.push({o:a[p],w:s[p]}),F.push({o:a[p+1],w:s[p+1]})):(F.push({o:se,w:ie}),F.push({o:-se,w:ie}))}}for(p=0;p<F.length;p++)B[p]=F[p].o,O[p]=F[p].w;a=B,s=O;var ce=this.getEngine().getCaps().maxVaryingVectors,ue=Math.max(ce,0)-1,fe=Math.min(a.length,ue),ve="";for(ve+=this._staticDefines,this._staticDefines.indexOf("DOF")!=-1&&(ve+="#define CENTER_WEIGHT "+this._glslFloat(s[fe-1])+`\r
-`,fe--),p=0;p<fe;p++)ve+="#define KERNEL_OFFSET"+p+" "+this._glslFloat(a[p])+`\r
-`,ve+="#define KERNEL_WEIGHT"+p+" "+this._glslFloat(s[p])+`\r
-`;var Te=0;for(p=ue;p<a.length;p++)ve+="#define KERNEL_DEP_OFFSET"+Te+" "+this._glslFloat(a[p])+`\r
-`,ve+="#define KERNEL_DEP_WEIGHT"+Te+" "+this._glslFloat(s[p])+`\r
-`,Te++;this.packedFloat&&(ve+="#define PACKEDFLOAT 1"),this.blockCompilation=!1,r.prototype.updateEffect.call(this,ve,null,null,{varyingCount:fe,depCount:Te},e,n)},t.prototype._nearestBestKernel=function(e){for(var n=Math.round(e),i=0,o=[n,n-1,n+1,n-2,n+2];i<o.length;i++){var a=o[i];if(a%2!=0&&Math.floor(a/2)%2==0&&a>0)return Math.max(a,3)}return Math.max(n,3)},t.prototype._gaussianWeight=function(e){var n=-e*e/.2222222222222222;return 1/(Math.sqrt(2*Math.PI)*(1/3))*Math.exp(n)},t.prototype._glslFloat=function(e,n){return n===void 0&&(n=8),e.toFixed(n).replace(/0+$/,"")},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.direction,e.kernel,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable,e.textureType,void 0,!1)},e,i,o)},Object(c.c)([Object(L.c)("kernel")],t.prototype,"_kernel",void 0),Object(c.c)([Object(L.c)("packedFloat")],t.prototype,"_packedFloat",void 0),Object(c.c)([Object(L.n)()],t.prototype,"direction",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.BlurPostProcess"]=gn;var Ds=function(r){function t(e,n,i,o,a,s,d){a===void 0&&(a=h.a.TEXTURETYPE_UNSIGNED_INT),s===void 0&&(s=we.a.BILINEAR_SAMPLINGMODE),d===void 0&&(d=!0);var p=r.call(this,e,n,i,o,!0,a,!1,s,d)||this;return p.scene=i,p.mirrorPlane=new vr.a(0,1,0,1),p._transformMatrix=u.a.Zero(),p._mirrorMatrix=u.a.Zero(),p._adaptiveBlurKernel=0,p._blurKernelX=0,p._blurKernelY=0,p._blurRatio=1,p.ignoreCameraViewport=!0,p._updateGammaSpace(),p._imageProcessingConfigChangeObserver=i.imageProcessingConfiguration.onUpdateParameters.add(function(){p._updateGammaSpace}),p.onBeforeRenderObservable.add(function(){u.a.ReflectionToRef(p.mirrorPlane,p._mirrorMatrix),p._savedViewMatrix=i.getViewMatrix(),p._mirrorMatrix.multiplyToRef(p._savedViewMatrix,p._transformMatrix),i.setTransformMatrix(p._transformMatrix,i.getProjectionMatrix()),i.clipPlane=p.mirrorPlane,i.getEngine().cullBackFaces=!1,i._mirroredCameraPosition=u.e.TransformCoordinates(i.activeCamera.globalPosition,p._mirrorMatrix)}),p.onAfterRenderObservable.add(function(){i.setTransformMatrix(p._savedViewMatrix,i.getProjectionMatrix()),i.getEngine().cullBackFaces=!0,i._mirroredCameraPosition=null,i.clipPlane=null}),p}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"blurRatio",{get:function(){return this._blurRatio},set:function(e){this._blurRatio!==e&&(this._blurRatio=e,this._preparePostProcesses())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"adaptiveBlurKernel",{set:function(e){this._adaptiveBlurKernel=e,this._autoComputeBlurKernel()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"blurKernel",{set:function(e){this.blurKernelX=e,this.blurKernelY=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"blurKernelX",{get:function(){return this._blurKernelX},set:function(e){this._blurKernelX!==e&&(this._blurKernelX=e,this._preparePostProcesses())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"blurKernelY",{get:function(){return this._blurKernelY},set:function(e){this._blurKernelY!==e&&(this._blurKernelY=e,this._preparePostProcesses())},enumerable:!1,configurable:!0}),t.prototype._autoComputeBlurKernel=function(){var e=this.getScene().getEngine(),n=this.getRenderWidth()/e.getRenderWidth(),i=this.getRenderHeight()/e.getRenderHeight();this.blurKernelX=this._adaptiveBlurKernel*n,this.blurKernelY=this._adaptiveBlurKernel*i},t.prototype._onRatioRescale=function(){this._sizeRatio&&(this.resize(this._initialSizeParameter),this._adaptiveBlurKernel||this._preparePostProcesses()),this._adaptiveBlurKernel&&this._autoComputeBlurKernel()},t.prototype._updateGammaSpace=function(){this.gammaSpace=!this.scene.imageProcessingConfiguration.isEnabled||!this.scene.imageProcessingConfiguration.applyByPostProcess},t.prototype._preparePostProcesses=function(){if(this.clearPostProcesses(!0),this._blurKernelX&&this._blurKernelY){var e=this.getScene().getEngine(),n=e.getCaps().textureFloatRender?h.a.TEXTURETYPE_FLOAT:h.a.TEXTURETYPE_HALF_FLOAT;this._blurX=new gn("horizontal blur",new u.d(1,0),this._blurKernelX,this._blurRatio,null,we.a.BILINEAR_SAMPLINGMODE,e,!1,n),this._blurX.autoClear=!1,this._blurRatio===1&&this.samples<2&&this._texture?this._blurX.inputTexture=this._texture:this._blurX.alwaysForcePOT=!0,this._blurY=new gn("vertical blur",new u.d(0,1),this._blurKernelY,this._blurRatio,null,we.a.BILINEAR_SAMPLINGMODE,e,!1,n),this._blurY.autoClear=!1,this._blurY.alwaysForcePOT=this._blurRatio!==1,this.addPostProcess(this._blurX),this.addPostProcess(this._blurY)}else this._blurY&&(this.removePostProcess(this._blurY),this._blurY.dispose(),this._blurY=null),this._blurX&&(this.removePostProcess(this._blurX),this._blurX.dispose(),this._blurX=null)},t.prototype.clone=function(){var e=this.getScene();if(!e)return this;var n=this.getSize(),i=new t(this.name,n.width,e,this._renderTargetOptions.generateMipMaps,this._renderTargetOptions.type,this._renderTargetOptions.samplingMode,this._renderTargetOptions.generateDepthBuffer);return i.hasAlpha=this.hasAlpha,i.level=this.level,i.mirrorPlane=this.mirrorPlane.clone(),this.renderList&&(i.renderList=this.renderList.slice(0)),i},t.prototype.serialize=function(){if(!this.name)return null;var e=r.prototype.serialize.call(this);return e.mirrorPlane=this.mirrorPlane.asArray(),e},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.scene.imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingConfigChangeObserver)},t}(sn);we.a._CreateMirror=function(r,t,e,n){return new Ds(r,t,e,n)};var Qn=f(34),ai=function(r){function t(e,n,i,o,a,s,d,p,b,P,O,B,F,z){var J;i===void 0&&(i=null),o===void 0&&(o=!1),a===void 0&&(a=null),s===void 0&&(s=null),d===void 0&&(d=null),p===void 0&&(p=h.a.TEXTUREFORMAT_RGBA),b===void 0&&(b=!1),P===void 0&&(P=null),O===void 0&&(O=!1),B===void 0&&(B=.8),F===void 0&&(F=0);var ie=r.call(this,n)||this;if(ie.onLoadObservable=new x.c,ie.boundingBoxPosition=u.e.Zero(),ie._rotationY=0,ie._files=null,ie._forcedExtension=null,ie._extensions=null,ie.name=e,ie.url=e,ie._noMipmap=o,ie.hasAlpha=!1,ie._format=p,ie.isCube=!0,ie._textureMatrix=u.a.Identity(),ie._createPolynomials=O,ie.coordinatesMode=we.a.CUBIC_MODE,ie._extensions=i,ie._files=a,ie._forcedExtension=P,ie._loaderOptions=z,!e&&!a)return ie;var se=e.lastIndexOf("."),ce=P||(se>-1?e.substring(se).toLowerCase():""),ue=ce===".dds",fe=ce===".env";if(fe?(ie.gammaSpace=!1,ie._prefiltered=!1,ie.anisotropicFilteringLevel=1):(ie._prefiltered=b,b&&(ie.gammaSpace=!1,ie.anisotropicFilteringLevel=1)),ie._texture=ie._getFromCache(e,o),!a&&(fe||ue||i||(i=["_px.jpg","_py.jpg","_pz.jpg","_nx.jpg","_ny.jpg","_nz.jpg"]),a=[],i))for(var ve=0;ve<i.length;ve++)a.push(e+i[ve]);ie._files=a;var Te=function(){ie.onLoadObservable.notifyObservers(ie),s&&s()};if(ie._texture)ie._texture.isReady?Xe.b.SetImmediate(function(){return Te()}):ie._texture.onLoadedObservable.add(function(){return Te()});else{var Re=ie.getScene();Re?.useDelayedTextureLoading?ie.delayLoadState=h.a.DELAYLOADSTATE_NOTLOADED:(ie._texture=b?ie._getEngine().createPrefilteredCubeTexture(e,Re,B,F,s,d,p,P,ie._createPolynomials):ie._getEngine().createCubeTexture(e,Re,a,o,s,d,ie._format,P,!1,B,F,null,z),(J=ie._texture)===null||J===void 0||J.onLoadedObservable.add(function(){return ie.onLoadObservable.notifyObservers(ie)}))}return ie}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"boundingBoxSize",{get:function(){return this._boundingBoxSize},set:function(e){if(!this._boundingBoxSize||!this._boundingBoxSize.equals(e)){this._boundingBoxSize=e;var n=this.getScene();n&&n.markAllMaterialsAsDirty(h.a.MATERIAL_TextureDirtyFlag)}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rotationY",{get:function(){return this._rotationY},set:function(e){this._rotationY=e,this.setReflectionTextureMatrix(u.a.RotationY(this._rotationY))},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"noMipmap",{get:function(){return this._noMipmap},enumerable:!1,configurable:!0}),t.CreateFromImages=function(e,n,i){var o="";return e.forEach(function(a){return o+=a}),new t(o,n,null,i,e)},t.CreateFromPrefilteredData=function(e,n,i,o){i===void 0&&(i=null),o===void 0&&(o=!0);var a=n.useDelayedTextureLoading;n.useDelayedTextureLoading=!1;var s=new t(e,n,null,!1,null,null,null,void 0,!0,i,o);return n.useDelayedTextureLoading=a,s},t.prototype.getClassName=function(){return"CubeTexture"},t.prototype.updateURL=function(e,n,i,o){var a;o===void 0&&(o=!1),this.url&&(this.releaseInternalTexture(),(a=this.getScene())===null||a===void 0||a.markAllMaterialsAsDirty(h.a.MATERIAL_TextureDirtyFlag)),this.name&&!Qn.a.StartsWith(this.name,"data:")||(this.name=e),this.url=e,this.delayLoadState=h.a.DELAYLOADSTATE_NOTLOADED,this._prefiltered=o,this._prefiltered&&(this.gammaSpace=!1,this.anisotropicFilteringLevel=1),this._forcedExtension=n||null,i&&(this._delayedOnLoad=i),this.delayLoad(n)},t.prototype.delayLoad=function(e){var n,i=this;if(this.delayLoadState===h.a.DELAYLOADSTATE_NOTLOADED&&(this.delayLoadState=h.a.DELAYLOADSTATE_LOADED,this._texture=this._getFromCache(this.url,this._noMipmap),!this._texture)){var o=this.getScene();this._prefiltered?this._texture=this._getEngine().createPrefilteredCubeTexture(this.url,o,.8,0,this._delayedOnLoad,void 0,this._format,e,this._createPolynomials):this._texture=this._getEngine().createCubeTexture(this.url,o,this._files,this._noMipmap,this._delayedOnLoad,null,this._format,e,!1,0,0,null,this._loaderOptions),(n=this._texture)===null||n===void 0||n.onLoadedObservable.add(function(){return i.onLoadObservable.notifyObservers(i)})}},t.prototype.getReflectionTextureMatrix=function(){return this._textureMatrix},t.prototype.setReflectionTextureMatrix=function(e){var n,i=this;e.updateFlag!==this._textureMatrix.updateFlag&&(e.isIdentity()!==this._textureMatrix.isIdentity()&&((n=this.getScene())===null||n===void 0||n.markAllMaterialsAsDirty(h.a.MATERIAL_TextureDirtyFlag,function(o){return o.getActiveTextures().indexOf(i)!==-1})),this._textureMatrix=e)},t.Parse=function(e,n,i){var o=L.a.Parse(function(){var p=!1;return e.prefiltered&&(p=e.prefiltered),new t(i+e.name,n,e.extensions,!1,e.files||null,null,null,void 0,p,e.forcedExtension)},e,n);if(e.boundingBoxPosition&&(o.boundingBoxPosition=u.e.FromArray(e.boundingBoxPosition)),e.boundingBoxSize&&(o.boundingBoxSize=u.e.FromArray(e.boundingBoxSize)),e.animations)for(var a=0;a<e.animations.length;a++){var s=e.animations[a],d=R.a.GetClass("BABYLON.Animation");d&&o.animations.push(d.Parse(s))}return o},t.prototype.clone=function(){var e=this,n=0,i=L.a.Clone(function(){var o=new t(e.url,e.getScene()||e._getEngine(),e._extensions,e._noMipmap,e._files);return n=o.uniqueId,o},this);return i.uniqueId=n,i},Object(c.c)([Object(L.c)()],t.prototype,"url",void 0),Object(c.c)([Object(L.c)("rotationY")],t.prototype,"rotationY",null),Object(c.c)([Object(L.c)("files")],t.prototype,"_files",void 0),Object(c.c)([Object(L.c)("forcedExtension")],t.prototype,"_forcedExtension",void 0),Object(c.c)([Object(L.c)("extensions")],t.prototype,"_extensions",void 0),Object(c.c)([Object(L.j)("textureMatrix")],t.prototype,"_textureMatrix",void 0),t}(zn.a);we.a._CubeTextureParser=ai.Parse,R.a.RegisteredTypes["BABYLON.CubeTexture"]=ai;var et=f(15),Jo=f(76),$o=f(87),ht=f(19),Tp=` uniform vec4 vPrimaryColor;
-#ifdef USEHIGHLIGHTANDSHADOWCOLORS
-uniform vec4 vPrimaryColorShadow;
-#endif
-uniform float shadowLevel;
-uniform float alpha;
-#ifdef DIFFUSE
-uniform vec2 vDiffuseInfos;
-#endif
-#ifdef REFLECTION
-uniform vec2 vReflectionInfos;
-uniform mat4 reflectionMatrix;
-uniform vec3 vReflectionMicrosurfaceInfos;
-#endif
-#if defined(REFLECTIONFRESNEL) || defined(OPACITYFRESNEL)
-uniform vec3 vBackgroundCenter;
-#endif
-#ifdef REFLECTIONFRESNEL
-uniform vec4 vReflectionControl;
-#endif
-#if defined(REFLECTIONMAP_SPHERICAL) || defined(REFLECTIONMAP_PROJECTION) || defined(REFRACTION)
-uniform mat4 view;
-#endif`;ze.a.IncludesShadersStore.backgroundFragmentDeclaration=Tp;var Ep=`layout(std140,column_major) uniform;
-uniform Material
-{
-uniform vec4 vPrimaryColor;
-uniform vec4 vPrimaryColorShadow;
-uniform vec2 vDiffuseInfos;
-uniform vec2 vReflectionInfos;
-uniform mat4 diffuseMatrix;
-uniform mat4 reflectionMatrix;
-uniform vec3 vReflectionMicrosurfaceInfos;
-uniform float fFovMultiplier;
-uniform float pointSize;
-uniform float shadowLevel;
-uniform float alpha;
-#if defined(REFLECTIONFRESNEL) || defined(OPACITYFRESNEL)
-uniform vec3 vBackgroundCenter;
-#endif
-#ifdef REFLECTIONFRESNEL
-uniform vec4 vReflectionControl;
-#endif
-};
-uniform Scene {
-mat4 viewProjection;
-#ifdef MULTIVIEW
-mat4 viewProjectionR;
-#endif
-mat4 view;
-};`;ze.a.IncludesShadersStore.backgroundUboDeclaration=Ep,f(131),f(106),f(107),f(154),f(130),f(115),f(125),f(110),f(135),f(136);var Sp=`#ifdef TEXTURELODSUPPORT
-#extension GL_EXT_shader_texture_lod : enable
-#endif
-precision highp float;
-#include<__decl__backgroundFragment>
-#define RECIPROCAL_PI2 0.15915494
-
-uniform vec3 vEyePosition;
-
-varying vec3 vPositionW;
-#ifdef MAINUV1
-varying vec2 vMainUV1;
-#endif
-#ifdef MAINUV2
-varying vec2 vMainUV2;
-#endif
-#ifdef NORMAL
-varying vec3 vNormalW;
-#endif
-#ifdef DIFFUSE
-#if DIFFUSEDIRECTUV == 1
-#define vDiffuseUV vMainUV1
-#elif DIFFUSEDIRECTUV == 2
-#define vDiffuseUV vMainUV2
-#else
-varying vec2 vDiffuseUV;
-#endif
-uniform sampler2D diffuseSampler;
-#endif
-
-#ifdef REFLECTION
-#ifdef REFLECTIONMAP_3D
-#define sampleReflection(s,c) textureCube(s,c)
-uniform samplerCube reflectionSampler;
-#ifdef TEXTURELODSUPPORT
-#define sampleReflectionLod(s,c,l) textureCubeLodEXT(s,c,l)
-#else
-uniform samplerCube reflectionSamplerLow;
-uniform samplerCube reflectionSamplerHigh;
-#endif
-#else
-#define sampleReflection(s,c) texture2D(s,c)
-uniform sampler2D reflectionSampler;
-#ifdef TEXTURELODSUPPORT
-#define sampleReflectionLod(s,c,l) texture2DLodEXT(s,c,l)
-#else
-uniform samplerCube reflectionSamplerLow;
-uniform samplerCube reflectionSamplerHigh;
-#endif
-#endif
-#ifdef REFLECTIONMAP_SKYBOX
-varying vec3 vPositionUVW;
-#else
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
-varying vec3 vDirectionW;
-#endif
-#endif
-#include<reflectionFunction>
-#endif
-
-#ifndef FROMLINEARSPACE
-#define FROMLINEARSPACE;
-#endif
-
-#ifndef SHADOWONLY
-#define SHADOWONLY;
-#endif
-#include<imageProcessingDeclaration>
-
-#include<__decl__lightFragment>[0..maxSimultaneousLights]
-#include<helperFunctions>
-#include<lightsFragmentFunctions>
-#include<shadowsFragmentFunctions>
-#include<imageProcessingFunctions>
-#include<clipPlaneFragmentDeclaration>
-
-#include<fogFragmentDeclaration>
-#ifdef REFLECTIONFRESNEL
-#define FRESNEL_MAXIMUM_ON_ROUGH 0.25
-vec3 fresnelSchlickEnvironmentGGX(float VdotN,vec3 reflectance0,vec3 reflectance90,float smoothness)
-{
-
-float weight=mix(FRESNEL_MAXIMUM_ON_ROUGH,1.0,smoothness);
-return reflectance0+weight*(reflectance90-reflectance0)*pow5(saturate(1.0-VdotN));
-}
-#endif
-void main(void) {
-#include<clipPlaneFragment>
-vec3 viewDirectionW=normalize(vEyePosition-vPositionW);
-
-#ifdef NORMAL
-vec3 normalW=normalize(vNormalW);
-#else
-vec3 normalW=vec3(0.0,1.0,0.0);
-#endif
-
-float shadow=1.;
-float globalShadow=0.;
-float shadowLightCount=0.;
-#include<lightFragment>[0..maxSimultaneousLights]
-#ifdef SHADOWINUSE
-globalShadow/=shadowLightCount;
-#else
-globalShadow=1.0;
-#endif
-#ifndef BACKMAT_SHADOWONLY
-
-vec4 reflectionColor=vec4(1.,1.,1.,1.);
-#ifdef REFLECTION
-vec3 reflectionVector=computeReflectionCoords(vec4(vPositionW,1.0),normalW);
-#ifdef REFLECTIONMAP_OPPOSITEZ
-reflectionVector.z*=-1.0;
-#endif
-
-#ifdef REFLECTIONMAP_3D
-vec3 reflectionCoords=reflectionVector;
-#else
-vec2 reflectionCoords=reflectionVector.xy;
-#ifdef REFLECTIONMAP_PROJECTION
-reflectionCoords/=reflectionVector.z;
-#endif
-reflectionCoords.y=1.0-reflectionCoords.y;
-#endif
-#ifdef REFLECTIONBLUR
-float reflectionLOD=vReflectionInfos.y;
-#ifdef TEXTURELODSUPPORT
-
-reflectionLOD=reflectionLOD*log2(vReflectionMicrosurfaceInfos.x)*vReflectionMicrosurfaceInfos.y+vReflectionMicrosurfaceInfos.z;
-reflectionColor=sampleReflectionLod(reflectionSampler,reflectionCoords,reflectionLOD);
-#else
-float lodReflectionNormalized=saturate(reflectionLOD);
-float lodReflectionNormalizedDoubled=lodReflectionNormalized*2.0;
-vec4 reflectionSpecularMid=sampleReflection(reflectionSampler,reflectionCoords);
-if(lodReflectionNormalizedDoubled<1.0){
-reflectionColor=mix(
-sampleReflection(reflectionSamplerHigh,reflectionCoords),
-reflectionSpecularMid,
-lodReflectionNormalizedDoubled
-);
-} else {
-reflectionColor=mix(
-reflectionSpecularMid,
-sampleReflection(reflectionSamplerLow,reflectionCoords),
-lodReflectionNormalizedDoubled-1.0
-);
-}
-#endif
-#else
-vec4 reflectionSample=sampleReflection(reflectionSampler,reflectionCoords);
-reflectionColor=reflectionSample;
-#endif
-#ifdef RGBDREFLECTION
-reflectionColor.rgb=fromRGBD(reflectionColor);
-#endif
-#ifdef GAMMAREFLECTION
-reflectionColor.rgb=toLinearSpace(reflectionColor.rgb);
-#endif
-#ifdef REFLECTIONBGR
-reflectionColor.rgb=reflectionColor.bgr;
-#endif
-
-reflectionColor.rgb*=vReflectionInfos.x;
-#endif
-
-vec3 diffuseColor=vec3(1.,1.,1.);
-float finalAlpha=alpha;
-#ifdef DIFFUSE
-vec4 diffuseMap=texture2D(diffuseSampler,vDiffuseUV);
-#ifdef GAMMADIFFUSE
-diffuseMap.rgb=toLinearSpace(diffuseMap.rgb);
-#endif
-
-diffuseMap.rgb*=vDiffuseInfos.y;
-#ifdef DIFFUSEHASALPHA
-finalAlpha*=diffuseMap.a;
-#endif
-diffuseColor=diffuseMap.rgb;
-#endif
-
-#ifdef REFLECTIONFRESNEL
-vec3 colorBase=diffuseColor;
-#else
-vec3 colorBase=reflectionColor.rgb*diffuseColor;
-#endif
-colorBase=max(colorBase,0.0);
-
-#ifdef USERGBCOLOR
-vec3 finalColor=colorBase;
-#else
-#ifdef USEHIGHLIGHTANDSHADOWCOLORS
-vec3 mainColor=mix(vPrimaryColorShadow.rgb,vPrimaryColor.rgb,colorBase);
-#else
-vec3 mainColor=vPrimaryColor.rgb;
-#endif
-vec3 finalColor=colorBase*mainColor;
-#endif
-
-#ifdef REFLECTIONFRESNEL
-vec3 reflectionAmount=vReflectionControl.xxx;
-vec3 reflectionReflectance0=vReflectionControl.yyy;
-vec3 reflectionReflectance90=vReflectionControl.zzz;
-float VdotN=dot(normalize(vEyePosition),normalW);
-vec3 planarReflectionFresnel=fresnelSchlickEnvironmentGGX(saturate(VdotN),reflectionReflectance0,reflectionReflectance90,1.0);
-reflectionAmount*=planarReflectionFresnel;
-#ifdef REFLECTIONFALLOFF
-float reflectionDistanceFalloff=1.0-saturate(length(vPositionW.xyz-vBackgroundCenter)*vReflectionControl.w);
-reflectionDistanceFalloff*=reflectionDistanceFalloff;
-reflectionAmount*=reflectionDistanceFalloff;
-#endif
-finalColor=mix(finalColor,reflectionColor.rgb,saturate(reflectionAmount));
-#endif
-#ifdef OPACITYFRESNEL
-float viewAngleToFloor=dot(normalW,normalize(vEyePosition-vBackgroundCenter));
-
-const float startAngle=0.1;
-float fadeFactor=saturate(viewAngleToFloor/startAngle);
-finalAlpha*=fadeFactor*fadeFactor;
-#endif
-
-#ifdef SHADOWINUSE
-finalColor=mix(finalColor*shadowLevel,finalColor,globalShadow);
-#endif
-
-vec4 color=vec4(finalColor,finalAlpha);
-#else
-vec4 color=vec4(vPrimaryColor.rgb,(1.0-clamp(globalShadow,0.,1.))*alpha);
-#endif
-#include<fogFragment>
-#ifdef IMAGEPROCESSINGPOSTPROCESS
-
-
-color.rgb=clamp(color.rgb,0.,30.0);
-#else
-
-color=applyImageProcessing(color);
-#endif
-#ifdef PREMULTIPLYALPHA
-
-color.rgb*=color.a;
-#endif
-#ifdef NOISE
-color.rgb+=dither(vPositionW.xy,0.5);
-color=max(color,0.0);
-#endif
-gl_FragColor=color;
-}
-`;ze.a.ShadersStore.backgroundPixelShader=Sp;var Ap=`uniform mat4 view;
-uniform mat4 viewProjection;
-uniform float shadowLevel;
-#ifdef DIFFUSE
-uniform mat4 diffuseMatrix;
-uniform vec2 vDiffuseInfos;
-#endif
-#ifdef REFLECTION
-uniform vec2 vReflectionInfos;
-uniform mat4 reflectionMatrix;
-uniform vec3 vReflectionMicrosurfaceInfos;
-uniform float fFovMultiplier;
-#endif
-#ifdef POINTSIZE
-uniform float pointSize;
-#endif`;ze.a.IncludesShadersStore.backgroundVertexDeclaration=Ap,f(78),f(79),f(117),f(137),f(80),f(81),f(111),f(157),f(138);var Pp=`precision highp float;
-#include<__decl__backgroundVertex>
-#include<helperFunctions>
-
-attribute vec3 position;
-#ifdef NORMAL
-attribute vec3 normal;
-#endif
-#include<bonesDeclaration>
-
-#include<instancesDeclaration>
-
-varying vec3 vPositionW;
-#ifdef NORMAL
-varying vec3 vNormalW;
-#endif
-#ifdef UV1
-attribute vec2 uv;
-#endif
-#ifdef UV2
-attribute vec2 uv2;
-#endif
-#ifdef MAINUV1
-varying vec2 vMainUV1;
-#endif
-#ifdef MAINUV2
-varying vec2 vMainUV2;
-#endif
-#if defined(DIFFUSE) && DIFFUSEDIRECTUV == 0
-varying vec2 vDiffuseUV;
-#endif
-#include<clipPlaneVertexDeclaration>
-#include<fogVertexDeclaration>
-#include<__decl__lightFragment>[0..maxSimultaneousLights]
-#ifdef REFLECTIONMAP_SKYBOX
-varying vec3 vPositionUVW;
-#endif
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
-varying vec3 vDirectionW;
-#endif
-void main(void) {
-#ifdef REFLECTIONMAP_SKYBOX
-vPositionUVW=position;
-#endif
-#include<instancesVertex>
-#include<bonesVertex>
-#ifdef MULTIVIEW
-if (gl_ViewID_OVR == 0u) {
-gl_Position=viewProjection*finalWorld*vec4(position,1.0);
-} else {
-gl_Position=viewProjectionR*finalWorld*vec4(position,1.0);
-}
-#else
-gl_Position=viewProjection*finalWorld*vec4(position,1.0);
-#endif
-vec4 worldPos=finalWorld*vec4(position,1.0);
-vPositionW=vec3(worldPos);
-#ifdef NORMAL
-mat3 normalWorld=mat3(finalWorld);
-#ifdef NONUNIFORMSCALING
-normalWorld=transposeMat3(inverseMat3(normalWorld));
-#endif
-vNormalW=normalize(normalWorld*normal);
-#endif
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
-vDirectionW=normalize(vec3(finalWorld*vec4(position,0.0)));
-#ifdef EQUIRECTANGULAR_RELFECTION_FOV
-mat3 screenToWorld=inverseMat3(mat3(finalWorld*viewProjection));
-vec3 segment=mix(vDirectionW,screenToWorld*vec3(0.0,0.0,1.0),abs(fFovMultiplier-1.0));
-if (fFovMultiplier<=1.0) {
-vDirectionW=normalize(segment);
-} else {
-vDirectionW=normalize(vDirectionW+(vDirectionW-segment));
-}
-#endif
-#endif
-#ifndef UV1
-vec2 uv=vec2(0.,0.);
-#endif
-#ifndef UV2
-vec2 uv2=vec2(0.,0.);
-#endif
-#ifdef MAINUV1
-vMainUV1=uv;
-#endif
-#ifdef MAINUV2
-vMainUV2=uv2;
-#endif
-#if defined(DIFFUSE) && DIFFUSEDIRECTUV == 0
-if (vDiffuseInfos.x == 0.)
-{
-vDiffuseUV=vec2(diffuseMatrix*vec4(uv,1.0,0.0));
-}
-else
-{
-vDiffuseUV=vec2(diffuseMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-
-#include<clipPlaneVertex>
-
-#include<fogVertex>
-
-#include<shadowsVertex>[0..maxSimultaneousLights]
-
-#ifdef VERTEXCOLOR
-vColor=color;
-#endif
-
-#ifdef POINTSIZE
-gl_PointSize=pointSize;
-#endif
-}
-`;ze.a.ShadersStore.backgroundVertexShader=Pp;var Sr=f(67),Cp=function(r){function t(){var e=r.call(this)||this;return e.DIFFUSE=!1,e.DIFFUSEDIRECTUV=0,e.GAMMADIFFUSE=!1,e.DIFFUSEHASALPHA=!1,e.OPACITYFRESNEL=!1,e.REFLECTIONBLUR=!1,e.REFLECTIONFRESNEL=!1,e.REFLECTIONFALLOFF=!1,e.TEXTURELODSUPPORT=!1,e.PREMULTIPLYALPHA=!1,e.USERGBCOLOR=!1,e.USEHIGHLIGHTANDSHADOWCOLORS=!1,e.BACKMAT_SHADOWONLY=!1,e.NOISE=!1,e.REFLECTIONBGR=!1,e.IMAGEPROCESSING=!1,e.VIGNETTE=!1,e.VIGNETTEBLENDMODEMULTIPLY=!1,e.VIGNETTEBLENDMODEOPAQUE=!1,e.TONEMAPPING=!1,e.TONEMAPPING_ACES=!1,e.CONTRAST=!1,e.COLORCURVES=!1,e.COLORGRADING=!1,e.COLORGRADING3D=!1,e.SAMPLER3DGREENDEPTH=!1,e.SAMPLER3DBGRMAP=!1,e.IMAGEPROCESSINGPOSTPROCESS=!1,e.EXPOSURE=!1,e.MULTIVIEW=!1,e.REFLECTION=!1,e.REFLECTIONMAP_3D=!1,e.REFLECTIONMAP_SPHERICAL=!1,e.REFLECTIONMAP_PLANAR=!1,e.REFLECTIONMAP_CUBIC=!1,e.REFLECTIONMAP_PROJECTION=!1,e.REFLECTIONMAP_SKYBOX=!1,e.REFLECTIONMAP_EXPLICIT=!1,e.REFLECTIONMAP_EQUIRECTANGULAR=!1,e.REFLECTIONMAP_EQUIRECTANGULAR_FIXED=!1,e.REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED=!1,e.INVERTCUBICMAP=!1,e.REFLECTIONMAP_OPPOSITEZ=!1,e.LODINREFLECTIONALPHA=!1,e.GAMMAREFLECTION=!1,e.RGBDREFLECTION=!1,e.EQUIRECTANGULAR_RELFECTION_FOV=!1,e.MAINUV1=!1,e.MAINUV2=!1,e.UV1=!1,e.UV2=!1,e.CLIPPLANE=!1,e.CLIPPLANE2=!1,e.CLIPPLANE3=!1,e.CLIPPLANE4=!1,e.CLIPPLANE5=!1,e.CLIPPLANE6=!1,e.POINTSIZE=!1,e.FOG=!1,e.NORMAL=!1,e.NUM_BONE_INFLUENCERS=0,e.BonesPerMesh=0,e.INSTANCES=!1,e.SHADOWFLOAT=!1,e.rebuild(),e}return Object(c.d)(t,r),t}(Jo.a),so=function(r){function t(e,n){var i=r.call(this,e,n)||this;return i.primaryColor=M.a.White(),i._primaryColorShadowLevel=0,i._primaryColorHighlightLevel=0,i.reflectionTexture=null,i.reflectionBlur=0,i.diffuseTexture=null,i._shadowLights=null,i.shadowLights=null,i.shadowLevel=0,i.sceneCenter=u.e.Zero(),i.opacityFresnel=!0,i.reflectionFresnel=!1,i.reflectionFalloffDistance=0,i.reflectionAmount=1,i.reflectionReflectance0=.05,i.reflectionReflectance90=.5,i.useRGBColor=!0,i.enableNoise=!1,i._fovMultiplier=1,i.useEquirectangularFOV=!1,i._maxSimultaneousLights=4,i.maxSimultaneousLights=4,i._shadowOnly=!1,i.shadowOnly=!1,i._imageProcessingObserver=null,i.switchToBGR=!1,i._renderTargets=new fi.a(16),i._reflectionControls=u.f.Zero(),i._white=M.a.White(),i._primaryShadowColor=M.a.Black(),i._primaryHighlightColor=M.a.Black(),i._attachImageProcessingConfiguration(null),i.getRenderTargetTextures=function(){return i._renderTargets.reset(),i._diffuseTexture&&i._diffuseTexture.isRenderTarget&&i._renderTargets.push(i._diffuseTexture),i._reflectionTexture&&i._reflectionTexture.isRenderTarget&&i._renderTargets.push(i._reflectionTexture),i._renderTargets},i}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"_perceptualColor",{get:function(){return this.__perceptualColor},set:function(e){this.__perceptualColor=e,this._computePrimaryColorFromPerceptualColor(),this._markAllSubMeshesAsLightsDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"primaryColorShadowLevel",{get:function(){return this._primaryColorShadowLevel},set:function(e){this._primaryColorShadowLevel=e,this._computePrimaryColors(),this._markAllSubMeshesAsLightsDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"primaryColorHighlightLevel",{get:function(){return this._primaryColorHighlightLevel},set:function(e){this._primaryColorHighlightLevel=e,this._computePrimaryColors(),this._markAllSubMeshesAsLightsDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"reflectionStandardFresnelWeight",{set:function(e){var n=e;n<.5?(n*=2,this.reflectionReflectance0=t.StandardReflectance0*n,this.reflectionReflectance90=t.StandardReflectance90*n):(n=2*n-1,this.reflectionReflectance0=t.StandardReflectance0+(1-t.StandardReflectance0)*n,this.reflectionReflectance90=t.StandardReflectance90+(1-t.StandardReflectance90)*n)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"fovMultiplier",{get:function(){return this._fovMultiplier},set:function(e){isNaN(e)&&(e=1),this._fovMultiplier=Math.max(0,Math.min(2,e))},enumerable:!1,configurable:!0}),t.prototype._attachImageProcessingConfiguration=function(e){var n=this;e!==this._imageProcessingConfiguration&&(this._imageProcessingConfiguration&&this._imageProcessingObserver&&this._imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingObserver),this._imageProcessingConfiguration=e||this.getScene().imageProcessingConfiguration,this._imageProcessingConfiguration&&(this._imageProcessingObserver=this._imageProcessingConfiguration.onUpdateParameters.add(function(){n._computePrimaryColorFromPerceptualColor(),n._markAllSubMeshesAsImageProcessingDirty()})))},Object.defineProperty(t.prototype,"imageProcessingConfiguration",{get:function(){return this._imageProcessingConfiguration},set:function(e){this._attachImageProcessingConfiguration(e),this._markAllSubMeshesAsTexturesDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraColorCurvesEnabled",{get:function(){return this.imageProcessingConfiguration.colorCurvesEnabled},set:function(e){this.imageProcessingConfiguration.colorCurvesEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraColorGradingEnabled",{get:function(){return this.imageProcessingConfiguration.colorGradingEnabled},set:function(e){this.imageProcessingConfiguration.colorGradingEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraToneMappingEnabled",{get:function(){return this._imageProcessingConfiguration.toneMappingEnabled},set:function(e){this._imageProcessingConfiguration.toneMappingEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraExposure",{get:function(){return this._imageProcessingConfiguration.exposure},set:function(e){this._imageProcessingConfiguration.exposure=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraContrast",{get:function(){return this._imageProcessingConfiguration.contrast},set:function(e){this._imageProcessingConfiguration.contrast=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraColorGradingTexture",{get:function(){return this._imageProcessingConfiguration.colorGradingTexture},set:function(e){this.imageProcessingConfiguration.colorGradingTexture=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraColorCurves",{get:function(){return this.imageProcessingConfiguration.colorCurves},set:function(e){this.imageProcessingConfiguration.colorCurves=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"hasRenderTargetTextures",{get:function(){return!(!this._diffuseTexture||!this._diffuseTexture.isRenderTarget)||!(!this._reflectionTexture||!this._reflectionTexture.isRenderTarget)},enumerable:!1,configurable:!0}),t.prototype.needAlphaTesting=function(){return!0},t.prototype.needAlphaBlending=function(){return this.alpha<1||this._diffuseTexture!=null&&this._diffuseTexture.hasAlpha||this._shadowOnly},t.prototype.isReadyForSubMesh=function(e,n,i){var o=this;if(i===void 0&&(i=!1),n.effect&&this.isFrozen&&n.effect._wasPreviouslyReady)return!0;n._materialDefines||(n._materialDefines=new Cp);var a=this.getScene(),s=n._materialDefines;if(this._isReadyForSubMesh(n))return!0;var d=a.getEngine();if(et.a.PrepareDefinesForLights(a,e,s,!1,this._maxSimultaneousLights),s._needNormals=!0,et.a.PrepareDefinesForMultiview(a,s),s._areTexturesDirty){if(s._needUVs=!1,a.texturesEnabled){if(a.getEngine().getCaps().textureLOD&&(s.TEXTURELODSUPPORT=!0),this._diffuseTexture&&ht.a.DiffuseTextureEnabled){if(!this._diffuseTexture.isReadyOrNotBlocking())return!1;et.a.PrepareDefinesForMergedUV(this._diffuseTexture,s,"DIFFUSE"),s.DIFFUSEHASALPHA=this._diffuseTexture.hasAlpha,s.GAMMADIFFUSE=this._diffuseTexture.gammaSpace,s.OPACITYFRESNEL=this._opacityFresnel}else s.DIFFUSE=!1,s.DIFFUSEHASALPHA=!1,s.GAMMADIFFUSE=!1,s.OPACITYFRESNEL=!1;var p=this._reflectionTexture;if(p&&ht.a.ReflectionTextureEnabled){if(!p.isReadyOrNotBlocking())return!1;switch(s.REFLECTION=!0,s.GAMMAREFLECTION=p.gammaSpace,s.RGBDREFLECTION=p.isRGBD,s.REFLECTIONBLUR=this._reflectionBlur>0,s.REFLECTIONMAP_OPPOSITEZ=this.getScene().useRightHandedSystem?!p.invertZ:p.invertZ,s.LODINREFLECTIONALPHA=p.lodLevelInAlpha,s.EQUIRECTANGULAR_RELFECTION_FOV=this.useEquirectangularFOV,s.REFLECTIONBGR=this.switchToBGR,p.coordinatesMode===we.a.INVCUBIC_MODE&&(s.INVERTCUBICMAP=!0),s.REFLECTIONMAP_3D=p.isCube,p.coordinatesMode){case we.a.EXPLICIT_MODE:s.REFLECTIONMAP_EXPLICIT=!0;break;case we.a.PLANAR_MODE:s.REFLECTIONMAP_PLANAR=!0;break;case we.a.PROJECTION_MODE:s.REFLECTIONMAP_PROJECTION=!0;break;case we.a.SKYBOX_MODE:s.REFLECTIONMAP_SKYBOX=!0;break;case we.a.SPHERICAL_MODE:s.REFLECTIONMAP_SPHERICAL=!0;break;case we.a.EQUIRECTANGULAR_MODE:s.REFLECTIONMAP_EQUIRECTANGULAR=!0;break;case we.a.FIXED_EQUIRECTANGULAR_MODE:s.REFLECTIONMAP_EQUIRECTANGULAR_FIXED=!0;break;case we.a.FIXED_EQUIRECTANGULAR_MIRRORED_MODE:s.REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED=!0;break;case we.a.CUBIC_MODE:case we.a.INVCUBIC_MODE:default:s.REFLECTIONMAP_CUBIC=!0}this.reflectionFresnel?(s.REFLECTIONFRESNEL=!0,s.REFLECTIONFALLOFF=this.reflectionFalloffDistance>0,this._reflectionControls.x=this.reflectionAmount,this._reflectionControls.y=this.reflectionReflectance0,this._reflectionControls.z=this.reflectionReflectance90,this._reflectionControls.w=1/this.reflectionFalloffDistance):(s.REFLECTIONFRESNEL=!1,s.REFLECTIONFALLOFF=!1)}else s.REFLECTION=!1,s.REFLECTIONFRESNEL=!1,s.REFLECTIONFALLOFF=!1,s.REFLECTIONBLUR=!1,s.REFLECTIONMAP_3D=!1,s.REFLECTIONMAP_SPHERICAL=!1,s.REFLECTIONMAP_PLANAR=!1,s.REFLECTIONMAP_CUBIC=!1,s.REFLECTIONMAP_PROJECTION=!1,s.REFLECTIONMAP_SKYBOX=!1,s.REFLECTIONMAP_EXPLICIT=!1,s.REFLECTIONMAP_EQUIRECTANGULAR=!1,s.REFLECTIONMAP_EQUIRECTANGULAR_FIXED=!1,s.REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED=!1,s.INVERTCUBICMAP=!1,s.REFLECTIONMAP_OPPOSITEZ=!1,s.LODINREFLECTIONALPHA=!1,s.GAMMAREFLECTION=!1,s.RGBDREFLECTION=!1}s.PREMULTIPLYALPHA=this.alphaMode===h.a.ALPHA_PREMULTIPLIED||this.alphaMode===h.a.ALPHA_PREMULTIPLIED_PORTERDUFF,s.USERGBCOLOR=this._useRGBColor,s.NOISE=this._enableNoise}if(s._areLightsDirty&&(s.USEHIGHLIGHTANDSHADOWCOLORS=!this._useRGBColor&&(this._primaryColorShadowLevel!==0||this._primaryColorHighlightLevel!==0),s.BACKMAT_SHADOWONLY=this._shadowOnly),s._areImageProcessingDirty&&this._imageProcessingConfiguration){if(!this._imageProcessingConfiguration.isReady())return!1;this._imageProcessingConfiguration.prepareDefines(s)}if(et.a.PrepareDefinesForMisc(e,a,!1,this.pointsCloud,this.fogEnabled,this._shouldTurnAlphaTestOn(e),s),et.a.PrepareDefinesForFrameBoundValues(a,d,s,i,null,n.getRenderingMesh().hasThinInstances),et.a.PrepareDefinesForAttributes(e,s,!1,!0,!1)&&e&&(a.getEngine().getCaps().standardDerivatives||e.isVerticesDataPresent(Oe.b.NormalKind)||(e.createNormals(!0),l.a.Warn("BackgroundMaterial: Normals have been created for the mesh: "+e.name))),s.isDirty){s.markAsProcessed(),a.resetCachedMaterial();var b=new Sr.a;s.FOG&&b.addFallback(0,"FOG"),s.POINTSIZE&&b.addFallback(1,"POINTSIZE"),s.MULTIVIEW&&b.addFallback(0,"MULTIVIEW"),et.a.HandleFallbacksForShadows(s,b,this._maxSimultaneousLights);var P=[Oe.b.PositionKind];s.NORMAL&&P.push(Oe.b.NormalKind),s.UV1&&P.push(Oe.b.UVKind),s.UV2&&P.push(Oe.b.UV2Kind),et.a.PrepareAttributesForBones(P,e,s,b),et.a.PrepareAttributesForInstances(P,s);var O=["world","view","viewProjection","vEyePosition","vLightsType","vFogInfos","vFogColor","pointSize","vClipPlane","vClipPlane2","vClipPlane3","vClipPlane4","vClipPlane5","vClipPlane6","mBones","vPrimaryColor","vPrimaryColorShadow","vReflectionInfos","reflectionMatrix","vReflectionMicrosurfaceInfos","fFovMultiplier","shadowLevel","alpha","vBackgroundCenter","vReflectionControl","vDiffuseInfos","diffuseMatrix"],B=["diffuseSampler","reflectionSampler","reflectionSamplerLow","reflectionSamplerHigh"],F=["Material","Scene"];yn.a&&(yn.a.PrepareUniforms(O,s),yn.a.PrepareSamplers(B,s)),et.a.PrepareUniformsAndSamplersList({uniformsNames:O,uniformBuffersNames:F,samplers:B,defines:s,maxSimultaneousLights:this._maxSimultaneousLights});var z=s.toString();n.setEffect(a.getEngine().createEffect("background",{attributes:P,uniformsNames:O,uniformBuffersNames:F,samplers:B,defines:z,fallbacks:b,onCompiled:function(J){o.onCompiled&&o.onCompiled(J),o.bindSceneUniformBuffer(J,a.getSceneUniformBuffer())},onError:this.onError,indexParameters:{maxSimultaneousLights:this._maxSimultaneousLights}},d),s),this.buildUniformLayout()}return!(!n.effect||!n.effect.isReady())&&(s._renderId=a.getRenderId(),n.effect._wasPreviouslyReady=!0,!0)},t.prototype._computePrimaryColorFromPerceptualColor=function(){this.__perceptualColor&&(this._primaryColor.copyFrom(this.__perceptualColor),this._primaryColor.toLinearSpaceToRef(this._primaryColor),this._imageProcessingConfiguration&&this._primaryColor.scaleToRef(1/this._imageProcessingConfiguration.exposure,this._primaryColor),this._computePrimaryColors())},t.prototype._computePrimaryColors=function(){this._primaryColorShadowLevel===0&&this._primaryColorHighlightLevel===0||(this._primaryColor.scaleToRef(this._primaryColorShadowLevel,this._primaryShadowColor),this._primaryColor.subtractToRef(this._primaryShadowColor,this._primaryShadowColor),this._white.subtractToRef(this._primaryColor,this._primaryHighlightColor),this._primaryHighlightColor.scaleToRef(this._primaryColorHighlightLevel,this._primaryHighlightColor),this._primaryColor.addToRef(this._primaryHighlightColor,this._primaryHighlightColor))},t.prototype.buildUniformLayout=function(){this._uniformBuffer.addUniform("vPrimaryColor",4),this._uniformBuffer.addUniform("vPrimaryColorShadow",4),this._uniformBuffer.addUniform("vDiffuseInfos",2),this._uniformBuffer.addUniform("vReflectionInfos",2),this._uniformBuffer.addUniform("diffuseMatrix",16),this._uniformBuffer.addUniform("reflectionMatrix",16),this._uniformBuffer.addUniform("vReflectionMicrosurfaceInfos",3),this._uniformBuffer.addUniform("fFovMultiplier",1),this._uniformBuffer.addUniform("pointSize",1),this._uniformBuffer.addUniform("shadowLevel",1),this._uniformBuffer.addUniform("alpha",1),this._uniformBuffer.addUniform("vBackgroundCenter",3),this._uniformBuffer.addUniform("vReflectionControl",4),this._uniformBuffer.create()},t.prototype.unbind=function(){this._diffuseTexture&&this._diffuseTexture.isRenderTarget&&this._uniformBuffer.setTexture("diffuseSampler",null),this._reflectionTexture&&this._reflectionTexture.isRenderTarget&&this._uniformBuffer.setTexture("reflectionSampler",null),r.prototype.unbind.call(this)},t.prototype.bindOnlyWorldMatrix=function(e){this._activeEffect.setMatrix("world",e)},t.prototype.bindForSubMesh=function(e,n,i){var o=this.getScene(),a=i._materialDefines;if(a){var s=i.effect;if(s){this._activeEffect=s,this.bindOnlyWorldMatrix(e),et.a.BindBonesParameters(n,this._activeEffect);var d=this._mustRebind(o,s,n.visibility);if(d){this._uniformBuffer.bindToEffect(s,"Material"),this.bindViewProjection(s);var p=this._reflectionTexture;this._uniformBuffer.useUbo&&this.isFrozen&&this._uniformBuffer.isSync||(o.texturesEnabled&&(this._diffuseTexture&&ht.a.DiffuseTextureEnabled&&(this._uniformBuffer.updateFloat2("vDiffuseInfos",this._diffuseTexture.coordinatesIndex,this._diffuseTexture.level),et.a.BindTextureMatrix(this._diffuseTexture,this._uniformBuffer,"diffuse")),p&&ht.a.ReflectionTextureEnabled&&(this._uniformBuffer.updateMatrix("reflectionMatrix",p.getReflectionTextureMatrix()),this._uniformBuffer.updateFloat2("vReflectionInfos",p.level,this._reflectionBlur),this._uniformBuffer.updateFloat3("vReflectionMicrosurfaceInfos",p.getSize().width,p.lodGenerationScale,p.lodGenerationOffset))),this.shadowLevel>0&&this._uniformBuffer.updateFloat("shadowLevel",this.shadowLevel),this._uniformBuffer.updateFloat("alpha",this.alpha),this.pointsCloud&&this._uniformBuffer.updateFloat("pointSize",this.pointSize),a.USEHIGHLIGHTANDSHADOWCOLORS?(this._uniformBuffer.updateColor4("vPrimaryColor",this._primaryHighlightColor,1),this._uniformBuffer.updateColor4("vPrimaryColorShadow",this._primaryShadowColor,1)):this._uniformBuffer.updateColor4("vPrimaryColor",this._primaryColor,1)),this._uniformBuffer.updateFloat("fFovMultiplier",this._fovMultiplier),o.texturesEnabled&&(this._diffuseTexture&&ht.a.DiffuseTextureEnabled&&this._uniformBuffer.setTexture("diffuseSampler",this._diffuseTexture),p&&ht.a.ReflectionTextureEnabled&&(a.REFLECTIONBLUR&&a.TEXTURELODSUPPORT?this._uniformBuffer.setTexture("reflectionSampler",p):a.REFLECTIONBLUR?(this._uniformBuffer.setTexture("reflectionSampler",p._lodTextureMid||p),this._uniformBuffer.setTexture("reflectionSamplerLow",p._lodTextureLow||p),this._uniformBuffer.setTexture("reflectionSamplerHigh",p._lodTextureHigh||p)):this._uniformBuffer.setTexture("reflectionSampler",p),a.REFLECTIONFRESNEL&&(this._uniformBuffer.updateFloat3("vBackgroundCenter",this.sceneCenter.x,this.sceneCenter.y,this.sceneCenter.z),this._uniformBuffer.updateFloat4("vReflectionControl",this._reflectionControls.x,this._reflectionControls.y,this._reflectionControls.z,this._reflectionControls.w)))),et.a.BindClipPlane(this._activeEffect,o),et.a.BindEyePosition(s,o)}!d&&this.isFrozen||(o.lightsEnabled&&et.a.BindLights(o,n,this._activeEffect,a,this._maxSimultaneousLights,!1),this.bindView(s),et.a.BindFogParameters(o,n,this._activeEffect,!0),this._imageProcessingConfiguration&&this._imageProcessingConfiguration.bind(this._activeEffect)),this._uniformBuffer.update(),this._afterBind(n,this._activeEffect)}}},t.prototype.hasTexture=function(e){return!!r.prototype.hasTexture.call(this,e)||this._reflectionTexture===e||this._diffuseTexture===e},t.prototype.dispose=function(e,n){e===void 0&&(e=!1),n===void 0&&(n=!1),n&&(this.diffuseTexture&&this.diffuseTexture.dispose(),this.reflectionTexture&&this.reflectionTexture.dispose()),this._renderTargets.dispose(),this._imageProcessingConfiguration&&this._imageProcessingObserver&&this._imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingObserver),r.prototype.dispose.call(this,e)},t.prototype.clone=function(e){var n=this;return L.a.Clone(function(){return new t(e,n.getScene())},this)},t.prototype.serialize=function(){var e=L.a.Serialize(this);return e.customType="BABYLON.BackgroundMaterial",e},t.prototype.getClassName=function(){return"BackgroundMaterial"},t.Parse=function(e,n,i){return L.a.Parse(function(){return new t(e.name,n)},e,n,i)},t.StandardReflectance0=.05,t.StandardReflectance90=.5,Object(c.c)([Object(L.e)()],t.prototype,"_primaryColor",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsLightsDirty")],t.prototype,"primaryColor",void 0),Object(c.c)([Object(L.e)()],t.prototype,"__perceptualColor",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_primaryColorShadowLevel",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_primaryColorHighlightLevel",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsLightsDirty")],t.prototype,"primaryColorHighlightLevel",null),Object(c.c)([Object(L.m)()],t.prototype,"_reflectionTexture",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectionTexture",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_reflectionBlur",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectionBlur",void 0),Object(c.c)([Object(L.m)()],t.prototype,"_diffuseTexture",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"diffuseTexture",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"shadowLights",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_shadowLevel",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"shadowLevel",void 0),Object(c.c)([Object(L.o)()],t.prototype,"_sceneCenter",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"sceneCenter",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_opacityFresnel",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"opacityFresnel",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_reflectionFresnel",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectionFresnel",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_reflectionFalloffDistance",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectionFalloffDistance",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_reflectionAmount",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectionAmount",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_reflectionReflectance0",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectionReflectance0",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_reflectionReflectance90",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectionReflectance90",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_useRGBColor",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useRGBColor",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_enableNoise",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"enableNoise",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_maxSimultaneousLights",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"maxSimultaneousLights",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_shadowOnly",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsLightsDirty")],t.prototype,"shadowOnly",void 0),Object(c.c)([Object(L.i)()],t.prototype,"_imageProcessingConfiguration",void 0),t}($o.a);R.a.RegisteredTypes["BABYLON.BackgroundMaterial"]=so;var Ls=function(){function r(t,e){var n=this;this._errorHandler=function(i,o){n.onErrorObservable.notifyObservers({message:i,exception:o})},this._options=Object(c.a)(Object(c.a)({},r._getDefaultOptions()),t),this._scene=e,this.onErrorObservable=new x.c,this._setupBackground(),this._setupImageProcessing()}return r._getDefaultOptions=function(){return{createGround:!0,groundSize:15,groundTexture:this._groundTextureCDNUrl,groundColor:new M.a(.2,.2,.3).toLinearSpace().scale(3),groundOpacity:.9,enableGroundShadow:!0,groundShadowLevel:.5,enableGroundMirror:!1,groundMirrorSizeRatio:.3,groundMirrorBlurKernel:64,groundMirrorAmount:1,groundMirrorFresnelWeight:1,groundMirrorFallOffDistance:0,groundMirrorTextureType:h.a.TEXTURETYPE_UNSIGNED_INT,groundYBias:1e-5,createSkybox:!0,skyboxSize:20,skyboxTexture:this._skyboxTextureCDNUrl,skyboxColor:new M.a(.2,.2,.3).toLinearSpace().scale(3),backgroundYRotation:0,sizeAuto:!0,rootPosition:u.e.Zero(),setupImageProcessing:!0,environmentTexture:this._environmentTextureCDNUrl,cameraExposure:.8,cameraContrast:1.2,toneMappingEnabled:!0}},Object.defineProperty(r.prototype,"rootMesh",{get:function(){return this._rootMesh},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"skybox",{get:function(){return this._skybox},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"skyboxTexture",{get:function(){return this._skyboxTexture},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"skyboxMaterial",{get:function(){return this._skyboxMaterial},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"ground",{get:function(){return this._ground},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"groundTexture",{get:function(){return this._groundTexture},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"groundMirror",{get:function(){return this._groundMirror},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"groundMirrorRenderList",{get:function(){return this._groundMirror?this._groundMirror.renderList:null},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"groundMaterial",{get:function(){return this._groundMaterial},enumerable:!1,configurable:!0}),r.prototype.updateOptions=function(t){var e=Object(c.a)(Object(c.a)({},this._options),t);this._ground&&!e.createGround&&(this._ground.dispose(),this._ground=null),this._groundMaterial&&!e.createGround&&(this._groundMaterial.dispose(),this._groundMaterial=null),this._groundTexture&&this._options.groundTexture!=e.groundTexture&&(this._groundTexture.dispose(),this._groundTexture=null),this._skybox&&!e.createSkybox&&(this._skybox.dispose(),this._skybox=null),this._skyboxMaterial&&!e.createSkybox&&(this._skyboxMaterial.dispose(),this._skyboxMaterial=null),this._skyboxTexture&&this._options.skyboxTexture!=e.skyboxTexture&&(this._skyboxTexture.dispose(),this._skyboxTexture=null),this._groundMirror&&!e.enableGroundMirror&&(this._groundMirror.dispose(),this._groundMirror=null),this._scene.environmentTexture&&this._options.environmentTexture!=e.environmentTexture&&this._scene.environmentTexture.dispose(),this._options=e,this._setupBackground(),this._setupImageProcessing()},r.prototype.setMainColor=function(t){this.groundMaterial&&(this.groundMaterial.primaryColor=t),this.skyboxMaterial&&(this.skyboxMaterial.primaryColor=t),this.groundMirror&&(this.groundMirror.clearColor=new M.b(t.r,t.g,t.b,1))},r.prototype._setupImageProcessing=function(){this._options.setupImageProcessing&&(this._scene.imageProcessingConfiguration.contrast=this._options.cameraContrast,this._scene.imageProcessingConfiguration.exposure=this._options.cameraExposure,this._scene.imageProcessingConfiguration.toneMappingEnabled=this._options.toneMappingEnabled,this._setupEnvironmentTexture())},r.prototype._setupEnvironmentTexture=function(){if(!this._scene.environmentTexture)if(this._options.environmentTexture instanceof zn.a)this._scene.environmentTexture=this._options.environmentTexture;else{var t=ai.CreateFromPrefilteredData(this._options.environmentTexture,this._scene);this._scene.environmentTexture=t}},r.prototype._setupBackground=function(){this._rootMesh||(this._rootMesh=new De.a("BackgroundHelper",this._scene)),this._rootMesh.rotation.y=this._options.backgroundYRotation;var t=this._getSceneSize();this._options.createGround&&(this._setupGround(t),this._setupGroundMaterial(),this._setupGroundDiffuseTexture(),this._options.enableGroundMirror&&this._setupGroundMirrorTexture(t),this._setupMirrorInGroundMaterial()),this._options.createSkybox&&(this._setupSkybox(t),this._setupSkyboxMaterial(),this._setupSkyboxReflectionTexture()),this._rootMesh.position.x=t.rootPosition.x,this._rootMesh.position.z=t.rootPosition.z,this._rootMesh.position.y=t.rootPosition.y},r.prototype._getSceneSize=function(){var t=this,e=this._options.groundSize,n=this._options.skyboxSize,i=this._options.rootPosition;if(!this._scene.meshes||this._scene.meshes.length===1)return{groundSize:e,skyboxSize:n,rootPosition:i};var o=this._scene.getWorldExtends(function(d){return d!==t._ground&&d!==t._rootMesh&&d!==t._skybox}),a=o.max.subtract(o.min);if(this._options.sizeAuto){this._scene.activeCamera instanceof Ji&&this._scene.activeCamera.upperRadiusLimit&&(n=e=2*this._scene.activeCamera.upperRadiusLimit);var s=a.length();s>e&&(n=e=2*s),e*=1.1,n*=1.5,(i=o.min.add(a.scale(.5))).y=o.min.y-this._options.groundYBias}return{groundSize:e,skyboxSize:n,rootPosition:i}},r.prototype._setupGround=function(t){var e=this;this._ground&&!this._ground.isDisposed()||(this._ground=De.a.CreatePlane("BackgroundPlane",t.groundSize,this._scene),this._ground.rotation.x=Math.PI/2,this._ground.parent=this._rootMesh,this._ground.onDisposeObservable.add(function(){e._ground=null})),this._ground.receiveShadows=this._options.enableGroundShadow},r.prototype._setupGroundMaterial=function(){this._groundMaterial||(this._groundMaterial=new so("BackgroundPlaneMaterial",this._scene)),this._groundMaterial.alpha=this._options.groundOpacity,this._groundMaterial.alphaMode=h.a.ALPHA_PREMULTIPLIED_PORTERDUFF,this._groundMaterial.shadowLevel=this._options.groundShadowLevel,this._groundMaterial.primaryColor=this._options.groundColor,this._groundMaterial.useRGBColor=!1,this._groundMaterial.enableNoise=!0,this._ground&&(this._ground.material=this._groundMaterial)},r.prototype._setupGroundDiffuseTexture=function(){this._groundMaterial&&(this._groundTexture||(this._options.groundTexture instanceof zn.a?this._groundMaterial.diffuseTexture=this._options.groundTexture:(this._groundTexture=new we.a(this._options.groundTexture,this._scene,void 0,void 0,void 0,void 0,this._errorHandler),this._groundTexture.gammaSpace=!1,this._groundTexture.hasAlpha=!0,this._groundMaterial.diffuseTexture=this._groundTexture)))},r.prototype._setupGroundMirrorTexture=function(t){var e=we.a.CLAMP_ADDRESSMODE;if(!this._groundMirror&&(this._groundMirror=new Ds("BackgroundPlaneMirrorTexture",{ratio:this._options.groundMirrorSizeRatio},this._scene,!1,this._options.groundMirrorTextureType,we.a.BILINEAR_SAMPLINGMODE,!0),this._groundMirror.mirrorPlane=new vr.a(0,-1,0,t.rootPosition.y),this._groundMirror.anisotropicFilteringLevel=1,this._groundMirror.wrapU=e,this._groundMirror.wrapV=e,this._groundMirror.gammaSpace=!1,this._groundMirror.renderList))for(var n=0;n<this._scene.meshes.length;n++){var i=this._scene.meshes[n];i!==this._ground&&i!==this._skybox&&i!==this._rootMesh&&this._groundMirror.renderList.push(i)}this._groundMirror.clearColor=new M.b(this._options.groundColor.r,this._options.groundColor.g,this._options.groundColor.b,1),this._groundMirror.adaptiveBlurKernel=this._options.groundMirrorBlurKernel},r.prototype._setupMirrorInGroundMaterial=function(){this._groundMaterial&&(this._groundMaterial.reflectionTexture=this._groundMirror,this._groundMaterial.reflectionFresnel=!0,this._groundMaterial.reflectionAmount=this._options.groundMirrorAmount,this._groundMaterial.reflectionStandardFresnelWeight=this._options.groundMirrorFresnelWeight,this._groundMaterial.reflectionFalloffDistance=this._options.groundMirrorFallOffDistance)},r.prototype._setupSkybox=function(t){var e=this;this._skybox&&!this._skybox.isDisposed()||(this._skybox=De.a.CreateBox("BackgroundSkybox",t.skyboxSize,this._scene,void 0,De.a.BACKSIDE),this._skybox.onDisposeObservable.add(function(){e._skybox=null})),this._skybox.parent=this._rootMesh},r.prototype._setupSkyboxMaterial=function(){this._skybox&&(this._skyboxMaterial||(this._skyboxMaterial=new so("BackgroundSkyboxMaterial",this._scene)),this._skyboxMaterial.useRGBColor=!1,this._skyboxMaterial.primaryColor=this._options.skyboxColor,this._skyboxMaterial.enableNoise=!0,this._skybox.material=this._skyboxMaterial)},r.prototype._setupSkyboxReflectionTexture=function(){this._skyboxMaterial&&(this._skyboxTexture||(this._options.skyboxTexture instanceof zn.a?this._skyboxMaterial.reflectionTexture=this._options.skyboxTexture:(this._skyboxTexture=new ai(this._options.skyboxTexture,this._scene,void 0,void 0,void 0,void 0,this._errorHandler),this._skyboxTexture.coordinatesMode=we.a.SKYBOX_MODE,this._skyboxTexture.gammaSpace=!1,this._skyboxMaterial.reflectionTexture=this._skyboxTexture)))},r.prototype.dispose=function(){this._groundMaterial&&this._groundMaterial.dispose(!0,!0),this._skyboxMaterial&&this._skyboxMaterial.dispose(!0,!0),this._rootMesh.dispose(!1)},r._groundTextureCDNUrl="https://assets.babylonjs.com/environments/backgroundGround.png",r._skyboxTextureCDNUrl="https://assets.babylonjs.com/environments/backgroundSkybox.dds",r._environmentTextureCDNUrl="https://assets.babylonjs.com/environments/environmentSpecular.env",r}(),ki=function(r){function t(e,n,i,o,a){a===void 0&&(a=null);var s=r.call(this,e,o)||this;s.onError=a,s._halfDome=!1,s._crossEye=!1,s._useDirectMapping=!1,s._textureMode=t.MODE_MONOSCOPIC,s._onBeforeCameraRenderObserver=null,s.onLoadErrorObservable=new x.c,o=s.getScene(),e=e||"textureDome",i.resolution=0|Math.abs(i.resolution)||32,i.clickToPlay=!!i.clickToPlay,i.autoPlay=i.autoPlay===void 0||!!i.autoPlay,i.loop=i.loop===void 0||!!i.loop,i.size=Math.abs(i.size)||(o.activeCamera?.48*o.activeCamera.maxZ:1e3),i.useDirectMapping===void 0?s._useDirectMapping=!0:s._useDirectMapping=i.useDirectMapping,i.faceForward===void 0&&(i.faceForward=!0),s._setReady(!1),s._mesh=De.a.CreateSphere(e+"_mesh",i.resolution,i.size,o,!1,De.a.BACKSIDE);var d=s._material=new so(e+"_material",o);d.useEquirectangularFOV=!0,d.fovMultiplier=1,d.opacityFresnel=!1;var p=s._initTexture(n,o,i);if(s.texture=p,s._mesh.material=d,s._mesh.parent=s,s._halfDomeMask=Fn.a.CreateSphere("",{slice:.5,diameter:.98*i.size,segments:2*i.resolution,sideOrientation:De.a.BACKSIDE},o),s._halfDomeMask.rotate(ye.a.X,-Math.PI/2),s._halfDomeMask.parent=s._mesh,s._halfDome=!!i.halfDomeMode,s._halfDomeMask.setEnabled(s._halfDome),s._crossEye=!!i.crossEyeMode,s._texture.anisotropicFilteringLevel=1,s._texture.onLoadObservable.addOnce(function(){s._setReady(!0)}),i.faceForward&&o.activeCamera){var b=o.activeCamera,P=u.e.Forward(),O=u.e.TransformNormal(P,b.getViewMatrix());O.normalize(),s.rotation.y=Math.acos(u.e.Dot(P,O))}return s._changeTextureMode(s._textureMode),s}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"texture",{get:function(){return this._texture},set:function(e){this._texture!==e&&(this._texture=e,this._useDirectMapping?(this._texture.wrapU=we.a.CLAMP_ADDRESSMODE,this._texture.wrapV=we.a.CLAMP_ADDRESSMODE,this._material.diffuseTexture=this._texture):(this._texture.coordinatesMode=we.a.FIXED_EQUIRECTANGULAR_MIRRORED_MODE,this._texture.wrapV=we.a.CLAMP_ADDRESSMODE,this._material.reflectionTexture=this._texture),this._changeTextureMode(this._textureMode))},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"mesh",{get:function(){return this._mesh},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"fovMultiplier",{get:function(){return this._material.fovMultiplier},set:function(e){this._material.fovMultiplier=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"textureMode",{get:function(){return this._textureMode},set:function(e){this._textureMode!==e&&this._changeTextureMode(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"halfDome",{get:function(){return this._halfDome},set:function(e){this._halfDome=e,this._halfDomeMask.setEnabled(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"crossEye",{get:function(){return this._crossEye},set:function(e){this._crossEye=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"material",{get:function(){return this._material},enumerable:!1,configurable:!0}),t.prototype._changeTextureMode=function(e){var n=this;switch(this._scene.onBeforeCameraRenderObservable.remove(this._onBeforeCameraRenderObserver),this._textureMode=e,this._texture.uScale=1,this._texture.vScale=1,this._texture.uOffset=0,this._texture.vOffset=0,this._texture.vAng=0,e){case t.MODE_MONOSCOPIC:this._halfDome&&(this._texture.uScale=2,this._texture.uOffset=-1);break;case t.MODE_SIDEBYSIDE:this._texture.uScale=this._halfDome?.99999:.5;var i=this._halfDome?0:.5,o=this._halfDome?-.5:0;this._onBeforeCameraRenderObserver=this._scene.onBeforeCameraRenderObservable.add(function(a){var s=a.isRightCamera;n._crossEye&&(s=!s),n._texture.uOffset=s?i:o});break;case t.MODE_TOPBOTTOM:this._texture.vScale=this._halfDome?.99999:.5,this._onBeforeCameraRenderObserver=this._scene.onBeforeCameraRenderObservable.add(function(a){var s=a.isRightCamera;n._crossEye&&(s=!s),n._texture.vOffset=s?.5:0})}},t.prototype.dispose=function(e,n){n===void 0&&(n=!1),this._texture.dispose(),this._mesh.dispose(),this._material.dispose(),this._scene.onBeforeCameraRenderObservable.remove(this._onBeforeCameraRenderObserver),this.onLoadErrorObservable.clear(),r.prototype.dispose.call(this,e,n)},t.MODE_MONOSCOPIC=0,t.MODE_TOPBOTTOM=1,t.MODE_SIDEBYSIDE=2,t}(Er.a),xp=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"photoTexture",{get:function(){return this.texture},set:function(e){this.texture=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"imageMode",{get:function(){return this.textureMode},set:function(e){this.textureMode=e},enumerable:!1,configurable:!0}),t.prototype._initTexture=function(e,n,i){var o=this;return new we.a(e,n,!i.generateMipMaps,!this._useDirectMapping,void 0,void 0,function(a,s){o.onLoadErrorObservable.notifyObservers(a||"Unknown error occured"),o.onError&&o.onError(a,s)})},t.MODE_MONOSCOPIC=ki.MODE_MONOSCOPIC,t.MODE_TOPBOTTOM=ki.MODE_TOPBOTTOM,t.MODE_SIDEBYSIDE=ki.MODE_SIDEBYSIDE,t}(ki),fu=function(){function r(){}return r.ExpandRGBDTexture=function(t){var e=t._texture;if(e&&t.isRGBD){var n=e.getEngine(),i=n.getCaps(),o=!1;i.textureHalfFloatRender&&i.textureHalfFloatLinearFiltering?(o=!0,e.type=h.a.TEXTURETYPE_HALF_FLOAT):i.textureFloatRender&&i.textureFloatLinearFiltering&&(o=!0,e.type=h.a.TEXTURETYPE_FLOAT),o&&(e.isReady=!1,e._isRGBD=!1,e.invertY=!1),t.onLoadObservable.addOnce(function(){if(o){var a=new _t("rgbdDecode","rgbdDecode",null,null,1,null,h.a.TEXTURE_TRILINEAR_SAMPLINGMODE,n,!1,void 0,e.type,void 0,null,!1),s=n.createRenderTargetTexture(e.width,{generateDepthBuffer:!1,generateMipMaps:!1,generateStencilBuffer:!1,samplingMode:e.samplingMode,type:e.type,format:h.a.TEXTUREFORMAT_RGBA});a.getEffect().executeWhenCompiled(function(){a.onApply=function(d){d._bindTexture("textureSampler",e),d.setFloat2("scale",1,1)},t.getScene().postProcessManager.directRender([a],s,!0),n.restoreDefaultFramebuffer(),n._releaseTexture(e),n._releaseFramebufferObjects(s),a&&a.dispose(),s._swapAndDie(e),e.isReady=!0})}})}},r}(),ea=function(){function r(){}return r.GetEnvironmentBRDFTexture=function(t){if(!t.environmentBRDFTexture){var e=t.useDelayedTextureLoading;t.useDelayedTextureLoading=!1;var n=t._blockEntityCollection;t._blockEntityCollection=!1;var i=we.a.CreateFromBase64String(this._environmentBRDFBase64Texture,"EnvironmentBRDFTexture"+this._instanceNumber++,t,!0,!1,we.a.BILINEAR_SAMPLINGMODE);t._blockEntityCollection=n;var o=t.getEngine().getLoadedTexturesCache(),a=o.indexOf(i.getInternalTexture());a!==-1&&o.splice(a,1),i.isRGBD=!0,i.wrapU=we.a.CLAMP_ADDRESSMODE,i.wrapV=we.a.CLAMP_ADDRESSMODE,t.environmentBRDFTexture=i,t.useDelayedTextureLoading=e,fu.ExpandRGBDTexture(i)}return 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",r}(),Ar=function(){function r(t){this._isEnabled=!1,this.isEnabled=!1,this.intensity=1,this.roughness=0,this._indexOfRefraction=r._DefaultIndexOfRefraction,this.indexOfRefraction=r._DefaultIndexOfRefraction,this._texture=null,this.texture=null,this._useRoughnessFromMainTexture=!0,this.useRoughnessFromMainTexture=!0,this._textureRoughness=null,this.textureRoughness=null,this._remapF0OnInterfaceChange=!0,this.remapF0OnInterfaceChange=!0,this._bumpTexture=null,this.bumpTexture=null,this._isTintEnabled=!1,this.isTintEnabled=!1,this.tintColor=M.a.White(),this.tintColorAtDistance=1,this.tintThickness=1,this._tintTexture=null,this.tintTexture=null,this._internalMarkAllSubMeshesAsTexturesDirty=t}return r.prototype._markAllSubMeshesAsTexturesDirty=function(){this._internalMarkAllSubMeshesAsTexturesDirty()},r.prototype.isReadyForSubMesh=function(t,e,n,i){return!(t._areTexturesDirty&&e.texturesEnabled&&(this._texture&&ht.a.ClearCoatTextureEnabled&&!this._texture.isReadyOrNotBlocking()||this._textureRoughness&&ht.a.ClearCoatTextureEnabled&&!this._textureRoughness.isReadyOrNotBlocking()||n.getCaps().standardDerivatives&&this._bumpTexture&&ht.a.ClearCoatBumpTextureEnabled&&!i&&!this._bumpTexture.isReady()||this._isTintEnabled&&this._tintTexture&&ht.a.ClearCoatTintTextureEnabled&&!this._tintTexture.isReadyOrNotBlocking()))},r.prototype.prepareDefines=function(t,e){var n;this._isEnabled?(t.CLEARCOAT=!0,t.CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE=this._useRoughnessFromMainTexture,t.CLEARCOAT_TEXTURE_ROUGHNESS_IDENTICAL=this._texture!==null&&this._texture._texture===((n=this._textureRoughness)===null||n===void 0?void 0:n._texture)&&this._texture.checkTransformsAreIdentical(this._textureRoughness),t.CLEARCOAT_REMAP_F0=this._remapF0OnInterfaceChange,t._areTexturesDirty&&e.texturesEnabled&&(this._texture&&ht.a.ClearCoatTextureEnabled?et.a.PrepareDefinesForMergedUV(this._texture,t,"CLEARCOAT_TEXTURE"):t.CLEARCOAT_TEXTURE=!1,this._textureRoughness&&ht.a.ClearCoatTextureEnabled?et.a.PrepareDefinesForMergedUV(this._textureRoughness,t,"CLEARCOAT_TEXTURE_ROUGHNESS"):t.CLEARCOAT_TEXTURE_ROUGHNESS=!1,this._bumpTexture&&ht.a.ClearCoatBumpTextureEnabled?et.a.PrepareDefinesForMergedUV(this._bumpTexture,t,"CLEARCOAT_BUMP"):t.CLEARCOAT_BUMP=!1,t.CLEARCOAT_DEFAULTIOR=this._indexOfRefraction===r._DefaultIndexOfRefraction,this._isTintEnabled?(t.CLEARCOAT_TINT=!0,this._tintTexture&&ht.a.ClearCoatTintTextureEnabled?et.a.PrepareDefinesForMergedUV(this._tintTexture,t,"CLEARCOAT_TINT_TEXTURE"):t.CLEARCOAT_TINT_TEXTURE=!1):(t.CLEARCOAT_TINT=!1,t.CLEARCOAT_TINT_TEXTURE=!1))):(t.CLEARCOAT=!1,t.CLEARCOAT_TEXTURE=!1,t.CLEARCOAT_TEXTURE_ROUGHNESS=!1,t.CLEARCOAT_BUMP=!1,t.CLEARCOAT_TINT=!1,t.CLEARCOAT_TINT_TEXTURE=!1,t.CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE=!1,t.CLEARCOAT_TEXTURE_ROUGHNESS_IDENTICAL=!1)},r.prototype.bindForSubMesh=function(t,e,n,i,o,a,s,d){var p,b,P,O,B,F,z,J,ie=d._materialDefines,se=ie.CLEARCOAT_TEXTURE_ROUGHNESS_IDENTICAL;if(!t.useUbo||!o||!t.isSync){se&&ht.a.ClearCoatTextureEnabled?(t.updateFloat4("vClearCoatInfos",this._texture.coordinatesIndex,this._texture.level,-1,-1),et.a.BindTextureMatrix(this._texture,t,"clearCoat")):(this._texture||this._textureRoughness)&&ht.a.ClearCoatTextureEnabled&&(t.updateFloat4("vClearCoatInfos",(b=(p=this._texture)===null||p===void 0?void 0:p.coordinatesIndex)!==null&&b!==void 0?b:0,(O=(P=this._texture)===null||P===void 0?void 0:P.level)!==null&&O!==void 0?O:0,(F=(B=this._textureRoughness)===null||B===void 0?void 0:B.coordinatesIndex)!==null&&F!==void 0?F:0,(J=(z=this._textureRoughness)===null||z===void 0?void 0:z.level)!==null&&J!==void 0?J:0),this._texture&&et.a.BindTextureMatrix(this._texture,t,"clearCoat"),!this._textureRoughness||se||ie.CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE||et.a.BindTextureMatrix(this._textureRoughness,t,"clearCoatRoughness")),this._bumpTexture&&n.getCaps().standardDerivatives&&ht.a.ClearCoatTextureEnabled&&!i&&(t.updateFloat2("vClearCoatBumpInfos",this._bumpTexture.coordinatesIndex,this._bumpTexture.level),et.a.BindTextureMatrix(this._bumpTexture,t,"clearCoatBump"),e._mirroredCameraPosition?t.updateFloat2("vClearCoatTangentSpaceParams",a?1:-1,s?1:-1):t.updateFloat2("vClearCoatTangentSpaceParams",a?-1:1,s?-1:1)),this._tintTexture&&ht.a.ClearCoatTintTextureEnabled&&(t.updateFloat2("vClearCoatTintInfos",this._tintTexture.coordinatesIndex,this._tintTexture.level),et.a.BindTextureMatrix(this._tintTexture,t,"clearCoatTint")),t.updateFloat2("vClearCoatParams",this.intensity,this.roughness);var ce=1-this._indexOfRefraction,ue=1+this._indexOfRefraction,fe=Math.pow(-ce/ue,2),ve=1/this._indexOfRefraction;t.updateFloat4("vClearCoatRefractionParams",fe,ve,ce,ue),this._isTintEnabled&&(t.updateFloat4("vClearCoatTintParams",this.tintColor.r,this.tintColor.g,this.tintColor.b,Math.max(1e-5,this.tintThickness)),t.updateFloat("clearCoatColorAtDistance",Math.max(1e-5,this.tintColorAtDistance)))}e.texturesEnabled&&(this._texture&&ht.a.ClearCoatTextureEnabled&&t.setTexture("clearCoatSampler",this._texture),this._textureRoughness&&!se&&!ie.CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE&&ht.a.ClearCoatTextureEnabled&&t.setTexture("clearCoatRoughnessSampler",this._textureRoughness),this._bumpTexture&&n.getCaps().standardDerivatives&&ht.a.ClearCoatBumpTextureEnabled&&!i&&t.setTexture("clearCoatBumpSampler",this._bumpTexture),this._isTintEnabled&&this._tintTexture&&ht.a.ClearCoatTintTextureEnabled&&t.setTexture("clearCoatTintSampler",this._tintTexture))},r.prototype.hasTexture=function(t){return this._texture===t||this._textureRoughness===t||this._bumpTexture===t||this._tintTexture===t},r.prototype.getActiveTextures=function(t){this._texture&&t.push(this._texture),this._textureRoughness&&t.push(this._textureRoughness),this._bumpTexture&&t.push(this._bumpTexture),this._tintTexture&&t.push(this._tintTexture)},r.prototype.getAnimatables=function(t){this._texture&&this._texture.animations&&this._texture.animations.length>0&&t.push(this._texture),this._textureRoughness&&this._textureRoughness.animations&&this._textureRoughness.animations.length>0&&t.push(this._textureRoughness),this._bumpTexture&&this._bumpTexture.animations&&this._bumpTexture.animations.length>0&&t.push(this._bumpTexture),this._tintTexture&&this._tintTexture.animations&&this._tintTexture.animations.length>0&&t.push(this._tintTexture)},r.prototype.dispose=function(t){var e,n,i,o;t&&((e=this._texture)===null||e===void 0||e.dispose(),(n=this._textureRoughness)===null||n===void 0||n.dispose(),(i=this._bumpTexture)===null||i===void 0||i.dispose(),(o=this._tintTexture)===null||o===void 0||o.dispose())},r.prototype.getClassName=function(){return"PBRClearCoatConfiguration"},r.AddFallbacks=function(t,e,n){return t.CLEARCOAT_BUMP&&e.addFallback(n++,"CLEARCOAT_BUMP"),t.CLEARCOAT_TINT&&e.addFallback(n++,"CLEARCOAT_TINT"),t.CLEARCOAT&&e.addFallback(n++,"CLEARCOAT"),n},r.AddUniforms=function(t){t.push("vClearCoatTangentSpaceParams","vClearCoatParams","vClearCoatRefractionParams","vClearCoatTintParams","clearCoatColorAtDistance","clearCoatMatrix","clearCoatRoughnessMatrix","clearCoatBumpMatrix","clearCoatTintMatrix","vClearCoatInfos","vClearCoatBumpInfos","vClearCoatTintInfos")},r.AddSamplers=function(t){t.push("clearCoatSampler","clearCoatRoughnessSampler","clearCoatBumpSampler","clearCoatTintSampler")},r.PrepareUniformBuffer=function(t){t.addUniform("vClearCoatParams",2),t.addUniform("vClearCoatRefractionParams",4),t.addUniform("vClearCoatInfos",4),t.addUniform("clearCoatMatrix",16),t.addUniform("clearCoatRoughnessMatrix",16),t.addUniform("vClearCoatBumpInfos",2),t.addUniform("vClearCoatTangentSpaceParams",2),t.addUniform("clearCoatBumpMatrix",16),t.addUniform("vClearCoatTintParams",4),t.addUniform("clearCoatColorAtDistance",1),t.addUniform("vClearCoatTintInfos",2),t.addUniform("clearCoatTintMatrix",16)},r.prototype.copyTo=function(t){L.a.Clone(function(){return t},this)},r.prototype.serialize=function(){return L.a.Serialize(this)},r.prototype.parse=function(t,e,n){var i=this;L.a.Parse(function(){return i},t,e,n)},r._DefaultIndexOfRefraction=1.5,Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"isEnabled",void 0),Object(c.c)([Object(L.c)()],r.prototype,"intensity",void 0),Object(c.c)([Object(L.c)()],r.prototype,"roughness",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"indexOfRefraction",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"texture",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"useRoughnessFromMainTexture",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"textureRoughness",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"remapF0OnInterfaceChange",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"bumpTexture",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"isTintEnabled",void 0),Object(c.c)([Object(L.e)()],r.prototype,"tintColor",void 0),Object(c.c)([Object(L.c)()],r.prototype,"tintColorAtDistance",void 0),Object(c.c)([Object(L.c)()],r.prototype,"tintThickness",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"tintTexture",void 0),r}(),Pr=function(){function r(t){this._isEnabled=!1,this.isEnabled=!1,this.intensity=1,this.direction=new u.d(1,0),this._texture=null,this.texture=null,this._internalMarkAllSubMeshesAsTexturesDirty=t}return r.prototype._markAllSubMeshesAsTexturesDirty=function(){this._internalMarkAllSubMeshesAsTexturesDirty()},r.prototype.isReadyForSubMesh=function(t,e){return!(t._areTexturesDirty&&e.texturesEnabled&&this._texture&&ht.a.AnisotropicTextureEnabled&&!this._texture.isReadyOrNotBlocking())},r.prototype.prepareDefines=function(t,e,n){this._isEnabled?(t.ANISOTROPIC=this._isEnabled,this._isEnabled&&!e.isVerticesDataPresent(Oe.b.TangentKind)&&(t._needUVs=!0,t.MAINUV1=!0),t._areTexturesDirty&&n.texturesEnabled&&(this._texture&&ht.a.AnisotropicTextureEnabled?et.a.PrepareDefinesForMergedUV(this._texture,t,"ANISOTROPIC_TEXTURE"):t.ANISOTROPIC_TEXTURE=!1)):(t.ANISOTROPIC=!1,t.ANISOTROPIC_TEXTURE=!1)},r.prototype.bindForSubMesh=function(t,e,n){t.useUbo&&n&&t.isSync||(this._texture&&ht.a.AnisotropicTextureEnabled&&(t.updateFloat2("vAnisotropyInfos",this._texture.coordinatesIndex,this._texture.level),et.a.BindTextureMatrix(this._texture,t,"anisotropy")),t.updateFloat3("vAnisotropy",this.direction.x,this.direction.y,this.intensity)),e.texturesEnabled&&this._texture&&ht.a.AnisotropicTextureEnabled&&t.setTexture("anisotropySampler",this._texture)},r.prototype.hasTexture=function(t){return this._texture===t},r.prototype.getActiveTextures=function(t){this._texture&&t.push(this._texture)},r.prototype.getAnimatables=function(t){this._texture&&this._texture.animations&&this._texture.animations.length>0&&t.push(this._texture)},r.prototype.dispose=function(t){t&&this._texture&&this._texture.dispose()},r.prototype.getClassName=function(){return"PBRAnisotropicConfiguration"},r.AddFallbacks=function(t,e,n){return t.ANISOTROPIC&&e.addFallback(n++,"ANISOTROPIC"),n},r.AddUniforms=function(t){t.push("vAnisotropy","vAnisotropyInfos","anisotropyMatrix")},r.PrepareUniformBuffer=function(t){t.addUniform("vAnisotropy",3),t.addUniform("vAnisotropyInfos",2),t.addUniform("anisotropyMatrix",16)},r.AddSamplers=function(t){t.push("anisotropySampler")},r.prototype.copyTo=function(t){L.a.Clone(function(){return t},this)},r.prototype.serialize=function(){return L.a.Serialize(this)},r.prototype.parse=function(t,e,n){var i=this;L.a.Parse(function(){return i},t,e,n)},Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"isEnabled",void 0),Object(c.c)([Object(L.c)()],r.prototype,"intensity",void 0),Object(c.c)([Object(L.n)()],r.prototype,"direction",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"texture",void 0),r}(),Rp=function(){function r(t){this._useEnergyConservation=r.DEFAULT_USE_ENERGY_CONSERVATION,this.useEnergyConservation=r.DEFAULT_USE_ENERGY_CONSERVATION,this._useSmithVisibilityHeightCorrelated=r.DEFAULT_USE_SMITH_VISIBILITY_HEIGHT_CORRELATED,this.useSmithVisibilityHeightCorrelated=r.DEFAULT_USE_SMITH_VISIBILITY_HEIGHT_CORRELATED,this._useSphericalHarmonics=r.DEFAULT_USE_SPHERICAL_HARMONICS,this.useSphericalHarmonics=r.DEFAULT_USE_SPHERICAL_HARMONICS,this._useSpecularGlossinessInputEnergyConservation=r.DEFAULT_USE_SPECULAR_GLOSSINESS_INPUT_ENERGY_CONSERVATION,this.useSpecularGlossinessInputEnergyConservation=r.DEFAULT_USE_SPECULAR_GLOSSINESS_INPUT_ENERGY_CONSERVATION,this._internalMarkAllSubMeshesAsMiscDirty=t}return r.prototype._markAllSubMeshesAsMiscDirty=function(){this._internalMarkAllSubMeshesAsMiscDirty()},r.prototype.prepareDefines=function(t){t.BRDF_V_HEIGHT_CORRELATED=this._useSmithVisibilityHeightCorrelated,t.MS_BRDF_ENERGY_CONSERVATION=this._useEnergyConservation&&this._useSmithVisibilityHeightCorrelated,t.SPHERICAL_HARMONICS=this._useSphericalHarmonics,t.SPECULAR_GLOSSINESS_ENERGY_CONSERVATION=this._useSpecularGlossinessInputEnergyConservation},r.prototype.getClassName=function(){return"PBRBRDFConfiguration"},r.prototype.copyTo=function(t){L.a.Clone(function(){return t},this)},r.prototype.serialize=function(){return L.a.Serialize(this)},r.prototype.parse=function(t,e,n){var i=this;L.a.Parse(function(){return i},t,e,n)},r.DEFAULT_USE_ENERGY_CONSERVATION=!0,r.DEFAULT_USE_SMITH_VISIBILITY_HEIGHT_CORRELATED=!0,r.DEFAULT_USE_SPHERICAL_HARMONICS=!0,r.DEFAULT_USE_SPECULAR_GLOSSINESS_INPUT_ENERGY_CONSERVATION=!0,Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsMiscDirty")],r.prototype,"useEnergyConservation",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsMiscDirty")],r.prototype,"useSmithVisibilityHeightCorrelated",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsMiscDirty")],r.prototype,"useSphericalHarmonics",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsMiscDirty")],r.prototype,"useSpecularGlossinessInputEnergyConservation",void 0),r}(),co=function(){function r(t){this._isEnabled=!1,this.isEnabled=!1,this._linkSheenWithAlbedo=!1,this.linkSheenWithAlbedo=!1,this.intensity=1,this.color=M.a.White(),this._texture=null,this.texture=null,this._useRoughnessFromMainTexture=!0,this.useRoughnessFromMainTexture=!0,this._roughness=null,this.roughness=null,this._textureRoughness=null,this.textureRoughness=null,this._albedoScaling=!1,this.albedoScaling=!1,this._internalMarkAllSubMeshesAsTexturesDirty=t}return r.prototype._markAllSubMeshesAsTexturesDirty=function(){this._internalMarkAllSubMeshesAsTexturesDirty()},r.prototype.isReadyForSubMesh=function(t,e){return!(t._areTexturesDirty&&e.texturesEnabled&&(this._texture&&ht.a.SheenTextureEnabled&&!this._texture.isReadyOrNotBlocking()||this._textureRoughness&&ht.a.SheenTextureEnabled&&!this._textureRoughness.isReadyOrNotBlocking()))},r.prototype.prepareDefines=function(t,e){var n;this._isEnabled?(t.SHEEN=this._isEnabled,t.SHEEN_LINKWITHALBEDO=this._linkSheenWithAlbedo,t.SHEEN_ROUGHNESS=this._roughness!==null,t.SHEEN_ALBEDOSCALING=this._albedoScaling,t.SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE=this._useRoughnessFromMainTexture,t.SHEEN_TEXTURE_ROUGHNESS_IDENTICAL=this._texture!==null&&this._texture._texture===((n=this._textureRoughness)===null||n===void 0?void 0:n._texture)&&this._texture.checkTransformsAreIdentical(this._textureRoughness),t._areTexturesDirty&&e.texturesEnabled&&(this._texture&&ht.a.SheenTextureEnabled?et.a.PrepareDefinesForMergedUV(this._texture,t,"SHEEN_TEXTURE"):t.SHEEN_TEXTURE=!1,this._textureRoughness&&ht.a.SheenTextureEnabled?et.a.PrepareDefinesForMergedUV(this._textureRoughness,t,"SHEEN_TEXTURE_ROUGHNESS"):t.SHEEN_TEXTURE_ROUGHNESS=!1)):(t.SHEEN=!1,t.SHEEN_TEXTURE=!1,t.SHEEN_TEXTURE_ROUGHNESS=!1,t.SHEEN_LINKWITHALBEDO=!1,t.SHEEN_ROUGHNESS=!1,t.SHEEN_ALBEDOSCALING=!1,t.SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE=!1,t.SHEEN_TEXTURE_ROUGHNESS_IDENTICAL=!1)},r.prototype.bindForSubMesh=function(t,e,n,i){var o,a,s,d,p,b,P,O,B=i._materialDefines,F=B.SHEEN_TEXTURE_ROUGHNESS_IDENTICAL;t.useUbo&&n&&t.isSync||(F&&ht.a.SheenTextureEnabled?(t.updateFloat4("vSheenInfos",this._texture.coordinatesIndex,this._texture.level,-1,-1),et.a.BindTextureMatrix(this._texture,t,"sheen")):(this._texture||this._textureRoughness)&&ht.a.SheenTextureEnabled&&(t.updateFloat4("vSheenInfos",(a=(o=this._texture)===null||o===void 0?void 0:o.coordinatesIndex)!==null&&a!==void 0?a:0,(d=(s=this._texture)===null||s===void 0?void 0:s.level)!==null&&d!==void 0?d:0,(b=(p=this._textureRoughness)===null||p===void 0?void 0:p.coordinatesIndex)!==null&&b!==void 0?b:0,(O=(P=this._textureRoughness)===null||P===void 0?void 0:P.level)!==null&&O!==void 0?O:0),this._texture&&et.a.BindTextureMatrix(this._texture,t,"sheen"),!this._textureRoughness||F||B.SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE||et.a.BindTextureMatrix(this._textureRoughness,t,"sheenRoughness")),t.updateFloat4("vSheenColor",this.color.r,this.color.g,this.color.b,this.intensity),this._roughness!==null&&t.updateFloat("vSheenRoughness",this._roughness)),e.texturesEnabled&&(this._texture&&ht.a.SheenTextureEnabled&&t.setTexture("sheenSampler",this._texture),this._textureRoughness&&!F&&!B.SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE&&ht.a.SheenTextureEnabled&&t.setTexture("sheenRoughnessSampler",this._textureRoughness))},r.prototype.hasTexture=function(t){return this._texture===t||this._textureRoughness===t},r.prototype.getActiveTextures=function(t){this._texture&&t.push(this._texture),this._textureRoughness&&t.push(this._textureRoughness)},r.prototype.getAnimatables=function(t){this._texture&&this._texture.animations&&this._texture.animations.length>0&&t.push(this._texture),this._textureRoughness&&this._textureRoughness.animations&&this._textureRoughness.animations.length>0&&t.push(this._textureRoughness)},r.prototype.dispose=function(t){var e,n;t&&((e=this._texture)===null||e===void 0||e.dispose(),(n=this._textureRoughness)===null||n===void 0||n.dispose())},r.prototype.getClassName=function(){return"PBRSheenConfiguration"},r.AddFallbacks=function(t,e,n){return t.SHEEN&&e.addFallback(n++,"SHEEN"),n},r.AddUniforms=function(t){t.push("vSheenColor","vSheenRoughness","vSheenInfos","sheenMatrix","sheenRoughnessMatrix")},r.PrepareUniformBuffer=function(t){t.addUniform("vSheenColor",4),t.addUniform("vSheenRoughness",1),t.addUniform("vSheenInfos",4),t.addUniform("sheenMatrix",16),t.addUniform("sheenRoughnessMatrix",16)},r.AddSamplers=function(t){t.push("sheenSampler"),t.push("sheenRoughnessSampler")},r.prototype.copyTo=function(t){L.a.Clone(function(){return t},this)},r.prototype.serialize=function(){return L.a.Serialize(this)},r.prototype.parse=function(t,e,n){var i=this;L.a.Parse(function(){return i},t,e,n)},Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"isEnabled",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"linkSheenWithAlbedo",void 0),Object(c.c)([Object(L.c)()],r.prototype,"intensity",void 0),Object(c.c)([Object(L.e)()],r.prototype,"color",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"texture",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"useRoughnessFromMainTexture",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"roughness",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"textureRoughness",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"albedoScaling",void 0),r}(),lo=function(){function r(t,e,n){this._isRefractionEnabled=!1,this.isRefractionEnabled=!1,this._isTranslucencyEnabled=!1,this.isTranslucencyEnabled=!1,this._isScatteringEnabled=!1,this.isScatteringEnabled=!1,this._scatteringDiffusionProfileIndex=0,this.refractionIntensity=1,this.translucencyIntensity=1,this.useAlbedoToTintRefraction=!1,this._thicknessTexture=null,this.thicknessTexture=null,this._refractionTexture=null,this.refractionTexture=null,this._indexOfRefraction=1.5,this.indexOfRefraction=1.5,this._volumeIndexOfRefraction=-1,this._invertRefractionY=!1,this.invertRefractionY=!1,this._linkRefractionWithTransparency=!1,this.linkRefractionWithTransparency=!1,this.minimumThickness=0,this.maximumThickness=1,this.tintColor=M.a.White(),this.tintColorAtDistance=1,this.diffusionDistance=M.a.White(),this._useMaskFromThicknessTexture=!1,this.useMaskFromThicknessTexture=!1,this._useMaskFromThicknessTextureGltf=!1,this.useMaskFromThicknessTextureGltf=!1,this._internalMarkAllSubMeshesAsTexturesDirty=t,this._internalMarkScenePrePassDirty=e,this._scene=n}return Object.defineProperty(r.prototype,"scatteringDiffusionProfile",{get:function(){return this._scene.subSurfaceConfiguration?this._scene.subSurfaceConfiguration.ssDiffusionProfileColors[this._scatteringDiffusionProfileIndex]:null},set:function(t){this._scene.enableSubSurfaceForPrePass()&&t&&(this._scatteringDiffusionProfileIndex=this._scene.subSurfaceConfiguration.addDiffusionProfile(t))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"volumeIndexOfRefraction",{get:function(){return this._volumeIndexOfRefraction>=1?this._volumeIndexOfRefraction:this._indexOfRefraction},set:function(t){this._volumeIndexOfRefraction=t>=1?t:-1},enumerable:!1,configurable:!0}),r.prototype._markAllSubMeshesAsTexturesDirty=function(){this._internalMarkAllSubMeshesAsTexturesDirty()},r.prototype._markScenePrePassDirty=function(){this._internalMarkAllSubMeshesAsTexturesDirty(),this._internalMarkScenePrePassDirty()},r.prototype.isReadyForSubMesh=function(t,e){if(t._areTexturesDirty&&e.texturesEnabled){if(this._thicknessTexture&&ht.a.ThicknessTextureEnabled&&!this._thicknessTexture.isReadyOrNotBlocking())return!1;var n=this._getRefractionTexture(e);if(n&&ht.a.RefractionTextureEnabled&&!n.isReadyOrNotBlocking())return!1}return!0},r.prototype.prepareDefines=function(t,e){if(t._areTexturesDirty&&(t.SUBSURFACE=!1,t.SS_TRANSLUCENCY=this._isTranslucencyEnabled,t.SS_SCATTERING=this._isScatteringEnabled,t.SS_THICKNESSANDMASK_TEXTURE=!1,t.SS_MASK_FROM_THICKNESS_TEXTURE=!1,t.SS_MASK_FROM_THICKNESS_TEXTURE_GLTF=!1,t.SS_REFRACTION=!1,t.SS_REFRACTIONMAP_3D=!1,t.SS_GAMMAREFRACTION=!1,t.SS_RGBDREFRACTION=!1,t.SS_LINEARSPECULARREFRACTION=!1,t.SS_REFRACTIONMAP_OPPOSITEZ=!1,t.SS_LODINREFRACTIONALPHA=!1,t.SS_LINKREFRACTIONTOTRANSPARENCY=!1,t.SS_ALBEDOFORREFRACTIONTINT=!1,(this._isRefractionEnabled||this._isTranslucencyEnabled||this._isScatteringEnabled)&&(t.SUBSURFACE=!0,t._areTexturesDirty&&e.texturesEnabled&&this._thicknessTexture&&ht.a.ThicknessTextureEnabled&&et.a.PrepareDefinesForMergedUV(this._thicknessTexture,t,"SS_THICKNESSANDMASK_TEXTURE"),t.SS_MASK_FROM_THICKNESS_TEXTURE=this._useMaskFromThicknessTexture,t.SS_MASK_FROM_THICKNESS_TEXTURE_GLTF=this._useMaskFromThicknessTextureGltf),this._isRefractionEnabled&&e.texturesEnabled)){var n=this._getRefractionTexture(e);n&&ht.a.RefractionTextureEnabled&&(t.SS_REFRACTION=!0,t.SS_REFRACTIONMAP_3D=n.isCube,t.SS_GAMMAREFRACTION=n.gammaSpace,t.SS_RGBDREFRACTION=n.isRGBD,t.SS_LINEARSPECULARREFRACTION=n.linearSpecularLOD,t.SS_REFRACTIONMAP_OPPOSITEZ=n.invertZ,t.SS_LODINREFRACTIONALPHA=n.lodLevelInAlpha,t.SS_LINKREFRACTIONTOTRANSPARENCY=this._linkRefractionWithTransparency,t.SS_ALBEDOFORREFRACTIONTINT=this.useAlbedoToTintRefraction)}},r.prototype.bindForSubMesh=function(t,e,n,i,o,a){var s=this._getRefractionTexture(e);if(!t.useUbo||!i||!t.isSync){if(this._thicknessTexture&&ht.a.ThicknessTextureEnabled&&(t.updateFloat2("vThicknessInfos",this._thicknessTexture.coordinatesIndex,this._thicknessTexture.level),et.a.BindTextureMatrix(this._thicknessTexture,t,"thickness")),t.updateFloat2("vThicknessParam",this.minimumThickness,this.maximumThickness-this.minimumThickness),s&&ht.a.RefractionTextureEnabled){t.updateMatrix("refractionMatrix",s.getReflectionTextureMatrix());var d=1;s.isCube||s.depth&&(d=s.depth);var p=s.getSize().width,b=this.volumeIndexOfRefraction;t.updateFloat4("vRefractionInfos",s.level,1/b,d,this._invertRefractionY?-1:1),t.updateFloat3("vRefractionMicrosurfaceInfos",p,s.lodGenerationScale,s.lodGenerationOffset),a&&t.updateFloat2("vRefractionFilteringInfo",p,$.a.Log2(p))}this.isScatteringEnabled&&t.updateFloat("scatteringDiffusionProfile",this._scatteringDiffusionProfileIndex),t.updateColor3("vDiffusionDistance",this.diffusionDistance),t.updateFloat4("vTintColor",this.tintColor.r,this.tintColor.g,this.tintColor.b,this.tintColorAtDistance),t.updateFloat3("vSubSurfaceIntensity",this.refractionIntensity,this.translucencyIntensity,0)}e.texturesEnabled&&(this._thicknessTexture&&ht.a.ThicknessTextureEnabled&&t.setTexture("thicknessSampler",this._thicknessTexture),s&&ht.a.RefractionTextureEnabled&&(o?t.setTexture("refractionSampler",s):(t.setTexture("refractionSampler",s._lodTextureMid||s),t.setTexture("refractionSamplerLow",s._lodTextureLow||s),t.setTexture("refractionSamplerHigh",s._lodTextureHigh||s))))},r.prototype.unbind=function(t){return!(!this._refractionTexture||!this._refractionTexture.isRenderTarget)&&(t.setTexture("refractionSampler",null),!0)},r.prototype._getRefractionTexture=function(t){return this._refractionTexture?this._refractionTexture:this._isRefractionEnabled?t.environmentTexture:null},Object.defineProperty(r.prototype,"disableAlphaBlending",{get:function(){return this.isRefractionEnabled&&this._linkRefractionWithTransparency},enumerable:!1,configurable:!0}),r.prototype.fillRenderTargetTextures=function(t){ht.a.RefractionTextureEnabled&&this._refractionTexture&&this._refractionTexture.isRenderTarget&&t.push(this._refractionTexture)},r.prototype.hasTexture=function(t){return this._thicknessTexture===t||this._refractionTexture===t},r.prototype.hasRenderTargetTextures=function(){return!!(ht.a.RefractionTextureEnabled&&this._refractionTexture&&this._refractionTexture.isRenderTarget)},r.prototype.getActiveTextures=function(t){this._thicknessTexture&&t.push(this._thicknessTexture),this._refractionTexture&&t.push(this._refractionTexture)},r.prototype.getAnimatables=function(t){this._thicknessTexture&&this._thicknessTexture.animations&&this._thicknessTexture.animations.length>0&&t.push(this._thicknessTexture),this._refractionTexture&&this._refractionTexture.animations&&this._refractionTexture.animations.length>0&&t.push(this._refractionTexture)},r.prototype.dispose=function(t){t&&(this._thicknessTexture&&this._thicknessTexture.dispose(),this._refractionTexture&&this._refractionTexture.dispose())},r.prototype.getClassName=function(){return"PBRSubSurfaceConfiguration"},r.AddFallbacks=function(t,e,n){return t.SS_SCATTERING&&e.addFallback(n++,"SS_SCATTERING"),t.SS_TRANSLUCENCY&&e.addFallback(n++,"SS_TRANSLUCENCY"),n},r.AddUniforms=function(t){t.push("vDiffusionDistance","vTintColor","vSubSurfaceIntensity","vRefractionMicrosurfaceInfos","vRefractionFilteringInfo","vRefractionInfos","vThicknessInfos","vThicknessParam","refractionMatrix","thicknessMatrix","scatteringDiffusionProfile")},r.AddSamplers=function(t){t.push("thicknessSampler","refractionSampler","refractionSamplerLow","refractionSamplerHigh")},r.PrepareUniformBuffer=function(t){t.addUniform("vRefractionMicrosurfaceInfos",3),t.addUniform("vRefractionFilteringInfo",2),t.addUniform("vRefractionInfos",4),t.addUniform("refractionMatrix",16),t.addUniform("vThicknessInfos",2),t.addUniform("thicknessMatrix",16),t.addUniform("vThicknessParam",2),t.addUniform("vDiffusionDistance",3),t.addUniform("vTintColor",4),t.addUniform("vSubSurfaceIntensity",3),t.addUniform("scatteringDiffusionProfile",1)},r.prototype.copyTo=function(t){L.a.Clone(function(){return t},this)},r.prototype.serialize=function(){return L.a.Serialize(this)},r.prototype.parse=function(t,e,n){var i=this;L.a.Parse(function(){return i},t,e,n)},Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"isRefractionEnabled",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"isTranslucencyEnabled",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markScenePrePassDirty")],r.prototype,"isScatteringEnabled",void 0),Object(c.c)([Object(L.c)()],r.prototype,"_scatteringDiffusionProfileIndex",void 0),Object(c.c)([Object(L.c)()],r.prototype,"refractionIntensity",void 0),Object(c.c)([Object(L.c)()],r.prototype,"translucencyIntensity",void 0),Object(c.c)([Object(L.c)()],r.prototype,"useAlbedoToTintRefraction",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"thicknessTexture",void 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-uniform vec4 vAlbedoColor;
-
-uniform vec4 vLightingIntensity;
-uniform vec4 vReflectivityColor;
-uniform vec4 vMetallicReflectanceFactors;
-uniform vec3 vEmissiveColor;
-uniform float visibility;
-
-#ifdef ALBEDO
-uniform vec2 vAlbedoInfos;
-#endif
-#ifdef AMBIENT
-uniform vec4 vAmbientInfos;
-#endif
-#ifdef BUMP
-uniform vec3 vBumpInfos;
-uniform vec2 vTangentSpaceParams;
-#endif
-#ifdef OPACITY
-uniform vec2 vOpacityInfos;
-#endif
-#ifdef EMISSIVE
-uniform vec2 vEmissiveInfos;
-#endif
-#ifdef LIGHTMAP
-uniform vec2 vLightmapInfos;
-#endif
-#ifdef REFLECTIVITY
-uniform vec3 vReflectivityInfos;
-#endif
-#ifdef MICROSURFACEMAP
-uniform vec2 vMicroSurfaceSamplerInfos;
-#endif
-
-#if defined(REFLECTIONMAP_SPHERICAL) || defined(REFLECTIONMAP_PROJECTION) || defined(SS_REFRACTION)
-uniform mat4 view;
-#endif
-
-#ifdef REFLECTION
-uniform vec2 vReflectionInfos;
-#ifdef REALTIME_FILTERING
-uniform vec2 vReflectionFilteringInfo;
-#endif
-uniform mat4 reflectionMatrix;
-uniform vec3 vReflectionMicrosurfaceInfos;
-#if defined(USE_LOCAL_REFLECTIONMAP_CUBIC) && defined(REFLECTIONMAP_CUBIC)
-uniform vec3 vReflectionPosition;
-uniform vec3 vReflectionSize;
-#endif
-#endif
-
-#ifdef CLEARCOAT
-uniform vec2 vClearCoatParams;
-uniform vec4 vClearCoatRefractionParams;
-#if defined(CLEARCOAT_TEXTURE) || defined(CLEARCOAT_TEXTURE_ROUGHNESS)
-uniform vec4 vClearCoatInfos;
-#endif
-#ifdef CLEARCOAT_TEXTURE
-uniform mat4 clearCoatMatrix;
-#endif
-#ifdef CLEARCOAT_TEXTURE_ROUGHNESS
-uniform mat4 clearCoatRoughnessMatrix;
-#endif
-#ifdef CLEARCOAT_BUMP
-uniform vec2 vClearCoatBumpInfos;
-uniform vec2 vClearCoatTangentSpaceParams;
-uniform mat4 clearCoatBumpMatrix;
-#endif
-#ifdef CLEARCOAT_TINT
-uniform vec4 vClearCoatTintParams;
-uniform float clearCoatColorAtDistance;
-#ifdef CLEARCOAT_TINT_TEXTURE
-uniform vec2 vClearCoatTintInfos;
-uniform mat4 clearCoatTintMatrix;
-#endif
-#endif
-#endif
-
-#ifdef ANISOTROPIC
-uniform vec3 vAnisotropy;
-#ifdef ANISOTROPIC_TEXTURE
-uniform vec2 vAnisotropyInfos;
-uniform mat4 anisotropyMatrix;
-#endif
-#endif
-
-#ifdef SHEEN
-uniform vec4 vSheenColor;
-#ifdef SHEEN_ROUGHNESS
-uniform float vSheenRoughness;
-#endif
-#if defined(SHEEN_TEXTURE) || defined(SHEEN_TEXTURE_ROUGHNESS)
-uniform vec4 vSheenInfos;
-#endif
-#ifdef SHEEN_TEXTURE
-uniform mat4 sheenMatrix;
-#endif
-#ifdef SHEEN_TEXTURE_ROUGHNESS
-uniform mat4 sheenRoughnessMatrix;
-#endif
-#endif
-
-#ifdef SUBSURFACE
-#ifdef SS_REFRACTION
-uniform vec3 vRefractionMicrosurfaceInfos;
-uniform vec4 vRefractionInfos;
-uniform mat4 refractionMatrix;
-#ifdef REALTIME_FILTERING
-uniform vec2 vRefractionFilteringInfo;
-#endif
-#endif
-#ifdef SS_THICKNESSANDMASK_TEXTURE
-uniform vec2 vThicknessInfos;
-uniform mat4 thicknessMatrix;
-#endif
-uniform vec2 vThicknessParam;
-uniform vec3 vDiffusionDistance;
-uniform vec4 vTintColor;
-uniform vec3 vSubSurfaceIntensity;
-#endif
-#ifdef PREPASS
-#ifdef PREPASS_IRRADIANCE
-uniform float scatteringDiffusionProfile;
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-uniform Material
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-uniform vec2 vAlbedoInfos;
-uniform vec4 vAmbientInfos;
-uniform vec2 vOpacityInfos;
-uniform vec2 vEmissiveInfos;
-uniform vec2 vLightmapInfos;
-uniform vec3 vReflectivityInfos;
-uniform vec2 vMicroSurfaceSamplerInfos;
-uniform vec2 vReflectionInfos;
-uniform vec2 vReflectionFilteringInfo;
-uniform vec3 vReflectionPosition;
-uniform vec3 vReflectionSize;
-uniform vec3 vBumpInfos;
-uniform mat4 albedoMatrix;
-uniform mat4 ambientMatrix;
-uniform mat4 opacityMatrix;
-uniform mat4 emissiveMatrix;
-uniform mat4 lightmapMatrix;
-uniform mat4 reflectivityMatrix;
-uniform mat4 microSurfaceSamplerMatrix;
-uniform mat4 bumpMatrix;
-uniform vec2 vTangentSpaceParams;
-uniform mat4 reflectionMatrix;
-uniform vec3 vReflectionColor;
-uniform vec4 vAlbedoColor;
-uniform vec4 vLightingIntensity;
-uniform vec3 vReflectionMicrosurfaceInfos;
-uniform float pointSize;
-uniform vec4 vReflectivityColor;
-uniform vec3 vEmissiveColor;
-uniform float visibility;
-uniform vec4 vMetallicReflectanceFactors;
-uniform vec2 vMetallicReflectanceInfos;
-uniform mat4 metallicReflectanceMatrix;
-uniform vec2 vClearCoatParams;
-uniform vec4 vClearCoatRefractionParams;
-uniform vec4 vClearCoatInfos;
-uniform mat4 clearCoatMatrix;
-uniform mat4 clearCoatRoughnessMatrix;
-uniform vec2 vClearCoatBumpInfos;
-uniform vec2 vClearCoatTangentSpaceParams;
-uniform mat4 clearCoatBumpMatrix;
-uniform vec4 vClearCoatTintParams;
-uniform float clearCoatColorAtDistance;
-uniform vec2 vClearCoatTintInfos;
-uniform mat4 clearCoatTintMatrix;
-uniform vec3 vAnisotropy;
-uniform vec2 vAnisotropyInfos;
-uniform mat4 anisotropyMatrix;
-uniform vec4 vSheenColor;
-uniform float vSheenRoughness;
-uniform vec4 vSheenInfos;
-uniform mat4 sheenMatrix;
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-uniform vec2 vRefractionFilteringInfo;
-uniform vec4 vRefractionInfos;
-uniform mat4 refractionMatrix;
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-uniform mat4 thicknessMatrix;
-uniform vec2 vThicknessParam;
-uniform vec3 vDiffusionDistance;
-uniform vec4 vTintColor;
-uniform vec3 vSubSurfaceIntensity;
-uniform float scatteringDiffusionProfile;
-uniform vec4 vDetailInfos;
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-#define vMetallicReflectanceUV vMainUV1
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-#define vClearCoatUV vMainUV1
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-#endif
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-#define sampleReflection(s,c) texture2D(s,c)
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-#ifdef USEIRRADIANCEMAP
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-#endif
-#endif
-#ifdef REFLECTIONMAP_SKYBOX
-varying vec3 vPositionUVW;
-#else
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
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-#ifdef ENVIRONMENTBRDF
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-#ifdef SUBSURFACE
-#ifdef SS_REFRACTION
-#ifdef SS_REFRACTIONMAP_3D
-#define sampleRefraction(s,c) textureCube(s,c)
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-#ifdef LODBASEDMICROSFURACE
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-{
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-float reflectance90=saturate(reflectance0*25.0);
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-
-vec3 getAnisotropicBentNormals(const vec3 T,const vec3 B,const vec3 N,const vec3 V,float anisotropy) {
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-#ifdef MICROSURFACEAUTOMATIC
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-{
-const float kReflectivityNoAlphaWorkflow_SmoothnessMax=0.95;
-float reflectivityLuminance=getLuminance(reflectivityColor);
-float reflectivityLuma=sqrt(reflectivityLuminance);
-microSurface=reflectivityLuma*kReflectivityNoAlphaWorkflow_SmoothnessMax;
-return microSurface;
-}
-#endif`;ze.a.IncludesShadersStore.pbrHelperFunctions=Np;var wp=`#ifdef USESPHERICALFROMREFLECTIONMAP
-#ifdef SPHERICAL_HARMONICS
-uniform vec3 vSphericalL00;
-uniform vec3 vSphericalL1_1;
-uniform vec3 vSphericalL10;
-uniform vec3 vSphericalL11;
-uniform vec3 vSphericalL2_2;
-uniform vec3 vSphericalL2_1;
-uniform vec3 vSphericalL20;
-uniform vec3 vSphericalL21;
-uniform vec3 vSphericalL22;
-
-
-
-
-
-
-
-vec3 computeEnvironmentIrradiance(vec3 normal) {
-return vSphericalL00
-+vSphericalL1_1*(normal.y)
-+vSphericalL10*(normal.z)
-+vSphericalL11*(normal.x)
-+vSphericalL2_2*(normal.y*normal.x)
-+vSphericalL2_1*(normal.y*normal.z)
-+vSphericalL20*((3.0*normal.z*normal.z)-1.0)
-+vSphericalL21*(normal.z*normal.x)
-+vSphericalL22*(normal.x*normal.x-(normal.y*normal.y));
-}
-#else
-uniform vec3 vSphericalX;
-uniform vec3 vSphericalY;
-uniform vec3 vSphericalZ;
-uniform vec3 vSphericalXX_ZZ;
-uniform vec3 vSphericalYY_ZZ;
-uniform vec3 vSphericalZZ;
-uniform vec3 vSphericalXY;
-uniform vec3 vSphericalYZ;
-uniform vec3 vSphericalZX;
-
-vec3 computeEnvironmentIrradiance(vec3 normal) {
-
-
-
-
-
-
-
-
-
-float Nx=normal.x;
-float Ny=normal.y;
-float Nz=normal.z;
-vec3 C1=vSphericalZZ.rgb;
-vec3 Cx=vSphericalX.rgb;
-vec3 Cy=vSphericalY.rgb;
-vec3 Cz=vSphericalZ.rgb;
-vec3 Cxx_zz=vSphericalXX_ZZ.rgb;
-vec3 Cyy_zz=vSphericalYY_ZZ.rgb;
-vec3 Cxy=vSphericalXY.rgb;
-vec3 Cyz=vSphericalYZ.rgb;
-vec3 Czx=vSphericalZX.rgb;
-vec3 a1=Cyy_zz*Ny+Cy;
-vec3 a2=Cyz*Nz+a1;
-vec3 b1=Czx*Nz+Cx;
-vec3 b2=Cxy*Ny+b1;
-vec3 b3=Cxx_zz*Nx+b2;
-vec3 t1=Cz*Nz+C1;
-vec3 t2=a2*Ny+t1;
-vec3 t3=b3*Nx+t2;
-return t3;
-}
-#endif
-#endif`;ze.a.IncludesShadersStore.harmonicsFunctions=wp;var Fp=`
-struct preLightingInfo
-{
-
-vec3 lightOffset;
-float lightDistanceSquared;
-float lightDistance;
-
-float attenuation;
-
-vec3 L;
-vec3 H;
-float NdotV;
-float NdotLUnclamped;
-float NdotL;
-float VdotH;
-float roughness;
-};
-preLightingInfo computePointAndSpotPreLightingInfo(vec4 lightData,vec3 V,vec3 N) {
-preLightingInfo result;
-
-result.lightOffset=lightData.xyz-vPositionW;
-result.lightDistanceSquared=dot(result.lightOffset,result.lightOffset);
-
-result.lightDistance=sqrt(result.lightDistanceSquared);
-
-result.L=normalize(result.lightOffset);
-result.H=normalize(V+result.L);
-result.VdotH=saturate(dot(V,result.H));
-result.NdotLUnclamped=dot(N,result.L);
-result.NdotL=saturateEps(result.NdotLUnclamped);
-return result;
-}
-preLightingInfo computeDirectionalPreLightingInfo(vec4 lightData,vec3 V,vec3 N) {
-preLightingInfo result;
-
-result.lightDistance=length(-lightData.xyz);
-
-result.L=normalize(-lightData.xyz);
-result.H=normalize(V+result.L);
-result.VdotH=saturate(dot(V,result.H));
-result.NdotLUnclamped=dot(N,result.L);
-result.NdotL=saturateEps(result.NdotLUnclamped);
-return result;
-}
-preLightingInfo computeHemisphericPreLightingInfo(vec4 lightData,vec3 V,vec3 N) {
-preLightingInfo result;
-
-
-result.NdotL=dot(N,lightData.xyz)*0.5+0.5;
-result.NdotL=saturateEps(result.NdotL);
-result.NdotLUnclamped=result.NdotL;
-#ifdef SPECULARTERM
-result.L=normalize(lightData.xyz);
-result.H=normalize(V+result.L);
-result.VdotH=saturate(dot(V,result.H));
-#endif
-return result;
-}`;ze.a.IncludesShadersStore.pbrDirectLightingSetupFunctions=Fp;var Bp=`float computeDistanceLightFalloff_Standard(vec3 lightOffset,float range)
-{
-return max(0.,1.0-length(lightOffset)/range);
-}
-float computeDistanceLightFalloff_Physical(float lightDistanceSquared)
-{
-return 1.0/maxEps(lightDistanceSquared);
-}
-float computeDistanceLightFalloff_GLTF(float lightDistanceSquared,float inverseSquaredRange)
-{
-float lightDistanceFalloff=1.0/maxEps(lightDistanceSquared);
-float factor=lightDistanceSquared*inverseSquaredRange;
-float attenuation=saturate(1.0-factor*factor);
-attenuation*=attenuation;
-
-lightDistanceFalloff*=attenuation;
-return lightDistanceFalloff;
-}
-float computeDistanceLightFalloff(vec3 lightOffset,float lightDistanceSquared,float range,float inverseSquaredRange)
-{
-#ifdef USEPHYSICALLIGHTFALLOFF
-return computeDistanceLightFalloff_Physical(lightDistanceSquared);
-#elif defined(USEGLTFLIGHTFALLOFF)
-return computeDistanceLightFalloff_GLTF(lightDistanceSquared,inverseSquaredRange);
-#else
-return computeDistanceLightFalloff_Standard(lightOffset,range);
-#endif
-}
-float computeDirectionalLightFalloff_Standard(vec3 lightDirection,vec3 directionToLightCenterW,float cosHalfAngle,float exponent)
-{
-float falloff=0.0;
-float cosAngle=maxEps(dot(-lightDirection,directionToLightCenterW));
-if (cosAngle>=cosHalfAngle)
-{
-falloff=max(0.,pow(cosAngle,exponent));
-}
-return falloff;
-}
-float computeDirectionalLightFalloff_Physical(vec3 lightDirection,vec3 directionToLightCenterW,float cosHalfAngle)
-{
-const float kMinusLog2ConeAngleIntensityRatio=6.64385618977;
-
-
-
-
-
-float concentrationKappa=kMinusLog2ConeAngleIntensityRatio/(1.0-cosHalfAngle);
-
-
-vec4 lightDirectionSpreadSG=vec4(-lightDirection*concentrationKappa,-concentrationKappa);
-float falloff=exp2(dot(vec4(directionToLightCenterW,1.0),lightDirectionSpreadSG));
-return falloff;
-}
-float computeDirectionalLightFalloff_GLTF(vec3 lightDirection,vec3 directionToLightCenterW,float lightAngleScale,float lightAngleOffset)
-{
-
-
-
-float cd=dot(-lightDirection,directionToLightCenterW);
-float falloff=saturate(cd*lightAngleScale+lightAngleOffset);
-
-falloff*=falloff;
-return falloff;
-}
-float computeDirectionalLightFalloff(vec3 lightDirection,vec3 directionToLightCenterW,float cosHalfAngle,float exponent,float lightAngleScale,float lightAngleOffset)
-{
-#ifdef USEPHYSICALLIGHTFALLOFF
-return computeDirectionalLightFalloff_Physical(lightDirection,directionToLightCenterW,cosHalfAngle);
-#elif defined(USEGLTFLIGHTFALLOFF)
-return computeDirectionalLightFalloff_GLTF(lightDirection,directionToLightCenterW,lightAngleScale,lightAngleOffset);
-#else
-return computeDirectionalLightFalloff_Standard(lightDirection,directionToLightCenterW,cosHalfAngle,exponent);
-#endif
-}`;ze.a.IncludesShadersStore.pbrDirectLightingFalloffFunctions=Bp;var Up=`
-#define FRESNEL_MAXIMUM_ON_ROUGH 0.25
-
-
-
-
-#ifdef MS_BRDF_ENERGY_CONSERVATION
-
-
-vec3 getEnergyConservationFactor(const vec3 specularEnvironmentR0,const vec3 environmentBrdf) {
-return 1.0+specularEnvironmentR0*(1.0/environmentBrdf.y-1.0);
-}
-#endif
-#ifdef ENVIRONMENTBRDF
-vec3 getBRDFLookup(float NdotV,float perceptualRoughness) {
-
-vec2 UV=vec2(NdotV,perceptualRoughness);
-
-vec4 brdfLookup=texture2D(environmentBrdfSampler,UV);
-#ifdef ENVIRONMENTBRDF_RGBD
-brdfLookup.rgb=fromRGBD(brdfLookup.rgba);
-#endif
-return brdfLookup.rgb;
-}
-vec3 getReflectanceFromBRDFLookup(const vec3 specularEnvironmentR0,const vec3 specularEnvironmentR90,const vec3 environmentBrdf) {
-#ifdef BRDF_V_HEIGHT_CORRELATED
-vec3 reflectance=(specularEnvironmentR90-specularEnvironmentR0)*environmentBrdf.x+specularEnvironmentR0*environmentBrdf.y;
-
-#else
-vec3 reflectance=specularEnvironmentR0*environmentBrdf.x+specularEnvironmentR90*environmentBrdf.y;
-#endif
-return reflectance;
-}
-vec3 getReflectanceFromBRDFLookup(const vec3 specularEnvironmentR0,const vec3 environmentBrdf) {
-#ifdef BRDF_V_HEIGHT_CORRELATED
-vec3 reflectance=mix(environmentBrdf.xxx,environmentBrdf.yyy,specularEnvironmentR0);
-#else
-vec3 reflectance=specularEnvironmentR0*environmentBrdf.x+environmentBrdf.y;
-#endif
-return reflectance;
-}
-#endif
-
-#if !defined(ENVIRONMENTBRDF) || defined(REFLECTIONMAP_SKYBOX) || defined(ALPHAFRESNEL)
-vec3 getReflectanceFromAnalyticalBRDFLookup_Jones(float VdotN,vec3 reflectance0,vec3 reflectance90,float smoothness)
-{
-
-float weight=mix(FRESNEL_MAXIMUM_ON_ROUGH,1.0,smoothness);
-return reflectance0+weight*(reflectance90-reflectance0)*pow5(saturate(1.0-VdotN));
-}
-#endif
-#if defined(SHEEN) && defined(ENVIRONMENTBRDF)
-
-vec3 getSheenReflectanceFromBRDFLookup(const vec3 reflectance0,const vec3 environmentBrdf) {
-vec3 sheenEnvironmentReflectance=reflectance0*environmentBrdf.b;
-return sheenEnvironmentReflectance;
-}
-#endif
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-vec3 fresnelSchlickGGX(float VdotH,vec3 reflectance0,vec3 reflectance90)
-{
-return reflectance0+(reflectance90-reflectance0)*pow5(1.0-VdotH);
-}
-float fresnelSchlickGGX(float VdotH,float reflectance0,float reflectance90)
-{
-return reflectance0+(reflectance90-reflectance0)*pow5(1.0-VdotH);
-}
-#ifdef CLEARCOAT
-
-
-
-
-
-vec3 getR0RemappedForClearCoat(vec3 f0) {
-#ifdef CLEARCOAT_DEFAULTIOR
-#ifdef MOBILE
-return saturate(f0*(f0*0.526868+0.529324)-0.0482256);
-#else
-return saturate(f0*(f0*(0.941892-0.263008*f0)+0.346479)-0.0285998);
-#endif
-#else
-vec3 s=sqrt(f0);
-vec3 t=(vClearCoatRefractionParams.z+vClearCoatRefractionParams.w*s)/(vClearCoatRefractionParams.w+vClearCoatRefractionParams.z*s);
-return t*t;
-#endif
-}
-#endif
-
-
-
-
-
-
-float normalDistributionFunction_TrowbridgeReitzGGX(float NdotH,float alphaG)
-{
-
-
-
-float a2=square(alphaG);
-float d=NdotH*NdotH*(a2-1.0)+1.0;
-return a2/(PI*d*d);
-}
-#ifdef SHEEN
-
-
-float normalDistributionFunction_CharlieSheen(float NdotH,float alphaG)
-{
-float invR=1./alphaG;
-float cos2h=NdotH*NdotH;
-float sin2h=1.-cos2h;
-return (2.+invR)*pow(sin2h,invR*.5)/(2.*PI);
-}
-#endif
-#ifdef ANISOTROPIC
-
-
-float normalDistributionFunction_BurleyGGX_Anisotropic(float NdotH,float TdotH,float BdotH,const vec2 alphaTB) {
-float a2=alphaTB.x*alphaTB.y;
-vec3 v=vec3(alphaTB.y*TdotH,alphaTB.x*BdotH,a2*NdotH);
-float v2=dot(v,v);
-float w2=a2/v2;
-return a2*w2*w2*RECIPROCAL_PI;
-}
-#endif
-
-
-
-
-#ifdef BRDF_V_HEIGHT_CORRELATED
-
-
-
-float smithVisibility_GGXCorrelated(float NdotL,float NdotV,float alphaG) {
-#ifdef MOBILE
-
-float GGXV=NdotL*(NdotV*(1.0-alphaG)+alphaG);
-float GGXL=NdotV*(NdotL*(1.0-alphaG)+alphaG);
-return 0.5/(GGXV+GGXL);
-#else
-float a2=alphaG*alphaG;
-float GGXV=NdotL*sqrt(NdotV*(NdotV-a2*NdotV)+a2);
-float GGXL=NdotV*sqrt(NdotL*(NdotL-a2*NdotL)+a2);
-return 0.5/(GGXV+GGXL);
-#endif
-}
-#else
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-float smithVisibilityG1_TrowbridgeReitzGGXFast(float dot,float alphaG)
-{
-#ifdef MOBILE
-
-return 1.0/(dot+alphaG+(1.0-alphaG)*dot ));
-#else
-float alphaSquared=alphaG*alphaG;
-return 1.0/(dot+sqrt(alphaSquared+(1.0-alphaSquared)*dot*dot));
-#endif
-}
-float smithVisibility_TrowbridgeReitzGGXFast(float NdotL,float NdotV,float alphaG)
-{
-float visibility=smithVisibilityG1_TrowbridgeReitzGGXFast(NdotL,alphaG)*smithVisibilityG1_TrowbridgeReitzGGXFast(NdotV,alphaG);
-
-return visibility;
-}
-#endif
-#ifdef ANISOTROPIC
-
-
-float smithVisibility_GGXCorrelated_Anisotropic(float NdotL,float NdotV,float TdotV,float BdotV,float TdotL,float BdotL,const vec2 alphaTB) {
-float lambdaV=NdotL*length(vec3(alphaTB.x*TdotV,alphaTB.y*BdotV,NdotV));
-float lambdaL=NdotV*length(vec3(alphaTB.x*TdotL,alphaTB.y*BdotL,NdotL));
-float v=0.5/(lambdaV+lambdaL);
-return v;
-}
-#endif
-#ifdef CLEARCOAT
-float visibility_Kelemen(float VdotH) {
-
-
-
-return 0.25/(VdotH*VdotH);
-}
-#endif
-#ifdef SHEEN
-
-
-
-float visibility_Ashikhmin(float NdotL,float NdotV)
-{
-return 1./(4.*(NdotL+NdotV-NdotL*NdotV));
-}
-
-#endif
-
-
-
-
-
-
-
-float diffuseBRDF_Burley(float NdotL,float NdotV,float VdotH,float roughness) {
-
-
-float diffuseFresnelNV=pow5(saturateEps(1.0-NdotL));
-float diffuseFresnelNL=pow5(saturateEps(1.0-NdotV));
-float diffuseFresnel90=0.5+2.0*VdotH*VdotH*roughness;
-float fresnel =
-(1.0+(diffuseFresnel90-1.0)*diffuseFresnelNL) *
-(1.0+(diffuseFresnel90-1.0)*diffuseFresnelNV);
-return fresnel/PI;
-}
-#ifdef SS_TRANSLUCENCY
-
-
-vec3 transmittanceBRDF_Burley(const vec3 tintColor,const vec3 diffusionDistance,float thickness) {
-vec3 S=1./maxEps(diffusionDistance);
-vec3 temp=exp((-0.333333333*thickness)*S);
-return tintColor.rgb*0.25*(temp*temp*temp+3.0*temp);
-}
-
-
-float computeWrappedDiffuseNdotL(float NdotL,float w) {
-float t=1.0+w;
-float invt2=1.0/square(t);
-return saturate((NdotL+w)*invt2);
-}
-#endif
-`;ze.a.IncludesShadersStore.pbrBRDFFunctions=Up;var Vp=`#ifdef NUM_SAMPLES
-#if NUM_SAMPLES>0
-#ifdef WEBGL2
-
-
-float radicalInverse_VdC(uint bits)
-{
-bits=(bits << 16u) | (bits >> 16u);
-bits=((bits & 0x55555555u) << 1u) | ((bits & 0xAAAAAAAAu) >> 1u);
-bits=((bits & 0x33333333u) << 2u) | ((bits & 0xCCCCCCCCu) >> 2u);
-bits=((bits & 0x0F0F0F0Fu) << 4u) | ((bits & 0xF0F0F0F0u) >> 4u);
-bits=((bits & 0x00FF00FFu) << 8u) | ((bits & 0xFF00FF00u) >> 8u);
-return float(bits)*2.3283064365386963e-10;
-}
-vec2 hammersley(uint i,uint N)
-{
-return vec2(float(i)/float(N),radicalInverse_VdC(i));
-}
-#else
-float vanDerCorpus(int n,int base)
-{
-float invBase=1.0/float(base);
-float denom=1.0;
-float result=0.0;
-for(int i=0; i<32; ++i)
-{
-if(n>0)
-{
-denom=mod(float(n),2.0);
-result+=denom*invBase;
-invBase=invBase/2.0;
-n=int(float(n)/2.0);
-}
-}
-return result;
-}
-vec2 hammersley(int i,int N)
-{
-return vec2(float(i)/float(N),vanDerCorpus(i,2));
-}
-#endif
-float log4(float x) {
-return log2(x)/2.;
-}
-const float NUM_SAMPLES_FLOAT=float(NUM_SAMPLES);
-const float NUM_SAMPLES_FLOAT_INVERSED=1./NUM_SAMPLES_FLOAT;
-const float K=4.;
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
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-
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-
-
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-
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-
-
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-
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-
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-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-#define inline
-vec3 irradiance(samplerCube inputTexture,vec3 inputN,vec2 filteringInfo)
-{
-vec3 n=normalize(inputN);
-vec3 result=vec3(0.0);
-vec3 tangent=abs(n.z)<0.999 ? vec3(0.,0.,1.) : vec3(1.,0.,0.);
-tangent=normalize(cross(tangent,n));
-vec3 bitangent=cross(n,tangent);
-mat3 tbn=mat3(tangent,bitangent,n);
-float maxLevel=filteringInfo.y;
-float dim0=filteringInfo.x;
-float omegaP=(4.*PI)/(6.*dim0*dim0);
-#ifdef WEBGL2
-for(uint i=0u; i<NUM_SAMPLES; ++i)
-#else
-for(int i=0; i<NUM_SAMPLES; ++i)
-#endif
-{
-vec2 Xi=hammersley(i,NUM_SAMPLES);
-vec3 Ls=hemisphereCosSample(Xi);
-Ls=normalize(Ls);
-vec3 Ns=vec3(0.,0.,1.);
-float NoL=dot(Ns,Ls);
-if (NoL>0.) {
-float pdf_inversed=PI/NoL;
-float omegaS=NUM_SAMPLES_FLOAT_INVERSED*pdf_inversed;
-float l=log4(omegaS)-log4(omegaP)+log4(K);
-float mipLevel=clamp(l,0.0,maxLevel);
-vec3 c=textureCubeLodEXT(inputTexture,tbn*Ls,mipLevel).rgb;
-#ifdef GAMMA_INPUT
-c=toLinearSpace(c);
-#endif
-result+=c;
-}
-}
-result=result*NUM_SAMPLES_FLOAT_INVERSED;
-return result;
-}
-#define inline
-vec3 radiance(float alphaG,samplerCube inputTexture,vec3 inputN,vec2 filteringInfo)
-{
-vec3 n=normalize(inputN);
-if (alphaG == 0.) {
-vec3 c=textureCube(inputTexture,n).rgb;
-#ifdef GAMMA_INPUT
-c=toLinearSpace(c);
-#endif
-return c;
-}
-vec3 result=vec3(0.);
-vec3 tangent=abs(n.z)<0.999 ? vec3(0.,0.,1.) : vec3(1.,0.,0.);
-tangent=normalize(cross(tangent,n));
-vec3 bitangent=cross(n,tangent);
-mat3 tbn=mat3(tangent,bitangent,n);
-float maxLevel=filteringInfo.y;
-float dim0=filteringInfo.x;
-float omegaP=(4.*PI)/(6.*dim0*dim0);
-float weight=0.;
-#ifdef WEBGL2
-for(uint i=0u; i<NUM_SAMPLES; ++i)
-#else
-for(int i=0; i<NUM_SAMPLES; ++i)
-#endif
-{
-vec2 Xi=hammersley(i,NUM_SAMPLES);
-vec3 H=hemisphereImportanceSampleDggx(Xi,alphaG);
-float NoV=1.;
-float NoH=H.z;
-float NoH2=H.z*H.z;
-float NoL=2.*NoH2-1.;
-vec3 L=vec3(2.*NoH*H.x,2.*NoH*H.y,NoL);
-L=normalize(L);
-if (NoL>0.) {
-float pdf_inversed=4./normalDistributionFunction_TrowbridgeReitzGGX(NoH,alphaG);
-float omegaS=NUM_SAMPLES_FLOAT_INVERSED*pdf_inversed;
-float l=log4(omegaS)-log4(omegaP)+log4(K);
-float mipLevel=clamp(float(l),0.0,maxLevel);
-weight+=NoL;
-vec3 c=textureCubeLodEXT(inputTexture,tbn*L,mipLevel).rgb;
-#ifdef GAMMA_INPUT
-c=toLinearSpace(c);
-#endif
-result+=c*NoL;
-}
-}
-result=result/weight;
-return result;
-}
-#endif
-#endif`;ze.a.IncludesShadersStore.hdrFilteringFunctions=Vp;var kp=`#define CLEARCOATREFLECTANCE90 1.0
-
-struct lightingInfo
-{
-vec3 diffuse;
-#ifdef SPECULARTERM
-vec3 specular;
-#endif
-#ifdef CLEARCOAT
-
-
-vec4 clearCoat;
-#endif
-#ifdef SHEEN
-vec3 sheen;
-#endif
-};
-
-float adjustRoughnessFromLightProperties(float roughness,float lightRadius,float lightDistance) {
-#if defined(USEPHYSICALLIGHTFALLOFF) || defined(USEGLTFLIGHTFALLOFF)
-
-float lightRoughness=lightRadius/lightDistance;
-
-float totalRoughness=saturate(lightRoughness+roughness);
-return totalRoughness;
-#else
-return roughness;
-#endif
-}
-vec3 computeHemisphericDiffuseLighting(preLightingInfo info,vec3 lightColor,vec3 groundColor) {
-return mix(groundColor,lightColor,info.NdotL);
-}
-vec3 computeDiffuseLighting(preLightingInfo info,vec3 lightColor) {
-float diffuseTerm=diffuseBRDF_Burley(info.NdotL,info.NdotV,info.VdotH,info.roughness);
-return diffuseTerm*info.attenuation*info.NdotL*lightColor;
-}
-#define inline
-vec3 computeProjectionTextureDiffuseLighting(sampler2D projectionLightSampler,mat4 textureProjectionMatrix){
-vec4 strq=textureProjectionMatrix*vec4(vPositionW,1.0);
-strq/=strq.w;
-vec3 textureColor=texture2D(projectionLightSampler,strq.xy).rgb;
-return toLinearSpace(textureColor);
-}
-#ifdef SS_TRANSLUCENCY
-vec3 computeDiffuseAndTransmittedLighting(preLightingInfo info,vec3 lightColor,vec3 transmittance) {
-float NdotL=absEps(info.NdotLUnclamped);
-
-float wrapNdotL=computeWrappedDiffuseNdotL(NdotL,0.02);
-
-float trAdapt=step(0.,info.NdotLUnclamped);
-vec3 transmittanceNdotL=mix(transmittance*wrapNdotL,vec3(wrapNdotL),trAdapt);
-float diffuseTerm=diffuseBRDF_Burley(NdotL,info.NdotV,info.VdotH,info.roughness);
-return diffuseTerm*transmittanceNdotL*info.attenuation*lightColor;
-}
-#endif
-#ifdef SPECULARTERM
-vec3 computeSpecularLighting(preLightingInfo info,vec3 N,vec3 reflectance0,vec3 reflectance90,float geometricRoughnessFactor,vec3 lightColor) {
-float NdotH=saturateEps(dot(N,info.H));
-float roughness=max(info.roughness,geometricRoughnessFactor);
-float alphaG=convertRoughnessToAverageSlope(roughness);
-vec3 fresnel=fresnelSchlickGGX(info.VdotH,reflectance0,reflectance90);
-float distribution=normalDistributionFunction_TrowbridgeReitzGGX(NdotH,alphaG);
-#ifdef BRDF_V_HEIGHT_CORRELATED
-float smithVisibility=smithVisibility_GGXCorrelated(info.NdotL,info.NdotV,alphaG);
-#else
-float smithVisibility=smithVisibility_TrowbridgeReitzGGXFast(info.NdotL,info.NdotV,alphaG);
-#endif
-vec3 specTerm=fresnel*distribution*smithVisibility;
-return specTerm*info.attenuation*info.NdotL*lightColor;
-}
-#endif
-#ifdef ANISOTROPIC
-vec3 computeAnisotropicSpecularLighting(preLightingInfo info,vec3 V,vec3 N,vec3 T,vec3 B,float anisotropy,vec3 reflectance0,vec3 reflectance90,float geometricRoughnessFactor,vec3 lightColor) {
-float NdotH=saturateEps(dot(N,info.H));
-float TdotH=dot(T,info.H);
-float BdotH=dot(B,info.H);
-float TdotV=dot(T,V);
-float BdotV=dot(B,V);
-float TdotL=dot(T,info.L);
-float BdotL=dot(B,info.L);
-float alphaG=convertRoughnessToAverageSlope(info.roughness);
-vec2 alphaTB=getAnisotropicRoughness(alphaG,anisotropy);
-alphaTB=max(alphaTB,square(geometricRoughnessFactor));
-vec3 fresnel=fresnelSchlickGGX(info.VdotH,reflectance0,reflectance90);
-float distribution=normalDistributionFunction_BurleyGGX_Anisotropic(NdotH,TdotH,BdotH,alphaTB);
-float smithVisibility=smithVisibility_GGXCorrelated_Anisotropic(info.NdotL,info.NdotV,TdotV,BdotV,TdotL,BdotL,alphaTB);
-vec3 specTerm=fresnel*distribution*smithVisibility;
-return specTerm*info.attenuation*info.NdotL*lightColor;
-}
-#endif
-#ifdef CLEARCOAT
-vec4 computeClearCoatLighting(preLightingInfo info,vec3 Ncc,float geometricRoughnessFactor,float clearCoatIntensity,vec3 lightColor) {
-float NccdotL=saturateEps(dot(Ncc,info.L));
-float NccdotH=saturateEps(dot(Ncc,info.H));
-float clearCoatRoughness=max(info.roughness,geometricRoughnessFactor);
-float alphaG=convertRoughnessToAverageSlope(clearCoatRoughness);
-float fresnel=fresnelSchlickGGX(info.VdotH,vClearCoatRefractionParams.x,CLEARCOATREFLECTANCE90);
-fresnel*=clearCoatIntensity;
-float distribution=normalDistributionFunction_TrowbridgeReitzGGX(NccdotH,alphaG);
-float kelemenVisibility=visibility_Kelemen(info.VdotH);
-float clearCoatTerm=fresnel*distribution*kelemenVisibility;
-return vec4(
-clearCoatTerm*info.attenuation*NccdotL*lightColor,
-1.0-fresnel
-);
-}
-vec3 computeClearCoatLightingAbsorption(float NdotVRefract,vec3 L,vec3 Ncc,vec3 clearCoatColor,float clearCoatThickness,float clearCoatIntensity) {
-vec3 LRefract=-refract(L,Ncc,vClearCoatRefractionParams.y);
-float NdotLRefract=saturateEps(dot(Ncc,LRefract));
-vec3 absorption=computeClearCoatAbsorption(NdotVRefract,NdotLRefract,clearCoatColor,clearCoatThickness,clearCoatIntensity);
-return absorption;
-}
-#endif
-#ifdef SHEEN
-vec3 computeSheenLighting(preLightingInfo info,vec3 N,vec3 reflectance0,vec3 reflectance90,float geometricRoughnessFactor,vec3 lightColor) {
-float NdotH=saturateEps(dot(N,info.H));
-float roughness=max(info.roughness,geometricRoughnessFactor);
-float alphaG=convertRoughnessToAverageSlope(roughness);
-
-
-float fresnel=1.;
-float distribution=normalDistributionFunction_CharlieSheen(NdotH,alphaG);
-
-float visibility=visibility_Ashikhmin(info.NdotL,info.NdotV);
-
-float sheenTerm=fresnel*distribution*visibility;
-return sheenTerm*info.attenuation*info.NdotL*lightColor;
-}
-#endif
-`;ze.a.IncludesShadersStore.pbrDirectLightingFunctions=kp;var Gp=`#if defined(REFLECTION) || defined(SS_REFRACTION)
-float getLodFromAlphaG(float cubeMapDimensionPixels,float microsurfaceAverageSlope) {
-float microsurfaceAverageSlopeTexels=cubeMapDimensionPixels*microsurfaceAverageSlope;
-float lod=log2(microsurfaceAverageSlopeTexels);
-return lod;
-}
-float getLinearLodFromRoughness(float cubeMapDimensionPixels,float roughness) {
-float lod=log2(cubeMapDimensionPixels)*roughness;
-return lod;
-}
-#endif
-#if defined(ENVIRONMENTBRDF) && defined(RADIANCEOCCLUSION)
-float environmentRadianceOcclusion(float ambientOcclusion,float NdotVUnclamped) {
-
-
-float temp=NdotVUnclamped+ambientOcclusion;
-return saturate(square(temp)-1.0+ambientOcclusion);
-}
-#endif
-#if defined(ENVIRONMENTBRDF) && defined(HORIZONOCCLUSION)
-float environmentHorizonOcclusion(vec3 view,vec3 normal,vec3 geometricNormal) {
-
-vec3 reflection=reflect(view,normal);
-float temp=saturate(1.0+1.1*dot(reflection,geometricNormal));
-return square(temp);
-}
-#endif
-
-
-
-
-#if defined(LODINREFLECTIONALPHA) || defined(SS_LODINREFRACTIONALPHA)
-
-
-#define UNPACK_LOD(x) (1.0-x)*255.0
-float getLodFromAlphaG(float cubeMapDimensionPixels,float alphaG,float NdotV) {
-float microsurfaceAverageSlope=alphaG;
-
-
-
-
-
-
-microsurfaceAverageSlope*=sqrt(abs(NdotV));
-return getLodFromAlphaG(cubeMapDimensionPixels,microsurfaceAverageSlope);
-}
-#endif`;ze.a.IncludesShadersStore.pbrIBLFunctions=Gp,f(132),f(133);var zp=`struct albedoOpacityOutParams
-{
-vec3 surfaceAlbedo;
-float alpha;
-};
-#define pbr_inline
-void albedoOpacityBlock(
-const in vec4 vAlbedoColor,
-#ifdef ALBEDO
-const in vec4 albedoTexture,
-const in vec2 albedoInfos,
-#endif
-#ifdef OPACITY
-const in vec4 opacityMap,
-const in vec2 vOpacityInfos,
-#endif
-#ifdef DETAIL
-const in vec4 detailColor,
-const in vec4 vDetailInfos,
-#endif
-out albedoOpacityOutParams outParams
-)
-{
-
-vec3 surfaceAlbedo=vAlbedoColor.rgb;
-float alpha=vAlbedoColor.a;
-#ifdef ALBEDO
-#if defined(ALPHAFROMALBEDO) || defined(ALPHATEST)
-alpha*=albedoTexture.a;
-#endif
-#ifdef GAMMAALBEDO
-surfaceAlbedo*=toLinearSpace(albedoTexture.rgb);
-#else
-surfaceAlbedo*=albedoTexture.rgb;
-#endif
-surfaceAlbedo*=albedoInfos.y;
-#endif
-#ifdef VERTEXCOLOR
-surfaceAlbedo*=vColor.rgb;
-#endif
-#ifdef DETAIL
-float detailAlbedo=2.0*mix(0.5,detailColor.r,vDetailInfos.y);
-surfaceAlbedo.rgb=surfaceAlbedo.rgb*detailAlbedo*detailAlbedo;
-#endif
-#define CUSTOM_FRAGMENT_UPDATE_ALBEDO
-
-#ifdef OPACITY
-#ifdef OPACITYRGB
-alpha=getLuminance(opacityMap.rgb);
-#else
-alpha*=opacityMap.a;
-#endif
-alpha*=vOpacityInfos.y;
-#endif
-#ifdef VERTEXALPHA
-alpha*=vColor.a;
-#endif
-#if !defined(SS_LINKREFRACTIONTOTRANSPARENCY) && !defined(ALPHAFRESNEL)
-#ifdef ALPHATEST
-if (alpha<ALPHATESTVALUE)
-discard;
-#ifndef ALPHABLEND
-
-alpha=1.0;
-#endif
-#endif
-#endif
-outParams.surfaceAlbedo=surfaceAlbedo;
-outParams.alpha=alpha;
-}
-`;ze.a.IncludesShadersStore.pbrBlockAlbedoOpacity=zp;var jp=`struct reflectivityOutParams
-{
-float microSurface;
-float roughness;
-vec3 surfaceReflectivityColor;
-#ifdef METALLICWORKFLOW
-vec3 surfaceAlbedo;
-#endif
-#if defined(METALLICWORKFLOW) && defined(REFLECTIVITY) && defined(AOSTOREINMETALMAPRED)
-vec3 ambientOcclusionColor;
-#endif
-#if DEBUGMODE>0
-vec4 surfaceMetallicColorMap;
-vec4 surfaceReflectivityColorMap;
-vec2 metallicRoughness;
-vec3 metallicF0;
-#endif
-};
-#define pbr_inline
-void reflectivityBlock(
-const in vec4 vReflectivityColor,
-#ifdef METALLICWORKFLOW
-const in vec3 surfaceAlbedo,
-const in vec4 metallicReflectanceFactors,
-#endif
-#ifdef REFLECTIVITY
-const in vec3 reflectivityInfos,
-const in vec4 surfaceMetallicOrReflectivityColorMap,
-#endif
-#if defined(METALLICWORKFLOW) && defined(REFLECTIVITY) && defined(AOSTOREINMETALMAPRED)
-const in vec3 ambientOcclusionColorIn,
-#endif
-#ifdef MICROSURFACEMAP
-const in vec4 microSurfaceTexel,
-#endif
-#ifdef DETAIL
-const in vec4 detailColor,
-const in vec4 vDetailInfos,
-#endif
-out reflectivityOutParams outParams
-)
-{
-float microSurface=vReflectivityColor.a;
-vec3 surfaceReflectivityColor=vReflectivityColor.rgb;
-#ifdef METALLICWORKFLOW
-vec2 metallicRoughness=surfaceReflectivityColor.rg;
-#ifdef REFLECTIVITY
-#if DEBUGMODE>0
-outParams.surfaceMetallicColorMap=surfaceMetallicOrReflectivityColorMap;
-#endif
-#ifdef AOSTOREINMETALMAPRED
-vec3 aoStoreInMetalMap=vec3(surfaceMetallicOrReflectivityColorMap.r,surfaceMetallicOrReflectivityColorMap.r,surfaceMetallicOrReflectivityColorMap.r);
-outParams.ambientOcclusionColor=mix(ambientOcclusionColorIn,aoStoreInMetalMap,reflectivityInfos.z);
-#endif
-#ifdef METALLNESSSTOREINMETALMAPBLUE
-metallicRoughness.r*=surfaceMetallicOrReflectivityColorMap.b;
-#else
-metallicRoughness.r*=surfaceMetallicOrReflectivityColorMap.r;
-#endif
-#ifdef ROUGHNESSSTOREINMETALMAPALPHA
-metallicRoughness.g*=surfaceMetallicOrReflectivityColorMap.a;
-#else
-#ifdef ROUGHNESSSTOREINMETALMAPGREEN
-metallicRoughness.g*=surfaceMetallicOrReflectivityColorMap.g;
-#endif
-#endif
-#endif
-#ifdef DETAIL
-float detailRoughness=mix(0.5,detailColor.b,vDetailInfos.w);
-float loLerp=mix(0.,metallicRoughness.g,detailRoughness*2.);
-float hiLerp=mix(metallicRoughness.g,1.,(detailRoughness-0.5)*2.);
-metallicRoughness.g=mix(loLerp,hiLerp,step(detailRoughness,0.5));
-#endif
-#ifdef MICROSURFACEMAP
-metallicRoughness.g*=microSurfaceTexel.r;
-#endif
-#if DEBUGMODE>0
-outParams.metallicRoughness=metallicRoughness;
-#endif
-#define CUSTOM_FRAGMENT_UPDATE_METALLICROUGHNESS
-
-microSurface=1.0-metallicRoughness.g;
-
-vec3 baseColor=surfaceAlbedo;
-#ifdef FROSTBITE_REFLECTANCE
-
-
-
-
-
-
-outParams.surfaceAlbedo=baseColor.rgb*(1.0-metallicRoughness.r);
-
-surfaceReflectivityColor=mix(0.16*reflectance*reflectance,baseColor,metallicRoughness.r);
-#else
-vec3 metallicF0=metallicReflectanceFactors.rgb;
-#if DEBUGMODE>0
-outParams.metallicF0=metallicF0;
-#endif
-
-outParams.surfaceAlbedo=mix(baseColor.rgb*(1.0-metallicF0),vec3(0.,0.,0.),metallicRoughness.r);
-
-surfaceReflectivityColor=mix(metallicF0,baseColor,metallicRoughness.r);
-#endif
-#else
-#ifdef REFLECTIVITY
-surfaceReflectivityColor*=surfaceMetallicOrReflectivityColorMap.rgb;
-#if DEBUGMODE>0
-outParams.surfaceReflectivityColorMap=surfaceMetallicOrReflectivityColorMap;
-#endif
-#ifdef MICROSURFACEFROMREFLECTIVITYMAP
-microSurface*=surfaceMetallicOrReflectivityColorMap.a;
-microSurface*=reflectivityInfos.z;
-#else
-#ifdef MICROSURFACEAUTOMATIC
-microSurface*=computeDefaultMicroSurface(microSurface,surfaceReflectivityColor);
-#endif
-#ifdef MICROSURFACEMAP
-microSurface*=microSurfaceTexel.r;
-#endif
-#define CUSTOM_FRAGMENT_UPDATE_MICROSURFACE
-#endif
-#endif
-#endif
-
-microSurface=saturate(microSurface);
-
-float roughness=1.-microSurface;
-outParams.microSurface=microSurface;
-outParams.roughness=roughness;
-outParams.surfaceReflectivityColor=surfaceReflectivityColor;
-}
-`;ze.a.IncludesShadersStore.pbrBlockReflectivity=jp;var Hp=`struct ambientOcclusionOutParams
-{
-vec3 ambientOcclusionColor;
-#if DEBUGMODE>0
-vec3 ambientOcclusionColorMap;
-#endif
-};
-#define pbr_inline
-void ambientOcclusionBlock(
-#ifdef AMBIENT
-const in vec3 ambientOcclusionColorMap_,
-const in vec4 vAmbientInfos,
-#endif
-out ambientOcclusionOutParams outParams
-)
-{
-vec3 ambientOcclusionColor=vec3(1.,1.,1.);
-#ifdef AMBIENT
-vec3 ambientOcclusionColorMap=ambientOcclusionColorMap_*vAmbientInfos.y;
-#ifdef AMBIENTINGRAYSCALE
-ambientOcclusionColorMap=vec3(ambientOcclusionColorMap.r,ambientOcclusionColorMap.r,ambientOcclusionColorMap.r);
-#endif
-ambientOcclusionColor=mix(ambientOcclusionColor,ambientOcclusionColorMap,vAmbientInfos.z);
-#if DEBUGMODE>0
-outParams.ambientOcclusionColorMap=ambientOcclusionColorMap;
-#endif
-#endif
-outParams.ambientOcclusionColor=ambientOcclusionColor;
-}
-`;ze.a.IncludesShadersStore.pbrBlockAmbientOcclusion=Hp;var Wp=`#ifdef ALPHAFRESNEL
-#if defined(ALPHATEST) || defined(ALPHABLEND)
-struct alphaFresnelOutParams
-{
-float alpha;
-};
-#define pbr_inline
-void alphaFresnelBlock(
-const in vec3 normalW,
-const in vec3 viewDirectionW,
-const in float alpha,
-const in float microSurface,
-out alphaFresnelOutParams outParams
-)
-{
-
-
-
-float opacityPerceptual=alpha;
-#ifdef LINEARALPHAFRESNEL
-float opacity0=opacityPerceptual;
-#else
-float opacity0=opacityPerceptual*opacityPerceptual;
-#endif
-float opacity90=fresnelGrazingReflectance(opacity0);
-vec3 normalForward=faceforward(normalW,-viewDirectionW,normalW);
-
-outParams.alpha=getReflectanceFromAnalyticalBRDFLookup_Jones(saturate(dot(viewDirectionW,normalForward)),vec3(opacity0),vec3(opacity90),sqrt(microSurface)).x;
-#ifdef ALPHATEST
-if (outParams.alpha<ALPHATESTVALUE)
-discard;
-#ifndef ALPHABLEND
-
-outParams.alpha=1.0;
-#endif
-#endif
-}
-#endif
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockAlphaFresnel=Wp;var Xp=`#ifdef ANISOTROPIC
-struct anisotropicOutParams
-{
-float anisotropy;
-vec3 anisotropicTangent;
-vec3 anisotropicBitangent;
-vec3 anisotropicNormal;
-#if DEBUGMODE>0
-vec3 anisotropyMapData;
-#endif
-};
-#define pbr_inline
-void anisotropicBlock(
-const in vec3 vAnisotropy,
-#ifdef ANISOTROPIC_TEXTURE
-const in vec3 anisotropyMapData,
-#endif
-const in mat3 TBN,
-const in vec3 normalW,
-const in vec3 viewDirectionW,
-out anisotropicOutParams outParams
-)
-{
-float anisotropy=vAnisotropy.b;
-vec3 anisotropyDirection=vec3(vAnisotropy.xy,0.);
-#ifdef ANISOTROPIC_TEXTURE
-anisotropy*=anisotropyMapData.b;
-anisotropyDirection.rg*=anisotropyMapData.rg*2.0-1.0;
-#if DEBUGMODE>0
-outParams.anisotropyMapData=anisotropyMapData;
-#endif
-#endif
-mat3 anisoTBN=mat3(normalize(TBN[0]),normalize(TBN[1]),normalize(TBN[2]));
-vec3 anisotropicTangent=normalize(anisoTBN*anisotropyDirection);
-vec3 anisotropicBitangent=normalize(cross(anisoTBN[2],anisotropicTangent));
-outParams.anisotropy=anisotropy;
-outParams.anisotropicTangent=anisotropicTangent;
-outParams.anisotropicBitangent=anisotropicBitangent;
-outParams.anisotropicNormal=getAnisotropicBentNormals(anisotropicTangent,anisotropicBitangent,normalW,viewDirectionW,anisotropy);
-}
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockAnisotropic=Xp;var Yp=`#ifdef REFLECTION
-struct reflectionOutParams
-{
-vec4 environmentRadiance;
-vec3 environmentIrradiance;
-#ifdef REFLECTIONMAP_3D
-vec3 reflectionCoords;
-#else
-vec2 reflectionCoords;
-#endif
-#ifdef SS_TRANSLUCENCY
-#ifdef USESPHERICALFROMREFLECTIONMAP
-#if !defined(NORMAL) || !defined(USESPHERICALINVERTEX)
-vec3 irradianceVector;
-#endif
-#endif
-#endif
-};
-#define pbr_inline
-void createReflectionCoords(
-const in vec3 vPositionW,
-const in vec3 normalW,
-#ifdef ANISOTROPIC
-const in anisotropicOutParams anisotropicOut,
-#endif
-#ifdef REFLECTIONMAP_3D
-out vec3 reflectionCoords
-#else
-out vec2 reflectionCoords
-#endif
-)
-{
-#ifdef ANISOTROPIC
-vec3 reflectionVector=computeReflectionCoords(vec4(vPositionW,1.0),anisotropicOut.anisotropicNormal);
-#else
-vec3 reflectionVector=computeReflectionCoords(vec4(vPositionW,1.0),normalW);
-#endif
-#ifdef REFLECTIONMAP_OPPOSITEZ
-reflectionVector.z*=-1.0;
-#endif
-
-#ifdef REFLECTIONMAP_3D
-reflectionCoords=reflectionVector;
-#else
-reflectionCoords=reflectionVector.xy;
-#ifdef REFLECTIONMAP_PROJECTION
-reflectionCoords/=reflectionVector.z;
-#endif
-reflectionCoords.y=1.0-reflectionCoords.y;
-#endif
-}
-#define pbr_inline
-#define inline
-void sampleReflectionTexture(
-const in float alphaG,
-const in vec3 vReflectionMicrosurfaceInfos,
-const in vec2 vReflectionInfos,
-const in vec3 vReflectionColor,
-#if defined(LODINREFLECTIONALPHA) && !defined(REFLECTIONMAP_SKYBOX)
-const in float NdotVUnclamped,
-#endif
-#ifdef LINEARSPECULARREFLECTION
-const in float roughness,
-#endif
-#ifdef REFLECTIONMAP_3D
-const in samplerCube reflectionSampler,
-const vec3 reflectionCoords,
-#else
-const in sampler2D reflectionSampler,
-const vec2 reflectionCoords,
-#endif
-#ifndef LODBASEDMICROSFURACE
-#ifdef REFLECTIONMAP_3D
-const in samplerCube reflectionSamplerLow,
-const in samplerCube reflectionSamplerHigh,
-#else
-const in sampler2D reflectionSamplerLow,
-const in sampler2D reflectionSamplerHigh,
-#endif
-#endif
-#ifdef REALTIME_FILTERING
-const in vec2 vReflectionFilteringInfo,
-#endif
-out vec4 environmentRadiance
-)
-{
-
-#if defined(LODINREFLECTIONALPHA) && !defined(REFLECTIONMAP_SKYBOX)
-float reflectionLOD=getLodFromAlphaG(vReflectionMicrosurfaceInfos.x,alphaG,NdotVUnclamped);
-#elif defined(LINEARSPECULARREFLECTION)
-float reflectionLOD=getLinearLodFromRoughness(vReflectionMicrosurfaceInfos.x,roughness);
-#else
-float reflectionLOD=getLodFromAlphaG(vReflectionMicrosurfaceInfos.x,alphaG);
-#endif
-#ifdef LODBASEDMICROSFURACE
-
-reflectionLOD=reflectionLOD*vReflectionMicrosurfaceInfos.y+vReflectionMicrosurfaceInfos.z;
-#ifdef LODINREFLECTIONALPHA
-
-
-
-
-
-
-
-
-
-float automaticReflectionLOD=UNPACK_LOD(sampleReflection(reflectionSampler,reflectionCoords).a);
-float requestedReflectionLOD=max(automaticReflectionLOD,reflectionLOD);
-#else
-float requestedReflectionLOD=reflectionLOD;
-#endif
-#ifdef REALTIME_FILTERING
-environmentRadiance=vec4(radiance(alphaG,reflectionSampler,reflectionCoords,vReflectionFilteringInfo),1.0);
-#else
-environmentRadiance=sampleReflectionLod(reflectionSampler,reflectionCoords,reflectionLOD);
-#endif
-#else
-float lodReflectionNormalized=saturate(reflectionLOD/log2(vReflectionMicrosurfaceInfos.x));
-float lodReflectionNormalizedDoubled=lodReflectionNormalized*2.0;
-vec4 environmentMid=sampleReflection(reflectionSampler,reflectionCoords);
-if (lodReflectionNormalizedDoubled<1.0){
-environmentRadiance=mix(
-sampleReflection(reflectionSamplerHigh,reflectionCoords),
-environmentMid,
-lodReflectionNormalizedDoubled
-);
-} else {
-environmentRadiance=mix(
-environmentMid,
-sampleReflection(reflectionSamplerLow,reflectionCoords),
-lodReflectionNormalizedDoubled-1.0
-);
-}
-#endif
-#ifdef RGBDREFLECTION
-environmentRadiance.rgb=fromRGBD(environmentRadiance);
-#endif
-#ifdef GAMMAREFLECTION
-environmentRadiance.rgb=toLinearSpace(environmentRadiance.rgb);
-#endif
-
-environmentRadiance.rgb*=vReflectionInfos.x;
-environmentRadiance.rgb*=vReflectionColor.rgb;
-}
-#define pbr_inline
-#define inline
-void reflectionBlock(
-const in vec3 vPositionW,
-const in vec3 normalW,
-const in float alphaG,
-const in vec3 vReflectionMicrosurfaceInfos,
-const in vec2 vReflectionInfos,
-const in vec3 vReflectionColor,
-#ifdef ANISOTROPIC
-const in anisotropicOutParams anisotropicOut,
-#endif
-#if defined(LODINREFLECTIONALPHA) && !defined(REFLECTIONMAP_SKYBOX)
-const in float NdotVUnclamped,
-#endif
-#ifdef LINEARSPECULARREFLECTION
-const in float roughness,
-#endif
-#ifdef REFLECTIONMAP_3D
-const in samplerCube reflectionSampler,
-#else
-const in sampler2D reflectionSampler,
-#endif
-#if defined(NORMAL) && defined(USESPHERICALINVERTEX)
-const in vec3 vEnvironmentIrradiance,
-#endif
-#ifdef USESPHERICALFROMREFLECTIONMAP
-#if !defined(NORMAL) || !defined(USESPHERICALINVERTEX)
-const in mat4 reflectionMatrix,
-#endif
-#endif
-#ifdef USEIRRADIANCEMAP
-#ifdef REFLECTIONMAP_3D
-const in samplerCube irradianceSampler,
-#else
-const in sampler2D irradianceSampler,
-#endif
-#endif
-#ifndef LODBASEDMICROSFURACE
-#ifdef REFLECTIONMAP_3D
-const in samplerCube reflectionSamplerLow,
-const in samplerCube reflectionSamplerHigh,
-#else
-const in sampler2D reflectionSamplerLow,
-const in sampler2D reflectionSamplerHigh,
-#endif
-#endif
-#ifdef REALTIME_FILTERING
-const in vec2 vReflectionFilteringInfo,
-#endif
-out reflectionOutParams outParams
-)
-{
-
-vec4 environmentRadiance=vec4(0.,0.,0.,0.);
-#ifdef REFLECTIONMAP_3D
-vec3 reflectionCoords=vec3(0.);
-#else
-vec2 reflectionCoords=vec2(0.);
-#endif
-createReflectionCoords(
-vPositionW,
-normalW,
-#ifdef ANISOTROPIC
-anisotropicOut,
-#endif
-reflectionCoords
-);
-sampleReflectionTexture(
-alphaG,
-vReflectionMicrosurfaceInfos,
-vReflectionInfos,
-vReflectionColor,
-#if defined(LODINREFLECTIONALPHA) && !defined(REFLECTIONMAP_SKYBOX)
-NdotVUnclamped,
-#endif
-#ifdef LINEARSPECULARREFLECTION
-roughness,
-#endif
-#ifdef REFLECTIONMAP_3D
-reflectionSampler,
-reflectionCoords,
-#else
-reflectionSampler,
-reflectionCoords,
-#endif
-#ifndef LODBASEDMICROSFURACE
-reflectionSamplerLow,
-reflectionSamplerHigh,
-#endif
-#ifdef REALTIME_FILTERING
-vReflectionFilteringInfo,
-#endif
-environmentRadiance
-);
-
-vec3 environmentIrradiance=vec3(0.,0.,0.);
-#ifdef USESPHERICALFROMREFLECTIONMAP
-#if defined(NORMAL) && defined(USESPHERICALINVERTEX)
-environmentIrradiance=vEnvironmentIrradiance;
-#else
-#ifdef ANISOTROPIC
-vec3 irradianceVector=vec3(reflectionMatrix*vec4(anisotropicOut.anisotropicNormal,0)).xyz;
-#else
-vec3 irradianceVector=vec3(reflectionMatrix*vec4(normalW,0)).xyz;
-#endif
-#ifdef REFLECTIONMAP_OPPOSITEZ
-irradianceVector.z*=-1.0;
-#endif
-#ifdef INVERTCUBICMAP
-irradianceVector.y*=-1.0;
-#endif
-#if defined(REALTIME_FILTERING)
-environmentIrradiance=irradiance(reflectionSampler,irradianceVector,vReflectionFilteringInfo);
-#else
-environmentIrradiance=computeEnvironmentIrradiance(irradianceVector);
-#endif
-#ifdef SS_TRANSLUCENCY
-outParams.irradianceVector=irradianceVector;
-#endif
-#endif
-#elif defined(USEIRRADIANCEMAP)
-vec4 environmentIrradiance4=sampleReflection(irradianceSampler,reflectionCoords);
-environmentIrradiance=environmentIrradiance4.rgb;
-#ifdef RGBDREFLECTION
-environmentIrradiance.rgb=fromRGBD(environmentIrradiance4);
-#endif
-#ifdef GAMMAREFLECTION
-environmentIrradiance.rgb=toLinearSpace(environmentIrradiance.rgb);
-#endif
-#endif
-environmentIrradiance*=vReflectionColor.rgb;
-outParams.environmentRadiance=environmentRadiance;
-outParams.environmentIrradiance=environmentIrradiance;
-outParams.reflectionCoords=reflectionCoords;
-}
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockReflection=Yp;var Kp=`#ifdef SHEEN
-struct sheenOutParams
-{
-float sheenIntensity;
-vec3 sheenColor;
-float sheenRoughness;
-#ifdef SHEEN_LINKWITHALBEDO
-vec3 surfaceAlbedo;
-#endif
-#if defined(ENVIRONMENTBRDF) && defined(SHEEN_ALBEDOSCALING)
-float sheenAlbedoScaling;
-#endif
-#if defined(REFLECTION) && defined(ENVIRONMENTBRDF)
-vec3 finalSheenRadianceScaled;
-#endif
-#if DEBUGMODE>0
-vec4 sheenMapData;
-vec3 sheenEnvironmentReflectance;
-#endif
-};
-#define pbr_inline
-#define inline
-void sheenBlock(
-const in vec4 vSheenColor,
-#ifdef SHEEN_ROUGHNESS
-const in float vSheenRoughness,
-#if defined(SHEEN_TEXTURE_ROUGHNESS) && !defined(SHEEN_TEXTURE_ROUGHNESS_IDENTICAL) && !defined(SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE)
-const in vec4 sheenMapRoughnessData,
-#endif
-#endif
-const in float roughness,
-#ifdef SHEEN_TEXTURE
-const in vec4 sheenMapData,
-#endif
-const in float reflectance,
-#ifdef SHEEN_LINKWITHALBEDO
-const in vec3 baseColor,
-const in vec3 surfaceAlbedo,
-#endif
-#ifdef ENVIRONMENTBRDF
-const in float NdotV,
-const in vec3 environmentBrdf,
-#endif
-#if defined(REFLECTION) && defined(ENVIRONMENTBRDF)
-const in vec2 AARoughnessFactors,
-const in vec3 vReflectionMicrosurfaceInfos,
-const in vec2 vReflectionInfos,
-const in vec3 vReflectionColor,
-const in vec4 vLightingIntensity,
-#ifdef REFLECTIONMAP_3D
-const in samplerCube reflectionSampler,
-const in vec3 reflectionCoords,
-#else
-const in sampler2D reflectionSampler,
-const in vec2 reflectionCoords,
-#endif
-const in float NdotVUnclamped,
-#ifndef LODBASEDMICROSFURACE
-#ifdef REFLECTIONMAP_3D
-const in samplerCube reflectionSamplerLow,
-const in samplerCube reflectionSamplerHigh,
-#else
-const in sampler2D reflectionSamplerLow,
-const in sampler2D reflectionSamplerHigh,
-#endif
-#endif
-#ifdef REALTIME_FILTERING
-const in vec2 vReflectionFilteringInfo,
-#endif
-#if !defined(REFLECTIONMAP_SKYBOX) && defined(RADIANCEOCCLUSION)
-const in float seo,
-#endif
-#if !defined(REFLECTIONMAP_SKYBOX) && defined(HORIZONOCCLUSION) && defined(BUMP) && defined(REFLECTIONMAP_3D)
-const in float eho,
-#endif
-#endif
-out sheenOutParams outParams
-)
-{
-float sheenIntensity=vSheenColor.a;
-#ifdef SHEEN_TEXTURE
-#if DEBUGMODE>0
-outParams.sheenMapData=sheenMapData;
-#endif
-#endif
-#ifdef SHEEN_LINKWITHALBEDO
-float sheenFactor=pow5(1.0-sheenIntensity);
-vec3 sheenColor=baseColor.rgb*(1.0-sheenFactor);
-float sheenRoughness=sheenIntensity;
-outParams.surfaceAlbedo=surfaceAlbedo*sheenFactor;
-#ifdef SHEEN_TEXTURE
-sheenIntensity*=sheenMapData.a;
-#endif
-#else
-vec3 sheenColor=vSheenColor.rgb;
-#ifdef SHEEN_TEXTURE
-sheenColor.rgb*=sheenMapData.rgb;
-#endif
-#ifdef SHEEN_ROUGHNESS
-float sheenRoughness=vSheenRoughness;
-#ifdef SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE
-#if defined(SHEEN_TEXTURE)
-sheenRoughness*=sheenMapData.a;
-#endif
-#elif defined(SHEEN_TEXTURE_ROUGHNESS)
-#ifdef SHEEN_TEXTURE_ROUGHNESS_IDENTICAL
-sheenRoughness*=sheenMapData.a;
-#else
-sheenRoughness*=sheenMapRoughnessData.a;
-#endif
-#endif
-#else
-float sheenRoughness=roughness;
-#ifdef SHEEN_TEXTURE
-sheenIntensity*=sheenMapData.a;
-#endif
-#endif
-
-#if !defined(SHEEN_ALBEDOSCALING)
-sheenIntensity*=(1.-reflectance);
-#endif
-
-sheenColor*=sheenIntensity;
-#endif
-
-#ifdef ENVIRONMENTBRDF
-
-#ifdef SHEEN_ROUGHNESS
-vec3 environmentSheenBrdf=getBRDFLookup(NdotV,sheenRoughness);
-#else
-vec3 environmentSheenBrdf=environmentBrdf;
-#endif
-
-#endif
-#if defined(REFLECTION) && defined(ENVIRONMENTBRDF)
-float sheenAlphaG=convertRoughnessToAverageSlope(sheenRoughness);
-#ifdef SPECULARAA
-
-sheenAlphaG+=AARoughnessFactors.y;
-#endif
-vec4 environmentSheenRadiance=vec4(0.,0.,0.,0.);
-sampleReflectionTexture(
-sheenAlphaG,
-vReflectionMicrosurfaceInfos,
-vReflectionInfos,
-vReflectionColor,
-#if defined(LODINREFLECTIONALPHA) && !defined(REFLECTIONMAP_SKYBOX)
-NdotVUnclamped,
-#endif
-#ifdef LINEARSPECULARREFLECTION
-sheenRoughness,
-#endif
-reflectionSampler,
-reflectionCoords,
-#ifndef LODBASEDMICROSFURACE
-reflectionSamplerLow,
-reflectionSamplerHigh,
-#endif
-#ifdef REALTIME_FILTERING
-vReflectionFilteringInfo,
-#endif
-environmentSheenRadiance
-);
-vec3 sheenEnvironmentReflectance=getSheenReflectanceFromBRDFLookup(sheenColor,environmentSheenBrdf);
-#if !defined(REFLECTIONMAP_SKYBOX) && defined(RADIANCEOCCLUSION)
-sheenEnvironmentReflectance*=seo;
-#endif
-#if !defined(REFLECTIONMAP_SKYBOX) && defined(HORIZONOCCLUSION) && defined(BUMP) && defined(REFLECTIONMAP_3D)
-sheenEnvironmentReflectance*=eho;
-#endif
-#if DEBUGMODE>0
-outParams.sheenEnvironmentReflectance=sheenEnvironmentReflectance;
-#endif
-outParams.finalSheenRadianceScaled=
-environmentSheenRadiance.rgb *
-sheenEnvironmentReflectance *
-vLightingIntensity.z;
-
-
-
-
-
-#endif
-#if defined(ENVIRONMENTBRDF) && defined(SHEEN_ALBEDOSCALING)
-
-
-
-outParams.sheenAlbedoScaling=1.0-sheenIntensity*max(max(sheenColor.r,sheenColor.g),sheenColor.b)*environmentSheenBrdf.b;
-#endif
-
-outParams.sheenIntensity=sheenIntensity;
-outParams.sheenColor=sheenColor;
-outParams.sheenRoughness=sheenRoughness;
-}
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockSheen=Kp;var Qp=`struct clearcoatOutParams
-{
-vec3 specularEnvironmentR0;
-float conservationFactor;
-vec3 clearCoatNormalW;
-vec2 clearCoatAARoughnessFactors;
-float clearCoatIntensity;
-float clearCoatRoughness;
-#ifdef REFLECTION
-vec3 finalClearCoatRadianceScaled;
-#endif
-#ifdef CLEARCOAT_TINT
-vec3 absorption;
-float clearCoatNdotVRefract;
-vec3 clearCoatColor;
-float clearCoatThickness;
-#endif
-#if defined(ENVIRONMENTBRDF) && defined(MS_BRDF_ENERGY_CONSERVATION)
-vec3 energyConservationFactorClearCoat;
-#endif
-#if DEBUGMODE>0
-mat3 TBNClearCoat;
-vec2 clearCoatMapData;
-vec4 clearCoatTintMapData;
-vec4 environmentClearCoatRadiance;
-float clearCoatNdotV;
-vec3 clearCoatEnvironmentReflectance;
-#endif
-};
-#ifdef CLEARCOAT
-#define pbr_inline
-#define inline
-void clearcoatBlock(
-const in vec3 vPositionW,
-const in vec3 geometricNormalW,
-const in vec3 viewDirectionW,
-const in vec2 vClearCoatParams,
-#if defined(CLEARCOAT_TEXTURE_ROUGHNESS) && !defined(CLEARCOAT_TEXTURE_ROUGHNESS_IDENTICAL) && !defined(CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE)
-const in vec4 clearCoatMapRoughnessData,
-#endif
-const in vec3 specularEnvironmentR0,
-#ifdef CLEARCOAT_TEXTURE
-const in vec2 clearCoatMapData,
-#endif
-#ifdef CLEARCOAT_TINT
-const in vec4 vClearCoatTintParams,
-const in float clearCoatColorAtDistance,
-const in vec4 vClearCoatRefractionParams,
-#ifdef CLEARCOAT_TINT_TEXTURE
-const in vec4 clearCoatTintMapData,
-#endif
-#endif
-#ifdef CLEARCOAT_BUMP
-const in vec2 vClearCoatBumpInfos,
-const in vec4 clearCoatBumpMapData,
-const in vec2 vClearCoatBumpUV,
-#if defined(TANGENT) && defined(NORMAL)
-const in mat3 vTBN,
-#else
-const in vec2 vClearCoatTangentSpaceParams,
-#endif
-#ifdef OBJECTSPACE_NORMALMAP
-const in mat4 normalMatrix,
-#endif
-#endif
-#if defined(FORCENORMALFORWARD) && defined(NORMAL)
-const in vec3 faceNormal,
-#endif
-#ifdef REFLECTION
-const in vec3 vReflectionMicrosurfaceInfos,
-const in vec2 vReflectionInfos,
-const in vec3 vReflectionColor,
-const in vec4 vLightingIntensity,
-#ifdef REFLECTIONMAP_3D
-const in samplerCube reflectionSampler,
-#else
-const in sampler2D reflectionSampler,
-#endif
-#ifndef LODBASEDMICROSFURACE
-#ifdef REFLECTIONMAP_3D
-const in samplerCube reflectionSamplerLow,
-const in samplerCube reflectionSamplerHigh,
-#else
-const in sampler2D reflectionSamplerLow,
-const in sampler2D reflectionSamplerHigh,
-#endif
-#endif
-#ifdef REALTIME_FILTERING
-const in vec2 vReflectionFilteringInfo,
-#endif
-#endif
-#if defined(ENVIRONMENTBRDF) && !defined(REFLECTIONMAP_SKYBOX)
-#ifdef RADIANCEOCCLUSION
-const in float ambientMonochrome,
-#endif
-#endif
-out clearcoatOutParams outParams
-)
-{
-
-float clearCoatIntensity=vClearCoatParams.x;
-float clearCoatRoughness=vClearCoatParams.y;
-#ifdef CLEARCOAT_TEXTURE
-clearCoatIntensity*=clearCoatMapData.x;
-#ifdef CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE
-clearCoatRoughness*=clearCoatMapData.y;
-#endif
-#if DEBUGMODE>0
-outParams.clearCoatMapData=clearCoatMapData;
-#endif
-#endif
-#if defined(CLEARCOAT_TEXTURE_ROUGHNESS) && !defined(CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE)
-#ifdef CLEARCOAT_TEXTURE_ROUGHNESS_IDENTICAL
-clearCoatRoughness*=clearCoatMapData.y;
-#else
-clearCoatRoughness*=clearCoatMapRoughnessData.y;
-#endif
-#endif
-outParams.clearCoatIntensity=clearCoatIntensity;
-outParams.clearCoatRoughness=clearCoatRoughness;
-#ifdef CLEARCOAT_TINT
-vec3 clearCoatColor=vClearCoatTintParams.rgb;
-float clearCoatThickness=vClearCoatTintParams.a;
-#ifdef CLEARCOAT_TINT_TEXTURE
-clearCoatColor*=clearCoatTintMapData.rgb;
-clearCoatThickness*=clearCoatTintMapData.a;
-#if DEBUGMODE>0
-outParams.clearCoatTintMapData=clearCoatTintMapData;
-#endif
-#endif
-outParams.clearCoatColor=computeColorAtDistanceInMedia(clearCoatColor,clearCoatColorAtDistance);
-outParams.clearCoatThickness=clearCoatThickness;
-#endif
-
-
-
-
-#ifdef CLEARCOAT_REMAP_F0
-vec3 specularEnvironmentR0Updated=getR0RemappedForClearCoat(specularEnvironmentR0);
-#else
-vec3 specularEnvironmentR0Updated=specularEnvironmentR0;
-#endif
-outParams.specularEnvironmentR0=mix(specularEnvironmentR0,specularEnvironmentR0Updated,clearCoatIntensity);
-
-vec3 clearCoatNormalW=geometricNormalW;
-#ifdef CLEARCOAT_BUMP
-#ifdef NORMALXYSCALE
-float clearCoatNormalScale=1.0;
-#else
-float clearCoatNormalScale=vClearCoatBumpInfos.y;
-#endif
-#if defined(TANGENT) && defined(NORMAL)
-mat3 TBNClearCoat=vTBN;
-#else
-mat3 TBNClearCoat=cotangent_frame(clearCoatNormalW*clearCoatNormalScale,vPositionW,vClearCoatBumpUV,vClearCoatTangentSpaceParams);
-#endif
-#if DEBUGMODE>0
-outParams.TBNClearCoat=TBNClearCoat;
-#endif
-#ifdef OBJECTSPACE_NORMALMAP
-clearCoatNormalW=normalize(clearCoatBumpMapData.xyz*2.0-1.0);
-clearCoatNormalW=normalize(mat3(normalMatrix)*clearCoatNormalW);
-#else
-clearCoatNormalW=perturbNormal(TBNClearCoat,clearCoatBumpMapData.xyz,vClearCoatBumpInfos.y);
-#endif
-#endif
-#if defined(FORCENORMALFORWARD) && defined(NORMAL)
-clearCoatNormalW*=sign(dot(clearCoatNormalW,faceNormal));
-#endif
-#if defined(TWOSIDEDLIGHTING) && defined(NORMAL)
-clearCoatNormalW=gl_FrontFacing ? clearCoatNormalW : -clearCoatNormalW;
-#endif
-outParams.clearCoatNormalW=clearCoatNormalW;
-
-outParams.clearCoatAARoughnessFactors=getAARoughnessFactors(clearCoatNormalW.xyz);
-
-float clearCoatNdotVUnclamped=dot(clearCoatNormalW,viewDirectionW);
-
-float clearCoatNdotV=absEps(clearCoatNdotVUnclamped);
-#if DEBUGMODE>0
-outParams.clearCoatNdotV=clearCoatNdotV;
-#endif
-#ifdef CLEARCOAT_TINT
-
-vec3 clearCoatVRefract=-refract(vPositionW,clearCoatNormalW,vClearCoatRefractionParams.y);
-
-outParams.clearCoatNdotVRefract=absEps(dot(clearCoatNormalW,clearCoatVRefract));
-#endif
-#if defined(ENVIRONMENTBRDF) && !defined(REFLECTIONMAP_SKYBOX)
-
-vec3 environmentClearCoatBrdf=getBRDFLookup(clearCoatNdotV,clearCoatRoughness);
-#endif
-
-#if defined(REFLECTION)
-float clearCoatAlphaG=convertRoughnessToAverageSlope(clearCoatRoughness);
-#ifdef SPECULARAA
-
-clearCoatAlphaG+=outParams.clearCoatAARoughnessFactors.y;
-#endif
-vec4 environmentClearCoatRadiance=vec4(0.,0.,0.,0.);
-vec3 clearCoatReflectionVector=computeReflectionCoords(vec4(vPositionW,1.0),clearCoatNormalW);
-#ifdef REFLECTIONMAP_OPPOSITEZ
-clearCoatReflectionVector.z*=-1.0;
-#endif
-
-#ifdef REFLECTIONMAP_3D
-vec3 clearCoatReflectionCoords=clearCoatReflectionVector;
-#else
-vec2 clearCoatReflectionCoords=clearCoatReflectionVector.xy;
-#ifdef REFLECTIONMAP_PROJECTION
-clearCoatReflectionCoords/=clearCoatReflectionVector.z;
-#endif
-clearCoatReflectionCoords.y=1.0-clearCoatReflectionCoords.y;
-#endif
-sampleReflectionTexture(
-clearCoatAlphaG,
-vReflectionMicrosurfaceInfos,
-vReflectionInfos,
-vReflectionColor,
-#if defined(LODINREFLECTIONALPHA) && !defined(REFLECTIONMAP_SKYBOX)
-clearCoatNdotVUnclamped,
-#endif
-#ifdef LINEARSPECULARREFLECTION
-clearCoatRoughness,
-#endif
-reflectionSampler,
-clearCoatReflectionCoords,
-#ifndef LODBASEDMICROSFURACE
-reflectionSamplerLow,
-reflectionSamplerHigh,
-#endif
-#ifdef REALTIME_FILTERING
-vReflectionFilteringInfo,
-#endif
-environmentClearCoatRadiance
-);
-#if DEBUGMODE>0
-outParams.environmentClearCoatRadiance=environmentClearCoatRadiance;
-#endif
-
-#if defined(ENVIRONMENTBRDF) && !defined(REFLECTIONMAP_SKYBOX)
-vec3 clearCoatEnvironmentReflectance=getReflectanceFromBRDFLookup(vec3(vClearCoatRefractionParams.x),environmentClearCoatBrdf);
-#ifdef RADIANCEOCCLUSION
-float clearCoatSeo=environmentRadianceOcclusion(ambientMonochrome,clearCoatNdotVUnclamped);
-clearCoatEnvironmentReflectance*=clearCoatSeo;
-#endif
-#ifdef HORIZONOCCLUSION
-#ifdef BUMP
-#ifdef REFLECTIONMAP_3D
-float clearCoatEho=environmentHorizonOcclusion(-viewDirectionW,clearCoatNormalW,geometricNormalW);
-clearCoatEnvironmentReflectance*=clearCoatEho;
-#endif
-#endif
-#endif
-#else
-
-vec3 clearCoatEnvironmentReflectance=getReflectanceFromAnalyticalBRDFLookup_Jones(clearCoatNdotV,vec3(1.),vec3(1.),sqrt(1.-clearCoatRoughness));
-#endif
-clearCoatEnvironmentReflectance*=clearCoatIntensity;
-#if DEBUGMODE>0
-outParams.clearCoatEnvironmentReflectance=clearCoatEnvironmentReflectance;
-#endif
-outParams.finalClearCoatRadianceScaled=
-environmentClearCoatRadiance.rgb *
-clearCoatEnvironmentReflectance *
-vLightingIntensity.z;
-#endif
-#if defined(CLEARCOAT_TINT)
-
-outParams.absorption=computeClearCoatAbsorption(outParams.clearCoatNdotVRefract,outParams.clearCoatNdotVRefract,outParams.clearCoatColor,clearCoatThickness,clearCoatIntensity);
-#endif
-
-float fresnelIBLClearCoat=fresnelSchlickGGX(clearCoatNdotV,vClearCoatRefractionParams.x,CLEARCOATREFLECTANCE90);
-fresnelIBLClearCoat*=clearCoatIntensity;
-outParams.conservationFactor=(1.-fresnelIBLClearCoat);
-#if defined(ENVIRONMENTBRDF) && defined(MS_BRDF_ENERGY_CONSERVATION)
-outParams.energyConservationFactorClearCoat=getEnergyConservationFactor(outParams.specularEnvironmentR0,environmentClearCoatBrdf);
-#endif
-}
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockClearcoat=Qp;var qp=`struct subSurfaceOutParams
-{
-vec3 specularEnvironmentReflectance;
-#ifdef SS_REFRACTION
-vec3 finalRefraction;
-vec3 surfaceAlbedo;
-#ifdef SS_LINKREFRACTIONTOTRANSPARENCY
-float alpha;
-#endif
-#ifdef REFLECTION
-float refractionFactorForIrradiance;
-#endif
-#endif
-#ifdef SS_TRANSLUCENCY
-vec3 transmittance;
-float translucencyIntensity;
-#ifdef REFLECTION
-vec3 refractionIrradiance;
-#endif
-#endif
-#if DEBUGMODE>0
-vec4 thicknessMap;
-vec4 environmentRefraction;
-vec3 refractionTransmittance;
-#endif
-};
-#ifdef SUBSURFACE
-#define pbr_inline
-#define inline
-void subSurfaceBlock(
-const in vec3 vSubSurfaceIntensity,
-const in vec2 vThicknessParam,
-const in vec4 vTintColor,
-const in vec3 normalW,
-const in vec3 specularEnvironmentReflectance,
-#ifdef SS_THICKNESSANDMASK_TEXTURE
-const in vec4 thicknessMap,
-#endif
-#ifdef REFLECTION
-#ifdef SS_TRANSLUCENCY
-const in mat4 reflectionMatrix,
-#ifdef USESPHERICALFROMREFLECTIONMAP
-#if !defined(NORMAL) || !defined(USESPHERICALINVERTEX)
-const in vec3 irradianceVector_,
-#endif
-#if defined(REALTIME_FILTERING)
-const in samplerCube reflectionSampler,
-const in vec2 vReflectionFilteringInfo,
-#endif
-#endif
-#ifdef USEIRRADIANCEMAP
-#ifdef REFLECTIONMAP_3D
-const in samplerCube irradianceSampler,
-#else
-const in sampler2D irradianceSampler,
-#endif
-#endif
-#endif
-#endif
-#ifdef SS_REFRACTION
-const in vec3 vPositionW,
-const in vec3 viewDirectionW,
-const in mat4 view,
-const in vec3 surfaceAlbedo,
-const in vec4 vRefractionInfos,
-const in mat4 refractionMatrix,
-const in vec3 vRefractionMicrosurfaceInfos,
-const in vec4 vLightingIntensity,
-#ifdef SS_LINKREFRACTIONTOTRANSPARENCY
-const in float alpha,
-#endif
-#ifdef SS_LODINREFRACTIONALPHA
-const in float NdotVUnclamped,
-#endif
-#ifdef SS_LINEARSPECULARREFRACTION
-const in float roughness,
-#else
-const in float alphaG,
-#endif
-#ifdef SS_REFRACTIONMAP_3D
-const in samplerCube refractionSampler,
-#ifndef LODBASEDMICROSFURACE
-const in samplerCube refractionSamplerLow,
-const in samplerCube refractionSamplerHigh,
-#endif
-#else
-const in sampler2D refractionSampler,
-#ifndef LODBASEDMICROSFURACE
-const in sampler2D refractionSamplerLow,
-const in sampler2D refractionSamplerHigh,
-#endif
-#endif
-#ifdef ANISOTROPIC
-const in anisotropicOutParams anisotropicOut,
-#endif
-#ifdef REALTIME_FILTERING
-const in vec2 vRefractionFilteringInfo,
-#endif
-#endif
-#ifdef SS_TRANSLUCENCY
-const in vec3 vDiffusionDistance,
-#endif
-out subSurfaceOutParams outParams
-)
-{
-outParams.specularEnvironmentReflectance=specularEnvironmentReflectance;
-
-
-
-#ifdef SS_REFRACTION
-float refractionIntensity=vSubSurfaceIntensity.x;
-#ifdef SS_LINKREFRACTIONTOTRANSPARENCY
-refractionIntensity*=(1.0-alpha);
-
-outParams.alpha=1.0;
-#endif
-#endif
-#ifdef SS_TRANSLUCENCY
-float translucencyIntensity=vSubSurfaceIntensity.y;
-#endif
-#ifdef SS_THICKNESSANDMASK_TEXTURE
-float thickness=thicknessMap.r*vThicknessParam.y+vThicknessParam.x;
-#if DEBUGMODE>0
-outParams.thicknessMap=thicknessMap;
-#endif
-#ifdef SS_MASK_FROM_THICKNESS_TEXTURE
-#ifdef SS_REFRACTION
-refractionIntensity*=thicknessMap.g;
-#endif
-#ifdef SS_TRANSLUCENCY
-translucencyIntensity*=thicknessMap.b;
-#endif
-#elif defined(SS_MASK_FROM_THICKNESS_TEXTURE_GLTF)
-#ifdef SS_REFRACTION
-refractionIntensity*=thicknessMap.r;
-#elif defined(SS_TRANSLUCENCY)
-translucencyIntensity*=thicknessMap.r;
-#endif
-thickness=thicknessMap.g*vThicknessParam.y+vThicknessParam.x;
-#endif
-#else
-float thickness=vThicknessParam.y;
-#endif
-
-
-
-#ifdef SS_TRANSLUCENCY
-thickness=maxEps(thickness);
-vec3 transmittance=transmittanceBRDF_Burley(vTintColor.rgb,vDiffusionDistance,thickness);
-transmittance*=translucencyIntensity;
-outParams.transmittance=transmittance;
-outParams.translucencyIntensity=translucencyIntensity;
-#endif
-
-
-
-#ifdef SS_REFRACTION
-vec4 environmentRefraction=vec4(0.,0.,0.,0.);
-#ifdef ANISOTROPIC
-vec3 refractionVector=refract(-viewDirectionW,anisotropicOut.anisotropicNormal,vRefractionInfos.y);
-#else
-vec3 refractionVector=refract(-viewDirectionW,normalW,vRefractionInfos.y);
-#endif
-#ifdef SS_REFRACTIONMAP_OPPOSITEZ
-refractionVector.z*=-1.0;
-#endif
-
-#ifdef SS_REFRACTIONMAP_3D
-refractionVector.y=refractionVector.y*vRefractionInfos.w;
-vec3 refractionCoords=refractionVector;
-refractionCoords=vec3(refractionMatrix*vec4(refractionCoords,0));
-#else
-vec3 vRefractionUVW=vec3(refractionMatrix*(view*vec4(vPositionW+refractionVector*vRefractionInfos.z,1.0)));
-vec2 refractionCoords=vRefractionUVW.xy/vRefractionUVW.z;
-refractionCoords.y=1.0-refractionCoords.y;
-#endif
-#ifdef SS_LODINREFRACTIONALPHA
-float refractionLOD=getLodFromAlphaG(vRefractionMicrosurfaceInfos.x,alphaG,NdotVUnclamped);
-#elif defined(SS_LINEARSPECULARREFRACTION)
-float refractionLOD=getLinearLodFromRoughness(vRefractionMicrosurfaceInfos.x,roughness);
-#else
-float refractionLOD=getLodFromAlphaG(vRefractionMicrosurfaceInfos.x,alphaG);
-#endif
-#ifdef LODBASEDMICROSFURACE
-
-refractionLOD=refractionLOD*vRefractionMicrosurfaceInfos.y+vRefractionMicrosurfaceInfos.z;
-#ifdef SS_LODINREFRACTIONALPHA
-
-
-
-
-
-
-
-
-
-float automaticRefractionLOD=UNPACK_LOD(sampleRefraction(refractionSampler,refractionCoords).a);
-float requestedRefractionLOD=max(automaticRefractionLOD,refractionLOD);
-#else
-float requestedRefractionLOD=refractionLOD;
-#endif
-#ifdef REALTIME_FILTERING
-environmentRefraction=vec4(radiance(alphaG,refractionSampler,refractionCoords,vRefractionFilteringInfo),1.0);
-#else
-environmentRefraction=sampleRefractionLod(refractionSampler,refractionCoords,requestedRefractionLOD);
-#endif
-#else
-float lodRefractionNormalized=saturate(refractionLOD/log2(vRefractionMicrosurfaceInfos.x));
-float lodRefractionNormalizedDoubled=lodRefractionNormalized*2.0;
-vec4 environmentRefractionMid=sampleRefraction(refractionSampler,refractionCoords);
-if (lodRefractionNormalizedDoubled<1.0){
-environmentRefraction=mix(
-sampleRefraction(refractionSamplerHigh,refractionCoords),
-environmentRefractionMid,
-lodRefractionNormalizedDoubled
-);
-} else {
-environmentRefraction=mix(
-environmentRefractionMid,
-sampleRefraction(refractionSamplerLow,refractionCoords),
-lodRefractionNormalizedDoubled-1.0
-);
-}
-#endif
-#ifdef SS_RGBDREFRACTION
-environmentRefraction.rgb=fromRGBD(environmentRefraction);
-#endif
-#ifdef SS_GAMMAREFRACTION
-environmentRefraction.rgb=toLinearSpace(environmentRefraction.rgb);
-#endif
-
-environmentRefraction.rgb*=vRefractionInfos.x;
-#endif
-
-
-
-#ifdef SS_REFRACTION
-vec3 refractionTransmittance=vec3(refractionIntensity);
-#ifdef SS_THICKNESSANDMASK_TEXTURE
-vec3 volumeAlbedo=computeColorAtDistanceInMedia(vTintColor.rgb,vTintColor.w);
-
-
-
-
-
-refractionTransmittance*=cocaLambert(volumeAlbedo,thickness);
-#elif defined(SS_LINKREFRACTIONTOTRANSPARENCY)
-
-float maxChannel=max(max(surfaceAlbedo.r,surfaceAlbedo.g),surfaceAlbedo.b);
-vec3 volumeAlbedo=saturate(maxChannel*surfaceAlbedo);
-
-environmentRefraction.rgb*=volumeAlbedo;
-#else
-
-vec3 volumeAlbedo=computeColorAtDistanceInMedia(vTintColor.rgb,vTintColor.w);
-refractionTransmittance*=cocaLambert(volumeAlbedo,vThicknessParam.y);
-#endif
-#ifdef SS_ALBEDOFORREFRACTIONTINT
-
-environmentRefraction.rgb*=surfaceAlbedo.rgb;
-#endif
-
-outParams.surfaceAlbedo=surfaceAlbedo*(1.-refractionIntensity);
-#ifdef REFLECTION
-
-outParams.refractionFactorForIrradiance=(1.-refractionIntensity);
-
-#endif
-
-vec3 bounceSpecularEnvironmentReflectance=(2.0*specularEnvironmentReflectance)/(1.0+specularEnvironmentReflectance);
-outParams.specularEnvironmentReflectance=mix(bounceSpecularEnvironmentReflectance,specularEnvironmentReflectance,refractionIntensity);
-
-refractionTransmittance*=1.0-outParams.specularEnvironmentReflectance;
-#if DEBUGMODE>0
-outParams.refractionTransmittance=refractionTransmittance;
-#endif
-outParams.finalRefraction=environmentRefraction.rgb*refractionTransmittance*vLightingIntensity.z;
-#if DEBUGMODE>0
-outParams.environmentRefraction=environmentRefraction;
-#endif
-#endif
-
-
-
-#if defined(REFLECTION) && defined(SS_TRANSLUCENCY)
-#if defined(NORMAL) && defined(USESPHERICALINVERTEX) || !defined(USESPHERICALFROMREFLECTIONMAP)
-vec3 irradianceVector=vec3(reflectionMatrix*vec4(normalW,0)).xyz;
-#ifdef REFLECTIONMAP_OPPOSITEZ
-irradianceVector.z*=-1.0;
-#endif
-#ifdef INVERTCUBICMAP
-irradianceVector.y*=-1.0;
-#endif
-#else
-vec3 irradianceVector=irradianceVector_;
-#endif
-#if defined(USESPHERICALFROMREFLECTIONMAP)
-#if defined(REALTIME_FILTERING)
-vec3 refractionIrradiance=irradiance(reflectionSampler,-irradianceVector,vReflectionFilteringInfo);
-#else
-vec3 refractionIrradiance=computeEnvironmentIrradiance(-irradianceVector);
-#endif
-#elif defined(USEIRRADIANCEMAP)
-#ifdef REFLECTIONMAP_3D
-vec3 irradianceCoords=irradianceVector;
-#else
-vec2 irradianceCoords=irradianceVector.xy;
-#ifdef REFLECTIONMAP_PROJECTION
-irradianceCoords/=irradianceVector.z;
-#endif
-irradianceCoords.y=1.0-irradianceCoords.y;
-#endif
-vec4 refractionIrradiance=sampleReflection(irradianceSampler,-irradianceCoords);
-#ifdef RGBDREFLECTION
-refractionIrradiance.rgb=fromRGBD(refractionIrradiance);
-#endif
-#ifdef GAMMAREFLECTION
-refractionIrradiance.rgb=toLinearSpace(refractionIrradiance.rgb);
-#endif
-#else
-vec4 refractionIrradiance=vec4(0.);
-#endif
-refractionIrradiance.rgb*=transmittance;
-outParams.refractionIrradiance=refractionIrradiance.rgb;
-#endif
-}
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockSubSurface=qp;var Zp=`vec3 viewDirectionW=normalize(vEyePosition.xyz-vPositionW);
-#ifdef NORMAL
-vec3 normalW=normalize(vNormalW);
-#else
-vec3 normalW=normalize(cross(dFdx(vPositionW),dFdy(vPositionW)))*vEyePosition.w;
-#endif
-vec3 geometricNormalW=normalW;
-#if defined(TWOSIDEDLIGHTING) && defined(NORMAL)
-geometricNormalW=gl_FrontFacing ? geometricNormalW : -geometricNormalW;
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockNormalGeometric=Zp,f(134);var Jp=`#if defined(FORCENORMALFORWARD) && defined(NORMAL)
-vec3 faceNormal=normalize(cross(dFdx(vPositionW),dFdy(vPositionW)))*vEyePosition.w;
-#if defined(TWOSIDEDLIGHTING)
-faceNormal=gl_FrontFacing ? faceNormal : -faceNormal;
-#endif
-normalW*=sign(dot(normalW,faceNormal));
-#endif
-#if defined(TWOSIDEDLIGHTING) && defined(NORMAL)
-normalW=gl_FrontFacing ? normalW : -normalW;
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockNormalFinal=Jp,f(162);var $p=`#ifdef LIGHTMAP
-vec4 lightmapColor=texture2D(lightmapSampler,vLightmapUV+uvOffset);
-#ifdef RGBDLIGHTMAP
-lightmapColor.rgb=fromRGBD(lightmapColor);
-#endif
-#ifdef GAMMALIGHTMAP
-lightmapColor.rgb=toLinearSpace(lightmapColor.rgb);
-#endif
-lightmapColor.rgb*=vLightmapInfos.y;
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockLightmapInit=$p;var e_=`float NdotVUnclamped=dot(normalW,viewDirectionW);
-
-float NdotV=absEps(NdotVUnclamped);
-float alphaG=convertRoughnessToAverageSlope(roughness);
-vec2 AARoughnessFactors=getAARoughnessFactors(normalW.xyz);
-#ifdef SPECULARAA
-
-alphaG+=AARoughnessFactors.y;
-#endif
-#if defined(ENVIRONMENTBRDF)
-
-vec3 environmentBrdf=getBRDFLookup(NdotV,roughness);
-#endif
-#if defined(ENVIRONMENTBRDF) && !defined(REFLECTIONMAP_SKYBOX)
-#ifdef RADIANCEOCCLUSION
-#ifdef AMBIENTINGRAYSCALE
-float ambientMonochrome=aoOut.ambientOcclusionColor.r;
-#else
-float ambientMonochrome=getLuminance(aoOut.ambientOcclusionColor);
-#endif
-float seo=environmentRadianceOcclusion(ambientMonochrome,NdotVUnclamped);
-#endif
-#ifdef HORIZONOCCLUSION
-#ifdef BUMP
-#ifdef REFLECTIONMAP_3D
-float eho=environmentHorizonOcclusion(-viewDirectionW,normalW,geometricNormalW);
-#endif
-#endif
-#endif
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockGeometryInfo=e_;var t_=`float reflectance=max(max(reflectivityOut.surfaceReflectivityColor.r,reflectivityOut.surfaceReflectivityColor.g),reflectivityOut.surfaceReflectivityColor.b);
-vec3 specularEnvironmentR0=reflectivityOut.surfaceReflectivityColor.rgb;
-#ifdef METALLICWORKFLOW
-vec3 specularEnvironmentR90=vec3(metallicReflectanceFactors.a);
-#else
-vec3 specularEnvironmentR90=vec3(1.0,1.0,1.0);
-#endif
-
-#ifdef ALPHAFRESNEL
-float reflectance90=fresnelGrazingReflectance(reflectance);
-specularEnvironmentR90=specularEnvironmentR90*reflectance90;
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockReflectance0=t_;var n_=`#if defined(ENVIRONMENTBRDF) && !defined(REFLECTIONMAP_SKYBOX)
-vec3 specularEnvironmentReflectance=getReflectanceFromBRDFLookup(clearcoatOut.specularEnvironmentR0,specularEnvironmentR90,environmentBrdf);
-#ifdef RADIANCEOCCLUSION
-specularEnvironmentReflectance*=seo;
-#endif
-#ifdef HORIZONOCCLUSION
-#ifdef BUMP
-#ifdef REFLECTIONMAP_3D
-specularEnvironmentReflectance*=eho;
-#endif
-#endif
-#endif
-#else
-
-vec3 specularEnvironmentReflectance=getReflectanceFromAnalyticalBRDFLookup_Jones(NdotV,clearcoatOut.specularEnvironmentR0,specularEnvironmentR90,sqrt(microSurface));
-#endif
-#ifdef CLEARCOAT
-specularEnvironmentReflectance*=clearcoatOut.conservationFactor;
-#if defined(CLEARCOAT_TINT)
-specularEnvironmentReflectance*=clearcoatOut.absorption;
-#endif
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockReflectance=n_;var i_=`vec3 diffuseBase=vec3(0.,0.,0.);
-#ifdef SPECULARTERM
-vec3 specularBase=vec3(0.,0.,0.);
-#endif
-#ifdef CLEARCOAT
-vec3 clearCoatBase=vec3(0.,0.,0.);
-#endif
-#ifdef SHEEN
-vec3 sheenBase=vec3(0.,0.,0.);
-#endif
-
-preLightingInfo preInfo;
-lightingInfo info;
-float shadow=1.;
-#if defined(CLEARCOAT) && defined(CLEARCOAT_TINT)
-vec3 absorption=vec3(0.);
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockDirectLighting=i_;var r_=`
-
-
-
-#if defined(ENVIRONMENTBRDF)
-#ifdef MS_BRDF_ENERGY_CONSERVATION
-vec3 energyConservationFactor=getEnergyConservationFactor(clearcoatOut.specularEnvironmentR0,environmentBrdf);
-#endif
-#endif
-#ifndef METALLICWORKFLOW
-#ifdef SPECULAR_GLOSSINESS_ENERGY_CONSERVATION
-surfaceAlbedo.rgb=(1.-reflectance)*surfaceAlbedo.rgb;
-#endif
-#endif
-#if defined(SHEEN) && defined(SHEEN_ALBEDOSCALING) && defined(ENVIRONMENTBRDF)
-surfaceAlbedo.rgb=sheenOut.sheenAlbedoScaling*surfaceAlbedo.rgb;
-#endif
-
-#ifdef REFLECTION
-vec3 finalIrradiance=reflectionOut.environmentIrradiance;
-#if defined(CLEARCOAT)
-finalIrradiance*=clearcoatOut.conservationFactor;
-#if defined(CLEARCOAT_TINT)
-finalIrradiance*=clearcoatOut.absorption;
-#endif
-#endif
-#if defined(SS_REFRACTION)
-finalIrradiance*=subSurfaceOut.refractionFactorForIrradiance;
-#endif
-#if defined(SS_TRANSLUCENCY)
-finalIrradiance*=(1.0-subSurfaceOut.translucencyIntensity);
-finalIrradiance+=subSurfaceOut.refractionIrradiance;
-#endif
-finalIrradiance*=surfaceAlbedo.rgb;
-finalIrradiance*=vLightingIntensity.z;
-finalIrradiance*=aoOut.ambientOcclusionColor;
-#endif
-
-#ifdef SPECULARTERM
-vec3 finalSpecular=specularBase;
-finalSpecular=max(finalSpecular,0.0);
-vec3 finalSpecularScaled=finalSpecular*vLightingIntensity.x*vLightingIntensity.w;
-#if defined(ENVIRONMENTBRDF) && defined(MS_BRDF_ENERGY_CONSERVATION)
-finalSpecularScaled*=energyConservationFactor;
-#endif
-#if defined(SHEEN) && defined(ENVIRONMENTBRDF) && defined(SHEEN_ALBEDOSCALING)
-finalSpecularScaled*=sheenOut.sheenAlbedoScaling;
-#endif
-#endif
-
-#ifdef REFLECTION
-vec3 finalRadiance=reflectionOut.environmentRadiance.rgb;
-finalRadiance*=subSurfaceOut.specularEnvironmentReflectance;
-vec3 finalRadianceScaled=finalRadiance*vLightingIntensity.z;
-#if defined(ENVIRONMENTBRDF) && defined(MS_BRDF_ENERGY_CONSERVATION)
-finalRadianceScaled*=energyConservationFactor;
-#endif
-#if defined(SHEEN) && defined(ENVIRONMENTBRDF) && defined(SHEEN_ALBEDOSCALING)
-finalRadianceScaled*=sheenOut.sheenAlbedoScaling;
-#endif
-#endif
-
-#ifdef SHEEN
-vec3 finalSheen=sheenBase*sheenOut.sheenColor;
-finalSheen=max(finalSheen,0.0);
-vec3 finalSheenScaled=finalSheen*vLightingIntensity.x*vLightingIntensity.w;
-#if defined(CLEARCOAT) && defined(REFLECTION) && defined(ENVIRONMENTBRDF)
-sheenOut.finalSheenRadianceScaled*=clearcoatOut.conservationFactor;
-#if defined(CLEARCOAT_TINT)
-sheenOut.finalSheenRadianceScaled*=clearcoatOut.absorption;
-#endif
-#endif
-#endif
-
-#ifdef CLEARCOAT
-vec3 finalClearCoat=clearCoatBase;
-finalClearCoat=max(finalClearCoat,0.0);
-vec3 finalClearCoatScaled=finalClearCoat*vLightingIntensity.x*vLightingIntensity.w;
-#if defined(ENVIRONMENTBRDF) && defined(MS_BRDF_ENERGY_CONSERVATION)
-finalClearCoatScaled*=clearcoatOut.energyConservationFactorClearCoat;
-#endif
-#ifdef SS_REFRACTION
-subSurfaceOut.finalRefraction*=clearcoatOut.conservationFactor;
-#ifdef CLEARCOAT_TINT
-subSurfaceOut.finalRefraction*=clearcoatOut.absorption;
-#endif
-#endif
-#endif
-
-#ifdef ALPHABLEND
-float luminanceOverAlpha=0.0;
-#if defined(REFLECTION) && defined(RADIANCEOVERALPHA)
-luminanceOverAlpha+=getLuminance(finalRadianceScaled);
-#if defined(CLEARCOAT)
-luminanceOverAlpha+=getLuminance(clearcoatOut.finalClearCoatRadianceScaled);
-#endif
-#endif
-#if defined(SPECULARTERM) && defined(SPECULAROVERALPHA)
-luminanceOverAlpha+=getLuminance(finalSpecularScaled);
-#endif
-#if defined(CLEARCOAT) && defined(CLEARCOATOVERALPHA)
-luminanceOverAlpha+=getLuminance(finalClearCoatScaled);
-#endif
-#if defined(RADIANCEOVERALPHA) || defined(SPECULAROVERALPHA) || defined(CLEARCOATOVERALPHA)
-alpha=saturate(alpha+luminanceOverAlpha*luminanceOverAlpha);
-#endif
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockFinalLitComponents=r_;var o_=`
-vec3 finalDiffuse=diffuseBase;
-finalDiffuse*=surfaceAlbedo.rgb;
-finalDiffuse=max(finalDiffuse,0.0);
-finalDiffuse*=vLightingIntensity.x;
-
-vec3 finalAmbient=vAmbientColor;
-finalAmbient*=surfaceAlbedo.rgb;
-
-vec3 finalEmissive=vEmissiveColor;
-#ifdef EMISSIVE
-vec3 emissiveColorTex=texture2D(emissiveSampler,vEmissiveUV+uvOffset).rgb;
-finalEmissive*=toLinearSpace(emissiveColorTex.rgb);
-finalEmissive*=vEmissiveInfos.y;
-#endif
-finalEmissive*=vLightingIntensity.y;
-
-#ifdef AMBIENT
-vec3 ambientOcclusionForDirectDiffuse=mix(vec3(1.),aoOut.ambientOcclusionColor,vAmbientInfos.w);
-#else
-vec3 ambientOcclusionForDirectDiffuse=aoOut.ambientOcclusionColor;
-#endif
-finalAmbient*=aoOut.ambientOcclusionColor;
-finalDiffuse*=ambientOcclusionForDirectDiffuse;
-`;ze.a.IncludesShadersStore.pbrBlockFinalUnlitComponents=o_;var a_=`vec4 finalColor=vec4(
-finalAmbient +
-finalDiffuse +
-#ifndef UNLIT
-#ifdef REFLECTION
-finalIrradiance +
-#endif
-#ifdef SPECULARTERM
-finalSpecularScaled +
-#endif
-#ifdef SHEEN
-finalSheenScaled +
-#endif
-#ifdef CLEARCOAT
-finalClearCoatScaled +
-#endif
-#ifdef REFLECTION
-finalRadianceScaled +
-#if defined(SHEEN) && defined(ENVIRONMENTBRDF)
-sheenOut.finalSheenRadianceScaled +
-#endif
-#ifdef CLEARCOAT
-clearcoatOut.finalClearCoatRadianceScaled +
-#endif
-#endif
-#ifdef SS_REFRACTION
-subSurfaceOut.finalRefraction +
-#endif
-#endif
-finalEmissive,
-alpha);
-
-#ifdef LIGHTMAP
-#ifndef LIGHTMAPEXCLUDED
-#ifdef USELIGHTMAPASSHADOWMAP
-finalColor.rgb*=lightmapColor.rgb;
-#else
-finalColor.rgb+=lightmapColor.rgb;
-#endif
-#endif
-#endif
-#define CUSTOM_FRAGMENT_BEFORE_FOG
-
-finalColor=max(finalColor,0.0);
-`;ze.a.IncludesShadersStore.pbrBlockFinalColorComposition=a_,f(155);var s_=`#ifdef IMAGEPROCESSINGPOSTPROCESS
-
-
-finalColor.rgb=clamp(finalColor.rgb,0.,30.0);
-#else
-
-finalColor=applyImageProcessing(finalColor);
-#endif
-finalColor.a*=visibility;
-#ifdef PREMULTIPLYALPHA
-
-finalColor.rgb*=finalColor.a;
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockImageProcessing=s_;var c_=`#if DEBUGMODE>0
-if (vClipSpacePosition.x/vClipSpacePosition.w>=vDebugMode.x) {
-
-#if DEBUGMODE == 1
-gl_FragColor.rgb=vPositionW.rgb;
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 2 && defined(NORMAL)
-gl_FragColor.rgb=vNormalW.rgb;
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 3 && defined(BUMP) || DEBUGMODE == 3 && defined(PARALLAX) || DEBUGMODE == 3 && defined(ANISOTROPIC)
-
-gl_FragColor.rgb=TBN[0];
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 4 && defined(BUMP) || DEBUGMODE == 4 && defined(PARALLAX) || DEBUGMODE == 4 && defined(ANISOTROPIC)
-
-gl_FragColor.rgb=TBN[1];
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 5
-
-gl_FragColor.rgb=normalW;
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 6 && defined(MAINUV1)
-gl_FragColor.rgb=vec3(vMainUV1,0.0);
-#elif DEBUGMODE == 7 && defined(MAINUV2)
-gl_FragColor.rgb=vec3(vMainUV2,0.0);
-#elif DEBUGMODE == 8 && defined(CLEARCOAT) && defined(CLEARCOAT_BUMP)
-
-gl_FragColor.rgb=clearcoatOut.TBNClearCoat[0];
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 9 && defined(CLEARCOAT) && defined(CLEARCOAT_BUMP)
-
-gl_FragColor.rgb=clearcoatOut.TBNClearCoat[1];
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 10 && defined(CLEARCOAT)
-
-gl_FragColor.rgb=clearcoatOut.clearCoatNormalW;
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 11 && defined(ANISOTROPIC)
-gl_FragColor.rgb=anisotropicOut.anisotropicNormal;
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 12 && defined(ANISOTROPIC)
-gl_FragColor.rgb=anisotropicOut.anisotropicTangent;
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 13 && defined(ANISOTROPIC)
-gl_FragColor.rgb=anisotropicOut.anisotropicBitangent;
-#define DEBUGMODE_NORMALIZE
-
-#elif DEBUGMODE == 20 && defined(ALBEDO)
-gl_FragColor.rgb=albedoTexture.rgb;
-#elif DEBUGMODE == 21 && defined(AMBIENT)
-gl_FragColor.rgb=aoOut.ambientOcclusionColorMap.rgb;
-#elif DEBUGMODE == 22 && defined(OPACITY)
-gl_FragColor.rgb=opacityMap.rgb;
-#elif DEBUGMODE == 23 && defined(EMISSIVE)
-gl_FragColor.rgb=emissiveColorTex.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 24 && defined(LIGHTMAP)
-gl_FragColor.rgb=lightmapColor.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 25 && defined(REFLECTIVITY) && defined(METALLICWORKFLOW)
-gl_FragColor.rgb=reflectivityOut.surfaceMetallicColorMap.rgb;
-#elif DEBUGMODE == 26 && defined(REFLECTIVITY) && !defined(METALLICWORKFLOW)
-gl_FragColor.rgb=reflectivityOut.surfaceReflectivityColorMap.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 27 && defined(CLEARCOAT) && defined(CLEARCOAT_TEXTURE)
-gl_FragColor.rgb=vec3(clearcoatOut.clearCoatMapData.rg,0.0);
-#elif DEBUGMODE == 28 && defined(CLEARCOAT) && defined(CLEARCOAT_TINT) && defined(CLEARCOAT_TINT_TEXTURE)
-gl_FragColor.rgb=clearcoatOut.clearCoatTintMapData.rgb;
-#elif DEBUGMODE == 29 && defined(SHEEN) && defined(SHEEN_TEXTURE)
-gl_FragColor.rgb=sheenOut.sheenMapData.rgb;
-#elif DEBUGMODE == 30 && defined(ANISOTROPIC) && defined(ANISOTROPIC_TEXTURE)
-gl_FragColor.rgb=anisotropicOut.anisotropyMapData.rgb;
-#elif DEBUGMODE == 31 && defined(SUBSURFACE) && defined(SS_THICKNESSANDMASK_TEXTURE)
-gl_FragColor.rgb=subSurfaceOut.thicknessMap.rgb;
-
-#elif DEBUGMODE == 40 && defined(SS_REFRACTION)
-
-gl_FragColor.rgb=subSurfaceOut.environmentRefraction.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 41 && defined(REFLECTION)
-gl_FragColor.rgb=reflectionOut.environmentRadiance.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 42 && defined(CLEARCOAT) && defined(REFLECTION)
-gl_FragColor.rgb=clearcoatOut.environmentClearCoatRadiance.rgb;
-#define DEBUGMODE_GAMMA
-
-#elif DEBUGMODE == 50
-gl_FragColor.rgb=diffuseBase.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 51 && defined(SPECULARTERM)
-gl_FragColor.rgb=specularBase.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 52 && defined(CLEARCOAT)
-gl_FragColor.rgb=clearCoatBase.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 53 && defined(SHEEN)
-gl_FragColor.rgb=sheenBase.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 54 && defined(REFLECTION)
-gl_FragColor.rgb=reflectionOut.environmentIrradiance.rgb;
-#define DEBUGMODE_GAMMA
-
-#elif DEBUGMODE == 60
-gl_FragColor.rgb=surfaceAlbedo.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 61
-gl_FragColor.rgb=clearcoatOut.specularEnvironmentR0;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 62 && defined(METALLICWORKFLOW)
-gl_FragColor.rgb=vec3(reflectivityOut.metallicRoughness.r);
-#elif DEBUGMODE == 71 && defined(METALLICWORKFLOW)
-gl_FragColor.rgb=reflectivityOut.metallicF0;
-#elif DEBUGMODE == 63
-gl_FragColor.rgb=vec3(roughness);
-#elif DEBUGMODE == 64
-gl_FragColor.rgb=vec3(alphaG);
-#elif DEBUGMODE == 65
-gl_FragColor.rgb=vec3(NdotV);
-#elif DEBUGMODE == 66 && defined(CLEARCOAT) && defined(CLEARCOAT_TINT)
-gl_FragColor.rgb=clearcoatOut.clearCoatColor.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 67 && defined(CLEARCOAT)
-gl_FragColor.rgb=vec3(clearcoatOut.clearCoatRoughness);
-#elif DEBUGMODE == 68 && defined(CLEARCOAT)
-gl_FragColor.rgb=vec3(clearcoatOut.clearCoatNdotV);
-#elif DEBUGMODE == 69 && defined(SUBSURFACE) && defined(SS_TRANSLUCENCY)
-gl_FragColor.rgb=subSurfaceOut.transmittance;
-#elif DEBUGMODE == 70 && defined(SUBSURFACE) && defined(SS_REFRACTION)
-gl_FragColor.rgb=subSurfaceOut.refractionTransmittance;
-
-#elif DEBUGMODE == 80 && defined(RADIANCEOCCLUSION)
-gl_FragColor.rgb=vec3(seo);
-#elif DEBUGMODE == 81 && defined(HORIZONOCCLUSION)
-gl_FragColor.rgb=vec3(eho);
-#elif DEBUGMODE == 82 && defined(MS_BRDF_ENERGY_CONSERVATION)
-gl_FragColor.rgb=vec3(energyConservationFactor);
-#elif DEBUGMODE == 83 && defined(ENVIRONMENTBRDF) && !defined(REFLECTIONMAP_SKYBOX)
-gl_FragColor.rgb=specularEnvironmentReflectance;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 84 && defined(CLEARCOAT) && defined(ENVIRONMENTBRDF) && !defined(REFLECTIONMAP_SKYBOX)
-gl_FragColor.rgb=clearcoatOut.clearCoatEnvironmentReflectance;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 85 && defined(SHEEN) && defined(REFLECTION)
-gl_FragColor.rgb=sheenOut.sheenEnvironmentReflectance;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 86 && defined(ALPHABLEND)
-gl_FragColor.rgb=vec3(luminanceOverAlpha);
-#elif DEBUGMODE == 87
-gl_FragColor.rgb=vec3(alpha);
-#endif
-gl_FragColor.rgb*=vDebugMode.y;
-#ifdef DEBUGMODE_NORMALIZE
-gl_FragColor.rgb=normalize(gl_FragColor.rgb)*0.5+0.5;
-#endif
-#ifdef DEBUGMODE_GAMMA
-gl_FragColor.rgb=toGammaSpace(gl_FragColor.rgb);
-#endif
-gl_FragColor.a=1.0;
-#ifdef PREPASS
-gl_FragData[0]=toLinearSpace(gl_FragColor);
-gl_FragData[1]=vec4(0.,0.,0.,0.);
-#endif
-return;
-}
-#endif`;ze.a.IncludesShadersStore.pbrDebug=c_;var l_=`#if defined(BUMP) || !defined(NORMAL) || defined(FORCENORMALFORWARD) || defined(SPECULARAA) || defined(CLEARCOAT_BUMP) || defined(ANISOTROPIC)
-#extension GL_OES_standard_derivatives : enable
-#endif
-#ifdef LODBASEDMICROSFURACE
-#extension GL_EXT_shader_texture_lod : enable
-#endif
-#define CUSTOM_FRAGMENT_BEGIN
-#ifdef LOGARITHMICDEPTH
-#extension GL_EXT_frag_depth : enable
-#endif
-#include<prePassDeclaration>[SCENE_MRT_COUNT]
-precision highp float;
-
-#ifndef FROMLINEARSPACE
-#define FROMLINEARSPACE
-#endif
-
-#include<__decl__pbrFragment>
-#include<pbrFragmentExtraDeclaration>
-#include<__decl__lightFragment>[0..maxSimultaneousLights]
-#include<pbrFragmentSamplersDeclaration>
-#include<imageProcessingDeclaration>
-#include<clipPlaneFragmentDeclaration>
-#include<logDepthDeclaration>
-#include<fogFragmentDeclaration>
-
-#include<helperFunctions>
-#include<subSurfaceScatteringFunctions>
-#include<importanceSampling>
-#include<pbrHelperFunctions>
-#include<imageProcessingFunctions>
-#include<shadowsFragmentFunctions>
-#include<harmonicsFunctions>
-#include<pbrDirectLightingSetupFunctions>
-#include<pbrDirectLightingFalloffFunctions>
-#include<pbrBRDFFunctions>
-#include<hdrFilteringFunctions>
-#include<pbrDirectLightingFunctions>
-#include<pbrIBLFunctions>
-#include<bumpFragmentMainFunctions>
-#include<bumpFragmentFunctions>
-#ifdef REFLECTION
-#include<reflectionFunction>
-#endif
-#define CUSTOM_FRAGMENT_DEFINITIONS
-#include<pbrBlockAlbedoOpacity>
-#include<pbrBlockReflectivity>
-#include<pbrBlockAmbientOcclusion>
-#include<pbrBlockAlphaFresnel>
-#include<pbrBlockAnisotropic>
-#include<pbrBlockReflection>
-#include<pbrBlockSheen>
-#include<pbrBlockClearcoat>
-#include<pbrBlockSubSurface>
-
-void main(void) {
-#define CUSTOM_FRAGMENT_MAIN_BEGIN
-#include<clipPlaneFragment>
-
-#include<pbrBlockNormalGeometric>
-#include<bumpFragment>
-#include<pbrBlockNormalFinal>
-
-albedoOpacityOutParams albedoOpacityOut;
-#ifdef ALBEDO
-vec4 albedoTexture=texture2D(albedoSampler,vAlbedoUV+uvOffset);
-#endif
-#ifdef OPACITY
-vec4 opacityMap=texture2D(opacitySampler,vOpacityUV+uvOffset);
-#endif
-albedoOpacityBlock(
-vAlbedoColor,
-#ifdef ALBEDO
-albedoTexture,
-vAlbedoInfos,
-#endif
-#ifdef OPACITY
-opacityMap,
-vOpacityInfos,
-#endif
-#ifdef DETAIL
-detailColor,
-vDetailInfos,
-#endif
-albedoOpacityOut
-);
-vec3 surfaceAlbedo=albedoOpacityOut.surfaceAlbedo;
-float alpha=albedoOpacityOut.alpha;
-#define CUSTOM_FRAGMENT_UPDATE_ALPHA
-#include<depthPrePass>
-#define CUSTOM_FRAGMENT_BEFORE_LIGHTS
-
-ambientOcclusionOutParams aoOut;
-#ifdef AMBIENT
-vec3 ambientOcclusionColorMap=texture2D(ambientSampler,vAmbientUV+uvOffset).rgb;
-#endif
-ambientOcclusionBlock(
-#ifdef AMBIENT
-ambientOcclusionColorMap,
-vAmbientInfos,
-#endif
-aoOut
-);
-#include<pbrBlockLightmapInit>
-#ifdef UNLIT
-vec3 diffuseBase=vec3(1.,1.,1.);
-#else
-
-vec3 baseColor=surfaceAlbedo;
-reflectivityOutParams reflectivityOut;
-#if defined(REFLECTIVITY)
-vec4 surfaceMetallicOrReflectivityColorMap=texture2D(reflectivitySampler,vReflectivityUV+uvOffset);
-vec4 baseReflectivity=surfaceMetallicOrReflectivityColorMap;
-#ifndef METALLICWORKFLOW
-surfaceMetallicOrReflectivityColorMap=toLinearSpace(surfaceMetallicOrReflectivityColorMap);
-surfaceMetallicOrReflectivityColorMap.rgb*=vReflectivityInfos.y;
-#endif
-#endif
-#if defined(MICROSURFACEMAP)
-vec4 microSurfaceTexel=texture2D(microSurfaceSampler,vMicroSurfaceSamplerUV+uvOffset)*vMicroSurfaceSamplerInfos.y;
-#endif
-#ifdef METALLICWORKFLOW
-vec4 metallicReflectanceFactors=vMetallicReflectanceFactors;
-#ifdef METALLIC_REFLECTANCE
-vec4 metallicReflectanceFactorsMap=texture2D(metallicReflectanceSampler,vMetallicReflectanceUV+uvOffset);
-metallicReflectanceFactorsMap=toLinearSpace(metallicReflectanceFactorsMap);
-metallicReflectanceFactors*=metallicReflectanceFactorsMap;
-#endif
-#endif
-reflectivityBlock(
-vReflectivityColor,
-#ifdef METALLICWORKFLOW
-surfaceAlbedo,
-metallicReflectanceFactors,
-#endif
-#ifdef REFLECTIVITY
-vReflectivityInfos,
-surfaceMetallicOrReflectivityColorMap,
-#endif
-#if defined(METALLICWORKFLOW) && defined(REFLECTIVITY) && defined(AOSTOREINMETALMAPRED)
-aoOut.ambientOcclusionColor,
-#endif
-#ifdef MICROSURFACEMAP
-microSurfaceTexel,
-#endif
-#ifdef DETAIL
-detailColor,
-vDetailInfos,
-#endif
-reflectivityOut
-);
-float microSurface=reflectivityOut.microSurface;
-float roughness=reflectivityOut.roughness;
-#ifdef METALLICWORKFLOW
-surfaceAlbedo=reflectivityOut.surfaceAlbedo;
-#endif
-#if defined(METALLICWORKFLOW) && defined(REFLECTIVITY) && defined(AOSTOREINMETALMAPRED)
-aoOut.ambientOcclusionColor=reflectivityOut.ambientOcclusionColor;
-#endif
-
-#ifdef ALPHAFRESNEL
-#if defined(ALPHATEST) || defined(ALPHABLEND)
-alphaFresnelOutParams alphaFresnelOut;
-alphaFresnelBlock(
-normalW,
-viewDirectionW,
-alpha,
-microSurface,
-alphaFresnelOut
-);
-alpha=alphaFresnelOut.alpha;
-#endif
-#endif
-
-#include<pbrBlockGeometryInfo>
-
-#ifdef ANISOTROPIC
-anisotropicOutParams anisotropicOut;
-#ifdef ANISOTROPIC_TEXTURE
-vec3 anisotropyMapData=texture2D(anisotropySampler,vAnisotropyUV+uvOffset).rgb*vAnisotropyInfos.y;
-#endif
-anisotropicBlock(
-vAnisotropy,
-#ifdef ANISOTROPIC_TEXTURE
-anisotropyMapData,
-#endif
-TBN,
-normalW,
-viewDirectionW,
-anisotropicOut
-);
-#endif
-
-#ifdef REFLECTION
-reflectionOutParams reflectionOut;
-reflectionBlock(
-vPositionW,
-normalW,
-alphaG,
-vReflectionMicrosurfaceInfos,
-vReflectionInfos,
-vReflectionColor,
-#ifdef ANISOTROPIC
-anisotropicOut,
-#endif
-#if defined(LODINREFLECTIONALPHA) && !defined(REFLECTIONMAP_SKYBOX)
-NdotVUnclamped,
-#endif
-#ifdef LINEARSPECULARREFLECTION
-roughness,
-#endif
-reflectionSampler,
-#if defined(NORMAL) && defined(USESPHERICALINVERTEX)
-vEnvironmentIrradiance,
-#endif
-#ifdef USESPHERICALFROMREFLECTIONMAP
-#if !defined(NORMAL) || !defined(USESPHERICALINVERTEX)
-reflectionMatrix,
-#endif
-#endif
-#ifdef USEIRRADIANCEMAP
-irradianceSampler,
-#endif
-#ifndef LODBASEDMICROSFURACE
-reflectionSamplerLow,
-reflectionSamplerHigh,
-#endif
-#ifdef REALTIME_FILTERING
-vReflectionFilteringInfo,
-#endif
-reflectionOut
-);
-#endif
-
-#include<pbrBlockReflectance0>
-
-#ifdef SHEEN
-sheenOutParams sheenOut;
-#ifdef SHEEN_TEXTURE
-vec4 sheenMapData=toLinearSpace(texture2D(sheenSampler,vSheenUV+uvOffset))*vSheenInfos.y;
-#endif
-#if defined(SHEEN_ROUGHNESS) && defined(SHEEN_TEXTURE_ROUGHNESS) && !defined(SHEEN_TEXTURE_ROUGHNESS_IDENTICAL) && !defined(SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE)
-vec4 sheenMapRoughnessData=texture2D(sheenRoughnessSampler,vSheenRoughnessUV+uvOffset)*vSheenInfos.w;
-#endif
-sheenBlock(
-vSheenColor,
-#ifdef SHEEN_ROUGHNESS
-vSheenRoughness,
-#if defined(SHEEN_TEXTURE_ROUGHNESS) && !defined(SHEEN_TEXTURE_ROUGHNESS_IDENTICAL) && !defined(SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE)
-sheenMapRoughnessData,
-#endif
-#endif
-roughness,
-#ifdef SHEEN_TEXTURE
-sheenMapData,
-#endif
-reflectance,
-#ifdef SHEEN_LINKWITHALBEDO
-baseColor,
-surfaceAlbedo,
-#endif
-#ifdef ENVIRONMENTBRDF
-NdotV,
-environmentBrdf,
-#endif
-#if defined(REFLECTION) && defined(ENVIRONMENTBRDF)
-AARoughnessFactors,
-vReflectionMicrosurfaceInfos,
-vReflectionInfos,
-vReflectionColor,
-vLightingIntensity,
-reflectionSampler,
-reflectionOut.reflectionCoords,
-NdotVUnclamped,
-#ifndef LODBASEDMICROSFURACE
-reflectionSamplerLow,
-reflectionSamplerHigh,
-#endif
-#ifdef REALTIME_FILTERING
-vReflectionFilteringInfo,
-#endif
-#if !defined(REFLECTIONMAP_SKYBOX) && defined(RADIANCEOCCLUSION)
-seo,
-#endif
-#if !defined(REFLECTIONMAP_SKYBOX) && defined(HORIZONOCCLUSION) && defined(BUMP) && defined(REFLECTIONMAP_3D)
-eho,
-#endif
-#endif
-sheenOut
-);
-#ifdef SHEEN_LINKWITHALBEDO
-surfaceAlbedo=sheenOut.surfaceAlbedo;
-#endif
-#endif
-
-clearcoatOutParams clearcoatOut;
-#ifdef CLEARCOAT
-#ifdef CLEARCOAT_TEXTURE
-vec2 clearCoatMapData=texture2D(clearCoatSampler,vClearCoatUV+uvOffset).rg*vClearCoatInfos.y;
-#endif
-#if defined(CLEARCOAT_TEXTURE_ROUGHNESS) && !defined(CLEARCOAT_TEXTURE_ROUGHNESS_IDENTICAL) && !defined(CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE)
-vec4 clearCoatMapRoughnessData=texture2D(clearCoatRoughnessSampler,vClearCoatRoughnessUV+uvOffset)*vClearCoatInfos.w;
-#endif
-#if defined(CLEARCOAT_TINT) && defined(CLEARCOAT_TINT_TEXTURE)
-vec4 clearCoatTintMapData=toLinearSpace(texture2D(clearCoatTintSampler,vClearCoatTintUV+uvOffset));
-#endif
-#ifdef CLEARCOAT_BUMP
-vec4 clearCoatBumpMapData=texture2D(clearCoatBumpSampler,vClearCoatBumpUV+uvOffset);
-#endif
-clearcoatBlock(
-vPositionW,
-geometricNormalW,
-viewDirectionW,
-vClearCoatParams,
-#if defined(CLEARCOAT_TEXTURE_ROUGHNESS) && !defined(CLEARCOAT_TEXTURE_ROUGHNESS_IDENTICAL) && !defined(CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE)
-clearCoatMapRoughnessData,
-#endif
-specularEnvironmentR0,
-#ifdef CLEARCOAT_TEXTURE
-clearCoatMapData,
-#endif
-#ifdef CLEARCOAT_TINT
-vClearCoatTintParams,
-clearCoatColorAtDistance,
-vClearCoatRefractionParams,
-#ifdef CLEARCOAT_TINT_TEXTURE
-clearCoatTintMapData,
-#endif
-#endif
-#ifdef CLEARCOAT_BUMP
-vClearCoatBumpInfos,
-clearCoatBumpMapData,
-vClearCoatBumpUV,
-#if defined(TANGENT) && defined(NORMAL)
-vTBN,
-#else
-vClearCoatTangentSpaceParams,
-#endif
-#ifdef OBJECTSPACE_NORMALMAP
-normalMatrix,
-#endif
-#endif
-#if defined(FORCENORMALFORWARD) && defined(NORMAL)
-faceNormal,
-#endif
-#ifdef REFLECTION
-vReflectionMicrosurfaceInfos,
-vReflectionInfos,
-vReflectionColor,
-vLightingIntensity,
-reflectionSampler,
-#ifndef LODBASEDMICROSFURACE
-reflectionSamplerLow,
-reflectionSamplerHigh,
-#endif
-#ifdef REALTIME_FILTERING
-vReflectionFilteringInfo,
-#endif
-#endif
-#if defined(ENVIRONMENTBRDF) && !defined(REFLECTIONMAP_SKYBOX)
-#ifdef RADIANCEOCCLUSION
-ambientMonochrome,
-#endif
-#endif
-clearcoatOut
-);
-#else
-clearcoatOut.specularEnvironmentR0=specularEnvironmentR0;
-#endif
-
-#include<pbrBlockReflectance>
-
-subSurfaceOutParams subSurfaceOut;
-#ifdef SUBSURFACE
-#ifdef SS_THICKNESSANDMASK_TEXTURE
-vec4 thicknessMap=texture2D(thicknessSampler,vThicknessUV+uvOffset);
-#endif
-subSurfaceBlock(
-vSubSurfaceIntensity,
-vThicknessParam,
-vTintColor,
-normalW,
-specularEnvironmentReflectance,
-#ifdef SS_THICKNESSANDMASK_TEXTURE
-thicknessMap,
-#endif
-#ifdef REFLECTION
-#ifdef SS_TRANSLUCENCY
-reflectionMatrix,
-#ifdef USESPHERICALFROMREFLECTIONMAP
-#if !defined(NORMAL) || !defined(USESPHERICALINVERTEX)
-reflectionOut.irradianceVector,
-#endif
-#if defined(REALTIME_FILTERING)
-reflectionSampler,
-vReflectionFilteringInfo,
-#endif
-#endif
-#ifdef USEIRRADIANCEMAP
-irradianceSampler,
-#endif
-#endif
-#endif
-#ifdef SS_REFRACTION
-vPositionW,
-viewDirectionW,
-view,
-surfaceAlbedo,
-vRefractionInfos,
-refractionMatrix,
-vRefractionMicrosurfaceInfos,
-vLightingIntensity,
-#ifdef SS_LINKREFRACTIONTOTRANSPARENCY
-alpha,
-#endif
-#ifdef SS_LODINREFRACTIONALPHA
-NdotVUnclamped,
-#endif
-#ifdef SS_LINEARSPECULARREFRACTION
-roughness,
-#else
-alphaG,
-#endif
-refractionSampler,
-#ifndef LODBASEDMICROSFURACE
-refractionSamplerLow,
-refractionSamplerHigh,
-#endif
-#ifdef ANISOTROPIC
-anisotropicOut,
-#endif
-#ifdef REALTIME_FILTERING
-vRefractionFilteringInfo,
-#endif
-#endif
-#ifdef SS_TRANSLUCENCY
-vDiffusionDistance,
-#endif
-subSurfaceOut
-);
-#ifdef SS_REFRACTION
-surfaceAlbedo=subSurfaceOut.surfaceAlbedo;
-#ifdef SS_LINKREFRACTIONTOTRANSPARENCY
-alpha=subSurfaceOut.alpha;
-#endif
-#endif
-#else
-subSurfaceOut.specularEnvironmentReflectance=specularEnvironmentReflectance;
-#endif
-
-#include<pbrBlockDirectLighting>
-#include<lightFragment>[0..maxSimultaneousLights]
-
-#include<pbrBlockFinalLitComponents>
-#endif
-#include<pbrBlockFinalUnlitComponents>
-#include<pbrBlockFinalColorComposition>
-#include<logDepthFragment>
-#include<fogFragment>(color,finalColor)
-#include<pbrBlockImageProcessing>
-#define CUSTOM_FRAGMENT_BEFORE_FRAGCOLOR
-#ifdef PREPASS
-#ifdef PREPASS_POSITION
-gl_FragData[PREPASS_POSITION_INDEX]=vec4(vPositionW,1.0);
-#endif
-#ifdef PREPASS_VELOCITY
-vec2 a=(vCurrentPosition.xy/vCurrentPosition.w)*0.5+0.5;
-vec2 b=(vPreviousPosition.xy/vPreviousPosition.w)*0.5+0.5;
-vec2 velocity=abs(a-b);
-velocity=vec2(pow(velocity.x,1.0/3.0),pow(velocity.y,1.0/3.0))*sign(a-b)*0.5+0.5;
-gl_FragData[PREPASS_VELOCITY_INDEX]=vec4(velocity,0.0,1.0);
-#endif
-#ifdef PREPASS_IRRADIANCE
-vec3 irradiance=finalDiffuse;
-#ifndef UNLIT
-#ifdef REFLECTION
-irradiance+=finalIrradiance;
-#endif
-#endif
-vec3 sqAlbedo=sqrt(surfaceAlbedo);
-#ifdef SS_SCATTERING
-gl_FragData[0]=vec4(finalColor.rgb-irradiance,finalColor.a);
-irradiance/=sqAlbedo;
-#else
-gl_FragData[0]=finalColor;
-float scatteringDiffusionProfile=255.;
-#endif
-gl_FragData[PREPASS_IRRADIANCE_INDEX]=vec4(irradiance,scatteringDiffusionProfile/255.);
-#else
-gl_FragData[0]=vec4(finalColor.rgb,finalColor.a);
-#endif
-#ifdef PREPASS_DEPTHNORMAL
-gl_FragData[PREPASS_DEPTHNORMAL_INDEX]=vec4(vViewPos.z,(view*vec4(normalW,0.0)).rgb);
-#endif
-#ifdef PREPASS_ALBEDO
-gl_FragData[PREPASS_ALBEDO_INDEX]=vec4(sqAlbedo,1.0);
-#endif
-#ifdef PREPASS_REFLECTIVITY
-#if defined(REFLECTIVITY)
-gl_FragData[PREPASS_REFLECTIVITY_INDEX]=vec4(baseReflectivity.rgb,1.0);
-#else
-gl_FragData[PREPASS_REFLECTIVITY_INDEX]=vec4(0.0,0.0,0.0,1.0);
-#endif
-#endif
-#endif
-#if !defined(PREPASS) || defined(WEBGL2)
-gl_FragColor=finalColor;
-#endif
-#include<pbrDebug>
-}
-`;ze.a.ShadersStore.pbrPixelShader=l_;var u_=`uniform mat4 view;
-uniform mat4 viewProjection;
-#ifdef ALBEDO
-uniform mat4 albedoMatrix;
-uniform vec2 vAlbedoInfos;
-#endif
-#ifdef AMBIENT
-uniform mat4 ambientMatrix;
-uniform vec4 vAmbientInfos;
-#endif
-#ifdef OPACITY
-uniform mat4 opacityMatrix;
-uniform vec2 vOpacityInfos;
-#endif
-#ifdef EMISSIVE
-uniform vec2 vEmissiveInfos;
-uniform mat4 emissiveMatrix;
-#endif
-#ifdef LIGHTMAP
-uniform vec2 vLightmapInfos;
-uniform mat4 lightmapMatrix;
-#endif
-#ifdef REFLECTIVITY
-uniform vec3 vReflectivityInfos;
-uniform mat4 reflectivityMatrix;
-#endif
-#ifdef METALLIC_REFLECTANCE
-uniform vec2 vMetallicReflectanceInfos;
-uniform mat4 metallicReflectanceMatrix;
-#endif
-#ifdef MICROSURFACEMAP
-uniform vec2 vMicroSurfaceSamplerInfos;
-uniform mat4 microSurfaceSamplerMatrix;
-#endif
-#ifdef BUMP
-uniform vec3 vBumpInfos;
-uniform mat4 bumpMatrix;
-#endif
-#ifdef POINTSIZE
-uniform float pointSize;
-#endif
-
-#ifdef REFLECTION
-uniform vec2 vReflectionInfos;
-uniform mat4 reflectionMatrix;
-#endif
-
-#ifdef CLEARCOAT
-#if defined(CLEARCOAT_TEXTURE) || defined(CLEARCOAT_TEXTURE_ROUGHNESS)
-uniform vec4 vClearCoatInfos;
-#endif
-#ifdef CLEARCOAT_TEXTURE
-uniform mat4 clearCoatMatrix;
-#endif
-#ifdef CLEARCOAT_TEXTURE_ROUGHNESS
-uniform mat4 clearCoatRoughnessMatrix;
-#endif
-#ifdef CLEARCOAT_BUMP
-uniform vec2 vClearCoatBumpInfos;
-uniform mat4 clearCoatBumpMatrix;
-#endif
-#ifdef CLEARCOAT_TINT_TEXTURE
-uniform vec2 vClearCoatTintInfos;
-uniform mat4 clearCoatTintMatrix;
-#endif
-#endif
-
-#ifdef ANISOTROPIC
-#ifdef ANISOTROPIC_TEXTURE
-uniform vec2 vAnisotropyInfos;
-uniform mat4 anisotropyMatrix;
-#endif
-#endif
-
-#ifdef SHEEN
-#if defined(SHEEN_TEXTURE) || defined(SHEEN_TEXTURE_ROUGHNESS)
-uniform vec4 vSheenInfos;
-#endif
-#ifdef SHEEN_TEXTURE
-uniform mat4 sheenMatrix;
-#endif
-#ifdef SHEEN_TEXTURE_ROUGHNESS
-uniform mat4 sheenRoughnessMatrix;
-#endif
-#endif
-
-#ifdef SUBSURFACE
-#ifdef SS_REFRACTION
-uniform vec4 vRefractionInfos;
-uniform mat4 refractionMatrix;
-#endif
-#ifdef SS_THICKNESSANDMASK_TEXTURE
-uniform vec2 vThicknessInfos;
-uniform mat4 thicknessMatrix;
-#endif
-#endif
-`;ze.a.IncludesShadersStore.pbrVertexDeclaration=u_,f(163),f(164),f(93),f(94),f(100),f(165),f(156),f(158);var h_=`precision highp float;
-#include<__decl__pbrVertex>
-#define CUSTOM_VERTEX_BEGIN
-
-attribute vec3 position;
-#ifdef NORMAL
-attribute vec3 normal;
-#endif
-#ifdef TANGENT
-attribute vec4 tangent;
-#endif
-#ifdef UV1
-attribute vec2 uv;
-#endif
-#ifdef UV2
-attribute vec2 uv2;
-#endif
-#ifdef MAINUV1
-varying vec2 vMainUV1;
-#endif
-#ifdef MAINUV2
-varying vec2 vMainUV2;
-#endif
-#ifdef VERTEXCOLOR
-attribute vec4 color;
-#endif
-#include<helperFunctions>
-#include<bonesDeclaration>
-
-#include<instancesDeclaration>
-#include<prePassVertexDeclaration>
-#if defined(ALBEDO) && ALBEDODIRECTUV == 0
-varying vec2 vAlbedoUV;
-#endif
-#if defined(DETAIL) && DETAILDIRECTUV == 0
-varying vec2 vDetailUV;
-#endif
-#if defined(AMBIENT) && AMBIENTDIRECTUV == 0
-varying vec2 vAmbientUV;
-#endif
-#if defined(OPACITY) && OPACITYDIRECTUV == 0
-varying vec2 vOpacityUV;
-#endif
-#if defined(EMISSIVE) && EMISSIVEDIRECTUV == 0
-varying vec2 vEmissiveUV;
-#endif
-#if defined(LIGHTMAP) && LIGHTMAPDIRECTUV == 0
-varying vec2 vLightmapUV;
-#endif
-#if defined(REFLECTIVITY) && REFLECTIVITYDIRECTUV == 0
-varying vec2 vReflectivityUV;
-#endif
-#if defined(MICROSURFACEMAP) && MICROSURFACEMAPDIRECTUV == 0
-varying vec2 vMicroSurfaceSamplerUV;
-#endif
-#if defined(METALLIC_REFLECTANCE) && METALLIC_REFLECTANCEDIRECTUV == 0
-varying vec2 vMetallicReflectanceUV;
-#endif
-#if defined(BUMP) && BUMPDIRECTUV == 0
-varying vec2 vBumpUV;
-#endif
-#ifdef CLEARCOAT
-#if defined(CLEARCOAT_TEXTURE) && CLEARCOAT_TEXTUREDIRECTUV == 0
-varying vec2 vClearCoatUV;
-#endif
-#if defined(CLEARCOAT_TEXTURE_ROUGHNESS) && CLEARCOAT_TEXTURE_ROUGHNESSDIRECTUV == 0
-varying vec2 vClearCoatRoughnessUV;
-#endif
-#if defined(CLEARCOAT_BUMP) && CLEARCOAT_BUMPDIRECTUV == 0
-varying vec2 vClearCoatBumpUV;
-#endif
-#if defined(CLEARCOAT_TINT_TEXTURE) && CLEARCOAT_TINT_TEXTUREDIRECTUV == 0
-varying vec2 vClearCoatTintUV;
-#endif
-#endif
-#ifdef SHEEN
-#if defined(SHEEN_TEXTURE) && SHEEN_TEXTUREDIRECTUV == 0
-varying vec2 vSheenUV;
-#endif
-#if defined(SHEEN_TEXTURE_ROUGHNESS) && SHEEN_TEXTURE_ROUGHNESSDIRECTUV == 0
-varying vec2 vSheenRoughnessUV;
-#endif
-#endif
-#ifdef ANISOTROPIC
-#if defined(ANISOTROPIC_TEXTURE) && ANISOTROPIC_TEXTUREDIRECTUV == 0
-varying vec2 vAnisotropyUV;
-#endif
-#endif
-#ifdef SUBSURFACE
-#if defined(SS_THICKNESSANDMASK_TEXTURE) && SS_THICKNESSANDMASK_TEXTUREDIRECTUV == 0
-varying vec2 vThicknessUV;
-#endif
-#endif
-
-varying vec3 vPositionW;
-#if DEBUGMODE>0
-varying vec4 vClipSpacePosition;
-#endif
-#ifdef NORMAL
-varying vec3 vNormalW;
-#if defined(USESPHERICALFROMREFLECTIONMAP) && defined(USESPHERICALINVERTEX)
-varying vec3 vEnvironmentIrradiance;
-#include<harmonicsFunctions>
-#endif
-#endif
-#ifdef VERTEXCOLOR
-varying vec4 vColor;
-#endif
-#include<bumpVertexDeclaration>
-#include<clipPlaneVertexDeclaration>
-#include<fogVertexDeclaration>
-#include<__decl__lightFragment>[0..maxSimultaneousLights]
-#include<morphTargetsVertexGlobalDeclaration>
-#include<morphTargetsVertexDeclaration>[0..maxSimultaneousMorphTargets]
-#ifdef REFLECTIONMAP_SKYBOX
-varying vec3 vPositionUVW;
-#endif
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
-varying vec3 vDirectionW;
-#endif
-#include<logDepthDeclaration>
-#define CUSTOM_VERTEX_DEFINITIONS
-void main(void) {
-#define CUSTOM_VERTEX_MAIN_BEGIN
-vec3 positionUpdated=position;
-#ifdef NORMAL
-vec3 normalUpdated=normal;
-#endif
-#ifdef TANGENT
-vec4 tangentUpdated=tangent;
-#endif
-#ifdef UV1
-vec2 uvUpdated=uv;
-#endif
-#include<morphTargetsVertex>[0..maxSimultaneousMorphTargets]
-#ifdef REFLECTIONMAP_SKYBOX
-vPositionUVW=positionUpdated;
-#endif
-#define CUSTOM_VERTEX_UPDATE_POSITION
-#define CUSTOM_VERTEX_UPDATE_NORMAL
-#include<instancesVertex>
-#if defined(PREPASS) && defined(PREPASS_VELOCITY) && !defined(BONES_VELOCITY_ENABLED)
-
-vCurrentPosition=viewProjection*finalWorld*vec4(positionUpdated,1.0);
-vPreviousPosition=previousViewProjection*previousWorld*vec4(positionUpdated,1.0);
-#endif
-#include<bonesVertex>
-vec4 worldPos=finalWorld*vec4(positionUpdated,1.0);
-vPositionW=vec3(worldPos);
-#include<prePassVertex>
-#ifdef NORMAL
-mat3 normalWorld=mat3(finalWorld);
-#if defined(INSTANCES) && defined(THIN_INSTANCES)
-vNormalW=normalUpdated/vec3(dot(normalWorld[0],normalWorld[0]),dot(normalWorld[1],normalWorld[1]),dot(normalWorld[2],normalWorld[2]));
-vNormalW=normalize(normalWorld*vNormalW);
-#else
-#ifdef NONUNIFORMSCALING
-normalWorld=transposeMat3(inverseMat3(normalWorld));
-#endif
-vNormalW=normalize(normalWorld*normalUpdated);
-#endif
-#if defined(USESPHERICALFROMREFLECTIONMAP) && defined(USESPHERICALINVERTEX)
-vec3 reflectionVector=vec3(reflectionMatrix*vec4(vNormalW,0)).xyz;
-#ifdef REFLECTIONMAP_OPPOSITEZ
-reflectionVector.z*=-1.0;
-#endif
-vEnvironmentIrradiance=computeEnvironmentIrradiance(reflectionVector);
-#endif
-#endif
-#define CUSTOM_VERTEX_UPDATE_WORLDPOS
-#ifdef MULTIVIEW
-if (gl_ViewID_OVR == 0u) {
-gl_Position=viewProjection*worldPos;
-} else {
-gl_Position=viewProjectionR*worldPos;
-}
-#else
-gl_Position=viewProjection*worldPos;
-#endif
-#if DEBUGMODE>0
-vClipSpacePosition=gl_Position;
-#endif
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
-vDirectionW=normalize(vec3(finalWorld*vec4(positionUpdated,0.0)));
-#endif
-
-#ifndef UV1
-vec2 uvUpdated=vec2(0.,0.);
-#endif
-#ifndef UV2
-vec2 uv2=vec2(0.,0.);
-#endif
-#ifdef MAINUV1
-vMainUV1=uvUpdated;
-#endif
-#ifdef MAINUV2
-vMainUV2=uv2;
-#endif
-#if defined(ALBEDO) && ALBEDODIRECTUV == 0
-if (vAlbedoInfos.x == 0.)
-{
-vAlbedoUV=vec2(albedoMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vAlbedoUV=vec2(albedoMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(DETAIL) && DETAILDIRECTUV == 0
-if (vDetailInfos.x == 0.)
-{
-vDetailUV=vec2(detailMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vDetailUV=vec2(detailMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(AMBIENT) && AMBIENTDIRECTUV == 0
-if (vAmbientInfos.x == 0.)
-{
-vAmbientUV=vec2(ambientMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vAmbientUV=vec2(ambientMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(OPACITY) && OPACITYDIRECTUV == 0
-if (vOpacityInfos.x == 0.)
-{
-vOpacityUV=vec2(opacityMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vOpacityUV=vec2(opacityMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(EMISSIVE) && EMISSIVEDIRECTUV == 0
-if (vEmissiveInfos.x == 0.)
-{
-vEmissiveUV=vec2(emissiveMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vEmissiveUV=vec2(emissiveMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(LIGHTMAP) && LIGHTMAPDIRECTUV == 0
-if (vLightmapInfos.x == 0.)
-{
-vLightmapUV=vec2(lightmapMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vLightmapUV=vec2(lightmapMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(REFLECTIVITY) && REFLECTIVITYDIRECTUV == 0
-if (vReflectivityInfos.x == 0.)
-{
-vReflectivityUV=vec2(reflectivityMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vReflectivityUV=vec2(reflectivityMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(MICROSURFACEMAP) && MICROSURFACEMAPDIRECTUV == 0
-if (vMicroSurfaceSamplerInfos.x == 0.)
-{
-vMicroSurfaceSamplerUV=vec2(microSurfaceSamplerMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vMicroSurfaceSamplerUV=vec2(microSurfaceSamplerMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(METALLIC_REFLECTANCE) && METALLIC_REFLECTANCEDIRECTUV == 0
-if (vMetallicReflectanceInfos.x == 0.)
-{
-vMetallicReflectanceUV=vec2(metallicReflectanceMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vMetallicReflectanceUV=vec2(metallicReflectanceMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(BUMP) && BUMPDIRECTUV == 0
-if (vBumpInfos.x == 0.)
-{
-vBumpUV=vec2(bumpMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vBumpUV=vec2(bumpMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#ifdef CLEARCOAT
-#if defined(CLEARCOAT_TEXTURE) && CLEARCOAT_TEXTUREDIRECTUV == 0
-if (vClearCoatInfos.x == 0.)
-{
-vClearCoatUV=vec2(clearCoatMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vClearCoatUV=vec2(clearCoatMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(CLEARCOAT_TEXTURE_ROUGHNESS) && CLEARCOAT_TEXTURE_ROUGHNESSDIRECTUV == 0
-if (vClearCoatInfos.z == 0.)
-{
-vClearCoatRoughnessUV=vec2(clearCoatRoughnessMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vClearCoatRoughnessUV=vec2(clearCoatRoughnessMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(CLEARCOAT_BUMP) && CLEARCOAT_BUMPDIRECTUV == 0
-if (vClearCoatBumpInfos.x == 0.)
-{
-vClearCoatBumpUV=vec2(clearCoatBumpMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vClearCoatBumpUV=vec2(clearCoatBumpMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(CLEARCOAT_TINT_TEXTURE) && CLEARCOAT_TINT_TEXTUREDIRECTUV == 0
-if (vClearCoatTintInfos.x == 0.)
-{
-vClearCoatTintUV=vec2(clearCoatTintMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vClearCoatTintUV=vec2(clearCoatTintMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#endif
-#ifdef SHEEN
-#if defined(SHEEN_TEXTURE) && SHEEN_TEXTUREDIRECTUV == 0
-if (vSheenInfos.x == 0.)
-{
-vSheenUV=vec2(sheenMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vSheenUV=vec2(sheenMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(SHEEN_TEXTURE_ROUGHNESS) && SHEEN_TEXTURE_ROUGHNESSDIRECTUV == 0
-if (vSheenInfos.z == 0.)
-{
-vSheenRoughnessUV=vec2(sheenRoughnessMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vSheenRoughnessUV=vec2(sheenRoughnessMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#endif
-#ifdef ANISOTROPIC
-#if defined(ANISOTROPIC_TEXTURE) && ANISOTROPIC_TEXTUREDIRECTUV == 0
-if (vAnisotropyInfos.x == 0.)
-{
-vAnisotropyUV=vec2(anisotropyMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vAnisotropyUV=vec2(anisotropyMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#endif
-#ifdef SUBSURFACE
-#if defined(SS_THICKNESSANDMASK_TEXTURE) && SS_THICKNESSANDMASK_TEXTUREDIRECTUV == 0
-if (vThicknessInfos.x == 0.)
-{
-vThicknessUV=vec2(thicknessMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vThicknessUV=vec2(thicknessMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#endif
-
-#include<bumpVertex>
-
-#include<clipPlaneVertex>
-
-#include<fogVertex>
-
-#include<shadowsVertex>[0..maxSimultaneousLights]
-
-#ifdef VERTEXCOLOR
-vColor=color;
-#endif
-
-#ifdef POINTSIZE
-gl_PointSize=pointSize;
-#endif
-
-#include<logDepthVertex>
-#define CUSTOM_VERTEX_MAIN_END
-}`;ze.a.ShadersStore.pbrVertexShader=h_;var ta=f(92),Cr={effect:null,subMesh:null},ws=function(r){function t(){var e=r.call(this)||this;return e.PBR=!0,e.NUM_SAMPLES="0",e.REALTIME_FILTERING=!1,e.MAINUV1=!1,e.MAINUV2=!1,e.UV1=!1,e.UV2=!1,e.ALBEDO=!1,e.GAMMAALBEDO=!1,e.ALBEDODIRECTUV=0,e.VERTEXCOLOR=!1,e.DETAIL=!1,e.DETAILDIRECTUV=0,e.DETAIL_NORMALBLENDMETHOD=0,e.AMBIENT=!1,e.AMBIENTDIRECTUV=0,e.AMBIENTINGRAYSCALE=!1,e.OPACITY=!1,e.VERTEXALPHA=!1,e.OPACITYDIRECTUV=0,e.OPACITYRGB=!1,e.ALPHATEST=!1,e.DEPTHPREPASS=!1,e.ALPHABLEND=!1,e.ALPHAFROMALBEDO=!1,e.ALPHATESTVALUE="0.5",e.SPECULAROVERALPHA=!1,e.RADIANCEOVERALPHA=!1,e.ALPHAFRESNEL=!1,e.LINEARALPHAFRESNEL=!1,e.PREMULTIPLYALPHA=!1,e.EMISSIVE=!1,e.EMISSIVEDIRECTUV=0,e.REFLECTIVITY=!1,e.REFLECTIVITYDIRECTUV=0,e.SPECULARTERM=!1,e.MICROSURFACEFROMREFLECTIVITYMAP=!1,e.MICROSURFACEAUTOMATIC=!1,e.LODBASEDMICROSFURACE=!1,e.MICROSURFACEMAP=!1,e.MICROSURFACEMAPDIRECTUV=0,e.METALLICWORKFLOW=!1,e.ROUGHNESSSTOREINMETALMAPALPHA=!1,e.ROUGHNESSSTOREINMETALMAPGREEN=!1,e.METALLNESSSTOREINMETALMAPBLUE=!1,e.AOSTOREINMETALMAPRED=!1,e.METALLIC_REFLECTANCE=!1,e.METALLIC_REFLECTANCEDIRECTUV=0,e.ENVIRONMENTBRDF=!1,e.ENVIRONMENTBRDF_RGBD=!1,e.NORMAL=!1,e.TANGENT=!1,e.BUMP=!1,e.BUMPDIRECTUV=0,e.OBJECTSPACE_NORMALMAP=!1,e.PARALLAX=!1,e.PARALLAXOCCLUSION=!1,e.NORMALXYSCALE=!0,e.LIGHTMAP=!1,e.LIGHTMAPDIRECTUV=0,e.USELIGHTMAPASSHADOWMAP=!1,e.GAMMALIGHTMAP=!1,e.RGBDLIGHTMAP=!1,e.REFLECTION=!1,e.REFLECTIONMAP_3D=!1,e.REFLECTIONMAP_SPHERICAL=!1,e.REFLECTIONMAP_PLANAR=!1,e.REFLECTIONMAP_CUBIC=!1,e.USE_LOCAL_REFLECTIONMAP_CUBIC=!1,e.REFLECTIONMAP_PROJECTION=!1,e.REFLECTIONMAP_SKYBOX=!1,e.REFLECTIONMAP_EXPLICIT=!1,e.REFLECTIONMAP_EQUIRECTANGULAR=!1,e.REFLECTIONMAP_EQUIRECTANGULAR_FIXED=!1,e.REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED=!1,e.INVERTCUBICMAP=!1,e.USESPHERICALFROMREFLECTIONMAP=!1,e.USEIRRADIANCEMAP=!1,e.SPHERICAL_HARMONICS=!1,e.USESPHERICALINVERTEX=!1,e.REFLECTIONMAP_OPPOSITEZ=!1,e.LODINREFLECTIONALPHA=!1,e.GAMMAREFLECTION=!1,e.RGBDREFLECTION=!1,e.LINEARSPECULARREFLECTION=!1,e.RADIANCEOCCLUSION=!1,e.HORIZONOCCLUSION=!1,e.INSTANCES=!1,e.THIN_INSTANCES=!1,e.PREPASS=!1,e.PREPASS_IRRADIANCE=!1,e.PREPASS_IRRADIANCE_INDEX=-1,e.PREPASS_ALBEDO=!1,e.PREPASS_ALBEDO_INDEX=-1,e.PREPASS_DEPTHNORMAL=!1,e.PREPASS_DEPTHNORMAL_INDEX=-1,e.PREPASS_POSITION=!1,e.PREPASS_POSITION_INDEX=-1,e.PREPASS_VELOCITY=!1,e.PREPASS_VELOCITY_INDEX=-1,e.PREPASS_REFLECTIVITY=!1,e.PREPASS_REFLECTIVITY_INDEX=-1,e.SCENE_MRT_COUNT=0,e.NUM_BONE_INFLUENCERS=0,e.BonesPerMesh=0,e.BONETEXTURE=!1,e.BONES_VELOCITY_ENABLED=!1,e.NONUNIFORMSCALING=!1,e.MORPHTARGETS=!1,e.MORPHTARGETS_NORMAL=!1,e.MORPHTARGETS_TANGENT=!1,e.MORPHTARGETS_UV=!1,e.NUM_MORPH_INFLUENCERS=0,e.IMAGEPROCESSING=!1,e.VIGNETTE=!1,e.VIGNETTEBLENDMODEMULTIPLY=!1,e.VIGNETTEBLENDMODEOPAQUE=!1,e.TONEMAPPING=!1,e.TONEMAPPING_ACES=!1,e.CONTRAST=!1,e.COLORCURVES=!1,e.COLORGRADING=!1,e.COLORGRADING3D=!1,e.SAMPLER3DGREENDEPTH=!1,e.SAMPLER3DBGRMAP=!1,e.IMAGEPROCESSINGPOSTPROCESS=!1,e.EXPOSURE=!1,e.MULTIVIEW=!1,e.USEPHYSICALLIGHTFALLOFF=!1,e.USEGLTFLIGHTFALLOFF=!1,e.TWOSIDEDLIGHTING=!1,e.SHADOWFLOAT=!1,e.CLIPPLANE=!1,e.CLIPPLANE2=!1,e.CLIPPLANE3=!1,e.CLIPPLANE4=!1,e.CLIPPLANE5=!1,e.CLIPPLANE6=!1,e.POINTSIZE=!1,e.FOG=!1,e.LOGARITHMICDEPTH=!1,e.FORCENORMALFORWARD=!1,e.SPECULARAA=!1,e.CLEARCOAT=!1,e.CLEARCOAT_DEFAULTIOR=!1,e.CLEARCOAT_TEXTURE=!1,e.CLEARCOAT_TEXTURE_ROUGHNESS=!1,e.CLEARCOAT_TEXTUREDIRECTUV=0,e.CLEARCOAT_TEXTURE_ROUGHNESSDIRECTUV=0,e.CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE=!1,e.CLEARCOAT_TEXTURE_ROUGHNESS_IDENTICAL=!1,e.CLEARCOAT_BUMP=!1,e.CLEARCOAT_BUMPDIRECTUV=0,e.CLEARCOAT_REMAP_F0=!0,e.CLEARCOAT_TINT=!1,e.CLEARCOAT_TINT_TEXTURE=!1,e.CLEARCOAT_TINT_TEXTUREDIRECTUV=0,e.ANISOTROPIC=!1,e.ANISOTROPIC_TEXTURE=!1,e.ANISOTROPIC_TEXTUREDIRECTUV=0,e.BRDF_V_HEIGHT_CORRELATED=!1,e.MS_BRDF_ENERGY_CONSERVATION=!1,e.SPECULAR_GLOSSINESS_ENERGY_CONSERVATION=!1,e.SHEEN=!1,e.SHEEN_TEXTURE=!1,e.SHEEN_TEXTURE_ROUGHNESS=!1,e.SHEEN_TEXTUREDIRECTUV=0,e.SHEEN_TEXTURE_ROUGHNESSDIRECTUV=0,e.SHEEN_LINKWITHALBEDO=!1,e.SHEEN_ROUGHNESS=!1,e.SHEEN_ALBEDOSCALING=!1,e.SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE=!1,e.SHEEN_TEXTURE_ROUGHNESS_IDENTICAL=!1,e.SUBSURFACE=!1,e.SS_REFRACTION=!1,e.SS_TRANSLUCENCY=!1,e.SS_SCATTERING=!1,e.SS_THICKNESSANDMASK_TEXTURE=!1,e.SS_THICKNESSANDMASK_TEXTUREDIRECTUV=0,e.SS_REFRACTIONMAP_3D=!1,e.SS_REFRACTIONMAP_OPPOSITEZ=!1,e.SS_LODINREFRACTIONALPHA=!1,e.SS_GAMMAREFRACTION=!1,e.SS_RGBDREFRACTION=!1,e.SS_LINEARSPECULARREFRACTION=!1,e.SS_LINKREFRACTIONTOTRANSPARENCY=!1,e.SS_ALBEDOFORREFRACTIONTINT=!1,e.SS_MASK_FROM_THICKNESS_TEXTURE=!1,e.SS_MASK_FROM_THICKNESS_TEXTURE_GLTF=!1,e.UNLIT=!1,e.DEBUGMODE=0,e.rebuild(),e}return 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M.a(1,1,1),i._reflectionColor=new M.a(1,1,1),i._emissiveColor=new M.a(0,0,0),i._microSurface=.9,i._useLightmapAsShadowmap=!1,i._useHorizonOcclusion=!0,i._useRadianceOcclusion=!0,i._useAlphaFromAlbedoTexture=!1,i._useSpecularOverAlpha=!0,i._useMicroSurfaceFromReflectivityMapAlpha=!1,i._useRoughnessFromMetallicTextureAlpha=!0,i._useRoughnessFromMetallicTextureGreen=!1,i._useMetallnessFromMetallicTextureBlue=!1,i._useAmbientOcclusionFromMetallicTextureRed=!1,i._useAmbientInGrayScale=!1,i._useAutoMicroSurfaceFromReflectivityMap=!1,i._lightFalloff=t.LIGHTFALLOFF_PHYSICAL,i._useRadianceOverAlpha=!0,i._useObjectSpaceNormalMap=!1,i._useParallax=!1,i._useParallaxOcclusion=!1,i._parallaxScaleBias=.05,i._disableLighting=!1,i._maxSimultaneousLights=4,i._invertNormalMapX=!1,i._invertNormalMapY=!1,i._twoSidedLighting=!1,i._alphaCutOff=.4,i._forceAlphaTest=!1,i._useAlphaFresnel=!1,i._useLinearAlphaFresnel=!1,i._environmentBRDFTexture=null,i._forceIrradianceInFragment=!1,i._realTimeFiltering=!1,i._realTimeFilteringQuality=h.a.TEXTURE_FILTERING_QUALITY_LOW,i._forceNormalForward=!1,i._enableSpecularAntiAliasing=!1,i._imageProcessingObserver=null,i._renderTargets=new fi.a(16),i._globalAmbientColor=new M.a(0,0,0),i._useLogarithmicDepth=!1,i._unlit=!1,i._debugMode=0,i.debugMode=0,i.debugLimit=-1,i.debugFactor=1,i.clearCoat=new Ar(i._markAllSubMeshesAsTexturesDirty.bind(i)),i.anisotropy=new Pr(i._markAllSubMeshesAsTexturesDirty.bind(i)),i.brdf=new Rp(i._markAllSubMeshesAsMiscDirty.bind(i)),i.sheen=new co(i._markAllSubMeshesAsTexturesDirty.bind(i)),i.detailMap=new ta.a(i._markAllSubMeshesAsTexturesDirty.bind(i)),i._rebuildInParallel=!1,i._attachImageProcessingConfiguration(null),i.getRenderTargetTextures=function(){return i._renderTargets.reset(),ht.a.ReflectionTextureEnabled&&i._reflectionTexture&&i._reflectionTexture.isRenderTarget&&i._renderTargets.push(i._reflectionTexture),i.subSurface.fillRenderTargetTextures(i._renderTargets),i._renderTargets},i._environmentBRDFTexture=ea.GetEnvironmentBRDFTexture(n),i.subSurface=new lo(i._markAllSubMeshesAsTexturesDirty.bind(i),i._markScenePrePassDirty.bind(i),n),i.prePassConfiguration=new Ns.a,i}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"realTimeFiltering",{get:function(){return this._realTimeFiltering},set:function(e){this._realTimeFiltering=e,this.markAsDirty(h.a.MATERIAL_TextureDirtyFlag)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"realTimeFilteringQuality",{get:function(){return this._realTimeFilteringQuality},set:function(e){this._realTimeFilteringQuality=e,this.markAsDirty(h.a.MATERIAL_TextureDirtyFlag)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"canRenderToMRT",{get:function(){return!0},enumerable:!1,configurable:!0}),t.prototype._attachImageProcessingConfiguration=function(e){var n=this;e!==this._imageProcessingConfiguration&&(this._imageProcessingConfiguration&&this._imageProcessingObserver&&this._imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingObserver),this._imageProcessingConfiguration=e||this.getScene().imageProcessingConfiguration,this._imageProcessingConfiguration&&(this._imageProcessingObserver=this._imageProcessingConfiguration.onUpdateParameters.add(function(){n._markAllSubMeshesAsImageProcessingDirty()})))},Object.defineProperty(t.prototype,"hasRenderTargetTextures",{get:function(){return!!(ht.a.ReflectionTextureEnabled&&this._reflectionTexture&&this._reflectionTexture.isRenderTarget)||this.subSurface.hasRenderTargetTextures()},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"PBRBaseMaterial"},Object.defineProperty(t.prototype,"useLogarithmicDepth",{get:function(){return this._useLogarithmicDepth},set:function(e){this._useLogarithmicDepth=e&&this.getScene().getEngine().getCaps().fragmentDepthSupported},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"_disableAlphaBlending",{get:function(){return this.subSurface.disableAlphaBlending||this._transparencyMode===t.PBRMATERIAL_OPAQUE||this._transparencyMode===t.PBRMATERIAL_ALPHATEST},enumerable:!1,configurable:!0}),t.prototype.needAlphaBlending=function(){return!this._disableAlphaBlending&&(this.alpha<1||this._opacityTexture!=null||this._shouldUseAlphaFromAlbedoTexture())},t.prototype.needAlphaTesting=function(){return!!this._forceAlphaTest||!this.subSurface.disableAlphaBlending&&this._hasAlphaChannel()&&(this._transparencyMode==null||this._transparencyMode===t.PBRMATERIAL_ALPHATEST)},t.prototype._shouldUseAlphaFromAlbedoTexture=function(){return this._albedoTexture!=null&&this._albedoTexture.hasAlpha&&this._useAlphaFromAlbedoTexture&&this._transparencyMode!==t.PBRMATERIAL_OPAQUE},t.prototype._hasAlphaChannel=function(){return this._albedoTexture!=null&&this._albedoTexture.hasAlpha||this._opacityTexture!=null},t.prototype.getAlphaTestTexture=function(){return this._albedoTexture},t.prototype.isReadyForSubMesh=function(e,n,i){if(n.effect&&this.isFrozen&&n.effect._wasPreviouslyReady)return!0;n._materialDefines||(n._materialDefines=new ws);var o=n._materialDefines;if(this._isReadyForSubMesh(n))return!0;var a=this.getScene(),s=a.getEngine();if(o._areTexturesDirty&&a.texturesEnabled){if(this._albedoTexture&&ht.a.DiffuseTextureEnabled&&!this._albedoTexture.isReadyOrNotBlocking()||this._ambientTexture&&ht.a.AmbientTextureEnabled&&!this._ambientTexture.isReadyOrNotBlocking()||this._opacityTexture&&ht.a.OpacityTextureEnabled&&!this._opacityTexture.isReadyOrNotBlocking())return!1;var d=this._getReflectionTexture();if(d&&ht.a.ReflectionTextureEnabled&&(!d.isReadyOrNotBlocking()||d.irradianceTexture&&!d.irradianceTexture.isReadyOrNotBlocking())||this._lightmapTexture&&ht.a.LightmapTextureEnabled&&!this._lightmapTexture.isReadyOrNotBlocking()||this._emissiveTexture&&ht.a.EmissiveTextureEnabled&&!this._emissiveTexture.isReadyOrNotBlocking())return!1;if(ht.a.SpecularTextureEnabled){if(this._metallicTexture){if(!this._metallicTexture.isReadyOrNotBlocking())return!1}else if(this._reflectivityTexture&&!this._reflectivityTexture.isReadyOrNotBlocking())return!1;if(this._metallicReflectanceTexture&&!this._metallicReflectanceTexture.isReadyOrNotBlocking()||this._microSurfaceTexture&&!this._microSurfaceTexture.isReadyOrNotBlocking())return!1}if(s.getCaps().standardDerivatives&&this._bumpTexture&&ht.a.BumpTextureEnabled&&!this._disableBumpMap&&!this._bumpTexture.isReady()||this._environmentBRDFTexture&&ht.a.ReflectionTextureEnabled&&!this._environmentBRDFTexture.isReady())return!1}if(!(this.subSurface.isReadyForSubMesh(o,a)&&this.clearCoat.isReadyForSubMesh(o,a,s,this._disableBumpMap)&&this.sheen.isReadyForSubMesh(o,a)&&this.anisotropy.isReadyForSubMesh(o,a)&&this.detailMap.isReadyForSubMesh(o,a))||o._areImageProcessingDirty&&this._imageProcessingConfiguration&&!this._imageProcessingConfiguration.isReady())return!1;s.getCaps().standardDerivatives||e.isVerticesDataPresent(Oe.b.NormalKind)||(e.createNormals(!0),l.a.Warn("PBRMaterial: Normals have been created for the mesh: "+e.name));var p=n.effect,b=o._areLightsDisposed,P=this._prepareEffect(e,o,this.onCompiled,this.onError,i,null,n.getRenderingMesh().hasThinInstances);if(P)if(this._onEffectCreatedObservable&&(Cr.effect=P,Cr.subMesh=n,this._onEffectCreatedObservable.notifyObservers(Cr)),this.allowShaderHotSwapping&&p&&!P.isReady()){if(P=p,this._rebuildInParallel=!0,o.markAsUnprocessed(),b)return o._areLightsDisposed=!0,!1}else this._rebuildInParallel=!1,a.resetCachedMaterial(),n.setEffect(P,o),this.buildUniformLayout();return!(!n.effect||!n.effect.isReady())&&(o._renderId=a.getRenderId(),n.effect._wasPreviouslyReady=!0,!0)},t.prototype.isMetallicWorkflow=function(){return!(this._metallic==null&&this._roughness==null&&!this._metallicTexture)},t.prototype._prepareEffect=function(e,n,i,o,a,s,d){if(i===void 0&&(i=null),o===void 0&&(o=null),a===void 0&&(a=null),s===void 0&&(s=null),this._prepareDefines(e,n,a,s,d),!n.isDirty)return null;n.markAsProcessed();var p=this.getScene().getEngine(),b=new Sr.a,P=0;n.USESPHERICALINVERTEX&&b.addFallback(P++,"USESPHERICALINVERTEX"),n.FOG&&b.addFallback(P,"FOG"),n.SPECULARAA&&b.addFallback(P,"SPECULARAA"),n.POINTSIZE&&b.addFallback(P,"POINTSIZE"),n.LOGARITHMICDEPTH&&b.addFallback(P,"LOGARITHMICDEPTH"),n.PARALLAX&&b.addFallback(P,"PARALLAX"),n.PARALLAXOCCLUSION&&b.addFallback(P++,"PARALLAXOCCLUSION"),P=Pr.AddFallbacks(n,b,P),P=Pr.AddFallbacks(n,b,P),P=lo.AddFallbacks(n,b,P),P=co.AddFallbacks(n,b,P),n.ENVIRONMENTBRDF&&b.addFallback(P++,"ENVIRONMENTBRDF"),n.TANGENT&&b.addFallback(P++,"TANGENT"),n.BUMP&&b.addFallback(P++,"BUMP"),P=et.a.HandleFallbacksForShadows(n,b,this._maxSimultaneousLights,P++),n.SPECULARTERM&&b.addFallback(P++,"SPECULARTERM"),n.USESPHERICALFROMREFLECTIONMAP&&b.addFallback(P++,"USESPHERICALFROMREFLECTIONMAP"),n.USEIRRADIANCEMAP&&b.addFallback(P++,"USEIRRADIANCEMAP"),n.LIGHTMAP&&b.addFallback(P++,"LIGHTMAP"),n.NORMAL&&b.addFallback(P++,"NORMAL"),n.AMBIENT&&b.addFallback(P++,"AMBIENT"),n.EMISSIVE&&b.addFallback(P++,"EMISSIVE"),n.VERTEXCOLOR&&b.addFallback(P++,"VERTEXCOLOR"),n.MORPHTARGETS&&b.addFallback(P++,"MORPHTARGETS"),n.MULTIVIEW&&b.addFallback(0,"MULTIVIEW");var O=[Oe.b.PositionKind];n.NORMAL&&O.push(Oe.b.NormalKind),n.TANGENT&&O.push(Oe.b.TangentKind),n.UV1&&O.push(Oe.b.UVKind),n.UV2&&O.push(Oe.b.UV2Kind),n.VERTEXCOLOR&&O.push(Oe.b.ColorKind),et.a.PrepareAttributesForBones(O,e,n,b),et.a.PrepareAttributesForInstances(O,n),et.a.PrepareAttributesForMorphTargets(O,e,n);var B="pbr",F=["world","view","viewProjection","vEyePosition","vLightsType","vAmbientColor","vAlbedoColor","vReflectivityColor","vMetallicReflectanceFactors","vEmissiveColor","visibility","vReflectionColor","vFogInfos","vFogColor","pointSize","vAlbedoInfos","vAmbientInfos","vOpacityInfos","vReflectionInfos","vReflectionPosition","vReflectionSize","vEmissiveInfos","vReflectivityInfos","vReflectionFilteringInfo","vMetallicReflectanceInfos","vMicroSurfaceSamplerInfos","vBumpInfos","vLightmapInfos","mBones","vClipPlane","vClipPlane2","vClipPlane3","vClipPlane4","vClipPlane5","vClipPlane6","albedoMatrix","ambientMatrix","opacityMatrix","reflectionMatrix","emissiveMatrix","reflectivityMatrix","normalMatrix","microSurfaceSamplerMatrix","bumpMatrix","lightmapMatrix","metallicReflectanceMatrix","vLightingIntensity","logarithmicDepthConstant","vSphericalX","vSphericalY","vSphericalZ","vSphericalXX_ZZ","vSphericalYY_ZZ","vSphericalZZ","vSphericalXY","vSphericalYZ","vSphericalZX","vSphericalL00","vSphericalL1_1","vSphericalL10","vSphericalL11","vSphericalL2_2","vSphericalL2_1","vSphericalL20","vSphericalL21","vSphericalL22","vReflectionMicrosurfaceInfos","vTangentSpaceParams","boneTextureWidth","vDebugMode"],z=["albedoSampler","reflectivitySampler","ambientSampler","emissiveSampler","bumpSampler","lightmapSampler","opacitySampler","reflectionSampler","reflectionSamplerLow","reflectionSamplerHigh","irradianceSampler","microSurfaceSampler","environmentBrdfSampler","boneSampler","metallicReflectanceSampler"],J=["Material","Scene"];ta.a.AddUniforms(F),ta.a.AddSamplers(z),lo.AddUniforms(F),lo.AddSamplers(z),Ar.AddUniforms(F),Ar.AddSamplers(z),Pr.AddUniforms(F),Pr.AddSamplers(z),co.AddUniforms(F),co.AddSamplers(z),Ns.a.AddUniforms(F),Ns.a.AddSamplers(F),yn.a&&(yn.a.PrepareUniforms(F,n),yn.a.PrepareSamplers(z,n)),et.a.PrepareUniformsAndSamplersList({uniformsNames:F,uniformBuffersNames:J,samplers:z,defines:n,maxSimultaneousLights:this._maxSimultaneousLights});var ie={};this.customShaderNameResolve&&(B=this.customShaderNameResolve(B,F,J,z,n,O,ie));var se=n.toString();return p.createEffect(B,{attributes:O,uniformsNames:F,uniformBuffersNames:J,samplers:z,defines:se,fallbacks:b,onCompiled:i,onError:o,indexParameters:{maxSimultaneousLights:this._maxSimultaneousLights,maxSimultaneousMorphTargets:n.NUM_MORPH_INFLUENCERS},processFinalCode:ie.processFinalCode,multiTarget:n.PREPASS},p)},t.prototype._prepareDefines=function(e,n,i,o,a){i===void 0&&(i=null),o===void 0&&(o=null),a===void 0&&(a=!1);var s=this.getScene(),d=s.getEngine();if(et.a.PrepareDefinesForLights(s,e,n,!0,this._maxSimultaneousLights,this._disableLighting),n._needNormals=!0,et.a.PrepareDefinesForMultiview(s,n),et.a.PrepareDefinesForPrePass(s,n,this.canRenderToMRT),n.METALLICWORKFLOW=this.isMetallicWorkflow(),n._areTexturesDirty){if(n._needUVs=!1,s.texturesEnabled){s.getEngine().getCaps().textureLOD&&(n.LODBASEDMICROSFURACE=!0),this._albedoTexture&&ht.a.DiffuseTextureEnabled?(et.a.PrepareDefinesForMergedUV(this._albedoTexture,n,"ALBEDO"),n.GAMMAALBEDO=this._albedoTexture.gammaSpace):n.ALBEDO=!1,this._ambientTexture&&ht.a.AmbientTextureEnabled?(et.a.PrepareDefinesForMergedUV(this._ambientTexture,n,"AMBIENT"),n.AMBIENTINGRAYSCALE=this._useAmbientInGrayScale):n.AMBIENT=!1,this._opacityTexture&&ht.a.OpacityTextureEnabled?(et.a.PrepareDefinesForMergedUV(this._opacityTexture,n,"OPACITY"),n.OPACITYRGB=this._opacityTexture.getAlphaFromRGB):n.OPACITY=!1;var p=this._getReflectionTexture();if(p&&ht.a.ReflectionTextureEnabled){switch(n.REFLECTION=!0,n.GAMMAREFLECTION=p.gammaSpace,n.RGBDREFLECTION=p.isRGBD,n.REFLECTIONMAP_OPPOSITEZ=this.getScene().useRightHandedSystem?!p.invertZ:p.invertZ,n.LODINREFLECTIONALPHA=p.lodLevelInAlpha,n.LINEARSPECULARREFLECTION=p.linearSpecularLOD,this.realTimeFiltering&&this.realTimeFilteringQuality>0?(n.NUM_SAMPLES=""+this.realTimeFilteringQuality,d.webGLVersion>1&&(n.NUM_SAMPLES=n.NUM_SAMPLES+"u"),n.REALTIME_FILTERING=!0):n.REALTIME_FILTERING=!1,p.coordinatesMode===we.a.INVCUBIC_MODE&&(n.INVERTCUBICMAP=!0),n.REFLECTIONMAP_3D=p.isCube,n.REFLECTIONMAP_CUBIC=!1,n.REFLECTIONMAP_EXPLICIT=!1,n.REFLECTIONMAP_PLANAR=!1,n.REFLECTIONMAP_PROJECTION=!1,n.REFLECTIONMAP_SKYBOX=!1,n.REFLECTIONMAP_SPHERICAL=!1,n.REFLECTIONMAP_EQUIRECTANGULAR=!1,n.REFLECTIONMAP_EQUIRECTANGULAR_FIXED=!1,n.REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED=!1,p.coordinatesMode){case we.a.EXPLICIT_MODE:n.REFLECTIONMAP_EXPLICIT=!0;break;case we.a.PLANAR_MODE:n.REFLECTIONMAP_PLANAR=!0;break;case we.a.PROJECTION_MODE:n.REFLECTIONMAP_PROJECTION=!0;break;case we.a.SKYBOX_MODE:n.REFLECTIONMAP_SKYBOX=!0;break;case we.a.SPHERICAL_MODE:n.REFLECTIONMAP_SPHERICAL=!0;break;case we.a.EQUIRECTANGULAR_MODE:n.REFLECTIONMAP_EQUIRECTANGULAR=!0;break;case we.a.FIXED_EQUIRECTANGULAR_MODE:n.REFLECTIONMAP_EQUIRECTANGULAR_FIXED=!0;break;case we.a.FIXED_EQUIRECTANGULAR_MIRRORED_MODE:n.REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED=!0;break;case we.a.CUBIC_MODE:case we.a.INVCUBIC_MODE:default:n.REFLECTIONMAP_CUBIC=!0,n.USE_LOCAL_REFLECTIONMAP_CUBIC=!!p.boundingBoxSize}p.coordinatesMode!==we.a.SKYBOX_MODE&&(p.irradianceTexture?(n.USEIRRADIANCEMAP=!0,n.USESPHERICALFROMREFLECTIONMAP=!1):p.isCube&&(n.USESPHERICALFROMREFLECTIONMAP=!0,n.USEIRRADIANCEMAP=!1,this._forceIrradianceInFragment||this.realTimeFiltering||s.getEngine().getCaps().maxVaryingVectors<=8?n.USESPHERICALINVERTEX=!1:n.USESPHERICALINVERTEX=!0))}else n.REFLECTION=!1,n.REFLECTIONMAP_3D=!1,n.REFLECTIONMAP_SPHERICAL=!1,n.REFLECTIONMAP_PLANAR=!1,n.REFLECTIONMAP_CUBIC=!1,n.USE_LOCAL_REFLECTIONMAP_CUBIC=!1,n.REFLECTIONMAP_PROJECTION=!1,n.REFLECTIONMAP_SKYBOX=!1,n.REFLECTIONMAP_EXPLICIT=!1,n.REFLECTIONMAP_EQUIRECTANGULAR=!1,n.REFLECTIONMAP_EQUIRECTANGULAR_FIXED=!1,n.REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED=!1,n.INVERTCUBICMAP=!1,n.USESPHERICALFROMREFLECTIONMAP=!1,n.USEIRRADIANCEMAP=!1,n.USESPHERICALINVERTEX=!1,n.REFLECTIONMAP_OPPOSITEZ=!1,n.LODINREFLECTIONALPHA=!1,n.GAMMAREFLECTION=!1,n.RGBDREFLECTION=!1,n.LINEARSPECULARREFLECTION=!1;this._lightmapTexture&&ht.a.LightmapTextureEnabled?(et.a.PrepareDefinesForMergedUV(this._lightmapTexture,n,"LIGHTMAP"),n.USELIGHTMAPASSHADOWMAP=this._useLightmapAsShadowmap,n.GAMMALIGHTMAP=this._lightmapTexture.gammaSpace,n.RGBDLIGHTMAP=this._lightmapTexture.isRGBD):n.LIGHTMAP=!1,this._emissiveTexture&&ht.a.EmissiveTextureEnabled?et.a.PrepareDefinesForMergedUV(this._emissiveTexture,n,"EMISSIVE"):n.EMISSIVE=!1,ht.a.SpecularTextureEnabled?(this._metallicTexture?(et.a.PrepareDefinesForMergedUV(this._metallicTexture,n,"REFLECTIVITY"),n.ROUGHNESSSTOREINMETALMAPALPHA=this._useRoughnessFromMetallicTextureAlpha,n.ROUGHNESSSTOREINMETALMAPGREEN=!this._useRoughnessFromMetallicTextureAlpha&&this._useRoughnessFromMetallicTextureGreen,n.METALLNESSSTOREINMETALMAPBLUE=this._useMetallnessFromMetallicTextureBlue,n.AOSTOREINMETALMAPRED=this._useAmbientOcclusionFromMetallicTextureRed):this._reflectivityTexture?(et.a.PrepareDefinesForMergedUV(this._reflectivityTexture,n,"REFLECTIVITY"),n.MICROSURFACEFROMREFLECTIVITYMAP=this._useMicroSurfaceFromReflectivityMapAlpha,n.MICROSURFACEAUTOMATIC=this._useAutoMicroSurfaceFromReflectivityMap):n.REFLECTIVITY=!1,this._metallicReflectanceTexture?et.a.PrepareDefinesForMergedUV(this._metallicReflectanceTexture,n,"METALLIC_REFLECTANCE"):n.METALLIC_REFLECTANCE=!1,this._microSurfaceTexture?et.a.PrepareDefinesForMergedUV(this._microSurfaceTexture,n,"MICROSURFACEMAP"):n.MICROSURFACEMAP=!1):(n.REFLECTIVITY=!1,n.MICROSURFACEMAP=!1),s.getEngine().getCaps().standardDerivatives&&this._bumpTexture&&ht.a.BumpTextureEnabled&&!this._disableBumpMap?(et.a.PrepareDefinesForMergedUV(this._bumpTexture,n,"BUMP"),this._useParallax&&this._albedoTexture&&ht.a.DiffuseTextureEnabled?(n.PARALLAX=!0,n.PARALLAXOCCLUSION=!!this._useParallaxOcclusion):n.PARALLAX=!1,n.OBJECTSPACE_NORMALMAP=this._useObjectSpaceNormalMap):n.BUMP=!1,this._environmentBRDFTexture&&ht.a.ReflectionTextureEnabled?(n.ENVIRONMENTBRDF=!0,n.ENVIRONMENTBRDF_RGBD=this._environmentBRDFTexture.isRGBD):(n.ENVIRONMENTBRDF=!1,n.ENVIRONMENTBRDF_RGBD=!1),this._shouldUseAlphaFromAlbedoTexture()?n.ALPHAFROMALBEDO=!0:n.ALPHAFROMALBEDO=!1}n.SPECULAROVERALPHA=this._useSpecularOverAlpha,this._lightFalloff===t.LIGHTFALLOFF_STANDARD?(n.USEPHYSICALLIGHTFALLOFF=!1,n.USEGLTFLIGHTFALLOFF=!1):this._lightFalloff===t.LIGHTFALLOFF_GLTF?(n.USEPHYSICALLIGHTFALLOFF=!1,n.USEGLTFLIGHTFALLOFF=!0):(n.USEPHYSICALLIGHTFALLOFF=!0,n.USEGLTFLIGHTFALLOFF=!1),n.RADIANCEOVERALPHA=this._useRadianceOverAlpha,!this.backFaceCulling&&this._twoSidedLighting?n.TWOSIDEDLIGHTING=!0:n.TWOSIDEDLIGHTING=!1,n.SPECULARAA=s.getEngine().getCaps().standardDerivatives&&this._enableSpecularAntiAliasing}(n._areTexturesDirty||n._areMiscDirty)&&(n.ALPHATESTVALUE=this._alphaCutOff+(this._alphaCutOff%1==0?".":""),n.PREMULTIPLYALPHA=this.alphaMode===h.a.ALPHA_PREMULTIPLIED||this.alphaMode===h.a.ALPHA_PREMULTIPLIED_PORTERDUFF,n.ALPHABLEND=this.needAlphaBlendingForMesh(e),n.ALPHAFRESNEL=this._useAlphaFresnel||this._useLinearAlphaFresnel,n.LINEARALPHAFRESNEL=this._useLinearAlphaFresnel),n._areImageProcessingDirty&&this._imageProcessingConfiguration&&this._imageProcessingConfiguration.prepareDefines(n),n.FORCENORMALFORWARD=this._forceNormalForward,n.RADIANCEOCCLUSION=this._useRadianceOcclusion,n.HORIZONOCCLUSION=this._useHorizonOcclusion,n._areMiscDirty&&(et.a.PrepareDefinesForMisc(e,s,this._useLogarithmicDepth,this.pointsCloud,this.fogEnabled,this._shouldTurnAlphaTestOn(e)||this._forceAlphaTest,n),n.UNLIT=this._unlit||(this.pointsCloud||this.wireframe)&&!e.isVerticesDataPresent(Oe.b.NormalKind),n.DEBUGMODE=this._debugMode),this.detailMap.prepareDefines(n,s),this.subSurface.prepareDefines(n,s),this.clearCoat.prepareDefines(n,s),this.anisotropy.prepareDefines(n,e,s),this.brdf.prepareDefines(n),this.sheen.prepareDefines(n,s),et.a.PrepareDefinesForFrameBoundValues(s,d,n,!!i,o,a),et.a.PrepareDefinesForAttributes(e,n,!0,!0,!0,this._transparencyMode!==t.PBRMATERIAL_OPAQUE)},t.prototype.forceCompilation=function(e,n,i){var o=this,a=Object(c.a)({clipPlane:!1,useInstances:!1},i),s=new ws,d=this._prepareEffect(e,s,void 0,void 0,a.useInstances,a.clipPlane,e.hasThinInstances);this._onEffectCreatedObservable&&(Cr.effect=d,Cr.subMesh=null,this._onEffectCreatedObservable.notifyObservers(Cr)),d.isReady()?n&&n(this):d.onCompileObservable.add(function(){n&&n(o)})},t.prototype.buildUniformLayout=function(){var e=this._uniformBuffer;e.addUniform("vAlbedoInfos",2),e.addUniform("vAmbientInfos",4),e.addUniform("vOpacityInfos",2),e.addUniform("vEmissiveInfos",2),e.addUniform("vLightmapInfos",2),e.addUniform("vReflectivityInfos",3),e.addUniform("vMicroSurfaceSamplerInfos",2),e.addUniform("vReflectionInfos",2),e.addUniform("vReflectionFilteringInfo",2),e.addUniform("vReflectionPosition",3),e.addUniform("vReflectionSize",3),e.addUniform("vBumpInfos",3),e.addUniform("albedoMatrix",16),e.addUniform("ambientMatrix",16),e.addUniform("opacityMatrix",16),e.addUniform("emissiveMatrix",16),e.addUniform("lightmapMatrix",16),e.addUniform("reflectivityMatrix",16),e.addUniform("microSurfaceSamplerMatrix",16),e.addUniform("bumpMatrix",16),e.addUniform("vTangentSpaceParams",2),e.addUniform("reflectionMatrix",16),e.addUniform("vReflectionColor",3),e.addUniform("vAlbedoColor",4),e.addUniform("vLightingIntensity",4),e.addUniform("vReflectionMicrosurfaceInfos",3),e.addUniform("pointSize",1),e.addUniform("vReflectivityColor",4),e.addUniform("vEmissiveColor",3),e.addUniform("visibility",1),e.addUniform("vMetallicReflectanceFactors",4),e.addUniform("vMetallicReflectanceInfos",2),e.addUniform("metallicReflectanceMatrix",16),Ar.PrepareUniformBuffer(e),Pr.PrepareUniformBuffer(e),co.PrepareUniformBuffer(e),lo.PrepareUniformBuffer(e),ta.a.PrepareUniformBuffer(e),e.create()},t.prototype.unbind=function(){if(this._activeEffect){var e=!1;this._reflectionTexture&&this._reflectionTexture.isRenderTarget&&(this._activeEffect.setTexture("reflection2DSampler",null),e=!0),this.subSurface.unbind(this._activeEffect)&&(e=!0),e&&this._markAllSubMeshesAsTexturesDirty()}r.prototype.unbind.call(this)},t.prototype.bindForSubMesh=function(e,n,i){var o=this.getScene(),a=i._materialDefines;if(a){var s=i.effect;if(s){this._activeEffect=s,a.INSTANCES&&!a.THIN_INSTANCES||this.bindOnlyWorldMatrix(e),this.prePassConfiguration.bindForSubMesh(this._activeEffect,o,n,e,this.isFrozen),a.OBJECTSPACE_NORMALMAP&&(e.toNormalMatrix(this._normalMatrix),this.bindOnlyNormalMatrix(this._normalMatrix));var d=this._mustRebind(o,s,n.visibility);et.a.BindBonesParameters(n,this._activeEffect,this.prePassConfiguration);var p=null,b=this._uniformBuffer;if(d){var P=o.getEngine();if(b.bindToEffect(s,"Material"),this.bindViewProjection(s),p=this._getReflectionTexture(),!b.useUbo||!this.isFrozen||!b.isSync){if(o.texturesEnabled){if(this._albedoTexture&&ht.a.DiffuseTextureEnabled&&(b.updateFloat2("vAlbedoInfos",this._albedoTexture.coordinatesIndex,this._albedoTexture.level),et.a.BindTextureMatrix(this._albedoTexture,b,"albedo")),this._ambientTexture&&ht.a.AmbientTextureEnabled&&(b.updateFloat4("vAmbientInfos",this._ambientTexture.coordinatesIndex,this._ambientTexture.level,this._ambientTextureStrength,this._ambientTextureImpactOnAnalyticalLights),et.a.BindTextureMatrix(this._ambientTexture,b,"ambient")),this._opacityTexture&&ht.a.OpacityTextureEnabled&&(b.updateFloat2("vOpacityInfos",this._opacityTexture.coordinatesIndex,this._opacityTexture.level),et.a.BindTextureMatrix(this._opacityTexture,b,"opacity")),p&&ht.a.ReflectionTextureEnabled){if(b.updateMatrix("reflectionMatrix",p.getReflectionTextureMatrix()),b.updateFloat2("vReflectionInfos",p.level,0),p.boundingBoxSize){var O=p;b.updateVector3("vReflectionPosition",O.boundingBoxPosition),b.updateVector3("vReflectionSize",O.boundingBoxSize)}if(this.realTimeFiltering){var B=p.getSize().width;b.updateFloat2("vReflectionFilteringInfo",B,$.a.Log2(B))}if(!a.USEIRRADIANCEMAP){var F=p.sphericalPolynomial;if(a.USESPHERICALFROMREFLECTIONMAP&&F)if(a.SPHERICAL_HARMONICS){var z=F.preScaledHarmonics;this._activeEffect.setVector3("vSphericalL00",z.l00),this._activeEffect.setVector3("vSphericalL1_1",z.l1_1),this._activeEffect.setVector3("vSphericalL10",z.l10),this._activeEffect.setVector3("vSphericalL11",z.l11),this._activeEffect.setVector3("vSphericalL2_2",z.l2_2),this._activeEffect.setVector3("vSphericalL2_1",z.l2_1),this._activeEffect.setVector3("vSphericalL20",z.l20),this._activeEffect.setVector3("vSphericalL21",z.l21),this._activeEffect.setVector3("vSphericalL22",z.l22)}else this._activeEffect.setFloat3("vSphericalX",F.x.x,F.x.y,F.x.z),this._activeEffect.setFloat3("vSphericalY",F.y.x,F.y.y,F.y.z),this._activeEffect.setFloat3("vSphericalZ",F.z.x,F.z.y,F.z.z),this._activeEffect.setFloat3("vSphericalXX_ZZ",F.xx.x-F.zz.x,F.xx.y-F.zz.y,F.xx.z-F.zz.z),this._activeEffect.setFloat3("vSphericalYY_ZZ",F.yy.x-F.zz.x,F.yy.y-F.zz.y,F.yy.z-F.zz.z),this._activeEffect.setFloat3("vSphericalZZ",F.zz.x,F.zz.y,F.zz.z),this._activeEffect.setFloat3("vSphericalXY",F.xy.x,F.xy.y,F.xy.z),this._activeEffect.setFloat3("vSphericalYZ",F.yz.x,F.yz.y,F.yz.z),this._activeEffect.setFloat3("vSphericalZX",F.zx.x,F.zx.y,F.zx.z)}b.updateFloat3("vReflectionMicrosurfaceInfos",p.getSize().width,p.lodGenerationScale,p.lodGenerationOffset)}this._emissiveTexture&&ht.a.EmissiveTextureEnabled&&(b.updateFloat2("vEmissiveInfos",this._emissiveTexture.coordinatesIndex,this._emissiveTexture.level),et.a.BindTextureMatrix(this._emissiveTexture,b,"emissive")),this._lightmapTexture&&ht.a.LightmapTextureEnabled&&(b.updateFloat2("vLightmapInfos",this._lightmapTexture.coordinatesIndex,this._lightmapTexture.level),et.a.BindTextureMatrix(this._lightmapTexture,b,"lightmap")),ht.a.SpecularTextureEnabled&&(this._metallicTexture?(b.updateFloat3("vReflectivityInfos",this._metallicTexture.coordinatesIndex,this._metallicTexture.level,this._ambientTextureStrength),et.a.BindTextureMatrix(this._metallicTexture,b,"reflectivity")):this._reflectivityTexture&&(b.updateFloat3("vReflectivityInfos",this._reflectivityTexture.coordinatesIndex,this._reflectivityTexture.level,1),et.a.BindTextureMatrix(this._reflectivityTexture,b,"reflectivity")),this._metallicReflectanceTexture&&(b.updateFloat2("vMetallicReflectanceInfos",this._metallicReflectanceTexture.coordinatesIndex,this._metallicReflectanceTexture.level),et.a.BindTextureMatrix(this._metallicReflectanceTexture,b,"metallicReflectance")),this._microSurfaceTexture&&(b.updateFloat2("vMicroSurfaceSamplerInfos",this._microSurfaceTexture.coordinatesIndex,this._microSurfaceTexture.level),et.a.BindTextureMatrix(this._microSurfaceTexture,b,"microSurfaceSampler"))),this._bumpTexture&&P.getCaps().standardDerivatives&&ht.a.BumpTextureEnabled&&!this._disableBumpMap&&(b.updateFloat3("vBumpInfos",this._bumpTexture.coordinatesIndex,this._bumpTexture.level,this._parallaxScaleBias),et.a.BindTextureMatrix(this._bumpTexture,b,"bump"),o._mirroredCameraPosition?b.updateFloat2("vTangentSpaceParams",this._invertNormalMapX?1:-1,this._invertNormalMapY?1:-1):b.updateFloat2("vTangentSpaceParams",this._invertNormalMapX?-1:1,this._invertNormalMapY?-1:1))}if(this.pointsCloud&&b.updateFloat("pointSize",this.pointSize),a.METALLICWORKFLOW){M.c.Color3[0].r=this._metallic===void 0||this._metallic===null?1:this._metallic,M.c.Color3[0].g=this._roughness===void 0||this._roughness===null?1:this._roughness,b.updateColor4("vReflectivityColor",M.c.Color3[0],1);var J=this.subSurface.indexOfRefraction,ie=Math.pow((J-1)/(J+1),2);this._metallicReflectanceColor.scaleToRef(ie*this._metallicF0Factor,M.c.Color3[0]);var se=this._metallicF0Factor;b.updateColor4("vMetallicReflectanceFactors",M.c.Color3[0],se)}else b.updateColor4("vReflectivityColor",this._reflectivityColor,this._microSurface);b.updateColor3("vEmissiveColor",ht.a.EmissiveTextureEnabled?this._emissiveColor:M.a.BlackReadOnly),b.updateColor3("vReflectionColor",this._reflectionColor),!a.SS_REFRACTION&&this.subSurface.linkRefractionWithTransparency?b.updateColor4("vAlbedoColor",this._albedoColor,1):b.updateColor4("vAlbedoColor",this._albedoColor,this.alpha),this._lightingInfos.x=this._directIntensity,this._lightingInfos.y=this._emissiveIntensity,this._lightingInfos.z=this._environmentIntensity*o.environmentIntensity,this._lightingInfos.w=this._specularIntensity,b.updateVector4("vLightingIntensity",this._lightingInfos)}b.updateFloat("visibility",n.visibility),o.texturesEnabled&&(this._albedoTexture&&ht.a.DiffuseTextureEnabled&&b.setTexture("albedoSampler",this._albedoTexture),this._ambientTexture&&ht.a.AmbientTextureEnabled&&b.setTexture("ambientSampler",this._ambientTexture),this._opacityTexture&&ht.a.OpacityTextureEnabled&&b.setTexture("opacitySampler",this._opacityTexture),p&&ht.a.ReflectionTextureEnabled&&(a.LODBASEDMICROSFURACE?b.setTexture("reflectionSampler",p):(b.setTexture("reflectionSampler",p._lodTextureMid||p),b.setTexture("reflectionSamplerLow",p._lodTextureLow||p),b.setTexture("reflectionSamplerHigh",p._lodTextureHigh||p)),a.USEIRRADIANCEMAP&&b.setTexture("irradianceSampler",p.irradianceTexture)),a.ENVIRONMENTBRDF&&b.setTexture("environmentBrdfSampler",this._environmentBRDFTexture),this._emissiveTexture&&ht.a.EmissiveTextureEnabled&&b.setTexture("emissiveSampler",this._emissiveTexture),this._lightmapTexture&&ht.a.LightmapTextureEnabled&&b.setTexture("lightmapSampler",this._lightmapTexture),ht.a.SpecularTextureEnabled&&(this._metallicTexture?b.setTexture("reflectivitySampler",this._metallicTexture):this._reflectivityTexture&&b.setTexture("reflectivitySampler",this._reflectivityTexture),this._metallicReflectanceTexture&&b.setTexture("metallicReflectanceSampler",this._metallicReflectanceTexture),this._microSurfaceTexture&&b.setTexture("microSurfaceSampler",this._microSurfaceTexture)),this._bumpTexture&&P.getCaps().standardDerivatives&&ht.a.BumpTextureEnabled&&!this._disableBumpMap&&b.setTexture("bumpSampler",this._bumpTexture)),this.detailMap.bindForSubMesh(b,o,this.isFrozen),this.subSurface.bindForSubMesh(b,o,P,this.isFrozen,a.LODBASEDMICROSFURACE,this.realTimeFiltering),this.clearCoat.bindForSubMesh(b,o,P,this._disableBumpMap,this.isFrozen,this._invertNormalMapX,this._invertNormalMapY,i),this.anisotropy.bindForSubMesh(b,o,this.isFrozen),this.sheen.bindForSubMesh(b,o,this.isFrozen,i),et.a.BindClipPlane(this._activeEffect,o),o.ambientColor.multiplyToRef(this._ambientColor,this._globalAmbientColor);var ce=o._forcedViewPosition?o._forcedViewPosition:o._mirroredCameraPosition?o._mirroredCameraPosition:o.activeCamera.globalPosition,ue=o.useRightHandedSystem===(o._mirroredCameraPosition!=null);s.setFloat4("vEyePosition",ce.x,ce.y,ce.z,ue?-1:1),s.setColor3("vAmbientColor",this._globalAmbientColor),s.setFloat2("vDebugMode",this.debugLimit,this.debugFactor)}!d&&this.isFrozen||(o.lightsEnabled&&!this._disableLighting&&et.a.BindLights(o,n,this._activeEffect,a,this._maxSimultaneousLights,this._rebuildInParallel),(o.fogEnabled&&n.applyFog&&o.fogMode!==_e.a.FOGMODE_NONE||p)&&this.bindView(s),et.a.BindFogParameters(o,n,this._activeEffect,!0),a.NUM_MORPH_INFLUENCERS&&et.a.BindMorphTargetParameters(n,this._activeEffect),this._imageProcessingConfiguration.bind(this._activeEffect),et.a.BindLogDepth(a,this._activeEffect,o)),b.update(),this._afterBind(n,this._activeEffect)}}},t.prototype.getAnimatables=function(){var e=[];return this._albedoTexture&&this._albedoTexture.animations&&this._albedoTexture.animations.length>0&&e.push(this._albedoTexture),this._ambientTexture&&this._ambientTexture.animations&&this._ambientTexture.animations.length>0&&e.push(this._ambientTexture),this._opacityTexture&&this._opacityTexture.animations&&this._opacityTexture.animations.length>0&&e.push(this._opacityTexture),this._reflectionTexture&&this._reflectionTexture.animations&&this._reflectionTexture.animations.length>0&&e.push(this._reflectionTexture),this._emissiveTexture&&this._emissiveTexture.animations&&this._emissiveTexture.animations.length>0&&e.push(this._emissiveTexture),this._metallicTexture&&this._metallicTexture.animations&&this._metallicTexture.animations.length>0?e.push(this._metallicTexture):this._reflectivityTexture&&this._reflectivityTexture.animations&&this._reflectivityTexture.animations.length>0&&e.push(this._reflectivityTexture),this._bumpTexture&&this._bumpTexture.animations&&this._bumpTexture.animations.length>0&&e.push(this._bumpTexture),this._lightmapTexture&&this._lightmapTexture.animations&&this._lightmapTexture.animations.length>0&&e.push(this._lightmapTexture),this.detailMap.getAnimatables(e),this.subSurface.getAnimatables(e),this.clearCoat.getAnimatables(e),this.sheen.getAnimatables(e),this.anisotropy.getAnimatables(e),e},t.prototype._getReflectionTexture=function(){return this._reflectionTexture?this._reflectionTexture:this.getScene().environmentTexture},t.prototype.getActiveTextures=function(){var e=r.prototype.getActiveTextures.call(this);return this._albedoTexture&&e.push(this._albedoTexture),this._ambientTexture&&e.push(this._ambientTexture),this._opacityTexture&&e.push(this._opacityTexture),this._reflectionTexture&&e.push(this._reflectionTexture),this._emissiveTexture&&e.push(this._emissiveTexture),this._reflectivityTexture&&e.push(this._reflectivityTexture),this._metallicTexture&&e.push(this._metallicTexture),this._metallicReflectanceTexture&&e.push(this._metallicReflectanceTexture),this._microSurfaceTexture&&e.push(this._microSurfaceTexture),this._bumpTexture&&e.push(this._bumpTexture),this._lightmapTexture&&e.push(this._lightmapTexture),this.detailMap.getActiveTextures(e),this.subSurface.getActiveTextures(e),this.clearCoat.getActiveTextures(e),this.sheen.getActiveTextures(e),this.anisotropy.getActiveTextures(e),e},t.prototype.hasTexture=function(e){return!!r.prototype.hasTexture.call(this,e)||this._albedoTexture===e||this._ambientTexture===e||this._opacityTexture===e||this._reflectionTexture===e||this._reflectivityTexture===e||this._metallicTexture===e||this._metallicReflectanceTexture===e||this._microSurfaceTexture===e||this._bumpTexture===e||this._lightmapTexture===e||this.detailMap.hasTexture(e)||this.subSurface.hasTexture(e)||this.clearCoat.hasTexture(e)||this.sheen.hasTexture(e)||this.anisotropy.hasTexture(e)},t.prototype.setPrePassRenderer=function(e){if(this.subSurface.isScatteringEnabled){var n=this.getScene().enableSubSurfaceForPrePass();return n&&(n.enabled=!0),!0}return!1},t.prototype.dispose=function(e,n){var i,o,a,s,d,p,b,P,O,B,F;n&&(this._environmentBRDFTexture&&this.getScene().environmentBRDFTexture!==this._environmentBRDFTexture&&this._environmentBRDFTexture.dispose(),(i=this._albedoTexture)===null||i===void 0||i.dispose(),(o=this._ambientTexture)===null||o===void 0||o.dispose(),(a=this._opacityTexture)===null||a===void 0||a.dispose(),(s=this._reflectionTexture)===null||s===void 0||s.dispose(),(d=this._emissiveTexture)===null||d===void 0||d.dispose(),(p=this._metallicTexture)===null||p===void 0||p.dispose(),(b=this._reflectivityTexture)===null||b===void 0||b.dispose(),(P=this._bumpTexture)===null||P===void 0||P.dispose(),(O=this._lightmapTexture)===null||O===void 0||O.dispose(),(B=this._metallicReflectanceTexture)===null||B===void 0||B.dispose(),(F=this._microSurfaceTexture)===null||F===void 0||F.dispose()),this.detailMap.dispose(n),this.subSurface.dispose(n),this.clearCoat.dispose(n),this.sheen.dispose(n),this.anisotropy.dispose(n),this._renderTargets.dispose(),this._imageProcessingConfiguration&&this._imageProcessingObserver&&this._imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingObserver),r.prototype.dispose.call(this,e,n)},t.PBRMATERIAL_OPAQUE=Ht.a.MATERIAL_OPAQUE,t.PBRMATERIAL_ALPHATEST=Ht.a.MATERIAL_ALPHATEST,t.PBRMATERIAL_ALPHABLEND=Ht.a.MATERIAL_ALPHABLEND,t.PBRMATERIAL_ALPHATESTANDBLEND=Ht.a.MATERIAL_ALPHATESTANDBLEND,t.DEFAULT_AO_ON_ANALYTICAL_LIGHTS=0,t.LIGHTFALLOFF_PHYSICAL=0,t.LIGHTFALLOFF_GLTF=1,t.LIGHTFALLOFF_STANDARD=2,Object(c.c)([Object(L.i)()],t.prototype,"_imageProcessingConfiguration",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsMiscDirty")],t.prototype,"debugMode",void 0),Object(c.c)([Object(L.c)()],t.prototype,"useLogarithmicDepth",null),t}($o.a),uo=function(r){function t(e,n){var i=r.call(this,e,n)||this;return i.directIntensity=1,i.emissiveIntensity=1,i.environmentIntensity=1,i.specularIntensity=1,i.disableBumpMap=!1,i.ambientTextureStrength=1,i.ambientTextureImpactOnAnalyticalLights=t.DEFAULT_AO_ON_ANALYTICAL_LIGHTS,i.metallicF0Factor=1,i.metallicReflectanceColor=M.a.White(),i.ambientColor=new M.a(0,0,0),i.albedoColor=new M.a(1,1,1),i.reflectivityColor=new M.a(1,1,1),i.reflectionColor=new M.a(1,1,1),i.emissiveColor=new M.a(0,0,0),i.microSurface=1,i.useLightmapAsShadowmap=!1,i.useAlphaFromAlbedoTexture=!1,i.forceAlphaTest=!1,i.alphaCutOff=.4,i.useSpecularOverAlpha=!0,i.useMicroSurfaceFromReflectivityMapAlpha=!1,i.useRoughnessFromMetallicTextureAlpha=!0,i.useRoughnessFromMetallicTextureGreen=!1,i.useMetallnessFromMetallicTextureBlue=!1,i.useAmbientOcclusionFromMetallicTextureRed=!1,i.useAmbientInGrayScale=!1,i.useAutoMicroSurfaceFromReflectivityMap=!1,i.useRadianceOverAlpha=!0,i.useObjectSpaceNormalMap=!1,i.useParallax=!1,i.useParallaxOcclusion=!1,i.parallaxScaleBias=.05,i.disableLighting=!1,i.forceIrradianceInFragment=!1,i.maxSimultaneousLights=4,i.invertNormalMapX=!1,i.invertNormalMapY=!1,i.twoSidedLighting=!1,i.useAlphaFresnel=!1,i.useLinearAlphaFresnel=!1,i.environmentBRDFTexture=null,i.forceNormalForward=!1,i.enableSpecularAntiAliasing=!1,i.useHorizonOcclusion=!0,i.useRadianceOcclusion=!0,i.unlit=!1,i._environmentBRDFTexture=ea.GetEnvironmentBRDFTexture(n),i}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"refractionTexture",{get:function(){return this.subSurface.refractionTexture},set:function(e){this.subSurface.refractionTexture=e,e?this.subSurface.isRefractionEnabled=!0:this.subSurface.linkRefractionWithTransparency||(this.subSurface.isRefractionEnabled=!1)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"indexOfRefraction",{get:function(){return this.subSurface.indexOfRefraction},set:function(e){this.subSurface.indexOfRefraction=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"invertRefractionY",{get:function(){return this.subSurface.invertRefractionY},set:function(e){this.subSurface.invertRefractionY=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"linkRefractionWithTransparency",{get:function(){return this.subSurface.linkRefractionWithTransparency},set:function(e){this.subSurface.linkRefractionWithTransparency=e,e&&(this.subSurface.isRefractionEnabled=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"usePhysicalLightFalloff",{get:function(){return this._lightFalloff===_n.LIGHTFALLOFF_PHYSICAL},set:function(e){e!==this.usePhysicalLightFalloff&&(this._markAllSubMeshesAsTexturesDirty(),this._lightFalloff=e?_n.LIGHTFALLOFF_PHYSICAL:_n.LIGHTFALLOFF_STANDARD)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"useGLTFLightFalloff",{get:function(){return this._lightFalloff===_n.LIGHTFALLOFF_GLTF},set:function(e){e!==this.useGLTFLightFalloff&&(this._markAllSubMeshesAsTexturesDirty(),this._lightFalloff=e?_n.LIGHTFALLOFF_GLTF:_n.LIGHTFALLOFF_STANDARD)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"imageProcessingConfiguration",{get:function(){return this._imageProcessingConfiguration},set:function(e){this._attachImageProcessingConfiguration(e),this._markAllSubMeshesAsTexturesDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraColorCurvesEnabled",{get:function(){return this.imageProcessingConfiguration.colorCurvesEnabled},set:function(e){this.imageProcessingConfiguration.colorCurvesEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraColorGradingEnabled",{get:function(){return this.imageProcessingConfiguration.colorGradingEnabled},set:function(e){this.imageProcessingConfiguration.colorGradingEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraToneMappingEnabled",{get:function(){return this._imageProcessingConfiguration.toneMappingEnabled},set:function(e){this._imageProcessingConfiguration.toneMappingEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraExposure",{get:function(){return this._imageProcessingConfiguration.exposure},set:function(e){this._imageProcessingConfiguration.exposure=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraContrast",{get:function(){return this._imageProcessingConfiguration.contrast},set:function(e){this._imageProcessingConfiguration.contrast=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraColorGradingTexture",{get:function(){return this._imageProcessingConfiguration.colorGradingTexture},set:function(e){this._imageProcessingConfiguration.colorGradingTexture=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraColorCurves",{get:function(){return this._imageProcessingConfiguration.colorCurves},set:function(e){this._imageProcessingConfiguration.colorCurves=e},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"PBRMaterial"},t.prototype.clone=function(e){var n=this,i=L.a.Clone(function(){return new t(e,n.getScene())},this);return i.id=e,i.name=e,this.clearCoat.copyTo(i.clearCoat),this.anisotropy.copyTo(i.anisotropy),this.brdf.copyTo(i.brdf),this.sheen.copyTo(i.sheen),this.subSurface.copyTo(i.subSurface),i},t.prototype.serialize=function(){var e=L.a.Serialize(this);return e.customType="BABYLON.PBRMaterial",e.clearCoat=this.clearCoat.serialize(),e.anisotropy=this.anisotropy.serialize(),e.brdf=this.brdf.serialize(),e.sheen=this.sheen.serialize(),e.subSurface=this.subSurface.serialize(),e},t.Parse=function(e,n,i){var o=L.a.Parse(function(){return new t(e.name,n)},e,n,i);return e.clearCoat&&o.clearCoat.parse(e.clearCoat,n,i),e.anisotropy&&o.anisotropy.parse(e.anisotropy,n,i),e.brdf&&o.brdf.parse(e.brdf,n,i),e.sheen&&o.sheen.parse(e.sheen,n,i),e.subSurface&&o.subSurface.parse(e.subSurface,n,i),o},t.PBRMATERIAL_OPAQUE=_n.PBRMATERIAL_OPAQUE,t.PBRMATERIAL_ALPHATEST=_n.PBRMATERIAL_ALPHATEST,t.PBRMATERIAL_ALPHABLEND=_n.PBRMATERIAL_ALPHABLEND,t.PBRMATERIAL_ALPHATESTANDBLEND=_n.PBRMATERIAL_ALPHATESTANDBLEND,t.DEFAULT_AO_ON_ANALYTICAL_LIGHTS=_n.DEFAULT_AO_ON_ANALYTICAL_LIGHTS,Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"directIntensity",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"emissiveIntensity",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"environmentIntensity",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"specularIntensity",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"disableBumpMap",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"albedoTexture",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"ambientTexture",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"ambientTextureStrength",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"ambientTextureImpactOnAnalyticalLights",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesAndMiscDirty")],t.prototype,"opacityTexture",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectionTexture",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"emissiveTexture",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectivityTexture",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"metallicTexture",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"metallic",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"roughness",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"metallicF0Factor",void 0),Object(c.c)([Object(L.e)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"metallicReflectanceColor",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"metallicReflectanceTexture",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"microSurfaceTexture",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"bumpTexture",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty",null)],t.prototype,"lightmapTexture",void 0),Object(c.c)([Object(L.e)("ambient"),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"ambientColor",void 0),Object(c.c)([Object(L.e)("albedo"),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"albedoColor",void 0),Object(c.c)([Object(L.e)("reflectivity"),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectivityColor",void 0),Object(c.c)([Object(L.e)("reflection"),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectionColor",void 0),Object(c.c)([Object(L.e)("emissive"),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"emissiveColor",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"microSurface",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useLightmapAsShadowmap",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesAndMiscDirty")],t.prototype,"useAlphaFromAlbedoTexture",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesAndMiscDirty")],t.prototype,"forceAlphaTest",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesAndMiscDirty")],t.prototype,"alphaCutOff",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useSpecularOverAlpha",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useMicroSurfaceFromReflectivityMapAlpha",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useRoughnessFromMetallicTextureAlpha",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useRoughnessFromMetallicTextureGreen",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useMetallnessFromMetallicTextureBlue",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useAmbientOcclusionFromMetallicTextureRed",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useAmbientInGrayScale",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useAutoMicroSurfaceFromReflectivityMap",void 0),Object(c.c)([Object(L.c)()],t.prototype,"usePhysicalLightFalloff",null),Object(c.c)([Object(L.c)()],t.prototype,"useGLTFLightFalloff",null),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useRadianceOverAlpha",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useObjectSpaceNormalMap",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useParallax",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useParallaxOcclusion",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"parallaxScaleBias",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsLightsDirty")],t.prototype,"disableLighting",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"forceIrradianceInFragment",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsLightsDirty")],t.prototype,"maxSimultaneousLights",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"invertNormalMapX",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"invertNormalMapY",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"twoSidedLighting",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useAlphaFresnel",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useLinearAlphaFresnel",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"environmentBRDFTexture",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"forceNormalForward",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"enableSpecularAntiAliasing",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useHorizonOcclusion",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useRadianceOcclusion",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsMiscDirty")],t.prototype,"unlit",void 0),t}(_n);R.a.RegisteredTypes["BABYLON.PBRMaterial"]=uo;function na(r){return r.charCodeAt(0)+(r.charCodeAt(1)<<8)+(r.charCodeAt(2)<<16)+(r.charCodeAt(3)<<24)}var pu=na("DXT1"),_u=na("DXT3"),mu=na("DXT5"),Fs=na("DX10"),Gi=function(){function r(){}return r.GetDDSInfo=function(t){var e=new Int32Array(t.buffer,t.byteOffset,31),n=new Int32Array(t.buffer,t.byteOffset,35),i=1;131072&e[2]&&(i=Math.max(1,e[7]));var o=e[21],a=o===Fs?n[32]:0,s=h.a.TEXTURETYPE_UNSIGNED_INT;switch(o){case 113:s=h.a.TEXTURETYPE_HALF_FLOAT;break;case 116:s=h.a.TEXTURETYPE_FLOAT;break;case Fs:if(a===10){s=h.a.TEXTURETYPE_HALF_FLOAT;break}if(a===2){s=h.a.TEXTURETYPE_FLOAT;break}}return{width:e[4],height:e[3],mipmapCount:i,isFourCC:(4&e[20])==4,isRGB:(64&e[20])==64,isLuminance:(131072&e[20])==131072,isCube:(512&e[28])==512,isCompressed:o===pu||o===_u||o===mu,dxgiFormat:a,textureType:s}},r._ToHalfFloat=function(t){r._FloatView||(r._FloatView=new Float32Array(1),r._Int32View=new Int32Array(r._FloatView.buffer)),r._FloatView[0]=t;var e=r._Int32View[0],n=e>>16&32768,i=e>>12&2047,o=e>>23&255;return o<103?n:o>142?(n|=31744,n|=(o==255?0:1)&&8388607&e):o<113?n|=((i|=2048)>>114-o)+(i>>113-o&1):(n|=o-112<<10|i>>1,n+=1&i)},r._FromHalfFloat=function(t){var e=(32768&t)>>15,n=(31744&t)>>10,i=1023&t;return n===0?(e?-1:1)*Math.pow(2,-14)*(i/Math.pow(2,10)):n==31?i?NaN:1/0*(e?-1:1):(e?-1:1)*Math.pow(2,n-15)*(1+i/Math.pow(2,10))},r._GetHalfFloatAsFloatRGBAArrayBuffer=function(t,e,n,i,o,a){for(var s=new Float32Array(i),d=new Uint16Array(o,n),p=0,b=0;b<e;b++)for(var P=0;P<t;P++){var O=4*(P+b*t);s[p]=r._FromHalfFloat(d[O]),s[p+1]=r._FromHalfFloat(d[O+1]),s[p+2]=r._FromHalfFloat(d[O+2]),r.StoreLODInAlphaChannel?s[p+3]=a:s[p+3]=r._FromHalfFloat(d[O+3]),p+=4}return s},r._GetHalfFloatRGBAArrayBuffer=function(t,e,n,i,o,a){if(r.StoreLODInAlphaChannel){for(var s=new Uint16Array(i),d=new Uint16Array(o,n),p=0,b=0;b<e;b++)for(var P=0;P<t;P++){var O=4*(P+b*t);s[p]=d[O],s[p+1]=d[O+1],s[p+2]=d[O+2],s[p+3]=r._ToHalfFloat(a),p+=4}return s}return new Uint16Array(o,n,i)},r._GetFloatRGBAArrayBuffer=function(t,e,n,i,o,a){if(r.StoreLODInAlphaChannel){for(var s=new Float32Array(i),d=new Float32Array(o,n),p=0,b=0;b<e;b++)for(var P=0;P<t;P++){var O=4*(P+b*t);s[p]=d[O],s[p+1]=d[O+1],s[p+2]=d[O+2],s[p+3]=a,p+=4}return s}return new Float32Array(o,n,i)},r._GetFloatAsUIntRGBAArrayBuffer=function(t,e,n,i,o,a){for(var s=new Uint8Array(i),d=new Float32Array(o,n),p=0,b=0;b<e;b++)for(var P=0;P<t;P++){var O=4*(P+b*t);s[p]=255*$.a.Clamp(d[O]),s[p+1]=255*$.a.Clamp(d[O+1]),s[p+2]=255*$.a.Clamp(d[O+2]),r.StoreLODInAlphaChannel?s[p+3]=a:s[p+3]=255*$.a.Clamp(d[O+3]),p+=4}return s},r._GetHalfFloatAsUIntRGBAArrayBuffer=function(t,e,n,i,o,a){for(var s=new Uint8Array(i),d=new Uint16Array(o,n),p=0,b=0;b<e;b++)for(var P=0;P<t;P++){var O=4*(P+b*t);s[p]=255*$.a.Clamp(r._FromHalfFloat(d[O])),s[p+1]=255*$.a.Clamp(r._FromHalfFloat(d[O+1])),s[p+2]=255*$.a.Clamp(r._FromHalfFloat(d[O+2])),r.StoreLODInAlphaChannel?s[p+3]=a:s[p+3]=255*$.a.Clamp(r._FromHalfFloat(d[O+3])),p+=4}return s},r._GetRGBAArrayBuffer=function(t,e,n,i,o,a,s,d,p){for(var b=new Uint8Array(i),P=new Uint8Array(o,n),O=0,B=0;B<e;B++)for(var F=0;F<t;F++){var z=4*(F+B*t);b[O]=P[z+a],b[O+1]=P[z+s],b[O+2]=P[z+d],b[O+3]=P[z+p],O+=4}return b},r._ExtractLongWordOrder=function(t){return t===0||t===255||t===-16777216?0:1+r._ExtractLongWordOrder(t>>8)},r._GetRGBArrayBuffer=function(t,e,n,i,o,a,s,d){for(var p=new Uint8Array(i),b=new Uint8Array(o,n),P=0,O=0;O<e;O++)for(var B=0;B<t;B++){var F=3*(B+O*t);p[P]=b[F+a],p[P+1]=b[F+s],p[P+2]=b[F+d],P+=3}return p},r._GetLuminanceArrayBuffer=function(t,e,n,i,o){for(var a=new Uint8Array(i),s=new Uint8Array(o,n),d=0,p=0;p<e;p++)for(var b=0;b<t;b++){var P=b+p*t;a[d]=s[P],d++}return a},r.UploadDDSLevels=function(t,e,n,i,o,a,s,d){s===void 0&&(s=-1);var p=null;i.sphericalPolynomial&&(p=new Array);var b,P,O,B,F,z,J,ie=t.getCaps().s3tc,se=new Int32Array(n.buffer,n.byteOffset,31),ce=0,ue=0,fe=1;if(se[0]===542327876)if(i.isFourCC||i.isRGB||i.isLuminance)if(!i.isCompressed||ie){var ve=se[22];B=se[1]+4;var Te,Re=!1;if(i.isFourCC)switch(b=se[21]){case pu:fe=8,ue=ie.COMPRESSED_RGBA_S3TC_DXT1_EXT;break;case _u:fe=16,ue=ie.COMPRESSED_RGBA_S3TC_DXT3_EXT;break;case mu:fe=16,ue=ie.COMPRESSED_RGBA_S3TC_DXT5_EXT;break;case 113:case 116:Re=!0;break;case Fs:B+=20;var Ae=!1;switch(i.dxgiFormat){case 10:case 2:Re=!0,Ae=!0;break;case 88:i.isRGB=!0,i.isFourCC=!1,ve=32,Ae=!0}if(Ae)break;default:return void console.error("Unsupported FourCC code:",(Te=b,String.fromCharCode(255&Te,Te>>8&255,Te>>16&255,Te>>24&255)))}var Ee=r._ExtractLongWordOrder(se[23]),Se=r._ExtractLongWordOrder(se[24]),Le=r._ExtractLongWordOrder(se[25]),Ce=r._ExtractLongWordOrder(se[26]);Re&&(ue=t._getRGBABufferInternalSizedFormat(i.textureType)),z=1,131072&se[2]&&o!==!1&&(z=Math.max(1,se[7]));for(var Ne=d||0;Ne<a;Ne++){for(P=se[4],O=se[3],J=0;J<z;++J){if(s===-1||s===J){var Ie=s===-1?J:0;if(!i.isCompressed&&i.isFourCC){e.format=h.a.TEXTUREFORMAT_RGBA,ce=P*O*4;var Fe=null;t._badOS||t._badDesktopOS||!t.getCaps().textureHalfFloat&&!t.getCaps().textureFloat?(ve===128?(Fe=r._GetFloatAsUIntRGBAArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer,Ie),p&&Ie==0&&p.push(r._GetFloatRGBAArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer,Ie))):ve===64&&(Fe=r._GetHalfFloatAsUIntRGBAArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer,Ie),p&&Ie==0&&p.push(r._GetHalfFloatAsFloatRGBAArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer,Ie))),e.type=h.a.TEXTURETYPE_UNSIGNED_INT):ve===128?(e.type=h.a.TEXTURETYPE_FLOAT,Fe=r._GetFloatRGBAArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer,Ie),p&&Ie==0&&p.push(Fe)):ve!==64||t.getCaps().textureHalfFloat?(e.type=h.a.TEXTURETYPE_HALF_FLOAT,Fe=r._GetHalfFloatRGBAArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer,Ie),p&&Ie==0&&p.push(r._GetHalfFloatAsFloatRGBAArrayBuffer(P,O,B,ce,n.buffer,Ie))):(e.type=h.a.TEXTURETYPE_FLOAT,Fe=r._GetHalfFloatAsFloatRGBAArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer,Ie),p&&Ie==0&&p.push(Fe)),Fe&&t._uploadDataToTextureDirectly(e,Fe,Ne,Ie)}else if(i.isRGB)e.type=h.a.TEXTURETYPE_UNSIGNED_INT,ve===24?(e.format=h.a.TEXTUREFORMAT_RGB,ce=P*O*3,F=r._GetRGBArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer,Ee,Se,Le),t._uploadDataToTextureDirectly(e,F,Ne,Ie)):(e.format=h.a.TEXTUREFORMAT_RGBA,ce=P*O*4,F=r._GetRGBAArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer,Ee,Se,Le,Ce),t._uploadDataToTextureDirectly(e,F,Ne,Ie));else if(i.isLuminance){var Ye=t._getUnpackAlignement(),tt=P;ce=Math.floor((P+Ye-1)/Ye)*Ye*(O-1)+tt,F=r._GetLuminanceArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer),e.format=h.a.TEXTUREFORMAT_LUMINANCE,e.type=h.a.TEXTURETYPE_UNSIGNED_INT,t._uploadDataToTextureDirectly(e,F,Ne,Ie)}else ce=Math.max(4,P)/4*Math.max(4,O)/4*fe,F=new Uint8Array(n.buffer,n.byteOffset+B,ce),e.type=h.a.TEXTURETYPE_UNSIGNED_INT,t._uploadCompressedDataToTextureDirectly(e,ue,P,O,F,Ne,Ie)}B+=ve?P*O*(ve/8):ce,P*=.5,O*=.5,P=Math.max(1,P),O=Math.max(1,O)}if(d!==void 0)break}p&&p.length>0?i.sphericalPolynomial=jo.ConvertCubeMapToSphericalPolynomial({size:se[4],right:p[0],left:p[1],up:p[2],down:p[3],front:p[4],back:p[5],format:h.a.TEXTUREFORMAT_RGBA,type:h.a.TEXTURETYPE_FLOAT,gammaSpace:!1}):i.sphericalPolynomial=void 0}else l.a.Error("Compressed textures are not supported on this platform.");else l.a.Error("Unsupported format, must contain a FourCC, RGB or LUMINANCE code");else l.a.Error("Invalid magic number in DDS header")},r.StoreLODInAlphaChannel=!1,r}();Bt.a.prototype.createPrefilteredCubeTexture=function(r,t,e,n,i,o,a,s,d){var p=this;return i===void 0&&(i=null),o===void 0&&(o=null),s===void 0&&(s=null),d===void 0&&(d=!0),this.createCubeTexture(r,t,null,!1,function(b){if(b){var P=b.texture;if(d?b.info.sphericalPolynomial&&(P._sphericalPolynomial=b.info.sphericalPolynomial):P._sphericalPolynomial=new ro,P._source=xt.b.CubePrefiltered,p.getCaps().textureLOD)i&&i(P);else{var O=p._gl,B=b.width;if(B){for(var F=[],z=0;z<3;z++){var J=1-z/2,ie=n,se=$.a.Log2(B)*e+n,ce=ie+(se-ie)*J,ue=Math.round(Math.min(Math.max(ce,0),se)),fe=new xt.a(p,xt.b.Temp);if(fe.type=P.type,fe.format=P.format,fe.width=Math.pow(2,Math.max($.a.Log2(B)-ue,0)),fe.height=fe.width,fe.isCube=!0,p._bindTextureDirectly(O.TEXTURE_CUBE_MAP,fe,!0),fe.samplingMode=h.a.TEXTURE_LINEAR_LINEAR,O.texParameteri(O.TEXTURE_CUBE_MAP,O.TEXTURE_MAG_FILTER,O.LINEAR),O.texParameteri(O.TEXTURE_CUBE_MAP,O.TEXTURE_MIN_FILTER,O.LINEAR),O.texParameteri(O.TEXTURE_CUBE_MAP,O.TEXTURE_WRAP_S,O.CLAMP_TO_EDGE),O.texParameteri(O.TEXTURE_CUBE_MAP,O.TEXTURE_WRAP_T,O.CLAMP_TO_EDGE),b.isDDS){var ve=b.info,Te=b.data;p._unpackFlipY(ve.isCompressed),Gi.UploadDDSLevels(p,fe,Te,ve,!0,6,ue)}else l.a.Warn("DDS is the only prefiltered cube map supported so far.");p._bindTextureDirectly(O.TEXTURE_CUBE_MAP,null);var Re=new zn.a(t);Re.isCube=!0,Re._texture=fe,fe.isReady=!0,F.push(Re)}P._lodTextureHigh=F[2],P._lodTextureMid=F[1],P._lodTextureLow=F[0],i&&i(P)}}}else i&&i(null)},o,a,s,d,e,n)};var gu=function(){function r(){this.supportCascades=!0}return r.prototype.canLoad=function(t){return Qn.a.EndsWith(t,".dds")},r.prototype.loadCubeData=function(t,e,n,i,o){var a,s=e.getEngine(),d=!1;if(Array.isArray(t))for(var p=0;p<t.length;p++){var b=t[p];a=Gi.GetDDSInfo(b),e.width=a.width,e.height=a.height,d=(a.isRGB||a.isLuminance||a.mipmapCount>1)&&e.generateMipMaps,s._unpackFlipY(a.isCompressed),Gi.UploadDDSLevels(s,e,b,a,d,6,-1,p),a.isFourCC||a.mipmapCount!==1||s.generateMipMapsForCubemap(e)}else{var P=t;a=Gi.GetDDSInfo(P),e.width=a.width,e.height=a.height,n&&(a.sphericalPolynomial=new ro),d=(a.isRGB||a.isLuminance||a.mipmapCount>1)&&e.generateMipMaps,s._unpackFlipY(a.isCompressed),Gi.UploadDDSLevels(s,e,P,a,d,6),a.isFourCC||a.mipmapCount!==1||s.generateMipMapsForCubemap(e,!1)}s._setCubeMapTextureParams(e,d),e.isReady=!0,e.onLoadedObservable.notifyObservers(e),e.onLoadedObservable.clear(),i&&i({isDDS:!0,width:e.width,info:a,data:t,texture:e})},r.prototype.loadData=function(t,e,n){var i=Gi.GetDDSInfo(t),o=(i.isRGB||i.isLuminance||i.mipmapCount>1)&&e.generateMipMaps&&i.width>>i.mipmapCount-1==1;n(i.width,i.height,o,i.isFourCC,function(){Gi.UploadDDSLevels(e.getEngine(),e,t,i,o,1)})},r}();Ue.a._TextureLoaders.push(new gu);var vu=function(){function r(){this.supportCascades=!1}return r.prototype.canLoad=function(t){return Qn.a.EndsWith(t,".env")},r.prototype.loadCubeData=function(t,e,n,i,o){if(!Array.isArray(t)){var a=Ai.GetEnvInfo(t);a?(e.width=a.width,e.height=a.width,Ai.UploadEnvSpherical(e,a),Ai.UploadEnvLevelsAsync(e,t,a).then(function(){e.isReady=!0,e.onLoadedObservable.notifyObservers(e),e.onLoadedObservable.clear(),i&&i()})):o&&o("Can not parse the environment file",null)}},r.prototype.loadData=function(t,e,n){throw".env not supported in 2d."},r}();Ue.a._TextureLoaders.push(new vu);var ia=function(){function r(t,e,n,i){if(this.data=t,this.isInvalid=!1,!r.IsValid(t))return this.isInvalid=!0,void l.a.Error("texture missing KTX identifier");var o=Uint32Array.BYTES_PER_ELEMENT,a=new DataView(this.data.buffer,this.data.byteOffset+12,13*o),s=a.getUint32(0,!0)===67305985;this.glType=a.getUint32(1*o,s),this.glTypeSize=a.getUint32(2*o,s),this.glFormat=a.getUint32(3*o,s),this.glInternalFormat=a.getUint32(4*o,s),this.glBaseInternalFormat=a.getUint32(5*o,s),this.pixelWidth=a.getUint32(6*o,s),this.pixelHeight=a.getUint32(7*o,s),this.pixelDepth=a.getUint32(8*o,s),this.numberOfArrayElements=a.getUint32(9*o,s),this.numberOfFaces=a.getUint32(10*o,s),this.numberOfMipmapLevels=a.getUint32(11*o,s),this.bytesOfKeyValueData=a.getUint32(12*o,s),this.glType===0?(this.numberOfMipmapLevels=Math.max(1,this.numberOfMipmapLevels),this.pixelHeight!==0&&this.pixelDepth===0?this.numberOfArrayElements===0?this.numberOfFaces===e?this.loadType=r.COMPRESSED_2D:l.a.Error("number of faces expected"+e+", but found "+this.numberOfFaces):l.a.Error("texture arrays not currently supported"):l.a.Error("only 2D textures currently supported")):l.a.Error("only compressed formats currently supported")}return r.prototype.uploadLevels=function(t,e){switch(this.loadType){case r.COMPRESSED_2D:this._upload2DCompressedLevels(t,e);break;case r.TEX_2D:case r.COMPRESSED_3D:case r.TEX_3D:}},r.prototype._upload2DCompressedLevels=function(t,e){for(var n=r.HEADER_LEN+this.bytesOfKeyValueData,i=this.pixelWidth,o=this.pixelHeight,a=e?this.numberOfMipmapLevels:1,s=0;s<a;s++){var d=new Int32Array(this.data.buffer,this.data.byteOffset+n,1)[0];n+=4;for(var p=0;p<this.numberOfFaces;p++){var b=new Uint8Array(this.data.buffer,this.data.byteOffset+n,d);t.getEngine()._uploadCompressedDataToTextureDirectly(t,this.glInternalFormat,i,o,b,p,s),n+=d,n+=3-(d+3)%4}i=Math.max(1,.5*i),o=Math.max(1,.5*o)}},r.IsValid=function(t){if(t.byteLength>=12){var e=new Uint8Array(t.buffer,t.byteOffset,12);if(e[0]===171&&e[1]===75&&e[2]===84&&e[3]===88&&e[4]===32&&e[5]===49&&e[6]===49&&e[7]===187&&e[8]===13&&e[9]===10&&e[10]===26&&e[11]===10)return!0}return!1},r.HEADER_LEN=64,r.COMPRESSED_2D=0,r.COMPRESSED_3D=1,r.TEX_2D=2,r.TEX_3D=3,r}(),Bs=function(){function r(t){this._pendingActions=new Array,this._workerInfos=t.map(function(e){return{worker:e,active:!1}})}return r.prototype.dispose=function(){for(var t=0,e=this._workerInfos;t<e.length;t++)e[t].worker.terminate();this._workerInfos=[],this._pendingActions=[]},r.prototype.push=function(t){for(var e=0,n=this._workerInfos;e<n.length;e++){var i=n[e];if(!i.active)return void this._execute(i,t)}this._pendingActions.push(t)},r.prototype._execute=function(t,e){var n=this;t.active=!0,e(t.worker,function(){t.active=!1;var i=n._pendingActions.shift();i&&n._execute(t,i)})},r}(),Us=function(){function r(t,e){e===void 0&&(e=r.DefaultNumWorkers),this._engine=t,r._Initialized||r._CreateWorkerPool(e)}return r.GetDefaultNumWorkers=function(){return typeof navigator=="object"&&navigator.hardwareConcurrency?Math.min(Math.floor(.5*navigator.hardwareConcurrency),4):1},r._CreateWorkerPool=function(t){this._Initialized=!0,t&&typeof Worker=="function"?r._WorkerPoolPromise=new Promise(function(e){for(var n="("+d_+")()",i=URL.createObjectURL(new Blob([n],{type:"application/javascript"})),o=new Array(t),a=0;a<o.length;a++)o[a]=new Promise(function(s,d){var p=new Worker(i),b=function(O){p.removeEventListener("error",b),p.removeEventListener("message",P),d(O)},P=function(O){O.data.action==="init"&&(p.removeEventListener("error",b),p.removeEventListener("message",P),s(p))};p.addEventListener("error",b),p.addEventListener("message",P),p.postMessage({action:"init",urls:r.URLConfig})});Promise.all(o).then(function(s){e(new Bs(s))})}):(KTX2DECODER.MSCTranscoder.UseFromWorkerThread=!1,KTX2DECODER.WASMMemoryManager.LoadBinariesFromCurrentThread=!0)},r.prototype.uploadAsync=function(t,e,n){var i=this,o=this._engine.getCaps(),a={astc:!!o.astc,bptc:!!o.bptc,s3tc:!!o.s3tc,pvrtc:!!o.pvrtc,etc2:!!o.etc2,etc1:!!o.etc1};return r._WorkerPoolPromise?r._WorkerPoolPromise.then(function(s){return new Promise(function(d,p){s.push(function(b,P){var O=function(F){b.removeEventListener("error",O),b.removeEventListener("message",B),p(F),P()},B=function(F){if(F.data.action==="decoded"){if(b.removeEventListener("error",O),b.removeEventListener("message",B),F.data.success)try{i._createTexture(F.data.decodedData,e,n),d()}catch(z){p({message:z})}else p({message:F.data.msg});P()}};b.addEventListener("error",O),b.addEventListener("message",B),b.postMessage({action:"decode",data:t,caps:a,options:n})})})}):new Promise(function(s,d){r._Ktx2Decoder||(r._Ktx2Decoder=new KTX2DECODER.KTX2Decoder),r._Ktx2Decoder.decode(t,o).then(function(p){i._createTexture(p,e),s()}).catch(function(p){d({message:p})})})},r.prototype.dispose=function(){r._WorkerPoolPromise&&r._WorkerPoolPromise.then(function(t){t.dispose()}),delete r._WorkerPoolPromise},r.prototype._createTexture=function(t,e,n){if(this._engine._bindTextureDirectly(this._engine._gl.TEXTURE_2D,e),n&&(n.transcodedFormat=t.transcodedFormat,n.isInGammaSpace=t.isInGammaSpace,n.transcoderName=t.transcoderName),t.transcodedFormat===32856?(e.type=h.a.TEXTURETYPE_UNSIGNED_BYTE,e.format=h.a.TEXTUREFORMAT_RGBA):e.format=t.transcodedFormat,e._gammaSpace=t.isInGammaSpace,t.errors)throw new Error("KTX2 container - could not transcode the data. "+t.errors);for(var i=0;i<t.mipmaps.length;++i){var o=t.mipmaps[i];if(!o||!o.data)throw new Error("KTX2 container - could not transcode one of the image");t.transcodedFormat===32856?(e.width=o.width,e.height=o.height,this._engine._uploadDataToTextureDirectly(e,o.data,0,i,void 0,!0)):this._engine._uploadCompressedDataToTextureDirectly(e,t.transcodedFormat,o.width,o.height,o.data,0,i)}e.width=t.mipmaps[0].width,e.height=t.mipmaps[0].height,e.generateMipMaps=t.mipmaps.length>1,e.isReady=!0,this._engine._bindTextureDirectly(this._engine._gl.TEXTURE_2D,null)},r.IsValid=function(t){if(t.byteLength>=12){var e=new Uint8Array(t.buffer,t.byteOffset,12);if(e[0]===171&&e[1]===75&&e[2]===84&&e[3]===88&&e[4]===32&&e[5]===50&&e[6]===48&&e[7]===187&&e[8]===13&&e[9]===10&&e[10]===26&&e[11]===10)return!0}return!1},r.URLConfig={jsDecoderModule:"https://preview.babylonjs.com/babylon.ktx2Decoder.js",wasmUASTCToASTC:null,wasmUASTCToBC7:null,wasmUASTCToRGBA_UNORM:null,wasmUASTCToRGBA_SRGB:null,jsMSCTranscoder:null,wasmMSCTranscoder:null},r.DefaultNumWorkers=r.GetDefaultNumWorkers(),r}();function d_(){var r;onmessage=function(t){switch(t.data.action){case"init":var e=t.data.urls;importScripts(e.jsDecoderModule),e.wasmUASTCToASTC!==null&&(KTX2DECODER.LiteTranscoder_UASTC_ASTC.WasmModuleURL=e.wasmUASTCToASTC),e.wasmUASTCToBC7!==null&&(KTX2DECODER.LiteTranscoder_UASTC_BC7.WasmModuleURL=e.wasmUASTCToBC7),e.wasmUASTCToRGBA_UNORM!==null&&(KTX2DECODER.LiteTranscoder_UASTC_RGBA_UNORM.WasmModuleURL=e.wasmUASTCToRGBA_UNORM),e.wasmUASTCToRGBA_SRGB!==null&&(KTX2DECODER.LiteTranscoder_UASTC_RGBA_SRGB.WasmModuleURL=e.wasmUASTCToRGBA_SRGB),e.jsMSCTranscoder!==null&&(KTX2DECODER.MSCTranscoder.JSModuleURL=e.jsMSCTranscoder),e.wasmMSCTranscoder!==null&&(KTX2DECODER.MSCTranscoder.WasmModuleURL=e.wasmMSCTranscoder),r=new KTX2DECODER.KTX2Decoder,postMessage({action:"init"});break;case"decode":r.decode(t.data.data,t.data.caps,t.data.options).then(function(n){for(var i=[],o=0;o<n.mipmaps.length;++o){var a=n.mipmaps[o];a&&a.data&&i.push(a.data.buffer)}postMessage({action:"decoded",success:!0,decodedData:n},i)}).catch(function(n){postMessage({action:"decoded",success:!1,msg:n})})}}}var bu=function(){function r(){this.supportCascades=!1}return r.prototype.canLoad=function(t,e){return Qn.a.EndsWith(t,".ktx")||Qn.a.EndsWith(t,".ktx2")||e==="image/ktx"||e==="image/ktx2"},r.prototype.loadCubeData=function(t,e,n,i,o){if(!Array.isArray(t)){e._invertVScale=!e.invertY;var a=e.getEngine(),s=new ia(t,6),d=s.numberOfMipmapLevels>1&&e.generateMipMaps;a._unpackFlipY(!0),s.uploadLevels(e,e.generateMipMaps),e.width=s.pixelWidth,e.height=s.pixelHeight,a._setCubeMapTextureParams(e,d),e.isReady=!0,e.onLoadedObservable.notifyObservers(e),e.onLoadedObservable.clear(),i&&i()}},r.prototype.loadData=function(t,e,n,i){if(ia.IsValid(t)){e._invertVScale=!e.invertY;var o=new ia(t,1);n(o.pixelWidth,o.pixelHeight,e.generateMipMaps,!0,function(){o.uploadLevels(e,e.generateMipMaps)},o.isInvalid)}else Us.IsValid(t)?new Us(e.getEngine()).uploadAsync(t,e,i).then(function(){n(e.width,e.height,e.generateMipMaps,!0,function(){},!1)},function(a){l.a.Warn("Failed to load KTX2 texture data: "+a.message),n(0,0,!1,!1,function(){},!0)}):(l.a.Error("texture missing KTX identifier"),n(0,0,!1,!1,function(){},!0))},r}();Ue.a._TextureLoaders.unshift(new bu);var yu=function(r){function t(e,n,i){var o=r.call(this,e,u.e.Zero(),n)||this;return o._xrSessionManager=i,o._firstFrame=!1,o._referenceQuaternion=u.b.Identity(),o._referencedPosition=new u.e,o._xrInvPositionCache=new u.e,o._xrInvQuaternionCache=u.b.Identity(),o._trackingState=tr.NOT_TRACKING,o.onBeforeCameraTeleport=new x.c,o.onAfterCameraTeleport=new x.c,o.onTrackingStateChanged=new x.c,o.compensateOnFirstFrame=!0,o._rotate180=new u.b(0,1,0,0),o.minZ=.1,o.rotationQuaternion=new u.b,o.cameraRigMode=gt.a.RIG_MODE_CUSTOM,o.updateUpVectorFromRotation=!0,o._updateNumberOfRigCameras(1),o.freezeProjectionMatrix(),o._xrSessionManager.onXRSessionInit.add(function(){o._referencedPosition.copyFromFloats(0,0,0),o._referenceQuaternion.copyFromFloats(0,0,0,1),o._firstFrame=o.compensateOnFirstFrame}),o._xrSessionManager.onXRFrameObservable.add(function(a){o._firstFrame&&o._updateFromXRSession(),o._updateReferenceSpace(),o._updateFromXRSession()},void 0,!0),o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"trackingState",{get:function(){return this._trackingState},enumerable:!1,configurable:!0}),t.prototype._setTrackingState=function(e){this._trackingState!==e&&(this._trackingState=e,this.onTrackingStateChanged.notifyObservers(e))},Object.defineProperty(t.prototype,"realWorldHeight",{get:function(){var e=this._xrSessionManager.currentFrame&&this._xrSessionManager.currentFrame.getViewerPose(this._xrSessionManager.baseReferenceSpace);return e&&e.transform?e.transform.position.y:0},enumerable:!1,configurable:!0}),t.prototype._updateForDualEyeDebugging=function(){this._updateNumberOfRigCameras(2),this.rigCameras[0].viewport=new Kn.a(0,0,.5,1),this.rigCameras[0].outputRenderTarget=null,this.rigCameras[1].viewport=new Kn.a(.5,0,.5,1),this.rigCameras[1].outputRenderTarget=null},t.prototype.setTransformationFromNonVRCamera=function(e,n){e===void 0&&(e=this.getScene().activeCamera),n===void 0&&(n=!0),e&&e!==this&&(e.computeWorldMatrix().decompose(void 0,this.rotationQuaternion,this.position),this.position.y=0,u.b.FromEulerAnglesToRef(0,this.rotationQuaternion.toEulerAngles().y,0,this.rotationQuaternion),this._firstFrame=!0,n&&this._xrSessionManager.resetReferenceSpace())},t.prototype.getClassName=function(){return"WebXRCamera"},t.prototype._updateFromXRSession=function(){var e=this,n=this._xrSessionManager.currentFrame&&this._xrSessionManager.currentFrame.getViewerPose(this._xrSessionManager.referenceSpace);if(n){var i=n.emulatedPosition?tr.TRACKING_LOST:tr.TRACKING;if(this._setTrackingState(i),n.transform){var o=n.transform.position;this._referencedPosition.set(o.x,o.y,o.z);var a=n.transform.orientation;this._referenceQuaternion.set(a.x,a.y,a.z,a.w),this._scene.useRightHandedSystem||(this._referencedPosition.z*=-1,this._referenceQuaternion.z*=-1,this._referenceQuaternion.w*=-1),this._firstFrame?(this._firstFrame=!1,this.position.y+=this._referencedPosition.y,this._referenceQuaternion.copyFromFloats(0,0,0,1)):(this.rotationQuaternion.copyFrom(this._referenceQuaternion),this.position.copyFrom(this._referencedPosition))}this.rigCameras.length!==n.views.length&&this._updateNumberOfRigCameras(n.views.length),n.views.forEach(function(s,d){var p=e.rigCameras[d];p.isLeftCamera||p.isRightCamera||(s.eye==="right"?p._isRightCamera=!0:s.eye==="left"&&(p._isLeftCamera=!0));var b=s.transform.position,P=s.transform.orientation;if(p.position.set(b.x,b.y,b.z),p.rotationQuaternion.set(P.x,P.y,P.z,P.w),e._scene.useRightHandedSystem?p.rotationQuaternion.multiplyInPlace(e._rotate180):(p.position.z*=-1,p.rotationQuaternion.z*=-1,p.rotationQuaternion.w*=-1),u.a.FromFloat32ArrayToRefScaled(s.projectionMatrix,0,1,p._projectionMatrix),e._scene.useRightHandedSystem||p._projectionMatrix.toggleProjectionMatrixHandInPlace(),d===0&&e._projectionMatrix.copyFrom(p._projectionMatrix),e._xrSessionManager.session.renderState.baseLayer){var O=e._xrSessionManager.session.renderState.baseLayer.getViewport(s),B=e._xrSessionManager.session.renderState.baseLayer.framebufferWidth,F=e._xrSessionManager.session.renderState.baseLayer.framebufferHeight;p.viewport.width=O.width/B,p.viewport.height=O.height/F,p.viewport.x=O.x/B,p.viewport.y=O.y/F}p.outputRenderTarget=e._xrSessionManager.getRenderTargetTextureForEye(s.eye)})}else this._setTrackingState(tr.NOT_TRACKING)},t.prototype._updateNumberOfRigCameras=function(e){for(e===void 0&&(e=1);this.rigCameras.length<e;){var n=new Ni("XR-RigCamera: "+this.rigCameras.length,u.e.Zero(),this.getScene());n.minZ=.1,n.rotationQuaternion=new u.b,n.updateUpVectorFromRotation=!0,n.isRigCamera=!0,n.rigParent=this,n.freezeProjectionMatrix(),this.rigCameras.push(n)}for(;this.rigCameras.length>e;){var i=this.rigCameras.pop();i&&i.dispose()}},t.prototype._updateReferenceSpace=function(){this.position.equals(this._referencedPosition)&&this.rotationQuaternion.equals(this._referenceQuaternion)||(this.position.subtractToRef(this._referencedPosition,this._referencedPosition),this._referenceQuaternion.conjugateInPlace(),this._referenceQuaternion.multiplyToRef(this.rotationQuaternion,this._referenceQuaternion),this._updateReferenceSpaceOffset(this._referencedPosition,this._referenceQuaternion.normalize()))},t.prototype._updateReferenceSpaceOffset=function(e,n,i){if(i===void 0&&(i=!1),this._xrSessionManager.referenceSpace&&this._xrSessionManager.currentFrame){this._xrInvPositionCache.copyFrom(e),n?this._xrInvQuaternionCache.copyFrom(n):this._xrInvQuaternionCache.copyFromFloats(0,0,0,1),this._scene.useRightHandedSystem||(this._xrInvPositionCache.z*=-1,this._xrInvQuaternionCache.z*=-1,this._xrInvQuaternionCache.w*=-1),this._xrInvPositionCache.negateInPlace(),this._xrInvQuaternionCache.conjugateInPlace(),this._xrInvPositionCache.rotateByQuaternionToRef(this._xrInvQuaternionCache,this._xrInvPositionCache),i&&(this._xrInvPositionCache.y=0);var o=new XRRigidTransform({x:this._xrInvPositionCache.x,y:this._xrInvPositionCache.y,z:this._xrInvPositionCache.z},{x:this._xrInvQuaternionCache.x,y:this._xrInvQuaternionCache.y,z:this._xrInvQuaternionCache.z,w:this._xrInvQuaternionCache.w}),a=this._xrSessionManager.referenceSpace.getOffsetReferenceSpace(o),s=this._xrSessionManager.currentFrame&&this._xrSessionManager.currentFrame.getViewerPose(a);if(s){var d=new u.e(s.transform.position.x,s.transform.position.y,s.transform.position.z);this._scene.useRightHandedSystem||(d.z*=-1),this.position.subtractToRef(d,d),this._scene.useRightHandedSystem||(d.z*=-1),d.negateInPlace();var p=new XRRigidTransform({x:d.x,y:d.y,z:d.z});this._xrSessionManager.referenceSpace=a.getOffsetReferenceSpace(p)}}},t}(Yn),si=function(){function r(){}return r.ANCHOR_SYSTEM="xr-anchor-system",r.BACKGROUND_REMOVER="xr-background-remover",r.HIT_TEST="xr-hit-test",r.PHYSICS_CONTROLLERS="xr-physics-controller",r.PLANE_DETECTION="xr-plane-detection",r.POINTER_SELECTION="xr-controller-pointer-selection",r.TELEPORTATION="xr-controller-teleportation",r.FEATURE_POINTS="xr-feature-points",r.HAND_TRACKING="xr-hand-tracking",r}(),qn=function(){function r(t){var e=this;this._xrSessionManager=t,this._features={},this._xrSessionManager.onXRSessionInit.add(function(){e.getEnabledFeatures().forEach(function(n){var i=e._features[n];!i.enabled||i.featureImplementation.attached||i.featureImplementation.disableAutoAttach||e.attachFeature(n)})}),this._xrSessionManager.onXRSessionEnded.add(function(){e.getEnabledFeatures().forEach(function(n){var i=e._features[n];i.enabled&&i.featureImplementation.attached&&e.detachFeature(n)})})}return r.AddWebXRFeature=function(t,e,n,i){n===void 0&&(n=1),i===void 0&&(i=!1),this._AvailableFeatures[t]=this._AvailableFeatures[t]||{latest:n},n>this._AvailableFeatures[t].latest&&(this._AvailableFeatures[t].latest=n),i&&(this._AvailableFeatures[t].stable=n),this._AvailableFeatures[t][n]=e},r.ConstructFeature=function(t,e,n,i){e===void 0&&(e=1);var o=this._AvailableFeatures[t][e];if(!o)throw new Error("feature not found");return o(n,i)},r.GetAvailableFeatures=function(){return Object.keys(this._AvailableFeatures)},r.GetAvailableVersions=function(t){return Object.keys(this._AvailableFeatures[t])},r.GetLatestVersionOfFeature=function(t){return this._AvailableFeatures[t]&&this._AvailableFeatures[t].latest||-1},r.GetStableVersionOfFeature=function(t){return this._AvailableFeatures[t]&&this._AvailableFeatures[t].stable||-1},r.prototype.attachFeature=function(t){var e=this._features[t];e&&e.enabled&&!e.featureImplementation.attached&&e.featureImplementation.attach()},r.prototype.detachFeature=function(t){var e=this._features[t];e&&e.featureImplementation.attached&&e.featureImplementation.detach()},r.prototype.disableFeature=function(t){var e=typeof t=="string"?t:t.Name,n=this._features[e];return!(!n||!n.enabled)&&(n.enabled=!1,this.detachFeature(e),n.featureImplementation.dispose(),!0)},r.prototype.dispose=function(){var t=this;this.getEnabledFeatures().forEach(function(e){t.disableFeature(e),t._features[e].featureImplementation.dispose()})},r.prototype.enableFeature=function(t,e,n,i,o){var a=this;e===void 0&&(e="latest"),n===void 0&&(n={}),i===void 0&&(i=!0),o===void 0&&(o=!0);var s=typeof t=="string"?t:t.Name,d=0;if(typeof e=="string"){if(!e)throw new Error("Error in provided version - "+s+" ("+e+")");if((d=e==="stable"?r.GetStableVersionOfFeature(s):e==="latest"?r.GetLatestVersionOfFeature(s):+e)===-1||isNaN(d))throw new Error("feature not found - "+s+" ("+e+")")}else d=e;var p=this._features[s],b=r.ConstructFeature(s,d,this._xrSessionManager,n);if(!b)throw new Error("feature not found - "+s);p&&this.disableFeature(s);var P=b();if(P.dependsOn&&!P.dependsOn.every(function(O){return!!a._features[O]}))throw new Error("Dependant features missing. Make sure the following features are enabled - "+P.dependsOn.join(", "));if(P.isCompatible())return this._features[s]={featureImplementation:P,enabled:!0,version:d,required:o},i?this._xrSessionManager.session&&!this._features[s].featureImplementation.attached&&this.attachFeature(s):this._features[s].featureImplementation.disableAutoAttach=!0,this._features[s].featureImplementation;if(o)throw new Error("required feature not compatible");return Xe.b.Warn("Feature "+s+" not compatible with the current environment/browser and was not enabled."),P},r.prototype.getEnabledFeature=function(t){return this._features[t]&&this._features[t].featureImplementation},r.prototype.getEnabledFeatures=function(){return Object.keys(this._features)},r.prototype.extendXRSessionInitObject=function(t){var e=this;return this.getEnabledFeatures().forEach(function(n){var i=e._features[n],o=i.featureImplementation.xrNativeFeatureName;o&&(i.required?(t.requiredFeatures=t.requiredFeatures||[],t.requiredFeatures.indexOf(o)===-1&&t.requiredFeatures.push(o)):(t.optionalFeatures=t.optionalFeatures||[],t.optionalFeatures.indexOf(o)===-1&&t.optionalFeatures.push(o)))}),t},r._AvailableFeatures={},r}(),Tu=function(){function r(t){var e=this;this.scene=t,this._nonVRCamera=null,this._originalSceneAutoClear=!0,this._supported=!1,this.onInitialXRPoseSetObservable=new x.c,this.onStateChangedObservable=new x.c,this.state=pn.NOT_IN_XR,this.sessionManager=new _s(t),this.camera=new yu("",t,this.sessionManager),this.featuresManager=new qn(this.sessionManager),t.onDisposeObservable.add(function(){e.exitXRAsync()})}return r.CreateAsync=function(t){var e=new r(t);return e.sessionManager.initializeAsync().then(function(){return e._supported=!0,e}).catch(function(n){throw e._setState(pn.NOT_IN_XR),e.dispose(),n})},r.prototype.dispose=function(){this.camera.dispose(),this.onStateChangedObservable.clear(),this.onInitialXRPoseSetObservable.clear(),this.sessionManager.dispose(),this._nonVRCamera&&(this.scene.activeCamera=this._nonVRCamera)},r.prototype.enterXRAsync=function(t,e,n,i){var o=this;if(n===void 0&&(n=this.sessionManager.getWebXRRenderTarget()),i===void 0&&(i={}),!this._supported)throw"WebXR not supported in this browser or environment";return this._setState(pn.ENTERING_XR),e!=="viewer"&&e!=="local"&&(i.optionalFeatures=i.optionalFeatures||[],i.optionalFeatures.push(e)),this.featuresManager.extendXRSessionInitObject(i),t==="immersive-ar"&&e!=="unbounded"&&l.a.Warn("We recommend using 'unbounded' reference space type when using 'immersive-ar' session mode"),this.sessionManager.initializeSessionAsync(t,i).then(function(){return o.sessionManager.setReferenceSpaceTypeAsync(e)}).then(function(){return n.initializeXRLayerAsync(o.sessionManager.session)}).then(function(){return o.sessionManager.updateRenderStateAsync({depthFar:o.camera.maxZ,depthNear:o.camera.minZ,baseLayer:n.xrLayer})}).then(function(){return o.sessionManager.runXRRenderLoop(),o._originalSceneAutoClear=o.scene.autoClear,o._nonVRCamera=o.scene.activeCamera,o.scene.activeCamera=o.camera,t!=="immersive-ar"?o._nonXRToXRCamera():(o.scene.autoClear=!1,o.camera.compensateOnFirstFrame=!1),o.sessionManager.onXRSessionEnded.addOnce(function(){o.camera.rigCameras.forEach(function(a){a.outputRenderTarget=null}),o.scene.autoClear=o._originalSceneAutoClear,o.scene.activeCamera=o._nonVRCamera,t!=="immersive-ar"&&o.camera.compensateOnFirstFrame&&(o._nonVRCamera.setPosition?o._nonVRCamera.setPosition(o.camera.position):o._nonVRCamera.position.copyFrom(o.camera.position)),o._setState(pn.NOT_IN_XR)}),o.sessionManager.onXRFrameObservable.addOnce(function(){o._setState(pn.IN_XR)}),o.sessionManager}).catch(function(a){throw console.log(a),console.log(a.message),o._setState(pn.NOT_IN_XR),a})},r.prototype.exitXRAsync=function(){return this.state!==pn.IN_XR?Promise.resolve():(this._setState(pn.EXITING_XR),this.sessionManager.exitXRAsync())},r.prototype._nonXRToXRCamera=function(){this.camera.setTransformationFromNonVRCamera(this._nonVRCamera),this.onInitialXRPoseSetObservable.notifyObservers(this.camera)},r.prototype._setState=function(t){this.state!==t&&(this.state=t,this.onStateChangedObservable.notifyObservers(this.state))},r}(),xr=function(){function r(t,e,n,i){n===void 0&&(n=-1),i===void 0&&(i=[]),this.id=t,this.type=e,this._buttonIndex=n,this._axesIndices=i,this._axes={x:0,y:0},this._changes={},this._currentValue=0,this._hasChanges=!1,this._pressed=!1,this._touched=!1,this.onAxisValueChangedObservable=new x.c,this.onButtonStateChangedObservable=new x.c}return Object.defineProperty(r.prototype,"axes",{get:function(){return this._axes},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"changes",{get:function(){return this._changes},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hasChanges",{get:function(){return this._hasChanges},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"pressed",{get:function(){return this._pressed},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"touched",{get:function(){return this._touched},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"value",{get:function(){return this._currentValue},enumerable:!1,configurable:!0}),r.prototype.dispose=function(){this.onAxisValueChangedObservable.clear(),this.onButtonStateChangedObservable.clear()},r.prototype.isAxes=function(){return this._axesIndices.length!==0},r.prototype.isButton=function(){return this._buttonIndex!==-1},r.prototype.update=function(t){var e=!1,n=!1;if(this._hasChanges=!1,this._changes={},this.isButton()){var i=t.buttons[this._buttonIndex];if(!i)return;this._currentValue!==i.value&&(this.changes.value={current:i.value,previous:this._currentValue},e=!0,this._currentValue=i.value),this._touched!==i.touched&&(this.changes.touched={current:i.touched,previous:this._touched},e=!0,this._touched=i.touched),this._pressed!==i.pressed&&(this.changes.pressed={current:i.pressed,previous:this._pressed},e=!0,this._pressed=i.pressed)}this.isAxes()&&(this._axes.x!==t.axes[this._axesIndices[0]]&&(this.changes.axes={current:{x:t.axes[this._axesIndices[0]],y:this._axes.y},previous:{x:this._axes.x,y:this._axes.y}},this._axes.x=t.axes[this._axesIndices[0]],n=!0),this._axes.y!==t.axes[this._axesIndices[1]]&&(this.changes.axes?this.changes.axes.current.y=t.axes[this._axesIndices[1]]:this.changes.axes={current:{x:this._axes.x,y:t.axes[this._axesIndices[1]]},previous:{x:this._axes.x,y:this._axes.y}},this._axes.y=t.axes[this._axesIndices[1]],n=!0)),e&&(this._hasChanges=!0,this.onButtonStateChangedObservable.notifyObservers(this)),n&&(this._hasChanges=!0,this.onAxisValueChangedObservable.notifyObservers(this._axes))},r.BUTTON_TYPE="button",r.SQUEEZE_TYPE="squeeze",r.THUMBSTICK_TYPE="thumbstick",r.TOUCHPAD_TYPE="touchpad",r.TRIGGER_TYPE="trigger",r}(),Rr=function(){function r(t,e,n,i,o){var a=this;this.scene=t,this.layout=e,this.gamepadObject=n,this.handedness=i,this._initComponent=function(s){if(s){var d=a.layout.components[s],p=d.type,b=d.gamepadIndices.button,P=[];d.gamepadIndices.xAxis!==void 0&&d.gamepadIndices.yAxis!==void 0&&P.push(d.gamepadIndices.xAxis,d.gamepadIndices.yAxis),a.components[s]=new xr(s,p,b,P)}},this._modelReady=!1,this.components={},this.disableAnimation=!1,this.onModelLoadedObservable=new x.c,e.components&&Object.keys(e.components).forEach(this._initComponent)}return r.prototype.dispose=function(){var t=this;this.getComponentIds().forEach(function(e){return t.getComponent(e).dispose()}),this.rootMesh&&this.rootMesh.dispose()},r.prototype.getAllComponentsOfType=function(t){var e=this;return this.getComponentIds().map(function(n){return e.components[n]}).filter(function(n){return n.type===t})},r.prototype.getComponent=function(t){return this.components[t]},r.prototype.getComponentIds=function(){return Object.keys(this.components)},r.prototype.getComponentOfType=function(t){return this.getAllComponentsOfType(t)[0]||null},r.prototype.getMainComponent=function(){return this.getComponent(this.layout.selectComponentId)},r.prototype.loadModel=function(){return Object(c.b)(this,void 0,void 0,function(){var t,e,n=this;return Object(c.e)(this,function(i){return t=!this._getModelLoadingConstraints(),e=this._getGenericFilenameAndPath(),t?l.a.Warn("Falling back to generic models"):e=this._getFilenameAndPath(),[2,new Promise(function(o,a){Ut.ImportMesh("",e.path,e.filename,n.scene,function(s){t?n._getGenericParentMesh(s):n._setRootMesh(s),n._processLoadedModel(s),n._modelReady=!0,n.onModelLoadedObservable.notifyObservers(n),o(!0)},null,function(s,d){l.a.Log(d),l.a.Warn("Failed to retrieve controller model of type "+n.profileId+" from the remote server: "+e.path+e.filename),a(d)})})]})})},r.prototype.updateFromXRFrame=function(t){var e=this;this.getComponentIds().forEach(function(n){return e.getComponent(n).update(e.gamepadObject)}),this.updateModel(t)},Object.defineProperty(r.prototype,"handness",{get:function(){return this.handedness},enumerable:!1,configurable:!0}),r.prototype.pulse=function(t,e,n){return n===void 0&&(n=0),this.gamepadObject.hapticActuators&&this.gamepadObject.hapticActuators[n]?this.gamepadObject.hapticActuators[n].pulse(t,e):Promise.resolve(!1)},r.prototype._getChildByName=function(t,e){return t.getChildren(function(n){return n.name===e},!1)[0]},r.prototype._getImmediateChildByName=function(t,e){return t.getChildren(function(n){return n.name==e},!0)[0]},r.prototype._lerpTransform=function(t,e,n){if(t.minMesh&&t.maxMesh&&t.valueMesh&&t.minMesh.rotationQuaternion&&t.maxMesh.rotationQuaternion&&t.valueMesh.rotationQuaternion){var i=n?.5*e+.5:e;u.b.SlerpToRef(t.minMesh.rotationQuaternion,t.maxMesh.rotationQuaternion,i,t.valueMesh.rotationQuaternion),u.e.LerpToRef(t.minMesh.position,t.maxMesh.position,i,t.valueMesh.position)}},r.prototype.updateModel=function(t){this._modelReady&&this._updateModel(t)},r.prototype._getGenericFilenameAndPath=function(){return{filename:"generic.babylon",path:"https://controllers.babylonjs.com/generic/"}},r.prototype._getGenericParentMesh=function(t){var e=this;this.rootMesh=new De.a(this.profileId+" "+this.handedness,this.scene),t.forEach(function(n){n.parent||(n.isPickable=!1,n.setParent(e.rootMesh))}),this.rootMesh.rotationQuaternion=u.b.FromEulerAngles(0,Math.PI,0)},r}(),Vs=function(r){function t(e,n,i){var o=r.call(this,e,f_[i],n,i)||this;return o.profileId=t.ProfileId,o}return Object(c.d)(t,r),t.prototype._getFilenameAndPath=function(){return{filename:"generic.babylon",path:"https://controllers.babylonjs.com/generic/"}},t.prototype._getModelLoadingConstraints=function(){return!0},t.prototype._processLoadedModel=function(e){},t.prototype._setRootMesh=function(e){var n=this;this.rootMesh=new De.a(this.profileId+" "+this.handedness,this.scene),e.forEach(function(i){i.isPickable=!1,i.parent||i.setParent(n.rootMesh)}),this.rootMesh.rotationQuaternion=u.b.FromEulerAngles(0,Math.PI,0)},t.prototype._updateModel=function(){},t.ProfileId="generic-trigger",t}(Rr),f_={left:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{}}},gamepadMapping:"xr-standard",rootNodeName:"generic-trigger-left",assetPath:"left.glb"},right:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{}}},gamepadMapping:"xr-standard",rootNodeName:"generic-trigger-right",assetPath:"right.glb"},none:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{}}},gamepadMapping:"xr-standard",rootNodeName:"generic-trigger-none",assetPath:"none.glb"}},Eu=function(r){function t(e,n,i,o){var a=r.call(this,e,i.layouts[n.handedness||"none"],n.gamepad,n.handedness)||this;return a._repositoryUrl=o,a._buttonMeshMapping={},a._touchDots={},a.profileId=i.profileId,a}return Object(c.d)(t,r),t.prototype.dispose=function(){var e=this;r.prototype.dispose.call(this),Object.keys(this._touchDots).forEach(function(n){e._touchDots[n].dispose()})},t.prototype._getFilenameAndPath=function(){return{filename:this.layout.assetPath,path:this._repositoryUrl+"/profiles/"+this.profileId+"/"}},t.prototype._getModelLoadingConstraints=function(){var e=Ut.IsPluginForExtensionAvailable(".glb");return e||l.a.Warn("glTF / glb loaded was not registered, using generic controller instead"),e},t.prototype._processLoadedModel=function(e){var n=this;this.getComponentIds().forEach(function(i){var o=n.layout.components[i];n._buttonMeshMapping[i]={mainMesh:n._getChildByName(n.rootMesh,o.rootNodeName),states:{}},Object.keys(o.visualResponses).forEach(function(a){var s=o.visualResponses[a];if(s.valueNodeProperty==="transform")n._buttonMeshMapping[i].states[a]={valueMesh:n._getChildByName(n.rootMesh,s.valueNodeName),minMesh:n._getChildByName(n.rootMesh,s.minNodeName),maxMesh:n._getChildByName(n.rootMesh,s.maxNodeName)};else{var d=o.type===xr.TOUCHPAD_TYPE&&o.touchPointNodeName?o.touchPointNodeName:s.valueNodeName;if(n._buttonMeshMapping[i].states[a]={valueMesh:n._getChildByName(n.rootMesh,d)},o.type===xr.TOUCHPAD_TYPE&&!n._touchDots[a]){var p=Fn.a.CreateSphere(a+"dot",{diameter:.0015,segments:8},n.scene);p.material=new Ft.a(a+"mat",n.scene),p.material.diffuseColor=M.a.Red(),p.parent=n._buttonMeshMapping[i].states[a].valueMesh||null,p.isVisible=!1,n._touchDots[a]=p}}})})},t.prototype._setRootMesh=function(e){var n;this.rootMesh=new De.a(this.profileId+"-"+this.handedness,this.scene),this.rootMesh.isPickable=!1;for(var i=0;i<e.length;i++){var o=e[i];o.isPickable=!1,o.parent||(n=o)}n&&n.setParent(this.rootMesh),this.scene.useRightHandedSystem||this.rootMesh.rotate(ye.a.Y,Math.PI,ye.c.WORLD)},t.prototype._updateModel=function(e){var n=this;this.disableAnimation||this.getComponentIds().forEach(function(i){var o=n.getComponent(i);if(o.hasChanges){var a=n._buttonMeshMapping[i],s=n.layout.components[i];Object.keys(s.visualResponses).forEach(function(d){var p=s.visualResponses[d],b=o.value;if(p.componentProperty==="xAxis"?b=o.axes.x:p.componentProperty==="yAxis"&&(b=o.axes.y),p.valueNodeProperty==="transform")n._lerpTransform(a.states[d],b,p.componentProperty!=="button");else{var P=a.states[d].valueMesh;P&&(P.isVisible=o.touched||o.pressed),n._touchDots[d]&&(n._touchDots[d].isVisible=o.touched||o.pressed)}})}})},t}(Rr),Bn=function(){function r(){}return r.ClearProfilesCache=function(){this._ProfilesList=null,this._ProfileLoadingPromises={}},r.DefaultFallbacks=function(){this.RegisterFallbacksForProfileId("google-daydream",["generic-touchpad"]),this.RegisterFallbacksForProfileId("htc-vive-focus",["generic-trigger-touchpad"]),this.RegisterFallbacksForProfileId("htc-vive",["generic-trigger-squeeze-touchpad"]),this.RegisterFallbacksForProfileId("magicleap-one",["generic-trigger-squeeze-touchpad"]),this.RegisterFallbacksForProfileId("windows-mixed-reality",["generic-trigger-squeeze-touchpad-thumbstick"]),this.RegisterFallbacksForProfileId("microsoft-mixed-reality",["windows-mixed-reality","generic-trigger-squeeze-touchpad-thumbstick"]),this.RegisterFallbacksForProfileId("oculus-go",["generic-trigger-touchpad"]),this.RegisterFallbacksForProfileId("oculus-touch-v2",["oculus-touch","generic-trigger-squeeze-thumbstick"]),this.RegisterFallbacksForProfileId("oculus-touch",["generic-trigger-squeeze-thumbstick"]),this.RegisterFallbacksForProfileId("samsung-gearvr",["windows-mixed-reality","generic-trigger-squeeze-touchpad-thumbstick"]),this.RegisterFallbacksForProfileId("samsung-odyssey",["generic-touchpad"]),this.RegisterFallbacksForProfileId("valve-index",["generic-trigger-squeeze-touchpad-thumbstick"])},r.FindFallbackWithProfileId=function(t){var e=this._Fallbacks[t]||[];return e.unshift(t),e},r.GetMotionControllerWithXRInput=function(t,e,n){var i=this,o=[];if(n&&o.push(n),o.push.apply(o,t.profiles||[]),o.length&&!o[0]&&o.pop(),t.gamepad&&t.gamepad.id)switch(t.gamepad.id){case(t.gamepad.id.match(/oculus touch/gi)?t.gamepad.id:void 0):o.push("oculus-touch-v2")}var a=o.indexOf("windows-mixed-reality");if(a!==-1&&o.splice(a,0,"microsoft-mixed-reality"),o.length||o.push("generic-trigger"),this.UseOnlineRepository){var s=this.PrioritizeOnlineRepository?this._LoadProfileFromRepository:this._LoadProfilesFromAvailableControllers,d=this.PrioritizeOnlineRepository?this._LoadProfilesFromAvailableControllers:this._LoadProfileFromRepository;return s.call(this,o,t,e).catch(function(){return d.call(i,o,t,e)})}return this._LoadProfilesFromAvailableControllers(o,t,e)},r.RegisterController=function(t,e){this._AvailableControllers[t]=e},r.RegisterFallbacksForProfileId=function(t,e){var n;this._Fallbacks[t]?(n=this._Fallbacks[t]).push.apply(n,e):this._Fallbacks[t]=e},r.UpdateProfilesList=function(){return this._ProfilesList=Xe.b.LoadFileAsync(this.BaseRepositoryUrl+"/profiles/profilesList.json",!1).then(function(t){return JSON.parse(t.toString())}),this._ProfilesList},r._LoadProfileFromRepository=function(t,e,n){var i=this;return Promise.resolve().then(function(){return i._ProfilesList?i._ProfilesList:i.UpdateProfilesList()}).then(function(o){for(var a=0;a<t.length;++a)if(t[a]&&o[t[a]])return t[a];throw new Error("neither controller "+t[0]+" nor all fallbacks were found in the repository,")}).then(function(o){return i._ProfileLoadingPromises[o]||(i._ProfileLoadingPromises[o]=Xe.b.LoadFileAsync(i.BaseRepositoryUrl+"/profiles/"+o+"/profile.json",!1).then(function(a){return JSON.parse(a)})),i._ProfileLoadingPromises[o]}).then(function(o){return new Eu(n,e,o,i.BaseRepositoryUrl)})},r._LoadProfilesFromAvailableControllers=function(t,e,n){for(var i=0;i<t.length;++i)if(t[i])for(var o=this.FindFallbackWithProfileId(t[i]),a=0;a<o.length;++a){var s=this._AvailableControllers[o[a]];if(s)return Promise.resolve(s(e,n))}throw new Error("no controller requested was found in the available controllers list")},r._AvailableControllers={},r._Fallbacks={},r._ProfileLoadingPromises={},r.BaseRepositoryUrl="https://immersive-web.github.io/webxr-input-profiles/packages/viewer/dist",r.PrioritizeOnlineRepository=!0,r.UseOnlineRepository=!0,r}();Bn.RegisterController(Vs.ProfileId,function(r,t){return new Vs(t,r.gamepad,r.handedness)}),Bn.DefaultFallbacks();var p_=0,Su=function(){function r(t,e,n){var i=this;n===void 0&&(n={}),this._scene=t,this.inputSource=e,this._options=n,this._tmpVector=new u.e,this._disposed=!1,this.onDisposeObservable=new x.c,this.onMeshLoadedObservable=new x.c,this.onMotionControllerInitObservable=new x.c,this._uniqueId="controller-"+p_+++"-"+e.targetRayMode+"-"+e.handedness,this.pointer=new Dt.a(this._uniqueId+"-pointer",t),this.pointer.rotationQuaternion=new u.b,this.inputSource.gripSpace&&(this.grip=new Dt.a(this._uniqueId+"-grip",this._scene),this.grip.rotationQuaternion=new u.b),this._tmpVector.set(0,0,this._scene.useRightHandedSystem?-1:1),this.inputSource.gamepad&&Bn.GetMotionControllerWithXRInput(e,t,this._options.forceControllerProfile).then(function(o){i.motionController=o,i.onMotionControllerInitObservable.notifyObservers(o),i._options.doNotLoadControllerMesh||i.motionController.loadModel().then(function(a){var s;a&&i.motionController&&i.motionController.rootMesh&&(i._options.renderingGroupId&&(i.motionController.rootMesh.renderingGroupId=i._options.renderingGroupId,i.motionController.rootMesh.getChildMeshes(!1).forEach(function(d){return d.renderingGroupId=i._options.renderingGroupId})),i.onMeshLoadedObservable.notifyObservers(i.motionController.rootMesh),i.motionController.rootMesh.parent=i.grip||i.pointer,i.motionController.disableAnimation=!!i._options.disableMotionControllerAnimation),i._disposed&&((s=i.motionController)===null||s===void 0||s.dispose())})},function(){Xe.b.Warn("Could not find a matching motion controller for the registered input source")})}return Object.defineProperty(r.prototype,"uniqueId",{get:function(){return this._uniqueId},enumerable:!1,configurable:!0}),r.prototype.dispose=function(){this.grip&&this.grip.dispose(),this.motionController&&this.motionController.dispose(),this.pointer.dispose(),this.onMotionControllerInitObservable.clear(),this.onMeshLoadedObservable.clear(),this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear(),this._disposed=!0},r.prototype.getWorldPointerRayToRef=function(t,e){e===void 0&&(e=!1);var n=e&&this.grip?this.grip:this.pointer;u.e.TransformNormalToRef(this._tmpVector,n.getWorldMatrix(),t.direction),t.direction.normalize(),t.origin.copyFrom(n.absolutePosition),t.length=1e3},r.prototype.updateFromXRFrame=function(t,e){var n=t.getPose(this.inputSource.targetRaySpace,e);if(n){var i=n.transform.position;this.pointer.position.set(i.x,i.y,i.z);var o=n.transform.orientation;this.pointer.rotationQuaternion.set(o.x,o.y,o.z,o.w),this._scene.useRightHandedSystem||(this.pointer.position.z*=-1,this.pointer.rotationQuaternion.z*=-1,this.pointer.rotationQuaternion.w*=-1)}if(this.inputSource.gripSpace&&this.grip){var a=t.getPose(this.inputSource.gripSpace,e);if(a){i=a.transform.position;var s=a.transform.orientation;this.grip.position.set(i.x,i.y,i.z),this.grip.rotationQuaternion.set(s.x,s.y,s.z,s.w),this._scene.useRightHandedSystem||(this.grip.position.z*=-1,this.grip.rotationQuaternion.z*=-1,this.grip.rotationQuaternion.w*=-1)}}this.motionController&&this.motionController.updateFromXRFrame(t)},r}(),Au=function(){function r(t,e,n){var i=this;if(n===void 0&&(n={}),this.xrSessionManager=t,this.xrCamera=e,this.options=n,this.controllers=[],this.onControllerAddedObservable=new x.c,this.onControllerRemovedObservable=new x.c,this._onInputSourcesChange=function(o){i._addAndRemoveControllers(o.added,o.removed)},this._sessionEndedObserver=this.xrSessionManager.onXRSessionEnded.add(function(){i._addAndRemoveControllers([],i.controllers.map(function(o){return o.inputSource}))}),this._sessionInitObserver=this.xrSessionManager.onXRSessionInit.add(function(o){o.addEventListener("inputsourceschange",i._onInputSourcesChange)}),this._frameObserver=this.xrSessionManager.onXRFrameObservable.add(function(o){i.controllers.forEach(function(a){a.updateFromXRFrame(o,i.xrSessionManager.referenceSpace)})}),this.options.customControllersRepositoryURL&&(Bn.BaseRepositoryUrl=this.options.customControllersRepositoryURL),Bn.UseOnlineRepository=!this.options.disableOnlineControllerRepository,Bn.UseOnlineRepository)try{Bn.UpdateProfilesList().catch(function(){Bn.UseOnlineRepository=!1})}catch{Bn.UseOnlineRepository=!1}}return r.prototype._addAndRemoveControllers=function(t,e){for(var n=this,i=this.controllers.map(function(P){return P.inputSource}),o=0,a=t;o<a.length;o++){var s=a[o];if(i.indexOf(s)===-1){var d=new Su(this.xrSessionManager.scene,s,Object(c.a)(Object(c.a)({},this.options.controllerOptions||{}),{forceControllerProfile:this.options.forceInputProfile,doNotLoadControllerMesh:this.options.doNotLoadControllerMeshes,disableMotionControllerAnimation:this.options.disableControllerAnimation}));this.controllers.push(d),this.onControllerAddedObservable.notifyObservers(d)}}var p=[],b=[];this.controllers.forEach(function(P){e.indexOf(P.inputSource)===-1?p.push(P):b.push(P)}),this.controllers=p,b.forEach(function(P){n.onControllerRemovedObservable.notifyObservers(P),P.dispose()})},r.prototype.dispose=function(){this.controllers.forEach(function(t){t.dispose()}),this.xrSessionManager.onXRFrameObservable.remove(this._frameObserver),this.xrSessionManager.onXRSessionInit.remove(this._sessionInitObserver),this.xrSessionManager.onXRSessionEnded.remove(this._sessionEndedObserver),this.onControllerAddedObservable.clear(),this.onControllerRemovedObservable.clear()},r}(),ci=function(){function r(t){this._xrSessionManager=t,this._attached=!1,this._removeOnDetach=[],this.isDisposed=!1,this.disableAutoAttach=!1,this.xrNativeFeatureName=""}return Object.defineProperty(r.prototype,"attached",{get:function(){return this._attached},enumerable:!1,configurable:!0}),r.prototype.attach=function(t){var e=this;if(this.isDisposed)return!1;if(t)this.attached&&this.detach();else if(this.attached)return!1;return this._attached=!0,this._addNewAttachObserver(this._xrSessionManager.onXRFrameObservable,function(n){return e._onXRFrame(n)}),!0},r.prototype.detach=function(){return this._attached?(this._attached=!1,this._removeOnDetach.forEach(function(t){t.observable.remove(t.observer)}),!0):(this.disableAutoAttach=!0,!1)},r.prototype.dispose=function(){this.detach(),this.isDisposed=!0},r.prototype.isCompatible=function(){return!0},r.prototype._addNewAttachObserver=function(t,e){this._removeOnDetach.push({observable:t,observer:t.add(e)})},r}(),ho=function(r){function t(e,n){var i=r.call(this,e)||this;return i._options=n,i._attachController=function(o){if(!i._controllers[o.uniqueId]){var a=i._generateNewMeshPair(o.pointer),s=a.laserPointer,d=a.selectionMesh;switch(i._controllers[o.uniqueId]={xrController:o,laserPointer:s,selectionMesh:d,meshUnderPointer:null,pick:null,tmpRay:new fn.a(new u.e,new u.e),id:t._idCounter++},i._attachedController?!i._options.enablePointerSelectionOnAllControllers&&i._options.preferredHandedness&&o.inputSource.handedness===i._options.preferredHandedness&&(i._attachedController=o.uniqueId):i._options.enablePointerSelectionOnAllControllers||(i._attachedController=o.uniqueId),o.inputSource.targetRayMode){case"tracked-pointer":return i._attachTrackedPointerRayMode(o);case"gaze":return i._attachGazeMode(o);case"screen":return i._attachScreenRayMode(o)}}},i._controllers={},i._tmpVectorForPickCompare=new u.e,i.disablePointerLighting=!0,i.disableSelectionMeshLighting=!0,i.displayLaserPointer=!0,i.displaySelectionMesh=!0,i.laserPointerPickedColor=new M.a(.9,.9,.9),i.laserPointerDefaultColor=new M.a(.7,.7,.7),i.selectionMeshDefaultColor=new M.a(.8,.8,.8),i.selectionMeshPickedColor=new M.a(.3,.3,1),i._identityMatrix=u.a.Identity(),i._screenCoordinatesRef=u.e.Zero(),i._viewportRef=new Kn.a(0,0,0,0),i._scene=i._xrSessionManager.scene,i}return Object(c.d)(t,r),t.prototype.attach=function(){var e=this;if(!r.prototype.attach.call(this))return!1;if(this._options.xrInput.controllers.forEach(this._attachController),this._addNewAttachObserver(this._options.xrInput.onControllerAddedObservable,this._attachController),this._addNewAttachObserver(this._options.xrInput.onControllerRemovedObservable,function(s){e._detachController(s.uniqueId)}),this._scene.constantlyUpdateMeshUnderPointer=!0,this._options.gazeCamera){var n=this._options.gazeCamera,i=this._generateNewMeshPair(n),o=i.laserPointer,a=i.selectionMesh;this._controllers.camera={webXRCamera:n,laserPointer:o,selectionMesh:a,meshUnderPointer:null,pick:null,tmpRay:new fn.a(new u.e,new u.e),id:t._idCounter++},this._attachGazeMode()}return!0},t.prototype.detach=function(){var e=this;return!!r.prototype.detach.call(this)&&(Object.keys(this._controllers).forEach(function(n){e._detachController(n)}),!0)},t.prototype.getMeshUnderPointer=function(e){return this._controllers[e]?this._controllers[e].meshUnderPointer:null},t.prototype.getXRControllerByPointerId=function(e){for(var n=Object.keys(this._controllers),i=0;i<n.length;++i)if(this._controllers[n[i]].id===e)return this._controllers[n[i]].xrController||null;return null},t.prototype._onXRFrame=function(e){var n=this;Object.keys(this._controllers).forEach(function(i){var o,a=n._controllers[i];if(!n._options.enablePointerSelectionOnAllControllers&&i!==n._attachedController)return a.selectionMesh.isVisible=!1,a.laserPointer.isVisible=!1,void(a.pick=null);if(a.laserPointer.isVisible=n.displayLaserPointer,a.xrController)o=a.xrController.pointer.position,a.xrController.getWorldPointerRayToRef(a.tmpRay);else{if(!a.webXRCamera)return;o=a.webXRCamera.position,a.webXRCamera.getForwardRayToRef(a.tmpRay)}if(n._options.maxPointerDistance&&(a.tmpRay.length=n._options.maxPointerDistance),!n._options.disableScenePointerVectorUpdate&&o){var s=n._xrSessionManager.scene,d=n._options.xrInput.xrCamera;d&&(d.viewport.toGlobalToRef(s.getEngine().getRenderWidth(),s.getEngine().getRenderHeight(),n._viewportRef),u.e.ProjectToRef(o,n._identityMatrix,s.getTransformMatrix(),n._viewportRef,n._screenCoordinatesRef),s.pointerX=n._screenCoordinatesRef.x,s.pointerY=n._screenCoordinatesRef.y)}a.pick=n._scene.pickWithRay(a.tmpRay,n._scene.pointerMovePredicate||n.raySelectionPredicate);var p=a.pick;if(p&&p.pickedPoint&&p.hit){n._updatePointerDistance(a.laserPointer,p.distance),a.selectionMesh.position.copyFrom(p.pickedPoint),a.selectionMesh.scaling.x=Math.sqrt(p.distance),a.selectionMesh.scaling.y=Math.sqrt(p.distance),a.selectionMesh.scaling.z=Math.sqrt(p.distance);var b=n._convertNormalToDirectionOfRay(p.getNormal(!0),a.tmpRay);if(a.selectionMesh.position.copyFrom(p.pickedPoint),b){var P=u.e.Cross(ye.a.Y,b),O=u.e.Cross(b,P);u.e.RotationFromAxisToRef(O,b,P,a.selectionMesh.rotation),a.selectionMesh.position.addInPlace(b.scale(.001))}a.selectionMesh.isVisible=n.displaySelectionMesh,a.meshUnderPointer=p.pickedMesh}else a.selectionMesh.isVisible=!1,n._updatePointerDistance(a.laserPointer,1),a.meshUnderPointer=null})},t.prototype._attachGazeMode=function(e){var n=this,i=this._controllers[e&&e.uniqueId||"camera"],o=this._options.timeToSelect||3e3,a=this._options.useUtilityLayer?this._options.customUtilityLayerScene||On.a.DefaultUtilityLayer.utilityLayerScene:this._scene,s=new nr.a,d=gr.CreateTorus("selection",{diameter:.0525,thickness:.015,tessellation:20},a);d.isVisible=!1,d.isPickable=!1,d.parent=i.selectionMesh;var p=0,b=!1;i.onFrameObserver=this._xrSessionManager.onXRFrameObservable.add(function(){if(i.pick){if(i.laserPointer.material.alpha=0,d.isVisible=!1,i.pick.hit)if(n._pickingMoved(s,i.pick))b&&(n._options.disablePointerUpOnTouchOut||n._scene.simulatePointerUp(i.pick,{pointerId:i.id})),b=!1,p=0;else if(p>o/10&&(d.isVisible=!0),(p+=n._scene.getEngine().getDeltaTime())>=o)n._scene.simulatePointerDown(i.pick,{pointerId:i.id}),b=!0,n._options.disablePointerUpOnTouchOut&&n._scene.simulatePointerUp(i.pick,{pointerId:i.id}),d.isVisible=!1;else{var P=1-p/o;d.scaling.set(P,P,P)}else b=!1,p=0;n._scene.simulatePointerMove(i.pick,{pointerId:i.id}),s=i.pick}}),this._options.renderingGroupId!==void 0&&(d.renderingGroupId=this._options.renderingGroupId),e&&e.onDisposeObservable.addOnce(function(){i.pick&&!n._options.disablePointerUpOnTouchOut&&b&&n._scene.simulatePointerUp(i.pick,{pointerId:i.id}),d.dispose()})},t.prototype._attachScreenRayMode=function(e){var n=this,i=this._controllers[e.uniqueId],o=!1;i.onFrameObserver=this._xrSessionManager.onXRFrameObservable.add(function(){!i.pick||n._options.disablePointerUpOnTouchOut&&o||(o?n._scene.simulatePointerMove(i.pick,{pointerId:i.id}):(n._scene.simulatePointerDown(i.pick,{pointerId:i.id}),o=!0,n._options.disablePointerUpOnTouchOut&&n._scene.simulatePointerUp(i.pick,{pointerId:i.id})))}),e.onDisposeObservable.addOnce(function(){i.pick&&o&&!n._options.disablePointerUpOnTouchOut&&n._scene.simulatePointerUp(i.pick,{pointerId:i.id})})},t.prototype._attachTrackedPointerRayMode=function(e){var n=this,i=this._controllers[e.uniqueId];if(this._options.forceGazeMode)return this._attachGazeMode(e);if(i.onFrameObserver=this._xrSessionManager.onXRFrameObservable.add(function(){i.laserPointer.material.disableLighting=n.disablePointerLighting,i.selectionMesh.material.disableLighting=n.disableSelectionMeshLighting,i.pick&&n._scene.simulatePointerMove(i.pick,{pointerId:i.id})}),e.inputSource.gamepad){var o=function(d){n._options.overrideButtonId&&(i.selectionComponent=d.getComponent(n._options.overrideButtonId)),i.selectionComponent||(i.selectionComponent=d.getMainComponent()),i.onButtonChangedObserver=i.selectionComponent.onButtonStateChangedObservable.add(function(p){if(p.changes.pressed){var b=p.changes.pressed.current;i.pick?(n._options.enablePointerSelectionOnAllControllers||e.uniqueId===n._attachedController)&&(b?(n._scene.simulatePointerDown(i.pick,{pointerId:i.id}),i.selectionMesh.material.emissiveColor=n.selectionMeshPickedColor,i.laserPointer.material.emissiveColor=n.laserPointerPickedColor):(n._scene.simulatePointerUp(i.pick,{pointerId:i.id}),i.selectionMesh.material.emissiveColor=n.selectionMeshDefaultColor,i.laserPointer.material.emissiveColor=n.laserPointerDefaultColor)):!b||n._options.enablePointerSelectionOnAllControllers||n._options.disableSwitchOnClick||(n._attachedController=e.uniqueId)}})};e.motionController?o(e.motionController):e.onMotionControllerInitObservable.add(o)}else{var a=function(d){i.xrController&&d.inputSource===i.xrController.inputSource&&i.pick&&(n._scene.simulatePointerDown(i.pick,{pointerId:i.id}),i.selectionMesh.material.emissiveColor=n.selectionMeshPickedColor,i.laserPointer.material.emissiveColor=n.laserPointerPickedColor)},s=function(d){i.xrController&&d.inputSource===i.xrController.inputSource&&i.pick&&(n._scene.simulatePointerUp(i.pick,{pointerId:i.id}),i.selectionMesh.material.emissiveColor=n.selectionMeshDefaultColor,i.laserPointer.material.emissiveColor=n.laserPointerDefaultColor)};i.eventListeners={selectend:s,selectstart:a},this._xrSessionManager.session.addEventListener("selectstart",a),this._xrSessionManager.session.addEventListener("selectend",s)}},t.prototype._convertNormalToDirectionOfRay=function(e,n){return e&&Math.acos(u.e.Dot(e,n.direction))<Math.PI/2&&e.scaleInPlace(-1),e},t.prototype._detachController=function(e){var n=this,i=this._controllers[e];if(i&&(i.selectionComponent&&i.onButtonChangedObserver&&i.selectionComponent.onButtonStateChangedObservable.remove(i.onButtonChangedObserver),i.onFrameObserver&&this._xrSessionManager.onXRFrameObservable.remove(i.onFrameObserver),i.eventListeners&&Object.keys(i.eventListeners).forEach(function(a){var s=i.eventListeners&&i.eventListeners[a];s&&n._xrSessionManager.session.removeEventListener(a,s)}),i.selectionMesh.dispose(),i.laserPointer.dispose(),delete this._controllers[e],this._attachedController===e)){var o=Object.keys(this._controllers);o.length?this._attachedController=o[0]:this._attachedController=""}},t.prototype._generateNewMeshPair=function(e){var n=this._options.useUtilityLayer?this._options.customUtilityLayerScene||On.a.DefaultUtilityLayer.utilityLayerScene:this._scene,i=pi.a.CreateCylinder("laserPointer",{height:1,diameterTop:2e-4,diameterBottom:.004,tessellation:20,subdivisions:1},n);i.parent=e;var o=new Ft.a("laserPointerMat",n);o.emissiveColor=this.laserPointerDefaultColor,o.alpha=.7,i.material=o,i.rotation.x=Math.PI/2,this._updatePointerDistance(i,1),i.isPickable=!1;var a=gr.CreateTorus("gazeTracker",{diameter:.0105,thickness:.0075,tessellation:20},n);a.bakeCurrentTransformIntoVertices(),a.isPickable=!1,a.isVisible=!1;var s=new Ft.a("targetMat",n);return s.specularColor=M.a.Black(),s.emissiveColor=this.selectionMeshDefaultColor,s.backFaceCulling=!1,a.material=s,this._options.renderingGroupId!==void 0&&(i.renderingGroupId=this._options.renderingGroupId,a.renderingGroupId=this._options.renderingGroupId),{laserPointer:i,selectionMesh:a}},t.prototype._pickingMoved=function(e,n){var i;if(!e.hit||!n.hit||!(e.pickedMesh&&e.pickedPoint&&n.pickedMesh&&n.pickedPoint)||e.pickedMesh!==n.pickedMesh)return!0;(i=e.pickedPoint)===null||i===void 0||i.subtractToRef(n.pickedPoint,this._tmpVectorForPickCompare),this._tmpVectorForPickCompare.set(Math.abs(this._tmpVectorForPickCompare.x),Math.abs(this._tmpVectorForPickCompare.y),Math.abs(this._tmpVectorForPickCompare.z));var o=.01*(this._options.gazeModePointerMovedFactor||1)*n.distance;return this._tmpVectorForPickCompare.length()>o},t.prototype._updatePointerDistance=function(e,n){n===void 0&&(n=100),e.scaling.y=n,this._scene.useRightHandedSystem&&(n*=-1),e.position.z=n/2+.05},Object.defineProperty(t.prototype,"lasterPointerDefaultColor",{get:function(){return this.laserPointerDefaultColor},enumerable:!1,configurable:!0}),t._idCounter=200,t.Name=si.POINTER_SELECTION,t.Version=1,t}(ci);qn.AddWebXRFeature(ho.Name,function(r,t){return function(){return new ho(r,t)}},ho.Version,!0);var zi,Pu=function(){function r(t,e,n){this.element=t,this.sessionMode=e,this.referenceSpaceType=n}return r.prototype.update=function(t){},r}(),__=function(){},Cu=function(){function r(t,e){var n=this;if(this.scene=t,this.options=e,this._activeButton=null,this._buttons=[],this.activeButtonChangedObservable=new x.c,this.overlay=document.createElement("div"),this.overlay.classList.add("xr-button-overlay"),this.overlay.style.cssText="z-index:11;position: absolute; right: 20px;bottom: 50px;",typeof window<"u"&&window.location&&window.location.protocol==="http:"&&Xe.b.Warn("WebXR can only be served over HTTPS"),e.customButtons)this._buttons=e.customButtons;else{var i=e.sessionMode||"immersive-vr",o=e.referenceSpaceType||"local-floor",a=".babylonVRicon { color: #868686; border-color: #868686; border-style: solid; margin-left: 10px; height: 50px; width: 80px; background-color: rgba(51,51,51,0.7); background-image: url("+(typeof SVGSVGElement>"u"?"https://cdn.babylonjs.com/Assets/vrButton.png":"data:image/svg+xml;charset=UTF-8,%3Csvg%20xmlns%3D%22http%3A//www.w3.org/2000/svg%22%20width%3D%222048%22%20height%3D%221152%22%20viewBox%3D%220%200%202048%201152%22%20version%3D%221.1%22%3E%3Cpath%20transform%3D%22rotate%28180%201024%2C576.0000000000001%29%22%20d%3D%22m1109%2C896q17%2C0%2030%2C-12t13%2C-30t-12.5%2C-30.5t-30.5%2C-12.5l-170%2C0q-18%2C0%20-30.5%2C12.5t-12.5%2C30.5t13%2C30t30%2C12l170%2C0zm-85%2C256q59%2C0%20132.5%2C-1.5t154.5%2C-5.5t164.5%2C-11.5t163%2C-20t150%2C-30t124.5%2C-41.5q23%2C-11%2042%2C-24t38%2C-30q27%2C-25%2041%2C-61.5t14%2C-72.5l0%2C-257q0%2C-123%20-47%2C-232t-128%2C-190t-190%2C-128t-232%2C-47l-81%2C0q-37%2C0%20-68.5%2C14t-60.5%2C34.5t-55.5%2C45t-53%2C45t-53%2C34.5t-55.5%2C14t-55.5%2C-14t-53%2C-34.5t-53%2C-45t-55.5%2C-45t-60.5%2C-34.5t-68.5%2C-14l-81%2C0q-123%2C0%20-232%2C47t-190%2C128t-128%2C190t-47%2C232l0%2C257q0%2C68%2038%2C115t97%2C73q54%2C24%20124.5%2C41.5t150%2C30t163%2C20t164.5%2C11.5t154.5%2C5.5t132.5%2C1.5zm939%2C-298q0%2C39%20-24.5%2C67t-58.5%2C42q-54%2C23%20-122%2C39.5t-143.5%2C28t-155.5%2C19t-157%2C11t-148.5%2C5t-129.5%2C1.5q-59%2C0%20-130%2C-1.5t-148%2C-5t-157%2C-11t-155.5%2C-19t-143.5%2C-28t-122%2C-39.5q-34%2C-14%20-58.5%2C-42t-24.5%2C-67l0%2C-257q0%2C-106%2040.5%2C-199t110%2C-162.5t162.5%2C-109.5t199%2C-40l81%2C0q27%2C0%2052%2C14t50%2C34.5t51%2C44.5t55.5%2C44.5t63.5%2C34.5t74%2C14t74%2C-14t63.5%2C-34.5t55.5%2C-44.5t51%2C-44.5t50%2C-34.5t52%2C-14l14%2C0q37%2C0%2070%2C0.5t64.5%2C4.5t63.5%2C12t68%2C23q71%2C30%20128.5%2C78.5t98.5%2C110t63.5%2C133.5t22.5%2C149l0%2C257z%22%20fill%3D%22white%22%20/%3E%3C/svg%3E%0A")+"); background-size: 80%; background-repeat:no-repeat; background-position: center; border: none; outline: none; transition: transform 0.125s ease-out } .babylonVRicon:hover { transform: scale(1.05) } .babylonVRicon:active {background-color: rgba(51,51,51,1) } .babylonVRicon:focus {background-color: rgba(51,51,51,1) }";a+='.babylonVRicon.vrdisplaypresenting { background-image: none;} .vrdisplaypresenting::after { content: "EXIT"} .xr-error::after { content: "ERROR"}';var s=document.createElement("style");s.appendChild(document.createTextNode(a)),document.getElementsByTagName("head")[0].appendChild(s);var d=document.createElement("button");d.className="babylonVRicon",d.title=i+" - "+o,this._buttons.push(new Pu(d,i,o)),this._buttons[this._buttons.length-1].update=function(b){this.element.style.display=b===null||b===this?"":"none",d.className="babylonVRicon"+(b===this?" vrdisplaypresenting":"")},this._updateButtons(null)}var p=t.getEngine().getInputElement();p&&p.parentNode&&(p.parentNode.appendChild(this.overlay),t.onDisposeObservable.addOnce(function(){n.dispose()}))}return r.CreateAsync=function(t,e,n){var i=this,o=new r(t,n),a=o._buttons.map(function(s){return e.sessionManager.isSessionSupportedAsync(s.sessionMode)});return e.onStateChangedObservable.add(function(s){s==pn.NOT_IN_XR&&o._updateButtons(null)}),Promise.all(a).then(function(s){return s.forEach(function(d,p){d?(o.overlay.appendChild(o._buttons[p].element),o._buttons[p].element.onclick=function(){return Object(c.b)(i,void 0,void 0,function(){var b,P,O;return Object(c.e)(this,function(B){switch(B.label){case 0:return e.state!=pn.IN_XR?[3,2]:[4,e.exitXRAsync()];case 1:return B.sent(),o._updateButtons(null),[3,6];case 2:if(e.state!=pn.NOT_IN_XR)return[3,6];if(!n.renderTarget)return[3,6];B.label=3;case 3:return B.trys.push([3,5,,6]),[4,e.enterXRAsync(o._buttons[p].sessionMode,o._buttons[p].referenceSpaceType,n.renderTarget,{optionalFeatures:n.optionalFeatures,requiredFeatures:n.requiredFeatures})];case 4:return B.sent(),o._updateButtons(o._buttons[p]),[3,6];case 5:return b=B.sent(),o._updateButtons(null),P=o._buttons[p].element,O=P.title,P.title="Error entering XR session : "+O,P.classList.add("xr-error"),n.onError&&n.onError(b),[3,6];case 6:return[2]}})})}):Xe.b.Warn('Session mode "'+o._buttons[p].sessionMode+'" not supported in browser')}),o})},r.prototype.dispose=function(){var t=this.scene.getEngine().getInputElement();t&&t.parentNode&&t.parentNode.contains(this.overlay)&&t.parentNode.removeChild(this.overlay),this.activeButtonChangedObservable.clear()},r.prototype._updateButtons=function(t){var e=this;this._activeButton=t,this._buttons.forEach(function(n){n.update(e._activeButton)}),this.activeButtonChangedObservable.notifyObservers(this._activeButton)},r}();function ks(r){var t,e=0,n=Date.now();r.observableParameters=(t=r.observableParameters)!==null&&t!==void 0?t:{};var i=r.contextObservable.add(function(o){var a=Date.now(),s={startTime:n,currentTime:a,deltaTime:e=a-n,completeRate:e/r.timeout,payload:o};r.onTick&&r.onTick(s),r.breakCondition&&r.breakCondition()&&(r.contextObservable.remove(i),r.onAborted&&r.onAborted(s)),e>=r.timeout&&(r.contextObservable.remove(i),r.onEnded&&r.onEnded(s))},r.observableParameters.mask,r.observableParameters.insertFirst,r.observableParameters.scope);return i}(function(r){r[r.INIT=0]="INIT",r[r.STARTED=1]="STARTED",r[r.ENDED=2]="ENDED"})(zi||(zi={}));var m_=function(){function r(t){var e,n,i=this;this.onEachCountObservable=new x.c,this.onTimerAbortedObservable=new x.c,this.onTimerEndedObservable=new x.c,this.onStateChangedObservable=new x.c,this._observer=null,this._breakOnNextTick=!1,this._tick=function(o){var a=Date.now();i._timer=a-i._startTime;var s={startTime:i._startTime,currentTime:a,deltaTime:i._timer,completeRate:i._timer/i._timeToEnd,payload:o},d=i._breakOnNextTick||i._breakCondition(s);d||i._timer>=i._timeToEnd?i._stop(s,d):i.onEachCountObservable.notifyObservers(s)},this._setState(zi.INIT),this._contextObservable=t.contextObservable,this._observableParameters=(e=t.observableParameters)!==null&&e!==void 0?e:{},this._breakCondition=(n=t.breakCondition)!==null&&n!==void 0?n:function(){return!1},t.onEnded&&this.onTimerEndedObservable.add(t.onEnded),t.onTick&&this.onEachCountObservable.add(t.onTick),t.onAborted&&this.onTimerAbortedObservable.add(t.onAborted)}return Object.defineProperty(r.prototype,"breakCondition",{set:function(t){this._breakCondition=t},enumerable:!1,configurable:!0}),r.prototype.clearObservables=function(){this.onEachCountObservable.clear(),this.onTimerAbortedObservable.clear(),this.onTimerEndedObservable.clear(),this.onStateChangedObservable.clear()},r.prototype.start=function(t){if(t===void 0&&(t=this._timeToEnd),this._state===zi.STARTED)throw new Error("Timer already started. Please stop it before starting again");this._timeToEnd=t,this._startTime=Date.now(),this._timer=0,this._observer=this._contextObservable.add(this._tick,this._observableParameters.mask,this._observableParameters.insertFirst,this._observableParameters.scope),this._setState(zi.STARTED)},r.prototype.stop=function(){this._state===zi.STARTED&&(this._breakOnNextTick=!0)},r.prototype.dispose=function(){this._observer&&this._contextObservable.remove(this._observer),this.clearObservables()},r.prototype._setState=function(t){this._state=t,this.onStateChangedObservable.notifyObservers(this._state)},r.prototype._stop=function(t,e){e===void 0&&(e=!1),this._contextObservable.remove(this._observer),this._setState(zi.ENDED),e?this.onTimerAbortedObservable.notifyObservers(t):this.onTimerEndedObservable.notifyObservers(t)},r}(),fo=function(r){function t(e,n){var i=r.call(this,e)||this;return i._options=n,i._controllers={},i._snappedToPoint=!1,i._tmpRay=new fn.a(new u.e,new u.e),i._tmpVector=new u.e,i._tmpQuaternion=new u.b,i.backwardsMovementEnabled=!0,i.backwardsTeleportationDistance=.7,i.parabolicCheckRadius=5,i.parabolicRayEnabled=!0,i.straightRayEnabled=!0,i.rotationAngle=Math.PI/8,i._rotationEnabled=!0,i._attachController=function(o){if(!(i._controllers[o.uniqueId]||i._options.forceHandedness&&o.inputSource.handedness!==i._options.forceHandedness)){i._controllers[o.uniqueId]={xrController:o,teleportationState:{forward:!1,backwards:!1,rotating:!1,currentRotation:0,baseRotation:0}};var a=i._controllers[o.uniqueId];if(a.xrController.inputSource.targetRayMode==="tracked-pointer"&&a.xrController.inputSource.gamepad){var s=function(){if(o.motionController){var d=o.motionController.getComponentOfType(xr.THUMBSTICK_TYPE)||o.motionController.getComponentOfType(xr.TOUCHPAD_TYPE);if(!d||i._options.useMainComponentOnly){var p=o.motionController.getMainComponent();if(!p)return;a.teleportationComponent=p,a.onButtonChangedObserver=p.onButtonStateChangedObservable.add(function(){p.changes.pressed&&(p.changes.pressed.current?(a.teleportationState.forward=!0,i._currentTeleportationControllerId=a.xrController.uniqueId,a.teleportationState.baseRotation=i._options.xrInput.xrCamera.rotationQuaternion.toEulerAngles().y,a.teleportationState.currentRotation=0,ks({timeout:i._options.timeToTeleport||3e3,contextObservable:i._xrSessionManager.onXRFrameObservable,breakCondition:function(){return!p.pressed},onEnded:function(){i._currentTeleportationControllerId===a.xrController.uniqueId&&a.teleportationState.forward&&i._teleportForward(o.uniqueId)}})):(a.teleportationState.forward=!1,i._currentTeleportationControllerId=""))})}else a.teleportationComponent=d,a.onAxisChangedObserver=d.onAxisValueChangedObservable.add(function(b){if(b.y<=.7&&a.teleportationState.backwards&&(a.teleportationState.backwards=!1),b.y>.7&&!a.teleportationState.forward&&i.backwardsMovementEnabled&&!i.snapPointsOnly&&!a.teleportationState.backwards){a.teleportationState.backwards=!0,i._tmpQuaternion.copyFrom(i._options.xrInput.xrCamera.rotationQuaternion),i._tmpQuaternion.toEulerAnglesToRef(i._tmpVector),i._tmpVector.x=0,i._tmpVector.z=0,u.b.FromEulerVectorToRef(i._tmpVector,i._tmpQuaternion),i._tmpVector.set(0,0,i.backwardsTeleportationDistance*(i._xrSessionManager.scene.useRightHandedSystem?1:-1)),i._tmpVector.rotateByQuaternionToRef(i._tmpQuaternion,i._tmpVector),i._tmpVector.addInPlace(i._options.xrInput.xrCamera.position),i._tmpRay.origin.copyFrom(i._tmpVector),i._tmpRay.length=i._options.xrInput.xrCamera.realWorldHeight+.1,i._tmpRay.direction.set(0,-1,0);var P=i._xrSessionManager.scene.pickWithRay(i._tmpRay,function(B){return i._floorMeshes.indexOf(B)!==-1});P&&P.pickedPoint&&(i._options.xrInput.xrCamera.position.x=P.pickedPoint.x,i._options.xrInput.xrCamera.position.z=P.pickedPoint.z)}if(b.y<-.7&&!i._currentTeleportationControllerId&&!a.teleportationState.rotating&&(a.teleportationState.forward=!0,i._currentTeleportationControllerId=a.xrController.uniqueId,a.teleportationState.baseRotation=i._options.xrInput.xrCamera.rotationQuaternion.toEulerAngles().y),b.x){if(a.teleportationState.forward)i._currentTeleportationControllerId===a.xrController.uniqueId&&(i.rotationEnabled?setTimeout(function(){a.teleportationState.currentRotation=Math.atan2(b.x,b.y*(i._xrSessionManager.scene.useRightHandedSystem?1:-1))}):a.teleportationState.currentRotation=0);else if(!a.teleportationState.rotating&&Math.abs(b.x)>.7){a.teleportationState.rotating=!0;var O=i.rotationAngle*(b.x>0?1:-1)*(i._xrSessionManager.scene.useRightHandedSystem?-1:1);i._options.xrInput.xrCamera.rotationQuaternion.multiplyInPlace(u.b.FromEulerAngles(0,O,0))}}else a.teleportationState.rotating=!1;b.x===0&&b.y===0&&a.teleportationState.forward&&i._teleportForward(o.uniqueId)})}};o.motionController?s():o.onMotionControllerInitObservable.addOnce(function(){s()})}else i._xrSessionManager.scene.onPointerObservable.add(function(d){d.type===Tt.a.POINTERDOWN?(a.teleportationState.forward=!0,i._currentTeleportationControllerId=a.xrController.uniqueId,a.teleportationState.baseRotation=i._options.xrInput.xrCamera.rotationQuaternion.toEulerAngles().y,a.teleportationState.currentRotation=0,ks({timeout:i._options.timeToTeleport||3e3,contextObservable:i._xrSessionManager.onXRFrameObservable,onEnded:function(){i._currentTeleportationControllerId===a.xrController.uniqueId&&a.teleportationState.forward&&i._teleportForward(o.uniqueId)}})):d.type===Tt.a.POINTERUP&&(a.teleportationState.forward=!1,i._currentTeleportationControllerId="")})}},i._options.teleportationTargetMesh||i._createDefaultTargetMesh(),i._floorMeshes=i._options.floorMeshes||[],i._snapToPositions=i._options.snapPositions||[],i._setTargetMeshVisibility(!1),i}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"rotationEnabled",{get:function(){return this._rotationEnabled},set:function(e){if(this._rotationEnabled=e,this._options.teleportationTargetMesh){var n=this._options.teleportationTargetMesh.getChildMeshes(!1,function(i){return i.name==="rotationCone"});n[0]&&n[0].setEnabled(e)}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"teleportationTargetMesh",{get:function(){return this._options.teleportationTargetMesh||null},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"snapPointsOnly",{get:function(){return!!this._options.snapPointsOnly},set:function(e){this._options.snapPointsOnly=e},enumerable:!1,configurable:!0}),t.prototype.addFloorMesh=function(e){this._floorMeshes.push(e)},t.prototype.addSnapPoint=function(e){this._snapToPositions.push(e)},t.prototype.attach=function(){var e=this;return!!r.prototype.attach.call(this)&&(this._currentTeleportationControllerId="",this._options.xrInput.controllers.forEach(this._attachController),this._addNewAttachObserver(this._options.xrInput.onControllerAddedObservable,this._attachController),this._addNewAttachObserver(this._options.xrInput.onControllerRemovedObservable,function(n){e._detachController(n.uniqueId)}),!0)},t.prototype.detach=function(){var e=this;return!!r.prototype.detach.call(this)&&(Object.keys(this._controllers).forEach(function(n){e._detachController(n)}),this._setTargetMeshVisibility(!1),this._currentTeleportationControllerId="",this._controllers={},!0)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this._options.teleportationTargetMesh&&this._options.teleportationTargetMesh.dispose(!1,!0)},t.prototype.removeFloorMesh=function(e){var n=this._floorMeshes.indexOf(e);n!==-1&&this._floorMeshes.splice(n,1)},t.prototype.removeFloorMeshByName=function(e){var n=this._xrSessionManager.scene.getMeshByName(e);n&&this.removeFloorMesh(n)},t.prototype.removeSnapPoint=function(e){var n=this._snapToPositions.indexOf(e);if(n===-1){for(var i=0;i<this._snapToPositions.length;++i)if(this._snapToPositions[i].equals(e)){n=i;break}}return n!==-1&&(this._snapToPositions.splice(n,1),!0)},t.prototype.setSelectionFeature=function(e){this._selectionFeature=e},t.prototype._onXRFrame=function(e){var n=this,i=this._xrSessionManager.currentFrame,o=this._xrSessionManager.scene;if(this.attach&&i){var a=this._options.teleportationTargetMesh;if(this._currentTeleportationControllerId){if(!a)return;a.rotationQuaternion=a.rotationQuaternion||new u.b;var s=this._controllers[this._currentTeleportationControllerId];if(s&&s.teleportationState.forward){u.b.RotationYawPitchRollToRef(s.teleportationState.currentRotation+s.teleportationState.baseRotation,0,0,a.rotationQuaternion);var d=!1;if(s.xrController.getWorldPointerRayToRef(this._tmpRay),this.straightRayEnabled){if((p=o.pickWithRay(this._tmpRay,function(B){if(n._options.pickBlockerMeshes&&n._options.pickBlockerMeshes.indexOf(B)!==-1)return!0;var F=n._floorMeshes.indexOf(B);return F!==-1&&n._floorMeshes[F].absolutePosition.y<n._options.xrInput.xrCamera.position.y}))&&p.pickedMesh&&this._options.pickBlockerMeshes&&this._options.pickBlockerMeshes.indexOf(p.pickedMesh)!==-1)return;p&&p.pickedPoint&&(d=!0,this._setTargetMeshPosition(p.pickedPoint),this._setTargetMeshVisibility(!0),this._showParabolicPath(p))}if(this.parabolicRayEnabled&&!d){var p,b=s.xrController.pointer.rotationQuaternion.toEulerAngles().x,P=Math.PI/2-Math.abs(b)+1,O=this.parabolicCheckRadius*P;if(this._tmpRay.origin.addToRef(this._tmpRay.direction.scale(2*O),this._tmpVector),this._tmpVector.y=this._tmpRay.origin.y,this._tmpRay.origin.addInPlace(this._tmpRay.direction.scale(O)),this._tmpVector.subtractToRef(this._tmpRay.origin,this._tmpRay.direction),this._tmpRay.direction.normalize(),(p=o.pickWithRay(this._tmpRay,function(B){return!(!n._options.pickBlockerMeshes||n._options.pickBlockerMeshes.indexOf(B)===-1)||n._floorMeshes.indexOf(B)!==-1}))&&p.pickedMesh&&this._options.pickBlockerMeshes&&this._options.pickBlockerMeshes.indexOf(p.pickedMesh)!==-1)return;p&&p.pickedPoint&&(d=!0,this._setTargetMeshPosition(p.pickedPoint),this._setTargetMeshVisibility(!0),this._showParabolicPath(p))}this._setTargetMeshVisibility(d)}else this._setTargetMeshVisibility(!1)}else this._setTargetMeshVisibility(!1)}},t.prototype._createDefaultTargetMesh=function(){this._options.defaultTargetMeshOptions=this._options.defaultTargetMeshOptions||{};var e=this._options.useUtilityLayer?this._options.customUtilityLayerScene||On.a.DefaultUtilityLayer.utilityLayerScene:this._xrSessionManager.scene,n=Ui.CreateGround("teleportationTarget",{width:2,height:2,subdivisions:2},e);n.isPickable=!1;var i=new Ti.a("teleportationPlaneDynamicTexture",512,e,!0);i.hasAlpha=!0;var o=i.getContext();o.beginPath(),o.arc(256,256,200,0,2*Math.PI,!1),o.fillStyle=this._options.defaultTargetMeshOptions.teleportationFillColor||"#444444",o.fill(),o.lineWidth=10,o.strokeStyle=this._options.defaultTargetMeshOptions.teleportationBorderColor||"#FFFFFF",o.stroke(),o.closePath(),i.update();var a=new Ft.a("teleportationPlaneMaterial",e);a.diffuseTexture=i,n.material=a;var s=gr.CreateTorus("torusTeleportation",{diameter:.75,thickness:.1,tessellation:20},e);if(s.isPickable=!1,s.parent=n,!this._options.defaultTargetMeshOptions.disableAnimation){var d=new k("animationInnerCircle","position.y",30,k.ANIMATIONTYPE_FLOAT,k.ANIMATIONLOOPMODE_CYCLE),p=[];p.push({frame:0,value:0}),p.push({frame:30,value:.4}),p.push({frame:60,value:0}),d.setKeys(p);var b=new on;b.setEasingMode(Ge.EASINGMODE_EASEINOUT),d.setEasingFunction(b),s.animations=[],s.animations.push(d),e.beginAnimation(s,0,60,!0)}var P=pi.a.CreateCylinder("rotationCone",{diameterTop:0,tessellation:4},e);if(P.isPickable=!1,P.scaling.set(.5,.12,.2),P.rotate(ye.a.X,Math.PI/2),P.position.z=.6,P.parent=s,this._options.defaultTargetMeshOptions.torusArrowMaterial)s.material=this._options.defaultTargetMeshOptions.torusArrowMaterial,P.material=this._options.defaultTargetMeshOptions.torusArrowMaterial;else{var O=new Ft.a("torusConsMat",e);O.disableLighting=!!this._options.defaultTargetMeshOptions.disableLighting,O.disableLighting?O.emissiveColor=new M.a(.3,.3,1):O.diffuseColor=new M.a(.3,.3,1),O.alpha=.9,s.material=O,P.material=O,this._teleportationRingMaterial=O}this._options.renderingGroupId!==void 0&&(n.renderingGroupId=this._options.renderingGroupId,s.renderingGroupId=this._options.renderingGroupId,P.renderingGroupId=this._options.renderingGroupId),this._options.teleportationTargetMesh=n},t.prototype._detachController=function(e){var n=this._controllers[e];n&&(n.teleportationComponent&&(n.onAxisChangedObserver&&n.teleportationComponent.onAxisValueChangedObservable.remove(n.onAxisChangedObserver),n.onButtonChangedObserver&&n.teleportationComponent.onButtonStateChangedObservable.remove(n.onButtonChangedObserver)),delete this._controllers[e])},t.prototype._findClosestSnapPointWithRadius=function(e,n){n===void 0&&(n=this._options.snapToPositionRadius||.8);var i=null,o=Number.MAX_VALUE;if(this._snapToPositions.length){var a=n*n;this._snapToPositions.forEach(function(s){var d=u.e.DistanceSquared(s,e);d<=a&&d<o&&(o=d,i=s)})}return i},t.prototype._setTargetMeshPosition=function(e){if(this._options.teleportationTargetMesh){var n=this._findClosestSnapPointWithRadius(e);this._snappedToPoint=!!n,this.snapPointsOnly&&!this._snappedToPoint&&this._teleportationRingMaterial?this._teleportationRingMaterial.diffuseColor.set(1,.3,.3):this.snapPointsOnly&&this._snappedToPoint&&this._teleportationRingMaterial&&this._teleportationRingMaterial.diffuseColor.set(.3,.3,1),this._options.teleportationTargetMesh.position.copyFrom(n||e),this._options.teleportationTargetMesh.position.y+=.01}},t.prototype._setTargetMeshVisibility=function(e){this._options.teleportationTargetMesh&&this._options.teleportationTargetMesh.isVisible!==e&&(this._options.teleportationTargetMesh.isVisible=e,this._options.teleportationTargetMesh.getChildren(void 0,!1).forEach(function(n){n.isVisible=e}),e?this._selectionFeature&&this._selectionFeature.detach():(this._quadraticBezierCurve&&(this._quadraticBezierCurve.dispose(),this._quadraticBezierCurve=null),this._selectionFeature&&this._selectionFeature.attach()))},t.prototype._showParabolicPath=function(e){if(e.pickedPoint){var n=this._controllers[this._currentTeleportationControllerId],i=qe.d.CreateQuadraticBezier(n.xrController.pointer.absolutePosition,e.ray.origin,e.pickedPoint,25);this._options.generateRayPathMesh?this._quadraticBezierCurve=this._options.generateRayPathMesh(i.getPoints()):this._quadraticBezierCurve=cn.a.CreateLines("teleportation path line",{points:i.getPoints(),instance:this._quadraticBezierCurve,updatable:!0}),this._quadraticBezierCurve.isPickable=!1}},t.prototype._teleportForward=function(e){var n=this._controllers[e];if(n&&n.teleportationState.forward&&(n.teleportationState.forward=!1,this._currentTeleportationControllerId="",(!this.snapPointsOnly||this._snappedToPoint)&&this._options.teleportationTargetMesh&&this._options.teleportationTargetMesh.isVisible)){var i=this._options.xrInput.xrCamera.realWorldHeight;this._options.xrInput.xrCamera.onBeforeCameraTeleport.notifyObservers(this._options.xrInput.xrCamera.position),this._options.xrInput.xrCamera.position.copyFrom(this._options.teleportationTargetMesh.position),this._options.xrInput.xrCamera.position.y+=i,this._options.xrInput.xrCamera.rotationQuaternion.multiplyInPlace(u.b.FromEulerAngles(0,n.teleportationState.currentRotation-(this._xrSessionManager.scene.useRightHandedSystem?Math.PI:0),0)),this._options.xrInput.xrCamera.onAfterCameraTeleport.notifyObservers(this._options.xrInput.xrCamera.position)}},t.Name=si.TELEPORTATION,t.Version=1,t}(ci);qn.AddWebXRFeature(fo.Name,function(r,t){return function(){return new fo(r,t)}},fo.Version,!0);var g_=function(){},xu=function(){function r(){}return r.CreateAsync=function(t,e){e===void 0&&(e={});var n=new r;return Tu.CreateAsync(t).then(function(i){if(n.baseExperience=i,e.ignoreNativeCameraTransformation&&(n.baseExperience.camera.compensateOnFirstFrame=!1),n.input=new Au(i.sessionManager,i.camera,Object(c.a)({controllerOptions:{renderingGroupId:e.renderingGroupId}},e.inputOptions||{})),n.pointerSelection=n.baseExperience.featuresManager.enableFeature(ho.Name,e.useStablePlugins?"stable":"latest",{xrInput:n.input,renderingGroupId:e.renderingGroupId}),e.disableTeleportation||(n.teleportation=n.baseExperience.featuresManager.enableFeature(fo.Name,e.useStablePlugins?"stable":"latest",{floorMeshes:e.floorMeshes,xrInput:n.input,renderingGroupId:e.renderingGroupId}),n.teleportation.setSelectionFeature(n.pointerSelection)),n.renderTarget=n.baseExperience.sessionManager.getWebXRRenderTarget(e.outputCanvasOptions),!e.disableDefaultUI){var o=Object(c.a)({renderTarget:n.renderTarget},e.uiOptions||{});return e.optionalFeatures&&(typeof e.optionalFeatures=="boolean"?o.optionalFeatures=["hit-test","anchors","plane-detection","hand-tracking"]:o.optionalFeatures=e.optionalFeatures),Cu.CreateAsync(t,n.baseExperience,o).then(function(a){n.enterExitUI=a})}}).then(function(){return n}).catch(function(i){return l.a.Error("Error initializing XR"),l.a.Error(i),n})},r.prototype.dispose=function(){this.baseExperience&&this.baseExperience.dispose(),this.input&&this.input.dispose(),this.enterExitUI&&this.enterExitUI.dispose(),this.renderTarget&&this.renderTarget.dispose()},r}(),v_=!0;_e.a.prototype.createDefaultLight=function(r){if(r===void 0&&(r=!1),r&&this.lights)for(var t=0;t<this.lights.length;t++)this.lights[t].dispose();this.lights.length===0&&new Vo.a("default light",u.e.Up(),this)},_e.a.prototype.createDefaultCamera=function(r,t,e){if(r===void 0&&(r=!1),t===void 0&&(t=!1),e===void 0&&(e=!1),t&&this.activeCamera&&(this.activeCamera.dispose(),this.activeCamera=null),!this.activeCamera){var n,i=this.getWorldExtends(function(P){return P.isVisible&&P.isEnabled()}),o=i.max.subtract(i.min),a=i.min.add(o.scale(.5)),s=1.5*o.length();if(isFinite(s)||(s=1,a.copyFromFloats(0,0,0)),r){var d=new Ji("default camera",-Math.PI/2,Math.PI/2,s,a,this);d.lowerRadiusLimit=.01*s,d.wheelPrecision=100/s,n=d}else{var p=new Yn("default camera",new u.e(a.x,a.y,-s),this);p.setTarget(a),n=p}n.minZ=.01*s,n.maxZ=1e3*s,n.speed=.2*s,this.activeCamera=n;var b=this.getEngine().getInputElement();e&&b&&n.attachControl()}},_e.a.prototype.createDefaultCameraOrLight=function(r,t,e){r===void 0&&(r=!1),t===void 0&&(t=!1),e===void 0&&(e=!1),this.createDefaultLight(t),this.createDefaultCamera(r,t,e)},_e.a.prototype.createDefaultSkybox=function(r,t,e,n,i){if(t===void 0&&(t=!1),e===void 0&&(e=1e3),n===void 0&&(n=0),i===void 0&&(i=!0),!r)return l.a.Warn("Can not create default skybox without environment texture."),null;i&&r&&(this.environmentTexture=r);var o=De.a.CreateBox("hdrSkyBox",e,this);if(t){var a=new uo("skyBox",this);a.backFaceCulling=!1,a.reflectionTexture=r.clone(),a.reflectionTexture&&(a.reflectionTexture.coordinatesMode=we.a.SKYBOX_MODE),a.microSurface=1-n,a.disableLighting=!0,a.twoSidedLighting=!0,o.infiniteDistance=!0,o.material=a}else{var s=new Ft.a("skyBox",this);s.backFaceCulling=!1,s.reflectionTexture=r.clone(),s.reflectionTexture&&(s.reflectionTexture.coordinatesMode=we.a.SKYBOX_MODE),s.disableLighting=!0,o.infiniteDistance=!0,o.material=s}return o.isPickable=!1,o},_e.a.prototype.createDefaultEnvironment=function(r){return Ls?new Ls(r,this):null},_e.a.prototype.createDefaultVRExperience=function(r){return r===void 0&&(r={}),new Kl(this,r)},_e.a.prototype.createDefaultXRExperienceAsync=function(r){return r===void 0&&(r={}),xu.CreateAsync(this,r).then(function(t){return t})};var Ru=function(r){function t(e,n,i,o,a,s,d){o===void 0&&(o=!1),a===void 0&&(a=!1),s===void 0&&(s=we.a.TRILINEAR_SAMPLINGMODE),d===void 0&&(d={autoPlay:!0,loop:!0,autoUpdateTexture:!0});var p=r.call(this,null,i,!o,a)||this;p._onUserActionRequestedObservable=null,p._stillImageCaptured=!1,p._displayingPosterTexture=!1,p._frameId=-1,p._currentSrc=null,p._createInternalTexture=function(){if(p._texture!=null){if(!p._displayingPosterTexture)return;p._texture.dispose(),p._displayingPosterTexture=!1}if(!p._getEngine().needPOTTextures||Xe.b.IsExponentOfTwo(p.video.videoWidth)&&Xe.b.IsExponentOfTwo(p.video.videoHeight)?(p.wrapU=we.a.WRAP_ADDRESSMODE,p.wrapV=we.a.WRAP_ADDRESSMODE):(p.wrapU=we.a.CLAMP_ADDRESSMODE,p.wrapV=we.a.CLAMP_ADDRESSMODE,p._generateMipMaps=!1),p._texture=p._getEngine().createDynamicTexture(p.video.videoWidth,p.video.videoHeight,p._generateMipMaps,p.samplingMode),p.video.autoplay||p._settings.poster)p._texture.isReady=!0,p._updateInternalTexture(),p.onLoadObservable.hasObservers()&&p.onLoadObservable.notifyObservers(p);else{var P=p.video.onplaying,O=!1,B=p.video.muted;p.video.muted=!0,p.video.onplaying=function(){p.video.muted=B,p.video.onplaying=P,p._texture.isReady=!0,p._updateInternalTexture(),O||p.video.pause(),p.onLoadObservable.hasObservers()&&p.onLoadObservable.notifyObservers(p)};var F=p.video.play();F?F.then(function(){}).catch(function(){O=!0,p._onUserActionRequestedObservable&&p._onUserActionRequestedObservable.hasObservers()&&p._onUserActionRequestedObservable.notifyObservers(p)}):(p.video.onplaying=P,p._texture.isReady=!0,p._updateInternalTexture(),p.onLoadObservable.hasObservers()&&p.onLoadObservable.notifyObservers(p))}},p.reset=function(){p._texture!=null&&(p._displayingPosterTexture||(p._texture.dispose(),p._texture=null))},p._updateInternalTexture=function(){if(p._texture!=null&&p._texture.isReady&&!(p.video.readyState<p.video.HAVE_CURRENT_DATA||p._displayingPosterTexture)){var P=p.getScene().getFrameId();p._frameId!==P&&(p._frameId=P,p._getEngine().updateVideoTexture(p._texture,p.video,p._invertY))}},p._generateMipMaps=o,p._initialSamplingMode=s,p.autoUpdateTexture=d.autoUpdateTexture,p._currentSrc=n,p.name=e||p._getName(n),p.video=p._getVideo(n),p._settings=d,d.poster&&(p.video.poster=d.poster),d.autoPlay!==void 0&&(p.video.autoplay=d.autoPlay),d.loop!==void 0&&(p.video.loop=d.loop),d.muted!==void 0&&(p.video.muted=d.muted),p.video.setAttribute("playsinline",""),p.video.addEventListener("paused",p._updateInternalTexture),p.video.addEventListener("seeked",p._updateInternalTexture),p.video.addEventListener("emptied",p.reset),p._createInternalTextureOnEvent=d.poster&&!d.autoPlay?"play":"canplay",p.video.addEventListener(p._createInternalTextureOnEvent,p._createInternalTexture),d.autoPlay&&p.video.play();var b=p.video.readyState>=p.video.HAVE_CURRENT_DATA;return!d.poster||d.autoPlay&&b?b&&p._createInternalTexture():(p._texture=p._getEngine().createTexture(d.poster,!1,!p.invertY,i),p._displayingPosterTexture=!0),p}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"onUserActionRequestedObservable",{get:function(){return this._onUserActionRequestedObservable||(this._onUserActionRequestedObservable=new x.c),this._onUserActionRequestedObservable},enumerable:!1,configurable:!0}),t.prototype._getName=function(e){return e instanceof HTMLVideoElement?e.currentSrc:typeof e=="object"?e.toString():e},t.prototype._getVideo=function(e){if(e instanceof HTMLVideoElement)return Xe.b.SetCorsBehavior(e.currentSrc,e),e;var n=document.createElement("video");return typeof e=="string"?(Xe.b.SetCorsBehavior(e,n),n.src=e):(Xe.b.SetCorsBehavior(e[0],n),e.forEach(function(i){var o=document.createElement("source");o.src=i,n.appendChild(o)})),n},t.prototype._rebuild=function(){this.update()},t.prototype.update=function(){this.autoUpdateTexture&&this.updateTexture(!0)},t.prototype.updateTexture=function(e){e&&(this.video.paused&&this._stillImageCaptured||(this._stillImageCaptured=!0,this._updateInternalTexture()))},t.prototype.updateURL=function(e){this.video.src=e,this._currentSrc=e},t.prototype.clone=function(){return new t(this.name,this._currentSrc,this.getScene(),this._generateMipMaps,this.invertY,this.samplingMode,this._settings)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this._currentSrc=null,this._onUserActionRequestedObservable&&(this._onUserActionRequestedObservable.clear(),this._onUserActionRequestedObservable=null),this.video.removeEventListener(this._createInternalTextureOnEvent,this._createInternalTexture),this.video.removeEventListener("paused",this._updateInternalTexture),this.video.removeEventListener("seeked",this._updateInternalTexture),this.video.removeEventListener("emptied",this.reset),this.video.pause()},t.CreateFromStreamAsync=function(e,n){var i=document.createElement("video");return e.getEngine()._badOS&&(document.body.appendChild(i),i.style.transform="scale(0.0001, 0.0001)",i.style.opacity="0",i.style.position="fixed",i.style.bottom="0px",i.style.right="0px"),i.setAttribute("autoplay",""),i.setAttribute("muted","true"),i.setAttribute("playsinline",""),i.muted=!0,i.mozSrcObject!==void 0?i.mozSrcObject=n:typeof i.srcObject=="object"?i.srcObject=n:(window.URL=window.URL||window.webkitURL||window.mozURL||window.msURL,i.src=window.URL&&window.URL.createObjectURL(n)),new Promise(function(o){var a=function(){o(new t("video",i,e,!0,!0)),i.removeEventListener("playing",a)};i.addEventListener("playing",a),i.play()})},t.CreateFromWebCamAsync=function(e,n,i){var o,a=this;return i===void 0&&(i=!1),n&&n.deviceId&&(o={exact:n.deviceId}),navigator.mediaDevices?navigator.mediaDevices.getUserMedia({video:n,audio:i}).then(function(s){return a.CreateFromStreamAsync(e,s)}):(navigator.getUserMedia=navigator.getUserMedia||navigator.webkitGetUserMedia||navigator.mozGetUserMedia||navigator.msGetUserMedia,navigator.getUserMedia&&navigator.getUserMedia({video:{deviceId:o,width:{min:n&&n.minWidth||256,max:n&&n.maxWidth||640},height:{min:n&&n.minHeight||256,max:n&&n.maxHeight||480}},audio:i},function(s){return a.CreateFromStreamAsync(e,s)},function(s){l.a.Error(s.name)}),Promise.reject("No support for userMedia on this device"))},t.CreateFromWebCam=function(e,n,i,o){o===void 0&&(o=!1),this.CreateFromWebCamAsync(e,i,o).then(function(a){n&&n(a)}).catch(function(a){l.a.Error(a.name)})},t}(we.a),b_=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"videoTexture",{get:function(){return this._texture},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"videoMode",{get:function(){return this.textureMode},set:function(e){this.textureMode=e},enumerable:!1,configurable:!0}),t.prototype._initTexture=function(e,n,i){var o=this,a={loop:i.loop,autoPlay:i.autoPlay,autoUpdateTexture:!0,poster:i.poster},s=new Ru((this.name||"videoDome")+"_texture",e,n,i.generateMipMaps,this._useDirectMapping,we.a.TRILINEAR_SAMPLINGMODE,a);return i.clickToPlay&&(n.onPointerUp=function(){o._texture.video.play()}),s},t.MODE_MONOSCOPIC=ki.MODE_MONOSCOPIC,t.MODE_TOPBOTTOM=ki.MODE_TOPBOTTOM,t.MODE_SIDEBYSIDE=ki.MODE_SIDEBYSIDE,t}(ki),jn=f(55),y_=function(){function r(t){this.engine=t,this._captureGPUFrameTime=!1,this._gpuFrameTime=new jn.a,this._captureShaderCompilationTime=!1,this._shaderCompilationTime=new jn.a,this._onBeginFrameObserver=null,this._onEndFrameObserver=null,this._onBeforeShaderCompilationObserver=null,this._onAfterShaderCompilationObserver=null}return Object.defineProperty(r.prototype,"gpuFrameTimeCounter",{get:function(){return this._gpuFrameTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureGPUFrameTime",{get:function(){return this._captureGPUFrameTime},set:function(t){var e=this;t!==this._captureGPUFrameTime&&(this._captureGPUFrameTime=t,t?(this._onBeginFrameObserver=this.engine.onBeginFrameObservable.add(function(){e._gpuFrameTimeToken||(e._gpuFrameTimeToken=e.engine.startTimeQuery())}),this._onEndFrameObserver=this.engine.onEndFrameObservable.add(function(){if(e._gpuFrameTimeToken){var n=e.engine.endTimeQuery(e._gpuFrameTimeToken);n>-1&&(e._gpuFrameTimeToken=null,e._gpuFrameTime.fetchNewFrame(),e._gpuFrameTime.addCount(n,!0))}})):(this.engine.onBeginFrameObservable.remove(this._onBeginFrameObserver),this._onBeginFrameObserver=null,this.engine.onEndFrameObservable.remove(this._onEndFrameObserver),this._onEndFrameObserver=null))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"shaderCompilationTimeCounter",{get:function(){return this._shaderCompilationTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureShaderCompilationTime",{get:function(){return this._captureShaderCompilationTime},set:function(t){var e=this;t!==this._captureShaderCompilationTime&&(this._captureShaderCompilationTime=t,t?(this._onBeforeShaderCompilationObserver=this.engine.onBeforeShaderCompilationObservable.add(function(){e._shaderCompilationTime.fetchNewFrame(),e._shaderCompilationTime.beginMonitoring()}),this._onAfterShaderCompilationObserver=this.engine.onAfterShaderCompilationObservable.add(function(){e._shaderCompilationTime.endMonitoring()})):(this.engine.onBeforeShaderCompilationObservable.remove(this._onBeforeShaderCompilationObserver),this._onBeforeShaderCompilationObserver=null,this.engine.onAfterShaderCompilationObservable.remove(this._onAfterShaderCompilationObserver),this._onAfterShaderCompilationObserver=null))},enumerable:!1,configurable:!0}),r.prototype.dispose=function(){this.engine.onBeginFrameObservable.remove(this._onBeginFrameObserver),this._onBeginFrameObserver=null,this.engine.onEndFrameObservable.remove(this._onEndFrameObserver),this._onEndFrameObserver=null,this.engine.onBeforeShaderCompilationObservable.remove(this._onBeforeShaderCompilationObserver),this._onBeforeShaderCompilationObserver=null,this.engine.onAfterShaderCompilationObservable.remove(this._onAfterShaderCompilationObserver),this._onAfterShaderCompilationObserver=null,this.engine=null},r}(),T_=function(){function r(t){var e=this;this.scene=t,this._captureActiveMeshesEvaluationTime=!1,this._activeMeshesEvaluationTime=new jn.a,this._captureRenderTargetsRenderTime=!1,this._renderTargetsRenderTime=new jn.a,this._captureFrameTime=!1,this._frameTime=new jn.a,this._captureRenderTime=!1,this._renderTime=new jn.a,this._captureInterFrameTime=!1,this._interFrameTime=new jn.a,this._captureParticlesRenderTime=!1,this._particlesRenderTime=new jn.a,this._captureSpritesRenderTime=!1,this._spritesRenderTime=new jn.a,this._capturePhysicsTime=!1,this._physicsTime=new jn.a,this._captureAnimationsTime=!1,this._animationsTime=new jn.a,this._captureCameraRenderTime=!1,this._cameraRenderTime=new jn.a,this._onBeforeActiveMeshesEvaluationObserver=null,this._onAfterActiveMeshesEvaluationObserver=null,this._onBeforeRenderTargetsRenderObserver=null,this._onAfterRenderTargetsRenderObserver=null,this._onAfterRenderObserver=null,this._onBeforeDrawPhaseObserver=null,this._onAfterDrawPhaseObserver=null,this._onBeforeAnimationsObserver=null,this._onBeforeParticlesRenderingObserver=null,this._onAfterParticlesRenderingObserver=null,this._onBeforeSpritesRenderingObserver=null,this._onAfterSpritesRenderingObserver=null,this._onBeforePhysicsObserver=null,this._onAfterPhysicsObserver=null,this._onAfterAnimationsObserver=null,this._onBeforeCameraRenderObserver=null,this._onAfterCameraRenderObserver=null,this._onBeforeAnimationsObserver=t.onBeforeAnimationsObservable.add(function(){e._captureActiveMeshesEvaluationTime&&e._activeMeshesEvaluationTime.fetchNewFrame(),e._captureRenderTargetsRenderTime&&e._renderTargetsRenderTime.fetchNewFrame(),e._captureFrameTime&&(Xe.b.StartPerformanceCounter("Scene rendering"),e._frameTime.beginMonitoring()),e._captureInterFrameTime&&e._interFrameTime.endMonitoring(),e._captureParticlesRenderTime&&e._particlesRenderTime.fetchNewFrame(),e._captureSpritesRenderTime&&e._spritesRenderTime.fetchNewFrame(),e._captureAnimationsTime&&e._animationsTime.beginMonitoring(),e.scene.getEngine()._drawCalls.fetchNewFrame()}),this._onAfterRenderObserver=t.onAfterRenderObservable.add(function(){e._captureFrameTime&&(Xe.b.EndPerformanceCounter("Scene rendering"),e._frameTime.endMonitoring()),e._captureRenderTime&&e._renderTime.endMonitoring(!1),e._captureInterFrameTime&&e._interFrameTime.beginMonitoring()})}return Object.defineProperty(r.prototype,"activeMeshesEvaluationTimeCounter",{get:function(){return this._activeMeshesEvaluationTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureActiveMeshesEvaluationTime",{get:function(){return this._captureActiveMeshesEvaluationTime},set:function(t){var e=this;t!==this._captureActiveMeshesEvaluationTime&&(this._captureActiveMeshesEvaluationTime=t,t?(this._onBeforeActiveMeshesEvaluationObserver=this.scene.onBeforeActiveMeshesEvaluationObservable.add(function(){Xe.b.StartPerformanceCounter("Active meshes evaluation"),e._activeMeshesEvaluationTime.beginMonitoring()}),this._onAfterActiveMeshesEvaluationObserver=this.scene.onAfterActiveMeshesEvaluationObservable.add(function(){Xe.b.EndPerformanceCounter("Active meshes evaluation"),e._activeMeshesEvaluationTime.endMonitoring()})):(this.scene.onBeforeActiveMeshesEvaluationObservable.remove(this._onBeforeActiveMeshesEvaluationObserver),this._onBeforeActiveMeshesEvaluationObserver=null,this.scene.onAfterActiveMeshesEvaluationObservable.remove(this._onAfterActiveMeshesEvaluationObserver),this._onAfterActiveMeshesEvaluationObserver=null))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"renderTargetsRenderTimeCounter",{get:function(){return this._renderTargetsRenderTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureRenderTargetsRenderTime",{get:function(){return this._captureRenderTargetsRenderTime},set:function(t){var e=this;t!==this._captureRenderTargetsRenderTime&&(this._captureRenderTargetsRenderTime=t,t?(this._onBeforeRenderTargetsRenderObserver=this.scene.onBeforeRenderTargetsRenderObservable.add(function(){Xe.b.StartPerformanceCounter("Render targets rendering"),e._renderTargetsRenderTime.beginMonitoring()}),this._onAfterRenderTargetsRenderObserver=this.scene.onAfterRenderTargetsRenderObservable.add(function(){Xe.b.EndPerformanceCounter("Render targets rendering"),e._renderTargetsRenderTime.endMonitoring(!1)})):(this.scene.onBeforeRenderTargetsRenderObservable.remove(this._onBeforeRenderTargetsRenderObserver),this._onBeforeRenderTargetsRenderObserver=null,this.scene.onAfterRenderTargetsRenderObservable.remove(this._onAfterRenderTargetsRenderObserver),this._onAfterRenderTargetsRenderObserver=null))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"particlesRenderTimeCounter",{get:function(){return this._particlesRenderTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureParticlesRenderTime",{get:function(){return this._captureParticlesRenderTime},set:function(t){var e=this;t!==this._captureParticlesRenderTime&&(this._captureParticlesRenderTime=t,t?(this._onBeforeParticlesRenderingObserver=this.scene.onBeforeParticlesRenderingObservable.add(function(){Xe.b.StartPerformanceCounter("Particles"),e._particlesRenderTime.beginMonitoring()}),this._onAfterParticlesRenderingObserver=this.scene.onAfterParticlesRenderingObservable.add(function(){Xe.b.EndPerformanceCounter("Particles"),e._particlesRenderTime.endMonitoring(!1)})):(this.scene.onBeforeParticlesRenderingObservable.remove(this._onBeforeParticlesRenderingObserver),this._onBeforeParticlesRenderingObserver=null,this.scene.onAfterParticlesRenderingObservable.remove(this._onAfterParticlesRenderingObserver),this._onAfterParticlesRenderingObserver=null))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"spritesRenderTimeCounter",{get:function(){return this._spritesRenderTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureSpritesRenderTime",{get:function(){return this._captureSpritesRenderTime},set:function(t){var e=this;t!==this._captureSpritesRenderTime&&(this._captureSpritesRenderTime=t,this.scene.spriteManagers&&(t?(this._onBeforeSpritesRenderingObserver=this.scene.onBeforeSpritesRenderingObservable.add(function(){Xe.b.StartPerformanceCounter("Sprites"),e._spritesRenderTime.beginMonitoring()}),this._onAfterSpritesRenderingObserver=this.scene.onAfterSpritesRenderingObservable.add(function(){Xe.b.EndPerformanceCounter("Sprites"),e._spritesRenderTime.endMonitoring(!1)})):(this.scene.onBeforeSpritesRenderingObservable.remove(this._onBeforeSpritesRenderingObserver),this._onBeforeSpritesRenderingObserver=null,this.scene.onAfterSpritesRenderingObservable.remove(this._onAfterSpritesRenderingObserver),this._onAfterSpritesRenderingObserver=null)))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"physicsTimeCounter",{get:function(){return this._physicsTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"capturePhysicsTime",{get:function(){return this._capturePhysicsTime},set:function(t){var e=this;t!==this._capturePhysicsTime&&this.scene.onBeforePhysicsObservable&&(this._capturePhysicsTime=t,t?(this._onBeforePhysicsObserver=this.scene.onBeforePhysicsObservable.add(function(){Xe.b.StartPerformanceCounter("Physics"),e._physicsTime.beginMonitoring()}),this._onAfterPhysicsObserver=this.scene.onAfterPhysicsObservable.add(function(){Xe.b.EndPerformanceCounter("Physics"),e._physicsTime.endMonitoring()})):(this.scene.onBeforePhysicsObservable.remove(this._onBeforePhysicsObserver),this._onBeforePhysicsObserver=null,this.scene.onAfterPhysicsObservable.remove(this._onAfterPhysicsObserver),this._onAfterPhysicsObserver=null))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"animationsTimeCounter",{get:function(){return this._animationsTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureAnimationsTime",{get:function(){return this._captureAnimationsTime},set:function(t){var e=this;t!==this._captureAnimationsTime&&(this._captureAnimationsTime=t,t?this._onAfterAnimationsObserver=this.scene.onAfterAnimationsObservable.add(function(){e._animationsTime.endMonitoring()}):(this.scene.onAfterAnimationsObservable.remove(this._onAfterAnimationsObserver),this._onAfterAnimationsObserver=null))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"frameTimeCounter",{get:function(){return this._frameTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureFrameTime",{get:function(){return this._captureFrameTime},set:function(t){this._captureFrameTime=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"interFrameTimeCounter",{get:function(){return this._interFrameTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureInterFrameTime",{get:function(){return this._captureInterFrameTime},set:function(t){this._captureInterFrameTime=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"renderTimeCounter",{get:function(){return this._renderTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureRenderTime",{get:function(){return this._captureRenderTime},set:function(t){var e=this;t!==this._captureRenderTime&&(this._captureRenderTime=t,t?(this._onBeforeDrawPhaseObserver=this.scene.onBeforeDrawPhaseObservable.add(function(){e._renderTime.beginMonitoring(),Xe.b.StartPerformanceCounter("Main render")}),this._onAfterDrawPhaseObserver=this.scene.onAfterDrawPhaseObservable.add(function(){e._renderTime.endMonitoring(!1),Xe.b.EndPerformanceCounter("Main render")})):(this.scene.onBeforeDrawPhaseObservable.remove(this._onBeforeDrawPhaseObserver),this._onBeforeDrawPhaseObserver=null,this.scene.onAfterDrawPhaseObservable.remove(this._onAfterDrawPhaseObserver),this._onAfterDrawPhaseObserver=null))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"cameraRenderTimeCounter",{get:function(){return this._cameraRenderTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureCameraRenderTime",{get:function(){return this._captureCameraRenderTime},set:function(t){var e=this;t!==this._captureCameraRenderTime&&(this._captureCameraRenderTime=t,t?(this._onBeforeCameraRenderObserver=this.scene.onBeforeCameraRenderObservable.add(function(n){e._cameraRenderTime.beginMonitoring(),Xe.b.StartPerformanceCounter("Rendering camera "+n.name)}),this._onAfterCameraRenderObserver=this.scene.onAfterCameraRenderObservable.add(function(n){e._cameraRenderTime.endMonitoring(!1),Xe.b.EndPerformanceCounter("Rendering camera "+n.name)})):(this.scene.onBeforeCameraRenderObservable.remove(this._onBeforeCameraRenderObserver),this._onBeforeCameraRenderObserver=null,this.scene.onAfterCameraRenderObservable.remove(this._onAfterCameraRenderObserver),this._onAfterCameraRenderObserver=null))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"drawCallsCounter",{get:function(){return this.scene.getEngine()._drawCalls},enumerable:!1,configurable:!0}),r.prototype.dispose=function(){this.scene.onAfterRenderObservable.remove(this._onAfterRenderObserver),this._onAfterRenderObserver=null,this.scene.onBeforeActiveMeshesEvaluationObservable.remove(this._onBeforeActiveMeshesEvaluationObserver),this._onBeforeActiveMeshesEvaluationObserver=null,this.scene.onAfterActiveMeshesEvaluationObservable.remove(this._onAfterActiveMeshesEvaluationObserver),this._onAfterActiveMeshesEvaluationObserver=null,this.scene.onBeforeRenderTargetsRenderObservable.remove(this._onBeforeRenderTargetsRenderObserver),this._onBeforeRenderTargetsRenderObserver=null,this.scene.onAfterRenderTargetsRenderObservable.remove(this._onAfterRenderTargetsRenderObserver),this._onAfterRenderTargetsRenderObserver=null,this.scene.onBeforeAnimationsObservable.remove(this._onBeforeAnimationsObserver),this._onBeforeAnimationsObserver=null,this.scene.onBeforeParticlesRenderingObservable.remove(this._onBeforeParticlesRenderingObserver),this._onBeforeParticlesRenderingObserver=null,this.scene.onAfterParticlesRenderingObservable.remove(this._onAfterParticlesRenderingObserver),this._onAfterParticlesRenderingObserver=null,this._onBeforeSpritesRenderingObserver&&(this.scene.onBeforeSpritesRenderingObservable.remove(this._onBeforeSpritesRenderingObserver),this._onBeforeSpritesRenderingObserver=null),this._onAfterSpritesRenderingObserver&&(this.scene.onAfterSpritesRenderingObservable.remove(this._onAfterSpritesRenderingObserver),this._onAfterSpritesRenderingObserver=null),this.scene.onBeforeDrawPhaseObservable.remove(this._onBeforeDrawPhaseObserver),this._onBeforeDrawPhaseObserver=null,this.scene.onAfterDrawPhaseObservable.remove(this._onAfterDrawPhaseObserver),this._onAfterDrawPhaseObserver=null,this._onBeforePhysicsObserver&&(this.scene.onBeforePhysicsObservable.remove(this._onBeforePhysicsObserver),this._onBeforePhysicsObserver=null),this._onAfterPhysicsObserver&&(this.scene.onAfterPhysicsObservable.remove(this._onAfterPhysicsObserver),this._onAfterPhysicsObserver=null),this.scene.onAfterAnimationsObservable.remove(this._onAfterAnimationsObserver),this._onAfterAnimationsObserver=null,this.scene.onBeforeCameraRenderObservable.remove(this._onBeforeCameraRenderObserver),this._onBeforeCameraRenderObserver=null,this.scene.onAfterCameraRenderObservable.remove(this._onAfterCameraRenderObserver),this._onAfterCameraRenderObserver=null,this.scene=null},r}(),E_=`#ifdef DIFFUSE
-varying vec2 vUVDiffuse;
-uniform sampler2D diffuseSampler;
-#endif
-#ifdef OPACITY
-varying vec2 vUVOpacity;
-uniform sampler2D opacitySampler;
-uniform float opacityIntensity;
-#endif
-#ifdef EMISSIVE
-varying vec2 vUVEmissive;
-uniform sampler2D emissiveSampler;
-#endif
-#ifdef VERTEXALPHA
-varying vec4 vColor;
-#endif
-uniform vec4 glowColor;
-void main(void)
-{
-vec4 finalColor=glowColor;
-
-#ifdef DIFFUSE
-vec4 albedoTexture=texture2D(diffuseSampler,vUVDiffuse);
-#ifdef GLOW
-
-finalColor.a*=albedoTexture.a;
-#endif
-#ifdef HIGHLIGHT
-
-finalColor.a=albedoTexture.a;
-#endif
-#endif
-#ifdef OPACITY
-vec4 opacityMap=texture2D(opacitySampler,vUVOpacity);
-#ifdef OPACITYRGB
-finalColor.a*=getLuminance(opacityMap.rgb);
-#else
-finalColor.a*=opacityMap.a;
-#endif
-finalColor.a*=opacityIntensity;
-#endif
-#ifdef VERTEXALPHA
-finalColor.a*=vColor.a;
-#endif
-#ifdef ALPHATEST
-if (finalColor.a<ALPHATESTVALUE)
-discard;
-#endif
-#ifdef EMISSIVE
-gl_FragColor=texture2D(emissiveSampler,vUVEmissive)*finalColor;
-#else
-gl_FragColor=finalColor;
-#endif
-#ifdef HIGHLIGHT
-
-gl_FragColor.a=glowColor.a;
-#endif
-}`;ze.a.ShadersStore.glowMapGenerationPixelShader=E_;var S_=`
-attribute vec3 position;
-#include<bonesDeclaration>
-#include<morphTargetsVertexGlobalDeclaration>
-#include<morphTargetsVertexDeclaration>[0..maxSimultaneousMorphTargets]
-
-#include<instancesDeclaration>
-uniform mat4 viewProjection;
-varying vec4 vPosition;
-#ifdef UV1
-attribute vec2 uv;
-#endif
-#ifdef UV2
-attribute vec2 uv2;
-#endif
-#ifdef DIFFUSE
-varying vec2 vUVDiffuse;
-uniform mat4 diffuseMatrix;
-#endif
-#ifdef OPACITY
-varying vec2 vUVOpacity;
-uniform mat4 opacityMatrix;
-#endif
-#ifdef EMISSIVE
-varying vec2 vUVEmissive;
-uniform mat4 emissiveMatrix;
-#endif
-#ifdef VERTEXALPHA
-attribute vec4 color;
-varying vec4 vColor;
-#endif
-void main(void)
-{
-vec3 positionUpdated=position;
-#ifdef UV1
-vec2 uvUpdated=uv;
-#endif
-#include<morphTargetsVertex>[0..maxSimultaneousMorphTargets]
-#include<instancesVertex>
-#include<bonesVertex>
-#ifdef CUBEMAP
-vPosition=finalWorld*vec4(positionUpdated,1.0);
-gl_Position=viewProjection*finalWorld*vec4(position,1.0);
-#else
-vPosition=viewProjection*finalWorld*vec4(positionUpdated,1.0);
-gl_Position=vPosition;
-#endif
-#ifdef DIFFUSE
-#ifdef DIFFUSEUV1
-vUVDiffuse=vec2(diffuseMatrix*vec4(uvUpdated,1.0,0.0));
-#endif
-#ifdef DIFFUSEUV2
-vUVDiffuse=vec2(diffuseMatrix*vec4(uv2,1.0,0.0));
-#endif
-#endif
-#ifdef OPACITY
-#ifdef OPACITYUV1
-vUVOpacity=vec2(opacityMatrix*vec4(uvUpdated,1.0,0.0));
-#endif
-#ifdef OPACITYUV2
-vUVOpacity=vec2(opacityMatrix*vec4(uv2,1.0,0.0));
-#endif
-#endif
-#ifdef EMISSIVE
-#ifdef EMISSIVEUV1
-vUVEmissive=vec2(emissiveMatrix*vec4(uvUpdated,1.0,0.0));
-#endif
-#ifdef EMISSIVEUV2
-vUVEmissive=vec2(emissiveMatrix*vec4(uv2,1.0,0.0));
-#endif
-#endif
-#ifdef VERTEXALPHA
-vColor=color;
-#endif
-}`;ze.a.ShadersStore.glowMapGenerationVertexShader=S_;var po=function(){function r(t,e){this._vertexBuffers={},this._maxSize=0,this._mainTextureDesiredSize={width:0,height:0},this._shouldRender=!0,this._postProcesses=[],this._textures=[],this._emissiveTextureAndColor={texture:null,color:new M.b},this.neutralColor=new M.b,this.isEnabled=!0,this.disableBoundingBoxesFromEffectLayer=!1,this.onDisposeObservable=new x.c,this.onBeforeRenderMainTextureObservable=new x.c,this.onBeforeComposeObservable=new x.c,this.onBeforeRenderMeshToEffect=new x.c,this.onAfterRenderMeshToEffect=new x.c,this.onAfterComposeObservable=new x.c,this.onSizeChangedObservable=new x.c,this.name=t,this._scene=e||te.a.LastCreatedScene,r._SceneComponentInitialization(this._scene),this._engine=this._scene.getEngine(),this._maxSize=this._engine.getCaps().maxTextureSize,this._scene.effectLayers.push(this),this._generateIndexBuffer(),this._generateVertexBuffer()}return Object.defineProperty(r.prototype,"camera",{get:function(){return this._effectLayerOptions.camera},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"renderingGroupId",{get:function(){return this._effectLayerOptions.renderingGroupId},set:function(t){this._effectLayerOptions.renderingGroupId=t},enumerable:!1,configurable:!0}),r.prototype._init=function(t){this._effectLayerOptions=Object(c.a)({mainTextureRatio:.5,alphaBlendingMode:h.a.ALPHA_COMBINE,camera:null,renderingGroupId:-1},t),this._setMainTextureSize(),this._createMainTexture(),this._createTextureAndPostProcesses(),this._mergeEffect=this._createMergeEffect()},r.prototype._generateIndexBuffer=function(){var t=[];t.push(0),t.push(1),t.push(2),t.push(0),t.push(2),t.push(3),this._indexBuffer=this._engine.createIndexBuffer(t)},r.prototype._generateVertexBuffer=function(){var t=[];t.push(1,1),t.push(-1,1),t.push(-1,-1),t.push(1,-1);var e=new Oe.b(this._engine,t,Oe.b.PositionKind,!1,!1,2);this._vertexBuffers[Oe.b.PositionKind]=e},r.prototype._setMainTextureSize=function(){this._effectLayerOptions.mainTextureFixedSize?(this._mainTextureDesiredSize.width=this._effectLayerOptions.mainTextureFixedSize,this._mainTextureDesiredSize.height=this._effectLayerOptions.mainTextureFixedSize):(this._mainTextureDesiredSize.width=this._engine.getRenderWidth()*this._effectLayerOptions.mainTextureRatio,this._mainTextureDesiredSize.height=this._engine.getRenderHeight()*this._effectLayerOptions.mainTextureRatio,this._mainTextureDesiredSize.width=this._engine.needPOTTextures?Ue.a.GetExponentOfTwo(this._mainTextureDesiredSize.width,this._maxSize):this._mainTextureDesiredSize.width,this._mainTextureDesiredSize.height=this._engine.needPOTTextures?Ue.a.GetExponentOfTwo(this._mainTextureDesiredSize.height,this._maxSize):this._mainTextureDesiredSize.height),this._mainTextureDesiredSize.width=Math.floor(this._mainTextureDesiredSize.width),this._mainTextureDesiredSize.height=Math.floor(this._mainTextureDesiredSize.height)},r.prototype._createMainTexture=function(){var t=this;this._mainTexture=new sn("HighlightLayerMainRTT",{width:this._mainTextureDesiredSize.width,height:this._mainTextureDesiredSize.height},this._scene,!1,!0,h.a.TEXTURETYPE_UNSIGNED_INT),this._mainTexture.activeCamera=this._effectLayerOptions.camera,this._mainTexture.wrapU=we.a.CLAMP_ADDRESSMODE,this._mainTexture.wrapV=we.a.CLAMP_ADDRESSMODE,this._mainTexture.anisotropicFilteringLevel=1,this._mainTexture.updateSamplingMode(we.a.BILINEAR_SAMPLINGMODE),this._mainTexture.renderParticles=!1,this._mainTexture.renderList=null,this._mainTexture.ignoreCameraViewport=!0,this._mainTexture.customRenderFunction=function(n,i,o,a){var s;t.onBeforeRenderMainTextureObservable.notifyObservers(t);var d=t._scene.getEngine();if(a.length){for(d.setColorWrite(!1),s=0;s<a.length;s++)t._renderSubMesh(a.data[s]);d.setColorWrite(!0)}for(s=0;s<n.length;s++)t._renderSubMesh(n.data[s]);for(s=0;s<i.length;s++)t._renderSubMesh(i.data[s]);var p=d.getAlphaMode();for(s=0;s<o.length;s++)t._renderSubMesh(o.data[s],!0);d.setAlphaMode(p)},this._mainTexture.onClearObservable.add(function(n){n.clear(t.neutralColor,!0,!0,!0)});var e=this._scene.getBoundingBoxRenderer().enabled;this._mainTexture.onBeforeBindObservable.add(function(){t._scene.getBoundingBoxRenderer().enabled=!t.disableBoundingBoxesFromEffectLayer&&e}),this._mainTexture.onAfterUnbindObservable.add(function(){t._scene.getBoundingBoxRenderer().enabled=e})},r.prototype._addCustomEffectDefines=function(t){},r.prototype._isReady=function(t,e,n){var i=t.getMaterial();if(!i||!i.isReadyForSubMesh(t.getMesh(),t,e))return!1;var o=[],a=[Oe.b.PositionKind],s=t.getMesh(),d=!1,p=!1;if(i){var b=i.needAlphaTesting(),P=i.getAlphaTestTexture(),O=P&&P.hasAlpha&&(i.useAlphaFromDiffuseTexture||i._useAlphaFromAlbedoTexture);P&&(b||O)&&(o.push("#define DIFFUSE"),s.isVerticesDataPresent(Oe.b.UV2Kind)&&P.coordinatesIndex===1?(o.push("#define DIFFUSEUV2"),p=!0):s.isVerticesDataPresent(Oe.b.UVKind)&&(o.push("#define DIFFUSEUV1"),d=!0),b&&(o.push("#define ALPHATEST"),o.push("#define ALPHATESTVALUE 0.4")));var B=i.opacityTexture;B&&(o.push("#define OPACITY"),s.isVerticesDataPresent(Oe.b.UV2Kind)&&B.coordinatesIndex===1?(o.push("#define OPACITYUV2"),p=!0):s.isVerticesDataPresent(Oe.b.UVKind)&&(o.push("#define OPACITYUV1"),d=!0))}n&&(o.push("#define EMISSIVE"),s.isVerticesDataPresent(Oe.b.UV2Kind)&&n.coordinatesIndex===1?(o.push("#define EMISSIVEUV2"),p=!0):s.isVerticesDataPresent(Oe.b.UVKind)&&(o.push("#define EMISSIVEUV1"),d=!0)),s.isVerticesDataPresent(Oe.b.ColorKind)&&s.hasVertexAlpha&&(a.push(Oe.b.ColorKind),o.push("#define VERTEXALPHA")),d&&(a.push(Oe.b.UVKind),o.push("#define UV1")),p&&(a.push(Oe.b.UV2Kind),o.push("#define UV2"));var F=new Sr.a;if(s.useBones&&s.computeBonesUsingShaders){a.push(Oe.b.MatricesIndicesKind),a.push(Oe.b.MatricesWeightsKind),s.numBoneInfluencers>4&&(a.push(Oe.b.MatricesIndicesExtraKind),a.push(Oe.b.MatricesWeightsExtraKind)),o.push("#define NUM_BONE_INFLUENCERS "+s.numBoneInfluencers);var z=s.skeleton;z&&z.isUsingTextureForMatrices?o.push("#define BONETEXTURE"):o.push("#define BonesPerMesh "+(z?z.bones.length+1:0)),s.numBoneInfluencers>0&&F.addCPUSkinningFallback(0,s)}else o.push("#define NUM_BONE_INFLUENCERS 0");var J=s.morphTargetManager,ie=0;J&&J.numInfluencers>0&&(o.push("#define MORPHTARGETS"),ie=J.numInfluencers,o.push("#define NUM_MORPH_INFLUENCERS "+ie),et.a.PrepareAttributesForMorphTargetsInfluencers(a,s,ie)),e&&(o.push("#define INSTANCES"),et.a.PushAttributesForInstances(a),t.getRenderingMesh().hasThinInstances&&o.push("#define THIN_INSTANCES")),this._addCustomEffectDefines(o);var se=o.join(`
-`);return this._cachedDefines!==se&&(this._cachedDefines=se,this._effectLayerMapGenerationEffect=this._scene.getEngine().createEffect("glowMapGeneration",a,["world","mBones","viewProjection","glowColor","morphTargetInfluences","boneTextureWidth","diffuseMatrix","emissiveMatrix","opacityMatrix","opacityIntensity"],["diffuseSampler","emissiveSampler","opacitySampler","boneSampler"],se,F,void 0,void 0,{maxSimultaneousMorphTargets:ie})),this._effectLayerMapGenerationEffect.isReady()},r.prototype.render=function(){var t=this._mergeEffect;if(t.isReady()){for(var e=0;e<this._postProcesses.length;e++)if(!this._postProcesses[e].isReady())return;var n=this._scene.getEngine();this.onBeforeComposeObservable.notifyObservers(this),n.enableEffect(t),n.setState(!1),n.bindBuffers(this._vertexBuffers,this._indexBuffer,t);var i=n.getAlphaMode();n.setAlphaMode(this._effectLayerOptions.alphaBlendingMode),this._internalRender(t),n.setAlphaMode(i),this.onAfterComposeObservable.notifyObservers(this);var o=this._mainTexture.getSize();this._setMainTextureSize(),o.width===this._mainTextureDesiredSize.width&&o.height===this._mainTextureDesiredSize.height||(this.onSizeChangedObservable.notifyObservers(this),this._disposeTextureAndPostProcesses(),this._createMainTexture(),this._createTextureAndPostProcesses())}},r.prototype.hasMesh=function(t){return this.renderingGroupId===-1||t.renderingGroupId===this.renderingGroupId},r.prototype.shouldRender=function(){return this.isEnabled&&this._shouldRender},r.prototype._shouldRenderMesh=function(t){return!0},r.prototype._canRenderMesh=function(t,e){return!e.needAlphaBlendingForMesh(t)},r.prototype._shouldRenderEmissiveTextureForMesh=function(){return!0},r.prototype._renderSubMesh=function(t,e){var n,i=this;if(e===void 0&&(e=!1),this.shouldRender()){var o=t.getMaterial(),a=t.getMesh(),s=t.getReplacementMesh(),d=t.getRenderingMesh(),p=t.getEffectiveMesh(),b=this._scene,P=b.getEngine();if(p._internalAbstractMeshDataInfo._isActiveIntermediate=!1,o&&this._canRenderMesh(d,o)){var O=(n=d.overrideMaterialSideOrientation)!==null&&n!==void 0?n:o.sideOrientation;d._getWorldMatrixDeterminant()<0&&(O=O===Ht.a.ClockWiseSideOrientation?Ht.a.CounterClockWiseSideOrientation:Ht.a.ClockWiseSideOrientation);var B=O===Ht.a.ClockWiseSideOrientation;P.setState(o.backFaceCulling,o.zOffset,void 0,B);var F=d._getInstancesRenderList(t._id,!!s);if(!F.mustReturn&&this._shouldRenderMesh(d)){var z=F.hardwareInstancedRendering[t._id]||d.hasThinInstances;if(this._setEmissiveTextureAndColor(d,t,o),this.onBeforeRenderMeshToEffect.notifyObservers(a),this._useMeshMaterial(d))d.render(t,z,s||void 0);else if(this._isReady(t,z,this._emissiveTextureAndColor.texture)){P.enableEffect(this._effectLayerMapGenerationEffect),d._bind(t,this._effectLayerMapGenerationEffect,Ht.a.TriangleFillMode),this._effectLayerMapGenerationEffect.setMatrix("viewProjection",b.getTransformMatrix()),this._effectLayerMapGenerationEffect.setMatrix("world",p.getWorldMatrix()),this._effectLayerMapGenerationEffect.setFloat4("glowColor",this._emissiveTextureAndColor.color.r,this._emissiveTextureAndColor.color.g,this._emissiveTextureAndColor.color.b,this._emissiveTextureAndColor.color.a);var J=o.needAlphaTesting(),ie=o.getAlphaTestTexture(),se=ie&&ie.hasAlpha&&(o.useAlphaFromDiffuseTexture||o._useAlphaFromAlbedoTexture);ie&&(J||se)&&(this._effectLayerMapGenerationEffect.setTexture("diffuseSampler",ie),(ce=ie.getTextureMatrix())&&this._effectLayerMapGenerationEffect.setMatrix("diffuseMatrix",ce));var ce,ue=o.opacityTexture;if(ue&&(this._effectLayerMapGenerationEffect.setTexture("opacitySampler",ue),this._effectLayerMapGenerationEffect.setFloat("opacityIntensity",ue.level),(ce=ue.getTextureMatrix())&&this._effectLayerMapGenerationEffect.setMatrix("opacityMatrix",ce)),this._emissiveTextureAndColor.texture&&(this._effectLayerMapGenerationEffect.setTexture("emissiveSampler",this._emissiveTextureAndColor.texture),this._effectLayerMapGenerationEffect.setMatrix("emissiveMatrix",this._emissiveTextureAndColor.texture.getTextureMatrix())),d.useBones&&d.computeBonesUsingShaders&&d.skeleton){var fe=d.skeleton;if(fe.isUsingTextureForMatrices){var ve=fe.getTransformMatrixTexture(d);if(!ve)return;this._effectLayerMapGenerationEffect.setTexture("boneSampler",ve),this._effectLayerMapGenerationEffect.setFloat("boneTextureWidth",4*(fe.bones.length+1))}else this._effectLayerMapGenerationEffect.setMatrices("mBones",fe.getTransformMatrices(d))}et.a.BindMorphTargetParameters(d,this._effectLayerMapGenerationEffect),e&&P.setAlphaMode(o.alphaMode),d._processRendering(p,t,this._effectLayerMapGenerationEffect,o.fillMode,F,z,function(Te,Re){return i._effectLayerMapGenerationEffect.setMatrix("world",Re)})}else this._mainTexture.resetRefreshCounter();this.onAfterRenderMeshToEffect.notifyObservers(a)}}}},r.prototype._useMeshMaterial=function(t){return!1},r.prototype._rebuild=function(){var t=this._vertexBuffers[Oe.b.PositionKind];t&&t._rebuild(),this._generateIndexBuffer()},r.prototype._disposeTextureAndPostProcesses=function(){this._mainTexture.dispose();for(var t=0;t<this._postProcesses.length;t++)this._postProcesses[t]&&this._postProcesses[t].dispose();for(this._postProcesses=[],t=0;t<this._textures.length;t++)this._textures[t]&&this._textures[t].dispose();this._textures=[]},r.prototype.dispose=function(){var t=this._vertexBuffers[Oe.b.PositionKind];t&&(t.dispose(),this._vertexBuffers[Oe.b.PositionKind]=null),this._indexBuffer&&(this._scene.getEngine()._releaseBuffer(this._indexBuffer),this._indexBuffer=null),this._disposeTextureAndPostProcesses();var e=this._scene.effectLayers.indexOf(this,0);e>-1&&this._scene.effectLayers.splice(e,1),this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear(),this.onBeforeRenderMainTextureObservable.clear(),this.onBeforeComposeObservable.clear(),this.onBeforeRenderMeshToEffect.clear(),this.onAfterRenderMeshToEffect.clear(),this.onAfterComposeObservable.clear(),this.onSizeChangedObservable.clear()},r.prototype.getClassName=function(){return"EffectLayer"},r.Parse=function(t,e,n){return Xe.b.Instantiate(t.customType).Parse(t,e,n)},r._SceneComponentInitialization=function(t){throw An.a.WarnImport("EffectLayerSceneComponent")},Object(c.c)([Object(L.c)()],r.prototype,"name",void 0),Object(c.c)([Object(L.f)()],r.prototype,"neutralColor",void 0),Object(c.c)([Object(L.c)()],r.prototype,"isEnabled",void 0),Object(c.c)([Object(L.d)()],r.prototype,"camera",null),Object(c.c)([Object(L.c)()],r.prototype,"renderingGroupId",null),Object(c.c)([Object(L.c)()],r.prototype,"disableBoundingBoxesFromEffectLayer",void 0),r}();U.a.AddParser(at.a.NAME_EFFECTLAYER,function(r,t,e,n){if(r.effectLayers){e.effectLayers||(e.effectLayers=new Array);for(var i=0;i<r.effectLayers.length;i++){var o=po.Parse(r.effectLayers[i],t,n);e.effectLayers.push(o)}}}),U.a.prototype.removeEffectLayer=function(r){var t=this.effectLayers.indexOf(r);return t!==-1&&this.effectLayers.splice(t,1),t},U.a.prototype.addEffectLayer=function(r){this.effectLayers.push(r)};var Ou=function(){function r(t){this.name=at.a.NAME_EFFECTLAYER,this._renderEffects=!1,this._needStencil=!1,this._previousStencilState=!1,this.scene=t,this._engine=t.getEngine(),t.effectLayers=new Array}return r.prototype.register=function(){this.scene._isReadyForMeshStage.registerStep(at.a.STEP_ISREADYFORMESH_EFFECTLAYER,this,this._isReadyForMesh),this.scene._cameraDrawRenderTargetStage.registerStep(at.a.STEP_CAMERADRAWRENDERTARGET_EFFECTLAYER,this,this._renderMainTexture),this.scene._beforeCameraDrawStage.registerStep(at.a.STEP_BEFORECAMERADRAW_EFFECTLAYER,this,this._setStencil),this.scene._afterRenderingGroupDrawStage.registerStep(at.a.STEP_AFTERRENDERINGGROUPDRAW_EFFECTLAYER_DRAW,this,this._drawRenderingGroup),this.scene._afterCameraDrawStage.registerStep(at.a.STEP_AFTERCAMERADRAW_EFFECTLAYER,this,this._setStencilBack),this.scene._afterCameraDrawStage.registerStep(at.a.STEP_AFTERCAMERADRAW_EFFECTLAYER_DRAW,this,this._drawCamera)},r.prototype.rebuild=function(){for(var t=0,e=this.scene.effectLayers;t<e.length;t++)e[t]._rebuild()},r.prototype.serialize=function(t){t.effectLayers=[];for(var e=0,n=this.scene.effectLayers;e<n.length;e++){var i=n[e];i.serialize&&t.effectLayers.push(i.serialize())}},r.prototype.addFromContainer=function(t){var e=this;t.effectLayers&&t.effectLayers.forEach(function(n){e.scene.addEffectLayer(n)})},r.prototype.removeFromContainer=function(t,e){var n=this;t.effectLayers&&t.effectLayers.forEach(function(i){n.scene.removeEffectLayer(i),e&&i.dispose()})},r.prototype.dispose=function(){for(var t=this.scene.effectLayers;t.length;)t[0].dispose()},r.prototype._isReadyForMesh=function(t,e){for(var n=0,i=this.scene.effectLayers;n<i.length;n++){var o=i[n];if(o.hasMesh(t))for(var a=0,s=t.subMeshes;a<s.length;a++){var d=s[a];if(!o.isReady(d,e))return!1}}return!0},r.prototype._renderMainTexture=function(t){this._renderEffects=!1,this._needStencil=!1;var e=!1,n=this.scene.effectLayers;if(n&&n.length>0){this._previousStencilState=this._engine.getStencilBuffer();for(var i=0,o=n;i<o.length;i++){var a=o[i];if(a.shouldRender()&&(!a.camera||a.camera.cameraRigMode===gt.a.RIG_MODE_NONE&&t===a.camera||a.camera.cameraRigMode!==gt.a.RIG_MODE_NONE&&a.camera._rigCameras.indexOf(t)>-1)){this._renderEffects=!0,this._needStencil=this._needStencil||a.needStencil();var s=a._mainTexture;s._shouldRender()&&(this.scene.incrementRenderId(),s.render(!1,!1),e=!0)}}this.scene.incrementRenderId()}return e},r.prototype._setStencil=function(){this._needStencil&&this._engine.setStencilBuffer(!0)},r.prototype._setStencilBack=function(){this._needStencil&&this._engine.setStencilBuffer(this._previousStencilState)},r.prototype._draw=function(t){if(this._renderEffects){this._engine.setDepthBuffer(!1);for(var e=this.scene.effectLayers,n=0;n<e.length;n++){var i=e[n];i.renderingGroupId===t&&i.shouldRender()&&i.render()}this._engine.setDepthBuffer(!0)}},r.prototype._drawCamera=function(){this._renderEffects&&this._draw(-1)},r.prototype._drawRenderingGroup=function(t){!this.scene._isInIntermediateRendering()&&this._renderEffects&&this._draw(t)},r}();po._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_EFFECTLAYER);t||(t=new Ou(r),r._addComponent(t))};var A_=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-#ifdef EMISSIVE
-uniform sampler2D textureSampler2;
-#endif
-
-uniform float offset;
-void main(void) {
-vec4 baseColor=texture2D(textureSampler,vUV);
-#ifdef EMISSIVE
-baseColor+=texture2D(textureSampler2,vUV);
-baseColor*=offset;
-#else
-baseColor.a=abs(offset-baseColor.a);
-#ifdef STROKE
-float alpha=smoothstep(.0,.1,baseColor.a);
-baseColor.a=alpha;
-baseColor.rgb=baseColor.rgb*alpha;
-#endif
-#endif
-gl_FragColor=baseColor;
-}`;ze.a.ShadersStore.glowMapMergePixelShader=A_;var P_=`
-attribute vec2 position;
-
-varying vec2 vUV;
-const vec2 madd=vec2(0.5,0.5);
-void main(void) {
-vUV=position*madd+madd;
-gl_Position=vec4(position,0.0,1.0);
-}`;ze.a.ShadersStore.glowMapMergeVertexShader=P_,U.a.prototype.getGlowLayerByName=function(r){for(var t=0;t<this.effectLayers.length;t++)if(this.effectLayers[t].name===r&&this.effectLayers[t].getEffectName()===ra.EffectName)return this.effectLayers[t];return null};var ra=function(r){function t(e,n,i){var o=r.call(this,e,n)||this;return o._intensity=1,o._includedOnlyMeshes=[],o._excludedMeshes=[],o._meshesUsingTheirOwnMaterials=[],o.neutralColor=new M.b(0,0,0,1),o._options=Object(c.a)({mainTextureRatio:t.DefaultTextureRatio,blurKernelSize:32,mainTextureFixedSize:void 0,camera:null,mainTextureSamples:1,renderingGroupId:-1},i),o._init({alphaBlendingMode:h.a.ALPHA_ADD,camera:o._options.camera,mainTextureFixedSize:o._options.mainTextureFixedSize,mainTextureRatio:o._options.mainTextureRatio,renderingGroupId:o._options.renderingGroupId}),o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"blurKernelSize",{get:function(){return this._horizontalBlurPostprocess1.kernel},set:function(e){this._horizontalBlurPostprocess1.kernel=e,this._verticalBlurPostprocess1.kernel=e,this._horizontalBlurPostprocess2.kernel=e,this._verticalBlurPostprocess2.kernel=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"intensity",{get:function(){return this._intensity},set:function(e){this._intensity=e},enumerable:!1,configurable:!0}),t.prototype.getEffectName=function(){return t.EffectName},t.prototype._createMergeEffect=function(){return this._engine.createEffect("glowMapMerge",[Oe.b.PositionKind],["offset"],["textureSampler","textureSampler2"],`#define EMISSIVE 
-`)},t.prototype._createTextureAndPostProcesses=function(){var e=this,n=this._mainTextureDesiredSize.width,i=this._mainTextureDesiredSize.height;n=this._engine.needPOTTextures?Ue.a.GetExponentOfTwo(n,this._maxSize):n,i=this._engine.needPOTTextures?Ue.a.GetExponentOfTwo(i,this._maxSize):i;var o=0;o=this._engine.getCaps().textureHalfFloatRender?h.a.TEXTURETYPE_HALF_FLOAT:h.a.TEXTURETYPE_UNSIGNED_INT,this._blurTexture1=new sn("GlowLayerBlurRTT",{width:n,height:i},this._scene,!1,!0,o),this._blurTexture1.wrapU=we.a.CLAMP_ADDRESSMODE,this._blurTexture1.wrapV=we.a.CLAMP_ADDRESSMODE,this._blurTexture1.updateSamplingMode(we.a.BILINEAR_SAMPLINGMODE),this._blurTexture1.renderParticles=!1,this._blurTexture1.ignoreCameraViewport=!0;var a=Math.floor(n/2),s=Math.floor(i/2);this._blurTexture2=new sn("GlowLayerBlurRTT2",{width:a,height:s},this._scene,!1,!0,o),this._blurTexture2.wrapU=we.a.CLAMP_ADDRESSMODE,this._blurTexture2.wrapV=we.a.CLAMP_ADDRESSMODE,this._blurTexture2.updateSamplingMode(we.a.BILINEAR_SAMPLINGMODE),this._blurTexture2.renderParticles=!1,this._blurTexture2.ignoreCameraViewport=!0,this._textures=[this._blurTexture1,this._blurTexture2],this._horizontalBlurPostprocess1=new gn("GlowLayerHBP1",new u.d(1,0),this._options.blurKernelSize/2,{width:n,height:i},null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,o),this._horizontalBlurPostprocess1.width=n,this._horizontalBlurPostprocess1.height=i,this._horizontalBlurPostprocess1.onApplyObservable.add(function(d){d.setTexture("textureSampler",e._mainTexture)}),this._verticalBlurPostprocess1=new gn("GlowLayerVBP1",new u.d(0,1),this._options.blurKernelSize/2,{width:n,height:i},null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,o),this._horizontalBlurPostprocess2=new gn("GlowLayerHBP2",new u.d(1,0),this._options.blurKernelSize/2,{width:a,height:s},null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,o),this._horizontalBlurPostprocess2.width=a,this._horizontalBlurPostprocess2.height=s,this._horizontalBlurPostprocess2.onApplyObservable.add(function(d){d.setTexture("textureSampler",e._blurTexture1)}),this._verticalBlurPostprocess2=new gn("GlowLayerVBP2",new u.d(0,1),this._options.blurKernelSize/2,{width:a,height:s},null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,o),this._postProcesses=[this._horizontalBlurPostprocess1,this._verticalBlurPostprocess1,this._horizontalBlurPostprocess2,this._verticalBlurPostprocess2],this._postProcesses1=[this._horizontalBlurPostprocess1,this._verticalBlurPostprocess1],this._postProcesses2=[this._horizontalBlurPostprocess2,this._verticalBlurPostprocess2],this._mainTexture.samples=this._options.mainTextureSamples,this._mainTexture.onAfterUnbindObservable.add(function(){var d=e._blurTexture1.getInternalTexture();if(d){e._scene.postProcessManager.directRender(e._postProcesses1,d,!0);var p=e._blurTexture2.getInternalTexture();p&&e._scene.postProcessManager.directRender(e._postProcesses2,p,!0),e._engine.unBindFramebuffer(p??d,!0)}}),this._postProcesses.map(function(d){d.autoClear=!1})},t.prototype.isReady=function(e,n){var i=e.getMaterial(),o=e.getRenderingMesh();if(!i||!o)return!1;var a=i.emissiveTexture;return r.prototype._isReady.call(this,e,n,a)},t.prototype.needStencil=function(){return!1},t.prototype._canRenderMesh=function(e,n){return!0},t.prototype._internalRender=function(e){e.setTexture("textureSampler",this._blurTexture1),e.setTexture("textureSampler2",this._blurTexture2),e.setFloat("offset",this._intensity);var n=this._engine,i=n.getStencilBuffer();n.setStencilBuffer(!1),n.drawElementsType(Ht.a.TriangleFillMode,0,6),n.setStencilBuffer(i)},t.prototype._setEmissiveTextureAndColor=function(e,n,i){var o=1;this.customEmissiveTextureSelector?this._emissiveTextureAndColor.texture=this.customEmissiveTextureSelector(e,n,i):i?(this._emissiveTextureAndColor.texture=i.emissiveTexture,this._emissiveTextureAndColor.texture&&(o=this._emissiveTextureAndColor.texture.level)):this._emissiveTextureAndColor.texture=null,this.customEmissiveColorSelector?this.customEmissiveColorSelector(e,n,i,this._emissiveTextureAndColor.color):i.emissiveColor?this._emissiveTextureAndColor.color.set(i.emissiveColor.r*o,i.emissiveColor.g*o,i.emissiveColor.b*o,i.alpha):this._emissiveTextureAndColor.color.set(this.neutralColor.r,this.neutralColor.g,this.neutralColor.b,this.neutralColor.a)},t.prototype._shouldRenderMesh=function(e){return this.hasMesh(e)},t.prototype._addCustomEffectDefines=function(e){e.push("#define GLOW")},t.prototype.addExcludedMesh=function(e){this._excludedMeshes.indexOf(e.uniqueId)===-1&&this._excludedMeshes.push(e.uniqueId)},t.prototype.removeExcludedMesh=function(e){var n=this._excludedMeshes.indexOf(e.uniqueId);n!==-1&&this._excludedMeshes.splice(n,1)},t.prototype.addIncludedOnlyMesh=function(e){this._includedOnlyMeshes.indexOf(e.uniqueId)===-1&&this._includedOnlyMeshes.push(e.uniqueId)},t.prototype.removeIncludedOnlyMesh=function(e){var n=this._includedOnlyMeshes.indexOf(e.uniqueId);n!==-1&&this._includedOnlyMeshes.splice(n,1)},t.prototype.hasMesh=function(e){return!!r.prototype.hasMesh.call(this,e)&&(this._includedOnlyMeshes.length?this._includedOnlyMeshes.indexOf(e.uniqueId)!==-1:!this._excludedMeshes.length||this._excludedMeshes.indexOf(e.uniqueId)===-1)},t.prototype._useMeshMaterial=function(e){return this._meshesUsingTheirOwnMaterials.length!=0&&this._meshesUsingTheirOwnMaterials.indexOf(e.uniqueId)>-1},t.prototype.referenceMeshToUseItsOwnMaterial=function(e){this._meshesUsingTheirOwnMaterials.push(e.uniqueId)},t.prototype.unReferenceMeshFromUsingItsOwnMaterial=function(e){for(var n=this._meshesUsingTheirOwnMaterials.indexOf(e.uniqueId);n>=0;)this._meshesUsingTheirOwnMaterials.splice(n,1),n=this._meshesUsingTheirOwnMaterials.indexOf(e.uniqueId)},t.prototype._disposeMesh=function(e){this.removeIncludedOnlyMesh(e),this.removeExcludedMesh(e)},t.prototype.getClassName=function(){return"GlowLayer"},t.prototype.serialize=function(){var e,n=L.a.Serialize(this);if(n.customType="BABYLON.GlowLayer",n.includedMeshes=[],this._includedOnlyMeshes.length)for(e=0;e<this._includedOnlyMeshes.length;e++)(i=this._scene.getMeshByUniqueID(this._includedOnlyMeshes[e]))&&n.includedMeshes.push(i.id);if(n.excludedMeshes=[],this._excludedMeshes.length)for(e=0;e<this._excludedMeshes.length;e++){var i;(i=this._scene.getMeshByUniqueID(this._excludedMeshes[e]))&&n.excludedMeshes.push(i.id)}return n},t.Parse=function(e,n,i){var o,a=L.a.Parse(function(){return new t(e.name,n,e.options)},e,n,i);for(o=0;o<e.excludedMeshes.length;o++)(s=n.getMeshByID(e.excludedMeshes[o]))&&a.addExcludedMesh(s);for(o=0;o<e.includedMeshes.length;o++){var s;(s=n.getMeshByID(e.includedMeshes[o]))&&a.addIncludedOnlyMesh(s)}return a},t.EffectName="GlowLayer",t.DefaultBlurKernelSize=32,t.DefaultTextureRatio=.5,Object(c.c)([Object(L.c)()],t.prototype,"blurKernelSize",null),Object(c.c)([Object(L.c)()],t.prototype,"intensity",null),Object(c.c)([Object(L.c)("options")],t.prototype,"_options",void 0),t}(po);R.a.RegisteredTypes["BABYLON.GlowLayer"]=ra;var C_=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-
-uniform vec2 screenSize;
-uniform vec2 direction;
-uniform float blurWidth;
-
-float getLuminance(vec3 color)
-{
-return dot(color,vec3(0.2126,0.7152,0.0722));
-}
-void main(void)
-{
-float weights[7];
-weights[0]=0.05;
-weights[1]=0.1;
-weights[2]=0.2;
-weights[3]=0.3;
-weights[4]=0.2;
-weights[5]=0.1;
-weights[6]=0.05;
-vec2 texelSize=vec2(1.0/screenSize.x,1.0/screenSize.y);
-vec2 texelStep=texelSize*direction*blurWidth;
-vec2 start=vUV-3.0*texelStep;
-vec4 baseColor=vec4(0.,0.,0.,0.);
-vec2 texelOffset=vec2(0.,0.);
-for (int i=0; i<7; i++)
-{
-
-vec4 texel=texture2D(textureSampler,start+texelOffset);
-baseColor.a+=texel.a*weights[i];
-
-float luminance=getLuminance(baseColor.rgb);
-float luminanceTexel=getLuminance(texel.rgb);
-float choice=step(luminanceTexel,luminance);
-baseColor.rgb=choice*baseColor.rgb+(1.0-choice)*texel.rgb;
-texelOffset+=texelStep;
-}
-gl_FragColor=baseColor;
-}`;ze.a.ShadersStore.glowBlurPostProcessPixelShader=C_,U.a.prototype.getHighlightLayerByName=function(r){for(var t=0;t<this.effectLayers.length;t++)if(this.effectLayers[t].name===r&&this.effectLayers[t].getEffectName()===Gs.EffectName)return this.effectLayers[t];return null};var Mu=function(r){function t(e,n,i,o,a,s,d,p){s===void 0&&(s=we.a.BILINEAR_SAMPLINGMODE);var b=r.call(this,e,"glowBlurPostProcess",["screenSize","direction","blurWidth"],null,o,a,s,d,p)||this;return b.direction=n,b.kernel=i,b.onApplyObservable.add(function(P){P.setFloat2("screenSize",b.width,b.height),P.setVector2("direction",b.direction),P.setFloat("blurWidth",b.kernel)}),b}return Object(c.d)(t,r),t}(_t),Gs=function(r){function t(e,n,i){var o=r.call(this,e,n)||this;return o.name=e,o.innerGlow=!0,o.outerGlow=!0,o.onBeforeBlurObservable=new x.c,o.onAfterBlurObservable=new x.c,o._instanceGlowingMeshStencilReference=t.GlowingMeshStencilReference++,o._meshes={},o._excludedMeshes={},o.neutralColor=t.NeutralColor,o._engine.isStencilEnable||l.a.Warn("Rendering the Highlight Layer requires the stencil to be active on the canvas. var engine = new Engine(canvas, antialias, { stencil: true }"),o._options=Object(c.a)({mainTextureRatio:.5,blurTextureSizeRatio:.5,blurHorizontalSize:1,blurVerticalSize:1,alphaBlendingMode:h.a.ALPHA_COMBINE,camera:null,renderingGroupId:-1},i),o._init({alphaBlendingMode:o._options.alphaBlendingMode,camera:o._options.camera,mainTextureFixedSize:o._options.mainTextureFixedSize,mainTextureRatio:o._options.mainTextureRatio,renderingGroupId:o._options.renderingGroupId}),o._shouldRender=!1,o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"blurHorizontalSize",{get:function(){return this._horizontalBlurPostprocess.kernel},set:function(e){this._horizontalBlurPostprocess.kernel=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"blurVerticalSize",{get:function(){return this._verticalBlurPostprocess.kernel},set:function(e){this._verticalBlurPostprocess.kernel=e},enumerable:!1,configurable:!0}),t.prototype.getEffectName=function(){return t.EffectName},t.prototype._createMergeEffect=function(){return this._engine.createEffect("glowMapMerge",[Oe.b.PositionKind],["offset"],["textureSampler"],this._options.isStroke?`#define STROKE 
-`:void 0)},t.prototype._createTextureAndPostProcesses=function(){var e=this,n=this._mainTextureDesiredSize.width*this._options.blurTextureSizeRatio,i=this._mainTextureDesiredSize.height*this._options.blurTextureSizeRatio;n=this._engine.needPOTTextures?Ue.a.GetExponentOfTwo(n,this._maxSize):n,i=this._engine.needPOTTextures?Ue.a.GetExponentOfTwo(i,this._maxSize):i;var o=0;o=this._engine.getCaps().textureHalfFloatRender?h.a.TEXTURETYPE_HALF_FLOAT:h.a.TEXTURETYPE_UNSIGNED_INT,this._blurTexture=new sn("HighlightLayerBlurRTT",{width:n,height:i},this._scene,!1,!0,o),this._blurTexture.wrapU=we.a.CLAMP_ADDRESSMODE,this._blurTexture.wrapV=we.a.CLAMP_ADDRESSMODE,this._blurTexture.anisotropicFilteringLevel=16,this._blurTexture.updateSamplingMode(we.a.TRILINEAR_SAMPLINGMODE),this._blurTexture.renderParticles=!1,this._blurTexture.ignoreCameraViewport=!0,this._textures=[this._blurTexture],this._options.alphaBlendingMode===h.a.ALPHA_COMBINE?(this._downSamplePostprocess=new Fi("HighlightLayerPPP",this._options.blurTextureSizeRatio,null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine()),this._downSamplePostprocess.onApplyObservable.add(function(a){a.setTexture("textureSampler",e._mainTexture)}),this._horizontalBlurPostprocess=new Mu("HighlightLayerHBP",new u.d(1,0),this._options.blurHorizontalSize,1,null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine()),this._horizontalBlurPostprocess.onApplyObservable.add(function(a){a.setFloat2("screenSize",n,i)}),this._verticalBlurPostprocess=new Mu("HighlightLayerVBP",new u.d(0,1),this._options.blurVerticalSize,1,null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine()),this._verticalBlurPostprocess.onApplyObservable.add(function(a){a.setFloat2("screenSize",n,i)}),this._postProcesses=[this._downSamplePostprocess,this._horizontalBlurPostprocess,this._verticalBlurPostprocess]):(this._horizontalBlurPostprocess=new gn("HighlightLayerHBP",new u.d(1,0),this._options.blurHorizontalSize/2,{width:n,height:i},null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,o),this._horizontalBlurPostprocess.width=n,this._horizontalBlurPostprocess.height=i,this._horizontalBlurPostprocess.onApplyObservable.add(function(a){a.setTexture("textureSampler",e._mainTexture)}),this._verticalBlurPostprocess=new gn("HighlightLayerVBP",new u.d(0,1),this._options.blurVerticalSize/2,{width:n,height:i},null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,o),this._postProcesses=[this._horizontalBlurPostprocess,this._verticalBlurPostprocess]),this._mainTexture.onAfterUnbindObservable.add(function(){e.onBeforeBlurObservable.notifyObservers(e);var a=e._blurTexture.getInternalTexture();a&&(e._scene.postProcessManager.directRender(e._postProcesses,a,!0),e._engine.unBindFramebuffer(a,!0)),e.onAfterBlurObservable.notifyObservers(e)}),this._postProcesses.map(function(a){a.autoClear=!1})},t.prototype.needStencil=function(){return!0},t.prototype.isReady=function(e,n){var i=e.getMaterial(),o=e.getRenderingMesh();if(!i||!o||!this._meshes)return!1;var a=null,s=this._meshes[o.uniqueId];return s&&s.glowEmissiveOnly&&i&&(a=i.emissiveTexture),r.prototype._isReady.call(this,e,n,a)},t.prototype._internalRender=function(e){e.setTexture("textureSampler",this._blurTexture);var n=this._engine;n.cacheStencilState(),n.setStencilOperationPass(h.a.REPLACE),n.setStencilOperationFail(h.a.KEEP),n.setStencilOperationDepthFail(h.a.KEEP),n.setStencilMask(0),n.setStencilBuffer(!0),n.setStencilFunctionReference(this._instanceGlowingMeshStencilReference),this.outerGlow&&(e.setFloat("offset",0),n.setStencilFunction(h.a.NOTEQUAL),n.drawElementsType(Ht.a.TriangleFillMode,0,6)),this.innerGlow&&(e.setFloat("offset",1),n.setStencilFunction(h.a.EQUAL),n.drawElementsType(Ht.a.TriangleFillMode,0,6)),n.restoreStencilState()},t.prototype.shouldRender=function(){return!!r.prototype.shouldRender.call(this)&&!!this._meshes},t.prototype._shouldRenderMesh=function(e){return(!this._excludedMeshes||!this._excludedMeshes[e.uniqueId])&&!!r.prototype.hasMesh.call(this,e)},t.prototype._canRenderMesh=function(e,n){return!0},t.prototype._addCustomEffectDefines=function(e){e.push("#define HIGHLIGHT")},t.prototype._setEmissiveTextureAndColor=function(e,n,i){var o=this._meshes[e.uniqueId];o?this._emissiveTextureAndColor.color.set(o.color.r,o.color.g,o.color.b,1):this._emissiveTextureAndColor.color.set(this.neutralColor.r,this.neutralColor.g,this.neutralColor.b,this.neutralColor.a),o&&o.glowEmissiveOnly&&i?(this._emissiveTextureAndColor.texture=i.emissiveTexture,this._emissiveTextureAndColor.color.set(1,1,1,1)):this._emissiveTextureAndColor.texture=null},t.prototype.addExcludedMesh=function(e){this._excludedMeshes&&(this._excludedMeshes[e.uniqueId]||(this._excludedMeshes[e.uniqueId]={mesh:e,beforeBind:e.onBeforeBindObservable.add(function(n){n.getEngine().setStencilBuffer(!1)}),afterRender:e.onAfterRenderObservable.add(function(n){n.getEngine().setStencilBuffer(!0)})}))},t.prototype.removeExcludedMesh=function(e){if(this._excludedMeshes){var n=this._excludedMeshes[e.uniqueId];n&&(n.beforeBind&&e.onBeforeBindObservable.remove(n.beforeBind),n.afterRender&&e.onAfterRenderObservable.remove(n.afterRender)),this._excludedMeshes[e.uniqueId]=null}},t.prototype.hasMesh=function(e){return!!this._meshes&&!!r.prototype.hasMesh.call(this,e)&&this._meshes[e.uniqueId]!==void 0&&this._meshes[e.uniqueId]!==null},t.prototype.addMesh=function(e,n,i){var o=this;if(i===void 0&&(i=!1),this._meshes){var a=this._meshes[e.uniqueId];a?a.color=n:(this._meshes[e.uniqueId]={mesh:e,color:n,observerHighlight:e.onBeforeBindObservable.add(function(s){o.isEnabled&&(o._excludedMeshes&&o._excludedMeshes[s.uniqueId]?o._defaultStencilReference(s):s.getScene().getEngine().setStencilFunctionReference(o._instanceGlowingMeshStencilReference))}),observerDefault:e.onAfterRenderObservable.add(function(s){o.isEnabled&&o._defaultStencilReference(s)}),glowEmissiveOnly:i},e.onDisposeObservable.add(function(){o._disposeMesh(e)})),this._shouldRender=!0}},t.prototype.removeMesh=function(e){if(this._meshes){var n=this._meshes[e.uniqueId];for(var i in n&&(n.observerHighlight&&e.onBeforeBindObservable.remove(n.observerHighlight),n.observerDefault&&e.onAfterRenderObservable.remove(n.observerDefault),delete this._meshes[e.uniqueId]),this._shouldRender=!1,this._meshes)if(this._meshes[i]){this._shouldRender=!0;break}}},t.prototype.removeAllMeshes=function(){if(this._meshes){for(var e in this._meshes)if(this._meshes.hasOwnProperty(e)){var n=this._meshes[e];n&&this.removeMesh(n.mesh)}}},t.prototype._defaultStencilReference=function(e){e.getScene().getEngine().setStencilFunctionReference(t.NormalMeshStencilReference)},t.prototype._disposeMesh=function(e){this.removeMesh(e),this.removeExcludedMesh(e)},t.prototype.dispose=function(){if(this._meshes){for(var e in this._meshes)(n=this._meshes[e])&&n.mesh&&(n.observerHighlight&&n.mesh.onBeforeBindObservable.remove(n.observerHighlight),n.observerDefault&&n.mesh.onAfterRenderObservable.remove(n.observerDefault));this._meshes=null}if(this._excludedMeshes){for(var e in this._excludedMeshes){var n;(n=this._excludedMeshes[e])&&(n.beforeBind&&n.mesh.onBeforeBindObservable.remove(n.beforeBind),n.afterRender&&n.mesh.onAfterRenderObservable.remove(n.afterRender))}this._excludedMeshes=null}r.prototype.dispose.call(this)},t.prototype.getClassName=function(){return"HighlightLayer"},t.prototype.serialize=function(){var e=L.a.Serialize(this);if(e.customType="BABYLON.HighlightLayer",e.meshes=[],this._meshes)for(var n in this._meshes){var i=this._meshes[n];i&&e.meshes.push({glowEmissiveOnly:i.glowEmissiveOnly,color:i.color.asArray(),meshId:i.mesh.id})}if(e.excludedMeshes=[],this._excludedMeshes)for(var o in this._excludedMeshes){var a=this._excludedMeshes[o];a&&e.excludedMeshes.push(a.mesh.id)}return e},t.Parse=function(e,n,i){var o,a=L.a.Parse(function(){return new t(e.name,n,e.options)},e,n,i);for(o=0;o<e.excludedMeshes.length;o++)(s=n.getMeshByID(e.excludedMeshes[o]))&&a.addExcludedMesh(s);for(o=0;o<e.meshes.length;o++){var s,d=e.meshes[o];(s=n.getMeshByID(d.meshId))&&a.addMesh(s,M.a.FromArray(d.color),d.glowEmissiveOnly)}return a},t.EffectName="HighlightLayer",t.NeutralColor=new M.b(0,0,0,0),t.GlowingMeshStencilReference=2,t.NormalMeshStencilReference=1,Object(c.c)([Object(L.c)()],t.prototype,"innerGlow",void 0),Object(c.c)([Object(L.c)()],t.prototype,"outerGlow",void 0),Object(c.c)([Object(L.c)()],t.prototype,"blurHorizontalSize",null),Object(c.c)([Object(L.c)()],t.prototype,"blurVerticalSize",null),Object(c.c)([Object(L.c)("options")],t.prototype,"_options",void 0),t}(po);R.a.RegisteredTypes["BABYLON.HighlightLayer"]=Gs;var Iu=function(){function r(t){this.name=at.a.NAME_LAYER,this.scene=t,this._engine=t.getEngine(),t.layers=new Array}return r.prototype.register=function(){this.scene._beforeCameraDrawStage.registerStep(at.a.STEP_BEFORECAMERADRAW_LAYER,this,this._drawCameraBackground),this.scene._afterCameraDrawStage.registerStep(at.a.STEP_AFTERCAMERADRAW_LAYER,this,this._drawCameraForeground),this.scene._beforeRenderTargetDrawStage.registerStep(at.a.STEP_BEFORERENDERTARGETDRAW_LAYER,this,this._drawRenderTargetBackground),this.scene._afterRenderTargetDrawStage.registerStep(at.a.STEP_AFTERRENDERTARGETDRAW_LAYER,this,this._drawRenderTargetForeground)},r.prototype.rebuild=function(){for(var t=0,e=this.scene.layers;t<e.length;t++)e[t]._rebuild()},r.prototype.dispose=function(){for(var t=this.scene.layers;t.length;)t[0].dispose()},r.prototype._draw=function(t){var e=this.scene.layers;if(e.length){this._engine.setDepthBuffer(!1);for(var n=0,i=e;n<i.length;n++){var o=i[n];t(o)&&o.render()}this._engine.setDepthBuffer(!0)}},r.prototype._drawCameraPredicate=function(t,e,n){return!t.renderOnlyInRenderTargetTextures&&t.isBackground===e&&(t.layerMask&n)!=0},r.prototype._drawCameraBackground=function(t){var e=this;this._draw(function(n){return e._drawCameraPredicate(n,!0,t.layerMask)})},r.prototype._drawCameraForeground=function(t){var e=this;this._draw(function(n){return e._drawCameraPredicate(n,!1,t.layerMask)})},r.prototype._drawRenderTargetPredicate=function(t,e,n,i){return t.renderTargetTextures.length>0&&t.isBackground===e&&t.renderTargetTextures.indexOf(i)>-1&&(t.layerMask&n)!=0},r.prototype._drawRenderTargetBackground=function(t){var e=this;this._draw(function(n){return e._drawRenderTargetPredicate(n,!0,e.scene.activeCamera.layerMask,t)})},r.prototype._drawRenderTargetForeground=function(t){var e=this;this._draw(function(n){return e._drawRenderTargetPredicate(n,!1,e.scene.activeCamera.layerMask,t)})},r.prototype.addFromContainer=function(t){var e=this;t.layers&&t.layers.forEach(function(n){e.scene.layers.push(n)})},r.prototype.removeFromContainer=function(t,e){var n=this;e===void 0&&(e=!1),t.layers&&t.layers.forEach(function(i){var o=n.scene.layers.indexOf(i);o!==-1&&n.scene.layers.splice(o,1),e&&i.dispose()})},r}(),x_=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-
-uniform vec4 color;
-
-#include<helperFunctions>
-void main(void) {
-vec4 baseColor=texture2D(textureSampler,vUV);
-#ifdef LINEAR
-baseColor.rgb=toGammaSpace(baseColor.rgb);
-#endif
-#ifdef ALPHATEST
-if (baseColor.a<0.4)
-discard;
-#endif
-gl_FragColor=baseColor*color;
-}`;ze.a.ShadersStore.layerPixelShader=x_;var R_=`
-attribute vec2 position;
-
-uniform vec2 scale;
-uniform vec2 offset;
-uniform mat4 textureMatrix;
-
-varying vec2 vUV;
-const vec2 madd=vec2(0.5,0.5);
-void main(void) {
-vec2 shiftedPosition=position*scale+offset;
-vUV=vec2(textureMatrix*vec4(shiftedPosition*madd+madd,1.0,0.0));
-gl_Position=vec4(shiftedPosition,0.0,1.0);
-}`;ze.a.ShadersStore.layerVertexShader=R_;var O_=function(){function r(t,e,n,i,o){this.name=t,this.scale=new u.d(1,1),this.offset=new u.d(0,0),this.alphaBlendingMode=h.a.ALPHA_COMBINE,this.layerMask=268435455,this.renderTargetTextures=[],this.renderOnlyInRenderTargetTextures=!1,this._vertexBuffers={},this.onDisposeObservable=new x.c,this.onBeforeRenderObservable=new x.c,this.onAfterRenderObservable=new x.c,this.texture=e?new we.a(e,n,!0):null,this.isBackground=i===void 0||i,this.color=o===void 0?new M.b(1,1,1,1):o,this._scene=n||te.a.LastCreatedScene;var a=this._scene._getComponent(at.a.NAME_LAYER);a||(a=new Iu(this._scene),this._scene._addComponent(a)),this._scene.layers.push(this);var s=this._scene.getEngine(),d=[];d.push(1,1),d.push(-1,1),d.push(-1,-1),d.push(1,-1);var p=new Oe.b(s,d,Oe.b.PositionKind,!1,!1,2);this._vertexBuffers[Oe.b.PositionKind]=p,this._createIndexBuffer()}return Object.defineProperty(r.prototype,"onDispose",{set:function(t){this._onDisposeObserver&&this.onDisposeObservable.remove(this._onDisposeObserver),this._onDisposeObserver=this.onDisposeObservable.add(t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"onBeforeRender",{set:function(t){this._onBeforeRenderObserver&&this.onBeforeRenderObservable.remove(this._onBeforeRenderObserver),this._onBeforeRenderObserver=this.onBeforeRenderObservable.add(t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"onAfterRender",{set:function(t){this._onAfterRenderObserver&&this.onAfterRenderObservable.remove(this._onAfterRenderObserver),this._onAfterRenderObserver=this.onAfterRenderObservable.add(t)},enumerable:!1,configurable:!0}),r.prototype._createIndexBuffer=function(){var t=this._scene.getEngine(),e=[];e.push(0),e.push(1),e.push(2),e.push(0),e.push(2),e.push(3),this._indexBuffer=t.createIndexBuffer(e)},r.prototype._rebuild=function(){var t=this._vertexBuffers[Oe.b.PositionKind];t&&t._rebuild(),this._createIndexBuffer()},r.prototype.render=function(){var t=this._scene.getEngine(),e="";this.alphaTest&&(e="#define ALPHATEST"),this.texture&&!this.texture.gammaSpace&&(e+=`\r
-#define LINEAR`),this._previousDefines!==e&&(this._previousDefines=e,this._effect=t.createEffect("layer",[Oe.b.PositionKind],["textureMatrix","color","scale","offset"],["textureSampler"],e));var n=this._effect;n&&n.isReady()&&this.texture&&this.texture.isReady()&&(t=this._scene.getEngine(),this.onBeforeRenderObservable.notifyObservers(this),t.enableEffect(n),t.setState(!1),n.setTexture("textureSampler",this.texture),n.setMatrix("textureMatrix",this.texture.getTextureMatrix()),n.setFloat4("color",this.color.r,this.color.g,this.color.b,this.color.a),n.setVector2("offset",this.offset),n.setVector2("scale",this.scale),t.bindBuffers(this._vertexBuffers,this._indexBuffer,n),this.alphaTest?t.drawElementsType(Ht.a.TriangleFillMode,0,6):(t.setAlphaMode(this.alphaBlendingMode),t.drawElementsType(Ht.a.TriangleFillMode,0,6),t.setAlphaMode(h.a.ALPHA_DISABLE)),this.onAfterRenderObservable.notifyObservers(this))},r.prototype.dispose=function(){var t=this._vertexBuffers[Oe.b.PositionKind];t&&(t.dispose(),this._vertexBuffers[Oe.b.PositionKind]=null),this._indexBuffer&&(this._scene.getEngine()._releaseBuffer(this._indexBuffer),this._indexBuffer=null),this.texture&&(this.texture.dispose(),this.texture=null),this.renderTargetTextures=[];var e=this._scene.layers.indexOf(this);this._scene.layers.splice(e,1),this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear(),this.onAfterRenderObservable.clear(),this.onBeforeRenderObservable.clear()},r}(),Du=function(){function r(t,e,n,i,o){this.size=t,this.position=e,this.alphaMode=h.a.ALPHA_ONEONE,this.color=n||new M.a(1,1,1),this.texture=i?new we.a(i,o.getScene(),!0):null,this._system=o,o.lensFlares.push(this)}return r.AddFlare=function(t,e,n,i,o){return new r(t,e,n,i,o)},r.prototype.dispose=function(){this.texture&&this.texture.dispose();var t=this._system.lensFlares.indexOf(this);this._system.lensFlares.splice(t,1)},r}(),M_=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-
-uniform vec4 color;
-void main(void) {
-vec4 baseColor=texture2D(textureSampler,vUV);
-gl_FragColor=baseColor*color;
-}`;ze.a.ShadersStore.lensFlarePixelShader=M_;var I_=`
-attribute vec2 position;
-
-uniform mat4 viewportMatrix;
-
-varying vec2 vUV;
-const vec2 madd=vec2(0.5,0.5);
-void main(void) {
-vUV=position*madd+madd;
-gl_Position=viewportMatrix*vec4(position,0.0,1.0);
-}`;ze.a.ShadersStore.lensFlareVertexShader=I_;var zs=function(){function r(t,e,n){this.name=t,this.lensFlares=new Array,this.borderLimit=300,this.viewportBorder=0,this.layerMask=268435455,this._vertexBuffers={},this._isEnabled=!0,this._scene=n||te.a.LastCreatedScene,r._SceneComponentInitialization(this._scene),this._emitter=e,this.id=t,n.lensFlareSystems.push(this),this.meshesSelectionPredicate=function(s){return n.activeCamera&&s.material&&s.isVisible&&s.isEnabled()&&s.isBlocker&&(s.layerMask&n.activeCamera.layerMask)!=0};var i=n.getEngine(),o=[];o.push(1,1),o.push(-1,1),o.push(-1,-1),o.push(1,-1),this._vertexBuffers[Oe.b.PositionKind]=new Oe.b(i,o,Oe.b.PositionKind,!1,!1,2);var a=[];a.push(0),a.push(1),a.push(2),a.push(0),a.push(2),a.push(3),this._indexBuffer=i.createIndexBuffer(a),this._effect=i.createEffect("lensFlare",[Oe.b.PositionKind],["color","viewportMatrix"],["textureSampler"],"")}return Object.defineProperty(r.prototype,"isEnabled",{get:function(){return this._isEnabled},set:function(t){this._isEnabled=t},enumerable:!1,configurable:!0}),r.prototype.getScene=function(){return this._scene},r.prototype.getEmitter=function(){return this._emitter},r.prototype.setEmitter=function(t){this._emitter=t},r.prototype.getEmitterPosition=function(){return this._emitter.getAbsolutePosition?this._emitter.getAbsolutePosition():this._emitter.position},r.prototype.computeEffectivePosition=function(t){var e=this.getEmitterPosition();return e=u.e.Project(e,u.a.Identity(),this._scene.getTransformMatrix(),t),this._positionX=e.x,this._positionY=e.y,e=u.e.TransformCoordinates(this.getEmitterPosition(),this._scene.getViewMatrix()),this.viewportBorder>0&&(t.x-=this.viewportBorder,t.y-=this.viewportBorder,t.width+=2*this.viewportBorder,t.height+=2*this.viewportBorder,e.x+=this.viewportBorder,e.y+=this.viewportBorder,this._positionX+=this.viewportBorder,this._positionY+=this.viewportBorder),e.z>0&&(this._positionX>t.x&&this._positionX<t.x+t.width&&this._positionY>t.y&&(this._positionY,t.y,t.height),!0)},r.prototype._isVisible=function(){if(!this._isEnabled||!this._scene.activeCamera)return!1;var t=this.getEmitterPosition().subtract(this._scene.activeCamera.globalPosition),e=t.length();t.normalize();var n=new fn.a(this._scene.activeCamera.globalPosition,t),i=this._scene.pickWithRay(n,this.meshesSelectionPredicate,!0);return!i||!i.hit||i.distance>e},r.prototype.render=function(){if(!this._effect.isReady()||!this._scene.activeCamera)return!1;var t,e,n=this._scene.getEngine(),i=this._scene.activeCamera.viewport.toGlobal(n.getRenderWidth(!0),n.getRenderHeight(!0));if(!this.computeEffectivePosition(i)||!this._isVisible())return!1;var o=(t=this._positionX<this.borderLimit+i.x?this.borderLimit+i.x-this._positionX:this._positionX>i.x+i.width-this.borderLimit?this._positionX-i.x-i.width+this.borderLimit:0)>(e=this._positionY<this.borderLimit+i.y?this.borderLimit+i.y-this._positionY:this._positionY>i.y+i.height-this.borderLimit?this._positionY-i.y-i.height+this.borderLimit:0)?t:e;(o-=this.viewportBorder)>this.borderLimit&&(o=this.borderLimit);var a=1-$.a.Clamp(o/this.borderLimit,0,1);if(a<0)return!1;a>1&&(a=1),this.viewportBorder>0&&(i.x+=this.viewportBorder,i.y+=this.viewportBorder,i.width-=2*this.viewportBorder,i.height-=2*this.viewportBorder,this._positionX-=this.viewportBorder,this._positionY-=this.viewportBorder);var s=i.x+i.width/2,d=i.y+i.height/2,p=s-this._positionX,b=d-this._positionY;n.enableEffect(this._effect),n.setState(!1),n.setDepthBuffer(!1),n.bindBuffers(this._vertexBuffers,this._indexBuffer,this._effect);for(var P=0;P<this.lensFlares.length;P++){var O=this.lensFlares[P];if(!O.texture||O.texture.isReady()){n.setAlphaMode(O.alphaMode);var B=s-p*O.position,F=d-b*O.position,z=O.size,J=O.size*n.getAspectRatio(this._scene.activeCamera,!0),ie=B/(i.width+2*i.x)*2-1,se=1-F/(i.height+2*i.y)*2,ce=u.a.FromValues(z/2,0,0,0,0,J/2,0,0,0,0,1,0,ie,se,0,1);this._effect.setMatrix("viewportMatrix",ce),this._effect.setTexture("textureSampler",O.texture),this._effect.setFloat4("color",O.color.r*a,O.color.g*a,O.color.b*a,1),n.drawElementsType(Ht.a.TriangleFillMode,0,6)}}return n.setDepthBuffer(!0),n.setAlphaMode(h.a.ALPHA_DISABLE),!0},r.prototype.dispose=function(){var t=this._vertexBuffers[Oe.b.PositionKind];for(t&&(t.dispose(),this._vertexBuffers[Oe.b.PositionKind]=null),this._indexBuffer&&(this._scene.getEngine()._releaseBuffer(this._indexBuffer),this._indexBuffer=null);this.lensFlares.length;)this.lensFlares[0].dispose();var e=this._scene.lensFlareSystems.indexOf(this);this._scene.lensFlareSystems.splice(e,1)},r.Parse=function(t,e,n){var i=e.getLastEntryByID(t.emitterId),o=t.name||"lensFlareSystem#"+t.emitterId,a=new r(o,i,e);a.id=t.id||o,a.borderLimit=t.borderLimit;for(var s=0;s<t.flares.length;s++){var d=t.flares[s];Du.AddFlare(d.size,d.position,M.a.FromArray(d.color),d.textureName?n+d.textureName:"",a)}return a},r.prototype.serialize=function(){var t={};t.id=this.id,t.name=this.name,t.emitterId=this.getEmitter().id,t.borderLimit=this.borderLimit,t.flares=[];for(var e=0;e<this.lensFlares.length;e++){var n=this.lensFlares[e];t.flares.push({size:n.size,position:n.position,color:n.color.asArray(),textureName:Xe.b.GetFilename(n.texture?n.texture.name:"")})}return t},r._SceneComponentInitialization=function(t){throw An.a.WarnImport("LensFlareSystemSceneComponent")},r}();U.a.AddParser(at.a.NAME_LENSFLARESYSTEM,function(r,t,e,n){if(r.lensFlareSystems!==void 0&&r.lensFlareSystems!==null){e.lensFlareSystems||(e.lensFlareSystems=new Array);for(var i=0,o=r.lensFlareSystems.length;i<o;i++){var a=r.lensFlareSystems[i],s=zs.Parse(a,t,n);e.lensFlareSystems.push(s)}}}),U.a.prototype.getLensFlareSystemByName=function(r){for(var t=0;t<this.lensFlareSystems.length;t++)if(this.lensFlareSystems[t].name===r)return this.lensFlareSystems[t];return null},U.a.prototype.getLensFlareSystemByID=function(r){for(var t=0;t<this.lensFlareSystems.length;t++)if(this.lensFlareSystems[t].id===r)return this.lensFlareSystems[t];return null},U.a.prototype.removeLensFlareSystem=function(r){var t=this.lensFlareSystems.indexOf(r);return t!==-1&&this.lensFlareSystems.splice(t,1),t},U.a.prototype.addLensFlareSystem=function(r){this.lensFlareSystems.push(r)};var Lu=function(){function r(t){this.name=at.a.NAME_LENSFLARESYSTEM,this.scene=t,t.lensFlareSystems=new Array}return r.prototype.register=function(){this.scene._afterCameraDrawStage.registerStep(at.a.STEP_AFTERCAMERADRAW_LENSFLARESYSTEM,this,this._draw)},r.prototype.rebuild=function(){},r.prototype.addFromContainer=function(t){var e=this;t.lensFlareSystems&&t.lensFlareSystems.forEach(function(n){e.scene.addLensFlareSystem(n)})},r.prototype.removeFromContainer=function(t,e){var n=this;t.lensFlareSystems&&t.lensFlareSystems.forEach(function(i){n.scene.removeLensFlareSystem(i),e&&i.dispose()})},r.prototype.serialize=function(t){t.lensFlareSystems=[];for(var e=0,n=this.scene.lensFlareSystems;e<n.length;e++){var i=n[e];t.lensFlareSystems.push(i.serialize())}},r.prototype.dispose=function(){for(var t=this.scene.lensFlareSystems;t.length;)t[0].dispose()},r.prototype._draw=function(t){if(this.scene.lensFlaresEnabled){var e=this.scene.lensFlareSystems;Xe.b.StartPerformanceCounter("Lens flares",e.length>0);for(var n=0,i=e;n<i.length;n++){var o=i[n];t.layerMask&o.layerMask&&o.render()}Xe.b.EndPerformanceCounter("Lens flares",e.length>0)}},r}();zs._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_LENSFLARESYSTEM);t||(t=new Lu(r),r._addComponent(t))};var D_=`
-
-
-
-
-float bayerDither2(vec2 _P) {
-return mod(2.0*_P.y+_P.x+1.0,4.0);
-}
-
-
-float bayerDither4(vec2 _P) {
-vec2 P1=mod(_P,2.0);
-vec2 P2=floor(0.5*mod(_P,4.0));
-return 4.0*bayerDither2(P1)+bayerDither2(P2);
-}
-
-float bayerDither8(vec2 _P) {
-vec2 P1=mod(_P,2.0);
-vec2 P2=floor(0.5*mod(_P,4.0));
-vec2 P4=floor(0.25*mod(_P,8.0));
-return 4.0*(4.0*bayerDither2(P1)+bayerDither2(P2))+bayerDither2(P4);
-}
-`;ze.a.IncludesShadersStore.bayerDitherFunctions=D_;var L_=`#if SM_FLOAT == 0
-#include<packingFunctions>
-#endif
-#if SM_SOFTTRANSPARENTSHADOW == 1
-#include<bayerDitherFunctions>
-uniform float softTransparentShadowSM;
-#endif
-varying float vDepthMetricSM;
-#if SM_USEDISTANCE == 1
-uniform vec3 lightDataSM;
-varying vec3 vPositionWSM;
-#endif
-uniform vec3 biasAndScaleSM;
-uniform vec2 depthValuesSM;
-#if defined(SM_DEPTHCLAMP) && SM_DEPTHCLAMP == 1
-varying float zSM;
-#endif
-`;ze.a.IncludesShadersStore.shadowMapFragmentDeclaration=L_;var N_=` float depthSM=vDepthMetricSM;
-#if defined(SM_DEPTHCLAMP) && SM_DEPTHCLAMP == 1
-#if SM_USEDISTANCE == 1
-depthSM=clamp(((length(vPositionWSM-lightDataSM)+depthValuesSM.x)/(depthValuesSM.y))+biasAndScaleSM.x,0.0,1.0);
-#else
-depthSM=clamp(((zSM+depthValuesSM.x)/(depthValuesSM.y))+biasAndScaleSM.x,0.0,1.0);
-#endif
-gl_FragDepth=depthSM;
-#elif SM_USEDISTANCE == 1
-depthSM=(length(vPositionWSM-lightDataSM)+depthValuesSM.x)/(depthValuesSM.y)+biasAndScaleSM.x;
-#endif
-#if SM_ESM == 1
-depthSM=clamp(exp(-min(87.,biasAndScaleSM.z*depthSM)),0.,1.);
-#endif
-#if SM_FLOAT == 1
-gl_FragColor=vec4(depthSM,1.0,1.0,1.0);
-#else
-gl_FragColor=pack(depthSM);
-#endif
-return;`;ze.a.IncludesShadersStore.shadowMapFragment=N_;var w_=`#include<shadowMapFragmentDeclaration>
-#ifdef ALPHATEST
-varying vec2 vUV;
-uniform sampler2D diffuseSampler;
-#endif
-#include<clipPlaneFragmentDeclaration>
-void main(void)
-{
-#include<clipPlaneFragment>
-#ifdef ALPHATEST
-float alphaFromAlphaTexture=texture2D(diffuseSampler,vUV).a;
-if (alphaFromAlphaTexture<0.4)
-discard;
-#endif
-#if SM_SOFTTRANSPARENTSHADOW == 1
-#ifdef ALPHATEST
-if ((bayerDither8(floor(mod(gl_FragCoord.xy,8.0))))/64.0>=softTransparentShadowSM*alphaFromAlphaTexture) discard;
-#else
-if ((bayerDither8(floor(mod(gl_FragCoord.xy,8.0))))/64.0>=softTransparentShadowSM) discard;
-#endif
-#endif
-#include<shadowMapFragment>
-}`;ze.a.ShadersStore.shadowMapPixelShader=w_;var F_=`#if SM_NORMALBIAS == 1
-uniform vec3 lightDataSM;
-#endif
-uniform vec3 biasAndScaleSM;
-uniform vec2 depthValuesSM;
-varying float vDepthMetricSM;
-#if SM_USEDISTANCE == 1
-varying vec3 vPositionWSM;
-#endif
-#if defined(SM_DEPTHCLAMP) && SM_DEPTHCLAMP == 1
-varying float zSM;
-#endif
-`;ze.a.IncludesShadersStore.shadowMapVertexDeclaration=F_;var B_=`
-#if SM_NORMALBIAS == 1
-#if SM_DIRECTIONINLIGHTDATA == 1
-vec3 worldLightDirSM=normalize(-lightDataSM.xyz);
-#else
-vec3 directionToLightSM=lightDataSM.xyz-worldPos.xyz;
-vec3 worldLightDirSM=normalize(directionToLightSM);
-#endif
-float ndlSM=dot(vNormalW,worldLightDirSM);
-float sinNLSM=sqrt(1.0-ndlSM*ndlSM);
-float normalBiasSM=biasAndScaleSM.y*sinNLSM;
-worldPos.xyz-=vNormalW*normalBiasSM;
-#endif
-`;ze.a.IncludesShadersStore.shadowMapVertexNormalBias=B_;var U_=`#if SM_USEDISTANCE == 1
-vPositionWSM=worldPos.xyz;
-#endif
-#if SM_DEPTHTEXTURE == 1
-
-gl_Position.z+=biasAndScaleSM.x*gl_Position.w;
-#endif
-#if defined(SM_DEPTHCLAMP) && SM_DEPTHCLAMP == 1
-zSM=gl_Position.z;
-gl_Position.z=0.0;
-#elif SM_USEDISTANCE == 0
-
-vDepthMetricSM=((gl_Position.z+depthValuesSM.x)/(depthValuesSM.y))+biasAndScaleSM.x;
-#endif
-`;ze.a.IncludesShadersStore.shadowMapVertexMetric=U_;var V_=`
-attribute vec3 position;
-#ifdef NORMAL
-attribute vec3 normal;
-#endif
-#include<bonesDeclaration>
-#include<morphTargetsVertexGlobalDeclaration>
-#include<morphTargetsVertexDeclaration>[0..maxSimultaneousMorphTargets]
-
-#include<instancesDeclaration>
-#include<helperFunctions>
-uniform mat4 viewProjection;
-#ifdef ALPHATEST
-varying vec2 vUV;
-uniform mat4 diffuseMatrix;
-#ifdef UV1
-attribute vec2 uv;
-#endif
-#ifdef UV2
-attribute vec2 uv2;
-#endif
-#endif
-#include<shadowMapVertexDeclaration>
-#include<clipPlaneVertexDeclaration>
-void main(void)
-{
-vec3 positionUpdated=position;
-#ifdef UV1
-vec2 uvUpdated=uv;
-#endif
-#ifdef NORMAL
-vec3 normalUpdated=normal;
-#endif
-#include<morphTargetsVertex>[0..maxSimultaneousMorphTargets]
-#include<instancesVertex>
-#include<bonesVertex>
-vec4 worldPos=finalWorld*vec4(positionUpdated,1.0);
-#ifdef NORMAL
-mat3 normWorldSM=mat3(finalWorld);
-#if defined(INSTANCES) && defined(THIN_INSTANCES)
-vec3 vNormalW=normalUpdated/vec3(dot(normWorldSM[0],normWorldSM[0]),dot(normWorldSM[1],normWorldSM[1]),dot(normWorldSM[2],normWorldSM[2]));
-vNormalW=normalize(normWorldSM*vNormalW);
-#else
-#ifdef NONUNIFORMSCALING
-normWorldSM=transposeMat3(inverseMat3(normWorldSM));
-#endif
-vec3 vNormalW=normalize(normWorldSM*normalUpdated);
-#endif
-#endif
-#include<shadowMapVertexNormalBias>
-
-gl_Position=viewProjection*worldPos;
-#include<shadowMapVertexMetric>
-#ifdef ALPHATEST
-#ifdef UV1
-vUV=vec2(diffuseMatrix*vec4(uvUpdated,1.0,0.0));
-#endif
-#ifdef UV2
-vUV=vec2(diffuseMatrix*vec4(uv2,1.0,0.0));
-#endif
-#endif
-#include<clipPlaneVertex>
-}`;ze.a.ShadersStore.shadowMapVertexShader=V_;var k_=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-
-uniform vec2 screenSize;
-void main(void)
-{
-vec4 colorDepth=vec4(0.0);
-for (int x=-OFFSET; x<=OFFSET; x++)
-for (int y=-OFFSET; y<=OFFSET; y++)
-colorDepth+=texture2D(textureSampler,vUV+vec2(x,y)/screenSize);
-gl_FragColor=(colorDepth/float((OFFSET*2+1)*(OFFSET*2+1)));
-}`;ze.a.ShadersStore.depthBoxBlurPixelShader=k_;var G_=`#if SM_SOFTTRANSPARENTSHADOW == 1
-if ((bayerDither8(floor(mod(gl_FragCoord.xy,8.0))))/64.0>=softTransparentShadowSM*alpha) discard;
-#endif
-`;ze.a.IncludesShadersStore.shadowMapFragmentSoftTransparentShadow=G_;var Nu=new u.a,wu=new u.a,Un=function(){function r(t,e,n){this.onBeforeShadowMapRenderObservable=new x.c,this.onAfterShadowMapRenderObservable=new x.c,this.onBeforeShadowMapRenderMeshObservable=new x.c,this.onAfterShadowMapRenderMeshObservable=new x.c,this._bias=5e-5,this._normalBias=0,this._blurBoxOffset=1,this._blurScale=2,this._blurKernel=1,this._useKernelBlur=!1,this._filter=r.FILTER_NONE,this._filteringQuality=r.QUALITY_HIGH,this._contactHardeningLightSizeUVRatio=.1,this._darkness=0,this._transparencyShadow=!1,this.enableSoftTransparentShadow=!1,this.frustumEdgeFalloff=0,this.forceBackFacesOnly=!1,this._lightDirection=u.e.Zero(),this._viewMatrix=u.a.Zero(),this._projectionMatrix=u.a.Zero(),this._transformMatrix=u.a.Zero(),this._cachedPosition=new u.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),this._cachedDirection=new u.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),this._currentFaceIndex=0,this._currentFaceIndexCache=0,this._defaultTextureMatrix=u.a.Identity(),this._mapSize=t,this._light=e,this._scene=e.getScene(),e._shadowGenerator=this,this.id=e.id,r._SceneComponentInitialization(this._scene);var i=this._scene.getEngine().getCaps();n?i.textureFloatRender&&i.textureFloatLinearFiltering?this._textureType=h.a.TEXTURETYPE_FLOAT:i.textureHalfFloatRender&&i.textureHalfFloatLinearFiltering?this._textureType=h.a.TEXTURETYPE_HALF_FLOAT:this._textureType=h.a.TEXTURETYPE_UNSIGNED_INT:i.textureHalfFloatRender&&i.textureHalfFloatLinearFiltering?this._textureType=h.a.TEXTURETYPE_HALF_FLOAT:i.textureFloatRender&&i.textureFloatLinearFiltering?this._textureType=h.a.TEXTURETYPE_FLOAT:this._textureType=h.a.TEXTURETYPE_UNSIGNED_INT,this._initializeGenerator(),this._applyFilterValues()}return Object.defineProperty(r.prototype,"bias",{get:function(){return this._bias},set:function(t){this._bias=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"normalBias",{get:function(){return this._normalBias},set:function(t){this._normalBias=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"blurBoxOffset",{get:function(){return this._blurBoxOffset},set:function(t){this._blurBoxOffset!==t&&(this._blurBoxOffset=t,this._disposeBlurPostProcesses())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"blurScale",{get:function(){return this._blurScale},set:function(t){this._blurScale!==t&&(this._blurScale=t,this._disposeBlurPostProcesses())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"blurKernel",{get:function(){return this._blurKernel},set:function(t){this._blurKernel!==t&&(this._blurKernel=t,this._disposeBlurPostProcesses())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"useKernelBlur",{get:function(){return this._useKernelBlur},set:function(t){this._useKernelBlur!==t&&(this._useKernelBlur=t,this._disposeBlurPostProcesses())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"depthScale",{get:function(){return this._depthScale!==void 0?this._depthScale:this._light.getDepthScale()},set:function(t){this._depthScale=t},enumerable:!1,configurable:!0}),r.prototype._validateFilter=function(t){return t},Object.defineProperty(r.prototype,"filter",{get:function(){return this._filter},set:function(t){if(t=this._validateFilter(t),this._light.needCube()){if(t===r.FILTER_BLUREXPONENTIALSHADOWMAP)return void(this.useExponentialShadowMap=!0);if(t===r.FILTER_BLURCLOSEEXPONENTIALSHADOWMAP)return void(this.useCloseExponentialShadowMap=!0);if(t===r.FILTER_PCF||t===r.FILTER_PCSS)return void(this.usePoissonSampling=!0)}t!==r.FILTER_PCF&&t!==r.FILTER_PCSS||this._scene.getEngine().webGLVersion!==1?this._filter!==t&&(this._filter=t,this._disposeBlurPostProcesses(),this._applyFilterValues(),this._light._markMeshesAsLightDirty()):this.usePoissonSampling=!0},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"usePoissonSampling",{get:function(){return this.filter===r.FILTER_POISSONSAMPLING},set:function(t){var e=this._validateFilter(r.FILTER_POISSONSAMPLING);(t||this.filter===r.FILTER_POISSONSAMPLING)&&(this.filter=t?e:r.FILTER_NONE)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"useExponentialShadowMap",{get:function(){return this.filter===r.FILTER_EXPONENTIALSHADOWMAP},set:function(t){var e=this._validateFilter(r.FILTER_EXPONENTIALSHADOWMAP);(t||this.filter===r.FILTER_EXPONENTIALSHADOWMAP)&&(this.filter=t?e:r.FILTER_NONE)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"useBlurExponentialShadowMap",{get:function(){return this.filter===r.FILTER_BLUREXPONENTIALSHADOWMAP},set:function(t){var e=this._validateFilter(r.FILTER_BLUREXPONENTIALSHADOWMAP);(t||this.filter===r.FILTER_BLUREXPONENTIALSHADOWMAP)&&(this.filter=t?e:r.FILTER_NONE)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"useCloseExponentialShadowMap",{get:function(){return this.filter===r.FILTER_CLOSEEXPONENTIALSHADOWMAP},set:function(t){var e=this._validateFilter(r.FILTER_CLOSEEXPONENTIALSHADOWMAP);(t||this.filter===r.FILTER_CLOSEEXPONENTIALSHADOWMAP)&&(this.filter=t?e:r.FILTER_NONE)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"useBlurCloseExponentialShadowMap",{get:function(){return this.filter===r.FILTER_BLURCLOSEEXPONENTIALSHADOWMAP},set:function(t){var e=this._validateFilter(r.FILTER_BLURCLOSEEXPONENTIALSHADOWMAP);(t||this.filter===r.FILTER_BLURCLOSEEXPONENTIALSHADOWMAP)&&(this.filter=t?e:r.FILTER_NONE)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"usePercentageCloserFiltering",{get:function(){return this.filter===r.FILTER_PCF},set:function(t){var e=this._validateFilter(r.FILTER_PCF);(t||this.filter===r.FILTER_PCF)&&(this.filter=t?e:r.FILTER_NONE)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"filteringQuality",{get:function(){return this._filteringQuality},set:function(t){this._filteringQuality!==t&&(this._filteringQuality=t,this._disposeBlurPostProcesses(),this._applyFilterValues(),this._light._markMeshesAsLightDirty())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"useContactHardeningShadow",{get:function(){return this.filter===r.FILTER_PCSS},set:function(t){var e=this._validateFilter(r.FILTER_PCSS);(t||this.filter===r.FILTER_PCSS)&&(this.filter=t?e:r.FILTER_NONE)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"contactHardeningLightSizeUVRatio",{get:function(){return this._contactHardeningLightSizeUVRatio},set:function(t){this._contactHardeningLightSizeUVRatio=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"darkness",{get:function(){return this._darkness},set:function(t){this.setDarkness(t)},enumerable:!1,configurable:!0}),r.prototype.getDarkness=function(){return this._darkness},r.prototype.setDarkness=function(t){return this._darkness=t>=1?1:t<=0?0:t,this},Object.defineProperty(r.prototype,"transparencyShadow",{get:function(){return this._transparencyShadow},set:function(t){this.setTransparencyShadow(t)},enumerable:!1,configurable:!0}),r.prototype.setTransparencyShadow=function(t){return this._transparencyShadow=t,this},r.prototype.getShadowMap=function(){return this._shadowMap},r.prototype.getShadowMapForRendering=function(){return this._shadowMap2?this._shadowMap2:this._shadowMap},r.prototype.getClassName=function(){return r.CLASSNAME},r.prototype.addShadowCaster=function(t,e){var n;return e===void 0&&(e=!0),this._shadowMap?(this._shadowMap.renderList||(this._shadowMap.renderList=[]),this._shadowMap.renderList.push(t),e&&(n=this._shadowMap.renderList).push.apply(n,t.getChildMeshes()),this):this},r.prototype.removeShadowCaster=function(t,e){if(e===void 0&&(e=!0),!this._shadowMap||!this._shadowMap.renderList)return this;var n=this._shadowMap.renderList.indexOf(t);if(n!==-1&&this._shadowMap.renderList.splice(n,1),e)for(var i=0,o=t.getChildren();i<o.length;i++){var a=o[i];this.removeShadowCaster(a)}return this},r.prototype.getLight=function(){return this._light},Object.defineProperty(r.prototype,"mapSize",{get:function(){return this._mapSize},set:function(t){this._mapSize=t,this._light._markMeshesAsLightDirty(),this.recreateShadowMap()},enumerable:!1,configurable:!0}),r.prototype._initializeGenerator=function(){this._light._markMeshesAsLightDirty(),this._initializeShadowMap()},r.prototype._createTargetRenderTexture=function(){this._scene.getEngine().webGLVersion>1?(this._shadowMap=new sn(this._light.name+"_shadowMap",this._mapSize,this._scene,!1,!0,this._textureType,this._light.needCube(),void 0,!1,!1),this._shadowMap.createDepthStencilTexture(h.a.LESS,!0)):this._shadowMap=new sn(this._light.name+"_shadowMap",this._mapSize,this._scene,!1,!0,this._textureType,this._light.needCube())},r.prototype._initializeShadowMap=function(){var t=this;if(this._createTargetRenderTexture(),this._shadowMap!==null){this._shadowMap.wrapU=we.a.CLAMP_ADDRESSMODE,this._shadowMap.wrapV=we.a.CLAMP_ADDRESSMODE,this._shadowMap.anisotropicFilteringLevel=1,this._shadowMap.updateSamplingMode(we.a.BILINEAR_SAMPLINGMODE),this._shadowMap.renderParticles=!1,this._shadowMap.ignoreCameraViewport=!0,this._storedUniqueId&&(this._shadowMap.uniqueId=this._storedUniqueId),this._shadowMap.customRenderFunction=this._renderForShadowMap.bind(this),this._shadowMap.customIsReadyFunction=function(a,s){return!0};var e=this._scene.getEngine();this._shadowMap.onBeforeRenderObservable.add(function(a){if(t._currentFaceIndex=a,t._filter===r.FILTER_PCF&&e.setColorWrite(!1),t._scene.getSceneUniformBuffer().useUbo){var s=t._scene.getSceneUniformBuffer();s.updateMatrix("viewProjection",t.getTransformMatrix()),s.updateMatrix("view",t._viewMatrix),s.update()}}),this._shadowMap.onAfterUnbindObservable.add(function(){if(t._scene.getSceneUniformBuffer().useUbo){var a=t._scene.getSceneUniformBuffer();a.updateMatrix("viewProjection",t._scene.getTransformMatrix()),a.updateMatrix("view",t._scene.getViewMatrix()),a.update()}if(t._filter===r.FILTER_PCF&&e.setColorWrite(!0),t.useBlurExponentialShadowMap||t.useBlurCloseExponentialShadowMap){var s=t.getShadowMapForRendering();if(s){var d=s.getInternalTexture();t._scene.postProcessManager.directRender(t._blurPostProcesses,d,!0),e.unBindFramebuffer(d,!0)}}});var n=new M.b(0,0,0,0),i=new M.b(1,1,1,1);this._shadowMap.onClearObservable.add(function(a){t._filter===r.FILTER_PCF?a.clear(i,!1,!0,!1):t.useExponentialShadowMap||t.useBlurExponentialShadowMap?a.clear(n,!0,!0,!1):a.clear(i,!0,!0,!1)}),this._shadowMap.onResizeObservable.add(function(a){t._storedUniqueId=t._shadowMap.uniqueId,t._mapSize=a.getRenderSize(),t._light._markMeshesAsLightDirty(),t.recreateShadowMap()});for(var o=to.b.MIN_RENDERINGGROUPS;o<to.b.MAX_RENDERINGGROUPS;o++)this._shadowMap.setRenderingAutoClearDepthStencil(o,!1)}},r.prototype._initializeBlurRTTAndPostProcesses=function(){var t=this,e=this._scene.getEngine(),n=this._mapSize/this.blurScale;this.useKernelBlur&&this.blurScale===1||(this._shadowMap2=new sn(this._light.name+"_shadowMap2",n,this._scene,!1,!0,this._textureType),this._shadowMap2.wrapU=we.a.CLAMP_ADDRESSMODE,this._shadowMap2.wrapV=we.a.CLAMP_ADDRESSMODE,this._shadowMap2.updateSamplingMode(we.a.BILINEAR_SAMPLINGMODE)),this.useKernelBlur?(this._kernelBlurXPostprocess=new gn(this._light.name+"KernelBlurX",new u.d(1,0),this.blurKernel,1,null,we.a.BILINEAR_SAMPLINGMODE,e,!1,this._textureType),this._kernelBlurXPostprocess.width=n,this._kernelBlurXPostprocess.height=n,this._kernelBlurXPostprocess.onApplyObservable.add(function(i){i.setTexture("textureSampler",t._shadowMap)}),this._kernelBlurYPostprocess=new gn(this._light.name+"KernelBlurY",new u.d(0,1),this.blurKernel,1,null,we.a.BILINEAR_SAMPLINGMODE,e,!1,this._textureType),this._kernelBlurXPostprocess.autoClear=!1,this._kernelBlurYPostprocess.autoClear=!1,this._textureType===h.a.TEXTURETYPE_UNSIGNED_INT&&(this._kernelBlurXPostprocess.packedFloat=!0,this._kernelBlurYPostprocess.packedFloat=!0),this._blurPostProcesses=[this._kernelBlurXPostprocess,this._kernelBlurYPostprocess]):(this._boxBlurPostprocess=new _t(this._light.name+"DepthBoxBlur","depthBoxBlur",["screenSize","boxOffset"],[],1,null,we.a.BILINEAR_SAMPLINGMODE,e,!1,"#define OFFSET "+this._blurBoxOffset,this._textureType),this._boxBlurPostprocess.onApplyObservable.add(function(i){i.setFloat2("screenSize",n,n),i.setTexture("textureSampler",t._shadowMap)}),this._boxBlurPostprocess.autoClear=!1,this._blurPostProcesses=[this._boxBlurPostprocess])},r.prototype._renderForShadowMap=function(t,e,n,i){var o,a=this._scene.getEngine(),s=a.getColorWrite();if(i.length){for(a.setColorWrite(!1),o=0;o<i.length;o++)this._renderSubMeshForShadowMap(i.data[o]);a.setColorWrite(s)}for(o=0;o<t.length;o++)this._renderSubMeshForShadowMap(t.data[o]);for(o=0;o<e.length;o++)this._renderSubMeshForShadowMap(e.data[o]);if(this._transparencyShadow)for(o=0;o<n.length;o++)this._renderSubMeshForShadowMap(n.data[o],!0);else for(o=0;o<n.length;o++)n.data[o].getEffectiveMesh()._internalAbstractMeshDataInfo._isActiveIntermediate=!1},r.prototype._bindCustomEffectForRenderSubMeshForShadowMap=function(t,e,n,i){var o,a,s,d,p,b;e.setMatrix((o=n?.viewProjection)!==null&&o!==void 0?o:"viewProjection",this.getTransformMatrix()),e.setMatrix((a=n?.view)!==null&&a!==void 0?a:"view",this._viewMatrix),e.setMatrix((s=n?.projection)!==null&&s!==void 0?s:"projection",this._projectionMatrix);var P=i.getWorldMatrix();e.setMatrix((d=n?.world)!==null&&d!==void 0?d:"world",P),P.multiplyToRef(this.getTransformMatrix(),Nu),e.setMatrix((p=n?.worldViewProjection)!==null&&p!==void 0?p:"worldViewProjection",Nu),P.multiplyToRef(this._viewMatrix,wu),e.setMatrix((b=n?.worldView)!==null&&b!==void 0?b:"worldView",wu)},r.prototype._renderSubMeshForShadowMap=function(t,e){var n,i;e===void 0&&(e=!1);var o=t.getRenderingMesh(),a=t.getEffectiveMesh(),s=this._scene,d=s.getEngine(),p=t.getMaterial();if(a._internalAbstractMeshDataInfo._isActiveIntermediate=!1,p&&t.verticesCount!==0&&t._renderId!==s.getRenderId()){d.setState(p.backFaceCulling);var b=o._getInstancesRenderList(t._id,!!t.getReplacementMesh());if(!b.mustReturn){var P=d.getCaps().instancedArrays&&(b.visibleInstances[t._id]!==null&&b.visibleInstances[t._id]!==void 0||o.hasThinInstances);if(!this.customAllowRendering||this.customAllowRendering(t))if(this.isReady(t,P,e)){t._renderId=s.getRenderId();var O=(n=o.material)===null||n===void 0?void 0:n.shadowDepthWrapper,B=(i=O?.getEffect(t,this))!==null&&i!==void 0?i:this._effect;if(d.enableEffect(B),o._bind(t,B,p.fillMode),this.getTransformMatrix(),B.setFloat3("biasAndScaleSM",this.bias,this.normalBias,this.depthScale),this.getLight().getTypeID()===xi.a.LIGHTTYPEID_DIRECTIONALLIGHT?B.setVector3("lightDataSM",this._cachedDirection):B.setVector3("lightDataSM",this._cachedPosition),s.activeCamera&&B.setFloat2("depthValuesSM",this.getLight().getDepthMinZ(s.activeCamera),this.getLight().getDepthMinZ(s.activeCamera)+this.getLight().getDepthMaxZ(s.activeCamera)),e&&this.enableSoftTransparentShadow&&B.setFloat("softTransparentShadowSM",a.visibility),O)t._effectOverride=B,O.standalone?O.baseMaterial.bindForSubMesh(a.getWorldMatrix(),o,t):p.bindForSubMesh(a.getWorldMatrix(),o,t),t._effectOverride=null;else{if(B.setMatrix("viewProjection",this.getTransformMatrix()),p&&p.needAlphaTesting()){var F=p.getAlphaTestTexture();F&&(B.setTexture("diffuseSampler",F),B.setMatrix("diffuseMatrix",F.getTextureMatrix()||this._defaultTextureMatrix))}if(o.useBones&&o.computeBonesUsingShaders&&o.skeleton){var z=o.skeleton;if(z.isUsingTextureForMatrices){var J=z.getTransformMatrixTexture(o);if(!J)return;B.setTexture("boneSampler",J),B.setFloat("boneTextureWidth",4*(z.bones.length+1))}else B.setMatrices("mBones",z.getTransformMatrices(o))}et.a.BindMorphTargetParameters(o,B),et.a.BindClipPlane(B,s)}this._bindCustomEffectForRenderSubMeshForShadowMap(t,B,O?._matriceNames,a),this.forceBackFacesOnly&&d.setState(!0,0,!1,!0),this.onBeforeShadowMapRenderMeshObservable.notifyObservers(o),this.onBeforeShadowMapRenderObservable.notifyObservers(B),o._processRendering(a,t,B,p.fillMode,b,P,function(ie,se){return B.setMatrix("world",se)}),this.forceBackFacesOnly&&d.setState(!0,0,!1,!1),this.onAfterShadowMapRenderObservable.notifyObservers(B),this.onAfterShadowMapRenderMeshObservable.notifyObservers(o)}else this._shadowMap&&this._shadowMap.resetRefreshCounter()}}},r.prototype._applyFilterValues=function(){this._shadowMap&&(this.filter===r.FILTER_NONE||this.filter===r.FILTER_PCSS?this._shadowMap.updateSamplingMode(we.a.NEAREST_SAMPLINGMODE):this._shadowMap.updateSamplingMode(we.a.BILINEAR_SAMPLINGMODE))},r.prototype.forceCompilation=function(t,e){var n=this,i=Object(c.a)({useInstances:!1},e),o=this.getShadowMap();if(o){var a=o.renderList;if(a){for(var s=new Array,d=0,p=a;d<p.length;d++){var b=p[d];s.push.apply(s,b.subMeshes)}if(s.length!==0){var P=0,O=function(){var B,F;if(n._scene&&n._scene.getEngine()){for(;n.isReady(s[P],i.useInstances,(F=(B=s[P].getMaterial())===null||B===void 0?void 0:B.needAlphaBlendingForMesh(s[P].getMesh()))!==null&&F!==void 0&&F);)if(++P>=s.length)return void(t&&t(n));setTimeout(O,16)}};O()}else t&&t(this)}else t&&t(this)}else t&&t(this)},r.prototype.forceCompilationAsync=function(t){var e=this;return new Promise(function(n){e.forceCompilation(function(){n()},t)})},r.prototype._isReadyCustomDefines=function(t,e,n){},r.prototype._prepareShadowDefines=function(t,e,n,i){n.push("#define SM_FLOAT "+(this._textureType!==h.a.TEXTURETYPE_UNSIGNED_INT?"1":"0")),n.push("#define SM_ESM "+(this.useExponentialShadowMap||this.useBlurExponentialShadowMap?"1":"0")),n.push("#define SM_DEPTHTEXTURE "+(this.usePercentageCloserFiltering||this.useContactHardeningShadow?"1":"0"));var o=t.getMesh();return n.push("#define SM_NORMALBIAS "+(this.normalBias&&o.isVerticesDataPresent(Oe.b.NormalKind)?"1":"0")),n.push("#define SM_DIRECTIONINLIGHTDATA "+(this.getLight().getTypeID()===xi.a.LIGHTTYPEID_DIRECTIONALLIGHT?"1":"0")),n.push("#define SM_USEDISTANCE "+(this._light.needCube()?"1":"0")),n.push("#define SM_SOFTTRANSPARENTSHADOW "+(this.enableSoftTransparentShadow&&i?"1":"0")),this._isReadyCustomDefines(n,t,e),n},r.prototype.isReady=function(t,e,n){var i=t.getMaterial(),o=i?.shadowDepthWrapper,a=[];if(this._prepareShadowDefines(t,e,a,n),o){if(!o.isReadyForSubMesh(t,a,this,e))return!1}else{var s=[Oe.b.PositionKind],d=t.getMesh();if(this.normalBias&&d.isVerticesDataPresent(Oe.b.NormalKind)&&(s.push(Oe.b.NormalKind),a.push("#define NORMAL"),d.nonUniformScaling&&a.push("#define NONUNIFORMSCALING")),i&&i.needAlphaTesting()){var p=i.getAlphaTestTexture();if(p){if(!p.isReady())return!1;a.push("#define ALPHATEST"),d.isVerticesDataPresent(Oe.b.UVKind)&&(s.push(Oe.b.UVKind),a.push("#define UV1")),d.isVerticesDataPresent(Oe.b.UV2Kind)&&p.coordinatesIndex===1&&(s.push(Oe.b.UV2Kind),a.push("#define UV2"))}}var b=new Sr.a;if(d.useBones&&d.computeBonesUsingShaders&&d.skeleton){s.push(Oe.b.MatricesIndicesKind),s.push(Oe.b.MatricesWeightsKind),d.numBoneInfluencers>4&&(s.push(Oe.b.MatricesIndicesExtraKind),s.push(Oe.b.MatricesWeightsExtraKind));var P=d.skeleton;a.push("#define NUM_BONE_INFLUENCERS "+d.numBoneInfluencers),d.numBoneInfluencers>0&&b.addCPUSkinningFallback(0,d),P.isUsingTextureForMatrices?a.push("#define BONETEXTURE"):a.push("#define BonesPerMesh "+(P.bones.length+1))}else a.push("#define NUM_BONE_INFLUENCERS 0");var O=d.morphTargetManager,B=0;O&&O.numInfluencers>0&&(a.push("#define MORPHTARGETS"),B=O.numInfluencers,a.push("#define NUM_MORPH_INFLUENCERS "+B),et.a.PrepareAttributesForMorphTargetsInfluencers(s,d,B));var F=this._scene;if(F.clipPlane&&a.push("#define CLIPPLANE"),F.clipPlane2&&a.push("#define CLIPPLANE2"),F.clipPlane3&&a.push("#define CLIPPLANE3"),F.clipPlane4&&a.push("#define CLIPPLANE4"),F.clipPlane5&&a.push("#define CLIPPLANE5"),F.clipPlane6&&a.push("#define CLIPPLANE6"),e&&(a.push("#define INSTANCES"),et.a.PushAttributesForInstances(s),t.getRenderingMesh().hasThinInstances&&a.push("#define THIN_INSTANCES")),this.customShaderOptions&&this.customShaderOptions.defines)for(var z=0,J=this.customShaderOptions.defines;z<J.length;z++){var ie=J[z];a.indexOf(ie)===-1&&a.push(ie)}var se=a.join(`
-`);if(this._cachedDefines!==se){this._cachedDefines=se;var ce="shadowMap",ue=["world","mBones","viewProjection","diffuseMatrix","lightDataSM","depthValuesSM","biasAndScaleSM","morphTargetInfluences","boneTextureWidth","vClipPlane","vClipPlane2","vClipPlane3","vClipPlane4","vClipPlane5","vClipPlane6","softTransparentShadowSM"],fe=["diffuseSampler","boneSampler"];if(this.customShaderOptions){if(ce=this.customShaderOptions.shaderName,this.customShaderOptions.attributes)for(var ve=0,Te=this.customShaderOptions.attributes;ve<Te.length;ve++){var Re=Te[ve];s.indexOf(Re)===-1&&s.push(Re)}if(this.customShaderOptions.uniforms)for(var Ae=0,Ee=this.customShaderOptions.uniforms;Ae<Ee.length;Ae++){var Se=Ee[Ae];ue.indexOf(Se)===-1&&ue.push(Se)}if(this.customShaderOptions.samplers)for(var Le=0,Ce=this.customShaderOptions.samplers;Le<Ce.length;Le++){var Ne=Ce[Le];fe.indexOf(Ne)===-1&&fe.push(Ne)}}this._effect=this._scene.getEngine().createEffect(ce,s,ue,fe,se,b,void 0,void 0,{maxSimultaneousMorphTargets:B})}if(!this._effect.isReady())return!1}return(this.useBlurExponentialShadowMap||this.useBlurCloseExponentialShadowMap)&&(this._blurPostProcesses&&this._blurPostProcesses.length||this._initializeBlurRTTAndPostProcesses()),!(this._kernelBlurXPostprocess&&!this._kernelBlurXPostprocess.isReady())&&!(this._kernelBlurYPostprocess&&!this._kernelBlurYPostprocess.isReady())&&!(this._boxBlurPostprocess&&!this._boxBlurPostprocess.isReady())},r.prototype.prepareDefines=function(t,e){var n=this._scene,i=this._light;n.shadowsEnabled&&i.shadowEnabled&&(t["SHADOW"+e]=!0,this.useContactHardeningShadow?(t["SHADOWPCSS"+e]=!0,this._filteringQuality===r.QUALITY_LOW?t["SHADOWLOWQUALITY"+e]=!0:this._filteringQuality===r.QUALITY_MEDIUM&&(t["SHADOWMEDIUMQUALITY"+e]=!0)):this.usePercentageCloserFiltering?(t["SHADOWPCF"+e]=!0,this._filteringQuality===r.QUALITY_LOW?t["SHADOWLOWQUALITY"+e]=!0:this._filteringQuality===r.QUALITY_MEDIUM&&(t["SHADOWMEDIUMQUALITY"+e]=!0)):this.usePoissonSampling?t["SHADOWPOISSON"+e]=!0:this.useExponentialShadowMap||this.useBlurExponentialShadowMap?t["SHADOWESM"+e]=!0:(this.useCloseExponentialShadowMap||this.useBlurCloseExponentialShadowMap)&&(t["SHADOWCLOSEESM"+e]=!0),i.needCube()&&(t["SHADOWCUBE"+e]=!0))},r.prototype.bindShadowLight=function(t,e){var n=this._light,i=this._scene;if(i.shadowsEnabled&&n.shadowEnabled){var o=i.activeCamera;if(o){var a=this.getShadowMap();a&&(n.needCube()||e.setMatrix("lightMatrix"+t,this.getTransformMatrix()),this._filter===r.FILTER_PCF?(e.setDepthStencilTexture("shadowSampler"+t,this.getShadowMapForRendering()),n._uniformBuffer.updateFloat4("shadowsInfo",this.getDarkness(),a.getSize().width,1/a.getSize().width,this.frustumEdgeFalloff,t)):this._filter===r.FILTER_PCSS?(e.setDepthStencilTexture("shadowSampler"+t,this.getShadowMapForRendering()),e.setTexture("depthSampler"+t,this.getShadowMapForRendering()),n._uniformBuffer.updateFloat4("shadowsInfo",this.getDarkness(),1/a.getSize().width,this._contactHardeningLightSizeUVRatio*a.getSize().width,this.frustumEdgeFalloff,t)):(e.setTexture("shadowSampler"+t,this.getShadowMapForRendering()),n._uniformBuffer.updateFloat4("shadowsInfo",this.getDarkness(),this.blurScale/a.getSize().width,this.depthScale,this.frustumEdgeFalloff,t)),n._uniformBuffer.updateFloat2("depthValues",this.getLight().getDepthMinZ(o),this.getLight().getDepthMinZ(o)+this.getLight().getDepthMaxZ(o),t))}}},r.prototype.getTransformMatrix=function(){var t=this._scene;if(this._currentRenderID===t.getRenderId()&&this._currentFaceIndexCache===this._currentFaceIndex)return this._transformMatrix;this._currentRenderID=t.getRenderId(),this._currentFaceIndexCache=this._currentFaceIndex;var e=this._light.position;if(this._light.computeTransformedInformation()&&(e=this._light.transformedPosition),u.e.NormalizeToRef(this._light.getShadowDirection(this._currentFaceIndex),this._lightDirection),Math.abs(u.e.Dot(this._lightDirection,u.e.Up()))===1&&(this._lightDirection.z=1e-13),this._light.needProjectionMatrixCompute()||!this._cachedPosition||!this._cachedDirection||!e.equals(this._cachedPosition)||!this._lightDirection.equals(this._cachedDirection)){this._cachedPosition.copyFrom(e),this._cachedDirection.copyFrom(this._lightDirection),u.a.LookAtLHToRef(e,e.add(this._lightDirection),u.e.Up(),this._viewMatrix);var n=this.getShadowMap();if(n){var i=n.renderList;i&&this._light.setShadowProjectionMatrix(this._projectionMatrix,this._viewMatrix,i)}this._viewMatrix.multiplyToRef(this._projectionMatrix,this._transformMatrix)}return this._transformMatrix},r.prototype.recreateShadowMap=function(){var t=this._shadowMap;if(t){var e=t.renderList;this._disposeRTTandPostProcesses(),this._initializeGenerator(),this.filter=this.filter,this._applyFilterValues(),this._shadowMap.renderList=e}},r.prototype._disposeBlurPostProcesses=function(){this._shadowMap2&&(this._shadowMap2.dispose(),this._shadowMap2=null),this._boxBlurPostprocess&&(this._boxBlurPostprocess.dispose(),this._boxBlurPostprocess=null),this._kernelBlurXPostprocess&&(this._kernelBlurXPostprocess.dispose(),this._kernelBlurXPostprocess=null),this._kernelBlurYPostprocess&&(this._kernelBlurYPostprocess.dispose(),this._kernelBlurYPostprocess=null),this._blurPostProcesses=[]},r.prototype._disposeRTTandPostProcesses=function(){this._shadowMap&&(this._shadowMap.dispose(),this._shadowMap=null),this._disposeBlurPostProcesses()},r.prototype.dispose=function(){this._disposeRTTandPostProcesses(),this._light&&(this._light._shadowGenerator=null,this._light._markMeshesAsLightDirty()),this.onBeforeShadowMapRenderMeshObservable.clear(),this.onBeforeShadowMapRenderObservable.clear(),this.onAfterShadowMapRenderMeshObservable.clear(),this.onAfterShadowMapRenderObservable.clear()},r.prototype.serialize=function(){var t={},e=this.getShadowMap();if(!e)return t;if(t.className=this.getClassName(),t.lightId=this._light.id,t.id=this._light.id,t.mapSize=e.getRenderSize(),t.forceBackFacesOnly=this.forceBackFacesOnly,t.darkness=this.getDarkness(),t.transparencyShadow=this._transparencyShadow,t.frustumEdgeFalloff=this.frustumEdgeFalloff,t.bias=this.bias,t.normalBias=this.normalBias,t.usePercentageCloserFiltering=this.usePercentageCloserFiltering,t.useContactHardeningShadow=this.useContactHardeningShadow,t.contactHardeningLightSizeUVRatio=this.contactHardeningLightSizeUVRatio,t.filteringQuality=this.filteringQuality,t.useExponentialShadowMap=this.useExponentialShadowMap,t.useBlurExponentialShadowMap=this.useBlurExponentialShadowMap,t.useCloseExponentialShadowMap=this.useBlurExponentialShadowMap,t.useBlurCloseExponentialShadowMap=this.useBlurExponentialShadowMap,t.usePoissonSampling=this.usePoissonSampling,t.depthScale=this.depthScale,t.blurBoxOffset=this.blurBoxOffset,t.blurKernel=this.blurKernel,t.blurScale=this.blurScale,t.useKernelBlur=this.useKernelBlur,t.renderList=[],e.renderList)for(var n=0;n<e.renderList.length;n++){var i=e.renderList[n];t.renderList.push(i.id)}return t},r.Parse=function(t,e,n){for(var i=e.getLightByID(t.lightId),o=n?n(t.mapSize,i):new r(t.mapSize,i),a=o.getShadowMap(),s=0;s<t.renderList.length;s++)e.getMeshesByID(t.renderList[s]).forEach(function(d){a&&(a.renderList||(a.renderList=[]),a.renderList.push(d))});return t.id!==void 0&&(o.id=t.id),o.forceBackFacesOnly=!!t.forceBackFacesOnly,t.darkness!==void 0&&o.setDarkness(t.darkness),t.transparencyShadow&&o.setTransparencyShadow(!0),t.frustumEdgeFalloff!==void 0&&(o.frustumEdgeFalloff=t.frustumEdgeFalloff),t.bias!==void 0&&(o.bias=t.bias),t.normalBias!==void 0&&(o.normalBias=t.normalBias),t.usePercentageCloserFiltering?o.usePercentageCloserFiltering=!0:t.useContactHardeningShadow?o.useContactHardeningShadow=!0:t.usePoissonSampling?o.usePoissonSampling=!0:t.useExponentialShadowMap?o.useExponentialShadowMap=!0:t.useBlurExponentialShadowMap?o.useBlurExponentialShadowMap=!0:t.useCloseExponentialShadowMap?o.useCloseExponentialShadowMap=!0:t.useBlurCloseExponentialShadowMap?o.useBlurCloseExponentialShadowMap=!0:t.useVarianceShadowMap?o.useExponentialShadowMap=!0:t.useBlurVarianceShadowMap&&(o.useBlurExponentialShadowMap=!0),t.contactHardeningLightSizeUVRatio!==void 0&&(o.contactHardeningLightSizeUVRatio=t.contactHardeningLightSizeUVRatio),t.filteringQuality!==void 0&&(o.filteringQuality=t.filteringQuality),t.depthScale&&(o.depthScale=t.depthScale),t.blurScale&&(o.blurScale=t.blurScale),t.blurBoxOffset&&(o.blurBoxOffset=t.blurBoxOffset),t.useKernelBlur&&(o.useKernelBlur=t.useKernelBlur),t.blurKernel&&(o.blurKernel=t.blurKernel),o},r.CLASSNAME="ShadowGenerator",r.FILTER_NONE=0,r.FILTER_EXPONENTIALSHADOWMAP=1,r.FILTER_POISSONSAMPLING=2,r.FILTER_BLUREXPONENTIALSHADOWMAP=3,r.FILTER_CLOSEEXPONENTIALSHADOWMAP=4,r.FILTER_BLURCLOSEEXPONENTIALSHADOWMAP=5,r.FILTER_PCF=6,r.FILTER_PCSS=7,r.QUALITY_HIGH=0,r.QUALITY_MEDIUM=1,r.QUALITY_LOW=2,r._SceneComponentInitialization=function(t){throw An.a.WarnImport("ShadowGeneratorSceneComponent")},r}(),z_=`#ifdef ALPHATEST
-varying vec2 vUV;
-uniform sampler2D diffuseSampler;
-#endif
-varying float vDepthMetric;
-#ifdef PACKED
-#include<packingFunctions>
-#endif
-void main(void)
-{
-#ifdef ALPHATEST
-if (texture2D(diffuseSampler,vUV).a<0.4)
-discard;
-#endif
-#ifdef NONLINEARDEPTH
-#ifdef PACKED
-gl_FragColor=pack(gl_FragCoord.z);
-#else
-gl_FragColor=vec4(gl_FragCoord.z,0.0,0.0,0.0);
-#endif
-#else
-#ifdef PACKED
-gl_FragColor=pack(vDepthMetric);
-#else
-gl_FragColor=vec4(vDepthMetric,0.0,0.0,1.0);
-#endif
-#endif
-}`;ze.a.ShadersStore.depthPixelShader=z_;var j_=`
-attribute vec3 position;
-#include<bonesDeclaration>
-#include<morphTargetsVertexGlobalDeclaration>
-#include<morphTargetsVertexDeclaration>[0..maxSimultaneousMorphTargets]
-
-#include<instancesDeclaration>
-uniform mat4 viewProjection;
-uniform vec2 depthValues;
-#if defined(ALPHATEST) || defined(NEED_UV)
-varying vec2 vUV;
-uniform mat4 diffuseMatrix;
-#ifdef UV1
-attribute vec2 uv;
-#endif
-#ifdef UV2
-attribute vec2 uv2;
-#endif
-#endif
-varying float vDepthMetric;
-void main(void)
-{
-vec3 positionUpdated=position;
-#ifdef UV1
-vec2 uvUpdated=uv;
-#endif
-#include<morphTargetsVertex>[0..maxSimultaneousMorphTargets]
-#include<instancesVertex>
-#include<bonesVertex>
-gl_Position=viewProjection*finalWorld*vec4(positionUpdated,1.0);
-vDepthMetric=((gl_Position.z+depthValues.x)/(depthValues.y));
-#if defined(ALPHATEST) || defined(BASIC_RENDER)
-#ifdef UV1
-vUV=vec2(diffuseMatrix*vec4(uvUpdated,1.0,0.0));
-#endif
-#ifdef UV2
-vUV=vec2(diffuseMatrix*vec4(uv2,1.0,0.0));
-#endif
-#endif
-}
-`;ze.a.ShadersStore.depthVertexShader=j_;var oa=function(){function r(t,e,n,i){var o=this;e===void 0&&(e=h.a.TEXTURETYPE_FLOAT),n===void 0&&(n=null),i===void 0&&(i=!1),this.enabled=!0,this.useOnlyInActiveCamera=!1,this._scene=t,this._storeNonLinearDepth=i,this.isPacked=e===h.a.TEXTURETYPE_UNSIGNED_BYTE,this.isPacked?this._clearColor=new M.b(1,1,1,1):this._clearColor=new M.b(1,0,0,1),r._SceneComponentInitialization(this._scene),this._camera=n;var a=t.getEngine(),s=this.isPacked||a.webGLVersion===1?h.a.TEXTUREFORMAT_RGBA:h.a.TEXTUREFORMAT_R;this._depthMap=new sn("depthMap",{width:a.getRenderWidth(),height:a.getRenderHeight()},this._scene,!1,!0,e,!1,void 0,void 0,void 0,void 0,s),this._depthMap.wrapU=we.a.CLAMP_ADDRESSMODE,this._depthMap.wrapV=we.a.CLAMP_ADDRESSMODE,this._depthMap.refreshRate=1,this._depthMap.renderParticles=!1,this._depthMap.renderList=null,this._depthMap.activeCamera=this._camera,this._depthMap.ignoreCameraViewport=!0,this._depthMap.useCameraPostProcesses=!1,this._depthMap.onClearObservable.add(function(p){p.clear(o._clearColor,!0,!0,!0)});var d=function(p){var b=p.getRenderingMesh(),P=p.getEffectiveMesh(),O=o._scene,B=O.getEngine(),F=p.getMaterial();if(P._internalAbstractMeshDataInfo._isActiveIntermediate=!1,F&&p.verticesCount!==0&&p._renderId!==O.getRenderId()){B.setState(F.backFaceCulling,0,!1,O.useRightHandedSystem);var z=b._getInstancesRenderList(p._id,!!p.getReplacementMesh());if(!z.mustReturn){var J=B.getCaps().instancedArrays&&(z.visibleInstances[p._id]!==null&&z.visibleInstances[p._id]!==void 0||b.hasThinInstances),ie=o._camera||O.activeCamera;if(o.isReady(p,J)&&ie){if(p._renderId=O.getRenderId(),B.enableEffect(o._effect),b._bind(p,o._effect,F.fillMode),o._effect.setMatrix("viewProjection",O.getTransformMatrix()),o._effect.setFloat2("depthValues",ie.minZ,ie.minZ+ie.maxZ),F&&F.needAlphaTesting()){var se=F.getAlphaTestTexture();se&&(o._effect.setTexture("diffuseSampler",se),o._effect.setMatrix("diffuseMatrix",se.getTextureMatrix()))}b.useBones&&b.computeBonesUsingShaders&&b.skeleton&&o._effect.setMatrices("mBones",b.skeleton.getTransformMatrices(b)),et.a.BindMorphTargetParameters(b,o._effect),b._processRendering(P,p,o._effect,F.fillMode,z,J,function(ce,ue){return o._effect.setMatrix("world",ue)})}}}};this._depthMap.customRenderFunction=function(p,b,P,O){var B;if(O.length){for(a.setColorWrite(!1),B=0;B<O.length;B++)d(O.data[B]);a.setColorWrite(!0)}for(B=0;B<p.length;B++)d(p.data[B]);for(B=0;B<b.length;B++)d(b.data[B])}}return r.prototype.isReady=function(t,e){var n=t.getMaterial();if(n.disableDepthWrite)return!1;var i=[],o=[Oe.b.PositionKind],a=t.getMesh();n&&n.needAlphaTesting()&&n.getAlphaTestTexture()&&(i.push("#define ALPHATEST"),a.isVerticesDataPresent(Oe.b.UVKind)&&(o.push(Oe.b.UVKind),i.push("#define UV1")),a.isVerticesDataPresent(Oe.b.UV2Kind)&&(o.push(Oe.b.UV2Kind),i.push("#define UV2"))),a.useBones&&a.computeBonesUsingShaders?(o.push(Oe.b.MatricesIndicesKind),o.push(Oe.b.MatricesWeightsKind),a.numBoneInfluencers>4&&(o.push(Oe.b.MatricesIndicesExtraKind),o.push(Oe.b.MatricesWeightsExtraKind)),i.push("#define NUM_BONE_INFLUENCERS "+a.numBoneInfluencers),i.push("#define BonesPerMesh "+(a.skeleton?a.skeleton.bones.length+1:0))):i.push("#define NUM_BONE_INFLUENCERS 0");var s=a.morphTargetManager,d=0;s&&s.numInfluencers>0&&(d=s.numInfluencers,i.push("#define MORPHTARGETS"),i.push("#define NUM_MORPH_INFLUENCERS "+d),et.a.PrepareAttributesForMorphTargetsInfluencers(o,a,d)),e&&(i.push("#define INSTANCES"),et.a.PushAttributesForInstances(o),t.getRenderingMesh().hasThinInstances&&i.push("#define THIN_INSTANCES")),this._storeNonLinearDepth&&i.push("#define NONLINEARDEPTH"),this.isPacked&&i.push("#define PACKED");var p=i.join(`
-`);return this._cachedDefines!==p&&(this._cachedDefines=p,this._effect=this._scene.getEngine().createEffect("depth",o,["world","mBones","viewProjection","diffuseMatrix","depthValues","morphTargetInfluences"],["diffuseSampler"],p,void 0,void 0,void 0,{maxSimultaneousMorphTargets:d})),this._effect.isReady()},r.prototype.getDepthMap=function(){return this._depthMap},r.prototype.dispose=function(){this._depthMap.dispose()},r._SceneComponentInitialization=function(t){throw An.a.WarnImport("DepthRendererSceneComponent")},r}(),H_=`attribute vec2 vUV;
-uniform sampler2D textureSampler;
-#if defined(INITIAL)
-uniform sampler2D sourceTexture;
-uniform vec2 texSize;
-void main(void)
-{
-ivec2 coord=ivec2(vUV*(texSize-1.0));
-float f1=texelFetch(sourceTexture,coord,0).r;
-float f2=texelFetch(sourceTexture,coord+ivec2(1,0),0).r;
-float f3=texelFetch(sourceTexture,coord+ivec2(1,1),0).r;
-float f4=texelFetch(sourceTexture,coord+ivec2(0,1),0).r;
-float minz=min(min(min(f1,f2),f3),f4);
-#ifdef DEPTH_REDUX
-float maxz=max(max(max(sign(1.0-f1)*f1,sign(1.0-f2)*f2),sign(1.0-f3)*f3),sign(1.0-f4)*f4);
-#else
-float maxz=max(max(max(f1,f2),f3),f4);
-#endif
-glFragColor=vec4(minz,maxz,0.,0.);
-}
-#elif defined(MAIN)
-uniform vec2 texSize;
-void main(void)
-{
-ivec2 coord=ivec2(vUV*(texSize-1.0));
-vec2 f1=texelFetch(textureSampler,coord,0).rg;
-vec2 f2=texelFetch(textureSampler,coord+ivec2(1,0),0).rg;
-vec2 f3=texelFetch(textureSampler,coord+ivec2(1,1),0).rg;
-vec2 f4=texelFetch(textureSampler,coord+ivec2(0,1),0).rg;
-float minz=min(min(min(f1.x,f2.x),f3.x),f4.x);
-float maxz=max(max(max(f1.y,f2.y),f3.y),f4.y);
-glFragColor=vec4(minz,maxz,0.,0.);
-}
-#elif defined(ONEBEFORELAST)
-uniform ivec2 texSize;
-void main(void)
-{
-ivec2 coord=ivec2(vUV*vec2(texSize-1));
-vec2 f1=texelFetch(textureSampler,coord % texSize,0).rg;
-vec2 f2=texelFetch(textureSampler,(coord+ivec2(1,0)) % texSize,0).rg;
-vec2 f3=texelFetch(textureSampler,(coord+ivec2(1,1)) % texSize,0).rg;
-vec2 f4=texelFetch(textureSampler,(coord+ivec2(0,1)) % texSize,0).rg;
-float minz=min(f1.x,f2.x);
-float maxz=max(f1.y,f2.y);
-glFragColor=vec4(minz,maxz,0.,0.);
-}
-#elif defined(LAST)
-void main(void)
-{
-discard;
-glFragColor=vec4(0.);
-}
-#endif
-`;ze.a.ShadersStore.minmaxReduxPixelShader=H_;var Fu=function(){function r(t){this.onAfterReductionPerformed=new x.c,this._forceFullscreenViewport=!0,this._activated=!1,this._camera=t,this._postProcessManager=new hs.a(t.getScene())}return Object.defineProperty(r.prototype,"sourceTexture",{get:function(){return this._sourceTexture},enumerable:!1,configurable:!0}),r.prototype.setSourceTexture=function(t,e,n,i){var o=this;if(n===void 0&&(n=h.a.TEXTURETYPE_HALF_FLOAT),i===void 0&&(i=!0),t!==this._sourceTexture){this.dispose(!1),this._sourceTexture=t,this._reductionSteps=[],this._forceFullscreenViewport=i;var a=this._camera.getScene(),s=new _t("Initial reduction phase","minmaxRedux",["texSize"],["sourceTexture"],1,null,h.a.TEXTURE_NEAREST_NEAREST,a.getEngine(),!1,"#define INITIAL"+(e?`
-#define DEPTH_REDUX`:""),n,void 0,void 0,void 0,h.a.TEXTUREFORMAT_RG);s.autoClear=!1,s.forceFullscreenViewport=i;var d=this._sourceTexture.getRenderWidth(),p=this._sourceTexture.getRenderHeight();s.onApply=function(O,B){return function(F){F.setTexture("sourceTexture",o._sourceTexture),F.setFloatArray2("texSize",new Float32Array([O,B]))}}(d,p),this._reductionSteps.push(s);for(var b=1;d>1||p>1;){d=Math.max(Math.round(d/2),1),p=Math.max(Math.round(p/2),1);var P=new _t("Reduction phase "+b,"minmaxRedux",["texSize"],null,{width:d,height:p},null,h.a.TEXTURE_NEAREST_NEAREST,a.getEngine(),!1,"#define "+(d==1&&p==1?"LAST":d==1||p==1?"ONEBEFORELAST":"MAIN"),n,void 0,void 0,void 0,h.a.TEXTUREFORMAT_RG);P.autoClear=!1,P.forceFullscreenViewport=i,P.onApply=function(O,B){return function(F){O==1||B==1?F.setIntArray2("texSize",new Int32Array([O,B])):F.setFloatArray2("texSize",new Float32Array([O,B]))}}(d,p),this._reductionSteps.push(P),b++,d==1&&p==1&&P.onAfterRenderObservable.add(function(O,B,F){var z=new Float32Array(4*O*B),J={min:0,max:0};return function(){a.getEngine()._readTexturePixels(F.inputTexture,O,B,-1,0,z),J.min=z[0],J.max=z[1],o.onAfterReductionPerformed.notifyObservers(J)}}(d,p,P))}}},Object.defineProperty(r.prototype,"refreshRate",{get:function(){return this._sourceTexture?this._sourceTexture.refreshRate:-1},set:function(t){this._sourceTexture&&(this._sourceTexture.refreshRate=t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"activated",{get:function(){return this._activated},enumerable:!1,configurable:!0}),r.prototype.activate=function(){var t=this;!this._onAfterUnbindObserver&&this._sourceTexture&&(this._onAfterUnbindObserver=this._sourceTexture.onAfterUnbindObservable.add(function(){t._reductionSteps[0].activate(t._camera),t._postProcessManager.directRender(t._reductionSteps,t._reductionSteps[0].inputTexture,t._forceFullscreenViewport),t._camera.getScene().getEngine().unBindFramebuffer(t._reductionSteps[0].inputTexture,!1)}),this._activated=!0)},r.prototype.deactivate=function(){this._onAfterUnbindObserver&&this._sourceTexture&&(this._sourceTexture.onAfterUnbindObservable.remove(this._onAfterUnbindObserver),this._onAfterUnbindObserver=null,this._activated=!1)},r.prototype.dispose=function(t){if(t===void 0&&(t=!0),t&&this.onAfterReductionPerformed.clear(),this.deactivate(),this._reductionSteps){for(var e=0;e<this._reductionSteps.length;++e)this._reductionSteps[e].dispose();this._reductionSteps=null}this._postProcessManager&&t&&this._postProcessManager.dispose(),this._sourceTexture=null},r}(),Bu=function(r){function t(e){return r.call(this,e)||this}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"depthRenderer",{get:function(){return this._depthRenderer},enumerable:!1,configurable:!0}),t.prototype.setDepthRenderer=function(e,n,i){e===void 0&&(e=null),n===void 0&&(n=h.a.TEXTURETYPE_HALF_FLOAT),i===void 0&&(i=!0);var o=this._camera.getScene();this._depthRenderer&&(delete o._depthRenderer[this._depthRendererId],this._depthRenderer.dispose(),this._depthRenderer=null),e===null&&(o._depthRenderer||(o._depthRenderer={}),(e=this._depthRenderer=new oa(o,n,this._camera,!1)).enabled=!1,this._depthRendererId="minmax"+this._camera.id,o._depthRenderer[this._depthRendererId]=e),r.prototype.setSourceTexture.call(this,e.getDepthMap(),!0,n,i)},t.prototype.setSourceTexture=function(e,n,i,o){i===void 0&&(i=h.a.TEXTURETYPE_HALF_FLOAT),o===void 0&&(o=!0),r.prototype.setSourceTexture.call(this,e,n,i,o)},t.prototype.activate=function(){this._depthRenderer&&(this._depthRenderer.enabled=!0),r.prototype.activate.call(this)},t.prototype.deactivate=function(){r.prototype.deactivate.call(this),this._depthRenderer&&(this._depthRenderer.enabled=!1)},t.prototype.dispose=function(e){if(e===void 0&&(e=!0),r.prototype.dispose.call(this,e),this._depthRenderer&&e){var n=this._depthRenderer.getDepthMap().getScene();n&&delete n._depthRenderer[this._depthRendererId],this._depthRenderer.dispose(),this._depthRenderer=null}},t}(Fu),Uu=u.e.Up(),W_=u.e.Zero(),vn=new u.e,Or=new u.e,Mr=new u.a,Vu=new u.a,js=function(r){function t(e,n,i){var o=this;if(t.IsSupported)return(o=r.call(this,e,n,i)||this).usePercentageCloserFiltering=!0,o;l.a.Error("CascadedShadowMap needs WebGL 2 support.")}return Object(c.d)(t,r),t.prototype._validateFilter=function(e){return e===Un.FILTER_NONE||e===Un.FILTER_PCF||e===Un.FILTER_PCSS?e:(console.error('Unsupported filter "'+e+'"!'),Un.FILTER_NONE)},Object.defineProperty(t.prototype,"numCascades",{get:function(){return this._numCascades},set:function(e){(e=Math.min(Math.max(e,t.MIN_CASCADES_COUNT),t.MAX_CASCADES_COUNT))!==this._numCascades&&(this._numCascades=e,this.recreateShadowMap())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"freezeShadowCastersBoundingInfo",{get:function(){return this._freezeShadowCastersBoundingInfo},set:function(e){this._freezeShadowCastersBoundingInfoObservable&&e&&(this._scene.onBeforeRenderObservable.remove(this._freezeShadowCastersBoundingInfoObservable),this._freezeShadowCastersBoundingInfoObservable=null),this._freezeShadowCastersBoundingInfoObservable||e||(this._freezeShadowCastersBoundingInfoObservable=this._scene.onBeforeRenderObservable.add(this._computeShadowCastersBoundingInfo.bind(this))),this._freezeShadowCastersBoundingInfo=e,e&&this._computeShadowCastersBoundingInfo()},enumerable:!1,configurable:!0}),t.prototype._computeShadowCastersBoundingInfo=function(){if(this._scbiMin.copyFromFloats(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),this._scbiMax.copyFromFloats(Number.MIN_VALUE,Number.MIN_VALUE,Number.MIN_VALUE),this._shadowMap&&this._shadowMap.renderList){for(var e=this._shadowMap.renderList,n=0;n<e.length;n++)if(a=e[n]){var i=a.getBoundingInfo().boundingBox;this._scbiMin.minimizeInPlace(i.minimumWorld),this._scbiMax.maximizeInPlace(i.maximumWorld)}var o=this._scene.meshes;for(n=0;n<o.length;n++){var a;(a=o[n])&&a.isVisible&&a.isEnabled&&a.receiveShadows&&(i=a.getBoundingInfo().boundingBox,this._scbiMin.minimizeInPlace(i.minimumWorld),this._scbiMax.maximizeInPlace(i.maximumWorld))}}this._shadowCastersBoundingInfo.reConstruct(this._scbiMin,this._scbiMax)},Object.defineProperty(t.prototype,"shadowCastersBoundingInfo",{get:function(){return this._shadowCastersBoundingInfo},set:function(e){this._shadowCastersBoundingInfo=e},enumerable:!1,configurable:!0}),t.prototype.setMinMaxDistance=function(e,n){this._minDistance===e&&this._maxDistance===n||(e>n&&(e=0,n=1),e<0&&(e=0),n>1&&(n=1),this._minDistance=e,this._maxDistance=n,this._breaksAreDirty=!0)},Object.defineProperty(t.prototype,"minDistance",{get:function(){return this._minDistance},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"maxDistance",{get:function(){return this._maxDistance},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return t.CLASSNAME},t.prototype.getCascadeMinExtents=function(e){return e>=0&&e<this._numCascades?this._cascadeMinExtents[e]:null},t.prototype.getCascadeMaxExtents=function(e){return e>=0&&e<this._numCascades?this._cascadeMaxExtents[e]:null},Object.defineProperty(t.prototype,"shadowMaxZ",{get:function(){return this._scene&&this._scene.activeCamera?this._shadowMaxZ:0},set:function(e){this._scene&&this._scene.activeCamera?this._shadowMaxZ===e||e<this._scene.activeCamera.minZ||e>this._scene.activeCamera.maxZ||(this._shadowMaxZ=e,this._light._markMeshesAsLightDirty(),this._breaksAreDirty=!0):this._shadowMaxZ=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"debug",{get:function(){return this._debug},set:function(e){this._debug=e,this._light._markMeshesAsLightDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"depthClamp",{get:function(){return this._depthClamp},set:function(e){this._depthClamp=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cascadeBlendPercentage",{get:function(){return this._cascadeBlendPercentage},set:function(e){this._cascadeBlendPercentage=e,this._light._markMeshesAsLightDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"lambda",{get:function(){return this._lambda},set:function(e){var n=Math.min(Math.max(e,0),1);this._lambda!=n&&(this._lambda=n,this._breaksAreDirty=!0)},enumerable:!1,configurable:!0}),t.prototype.getCascadeViewMatrix=function(e){return e>=0&&e<this._numCascades?this._viewMatrices[e]:null},t.prototype.getCascadeProjectionMatrix=function(e){return e>=0&&e<this._numCascades?this._projectionMatrices[e]:null},t.prototype.getCascadeTransformMatrix=function(e){return e>=0&&e<this._numCascades?this._transformMatrices[e]:null},t.prototype.setDepthRenderer=function(e){this._depthRenderer=e,this._depthReducer&&this._depthReducer.setDepthRenderer(this._depthRenderer)},Object.defineProperty(t.prototype,"autoCalcDepthBounds",{get:function(){return this._autoCalcDepthBounds},set:function(e){var n=this,i=this._scene.activeCamera;if(i){if(this._autoCalcDepthBounds=e,!e)return this._depthReducer&&this._depthReducer.deactivate(),void this.setMinMaxDistance(0,1);this._depthReducer||(this._depthReducer=new Bu(i),this._depthReducer.onAfterReductionPerformed.add(function(o){var a=o.min,s=o.max;a>=s&&(a=0,s=1),a==n._minDistance&&s==n._maxDistance||n.setMinMaxDistance(a,s)}),this._depthReducer.setDepthRenderer(this._depthRenderer)),this._depthReducer.activate()}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"autoCalcDepthBoundsRefreshRate",{get:function(){var e,n,i;return(i=(n=(e=this._depthReducer)===null||e===void 0?void 0:e.depthRenderer)===null||n===void 0?void 0:n.getDepthMap().refreshRate)!==null&&i!==void 0?i:-1},set:function(e){var n;!((n=this._depthReducer)===null||n===void 0)&&n.depthRenderer&&(this._depthReducer.depthRenderer.getDepthMap().refreshRate=e)},enumerable:!1,configurable:!0}),t.prototype.splitFrustum=function(){this._breaksAreDirty=!0},t.prototype._splitFrustum=function(){var e=this._scene.activeCamera;if(e){for(var n=e.minZ,i=e.maxZ,o=i-n,a=this._minDistance,s=n+a*o,d=n+(this._shadowMaxZ<i&&this._shadowMaxZ>=n?Math.min((this._shadowMaxZ-n)/(i-n),this._maxDistance):this._maxDistance)*o,p=d-s,b=d/s,P=0;P<this._cascades.length;++P){var O=(P+1)/this._numCascades,B=s*Math.pow(b,O),F=s+p*O,z=this._lambda*(B-F)+F;this._cascades[P].prevBreakDistance=P===0?a:this._cascades[P-1].breakDistance,this._cascades[P].breakDistance=(z-n)/o,this._viewSpaceFrustumsZ[P]=n+this._cascades[P].breakDistance*o,this._frustumLengths[P]=(this._cascades[P].breakDistance-this._cascades[P].prevBreakDistance)*o}this._breaksAreDirty=!1}},t.prototype._computeMatrices=function(){if(this._scene.activeCamera){u.e.NormalizeToRef(this._light.getShadowDirection(0),this._lightDirection),Math.abs(u.e.Dot(this._lightDirection,u.e.Up()))===1&&(this._lightDirection.z=1e-13),this._cachedDirection.copyFrom(this._lightDirection);for(var e=0;e<this._numCascades;++e){this._computeFrustumInWorldSpace(e),this._computeCascadeFrustum(e),this._cascadeMaxExtents[e].subtractToRef(this._cascadeMinExtents[e],vn),this._frustumCenter[e].addToRef(this._lightDirection.scale(this._cascadeMinExtents[e].z),this._shadowCameraPos[e]),u.a.LookAtLHToRef(this._shadowCameraPos[e],this._frustumCenter[e],Uu,this._viewMatrices[e]);var n=0,i=vn.z,o=this._shadowCastersBoundingInfo;o.update(this._viewMatrices[e]),i=Math.min(i,o.boundingBox.maximumWorld.z),n=this._depthClamp&&this.filter!==Un.FILTER_PCSS?Math.max(n,o.boundingBox.minimumWorld.z):Math.min(n,o.boundingBox.minimumWorld.z),u.a.OrthoOffCenterLHToRef(this._cascadeMinExtents[e].x,this._cascadeMaxExtents[e].x,this._cascadeMinExtents[e].y,this._cascadeMaxExtents[e].y,n,i,this._projectionMatrices[e]),this._cascadeMinExtents[e].z=n,this._cascadeMaxExtents[e].z=i,this._viewMatrices[e].multiplyToRef(this._projectionMatrices[e],this._transformMatrices[e]),u.e.TransformCoordinatesToRef(W_,this._transformMatrices[e],vn),vn.scaleInPlace(this._mapSize/2),Or.copyFromFloats(Math.round(vn.x),Math.round(vn.y),Math.round(vn.z)),Or.subtractInPlace(vn).scaleInPlace(2/this._mapSize),u.a.TranslationToRef(Or.x,Or.y,0,Mr),this._projectionMatrices[e].multiplyToRef(Mr,this._projectionMatrices[e]),this._viewMatrices[e].multiplyToRef(this._projectionMatrices[e],this._transformMatrices[e]),this._transformMatrices[e].copyToArray(this._transformMatricesAsArray,16*e)}}},t.prototype._computeFrustumInWorldSpace=function(e){if(this._scene.activeCamera){var n=this._cascades[e].prevBreakDistance,i=this._cascades[e].breakDistance;this._scene.activeCamera.getViewMatrix();for(var o=u.a.Invert(this._scene.activeCamera.getTransformationMatrix()),a=0;a<t.frustumCornersNDCSpace.length;++a)u.e.TransformCoordinatesToRef(t.frustumCornersNDCSpace[a],o,this._frustumCornersWorldSpace[e][a]);for(a=0;a<t.frustumCornersNDCSpace.length/2;++a)vn.copyFrom(this._frustumCornersWorldSpace[e][a+4]).subtractInPlace(this._frustumCornersWorldSpace[e][a]),Or.copyFrom(vn).scaleInPlace(n),vn.scaleInPlace(i),vn.addInPlace(this._frustumCornersWorldSpace[e][a]),this._frustumCornersWorldSpace[e][a+4].copyFrom(vn),this._frustumCornersWorldSpace[e][a].addInPlace(Or)}},t.prototype._computeCascadeFrustum=function(e){if(this._cascadeMinExtents[e].copyFromFloats(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),this._cascadeMaxExtents[e].copyFromFloats(Number.MIN_VALUE,Number.MIN_VALUE,Number.MIN_VALUE),this._frustumCenter[e].copyFromFloats(0,0,0),this._scene.activeCamera){for(var n=0;n<this._frustumCornersWorldSpace[e].length;++n)this._frustumCenter[e].addInPlace(this._frustumCornersWorldSpace[e][n]);if(this._frustumCenter[e].scaleInPlace(1/this._frustumCornersWorldSpace[e].length),this.stabilizeCascades){var i=0;for(n=0;n<this._frustumCornersWorldSpace[e].length;++n){var o=this._frustumCornersWorldSpace[e][n].subtractToRef(this._frustumCenter[e],vn).length();i=Math.max(i,o)}i=Math.ceil(16*i)/16,this._cascadeMaxExtents[e].copyFromFloats(i,i,i),this._cascadeMinExtents[e].copyFromFloats(-i,-i,-i)}else{var a=this._frustumCenter[e];for(this._frustumCenter[e].addToRef(this._lightDirection,vn),u.a.LookAtLHToRef(a,vn,Uu,Mr),n=0;n<this._frustumCornersWorldSpace[e].length;++n)u.e.TransformCoordinatesToRef(this._frustumCornersWorldSpace[e][n],Mr,vn),this._cascadeMinExtents[e].minimizeInPlace(vn),this._cascadeMaxExtents[e].maximizeInPlace(vn)}}},Object.defineProperty(t,"IsSupported",{get:function(){var e=te.a.LastCreatedEngine;return!!e&&e.webGLVersion!=1},enumerable:!1,configurable:!0}),t.prototype._initializeGenerator=function(){var e,n,i,o,a,s,d,p,b,P,O,B,F,z,J,ie,se,ce,ue,fe;this.penumbraDarkness=(e=this.penumbraDarkness)!==null&&e!==void 0?e:1,this._numCascades=(n=this._numCascades)!==null&&n!==void 0?n:t.DEFAULT_CASCADES_COUNT,this.stabilizeCascades=(i=this.stabilizeCascades)!==null&&i!==void 0&&i,this._freezeShadowCastersBoundingInfoObservable=(o=this._freezeShadowCastersBoundingInfoObservable)!==null&&o!==void 0?o:null,this.freezeShadowCastersBoundingInfo=(a=this.freezeShadowCastersBoundingInfo)!==null&&a!==void 0&&a,this._scbiMin=(s=this._scbiMin)!==null&&s!==void 0?s:new u.e(0,0,0),this._scbiMax=(d=this._scbiMax)!==null&&d!==void 0?d:new u.e(0,0,0),this._shadowCastersBoundingInfo=(p=this._shadowCastersBoundingInfo)!==null&&p!==void 0?p:new Vi.a(new u.e(0,0,0),new u.e(0,0,0)),this._breaksAreDirty=(b=this._breaksAreDirty)===null||b===void 0||b,this._minDistance=(P=this._minDistance)!==null&&P!==void 0?P:0,this._maxDistance=(O=this._maxDistance)!==null&&O!==void 0?O:1,this._currentLayer=(B=this._currentLayer)!==null&&B!==void 0?B:0,this._shadowMaxZ=(J=(F=this._shadowMaxZ)!==null&&F!==void 0?F:(z=this._scene.activeCamera)===null||z===void 0?void 0:z.maxZ)!==null&&J!==void 0?J:1e4,this._debug=(ie=this._debug)!==null&&ie!==void 0&&ie,this._depthClamp=(se=this._depthClamp)===null||se===void 0||se,this._cascadeBlendPercentage=(ce=this._cascadeBlendPercentage)!==null&&ce!==void 0?ce:.1,this._lambda=(ue=this._lambda)!==null&&ue!==void 0?ue:.5,this._autoCalcDepthBounds=(fe=this._autoCalcDepthBounds)!==null&&fe!==void 0&&fe,r.prototype._initializeGenerator.call(this)},t.prototype._createTargetRenderTexture=function(){var e={width:this._mapSize,height:this._mapSize,layers:this.numCascades};this._shadowMap=new sn(this._light.name+"_shadowMap",e,this._scene,!1,!0,this._textureType,!1,void 0,!1,!1,void 0),this._shadowMap.createDepthStencilTexture(h.a.LESS,!0)},t.prototype._initializeShadowMap=function(){var e=this;if(r.prototype._initializeShadowMap.call(this),this._shadowMap!==null){this._transformMatricesAsArray=new Float32Array(16*this._numCascades),this._viewSpaceFrustumsZ=new Array(this._numCascades),this._frustumLengths=new Array(this._numCascades),this._lightSizeUVCorrection=new Array(2*this._numCascades),this._depthCorrection=new Array(this._numCascades),this._cascades=[],this._viewMatrices=[],this._projectionMatrices=[],this._transformMatrices=[],this._cascadeMinExtents=[],this._cascadeMaxExtents=[],this._frustumCenter=[],this._shadowCameraPos=[],this._frustumCornersWorldSpace=[];for(var n=0;n<this._numCascades;++n){this._cascades[n]={prevBreakDistance:0,breakDistance:0},this._viewMatrices[n]=u.a.Zero(),this._projectionMatrices[n]=u.a.Zero(),this._transformMatrices[n]=u.a.Zero(),this._cascadeMinExtents[n]=new u.e,this._cascadeMaxExtents[n]=new u.e,this._frustumCenter[n]=new u.e,this._shadowCameraPos[n]=new u.e,this._frustumCornersWorldSpace[n]=new Array(t.frustumCornersNDCSpace.length);for(var i=0;i<t.frustumCornersNDCSpace.length;++i)this._frustumCornersWorldSpace[n][i]=new u.e}this._shadowMap.onBeforeRenderObservable.add(function(o){if(e._currentLayer=o,e._scene.getSceneUniformBuffer().useUbo){var a=e._scene.getSceneUniformBuffer();a.updateMatrix("viewProjection",e.getCascadeTransformMatrix(o)),a.updateMatrix("view",e.getCascadeViewMatrix(o)),a.update()}}),this._shadowMap.onBeforeBindObservable.add(function(){e._breaksAreDirty&&e._splitFrustum(),e._computeMatrices()}),this._splitFrustum()}},t.prototype._bindCustomEffectForRenderSubMeshForShadowMap=function(e,n,i,o){var a,s,d,p,b,P;n.setMatrix((a=i?.viewProjection)!==null&&a!==void 0?a:"viewProjection",this.getCascadeTransformMatrix(this._currentLayer)),n.setMatrix((s=i?.view)!==null&&s!==void 0?s:"view",this.getCascadeViewMatrix(this._currentLayer)),n.setMatrix((d=i?.projection)!==null&&d!==void 0?d:"projection",this.getCascadeProjectionMatrix(this._currentLayer));var O=o.getWorldMatrix();n.setMatrix((p=i?.world)!==null&&p!==void 0?p:"world",O),O.multiplyToRef(this.getCascadeTransformMatrix(this._currentLayer),Mr),n.setMatrix((b=i?.worldViewProjection)!==null&&b!==void 0?b:"worldViewProjection",Mr),O.multiplyToRef(this.getCascadeViewMatrix(this._currentLayer),Vu),n.setMatrix((P=i?.worldView)!==null&&P!==void 0?P:"worldView",Vu)},t.prototype._isReadyCustomDefines=function(e,n,i){e.push("#define SM_DEPTHCLAMP "+(this._depthClamp&&this._filter!==Un.FILTER_PCSS?"1":"0"))},t.prototype.prepareDefines=function(e,n){r.prototype.prepareDefines.call(this,e,n);var i=this._scene,o=this._light;if(i.shadowsEnabled&&o.shadowEnabled){e["SHADOWCSM"+n]=!0,e["SHADOWCSMDEBUG"+n]=this.debug,e["SHADOWCSMNUM_CASCADES"+n]=this.numCascades,e["SHADOWCSM_RIGHTHANDED"+n]=i.useRightHandedSystem;var a=i.activeCamera;a&&this._shadowMaxZ<a.maxZ&&(e["SHADOWCSMUSESHADOWMAXZ"+n]=!0),this.cascadeBlendPercentage===0&&(e["SHADOWCSMNOBLEND"+n]=!0)}},t.prototype.bindShadowLight=function(e,n){var i=this._light,o=this._scene;if(o.shadowsEnabled&&i.shadowEnabled){var a=o.activeCamera;if(a){var s=this.getShadowMap();if(s){var d=s.getSize().width;if(n.setMatrices("lightMatrix"+e,this._transformMatricesAsArray),n.setArray("viewFrustumZ"+e,this._viewSpaceFrustumsZ),n.setFloat("cascadeBlendFactor"+e,this.cascadeBlendPercentage===0?1e4:1/this.cascadeBlendPercentage),n.setArray("frustumLengths"+e,this._frustumLengths),this._filter===Un.FILTER_PCF)n.setDepthStencilTexture("shadowSampler"+e,s),i._uniformBuffer.updateFloat4("shadowsInfo",this.getDarkness(),d,1/d,this.frustumEdgeFalloff,e);else if(this._filter===Un.FILTER_PCSS){for(var p=0;p<this._numCascades;++p)this._lightSizeUVCorrection[2*p+0]=p===0?1:(this._cascadeMaxExtents[0].x-this._cascadeMinExtents[0].x)/(this._cascadeMaxExtents[p].x-this._cascadeMinExtents[p].x),this._lightSizeUVCorrection[2*p+1]=p===0?1:(this._cascadeMaxExtents[0].y-this._cascadeMinExtents[0].y)/(this._cascadeMaxExtents[p].y-this._cascadeMinExtents[p].y),this._depthCorrection[p]=p===0?1:(this._cascadeMaxExtents[p].z-this._cascadeMinExtents[p].z)/(this._cascadeMaxExtents[0].z-this._cascadeMinExtents[0].z);n.setDepthStencilTexture("shadowSampler"+e,s),n.setTexture("depthSampler"+e,s),n.setArray2("lightSizeUVCorrection"+e,this._lightSizeUVCorrection),n.setArray("depthCorrection"+e,this._depthCorrection),n.setFloat("penumbraDarkness"+e,this.penumbraDarkness),i._uniformBuffer.updateFloat4("shadowsInfo",this.getDarkness(),1/d,this._contactHardeningLightSizeUVRatio*d,this.frustumEdgeFalloff,e)}else n.setTexture("shadowSampler"+e,s),i._uniformBuffer.updateFloat4("shadowsInfo",this.getDarkness(),d,1/d,this.frustumEdgeFalloff,e);i._uniformBuffer.updateFloat2("depthValues",this.getLight().getDepthMinZ(a),this.getLight().getDepthMinZ(a)+this.getLight().getDepthMaxZ(a),e)}}}},t.prototype.getTransformMatrix=function(){return this.getCascadeTransformMatrix(0)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this._freezeShadowCastersBoundingInfoObservable&&(this._scene.onBeforeRenderObservable.remove(this._freezeShadowCastersBoundingInfoObservable),this._freezeShadowCastersBoundingInfoObservable=null),this._depthReducer&&(this._depthReducer.dispose(),this._depthReducer=null)},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this),n=this.getShadowMap();if(!n)return e;if(e.numCascades=this._numCascades,e.debug=this._debug,e.stabilizeCascades=this.stabilizeCascades,e.lambda=this._lambda,e.cascadeBlendPercentage=this.cascadeBlendPercentage,e.depthClamp=this._depthClamp,e.autoCalcDepthBounds=this.autoCalcDepthBounds,e.shadowMaxZ=this._shadowMaxZ,e.penumbraDarkness=this.penumbraDarkness,e.freezeShadowCastersBoundingInfo=this._freezeShadowCastersBoundingInfo,e.minDistance=this.minDistance,e.maxDistance=this.maxDistance,e.renderList=[],n.renderList)for(var i=0;i<n.renderList.length;i++){var o=n.renderList[i];e.renderList.push(o.id)}return e},t.Parse=function(e,n){var i=Un.Parse(e,n,function(o,a){return new t(o,a)});return e.numCascades!==void 0&&(i.numCascades=e.numCascades),e.debug!==void 0&&(i.debug=e.debug),e.stabilizeCascades!==void 0&&(i.stabilizeCascades=e.stabilizeCascades),e.lambda!==void 0&&(i.lambda=e.lambda),e.cascadeBlendPercentage!==void 0&&(i.cascadeBlendPercentage=e.cascadeBlendPercentage),e.depthClamp!==void 0&&(i.depthClamp=e.depthClamp),e.autoCalcDepthBounds!==void 0&&(i.autoCalcDepthBounds=e.autoCalcDepthBounds),e.shadowMaxZ!==void 0&&(i.shadowMaxZ=e.shadowMaxZ),e.penumbraDarkness!==void 0&&(i.penumbraDarkness=e.penumbraDarkness),e.freezeShadowCastersBoundingInfo!==void 0&&(i.freezeShadowCastersBoundingInfo=e.freezeShadowCastersBoundingInfo),e.minDistance!==void 0&&e.maxDistance!==void 0&&i.setMinMaxDistance(e.minDistance,e.maxDistance),i},t.frustumCornersNDCSpace=[new u.e(-1,1,-1),new u.e(1,1,-1),new u.e(1,-1,-1),new u.e(-1,-1,-1),new u.e(-1,1,1),new u.e(1,1,1),new u.e(1,-1,1),new u.e(-1,-1,1)],t.CLASSNAME="CascadedShadowGenerator",t.DEFAULT_CASCADES_COUNT=4,t.MIN_CASCADES_COUNT=2,t.MAX_CASCADES_COUNT=4,t._SceneComponentInitialization=function(e){throw An.a.WarnImport("ShadowGeneratorSceneComponent")},t}(Un);U.a.AddParser(at.a.NAME_SHADOWGENERATOR,function(r,t){if(r.shadowGenerators!==void 0&&r.shadowGenerators!==null)for(var e=0,n=r.shadowGenerators.length;e<n;e++){var i=r.shadowGenerators[e];i.className===js.CLASSNAME?js.Parse(i,t):Un.Parse(i,t)}});var ku=function(){function r(t){this.name=at.a.NAME_SHADOWGENERATOR,this.scene=t}return r.prototype.register=function(){this.scene._gatherRenderTargetsStage.registerStep(at.a.STEP_GATHERRENDERTARGETS_SHADOWGENERATOR,this,this._gatherRenderTargets)},r.prototype.rebuild=function(){},r.prototype.serialize=function(t){t.shadowGenerators=[];for(var e=0,n=this.scene.lights;e<n.length;e++){var i=n[e].getShadowGenerator();i&&t.shadowGenerators.push(i.serialize())}},r.prototype.addFromContainer=function(t){},r.prototype.removeFromContainer=function(t,e){},r.prototype.dispose=function(){},r.prototype._gatherRenderTargets=function(t){var e=this.scene;if(this.scene.shadowsEnabled)for(var n=0;n<e.lights.length;n++){var i=e.lights[n],o=i.getShadowGenerator();if(i.isEnabled()&&i.shadowEnabled&&o){var a=o.getShadowMap();e.textures.indexOf(a)!==-1&&t.push(a)}}},r}();Un._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_SHADOWGENERATOR);t||(t=new ku(r),r._addComponent(t))},Q.a.AddNodeConstructor("Light_Type_0",function(r,t){return function(){return new Hs(r,u.e.Zero(),t)}});var Hs=function(r){function t(e,n,i){var o=r.call(this,e,i)||this;return o._shadowAngle=Math.PI/2,o.position=n,o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"shadowAngle",{get:function(){return this._shadowAngle},set:function(e){this._shadowAngle=e,this.forceProjectionMatrixCompute()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"direction",{get:function(){return this._direction},set:function(e){var n=this.needCube();this._direction=e,this.needCube()!==n&&this._shadowGenerator&&this._shadowGenerator.recreateShadowMap()},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"PointLight"},t.prototype.getTypeID=function(){return xi.a.LIGHTTYPEID_POINTLIGHT},t.prototype.needCube=function(){return!this.direction},t.prototype.getShadowDirection=function(e){if(this.direction)return r.prototype.getShadowDirection.call(this,e);switch(e){case 0:return new u.e(1,0,0);case 1:return new u.e(-1,0,0);case 2:return new u.e(0,-1,0);case 3:return new u.e(0,1,0);case 4:return new u.e(0,0,1);case 5:return new u.e(0,0,-1)}return u.e.Zero()},t.prototype._setDefaultShadowProjectionMatrix=function(e,n,i){var o=this.getScene().activeCamera;o&&u.a.PerspectiveFovLHToRef(this.shadowAngle,1,this.getDepthMinZ(o),this.getDepthMaxZ(o),e)},t.prototype._buildUniformLayout=function(){this._uniformBuffer.addUniform("vLightData",4),this._uniformBuffer.addUniform("vLightDiffuse",4),this._uniformBuffer.addUniform("vLightSpecular",4),this._uniformBuffer.addUniform("vLightFalloff",4),this._uniformBuffer.addUniform("shadowsInfo",3),this._uniformBuffer.addUniform("depthValues",2),this._uniformBuffer.create()},t.prototype.transferToEffect=function(e,n){return this.computeTransformedInformation()?this._uniformBuffer.updateFloat4("vLightData",this.transformedPosition.x,this.transformedPosition.y,this.transformedPosition.z,0,n):this._uniformBuffer.updateFloat4("vLightData",this.position.x,this.position.y,this.position.z,0,n),this._uniformBuffer.updateFloat4("vLightFalloff",this.range,this._inverseSquaredRange,0,0,n),this},t.prototype.transferToNodeMaterialEffect=function(e,n){return this.computeTransformedInformation()?e.setFloat3(n,this.transformedPosition.x,this.transformedPosition.y,this.transformedPosition.z):e.setFloat3(n,this.position.x,this.position.y,this.position.z),this},t.prototype.prepareLightSpecificDefines=function(e,n){e["POINTLIGHT"+n]=!0},Object(c.c)([Object(L.c)()],t.prototype,"shadowAngle",null),t}(qo),Gu=function(){function r(t,e,n){var i=this;e===void 0&&(e=""),n===void 0&&(n="black"),this._renderingCanvas=t,this._loadingText=e,this._loadingDivBackgroundColor=n,this._resizeLoadingUI=function(){var o=i._renderingCanvas.getBoundingClientRect(),a=window.getComputedStyle(i._renderingCanvas).position;i._loadingDiv&&(i._loadingDiv.style.position=a==="fixed"?"fixed":"absolute",i._loadingDiv.style.left=o.left+"px",i._loadingDiv.style.top=o.top+"px",i._loadingDiv.style.width=o.width+"px",i._loadingDiv.style.height=o.height+"px")}}return r.prototype.displayLoadingUI=function(){if(!this._loadingDiv){this._loadingDiv=document.createElement("div"),this._loadingDiv.id="babylonjsLoadingDiv",this._loadingDiv.style.opacity="0",this._loadingDiv.style.transition="opacity 1.5s ease",this._loadingDiv.style.pointerEvents="none",this._loadingDiv.style.display="grid",this._loadingDiv.style.gridTemplateRows="100%",this._loadingDiv.style.gridTemplateColumns="100%",this._loadingDiv.style.justifyItems="center",this._loadingDiv.style.alignItems="center",this._loadingTextDiv=document.createElement("div"),this._loadingTextDiv.style.position="absolute",this._loadingTextDiv.style.left="0",this._loadingTextDiv.style.top="50%",this._loadingTextDiv.style.marginTop="80px",this._loadingTextDiv.style.width="100%",this._loadingTextDiv.style.height="20px",this._loadingTextDiv.style.fontFamily="Arial",this._loadingTextDiv.style.fontSize="14px",this._loadingTextDiv.style.color="white",this._loadingTextDiv.style.textAlign="center",this._loadingTextDiv.style.zIndex="1",this._loadingTextDiv.innerHTML="Loading",this._loadingDiv.appendChild(this._loadingTextDiv),this._loadingTextDiv.innerHTML=this._loadingText;var t=document.createElement("style");t.type="text/css",t.innerHTML=`@-webkit-keyframes spin1 {                    0% { -webkit-transform: rotate(0deg);}
-                    100% { -webkit-transform: rotate(360deg);}
-                }                @keyframes spin1 {                    0% { transform: rotate(0deg);}
-                    100% { transform: rotate(360deg);}
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"+a.w/2+"vh)",n.style.top="calc(50% - "+a.h/2+"vh)",o.style.width=s.w+"vh",o.style.height=s.h+"vh",o.style.left="calc(50% - "+s.w/2+"vh)",o.style.top="calc(50% - "+s.h/2+"vh)"}i.appendChild(o),this._loadingDiv.appendChild(n),this._loadingDiv.appendChild(i),this._resizeLoadingUI(),window.addEventListener("resize",this._resizeLoadingUI),this._loadingDiv.style.backgroundColor=this._loadingDivBackgroundColor,document.body.appendChild(this._loadingDiv),this._loadingDiv.style.opacity="1"}},r.prototype.hideLoadingUI=function(){var t=this;this._loadingDiv&&(this._loadingDiv.style.opacity="0",this._loadingDiv.addEventListener("transitionend",function(){t._loadingDiv&&(t._loadingDiv.parentElement&&t._loadingDiv.parentElement.removeChild(t._loadingDiv),window.removeEventListener("resize",t._resizeLoadingUI),t._loadingDiv=null)}))},Object.defineProperty(r.prototype,"loadingUIText",{get:function(){return this._loadingText},set:function(t){this._loadingText=t,this._loadingTextDiv&&(this._loadingTextDiv.innerHTML=this._loadingText)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"loadingUIBackgroundColor",{get:function(){return this._loadingDivBackgroundColor},set:function(t){this._loadingDivBackgroundColor=t,this._loadingDiv&&(this._loadingDiv.style.backgroundColor=this._loadingDivBackgroundColor)},enumerable:!1,configurable:!0}),r.DefaultLogoUrl="",r.DefaultSpinnerUrl="",r}();Ue.a.DefaultLoadingScreenFactory=function(r){return new Gu(r)};var Ws=f(71),rr=f(68),Xs=function(){function r(){}return r.ConvertPanoramaToCubemap=function(t,e,n,i){if(!t)throw"ConvertPanoramaToCubemap: input cannot be null";if(t.length!=e*n*3)throw"ConvertPanoramaToCubemap: input size is wrong";return{front:this.CreateCubemapTexture(i,this.FACE_FRONT,t,e,n),back:this.CreateCubemapTexture(i,this.FACE_BACK,t,e,n),left:this.CreateCubemapTexture(i,this.FACE_LEFT,t,e,n),right:this.CreateCubemapTexture(i,this.FACE_RIGHT,t,e,n),up:this.CreateCubemapTexture(i,this.FACE_UP,t,e,n),down:this.CreateCubemapTexture(i,this.FACE_DOWN,t,e,n),size:i,type:h.a.TEXTURETYPE_FLOAT,format:h.a.TEXTUREFORMAT_RGB,gammaSpace:!1}},r.CreateCubemapTexture=function(t,e,n,i,o){for(var a=new ArrayBuffer(t*t*4*3),s=new Float32Array(a),d=e[1].subtract(e[0]).scale(1/t),p=e[3].subtract(e[2]).scale(1/t),b=1/t,P=0,O=0;O<t;O++){for(var B=e[0],F=e[2],z=0;z<t;z++){var J=F.subtract(B).scale(P).add(B);J.normalize();var ie=this.CalcProjectionSpherical(J,n,i,o);s[O*t*3+3*z+0]=ie.r,s[O*t*3+3*z+1]=ie.g,s[O*t*3+3*z+2]=ie.b,B=B.add(d),F=F.add(p)}P+=b}return s},r.CalcProjectionSpherical=function(t,e,n,i){for(var o=Math.atan2(t.z,t.x),a=Math.acos(t.y);o<-Math.PI;)o+=2*Math.PI;for(;o>Math.PI;)o-=2*Math.PI;var s=o/Math.PI,d=a/Math.PI;s=.5*s+.5;var p=Math.round(s*n);p<0?p=0:p>=n&&(p=n-1);var b=Math.round(d*i);b<0?b=0:b>=i&&(b=i-1);var P=i-b-1;return{r:e[P*n*3+3*p+0],g:e[P*n*3+3*p+1],b:e[P*n*3+3*p+2]}},r.FACE_LEFT=[new u.e(-1,-1,-1),new u.e(1,-1,-1),new u.e(-1,1,-1),new u.e(1,1,-1)],r.FACE_RIGHT=[new u.e(1,-1,1),new u.e(-1,-1,1),new u.e(1,1,1),new u.e(-1,1,1)],r.FACE_FRONT=[new u.e(1,-1,-1),new u.e(1,-1,1),new u.e(1,1,-1),new u.e(1,1,1)],r.FACE_BACK=[new u.e(-1,-1,1),new u.e(-1,-1,-1),new u.e(-1,1,1),new u.e(-1,1,-1)],r.FACE_DOWN=[new u.e(1,1,-1),new u.e(1,1,1),new u.e(-1,1,-1),new u.e(-1,1,1)],r.FACE_UP=[new u.e(-1,-1,-1),new u.e(-1,-1,1),new u.e(1,-1,-1),new u.e(1,-1,1)],r}(),zu=function(){function r(){}return r.Ldexp=function(t,e){return e>1023?t*Math.pow(2,1023)*Math.pow(2,e-1023):e<-1074?t*Math.pow(2,-1074)*Math.pow(2,e+1074):t*Math.pow(2,e)},r.Rgbe2float=function(t,e,n,i,o,a){o>0?(o=this.Ldexp(1,o-136),t[a+0]=e*o,t[a+1]=n*o,t[a+2]=i*o):(t[a+0]=0,t[a+1]=0,t[a+2]=0)},r.readStringLine=function(t,e){for(var n="",i="",o=e;o<t.length-e&&(i=String.fromCharCode(t[o]))!=`
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-`):"";t.useShaderStore?(e.fragment=e.fragmentSource,e.vertex||(e.vertex=e.vertexSource),delete e.fragmentSource,delete e.vertexSource,this.effect=t.engine.createEffect(e.spectorName,t.attributeNames||["position"],i,t.samplerNames,o,void 0,t.onCompiled)):this.effect=new ze.a(e,t.attributeNames||["position"],i,t.samplerNames,t.engine,o,void 0,t.onCompiled)}return r.prototype.dispose=function(){this.effect.dispose()},r}(),X_=`
-attribute vec2 position;
-
-varying vec3 direction;
-
-uniform vec3 up;
-uniform vec3 right;
-uniform vec3 front;
-void main(void) {
-mat3 view=mat3(up,right,front);
-direction=view*vec3(position,1.0);
-gl_Position=vec4(position,0.0,1.0);
-}`;ze.a.ShadersStore.hdrFilteringVertexShader=X_;var Y_=`#include<helperFunctions>
-#include<importanceSampling>
-#include<pbrBRDFFunctions>
-#include<hdrFilteringFunctions>
-uniform float alphaG;
-uniform samplerCube inputTexture;
-uniform vec2 vFilteringInfo;
-uniform float hdrScale;
-varying vec3 direction;
-void main() {
-vec3 color=radiance(alphaG,inputTexture,direction,vFilteringInfo);
-gl_FragColor=vec4(color*hdrScale,1.0);
-}`;ze.a.ShadersStore.hdrFilteringPixelShader=Y_;var Wu=function(){function r(t,e){e===void 0&&(e={}),this._lodGenerationOffset=0,this._lodGenerationScale=.8,this.quality=h.a.TEXTURE_FILTERING_QUALITY_OFFLINE,this.hdrScale=1,this._engine=t,this.hdrScale=e.hdrScale||this.hdrScale,this.quality=e.hdrScale||this.quality}return r.prototype._createRenderTarget=function(t){var e=h.a.TEXTURETYPE_UNSIGNED_BYTE;this._engine.getCaps().textureHalfFloatRender?e=h.a.TEXTURETYPE_HALF_FLOAT:this._engine.getCaps().textureFloatRender&&(e=h.a.TEXTURETYPE_FLOAT);var n=this._engine.createRenderTargetCubeTexture(t,{format:h.a.TEXTUREFORMAT_RGBA,type:e,generateMipMaps:!1,generateDepthBuffer:!1,generateStencilBuffer:!1,samplingMode:h.a.TEXTURE_NEAREST_SAMPLINGMODE});return this._engine.updateTextureWrappingMode(n,h.a.TEXTURE_CLAMP_ADDRESSMODE,h.a.TEXTURE_CLAMP_ADDRESSMODE,h.a.TEXTURE_CLAMP_ADDRESSMODE),this._engine.updateTextureSamplingMode(h.a.TEXTURE_TRILINEAR_SAMPLINGMODE,n,!0),n},r.prototype._prefilterInternal=function(t){var e=t.getSize().width,n=Math.round($.a.Log2(e))+1,i=this._effectWrapper.effect,o=this._createRenderTarget(e);this._effectRenderer.setViewport();var a=t.getInternalTexture();a&&this._engine.updateTextureSamplingMode(h.a.TEXTURE_TRILINEAR_SAMPLINGMODE,a,!0),this._effectRenderer.applyEffectWrapper(this._effectWrapper);var s=[[new u.e(0,0,-1),new u.e(0,-1,0),new u.e(1,0,0)],[new u.e(0,0,1),new u.e(0,-1,0),new u.e(-1,0,0)],[new u.e(1,0,0),new u.e(0,0,1),new u.e(0,1,0)],[new u.e(1,0,0),new u.e(0,0,-1),new u.e(0,-1,0)],[new u.e(1,0,0),new u.e(0,-1,0),new u.e(0,0,1)],[new u.e(-1,0,0),new u.e(0,-1,0),new u.e(0,0,-1)]];i.setFloat("hdrScale",this.hdrScale),i.setFloat2("vFilteringInfo",t.getSize().width,n),i.setTexture("inputTexture",t);for(var d=0;d<6;d++){i.setVector3("up",s[d][0]),i.setVector3("right",s[d][1]),i.setVector3("front",s[d][2]);for(var p=0;p<n;p++){this._engine.bindFramebuffer(o,d,void 0,void 0,!0,p),this._effectRenderer.applyEffectWrapper(this._effectWrapper);var b=Math.pow(2,(p-this._lodGenerationOffset)/this._lodGenerationScale)/e;p===0&&(b=0),i.setFloat("alphaG",b),this._effectRenderer.draw()}}return this._effectRenderer.restoreStates(),this._engine.restoreDefaultFramebuffer(),this._engine._releaseFramebufferObjects(o),this._engine._releaseTexture(t._texture),o._swapAndDie(t._texture),t._prefiltered=!0,t},r.prototype._createEffect=function(t,e){var n=[];return t.gammaSpace&&n.push("#define GAMMA_INPUT"),n.push("#define NUM_SAMPLES "+this.quality+"u"),new Hu({engine:this._engine,name:"hdrFiltering",vertexShader:"hdrFiltering",fragmentShader:"hdrFiltering",samplerNames:["inputTexture"],uniformNames:["vSampleDirections","vWeights","up","right","front","vFilteringInfo","hdrScale","alphaG"],useShaderStore:!0,defines:n,onCompiled:e})},r.prototype.isReady=function(t){return t.isReady()&&this._effectWrapper.effect.isReady()},r.prototype.prefilter=function(t,e){var n=this;if(e===void 0&&(e=null),this._engine.webGLVersion!==1)return new Promise(function(i){n._effectRenderer=new ju(n._engine),n._effectWrapper=n._createEffect(t),n._effectWrapper.effect.executeWhenCompiled(function(){n._prefilterInternal(t),n._effectRenderer.dispose(),n._effectWrapper.dispose(),i(),e&&e()})});l.a.Warn("HDR prefiltering is not available in WebGL 1., you can use real time filtering instead.")},r}(),aa=function(r){function t(e,n,i,o,a,s,d,p,b){var P;o===void 0&&(o=!1),a===void 0&&(a=!0),s===void 0&&(s=!1),d===void 0&&(d=!1),p===void 0&&(p=null),b===void 0&&(b=null);var O=r.call(this,n)||this;return O._generateHarmonics=!0,O._onLoad=null,O._onError=null,O._isBlocking=!0,O._rotationY=0,O.boundingBoxPosition=u.e.Zero(),e&&(O._coordinatesMode=we.a.CUBIC_MODE,O.name=e,O.url=e,O.hasAlpha=!1,O.isCube=!0,O._textureMatrix=u.a.Identity(),O._prefilterOnLoad=d,O._onLoad=p,O._onError=b,O.gammaSpace=s,O._noMipmap=o,O._size=i,O._generateHarmonics=a,O._texture=O._getFromCache(e,O._noMipmap),O._texture?p&&(O._texture.isReady?Xe.b.SetImmediate(function(){return p()}):O._texture.onLoadedObservable.add(p)):!((P=O.getScene())===null||P===void 0)&&P.useDelayedTextureLoading?O.delayLoadState=h.a.DELAYLOADSTATE_NOTLOADED:O.loadTexture()),O}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"isBlocking",{get:function(){return this._isBlocking},set:function(e){this._isBlocking=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rotationY",{get:function(){return this._rotationY},set:function(e){this._rotationY=e,this.setReflectionTextureMatrix(u.a.RotationY(this._rotationY))},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"boundingBoxSize",{get:function(){return this._boundingBoxSize},set:function(e){if(!this._boundingBoxSize||!this._boundingBoxSize.equals(e)){this._boundingBoxSize=e;var n=this.getScene();n&&n.markAllMaterialsAsDirty(h.a.MATERIAL_TextureDirtyFlag)}},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"HDRCubeTexture"},t.prototype.loadTexture=function(){var e=this,n=this._getEngine();if(this._getEngine().webGLVersion>=2&&this._prefilterOnLoad){var i=this._onLoad,o=new Wu(n);this._onLoad=function(){o.prefilter(e,i)}}this._texture=n.createRawCubeTextureFromUrl(this.url,this.getScene(),this._size,h.a.TEXTUREFORMAT_RGB,n.getCaps().textureFloat?h.a.TEXTURETYPE_FLOAT:h.a.TEXTURETYPE_UNSIGNED_INT,this._noMipmap,function(a){e.lodGenerationOffset=0,e.lodGenerationScale=.8;var s=zu.GetCubeMapTextureData(a,e._size);if(e._generateHarmonics){var d=jo.ConvertCubeMapToSphericalPolynomial(s);e.sphericalPolynomial=d}for(var p=[],b=null,P=0;P<6;P++){if(!n.getCaps().textureFloat){var O=new ArrayBuffer(e._size*e._size*3);b=new Uint8Array(O)}var B=s[t._facesMapping[P]];if(e.gammaSpace||b){for(var F=0;F<e._size*e._size;F++)if(e.gammaSpace&&(B[3*F+0]=Math.pow(B[3*F+0],Gt.b),B[3*F+1]=Math.pow(B[3*F+1],Gt.b),B[3*F+2]=Math.pow(B[3*F+2],Gt.b)),b){var z=Math.max(255*B[3*F+0],0),J=Math.max(255*B[3*F+1],0),ie=Math.max(255*B[3*F+2],0),se=Math.max(Math.max(z,J),ie);if(se>255){var ce=255/se;z*=ce,J*=ce,ie*=ce}b[3*F+0]=z,b[3*F+1]=J,b[3*F+2]=ie}}b?p.push(b):p.push(B)}return p},null,this._onLoad,this._onError)},t.prototype.clone=function(){var e=new t(this.url,this.getScene()||this._getEngine(),this._size,this._noMipmap,this._generateHarmonics,this.gammaSpace);return e.level=this.level,e.wrapU=this.wrapU,e.wrapV=this.wrapV,e.coordinatesIndex=this.coordinatesIndex,e.coordinatesMode=this.coordinatesMode,e},t.prototype.delayLoad=function(){this.delayLoadState===h.a.DELAYLOADSTATE_NOTLOADED&&(this.delayLoadState=h.a.DELAYLOADSTATE_LOADED,this._texture=this._getFromCache(this.url,this._noMipmap),this._texture||this.loadTexture())},t.prototype.getReflectionTextureMatrix=function(){return this._textureMatrix},t.prototype.setReflectionTextureMatrix=function(e){var n,i=this;this._textureMatrix=e,e.updateFlag!==this._textureMatrix.updateFlag&&e.isIdentity()!==this._textureMatrix.isIdentity()&&((n=this.getScene())===null||n===void 0||n.markAllMaterialsAsDirty(h.a.MATERIAL_TextureDirtyFlag,function(o){return o.getActiveTextures().indexOf(i)!==-1}))},t.Parse=function(e,n,i){var o=null;return e.name&&!e.isRenderTarget&&((o=new t(i+e.name,n,e.size,e.noMipmap,e.generateHarmonics,e.useInGammaSpace)).name=e.name,o.hasAlpha=e.hasAlpha,o.level=e.level,o.coordinatesMode=e.coordinatesMode,o.isBlocking=e.isBlocking),o&&(e.boundingBoxPosition&&(o.boundingBoxPosition=u.e.FromArray(e.boundingBoxPosition)),e.boundingBoxSize&&(o.boundingBoxSize=u.e.FromArray(e.boundingBoxSize)),e.rotationY&&(o.rotationY=e.rotationY)),o},t.prototype.serialize=function(){if(!this.name)return null;var e={};return e.name=this.name,e.hasAlpha=this.hasAlpha,e.isCube=!0,e.level=this.level,e.size=this._size,e.coordinatesMode=this.coordinatesMode,e.useInGammaSpace=this.gammaSpace,e.generateHarmonics=this._generateHarmonics,e.customType="BABYLON.HDRCubeTexture",e.noMipmap=this._noMipmap,e.isBlocking=this._isBlocking,e.rotationY=this._rotationY,e},t._facesMapping=["right","left","up","down","front","back"],t}(zn.a);R.a.RegisteredTypes["BABYLON.HDRCubeTexture"]=aa;var Xu=function(){function r(t,e,n){e===void 0&&(e=0),n===void 0&&(n=null),this.name=t,this.animations=new Array,this._positions=null,this._normals=null,this._tangents=null,this._uvs=null,this._uniqueId=0,this.onInfluenceChanged=new x.c,this._onDataLayoutChanged=new x.c,this._animationPropertiesOverride=null,this._scene=n||te.a.LastCreatedScene,this.influence=e,this._scene&&(this._uniqueId=this._scene.getUniqueId())}return Object.defineProperty(r.prototype,"influence",{get:function(){return this._influence},set:function(t){if(this._influence!==t){var e=this._influence;this._influence=t,this.onInfluenceChanged.hasObservers()&&this.onInfluenceChanged.notifyObservers(e===0||t===0)}},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"animationPropertiesOverride",{get:function(){return!this._animationPropertiesOverride&&this._scene?this._scene.animationPropertiesOverride:this._animationPropertiesOverride},set:function(t){this._animationPropertiesOverride=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"uniqueId",{get:function(){return this._uniqueId},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hasPositions",{get:function(){return!!this._positions},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hasNormals",{get:function(){return!!this._normals},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hasTangents",{get:function(){return!!this._tangents},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hasUVs",{get:function(){return!!this._uvs},enumerable:!1,configurable:!0}),r.prototype.setPositions=function(t){var e=this.hasPositions;this._positions=t,e!==this.hasPositions&&this._onDataLayoutChanged.notifyObservers(void 0)},r.prototype.getPositions=function(){return this._positions},r.prototype.setNormals=function(t){var e=this.hasNormals;this._normals=t,e!==this.hasNormals&&this._onDataLayoutChanged.notifyObservers(void 0)},r.prototype.getNormals=function(){return this._normals},r.prototype.setTangents=function(t){var e=this.hasTangents;this._tangents=t,e!==this.hasTangents&&this._onDataLayoutChanged.notifyObservers(void 0)},r.prototype.getTangents=function(){return this._tangents},r.prototype.setUVs=function(t){var e=this.hasUVs;this._uvs=t,e!==this.hasUVs&&this._onDataLayoutChanged.notifyObservers(void 0)},r.prototype.getUVs=function(){return this._uvs},r.prototype.clone=function(){var t=this,e=L.a.Clone(function(){return new r(t.name,t.influence,t._scene)},this);return e._positions=this._positions,e._normals=this._normals,e._tangents=this._tangents,e._uvs=this._uvs,e},r.prototype.serialize=function(){var t={};return t.name=this.name,t.influence=this.influence,t.positions=Array.prototype.slice.call(this.getPositions()),this.id!=null&&(t.id=this.id),this.hasNormals&&(t.normals=Array.prototype.slice.call(this.getNormals())),this.hasTangents&&(t.tangents=Array.prototype.slice.call(this.getTangents())),this.hasUVs&&(t.uvs=Array.prototype.slice.call(this.getUVs())),L.a.AppendSerializedAnimations(this,t),t},r.prototype.getClassName=function(){return"MorphTarget"},r.Parse=function(t){var e=new r(t.name,t.influence);if(e.setPositions(t.positions),t.id!=null&&(e.id=t.id),t.normals&&e.setNormals(t.normals),t.tangents&&e.setTangents(t.tangents),t.uvs&&e.setUVs(t.uvs),t.animations)for(var n=0;n<t.animations.length;n++){var i=t.animations[n],o=R.a.GetClass("BABYLON.Animation");o&&e.animations.push(o.Parse(i))}return e},r.FromMesh=function(t,e,n){e||(e=t.name);var i=new r(e,n,t.getScene());return i.setPositions(t.getVerticesData(Oe.b.PositionKind)),t.isVerticesDataPresent(Oe.b.NormalKind)&&i.setNormals(t.getVerticesData(Oe.b.NormalKind)),t.isVerticesDataPresent(Oe.b.TangentKind)&&i.setTangents(t.getVerticesData(Oe.b.TangentKind)),t.isVerticesDataPresent(Oe.b.UVKind)&&i.setUVs(t.getVerticesData(Oe.b.UVKind)),i},Object(c.c)([Object(L.c)()],r.prototype,"id",void 0),r}(),sa=function(){function r(t){t===void 0&&(t=null),this._targets=new Array,this._targetInfluenceChangedObservers=new Array,this._targetDataLayoutChangedObservers=new Array,this._activeTargets=new fi.a(16),this._supportsNormals=!1,this._supportsTangents=!1,this._supportsUVs=!1,this._vertexCount=0,this._uniqueId=0,this._tempInfluences=new Array,this.enableNormalMorphing=!0,this.enableTangentMorphing=!0,this.enableUVMorphing=!0,t||(t=te.a.LastCreatedScene),this._scene=t,this._scene&&(this._scene.morphTargetManagers.push(this),this._uniqueId=this._scene.getUniqueId())}return Object.defineProperty(r.prototype,"uniqueId",{get:function(){return this._uniqueId},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"vertexCount",{get:function(){return this._vertexCount},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"supportsNormals",{get:function(){return this._supportsNormals&&this.enableNormalMorphing},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"supportsTangents",{get:function(){return this._supportsTangents&&this.enableTangentMorphing},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"supportsUVs",{get:function(){return this._supportsUVs&&this.enableUVMorphing},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"numTargets",{get:function(){return this._targets.length},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"numInfluencers",{get:function(){return this._activeTargets.length},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"influences",{get:function(){return this._influences},enumerable:!1,configurable:!0}),r.prototype.getActiveTarget=function(t){return this._activeTargets.data[t]},r.prototype.getTarget=function(t){return this._targets[t]},r.prototype.addTarget=function(t){var e=this;this._targets.push(t),this._targetInfluenceChangedObservers.push(t.onInfluenceChanged.add(function(n){e._syncActiveTargets(n)})),this._targetDataLayoutChangedObservers.push(t._onDataLayoutChanged.add(function(){e._syncActiveTargets(!0)})),this._syncActiveTargets(!0)},r.prototype.removeTarget=function(t){var e=this._targets.indexOf(t);e>=0&&(this._targets.splice(e,1),t.onInfluenceChanged.remove(this._targetInfluenceChangedObservers.splice(e,1)[0]),t._onDataLayoutChanged.remove(this._targetDataLayoutChangedObservers.splice(e,1)[0]),this._syncActiveTargets(!0))},r.prototype.clone=function(){for(var t=new r(this._scene),e=0,n=this._targets;e<n.length;e++){var i=n[e];t.addTarget(i.clone())}return t.enableNormalMorphing=this.enableNormalMorphing,t.enableTangentMorphing=this.enableTangentMorphing,t.enableUVMorphing=this.enableUVMorphing,t},r.prototype.serialize=function(){var t={};t.id=this.uniqueId,t.targets=[];for(var e=0,n=this._targets;e<n.length;e++){var i=n[e];t.targets.push(i.serialize())}return t},r.prototype._syncActiveTargets=function(t){var e=0;this._activeTargets.reset(),this._supportsNormals=!0,this._supportsTangents=!0,this._supportsUVs=!0,this._vertexCount=0;for(var n=0,i=this._targets;n<i.length;n++){var o=i[n];if(o.influence!==0){this._activeTargets.push(o),this._tempInfluences[e++]=o.influence,this._supportsNormals=this._supportsNormals&&o.hasNormals,this._supportsTangents=this._supportsTangents&&o.hasTangents,this._supportsUVs=this._supportsUVs&&o.hasUVs;var a=o.getPositions();if(a){var s=a.length/3;if(this._vertexCount===0)this._vertexCount=s;else if(this._vertexCount!==s)return void l.a.Error("Incompatible target. Targets must all have the same vertices count.")}}}this._influences&&this._influences.length===e||(this._influences=new Float32Array(e));for(var d=0;d<e;d++)this._influences[d]=this._tempInfluences[d];t&&this.synchronize()},r.prototype.synchronize=function(){if(this._scene)for(var t=0,e=this._scene.meshes;t<e.length;t++){var n=e[t];n.morphTargetManager===this&&n._syncGeometryWithMorphTargetManager()}},r.Parse=function(t,e){var n=new r(e);n._uniqueId=t.id;for(var i=0,o=t.targets;i<o.length;i++){var a=o[i];n.addTarget(Xu.Parse(a))}return n},r}(),Ct=f(32),en=f(50),Ir=function(){function r(t,e){if(e===void 0&&(e=r.DefaultPluginFactory()),this._physicsPlugin=e,this._impostors=[],this._joints=[],this._subTimeStep=0,!this._physicsPlugin.isSupported())throw new Error("Physics Engine "+this._physicsPlugin.name+" cannot be found. Please make sure it is included.");t=t||new u.e(0,-9.807,0),this.setGravity(t),this.setTimeStep()}return r.DefaultPluginFactory=function(){throw An.a.WarnImport("CannonJSPlugin")},r.prototype.setGravity=function(t){this.gravity=t,this._physicsPlugin.setGravity(this.gravity)},r.prototype.setTimeStep=function(t){t===void 0&&(t=1/60),this._physicsPlugin.setTimeStep(t)},r.prototype.getTimeStep=function(){return this._physicsPlugin.getTimeStep()},r.prototype.setSubTimeStep=function(t){t===void 0&&(t=0),this._subTimeStep=t},r.prototype.getSubTimeStep=function(){return this._subTimeStep},r.prototype.dispose=function(){this._impostors.forEach(function(t){t.dispose()}),this._physicsPlugin.dispose()},r.prototype.getPhysicsPluginName=function(){return this._physicsPlugin.name},r.prototype.addImpostor=function(t){t.uniqueId=this._impostors.push(t),t.parent||this._physicsPlugin.generatePhysicsBody(t)},r.prototype.removeImpostor=function(t){var e=this._impostors.indexOf(t);e>-1&&this._impostors.splice(e,1).length&&this.getPhysicsPlugin().removePhysicsBody(t)},r.prototype.addJoint=function(t,e,n){var i={mainImpostor:t,connectedImpostor:e,joint:n};n.physicsPlugin=this._physicsPlugin,this._joints.push(i),this._physicsPlugin.generateJoint(i)},r.prototype.removeJoint=function(t,e,n){var i=this._joints.filter(function(o){return o.connectedImpostor===e&&o.joint===n&&o.mainImpostor===t});i.length&&this._physicsPlugin.removeJoint(i[0])},r.prototype._step=function(t){var e=this;this._impostors.forEach(function(n){n.isBodyInitRequired()&&e._physicsPlugin.generatePhysicsBody(n)}),t>.1?t=.1:t<=0&&(t=1/60),this._physicsPlugin.executeStep(t,this._impostors)},r.prototype.getPhysicsPlugin=function(){return this._physicsPlugin},r.prototype.getImpostors=function(){return this._impostors},r.prototype.getImpostorForPhysicsObject=function(t){for(var e=0;e<this._impostors.length;++e)if(this._impostors[e].object===t)return this._impostors[e];return null},r.prototype.getImpostorWithPhysicsBody=function(t){for(var e=0;e<this._impostors.length;++e)if(this._impostors[e].physicsBody===t)return this._impostors[e];return null},r.prototype.raycast=function(t,e){return this._physicsPlugin.raycast(t,e)},r.Epsilon=.001,r}(),Ys=function(){function r(){this._hasHit=!1,this._hitDistance=0,this._hitNormalWorld=u.e.Zero(),this._hitPointWorld=u.e.Zero(),this._rayFromWorld=u.e.Zero(),this._rayToWorld=u.e.Zero()}return Object.defineProperty(r.prototype,"hasHit",{get:function(){return this._hasHit},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hitDistance",{get:function(){return this._hitDistance},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hitNormalWorld",{get:function(){return this._hitNormalWorld},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hitPointWorld",{get:function(){return this._hitPointWorld},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"rayFromWorld",{get:function(){return this._rayFromWorld},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"rayToWorld",{get:function(){return this._rayToWorld},enumerable:!1,configurable:!0}),r.prototype.setHitData=function(t,e){this._hasHit=!0,this._hitNormalWorld=new u.e(t.x,t.y,t.z),this._hitPointWorld=new u.e(e.x,e.y,e.z)},r.prototype.setHitDistance=function(t){this._hitDistance=t},r.prototype.calculateHitDistance=function(){this._hitDistance=u.e.Distance(this._rayFromWorld,this._hitPointWorld)},r.prototype.reset=function(t,e){t===void 0&&(t=u.e.Zero()),e===void 0&&(e=u.e.Zero()),this._rayFromWorld=t,this._rayToWorld=e,this._hasHit=!1,this._hitDistance=0,this._hitNormalWorld=u.e.Zero(),this._hitPointWorld=u.e.Zero()},r}(),Ks=function(){function r(t,e,n){t===void 0&&(t=!0),e===void 0&&(e=10),n===void 0&&(n=CANNON),this._useDeltaForWorldStep=t,this.name="CannonJSPlugin",this._physicsMaterials=new Array,this._fixedTimeStep=1/60,this._physicsBodysToRemoveAfterStep=new Array,this._firstFrame=!0,this._minus90X=new u.b(-.7071067811865475,0,0,.7071067811865475),this._plus90X=new u.b(.7071067811865475,0,0,.7071067811865475),this._tmpPosition=u.e.Zero(),this._tmpDeltaPosition=u.e.Zero(),this._tmpUnityRotation=new u.b,this.BJSCANNON=n,this.isSupported()?(this._extendNamespace(),this.world=new this.BJSCANNON.World,this.world.broadphase=new this.BJSCANNON.NaiveBroadphase,this.world.solver.iterations=e,this._cannonRaycastResult=new this.BJSCANNON.RaycastResult,this._raycastResult=new Ys):l.a.Error("CannonJS is not available. Please make sure you included the js file.")}return r.prototype.setGravity=function(t){var e=t;this.world.gravity.set(e.x,e.y,e.z)},r.prototype.setTimeStep=function(t){this._fixedTimeStep=t},r.prototype.getTimeStep=function(){return this._fixedTimeStep},r.prototype.executeStep=function(t,e){if(this._firstFrame){this._firstFrame=!1;for(var n=0,i=e;n<i.length;n++){var o=i[n];o.type!=Ct.a.HeightmapImpostor&&o.type!==Ct.a.PlaneImpostor&&o.beforeStep()}}this.world.step(this._useDeltaForWorldStep?t:this._fixedTimeStep),this._removeMarkedPhysicsBodiesFromWorld()},r.prototype._removeMarkedPhysicsBodiesFromWorld=function(){var t=this;this._physicsBodysToRemoveAfterStep.length>0&&(this._physicsBodysToRemoveAfterStep.forEach(function(e){t.world.remove(e)}),this._physicsBodysToRemoveAfterStep=[])},r.prototype.applyImpulse=function(t,e,n){var i=new this.BJSCANNON.Vec3(n.x,n.y,n.z),o=new this.BJSCANNON.Vec3(e.x,e.y,e.z);t.physicsBody.applyImpulse(o,i)},r.prototype.applyForce=function(t,e,n){var i=new this.BJSCANNON.Vec3(n.x,n.y,n.z),o=new this.BJSCANNON.Vec3(e.x,e.y,e.z);t.physicsBody.applyForce(o,i)},r.prototype.generatePhysicsBody=function(t){if(this._removeMarkedPhysicsBodiesFromWorld(),t.parent)t.physicsBody&&(this.removePhysicsBody(t),t.forceUpdate());else{if(t.isBodyInitRequired()){var e=this._createShape(t),n=t.physicsBody;n&&this.removePhysicsBody(t);var i=this._addMaterial("mat-"+t.uniqueId,t.getParam("friction"),t.getParam("restitution")),o={mass:t.getParam("mass"),material:i},a=t.getParam("nativeOptions");for(var s in a)a.hasOwnProperty(s)&&(o[s]=a[s]);t.physicsBody=new this.BJSCANNON.Body(o),t.physicsBody.addEventListener("collide",t.onCollide),this.world.addEventListener("preStep",t.beforeStep),this.world.addEventListener("postStep",t.afterStep),t.physicsBody.addShape(e),this.world.add(t.physicsBody),n&&["force","torque","velocity","angularVelocity"].forEach(function(d){var p=n[d];t.physicsBody[d].set(p.x,p.y,p.z)}),this._processChildMeshes(t)}this._updatePhysicsBodyTransformation(t)}},r.prototype._processChildMeshes=function(t){var e=this,n=t.object.getChildMeshes?t.object.getChildMeshes(!0):[],i=t.object.rotationQuaternion;if(n.length){var o=function(a){if(i&&a.rotationQuaternion){var s=a.getPhysicsImpostor();if(s&&s.parent!==t){var d=a.getAbsolutePosition().subtract(a.parent.getAbsolutePosition()),p=a.rotationQuaternion;s.physicsBody&&(e.removePhysicsBody(s),s.physicsBody=null),s.parent=t,s.resetUpdateFlags(),t.physicsBody.addShape(e._createShape(s),new e.BJSCANNON.Vec3(d.x,d.y,d.z),new e.BJSCANNON.Quaternion(p.x,p.y,p.z,p.w)),t.physicsBody.mass+=s.getParam("mass")}i.multiplyInPlace(a.rotationQuaternion),a.getChildMeshes(!0).filter(function(b){return!!b.physicsImpostor}).forEach(o)}};n.filter(function(a){return!!a.physicsImpostor}).forEach(o)}},r.prototype.removePhysicsBody=function(t){t.physicsBody.removeEventListener("collide",t.onCollide),this.world.removeEventListener("preStep",t.beforeStep),this.world.removeEventListener("postStep",t.afterStep),this._physicsBodysToRemoveAfterStep.indexOf(t.physicsBody)===-1&&this._physicsBodysToRemoveAfterStep.push(t.physicsBody)},r.prototype.generateJoint=function(t){var e=t.mainImpostor.physicsBody,n=t.connectedImpostor.physicsBody;if(e&&n){var i,o=t.joint.jointData,a={pivotA:o.mainPivot?new this.BJSCANNON.Vec3().set(o.mainPivot.x,o.mainPivot.y,o.mainPivot.z):null,pivotB:o.connectedPivot?new this.BJSCANNON.Vec3().set(o.connectedPivot.x,o.connectedPivot.y,o.connectedPivot.z):null,axisA:o.mainAxis?new this.BJSCANNON.Vec3().set(o.mainAxis.x,o.mainAxis.y,o.mainAxis.z):null,axisB:o.connectedAxis?new this.BJSCANNON.Vec3().set(o.connectedAxis.x,o.connectedAxis.y,o.connectedAxis.z):null,maxForce:o.nativeParams.maxForce,collideConnected:!!o.collision};switch(t.joint.type){case en.e.HingeJoint:case en.e.Hinge2Joint:i=new this.BJSCANNON.HingeConstraint(e,n,a);break;case en.e.DistanceJoint:i=new this.BJSCANNON.DistanceConstraint(e,n,o.maxDistance||2);break;case en.e.SpringJoint:var s=o;i=new this.BJSCANNON.Spring(e,n,{restLength:s.length,stiffness:s.stiffness,damping:s.damping,localAnchorA:a.pivotA,localAnchorB:a.pivotB});break;case en.e.LockJoint:i=new this.BJSCANNON.LockConstraint(e,n,a);break;case en.e.PointToPointJoint:case en.e.BallAndSocketJoint:default:i=new this.BJSCANNON.PointToPointConstraint(e,a.pivotA,n,a.pivotB,a.maxForce)}i.collideConnected=!!o.collision,t.joint.physicsJoint=i,t.joint.type!==en.e.SpringJoint?this.world.addConstraint(i):(t.joint.jointData.forceApplicationCallback=t.joint.jointData.forceApplicationCallback||function(){i.applyForce()},t.mainImpostor.registerAfterPhysicsStep(t.joint.jointData.forceApplicationCallback))}},r.prototype.removeJoint=function(t){t.joint.type!==en.e.SpringJoint?this.world.removeConstraint(t.joint.physicsJoint):t.mainImpostor.unregisterAfterPhysicsStep(t.joint.jointData.forceApplicationCallback)},r.prototype._addMaterial=function(t,e,n){var i,o;for(i=0;i<this._physicsMaterials.length;i++)if((o=this._physicsMaterials[i]).friction===e&&o.restitution===n)return o;var a=new this.BJSCANNON.Material(t);return a.friction=e,a.restitution=n,this._physicsMaterials.push(a),a},r.prototype._checkWithEpsilon=function(t){return t<Ir.Epsilon?Ir.Epsilon:t},r.prototype._createShape=function(t){var e,n=t.object,i=t.getObjectExtendSize();switch(t.type){case Ct.a.SphereImpostor:var o=i.x,a=i.y,s=i.z;e=new this.BJSCANNON.Sphere(Math.max(this._checkWithEpsilon(o),this._checkWithEpsilon(a),this._checkWithEpsilon(s))/2);break;case Ct.a.CylinderImpostor:var d=t.getParam("nativeOptions");d||(d={});var p=d.radiusTop!==void 0?d.radiusTop:this._checkWithEpsilon(i.x)/2,b=d.radiusBottom!==void 0?d.radiusBottom:this._checkWithEpsilon(i.x)/2,P=d.height!==void 0?d.height:this._checkWithEpsilon(i.y),O=d.numSegments!==void 0?d.numSegments:16;e=new this.BJSCANNON.Cylinder(p,b,P,O);var B=new this.BJSCANNON.Quaternion;B.setFromAxisAngle(new this.BJSCANNON.Vec3(1,0,0),-Math.PI/2);var F=new this.BJSCANNON.Vec3(0,0,0);e.transformAllPoints(F,B);break;case Ct.a.BoxImpostor:var z=i.scale(.5);e=new this.BJSCANNON.Box(new this.BJSCANNON.Vec3(this._checkWithEpsilon(z.x),this._checkWithEpsilon(z.y),this._checkWithEpsilon(z.z)));break;case Ct.a.PlaneImpostor:l.a.Warn("Attention, PlaneImposter might not behave as you expect. Consider using BoxImposter instead"),e=new this.BJSCANNON.Plane;break;case Ct.a.MeshImpostor:var J=n.getVerticesData?n.getVerticesData(Oe.b.PositionKind):[],ie=n.getIndices?n.getIndices():[];if(!J)return;var se=n.position.clone(),ce=n.rotation&&n.rotation.clone(),ue=n.rotationQuaternion&&n.rotationQuaternion.clone();n.position.copyFromFloats(0,0,0),n.rotation&&n.rotation.copyFromFloats(0,0,0),n.rotationQuaternion&&n.rotationQuaternion.copyFrom(t.getParentsRotation()),n.rotationQuaternion&&n.parent&&n.rotationQuaternion.conjugateInPlace();var fe,ve=n.computeWorldMatrix(!0),Te=new Array;for(fe=0;fe<J.length;fe+=3)u.e.TransformCoordinates(u.e.FromArray(J,fe),ve).toArray(Te,fe);l.a.Warn("MeshImpostor only collides against spheres."),e=new this.BJSCANNON.Trimesh(Te,ie),n.position.copyFrom(se),ce&&n.rotation&&n.rotation.copyFrom(ce),ue&&n.rotationQuaternion&&n.rotationQuaternion.copyFrom(ue);break;case Ct.a.HeightmapImpostor:var Re=n.position.clone(),Ae=n.rotation&&n.rotation.clone(),Ee=n.rotationQuaternion&&n.rotationQuaternion.clone();n.position.copyFromFloats(0,0,0),n.rotation&&n.rotation.copyFromFloats(0,0,0),n.rotationQuaternion&&n.rotationQuaternion.copyFrom(t.getParentsRotation()),n.rotationQuaternion&&n.parent&&n.rotationQuaternion.conjugateInPlace(),n.rotationQuaternion&&n.rotationQuaternion.multiplyInPlace(this._minus90X),e=this._createHeightmap(n),n.position.copyFrom(Re),Ae&&n.rotation&&n.rotation.copyFrom(Ae),Ee&&n.rotationQuaternion&&n.rotationQuaternion.copyFrom(Ee),n.computeWorldMatrix(!0);break;case Ct.a.ParticleImpostor:e=new this.BJSCANNON.Particle;break;case Ct.a.NoImpostor:e=new this.BJSCANNON.Box(new this.BJSCANNON.Vec3(0,0,0))}return e},r.prototype._createHeightmap=function(t,e){var n,i=t.getVerticesData(Oe.b.PositionKind),o=t.computeWorldMatrix(!0),a=new Array;for(n=0;n<i.length;n+=3)u.e.TransformCoordinates(u.e.FromArray(i,n),o).toArray(a,n);i=a;for(var s=new Array,d=e||~~(Math.sqrt(i.length/3)-1),p=t.getBoundingInfo(),b=Math.min(p.boundingBox.extendSizeWorld.x,p.boundingBox.extendSizeWorld.y),P=p.boundingBox.extendSizeWorld.z,O=2*b/d,B=0;B<i.length;B+=3){var F=Math.round(i[B+0]/O+d/2),z=Math.round(-1*(i[B+1]/O-d/2)),J=-i[B+2]+P;s[F]||(s[F]=[]),s[F][z]||(s[F][z]=J),s[F][z]=Math.max(J,s[F][z])}for(F=0;F<=d;++F){if(!s[F]){for(var ie=1;!s[(F+ie)%d];)ie++;s[F]=s[(F+ie)%d].slice()}for(z=0;z<=d;++z)if(!s[F][z]){var se;for(ie=1;se===void 0;)se=s[F][(z+ie++)%d];s[F][z]=se}}var ce=new this.BJSCANNON.Heightfield(s,{elementSize:O});return ce.minY=P,ce},r.prototype._updatePhysicsBodyTransformation=function(t){var e=t.object;if(e.computeWorldMatrix&&e.computeWorldMatrix(!0),e.getBoundingInfo()){var n=t.getObjectCenter();this._tmpDeltaPosition.copyFrom(e.getAbsolutePivotPoint().subtract(n)),this._tmpDeltaPosition.divideInPlace(t.object.scaling),this._tmpPosition.copyFrom(n);var i=e.rotationQuaternion;if(i){if(t.type!==Ct.a.PlaneImpostor&&t.type!==Ct.a.HeightmapImpostor||(i=i.multiply(this._minus90X),t.setDeltaRotation(this._plus90X)),t.type===Ct.a.HeightmapImpostor){var o=e,a=o.getBoundingInfo(),s=o.rotationQuaternion;o.rotationQuaternion=this._tmpUnityRotation,o.computeWorldMatrix(!0);var d=n.clone(),p=o.getPivotMatrix();p=p?p.clone():u.a.Identity();var b=u.a.Translation(a.boundingBox.extendSizeWorld.x,0,-a.boundingBox.extendSizeWorld.z);o.setPreTransformMatrix(b),o.computeWorldMatrix(!0);var P=a.boundingBox.centerWorld.subtract(n).subtract(o.position).negate();this._tmpPosition.copyFromFloats(P.x,P.y-a.boundingBox.extendSizeWorld.y,P.z),this._tmpDeltaPosition.copyFrom(a.boundingBox.centerWorld.subtract(d)),this._tmpDeltaPosition.y+=a.boundingBox.extendSizeWorld.y,o.rotationQuaternion=s,o.setPreTransformMatrix(p),o.computeWorldMatrix(!0)}else t.type===Ct.a.MeshImpostor&&this._tmpDeltaPosition.copyFromFloats(0,0,0);t.setDeltaPosition(this._tmpDeltaPosition),t.physicsBody.position.set(this._tmpPosition.x,this._tmpPosition.y,this._tmpPosition.z),t.physicsBody.quaternion.set(i.x,i.y,i.z,i.w)}}},r.prototype.setTransformationFromPhysicsBody=function(t){if(t.object.position.set(t.physicsBody.position.x,t.physicsBody.position.y,t.physicsBody.position.z),t.object.rotationQuaternion){var e=t.physicsBody.quaternion;t.object.rotationQuaternion.set(e.x,e.y,e.z,e.w)}},r.prototype.setPhysicsBodyTransformation=function(t,e,n){t.physicsBody.position.set(e.x,e.y,e.z),t.physicsBody.quaternion.set(n.x,n.y,n.z,n.w)},r.prototype.isSupported=function(){return this.BJSCANNON!==void 0},r.prototype.setLinearVelocity=function(t,e){t.physicsBody.velocity.set(e.x,e.y,e.z)},r.prototype.setAngularVelocity=function(t,e){t.physicsBody.angularVelocity.set(e.x,e.y,e.z)},r.prototype.getLinearVelocity=function(t){var e=t.physicsBody.velocity;return e?new u.e(e.x,e.y,e.z):null},r.prototype.getAngularVelocity=function(t){var e=t.physicsBody.angularVelocity;return e?new u.e(e.x,e.y,e.z):null},r.prototype.setBodyMass=function(t,e){t.physicsBody.mass=e,t.physicsBody.updateMassProperties()},r.prototype.getBodyMass=function(t){return t.physicsBody.mass},r.prototype.getBodyFriction=function(t){return t.physicsBody.material.friction},r.prototype.setBodyFriction=function(t,e){t.physicsBody.material.friction=e},r.prototype.getBodyRestitution=function(t){return t.physicsBody.material.restitution},r.prototype.setBodyRestitution=function(t,e){t.physicsBody.material.restitution=e},r.prototype.sleepBody=function(t){t.physicsBody.sleep()},r.prototype.wakeUpBody=function(t){t.physicsBody.wakeUp()},r.prototype.updateDistanceJoint=function(t,e){t.physicsJoint.distance=e},r.prototype.setMotor=function(t,e,n,i){i||(t.physicsJoint.enableMotor(),t.physicsJoint.setMotorSpeed(e),n&&this.setLimit(t,n))},r.prototype.setLimit=function(t,e,n){t.physicsJoint.motorEquation.maxForce=e,t.physicsJoint.motorEquation.minForce=n===void 0?-e:n},r.prototype.syncMeshWithImpostor=function(t,e){var n=e.physicsBody;t.position.x=n.position.x,t.position.y=n.position.y,t.position.z=n.position.z,t.rotationQuaternion&&(t.rotationQuaternion.x=n.quaternion.x,t.rotationQuaternion.y=n.quaternion.y,t.rotationQuaternion.z=n.quaternion.z,t.rotationQuaternion.w=n.quaternion.w)},r.prototype.getRadius=function(t){return t.physicsBody.shapes[0].boundingSphereRadius},r.prototype.getBoxSizeToRef=function(t,e){var n=t.physicsBody.shapes[0];e.x=2*n.halfExtents.x,e.y=2*n.halfExtents.y,e.z=2*n.halfExtents.z},r.prototype.dispose=function(){},r.prototype._extendNamespace=function(){var t=new this.BJSCANNON.Vec3,e=this.BJSCANNON;this.BJSCANNON.World.prototype.step=function(n,i,o){if(o=o||10,(i=i||0)===0)this.internalStep(n),this.time+=n;else{var a=Math.floor((this.time+i)/n)-Math.floor(this.time/n);a=Math.min(a,o)||1;for(var s=performance.now(),d=0;d!==a&&(this.internalStep(n),!(performance.now()-s>1e3*n));d++);this.time+=i;for(var p=this.time%n/n,b=t,P=this.bodies,O=0;O!==P.length;O++){var B=P[O];B.type!==e.Body.STATIC&&B.sleepState!==e.Body.SLEEPING?(B.position.vsub(B.previousPosition,b),b.scale(p,b),B.position.vadd(b,B.interpolatedPosition)):(B.interpolatedPosition.set(B.position.x,B.position.y,B.position.z),B.interpolatedQuaternion.set(B.quaternion.x,B.quaternion.y,B.quaternion.z,B.quaternion.w))}}}},r.prototype.raycast=function(t,e){return this._cannonRaycastResult.reset(),this.world.raycastClosest(t,e,{},this._cannonRaycastResult),this._raycastResult.reset(t,e),this._cannonRaycastResult.hasHit&&(this._raycastResult.setHitData({x:this._cannonRaycastResult.hitNormalWorld.x,y:this._cannonRaycastResult.hitNormalWorld.y,z:this._cannonRaycastResult.hitNormalWorld.z},{x:this._cannonRaycastResult.hitPointWorld.x,y:this._cannonRaycastResult.hitPointWorld.y,z:this._cannonRaycastResult.hitPointWorld.z}),this._raycastResult.setHitDistance(this._cannonRaycastResult.distance)),this._raycastResult},r}();Ir.DefaultPluginFactory=function(){return new Ks};var Yu=function(){function r(t,e,n){t===void 0&&(t=!0),n===void 0&&(n=OIMO),this._useDeltaForWorldStep=t,this.name="OimoJSPlugin",this._fixedTimeStep=1/60,this._tmpImpostorsArray=[],this._tmpPositionVector=u.e.Zero(),this.BJSOIMO=n,this.world=new this.BJSOIMO.World({iterations:e}),this.world.clear(),this._raycastResult=new Ys}return r.prototype.setGravity=function(t){this.world.gravity.set(t.x,t.y,t.z)},r.prototype.setTimeStep=function(t){this.world.timeStep=t},r.prototype.getTimeStep=function(){return this.world.timeStep},r.prototype.executeStep=function(t,e){var n=this;e.forEach(function(s){s.beforeStep()}),this.world.timeStep=this._useDeltaForWorldStep?t:this._fixedTimeStep,this.world.step(),e.forEach(function(s){s.afterStep(),n._tmpImpostorsArray[s.uniqueId]=s});for(var i=this.world.contacts;i!==null;)if(!i.touching||i.body1.sleeping||i.body2.sleeping){var o=this._tmpImpostorsArray[+i.body1.name],a=this._tmpImpostorsArray[+i.body2.name];o&&a&&(o.onCollide({body:a.physicsBody,point:null}),a.onCollide({body:o.physicsBody,point:null})),i=i.next}else i=i.next},r.prototype.applyImpulse=function(t,e,n){var i=t.physicsBody.mass;t.physicsBody.applyImpulse(n.scale(this.world.invScale),e.scale(this.world.invScale*i))},r.prototype.applyForce=function(t,e,n){l.a.Warn("Oimo doesn't support applying force. Using impule instead."),this.applyImpulse(t,e,n)},r.prototype.generatePhysicsBody=function(t){var e=this;if(t.parent)t.physicsBody&&(this.removePhysicsBody(t),t.forceUpdate());else{if(t.isBodyInitRequired()){var n={name:t.uniqueId,config:[t.getParam("mass")||.001,t.getParam("friction"),t.getParam("restitution")],size:[],type:[],pos:[],posShape:[],rot:[],rotShape:[],move:t.getParam("mass")!==0,density:t.getParam("mass"),friction:t.getParam("friction"),restitution:t.getParam("restitution"),world:this.world},i=[t];(s=t.object).getChildMeshes&&s.getChildMeshes().forEach(function(d){d.physicsImpostor&&i.push(d.physicsImpostor)});var o=function(d){return Math.max(d,Ir.Epsilon)},a=new u.b;i.forEach(function(d){if(d.object.rotationQuaternion){var p=d.object.rotationQuaternion;a.copyFrom(p),d.object.rotationQuaternion.set(0,0,0,1),d.object.computeWorldMatrix(!0);var b=a.toEulerAngles(),P=d.getObjectExtendSize();if(d===t){var O=t.getObjectCenter();t.object.getAbsolutePivotPoint().subtractToRef(O,e._tmpPositionVector),e._tmpPositionVector.divideInPlace(t.object.scaling),n.pos.push(O.x),n.pos.push(O.y),n.pos.push(O.z),n.posShape.push(0,0,0),n.rotShape.push(0,0,0)}else{var B=d.object.position.clone();n.posShape.push(B.x),n.posShape.push(B.y),n.posShape.push(B.z),n.rotShape.push(57.29577951308232*b.x,57.29577951308232*b.y,57.29577951308232*b.z)}switch(d.object.rotationQuaternion.copyFrom(a),d.type){case Ct.a.ParticleImpostor:l.a.Warn("No Particle support in OIMO.js. using SphereImpostor instead");case Ct.a.SphereImpostor:var F=P.x,z=P.y,J=P.z,ie=Math.max(o(F),o(z),o(J))/2;n.type.push("sphere"),n.size.push(ie),n.size.push(ie),n.size.push(ie);break;case Ct.a.CylinderImpostor:var se=o(P.x)/2,ce=o(P.y);n.type.push("cylinder"),n.size.push(se),n.size.push(ce),n.size.push(ce);break;case Ct.a.PlaneImpostor:case Ct.a.BoxImpostor:default:se=o(P.x),ce=o(P.y);var ue=o(P.z);n.type.push("box"),n.size.push(se),n.size.push(ce),n.size.push(ue)}d.object.rotationQuaternion=p}}),t.physicsBody=this.world.add(n),t.physicsBody.resetQuaternion(a),t.physicsBody.updatePosition(0)}else this._tmpPositionVector.copyFromFloats(0,0,0);var s;t.setDeltaPosition(this._tmpPositionVector)}},r.prototype.removePhysicsBody=function(t){this.world.removeRigidBody(t.physicsBody)},r.prototype.generateJoint=function(t){var e=t.mainImpostor.physicsBody,n=t.connectedImpostor.physicsBody;if(e&&n){var i,o=t.joint.jointData,a=o.nativeParams||{},s={body1:e,body2:n,axe1:a.axe1||(o.mainAxis?o.mainAxis.asArray():null),axe2:a.axe2||(o.connectedAxis?o.connectedAxis.asArray():null),pos1:a.pos1||(o.mainPivot?o.mainPivot.asArray():null),pos2:a.pos2||(o.connectedPivot?o.connectedPivot.asArray():null),min:a.min,max:a.max,collision:a.collision||o.collision,spring:a.spring,world:this.world};switch(t.joint.type){case en.e.BallAndSocketJoint:i="jointBall";break;case en.e.SpringJoint:l.a.Warn("OIMO.js doesn't support Spring Constraint. Simulating using DistanceJoint instead");var d=o;s.min=d.length||s.min,s.max=Math.max(s.min,s.max);case en.e.DistanceJoint:i="jointDistance",s.max=o.maxDistance;break;case en.e.PrismaticJoint:i="jointPrisme";break;case en.e.SliderJoint:i="jointSlide";break;case en.e.WheelJoint:i="jointWheel";break;case en.e.HingeJoint:default:i="jointHinge"}s.type=i,t.joint.physicsJoint=this.world.add(s)}},r.prototype.removeJoint=function(t){try{this.world.removeJoint(t.joint.physicsJoint)}catch(e){l.a.Warn(e)}},r.prototype.isSupported=function(){return this.BJSOIMO!==void 0},r.prototype.setTransformationFromPhysicsBody=function(t){if(!t.physicsBody.sleeping){if(t.physicsBody.shapes.next){for(var e=t.physicsBody.shapes;e.next;)e=e.next;t.object.position.set(e.position.x,e.position.y,e.position.z)}else{var n=t.physicsBody.getPosition();t.object.position.set(n.x,n.y,n.z)}if(t.object.rotationQuaternion){var i=t.physicsBody.getQuaternion();t.object.rotationQuaternion.set(i.x,i.y,i.z,i.w)}}},r.prototype.setPhysicsBodyTransformation=function(t,e,n){var i=t.physicsBody;t.physicsBody.shapes.next||(i.position.set(e.x,e.y,e.z),i.orientation.set(n.x,n.y,n.z,n.w),i.syncShapes(),i.awake())},r.prototype.setLinearVelocity=function(t,e){t.physicsBody.linearVelocity.set(e.x,e.y,e.z)},r.prototype.setAngularVelocity=function(t,e){t.physicsBody.angularVelocity.set(e.x,e.y,e.z)},r.prototype.getLinearVelocity=function(t){var e=t.physicsBody.linearVelocity;return e?new u.e(e.x,e.y,e.z):null},r.prototype.getAngularVelocity=function(t){var e=t.physicsBody.angularVelocity;return e?new u.e(e.x,e.y,e.z):null},r.prototype.setBodyMass=function(t,e){var n=e===0;t.physicsBody.shapes.density=n?1:e,t.physicsBody.setupMass(n?2:1)},r.prototype.getBodyMass=function(t){return t.physicsBody.shapes.density},r.prototype.getBodyFriction=function(t){return t.physicsBody.shapes.friction},r.prototype.setBodyFriction=function(t,e){t.physicsBody.shapes.friction=e},r.prototype.getBodyRestitution=function(t){return t.physicsBody.shapes.restitution},r.prototype.setBodyRestitution=function(t,e){t.physicsBody.shapes.restitution=e},r.prototype.sleepBody=function(t){t.physicsBody.sleep()},r.prototype.wakeUpBody=function(t){t.physicsBody.awake()},r.prototype.updateDistanceJoint=function(t,e,n){t.physicsJoint.limitMotor.upperLimit=e,n!==void 0&&(t.physicsJoint.limitMotor.lowerLimit=n)},r.prototype.setMotor=function(t,e,n,i){n!==void 0?l.a.Warn("OimoJS plugin currently has unexpected behavior when using setMotor with force parameter"):n=1e6,e*=-1;var o=i?t.physicsJoint.rotationalLimitMotor2:t.physicsJoint.rotationalLimitMotor1||t.physicsJoint.rotationalLimitMotor||t.physicsJoint.limitMotor;o&&o.setMotor(e,n)},r.prototype.setLimit=function(t,e,n,i){var o=i?t.physicsJoint.rotationalLimitMotor2:t.physicsJoint.rotationalLimitMotor1||t.physicsJoint.rotationalLimitMotor||t.physicsJoint.limitMotor;o&&o.setLimit(e,n===void 0?-e:n)},r.prototype.syncMeshWithImpostor=function(t,e){var n=e.physicsBody;t.position.x=n.position.x,t.position.y=n.position.y,t.position.z=n.position.z,t.rotationQuaternion&&(t.rotationQuaternion.x=n.orientation.x,t.rotationQuaternion.y=n.orientation.y,t.rotationQuaternion.z=n.orientation.z,t.rotationQuaternion.w=n.orientation.s)},r.prototype.getRadius=function(t){return t.physicsBody.shapes.radius},r.prototype.getBoxSizeToRef=function(t,e){var n=t.physicsBody.shapes;e.x=2*n.halfWidth,e.y=2*n.halfHeight,e.z=2*n.halfDepth},r.prototype.dispose=function(){this.world.clear()},r.prototype.raycast=function(t,e){return l.a.Warn("raycast is not currently supported by the Oimo physics plugin"),this._raycastResult.reset(t,e),this._raycastResult},r}(),ca=f(97),Ku=function(){function r(t,e,n){var i=this;t===void 0&&(t=!0),e===void 0&&(e=Ammo),n===void 0&&(n=null),this._useDeltaForWorldStep=t,this.bjsAMMO={},this.name="AmmoJSPlugin",this._timeStep=1/60,this._fixedTimeStep=1/60,this._maxSteps=5,this._tmpQuaternion=new u.b,this._tmpContactCallbackResult=!1,this._tmpContactPoint=new u.e,this._tmpMatrix=new u.a,typeof e=="function"?e(this.bjsAMMO):this.bjsAMMO=e,this.isSupported()?(this._collisionConfiguration=new this.bjsAMMO.btSoftBodyRigidBodyCollisionConfiguration,this._dispatcher=new this.bjsAMMO.btCollisionDispatcher(this._collisionConfiguration),this._overlappingPairCache=n||new this.bjsAMMO.btDbvtBroadphase,this._solver=new this.bjsAMMO.btSequentialImpulseConstraintSolver,this._softBodySolver=new this.bjsAMMO.btDefaultSoftBodySolver,this.world=new this.bjsAMMO.btSoftRigidDynamicsWorld(this._dispatcher,this._overlappingPairCache,this._solver,this._collisionConfiguration,this._softBodySolver),this._tmpAmmoConcreteContactResultCallback=new this.bjsAMMO.ConcreteContactResultCallback,this._tmpAmmoConcreteContactResultCallback.addSingleResult=function(o,a,s,d){var p=(o=i.bjsAMMO.wrapPointer(o,Ammo.btManifoldPoint)).getPositionWorldOnA();i._tmpContactPoint.x=p.x(),i._tmpContactPoint.y=p.y(),i._tmpContactPoint.z=p.z(),i._tmpContactCallbackResult=!0},this._raycastResult=new Ys,this._tmpAmmoTransform=new this.bjsAMMO.btTransform,this._tmpAmmoTransform.setIdentity(),this._tmpAmmoQuaternion=new this.bjsAMMO.btQuaternion(0,0,0,1),this._tmpAmmoVectorA=new this.bjsAMMO.btVector3(0,0,0),this._tmpAmmoVectorB=new this.bjsAMMO.btVector3(0,0,0),this._tmpAmmoVectorC=new this.bjsAMMO.btVector3(0,0,0),this._tmpAmmoVectorD=new this.bjsAMMO.btVector3(0,0,0)):l.a.Error("AmmoJS is not available. Please make sure you included the js file.")}return r.prototype.setGravity=function(t){this._tmpAmmoVectorA.setValue(t.x,t.y,t.z),this.world.setGravity(this._tmpAmmoVectorA),this.world.getWorldInfo().set_m_gravity(this._tmpAmmoVectorA)},r.prototype.setTimeStep=function(t){this._timeStep=t},r.prototype.setFixedTimeStep=function(t){this._fixedTimeStep=t},r.prototype.setMaxSteps=function(t){this._maxSteps=t},r.prototype.getTimeStep=function(){return this._timeStep},r.prototype._isImpostorInContact=function(t){return this._tmpContactCallbackResult=!1,this.world.contactTest(t.physicsBody,this._tmpAmmoConcreteContactResultCallback),this._tmpContactCallbackResult},r.prototype._isImpostorPairInContact=function(t,e){return this._tmpContactCallbackResult=!1,this.world.contactPairTest(t.physicsBody,e.physicsBody,this._tmpAmmoConcreteContactResultCallback),this._tmpContactCallbackResult},r.prototype._stepSimulation=function(t,e,n){if(t===void 0&&(t=1/60),e===void 0&&(e=10),n===void 0&&(n=1/60),e==0)this.world.stepSimulation(t,0);else for(;e>0&&t>0;)t-n<n?(this.world.stepSimulation(t,0),t=0):(t-=n,this.world.stepSimulation(n,0)),e--},r.prototype.executeStep=function(t,e){for(var n=0,i=e;n<i.length;n++){var o=i[n];o.soft||o.beforeStep()}this._stepSimulation(this._useDeltaForWorldStep?t:this._timeStep,this._maxSteps,this._fixedTimeStep);for(var a=0,s=e;a<s.length;a++){var d=s[a];if(d.soft?this._afterSoftStep(d):d.afterStep(),d._onPhysicsCollideCallbacks.length>0&&this._isImpostorInContact(d))for(var p=0,b=d._onPhysicsCollideCallbacks;p<b.length;p++)for(var P=0,O=b[p].otherImpostors;P<O.length;P++){var B=O[P];(d.physicsBody.isActive()||B.physicsBody.isActive())&&this._isImpostorPairInContact(d,B)&&(d.onCollide({body:B.physicsBody,point:this._tmpContactPoint}),B.onCollide({body:d.physicsBody,point:this._tmpContactPoint}))}}},r.prototype._afterSoftStep=function(t){t.type===Ct.a.RopeImpostor?this._ropeStep(t):this._softbodyOrClothStep(t)},r.prototype._ropeStep=function(t){for(var e,n,i,o,a=t.physicsBody.get_m_nodes(),s=a.size(),d=new Array,p=0;p<s;p++)n=(e=a.at(p).get_m_x()).x(),i=e.y(),o=e.z(),d.push(new u.e(n,i,o));var b=t.object,P=t.getParam("shape");t._isFromLine?t.object=cn.a.CreateLines("lines",{points:d,instance:b}):t.object=ca.a.ExtrudeShape("ext",{shape:P,path:d,instance:b})},r.prototype._softbodyOrClothStep=function(t){var e=t.type===Ct.a.ClothImpostor?1:-1,n=t.object,i=n.getVerticesData(Oe.b.PositionKind);i||(i=[]);var o=n.getVerticesData(Oe.b.NormalKind);o||(o=[]);for(var a,s,d,p,b,P,O,B,F=i.length/3,z=t.physicsBody.get_m_nodes(),J=0;J<F;J++){var ie;d=(s=(a=z.at(J)).get_m_x()).x(),p=s.y(),b=s.z()*e,P=(ie=a.get_m_n()).x(),O=ie.y(),B=ie.z()*e,i[3*J]=d,i[3*J+1]=p,i[3*J+2]=b,o[3*J]=P,o[3*J+1]=O,o[3*J+2]=B}var se=new ft.a;se.positions=i,se.normals=o,se.uvs=n.getVerticesData(Oe.b.UVKind),se.colors=n.getVerticesData(Oe.b.ColorKind),n&&n.getIndices&&(se.indices=n.getIndices()),se.applyToMesh(n)},r.prototype.applyImpulse=function(t,e,n){if(t.soft)l.a.Warn("Cannot be applied to a soft body");else{t.physicsBody.activate();var i=this._tmpAmmoVectorA,o=this._tmpAmmoVectorB;t.object&&t.object.getWorldMatrix&&n.subtractInPlace(t.object.getWorldMatrix().getTranslation()),i.setValue(n.x,n.y,n.z),o.setValue(e.x,e.y,e.z),t.physicsBody.applyImpulse(o,i)}},r.prototype.applyForce=function(t,e,n){if(t.soft)l.a.Warn("Cannot be applied to a soft body");else{t.physicsBody.activate();var i=this._tmpAmmoVectorA,o=this._tmpAmmoVectorB;t.object&&t.object.getWorldMatrix&&n.subtractInPlace(t.object.getWorldMatrix().getTranslation()),i.setValue(n.x,n.y,n.z),o.setValue(e.x,e.y,e.z),t.physicsBody.applyForce(o,i)}},r.prototype.generatePhysicsBody=function(t){if(t._pluginData.toDispose=[],t.parent)t.physicsBody&&(this.removePhysicsBody(t),t.forceUpdate());else if(t.isBodyInitRequired()){var e=this._createShape(t),n=t.getParam("mass");if(t._pluginData.mass=n,t.soft)e.get_m_cfg().set_collisions(17),e.get_m_cfg().set_kDP(t.getParam("damping")),this.bjsAMMO.castObject(e,this.bjsAMMO.btCollisionObject).getCollisionShape().setMargin(t.getParam("margin")),e.setActivationState(r.DISABLE_DEACTIVATION_FLAG),this.world.addSoftBody(e,1,-1),t.physicsBody=e,t._pluginData.toDispose.push(e),this.setBodyPressure(t,0),t.type===Ct.a.SoftbodyImpostor&&this.setBodyPressure(t,t.getParam("pressure")),this.setBodyStiffness(t,t.getParam("stiffness")),this.setBodyVelocityIterations(t,t.getParam("velocityIterations")),this.setBodyPositionIterations(t,t.getParam("positionIterations"));else{var i=new this.bjsAMMO.btVector3(0,0,0),o=new this.bjsAMMO.btTransform;o.setIdentity(),n!==0&&e.calculateLocalInertia(n,i),this._tmpAmmoVectorA.setValue(t.object.position.x,t.object.position.y,t.object.position.z),this._tmpAmmoQuaternion.setValue(t.object.rotationQuaternion.x,t.object.rotationQuaternion.y,t.object.rotationQuaternion.z,t.object.rotationQuaternion.w),o.setOrigin(this._tmpAmmoVectorA),o.setRotation(this._tmpAmmoQuaternion);var a=new this.bjsAMMO.btDefaultMotionState(o),s=new this.bjsAMMO.btRigidBodyConstructionInfo(n,a,e,i),d=new this.bjsAMMO.btRigidBody(s);n===0&&(d.setCollisionFlags(d.getCollisionFlags()|r.KINEMATIC_FLAG),d.setActivationState(r.DISABLE_DEACTIVATION_FLAG)),t.type!=Ct.a.NoImpostor||e.getChildShape||d.setCollisionFlags(d.getCollisionFlags()|r.DISABLE_COLLISION_FLAG);var p=t.getParam("group"),b=t.getParam("mask");p&&b?this.world.addRigidBody(d,p,b):this.world.addRigidBody(d),t.physicsBody=d,t._pluginData.toDispose=t._pluginData.toDispose.concat([d,s,a,o,i,e])}this.setBodyRestitution(t,t.getParam("restitution")),this.setBodyFriction(t,t.getParam("friction"))}},r.prototype.removePhysicsBody=function(t){var e=this;this.world&&(t.soft?this.world.removeSoftBody(t.physicsBody):this.world.removeRigidBody(t.physicsBody),t._pluginData&&(t._pluginData.toDispose.forEach(function(n){e.bjsAMMO.destroy(n)}),t._pluginData.toDispose=[]))},r.prototype.generateJoint=function(t){var e=t.mainImpostor.physicsBody,n=t.connectedImpostor.physicsBody;if(e&&n){var i,o=t.joint.jointData;switch(o.mainPivot||(o.mainPivot=new u.e(0,0,0)),o.connectedPivot||(o.connectedPivot=new u.e(0,0,0)),t.joint.type){case en.e.DistanceJoint:var a=o.maxDistance;a&&(o.mainPivot=new u.e(0,-a/2,0),o.connectedPivot=new u.e(0,a/2,0)),i=new this.bjsAMMO.btPoint2PointConstraint(e,n,new this.bjsAMMO.btVector3(o.mainPivot.x,o.mainPivot.y,o.mainPivot.z),new this.bjsAMMO.btVector3(o.connectedPivot.x,o.connectedPivot.y,o.connectedPivot.z));break;case en.e.HingeJoint:o.mainAxis||(o.mainAxis=new u.e(0,0,0)),o.connectedAxis||(o.connectedAxis=new u.e(0,0,0));var s=new this.bjsAMMO.btVector3(o.mainAxis.x,o.mainAxis.y,o.mainAxis.z),d=new this.bjsAMMO.btVector3(o.connectedAxis.x,o.connectedAxis.y,o.connectedAxis.z);i=new this.bjsAMMO.btHingeConstraint(e,n,new this.bjsAMMO.btVector3(o.mainPivot.x,o.mainPivot.y,o.mainPivot.z),new this.bjsAMMO.btVector3(o.connectedPivot.x,o.connectedPivot.y,o.connectedPivot.z),s,d);break;case en.e.BallAndSocketJoint:i=new this.bjsAMMO.btPoint2PointConstraint(e,n,new this.bjsAMMO.btVector3(o.mainPivot.x,o.mainPivot.y,o.mainPivot.z),new this.bjsAMMO.btVector3(o.connectedPivot.x,o.connectedPivot.y,o.connectedPivot.z));break;default:l.a.Warn("JointType not currently supported by the Ammo plugin, falling back to PhysicsJoint.BallAndSocketJoint"),i=new this.bjsAMMO.btPoint2PointConstraint(e,n,new this.bjsAMMO.btVector3(o.mainPivot.x,o.mainPivot.y,o.mainPivot.z),new this.bjsAMMO.btVector3(o.connectedPivot.x,o.connectedPivot.y,o.connectedPivot.z))}this.world.addConstraint(i,!t.joint.jointData.collision),t.joint.physicsJoint=i}},r.prototype.removeJoint=function(t){this.world&&this.world.removeConstraint(t.joint.physicsJoint)},r.prototype._addMeshVerts=function(t,e,n){var i=this,o=0;if(n&&n.getIndices&&n.getWorldMatrix&&n.getChildMeshes){var a=n.getIndices();a||(a=[]);var s=n.getVerticesData(Oe.b.PositionKind);s||(s=[]),n.computeWorldMatrix(!1);for(var d=a.length/3,p=0;p<d;p++){for(var b=[],P=0;P<3;P++){var O,B=new u.e(s[3*a[3*p+P]+0],s[3*a[3*p+P]+1],s[3*a[3*p+P]+2]);u.a.ScalingToRef(n.scaling.x,n.scaling.y,n.scaling.z,this._tmpMatrix),B=u.e.TransformCoordinates(B,this._tmpMatrix),(O=P==0?this._tmpAmmoVectorA:P==1?this._tmpAmmoVectorB:this._tmpAmmoVectorC).setValue(B.x,B.y,B.z),b.push(O)}t.addTriangle(b[0],b[1],b[2]),o++}n.getChildMeshes().forEach(function(F){o+=i._addMeshVerts(t,e,F)})}return o},r.prototype._softVertexData=function(t){var e=t.object;if(e&&e.getIndices&&e.getWorldMatrix&&e.getChildMeshes){e.getIndices();var n=e.getVerticesData(Oe.b.PositionKind);n||(n=[]);var i=e.getVerticesData(Oe.b.NormalKind);i||(i=[]),e.computeWorldMatrix(!1);for(var o=[],a=[],s=0;s<n.length;s+=3){var d=new u.e(n[s],n[s+1],n[s+2]),p=new u.e(i[s],i[s+1],i[s+2]);d=u.e.TransformCoordinates(d,e.getWorldMatrix()),p=u.e.TransformNormal(p,e.getWorldMatrix()),o.push(d.x,d.y,d.z),a.push(p.x,p.y,p.z)}var b=new ft.a;return b.positions=o,b.normals=a,b.uvs=e.getVerticesData(Oe.b.UVKind),b.colors=e.getVerticesData(Oe.b.ColorKind),e&&e.getIndices&&(b.indices=e.getIndices()),b.applyToMesh(e),e.position=u.e.Zero(),e.rotationQuaternion=null,e.rotation=u.e.Zero(),e.computeWorldMatrix(!0),b}return ft.a.ExtractFromMesh(e)},r.prototype._createSoftbody=function(t){var e=t.object;if(e&&e.getIndices){var n=e.getIndices();n||(n=[]);var i=this._softVertexData(t),o=i.positions,a=i.normals;if(o===null||a===null)return new this.bjsAMMO.btCompoundShape;for(var s=[],d=[],p=0;p<o.length;p+=3){var b=new u.e(o[p],o[p+1],o[p+2]),P=new u.e(a[p],a[p+1],a[p+2]);s.push(b.x,b.y,-b.z),d.push(P.x,P.y,-P.z)}var O=new this.bjsAMMO.btSoftBodyHelpers().CreateFromTriMesh(this.world.getWorldInfo(),s,e.getIndices(),n.length/3,!0),B=o.length/3,F=O.get_m_nodes();for(p=0;p<B;p++){var z;(z=F.at(p).get_m_n()).setX(d[3*p]),z.setY(d[3*p+1]),z.setZ(d[3*p+2])}return O}},r.prototype._createCloth=function(t){var e=t.object;if(e&&e.getIndices){e.getIndices();var n=this._softVertexData(t),i=n.positions,o=n.normals;if(i===null||o===null)return new this.bjsAMMO.btCompoundShape;var a=i.length,s=Math.sqrt(a/3);t.segments=s;var d=s-1;return this._tmpAmmoVectorA.setValue(i[0],i[1],i[2]),this._tmpAmmoVectorB.setValue(i[3*d],i[3*d+1],i[3*d+2]),this._tmpAmmoVectorD.setValue(i[a-3],i[a-2],i[a-1]),this._tmpAmmoVectorC.setValue(i[a-3-3*d],i[a-2-3*d],i[a-1-3*d]),new this.bjsAMMO.btSoftBodyHelpers().CreatePatch(this.world.getWorldInfo(),this._tmpAmmoVectorA,this._tmpAmmoVectorB,this._tmpAmmoVectorC,this._tmpAmmoVectorD,s,s,t.getParam("fixedPoints"),!0)}},r.prototype._createRope=function(t){var e,n,i=this._softVertexData(t),o=i.positions,a=i.normals;if(o===null||a===null)return new this.bjsAMMO.btCompoundShape;if(i.applyToMesh(t.object,!0),t._isFromLine=!0,a.map(function(b){return b*b}).reduce(function(b,P){return b+P})===0)n=(e=o.length)/3-1,this._tmpAmmoVectorA.setValue(o[0],o[1],o[2]),this._tmpAmmoVectorB.setValue(o[e-3],o[e-2],o[e-1]);else{t._isFromLine=!1;var s=t.getParam("path");if(t.getParam("shape")===null)return l.a.Warn("No shape available for extruded mesh"),new this.bjsAMMO.btCompoundShape;if(o.length%(3*s.length)!=0)return l.a.Warn("Path does not match extrusion"),new this.bjsAMMO.btCompoundShape;n=(e=s.length)-1,this._tmpAmmoVectorA.setValue(s[0].x,s[0].y,s[0].z),this._tmpAmmoVectorB.setValue(s[e-1].x,s[e-1].y,s[e-1].z)}t.segments=n;var d=t.getParam("fixedPoints");d=d>3?3:d;var p=new this.bjsAMMO.btSoftBodyHelpers().CreateRope(this.world.getWorldInfo(),this._tmpAmmoVectorA,this._tmpAmmoVectorB,n-1,d);return p.get_m_cfg().set_collisions(17),p},r.prototype._createCustom=function(t){var e=null;return this.onCreateCustomShape&&(e=this.onCreateCustomShape(t)),e==null&&(e=new this.bjsAMMO.btCompoundShape),e},r.prototype._addHullVerts=function(t,e,n){var i=this,o=0;if(n&&n.getIndices&&n.getWorldMatrix&&n.getChildMeshes){var a=n.getIndices();a||(a=[]);var s=n.getVerticesData(Oe.b.PositionKind);s||(s=[]),n.computeWorldMatrix(!1);for(var d=a.length/3,p=0;p<d;p++){for(var b=[],P=0;P<3;P++){var O,B=new u.e(s[3*a[3*p+P]+0],s[3*a[3*p+P]+1],s[3*a[3*p+P]+2]);u.a.ScalingToRef(n.scaling.x,n.scaling.y,n.scaling.z,this._tmpMatrix),B=u.e.TransformCoordinates(B,this._tmpMatrix),(O=P==0?this._tmpAmmoVectorA:P==1?this._tmpAmmoVectorB:this._tmpAmmoVectorC).setValue(B.x,B.y,B.z),b.push(O)}t.addPoint(b[0],!0),t.addPoint(b[1],!0),t.addPoint(b[2],!0),o++}n.getChildMeshes().forEach(function(F){o+=i._addHullVerts(t,e,F)})}return o},r.prototype._createShape=function(t,e){var n=this;e===void 0&&(e=!1);var i,o=t.object,a=t.getObjectExtendSize();if(!e){var s=t.object.getChildMeshes?t.object.getChildMeshes(!0):[];i=new this.bjsAMMO.btCompoundShape;var d=0;if(s.forEach(function(F){var z=F.getPhysicsImpostor();if(z){if(z.type==Ct.a.MeshImpostor)throw"A child MeshImpostor is not supported. Only primitive impostors are supported as children (eg. box or sphere)";var J=n._createShape(z),ie=F.parent.getWorldMatrix().clone(),se=new u.e;ie.decompose(se),n._tmpAmmoTransform.getOrigin().setValue(F.position.x*se.x,F.position.y*se.y,F.position.z*se.z),n._tmpAmmoQuaternion.setValue(F.rotationQuaternion.x,F.rotationQuaternion.y,F.rotationQuaternion.z,F.rotationQuaternion.w),n._tmpAmmoTransform.setRotation(n._tmpAmmoQuaternion),i.addChildShape(n._tmpAmmoTransform,J),z.dispose(),d++}}),d>0){if(t.type!=Ct.a.NoImpostor){var p=this._createShape(t,!0);p&&(this._tmpAmmoTransform.getOrigin().setValue(0,0,0),this._tmpAmmoQuaternion.setValue(0,0,0,1),this._tmpAmmoTransform.setRotation(this._tmpAmmoQuaternion),i.addChildShape(this._tmpAmmoTransform,p))}return i}this.bjsAMMO.destroy(i),i=null}switch(t.type){case Ct.a.SphereImpostor:if($.a.WithinEpsilon(a.x,a.y,1e-4)&&$.a.WithinEpsilon(a.x,a.z,1e-4))i=new this.bjsAMMO.btSphereShape(a.x/2);else{var b=[new this.bjsAMMO.btVector3(0,0,0)];(i=new this.bjsAMMO.btMultiSphereShape(b,[1],1)).setLocalScaling(new this.bjsAMMO.btVector3(a.x/2,a.y/2,a.z/2))}break;case Ct.a.CapsuleImpostor:i=new this.bjsAMMO.btCapsuleShape(a.x/2,a.y/2);break;case Ct.a.CylinderImpostor:this._tmpAmmoVectorA.setValue(a.x/2,a.y/2,a.z/2),i=new this.bjsAMMO.btCylinderShape(this._tmpAmmoVectorA);break;case Ct.a.PlaneImpostor:case Ct.a.BoxImpostor:this._tmpAmmoVectorA.setValue(a.x/2,a.y/2,a.z/2),i=new this.bjsAMMO.btBoxShape(this._tmpAmmoVectorA);break;case Ct.a.MeshImpostor:if(t.getParam("mass")==0){var P=new this.bjsAMMO.btTriangleMesh;t._pluginData.toDispose.push(P);var O=this._addMeshVerts(P,o,o);i=O==0?new this.bjsAMMO.btCompoundShape:new this.bjsAMMO.btBvhTriangleMeshShape(P);break}case Ct.a.ConvexHullImpostor:var B=new this.bjsAMMO.btConvexHullShape;(O=this._addHullVerts(B,o,o))==0?(t._pluginData.toDispose.push(B),i=new this.bjsAMMO.btCompoundShape):i=B;break;case Ct.a.NoImpostor:i=new this.bjsAMMO.btSphereShape(a.x/2);break;case Ct.a.CustomImpostor:i=this._createCustom(t);break;case Ct.a.SoftbodyImpostor:i=this._createSoftbody(t);break;case Ct.a.ClothImpostor:i=this._createCloth(t);break;case Ct.a.RopeImpostor:i=this._createRope(t);break;default:l.a.Warn("The impostor type is not currently supported by the ammo plugin.")}return i},r.prototype.setTransformationFromPhysicsBody=function(t){t.physicsBody.getMotionState().getWorldTransform(this._tmpAmmoTransform),t.object.position.set(this._tmpAmmoTransform.getOrigin().x(),this._tmpAmmoTransform.getOrigin().y(),this._tmpAmmoTransform.getOrigin().z()),t.object.rotationQuaternion?t.object.rotationQuaternion.set(this._tmpAmmoTransform.getRotation().x(),this._tmpAmmoTransform.getRotation().y(),this._tmpAmmoTransform.getRotation().z(),this._tmpAmmoTransform.getRotation().w()):t.object.rotation&&(this._tmpQuaternion.set(this._tmpAmmoTransform.getRotation().x(),this._tmpAmmoTransform.getRotation().y(),this._tmpAmmoTransform.getRotation().z(),this._tmpAmmoTransform.getRotation().w()),this._tmpQuaternion.toEulerAnglesToRef(t.object.rotation))},r.prototype.setPhysicsBodyTransformation=function(t,e,n){var i=t.physicsBody.getWorldTransform();if(Math.abs(i.getOrigin().x()-e.x)>Gt.a||Math.abs(i.getOrigin().y()-e.y)>Gt.a||Math.abs(i.getOrigin().z()-e.z)>Gt.a||Math.abs(i.getRotation().x()-n.x)>Gt.a||Math.abs(i.getRotation().y()-n.y)>Gt.a||Math.abs(i.getRotation().z()-n.z)>Gt.a||Math.abs(i.getRotation().w()-n.w)>Gt.a)if(this._tmpAmmoVectorA.setValue(e.x,e.y,e.z),i.setOrigin(this._tmpAmmoVectorA),this._tmpAmmoQuaternion.setValue(n.x,n.y,n.z,n.w),i.setRotation(this._tmpAmmoQuaternion),t.physicsBody.setWorldTransform(i),t.mass==0){var o=t.physicsBody.getMotionState();o&&o.setWorldTransform(i)}else t.physicsBody.activate()},r.prototype.isSupported=function(){return this.bjsAMMO!==void 0},r.prototype.setLinearVelocity=function(t,e){this._tmpAmmoVectorA.setValue(e.x,e.y,e.z),t.soft?t.physicsBody.linearVelocity(this._tmpAmmoVectorA):t.physicsBody.setLinearVelocity(this._tmpAmmoVectorA)},r.prototype.setAngularVelocity=function(t,e){this._tmpAmmoVectorA.setValue(e.x,e.y,e.z),t.soft?t.physicsBody.angularVelocity(this._tmpAmmoVectorA):t.physicsBody.setAngularVelocity(this._tmpAmmoVectorA)},r.prototype.getLinearVelocity=function(t){if(t.soft)var e=t.physicsBody.linearVelocity();else e=t.physicsBody.getLinearVelocity();if(!e)return null;var n=new u.e(e.x(),e.y(),e.z());return this.bjsAMMO.destroy(e),n},r.prototype.getAngularVelocity=function(t){if(t.soft)var e=t.physicsBody.angularVelocity();else e=t.physicsBody.getAngularVelocity();if(!e)return null;var n=new u.e(e.x(),e.y(),e.z());return this.bjsAMMO.destroy(e),n},r.prototype.setBodyMass=function(t,e){t.soft?t.physicsBody.setTotalMass(e,!1):t.physicsBody.setMassProps(e),t._pluginData.mass=e},r.prototype.getBodyMass=function(t){return t._pluginData.mass||0},r.prototype.getBodyFriction=function(t){return t._pluginData.friction||0},r.prototype.setBodyFriction=function(t,e){t.soft?t.physicsBody.get_m_cfg().set_kDF(e):t.physicsBody.setFriction(e),t._pluginData.friction=e},r.prototype.getBodyRestitution=function(t){return t._pluginData.restitution||0},r.prototype.setBodyRestitution=function(t,e){t.physicsBody.setRestitution(e),t._pluginData.restitution=e},r.prototype.getBodyPressure=function(t){return t.soft?t._pluginData.pressure||0:(l.a.Warn("Pressure is not a property of a rigid body"),0)},r.prototype.setBodyPressure=function(t,e){t.soft?t.type===Ct.a.SoftbodyImpostor?(t.physicsBody.get_m_cfg().set_kPR(e),t._pluginData.pressure=e):(t.physicsBody.get_m_cfg().set_kPR(0),t._pluginData.pressure=0):l.a.Warn("Pressure can only be applied to a softbody")},r.prototype.getBodyStiffness=function(t){return t.soft?t._pluginData.stiffness||0:(l.a.Warn("Stiffness is not a property of a rigid body"),0)},r.prototype.setBodyStiffness=function(t,e){t.soft?(e=(e=e<0?0:e)>1?1:e,t.physicsBody.get_m_materials().at(0).set_m_kLST(e),t._pluginData.stiffness=e):l.a.Warn("Stiffness cannot be applied to a rigid body")},r.prototype.getBodyVelocityIterations=function(t){return t.soft?t._pluginData.velocityIterations||0:(l.a.Warn("Velocity iterations is not a property of a rigid body"),0)},r.prototype.setBodyVelocityIterations=function(t,e){t.soft?(e=e<0?0:e,t.physicsBody.get_m_cfg().set_viterations(e),t._pluginData.velocityIterations=e):l.a.Warn("Velocity iterations cannot be applied to a rigid body")},r.prototype.getBodyPositionIterations=function(t){return t.soft?t._pluginData.positionIterations||0:(l.a.Warn("Position iterations is not a property of a rigid body"),0)},r.prototype.setBodyPositionIterations=function(t,e){t.soft?(e=e<0?0:e,t.physicsBody.get_m_cfg().set_piterations(e),t._pluginData.positionIterations=e):l.a.Warn("Position iterations cannot be applied to a rigid body")},r.prototype.appendAnchor=function(t,e,n,i,o,a){o===void 0&&(o=1),a===void 0&&(a=!1);var s=t.segments,d=Math.round((s-1)*n)+s*(s-1-Math.round((s-1)*i));t.physicsBody.appendAnchor(d,e.physicsBody,a,o)},r.prototype.appendHook=function(t,e,n,i,o){i===void 0&&(i=1),o===void 0&&(o=!1);var a=Math.round(t.segments*n);t.physicsBody.appendAnchor(a,e.physicsBody,o,i)},r.prototype.sleepBody=function(t){l.a.Warn("sleepBody is not currently supported by the Ammo physics plugin")},r.prototype.wakeUpBody=function(t){t.physicsBody.activate()},r.prototype.updateDistanceJoint=function(t,e,n){l.a.Warn("updateDistanceJoint is not currently supported by the Ammo physics plugin")},r.prototype.setMotor=function(t,e,n,i){t.physicsJoint.enableAngularMotor(!0,e,n)},r.prototype.setLimit=function(t,e,n){l.a.Warn("setLimit is not currently supported by the Ammo physics plugin")},r.prototype.syncMeshWithImpostor=function(t,e){e.physicsBody.getMotionState().getWorldTransform(this._tmpAmmoTransform),t.position.x=this._tmpAmmoTransform.getOrigin().x(),t.position.y=this._tmpAmmoTransform.getOrigin().y(),t.position.z=this._tmpAmmoTransform.getOrigin().z(),t.rotationQuaternion&&(t.rotationQuaternion.x=this._tmpAmmoTransform.getRotation().x(),t.rotationQuaternion.y=this._tmpAmmoTransform.getRotation().y(),t.rotationQuaternion.z=this._tmpAmmoTransform.getRotation().z(),t.rotationQuaternion.w=this._tmpAmmoTransform.getRotation().w())},r.prototype.getRadius=function(t){return t.getObjectExtendSize().x/2},r.prototype.getBoxSizeToRef=function(t,e){var n=t.getObjectExtendSize();e.x=n.x,e.y=n.y,e.z=n.z},r.prototype.dispose=function(){this.bjsAMMO.destroy(this.world),this.bjsAMMO.destroy(this._solver),this.bjsAMMO.destroy(this._overlappingPairCache),this.bjsAMMO.destroy(this._dispatcher),this.bjsAMMO.destroy(this._collisionConfiguration),this.bjsAMMO.destroy(this._tmpAmmoVectorA),this.bjsAMMO.destroy(this._tmpAmmoVectorB),this.bjsAMMO.destroy(this._tmpAmmoVectorC),this.bjsAMMO.destroy(this._tmpAmmoTransform),this.bjsAMMO.destroy(this._tmpAmmoQuaternion),this.bjsAMMO.destroy(this._tmpAmmoConcreteContactResultCallback),this.world=null},r.prototype.raycast=function(t,e){this._tmpAmmoVectorRCA=new this.bjsAMMO.btVector3(t.x,t.y,t.z),this._tmpAmmoVectorRCB=new this.bjsAMMO.btVector3(e.x,e.y,e.z);var n=new this.bjsAMMO.ClosestRayResultCallback(this._tmpAmmoVectorRCA,this._tmpAmmoVectorRCB);return this.world.rayTest(this._tmpAmmoVectorRCA,this._tmpAmmoVectorRCB,n),this._raycastResult.reset(t,e),n.hasHit()&&(this._raycastResult.setHitData({x:n.get_m_hitNormalWorld().x(),y:n.get_m_hitNormalWorld().y(),z:n.get_m_hitNormalWorld().z()},{x:n.get_m_hitPointWorld().x(),y:n.get_m_hitPointWorld().y(),z:n.get_m_hitPointWorld().z()}),this._raycastResult.calculateHitDistance()),this.bjsAMMO.destroy(n),this.bjsAMMO.destroy(this._tmpAmmoVectorRCA),this.bjsAMMO.destroy(this._tmpAmmoVectorRCB),this._raycastResult},r.DISABLE_COLLISION_FLAG=4,r.KINEMATIC_FLAG=2,r.DISABLE_DEACTIVATION_FLAG=4,r}();U.a.prototype.removeReflectionProbe=function(r){if(!this.reflectionProbes)return-1;var t=this.reflectionProbes.indexOf(r);return t!==-1&&this.reflectionProbes.splice(t,1),t},U.a.prototype.addReflectionProbe=function(r){this.reflectionProbes||(this.reflectionProbes=[]),this.reflectionProbes.push(r)};var Qu=function(){function r(t,e,n,i,o){var a=this;i===void 0&&(i=!0),o===void 0&&(o=!1),this.name=t,this._viewMatrix=u.a.Identity(),this._target=u.e.Zero(),this._add=u.e.Zero(),this._invertYAxis=!1,this.position=u.e.Zero(),this._scene=n,this._scene.reflectionProbes||(this._scene.reflectionProbes=new Array),this._scene.reflectionProbes.push(this);var s=h.a.TEXTURETYPE_UNSIGNED_BYTE;if(o){var d=this._scene.getEngine().getCaps();d.textureHalfFloatRender?s=h.a.TEXTURETYPE_HALF_FLOAT:d.textureFloatRender&&(s=h.a.TEXTURETYPE_FLOAT)}this._renderTargetTexture=new sn(t,e,n,i,!0,s,!0),this._renderTargetTexture.onBeforeRenderObservable.add(function(p){switch(p){case 0:a._add.copyFromFloats(1,0,0);break;case 1:a._add.copyFromFloats(-1,0,0);break;case 2:a._add.copyFromFloats(0,a._invertYAxis?1:-1,0);break;case 3:a._add.copyFromFloats(0,a._invertYAxis?-1:1,0);break;case 4:a._add.copyFromFloats(0,0,1);break;case 5:a._add.copyFromFloats(0,0,-1)}a._attachedMesh&&a.position.copyFrom(a._attachedMesh.getAbsolutePosition()),a.position.addToRef(a._add,a._target),u.a.LookAtLHToRef(a.position,a._target,u.e.Up(),a._viewMatrix),n.activeCamera&&(a._projectionMatrix=u.a.PerspectiveFovLH(Math.PI/2,1,n.activeCamera.minZ,n.activeCamera.maxZ),n.setTransformMatrix(a._viewMatrix,a._projectionMatrix)),n._forcedViewPosition=a.position}),this._renderTargetTexture.onAfterUnbindObservable.add(function(){n._forcedViewPosition=null,n.updateTransformMatrix(!0)})}return Object.defineProperty(r.prototype,"samples",{get:function(){return this._renderTargetTexture.samples},set:function(t){this._renderTargetTexture.samples=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"refreshRate",{get:function(){return this._renderTargetTexture.refreshRate},set:function(t){this._renderTargetTexture.refreshRate=t},enumerable:!1,configurable:!0}),r.prototype.getScene=function(){return this._scene},Object.defineProperty(r.prototype,"cubeTexture",{get:function(){return this._renderTargetTexture},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"renderList",{get:function(){return this._renderTargetTexture.renderList},enumerable:!1,configurable:!0}),r.prototype.attachToMesh=function(t){this._attachedMesh=t},r.prototype.setRenderingAutoClearDepthStencil=function(t,e){this._renderTargetTexture.setRenderingAutoClearDepthStencil(t,e)},r.prototype.dispose=function(){var t=this._scene.reflectionProbes.indexOf(this);t!==-1&&this._scene.reflectionProbes.splice(t,1),this._renderTargetTexture&&(this._renderTargetTexture.dispose(),this._renderTargetTexture=null)},r.prototype.toString=function(t){var e="Name: "+this.name;return t&&(e+=", position: "+this.position.toString(),this._attachedMesh&&(e+=", attached mesh: "+this._attachedMesh.name)),e},r.prototype.getClassName=function(){return"ReflectionProbe"},r.prototype.serialize=function(){var t=L.a.Serialize(this,this._renderTargetTexture.serialize());return t.isReflectionProbe=!0,t},r.Parse=function(t,e,n){var i=null;if(e.reflectionProbes)for(var o=0;o<e.reflectionProbes.length;o++){var a=e.reflectionProbes[o];if(a.name===t.name){i=a;break}}return(i=L.a.Parse(function(){return i||new r(t.name,t.renderTargetSize,e,t._generateMipMaps)},t,e,n)).cubeTexture._waitingRenderList=t.renderList,t._attachedMesh&&i.attachToMesh(e.getMeshByID(t._attachedMesh)),i},Object(c.c)([Object(L.k)()],r.prototype,"_attachedMesh",void 0),Object(c.c)([Object(L.o)()],r.prototype,"position",void 0),r}(),K_=!0,la=function(){function r(){}return r.LoaderInjectedPhysicsEngine=void 0,r}(),qu=function(r,t,e,n){for(var i=0,o=t.materials.length;i<o;i++){var a=t.materials[i];if(a.id===r)return Ht.a.Parse(a,e,n)}return null},Q_=function(r,t,e){for(var n in t)if(r.name===t[n])return e.push(r.id),!0;return!(!r.parentId||e.indexOf(r.parentId)===-1)&&(e.push(r.id),!0)},Dr=function(r,t){return r+" of "+(t?t.file+" from "+t.name+" version: "+t.version+", exporter version: "+t.exporter_version:"unknown")},Zu=function(r,t){var e=t;if(t._waitingData.lods){if(t._waitingData.lods.ids&&t._waitingData.lods.ids.length>0){var n=t._waitingData.lods.ids,i=e.isEnabled(!1);if(t._waitingData.lods.distances){var o=t._waitingData.lods.distances;if(o.length>=n.length){var a=o.length>n.length?o[o.length-1]:0;e.setEnabled(!1);for(var s=0;s<n.length;s++){var d=n[s],p=r.getMeshByID(d);p!=null&&e.addLODLevel(o[s],p)}a>0&&e.addLODLevel(a,null),i===!0&&e.setEnabled(!0)}else Xe.b.Warn("Invalid level of detail distances for "+t.name)}}t._waitingData.lods=null}},Ju=function(r,t,e,n,i){i===void 0&&(i=!1);var o=new Cn(r),a="importScene has failed JSON parse";try{var s=JSON.parse(t);a="";var d,p,b=Ut.loggingLevel===Ut.DETAILED_LOGGING;if(s.environmentTexture!==void 0&&s.environmentTexture!==null){var P=s.isPBR===void 0||s.isPBR;if(s.environmentTextureType&&s.environmentTextureType==="BABYLON.HDRCubeTexture"){var O=s.environmentTextureSize?s.environmentTextureSize:128,B=new aa((s.environmentTexture.match(/https?:\/\//g)?"":e)+s.environmentTexture,r,O,!0,!P);s.environmentTextureRotationY&&(B.rotationY=s.environmentTextureRotationY),r.environmentTexture=B}else if(Qn.a.EndsWith(s.environmentTexture,".env")){var F=new ai((s.environmentTexture.match(/https?:\/\//g)?"":e)+s.environmentTexture,r);s.environmentTextureRotationY&&(F.rotationY=s.environmentTextureRotationY),r.environmentTexture=F}else{var z=ai.CreateFromPrefilteredData((s.environmentTexture.match(/https?:\/\//g)?"":e)+s.environmentTexture,r);s.environmentTextureRotationY&&(z.rotationY=s.environmentTextureRotationY),r.environmentTexture=z}if(s.createDefaultSkybox===!0){var J=r.activeCamera!==void 0&&r.activeCamera!==null?(r.activeCamera.maxZ-r.activeCamera.minZ)/2:1e3,ie=s.skyboxBlurLevel||0;r.createDefaultSkybox(r.environmentTexture,P,J,ie)}o.environmentTexture=r.environmentTexture}if(s.environmentIntensity!==void 0&&s.environmentIntensity!==null&&(r.environmentIntensity=s.environmentIntensity),s.lights!==void 0&&s.lights!==null)for(d=0,p=s.lights.length;d<p;d++){var se=s.lights[d],ce=xi.a.Parse(se,r);ce&&(o.lights.push(ce),a+=d===0?`
-	Lights:`:"",a+=`
-		`+ce.toString(b))}if(s.reflectionProbes!==void 0&&s.reflectionProbes!==null)for(d=0,p=s.reflectionProbes.length;d<p;d++){var ue=s.reflectionProbes[d],fe=Qu.Parse(ue,r,e);fe&&(o.reflectionProbes.push(fe),a+=d===0?`
-	Reflection Probes:`:"",a+=`
-		`+fe.toString(b))}if(s.animations!==void 0&&s.animations!==null)for(d=0,p=s.animations.length;d<p;d++){var ve=s.animations[d],Te=R.a.GetClass("BABYLON.Animation");if(Te){var Re=Te.Parse(ve);r.animations.push(Re),o.animations.push(Re),a+=d===0?`
-	Animations:`:"",a+=`
-		`+Re.toString(b)}}if(s.materials!==void 0&&s.materials!==null)for(d=0,p=s.materials.length;d<p;d++){var Ae=s.materials[d],Ee=Ht.a.Parse(Ae,r,e);Ee&&(o.materials.push(Ee),a+=d===0?`
-	Materials:`:"",a+=`
-		`+Ee.toString(b),Ee.getActiveTextures().forEach(function(qt){o.textures.indexOf(qt)==-1&&o.textures.push(qt)}))}if(s.multiMaterials!==void 0&&s.multiMaterials!==null)for(d=0,p=s.multiMaterials.length;d<p;d++){var Se=s.multiMaterials[d],Le=rr.a.ParseMultiMaterial(Se,r);o.multiMaterials.push(Le),a+=d===0?`
-	MultiMaterials:`:"",a+=`
-		`+Le.toString(b),Le.getActiveTextures().forEach(function(qt){o.textures.indexOf(qt)==-1&&o.textures.push(qt)})}if(s.morphTargetManagers!==void 0&&s.morphTargetManagers!==null)for(var Ce=0,Ne=s.morphTargetManagers;Ce<Ne.length;Ce++){var Ie=Ne[Ce];o.morphTargetManagers.push(sa.Parse(Ie,r))}if(s.skeletons!==void 0&&s.skeletons!==null)for(d=0,p=s.skeletons.length;d<p;d++){var Fe=s.skeletons[d],Ye=No.Parse(Fe,r);o.skeletons.push(Ye),a+=d===0?`
-	Skeletons:`:"",a+=`
-		`+Ye.toString(b)}var tt=s.geometries;if(tt!=null){var it=new Array,lt=tt.vertexData;if(lt!=null)for(d=0,p=lt.length;d<p;d++){var Qe=lt[d];it.push(Ws.a.Parse(Qe,r,e))}it.forEach(function(qt){qt&&o.geometries.push(qt)})}if(s.transformNodes!==void 0&&s.transformNodes!==null)for(d=0,p=s.transformNodes.length;d<p;d++){var ot=s.transformNodes[d],rt=Er.a.Parse(ot,r,e);o.transformNodes.push(rt)}if(s.meshes!==void 0&&s.meshes!==null)for(d=0,p=s.meshes.length;d<p;d++){var Ze=s.meshes[d],dt=De.a.Parse(Ze,r,e);if(o.meshes.push(dt),dt.hasInstances)for(var Ve=0,Je=dt.instances;Ve<Je.length;Ve++){var yt=Je[Ve];o.meshes.push(yt)}a+=d===0?`
-	Meshes:`:"",a+=`
-		`+dt.toString(b)}if(s.cameras!==void 0&&s.cameras!==null)for(d=0,p=s.cameras.length;d<p;d++){var Wt=s.cameras[d],Nt=gt.a.Parse(Wt,r);o.cameras.push(Nt),a+=d===0?`
-	Cameras:`:"",a+=`
-		`+Nt.toString(b)}if(s.postProcesses!==void 0&&s.postProcesses!==null)for(d=0,p=s.postProcesses.length;d<p;d++){var Qt=s.postProcesses[d],vt=_t.Parse(Qt,r,e);vt&&(o.postProcesses.push(vt),a+=d===0?`
-Postprocesses:`:"",a+=`
-		`+vt.toString())}if(s.animationGroups!==void 0&&s.animationGroups!==null)for(d=0,p=s.animationGroups.length;d<p;d++){var Jt=s.animationGroups[d],Xt=je.Parse(Jt,r);o.animationGroups.push(Xt),a+=d===0?`
-	AnimationGroups:`:"",a+=`
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r({isEnabled:t.isEnabled,leftColor:M.a.FromArray(t.leftColor),rightColor:M.a.FromArray(t.rightColor),bias:t.bias,power:t.power||1})},r}();L.a._FresnelParametersParser=$u.Parse;var eh=f(119),Qs=function(r){function t(e,n){var i=r.call(this,e,n)||this;return i.maxSimultaneousLights=4,i.disableLighting=!1,i.invertNormalMapX=!1,i.invertNormalMapY=!1,i.emissiveColor=new M.a(0,0,0),i.occlusionStrength=1,i.useLightmapAsShadowmap=!1,i._useAlphaFromAlbedoTexture=!0,i._useAmbientInGrayScale=!0,i}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"doubleSided",{get:function(){return this._twoSidedLighting},set:function(e){this._twoSidedLighting!==e&&(this._twoSidedLighting=e,this.backFaceCulling=!e,this._markAllSubMeshesAsTexturesDirty())},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"PBRBaseSimpleMaterial"},Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsLightsDirty")],t.prototype,"maxSimultaneousLights",void 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i.id=e,i.name=e,this.clearCoat.copyTo(i.clearCoat),this.anisotropy.copyTo(i.anisotropy),this.brdf.copyTo(i.brdf),this.sheen.copyTo(i.sheen),this.subSurface.copyTo(i.subSurface),i},t.prototype.serialize=function(){var e=L.a.Serialize(this);return e.customType="BABYLON.PBRMetallicRoughnessMaterial",e.clearCoat=this.clearCoat.serialize(),e.anisotropy=this.anisotropy.serialize(),e.brdf=this.brdf.serialize(),e.sheen=this.sheen.serialize(),e.subSurface=this.subSurface.serialize(),e},t.Parse=function(e,n,i){var o=L.a.Parse(function(){return new t(e.name,n)},e,n,i);return e.clearCoat&&o.clearCoat.parse(e.clearCoat,n,i),e.anisotropy&&o.anisotropy.parse(e.anisotropy,n,i),e.brdf&&o.brdf.parse(e.brdf,n,i),e.sheen&&o.sheen.parse(e.sheen,n,i),e.subSurface&&o.subSurface.parse(e.subSurface,n,i),o},Object(c.c)([Object(L.e)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty","_albedoColor")],t.prototype,"baseColor",void 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t=this;return this._WorkerPromise||(this._WorkerPromise=new Promise(function(e){t._Worker?e(t._Worker):Xe.b.LoadFileAsync(r.WasmModuleURL).then(function(n){var i=URL.createObjectURL(new Blob(["("+$_+")()"],{type:"application/javascript"}));t._Worker=new Worker(i);var o=function(a){a.data.action==="init"&&(t._Worker.removeEventListener("message",o),e(t._Worker))};t._Worker.addEventListener("message",o),t._Worker.postMessage({action:"init",url:r.JSModuleURL,wasmBinary:n})})})),this._WorkerPromise},r.TranscodeAsync=function(t,e){var n=this,i=t instanceof ArrayBuffer?new Uint8Array(t):t;return new Promise(function(o,a){n._CreateWorkerAsync().then(function(){var s=n._actionId++,d=function(b){b.data.action==="transcode"&&b.data.id===s&&(n._Worker.removeEventListener("message",d),b.data.success?o(b.data):a("Transcode is not supported on this device"))};n._Worker.addEventListener("message",d);var p=new Uint8Array(i.byteLength);p.set(new 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t._invertVScale=!t.invertY,t.width=n.width+3&-4,t.height=n.height+3&-4,i._uploadDataToTextureDirectly(t,n.transcodedPixels,a,0,h.a.TEXTUREFORMAT_RGB,!0);else t.width=n.width,t.height=n.height,e.fileInfo.images[a].levels.forEach(function(d,p){i._uploadCompressedDataToTextureDirectly(t,r.GetInternalFormatFromBasisFormat(e.format),d.width,d.height,d.transcodedPixels,a,p)}),i.webGLVersion<2&&($.a.Log2(t.width)%1!=0||$.a.Log2(t.height)%1!=0)&&(Xe.b.Warn("Loaded .basis texture width and height are not a power of two. 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Te=F+8*(fe*ce+ve);ie[0]=B[Te]|B[Te+1]<<8,ie[1]=B[Te+2]|B[Te+3]<<8,ie[2]=(2*(31&ie[0])+1*(31&ie[1]))/3|(2*(2016&ie[0])+1*(2016&ie[1]))/3&2016|(2*(63488&ie[0])+1*(63488&ie[1]))/3&63488,ie[3]=(2*(31&ie[1])+1*(31&ie[0]))/3|(2*(2016&ie[1])+1*(2016&ie[0]))/3&2016|(2*(63488&ie[1])+1*(63488&ie[0]))/3&63488;for(var Re=0;Re<4;Re++){var Ae=B[Te+4+Re],Ee=(4*fe+Re)*z+4*ve;se[Ee++]=ie[3&Ae],se[Ee++]=ie[Ae>>2&3],se[Ee++]=ie[Ae>>4&3],se[Ee++]=ie[Ae>>6&3]}}return se}(O,0,a.getImageWidth(s,d)+3&-4,a.getImageHeight(s,d)+3&-4)),O):null}onmessage=function(a){if(a.data.action==="init")i||(Module={wasmBinary:a.data.wasmBinary},importScripts(a.data.url),i=new Promise(function(fe){Module.onRuntimeInitialized=function(){Module.initializeBasis(),fe()}})),i.then(function(){postMessage({action:"init"})});else if(a.data.action==="transcode"){var s=a.data.config,d=a.data.imageData,p=new Module.BasisFile(d),b=function(fe){for(var ve=fe.getHasAlpha(),Te=fe.getNumImages(),Re=[],Ae=0;Ae<Te;Ae++){for(var 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ce=J.levels[se],ue=o(p,z,se,P,O);if(!ue){B=!1;break}ce.transcodedPixels=ue,F.push(ce.transcodedPixels.buffer)}}}p.close(),p.delete(),O&&(P=-1),B?postMessage({action:"transcode",success:B,id:a.data.id,fileInfo:b,format:P},F):postMessage({action:"transcode",success:B,id:a.data.id})}}}var ah=function(){function r(){this.supportCascades=!1}return r.prototype.canLoad=function(t){return Qn.a.EndsWith(t,".basis")},r.prototype.loadCubeData=function(t,e,n,i,o){if(!Array.isArray(t)){var a=e.getEngine().getCaps(),s={supportedCompressionFormats:{etc1:!!a.etc1,s3tc:!!a.s3tc,pvrtc:!!a.pvrtc,etc2:!!a.etc2}};mo.TranscodeAsync(t,s).then(function(d){var p=d.fileInfo.images[0].levels.length>1&&e.generateMipMaps;mo.LoadTextureFromTranscodeResult(e,d),e.getEngine()._setCubeMapTextureParams(e,p),e.isReady=!0,e.onLoadedObservable.notifyObservers(e),e.onLoadedObservable.clear(),i&&i()}).catch(function(d){Xe.b.Warn("Failed to transcode Basis file, transcoding may not be supported on this 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n=0;n<this._textures.length;n++)this._textures[n].wrapU=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wrapV",{set:function(e){if(this._textures)for(var n=0;n<this._textures.length;n++)this._textures[n].wrapV=e},enumerable:!1,configurable:!0}),t.prototype._initTypes=function(e,n,i,o){for(var a=0;a<e;a++)o&&o.types&&o.types[a]!==void 0?n.push(o.types[a]):n.push(o&&o.defaultType?o.defaultType:h.a.TEXTURETYPE_UNSIGNED_INT),o&&o.samplingModes&&o.samplingModes[a]!==void 0?i.push(o.samplingModes[a]):i.push(we.a.BILINEAR_SAMPLINGMODE)},t.prototype._rebuild=function(e){e===void 0&&(e=!1),this.releaseInternalTextures(),this._createInternalTextures(),e&&this._createTextures();for(var n=0;n<this._internalTextures.length;n++)this._textures[n]._texture=this._internalTextures[n];this._texture=this._internalTextures[0],this.samples!==1&&this._getEngine().updateMultipleRenderTargetTextureSampleCount(this._internalTextures,this.samples)},t.prototype._createInternalTextures=function(){this._internalTextures=this._getEngine().createMultipleRenderTarget(this._size,this._multiRenderTargetOptions)},t.prototype._createTextures=function(){this._textures=[];for(var e=0;e<this._internalTextures.length;e++){var n=new we.a(null,this.getScene());n._texture=this._internalTextures[e],this._textures.push(n)}this._texture=this._internalTextures[0]},t.prototype.replaceTexture=function(e,n){e._texture&&(this._textures[n]=e,this._internalTextures[n]=e._texture)},Object.defineProperty(t.prototype,"samples",{get:function(){return this._samples},set:function(e){this._samples!==e&&(this._samples=this._getEngine().updateMultipleRenderTargetTextureSampleCount(this._internalTextures,e))},enumerable:!1,configurable:!0}),t.prototype.resize=function(e){this._size=e,this._rebuild()},t.prototype.updateCount=function(e,n){this._multiRenderTargetOptions.textureCount=e,this._count=e;var i=[],o=[];this._initTypes(e,i,o,n),this._multiRenderTargetOptions.types=i,this._multiRenderTargetOptions.samplingModes=o,this._rebuild(!0)},t.prototype.unbindFrameBuffer=function(e,n){var i=this;e.unBindMultiColorAttachmentFramebuffer(this._internalTextures,this.isCube,function(){i.onAfterRenderObservable.notifyObservers(n)})},t.prototype.dispose=function(){this.releaseInternalTextures(),r.prototype.dispose.call(this)},t.prototype.releaseInternalTextures=function(){if(this._internalTextures)for(var e=this._internalTextures.length-1;e>=0;e--)this._internalTextures[e]!==void 0&&(this._internalTextures[e].dispose(),this._internalTextures.splice(e,1))},t}(sn),Zs=function(r,t,e){this.id=r,this.scale=t,this.offset=e},em=function(){function r(t,e,n,i){var o,a,s,d,p,b,P,O,B,F,z,J,ie;return this.name=t,this.meshes=e,this.scene=i,this.options=n,this.options.map=(o=this.options.map)!==null&&o!==void 0?o:["ambientTexture","bumpTexture","diffuseTexture","emissiveTexture","lightmapTexture","opacityTexture","reflectionTexture","refractionTexture","specularTexture"],this.options.uvsIn=(a=this.options.uvsIn)!==null&&a!==void 0?a:Oe.b.UVKind,this.options.uvsOut=(s=this.options.uvsOut)!==null&&s!==void 0?s:Oe.b.UVKind,this.options.layout=(d=this.options.layout)!==null&&d!==void 0?d:r.LAYOUT_STRIP,this.options.layout===r.LAYOUT_COLNUM&&(this.options.colnum=(p=this.options.colnum)!==null&&p!==void 0?p:8),this.options.updateInputMeshes=(b=this.options.updateInputMeshes)===null||b===void 0||b,this.options.disposeSources=(P=this.options.disposeSources)===null||P===void 0||P,this._expecting=0,this.options.fillBlanks=(O=this.options.fillBlanks)===null||O===void 0||O,this.options.fillBlanks===!0&&(this.options.customFillColor=(B=this.options.customFillColor)!==null&&B!==void 0?B:"black"),this.options.frameSize=(F=this.options.frameSize)!==null&&F!==void 0?F:256,this.options.paddingRatio=(z=this.options.paddingRatio)!==null&&z!==void 0?z:.0115,this._paddingValue=Math.ceil(this.options.frameSize*this.options.paddingRatio),this._paddingValue%2!=0&&this._paddingValue++,this.options.paddingMode=(J=this.options.paddingMode)!==null&&J!==void 0?J:r.SUBUV_WRAP,this.options.paddingMode===r.SUBUV_COLOR&&(this.options.paddingColor=(ie=this.options.paddingColor)!==null&&ie!==void 0?ie:new M.b(0,0,0,1)),this.sets={},this.frames=[],this}return r.prototype._createFrames=function(t){for(var e=this,n=this._calculateSize(),i=new u.d(1,1).divide(n),o=0,a=this._expecting,s=this.meshes.length,d=Object.keys(this.sets),p=0;p<d.length;p++){var b=d[p],P=new Ti.a(this.name+".TexturePack."+b+"Set",{width:n.x,height:n.y},this.scene,!0,we.a.TRILINEAR_SAMPLINGMODE,Ue.a.TEXTUREFORMAT_RGBA),O=P.getContext();O.fillStyle="rgba(0,0,0,0)",O.fillRect(0,0,n.x,n.y),P.update(!1),this.sets[b]=P}var B=this.options.frameSize||256,F=this._paddingValue,z=B+2*F;for(p=0;p<s;p++)for(var J=this.meshes[p].material,ie=function(ue){var fe=new Ti.a("temp",z,se.scene,!0),ve=fe.getContext(),Te=se._getFrameOffset(p),Re=function(){o++,fe.update(!1);var Le=ve.getImageData(0,0,z,z),Ce=e.sets[Ae];if(Ce.getContext().putImageData(Le,n.x*Te.x,n.y*Te.y),fe.dispose(),Ce.update(!1),o==a)return e._calculateMeshUVFrames(B,F,n,i,e.options.updateInputMeshes||!1),void t()},Ae=d[ue]||"_blank";if(J&&J[Ae]!==null){var Ee=J[Ae],Se=new Image;Ee instanceof Ti.a?Se.src=Ee.getContext().canvas.toDataURL("image/png"):Se.src=Ee.url,Xe.b.SetCorsBehavior(Se.src,Se),Se.onload=function(){ve.fillStyle="rgba(0,0,0,0)",ve.fillRect(0,0,z,z),fe.update(!1),ve.setTransform(1,0,0,-1,0,0);var Le=[0,0,1,0,1,1,0,1,-1,1,-1,0,-2,0,-1,1,-1];switch(e.options.paddingMode){case 0:for(var Ce=0;Ce<9;Ce++)ve.drawImage(Se,0,0,Se.width,Se.height,F+B*Le[Ce],F+B*Le[Ce+1]-z,B,B);break;case 1:for(var Ne=0;Ne<F;Ne++)ve.drawImage(Se,0,0,Se.width,Se.height,Ne+B*Le[0],F-z,B,B),ve.drawImage(Se,0,0,Se.width,Se.height,2*F-Ne,F-z,B,B),ve.drawImage(Se,0,0,Se.width,Se.height,F,Ne-z,B,B),ve.drawImage(Se,0,0,Se.width,Se.height,F,2*F-Ne-z,B,B);ve.drawImage(Se,0,0,Se.width,Se.height,F+B*Le[0],F+B*Le[1]-z,B,B);break;case 2:ve.fillStyle=(e.options.paddingColor||M.a.Black()).toHexString(),ve.fillRect(0,0,z,-z),ve.clearRect(F,F,B,B),ve.drawImage(Se,0,0,Se.width,Se.height,F+B*Le[0],F+B*Le[1]-z,B,B)}ve.setTransform(1,0,0,1,0,0),Re()}}else ve.fillStyle="rgba(0,0,0,0)",se.options.fillBlanks&&(ve.fillStyle=se.options.customFillColor),ve.fillRect(0,0,z,z),Re()},se=this,ce=0;ce<d.length;ce++)ie(ce)},r.prototype._calculateSize=function(){var t=this.meshes.length||0,e=this.options.frameSize||0,n=this._paddingValue||0;switch(this.options.layout){case 0:return new u.d(e*t+2*n*t,e+2*n);case 1:var i=Math.max(2,Math.ceil(Math.sqrt(t))),o=e*i+2*n*i;return new u.d(o,o);case 2:var a=this.options.colnum||1,s=Math.max(1,Math.ceil(t/a));return new u.d(e*a+2*n*a,e*s+2*n*s)}return u.d.Zero()},r.prototype._calculateMeshUVFrames=function(t,e,n,i,o){for(var a=this.meshes.length,s=0;s<a;s++){var d=this.meshes[s],p=new u.d(t/n.x,t/n.y),b=i.clone().scale(e),P=this._getFrameOffset(s).add(b),O=new Zs(s,p,P);this.frames.push(O),o&&(this._updateMeshUV(d,s),this._updateTextureReferences(d))}},r.prototype._getFrameOffset=function(t){var e,n,i,o=this.meshes.length;switch(this.options.layout){case 0:return e=1/o,new u.d(t*e,0);case 1:var a=Math.max(2,Math.ceil(Math.sqrt(o)));return i=t-(n=Math.floor(t/a))*a,e=1/a,new u.d(i*e,n*e);case 2:var s=this.options.colnum||1,d=Math.max(1,Math.ceil(o/s));return n=t-(i=Math.floor(t/d))*d,e=new u.d(1/s,1/d),new u.d(i*e.x,n*e.y)}return u.d.Zero()},r.prototype._updateMeshUV=function(t,e){var n=this.frames[e],i=t.getVerticesData(this.options.uvsIn||Oe.b.UVKind),o=[],a=0;i.length&&(a=i.length||0);for(var s=0;s<a;s+=2)o.push(i[s]*n.scale.x+n.offset.x,i[s+1]*n.scale.y+n.offset.y);t.setVerticesData(this.options.uvsOut||Oe.b.UVKind,o)},r.prototype._updateTextureReferences=function(t,e){e===void 0&&(e=!1);for(var n=t.material,i=Object.keys(this.sets),o=function(d){d.dispose&&d.dispose()},a=0;a<i.length;a++){var s=i[a];if(e)n[s]!==null&&o(n[s]),n[s]=this.sets[s];else{if(!n)return;n[s]!==null&&(o(n[s]),n[s]=this.sets[s])}}},r.prototype.setMeshToFrame=function(t,e,n){n===void 0&&(n=!1),this._updateMeshUV(t,e),n&&this._updateTextureReferences(t,!0)},r.prototype.processAsync=function(){var t=this;return new Promise(function(e,n){try{if(t.meshes.length===0)return void e();for(var i=0,o=function(d){var p=t.meshes[d],b=p.material;if(!b)return++i===t.meshes.length?{value:t._createFrames(e)}:"continue";b.forceCompilationAsync(p).then(function(){(function(P){if(i++,t.options.map){for(var O=0;O<t.options.map.length;O++)P[t.options.map[O]]!==null&&(t.sets[t.options.map[O]]||(t.sets[t.options.map[O]]=!0),t._expecting++);i===t.meshes.length&&t._createFrames(e)}})(b)})},a=0;a<t.meshes.length;a++){var s=o(a);if(typeof s=="object")return s.value}}catch(d){return n(d)}})},r.prototype.dispose=function(){for(var t=Object.keys(this.sets),e=0;e<t.length;e++){var n=t[e];this.sets[n].dispose()}},r.prototype.download=function(t,e){var n=this;t===void 0&&(t="png"),e===void 0&&(e=1),setTimeout(function(){var i={name:n.name,sets:{},options:{},frames:[]},o=Object.keys(n.sets),a=Object.keys(n.options);try{for(var s=0;s<o.length;s++){var d=o[s],p=n.sets[d];i.sets[d]=p.getContext().canvas.toDataURL("image/"+t,e)}for(s=0;s<a.length;s++){var b=a[s];i.options[b]=n.options[b]}for(s=0;s<n.frames.length;s++){var P=n.frames[s];i.frames.push(P.scale.x,P.scale.y,P.offset.x,P.offset.y)}}catch(F){return void l.a.Warn("Unable to download: "+F)}var O="data:text/json;charset=utf-8,"+encodeURIComponent(JSON.stringify(i,null,4)),B=document.createElement("a");B.setAttribute("href",O),B.setAttribute("download",n.name+"_texurePackage.json"),document.body.appendChild(B),B.click(),B.remove()},0)},r.prototype.updateFromJSON=function(t){try{var e=JSON.parse(t);this.name=e.name;for(var n=Object.keys(e.options),i=0;i<n.length;i++)this.options[n[i]]=e.options[n[i]];for(i=0;i<e.frames.length;i+=4){var o=new Zs(i/4,new u.d(e.frames[i],e.frames[i+1]),new u.d(e.frames[i+2],e.frames[i+3]));this.frames.push(o)}var a=Object.keys(e.sets);for(i=0;i<a.length;i++){var s=new we.a(e.sets[a[i]],this.scene,!1,!1);this.sets[a[i]]=s}}catch(d){l.a.Warn("Unable to update from JSON: "+d)}},r.LAYOUT_STRIP=0,r.LAYOUT_POWER2=1,r.LAYOUT_COLNUM=2,r.SUBUV_WRAP=0,r.SUBUV_EXTEND=1,r.SUBUV_COLOR=2,r}(),sh=function(){function r(t){this.name=at.a.NAME_PROCEDURALTEXTURE,this.scene=t,this.scene.proceduralTextures=new Array}return r.prototype.register=function(){this.scene._beforeClearStage.registerStep(at.a.STEP_BEFORECLEAR_PROCEDURALTEXTURE,this,this._beforeClear)},r.prototype.rebuild=function(){},r.prototype.dispose=function(){},r.prototype._beforeClear=function(){if(this.scene.proceduralTexturesEnabled){Xe.b.StartPerformanceCounter("Procedural textures",this.scene.proceduralTextures.length>0);for(var t=0;t<this.scene.proceduralTextures.length;t++){var e=this.scene.proceduralTextures[t];e._shouldRender()&&e.render()}Xe.b.EndPerformanceCounter("Procedural textures",this.scene.proceduralTextures.length>0)}},r}(),tm=`
-attribute vec2 position;
-
-varying vec2 vPosition;
-varying vec2 vUV;
-const vec2 madd=vec2(0.5,0.5);
-void main(void) {
-vPosition=position;
-vUV=position*madd+madd;
-gl_Position=vec4(position,0.0,1.0);
-}`;ze.a.ShadersStore.proceduralVertexShader=tm;var go=function(r){function t(e,n,i,o,a,s,d,p){a===void 0&&(a=null),s===void 0&&(s=!0),d===void 0&&(d=!1),p===void 0&&(p=h.a.TEXTURETYPE_UNSIGNED_INT);var b=r.call(this,null,o,!s)||this;b.isEnabled=!0,b.autoClear=!0,b.onGeneratedObservable=new x.c,b.onBeforeGenerationObservable=new x.c,b.nodeMaterialSource=null,b._textures={},b._currentRefreshId=-1,b._frameId=-1,b._refreshRate=1,b._vertexBuffers={},b._uniforms=new Array,b._samplers=new Array,b._floats={},b._ints={},b._floatsArrays={},b._colors3={},b._colors4={},b._vectors2={},b._vectors3={},b._matrices={},b._fallbackTextureUsed=!1,b._cachedDefines="",b._contentUpdateId=-1;var P=(o=b.getScene()||te.a.LastCreatedScene)._getComponent(at.a.NAME_PROCEDURALTEXTURE);P||(P=new sh(o),o._addComponent(P)),o.proceduralTextures.push(b),b._fullEngine=o.getEngine(),b.name=e,b.isRenderTarget=!0,b._size=n,b._generateMipMaps=s,b.setFragment(i),b._fallbackTexture=a,d?(b._texture=b._fullEngine.createRenderTargetCubeTexture(n,{generateMipMaps:s,generateDepthBuffer:!1,generateStencilBuffer:!1,type:p}),b.setFloat("face",0)):b._texture=b._fullEngine.createRenderTargetTexture(n,{generateMipMaps:s,generateDepthBuffer:!1,generateStencilBuffer:!1,type:p});var O=[];return O.push(1,1),O.push(-1,1),O.push(-1,-1),O.push(1,-1),b._vertexBuffers[Oe.b.PositionKind]=new Oe.b(b._fullEngine,O,Oe.b.PositionKind,!1,!1,2),b._createIndexBuffer(),b}return Object(c.d)(t,r),t.prototype.getEffect=function(){return this._effect},t.prototype.getContent=function(){return this._contentData&&this._frameId===this._contentUpdateId||(this._contentData=this.readPixels(0,0,this._contentData),this._contentUpdateId=this._frameId),this._contentData},t.prototype._createIndexBuffer=function(){var e=this._fullEngine,n=[];n.push(0),n.push(1),n.push(2),n.push(0),n.push(2),n.push(3),this._indexBuffer=e.createIndexBuffer(n)},t.prototype._rebuild=function(){var e=this._vertexBuffers[Oe.b.PositionKind];e&&e._rebuild(),this._createIndexBuffer(),this.refreshRate===sn.REFRESHRATE_RENDER_ONCE&&(this.refreshRate=sn.REFRESHRATE_RENDER_ONCE)},t.prototype.reset=function(){this._effect!==void 0&&this._effect.dispose()},t.prototype._getDefines=function(){return""},t.prototype.isReady=function(){var e,n=this,i=this._fullEngine;if(this.nodeMaterialSource)return this._effect.isReady();if(!this._fragment)return!1;if(this._fallbackTextureUsed)return!0;var o=this._getDefines();return!(!this._effect||o!==this._cachedDefines||!this._effect.isReady())||(e=this._fragment.fragmentElement!==void 0?{vertex:"procedural",fragmentElement:this._fragment.fragmentElement}:{vertex:"procedural",fragment:this._fragment},this._cachedDefines=o,this._effect=i.createEffect(e,[Oe.b.PositionKind],this._uniforms,this._samplers,o,void 0,void 0,function(){n.releaseInternalTexture(),n._fallbackTexture&&(n._texture=n._fallbackTexture._texture,n._texture&&n._texture.incrementReferences()),n._fallbackTextureUsed=!0}),this._effect.isReady())},t.prototype.resetRefreshCounter=function(){this._currentRefreshId=-1},t.prototype.setFragment=function(e){this._fragment=e},Object.defineProperty(t.prototype,"refreshRate",{get:function(){return this._refreshRate},set:function(e){this._refreshRate=e,this.resetRefreshCounter()},enumerable:!1,configurable:!0}),t.prototype._shouldRender=function(){return this.isEnabled&&this.isReady()&&this._texture?!this._fallbackTextureUsed&&(this._currentRefreshId===-1||this.refreshRate===this._currentRefreshId?(this._currentRefreshId=1,this._frameId++,!0):(this._currentRefreshId++,!1)):(this._texture&&(this._texture.isReady=!1),!1)},t.prototype.getRenderSize=function(){return this._size},t.prototype.resize=function(e,n){this._fallbackTextureUsed||(this.releaseInternalTexture(),this._texture=this._fullEngine.createRenderTargetTexture(e,n),this._size=e,this._generateMipMaps=n)},t.prototype._checkUniform=function(e){this._uniforms.indexOf(e)===-1&&this._uniforms.push(e)},t.prototype.setTexture=function(e,n){return this._samplers.indexOf(e)===-1&&this._samplers.push(e),this._textures[e]=n,this},t.prototype.setFloat=function(e,n){return this._checkUniform(e),this._floats[e]=n,this},t.prototype.setInt=function(e,n){return this._checkUniform(e),this._ints[e]=n,this},t.prototype.setFloats=function(e,n){return this._checkUniform(e),this._floatsArrays[e]=n,this},t.prototype.setColor3=function(e,n){return this._checkUniform(e),this._colors3[e]=n,this},t.prototype.setColor4=function(e,n){return this._checkUniform(e),this._colors4[e]=n,this},t.prototype.setVector2=function(e,n){return this._checkUniform(e),this._vectors2[e]=n,this},t.prototype.setVector3=function(e,n){return this._checkUniform(e),this._vectors3[e]=n,this},t.prototype.setMatrix=function(e,n){return this._checkUniform(e),this._matrices[e]=n,this},t.prototype.render=function(e){var n=this.getScene();if(n){var i=this._fullEngine;if(i.enableEffect(this._effect),this.onBeforeGenerationObservable.notifyObservers(this),i.setState(!1),!this.nodeMaterialSource){for(var o in this._textures)this._effect.setTexture(o,this._textures[o]);for(o in this._ints)this._effect.setInt(o,this._ints[o]);for(o in this._floats)this._effect.setFloat(o,this._floats[o]);for(o in this._floatsArrays)this._effect.setArray(o,this._floatsArrays[o]);for(o in this._colors3)this._effect.setColor3(o,this._colors3[o]);for(o in this._colors4){var a=this._colors4[o];this._effect.setFloat4(o,a.r,a.g,a.b,a.a)}for(o in this._vectors2)this._effect.setVector2(o,this._vectors2[o]);for(o in this._vectors3)this._effect.setVector3(o,this._vectors3[o]);for(o in this._matrices)this._effect.setMatrix(o,this._matrices[o])}if(this._texture){if(this.isCube)for(var s=0;s<6;s++)i.bindFramebuffer(this._texture,s,void 0,void 0,!0),i.bindBuffers(this._vertexBuffers,this._indexBuffer,this._effect),this._effect.setFloat("face",s),this.autoClear&&i.clear(n.clearColor,!0,!1,!1),i.drawElementsType(Ht.a.TriangleFillMode,0,6),s===5&&i.generateMipMapsForCubemap(this._texture);else i.bindFramebuffer(this._texture,0,void 0,void 0,!0),i.bindBuffers(this._vertexBuffers,this._indexBuffer,this._effect),this.autoClear&&i.clear(n.clearColor,!0,!1,!1),i.drawElementsType(Ht.a.TriangleFillMode,0,6);i.unBindFramebuffer(this._texture,this.isCube),this.onGenerated&&this.onGenerated(),this.onGeneratedObservable.notifyObservers(this)}}},t.prototype.clone=function(){var e=this.getSize(),n=new t(this.name,e.width,this._fragment,this.getScene(),this._fallbackTexture,this._generateMipMaps);return n.hasAlpha=this.hasAlpha,n.level=this.level,n.coordinatesMode=this.coordinatesMode,n},t.prototype.dispose=function(){var e=this.getScene();if(e){var n=e.proceduralTextures.indexOf(this);n>=0&&e.proceduralTextures.splice(n,1);var i=this._vertexBuffers[Oe.b.PositionKind];i&&(i.dispose(),this._vertexBuffers[Oe.b.PositionKind]=null),this._indexBuffer&&this._fullEngine._releaseBuffer(this._indexBuffer)&&(this._indexBuffer=null),this.onGeneratedObservable.clear(),this.onBeforeGenerationObservable.clear(),r.prototype.dispose.call(this)}},Object(c.c)([Object(L.c)()],t.prototype,"isEnabled",void 0),Object(c.c)([Object(L.c)()],t.prototype,"autoClear",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_generateMipMaps",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_size",void 0),Object(c.c)([Object(L.c)()],t.prototype,"refreshRate",null),t}(we.a);R.a.RegisteredTypes["BABYLON.ProceduralTexture"]=go;var nm=function(r){function t(e,n,i,o,a,s){var d=r.call(this,e,i,null,o,a,s)||this;return d._animate=!0,d._time=0,d._texturePath=n,d._loadJson(n),d.refreshRate=1,d}return Object(c.d)(t,r),t.prototype._loadJson=function(e){var n=this,i=function(){try{n.setFragment(n._texturePath)}catch{l.a.Error("No json or ShaderStore or DOM element found for CustomProceduralTexture")}},o=e+"/config.json",a=new re.a;a.open("GET",o),a.addEventListener("load",function(){if(a.status===200||a.responseText&&a.responseText.length>0)try{n._config=JSON.parse(a.response),n.updateShaderUniforms(),n.updateTextures(),n.setFragment(n._texturePath+"/custom"),n._animate=n._config.animate,n.refreshRate=n._config.refreshrate}catch{i()}else i()},!1),a.addEventListener("error",function(){i()},!1);try{a.send()}catch{l.a.Error("CustomProceduralTexture: Error on XHR send request.")}},t.prototype.isReady=function(){if(!r.prototype.isReady.call(this))return!1;for(var e in this._textures)if(!this._textures[e].isReady())return!1;return!0},t.prototype.render=function(e){var n=this.getScene();this._animate&&n&&(this._time+=.03*n.getAnimationRatio(),this.updateShaderUniforms()),r.prototype.render.call(this,e)},t.prototype.updateTextures=function(){for(var e=0;e<this._config.sampler2Ds.length;e++)this.setTexture(this._config.sampler2Ds[e].sample2Dname,new we.a(this._texturePath+"/"+this._config.sampler2Ds[e].textureRelativeUrl,this.getScene()))},t.prototype.updateShaderUniforms=function(){if(this._config)for(var e=0;e<this._config.uniforms.length;e++){var n=this._config.uniforms[e];switch(n.type){case"float":this.setFloat(n.name,n.value);break;case"color3":this.setColor3(n.name,new M.a(n.r,n.g,n.b));break;case"color4":this.setColor4(n.name,new M.b(n.r,n.g,n.b,n.a));break;case"vector2":this.setVector2(n.name,new u.d(n.x,n.y));break;case"vector3":this.setVector3(n.name,new u.e(n.x,n.y,n.z))}}this.setFloat("time",this._time)},Object.defineProperty(t.prototype,"animate",{get:function(){return this._animate},set:function(e){this._animate=e},enumerable:!1,configurable:!0}),t}(go),im=`
-
-uniform float brightness;
-uniform float persistence;
-uniform float timeScale;
-
-varying vec2 vUV;
-
-vec2 hash22(vec2 p)
-{
-p=p*mat2(127.1,311.7,269.5,183.3);
-p=-1.0+2.0*fract(sin(p)*43758.5453123);
-return sin(p*6.283+timeScale);
-}
-float interpolationNoise(vec2 p)
-{
-vec2 pi=floor(p);
-vec2 pf=p-pi;
-vec2 w=pf*pf*(3.-2.*pf);
-float f00=dot(hash22(pi+vec2(.0,.0)),pf-vec2(.0,.0));
-float f01=dot(hash22(pi+vec2(.0,1.)),pf-vec2(.0,1.));
-float f10=dot(hash22(pi+vec2(1.0,0.)),pf-vec2(1.0,0.));
-float f11=dot(hash22(pi+vec2(1.0,1.)),pf-vec2(1.0,1.));
-float xm1=mix(f00,f10,w.x);
-float xm2=mix(f01,f11,w.x);
-float ym=mix(xm1,xm2,w.y);
-return ym;
-}
-float perlinNoise2D(float x,float y)
-{
-float sum=0.0;
-float frequency=0.0;
-float amplitude=0.0;
-for(int i=0; i<OCTAVES; i++)
-{
-frequency=pow(2.0,float(i));
-amplitude=pow(persistence,float(i));
-sum=sum+interpolationNoise(vec2(x*frequency,y*frequency))*amplitude;
-}
-return sum;
-}
-
-void main(void)
-{
-float x=abs(vUV.x);
-float y=abs(vUV.y);
-float noise=brightness+(1.0-brightness)*perlinNoise2D(x,y);
-gl_FragColor=vec4(noise,noise,noise,1.0);
-}
-`;ze.a.ShadersStore.noisePixelShader=im;var ch=function(r){function t(e,n,i,o,a){n===void 0&&(n=256),i===void 0&&(i=te.a.LastCreatedScene);var s=r.call(this,e,n,"noise",i,o,a)||this;return s.time=0,s.brightness=.2,s.octaves=3,s.persistence=.8,s.animationSpeedFactor=1,s.autoClear=!1,s._updateShaderUniforms(),s}return Object(c.d)(t,r),t.prototype._updateShaderUniforms=function(){var e=this.getScene();e&&(this.time+=e.getAnimationRatio()*this.animationSpeedFactor*.01,this.setFloat("brightness",this.brightness),this.setFloat("persistence",this.persistence),this.setFloat("timeScale",this.time))},t.prototype._getDefines=function(){return"#define OCTAVES "+(0|this.octaves)},t.prototype.render=function(e){this._updateShaderUniforms(),r.prototype.render.call(this,e)},t.prototype.serialize=function(){var e={customType:"BABYLON.NoiseProceduralTexture"};return e.brightness=this.brightness,e.octaves=this.octaves,e.persistence=this.persistence,e.animationSpeedFactor=this.animationSpeedFactor,e.size=this.getSize().width,e.generateMipMaps=this._generateMipMaps,e.time=this.time,e},t.prototype.clone=function(){var e=this.getSize(),n=new t(this.name,e.width,this.getScene(),this._fallbackTexture?this._fallbackTexture:void 0,this._generateMipMaps);return n.hasAlpha=this.hasAlpha,n.level=this.level,n.coordinatesMode=this.coordinatesMode,n.brightness=this.brightness,n.octaves=this.octaves,n.persistence=this.persistence,n.animationSpeedFactor=this.animationSpeedFactor,n.time=this.time,n},t.Parse=function(e,n){var i,o=new t(e.name,e.size,n,void 0,e.generateMipMaps);return o.brightness=e.brightness,o.octaves=e.octaves,o.persistence=e.persistence,o.animationSpeedFactor=e.animationSpeedFactor,o.time=(i=e.time)!==null&&i!==void 0?i:0,o},t}(go);R.a.RegisteredTypes["BABYLON.NoiseProceduralTexture"]=ch;var xe,le,bn,bt,Mn,li,Tn,rm=function(r){function t(e,n,i,o,a,s,d,p,b){o===void 0&&(o=h.a.TEXTUREFORMAT_RGBA),a===void 0&&(a=h.a.TEXTURETYPE_UNSIGNED_INT),s===void 0&&(s=!1),d===void 0&&(d=!1),p===void 0&&(p=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE),b===void 0&&(b=null);var P=r.call(this,"",e)||this;return P._texture=e.getEngine().createRawCubeTexture(n,i,o,a,s,d,p,b),P}return Object(c.d)(t,r),t.prototype.update=function(e,n,i,o,a){a===void 0&&(a=null),this._texture.getEngine().updateRawCubeTexture(this._texture,e,n,i,o,a)},t.prototype.updateRGBDAsync=function(e,n,i,o){return n===void 0&&(n=null),i===void 0&&(i=.8),o===void 0&&(o=0),t._UpdateRGBDAsync(this._texture,e,n,i,o)},t.prototype.clone=function(){var e=this;return L.a.Clone(function(){var n=e.getScene(),i=e._texture,o=new t(n,i._bufferViewArray,i.width,i.format,i.type,i.generateMipMaps,i.invertY,i.samplingMode,i._compression);return i.source===xt.b.CubeRawRGBD&&o.updateRGBDAsync(i._bufferViewArrayArray,i._sphericalPolynomial,i._lodGenerationScale,i._lodGenerationOffset),o},this)},t._UpdateRGBDAsync=function(e,n,i,o,a){return e._source=xt.b.CubeRawRGBD,e._bufferViewArrayArray=n,e._lodGenerationScale=o,e._lodGenerationOffset=a,e._sphericalPolynomial=i,Ai.UploadLevelsAsync(e,n).then(function(){e.isReady=!0})},t}(ai),om=function(r){function t(e,n,i,o,a,s,d,p,b,P){d===void 0&&(d=!0),p===void 0&&(p=!1),b===void 0&&(b=we.a.TRILINEAR_SAMPLINGMODE),P===void 0&&(P=h.a.TEXTURETYPE_UNSIGNED_INT);var O=r.call(this,null,s,!d,p)||this;return O.format=a,O._texture=s.getEngine().createRawTexture2DArray(e,n,i,o,a,d,p,b,null,P),O.is2DArray=!0,O}return Object(c.d)(t,r),t.prototype.update=function(e){this._texture&&this._getEngine().updateRawTexture2DArray(this._texture,e,this._texture.format,this._texture.invertY,null,this._texture.type)},t}(we.a),am=function(r){function t(e,n,i,o,a,s,d,p,b,P){d===void 0&&(d=!0),p===void 0&&(p=!1),b===void 0&&(b=we.a.TRILINEAR_SAMPLINGMODE),P===void 0&&(P=h.a.TEXTURETYPE_UNSIGNED_INT);var O=r.call(this,null,s,!d,p)||this;return O.format=a,O._texture=s.getEngine().createRawTexture3D(e,n,i,o,a,d,p,b,null,P),O.is3D=!0,O}return Object(c.d)(t,r),t.prototype.update=function(e){this._texture&&this._getEngine().updateRawTexture3D(this._texture,e,this._texture.format,this._texture.invertY,null,this._texture.type)},t}(we.a),sm=function(r){function t(e,n,i,o){var a=r.call(this,e,n,i,o,!0)||this;return a.refractionPlane=new vr.a(0,1,0,1),a.depth=2,a.onBeforeRenderObservable.add(function(){i.clipPlane=a.refractionPlane}),a.onAfterRenderObservable.add(function(){i.clipPlane=null}),a}return Object(c.d)(t,r),t.prototype.clone=function(){var e=this.getScene();if(!e)return this;var n=this.getSize(),i=new t(this.name,n.width,e,this._generateMipMaps);return i.hasAlpha=this.hasAlpha,i.level=this.level,i.refractionPlane=this.refractionPlane.clone(),this.renderList&&(i.renderList=this.renderList.slice(0)),i.depth=this.depth,i},t.prototype.serialize=function(){if(!this.name)return null;var e=r.prototype.serialize.call(this);return e.mirrorPlane=this.refractionPlane.asArray(),e.depth=this.depth,e},t}(sn);(function(r){r[r.Vertex=1]="Vertex",r[r.Fragment=2]="Fragment",r[r.Neutral=4]="Neutral",r[r.VertexAndFragment=3]="VertexAndFragment"})(xe||(xe={})),function(r){r[r.Float=1]="Float",r[r.Int=2]="Int",r[r.Vector2=4]="Vector2",r[r.Vector3=8]="Vector3",r[r.Vector4=16]="Vector4",r[r.Color3=32]="Color3",r[r.Color4=64]="Color4",r[r.Matrix=128]="Matrix",r[r.Object=256]="Object",r[r.AutoDetect=1024]="AutoDetect",r[r.BasedOnInput=2048]="BasedOnInput"}(le||(le={})),function(r){r[r.Uniform=0]="Uniform",r[r.Attribute=1]="Attribute",r[r.Varying=2]="Varying",r[r.Undefined=3]="Undefined"}(bn||(bn={})),function(r){r[r.World=1]="World",r[r.View=2]="View",r[r.Projection=3]="Projection",r[r.ViewProjection=4]="ViewProjection",r[r.WorldView=5]="WorldView",r[r.WorldViewProjection=6]="WorldViewProjection",r[r.CameraPosition=7]="CameraPosition",r[r.FogColor=8]="FogColor",r[r.DeltaTime=9]="DeltaTime"}(bt||(bt={})),function(r){r[r.Material=0]="Material",r[r.PostProcess=1]="PostProcess",r[r.Particle=2]="Particle",r[r.ProceduralTexture=3]="ProceduralTexture"}(Mn||(Mn={})),function(r){r[r.Compatible=0]="Compatible",r[r.TypeIncompatible=1]="TypeIncompatible",r[r.TargetIncompatible=2]="TargetIncompatible"}(li||(li={})),function(r){r[r.Input=0]="Input",r[r.Output=1]="Output"}(Tn||(Tn={}));var da=function(){function r(t,e,n){this._connectedPoint=null,this._endpoints=new Array,this._typeConnectionSource=null,this._linkedConnectionSource=null,this._acceptedConnectionPointType=null,this._type=le.Float,this._enforceAssociatedVariableName=!1,this.needDualDirectionValidation=!1,this.acceptedConnectionPointTypes=new Array,this.excludedConnectionPointTypes=new Array,this.onConnectionObservable=new x.c,this.isExposedOnFrame=!1,this.exposedPortPosition=-1,this._prioritizeVertex=!1,this._target=xe.VertexAndFragment,this._ownerBlock=e,this.name=t,this._direction=n}return r.AreEquivalentTypes=function(t,e){switch(t){case le.Vector3:if(e===le.Color3)return!0;break;case le.Vector4:if(e===le.Color4)return!0;break;case le.Color3:if(e===le.Vector3)return!0;break;case le.Color4:if(e===le.Vector4)return!0}return!1},Object.defineProperty(r.prototype,"direction",{get:function(){return this._direction},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"associatedVariableName",{get:function(){return this._ownerBlock.isInput?this._ownerBlock.associatedVariableName:this._enforceAssociatedVariableName&&this._associatedVariableName||!this._connectedPoint?this._associatedVariableName:this._connectedPoint.associatedVariableName},set:function(t){this._associatedVariableName=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"innerType",{get:function(){return this._linkedConnectionSource&&this._linkedConnectionSource.isConnected?this.type:this._type},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"type",{get:function(){if(this._type===le.AutoDetect){if(this._ownerBlock.isInput)return this._ownerBlock.type;if(this._connectedPoint)return this._connectedPoint.type;if(this._linkedConnectionSource&&this._linkedConnectionSource.isConnected)return this._linkedConnectionSource.type}return this._type===le.BasedOnInput&&this._typeConnectionSource?this._typeConnectionSource.type:this._type},set:function(t){this._type=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"target",{get:function(){return this._prioritizeVertex&&this._ownerBlock?this._target!==xe.VertexAndFragment?this._target:this._ownerBlock.target===xe.Fragment?xe.Fragment:xe.Vertex:this._target},set:function(t){this._target=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isConnected",{get:function(){return this.connectedPoint!==null||this.hasEndpoints},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isConnectedToInputBlock",{get:function(){return this.connectedPoint!==null&&this.connectedPoint.ownerBlock.isInput},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"connectInputBlock",{get:function(){return this.isConnectedToInputBlock?this.connectedPoint.ownerBlock:null},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"connectedPoint",{get:function(){return this._connectedPoint},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"ownerBlock",{get:function(){return this._ownerBlock},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"sourceBlock",{get:function(){return this._connectedPoint?this._connectedPoint.ownerBlock:null},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"connectedBlocks",{get:function(){return this._endpoints.length===0?[]:this._endpoints.map(function(t){return t.ownerBlock})},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"endpoints",{get:function(){return this._endpoints},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hasEndpoints",{get:function(){return this._endpoints&&this._endpoints.length>0},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isConnectedInVertexShader",{get:function(){if(this.target===xe.Vertex)return!0;if(!this.hasEndpoints)return!1;for(var t=0,e=this._endpoints;t<e.length;t++){var n=e[t];if(n.ownerBlock.target===xe.Vertex||n.target===xe.Vertex||(n.ownerBlock.target===xe.Neutral||n.ownerBlock.target===xe.VertexAndFragment)&&n.ownerBlock.outputs.some(function(i){return i.isConnectedInVertexShader}))return!0}return!1},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isConnectedInFragmentShader",{get:function(){if(this.target===xe.Fragment)return!0;if(!this.hasEndpoints)return!1;for(var t=0,e=this._endpoints;t<e.length;t++){var n=e[t];if(n.ownerBlock.target===xe.Fragment||(n.ownerBlock.target===xe.Neutral||n.ownerBlock.target===xe.VertexAndFragment)&&n.ownerBlock.outputs.some(function(i){return i.isConnectedInFragmentShader}))return!0}return!1},enumerable:!1,configurable:!0}),r.prototype.createCustomInputBlock=function(){return null},r.prototype.getClassName=function(){return"NodeMaterialConnectionPoint"},r.prototype.canConnectTo=function(t){return this.checkCompatibilityState(t)===li.Compatible},r.prototype.checkCompatibilityState=function(t){if(this._ownerBlock.target===xe.Fragment){var e=t.ownerBlock;if(e.target===xe.Vertex)return li.TargetIncompatible;for(var n=0,i=e.outputs;n<i.length;n++)if(i[n].isConnectedInVertexShader)return li.TargetIncompatible}return this.type!==t.type&&t.innerType!==le.AutoDetect?r.AreEquivalentTypes(this.type,t.type)||t.acceptedConnectionPointTypes&&t.acceptedConnectionPointTypes.indexOf(this.type)!==-1||t._acceptedConnectionPointType&&r.AreEquivalentTypes(t._acceptedConnectionPointType.type,this.type)?li.Compatible:li.TypeIncompatible:t.excludedConnectionPointTypes&&t.excludedConnectionPointTypes.indexOf(this.type)!==-1?1:li.Compatible},r.prototype.connectTo=function(t,e){if(e===void 0&&(e=!1),!e&&!this.canConnectTo(t))throw"Cannot connect these two connectors.";return this._endpoints.push(t),t._connectedPoint=this,this._enforceAssociatedVariableName=!1,this.onConnectionObservable.notifyObservers(t),t.onConnectionObservable.notifyObservers(this),this},r.prototype.disconnectFrom=function(t){var e=this._endpoints.indexOf(t);return e===-1||(this._endpoints.splice(e,1),t._connectedPoint=null,this._enforceAssociatedVariableName=!1,t._enforceAssociatedVariableName=!1),this},r.prototype.serialize=function(t){t===void 0&&(t=!0);var e={};return e.name=this.name,e.displayName=this.displayName,t&&this.connectedPoint&&(e.inputName=this.name,e.targetBlockId=this.connectedPoint.ownerBlock.uniqueId,e.targetConnectionName=this.connectedPoint.name,e.isExposedOnFrame=!0,e.exposedPortPosition=this.exposedPortPosition),(this.isExposedOnFrame||this.exposedPortPosition>=0)&&(e.isExposedOnFrame=!0,e.exposedPortPosition=this.exposedPortPosition),e},r.prototype.dispose=function(){this.onConnectionObservable.clear()},r}(),cm=f(152),pt=function(){function r(t,e,n,i){e===void 0&&(e=xe.Vertex),n===void 0&&(n=!1),i===void 0&&(i=!1),this._isFinalMerger=!1,this._isInput=!1,this._name="",this._isUnique=!1,this.inputsAreExclusive=!1,this._codeVariableName="",this._inputs=new Array,this._outputs=new Array,this.comments="",this.visibleInInspector=!1,this._target=e,this._isFinalMerger=n,this._isInput=i,this._name=t,this.uniqueId=cm.a.UniqueId}return Object.defineProperty(r.prototype,"name",{get:function(){return this._name},set:function(t){this.validateBlockName(t)&&(this._name=t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isUnique",{get:function(){return this._isUnique},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isFinalMerger",{get:function(){return this._isFinalMerger},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isInput",{get:function(){return this._isInput},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"buildId",{get:function(){return this._buildId},set:function(t){this._buildId=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"target",{get:function(){return this._target},set:function(t){!(this._target&t)&&(this._target=t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"inputs",{get:function(){return this._inputs},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"outputs",{get:function(){return this._outputs},enumerable:!1,configurable:!0}),r.prototype.getInputByName=function(t){var e=this._inputs.filter(function(n){return n.name===t});return e.length?e[0]:null},r.prototype.getOutputByName=function(t){var e=this._outputs.filter(function(n){return n.name===t});return e.length?e[0]:null},r.prototype.initialize=function(t){},r.prototype.bind=function(t,e,n,i){},r.prototype._declareOutput=function(t,e){return e._getGLType(t.type)+" "+t.associatedVariableName},r.prototype._writeVariable=function(t){return t.connectedPoint?""+t.associatedVariableName:"0."},r.prototype._writeFloat=function(t){var e=t.toString();return e.indexOf(".")===-1&&(e+=".0"),""+e},r.prototype.getClassName=function(){return"NodeMaterialBlock"},r.prototype.registerInput=function(t,e,n,i,o){return n===void 0&&(n=!1),(o=o??new da(t,this,Tn.Input)).type=e,o.isOptional=n,i&&(o.target=i),this._inputs.push(o),this},r.prototype.registerOutput=function(t,e,n,i){return(i=i??new da(t,this,Tn.Output)).type=e,n&&(i.target=n),this._outputs.push(i),this},r.prototype.getFirstAvailableInput=function(t){t===void 0&&(t=null);for(var e=0,n=this._inputs;e<n.length;e++){var i=n[e];if(!(i.connectedPoint||t&&t.type!==i.type&&i.type!==le.AutoDetect))return i}return null},r.prototype.getFirstAvailableOutput=function(t){t===void 0&&(t=null);for(var e=0,n=this._outputs;e<n.length;e++){var i=n[e];if(!t||!t.target||t.target===xe.Neutral||t.target&i.target)return i}return null},r.prototype.getSiblingOutput=function(t){var e=this._outputs.indexOf(t);return e===-1||e>=this._outputs.length?null:this._outputs[e+1]},r.prototype.connectTo=function(t,e){if(this._outputs.length!==0){for(var n=e&&e.output?this.getOutputByName(e.output):this.getFirstAvailableOutput(t),i=!0;i;){var o=e&&e.input?t.getInputByName(e.input):t.getFirstAvailableInput(n);if(n&&o&&n.canConnectTo(o))n.connectTo(o),i=!1;else{if(!n)throw"Unable to find a compatible match";n=this.getSiblingOutput(n)}}return this}},r.prototype._buildBlock=function(t){},r.prototype.updateUniformsAndSamples=function(t,e,n,i){},r.prototype.provideFallbacks=function(t,e){},r.prototype.initializeDefines=function(t,e,n,i){},r.prototype.prepareDefines=function(t,e,n,i,o){},r.prototype.autoConfigure=function(t){},r.prototype.replaceRepeatableContent=function(t,e,n,i){},r.prototype.isReady=function(t,e,n,i){return!0},r.prototype._linkConnectionTypes=function(t,e,n){n===void 0&&(n=!1),n?this._inputs[e]._acceptedConnectionPointType=this._inputs[t]:this._inputs[t]._linkedConnectionSource=this._inputs[e],this._inputs[e]._linkedConnectionSource=this._inputs[t]},r.prototype._processBuild=function(t,e,n,i){t.build(e,i);var o=e._vertexState!=null,a=t._buildTarget===xe.Vertex&&t.target!==xe.VertexAndFragment;if(o&&(!(t.target&t._buildTarget)||!(t.target&n.target)||this.target!==xe.VertexAndFragment&&a)&&(!t.isInput&&e.target!==t._buildTarget||t.isInput&&t.isAttribute&&!t._noContextSwitch)){var s=n.connectedPoint;e._vertexState._emitVaryingFromString("v_"+s.associatedVariableName,e._getGLType(s.type))&&(e._vertexState.compilationString+="v_"+s.associatedVariableName+" = "+s.associatedVariableName+`;\r
-`),n.associatedVariableName="v_"+s.associatedVariableName,n._enforceAssociatedVariableName=!0}},r.prototype.validateBlockName=function(t){for(var e=0,n=["position","normal","tangent","particle_positionw","uv","uv2","position2d","particle_uv","matricesIndices","matricesWeights","world0","world1","world2","world3","particle_color","particle_texturemask"];e<n.length;e++)if(t===n[e])return!1;return!0},r.prototype.build=function(t,e){if(this._buildId===t.sharedData.buildId)return!0;if(!this.isInput)for(var n=0,i=this._outputs;n<i.length;n++)(b=i[n]).associatedVariableName||(b.associatedVariableName=t._getFreeVariableName(b.name));for(var o=0,a=this._inputs;o<a.length;o++){var s=a[o];if(s.connectedPoint){if(this.target!==xe.Neutral&&(!(s.target&this.target)||!(s.target&t.target)))continue;(B=s.connectedPoint.ownerBlock)&&B!==this&&this._processBuild(B,t,s,e)}else s.isOptional||t.sharedData.checks.notConnectedNonOptionalInputs.push(s)}if(this._buildId===t.sharedData.buildId)return!0;if(t.sharedData.verbose&&console.log((t.target===xe.Vertex?"Vertex shader":"Fragment shader")+": Building "+this.name+" ["+this.getClassName()+"]"),this.isFinalMerger)switch(t.target){case xe.Vertex:t.sharedData.checks.emitVertex=!0;break;case xe.Fragment:t.sharedData.checks.emitFragment=!0}!this.isInput&&t.sharedData.emitComments&&(t.compilationString+=`\r
-//`+this.name+`\r
-`),this._buildBlock(t),this._buildId=t.sharedData.buildId,this._buildTarget=t.target;for(var d=0,p=this._outputs;d<p.length;d++){var b;if((b=p[d]).target&t.target)for(var P=0,O=b.endpoints;P<O.length;P++){var B,F=O[P];(B=F.ownerBlock)&&B.target&t.target&&e.indexOf(B)!==-1&&this._processBuild(B,t,F,e)}}return!1},r.prototype._inputRename=function(t){return t},r.prototype._outputRename=function(t){return t},r.prototype._dumpPropertiesCode=function(){return this._codeVariableName+".visibleInInspector = "+this.visibleInInspector+`;\r
-`},r.prototype._dumpCode=function(t,e){var n;e.push(this);var i=this.name.replace(/[^A-Za-z_]+/g,"");if(this._codeVariableName=i||this.getClassName()+"_"+this.uniqueId,t.indexOf(this._codeVariableName)!==-1){var o=0;do o++,this._codeVariableName=i+o;while(t.indexOf(this._codeVariableName)!==-1)}t.push(this._codeVariableName),n=`\r
-// `+this.getClassName()+`\r
-`,this.comments&&(n+="// "+this.comments+`\r
-`),n+="var "+this._codeVariableName+" = new BABYLON."+this.getClassName()+'("'+this.name+`");\r
-`,n+=this._dumpPropertiesCode();for(var a=0,s=this.inputs;a<s.length;a++){var d=s[a];if(d.isConnected){var p=d.connectedPoint.ownerBlock;e.indexOf(p)===-1&&(n+=p._dumpCode(t,e))}}for(var b=0,P=this.outputs;b<P.length;b++){var O=P[b];if(O.hasEndpoints)for(var B=0,F=O.endpoints;B<F.length;B++)(p=F[B].ownerBlock)&&e.indexOf(p)===-1&&(n+=p._dumpCode(t,e))}return n},r.prototype._dumpCodeForOutputConnections=function(t){var e="";if(t.indexOf(this)!==-1)return e;t.push(this);for(var n=0,i=this.inputs;n<i.length;n++){var o=i[n];if(o.isConnected){var a=o.connectedPoint,s=a.ownerBlock;e+=s._dumpCodeForOutputConnections(t),e+=s._codeVariableName+"."+s._outputRename(a.name)+".connectTo("+this._codeVariableName+"."+this._inputRename(o.name)+`);\r
-`}}return e},r.prototype.clone=function(t,e){e===void 0&&(e="");var n=this.serialize(),i=R.a.GetClass(n.customType);if(i){var o=new i;return o._deserialize(n,t,e),o}return null},r.prototype.serialize=function(){var t={};t.customType="BABYLON."+this.getClassName(),t.id=this.uniqueId,t.name=this.name,t.comments=this.comments,t.visibleInInspector=this.visibleInInspector,t.inputs=[],t.outputs=[];for(var e=0,n=this.inputs;e<n.length;e++){var i=n[e];t.inputs.push(i.serialize())}for(var o=0,a=this.outputs;o<a.length;o++){var s=a[o];t.outputs.push(s.serialize(!1))}return t},r.prototype._deserialize=function(t,e,n){this.name=t.name,this.comments=t.comments,this.visibleInInspector=!!t.visibleInInspector,this._deserializePortDisplayNamesAndExposedOnFrame(t)},r.prototype._deserializePortDisplayNamesAndExposedOnFrame=function(t){var e=this,n=t.inputs,i=t.outputs;n&&n.forEach(function(o,a){o.displayName&&(e.inputs[a].displayName=o.displayName),o.isExposedOnFrame&&(e.inputs[a].isExposedOnFrame=o.isExposedOnFrame,e.inputs[a].exposedPortPosition=o.exposedPortPosition)}),i&&i.forEach(function(o,a){o.displayName&&(e.outputs[a].displayName=o.displayName),o.isExposedOnFrame&&(e.outputs[a].isExposedOnFrame=o.isExposedOnFrame,e.outputs[a].exposedPortPosition=o.exposedPortPosition)})},r.prototype.dispose=function(){for(var t=0,e=this.inputs;t<e.length;t++)e[t].dispose();for(var n=0,i=this.outputs;n<i.length;n++)i[n].dispose()},r}(),lh=function(){function r(){this.supportUniformBuffers=!1,this.attributes=new Array,this.uniforms=new Array,this.constants=new Array,this.samplers=new Array,this.functions={},this.extensions={},this.counters={},this._attributeDeclaration="",this._uniformDeclaration="",this._constantDeclaration="",this._samplerDeclaration="",this._varyingTransfer="",this._injectAtEnd="",this._repeatableContentAnchorIndex=0,this._builtCompilationString="",this.compilationString=""}return r.prototype.finalize=function(t){var e=t.sharedData.emitComments,n=this.target===xe.Fragment;this.compilationString=`\r
-`+(e?`//Entry point\r
-`:"")+`void main(void) {\r
-`+this.compilationString,this._constantDeclaration&&(this.compilationString=`\r
-`+(e?`//Constants\r
-`:"")+this._constantDeclaration+`\r
-`+this.compilationString);var i="";for(var o in this.functions)i+=this.functions[o]+`\r
-`;for(var a in this.compilationString=`\r
-`+i+`\r
-`+this.compilationString,!n&&this._varyingTransfer&&(this.compilationString=this.compilationString+`\r
-`+this._varyingTransfer),this._injectAtEnd&&(this.compilationString=this.compilationString+`\r
-`+this._injectAtEnd),this.compilationString=this.compilationString+`\r
-}`,this.sharedData.varyingDeclaration&&(this.compilationString=`\r
-`+(e?`//Varyings\r
-`:"")+this.sharedData.varyingDeclaration+`\r
-`+this.compilationString),this._samplerDeclaration&&(this.compilationString=`\r
-`+(e?`//Samplers\r
-`:"")+this._samplerDeclaration+`\r
-`+this.compilationString),this._uniformDeclaration&&(this.compilationString=`\r
-`+(e?`//Uniforms\r
-`:"")+this._uniformDeclaration+`\r
-`+this.compilationString),this._attributeDeclaration&&!n&&(this.compilationString=`\r
-`+(e?`//Attributes\r
-`:"")+this._attributeDeclaration+`\r
-`+this.compilationString),this.compilationString=`precision highp float;\r
-`+this.compilationString,this.extensions){var s=this.extensions[a];this.compilationString=`\r
-`+s+`\r
-`+this.compilationString}this._builtCompilationString=this.compilationString},Object.defineProperty(r.prototype,"_repeatableContentAnchor",{get:function(){return"###___ANCHOR"+this._repeatableContentAnchorIndex+++"___###"},enumerable:!1,configurable:!0}),r.prototype._getFreeVariableName=function(t){return t=t.replace(/[^a-zA-Z_]+/g,""),this.sharedData.variableNames[t]===void 0?(this.sharedData.variableNames[t]=0,t==="output"||t==="texture"?t+this.sharedData.variableNames[t]:t):(this.sharedData.variableNames[t]++,t+this.sharedData.variableNames[t])},r.prototype._getFreeDefineName=function(t){return this.sharedData.defineNames[t]===void 0?this.sharedData.defineNames[t]=0:this.sharedData.defineNames[t]++,t+this.sharedData.defineNames[t]},r.prototype._excludeVariableName=function(t){this.sharedData.variableNames[t]=0},r.prototype._emit2DSampler=function(t){this.samplers.indexOf(t)<0&&(this._samplerDeclaration+="uniform sampler2D "+t+`;\r
-`,this.samplers.push(t))},r.prototype._getGLType=function(t){switch(t){case le.Float:return"float";case le.Int:return"int";case le.Vector2:return"vec2";case le.Color3:case le.Vector3:return"vec3";case le.Color4:case le.Vector4:return"vec4";case le.Matrix:return"mat4"}return""},r.prototype._emitExtension=function(t,e,n){n===void 0&&(n=""),this.extensions[t]||(n&&(e="#if "+n+`\r
-`+e+`\r
-#endif`),this.extensions[t]=e)},r.prototype._emitFunction=function(t,e,n){this.functions[t]||(this.sharedData.emitComments&&(e=n+`\r
-`+e),this.functions[t]=e)},r.prototype._emitCodeFromInclude=function(t,e,n){if(n&&n.repeatKey)return"#include<"+t+">[0.."+n.repeatKey+`]\r
-`;var i=ze.a.IncludesShadersStore[t]+`\r
-`;if(this.sharedData.emitComments&&(i=e+`\r
-`+i),!n)return i;if(n.replaceStrings)for(var o=0;o<n.replaceStrings.length;o++){var a=n.replaceStrings[o];i=i.replace(a.search,a.replace)}return i},r.prototype._emitFunctionFromInclude=function(t,e,n,i){i===void 0&&(i="");var o=t+i;if(!this.functions[o]){if(!(n&&(n.removeAttributes||n.removeUniforms||n.removeVaryings||n.removeIfDef||n.replaceStrings)))return n&&n.repeatKey?this.functions[o]="#include<"+t+">[0.."+n.repeatKey+`]\r
-`:this.functions[o]="#include<"+t+`>\r
-`,void(this.sharedData.emitComments&&(this.functions[o]=e+`\r
-`+this.functions[o]));if(this.functions[o]=ze.a.IncludesShadersStore[t],this.sharedData.emitComments&&(this.functions[o]=e+`\r
-`+this.functions[o]),n.removeIfDef&&(this.functions[o]=this.functions[o].replace(/^\s*?#ifdef.+$/gm,""),this.functions[o]=this.functions[o].replace(/^\s*?#endif.*$/gm,""),this.functions[o]=this.functions[o].replace(/^\s*?#else.*$/gm,""),this.functions[o]=this.functions[o].replace(/^\s*?#elif.*$/gm,"")),n.removeAttributes&&(this.functions[o]=this.functions[o].replace(/^\s*?attribute.+$/gm,"")),n.removeUniforms&&(this.functions[o]=this.functions[o].replace(/^\s*?uniform.+$/gm,"")),n.removeVaryings&&(this.functions[o]=this.functions[o].replace(/^\s*?varying.+$/gm,"")),n.replaceStrings)for(var a=0;a<n.replaceStrings.length;a++){var s=n.replaceStrings[a];this.functions[o]=this.functions[o].replace(s.search,s.replace)}}},r.prototype._registerTempVariable=function(t){return this.sharedData.temps.indexOf(t)===-1&&(this.sharedData.temps.push(t),!0)},r.prototype._emitVaryingFromString=function(t,e,n,i){return n===void 0&&(n=""),i===void 0&&(i=!1),this.sharedData.varyings.indexOf(t)===-1&&(this.sharedData.varyings.push(t),n&&(Qn.a.StartsWith(n,"defined(")?this.sharedData.varyingDeclaration+="#if "+n+`\r
-`:this.sharedData.varyingDeclaration+=(i?"#ifndef":"#ifdef")+" "+n+`\r
-`),this.sharedData.varyingDeclaration+="varying "+e+" "+t+`;\r
-`,n&&(this.sharedData.varyingDeclaration+=`#endif\r
-`),!0)},r.prototype._emitUniformFromString=function(t,e,n,i){n===void 0&&(n=""),i===void 0&&(i=!1),this.uniforms.indexOf(t)===-1&&(this.uniforms.push(t),n&&(Qn.a.StartsWith(n,"defined(")?this._uniformDeclaration+="#if "+n+`\r
-`:this._uniformDeclaration+=(i?"#ifndef":"#ifdef")+" "+n+`\r
-`),this._uniformDeclaration+="uniform "+e+" "+t+`;\r
-`,n&&(this._uniformDeclaration+=`#endif\r
-`))},r.prototype._emitFloat=function(t){return t.toString()===t.toFixed(0)?t+".0":t.toString()},r}(),lm=function(){function r(){this.temps=new Array,this.varyings=new Array,this.varyingDeclaration="",this.inputBlocks=new Array,this.textureBlocks=new Array,this.bindableBlocks=new Array,this.blocksWithFallbacks=new Array,this.blocksWithDefines=new Array,this.repeatableContentBlocks=new Array,this.dynamicUniformBlocks=new Array,this.blockingBlocks=new Array,this.animatedInputs=new Array,this.variableNames={},this.defineNames={},this.hints={needWorldViewMatrix:!1,needWorldViewProjectionMatrix:!1,needAlphaBlending:!1,needAlphaTesting:!1},this.checks={emitVertex:!1,emitFragment:!1,notConnectedNonOptionalInputs:new Array},this.allowEmptyVertexProgram=!1,this.variableNames.position=0,this.variableNames.normal=0,this.variableNames.tangent=0,this.variableNames.uv=0,this.variableNames.uv2=0,this.variableNames.uv3=0,this.variableNames.uv4=0,this.variableNames.uv4=0,this.variableNames.uv5=0,this.variableNames.uv6=0,this.variableNames.color=0,this.variableNames.matricesIndices=0,this.variableNames.matricesWeights=0,this.variableNames.matricesIndicesExtra=0,this.variableNames.matricesWeightsExtra=0,this.variableNames.diffuseBase=0,this.variableNames.specularBase=0,this.variableNames.worldPos=0,this.variableNames.shadow=0,this.variableNames.view=0,this.variableNames.vTBN=0,this.defineNames.MAINUV0=0,this.defineNames.MAINUV1=0,this.defineNames.MAINUV2=0,this.defineNames.MAINUV3=0,this.defineNames.MAINUV4=0,this.defineNames.MAINUV5=0,this.defineNames.MAINUV6=0,this.defineNames.MAINUV7=0}return r.prototype.emitErrors=function(){var t="";this.checks.emitVertex||this.allowEmptyVertexProgram||(t+=`NodeMaterial does not have a vertex output. You need to at least add a block that generates a glPosition value.\r
-`),this.checks.emitFragment||(t+=`NodeMaterial does not have a fragment output. You need to at least add a block that generates a glFragColor value.\r
-`);for(var e=0,n=this.checks.notConnectedNonOptionalInputs;e<n.length;e++){var i=n[e];t+="input "+i.name+" from block "+i.ownerBlock.name+"["+i.ownerBlock.getClassName()+`] is not connected and is not optional.\r
-`}if(t)throw`Build of NodeMaterial failed:\r
-`+t},r}(),fa=function(r){function t(e){var n=r.call(this,e,xe.Vertex)||this;return n.complementW=1,n.complementZ=0,n.registerInput("vector",le.AutoDetect),n.registerInput("transform",le.Matrix),n.registerOutput("output",le.Vector4),n.registerOutput("xyz",le.Vector3),n._inputs[0].onConnectionObservable.add(function(i){if(i.ownerBlock.isInput){var o=i.ownerBlock;o.name!=="normal"&&o.name!=="tangent"||(n.complementW=0)}}),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"TransformBlock"},Object.defineProperty(t.prototype,"vector",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyz",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"transform",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this.vector,i=this.transform;if(n.connectedPoint){if(this.complementW===0){var o="//"+this.name;e._emitFunctionFromInclude("helperFunctions",o),e.sharedData.blocksWithDefines.push(this);var a=e._getFreeVariableName(i.associatedVariableName+"_NUS");switch(e.compilationString+="mat3 "+a+" = mat3("+i.associatedVariableName+`);\r
-`,e.compilationString+=`#ifdef NONUNIFORMSCALING\r
-`,e.compilationString+=a+" = transposeMat3(inverseMat3("+a+`));\r
-`,e.compilationString+=`#endif\r
-`,n.connectedPoint.type){case le.Vector2:e.compilationString+=this._declareOutput(this.output,e)+" = vec4("+a+" * vec3("+n.associatedVariableName+", "+this._writeFloat(this.complementZ)+"), "+this._writeFloat(this.complementW)+`);\r
-`;break;case le.Vector3:case le.Color3:e.compilationString+=this._declareOutput(this.output,e)+" = vec4("+a+" * "+n.associatedVariableName+", "+this._writeFloat(this.complementW)+`);\r
-`;break;default:e.compilationString+=this._declareOutput(this.output,e)+" = vec4("+a+" * "+n.associatedVariableName+".xyz, "+this._writeFloat(this.complementW)+`);\r
-`}}else switch(a=i.associatedVariableName,n.connectedPoint.type){case le.Vector2:e.compilationString+=this._declareOutput(this.output,e)+" = "+a+" * vec4("+n.associatedVariableName+", "+this._writeFloat(this.complementZ)+", "+this._writeFloat(this.complementW)+`);\r
-`;break;case le.Vector3:case le.Color3:e.compilationString+=this._declareOutput(this.output,e)+" = "+a+" * vec4("+n.associatedVariableName+", "+this._writeFloat(this.complementW)+`);\r
-`;break;default:e.compilationString+=this._declareOutput(this.output,e)+" = "+a+" * "+n.associatedVariableName+`;\r
-`}this.xyz.hasEndpoints&&(e.compilationString+=this._declareOutput(this.xyz,e)+" = "+this.output.associatedVariableName+`.xyz;\r
-`)}return this},t.prototype.prepareDefines=function(e,n,i,o,a){e.nonUniformScaling&&i.setValue("NONUNIFORMSCALING",!0)},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.complementZ=this.complementZ,e.complementW=this.complementW,e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.complementZ=e.complementZ!==void 0?e.complementZ:0,this.complementW=e.complementW!==void 0?e.complementW:1},t.prototype._dumpPropertiesCode=function(){var e=this._codeVariableName+".complementZ = "+this.complementZ+`;\r
-`;return e+=this._codeVariableName+".complementW = "+this.complementW+`;\r
-`},t}(pt);R.a.RegisteredTypes["BABYLON.TransformBlock"]=fa;var vo=function(r){function t(e){var n=r.call(this,e,xe.Vertex,!0)||this;return n.registerInput("vector",le.Vector4),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"VertexOutputBlock"},Object.defineProperty(t.prototype,"vector",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this.vector;return e.compilationString+="gl_Position = "+n.associatedVariableName+`;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.VertexOutputBlock"]=vo;var ji,Lr=function(r){function t(e){var n=r.call(this,e,xe.Fragment,!0)||this;return n.registerInput("rgba",le.Color4,!0),n.registerInput("rgb",le.Color3,!0),n.registerInput("a",le.Float,!0),n.rgb.acceptedConnectionPointTypes.push(le.Float),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"FragmentOutputBlock"},Object.defineProperty(t.prototype,"rgba",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgb",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"a",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this.rgba,i=this.rgb,o=this.a;if(e.sharedData.hints.needAlphaBlending=n.isConnected||o.isConnected,n.connectedPoint)o.isConnected?e.compilationString+="gl_FragColor = vec4("+n.associatedVariableName+".rgb, "+o.associatedVariableName+`);\r
-`:e.compilationString+="gl_FragColor = "+n.associatedVariableName+`;\r
-`;else if(i.connectedPoint){var a="1.0";o.connectedPoint&&(a=o.associatedVariableName),i.connectedPoint.type===le.Float?e.compilationString+="gl_FragColor = vec4("+i.associatedVariableName+", "+i.associatedVariableName+", "+i.associatedVariableName+", "+a+`);\r
-`:e.compilationString+="gl_FragColor = vec4("+i.associatedVariableName+", "+a+`);\r
-`}else e.sharedData.checks.notConnectedNonOptionalInputs.push(n);return this},t}(pt);R.a.RegisteredTypes["BABYLON.FragmentOutputBlock"]=Lr,function(r){r[r.None=0]="None",r[r.Time=1]="Time"}(ji||(ji={}));var um={position2d:"position",particle_uv:"vUV",particle_color:"vColor",particle_texturemask:"textureMask",particle_positionw:"vPositionW"},Js={particle_uv:!0,particle_color:!0,particle_texturemask:!0,particle_positionw:!0},uh={particle_texturemask:!0},At=function(r){function t(e,n,i){n===void 0&&(n=xe.Vertex),i===void 0&&(i=le.AutoDetect);var o=r.call(this,e,n,!1,!0)||this;return o._mode=bn.Undefined,o._animationType=ji.None,o.min=0,o.max=0,o.isBoolean=!1,o.matrixMode=0,o._systemValue=null,o.isConstant=!1,o.groupInInspector="",o.onValueChangedObservable=new x.c,o.convertToGammaSpace=!1,o.convertToLinearSpace=!1,o._type=i,o.setDefaultValue(),o.registerOutput("output",i),o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"type",{get:function(){if(this._type===le.AutoDetect){if(this.isUniform&&this.value!=null){if(!isNaN(this.value))return this._type=le.Float,this._type;switch(this.value.getClassName()){case"Vector2":return this._type=le.Vector2,this._type;case"Vector3":return this._type=le.Vector3,this._type;case"Vector4":return this._type=le.Vector4,this._type;case"Color3":return this._type=le.Color3,this._type;case"Color4":return this._type=le.Color4,this._type;case"Matrix":return this._type=le.Matrix,this._type}}if(this.isAttribute)switch(this.name){case"position":case"normal":case"tangent":case"particle_positionw":return this._type=le.Vector3,this._type;case"uv":case"uv2":case"position2d":case"particle_uv":return this._type=le.Vector2,this._type;case"matricesIndices":case"matricesWeights":case"world0":case"world1":case"world2":case"world3":return this._type=le.Vector4,this._type;case"color":case"particle_color":case"particle_texturemask":return this._type=le.Color4,this._type}if(this.isSystemValue)switch(this._systemValue){case bt.World:case bt.WorldView:case bt.WorldViewProjection:case bt.View:case bt.ViewProjection:case bt.Projection:return this._type=le.Matrix,this._type;case bt.CameraPosition:return this._type=le.Vector3,this._type;case bt.FogColor:return this._type=le.Color3,this._type;case bt.DeltaTime:return this._type=le.Float,this._type}}return this._type},enumerable:!1,configurable:!0}),t.prototype.validateBlockName=function(e){return!!this.isAttribute||r.prototype.validateBlockName.call(this,e)},Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.setAsAttribute=function(e){return this._mode=bn.Attribute,e&&(this.name=e),this},t.prototype.setAsSystemValue=function(e){return this.systemValue=e,this},Object.defineProperty(t.prototype,"value",{get:function(){return this._storedValue},set:function(e){this.type===le.Float&&(this.isBoolean?e=e?1:0:this.min!==this.max&&(e=Math.max(this.min,e),e=Math.min(this.max,e))),this._storedValue=e,this._mode=bn.Uniform,this.onValueChangedObservable.notifyObservers(this)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"valueCallback",{get:function(){return this._valueCallback},set:function(e){this._valueCallback=e,this._mode=bn.Uniform},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"associatedVariableName",{get:function(){return this._associatedVariableName},set:function(e){this._associatedVariableName=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"animationType",{get:function(){return this._animationType},set:function(e){this._animationType=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"isUndefined",{get:function(){return this._mode===bn.Undefined},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"isUniform",{get:function(){return this._mode===bn.Uniform},set:function(e){this._mode=e?bn.Uniform:bn.Undefined,this.associatedVariableName=""},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"isAttribute",{get:function(){return this._mode===bn.Attribute},set:function(e){this._mode=e?bn.Attribute:bn.Undefined,this.associatedVariableName=""},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"isVarying",{get:function(){return this._mode===bn.Varying},set:function(e){this._mode=e?bn.Varying:bn.Undefined,this.associatedVariableName=""},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"isSystemValue",{get:function(){return this._systemValue!=null},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"systemValue",{get:function(){return this._systemValue},set:function(e){this._mode=bn.Uniform,this.associatedVariableName="",this._systemValue=e},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"InputBlock"},t.prototype.animate=function(e){switch(this._animationType){case ji.Time:this.type===le.Float&&(this.value+=.01*e.getAnimationRatio())}},t.prototype._emitDefine=function(e){return e[0]==="!"?"#ifndef "+e.substring(1)+`\r
-`:"#ifdef "+e+`\r
-`},t.prototype.initialize=function(e){this.associatedVariableName=""},t.prototype.setDefaultValue=function(){switch(this.type){case le.Float:this.value=0;break;case le.Vector2:this.value=u.d.Zero();break;case le.Vector3:this.value=u.e.Zero();break;case le.Vector4:this.value=u.f.Zero();break;case le.Color3:this.value=M.a.White();break;case le.Color4:this.value=new M.b(1,1,1,1);break;case le.Matrix:this.value=u.a.Identity()}},t.prototype._emitConstant=function(e){switch(this.type){case le.Float:return""+e._emitFloat(this.value);case le.Vector2:return"vec2("+this.value.x+", "+this.value.y+")";case le.Vector3:return"vec3("+this.value.x+", "+this.value.y+", "+this.value.z+")";case le.Vector4:return"vec4("+this.value.x+", "+this.value.y+", "+this.value.z+", "+this.value.w+")";case le.Color3:return M.c.Color3[0].set(this.value.r,this.value.g,this.value.b),this.convertToGammaSpace&&M.c.Color3[0].toGammaSpaceToRef(M.c.Color3[0]),this.convertToLinearSpace&&M.c.Color3[0].toLinearSpaceToRef(M.c.Color3[0]),"vec3("+M.c.Color3[0].r+", "+M.c.Color3[0].g+", "+M.c.Color3[0].b+")";case le.Color4:return M.c.Color4[0].set(this.value.r,this.value.g,this.value.b,this.value.a),this.convertToGammaSpace&&M.c.Color4[0].toGammaSpaceToRef(M.c.Color4[0]),this.convertToLinearSpace&&M.c.Color4[0].toLinearSpaceToRef(M.c.Color4[0]),"vec4("+M.c.Color4[0].r+", "+M.c.Color4[0].g+", "+M.c.Color4[0].b+", "+M.c.Color4[0].a+")"}return""},Object.defineProperty(t.prototype,"_noContextSwitch",{get:function(){return Js[this.name]},enumerable:!1,configurable:!0}),t.prototype._emit=function(e,n){var i;if(this.isUniform){if(this.associatedVariableName||(this.associatedVariableName=e._getFreeVariableName("u_"+this.name)),this.isConstant)return e.constants.indexOf(this.associatedVariableName)!==-1?void 0:(e.constants.push(this.associatedVariableName),void(e._constantDeclaration+=this._declareOutput(this.output,e)+" = "+this._emitConstant(e)+`;\r
-`));if(e.uniforms.indexOf(this.associatedVariableName)!==-1)return;e.uniforms.push(this.associatedVariableName),n&&(e._uniformDeclaration+=this._emitDefine(n)),e._uniformDeclaration+="uniform "+e._getGLType(this.type)+" "+this.associatedVariableName+`;\r
-`,n&&(e._uniformDeclaration+=`#endif\r
-`);var o=e.sharedData.hints;if(this._systemValue!==null&&this._systemValue!==void 0)switch(this._systemValue){case bt.WorldView:o.needWorldViewMatrix=!0;break;case bt.WorldViewProjection:o.needWorldViewProjectionMatrix=!0}else this._animationType!==ji.None&&e.sharedData.animatedInputs.push(this)}else if(this.isAttribute){if(this.associatedVariableName=(i=um[this.name])!==null&&i!==void 0?i:this.name,this.target===xe.Vertex&&e._vertexState)return void(Js[this.name]?uh[this.name]?e._emitUniformFromString(this.associatedVariableName,e._getGLType(this.type),n):e._emitVaryingFromString(this.associatedVariableName,e._getGLType(this.type),n):this._emit(e._vertexState,n));if(e.attributes.indexOf(this.associatedVariableName)!==-1)return;e.attributes.push(this.associatedVariableName),Js[this.name]?uh[this.name]?e._emitUniformFromString(this.associatedVariableName,e._getGLType(this.type),n):e._emitVaryingFromString(this.associatedVariableName,e._getGLType(this.type),n):(n&&(e._attributeDeclaration+=this._emitDefine(n)),e._attributeDeclaration+="attribute "+e._getGLType(this.type)+" "+this.associatedVariableName+`;\r
-`,n&&(e._attributeDeclaration+=`#endif\r
-`))}},t.prototype._transmitWorld=function(e,n,i,o){if(this._systemValue){var a=this.associatedVariableName;switch(this._systemValue){case bt.World:e.setMatrix(a,n);break;case bt.WorldView:e.setMatrix(a,i);break;case bt.WorldViewProjection:e.setMatrix(a,o)}}},t.prototype._transmit=function(e,n){if(!this.isAttribute){var i=this.associatedVariableName;if(this._systemValue)switch(this._systemValue){case bt.World:case bt.WorldView:case bt.WorldViewProjection:return;case bt.View:e.setMatrix(i,n.getViewMatrix());break;case bt.Projection:e.setMatrix(i,n.getProjectionMatrix());break;case bt.ViewProjection:e.setMatrix(i,n.getTransformMatrix());break;case bt.CameraPosition:et.a.BindEyePosition(e,n,i);break;case bt.FogColor:e.setColor3(i,n.fogColor);break;case bt.DeltaTime:e.setFloat(i,n.deltaTime/1e3)}else{var o=this._valueCallback?this._valueCallback():this._storedValue;if(o!==null)switch(this.type){case le.Float:e.setFloat(i,o);break;case le.Int:e.setInt(i,o);break;case le.Color3:M.c.Color3[0].set(this.value.r,this.value.g,this.value.b),this.convertToGammaSpace&&M.c.Color3[0].toGammaSpaceToRef(M.c.Color3[0]),this.convertToLinearSpace&&M.c.Color3[0].toLinearSpaceToRef(M.c.Color3[0]),e.setColor3(i,M.c.Color3[0]);break;case le.Color4:M.c.Color4[0].set(this.value.r,this.value.g,this.value.b,this.value.a),this.convertToGammaSpace&&M.c.Color4[0].toGammaSpaceToRef(M.c.Color4[0]),this.convertToLinearSpace&&M.c.Color4[0].toLinearSpaceToRef(M.c.Color4[0]),e.setDirectColor4(i,M.c.Color4[0]);break;case le.Vector2:e.setVector2(i,o);break;case le.Vector3:e.setVector3(i,o);break;case le.Vector4:e.setVector4(i,o);break;case le.Matrix:e.setMatrix(i,o)}}}},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e),(this.isUniform||this.isSystemValue)&&e.sharedData.inputBlocks.push(this),this._emit(e)},t.prototype._dumpPropertiesCode=function(){var e=this._codeVariableName;if(this.isAttribute)return e+'.setAsAttribute("'+this.name+`");\r
-`;if(this.isSystemValue)return e+".setAsSystemValue(BABYLON.NodeMaterialSystemValues."+bt[this._systemValue]+`);\r
-`;if(this.isUniform){var n=[],i="";switch(this.type){case le.Float:i=""+this.value;break;case le.Vector2:i="new BABYLON.Vector2("+this.value.x+", "+this.value.y+")";break;case le.Vector3:i="new BABYLON.Vector3("+this.value.x+", "+this.value.y+", "+this.value.z+")";break;case le.Vector4:i="new BABYLON.Vector4("+this.value.x+", "+this.value.y+", "+this.value.z+", "+this.value.w+")";break;case le.Color3:i="new BABYLON.Color3("+this.value.r+", "+this.value.g+", "+this.value.b+")",this.convertToGammaSpace&&(i+=".toGammaSpace()"),this.convertToLinearSpace&&(i+=".toLinearSpace()");break;case le.Color4:i="new BABYLON.Color4("+this.value.r+", "+this.value.g+", "+this.value.b+", "+this.value.a+")",this.convertToGammaSpace&&(i+=".toGammaSpace()"),this.convertToLinearSpace&&(i+=".toLinearSpace()");break;case le.Matrix:i="BABYLON.Matrix.FromArray(["+this.value.m+"])"}return n.push(e+".value = "+i),this.type===le.Float&&n.push(e+".min = "+this.min,e+".max = "+this.max,e+".isBoolean = "+this.isBoolean,e+".matrixMode = "+this.matrixMode,e+".animationType = BABYLON.AnimatedInputBlockTypes."+ji[this.animationType]),n.push(e+".isConstant = "+this.isConstant),n.push(""),n.join(`;\r
-`)}return""},t.prototype.dispose=function(){this.onValueChangedObservable.clear(),r.prototype.dispose.call(this)},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.type=this.type,e.mode=this._mode,e.systemValue=this._systemValue,e.animationType=this._animationType,e.min=this.min,e.max=this.max,e.isBoolean=this.isBoolean,e.matrixMode=this.matrixMode,e.isConstant=this.isConstant,e.groupInInspector=this.groupInInspector,e.convertToGammaSpace=this.convertToGammaSpace,e.convertToLinearSpace=this.convertToLinearSpace,this._storedValue!=null&&this._mode===bn.Uniform&&(this._storedValue.asArray?(e.valueType="BABYLON."+this._storedValue.getClassName(),e.value=this._storedValue.asArray()):(e.valueType="number",e.value=this._storedValue)),e},t.prototype._deserialize=function(e,n,i){if(this._mode=e.mode,r.prototype._deserialize.call(this,e,n,i),this._type=e.type,this._systemValue=e.systemValue||e.wellKnownValue,this._animationType=e.animationType,this.min=e.min||0,this.max=e.max||0,this.isBoolean=!!e.isBoolean,this.matrixMode=e.matrixMode||0,this.isConstant=!!e.isConstant,this.groupInInspector=e.groupInInspector||"",this.convertToGammaSpace=!!e.convertToGammaSpace,this.convertToLinearSpace=!!e.convertToLinearSpace,e.valueType)if(e.valueType==="number")this._storedValue=e.value;else{var o=R.a.GetClass(e.valueType);o&&(this._storedValue=o.FromArray(e.value))}},t}(pt);R.a.RegisteredTypes["BABYLON.InputBlock"]=At;var $s=function(r){function t(e){var n=r.call(this,e,xe.VertexAndFragment)||this;return n._samplerName="textureSampler",n.convertToGammaSpace=!1,n.convertToLinearSpace=!1,n._isUnique=!1,n.registerInput("uv",le.Vector2,!1,xe.VertexAndFragment),n.registerOutput("rgba",le.Color4,xe.Neutral),n.registerOutput("rgb",le.Color3,xe.Neutral),n.registerOutput("r",le.Float,xe.Neutral),n.registerOutput("g",le.Float,xe.Neutral),n.registerOutput("b",le.Float,xe.Neutral),n.registerOutput("a",le.Float,xe.Neutral),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector3),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector4),n._inputs[0]._prioritizeVertex=!1,n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"CurrentScreenBlock"},Object.defineProperty(t.prototype,"uv",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgba",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgb",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"r",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"g",{get:function(){return this._outputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"b",{get:function(){return this._outputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"a",{get:function(){return this._outputs[5]},enumerable:!1,configurable:!0}),t.prototype.initialize=function(e){e._excludeVariableName("textureSampler")},Object.defineProperty(t.prototype,"target",{get:function(){return this.uv.isConnected?this.uv.sourceBlock.isInput?xe.VertexAndFragment:xe.Fragment:xe.VertexAndFragment},enumerable:!1,configurable:!0}),t.prototype.prepareDefines=function(e,n,i){i.setValue(this._linearDefineName,this.convertToGammaSpace,!0),i.setValue(this._gammaDefineName,this.convertToLinearSpace,!0)},t.prototype.isReady=function(){return!(this.texture&&!this.texture.isReadyOrNotBlocking())},t.prototype._injectVertexCode=function(e){var n=this.uv;if(n.connectedPoint.ownerBlock.isInput&&(n.connectedPoint.ownerBlock.isAttribute||e._emitUniformFromString(n.associatedVariableName,"vec2")),this._mainUVName="vMain"+n.associatedVariableName,e._emitVaryingFromString(this._mainUVName,"vec2"),e.compilationString+=this._mainUVName+" = "+n.associatedVariableName+`.xy;\r
-`,this._outputs.some(function(s){return s.isConnectedInVertexShader})){this._writeTextureRead(e,!0);for(var i=0,o=this._outputs;i<o.length;i++){var a=o[i];a.hasEndpoints&&this._writeOutput(e,a,a.name,!0)}}},t.prototype._writeTextureRead=function(e,n){n===void 0&&(n=!1);var i=this.uv;if(n){if(e.target===xe.Fragment)return;e.compilationString+="vec4 "+this._tempTextureRead+" = texture2D("+this._samplerName+", "+i.associatedVariableName+`);\r
-`}else this.uv.ownerBlock.target!==xe.Fragment?e.compilationString+="vec4 "+this._tempTextureRead+" = texture2D("+this._samplerName+", "+this._mainUVName+`);\r
-`:e.compilationString+="vec4 "+this._tempTextureRead+" = texture2D("+this._samplerName+", "+i.associatedVariableName+`);\r
-`},t.prototype._writeOutput=function(e,n,i,o){if(o===void 0&&(o=!1),o){if(e.target===xe.Fragment)return;e.compilationString+=this._declareOutput(n,e)+" = "+this._tempTextureRead+"."+i+`;\r
-`}else this.uv.ownerBlock.target!==xe.Fragment?(e.compilationString+=this._declareOutput(n,e)+" = "+this._tempTextureRead+"."+i+`;\r
-`,e.compilationString+="#ifdef "+this._linearDefineName+`\r
-`,e.compilationString+=n.associatedVariableName+" = toGammaSpace("+n.associatedVariableName+`);\r
-`,e.compilationString+=`#endif\r
-`,e.compilationString+="#ifdef "+this._gammaDefineName+`\r
-`,e.compilationString+=n.associatedVariableName+" = toLinearSpace("+n.associatedVariableName+`);\r
-`,e.compilationString+=`#endif\r
-`):e.compilationString+=this._declareOutput(n,e)+" = "+this._tempTextureRead+"."+i+`;\r
-`},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),this._tempTextureRead=e._getFreeVariableName("tempTextureRead"),e.sharedData.blockingBlocks.indexOf(this)<0&&e.sharedData.blockingBlocks.push(this),e.sharedData.textureBlocks.indexOf(this)<0&&e.sharedData.textureBlocks.push(this),e.sharedData.blocksWithDefines.indexOf(this)<0&&e.sharedData.blocksWithDefines.push(this),e.target!==xe.Fragment)return e._emit2DSampler(this._samplerName),void this._injectVertexCode(e);if(this._outputs.some(function(s){return s.isConnectedInFragmentShader})){e._emit2DSampler(this._samplerName),this._linearDefineName=e._getFreeDefineName("ISLINEAR"),this._gammaDefineName=e._getFreeDefineName("ISGAMMA");var n="//"+this.name;e._emitFunctionFromInclude("helperFunctions",n),this._writeTextureRead(e);for(var i=0,o=this._outputs;i<o.length;i++){var a=o[i];a.hasEndpoints&&this._writeOutput(e,a,a.name)}return this}},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.convertToGammaSpace=this.convertToGammaSpace,e.convertToLinearSpace=this.convertToLinearSpace,this.texture&&(e.texture=this.texture.serialize()),e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.convertToGammaSpace=e.convertToGammaSpace,this.convertToLinearSpace=!!e.convertToLinearSpace,e.texture&&(i=e.texture.url.indexOf("data:")===0?"":i,this.texture=we.a.Parse(e.texture,n,i))},t}(pt);R.a.RegisteredTypes["BABYLON.CurrentScreenBlock"]=$s;var ec=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n._samplerName="diffuseSampler",n.convertToGammaSpace=!1,n.convertToLinearSpace=!1,n._isUnique=!1,n.registerInput("uv",le.Vector2,!1,xe.VertexAndFragment),n.registerOutput("rgba",le.Color4,xe.Neutral),n.registerOutput("rgb",le.Color3,xe.Neutral),n.registerOutput("r",le.Float,xe.Neutral),n.registerOutput("g",le.Float,xe.Neutral),n.registerOutput("b",le.Float,xe.Neutral),n.registerOutput("a",le.Float,xe.Neutral),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector3),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector4),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ParticleTextureBlock"},Object.defineProperty(t.prototype,"uv",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgba",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgb",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"r",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"g",{get:function(){return this._outputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"b",{get:function(){return this._outputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"a",{get:function(){return this._outputs[5]},enumerable:!1,configurable:!0}),t.prototype.initialize=function(e){e._excludeVariableName("diffuseSampler")},t.prototype.autoConfigure=function(e){if(!this.uv.isConnected){var n=e.getInputBlockByPredicate(function(i){return i.isAttribute&&i.name==="particle_uv"});n||(n=new At("uv")).setAsAttribute("particle_uv"),n.output.connectTo(this.uv)}},t.prototype.prepareDefines=function(e,n,i){i.setValue(this._linearDefineName,this.convertToGammaSpace,!0),i.setValue(this._gammaDefineName,this.convertToLinearSpace,!0)},t.prototype.isReady=function(){return!(this.texture&&!this.texture.isReadyOrNotBlocking())},t.prototype._writeOutput=function(e,n,i){e.compilationString+=this._declareOutput(n,e)+" = "+this._tempTextureRead+"."+i+`;\r
-`,e.compilationString+="#ifdef "+this._linearDefineName+`\r
-`,e.compilationString+=n.associatedVariableName+" = toGammaSpace("+n.associatedVariableName+`);\r
-`,e.compilationString+=`#endif\r
-`,e.compilationString+="#ifdef "+this._gammaDefineName+`\r
-`,e.compilationString+=n.associatedVariableName+" = toLinearSpace("+n.associatedVariableName+`);\r
-`,e.compilationString+=`#endif\r
-`},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),e.target!==xe.Vertex){this._tempTextureRead=e._getFreeVariableName("tempTextureRead"),e._emit2DSampler(this._samplerName),e.sharedData.blockingBlocks.push(this),e.sharedData.textureBlocks.push(this),e.sharedData.blocksWithDefines.push(this),this._linearDefineName=e._getFreeDefineName("ISLINEAR"),this._gammaDefineName=e._getFreeDefineName("ISGAMMA");var n="//"+this.name;e._emitFunctionFromInclude("helperFunctions",n),e.compilationString+="vec4 "+this._tempTextureRead+" = texture2D("+this._samplerName+", "+this.uv.associatedVariableName+`);\r
-`;for(var i=0,o=this._outputs;i<o.length;i++){var a=o[i];a.hasEndpoints&&this._writeOutput(e,a,a.name)}return this}},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.convertToGammaSpace=this.convertToGammaSpace,e.convertToLinearSpace=this.convertToLinearSpace,this.texture&&(e.texture=this.texture.serialize()),e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.convertToGammaSpace=e.convertToGammaSpace,this.convertToLinearSpace=!!e.convertToLinearSpace,e.texture&&(i=e.texture.url.indexOf("data:")===0?"":i,this.texture=we.a.Parse(e.texture,n,i))},t}(pt);R.a.RegisteredTypes["BABYLON.ParticleTextureBlock"]=ec;var tc=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n._isUnique=!0,n.registerInput("color",le.Color4,!1,xe.Fragment),n.registerOutput("rampColor",le.Color4,xe.Fragment),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ParticleRampGradientBlock"},Object.defineProperty(t.prototype,"color",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rampColor",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.initialize=function(e){e._excludeVariableName("remapRanges"),e._excludeVariableName("rampSampler"),e._excludeVariableName("baseColor"),e._excludeVariableName("alpha"),e._excludeVariableName("remappedColorIndex"),e._excludeVariableName("rampColor"),e._excludeVariableName("finalAlpha")},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),e.target!==xe.Vertex)return e._emit2DSampler("rampSampler"),e._emitVaryingFromString("remapRanges","vec4","RAMPGRADIENT"),e.compilationString+=`
-            #ifdef RAMPGRADIENT
-                vec4 baseColor = `+this.color.associatedVariableName+`;
-                float alpha = `+this.color.associatedVariableName+`.a;
-
-                float remappedColorIndex = clamp((alpha - remapRanges.x) / remapRanges.y, 0.0, 1.0);
-
-                vec4 rampColor = texture2D(rampSampler, vec2(1.0 - remappedColorIndex, 0.));
-                baseColor.rgb *= rampColor.rgb;
-
-                // Remapped alpha
-                float finalAlpha = baseColor.a;
-                baseColor.a = clamp((alpha * rampColor.a - remapRanges.z) / remapRanges.w, 0.0, 1.0);
-
-                `+this._declareOutput(this.rampColor,e)+` = baseColor;
-            #else
-                `+this._declareOutput(this.rampColor,e)+" = "+this.color.associatedVariableName+`;
-            #endif
-        `,this},t}(pt);R.a.RegisteredTypes["BABYLON.ParticleRampGradientBlock"]=tc;var nc=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n._isUnique=!0,n.registerInput("color",le.Color4,!1,xe.Fragment),n.registerInput("alphaTexture",le.Float,!1,xe.Fragment),n.registerInput("alphaColor",le.Float,!1,xe.Fragment),n.registerOutput("blendColor",le.Color4,xe.Fragment),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ParticleBlendMultiplyBlock"},Object.defineProperty(t.prototype,"color",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"alphaTexture",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"alphaColor",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"blendColor",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.initialize=function(e){e._excludeVariableName("sourceAlpha")},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),e.target!==xe.Vertex)return e.compilationString+=`
-            #ifdef BLENDMULTIPLYMODE
-                `+this._declareOutput(this.blendColor,e)+`;
-                float sourceAlpha = `+this.alphaColor.associatedVariableName+" * "+this.alphaTexture.associatedVariableName+`;
-                `+this.blendColor.associatedVariableName+".rgb = "+this.color.associatedVariableName+`.rgb * sourceAlpha + vec3(1.0) * (1.0 - sourceAlpha);
-                `+this.blendColor.associatedVariableName+".a = "+this.color.associatedVariableName+`.a;
-            #else
-                `+this._declareOutput(this.blendColor,e)+" = "+this.color.associatedVariableName+`;
-            #endif
-        `,this},t}(pt);R.a.RegisteredTypes["BABYLON.ParticleBlendMultiplyBlock"]=nc;var Lt,bo=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("xyz ",le.Vector3,!0),n.registerInput("xy ",le.Vector2,!0),n.registerInput("x",le.Float,!0),n.registerInput("y",le.Float,!0),n.registerInput("z",le.Float,!0),n.registerInput("w",le.Float,!0),n.registerOutput("xyzw",le.Vector4),n.registerOutput("xyz",le.Vector3),n.registerOutput("xy",le.Vector2),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"VectorMergerBlock"},Object.defineProperty(t.prototype,"xyzIn",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyIn",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"x",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"y",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"z",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"w",{get:function(){return this._inputs[5]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyzw",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyzOut",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyOut",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xy",{get:function(){return this.xyOut},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyz",{get:function(){return this.xyzOut},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this.x,i=this.y,o=this.z,a=this.w,s=this.xyIn,d=this.xyzIn,p=this._outputs[0],b=this._outputs[1],P=this._outputs[2];return d.isConnected?p.hasEndpoints?e.compilationString+=this._declareOutput(p,e)+" = vec4("+d.associatedVariableName+", "+(a.isConnected?this._writeVariable(a):"0.0")+`);\r
-`:b.hasEndpoints?e.compilationString+=this._declareOutput(b,e)+" = "+d.associatedVariableName+`;\r
-`:P.hasEndpoints&&(e.compilationString+=this._declareOutput(P,e)+" = "+d.associatedVariableName+`.xy;\r
-`):s.isConnected?p.hasEndpoints?e.compilationString+=this._declareOutput(p,e)+" = vec4("+s.associatedVariableName+", "+(o.isConnected?this._writeVariable(o):"0.0")+", "+(a.isConnected?this._writeVariable(a):"0.0")+`);\r
-`:b.hasEndpoints?e.compilationString+=this._declareOutput(b,e)+" = vec3("+s.associatedVariableName+", "+(o.isConnected?this._writeVariable(o):"0.0")+`);\r
-`:P.hasEndpoints&&(e.compilationString+=this._declareOutput(P,e)+" = "+s.associatedVariableName+`;\r
-`):p.hasEndpoints?e.compilationString+=this._declareOutput(p,e)+" = vec4("+(n.isConnected?this._writeVariable(n):"0.0")+", "+(i.isConnected?this._writeVariable(i):"0.0")+", "+(o.isConnected?this._writeVariable(o):"0.0")+", "+(a.isConnected?this._writeVariable(a):"0.0")+`);\r
-`:b.hasEndpoints?e.compilationString+=this._declareOutput(b,e)+" = vec3("+(n.isConnected?this._writeVariable(n):"0.0")+", "+(i.isConnected?this._writeVariable(i):"0.0")+", "+(o.isConnected?this._writeVariable(o):"0.0")+`);\r
-`:P.hasEndpoints&&(e.compilationString+=this._declareOutput(P,e)+" = vec2("+(n.isConnected?this._writeVariable(n):"0.0")+", "+(i.isConnected?this._writeVariable(i):"0.0")+`);\r
-`),this},t}(pt);function Vt(r,t,e,n){return t===void 0&&(t=Lt.Boolean),e===void 0&&(e="PROPERTIES"),function(i,o){var a=i._propStore;a||(a=[],i._propStore=a),a.push({propertyName:o,displayName:r,type:t,groupName:e,options:n??{}})}}R.a.RegisteredTypes["BABYLON.VectorMergerBlock"]=bo,function(r){r[r.Boolean=0]="Boolean",r[r.Float=1]="Float",r[r.Vector2=2]="Vector2",r[r.List=3]="List"}(Lt||(Lt={}));var ic=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.sourceRange=new u.d(-1,1),n.targetRange=new u.d(0,1),n.registerInput("input",le.AutoDetect),n.registerInput("sourceMin",le.Float,!0),n.registerInput("sourceMax",le.Float,!0),n.registerInput("targetMin",le.Float,!0),n.registerInput("targetMax",le.Float,!0),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"RemapBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"sourceMin",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"sourceMax",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"targetMin",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"targetMax",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0],i=this.sourceMin.isConnected?this.sourceMin.associatedVariableName:this._writeFloat(this.sourceRange.x),o=this.sourceMax.isConnected?this.sourceMax.associatedVariableName:this._writeFloat(this.sourceRange.y),a=this.targetMin.isConnected?this.targetMin.associatedVariableName:this._writeFloat(this.targetRange.x),s=this.targetMax.isConnected?this.targetMax.associatedVariableName:this._writeFloat(this.targetRange.y);return e.compilationString+=this._declareOutput(n,e)+" = "+a+" + ("+this._inputs[0].associatedVariableName+" - "+i+") * ("+s+" - "+a+") / ("+o+" - "+i+`);\r
-`,this},t.prototype._dumpPropertiesCode=function(){var e=this._codeVariableName+".sourceRange = new BABYLON.Vector2("+this.sourceRange.x+", "+this.sourceRange.y+`);\r
-`;return e+=this._codeVariableName+".targetRange = new BABYLON.Vector2("+this.targetRange.x+", "+this.targetRange.y+`);\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.sourceRange=this.sourceRange.asArray(),e.targetRange=this.targetRange.asArray(),e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.sourceRange=u.d.FromArray(e.sourceRange),this.targetRange=u.d.FromArray(e.targetRange)},Object(c.c)([Vt("From",Lt.Vector2)],t.prototype,"sourceRange",void 0),Object(c.c)([Vt("To",Lt.Vector2)],t.prototype,"targetRange",void 0),t}(pt);R.a.RegisteredTypes["BABYLON.RemapBlock"]=ic;var pa=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"MultiplyBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = "+this.left.associatedVariableName+" * "+this.right.associatedVariableName+`;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.MultiplyBlock"]=pa;var Nr=function(){function r(){this.direction1=new u.e(0,1,0),this.direction2=new u.e(0,1,0),this.minEmitBox=new u.e(-.5,-.5,-.5),this.maxEmitBox=new u.e(.5,.5,.5)}return r.prototype.startDirectionFunction=function(t,e,n,i){var o=$.a.RandomRange(this.direction1.x,this.direction2.x),a=$.a.RandomRange(this.direction1.y,this.direction2.y),s=$.a.RandomRange(this.direction1.z,this.direction2.z);if(i)return e.x=o,e.y=a,void(e.z=s);u.e.TransformNormalFromFloatsToRef(o,a,s,t,e)},r.prototype.startPositionFunction=function(t,e,n,i){var o=$.a.RandomRange(this.minEmitBox.x,this.maxEmitBox.x),a=$.a.RandomRange(this.minEmitBox.y,this.maxEmitBox.y),s=$.a.RandomRange(this.minEmitBox.z,this.maxEmitBox.z);if(i)return e.x=o,e.y=a,void(e.z=s);u.e.TransformCoordinatesFromFloatsToRef(o,a,s,t,e)},r.prototype.clone=function(){var t=new r;return de.a.DeepCopy(this,t),t},r.prototype.applyToShader=function(t){t.setVector3("direction1",this.direction1),t.setVector3("direction2",this.direction2),t.setVector3("minEmitBox",this.minEmitBox),t.setVector3("maxEmitBox",this.maxEmitBox)},r.prototype.getEffectDefines=function(){return"#define BOXEMITTER"},r.prototype.getClassName=function(){return"BoxParticleEmitter"},r.prototype.serialize=function(){var t={};return t.type=this.getClassName(),t.direction1=this.direction1.asArray(),t.direction2=this.direction2.asArray(),t.minEmitBox=this.minEmitBox.asArray(),t.maxEmitBox=this.maxEmitBox.asArray(),t},r.prototype.parse=function(t){u.e.FromArrayToRef(t.direction1,0,this.direction1),u.e.FromArrayToRef(t.direction2,0,this.direction2),u.e.FromArrayToRef(t.minEmitBox,0,this.minEmitBox),u.e.FromArrayToRef(t.maxEmitBox,0,this.maxEmitBox)},r}(),rc=function(){function r(t,e,n){t===void 0&&(t=1),e===void 0&&(e=Math.PI),n===void 0&&(n=0),this.directionRandomizer=n,this.radiusRange=1,this.heightRange=1,this.emitFromSpawnPointOnly=!1,this.angle=e,this.radius=t}return Object.defineProperty(r.prototype,"radius",{get:function(){return this._radius},set:function(t){this._radius=t,this._buildHeight()},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"angle",{get:function(){return this._angle},set:function(t){this._angle=t,this._buildHeight()},enumerable:!1,configurable:!0}),r.prototype._buildHeight=function(){this._angle!==0?this._height=this._radius/Math.tan(this._angle/2):this._height=1},r.prototype.startDirectionFunction=function(t,e,n,i){i?u.c.Vector3[0].copyFrom(n._localPosition).normalize():n.position.subtractToRef(t.getTranslation(),u.c.Vector3[0]).normalize();var o=$.a.RandomRange(0,this.directionRandomizer),a=$.a.RandomRange(0,this.directionRandomizer),s=$.a.RandomRange(0,this.directionRandomizer);e.x=u.c.Vector3[0].x+o,e.y=u.c.Vector3[0].y+a,e.z=u.c.Vector3[0].z+s,e.normalize()},r.prototype.startPositionFunction=function(t,e,n,i){var o,a=$.a.RandomRange(0,2*Math.PI);o=this.emitFromSpawnPointOnly?1e-4:1-(o=$.a.RandomRange(0,this.heightRange))*o;var s=this._radius-$.a.RandomRange(0,this._radius*this.radiusRange),d=(s*=o)*Math.sin(a),p=s*Math.cos(a),b=o*this._height;if(i)return e.x=d,e.y=b,void(e.z=p);u.e.TransformCoordinatesFromFloatsToRef(d,b,p,t,e)},r.prototype.clone=function(){var t=new r(this._radius,this._angle,this.directionRandomizer);return de.a.DeepCopy(this,t),t},r.prototype.applyToShader=function(t){t.setFloat2("radius",this._radius,this.radiusRange),t.setFloat("coneAngle",this._angle),t.setFloat2("height",this._height,this.heightRange),t.setFloat("directionRandomizer",this.directionRandomizer)},r.prototype.getEffectDefines=function(){var t="#define CONEEMITTER";return this.emitFromSpawnPointOnly&&(t+=`
-#define CONEEMITTERSPAWNPOINT`),t},r.prototype.getClassName=function(){return"ConeParticleEmitter"},r.prototype.serialize=function(){var t={};return t.type=this.getClassName(),t.radius=this._radius,t.angle=this._angle,t.directionRandomizer=this.directionRandomizer,t.radiusRange=this.radiusRange,t.heightRange=this.heightRange,t.emitFromSpawnPointOnly=this.emitFromSpawnPointOnly,t},r.prototype.parse=function(t){this.radius=t.radius,this.angle=t.angle,this.directionRandomizer=t.directionRandomizer,this.radiusRange=t.radiusRange!==void 0?t.radiusRange:1,this.heightRange=t.radiusRange!==void 0?t.heightRange:1,this.emitFromSpawnPointOnly=t.emitFromSpawnPointOnly!==void 0&&t.emitFromSpawnPointOnly},r}(),_a=function(){function r(t,e,n,i){t===void 0&&(t=1),e===void 0&&(e=1),n===void 0&&(n=1),i===void 0&&(i=0),this.radius=t,this.height=e,this.radiusRange=n,this.directionRandomizer=i}return r.prototype.startDirectionFunction=function(t,e,n,i){var o=n.position.subtract(t.getTranslation()).normalize(),a=$.a.RandomRange(-this.directionRandomizer/2,this.directionRandomizer/2),s=Math.atan2(o.x,o.z);s+=$.a.RandomRange(-Math.PI/2,Math.PI/2)*this.directionRandomizer,o.y=a,o.x=Math.sin(s),o.z=Math.cos(s),o.normalize(),i?e.copyFrom(o):u.e.TransformNormalFromFloatsToRef(o.x,o.y,o.z,t,e)},r.prototype.startPositionFunction=function(t,e,n,i){var o=$.a.RandomRange(-this.height/2,this.height/2),a=$.a.RandomRange(0,2*Math.PI),s=$.a.RandomRange((1-this.radiusRange)*(1-this.radiusRange),1),d=Math.sqrt(s)*this.radius,p=d*Math.cos(a),b=d*Math.sin(a);i?e.copyFromFloats(p,o,b):u.e.TransformCoordinatesFromFloatsToRef(p,o,b,t,e)},r.prototype.clone=function(){var t=new r(this.radius,this.directionRandomizer);return de.a.DeepCopy(this,t),t},r.prototype.applyToShader=function(t){t.setFloat("radius",this.radius),t.setFloat("height",this.height),t.setFloat("radiusRange",this.radiusRange),t.setFloat("directionRandomizer",this.directionRandomizer)},r.prototype.getEffectDefines=function(){return"#define CYLINDEREMITTER"},r.prototype.getClassName=function(){return"CylinderParticleEmitter"},r.prototype.serialize=function(){var t={};return t.type=this.getClassName(),t.radius=this.radius,t.height=this.height,t.radiusRange=this.radiusRange,t.directionRandomizer=this.directionRandomizer,t},r.prototype.parse=function(t){this.radius=t.radius,this.height=t.height,this.radiusRange=t.radiusRange,this.directionRandomizer=t.directionRandomizer},r}(),oc=function(r){function t(e,n,i,o,a){e===void 0&&(e=1),n===void 0&&(n=1),i===void 0&&(i=1),o===void 0&&(o=new u.e(0,1,0)),a===void 0&&(a=new u.e(0,1,0));var s=r.call(this,e,n,i)||this;return s.direction1=o,s.direction2=a,s}return Object(c.d)(t,r),t.prototype.startDirectionFunction=function(e,n,i){var o=$.a.RandomRange(this.direction1.x,this.direction2.x),a=$.a.RandomRange(this.direction1.y,this.direction2.y),s=$.a.RandomRange(this.direction1.z,this.direction2.z);u.e.TransformNormalFromFloatsToRef(o,a,s,e,n)},t.prototype.clone=function(){var e=new t(this.radius,this.height,this.radiusRange,this.direction1,this.direction2);return de.a.DeepCopy(this,e),e},t.prototype.applyToShader=function(e){e.setFloat("radius",this.radius),e.setFloat("height",this.height),e.setFloat("radiusRange",this.radiusRange),e.setVector3("direction1",this.direction1),e.setVector3("direction2",this.direction2)},t.prototype.getEffectDefines=function(){return`#define CYLINDEREMITTER
-#define DIRECTEDCYLINDEREMITTER`},t.prototype.getClassName=function(){return"CylinderDirectedParticleEmitter"},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.direction1=this.direction1.asArray(),e.direction2=this.direction2.asArray(),e},t.prototype.parse=function(e){r.prototype.parse.call(this,e),this.direction1.copyFrom(e.direction1),this.direction2.copyFrom(e.direction2)},t}(_a),ac=function(){function r(t,e,n){t===void 0&&(t=1),e===void 0&&(e=1),n===void 0&&(n=0),this.radius=t,this.radiusRange=e,this.directionRandomizer=n}return r.prototype.startDirectionFunction=function(t,e,n,i){var o=n.position.subtract(t.getTranslation()).normalize(),a=$.a.RandomRange(0,this.directionRandomizer),s=$.a.RandomRange(0,this.directionRandomizer),d=$.a.RandomRange(0,this.directionRandomizer);o.x+=a,o.y+=s,o.z+=d,o.normalize(),i?e.copyFrom(o):u.e.TransformNormalFromFloatsToRef(o.x,o.y,o.z,t,e)},r.prototype.startPositionFunction=function(t,e,n,i){var o=this.radius-$.a.RandomRange(0,this.radius*this.radiusRange),a=$.a.RandomRange(0,1),s=$.a.RandomRange(0,2*Math.PI),d=Math.acos(2*a-1),p=o*Math.cos(s)*Math.sin(d),b=o*Math.cos(d),P=o*Math.sin(s)*Math.sin(d);i?e.copyFromFloats(p,Math.abs(b),P):u.e.TransformCoordinatesFromFloatsToRef(p,Math.abs(b),P,t,e)},r.prototype.clone=function(){var t=new r(this.radius,this.directionRandomizer);return de.a.DeepCopy(this,t),t},r.prototype.applyToShader=function(t){t.setFloat("radius",this.radius),t.setFloat("radiusRange",this.radiusRange),t.setFloat("directionRandomizer",this.directionRandomizer)},r.prototype.getEffectDefines=function(){return"#define HEMISPHERICEMITTER"},r.prototype.getClassName=function(){return"HemisphericParticleEmitter"},r.prototype.serialize=function(){var t={};return t.type=this.getClassName(),t.radius=this.radius,t.radiusRange=this.radiusRange,t.directionRandomizer=this.directionRandomizer,t},r.prototype.parse=function(t){this.radius=t.radius,this.radiusRange=t.radiusRange,this.directionRandomizer=t.directionRandomizer},r}(),sc=function(){function r(){this.direction1=new u.e(0,1,0),this.direction2=new u.e(0,1,0)}return r.prototype.startDirectionFunction=function(t,e,n,i){var o=$.a.RandomRange(this.direction1.x,this.direction2.x),a=$.a.RandomRange(this.direction1.y,this.direction2.y),s=$.a.RandomRange(this.direction1.z,this.direction2.z);i?e.copyFromFloats(o,a,s):u.e.TransformNormalFromFloatsToRef(o,a,s,t,e)},r.prototype.startPositionFunction=function(t,e,n,i){i?e.copyFromFloats(0,0,0):u.e.TransformCoordinatesFromFloatsToRef(0,0,0,t,e)},r.prototype.clone=function(){var t=new r;return de.a.DeepCopy(this,t),t},r.prototype.applyToShader=function(t){t.setVector3("direction1",this.direction1),t.setVector3("direction2",this.direction2)},r.prototype.getEffectDefines=function(){return"#define POINTEMITTER"},r.prototype.getClassName=function(){return"PointParticleEmitter"},r.prototype.serialize=function(){var t={};return t.type=this.getClassName(),t.direction1=this.direction1.asArray(),t.direction2=this.direction2.asArray(),t},r.prototype.parse=function(t){u.e.FromArrayToRef(t.direction1,0,this.direction1),u.e.FromArrayToRef(t.direction2,0,this.direction2)},r}(),ma=function(){function r(t,e,n){t===void 0&&(t=1),e===void 0&&(e=1),n===void 0&&(n=0),this.radius=t,this.radiusRange=e,this.directionRandomizer=n}return r.prototype.startDirectionFunction=function(t,e,n,i){var o=n.position.subtract(t.getTranslation()).normalize(),a=$.a.RandomRange(0,this.directionRandomizer),s=$.a.RandomRange(0,this.directionRandomizer),d=$.a.RandomRange(0,this.directionRandomizer);o.x+=a,o.y+=s,o.z+=d,o.normalize(),i?e.copyFrom(o):u.e.TransformNormalFromFloatsToRef(o.x,o.y,o.z,t,e)},r.prototype.startPositionFunction=function(t,e,n,i){var o=this.radius-$.a.RandomRange(0,this.radius*this.radiusRange),a=$.a.RandomRange(0,1),s=$.a.RandomRange(0,2*Math.PI),d=Math.acos(2*a-1),p=o*Math.cos(s)*Math.sin(d),b=o*Math.cos(d),P=o*Math.sin(s)*Math.sin(d);i?e.copyFromFloats(p,b,P):u.e.TransformCoordinatesFromFloatsToRef(p,b,P,t,e)},r.prototype.clone=function(){var t=new r(this.radius,this.directionRandomizer);return de.a.DeepCopy(this,t),t},r.prototype.applyToShader=function(t){t.setFloat("radius",this.radius),t.setFloat("radiusRange",this.radiusRange),t.setFloat("directionRandomizer",this.directionRandomizer)},r.prototype.getEffectDefines=function(){return"#define SPHEREEMITTER"},r.prototype.getClassName=function(){return"SphereParticleEmitter"},r.prototype.serialize=function(){var t={};return t.type=this.getClassName(),t.radius=this.radius,t.radiusRange=this.radiusRange,t.directionRandomizer=this.directionRandomizer,t},r.prototype.parse=function(t){this.radius=t.radius,this.radiusRange=t.radiusRange,this.directionRandomizer=t.directionRandomizer},r}(),cc=function(r){function t(e,n,i){e===void 0&&(e=1),n===void 0&&(n=new u.e(0,1,0)),i===void 0&&(i=new u.e(0,1,0));var o=r.call(this,e)||this;return o.direction1=n,o.direction2=i,o}return Object(c.d)(t,r),t.prototype.startDirectionFunction=function(e,n,i){var o=$.a.RandomRange(this.direction1.x,this.direction2.x),a=$.a.RandomRange(this.direction1.y,this.direction2.y),s=$.a.RandomRange(this.direction1.z,this.direction2.z);u.e.TransformNormalFromFloatsToRef(o,a,s,e,n)},t.prototype.clone=function(){var e=new t(this.radius,this.direction1,this.direction2);return de.a.DeepCopy(this,e),e},t.prototype.applyToShader=function(e){e.setFloat("radius",this.radius),e.setFloat("radiusRange",this.radiusRange),e.setVector3("direction1",this.direction1),e.setVector3("direction2",this.direction2)},t.prototype.getEffectDefines=function(){return`#define SPHEREEMITTER
-#define DIRECTEDSPHEREEMITTER`},t.prototype.getClassName=function(){return"SphereDirectedParticleEmitter"},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.direction1=this.direction1.asArray(),e.direction2=this.direction2.asArray(),e},t.prototype.parse=function(e){r.prototype.parse.call(this,e),this.direction1.copyFrom(e.direction1),this.direction2.copyFrom(e.direction2)},t}(ma),wr=function(){function r(){this.particlePositionGenerator=function(){},this.particleDestinationGenerator=function(){}}return r.prototype.startDirectionFunction=function(t,e,n,i){var o=u.c.Vector3[0];if(this.particleDestinationGenerator){this.particleDestinationGenerator(-1,n,o);var a=u.c.Vector3[1];o.subtractToRef(n.position,a),a.scaleToRef(1/n.lifeTime,o)}else o.set(0,0,0);i?e.copyFrom(o):u.e.TransformNormalToRef(o,t,e)},r.prototype.startPositionFunction=function(t,e,n,i){var o=u.c.Vector3[0];this.particlePositionGenerator?this.particlePositionGenerator(-1,n,o):o.set(0,0,0),i?e.copyFrom(o):u.e.TransformCoordinatesToRef(o,t,e)},r.prototype.clone=function(){var t=new r;return de.a.DeepCopy(this,t),t},r.prototype.applyToShader=function(t){},r.prototype.getEffectDefines=function(){return"#define CUSTOMEMITTER"},r.prototype.getClassName=function(){return"CustomParticleEmitter"},r.prototype.serialize=function(){var t={};return t.type=this.getClassName(),t},r.prototype.parse=function(t){},r}(),hh=function(){function r(t){t===void 0&&(t=null),this._indices=null,this._positions=null,this._normals=null,this._storedNormal=u.e.Zero(),this._mesh=null,this.direction1=new u.e(0,1,0),this.direction2=new u.e(0,1,0),this.useMeshNormalsForDirection=!0,this.mesh=t}return Object.defineProperty(r.prototype,"mesh",{get:function(){return this._mesh},set:function(t){this._mesh!==t&&(this._mesh=t,t?(this._indices=t.getIndices(),this._positions=t.getVerticesData(Oe.b.PositionKind),this._normals=t.getVerticesData(Oe.b.NormalKind)):(this._indices=null,this._positions=null,this._normals=null))},enumerable:!1,configurable:!0}),r.prototype.startDirectionFunction=function(t,e,n,i){if(this.useMeshNormalsForDirection&&this._normals)u.e.TransformNormalToRef(this._storedNormal,t,e);else{var o=$.a.RandomRange(this.direction1.x,this.direction2.x),a=$.a.RandomRange(this.direction1.y,this.direction2.y),s=$.a.RandomRange(this.direction1.z,this.direction2.z);i?e.copyFromFloats(o,a,s):u.e.TransformNormalFromFloatsToRef(o,a,s,t,e)}},r.prototype.startPositionFunction=function(t,e,n,i){if(this._indices&&this._positions){var o=3*Math.random()*(this._indices.length/3)|0,a=Math.random(),s=Math.random()*(1-a),d=1-a-s,p=this._indices[o],b=this._indices[o+1],P=this._indices[o+2],O=u.c.Vector3[0],B=u.c.Vector3[1],F=u.c.Vector3[2],z=u.c.Vector3[3];u.e.FromArrayToRef(this._positions,3*p,O),u.e.FromArrayToRef(this._positions,3*b,B),u.e.FromArrayToRef(this._positions,3*P,F),z.x=a*O.x+s*B.x+d*F.x,z.y=a*O.y+s*B.y+d*F.y,z.z=a*O.z+s*B.z+d*F.z,i?e.copyFromFloats(z.x,z.y,z.z):u.e.TransformCoordinatesFromFloatsToRef(z.x,z.y,z.z,t,e),this.useMeshNormalsForDirection&&this._normals&&(u.e.FromArrayToRef(this._normals,3*p,O),u.e.FromArrayToRef(this._normals,3*b,B),u.e.FromArrayToRef(this._normals,3*P,F),this._storedNormal.x=a*O.x+s*B.x+d*F.x,this._storedNormal.y=a*O.y+s*B.y+d*F.y,this._storedNormal.z=a*O.z+s*B.z+d*F.z)}},r.prototype.clone=function(){var t=new r(this.mesh);return de.a.DeepCopy(this,t),t},r.prototype.applyToShader=function(t){t.setVector3("direction1",this.direction1),t.setVector3("direction2",this.direction2)},r.prototype.getEffectDefines=function(){return""},r.prototype.getClassName=function(){return"MeshParticleEmitter"},r.prototype.serialize=function(){var t,e={};return e.type=this.getClassName(),e.direction1=this.direction1.asArray(),e.direction2=this.direction2.asArray(),e.meshId=(t=this.mesh)===null||t===void 0?void 0:t.id,e.useMeshNormalsForDirection=this.useMeshNormalsForDirection,e},r.prototype.parse=function(t,e){u.e.FromArrayToRef(t.direction1,0,this.direction1),u.e.FromArrayToRef(t.direction2,0,this.direction2),t.meshId&&e&&(this.mesh=e.getLastMeshByID(t.meshId)),this.useMeshNormalsForDirection=t.useMeshNormalsForDirection},r}(),yo=function(){function r(t){this.animations=[],this.renderingGroupId=0,this.emitter=u.e.Zero(),this.emitRate=10,this.manualEmitCount=-1,this.updateSpeed=.01,this.targetStopDuration=0,this.disposeOnStop=!1,this.minEmitPower=1,this.maxEmitPower=1,this.minLifeTime=1,this.maxLifeTime=1,this.minSize=1,this.maxSize=1,this.minScaleX=1,this.maxScaleX=1,this.minScaleY=1,this.maxScaleY=1,this.minInitialRotation=0,this.maxInitialRotation=0,this.minAngularSpeed=0,this.maxAngularSpeed=0,this.layerMask=268435455,this.customShader=null,this.preventAutoStart=!1,this.noiseStrength=new u.e(10,10,10),this.onAnimationEnd=null,this.blendMode=r.BLENDMODE_ONEONE,this.forceDepthWrite=!1,this.preWarmCycles=0,this.preWarmStepOffset=1,this.spriteCellChangeSpeed=1,this.startSpriteCellID=0,this.endSpriteCellID=0,this.spriteCellWidth=0,this.spriteCellHeight=0,this.spriteRandomStartCell=!1,this.translationPivot=new u.d(0,0),this.beginAnimationOnStart=!1,this.beginAnimationFrom=0,this.beginAnimationTo=60,this.beginAnimationLoop=!1,this.worldOffset=new u.e(0,0,0),this.gravity=u.e.Zero(),this._colorGradients=null,this._sizeGradients=null,this._lifeTimeGradients=null,this._angularSpeedGradients=null,this._velocityGradients=null,this._limitVelocityGradients=null,this._dragGradients=null,this._emitRateGradients=null,this._startSizeGradients=null,this._rampGradients=null,this._colorRemapGradients=null,this._alphaRemapGradients=null,this.startDelay=0,this.limitVelocityDamping=.4,this.color1=new M.b(1,1,1,1),this.color2=new M.b(1,1,1,1),this.colorDead=new M.b(0,0,0,1),this.textureMask=new M.b(1,1,1,1),this._isSubEmitter=!1,this.billboardMode=h.a.PARTICLES_BILLBOARDMODE_ALL,this._isBillboardBased=!0,this._imageProcessingConfigurationDefines=new yn.b,this.id=t,this.name=t}return Object.defineProperty(r.prototype,"noiseTexture",{get:function(){return this._noiseTexture},set:function(t){this._noiseTexture!==t&&(this._noiseTexture=t,this._reset())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isAnimationSheetEnabled",{get:function(){return this._isAnimationSheetEnabled},set:function(t){this._isAnimationSheetEnabled!=t&&(this._isAnimationSheetEnabled=t,this._reset())},enumerable:!1,configurable:!0}),r.prototype.getScene=function(){return this._scene},r.prototype._hasTargetStopDurationDependantGradient=function(){return this._startSizeGradients&&this._startSizeGradients.length>0||this._emitRateGradients&&this._emitRateGradients.length>0||this._lifeTimeGradients&&this._lifeTimeGradients.length>0},r.prototype.getDragGradients=function(){return this._dragGradients},r.prototype.getLimitVelocityGradients=function(){return this._limitVelocityGradients},r.prototype.getColorGradients=function(){return this._colorGradients},r.prototype.getSizeGradients=function(){return this._sizeGradients},r.prototype.getColorRemapGradients=function(){return this._colorRemapGradients},r.prototype.getAlphaRemapGradients=function(){return this._alphaRemapGradients},r.prototype.getLifeTimeGradients=function(){return this._lifeTimeGradients},r.prototype.getAngularSpeedGradients=function(){return this._angularSpeedGradients},r.prototype.getVelocityGradients=function(){return this._velocityGradients},r.prototype.getStartSizeGradients=function(){return this._startSizeGradients},r.prototype.getEmitRateGradients=function(){return this._emitRateGradients},Object.defineProperty(r.prototype,"direction1",{get:function(){return this.particleEmitterType.direction1?this.particleEmitterType.direction1:u.e.Zero()},set:function(t){this.particleEmitterType.direction1&&(this.particleEmitterType.direction1=t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"direction2",{get:function(){return this.particleEmitterType.direction2?this.particleEmitterType.direction2:u.e.Zero()},set:function(t){this.particleEmitterType.direction2&&(this.particleEmitterType.direction2=t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"minEmitBox",{get:function(){return this.particleEmitterType.minEmitBox?this.particleEmitterType.minEmitBox:u.e.Zero()},set:function(t){this.particleEmitterType.minEmitBox&&(this.particleEmitterType.minEmitBox=t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"maxEmitBox",{get:function(){return this.particleEmitterType.maxEmitBox?this.particleEmitterType.maxEmitBox:u.e.Zero()},set:function(t){this.particleEmitterType.maxEmitBox&&(this.particleEmitterType.maxEmitBox=t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isBillboardBased",{get:function(){return this._isBillboardBased},set:function(t){this._isBillboardBased!==t&&(this._isBillboardBased=t,this._reset())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"imageProcessingConfiguration",{get:function(){return this._imageProcessingConfiguration},set:function(t){this._attachImageProcessingConfiguration(t)},enumerable:!1,configurable:!0}),r.prototype._attachImageProcessingConfiguration=function(t){t!==this._imageProcessingConfiguration&&(!t&&this._scene?this._imageProcessingConfiguration=this._scene.imageProcessingConfiguration:this._imageProcessingConfiguration=t)},r.prototype._reset=function(){},r.prototype._removeGradientAndTexture=function(t,e,n){if(!e)return this;for(var i=0,o=0,a=e;o<a.length;o++){if(a[o].gradient===t){e.splice(i,1);break}i++}return n&&n.dispose(),this},r.prototype.createPointEmitter=function(t,e){var n=new sc;return n.direction1=t,n.direction2=e,this.particleEmitterType=n,n},r.prototype.createHemisphericEmitter=function(t,e){t===void 0&&(t=1),e===void 0&&(e=1);var n=new ac(t,e);return this.particleEmitterType=n,n},r.prototype.createSphereEmitter=function(t,e){t===void 0&&(t=1),e===void 0&&(e=1);var n=new ma(t,e);return this.particleEmitterType=n,n},r.prototype.createDirectedSphereEmitter=function(t,e,n){t===void 0&&(t=1),e===void 0&&(e=new u.e(0,1,0)),n===void 0&&(n=new u.e(0,1,0));var i=new cc(t,e,n);return this.particleEmitterType=i,i},r.prototype.createCylinderEmitter=function(t,e,n,i){t===void 0&&(t=1),e===void 0&&(e=1),n===void 0&&(n=1),i===void 0&&(i=0);var o=new _a(t,e,n,i);return this.particleEmitterType=o,o},r.prototype.createDirectedCylinderEmitter=function(t,e,n,i,o){t===void 0&&(t=1),e===void 0&&(e=1),n===void 0&&(n=1),i===void 0&&(i=new u.e(0,1,0)),o===void 0&&(o=new u.e(0,1,0));var a=new oc(t,e,n,i,o);return this.particleEmitterType=a,a},r.prototype.createConeEmitter=function(t,e){t===void 0&&(t=1),e===void 0&&(e=Math.PI/4);var n=new rc(t,e);return this.particleEmitterType=n,n},r.prototype.createBoxEmitter=function(t,e,n,i){var o=new Nr;return this.particleEmitterType=o,this.direction1=t,this.direction2=e,this.minEmitBox=n,this.maxEmitBox=i,o},r.BLENDMODE_ONEONE=0,r.BLENDMODE_STANDARD=1,r.BLENDMODE_ADD=2,r.BLENDMODE_MULTIPLY=3,r.BLENDMODE_MULTIPLYADD=4,r}(),lc=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("rgba",le.Color4,!0),n.registerInput("rgb ",le.Color3,!0),n.registerOutput("rgb",le.Color3),n.registerOutput("r",le.Float),n.registerOutput("g",le.Float),n.registerOutput("b",le.Float),n.registerOutput("a",le.Float),n.inputsAreExclusive=!0,n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ColorSplitterBlock"},Object.defineProperty(t.prototype,"rgba",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgbIn",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgbOut",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"r",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"g",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"b",{get:function(){return this._outputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"a",{get:function(){return this._outputs[4]},enumerable:!1,configurable:!0}),t.prototype._inputRename=function(e){return e==="rgb "?"rgbIn":e},t.prototype._outputRename=function(e){return e==="rgb"?"rgbOut":e},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this.rgba.isConnected?this.rgba:this.rgbIn;if(n.isConnected){var i=this._outputs[0],o=this._outputs[1],a=this._outputs[2],s=this._outputs[3],d=this._outputs[4];return i.hasEndpoints&&(e.compilationString+=this._declareOutput(i,e)+" = "+n.associatedVariableName+`.rgb;\r
-`),o.hasEndpoints&&(e.compilationString+=this._declareOutput(o,e)+" = "+n.associatedVariableName+`.r;\r
-`),a.hasEndpoints&&(e.compilationString+=this._declareOutput(a,e)+" = "+n.associatedVariableName+`.g;\r
-`),s.hasEndpoints&&(e.compilationString+=this._declareOutput(s,e)+" = "+n.associatedVariableName+`.b;\r
-`),d.hasEndpoints&&(e.compilationString+=this._declareOutput(d,e)+" = "+n.associatedVariableName+`.a;\r
-`),this}},t}(pt);R.a.RegisteredTypes["BABYLON.ColorSplitterBlock"]=lc;var rn,dh=f(104);(function(r){r[r.Cos=0]="Cos",r[r.Sin=1]="Sin",r[r.Abs=2]="Abs",r[r.Exp=3]="Exp",r[r.Exp2=4]="Exp2",r[r.Round=5]="Round",r[r.Floor=6]="Floor",r[r.Ceiling=7]="Ceiling",r[r.Sqrt=8]="Sqrt",r[r.Log=9]="Log",r[r.Tan=10]="Tan",r[r.ArcTan=11]="ArcTan",r[r.ArcCos=12]="ArcCos",r[r.ArcSin=13]="ArcSin",r[r.Fract=14]="Fract",r[r.Sign=15]="Sign",r[r.Radians=16]="Radians",r[r.Degrees=17]="Degrees"})(rn||(rn={}));var uc=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.operation=rn.Cos,n.registerInput("input",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"TrigonometryBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0],i="";switch(this.operation){case rn.Cos:i="cos";break;case rn.Sin:i="sin";break;case rn.Abs:i="abs";break;case rn.Exp:i="exp";break;case rn.Exp2:i="exp2";break;case rn.Round:i="round";break;case rn.Floor:i="floor";break;case rn.Ceiling:i="ceil";break;case rn.Sqrt:i="sqrt";break;case rn.Log:i="log";break;case rn.Tan:i="tan";break;case rn.ArcTan:i="atan";break;case rn.ArcCos:i="acos";break;case rn.ArcSin:i="asin";break;case rn.Fract:i="fract";break;case rn.Sign:i="sign";break;case rn.Radians:i="radians";break;case rn.Degrees:i="degrees"}return e.compilationString+=this._declareOutput(n,e)+" = "+i+"("+this.input.associatedVariableName+`);\r
-`,this},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.operation=this.operation,e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.operation=e.operation},t.prototype._dumpPropertiesCode=function(){return this._codeVariableName+".operation = BABYLON.TrigonometryBlockOperations."+rn[this.operation]+`;\r
-`},t}(pt);R.a.RegisteredTypes["BABYLON.TrigonometryBlock"]=uc;var hc={effect:null,subMesh:null},To=function(r){function t(){var e=r.call(this)||this;return e.NORMAL=!1,e.TANGENT=!1,e.UV1=!1,e.NUM_BONE_INFLUENCERS=0,e.BonesPerMesh=0,e.BONETEXTURE=!1,e.MORPHTARGETS=!1,e.MORPHTARGETS_NORMAL=!1,e.MORPHTARGETS_TANGENT=!1,e.MORPHTARGETS_UV=!1,e.NUM_MORPH_INFLUENCERS=0,e.IMAGEPROCESSING=!1,e.VIGNETTE=!1,e.VIGNETTEBLENDMODEMULTIPLY=!1,e.VIGNETTEBLENDMODEOPAQUE=!1,e.TONEMAPPING=!1,e.TONEMAPPING_ACES=!1,e.CONTRAST=!1,e.EXPOSURE=!1,e.COLORCURVES=!1,e.COLORGRADING=!1,e.COLORGRADING3D=!1,e.SAMPLER3DGREENDEPTH=!1,e.SAMPLER3DBGRMAP=!1,e.IMAGEPROCESSINGPOSTPROCESS=!1,e.BUMPDIRECTUV=0,e.rebuild(),e}return Object(c.d)(t,r),t.prototype.setValue=function(e,n,i){i===void 0&&(i=!1),this[e]===void 0&&this._keys.push(e),i&&this[e]!==n&&this.markAsUnprocessed(),this[e]=n},t}(Jo.a),ga=function(r){function t(e,n,i){i===void 0&&(i={});var o=r.call(this,e,n||Ue.a.LastCreatedScene)||this;return o._buildId=t._BuildIdGenerator++,o._buildWasSuccessful=!1,o._cachedWorldViewMatrix=new u.a,o._cachedWorldViewProjectionMatrix=new u.a,o._optimizers=new Array,o._animationFrame=-1,o.BJSNODEMATERIALEDITOR=o._getGlobalNodeMaterialEditor(),o.editorData=null,o.ignoreAlpha=!1,o.maxSimultaneousLights=4,o.onBuildObservable=new x.c,o._vertexOutputNodes=new Array,o._fragmentOutputNodes=new Array,o.attachedBlocks=new Array,o._mode=Mn.Material,o._options=Object(c.a)({emitComments:!1},i),o._attachImageProcessingConfiguration(null),o}return Object(c.d)(t,r),t.prototype._getGlobalNodeMaterialEditor=function(){return typeof NODEEDITOR<"u"?NODEEDITOR:typeof BABYLON<"u"&&BABYLON.NodeEditor!==void 0?BABYLON:void 0},Object.defineProperty(t.prototype,"options",{get:function(){return this._options},set:function(e){this._options=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"imageProcessingConfiguration",{get:function(){return this._imageProcessingConfiguration},set:function(e){this._attachImageProcessingConfiguration(e),this._markAllSubMeshesAsTexturesDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"mode",{get:function(){return this._mode},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"NodeMaterial"},t.prototype._attachImageProcessingConfiguration=function(e){var n=this;e!==this._imageProcessingConfiguration&&(this._imageProcessingConfiguration&&this._imageProcessingObserver&&this._imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingObserver),this._imageProcessingConfiguration=e||this.getScene().imageProcessingConfiguration,this._imageProcessingConfiguration&&(this._imageProcessingObserver=this._imageProcessingConfiguration.onUpdateParameters.add(function(){n._markAllSubMeshesAsImageProcessingDirty()})))},t.prototype.getBlockByName=function(e){for(var n=null,i=0,o=this.attachedBlocks;i<o.length;i++){var a=o[i];if(a.name===e){if(n)return Xe.b.Warn("More than one block was found with the name `"+e+"`"),n;n=a}}return n},t.prototype.getBlockByPredicate=function(e){for(var n=0,i=this.attachedBlocks;n<i.length;n++){var o=i[n];if(e(o))return o}return null},t.prototype.getInputBlockByPredicate=function(e){for(var n=0,i=this.attachedBlocks;n<i.length;n++){var o=i[n];if(o.isInput&&e(o))return o}return null},t.prototype.getInputBlocks=function(){for(var e=[],n=0,i=this.attachedBlocks;n<i.length;n++){var o=i[n];o.isInput&&e.push(o)}return e},t.prototype.registerOptimizer=function(e){if(!(this._optimizers.indexOf(e)>-1))return this._optimizers.push(e),this},t.prototype.unregisterOptimizer=function(e){var n=this._optimizers.indexOf(e);if(n!==-1)return this._optimizers.splice(n,1),this},t.prototype.addOutputNode=function(e){if(e.target===null)throw"This node is not meant to be an output node. You may want to explicitly set its target value.";return e.target&xe.Vertex&&this._addVertexOutputNode(e),e.target&xe.Fragment&&this._addFragmentOutputNode(e),this},t.prototype.removeOutputNode=function(e){return e.target===null||(e.target&xe.Vertex&&this._removeVertexOutputNode(e),e.target&xe.Fragment&&this._removeFragmentOutputNode(e)),this},t.prototype._addVertexOutputNode=function(e){if(this._vertexOutputNodes.indexOf(e)===-1)return e.target=xe.Vertex,this._vertexOutputNodes.push(e),this},t.prototype._removeVertexOutputNode=function(e){var n=this._vertexOutputNodes.indexOf(e);if(n!==-1)return this._vertexOutputNodes.splice(n,1),this},t.prototype._addFragmentOutputNode=function(e){if(this._fragmentOutputNodes.indexOf(e)===-1)return e.target=xe.Fragment,this._fragmentOutputNodes.push(e),this},t.prototype._removeFragmentOutputNode=function(e){var n=this._fragmentOutputNodes.indexOf(e);if(n!==-1)return this._fragmentOutputNodes.splice(n,1),this},t.prototype.needAlphaBlending=function(){return!this.ignoreAlpha&&(this.alpha<1||this._sharedData&&this._sharedData.hints.needAlphaBlending)},t.prototype.needAlphaTesting=function(){return this._sharedData&&this._sharedData.hints.needAlphaTesting},t.prototype._initializeBlock=function(e,n,i){if(e.initialize(n),e.autoConfigure(this),e._preparationId=this._buildId,this.attachedBlocks.indexOf(e)===-1){if(e.isUnique){for(var o=e.getClassName(),a=0,s=this.attachedBlocks;a<s.length;a++)if(s[a].getClassName()===o)throw"Cannot have multiple blocks of type "+o+" in the same NodeMaterial"}this.attachedBlocks.push(e)}for(var d=0,p=e.inputs;d<p.length;d++){var b=p[d];b.associatedVariableName="";var P=b.connectedPoint;if(P){var O=P.ownerBlock;O!==e&&((O.target===xe.VertexAndFragment||n.target===xe.Fragment&&O.target===xe.Vertex&&O._preparationId!==this._buildId)&&i.push(O),this._initializeBlock(O,n,i))}}for(var B=0,F=e.outputs;B<F.length;B++)F[B].associatedVariableName=""},t.prototype._resetDualBlocks=function(e,n){e.target===xe.VertexAndFragment&&(e.buildId=n);for(var i=0,o=e.inputs;i<o.length;i++){var a=o[i].connectedPoint;if(a){var s=a.ownerBlock;s!==e&&this._resetDualBlocks(s,n)}}},t.prototype.removeBlock=function(e){var n=this.attachedBlocks.indexOf(e);n>-1&&this.attachedBlocks.splice(n,1),e.isFinalMerger&&this.removeOutputNode(e)},t.prototype.build=function(e){e===void 0&&(e=!1),this._buildWasSuccessful=!1;var n=this.getScene().getEngine(),i=this._mode===Mn.Particle;if(this._vertexOutputNodes.length===0&&!i)throw"You must define at least one vertexOutputNode";if(this._fragmentOutputNodes.length===0)throw"You must define at least one fragmentOutputNode";this._vertexCompilationState=new lh,this._vertexCompilationState.supportUniformBuffers=n.supportsUniformBuffers,this._vertexCompilationState.target=xe.Vertex,this._fragmentCompilationState=new lh,this._fragmentCompilationState.supportUniformBuffers=n.supportsUniformBuffers,this._fragmentCompilationState.target=xe.Fragment,this._sharedData=new lm,this._vertexCompilationState.sharedData=this._sharedData,this._fragmentCompilationState.sharedData=this._sharedData,this._sharedData.buildId=this._buildId,this._sharedData.emitComments=this._options.emitComments,this._sharedData.verbose=e,this._sharedData.scene=this.getScene(),this._sharedData.allowEmptyVertexProgram=i;for(var o=[],a=[],s=0,d=this._vertexOutputNodes;s<d.length;s++){var p=d[s];o.push(p),this._initializeBlock(p,this._vertexCompilationState,a)}for(var b=0,P=this._fragmentOutputNodes;b<P.length;b++){var O=P[b];a.push(O),this._initializeBlock(O,this._fragmentCompilationState,o)}this.optimize();for(var B=0,F=o;B<F.length;B++)(p=F[B]).build(this._vertexCompilationState,o);this._fragmentCompilationState.uniforms=this._vertexCompilationState.uniforms.slice(0),this._fragmentCompilationState._uniformDeclaration=this._vertexCompilationState._uniformDeclaration,this._fragmentCompilationState._constantDeclaration=this._vertexCompilationState._constantDeclaration,this._fragmentCompilationState._vertexState=this._vertexCompilationState;for(var z=0,J=a;z<J.length;z++)O=J[z],this._resetDualBlocks(O,this._buildId-1);for(var ie=0,se=a;ie<se.length;ie++)(O=se[ie]).build(this._fragmentCompilationState,a);this._vertexCompilationState.finalize(this._vertexCompilationState),this._fragmentCompilationState.finalize(this._fragmentCompilationState),this._buildId=t._BuildIdGenerator++,this._sharedData.emitErrors(),e&&(console.log("Vertex shader:"),console.log(this._vertexCompilationState.compilationString),console.log("Fragment shader:"),console.log(this._fragmentCompilationState.compilationString)),this._buildWasSuccessful=!0,this.onBuildObservable.notifyObservers(this);for(var ce=0,ue=this.getScene().meshes;ce<ue.length;ce++){var fe=ue[ce];if(fe.subMeshes)for(var ve=0,Te=fe.subMeshes;ve<Te.length;ve++){var Re=Te[ve];if(Re.getMaterial()===this&&Re._materialDefines){var Ae=Re._materialDefines;Ae.markAllAsDirty(),Ae.reset()}}}},t.prototype.optimize=function(){for(var e=0,n=this._optimizers;e<n.length;e++)n[e].optimize(this._vertexOutputNodes,this._fragmentOutputNodes)},t.prototype._prepareDefinesForAttributes=function(e,n){var i=n.NORMAL,o=n.TANGENT,a=n.UV1;n.NORMAL=e.isVerticesDataPresent(Oe.b.NormalKind),n.TANGENT=e.isVerticesDataPresent(Oe.b.TangentKind),n.UV1=e.isVerticesDataPresent(Oe.b.UVKind),i===n.NORMAL&&o===n.TANGENT&&a===n.UV1||n.markAsAttributesDirty()},t.prototype.createPostProcess=function(e,n,i,o,a,s,d){return n===void 0&&(n=1),i===void 0&&(i=h.a.TEXTURE_NEAREST_SAMPLINGMODE),s===void 0&&(s=h.a.TEXTURETYPE_UNSIGNED_INT),d===void 0&&(d=h.a.TEXTUREFORMAT_RGBA),this.mode!==Mn.PostProcess?(console.log("Incompatible material mode"),null):this._createEffectForPostProcess(null,e,n,i,o,a,s,d)},t.prototype.createEffectForPostProcess=function(e){this._createEffectForPostProcess(e)},t.prototype._createEffectForPostProcess=function(e,n,i,o,a,s,d,p){var b=this;i===void 0&&(i=1),o===void 0&&(o=h.a.TEXTURE_NEAREST_SAMPLINGMODE),d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT),p===void 0&&(p=h.a.TEXTUREFORMAT_RGBA);var P=this.name+this._buildId,O=new To,B=new Dt.a(P+"PostProcess",this.getScene()),F=this._buildId;return this._processDefines(B,O),ze.a.RegisterShader(P,this._fragmentCompilationState._builtCompilationString,this._vertexCompilationState._builtCompilationString),e?e.updateEffect(O.toString(),this._fragmentCompilationState.uniforms,this._fragmentCompilationState.samplers,{maxSimultaneousLights:this.maxSimultaneousLights},void 0,void 0,P,P):e=new _t(this.name+"PostProcess",P,this._fragmentCompilationState.uniforms,this._fragmentCompilationState.samplers,i,n,o,a,s,O.toString(),d,P,{maxSimultaneousLights:this.maxSimultaneousLights},!1,p),e.nodeMaterialSource=this,e.onApplyObservable.add(function(z){F!==b._buildId&&(delete ze.a.ShadersStore[P+"VertexShader"],delete ze.a.ShadersStore[P+"PixelShader"],P=b.name+b._buildId,O.markAsUnprocessed(),F=b._buildId),b._processDefines(B,O)&&(ze.a.RegisterShader(P,b._fragmentCompilationState._builtCompilationString,b._vertexCompilationState._builtCompilationString),dh.a.SetImmediate(function(){return e.updateEffect(O.toString(),b._fragmentCompilationState.uniforms,b._fragmentCompilationState.samplers,{maxSimultaneousLights:b.maxSimultaneousLights},void 0,void 0,P,P)})),b._checkInternals(z)}),e},t.prototype.createProceduralTexture=function(e,n){var i=this;if(this.mode!==Mn.ProceduralTexture)return console.log("Incompatible material mode"),null;var o=this.name+this._buildId,a=new go(o,e,null,n),s=new Dt.a(o+"Procedural",this.getScene());s.reservedDataStore={hidden:!0};var d=new To,p=this._processDefines(s,d);ze.a.RegisterShader(o,this._fragmentCompilationState._builtCompilationString,this._vertexCompilationState._builtCompilationString);var b=this.getScene().getEngine().createEffect({vertexElement:o,fragmentElement:o},[Oe.b.PositionKind],this._fragmentCompilationState.uniforms,this._fragmentCompilationState.samplers,d.toString(),p?.fallbacks,void 0);a.nodeMaterialSource=this,a._effect=b;var P=this._buildId;return a.onBeforeGenerationObservable.add(function(){P!==i._buildId&&(delete ze.a.ShadersStore[o+"VertexShader"],delete ze.a.ShadersStore[o+"PixelShader"],o=i.name+i._buildId,d.markAsUnprocessed(),P=i._buildId);var O=i._processDefines(s,d);O&&(ze.a.RegisterShader(o,i._fragmentCompilationState._builtCompilationString,i._vertexCompilationState._builtCompilationString),dh.a.SetImmediate(function(){b=i.getScene().getEngine().createEffect({vertexElement:o,fragmentElement:o},[Oe.b.PositionKind],i._fragmentCompilationState.uniforms,i._fragmentCompilationState.samplers,d.toString(),O?.fallbacks,void 0),a._effect=b})),i._checkInternals(b)}),a},t.prototype._createEffectForParticles=function(e,n,i,o,a,s,d,p){var b=this;p===void 0&&(p="");var P=this.name+this._buildId+"_"+n;s||(s=new To),d||(d=this.getScene().getMeshByName(this.name+"Particle"))||((d=new Dt.a(this.name+"Particle",this.getScene())).reservedDataStore={hidden:!0});var O=this._buildId,B=[],F=p;if(!a){var z=this._processDefines(d,s);ze.a.RegisterShader(P,this._fragmentCompilationState._builtCompilationString),e.fillDefines(B,n),F=B.join(`
-`),a=this.getScene().getEngine().createEffectForParticles(P,this._fragmentCompilationState.uniforms,this._fragmentCompilationState.samplers,s.toString()+`
-`+F,z?.fallbacks,i,o,e),e.setCustomEffect(a,n)}a.onBindObservable.add(function(J){O!==b._buildId&&(delete ze.a.ShadersStore[P+"PixelShader"],P=b.name+b._buildId+"_"+n,s.markAsUnprocessed(),O=b._buildId),B.length=0,e.fillDefines(B,n);var ie=B.join(`
-`);ie!==F&&(s.markAsUnprocessed(),F=ie);var se=b._processDefines(d,s);if(se)return ze.a.RegisterShader(P,b._fragmentCompilationState._builtCompilationString),J=b.getScene().getEngine().createEffectForParticles(P,b._fragmentCompilationState.uniforms,b._fragmentCompilationState.samplers,s.toString()+`
-`+F,se?.fallbacks,i,o,e),e.setCustomEffect(J,n),void b._createEffectForParticles(e,n,i,o,J,s,d,F);b._checkInternals(J)})},t.prototype._checkInternals=function(e){if(this._sharedData.animatedInputs){var n=this.getScene(),i=n.getFrameId();if(this._animationFrame!==i){for(var o=0,a=this._sharedData.animatedInputs;o<a.length;o++)a[o].animate(n);this._animationFrame=i}}for(var s=0,d=this._sharedData.bindableBlocks;s<d.length;s++)d[s].bind(e,this);for(var p=0,b=this._sharedData.inputBlocks;p<b.length;p++)b[p]._transmit(e,this.getScene())},t.prototype.createEffectForParticles=function(e,n,i){this.mode===Mn.Particle?(this._createEffectForParticles(e,yo.BLENDMODE_ONEONE,n,i),this._createEffectForParticles(e,yo.BLENDMODE_MULTIPLY,n,i)):console.log("Incompatible material mode")},t.prototype._processDefines=function(e,n,i,o){var a=this;i===void 0&&(i=!1);var s=null;if(this._sharedData.blocksWithDefines.forEach(function(B){B.initializeDefines(e,a,n,i)}),this._sharedData.blocksWithDefines.forEach(function(B){B.prepareDefines(e,a,n,i,o)}),n.isDirty){var d=n._areLightsDisposed;n.markAsProcessed(),this._vertexCompilationState.compilationString=this._vertexCompilationState._builtCompilationString,this._fragmentCompilationState.compilationString=this._fragmentCompilationState._builtCompilationString,this._sharedData.repeatableContentBlocks.forEach(function(B){B.replaceRepeatableContent(a._vertexCompilationState,a._fragmentCompilationState,e,n)});var p=[];this._sharedData.dynamicUniformBlocks.forEach(function(B){B.updateUniformsAndSamples(a._vertexCompilationState,a,n,p)});var b=this._vertexCompilationState.uniforms;this._fragmentCompilationState.uniforms.forEach(function(B){b.indexOf(B)===-1&&b.push(B)});var P=this._vertexCompilationState.samplers;this._fragmentCompilationState.samplers.forEach(function(B){P.indexOf(B)===-1&&P.push(B)});var O=new Sr.a;this._sharedData.blocksWithFallbacks.forEach(function(B){B.provideFallbacks(e,O)}),s={lightDisposed:d,uniformBuffers:p,mergedUniforms:b,mergedSamplers:P,fallbacks:O}}return s},t.prototype.isReadyForSubMesh=function(e,n,i){var o=this;if(i===void 0&&(i=!1),!this._buildWasSuccessful)return!1;var a=this.getScene();if(this._sharedData.animatedInputs){var s=a.getFrameId();if(this._animationFrame!==s){for(var d=0,p=this._sharedData.animatedInputs;d<p.length;d++)p[d].animate(a);this._animationFrame=s}}if(n.effect&&this.isFrozen&&n.effect._wasPreviouslyReady)return!0;n._materialDefines||(n._materialDefines=new To);var b=n._materialDefines;if(this._isReadyForSubMesh(n))return!0;var P=a.getEngine();if(this._prepareDefinesForAttributes(e,b),this._sharedData.blockingBlocks.some(function(J){return!J.isReady(e,o,b,i)}))return!1;var O=this._processDefines(e,b,i,n);if(O){var B=n.effect,F=b.toString(),z=P.createEffect({vertex:"nodeMaterial"+this._buildId,fragment:"nodeMaterial"+this._buildId,vertexSource:this._vertexCompilationState.compilationString,fragmentSource:this._fragmentCompilationState.compilationString},{attributes:this._vertexCompilationState.attributes,uniformsNames:O.mergedUniforms,uniformBuffersNames:O.uniformBuffers,samplers:O.mergedSamplers,defines:F,fallbacks:O.fallbacks,onCompiled:this.onCompiled,onError:this.onError,indexParameters:{maxSimultaneousLights:this.maxSimultaneousLights,maxSimultaneousMorphTargets:b.NUM_MORPH_INFLUENCERS}},P);if(z)if(this._onEffectCreatedObservable&&(hc.effect=z,hc.subMesh=n,this._onEffectCreatedObservable.notifyObservers(hc)),this.allowShaderHotSwapping&&B&&!z.isReady()){if(z=B,b.markAsUnprocessed(),O.lightDisposed)return b._areLightsDisposed=!0,!1}else a.resetCachedMaterial(),n.setEffect(z,b)}return!(!n.effect||!n.effect.isReady())&&(b._renderId=a.getRenderId(),n.effect._wasPreviouslyReady=!0,!0)},Object.defineProperty(t.prototype,"compiledShaders",{get:function(){return`// Vertex shader\r
-`+this._vertexCompilationState.compilationString+`\r
-\r
-// Fragment shader\r
-`+this._fragmentCompilationState.compilationString},enumerable:!1,configurable:!0}),t.prototype.bindOnlyWorldMatrix=function(e){var n=this.getScene();if(this._activeEffect){var i=this._sharedData.hints;i.needWorldViewMatrix&&e.multiplyToRef(n.getViewMatrix(),this._cachedWorldViewMatrix),i.needWorldViewProjectionMatrix&&e.multiplyToRef(n.getTransformMatrix(),this._cachedWorldViewProjectionMatrix);for(var o=0,a=this._sharedData.inputBlocks;o<a.length;o++)a[o]._transmitWorld(this._activeEffect,e,this._cachedWorldViewMatrix,this._cachedWorldViewProjectionMatrix)}},t.prototype.bindForSubMesh=function(e,n,i){var o=this.getScene(),a=i.effect;if(a){if(this._activeEffect=a,this.bindOnlyWorldMatrix(e),this._mustRebind(o,a,n.visibility)){var s=this._sharedData;if(a&&o.getCachedEffect()!==a){for(var d=0,p=s.bindableBlocks;d<p.length;d++)p[d].bind(a,this,n,i);for(var b=0,P=s.inputBlocks;b<P.length;b++)P[b]._transmit(a,o)}}this._afterBind(n,this._activeEffect)}},t.prototype.getActiveTextures=function(){var e=r.prototype.getActiveTextures.call(this);return this._sharedData&&e.push.apply(e,this._sharedData.textureBlocks.filter(function(n){return n.texture}).map(function(n){return n.texture})),e},t.prototype.getTextureBlocks=function(){return this._sharedData?this._sharedData.textureBlocks:[]},t.prototype.hasTexture=function(e){if(r.prototype.hasTexture.call(this,e))return!0;if(!this._sharedData)return!1;for(var n=0,i=this._sharedData.textureBlocks;n<i.length;n++)if(i[n].texture===e)return!0;return!1},t.prototype.dispose=function(e,n,i){if(n)for(var o=0,a=this._sharedData.textureBlocks.filter(function(p){return p.texture}).map(function(p){return p.texture});o<a.length;o++)a[o].dispose();for(var s=0,d=this.attachedBlocks;s<d.length;s++)d[s].dispose();this.onBuildObservable.clear(),r.prototype.dispose.call(this,e,n,i)},t.prototype._createNodeEditor=function(){this.BJSNODEMATERIALEDITOR=this.BJSNODEMATERIALEDITOR||this._getGlobalNodeMaterialEditor(),this.BJSNODEMATERIALEDITOR.NodeEditor.Show({nodeMaterial:this})},t.prototype.edit=function(e){var n=this;return new Promise(function(i,o){if(n.BJSNODEMATERIALEDITOR===void 0){var a=e&&e.editorURL?e.editorURL:t.EditorURL;Xe.b.LoadScript(a,function(){n._createNodeEditor(),i()})}else n._createNodeEditor(),i()})},t.prototype.clear=function(){this._vertexOutputNodes=[],this._fragmentOutputNodes=[],this.attachedBlocks=[]},t.prototype.setToDefault=function(){this.clear(),this.editorData=null;var e=new At("Position");e.setAsAttribute("position");var n=new At("World");n.setAsSystemValue(BABYLON.NodeMaterialSystemValues.World);var i=new fa("WorldPos");e.connectTo(i),n.connectTo(i);var o=new At("ViewProjection");o.setAsSystemValue(BABYLON.NodeMaterialSystemValues.ViewProjection);var a=new fa("WorldPos * ViewProjectionTransform");i.connectTo(a),o.connectTo(a);var s=new vo("VertexOutput");a.connectTo(s);var d=new At("color");d.value=new M.b(.8,.8,.8,1);var p=new Lr("FragmentOutput");d.connectTo(p),this.addOutputNode(s),this.addOutputNode(p),this._mode=Mn.Material},t.prototype.setToDefaultPostProcess=function(){this.clear(),this.editorData=null;var e=new At("Position");e.setAsAttribute("position2d");var n=new At("Constant1");n.isConstant=!0,n.value=1;var i=new bo("Position3D");e.connectTo(i),n.connectTo(i,{input:"w"});var o=new vo("VertexOutput");i.connectTo(o);var a=new At("Scale");a.visibleInInspector=!0,a.value=new u.d(1,1);var s=new ic("uv0");e.connectTo(s);var d=new pa("UV scale");s.connectTo(d),a.connectTo(d);var p=new $s("CurrentScreen");d.connectTo(p),p.texture=new we.a("https://assets.babylonjs.com/nme/currentScreenPostProcess.png",this.getScene());var b=new Lr("FragmentOutput");p.connectTo(b,{output:"rgba"}),this.addOutputNode(o),this.addOutputNode(b),this._mode=Mn.PostProcess},t.prototype.setToDefaultProceduralTexture=function(){this.clear(),this.editorData=null;var e=new At("Position");e.setAsAttribute("position2d");var n=new At("Constant1");n.isConstant=!0,n.value=1;var i=new bo("Position3D");e.connectTo(i),n.connectTo(i,{input:"w"});var o=new vo("VertexOutput");i.connectTo(o);var a=new At("Time");a.value=0,a.min=0,a.max=0,a.isBoolean=!1,a.matrixMode=0,a.animationType=ji.Time,a.isConstant=!1;var s=new At("Color3");s.value=new M.a(1,1,1),s.isConstant=!1;var d=new Lr("FragmentOutput"),p=new bo("VectorMerger");p.visibleInInspector=!1;var b=new uc("Cos");b.operation=rn.Cos,e.connectTo(p),a.output.connectTo(b.input),b.output.connectTo(p.z),p.xyzOut.connectTo(d.rgb),this.addOutputNode(o),this.addOutputNode(d),this._mode=Mn.ProceduralTexture},t.prototype.setToDefaultParticle=function(){this.clear(),this.editorData=null;var e=new At("uv");e.setAsAttribute("particle_uv");var n=new ec("ParticleTexture");e.connectTo(n);var i=new At("Color");i.setAsAttribute("particle_color");var o=new pa("Texture * Color");n.connectTo(o),i.connectTo(o);var a=new tc("ParticleRampGradient");o.connectTo(a);var s=new lc("ColorSplitter");i.connectTo(s);var d=new nc("ParticleBlendMultiply");a.connectTo(d),n.connectTo(d,{output:"a"}),s.connectTo(d,{output:"a"});var p=new Lr("FragmentOutput");d.connectTo(p),this.addOutputNode(p),this._mode=Mn.Particle},t.prototype.loadAsync=function(e){var n=this;return this.getScene()._loadFileAsync(e).then(function(i){var o=JSON.parse(i);n.loadFromSerialization(o,"")})},t.prototype._gatherBlocks=function(e,n){if(n.indexOf(e)===-1){n.push(e);for(var i=0,o=e.inputs;i<o.length;i++){var a=o[i].connectedPoint;if(a){var s=a.ownerBlock;s!==e&&this._gatherBlocks(s,n)}}}},t.prototype.generateCode=function(){for(var e=[],n=[],i=[],o=0,a=this._vertexOutputNodes;o<a.length;o++){var s=a[o];this._gatherBlocks(s,n)}for(var d=[],p=0,b=this._fragmentOutputNodes;p<b.length;p++)s=b[p],this._gatherBlocks(s,d);for(var P='var nodeMaterial = new BABYLON.NodeMaterial("'+(this.name||"node material")+`");\r
-`,O=0,B=n;O<B.length;O++)(Re=B[O]).isInput&&e.indexOf(Re)===-1&&(P+=Re._dumpCode(i,e));for(var F=0,z=d;F<z.length;F++)(Re=z[F]).isInput&&e.indexOf(Re)===-1&&(P+=Re._dumpCode(i,e));e=[],P+=`\r
-// Connections\r
-`;for(var J=0,ie=this._vertexOutputNodes;J<ie.length;J++)P+=(Re=ie[J])._dumpCodeForOutputConnections(e);for(var se=0,ce=this._fragmentOutputNodes;se<ce.length;se++)P+=(Re=ce[se])._dumpCodeForOutputConnections(e);P+=`\r
-// Output nodes\r
-`;for(var ue=0,fe=this._vertexOutputNodes;ue<fe.length;ue++)P+="nodeMaterial.addOutputNode("+(Re=fe[ue])._codeVariableName+`);\r
-`;for(var ve=0,Te=this._fragmentOutputNodes;ve<Te.length;ve++){var Re;P+="nodeMaterial.addOutputNode("+(Re=Te[ve])._codeVariableName+`);\r
-`}return P+=`nodeMaterial.build();\r
-`},t.prototype.serialize=function(e){var n=e?{}:L.a.Serialize(this);n.editorData=JSON.parse(JSON.stringify(this.editorData));var i=[];if(e)i=e;else{n.customType="BABYLON.NodeMaterial",n.outputNodes=[];for(var o=0,a=this._vertexOutputNodes;o<a.length;o++){var s=a[o];this._gatherBlocks(s,i),n.outputNodes.push(s.uniqueId)}for(var d=0,p=this._fragmentOutputNodes;d<p.length;d++)s=p[d],this._gatherBlocks(s,i),n.outputNodes.indexOf(s.uniqueId)===-1&&n.outputNodes.push(s.uniqueId)}n.blocks=[];for(var b=0,P=i;b<P.length;b++){var O=P[b];n.blocks.push(O.serialize())}if(!e)for(var B=0,F=this.attachedBlocks;B<F.length;B++)O=F[B],i.indexOf(O)===-1&&n.blocks.push(O.serialize());return n},t.prototype._restoreConnections=function(e,n,i){for(var o=0,a=e.outputs;o<a.length;o++)for(var s=a[o],d=0,p=n.blocks;d<p.length;d++){var b=p[d],P=i[b.id];if(P)for(var O=0,B=b.inputs;O<B.length;O++){var F=B[O];if(!(i[F.targetBlockId]!==e||F.targetConnectionName!==s.name)){var z=P.getInputByName(F.inputName);if(!z||z.isConnected)continue;s.connectTo(z,!0),this._restoreConnections(P,n,i)}}}},t.prototype.loadFromSerialization=function(e,n,i){var o;n===void 0&&(n=""),i===void 0&&(i=!1),i||this.clear();for(var a={},s=0,d=e.blocks;s<d.length;s++){var p=d[s],b=R.a.GetClass(p.customType);b&&((O=new b)._deserialize(p,this.getScene(),n),a[p.id]=O,this.attachedBlocks.push(O))}for(var P=0;P<e.blocks.length;P++){var O;(O=a[e.blocks[P].id])&&(O.inputs.length&&!i||this._restoreConnections(O,e,a))}if(e.outputNodes)for(var B=0,F=e.outputNodes;B<F.length;B++){var z=F[B];this.addOutputNode(a[z])}if(e.locations||e.editorData&&e.editorData.locations){for(var J=e.locations||e.editorData.locations,ie=0,se=J;ie<se.length;ie++){var ce=se[ie];a[ce.blockId]&&(ce.blockId=a[ce.blockId].uniqueId)}i&&this.editorData&&this.editorData.locations&&J.concat(this.editorData.locations),e.locations?this.editorData={locations:J}:(this.editorData=e.editorData,this.editorData.locations=J);var ue=[];for(var fe in a)ue[fe]=a[fe].uniqueId;this.editorData.map=ue}this.comment=e.comment,i||(this._mode=(o=e.mode)!==null&&o!==void 0?o:Mn.Material)},t.prototype.clone=function(e){var n=this,i=this.serialize(),o=L.a.Clone(function(){return new t(e,n.getScene(),n.options)},this);return o.id=e,o.name=e,o.loadFromSerialization(i),o.build(),o},t.Parse=function(e,n,i){i===void 0&&(i="");var o=L.a.Parse(function(){return new t(e.name,n)},e,n,i);return o.loadFromSerialization(e,i),o.build(),o},t.ParseFromFileAsync=function(e,n,i){var o=new t(e,i);return new Promise(function(a,s){return o.loadAsync(n).then(function(){o.build(),a(o)}).catch(s)})},t.ParseFromSnippetAsync=function(e,n,i,o){var a=this;return i===void 0&&(i=""),e==="_BLANK"?Promise.resolve(this.CreateDefault("blank",n)):new Promise(function(s,d){var p=new re.a;p.addEventListener("readystatechange",function(){if(p.readyState==4)if(p.status==200){var b=JSON.parse(JSON.parse(p.responseText).jsonPayload),P=JSON.parse(b.nodeMaterial);o||((o=L.a.Parse(function(){return new t(e,n)},P,n,i)).uniqueId=n.getUniqueId()),o.loadFromSerialization(P),o.snippetId=e;try{o.build(),s(o)}catch(O){d(O)}}else d("Unable to load the snippet "+e)}),p.open("GET",a.SnippetUrl+"/"+e.replace(/#/g,"/")),p.send()})},t.CreateDefault=function(e,n){var i=new t(e,n);return i.setToDefault(),i.build(),i},t._BuildIdGenerator=0,t.EditorURL="https://unpkg.com/babylonjs-node-editor@"+Ue.a.Version+"/babylon.nodeEditor.js",t.SnippetUrl="https://snippet.babylonjs.com",t.IgnoreTexturesAtLoadTime=!1,Object(c.c)([Object(L.c)("mode")],t.prototype,"_mode",void 0),Object(c.c)([Object(L.c)("comment")],t.prototype,"comment",void 0),t}($o.a);R.a.RegisteredTypes["BABYLON.NodeMaterial"]=ga;var fh=function(r){function t(e){var n=r.call(this,e,xe.Vertex)||this;return n.registerInput("matricesIndices",le.Vector4),n.registerInput("matricesWeights",le.Vector4),n.registerInput("matricesIndicesExtra",le.Vector4,!0),n.registerInput("matricesWeightsExtra",le.Vector4,!0),n.registerInput("world",le.Matrix),n.registerOutput("output",le.Matrix),n}return Object(c.d)(t,r),t.prototype.initialize=function(e){e._excludeVariableName("boneSampler"),e._excludeVariableName("boneTextureWidth"),e._excludeVariableName("mBones"),e._excludeVariableName("BonesPerMesh")},t.prototype.getClassName=function(){return"BonesBlock"},Object.defineProperty(t.prototype,"matricesIndices",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"matricesWeights",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"matricesIndicesExtra",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"matricesWeightsExtra",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"world",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.matricesIndices.isConnected){var n=e.getInputBlockByPredicate(function(a){return a.isAttribute&&a.name==="matricesIndices"});n||(n=new At("matricesIndices")).setAsAttribute("matricesIndices"),n.output.connectTo(this.matricesIndices)}if(!this.matricesWeights.isConnected){var i=e.getInputBlockByPredicate(function(a){return a.isAttribute&&a.name==="matricesWeights"});i||(i=new At("matricesWeights")).setAsAttribute("matricesWeights"),i.output.connectTo(this.matricesWeights)}if(!this.world.isConnected){var o=e.getInputBlockByPredicate(function(a){return a.systemValue===bt.World});o||(o=new At("world")).setAsSystemValue(bt.World),o.output.connectTo(this.world)}},t.prototype.provideFallbacks=function(e,n){e&&e.useBones&&e.computeBonesUsingShaders&&e.skeleton&&n.addCPUSkinningFallback(0,e)},t.prototype.bind=function(e,n,i){et.a.BindBonesParameters(i,e)},t.prototype.prepareDefines=function(e,n,i){i._areAttributesDirty&&et.a.PrepareDefinesForBones(e,i)},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e),e.sharedData.blocksWithFallbacks.push(this),e.sharedData.bindableBlocks.push(this),e.sharedData.blocksWithDefines.push(this),e.uniforms.push("boneTextureWidth"),e.uniforms.push("mBones"),e.samplers.push("boneSampler");var n="//"+this.name;e._emitFunctionFromInclude("bonesDeclaration",n,{removeAttributes:!0,removeUniforms:!1,removeVaryings:!0,removeIfDef:!1});var i=e._getFreeVariableName("influence");e.compilationString+=e._emitCodeFromInclude("bonesVertex",n,{replaceStrings:[{search:/finalWorld=finalWorld\*influence;/,replace:""},{search:/influence/gm,replace:i}]});var o=this._outputs[0],a=this.world;return e.compilationString+=`#if NUM_BONE_INFLUENCERS>0\r
-`,e.compilationString+=this._declareOutput(o,e)+" = "+a.associatedVariableName+" * "+i+`;\r
-`,e.compilationString+=`#else\r
-`,e.compilationString+=this._declareOutput(o,e)+" = "+a.associatedVariableName+`;\r
-`,e.compilationString+=`#endif\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.BonesBlock"]=fh;var ph=function(r){function t(e){var n=r.call(this,e,xe.Vertex)||this;return n.registerInput("world0",le.Vector4),n.registerInput("world1",le.Vector4),n.registerInput("world2",le.Vector4),n.registerInput("world3",le.Vector4),n.registerInput("world",le.Matrix,!0),n.registerOutput("output",le.Matrix),n.registerOutput("instanceID",le.Float),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"InstancesBlock"},Object.defineProperty(t.prototype,"world0",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"world1",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"world2",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"world3",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"world",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"instanceID",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.world0.connectedPoint){var n=e.getInputBlockByPredicate(function(d){return d.isAttribute&&d.name==="world0"});n||(n=new At("world0")).setAsAttribute("world0"),n.output.connectTo(this.world0)}if(!this.world1.connectedPoint){var i=e.getInputBlockByPredicate(function(d){return d.isAttribute&&d.name==="world1"});i||(i=new At("world1")).setAsAttribute("world1"),i.output.connectTo(this.world1)}if(!this.world2.connectedPoint){var o=e.getInputBlockByPredicate(function(d){return d.isAttribute&&d.name==="world2"});o||(o=new At("world2")).setAsAttribute("world2"),o.output.connectTo(this.world2)}if(!this.world3.connectedPoint){var a=e.getInputBlockByPredicate(function(d){return d.isAttribute&&d.name==="world3"});a||(a=new At("world3")).setAsAttribute("world3"),a.output.connectTo(this.world3)}if(!this.world.connectedPoint){var s=e.getInputBlockByPredicate(function(d){return d.isAttribute&&d.name==="world"});s||(s=new At("world")).setAsSystemValue(bt.World),s.output.connectTo(this.world)}this.world.define="!INSTANCES || THIN_INSTANCES"},t.prototype.prepareDefines=function(e,n,i,o,a){o===void 0&&(o=!1);var s=!1;i.INSTANCES!==o&&(i.setValue("INSTANCES",o),s=!0),a&&i.THIN_INSTANCES!==!!a?.getRenderingMesh().hasThinInstances&&(i.setValue("THIN_INSTANCES",!!a?.getRenderingMesh().hasThinInstances),s=!0),s&&i.markAsUnprocessed()},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e),e.sharedData.blocksWithDefines.push(this);var n=this._outputs[0],i=this._outputs[1],o=this.world0,a=this.world1,s=this.world2,d=this.world3;return e.compilationString+=`#ifdef INSTANCES\r
-`,e.compilationString+=this._declareOutput(n,e)+" = mat4("+o.associatedVariableName+", "+a.associatedVariableName+", "+s.associatedVariableName+", "+d.associatedVariableName+`);\r
-`,e.compilationString+=`#ifdef THIN_INSTANCES\r
-`,e.compilationString+=n.associatedVariableName+" = "+this.world.associatedVariableName+" * "+n.associatedVariableName+`;\r
-`,e.compilationString+=`#endif\r
-`,e.compilationString+=this._declareOutput(i,e)+` = float(gl_InstanceID);\r
-`,e.compilationString+=`#else\r
-`,e.compilationString+=this._declareOutput(n,e)+" = "+this.world.associatedVariableName+`;\r
-`,e.compilationString+=this._declareOutput(i,e)+` = 0.0;\r
-`,e.compilationString+=`#endif\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.InstancesBlock"]=ph;var _h=function(r){function t(e){var n=r.call(this,e,xe.Vertex)||this;return n.registerInput("position",le.Vector3),n.registerInput("normal",le.Vector3),n.registerInput("tangent",le.Vector3),n.registerInput("uv",le.Vector2),n.registerOutput("positionOutput",le.Vector3),n.registerOutput("normalOutput",le.Vector3),n.registerOutput("tangentOutput",le.Vector3),n.registerOutput("uvOutput",le.Vector2),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"MorphTargetsBlock"},Object.defineProperty(t.prototype,"position",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"normal",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"tangent",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"uv",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"positionOutput",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"normalOutput",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"tangentOutput",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"uvOutput",{get:function(){return this._outputs[3]},enumerable:!1,configurable:!0}),t.prototype.initialize=function(e){e._excludeVariableName("morphTargetInfluences")},t.prototype.autoConfigure=function(e){if(!this.position.isConnected){var n=e.getInputBlockByPredicate(function(s){return s.isAttribute&&s.name==="position"});n||(n=new At("position")).setAsAttribute(),n.output.connectTo(this.position)}if(!this.normal.isConnected){var i=e.getInputBlockByPredicate(function(s){return s.isAttribute&&s.name==="normal"});i||(i=new At("normal")).setAsAttribute("normal"),i.output.connectTo(this.normal)}if(!this.tangent.isConnected){var o=e.getInputBlockByPredicate(function(s){return s.isAttribute&&s.name==="tangent"});o||(o=new At("tangent")).setAsAttribute("tangent"),o.output.connectTo(this.tangent)}if(!this.uv.isConnected){var a=e.getInputBlockByPredicate(function(s){return s.isAttribute&&s.name==="uv"});a||(a=new At("uv")).setAsAttribute("uv"),a.output.connectTo(this.uv)}},t.prototype.prepareDefines=function(e,n,i){i._areAttributesDirty&&et.a.PrepareDefinesForMorphTargets(e,i)},t.prototype.bind=function(e,n,i){i&&i.morphTargetManager&&i.morphTargetManager.numInfluencers>0&&et.a.BindMorphTargetParameters(i,e)},t.prototype.replaceRepeatableContent=function(e,n,i,o){for(var a=this.position,s=this.normal,d=this.tangent,p=this.uv,b=this.positionOutput,P=this.normalOutput,O=this.tangentOutput,B=this.uvOutput,F=e,z=o.NUM_MORPH_INFLUENCERS,J=i.morphTargetManager,ie=J&&J.supportsNormals&&o.NORMAL,se=J&&J.supportsTangents&&o.TANGENT,ce=J&&J.supportsUVs&&o.UV1,ue="",fe=0;fe<z;fe++)ue+=`#ifdef MORPHTARGETS\r
-`,ue+=b.associatedVariableName+" += (position"+fe+" - "+a.associatedVariableName+") * morphTargetInfluences["+fe+`];\r
-`,ie&&(ue+=`#ifdef MORPHTARGETS_NORMAL\r
-`,ue+=P.associatedVariableName+" += (normal"+fe+" - "+s.associatedVariableName+") * morphTargetInfluences["+fe+`];\r
-`,ue+=`#endif\r
-`),se&&(ue+=`#ifdef MORPHTARGETS_TANGENT\r
-`,ue+=O.associatedVariableName+".xyz += (tangent"+fe+" - "+d.associatedVariableName+".xyz) * morphTargetInfluences["+fe+`];\r
-`,ue+=`#endif\r
-`),ce&&(ue+=`#ifdef MORPHTARGETS_UV\r
-`,ue+=B.associatedVariableName+".xy += (uv_"+fe+" - "+p.associatedVariableName+".xy) * morphTargetInfluences["+fe+`];\r
-`,ue+=`#endif\r
-`),ue+=`#endif\r
-`;if(F.compilationString=F.compilationString.replace(this._repeatableContentAnchor,ue),z>0)for(fe=0;fe<z;fe++)F.attributes.push(Oe.b.PositionKind+fe),ie&&F.attributes.push(Oe.b.NormalKind+fe),se&&F.attributes.push(Oe.b.TangentKind+fe),ce&&F.attributes.push(Oe.b.UVKind+"_"+fe)},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e),e.sharedData.blocksWithDefines.push(this),e.sharedData.bindableBlocks.push(this),e.sharedData.repeatableContentBlocks.push(this);var n=this.position,i=this.normal,o=this.tangent,a=this.uv,s=this.positionOutput,d=this.normalOutput,p=this.tangentOutput,b=this.uvOutput,P="//"+this.name;return e.uniforms.push("morphTargetInfluences"),e._emitFunctionFromInclude("morphTargetsVertexGlobalDeclaration",P),e._emitFunctionFromInclude("morphTargetsVertexDeclaration",P,{repeatKey:"maxSimultaneousMorphTargets"}),e.compilationString+=this._declareOutput(s,e)+" = "+n.associatedVariableName+`;\r
-`,e.compilationString+=`#ifdef NORMAL\r
-`,e.compilationString+=this._declareOutput(d,e)+" = "+i.associatedVariableName+`;\r
-`,e.compilationString+=`#else\r
-`,e.compilationString+=this._declareOutput(d,e)+` = vec3(0., 0., 0.);\r
-`,e.compilationString+=`#endif\r
-`,e.compilationString+=`#ifdef TANGENT\r
-`,e.compilationString+=this._declareOutput(p,e)+" = "+o.associatedVariableName+`;\r
-`,e.compilationString+=`#else\r
-`,e.compilationString+=this._declareOutput(p,e)+` = vec3(0., 0., 0.);\r
-`,e.compilationString+=`#endif\r
-`,e.compilationString+=`#ifdef UV1\r
-`,e.compilationString+=this._declareOutput(b,e)+" = "+a.associatedVariableName+`;\r
-`,e.compilationString+=`#else\r
-`,e.compilationString+=this._declareOutput(b,e)+` = vec2(0., 0.);\r
-`,e.compilationString+=`#endif\r
-`,this._repeatableContentAnchor=e._repeatableContentAnchor,e.compilationString+=this._repeatableContentAnchor,this},t}(pt);R.a.RegisteredTypes["BABYLON.MorphTargetsBlock"]=_h;var mh=function(r){function t(e){var n=r.call(this,e,xe.Vertex)||this;return n.registerInput("worldPosition",le.Vector4,!1,xe.Vertex),n.registerOutput("direction",le.Vector3),n.registerOutput("color",le.Color3),n.registerOutput("intensity",le.Float),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"LightInformationBlock"},Object.defineProperty(t.prototype,"worldPosition",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"direction",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"color",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"intensity",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),t.prototype.bind=function(e,n,i){if(i){this.light&&this.light.isDisposed&&(this.light=null);var o=this.light,a=n.getScene();if(!o&&a.lights.length&&(o=a.lights[0]),!o||!o.isEnabled)return e.setFloat3(this._lightDataUniformName,0,0,0),void e.setFloat4(this._lightColorUniformName,0,0,0,0);o.transferToNodeMaterialEffect(e,this._lightDataUniformName),e.setColor4(this._lightColorUniformName,o.diffuse,o.intensity)}},t.prototype.prepareDefines=function(e,n,i){if(i._areLightsDirty){var o=this.light;i.setValue(this._lightTypeDefineName,!!(o&&o instanceof Hs))}},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e),e.sharedData.bindableBlocks.push(this),e.sharedData.blocksWithDefines.push(this);var n=this.direction,i=this.color,o=this.intensity;return this._lightDataUniformName=e._getFreeVariableName("lightData"),this._lightColorUniformName=e._getFreeVariableName("lightColor"),this._lightTypeDefineName=e._getFreeDefineName("LIGHTPOINTTYPE"),e._emitUniformFromString(this._lightDataUniformName,"vec3"),e._emitUniformFromString(this._lightColorUniformName,"vec4"),e.compilationString+="#ifdef "+this._lightTypeDefineName+`\r
-`,e.compilationString+=this._declareOutput(n,e)+" = normalize("+this.worldPosition.associatedVariableName+".xyz - "+this._lightDataUniformName+`);\r
-`,e.compilationString+=`#else\r
-`,e.compilationString+=this._declareOutput(n,e)+" = "+this._lightDataUniformName+`;\r
-`,e.compilationString+=`#endif\r
-`,e.compilationString+=this._declareOutput(i,e)+" = "+this._lightColorUniformName+`.rgb;\r
-`,e.compilationString+=this._declareOutput(o,e)+" = "+this._lightColorUniformName+`.a;\r
-`,this},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return this.light&&(e.lightId=this.light.id),e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),e.lightId&&(this.light=n.getLightByID(e.lightId))},t}(pt);R.a.RegisteredTypes["BABYLON.LightInformationBlock"]=mh;var gh=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n.registerInput("color",le.Color4),n.registerOutput("output",le.Color4),n._inputs[0].acceptedConnectionPointTypes.push(le.Color3),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ImageProcessingBlock"},Object.defineProperty(t.prototype,"color",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.initialize=function(e){e._excludeVariableName("exposureLinear"),e._excludeVariableName("contrast"),e._excludeVariableName("vInverseScreenSize"),e._excludeVariableName("vignetteSettings1"),e._excludeVariableName("vignetteSettings2"),e._excludeVariableName("vCameraColorCurveNegative"),e._excludeVariableName("vCameraColorCurveNeutral"),e._excludeVariableName("vCameraColorCurvePositive"),e._excludeVariableName("txColorTransform"),e._excludeVariableName("colorTransformSettings")},t.prototype.isReady=function(e,n,i){return!(i._areImageProcessingDirty&&n.imageProcessingConfiguration&&!n.imageProcessingConfiguration.isReady())},t.prototype.prepareDefines=function(e,n,i){i._areImageProcessingDirty&&n.imageProcessingConfiguration&&n.imageProcessingConfiguration.prepareDefines(i)},t.prototype.bind=function(e,n,i){i&&n.imageProcessingConfiguration&&n.imageProcessingConfiguration.bind(e)},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e),e.sharedData.blocksWithDefines.push(this),e.sharedData.blockingBlocks.push(this),e.sharedData.bindableBlocks.push(this),e.uniforms.push("exposureLinear"),e.uniforms.push("contrast"),e.uniforms.push("vInverseScreenSize"),e.uniforms.push("vignetteSettings1"),e.uniforms.push("vignetteSettings2"),e.uniforms.push("vCameraColorCurveNegative"),e.uniforms.push("vCameraColorCurveNeutral"),e.uniforms.push("vCameraColorCurvePositive"),e.uniforms.push("txColorTransform"),e.uniforms.push("colorTransformSettings");var n=this.color,i=this._outputs[0],o="//"+this.name;return e._emitFunctionFromInclude("helperFunctions",o),e._emitFunctionFromInclude("imageProcessingDeclaration",o),e._emitFunctionFromInclude("imageProcessingFunctions",o),n.connectedPoint.type===le.Color4||n.connectedPoint.type===le.Vector4?e.compilationString+=this._declareOutput(i,e)+" = "+n.associatedVariableName+`;\r
-`:e.compilationString+=this._declareOutput(i,e)+" = vec4("+n.associatedVariableName+`, 1.0);\r
-`,e.compilationString+=`#ifdef IMAGEPROCESSINGPOSTPROCESS\r
-`,e.compilationString+=i.associatedVariableName+".rgb = toLinearSpace("+n.associatedVariableName+`.rgb);\r
-`,e.compilationString+=`#else\r
-`,e.compilationString+=`#ifdef IMAGEPROCESSING\r
-`,e.compilationString+=i.associatedVariableName+".rgb = toLinearSpace("+n.associatedVariableName+`.rgb);\r
-`,e.compilationString+=i.associatedVariableName+" = applyImageProcessing("+i.associatedVariableName+`);\r
-`,e.compilationString+=`#endif\r
-`,e.compilationString+=`#endif\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.ImageProcessingBlock"]=gh;var vh=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n._tangentSpaceParameterName="",n.invertX=!1,n.invertY=!1,n.registerInput("worldPosition",le.Vector4,!1),n.registerInput("worldNormal",le.Vector4,!1),n.registerInput("worldTangent",le.Vector4,!0),n.registerInput("uv",le.Vector2,!1),n.registerInput("normalMapColor",le.Color3,!1),n.registerInput("strength",le.Float,!1),n.registerOutput("output",le.Vector4),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"PerturbNormalBlock"},Object.defineProperty(t.prototype,"worldPosition",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldNormal",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldTangent",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"uv",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"normalMapColor",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"strength",{get:function(){return this._inputs[5]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.prepareDefines=function(e,n,i){i.setValue("BUMP",!0)},t.prototype.bind=function(e,n,i){n.getScene()._mirroredCameraPosition?e.setFloat2(this._tangentSpaceParameterName,this.invertX?1:-1,this.invertY?1:-1):e.setFloat2(this._tangentSpaceParameterName,this.invertX?-1:1,this.invertY?-1:1)},t.prototype.autoConfigure=function(e){if(!this.uv.isConnected){var n=e.getInputBlockByPredicate(function(o){return o.isAttribute&&o.name==="uv"});n||(n=new At("uv")).setAsAttribute(),n.output.connectTo(this.uv)}if(!this.strength.isConnected){var i=new At("strength");i.value=1,i.output.connectTo(this.strength)}},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n="//"+this.name,i=this.uv,o=this.worldPosition,a=this.worldNormal,s=this.worldTangent;e.sharedData.blocksWithDefines.push(this),e.sharedData.bindableBlocks.push(this),this._tangentSpaceParameterName=e._getFreeDefineName("tangentSpaceParameter"),e._emitUniformFromString(this._tangentSpaceParameterName,"vec2");var d=this.strength.isConnectedToInputBlock&&this.strength.connectInputBlock.isConstant?""+e._emitFloat(1/this.strength.connectInputBlock.value):"1.0 / "+this.strength.associatedVariableName;e._emitExtension("derivatives","#extension GL_OES_standard_derivatives : enable");var p={search:/defined\(TANGENT\)/g,replace:s.isConnected?"defined(TANGENT)":"defined(IGNORE)"};return s.isConnected&&(e.compilationString+="vec3 tbnNormal = normalize("+a.associatedVariableName+`.xyz);\r
-`,e.compilationString+="vec3 tbnTangent = normalize("+s.associatedVariableName+`.xyz);\r
-`,e.compilationString+=`vec3 tbnBitangent = cross(tbnNormal, tbnTangent);\r
-`,e.compilationString+=`mat3 vTBN = mat3(tbnTangent, tbnBitangent, tbnNormal);\r
-`),e._emitFunctionFromInclude("bumpFragmentMainFunctions",n,{replaceStrings:[p]}),e._emitFunctionFromInclude("bumpFragmentFunctions",n,{replaceStrings:[{search:/vBumpInfos.y/g,replace:d},{search:/vTangentSpaceParams/g,replace:this._tangentSpaceParameterName},{search:/vPositionW/g,replace:o.associatedVariableName+".xyz"}]}),e.compilationString+=this._declareOutput(this.output,e)+` = vec4(0.);\r
-`,e.compilationString+=e._emitCodeFromInclude("bumpFragment",n,{replaceStrings:[{search:/perturbNormal\(TBN,vBumpUV\+uvOffset\)/g,replace:"perturbNormal(TBN, "+this.normalMapColor.associatedVariableName+")"},{search:/vBumpInfos.y/g,replace:d},{search:/vBumpUV/g,replace:i.associatedVariableName},{search:/vPositionW/g,replace:o.associatedVariableName+".xyz"},{search:/normalW=/g,replace:this.output.associatedVariableName+".xyz = "},{search:/mat3\(normalMatrix\)\*normalW/g,replace:"mat3(normalMatrix) * "+this.output.associatedVariableName+".xyz"},{search:/normalW/g,replace:a.associatedVariableName+".xyz"},p]}),this},t.prototype._dumpPropertiesCode=function(){var e=this._codeVariableName+".invertX = "+this.invertX+`;\r
-`;return e+=this._codeVariableName+".invertY = "+this.invertY+`;\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.invertX=this.invertX,e.invertY=this.invertY,e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.invertX=e.invertX,this.invertY=e.invertY},Object(c.c)([Vt("Invert X axis",Lt.Boolean,"PROPERTIES",{notifiers:{update:!1}})],t.prototype,"invertX",void 0),Object(c.c)([Vt("Invert Y axis",Lt.Boolean,"PROPERTIES",{notifiers:{update:!1}})],t.prototype,"invertY",void 0),t}(pt);R.a.RegisteredTypes["BABYLON.PerturbNormalBlock"]=vh;var bh=function(r){function t(e){var n=r.call(this,e,xe.Fragment,!0)||this;return n.registerInput("value",le.Float,!0),n.registerInput("cutoff",le.Float,!0),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"DiscardBlock"},Object.defineProperty(t.prototype,"value",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cutoff",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),e.sharedData.hints.needAlphaTesting=!0,this.cutoff.isConnected&&this.value.isConnected)return e.compilationString+="if ("+this.value.associatedVariableName+" < "+this.cutoff.associatedVariableName+`) discard;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.DiscardBlock"]=bh;var yh=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n.registerOutput("output",le.Float,xe.Fragment),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"FrontFacingBlock"},Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),e.target===xe.Vertex)throw"FrontFacingBlock must only be used in a fragment shader";var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+` = gl_FrontFacing ? 1.0 : 0.0;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.FrontFacingBlock"]=yh;var Th=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n.registerInput("input",le.AutoDetect,!1),n.registerOutput("dx",le.BasedOnInput),n.registerOutput("dy",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._outputs[1]._typeConnectionSource=n._inputs[0],n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"DerivativeBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dx",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dy",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0],i=this._outputs[1];return e._emitExtension("derivatives","#extension GL_OES_standard_derivatives : enable"),n.hasEndpoints&&(e.compilationString+=this._declareOutput(n,e)+" = dFdx("+this.input.associatedVariableName+`);\r
-`),i.hasEndpoints&&(e.compilationString+=this._declareOutput(i,e)+" = dFdy("+this.input.associatedVariableName+`);\r
-`),this},t}(pt);R.a.RegisteredTypes["BABYLON.DerivativeBlock"]=Th;var Eh=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n.registerOutput("xy",le.Vector2,xe.Fragment),n.registerOutput("xyz",le.Vector3,xe.Fragment),n.registerOutput("xyzw",le.Vector4,xe.Fragment),n.registerOutput("x",le.Float,xe.Fragment),n.registerOutput("y",le.Float,xe.Fragment),n.registerOutput("z",le.Float,xe.Fragment),n.registerOutput("w",le.Float,xe.Fragment),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"FragCoordBlock"},Object.defineProperty(t.prototype,"xy",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyz",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyzw",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"x",{get:function(){return this._outputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"y",{get:function(){return this._outputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"z",{get:function(){return this._outputs[5]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[6]},enumerable:!1,configurable:!0}),t.prototype.writeOutputs=function(e){for(var n="",i=0,o=this._outputs;i<o.length;i++){var a=o[i];a.hasEndpoints&&(n+=this._declareOutput(a,e)+" = gl_FragCoord."+a.name+`;\r
-`)}return n},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),e.target===xe.Vertex)throw"FragCoordBlock must only be used in a fragment shader";return e.compilationString+=this.writeOutputs(e),this},t}(pt);R.a.RegisteredTypes["BABYLON.FragCoordBlock"]=Eh;var Sh=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n.registerOutput("xy",le.Vector2,xe.Fragment),n.registerOutput("x",le.Float,xe.Fragment),n.registerOutput("y",le.Float,xe.Fragment),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ScreenSizeBlock"},Object.defineProperty(t.prototype,"xy",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"x",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"y",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),t.prototype.bind=function(e,n,i){var o=this._scene.getEngine();e.setFloat2(this._varName,o.getRenderWidth(),o.getRenderWidth())},t.prototype.writeOutputs=function(e,n){for(var i="",o=0,a=this._outputs;o<a.length;o++){var s=a[o];s.hasEndpoints&&(i+=this._declareOutput(s,e)+" = "+n+"."+s.name+`;\r
-`)}return i},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),this._scene=e.sharedData.scene,e.target===xe.Vertex)throw"ScreenSizeBlock must only be used in a fragment shader";return e.sharedData.bindableBlocks.push(this),this._varName=e._getFreeVariableName("screenSize"),e._emitUniformFromString(this._varName,"vec2"),e.compilationString+=this.writeOutputs(e,this._varName),this},t}(pt);R.a.RegisteredTypes["BABYLON.ScreenSizeBlock"]=Sh;var Ah=function(r){function t(e){var n=r.call(this,e,xe.VertexAndFragment,!0)||this;return n.registerInput("worldPosition",le.Vector4,!1,xe.Vertex),n.registerInput("view",le.Matrix,!1,xe.Vertex),n.registerInput("input",le.Color3,!1,xe.Fragment),n.registerInput("fogColor",le.Color3,!1,xe.Fragment),n.registerOutput("output",le.Color3,xe.Fragment),n.input.acceptedConnectionPointTypes.push(le.Color4),n.fogColor.acceptedConnectionPointTypes.push(le.Color4),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"FogBlock"},Object.defineProperty(t.prototype,"worldPosition",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"view",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"fogColor",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.view.isConnected){var n=e.getInputBlockByPredicate(function(o){return o.systemValue===bt.View});n||(n=new At("view")).setAsSystemValue(bt.View),n.output.connectTo(this.view)}if(!this.fogColor.isConnected){var i=e.getInputBlockByPredicate(function(o){return o.systemValue===bt.FogColor});i||(i=new At("fogColor",void 0,le.Color3)).setAsSystemValue(bt.FogColor),i.output.connectTo(this.fogColor)}},t.prototype.prepareDefines=function(e,n,i){var o=e.getScene();i.setValue("FOG",n.fogEnabled&&et.a.GetFogState(e,o))},t.prototype.bind=function(e,n,i){if(i){var o=i.getScene();e.setFloat4(this._fogParameters,o.fogMode,o.fogStart,o.fogEnd,o.fogDensity)}},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),e.target===xe.Fragment){e.sharedData.blocksWithDefines.push(this),e.sharedData.bindableBlocks.push(this),e._emitFunctionFromInclude("fogFragmentDeclaration","//"+this.name,{removeUniforms:!0,removeVaryings:!0,removeIfDef:!1,replaceStrings:[{search:/float CalcFogFactor\(\)/,replace:"float CalcFogFactor(vec3 vFogDistance, vec4 vFogInfos)"}]});var n=e._getFreeVariableName("fog"),i=this.input,o=this.fogColor;this._fogParameters=e._getFreeVariableName("fogParameters");var a=this._outputs[0];e._emitUniformFromString(this._fogParameters,"vec4"),e.compilationString+=`#ifdef FOG\r
-`,e.compilationString+="float "+n+" = CalcFogFactor("+this._fogDistanceName+", "+this._fogParameters+`);\r
-`,e.compilationString+=this._declareOutput(a,e)+" = "+n+" * "+i.associatedVariableName+".rgb + (1.0 - "+n+") * "+o.associatedVariableName+`.rgb;\r
-`,e.compilationString+=`#else\r
-`+this._declareOutput(a,e)+" =  "+i.associatedVariableName+`.rgb;\r
-`,e.compilationString+=`#endif\r
-`}else{var s=this.worldPosition,d=this.view;this._fogDistanceName=e._getFreeVariableName("vFogDistance"),e._emitVaryingFromString(this._fogDistanceName,"vec3"),e.compilationString+=this._fogDistanceName+" = ("+d.associatedVariableName+" * "+s.associatedVariableName+`).xyz;\r
-`}return this},t}(pt);R.a.RegisteredTypes["BABYLON.FogBlock"]=Ah;var Ph=function(r){function t(e){var n=r.call(this,e,xe.VertexAndFragment)||this;return n._isUnique=!0,n.registerInput("worldPosition",le.Vector4,!1,xe.Vertex),n.registerInput("worldNormal",le.Vector4,!1,xe.Fragment),n.registerInput("cameraPosition",le.Vector3,!1,xe.Fragment),n.registerInput("glossiness",le.Float,!0,xe.Fragment),n.registerInput("glossPower",le.Float,!0,xe.Fragment),n.registerInput("diffuseColor",le.Color3,!0,xe.Fragment),n.registerInput("specularColor",le.Color3,!0,xe.Fragment),n.registerInput("view",le.Matrix,!0),n.registerOutput("diffuseOutput",le.Color3,xe.Fragment),n.registerOutput("specularOutput",le.Color3,xe.Fragment),n.registerOutput("shadow",le.Float,xe.Fragment),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"LightBlock"},Object.defineProperty(t.prototype,"worldPosition",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldNormal",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraPosition",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"glossiness",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"glossPower",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"diffuseColor",{get:function(){return this._inputs[5]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"specularColor",{get:function(){return this._inputs[6]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"view",{get:function(){return this._inputs[7]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"diffuseOutput",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"specularOutput",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"shadow",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.cameraPosition.isConnected){var n=e.getInputBlockByPredicate(function(i){return i.systemValue===bt.CameraPosition});n||(n=new At("cameraPosition")).setAsSystemValue(bt.CameraPosition),n.output.connectTo(this.cameraPosition)}},t.prototype.prepareDefines=function(e,n,i){if(i._areLightsDirty){var o=e.getScene();if(this.light){var a={needNormals:!1,needRebuild:!1,lightmapMode:!1,shadowEnabled:!1,specularEnabled:!1};et.a.PrepareDefinesForLight(o,e,this.light,this._lightId,i,!0,a),a.needRebuild&&i.rebuild()}else et.a.PrepareDefinesForLights(o,e,i,!0,n.maxSimultaneousLights)}},t.prototype.updateUniformsAndSamples=function(e,n,i,o){for(var a=0;a<n.maxSimultaneousLights&&i["LIGHT"+a];a++){var s=e.uniforms.indexOf("vLightData"+a)>=0;et.a.PrepareUniformsAndSamplersForLight(a,e.uniforms,e.samplers,i["PROJECTEDLIGHTTEXTURE"+a],o,s)}},t.prototype.bind=function(e,n,i){if(i){var o=i.getScene();this.light?et.a.BindLight(this.light,this._lightId,o,e,!0):et.a.BindLights(o,i,e,!0,n.maxSimultaneousLights)}},t.prototype._injectVertexCode=function(e){var n=this.worldPosition,i="//"+this.name;this.light?(this._lightId=(e.counters.lightCounter!==void 0?e.counters.lightCounter:-1)+1,e.counters.lightCounter=this._lightId,e._emitFunctionFromInclude(e.supportUniformBuffers?"lightUboDeclaration":"lightFragmentDeclaration",i,{replaceStrings:[{search:/{X}/g,replace:this._lightId.toString()}]},this._lightId.toString())):(e._emitFunctionFromInclude(e.supportUniformBuffers?"lightUboDeclaration":"lightFragmentDeclaration",i,{repeatKey:"maxSimultaneousLights"}),this._lightId=0,e.sharedData.dynamicUniformBlocks.push(this));var o="v_"+n.associatedVariableName;e._emitVaryingFromString(o,"vec4")&&(e.compilationString+=o+" = "+n.associatedVariableName+`;\r
-`),this.light?e.compilationString+=e._emitCodeFromInclude("shadowsVertex",i,{replaceStrings:[{search:/{X}/g,replace:this._lightId.toString()},{search:/worldPos/g,replace:n.associatedVariableName}]}):(e.compilationString+="vec4 worldPos = "+n.associatedVariableName+`;\r
-`,this.view.isConnected&&(e.compilationString+="mat4 view = "+this.view.associatedVariableName+`;\r
-`),e.compilationString+=e._emitCodeFromInclude("shadowsVertex",i,{repeatKey:"maxSimultaneousLights"}))},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),e.target===xe.Fragment){e.sharedData.bindableBlocks.push(this),e.sharedData.blocksWithDefines.push(this);var n="//"+this.name,i=this.worldPosition;e._emitFunctionFromInclude("helperFunctions",n),e._emitFunctionFromInclude("lightsFragmentFunctions",n,{replaceStrings:[{search:/vPositionW/g,replace:"v_"+i.associatedVariableName+".xyz"}]}),e._emitFunctionFromInclude("shadowsFragmentFunctions",n,{replaceStrings:[{search:/vPositionW/g,replace:"v_"+i.associatedVariableName+".xyz"}]}),this.light?e._emitFunctionFromInclude(e.supportUniformBuffers?"lightUboDeclaration":"lightFragmentDeclaration",n,{replaceStrings:[{search:/{X}/g,replace:this._lightId.toString()}]},this._lightId.toString()):e._emitFunctionFromInclude(e.supportUniformBuffers?"lightUboDeclaration":"lightFragmentDeclaration",n,{repeatKey:"maxSimultaneousLights"}),this._lightId===0&&(e._registerTempVariable("viewDirectionW")&&(e.compilationString+="vec3 viewDirectionW = normalize("+this.cameraPosition.associatedVariableName+" - v_"+i.associatedVariableName+`.xyz);\r
-`),e.compilationString+=`lightingInfo info;\r
-`,e.compilationString+=`float shadow = 1.;\r
-`,e.compilationString+="float glossiness = "+(this.glossiness.isConnected?this.glossiness.associatedVariableName:"1.0")+" * "+(this.glossPower.isConnected?this.glossPower.associatedVariableName:"1024.0")+`;\r
-`,e.compilationString+=`vec3 diffuseBase = vec3(0., 0., 0.);\r
-`,e.compilationString+=`vec3 specularBase = vec3(0., 0., 0.);\r
-`,e.compilationString+="vec3 normalW = "+this.worldNormal.associatedVariableName+`.xyz;\r
-`),this.light?e.compilationString+=e._emitCodeFromInclude("lightFragment",n,{replaceStrings:[{search:/{X}/g,replace:this._lightId.toString()}]}):e.compilationString+=e._emitCodeFromInclude("lightFragment",n,{repeatKey:"maxSimultaneousLights"});var o=this.diffuseOutput,a=this.specularOutput;return e.compilationString+=this._declareOutput(o,e)+" = diffuseBase"+(this.diffuseColor.isConnected?" * "+this.diffuseColor.associatedVariableName:"")+`;\r
-`,a.hasEndpoints&&(e.compilationString+=this._declareOutput(a,e)+" = specularBase"+(this.specularColor.isConnected?" * "+this.specularColor.associatedVariableName:"")+`;\r
-`),this.shadow.hasEndpoints&&(e.compilationString+=this._declareOutput(this.shadow,e)+` = shadow;\r
-`),this}this._injectVertexCode(e)},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return this.light&&(e.lightId=this.light.id),e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),e.lightId&&(this.light=n.getLightByID(e.lightId))},t}(pt);R.a.RegisteredTypes["BABYLON.LightBlock"]=Ph;var Ch=function(r){function t(e,n){n===void 0&&(n=!1);var i=r.call(this,e,n?xe.Fragment:xe.VertexAndFragment)||this;return i.convertToGammaSpace=!1,i.convertToLinearSpace=!1,i._fragmentOnly=n,i.registerInput("uv",le.Vector2,!1,xe.VertexAndFragment),i.registerOutput("rgba",le.Color4,xe.Neutral),i.registerOutput("rgb",le.Color3,xe.Neutral),i.registerOutput("r",le.Float,xe.Neutral),i.registerOutput("g",le.Float,xe.Neutral),i.registerOutput("b",le.Float,xe.Neutral),i.registerOutput("a",le.Float,xe.Neutral),i._inputs[0].acceptedConnectionPointTypes.push(le.Vector3),i._inputs[0].acceptedConnectionPointTypes.push(le.Vector4),i._inputs[0]._prioritizeVertex=!n,i}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"TextureBlock"},Object.defineProperty(t.prototype,"uv",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgba",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgb",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"r",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"g",{get:function(){return this._outputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"b",{get:function(){return this._outputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"a",{get:function(){return this._outputs[5]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"target",{get:function(){if(this._fragmentOnly)return xe.Fragment;if(!this.uv.isConnected||this.uv.sourceBlock.isInput)return xe.VertexAndFragment;for(var e=this.uv.connectedPoint;e;){if(e.target===xe.Fragment)return xe.Fragment;if(e.target===xe.Vertex)return xe.VertexAndFragment;if(e.target===xe.Neutral||e.target===xe.VertexAndFragment){var n=e.ownerBlock;e=null;for(var i=0,o=n.inputs;i<o.length;i++){var a=o[i];if(a.connectedPoint){e=a.connectedPoint;break}}}}return xe.VertexAndFragment},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.uv.isConnected)if(e.mode===Mn.PostProcess)(n=e.getBlockByPredicate(function(o){return o.name==="uv"}))&&n.connectTo(this);else{var n,i=e.mode===Mn.Particle?"particle_uv":"uv";(n=e.getInputBlockByPredicate(function(o){return o.isAttribute&&o.name===i}))||(n=new At("uv")).setAsAttribute(i),n.output.connectTo(this.uv)}},t.prototype.initializeDefines=function(e,n,i,o){i._areTexturesDirty&&i.setValue(this._mainUVDefineName,!1)},t.prototype.prepareDefines=function(e,n,i){if(i._areTexturesDirty){if(!this.texture||!this.texture.getTextureMatrix)return i.setValue(this._defineName,!1),void i.setValue(this._mainUVDefineName,!0);i.setValue(this._linearDefineName,this.convertToGammaSpace),i.setValue(this._gammaDefineName,this.convertToLinearSpace),this._isMixed&&(this.texture.getTextureMatrix().isIdentityAs3x2()?(i.setValue(this._defineName,!1),i.setValue(this._mainUVDefineName,!0)):i.setValue(this._defineName,!0))}},t.prototype.isReady=function(){return!(this.texture&&!this.texture.isReadyOrNotBlocking())},t.prototype.bind=function(e,n,i){this.texture&&(this._isMixed&&(e.setFloat(this._textureInfoName,this.texture.level),e.setMatrix(this._textureTransformName,this.texture.getTextureMatrix())),e.setTexture(this._samplerName,this.texture))},Object.defineProperty(t.prototype,"_isMixed",{get:function(){return this.target!==xe.Fragment},enumerable:!1,configurable:!0}),t.prototype._injectVertexCode=function(e){var n=this.uv;if(this._defineName=e._getFreeDefineName("UVTRANSFORM"),this._mainUVDefineName="VMAIN"+n.associatedVariableName.toUpperCase(),n.connectedPoint.ownerBlock.isInput&&(n.connectedPoint.ownerBlock.isAttribute||e._emitUniformFromString(n.associatedVariableName,"vec2")),this._mainUVName="vMain"+n.associatedVariableName,this._transformedUVName=e._getFreeVariableName("transformedUV"),this._textureTransformName=e._getFreeVariableName("textureTransform"),this._textureInfoName=e._getFreeVariableName("textureInfoName"),e._emitVaryingFromString(this._transformedUVName,"vec2",this._defineName),e._emitVaryingFromString(this._mainUVName,"vec2",this._mainUVDefineName),e._emitUniformFromString(this._textureTransformName,"mat4",this._defineName),e.compilationString+="#ifdef "+this._defineName+`\r
-`,e.compilationString+=this._transformedUVName+" = vec2("+this._textureTransformName+" * vec4("+n.associatedVariableName+`.xy, 1.0, 0.0));\r
-`,e.compilationString+="#elif defined("+this._mainUVDefineName+`)\r
-`,e.compilationString+=this._mainUVName+" = "+n.associatedVariableName+`.xy;\r
-`,e.compilationString+=`#endif\r
-`,this._outputs.some(function(s){return s.isConnectedInVertexShader})){this._writeTextureRead(e,!0);for(var i=0,o=this._outputs;i<o.length;i++){var a=o[i];a.hasEndpoints&&this._writeOutput(e,a,a.name,!0)}}},t.prototype._writeTextureRead=function(e,n){n===void 0&&(n=!1);var i=this.uv;if(n){if(e.target===xe.Fragment)return;e.compilationString+="vec4 "+this._tempTextureRead+" = texture2D("+this._samplerName+", "+i.associatedVariableName+`);\r
-`}else this.uv.ownerBlock.target!==xe.Fragment?(e.compilationString+="#ifdef "+this._defineName+`\r
-`,e.compilationString+="vec4 "+this._tempTextureRead+" = texture2D("+this._samplerName+", "+this._transformedUVName+`);\r
-`,e.compilationString+="#elif defined("+this._mainUVDefineName+`)\r
-`,e.compilationString+="vec4 "+this._tempTextureRead+" = texture2D("+this._samplerName+", "+this._mainUVName+`);\r
-`,e.compilationString+=`#endif\r
-`):e.compilationString+="vec4 "+this._tempTextureRead+" = texture2D("+this._samplerName+", "+i.associatedVariableName+`);\r
-`},t.prototype._writeOutput=function(e,n,i,o){if(o===void 0&&(o=!1),o){if(e.target===xe.Fragment)return;e.compilationString+=this._declareOutput(n,e)+" = "+this._tempTextureRead+"."+i+`;\r
-`}else if(this.uv.ownerBlock.target!==xe.Fragment){var a=" * "+this._textureInfoName;e.compilationString+=this._declareOutput(n,e)+" = "+this._tempTextureRead+"."+i+a+`;\r
-`,i!=="a"&&(e.compilationString+="#ifdef "+this._linearDefineName+`\r
-`,e.compilationString+=n.associatedVariableName+" = toGammaSpace("+n.associatedVariableName+`);\r
-`,e.compilationString+=`#endif\r
-`,e.compilationString+="#ifdef "+this._gammaDefineName+`\r
-`,e.compilationString+=n.associatedVariableName+" = toLinearSpace("+n.associatedVariableName+`);\r
-`,e.compilationString+=`#endif\r
-`)}else e.compilationString+=this._declareOutput(n,e)+" = "+this._tempTextureRead+"."+i+`;\r
-`},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),(e.target===xe.Vertex||this._fragmentOnly)&&(this._tempTextureRead=e._getFreeVariableName("tempTextureRead")),(!this._isMixed&&e.target===xe.Fragment||this._isMixed&&e.target===xe.Vertex)&&(this._samplerName=e._getFreeVariableName(this.name+"Sampler"),e._emit2DSampler(this._samplerName),e.sharedData.blockingBlocks.push(this),e.sharedData.textureBlocks.push(this),e.sharedData.blocksWithDefines.push(this),e.sharedData.bindableBlocks.push(this)),e.target===xe.Fragment){if(this._outputs.some(function(s){return s.isConnectedInFragmentShader})){this._isMixed&&e._emit2DSampler(this._samplerName),this._linearDefineName=e._getFreeDefineName("ISLINEAR"),this._gammaDefineName=e._getFreeDefineName("ISGAMMA");var n="//"+this.name;e._emitFunctionFromInclude("helperFunctions",n),this._isMixed&&e._emitUniformFromString(this._textureInfoName,"float"),this._writeTextureRead(e);for(var i=0,o=this._outputs;i<o.length;i++){var a=o[i];a.hasEndpoints&&this._writeOutput(e,a,a.name)}return this}}else this._injectVertexCode(e)},t.prototype._dumpPropertiesCode=function(){if(!this.texture)return"";var e=this._codeVariableName+'.texture = new BABYLON.Texture("'+this.texture.name+`", null);\r
-`;return e+=this._codeVariableName+".texture.wrapU = "+this.texture.wrapU+`;\r
-`,e+=this._codeVariableName+".texture.wrapV = "+this.texture.wrapV+`;\r
-`,e+=this._codeVariableName+".texture.uAng = "+this.texture.uAng+`;\r
-`,e+=this._codeVariableName+".texture.vAng = "+this.texture.vAng+`;\r
-`,e+=this._codeVariableName+".texture.wAng = "+this.texture.wAng+`;\r
-`,e+=this._codeVariableName+".texture.uOffset = "+this.texture.uOffset+`;\r
-`,e+=this._codeVariableName+".texture.vOffset = "+this.texture.vOffset+`;\r
-`,e+=this._codeVariableName+".texture.uScale = "+this.texture.uScale+`;\r
-`,e+=this._codeVariableName+".texture.vScale = "+this.texture.vScale+`;\r
-`,e+=this._codeVariableName+".convertToGammaSpace = "+this.convertToGammaSpace+`;\r
-`,e+=this._codeVariableName+".convertToLinearSpace = "+this.convertToLinearSpace+`;\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.convertToGammaSpace=this.convertToGammaSpace,e.convertToLinearSpace=this.convertToLinearSpace,e.fragmentOnly=this._fragmentOnly,this.texture&&!this.texture.isRenderTarget&&(e.texture=this.texture.serialize()),e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.convertToGammaSpace=e.convertToGammaSpace,this.convertToLinearSpace=!!e.convertToLinearSpace,this._fragmentOnly=!!e.fragmentOnly,e.texture&&!ga.IgnoreTexturesAtLoadTime&&(i=e.texture.url.indexOf("data:")===0?"":i,this.texture=we.a.Parse(e.texture,n,i))},t}(pt);R.a.RegisteredTypes["BABYLON.TextureBlock"]=Ch;var dc=function(r){function t(e){return r.call(this,e,xe.VertexAndFragment)||this}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ReflectionTextureBaseBlock"},t.prototype._getTexture=function(){return this.texture},t.prototype.autoConfigure=function(e){if(!this.position.isConnected){var n=e.getInputBlockByPredicate(function(a){return a.isAttribute&&a.name==="position"});n||(n=new At("position")).setAsAttribute(),n.output.connectTo(this.position)}if(!this.world.isConnected){var i=e.getInputBlockByPredicate(function(a){return a.systemValue===bt.World});i||(i=new At("world")).setAsSystemValue(bt.World),i.output.connectTo(this.world)}if(this.view&&!this.view.isConnected){var o=e.getInputBlockByPredicate(function(a){return a.systemValue===bt.View});o||(o=new At("view")).setAsSystemValue(bt.View),o.output.connectTo(this.view)}},t.prototype.prepareDefines=function(e,n,i){if(i._areTexturesDirty){var o=this._getTexture();o&&o.getTextureMatrix&&(i.setValue(this._define3DName,o.isCube,!0),i.setValue(this._defineLocalCubicName,!!o.boundingBoxSize,!0),i.setValue(this._defineExplicitName,o.coordinatesMode===h.a.TEXTURE_EXPLICIT_MODE,!0),i.setValue(this._defineSkyboxName,o.coordinatesMode===h.a.TEXTURE_SKYBOX_MODE,!0),i.setValue(this._defineCubicName,o.coordinatesMode===h.a.TEXTURE_CUBIC_MODE||o.coordinatesMode===h.a.TEXTURE_INVCUBIC_MODE,!0),i.setValue("INVERTCUBICMAP",o.coordinatesMode===h.a.TEXTURE_INVCUBIC_MODE,!0),i.setValue(this._defineSphericalName,o.coordinatesMode===h.a.TEXTURE_SPHERICAL_MODE,!0),i.setValue(this._definePlanarName,o.coordinatesMode===h.a.TEXTURE_PLANAR_MODE,!0),i.setValue(this._defineProjectionName,o.coordinatesMode===h.a.TEXTURE_PROJECTION_MODE,!0),i.setValue(this._defineEquirectangularName,o.coordinatesMode===h.a.TEXTURE_EQUIRECTANGULAR_MODE,!0),i.setValue(this._defineEquirectangularFixedName,o.coordinatesMode===h.a.TEXTURE_FIXED_EQUIRECTANGULAR_MODE,!0),i.setValue(this._defineMirroredEquirectangularFixedName,o.coordinatesMode===h.a.TEXTURE_FIXED_EQUIRECTANGULAR_MIRRORED_MODE,!0))}},t.prototype.isReady=function(){var e=this._getTexture();return!(e&&!e.isReadyOrNotBlocking())},t.prototype.bind=function(e,n,i){var o=this._getTexture();i&&o&&(e.setMatrix(this._reflectionMatrixName,o.getReflectionTextureMatrix()),o.isCube?e.setTexture(this._cubeSamplerName,o):e.setTexture(this._2DSamplerName,o))},t.prototype.handleVertexSide=function(e){this._define3DName=e._getFreeDefineName("REFLECTIONMAP_3D"),this._defineCubicName=e._getFreeDefineName("REFLECTIONMAP_CUBIC"),this._defineSphericalName=e._getFreeDefineName("REFLECTIONMAP_SPHERICAL"),this._definePlanarName=e._getFreeDefineName("REFLECTIONMAP_PLANAR"),this._defineProjectionName=e._getFreeDefineName("REFLECTIONMAP_PROJECTION"),this._defineExplicitName=e._getFreeDefineName("REFLECTIONMAP_EXPLICIT"),this._defineEquirectangularName=e._getFreeDefineName("REFLECTIONMAP_EQUIRECTANGULAR"),this._defineLocalCubicName=e._getFreeDefineName("USE_LOCAL_REFLECTIONMAP_CUBIC"),this._defineMirroredEquirectangularFixedName=e._getFreeDefineName("REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED"),this._defineEquirectangularFixedName=e._getFreeDefineName("REFLECTIONMAP_EQUIRECTANGULAR_FIXED"),this._defineSkyboxName=e._getFreeDefineName("REFLECTIONMAP_SKYBOX"),this._defineOppositeZ=e._getFreeDefineName("REFLECTIONMAP_OPPOSITEZ"),this._reflectionMatrixName=e._getFreeVariableName("reflectionMatrix"),e._emitUniformFromString(this._reflectionMatrixName,"mat4");var n="",i="v_"+this.worldPosition.associatedVariableName;return e._emitVaryingFromString(i,"vec4")&&(n+=i+" = "+this.worldPosition.associatedVariableName+`;\r
-`),this._positionUVWName=e._getFreeVariableName("positionUVW"),this._directionWName=e._getFreeVariableName("directionW"),e._emitVaryingFromString(this._positionUVWName,"vec3",this._defineSkyboxName)&&(n+="#ifdef "+this._defineSkyboxName+`\r
-`,n+=this._positionUVWName+" = "+this.position.associatedVariableName+`.xyz;\r
-`,n+=`#endif\r
-`),e._emitVaryingFromString(this._directionWName,"vec3","defined("+this._defineEquirectangularFixedName+") || defined("+this._defineMirroredEquirectangularFixedName+")")&&(n+="#if defined("+this._defineEquirectangularFixedName+") || defined("+this._defineMirroredEquirectangularFixedName+`)\r
-`,n+=this._directionWName+" = normalize(vec3("+this.world.associatedVariableName+" * vec4("+this.position.associatedVariableName+`.xyz, 0.0)));\r
-`,n+=`#endif\r
-`),n},t.prototype.handleFragmentSideInits=function(e){e.sharedData.blockingBlocks.push(this),e.sharedData.textureBlocks.push(this),this._cubeSamplerName=e._getFreeVariableName(this.name+"CubeSampler"),e.samplers.push(this._cubeSamplerName),this._2DSamplerName=e._getFreeVariableName(this.name+"2DSampler"),e.samplers.push(this._2DSamplerName),e._samplerDeclaration+="#ifdef "+this._define3DName+`\r
-`,e._samplerDeclaration+="uniform samplerCube "+this._cubeSamplerName+`;\r
-`,e._samplerDeclaration+=`#else\r
-`,e._samplerDeclaration+="uniform sampler2D "+this._2DSamplerName+`;\r
-`,e._samplerDeclaration+=`#endif\r
-`,e.sharedData.blocksWithDefines.push(this),e.sharedData.bindableBlocks.push(this);var n="//"+this.name;e._emitFunction("ReciprocalPI","#define RECIPROCAL_PI2 0.15915494",""),e._emitFunctionFromInclude("reflectionFunction",n,{replaceStrings:[{search:/vec3 computeReflectionCoords/g,replace:"void DUMMYFUNC"}]}),this._reflectionColorName=e._getFreeVariableName("reflectionColor"),this._reflectionVectorName=e._getFreeVariableName("reflectionUVW"),this._reflectionCoordsName=e._getFreeVariableName("reflectionCoords")},t.prototype.handleFragmentSideCodeReflectionCoords=function(e,n,i){i===void 0&&(i=!1),n||(n="v_"+this.worldPosition.associatedVariableName);var o=this._reflectionMatrixName,a="normalize("+this._directionWName+")",s=""+this._positionUVWName,d=""+this.cameraPosition.associatedVariableName,p=""+this.view.associatedVariableName;e+=".xyz";var b=`
-            #ifdef `+this._defineMirroredEquirectangularFixedName+`
-                vec3 `+this._reflectionVectorName+" = computeMirroredFixedEquirectangularCoords("+n+", "+e+", "+a+`);
-            #endif
-
-            #ifdef `+this._defineEquirectangularFixedName+`
-                vec3 `+this._reflectionVectorName+" = computeFixedEquirectangularCoords("+n+", "+e+", "+a+`);
-            #endif
-
-            #ifdef `+this._defineEquirectangularName+`
-                vec3 `+this._reflectionVectorName+" = computeEquirectangularCoords("+n+", "+e+", "+d+".xyz, "+o+`);
-            #endif
-
-            #ifdef `+this._defineSphericalName+`
-                vec3 `+this._reflectionVectorName+" = computeSphericalCoords("+n+", "+e+", "+p+", "+o+`);
-            #endif
-
-            #ifdef `+this._definePlanarName+`
-                vec3 `+this._reflectionVectorName+" = computePlanarCoords("+n+", "+e+", "+d+".xyz, "+o+`);
-            #endif
-
-            #ifdef `+this._defineCubicName+`
-                #ifdef `+this._defineLocalCubicName+`
-                    vec3 `+this._reflectionVectorName+" = computeCubicLocalCoords("+n+", "+e+", "+d+".xyz, "+o+`, vReflectionSize, vReflectionPosition);
-                #else
-                vec3 `+this._reflectionVectorName+" = computeCubicCoords("+n+", "+e+", "+d+".xyz, "+o+`);
-                #endif
-            #endif
-
-            #ifdef `+this._defineProjectionName+`
-                vec3 `+this._reflectionVectorName+" = computeProjectionCoords("+n+", "+p+", "+o+`);
-            #endif
-
-            #ifdef `+this._defineSkyboxName+`
-                vec3 `+this._reflectionVectorName+" = computeSkyBoxCoords("+s+", "+o+`);
-            #endif
-
-            #ifdef `+this._defineExplicitName+`
-                vec3 `+this._reflectionVectorName+` = vec3(0, 0, 0);
-            #endif
-
-            #ifdef `+this._defineOppositeZ+`
-                `+this._reflectionVectorName+`.z *= -1.0;
-            #endif\r
-`;return i||(b+=`
-                #ifdef `+this._define3DName+`
-                    vec3 `+this._reflectionCoordsName+" = "+this._reflectionVectorName+`;
-                #else
-                    vec2 `+this._reflectionCoordsName+" = "+this._reflectionVectorName+`.xy;
-                    #ifdef `+this._defineProjectionName+`
-                        `+this._reflectionCoordsName+" /= "+this._reflectionVectorName+`.z;
-                    #endif
-                    `+this._reflectionCoordsName+".y = 1.0 - "+this._reflectionCoordsName+`.y;
-                #endif\r
-`),b},t.prototype.handleFragmentSideCodeReflectionColor=function(e,n){n===void 0&&(n=".rgb");var i="vec"+(n.length===0?"4":n.length-1)+" "+this._reflectionColorName+`;
-            #ifdef `+this._define3DName+`\r
-`;return i+=e?this._reflectionColorName+" = textureCubeLodEXT("+this._cubeSamplerName+", "+this._reflectionVectorName+", "+e+")"+n+`;\r
-`:this._reflectionColorName+" = textureCube("+this._cubeSamplerName+", "+this._reflectionVectorName+")"+n+`;\r
-`,i+=`
-            #else\r
-`,i+=e?this._reflectionColorName+" = texture2DLodEXT("+this._2DSamplerName+", "+this._reflectionCoordsName+", "+e+")"+n+`;\r
-`:this._reflectionColorName+" = texture2D("+this._2DSamplerName+", "+this._reflectionCoordsName+")"+n+`;\r
-`,i+=`#endif\r
-`},t.prototype.writeOutputs=function(e,n){var i="";if(e.target===xe.Fragment)for(var o=0,a=this._outputs;o<a.length;o++){var s=a[o];s.hasEndpoints&&(i+=this._declareOutput(s,e)+" = "+n+"."+s.name+`;\r
-`)}return i},t.prototype._buildBlock=function(e){return r.prototype._buildBlock.call(this,e),this},t.prototype._dumpPropertiesCode=function(){return this.texture?(e=this.texture.isCube?this._codeVariableName+'.texture = new BABYLON.CubeTexture("'+this.texture.name+`");\r
-`:this._codeVariableName+'.texture = new BABYLON.Texture("'+this.texture.name+`");\r
-`,e+=this._codeVariableName+".texture.coordinatesMode = "+this.texture.coordinatesMode+`;\r
-`):"";var e},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return this.texture&&(e.texture=this.texture.serialize()),e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),e.texture&&(i=e.texture.url.indexOf("data:")===0?"":i,e.texture.isCube?this.texture=ai.Parse(e.texture,n,i):this.texture=we.a.Parse(e.texture,n,i))},t}(pt);R.a.RegisteredTypes["BABYLON.ReflectionTextureBaseBlock"]=dc;var xh=function(r){function t(e){var n=r.call(this,e)||this;return n.registerInput("position",le.Vector3,!1,xe.Vertex),n.registerInput("worldPosition",le.Vector4,!1,xe.Vertex),n.registerInput("worldNormal",le.Vector4,!1,xe.Fragment),n.registerInput("world",le.Matrix,!1,xe.Vertex),n.registerInput("cameraPosition",le.Vector3,!1,xe.Fragment),n.registerInput("view",le.Matrix,!1,xe.Fragment),n.registerOutput("rgb",le.Color3,xe.Fragment),n.registerOutput("rgba",le.Color4,xe.Fragment),n.registerOutput("r",le.Float,xe.Fragment),n.registerOutput("g",le.Float,xe.Fragment),n.registerOutput("b",le.Float,xe.Fragment),n.registerOutput("a",le.Float,xe.Fragment),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector4),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ReflectionTextureBlock"},Object.defineProperty(t.prototype,"position",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldPosition",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldNormal",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"world",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraPosition",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"view",{get:function(){return this._inputs[5]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgb",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgba",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"r",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"g",{get:function(){return this._outputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"b",{get:function(){return this._outputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"a",{get:function(){return this._outputs[5]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(r.prototype.autoConfigure.call(this,e),!this.cameraPosition.isConnected){var n=e.getInputBlockByPredicate(function(i){return i.systemValue===bt.CameraPosition});n||(n=new At("cameraPosition")).setAsSystemValue(bt.CameraPosition),n.output.connectTo(this.cameraPosition)}},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),!this.texture)return e.compilationString+=this.writeOutputs(e,"vec3(0.)"),this;if(e.target!==xe.Fragment)return e.compilationString+=this.handleVertexSide(e),this;this.handleFragmentSideInits(e);var n=e._getFreeVariableName("normalWUnit");return e.compilationString+="vec4 "+n+" = normalize("+this.worldNormal.associatedVariableName+`);\r
-`,e.compilationString+=this.handleFragmentSideCodeReflectionCoords(n),e.compilationString+=this.handleFragmentSideCodeReflectionColor(void 0,""),e.compilationString+=this.writeOutputs(e,this._reflectionColorName),this},t}(dc);R.a.RegisteredTypes["BABYLON.ReflectionTextureBlock"]=xh;var Rh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"AddBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = "+this.left.associatedVariableName+" + "+this.right.associatedVariableName+`;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.AddBlock"]=Rh;var Oh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("input",le.AutoDetect),n.registerInput("factor",le.Float),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ScaleBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"factor",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = "+this.input.associatedVariableName+" * "+this.factor.associatedVariableName+`;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.ScaleBlock"]=Oh;var Mh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.minimum=0,n.maximum=1,n.registerInput("value",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ClampBlock"},Object.defineProperty(t.prototype,"value",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = clamp("+this.value.associatedVariableName+", "+this._writeFloat(this.minimum)+", "+this._writeFloat(this.maximum)+`);\r
-`,this},t.prototype._dumpPropertiesCode=function(){var e=this._codeVariableName+".minimum = "+this.minimum+`;\r
-`;return e+=this._codeVariableName+".maximum = "+this.maximum+`;\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.minimum=this.minimum,e.maximum=this.maximum,e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.minimum=e.minimum,this.maximum=e.maximum},Object(c.c)([Vt("Minimum",Lt.Float)],t.prototype,"minimum",void 0),Object(c.c)([Vt("Maximum",Lt.Float)],t.prototype,"maximum",void 0),t}(pt);R.a.RegisteredTypes["BABYLON.ClampBlock"]=Mh;var Ih=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.Vector3),n._linkConnectionTypes(0,1),n._inputs[0].excludedConnectionPointTypes.push(le.Float),n._inputs[0].excludedConnectionPointTypes.push(le.Matrix),n._inputs[0].excludedConnectionPointTypes.push(le.Vector2),n._inputs[1].excludedConnectionPointTypes.push(le.Float),n._inputs[1].excludedConnectionPointTypes.push(le.Matrix),n._inputs[1].excludedConnectionPointTypes.push(le.Vector2),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"CrossBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = cross("+this.left.associatedVariableName+".xyz, "+this.right.associatedVariableName+`.xyz);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.CrossBlock"]=Ih;var Dh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.Float),n._linkConnectionTypes(0,1),n._inputs[0].excludedConnectionPointTypes.push(le.Float),n._inputs[0].excludedConnectionPointTypes.push(le.Matrix),n._inputs[1].excludedConnectionPointTypes.push(le.Float),n._inputs[1].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"DotBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = dot("+this.left.associatedVariableName+", "+this.right.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.DotBlock"]=Dh;var Lh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("input",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._inputs[0].excludedConnectionPointTypes.push(le.Float),n._inputs[0].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"NormalizeBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0],i=this._inputs[0];return e.compilationString+=this._declareOutput(n,e)+" = normalize("+i.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.NormalizeBlock"]=Lh;var Nh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("rgb ",le.Color3,!0),n.registerInput("r",le.Float,!0),n.registerInput("g",le.Float,!0),n.registerInput("b",le.Float,!0),n.registerInput("a",le.Float,!0),n.registerOutput("rgba",le.Color4),n.registerOutput("rgb",le.Color3),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ColorMergerBlock"},Object.defineProperty(t.prototype,"rgbIn",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"r",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"g",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"b",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"a",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgba",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgbOut",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgb",{get:function(){return this.rgbOut},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this.r,i=this.g,o=this.b,a=this.a,s=this.rgbIn,d=this._outputs[0],p=this._outputs[1];return s.isConnected?d.hasEndpoints?e.compilationString+=this._declareOutput(d,e)+" = vec4("+s.associatedVariableName+", "+(a.isConnected?this._writeVariable(a):"0.0")+`);\r
-`:p.hasEndpoints&&(e.compilationString+=this._declareOutput(p,e)+" = "+s.associatedVariableName+`;\r
-`):d.hasEndpoints?e.compilationString+=this._declareOutput(d,e)+" = vec4("+(n.isConnected?this._writeVariable(n):"0.0")+", "+(i.isConnected?this._writeVariable(i):"0.0")+", "+(o.isConnected?this._writeVariable(o):"0.0")+", "+(a.isConnected?this._writeVariable(a):"0.0")+`);\r
-`:p.hasEndpoints&&(e.compilationString+=this._declareOutput(p,e)+" = vec3("+(n.isConnected?this._writeVariable(n):"0.0")+", "+(i.isConnected?this._writeVariable(i):"0.0")+", "+(o.isConnected?this._writeVariable(o):"0.0")+`);\r
-`),this},t}(pt);R.a.RegisteredTypes["BABYLON.ColorMergerBlock"]=Nh;var wh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("xyzw",le.Vector4,!0),n.registerInput("xyz ",le.Vector3,!0),n.registerInput("xy ",le.Vector2,!0),n.registerOutput("xyz",le.Vector3),n.registerOutput("xy",le.Vector2),n.registerOutput("x",le.Float),n.registerOutput("y",le.Float),n.registerOutput("z",le.Float),n.registerOutput("w",le.Float),n.inputsAreExclusive=!0,n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"VectorSplitterBlock"},Object.defineProperty(t.prototype,"xyzw",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyzIn",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyIn",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyzOut",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyOut",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"x",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"y",{get:function(){return this._outputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"z",{get:function(){return this._outputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"w",{get:function(){return this._outputs[5]},enumerable:!1,configurable:!0}),t.prototype._inputRename=function(e){switch(e){case"xy ":return"xyIn";case"xyz ":return"xyzIn";default:return e}},t.prototype._outputRename=function(e){switch(e){case"xy":return"xyOut";case"xyz":return"xyzOut";default:return e}},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this.xyzw.isConnected?this.xyzw:this.xyzIn.isConnected?this.xyzIn:this.xyIn,i=this._outputs[0],o=this._outputs[1],a=this._outputs[2],s=this._outputs[3],d=this._outputs[4],p=this._outputs[5];return i.hasEndpoints&&(n===this.xyIn?e.compilationString+=this._declareOutput(i,e)+" = vec3("+n.associatedVariableName+`, 0.0);\r
-`:e.compilationString+=this._declareOutput(i,e)+" = "+n.associatedVariableName+`.xyz;\r
-`),o.hasEndpoints&&(e.compilationString+=this._declareOutput(o,e)+" = "+n.associatedVariableName+`.xy;\r
-`),a.hasEndpoints&&(e.compilationString+=this._declareOutput(a,e)+" = "+n.associatedVariableName+`.x;\r
-`),s.hasEndpoints&&(e.compilationString+=this._declareOutput(s,e)+" = "+n.associatedVariableName+`.y;\r
-`),d.hasEndpoints&&(e.compilationString+=this._declareOutput(d,e)+" = "+n.associatedVariableName+`.z;\r
-`),p.hasEndpoints&&(e.compilationString+=this._declareOutput(p,e)+" = "+n.associatedVariableName+`.w;\r
-`),this},t}(pt);R.a.RegisteredTypes["BABYLON.VectorSplitterBlock"]=wh;var Fh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerInput("gradient",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n._linkConnectionTypes(1,2,!0),n._inputs[2].acceptedConnectionPointTypes.push(le.Float),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"LerpBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"gradient",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = mix("+this.left.associatedVariableName+" , "+this.right.associatedVariableName+", "+this.gradient.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.LerpBlock"]=Fh;var Bh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"DivideBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = "+this.left.associatedVariableName+" / "+this.right.associatedVariableName+`;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.DivideBlock"]=Bh;var Uh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"SubtractBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = "+this.left.associatedVariableName+" - "+this.right.associatedVariableName+`;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.SubtractBlock"]=Uh;var Vh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("value",le.Float),n.registerInput("edge",le.Float),n.registerOutput("output",le.Float),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"StepBlock"},Object.defineProperty(t.prototype,"value",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"edge",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = step("+this.edge.associatedVariableName+", "+this.value.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.StepBlock"]=Vh;var fc=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("input",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._outputs[0].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"OneMinusBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = 1. - "+this.input.associatedVariableName+`;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.OneMinusBlock"]=fc,R.a.RegisteredTypes["BABYLON.OppositeBlock"]=fc;var pc=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("worldPosition",le.Vector4),n.registerInput("cameraPosition",le.Vector3),n.registerOutput("output",le.Vector3),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ViewDirectionBlock"},Object.defineProperty(t.prototype,"worldPosition",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraPosition",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.cameraPosition.isConnected){var n=e.getInputBlockByPredicate(function(i){return i.systemValue===bt.CameraPosition});n||(n=new At("cameraPosition")).setAsSystemValue(bt.CameraPosition),n.output.connectTo(this.cameraPosition)}},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = normalize("+this.cameraPosition.associatedVariableName+" - "+this.worldPosition.associatedVariableName+`.xyz);\r
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-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.FresnelBlock"]=kh;var Gh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"MaxBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = max("+this.left.associatedVariableName+", "+this.right.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.MaxBlock"]=Gh;var zh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"MinBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = min("+this.left.associatedVariableName+", "+this.right.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.MinBlock"]=zh;var jh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.Float),n._linkConnectionTypes(0,1),n._inputs[0].excludedConnectionPointTypes.push(le.Float),n._inputs[0].excludedConnectionPointTypes.push(le.Matrix),n._inputs[1].excludedConnectionPointTypes.push(le.Float),n._inputs[1].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"DistanceBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = length("+this.left.associatedVariableName+" - "+this.right.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.DistanceBlock"]=jh;var Hh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("value",le.AutoDetect),n.registerOutput("output",le.Float),n._inputs[0].excludedConnectionPointTypes.push(le.Float),n._inputs[0].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"LengthBlock"},Object.defineProperty(t.prototype,"value",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = length("+this.value.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.LengthBlock"]=Hh;var Wh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("value",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"NegateBlock"},Object.defineProperty(t.prototype,"value",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = -1.0 * "+this.value.associatedVariableName+`;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.NegateBlock"]=Wh;var Xh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("value",le.AutoDetect),n.registerInput("power",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"PowBlock"},Object.defineProperty(t.prototype,"value",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"power",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = pow("+this.value.associatedVariableName+", "+this.power.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.PowBlock"]=Xh;var Yh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("seed",le.Vector2),n.registerOutput("output",le.Float),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector3),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector4),n._inputs[0].acceptedConnectionPointTypes.push(le.Color3),n._inputs[0].acceptedConnectionPointTypes.push(le.Color4),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"RandomNumberBlock"},Object.defineProperty(t.prototype,"seed",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0],i="//"+this.name;return e._emitFunctionFromInclude("helperFunctions",i),e.compilationString+=this._declareOutput(n,e)+" = getRand("+this.seed.associatedVariableName+`.xy);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.RandomNumberBlock"]=Yh;var Kh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("x",le.Float),n.registerInput("y",le.Float),n.registerOutput("output",le.Float),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ArcTan2Block"},Object.defineProperty(t.prototype,"x",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"y",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = atan("+this.x.associatedVariableName+", "+this.y.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.ArcTan2Block"]=Kh;var Qh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("value",le.AutoDetect),n.registerInput("edge0",le.Float),n.registerInput("edge1",le.Float),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"SmoothStepBlock"},Object.defineProperty(t.prototype,"value",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"edge0",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"edge1",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = smoothstep("+this.edge0.associatedVariableName+", "+this.edge1.associatedVariableName+", "+this.value.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.SmoothStepBlock"]=Qh;var qh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("input",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._outputs[0].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ReciprocalBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = 1. / "+this.input.associatedVariableName+`;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.ReciprocalBlock"]=qh;var Zh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("value",le.AutoDetect),n.registerInput("reference",le.AutoDetect),n.registerInput("distance",le.Float),n.registerInput("replacement",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n._linkConnectionTypes(0,3),n._inputs[0].excludedConnectionPointTypes.push(le.Float),n._inputs[0].excludedConnectionPointTypes.push(le.Matrix),n._inputs[1].excludedConnectionPointTypes.push(le.Float),n._inputs[1].excludedConnectionPointTypes.push(le.Matrix),n._inputs[3].excludedConnectionPointTypes.push(le.Float),n._inputs[3].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ReplaceColorBlock"},Object.defineProperty(t.prototype,"value",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"reference",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"distance",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"replacement",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+`;\r
-`,e.compilationString+="if (length("+this.value.associatedVariableName+" - "+this.reference.associatedVariableName+") < "+this.distance.associatedVariableName+`) {\r
-`,e.compilationString+=n.associatedVariableName+" = "+this.replacement.associatedVariableName+`;\r
-`,e.compilationString+=`} else {\r
-`,e.compilationString+=n.associatedVariableName+" = "+this.value.associatedVariableName+`;\r
-`,e.compilationString+=`}\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.ReplaceColorBlock"]=Zh;var or,Jh=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("value",le.AutoDetect),n.registerInput("steps",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n._inputs[0].excludedConnectionPointTypes.push(le.Matrix),n._inputs[1].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"PosterizeBlock"},Object.defineProperty(t.prototype,"value",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"steps",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = floor("+this.value.associatedVariableName+" / (1.0 / "+this.steps.associatedVariableName+")) * (1.0 / "+this.steps.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.PosterizeBlock"]=Jh,function(r){r[r.SawTooth=0]="SawTooth",r[r.Square=1]="Square",r[r.Triangle=2]="Triangle"}(or||(or={}));var $h=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.kind=or.SawTooth,n.registerInput("input",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._inputs[0].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"WaveBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];switch(this.kind){case or.SawTooth:e.compilationString+=this._declareOutput(n,e)+" = "+this.input.associatedVariableName+" - floor(0.5 + "+this.input.associatedVariableName+`);\r
-`;break;case or.Square:e.compilationString+=this._declareOutput(n,e)+" = 1.0 - 2.0 * round(fract("+this.input.associatedVariableName+`));\r
-`;break;case or.Triangle:e.compilationString+=this._declareOutput(n,e)+" = 2.0 * abs(2.0 * ("+this.input.associatedVariableName+" - floor(0.5 + "+this.input.associatedVariableName+`))) - 1.0;\r
-`}return this},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.kind=this.kind,e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.kind=e.kind},t}(pt);R.a.RegisteredTypes["BABYLON.WaveBlock"]=$h;var va=function(){function r(t,e){this.step=t,this.color=e}return Object.defineProperty(r.prototype,"step",{get:function(){return this._step},set:function(t){this._step=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"color",{get:function(){return this._color},set:function(t){this._color=t},enumerable:!1,configurable:!0}),r}(),ed=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.colorSteps=[new va(0,M.a.Black()),new va(1,M.a.White())],n.onValueChangedObservable=new x.c,n.registerInput("gradient",le.Float),n.registerOutput("output",le.Color3),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector2),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector3),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector4),n._inputs[0].acceptedConnectionPointTypes.push(le.Color3),n._inputs[0].acceptedConnectionPointTypes.push(le.Color4),n}return Object(c.d)(t,r),t.prototype.colorStepsUpdated=function(){this.onValueChangedObservable.notifyObservers(this)},t.prototype.getClassName=function(){return"GradientBlock"},Object.defineProperty(t.prototype,"gradient",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._writeColorConstant=function(e){var n=this.colorSteps[e];return"vec3("+n.color.r+", "+n.color.g+", "+n.color.b+")"},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];if(this.colorSteps.length&&this.gradient.connectedPoint){var i=e._getFreeVariableName("gradientTempColor"),o=e._getFreeVariableName("gradientTempPosition");e.compilationString+="vec3 "+i+" = "+this._writeColorConstant(0)+`;\r
-`,e.compilationString+="float "+o+`;\r
-`;var a=this.gradient.associatedVariableName;this.gradient.connectedPoint.type!==le.Float&&(a+=".x");for(var s=1;s<this.colorSteps.length;s++){var d=this.colorSteps[s],p=this.colorSteps[s-1];e.compilationString+=o+" = clamp(("+a+" - "+e._emitFloat(p.step)+") / ("+e._emitFloat(d.step)+" -  "+e._emitFloat(p.step)+"), 0.0, 1.0) * step("+e._emitFloat(s)+", "+e._emitFloat(this.colorSteps.length-1)+`);\r
-`,e.compilationString+=i+" = mix("+i+", "+this._writeColorConstant(s)+", "+o+`);\r
-`}return e.compilationString+=this._declareOutput(n,e)+" = "+i+`;\r
-`,this}e.compilationString+=this._declareOutput(n,e)+` = vec3(0., 0., 0.);\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);e.colorSteps=[];for(var n=0,i=this.colorSteps;n<i.length;n++){var o=i[n];e.colorSteps.push({step:o.step,color:{r:o.color.r,g:o.color.g,b:o.color.b}})}return e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.colorSteps=[];for(var o=0,a=e.colorSteps;o<a.length;o++){var s=a[o];this.colorSteps.push(new va(s.step,new M.a(s.color.r,s.color.g,s.color.b)))}},t.prototype._dumpPropertiesCode=function(){for(var e="",n=0,i=this.colorSteps;n<i.length;n++){var o=i[n];e+=this._codeVariableName+".colorSteps.push(new BABYLON.GradientBlockColorStep("+o.step+", new BABYLON.Color3("+o.color.r+", "+o.color.g+", "+o.color.b+`)));\r
-`}return e},t}(pt);R.a.RegisteredTypes["BABYLON.GradientBlock"]=ed;var td=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerInput("gradient",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n._linkConnectionTypes(1,2,!0),n._inputs[2].acceptedConnectionPointTypes.push(le.Float),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"NLerpBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"gradient",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = normalize(mix("+this.left.associatedVariableName+" , "+this.right.associatedVariableName+", "+this.gradient.associatedVariableName+`));\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.NLerpBlock"]=td;var nd=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.manhattanDistance=!1,n.registerInput("seed",le.Vector3),n.registerInput("jitter",le.Float),n.registerOutput("output",le.Vector2),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"WorleyNoise3DBlock"},Object.defineProperty(t.prototype,"seed",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"jitter",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),this.seed.isConnected&&this._outputs[0].hasEndpoints)return e._emitFunction("worley3D",`vec3 permute(vec3 x){\r
-    return mod((34.0 * x + 1.0) * x, 289.0);\r
-}\r
-\r
-vec3 dist(vec3 x, vec3 y, vec3 z,  bool manhattanDistance){\r
-    return manhattanDistance ?  abs(x) + abs(y) + abs(z) :  (x * x + y * y + z * z);\r
-}\r
-\r
-vec2 worley(vec3 P, float jitter, bool manhattanDistance){\r
-    float K = 0.142857142857; // 1/7\r
-    float Ko = 0.428571428571; // 1/2-K/2\r
-    float  K2 = 0.020408163265306; // 1/(7*7)\r
-    float Kz = 0.166666666667; // 1/6\r
-    float Kzo = 0.416666666667; // 1/2-1/6*2\r
-\r
-    vec3 Pi = mod(floor(P), 289.0);\r
-    vec3 Pf = fract(P) - 0.5;\r
-\r
-    vec3 Pfx = Pf.x + vec3(1.0, 0.0, -1.0);\r
-    vec3 Pfy = Pf.y + vec3(1.0, 0.0, -1.0);\r
-    vec3 Pfz = Pf.z + vec3(1.0, 0.0, -1.0);\r
-\r
-    vec3 p = permute(Pi.x + vec3(-1.0, 0.0, 1.0));\r
-    vec3 p1 = permute(p + Pi.y - 1.0);\r
-    vec3 p2 = permute(p + Pi.y);\r
-    vec3 p3 = permute(p + Pi.y + 1.0);\r
-\r
-    vec3 p11 = permute(p1 + Pi.z - 1.0);\r
-    vec3 p12 = permute(p1 + Pi.z);\r
-    vec3 p13 = permute(p1 + Pi.z + 1.0);\r
-\r
-    vec3 p21 = permute(p2 + Pi.z - 1.0);\r
-    vec3 p22 = permute(p2 + Pi.z);\r
-    vec3 p23 = permute(p2 + Pi.z + 1.0);\r
-\r
-    vec3 p31 = permute(p3 + Pi.z - 1.0);\r
-    vec3 p32 = permute(p3 + Pi.z);\r
-    vec3 p33 = permute(p3 + Pi.z + 1.0);\r
-\r
-    vec3 ox11 = fract(p11*K) - Ko;\r
-    vec3 oy11 = mod(floor(p11*K), 7.0)*K - Ko;\r
-    vec3 oz11 = floor(p11*K2)*Kz - Kzo; // p11 < 289 guaranteed\r
-\r
-    vec3 ox12 = fract(p12*K) - Ko;\r
-    vec3 oy12 = mod(floor(p12*K), 7.0)*K - Ko;\r
-    vec3 oz12 = floor(p12*K2)*Kz - Kzo;\r
-\r
-    vec3 ox13 = fract(p13*K) - Ko;\r
-    vec3 oy13 = mod(floor(p13*K), 7.0)*K - Ko;\r
-    vec3 oz13 = floor(p13*K2)*Kz - Kzo;\r
-\r
-    vec3 ox21 = fract(p21*K) - Ko;\r
-    vec3 oy21 = mod(floor(p21*K), 7.0)*K - Ko;\r
-    vec3 oz21 = floor(p21*K2)*Kz - Kzo;\r
-\r
-    vec3 ox22 = fract(p22*K) - Ko;\r
-    vec3 oy22 = mod(floor(p22*K), 7.0)*K - Ko;\r
-    vec3 oz22 = floor(p22*K2)*Kz - Kzo;\r
-\r
-    vec3 ox23 = fract(p23*K) - Ko;\r
-    vec3 oy23 = mod(floor(p23*K), 7.0)*K - Ko;\r
-    vec3 oz23 = floor(p23*K2)*Kz - Kzo;\r
-\r
-    vec3 ox31 = fract(p31*K) - Ko;\r
-    vec3 oy31 = mod(floor(p31*K), 7.0)*K - Ko;\r
-    vec3 oz31 = floor(p31*K2)*Kz - Kzo;\r
-\r
-    vec3 ox32 = fract(p32*K) - Ko;\r
-    vec3 oy32 = mod(floor(p32*K), 7.0)*K - Ko;\r
-    vec3 oz32 = floor(p32*K2)*Kz - Kzo;\r
-\r
-    vec3 ox33 = fract(p33*K) - Ko;\r
-    vec3 oy33 = mod(floor(p33*K), 7.0)*K - Ko;\r
-    vec3 oz33 = floor(p33*K2)*Kz - Kzo;\r
-\r
-    vec3 dx11 = Pfx + jitter*ox11;\r
-    vec3 dy11 = Pfy.x + jitter*oy11;\r
-    vec3 dz11 = Pfz.x + jitter*oz11;\r
-\r
-    vec3 dx12 = Pfx + jitter*ox12;\r
-    vec3 dy12 = Pfy.x + jitter*oy12;\r
-    vec3 dz12 = Pfz.y + jitter*oz12;\r
-\r
-    vec3 dx13 = Pfx + jitter*ox13;\r
-    vec3 dy13 = Pfy.x + jitter*oy13;\r
-    vec3 dz13 = Pfz.z + jitter*oz13;\r
-\r
-    vec3 dx21 = Pfx + jitter*ox21;\r
-    vec3 dy21 = Pfy.y + jitter*oy21;\r
-    vec3 dz21 = Pfz.x + jitter*oz21;\r
-\r
-    vec3 dx22 = Pfx + jitter*ox22;\r
-    vec3 dy22 = Pfy.y + jitter*oy22;\r
-    vec3 dz22 = Pfz.y + jitter*oz22;\r
-\r
-    vec3 dx23 = Pfx + jitter*ox23;\r
-    vec3 dy23 = Pfy.y + jitter*oy23;\r
-    vec3 dz23 = Pfz.z + jitter*oz23;\r
-\r
-    vec3 dx31 = Pfx + jitter*ox31;\r
-    vec3 dy31 = Pfy.z + jitter*oy31;\r
-    vec3 dz31 = Pfz.x + jitter*oz31;\r
-\r
-    vec3 dx32 = Pfx + jitter*ox32;\r
-    vec3 dy32 = Pfy.z + jitter*oy32;\r
-    vec3 dz32 = Pfz.y + jitter*oz32;\r
-\r
-    vec3 dx33 = Pfx + jitter*ox33;\r
-    vec3 dy33 = Pfy.z + jitter*oy33;\r
-    vec3 dz33 = Pfz.z + jitter*oz33;\r
-\r
-    vec3 d11 = dist(dx11, dy11, dz11, manhattanDistance);\r
-    vec3 d12 =dist(dx12, dy12, dz12, manhattanDistance);\r
-    vec3 d13 = dist(dx13, dy13, dz13, manhattanDistance);\r
-    vec3 d21 = dist(dx21, dy21, dz21, manhattanDistance);\r
-    vec3 d22 = dist(dx22, dy22, dz22, manhattanDistance);\r
-    vec3 d23 = dist(dx23, dy23, dz23, manhattanDistance);\r
-    vec3 d31 = dist(dx31, dy31, dz31, manhattanDistance);\r
-    vec3 d32 = dist(dx32, dy32, dz32, manhattanDistance);\r
-    vec3 d33 = dist(dx33, dy33, dz33, manhattanDistance);\r
-\r
-    vec3 d1a = min(d11, d12);\r
-    d12 = max(d11, d12);\r
-    d11 = min(d1a, d13); // Smallest now not in d12 or d13\r
-    d13 = max(d1a, d13);\r
-    d12 = min(d12, d13); // 2nd smallest now not in d13\r
-    vec3 d2a = min(d21, d22);\r
-    d22 = max(d21, d22);\r
-    d21 = min(d2a, d23); // Smallest now not in d22 or d23\r
-    d23 = max(d2a, d23);\r
-    d22 = min(d22, d23); // 2nd smallest now not in d23\r
-    vec3 d3a = min(d31, d32);\r
-    d32 = max(d31, d32);\r
-    d31 = min(d3a, d33); // Smallest now not in d32 or d33\r
-    d33 = max(d3a, d33);\r
-    d32 = min(d32, d33); // 2nd smallest now not in d33\r
-    vec3 da = min(d11, d21);\r
-    d21 = max(d11, d21);\r
-    d11 = min(da, d31); // Smallest now in d11\r
-    d31 = max(da, d31); // 2nd smallest now not in d31\r
-    d11.xy = (d11.x < d11.y) ? d11.xy : d11.yx;\r
-    d11.xz = (d11.x < d11.z) ? d11.xz : d11.zx; // d11.x now smallest\r
-    d12 = min(d12, d21); // 2nd smallest now not in d21\r
-    d12 = min(d12, d22); // nor in d22\r
-    d12 = min(d12, d31); // nor in d31\r
-    d12 = min(d12, d32); // nor in d32\r
-    d11.yz = min(d11.yz,d12.xy); // nor in d12.yz\r
-    d11.y = min(d11.y,d12.z); // Only two more to go\r
-    d11.y = min(d11.y,d11.z); // Done! (Phew!)\r
-    return sqrt(d11.xy); // F1, F2\r
-}\r
-\r
-`,"// Worley3D"),e.compilationString+=this._declareOutput(this._outputs[0],e)+" = worley("+this.seed.associatedVariableName+", "+this.jitter.associatedVariableName+", "+this.manhattanDistance+`);\r
-`,this},t.prototype._dumpPropertiesCode=function(){return this._codeVariableName+".manhattanDistance = "+this.manhattanDistance+`;\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.manhattanDistance=this.manhattanDistance,e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.manhattanDistance=e.manhattanDistance},Object(c.c)([Vt("Use Manhattan Distance",Lt.Boolean,"PROPERTIES",{notifiers:{update:!1}})],t.prototype,"manhattanDistance",void 0),t}(pt);R.a.RegisteredTypes["BABYLON.WorleyNoise3DBlock"]=nd;var id=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("seed",le.Vector3),n.registerOutput("output",le.Float),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"SimplexPerlin3DBlock"},Object.defineProperty(t.prototype,"seed",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),this.seed.isConnected&&this._outputs[0].hasEndpoints)return e._emitFunction("SimplexPerlin3D",`const float SKEWFACTOR = 1.0/3.0;\r
-const float UNSKEWFACTOR = 1.0/6.0;\r
-const float SIMPLEX_CORNER_POS = 0.5;\r
-const float SIMPLEX_TETRAHADRON_HEIGHT = 0.70710678118654752440084436210485;\r
-float SimplexPerlin3D( vec3 P ){\r
-    P *= SIMPLEX_TETRAHADRON_HEIGHT;\r
-    vec3 Pi = floor( P + dot( P, vec3( SKEWFACTOR) ) );    vec3 x0 = P - Pi + dot(Pi, vec3( UNSKEWFACTOR ) );\r
-    vec3 g = step(x0.yzx, x0.xyz);\r
-    vec3 l = 1.0 - g;\r
-    vec3 Pi_1 = min( g.xyz, l.zxy );\r
-    vec3 Pi_2 = max( g.xyz, l.zxy );\r
-    vec3 x1 = x0 - Pi_1 + UNSKEWFACTOR;\r
-    vec3 x2 = x0 - Pi_2 + SKEWFACTOR;\r
-    vec3 x3 = x0 - SIMPLEX_CORNER_POS;\r
-    vec4 v1234_x = vec4( x0.x, x1.x, x2.x, x3.x );\r
-    vec4 v1234_y = vec4( x0.y, x1.y, x2.y, x3.y );\r
-    vec4 v1234_z = vec4( x0.z, x1.z, x2.z, x3.z );\r
-    Pi.xyz = Pi.xyz - floor(Pi.xyz * ( 1.0 / 69.0 )) * 69.0;\r
-    vec3 Pi_inc1 = step( Pi, vec3( 69.0 - 1.5 ) ) * ( Pi + 1.0 );\r
-    vec4 Pt = vec4( Pi.xy, Pi_inc1.xy ) + vec2( 50.0, 161.0 ).xyxy;\r
-    Pt *= Pt;\r
-    vec4 V1xy_V2xy = mix( Pt.xyxy, Pt.zwzw, vec4( Pi_1.xy, Pi_2.xy ) );\r
-    Pt = vec4( Pt.x, V1xy_V2xy.xz, Pt.z ) * vec4( Pt.y, V1xy_V2xy.yw, Pt.w );\r
-    const vec3 SOMELARGEFLOATS = vec3( 635.298681, 682.357502, 668.926525 );\r
-    const vec3 ZINC = vec3( 48.500388, 65.294118, 63.934599 );\r
-    vec3 lowz_mods = vec3( 1.0 / ( SOMELARGEFLOATS.xyz + Pi.zzz * ZINC.xyz ) );\r
-    vec3 highz_mods = vec3( 1.0 / ( SOMELARGEFLOATS.xyz + Pi_inc1.zzz * ZINC.xyz ) );\r
-    Pi_1 = ( Pi_1.z < 0.5 ) ? lowz_mods : highz_mods;\r
-    Pi_2 = ( Pi_2.z < 0.5 ) ? lowz_mods : highz_mods;\r
-    vec4 hash_0 = fract( Pt * vec4( lowz_mods.x, Pi_1.x, Pi_2.x, highz_mods.x ) ) - 0.49999;\r
-    vec4 hash_1 = fract( Pt * vec4( lowz_mods.y, Pi_1.y, Pi_2.y, highz_mods.y ) ) - 0.49999;\r
-    vec4 hash_2 = fract( Pt * vec4( lowz_mods.z, Pi_1.z, Pi_2.z, highz_mods.z ) ) - 0.49999;\r
-    vec4 grad_results = inversesqrt( hash_0 * hash_0 + hash_1 * hash_1 + hash_2 * hash_2 ) * ( hash_0 * v1234_x + hash_1 * v1234_y + hash_2 * v1234_z );\r
-    const float FINAL_NORMALIZATION = 37.837227241611314102871574478976;\r
-    vec4 kernel_weights = v1234_x * v1234_x + v1234_y * v1234_y + v1234_z * v1234_z;\r
-    kernel_weights = max(0.5 - kernel_weights, 0.0);\r
-    kernel_weights = kernel_weights*kernel_weights*kernel_weights;\r
-    return dot( kernel_weights, grad_results ) * FINAL_NORMALIZATION;\r
-}\r
-`,"// SimplexPerlin3D"),e.compilationString+=this._declareOutput(this._outputs[0],e)+" = SimplexPerlin3D("+this.seed.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.SimplexPerlin3DBlock"]=id;var rd=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("normalMap0",le.Vector3),n.registerInput("normalMap1",le.Vector3),n.registerOutput("output",le.Vector3),n._inputs[0].acceptedConnectionPointTypes.push(le.Color3),n._inputs[0].acceptedConnectionPointTypes.push(le.Color4),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector4),n._inputs[1].acceptedConnectionPointTypes.push(le.Color3),n._inputs[1].acceptedConnectionPointTypes.push(le.Color4),n._inputs[1].acceptedConnectionPointTypes.push(le.Vector4),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"NormalBlendBlock"},Object.defineProperty(t.prototype,"normalMap0",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"normalMap1",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0],i=this._inputs[0],o=this._inputs[1],a=e._getFreeVariableName("stepR"),s=e._getFreeVariableName("stepG");return e.compilationString+="float "+a+" = step(0.5, "+i.associatedVariableName+`.r);\r
-`,e.compilationString+="float "+s+" = step(0.5, "+i.associatedVariableName+`.g);\r
-`,e.compilationString+=this._declareOutput(n,e)+`;\r
-`,e.compilationString+=n.associatedVariableName+".r = (1.0 - "+a+") * "+i.associatedVariableName+".r * "+o.associatedVariableName+".r * 2.0 + "+a+" * (1.0 - "+i.associatedVariableName+".r) * (1.0 - "+o.associatedVariableName+`.r) * 2.0;\r
-`,e.compilationString+=n.associatedVariableName+".g = (1.0 - "+s+") * "+i.associatedVariableName+".g * "+o.associatedVariableName+".g * 2.0 + "+s+" * (1.0 - "+i.associatedVariableName+".g) * (1.0 - "+o.associatedVariableName+`.g) * 2.0;\r
-`,e.compilationString+=n.associatedVariableName+".b = "+i.associatedVariableName+".b * "+o.associatedVariableName+`.b;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.NormalBlendBlock"]=rd;var od=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("input",le.Vector2),n.registerInput("angle",le.Float),n.registerOutput("output",le.Vector2),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"Rotate2dBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"angle",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.angle.isConnected){var n=new At("angle");n.value=0,n.output.connectTo(this.angle)}},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0],i=this.angle,o=this.input;return e.compilationString+=this._declareOutput(n,e)+" = vec2(cos("+i.associatedVariableName+") * "+o.associatedVariableName+".x - sin("+i.associatedVariableName+") * "+o.associatedVariableName+".y, sin("+i.associatedVariableName+") * "+o.associatedVariableName+".x + cos("+i.associatedVariableName+") * "+o.associatedVariableName+`.y);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.Rotate2dBlock"]=od;var ad=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("incident",le.Vector3),n.registerInput("normal",le.Vector3),n.registerOutput("output",le.Vector3),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector4),n._inputs[0].acceptedConnectionPointTypes.push(le.Color3),n._inputs[0].acceptedConnectionPointTypes.push(le.Color4),n._inputs[1].acceptedConnectionPointTypes.push(le.Vector4),n._inputs[1].acceptedConnectionPointTypes.push(le.Color3),n._inputs[1].acceptedConnectionPointTypes.push(le.Color4),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ReflectBlock"},Object.defineProperty(t.prototype,"incident",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"normal",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = reflect("+this.incident.associatedVariableName+".xyz, "+this.normal.associatedVariableName+`.xyz);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.ReflectBlock"]=ad;var sd=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("incident",le.Vector3),n.registerInput("normal",le.Vector3),n.registerInput("ior",le.Float),n.registerOutput("output",le.Vector3),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector4),n._inputs[0].acceptedConnectionPointTypes.push(le.Color3),n._inputs[0].acceptedConnectionPointTypes.push(le.Color4),n._inputs[1].acceptedConnectionPointTypes.push(le.Vector4),n._inputs[1].acceptedConnectionPointTypes.push(le.Color3),n._inputs[1].acceptedConnectionPointTypes.push(le.Color4),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"RefractBlock"},Object.defineProperty(t.prototype,"incident",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"normal",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"ior",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = refract("+this.incident.associatedVariableName+".xyz, "+this.normal.associatedVariableName+".xyz, "+this.ior.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.RefractBlock"]=sd;var cd=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("color",le.Color3),n.registerInput("level",le.Float),n.registerOutput("output",le.Color3),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"DesaturateBlock"},Object.defineProperty(t.prototype,"color",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"level",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0],i=this.color.associatedVariableName,o=e._getFreeVariableName("colorMin"),a=e._getFreeVariableName("colorMax"),s=e._getFreeVariableName("colorMerge");return e.compilationString+="float "+o+" = min(min("+i+".x, "+i+".y), "+i+`.z);\r
-`,e.compilationString+="float "+a+" = max(max("+i+".x, "+i+".y), "+i+`.z);\r
-`,e.compilationString+="float "+s+" = 0.5 * ("+o+" + "+a+`);\r
-`,e.compilationString+=this._declareOutput(n,e)+" = mix("+i+", vec3("+s+", "+s+", "+s+"), "+this.level.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.DesaturateBlock"]=cd;var Zn=function(r){function t(e,n,i,o,a,s){var d=r.call(this,e,n,i)||this;return d._blockType=o,d._blockName=a,d._nameForCheking=s,d._nameForCheking||(d._nameForCheking=e),d.needDualDirectionValidation=!0,d}return Object(c.d)(t,r),t.prototype.checkCompatibilityState=function(e){return e instanceof t&&e.name===this._nameForCheking?li.Compatible:li.TypeIncompatible},t.prototype.createCustomInputBlock=function(){return[new this._blockType(this._blockName),this.name]},t}(da),_c=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n.albedoScaling=!1,n.linkSheenWithAlbedo=!1,n._isUnique=!0,n.registerInput("intensity",le.Float,!0,xe.Fragment),n.registerInput("color",le.Color3,!0,xe.Fragment),n.registerInput("roughness",le.Float,!0,xe.Fragment),n.registerOutput("sheen",le.Object,xe.Fragment,new Zn("sheen",n,Tn.Output,t,"SheenBlock")),n}return Object(c.d)(t,r),t.prototype.initialize=function(e){e._excludeVariableName("sheenOut"),e._excludeVariableName("sheenMapData"),e._excludeVariableName("vSheenColor"),e._excludeVariableName("vSheenRoughness")},t.prototype.getClassName=function(){return"SheenBlock"},Object.defineProperty(t.prototype,"intensity",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"color",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"roughness",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"sheen",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.prepareDefines=function(e,n,i){r.prototype.prepareDefines.call(this,e,n,i),i.setValue("SHEEN",!0),i.setValue("SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE",!0,!0),i.setValue("SHEEN_LINKWITHALBEDO",this.linkSheenWithAlbedo,!0),i.setValue("SHEEN_ROUGHNESS",this.roughness.isConnected,!0),i.setValue("SHEEN_ALBEDOSCALING",this.albedoScaling,!0)},t.prototype.getCode=function(e){return`#ifdef SHEEN
-            sheenOutParams sheenOut;
-
-            vec4 vSheenColor = vec4(`+(this.color.isConnected?this.color.associatedVariableName:"vec3(1.)")+", "+(this.intensity.isConnected?this.intensity.associatedVariableName:"1.")+`);
-
-            sheenBlock(
-                vSheenColor,
-            #ifdef SHEEN_ROUGHNESS
-                `+(this.roughness.isConnected?this.roughness.associatedVariableName:"0.")+`,
-            #endif
-                roughness,
-            #ifdef SHEEN_TEXTURE
-                vec4(0.),
-            #endif
-                reflectance,
-            #ifdef SHEEN_LINKWITHALBEDO
-                baseColor,
-                surfaceAlbedo,
-            #endif
-            #ifdef ENVIRONMENTBRDF
-                NdotV,
-                environmentBrdf,
-            #endif
-            #if defined(REFLECTION) && defined(ENVIRONMENTBRDF)
-                AARoughnessFactors,
-                `+e?._vReflectionMicrosurfaceInfosName+`,
-                `+e?._vReflectionInfosName+`,
-                `+e?.reflectionColor+`,
-                vLightingIntensity,
-                #ifdef `+e?._define3DName+`
-                    `+e?._cubeSamplerName+`,
-                #else
-                    `+e?._2DSamplerName+`,
-                #endif
-                reflectionOut.reflectionCoords,
-                NdotVUnclamped,
-                #ifndef LODBASEDMICROSFURACE
-                    #ifdef `+e?._define3DName+`
-                        `+e?._cubeSamplerName+`,
-                        `+e?._cubeSamplerName+`,
-                    #else
-                        `+e?._2DSamplerName+`,
-                        `+e?._2DSamplerName+`,
-                    #endif
-                #endif
-                #if !defined(`+e?._defineSkyboxName+`) && defined(RADIANCEOCCLUSION)
-                    seo,
-                #endif
-                #if !defined(`+e?._defineSkyboxName+") && defined(HORIZONOCCLUSION) && defined(BUMP) && defined("+e?._define3DName+`)
-                    eho,
-                #endif
-            #endif
-                sheenOut
-            );
-
-            #ifdef SHEEN_LINKWITHALBEDO
-                surfaceAlbedo = sheenOut.surfaceAlbedo;
-            #endif
-        #endif\r
-`},t.prototype._buildBlock=function(e){return e.target===xe.Fragment&&e.sharedData.blocksWithDefines.push(this),this},t.prototype._dumpPropertiesCode=function(){var e=r.prototype._dumpPropertiesCode.call(this);return e+=this._codeVariableName+".albedoScaling = "+this.albedoScaling+`;\r
-`,e+=this._codeVariableName+".linkSheenWithAlbedo = "+this.linkSheenWithAlbedo+`;\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.albedoScaling=this.albedoScaling,e.linkSheenWithAlbedo=this.linkSheenWithAlbedo,e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.albedoScaling=e.albedoScaling,this.linkSheenWithAlbedo=e.linkSheenWithAlbedo},Object(c.c)([Vt("Albedo scaling",Lt.Boolean,"PROPERTIES",{notifiers:{update:!0}})],t.prototype,"albedoScaling",void 0),Object(c.c)([Vt("Link sheen with albedo",Lt.Boolean,"PROPERTIES",{notifiers:{update:!0}})],t.prototype,"linkSheenWithAlbedo",void 0),t}(pt);R.a.RegisteredTypes["BABYLON.SheenBlock"]=_c;var mc=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n._isUnique=!0,n.registerInput("intensity",le.Float,!0,xe.Fragment),n.registerInput("direction",le.Vector2,!0,xe.Fragment),n.registerInput("uv",le.Vector2,!0),n.registerInput("worldTangent",le.Vector4,!0),n.registerOutput("anisotropy",le.Object,xe.Fragment,new Zn("anisotropy",n,Tn.Output,t,"AnisotropyBlock")),n}return Object(c.d)(t,r),t.prototype.initialize=function(e){e._excludeVariableName("anisotropicOut"),e._excludeVariableName("TBN")},t.prototype.getClassName=function(){return"AnisotropyBlock"},Object.defineProperty(t.prototype,"intensity",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"direction",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"uv",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldTangent",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"anisotropy",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._generateTBNSpace=function(e){var n="",i="//"+this.name,o=this.uv,a=this.worldPositionConnectionPoint,s=this.worldNormalConnectionPoint,d=this.worldTangent;o.isConnected||console.error("You must connect the 'uv' input of the Anisotropy block!"),e._emitExtension("derivatives","#extension GL_OES_standard_derivatives : enable");var p={search:/defined\(TANGENT\)/g,replace:d.isConnected?"defined(TANGENT)":"defined(IGNORE)"};return d.isConnected&&(n+="vec3 tbnNormal = normalize("+s.associatedVariableName+`.xyz);\r
-`,n+="vec3 tbnTangent = normalize("+d.associatedVariableName+`.xyz);\r
-`,n+=`vec3 tbnBitangent = cross(tbnNormal, tbnTangent);\r
-`,n+=`mat3 vTBN = mat3(tbnTangent, tbnBitangent, tbnNormal);\r
-`),n+=`
-            #if defined(`+(d.isConnected?"TANGENT":"IGNORE")+`) && defined(NORMAL)
-                mat3 TBN = vTBN;
-            #else
-                mat3 TBN = cotangent_frame(`+s.associatedVariableName+".xyz, v_"+a.associatedVariableName+".xyz, "+(o.isConnected?o.associatedVariableName:"vec2(0.)")+`, vec2(1., 1.));
-            #endif\r
-`,e._emitFunctionFromInclude("bumpFragmentMainFunctions",i,{replaceStrings:[p]}),n},t.prototype.getCode=function(e,n){n===void 0&&(n=!1);var i="";n&&(i+=this._generateTBNSpace(e));var o=this.intensity.isConnected?this.intensity.associatedVariableName:"1.0";return i+=`anisotropicOutParams anisotropicOut;
-            anisotropicBlock(
-                vec3(`+(this.direction.isConnected?this.direction.associatedVariableName:"vec2(1., 0.)")+", "+o+`),
-            #ifdef ANISOTROPIC_TEXTURE
-                vec3(0.),
-            #endif
-                TBN,
-                normalW,
-                viewDirectionW,
-                anisotropicOut
-            );\r
-`},t.prototype.prepareDefines=function(e,n,i){r.prototype.prepareDefines.call(this,e,n,i),i.setValue("ANISOTROPIC",!0),i.setValue("ANISOTROPIC_TEXTURE",!1,!0)},t.prototype._buildBlock=function(e){return e.target===xe.Fragment&&e.sharedData.blocksWithDefines.push(this),this},t}(pt);R.a.RegisteredTypes["BABYLON.AnisotropyBlock"]=mc;var gc=function(r){function t(e){var n=r.call(this,e)||this;return n.useSphericalHarmonics=!0,n.forceIrradianceInFragment=!1,n._isUnique=!0,n.registerInput("position",le.Vector3,!1,xe.Vertex),n.registerInput("world",le.Matrix,!1,xe.Vertex),n.registerInput("color",le.Color3,!0,xe.Fragment),n.registerOutput("reflection",le.Object,xe.Fragment,new Zn("reflection",n,Tn.Output,t,"ReflectionBlock")),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ReflectionBlock"},Object.defineProperty(t.prototype,"position",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldPosition",{get:function(){return this.worldPositionConnectionPoint},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldNormal",{get:function(){return this.worldNormalConnectionPoint},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"world",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraPosition",{get:function(){return this.cameraPositionConnectionPoint},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"view",{get:function(){return this.viewConnectionPoint},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"color",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"reflection",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"hasTexture",{get:function(){return!!this._getTexture()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"reflectionColor",{get:function(){return this.color.isConnected?this.color.associatedVariableName:"vec3(1., 1., 1.)"},enumerable:!1,configurable:!0}),t.prototype._getTexture=function(){return this.texture?this.texture:this._scene.environmentTexture},t.prototype.prepareDefines=function(e,n,i){r.prototype.prepareDefines.call(this,e,n,i);var o=this._getTexture(),a=o&&o.getTextureMatrix;i.setValue("REFLECTION",a,!0),a&&(i.setValue(this._defineLODReflectionAlpha,o.lodLevelInAlpha,!0),i.setValue(this._defineLinearSpecularReflection,o.linearSpecularLOD,!0),i.setValue(this._defineOppositeZ,this._scene.useRightHandedSystem?!o.invertZ:o.invertZ,!0),i.setValue("SPHERICAL_HARMONICS",this.useSphericalHarmonics,!0),i.setValue("GAMMAREFLECTION",o.gammaSpace,!0),i.setValue("RGBDREFLECTION",o.isRGBD,!0),o&&o.coordinatesMode!==we.a.SKYBOX_MODE&&o.isCube&&(i.setValue("USESPHERICALFROMREFLECTIONMAP",!0),i.setValue("USEIRRADIANCEMAP",!1),this.forceIrradianceInFragment||this._scene.getEngine().getCaps().maxVaryingVectors<=8?i.setValue("USESPHERICALINVERTEX",!1):i.setValue("USESPHERICALINVERTEX",!0)))},t.prototype.bind=function(e,n,i,o){r.prototype.bind.call(this,e,n,i);var a=this._getTexture();if(a&&o){a.isCube?e.setTexture(this._cubeSamplerName,a):e.setTexture(this._2DSamplerName,a);var s=a.getSize().width;e.setFloat3(this._vReflectionMicrosurfaceInfosName,s,a.lodGenerationScale,a.lodGenerationOffset),e.setFloat2(this._vReflectionFilteringInfoName,s,$.a.Log2(s));var d=o._materialDefines,p=a.sphericalPolynomial;if(d.USESPHERICALFROMREFLECTIONMAP&&p)if(d.SPHERICAL_HARMONICS){var b=p.preScaledHarmonics;e.setVector3("vSphericalL00",b.l00),e.setVector3("vSphericalL1_1",b.l1_1),e.setVector3("vSphericalL10",b.l10),e.setVector3("vSphericalL11",b.l11),e.setVector3("vSphericalL2_2",b.l2_2),e.setVector3("vSphericalL2_1",b.l2_1),e.setVector3("vSphericalL20",b.l20),e.setVector3("vSphericalL21",b.l21),e.setVector3("vSphericalL22",b.l22)}else e.setFloat3("vSphericalX",p.x.x,p.x.y,p.x.z),e.setFloat3("vSphericalY",p.y.x,p.y.y,p.y.z),e.setFloat3("vSphericalZ",p.z.x,p.z.y,p.z.z),e.setFloat3("vSphericalXX_ZZ",p.xx.x-p.zz.x,p.xx.y-p.zz.y,p.xx.z-p.zz.z),e.setFloat3("vSphericalYY_ZZ",p.yy.x-p.zz.x,p.yy.y-p.zz.y,p.yy.z-p.zz.z),e.setFloat3("vSphericalZZ",p.zz.x,p.zz.y,p.zz.z),e.setFloat3("vSphericalXY",p.xy.x,p.xy.y,p.xy.z),e.setFloat3("vSphericalYZ",p.yz.x,p.yz.y,p.yz.z),e.setFloat3("vSphericalZX",p.zx.x,p.zx.y,p.zx.z)}},t.prototype.handleVertexSide=function(e){var n=r.prototype.handleVertexSide.call(this,e);e._emitFunctionFromInclude("harmonicsFunctions","//"+this.name,{replaceStrings:[{search:/uniform vec3 vSphericalL00;[\s\S]*?uniform vec3 vSphericalL22;/g,replace:""},{search:/uniform vec3 vSphericalX;[\s\S]*?uniform vec3 vSphericalZX;/g,replace:""}]});var i=e._getFreeVariableName("reflectionVector");return this._vEnvironmentIrradianceName=e._getFreeVariableName("vEnvironmentIrradiance"),e._emitVaryingFromString(this._vEnvironmentIrradianceName,"vec3","defined(USESPHERICALFROMREFLECTIONMAP) && defined(USESPHERICALINVERTEX)"),e._emitUniformFromString("vSphericalL00","vec3","SPHERICAL_HARMONICS"),e._emitUniformFromString("vSphericalL1_1","vec3","SPHERICAL_HARMONICS"),e._emitUniformFromString("vSphericalL10","vec3","SPHERICAL_HARMONICS"),e._emitUniformFromString("vSphericalL11","vec3","SPHERICAL_HARMONICS"),e._emitUniformFromString("vSphericalL2_2","vec3","SPHERICAL_HARMONICS"),e._emitUniformFromString("vSphericalL2_1","vec3","SPHERICAL_HARMONICS"),e._emitUniformFromString("vSphericalL20","vec3","SPHERICAL_HARMONICS"),e._emitUniformFromString("vSphericalL21","vec3","SPHERICAL_HARMONICS"),e._emitUniformFromString("vSphericalL22","vec3","SPHERICAL_HARMONICS"),e._emitUniformFromString("vSphericalX","vec3","SPHERICAL_HARMONICS",!0),e._emitUniformFromString("vSphericalY","vec3","SPHERICAL_HARMONICS",!0),e._emitUniformFromString("vSphericalZ","vec3","SPHERICAL_HARMONICS",!0),e._emitUniformFromString("vSphericalXX_ZZ","vec3","SPHERICAL_HARMONICS",!0),e._emitUniformFromString("vSphericalYY_ZZ","vec3","SPHERICAL_HARMONICS",!0),e._emitUniformFromString("vSphericalZZ","vec3","SPHERICAL_HARMONICS",!0),e._emitUniformFromString("vSphericalXY","vec3","SPHERICAL_HARMONICS",!0),e._emitUniformFromString("vSphericalYZ","vec3","SPHERICAL_HARMONICS",!0),e._emitUniformFromString("vSphericalZX","vec3","SPHERICAL_HARMONICS",!0),n+=`#if defined(USESPHERICALFROMREFLECTIONMAP) && defined(USESPHERICALINVERTEX)
-                vec3 `+i+" = vec3("+this._reflectionMatrixName+" * vec4(normalize("+this.worldNormal.associatedVariableName+`).xyz, 0)).xyz;
-                #ifdef `+this._defineOppositeZ+`
-                    `+i+`.z *= -1.0;
-                #endif
-                `+this._vEnvironmentIrradianceName+" = computeEnvironmentIrradiance("+i+`);
-            #endif\r
-`},t.prototype.getCode=function(e,n){var i="";this.handleFragmentSideInits(e),e._emitFunctionFromInclude("harmonicsFunctions","//"+this.name,{replaceStrings:[{search:/uniform vec3 vSphericalL00;[\s\S]*?uniform vec3 vSphericalL22;/g,replace:""},{search:/uniform vec3 vSphericalX;[\s\S]*?uniform vec3 vSphericalZX;/g,replace:""}]}),e._emitFunction("sampleReflection",`
-            #ifdef `+this._define3DName+`
-                #define sampleReflection(s, c) textureCube(s, c)
-            #else
-                #define sampleReflection(s, c) texture2D(s, c)
-            #endif\r
-`,"//"+this.name),e._emitFunction("sampleReflectionLod",`
-            #ifdef `+this._define3DName+`
-                #define sampleReflectionLod(s, c, l) textureCubeLodEXT(s, c, l)
-            #else
-                #define sampleReflectionLod(s, c, l) texture2DLodEXT(s, c, l)
-            #endif\r
-`,"//"+this.name);var o=`
-            vec3 computeReflectionCoordsPBR(vec4 worldPos, vec3 worldNormal) {
-                `+this.handleFragmentSideCodeReflectionCoords("worldNormal","worldPos",!0)+`
-                return `+this._reflectionVectorName+`;
-            }\r
-`;return e._emitFunction("computeReflectionCoordsPBR",o,"//"+this.name),this._vReflectionMicrosurfaceInfosName=e._getFreeVariableName("vReflectionMicrosurfaceInfos"),e._emitUniformFromString(this._vReflectionMicrosurfaceInfosName,"vec3"),this._vReflectionInfosName=e._getFreeVariableName("vReflectionInfos"),this._vReflectionFilteringInfoName=e._getFreeVariableName("vReflectionFilteringInfo"),e._emitUniformFromString(this._vReflectionFilteringInfoName,"vec2"),i+=`#ifdef REFLECTION
-            vec2 `+this._vReflectionInfosName+` = vec2(1., 0.);
-
-            reflectionOutParams reflectionOut;
-
-            reflectionBlock(
-                v_`+this.worldPosition.associatedVariableName+`.xyz,
-                `+n+`,
-                alphaG,
-                `+this._vReflectionMicrosurfaceInfosName+`,
-                `+this._vReflectionInfosName+`,
-                `+this.reflectionColor+`,
-            #ifdef ANISOTROPIC
-                anisotropicOut,
-            #endif
-            #if defined(`+this._defineLODReflectionAlpha+") && !defined("+this._defineSkyboxName+`)
-                NdotVUnclamped,
-            #endif
-            #ifdef `+this._defineLinearSpecularReflection+`
-                roughness,
-            #endif
-            #ifdef `+this._define3DName+`
-                `+this._cubeSamplerName+`,
-            #else
-                `+this._2DSamplerName+`,
-            #endif
-            #if defined(NORMAL) && defined(USESPHERICALINVERTEX)
-                `+this._vEnvironmentIrradianceName+`,
-            #endif
-            #ifdef USESPHERICALFROMREFLECTIONMAP
-                #if !defined(NORMAL) || !defined(USESPHERICALINVERTEX)
-                    `+this._reflectionMatrixName+`,
-                #endif
-            #endif
-            #ifdef USEIRRADIANCEMAP
-                irradianceSampler, // ** not handled **
-            #endif
-            #ifndef LODBASEDMICROSFURACE
-                #ifdef `+this._define3DName+`
-                    `+this._cubeSamplerName+`,
-                    `+this._cubeSamplerName+`,
-                #else
-                    `+this._2DSamplerName+`,
-                    `+this._2DSamplerName+`,
-                #endif
-            #endif
-            #ifdef REALTIME_FILTERING
-                `+this._vReflectionFilteringInfoName+`,
-            #endif
-                reflectionOut
-            );
-        #endif\r
-`},t.prototype._buildBlock=function(e){return this._scene=e.sharedData.scene,e.target!==xe.Fragment&&(this._defineLODReflectionAlpha=e._getFreeDefineName("LODINREFLECTIONALPHA"),this._defineLinearSpecularReflection=e._getFreeDefineName("LINEARSPECULARREFLECTION")),this},t.prototype._dumpPropertiesCode=function(){var e=r.prototype._dumpPropertiesCode.call(this);return this.texture&&(e+=this._codeVariableName+".texture.gammaSpace = "+this.texture.gammaSpace+`);\r
-`),e+=this._codeVariableName+".useSphericalHarmonics = "+this.useSphericalHarmonics+`;\r
-`,e+=this._codeVariableName+".forceIrradianceInFragment = "+this.forceIrradianceInFragment+`;\r
-`},t.prototype.serialize=function(){var e,n,i=r.prototype.serialize.call(this);return i.useSphericalHarmonics=this.useSphericalHarmonics,i.forceIrradianceInFragment=this.forceIrradianceInFragment,i.gammaSpace=(n=(e=this.texture)===null||e===void 0?void 0:e.gammaSpace)===null||n===void 0||n,i},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.useSphericalHarmonics=e.useSphericalHarmonics,this.forceIrradianceInFragment=e.forceIrradianceInFragment,this.texture&&(this.texture.gammaSpace=e.gammaSpace)},Object(c.c)([Vt("Spherical Harmonics",Lt.Boolean,"ADVANCED",{notifiers:{update:!0}})],t.prototype,"useSphericalHarmonics",void 0),Object(c.c)([Vt("Force irradiance in fragment",Lt.Boolean,"ADVANCED",{notifiers:{update:!0}})],t.prototype,"forceIrradianceInFragment",void 0),t}(dc);R.a.RegisteredTypes["BABYLON.ReflectionBlock"]=gc;var ba=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n.remapF0OnInterfaceChange=!0,n._isUnique=!0,n.registerInput("intensity",le.Float,!1,xe.Fragment),n.registerInput("roughness",le.Float,!0,xe.Fragment),n.registerInput("indexOfRefraction",le.Float,!0,xe.Fragment),n.registerInput("normalMapColor",le.Color3,!0,xe.Fragment),n.registerInput("uv",le.Vector2,!0,xe.Fragment),n.registerInput("tintColor",le.Color3,!0,xe.Fragment),n.registerInput("tintAtDistance",le.Float,!0,xe.Fragment),n.registerInput("tintThickness",le.Float,!0,xe.Fragment),n.registerInput("worldTangent",le.Vector4,!0),n.registerOutput("clearcoat",le.Object,xe.Fragment,new Zn("clearcoat",n,Tn.Output,t,"ClearCoatBlock")),n}return Object(c.d)(t,r),t.prototype.initialize=function(e){e._excludeVariableName("clearcoatOut"),e._excludeVariableName("vClearCoatParams"),e._excludeVariableName("vClearCoatTintParams"),e._excludeVariableName("vClearCoatRefractionParams"),e._excludeVariableName("vClearCoatTangentSpaceParams")},t.prototype.getClassName=function(){return"ClearCoatBlock"},Object.defineProperty(t.prototype,"intensity",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"roughness",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"indexOfRefraction",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"normalMapColor",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"uv",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"tintColor",{get:function(){return this._inputs[5]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"tintAtDistance",{get:function(){return this._inputs[6]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"tintThickness",{get:function(){return this._inputs[7]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldTangent",{get:function(){return this._inputs[8]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"clearcoat",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.intensity.isConnected){var n=new At("ClearCoat intensity",xe.Fragment,le.Float);n.value=1,n.output.connectTo(this.intensity)}},t.prototype.prepareDefines=function(e,n,i){r.prototype.prepareDefines.call(this,e,n,i),i.setValue("CLEARCOAT",!0),i.setValue("CLEARCOAT_TEXTURE",!1,!0),i.setValue("CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE",!0,!0),i.setValue("CLEARCOAT_TINT",this.tintColor.isConnected||this.tintThickness.isConnected||this.tintAtDistance.isConnected,!0),i.setValue("CLEARCOAT_BUMP",this.normalMapColor.isConnected,!0),i.setValue("CLEARCOAT_DEFAULTIOR",!this.indexOfRefraction.isConnected||this.indexOfRefraction.connectInputBlock.value===Ar._DefaultIndexOfRefraction,!0),i.setValue("CLEARCOAT_REMAP_F0",this.remapF0OnInterfaceChange,!0)},t.prototype.bind=function(e,n,i,o){var a,s;r.prototype.bind.call(this,e,n,i);var d=(s=(a=this.indexOfRefraction.connectInputBlock)===null||a===void 0?void 0:a.value)!==null&&s!==void 0?s:Ar._DefaultIndexOfRefraction,p=1-d,b=1+d,P=Math.pow(-p/b,2),O=1/d;e.setFloat4("vClearCoatRefractionParams",P,O,p,b);var B=this.clearcoat.hasEndpoints?this.clearcoat.endpoints[0].ownerBlock:null,F=B?.perturbedNormal.isConnected?B.perturbedNormal.connectedPoint.ownerBlock:null;this._scene._mirroredCameraPosition?e.setFloat2("vClearCoatTangentSpaceParams",F?.invertX?1:-1,F?.invertY?1:-1):e.setFloat2("vClearCoatTangentSpaceParams",F?.invertX?-1:1,F?.invertY?-1:1)},t.prototype._generateTBNSpace=function(e,n,i){var o="",a="//"+this.name,s=this.worldTangent;e._emitExtension("derivatives","#extension GL_OES_standard_derivatives : enable");var d={search:/defined\(TANGENT\)/g,replace:s.isConnected?"defined(TANGENT)":"defined(IGNORE)"};return s.isConnected&&(o+="vec3 tbnNormal = normalize("+i+`.xyz);\r
-`,o+="vec3 tbnTangent = normalize("+s.associatedVariableName+`.xyz);\r
-`,o+=`vec3 tbnBitangent = cross(tbnNormal, tbnTangent);\r
-`,o+=`mat3 vTBN = mat3(tbnTangent, tbnBitangent, tbnNormal);\r
-`),e._emitFunctionFromInclude("bumpFragmentMainFunctions",a,{replaceStrings:[d]}),o},t.GetCode=function(e,n,i,o,a,s,d){var p="",b=n?.intensity.isConnected?n.intensity.associatedVariableName:"1.",P=n?.roughness.isConnected?n.roughness.associatedVariableName:"0.",O=n?.normalMapColor.isConnected?n.normalMapColor.associatedVariableName:"vec3(0.)",B=n?.uv.isConnected?n.uv.associatedVariableName:"vec2(0.)",F=n?.tintColor.isConnected?n.tintColor.associatedVariableName:"vec3(1.)",z=n?.tintThickness.isConnected?n.tintThickness.associatedVariableName:"1.",J=n?.tintAtDistance.isConnected?n.tintAtDistance.associatedVariableName:"1.";return n&&(e._emitUniformFromString("vClearCoatRefractionParams","vec4"),e._emitUniformFromString("vClearCoatTangentSpaceParams","vec2")),a&&n&&(p+=n._generateTBNSpace(e,o,d),s=n.worldTangent.isConnected),p+=`clearcoatOutParams clearcoatOut;
-
-        #ifdef CLEARCOAT
-            vec2 vClearCoatParams = vec2(`+b+", "+P+`);
-            vec4 vClearCoatTintParams = vec4(`+F+", "+z+`);
-
-            clearcoatBlock(
-                `+o+`.xyz,
-                geometricNormalW,
-                viewDirectionW,
-                vClearCoatParams,
-                specularEnvironmentR0,
-            #ifdef CLEARCOAT_TEXTURE
-                vec2(0.),
-            #endif
-            #ifdef CLEARCOAT_TINT
-                vClearCoatTintParams,
-                `+J+`,
-                vClearCoatRefractionParams,
-                #ifdef CLEARCOAT_TINT_TEXTURE
-                    vec4(0.),
-                #endif
-            #endif
-            #ifdef CLEARCOAT_BUMP
-                vec2(0., 1.),
-                vec4(`+O+`, 0.),
-                `+B+`,
-                #if defined(`+(s?"TANGENT":"IGNORE")+`) && defined(NORMAL)
-                    vTBN,
-                #else
-                    vClearCoatTangentSpaceParams,
-                #endif
-                #ifdef OBJECTSPACE_NORMALMAP
-                    normalMatrix,
-                #endif
-            #endif
-            #if defined(FORCENORMALFORWARD) && defined(NORMAL)
-                faceNormal,
-            #endif
-            #ifdef REFLECTION
-                `+i?._vReflectionMicrosurfaceInfosName+`,
-                `+i?._vReflectionInfosName+`,
-                `+i?.reflectionColor+`,
-                vLightingIntensity,
-                #ifdef `+i?._define3DName+`
-                    `+i?._cubeSamplerName+`,
-                #else
-                    `+i?._2DSamplerName+`,
-                #endif
-                #ifndef LODBASEDMICROSFURACE
-                    #ifdef `+i?._define3DName+`
-                        `+i?._cubeSamplerName+`,
-                        `+i?._cubeSamplerName+`,
-                    #else
-                        `+i?._2DSamplerName+`,
-                        `+i?._2DSamplerName+`,
-                    #endif
-                #endif
-            #endif
-            #if defined(ENVIRONMENTBRDF) && !defined(`+i?._defineSkyboxName+`)
-                #ifdef RADIANCEOCCLUSION
-                    ambientMonochrome,
-                #endif
-            #endif
-                clearcoatOut
-            );
-        #else
-            clearcoatOut.specularEnvironmentR0 = specularEnvironmentR0;
-        #endif\r
-`},t.prototype._buildBlock=function(e){return this._scene=e.sharedData.scene,e.target===xe.Fragment&&(e.sharedData.bindableBlocks.push(this),e.sharedData.blocksWithDefines.push(this)),this},t.prototype._dumpPropertiesCode=function(){var e="";return e+=this._codeVariableName+".remapF0OnInterfaceChange = "+this.remapF0OnInterfaceChange+`;\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.remapF0OnInterfaceChange=this.remapF0OnInterfaceChange,e},t.prototype._deserialize=function(e,n,i){var o;r.prototype._deserialize.call(this,e,n,i),this.remapF0OnInterfaceChange=(o=e.remapF0OnInterfaceChange)===null||o===void 0||o},Object(c.c)([Vt("Remap F0 on interface change",Lt.Boolean,"ADVANCED")],t.prototype,"remapF0OnInterfaceChange",void 0),t}(pt);R.a.RegisteredTypes["BABYLON.ClearCoatBlock"]=ba;var vc=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n.linkRefractionWithTransparency=!1,n.invertRefractionY=!1,n._isUnique=!0,n.registerInput("intensity",le.Float,!1,xe.Fragment),n.registerInput("tintAtDistance",le.Float,!0,xe.Fragment),n.registerOutput("refraction",le.Object,xe.Fragment,new Zn("refraction",n,Tn.Output,t,"RefractionBlock")),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"RefractionBlock"},Object.defineProperty(t.prototype,"intensity",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"tintAtDistance",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"view",{get:function(){return this.viewConnectionPoint},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"refraction",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"hasTexture",{get:function(){return!!this._getTexture()},enumerable:!1,configurable:!0}),t.prototype._getTexture=function(){return this.texture?this.texture:this._scene.environmentTexture},t.prototype.autoConfigure=function(e){if(!this.intensity.isConnected){var n=new At("Refraction intensity",xe.Fragment,le.Float);n.value=1,n.output.connectTo(this.intensity)}if(this.view&&!this.view.isConnected){var i=e.getInputBlockByPredicate(function(o){return o.systemValue===bt.View});i||(i=new At("view")).setAsSystemValue(bt.View),i.output.connectTo(this.view)}},t.prototype.prepareDefines=function(e,n,i){r.prototype.prepareDefines.call(this,e,n,i);var o=this._getTexture(),a=o&&o.getTextureMatrix;i.setValue("SS_REFRACTION",a,!0),a&&(i.setValue(this._define3DName,o.isCube,!0),i.setValue(this._defineLODRefractionAlpha,o.lodLevelInAlpha,!0),i.setValue(this._defineLinearSpecularRefraction,o.linearSpecularLOD,!0),i.setValue(this._defineOppositeZ,this._scene.useRightHandedSystem?!o.invertZ:o.invertZ,!0),i.setValue("SS_LINKREFRACTIONTOTRANSPARENCY",this.linkRefractionWithTransparency,!0),i.setValue("SS_GAMMAREFRACTION",o.gammaSpace,!0),i.setValue("SS_RGBDREFRACTION",o.isRGBD,!0))},t.prototype.isReady=function(){var e=this._getTexture();return!(e&&!e.isReadyOrNotBlocking())},t.prototype.bind=function(e,n,i,o){var a,s;r.prototype.bind.call(this,e,n,i);var d=this._getTexture();if(d){d.isCube?e.setTexture(this._cubeSamplerName,d):e.setTexture(this._2DSamplerName,d),e.setMatrix(this._refractionMatrixName,d.getReflectionTextureMatrix());var p=1;d.isCube||d.depth&&(p=d.depth);var b=(s=(a=this.indexOfRefractionConnectionPoint.connectInputBlock)===null||a===void 0?void 0:a.value)!==null&&s!==void 0?s:1.5;e.setFloat4(this._vRefractionInfosName,d.level,1/b,p,this.invertRefractionY?-1:1),e.setFloat3(this._vRefractionMicrosurfaceInfosName,d.getSize().width,d.lodGenerationScale,d.lodGenerationOffset);var P=d.getSize().width;e.setFloat2(this._vRefractionFilteringInfoName,P,$.a.Log2(P))}},t.prototype.getCode=function(e){return e.sharedData.blockingBlocks.push(this),e.sharedData.textureBlocks.push(this),this._cubeSamplerName=e._getFreeVariableName(this.name+"CubeSampler"),e.samplers.push(this._cubeSamplerName),this._2DSamplerName=e._getFreeVariableName(this.name+"2DSampler"),e.samplers.push(this._2DSamplerName),this._define3DName=e._getFreeDefineName("SS_REFRACTIONMAP_3D"),e._samplerDeclaration+="#ifdef "+this._define3DName+`\r
-`,e._samplerDeclaration+="uniform samplerCube "+this._cubeSamplerName+`;\r
-`,e._samplerDeclaration+=`#else\r
-`,e._samplerDeclaration+="uniform sampler2D "+this._2DSamplerName+`;\r
-`,e._samplerDeclaration+=`#endif\r
-`,e.sharedData.blocksWithDefines.push(this),e.sharedData.bindableBlocks.push(this),this._defineLODRefractionAlpha=e._getFreeDefineName("SS_LODINREFRACTIONALPHA"),this._defineLinearSpecularRefraction=e._getFreeDefineName("SS_LINEARSPECULARREFRACTION"),this._defineOppositeZ=e._getFreeDefineName("SS_REFRACTIONMAP_OPPOSITEZ"),this._refractionMatrixName=e._getFreeVariableName("refractionMatrix"),e._emitUniformFromString(this._refractionMatrixName,"mat4"),e._emitFunction("sampleRefraction",`
-            #ifdef `+this._define3DName+`
-                #define sampleRefraction(s, c) textureCube(s, c)
-            #else
-                #define sampleRefraction(s, c) texture2D(s, c)
-            #endif\r
-`,"//"+this.name),e._emitFunction("sampleRefractionLod",`
-            #ifdef `+this._define3DName+`
-                #define sampleRefractionLod(s, c, l) textureCubeLodEXT(s, c, l)
-            #else
-                #define sampleRefractionLod(s, c, l) texture2DLodEXT(s, c, l)
-            #endif\r
-`,"//"+this.name),this._vRefractionMicrosurfaceInfosName=e._getFreeVariableName("vRefractionMicrosurfaceInfos"),e._emitUniformFromString(this._vRefractionMicrosurfaceInfosName,"vec3"),this._vRefractionInfosName=e._getFreeVariableName("vRefractionInfos"),e._emitUniformFromString(this._vRefractionInfosName,"vec4"),this._vRefractionFilteringInfoName=e._getFreeVariableName("vRefractionFilteringInfo"),e._emitUniformFromString(this._vRefractionFilteringInfoName,"vec2"),""},t.prototype._buildBlock=function(e){return this._scene=e.sharedData.scene,this},t.prototype._dumpPropertiesCode=function(){var e=r.prototype._dumpPropertiesCode.call(this);return this.texture&&(e=this.texture.isCube?this._codeVariableName+'.texture = new BABYLON.CubeTexture("'+this.texture.name+`");\r
-`:this._codeVariableName+'.texture = new BABYLON.Texture("'+this.texture.name+`");\r
-`,e+=this._codeVariableName+".texture.coordinatesMode = "+this.texture.coordinatesMode+`;\r
-`),e+=this._codeVariableName+".linkRefractionWithTransparency = "+this.linkRefractionWithTransparency+`;\r
-`,e+=this._codeVariableName+".invertRefractionY = "+this.invertRefractionY+`;\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return this.texture&&(e.texture=this.texture.serialize()),e.linkRefractionWithTransparency=this.linkRefractionWithTransparency,e.invertRefractionY=this.invertRefractionY,e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),e.texture&&(i=e.texture.url.indexOf("data:")===0?"":i,e.texture.isCube?this.texture=ai.Parse(e.texture,n,i):this.texture=we.a.Parse(e.texture,n,i)),this.linkRefractionWithTransparency=e.linkRefractionWithTransparency,this.invertRefractionY=e.invertRefractionY},Object(c.c)([Vt("Link refraction to transparency",Lt.Boolean,"ADVANCED",{notifiers:{update:!0}})],t.prototype,"linkRefractionWithTransparency",void 0),Object(c.c)([Vt("Invert refraction Y",Lt.Boolean,"ADVANCED",{notifiers:{update:!0}})],t.prototype,"invertRefractionY",void 0),t}(pt);R.a.RegisteredTypes["BABYLON.RefractionBlock"]=vc;var ya=function(r){function t(e){var n=r.call(this,e,xe.Fragment)||this;return n._isUnique=!0,n.registerInput("thickness",le.Float,!1,xe.Fragment),n.registerInput("tintColor",le.Color3,!0,xe.Fragment),n.registerInput("translucencyIntensity",le.Float,!0,xe.Fragment),n.registerInput("translucencyDiffusionDist",le.Color3,!0,xe.Fragment),n.registerInput("refraction",le.Object,!0,xe.Fragment,new Zn("refraction",n,Tn.Input,vc,"RefractionBlock")),n.registerOutput("subsurface",le.Object,xe.Fragment,new Zn("subsurface",n,Tn.Output,t,"SubSurfaceBlock")),n}return Object(c.d)(t,r),t.prototype.initialize=function(e){e._excludeVariableName("subSurfaceOut"),e._excludeVariableName("vThicknessParam"),e._excludeVariableName("vTintColor"),e._excludeVariableName("vSubSurfaceIntensity")},t.prototype.getClassName=function(){return"SubSurfaceBlock"},Object.defineProperty(t.prototype,"thickness",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"tintColor",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"translucencyIntensity",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"translucencyDiffusionDist",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"refraction",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"subsurface",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.thickness.isConnected){var n=new At("SubSurface thickness",xe.Fragment,le.Float);n.value=0,n.output.connectTo(this.thickness)}},t.prototype.prepareDefines=function(e,n,i){r.prototype.prepareDefines.call(this,e,n,i);var o=this.translucencyDiffusionDist.isConnected||this.translucencyIntensity.isConnected;i.setValue("SUBSURFACE",o||this.refraction.isConnected,!0),i.setValue("SS_TRANSLUCENCY",o,!0),i.setValue("SS_THICKNESSANDMASK_TEXTURE",!1,!0),i.setValue("SS_MASK_FROM_THICKNESS_TEXTURE",!1,!0),i.setValue("SS_MASK_FROM_THICKNESS_TEXTURE_GLTF",!1,!0)},t.GetCode=function(e,n,i,o){var a,s,d,p,b,P,O,B,F,z,J,ie,se,ce,ue,fe,ve="",Te=n?.thickness.isConnected?n.thickness.associatedVariableName:"0.",Re=n?.tintColor.isConnected?n.tintColor.associatedVariableName:"vec3(1.)",Ae=n?.translucencyIntensity.isConnected?n?.translucencyIntensity.associatedVariableName:"1.",Ee=n?.translucencyDiffusionDist.isConnected?n?.translucencyDiffusionDist.associatedVariableName:"vec3(1.)",Se=n?.refraction.isConnected?(a=n?.refraction.connectedPoint)===null||a===void 0?void 0:a.ownerBlock:null,Le=Se?.tintAtDistance.isConnected?Se.tintAtDistance.associatedVariableName:"1.",Ce=Se?.intensity.isConnected?Se.intensity.associatedVariableName:"1.",Ne=Se?.view.isConnected?Se.view.associatedVariableName:"";return ve+=(s=Se?.getCode(e))!==null&&s!==void 0?s:"",ve+=`subSurfaceOutParams subSurfaceOut;
-
-        #ifdef SUBSURFACE
-            vec2 vThicknessParam = vec2(0., `+Te+`);
-            vec4 vTintColor = vec4(`+Re+", "+Le+`);
-            vec3 vSubSurfaceIntensity = vec3(`+Ce+", "+Ae+`, 0.);
-
-            subSurfaceBlock(
-                vSubSurfaceIntensity,
-                vThicknessParam,
-                vTintColor,
-                normalW,
-                specularEnvironmentReflectance,
-            #ifdef SS_THICKNESSANDMASK_TEXTURE
-                vec4(0.),
-            #endif
-            #ifdef REFLECTION
-                #ifdef SS_TRANSLUCENCY
-                    `+i?._reflectionMatrixName+`,
-                    #ifdef USESPHERICALFROMREFLECTIONMAP
-                        #if !defined(NORMAL) || !defined(USESPHERICALINVERTEX)
-                            reflectionOut.irradianceVector,
-                        #endif
-                        #if defined(REALTIME_FILTERING)
-                            `+i?._cubeSamplerName+`,
-                            `+i?._vReflectionFilteringInfoName+`,
-                        #endif
-                        #endif
-                    #ifdef USEIRRADIANCEMAP
-                        irradianceSampler,
-                    #endif
-                #endif
-            #endif
-            #ifdef SS_REFRACTION
-                `+o+`.xyz,
-                viewDirectionW,
-                `+Ne+`,
-                surfaceAlbedo,
-                `+((d=Se?._vRefractionInfosName)!==null&&d!==void 0?d:"")+`,
-                `+((p=Se?._refractionMatrixName)!==null&&p!==void 0?p:"")+`,
-                `+((b=Se?._vRefractionMicrosurfaceInfosName)!==null&&b!==void 0?b:"")+`,
-                vLightingIntensity,
-                #ifdef SS_LINKREFRACTIONTOTRANSPARENCY
-                    alpha,
-                #endif
-                #ifdef `+((P=Se?._defineLODRefractionAlpha)!==null&&P!==void 0?P:"IGNORE")+`
-                    NdotVUnclamped,
-                #endif
-                #ifdef `+((O=Se?._defineLinearSpecularRefraction)!==null&&O!==void 0?O:"IGNORE")+`
-                    roughness,
-                #else
-                    alphaG,
-                #endif
-                #ifdef `+((B=Se?._define3DName)!==null&&B!==void 0?B:"IGNORE")+`
-                    `+((F=Se?._cubeSamplerName)!==null&&F!==void 0?F:"")+`,
-                #else
-                    `+((z=Se?._2DSamplerName)!==null&&z!==void 0?z:"")+`,
-                #endif
-                #ifndef LODBASEDMICROSFURACE
-                    #ifdef `+((J=Se?._define3DName)!==null&&J!==void 0?J:"IGNORE")+`
-                        `+((ie=Se?._cubeSamplerName)!==null&&ie!==void 0?ie:"")+`,
-                        `+((se=Se?._cubeSamplerName)!==null&&se!==void 0?se:"")+`,
-                    #else
-                        `+((ce=Se?._2DSamplerName)!==null&&ce!==void 0?ce:"")+`,
-                        `+((ue=Se?._2DSamplerName)!==null&&ue!==void 0?ue:"")+`,
-                    #endif
-                #endif
-                #ifdef ANISOTROPIC
-                    anisotropicOut,
-                #endif
-                #ifdef REALTIME_FILTERING
-                    `+((fe=Se?._vRefractionFilteringInfoName)!==null&&fe!==void 0?fe:"")+`,
-                #endif
-            #endif
-            #ifdef SS_TRANSLUCENCY
-                `+Ee+`,
-            #endif
-                subSurfaceOut
-            );
-
-            #ifdef SS_REFRACTION
-                surfaceAlbedo = subSurfaceOut.surfaceAlbedo;
-                #ifdef SS_LINKREFRACTIONTOTRANSPARENCY
-                    alpha = subSurfaceOut.alpha;
-                #endif
-            #endif
-        #else
-            subSurfaceOut.specularEnvironmentReflectance = specularEnvironmentReflectance;
-        #endif\r
-`},t.prototype._buildBlock=function(e){return e.target===xe.Fragment&&e.sharedData.blocksWithDefines.push(this),this},t}(pt);R.a.RegisteredTypes["BABYLON.SubSurfaceBlock"]=ya;var hm={ambientClr:["finalAmbient",""],diffuseDir:["finalDiffuse",""],specularDir:["finalSpecularScaled","!defined(UNLIT) && defined(SPECULARTERM)"],clearcoatDir:["finalClearCoatScaled","!defined(UNLIT) && defined(CLEARCOAT)"],sheenDir:["finalSheenScaled","!defined(UNLIT) && defined(SHEEN)"],diffuseInd:["finalIrradiance","!defined(UNLIT) && defined(REFLECTION)"],specularInd:["finalRadianceScaled","!defined(UNLIT) && defined(REFLECTION)"],clearcoatInd:["clearcoatOut.finalClearCoatRadianceScaled","!defined(UNLIT) && defined(REFLECTION) && defined(CLEARCOAT)"],sheenInd:["sheenOut.finalSheenRadianceScaled","!defined(UNLIT) && defined(REFLECTION) && defined(SHEEN) && defined(ENVIRONMENTBRDF)"],refraction:["subSurfaceOut.finalRefraction","!defined(UNLIT) && defined(SS_REFRACTION)"],lighting:["finalColor.rgb",""],shadow:["shadow",""],alpha:["alpha",""]},ld=function(r){function t(e){var n=r.call(this,e,xe.VertexAndFragment)||this;return n._environmentBRDFTexture=null,n._metallicReflectanceColor=M.a.White(),n._metallicF0Factor=1,n.directIntensity=1,n.environmentIntensity=1,n.specularIntensity=1,n.lightFalloff=0,n.useAlphaTest=!1,n.alphaTestCutoff=.5,n.useAlphaBlending=!1,n.useRadianceOverAlpha=!0,n.useSpecularOverAlpha=!0,n.enableSpecularAntiAliasing=!1,n.realTimeFiltering=!1,n.realTimeFilteringQuality=h.a.TEXTURE_FILTERING_QUALITY_LOW,n.useEnergyConservation=!0,n.useRadianceOcclusion=!0,n.useHorizonOcclusion=!0,n.unlit=!1,n.forceNormalForward=!1,n.debugMode=0,n.debugLimit=0,n.debugFactor=1,n._isUnique=!0,n.registerInput("worldPosition",le.Vector4,!1,xe.Vertex),n.registerInput("worldNormal",le.Vector4,!1,xe.Fragment),n.registerInput("view",le.Matrix,!1),n.registerInput("cameraPosition",le.Vector3,!1,xe.Fragment),n.registerInput("perturbedNormal",le.Vector4,!0,xe.Fragment),n.registerInput("baseColor",le.Color3,!0,xe.Fragment),n.registerInput("metallic",le.Float,!1,xe.Fragment),n.registerInput("roughness",le.Float,!1,xe.Fragment),n.registerInput("ambientOcc",le.Float,!0,xe.Fragment),n.registerInput("opacity",le.Float,!0,xe.Fragment),n.registerInput("indexOfRefraction",le.Float,!0,xe.Fragment),n.registerInput("ambientColor",le.Color3,!0,xe.Fragment),n.registerInput("reflection",le.Object,!0,xe.Fragment,new Zn("reflection",n,Tn.Input,gc,"ReflectionBlock")),n.registerInput("clearcoat",le.Object,!0,xe.Fragment,new Zn("clearcoat",n,Tn.Input,ba,"ClearCoatBlock")),n.registerInput("sheen",le.Object,!0,xe.Fragment,new Zn("sheen",n,Tn.Input,_c,"SheenBlock")),n.registerInput("subsurface",le.Object,!0,xe.Fragment,new Zn("subsurface",n,Tn.Input,ya,"SubSurfaceBlock")),n.registerInput("anisotropy",le.Object,!0,xe.Fragment,new Zn("anisotropy",n,Tn.Input,mc,"AnisotropyBlock")),n.registerOutput("ambientClr",le.Color3,xe.Fragment),n.registerOutput("diffuseDir",le.Color3,xe.Fragment),n.registerOutput("specularDir",le.Color3,xe.Fragment),n.registerOutput("clearcoatDir",le.Color3,xe.Fragment),n.registerOutput("sheenDir",le.Color3,xe.Fragment),n.registerOutput("diffuseInd",le.Color3,xe.Fragment),n.registerOutput("specularInd",le.Color3,xe.Fragment),n.registerOutput("clearcoatInd",le.Color3,xe.Fragment),n.registerOutput("sheenInd",le.Color3,xe.Fragment),n.registerOutput("refraction",le.Color3,xe.Fragment),n.registerOutput("lighting",le.Color3,xe.Fragment),n.registerOutput("shadow",le.Float,xe.Fragment),n.registerOutput("alpha",le.Float,xe.Fragment),n}return Object(c.d)(t,r),t.prototype.initialize=function(e){e._excludeVariableName("vLightingIntensity"),e._excludeVariableName("geometricNormalW"),e._excludeVariableName("normalW"),e._excludeVariableName("faceNormal"),e._excludeVariableName("albedoOpacityOut"),e._excludeVariableName("surfaceAlbedo"),e._excludeVariableName("alpha"),e._excludeVariableName("aoOut"),e._excludeVariableName("baseColor"),e._excludeVariableName("reflectivityOut"),e._excludeVariableName("microSurface"),e._excludeVariableName("roughness"),e._excludeVariableName("NdotVUnclamped"),e._excludeVariableName("NdotV"),e._excludeVariableName("alphaG"),e._excludeVariableName("AARoughnessFactors"),e._excludeVariableName("environmentBrdf"),e._excludeVariableName("ambientMonochrome"),e._excludeVariableName("seo"),e._excludeVariableName("eho"),e._excludeVariableName("environmentRadiance"),e._excludeVariableName("irradianceVector"),e._excludeVariableName("environmentIrradiance"),e._excludeVariableName("diffuseBase"),e._excludeVariableName("specularBase"),e._excludeVariableName("preInfo"),e._excludeVariableName("info"),e._excludeVariableName("shadow"),e._excludeVariableName("finalDiffuse"),e._excludeVariableName("finalAmbient"),e._excludeVariableName("ambientOcclusionForDirectDiffuse"),e._excludeVariableName("finalColor"),e._excludeVariableName("vClipSpacePosition"),e._excludeVariableName("vDebugMode")},t.prototype.getClassName=function(){return"PBRMetallicRoughnessBlock"},Object.defineProperty(t.prototype,"worldPosition",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldNormal",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"view",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraPosition",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"perturbedNormal",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"baseColor",{get:function(){return this._inputs[5]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"metallic",{get:function(){return this._inputs[6]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"roughness",{get:function(){return this._inputs[7]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"ambientOcc",{get:function(){return this._inputs[8]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"opacity",{get:function(){return this._inputs[9]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"indexOfRefraction",{get:function(){return this._inputs[10]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"ambientColor",{get:function(){return this._inputs[11]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"reflection",{get:function(){return this._inputs[12]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"clearcoat",{get:function(){return this._inputs[13]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"sheen",{get:function(){return this._inputs[14]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"subsurface",{get:function(){return this._inputs[15]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"anisotropy",{get:function(){return this._inputs[16]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"ambientClr",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"diffuseDir",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"specularDir",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"clearcoatDir",{get:function(){return this._outputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"sheenDir",{get:function(){return this._outputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"diffuseIndirect",{get:function(){return this._outputs[5]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"specularIndirect",{get:function(){return this._outputs[6]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"clearcoatIndirect",{get:function(){return this._outputs[7]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"sheenIndirect",{get:function(){return this._outputs[8]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"refraction",{get:function(){return this._outputs[9]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"lighting",{get:function(){return this._outputs[10]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"shadow",{get:function(){return this._outputs[11]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"alpha",{get:function(){return this._outputs[12]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.cameraPosition.isConnected){var n=e.getInputBlockByPredicate(function(o){return o.systemValue===bt.CameraPosition});n||(n=new At("cameraPosition")).setAsSystemValue(bt.CameraPosition),n.output.connectTo(this.cameraPosition)}if(!this.view.isConnected){var i=e.getInputBlockByPredicate(function(o){return o.systemValue===bt.View});i||(i=new At("view")).setAsSystemValue(bt.View),i.output.connectTo(this.view)}},t.prototype.prepareDefines=function(e,n,i){i.setValue("PBR",!0),i.setValue("METALLICWORKFLOW",!0),i.setValue("DEBUGMODE",this.debugMode,!0),i.setValue("NORMALXYSCALE",!0),i.setValue("BUMP",this.perturbedNormal.isConnected,!0),i.setValue("LODBASEDMICROSFURACE",this._scene.getEngine().getCaps().textureLOD),i.setValue("ALBEDO",!1,!0),i.setValue("OPACITY",this.opacity.isConnected,!0),i.setValue("AMBIENT",!0,!0),i.setValue("AMBIENTINGRAYSCALE",!1,!0),i.setValue("REFLECTIVITY",!1,!0),i.setValue("AOSTOREINMETALMAPRED",!1,!0),i.setValue("METALLNESSSTOREINMETALMAPBLUE",!1,!0),i.setValue("ROUGHNESSSTOREINMETALMAPALPHA",!1,!0),i.setValue("ROUGHNESSSTOREINMETALMAPGREEN",!1,!0),this.lightFalloff===_n.LIGHTFALLOFF_STANDARD?(i.setValue("USEPHYSICALLIGHTFALLOFF",!1),i.setValue("USEGLTFLIGHTFALLOFF",!1)):this.lightFalloff===_n.LIGHTFALLOFF_GLTF?(i.setValue("USEPHYSICALLIGHTFALLOFF",!1),i.setValue("USEGLTFLIGHTFALLOFF",!0)):(i.setValue("USEPHYSICALLIGHTFALLOFF",!0),i.setValue("USEGLTFLIGHTFALLOFF",!1));var o=this.alphaTestCutoff.toString();if(i.setValue("ALPHABLEND",this.useAlphaBlending,!0),i.setValue("ALPHAFROMALBEDO",!1,!0),i.setValue("ALPHATEST",this.useAlphaTest,!0),i.setValue("ALPHATESTVALUE",o.indexOf(".")<0?o+".":o,!0),i.setValue("OPACITYRGB",!1,!0),i.setValue("RADIANCEOVERALPHA",this.useRadianceOverAlpha,!0),i.setValue("SPECULAROVERALPHA",this.useSpecularOverAlpha,!0),i.setValue("SPECULARAA",this._scene.getEngine().getCaps().standardDerivatives&&this.enableSpecularAntiAliasing,!0),i.setValue("REALTIME_FILTERING",this.realTimeFiltering,!0),this._scene.getEngine().webGLVersion>1?i.setValue("NUM_SAMPLES",this.realTimeFilteringQuality+"u",!0):i.setValue("NUM_SAMPLES",""+this.realTimeFilteringQuality,!0),i.setValue("BRDF_V_HEIGHT_CORRELATED",!0),i.setValue("MS_BRDF_ENERGY_CONSERVATION",this.useEnergyConservation,!0),i.setValue("RADIANCEOCCLUSION",this.useRadianceOcclusion,!0),i.setValue("HORIZONOCCLUSION",this.useHorizonOcclusion,!0),i.setValue("UNLIT",this.unlit,!0),i.setValue("FORCENORMALFORWARD",this.forceNormalForward,!0),this._environmentBRDFTexture&&ht.a.ReflectionTextureEnabled?(i.setValue("ENVIRONMENTBRDF",!0),i.setValue("ENVIRONMENTBRDF_RGBD",this._environmentBRDFTexture.isRGBD,!0)):(i.setValue("ENVIRONMENTBRDF",!1),i.setValue("ENVIRONMENTBRDF_RGBD",!1)),i._areLightsDirty){var a=e.getScene();if(this.light){var s={needNormals:!1,needRebuild:!1,lightmapMode:!1,shadowEnabled:!1,specularEnabled:!1};et.a.PrepareDefinesForLight(a,e,this.light,this._lightId,i,!0,s),s.needRebuild&&i.rebuild()}else et.a.PrepareDefinesForLights(a,e,i,!0,n.maxSimultaneousLights),i._needNormals=!0,et.a.PrepareDefinesForMultiview(a,i)}},t.prototype.updateUniformsAndSamples=function(e,n,i,o){for(var a=0;a<n.maxSimultaneousLights&&i["LIGHT"+a];a++){var s=e.uniforms.indexOf("vLightData"+a)>=0;et.a.PrepareUniformsAndSamplersForLight(a,e.uniforms,e.samplers,i["PROJECTEDLIGHTTEXTURE"+a],o,s)}},t.prototype.bind=function(e,n,i){var o,a;if(i){var s=i.getScene();this.light?et.a.BindLight(this.light,this._lightId,s,e,!0):et.a.BindLights(s,i,e,!0,n.maxSimultaneousLights),e.setTexture(this._environmentBrdfSamplerName,this._environmentBRDFTexture),e.setFloat2("vDebugMode",this.debugLimit,this.debugFactor);var d=this._scene.ambientColor;d&&e.setColor3("ambientFromScene",d);var p=s.useRightHandedSystem===(s._mirroredCameraPosition!=null);e.setFloat(this._invertNormalName,p?-1:1),e.setFloat4("vLightingIntensity",this.directIntensity,1,this.environmentIntensity*this._scene.environmentIntensity,this.specularIntensity);var b=(a=(o=this.indexOfRefraction.connectInputBlock)===null||o===void 0?void 0:o.value)!==null&&a!==void 0?a:1.5,P=Math.pow((b-1)/(b+1),2);this._metallicReflectanceColor.scaleToRef(P*this._metallicF0Factor,M.c.Color3[0]);var O=this._metallicF0Factor;e.setColor4(this._vMetallicReflectanceFactorsName,M.c.Color3[0],O)}},t.prototype._injectVertexCode=function(e){var n,i,o=this.worldPosition,a="//"+this.name;this.light?(this._lightId=(e.counters.lightCounter!==void 0?e.counters.lightCounter:-1)+1,e.counters.lightCounter=this._lightId,e._emitFunctionFromInclude(e.supportUniformBuffers?"lightUboDeclaration":"lightFragmentDeclaration",a,{replaceStrings:[{search:/{X}/g,replace:this._lightId.toString()}]},this._lightId.toString())):(e._emitFunctionFromInclude(e.supportUniformBuffers?"lightUboDeclaration":"lightFragmentDeclaration",a,{repeatKey:"maxSimultaneousLights"}),this._lightId=0,e.sharedData.dynamicUniformBlocks.push(this));var s="v_"+o.associatedVariableName;e._emitVaryingFromString(s,"vec4")&&(e.compilationString+=s+" = "+o.associatedVariableName+`;\r
-`);var d=this.reflection.isConnected?(n=this.reflection.connectedPoint)===null||n===void 0?void 0:n.ownerBlock:null;d&&(d.viewConnectionPoint=this.view),e.compilationString+=(i=d?.handleVertexSide(e))!==null&&i!==void 0?i:"",e._emitUniformFromString("vDebugMode","vec2","defined(IGNORE) || DEBUGMODE > 0"),e._emitUniformFromString("ambientFromScene","vec3"),e._emitVaryingFromString("vClipSpacePosition","vec4","defined(IGNORE) || DEBUGMODE > 0")&&(e._injectAtEnd+=`#if DEBUGMODE > 0\r
-`,e._injectAtEnd+=`vClipSpacePosition = gl_Position;\r
-`,e._injectAtEnd+=`#endif\r
-`),this.light?e.compilationString+=e._emitCodeFromInclude("shadowsVertex",a,{replaceStrings:[{search:/{X}/g,replace:this._lightId.toString()},{search:/worldPos/g,replace:o.associatedVariableName}]}):(e.compilationString+="vec4 worldPos = "+o.associatedVariableName+`;\r
-`,this.view.isConnected&&(e.compilationString+="mat4 view = "+this.view.associatedVariableName+`;\r
-`),e.compilationString+=e._emitCodeFromInclude("shadowsVertex",a,{repeatKey:"maxSimultaneousLights"}))},t.prototype._getAlbedoOpacityCode=function(){var e=`albedoOpacityOutParams albedoOpacityOut;\r
-`;return e+=`albedoOpacityBlock(
-                vec4(`+(this.baseColor.isConnected?this.baseColor.associatedVariableName:"vec3(1.)")+`, 1.),
-            #ifdef ALBEDO
-                vec4(1.),
-                vec2(1., 1.),
-            #endif
-            #ifdef OPACITY
-                vec4(`+(this.opacity.isConnected?this.opacity.associatedVariableName:"1.")+`),
-                vec2(1., 1.),
-            #endif
-                albedoOpacityOut
-            );
-
-            vec3 surfaceAlbedo = albedoOpacityOut.surfaceAlbedo;
-            float alpha = albedoOpacityOut.alpha;\r
-`},t.prototype._getAmbientOcclusionCode=function(){var e=`ambientOcclusionOutParams aoOut;\r
-`;return e+=`ambientOcclusionBlock(
-            #ifdef AMBIENT
-                vec3(`+(this.ambientOcc.isConnected?this.ambientOcc.associatedVariableName:"1.")+`),
-                vec4(0., 1.0, 1.0, 0.),
-            #endif
-                aoOut
-            );\r
-`},t.prototype._getReflectivityCode=function(e){var n=`reflectivityOutParams reflectivityOut;\r
-`;return this._vMetallicReflectanceFactorsName=e._getFreeVariableName("vMetallicReflectanceFactors"),e._emitUniformFromString(this._vMetallicReflectanceFactorsName,"vec4"),n+=`vec3 baseColor = surfaceAlbedo;
-
-            reflectivityBlock(
-                vec4(`+this.metallic.associatedVariableName+", "+this.roughness.associatedVariableName+`, 0., 0.),
-            #ifdef METALLICWORKFLOW
-                surfaceAlbedo,
-                `+this._vMetallicReflectanceFactorsName+`,
-            #endif
-            #ifdef REFLECTIVITY
-                vec3(0., 0., 1.),
-                vec4(1.),
-            #endif
-            #if defined(METALLICWORKFLOW) && defined(REFLECTIVITY)  && defined(AOSTOREINMETALMAPRED)
-                aoOut.ambientOcclusionColor,
-            #endif
-            #ifdef MICROSURFACEMAP
-                microSurfaceTexel, <== not handled!
-            #endif
-                reflectivityOut
-            );
-
-            float microSurface = reflectivityOut.microSurface;
-            float roughness = reflectivityOut.roughness;
-
-            #ifdef METALLICWORKFLOW
-                surfaceAlbedo = reflectivityOut.surfaceAlbedo;
-            #endif
-            #if defined(METALLICWORKFLOW) && defined(REFLECTIVITY) && defined(AOSTOREINMETALMAPRED)
-                aoOut.ambientOcclusionColor = reflectivityOut.ambientOcclusionColor;
-            #endif\r
-`},t.prototype._buildBlock=function(e){var n,i,o,a,s,d,p,b,P,O,B,F,z,J,ie,se,ce,ue,fe,ve,Te,Re,Ae,Ee,Se,Le,Ce,Ne,Ie,Fe,Ye,tt,it,lt,Qe,ot,rt,Ze,dt;r.prototype._buildBlock.call(this,e),this._scene=e.sharedData.scene,this._environmentBRDFTexture||(this._environmentBRDFTexture=ea.GetEnvironmentBRDFTexture(this._scene));var Ve=this.reflection.isConnected?(n=this.reflection.connectedPoint)===null||n===void 0?void 0:n.ownerBlock:null;if(Ve&&(Ve.worldPositionConnectionPoint=this.worldPosition,Ve.cameraPositionConnectionPoint=this.cameraPosition,Ve.worldNormalConnectionPoint=this.worldNormal),e.target!==xe.Fragment)return this._injectVertexCode(e),this;e.sharedData.bindableBlocks.push(this),e.sharedData.blocksWithDefines.push(this);var Je="//"+this.name,yt="v_"+this.worldPosition.associatedVariableName,Wt=this.perturbedNormal;this._environmentBrdfSamplerName=e._getFreeVariableName("environmentBrdfSampler"),e._emit2DSampler(this._environmentBrdfSamplerName),e.sharedData.hints.needAlphaBlending=e.sharedData.hints.needAlphaBlending||this.useAlphaBlending,e.sharedData.hints.needAlphaTesting=e.sharedData.hints.needAlphaTesting||this.useAlphaTest,e._emitExtension("lod","#extension GL_EXT_shader_texture_lod : enable","defined(LODBASEDMICROSFURACE)"),e._emitExtension("derivatives","#extension GL_OES_standard_derivatives : enable"),this.light?e._emitFunctionFromInclude(e.supportUniformBuffers?"lightUboDeclaration":"lightFragmentDeclaration",Je,{replaceStrings:[{search:/{X}/g,replace:this._lightId.toString()}]},this._lightId.toString()):e._emitFunctionFromInclude(e.supportUniformBuffers?"lightUboDeclaration":"lightFragmentDeclaration",Je,{repeatKey:"maxSimultaneousLights"}),e._emitFunctionFromInclude("helperFunctions",Je),e._emitFunctionFromInclude("importanceSampling",Je),e._emitFunctionFromInclude("pbrHelperFunctions",Je),e._emitFunctionFromInclude("imageProcessingFunctions",Je),e._emitFunctionFromInclude("shadowsFragmentFunctions",Je,{replaceStrings:[{search:/vPositionW/g,replace:yt+".xyz"}]}),e._emitFunctionFromInclude("pbrDirectLightingSetupFunctions",Je,{replaceStrings:[{search:/vPositionW/g,replace:yt+".xyz"}]}),e._emitFunctionFromInclude("pbrDirectLightingFalloffFunctions",Je),e._emitFunctionFromInclude("pbrBRDFFunctions",Je,{replaceStrings:[{search:/REFLECTIONMAP_SKYBOX/g,replace:(i=Ve?._defineSkyboxName)!==null&&i!==void 0?i:"REFLECTIONMAP_SKYBOX"}]}),e._emitFunctionFromInclude("hdrFilteringFunctions",Je),e._emitFunctionFromInclude("pbrDirectLightingFunctions",Je,{replaceStrings:[{search:/vPositionW/g,replace:yt+".xyz"}]}),e._emitFunctionFromInclude("pbrIBLFunctions",Je),e._emitFunctionFromInclude("pbrBlockAlbedoOpacity",Je),e._emitFunctionFromInclude("pbrBlockReflectivity",Je),e._emitFunctionFromInclude("pbrBlockAmbientOcclusion",Je),e._emitFunctionFromInclude("pbrBlockAlphaFresnel",Je),e._emitFunctionFromInclude("pbrBlockAnisotropic",Je),e._emitUniformFromString("vLightingIntensity","vec4"),this._vNormalWName=e._getFreeVariableName("vNormalW"),e.compilationString+="vec4 "+this._vNormalWName+" = normalize("+this.worldNormal.associatedVariableName+`);\r
-`,e._registerTempVariable("viewDirectionW")&&(e.compilationString+="vec3 viewDirectionW = normalize("+this.cameraPosition.associatedVariableName+" - "+yt+`.xyz);\r
-`),e.compilationString+="vec3 geometricNormalW = "+this._vNormalWName+`.xyz;\r
-`,e.compilationString+="vec3 normalW = "+(Wt.isConnected?"normalize("+Wt.associatedVariableName+".xyz)":"geometricNormalW")+`;\r
-`,this._invertNormalName=e._getFreeVariableName("invertNormal"),e._emitUniformFromString(this._invertNormalName,"float"),e.compilationString+=e._emitCodeFromInclude("pbrBlockNormalFinal",Je,{replaceStrings:[{search:/vPositionW/g,replace:yt+".xyz"},{search:/vEyePosition.w/g,replace:this._invertNormalName}]}),e.compilationString+=this._getAlbedoOpacityCode(),e.compilationString+=e._emitCodeFromInclude("depthPrePass",Je),e.compilationString+=this._getAmbientOcclusionCode(),e.compilationString+=e._emitCodeFromInclude("pbrBlockLightmapInit",Je),e.compilationString+=`#ifdef UNLIT
-                vec3 diffuseBase = vec3(1., 1., 1.);
-            #else\r
-`,e.compilationString+=this._getReflectivityCode(e),e.compilationString+=e._emitCodeFromInclude("pbrBlockGeometryInfo",Je,{replaceStrings:[{search:/REFLECTIONMAP_SKYBOX/g,replace:(o=Ve?._defineSkyboxName)!==null&&o!==void 0?o:"REFLECTIONMAP_SKYBOX"},{search:/REFLECTIONMAP_3D/g,replace:(a=Ve?._define3DName)!==null&&a!==void 0?a:"REFLECTIONMAP_3D"}]});var Nt=this.anisotropy.isConnected?(s=this.anisotropy.connectedPoint)===null||s===void 0?void 0:s.ownerBlock:null;Nt&&(Nt.worldPositionConnectionPoint=this.worldPosition,Nt.worldNormalConnectionPoint=this.worldNormal,e.compilationString+=Nt.getCode(e,!this.perturbedNormal.isConnected)),Ve&&Ve.hasTexture&&(e.compilationString+=Ve.getCode(e,Nt?"anisotropicOut.anisotropicNormal":"normalW")),e._emitFunctionFromInclude("pbrBlockReflection",Je,{replaceStrings:[{search:/computeReflectionCoords/g,replace:"computeReflectionCoordsPBR"},{search:/REFLECTIONMAP_3D/g,replace:(d=Ve?._define3DName)!==null&&d!==void 0?d:"REFLECTIONMAP_3D"},{search:/REFLECTIONMAP_OPPOSITEZ/g,replace:(p=Ve?._defineOppositeZ)!==null&&p!==void 0?p:"REFLECTIONMAP_OPPOSITEZ"},{search:/REFLECTIONMAP_PROJECTION/g,replace:(b=Ve?._defineProjectionName)!==null&&b!==void 0?b:"REFLECTIONMAP_PROJECTION"},{search:/REFLECTIONMAP_SKYBOX/g,replace:(P=Ve?._defineSkyboxName)!==null&&P!==void 0?P:"REFLECTIONMAP_SKYBOX"},{search:/LODINREFLECTIONALPHA/g,replace:(O=Ve?._defineLODReflectionAlpha)!==null&&O!==void 0?O:"LODINREFLECTIONALPHA"},{search:/LINEARSPECULARREFLECTION/g,replace:(B=Ve?._defineLinearSpecularReflection)!==null&&B!==void 0?B:"LINEARSPECULARREFLECTION"},{search:/vReflectionFilteringInfo/g,replace:(F=Ve?._vReflectionFilteringInfoName)!==null&&F!==void 0?F:"vReflectionFilteringInfo"}]}),e.compilationString+=e._emitCodeFromInclude("pbrBlockReflectance0",Je,{replaceStrings:[{search:/metallicReflectanceFactors/g,replace:this._vMetallicReflectanceFactorsName}]});var Qt=this.sheen.isConnected?(z=this.sheen.connectedPoint)===null||z===void 0?void 0:z.ownerBlock:null;Qt&&(e.compilationString+=Qt.getCode(Ve)),e._emitFunctionFromInclude("pbrBlockSheen",Je,{replaceStrings:[{search:/REFLECTIONMAP_3D/g,replace:(J=Ve?._define3DName)!==null&&J!==void 0?J:"REFLECTIONMAP_3D"},{search:/REFLECTIONMAP_SKYBOX/g,replace:(ie=Ve?._defineSkyboxName)!==null&&ie!==void 0?ie:"REFLECTIONMAP_SKYBOX"},{search:/LODINREFLECTIONALPHA/g,replace:(se=Ve?._defineLODReflectionAlpha)!==null&&se!==void 0?se:"LODINREFLECTIONALPHA"},{search:/LINEARSPECULARREFLECTION/g,replace:(ce=Ve?._defineLinearSpecularReflection)!==null&&ce!==void 0?ce:"LINEARSPECULARREFLECTION"}]});var vt=this.clearcoat.isConnected?(ue=this.clearcoat.connectedPoint)===null||ue===void 0?void 0:ue.ownerBlock:null,Jt=!this.perturbedNormal.isConnected&&!this.anisotropy.isConnected,Xt=this.perturbedNormal.isConnected&&((fe=this.perturbedNormal.connectedPoint)===null||fe===void 0?void 0:fe.ownerBlock).worldTangent.isConnected,zt=this.anisotropy.isConnected&&((ve=this.anisotropy.connectedPoint)===null||ve===void 0?void 0:ve.ownerBlock).worldTangent.isConnected,Yt=Xt||!this.perturbedNormal.isConnected&&zt;e.compilationString+=ba.GetCode(e,vt,Ve,yt,Jt,Yt,this.worldNormal.associatedVariableName),Jt&&(Yt=(Te=vt?.worldTangent.isConnected)!==null&&Te!==void 0&&Te),e._emitFunctionFromInclude("pbrBlockClearcoat",Je,{replaceStrings:[{search:/computeReflectionCoords/g,replace:"computeReflectionCoordsPBR"},{search:/REFLECTIONMAP_3D/g,replace:(Re=Ve?._define3DName)!==null&&Re!==void 0?Re:"REFLECTIONMAP_3D"},{search:/REFLECTIONMAP_OPPOSITEZ/g,replace:(Ae=Ve?._defineOppositeZ)!==null&&Ae!==void 0?Ae:"REFLECTIONMAP_OPPOSITEZ"},{search:/REFLECTIONMAP_PROJECTION/g,replace:(Ee=Ve?._defineProjectionName)!==null&&Ee!==void 0?Ee:"REFLECTIONMAP_PROJECTION"},{search:/REFLECTIONMAP_SKYBOX/g,replace:(Se=Ve?._defineSkyboxName)!==null&&Se!==void 0?Se:"REFLECTIONMAP_SKYBOX"},{search:/LODINREFLECTIONALPHA/g,replace:(Le=Ve?._defineLODReflectionAlpha)!==null&&Le!==void 0?Le:"LODINREFLECTIONALPHA"},{search:/LINEARSPECULARREFLECTION/g,replace:(Ce=Ve?._defineLinearSpecularReflection)!==null&&Ce!==void 0?Ce:"LINEARSPECULARREFLECTION"},{search:/defined\(TANGENT\)/g,replace:Yt?"defined(TANGENT)":"defined(IGNORE)"}]}),e.compilationString+=e._emitCodeFromInclude("pbrBlockReflectance",Je,{replaceStrings:[{search:/REFLECTIONMAP_SKYBOX/g,replace:(Ne=Ve?._defineSkyboxName)!==null&&Ne!==void 0?Ne:"REFLECTIONMAP_SKYBOX"},{search:/REFLECTIONMAP_3D/g,replace:(Ie=Ve?._define3DName)!==null&&Ie!==void 0?Ie:"REFLECTIONMAP_3D"}]});var Et=this.subsurface.isConnected?(Fe=this.subsurface.connectedPoint)===null||Fe===void 0?void 0:Fe.ownerBlock:null,Mt=this.subsurface.isConnected?(tt=((Ye=this.subsurface.connectedPoint)===null||Ye===void 0?void 0:Ye.ownerBlock).refraction.connectedPoint)===null||tt===void 0?void 0:tt.ownerBlock:null;Mt&&(Mt.viewConnectionPoint=this.view,Mt.indexOfRefractionConnectionPoint=this.indexOfRefraction),e.compilationString+=ya.GetCode(e,Et,Ve,yt),e._emitFunctionFromInclude("pbrBlockSubSurface",Je,{replaceStrings:[{search:/REFLECTIONMAP_3D/g,replace:(it=Ve?._define3DName)!==null&&it!==void 0?it:"REFLECTIONMAP_3D"},{search:/REFLECTIONMAP_OPPOSITEZ/g,replace:(lt=Ve?._defineOppositeZ)!==null&&lt!==void 0?lt:"REFLECTIONMAP_OPPOSITEZ"},{search:/REFLECTIONMAP_PROJECTION/g,replace:(Qe=Ve?._defineProjectionName)!==null&&Qe!==void 0?Qe:"REFLECTIONMAP_PROJECTION"},{search:/SS_REFRACTIONMAP_3D/g,replace:(ot=Mt?._define3DName)!==null&&ot!==void 0?ot:"SS_REFRACTIONMAP_3D"},{search:/SS_LODINREFRACTIONALPHA/g,replace:(rt=Mt?._defineLODRefractionAlpha)!==null&&rt!==void 0?rt:"SS_LODINREFRACTIONALPHA"},{search:/SS_LINEARSPECULARREFRACTION/g,replace:(Ze=Mt?._defineLinearSpecularRefraction)!==null&&Ze!==void 0?Ze:"SS_LINEARSPECULARREFRACTION"},{search:/SS_REFRACTIONMAP_OPPOSITEZ/g,replace:(dt=Mt?._defineOppositeZ)!==null&&dt!==void 0?dt:"SS_REFRACTIONMAP_OPPOSITEZ"}]}),e.compilationString+=e._emitCodeFromInclude("pbrBlockDirectLighting",Je),this.light?e.compilationString+=e._emitCodeFromInclude("lightFragment",Je,{replaceStrings:[{search:/{X}/g,replace:this._lightId.toString()}]}):e.compilationString+=e._emitCodeFromInclude("lightFragment",Je,{repeatKey:"maxSimultaneousLights"}),e.compilationString+=e._emitCodeFromInclude("pbrBlockFinalLitComponents",Je),e.compilationString+=`#endif\r
-`;var $t=this.ambientColor.isConnected?this.ambientColor.associatedVariableName:"vec3(0., 0., 0.)",Dn=_n.DEFAULT_AO_ON_ANALYTICAL_LIGHTS.toString();Dn.indexOf(".")===-1&&(Dn+="."),e.compilationString+=e._emitCodeFromInclude("pbrBlockFinalUnlitComponents",Je,{replaceStrings:[{search:/vec3 finalEmissive[\s\S]*?finalEmissive\*=vLightingIntensity\.y;/g,replace:""},{search:/vAmbientColor/g,replace:$t+" * ambientFromScene"},{search:/vAmbientInfos\.w/g,replace:Dn}]}),e.compilationString+=e._emitCodeFromInclude("pbrBlockFinalColorComposition",Je,{replaceStrings:[{search:/finalEmissive/g,replace:"vec3(0.)"}]}),e.compilationString+=e._emitCodeFromInclude("pbrBlockImageProcessing",Je,{replaceStrings:[{search:/visibility/g,replace:"1."}]}),e.compilationString+=e._emitCodeFromInclude("pbrDebug",Je,{replaceStrings:[{search:/vNormalW/g,replace:this._vNormalWName},{search:/vPositionW/g,replace:yt},{search:/albedoTexture\.rgb;/g,replace:`vec3(1.);\r
-gl_FragColor.rgb = toGammaSpace(gl_FragColor.rgb);\r
-`}]});for(var Vn=0,$n=this._outputs;Vn<$n.length;Vn++){var Ln=$n[Vn];if(Ln.hasEndpoints){var qt=hm[Ln.name];if(qt){var hi=qt[0],Ri=qt[1];Ri&&(e.compilationString+="#if "+Ri+`\r
-`),e.compilationString+=this._declareOutput(Ln,e)+" = "+hi+`;\r
-`,Ri&&(e.compilationString+=`#else\r
-`,e.compilationString+=this._declareOutput(Ln,e)+` = vec3(0.);\r
-`,e.compilationString+=`#endif\r
-`)}else console.error("There's no remapping for the "+Ln.name+" end point! No code generated")}}return this},t.prototype._dumpPropertiesCode=function(){var e="";return e+=this._codeVariableName+".lightFalloff = "+this.lightFalloff+`;\r
-`,e+=this._codeVariableName+".useAlphaTest = "+this.useAlphaTest+`;\r
-`,e+=this._codeVariableName+".alphaTestCutoff = "+this.alphaTestCutoff+`;\r
-`,e+=this._codeVariableName+".useAlphaBlending = "+this.useAlphaBlending+`;\r
-`,e+=this._codeVariableName+".useRadianceOverAlpha = "+this.useRadianceOverAlpha+`;\r
-`,e+=this._codeVariableName+".useSpecularOverAlpha = "+this.useSpecularOverAlpha+`;\r
-`,e+=this._codeVariableName+".enableSpecularAntiAliasing = "+this.enableSpecularAntiAliasing+`;\r
-`,e+=this._codeVariableName+".realTimeFiltering = "+this.realTimeFiltering+`;\r
-`,e+=this._codeVariableName+".realTimeFilteringQuality = "+this.realTimeFilteringQuality+`;\r
-`,e+=this._codeVariableName+".useEnergyConservation = "+this.useEnergyConservation+`;\r
-`,e+=this._codeVariableName+".useRadianceOcclusion = "+this.useRadianceOcclusion+`;\r
-`,e+=this._codeVariableName+".useHorizonOcclusion = "+this.useHorizonOcclusion+`;\r
-`,e+=this._codeVariableName+".unlit = "+this.unlit+`;\r
-`,e+=this._codeVariableName+".forceNormalForward = "+this.forceNormalForward+`;\r
-`,e+=this._codeVariableName+".debugMode = "+this.debugMode+`;\r
-`,e+=this._codeVariableName+".debugLimit = "+this.debugLimit+`;\r
-`,e+=this._codeVariableName+".debugFactor = "+this.debugFactor+`;\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return this.light&&(e.lightId=this.light.id),e.lightFalloff=this.lightFalloff,e.useAlphaTest=this.useAlphaTest,e.alphaTestCutoff=this.alphaTestCutoff,e.useAlphaBlending=this.useAlphaBlending,e.useRadianceOverAlpha=this.useRadianceOverAlpha,e.useSpecularOverAlpha=this.useSpecularOverAlpha,e.enableSpecularAntiAliasing=this.enableSpecularAntiAliasing,e.realTimeFiltering=this.realTimeFiltering,e.realTimeFilteringQuality=this.realTimeFilteringQuality,e.useEnergyConservation=this.useEnergyConservation,e.useRadianceOcclusion=this.useRadianceOcclusion,e.useHorizonOcclusion=this.useHorizonOcclusion,e.unlit=this.unlit,e.forceNormalForward=this.forceNormalForward,e.debugMode=this.debugMode,e.debugLimit=this.debugLimit,e.debugFactor=this.debugFactor,e},t.prototype._deserialize=function(e,n,i){var o,a;r.prototype._deserialize.call(this,e,n,i),e.lightId&&(this.light=n.getLightByID(e.lightId)),this.lightFalloff=(o=e.lightFalloff)!==null&&o!==void 0?o:0,this.useAlphaTest=e.useAlphaTest,this.alphaTestCutoff=e.alphaTestCutoff,this.useAlphaBlending=e.useAlphaBlending,this.useRadianceOverAlpha=e.useRadianceOverAlpha,this.useSpecularOverAlpha=e.useSpecularOverAlpha,this.enableSpecularAntiAliasing=e.enableSpecularAntiAliasing,this.realTimeFiltering=!!e.realTimeFiltering,this.realTimeFilteringQuality=(a=e.realTimeFilteringQuality)!==null&&a!==void 0?a:h.a.TEXTURE_FILTERING_QUALITY_LOW,this.useEnergyConservation=e.useEnergyConservation,this.useRadianceOcclusion=e.useRadianceOcclusion,this.useHorizonOcclusion=e.useHorizonOcclusion,this.unlit=e.unlit,this.forceNormalForward=!!e.forceNormalForward,this.debugMode=e.debugMode,this.debugLimit=e.debugLimit,this.debugFactor=e.debugFactor},Object(c.c)([Vt("Direct lights",Lt.Float,"INTENSITY",{min:0,max:1,notifiers:{update:!0}})],t.prototype,"directIntensity",void 0),Object(c.c)([Vt("Environment lights",Lt.Float,"INTENSITY",{min:0,max:1,notifiers:{update:!0}})],t.prototype,"environmentIntensity",void 0),Object(c.c)([Vt("Specular highlights",Lt.Float,"INTENSITY",{min:0,max:1,notifiers:{update:!0}})],t.prototype,"specularIntensity",void 0),Object(c.c)([Vt("Light falloff",Lt.List,"LIGHTING & COLORS",{notifiers:{update:!0},options:[{label:"Physical",value:_n.LIGHTFALLOFF_PHYSICAL},{label:"GLTF",value:_n.LIGHTFALLOFF_GLTF},{label:"Standard",value:_n.LIGHTFALLOFF_STANDARD}]})],t.prototype,"lightFalloff",void 0),Object(c.c)([Vt("Alpha Testing",Lt.Boolean,"OPACITY")],t.prototype,"useAlphaTest",void 0),Object(c.c)([Vt("Alpha CutOff",Lt.Float,"OPACITY",{min:0,max:1,notifiers:{update:!0}})],t.prototype,"alphaTestCutoff",void 0),Object(c.c)([Vt("Alpha blending",Lt.Boolean,"OPACITY")],t.prototype,"useAlphaBlending",void 0),Object(c.c)([Vt("Radiance over alpha",Lt.Boolean,"RENDERING",{notifiers:{update:!0}})],t.prototype,"useRadianceOverAlpha",void 0),Object(c.c)([Vt("Specular over alpha",Lt.Boolean,"RENDERING",{notifiers:{update:!0}})],t.prototype,"useSpecularOverAlpha",void 0),Object(c.c)([Vt("Specular anti-aliasing",Lt.Boolean,"RENDERING",{notifiers:{update:!0}})],t.prototype,"enableSpecularAntiAliasing",void 0),Object(c.c)([Vt("Realtime filtering",Lt.Boolean,"RENDERING",{notifiers:{update:!0}})],t.prototype,"realTimeFiltering",void 0),Object(c.c)([Vt("Realtime filtering quality",Lt.List,"RENDERING",{notifiers:{update:!0},options:[{label:"Low",value:h.a.TEXTURE_FILTERING_QUALITY_LOW},{label:"Medium",value:h.a.TEXTURE_FILTERING_QUALITY_MEDIUM},{label:"High",value:h.a.TEXTURE_FILTERING_QUALITY_HIGH}]})],t.prototype,"realTimeFilteringQuality",void 0),Object(c.c)([Vt("Energy Conservation",Lt.Boolean,"ADVANCED",{notifiers:{update:!0}})],t.prototype,"useEnergyConservation",void 0),Object(c.c)([Vt("Radiance occlusion",Lt.Boolean,"ADVANCED",{notifiers:{update:!0}})],t.prototype,"useRadianceOcclusion",void 0),Object(c.c)([Vt("Horizon occlusion",Lt.Boolean,"ADVANCED",{notifiers:{update:!0}})],t.prototype,"useHorizonOcclusion",void 0),Object(c.c)([Vt("Unlit",Lt.Boolean,"ADVANCED",{notifiers:{update:!0}})],t.prototype,"unlit",void 0),Object(c.c)([Vt("Force normal forward",Lt.Boolean,"ADVANCED",{notifiers:{update:!0}})],t.prototype,"forceNormalForward",void 0),Object(c.c)([Vt("Debug mode",Lt.List,"DEBUG",{notifiers:{update:!0},options:[{label:"None",value:0},{label:"Normalized position",value:1},{label:"Normals",value:2},{label:"Tangents",value:3},{label:"Bitangents",value:4},{label:"Bump Normals",value:5},{label:"ClearCoat Normals",value:8},{label:"ClearCoat Tangents",value:9},{label:"ClearCoat Bitangents",value:10},{label:"Anisotropic Normals",value:11},{label:"Anisotropic Tangents",value:12},{label:"Anisotropic Bitangents",value:13},{label:"Env Refraction",value:40},{label:"Env Reflection",value:41},{label:"Env Clear Coat",value:42},{label:"Direct Diffuse",value:50},{label:"Direct Specular",value:51},{label:"Direct Clear Coat",value:52},{label:"Direct Sheen",value:53},{label:"Env Irradiance",value:54},{label:"Surface Albedo",value:60},{label:"Reflectance 0",value:61},{label:"Metallic",value:62},{label:"Metallic F0",value:71},{label:"Roughness",value:63},{label:"AlphaG",value:64},{label:"NdotV",value:65},{label:"ClearCoat Color",value:66},{label:"ClearCoat Roughness",value:67},{label:"ClearCoat NdotV",value:68},{label:"Transmittance",value:69},{label:"Refraction Transmittance",value:70},{label:"SEO",value:80},{label:"EHO",value:81},{label:"Energy Factor",value:82},{label:"Specular Reflectance",value:83},{label:"Clear Coat Reflectance",value:84},{label:"Sheen Reflectance",value:85},{label:"Luminance Over Alpha",value:86},{label:"Alpha",value:87}]})],t.prototype,"debugMode",void 0),Object(c.c)([Vt("Split position",Lt.Float,"DEBUG",{min:-1,max:1,notifiers:{update:!0}})],t.prototype,"debugLimit",void 0),Object(c.c)([Vt("Output factor",Lt.Float,"DEBUG",{min:0,max:5,notifiers:{update:!0}})],t.prototype,"debugFactor",void 0),t}(pt);R.a.RegisteredTypes["BABYLON.PBRMetallicRoughnessBlock"]=ld;var ud=function(r){function t(e){var n=r.call(this,e,xe.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ModBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = mod("+this.left.associatedVariableName+", "+this.right.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.ModBlock"]=ud;var dm=function(){function r(){}return r.prototype.optimize=function(t,e){},r}(),fm=f(120),pm=function(){function r(){this.mm=new Map}return r.prototype.get=function(t,e){var n=this.mm.get(t);if(n!==void 0)return n.get(e)},r.prototype.set=function(t,e,n){var i=this.mm.get(t);i===void 0&&this.mm.set(t,i=new Map),i.set(e,n)},r}(),_m=function(){function r(t,e,n){var i=this;this._baseMaterial=t,this._scene=e,this._options=n,this._subMeshToEffect=new Map,this._subMeshToDepthEffect=new pm,this._meshes=new Map;var o=t.getClassName()==="NodeMaterial"?"u_":"";if(o){this._matriceNames={world:o+"World",view:o+"View",projection:o+"Projection",viewProjection:o+"ViewProjection",worldView:o+"WorldxView",worldViewProjection:o+"WorldxViewxProjection"};for(var a=t.getInputBlocks(),s=0;s<a.length;++s)switch(a[s]._systemValue){case bt.World:this._matriceNames.world=a[s].associatedVariableName;break;case bt.View:this._matriceNames.view=a[s].associatedVariableName;break;case bt.Projection:this._matriceNames.projection=a[s].associatedVariableName;break;case bt.ViewProjection:this._matriceNames.viewProjection=a[s].associatedVariableName;break;case bt.WorldView:this._matriceNames.worldView=a[s].associatedVariableName;break;case bt.WorldViewProjection:this._matriceNames.worldViewProjection=a[s].associatedVariableName}}else this._matriceNames={world:o+"world",view:o+"view",projection:o+"projection",viewProjection:o+"viewProjection",worldView:o+"worldView",worldViewProjection:o+"worldViewProjection"};this._onEffectCreatedObserver=this._baseMaterial.onEffectCreatedObservable.add(function(d){var p,b=(p=d.subMesh)===null||p===void 0?void 0:p.getMesh();b&&!i._meshes.has(b)&&i._meshes.set(b,b.onDisposeObservable.add(function(P){for(var O=i._subMeshToEffect.keys(),B=O.next();B.done!==!0;B=O.next()){var F=B.value;F?.getMesh()===P&&(i._subMeshToEffect.delete(F),i._subMeshToDepthEffect.mm.delete(F))}})),i._subMeshToEffect.set(d.subMesh,d.effect),i._subMeshToDepthEffect.mm.delete(d.subMesh)})}return Object.defineProperty(r.prototype,"standalone",{get:function(){var t,e;return(e=(t=this._options)===null||t===void 0?void 0:t.standalone)!==null&&e!==void 0&&e},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"baseMaterial",{get:function(){return this._baseMaterial},enumerable:!1,configurable:!0}),r.prototype.getEffect=function(t,e){var n,i,o,a,s,d;return(d=(o=(i=(n=this._subMeshToDepthEffect.mm.get(t))===null||n===void 0?void 0:n.get(e))===null||i===void 0?void 0:i.depthEffect)!==null&&o!==void 0?o:(s=(a=this._subMeshToDepthEffect.mm.get(null))===null||a===void 0?void 0:a.get(e))===null||s===void 0?void 0:s.depthEffect)!==null&&d!==void 0?d:null},r.prototype.isReadyForSubMesh=function(t,e,n,i){var o,a;return this.standalone&&this._baseMaterial.isReadyForSubMesh(t.getMesh(),t,i),(a=(o=this._makeEffect(t,e,n))===null||o===void 0?void 0:o.isReady())!==null&&a!==void 0&&a},r.prototype.dispose=function(){this._baseMaterial.onEffectCreatedObservable.remove(this._onEffectCreatedObserver),this._onEffectCreatedObserver=null;for(var t=this._meshes.entries(),e=t.next();e.done!==!0;e=t.next()){var n=e.value,i=n[0],o=n[1];i.onDisposeObservable.remove(o)}},r.prototype._makeEffect=function(t,e,n){var i,o=(i=this._subMeshToEffect.get(t))!==null&&i!==void 0?i:this._subMeshToEffect.get(null);if(!o)return null;var a=this._subMeshToDepthEffect.get(t,n);a||(a={depthEffect:null,depthDefines:"",token:fm.a.RandomId()},this._subMeshToDepthEffect.set(t,n,a));var s=e.join(`
-`);if(a.depthEffect&&s===a.depthDefines)return a.depthEffect;a.depthDefines=s;var d=o.rawVertexSourceCode,p=o.rawFragmentSourceCode,b=this._options&&this._options.remappedVariables?"#include<shadowMapVertexNormalBias>("+this._options.remappedVariables.join(",")+")":ze.a.IncludesShadersStore.shadowMapVertexNormalBias,P=this._options&&this._options.remappedVariables?"#include<shadowMapVertexMetric>("+this._options.remappedVariables.join(",")+")":ze.a.IncludesShadersStore.shadowMapVertexMetric,O=this._options&&this._options.remappedVariables?"#include<shadowMapFragmentSoftTransparentShadow>("+this._options.remappedVariables.join(",")+")":ze.a.IncludesShadersStore.shadowMapFragmentSoftTransparentShadow,B=ze.a.IncludesShadersStore.shadowMapFragment;d=(d=(d=(d=d.replace(/void\s+?main/g,ze.a.IncludesShadersStore.shadowMapVertexDeclaration+`\r
-void main`)).replace(/#define SHADOWDEPTH_NORMALBIAS|#define CUSTOM_VERTEX_UPDATE_WORLDPOS/g,b)).indexOf("#define SHADOWDEPTH_METRIC")!==-1?d.replace(/#define SHADOWDEPTH_METRIC/g,P):d.replace(/}\s*$/g,P+`\r
-}`)).replace(/#define SHADER_NAME.*?\n|out vec4 glFragColor;\n/g,"");var F=p.indexOf("#define SHADOWDEPTH_SOFTTRANSPARENTSHADOW")>=0||p.indexOf("#define CUSTOM_FRAGMENT_BEFORE_FOG")>=0,z=p.indexOf("#define SHADOWDEPTH_FRAGMENT")!==-1,J="";F?p=p.replace(/#define SHADOWDEPTH_SOFTTRANSPARENTSHADOW|#define CUSTOM_FRAGMENT_BEFORE_FOG/g,O):J=O+`\r
-`,p=p.replace(/void\s+?main/g,ze.a.IncludesShadersStore.shadowMapFragmentDeclaration+`\r
-void main`),z?p=p.replace(/#define SHADOWDEPTH_FRAGMENT/g,B):J+=B+`\r
-`,J&&(p=p.replace(/}\s*$/g,J+"}")),p=p.replace(/#define SHADER_NAME.*?\n|out vec4 glFragColor;\n/g,"");var ie=o.getUniformNames().slice();return ie.push("biasAndScaleSM","depthValuesSM","lightDataSM","softTransparentShadowSM"),a.depthEffect=this._scene.getEngine().createEffect({vertexSource:d,fragmentSource:p,vertexToken:a.token,fragmentToken:a.token},{attributes:o.getAttributesNames(),uniformsNames:ie,uniformBuffersNames:o.getUniformBuffersNames(),samplers:o.getSamplers(),defines:s+`
-`+o.defines.replace("#define SHADOWS","").replace(/#define SHADOW\d/g,""),indexParameters:o.getIndexParameters()},this._scene.getEngine()),a.depthEffect},r}(),hd=f(101);function bc(r,t,e,n,i){var o=new r.DecoderBuffer;o.Init(t,t.byteLength);var a,s,d=new r.Decoder;try{var p=d.GetEncodedGeometryType(o);switch(p){case r.TRIANGULAR_MESH:a=new r.Mesh,s=d.DecodeBufferToMesh(o,a);break;case r.POINT_CLOUD:a=new r.PointCloud,s=d.DecodeBufferToPointCloud(o,a);break;default:throw new Error("Invalid geometry type "+p)}if(!s.ok()||!a.ptr)throw new Error(s.error_msg());if(p===r.TRIANGULAR_MESH){var b=3*a.num_faces(),P=4*b,O=r._malloc(P);try{d.GetTrianglesUInt32Array(a,P,O);var B=new Uint32Array(b);B.set(new Uint32Array(r.HEAPF32.buffer,O,b)),n(B)}finally{r._free(O)}}var F=function(se,ce){var ue=ce.num_components(),fe=a.num_points(),ve=fe*ue,Te=ve*Float32Array.BYTES_PER_ELEMENT,Re=r._malloc(Te);try{d.GetAttributeDataArrayForAllPoints(a,ce,r.DT_FLOAT32,Te,Re);var Ae=new Float32Array(r.HEAPF32.buffer,Re,ve);if(se==="color"&&ue===3){for(var Ee=new Float32Array(4*fe),Se=0,Le=0;Se<Ee.length;Se+=4,Le+=ue)Ee[Se+0]=Ae[Le+0],Ee[Se+1]=Ae[Le+1],Ee[Se+2]=Ae[Le+2],Ee[Se+3]=1;i(se,Ee)}else(Ee=new Float32Array(ve)).set(new Float32Array(r.HEAPF32.buffer,Re,ve)),i(se,Ee)}finally{r._free(Re)}};if(e)for(var z in e){var J=e[z];F(z,d.GetAttributeByUniqueId(a,J))}else{var ie={position:"POSITION",normal:"NORMAL",color:"COLOR",uv:"TEX_COORD"};for(var z in ie)(J=d.GetAttributeId(a,r[ie[z]]))!==-1&&F(z,d.GetAttribute(a,J))}}finally{a&&r.destroy(a),r.destroy(d),r.destroy(o)}}function mm(){var r;onmessage=function(t){var e=t.data;switch(e.id){case"init":var n=e.decoder;n.url&&(importScripts(n.url),r=DracoDecoderModule({wasmBinary:n.wasmBinary})),postMessage("done");break;case"decodeMesh":if(!r)throw new Error("Draco decoder module is not available");r.then(function(i){bc(i,e.dataView,e.attributes,function(o){postMessage({id:"indices",value:o},[o.buffer])},function(o,a){postMessage({id:o,value:a},[a.buffer])}),postMessage("done")})}}}function dd(r){return typeof document!="object"||typeof r!="string"?r:Xe.b.GetAbsoluteUrl(r)}var gm=function(){function r(t){t===void 0&&(t=r.DefaultNumWorkers);var e=r.Configuration.decoder,n=e.wasmUrl&&e.wasmBinaryUrl&&typeof WebAssembly=="object"?{url:e.wasmUrl,wasmBinaryPromise:Xe.b.LoadFileAsync(dd(e.wasmBinaryUrl))}:{url:e.fallbackUrl,wasmBinaryPromise:Promise.resolve(void 0)};t&&typeof Worker=="function"?this._workerPoolPromise=n.wasmBinaryPromise.then(function(i){for(var o=bc+"("+mm+")()",a=URL.createObjectURL(new Blob([o],{type:"application/javascript"})),s=new Array(t),d=0;d<s.length;d++)s[d]=new Promise(function(p,b){var P=new Worker(a),O=function(F){P.removeEventListener("error",O),P.removeEventListener("message",B),b(F)},B=function(F){F.data==="done"&&(P.removeEventListener("error",O),P.removeEventListener("message",B),p(P))};P.addEventListener("error",O),P.addEventListener("message",B),P.postMessage({id:"init",decoder:{url:dd(n.url),wasmBinary:i}})});return Promise.all(s).then(function(p){return new Bs(p)})}):this._decoderModulePromise=n.wasmBinaryPromise.then(function(i){if(!n.url)throw new Error("Draco decoder module is not available");return Xe.b.LoadScriptAsync(n.url).then(function(){return o=i,new Promise(function(a){DracoDecoderModule({wasmBinary:o}).then(function(s){a({module:s})})});var o})})}return Object.defineProperty(r,"DecoderAvailable",{get:function(){var t=r.Configuration.decoder;return!!(t.wasmUrl&&t.wasmBinaryUrl&&typeof WebAssembly=="object"||t.fallbackUrl)},enumerable:!1,configurable:!0}),r.GetDefaultNumWorkers=function(){return typeof navigator=="object"&&navigator.hardwareConcurrency?Math.min(Math.floor(.5*navigator.hardwareConcurrency),4):1},Object.defineProperty(r,"Default",{get:function(){return r._Default||(r._Default=new r),r._Default},enumerable:!1,configurable:!0}),r.prototype.dispose=function(){this._workerPoolPromise&&this._workerPoolPromise.then(function(t){t.dispose()}),delete this._workerPoolPromise,delete this._decoderModulePromise},r.prototype.whenReadyAsync=function(){return this._workerPoolPromise?this._workerPoolPromise.then(function(){}):this._decoderModulePromise?this._decoderModulePromise.then(function(){}):Promise.resolve()},r.prototype.decodeMeshAsync=function(t,e){var n=t instanceof ArrayBuffer?new Uint8Array(t):t;if(this._workerPoolPromise)return this._workerPoolPromise.then(function(i){return new Promise(function(o,a){i.push(function(s,d){var p=new ft.a,b=function(B){s.removeEventListener("error",b),s.removeEventListener("message",P),a(B),d()},P=function(B){B.data==="done"?(s.removeEventListener("error",b),s.removeEventListener("message",P),o(p),d()):B.data.id==="indices"?p.indices=B.data.value:p.set(B.data.value,B.data.id)};s.addEventListener("error",b),s.addEventListener("message",P);var O=new Uint8Array(n.byteLength);O.set(new Uint8Array(n.buffer,n.byteOffset,n.byteLength)),s.postMessage({id:"decodeMesh",dataView:O,attributes:e},[O.buffer])})})});if(this._decoderModulePromise)return this._decoderModulePromise.then(function(i){var o=new ft.a;return bc(i.module,n,e,function(a){o.indices=a},function(a,s){o.set(s,a)}),o});throw new Error("Draco decoder module is not available")},r.Configuration={decoder:{wasmUrl:"https://preview.babylonjs.com/draco_wasm_wrapper_gltf.js",wasmBinaryUrl:"https://preview.babylonjs.com/draco_decoder_gltf.wasm",fallbackUrl:"https://preview.babylonjs.com/draco_decoder_gltf.js"}},r.DefaultNumWorkers=r.GetDefaultNumWorkers(),r._Default=null,r}(),Eo=f(61),fd=0,vm=function(){function r(t,e,n,i){this.pos=t,this.normal=e,this.uv=n,this.vertColor=i}return r.prototype.clone=function(){var t,e;return new r(this.pos.clone(),this.normal.clone(),(t=this.uv)===null||t===void 0?void 0:t.clone(),(e=this.vertColor)===null||e===void 0?void 0:e.clone())},r.prototype.flip=function(){this.normal=this.normal.scale(-1)},r.prototype.interpolate=function(t,e){return new r(u.e.Lerp(this.pos,t.pos,e),u.e.Lerp(this.normal,t.normal,e),this.uv&&t.uv?u.d.Lerp(this.uv,t.uv,e):void 0,this.vertColor&&t.vertColor?M.b.Lerp(this.vertColor,t.vertColor,e):void 0)},r}(),bm=function(){function r(t,e){this.normal=t,this.w=e}return r.FromPoints=function(t,e,n){var i=n.subtract(t),o=e.subtract(t);if(i.lengthSquared()===0||o.lengthSquared()===0)return null;var a=u.e.Normalize(u.e.Cross(i,o));return new r(a,u.e.Dot(a,t))},r.prototype.clone=function(){return new r(this.normal.clone(),this.w)},r.prototype.flip=function(){this.normal.scaleInPlace(-1),this.w=-this.w},r.prototype.splitPolygon=function(t,e,n,i,o){var a,s,d=0,p=[];for(a=0;a<t.vertices.length;a++){var b=(s=u.e.Dot(this.normal,t.vertices[a].pos)-this.w)<-r.EPSILON?2:s>r.EPSILON?1:0;d|=b,p.push(b)}switch(d){case 0:(u.e.Dot(this.normal,t.plane.normal)>0?e:n).push(t);break;case 1:i.push(t);break;case 2:o.push(t);break;case 3:var P,O=[],B=[];for(a=0;a<t.vertices.length;a++){var F=(a+1)%t.vertices.length,z=p[a],J=p[F],ie=t.vertices[a],se=t.vertices[F];if(z!==2&&O.push(ie),z!==1&&B.push(z!==2?ie.clone():ie),(z|J)==3){s=(this.w-u.e.Dot(this.normal,ie.pos))/u.e.Dot(this.normal,se.pos.subtract(ie.pos));var ce=ie.interpolate(se,s);O.push(ce),B.push(ce.clone())}}O.length>=3&&(P=new yc(O,t.shared)).plane&&i.push(P),B.length>=3&&(P=new yc(B,t.shared)).plane&&o.push(P)}},r.EPSILON=1e-5,r}(),yc=function(){function r(t,e){this.vertices=t,this.shared=e,this.plane=bm.FromPoints(t[0].pos,t[1].pos,t[2].pos)}return r.prototype.clone=function(){return new r(this.vertices.map(function(t){return t.clone()}),this.shared)},r.prototype.flip=function(){this.vertices.reverse().map(function(t){t.flip()}),this.plane.flip()},r}(),Jn=function(){function r(t){this.plane=null,this.front=null,this.back=null,this.polygons=new Array,t&&this.build(t)}return r.prototype.clone=function(){var t=new r;return t.plane=this.plane&&this.plane.clone(),t.front=this.front&&this.front.clone(),t.back=this.back&&this.back.clone(),t.polygons=this.polygons.map(function(e){return e.clone()}),t},r.prototype.invert=function(){for(var t=0;t<this.polygons.length;t++)this.polygons[t].flip();this.plane&&this.plane.flip(),this.front&&this.front.invert(),this.back&&this.back.invert();var e=this.front;this.front=this.back,this.back=e},r.prototype.clipPolygons=function(t){if(!this.plane)return t.slice();for(var e=new Array,n=new Array,i=0;i<t.length;i++)this.plane.splitPolygon(t[i],e,n,e,n);return this.front&&(e=this.front.clipPolygons(e)),n=this.back?this.back.clipPolygons(n):[],e.concat(n)},r.prototype.clipTo=function(t){this.polygons=t.clipPolygons(this.polygons),this.front&&this.front.clipTo(t),this.back&&this.back.clipTo(t)},r.prototype.allPolygons=function(){var t=this.polygons.slice();return this.front&&(t=t.concat(this.front.allPolygons())),this.back&&(t=t.concat(this.back.allPolygons())),t},r.prototype.build=function(t){if(t.length){this.plane||(this.plane=t[0].plane.clone());for(var e=new Array,n=new Array,i=0;i<t.length;i++)this.plane.splitPolygon(t[i],this.polygons,this.polygons,e,n);e.length&&(this.front||(this.front=new r),this.front.build(e)),n.length&&(this.back||(this.back=new r),this.back.build(n))}},r}(),ym=function(){function r(){this.polygons=new Array}return r.FromMesh=function(t){var e,n,i,o,a,s,d,p,b,P=void 0,O=void 0,B=new Array,F=null;if(!(t instanceof De.a))throw"BABYLON.CSG: Wrong Mesh type, must be BABYLON.Mesh";t.computeWorldMatrix(!0),s=t.getWorldMatrix(),d=t.position.clone(),p=t.rotation.clone(),t.rotationQuaternion&&(F=t.rotationQuaternion.clone()),b=t.scaling.clone();for(var z=t.getIndices(),J=t.getVerticesData(Oe.b.PositionKind),ie=t.getVerticesData(Oe.b.NormalKind),se=t.getVerticesData(Oe.b.UVKind),ce=t.getVerticesData(Oe.b.ColorKind),ue=t.subMeshes,fe=0,ve=ue.length;fe<ve;fe++)for(var Te=ue[fe].indexStart,Re=ue[fe].indexCount+ue[fe].indexStart;Te<Re;Te+=3){a=[];for(var Ae=0;Ae<3;Ae++){var Ee=new u.e(ie[3*z[Te+Ae]],ie[3*z[Te+Ae]+1],ie[3*z[Te+Ae]+2]);se&&(P=new u.d(se[2*z[Te+Ae]],se[2*z[Te+Ae]+1])),ce&&(O=new M.b(ce[4*z[Te+Ae]],ce[4*z[Te+Ae]+1],ce[4*z[Te+Ae]+2],ce[4*z[Te+Ae]+3]));var Se=new u.e(J[3*z[Te+Ae]],J[3*z[Te+Ae]+1],J[3*z[Te+Ae]+2]);i=u.e.TransformCoordinates(Se,s),n=u.e.TransformNormal(Ee,s),e=new vm(i,n,P,O),a.push(e)}(o=new yc(a,{subMeshId:fe,meshId:fd,materialIndex:ue[fe].materialIndex})).plane&&B.push(o)}var Le=r.FromPolygons(B);return Le.matrix=s,Le.position=d,Le.rotation=p,Le.scaling=b,Le.rotationQuaternion=F,fd++,Le},r.FromPolygons=function(t){var e=new r;return e.polygons=t,e},r.prototype.clone=function(){var t=new r;return t.polygons=this.polygons.map(function(e){return e.clone()}),t.copyTransformAttributes(this),t},r.prototype.union=function(t){var e=new Jn(this.clone().polygons),n=new Jn(t.clone().polygons);return e.clipTo(n),n.clipTo(e),n.invert(),n.clipTo(e),n.invert(),e.build(n.allPolygons()),r.FromPolygons(e.allPolygons()).copyTransformAttributes(this)},r.prototype.unionInPlace=function(t){var e=new Jn(this.polygons),n=new Jn(t.polygons);e.clipTo(n),n.clipTo(e),n.invert(),n.clipTo(e),n.invert(),e.build(n.allPolygons()),this.polygons=e.allPolygons()},r.prototype.subtract=function(t){var e=new Jn(this.clone().polygons),n=new Jn(t.clone().polygons);return e.invert(),e.clipTo(n),n.clipTo(e),n.invert(),n.clipTo(e),n.invert(),e.build(n.allPolygons()),e.invert(),r.FromPolygons(e.allPolygons()).copyTransformAttributes(this)},r.prototype.subtractInPlace=function(t){var e=new Jn(this.polygons),n=new Jn(t.polygons);e.invert(),e.clipTo(n),n.clipTo(e),n.invert(),n.clipTo(e),n.invert(),e.build(n.allPolygons()),e.invert(),this.polygons=e.allPolygons()},r.prototype.intersect=function(t){var e=new Jn(this.clone().polygons),n=new Jn(t.clone().polygons);return e.invert(),n.clipTo(e),n.invert(),e.clipTo(n),n.clipTo(e),e.build(n.allPolygons()),e.invert(),r.FromPolygons(e.allPolygons()).copyTransformAttributes(this)},r.prototype.intersectInPlace=function(t){var e=new Jn(this.polygons),n=new Jn(t.polygons);e.invert(),n.clipTo(e),n.invert(),e.clipTo(n),n.clipTo(e),e.build(n.allPolygons()),e.invert(),this.polygons=e.allPolygons()},r.prototype.inverse=function(){var t=this.clone();return t.inverseInPlace(),t},r.prototype.inverseInPlace=function(){this.polygons.map(function(t){t.flip()})},r.prototype.copyTransformAttributes=function(t){return this.matrix=t.matrix,this.position=t.position,this.rotation=t.rotation,this.scaling=t.scaling,this.rotationQuaternion=t.rotationQuaternion,this},r.prototype.buildMeshGeometry=function(t,e,n){var i=this.matrix.clone();i.invert();var o,a,s,d=new De.a(t,e),p=[],b=[],P=[],O=null,B=null,F=u.e.Zero(),z=u.e.Zero(),J=u.d.Zero(),ie=new M.b(0,0,0,0),se=this.polygons,ce=[0,0,0],ue={},fe=0,ve={};n&&se.sort(function(lt,Qe){return lt.shared.meshId===Qe.shared.meshId?lt.shared.subMeshId-Qe.shared.subMeshId:lt.shared.meshId-Qe.shared.meshId});for(var Te=0,Re=se.length;Te<Re;Te++){ve[(o=se[Te]).shared.meshId]||(ve[o.shared.meshId]={}),ve[o.shared.meshId][o.shared.subMeshId]||(ve[o.shared.meshId][o.shared.subMeshId]={indexStart:1/0,indexEnd:-1/0,materialIndex:o.shared.materialIndex}),s=ve[o.shared.meshId][o.shared.subMeshId];for(var Ae=2,Ee=o.vertices.length;Ae<Ee;Ae++){ce[0]=0,ce[1]=Ae-1,ce[2]=Ae;for(var Se=0;Se<3;Se++){F.copyFrom(o.vertices[ce[Se]].pos),z.copyFrom(o.vertices[ce[Se]].normal),o.vertices[ce[Se]].uv&&(O||(O=[]),J.copyFrom(o.vertices[ce[Se]].uv)),o.vertices[ce[Se]].vertColor&&(B||(B=[]),ie.copyFrom(o.vertices[ce[Se]].vertColor));var Le=u.e.TransformCoordinates(F,i),Ce=u.e.TransformNormal(z,i);a=ue[Le.x+","+Le.y+","+Le.z];var Ne=!1;O&&O[2*a]!==J.x&&O[2*a+1]!==J.y&&(Ne=!0);var Ie=!1;B&&B[4*a]!==ie.r&&B[4*a+1]!==ie.g&&B[4*a+2]!==ie.b&&B[4*a+3]!==ie.a&&(Ie=!0),(a===void 0||P[3*a]!==Ce.x||P[3*a+1]!==Ce.y||P[3*a+2]!==Ce.z||Ne||Ie)&&(p.push(Le.x,Le.y,Le.z),O&&O.push(J.x,J.y),P.push(z.x,z.y,z.z),B&&B.push(ie.r,ie.g,ie.b,ie.a),a=ue[Le.x+","+Le.y+","+Le.z]=p.length/3-1),b.push(a),s.indexStart=Math.min(fe,s.indexStart),s.indexEnd=Math.max(fe,s.indexEnd),fe++}}}if(d.setVerticesData(Oe.b.PositionKind,p),d.setVerticesData(Oe.b.NormalKind,P),O&&d.setVerticesData(Oe.b.UVKind,O),B&&d.setVerticesData(Oe.b.ColorKind,B),d.setIndices(b,null),n){var Fe,Ye=0;for(var tt in d.subMeshes=new Array,ve){for(var it in Fe=-1,ve[tt])s=ve[tt][it],Eo.a.CreateFromIndices(s.materialIndex+Ye,s.indexStart,s.indexEnd-s.indexStart+1,d),Fe=Math.max(s.materialIndex,Fe);Ye+=++Fe}}return d},r.prototype.toMesh=function(t,e,n,i){e===void 0&&(e=null);var o=this.buildMeshGeometry(t,n,i);return o.material=e,o.position.copyFrom(this.position),o.rotation.copyFrom(this.rotation),this.rotationQuaternion&&(o.rotationQuaternion=this.rotationQuaternion.clone()),o.scaling.copyFrom(this.scaling),o.computeWorldMatrix(!0),o},r}(),Tm=function(r){function t(e,n,i,o,a,s){o===void 0&&(o=1),a===void 0&&(a=60),s===void 0&&(s=!0);var d=r.call(this,e,i)||this;d._sectionPolygonPointsCount=4,d._running=!1,d._autoStart=s,d._generator=n,d._diameter=o,d._length=a,d._sectionVectors=[],d._sectionNormalVectors=[];for(var p=0;p<d._sectionPolygonPointsCount;p++)d._sectionVectors[p]=u.e.Zero(),d._sectionNormalVectors[p]=u.e.Zero();return d._createMesh(),d}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"TrailMesh"},t.prototype._createMesh=function(){var e=new ft.a,n=[],i=[],o=[],a=u.e.Zero();a=this._generator instanceof Dt.a&&this._generator._boundingInfo?this._generator._boundingInfo.boundingBox.centerWorld:this._generator.position;for(var s=2*Math.PI/this._sectionPolygonPointsCount,d=0;d<this._sectionPolygonPointsCount;d++)n.push(a.x+Math.cos(d*s)*this._diameter,a.y+Math.sin(d*s)*this._diameter,a.z);for(d=1;d<=this._length;d++){for(var p=0;p<this._sectionPolygonPointsCount;p++)n.push(a.x+Math.cos(p*s)*this._diameter,a.y+Math.sin(p*s)*this._diameter,a.z);var b=n.length/3-2*this._sectionPolygonPointsCount;for(p=0;p<this._sectionPolygonPointsCount-1;p++)o.push(b+p,b+p+this._sectionPolygonPointsCount,b+p+this._sectionPolygonPointsCount+1),o.push(b+p,b+p+this._sectionPolygonPointsCount+1,b+p+1);o.push(b+this._sectionPolygonPointsCount-1,b+this._sectionPolygonPointsCount-1+this._sectionPolygonPointsCount,b+this._sectionPolygonPointsCount),o.push(b+this._sectionPolygonPointsCount-1,b+this._sectionPolygonPointsCount,b)}ft.a.ComputeNormals(n,o,i),e.positions=n,e.normals=i,e.indices=o,e.applyToMesh(this,!0),this._autoStart&&this.start()},t.prototype.start=function(){var e=this;this._running||(this._running=!0,this._beforeRenderObserver=this.getScene().onBeforeRenderObservable.add(function(){e.update()}))},t.prototype.stop=function(){this._beforeRenderObserver&&this._running&&(this._running=!1,this.getScene().onBeforeRenderObservable.remove(this._beforeRenderObserver))},t.prototype.update=function(){var e=this.getVerticesData(Oe.b.PositionKind),n=this.getVerticesData(Oe.b.NormalKind),i=this._generator.getWorldMatrix();if(e&&n){for(var o=3*this._sectionPolygonPointsCount;o<e.length;o++)e[o-3*this._sectionPolygonPointsCount]=e[o]-n[o]/this._length*this._diameter;for(o=3*this._sectionPolygonPointsCount;o<n.length;o++)n[o-3*this._sectionPolygonPointsCount]=n[o];var a=e.length-3*this._sectionPolygonPointsCount,s=2*Math.PI/this._sectionPolygonPointsCount;for(o=0;o<this._sectionPolygonPointsCount;o++)this._sectionVectors[o].copyFromFloats(Math.cos(o*s)*this._diameter,Math.sin(o*s)*this._diameter,0),this._sectionNormalVectors[o].copyFromFloats(Math.cos(o*s),Math.sin(o*s),0),u.e.TransformCoordinatesToRef(this._sectionVectors[o],i,this._sectionVectors[o]),u.e.TransformNormalToRef(this._sectionNormalVectors[o],i,this._sectionNormalVectors[o]);for(o=0;o<this._sectionPolygonPointsCount;o++)e[a+3*o]=this._sectionVectors[o].x,e[a+3*o+1]=this._sectionVectors[o].y,e[a+3*o+2]=this._sectionVectors[o].z,n[a+3*o]=this._sectionNormalVectors[o].x,n[a+3*o+1]=this._sectionNormalVectors[o].y,n[a+3*o+2]=this._sectionNormalVectors[o].z;this.updateVerticesData(Oe.b.PositionKind,e,!0,!1),this.updateVerticesData(Oe.b.NormalKind,n,!0,!1)}},t.prototype.clone=function(e,n){return e===void 0&&(e=""),new t(e,n===void 0?this._generator:n,this.getScene(),this._diameter,this._length,this._autoStart)},t.prototype.serialize=function(e){r.prototype.serialize.call(this,e)},t.Parse=function(e,n){return new t(e.name,e._generator,n,e._diameter,e._length,e._autoStart)},t}(De.a),Em=f(151),So=f(98),Ao=f(82);ft.a.CreateDisc=function(r){var t=new Array,e=new Array,n=new Array,i=new Array,o=r.radius||.5,a=r.tessellation||64,s=r.arc&&(r.arc<=0||r.arc>1)?1:r.arc||1,d=r.sideOrientation===0?0:r.sideOrientation||ft.a.DEFAULTSIDE;t.push(0,0,0),i.push(.5,.5);for(var p=2*Math.PI*s,b=s===1?p/a:p/(a-1),P=0,O=0;O<a;O++){var B=Math.cos(P),F=Math.sin(P),z=(B+1)/2,J=(1-F)/2;t.push(o*B,o*F,0),i.push(z,J),P+=b}s===1&&(t.push(t[3],t[4],t[5]),i.push(i[2],i[3]));for(var ie=t.length/3,se=1;se<ie-1;se++)e.push(se+1,0,se);ft.a.ComputeNormals(t,e,n),ft.a._ComputeSides(d,t,e,n,i,r.frontUVs,r.backUVs);var ce=new ft.a;return ce.indices=e,ce.positions=t,ce.normals=n,ce.uvs=i,ce},De.a.CreateDisc=function(r,t,e,n,i,o){n===void 0&&(n=null);var a={radius:t,tessellation:e,sideOrientation:o,updatable:i};return Ta.CreateDisc(r,a,n)};var Ta=function(){function r(){}return r.CreateDisc=function(t,e,n){n===void 0&&(n=null);var i=new De.a(t,n);return e.sideOrientation=De.a._GetDefaultSideOrientation(e.sideOrientation),i._originalBuilderSideOrientation=e.sideOrientation,ft.a.CreateDisc(e).applyToMesh(i,e.updatable),i},r}();ft.a.CreateTiledBox=function(r){for(var t=r.faceUV||new Array(6),e=r.faceColors,n=r.pattern||De.a.NO_FLIP,i=r.width||r.size||1,o=r.height||r.size||1,a=r.depth||r.size||1,s=r.tileWidth||r.tileSize||1,d=r.tileHeight||r.tileSize||1,p=r.alignHorizontal||0,b=r.alignVertical||0,P=r.sideOrientation===0?0:r.sideOrientation||ft.a.DEFAULTSIDE,O=0;O<6;O++)t[O]===void 0&&(t[O]=new u.f(0,0,1,1)),e&&e[O]===void 0&&(e[O]=new M.b(1,1,1,1));var B=i/2,F=o/2,z=a/2,J=[];for(O=0;O<2;O++)J[O]=ft.a.CreateTiledPlane({pattern:n,tileWidth:s,tileHeight:d,width:i,height:o,alignVertical:b,alignHorizontal:p,sideOrientation:P});for(O=2;O<4;O++)J[O]=ft.a.CreateTiledPlane({pattern:n,tileWidth:s,tileHeight:d,width:a,height:o,alignVertical:b,alignHorizontal:p,sideOrientation:P});var ie=b;for(b===De.a.BOTTOM?ie=De.a.TOP:b===De.a.TOP&&(ie=De.a.BOTTOM),O=4;O<6;O++)J[O]=ft.a.CreateTiledPlane({pattern:n,tileWidth:s,tileHeight:d,width:i,height:a,alignVertical:ie,alignHorizontal:p,sideOrientation:P});var se=[],ce=[],ue=[],fe=[],ve=[],Te=[],Re=[],Ae=[],Ee=0,Se=0,Le=0;for(O=0;O<6;O++){Ee=J[O].positions.length,Te[O]=[],Re[O]=[];for(var Ce=0;Ce<Ee/3;Ce++)Te[O].push(new u.e(J[O].positions[3*Ce],J[O].positions[3*Ce+1],J[O].positions[3*Ce+2])),Re[O].push(new u.e(J[O].normals[3*Ce],J[O].normals[3*Ce+1],J[O].normals[3*Ce+2]));Se=J[O].uvs.length,Ae[O]=[];for(var Ne=0;Ne<Se;Ne+=2)Ae[O][Ne]=t[O].x+(t[O].z-t[O].x)*J[O].uvs[Ne],Ae[O][Ne+1]=t[O].y+(t[O].w-t[O].y)*J[O].uvs[Ne+1];if(ue=ue.concat(Ae[O]),fe=fe.concat(J[O].indices.map(function(Ve){return Ve+Le})),Le+=Te[O].length,e)for(var Ie=0;Ie<4;Ie++)ve.push(e[O].r,e[O].g,e[O].b,e[O].a)}var Fe=new u.e(0,0,z),Ye=u.a.RotationY(Math.PI);se=Te[0].map(function(Ve){return u.e.TransformNormal(Ve,Ye).add(Fe)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[]),ce=Re[0].map(function(Ve){return u.e.TransformNormal(Ve,Ye)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[]),se=se.concat(Te[1].map(function(Ve){return Ve.subtract(Fe)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[])),ce=ce.concat(Re[1].map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[]));var tt=new u.e(B,0,0),it=u.a.RotationY(-Math.PI/2);se=se.concat(Te[2].map(function(Ve){return u.e.TransformNormal(Ve,it).add(tt)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[])),ce=ce.concat(Re[2].map(function(Ve){return u.e.TransformNormal(Ve,it)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[]));var lt=u.a.RotationY(Math.PI/2);se=se.concat(Te[3].map(function(Ve){return u.e.TransformNormal(Ve,lt).subtract(tt)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[])),ce=ce.concat(Re[3].map(function(Ve){return u.e.TransformNormal(Ve,lt)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[]));var Qe=new u.e(0,F,0),ot=u.a.RotationX(Math.PI/2);se=se.concat(Te[4].map(function(Ve){return u.e.TransformNormal(Ve,ot).add(Qe)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[])),ce=ce.concat(Re[4].map(function(Ve){return u.e.TransformNormal(Ve,ot)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[]));var rt=u.a.RotationX(-Math.PI/2);se=se.concat(Te[5].map(function(Ve){return u.e.TransformNormal(Ve,rt).subtract(Qe)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[])),ce=ce.concat(Re[5].map(function(Ve){return u.e.TransformNormal(Ve,rt)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[])),ft.a._ComputeSides(P,se,fe,ce,ue);var Ze=new ft.a;if(Ze.indices=fe,Ze.positions=se,Ze.normals=ce,Ze.uvs=ue,e){var dt=P===ft.a.DOUBLESIDE?ve.concat(ve):ve;Ze.colors=dt}return Ze};var pd=function(){function r(){}return r.CreateTiledBox=function(t,e,n){n===void 0&&(n=null);var i=new De.a(t,n);return e.sideOrientation=De.a._GetDefaultSideOrientation(e.sideOrientation),i._originalBuilderSideOrientation=e.sideOrientation,ft.a.CreateTiledBox(e).applyToMesh(i,e.updatable),i},r}();ft.a.CreateTorusKnot=function(r){var t,e,n=new Array,i=new Array,o=new Array,a=new Array,s=r.radius||2,d=r.tube||.5,p=r.radialSegments||32,b=r.tubularSegments||32,P=r.p||2,O=r.q||3,B=r.sideOrientation===0?0:r.sideOrientation||ft.a.DEFAULTSIDE,F=function(Ne){var Ie=Math.cos(Ne),Fe=Math.sin(Ne),Ye=O/P*Ne,tt=Math.cos(Ye),it=s*(2+tt)*.5*Ie,lt=s*(2+tt)*Fe*.5,Qe=s*Math.sin(Ye)*.5;return new u.e(it,lt,Qe)};for(t=0;t<=p;t++){var z=t%p/p*2*P*Math.PI,J=F(z),ie=F(z+.01),se=ie.subtract(J),ce=ie.add(J),ue=u.e.Cross(se,ce);for(ce=u.e.Cross(ue,se),ue.normalize(),ce.normalize(),e=0;e<b;e++){var fe=e%b/b*2*Math.PI,ve=-d*Math.cos(fe),Te=d*Math.sin(fe);i.push(J.x+ve*ce.x+Te*ue.x),i.push(J.y+ve*ce.y+Te*ue.y),i.push(J.z+ve*ce.z+Te*ue.z),a.push(t/p),a.push(e/b)}}for(t=0;t<p;t++)for(e=0;e<b;e++){var Re=(e+1)%b,Ae=t*b+e,Ee=(t+1)*b+e,Se=(t+1)*b+Re,Le=t*b+Re;n.push(Le),n.push(Ee),n.push(Ae),n.push(Le),n.push(Se),n.push(Ee)}ft.a.ComputeNormals(i,n,o),ft.a._ComputeSides(B,i,n,o,a,r.frontUVs,r.backUVs);var Ce=new ft.a;return Ce.indices=n,Ce.positions=i,Ce.normals=o,Ce.uvs=a,Ce},De.a.CreateTorusKnot=function(r,t,e,n,i,o,a,s,d,p){var b={radius:t,tube:e,radialSegments:n,tubularSegments:i,p:o,q:a,sideOrientation:p,updatable:d};return Tc.CreateTorusKnot(r,b,s)};var Tc=function(){function r(){}return r.CreateTorusKnot=function(t,e,n){var i=new De.a(t,n);return e.sideOrientation=De.a._GetDefaultSideOrientation(e.sideOrientation),i._originalBuilderSideOrientation=e.sideOrientation,ft.a.CreateTorusKnot(e).applyToMesh(i,e.updatable),i},r}(),Sm=function(r){function t(e,n){var i=r.call(this,e.x,e.y)||this;return i.index=n,i}return Object(c.d)(t,r),t}(u.d),Ec=function(){function r(){this.elements=new Array}return r.prototype.add=function(t){var e=this,n=new Array;return t.forEach(function(i){var o=new Sm(i,e.elements.length);n.push(o),e.elements.push(o)}),n},r.prototype.computeBounds=function(){var t=new u.d(this.elements[0].x,this.elements[0].y),e=new u.d(this.elements[0].x,this.elements[0].y);return this.elements.forEach(function(n){n.x<t.x?t.x=n.x:n.x>e.x&&(e.x=n.x),n.y<t.y?t.y=n.y:n.y>e.y&&(e.y=n.y)}),{min:t,max:e,width:e.x-t.x,height:e.y-t.y}},r}(),Am=function(){function r(){}return r.Rectangle=function(t,e,n,i){return[new u.d(t,e),new u.d(n,e),new u.d(n,i),new u.d(t,i)]},r.Circle=function(t,e,n,i){e===void 0&&(e=0),n===void 0&&(n=0),i===void 0&&(i=32);for(var o=new Array,a=0,s=2*Math.PI/i,d=0;d<i;d++)o.push(new u.d(e+Math.cos(a)*t,n+Math.sin(a)*t)),a-=s;return o},r.Parse=function(t){var e,n=t.split(/[^-+eE\.\d]+/).map(parseFloat).filter(function(o){return!isNaN(o)}),i=[];for(e=0;e<(2147483646&n.length);e+=2)i.push(new u.d(n[e],n[e+1]));return i},r.StartingAt=function(t,e){return qe.f.StartingAt(t,e)},r}(),_d=function(){function r(t,e,n,i){var o;i===void 0&&(i=earcut),this._points=new Ec,this._outlinepoints=new Ec,this._holes=new Array,this._epoints=new Array,this._eholes=new Array,this.bjsEarcut=i,this._name=t,this._scene=n||Ue.a.LastCreatedScene,o=e instanceof qe.f?e.getPoints():e,this._addToepoint(o),this._points.add(o),this._outlinepoints.add(o),this.bjsEarcut===void 0&&l.a.Warn("Earcut was not found, the polygon will not be built.")}return r.prototype._addToepoint=function(t){for(var e=0,n=t;e<n.length;e++){var i=n[e];this._epoints.push(i.x,i.y)}},r.prototype.addHole=function(t){this._points.add(t);var e=new Ec;return e.add(t),this._holes.push(e),this._eholes.push(this._epoints.length/2),this._addToepoint(t),this},r.prototype.build=function(t,e){t===void 0&&(t=!1),e===void 0&&(e=0);var n=new De.a(this._name,this._scene),i=this.buildVertexData(e);return n.setVerticesData(Oe.b.PositionKind,i.positions,t),n.setVerticesData(Oe.b.NormalKind,i.normals,t),n.setVerticesData(Oe.b.UVKind,i.uvs,t),n.setIndices(i.indices),n},r.prototype.buildVertexData=function(t){var e=this;t===void 0&&(t=0);var n=new ft.a,i=new Array,o=new Array,a=new Array,s=this._points.computeBounds();this._points.elements.forEach(function(J){i.push(0,1,0),o.push(J.x,0,J.y),a.push((J.x-s.min.x)/s.width,(J.y-s.min.y)/s.height)});for(var d=new Array,p=this.bjsEarcut(this._epoints,this._eholes,2),b=0;b<p.length;b++)d.push(p[b]);if(t>0){var P=o.length/3;this._points.elements.forEach(function(J){i.push(0,-1,0),o.push(J.x,-t,J.y),a.push(1-(J.x-s.min.x)/s.width,1-(J.y-s.min.y)/s.height)});var O=d.length;for(b=0;b<O;b+=3){var B=d[b+0],F=d[b+1],z=d[b+2];d.push(z+P),d.push(F+P),d.push(B+P)}this.addSide(o,i,a,d,s,this._outlinepoints,t,!1),this._holes.forEach(function(J){e.addSide(o,i,a,d,s,J,t,!0)})}return n.indices=d,n.positions=o,n.normals=i,n.uvs=a,n},r.prototype.addSide=function(t,e,n,i,o,a,s,d){for(var p=t.length/3,b=0,P=0;P<a.elements.length;P++){var O,B=a.elements[P];O=P+1>a.elements.length-1?a.elements[0]:a.elements[P+1],t.push(B.x,0,B.y),t.push(B.x,-s,B.y),t.push(O.x,0,O.y),t.push(O.x,-s,O.y);var F=new u.e(B.x,0,B.y),z=new u.e(O.x,0,O.y).subtract(F),J=new u.e(0,1,0),ie=u.e.Cross(z,J);ie=ie.normalize(),n.push(b/o.width,0),n.push(b/o.width,1),b+=z.length(),n.push(b/o.width,0),n.push(b/o.width,1),d?(e.push(ie.x,ie.y,ie.z),e.push(ie.x,ie.y,ie.z),e.push(ie.x,ie.y,ie.z),e.push(ie.x,ie.y,ie.z),i.push(p),i.push(p+2),i.push(p+1),i.push(p+1),i.push(p+2),i.push(p+3)):(e.push(-ie.x,-ie.y,-ie.z),e.push(-ie.x,-ie.y,-ie.z),e.push(-ie.x,-ie.y,-ie.z),e.push(-ie.x,-ie.y,-ie.z),i.push(p),i.push(p+1),i.push(p+2),i.push(p+1),i.push(p+3),i.push(p+2)),p+=4}},r}();ft.a.CreatePolygon=function(r,t,e,n,i,o,a){for(var s=e||new Array(3),d=n,p=[],b=a||!1,P=0;P<3;P++)s[P]===void 0&&(s[P]=new u.f(0,0,1,1)),d&&d[P]===void 0&&(d[P]=new M.b(1,1,1,1));var O=r.getVerticesData(Oe.b.PositionKind),B=r.getVerticesData(Oe.b.NormalKind),F=r.getVerticesData(Oe.b.UVKind),z=r.getIndices(),J=O.length/9,ie=0,se=0,ce=0,ue=0,fe=[0];if(b)for(var ve=J;ve<O.length/3;ve+=4)se=O[3*(ve+2)]-O[3*ve],ce=O[3*(ve+2)+2]-O[3*ve+2],ue+=Math.sqrt(se*se+ce*ce),fe.push(ue);ve=0;for(var Te=0,Re=0;Re<B.length;Re+=3)Math.abs(B[Re+1])<.001&&(Te=1),Math.abs(B[Re+1]-1)<.001&&(Te=0),Math.abs(B[Re+1]+1)<.001&&(Te=2),ve=Re/3,Te===1?(ie=ve-J,F[2*ve]=ie%4<1.5?b?s[Te].x+(s[Te].z-s[Te].x)*fe[Math.floor(ie/4)]/ue:s[Te].x:b?s[Te].x+(s[Te].z-s[Te].x)*fe[Math.floor(ie/4)+1]/ue:s[Te].z,F[2*ve+1]=ie%2==0?s[Te].w:s[Te].y):(F[2*ve]=(1-F[2*ve])*s[Te].x+F[2*ve]*s[Te].z,F[2*ve+1]=(1-F[2*ve+1])*s[Te].y+F[2*ve+1]*s[Te].w),d&&p.push(d[Te].r,d[Te].g,d[Te].b,d[Te].a);ft.a._ComputeSides(t,O,z,B,F,i,o);var Ae=new ft.a;if(Ae.indices=z,Ae.positions=O,Ae.normals=B,Ae.uvs=F,d){var Ee=t===ft.a.DOUBLESIDE?p.concat(p):p;Ae.colors=Ee}return Ae},De.a.CreatePolygon=function(r,t,e,n,i,o,a){a===void 0&&(a=earcut);var s={shape:t,holes:n,updatable:i,sideOrientation:o};return Po.CreatePolygon(r,s,e,a)},De.a.ExtrudePolygon=function(r,t,e,n,i,o,a,s){s===void 0&&(s=earcut);var d={shape:t,holes:i,depth:e,updatable:o,sideOrientation:a};return Po.ExtrudePolygon(r,d,n,s)};var Po=function(){function r(){}return r.CreatePolygon=function(t,e,n,i){n===void 0&&(n=null),i===void 0&&(i=earcut),e.sideOrientation=De.a._GetDefaultSideOrientation(e.sideOrientation);for(var o=e.shape,a=e.holes||[],s=e.depth||0,d=[],p=[],b=0;b<o.length;b++)d[b]=new u.d(o[b].x,o[b].z);d[0].equalsWithEpsilon(d[d.length-1],1e-8)&&d.pop();for(var P=new _d(t,d,n||te.a.LastCreatedScene,i),O=0;O<a.length;O++){p=[];for(var B=0;B<a[O].length;B++)p.push(new u.d(a[O][B].x,a[O][B].z));P.addHole(p)}var F=P.build(e.updatable,s);return F._originalBuilderSideOrientation=e.sideOrientation,ft.a.CreatePolygon(F,e.sideOrientation,e.faceUV,e.faceColors,e.frontUVs,e.backUVs,e.wrap).applyToMesh(F,e.updatable),F},r.ExtrudePolygon=function(t,e,n,i){return n===void 0&&(n=null),i===void 0&&(i=earcut),r.CreatePolygon(t,e,n,i)},r}();De.a.CreateLathe=function(r,t,e,n,i,o,a){var s={shape:t,radius:e,tessellation:n,sideOrientation:a,updatable:o};return Sc.CreateLathe(r,s,i)};var Sc=function(){function r(){}return r.CreateLathe=function(t,e,n){n===void 0&&(n=null);var i,o=e.arc?e.arc<=0||e.arc>1?1:e.arc:1,a=e.closed===void 0||e.closed,s=e.shape,d=e.radius||1,p=e.tessellation||64,b=e.clip||0,P=e.updatable,O=De.a._GetDefaultSideOrientation(e.sideOrientation),B=e.cap||De.a.NO_CAP,F=2*Math.PI,z=new Array,J=e.invertUV||!1,ie=0,se=0,ce=F/p*o,ue=new Array;for(ie=0;ie<=p-b;ie++){for(ue=[],B!=De.a.CAP_START&&B!=De.a.CAP_ALL||(ue.push(new u.e(0,s[0].y,0)),ue.push(new u.e(Math.cos(ie*ce)*s[0].x*d,s[0].y,Math.sin(ie*ce)*s[0].x*d))),se=0;se<s.length;se++)i=new u.e(Math.cos(ie*ce)*s[se].x*d,s[se].y,Math.sin(ie*ce)*s[se].x*d),ue.push(i);B!=De.a.CAP_END&&B!=De.a.CAP_ALL||(ue.push(new u.e(Math.cos(ie*ce)*s[s.length-1].x*d,s[s.length-1].y,Math.sin(ie*ce)*s[s.length-1].x*d)),ue.push(new u.e(0,s[s.length-1].y,0))),z.push(ue)}return Ao.a.CreateRibbon(t,{pathArray:z,closeArray:a,sideOrientation:O,updatable:P,invertUV:J,frontUVs:e.frontUVs,backUVs:e.backUVs},n)},r}();ft.a.CreateTiledPlane=function(r){var t=r.pattern||De.a.NO_FLIP,e=r.tileWidth||r.tileSize||1,n=r.tileHeight||r.tileSize||1,i=r.alignHorizontal||0,o=r.alignVertical||0,a=r.width||r.size||1,s=Math.floor(a/e),d=a-s*e,p=r.height||r.size||1,b=Math.floor(p/n),P=p-b*n,O=e*s/2,B=n*b/2,F=0,z=0,J=0,ie=0,se=0,ce=0;if(d>0||P>0){switch(J=-O,ie=-B,se=O,ce=B,i){case De.a.CENTER:J-=d/=2,se+=d;break;case De.a.LEFT:se+=d,F=-d/2;break;case De.a.RIGHT:J-=d,F=d/2}switch(o){case De.a.CENTER:ie-=P/=2,ce+=P;break;case De.a.BOTTOM:ce+=P,z=-P/2;break;case De.a.TOP:ie-=P,z=P/2}}var ue=[],fe=[],ve=[];ve[0]=[0,0,1,0,1,1,0,1],ve[1]=[0,0,1,0,1,1,0,1],t!==De.a.ROTATE_TILE&&t!==De.a.ROTATE_ROW||(ve[1]=[1,1,0,1,0,0,1,0]),t!==De.a.FLIP_TILE&&t!==De.a.FLIP_ROW||(ve[1]=[1,0,0,0,0,1,1,1]),t!==De.a.FLIP_N_ROTATE_TILE&&t!==De.a.FLIP_N_ROTATE_ROW||(ve[1]=[0,1,1,1,1,0,0,0]);for(var Te=[],Re=[],Ae=[],Ee=0,Se=0;Se<b;Se++)for(var Le=0;Le<s;Le++)ue.push(Le*e-O+F,Se*n-B+z,0),ue.push((Le+1)*e-O+F,Se*n-B+z,0),ue.push((Le+1)*e-O+F,(Se+1)*n-B+z,0),ue.push(Le*e-O+F,(Se+1)*n-B+z,0),Ae.push(Ee,Ee+1,Ee+3,Ee+1,Ee+2,Ee+3),Te=t===De.a.FLIP_TILE||t===De.a.ROTATE_TILE||t===De.a.FLIP_N_ROTATE_TILE?Te.concat(ve[(Le%2+Se%2)%2]):t===De.a.FLIP_ROW||t===De.a.ROTATE_ROW||t===De.a.FLIP_N_ROTATE_ROW?Te.concat(ve[Se%2]):Te.concat(ve[0]),Re.push(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),fe.push(0,0,-1,0,0,-1,0,0,-1,0,0,-1),Ee+=4;if(d>0||P>0){var Ce,Ne,Ie,Fe,Ye=P>0&&(o===De.a.CENTER||o===De.a.TOP),tt=P>0&&(o===De.a.CENTER||o===De.a.BOTTOM),it=d>0&&(i===De.a.CENTER||i===De.a.RIGHT),lt=d>0&&(i===De.a.CENTER||i===De.a.LEFT),Qe=[];if(Ye&&it&&(ue.push(J+F,ie+z,0),ue.push(-O+F,ie+z,0),ue.push(-O+F,ie+P+z,0),ue.push(J+F,ie+P+z,0),Ae.push(Ee,Ee+1,Ee+3,Ee+1,Ee+2,Ee+3),Ee+=4,Qe=[Ce=1-d/e,Ne=1-P/n,Ie=1,Ne,Ie,Fe=1,Ce,Fe],t===De.a.ROTATE_ROW&&(Qe=[1-Ce,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-Ce,1-Fe]),t===De.a.FLIP_ROW&&(Qe=[1-Ce,Ne,1-Ie,Ne,1-Ie,Fe,1-Ce,Fe]),t===De.a.FLIP_N_ROTATE_ROW&&(Qe=[Ce,1-Ne,Ie,1-Ne,Ie,1-Fe,Ce,1-Fe]),Te=Te.concat(Qe),Re.push(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),fe.push(0,0,-1,0,0,-1,0,0,-1,0,0,-1)),Ye&&lt&&(ue.push(O+F,ie+z,0),ue.push(se+F,ie+z,0),ue.push(se+F,ie+P+z,0),ue.push(O+F,ie+P+z,0),Ae.push(Ee,Ee+1,Ee+3,Ee+1,Ee+2,Ee+3),Ee+=4,Qe=[Ce=0,Ne=1-P/n,Ie=d/e,Ne,Ie,Fe=1,Ce,Fe],(t===De.a.ROTATE_ROW||t===De.a.ROTATE_TILE&&s%2==0)&&(Qe=[1-Ce,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-Ce,1-Fe]),(t===De.a.FLIP_ROW||t===De.a.FLIP_TILE&&s%2==0)&&(Qe=[1-Ce,Ne,1-Ie,Ne,1-Ie,Fe,1-Ce,Fe]),(t===De.a.FLIP_N_ROTATE_ROW||t===De.a.FLIP_N_ROTATE_TILE&&s%2==0)&&(Qe=[Ce,1-Ne,Ie,1-Ne,Ie,1-Fe,Ce,1-Fe]),Te=Te.concat(Qe),Re.push(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),fe.push(0,0,-1,0,0,-1,0,0,-1,0,0,-1)),tt&&it&&(ue.push(J+F,B+z,0),ue.push(-O+F,B+z,0),ue.push(-O+F,ce+z,0),ue.push(J+F,ce+z,0),Ae.push(Ee,Ee+1,Ee+3,Ee+1,Ee+2,Ee+3),Ee+=4,Qe=[Ce=1-d/e,Ne=0,Ie=1,Ne,Ie,Fe=P/n,Ce,Fe],(t===De.a.ROTATE_ROW&&b%2==1||t===De.a.ROTATE_TILE&&b%1==0)&&(Qe=[1-Ce,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-Ce,1-Fe]),(t===De.a.FLIP_ROW&&b%2==1||t===De.a.FLIP_TILE&&b%2==0)&&(Qe=[1-Ce,Ne,1-Ie,Ne,1-Ie,Fe,1-Ce,Fe]),(t===De.a.FLIP_N_ROTATE_ROW&&b%2==1||t===De.a.FLIP_N_ROTATE_TILE&&b%2==0)&&(Qe=[Ce,1-Ne,Ie,1-Ne,Ie,1-Fe,Ce,1-Fe]),Te=Te.concat(Qe),Re.push(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),fe.push(0,0,-1,0,0,-1,0,0,-1,0,0,-1)),tt&&lt&&(ue.push(O+F,B+z,0),ue.push(se+F,B+z,0),ue.push(se+F,ce+z,0),ue.push(O+F,ce+z,0),Ae.push(Ee,Ee+1,Ee+3,Ee+1,Ee+2,Ee+3),Ee+=4,Qe=[Ce=0,Ne=0,Ie=d/e,Ne,Ie,Fe=P/n,Ce,Fe],(t===De.a.ROTATE_ROW&&b%2==1||t===De.a.ROTATE_TILE&&(b+s)%2==1)&&(Qe=[1-Ce,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-Ce,1-Fe]),(t===De.a.FLIP_ROW&&b%2==1||t===De.a.FLIP_TILE&&(b+s)%2==1)&&(Qe=[1-Ce,Ne,1-Ie,Ne,1-Ie,Fe,1-Ce,Fe]),(t===De.a.FLIP_N_ROTATE_ROW&&b%2==1||t===De.a.FLIP_N_ROTATE_TILE&&(b+s)%2==1)&&(Qe=[Ce,1-Ne,Ie,1-Ne,Ie,1-Fe,Ce,1-Fe]),Te=Te.concat(Qe),Re.push(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),fe.push(0,0,-1,0,0,-1,0,0,-1,0,0,-1)),Ye){var ot=[];for(Ce=0,Ne=1-P/n,Ie=1,Fe=1,ot[0]=[Ce,Ne,Ie,Ne,Ie,Fe,Ce,Fe],ot[1]=[Ce,Ne,Ie,Ne,Ie,Fe,Ce,Fe],t!==De.a.ROTATE_TILE&&t!==De.a.ROTATE_ROW||(ot[1]=[1-Ce,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-Ce,1-Fe]),t!==De.a.FLIP_TILE&&t!==De.a.FLIP_ROW||(ot[1]=[1-Ce,Ne,1-Ie,Ne,1-Ie,Fe,1-Ce,Fe]),t!==De.a.FLIP_N_ROTATE_TILE&&t!==De.a.FLIP_N_ROTATE_ROW||(ot[1]=[Ce,1-Ne,Ie,1-Ne,Ie,1-Fe,Ce,1-Fe]),Le=0;Le<s;Le++)ue.push(Le*e-O+F,ie+z,0),ue.push((Le+1)*e-O+F,ie+z,0),ue.push((Le+1)*e-O+F,ie+P+z,0),ue.push(Le*e-O+F,ie+P+z,0),Ae.push(Ee,Ee+1,Ee+3,Ee+1,Ee+2,Ee+3),Ee+=4,Te=t===De.a.FLIP_TILE||t===De.a.ROTATE_TILE||t===De.a.FLIP_N_ROTATE_TILE?Te.concat(ot[(Le+1)%2]):t===De.a.FLIP_ROW||t===De.a.ROTATE_ROW||t===De.a.FLIP_N_ROTATE_ROW?Te.concat(ot[1]):Te.concat(ot[0]),Re.push(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),fe.push(0,0,-1,0,0,-1,0,0,-1,0,0,-1)}if(tt){var rt=[];for(Ce=0,Ne=0,Ie=1,Fe=P/n,rt[0]=[Ce,Ne,Ie,Ne,Ie,Fe,Ce,Fe],rt[1]=[Ce,Ne,Ie,Ne,Ie,Fe,Ce,Fe],t!==De.a.ROTATE_TILE&&t!==De.a.ROTATE_ROW||(rt[1]=[1-Ce,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-Ce,1-Fe]),t!==De.a.FLIP_TILE&&t!==De.a.FLIP_ROW||(rt[1]=[1-Ce,Ne,1-Ie,Ne,1-Ie,Fe,1-Ce,Fe]),t!==De.a.FLIP_N_ROTATE_TILE&&t!==De.a.FLIP_N_ROTATE_ROW||(rt[1]=[Ce,1-Ne,Ie,1-Ne,Ie,1-Fe,Ce,1-Fe]),Le=0;Le<s;Le++)ue.push(Le*e-O+F,ce-P+z,0),ue.push((Le+1)*e-O+F,ce-P+z,0),ue.push((Le+1)*e-O+F,ce+z,0),ue.push(Le*e-O+F,ce+z,0),Ae.push(Ee,Ee+1,Ee+3,Ee+1,Ee+2,Ee+3),Ee+=4,Te=t===De.a.FLIP_TILE||t===De.a.ROTATE_TILE||t===De.a.FLIP_N_ROTATE_TILE?Te.concat(rt[(Le+b)%2]):t===De.a.FLIP_ROW||t===De.a.ROTATE_ROW||t===De.a.FLIP_N_ROTATE_ROW?Te.concat(rt[b%2]):Te.concat(rt[0]),Re.push(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),fe.push(0,0,-1,0,0,-1,0,0,-1,0,0,-1)}if(it){var Ze=[];for(Ce=1-d/e,Ne=0,Ie=1,Fe=1,Ze[0]=[Ce,Ne,Ie,Ne,Ie,Fe,Ce,Fe],Ze[1]=[Ce,Ne,Ie,Ne,Ie,Fe,Ce,Fe],t!==De.a.ROTATE_TILE&&t!==De.a.ROTATE_ROW||(Ze[1]=[1-Ce,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-Ce,1-Fe]),t!==De.a.FLIP_TILE&&t!==De.a.FLIP_ROW||(Ze[1]=[1-Ce,Ne,1-Ie,Ne,1-Ie,Fe,1-Ce,Fe]),t!==De.a.FLIP_N_ROTATE_TILE&&t!==De.a.FLIP_N_ROTATE_ROW||(Ze[1]=[Ce,1-Ne,Ie,1-Ne,Ie,1-Fe,Ce,1-Fe]),Se=0;Se<b;Se++)ue.push(J+F,Se*n-B+z,0),ue.push(J+d+F,Se*n-B+z,0),ue.push(J+d+F,(Se+1)*n-B+z,0),ue.push(J+F,(Se+1)*n-B+z,0),Ae.push(Ee,Ee+1,Ee+3,Ee+1,Ee+2,Ee+3),Ee+=4,Te=t===De.a.FLIP_TILE||t===De.a.ROTATE_TILE||t===De.a.FLIP_N_ROTATE_TILE?Te.concat(Ze[(Se+1)%2]):t===De.a.FLIP_ROW||t===De.a.ROTATE_ROW||t===De.a.FLIP_N_ROTATE_ROW?Te.concat(Ze[Se%2]):Te.concat(Ze[0]),Re.push(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),fe.push(0,0,-1,0,0,-1,0,0,-1,0,0,-1)}if(lt){var dt=[];for(Ce=0,Ne=0,Ie=d/n,Fe=1,dt[0]=[Ce,Ne,Ie,Ne,Ie,Fe,Ce,Fe],dt[1]=[Ce,Ne,Ie,Ne,Ie,Fe,Ce,Fe],t!==De.a.ROTATE_TILE&&t!==De.a.ROTATE_ROW||(dt[1]=[1-Ce,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-Ce,1-Fe]),t!==De.a.FLIP_TILE&&t!==De.a.FLIP_ROW||(dt[1]=[1-Ce,Ne,1-Ie,Ne,1-Ie,Fe,1-Ce,Fe]),t!==De.a.FLIP_N_ROTATE_TILE&&t!==De.a.FLIP_N_ROTATE_ROW||(dt[1]=[Ce,1-Ne,Ie,1-Ne,Ie,1-Fe,Ce,1-Fe]),Se=0;Se<b;Se++)ue.push(se-d+F,Se*n-B+z,0),ue.push(se+F,Se*n-B+z,0),ue.push(se+F,(Se+1)*n-B+z,0),ue.push(se-d+F,(Se+1)*n-B+z,0),Ae.push(Ee,Ee+1,Ee+3,Ee+1,Ee+2,Ee+3),Ee+=4,Te=t===De.a.FLIP_TILE||t===De.a.ROTATE_TILE||t===De.a.FLIP_N_ROTATE_TILE?Te.concat(dt[(Se+s)%2]):t===De.a.FLIP_ROW||t===De.a.ROTATE_ROW||t===De.a.FLIP_N_ROTATE_ROW?Te.concat(dt[Se%2]):Te.concat(dt[0]),Re.push(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),fe.push(0,0,-1,0,0,-1,0,0,-1,0,0,-1)}}var Ve=r.sideOrientation===0?0:r.sideOrientation||ft.a.DEFAULTSIDE;ft.a._ComputeSides(Ve,ue,Ae,fe,Te,r.frontUVs,r.backUVs);var Je=new ft.a;Je.indices=Ae,Je.positions=ue,Je.normals=fe,Je.uvs=Te;var yt=Ve===ft.a.DOUBLESIDE?Re.concat(Re):Re;return Je.colors=yt,Je};var md=function(){function r(){}return r.CreateTiledPlane=function(t,e,n){n===void 0&&(n=null);var i=new De.a(t,n);return e.sideOrientation=De.a._GetDefaultSideOrientation(e.sideOrientation),i._originalBuilderSideOrientation=e.sideOrientation,ft.a.CreateTiledPlane(e).applyToMesh(i,e.updatable),i},r}();De.a.CreateTube=function(r,t,e,n,i,o,a,s,d,p){var b={path:t,radius:e,tessellation:n,radiusFunction:i,arc:1,cap:o,updatable:s,sideOrientation:d,instance:p};return Ac.CreateTube(r,b,a)};var Ac=function(){function r(){}return r.CreateTube=function(t,e,n){n===void 0&&(n=null);var i=e.path,o=e.instance,a=1;e.radius!==void 0?a=e.radius:o&&(a=o._creationDataStorage.radius);var s=e.tessellation||64,d=e.radiusFunction||null,p=e.cap||De.a.NO_CAP,b=e.invertUV||!1,P=e.updatable,O=De.a._GetDefaultSideOrientation(e.sideOrientation);e.arc=e.arc&&(e.arc<=0||e.arc>1)?1:e.arc||1;var B,F,z=function(ce,ue,fe,ve,Te,Re,Ae,Ee){for(var Se,Le,Ce,Ne,Ie=ue.getTangents(),Fe=ue.getNormals(),Ye=ue.getDistances(),tt=2*Math.PI/Te*Ee,it=Re||function(){return ve},lt=u.c.Matrix[0],Qe=Ae===De.a.NO_CAP||Ae===De.a.CAP_END?0:2,ot=0;ot<ce.length;ot++){Le=it(ot,Ye[ot]),Se=Array(),Ce=Fe[ot];for(var rt=0;rt<Te;rt++)u.a.RotationAxisToRef(Ie[ot],tt*rt,lt),Ne=Se[rt]?Se[rt]:u.e.Zero(),u.e.TransformCoordinatesToRef(Ce,lt,Ne),Ne.scaleInPlace(Le).addInPlace(ce[ot]),Se[rt]=Ne;fe[Qe]=Se,Qe++}var Ze=function(dt,Ve){for(var Je=Array(),yt=0;yt<dt;yt++)Je.push(ce[Ve]);return Je};switch(Ae){case De.a.NO_CAP:break;case De.a.CAP_START:fe[0]=Ze(Te,0),fe[1]=fe[2].slice(0);break;case De.a.CAP_END:fe[Qe]=fe[Qe-1].slice(0),fe[Qe+1]=Ze(Te,ce.length-1);break;case De.a.CAP_ALL:fe[0]=Ze(Te,0),fe[1]=fe[2].slice(0),fe[Qe]=fe[Qe-1].slice(0),fe[Qe+1]=Ze(Te,ce.length-1)}return fe};if(o){var J=o._creationDataStorage,ie=e.arc||J.arc;return F=z(i,B=J.path3D.update(i),J.pathArray,a,J.tessellation,d,J.cap,ie),o=Ao.a.CreateRibbon("",{pathArray:F,instance:o}),J.path3D=B,J.pathArray=F,J.arc=ie,J.radius=a,o}F=z(i,B=new qe.g(i),new Array,a,s,d,p=p<0||p>3?0:p,e.arc);var se=Ao.a.CreateRibbon(t,{pathArray:F,closePath:!0,closeArray:!1,updatable:P,sideOrientation:O,invertUV:b,frontUVs:e.frontUVs,backUVs:e.backUVs},n);return se._creationDataStorage.pathArray=F,se._creationDataStorage.path3D=B,se._creationDataStorage.tessellation=s,se._creationDataStorage.cap=p,se._creationDataStorage.arc=e.arc,se._creationDataStorage.radius=a,se},r}();ft.a.CreateIcoSphere=function(r){var t,e=r.sideOrientation||ft.a.DEFAULTSIDE,n=r.radius||1,i=r.flat===void 0||r.flat,o=r.subdivisions||4,a=r.radiusX||n,s=r.radiusY||n,d=r.radiusZ||n,p=(1+Math.sqrt(5))/2,b=[-1,p,-0,1,p,0,-1,-p,0,1,-p,0,0,-1,-p,0,1,-p,0,-1,p,0,1,p,p,0,1,p,0,-1,-p,0,1,-p,0,-1],P=[0,11,5,0,5,1,0,1,7,0,7,10,12,22,23,1,5,20,5,11,4,23,22,13,22,18,6,7,1,8,14,21,4,14,4,2,16,13,6,15,6,19,3,8,9,4,21,5,13,17,23,6,13,22,19,6,18,9,8,1],O=[0,1,2,3,4,5,6,7,8,9,10,11,0,2,3,3,3,4,7,8,9,9,10,11],B=[5,1,3,1,6,4,0,0,5,3,4,2,2,2,4,0,2,0,1,1,6,0,6,2,0,4,3,3,4,4,3,1,4,2,4,4,0,2,1,1,2,2,3,3,1,3,2,4],F=[0,0,0,0,1,0,0,1,1,0,0,0,1,1,0,0,1,1,1,0],z=new Array,J=new Array,ie=new Array,se=new Array,ce=0,ue=new Array(3),fe=new Array(3);for(t=0;t<3;t++)ue[t]=u.e.Zero(),fe[t]=u.d.Zero();for(var ve=0;ve<20;ve++){for(t=0;t<3;t++){var Te=P[3*ve+t];ue[t].copyFromFloats(b[3*O[Te]],b[3*O[Te]+1],b[3*O[Te]+2]),ue[t].normalize().scaleInPlace(n),fe[t].copyFromFloats(B[2*Te]*(138/1024)+60/1024+F[ve]*(-40/1024),B[2*Te+1]*(239/1024)+26/1024+F[ve]*(20/1024))}for(var Re=function(Le,Ce,Ne,Ie){var Fe,Ye=u.e.Lerp(ue[0],ue[2],Ce/o),tt=u.e.Lerp(ue[1],ue[2],Ce/o),it=o===Ce?ue[2]:u.e.Lerp(Ye,tt,Le/(o-Ce));if(it.normalize(),i){var lt=u.e.Lerp(ue[0],ue[2],Ie/o),Qe=u.e.Lerp(ue[1],ue[2],Ie/o);Fe=u.e.Lerp(lt,Qe,Ne/(o-Ie))}else Fe=new u.e(it.x,it.y,it.z);Fe.x/=a,Fe.y/=s,Fe.z/=d,Fe.normalize();var ot=u.d.Lerp(fe[0],fe[2],Ce/o),rt=u.d.Lerp(fe[1],fe[2],Ce/o),Ze=o===Ce?fe[2]:u.d.Lerp(ot,rt,Le/(o-Ce));J.push(it.x*a,it.y*s,it.z*d),ie.push(Fe.x,Fe.y,Fe.z),se.push(Ze.x,Ze.y),z.push(ce),ce++},Ae=0;Ae<o;Ae++)for(var Ee=0;Ee+Ae<o;Ee++)Re(Ee,Ae,Ee+1/3,Ae+1/3),Re(Ee+1,Ae,Ee+1/3,Ae+1/3),Re(Ee,Ae+1,Ee+1/3,Ae+1/3),Ee+Ae+1<o&&(Re(Ee+1,Ae,Ee+2/3,Ae+2/3),Re(Ee+1,Ae+1,Ee+2/3,Ae+2/3),Re(Ee,Ae+1,Ee+2/3,Ae+2/3))}ft.a._ComputeSides(e,J,z,ie,se,r.frontUVs,r.backUVs);var Se=new ft.a;return Se.indices=z,Se.positions=J,Se.normals=ie,Se.uvs=se,Se},De.a.CreateIcoSphere=function(r,t,e){return Pc.CreateIcoSphere(r,t,e)};var Pc=function(){function r(){}return r.CreateIcoSphere=function(t,e,n){n===void 0&&(n=null);var i=new De.a(t,n);return e.sideOrientation=De.a._GetDefaultSideOrientation(e.sideOrientation),i._originalBuilderSideOrientation=e.sideOrientation,ft.a.CreateIcoSphere(e).applyToMesh(i,e.updatable),i},r}();De.a.CreateDecal=function(r,t,e,n,i,o){var a={position:e,normal:n,size:i,angle:o};return Cc.CreateDecal(r,t,a)};var Cc=function(){function r(){}return r.CreateDecal=function(t,e,n){var i=e.getIndices(),o=e.getVerticesData(Oe.b.PositionKind),a=e.getVerticesData(Oe.b.NormalKind),s=n.position||u.e.Zero(),d=n.normal||u.e.Up(),p=n.size||u.e.One(),b=n.angle||0;if(!d){var P=new u.e(0,0,1),O=e.getScene().activeCamera,B=u.e.TransformCoordinates(P,O.getWorldMatrix());d=O.globalPosition.subtract(B)}var F=-Math.atan2(d.z,d.x)-Math.PI/2,z=Math.sqrt(d.x*d.x+d.z*d.z),J=Math.atan2(d.y,z),ie=u.a.RotationYawPitchRoll(F,J,b).multiply(u.a.Translation(s.x,s.y,s.z)),se=u.a.Invert(ie),ce=e.getWorldMatrix().multiply(se),ue=new ft.a;ue.indices=[],ue.positions=[],ue.normals=[],ue.uvs=[];for(var fe=0,ve=function(Ce){var Ne=new Is;if(!i||!o||!a)return Ne;var Ie=i[Ce];return Ne.position=new u.e(o[3*Ie],o[3*Ie+1],o[3*Ie+2]),Ne.position=u.e.TransformCoordinates(Ne.position,ce),Ne.normal=new u.e(a[3*Ie],a[3*Ie+1],a[3*Ie+2]),Ne.normal=u.e.TransformNormal(Ne.normal,ce),Ne},Te=function(Ce,Ne){if(Ce.length===0)return Ce;for(var Ie=.5*Math.abs(u.e.Dot(p,Ne)),Fe=function(Ve,Je){var yt=u.e.GetClipFactor(Ve.position,Je.position,Ne,Ie);return new Is(u.e.Lerp(Ve.position,Je.position,yt),u.e.Lerp(Ve.normal,Je.normal,yt))},Ye=new Array,tt=0;tt<Ce.length;tt+=3){var it,lt,Qe,ot=null,rt=null,Ze=null,dt=null;switch(((it=u.e.Dot(Ce[tt].position,Ne)-Ie>0)?1:0)+((lt=u.e.Dot(Ce[tt+1].position,Ne)-Ie>0)?1:0)+((Qe=u.e.Dot(Ce[tt+2].position,Ne)-Ie>0)?1:0)){case 0:Ye.push(Ce[tt]),Ye.push(Ce[tt+1]),Ye.push(Ce[tt+2]);break;case 1:if(it&&(ot=Ce[tt+1],rt=Ce[tt+2],Ze=Fe(Ce[tt],ot),dt=Fe(Ce[tt],rt)),lt){ot=Ce[tt],rt=Ce[tt+2],Ze=Fe(Ce[tt+1],ot),dt=Fe(Ce[tt+1],rt),Ye.push(Ze),Ye.push(rt.clone()),Ye.push(ot.clone()),Ye.push(rt.clone()),Ye.push(Ze.clone()),Ye.push(dt);break}Qe&&(ot=Ce[tt],rt=Ce[tt+1],Ze=Fe(Ce[tt+2],ot),dt=Fe(Ce[tt+2],rt)),ot&&rt&&Ze&&dt&&(Ye.push(ot.clone()),Ye.push(rt.clone()),Ye.push(Ze),Ye.push(dt),Ye.push(Ze.clone()),Ye.push(rt.clone()));break;case 2:it||(rt=Fe(ot=Ce[tt].clone(),Ce[tt+1]),Ze=Fe(ot,Ce[tt+2]),Ye.push(ot),Ye.push(rt),Ye.push(Ze)),lt||(rt=Fe(ot=Ce[tt+1].clone(),Ce[tt+2]),Ze=Fe(ot,Ce[tt]),Ye.push(ot),Ye.push(rt),Ye.push(Ze)),Qe||(rt=Fe(ot=Ce[tt+2].clone(),Ce[tt]),Ze=Fe(ot,Ce[tt+1]),Ye.push(ot),Ye.push(rt),Ye.push(Ze))}}return Ye},Re=0;Re<i.length;Re+=3){var Ae=new Array;if(Ae.push(ve(Re)),Ae.push(ve(Re+1)),Ae.push(ve(Re+2)),Ae=Te(Ae,new u.e(1,0,0)),Ae=Te(Ae,new u.e(-1,0,0)),Ae=Te(Ae,new u.e(0,1,0)),Ae=Te(Ae,new u.e(0,-1,0)),Ae=Te(Ae,new u.e(0,0,1)),(Ae=Te(Ae,new u.e(0,0,-1))).length!==0)for(var Ee=0;Ee<Ae.length;Ee++){var Se=Ae[Ee];ue.indices.push(fe),Se.position.toArray(ue.positions,3*fe),Se.normal.toArray(ue.normals,3*fe),ue.uvs.push(.5+Se.position.x/p.x),ue.uvs.push(.5+Se.position.y/p.y),fe++}}var Le=new De.a(t,e.getScene());return ue.applyToMesh(Le),Le.position=s.clone(),Le.rotation=new u.e(J,F,b),Le},r}();ft.a.CreateCapsule=function(r){r===void 0&&(r={subdivisions:2,tessellation:16,height:1,radius:.25,capSubdivisions:6});var t,e,n=Math.max(r.subdivisions?r.subdivisions:2,1),i=Math.max(r.tessellation?r.tessellation:16,3),o=Math.max(r.height?r.height:1,0),a=Math.max(r.radius?r.radius:.25,0),s=Math.max(r.capSubdivisions?r.capSubdivisions:6,1),d=i,p=n,b=Math.max(r.radiusTop?r.radiusTop:a,0),P=Math.max(r.radiusBottom?r.radiusBottom:a,0),O=o-(b+P),B=2*Math.PI,F=Math.max(r.topCapSubdivisions?r.topCapSubdivisions:s,1),z=Math.max(r.bottomCapSubdivisions?r.bottomCapSubdivisions:s,1),J=Math.acos((P-b)/o),ie=[],se=[],ce=[],ue=[],fe=0,ve=[],Te=.5*O,Re=.5*Math.PI,Ae=u.e.Zero(),Ee=u.e.Zero(),Se=Math.cos(J),Le=Math.sin(J),Ce=new u.d(b*Le,Te+b*Se).subtract(new u.d(P*Le,P*Se-Te)).length(),Ne=b*J+Ce+P*(Re-J),Ie=0;for(e=0;e<=F;e++){var Fe=[],Ye=Re-J*(e/F);Ie+=b*J/F;var tt=Math.cos(Ye),it=Math.sin(Ye),lt=tt*b;for(t=0;t<=d;t++){var Qe=(Ve=t/d)*B+0,ot=Math.sin(Qe),rt=Math.cos(Qe);Ee.x=lt*ot,Ee.y=Te+it*b,Ee.z=lt*rt,se.push(Ee.x,Ee.y,Ee.z),Ae.set(tt*ot,it,tt*rt),ce.push(Ae.x,Ae.y,Ae.z),ue.push(Ve,1-Ie/Ne),Fe.push(fe),fe++}ve.push(Fe)}var Ze=o-b-P+Se*b-Se*P,dt=Le*(P-b)/Ze;for(e=1;e<=p;e++){for(Fe=[],Ie+=Ce/p,lt=Le*(e*(P-b)/p+b),t=0;t<=d;t++)Qe=(Ve=t/d)*B+0,ot=Math.sin(Qe),rt=Math.cos(Qe),Ee.x=lt*ot,Ee.y=Te+Se*b-e*Ze/p,Ee.z=lt*rt,se.push(Ee.x,Ee.y,Ee.z),Ae.set(ot,dt,rt).normalize(),ce.push(Ae.x,Ae.y,Ae.z),ue.push(Ve,1-Ie/Ne),Fe.push(fe),fe++;ve.push(Fe)}for(e=1;e<=z;e++){for(Fe=[],Ye=Re-J-(Math.PI-J)*(e/z),Ie+=P*J/z,tt=Math.cos(Ye),it=Math.sin(Ye),lt=tt*P,t=0;t<=d;t++){var Ve;Qe=(Ve=t/d)*B+0,ot=Math.sin(Qe),rt=Math.cos(Qe),Ee.x=lt*ot,Ee.y=it*P-Te,Ee.z=lt*rt,se.push(Ee.x,Ee.y,Ee.z),Ae.set(tt*ot,it,tt*rt),ce.push(Ae.x,Ae.y,Ae.z),ue.push(Ve,1-Ie/Ne),Fe.push(fe),fe++}ve.push(Fe)}for(t=0;t<d;t++)for(e=0;e<F+p+z;e++){var Je=ve[e][t],yt=ve[e+1][t],Wt=ve[e+1][t+1],Nt=ve[e][t+1];ie.push(Je),ie.push(yt),ie.push(Nt),ie.push(yt),ie.push(Wt),ie.push(Nt)}if(ie=ie.reverse(),r.orientation&&!r.orientation.equals(u.e.Up())){var Qt=new u.a;r.orientation.clone().scale(.5*Math.PI).cross(u.e.Up()).toQuaternion().toRotationMatrix(Qt);for(var vt=u.e.Zero(),Jt=0;Jt<se.length;Jt+=3)vt.set(se[Jt],se[Jt+1],se[Jt+2]),u.e.TransformCoordinatesToRef(vt.clone(),Qt,vt),se[Jt]=vt.x,se[Jt+1]=vt.y,se[Jt+2]=vt.z}var Xt=new ft.a;return Xt.positions=se,Xt.normals=ce,Xt.uvs=ue,Xt.indices=ie,Xt},De.a.CreateCapsule=function(r,t,e){return xc.CreateCapsule(r,t,e)};var Co,xc=function(){function r(){}return r.CreateCapsule=function(t,e,n){e===void 0&&(e={orientation:u.e.Up(),subdivisions:2,tessellation:16,height:1,radius:.25,capSubdivisions:6});var i=new De.a(t,n);return ft.a.CreateCapsule(e).applyToMesh(i),i},r}(),Pm=function(){function r(){}return r.CreateBox=function(t,e,n){return n===void 0&&(n=null),Tr.a.CreateBox(t,e,n)},r.CreateTiledBox=function(t,e,n){return n===void 0&&(n=null),pd.CreateTiledBox(t,e,n)},r.CreateSphere=function(t,e,n){return n===void 0&&(n=null),Fn.a.CreateSphere(t,e,n)},r.CreateDisc=function(t,e,n){return n===void 0&&(n=null),Ta.CreateDisc(t,e,n)},r.CreateIcoSphere=function(t,e,n){return n===void 0&&(n=null),Pc.CreateIcoSphere(t,e,n)},r.CreateRibbon=function(t,e,n){return n===void 0&&(n=null),Ao.a.CreateRibbon(t,e,n)},r.CreateCylinder=function(t,e,n){return n===void 0&&(n=null),pi.a.CreateCylinder(t,e,n)},r.CreateTorus=function(t,e,n){return n===void 0&&(n=null),gr.CreateTorus(t,e,n)},r.CreateTorusKnot=function(t,e,n){return n===void 0&&(n=null),Tc.CreateTorusKnot(t,e,n)},r.CreateLineSystem=function(t,e,n){return cn.a.CreateLineSystem(t,e,n)},r.CreateLines=function(t,e,n){return n===void 0&&(n=null),cn.a.CreateLines(t,e,n)},r.CreateDashedLines=function(t,e,n){return n===void 0&&(n=null),cn.a.CreateDashedLines(t,e,n)},r.ExtrudeShape=function(t,e,n){return n===void 0&&(n=null),ca.a.ExtrudeShape(t,e,n)},r.ExtrudeShapeCustom=function(t,e,n){return n===void 0&&(n=null),ca.a.ExtrudeShapeCustom(t,e,n)},r.CreateLathe=function(t,e,n){return n===void 0&&(n=null),Sc.CreateLathe(t,e,n)},r.CreateTiledPlane=function(t,e,n){return n===void 0&&(n=null),md.CreateTiledPlane(t,e,n)},r.CreatePlane=function(t,e,n){return n===void 0&&(n=null),Rs.a.CreatePlane(t,e,n)},r.CreateGround=function(t,e,n){return n===void 0&&(n=null),Ui.CreateGround(t,e,n)},r.CreateTiledGround=function(t,e,n){return n===void 0&&(n=null),Ui.CreateTiledGround(t,e,n)},r.CreateGroundFromHeightMap=function(t,e,n,i){return i===void 0&&(i=null),Ui.CreateGroundFromHeightMap(t,e,n,i)},r.CreatePolygon=function(t,e,n,i){return n===void 0&&(n=null),i===void 0&&(i=earcut),Po.CreatePolygon(t,e,n,i)},r.ExtrudePolygon=function(t,e,n,i){return n===void 0&&(n=null),i===void 0&&(i=earcut),Po.ExtrudePolygon(t,e,n,i)},r.CreateTube=function(t,e,n){return n===void 0&&(n=null),Ac.CreateTube(t,e,n)},r.CreatePolyhedron=function(t,e,n){return n===void 0&&(n=null),ao.CreatePolyhedron(t,e,n)},r.CreateDecal=function(t,e,n){return Cc.CreateDecal(t,e,n)},r.CreateCapsule=function(t,e,n){return e===void 0&&(e={orientation:u.e.Up(),subdivisions:2,tessellation:16,height:1,radius:.25,capSubdivisions:6}),n===void 0&&(n=null),xc.CreateCapsule(t,e,n)},r}(),Cm=function(r,t,e){this.quality=r,this.distance=t,this.optimizeMesh=e},gd=function(){function r(){this.running=!1,this._simplificationArray=[]}return r.prototype.addTask=function(t){this._simplificationArray.push(t)},r.prototype.executeNext=function(){var t=this._simplificationArray.pop();t?(this.running=!0,this.runSimplification(t)):this.running=!1},r.prototype.runSimplification=function(t){var e=this;if(t.parallelProcessing)t.settings.forEach(function(i){e.getSimplifier(t).simplify(i,function(o){i.distance!==void 0&&t.mesh.addLODLevel(i.distance,o),o.isVisible=!0,i.quality===t.settings[t.settings.length-1].quality&&t.successCallback&&t.successCallback(),e.executeNext()})});else{var n=this.getSimplifier(t);Xe.a.Run(t.settings.length,function(i){var o,a;o=t.settings[i.index],a=function(){i.executeNext()},n.simplify(o,function(s){o.distance!==void 0&&t.mesh.addLODLevel(o.distance,s),s.isVisible=!0,a()})},function(){t.successCallback&&t.successCallback(),e.executeNext()})}},r.prototype.getSimplifier=function(t){switch(t.simplificationType){case Co.QUADRATIC:default:return new bd(t.mesh)}},r}();(function(r){r[r.QUADRATIC=0]="QUADRATIC"})(Co||(Co={}));var xm=function(r){this.vertices=r,this.error=new Array(4),this.deleted=!1,this.isDirty=!1,this.deletePending=!1,this.borderFactor=0},Rm=function(){function r(t,e){this.position=t,this.id=e,this.isBorder=!0,this.q=new vd,this.triangleCount=0,this.triangleStart=0,this.originalOffsets=[]}return r.prototype.updatePosition=function(t){this.position.copyFrom(t)},r}(),vd=function(){function r(t){this.data=new Array(10);for(var e=0;e<10;++e)t&&t[e]?this.data[e]=t[e]:this.data[e]=0}return r.prototype.det=function(t,e,n,i,o,a,s,d,p){return this.data[t]*this.data[o]*this.data[p]+this.data[n]*this.data[i]*this.data[d]+this.data[e]*this.data[a]*this.data[s]-this.data[n]*this.data[o]*this.data[s]-this.data[t]*this.data[a]*this.data[d]-this.data[e]*this.data[i]*this.data[p]},r.prototype.addInPlace=function(t){for(var e=0;e<10;++e)this.data[e]+=t.data[e]},r.prototype.addArrayInPlace=function(t){for(var e=0;e<10;++e)this.data[e]+=t[e]},r.prototype.add=function(t){for(var e=new r,n=0;n<10;++n)e.data[n]=this.data[n]+t.data[n];return e},r.FromData=function(t,e,n,i){return new r(r.DataFromNumbers(t,e,n,i))},r.DataFromNumbers=function(t,e,n,i){return[t*t,t*e,t*n,t*i,e*e,e*n,e*i,n*n,n*i,i*i]},r}(),Om=function(r,t){this.vertexId=r,this.triangleId=t},bd=function(){function r(t){this._mesh=t,this.syncIterations=5e3,this.aggressiveness=7,this.decimationIterations=100,this.boundingBoxEpsilon=Gt.a}return r.prototype.simplify=function(t,e){var n=this;this.initDecimatedMesh(),Xe.a.Run(this._mesh.subMeshes.length,function(i){n.initWithMesh(i.index,function(){n.runDecimation(t,i.index,function(){i.executeNext()})},t.optimizeMesh)},function(){setTimeout(function(){e(n._reconstructedMesh)},0)})},r.prototype.runDecimation=function(t,e,n){var i=this,o=~~(this.triangles.length*t.quality),a=0,s=this.triangles.length;Xe.a.Run(this.decimationIterations,function(d){var p,b;s-a<=o?d.breakLoop():(p=d.index,b=function(){d.executeNext()},setTimeout(function(){p%5==0&&i.updateMesh(p===0);for(var P=0;P<i.triangles.length;++P)i.triangles[P].isDirty=!1;var O=1e-9*Math.pow(p+3,i.aggressiveness);Xe.a.SyncAsyncForLoop(i.triangles.length,i.syncIterations,function(B){var F=~~((i.triangles.length/2+B)%i.triangles.length),z=i.triangles[F];if(z&&!(z.error[3]>O||z.deleted||z.isDirty)){for(var J=0;J<3;++J)if(z.error[J]<O){var ie=[],se=[],ce=z.vertices[J],ue=z.vertices[(J+1)%3];if(ce.isBorder||ue.isBorder)continue;var fe=u.e.Zero();i.calculateError(ce,ue,fe);var ve=new Array;if(i.isFlipped(ce,ue,fe,ie,ve)||i.isFlipped(ue,ce,fe,se,ve)||ie.indexOf(!0)<0||se.indexOf(!0)<0)continue;var Te=new Array;if(ve.forEach(function(Se){Te.indexOf(Se)===-1&&(Se.deletePending=!0,Te.push(Se))}),Te.length%2!=0)continue;ce.q=ue.q.add(ce.q),ce.updatePosition(fe);var Re=i.references.length;a=i.updateTriangles(ce,ce,ie,a),a=i.updateTriangles(ce,ue,se,a);var Ae=i.references.length-Re;if(Ae<=ce.triangleCount){if(Ae)for(var Ee=0;Ee<Ae;Ee++)i.references[ce.triangleStart+Ee]=i.references[Re+Ee]}else ce.triangleStart=Re;ce.triangleCount=Ae;break}}},b,function(){return s-a<=o})},0))},function(){setTimeout(function(){i.reconstructMesh(e),n()},0)})},r.prototype.initWithMesh=function(t,e,n){var i=this;this.vertices=[],this.triangles=[];var o=this._mesh.getVerticesData(Oe.b.PositionKind),a=this._mesh.getIndices(),s=this._mesh.subMeshes[t],d=[],p=s.verticesCount;Xe.a.SyncAsyncForLoop(p,this.syncIterations/4>>0,function(b){if(o){var P=b+s.verticesStart,O=u.e.FromArray(o,3*P),B=function(F){if(n){for(var z=0;z<i.vertices.length;++z)if(i.vertices[z].position.equalsWithEpsilon(F,1e-4))return i.vertices[z]}return null}(O)||new Rm(O,i.vertices.length);B.originalOffsets.push(P),B.id===i.vertices.length&&i.vertices.push(B),d.push(B.id)}},function(){Xe.a.SyncAsyncForLoop(s.indexCount/3,i.syncIterations,function(b){if(a){var P=3*(s.indexStart/3+b),O=a[P+0],B=a[P+1],F=a[P+2],z=i.vertices[d[O-s.verticesStart]],J=i.vertices[d[B-s.verticesStart]],ie=i.vertices[d[F-s.verticesStart]],se=new xm([z,J,ie]);se.originalOffset=P,i.triangles.push(se)}},function(){i.init(e)})})},r.prototype.init=function(t){var e=this;Xe.a.SyncAsyncForLoop(this.triangles.length,this.syncIterations,function(n){var i=e.triangles[n];i.normal=u.e.Cross(i.vertices[1].position.subtract(i.vertices[0].position),i.vertices[2].position.subtract(i.vertices[0].position)).normalize();for(var o=0;o<3;o++)i.vertices[o].q.addArrayInPlace(vd.DataFromNumbers(i.normal.x,i.normal.y,i.normal.z,-u.e.Dot(i.normal,i.vertices[0].position)))},function(){Xe.a.SyncAsyncForLoop(e.triangles.length,e.syncIterations,function(n){for(var i=e.triangles[n],o=0;o<3;++o)i.error[o]=e.calculateError(i.vertices[o],i.vertices[(o+1)%3]);i.error[3]=Math.min(i.error[0],i.error[1],i.error[2])},function(){t()})})},r.prototype.reconstructMesh=function(t){var e,n,i,o=[];for(e=0;e<this.vertices.length;++e)this.vertices[e].triangleCount=0;for(e=0;e<this.triangles.length;++e)if(!this.triangles[e].deleted){for(n=this.triangles[e],i=0;i<3;++i)n.vertices[i].triangleCount=1;o.push(n)}var a=this._reconstructedMesh.getVerticesData(Oe.b.PositionKind)||[],s=this._reconstructedMesh.getVerticesData(Oe.b.NormalKind)||[],d=this._reconstructedMesh.getVerticesData(Oe.b.UVKind)||[],p=this._reconstructedMesh.getVerticesData(Oe.b.ColorKind)||[],b=this._mesh.getVerticesData(Oe.b.NormalKind),P=this._mesh.getVerticesData(Oe.b.UVKind),O=this._mesh.getVerticesData(Oe.b.ColorKind),B=0;for(e=0;e<this.vertices.length;++e){var F=this.vertices[e];F.id=B,F.triangleCount&&F.originalOffsets.forEach(function(fe){a.push(F.position.x),a.push(F.position.y),a.push(F.position.z),b&&b.length&&(s.push(b[3*fe]),s.push(b[3*fe+1]),s.push(b[3*fe+2])),P&&P.length&&(d.push(P[2*fe]),d.push(P[2*fe+1])),O&&O.length&&(p.push(O[4*fe]),p.push(O[4*fe+1]),p.push(O[4*fe+2]),p.push(O[4*fe+3])),++B})}var z=this._reconstructedMesh.getTotalIndices(),J=this._reconstructedMesh.getTotalVertices(),ie=this._reconstructedMesh.subMeshes;this._reconstructedMesh.subMeshes=[];var se=this._reconstructedMesh.getIndices(),ce=this._mesh.getIndices();for(e=0;e<o.length;++e)n=o[e],[0,1,2].forEach(function(fe){var ve=ce[n.originalOffset+fe],Te=n.vertices[fe].originalOffsets.indexOf(ve);Te<0&&(Te=0),se.push(n.vertices[fe].id+Te+J)});this._reconstructedMesh.setIndices(se),this._reconstructedMesh.setVerticesData(Oe.b.PositionKind,a),s.length>0&&this._reconstructedMesh.setVerticesData(Oe.b.NormalKind,s),d.length>0&&this._reconstructedMesh.setVerticesData(Oe.b.UVKind,d),p.length>0&&this._reconstructedMesh.setVerticesData(Oe.b.ColorKind,p);var ue=this._mesh.subMeshes[t];t>0&&(this._reconstructedMesh.subMeshes=[],ie.forEach(function(fe){Eo.a.AddToMesh(fe.materialIndex,fe.verticesStart,fe.verticesCount,fe.indexStart,fe.indexCount,fe.getMesh())}),Eo.a.AddToMesh(ue.materialIndex,J,B,z,3*o.length,this._reconstructedMesh))},r.prototype.initDecimatedMesh=function(){this._reconstructedMesh=new De.a(this._mesh.name+"Decimated",this._mesh.getScene()),this._reconstructedMesh.material=this._mesh.material,this._reconstructedMesh.parent=this._mesh.parent,this._reconstructedMesh.isVisible=!1,this._reconstructedMesh.renderingGroupId=this._mesh.renderingGroupId},r.prototype.isFlipped=function(t,e,n,i,o){for(var a=0;a<t.triangleCount;++a){var s=this.triangles[this.references[t.triangleStart+a].triangleId];if(!s.deleted){var d=this.references[t.triangleStart+a].vertexId,p=s.vertices[(d+1)%3],b=s.vertices[(d+2)%3];if(p!==e&&b!==e){var P=p.position.subtract(n);P=P.normalize();var O=b.position.subtract(n);if(O=O.normalize(),Math.abs(u.e.Dot(P,O))>.999)return!0;var B=u.e.Cross(P,O).normalize();if(i[a]=!1,u.e.Dot(B,s.normal)<.2)return!0}else i[a]=!0,o.push(s)}}return!1},r.prototype.updateTriangles=function(t,e,n,i){for(var o=i,a=0;a<e.triangleCount;++a){var s=this.references[e.triangleStart+a],d=this.triangles[s.triangleId];d.deleted||(n[a]&&d.deletePending?(d.deleted=!0,o++):(d.vertices[s.vertexId]=t,d.isDirty=!0,d.error[0]=this.calculateError(d.vertices[0],d.vertices[1])+d.borderFactor/2,d.error[1]=this.calculateError(d.vertices[1],d.vertices[2])+d.borderFactor/2,d.error[2]=this.calculateError(d.vertices[2],d.vertices[0])+d.borderFactor/2,d.error[3]=Math.min(d.error[0],d.error[1],d.error[2]),this.references.push(s)))}return o},r.prototype.identifyBorder=function(){for(var t=0;t<this.vertices.length;++t){var e,n=[],i=[],o=this.vertices[t];for(e=0;e<o.triangleCount;++e)for(var a=this.triangles[this.references[o.triangleStart+e].triangleId],s=0;s<3;s++){for(var d=0,p=a.vertices[s];d<n.length&&i[d]!==p.id;)++d;d===n.length?(n.push(1),i.push(p.id)):n[d]++}for(e=0;e<n.length;++e)n[e]===1?this.vertices[i[e]].isBorder=!0:this.vertices[i[e]].isBorder=!1}},r.prototype.updateMesh=function(t){var e,n,i,o;if(t===void 0&&(t=!1),!t){var a=[];for(e=0;e<this.triangles.length;++e)this.triangles[e].deleted||a.push(this.triangles[e]);this.triangles=a}for(e=0;e<this.vertices.length;++e)this.vertices[e].triangleCount=0,this.vertices[e].triangleStart=0;for(e=0;e<this.triangles.length;++e)for(n=this.triangles[e],i=0;i<3;++i)(o=n.vertices[i]).triangleCount++;var s=0;for(e=0;e<this.vertices.length;++e)this.vertices[e].triangleStart=s,s+=this.vertices[e].triangleCount,this.vertices[e].triangleCount=0;var d=new Array(3*this.triangles.length);for(e=0;e<this.triangles.length;++e)for(n=this.triangles[e],i=0;i<3;++i)d[(o=n.vertices[i]).triangleStart+o.triangleCount]=new Om(i,e),o.triangleCount++;this.references=d,t&&this.identifyBorder()},r.prototype.vertexError=function(t,e){var n=e.x,i=e.y,o=e.z;return t.data[0]*n*n+2*t.data[1]*n*i+2*t.data[2]*n*o+2*t.data[3]*n+t.data[4]*i*i+2*t.data[5]*i*o+2*t.data[6]*i+t.data[7]*o*o+2*t.data[8]*o+t.data[9]},r.prototype.calculateError=function(t,e,n){var i=t.q.add(e.q),o=t.isBorder&&e.isBorder,a=0,s=i.det(0,1,2,1,4,5,2,5,7);if(s===0||o){var d=t.position.add(e.position).divide(new u.e(2,2,2)),p=this.vertexError(i,t.position),b=this.vertexError(i,e.position),P=this.vertexError(i,d);(a=Math.min(p,b,P))===p?n&&n.copyFrom(t.position):a===b?n&&n.copyFrom(e.position):n&&n.copyFrom(d)}else n||(n=u.e.Zero()),n.x=-1/s*i.det(1,2,3,4,5,6,5,7,8),n.y=1/s*i.det(0,2,3,1,5,6,2,7,8),n.z=-1/s*i.det(0,1,3,1,4,6,2,5,8),a=this.vertexError(i,n);return a},r}();Object.defineProperty(_e.a.prototype,"simplificationQueue",{get:function(){if(!this._simplificationQueue){this._simplificationQueue=new gd;var r=this._getComponent(at.a.NAME_SIMPLIFICATIONQUEUE);r||(r=new yd(this),this._addComponent(r))}return this._simplificationQueue},set:function(r){this._simplificationQueue=r},enumerable:!0,configurable:!0}),De.a.prototype.simplify=function(r,t,e,n){return t===void 0&&(t=!0),e===void 0&&(e=Co.QUADRATIC),this.getScene().simplificationQueue.addTask({settings:r,parallelProcessing:t,mesh:this,simplificationType:e,successCallback:n}),this};var yd=function(){function r(t){this.name=at.a.NAME_SIMPLIFICATIONQUEUE,this.scene=t}return r.prototype.register=function(){this.scene._beforeCameraUpdateStage.registerStep(at.a.STEP_BEFORECAMERAUPDATE_SIMPLIFICATIONQUEUE,this,this._beforeCameraUpdate)},r.prototype.rebuild=function(){},r.prototype.dispose=function(){},r.prototype._beforeCameraUpdate=function(){this.scene._simplificationQueue&&!this.scene._simplificationQueue.running&&this.scene._simplificationQueue.executeNext()},r}(),Mm=f(149),Im=f(88);De.a.prototype.thinInstanceAdd=function(r,t){t===void 0&&(t=!0),this._thinInstanceUpdateBufferSize("matrix",Array.isArray(r)?r.length:1);var e=this._thinInstanceDataStorage.instancesCount;if(Array.isArray(r))for(var n=0;n<r.length;++n)this.thinInstanceSetMatrixAt(this._thinInstanceDataStorage.instancesCount++,r[n],n===r.length-1&&t);else this.thinInstanceSetMatrixAt(this._thinInstanceDataStorage.instancesCount++,r,t);return e},De.a.prototype.thinInstanceAddSelf=function(r){return r===void 0&&(r=!0),this.thinInstanceAdd(u.a.IdentityReadOnly,r)},De.a.prototype.thinInstanceRegisterAttribute=function(r,t){this.removeVerticesData(r),this._thinInstanceInitializeUserStorage(),this._userThinInstanceBuffersStorage.strides[r]=t,this._userThinInstanceBuffersStorage.sizes[r]=t*Math.max(32,this._thinInstanceDataStorage.instancesCount),this._userThinInstanceBuffersStorage.data[r]=new Float32Array(this._userThinInstanceBuffersStorage.sizes[r]),this._userThinInstanceBuffersStorage.vertexBuffers[r]=new Oe.b(this.getEngine(),this._userThinInstanceBuffersStorage.data[r],r,!0,!1,t,!0),this.setVerticesBuffer(this._userThinInstanceBuffersStorage.vertexBuffers[r])},De.a.prototype.thinInstanceSetMatrixAt=function(r,t,e){if(e===void 0&&(e=!0),!this._thinInstanceDataStorage.matrixData||r>=this._thinInstanceDataStorage.instancesCount)return!1;var n=this._thinInstanceDataStorage.matrixData;return t.copyToArray(n,16*r),this._thinInstanceDataStorage.worldMatrices&&(this._thinInstanceDataStorage.worldMatrices[r]=t),e&&(this.thinInstanceBufferUpdated("matrix"),this.doNotSyncBoundingInfo||this.thinInstanceRefreshBoundingInfo(!1)),!0},De.a.prototype.thinInstanceSetAttributeAt=function(r,t,e,n){return n===void 0&&(n=!0),!(!this._userThinInstanceBuffersStorage||!this._userThinInstanceBuffersStorage.data[r]||t>=this._thinInstanceDataStorage.instancesCount)&&(this._thinInstanceUpdateBufferSize(r,0),this._userThinInstanceBuffersStorage.data[r].set(e,t*this._userThinInstanceBuffersStorage.strides[r]),n&&this.thinInstanceBufferUpdated(r),!0)},Object.defineProperty(De.a.prototype,"thinInstanceCount",{get:function(){return this._thinInstanceDataStorage.instancesCount},set:function(r){var t,e;r<=((e=(t=this._thinInstanceDataStorage.matrixData)===null||t===void 0?void 0:t.length)!==null&&e!==void 0?e:0)/16&&(this._thinInstanceDataStorage.instancesCount=r)},enumerable:!0,configurable:!0}),De.a.prototype.thinInstanceSetBuffer=function(r,t,e,n){var i,o;if(e===void 0&&(e=0),n===void 0&&(n=!1),e=e||16,r==="matrix")if((i=this._thinInstanceDataStorage.matrixBuffer)===null||i===void 0||i.dispose(),this._thinInstanceDataStorage.matrixBuffer=null,this._thinInstanceDataStorage.matrixBufferSize=t?t.length:32*e,this._thinInstanceDataStorage.matrixData=t,this._thinInstanceDataStorage.worldMatrices=null,t!==null){this._thinInstanceDataStorage.instancesCount=t.length/e;var a=new Oe.a(this.getEngine(),t,!n,e,!1,!0);this._thinInstanceDataStorage.matrixBuffer=a,this.setVerticesBuffer(a.createVertexBuffer("world0",0,4)),this.setVerticesBuffer(a.createVertexBuffer("world1",4,4)),this.setVerticesBuffer(a.createVertexBuffer("world2",8,4)),this.setVerticesBuffer(a.createVertexBuffer("world3",12,4)),this.doNotSyncBoundingInfo||this.thinInstanceRefreshBoundingInfo(!1)}else this._thinInstanceDataStorage.instancesCount=0,this.doNotSyncBoundingInfo||this.refreshBoundingInfo(!0);else t===null?!((o=this._userThinInstanceBuffersStorage)===null||o===void 0)&&o.data[r]&&(this.removeVerticesData(r),delete this._userThinInstanceBuffersStorage.data[r],delete this._userThinInstanceBuffersStorage.strides[r],delete this._userThinInstanceBuffersStorage.sizes[r],delete this._userThinInstanceBuffersStorage.vertexBuffers[r]):(this._thinInstanceInitializeUserStorage(),this._userThinInstanceBuffersStorage.data[r]=t,this._userThinInstanceBuffersStorage.strides[r]=e,this._userThinInstanceBuffersStorage.sizes[r]=t.length,this._userThinInstanceBuffersStorage.vertexBuffers[r]=new Oe.b(this.getEngine(),t,r,!n,!1,e,!0),this.setVerticesBuffer(this._userThinInstanceBuffersStorage.vertexBuffers[r]))},De.a.prototype.thinInstanceBufferUpdated=function(r){var t;r==="matrix"?this._thinInstanceDataStorage.matrixBuffer&&this._thinInstanceDataStorage.matrixBuffer.updateDirectly(this._thinInstanceDataStorage.matrixData,0,this._thinInstanceDataStorage.instancesCount):!((t=this._userThinInstanceBuffersStorage)===null||t===void 0)&&t.vertexBuffers[r]&&this._userThinInstanceBuffersStorage.vertexBuffers[r].updateDirectly(this._userThinInstanceBuffersStorage.data[r],0)},De.a.prototype.thinInstancePartialBufferUpdate=function(r,t,e){var n;r==="matrix"?this._thinInstanceDataStorage.matrixBuffer&&this._thinInstanceDataStorage.matrixBuffer.updateDirectly(t,e):!((n=this._userThinInstanceBuffersStorage)===null||n===void 0)&&n.vertexBuffers[r]&&this._userThinInstanceBuffersStorage.vertexBuffers[r].updateDirectly(t,e)},De.a.prototype.thinInstanceGetWorldMatrices=function(){if(!this._thinInstanceDataStorage.matrixData||!this._thinInstanceDataStorage.matrixBuffer)return[];var r=this._thinInstanceDataStorage.matrixData;if(!this._thinInstanceDataStorage.worldMatrices){this._thinInstanceDataStorage.worldMatrices=new Array;for(var t=0;t<this._thinInstanceDataStorage.instancesCount;++t)this._thinInstanceDataStorage.worldMatrices[t]=u.a.FromArray(r,16*t)}return this._thinInstanceDataStorage.worldMatrices},De.a.prototype.thinInstanceRefreshBoundingInfo=function(r){if(r===void 0&&(r=!1),this._thinInstanceDataStorage.matrixData&&this._thinInstanceDataStorage.matrixBuffer){var t=this._thinInstanceDataStorage.boundingVectors;r&&(t.length=0,this.refreshBoundingInfo(!0));var e=this.getBoundingInfo(),n=this._thinInstanceDataStorage.matrixData;if(t.length===0)for(var i=0;i<e.boundingBox.vectors.length;++i)t.push(e.boundingBox.vectors[i].clone());u.c.Vector3[0].setAll(Number.POSITIVE_INFINITY),u.c.Vector3[1].setAll(Number.NEGATIVE_INFINITY);for(var o=0;o<this._thinInstanceDataStorage.instancesCount;++o)for(u.a.FromArrayToRef(n,16*o,u.c.Matrix[0]),i=0;i<t.length;++i)u.e.TransformCoordinatesToRef(t[i],u.c.Matrix[0],u.c.Vector3[2]),u.c.Vector3[0].minimizeInPlace(u.c.Vector3[2]),u.c.Vector3[1].maximizeInPlace(u.c.Vector3[2]);e.reConstruct(u.c.Vector3[0],u.c.Vector3[1]),this._updateBoundingInfo()}},De.a.prototype._thinInstanceUpdateBufferSize=function(r,t){var e,n;t===void 0&&(t=1);var i=r==="matrix";if(i||this._userThinInstanceBuffersStorage&&this._userThinInstanceBuffersStorage.strides[r]){for(var o=i?16:this._userThinInstanceBuffersStorage.strides[r],a=i?this._thinInstanceDataStorage.matrixBufferSize:this._userThinInstanceBuffersStorage.sizes[r],s=i?this._thinInstanceDataStorage.matrixData:this._userThinInstanceBuffersStorage.data[r],d=(this._thinInstanceDataStorage.instancesCount+t)*o,p=a;p<d;)p*=2;if(!s||a!=p){if(s){var b=new Float32Array(p);b.set(s,0),s=b}else s=new Float32Array(p);if(i){(e=this._thinInstanceDataStorage.matrixBuffer)===null||e===void 0||e.dispose();var P=new Oe.a(this.getEngine(),s,!0,o,!1,!0);this._thinInstanceDataStorage.matrixBuffer=P,this._thinInstanceDataStorage.matrixData=s,this._thinInstanceDataStorage.matrixBufferSize=p,this.setVerticesBuffer(P.createVertexBuffer("world0",0,4)),this.setVerticesBuffer(P.createVertexBuffer("world1",4,4)),this.setVerticesBuffer(P.createVertexBuffer("world2",8,4)),this.setVerticesBuffer(P.createVertexBuffer("world3",12,4))}else(n=this._userThinInstanceBuffersStorage.vertexBuffers[r])===null||n===void 0||n.dispose(),this._userThinInstanceBuffersStorage.data[r]=s,this._userThinInstanceBuffersStorage.sizes[r]=p,this._userThinInstanceBuffersStorage.vertexBuffers[r]=new Oe.b(this.getEngine(),s,r,!0,!1,o,!0),this.setVerticesBuffer(this._userThinInstanceBuffersStorage.vertexBuffers[r])}}},De.a.prototype._thinInstanceInitializeUserStorage=function(){this._userThinInstanceBuffersStorage||(this._userThinInstanceBuffersStorage={data:{},sizes:{},vertexBuffers:{},strides:{}})},De.a.prototype._disposeThinInstanceSpecificData=function(){var r;!((r=this._thinInstanceDataStorage)===null||r===void 0)&&r.matrixBuffer&&(this._thinInstanceDataStorage.matrixBuffer.dispose(),this._thinInstanceDataStorage.matrixBuffer=null)};var Dm=function(){function r(t){t===void 0&&(t=Recast),this.bjsRECAST={},this.name="RecastJSPlugin",this._maximumSubStepCount=10,this._timeStep=1/60,typeof t=="function"?t(this.bjsRECAST):this.bjsRECAST=t,this.isSupported()?this.setTimeStep():l.a.Error("RecastJS is not available. Please make sure you included the js file.")}return r.prototype.setTimeStep=function(t){t===void 0&&(t=1/60),this._timeStep=t},r.prototype.getTimeStep=function(){return this._timeStep},r.prototype.setMaximumSubStepCount=function(t){t===void 0&&(t=10),this._maximumSubStepCount=t},r.prototype.getMaximumSubStepCount=function(){return this._maximumSubStepCount},r.prototype.createNavMesh=function(t,e){var n,i,o,a=new this.bjsRECAST.rcConfig;a.cs=e.cs,a.ch=e.ch,a.borderSize=0,a.tileSize=0,a.walkableSlopeAngle=e.walkableSlopeAngle,a.walkableHeight=e.walkableHeight,a.walkableClimb=e.walkableClimb,a.walkableRadius=e.walkableRadius,a.maxEdgeLen=e.maxEdgeLen,a.maxSimplificationError=e.maxSimplificationError,a.minRegionArea=e.minRegionArea,a.mergeRegionArea=e.mergeRegionArea,a.maxVertsPerPoly=e.maxVertsPerPoly,a.detailSampleDist=e.detailSampleDist,a.detailSampleMaxError=e.detailSampleMaxError,this.navMesh=new this.bjsRECAST.NavMesh;var s=[],d=[],p=0;for(n=0;n<t.length;n++)if(t[n]){var b=t[n],P=b.getIndices();if(!P)continue;var O=b.getVerticesData(Oe.b.PositionKind,!1,!1);if(!O)continue;var B=b.computeWorldMatrix(!0);for(i=0;i<P.length;i++)s.push(P[i]+p);var F=u.e.Zero(),z=u.e.Zero();for(o=0;o<O.length;o+=3)u.e.FromArrayToRef(O,o,z),u.e.TransformCoordinatesToRef(z,B,F),d.push(F.x,F.y,F.z);p+=O.length/3}this.navMesh.build(d,p,s,s.length,a)},r.prototype.createDebugNavMesh=function(t){var e,n,i=this.navMesh.getDebugNavMesh(),o=i.getTriangleCount(),a=[],s=[];for(e=0;e<3*o;e++)a.push(e);for(e=0;e<o;e++)for(n=0;n<3;n++){var d=i.getTriangle(e).getPoint(n);s.push(d.x,d.y,d.z)}var p=new De.a("NavMeshDebug",t),b=new ft.a;return b.indices=a,b.positions=s,b.applyToMesh(p,!1),p},r.prototype.getClosestPoint=function(t){var e=new this.bjsRECAST.Vec3(t.x,t.y,t.z),n=this.navMesh.getClosestPoint(e);return new u.e(n.x,n.y,n.z)},r.prototype.getClosestPointToRef=function(t,e){var n=new this.bjsRECAST.Vec3(t.x,t.y,t.z),i=this.navMesh.getClosestPoint(n);e.set(i.x,i.y,i.z)},r.prototype.getRandomPointAround=function(t,e){var n=new this.bjsRECAST.Vec3(t.x,t.y,t.z),i=this.navMesh.getRandomPointAround(n,e);return new u.e(i.x,i.y,i.z)},r.prototype.getRandomPointAroundToRef=function(t,e,n){var i=new this.bjsRECAST.Vec3(t.x,t.y,t.z),o=this.navMesh.getRandomPointAround(i,e);n.set(o.x,o.y,o.z)},r.prototype.moveAlong=function(t,e){var n=new this.bjsRECAST.Vec3(t.x,t.y,t.z),i=new this.bjsRECAST.Vec3(e.x,e.y,e.z),o=this.navMesh.moveAlong(n,i);return new u.e(o.x,o.y,o.z)},r.prototype.moveAlongToRef=function(t,e,n){var i=new this.bjsRECAST.Vec3(t.x,t.y,t.z),o=new this.bjsRECAST.Vec3(e.x,e.y,e.z),a=this.navMesh.moveAlong(i,o);n.set(a.x,a.y,a.z)},r.prototype.computePath=function(t,e){var n,i=new this.bjsRECAST.Vec3(t.x,t.y,t.z),o=new this.bjsRECAST.Vec3(e.x,e.y,e.z),a=this.navMesh.computePath(i,o),s=a.getPointCount(),d=[];for(n=0;n<s;n++){var p=a.getPoint(n);d.push(new u.e(p.x,p.y,p.z))}return d},r.prototype.createCrowd=function(t,e,n){return new Td(this,t,e,n)},r.prototype.setDefaultQueryExtent=function(t){var e=new this.bjsRECAST.Vec3(t.x,t.y,t.z);this.navMesh.setDefaultQueryExtent(e)},r.prototype.getDefaultQueryExtent=function(){var t=this.navMesh.getDefaultQueryExtent();return new u.e(t.x,t.y,t.z)},r.prototype.buildFromNavmeshData=function(t){var e=t.length*t.BYTES_PER_ELEMENT,n=this.bjsRECAST._malloc(e),i=new Uint8Array(this.bjsRECAST.HEAPU8.buffer,n,e);i.set(t);var o=new this.bjsRECAST.NavmeshData;o.dataPointer=i.byteOffset,o.size=t.length,this.navMesh=new this.bjsRECAST.NavMesh,this.navMesh.buildFromNavmeshData(o),this.bjsRECAST._free(i.byteOffset)},r.prototype.getNavmeshData=function(){var t=this.navMesh.getNavmeshData(),e=new Uint8Array(this.bjsRECAST.HEAPU8.buffer,t.dataPointer,t.size),n=new Uint8Array(t.size);return n.set(e),this.navMesh.freeNavmeshData(t),n},r.prototype.getDefaultQueryExtentToRef=function(t){var e=this.navMesh.getDefaultQueryExtent();t.set(e.x,e.y,e.z)},r.prototype.dispose=function(){},r.prototype.isSupported=function(){return this.bjsRECAST!==void 0},r}(),Td=function(){function r(t,e,n,i){var o=this;this.recastCrowd={},this.transforms=new Array,this.agents=new Array,this._onBeforeAnimationsObserver=null,this.bjsRECASTPlugin=t,this.recastCrowd=new this.bjsRECASTPlugin.bjsRECAST.Crowd(e,n,this.bjsRECASTPlugin.navMesh.getNavMesh()),this._scene=i,this._onBeforeAnimationsObserver=i.onBeforeAnimationsObservable.add(function(){o.update(.001*i.getEngine().getDeltaTime())})}return r.prototype.addAgent=function(t,e,n){var i=new this.bjsRECASTPlugin.bjsRECAST.dtCrowdAgentParams;i.radius=e.radius,i.height=e.height,i.maxAcceleration=e.maxAcceleration,i.maxSpeed=e.maxSpeed,i.collisionQueryRange=e.collisionQueryRange,i.pathOptimizationRange=e.pathOptimizationRange,i.separationWeight=e.separationWeight,i.updateFlags=7,i.obstacleAvoidanceType=0,i.queryFilterType=0,i.userData=0;var o=this.recastCrowd.addAgent(new this.bjsRECASTPlugin.bjsRECAST.Vec3(t.x,t.y,t.z),i);return this.transforms.push(n),this.agents.push(o),o},r.prototype.getAgentPosition=function(t){var e=this.recastCrowd.getAgentPosition(t);return new u.e(e.x,e.y,e.z)},r.prototype.getAgentPositionToRef=function(t,e){var n=this.recastCrowd.getAgentPosition(t);e.set(n.x,n.y,n.z)},r.prototype.getAgentVelocity=function(t){var e=this.recastCrowd.getAgentVelocity(t);return new u.e(e.x,e.y,e.z)},r.prototype.getAgentVelocityToRef=function(t,e){var n=this.recastCrowd.getAgentVelocity(t);e.set(n.x,n.y,n.z)},r.prototype.getAgentNextTargetPath=function(t){var e=this.recastCrowd.getAgentNextTargetPath(t);return new u.e(e.x,e.y,e.z)},r.prototype.getAgentNextTargetPathToRef=function(t,e){var n=this.recastCrowd.getAgentNextTargetPath(t);e.set(n.x,n.y,n.z)},r.prototype.getAgentState=function(t){return this.recastCrowd.getAgentState(t)},r.prototype.overOffmeshConnection=function(t){return this.recastCrowd.overOffmeshConnection(t)},r.prototype.agentGoto=function(t,e){this.recastCrowd.agentGoto(t,new this.bjsRECASTPlugin.bjsRECAST.Vec3(e.x,e.y,e.z))},r.prototype.agentTeleport=function(t,e){this.recastCrowd.agentTeleport(t,new this.bjsRECASTPlugin.bjsRECAST.Vec3(e.x,e.y,e.z))},r.prototype.updateAgentParameters=function(t,e){var n=this.recastCrowd.getAgentParameters(t);e.radius!==void 0&&(n.radius=e.radius),e.height!==void 0&&(n.height=e.height),e.maxAcceleration!==void 0&&(n.maxAcceleration=e.maxAcceleration),e.maxSpeed!==void 0&&(n.maxSpeed=e.maxSpeed),e.collisionQueryRange!==void 0&&(n.collisionQueryRange=e.collisionQueryRange),e.pathOptimizationRange!==void 0&&(n.pathOptimizationRange=e.pathOptimizationRange),e.separationWeight!==void 0&&(n.separationWeight=e.separationWeight),this.recastCrowd.setAgentParameters(t,n)},r.prototype.removeAgent=function(t){this.recastCrowd.removeAgent(t);var e=this.agents.indexOf(t);e>-1&&(this.agents.splice(e,1),this.transforms.splice(e,1))},r.prototype.getAgents=function(){return this.agents},r.prototype.update=function(t){var e=this.bjsRECASTPlugin.getTimeStep(),n=this.bjsRECASTPlugin.getMaximumSubStepCount();if(e<=Gt.a)this.recastCrowd.update(t);else{var i=t/e;n&&i>n&&(i=n),i<1&&(i=1);for(var o=0;o<i;o++)this.recastCrowd.update(e)}for(var a=0;a<this.agents.length;a++)this.transforms[a].position=this.getAgentPosition(this.agents[a])},r.prototype.setDefaultQueryExtent=function(t){var e=new this.bjsRECASTPlugin.bjsRECAST.Vec3(t.x,t.y,t.z);this.recastCrowd.setDefaultQueryExtent(e)},r.prototype.getDefaultQueryExtent=function(){var t=this.recastCrowd.getDefaultQueryExtent();return new u.e(t.x,t.y,t.z)},r.prototype.getDefaultQueryExtentToRef=function(t){var e=this.recastCrowd.getDefaultQueryExtent();t.set(e.x,e.y,e.z)},r.prototype.dispose=function(){this.recastCrowd.destroy(),this._scene.onBeforeAnimationsObservable.remove(this._onBeforeAnimationsObserver),this._onBeforeAnimationsObserver=null},r}();Ue.a.OfflineProviderFactory=function(r,t,e){return e===void 0&&(e=!1),new Ed(r,t,e)};var Fr,Ed=function(){function r(t,e,n){var i=this;n===void 0&&(n=!1),this._idbFactory=typeof window<"u"?window.indexedDB||window.mozIndexedDB||window.webkitIndexedDB||window.msIndexedDB:indexedDB,this._callbackManifestChecked=e,this._currentSceneUrl=r._ReturnFullUrlLocation(t),this._db=null,this._enableSceneOffline=!1,this._enableTexturesOffline=!1,this._manifestVersionFound=0,this._mustUpdateRessources=!1,this._hasReachedQuota=!1,r.IDBStorageEnabled?n?(this._enableSceneOffline=!0,this._enableTexturesOffline=!0,this._manifestVersionFound=1,Xe.b.SetImmediate(function(){i._callbackManifestChecked(!0)})):this._checkManifestFile():this._callbackManifestChecked(!0)}return Object.defineProperty(r.prototype,"enableSceneOffline",{get:function(){return this._enableSceneOffline},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"enableTexturesOffline",{get:function(){return this._enableTexturesOffline},enumerable:!1,configurable:!0}),r.prototype._checkManifestFile=function(){var t=this,e=function(){t._enableSceneOffline=!1,t._enableTexturesOffline=!1,t._callbackManifestChecked(!1)},n=!1,i=this._currentSceneUrl+".manifest",o=new re.a;navigator.onLine&&(n=!0,i=i+(i.match(/\?/)==null?"?":"&")+Date.now()),o.open("GET",i),o.addEventListener("load",function(){if(o.status===200||r._ValidateXHRData(o,1))try{var a=JSON.parse(o.response);t._enableSceneOffline=a.enableSceneOffline,t._enableTexturesOffline=a.enableTexturesOffline&&r.IsUASupportingBlobStorage,a.version&&!isNaN(parseInt(a.version))&&(t._manifestVersionFound=a.version),t._callbackManifestChecked&&t._callbackManifestChecked(!0)}catch{e()}else e()},!1),o.addEventListener("error",function(){if(n){n=!1;var a=t._currentSceneUrl+".manifest";o.open("GET",a),o.send()}else e()},!1);try{o.send()}catch{l.a.Error("Error on XHR send request."),this._callbackManifestChecked(!1)}},r.prototype.open=function(t,e){var n=this,i=function(){n._isSupported=!1,e&&e()};if(this._idbFactory&&(this._enableSceneOffline||this._enableTexturesOffline))if(this._db)t&&t();else{this._hasReachedQuota=!1,this._isSupported=!0;var o=this._idbFactory.open("babylonjs",1);o.onerror=function(){i()},o.onblocked=function(){l.a.Error("IDB request blocked. Please reload the page."),i()},o.onsuccess=function(){n._db=o.result,t()},o.onupgradeneeded=function(a){if(n._db=a.target.result,n._db)try{n._db.createObjectStore("scenes",{keyPath:"sceneUrl"}),n._db.createObjectStore("versions",{keyPath:"sceneUrl"}),n._db.createObjectStore("textures",{keyPath:"textureUrl"})}catch(s){l.a.Error("Error while creating object stores. Exception: "+s.message),i()}}}else this._isSupported=!1,e&&e()},r.prototype.loadImage=function(t,e){var n=this,i=r._ReturnFullUrlLocation(t),o=function(){n._hasReachedQuota||n._db===null?e.src=t:n._saveImageIntoDBAsync(i,e)};this._mustUpdateRessources?o():this._loadImageFromDBAsync(i,e,o)},r.prototype._loadImageFromDBAsync=function(t,e,n){if(this._isSupported&&this._db!==null){var i,o=this._db.transaction(["textures"]);o.onabort=function(){e.src=t},o.oncomplete=function(){var s;if(i){var d=window.URL||window.webkitURL;s=d.createObjectURL(i.data),e.onerror=function(){l.a.Error("Error loading image from blob URL: "+s+" switching back to web url: "+t),e.src=t},e.src=s}else n()};var a=o.objectStore("textures").get(t);a.onsuccess=function(s){i=s.target.result},a.onerror=function(){l.a.Error("Error loading texture "+t+" from DB."),e.src=t}}else l.a.Error("Error: IndexedDB not supported by your browser or BabylonJS Database is not open."),e.src=t},r.prototype._saveImageIntoDBAsync=function(t,e){var n=this;if(this._isSupported){var i=function(){var s;if(o){var d=window.URL||window.webkitURL;try{s=d.createObjectURL(o)}catch{s=d.createObjectURL(o)}}s&&(e.src=s)};if(r.IsUASupportingBlobStorage){var o,a=new re.a;a.open("GET",t),a.responseType="blob",a.addEventListener("load",function(){if(a.status===200&&n._db){o=a.response;var s=n._db.transaction(["textures"],"readwrite");s.onabort=function(b){try{var P=(b.srcElement||b.target).error;P&&P.name==="QuotaExceededError"&&(n._hasReachedQuota=!0)}catch{}i()},s.oncomplete=function(){i()};var d={textureUrl:t,data:o};try{var p=s.objectStore("textures").put(d);p.onsuccess=function(){},p.onerror=function(){i()}}catch(b){b.code===25&&(r.IsUASupportingBlobStorage=!1,n._enableTexturesOffline=!1),e.src=t}}else e.src=t},!1),a.addEventListener("error",function(){l.a.Error("Error in XHR request in BABYLON.Database."),e.src=t},!1),a.send()}else e.src=t}else l.a.Error("Error: IndexedDB not supported by your browser or Babylon.js database is not open."),e.src=t},r.prototype._checkVersionFromDB=function(t,e){var n=this;this._loadVersionFromDBAsync(t,e,function(){n._saveVersionIntoDBAsync(t,e)})},r.prototype._loadVersionFromDBAsync=function(t,e,n){var i,o=this;if(this._isSupported&&this._db)try{var a=this._db.transaction(["versions"]);a.oncomplete=function(){i?o._manifestVersionFound!==i.data?(o._mustUpdateRessources=!0,n()):e(i.data):(o._mustUpdateRessources=!0,n())},a.onabort=function(){e(-1)};var s=a.objectStore("versions").get(t);s.onsuccess=function(d){i=d.target.result},s.onerror=function(){l.a.Error("Error loading version for scene "+t+" from DB."),e(-1)}}catch(d){l.a.Error("Error while accessing 'versions' object store (READ OP). Exception: "+d.message),e(-1)}else l.a.Error("Error: IndexedDB not supported by your browser or Babylon.js database is not open."),e(-1)},r.prototype._saveVersionIntoDBAsync=function(t,e){var n=this;if(this._isSupported&&!this._hasReachedQuota&&this._db)try{var i=this._db.transaction(["versions"],"readwrite");i.onabort=function(s){try{var d=s.srcElement.error;d&&d.name==="QuotaExceededError"&&(n._hasReachedQuota=!0)}catch{}e(-1)},i.oncomplete=function(){e(n._manifestVersionFound)};var o={sceneUrl:t,data:this._manifestVersionFound},a=i.objectStore("versions").put(o);a.onsuccess=function(){},a.onerror=function(){l.a.Error("Error in DB add version request in BABYLON.Database.")}}catch(s){l.a.Error("Error while accessing 'versions' object store (WRITE OP). Exception: "+s.message),e(-1)}else e(-1)},r.prototype.loadFile=function(t,e,n,i,o){var a=this,s=r._ReturnFullUrlLocation(t),d=function(){a._saveFileAsync(s,e,n,o,i)};this._checkVersionFromDB(s,function(p){p!==-1?a._mustUpdateRessources?a._saveFileAsync(s,e,n,o,i):a._loadFileAsync(s,e,d):i&&i()})},r.prototype._loadFileAsync=function(t,e,n){if(this._isSupported&&this._db){var i,o;i=t.indexOf(".babylon")!==-1?"scenes":"textures";var a=this._db.transaction([i]);a.oncomplete=function(){o?e(o.data):n()},a.onabort=function(){n()};var s=a.objectStore(i).get(t);s.onsuccess=function(d){o=d.target.result},s.onerror=function(){l.a.Error("Error loading file "+t+" from DB."),n()}}else l.a.Error("Error: IndexedDB not supported by your browser or BabylonJS Database is not open."),e()},r.prototype._saveFileAsync=function(t,e,n,i,o){var a=this;if(this._isSupported){var s;s=t.indexOf(".babylon")!==-1?"scenes":"textures";var d,p=new re.a;p.open("GET",t+"?"+Date.now()),i&&(p.responseType="arraybuffer"),n&&(p.onprogress=n),p.addEventListener("load",function(){if(p.status===200||p.status<400&&r._ValidateXHRData(p,i?6:1))if(d=i?p.response:p.responseText,!a._hasReachedQuota&&a._db){var b,P=a._db.transaction([s],"readwrite");P.onabort=function(B){try{var F=B.srcElement.error;F&&F.name==="QuotaExceededError"&&(a._hasReachedQuota=!0)}catch{}e(d)},P.oncomplete=function(){e(d)},b=s==="scenes"?{sceneUrl:t,data:d,version:a._manifestVersionFound}:{textureUrl:t,data:d};try{var O=P.objectStore(s).put(b);O.onsuccess=function(){},O.onerror=function(){l.a.Error("Error in DB add file request in BABYLON.Database.")}}catch{e(d)}}else e(d);else p.status>=400&&o?o(p):e()},!1),p.addEventListener("error",function(){l.a.Error("error on XHR request."),e()},!1),p.send()}else l.a.Error("Error: IndexedDB not supported by your browser or Babylon.js database is not open."),e()},r._ValidateXHRData=function(t,e){e===void 0&&(e=7);try{if(1&e){if(t.responseText&&t.responseText.length>0)return!0;if(e===1)return!1}if(2&e){var n=ha.GetTGAHeader(t.response);if(n.width&&n.height&&n.width>0&&n.height>0)return!0;if(e===2)return!1}if(4&e){var i=new Uint8Array(t.response,0,3);return i[0]===68&&i[1]===68&&i[2]===83}}catch{}return!1},r.IsUASupportingBlobStorage=!0,r.IDBStorageEnabled=!1,r._ParseURL=function(t){document.createElement("a").href=t;var e=t.substring(0,t.lastIndexOf("#")),n=t.substring(e.lastIndexOf("/")+1,t.length);return t.substring(0,t.indexOf(n,0))},r._ReturnFullUrlLocation=function(t){return t.indexOf("http:/")===-1&&t.indexOf("https:/")===-1&&typeof window<"u"?r._ParseURL(window.location.href)+t:t},r}(),Rc=function(){function r(t,e,n){this.gradient=t,this.color1=e,this.color2=n}return r.prototype.getColorToRef=function(t){this.color2?M.b.LerpToRef(this.color1,this.color2,Math.random(),t):t.copyFrom(this.color1)},r}(),Sd=function(r,t){this.gradient=r,this.color=t},Oc=function(){function r(t,e,n){this.gradient=t,this.factor1=e,this.factor2=n}return r.prototype.getFactor=function(){return this.factor2===void 0||this.factor2===this.factor1?this.factor1:this.factor1+(this.factor2-this.factor1)*Math.random()},r}(),In=function(){function r(){}return r.GetCurrentGradient=function(t,e,n){if(e[0].gradient>t)n(e[0],e[0],1);else{for(var i=0;i<e.length-1;i++){var o=e[i],a=e[i+1];if(t>=o.gradient&&t<=a.gradient)return void n(o,a,(t-o.gradient)/(a.gradient-o.gradient))}var s=e.length-1;n(e[s],e[s],1)}},r}(),Ad=function(){function r(t){this.particleSystem=t,this.position=u.e.Zero(),this.direction=u.e.Zero(),this.color=new M.b(0,0,0,0),this.colorStep=new M.b(0,0,0,0),this.lifeTime=1,this.age=0,this.size=0,this.scale=new u.d(1,1),this.angle=0,this.angularSpeed=0,this.cellIndex=0,this._attachedSubEmitters=null,this._currentColor1=new M.b(0,0,0,0),this._currentColor2=new M.b(0,0,0,0),this._currentSize1=0,this._currentSize2=0,this._currentAngularSpeed1=0,this._currentAngularSpeed2=0,this._currentVelocity1=0,this._currentVelocity2=0,this._currentLimitVelocity1=0,this._currentLimitVelocity2=0,this._currentDrag1=0,this._currentDrag2=0,this.id=r._Count++,this.particleSystem.isAnimationSheetEnabled&&this.updateCellInfoFromSystem()}return r.prototype.updateCellInfoFromSystem=function(){this.cellIndex=this.particleSystem.startSpriteCellID},r.prototype.updateCellIndex=function(){var t=this.age,e=this.particleSystem.spriteCellChangeSpeed;this.particleSystem.spriteRandomStartCell&&(this._randomCellOffset===void 0&&(this._randomCellOffset=Math.random()*this.lifeTime),e===0?(e=1,t=this._randomCellOffset):t+=this._randomCellOffset);var n=this._initialEndSpriteCellID-this._initialStartSpriteCellID,i=$.a.Clamp(t*e%this.lifeTime/this.lifeTime);this.cellIndex=this._initialStartSpriteCellID+i*n|0},r.prototype._inheritParticleInfoToSubEmitter=function(t){if(t.particleSystem.emitter.position){var e=t.particleSystem.emitter;if(e.position.copyFrom(this.position),t.inheritDirection){var n=u.c.Vector3[0];this.direction.normalizeToRef(n),e.setDirection(n,0,Math.PI/2)}}else t.particleSystem.emitter.copyFrom(this.position);this.direction.scaleToRef(t.inheritedVelocityAmount/2,u.c.Vector3[0]),t.particleSystem._inheritedVelocityOffset.copyFrom(u.c.Vector3[0])},r.prototype._inheritParticleInfoToSubEmitters=function(){var t=this;this._attachedSubEmitters&&this._attachedSubEmitters.length>0&&this._attachedSubEmitters.forEach(function(e){t._inheritParticleInfoToSubEmitter(e)})},r.prototype._reset=function(){this.age=0,this.id=r._Count++,this._currentColorGradient=null,this._currentSizeGradient=null,this._currentAngularSpeedGradient=null,this._currentVelocityGradient=null,this._currentLimitVelocityGradient=null,this._currentDragGradient=null,this.cellIndex=this.particleSystem.startSpriteCellID,this._randomCellOffset=void 0},r.prototype.copyTo=function(t){t.position.copyFrom(this.position),this._initialDirection?t._initialDirection?t._initialDirection.copyFrom(this._initialDirection):t._initialDirection=this._initialDirection.clone():t._initialDirection=null,t.direction.copyFrom(this.direction),this._localPosition&&(t._localPosition?t._localPosition.copyFrom(this._localPosition):t._localPosition=this._localPosition.clone()),t.color.copyFrom(this.color),t.colorStep.copyFrom(this.colorStep),t.lifeTime=this.lifeTime,t.age=this.age,t._randomCellOffset=this._randomCellOffset,t.size=this.size,t.scale.copyFrom(this.scale),t.angle=this.angle,t.angularSpeed=this.angularSpeed,t.particleSystem=this.particleSystem,t.cellIndex=this.cellIndex,t.id=this.id,t._attachedSubEmitters=this._attachedSubEmitters,this._currentColorGradient&&(t._currentColorGradient=this._currentColorGradient,t._currentColor1.copyFrom(this._currentColor1),t._currentColor2.copyFrom(this._currentColor2)),this._currentSizeGradient&&(t._currentSizeGradient=this._currentSizeGradient,t._currentSize1=this._currentSize1,t._currentSize2=this._currentSize2),this._currentAngularSpeedGradient&&(t._currentAngularSpeedGradient=this._currentAngularSpeedGradient,t._currentAngularSpeed1=this._currentAngularSpeed1,t._currentAngularSpeed2=this._currentAngularSpeed2),this._currentVelocityGradient&&(t._currentVelocityGradient=this._currentVelocityGradient,t._currentVelocity1=this._currentVelocity1,t._currentVelocity2=this._currentVelocity2),this._currentLimitVelocityGradient&&(t._currentLimitVelocityGradient=this._currentLimitVelocityGradient,t._currentLimitVelocity1=this._currentLimitVelocity1,t._currentLimitVelocity2=this._currentLimitVelocity2),this._currentDragGradient&&(t._currentDragGradient=this._currentDragGradient,t._currentDrag1=this._currentDrag1,t._currentDrag2=this._currentDrag2),this.particleSystem.isAnimationSheetEnabled&&(t._initialStartSpriteCellID=this._initialStartSpriteCellID,t._initialEndSpriteCellID=this._initialEndSpriteCellID),this.particleSystem.useRampGradients&&(t.remapData&&this.remapData?t.remapData.copyFrom(this.remapData):t.remapData=new u.f(0,0,0,0)),this._randomNoiseCoordinates1&&(t._randomNoiseCoordinates1?(t._randomNoiseCoordinates1.copyFrom(this._randomNoiseCoordinates1),t._randomNoiseCoordinates2.copyFrom(this._randomNoiseCoordinates2)):(t._randomNoiseCoordinates1=this._randomNoiseCoordinates1.clone(),t._randomNoiseCoordinates2=this._randomNoiseCoordinates2.clone()))},r._Count=0,r}();(function(r){r[r.ATTACHED=0]="ATTACHED",r[r.END=1]="END"})(Fr||(Fr={}));var xo=function(){function r(t){if(this.particleSystem=t,this.type=Fr.END,this.inheritDirection=!1,this.inheritedVelocityAmount=0,!t.emitter||!t.emitter.dispose){var e=R.a.GetClass("BABYLON.AbstractMesh");t.emitter=new e("SubemitterSystemEmitter",t.getScene())}t.onDisposeObservable.add(function(){t.emitter&&t.emitter.dispose&&t.emitter.dispose()})}return r.prototype.clone=function(){var t=this.particleSystem.emitter;t?t instanceof u.e?t=t.clone():t.getClassName().indexOf("Mesh")!==-1&&((t=new(R.a.GetClass("BABYLON.Mesh"))("",t.getScene())).isVisible=!1):t=new u.e;var e=new r(this.particleSystem.clone("",t));return e.particleSystem.name+="Clone",e.type=this.type,e.inheritDirection=this.inheritDirection,e.inheritedVelocityAmount=this.inheritedVelocityAmount,e.particleSystem._disposeEmitterOnDispose=!0,e.particleSystem.disposeOnStop=!0,e},r.prototype.serialize=function(){var t={};return t.type=this.type,t.inheritDirection=this.inheritDirection,t.inheritedVelocityAmount=this.inheritedVelocityAmount,t.particleSystem=this.particleSystem.serialize(),t},r._ParseParticleSystem=function(t,e,n){throw An.a.WarnImport("ParseParticle")},r.Parse=function(t,e,n){var i=t.particleSystem,o=new r(r._ParseParticleSystem(i,e,n));return o.type=t.type,o.inheritDirection=t.inheritDirection,o.inheritedVelocityAmount=t.inheritedVelocityAmount,o.particleSystem._isSubEmitter=!0,o},r.prototype.dispose=function(){this.particleSystem.dispose()},r}(),Lm=`
-varying vec2 vUV;
-varying vec4 vColor;
-uniform vec4 textureMask;
-uniform sampler2D diffuseSampler;
-#include<clipPlaneFragmentDeclaration>
-#include<imageProcessingDeclaration>
-#include<helperFunctions>
-#include<imageProcessingFunctions>
-#ifdef RAMPGRADIENT
-varying vec4 remapRanges;
-uniform sampler2D rampSampler;
-#endif
-void main(void) {
-#include<clipPlaneFragment>
-vec4 textureColor=texture2D(diffuseSampler,vUV);
-vec4 baseColor=(textureColor*textureMask+(vec4(1.,1.,1.,1.)-textureMask))*vColor;
-#ifdef RAMPGRADIENT
-float alpha=baseColor.a;
-float remappedColorIndex=clamp((alpha-remapRanges.x)/remapRanges.y,0.0,1.0);
-vec4 rampColor=texture2D(rampSampler,vec2(1.0-remappedColorIndex,0.));
-baseColor.rgb*=rampColor.rgb;
-
-float finalAlpha=baseColor.a;
-baseColor.a=clamp((alpha*rampColor.a-remapRanges.z)/remapRanges.w,0.0,1.0);
-#endif
-#ifdef BLENDMULTIPLYMODE
-float sourceAlpha=vColor.a*textureColor.a;
-baseColor.rgb=baseColor.rgb*sourceAlpha+vec3(1.0)*(1.0-sourceAlpha);
-#endif
-
-
-#ifdef IMAGEPROCESSINGPOSTPROCESS
-baseColor.rgb=toLinearSpace(baseColor.rgb);
-#else
-#ifdef IMAGEPROCESSING
-baseColor.rgb=toLinearSpace(baseColor.rgb);
-baseColor=applyImageProcessing(baseColor);
-#endif
-#endif
-gl_FragColor=baseColor;
-}`;ze.a.ShadersStore.particlesPixelShader=Lm;var Nm=`
-attribute vec3 position;
-attribute vec4 color;
-attribute float angle;
-attribute vec2 size;
-#ifdef ANIMATESHEET
-attribute float cellIndex;
-#endif
-#ifndef BILLBOARD
-attribute vec3 direction;
-#endif
-#ifdef BILLBOARDSTRETCHED
-attribute vec3 direction;
-#endif
-#ifdef RAMPGRADIENT
-attribute vec4 remapData;
-#endif
-attribute vec2 offset;
-
-uniform mat4 view;
-uniform mat4 projection;
-uniform vec2 translationPivot;
-#ifdef ANIMATESHEET
-uniform vec3 particlesInfos;
-#endif
-
-varying vec2 vUV;
-varying vec4 vColor;
-varying vec3 vPositionW;
-#ifdef RAMPGRADIENT
-varying vec4 remapRanges;
-#endif
-#if defined(BILLBOARD) && !defined(BILLBOARDY) && !defined(BILLBOARDSTRETCHED)
-uniform mat4 invView;
-#endif
-#include<clipPlaneVertexDeclaration>
-#ifdef BILLBOARD
-uniform vec3 eyePosition;
-#endif
-vec3 rotate(vec3 yaxis,vec3 rotatedCorner) {
-vec3 xaxis=normalize(cross(vec3(0.,1.0,0.),yaxis));
-vec3 zaxis=normalize(cross(yaxis,xaxis));
-vec3 row0=vec3(xaxis.x,xaxis.y,xaxis.z);
-vec3 row1=vec3(yaxis.x,yaxis.y,yaxis.z);
-vec3 row2=vec3(zaxis.x,zaxis.y,zaxis.z);
-mat3 rotMatrix=mat3(row0,row1,row2);
-vec3 alignedCorner=rotMatrix*rotatedCorner;
-return position+alignedCorner;
-}
-#ifdef BILLBOARDSTRETCHED
-vec3 rotateAlign(vec3 toCamera,vec3 rotatedCorner) {
-vec3 normalizedToCamera=normalize(toCamera);
-vec3 normalizedCrossDirToCamera=normalize(cross(normalize(direction),normalizedToCamera));
-vec3 crossProduct=normalize(cross(normalizedToCamera,normalizedCrossDirToCamera));
-vec3 row0=vec3(normalizedCrossDirToCamera.x,normalizedCrossDirToCamera.y,normalizedCrossDirToCamera.z);
-vec3 row1=vec3(crossProduct.x,crossProduct.y,crossProduct.z);
-vec3 row2=vec3(normalizedToCamera.x,normalizedToCamera.y,normalizedToCamera.z);
-mat3 rotMatrix=mat3(row0,row1,row2);
-vec3 alignedCorner=rotMatrix*rotatedCorner;
-return position+alignedCorner;
-}
-#endif
-void main(void) {
-vec2 cornerPos;
-cornerPos=(vec2(offset.x-0.5,offset.y-0.5)-translationPivot)*size+translationPivot;
-#ifdef BILLBOARD
-
-vec3 rotatedCorner;
-#ifdef BILLBOARDY
-rotatedCorner.x=cornerPos.x*cos(angle)-cornerPos.y*sin(angle);
-rotatedCorner.z=cornerPos.x*sin(angle)+cornerPos.y*cos(angle);
-rotatedCorner.y=0.;
-vec3 yaxis=position-eyePosition;
-yaxis.y=0.;
-vPositionW=rotate(normalize(yaxis),rotatedCorner);
-vec3 viewPos=(view*vec4(vPositionW,1.0)).xyz;
-#elif defined(BILLBOARDSTRETCHED)
-rotatedCorner.x=cornerPos.x*cos(angle)-cornerPos.y*sin(angle);
-rotatedCorner.y=cornerPos.x*sin(angle)+cornerPos.y*cos(angle);
-rotatedCorner.z=0.;
-vec3 toCamera=position-eyePosition;
-vPositionW=rotateAlign(toCamera,rotatedCorner);
-vec3 viewPos=(view*vec4(vPositionW,1.0)).xyz;
-#else
-rotatedCorner.x=cornerPos.x*cos(angle)-cornerPos.y*sin(angle);
-rotatedCorner.y=cornerPos.x*sin(angle)+cornerPos.y*cos(angle);
-rotatedCorner.z=0.;
-vec3 viewPos=(view*vec4(position,1.0)).xyz+rotatedCorner;
-vPositionW=(invView*vec4(viewPos,1)).xyz;
-#endif
-#ifdef RAMPGRADIENT
-remapRanges=remapData;
-#endif
-
-gl_Position=projection*vec4(viewPos,1.0);
-#else
-
-vec3 rotatedCorner;
-rotatedCorner.x=cornerPos.x*cos(angle)-cornerPos.y*sin(angle);
-rotatedCorner.z=cornerPos.x*sin(angle)+cornerPos.y*cos(angle);
-rotatedCorner.y=0.;
-vec3 yaxis=normalize(direction);
-vPositionW=rotate(yaxis,rotatedCorner);
-gl_Position=projection*view*vec4(vPositionW,1.0);
-#endif
-vColor=color;
-#ifdef ANIMATESHEET
-float rowOffset=floor(cellIndex*particlesInfos.z);
-float columnOffset=cellIndex-rowOffset/particlesInfos.z;
-vec2 uvScale=particlesInfos.xy;
-vec2 uvOffset=vec2(offset.x ,1.0-offset.y);
-vUV=(uvOffset+vec2(columnOffset,rowOffset))*uvScale;
-#else
-vUV=offset;
-#endif
-
-#if defined(CLIPPLANE) || defined(CLIPPLANE2) || defined(CLIPPLANE3) || defined(CLIPPLANE4) || defined(CLIPPLANE5) || defined(CLIPPLANE6)
-vec4 worldPos=vec4(vPositionW,1.0);
-#endif
-#include<clipPlaneVertex>
-}`;ze.a.ShadersStore.particlesVertexShader=Nm;var ln=function(r){function t(e,n,i,o,a,s){o===void 0&&(o=null),a===void 0&&(a=!1),s===void 0&&(s=.01);var d=r.call(this,e)||this;return d._inheritedVelocityOffset=new u.e,d.onDisposeObservable=new x.c,d.onStoppedObservable=new x.c,d._particles=new Array,d._stockParticles=new Array,d._newPartsExcess=0,d._vertexBuffers={},d._scaledColorStep=new M.b(0,0,0,0),d._colorDiff=new M.b(0,0,0,0),d._scaledDirection=u.e.Zero(),d._scaledGravity=u.e.Zero(),d._currentRenderId=-1,d._useInstancing=!1,d._started=!1,d._stopped=!1,d._actualFrame=0,d._currentEmitRate1=0,d._currentEmitRate2=0,d._currentStartSize1=0,d._currentStartSize2=0,d._rawTextureWidth=256,d._useRampGradients=!1,d._disposeEmitterOnDispose=!1,d.isLocal=!1,d._onBeforeDrawParticlesObservable=null,d.recycleParticle=function(p){var b=d._particles.pop();b!==p&&b.copyTo(p),d._stockParticles.push(b)},d._createParticle=function(){var p;if(d._stockParticles.length!==0?(p=d._stockParticles.pop())._reset():p=new Ad(d),d._subEmitters&&d._subEmitters.length>0){var b=d._subEmitters[Math.floor(Math.random()*d._subEmitters.length)];p._attachedSubEmitters=[],b.forEach(function(P){if(P.type===Fr.ATTACHED){var O=P.clone();p._attachedSubEmitters.push(O),O.particleSystem.start()}})}return p},d._emitFromParticle=function(p){if(d._subEmitters&&d._subEmitters.length!==0){var b=Math.floor(Math.random()*d._subEmitters.length);d._subEmitters[b].forEach(function(P){if(P.type===Fr.END){var O=P.clone();p._inheritParticleInfoToSubEmitter(O),O.particleSystem._rootParticleSystem=d,d.activeSubSystems.push(O.particleSystem),O.particleSystem.start()}})}},d._capacity=n,d._epsilon=s,d._isAnimationSheetEnabled=a,i&&i.getClassName()!=="Scene"?(d._engine=i,d.defaultProjectionMatrix=u.a.PerspectiveFovLH(.8,1,.1,100)):(d._scene=i||te.a.LastCreatedScene,d._engine=d._scene.getEngine(),d.uniqueId=d._scene.getUniqueId(),d._scene.particleSystems.push(d)),d._engine.getCaps().vertexArrayObject&&(d._vertexArrayObject=null),d._attachImageProcessingConfiguration(null),d._customEffect={0:o},d._useInstancing=d._engine.getCaps().instancedArrays,d._createIndexBuffer(),d._createVertexBuffers(),d.particleEmitterType=new Nr,d.updateFunction=function(p){var b=null,P=null;d.noiseTexture&&(b=d.noiseTexture.getSize(),P=d.noiseTexture.getContent());for(var O,B=function(){O=p[F];var z=d._scaledUpdateSpeed,J=O.age;if(O.age+=z,O.age>O.lifeTime){var ie=O.age-J;z=(O.lifeTime-J)*z/ie,O.age=O.lifeTime}var se=O.age/O.lifeTime;d._colorGradients&&d._colorGradients.length>0?In.GetCurrentGradient(se,d._colorGradients,function(Ae,Ee,Se){Ae!==O._currentColorGradient&&(O._currentColor1.copyFrom(O._currentColor2),Ee.getColorToRef(O._currentColor2),O._currentColorGradient=Ae),M.b.LerpToRef(O._currentColor1,O._currentColor2,Se,O.color)}):(O.colorStep.scaleToRef(z,d._scaledColorStep),O.color.addInPlace(d._scaledColorStep),O.color.a<0&&(O.color.a=0)),d._angularSpeedGradients&&d._angularSpeedGradients.length>0&&In.GetCurrentGradient(se,d._angularSpeedGradients,function(Ae,Ee,Se){Ae!==O._currentAngularSpeedGradient&&(O._currentAngularSpeed1=O._currentAngularSpeed2,O._currentAngularSpeed2=Ee.getFactor(),O._currentAngularSpeedGradient=Ae),O.angularSpeed=$.a.Lerp(O._currentAngularSpeed1,O._currentAngularSpeed2,Se)}),O.angle+=O.angularSpeed*z;var ce=z;if(d._velocityGradients&&d._velocityGradients.length>0&&In.GetCurrentGradient(se,d._velocityGradients,function(Ae,Ee,Se){Ae!==O._currentVelocityGradient&&(O._currentVelocity1=O._currentVelocity2,O._currentVelocity2=Ee.getFactor(),O._currentVelocityGradient=Ae),ce*=$.a.Lerp(O._currentVelocity1,O._currentVelocity2,Se)}),O.direction.scaleToRef(ce,d._scaledDirection),d._limitVelocityGradients&&d._limitVelocityGradients.length>0&&In.GetCurrentGradient(se,d._limitVelocityGradients,function(Ae,Ee,Se){Ae!==O._currentLimitVelocityGradient&&(O._currentLimitVelocity1=O._currentLimitVelocity2,O._currentLimitVelocity2=Ee.getFactor(),O._currentLimitVelocityGradient=Ae);var Le=$.a.Lerp(O._currentLimitVelocity1,O._currentLimitVelocity2,Se);O.direction.length()>Le&&O.direction.scaleInPlace(d.limitVelocityDamping)}),d._dragGradients&&d._dragGradients.length>0&&In.GetCurrentGradient(se,d._dragGradients,function(Ae,Ee,Se){Ae!==O._currentDragGradient&&(O._currentDrag1=O._currentDrag2,O._currentDrag2=Ee.getFactor(),O._currentDragGradient=Ae);var Le=$.a.Lerp(O._currentDrag1,O._currentDrag2,Se);d._scaledDirection.scaleInPlace(1-Le)}),d.isLocal&&O._localPosition?(O._localPosition.addInPlace(d._scaledDirection),u.e.TransformCoordinatesToRef(O._localPosition,d._emitterWorldMatrix,O.position)):O.position.addInPlace(d._scaledDirection),P&&b&&O._randomNoiseCoordinates1){var ue=d._fetchR(O._randomNoiseCoordinates1.x,O._randomNoiseCoordinates1.y,b.width,b.height,P),fe=d._fetchR(O._randomNoiseCoordinates1.z,O._randomNoiseCoordinates2.x,b.width,b.height,P),ve=d._fetchR(O._randomNoiseCoordinates2.y,O._randomNoiseCoordinates2.z,b.width,b.height,P),Te=u.c.Vector3[0],Re=u.c.Vector3[1];Te.copyFromFloats((2*ue-1)*d.noiseStrength.x,(2*fe-1)*d.noiseStrength.y,(2*ve-1)*d.noiseStrength.z),Te.scaleToRef(z,Re),O.direction.addInPlace(Re)}if(d.gravity.scaleToRef(z,d._scaledGravity),O.direction.addInPlace(d._scaledGravity),d._sizeGradients&&d._sizeGradients.length>0&&In.GetCurrentGradient(se,d._sizeGradients,function(Ae,Ee,Se){Ae!==O._currentSizeGradient&&(O._currentSize1=O._currentSize2,O._currentSize2=Ee.getFactor(),O._currentSizeGradient=Ae),O.size=$.a.Lerp(O._currentSize1,O._currentSize2,Se)}),d._useRampGradients&&(d._colorRemapGradients&&d._colorRemapGradients.length>0&&In.GetCurrentGradient(se,d._colorRemapGradients,function(Ae,Ee,Se){var Le=$.a.Lerp(Ae.factor1,Ee.factor1,Se),Ce=$.a.Lerp(Ae.factor2,Ee.factor2,Se);O.remapData.x=Le,O.remapData.y=Ce-Le}),d._alphaRemapGradients&&d._alphaRemapGradients.length>0&&In.GetCurrentGradient(se,d._alphaRemapGradients,function(Ae,Ee,Se){var Le=$.a.Lerp(Ae.factor1,Ee.factor1,Se),Ce=$.a.Lerp(Ae.factor2,Ee.factor2,Se);O.remapData.z=Le,O.remapData.w=Ce-Le})),d._isAnimationSheetEnabled&&O.updateCellIndex(),O._inheritParticleInfoToSubEmitters(),O.age>=O.lifeTime)return d._emitFromParticle(O),O._attachedSubEmitters&&(O._attachedSubEmitters.forEach(function(Ae){Ae.particleSystem.disposeOnStop=!0,Ae.particleSystem.stop()}),O._attachedSubEmitters=null),d.recycleParticle(O),F--,"continue"},F=0;F<p.length;F++)B()},d}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"onDispose",{set:function(e){this._onDisposeObserver&&this.onDisposeObservable.remove(this._onDisposeObserver),this._onDisposeObserver=this.onDisposeObservable.add(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"useRampGradients",{get:function(){return this._useRampGradients},set:function(e){this._useRampGradients!==e&&(this._useRampGradients=e,this._resetEffect())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"particles",{get:function(){return this._particles},enumerable:!1,configurable:!0}),t.prototype.getActiveCount=function(){return this._particles.length},t.prototype.getClassName=function(){return"ParticleSystem"},t.prototype.isStopping=function(){return this._stopped&&this.isAlive()},t.prototype.getCustomEffect=function(e){var n;return e===void 0&&(e=0),(n=this._customEffect[e])!==null&&n!==void 0?n:this._customEffect[0]},t.prototype.setCustomEffect=function(e,n){n===void 0&&(n=0),this._customEffect[n]=e},Object.defineProperty(t.prototype,"onBeforeDrawParticlesObservable",{get:function(){return this._onBeforeDrawParticlesObservable||(this._onBeforeDrawParticlesObservable=new x.c),this._onBeforeDrawParticlesObservable},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vertexShaderName",{get:function(){return"particles"},enumerable:!1,configurable:!0}),t.prototype._addFactorGradient=function(e,n,i,o){var a=new Oc(n,i,o);e.push(a),e.sort(function(s,d){return s.gradient<d.gradient?-1:s.gradient>d.gradient?1:0})},t.prototype._removeFactorGradient=function(e,n){if(e)for(var i=0,o=0,a=e;o<a.length;o++){if(a[o].gradient===n){e.splice(i,1);break}i++}},t.prototype.addLifeTimeGradient=function(e,n,i){return this._lifeTimeGradients||(this._lifeTimeGradients=[]),this._addFactorGradient(this._lifeTimeGradients,e,n,i),this},t.prototype.removeLifeTimeGradient=function(e){return this._removeFactorGradient(this._lifeTimeGradients,e),this},t.prototype.addSizeGradient=function(e,n,i){return this._sizeGradients||(this._sizeGradients=[]),this._addFactorGradient(this._sizeGradients,e,n,i),this},t.prototype.removeSizeGradient=function(e){return this._removeFactorGradient(this._sizeGradients,e),this},t.prototype.addColorRemapGradient=function(e,n,i){return this._colorRemapGradients||(this._colorRemapGradients=[]),this._addFactorGradient(this._colorRemapGradients,e,n,i),this},t.prototype.removeColorRemapGradient=function(e){return this._removeFactorGradient(this._colorRemapGradients,e),this},t.prototype.addAlphaRemapGradient=function(e,n,i){return this._alphaRemapGradients||(this._alphaRemapGradients=[]),this._addFactorGradient(this._alphaRemapGradients,e,n,i),this},t.prototype.removeAlphaRemapGradient=function(e){return this._removeFactorGradient(this._alphaRemapGradients,e),this},t.prototype.addAngularSpeedGradient=function(e,n,i){return this._angularSpeedGradients||(this._angularSpeedGradients=[]),this._addFactorGradient(this._angularSpeedGradients,e,n,i),this},t.prototype.removeAngularSpeedGradient=function(e){return this._removeFactorGradient(this._angularSpeedGradients,e),this},t.prototype.addVelocityGradient=function(e,n,i){return this._velocityGradients||(this._velocityGradients=[]),this._addFactorGradient(this._velocityGradients,e,n,i),this},t.prototype.removeVelocityGradient=function(e){return this._removeFactorGradient(this._velocityGradients,e),this},t.prototype.addLimitVelocityGradient=function(e,n,i){return this._limitVelocityGradients||(this._limitVelocityGradients=[]),this._addFactorGradient(this._limitVelocityGradients,e,n,i),this},t.prototype.removeLimitVelocityGradient=function(e){return this._removeFactorGradient(this._limitVelocityGradients,e),this},t.prototype.addDragGradient=function(e,n,i){return this._dragGradients||(this._dragGradients=[]),this._addFactorGradient(this._dragGradients,e,n,i),this},t.prototype.removeDragGradient=function(e){return this._removeFactorGradient(this._dragGradients,e),this},t.prototype.addEmitRateGradient=function(e,n,i){return this._emitRateGradients||(this._emitRateGradients=[]),this._addFactorGradient(this._emitRateGradients,e,n,i),this},t.prototype.removeEmitRateGradient=function(e){return this._removeFactorGradient(this._emitRateGradients,e),this},t.prototype.addStartSizeGradient=function(e,n,i){return this._startSizeGradients||(this._startSizeGradients=[]),this._addFactorGradient(this._startSizeGradients,e,n,i),this},t.prototype.removeStartSizeGradient=function(e){return this._removeFactorGradient(this._startSizeGradients,e),this},t.prototype._createRampGradientTexture=function(){if(this._rampGradients&&this._rampGradients.length&&!this._rampGradientsTexture&&this._scene){for(var e=new Uint8Array(4*this._rawTextureWidth),n=M.c.Color3[0],i=0;i<this._rawTextureWidth;i++){var o=i/this._rawTextureWidth;In.GetCurrentGradient(o,this._rampGradients,function(a,s,d){M.a.LerpToRef(a.color,s.color,d,n),e[4*i]=255*n.r,e[4*i+1]=255*n.g,e[4*i+2]=255*n.b,e[4*i+3]=255})}this._rampGradientsTexture=ii.CreateRGBATexture(e,this._rawTextureWidth,1,this._scene,!1,!1,h.a.TEXTURE_NEAREST_SAMPLINGMODE)}},t.prototype.getRampGradients=function(){return this._rampGradients},t.prototype.forceRefreshGradients=function(){this._syncRampGradientTexture()},t.prototype._syncRampGradientTexture=function(){this._rampGradients&&(this._rampGradients.sort(function(e,n){return e.gradient<n.gradient?-1:e.gradient>n.gradient?1:0}),this._rampGradientsTexture&&(this._rampGradientsTexture.dispose(),this._rampGradientsTexture=null),this._createRampGradientTexture())},t.prototype.addRampGradient=function(e,n){this._rampGradients||(this._rampGradients=[]);var i=new Sd(e,n);return this._rampGradients.push(i),this._syncRampGradientTexture(),this},t.prototype.removeRampGradient=function(e){return this._removeGradientAndTexture(e,this._rampGradients,this._rampGradientsTexture),this._rampGradientsTexture=null,this._rampGradients&&this._rampGradients.length>0&&this._createRampGradientTexture(),this},t.prototype.addColorGradient=function(e,n,i){this._colorGradients||(this._colorGradients=[]);var o=new Rc(e,n,i);return this._colorGradients.push(o),this._colorGradients.sort(function(a,s){return a.gradient<s.gradient?-1:a.gradient>s.gradient?1:0}),this},t.prototype.removeColorGradient=function(e){if(!this._colorGradients)return this;for(var n=0,i=0,o=this._colorGradients;i<o.length;i++){if(o[i].gradient===e){this._colorGradients.splice(n,1);break}n++}return this},t.prototype._fetchR=function(e,n,i,o,a){return a[4*(((e=.5*Math.abs(e)+.5)*i%i|0)+((n=.5*Math.abs(n)+.5)*o%o|0)*i)]/255},t.prototype._reset=function(){this._resetEffect()},t.prototype._resetEffect=function(){this._vertexBuffer&&(this._vertexBuffer.dispose(),this._vertexBuffer=null),this._spriteBuffer&&(this._spriteBuffer.dispose(),this._spriteBuffer=null),this._vertexArrayObject&&(this._engine.releaseVertexArrayObject(this._vertexArrayObject),this._vertexArrayObject=null),this._createVertexBuffers()},t.prototype._createVertexBuffers=function(){this._vertexBufferSize=this._useInstancing?10:12,this._isAnimationSheetEnabled&&(this._vertexBufferSize+=1),this._isBillboardBased&&this.billboardMode!==t.BILLBOARDMODE_STRETCHED||(this._vertexBufferSize+=3),this._useRampGradients&&(this._vertexBufferSize+=4);var e=this._engine;this._vertexData=new Float32Array(this._capacity*this._vertexBufferSize*(this._useInstancing?1:4)),this._vertexBuffer=new Oe.a(e,this._vertexData,!0,this._vertexBufferSize);var n=0,i=this._vertexBuffer.createVertexBuffer(Oe.b.PositionKind,n,3,this._vertexBufferSize,this._useInstancing);this._vertexBuffers[Oe.b.PositionKind]=i,n+=3;var o=this._vertexBuffer.createVertexBuffer(Oe.b.ColorKind,n,4,this._vertexBufferSize,this._useInstancing);this._vertexBuffers[Oe.b.ColorKind]=o,n+=4;var a=this._vertexBuffer.createVertexBuffer("angle",n,1,this._vertexBufferSize,this._useInstancing);this._vertexBuffers.angle=a,n+=1;var s,d=this._vertexBuffer.createVertexBuffer("size",n,2,this._vertexBufferSize,this._useInstancing);if(this._vertexBuffers.size=d,n+=2,this._isAnimationSheetEnabled){var p=this._vertexBuffer.createVertexBuffer("cellIndex",n,1,this._vertexBufferSize,this._useInstancing);this._vertexBuffers.cellIndex=p,n+=1}if(!this._isBillboardBased||this.billboardMode===t.BILLBOARDMODE_STRETCHED){var b=this._vertexBuffer.createVertexBuffer("direction",n,3,this._vertexBufferSize,this._useInstancing);this._vertexBuffers.direction=b,n+=3}if(this._useRampGradients){var P=this._vertexBuffer.createVertexBuffer("remapData",n,4,this._vertexBufferSize,this._useInstancing);this._vertexBuffers.remapData=P,n+=4}if(this._useInstancing){var O=new Float32Array([0,0,1,0,1,1,0,1]);this._spriteBuffer=new Oe.a(e,O,!1,2),s=this._spriteBuffer.createVertexBuffer("offset",0,2)}else s=this._vertexBuffer.createVertexBuffer("offset",n,2,this._vertexBufferSize,this._useInstancing),n+=2;this._vertexBuffers.offset=s},t.prototype._createIndexBuffer=function(){if(!this._useInstancing){for(var e=[],n=0,i=0;i<this._capacity;i++)e.push(n),e.push(n+1),e.push(n+2),e.push(n),e.push(n+2),e.push(n+3),n+=4;this._indexBuffer=this._engine.createIndexBuffer(e)}},t.prototype.getCapacity=function(){return this._capacity},t.prototype.isAlive=function(){return this._alive},t.prototype.isStarted=function(){return this._started},t.prototype._prepareSubEmitterInternalArray=function(){var e=this;this._subEmitters=new Array,this.subEmitters&&this.subEmitters.forEach(function(n){n instanceof t?e._subEmitters.push([new xo(n)]):n instanceof xo?e._subEmitters.push([n]):n instanceof Array&&e._subEmitters.push(n)})},t.prototype.start=function(e){var n,i=this;if(e===void 0&&(e=this.startDelay),!this.targetStopDuration&&this._hasTargetStopDurationDependantGradient())throw"Particle system started with a targetStopDuration dependant gradient (eg. startSizeGradients) but no targetStopDuration set";if(e)setTimeout(function(){i.start(0)},e);else{if(this._prepareSubEmitterInternalArray(),this._started=!0,this._stopped=!1,this._actualFrame=0,this._subEmitters&&this._subEmitters.length!=0&&(this.activeSubSystems=new Array),this._emitRateGradients&&(this._emitRateGradients.length>0&&(this._currentEmitRateGradient=this._emitRateGradients[0],this._currentEmitRate1=this._currentEmitRateGradient.getFactor(),this._currentEmitRate2=this._currentEmitRate1),this._emitRateGradients.length>1&&(this._currentEmitRate2=this._emitRateGradients[1].getFactor())),this._startSizeGradients&&(this._startSizeGradients.length>0&&(this._currentStartSizeGradient=this._startSizeGradients[0],this._currentStartSize1=this._currentStartSizeGradient.getFactor(),this._currentStartSize2=this._currentStartSize1),this._startSizeGradients.length>1&&(this._currentStartSize2=this._startSizeGradients[1].getFactor())),this.preWarmCycles){((n=this.emitter)===null||n===void 0?void 0:n.getClassName().indexOf("Mesh"))!==-1&&this.emitter.computeWorldMatrix(!0);var o=this.noiseTexture;if(o&&o.onGeneratedObservable)o.onGeneratedObservable.addOnce(function(){setTimeout(function(){for(var s=0;s<i.preWarmCycles;s++)i.animate(!0),o.render()})});else for(var a=0;a<this.preWarmCycles;a++)this.animate(!0)}this.beginAnimationOnStart&&this.animations&&this.animations.length>0&&this._scene&&this._scene.beginAnimation(this,this.beginAnimationFrom,this.beginAnimationTo,this.beginAnimationLoop)}},t.prototype.stop=function(e){e===void 0&&(e=!0),this._stopped||(this.onStoppedObservable.notifyObservers(this),this._stopped=!0,e&&this._stopSubEmitters())},t.prototype.reset=function(){this._stockParticles=[],this._particles=[]},t.prototype._appendParticleVertex=function(e,n,i,o){var a=e*this._vertexBufferSize;if(this._vertexData[a++]=n.position.x+this.worldOffset.x,this._vertexData[a++]=n.position.y+this.worldOffset.y,this._vertexData[a++]=n.position.z+this.worldOffset.z,this._vertexData[a++]=n.color.r,this._vertexData[a++]=n.color.g,this._vertexData[a++]=n.color.b,this._vertexData[a++]=n.color.a,this._vertexData[a++]=n.angle,this._vertexData[a++]=n.scale.x*n.size,this._vertexData[a++]=n.scale.y*n.size,this._isAnimationSheetEnabled&&(this._vertexData[a++]=n.cellIndex),this._isBillboardBased)this.billboardMode===t.BILLBOARDMODE_STRETCHED&&(this._vertexData[a++]=n.direction.x,this._vertexData[a++]=n.direction.y,this._vertexData[a++]=n.direction.z);else if(n._initialDirection){var s=n._initialDirection;this.isLocal&&(u.e.TransformNormalToRef(s,this._emitterWorldMatrix,u.c.Vector3[0]),s=u.c.Vector3[0]),s.x===0&&s.z===0&&(s.x=.001),this._vertexData[a++]=s.x,this._vertexData[a++]=s.y,this._vertexData[a++]=s.z}else{var d=n.direction;this.isLocal&&(u.e.TransformNormalToRef(d,this._emitterWorldMatrix,u.c.Vector3[0]),d=u.c.Vector3[0]),d.x===0&&d.z===0&&(d.x=.001),this._vertexData[a++]=d.x,this._vertexData[a++]=d.y,this._vertexData[a++]=d.z}this._useRampGradients&&n.remapData&&(this._vertexData[a++]=n.remapData.x,this._vertexData[a++]=n.remapData.y,this._vertexData[a++]=n.remapData.z,this._vertexData[a++]=n.remapData.w),this._useInstancing||(this._isAnimationSheetEnabled&&(i===0?i=this._epsilon:i===1&&(i=1-this._epsilon),o===0?o=this._epsilon:o===1&&(o=1-this._epsilon)),this._vertexData[a++]=i,this._vertexData[a++]=o)},t.prototype._stopSubEmitters=function(){this.activeSubSystems&&(this.activeSubSystems.forEach(function(e){e.stop(!0)}),this.activeSubSystems=new Array)},t.prototype._removeFromRoot=function(){if(this._rootParticleSystem){var e=this._rootParticleSystem.activeSubSystems.indexOf(this);e!==-1&&this._rootParticleSystem.activeSubSystems.splice(e,1),this._rootParticleSystem=null}},t.prototype._update=function(e){var n,i=this;if(this._alive=this._particles.length>0,this.emitter.position){var o=this.emitter;this._emitterWorldMatrix=o.getWorldMatrix()}else{var a=this.emitter;this._emitterWorldMatrix=u.a.Translation(a.x,a.y,a.z)}this.updateFunction(this._particles);for(var s,d=function(){if(p._particles.length===p._capacity)return"break";if(n=p._createParticle(),p._particles.push(n),p.targetStopDuration&&p._lifeTimeGradients&&p._lifeTimeGradients.length>0){var P=$.a.Clamp(p._actualFrame/p.targetStopDuration);In.GetCurrentGradient(P,p._lifeTimeGradients,function(F,z){var J=F,ie=z,se=J.getFactor(),ce=ie.getFactor(),ue=(P-J.gradient)/(ie.gradient-J.gradient);n.lifeTime=$.a.Lerp(se,ce,ue)})}else n.lifeTime=$.a.RandomRange(p.minLifeTime,p.maxLifeTime);var O=$.a.RandomRange(p.minEmitPower,p.maxEmitPower);if(p.startPositionFunction?p.startPositionFunction(p._emitterWorldMatrix,n.position,n,p.isLocal):p.particleEmitterType.startPositionFunction(p._emitterWorldMatrix,n.position,n,p.isLocal),p.isLocal&&(n._localPosition?n._localPosition.copyFrom(n.position):n._localPosition=n.position.clone(),u.e.TransformCoordinatesToRef(n._localPosition,p._emitterWorldMatrix,n.position)),p.startDirectionFunction?p.startDirectionFunction(p._emitterWorldMatrix,n.direction,n,p.isLocal):p.particleEmitterType.startDirectionFunction(p._emitterWorldMatrix,n.direction,n,p.isLocal),O===0?n._initialDirection?n._initialDirection.copyFrom(n.direction):n._initialDirection=n.direction.clone():n._initialDirection=null,n.direction.scaleInPlace(O),p._sizeGradients&&p._sizeGradients.length!==0?(n._currentSizeGradient=p._sizeGradients[0],n._currentSize1=n._currentSizeGradient.getFactor(),n.size=n._currentSize1,p._sizeGradients.length>1?n._currentSize2=p._sizeGradients[1].getFactor():n._currentSize2=n._currentSize1):n.size=$.a.RandomRange(p.minSize,p.maxSize),n.scale.copyFromFloats($.a.RandomRange(p.minScaleX,p.maxScaleX),$.a.RandomRange(p.minScaleY,p.maxScaleY)),p._startSizeGradients&&p._startSizeGradients[0]&&p.targetStopDuration){var B=p._actualFrame/p.targetStopDuration;In.GetCurrentGradient(B,p._startSizeGradients,function(F,z,J){F!==i._currentStartSizeGradient&&(i._currentStartSize1=i._currentStartSize2,i._currentStartSize2=z.getFactor(),i._currentStartSizeGradient=F);var ie=$.a.Lerp(i._currentStartSize1,i._currentStartSize2,J);n.scale.scaleInPlace(ie)})}p._angularSpeedGradients&&p._angularSpeedGradients.length!==0?(n._currentAngularSpeedGradient=p._angularSpeedGradients[0],n.angularSpeed=n._currentAngularSpeedGradient.getFactor(),n._currentAngularSpeed1=n.angularSpeed,p._angularSpeedGradients.length>1?n._currentAngularSpeed2=p._angularSpeedGradients[1].getFactor():n._currentAngularSpeed2=n._currentAngularSpeed1):n.angularSpeed=$.a.RandomRange(p.minAngularSpeed,p.maxAngularSpeed),n.angle=$.a.RandomRange(p.minInitialRotation,p.maxInitialRotation),p._velocityGradients&&p._velocityGradients.length>0&&(n._currentVelocityGradient=p._velocityGradients[0],n._currentVelocity1=n._currentVelocityGradient.getFactor(),p._velocityGradients.length>1?n._currentVelocity2=p._velocityGradients[1].getFactor():n._currentVelocity2=n._currentVelocity1),p._limitVelocityGradients&&p._limitVelocityGradients.length>0&&(n._currentLimitVelocityGradient=p._limitVelocityGradients[0],n._currentLimitVelocity1=n._currentLimitVelocityGradient.getFactor(),p._limitVelocityGradients.length>1?n._currentLimitVelocity2=p._limitVelocityGradients[1].getFactor():n._currentLimitVelocity2=n._currentLimitVelocity1),p._dragGradients&&p._dragGradients.length>0&&(n._currentDragGradient=p._dragGradients[0],n._currentDrag1=n._currentDragGradient.getFactor(),p._dragGradients.length>1?n._currentDrag2=p._dragGradients[1].getFactor():n._currentDrag2=n._currentDrag1),p._colorGradients&&p._colorGradients.length!==0?(n._currentColorGradient=p._colorGradients[0],n._currentColorGradient.getColorToRef(n.color),n._currentColor1.copyFrom(n.color),p._colorGradients.length>1?p._colorGradients[1].getColorToRef(n._currentColor2):n._currentColor2.copyFrom(n.color)):(s=$.a.RandomRange(0,1),M.b.LerpToRef(p.color1,p.color2,s,n.color),p.colorDead.subtractToRef(n.color,p._colorDiff),p._colorDiff.scaleToRef(1/n.lifeTime,n.colorStep)),p._isAnimationSheetEnabled&&(n._initialStartSpriteCellID=p.startSpriteCellID,n._initialEndSpriteCellID=p.endSpriteCellID),n.direction.addInPlace(p._inheritedVelocityOffset),p._useRampGradients&&(n.remapData=new u.f(0,1,0,1)),p.noiseTexture&&(n._randomNoiseCoordinates1?(n._randomNoiseCoordinates1.copyFromFloats(Math.random(),Math.random(),Math.random()),n._randomNoiseCoordinates2.copyFromFloats(Math.random(),Math.random(),Math.random())):(n._randomNoiseCoordinates1=new u.e(Math.random(),Math.random(),Math.random()),n._randomNoiseCoordinates2=new u.e(Math.random(),Math.random(),Math.random()))),n._inheritParticleInfoToSubEmitters()},p=this,b=0;b<e&&d()!=="break";b++);},t._GetAttributeNamesOrOptions=function(e,n,i){e===void 0&&(e=!1),n===void 0&&(n=!1),i===void 0&&(i=!1);var o=[Oe.b.PositionKind,Oe.b.ColorKind,"angle","offset","size"];return e&&o.push("cellIndex"),n||o.push("direction"),i&&o.push("remapData"),o},t._GetEffectCreationOptions=function(e){e===void 0&&(e=!1);var n=["invView","view","projection","vClipPlane","vClipPlane2","vClipPlane3","vClipPlane4","vClipPlane5","vClipPlane6","textureMask","translationPivot","eyePosition"];return e&&n.push("particlesInfos"),n},t.prototype.fillDefines=function(e,n){if(this._scene&&(this._scene.clipPlane&&e.push("#define CLIPPLANE"),this._scene.clipPlane2&&e.push("#define CLIPPLANE2"),this._scene.clipPlane3&&e.push("#define CLIPPLANE3"),this._scene.clipPlane4&&e.push("#define CLIPPLANE4"),this._scene.clipPlane5&&e.push("#define CLIPPLANE5"),this._scene.clipPlane6&&e.push("#define CLIPPLANE6")),this._isAnimationSheetEnabled&&e.push("#define ANIMATESHEET"),n===t.BLENDMODE_MULTIPLY&&e.push("#define BLENDMULTIPLYMODE"),this._useRampGradients&&e.push("#define RAMPGRADIENT"),this._isBillboardBased)switch(e.push("#define BILLBOARD"),this.billboardMode){case t.BILLBOARDMODE_Y:e.push("#define BILLBOARDY");break;case t.BILLBOARDMODE_STRETCHED:e.push("#define BILLBOARDSTRETCHED");break;case t.BILLBOARDMODE_ALL:e.push("#define BILLBOARDMODE_ALL")}this._imageProcessingConfiguration&&(this._imageProcessingConfiguration.prepareDefines(this._imageProcessingConfigurationDefines),e.push(this._imageProcessingConfigurationDefines.toString()))},t.prototype.fillUniformsAttributesAndSamplerNames=function(e,n,i){n.push.apply(n,t._GetAttributeNamesOrOptions(this._isAnimationSheetEnabled,this._isBillboardBased&&this.billboardMode!==t.BILLBOARDMODE_STRETCHED,this._useRampGradients)),e.push.apply(e,t._GetEffectCreationOptions(this._isAnimationSheetEnabled)),i.push("diffuseSampler","rampSampler"),this._imageProcessingConfiguration&&(yn.a.PrepareUniforms(e,this._imageProcessingConfigurationDefines),yn.a.PrepareSamplers(i,this._imageProcessingConfigurationDefines))},t.prototype._getEffect=function(e){var n=this.getCustomEffect(e);if(n)return n;var i=[];this.fillDefines(i,e);var o=i.join(`
-`);if(this._cachedDefines!==o){this._cachedDefines=o;var a=[],s=[],d=[];this.fillUniformsAttributesAndSamplerNames(s,a,d),this._effect=this._engine.createEffect("particles",a,s,d,o)}return this._effect},t.prototype.animate=function(e){var n,i=this;if(e===void 0&&(e=!1),this._started){if(!e&&this._scene){if(!this.isReady()||this._currentRenderId===this._scene.getFrameId())return;this._currentRenderId=this._scene.getFrameId()}var o;if(this._scaledUpdateSpeed=this.updateSpeed*(e?this.preWarmStepOffset:((n=this._scene)===null||n===void 0?void 0:n.getAnimationRatio())||1),this.manualEmitCount>-1)o=this.manualEmitCount,this._newPartsExcess=0,this.manualEmitCount=0;else{var a=this.emitRate;if(this._emitRateGradients&&this._emitRateGradients.length>0&&this.targetStopDuration){var s=this._actualFrame/this.targetStopDuration;In.GetCurrentGradient(s,this._emitRateGradients,function(P,O,B){P!==i._currentEmitRateGradient&&(i._currentEmitRate1=i._currentEmitRate2,i._currentEmitRate2=O.getFactor(),i._currentEmitRateGradient=P),a=$.a.Lerp(i._currentEmitRate1,i._currentEmitRate2,B)})}o=a*this._scaledUpdateSpeed>>0,this._newPartsExcess+=a*this._scaledUpdateSpeed-o}if(this._newPartsExcess>1&&(o+=this._newPartsExcess>>0,this._newPartsExcess-=this._newPartsExcess>>0),this._alive=!1,this._stopped?o=0:(this._actualFrame+=this._scaledUpdateSpeed,this.targetStopDuration&&this._actualFrame>=this.targetStopDuration&&this.stop()),this._update(o),this._stopped&&(this._alive||(this._started=!1,this.onAnimationEnd&&this.onAnimationEnd(),this.disposeOnStop&&this._scene&&this._scene._toBeDisposed.push(this))),!e){for(var d=0,p=0;p<this._particles.length;p++){var b=this._particles[p];this._appendParticleVertices(d,b),d+=this._useInstancing?1:4}this._vertexBuffer&&this._vertexBuffer.update(this._vertexData)}this.manualEmitCount===0&&this.disposeOnStop&&this.stop()}},t.prototype._appendParticleVertices=function(e,n){this._appendParticleVertex(e++,n,0,0),this._useInstancing||(this._appendParticleVertex(e++,n,1,0),this._appendParticleVertex(e++,n,1,1),this._appendParticleVertex(e++,n,0,1))},t.prototype.rebuild=function(){for(var e in this._createIndexBuffer(),this._vertexBuffer&&this._vertexBuffer._rebuild(),this._vertexBuffers)this._vertexBuffers[e]._rebuild()},t.prototype.isReady=function(){if(!this.emitter||this._imageProcessingConfiguration&&!this._imageProcessingConfiguration.isReady()||!this.particleTexture||!this.particleTexture.isReady())return!1;if(this.blendMode!==t.BLENDMODE_MULTIPLYADD){if(!this._getEffect(this.blendMode).isReady())return!1}else if(!this._getEffect(t.BLENDMODE_MULTIPLY).isReady()||!this._getEffect(t.BLENDMODE_ADD).isReady())return!1;return!0},t.prototype._render=function(e){var n,i,o=this._getEffect(e),a=this._engine;a.enableEffect(o);var s=(n=this.defaultViewMatrix)!==null&&n!==void 0?n:this._scene.getViewMatrix();if(o.setTexture("diffuseSampler",this.particleTexture),o.setMatrix("view",s),o.setMatrix("projection",(i=this.defaultProjectionMatrix)!==null&&i!==void 0?i:this._scene.getProjectionMatrix()),this._isAnimationSheetEnabled&&this.particleTexture){var d=this.particleTexture.getBaseSize();o.setFloat3("particlesInfos",this.spriteCellWidth/d.width,this.spriteCellHeight/d.height,this.spriteCellWidth/d.width)}if(o.setVector2("translationPivot",this.translationPivot),o.setFloat4("textureMask",this.textureMask.r,this.textureMask.g,this.textureMask.b,this.textureMask.a),this._isBillboardBased&&this._scene){var p=this._scene.activeCamera;o.setVector3("eyePosition",p.globalPosition)}this._rampGradientsTexture&&(this._rampGradients&&this._rampGradients.length||(this._rampGradientsTexture.dispose(),this._rampGradientsTexture=null),o.setTexture("rampSampler",this._rampGradientsTexture));var b=o.defines;switch(this._scene&&(this._scene.clipPlane||this._scene.clipPlane2||this._scene.clipPlane3||this._scene.clipPlane4||this._scene.clipPlane5||this._scene.clipPlane6)&&eh.a.BindClipPlane(o,this._scene),b.indexOf("#define BILLBOARDMODE_ALL")>=0&&(s.invertToRef(u.c.Matrix[0]),o.setMatrix("invView",u.c.Matrix[0])),this._vertexArrayObject!==void 0?(this._vertexArrayObject||(this._vertexArrayObject=this._engine.recordVertexArrayObject(this._vertexBuffers,this._indexBuffer,o)),this._engine.bindVertexArrayObject(this._vertexArrayObject,this._indexBuffer)):a.bindBuffers(this._vertexBuffers,this._indexBuffer,o),this._imageProcessingConfiguration&&!this._imageProcessingConfiguration.applyByPostProcess&&this._imageProcessingConfiguration.bind(o),e){case t.BLENDMODE_ADD:a.setAlphaMode(h.a.ALPHA_ADD);break;case t.BLENDMODE_ONEONE:a.setAlphaMode(h.a.ALPHA_ONEONE);break;case t.BLENDMODE_STANDARD:a.setAlphaMode(h.a.ALPHA_COMBINE);break;case t.BLENDMODE_MULTIPLY:a.setAlphaMode(h.a.ALPHA_MULTIPLY)}return this._onBeforeDrawParticlesObservable&&this._onBeforeDrawParticlesObservable.notifyObservers(o),this._useInstancing?a.drawArraysType(h.a.MATERIAL_TriangleFanDrawMode,0,4,this._particles.length):a.drawElementsType(h.a.MATERIAL_TriangleFillMode,0,6*this._particles.length),this._particles.length},t.prototype.render=function(){if(!this.isReady()||!this._particles.length)return 0;var e=this._engine;e.setState&&(e.setState(!1),this.forceDepthWrite&&e.setDepthWrite(!0));var n=0;return n=this.blendMode===t.BLENDMODE_MULTIPLYADD?this._render(t.BLENDMODE_MULTIPLY)+this._render(t.BLENDMODE_ADD):this._render(this.blendMode),this._engine.unbindInstanceAttributes(),this._engine.setAlphaMode(h.a.ALPHA_DISABLE),n},t.prototype.dispose=function(e){if(e===void 0&&(e=!0),this._vertexBuffer&&(this._vertexBuffer.dispose(),this._vertexBuffer=null),this._spriteBuffer&&(this._spriteBuffer.dispose(),this._spriteBuffer=null),this._indexBuffer&&(this._engine._releaseBuffer(this._indexBuffer),this._indexBuffer=null),this._vertexArrayObject&&(this._engine.releaseVertexArrayObject(this._vertexArrayObject),this._vertexArrayObject=null),e&&this.particleTexture&&(this.particleTexture.dispose(),this.particleTexture=null),e&&this.noiseTexture&&(this.noiseTexture.dispose(),this.noiseTexture=null),this._rampGradientsTexture&&(this._rampGradientsTexture.dispose(),this._rampGradientsTexture=null),this._removeFromRoot(),this._subEmitters&&this._subEmitters.length){for(var n=0;n<this._subEmitters.length;n++)for(var i=0,o=this._subEmitters[n];i<o.length;i++)o[i].dispose();this._subEmitters=[],this.subEmitters=[]}this._disposeEmitterOnDispose&&this.emitter&&this.emitter.dispose&&this.emitter.dispose(!0),this._onBeforeDrawParticlesObservable&&this._onBeforeDrawParticlesObservable.clear(),this._scene&&((n=this._scene.particleSystems.indexOf(this))>-1&&this._scene.particleSystems.splice(n,1),this._scene._activeParticleSystems.dispose()),this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear(),this.onStoppedObservable.clear(),this.reset()},t.prototype.clone=function(e,n){var i=Object(c.a)({},this._customEffect),o=null,a=this._engine;if(a.createEffectForParticles&&this.customShader!=null){var s=(o=this.customShader).shaderOptions.defines.length>0?o.shaderOptions.defines.join(`
-`):"";i[0]=a.createEffectForParticles(o.shaderPath.fragmentElement,o.shaderOptions.uniforms,o.shaderOptions.samplers,s)}var d=this.serialize(),p=t.Parse(d,this._scene||this._engine,"");return p.name=e,p.customShader=o,p._customEffect=i,n===void 0&&(n=this.emitter),this.noiseTexture&&(p.noiseTexture=this.noiseTexture.clone()),p.emitter=n,this.preventAutoStart||p.start(),p},t.prototype.serialize=function(e){e===void 0&&(e=!1);var n={};if(t._Serialize(n,this,e),n.textureMask=this.textureMask.asArray(),n.customShader=this.customShader,n.preventAutoStart=this.preventAutoStart,this.subEmitters){n.subEmitters=[],this._subEmitters||this._prepareSubEmitterInternalArray();for(var i=0,o=this._subEmitters;i<o.length;i++){for(var a=[],s=0,d=o[i];s<d.length;s++){var p=d[s];a.push(p.serialize())}n.subEmitters.push(a)}}return n},t._Serialize=function(e,n,i){if(e.name=n.name,e.id=n.id,e.capacity=n.getCapacity(),n.emitter.position){var o=n.emitter;e.emitterId=o.id}else{var a=n.emitter;e.emitter=a.asArray()}n.particleEmitterType&&(e.particleEmitterType=n.particleEmitterType.serialize()),n.particleTexture&&(i?e.texture=n.particleTexture.serialize():(e.textureName=n.particleTexture.name,e.invertY=!!n.particleTexture._invertY)),e.isLocal=n.isLocal,L.a.AppendSerializedAnimations(n,e),e.beginAnimationOnStart=n.beginAnimationOnStart,e.beginAnimationFrom=n.beginAnimationFrom,e.beginAnimationTo=n.beginAnimationTo,e.beginAnimationLoop=n.beginAnimationLoop,e.startDelay=n.startDelay,e.renderingGroupId=n.renderingGroupId,e.isBillboardBased=n.isBillboardBased,e.billboardMode=n.billboardMode,e.minAngularSpeed=n.minAngularSpeed,e.maxAngularSpeed=n.maxAngularSpeed,e.minSize=n.minSize,e.maxSize=n.maxSize,e.minScaleX=n.minScaleX,e.maxScaleX=n.maxScaleX,e.minScaleY=n.minScaleY,e.maxScaleY=n.maxScaleY,e.minEmitPower=n.minEmitPower,e.maxEmitPower=n.maxEmitPower,e.minLifeTime=n.minLifeTime,e.maxLifeTime=n.maxLifeTime,e.emitRate=n.emitRate,e.gravity=n.gravity.asArray(),e.noiseStrength=n.noiseStrength.asArray(),e.color1=n.color1.asArray(),e.color2=n.color2.asArray(),e.colorDead=n.colorDead.asArray(),e.updateSpeed=n.updateSpeed,e.targetStopDuration=n.targetStopDuration,e.blendMode=n.blendMode,e.preWarmCycles=n.preWarmCycles,e.preWarmStepOffset=n.preWarmStepOffset,e.minInitialRotation=n.minInitialRotation,e.maxInitialRotation=n.maxInitialRotation,e.startSpriteCellID=n.startSpriteCellID,e.endSpriteCellID=n.endSpriteCellID,e.spriteCellChangeSpeed=n.spriteCellChangeSpeed,e.spriteCellWidth=n.spriteCellWidth,e.spriteCellHeight=n.spriteCellHeight,e.spriteRandomStartCell=n.spriteRandomStartCell,e.isAnimationSheetEnabled=n.isAnimationSheetEnabled;var s=n.getColorGradients();if(s){e.colorGradients=[];for(var d=0,p=s;d<p.length;d++){var b=p[d],P={gradient:b.gradient,color1:b.color1.asArray()};b.color2?P.color2=b.color2.asArray():P.color2=b.color1.asArray(),e.colorGradients.push(P)}}var O=n.getRampGradients();if(O){e.rampGradients=[];for(var B=0,F=O;B<F.length;B++){var z=F[B];P={gradient:z.gradient,color:z.color.asArray()},e.rampGradients.push(P)}e.useRampGradients=n.useRampGradients}var J=n.getColorRemapGradients();if(J){e.colorRemapGradients=[];for(var ie=0,se=J;ie<se.length;ie++){var ce=se[ie];P={gradient:ce.gradient,factor1:ce.factor1},ce.factor2!==void 0?P.factor2=ce.factor2:P.factor2=ce.factor1,e.colorRemapGradients.push(P)}}var ue=n.getAlphaRemapGradients();if(ue){e.alphaRemapGradients=[];for(var fe=0,ve=ue;fe<ve.length;fe++){var Te=ve[fe];P={gradient:Te.gradient,factor1:Te.factor1},Te.factor2!==void 0?P.factor2=Te.factor2:P.factor2=Te.factor1,e.alphaRemapGradients.push(P)}}var Re=n.getSizeGradients();if(Re){e.sizeGradients=[];for(var Ae=0,Ee=Re;Ae<Ee.length;Ae++){var Se=Ee[Ae];P={gradient:Se.gradient,factor1:Se.factor1},Se.factor2!==void 0?P.factor2=Se.factor2:P.factor2=Se.factor1,e.sizeGradients.push(P)}}var Le=n.getAngularSpeedGradients();if(Le){e.angularSpeedGradients=[];for(var Ce=0,Ne=Le;Ce<Ne.length;Ce++){var Ie=Ne[Ce];P={gradient:Ie.gradient,factor1:Ie.factor1},Ie.factor2!==void 0?P.factor2=Ie.factor2:P.factor2=Ie.factor1,e.angularSpeedGradients.push(P)}}var Fe=n.getVelocityGradients();if(Fe){e.velocityGradients=[];for(var Ye=0,tt=Fe;Ye<tt.length;Ye++){var it=tt[Ye];P={gradient:it.gradient,factor1:it.factor1},it.factor2!==void 0?P.factor2=it.factor2:P.factor2=it.factor1,e.velocityGradients.push(P)}}var lt=n.getDragGradients();if(lt){e.dragGradients=[];for(var Qe=0,ot=lt;Qe<ot.length;Qe++){var rt=ot[Qe];P={gradient:rt.gradient,factor1:rt.factor1},rt.factor2!==void 0?P.factor2=rt.factor2:P.factor2=rt.factor1,e.dragGradients.push(P)}}var Ze=n.getEmitRateGradients();if(Ze){e.emitRateGradients=[];for(var dt=0,Ve=Ze;dt<Ve.length;dt++){var Je=Ve[dt];P={gradient:Je.gradient,factor1:Je.factor1},Je.factor2!==void 0?P.factor2=Je.factor2:P.factor2=Je.factor1,e.emitRateGradients.push(P)}}var yt=n.getStartSizeGradients();if(yt){e.startSizeGradients=[];for(var Wt=0,Nt=yt;Wt<Nt.length;Wt++){var Qt=Nt[Wt];P={gradient:Qt.gradient,factor1:Qt.factor1},Qt.factor2!==void 0?P.factor2=Qt.factor2:P.factor2=Qt.factor1,e.startSizeGradients.push(P)}}var vt=n.getLifeTimeGradients();if(vt){e.lifeTimeGradients=[];for(var Jt=0,Xt=vt;Jt<Xt.length;Jt++){var zt=Xt[Jt];P={gradient:zt.gradient,factor1:zt.factor1},zt.factor2!==void 0?P.factor2=zt.factor2:P.factor2=zt.factor1,e.lifeTimeGradients.push(P)}}var Yt=n.getLimitVelocityGradients();if(Yt){e.limitVelocityGradients=[];for(var Et=0,Mt=Yt;Et<Mt.length;Et++){var $t=Mt[Et];P={gradient:$t.gradient,factor1:$t.factor1},$t.factor2!==void 0?P.factor2=$t.factor2:P.factor2=$t.factor1,e.limitVelocityGradients.push(P)}e.limitVelocityDamping=n.limitVelocityDamping}n.noiseTexture&&(e.noiseTexture=n.noiseTexture.serialize())},t._Parse=function(e,n,i,o){var a;a=i instanceof Bt.a?null:i;var s,d=R.a.GetClass("BABYLON.Texture");if(d&&a&&(e.texture?n.particleTexture=d.Parse(e.texture,a,o):e.textureName&&(n.particleTexture=new d(o+e.textureName,a,!1,e.invertY===void 0||e.invertY),n.particleTexture.name=e.textureName)),e.emitterId||e.emitterId===0||e.emitter!==void 0?e.emitterId&&a?n.emitter=a.getLastMeshByID(e.emitterId):n.emitter=u.e.FromArray(e.emitter):n.emitter=u.e.Zero(),n.isLocal=!!e.isLocal,e.renderingGroupId!==void 0&&(n.renderingGroupId=e.renderingGroupId),e.isBillboardBased!==void 0&&(n.isBillboardBased=e.isBillboardBased),e.billboardMode!==void 0&&(n.billboardMode=e.billboardMode),e.animations){for(var p=0;p<e.animations.length;p++){var b=e.animations[p],P=R.a.GetClass("BABYLON.Animation");P&&n.animations.push(P.Parse(b))}n.beginAnimationOnStart=e.beginAnimationOnStart,n.beginAnimationFrom=e.beginAnimationFrom,n.beginAnimationTo=e.beginAnimationTo,n.beginAnimationLoop=e.beginAnimationLoop}if(e.autoAnimate&&a&&a.beginAnimation(n,e.autoAnimateFrom,e.autoAnimateTo,e.autoAnimateLoop,e.autoAnimateSpeed||1),n.startDelay=0|e.startDelay,n.minAngularSpeed=e.minAngularSpeed,n.maxAngularSpeed=e.maxAngularSpeed,n.minSize=e.minSize,n.maxSize=e.maxSize,e.minScaleX&&(n.minScaleX=e.minScaleX,n.maxScaleX=e.maxScaleX,n.minScaleY=e.minScaleY,n.maxScaleY=e.maxScaleY),e.preWarmCycles!==void 0&&(n.preWarmCycles=e.preWarmCycles,n.preWarmStepOffset=e.preWarmStepOffset),e.minInitialRotation!==void 0&&(n.minInitialRotation=e.minInitialRotation,n.maxInitialRotation=e.maxInitialRotation),n.minLifeTime=e.minLifeTime,n.maxLifeTime=e.maxLifeTime,n.minEmitPower=e.minEmitPower,n.maxEmitPower=e.maxEmitPower,n.emitRate=e.emitRate,n.gravity=u.e.FromArray(e.gravity),e.noiseStrength&&(n.noiseStrength=u.e.FromArray(e.noiseStrength)),n.color1=M.b.FromArray(e.color1),n.color2=M.b.FromArray(e.color2),n.colorDead=M.b.FromArray(e.colorDead),n.updateSpeed=e.updateSpeed,n.targetStopDuration=e.targetStopDuration,n.blendMode=e.blendMode,e.colorGradients)for(var O=0,B=e.colorGradients;O<B.length;O++){var F=B[O];n.addColorGradient(F.gradient,M.b.FromArray(F.color1),F.color2?M.b.FromArray(F.color2):void 0)}if(e.rampGradients){for(var z=0,J=e.rampGradients;z<J.length;z++){var ie=J[z];n.addRampGradient(ie.gradient,M.a.FromArray(ie.color))}n.useRampGradients=e.useRampGradients}if(e.colorRemapGradients)for(var se=0,ce=e.colorRemapGradients;se<ce.length;se++){var ue=ce[se];n.addColorRemapGradient(ue.gradient,ue.factor1!==void 0?ue.factor1:ue.factor,ue.factor2)}if(e.alphaRemapGradients)for(var fe=0,ve=e.alphaRemapGradients;fe<ve.length;fe++){var Te=ve[fe];n.addAlphaRemapGradient(Te.gradient,Te.factor1!==void 0?Te.factor1:Te.factor,Te.factor2)}if(e.sizeGradients)for(var Re=0,Ae=e.sizeGradients;Re<Ae.length;Re++){var Ee=Ae[Re];n.addSizeGradient(Ee.gradient,Ee.factor1!==void 0?Ee.factor1:Ee.factor,Ee.factor2)}if(e.angularSpeedGradients)for(var Se=0,Le=e.angularSpeedGradients;Se<Le.length;Se++){var Ce=Le[Se];n.addAngularSpeedGradient(Ce.gradient,Ce.factor1!==void 0?Ce.factor1:Ce.factor,Ce.factor2)}if(e.velocityGradients)for(var Ne=0,Ie=e.velocityGradients;Ne<Ie.length;Ne++){var Fe=Ie[Ne];n.addVelocityGradient(Fe.gradient,Fe.factor1!==void 0?Fe.factor1:Fe.factor,Fe.factor2)}if(e.dragGradients)for(var Ye=0,tt=e.dragGradients;Ye<tt.length;Ye++){var it=tt[Ye];n.addDragGradient(it.gradient,it.factor1!==void 0?it.factor1:it.factor,it.factor2)}if(e.emitRateGradients)for(var lt=0,Qe=e.emitRateGradients;lt<Qe.length;lt++){var ot=Qe[lt];n.addEmitRateGradient(ot.gradient,ot.factor1!==void 0?ot.factor1:ot.factor,ot.factor2)}if(e.startSizeGradients)for(var rt=0,Ze=e.startSizeGradients;rt<Ze.length;rt++){var dt=Ze[rt];n.addStartSizeGradient(dt.gradient,dt.factor1!==void 0?dt.factor1:dt.factor,dt.factor2)}if(e.lifeTimeGradients)for(var Ve=0,Je=e.lifeTimeGradients;Ve<Je.length;Ve++){var yt=Je[Ve];n.addLifeTimeGradient(yt.gradient,yt.factor1!==void 0?yt.factor1:yt.factor,yt.factor2)}if(e.limitVelocityGradients){for(var Wt=0,Nt=e.limitVelocityGradients;Wt<Nt.length;Wt++){var Qt=Nt[Wt];n.addLimitVelocityGradient(Qt.gradient,Qt.factor1!==void 0?Qt.factor1:Qt.factor,Qt.factor2)}n.limitVelocityDamping=e.limitVelocityDamping}if(e.noiseTexture&&a){var vt=R.a.GetClass("BABYLON.ProceduralTexture");n.noiseTexture=vt.Parse(e.noiseTexture,a,o)}if(e.particleEmitterType){switch(e.particleEmitterType.type){case"SphereParticleEmitter":s=new ma;break;case"SphereDirectedParticleEmitter":s=new cc;break;case"ConeEmitter":case"ConeParticleEmitter":s=new rc;break;case"CylinderParticleEmitter":s=new _a;break;case"CylinderDirectedParticleEmitter":s=new oc;break;case"HemisphericParticleEmitter":s=new ac;break;case"PointParticleEmitter":s=new sc;break;case"MeshParticleEmitter":s=new hh;break;case"BoxEmitter":case"BoxParticleEmitter":default:s=new Nr}s.parse(e.particleEmitterType,a)}else(s=new Nr).parse(e,a);n.particleEmitterType=s,n.startSpriteCellID=e.startSpriteCellID,n.endSpriteCellID=e.endSpriteCellID,n.spriteCellWidth=e.spriteCellWidth,n.spriteCellHeight=e.spriteCellHeight,n.spriteCellChangeSpeed=e.spriteCellChangeSpeed,n.spriteRandomStartCell=e.spriteRandomStartCell},t.Parse=function(e,n,i,o){o===void 0&&(o=!1);var a,s=e.name,d=null,p=null;if(a=n instanceof Bt.a?n:n.getEngine(),e.customShader&&a.createEffectForParticles){var b=(p=e.customShader).shaderOptions.defines.length>0?p.shaderOptions.defines.join(`
-`):"";d=a.createEffectForParticles(p.shaderPath.fragmentElement,p.shaderOptions.uniforms,p.shaderOptions.samplers,b)}var P=new t(s,e.capacity,n,d,e.isAnimationSheetEnabled);if(P.customShader=p,e.id&&(P.id=e.id),e.subEmitters){P.subEmitters=[];for(var O=0,B=e.subEmitters;O<B.length;O++){for(var F=[],z=0,J=B[O];z<J.length;z++){var ie=J[z];F.push(xo.Parse(ie,n,i))}P.subEmitters.push(F)}}return t._Parse(e,P,n,i),e.textureMask&&(P.textureMask=M.b.FromArray(e.textureMask)),e.preventAutoStart&&(P.preventAutoStart=e.preventAutoStart),o||P.preventAutoStart||P.start(),P},t.BILLBOARDMODE_Y=h.a.PARTICLES_BILLBOARDMODE_Y,t.BILLBOARDMODE_ALL=h.a.PARTICLES_BILLBOARDMODE_ALL,t.BILLBOARDMODE_STRETCHED=h.a.PARTICLES_BILLBOARDMODE_STRETCHED,t}(yo);xo._ParseParticleSystem=ln.Parse,ze.a.ShadersStore.gpuUpdateParticlesPixelShader=`#version 300 es
-void main() {
-discard;
-}
-`;var wm=`#version 300 es
-#define PI 3.14159
-uniform float currentCount;
-uniform float timeDelta;
-uniform float stopFactor;
-#ifndef LOCAL
-uniform mat4 emitterWM;
-#endif
-uniform vec2 lifeTime;
-uniform vec2 emitPower;
-uniform vec2 sizeRange;
-uniform vec4 scaleRange;
-#ifndef COLORGRADIENTS
-uniform vec4 color1;
-uniform vec4 color2;
-#endif
-uniform vec3 gravity;
-uniform sampler2D randomSampler;
-uniform sampler2D randomSampler2;
-uniform vec4 angleRange;
-#ifdef BOXEMITTER
-uniform vec3 direction1;
-uniform vec3 direction2;
-uniform vec3 minEmitBox;
-uniform vec3 maxEmitBox;
-#endif
-#ifdef POINTEMITTER
-uniform vec3 direction1;
-uniform vec3 direction2;
-#endif
-#ifdef HEMISPHERICEMITTER
-uniform float radius;
-uniform float radiusRange;
-uniform float directionRandomizer;
-#endif
-#ifdef SPHEREEMITTER
-uniform float radius;
-uniform float radiusRange;
-#ifdef DIRECTEDSPHEREEMITTER
-uniform vec3 direction1;
-uniform vec3 direction2;
-#else
-uniform float directionRandomizer;
-#endif
-#endif
-#ifdef CYLINDEREMITTER
-uniform float radius;
-uniform float height;
-uniform float radiusRange;
-#ifdef DIRECTEDCYLINDEREMITTER
-uniform vec3 direction1;
-uniform vec3 direction2;
-#else
-uniform float directionRandomizer;
-#endif
-#endif
-#ifdef CONEEMITTER
-uniform vec2 radius;
-uniform float coneAngle;
-uniform vec2 height;
-uniform float directionRandomizer;
-#endif
-
-in vec3 position;
-#ifdef CUSTOMEMITTER
-in vec3 initialPosition;
-#endif
-in float age;
-in float life;
-in vec4 seed;
-in vec3 size;
-#ifndef COLORGRADIENTS
-in vec4 color;
-#endif
-in vec3 direction;
-#ifndef BILLBOARD
-in vec3 initialDirection;
-#endif
-#ifdef ANGULARSPEEDGRADIENTS
-in float angle;
-#else
-in vec2 angle;
-#endif
-#ifdef ANIMATESHEET
-in float cellIndex;
-#ifdef ANIMATESHEETRANDOMSTART
-in float cellStartOffset;
-#endif
-#endif
-#ifdef NOISE
-in vec3 noiseCoordinates1;
-in vec3 noiseCoordinates2;
-#endif
-
-out vec3 outPosition;
-#ifdef CUSTOMEMITTER
-out vec3 outInitialPosition;
-#endif
-out float outAge;
-out float outLife;
-out vec4 outSeed;
-out vec3 outSize;
-#ifndef COLORGRADIENTS
-out vec4 outColor;
-#endif
-out vec3 outDirection;
-#ifndef BILLBOARD
-out vec3 outInitialDirection;
-#endif
-#ifdef ANGULARSPEEDGRADIENTS
-out float outAngle;
-#else
-out vec2 outAngle;
-#endif
-#ifdef ANIMATESHEET
-out float outCellIndex;
-#ifdef ANIMATESHEETRANDOMSTART
-out float outCellStartOffset;
-#endif
-#endif
-#ifdef NOISE
-out vec3 outNoiseCoordinates1;
-out vec3 outNoiseCoordinates2;
-#endif
-#ifdef SIZEGRADIENTS
-uniform sampler2D sizeGradientSampler;
-#endif
-#ifdef ANGULARSPEEDGRADIENTS
-uniform sampler2D angularSpeedGradientSampler;
-#endif
-#ifdef VELOCITYGRADIENTS
-uniform sampler2D velocityGradientSampler;
-#endif
-#ifdef LIMITVELOCITYGRADIENTS
-uniform sampler2D limitVelocityGradientSampler;
-uniform float limitVelocityDamping;
-#endif
-#ifdef DRAGGRADIENTS
-uniform sampler2D dragGradientSampler;
-#endif
-#ifdef NOISE
-uniform vec3 noiseStrength;
-uniform sampler2D noiseSampler;
-#endif
-#ifdef ANIMATESHEET
-uniform vec3 cellInfos;
-#endif
-vec3 getRandomVec3(float offset) {
-return texture(randomSampler2,vec2(float(gl_VertexID)*offset/currentCount,0)).rgb;
-}
-vec4 getRandomVec4(float offset) {
-return texture(randomSampler,vec2(float(gl_VertexID)*offset/currentCount,0));
-}
-void main() {
-float newAge=age+timeDelta;
-
-if (newAge>=life && stopFactor != 0.) {
-vec3 newPosition;
-vec3 newDirection;
-
-vec4 randoms=getRandomVec4(seed.x);
-
-outLife=lifeTime.x+(lifeTime.y-lifeTime.x)*randoms.r;
-outAge=newAge-life;
-
-outSeed=seed;
-
-#ifdef SIZEGRADIENTS
-outSize.x=texture(sizeGradientSampler,vec2(0,0)).r;
-#else
-outSize.x=sizeRange.x+(sizeRange.y-sizeRange.x)*randoms.g;
-#endif
-outSize.y=scaleRange.x+(scaleRange.y-scaleRange.x)*randoms.b;
-outSize.z=scaleRange.z+(scaleRange.w-scaleRange.z)*randoms.a;
-#ifndef COLORGRADIENTS
-
-outColor=color1+(color2-color1)*randoms.b;
-#endif
-
-#ifndef ANGULARSPEEDGRADIENTS
-outAngle.y=angleRange.x+(angleRange.y-angleRange.x)*randoms.a;
-outAngle.x=angleRange.z+(angleRange.w-angleRange.z)*randoms.r;
-#else
-outAngle=angleRange.z+(angleRange.w-angleRange.z)*randoms.r;
-#endif
-
-#ifdef POINTEMITTER
-vec3 randoms2=getRandomVec3(seed.y);
-vec3 randoms3=getRandomVec3(seed.z);
-newPosition=vec3(0,0,0);
-newDirection=direction1+(direction2-direction1)*randoms3;
-#elif defined(BOXEMITTER)
-vec3 randoms2=getRandomVec3(seed.y);
-vec3 randoms3=getRandomVec3(seed.z);
-newPosition=minEmitBox+(maxEmitBox-minEmitBox)*randoms2;
-newDirection=direction1+(direction2-direction1)*randoms3;
-#elif defined(HEMISPHERICEMITTER)
-vec3 randoms2=getRandomVec3(seed.y);
-vec3 randoms3=getRandomVec3(seed.z);
-
-float phi=2.0*PI*randoms2.x;
-float theta=acos(2.0*randoms2.y-1.0);
-float randX=cos(phi)*sin(theta);
-float randY=cos(theta);
-float randZ=sin(phi)*sin(theta);
-newPosition=(radius-(radius*radiusRange*randoms2.z))*vec3(randX,abs(randY),randZ);
-newDirection=newPosition+directionRandomizer*randoms3;
-#elif defined(SPHEREEMITTER)
-vec3 randoms2=getRandomVec3(seed.y);
-vec3 randoms3=getRandomVec3(seed.z);
-
-float phi=2.0*PI*randoms2.x;
-float theta=acos(2.0*randoms2.y-1.0);
-float randX=cos(phi)*sin(theta);
-float randY=cos(theta);
-float randZ=sin(phi)*sin(theta);
-newPosition=(radius-(radius*radiusRange*randoms2.z))*vec3(randX,randY,randZ);
-#ifdef DIRECTEDSPHEREEMITTER
-newDirection=direction1+(direction2-direction1)*randoms3;
-#else
-
-newDirection=newPosition+directionRandomizer*randoms3;
-#endif
-#elif defined(CYLINDEREMITTER)
-vec3 randoms2=getRandomVec3(seed.y);
-vec3 randoms3=getRandomVec3(seed.z);
-
-float yPos=(randoms2.x-0.5)*height;
-float angle=randoms2.y*PI*2.;
-float inverseRadiusRangeSquared=((1.-radiusRange)*(1.-radiusRange));
-float positionRadius=radius*sqrt(inverseRadiusRangeSquared+(randoms2.z*(1.-inverseRadiusRangeSquared)));
-float xPos=positionRadius*cos(angle);
-float zPos=positionRadius*sin(angle);
-newPosition=vec3(xPos,yPos,zPos);
-#ifdef DIRECTEDCYLINDEREMITTER
-newDirection=direction1+(direction2-direction1)*randoms3;
-#else
-
-angle=angle+((randoms3.x-0.5)*PI);
-newDirection=vec3(cos(angle),randoms3.y-0.5,sin(angle));
-newDirection=normalize(newDirection);
-#endif
-#elif defined(CONEEMITTER)
-vec3 randoms2=getRandomVec3(seed.y);
-float s=2.0*PI*randoms2.x;
-#ifdef CONEEMITTERSPAWNPOINT
-float h=0.0001;
-#else
-float h=randoms2.y*height.y;
-
-h=1.-h*h;
-#endif
-float lRadius=radius.x-radius.x*randoms2.z*radius.y;
-lRadius=lRadius*h;
-float randX=lRadius*sin(s);
-float randZ=lRadius*cos(s);
-float randY=h*height.x;
-newPosition=vec3(randX,randY,randZ);
-
-if (abs(cos(coneAngle)) == 1.0) {
-newDirection=vec3(0.,1.0,0.);
-} else {
-vec3 randoms3=getRandomVec3(seed.z);
-newDirection=normalize(newPosition+directionRandomizer*randoms3);
-}
-#elif defined(CUSTOMEMITTER)
-newPosition=initialPosition;
-outInitialPosition=initialPosition;
-#else
-
-newPosition=vec3(0.,0.,0.);
-
-newDirection=2.0*(getRandomVec3(seed.w)-vec3(0.5,0.5,0.5));
-#endif
-float power=emitPower.x+(emitPower.y-emitPower.x)*randoms.a;
-#ifdef LOCAL
-outPosition=newPosition;
-#else
-outPosition=(emitterWM*vec4(newPosition,1.)).xyz;
-#endif
-#ifdef CUSTOMEMITTER
-outDirection=direction;
-#ifndef BILLBOARD
-outInitialDirection=direction;
-#endif
-#else
-#ifdef LOCAL
-vec3 initial=newDirection;
-#else
-vec3 initial=(emitterWM*vec4(newDirection,0.)).xyz;
-#endif
-outDirection=initial*power;
-#ifndef BILLBOARD
-outInitialDirection=initial;
-#endif
-#endif
-#ifdef ANIMATESHEET
-outCellIndex=cellInfos.x;
-#ifdef ANIMATESHEETRANDOMSTART
-outCellStartOffset=randoms.a*outLife;
-#endif
-#endif
-#ifdef NOISE
-outNoiseCoordinates1=noiseCoordinates1;
-outNoiseCoordinates2=noiseCoordinates2;
-#endif
-} else {
-float directionScale=timeDelta;
-outAge=newAge;
-float ageGradient=newAge/life;
-#ifdef VELOCITYGRADIENTS
-directionScale*=texture(velocityGradientSampler,vec2(ageGradient,0)).r;
-#endif
-#ifdef DRAGGRADIENTS
-directionScale*=1.0-texture(dragGradientSampler,vec2(ageGradient,0)).r;
-#endif
-#if defined(CUSTOMEMITTER)
-outPosition=position+(direction-position)*ageGradient;
-outInitialPosition=initialPosition;
-#else
-outPosition=position+direction*directionScale;
-#endif
-outLife=life;
-outSeed=seed;
-#ifndef COLORGRADIENTS
-outColor=color;
-#endif
-#ifdef SIZEGRADIENTS
-outSize.x=texture(sizeGradientSampler,vec2(ageGradient,0)).r;
-outSize.yz=size.yz;
-#else
-outSize=size;
-#endif
-#ifndef BILLBOARD
-outInitialDirection=initialDirection;
-#endif
-#ifdef CUSTOMEMITTER
-outDirection=direction;
-#else
-vec3 updatedDirection=direction+gravity*timeDelta;
-#ifdef LIMITVELOCITYGRADIENTS
-float limitVelocity=texture(limitVelocityGradientSampler,vec2(ageGradient,0)).r;
-float currentVelocity=length(updatedDirection);
-if (currentVelocity>limitVelocity) {
-updatedDirection=updatedDirection*limitVelocityDamping;
-}
-#endif
-outDirection=updatedDirection;
-#ifdef NOISE
-float fetchedR=texture(noiseSampler,vec2(noiseCoordinates1.x,noiseCoordinates1.y)*vec2(0.5)+vec2(0.5)).r;
-float fetchedG=texture(noiseSampler,vec2(noiseCoordinates1.z,noiseCoordinates2.x)*vec2(0.5)+vec2(0.5)).r;
-float fetchedB=texture(noiseSampler,vec2(noiseCoordinates2.y,noiseCoordinates2.z)*vec2(0.5)+vec2(0.5)).r;
-vec3 force=vec3(2.*fetchedR-1.,2.*fetchedG-1.,2.*fetchedB-1.)*noiseStrength;
-outDirection=outDirection+force*timeDelta;
-outNoiseCoordinates1=noiseCoordinates1;
-outNoiseCoordinates2=noiseCoordinates2;
-#endif
-#endif
-#ifdef ANGULARSPEEDGRADIENTS
-float angularSpeed=texture(angularSpeedGradientSampler,vec2(ageGradient,0)).r;
-outAngle=angle+angularSpeed*timeDelta;
-#else
-outAngle=vec2(angle.x+angle.y*timeDelta,angle.y);
-#endif
-#ifdef ANIMATESHEET
-float offsetAge=outAge;
-float dist=cellInfos.y-cellInfos.x;
-#ifdef ANIMATESHEETRANDOMSTART
-outCellStartOffset=cellStartOffset;
-offsetAge+=cellStartOffset;
-#else
-float cellStartOffset=0.;
-#endif
-float ratio=clamp(mod(cellStartOffset+cellInfos.z*offsetAge,life)/life,0.,1.0);
-outCellIndex=float(int(cellInfos.x+ratio*dist));
-#endif
-}
-}`;ze.a.ShadersStore.gpuUpdateParticlesVertexShader=wm;var Fm=`#ifdef CLIPPLANE
-in float fClipDistance;
-#endif
-#ifdef CLIPPLANE2
-in float fClipDistance2;
-#endif
-#ifdef CLIPPLANE3
-in float fClipDistance3;
-#endif
-#ifdef CLIPPLANE4
-in float fClipDistance4;
-#endif
-#ifdef CLIPPLANE5
-in float fClipDistance5;
-#endif
-#ifdef CLIPPLANE6
-in float fClipDistance6;
-#endif`;ze.a.IncludesShadersStore.clipPlaneFragmentDeclaration2=Fm;var Bm=`#version 300 es
-uniform sampler2D diffuseSampler;
-in vec2 vUV;
-in vec4 vColor;
-out vec4 outFragColor;
-#include<clipPlaneFragmentDeclaration2>
-#include<imageProcessingDeclaration>
-#include<helperFunctions>
-#include<imageProcessingFunctions>
-void main() {
-#include<clipPlaneFragment>
-vec4 textureColor=texture(diffuseSampler,vUV);
-outFragColor=textureColor*vColor;
-#ifdef BLENDMULTIPLYMODE
-float alpha=vColor.a*textureColor.a;
-outFragColor.rgb=outFragColor.rgb*alpha+vec3(1.0)*(1.0-alpha);
-#endif
-
-
-#ifdef IMAGEPROCESSINGPOSTPROCESS
-outFragColor.rgb=toLinearSpace(outFragColor.rgb);
-#else
-#ifdef IMAGEPROCESSING
-outFragColor.rgb=toLinearSpace(outFragColor.rgb);
-outFragColor=applyImageProcessing(outFragColor);
-#endif
-#endif
-}
-`;ze.a.ShadersStore.gpuRenderParticlesPixelShader=Bm;var Um=`#ifdef CLIPPLANE
-uniform vec4 vClipPlane;
-out float fClipDistance;
-#endif
-#ifdef CLIPPLANE2
-uniform vec4 vClipPlane2;
-out float fClipDistance2;
-#endif
-#ifdef CLIPPLANE3
-uniform vec4 vClipPlane3;
-out float fClipDistance3;
-#endif
-#ifdef CLIPPLANE4
-uniform vec4 vClipPlane4;
-out float fClipDistance4;
-#endif
-#ifdef CLIPPLANE5
-uniform vec4 vClipPlane5;
-out float fClipDistance5;
-#endif
-#ifdef CLIPPLANE6
-uniform vec4 vClipPlane6;
-out float fClipDistance6;
-#endif`;ze.a.IncludesShadersStore.clipPlaneVertexDeclaration2=Um;var Vm=`#version 300 es
-uniform mat4 view;
-uniform mat4 projection;
-uniform vec2 translationPivot;
-uniform vec3 worldOffset;
-#ifdef LOCAL
-uniform mat4 emitterWM;
-#endif
-
-in vec3 position;
-in float age;
-in float life;
-in vec3 size;
-#ifndef BILLBOARD
-in vec3 initialDirection;
-#endif
-#ifdef BILLBOARDSTRETCHED
-in vec3 direction;
-#endif
-in float angle;
-#ifdef ANIMATESHEET
-in float cellIndex;
-#endif
-in vec2 offset;
-in vec2 uv;
-out vec2 vUV;
-out vec4 vColor;
-out vec3 vPositionW;
-#if defined(BILLBOARD) && !defined(BILLBOARDY) && !defined(BILLBOARDSTRETCHED)
-uniform mat4 invView;
-#endif
-#include<clipPlaneVertexDeclaration2>
-#ifdef COLORGRADIENTS
-uniform sampler2D colorGradientSampler;
-#else
-uniform vec4 colorDead;
-in vec4 color;
-#endif
-#ifdef ANIMATESHEET
-uniform vec3 sheetInfos;
-#endif
-#ifdef BILLBOARD
-uniform vec3 eyePosition;
-#endif
-vec3 rotate(vec3 yaxis,vec3 rotatedCorner) {
-vec3 xaxis=normalize(cross(vec3(0.,1.0,0.),yaxis));
-vec3 zaxis=normalize(cross(yaxis,xaxis));
-vec3 row0=vec3(xaxis.x,xaxis.y,xaxis.z);
-vec3 row1=vec3(yaxis.x,yaxis.y,yaxis.z);
-vec3 row2=vec3(zaxis.x,zaxis.y,zaxis.z);
-mat3 rotMatrix=mat3(row0,row1,row2);
-vec3 alignedCorner=rotMatrix*rotatedCorner;
-#ifdef LOCAL
-return ((emitterWM*vec4(position,1.0)).xyz+worldOffset)+alignedCorner;
-#else
-return (position+worldOffset)+alignedCorner;
-#endif
-}
-#ifdef BILLBOARDSTRETCHED
-vec3 rotateAlign(vec3 toCamera,vec3 rotatedCorner) {
-vec3 normalizedToCamera=normalize(toCamera);
-vec3 normalizedCrossDirToCamera=normalize(cross(normalize(direction),normalizedToCamera));
-vec3 crossProduct=normalize(cross(normalizedToCamera,normalizedCrossDirToCamera));
-vec3 row0=vec3(normalizedCrossDirToCamera.x,normalizedCrossDirToCamera.y,normalizedCrossDirToCamera.z);
-vec3 row1=vec3(crossProduct.x,crossProduct.y,crossProduct.z);
-vec3 row2=vec3(normalizedToCamera.x,normalizedToCamera.y,normalizedToCamera.z);
-mat3 rotMatrix=mat3(row0,row1,row2);
-vec3 alignedCorner=rotMatrix*rotatedCorner;
-#ifdef LOCAL
-return ((emitterWM*vec4(position,1.0)).xyz+worldOffset)+alignedCorner;
-#else
-return (position+worldOffset)+alignedCorner;
-#endif
-}
-#endif
-void main() {
-#ifdef ANIMATESHEET
-float rowOffset=floor(cellIndex/sheetInfos.z);
-float columnOffset=cellIndex-rowOffset*sheetInfos.z;
-vec2 uvScale=sheetInfos.xy;
-vec2 uvOffset=vec2(uv.x ,1.0-uv.y);
-vUV=(uvOffset+vec2(columnOffset,rowOffset))*uvScale;
-#else
-vUV=uv;
-#endif
-float ratio=age/life;
-#ifdef COLORGRADIENTS
-vColor=texture(colorGradientSampler,vec2(ratio,0));
-#else
-vColor=color*vec4(1.0-ratio)+colorDead*vec4(ratio);
-#endif
-vec2 cornerPos=(offset-translationPivot)*size.yz*size.x+translationPivot;
-#ifdef BILLBOARD
-vec4 rotatedCorner;
-rotatedCorner.w=0.;
-#ifdef BILLBOARDY
-rotatedCorner.x=cornerPos.x*cos(angle)-cornerPos.y*sin(angle);
-rotatedCorner.z=cornerPos.x*sin(angle)+cornerPos.y*cos(angle);
-rotatedCorner.y=0.;
-vec3 yaxis=(position+worldOffset)-eyePosition;
-yaxis.y=0.;
-vPositionW=rotate(normalize(yaxis),rotatedCorner.xyz);
-vec4 viewPosition=(view*vec4(vPositionW,1.0));
-#elif defined(BILLBOARDSTRETCHED)
-rotatedCorner.x=cornerPos.x*cos(angle)-cornerPos.y*sin(angle);
-rotatedCorner.y=cornerPos.x*sin(angle)+cornerPos.y*cos(angle);
-rotatedCorner.z=0.;
-vec3 toCamera=(position+worldOffset)-eyePosition;
-vPositionW=rotateAlign(toCamera,rotatedCorner.xyz);
-vec4 viewPosition=(view*vec4(vPositionW,1.0));
-#else
-
-rotatedCorner.x=cornerPos.x*cos(angle)-cornerPos.y*sin(angle);
-rotatedCorner.y=cornerPos.x*sin(angle)+cornerPos.y*cos(angle);
-rotatedCorner.z=0.;
-
-#ifdef LOCAL
-vec4 viewPosition=view*vec4(((emitterWM*vec4(position,1.0)).xyz+worldOffset),1.0)+rotatedCorner;
-#else
-vec4 viewPosition=view*vec4((position+worldOffset),1.0)+rotatedCorner;
-#endif
-vPositionW=(invView*viewPosition).xyz;
-#endif
-#else
-
-vec3 rotatedCorner;
-rotatedCorner.x=cornerPos.x*cos(angle)-cornerPos.y*sin(angle);
-rotatedCorner.y=0.;
-rotatedCorner.z=cornerPos.x*sin(angle)+cornerPos.y*cos(angle);
-vec3 yaxis=normalize(initialDirection);
-vPositionW=rotate(yaxis,rotatedCorner);
-
-vec4 viewPosition=view*vec4(vPositionW,1.0);
-#endif
-gl_Position=projection*viewPosition;
-
-#if defined(CLIPPLANE) || defined(CLIPPLANE2) || defined(CLIPPLANE3) || defined(CLIPPLANE4) || defined(CLIPPLANE5) || defined(CLIPPLANE6)
-vec4 worldPos=vec4(vPositionW,1.0);
-#endif
-#include<clipPlaneVertex>
-}`;ze.a.ShadersStore.gpuRenderParticlesVertexShader=Vm;var ar=function(r){function t(e,n,i,o,a){o===void 0&&(o=!1),a===void 0&&(a=null);var s=r.call(this,e)||this;s.layerMask=268435455,s._accumulatedCount=0,s._targetIndex=0,s._currentRenderId=-1,s._started=!1,s._stopped=!1,s._timeDelta=0,s._actualFrame=0,s._rawTextureWidth=256,s.onDisposeObservable=new x.c,s.onStoppedObservable=new x.c,s.forceDepthWrite=!1,s._preWarmDone=!1,s.isLocal=!1,s._onBeforeDrawParticlesObservable=null,i&&i.getClassName()!=="Scene"?(s._engine=i,s.defaultProjectionMatrix=u.a.PerspectiveFovLH(.8,1,.1,100)):(s._scene=i||te.a.LastCreatedScene,s._engine=s._scene.getEngine(),s.uniqueId=s._scene.getUniqueId(),s._scene.particleSystems.push(s)),s._customEffect={0:a},s._attachImageProcessingConfiguration(null),n.randomTextureSize||delete n.randomTextureSize;var d=Object(c.a)({capacity:5e4,randomTextureSize:s._engine.getCaps().maxTextureSize},n),p=n;isFinite(p)&&(d.capacity=p),s._capacity=d.capacity,s._activeCount=d.capacity,s._currentActiveCount=0,s._isAnimationSheetEnabled=o,s._updateEffectOptions={attributes:["position","initialPosition","age","life","seed","size","color","direction","initialDirection","angle","cellIndex","cellStartOffset","noiseCoordinates1","noiseCoordinates2"],uniformsNames:["currentCount","timeDelta","emitterWM","lifeTime","color1","color2","sizeRange","scaleRange","gravity","emitPower","direction1","direction2","minEmitBox","maxEmitBox","radius","directionRandomizer","height","coneAngle","stopFactor","angleRange","radiusRange","cellInfos","noiseStrength","limitVelocityDamping"],uniformBuffersNames:[],samplers:["randomSampler","randomSampler2","sizeGradientSampler","angularSpeedGradientSampler","velocityGradientSampler","limitVelocityGradientSampler","noiseSampler","dragGradientSampler"],defines:"",fallbacks:null,onCompiled:null,onError:null,indexParameters:null,maxSimultaneousLights:0,transformFeedbackVaryings:[]},s.particleEmitterType=new Nr;for(var b=Math.min(s._engine.getCaps().maxTextureSize,d.randomTextureSize),P=[],O=0;O<b;++O)P.push(Math.random()),P.push(Math.random()),P.push(Math.random()),P.push(Math.random());for(s._randomTexture=new ii(new Float32Array(P),b,1,h.a.TEXTUREFORMAT_RGBA,i,!1,!1,h.a.TEXTURE_NEAREST_SAMPLINGMODE,h.a.TEXTURETYPE_FLOAT),s._randomTexture.wrapU=h.a.TEXTURE_WRAP_ADDRESSMODE,s._randomTexture.wrapV=h.a.TEXTURE_WRAP_ADDRESSMODE,P=[],O=0;O<b;++O)P.push(Math.random()),P.push(Math.random()),P.push(Math.random()),P.push(Math.random());return s._randomTexture2=new ii(new Float32Array(P),b,1,h.a.TEXTUREFORMAT_RGBA,i,!1,!1,h.a.TEXTURE_NEAREST_SAMPLINGMODE,h.a.TEXTURETYPE_FLOAT),s._randomTexture2.wrapU=h.a.TEXTURE_WRAP_ADDRESSMODE,s._randomTexture2.wrapV=h.a.TEXTURE_WRAP_ADDRESSMODE,s._randomTextureSize=b,s}return Object(c.d)(t,r),Object.defineProperty(t,"IsSupported",{get:function(){return!!te.a.LastCreatedEngine&&te.a.LastCreatedEngine.webGLVersion>1},enumerable:!1,configurable:!0}),t.prototype.getCapacity=function(){return this._capacity},Object.defineProperty(t.prototype,"activeParticleCount",{get:function(){return this._activeCount},set:function(e){this._activeCount=Math.min(e,this._capacity)},enumerable:!1,configurable:!0}),t.prototype.isReady=function(){return this._updateEffect?!!(this.emitter&&this._updateEffect.isReady()&&(!this._imageProcessingConfiguration||this._imageProcessingConfiguration.isReady())&&this._getEffect().isReady()&&this.particleTexture&&this.particleTexture.isReady()):(this._recreateUpdateEffect(),this._recreateRenderEffect(),!1)},t.prototype.isStarted=function(){return this._started},t.prototype.isStopped=function(){return this._stopped},t.prototype.isStopping=function(){return!1},t.prototype.getActiveCount=function(){return this._currentActiveCount},t.prototype.start=function(e){var n=this;if(e===void 0&&(e=this.startDelay),!this.targetStopDuration&&this._hasTargetStopDurationDependantGradient())throw"Particle system started with a targetStopDuration dependant gradient (eg. startSizeGradients) but no targetStopDuration set";e?setTimeout(function(){n.start(0)},e):(this._started=!0,this._stopped=!1,this._preWarmDone=!1,this.beginAnimationOnStart&&this.animations&&this.animations.length>0&&this._scene&&this._scene.beginAnimation(this,this.beginAnimationFrom,this.beginAnimationTo,this.beginAnimationLoop))},t.prototype.stop=function(){this._stopped||(this._stopped=!0)},t.prototype.reset=function(){this._releaseBuffers(),this._releaseVAOs(),this._currentActiveCount=0,this._targetIndex=0},t.prototype.getClassName=function(){return"GPUParticleSystem"},t.prototype.getCustomEffect=function(e){var n;return e===void 0&&(e=0),(n=this._customEffect[e])!==null&&n!==void 0?n:this._customEffect[0]},t.prototype.setCustomEffect=function(e,n){n===void 0&&(n=0),this._customEffect[n]=e},Object.defineProperty(t.prototype,"onBeforeDrawParticlesObservable",{get:function(){return this._onBeforeDrawParticlesObservable||(this._onBeforeDrawParticlesObservable=new x.c),this._onBeforeDrawParticlesObservable},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vertexShaderName",{get:function(){return"gpuRenderParticles"},enumerable:!1,configurable:!0}),t.prototype._removeGradientAndTexture=function(e,n,i){return r.prototype._removeGradientAndTexture.call(this,e,n,i),this._releaseBuffers(),this},t.prototype.addColorGradient=function(e,n,i){this._colorGradients||(this._colorGradients=[]);var o=new Rc(e,n);return this._colorGradients.push(o),this._refreshColorGradient(!0),this._releaseBuffers(),this},t.prototype._refreshColorGradient=function(e){e===void 0&&(e=!1),this._colorGradients&&(e&&this._colorGradients.sort(function(n,i){return n.gradient<i.gradient?-1:n.gradient>i.gradient?1:0}),this._colorGradientsTexture&&(this._colorGradientsTexture.dispose(),this._colorGradientsTexture=null))},t.prototype.forceRefreshGradients=function(){this._refreshColorGradient(),this._refreshFactorGradient(this._sizeGradients,"_sizeGradientsTexture"),this._refreshFactorGradient(this._angularSpeedGradients,"_angularSpeedGradientsTexture"),this._refreshFactorGradient(this._velocityGradients,"_velocityGradientsTexture"),this._refreshFactorGradient(this._limitVelocityGradients,"_limitVelocityGradientsTexture"),this._refreshFactorGradient(this._dragGradients,"_dragGradientsTexture"),this.reset()},t.prototype.removeColorGradient=function(e){return this._removeGradientAndTexture(e,this._colorGradients,this._colorGradientsTexture),this._colorGradientsTexture=null,this},t.prototype._addFactorGradient=function(e,n,i){var o=new Oc(n,i);e.push(o),this._releaseBuffers()},t.prototype.addSizeGradient=function(e,n){return this._sizeGradients||(this._sizeGradients=[]),this._addFactorGradient(this._sizeGradients,e,n),this._refreshFactorGradient(this._sizeGradients,"_sizeGradientsTexture",!0),this._releaseBuffers(),this},t.prototype.removeSizeGradient=function(e){return this._removeGradientAndTexture(e,this._sizeGradients,this._sizeGradientsTexture),this._sizeGradientsTexture=null,this},t.prototype._refreshFactorGradient=function(e,n,i){i===void 0&&(i=!1),e&&(i&&e.sort(function(o,a){return o.gradient<a.gradient?-1:o.gradient>a.gradient?1:0}),this[n]&&(this[n].dispose(),this[n]=null))},t.prototype.addAngularSpeedGradient=function(e,n){return this._angularSpeedGradients||(this._angularSpeedGradients=[]),this._addFactorGradient(this._angularSpeedGradients,e,n),this._refreshFactorGradient(this._angularSpeedGradients,"_angularSpeedGradientsTexture",!0),this._releaseBuffers(),this},t.prototype.removeAngularSpeedGradient=function(e){return this._removeGradientAndTexture(e,this._angularSpeedGradients,this._angularSpeedGradientsTexture),this._angularSpeedGradientsTexture=null,this},t.prototype.addVelocityGradient=function(e,n){return this._velocityGradients||(this._velocityGradients=[]),this._addFactorGradient(this._velocityGradients,e,n),this._refreshFactorGradient(this._velocityGradients,"_velocityGradientsTexture",!0),this._releaseBuffers(),this},t.prototype.removeVelocityGradient=function(e){return this._removeGradientAndTexture(e,this._velocityGradients,this._velocityGradientsTexture),this._velocityGradientsTexture=null,this},t.prototype.addLimitVelocityGradient=function(e,n){return this._limitVelocityGradients||(this._limitVelocityGradients=[]),this._addFactorGradient(this._limitVelocityGradients,e,n),this._refreshFactorGradient(this._limitVelocityGradients,"_limitVelocityGradientsTexture",!0),this._releaseBuffers(),this},t.prototype.removeLimitVelocityGradient=function(e){return this._removeGradientAndTexture(e,this._limitVelocityGradients,this._limitVelocityGradientsTexture),this._limitVelocityGradientsTexture=null,this},t.prototype.addDragGradient=function(e,n){return this._dragGradients||(this._dragGradients=[]),this._addFactorGradient(this._dragGradients,e,n),this._refreshFactorGradient(this._dragGradients,"_dragGradientsTexture",!0),this._releaseBuffers(),this},t.prototype.removeDragGradient=function(e){return this._removeGradientAndTexture(e,this._dragGradients,this._dragGradientsTexture),this._dragGradientsTexture=null,this},t.prototype.addEmitRateGradient=function(e,n,i){return this},t.prototype.removeEmitRateGradient=function(e){return this},t.prototype.addStartSizeGradient=function(e,n,i){return this},t.prototype.removeStartSizeGradient=function(e){return this},t.prototype.addColorRemapGradient=function(e,n,i){return this},t.prototype.removeColorRemapGradient=function(){return this},t.prototype.addAlphaRemapGradient=function(e,n,i){return this},t.prototype.removeAlphaRemapGradient=function(){return this},t.prototype.addRampGradient=function(e,n){return this},t.prototype.removeRampGradient=function(){return this},t.prototype.getRampGradients=function(){return null},Object.defineProperty(t.prototype,"useRampGradients",{get:function(){return!1},set:function(e){},enumerable:!1,configurable:!0}),t.prototype.addLifeTimeGradient=function(e,n,i){return this},t.prototype.removeLifeTimeGradient=function(e){return this},t.prototype._reset=function(){this._releaseBuffers()},t.prototype._createUpdateVAO=function(e){var n={};n.position=e.createVertexBuffer("position",0,3);var i=3;this.particleEmitterType instanceof wr&&(n.initialPosition=e.createVertexBuffer("initialPosition",i,3),i+=3),n.age=e.createVertexBuffer("age",i,1),i+=1,n.life=e.createVertexBuffer("life",i,1),i+=1,n.seed=e.createVertexBuffer("seed",i,4),i+=4,n.size=e.createVertexBuffer("size",i,3),i+=3,this._colorGradientsTexture||(n.color=e.createVertexBuffer("color",i,4),i+=4),n.direction=e.createVertexBuffer("direction",i,3),i+=3,this._isBillboardBased||(n.initialDirection=e.createVertexBuffer("initialDirection",i,3),i+=3),this._angularSpeedGradientsTexture?(n.angle=e.createVertexBuffer("angle",i,1),i+=1):(n.angle=e.createVertexBuffer("angle",i,2),i+=2),this._isAnimationSheetEnabled&&(n.cellIndex=e.createVertexBuffer("cellIndex",i,1),i+=1,this.spriteRandomStartCell&&(n.cellStartOffset=e.createVertexBuffer("cellStartOffset",i,1),i+=1)),this.noiseTexture&&(n.noiseCoordinates1=e.createVertexBuffer("noiseCoordinates1",i,3),i+=3,n.noiseCoordinates2=e.createVertexBuffer("noiseCoordinates2",i,3),i+=3);var o=this._engine.recordVertexArrayObject(n,null,this._updateEffect);return this._engine.bindArrayBuffer(null),o},t.prototype._createRenderVAO=function(e,n){var i={};i.position=e.createVertexBuffer("position",0,3,this._attributesStrideSize,!0);var o=3;this.particleEmitterType instanceof wr&&(o+=3),i.age=e.createVertexBuffer("age",o,1,this._attributesStrideSize,!0),o+=1,i.life=e.createVertexBuffer("life",o,1,this._attributesStrideSize,!0),o+=5,i.size=e.createVertexBuffer("size",o,3,this._attributesStrideSize,!0),o+=3,this._colorGradientsTexture||(i.color=e.createVertexBuffer("color",o,4,this._attributesStrideSize,!0),o+=4),this.billboardMode===ln.BILLBOARDMODE_STRETCHED&&(i.direction=e.createVertexBuffer("direction",o,3,this._attributesStrideSize,!0)),o+=3,this._isBillboardBased||(i.initialDirection=e.createVertexBuffer("initialDirection",o,3,this._attributesStrideSize,!0),o+=3),i.angle=e.createVertexBuffer("angle",o,1,this._attributesStrideSize,!0),this._angularSpeedGradientsTexture?o++:o+=2,this._isAnimationSheetEnabled&&(i.cellIndex=e.createVertexBuffer("cellIndex",o,1,this._attributesStrideSize,!0),o+=1,this.spriteRandomStartCell&&(i.cellStartOffset=e.createVertexBuffer("cellStartOffset",o,1,this._attributesStrideSize,!0),o+=1)),this.noiseTexture&&(i.noiseCoordinates1=e.createVertexBuffer("noiseCoordinates1",o,3,this._attributesStrideSize,!0),o+=3,i.noiseCoordinates2=e.createVertexBuffer("noiseCoordinates2",o,3,this._attributesStrideSize,!0),o+=3),i.offset=n.createVertexBuffer("offset",0,2),i.uv=n.createVertexBuffer("uv",2,2);var a=this._engine.recordVertexArrayObject(i,null,this._getEffect());return this._engine.bindArrayBuffer(null),a},t.prototype._initialize=function(e){if(e===void 0&&(e=!1),!this._buffer0||e){var n=this._engine,i=new Array;this._attributesStrideSize=21,this._targetIndex=0,this.particleEmitterType instanceof wr&&(this._attributesStrideSize+=3),this.isBillboardBased||(this._attributesStrideSize+=3),this._colorGradientsTexture&&(this._attributesStrideSize-=4),this._angularSpeedGradientsTexture&&(this._attributesStrideSize-=1),this._isAnimationSheetEnabled&&(this._attributesStrideSize+=1,this.spriteRandomStartCell&&(this._attributesStrideSize+=1)),this.noiseTexture&&(this._attributesStrideSize+=6);for(var o=this.particleEmitterType instanceof wr,a=u.c.Vector3[0],s=0;s<this._capacity;s++)i.push(0),i.push(0),i.push(0),o&&(this.particleEmitterType.particlePositionGenerator(s,null,a),i.push(a.x),i.push(a.y),i.push(a.z)),i.push(0),i.push(0),i.push(Math.random()),i.push(Math.random()),i.push(Math.random()),i.push(Math.random()),i.push(0),i.push(0),i.push(0),this._colorGradientsTexture||(i.push(0),i.push(0),i.push(0),i.push(0)),o?(this.particleEmitterType.particleDestinationGenerator(s,null,a),i.push(a.x),i.push(a.y),i.push(a.z)):(i.push(0),i.push(0),i.push(0)),this.isBillboardBased||(i.push(0),i.push(0),i.push(0)),i.push(0),this._angularSpeedGradientsTexture||i.push(0),this._isAnimationSheetEnabled&&(i.push(0),this.spriteRandomStartCell&&i.push(0)),this.noiseTexture&&(i.push(Math.random()),i.push(Math.random()),i.push(Math.random()),i.push(Math.random()),i.push(Math.random()),i.push(Math.random()));var d=new Float32Array([.5,.5,1,1,-.5,.5,0,1,-.5,-.5,0,0,.5,-.5,1,0]);this._buffer0=new Oe.a(n,i,!1,this._attributesStrideSize),this._buffer1=new Oe.a(n,i,!1,this._attributesStrideSize),this._spriteBuffer=new Oe.a(n,d,!1,4),this._updateVAO=[],this._updateVAO.push(this._createUpdateVAO(this._buffer0)),this._updateVAO.push(this._createUpdateVAO(this._buffer1)),this._renderVAO=[],this._renderVAO.push(this._createRenderVAO(this._buffer1,this._spriteBuffer)),this._renderVAO.push(this._createRenderVAO(this._buffer0,this._spriteBuffer)),this._sourceBuffer=this._buffer0,this._targetBuffer=this._buffer1}},t.prototype._recreateUpdateEffect=function(){var e=this.particleEmitterType?this.particleEmitterType.getEffectDefines():"";this._isBillboardBased&&(e+=`
-#define BILLBOARD`),this._colorGradientsTexture&&(e+=`
-#define COLORGRADIENTS`),this._sizeGradientsTexture&&(e+=`
-#define SIZEGRADIENTS`),this._angularSpeedGradientsTexture&&(e+=`
-#define ANGULARSPEEDGRADIENTS`),this._velocityGradientsTexture&&(e+=`
-#define VELOCITYGRADIENTS`),this._limitVelocityGradientsTexture&&(e+=`
-#define LIMITVELOCITYGRADIENTS`),this._dragGradientsTexture&&(e+=`
-#define DRAGGRADIENTS`),this.isAnimationSheetEnabled&&(e+=`
-#define ANIMATESHEET`,this.spriteRandomStartCell&&(e+=`
-#define ANIMATESHEETRANDOMSTART`)),this.noiseTexture&&(e+=`
-#define NOISE`),this.isLocal&&(e+=`
-#define LOCAL`),this._updateEffect&&this._updateEffectOptions.defines===e||(this._updateEffectOptions.transformFeedbackVaryings=["outPosition"],this.particleEmitterType instanceof wr&&this._updateEffectOptions.transformFeedbackVaryings.push("outInitialPosition"),this._updateEffectOptions.transformFeedbackVaryings.push("outAge"),this._updateEffectOptions.transformFeedbackVaryings.push("outLife"),this._updateEffectOptions.transformFeedbackVaryings.push("outSeed"),this._updateEffectOptions.transformFeedbackVaryings.push("outSize"),this._colorGradientsTexture||this._updateEffectOptions.transformFeedbackVaryings.push("outColor"),this._updateEffectOptions.transformFeedbackVaryings.push("outDirection"),this._isBillboardBased||this._updateEffectOptions.transformFeedbackVaryings.push("outInitialDirection"),this._updateEffectOptions.transformFeedbackVaryings.push("outAngle"),this.isAnimationSheetEnabled&&(this._updateEffectOptions.transformFeedbackVaryings.push("outCellIndex"),this.spriteRandomStartCell&&this._updateEffectOptions.transformFeedbackVaryings.push("outCellStartOffset")),this.noiseTexture&&(this._updateEffectOptions.transformFeedbackVaryings.push("outNoiseCoordinates1"),this._updateEffectOptions.transformFeedbackVaryings.push("outNoiseCoordinates2")),this._updateEffectOptions.defines=e,this._updateEffect=new ze.a("gpuUpdateParticles",this._updateEffectOptions,this._engine))},t.prototype._getEffect=function(){var e;return(e=this.getCustomEffect())!==null&&e!==void 0?e:this._renderEffect},t.prototype.fillDefines=function(e,n){if(this._scene&&(this._scene.clipPlane&&e.push("#define CLIPPLANE"),this._scene.clipPlane2&&e.push("#define CLIPPLANE2"),this._scene.clipPlane3&&e.push("#define CLIPPLANE3"),this._scene.clipPlane4&&e.push("#define CLIPPLANE4"),this._scene.clipPlane5&&e.push("#define CLIPPLANE5"),this._scene.clipPlane6&&e.push("#define CLIPPLANE6")),this.blendMode===ln.BLENDMODE_MULTIPLY&&e.push("#define BLENDMULTIPLYMODE"),this.isLocal&&e.push("#define LOCAL"),this._isBillboardBased)switch(e.push("#define BILLBOARD"),this.billboardMode){case ln.BILLBOARDMODE_Y:e.push("#define BILLBOARDY");break;case ln.BILLBOARDMODE_STRETCHED:e.push("#define BILLBOARDSTRETCHED");break;case ln.BILLBOARDMODE_ALL:e.push("#define BILLBOARDMODE_ALL")}this._colorGradientsTexture&&e.push("#define COLORGRADIENTS"),this.isAnimationSheetEnabled&&e.push("#define ANIMATESHEET"),this._imageProcessingConfiguration&&(this._imageProcessingConfiguration.prepareDefines(this._imageProcessingConfigurationDefines),e.push(""+this._imageProcessingConfigurationDefines.toString()))},t.prototype.fillUniformsAttributesAndSamplerNames=function(e,n,i){n.push("position","age","life","size","color","offset","uv","direction","initialDirection","angle","cellIndex"),e.push("emitterWM","worldOffset","view","projection","colorDead","invView","vClipPlane","vClipPlane2","vClipPlane3","vClipPlane4","vClipPlane5","vClipPlane6","sheetInfos","translationPivot","eyePosition"),i.push("diffuseSampler","colorGradientSampler"),this._imageProcessingConfiguration&&(yn.a.PrepareUniforms(e,this._imageProcessingConfigurationDefines),yn.a.PrepareSamplers(i,this._imageProcessingConfigurationDefines))},t.prototype._recreateRenderEffect=function(){var e=this.getCustomEffect();if(e)return e;var n=[];this.fillDefines(n);var i=n.join(`
-`);if(this._renderEffect&&this._renderEffect.defines===i)return this._renderEffect;var o=[],a=[],s=[];return this.fillUniformsAttributesAndSamplerNames(a,o,s),this._renderEffect=new ze.a("gpuRenderParticles",o,a,s,this._engine,i),this._renderEffect},t.prototype.animate=function(e){var n;e===void 0&&(e=!1),this._timeDelta=this.updateSpeed*(e?this.preWarmStepOffset:((n=this._scene)===null||n===void 0?void 0:n.getAnimationRatio())||1),this._actualFrame+=this._timeDelta,this._stopped||this.targetStopDuration&&this._actualFrame>=this.targetStopDuration&&this.stop()},t.prototype._createFactorGradientTexture=function(e,n){var i=this[n];if(e&&e.length&&!i){for(var o=new Float32Array(this._rawTextureWidth),a=0;a<this._rawTextureWidth;a++){var s=a/this._rawTextureWidth;In.GetCurrentGradient(s,e,function(d,p,b){o[a]=$.a.Lerp(d.factor1,p.factor1,b)})}this[n]=ii.CreateRTexture(o,this._rawTextureWidth,1,this._scene||this._engine,!1,!1,h.a.TEXTURE_NEAREST_SAMPLINGMODE)}},t.prototype._createSizeGradientTexture=function(){this._createFactorGradientTexture(this._sizeGradients,"_sizeGradientsTexture")},t.prototype._createAngularSpeedGradientTexture=function(){this._createFactorGradientTexture(this._angularSpeedGradients,"_angularSpeedGradientsTexture")},t.prototype._createVelocityGradientTexture=function(){this._createFactorGradientTexture(this._velocityGradients,"_velocityGradientsTexture")},t.prototype._createLimitVelocityGradientTexture=function(){this._createFactorGradientTexture(this._limitVelocityGradients,"_limitVelocityGradientsTexture")},t.prototype._createDragGradientTexture=function(){this._createFactorGradientTexture(this._dragGradients,"_dragGradientsTexture")},t.prototype._createColorGradientTexture=function(){if(this._colorGradients&&this._colorGradients.length&&!this._colorGradientsTexture){for(var e=new Uint8Array(4*this._rawTextureWidth),n=M.c.Color4[0],i=0;i<this._rawTextureWidth;i++){var o=i/this._rawTextureWidth;In.GetCurrentGradient(o,this._colorGradients,function(a,s,d){M.b.LerpToRef(a.color1,s.color1,d,n),e[4*i]=255*n.r,e[4*i+1]=255*n.g,e[4*i+2]=255*n.b,e[4*i+3]=255*n.a})}this._colorGradientsTexture=ii.CreateRGBATexture(e,this._rawTextureWidth,1,this._scene,!1,!1,h.a.TEXTURE_NEAREST_SAMPLINGMODE)}},t.prototype.render=function(e){var n,i;if(e===void 0&&(e=!1),!this._started||(this._createColorGradientTexture(),this._createSizeGradientTexture(),this._createAngularSpeedGradientTexture(),this._createVelocityGradientTexture(),this._createLimitVelocityGradientTexture(),this._createDragGradientTexture(),this._recreateUpdateEffect(),this._recreateRenderEffect(),!this.isReady()))return 0;if(!e&&this._scene){if(!this._preWarmDone&&this.preWarmCycles){for(var o=0;o<this.preWarmCycles;o++)this.animate(!0),this.render(!0);this._preWarmDone=!0}if(this._currentRenderId===this._scene.getFrameId())return 0;this._currentRenderId=this._scene.getFrameId()}if(this._initialize(),this._accumulatedCount+=this.emitRate*this._timeDelta,this._accumulatedCount>1){var a=0|this._accumulatedCount;this._accumulatedCount-=a,this._currentActiveCount=Math.min(this._activeCount,this._currentActiveCount+a)}if(!this._currentActiveCount)return 0;this._engine.enableEffect(this._updateEffect);var s,d=this._engine;if(!d.setState)throw new Error("GPU particles cannot work with a full Engine. ThinEngine is not supported");if(this._updateEffect.setFloat("currentCount",this._currentActiveCount),this._updateEffect.setFloat("timeDelta",this._timeDelta),this._updateEffect.setFloat("stopFactor",this._stopped?0:1),this._updateEffect.setTexture("randomSampler",this._randomTexture),this._updateEffect.setTexture("randomSampler2",this._randomTexture2),this._updateEffect.setFloat2("lifeTime",this.minLifeTime,this.maxLifeTime),this._updateEffect.setFloat2("emitPower",this.minEmitPower,this.maxEmitPower),this._colorGradientsTexture||(this._updateEffect.setDirectColor4("color1",this.color1),this._updateEffect.setDirectColor4("color2",this.color2)),this._updateEffect.setFloat2("sizeRange",this.minSize,this.maxSize),this._updateEffect.setFloat4("scaleRange",this.minScaleX,this.maxScaleX,this.minScaleY,this.maxScaleY),this._updateEffect.setFloat4("angleRange",this.minAngularSpeed,this.maxAngularSpeed,this.minInitialRotation,this.maxInitialRotation),this._updateEffect.setVector3("gravity",this.gravity),this._sizeGradientsTexture&&this._updateEffect.setTexture("sizeGradientSampler",this._sizeGradientsTexture),this._angularSpeedGradientsTexture&&this._updateEffect.setTexture("angularSpeedGradientSampler",this._angularSpeedGradientsTexture),this._velocityGradientsTexture&&this._updateEffect.setTexture("velocityGradientSampler",this._velocityGradientsTexture),this._limitVelocityGradientsTexture&&(this._updateEffect.setTexture("limitVelocityGradientSampler",this._limitVelocityGradientsTexture),this._updateEffect.setFloat("limitVelocityDamping",this.limitVelocityDamping)),this._dragGradientsTexture&&this._updateEffect.setTexture("dragGradientSampler",this._dragGradientsTexture),this.particleEmitterType&&this.particleEmitterType.applyToShader(this._updateEffect),this._isAnimationSheetEnabled&&this._updateEffect.setFloat3("cellInfos",this.startSpriteCellID,this.endSpriteCellID,this.spriteCellChangeSpeed),this.noiseTexture&&(this._updateEffect.setTexture("noiseSampler",this.noiseTexture),this._updateEffect.setVector3("noiseStrength",this.noiseStrength)),this.emitter.position)s=this.emitter.getWorldMatrix();else{var p=this.emitter;s=u.a.Translation(p.x,p.y,p.z)}if(this.isLocal||this._updateEffect.setMatrix("emitterWM",s),this._engine.bindVertexArrayObject(this._updateVAO[this._targetIndex],null),d.bindTransformFeedbackBuffer(this._targetBuffer.getBuffer()),d.setRasterizerState(!1),d.beginTransformFeedback(!0),d.drawArraysType(h.a.MATERIAL_PointListDrawMode,0,this._currentActiveCount),d.endTransformFeedback(),d.setRasterizerState(!0),d.bindTransformFeedbackBuffer(null),!e){var b=this._getEffect();this._engine.enableEffect(b);var P=((n=this._scene)===null||n===void 0?void 0:n.getViewMatrix())||u.a.IdentityReadOnly;if(b.setMatrix("view",P),b.setMatrix("projection",(i=this.defaultProjectionMatrix)!==null&&i!==void 0?i:this._scene.getProjectionMatrix()),b.setTexture("diffuseSampler",this.particleTexture),b.setVector2("translationPivot",this.translationPivot),b.setVector3("worldOffset",this.worldOffset),this.isLocal&&b.setMatrix("emitterWM",s),this._colorGradientsTexture?b.setTexture("colorGradientSampler",this._colorGradientsTexture):b.setDirectColor4("colorDead",this.colorDead),this._isAnimationSheetEnabled&&this.particleTexture){var O=this.particleTexture.getBaseSize();b.setFloat3("sheetInfos",this.spriteCellWidth/O.width,this.spriteCellHeight/O.height,O.width/this.spriteCellWidth)}if(this._isBillboardBased&&this._scene){var B=this._scene.activeCamera;b.setVector3("eyePosition",B.globalPosition)}var F=b.defines;if(this._scene&&(this._scene.clipPlane||this._scene.clipPlane2||this._scene.clipPlane3||this._scene.clipPlane4||this._scene.clipPlane5||this._scene.clipPlane6)&&et.a.BindClipPlane(b,this._scene),F.indexOf("#define BILLBOARDMODE_ALL")>=0){var z=P.clone();z.invert(),b.setMatrix("invView",z)}switch(this._imageProcessingConfiguration&&!this._imageProcessingConfiguration.applyByPostProcess&&this._imageProcessingConfiguration.bind(b),this.blendMode){case ln.BLENDMODE_ADD:this._engine.setAlphaMode(h.a.ALPHA_ADD);break;case ln.BLENDMODE_ONEONE:this._engine.setAlphaMode(h.a.ALPHA_ONEONE);break;case ln.BLENDMODE_STANDARD:this._engine.setAlphaMode(h.a.ALPHA_COMBINE);break;case ln.BLENDMODE_MULTIPLY:this._engine.setAlphaMode(h.a.ALPHA_MULTIPLY)}this.forceDepthWrite&&d.setDepthWrite(!0),this._engine.bindVertexArrayObject(this._renderVAO[this._targetIndex],null),this._onBeforeDrawParticlesObservable&&this._onBeforeDrawParticlesObservable.notifyObservers(b),this._engine.drawArraysType(h.a.MATERIAL_TriangleFanDrawMode,0,4,this._currentActiveCount),this._engine.setAlphaMode(h.a.ALPHA_DISABLE)}this._targetIndex++,this._targetIndex===2&&(this._targetIndex=0);var J=this._sourceBuffer;return this._sourceBuffer=this._targetBuffer,this._targetBuffer=J,this._currentActiveCount},t.prototype.rebuild=function(){this._initialize(!0)},t.prototype._releaseBuffers=function(){this._buffer0&&(this._buffer0.dispose(),this._buffer0=null),this._buffer1&&(this._buffer1.dispose(),this._buffer1=null),this._spriteBuffer&&(this._spriteBuffer.dispose(),this._spriteBuffer=null)},t.prototype._releaseVAOs=function(){if(this._updateVAO){for(var e=0;e<this._updateVAO.length;e++)this._engine.releaseVertexArrayObject(this._updateVAO[e]);for(this._updateVAO=[],e=0;e<this._renderVAO.length;e++)this._engine.releaseVertexArrayObject(this._renderVAO[e]);this._renderVAO=[]}},t.prototype.dispose=function(e){if(e===void 0&&(e=!0),this._scene){var n=this._scene.particleSystems.indexOf(this);n>-1&&this._scene.particleSystems.splice(n,1)}this._releaseBuffers(),this._releaseVAOs(),this._colorGradientsTexture&&(this._colorGradientsTexture.dispose(),this._colorGradientsTexture=null),this._sizeGradientsTexture&&(this._sizeGradientsTexture.dispose(),this._sizeGradientsTexture=null),this._angularSpeedGradientsTexture&&(this._angularSpeedGradientsTexture.dispose(),this._angularSpeedGradientsTexture=null),this._velocityGradientsTexture&&(this._velocityGradientsTexture.dispose(),this._velocityGradientsTexture=null),this._limitVelocityGradientsTexture&&(this._limitVelocityGradientsTexture.dispose(),this._limitVelocityGradientsTexture=null),this._dragGradientsTexture&&(this._dragGradientsTexture.dispose(),this._dragGradientsTexture=null),this._randomTexture&&(this._randomTexture.dispose(),this._randomTexture=null),this._randomTexture2&&(this._randomTexture2.dispose(),this._randomTexture2=null),e&&this.particleTexture&&(this.particleTexture.dispose(),this.particleTexture=null),e&&this.noiseTexture&&(this.noiseTexture.dispose(),this.noiseTexture=null),this.onStoppedObservable.clear(),this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear()},t.prototype.clone=function(e,n){var i=this.serialize(),o=t.Parse(i,this._scene||this._engine,""),a=Object(c.a)({},this._customEffect);return o.name=e,o._customEffect=a,n===void 0&&(n=this.emitter),o.emitter=n,o.noiseTexture=this.noiseTexture,o},t.prototype.serialize=function(e){e===void 0&&(e=!1);var n={};return ln._Serialize(n,this,e),n.activeParticleCount=this.activeParticleCount,n.randomTextureSize=this._randomTextureSize,n},t.Parse=function(e,n,i,o){o===void 0&&(o=!1);var a=new t(e.name,{capacity:e.capacity,randomTextureSize:e.randomTextureSize},n);return e.activeParticleCount&&(a.activeParticleCount=e.activeParticleCount),ln._Parse(e,a,n,i),e.preventAutoStart&&(a.preventAutoStart=e.preventAutoStart),o||a.preventAutoStart||a.start(),a},t}(yo),Ea=function(){function r(){this.systems=new Array}return Object.defineProperty(r.prototype,"emitterNode",{get:function(){return this._emitterNode},enumerable:!1,configurable:!0}),r.prototype.setEmitterAsSphere=function(t,e,n){this._emitterNode&&this._emitterNode.dispose(),this._emitterCreationOptions={kind:"Sphere",options:t,renderingGroupId:e};var i=Fn.a.CreateSphere("emitterSphere",{diameter:t.diameter,segments:t.segments},n);i.renderingGroupId=e;var o=new Ft.a("emitterSphereMaterial",n);o.emissiveColor=t.color,i.material=o;for(var a=0,s=this.systems;a<s.length;a++)s[a].emitter=i;this._emitterNode=i},r.prototype.start=function(t){for(var e=0,n=this.systems;e<n.length;e++){var i=n[e];t&&(i.emitter=t),i.start()}},r.prototype.dispose=function(){for(var t=0,e=this.systems;t<e.length;t++)e[t].dispose();this.systems=[],this._emitterNode&&(this._emitterNode.dispose(),this._emitterNode=null)},r.prototype.serialize=function(t){t===void 0&&(t=!1);for(var e={systems:[]},n=0,i=this.systems;n<i.length;n++){var o=i[n];e.systems.push(o.serialize(t))}return this._emitterNode&&(e.emitter=this._emitterCreationOptions),e},r.Parse=function(t,e,n){n===void 0&&(n=!1);var i=new r,o=this.BaseAssetsUrl+"/textures/";e=e||te.a.LastCreatedScene;for(var a=0,s=t.systems;a<s.length;a++){var d=s[a];i.systems.push(n?ar.Parse(d,e,o,!0):ln.Parse(d,e,o,!0))}if(t.emitter){var p=t.emitter.options;switch(t.emitter.kind){case"Sphere":i.setEmitterAsSphere({diameter:p.diameter,segments:p.segments,color:M.a.FromArray(p.color)},t.emitter.renderingGroupId,e)}}return i},r.BaseAssetsUrl="https://assets.babylonjs.com/particles",r}(),km=function(){function r(){}return r.CreateDefault=function(t,e,n,i){var o;return e===void 0&&(e=500),i===void 0&&(i=!1),(o=i?new ar("default system",{capacity:e},n):new ln("default system",e,n)).emitter=t,o.particleTexture=new we.a("https://www.babylonjs.com/assets/Flare.png",o.getScene()),o.createConeEmitter(.1,Math.PI/4),o.color1=new M.b(1,1,1,1),o.color2=new M.b(1,1,1,1),o.colorDead=new M.b(1,1,1,0),o.minSize=.1,o.maxSize=.1,o.minEmitPower=2,o.maxEmitPower=2,o.updateSpeed=1/60,o.emitRate=30,o},r.CreateAsync=function(t,e,n){n===void 0&&(n=!1),e||(e=te.a.LastCreatedScene);var i={};return e._addPendingData(i),new Promise(function(o,a){if(n&&!ar.IsSupported)return e._removePendingData(i),a("Particle system with GPU is not supported.");Xe.b.LoadFile(r.BaseAssetsUrl+"/systems/"+t+".json",function(s){e._removePendingData(i);var d=JSON.parse(s.toString());return o(Ea.Parse(d,e,n))},void 0,void 0,void 0,function(){return e._removePendingData(i),a("An error occured while the creation of your particle system. Check if your type '"+t+"' exists.")})})},r.ExportSet=function(t){for(var e=new Ea,n=0,i=t;n<i.length;n++){var o=i[n];e.systems.push(o)}return e},r.ParseFromFileAsync=function(t,e,n,i,o){return i===void 0&&(i=!1),o===void 0&&(o=""),new Promise(function(a,s){var d=new re.a;d.addEventListener("readystatechange",function(){if(d.readyState==4)if(d.status==200){var p=JSON.parse(d.responseText),b=void 0;b=i?ar.Parse(p,n,o):ln.Parse(p,n,o),t&&(b.name=t),a(b)}else s("Unable to load the particle system")}),d.open("GET",e),d.send()})},r.CreateFromSnippetAsync=function(t,e,n,i){var o=this;if(n===void 0&&(n=!1),i===void 0&&(i=""),t==="_BLANK"){var a=this.CreateDefault(null);return a.start(),Promise.resolve(a)}return new Promise(function(s,d){var p=new re.a;p.addEventListener("readystatechange",function(){if(p.readyState==4)if(p.status==200){var b=JSON.parse(JSON.parse(p.responseText).jsonPayload),P=JSON.parse(b.particleSystem),O=void 0;(O=n?ar.Parse(P,e,i):ln.Parse(P,e,i)).snippetId=t,s(O)}else d("Unable to load the snippet "+t)}),p.open("GET",o.SnippetUrl+"/"+t.replace(/#/g,"/")),p.send()})},r.BaseAssetsUrl=Ea.BaseAssetsUrl,r.SnippetUrl="https://snippet.babylonjs.com",r}();U.a.AddParser(at.a.NAME_PARTICLESYSTEM,function(r,t,e,n){var i=U.a.GetIndividualParser(at.a.NAME_PARTICLESYSTEM);if(i&&r.particleSystems!==void 0&&r.particleSystems!==null)for(var o=0,a=r.particleSystems.length;o<a;o++){var s=r.particleSystems[o];e.particleSystems.push(i(s,t,n))}}),U.a.AddIndividualParser(at.a.NAME_PARTICLESYSTEM,function(r,t,e){return r.activeParticleCount?ar.Parse(r,t,e):ln.Parse(r,t,e)}),Ue.a.prototype.createEffectForParticles=function(r,t,e,n,i,o,a,s){var d;t===void 0&&(t=[]),e===void 0&&(e=[]),n===void 0&&(n="");var p=[],b=[],P=[];return s?s.fillUniformsAttributesAndSamplerNames(b,p,P):(p=ln._GetAttributeNamesOrOptions(),b=ln._GetEffectCreationOptions()),n.indexOf(" BILLBOARD")===-1&&(n+=`
-#define BILLBOARD
-`),e.indexOf("diffuseSampler")===-1&&e.push("diffuseSampler"),this.createEffect({vertex:(d=s?.vertexShaderName)!==null&&d!==void 0?d:"particles",fragmentElement:r},p,b.concat(t),P.concat(e),n,i,o,a)},De.a.prototype.getEmittedParticleSystems=function(){for(var r=new Array,t=0;t<this.getScene().particleSystems.length;t++){var e=this.getScene().particleSystems[t];e.emitter===this&&r.push(e)}return r},De.a.prototype.getHierarchyEmittedParticleSystems=function(){var r=new Array,t=this.getDescendants();t.push(this);for(var e=0;e<this.getScene().particleSystems.length;e++){var n=this.getScene().particleSystems[e],i=n.emitter;i.position&&t.indexOf(i)!==-1&&r.push(n)}return r};var En,Mc=function(){function r(t,e,n,i,o,a,s,d,p,b){p===void 0&&(p=null),b===void 0&&(b=null),this.idx=0,this.id=0,this.color=new M.b(1,1,1,1),this.position=u.e.Zero(),this.rotation=u.e.Zero(),this.scaling=u.e.One(),this.uvs=new u.f(0,0,1,1),this.velocity=u.e.Zero(),this.pivot=u.e.Zero(),this.translateFromPivot=!1,this.alive=!0,this.isVisible=!0,this._pos=0,this._ind=0,this.shapeId=0,this.idxInShape=0,this._stillInvisible=!1,this._rotationMatrix=[1,0,0,0,1,0,0,0,1],this.parentId=null,this.materialIndex=null,this.props=null,this.cullingStrategy=Dt.a.CULLINGSTRATEGY_BOUNDINGSPHERE_ONLY,this._globalPosition=u.e.Zero(),this.idx=t,this.id=e,this._pos=n,this._ind=i,this._model=o,this.shapeId=a,this.idxInShape=s,this._sps=d,p&&(this._modelBoundingInfo=p,this._boundingInfo=new Vi.a(p.minimum,p.maximum)),b!==null&&(this.materialIndex=b)}return r.prototype.copyToRef=function(t){return t.position.copyFrom(this.position),t.rotation.copyFrom(this.rotation),this.rotationQuaternion&&(t.rotationQuaternion?t.rotationQuaternion.copyFrom(this.rotationQuaternion):t.rotationQuaternion=this.rotationQuaternion.clone()),t.scaling.copyFrom(this.scaling),this.color&&(t.color?t.color.copyFrom(this.color):t.color=this.color.clone()),t.uvs.copyFrom(this.uvs),t.velocity.copyFrom(this.velocity),t.pivot.copyFrom(this.pivot),t.translateFromPivot=this.translateFromPivot,t.alive=this.alive,t.isVisible=this.isVisible,t.parentId=this.parentId,t.cullingStrategy=this.cullingStrategy,this.materialIndex!==null&&(t.materialIndex=this.materialIndex),this},Object.defineProperty(r.prototype,"scale",{get:function(){return this.scaling},set:function(t){this.scaling=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"quaternion",{get:function(){return this.rotationQuaternion},set:function(t){this.rotationQuaternion=t},enumerable:!1,configurable:!0}),r.prototype.intersectsMesh=function(t){return!(!this._boundingInfo||!t._boundingInfo)&&(this._sps._bSphereOnly?Zl.a.Intersects(this._boundingInfo.boundingSphere,t._boundingInfo.boundingSphere):this._boundingInfo.intersects(t._boundingInfo,!1))},r.prototype.isInFrustum=function(t){return this._boundingInfo!==null&&this._boundingInfo.isInFrustum(t,this.cullingStrategy)},r.prototype.getRotationMatrix=function(t){var e;if(this.rotationQuaternion)e=this.rotationQuaternion;else{e=u.c.Quaternion[0];var n=this.rotation;u.b.RotationYawPitchRollToRef(n.y,n.x,n.z,e)}e.toRotationMatrix(t)},r}(),Ic=function(r,t,e,n,i,o,a,s,d){this._indicesLength=0,this.shapeID=r,this._shape=t,this._indices=e,this._indicesLength=e.length,this._shapeUV=o,this._shapeColors=i,this._normals=n,this._positionFunction=a,this._vertexFunction=s,this._material=d},Pd=function(r,t,e,n){this.idx=0,this.ind=0,this.indicesLength=0,this.sqDistance=0,this.materialIndex=0,this.idx=r,this.ind=t,this.indicesLength=e,this.materialIndex=n},Cd=function(){function r(){this.position=u.e.Zero(),this.color=new M.b(1,1,1,1),this.uv=u.d.Zero()}return Object.defineProperty(r.prototype,"x",{get:function(){return this.position.x},set:function(t){this.position.x=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"y",{get:function(){return this.position.y},set:function(t){this.position.y=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"z",{get:function(){return this.position.z},set:function(t){this.position.z=t},enumerable:!1,configurable:!0}),r}(),Gm=function(){function r(t,e,n){this.particles=new Array,this.nbParticles=0,this.billboard=!1,this.recomputeNormals=!1,this.counter=0,this.vars={},this._bSphereOnly=!1,this._bSphereRadiusFactor=1,this._positions=new Array,this._indices=new Array,this._normals=new Array,this._colors=new Array,this._uvs=new Array,this._index=0,this._updatable=!0,this._pickable=!1,this._isVisibilityBoxLocked=!1,this._alwaysVisible=!1,this._depthSort=!1,this._expandable=!1,this._shapeCounter=0,this._copy=new Mc(0,0,0,0,null,0,0,this),this._color=new M.b(0,0,0,0),this._computeParticleColor=!0,this._computeParticleTexture=!0,this._computeParticleRotation=!0,this._computeParticleVertex=!1,this._computeBoundingBox=!1,this._depthSortParticles=!0,this._mustUnrotateFixedNormals=!1,this._particlesIntersect=!1,this._needs32Bits=!1,this._isNotBuilt=!0,this._lastParticleId=0,this._idxOfId=[],this._multimaterialEnabled=!1,this._useModelMaterial=!1,this._depthSortFunction=function(i,o){return o.sqDistance-i.sqDistance},this._materialSortFunction=function(i,o){return i.materialIndex-o.materialIndex},this._autoUpdateSubMeshes=!1,this.name=t,this._scene=e||te.a.LastCreatedScene,this._camera=e.activeCamera,this._pickable=!!n&&n.isPickable,this._depthSort=!!n&&n.enableDepthSort,this._multimaterialEnabled=!!n&&n.enableMultiMaterial,this._useModelMaterial=!!n&&n.useModelMaterial,this._multimaterialEnabled=!!this._useModelMaterial||this._multimaterialEnabled,this._expandable=!!n&&n.expandable,this._particlesIntersect=!!n&&n.particleIntersection,this._bSphereOnly=!!n&&n.boundingSphereOnly,this._bSphereRadiusFactor=n&&n.bSphereRadiusFactor?n.bSphereRadiusFactor:1,n&&n.updatable!==void 0?this._updatable=n.updatable:this._updatable=!0,this._pickable&&(this.pickedBySubMesh=[[]],this.pickedParticles=this.pickedBySubMesh[0]),(this._depthSort||this._multimaterialEnabled)&&(this.depthSortedParticles=[]),this._multimaterialEnabled&&(this._multimaterial=new rr.a(this.name+"MultiMaterial",this._scene),this._materials=[],this._materialIndexesById={}),this._tmpVertex=new Cd}return r.prototype.buildMesh=function(){if(!this._isNotBuilt&&this.mesh)return this.mesh;if(this.nbParticles===0&&!this.mesh){var t=Ta.CreateDisc("",{radius:1,tessellation:3},this._scene);this.addShape(t,1),t.dispose()}if(this._indices32=this._needs32Bits?new Uint32Array(this._indices):new Uint16Array(this._indices),this._positions32=new Float32Array(this._positions),this._uvs32=new Float32Array(this._uvs),this._colors32=new Float32Array(this._colors),!this.mesh){var e=new De.a(this.name,this._scene);this.mesh=e}!this._updatable&&this._multimaterialEnabled&&this._sortParticlesByMaterial(),this.recomputeNormals&&ft.a.ComputeNormals(this._positions32,this._indices32,this._normals),this._normals32=new Float32Array(this._normals),this._fixedNormal32=new Float32Array(this._normals),this._mustUnrotateFixedNormals&&this._unrotateFixedNormals();var n=new ft.a;if(n.indices=this._depthSort?this._indices:this._indices32,n.set(this._positions32,Oe.b.PositionKind),n.set(this._normals32,Oe.b.NormalKind),this._uvs32.length>0&&n.set(this._uvs32,Oe.b.UVKind),this._colors32.length>0&&n.set(this._colors32,Oe.b.ColorKind),n.applyToMesh(this.mesh,this._updatable),this.mesh.isPickable=this._pickable,this._pickable){for(var i=0,o=0;o<this.nbParticles;o++)for(var a=this.particles[o],s=a._model._indicesLength,d=0;d<s;d++)if(d%3==0){var p={idx:a.idx,faceId:i};this.pickedParticles[i]=p,i++}}return this._multimaterialEnabled&&this.setMultiMaterial(this._materials),this._expandable||(this._depthSort||this._multimaterialEnabled||(this._indices=null),this._positions=null,this._normals=null,this._uvs=null,this._colors=null,this._updatable||(this.particles.length=0)),this._isNotBuilt=!1,this.recomputeNormals=!1,this.mesh},r.prototype.digest=function(t,e){var n=e&&e.facetNb||1,i=e&&e.number||0,o=e&&e.delta||0,a=t.getVerticesData(Oe.b.PositionKind),s=t.getIndices(),d=t.getVerticesData(Oe.b.UVKind),p=t.getVerticesData(Oe.b.ColorKind),b=t.getVerticesData(Oe.b.NormalKind),P=e&&e.storage?e.storage:null,O=0,B=s.length/3;i?(i=i>B?B:i,n=Math.round(B/i),o=0):n=n>B?B:n;for(var F=[],z=[],J=[],ie=[],se=[],ce=u.e.Zero(),ue=n;O<B;){O>B-(n=ue+Math.floor((1+o)*Math.random()))&&(n=B-O),F.length=0,z.length=0,J.length=0,ie.length=0,se.length=0;for(var fe=0,ve=3*O;ve<3*(O+n);ve++){J.push(fe);var Te=s[ve],Re=3*Te;if(F.push(a[Re],a[Re+1],a[Re+2]),z.push(b[Re],b[Re+1],b[Re+2]),d){var Ae=2*Te;ie.push(d[Ae],d[Ae+1])}if(p){var Ee=4*Te;se.push(p[Ee],p[Ee+1],p[Ee+2],p[Ee+3])}fe++}var Se,Le=this.nbParticles,Ce=this._posToShape(F),Ne=this._uvsToShapeUV(ie),Ie=Xe.b.Slice(J),Fe=Xe.b.Slice(se),Ye=Xe.b.Slice(z);for(ce.copyFromFloats(0,0,0),Se=0;Se<Ce.length;Se++)ce.addInPlace(Ce[Se]);ce.scaleInPlace(1/Ce.length);var tt,it=new u.e(1/0,1/0,1/0),lt=new u.e(-1/0,-1/0,-1/0);for(Se=0;Se<Ce.length;Se++)Ce[Se].subtractInPlace(ce),it.minimizeInPlaceFromFloats(Ce[Se].x,Ce[Se].y,Ce[Se].z),lt.maximizeInPlaceFromFloats(Ce[Se].x,Ce[Se].y,Ce[Se].z);this._particlesIntersect&&(tt=new Vi.a(it,lt));var Qe=null;this._useModelMaterial&&(Qe=t.material?t.material:this._setDefaultMaterial());var ot=new Ic(this._shapeCounter,Ce,Ie,Ye,Fe,Ne,null,null,Qe),rt=this._positions.length,Ze=this._indices.length;this._meshBuilder(this._index,Ze,Ce,this._positions,Ie,this._indices,ie,this._uvs,Fe,this._colors,Ye,this._normals,Le,0,null,ot),this._addParticle(Le,this._lastParticleId,rt,Ze,ot,this._shapeCounter,0,tt,P),this.particles[this.nbParticles].position.addInPlace(ce),P||(this._index+=Ce.length,Le++,this.nbParticles++,this._lastParticleId++),this._shapeCounter++,O+=n}return this._isNotBuilt=!0,this},r.prototype._unrotateFixedNormals=function(){for(var t=0,e=0,n=u.c.Vector3[0],i=u.c.Quaternion[0],o=u.c.Matrix[0],a=0;a<this.particles.length;a++){var s=this.particles[a],d=s._model._shape;if(s.rotationQuaternion)s.rotationQuaternion.conjugateToRef(i);else{var p=s.rotation;u.b.RotationYawPitchRollToRef(p.y,p.x,p.z,i),i.conjugateInPlace()}i.toRotationMatrix(o);for(var b=0;b<d.length;b++)e=t+3*b,u.e.TransformNormalFromFloatsToRef(this._normals32[e],this._normals32[e+1],this._normals32[e+2],o,n),n.toArray(this._fixedNormal32,e);t=e+3}},r.prototype._resetCopy=function(){var t=this._copy;t.position.setAll(0),t.rotation.setAll(0),t.rotationQuaternion=null,t.scaling.setAll(1),t.uvs.copyFromFloats(0,0,1,1),t.color=null,t.translateFromPivot=!1,t.shapeId=0,t.materialIndex=null},r.prototype._meshBuilder=function(t,e,n,i,o,a,s,d,p,b,P,O,B,F,z,J){var ie,se=0,ce=0,ue=0;this._resetCopy();var fe=this._copy,ve=!(!z||!z.storage);if(fe.idx=B,fe.idxInShape=F,fe.shapeId=J.shapeID,this._useModelMaterial){var Te=J._material.uniqueId,Re=this._materialIndexesById;Re.hasOwnProperty(Te)||(Re[Te]=this._materials.length,this._materials.push(J._material));var Ae=Re[Te];fe.materialIndex=Ae}if(z&&z.positionFunction&&(z.positionFunction(fe,B,F),this._mustUnrotateFixedNormals=!0),ve)return fe;var Ee=u.c.Matrix[0],Se=this._tmpVertex,Le=Se.position,Ce=Se.color,Ne=Se.uv,Ie=u.c.Vector3[1],Fe=u.c.Vector3[2],Ye=u.c.Vector3[3];u.a.IdentityToRef(Ee),fe.getRotationMatrix(Ee),fe.pivot.multiplyToRef(fe.scaling,Ye),fe.translateFromPivot?Fe.setAll(0):Fe.copyFrom(Ye);var tt=z&&z.vertexFunction;for(ie=0;ie<n.length;ie++){if(Le.copyFrom(n[ie]),fe.color&&Ce.copyFrom(fe.color),s&&Ne.copyFromFloats(s[se],s[se+1]),tt&&z.vertexFunction(fe,Se,ie),Le.multiplyInPlace(fe.scaling).subtractInPlace(Ye),u.e.TransformCoordinatesToRef(Le,Ee,Ie),Ie.addInPlace(Fe).addInPlace(fe.position),i.push(Ie.x,Ie.y,Ie.z),s){var it=fe.uvs;d.push((it.z-it.x)*Ne.x+it.x,(it.w-it.y)*Ne.y+it.y),se+=2}if(fe.color)this._color.copyFrom(Ce);else{var lt=this._color;p&&p[ce]!==void 0?(lt.r=p[ce],lt.g=p[ce+1],lt.b=p[ce+2],lt.a=p[ce+3]):(lt.r=1,lt.g=1,lt.b=1,lt.a=1)}b.push(this._color.r,this._color.g,this._color.b,this._color.a),ce+=4,!this.recomputeNormals&&P&&(u.e.TransformNormalFromFloatsToRef(P[ue],P[ue+1],P[ue+2],Ee,Le),O.push(Le.x,Le.y,Le.z),ue+=3)}for(ie=0;ie<o.length;ie++){var Qe=t+o[ie];a.push(Qe),Qe>65535&&(this._needs32Bits=!0)}if(this._depthSort||this._multimaterialEnabled){var ot=fe.materialIndex!==null?fe.materialIndex:0;this.depthSortedParticles.push(new Pd(B,e,o.length,ot))}return fe},r.prototype._posToShape=function(t){for(var e=[],n=0;n<t.length;n+=3)e.push(u.e.FromArray(t,n));return e},r.prototype._uvsToShapeUV=function(t){var e=[];if(t)for(var n=0;n<t.length;n++)e.push(t[n]);return e},r.prototype._addParticle=function(t,e,n,i,o,a,s,d,p){d===void 0&&(d=null),p===void 0&&(p=null);var b=new Mc(t,e,n,i,o,a,s,this,d);return(p||this.particles).push(b),b},r.prototype.addShape=function(t,e,n){var i=t.getVerticesData(Oe.b.PositionKind),o=t.getIndices(),a=t.getVerticesData(Oe.b.UVKind),s=t.getVerticesData(Oe.b.ColorKind),d=t.getVerticesData(Oe.b.NormalKind);this.recomputeNormals=!d;var p=Xe.b.SliceToArray(o),b=Xe.b.SliceToArray(d),P=s?Xe.b.SliceToArray(s):[],O=n&&n.storage?n.storage:null,B=null;this._particlesIntersect&&(B=t.getBoundingInfo());var F=this._posToShape(i),z=this._uvsToShapeUV(a),J=n?n.positionFunction:null,ie=n?n.vertexFunction:null,se=null;this._useModelMaterial&&(se=t.material?t.material:this._setDefaultMaterial());for(var ce=new Ic(this._shapeCounter,F,p,b,P,z,J,ie,se),ue=0;ue<e;ue++)this._insertNewParticle(this.nbParticles,ue,ce,F,o,a,s,d,B,O,n);return this._shapeCounter++,this._isNotBuilt=!0,this._shapeCounter-1},r.prototype._rebuildParticle=function(t,e){e===void 0&&(e=!1),this._resetCopy();var n=this._copy;t._model._positionFunction&&t._model._positionFunction(n,t.idx,t.idxInShape);var i=u.c.Matrix[0],o=u.c.Vector3[0],a=u.c.Vector3[1],s=u.c.Vector3[2],d=u.c.Vector3[3];n.getRotationMatrix(i),t.pivot.multiplyToRef(t.scaling,d),n.translateFromPivot?s.copyFromFloats(0,0,0):s.copyFrom(d);for(var p=t._model._shape,b=0;b<p.length;b++)o.copyFrom(p[b]),t._model._vertexFunction&&t._model._vertexFunction(n,o,b),o.multiplyInPlace(n.scaling).subtractInPlace(d),u.e.TransformCoordinatesToRef(o,i,a),a.addInPlace(s).addInPlace(n.position).toArray(this._positions32,t._pos+3*b);e&&(t.position.setAll(0),t.rotation.setAll(0),t.rotationQuaternion=null,t.scaling.setAll(1),t.uvs.setAll(0),t.pivot.setAll(0),t.translateFromPivot=!1,t.parentId=null)},r.prototype.rebuildMesh=function(t){t===void 0&&(t=!1);for(var e=0;e<this.particles.length;e++)this._rebuildParticle(this.particles[e],t);return this.mesh.updateVerticesData(Oe.b.PositionKind,this._positions32,!1,!1),this},r.prototype.removeParticles=function(t,e){var n=e-t+1;if(!this._expandable||n<=0||n>=this.nbParticles||!this._updatable)return[];var i=this.particles,o=this.nbParticles;if(e<o-1)for(var a=e+1,s=i[a]._pos-i[t]._pos,d=i[a]._ind-i[t]._ind,p=a;p<o;p++){var b=i[p];b._pos-=s,b._ind-=d}var P=i.splice(t,n);this._positions.length=0,this._indices.length=0,this._colors.length=0,this._uvs.length=0,this._normals.length=0,this._index=0,this._idxOfId.length=0,(this._depthSort||this._multimaterialEnabled)&&(this.depthSortedParticles=[]);for(var O=0,B=i.length,F=0;F<B;F++){var z=i[F],J=z._model,ie=J._shape,se=J._indices,ce=J._normals,ue=J._shapeColors,fe=J._shapeUV;z.idx=F,this._idxOfId[z.id]=F,this._meshBuilder(this._index,O,ie,this._positions,se,this._indices,fe,this._uvs,ue,this._colors,ce,this._normals,z.idx,z.idxInShape,null,J),this._index+=ie.length,O+=se.length}return this.nbParticles-=n,this._isNotBuilt=!0,P},r.prototype.insertParticlesFromArray=function(t){if(!this._expandable)return this;for(var e=0,n=t[0].shapeId,i=t.length,o=0;o<i;o++){var a=t[o],s=a._model,d=s._shape,p=s._indices,b=s._shapeUV,P=s._shapeColors,O=s._normals,B=!O;this.recomputeNormals=B||this.recomputeNormals;var F=a._boundingInfo,z=this._insertNewParticle(this.nbParticles,e,s,d,p,b,P,O,F,null,null);a.copyToRef(z),e++,n!=a.shapeId&&(n=a.shapeId,e=0)}return this._isNotBuilt=!0,this},r.prototype._insertNewParticle=function(t,e,n,i,o,a,s,d,p,b,P){var O=this._positions.length,B=this._indices.length,F=this._meshBuilder(this._index,B,i,this._positions,o,this._indices,a,this._uvs,s,this._colors,d,this._normals,t,e,P,n),z=null;return this._updatable&&((z=this._addParticle(this.nbParticles,this._lastParticleId,O,B,n,this._shapeCounter,e,p,b)).position.copyFrom(F.position),z.rotation.copyFrom(F.rotation),F.rotationQuaternion&&(z.rotationQuaternion?z.rotationQuaternion.copyFrom(F.rotationQuaternion):z.rotationQuaternion=F.rotationQuaternion.clone()),F.color&&(z.color?z.color.copyFrom(F.color):z.color=F.color.clone()),z.scaling.copyFrom(F.scaling),z.uvs.copyFrom(F.uvs),F.materialIndex!==null&&(z.materialIndex=F.materialIndex),this.expandable&&(this._idxOfId[z.id]=z.idx)),b||(this._index+=i.length,this.nbParticles++,this._lastParticleId++),z},r.prototype.setParticles=function(t,e,n){if(t===void 0&&(t=0),e===void 0&&(e=this.nbParticles-1),n===void 0&&(n=!0),!this._updatable||this._isNotBuilt)return this;this.beforeUpdateParticles(t,e,n);var i=u.c.Matrix[0],o=u.c.Matrix[1],a=this.mesh,s=this._colors32,d=this._positions32,p=this._normals32,b=this._uvs32,P=this._indices32,O=this._indices,B=this._fixedNormal32,F=u.c.Vector3,z=F[5].copyFromFloats(1,0,0),J=F[6].copyFromFloats(0,1,0),ie=F[7].copyFromFloats(0,0,1),se=F[8].setAll(Number.MAX_VALUE),ce=F[9].setAll(-Number.MAX_VALUE),ue=F[10].setAll(0),fe=this._tmpVertex,ve=fe.position,Te=fe.color,Re=fe.uv;if((this.billboard||this._depthSort)&&(this.mesh.computeWorldMatrix(!0),this.mesh._worldMatrix.invertToRef(o)),this.billboard){var Ae=F[0];this._camera.getDirectionToRef(ye.a.Z,Ae),u.e.TransformNormalToRef(Ae,o,ie),ie.normalize();var Ee=this._camera.getViewMatrix(!0);u.e.TransformNormalFromFloatsToRef(Ee.m[1],Ee.m[5],Ee.m[9],o,J),u.e.CrossToRef(J,ie,z),J.normalize(),z.normalize()}this._depthSort&&u.e.TransformCoordinatesToRef(this._camera.globalPosition,o,ue),u.a.IdentityToRef(i);var Se=0,Le=0,Ce=0,Ne=0,Ie=0,Fe=0,Ye=0;if(this.mesh.isFacetDataEnabled&&(this._computeBoundingBox=!0),e=e>=this.nbParticles?this.nbParticles-1:e,this._computeBoundingBox&&(t!=0||e!=this.nbParticles-1)){var tt=this.mesh._boundingInfo;tt&&(se.copyFrom(tt.minimum),ce.copyFrom(tt.maximum))}var it=(Le=this.particles[t]._pos)/3|0;Ne=4*it,Fe=2*it;for(var lt=t;lt<=e;lt++){var Qe=this.particles[lt];this.updateParticle(Qe);var ot=Qe._model._shape,rt=Qe._model._shapeUV,Ze=Qe._rotationMatrix,dt=Qe.position,Ve=Qe.rotation,Je=Qe.scaling,yt=Qe._globalPosition;if(this._depthSort&&this._depthSortParticles){var Wt=this.depthSortedParticles[lt];Wt.idx=Qe.idx,Wt.ind=Qe._ind,Wt.indicesLength=Qe._model._indicesLength,Wt.sqDistance=u.e.DistanceSquared(Qe.position,ue)}if(!Qe.alive||Qe._stillInvisible&&!Qe.isVisible)Le+=3*(Ye=ot.length),Ne+=4*Ye,Fe+=2*Ye;else{if(Qe.isVisible){Qe._stillInvisible=!1;var Nt=F[12];if(Qe.pivot.multiplyToRef(Je,Nt),this.billboard&&(Ve.x=0,Ve.y=0),(this._computeParticleRotation||this.billboard)&&Qe.getRotationMatrix(i),Qe.parentId!==null){var Qt=this.getParticleById(Qe.parentId);if(Qt){var vt=Qt._rotationMatrix,Jt=Qt._globalPosition,Xt=dt.x*vt[1]+dt.y*vt[4]+dt.z*vt[7],zt=dt.x*vt[0]+dt.y*vt[3]+dt.z*vt[6],Yt=dt.x*vt[2]+dt.y*vt[5]+dt.z*vt[8];if(yt.x=Jt.x+zt,yt.y=Jt.y+Xt,yt.z=Jt.z+Yt,this._computeParticleRotation||this.billboard){var Et=i.m;Ze[0]=Et[0]*vt[0]+Et[1]*vt[3]+Et[2]*vt[6],Ze[1]=Et[0]*vt[1]+Et[1]*vt[4]+Et[2]*vt[7],Ze[2]=Et[0]*vt[2]+Et[1]*vt[5]+Et[2]*vt[8],Ze[3]=Et[4]*vt[0]+Et[5]*vt[3]+Et[6]*vt[6],Ze[4]=Et[4]*vt[1]+Et[5]*vt[4]+Et[6]*vt[7],Ze[5]=Et[4]*vt[2]+Et[5]*vt[5]+Et[6]*vt[8],Ze[6]=Et[8]*vt[0]+Et[9]*vt[3]+Et[10]*vt[6],Ze[7]=Et[8]*vt[1]+Et[9]*vt[4]+Et[10]*vt[7],Ze[8]=Et[8]*vt[2]+Et[9]*vt[5]+Et[10]*vt[8]}}else Qe.parentId=null}else yt.x=dt.x,yt.y=dt.y,yt.z=dt.z,(this._computeParticleRotation||this.billboard)&&(Et=i.m,Ze[0]=Et[0],Ze[1]=Et[1],Ze[2]=Et[2],Ze[3]=Et[4],Ze[4]=Et[5],Ze[5]=Et[6],Ze[6]=Et[8],Ze[7]=Et[9],Ze[8]=Et[10]);var Mt=F[11];for(Qe.translateFromPivot?Mt.setAll(0):Mt.copyFrom(Nt),Ye=0;Ye<ot.length;Ye++){Se=Le+3*Ye,Ce=Ne+4*Ye,Ie=Fe+2*Ye;var $t=2*Ye,Dn=$t+1;ve.copyFrom(ot[Ye]),this._computeParticleColor&&Qe.color&&Te.copyFrom(Qe.color),this._computeParticleTexture&&Re.copyFromFloats(rt[$t],rt[Dn]),this._computeParticleVertex&&this.updateParticleVertex(Qe,fe,Ye);var Vn=ve.x*Je.x-Nt.x,$n=ve.y*Je.y-Nt.y,Ln=ve.z*Je.z-Nt.z;zt=Vn*Ze[0]+$n*Ze[3]+Ln*Ze[6],Xt=Vn*Ze[1]+$n*Ze[4]+Ln*Ze[7],Yt=Vn*Ze[2]+$n*Ze[5]+Ln*Ze[8],zt+=Mt.x,Xt+=Mt.y,Yt+=Mt.z;var qt=d[Se]=yt.x+z.x*zt+J.x*Xt+ie.x*Yt,hi=d[Se+1]=yt.y+z.y*zt+J.y*Xt+ie.y*Yt,Ri=d[Se+2]=yt.z+z.z*zt+J.z*Xt+ie.z*Yt;if(this._computeBoundingBox&&(se.minimizeInPlaceFromFloats(qt,hi,Ri),ce.maximizeInPlaceFromFloats(qt,hi,Ri)),!this._computeParticleVertex){var Gr=B[Se],zr=B[Se+1],di=B[Se+2],Hi=Gr*Ze[0]+zr*Ze[3]+di*Ze[6],jr=Gr*Ze[1]+zr*Ze[4]+di*Ze[7],jt=Gr*Ze[2]+zr*Ze[5]+di*Ze[8];p[Se]=z.x*Hi+J.x*jr+ie.x*jt,p[Se+1]=z.y*Hi+J.y*jr+ie.y*jt,p[Se+2]=z.z*Hi+J.z*jr+ie.z*jt}if(this._computeParticleColor&&Qe.color){var Wi=this._colors32;Wi[Ce]=Te.r,Wi[Ce+1]=Te.g,Wi[Ce+2]=Te.b,Wi[Ce+3]=Te.a}if(this._computeParticleTexture){var Sn=Qe.uvs;b[Ie]=Re.x*(Sn.z-Sn.x)+Sn.x,b[Ie+1]=Re.y*(Sn.w-Sn.y)+Sn.y}}}else for(Qe._stillInvisible=!0,Ye=0;Ye<ot.length;Ye++){if(Ce=Ne+4*Ye,Ie=Fe+2*Ye,d[Se=Le+3*Ye]=d[Se+1]=d[Se+2]=0,p[Se]=p[Se+1]=p[Se+2]=0,this._computeParticleColor&&Qe.color){var lr=Qe.color;s[Ce]=lr.r,s[Ce+1]=lr.g,s[Ce+2]=lr.b,s[Ce+3]=lr.a}this._computeParticleTexture&&(Sn=Qe.uvs,b[Ie]=rt[2*Ye]*(Sn.z-Sn.x)+Sn.x,b[Ie+1]=rt[2*Ye+1]*(Sn.w-Sn.y)+Sn.y)}if(this._particlesIntersect){var Oi=Qe._boundingInfo,ka=Oi.boundingBox,Ga=Oi.boundingSphere,Hr=Qe._modelBoundingInfo;if(!this._bSphereOnly){var Xi=Hr.boundingBox.vectors,Yi=F[1],ur=F[2];Yi.setAll(Number.MAX_VALUE),ur.setAll(-Number.MAX_VALUE);for(var Ki=0;Ki<8;Ki++){var Wr=Xi[Ki].x*Je.x,Xr=Xi[Ki].y*Je.y,Yr=Xi[Ki].z*Je.z,Qi=(zt=Wr*Ze[0]+Xr*Ze[3]+Yr*Ze[6],Xt=Wr*Ze[1]+Xr*Ze[4]+Yr*Ze[7],Yt=Wr*Ze[2]+Xr*Ze[5]+Yr*Ze[8],dt.x+z.x*zt+J.x*Xt+ie.x*Yt),qi=dt.y+z.y*zt+J.y*Xt+ie.y*Yt,Kr=dt.z+z.z*zt+J.z*Xt+ie.z*Yt;Yi.minimizeInPlaceFromFloats(Qi,qi,Kr),ur.maximizeInPlaceFromFloats(Qi,qi,Kr)}ka.reConstruct(Yi,ur,a._worldMatrix)}var Mi=Hr.minimum.multiplyToRef(Je,F[1]),Nn=Hr.maximum.multiplyToRef(Je,F[2]),Io=Nn.addToRef(Mi,F[3]).scaleInPlace(.5).addInPlace(yt),hr=Nn.subtractToRef(Mi,F[4]).scaleInPlace(.5*this._bSphereRadiusFactor),Do=Io.subtractToRef(hr,F[1]),Sv=Io.addToRef(hr,F[2]);Ga.reConstruct(Do,Sv,a._worldMatrix)}Le=Se+3,Ne=Ce+4,Fe=Ie+2}}if(n){if(this._computeParticleColor&&a.updateVerticesData(Oe.b.ColorKind,s,!1,!1),this._computeParticleTexture&&a.updateVerticesData(Oe.b.UVKind,b,!1,!1),a.updateVerticesData(Oe.b.PositionKind,d,!1,!1),!a.areNormalsFrozen||a.isFacetDataEnabled){if(this._computeParticleVertex||a.isFacetDataEnabled){var Av=a.isFacetDataEnabled?a.getFacetDataParameters():null;ft.a.ComputeNormals(d,P,p,Av);for(var Ii=0;Ii<p.length;Ii++)B[Ii]=p[Ii]}a.areNormalsFrozen||a.updateVerticesData(Oe.b.NormalKind,p,!1,!1)}if(this._depthSort&&this._depthSortParticles){var el=this.depthSortedParticles;el.sort(this._depthSortFunction);for(var Pv=el.length,yf=0,tl=0,nl=0;nl<Pv;nl++){var il=el[nl],Cv=il.indicesLength,xv=il.ind;for(Ii=0;Ii<Cv;Ii++)if(P[yf]=O[xv+Ii],yf++,this._pickable&&Ii%3==0){var Tf=this.pickedParticles[tl];Tf.idx=il.idx,Tf.faceId=tl,tl++}}a.updateIndices(P)}}return this._computeBoundingBox&&(a._boundingInfo?a._boundingInfo.reConstruct(se,ce,a._worldMatrix):a._boundingInfo=new Vi.a(se,ce,a._worldMatrix)),this._autoUpdateSubMeshes&&this.computeSubMeshes(),this.afterUpdateParticles(t,e,n),this},r.prototype.dispose=function(){this.mesh.dispose(),this.vars=null,this._positions=null,this._indices=null,this._normals=null,this._uvs=null,this._colors=null,this._indices32=null,this._positions32=null,this._normals32=null,this._fixedNormal32=null,this._uvs32=null,this._colors32=null,this.pickedParticles=null,this.pickedBySubMesh=null,this._materials=null,this._materialIndexes=null,this._indicesByMaterial=null,this._idxOfId=null},r.prototype.pickedParticle=function(t){if(t.hit){var e=t.subMeshId,n=t.faceId,i=this.pickedBySubMesh;if(i[e]&&i[e][n])return i[e][n]}return null},r.prototype.getParticleById=function(t){var e=this.particles[t];if(e&&e.id==t)return e;var n=this.particles,i=this._idxOfId[t];if(i!==void 0)return n[i];for(var o=0,a=this.nbParticles;o<a;){var s=n[o];if(s.id==t)return s;o++}return null},r.prototype.getParticlesByShapeId=function(t){var e=[];return this.getParticlesByShapeIdToRef(t,e),e},r.prototype.getParticlesByShapeIdToRef=function(t,e){e.length=0;for(var n=0;n<this.nbParticles;n++){var i=this.particles[n];i.shapeId==t&&e.push(i)}return this},r.prototype.computeSubMeshes=function(){if(!this.mesh||!this._multimaterialEnabled)return this;var t=this.depthSortedParticles;if(this.particles.length>0)for(var e=0;e<this.particles.length;e++){var n=this.particles[e];n.materialIndex||(n.materialIndex=0);var i=t[e];i.materialIndex=n.materialIndex,i.ind=n._ind,i.indicesLength=n._model._indicesLength,i.idx=n.idx}this._sortParticlesByMaterial();var o=this._indicesByMaterial,a=this._materialIndexes,s=this.mesh;s.subMeshes=[];for(var d=s.getTotalVertices(),p=0;p<a.length;p++){var b=o[p],P=o[p+1]-b,O=a[p];new Eo.a(O,0,d,b,P,s)}return this},r.prototype._sortParticlesByMaterial=function(){var t=[0];this._indicesByMaterial=t;var e=[];this._materialIndexes=e;var n=this.depthSortedParticles;n.sort(this._materialSortFunction);var i=n.length,o=this._indices32,a=this._indices,s=0,d=0,p=0,b=n[0].materialIndex;e.push(b),this._pickable&&(this.pickedBySubMesh=[[]],this.pickedParticles=this.pickedBySubMesh[0]);for(var P=0;P<i;P++){var O=n[P],B=O.indicesLength,F=O.ind;O.materialIndex!==b&&(b=O.materialIndex,t.push(p),e.push(b),this._pickable&&(s++,this.pickedBySubMesh[s]=[],d=0));for(var z=0,J=0;J<B;J++){if(o[p]=a[F+J],this._pickable&&J%3==0){var ie=this.pickedBySubMesh[s][d];ie?(ie.idx=O.idx,ie.faceId=z):this.pickedBySubMesh[s][d]={idx:O.idx,faceId:z},d++,z++}p++}}return t.push(o.length),this._updatable&&this.mesh.updateIndices(o),this},r.prototype._setMaterialIndexesById=function(){this._materialIndexesById={};for(var t=0;t<this._materials.length;t++){var e=this._materials[t].uniqueId;this._materialIndexesById[e]=t}},r.prototype._filterUniqueMaterialId=function(t){return t.filter(function(e,n,i){return i.indexOf(e)===n})},r.prototype._setDefaultMaterial=function(){return this._defaultMaterial||(this._defaultMaterial=new Ft.a(this.name+"DefaultMaterial",this._scene)),this._defaultMaterial},r.prototype.refreshVisibleSize=function(){return this._isVisibilityBoxLocked||this.mesh.refreshBoundingInfo(),this},r.prototype.setVisibilityBox=function(t){var e=t/2;this.mesh._boundingInfo=new Vi.a(new u.e(-e,-e,-e),new u.e(e,e,e))},Object.defineProperty(r.prototype,"isAlwaysVisible",{get:function(){return this._alwaysVisible},set:function(t){this._alwaysVisible=t,this.mesh.alwaysSelectAsActiveMesh=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isVisibilityBoxLocked",{get:function(){return this._isVisibilityBoxLocked},set:function(t){this._isVisibilityBoxLocked=t,this.mesh.getBoundingInfo().isLocked=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"computeParticleRotation",{get:function(){return this._computeParticleRotation},set:function(t){this._computeParticleRotation=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"computeParticleColor",{get:function(){return this._computeParticleColor},set:function(t){this._computeParticleColor=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"computeParticleTexture",{get:function(){return this._computeParticleTexture},set:function(t){this._computeParticleTexture=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"computeParticleVertex",{get:function(){return this._computeParticleVertex},set:function(t){this._computeParticleVertex=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"computeBoundingBox",{get:function(){return this._computeBoundingBox},set:function(t){this._computeBoundingBox=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"depthSortParticles",{get:function(){return this._depthSortParticles},set:function(t){this._depthSortParticles=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"expandable",{get:function(){return this._expandable},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"multimaterialEnabled",{get:function(){return this._multimaterialEnabled},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"useModelMaterial",{get:function(){return this._useModelMaterial},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"materials",{get:function(){return this._materials},enumerable:!1,configurable:!0}),r.prototype.setMultiMaterial=function(t){this._materials=this._filterUniqueMaterialId(t),this._setMaterialIndexesById(),this._multimaterial&&this._multimaterial.dispose(),this._multimaterial=new rr.a(this.name+"MultiMaterial",this._scene);for(var e=0;e<this._materials.length;e++)this._multimaterial.subMaterials.push(this._materials[e]);this.computeSubMeshes(),this.mesh.material=this._multimaterial},Object.defineProperty(r.prototype,"multimaterial",{get:function(){return this._multimaterial},set:function(t){this._multimaterial=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"autoUpdateSubMeshes",{get:function(){return this._autoUpdateSubMeshes},set:function(t){this._autoUpdateSubMeshes=t},enumerable:!1,configurable:!0}),r.prototype.initParticles=function(){},r.prototype.recycleParticle=function(t){return t},r.prototype.updateParticle=function(t){return t},r.prototype.updateParticleVertex=function(t,e,n){return this},r.prototype.beforeUpdateParticles=function(t,e,n){},r.prototype.afterUpdateParticles=function(t,e,n){},r}(),xd=function(){function r(t,e,n,i,o){this.idx=0,this.color=new M.b(1,1,1,1),this.position=u.e.Zero(),this.rotation=u.e.Zero(),this.uv=new u.d(0,0),this.velocity=u.e.Zero(),this.pivot=u.e.Zero(),this.translateFromPivot=!1,this._pos=0,this._ind=0,this.groupId=0,this.idxInGroup=0,this._stillInvisible=!1,this._rotationMatrix=[1,0,0,0,1,0,0,0,1],this.parentId=null,this._globalPosition=u.e.Zero(),this.idx=t,this._group=e,this.groupId=n,this.idxInGroup=i,this._pcs=o}return Object.defineProperty(r.prototype,"size",{get:function(){return this.size},set:function(t){this.size=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"quaternion",{get:function(){return this.rotationQuaternion},set:function(t){this.rotationQuaternion=t},enumerable:!1,configurable:!0}),r.prototype.intersectsMesh=function(t,e){if(!t._boundingInfo)return!1;if(e=e||!1)return t.getBoundingInfo().boundingSphere.intersectsPoint(this.position.add(this._pcs.mesh.position));var n,i,o,a,s,d;n=t.getBoundingInfo().boundingBox.maximumWorld.x,i=t.getBoundingInfo().boundingBox.minimumWorld.x,o=t.getBoundingInfo().boundingBox.maximumWorld.y,a=t.getBoundingInfo().boundingBox.minimumWorld.y,s=t.getBoundingInfo().boundingBox.maximumWorld.z,d=t.getBoundingInfo().boundingBox.minimumWorld.z;var p=this.position.x+this._pcs.mesh.position.x,b=this.position.y+this._pcs.mesh.position.y,P=this.position.z+this._pcs.mesh.position.z;return i<=p&&p<=n&&a<=b&&b<=o&&d<=P&&P<=s},r.prototype.getRotationMatrix=function(t){var e;if(this.rotationQuaternion)e=this.rotationQuaternion;else{e=u.c.Quaternion[0];var n=this.rotation;u.b.RotationYawPitchRollToRef(n.y,n.x,n.z,e)}e.toRotationMatrix(t)},r}(),Sa=function(r,t){this.groupID=r,this._positionFunction=t};(function(r){r[r.Color=2]="Color",r[r.UV=1]="UV",r[r.Random=0]="Random",r[r.Stated=3]="Stated"})(En||(En={}));var zm=function(){function r(t,e,n,i){this.particles=new Array,this.nbParticles=0,this.counter=0,this.vars={},this._promises=[],this._positions=new Array,this._indices=new Array,this._normals=new Array,this._colors=new Array,this._uvs=new Array,this._updatable=!0,this._isVisibilityBoxLocked=!1,this._alwaysVisible=!1,this._groups=new Array,this._groupCounter=0,this._computeParticleColor=!0,this._computeParticleTexture=!0,this._computeParticleRotation=!0,this._computeBoundingBox=!1,this._isReady=!1,this.name=t,this._size=e,this._scene=n||te.a.LastCreatedScene,i&&i.updatable!==void 0?this._updatable=i.updatable:this._updatable=!0}return r.prototype.buildMeshAsync=function(){var t=this;return Promise.all(this._promises).then(function(){return t._isReady=!0,t._buildMesh()})},r.prototype._buildMesh=function(){this.nbParticles===0&&this.addPoints(1),this._positions32=new Float32Array(this._positions),this._uvs32=new Float32Array(this._uvs),this._colors32=new Float32Array(this._colors);var t=new ft.a;t.set(this._positions32,Oe.b.PositionKind),this._uvs32.length>0&&t.set(this._uvs32,Oe.b.UVKind);var e=0;this._colors32.length>0&&(e=1,t.set(this._colors32,Oe.b.ColorKind));var n=new De.a(this.name,this._scene);t.applyToMesh(n,this._updatable),this.mesh=n,this._positions=null,this._uvs=null,this._colors=null,this._updatable||(this.particles.length=0);var i=new Ft.a("point cloud material",this._scene);return i.emissiveColor=new M.a(e,e,e),i.disableLighting=!0,i.pointsCloud=!0,i.pointSize=this._size,n.material=i,new Promise(function(o){return o(n)})},r.prototype._addParticle=function(t,e,n,i){var o=new xd(t,e,n,i,this);return this.particles.push(o),o},r.prototype._randomUnitVector=function(t){t.position=new u.e(Math.random(),Math.random(),Math.random()),t.color=new M.b(1,1,1,1)},r.prototype._getColorIndicesForCoord=function(t,e,n,i){var o=t._groupImageData,a=n*(4*i)+4*e,s=[a,a+1,a+2,a+3],d=s[1],p=s[2],b=s[3],P=o[s[0]],O=o[d],B=o[p],F=o[b];return new M.b(P/255,O/255,B/255,F)},r.prototype._setPointsColorOrUV=function(t,e,n,i,o,a,s){n&&t.updateFacetData();var d=2*t.getBoundingInfo().boundingSphere.radius,p=t.getVerticesData(Oe.b.PositionKind),b=t.getIndices(),P=t.getVerticesData(Oe.b.UVKind),O=t.getVerticesData(Oe.b.ColorKind),B=u.e.Zero();t.computeWorldMatrix();var F=t.getWorldMatrix();if(!F.isIdentity())for(var z=0;z<p.length/3;z++)u.e.TransformCoordinatesFromFloatsToRef(p[3*z],p[3*z+1],p[3*z+2],F,B),p[3*z]=B.x,p[3*z+1]=B.y,p[3*z+2]=B.z;var J,ie,se=0,ce=0,ue=0,fe=0,ve=0,Te=0,Re=0,Ae=0,Ee=0,Se=0,Le=0,Ce=0,Ne=0,Ie=0,Fe=u.e.Zero(),Ye=u.e.Zero(),tt=u.e.Zero(),it=u.e.Zero(),lt=u.e.Zero(),Qe=0,ot=0,rt=0,Ze=0,dt=0,Ve=0,Je=u.d.Zero(),yt=u.d.Zero(),Wt=u.d.Zero(),Nt=u.d.Zero(),Qt=u.d.Zero(),vt=0,Jt=0,Xt=0,zt=0,Yt=0,Et=0,Mt=0,$t=0,Dn=0,Vn=0,$n=0,Ln=0,qt=u.f.Zero(),hi=u.f.Zero(),Ri=u.f.Zero(),Gr=u.f.Zero(),zr=u.f.Zero(),di=0,Hi=0;s=s||0;var jr,jt=new u.f(0,0,0,0),Wi=u.e.Zero(),Sn=u.e.Zero(),lr=u.e.Zero(),Oi=0,ka=u.e.Zero(),Ga=0,Hr=0,Xi=new fn.a(u.e.Zero(),new u.e(1,0,0)),Yi=u.e.Zero();for(ce=0;ce<b.length/3;ce++){var ur,Ki,Wr,Xr,Yr,Qi,qi,Kr;ue=b[3*ce],fe=b[3*ce+1],ve=b[3*ce+2],Te=p[3*ue],Re=p[3*ue+1],Ae=p[3*ue+2],Ee=p[3*fe],Se=p[3*fe+1],Le=p[3*fe+2],Ce=p[3*ve],Ne=p[3*ve+1],Ie=p[3*ve+2],Fe.set(Te,Re,Ae),Ye.set(Ee,Se,Le),tt.set(Ce,Ne,Ie),Ye.subtractToRef(Fe,it),tt.subtractToRef(Ye,lt),P&&(Qe=P[2*ue],ot=P[2*ue+1],rt=P[2*fe],Ze=P[2*fe+1],dt=P[2*ve],Ve=P[2*ve+1],Je.set(Qe,ot),yt.set(rt,Ze),Wt.set(dt,Ve),yt.subtractToRef(Je,Nt),Wt.subtractToRef(yt,Qt)),O&&i&&(vt=O[4*ue],Jt=O[4*ue+1],Xt=O[4*ue+2],zt=O[4*ue+3],Yt=O[4*fe],Et=O[4*fe+1],Mt=O[4*fe+2],$t=O[4*fe+3],Dn=O[4*ve],Vn=O[4*ve+1],$n=O[4*ve+2],Ln=O[4*ve+3],qt.set(vt,Jt,Xt,zt),hi.set(Yt,Et,Mt,$t),Ri.set(Dn,Vn,$n,Ln),hi.subtractToRef(qt,Gr),Ri.subtractToRef(hi,zr));for(var Mi,Nn,Io=new M.a(0,0,0),hr=new M.a(0,0,0),Do=0;Do<e._groupDensity[ce];Do++)se=this.particles.length,this._addParticle(se,e,this._groupCounter,ce+Do),Nn=this.particles[se],di=$.a.RandomRange(0,1),Hi=$.a.RandomRange(0,1),J=Fe.add(it.scale(di)).add(lt.scale(di*Hi)),n&&(Wi=t.getFacetNormal(ce).normalize().scale(-1),Sn=it.clone().normalize(),lr=u.e.Cross(Wi,Sn),Oi=$.a.RandomRange(0,2*Math.PI),ka=Sn.scale(Math.cos(Oi)).add(lr.scale(Math.sin(Oi))),Oi=$.a.RandomRange(.1,Math.PI/2),Yi=ka.scale(Math.cos(Oi)).add(Wi.scale(Math.sin(Oi))),Xi.origin=J.add(Yi.scale(1e-5)),Xi.direction=Yi,Xi.length=d,(jr=Xi.intersectsMesh(t)).hit&&(Hr=jr.pickedPoint.subtract(J).length(),Ga=$.a.RandomRange(0,1)*Hr,J.addInPlace(Yi.scale(Ga)))),Nn.position=J.clone(),this._positions.push(Nn.position.x,Nn.position.y,Nn.position.z),i!==void 0?P&&(ie=Je.add(Nt.scale(di)).add(Qt.scale(di*Hi)),i?o&&e._groupImageData!==null?(ur=e._groupImgWidth,Ki=e._groupImgHeight,Mi=this._getColorIndicesForCoord(e,Math.round(ie.x*ur),Math.round(ie.y*Ki),ur),Nn.color=Mi,this._colors.push(Mi.r,Mi.g,Mi.b,Mi.a)):O?(jt=qt.add(Gr.scale(di)).add(zr.scale(di*Hi)),Nn.color=new M.b(jt.x,jt.y,jt.z,jt.w),this._colors.push(jt.x,jt.y,jt.z,jt.w)):(jt=qt.set(Math.random(),Math.random(),Math.random(),1),Nn.color=new M.b(jt.x,jt.y,jt.z,jt.w),this._colors.push(jt.x,jt.y,jt.z,jt.w)):(Nn.uv=ie.clone(),this._uvs.push(Nn.uv.x,Nn.uv.y))):(a?(Io.set(a.r,a.g,a.b),Wr=$.a.RandomRange(-s,s),Xr=$.a.RandomRange(-s,s),Yr=(Kr=Io.toHSV()).r,(Qi=Kr.g+Wr)<0&&(Qi=0),Qi>1&&(Qi=1),(qi=Kr.b+Xr)<0&&(qi=0),qi>1&&(qi=1),M.a.HSVtoRGBToRef(Yr,Qi,qi,hr),jt.set(hr.r,hr.g,hr.b,1)):jt=qt.set(Math.random(),Math.random(),Math.random(),1),Nn.color=new M.b(jt.x,jt.y,jt.z,jt.w),this._colors.push(jt.x,jt.y,jt.z,jt.w))}},r.prototype._colorFromTexture=function(t,e,n){var i=this;if(t.material===null)return l.a.Warn(t.name+"has no material."),e._groupImageData=null,void this._setPointsColorOrUV(t,e,n,!0,!1);var o=t.material.getActiveTextures();if(o.length===0)return l.a.Warn(t.name+"has no useable texture."),e._groupImageData=null,void this._setPointsColorOrUV(t,e,n,!0,!1);var a=t.clone();a.setEnabled(!1),this._promises.push(new Promise(function(s){zn.a.WhenAllReady(o,function(){var d=e._textureNb;return d<0&&(d=0),d>o.length-1&&(d=o.length-1),e._groupImageData=o[d].readPixels(),e._groupImgWidth=o[d].getSize().width,e._groupImgHeight=o[d].getSize().height,i._setPointsColorOrUV(a,e,n,!0,!0),a.dispose(),s()})}))},r.prototype._calculateDensity=function(t,e,n){for(var i,o,a,s,d,p,b,P,O,B,F,z,J,ie,se,ce,ue,fe=new Array,ve=u.e.Zero(),Te=u.e.Zero(),Re=u.e.Zero(),Ae=u.e.Zero(),Ee=u.e.Zero(),Se=u.e.Zero(),Le=new Array,Ce=0,Ne=n.length/3,Ie=0;Ie<Ne;Ie++)i=n[3*Ie],o=n[3*Ie+1],a=n[3*Ie+2],s=e[3*i],d=e[3*i+1],p=e[3*i+2],b=e[3*o],P=e[3*o+1],O=e[3*o+2],B=e[3*a],F=e[3*a+1],z=e[3*a+2],ve.set(s,d,p),Te.set(b,P,O),Re.set(B,F,z),Te.subtractToRef(ve,Ae),Re.subtractToRef(Te,Ee),Re.subtractToRef(ve,Se),ce=((J=Ae.length())+(ie=Ee.length())+(se=Se.length()))/2,Ce+=ue=Math.sqrt(ce*(ce-J)*(ce-ie)*(ce-se)),Le[Ie]=ue;var Fe=0;for(Ie=0;Ie<Ne;Ie++)fe[Ie]=Math.floor(t*Le[Ie]/Ce),Fe+=fe[Ie];var Ye=t-Fe,tt=Math.floor(Ye/Ne),it=Ye%Ne;for(tt>0&&(fe=fe.map(function(lt){return lt+tt})),Ie=0;Ie<it;Ie++)fe[Ie]+=1;return fe},r.prototype.addPoints=function(t,e){e===void 0&&(e=this._randomUnitVector);for(var n,i=new Sa(this._groupCounter,e),o=this.nbParticles,a=0;a<t;a++)n=this._addParticle(o,i,this._groupCounter,a),i&&i._positionFunction&&i._positionFunction(n,o,a),this._positions.push(n.position.x,n.position.y,n.position.z),n.color&&this._colors.push(n.color.r,n.color.g,n.color.b,n.color.a),n.uv&&this._uvs.push(n.uv.x,n.uv.y),o++;return this.nbParticles+=t,this._groupCounter++,this._groupCounter},r.prototype.addSurfacePoints=function(t,e,n,i,o){var a=n||En.Random;(isNaN(a)||a<0||a>3)&&(a=En.Random);var s=t.getVerticesData(Oe.b.PositionKind),d=t.getIndices();this._groups.push(this._groupCounter);var p=new Sa(this._groupCounter,null);switch(p._groupDensity=this._calculateDensity(e,s,d),a===En.Color?p._textureNb=i||0:i=i||new M.b(1,1,1,1),a){case En.Color:this._colorFromTexture(t,p,!1);break;case En.UV:this._setPointsColorOrUV(t,p,!1,!1,!1);break;case En.Random:this._setPointsColorOrUV(t,p,!1);break;case En.Stated:this._setPointsColorOrUV(t,p,!1,void 0,void 0,i,o)}return this.nbParticles+=e,this._groupCounter++,this._groupCounter-1},r.prototype.addVolumePoints=function(t,e,n,i,o){var a=n||En.Random;(isNaN(a)||a<0||a>3)&&(a=En.Random);var s=t.getVerticesData(Oe.b.PositionKind),d=t.getIndices();this._groups.push(this._groupCounter);var p=new Sa(this._groupCounter,null);switch(p._groupDensity=this._calculateDensity(e,s,d),a===En.Color?p._textureNb=i||0:i=i||new M.b(1,1,1,1),a){case En.Color:this._colorFromTexture(t,p,!0);break;case En.UV:this._setPointsColorOrUV(t,p,!0,!1,!1);break;case En.Random:this._setPointsColorOrUV(t,p,!0);break;case En.Stated:this._setPointsColorOrUV(t,p,!0,void 0,void 0,i,o)}return this.nbParticles+=e,this._groupCounter++,this._groupCounter-1},r.prototype.setParticles=function(t,e,n){if(t===void 0&&(t=0),e===void 0&&(e=this.nbParticles-1),n===void 0&&(n=!0),!this._updatable||!this._isReady)return this;this.beforeUpdateParticles(t,e,n);var i=u.c.Matrix[0],o=this.mesh,a=this._colors32,s=this._positions32,d=this._uvs32,p=u.c.Vector3,b=p[5].copyFromFloats(1,0,0),P=p[6].copyFromFloats(0,1,0),O=p[7].copyFromFloats(0,0,1),B=p[8].setAll(Number.MAX_VALUE),F=p[9].setAll(-Number.MAX_VALUE);u.a.IdentityToRef(i);var z=0;if(this.mesh.isFacetDataEnabled&&(this._computeBoundingBox=!0),e=e>=this.nbParticles?this.nbParticles-1:e,this._computeBoundingBox&&(t!=0||e!=this.nbParticles-1)){var J=this.mesh._boundingInfo;J&&(B.copyFrom(J.minimum),F.copyFrom(J.maximum))}z=0;for(var ie=0,se=0,ce=0,ue=t;ue<=e;ue++){var fe=this.particles[ue];ie=3*(z=fe.idx),se=4*z,ce=2*z,this.updateParticle(fe);var ve=fe._rotationMatrix,Te=fe.position,Re=fe._globalPosition;if(this._computeParticleRotation&&fe.getRotationMatrix(i),fe.parentId!==null){var Ae=this.particles[fe.parentId],Ee=Ae._rotationMatrix,Se=Ae._globalPosition,Le=Te.x*Ee[1]+Te.y*Ee[4]+Te.z*Ee[7],Ce=Te.x*Ee[0]+Te.y*Ee[3]+Te.z*Ee[6],Ne=Te.x*Ee[2]+Te.y*Ee[5]+Te.z*Ee[8];if(Re.x=Se.x+Ce,Re.y=Se.y+Le,Re.z=Se.z+Ne,this._computeParticleRotation){var Ie=i.m;ve[0]=Ie[0]*Ee[0]+Ie[1]*Ee[3]+Ie[2]*Ee[6],ve[1]=Ie[0]*Ee[1]+Ie[1]*Ee[4]+Ie[2]*Ee[7],ve[2]=Ie[0]*Ee[2]+Ie[1]*Ee[5]+Ie[2]*Ee[8],ve[3]=Ie[4]*Ee[0]+Ie[5]*Ee[3]+Ie[6]*Ee[6],ve[4]=Ie[4]*Ee[1]+Ie[5]*Ee[4]+Ie[6]*Ee[7],ve[5]=Ie[4]*Ee[2]+Ie[5]*Ee[5]+Ie[6]*Ee[8],ve[6]=Ie[8]*Ee[0]+Ie[9]*Ee[3]+Ie[10]*Ee[6],ve[7]=Ie[8]*Ee[1]+Ie[9]*Ee[4]+Ie[10]*Ee[7],ve[8]=Ie[8]*Ee[2]+Ie[9]*Ee[5]+Ie[10]*Ee[8]}}else Re.x=0,Re.y=0,Re.z=0,this._computeParticleRotation&&(Ie=i.m,ve[0]=Ie[0],ve[1]=Ie[1],ve[2]=Ie[2],ve[3]=Ie[4],ve[4]=Ie[5],ve[5]=Ie[6],ve[6]=Ie[8],ve[7]=Ie[9],ve[8]=Ie[10]);var Fe=p[11];fe.translateFromPivot?Fe.setAll(0):Fe.copyFrom(fe.pivot);var Ye=p[0];Ye.copyFrom(fe.position);var tt=Ye.x-fe.pivot.x,it=Ye.y-fe.pivot.y,lt=Ye.z-fe.pivot.z,Qe=tt*ve[0]+it*ve[3]+lt*ve[6],ot=tt*ve[1]+it*ve[4]+lt*ve[7],rt=tt*ve[2]+it*ve[5]+lt*ve[8];Qe+=Fe.x,ot+=Fe.y,rt+=Fe.z;var Ze=s[ie]=Re.x+b.x*Qe+P.x*ot+O.x*rt,dt=s[ie+1]=Re.y+b.y*Qe+P.y*ot+O.y*rt,Ve=s[ie+2]=Re.z+b.z*Qe+P.z*ot+O.z*rt;if(this._computeBoundingBox&&(B.minimizeInPlaceFromFloats(Ze,dt,Ve),F.maximizeInPlaceFromFloats(Ze,dt,Ve)),this._computeParticleColor&&fe.color){var Je=fe.color,yt=this._colors32;yt[se]=Je.r,yt[se+1]=Je.g,yt[se+2]=Je.b,yt[se+3]=Je.a}if(this._computeParticleTexture&&fe.uv){var Wt=fe.uv,Nt=this._uvs32;Nt[ce]=Wt.x,Nt[ce+1]=Wt.y}}return n&&(this._computeParticleColor&&o.updateVerticesData(Oe.b.ColorKind,a,!1,!1),this._computeParticleTexture&&o.updateVerticesData(Oe.b.UVKind,d,!1,!1),o.updateVerticesData(Oe.b.PositionKind,s,!1,!1)),this._computeBoundingBox&&(o._boundingInfo?o._boundingInfo.reConstruct(B,F,o._worldMatrix):o._boundingInfo=new Vi.a(B,F,o._worldMatrix)),this.afterUpdateParticles(t,e,n),this},r.prototype.dispose=function(){this.mesh.dispose(),this.vars=null,this._positions=null,this._indices=null,this._normals=null,this._uvs=null,this._colors=null,this._indices32=null,this._positions32=null,this._uvs32=null,this._colors32=null},r.prototype.refreshVisibleSize=function(){return this._isVisibilityBoxLocked||this.mesh.refreshBoundingInfo(),this},r.prototype.setVisibilityBox=function(t){var e=t/2;this.mesh._boundingInfo=new Vi.a(new u.e(-e,-e,-e),new u.e(e,e,e))},Object.defineProperty(r.prototype,"isAlwaysVisible",{get:function(){return this._alwaysVisible},set:function(t){this._alwaysVisible=t,this.mesh.alwaysSelectAsActiveMesh=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"computeParticleRotation",{set:function(t){this._computeParticleRotation=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"computeParticleColor",{get:function(){return this._computeParticleColor},set:function(t){this._computeParticleColor=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"computeParticleTexture",{get:function(){return this._computeParticleTexture},set:function(t){this._computeParticleTexture=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"computeBoundingBox",{get:function(){return this._computeBoundingBox},set:function(t){this._computeBoundingBox=t},enumerable:!1,configurable:!0}),r.prototype.initParticles=function(){},r.prototype.recycleParticle=function(t){return t},r.prototype.updateParticle=function(t){return t},r.prototype.beforeUpdateParticles=function(t,e,n){},r.prototype.afterUpdateParticles=function(t,e,n){},r}();_e.a.prototype.getPhysicsEngine=function(){return this._physicsEngine},_e.a.prototype.enablePhysics=function(r,t){if(r===void 0&&(r=null),this._physicsEngine)return!0;var e=this._getComponent(at.a.NAME_PHYSICSENGINE);e||(e=new Rd(this),this._addComponent(e));try{return this._physicsEngine=new Ir(r,t),this._physicsTimeAccumulator=0,!0}catch(n){return l.a.Error(n.message),!1}},_e.a.prototype.disablePhysicsEngine=function(){this._physicsEngine&&(this._physicsEngine.dispose(),this._physicsEngine=null)},_e.a.prototype.isPhysicsEnabled=function(){return this._physicsEngine!==void 0},_e.a.prototype.deleteCompoundImpostor=function(r){var t=r.parts[0].mesh;t.physicsImpostor&&(t.physicsImpostor.dispose(),t.physicsImpostor=null)},_e.a.prototype._advancePhysicsEngineStep=function(r){if(this._physicsEngine){var t=this._physicsEngine.getSubTimeStep();if(t>0)for(this._physicsTimeAccumulator+=r;this._physicsTimeAccumulator>t;)this.onBeforePhysicsObservable.notifyObservers(this),this._physicsEngine._step(t/1e3),this.onAfterPhysicsObservable.notifyObservers(this),this._physicsTimeAccumulator-=t;else this.onBeforePhysicsObservable.notifyObservers(this),this._physicsEngine._step(r/1e3),this.onAfterPhysicsObservable.notifyObservers(this)}},Object.defineProperty(Dt.a.prototype,"physicsImpostor",{get:function(){return this._physicsImpostor},set:function(r){var t=this;this._physicsImpostor!==r&&(this._disposePhysicsObserver&&this.onDisposeObservable.remove(this._disposePhysicsObserver),this._physicsImpostor=r,r&&(this._disposePhysicsObserver=this.onDisposeObservable.add(function(){t.physicsImpostor&&(t.physicsImpostor.dispose(),t.physicsImpostor=null)})))},enumerable:!0,configurable:!0}),Dt.a.prototype.getPhysicsImpostor=function(){return this.physicsImpostor},Dt.a.prototype.applyImpulse=function(r,t){return this.physicsImpostor?(this.physicsImpostor.applyImpulse(r,t),this):this},Dt.a.prototype.setPhysicsLinkWith=function(r,t,e,n){return this.physicsImpostor&&r.physicsImpostor?(this.physicsImpostor.createJoint(r.physicsImpostor,en.e.HingeJoint,{mainPivot:t,connectedPivot:e,nativeParams:n}),this):this};var Ro,Br,Rd=function(){function r(t){var e=this;this.name=at.a.NAME_PHYSICSENGINE,this.scene=t,this.scene.onBeforePhysicsObservable=new x.c,this.scene.onAfterPhysicsObservable=new x.c,this.scene.getDeterministicFrameTime=function(){return e.scene._physicsEngine?1e3*e.scene._physicsEngine.getTimeStep():1e3/60}}return r.prototype.register=function(){},r.prototype.rebuild=function(){},r.prototype.dispose=function(){this.scene.onBeforePhysicsObservable.clear(),this.scene.onAfterPhysicsObservable.clear(),this.scene._physicsEngine&&this.scene.disablePhysicsEngine()},r}(),jm=function(){function r(t){this._scene=t,this._physicsEngine=this._scene.getPhysicsEngine(),this._physicsEngine||l.a.Warn("Physics engine not enabled. Please enable the physics before you can use the methods.")}return r.prototype.applyRadialExplosionImpulse=function(t,e,n,i){if(!this._physicsEngine)return l.a.Warn("Physics engine not enabled. Please enable the physics before you call this method."),null;var o=this._physicsEngine.getImpostors();if(o.length===0)return null;typeof e=="number"&&((e=new Ur).radius=e,e.strength=n||e.strength,e.falloff=i||e.falloff);var a=new Od(this._scene,e),s=Array();return o.forEach(function(d){var p=a.getImpostorHitData(d,t);p&&(d.applyImpulse(p.force,p.contactPoint),s.push({impostor:d,hitData:p}))}),a.triggerAffectedImpostorsCallback(s),a.dispose(!1),a},r.prototype.applyRadialExplosionForce=function(t,e,n,i){if(!this._physicsEngine)return l.a.Warn("Physics engine not enabled. Please enable the physics before you call the PhysicsHelper."),null;var o=this._physicsEngine.getImpostors();if(o.length===0)return null;typeof e=="number"&&((e=new Ur).radius=e,e.strength=n||e.strength,e.falloff=i||e.falloff);var a=new Od(this._scene,e),s=Array();return o.forEach(function(d){var p=a.getImpostorHitData(d,t);p&&(d.applyForce(p.force,p.contactPoint),s.push({impostor:d,hitData:p}))}),a.triggerAffectedImpostorsCallback(s),a.dispose(!1),a},r.prototype.gravitationalField=function(t,e,n,i){if(!this._physicsEngine)return l.a.Warn("Physics engine not enabled. Please enable the physics before you call the PhysicsHelper."),null;if(this._physicsEngine.getImpostors().length===0)return null;typeof e=="number"&&((e=new Ur).radius=e,e.strength=n||e.strength,e.falloff=i||e.falloff);var o=new Hm(this,this._scene,t,e);return o.dispose(!1),o},r.prototype.updraft=function(t,e,n,i,o){if(!this._physicsEngine)return l.a.Warn("Physics engine not enabled. Please enable the physics before you call the PhysicsHelper."),null;if(this._physicsEngine.getImpostors().length===0)return null;typeof e=="number"&&((e=new Dc).radius=e,e.strength=n||e.strength,e.height=i||e.height,e.updraftMode=o||e.updraftMode);var a=new Wm(this._scene,t,e);return a.dispose(!1),a},r.prototype.vortex=function(t,e,n,i){if(!this._physicsEngine)return l.a.Warn("Physics engine not enabled. Please enable the physics before you call the PhysicsHelper."),null;if(this._physicsEngine.getImpostors().length===0)return null;typeof e=="number"&&((e=new Lc).radius=e,e.strength=n||e.strength,e.height=i||e.height);var o=new Xm(this._scene,t,e);return o.dispose(!1),o},r}(),Od=function(){function r(t,e){this._scene=t,this._options=e,this._dataFetched=!1,this._options=Object(c.a)(Object(c.a)({},new Ur),this._options)}return r.prototype.getData=function(){return this._dataFetched=!0,{sphere:this._sphere}},r.prototype.getImpostorHitData=function(t,e){if(t.mass===0||!this._intersectsWithSphere(t,e,this._options.radius)||t.object.getClassName()!=="Mesh"&&t.object.getClassName()!=="InstancedMesh")return null;var n=t.getObjectCenter().subtract(e),i=new fn.a(e,n,this._options.radius).intersectsMesh(t.object).pickedPoint;if(!i)return null;var o=u.e.Distance(e,i);if(o>this._options.radius)return null;var a=this._options.falloff===Ro.Constant?this._options.strength:this._options.strength*(1-o/this._options.radius);return{force:n.multiplyByFloats(a,a,a),contactPoint:i,distanceFromOrigin:o}},r.prototype.triggerAffectedImpostorsCallback=function(t){this._options.affectedImpostorsCallback&&this._options.affectedImpostorsCallback(t)},r.prototype.dispose=function(t){var e=this;t===void 0&&(t=!0),t?this._sphere.dispose():setTimeout(function(){e._dataFetched||e._sphere.dispose()},0)},r.prototype._prepareSphere=function(){this._sphere||(this._sphere=Fn.a.CreateSphere("radialExplosionEventSphere",this._options.sphere,this._scene),this._sphere.isVisible=!1)},r.prototype._intersectsWithSphere=function(t,e,n){var i=t.object;return this._prepareSphere(),this._sphere.position=e,this._sphere.scaling=new u.e(2*n,2*n,2*n),this._sphere._updateBoundingInfo(),this._sphere.computeWorldMatrix(!0),this._sphere.intersectsMesh(i,!0)},r}(),Hm=function(){function r(t,e,n,i){this._physicsHelper=t,this._scene=e,this._origin=n,this._options=i,this._dataFetched=!1,this._options=Object(c.a)(Object(c.a)({},new Ur),this._options),this._tickCallback=this._tick.bind(this),this._options.strength=-1*this._options.strength}return r.prototype.getData=function(){return this._dataFetched=!0,{sphere:this._sphere}},r.prototype.enable=function(){this._tickCallback.call(this),this._scene.registerBeforeRender(this._tickCallback)},r.prototype.disable=function(){this._scene.unregisterBeforeRender(this._tickCallback)},r.prototype.dispose=function(t){var e=this;t===void 0&&(t=!0),t?this._sphere.dispose():setTimeout(function(){e._dataFetched||e._sphere.dispose()},0)},r.prototype._tick=function(){if(this._sphere)this._physicsHelper.applyRadialExplosionForce(this._origin,this._options);else{var t=this._physicsHelper.applyRadialExplosionForce(this._origin,this._options);t&&(this._sphere=t.getData().sphere.clone("radialExplosionEventSphereClone"))}},r}(),Wm=function(){function r(t,e,n){this._scene=t,this._origin=e,this._options=n,this._originTop=u.e.Zero(),this._originDirection=u.e.Zero(),this._cylinderPosition=u.e.Zero(),this._dataFetched=!1,this._physicsEngine=this._scene.getPhysicsEngine(),this._options=Object(c.a)(Object(c.a)({},new Dc),this._options),this._origin.addToRef(new u.e(0,this._options.height/2,0),this._cylinderPosition),this._origin.addToRef(new u.e(0,this._options.height,0),this._originTop),this._options.updraftMode===Br.Perpendicular&&(this._originDirection=this._origin.subtract(this._originTop).normalize()),this._tickCallback=this._tick.bind(this),this._prepareCylinder()}return r.prototype.getData=function(){return this._dataFetched=!0,{cylinder:this._cylinder}},r.prototype.enable=function(){this._tickCallback.call(this),this._scene.registerBeforeRender(this._tickCallback)},r.prototype.disable=function(){this._scene.unregisterBeforeRender(this._tickCallback)},r.prototype.dispose=function(t){var e=this;t===void 0&&(t=!0),this._cylinder&&(t?this._cylinder.dispose():setTimeout(function(){e._dataFetched||e._cylinder.dispose()},0))},r.prototype.getImpostorHitData=function(t){if(t.mass===0||!this._intersectsWithCylinder(t))return null;var e=t.getObjectCenter();if(this._options.updraftMode===Br.Perpendicular)var n=this._originDirection;else n=e.subtract(this._originTop);var i=u.e.Distance(this._origin,e),o=-1*this._options.strength;return{force:n.multiplyByFloats(o,o,o),contactPoint:e,distanceFromOrigin:i}},r.prototype._tick=function(){var t=this;this._physicsEngine.getImpostors().forEach(function(e){var n=t.getImpostorHitData(e);n&&e.applyForce(n.force,n.contactPoint)})},r.prototype._prepareCylinder=function(){this._cylinder||(this._cylinder=pi.a.CreateCylinder("updraftEventCylinder",{height:this._options.height,diameter:2*this._options.radius},this._scene),this._cylinder.isVisible=!1)},r.prototype._intersectsWithCylinder=function(t){var e=t.object;return this._cylinder.position=this._cylinderPosition,this._cylinder.intersectsMesh(e,!0)},r}(),Xm=function(){function r(t,e,n){this._scene=t,this._origin=e,this._options=n,this._originTop=u.e.Zero(),this._cylinderPosition=u.e.Zero(),this._dataFetched=!1,this._physicsEngine=this._scene.getPhysicsEngine(),this._options=Object(c.a)(Object(c.a)({},new Lc),this._options),this._origin.addToRef(new u.e(0,this._options.height/2,0),this._cylinderPosition),this._origin.addToRef(new u.e(0,this._options.height,0),this._originTop),this._tickCallback=this._tick.bind(this),this._prepareCylinder()}return r.prototype.getData=function(){return this._dataFetched=!0,{cylinder:this._cylinder}},r.prototype.enable=function(){this._tickCallback.call(this),this._scene.registerBeforeRender(this._tickCallback)},r.prototype.disable=function(){this._scene.unregisterBeforeRender(this._tickCallback)},r.prototype.dispose=function(t){var e=this;t===void 0&&(t=!0),t?this._cylinder.dispose():setTimeout(function(){e._dataFetched||e._cylinder.dispose()},0)},r.prototype.getImpostorHitData=function(t){if(t.mass===0||!this._intersectsWithCylinder(t)||t.object.getClassName()!=="Mesh"&&t.object.getClassName()!=="InstancedMesh")return null;var e=t.getObjectCenter(),n=new u.e(this._origin.x,e.y,this._origin.z),i=e.subtract(n),o=new fn.a(n,i,this._options.radius).intersectsMesh(t.object),a=o.pickedPoint;if(!a)return null;var s=o.distance/this._options.radius,d=a.normalize();if(s>this._options.centripetalForceThreshold&&(d=d.negate()),s>this._options.centripetalForceThreshold)var p=d.x*this._options.centripetalForceMultiplier,b=d.y*this._options.updraftForceMultiplier,P=d.z*this._options.centripetalForceMultiplier;else{var O=u.e.Cross(n,e).normalize();p=(O.x+d.x)*this._options.centrifugalForceMultiplier,b=this._originTop.y*this._options.updraftForceMultiplier,P=(O.z+d.z)*this._options.centrifugalForceMultiplier}var B=new u.e(p,b,P);return{force:B=B.multiplyByFloats(this._options.strength,this._options.strength,this._options.strength),contactPoint:e,distanceFromOrigin:s}},r.prototype._tick=function(){var t=this;this._physicsEngine.getImpostors().forEach(function(e){var n=t.getImpostorHitData(e);n&&e.applyForce(n.force,n.contactPoint)})},r.prototype._prepareCylinder=function(){this._cylinder||(this._cylinder=pi.a.CreateCylinder("vortexEventCylinder",{height:this._options.height,diameter:2*this._options.radius},this._scene),this._cylinder.isVisible=!1)},r.prototype._intersectsWithCylinder=function(t){var e=t.object;return this._cylinder.position=this._cylinderPosition,this._cylinder.intersectsMesh(e,!0)},r}(),Ur=function(){this.radius=5,this.strength=10,this.falloff=Ro.Constant,this.sphere={segments:32,diameter:1}},Dc=function(){this.radius=5,this.strength=10,this.height=10,this.updraftMode=Br.Center},Lc=function(){this.radius=5,this.strength=10,this.height=10,this.centripetalForceThreshold=.7,this.centripetalForceMultiplier=5,this.centrifugalForceMultiplier=.5,this.updraftForceMultiplier=.02};(function(r){r[r.Constant=0]="Constant",r[r.Linear=1]="Linear"})(Ro||(Ro={})),function(r){r[r.Center=0]="Center",r[r.Perpendicular=1]="Perpendicular"}(Br||(Br={}));var Ym=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform float degree;
-void main(void)
-{
-vec3 color=texture2D(textureSampler,vUV).rgb;
-float luminance=dot(color,vec3(0.3,0.59,0.11));
-vec3 blackAndWhite=vec3(luminance,luminance,luminance);
-gl_FragColor=vec4(color-((color-blackAndWhite)*degree),1.0);
-}`;ze.a.ShadersStore.blackAndWhitePixelShader=Ym;var Md=function(r){function t(e,n,i,o,a,s){var d=r.call(this,e,"blackAndWhite",["degree"],null,n,i,o,a,s)||this;return d.degree=1,d.onApplyObservable.add(function(p){p.setFloat("degree",d.degree)}),d}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"BlackAndWhitePostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable)},e,i,o)},Object(c.c)([Object(L.c)()],t.prototype,"degree",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.BlackAndWhitePostProcess"]=Md;var Rt=function(){function r(t,e,n,i){this._name=e,this._singleInstance=i||!0,this._getPostProcesses=n,this._cameras={},this._indicesForCamera={},this._postProcesses={}}return Object.defineProperty(r.prototype,"isSupported",{get:function(){for(var t in this._postProcesses)if(this._postProcesses.hasOwnProperty(t)){for(var e=this._postProcesses[t],n=0;n<e.length;n++)if(!e[n].isSupported)return!1}return!0},enumerable:!1,configurable:!0}),r.prototype._update=function(){},r.prototype._attachCameras=function(t){var e,n=this,i=Xe.b.MakeArray(t||this._cameras);if(i)for(var o=0;o<i.length;o++){var a=i[o];if(a){var s=a.name;if(e=this._singleInstance?0:s,!this._postProcesses[e]){var d=this._getPostProcesses();d&&(this._postProcesses[e]=Array.isArray(d)?d:[d])}this._indicesForCamera[s]||(this._indicesForCamera[s]=[]),this._postProcesses[e].forEach(function(p){var b=a.attachPostProcess(p);n._indicesForCamera[s].push(b)}),this._cameras[s]||(this._cameras[s]=a)}}},r.prototype._detachCameras=function(t){var e=Xe.b.MakeArray(t||this._cameras);if(e)for(var n=0;n<e.length;n++){var i=e[n],o=i.name,a=this._postProcesses[this._singleInstance?0:o];a&&a.forEach(function(s){i.detachPostProcess(s)}),this._cameras[o]&&(this._cameras[o]=null)}},r.prototype._enable=function(t){var e=this,n=Xe.b.MakeArray(t||this._cameras);if(n)for(var i=0;i<n.length;i++)for(var o=n[i],a=o.name,s=0;s<this._indicesForCamera[a].length;s++)o._postProcesses[this._indicesForCamera[a][s]]!==void 0&&o._postProcesses[this._indicesForCamera[a][s]]!==null||this._postProcesses[this._singleInstance?0:a].forEach(function(d){n[i].attachPostProcess(d,e._indicesForCamera[a][s])})},r.prototype._disable=function(t){var e=Xe.b.MakeArray(t||this._cameras);if(e)for(var n=0;n<e.length;n++){var i=e[n],o=i.name;this._postProcesses[this._singleInstance?0:o].forEach(function(a){i.detachPostProcess(a)})}},r.prototype.getPostProcesses=function(t){return this._singleInstance?this._postProcesses[0]:t?this._postProcesses[t.name]:null},r}(),Km=`#include<helperFunctions>
-
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform float threshold;
-uniform float exposure;
-void main(void)
-{
-gl_FragColor=texture2D(textureSampler,vUV);
-float luma=getLuminance(gl_FragColor.rgb*exposure);
-gl_FragColor.rgb=step(threshold,luma)*gl_FragColor.rgb;
-}`;ze.a.ShadersStore.extractHighlightsPixelShader=Km;var Nc=function(r){function t(e,n,i,o,a,s,d,p){d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT),p===void 0&&(p=!1);var b=r.call(this,e,"extractHighlights",["threshold","exposure"],null,n,i,o,a,s,null,d,void 0,null,p)||this;return b.threshold=.9,b._exposure=1,b._inputPostProcess=null,b.onApplyObservable.add(function(P){b._inputPostProcess&&P.setTextureFromPostProcess("textureSampler",b._inputPostProcess),P.setFloat("threshold",Math.pow(b.threshold,Gt.b)),P.setFloat("exposure",b._exposure)}),b}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ExtractHighlightsPostProcess"},Object(c.c)([Object(L.c)()],t.prototype,"threshold",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.ExtractHighlightsPostProcess"]=Nc;var Qm=`uniform sampler2D textureSampler;
-uniform sampler2D bloomBlur;
-varying vec2 vUV;
-uniform float bloomWeight;
-void main(void)
-{
-gl_FragColor=texture2D(textureSampler,vUV);
-vec3 blurred=texture2D(bloomBlur,vUV).rgb;
-gl_FragColor.rgb=gl_FragColor.rgb+(blurred.rgb*bloomWeight);
-}
-`;ze.a.ShadersStore.bloomMergePixelShader=Qm;var wc=function(r){function t(e,n,i,o,a,s,d,p,b,P,O){P===void 0&&(P=h.a.TEXTURETYPE_UNSIGNED_INT),O===void 0&&(O=!1);var B=r.call(this,e,"bloomMerge",["bloomWeight"],["circleOfConfusionSampler","blurStep0","blurStep1","blurStep2","bloomBlur"],a,s,d,p,b,null,P,void 0,null,!0)||this;return B.weight=1,B.weight=o,B.onApplyObservable.add(function(F){F.setTextureFromPostProcess("textureSampler",n),F.setTextureFromPostProcessOutput("bloomBlur",i),F.setFloat("bloomWeight",B.weight)}),O||B.updateEffect(),B}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"BloomMergePostProcess"},Object(c.c)([Object(L.c)()],t.prototype,"weight",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.BloomMergePostProcess"]=wc;var Fc=function(r){function t(e,n,i,o,a,s){a===void 0&&(a=0),s===void 0&&(s=!1);var d=r.call(this,e.getEngine(),"bloom",function(){return d._effects},!0)||this;return d.bloomScale=n,d._effects=[],d._downscale=new Nc("highlights",1,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,a,s),d._blurX=new gn("horizontal blur",new u.d(1,0),10,n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,a,void 0,s),d._blurX.alwaysForcePOT=!0,d._blurX.autoClear=!1,d._blurY=new gn("vertical blur",new u.d(0,1),10,n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,a,void 0,s),d._blurY.alwaysForcePOT=!0,d._blurY.autoClear=!1,d.kernel=o,d._effects=[d._downscale,d._blurX,d._blurY],d._merge=new wc("bloomMerge",d._downscale,d._blurY,i,n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,a,s),d._merge.autoClear=!1,d._effects.push(d._merge),d}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"threshold",{get:function(){return this._downscale.threshold},set:function(e){this._downscale.threshold=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"weight",{get:function(){return this._merge.weight},set:function(e){this._merge.weight=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"kernel",{get:function(){return this._blurX.kernel/this.bloomScale},set:function(e){this._blurX.kernel=e*this.bloomScale,this._blurY.kernel=e*this.bloomScale},enumerable:!1,configurable:!0}),t.prototype.disposeEffects=function(e){for(var n=0;n<this._effects.length;n++)this._effects[n].dispose(e)},t.prototype._updateEffects=function(){for(var e=0;e<this._effects.length;e++)this._effects[e].updateEffect()},t.prototype._isReady=function(){for(var e=0;e<this._effects.length;e++)if(!this._effects[e].isReady())return!1;return!0},t}(Rt),qm=`
-uniform sampler2D textureSampler;
-
-uniform float chromatic_aberration;
-uniform float radialIntensity;
-uniform vec2 direction;
-uniform vec2 centerPosition;
-uniform float screen_width;
-uniform float screen_height;
-
-varying vec2 vUV;
-void main(void)
-{
-vec2 centered_screen_pos=vec2(vUV.x-centerPosition.x,vUV.y-centerPosition.y);
-vec2 directionOfEffect=direction;
-if(directionOfEffect.x == 0. && directionOfEffect.y == 0.){
-directionOfEffect=normalize(centered_screen_pos);
-}
-float radius2=centered_screen_pos.x*centered_screen_pos.x
-+centered_screen_pos.y*centered_screen_pos.y;
-float radius=sqrt(radius2);
-vec4 original=texture2D(textureSampler,vUV);
-
-vec3 ref_indices=vec3(-0.3,0.0,0.3);
-float ref_shiftX=chromatic_aberration*pow(radius,radialIntensity)*directionOfEffect.x/screen_width;
-float ref_shiftY=chromatic_aberration*pow(radius,radialIntensity)*directionOfEffect.y/screen_height;
-
-vec2 ref_coords_r=vec2(vUV.x+ref_indices.r*ref_shiftX,vUV.y+ref_indices.r*ref_shiftY*0.5);
-vec2 ref_coords_g=vec2(vUV.x+ref_indices.g*ref_shiftX,vUV.y+ref_indices.g*ref_shiftY*0.5);
-vec2 ref_coords_b=vec2(vUV.x+ref_indices.b*ref_shiftX,vUV.y+ref_indices.b*ref_shiftY*0.5);
-original.r=texture2D(textureSampler,ref_coords_r).r;
-original.g=texture2D(textureSampler,ref_coords_g).g;
-original.b=texture2D(textureSampler,ref_coords_b).b;
-original.a=clamp(texture2D(textureSampler,ref_coords_r).a+texture2D(textureSampler,ref_coords_g).a+texture2D(textureSampler,ref_coords_b).a,0.,1.);
-gl_FragColor=original;
-}`;ze.a.ShadersStore.chromaticAberrationPixelShader=qm;var Bc=function(r){function t(e,n,i,o,a,s,d,p,b,P){b===void 0&&(b=h.a.TEXTURETYPE_UNSIGNED_INT),P===void 0&&(P=!1);var O=r.call(this,e,"chromaticAberration",["chromatic_aberration","screen_width","screen_height","direction","radialIntensity","centerPosition"],[],o,a,s,d,p,null,b,void 0,null,P)||this;return O.aberrationAmount=30,O.radialIntensity=0,O.direction=new u.d(.707,.707),O.centerPosition=new u.d(.5,.5),O.screenWidth=n,O.screenHeight=i,O.onApplyObservable.add(function(B){B.setFloat("chromatic_aberration",O.aberrationAmount),B.setFloat("screen_width",n),B.setFloat("screen_height",i),B.setFloat("radialIntensity",O.radialIntensity),B.setFloat2("direction",O.direction.x,O.direction.y),B.setFloat2("centerPosition",O.centerPosition.x,O.centerPosition.y)}),O}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ChromaticAberrationPostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.screenWidth,e.screenHeight,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable,e.textureType,!1)},e,i,o)},Object(c.c)([Object(L.c)()],t.prototype,"aberrationAmount",void 0),Object(c.c)([Object(L.c)()],t.prototype,"radialIntensity",void 0),Object(c.c)([Object(L.c)()],t.prototype,"direction",void 0),Object(c.c)([Object(L.c)()],t.prototype,"centerPosition",void 0),Object(c.c)([Object(L.c)()],t.prototype,"screenWidth",void 0),Object(c.c)([Object(L.c)()],t.prototype,"screenHeight",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.ChromaticAberrationPostProcess"]=Bc;var Zm=`
-uniform sampler2D depthSampler;
-
-varying vec2 vUV;
-
-uniform vec2 cameraMinMaxZ;
-
-uniform float focusDistance;
-uniform float cocPrecalculation;
-void main(void)
-{
-float depth=texture2D(depthSampler,vUV).r;
-float pixelDistance=(cameraMinMaxZ.x+(cameraMinMaxZ.y-cameraMinMaxZ.x)*depth)*1000.0;
-float coc=abs(cocPrecalculation* ((focusDistance-pixelDistance)/pixelDistance));
-coc=clamp(coc,0.0,1.0);
-gl_FragColor=vec4(coc,depth,coc,1.0);
-}
-`;ze.a.ShadersStore.circleOfConfusionPixelShader=Zm;var Uc=function(r){function t(e,n,i,o,a,s,d,p,b){p===void 0&&(p=h.a.TEXTURETYPE_UNSIGNED_INT),b===void 0&&(b=!1);var P=r.call(this,e,"circleOfConfusion",["cameraMinMaxZ","focusDistance","cocPrecalculation"],["depthSampler"],i,o,a,s,d,null,p,void 0,null,b)||this;return P.lensSize=50,P.fStop=1.4,P.focusDistance=2e3,P.focalLength=50,P._depthTexture=null,P._depthTexture=n,P.onApplyObservable.add(function(O){if(P._depthTexture){O.setTexture("depthSampler",P._depthTexture);var B=P.lensSize/P.fStop*P.focalLength/(P.focusDistance-P.focalLength);O.setFloat("focusDistance",P.focusDistance),O.setFloat("cocPrecalculation",B),O.setFloat2("cameraMinMaxZ",P._depthTexture.activeCamera.minZ,P._depthTexture.activeCamera.maxZ)}else l.a.Warn("No depth texture set on CircleOfConfusionPostProcess")}),P}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"CircleOfConfusionPostProcess"},Object.defineProperty(t.prototype,"depthTexture",{set:function(e){this._depthTexture=e},enumerable:!1,configurable:!0}),Object(c.c)([Object(L.c)()],t.prototype,"lensSize",void 0),Object(c.c)([Object(L.c)()],t.prototype,"fStop",void 0),Object(c.c)([Object(L.c)()],t.prototype,"focusDistance",void 0),Object(c.c)([Object(L.c)()],t.prototype,"focalLength",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.CircleOfConfusionPostProcess"]=Uc;var Jm=`
-uniform sampler2D textureSampler;
-uniform sampler2D colorTable;
-
-varying vec2 vUV;
-
-const float SLICE_COUNT=16.0;
-
-vec4 sampleAs3DTexture(sampler2D textureSampler,vec3 uv,float width) {
-float sliceSize=1.0/width;
-float slicePixelSize=sliceSize/width;
-float sliceInnerSize=slicePixelSize*(width-1.0);
-float zSlice0=min(floor(uv.z*width),width-1.0);
-float zSlice1=min(zSlice0+1.0,width-1.0);
-float xOffset=slicePixelSize*0.5+uv.x*sliceInnerSize;
-float s0=xOffset+(zSlice0*sliceSize);
-float s1=xOffset+(zSlice1*sliceSize);
-vec4 slice0Color=texture2D(textureSampler,vec2(s0,uv.y));
-vec4 slice1Color=texture2D(textureSampler,vec2(s1,uv.y));
-float zOffset=mod(uv.z*width,1.0);
-vec4 result=mix(slice0Color,slice1Color,zOffset);
-return result;
-}
-void main(void)
-{
-vec4 screen_color=texture2D(textureSampler,vUV);
-gl_FragColor=sampleAs3DTexture(colorTable,screen_color.rgb,SLICE_COUNT);
-}`;ze.a.ShadersStore.colorCorrectionPixelShader=Jm;var Id=function(r){function t(e,n,i,o,a,s,d){var p=r.call(this,e,"colorCorrection",null,["colorTable"],i,o,a,s,d)||this;return p._colorTableTexture=new we.a(n,o.getScene(),!0,!1,we.a.TRILINEAR_SAMPLINGMODE),p._colorTableTexture.anisotropicFilteringLevel=1,p._colorTableTexture.wrapU=we.a.CLAMP_ADDRESSMODE,p._colorTableTexture.wrapV=we.a.CLAMP_ADDRESSMODE,p.colorTableUrl=n,p.onApply=function(b){b.setTexture("colorTable",p._colorTableTexture)},p}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ColorCorrectionPostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.colorTableUrl,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable)},e,i,o)},Object(c.c)([Object(L.c)()],t.prototype,"colorTableUrl",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.ColorCorrectionPostProcess"]=Id;var $m=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform vec2 screenSize;
-uniform float kernel[9];
-void main(void)
-{
-vec2 onePixel=vec2(1.0,1.0)/screenSize;
-vec4 colorSum =
-texture2D(textureSampler,vUV+onePixel*vec2(-1,-1))*kernel[0] +
-texture2D(textureSampler,vUV+onePixel*vec2(0,-1))*kernel[1] +
-texture2D(textureSampler,vUV+onePixel*vec2(1,-1))*kernel[2] +
-texture2D(textureSampler,vUV+onePixel*vec2(-1,0))*kernel[3] +
-texture2D(textureSampler,vUV+onePixel*vec2(0,0))*kernel[4] +
-texture2D(textureSampler,vUV+onePixel*vec2(1,0))*kernel[5] +
-texture2D(textureSampler,vUV+onePixel*vec2(-1,1))*kernel[6] +
-texture2D(textureSampler,vUV+onePixel*vec2(0,1))*kernel[7] +
-texture2D(textureSampler,vUV+onePixel*vec2(1,1))*kernel[8];
-float kernelWeight =
-kernel[0] +
-kernel[1] +
-kernel[2] +
-kernel[3] +
-kernel[4] +
-kernel[5] +
-kernel[6] +
-kernel[7] +
-kernel[8];
-if (kernelWeight<=0.0) {
-kernelWeight=1.0;
-}
-gl_FragColor=vec4((colorSum/kernelWeight).rgb,1);
-}`;ze.a.ShadersStore.convolutionPixelShader=$m;var Dd=function(r){function t(e,n,i,o,a,s,d,p){p===void 0&&(p=h.a.TEXTURETYPE_UNSIGNED_INT);var b=r.call(this,e,"convolution",["kernel","screenSize"],null,i,o,a,s,d,null,p)||this;return b.kernel=n,b.onApply=function(P){P.setFloat2("screenSize",b.width,b.height),P.setArray("kernel",b.kernel)},b}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ConvolutionPostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.kernel,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable,e.textureType)},e,i,o)},t.EdgeDetect0Kernel=[1,0,-1,0,0,0,-1,0,1],t.EdgeDetect1Kernel=[0,1,0,1,-4,1,0,1,0],t.EdgeDetect2Kernel=[-1,-1,-1,-1,8,-1,-1,-1,-1],t.SharpenKernel=[0,-1,0,-1,5,-1,0,-1,0],t.EmbossKernel=[-2,-1,0,-1,1,1,0,1,2],t.GaussianKernel=[0,1,0,1,1,1,0,1,0],Object(c.c)([Object(L.c)()],t.prototype,"kernel",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.ConvolutionPostProcess"]=Dd;var Aa=function(r){function t(e,n,i,o,a,s,d,p,b,P,O,B,F){p===void 0&&(p=null),b===void 0&&(b=we.a.BILINEAR_SAMPLINGMODE),B===void 0&&(B=h.a.TEXTURETYPE_UNSIGNED_INT),F===void 0&&(F=!1);var z=r.call(this,e,i,o,a,s,b=h.a.TEXTURE_BILINEAR_SAMPLINGMODE,P,O,B=h.a.TEXTURETYPE_UNSIGNED_INT,`#define DOF 1\r
-`,F)||this;return z.direction=i,z.onApplyObservable.add(function(J){p!=null&&J.setTextureFromPostProcess("textureSampler",p),J.setTextureFromPostProcessOutput("circleOfConfusionSampler",d),n.activeCamera&&J.setFloat2("cameraMinMaxZ",n.activeCamera.minZ,n.activeCamera.maxZ)}),z}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"DepthOfFieldBlurPostProcess"},Object(c.c)([Object(L.c)()],t.prototype,"direction",void 0),t}(gn);R.a.RegisteredTypes["BABYLON.DepthOfFieldBlurPostProcess"]=Aa;var eg=`uniform sampler2D textureSampler;
-varying vec2 vUV;
-uniform sampler2D circleOfConfusionSampler;
-uniform sampler2D blurStep0;
-#if BLUR_LEVEL>0
-uniform sampler2D blurStep1;
-#endif
-#if BLUR_LEVEL>1
-uniform sampler2D blurStep2;
-#endif
-void main(void)
-{
-float coc=texture2D(circleOfConfusionSampler,vUV).r;
-#if BLUR_LEVEL == 0
-vec4 original=texture2D(textureSampler,vUV);
-vec4 blurred0=texture2D(blurStep0,vUV);
-gl_FragColor=mix(original,blurred0,coc);
-#endif
-#if BLUR_LEVEL == 1
-if(coc<0.5){
-vec4 original=texture2D(textureSampler,vUV);
-vec4 blurred1=texture2D(blurStep1,vUV);
-gl_FragColor=mix(original,blurred1,coc/0.5);
-}else{
-vec4 blurred0=texture2D(blurStep0,vUV);
-vec4 blurred1=texture2D(blurStep1,vUV);
-gl_FragColor=mix(blurred1,blurred0,(coc-0.5)/0.5);
-}
-#endif
-#if BLUR_LEVEL == 2
-if(coc<0.33){
-vec4 original=texture2D(textureSampler,vUV);
-vec4 blurred2=texture2D(blurStep2,vUV);
-gl_FragColor=mix(original,blurred2,coc/0.33);
-}else if(coc<0.66){
-vec4 blurred1=texture2D(blurStep1,vUV);
-vec4 blurred2=texture2D(blurStep2,vUV);
-gl_FragColor=mix(blurred2,blurred1,(coc-0.33)/0.33);
-}else{
-vec4 blurred0=texture2D(blurStep0,vUV);
-vec4 blurred1=texture2D(blurStep1,vUV);
-gl_FragColor=mix(blurred1,blurred0,(coc-0.66)/0.34);
-}
-#endif
-}
-`;ze.a.ShadersStore.depthOfFieldMergePixelShader=eg;var sr,tg=function(){},Ld=function(r){function t(e,n,i,o,a,s,d,p,b,P,O){P===void 0&&(P=h.a.TEXTURETYPE_UNSIGNED_INT),O===void 0&&(O=!1);var B=r.call(this,e,"depthOfFieldMerge",[],["circleOfConfusionSampler","blurStep0","blurStep1","blurStep2"],a,s,d,p,b,null,P,void 0,null,!0)||this;return B.blurSteps=o,B.onApplyObservable.add(function(F){F.setTextureFromPostProcess("textureSampler",n),F.setTextureFromPostProcessOutput("circleOfConfusionSampler",i),o.forEach(function(z,J){F.setTextureFromPostProcessOutput("blurStep"+(o.length-J-1),z)})}),O||B.updateEffect(),B}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"DepthOfFieldMergePostProcess"},t.prototype.updateEffect=function(e,n,i,o,a,s){e===void 0&&(e=null),n===void 0&&(n=null),i===void 0&&(i=null),e||(e="",e+="#define BLUR_LEVEL "+(this.blurSteps.length-1)+`
-`),r.prototype.updateEffect.call(this,e,n,i,o,a,s)},t}(_t);(function(r){r[r.Low=0]="Low",r[r.Medium=1]="Medium",r[r.High=2]="High"})(sr||(sr={}));var Vc=function(r){function t(e,n,i,o,a){i===void 0&&(i=sr.Low),o===void 0&&(o=0),a===void 0&&(a=!1);var s=r.call(this,e.getEngine(),"depth of field",function(){return s._effects},!0)||this;s._effects=[],s._circleOfConfusion=new Uc("circleOfConfusion",n,1,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,o,a),s._depthOfFieldBlurY=[],s._depthOfFieldBlurX=[];var d=1,p=15;switch(i){case sr.High:d=3,p=51;break;case sr.Medium:d=2,p=31;break;default:p=15,d=1}for(var b=p/Math.pow(2,d-1),P=1,O=0;O<d;O++){var B=new Aa("verticle blur",e,new u.d(0,1),b,P,null,s._circleOfConfusion,O==0?s._circleOfConfusion:null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,o,a);B.autoClear=!1,P=.75/Math.pow(2,O);var F=new Aa("horizontal blur",e,new u.d(1,0),b,P,null,s._circleOfConfusion,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,o,a);F.autoClear=!1,s._depthOfFieldBlurY.push(B),s._depthOfFieldBlurX.push(F)}for(s._effects=[s._circleOfConfusion],O=0;O<s._depthOfFieldBlurX.length;O++)s._effects.push(s._depthOfFieldBlurY[O]),s._effects.push(s._depthOfFieldBlurX[O]);return s._dofMerge=new Ld("dofMerge",s._circleOfConfusion,s._circleOfConfusion,s._depthOfFieldBlurX,P,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,o,a),s._dofMerge.autoClear=!1,s._effects.push(s._dofMerge),s}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"focalLength",{get:function(){return this._circleOfConfusion.focalLength},set:function(e){this._circleOfConfusion.focalLength=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"fStop",{get:function(){return this._circleOfConfusion.fStop},set:function(e){this._circleOfConfusion.fStop=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"focusDistance",{get:function(){return this._circleOfConfusion.focusDistance},set:function(e){this._circleOfConfusion.focusDistance=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"lensSize",{get:function(){return this._circleOfConfusion.lensSize},set:function(e){this._circleOfConfusion.lensSize=e},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"DepthOfFieldEffect"},Object.defineProperty(t.prototype,"depthTexture",{set:function(e){this._circleOfConfusion.depthTexture=e},enumerable:!1,configurable:!0}),t.prototype.disposeEffects=function(e){for(var n=0;n<this._effects.length;n++)this._effects[n].dispose(e)},t.prototype._updateEffects=function(){for(var e=0;e<this._effects.length;e++)this._effects[e].updateEffect()},t.prototype._isReady=function(){for(var e=0;e<this._effects.length;e++)if(!this._effects[e].isReady())return!1;return!0},t}(Rt),ng=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform sampler2D passSampler;
-void main(void)
-{
-gl_FragColor=texture2D(passSampler,vUV);
-}`;ze.a.ShadersStore.displayPassPixelShader=ng;var Nd=function(r){function t(e,n,i,o,a,s){return r.call(this,e,"displayPass",["passSampler"],["passSampler"],n,i,o,a,s)||this}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"DisplayPassPostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable)},e,i,o)},t}(_t);R.a.RegisteredTypes["BABYLON.DisplayPassPostProcess"]=Nd;var ig=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform mat4 kernelMatrix;
-void main(void)
-{
-vec3 baseColor=texture2D(textureSampler,vUV).rgb;
-vec3 updatedColor=(kernelMatrix*vec4(baseColor,1.0)).rgb;
-gl_FragColor=vec4(updatedColor,1.0);
-}`;ze.a.ShadersStore.filterPixelShader=ig;var wd=function(r){function t(e,n,i,o,a,s,d){var p=r.call(this,e,"filter",["kernelMatrix"],null,i,o,a,s,d)||this;return p.kernelMatrix=n,p.onApply=function(b){b.setMatrix("kernelMatrix",p.kernelMatrix)},p}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"FilterPostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.kernelMatrix,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable)},e,i,o)},Object(c.c)([Object(L.j)()],t.prototype,"kernelMatrix",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.FilterPostProcess"]=wd;var rg=`uniform sampler2D textureSampler;
-uniform vec2 texelSize;
-varying vec2 vUV;
-varying vec2 sampleCoordS;
-varying vec2 sampleCoordE;
-varying vec2 sampleCoordN;
-varying vec2 sampleCoordW;
-varying vec2 sampleCoordNW;
-varying vec2 sampleCoordSE;
-varying vec2 sampleCoordNE;
-varying vec2 sampleCoordSW;
-const float fxaaQualitySubpix=1.0;
-const float fxaaQualityEdgeThreshold=0.166;
-const float fxaaQualityEdgeThresholdMin=0.0833;
-const vec3 kLumaCoefficients=vec3(0.2126,0.7152,0.0722);
-#define FxaaLuma(rgba) dot(rgba.rgb,kLumaCoefficients)
-void main(){
-vec2 posM;
-posM.x=vUV.x;
-posM.y=vUV.y;
-vec4 rgbyM=texture2D(textureSampler,vUV,0.0);
-float lumaM=FxaaLuma(rgbyM);
-float lumaS=FxaaLuma(texture2D(textureSampler,sampleCoordS,0.0));
-float lumaE=FxaaLuma(texture2D(textureSampler,sampleCoordE,0.0));
-float lumaN=FxaaLuma(texture2D(textureSampler,sampleCoordN,0.0));
-float lumaW=FxaaLuma(texture2D(textureSampler,sampleCoordW,0.0));
-float maxSM=max(lumaS,lumaM);
-float minSM=min(lumaS,lumaM);
-float maxESM=max(lumaE,maxSM);
-float minESM=min(lumaE,minSM);
-float maxWN=max(lumaN,lumaW);
-float minWN=min(lumaN,lumaW);
-float rangeMax=max(maxWN,maxESM);
-float rangeMin=min(minWN,minESM);
-float rangeMaxScaled=rangeMax*fxaaQualityEdgeThreshold;
-float range=rangeMax-rangeMin;
-float rangeMaxClamped=max(fxaaQualityEdgeThresholdMin,rangeMaxScaled);
-#ifndef MALI
-if(range<rangeMaxClamped)
-{
-gl_FragColor=rgbyM;
-return;
-}
-#endif
-float lumaNW=FxaaLuma(texture2D(textureSampler,sampleCoordNW,0.0));
-float lumaSE=FxaaLuma(texture2D(textureSampler,sampleCoordSE,0.0));
-float lumaNE=FxaaLuma(texture2D(textureSampler,sampleCoordNE,0.0));
-float lumaSW=FxaaLuma(texture2D(textureSampler,sampleCoordSW,0.0));
-float lumaNS=lumaN+lumaS;
-float lumaWE=lumaW+lumaE;
-float subpixRcpRange=1.0/range;
-float subpixNSWE=lumaNS+lumaWE;
-float edgeHorz1=(-2.0*lumaM)+lumaNS;
-float edgeVert1=(-2.0*lumaM)+lumaWE;
-float lumaNESE=lumaNE+lumaSE;
-float lumaNWNE=lumaNW+lumaNE;
-float edgeHorz2=(-2.0*lumaE)+lumaNESE;
-float edgeVert2=(-2.0*lumaN)+lumaNWNE;
-float lumaNWSW=lumaNW+lumaSW;
-float lumaSWSE=lumaSW+lumaSE;
-float edgeHorz4=(abs(edgeHorz1)*2.0)+abs(edgeHorz2);
-float edgeVert4=(abs(edgeVert1)*2.0)+abs(edgeVert2);
-float edgeHorz3=(-2.0*lumaW)+lumaNWSW;
-float edgeVert3=(-2.0*lumaS)+lumaSWSE;
-float edgeHorz=abs(edgeHorz3)+edgeHorz4;
-float edgeVert=abs(edgeVert3)+edgeVert4;
-float subpixNWSWNESE=lumaNWSW+lumaNESE;
-float lengthSign=texelSize.x;
-bool horzSpan=edgeHorz>=edgeVert;
-float subpixA=subpixNSWE*2.0+subpixNWSWNESE;
-if (!horzSpan)
-{
-lumaN=lumaW;
-}
-if (!horzSpan)
-{
-lumaS=lumaE;
-}
-if (horzSpan)
-{
-lengthSign=texelSize.y;
-}
-float subpixB=(subpixA*(1.0/12.0))-lumaM;
-float gradientN=lumaN-lumaM;
-float gradientS=lumaS-lumaM;
-float lumaNN=lumaN+lumaM;
-float lumaSS=lumaS+lumaM;
-bool pairN=abs(gradientN)>=abs(gradientS);
-float gradient=max(abs(gradientN),abs(gradientS));
-if (pairN)
-{
-lengthSign=-lengthSign;
-}
-float subpixC=clamp(abs(subpixB)*subpixRcpRange,0.0,1.0);
-vec2 posB;
-posB.x=posM.x;
-posB.y=posM.y;
-vec2 offNP;
-offNP.x=(!horzSpan) ? 0.0 : texelSize.x;
-offNP.y=(horzSpan) ? 0.0 : texelSize.y;
-if (!horzSpan)
-{
-posB.x+=lengthSign*0.5;
-}
-if (horzSpan)
-{
-posB.y+=lengthSign*0.5;
-}
-vec2 posN;
-posN.x=posB.x-offNP.x*1.5;
-posN.y=posB.y-offNP.y*1.5;
-vec2 posP;
-posP.x=posB.x+offNP.x*1.5;
-posP.y=posB.y+offNP.y*1.5;
-float subpixD=((-2.0)*subpixC)+3.0;
-float lumaEndN=FxaaLuma(texture2D(textureSampler,posN,0.0));
-float subpixE=subpixC*subpixC;
-float lumaEndP=FxaaLuma(texture2D(textureSampler,posP,0.0));
-if (!pairN)
-{
-lumaNN=lumaSS;
-}
-float gradientScaled=gradient*1.0/4.0;
-float lumaMM=lumaM-lumaNN*0.5;
-float subpixF=subpixD*subpixE;
-bool lumaMLTZero=lumaMM<0.0;
-lumaEndN-=lumaNN*0.5;
-lumaEndP-=lumaNN*0.5;
-bool doneN=abs(lumaEndN)>=gradientScaled;
-bool doneP=abs(lumaEndP)>=gradientScaled;
-if (!doneN)
-{
-posN.x-=offNP.x*3.0;
-}
-if (!doneN)
-{
-posN.y-=offNP.y*3.0;
-}
-bool doneNP=(!doneN) || (!doneP);
-if (!doneP)
-{
-posP.x+=offNP.x*3.0;
-}
-if (!doneP)
-{
-posP.y+=offNP.y*3.0;
-}
-if (doneNP)
-{
-if (!doneN) lumaEndN=FxaaLuma(texture2D(textureSampler,posN.xy,0.0));
-if (!doneP) lumaEndP=FxaaLuma(texture2D(textureSampler,posP.xy,0.0));
-if (!doneN) lumaEndN=lumaEndN-lumaNN*0.5;
-if (!doneP) lumaEndP=lumaEndP-lumaNN*0.5;
-doneN=abs(lumaEndN)>=gradientScaled;
-doneP=abs(lumaEndP)>=gradientScaled;
-if (!doneN) posN.x-=offNP.x*12.0;
-if (!doneN) posN.y-=offNP.y*12.0;
-doneNP=(!doneN) || (!doneP);
-if (!doneP) posP.x+=offNP.x*12.0;
-if (!doneP) posP.y+=offNP.y*12.0;
-}
-float dstN=posM.x-posN.x;
-float dstP=posP.x-posM.x;
-if (!horzSpan)
-{
-dstN=posM.y-posN.y;
-}
-if (!horzSpan)
-{
-dstP=posP.y-posM.y;
-}
-bool goodSpanN=(lumaEndN<0.0) != lumaMLTZero;
-float spanLength=(dstP+dstN);
-bool goodSpanP=(lumaEndP<0.0) != lumaMLTZero;
-float spanLengthRcp=1.0/spanLength;
-bool directionN=dstN<dstP;
-float dst=min(dstN,dstP);
-bool goodSpan=directionN ? goodSpanN : goodSpanP;
-float subpixG=subpixF*subpixF;
-float pixelOffset=(dst*(-spanLengthRcp))+0.5;
-float subpixH=subpixG*fxaaQualitySubpix;
-float pixelOffsetGood=goodSpan ? pixelOffset : 0.0;
-float pixelOffsetSubpix=max(pixelOffsetGood,subpixH);
-if (!horzSpan)
-{
-posM.x+=pixelOffsetSubpix*lengthSign;
-}
-if (horzSpan)
-{
-posM.y+=pixelOffsetSubpix*lengthSign;
-}
-#ifdef MALI
-if(range<rangeMaxClamped)
-{
-gl_FragColor=rgbyM;
-}
-else
-{
-gl_FragColor=texture2D(textureSampler,posM,0.0);
-}
-#else
-gl_FragColor=texture2D(textureSampler,posM,0.0);
-#endif
-}`;ze.a.ShadersStore.fxaaPixelShader=rg;var og=`
-attribute vec2 position;
-uniform vec2 texelSize;
-
-varying vec2 vUV;
-varying vec2 sampleCoordS;
-varying vec2 sampleCoordE;
-varying vec2 sampleCoordN;
-varying vec2 sampleCoordW;
-varying vec2 sampleCoordNW;
-varying vec2 sampleCoordSE;
-varying vec2 sampleCoordNE;
-varying vec2 sampleCoordSW;
-const vec2 madd=vec2(0.5,0.5);
-void main(void) {
-vUV=(position*madd+madd);
-sampleCoordS=vUV+vec2( 0.0,1.0)*texelSize;
-sampleCoordE=vUV+vec2( 1.0,0.0)*texelSize;
-sampleCoordN=vUV+vec2( 0.0,-1.0)*texelSize;
-sampleCoordW=vUV+vec2(-1.0,0.0)*texelSize;
-sampleCoordNW=vUV+vec2(-1.0,-1.0)*texelSize;
-sampleCoordSE=vUV+vec2( 1.0,1.0)*texelSize;
-sampleCoordNE=vUV+vec2( 1.0,-1.0)*texelSize;
-sampleCoordSW=vUV+vec2(-1.0,1.0)*texelSize;
-gl_Position=vec4(position,0.0,1.0);
-}`;ze.a.ShadersStore.fxaaVertexShader=og;var Oo=function(r){function t(e,n,i,o,a,s,d){i===void 0&&(i=null),d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT);var p=r.call(this,e,"fxaa",["texelSize"],null,n,i,o||we.a.BILINEAR_SAMPLINGMODE,a,s,null,d,"fxaa",void 0,!0)||this,b=p._getDefines();return p.updateEffect(b),p.onApplyObservable.add(function(P){var O=p.texelSize;P.setFloat2("texelSize",O.x,O.y)}),p}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"FxaaPostProcess"},t.prototype._getDefines=function(){var e=this.getEngine();if(!e)return null;var n=e.getGlInfo();return n&&n.renderer&&n.renderer.toLowerCase().indexOf("mali")>-1?`#define MALI 1
-`:null},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable)},e,i,o)},t}(_t);R.a.RegisteredTypes["BABYLON.FxaaPostProcess"]=Oo;var ag=`#include<helperFunctions>
-
-uniform sampler2D textureSampler;
-
-uniform float intensity;
-uniform float animatedSeed;
-
-varying vec2 vUV;
-void main(void)
-{
-gl_FragColor=texture2D(textureSampler,vUV);
-vec2 seed=vUV*(animatedSeed);
-float grain=dither(seed,intensity);
-
-float lum=getLuminance(gl_FragColor.rgb);
-float grainAmount=(cos(-PI+(lum*PI*2.))+1.)/2.;
-gl_FragColor.rgb+=grain*grainAmount;
-gl_FragColor.rgb=max(gl_FragColor.rgb,0.0);
-}`;ze.a.ShadersStore.grainPixelShader=ag;var kc=function(r){function t(e,n,i,o,a,s,d,p){d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT),p===void 0&&(p=!1);var b=r.call(this,e,"grain",["intensity","animatedSeed"],[],n,i,o,a,s,null,d,void 0,null,p)||this;return b.intensity=30,b.animated=!1,b.onApplyObservable.add(function(P){P.setFloat("intensity",b.intensity),P.setFloat("animatedSeed",b.animated?Math.random()+1:1)}),b}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"GrainPostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable)},e,i,o)},Object(c.c)([Object(L.c)()],t.prototype,"intensity",void 0),Object(c.c)([Object(L.c)()],t.prototype,"animated",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.GrainPostProcess"]=kc;var sg=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-const vec3 RGBLuminanceCoefficients=vec3(0.2126,0.7152,0.0722);
-void main(void)
-{
-vec4 tex=texture2D(textureSampler,vUV);
-vec3 c=tex.rgb;
-float luma=dot(c.rgb,RGBLuminanceCoefficients);
-
-
-gl_FragColor=vec4(pow(c,vec3(25.0-luma*15.0)),tex.a);
-}`;ze.a.ShadersStore.highlightsPixelShader=sg;var cg=function(r){function t(e,n,i,o,a,s,d){return d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT),r.call(this,e,"highlights",null,null,n,i,o,a,s,null,d)||this}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"HighlightsPostProcess"},t}(_t);ze.a.IncludesShadersStore.mrtFragmentDeclaration=`#if __VERSION__>=200
-layout(location=0) out vec4 glFragData[{X}];
-#endif
-`;var lg=`#extension GL_EXT_draw_buffers : require
-#if defined(BUMP) || !defined(NORMAL)
-#extension GL_OES_standard_derivatives : enable
-#endif
-precision highp float;
-precision highp int;
-#ifdef BUMP
-varying mat4 vWorldView;
-varying vec3 vNormalW;
-#else
-varying vec3 vNormalV;
-#endif
-varying vec4 vViewPos;
-#if defined(POSITION) || defined(BUMP)
-varying vec3 vPositionW;
-#endif
-#ifdef VELOCITY
-varying vec4 vCurrentPosition;
-varying vec4 vPreviousPosition;
-#endif
-#ifdef NEED_UV
-varying vec2 vUV;
-#endif
-#ifdef BUMP
-uniform vec3 vBumpInfos;
-uniform vec2 vTangentSpaceParams;
-#endif
-#ifdef REFLECTIVITY
-varying vec2 vReflectivityUV;
-uniform sampler2D reflectivitySampler;
-#endif
-#ifdef ALPHATEST
-uniform sampler2D diffuseSampler;
-#endif
-#include<mrtFragmentDeclaration>[RENDER_TARGET_COUNT]
-#include<bumpFragmentMainFunctions>
-#include<bumpFragmentFunctions>
-void main() {
-#ifdef ALPHATEST
-if (texture2D(diffuseSampler,vUV).a<0.4)
-discard;
-#endif
-vec3 normalOutput;
-#ifdef BUMP
-vec3 normalW=normalize(vNormalW);
-#include<bumpFragment>
-normalOutput=normalize(vec3(vWorldView*vec4(normalW,0.0)));
-#else
-normalOutput=normalize(vNormalV);
-#endif
-#ifdef PREPASS
-#ifdef PREPASS_DEPTHNORMAL
-gl_FragData[DEPTHNORMAL_INDEX]=vec4(vViewPos.z/vViewPos.w,normalOutput);
-#endif
-#else
-gl_FragData[0]=vec4(vViewPos.z/vViewPos.w,0.0,0.0,1.0);
-gl_FragData[1]=vec4(normalOutput,1.0);
-#endif
-#ifdef POSITION
-gl_FragData[POSITION_INDEX]=vec4(vPositionW,1.0);
-#endif
-#ifdef VELOCITY
-vec2 a=(vCurrentPosition.xy/vCurrentPosition.w)*0.5+0.5;
-vec2 b=(vPreviousPosition.xy/vPreviousPosition.w)*0.5+0.5;
-vec2 velocity=abs(a-b);
-velocity=vec2(pow(velocity.x,1.0/3.0),pow(velocity.y,1.0/3.0))*sign(a-b)*0.5+0.5;
-gl_FragData[VELOCITY_INDEX]=vec4(velocity,0.0,1.0);
-#endif
-#ifdef REFLECTIVITY
-#ifdef HAS_SPECULAR
-
-vec4 reflectivity=texture2D(reflectivitySampler,vReflectivityUV);
-#elif HAS_REFLECTIVITY
-
-vec4 reflectivity=vec4(texture2D(reflectivitySampler,vReflectivityUV).rgb,1.0);
-#else
-vec4 reflectivity=vec4(0.0,0.0,0.0,1.0);
-#endif
-gl_FragData[REFLECTIVITY_INDEX]=reflectivity;
-#endif
-}`;ze.a.ShadersStore.geometryPixelShader=lg;var ug=`precision highp float;
-precision highp int;
-#include<bonesDeclaration>
-#include<morphTargetsVertexGlobalDeclaration>
-#include<morphTargetsVertexDeclaration>[0..maxSimultaneousMorphTargets]
-#include<instancesDeclaration>
-attribute vec3 position;
-attribute vec3 normal;
-#ifdef NEED_UV
-varying vec2 vUV;
-#ifdef ALPHATEST
-uniform mat4 diffuseMatrix;
-#endif
-#ifdef BUMP
-uniform mat4 bumpMatrix;
-varying vec2 vBumpUV;
-#endif
-#ifdef REFLECTIVITY
-uniform mat4 reflectivityMatrix;
-varying vec2 vReflectivityUV;
-#endif
-#ifdef UV1
-attribute vec2 uv;
-#endif
-#ifdef UV2
-attribute vec2 uv2;
-#endif
-#endif
-
-uniform mat4 viewProjection;
-uniform mat4 view;
-#ifdef BUMP
-varying mat4 vWorldView;
-#endif
-#ifdef BUMP
-varying vec3 vNormalW;
-#else
-varying vec3 vNormalV;
-#endif
-varying vec4 vViewPos;
-#if defined(POSITION) || defined(BUMP)
-varying vec3 vPositionW;
-#endif
-#ifdef VELOCITY
-uniform mat4 previousWorld;
-uniform mat4 previousViewProjection;
-#ifdef BONES_VELOCITY_ENABLED
-#if NUM_BONE_INFLUENCERS>0
-uniform mat4 mPreviousBones[BonesPerMesh];
-#endif
-#endif
-varying vec4 vCurrentPosition;
-varying vec4 vPreviousPosition;
-#endif
-void main(void)
-{
-vec3 positionUpdated=position;
-vec3 normalUpdated=normal;
-#ifdef UV1
-vec2 uvUpdated=uv;
-#endif
-#include<morphTargetsVertex>[0..maxSimultaneousMorphTargets]
-#include<instancesVertex>
-#if defined(VELOCITY) && !defined(BONES_VELOCITY_ENABLED)
-
-vCurrentPosition=viewProjection*finalWorld*vec4(positionUpdated,1.0);
-vPreviousPosition=previousViewProjection*previousWorld*vec4(positionUpdated,1.0);
-#endif
-#include<bonesVertex>
-vec4 pos=vec4(finalWorld*vec4(positionUpdated,1.0));
-#ifdef BUMP
-vWorldView=view*finalWorld;
-vNormalW=normalUpdated;
-#else
-vNormalV=normalize(vec3((view*finalWorld)*vec4(normalUpdated,0.0)));
-#endif
-vViewPos=view*pos;
-#if defined(VELOCITY) && defined(BONES_VELOCITY_ENABLED)
-vCurrentPosition=viewProjection*finalWorld*vec4(positionUpdated,1.0);
-#if NUM_BONE_INFLUENCERS>0
-mat4 previousInfluence;
-previousInfluence=mPreviousBones[int(matricesIndices[0])]*matricesWeights[0];
-#if NUM_BONE_INFLUENCERS>1
-previousInfluence+=mPreviousBones[int(matricesIndices[1])]*matricesWeights[1];
-#endif
-#if NUM_BONE_INFLUENCERS>2
-previousInfluence+=mPreviousBones[int(matricesIndices[2])]*matricesWeights[2];
-#endif
-#if NUM_BONE_INFLUENCERS>3
-previousInfluence+=mPreviousBones[int(matricesIndices[3])]*matricesWeights[3];
-#endif
-#if NUM_BONE_INFLUENCERS>4
-previousInfluence+=mPreviousBones[int(matricesIndicesExtra[0])]*matricesWeightsExtra[0];
-#endif
-#if NUM_BONE_INFLUENCERS>5
-previousInfluence+=mPreviousBones[int(matricesIndicesExtra[1])]*matricesWeightsExtra[1];
-#endif
-#if NUM_BONE_INFLUENCERS>6
-previousInfluence+=mPreviousBones[int(matricesIndicesExtra[2])]*matricesWeightsExtra[2];
-#endif
-#if NUM_BONE_INFLUENCERS>7
-previousInfluence+=mPreviousBones[int(matricesIndicesExtra[3])]*matricesWeightsExtra[3];
-#endif
-vPreviousPosition=previousViewProjection*previousWorld*previousInfluence*vec4(positionUpdated,1.0);
-#else
-vPreviousPosition=previousViewProjection*previousWorld*vec4(positionUpdated,1.0);
-#endif
-#endif
-#if defined(POSITION) || defined(BUMP)
-vPositionW=pos.xyz/pos.w;
-#endif
-gl_Position=viewProjection*finalWorld*vec4(positionUpdated,1.0);
-#ifdef NEED_UV
-#ifdef UV1
-#ifdef ALPHATEST
-vUV=vec2(diffuseMatrix*vec4(uvUpdated,1.0,0.0));
-#else
-vUV=uv;
-#endif
-#ifdef BUMP
-vBumpUV=vec2(bumpMatrix*vec4(uvUpdated,1.0,0.0));
-#endif
-#ifdef REFLECTIVITY
-vReflectivityUV=vec2(reflectivityMatrix*vec4(uvUpdated,1.0,0.0));
-#endif
-#endif
-#ifdef UV2
-#ifdef ALPHATEST
-vUV=vec2(diffuseMatrix*vec4(uv2,1.0,0.0));
-#else
-vUV=uv2;
-#endif
-#ifdef BUMP
-vBumpUV=vec2(bumpMatrix*vec4(uv2,1.0,0.0));
-#endif
-#ifdef REFLECTIVITY
-vReflectivityUV=vec2(reflectivityMatrix*vec4(uv2,1.0,0.0));
-#endif
-#endif
-#endif
-#include<bumpVertex>
-}
-`;ze.a.ShadersStore.geometryVertexShader=ug;var ui=function(){function r(t,e){e===void 0&&(e=1),this._previousTransformationMatrices={},this._previousBonesTransformationMatrices={},this.excludedSkinnedMeshesFromVelocity=[],this.renderTransparentMeshes=!0,this._resizeObserver=null,this._enablePosition=!1,this._enableVelocity=!1,this._enableReflectivity=!1,this._positionIndex=-1,this._velocityIndex=-1,this._reflectivityIndex=-1,this._depthNormalIndex=-1,this._linkedWithPrePass=!1,this._scene=t,this._ratio=e,r._SceneComponentInitialization(this._scene),this._createRenderTargets()}return r.prototype._linkPrePassRenderer=function(t){this._linkedWithPrePass=!0,this._prePassRenderer=t,this._multiRenderTarget&&(this._multiRenderTarget.onClearObservable.clear(),this._multiRenderTarget.onClearObservable.add(function(e){}))},r.prototype._unlinkPrePassRenderer=function(){this._linkedWithPrePass=!1,this._createRenderTargets()},r.prototype._resetLayout=function(){this._enablePosition=!1,this._enableReflectivity=!1,this._enableVelocity=!1,this._attachments=[]},r.prototype._forceTextureType=function(t,e){t===r.POSITION_TEXTURE_TYPE?(this._positionIndex=e,this._enablePosition=!0):t===r.VELOCITY_TEXTURE_TYPE?(this._velocityIndex=e,this._enableVelocity=!0):t===r.REFLECTIVITY_TEXTURE_TYPE?(this._reflectivityIndex=e,this._enableReflectivity=!0):t===r.DEPTHNORMAL_TEXTURE_TYPE&&(this._depthNormalIndex=e)},r.prototype._setAttachments=function(t){this._attachments=t},r.prototype._linkInternalTexture=function(t){this._multiRenderTarget._texture=t},Object.defineProperty(r.prototype,"renderList",{get:function(){return this._multiRenderTarget.renderList},set:function(t){this._multiRenderTarget.renderList=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isSupported",{get:function(){return this._multiRenderTarget.isSupported},enumerable:!1,configurable:!0}),r.prototype.getTextureIndex=function(t){switch(t){case r.POSITION_TEXTURE_TYPE:return this._positionIndex;case r.VELOCITY_TEXTURE_TYPE:return this._velocityIndex;case r.REFLECTIVITY_TEXTURE_TYPE:return this._reflectivityIndex;default:return-1}},Object.defineProperty(r.prototype,"enablePosition",{get:function(){return this._enablePosition},set:function(t){this._enablePosition=t,this._linkedWithPrePass||(this.dispose(),this._createRenderTargets())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"enableVelocity",{get:function(){return this._enableVelocity},set:function(t){this._enableVelocity=t,t||(this._previousTransformationMatrices={}),this._linkedWithPrePass||(this.dispose(),this._createRenderTargets())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"enableReflectivity",{get:function(){return this._enableReflectivity},set:function(t){this._enableReflectivity=t,this._linkedWithPrePass||(this.dispose(),this._createRenderTargets())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"scene",{get:function(){return this._scene},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"ratio",{get:function(){return this._ratio},enumerable:!1,configurable:!0}),r.prototype.isReady=function(t,e){var n=t.getMaterial();if(n&&n.disableDepthWrite)return!1;var i=[],o=[Oe.b.PositionKind,Oe.b.NormalKind],a=t.getMesh();if(n){var s=!1;n.needAlphaTesting()&&(i.push("#define ALPHATEST"),s=!0),n.bumpTexture&&Ft.a.BumpTextureEnabled&&(i.push("#define BUMP"),i.push("#define BUMPDIRECTUV 0"),s=!0),this._enableReflectivity&&(n instanceof Ft.a&&n.specularTexture?(i.push("#define HAS_SPECULAR"),s=!0):n instanceof uo&&n.reflectivityTexture&&(i.push("#define HAS_REFLECTIVITY"),s=!0)),s&&(i.push("#define NEED_UV"),a.isVerticesDataPresent(Oe.b.UVKind)&&(o.push(Oe.b.UVKind),i.push("#define UV1")),a.isVerticesDataPresent(Oe.b.UV2Kind)&&(o.push(Oe.b.UV2Kind),i.push("#define UV2")))}this._linkedWithPrePass&&(i.push("#define PREPASS"),this._depthNormalIndex!==-1&&(i.push("#define DEPTHNORMAL_INDEX "+this._depthNormalIndex),i.push("#define PREPASS_DEPTHNORMAL"))),this._enablePosition&&(i.push("#define POSITION"),i.push("#define POSITION_INDEX "+this._positionIndex)),this._enableVelocity&&(i.push("#define VELOCITY"),i.push("#define VELOCITY_INDEX "+this._velocityIndex),this.excludedSkinnedMeshesFromVelocity.indexOf(a)===-1&&i.push("#define BONES_VELOCITY_ENABLED")),this._enableReflectivity&&(i.push("#define REFLECTIVITY"),i.push("#define REFLECTIVITY_INDEX "+this._reflectivityIndex)),a.useBones&&a.computeBonesUsingShaders?(o.push(Oe.b.MatricesIndicesKind),o.push(Oe.b.MatricesWeightsKind),a.numBoneInfluencers>4&&(o.push(Oe.b.MatricesIndicesExtraKind),o.push(Oe.b.MatricesWeightsExtraKind)),i.push("#define NUM_BONE_INFLUENCERS "+a.numBoneInfluencers),i.push("#define BonesPerMesh "+(a.skeleton?a.skeleton.bones.length+1:0))):i.push("#define NUM_BONE_INFLUENCERS 0");var d=a.morphTargetManager,p=0;d&&d.numInfluencers>0&&(p=d.numInfluencers,i.push("#define MORPHTARGETS"),i.push("#define NUM_MORPH_INFLUENCERS "+p),et.a.PrepareAttributesForMorphTargetsInfluencers(o,a,p)),e&&(i.push("#define INSTANCES"),et.a.PushAttributesForInstances(o),t.getRenderingMesh().hasThinInstances&&i.push("#define THIN_INSTANCES")),this._linkedWithPrePass?i.push("#define RENDER_TARGET_COUNT "+this._attachments.length):i.push("#define RENDER_TARGET_COUNT "+this._multiRenderTarget.textures.length);var b=i.join(`
-`);return this._cachedDefines!==b&&(this._cachedDefines=b,this._effect=this._scene.getEngine().createEffect("geometry",o,["world","mBones","viewProjection","diffuseMatrix","view","previousWorld","previousViewProjection","mPreviousBones","morphTargetInfluences","bumpMatrix","reflectivityMatrix","vTangentSpaceParams","vBumpInfos"],["diffuseSampler","bumpSampler","reflectivitySampler"],b,void 0,void 0,void 0,{buffersCount:this._multiRenderTarget.textures.length-1,maxSimultaneousMorphTargets:p})),this._effect.isReady()},r.prototype.getGBuffer=function(){return this._multiRenderTarget},Object.defineProperty(r.prototype,"samples",{get:function(){return this._multiRenderTarget.samples},set:function(t){this._multiRenderTarget.samples=t},enumerable:!1,configurable:!0}),r.prototype.dispose=function(){this._resizeObserver&&(this._scene.getEngine().onResizeObservable.remove(this._resizeObserver),this._resizeObserver=null),this.getGBuffer().dispose()},r.prototype._assignRenderTargetIndices=function(){var t=2;return this._enablePosition&&(this._positionIndex=t,t++),this._enableVelocity&&(this._velocityIndex=t,t++),this._enableReflectivity&&(this._reflectivityIndex=t,t++),t},r.prototype._createRenderTargets=function(){var t=this,e=this._scene.getEngine(),n=this._assignRenderTargetIndices();if(this._multiRenderTarget=new qs("gBuffer",{width:e.getRenderWidth()*this._ratio,height:e.getRenderHeight()*this._ratio},n,this._scene,{generateMipMaps:!1,generateDepthTexture:!0,defaultType:h.a.TEXTURETYPE_FLOAT}),this.isSupported){this._multiRenderTarget.wrapU=we.a.CLAMP_ADDRESSMODE,this._multiRenderTarget.wrapV=we.a.CLAMP_ADDRESSMODE,this._multiRenderTarget.refreshRate=1,this._multiRenderTarget.renderParticles=!1,this._multiRenderTarget.renderList=null,this._multiRenderTarget.onClearObservable.add(function(o){o.clear(new M.b(0,0,0,1),!0,!0,!0)}),this._resizeObserver=e.onResizeObservable.add(function(){t._multiRenderTarget&&t._multiRenderTarget.resize({width:e.getRenderWidth()*t._ratio,height:e.getRenderHeight()*t._ratio})});var i=function(o){var a=o.getRenderingMesh(),s=o.getEffectiveMesh(),d=t._scene,p=d.getEngine(),b=o.getMaterial();if(b){if(s._internalAbstractMeshDataInfo._isActiveIntermediate=!1,t._enableVelocity&&!t._previousTransformationMatrices[s.uniqueId]&&(t._previousTransformationMatrices[s.uniqueId]={world:u.a.Identity(),viewProjection:d.getTransformMatrix()},a.skeleton)){var P=a.skeleton.getTransformMatrices(a);t._previousBonesTransformationMatrices[a.uniqueId]=t._copyBonesTransformationMatrices(P,new Float32Array(P.length))}var O=a._getInstancesRenderList(o._id,!!o.getReplacementMesh());if(!O.mustReturn){var B=p.getCaps().instancedArrays&&(O.visibleInstances[o._id]!==null||a.hasThinInstances),F=s.getWorldMatrix();if(t.isReady(o,B)){if(p.enableEffect(t._effect),a._bind(o,t._effect,b.fillMode),t._effect.setMatrix("viewProjection",d.getTransformMatrix()),t._effect.setMatrix("view",d.getViewMatrix()),b){var z,J=s._instanceDataStorage;if(J.isFrozen||!b.backFaceCulling&&b.overrideMaterialSideOrientation===null)z=J.sideOrientation;else{var ie=s._getWorldMatrixDeterminant();(z=b.overrideMaterialSideOrientation)==null&&(z=b.sideOrientation),ie<0&&(z=z===Ht.a.ClockWiseSideOrientation?Ht.a.CounterClockWiseSideOrientation:Ht.a.ClockWiseSideOrientation)}if(b._preBind(t._effect,z),b.needAlphaTesting()){var se=b.getAlphaTestTexture();se&&(t._effect.setTexture("diffuseSampler",se),t._effect.setMatrix("diffuseMatrix",se.getTextureMatrix()))}b.bumpTexture&&d.getEngine().getCaps().standardDerivatives&&Ft.a.BumpTextureEnabled&&(t._effect.setFloat3("vBumpInfos",b.bumpTexture.coordinatesIndex,1/b.bumpTexture.level,b.parallaxScaleBias),t._effect.setMatrix("bumpMatrix",b.bumpTexture.getTextureMatrix()),t._effect.setTexture("bumpSampler",b.bumpTexture),t._effect.setFloat2("vTangentSpaceParams",b.invertNormalMapX?-1:1,b.invertNormalMapY?-1:1)),t._enableReflectivity&&(b instanceof Ft.a&&b.specularTexture?(t._effect.setMatrix("reflectivityMatrix",b.specularTexture.getTextureMatrix()),t._effect.setTexture("reflectivitySampler",b.specularTexture)):b instanceof uo&&b.reflectivityTexture&&(t._effect.setMatrix("reflectivityMatrix",b.reflectivityTexture.getTextureMatrix()),t._effect.setTexture("reflectivitySampler",b.reflectivityTexture)))}a.useBones&&a.computeBonesUsingShaders&&a.skeleton&&(t._effect.setMatrices("mBones",a.skeleton.getTransformMatrices(a)),t._enableVelocity&&t._effect.setMatrices("mPreviousBones",t._previousBonesTransformationMatrices[a.uniqueId])),et.a.BindMorphTargetParameters(a,t._effect),t._enableVelocity&&(t._effect.setMatrix("previousWorld",t._previousTransformationMatrices[s.uniqueId].world),t._effect.setMatrix("previousViewProjection",t._previousTransformationMatrices[s.uniqueId].viewProjection)),a._processRendering(s,o,t._effect,b.fillMode,O,B,function(ce,ue){return t._effect.setMatrix("world",ue)})}t._enableVelocity&&(t._previousTransformationMatrices[s.uniqueId].world=F.clone(),t._previousTransformationMatrices[s.uniqueId].viewProjection=t._scene.getTransformMatrix().clone(),a.skeleton&&t._copyBonesTransformationMatrices(a.skeleton.getTransformMatrices(a),t._previousBonesTransformationMatrices[s.uniqueId]))}}};this._multiRenderTarget.customRenderFunction=function(o,a,s,d){var p;if(t._linkedWithPrePass){if(!t._prePassRenderer.enabled)return;t._scene.getEngine().bindAttachments(t._attachments)}if(d.length){for(e.setColorWrite(!1),p=0;p<d.length;p++)i(d.data[p]);e.setColorWrite(!0)}for(p=0;p<o.length;p++)i(o.data[p]);for(p=0;p<a.length;p++)i(a.data[p]);if(t.renderTransparentMeshes)for(p=0;p<s.length;p++)i(s.data[p])}}},r.prototype._copyBonesTransformationMatrices=function(t,e){for(var n=0;n<t.length;n++)e[n]=t[n];return e},r.DEPTHNORMAL_TEXTURE_TYPE=0,r.POSITION_TEXTURE_TYPE=1,r.VELOCITY_TEXTURE_TYPE=2,r.REFLECTIVITY_TEXTURE_TYPE=3,r._SceneComponentInitialization=function(t){throw An.a.WarnImport("GeometryBufferRendererSceneComponent")},r}(),hg=function(){this.enabled=!1,this.name="motionBlur",this.texturesRequired=[h.a.PREPASS_VELOCITY_TEXTURE_TYPE]};Object.defineProperty(_e.a.prototype,"geometryBufferRenderer",{get:function(){this._geometryBufferRenderer},set:function(r){r&&r.isSupported&&(this._geometryBufferRenderer=r)},enumerable:!0,configurable:!0}),_e.a.prototype.enableGeometryBufferRenderer=function(r){return r===void 0&&(r=1),this._geometryBufferRenderer||(this._geometryBufferRenderer=new ui(this,r),this._geometryBufferRenderer.isSupported||(this._geometryBufferRenderer=null)),this._geometryBufferRenderer},_e.a.prototype.disableGeometryBufferRenderer=function(){this._geometryBufferRenderer&&(this._geometryBufferRenderer.dispose(),this._geometryBufferRenderer=null)};var Fd=function(){function r(t){this.name=at.a.NAME_GEOMETRYBUFFERRENDERER,this.scene=t}return r.prototype.register=function(){this.scene._gatherRenderTargetsStage.registerStep(at.a.STEP_GATHERRENDERTARGETS_GEOMETRYBUFFERRENDERER,this,this._gatherRenderTargets)},r.prototype.rebuild=function(){},r.prototype.dispose=function(){},r.prototype._gatherRenderTargets=function(t){this.scene._geometryBufferRenderer&&t.push(this.scene._geometryBufferRenderer.getGBuffer())},r}();ui._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_GEOMETRYBUFFERRENDERER);t||(t=new Fd(r),r._addComponent(t))};var dg=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform float motionStrength;
-uniform float motionScale;
-uniform vec2 screenSize;
-#ifdef OBJECT_BASED
-uniform sampler2D velocitySampler;
-#else
-uniform sampler2D depthSampler;
-uniform mat4 inverseViewProjection;
-uniform mat4 prevViewProjection;
-#endif
-void main(void)
-{
-#ifdef GEOMETRY_SUPPORTED
-#ifdef OBJECT_BASED
-vec2 texelSize=1.0/screenSize;
-vec2 velocityColor=texture2D(velocitySampler,vUV).rg*2.0-1.0;
-vec2 velocity=vec2(pow(velocityColor.r,3.0),pow(velocityColor.g,3.0));
-velocity*=motionScale*motionStrength;
-float speed=length(velocity/texelSize);
-int samplesCount=int(clamp(speed,1.0,SAMPLES));
-velocity=normalize(velocity)*texelSize;
-float hlim=float(-samplesCount)*0.5+0.5;
-vec4 result=texture2D(textureSampler,vUV);
-for (int i=1; i<int(SAMPLES); ++i)
-{
-if (i>=samplesCount)
-break;
-vec2 offset=vUV+velocity*(hlim+float(i));
-result+=texture2D(textureSampler,offset);
-}
-gl_FragColor=result/float(samplesCount);
-gl_FragColor.a=1.0;
-#else
-vec2 texelSize=1.0/screenSize;
-float depth=texture2D(depthSampler,vUV).r;
-vec4 cpos=vec4(vUV*2.0-1.0,depth,1.0);
-cpos=cpos*inverseViewProjection;
-vec4 ppos=cpos*prevViewProjection;
-ppos.xyz/=ppos.w;
-ppos.xy=ppos.xy*0.5+0.5;
-vec2 velocity=(ppos.xy-vUV)*motionScale*motionStrength;
-float speed=length(velocity/texelSize);
-int nSamples=int(clamp(speed,1.0,SAMPLES));
-vec4 result=texture2D(textureSampler,vUV);
-for (int i=1; i<int(SAMPLES); ++i) {
-if (i>=nSamples)
-break;
-vec2 offset1=vUV+velocity*(float(i)/float(nSamples-1)-0.5);
-result+=texture2D(textureSampler,offset1);
-}
-gl_FragColor=result/float(nSamples);
-#endif
-#else
-gl_FragColor=texture2D(textureSampler,vUV);
-#endif
-}
-`;ze.a.ShadersStore.motionBlurPixelShader=dg;var Gc=function(r){function t(e,n,i,o,a,s,d,p,b,P){p===void 0&&(p=h.a.TEXTURETYPE_UNSIGNED_INT),b===void 0&&(b=!1),P===void 0&&(P=!0);var O=r.call(this,e,"motionBlur",["motionStrength","motionScale","screenSize","inverseViewProjection","prevViewProjection"],["velocitySampler"],i,o,a,s,d,`#define GEOMETRY_SUPPORTED
-#define SAMPLES 64.0
-#define OBJECT_BASED`,p,void 0,null,b)||this;return O.motionStrength=1,O._motionBlurSamples=32,O._isObjectBased=!0,O._forceGeometryBuffer=!1,O._geometryBufferRenderer=null,O._prePassRenderer=null,O._invViewProjection=null,O._previousViewProjection=null,O._forceGeometryBuffer=P,O._forceGeometryBuffer?(O._geometryBufferRenderer=n.enableGeometryBufferRenderer(),O._geometryBufferRenderer&&(O._geometryBufferRenderer.enableVelocity=!0)):(O._prePassRenderer=n.enablePrePassRenderer(),O._prePassRenderer&&(O._prePassRenderer.markAsDirty(),O._prePassEffectConfiguration=new hg)),O._applyMode(),O}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"motionBlurSamples",{get:function(){return this._motionBlurSamples},set:function(e){this._motionBlurSamples=e,this._updateEffect()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"isObjectBased",{get:function(){return this._isObjectBased},set:function(e){this._isObjectBased!==e&&(this._isObjectBased=e,this._applyMode())},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"MotionBlurPostProcess"},t.prototype.excludeSkinnedMesh=function(e){if(e.skeleton){var n=void 0;if(this._geometryBufferRenderer)n=this._geometryBufferRenderer.excludedSkinnedMeshesFromVelocity;else{if(!this._prePassRenderer)return;n=this._prePassRenderer.excludedSkinnedMesh}n.push(e)}},t.prototype.removeExcludedSkinnedMesh=function(e){if(e.skeleton){var n=void 0;if(this._geometryBufferRenderer)n=this._geometryBufferRenderer.excludedSkinnedMeshesFromVelocity;else{if(!this._prePassRenderer)return;n=this._prePassRenderer.excludedSkinnedMesh}var i=n.indexOf(e);i!==-1&&n.splice(i,1)}},t.prototype.dispose=function(e){this._geometryBufferRenderer&&(this._geometryBufferRenderer._previousTransformationMatrices={},this._geometryBufferRenderer._previousBonesTransformationMatrices={},this._geometryBufferRenderer.excludedSkinnedMeshesFromVelocity=[]),r.prototype.dispose.call(this,e)},t.prototype._applyMode=function(){var e=this;if(!this._geometryBufferRenderer&&!this._prePassRenderer)return l.a.Warn("Multiple Render Target support needed to compute object based motion blur"),this.updateEffect();this._updateEffect(),this._invViewProjection=null,this._previousViewProjection=null,this.isObjectBased?(this._prePassRenderer&&this._prePassEffectConfiguration&&(this._prePassEffectConfiguration.texturesRequired[0]=h.a.PREPASS_VELOCITY_TEXTURE_TYPE),this.onApply=function(n){return e._onApplyObjectBased(n)}):(this._invViewProjection=u.a.Identity(),this._previousViewProjection=u.a.Identity(),this._prePassRenderer&&this._prePassEffectConfiguration&&(this._prePassEffectConfiguration.texturesRequired[0]=h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE),this.onApply=function(n){return e._onApplyScreenBased(n)})},t.prototype._onApplyObjectBased=function(e){if(e.setVector2("screenSize",new u.d(this.width,this.height)),e.setFloat("motionScale",this._scene.getAnimationRatio()),e.setFloat("motionStrength",this.motionStrength),this._geometryBufferRenderer){var n=this._geometryBufferRenderer.getTextureIndex(ui.VELOCITY_TEXTURE_TYPE);e.setTexture("velocitySampler",this._geometryBufferRenderer.getGBuffer().textures[n])}else this._prePassRenderer&&(n=this._prePassRenderer.getIndex(h.a.PREPASS_VELOCITY_TEXTURE_TYPE),e.setTexture("velocitySampler",this._prePassRenderer.prePassRT.textures[n]))},t.prototype._onApplyScreenBased=function(e){var n=this._scene.getProjectionMatrix().multiply(this._scene.getViewMatrix());if(n.invertToRef(this._invViewProjection),e.setMatrix("inverseViewProjection",this._invViewProjection),e.setMatrix("prevViewProjection",this._previousViewProjection),this._previousViewProjection=n,e.setVector2("screenSize",new u.d(this.width,this.height)),e.setFloat("motionScale",this._scene.getAnimationRatio()),e.setFloat("motionStrength",this.motionStrength),this._geometryBufferRenderer){var i=this._geometryBufferRenderer.getTextureIndex(ui.DEPTHNORMAL_TEXTURE_TYPE);e.setTexture("depthSampler",this._geometryBufferRenderer.getGBuffer().textures[i])}else this._prePassRenderer&&(i=this._prePassRenderer.getIndex(h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE),e.setTexture("depthSampler",this._prePassRenderer.prePassRT.textures[i]))},t.prototype._updateEffect=function(){if(this._geometryBufferRenderer||this._prePassRenderer){var e=["#define GEOMETRY_SUPPORTED","#define SAMPLES "+this._motionBlurSamples.toFixed(1),this._isObjectBased?"#define OBJECT_BASED":"#define SCREEN_BASED"];this.updateEffect(e.join(`
-`))}},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,i,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable,e.textureType,!1)},e,i,o)},Object(c.c)([Object(L.c)()],t.prototype,"motionStrength",void 0),Object(c.c)([Object(L.c)()],t.prototype,"motionBlurSamples",null),Object(c.c)([Object(L.c)()],t.prototype,"isObjectBased",null),t}(_t);R.a.RegisteredTypes["BABYLON.MotionBlurPostProcess"]=Gc;var fg=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform sampler2D refractionSampler;
-
-uniform vec3 baseColor;
-uniform float depth;
-uniform float colorLevel;
-void main() {
-float ref=1.0-texture2D(refractionSampler,vUV).r;
-vec2 uv=vUV-vec2(0.5);
-vec2 offset=uv*depth*ref;
-vec3 sourceColor=texture2D(textureSampler,vUV-offset).rgb;
-gl_FragColor=vec4(sourceColor+sourceColor*ref*colorLevel,1.0);
-}`;ze.a.ShadersStore.refractionPixelShader=fg;var Bd=function(r){function t(e,n,i,o,a,s,d,p,b,P){var O=r.call(this,e,"refraction",["baseColor","depth","colorLevel"],["refractionSampler"],s,d,p,b,P)||this;return O._ownRefractionTexture=!0,O.color=i,O.depth=o,O.colorLevel=a,O.refractionTextureUrl=n,O.onActivateObservable.add(function(B){O._refTexture=O._refTexture||new we.a(n,B.getScene())}),O.onApplyObservable.add(function(B){B.setColor3("baseColor",O.color),B.setFloat("depth",O.depth),B.setFloat("colorLevel",O.colorLevel),B.setTexture("refractionSampler",O._refTexture)}),O}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"refractionTexture",{get:function(){return this._refTexture},set:function(e){this._refTexture&&this._ownRefractionTexture&&this._refTexture.dispose(),this._refTexture=e,this._ownRefractionTexture=!1},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"RefractionPostProcess"},t.prototype.dispose=function(e){this._refTexture&&this._ownRefractionTexture&&(this._refTexture.dispose(),this._refTexture=null),r.prototype.dispose.call(this,e)},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.refractionTextureUrl,e.color,e.depth,e.colorLevel,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable)},e,i,o)},Object(c.c)([Object(L.c)()],t.prototype,"color",void 0),Object(c.c)([Object(L.c)()],t.prototype,"depth",void 0),Object(c.c)([Object(L.c)()],t.prototype,"colorLevel",void 0),Object(c.c)([Object(L.c)()],t.prototype,"refractionTextureUrl",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.RefractionPostProcess"]=Bd;var pg=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform vec2 screenSize;
-uniform vec2 sharpnessAmounts;
-void main(void)
-{
-vec2 onePixel=vec2(1.0,1.0)/screenSize;
-vec4 color=texture2D(textureSampler,vUV);
-vec4 edgeDetection=texture2D(textureSampler,vUV+onePixel*vec2(0,-1)) +
-texture2D(textureSampler,vUV+onePixel*vec2(-1,0)) +
-texture2D(textureSampler,vUV+onePixel*vec2(1,0)) +
-texture2D(textureSampler,vUV+onePixel*vec2(0,1)) -
-color*4.0;
-gl_FragColor=max(vec4(color.rgb*sharpnessAmounts.y,color.a)-(sharpnessAmounts.x*vec4(edgeDetection.rgb,0)),0.);
-}`;ze.a.ShadersStore.sharpenPixelShader=pg;var zc=function(r){function t(e,n,i,o,a,s,d,p){d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT),p===void 0&&(p=!1);var b=r.call(this,e,"sharpen",["sharpnessAmounts","screenSize"],null,n,i,o,a,s,null,d,void 0,null,p)||this;return b.colorAmount=1,b.edgeAmount=.3,b.onApply=function(P){P.setFloat2("screenSize",b.width,b.height),P.setFloat2("sharpnessAmounts",b.edgeAmount,b.colorAmount)},b}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"SharpenPostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.textureType,e.reusable)},e,i,o)},Object(c.c)([Object(L.c)()],t.prototype,"colorAmount",void 0),Object(c.c)([Object(L.c)()],t.prototype,"edgeAmount",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.SharpenPostProcess"]=zc;var Vr=function(){function r(t,e){this.engine=t,this._name=e,this._renderEffects={},this._renderEffectsForIsolatedPass=new Array,this._cameras=[]}return Object.defineProperty(r.prototype,"name",{get:function(){return this._name},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"cameras",{get:function(){return this._cameras},enumerable:!1,configurable:!0}),r.prototype.getClassName=function(){return"PostProcessRenderPipeline"},Object.defineProperty(r.prototype,"isSupported",{get:function(){for(var t in this._renderEffects)if(this._renderEffects.hasOwnProperty(t)&&!this._renderEffects[t].isSupported)return!1;return!0},enumerable:!1,configurable:!0}),r.prototype.addEffect=function(t){this._renderEffects[t._name]=t},r.prototype._rebuild=function(){},r.prototype._enableEffect=function(t,e){var n=this._renderEffects[t];n&&n._enable(Xe.b.MakeArray(e||this._cameras))},r.prototype._disableEffect=function(t,e){var n=this._renderEffects[t];n&&n._disable(Xe.b.MakeArray(e||this._cameras))},r.prototype._attachCameras=function(t,e){var n=Xe.b.MakeArray(t||this._cameras);if(n){var i,o=[];for(i=0;i<n.length;i++){var a=n[i];if(a){var s=a.name;this._cameras.indexOf(a)===-1?this._cameras[s]=a:e&&o.push(i)}}for(i=0;i<o.length;i++)t.splice(o[i],1);for(var d in this._renderEffects)this._renderEffects.hasOwnProperty(d)&&this._renderEffects[d]._attachCameras(n)}},r.prototype._detachCameras=function(t){var e=Xe.b.MakeArray(t||this._cameras);if(e){for(var n in this._renderEffects)this._renderEffects.hasOwnProperty(n)&&this._renderEffects[n]._detachCameras(e);for(var i=0;i<e.length;i++)this._cameras.splice(this._cameras.indexOf(e[i]),1)}},r.prototype._update=function(){for(var t in this._renderEffects)this._renderEffects.hasOwnProperty(t)&&this._renderEffects[t]._update();for(var e=0;e<this._cameras.length;e++)if(this._cameras[e]){var n=this._cameras[e].name;this._renderEffectsForIsolatedPass[n]&&this._renderEffectsForIsolatedPass[n]._update()}},r.prototype._reset=function(){this._renderEffects={},this._renderEffectsForIsolatedPass=new Array},r.prototype._enableMSAAOnFirstPostProcess=function(t){if(this.engine.webGLVersion===1)return!1;var e=Object.keys(this._renderEffects);if(e.length>0){var n=this._renderEffects[e[0]].getPostProcesses();n&&(n[0].samples=t)}return!0},r.prototype.setPrePassRenderer=function(t){return!1},r.prototype.dispose=function(){},Object(c.c)([Object(L.c)()],r.prototype,"_name",void 0),r}(),Ud=function(){function r(){this._renderPipelines={}}return Object.defineProperty(r.prototype,"supportedPipelines",{get:function(){var t=[];for(var e in this._renderPipelines)if(this._renderPipelines.hasOwnProperty(e)){var n=this._renderPipelines[e];n.isSupported&&t.push(n)}return t},enumerable:!1,configurable:!0}),r.prototype.addPipeline=function(t){this._renderPipelines[t._name]=t},r.prototype.attachCamerasToRenderPipeline=function(t,e,n){n===void 0&&(n=!1);var i=this._renderPipelines[t];i&&i._attachCameras(e,n)},r.prototype.detachCamerasFromRenderPipeline=function(t,e){var n=this._renderPipelines[t];n&&n._detachCameras(e)},r.prototype.enableEffectInPipeline=function(t,e,n){var i=this._renderPipelines[t];i&&i._enableEffect(e,n)},r.prototype.disableEffectInPipeline=function(t,e,n){var i=this._renderPipelines[t];i&&i._disableEffect(e,n)},r.prototype.update=function(){for(var t in this._renderPipelines)if(this._renderPipelines.hasOwnProperty(t)){var e=this._renderPipelines[t];e.isSupported?e._update():(e.dispose(),delete this._renderPipelines[t])}},r.prototype._rebuild=function(){for(var t in this._renderPipelines)this._renderPipelines.hasOwnProperty(t)&&this._renderPipelines[t]._rebuild()},r.prototype.dispose=function(){for(var t in this._renderPipelines)this._renderPipelines.hasOwnProperty(t)&&this._renderPipelines[t].dispose()},r}();Object.defineProperty(_e.a.prototype,"postProcessRenderPipelineManager",{get:function(){if(!this._postProcessRenderPipelineManager){var r=this._getComponent(at.a.NAME_POSTPROCESSRENDERPIPELINEMANAGER);r||(r=new Vd(this),this._addComponent(r)),this._postProcessRenderPipelineManager=new Ud}return this._postProcessRenderPipelineManager},enumerable:!0,configurable:!0});var Vd=function(){function r(t){this.name=at.a.NAME_POSTPROCESSRENDERPIPELINEMANAGER,this.scene=t}return r.prototype.register=function(){this.scene._gatherRenderTargetsStage.registerStep(at.a.STEP_GATHERRENDERTARGETS_POSTPROCESSRENDERPIPELINEMANAGER,this,this._gatherRenderTargets)},r.prototype.rebuild=function(){this.scene._postProcessRenderPipelineManager&&this.scene._postProcessRenderPipelineManager._rebuild()},r.prototype.dispose=function(){this.scene._postProcessRenderPipelineManager&&this.scene._postProcessRenderPipelineManager.dispose()},r.prototype._gatherRenderTargets=function(){this.scene._postProcessRenderPipelineManager&&this.scene._postProcessRenderPipelineManager.update()},r}(),kd=function(r){function t(e,n,i,o,a){e===void 0&&(e=""),n===void 0&&(n=!0),i===void 0&&(i=te.a.LastCreatedScene),a===void 0&&(a=!0);var s=r.call(this,i.getEngine(),e)||this;s._camerasToBeAttached=[],s.SharpenPostProcessId="SharpenPostProcessEffect",s.ImageProcessingPostProcessId="ImageProcessingPostProcessEffect",s.FxaaPostProcessId="FxaaPostProcessEffect",s.ChromaticAberrationPostProcessId="ChromaticAberrationPostProcessEffect",s.GrainPostProcessId="GrainPostProcessEffect",s._glowLayer=null,s.animations=[],s._imageProcessingConfigurationObserver=null,s._sharpenEnabled=!1,s._bloomEnabled=!1,s._depthOfFieldEnabled=!1,s._depthOfFieldBlurLevel=sr.Low,s._fxaaEnabled=!1,s._imageProcessingEnabled=!0,s._bloomScale=.5,s._chromaticAberrationEnabled=!1,s._grainEnabled=!1,s._buildAllowed=!0,s.onBuildObservable=new x.c,s._resizeObserver=null,s._hardwareScaleLevel=1,s._bloomKernel=64,s._bloomWeight=.15,s._bloomThreshold=.9,s._samples=1,s._hasCleared=!1,s._prevPostProcess=null,s._prevPrevPostProcess=null,s._depthOfFieldSceneObserver=null,s._cameras=o||i.cameras,s._cameras=s._cameras.slice(),s._camerasToBeAttached=s._cameras.slice(),s._buildAllowed=a,s._scene=i;var d=s._scene.getEngine().getCaps();s._hdr=n&&(d.textureHalfFloatRender||d.textureFloatRender),s._hdr?d.textureHalfFloatRender?s._defaultPipelineTextureType=h.a.TEXTURETYPE_HALF_FLOAT:d.textureFloatRender&&(s._defaultPipelineTextureType=h.a.TEXTURETYPE_FLOAT):s._defaultPipelineTextureType=h.a.TEXTURETYPE_UNSIGNED_INT,i.postProcessRenderPipelineManager.addPipeline(s);var p=s._scene.getEngine();return s.sharpen=new zc("sharpen",1,null,we.a.BILINEAR_SAMPLINGMODE,p,!1,s._defaultPipelineTextureType,!0),s._sharpenEffect=new Rt(p,s.SharpenPostProcessId,function(){return s.sharpen},!0),s.depthOfField=new Vc(s._scene,null,s._depthOfFieldBlurLevel,s._defaultPipelineTextureType,!0),s.bloom=new Fc(s._scene,s._bloomScale,s._bloomWeight,s.bloomKernel,s._defaultPipelineTextureType,!0),s.chromaticAberration=new Bc("ChromaticAberration",p.getRenderWidth(),p.getRenderHeight(),1,null,we.a.BILINEAR_SAMPLINGMODE,p,!1,s._defaultPipelineTextureType,!0),s._chromaticAberrationEffect=new Rt(p,s.ChromaticAberrationPostProcessId,function(){return s.chromaticAberration},!0),s.grain=new kc("Grain",1,null,we.a.BILINEAR_SAMPLINGMODE,p,!1,s._defaultPipelineTextureType,!0),s._grainEffect=new Rt(p,s.GrainPostProcessId,function(){return s.grain},!0),s._resizeObserver=p.onResizeObservable.add(function(){s._hardwareScaleLevel=p.getHardwareScalingLevel(),s.bloomKernel=s.bloomKernel}),s._imageProcessingConfigurationObserver=s._scene.imageProcessingConfiguration.onUpdateParameters.add(function(){s.bloom._downscale._exposure=s._scene.imageProcessingConfiguration.exposure,s.imageProcessingEnabled!==s._scene.imageProcessingConfiguration.isEnabled&&(s._imageProcessingEnabled=s._scene.imageProcessingConfiguration.isEnabled,s._buildPipeline())}),s._buildPipeline(),s}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"scene",{get:function(){return this._scene},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"sharpenEnabled",{get:function(){return this._sharpenEnabled},set:function(e){this._sharpenEnabled!==e&&(this._sharpenEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"bloomKernel",{get:function(){return this._bloomKernel},set:function(e){this._bloomKernel=e,this.bloom.kernel=e/this._hardwareScaleLevel},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"bloomWeight",{get:function(){return this._bloomWeight},set:function(e){this._bloomWeight!==e&&(this.bloom.weight=e,this._bloomWeight=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"bloomThreshold",{get:function(){return this._bloomThreshold},set:function(e){this._bloomThreshold!==e&&(this.bloom.threshold=e,this._bloomThreshold=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"bloomScale",{get:function(){return this._bloomScale},set:function(e){this._bloomScale!==e&&(this._bloomScale=e,this._rebuildBloom(),this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"bloomEnabled",{get:function(){return this._bloomEnabled},set:function(e){this._bloomEnabled!==e&&(this._bloomEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),t.prototype._rebuildBloom=function(){var e=this.bloom;this.bloom=new Fc(this._scene,this.bloomScale,this._bloomWeight,this.bloomKernel,this._defaultPipelineTextureType,!1),this.bloom.threshold=e.threshold;for(var n=0;n<this._cameras.length;n++)e.disposeEffects(this._cameras[n])},Object.defineProperty(t.prototype,"depthOfFieldEnabled",{get:function(){return this._depthOfFieldEnabled},set:function(e){this._depthOfFieldEnabled!==e&&(this._depthOfFieldEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"depthOfFieldBlurLevel",{get:function(){return this._depthOfFieldBlurLevel},set:function(e){if(this._depthOfFieldBlurLevel!==e){this._depthOfFieldBlurLevel=e;var n=this.depthOfField;this.depthOfField=new Vc(this._scene,null,this._depthOfFieldBlurLevel,this._defaultPipelineTextureType,!1),this.depthOfField.focalLength=n.focalLength,this.depthOfField.focusDistance=n.focusDistance,this.depthOfField.fStop=n.fStop,this.depthOfField.lensSize=n.lensSize;for(var i=0;i<this._cameras.length;i++)n.disposeEffects(this._cameras[i]);this._buildPipeline()}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"fxaaEnabled",{get:function(){return this._fxaaEnabled},set:function(e){this._fxaaEnabled!==e&&(this._fxaaEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"samples",{get:function(){return this._samples},set:function(e){this._samples!==e&&(this._samples=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"imageProcessingEnabled",{get:function(){return this._imageProcessingEnabled},set:function(e){this._imageProcessingEnabled!==e&&(this._scene.imageProcessingConfiguration.isEnabled=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"glowLayerEnabled",{get:function(){return this._glowLayer!=null},set:function(e){e&&!this._glowLayer?this._glowLayer=new ra("",this._scene):!e&&this._glowLayer&&(this._glowLayer.dispose(),this._glowLayer=null)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"glowLayer",{get:function(){return this._glowLayer},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"chromaticAberrationEnabled",{get:function(){return this._chromaticAberrationEnabled},set:function(e){this._chromaticAberrationEnabled!==e&&(this._chromaticAberrationEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"grainEnabled",{get:function(){return this._grainEnabled},set:function(e){this._grainEnabled!==e&&(this._grainEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"DefaultRenderingPipeline"},t.prototype.prepare=function(){var e=this._buildAllowed;this._buildAllowed=!0,this._buildPipeline(),this._buildAllowed=e},t.prototype._setAutoClearAndTextureSharing=function(e,n){n===void 0&&(n=!1),this._hasCleared?e.autoClear=!1:(e.autoClear=!0,this._scene.autoClear=!1,this._hasCleared=!0),n||(this._prevPrevPostProcess?e.shareOutputWith(this._prevPrevPostProcess):e.useOwnOutput(),this._prevPostProcess&&(this._prevPrevPostProcess=this._prevPostProcess),this._prevPostProcess=e)},t.prototype._buildPipeline=function(){var e=this;if(this._buildAllowed){this._scene.autoClear=!0;var n=this._scene.getEngine();if(this._disposePostProcesses(),this._cameras!==null&&(this._scene.postProcessRenderPipelineManager.detachCamerasFromRenderPipeline(this._name,this._cameras),this._cameras=this._camerasToBeAttached.slice()),this._reset(),this._prevPostProcess=null,this._prevPrevPostProcess=null,this._hasCleared=!1,this.depthOfFieldEnabled){if(this._cameras.length>1){for(var i=0,o=this._cameras;i<o.length;i++){var a=o[i];(s=this._scene.enableDepthRenderer(a)).useOnlyInActiveCamera=!0}this._depthOfFieldSceneObserver=this._scene.onAfterRenderTargetsRenderObservable.add(function(d){e._cameras.indexOf(d.activeCamera)>-1&&(e.depthOfField.depthTexture=d.enableDepthRenderer(d.activeCamera).getDepthMap())})}else{this._scene.onAfterRenderTargetsRenderObservable.remove(this._depthOfFieldSceneObserver);var s=this._scene.enableDepthRenderer(this._cameras[0]);this.depthOfField.depthTexture=s.getDepthMap()}this.depthOfField._isReady()||this.depthOfField._updateEffects(),this.addEffect(this.depthOfField),this._setAutoClearAndTextureSharing(this.depthOfField._effects[0],!0)}else this._scene.onAfterRenderTargetsRenderObservable.remove(this._depthOfFieldSceneObserver);this.bloomEnabled&&(this.bloom._isReady()||this.bloom._updateEffects(),this.addEffect(this.bloom),this._setAutoClearAndTextureSharing(this.bloom._effects[0],!0)),this._imageProcessingEnabled&&(this.imageProcessing=new Go("imageProcessing",1,null,we.a.BILINEAR_SAMPLINGMODE,n,!1,this._defaultPipelineTextureType),this._hdr?(this.addEffect(new Rt(n,this.ImageProcessingPostProcessId,function(){return e.imageProcessing},!0)),this._setAutoClearAndTextureSharing(this.imageProcessing)):this._scene.imageProcessingConfiguration.applyByPostProcess=!1,this.cameras&&this.cameras.length!==0||(this._scene.imageProcessingConfiguration.applyByPostProcess=!1),this.imageProcessing.getEffect()||this.imageProcessing._updateParameters()),this.sharpenEnabled&&(this.sharpen.isReady()||this.sharpen.updateEffect(),this.addEffect(this._sharpenEffect),this._setAutoClearAndTextureSharing(this.sharpen)),this.grainEnabled&&(this.grain.isReady()||this.grain.updateEffect(),this.addEffect(this._grainEffect),this._setAutoClearAndTextureSharing(this.grain)),this.chromaticAberrationEnabled&&(this.chromaticAberration.isReady()||this.chromaticAberration.updateEffect(),this.addEffect(this._chromaticAberrationEffect),this._setAutoClearAndTextureSharing(this.chromaticAberration)),this.fxaaEnabled&&(this.fxaa=new Oo("fxaa",1,null,we.a.BILINEAR_SAMPLINGMODE,n,!1,this._defaultPipelineTextureType),this.addEffect(new Rt(n,this.FxaaPostProcessId,function(){return e.fxaa},!0)),this._setAutoClearAndTextureSharing(this.fxaa,!0)),this._cameras!==null&&this._scene.postProcessRenderPipelineManager.attachCamerasToRenderPipeline(this._name,this._cameras),this._scene.activeCameras&&this._scene.activeCameras.length>1&&(this._scene.autoClear=!0),!this._enableMSAAOnFirstPostProcess(this.samples)&&this.samples>1&&l.a.Warn("MSAA failed to enable, MSAA is only supported in browsers that support webGL >= 2.0"),this.onBuildObservable.notifyObservers(this)}},t.prototype._disposePostProcesses=function(e){e===void 0&&(e=!1);for(var n=0;n<this._cameras.length;n++){var i=this._cameras[n];this.imageProcessing&&this.imageProcessing.dispose(i),this.fxaa&&this.fxaa.dispose(i),e&&(this.sharpen&&this.sharpen.dispose(i),this.depthOfField&&(this._scene.onAfterRenderTargetsRenderObservable.remove(this._depthOfFieldSceneObserver),this.depthOfField.disposeEffects(i)),this.bloom&&this.bloom.disposeEffects(i),this.chromaticAberration&&this.chromaticAberration.dispose(i),this.grain&&this.grain.dispose(i),this._glowLayer&&this._glowLayer.dispose())}this.imageProcessing=null,this.fxaa=null,e&&(this.sharpen=null,this._sharpenEffect=null,this.depthOfField=null,this.bloom=null,this.chromaticAberration=null,this._chromaticAberrationEffect=null,this.grain=null,this._grainEffect=null,this._glowLayer=null)},t.prototype.addCamera=function(e){this._camerasToBeAttached.push(e),this._buildPipeline()},t.prototype.removeCamera=function(e){var n=this._camerasToBeAttached.indexOf(e);this._camerasToBeAttached.splice(n,1),this._buildPipeline()},t.prototype.dispose=function(){this.onBuildObservable.clear(),this._disposePostProcesses(!0),this._scene.postProcessRenderPipelineManager.detachCamerasFromRenderPipeline(this._name,this._cameras),this._scene.autoClear=!0,this._resizeObserver&&(this._scene.getEngine().onResizeObservable.remove(this._resizeObserver),this._resizeObserver=null),this._scene.imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingConfigurationObserver),r.prototype.dispose.call(this)},t.prototype.serialize=function(){var e=L.a.Serialize(this);return e.customType="DefaultRenderingPipeline",e},t.Parse=function(e,n,i){return L.a.Parse(function(){return new t(e._name,e._name._hdr,n)},e,n,i)},Object(c.c)([Object(L.c)()],t.prototype,"sharpenEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"bloomKernel",null),Object(c.c)([Object(L.c)()],t.prototype,"_bloomWeight",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_bloomThreshold",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_hdr",void 0),Object(c.c)([Object(L.c)()],t.prototype,"bloomWeight",null),Object(c.c)([Object(L.c)()],t.prototype,"bloomThreshold",null),Object(c.c)([Object(L.c)()],t.prototype,"bloomScale",null),Object(c.c)([Object(L.c)()],t.prototype,"bloomEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"depthOfFieldEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"depthOfFieldBlurLevel",null),Object(c.c)([Object(L.c)()],t.prototype,"fxaaEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"samples",null),Object(c.c)([Object(L.c)()],t.prototype,"imageProcessingEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"glowLayerEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"chromaticAberrationEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"grainEnabled",null),t}(Vr);R.a.RegisteredTypes["BABYLON.DefaultRenderingPipeline"]=kd;var _g=`
-uniform sampler2D textureSampler;
-
-uniform float gain;
-uniform float threshold;
-uniform float screen_width;
-uniform float screen_height;
-
-varying vec2 vUV;
-
-vec4 highlightColor(vec4 color) {
-vec4 highlight=color;
-float luminance=dot(highlight.rgb,vec3(0.2125,0.7154,0.0721));
-float lum_threshold;
-if (threshold>1.0) { lum_threshold=0.94+0.01*threshold; }
-else { lum_threshold=0.5+0.44*threshold; }
-luminance=clamp((luminance-lum_threshold)*(1.0/(1.0-lum_threshold)),0.0,1.0);
-highlight*=luminance*gain;
-highlight.a=1.0;
-return highlight;
-}
-void main(void)
-{
-vec4 original=texture2D(textureSampler,vUV);
-
-if (gain == -1.0) {
-gl_FragColor=vec4(0.0,0.0,0.0,1.0);
-return;
-}
-float w=2.0/screen_width;
-float h=2.0/screen_height;
-float weight=1.0;
-
-vec4 blurred=vec4(0.0,0.0,0.0,0.0);
-#ifdef PENTAGON
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.84*w,0.43*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(0.48*w,-1.29*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(0.61*w,1.51*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.55*w,-0.74*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.71*w,-0.52*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.94*w,1.59*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.40*w,-1.87*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.62*w,1.16*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.09*w,0.25*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.46*w,-1.71*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(0.08*w,2.42*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.85*w,-1.89*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.89*w,0.16*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.29*w,1.88*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(0.40*w,-2.81*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.54*w,2.26*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.60*w,-0.61*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.31*w,-1.30*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.83*w,2.53*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.12*w,-2.48*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.60*w,1.11*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.82*w,0.99*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.50*w,-2.81*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(0.85*w,3.33*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.94*w,-1.92*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(3.27*w,-0.53*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.95*w,2.48*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.23*w,-3.04*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.17*w,2.05*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.97*w,-0.04*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.25*w,-2.00*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.31*w,3.08*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.94*w,-2.59*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(3.37*w,0.64*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-3.13*w,1.93*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.03*w,-3.65*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.60*w,3.17*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-3.14*w,-1.19*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(3.00*w,-1.19*h)));
-#else
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.85*w,0.36*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(0.52*w,-1.14*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(0.46*w,1.42*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.46*w,-0.83*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.79*w,-0.42*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.11*w,1.62*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.29*w,-2.07*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.69*w,1.39*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.28*w,0.12*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.65*w,-1.69*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.08*w,2.44*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.63*w,-1.90*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.55*w,0.31*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.13*w,1.52*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(0.56*w,-2.61*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.38*w,2.34*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.64*w,-0.81*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.53*w,-1.21*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.06*w,2.63*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.00*w,-2.69*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.59*w,1.32*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.82*w,0.78*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.57*w,-2.50*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(0.54*w,2.93*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.39*w,-1.81*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(3.01*w,-0.28*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.04*w,2.25*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.02*w,-3.05*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.09*w,2.25*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-3.07*w,-0.25*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.44*w,-1.90*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.52*w,3.05*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.68*w,-2.61*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(3.01*w,0.79*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.76*w,1.46*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.05*w,-2.94*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.21*w,2.88*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.84*w,-1.30*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.98*w,-0.96*h)));
-#endif
-blurred/=39.0;
-gl_FragColor=blurred;
-
-}`;ze.a.ShadersStore.lensHighlightsPixelShader=_g;var mg=`
-
-
-
-
-uniform sampler2D textureSampler;
-uniform sampler2D highlightsSampler;
-uniform sampler2D depthSampler;
-uniform sampler2D grainSampler;
-
-uniform float grain_amount;
-uniform bool blur_noise;
-uniform float screen_width;
-uniform float screen_height;
-uniform float distortion;
-uniform bool dof_enabled;
-
-uniform float screen_distance;
-uniform float aperture;
-uniform float darken;
-uniform float edge_blur;
-uniform bool highlights;
-
-uniform float near;
-uniform float far;
-
-varying vec2 vUV;
-
-#define PI 3.14159265
-#define TWOPI 6.28318530
-#define inverse_focal_length 0.1
-
-vec2 centered_screen_pos;
-vec2 distorted_coords;
-float radius2;
-float radius;
-
-vec2 rand(vec2 co)
-{
-float noise1=(fract(sin(dot(co,vec2(12.9898,78.233)))*43758.5453));
-float noise2=(fract(sin(dot(co,vec2(12.9898,78.233)*2.0))*43758.5453));
-return clamp(vec2(noise1,noise2),0.0,1.0);
-}
-
-vec2 getDistortedCoords(vec2 coords) {
-if (distortion == 0.0) { return coords; }
-vec2 direction=1.0*normalize(centered_screen_pos);
-vec2 dist_coords=vec2(0.5,0.5);
-dist_coords.x=0.5+direction.x*radius2*1.0;
-dist_coords.y=0.5+direction.y*radius2*1.0;
-float dist_amount=clamp(distortion*0.23,0.0,1.0);
-dist_coords=mix(coords,dist_coords,dist_amount);
-return dist_coords;
-}
-
-float sampleScreen(inout vec4 color,const in vec2 offset,const in float weight) {
-
-vec2 coords=distorted_coords;
-float angle=rand(coords*100.0).x*TWOPI;
-coords+=vec2(offset.x*cos(angle)-offset.y*sin(angle),offset.x*sin(angle)+offset.y*cos(angle));
-color+=texture2D(textureSampler,coords)*weight;
-return weight;
-}
-
-float getBlurLevel(float size) {
-return min(3.0,ceil(size/1.0));
-}
-
-vec4 getBlurColor(float size) {
-vec4 col=texture2D(textureSampler,distorted_coords);
-if (size == 0.0) { return col; }
-
-
-float blur_level=getBlurLevel(size);
-float w=(size/screen_width);
-float h=(size/screen_height);
-float total_weight=1.0;
-vec2 sample_coords;
-total_weight+=sampleScreen(col,vec2(-0.50*w,0.24*h),0.93);
-total_weight+=sampleScreen(col,vec2(0.30*w,-0.75*h),0.90);
-total_weight+=sampleScreen(col,vec2(0.36*w,0.96*h),0.87);
-total_weight+=sampleScreen(col,vec2(-1.08*w,-0.55*h),0.85);
-total_weight+=sampleScreen(col,vec2(1.33*w,-0.37*h),0.83);
-total_weight+=sampleScreen(col,vec2(-0.82*w,1.31*h),0.80);
-total_weight+=sampleScreen(col,vec2(-0.31*w,-1.67*h),0.78);
-total_weight+=sampleScreen(col,vec2(1.47*w,1.11*h),0.76);
-total_weight+=sampleScreen(col,vec2(-1.97*w,0.19*h),0.74);
-total_weight+=sampleScreen(col,vec2(1.42*w,-1.57*h),0.72);
-if (blur_level>1.0) {
-total_weight+=sampleScreen(col,vec2(0.01*w,2.25*h),0.70);
-total_weight+=sampleScreen(col,vec2(-1.62*w,-1.74*h),0.67);
-total_weight+=sampleScreen(col,vec2(2.49*w,0.20*h),0.65);
-total_weight+=sampleScreen(col,vec2(-2.07*w,1.61*h),0.63);
-total_weight+=sampleScreen(col,vec2(0.46*w,-2.70*h),0.61);
-total_weight+=sampleScreen(col,vec2(1.55*w,2.40*h),0.59);
-total_weight+=sampleScreen(col,vec2(-2.88*w,-0.75*h),0.56);
-total_weight+=sampleScreen(col,vec2(2.73*w,-1.44*h),0.54);
-total_weight+=sampleScreen(col,vec2(-1.08*w,3.02*h),0.52);
-total_weight+=sampleScreen(col,vec2(-1.28*w,-3.05*h),0.49);
-}
-if (blur_level>2.0) {
-total_weight+=sampleScreen(col,vec2(3.11*w,1.43*h),0.46);
-total_weight+=sampleScreen(col,vec2(-3.36*w,1.08*h),0.44);
-total_weight+=sampleScreen(col,vec2(1.80*w,-3.16*h),0.41);
-total_weight+=sampleScreen(col,vec2(0.83*w,3.65*h),0.38);
-total_weight+=sampleScreen(col,vec2(-3.16*w,-2.19*h),0.34);
-total_weight+=sampleScreen(col,vec2(3.92*w,-0.53*h),0.31);
-total_weight+=sampleScreen(col,vec2(-2.59*w,3.12*h),0.26);
-total_weight+=sampleScreen(col,vec2(-0.20*w,-4.15*h),0.22);
-total_weight+=sampleScreen(col,vec2(3.02*w,3.00*h),0.15);
-}
-col/=total_weight;
-
-if (darken>0.0) {
-col.rgb*=clamp(0.3,1.0,1.05-size*0.5*darken);
-}
-
-
-
-
-return col;
-}
-void main(void)
-{
-
-centered_screen_pos=vec2(vUV.x-0.5,vUV.y-0.5);
-radius2=centered_screen_pos.x*centered_screen_pos.x+centered_screen_pos.y*centered_screen_pos.y;
-radius=sqrt(radius2);
-distorted_coords=getDistortedCoords(vUV);
-vec2 texels_coords=vec2(vUV.x*screen_width,vUV.y*screen_height);
-float depth=texture2D(depthSampler,distorted_coords).r;
-float distance=near+(far-near)*depth;
-vec4 color=texture2D(textureSampler,vUV);
-
-
-float coc=abs(aperture*(screen_distance*(inverse_focal_length-1.0/distance)-1.0));
-
-if (dof_enabled == false || coc<0.07) { coc=0.0; }
-
-float edge_blur_amount=0.0;
-if (edge_blur>0.0) {
-edge_blur_amount=clamp((radius*2.0-1.0+0.15*edge_blur)*1.5,0.0,1.0)*1.3;
-}
-
-float blur_amount=max(edge_blur_amount,coc);
-
-if (blur_amount == 0.0) {
-gl_FragColor=texture2D(textureSampler,distorted_coords);
-}
-else {
-
-gl_FragColor=getBlurColor(blur_amount*1.7);
-
-if (highlights) {
-gl_FragColor.rgb+=clamp(coc,0.0,1.0)*texture2D(highlightsSampler,distorted_coords).rgb;
-}
-if (blur_noise) {
-
-vec2 noise=rand(distorted_coords)*0.01*blur_amount;
-vec2 blurred_coord=vec2(distorted_coords.x+noise.x,distorted_coords.y+noise.y);
-gl_FragColor=0.04*texture2D(textureSampler,blurred_coord)+0.96*gl_FragColor;
-}
-}
-
-if (grain_amount>0.0) {
-vec4 grain_color=texture2D(grainSampler,texels_coords*0.003);
-gl_FragColor.rgb+=(-0.5+grain_color.rgb)*0.30*grain_amount;
-}
-}
-`;ze.a.ShadersStore.depthOfFieldPixelShader=mg;var gg=function(r){function t(e,n,i,o,a){o===void 0&&(o=1);var s=r.call(this,i.getEngine(),e)||this;return s.LensChromaticAberrationEffect="LensChromaticAberrationEffect",s.HighlightsEnhancingEffect="HighlightsEnhancingEffect",s.LensDepthOfFieldEffect="LensDepthOfFieldEffect",s._pentagonBokehIsEnabled=!1,s._scene=i,s._depthTexture=i.enableDepthRenderer().getDepthMap(),n.grain_texture?s._grainTexture=n.grain_texture:s._createGrainTexture(),s._edgeBlur=n.edge_blur?n.edge_blur:0,s._grainAmount=n.grain_amount?n.grain_amount:0,s._chromaticAberration=n.chromatic_aberration?n.chromatic_aberration:0,s._distortion=n.distortion?n.distortion:0,s._highlightsGain=n.dof_gain!==void 0?n.dof_gain:-1,s._highlightsThreshold=n.dof_threshold?n.dof_threshold:1,s._dofDistance=n.dof_focus_distance!==void 0?n.dof_focus_distance:-1,s._dofAperture=n.dof_aperture?n.dof_aperture:1,s._dofDarken=n.dof_darken?n.dof_darken:0,s._dofPentagon=n.dof_pentagon===void 0||n.dof_pentagon,s._blurNoise=n.blur_noise===void 0||n.blur_noise,s._createChromaticAberrationPostProcess(o),s._createHighlightsPostProcess(o),s._createDepthOfFieldPostProcess(o/4),s.addEffect(new Rt(i.getEngine(),s.LensChromaticAberrationEffect,function(){return s._chromaticAberrationPostProcess},!0)),s.addEffect(new Rt(i.getEngine(),s.HighlightsEnhancingEffect,function(){return s._highlightsPostProcess},!0)),s.addEffect(new Rt(i.getEngine(),s.LensDepthOfFieldEffect,function(){return s._depthOfFieldPostProcess},!0)),s._highlightsGain===-1&&s._disableEffect(s.HighlightsEnhancingEffect,null),i.postProcessRenderPipelineManager.addPipeline(s),a&&i.postProcessRenderPipelineManager.attachCamerasToRenderPipeline(e,a),s}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"LensRenderingPipeline"},Object.defineProperty(t.prototype,"scene",{get:function(){return this._scene},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"edgeBlur",{get:function(){return this._edgeBlur},set:function(e){this.setEdgeBlur(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"grainAmount",{get:function(){return this._grainAmount},set:function(e){this.setGrainAmount(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"chromaticAberration",{get:function(){return this._chromaticAberration},set:function(e){this.setChromaticAberration(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dofAperture",{get:function(){return this._dofAperture},set:function(e){this.setAperture(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"edgeDistortion",{get:function(){return this._distortion},set:function(e){this.setEdgeDistortion(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dofDistortion",{get:function(){return this._dofDistance},set:function(e){this.setFocusDistance(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"darkenOutOfFocus",{get:function(){return this._dofDarken},set:function(e){this.setDarkenOutOfFocus(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"blurNoise",{get:function(){return this._blurNoise},set:function(e){this._blurNoise=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"pentagonBokeh",{get:function(){return this._pentagonBokehIsEnabled},set:function(e){e?this.enablePentagonBokeh():this.disablePentagonBokeh()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"highlightsGain",{get:function(){return this._highlightsGain},set:function(e){this.setHighlightsGain(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"highlightsThreshold",{get:function(){return this._highlightsThreshold},set:function(e){this.setHighlightsThreshold(e)},enumerable:!1,configurable:!0}),t.prototype.setEdgeBlur=function(e){this._edgeBlur=e},t.prototype.disableEdgeBlur=function(){this._edgeBlur=0},t.prototype.setGrainAmount=function(e){this._grainAmount=e},t.prototype.disableGrain=function(){this._grainAmount=0},t.prototype.setChromaticAberration=function(e){this._chromaticAberration=e},t.prototype.disableChromaticAberration=function(){this._chromaticAberration=0},t.prototype.setEdgeDistortion=function(e){this._distortion=e},t.prototype.disableEdgeDistortion=function(){this._distortion=0},t.prototype.setFocusDistance=function(e){this._dofDistance=e},t.prototype.disableDepthOfField=function(){this._dofDistance=-1},t.prototype.setAperture=function(e){this._dofAperture=e},t.prototype.setDarkenOutOfFocus=function(e){this._dofDarken=e},t.prototype.enablePentagonBokeh=function(){this._highlightsPostProcess.updateEffect(`#define PENTAGON
-`),this._pentagonBokehIsEnabled=!0},t.prototype.disablePentagonBokeh=function(){this._pentagonBokehIsEnabled=!1,this._highlightsPostProcess.updateEffect()},t.prototype.enableNoiseBlur=function(){this._blurNoise=!0},t.prototype.disableNoiseBlur=function(){this._blurNoise=!1},t.prototype.setHighlightsGain=function(e){this._highlightsGain=e},t.prototype.setHighlightsThreshold=function(e){this._highlightsGain===-1&&(this._highlightsGain=1),this._highlightsThreshold=e},t.prototype.disableHighlights=function(){this._highlightsGain=-1},t.prototype.dispose=function(e){e===void 0&&(e=!1),this._scene.postProcessRenderPipelineManager.detachCamerasFromRenderPipeline(this._name,this._scene.cameras),this._chromaticAberrationPostProcess=null,this._highlightsPostProcess=null,this._depthOfFieldPostProcess=null,this._grainTexture.dispose(),e&&this._scene.disableDepthRenderer()},t.prototype._createChromaticAberrationPostProcess=function(e){var n=this;this._chromaticAberrationPostProcess=new _t("LensChromaticAberration","chromaticAberration",["chromatic_aberration","screen_width","screen_height","direction","radialIntensity","centerPosition"],[],e,null,we.a.TRILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1),this._chromaticAberrationPostProcess.onApply=function(i){i.setFloat("chromatic_aberration",n._chromaticAberration),i.setFloat("screen_width",n._scene.getEngine().getRenderWidth()),i.setFloat("screen_height",n._scene.getEngine().getRenderHeight()),i.setFloat("radialIntensity",1),i.setFloat2("direction",17,17),i.setFloat2("centerPosition",.5,.5)}},t.prototype._createHighlightsPostProcess=function(e){var n=this;this._highlightsPostProcess=new _t("LensHighlights","lensHighlights",["gain","threshold","screen_width","screen_height"],[],e,null,we.a.TRILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,this._dofPentagon?`#define PENTAGON
-`:""),this._highlightsPostProcess.onApply=function(i){i.setFloat("gain",n._highlightsGain),i.setFloat("threshold",n._highlightsThreshold),i.setTextureFromPostProcess("textureSampler",n._chromaticAberrationPostProcess),i.setFloat("screen_width",n._scene.getEngine().getRenderWidth()),i.setFloat("screen_height",n._scene.getEngine().getRenderHeight())}},t.prototype._createDepthOfFieldPostProcess=function(e){var n=this;this._depthOfFieldPostProcess=new _t("LensDepthOfField","depthOfField",["grain_amount","blur_noise","screen_width","screen_height","distortion","dof_enabled","screen_distance","aperture","darken","edge_blur","highlights","near","far"],["depthSampler","grainSampler","highlightsSampler"],e,null,we.a.TRILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1),this._depthOfFieldPostProcess.onApply=function(i){i.setTexture("depthSampler",n._depthTexture),i.setTexture("grainSampler",n._grainTexture),i.setTextureFromPostProcess("textureSampler",n._highlightsPostProcess),i.setTextureFromPostProcess("highlightsSampler",n._depthOfFieldPostProcess),i.setFloat("grain_amount",n._grainAmount),i.setBool("blur_noise",n._blurNoise),i.setFloat("screen_width",n._scene.getEngine().getRenderWidth()),i.setFloat("screen_height",n._scene.getEngine().getRenderHeight()),i.setFloat("distortion",n._distortion),i.setBool("dof_enabled",n._dofDistance!==-1),i.setFloat("screen_distance",1/(.1-1/n._dofDistance)),i.setFloat("aperture",n._dofAperture),i.setFloat("darken",n._dofDarken),i.setFloat("edge_blur",n._edgeBlur),i.setBool("highlights",n._highlightsGain!==-1),n._scene.activeCamera&&(i.setFloat("near",n._scene.activeCamera.minZ),i.setFloat("far",n._scene.activeCamera.maxZ))}},t.prototype._createGrainTexture=function(){this._grainTexture=new Ti.a("LensNoiseTexture",512,this._scene,!1,we.a.BILINEAR_SAMPLINGMODE),this._grainTexture.wrapU=we.a.WRAP_ADDRESSMODE,this._grainTexture.wrapV=we.a.WRAP_ADDRESSMODE;for(var e,n,i,o=this._grainTexture.getContext(),a=0;a<512;a++)for(var s=0;s<512;s++)e=Math.floor(255*(n=.42,i=.58,Math.random()*(i-n)+n)),o.fillStyle="rgb("+e+", "+e+", "+e+")",o.fillRect(a,s,1,1);this._grainTexture.update(!1)},t}(Vr),vg=function(){this.enabled=!1,this.name="ssao2",this.texturesRequired=[h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE]},bg=`
-precision highp float;
-uniform sampler2D textureSampler;
-uniform float near;
-uniform float far;
-uniform float radius;
-float scales[16]=float[16](
-0.1,
-0.11406250000000001,
-0.131640625,
-0.15625,
-0.187890625,
-0.2265625,
-0.272265625,
-0.325,
-0.384765625,
-0.4515625,
-0.525390625,
-0.60625,
-0.694140625,
-0.7890625,
-0.891015625,
-1.0
-);
-varying vec2 vUV;
-float perspectiveDepthToViewZ( const in float invClipZ,const in float near,const in float far ) {
-return ( near*far )/( ( far-near )*invClipZ-far );
-}
-float viewZToPerspectiveDepth( const in float viewZ,const in float near,const in float far ) {
-return ( near*far/viewZ+far)/( far-near );
-}
-float viewZToOrthographicDepth( const in float viewZ,const in float near,const in float far ) {
-return ( viewZ+near )/( near-far );
-}
-#ifdef SSAO
-uniform sampler2D randomSampler;
-#ifndef GEOMETRYBUFFER
-uniform sampler2D depthNormalSampler;
-#else
-uniform sampler2D depthSampler;
-uniform sampler2D normalSampler;
-#endif
-uniform float randTextureTiles;
-uniform float samplesFactor;
-uniform vec3 sampleSphere[SAMPLES];
-uniform float totalStrength;
-uniform float base;
-uniform float xViewport;
-uniform float yViewport;
-uniform float maxZ;
-uniform float minZAspect;
-uniform vec2 texelSize;
-uniform mat4 projection;
-void main()
-{
-vec3 random=texture2D(randomSampler,vUV*randTextureTiles).rgb;
-#ifndef GEOMETRYBUFFER
-float depth=texture2D(depthNormalSampler,vUV).r;
-#else
-float depth=texture2D(depthSampler,vUV).r;
-#endif
-float depthSign=depth/abs(depth);
-depth=depth*depthSign;
-#ifndef GEOMETRYBUFFER
-vec3 normal=texture2D(depthNormalSampler,vUV).gba;
-#else
-vec3 normal=texture2D(normalSampler,vUV).rgb;
-#endif
-float occlusion=0.0;
-float correctedRadius=min(radius,minZAspect*depth/near);
-vec3 vViewRay=vec3((vUV.x*2.0-1.0)*xViewport,(vUV.y*2.0-1.0)*yViewport,depthSign);
-vec3 origin=vViewRay*depth;
-vec3 rvec=random*2.0-1.0;
-rvec.z=0.0;
-
-float dotProduct=dot(rvec,normal);
-rvec=1.0-abs(dotProduct)>1e-2 ? rvec : vec3(-rvec.y,0.0,rvec.x);
-vec3 tangent=normalize(rvec-normal*dot(rvec,normal));
-vec3 bitangent=cross(normal,tangent);
-mat3 tbn=mat3(tangent,bitangent,normal);
-float difference;
-for (int i=0; i<SAMPLES; ++i) {
-
-vec3 samplePosition=scales[(i+int(random.x*16.0)) % 16]*tbn*sampleSphere[(i+int(random.y*16.0)) % 16];
-samplePosition=samplePosition*correctedRadius+origin;
-
-vec4 offset=vec4(samplePosition,1.0);
-offset=projection*offset;
-offset.xyz/=offset.w;
-offset.xy=offset.xy*0.5+0.5;
-if (offset.x<0.0 || offset.y<0.0 || offset.x>1.0 || offset.y>1.0) {
-continue;
-}
-
-#ifndef GEOMETRYBUFFER
-float sampleDepth=abs(texture2D(depthNormalSampler,offset.xy).r);
-#else
-float sampleDepth=abs(texture2D(depthSampler,offset.xy).r);
-#endif
-
-difference=depthSign*samplePosition.z-sampleDepth;
-float rangeCheck=1.0-smoothstep(correctedRadius*0.5,correctedRadius,difference);
-occlusion+=(difference>=0.0 ? 1.0 : 0.0)*rangeCheck;
-}
-occlusion=occlusion*(1.0-smoothstep(maxZ*0.75,maxZ,depth));
-float ao=1.0-totalStrength*occlusion*samplesFactor;
-float result=clamp(ao+base,0.0,1.0);
-gl_FragColor=vec4(vec3(result),1.0);
-}
-#endif
-#ifdef BILATERAL_BLUR
-uniform sampler2D depthNormalSampler;
-uniform float outSize;
-uniform float samplerOffsets[SAMPLES];
-vec4 blur9(sampler2D image,vec2 uv,float resolution,vec2 direction) {
-vec4 color=vec4(0.0);
-vec2 off1=vec2(1.3846153846)*direction;
-vec2 off2=vec2(3.2307692308)*direction;
-color+=texture2D(image,uv)*0.2270270270;
-color+=texture2D(image,uv+(off1/resolution))*0.3162162162;
-color+=texture2D(image,uv-(off1/resolution))*0.3162162162;
-color+=texture2D(image,uv+(off2/resolution))*0.0702702703;
-color+=texture2D(image,uv-(off2/resolution))*0.0702702703;
-return color;
-}
-vec4 blur13(sampler2D image,vec2 uv,float resolution,vec2 direction) {
-vec4 color=vec4(0.0);
-vec2 off1=vec2(1.411764705882353)*direction;
-vec2 off2=vec2(3.2941176470588234)*direction;
-vec2 off3=vec2(5.176470588235294)*direction;
-color+=texture2D(image,uv)*0.1964825501511404;
-color+=texture2D(image,uv+(off1/resolution))*0.2969069646728344;
-color+=texture2D(image,uv-(off1/resolution))*0.2969069646728344;
-color+=texture2D(image,uv+(off2/resolution))*0.09447039785044732;
-color+=texture2D(image,uv-(off2/resolution))*0.09447039785044732;
-color+=texture2D(image,uv+(off3/resolution))*0.010381362401148057;
-color+=texture2D(image,uv-(off3/resolution))*0.010381362401148057;
-return color;
-}
-vec4 blur13Bilateral(sampler2D image,vec2 uv,float resolution,vec2 direction) {
-vec4 color=vec4(0.0);
-vec2 off1=vec2(1.411764705882353)*direction;
-vec2 off2=vec2(3.2941176470588234)*direction;
-vec2 off3=vec2(5.176470588235294)*direction;
-float compareDepth=abs(texture2D(depthNormalSampler,uv).r);
-float sampleDepth;
-float weight;
-float weightSum=30.0;
-color+=texture2D(image,uv)*30.0;
-sampleDepth=abs(texture2D(depthNormalSampler,uv+(off1/resolution)).r);
-weight=clamp(1.0/( 0.003+abs(compareDepth-sampleDepth)),0.0,30.0);
-weightSum+=weight;
-color+=texture2D(image,uv+(off1/resolution))*weight;
-sampleDepth=abs(texture2D(depthNormalSampler,uv-(off1/resolution)).r);
-weight=clamp(1.0/( 0.003+abs(compareDepth-sampleDepth)),0.0,30.0);
-weightSum+=weight;
-color+=texture2D(image,uv-(off1/resolution))*weight;
-sampleDepth=abs(texture2D(depthNormalSampler,uv+(off2/resolution)).r);
-weight=clamp(1.0/( 0.003+abs(compareDepth-sampleDepth)),0.0,30.0);
-weightSum+=weight;
-color+=texture2D(image,uv+(off2/resolution))*weight;
-sampleDepth=abs(texture2D(depthNormalSampler,uv-(off2/resolution)).r);
-weight=clamp(1.0/( 0.003+abs(compareDepth-sampleDepth)),0.0,30.0);
-weightSum+=weight;
-color+=texture2D(image,uv-(off2/resolution))*weight;
-sampleDepth=abs(texture2D(depthNormalSampler,uv+(off3/resolution)).r);
-weight=clamp(1.0/( 0.003+abs(compareDepth-sampleDepth)),0.0,30.0);
-weightSum+=weight;
-color+=texture2D(image,uv+(off3/resolution))*weight;
-sampleDepth=abs(texture2D(depthNormalSampler,uv-(off3/resolution)).r);
-weight=clamp(1.0/( 0.003+abs(compareDepth-sampleDepth)),0.0,30.0);
-weightSum+=weight;
-color+=texture2D(image,uv-(off3/resolution))*weight;
-return color/weightSum;
-}
-void main()
-{
-#if EXPENSIVE
-float compareDepth=abs(texture2D(depthNormalSampler,vUV).r);
-float texelsize=1.0/outSize;
-float result=0.0;
-float weightSum=0.0;
-for (int i=0; i<SAMPLES; ++i)
-{
-#ifdef BILATERAL_BLUR_H
-vec2 direction=vec2(1.0,0.0);
-vec2 sampleOffset=vec2(texelsize*samplerOffsets[i],0.0);
-#else
-vec2 direction=vec2(0.0,1.0);
-vec2 sampleOffset=vec2(0.0,texelsize*samplerOffsets[i]);
-#endif
-vec2 samplePos=vUV+sampleOffset;
-float sampleDepth=abs(texture2D(depthNormalSampler,samplePos).r);
-float weight=clamp(1.0/( 0.003+abs(compareDepth-sampleDepth)),0.0,30000.0);
-result+=texture2D(textureSampler,samplePos).r*weight;
-weightSum+=weight;
-}
-result/=weightSum;
-gl_FragColor.rgb=vec3(result);
-gl_FragColor.a=1.0;
-#else
-vec4 color;
-#ifdef BILATERAL_BLUR_H
-vec2 direction=vec2(1.0,0.0);
-color=blur13Bilateral(textureSampler,vUV,outSize,direction);
-#else
-vec2 direction=vec2(0.0,1.0);
-color=blur13Bilateral(textureSampler,vUV,outSize,direction);
-#endif
-gl_FragColor.rgb=vec3(color.r);
-gl_FragColor.a=1.0;
-#endif
-}
-#endif
-`;ze.a.ShadersStore.ssao2PixelShader=bg;var yg=`uniform sampler2D textureSampler;
-uniform sampler2D originalColor;
-uniform vec4 viewport;
-varying vec2 vUV;
-void main(void) {
-vec4 ssaoColor=texture2D(textureSampler,viewport.xy+vUV*viewport.zw);
-vec4 sceneColor=texture2D(originalColor,vUV);
-gl_FragColor=sceneColor*ssaoColor;
-}
-`;ze.a.ShadersStore.ssaoCombinePixelShader=yg;var Gd=function(r){function t(e,n,i,o,a){a===void 0&&(a=!0);var s=r.call(this,n.getEngine(),e)||this;if(s.SSAOOriginalSceneColorEffect="SSAOOriginalSceneColorEffect",s.SSAORenderEffect="SSAORenderEffect",s.SSAOBlurHRenderEffect="SSAOBlurHRenderEffect",s.SSAOBlurVRenderEffect="SSAOBlurVRenderEffect",s.SSAOCombineRenderEffect="SSAOCombineRenderEffect",s.totalStrength=1,s.maxZ=100,s.minZAspect=.2,s._samples=8,s._textureSamples=1,s._forceGeometryBuffer=!1,s._expensiveBlur=!0,s.radius=2,s.base=0,s._bits=new Uint32Array(1),s._scene=n,s._ratio=i,s._forceGeometryBuffer=a,!s.isSupported)return l.a.Error("SSAO 2 needs WebGL 2 support."),s;var d=s._ratio.ssaoRatio||i,p=s._ratio.blurRatio||i;return s._forceGeometryBuffer?n.enableGeometryBufferRenderer():s._prePassRenderer=n.enablePrePassRenderer(),s._createRandomTexture(),s._originalColorPostProcess=new Fi("SSAOOriginalSceneColor",1,null,we.a.BILINEAR_SAMPLINGMODE,n.getEngine(),!1),s._originalColorPostProcess.samples=s.textureSamples,s._createSSAOPostProcess(1),s._createBlurPostProcess(d,p),s._createSSAOCombinePostProcess(p),s.addEffect(new Rt(n.getEngine(),s.SSAOOriginalSceneColorEffect,function(){return s._originalColorPostProcess},!0)),s.addEffect(new Rt(n.getEngine(),s.SSAORenderEffect,function(){return s._ssaoPostProcess},!0)),s.addEffect(new Rt(n.getEngine(),s.SSAOBlurHRenderEffect,function(){return s._blurHPostProcess},!0)),s.addEffect(new Rt(n.getEngine(),s.SSAOBlurVRenderEffect,function(){return s._blurVPostProcess},!0)),s.addEffect(new Rt(n.getEngine(),s.SSAOCombineRenderEffect,function(){return s._ssaoCombinePostProcess},!0)),n.postProcessRenderPipelineManager.addPipeline(s),o&&n.postProcessRenderPipelineManager.attachCamerasToRenderPipeline(e,o),s}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"samples",{get:function(){return this._samples},set:function(e){this._samples=e,this._ssaoPostProcess.updateEffect(this._getDefinesForSSAO()),this._sampleSphere=this._generateHemisphere()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"textureSamples",{get:function(){return this._textureSamples},set:function(e){this._textureSamples=e,this._originalColorPostProcess.samples=e,this._blurHPostProcess.samples=e,this._blurVPostProcess.samples=e,this._ssaoPostProcess.samples=e,this._ssaoCombinePostProcess.samples=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"expensiveBlur",{get:function(){return this._expensiveBlur},set:function(e){this._blurHPostProcess.updateEffect(`#define BILATERAL_BLUR
-#define BILATERAL_BLUR_H
-#define SAMPLES 16
-#define EXPENSIVE `+(e?"1":"0")+`
-`,null,["textureSampler","depthNormalSampler"]),this._blurVPostProcess.updateEffect(`#define BILATERAL_BLUR
-#define SAMPLES 16
-#define EXPENSIVE `+(e?"1":"0")+`
-`,null,["textureSampler","depthNormalSampler"]),this._expensiveBlur=e},enumerable:!1,configurable:!0}),Object.defineProperty(t,"IsSupported",{get:function(){var e=te.a.LastCreatedEngine;return!!e&&e.webGLVersion>=2},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"scene",{get:function(){return this._scene},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"SSAO2RenderingPipeline"},t.prototype.dispose=function(e){e===void 0&&(e=!1);for(var n=0;n<this._scene.cameras.length;n++){var i=this._scene.cameras[n];this._originalColorPostProcess.dispose(i),this._ssaoPostProcess.dispose(i),this._blurHPostProcess.dispose(i),this._blurVPostProcess.dispose(i),this._ssaoCombinePostProcess.dispose(i)}this._randomTexture.dispose(),e&&this._scene.disableGeometryBufferRenderer(),this._scene.postProcessRenderPipelineManager.detachCamerasFromRenderPipeline(this._name,this._scene.cameras),r.prototype.dispose.call(this)},t.prototype._createBlurPostProcess=function(e,n){var i=this;this._samplerOffsets=[];for(var o=this.expensiveBlur,a=-8;a<8;a++)this._samplerOffsets.push(2*a+.5);this._blurHPostProcess=new _t("BlurH","ssao2",["outSize","samplerOffsets","near","far","radius"],["depthNormalSampler"],e,null,we.a.TRILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,`#define BILATERAL_BLUR
-#define BILATERAL_BLUR_H
-#define SAMPLES 16
-#define EXPENSIVE `+(o?"1":"0")+`
-`),this._blurHPostProcess.onApply=function(s){i._scene.activeCamera&&(s.setFloat("outSize",i._ssaoCombinePostProcess.width>0?i._ssaoCombinePostProcess.width:i._originalColorPostProcess.width),s.setFloat("near",i._scene.activeCamera.minZ),s.setFloat("far",i._scene.activeCamera.maxZ),s.setFloat("radius",i.radius),i._forceGeometryBuffer?s.setTexture("depthNormalSampler",i._scene.enableGeometryBufferRenderer().getGBuffer().textures[0]):s.setTexture("depthNormalSampler",i._prePassRenderer.prePassRT.textures[i._prePassRenderer.getIndex(h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE)]),s.setArray("samplerOffsets",i._samplerOffsets))},this._blurVPostProcess=new _t("BlurV","ssao2",["outSize","samplerOffsets","near","far","radius"],["depthNormalSampler"],n,null,we.a.TRILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,`#define BILATERAL_BLUR
-#define BILATERAL_BLUR_V
-#define SAMPLES 16
-#define EXPENSIVE `+(o?"1":"0")+`
-`),this._blurVPostProcess.onApply=function(s){i._scene.activeCamera&&(s.setFloat("outSize",i._ssaoCombinePostProcess.height>0?i._ssaoCombinePostProcess.height:i._originalColorPostProcess.height),s.setFloat("near",i._scene.activeCamera.minZ),s.setFloat("far",i._scene.activeCamera.maxZ),s.setFloat("radius",i.radius),i._forceGeometryBuffer?s.setTexture("depthNormalSampler",i._scene.enableGeometryBufferRenderer().getGBuffer().textures[0]):s.setTexture("depthNormalSampler",i._prePassRenderer.prePassRT.textures[i._prePassRenderer.getIndex(h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE)]),s.setArray("samplerOffsets",i._samplerOffsets))},this._blurHPostProcess.samples=this.textureSamples,this._blurVPostProcess.samples=this.textureSamples},t.prototype._rebuild=function(){r.prototype._rebuild.call(this)},t.prototype._radicalInverse_VdC=function(e){return this._bits[0]=e,this._bits[0]=(this._bits[0]<<16|this._bits[0]>>16)>>>0,this._bits[0]=(1431655765&this._bits[0])<<1|(2863311530&this._bits[0])>>>1>>>0,this._bits[0]=(858993459&this._bits[0])<<2|(3435973836&this._bits[0])>>>2>>>0,this._bits[0]=(252645135&this._bits[0])<<4|(4042322160&this._bits[0])>>>4>>>0,this._bits[0]=(16711935&this._bits[0])<<8|(4278255360&this._bits[0])>>>8>>>0,23283064365386963e-26*this._bits[0]},t.prototype._hammersley=function(e,n){return[e/n,this._radicalInverse_VdC(e)]},t.prototype._hemisphereSample_uniform=function(e,n){var i=2*n*Math.PI,o=1-(.85*e+.15),a=Math.sqrt(1-o*o);return new u.e(Math.cos(i)*a,Math.sin(i)*a,o)},t.prototype._generateHemisphere=function(){for(var e,n=this.samples,i=[],o=0;o<n;){if(n<16)e=this._hemisphereSample_uniform(Math.random(),Math.random());else{var a=this._hammersley(o,n);e=this._hemisphereSample_uniform(a[0],a[1])}i.push(e.x,e.y,e.z),o++}return i},t.prototype._getDefinesForSSAO=function(){var e="#define SAMPLES "+this.samples+`
-#define SSAO`;return this._forceGeometryBuffer&&(e+=`
-#define GEOMETRYBUFFER`),e},t.prototype._createSSAOPostProcess=function(e){var n=this;this._sampleSphere=this._generateHemisphere();var i,o=this._getDefinesForSSAO();i=this._forceGeometryBuffer?["randomSampler","depthSampler","normalSampler"]:["randomSampler","depthNormalSampler"],this._ssaoPostProcess=new _t("ssao2","ssao2",["sampleSphere","samplesFactor","randTextureTiles","totalStrength","radius","base","range","projection","near","far","texelSize","xViewport","yViewport","maxZ","minZAspect"],i,e,null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,o),this._ssaoPostProcess.onApply=function(a){n._scene.activeCamera&&(a.setArray3("sampleSphere",n._sampleSphere),a.setFloat("randTextureTiles",32),a.setFloat("samplesFactor",1/n.samples),a.setFloat("totalStrength",n.totalStrength),a.setFloat2("texelSize",1/n._ssaoPostProcess.width,1/n._ssaoPostProcess.height),a.setFloat("radius",n.radius),a.setFloat("maxZ",n.maxZ),a.setFloat("minZAspect",n.minZAspect),a.setFloat("base",n.base),a.setFloat("near",n._scene.activeCamera.minZ),a.setFloat("far",n._scene.activeCamera.maxZ),a.setFloat("xViewport",Math.tan(n._scene.activeCamera.fov/2)*n._scene.getEngine().getAspectRatio(n._scene.activeCamera,!0)),a.setFloat("yViewport",Math.tan(n._scene.activeCamera.fov/2)),a.setMatrix("projection",n._scene.getProjectionMatrix()),n._forceGeometryBuffer?(a.setTexture("depthSampler",n._scene.enableGeometryBufferRenderer().getGBuffer().textures[0]),a.setTexture("normalSampler",n._scene.enableGeometryBufferRenderer().getGBuffer().textures[1])):a.setTexture("depthNormalSampler",n._prePassRenderer.prePassRT.textures[n._prePassRenderer.getIndex(h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE)]),a.setTexture("randomSampler",n._randomTexture))},this._ssaoPostProcess.samples=this.textureSamples},t.prototype._createSSAOCombinePostProcess=function(e){var n=this;this._ssaoCombinePostProcess=new _t("ssaoCombine","ssaoCombine",[],["originalColor","viewport"],e,null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1),this._ssaoCombinePostProcess.onApply=function(i){var o=n._scene.activeCamera.viewport;i.setVector4("viewport",u.c.Vector4[0].copyFromFloats(o.x,o.y,o.width,o.height)),i.setTextureFromPostProcessOutput("originalColor",n._originalColorPostProcess)},this._ssaoCombinePostProcess.samples=this.textureSamples,this._forceGeometryBuffer||(this._ssaoCombinePostProcess._prePassEffectConfiguration=new vg)},t.prototype._createRandomTexture=function(){this._randomTexture=new Ti.a("SSAORandomTexture",128,this._scene,!1,we.a.TRILINEAR_SAMPLINGMODE),this._randomTexture.wrapU=we.a.WRAP_ADDRESSMODE,this._randomTexture.wrapV=we.a.WRAP_ADDRESSMODE;for(var e=this._randomTexture.getContext(),n=function(s,d){return Math.random()*(d-s)+s},i=u.e.Zero(),o=0;o<128;o++)for(var a=0;a<128;a++)i.x=n(0,1),i.y=n(0,1),i.z=0,i.normalize(),i.scaleInPlace(255),i.x=Math.floor(i.x),i.y=Math.floor(i.y),e.fillStyle="rgb("+i.x+", "+i.y+", "+i.z+")",e.fillRect(o,a,1,1);this._randomTexture.update(!1)},t.prototype.serialize=function(){var e=L.a.Serialize(this);return e.customType="SSAO2RenderingPipeline",e},t.Parse=function(e,n,i){return L.a.Parse(function(){return new t(e._name,n,e._ratio)},e,n,i)},Object(c.c)([Object(L.c)()],t.prototype,"totalStrength",void 0),Object(c.c)([Object(L.c)()],t.prototype,"maxZ",void 0),Object(c.c)([Object(L.c)()],t.prototype,"minZAspect",void 0),Object(c.c)([Object(L.c)("samples")],t.prototype,"_samples",void 0),Object(c.c)([Object(L.c)("textureSamples")],t.prototype,"_textureSamples",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_ratio",void 0),Object(c.c)([Object(L.c)("expensiveBlur")],t.prototype,"_expensiveBlur",void 0),Object(c.c)([Object(L.c)()],t.prototype,"radius",void 0),Object(c.c)([Object(L.c)()],t.prototype,"base",void 0),t}(Vr);R.a.RegisteredTypes["BABYLON.SSAO2RenderingPipeline"]=Gd;var Tg=`
-uniform sampler2D textureSampler;
-varying vec2 vUV;
-#ifdef SSAO
-uniform sampler2D randomSampler;
-uniform float randTextureTiles;
-uniform float samplesFactor;
-uniform vec3 sampleSphere[SAMPLES];
-uniform float totalStrength;
-uniform float radius;
-uniform float area;
-uniform float fallOff;
-uniform float base;
-vec3 normalFromDepth(float depth,vec2 coords)
-{
-vec2 offset1=vec2(0.0,radius);
-vec2 offset2=vec2(radius,0.0);
-float depth1=texture2D(textureSampler,coords+offset1).r;
-float depth2=texture2D(textureSampler,coords+offset2).r;
-vec3 p1=vec3(offset1,depth1-depth);
-vec3 p2=vec3(offset2,depth2-depth);
-vec3 normal=cross(p1,p2);
-normal.z=-normal.z;
-return normalize(normal);
-}
-void main()
-{
-vec3 random=normalize(texture2D(randomSampler,vUV*randTextureTiles).rgb);
-float depth=texture2D(textureSampler,vUV).r;
-vec3 position=vec3(vUV,depth);
-vec3 normal=normalFromDepth(depth,vUV);
-float radiusDepth=radius/depth;
-float occlusion=0.0;
-vec3 ray;
-vec3 hemiRay;
-float occlusionDepth;
-float difference;
-for (int i=0; i<SAMPLES; i++)
-{
-ray=radiusDepth*reflect(sampleSphere[i],random);
-hemiRay=position+sign(dot(ray,normal))*ray;
-occlusionDepth=texture2D(textureSampler,clamp(hemiRay.xy,vec2(0.001,0.001),vec2(0.999,0.999))).r;
-difference=depth-occlusionDepth;
-occlusion+=step(fallOff,difference)*(1.0-smoothstep(fallOff,area,difference));
-}
-float ao=1.0-totalStrength*occlusion*samplesFactor;
-float result=clamp(ao+base,0.0,1.0);
-gl_FragColor.r=result;
-gl_FragColor.g=result;
-gl_FragColor.b=result;
-gl_FragColor.a=1.0;
-}
-#endif
-`;ze.a.ShadersStore.ssaoPixelShader=Tg;var Eg=function(r){function t(e,n,i,o){var a=r.call(this,n.getEngine(),e)||this;a.SSAOOriginalSceneColorEffect="SSAOOriginalSceneColorEffect",a.SSAORenderEffect="SSAORenderEffect",a.SSAOBlurHRenderEffect="SSAOBlurHRenderEffect",a.SSAOBlurVRenderEffect="SSAOBlurVRenderEffect",a.SSAOCombineRenderEffect="SSAOCombineRenderEffect",a.totalStrength=1,a.radius=1e-4,a.area=.0075,a.fallOff=1e-6,a.base=.5,a._firstUpdate=!0,a._scene=n,a._createRandomTexture(),a._depthTexture=n.enableDepthRenderer().getDepthMap();var s=i.ssaoRatio||i,d=i.combineRatio||i;return a._originalColorPostProcess=new Fi("SSAOOriginalSceneColor",d,null,we.a.BILINEAR_SAMPLINGMODE,n.getEngine(),!1),a._createSSAOPostProcess(s),a._createBlurPostProcess(s),a._createSSAOCombinePostProcess(d),a.addEffect(new Rt(n.getEngine(),a.SSAOOriginalSceneColorEffect,function(){return a._originalColorPostProcess},!0)),a.addEffect(new Rt(n.getEngine(),a.SSAORenderEffect,function(){return a._ssaoPostProcess},!0)),a.addEffect(new Rt(n.getEngine(),a.SSAOBlurHRenderEffect,function(){return a._blurHPostProcess},!0)),a.addEffect(new Rt(n.getEngine(),a.SSAOBlurVRenderEffect,function(){return a._blurVPostProcess},!0)),a.addEffect(new Rt(n.getEngine(),a.SSAOCombineRenderEffect,function(){return a._ssaoCombinePostProcess},!0)),n.postProcessRenderPipelineManager.addPipeline(a),o&&n.postProcessRenderPipelineManager.attachCamerasToRenderPipeline(e,o),a}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"scene",{get:function(){return this._scene},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"SSAORenderingPipeline"},t.prototype.dispose=function(e){e===void 0&&(e=!1);for(var n=0;n<this._scene.cameras.length;n++){var i=this._scene.cameras[n];this._originalColorPostProcess.dispose(i),this._ssaoPostProcess.dispose(i),this._blurHPostProcess.dispose(i),this._blurVPostProcess.dispose(i),this._ssaoCombinePostProcess.dispose(i)}this._randomTexture.dispose(),e&&this._scene.disableDepthRenderer(),this._scene.postProcessRenderPipelineManager.detachCamerasFromRenderPipeline(this._name,this._scene.cameras),r.prototype.dispose.call(this)},t.prototype._createBlurPostProcess=function(e){var n=this;this._blurHPostProcess=new gn("BlurH",new u.d(1,0),16,e,null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,h.a.TEXTURETYPE_UNSIGNED_INT),this._blurVPostProcess=new gn("BlurV",new u.d(0,1),16,e,null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,h.a.TEXTURETYPE_UNSIGNED_INT),this._blurHPostProcess.onActivateObservable.add(function(){var i=n._blurHPostProcess.width/n._scene.getEngine().getRenderWidth();n._blurHPostProcess.kernel=16*i}),this._blurVPostProcess.onActivateObservable.add(function(){var i=n._blurVPostProcess.height/n._scene.getEngine().getRenderHeight();n._blurVPostProcess.kernel=16*i})},t.prototype._rebuild=function(){this._firstUpdate=!0,r.prototype._rebuild.call(this)},t.prototype._createSSAOPostProcess=function(e){var n=this,i=[.5381,.1856,-.4319,.1379,.2486,.443,.3371,.5679,-.0057,-.6999,-.0451,-.0019,.0689,-.1598,-.8547,.056,.0069,-.1843,-.0146,.1402,.0762,.01,-.1924,-.0344,-.3577,-.5301,-.4358,-.3169,.1063,.0158,.0103,-.5869,.0046,-.0897,-.494,.3287,.7119,-.0154,-.0918,-.0533,.0596,-.5411,.0352,-.0631,.546,-.4776,.2847,-.0271];this._ssaoPostProcess=new _t("ssao","ssao",["sampleSphere","samplesFactor","randTextureTiles","totalStrength","radius","area","fallOff","base","range","viewport"],["randomSampler"],e,null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,`#define SAMPLES 16
-#define SSAO`),this._ssaoPostProcess.onApply=function(o){n._firstUpdate&&(o.setArray3("sampleSphere",i),o.setFloat("samplesFactor",1/16),o.setFloat("randTextureTiles",4)),o.setFloat("totalStrength",n.totalStrength),o.setFloat("radius",n.radius),o.setFloat("area",n.area),o.setFloat("fallOff",n.fallOff),o.setFloat("base",n.base),o.setTexture("textureSampler",n._depthTexture),o.setTexture("randomSampler",n._randomTexture)}},t.prototype._createSSAOCombinePostProcess=function(e){var n=this;this._ssaoCombinePostProcess=new _t("ssaoCombine","ssaoCombine",[],["originalColor","viewport"],e,null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1),this._ssaoCombinePostProcess.onApply=function(i){i.setVector4("viewport",u.c.Vector4[0].copyFromFloats(0,0,1,1)),i.setTextureFromPostProcess("originalColor",n._originalColorPostProcess)}},t.prototype._createRandomTexture=function(){this._randomTexture=new Ti.a("SSAORandomTexture",512,this._scene,!1,we.a.TRILINEAR_SAMPLINGMODE),this._randomTexture.wrapU=we.a.WRAP_ADDRESSMODE,this._randomTexture.wrapV=we.a.WRAP_ADDRESSMODE;for(var e=this._randomTexture.getContext(),n=function(s,d){return Math.random()*(d-s)+s},i=u.e.Zero(),o=0;o<512;o++)for(var a=0;a<512;a++)i.x=Math.floor(255*n(-1,1)),i.y=Math.floor(255*n(-1,1)),i.z=Math.floor(255*n(-1,1)),e.fillStyle="rgb("+i.x+", "+i.y+", "+i.z+")",e.fillRect(o,a,1,1);this._randomTexture.update(!1)},Object(c.c)([Object(L.c)()],t.prototype,"totalStrength",void 0),Object(c.c)([Object(L.c)()],t.prototype,"radius",void 0),Object(c.c)([Object(L.c)()],t.prototype,"area",void 0),Object(c.c)([Object(L.c)()],t.prototype,"fallOff",void 0),Object(c.c)([Object(L.c)()],t.prototype,"base",void 0),t}(Vr),Sg=function(){this.enabled=!1,this.name="screenSpaceReflections",this.texturesRequired=[h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE,h.a.PREPASS_REFLECTIVITY_TEXTURE_TYPE,h.a.PREPASS_POSITION_TEXTURE_TYPE]},Ag=`
-
-uniform sampler2D textureSampler;
-uniform sampler2D normalSampler;
-uniform sampler2D positionSampler;
-uniform sampler2D reflectivitySampler;
-uniform mat4 view;
-uniform mat4 projection;
-uniform float step;
-uniform float strength;
-uniform float threshold;
-uniform float roughnessFactor;
-uniform float reflectionSpecularFalloffExponent;
-
-varying vec2 vUV;
-
-struct ReflectionInfo {
-vec3 color;
-vec4 coords;
-};
-
-vec3 fresnelSchlick(float cosTheta,vec3 F0)
-{
-return F0+(1.0-F0)*pow(1.0-cosTheta,5.0);
-}
-
-ReflectionInfo smoothReflectionInfo(vec3 dir,vec3 hitCoord)
-{
-ReflectionInfo info;
-info.color=vec3(0.0);
-vec4 projectedCoord;
-float sampledDepth;
-for(int i=0; i<SMOOTH_STEPS; i++)
-{
-projectedCoord=projection*vec4(hitCoord,1.0);
-projectedCoord.xy/=projectedCoord.w;
-projectedCoord.xy=0.5*projectedCoord.xy+vec2(0.5);
-sampledDepth=(view*texture2D(positionSampler,projectedCoord.xy)).z;
-float depth=sampledDepth-hitCoord.z;
-dir*=0.5;
-if(depth>0.0)
-hitCoord-=dir;
-else
-hitCoord+=dir;
-info.color+=texture2D(textureSampler,projectedCoord.xy).rgb;
-}
-projectedCoord=projection*vec4(hitCoord,1.0);
-projectedCoord.xy/=projectedCoord.w;
-projectedCoord.xy=0.5*projectedCoord.xy+vec2(0.5);
-
-info.coords=vec4(projectedCoord.xy,sampledDepth,1.0);
-info.color+=texture2D(textureSampler,projectedCoord.xy).rgb;
-info.color/=float(SMOOTH_STEPS+1);
-return info;
-}
-
-ReflectionInfo getReflectionInfo(vec3 dir,vec3 hitCoord)
-{
-ReflectionInfo info;
-vec4 projectedCoord;
-float sampledDepth;
-dir*=step;
-for(int i=0; i<REFLECTION_SAMPLES; i++)
-{
-hitCoord+=dir;
-projectedCoord=projection*vec4(hitCoord,1.0);
-projectedCoord.xy/=projectedCoord.w;
-projectedCoord.xy=0.5*projectedCoord.xy+vec2(0.5);
-sampledDepth=(view*texture2D(positionSampler,projectedCoord.xy)).z;
-float depth=sampledDepth-hitCoord.z;
-if(((depth-dir.z)<threshold) && depth<=0.0)
-{
-#ifdef ENABLE_SMOOTH_REFLECTIONS
-return smoothReflectionInfo(dir,hitCoord);
-#else
-info.color=texture2D(textureSampler,projectedCoord.xy).rgb;
-info.coords=vec4(projectedCoord.xy,sampledDepth,0.0);
-return info;
-#endif
-}
-}
-info.color=texture2D(textureSampler,projectedCoord.xy).rgb;
-info.coords=vec4(projectedCoord.xy,sampledDepth,0.0);
-return info;
-}
-vec3 hash(vec3 a)
-{
-a=fract(a*0.8);
-a+=dot(a,a.yxz+19.19);
-return fract((a.xxy+a.yxx)*a.zyx);
-}
-void main()
-{
-#ifdef SSR_SUPPORTED
-
-vec4 albedoFull=texture2D(textureSampler,vUV);
-vec3 albedo=albedoFull.rgb;
-float spec=texture2D(reflectivitySampler,vUV).r;
-if (spec == 0.0) {
-gl_FragColor=albedoFull;
-return;
-}
-
-#ifdef PREPASS_LAYOUT
-vec3 normal=(texture2D(normalSampler,vUV)).gba;
-#else
-vec3 normal=(texture2D(normalSampler,vUV)).xyz;
-#endif
-vec3 position=(view*texture2D(positionSampler,vUV)).xyz;
-vec3 reflected=normalize(reflect(normalize(position),normalize(normal)));
-float roughness=1.0-texture2D(reflectivitySampler,vUV).a;
-vec3 jitt=mix(vec3(0.0),hash(position),roughness)*roughnessFactor;
-ReflectionInfo info=getReflectionInfo(jitt+reflected,position);
-
-vec2 dCoords=smoothstep(0.2,0.6,abs(vec2(0.5,0.5)-info.coords.xy));
-float screenEdgefactor=clamp(1.0-(dCoords.x+dCoords.y),0.0,1.0);
-
-vec3 F0=vec3(0.04);
-F0=mix(F0,albedo,spec);
-vec3 fresnel=fresnelSchlick(max(dot(normalize(normal),normalize(position)),0.0),F0);
-
-float reflectionMultiplier=clamp(pow(spec*strength,reflectionSpecularFalloffExponent)*screenEdgefactor*reflected.z,0.0,0.9);
-float albedoMultiplier=1.0-reflectionMultiplier;
-vec3 SSR=info.color*fresnel;
-gl_FragColor=vec4((albedo*albedoMultiplier)+(SSR*reflectionMultiplier),albedoFull.a);
-#else
-gl_FragColor=texture2D(textureSampler,vUV);
-#endif
-}
-`;ze.a.ShadersStore.screenSpaceReflectionPixelShader=Ag;var jc=function(r){function t(e,n,i,o,a,s,d,p,b,P){p===void 0&&(p=h.a.TEXTURETYPE_UNSIGNED_INT),b===void 0&&(b=!1),P===void 0&&(P=!0);var O=r.call(this,e,"screenSpaceReflection",["projection","view","threshold","reflectionSpecularFalloffExponent","strength","step","roughnessFactor"],["textureSampler","normalSampler","positionSampler","reflectivitySampler"],i,o,a,s,d,`#define SSR_SUPPORTED
-#define REFLECTION_SAMPLES 64
-#define SMOOTH_STEPS 5
-`,p,void 0,null,b)||this;if(O.threshold=1.2,O.strength=1,O.reflectionSpecularFalloffExponent=3,O.step=1,O.roughnessFactor=.2,O._forceGeometryBuffer=!1,O._enableSmoothReflections=!1,O._reflectionSamples=64,O._smoothSteps=5,O._forceGeometryBuffer=P,O._forceGeometryBuffer){var B=n.enableGeometryBufferRenderer();B&&B.isSupported&&(B.enablePosition=!0,B.enableReflectivity=!0,O._geometryBufferRenderer=B)}else O._prePassRenderer=n.enablePrePassRenderer(),O._prePassRenderer.markAsDirty(),O._prePassEffectConfiguration=new Sg;return O._updateEffectDefines(),O.onApply=function(F){var z=O._geometryBufferRenderer,J=O._prePassRenderer;if(J||z){if(z){var ie=z.getTextureIndex(ui.POSITION_TEXTURE_TYPE),se=z.getTextureIndex(ui.REFLECTIVITY_TEXTURE_TYPE);F.setTexture("normalSampler",z.getGBuffer().textures[1]),F.setTexture("positionSampler",z.getGBuffer().textures[ie]),F.setTexture("reflectivitySampler",z.getGBuffer().textures[se])}else{ie=J.getIndex(h.a.PREPASS_POSITION_TEXTURE_TYPE),se=J.getIndex(h.a.PREPASS_REFLECTIVITY_TEXTURE_TYPE);var ce=J.getIndex(h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE);F.setTexture("normalSampler",J.prePassRT.textures[ce]),F.setTexture("positionSampler",J.prePassRT.textures[ie]),F.setTexture("reflectivitySampler",J.prePassRT.textures[se])}var ue=n.activeCamera;if(ue){var fe=ue.getViewMatrix(),ve=ue.getProjectionMatrix();F.setMatrix("projection",ve),F.setMatrix("view",fe),F.setFloat("threshold",O.threshold),F.setFloat("reflectionSpecularFalloffExponent",O.reflectionSpecularFalloffExponent),F.setFloat("strength",O.strength),F.setFloat("step",O.step),F.setFloat("roughnessFactor",O.roughnessFactor)}}},O}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ScreenSpaceReflectionPostProcess"},Object.defineProperty(t.prototype,"enableSmoothReflections",{get:function(){return this._enableSmoothReflections},set:function(e){e!==this._enableSmoothReflections&&(this._enableSmoothReflections=e,this._updateEffectDefines())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"reflectionSamples",{get:function(){return this._reflectionSamples},set:function(e){e!==this._reflectionSamples&&(this._reflectionSamples=e,this._updateEffectDefines())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"smoothSteps",{get:function(){return this._smoothSteps},set:function(e){e!==this._smoothSteps&&(this._smoothSteps=e,this._updateEffectDefines())},enumerable:!1,configurable:!0}),t.prototype._updateEffectDefines=function(){var e=[];(this._geometryBufferRenderer||this._prePassRenderer)&&(e.push("#define SSR_SUPPORTED"),this._prePassRenderer&&e.push("#define PREPASS_LAYOUT")),this._enableSmoothReflections&&e.push("#define ENABLE_SMOOTH_REFLECTIONS"),e.push("#define REFLECTION_SAMPLES "+(this._reflectionSamples>>0)),e.push("#define SMOOTH_STEPS "+(this._smoothSteps>>0)),this.updateEffect(e.join(`
-`))},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,i,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.textureType,e.reusable)},e,i,o)},Object(c.c)([Object(L.c)()],t.prototype,"threshold",void 0),Object(c.c)([Object(L.c)()],t.prototype,"strength",void 0),Object(c.c)([Object(L.c)()],t.prototype,"reflectionSpecularFalloffExponent",void 0),Object(c.c)([Object(L.c)()],t.prototype,"step",void 0),Object(c.c)([Object(L.c)()],t.prototype,"roughnessFactor",void 0),Object(c.c)([Object(L.c)()],t.prototype,"enableSmoothReflections",null),Object(c.c)([Object(L.c)()],t.prototype,"reflectionSamples",null),Object(c.c)([Object(L.c)()],t.prototype,"smoothSteps",null),t}(_t);R.a.RegisteredTypes["BABYLON.ScreenSpaceReflectionPostProcess"]=jc;var Pg=`uniform sampler2D textureSampler;
-varying vec2 vUV;
-#if defined(PASS_POST_PROCESS)
-void main(void)
-{
-vec4 color=texture2D(textureSampler,vUV);
-gl_FragColor=color;
-}
-#endif
-#if defined(DOWN_SAMPLE_X4)
-uniform vec2 dsOffsets[16];
-void main(void)
-{
-vec4 average=vec4(0.0,0.0,0.0,0.0);
-average=texture2D(textureSampler,vUV+dsOffsets[0]);
-average+=texture2D(textureSampler,vUV+dsOffsets[1]);
-average+=texture2D(textureSampler,vUV+dsOffsets[2]);
-average+=texture2D(textureSampler,vUV+dsOffsets[3]);
-average+=texture2D(textureSampler,vUV+dsOffsets[4]);
-average+=texture2D(textureSampler,vUV+dsOffsets[5]);
-average+=texture2D(textureSampler,vUV+dsOffsets[6]);
-average+=texture2D(textureSampler,vUV+dsOffsets[7]);
-average+=texture2D(textureSampler,vUV+dsOffsets[8]);
-average+=texture2D(textureSampler,vUV+dsOffsets[9]);
-average+=texture2D(textureSampler,vUV+dsOffsets[10]);
-average+=texture2D(textureSampler,vUV+dsOffsets[11]);
-average+=texture2D(textureSampler,vUV+dsOffsets[12]);
-average+=texture2D(textureSampler,vUV+dsOffsets[13]);
-average+=texture2D(textureSampler,vUV+dsOffsets[14]);
-average+=texture2D(textureSampler,vUV+dsOffsets[15]);
-average/=16.0;
-gl_FragColor=average;
-}
-#endif
-#if defined(BRIGHT_PASS)
-uniform vec2 dsOffsets[4];
-uniform float brightThreshold;
-void main(void)
-{
-vec4 average=vec4(0.0,0.0,0.0,0.0);
-average=texture2D(textureSampler,vUV+vec2(dsOffsets[0].x,dsOffsets[0].y));
-average+=texture2D(textureSampler,vUV+vec2(dsOffsets[1].x,dsOffsets[1].y));
-average+=texture2D(textureSampler,vUV+vec2(dsOffsets[2].x,dsOffsets[2].y));
-average+=texture2D(textureSampler,vUV+vec2(dsOffsets[3].x,dsOffsets[3].y));
-average*=0.25;
-float luminance=length(average.rgb);
-if (luminance<brightThreshold) {
-average=vec4(0.0,0.0,0.0,1.0);
-}
-gl_FragColor=average;
-}
-#endif
-#if defined(TEXTURE_ADDER)
-uniform sampler2D otherSampler;
-uniform sampler2D lensSampler;
-uniform float exposure;
-void main(void)
-{
-vec3 colour=texture2D(textureSampler,vUV).rgb;
-colour*=exposure;
-vec3 X=max(vec3(0.0,0.0,0.0),colour-0.004);
-vec3 retColor=(X*(6.2*X+0.5))/(X*(6.2*X+1.7)+0.06);
-colour=retColor*retColor;
-colour+=colour*texture2D(lensSampler,vUV).rgb;
-vec4 finalColor=vec4(colour.rgb,1.0)+texture2D(otherSampler,vUV);
-gl_FragColor=finalColor;
-}
-#endif
-#if defined(VLS)
-#define PI 3.1415926535897932384626433832795
-uniform mat4 shadowViewProjection;
-uniform mat4 lightWorld;
-uniform vec3 cameraPosition;
-uniform vec3 sunDirection;
-uniform vec3 sunColor;
-uniform vec2 depthValues;
-uniform float scatteringCoefficient;
-uniform float scatteringPower;
-uniform sampler2D shadowMapSampler;
-uniform sampler2D positionSampler;
-float computeScattering(float lightDotView)
-{
-float result=1.0-scatteringCoefficient*scatteringCoefficient;
-result/=(4.0*PI*pow(1.0+scatteringCoefficient*scatteringCoefficient-(2.0*scatteringCoefficient)*lightDotView,1.5));
-return result;
-}
-void main(void)
-{
-
-vec3 worldPos=texture2D(positionSampler,vUV).rgb;
-vec3 startPosition=cameraPosition;
-vec3 rayVector=worldPos-startPosition;
-float rayLength=length(rayVector);
-vec3 rayDirection=rayVector/rayLength;
-float stepLength=rayLength/NB_STEPS;
-vec3 stepL=rayDirection*stepLength;
-vec3 currentPosition=startPosition;
-vec3 accumFog=vec3(0.0);
-for (int i=0; i<int(NB_STEPS); i++)
-{
-vec4 worldInShadowCameraSpace=shadowViewProjection*vec4(currentPosition,1.0);
-float depthMetric=(worldInShadowCameraSpace.z+depthValues.x)/(depthValues.y);
-float shadowPixelDepth=clamp(depthMetric,0.0,1.0);
-worldInShadowCameraSpace.xyz/=worldInShadowCameraSpace.w;
-worldInShadowCameraSpace.xyz=0.5*worldInShadowCameraSpace.xyz+vec3(0.5);
-float shadowMapValue=texture2D(shadowMapSampler,worldInShadowCameraSpace.xy).r;
-if (shadowMapValue>shadowPixelDepth)
-accumFog+=sunColor*computeScattering(dot(rayDirection,sunDirection));
-currentPosition+=stepL;
-}
-accumFog/=NB_STEPS;
-vec3 color=accumFog*scatteringPower;
-gl_FragColor=vec4(color*exp(color) ,1.0);
-}
-#endif
-#if defined(VLSMERGE)
-uniform sampler2D originalSampler;
-void main(void)
-{
-gl_FragColor=texture2D(originalSampler,vUV)+texture2D(textureSampler,vUV);
-}
-#endif
-#if defined(LUMINANCE)
-uniform vec2 lumOffsets[4];
-void main()
-{
-float average=0.0;
-vec4 color=vec4(0.0);
-float maximum=-1e20;
-vec3 weight=vec3(0.299,0.587,0.114);
-for (int i=0; i<4; i++)
-{
-color=texture2D(textureSampler,vUV+ lumOffsets[i]);
-
-float GreyValue=dot(color.rgb,vec3(0.33,0.33,0.33));
-
-#ifdef WEIGHTED_AVERAGE
-float GreyValue=dot(color.rgb,weight);
-#endif
-#ifdef BRIGHTNESS
-float GreyValue=max(color.r,max(color.g,color.b));
-#endif
-#ifdef HSL_COMPONENT
-float GreyValue=0.5*(max(color.r,max(color.g,color.b))+min(color.r,min(color.g,color.b)));
-#endif
-#ifdef MAGNITUDE
-float GreyValue=length(color.rgb);
-#endif
-maximum=max(maximum,GreyValue);
-average+=(0.25*log(1e-5+GreyValue));
-}
-average=exp(average);
-gl_FragColor=vec4(average,maximum,0.0,1.0);
-}
-#endif
-#if defined(LUMINANCE_DOWN_SAMPLE)
-uniform vec2 dsOffsets[9];
-uniform float halfDestPixelSize;
-#ifdef FINAL_DOWN_SAMPLER
-#include<packingFunctions>
-#endif
-void main()
-{
-vec4 color=vec4(0.0);
-float average=0.0;
-for (int i=0; i<9; i++)
-{
-color=texture2D(textureSampler,vUV+vec2(halfDestPixelSize,halfDestPixelSize)+dsOffsets[i]);
-average+=color.r;
-}
-average/=9.0;
-#ifdef FINAL_DOWN_SAMPLER
-gl_FragColor=pack(average);
-#else
-gl_FragColor=vec4(average,average,0.0,1.0);
-#endif
-}
-#endif
-#if defined(HDR)
-uniform sampler2D textureAdderSampler;
-uniform float averageLuminance;
-void main()
-{
-vec4 color=texture2D(textureAdderSampler,vUV);
-#ifndef AUTO_EXPOSURE
-vec4 adjustedColor=color/averageLuminance;
-color=adjustedColor;
-color.a=1.0;
-#endif
-gl_FragColor=color;
-}
-#endif
-#if defined(LENS_FLARE)
-#define GHOSTS 3
-uniform sampler2D lensColorSampler;
-uniform float strength;
-uniform float ghostDispersal;
-uniform float haloWidth;
-uniform vec2 resolution;
-uniform float distortionStrength;
-float hash(vec2 p)
-{
-float h=dot(p,vec2(127.1,311.7));
-return -1.0+2.0*fract(sin(h)*43758.5453123);
-}
-float noise(in vec2 p)
-{
-vec2 i=floor(p);
-vec2 f=fract(p);
-vec2 u=f*f*(3.0-2.0*f);
-return mix(mix(hash(i+vec2(0.0,0.0)),
-hash(i+vec2(1.0,0.0)),u.x),
-mix(hash(i+vec2(0.0,1.0)),
-hash(i+vec2(1.0,1.0)),u.x),u.y);
-}
-float fbm(vec2 p)
-{
-float f=0.0;
-f+=0.5000*noise(p); p*=2.02;
-f+=0.2500*noise(p); p*=2.03;
-f+=0.1250*noise(p); p*=2.01;
-f+=0.0625*noise(p); p*=2.04;
-f/=0.9375;
-return f;
-}
-vec3 pattern(vec2 uv)
-{
-vec2 p=-1.0+2.0*uv;
-float p2=dot(p,p);
-float f=fbm(vec2(15.0*p2))/2.0;
-float r=0.2+0.6*sin(12.5*length(uv-vec2(0.5)));
-float g=0.2+0.6*sin(20.5*length(uv-vec2(0.5)));
-float b=0.2+0.6*sin(17.2*length(uv-vec2(0.5)));
-return (1.0-f)*vec3(r,g,b);
-}
-float luminance(vec3 color)
-{
-return dot(color.rgb,vec3(0.2126,0.7152,0.0722));
-}
-vec4 textureDistorted(sampler2D tex,vec2 texcoord,vec2 direction,vec3 distortion)
-{
-return vec4(
-texture2D(tex,texcoord+direction*distortion.r).r,
-texture2D(tex,texcoord+direction*distortion.g).g,
-texture2D(tex,texcoord+direction*distortion.b).b,
-1.0
-);
-}
-void main(void)
-{
-vec2 uv=-vUV+vec2(1.0);
-vec2 ghostDir=(vec2(0.5)-uv)*ghostDispersal;
-vec2 texelSize=1.0/resolution;
-vec3 distortion=vec3(-texelSize.x*distortionStrength,0.0,texelSize.x*distortionStrength);
-vec4 result=vec4(0.0);
-float ghostIndice=1.0;
-for (int i=0; i<GHOSTS; ++i)
-{
-vec2 offset=fract(uv+ghostDir*ghostIndice);
-float weight=length(vec2(0.5)-offset)/length(vec2(0.5));
-weight=pow(1.0-weight,10.0);
-result+=textureDistorted(textureSampler,offset,normalize(ghostDir),distortion)*weight*strength;
-ghostIndice+=1.0;
-}
-vec2 haloVec=normalize(ghostDir)*haloWidth;
-float weight=length(vec2(0.5)-fract(uv+haloVec))/length(vec2(0.5));
-weight=pow(1.0-weight,10.0);
-result+=textureDistorted(textureSampler,fract(uv+haloVec),normalize(ghostDir),distortion)*weight*strength;
-result*=texture2D(lensColorSampler,vec2(length(vec2(0.5)-uv)/length(vec2(0.5))));
-gl_FragColor=result;
-}
-#endif
-#if defined(LENS_FLARE_COMPOSE)
-uniform sampler2D otherSampler;
-uniform sampler2D lensDirtSampler;
-uniform sampler2D lensStarSampler;
-uniform mat4 lensStarMatrix;
-void main(void)
-{
-vec2 lensFlareCoords=(lensStarMatrix*vec4(vUV,1.0,1.0)).xy;
-vec4 lensMod=texture2D(lensDirtSampler,vUV);
-lensMod+=texture2D(lensStarSampler,vUV);
-vec4 result=texture2D(textureSampler,vUV)*lensMod;
-gl_FragColor=texture2D(otherSampler,vUV)+result;
-}
-#endif
-#if defined(DEPTH_OF_FIELD)
-uniform sampler2D otherSampler;
-uniform sampler2D depthSampler;
-uniform float distance;
-void main(void)
-{
-vec4 sharp=texture2D(otherSampler,vUV);
-vec4 blur=texture2D(textureSampler,vUV);
-float dist=clamp(texture2D(depthSampler,vUV).r*distance,0.0,1.0);
-float factor=0.0;
-if (dist<0.05)
-factor=1.0;
-else if (dist<0.1)
-factor=20.0*(0.1-dist);
-else if (dist<0.5)
-factor=0.0;
-else
-factor=2.0*(dist-0.5);
-factor=clamp(factor,0.0,0.90);
-gl_FragColor=mix(sharp,blur,factor);
-}
-#endif
-#if defined(MOTION_BLUR)
-uniform mat4 inverseViewProjection;
-uniform mat4 prevViewProjection;
-uniform vec2 screenSize;
-uniform float motionScale;
-uniform float motionStrength;
-uniform sampler2D depthSampler;
-void main(void)
-{
-vec2 texelSize=1.0/screenSize;
-float depth=texture2D(depthSampler,vUV).r;
-vec4 cpos=vec4(vUV*2.0-1.0,depth,1.0);
-cpos=cpos*inverseViewProjection;
-vec4 ppos=cpos*prevViewProjection;
-ppos.xyz/=ppos.w;
-ppos.xy=ppos.xy*0.5+0.5;
-vec2 velocity=(ppos.xy-vUV)*motionScale*motionStrength;
-float speed=length(velocity/texelSize);
-int nSamples=int(clamp(speed,1.0,MAX_MOTION_SAMPLES));
-vec4 result=texture2D(textureSampler,vUV);
-for (int i=1; i<int(MAX_MOTION_SAMPLES); ++i) {
-if (i>=nSamples)
-break;
-vec2 offset1=vUV+velocity*(float(i)/float(nSamples-1)-0.5);
-result+=texture2D(textureSampler,offset1);
-}
-gl_FragColor=result/float(nSamples);
-}
-#endif
-`;ze.a.ShadersStore.standardPixelShader=Pg;var zd=function(r){function t(e,n,i,o,a){o===void 0&&(o=null);var s=r.call(this,n.getEngine(),e)||this;return s.downSampleX4PostProcess=null,s.brightPassPostProcess=null,s.blurHPostProcesses=[],s.blurVPostProcesses=[],s.textureAdderPostProcess=null,s.volumetricLightPostProcess=null,s.volumetricLightSmoothXPostProcess=null,s.volumetricLightSmoothYPostProcess=null,s.volumetricLightMergePostProces=null,s.volumetricLightFinalPostProcess=null,s.luminancePostProcess=null,s.luminanceDownSamplePostProcesses=[],s.hdrPostProcess=null,s.textureAdderFinalPostProcess=null,s.lensFlareFinalPostProcess=null,s.hdrFinalPostProcess=null,s.lensFlarePostProcess=null,s.lensFlareComposePostProcess=null,s.motionBlurPostProcess=null,s.depthOfFieldPostProcess=null,s.fxaaPostProcess=null,s.screenSpaceReflectionPostProcess=null,s.brightThreshold=1,s.blurWidth=512,s.horizontalBlur=!1,s.lensTexture=null,s.volumetricLightCoefficient=.2,s.volumetricLightPower=4,s.volumetricLightBlurScale=64,s.sourceLight=null,s.hdrMinimumLuminance=1,s.hdrDecreaseRate=.5,s.hdrIncreaseRate=.5,s.lensColorTexture=null,s.lensFlareStrength=20,s.lensFlareGhostDispersal=1.4,s.lensFlareHaloWidth=.7,s.lensFlareDistortionStrength=16,s.lensFlareBlurWidth=512,s.lensStarTexture=null,s.lensFlareDirtTexture=null,s.depthOfFieldDistance=10,s.depthOfFieldBlurWidth=64,s.animations=[],s._currentDepthOfFieldSource=null,s._fixedExposure=1,s._currentExposure=1,s._hdrAutoExposure=!1,s._hdrCurrentLuminance=1,s._motionStrength=1,s._isObjectBasedMotionBlur=!1,s._camerasToBeAttached=[],s._bloomEnabled=!1,s._depthOfFieldEnabled=!1,s._vlsEnabled=!1,s._lensFlareEnabled=!1,s._hdrEnabled=!1,s._motionBlurEnabled=!1,s._fxaaEnabled=!1,s._screenSpaceReflectionsEnabled=!1,s._motionBlurSamples=64,s._volumetricLightStepsCount=50,s._samples=1,s._cameras=a||n.cameras,s._cameras=s._cameras.slice(),s._camerasToBeAttached=s._cameras.slice(),s._scene=n,s._basePostProcess=o,s._ratio=i,s._floatTextureType=n.getEngine().getCaps().textureFloatRender?h.a.TEXTURETYPE_FLOAT:h.a.TEXTURETYPE_HALF_FLOAT,n.postProcessRenderPipelineManager.addPipeline(s),s._buildPipeline(),s}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"exposure",{get:function(){return this._fixedExposure},set:function(e){this._fixedExposure=e,this._currentExposure=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"hdrAutoExposure",{get:function(){return this._hdrAutoExposure},set:function(e){if(this._hdrAutoExposure=e,this.hdrPostProcess){var n=["#define HDR"];e&&n.push("#define AUTO_EXPOSURE"),this.hdrPostProcess.updateEffect(n.join(`
-`))}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"motionStrength",{get:function(){return this._motionStrength},set:function(e){this._motionStrength=e,this._isObjectBasedMotionBlur&&this.motionBlurPostProcess&&(this.motionBlurPostProcess.motionStrength=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"objectBasedMotionBlur",{get:function(){return this._isObjectBasedMotionBlur},set:function(e){var n=this._isObjectBasedMotionBlur!==e;this._isObjectBasedMotionBlur=e,n&&this._buildPipeline()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"BloomEnabled",{get:function(){return this._bloomEnabled},set:function(e){this._bloomEnabled!==e&&(this._bloomEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"DepthOfFieldEnabled",{get:function(){return this._depthOfFieldEnabled},set:function(e){this._depthOfFieldEnabled!==e&&(this._depthOfFieldEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"LensFlareEnabled",{get:function(){return this._lensFlareEnabled},set:function(e){this._lensFlareEnabled!==e&&(this._lensFlareEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"HDREnabled",{get:function(){return this._hdrEnabled},set:function(e){this._hdrEnabled!==e&&(this._hdrEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"VLSEnabled",{get:function(){return this._vlsEnabled},set:function(e){if(this._vlsEnabled!==e){if(e&&!this._scene.enableGeometryBufferRenderer())return void l.a.Warn("Geometry renderer is not supported, cannot create volumetric lights in Standard Rendering Pipeline");this._vlsEnabled=e,this._buildPipeline()}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"MotionBlurEnabled",{get:function(){return this._motionBlurEnabled},set:function(e){this._motionBlurEnabled!==e&&(this._motionBlurEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"fxaaEnabled",{get:function(){return this._fxaaEnabled},set:function(e){this._fxaaEnabled!==e&&(this._fxaaEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"screenSpaceReflectionsEnabled",{get:function(){return this._screenSpaceReflectionsEnabled},set:function(e){this._screenSpaceReflectionsEnabled!==e&&(this._screenSpaceReflectionsEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"volumetricLightStepsCount",{get:function(){return this._volumetricLightStepsCount},set:function(e){this.volumetricLightPostProcess&&this.volumetricLightPostProcess.updateEffect(`#define VLS
-#define NB_STEPS `+e.toFixed(1)),this._volumetricLightStepsCount=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"motionBlurSamples",{get:function(){return this._motionBlurSamples},set:function(e){this.motionBlurPostProcess&&(this._isObjectBasedMotionBlur?this.motionBlurPostProcess.motionBlurSamples=e:this.motionBlurPostProcess.updateEffect(`#define MOTION_BLUR
-#define MAX_MOTION_SAMPLES `+e.toFixed(1))),this._motionBlurSamples=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"samples",{get:function(){return this._samples},set:function(e){this._samples!==e&&(this._samples=e,this._buildPipeline())},enumerable:!1,configurable:!0}),t.prototype._buildPipeline=function(){var e=this,n=this._ratio,i=this._scene;this._disposePostProcesses(),this._cameras!==null&&(this._scene.postProcessRenderPipelineManager.detachCamerasFromRenderPipeline(this._name,this._cameras),this._cameras=this._camerasToBeAttached.slice()),this._reset(),this._screenSpaceReflectionsEnabled&&(this.screenSpaceReflectionPostProcess=new jc("HDRPass",i,n,null,we.a.BILINEAR_SAMPLINGMODE,i.getEngine(),!1,this._floatTextureType),this.screenSpaceReflectionPostProcess.onApplyObservable.add(function(){e._currentDepthOfFieldSource=e.screenSpaceReflectionPostProcess}),this.addEffect(new Rt(i.getEngine(),"HDRScreenSpaceReflections",function(){return e.screenSpaceReflectionPostProcess},!0))),this._basePostProcess?this.originalPostProcess=this._basePostProcess:this.originalPostProcess=new _t("HDRPass","standard",[],[],n,null,we.a.BILINEAR_SAMPLINGMODE,i.getEngine(),!1,"#define PASS_POST_PROCESS",this._floatTextureType),this.originalPostProcess.autoClear=!this.screenSpaceReflectionPostProcess,this.originalPostProcess.onApplyObservable.add(function(){e._currentDepthOfFieldSource=e.originalPostProcess}),this.addEffect(new Rt(i.getEngine(),"HDRPassPostProcess",function(){return e.originalPostProcess},!0)),this._bloomEnabled&&(this._createDownSampleX4PostProcess(i,n/4),this._createBrightPassPostProcess(i,n/4),this._createBlurPostProcesses(i,n/4,1),this._createTextureAdderPostProcess(i,n),this.textureAdderFinalPostProcess=new _t("HDRDepthOfFieldSource","standard",[],[],n,null,we.a.BILINEAR_SAMPLINGMODE,i.getEngine(),!1,"#define PASS_POST_PROCESS",h.a.TEXTURETYPE_UNSIGNED_INT),this.addEffect(new Rt(i.getEngine(),"HDRBaseDepthOfFieldSource",function(){return e.textureAdderFinalPostProcess},!0))),this._vlsEnabled&&(this._createVolumetricLightPostProcess(i,n),this.volumetricLightFinalPostProcess=new _t("HDRVLSFinal","standard",[],[],n,null,we.a.BILINEAR_SAMPLINGMODE,i.getEngine(),!1,"#define PASS_POST_PROCESS",h.a.TEXTURETYPE_UNSIGNED_INT),this.addEffect(new Rt(i.getEngine(),"HDRVLSFinal",function(){return e.volumetricLightFinalPostProcess},!0))),this._lensFlareEnabled&&(this._createLensFlarePostProcess(i,n),this.lensFlareFinalPostProcess=new _t("HDRPostLensFlareDepthOfFieldSource","standard",[],[],n,null,we.a.BILINEAR_SAMPLINGMODE,i.getEngine(),!1,"#define PASS_POST_PROCESS",h.a.TEXTURETYPE_UNSIGNED_INT),this.addEffect(new Rt(i.getEngine(),"HDRPostLensFlareDepthOfFieldSource",function(){return e.lensFlareFinalPostProcess},!0))),this._hdrEnabled&&(this._createLuminancePostProcesses(i,this._floatTextureType),this._createHdrPostProcess(i,n),this.hdrFinalPostProcess=new _t("HDRPostHDReDepthOfFieldSource","standard",[],[],n,null,we.a.BILINEAR_SAMPLINGMODE,i.getEngine(),!1,"#define PASS_POST_PROCESS",h.a.TEXTURETYPE_UNSIGNED_INT),this.addEffect(new Rt(i.getEngine(),"HDRPostHDReDepthOfFieldSource",function(){return e.hdrFinalPostProcess},!0))),this._depthOfFieldEnabled&&(this._createBlurPostProcesses(i,n/2,3,"depthOfFieldBlurWidth"),this._createDepthOfFieldPostProcess(i,n)),this._motionBlurEnabled&&this._createMotionBlurPostProcess(i,n),this._fxaaEnabled&&(this.fxaaPostProcess=new Oo("fxaa",1,null,we.a.BILINEAR_SAMPLINGMODE,i.getEngine(),!1,h.a.TEXTURETYPE_UNSIGNED_INT),this.addEffect(new Rt(i.getEngine(),"HDRFxaa",function(){return e.fxaaPostProcess},!0))),this._cameras!==null&&this._scene.postProcessRenderPipelineManager.attachCamerasToRenderPipeline(this._name,this._cameras),!this._enableMSAAOnFirstPostProcess(this._samples)&&this._samples>1&&l.a.Warn("MSAA failed to enable, MSAA is only supported in browsers that support webGL >= 2.0")},t.prototype._createDownSampleX4PostProcess=function(e,n){var i=this,o=new Array(32);this.downSampleX4PostProcess=new _t("HDRDownSampleX4","standard",["dsOffsets"],[],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,"#define DOWN_SAMPLE_X4",this._floatTextureType),this.downSampleX4PostProcess.onApply=function(a){for(var s=0,d=i.downSampleX4PostProcess.width,p=i.downSampleX4PostProcess.height,b=-2;b<2;b++)for(var P=-2;P<2;P++)o[s]=(b+.5)*(1/d),o[s+1]=(P+.5)*(1/p),s+=2;a.setArray2("dsOffsets",o)},this.addEffect(new Rt(e.getEngine(),"HDRDownSampleX4",function(){return i.downSampleX4PostProcess},!0))},t.prototype._createBrightPassPostProcess=function(e,n){var i=this,o=new Array(8);this.brightPassPostProcess=new _t("HDRBrightPass","standard",["dsOffsets","brightThreshold"],[],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,"#define BRIGHT_PASS",this._floatTextureType),this.brightPassPostProcess.onApply=function(a){var s=1/i.brightPassPostProcess.width,d=1/i.brightPassPostProcess.height;o[0]=-.5*s,o[1]=.5*d,o[2]=.5*s,o[3]=.5*d,o[4]=-.5*s,o[5]=-.5*d,o[6]=.5*s,o[7]=-.5*d,a.setArray2("dsOffsets",o),a.setFloat("brightThreshold",i.brightThreshold)},this.addEffect(new Rt(e.getEngine(),"HDRBrightPass",function(){return i.brightPassPostProcess},!0))},t.prototype._createBlurPostProcesses=function(e,n,i,o){var a=this;o===void 0&&(o="blurWidth");var s=e.getEngine(),d=new gn("HDRBlurH_"+i,new u.d(1,0),this[o],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,this._floatTextureType),p=new gn("HDRBlurV_"+i,new u.d(0,1),this[o],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,this._floatTextureType);d.onActivateObservable.add(function(){var b=d.width/s.getRenderWidth();d.kernel=a[o]*b}),p.onActivateObservable.add(function(){var b=p.height/s.getRenderHeight();p.kernel=a.horizontalBlur?64*b:a[o]*b}),this.addEffect(new Rt(e.getEngine(),"HDRBlurH"+i,function(){return d},!0)),this.addEffect(new Rt(e.getEngine(),"HDRBlurV"+i,function(){return p},!0)),this.blurHPostProcesses.push(d),this.blurVPostProcesses.push(p)},t.prototype._createTextureAdderPostProcess=function(e,n){var i=this;this.textureAdderPostProcess=new _t("HDRTextureAdder","standard",["exposure"],["otherSampler","lensSampler"],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,"#define TEXTURE_ADDER",this._floatTextureType),this.textureAdderPostProcess.onApply=function(o){o.setTextureFromPostProcess("otherSampler",i._vlsEnabled?i._currentDepthOfFieldSource:i.originalPostProcess),o.setTexture("lensSampler",i.lensTexture),o.setFloat("exposure",i._currentExposure),i._currentDepthOfFieldSource=i.textureAdderFinalPostProcess},this.addEffect(new Rt(e.getEngine(),"HDRTextureAdder",function(){return i.textureAdderPostProcess},!0))},t.prototype._createVolumetricLightPostProcess=function(e,n){var i=this,o=e.enableGeometryBufferRenderer();o.enablePosition=!0;var a=o.getGBuffer();this.volumetricLightPostProcess=new _t("HDRVLS","standard",["shadowViewProjection","cameraPosition","sunDirection","sunColor","scatteringCoefficient","scatteringPower","depthValues"],["shadowMapSampler","positionSampler"],n/8,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,`#define VLS
-#define NB_STEPS `+this._volumetricLightStepsCount.toFixed(1));var s=u.d.Zero();this.volumetricLightPostProcess.onApply=function(d){if(i.sourceLight&&i.sourceLight.getShadowGenerator()&&i._scene.activeCamera){var p=i.sourceLight.getShadowGenerator();d.setTexture("shadowMapSampler",p.getShadowMap()),d.setTexture("positionSampler",a.textures[2]),d.setColor3("sunColor",i.sourceLight.diffuse),d.setVector3("sunDirection",i.sourceLight.getShadowDirection()),d.setVector3("cameraPosition",i._scene.activeCamera.globalPosition),d.setMatrix("shadowViewProjection",p.getTransformMatrix()),d.setFloat("scatteringCoefficient",i.volumetricLightCoefficient),d.setFloat("scatteringPower",i.volumetricLightPower),s.x=i.sourceLight.getDepthMinZ(i._scene.activeCamera),s.y=i.sourceLight.getDepthMaxZ(i._scene.activeCamera),d.setVector2("depthValues",s)}},this.addEffect(new Rt(e.getEngine(),"HDRVLS",function(){return i.volumetricLightPostProcess},!0)),this._createBlurPostProcesses(e,n/4,0,"volumetricLightBlurScale"),this.volumetricLightMergePostProces=new _t("HDRVLSMerge","standard",[],["originalSampler"],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,"#define VLSMERGE"),this.volumetricLightMergePostProces.onApply=function(d){d.setTextureFromPostProcess("originalSampler",i._bloomEnabled?i.textureAdderFinalPostProcess:i.originalPostProcess),i._currentDepthOfFieldSource=i.volumetricLightFinalPostProcess},this.addEffect(new Rt(e.getEngine(),"HDRVLSMerge",function(){return i.volumetricLightMergePostProces},!0))},t.prototype._createLuminancePostProcesses=function(e,n){var i=this,o=Math.pow(3,t.LuminanceSteps);this.luminancePostProcess=new _t("HDRLuminance","standard",["lumOffsets"],[],{width:o,height:o},null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,"#define LUMINANCE",n);var a=[];this.luminancePostProcess.onApply=function(P){var O=1/i.luminancePostProcess.width,B=1/i.luminancePostProcess.height;a[0]=-.5*O,a[1]=.5*B,a[2]=.5*O,a[3]=.5*B,a[4]=-.5*O,a[5]=-.5*B,a[6]=.5*O,a[7]=-.5*B,P.setArray2("lumOffsets",a)},this.addEffect(new Rt(e.getEngine(),"HDRLuminance",function(){return i.luminancePostProcess},!0));for(var s=t.LuminanceSteps-1;s>=0;s--){o=Math.pow(3,s);var d=`#define LUMINANCE_DOWN_SAMPLE
-`;s===0&&(d+="#define FINAL_DOWN_SAMPLER");var p=new _t("HDRLuminanceDownSample"+s,"standard",["dsOffsets","halfDestPixelSize"],[],{width:o,height:o},null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,d,n);this.luminanceDownSamplePostProcesses.push(p)}var b=this.luminancePostProcess;this.luminanceDownSamplePostProcesses.forEach(function(P,O){var B=new Array(18);P.onApply=function(F){if(b){for(var z=0,J=-1;J<2;J++)for(var ie=-1;ie<2;ie++)B[z]=J/b.width,B[z+1]=ie/b.height,z+=2;F.setArray2("dsOffsets",B),F.setFloat("halfDestPixelSize",.5/b.width),b=O===i.luminanceDownSamplePostProcesses.length-1?i.luminancePostProcess:P}},O===i.luminanceDownSamplePostProcesses.length-1&&(P.onAfterRender=function(){var F=e.getEngine().readPixels(0,0,1,1),z=new u.f(1/16581375,1/65025,1/255,1);i._hdrCurrentLuminance=(F[0]*z.x+F[1]*z.y+F[2]*z.z+F[3]*z.w)/100}),i.addEffect(new Rt(e.getEngine(),"HDRLuminanceDownSample"+O,function(){return P},!0))})},t.prototype._createHdrPostProcess=function(e,n){var i=this,o=["#define HDR"];this._hdrAutoExposure&&o.push("#define AUTO_EXPOSURE"),this.hdrPostProcess=new _t("HDR","standard",["averageLuminance"],["textureAdderSampler"],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,o.join(`
-`),h.a.TEXTURETYPE_UNSIGNED_INT);var a=1,s=0,d=0;this.hdrPostProcess.onApply=function(p){if(p.setTextureFromPostProcess("textureAdderSampler",i._currentDepthOfFieldSource),s+=e.getEngine().getDeltaTime(),a<0)a=i._hdrCurrentLuminance;else{var b=(d-s)/1e3;i._hdrCurrentLuminance<a+i.hdrDecreaseRate*b?a+=i.hdrDecreaseRate*b:i._hdrCurrentLuminance>a-i.hdrIncreaseRate*b?a-=i.hdrIncreaseRate*b:a=i._hdrCurrentLuminance}i.hdrAutoExposure?i._currentExposure=i._fixedExposure/a:(a=$.a.Clamp(a,i.hdrMinimumLuminance,1e20),p.setFloat("averageLuminance",a)),d=s,i._currentDepthOfFieldSource=i.hdrFinalPostProcess},this.addEffect(new Rt(e.getEngine(),"HDR",function(){return i.hdrPostProcess},!0))},t.prototype._createLensFlarePostProcess=function(e,n){var i=this;this.lensFlarePostProcess=new _t("HDRLensFlare","standard",["strength","ghostDispersal","haloWidth","resolution","distortionStrength"],["lensColorSampler"],n/2,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,"#define LENS_FLARE",h.a.TEXTURETYPE_UNSIGNED_INT),this.addEffect(new Rt(e.getEngine(),"HDRLensFlare",function(){return i.lensFlarePostProcess},!0)),this._createBlurPostProcesses(e,n/4,2,"lensFlareBlurWidth"),this.lensFlareComposePostProcess=new _t("HDRLensFlareCompose","standard",["lensStarMatrix"],["otherSampler","lensDirtSampler","lensStarSampler"],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,"#define LENS_FLARE_COMPOSE",h.a.TEXTURETYPE_UNSIGNED_INT),this.addEffect(new Rt(e.getEngine(),"HDRLensFlareCompose",function(){return i.lensFlareComposePostProcess},!0));var o=new u.d(0,0);this.lensFlarePostProcess.onApply=function(d){d.setTextureFromPostProcess("textureSampler",i._bloomEnabled?i.blurHPostProcesses[0]:i.originalPostProcess),d.setTexture("lensColorSampler",i.lensColorTexture),d.setFloat("strength",i.lensFlareStrength),d.setFloat("ghostDispersal",i.lensFlareGhostDispersal),d.setFloat("haloWidth",i.lensFlareHaloWidth),o.x=i.lensFlarePostProcess.width,o.y=i.lensFlarePostProcess.height,d.setVector2("resolution",o),d.setFloat("distortionStrength",i.lensFlareDistortionStrength)};var a=u.a.FromValues(2,0,-1,0,0,2,-1,0,0,0,1,0,0,0,0,1),s=u.a.FromValues(.5,0,.5,0,0,.5,.5,0,0,0,1,0,0,0,0,1);this.lensFlareComposePostProcess.onApply=function(d){if(i._scene.activeCamera){d.setTextureFromPostProcess("otherSampler",i.lensFlarePostProcess),d.setTexture("lensDirtSampler",i.lensFlareDirtTexture),d.setTexture("lensStarSampler",i.lensStarTexture);var p=i._scene.activeCamera.getViewMatrix().getRow(0),b=i._scene.activeCamera.getViewMatrix().getRow(2),P=u.e.Dot(p.toVector3(),new u.e(1,0,0))+u.e.Dot(b.toVector3(),new u.e(0,0,1));P*=4;var O=u.a.FromValues(.5*Math.cos(P),-Math.sin(P),0,0,Math.sin(P),.5*Math.cos(P),0,0,0,0,1,0,0,0,0,1),B=s.multiply(O).multiply(a);d.setMatrix("lensStarMatrix",B),i._currentDepthOfFieldSource=i.lensFlareFinalPostProcess}}},t.prototype._createDepthOfFieldPostProcess=function(e,n){var i=this;this.depthOfFieldPostProcess=new _t("HDRDepthOfField","standard",["distance"],["otherSampler","depthSampler"],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,"#define DEPTH_OF_FIELD",h.a.TEXTURETYPE_UNSIGNED_INT),this.depthOfFieldPostProcess.onApply=function(o){o.setTextureFromPostProcess("otherSampler",i._currentDepthOfFieldSource),o.setTexture("depthSampler",i._getDepthTexture()),o.setFloat("distance",i.depthOfFieldDistance)},this.addEffect(new Rt(e.getEngine(),"HDRDepthOfField",function(){return i.depthOfFieldPostProcess},!0))},t.prototype._createMotionBlurPostProcess=function(e,n){var i=this;if(this._isObjectBasedMotionBlur){var o=new Gc("HDRMotionBlur",e,n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,h.a.TEXTURETYPE_UNSIGNED_INT);o.motionStrength=this.motionStrength,o.motionBlurSamples=this.motionBlurSamples,this.motionBlurPostProcess=o}else{this.motionBlurPostProcess=new _t("HDRMotionBlur","standard",["inverseViewProjection","prevViewProjection","screenSize","motionScale","motionStrength"],["depthSampler"],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,`#define MOTION_BLUR
-#define MAX_MOTION_SAMPLES `+this.motionBlurSamples.toFixed(1),h.a.TEXTURETYPE_UNSIGNED_INT);var a=0,s=u.a.Identity(),d=u.a.Identity(),p=u.a.Identity(),b=u.d.Zero();this.motionBlurPostProcess.onApply=function(P){(p=e.getProjectionMatrix().multiply(e.getViewMatrix())).invertToRef(d),P.setMatrix("inverseViewProjection",d),P.setMatrix("prevViewProjection",s),s=p,b.x=i.motionBlurPostProcess.width,b.y=i.motionBlurPostProcess.height,P.setVector2("screenSize",b),a=e.getEngine().getFps()/60,P.setFloat("motionScale",a),P.setFloat("motionStrength",i.motionStrength),P.setTexture("depthSampler",i._getDepthTexture())}}this.addEffect(new Rt(e.getEngine(),"HDRMotionBlur",function(){return i.motionBlurPostProcess},!0))},t.prototype._getDepthTexture=function(){return this._scene.getEngine().getCaps().drawBuffersExtension?this._scene.enableGeometryBufferRenderer().getGBuffer().textures[0]:this._scene.enableDepthRenderer().getDepthMap()},t.prototype._disposePostProcesses=function(){for(var e=0;e<this._cameras.length;e++){var n=this._cameras[e];this.originalPostProcess&&this.originalPostProcess.dispose(n),this.screenSpaceReflectionPostProcess&&this.screenSpaceReflectionPostProcess.dispose(n),this.downSampleX4PostProcess&&this.downSampleX4PostProcess.dispose(n),this.brightPassPostProcess&&this.brightPassPostProcess.dispose(n),this.textureAdderPostProcess&&this.textureAdderPostProcess.dispose(n),this.volumetricLightPostProcess&&this.volumetricLightPostProcess.dispose(n),this.volumetricLightSmoothXPostProcess&&this.volumetricLightSmoothXPostProcess.dispose(n),this.volumetricLightSmoothYPostProcess&&this.volumetricLightSmoothYPostProcess.dispose(n),this.volumetricLightMergePostProces&&this.volumetricLightMergePostProces.dispose(n),this.volumetricLightFinalPostProcess&&this.volumetricLightFinalPostProcess.dispose(n),this.lensFlarePostProcess&&this.lensFlarePostProcess.dispose(n),this.lensFlareComposePostProcess&&this.lensFlareComposePostProcess.dispose(n);for(var i=0;i<this.luminanceDownSamplePostProcesses.length;i++)this.luminanceDownSamplePostProcesses[i].dispose(n);for(this.luminancePostProcess&&this.luminancePostProcess.dispose(n),this.hdrPostProcess&&this.hdrPostProcess.dispose(n),this.hdrFinalPostProcess&&this.hdrFinalPostProcess.dispose(n),this.depthOfFieldPostProcess&&this.depthOfFieldPostProcess.dispose(n),this.motionBlurPostProcess&&this.motionBlurPostProcess.dispose(n),this.fxaaPostProcess&&this.fxaaPostProcess.dispose(n),i=0;i<this.blurHPostProcesses.length;i++)this.blurHPostProcesses[i].dispose(n);for(i=0;i<this.blurVPostProcesses.length;i++)this.blurVPostProcesses[i].dispose(n)}this.originalPostProcess=null,this.downSampleX4PostProcess=null,this.brightPassPostProcess=null,this.textureAdderPostProcess=null,this.textureAdderFinalPostProcess=null,this.volumetricLightPostProcess=null,this.volumetricLightSmoothXPostProcess=null,this.volumetricLightSmoothYPostProcess=null,this.volumetricLightMergePostProces=null,this.volumetricLightFinalPostProcess=null,this.lensFlarePostProcess=null,this.lensFlareComposePostProcess=null,this.luminancePostProcess=null,this.hdrPostProcess=null,this.hdrFinalPostProcess=null,this.depthOfFieldPostProcess=null,this.motionBlurPostProcess=null,this.fxaaPostProcess=null,this.screenSpaceReflectionPostProcess=null,this.luminanceDownSamplePostProcesses=[],this.blurHPostProcesses=[],this.blurVPostProcesses=[]},t.prototype.dispose=function(){this._disposePostProcesses(),this._scene.postProcessRenderPipelineManager.detachCamerasFromRenderPipeline(this._name,this._cameras),r.prototype.dispose.call(this)},t.prototype.serialize=function(){var e=L.a.Serialize(this);return this.sourceLight&&(e.sourceLightId=this.sourceLight.id),this.screenSpaceReflectionPostProcess&&(e.screenSpaceReflectionPostProcess=L.a.Serialize(this.screenSpaceReflectionPostProcess)),e.customType="StandardRenderingPipeline",e},t.Parse=function(e,n,i){var o=L.a.Parse(function(){return new t(e._name,n,e._ratio)},e,n,i);return e.sourceLightId&&(o.sourceLight=n.getLightByID(e.sourceLightId)),e.screenSpaceReflectionPostProcess&&L.a.Parse(function(){return o.screenSpaceReflectionPostProcess},e.screenSpaceReflectionPostProcess,n,i),o},t.LuminanceSteps=6,Object(c.c)([Object(L.c)()],t.prototype,"brightThreshold",void 0),Object(c.c)([Object(L.c)()],t.prototype,"blurWidth",void 0),Object(c.c)([Object(L.c)()],t.prototype,"horizontalBlur",void 0),Object(c.c)([Object(L.c)()],t.prototype,"exposure",null),Object(c.c)([Object(L.m)("lensTexture")],t.prototype,"lensTexture",void 0),Object(c.c)([Object(L.c)()],t.prototype,"volumetricLightCoefficient",void 0),Object(c.c)([Object(L.c)()],t.prototype,"volumetricLightPower",void 0),Object(c.c)([Object(L.c)()],t.prototype,"volumetricLightBlurScale",void 0),Object(c.c)([Object(L.c)()],t.prototype,"hdrMinimumLuminance",void 0),Object(c.c)([Object(L.c)()],t.prototype,"hdrDecreaseRate",void 0),Object(c.c)([Object(L.c)()],t.prototype,"hdrIncreaseRate",void 0),Object(c.c)([Object(L.c)()],t.prototype,"hdrAutoExposure",null),Object(c.c)([Object(L.m)("lensColorTexture")],t.prototype,"lensColorTexture",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lensFlareStrength",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lensFlareGhostDispersal",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lensFlareHaloWidth",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lensFlareDistortionStrength",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lensFlareBlurWidth",void 0),Object(c.c)([Object(L.m)("lensStarTexture")],t.prototype,"lensStarTexture",void 0),Object(c.c)([Object(L.m)("lensFlareDirtTexture")],t.prototype,"lensFlareDirtTexture",void 0),Object(c.c)([Object(L.c)()],t.prototype,"depthOfFieldDistance",void 0),Object(c.c)([Object(L.c)()],t.prototype,"depthOfFieldBlurWidth",void 0),Object(c.c)([Object(L.c)()],t.prototype,"motionStrength",null),Object(c.c)([Object(L.c)()],t.prototype,"objectBasedMotionBlur",null),Object(c.c)([Object(L.c)()],t.prototype,"_ratio",void 0),Object(c.c)([Object(L.c)()],t.prototype,"BloomEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"DepthOfFieldEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"LensFlareEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"HDREnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"VLSEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"MotionBlurEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"fxaaEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"screenSpaceReflectionsEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"volumetricLightStepsCount",null),Object(c.c)([Object(L.c)()],t.prototype,"motionBlurSamples",null),Object(c.c)([Object(L.c)()],t.prototype,"samples",null),t}(Vr);R.a.RegisteredTypes["BABYLON.StandardRenderingPipeline"]=zd;var Cg=`const vec3 TWO=vec3(2.0,2.0,2.0);
-varying vec2 vUV;
-uniform sampler2D camASampler;
-uniform sampler2D textureSampler;
-uniform vec2 stepSize;
-void main(void)
-{
-bool useCamA;
-bool useCamB;
-vec2 texCoord1;
-vec2 texCoord2;
-vec3 frag1;
-vec3 frag2;
-#ifdef IS_STEREOSCOPIC_HORIZ
-useCamB=vUV.x>0.5;
-useCamA=!useCamB;
-texCoord1=vec2(useCamB ? (vUV.x-0.5)*2.0 : vUV.x*2.0,vUV.y);
-texCoord2=vec2(texCoord1.x+stepSize.x,vUV.y);
-#else
-#ifdef IS_STEREOSCOPIC_INTERLACED
-float rowNum=floor(vUV.y/stepSize.y);
-useCamA=mod(rowNum,2.0) == 1.0;
-useCamB=mod(rowNum,2.0) == 0.0;
-texCoord1=vec2(vUV.x,vUV.y);
-texCoord2=vec2(vUV.x,vUV.y);
-#else
-useCamB=vUV.y>0.5;
-useCamA=!useCamB;
-texCoord1=vec2(vUV.x,useCamB ? (vUV.y-0.5)*2.0 : vUV.y*2.0);
-texCoord2=vec2(vUV.x,texCoord1.y+stepSize.y);
-#endif
-#endif
-
-if (useCamB){
-frag1=texture2D(textureSampler,texCoord1).rgb;
-frag2=texture2D(textureSampler,texCoord2).rgb;
-}else if (useCamA){
-frag1=texture2D(camASampler ,texCoord1).rgb;
-frag2=texture2D(camASampler ,texCoord2).rgb;
-}else {
-discard;
-}
-gl_FragColor=vec4((frag1+frag2)/TWO,1.0);
-}
-`;ze.a.ShadersStore.stereoscopicInterlacePixelShader=Cg;var xg=function(r){function t(e,n,i,o,a,s,d){var p=r.call(this,e,"stereoscopicInterlace",["stepSize"],["camASampler"],1,n[1],a,s,d,o?"#define IS_STEREOSCOPIC_INTERLACED 1":i?"#define IS_STEREOSCOPIC_HORIZ 1":void 0)||this;return p._passedProcess=n[0]._rigPostProcess,p._stepSize=new u.d(1/p.width,1/p.height),p.onSizeChangedObservable.add(function(){p._stepSize=new u.d(1/p.width,1/p.height)}),p.onApplyObservable.add(function(b){b.setTextureFromPostProcess("camASampler",p._passedProcess),b.setFloat2("stepSize",p._stepSize.x,p._stepSize.y)}),p}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"StereoscopicInterlacePostProcessI"},t}(_t),Rg=function(r){function t(e,n,i,o,a,s){var d=r.call(this,e,"stereoscopicInterlace",["stepSize"],["camASampler"],1,n[1],o,a,s,i?"#define IS_STEREOSCOPIC_HORIZ 1":void 0)||this;return d._passedProcess=n[0]._rigPostProcess,d._stepSize=new u.d(1/d.width,1/d.height),d.onSizeChangedObservable.add(function(){d._stepSize=new u.d(1/d.width,1/d.height)}),d.onApplyObservable.add(function(p){p.setTextureFromPostProcess("camASampler",d._passedProcess),p.setFloat2("stepSize",d._stepSize.x,d._stepSize.y)}),d}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"StereoscopicInterlacePostProcess"},t}(_t),Og=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-
-uniform float _ExposureAdjustment;
-#if defined(HABLE_TONEMAPPING)
-const float A=0.15;
-const float B=0.50;
-const float C=0.10;
-const float D=0.20;
-const float E=0.02;
-const float F=0.30;
-const float W=11.2;
-#endif
-float Luminance(vec3 c)
-{
-return dot(c,vec3(0.22,0.707,0.071));
-}
-void main(void)
-{
-vec3 colour=texture2D(textureSampler,vUV).rgb;
-#if defined(REINHARD_TONEMAPPING)
-float lum=Luminance(colour.rgb);
-float lumTm=lum*_ExposureAdjustment;
-float scale=lumTm/(1.0+lumTm);
-colour*=scale/lum;
-#elif defined(HABLE_TONEMAPPING)
-colour*=_ExposureAdjustment;
-const float ExposureBias=2.0;
-vec3 x=ExposureBias*colour;
-vec3 curr=((x*(A*x+C*B)+D*E)/(x*(A*x+B)+D*F))-E/F;
-x=vec3(W,W,W);
-vec3 whiteScale=1.0/(((x*(A*x+C*B)+D*E)/(x*(A*x+B)+D*F))-E/F);
-colour=curr*whiteScale;
-#elif defined(OPTIMIZED_HEJIDAWSON_TONEMAPPING)
-colour*=_ExposureAdjustment;
-vec3 X=max(vec3(0.0,0.0,0.0),colour-0.004);
-vec3 retColor=(X*(6.2*X+0.5))/(X*(6.2*X+1.7)+0.06);
-colour=retColor*retColor;
-#elif defined(PHOTOGRAPHIC_TONEMAPPING)
-colour=vec3(1.0,1.0,1.0)-exp2(-_ExposureAdjustment*colour);
-#endif
-gl_FragColor=vec4(colour.rgb,1.0);
-}`;ze.a.ShadersStore.tonemapPixelShader=Og;var cr;(function(r){r[r.Hable=0]="Hable",r[r.Reinhard=1]="Reinhard",r[r.HejiDawson=2]="HejiDawson",r[r.Photographic=3]="Photographic"})(cr||(cr={}));var Mg=function(r){function t(e,n,i,o,a,s,d){a===void 0&&(a=h.a.TEXTURE_BILINEAR_SAMPLINGMODE),d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT);var p=r.call(this,e,"tonemap",["_ExposureAdjustment"],null,1,o,a,s,!0,null,d)||this;p._operator=n,p.exposureAdjustment=i;var b="#define ";return p._operator===cr.Hable?b+="HABLE_TONEMAPPING":p._operator===cr.Reinhard?b+="REINHARD_TONEMAPPING":p._operator===cr.HejiDawson?b+="OPTIMIZED_HEJIDAWSON_TONEMAPPING":p._operator===cr.Photographic&&(b+="PHOTOGRAPHIC_TONEMAPPING"),p.updateEffect(b),p.onApply=function(P){P.setFloat("_ExposureAdjustment",p.exposureAdjustment)},p}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"TonemapPostProcess"},t}(_t),Ig=`uniform sampler2D textureSampler;
-uniform sampler2D lightScatteringSampler;
-uniform float decay;
-uniform float exposure;
-uniform float weight;
-uniform float density;
-uniform vec2 meshPositionOnScreen;
-varying vec2 vUV;
-void main(void) {
-vec2 tc=vUV;
-vec2 deltaTexCoord=(tc-meshPositionOnScreen.xy);
-deltaTexCoord*=1.0/float(NUM_SAMPLES)*density;
-float illuminationDecay=1.0;
-vec4 color=texture2D(lightScatteringSampler,tc)*0.4;
-for(int i=0; i<NUM_SAMPLES; i++) {
-tc-=deltaTexCoord;
-vec4 dataSample=texture2D(lightScatteringSampler,tc)*0.4;
-dataSample*=illuminationDecay*weight;
-color+=dataSample;
-illuminationDecay*=decay;
-}
-vec4 realColor=texture2D(textureSampler,vUV);
-gl_FragColor=((vec4((vec3(color.r,color.g,color.b)*exposure),1))+(realColor*(1.5-0.4)));
-}
-`;ze.a.ShadersStore.volumetricLightScatteringPixelShader=Ig;var Dg=`
-attribute vec3 position;
-#include<bonesDeclaration>
-#include<morphTargetsVertexGlobalDeclaration>
-#include<morphTargetsVertexDeclaration>[0..maxSimultaneousMorphTargets]
-
-#include<instancesDeclaration>
-uniform mat4 viewProjection;
-uniform vec2 depthValues;
-#if defined(ALPHATEST) || defined(NEED_UV)
-varying vec2 vUV;
-uniform mat4 diffuseMatrix;
-#ifdef UV1
-attribute vec2 uv;
-#endif
-#ifdef UV2
-attribute vec2 uv2;
-#endif
-#endif
-void main(void)
-{
-vec3 positionUpdated=position;
-#if (defined(ALPHATEST) || defined(NEED_UV)) && defined(UV1)
-vec2 uvUpdated=uv;
-#endif
-#include<morphTargetsVertex>[0..maxSimultaneousMorphTargets]
-#include<instancesVertex>
-#include<bonesVertex>
-gl_Position=viewProjection*finalWorld*vec4(positionUpdated,1.0);
-#if defined(ALPHATEST) || defined(BASIC_RENDER)
-#ifdef UV1
-vUV=vec2(diffuseMatrix*vec4(uvUpdated,1.0,0.0));
-#endif
-#ifdef UV2
-vUV=vec2(diffuseMatrix*vec4(uv2,1.0,0.0));
-#endif
-#endif
-}
-`;ze.a.ShadersStore.volumetricLightScatteringPassVertexShader=Dg;var Lg=`#if defined(ALPHATEST) || defined(NEED_UV)
-varying vec2 vUV;
-#endif
-#if defined(ALPHATEST)
-uniform sampler2D diffuseSampler;
-#endif
-void main(void)
-{
-#if defined(ALPHATEST)
-vec4 diffuseColor=texture2D(diffuseSampler,vUV);
-if (diffuseColor.a<0.4)
-discard;
-#endif
-gl_FragColor=vec4(0.0,0.0,0.0,1.0);
-}
-`;ze.a.ShadersStore.volumetricLightScatteringPassPixelShader=Lg;var jd=function(r){function t(e,n,i,o,a,s,d,p,b){a===void 0&&(a=100),s===void 0&&(s=we.a.BILINEAR_SAMPLINGMODE);var P=r.call(this,e,"volumetricLightScattering",["decay","exposure","weight","meshPositionOnScreen","density"],["lightScatteringSampler"],n.postProcessRatio||n,i,s,d,p,"#define NUM_SAMPLES "+a)||this;return P._screenCoordinates=u.d.Zero(),P.customMeshPosition=u.e.Zero(),P.useCustomMeshPosition=!1,P.invert=!0,P.excludedMeshes=new Array,P.exposure=.3,P.decay=.96815,P.weight=.58767,P.density=.926,d=(b=i===null?b:i.getScene()).getEngine(),P._viewPort=new Kn.a(0,0,1,1).toGlobal(d.getRenderWidth(),d.getRenderHeight()),P.mesh=o!==null?o:t.CreateDefaultMesh("VolumetricLightScatteringMesh",b),P._createPass(b,n.passRatio||n),P.onActivate=function(O){P.isSupported||P.dispose(O),P.onActivate=null},P.onApplyObservable.add(function(O){P._updateMeshScreenCoordinates(b),O.setTexture("lightScatteringSampler",P._volumetricLightScatteringRTT),O.setFloat("exposure",P.exposure),O.setFloat("decay",P.decay),O.setFloat("weight",P.weight),O.setFloat("density",P.density),O.setVector2("meshPositionOnScreen",P._screenCoordinates)}),P}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"useDiffuseColor",{get:function(){return l.a.Warn("VolumetricLightScatteringPostProcess.useDiffuseColor is no longer used, use the mesh material directly instead"),!1},set:function(e){l.a.Warn("VolumetricLightScatteringPostProcess.useDiffuseColor is no longer used, use the mesh material directly instead")},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"VolumetricLightScatteringPostProcess"},t.prototype._isReady=function(e,n){var i=e.getMesh();if(i===this.mesh&&i.material)return i.material.isReady(i);var o=[],a=[Oe.b.PositionKind],s=e.getMaterial();s&&(s.needAlphaTesting()&&o.push("#define ALPHATEST"),i.isVerticesDataPresent(Oe.b.UVKind)&&(a.push(Oe.b.UVKind),o.push("#define UV1")),i.isVerticesDataPresent(Oe.b.UV2Kind)&&(a.push(Oe.b.UV2Kind),o.push("#define UV2"))),i.useBones&&i.computeBonesUsingShaders?(a.push(Oe.b.MatricesIndicesKind),a.push(Oe.b.MatricesWeightsKind),o.push("#define NUM_BONE_INFLUENCERS "+i.numBoneInfluencers),o.push("#define BonesPerMesh "+(i.skeleton?i.skeleton.bones.length+1:0))):o.push("#define NUM_BONE_INFLUENCERS 0"),n&&(o.push("#define INSTANCES"),et.a.PushAttributesForInstances(a),e.getRenderingMesh().hasThinInstances&&o.push("#define THIN_INSTANCES"));var d=o.join(`
-`);return this._cachedDefines!==d&&(this._cachedDefines=d,this._volumetricLightScatteringPass=i.getScene().getEngine().createEffect("volumetricLightScatteringPass",a,["world","mBones","viewProjection","diffuseMatrix"],["diffuseSampler"],d,void 0,void 0,void 0,{maxSimultaneousMorphTargets:i.numBoneInfluencers})),this._volumetricLightScatteringPass.isReady()},t.prototype.setCustomMeshPosition=function(e){this.customMeshPosition=e},t.prototype.getCustomMeshPosition=function(){return this.customMeshPosition},t.prototype.dispose=function(e){var n=e.getScene().customRenderTargets.indexOf(this._volumetricLightScatteringRTT);n!==-1&&e.getScene().customRenderTargets.splice(n,1),this._volumetricLightScatteringRTT.dispose(),r.prototype.dispose.call(this,e)},t.prototype.getPass=function(){return this._volumetricLightScatteringRTT},t.prototype._meshExcluded=function(e){return this.excludedMeshes.length>0&&this.excludedMeshes.indexOf(e)!==-1},t.prototype._createPass=function(e,n){var i=this,o=e.getEngine();this._volumetricLightScatteringRTT=new sn("volumetricLightScatteringMap",{width:o.getRenderWidth()*n,height:o.getRenderHeight()*n},e,!1,!0,h.a.TEXTURETYPE_UNSIGNED_INT),this._volumetricLightScatteringRTT.wrapU=we.a.CLAMP_ADDRESSMODE,this._volumetricLightScatteringRTT.wrapV=we.a.CLAMP_ADDRESSMODE,this._volumetricLightScatteringRTT.renderList=null,this._volumetricLightScatteringRTT.renderParticles=!1,this._volumetricLightScatteringRTT.ignoreCameraViewport=!0;var a=this.getCamera();a?a.customRenderTargets.push(this._volumetricLightScatteringRTT):e.customRenderTargets.push(this._volumetricLightScatteringRTT);var s,d=function(b){var P=b.getRenderingMesh(),O=b.getEffectiveMesh();if(!i._meshExcluded(P)){O._internalAbstractMeshDataInfo._isActiveIntermediate=!1;var B=b.getMaterial();if(B){var F=P.getScene(),z=F.getEngine();z.setState(B.backFaceCulling);var J=P._getInstancesRenderList(b._id,!!b.getReplacementMesh());if(!J.mustReturn){var ie=z.getCaps().instancedArrays&&(J.visibleInstances[b._id]!==null||P.hasThinInstances);if(i._isReady(b,ie)){var se=i._volumetricLightScatteringPass;if(P===i.mesh&&(se=b.effect?b.effect:B.getEffect()),z.enableEffect(se),P._bind(b,se,B.fillMode),P===i.mesh)B.bind(O.getWorldMatrix(),P);else{if(i._volumetricLightScatteringPass.setMatrix("viewProjection",F.getTransformMatrix()),B&&B.needAlphaTesting()){var ce=B.getAlphaTestTexture();i._volumetricLightScatteringPass.setTexture("diffuseSampler",ce),ce&&i._volumetricLightScatteringPass.setMatrix("diffuseMatrix",ce.getTextureMatrix())}P.useBones&&P.computeBonesUsingShaders&&P.skeleton&&i._volumetricLightScatteringPass.setMatrices("mBones",P.skeleton.getTransformMatrices(P))}P._processRendering(O,b,i._volumetricLightScatteringPass,Ht.a.TriangleFillMode,J,ie,function(ue,fe){return se.setMatrix("world",fe)})}}}}},p=new M.b(0,0,0,1);this._volumetricLightScatteringRTT.onBeforeRenderObservable.add(function(){s=e.clearColor,e.clearColor=p}),this._volumetricLightScatteringRTT.onAfterRenderObservable.add(function(){e.clearColor=s}),this._volumetricLightScatteringRTT.customRenderFunction=function(b,P,O,B){var F,z=e.getEngine();if(B.length){for(z.setColorWrite(!1),F=0;F<B.length;F++)d(B.data[F]);z.setColorWrite(!0)}for(F=0;F<b.length;F++)d(b.data[F]);for(F=0;F<P.length;F++)d(P.data[F]);if(O.length){for(F=0;F<O.length;F++){var J=O.data[F],ie=J.getBoundingInfo();ie&&e.activeCamera&&(J._alphaIndex=J.getMesh().alphaIndex,J._distanceToCamera=ie.boundingSphere.centerWorld.subtract(e.activeCamera.position).length())}var se=O.data.slice(0,O.length);for(se.sort(function(ce,ue){return ce._alphaIndex>ue._alphaIndex?1:ce._alphaIndex<ue._alphaIndex?-1:ce._distanceToCamera<ue._distanceToCamera?1:ce._distanceToCamera>ue._distanceToCamera?-1:0}),z.setAlphaMode(h.a.ALPHA_COMBINE),F=0;F<se.length;F++)d(se[F]);z.setAlphaMode(h.a.ALPHA_DISABLE)}}},t.prototype._updateMeshScreenCoordinates=function(e){var n,i=e.getTransformMatrix();n=this.useCustomMeshPosition?this.customMeshPosition:this.attachedNode?this.attachedNode.position:this.mesh.parent?this.mesh.getAbsolutePosition():this.mesh.position;var o=u.e.Project(n,u.a.Identity(),i,this._viewPort);this._screenCoordinates.x=o.x/this._viewPort.width,this._screenCoordinates.y=o.y/this._viewPort.height,this.invert&&(this._screenCoordinates.y=1-this._screenCoordinates.y)},t.CreateDefaultMesh=function(e,n){var i=De.a.CreatePlane(e,1,n);i.billboardMode=Dt.a.BILLBOARDMODE_ALL;var o=new Ft.a(e+"Material",n);return o.emissiveColor=new M.a(1,1,1),i.material=o,i},Object(c.c)([Object(L.o)()],t.prototype,"customMeshPosition",void 0),Object(c.c)([Object(L.c)()],t.prototype,"useCustomMeshPosition",void 0),Object(c.c)([Object(L.c)()],t.prototype,"invert",void 0),Object(c.c)([Object(L.k)()],t.prototype,"mesh",void 0),Object(c.c)([Object(L.c)()],t.prototype,"excludedMeshes",void 0),Object(c.c)([Object(L.c)()],t.prototype,"exposure",void 0),Object(c.c)([Object(L.c)()],t.prototype,"decay",void 0),Object(c.c)([Object(L.c)()],t.prototype,"weight",void 0),Object(c.c)([Object(L.c)()],t.prototype,"density",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.VolumetricLightScatteringPostProcess"]=jd;var Ng=`
-
-precision highp float;
-
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform sampler2D normalSampler;
-uniform float curvature_ridge;
-uniform float curvature_valley;
-#ifndef CURVATURE_OFFSET
-#define CURVATURE_OFFSET 1
-#endif
-float curvature_soft_clamp(float curvature,float control)
-{
-if (curvature<0.5/control)
-return curvature*(1.0-curvature*control);
-return 0.25/control;
-}
-float calculate_curvature(ivec2 texel,float ridge,float valley)
-{
-vec2 normal_up=texelFetchOffset(normalSampler,texel,0,ivec2(0,CURVATURE_OFFSET)).rb;
-vec2 normal_down=texelFetchOffset(normalSampler,texel,0,ivec2(0,-CURVATURE_OFFSET)).rb;
-vec2 normal_left=texelFetchOffset(normalSampler,texel,0,ivec2(-CURVATURE_OFFSET,0)).rb;
-vec2 normal_right=texelFetchOffset(normalSampler,texel,0,ivec2( CURVATURE_OFFSET,0)).rb;
-float normal_diff=((normal_up.g-normal_down.g)+(normal_right.r-normal_left.r));
-if (normal_diff<0.0)
-return -2.0*curvature_soft_clamp(-normal_diff,valley);
-return 2.0*curvature_soft_clamp(normal_diff,ridge);
-}
-void main(void)
-{
-ivec2 texel=ivec2(gl_FragCoord.xy);
-vec4 baseColor=texture2D(textureSampler,vUV);
-float curvature=calculate_curvature(texel,curvature_ridge,curvature_valley);
-baseColor.rgb*=curvature+1.0;
-gl_FragColor=baseColor;
-}`;ze.a.ShadersStore.screenSpaceCurvaturePixelShader=Ng;var Hd=function(r){function t(e,n,i,o,a,s,d,p,b){p===void 0&&(p=h.a.TEXTURETYPE_UNSIGNED_INT),b===void 0&&(b=!1);var P=r.call(this,e,"screenSpaceCurvature",["curvature_ridge","curvature_valley"],["textureSampler","normalSampler"],i,o,a,s,d,void 0,p,void 0,null,b)||this;return P.ridge=1,P.valley=1,P._geometryBufferRenderer=n.enableGeometryBufferRenderer(),P._geometryBufferRenderer?P.onApply=function(O){O.setFloat("curvature_ridge",.5/Math.max(P.ridge*P.ridge,1e-4)),O.setFloat("curvature_valley",.7/Math.max(P.valley*P.valley,1e-4));var B=P._geometryBufferRenderer.getGBuffer().textures[1];O.setTexture("normalSampler",B)}:l.a.Error("Multiple Render Target support needed for screen space curvature post process. Please use IsSupported test first."),P}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ScreenSpaceCurvaturePostProcess"},Object.defineProperty(t,"IsSupported",{get:function(){var e=te.a.LastCreatedEngine;return!!e&&(e.webGLVersion>1||e.getCaps().drawBuffersExtension)},enumerable:!1,configurable:!0}),t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,i,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.textureType,e.reusable)},e,i,o)},Object(c.c)([Object(L.c)()],t.prototype,"ridge",void 0),Object(c.c)([Object(L.c)()],t.prototype,"valley",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.ScreenSpaceCurvaturePostProcess"]=Hd,f(166),f(167),Object.defineProperty(_e.a.prototype,"forceShowBoundingBoxes",{get:function(){return this._forceShowBoundingBoxes||!1},set:function(r){this._forceShowBoundingBoxes=r,r&&this.getBoundingBoxRenderer()},enumerable:!0,configurable:!0}),_e.a.prototype.getBoundingBoxRenderer=function(){return this._boundingBoxRenderer||(this._boundingBoxRenderer=new Wd(this)),this._boundingBoxRenderer},Object.defineProperty(Dt.a.prototype,"showBoundingBox",{get:function(){return this._showBoundingBox||!1},set:function(r){this._showBoundingBox=r,r&&this.getScene().getBoundingBoxRenderer()},enumerable:!0,configurable:!0});var Wd=function(){function r(t){this.name=at.a.NAME_BOUNDINGBOXRENDERER,this.frontColor=new M.a(1,1,1),this.backColor=new M.a(.1,.1,.1),this.showBackLines=!0,this.onBeforeBoxRenderingObservable=new x.c,this.onAfterBoxRenderingObservable=new x.c,this.onResourcesReadyObservable=new x.c,this.enabled=!0,this.renderList=new fi.a(32),this._vertexBuffers={},this._fillIndexBuffer=null,this._fillIndexData=null,this.scene=t,t._addComponent(this)}return r.prototype.register=function(){this.scene._beforeEvaluateActiveMeshStage.registerStep(at.a.STEP_BEFOREEVALUATEACTIVEMESH_BOUNDINGBOXRENDERER,this,this.reset),this.scene._preActiveMeshStage.registerStep(at.a.STEP_PREACTIVEMESH_BOUNDINGBOXRENDERER,this,this._preActiveMesh),this.scene._evaluateSubMeshStage.registerStep(at.a.STEP_EVALUATESUBMESH_BOUNDINGBOXRENDERER,this,this._evaluateSubMesh),this.scene._afterRenderingGroupDrawStage.registerStep(at.a.STEP_AFTERRENDERINGGROUPDRAW_BOUNDINGBOXRENDERER,this,this.render)},r.prototype._evaluateSubMesh=function(t,e){if(t.showSubMeshesBoundingBox){var n=e.getBoundingInfo();n!=null&&(n.boundingBox._tag=t.renderingGroupId,this.renderList.push(n.boundingBox))}},r.prototype._preActiveMesh=function(t){if(t.showBoundingBox||this.scene.forceShowBoundingBoxes){var e=t.getBoundingInfo();e.boundingBox._tag=t.renderingGroupId,this.renderList.push(e.boundingBox)}},r.prototype._prepareResources=function(){if(!this._colorShader){this._colorShader=new ua.a("colorShader",this.scene,"color",{attributes:[Oe.b.PositionKind],uniforms:["world","viewProjection","color"]}),this._colorShader.reservedDataStore={hidden:!0};var t=this.scene.getEngine(),e=ft.a.CreateBox({size:1});this._vertexBuffers[Oe.b.PositionKind]=new Oe.b(t,e.positions,Oe.b.PositionKind,!1),this._createIndexBuffer(),this._fillIndexData=e.indices,this.onResourcesReadyObservable.notifyObservers(this)}},r.prototype._createIndexBuffer=function(){var t=this.scene.getEngine();this._indexBuffer=t.createIndexBuffer([0,1,1,2,2,3,3,0,4,5,5,6,6,7,7,4,0,7,1,6,2,5,3,4])},r.prototype.rebuild=function(){var t=this._vertexBuffers[Oe.b.PositionKind];t&&t._rebuild(),this._createIndexBuffer()},r.prototype.reset=function(){this.renderList.reset()},r.prototype.render=function(t){if(this.renderList.length!==0&&this.enabled&&(this._prepareResources(),this._colorShader.isReady())){var e=this.scene.getEngine();e.setDepthWrite(!1),this._colorShader._preBind();for(var n=0;n<this.renderList.length;n++){var i=this.renderList.data[n];if(i._tag===t){this.onBeforeBoxRenderingObservable.notifyObservers(i);var o=i.minimum,a=i.maximum.subtract(o),s=o.add(a.scale(.5)),d=u.a.Scaling(a.x,a.y,a.z).multiply(u.a.Translation(s.x,s.y,s.z)).multiply(i.getWorldMatrix());e.bindBuffers(this._vertexBuffers,this._indexBuffer,this._colorShader.getEffect()),this.showBackLines&&(e.setDepthFunctionToGreaterOrEqual(),this.scene.resetCachedMaterial(),this._colorShader.setColor4("color",this.backColor.toColor4()),this._colorShader.bind(d),e.drawElementsType(Ht.a.LineListDrawMode,0,24)),e.setDepthFunctionToLess(),this.scene.resetCachedMaterial(),this._colorShader.setColor4("color",this.frontColor.toColor4()),this._colorShader.bind(d),e.drawElementsType(Ht.a.LineListDrawMode,0,24),this.onAfterBoxRenderingObservable.notifyObservers(i)}}this._colorShader.unbind(),e.setDepthFunctionToLessOrEqual(),e.setDepthWrite(!0)}},r.prototype.renderOcclusionBoundingBox=function(t){if(this._prepareResources(),this._colorShader.isReady()&&t._boundingInfo){var e=this.scene.getEngine();this._fillIndexBuffer||(this._fillIndexBuffer=e.createIndexBuffer(this._fillIndexData)),e.setDepthWrite(!1),e.setColorWrite(!1),this._colorShader._preBind();var n=t._boundingInfo.boundingBox,i=n.minimum,o=n.maximum.subtract(i),a=i.add(o.scale(.5)),s=u.a.Scaling(o.x,o.y,o.z).multiply(u.a.Translation(a.x,a.y,a.z)).multiply(n.getWorldMatrix());e.bindBuffers(this._vertexBuffers,this._fillIndexBuffer,this._colorShader.getEffect()),e.setDepthFunctionToLess(),this.scene.resetCachedMaterial(),this._colorShader.bind(s),e.drawElementsType(Ht.a.TriangleFillMode,0,36),this._colorShader.unbind(),e.setDepthFunctionToLessOrEqual(),e.setDepthWrite(!0),e.setColorWrite(!0)}},r.prototype.dispose=function(){if(this._colorShader){this.onBeforeBoxRenderingObservable.clear(),this.onAfterBoxRenderingObservable.clear(),this.onResourcesReadyObservable.clear(),this.renderList.dispose(),this._colorShader.dispose();var t=this._vertexBuffers[Oe.b.PositionKind];t&&(t.dispose(),this._vertexBuffers[Oe.b.PositionKind]=null),this.scene.getEngine()._releaseBuffer(this._indexBuffer),this._fillIndexBuffer&&(this.scene.getEngine()._releaseBuffer(this._fillIndexBuffer),this._fillIndexBuffer=null)}},r}();_e.a.prototype.enableDepthRenderer=function(r,t,e){if(t===void 0&&(t=!1),e===void 0&&(e=!1),!(r=r||this.activeCamera))throw"No camera available to enable depth renderer";if(this._depthRenderer||(this._depthRenderer={}),!this._depthRenderer[r.id]){var n=!!this.getEngine().getCaps().textureFloatRender,i=0;i=!this.getEngine().getCaps().textureHalfFloatRender||e&&n?n?h.a.TEXTURETYPE_FLOAT:h.a.TEXTURETYPE_UNSIGNED_BYTE:h.a.TEXTURETYPE_HALF_FLOAT,this._depthRenderer[r.id]=new oa(this,i,r,t)}return this._depthRenderer[r.id]},_e.a.prototype.disableDepthRenderer=function(r){(r=r||this.activeCamera)&&this._depthRenderer&&this._depthRenderer[r.id]&&(this._depthRenderer[r.id].dispose(),delete this._depthRenderer[r.id])};var Xd=function(){function r(t){this.name=at.a.NAME_DEPTHRENDERER,this.scene=t}return r.prototype.register=function(){this.scene._gatherRenderTargetsStage.registerStep(at.a.STEP_GATHERRENDERTARGETS_DEPTHRENDERER,this,this._gatherRenderTargets),this.scene._gatherActiveCameraRenderTargetsStage.registerStep(at.a.STEP_GATHERACTIVECAMERARENDERTARGETS_DEPTHRENDERER,this,this._gatherActiveCameraRenderTargets)},r.prototype.rebuild=function(){},r.prototype.dispose=function(){for(var t in this.scene._depthRenderer)this.scene._depthRenderer[t].dispose()},r.prototype._gatherRenderTargets=function(t){if(this.scene._depthRenderer)for(var e in this.scene._depthRenderer){var n=this.scene._depthRenderer[e];n.enabled&&!n.useOnlyInActiveCamera&&t.push(n.getDepthMap())}},r.prototype._gatherActiveCameraRenderTargets=function(t){if(this.scene._depthRenderer)for(var e in this.scene._depthRenderer){var n=this.scene._depthRenderer[e];n.enabled&&n.useOnlyInActiveCamera&&this.scene.activeCamera.id===e&&t.push(n.getDepthMap())}},r}();oa._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_DEPTHRENDERER);t||(t=new Xd(r),r._addComponent(t))},ze.a.ShadersStore.linePixelShader=`uniform vec4 color;
-void main(void) {
-gl_FragColor=color;
-}`;var wg=`#include<instancesDeclaration>
-
-attribute vec3 position;
-attribute vec4 normal;
-
-uniform mat4 viewProjection;
-uniform float width;
-uniform float aspectRatio;
-void main(void) {
-#include<instancesVertex>
-mat4 worldViewProjection=viewProjection*finalWorld;
-vec4 viewPosition=worldViewProjection*vec4(position,1.0);
-vec4 viewPositionNext=worldViewProjection*vec4(normal.xyz,1.0);
-vec2 currentScreen=viewPosition.xy/viewPosition.w;
-vec2 nextScreen=viewPositionNext.xy/viewPositionNext.w;
-currentScreen.x*=aspectRatio;
-nextScreen.x*=aspectRatio;
-vec2 dir=normalize(nextScreen-currentScreen);
-vec2 normalDir=vec2(-dir.y,dir.x);
-normalDir*=width/2.0;
-normalDir.x/=aspectRatio;
-vec4 offset=vec4(normalDir*normal.w,0.0,0.0);
-gl_Position=viewPosition+offset;
-}`;ze.a.ShadersStore.lineVertexShader=wg,Dt.a.prototype.disableEdgesRendering=function(){return this._edgesRenderer&&(this._edgesRenderer.dispose(),this._edgesRenderer=null),this},Dt.a.prototype.enableEdgesRendering=function(r,t,e){return r===void 0&&(r=.95),t===void 0&&(t=!1),this.disableEdgesRendering(),this._edgesRenderer=new Hc(this,r,t,!0,e),this},Object.defineProperty(Dt.a.prototype,"edgesRenderer",{get:function(){return this._edgesRenderer},enumerable:!0,configurable:!0}),So.b.prototype.enableEdgesRendering=function(r,t){return r===void 0&&(r=.95),t===void 0&&(t=!1),this.disableEdgesRendering(),this._edgesRenderer=new Yd(this,r,t),this},So.a.prototype.enableEdgesRendering=function(r,t){return r===void 0&&(r=.95),t===void 0&&(t=!1),So.b.prototype.enableEdgesRendering.apply(this,arguments),this};var Fg=function(){this.edges=new Array,this.edgesConnectedCount=0},Hc=function(){function r(t,e,n,i,o){var a,s=this;e===void 0&&(e=.95),n===void 0&&(n=!1),i===void 0&&(i=!0),this.edgesWidthScalerForOrthographic=1e3,this.edgesWidthScalerForPerspective=50,this._linesPositions=new Array,this._linesNormals=new Array,this._linesIndices=new Array,this._buffers={},this._buffersForInstances={},this._checkVerticesInsteadOfIndices=!1,this.isEnabled=!0,this.customInstances=new fi.a(32),this._source=t,this._checkVerticesInsteadOfIndices=n,this._options=o??null,this._epsilon=e,this._prepareRessources(),i&&((a=o?.useAlternateEdgeFinder)===null||a===void 0||a?this._generateEdgesLinesAlternate():this._generateEdgesLines()),this._meshRebuildObserver=this._source.onRebuildObservable.add(function(){s._rebuild()}),this._meshDisposeObserver=this._source.onDisposeObservable.add(function(){s.dispose()})}return Object.defineProperty(r.prototype,"linesPositions",{get:function(){return this._linesPositions},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"linesNormals",{get:function(){return this._linesNormals},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"linesIndices",{get:function(){return this._linesIndices},enumerable:!1,configurable:!0}),r.GetShader=function(t){if(!t._edgeRenderLineShader){var e=new ua.a("lineShader",t,"line",{attributes:["position","normal"],uniforms:["world","viewProjection","color","width","aspectRatio"]});e.disableDepthWrite=!0,e.backFaceCulling=!1,t._edgeRenderLineShader=e}return t._edgeRenderLineShader},r.prototype._prepareRessources=function(){this._lineShader||(this._lineShader=r.GetShader(this._source.getScene()))},r.prototype._rebuild=function(){var t=this._buffers[Oe.b.PositionKind];t&&t._rebuild(),(t=this._buffers[Oe.b.NormalKind])&&t._rebuild();var e=this._source.getScene().getEngine();this._ib=e.createIndexBuffer(this._linesIndices)},r.prototype.dispose=function(){this._source.onRebuildObservable.remove(this._meshRebuildObserver),this._source.onDisposeObservable.remove(this._meshDisposeObserver);var t=this._buffers[Oe.b.PositionKind];t&&(t.dispose(),this._buffers[Oe.b.PositionKind]=null),(t=this._buffers[Oe.b.NormalKind])&&(t.dispose(),this._buffers[Oe.b.NormalKind]=null),this._ib&&this._source.getScene().getEngine()._releaseBuffer(this._ib),this._lineShader.dispose()},r.prototype._processEdgeForAdjacencies=function(t,e,n,i,o){return t===n&&e===i||t===i&&e===n?0:t===i&&e===o||t===o&&e===i?1:t===o&&e===n||t===n&&e===o?2:-1},r.prototype._processEdgeForAdjacenciesWithVertices=function(t,e,n,i,o){var a=1e-10;return t.equalsWithEpsilon(n,a)&&e.equalsWithEpsilon(i,a)||t.equalsWithEpsilon(i,a)&&e.equalsWithEpsilon(n,a)?0:t.equalsWithEpsilon(i,a)&&e.equalsWithEpsilon(o,a)||t.equalsWithEpsilon(o,a)&&e.equalsWithEpsilon(i,a)?1:t.equalsWithEpsilon(o,a)&&e.equalsWithEpsilon(n,a)||t.equalsWithEpsilon(n,a)&&e.equalsWithEpsilon(o,a)?2:-1},r.prototype._checkEdge=function(t,e,n,i,o){var a;e===void 0?a=!0:a=u.e.Dot(n[t],n[e])<this._epsilon,a&&this.createLine(i,o,this._linesPositions.length/3)},r.prototype.createLine=function(t,e,n){this._linesPositions.push(t.x,t.y,t.z,t.x,t.y,t.z,e.x,e.y,e.z,e.x,e.y,e.z),this._linesNormals.push(e.x,e.y,e.z,-1,e.x,e.y,e.z,1,t.x,t.y,t.z,-1,t.x,t.y,t.z,1),this._linesIndices.push(n,n+1,n+2,n,n+2,n+3)},r.prototype._tessellateTriangle=function(t,e,n,i){var o=function(Ae,Ee,Se){Se>=0&&Ee.push(Se);for(var Le=0;Le<Ae.length;++Le)Ee.push(Ae[Le][0])},a=0;t[1].length>=t[0].length&&t[1].length>=t[2].length?a=1:t[2].length>=t[0].length&&t[2].length>=t[1].length&&(a=2);for(var s=0;s<3;++s)s===a?t[s].sort(function(Ae,Ee){return Ae[1]<Ee[1]?-1:Ae[1]>Ee[1]?1:0}):t[s].sort(function(Ae,Ee){return Ae[1]>Ee[1]?-1:Ae[1]<Ee[1]?1:0});var d=[],p=[];o(t[a],d,-1);for(var b=d.length,P=a+2;P>=a+1;--P)o(t[P%3],p,P!==a+2?i[n[e+(P+1)%3]]:-1);var O=p.length;n.push(i[n[e+a]],d[0],p[0]),n.push(i[n[e+(a+1)%3]],p[O-1],d[b-1]);for(var B=b<=O,F=B?b:O,z=B?O:b,J=B?b-1:O-1,ie=B?0:1,se=b+O-2,ce=0,ue=0,fe=B?d:p,ve=B?p:d,Te=0;se-- >0;){ie?n.push(fe[ce],ve[ue]):n.push(ve[ue],fe[ce]);var Re=void 0;(Te+=F)>=z&&ce<J?(Re=fe[++ce],Te-=z):Re=ve[++ue],n.push(Re)}n[e+0]=n[n.length-3],n[e+1]=n[n.length-2],n[e+2]=n[n.length-1],n.length=n.length-3},r.prototype._generateEdgesLinesAlternate=function(){var t,e,n,i,o,a,s,d,p,b=this._source.getVerticesData(Oe.b.PositionKind),P=this._source.getIndices();if(P&&b){Array.isArray(P)||(P=Xe.b.SliceToArray(P));var O=(e=(t=this._options)===null||t===void 0?void 0:t.useFastVertexMerger)===null||e===void 0||e,B=O?Math.round(-Math.log((i=(n=this._options)===null||n===void 0?void 0:n.epsilonVertexMerge)!==null&&i!==void 0?i:1e-6)/Math.log(10)):(a=(o=this._options)===null||o===void 0?void 0:o.epsilonVertexMerge)!==null&&a!==void 0?a:1e-6,F=[],z=[];if(O)for(var J={},ie=0;ie<b.length;ie+=3){var se=b[ie+0],ce=b[ie+1],ue=b[ie+2];if(J[Mt=se.toFixed(B)+"|"+ce.toFixed(B)+"|"+ue.toFixed(B)]!==void 0)F.push(J[Mt]);else{var fe=ie/3;J[Mt]=fe,F.push(fe),z.push(fe)}}else for(ie=0;ie<b.length;ie+=3){se=b[ie+0],ce=b[ie+1],ue=b[ie+2];for(var ve=!1,Te=0;Te<ie&&!ve;Te+=3){var Re=b[Te+0],Ae=b[Te+1],Ee=b[Te+2];if(Math.abs(se-Re)<B&&Math.abs(ce-Ae)<B&&Math.abs(ue-Ee)<B){F.push(Te/3),ve=!0;break}}ve||(F.push(ie/3),z.push(ie/3))}if(!((s=this._options)===null||s===void 0)&&s.applyTessellation){for(var Se=(p=(d=this._options)===null||d===void 0?void 0:d.epsilonVertexAligned)!==null&&p!==void 0?p:1e-6,Le=[],Ce=0;Ce<P.length;Ce+=3)for(var Ne=void 0,Ie=0;Ie<3;++Ie){var Fe=F[P[Ce+Ie]],Ye=F[P[Ce+(Ie+1)%3]],tt=F[P[Ce+(Ie+2)%3]];if(Fe!==Ye)for(var it=b[3*Fe+0],lt=b[3*Fe+1],Qe=b[3*Fe+2],ot=b[3*Ye+0],rt=b[3*Ye+1],Ze=b[3*Ye+2],dt=Math.sqrt((ot-it)*(ot-it)+(rt-lt)*(rt-lt)+(Ze-Qe)*(Ze-Qe)),Ve=0;Ve<z.length-1;Ve++){var Je=z[Ve];if(Je!==Fe&&Je!==Ye&&Je!==tt){var yt=b[3*Je+0],Wt=b[3*Je+1],Nt=b[3*Je+2],Qt=Math.sqrt((yt-it)*(yt-it)+(Wt-lt)*(Wt-lt)+(Nt-Qe)*(Nt-Qe)),vt=Math.sqrt((yt-ot)*(yt-ot)+(Wt-rt)*(Wt-rt)+(Nt-Ze)*(Nt-Ze));Math.abs(Qt+vt-dt)<Se&&(Ne||(Ne={index:Ce,edgesPoints:[[],[],[]]},Le.push(Ne)),Ne.edgesPoints[Ie].push([Je,Qt]))}}}for(var Jt=0;Jt<Le.length;++Jt){var Xt=Le[Jt];this._tessellateTriangle(Xt.edgesPoints,Xt.index,P,F)}Le=null}var zt={};for(Ce=0;Ce<P.length;Ce+=3){var Yt=void 0;for(Ie=0;Ie<3;++Ie)if(Fe=F[P[Ce+Ie]],Ye=F[P[Ce+(Ie+1)%3]],tt=F[P[Ce+(Ie+2)%3]],Fe!==Ye){if(u.c.Vector3[0].copyFromFloats(b[3*Fe+0],b[3*Fe+1],b[3*Fe+2]),u.c.Vector3[1].copyFromFloats(b[3*Ye+0],b[3*Ye+1],b[3*Ye+2]),u.c.Vector3[2].copyFromFloats(b[3*tt+0],b[3*tt+1],b[3*tt+2]),Yt||(u.c.Vector3[1].subtractToRef(u.c.Vector3[0],u.c.Vector3[3]),u.c.Vector3[2].subtractToRef(u.c.Vector3[1],u.c.Vector3[4]),(Yt=u.e.Cross(u.c.Vector3[3],u.c.Vector3[4])).normalize()),Fe>Ye){var Et=Fe;Fe=Ye,Ye=Et}($t=zt[Mt=Fe+"_"+Ye])?$t.done||(u.e.Dot(Yt,$t.normal)<this._epsilon&&this.createLine(u.c.Vector3[0],u.c.Vector3[1],this._linesPositions.length/3),$t.done=!0):zt[Mt]={normal:Yt,done:!1,index:Ce,i:Ie}}}for(var Mt in zt){var $t;($t=zt[Mt]).done||(Fe=F[P[$t.index+$t.i]],Ye=F[P[$t.index+($t.i+1)%3]],u.c.Vector3[0].copyFromFloats(b[3*Fe+0],b[3*Fe+1],b[3*Fe+2]),u.c.Vector3[1].copyFromFloats(b[3*Ye+0],b[3*Ye+1],b[3*Ye+2]),this.createLine(u.c.Vector3[0],u.c.Vector3[1],this._linesPositions.length/3))}var Dn=this._source.getScene().getEngine();this._buffers[Oe.b.PositionKind]=new Oe.b(Dn,this._linesPositions,Oe.b.PositionKind,!1),this._buffers[Oe.b.NormalKind]=new Oe.b(Dn,this._linesNormals,Oe.b.NormalKind,!1,!1,4),this._buffersForInstances[Oe.b.PositionKind]=this._buffers[Oe.b.PositionKind],this._buffersForInstances[Oe.b.NormalKind]=this._buffers[Oe.b.NormalKind],this._ib=Dn.createIndexBuffer(this._linesIndices),this._indicesCount=this._linesIndices.length}},r.prototype._generateEdgesLines=function(){var t=this._source.getVerticesData(Oe.b.PositionKind),e=this._source.getIndices();if(e&&t){var n,i,o=new Array,a=new Array;for(n=0;n<e.length;n+=3){i=new Fg;var s=e[n],d=e[n+1],p=e[n+2];i.p0=new u.e(t[3*s],t[3*s+1],t[3*s+2]),i.p1=new u.e(t[3*d],t[3*d+1],t[3*d+2]),i.p2=new u.e(t[3*p],t[3*p+1],t[3*p+2]);var b=u.e.Cross(i.p1.subtract(i.p0),i.p2.subtract(i.p1));b.normalize(),a.push(b),o.push(i)}for(n=0;n<o.length;n++){i=o[n];for(var P=n+1;P<o.length;P++){var O=o[P];if(i.edgesConnectedCount===3)break;if(O.edgesConnectedCount!==3)for(var B=e[3*P],F=e[3*P+1],z=e[3*P+2],J=0;J<3;J++){var ie=0;if(i.edges[J]===void 0){switch(J){case 0:ie=this._checkVerticesInsteadOfIndices?this._processEdgeForAdjacenciesWithVertices(i.p0,i.p1,O.p0,O.p1,O.p2):this._processEdgeForAdjacencies(e[3*n],e[3*n+1],B,F,z);break;case 1:ie=this._checkVerticesInsteadOfIndices?this._processEdgeForAdjacenciesWithVertices(i.p1,i.p2,O.p0,O.p1,O.p2):this._processEdgeForAdjacencies(e[3*n+1],e[3*n+2],B,F,z);break;case 2:ie=this._checkVerticesInsteadOfIndices?this._processEdgeForAdjacenciesWithVertices(i.p2,i.p0,O.p0,O.p1,O.p2):this._processEdgeForAdjacencies(e[3*n+2],e[3*n],B,F,z)}if(ie!==-1&&(i.edges[J]=P,O.edges[ie]=n,i.edgesConnectedCount++,O.edgesConnectedCount++,i.edgesConnectedCount===3))break}}}}for(n=0;n<o.length;n++){var se=o[n];this._checkEdge(n,se.edges[0],a,se.p0,se.p1),this._checkEdge(n,se.edges[1],a,se.p1,se.p2),this._checkEdge(n,se.edges[2],a,se.p2,se.p0)}var ce=this._source.getScene().getEngine();this._buffers[Oe.b.PositionKind]=new Oe.b(ce,this._linesPositions,Oe.b.PositionKind,!1),this._buffers[Oe.b.NormalKind]=new Oe.b(ce,this._linesNormals,Oe.b.NormalKind,!1,!1,4),this._buffersForInstances[Oe.b.PositionKind]=this._buffers[Oe.b.PositionKind],this._buffersForInstances[Oe.b.NormalKind]=this._buffers[Oe.b.NormalKind],this._ib=ce.createIndexBuffer(this._linesIndices),this._indicesCount=this._linesIndices.length}},r.prototype.isReady=function(){return this._lineShader.isReady(this._source,this._source.hasInstances&&this.customInstances.length>0||this._source.hasThinInstances)},r.prototype.render=function(){var t=this._source.getScene();if(this.isReady()&&t.activeCamera){var e=t.getEngine();this._lineShader._preBind(),this._source.edgesColor.a!==1?e.setAlphaMode(h.a.ALPHA_COMBINE):e.setAlphaMode(h.a.ALPHA_DISABLE);var n=this._source.hasInstances&&this.customInstances.length>0,i=n||this._source.hasThinInstances,o=0;if(i)if(this._buffersForInstances.world0=this._source.getVertexBuffer("world0"),this._buffersForInstances.world1=this._source.getVertexBuffer("world1"),this._buffersForInstances.world2=this._source.getVertexBuffer("world2"),this._buffersForInstances.world3=this._source.getVertexBuffer("world3"),n){var a=this._source._instanceDataStorage;if(o=this.customInstances.length,!a.isFrozen){for(var s=0,d=0;d<o;++d)this.customInstances.data[d].copyToArray(a.instancesData,s),s+=16;a.instancesBuffer.updateDirectly(a.instancesData,0,o)}}else o=this._source.thinInstanceCount;e.bindBuffers(i?this._buffersForInstances:this._buffers,this._ib,this._lineShader.getEffect()),t.resetCachedMaterial(),this._lineShader.setColor4("color",this._source.edgesColor),t.activeCamera.mode===gt.a.ORTHOGRAPHIC_CAMERA?this._lineShader.setFloat("width",this._source.edgesWidth/this.edgesWidthScalerForOrthographic):this._lineShader.setFloat("width",this._source.edgesWidth/this.edgesWidthScalerForPerspective),this._lineShader.setFloat("aspectRatio",e.getAspectRatio(t.activeCamera)),this._lineShader.bind(this._source.getWorldMatrix()),e.drawElementsType(Ht.a.TriangleFillMode,0,this._indicesCount,o),this._lineShader.unbind(),i&&e.unbindInstanceAttributes(),this._source.getScene()._activeMeshesFrozen||this.customInstances.reset()}},r}(),Yd=function(r){function t(e,n,i){n===void 0&&(n=.95),i===void 0&&(i=!1);var o=r.call(this,e,n,i,!1)||this;return o._generateEdgesLines(),o}return Object(c.d)(t,r),t.prototype._generateEdgesLines=function(){var e=this._source.getVerticesData(Oe.b.PositionKind),n=this._source.getIndices();if(n&&e){for(var i=u.c.Vector3[0],o=u.c.Vector3[1],a=n.length-1,s=0,d=0;s<a;s+=2,d+=4)u.e.FromArrayToRef(e,3*n[s],i),u.e.FromArrayToRef(e,3*n[s+1],o),this.createLine(i,o,d);var p=this._source.getScene().getEngine();this._buffers[Oe.b.PositionKind]=new Oe.b(p,this._linesPositions,Oe.b.PositionKind,!1),this._buffers[Oe.b.NormalKind]=new Oe.b(p,this._linesNormals,Oe.b.NormalKind,!1,!1,4),this._ib=p.createIndexBuffer(this._linesIndices),this._indicesCount=this._linesIndices.length}},t}(Hc),Wc=function(){function r(t){this._textureFormats=[{type:h.a.PREPASS_IRRADIANCE_TEXTURE_TYPE,format:h.a.TEXTURETYPE_HALF_FLOAT},{type:h.a.PREPASS_POSITION_TEXTURE_TYPE,format:h.a.TEXTURETYPE_HALF_FLOAT},{type:h.a.PREPASS_VELOCITY_TEXTURE_TYPE,format:h.a.TEXTURETYPE_HALF_FLOAT},{type:h.a.PREPASS_REFLECTIVITY_TEXTURE_TYPE,format:h.a.TEXTURETYPE_UNSIGNED_INT},{type:h.a.PREPASS_COLOR_TEXTURE_TYPE,format:h.a.TEXTURETYPE_HALF_FLOAT},{type:h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE,format:h.a.TEXTURETYPE_HALF_FLOAT},{type:h.a.PREPASS_ALBEDO_TEXTURE_TYPE,format:h.a.TEXTURETYPE_UNSIGNED_INT}],this.excludedSkinnedMesh=[],this.excludedMaterials=[],this._textureIndices=[],this._isDirty=!1,this.mrtCount=0,this._postProcesses=[],this._clearColor=new M.b(0,0,0,0),this._effectConfigurations=[],this._mrtFormats=[],this._enabled=!1,this._useGeometryBufferFallback=!1,this.disableGammaTransform=!1,this._scene=t,this._engine=t.getEngine(),r._SceneComponentInitialization(this._scene),this._resetLayout()}return Object.defineProperty(r.prototype,"enabled",{get:function(){return this._enabled},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"samples",{get:function(){return this.prePassRT.samples},set:function(t){this.imageProcessingPostProcess||this._createCompositionEffect(),this.prePassRT.samples=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"useGeometryBufferFallback",{get:function(){return this._useGeometryBufferFallback},set:function(t){if(this._useGeometryBufferFallback=t,t){if(this._geometryBuffer=this._scene.enableGeometryBufferRenderer(),!this._geometryBuffer)return void(this._useGeometryBufferFallback=!1);this._geometryBuffer.renderList=[],this._geometryBuffer._linkPrePassRenderer(this),this._updateGeometryBufferLayout()}else this._geometryBuffer&&this._geometryBuffer._unlinkPrePassRenderer(),this._geometryBuffer=null,this._scene.disableGeometryBufferRenderer()},enumerable:!1,configurable:!0}),r.prototype._initializeAttachments=function(){for(var t=[],e=[!1],n=[!0],i=0;i<this.mrtCount;i++)t.push(!0),i>0&&(e.push(!0),n.push(!1));this._multiRenderAttachments=this._engine.buildTextureLayout(t),this._clearAttachments=this._engine.buildTextureLayout(e),this._defaultAttachments=this._engine.buildTextureLayout(n)},r.prototype._createCompositionEffect=function(){this.prePassRT=new qs("sceneprePassRT",{width:this._engine.getRenderWidth(),height:this._engine.getRenderHeight()},this.mrtCount,this._scene,{generateMipMaps:!1,generateDepthTexture:!0,defaultType:h.a.TEXTURETYPE_UNSIGNED_INT,types:this._mrtFormats}),this.prePassRT.samples=1,this._initializeAttachments(),this._useGeometryBufferFallback&&!this._geometryBuffer&&(this.useGeometryBufferFallback=!0),this.imageProcessingPostProcess=new Go("sceneCompositionPass",1,null,void 0,this._engine),this.imageProcessingPostProcess.autoClear=!1},Object.defineProperty(r.prototype,"isSupported",{get:function(){return this._engine.webGLVersion>1||this._scene.getEngine().getCaps().drawBuffersExtension},enumerable:!1,configurable:!0}),r.prototype.bindAttachmentsForEffect=function(t,e){if(this.enabled){if(t._multiTarget)this._engine.bindAttachments(this._multiRenderAttachments);else if(this._engine.bindAttachments(this._defaultAttachments),this._geometryBuffer){var n=e.getMaterial();n&&this.excludedMaterials.indexOf(n)===-1&&this._geometryBuffer.renderList.push(e.getRenderingMesh())}}},r.prototype.restoreAttachments=function(){this.enabled&&this._defaultAttachments&&this._engine.bindAttachments(this._defaultAttachments)},r.prototype._beforeCameraDraw=function(){this._isDirty&&this._update(),this._geometryBuffer&&(this._geometryBuffer.renderList.length=0),this._bindFrameBuffer()},r.prototype._afterCameraDraw=function(){if(this._enabled){var t=this._scene.activeCamera&&this._scene.activeCamera._getFirstPostProcess();t&&this._postProcesses.length&&this._scene.postProcessManager._prepareFrame(),this._scene.postProcessManager.directRender(this._postProcesses,t?t.inputTexture:null)}},r.prototype._checkRTSize=function(){var t=this._engine.getRenderWidth(!0),e=this._engine.getRenderHeight(!0),n=this.prePassRT.getRenderWidth(),i=this.prePassRT.getRenderHeight();n===t&&i===e||(this.prePassRT.resize({width:t,height:e}),this._updateGeometryBufferLayout(),this._bindPostProcessChain())},r.prototype._bindFrameBuffer=function(){if(this._enabled){this._checkRTSize();var t=this.prePassRT.getInternalTexture();t&&this._engine.bindFramebuffer(t)}},r.prototype.clear=function(){this._enabled&&(this._bindFrameBuffer(),this._engine.clear(this._scene.clearColor,this._scene.autoClear||this._scene.forceWireframe||this._scene.forcePointsCloud,this._scene.autoClearDepthAndStencil,this._scene.autoClearDepthAndStencil),this._engine.bindAttachments(this._clearAttachments),this._engine.clear(this._clearColor,!0,!1,!1),this._engine.bindAttachments(this._defaultAttachments))},r.prototype._setState=function(t){this._enabled=t,this._scene.prePass=t,this.imageProcessingPostProcess&&(this.imageProcessingPostProcess.imageProcessingConfiguration.applyByPostProcess=t)},r.prototype._updateGeometryBufferLayout=function(){if(this._geometryBuffer){this._geometryBuffer._resetLayout();for(var t=[],e=0;e<this._mrtLayout.length;e++)t.push(!1);this._geometryBuffer._linkInternalTexture(this.prePassRT.getInternalTexture());var n=[{prePassConstant:h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE,geometryBufferConstant:ui.DEPTHNORMAL_TEXTURE_TYPE},{prePassConstant:h.a.PREPASS_POSITION_TEXTURE_TYPE,geometryBufferConstant:ui.POSITION_TEXTURE_TYPE},{prePassConstant:h.a.PREPASS_REFLECTIVITY_TEXTURE_TYPE,geometryBufferConstant:ui.REFLECTIVITY_TEXTURE_TYPE},{prePassConstant:h.a.PREPASS_VELOCITY_TEXTURE_TYPE,geometryBufferConstant:ui.VELOCITY_TEXTURE_TYPE}];for(e=0;e<n.length;e++){var i=this._mrtLayout.indexOf(n[e].prePassConstant);i!==-1&&(this._geometryBuffer._forceTextureType(n[e].geometryBufferConstant,i),t[i]=!0)}this._geometryBuffer._setAttachments(this._engine.buildTextureLayout(t))}},r.prototype.addEffectConfiguration=function(t){for(var e=0;e<this._effectConfigurations.length;e++)if(this._effectConfigurations[e].name===t.name)return this._effectConfigurations[e];return this._effectConfigurations.push(t),t},r.prototype.getIndex=function(t){return this._textureIndices[t]},r.prototype._enable=function(){for(var t,e,n=this.mrtCount,i=0;i<this._effectConfigurations.length;i++)this._effectConfigurations[i].enabled&&this._enableTextures(this._effectConfigurations[i].texturesRequired);for(this.prePassRT&&this.mrtCount!==n&&this.prePassRT.updateCount(this.mrtCount,{types:this._mrtFormats}),this._updateGeometryBufferLayout(),this._resetPostProcessChain(),i=0;i<this._effectConfigurations.length;i++)this._effectConfigurations[i].enabled&&(!this._effectConfigurations[i].postProcess&&this._effectConfigurations[i].createPostProcess&&this._effectConfigurations[i].createPostProcess(),this._effectConfigurations[i].postProcess&&this._postProcesses.push(this._effectConfigurations[i].postProcess));this._initializeAttachments(),this.imageProcessingPostProcess||this._createCompositionEffect();var o=!1;if(!((t=this._scene.activeCamera)===null||t===void 0)&&t._postProcesses)for(i=0;i<this._scene.activeCamera._postProcesses.length;i++)((e=this._scene.activeCamera._postProcesses[i])===null||e===void 0?void 0:e.getClassName())==="ImageProcessingPostProcess"&&(o=!0);o||this.disableGammaTransform||this._postProcesses.push(this.imageProcessingPostProcess),this._bindPostProcessChain(),this._setState(!0)},r.prototype._disable=function(){this._setState(!1),this._resetLayout();for(var t=0;t<this._effectConfigurations.length;t++)this._effectConfigurations[t].enabled=!1},r.prototype._resetLayout=function(){for(var t=0;t<this._textureFormats.length;t++)this._textureIndices[this._textureFormats[t].type]=-1;this._textureIndices[h.a.PREPASS_COLOR_TEXTURE_TYPE]=0,this._mrtLayout=[h.a.PREPASS_COLOR_TEXTURE_TYPE],this._mrtFormats=[h.a.TEXTURETYPE_HALF_FLOAT],this.mrtCount=1},r.prototype._resetPostProcessChain=function(){this._postProcesses=[],this.imageProcessingPostProcess&&this.imageProcessingPostProcess.restoreDefaultInputTexture();for(var t=0;t<this._effectConfigurations.length;t++)this._effectConfigurations[t].postProcess&&this._effectConfigurations[t].postProcess.restoreDefaultInputTexture()},r.prototype._bindPostProcessChain=function(){var t;if(this._postProcesses.length)this._postProcesses[0].inputTexture=this.prePassRT.getInternalTexture();else{var e=(t=this._scene.activeCamera)===null||t===void 0?void 0:t._getFirstPostProcess();e&&(e.inputTexture=this.prePassRT.getInternalTexture())}},r.prototype.markAsDirty=function(){this._isDirty=!0},r.prototype._enableTextures=function(t){for(var e=0;e<t.length;e++){var n=t[e];this._textureIndices[n]===-1&&(this._textureIndices[n]=this._mrtLayout.length,this._mrtLayout.push(n),this._mrtFormats.push(this._textureFormats[n].format),this.mrtCount++)}},r.prototype._update=function(){this._disable();for(var t=!1,e=0;e<this._scene.materials.length;e++)this._scene.materials[e].setPrePassRenderer(this)&&(t=!0);var n=this._scene.activeCamera;if(n){var i=n._postProcesses.filter(function(o){return o!=null});if(i)for(e=0;e<i.length;e++)i[e].setPrePassRenderer(this)&&(t=!0);this._markAllMaterialsAsPrePassDirty(),this._isDirty=!1,t&&this._enable(),this.enabled||(this._engine.restoreDefaultFramebuffer(),this._engine.restoreSingleAttachment())}},r.prototype._markAllMaterialsAsPrePassDirty=function(){for(var t=this._scene.materials,e=0;e<t.length;e++)t[e].markAsDirty(Ht.a.PrePassDirtyFlag)},r.prototype.dispose=function(){for(var t=0;t<this._effectConfigurations.length;t++)this._effectConfigurations[t].dispose&&this._effectConfigurations[t].dispose();this.imageProcessingPostProcess.dispose(),this.prePassRT.dispose()},r._SceneComponentInitialization=function(t){throw An.a.WarnImport("PrePassRendererSceneComponent")},r}();Object.defineProperty(_e.a.prototype,"prePassRenderer",{get:function(){return this._prePassRenderer},set:function(r){r&&r.isSupported&&(this._prePassRenderer=r)},enumerable:!0,configurable:!0}),_e.a.prototype.enablePrePassRenderer=function(){return this._prePassRenderer||(this._prePassRenderer=new Wc(this),this._prePassRenderer.isSupported||(this._prePassRenderer=null,l.a.Error(`PrePassRenderer needs WebGL 2 support.
-Maybe you tried to use the following features that need the PrePassRenderer :
- + Subsurface Scattering`))),this._prePassRenderer},_e.a.prototype.disablePrePassRenderer=function(){this._prePassRenderer&&(this._prePassRenderer.dispose(),this._prePassRenderer=null)};var Kd=function(){function r(t){this.name=at.a.NAME_PREPASSRENDERER,this.scene=t}return r.prototype.register=function(){this.scene._beforeCameraDrawStage.registerStep(at.a.STEP_BEFORECAMERADRAW_PREPASS,this,this._beforeCameraDraw),this.scene._afterCameraDrawStage.registerStep(at.a.STEP_AFTERCAMERADRAW_PREPASS,this,this._afterCameraDraw),this.scene._beforeClearStage.registerStep(at.a.STEP_BEFORECLEARSTAGE_PREPASS,this,this._beforeClearStage),this.scene._beforeRenderingMeshStage.registerStep(at.a.STEP_BEFORERENDERINGMESH_PREPASS,this,this._beforeRenderingMeshStage),this.scene._afterRenderingMeshStage.registerStep(at.a.STEP_AFTERRENDERINGMESH_PREPASS,this,this._afterRenderingMeshStage)},r.prototype._beforeCameraDraw=function(){this.scene.prePassRenderer&&this.scene.prePassRenderer._beforeCameraDraw()},r.prototype._afterCameraDraw=function(){this.scene.prePassRenderer&&this.scene.prePassRenderer._afterCameraDraw()},r.prototype._beforeClearStage=function(){this.scene.prePassRenderer&&this.scene.prePassRenderer.clear()},r.prototype._beforeRenderingMeshStage=function(t,e,n,i){if(i){var o=t.getScene();o.prePassRenderer&&o.prePassRenderer.bindAttachmentsForEffect(i,e)}},r.prototype._afterRenderingMeshStage=function(t){var e=t.getScene();e.prePassRenderer&&e.prePassRenderer.restoreAttachments()},r.prototype.rebuild=function(){},r.prototype.dispose=function(){},r}();Wc._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_PREPASSRENDERER);t||(t=new Kd(r),r._addComponent(t))};var Bg=`#define rcp(x) 1./x
-#define GOLDEN_RATIO 1.618033988749895
-#define TWO_PI 6.2831855
-
-
-vec2 Golden2dSeq(int i,float n)
-{
-
-
-return vec2(float(i)/n+(0.5/n),fract(float(i)*rcp(GOLDEN_RATIO)));
-}
-vec2 SampleDiskGolden(int i,int sampleCount)
-{
-vec2 f=Golden2dSeq(i,float(sampleCount));
-return vec2(sqrt(f.x),TWO_PI*f.y);
-}`;ze.a.IncludesShadersStore.fibonacci=Bg;var Ug=`uniform vec3 diffusionS[5];
-uniform float diffusionD[5];
-uniform float filterRadii[5];`;ze.a.IncludesShadersStore.diffusionProfile=Ug;var Vg=`
-#include<fibonacci>
-#include<helperFunctions>
-#include<subSurfaceScatteringFunctions>
-#include<diffusionProfile>
-varying vec2 vUV;
-uniform vec2 texelSize;
-uniform sampler2D textureSampler;
-uniform sampler2D irradianceSampler;
-uniform sampler2D depthSampler;
-uniform sampler2D albedoSampler;
-uniform vec2 viewportSize;
-uniform float metersPerUnit;
-const float LOG2_E=1.4426950408889634;
-const float SSS_PIXELS_PER_SAMPLE=4.;
-const int _SssSampleBudget=40;
-#define rcp(x) 1./x
-#define Sq(x) x*x
-#define SSS_BILATERAL_FILTER true
-
-
-vec3 EvalBurleyDiffusionProfile(float r,vec3 S)
-{
-vec3 exp_13=exp2(((LOG2_E*(-1.0/3.0))*r)*S);
-vec3 expSum=exp_13*(1.+exp_13*exp_13);
-return (S*rcp(8.*PI))*expSum;
-}
-
-
-
-
-
-
-vec2 SampleBurleyDiffusionProfile(float u,float rcpS)
-{
-u=1.-u;
-float g=1.+(4.*u)*(2.*u+sqrt(1.+(4.*u)*u));
-float n=exp2(log2(g)*(-1.0/3.0));
-float p=(g*n)*n;
-float c=1.+p+n;
-float d=(3./LOG2_E*2.)+(3./LOG2_E)*log2(u);
-float x=(3./LOG2_E)*log2(c)-d;
-
-
-
-
-
-
-float rcpExp=((c*c)*c)*rcp((4.*u)*((c*c)+(4.*u)*(4.*u)));
-float r=x*rcpS;
-float rcpPdf=(8.*PI*rcpS)*rcpExp;
-return vec2(r,rcpPdf);
-}
-
-
-vec3 ComputeBilateralWeight(float xy2,float z,float mmPerUnit,vec3 S,float rcpPdf)
-{
-#ifndef SSS_BILATERAL_FILTER
-z=0.;
-#endif
-
-
-
-float r=sqrt(xy2+(z*mmPerUnit)*(z*mmPerUnit));
-float area=rcpPdf;
-#if SSS_CLAMP_ARTIFACT
-return clamp(EvalBurleyDiffusionProfile(r,S)*area,0.0,1.0);
-#else
-return EvalBurleyDiffusionProfile(r,S)*area;
-#endif
-}
-void EvaluateSample(int i,int n,vec3 S,float d,vec3 centerPosVS,float mmPerUnit,float pixelsPerMm,
-float phase,inout vec3 totalIrradiance,inout vec3 totalWeight)
-{
-
-float scale=rcp(float(n));
-float offset=rcp(float(n))*0.5;
-
-float sinPhase,cosPhase;
-sinPhase=sin(phase);
-cosPhase=cos(phase);
-vec2 bdp=SampleBurleyDiffusionProfile(float(i)*scale+offset,d);
-float r=bdp.x;
-float rcpPdf=bdp.y;
-float phi=SampleDiskGolden(i,n).y;
-float sinPhi,cosPhi;
-sinPhi=sin(phi);
-cosPhi=cos(phi);
-float sinPsi=cosPhase*sinPhi+sinPhase*cosPhi;
-float cosPsi=cosPhase*cosPhi-sinPhase*sinPhi;
-vec2 vec=r*vec2(cosPsi,sinPsi);
-
-vec2 position;
-float xy2;
-position=vUV+round((pixelsPerMm*r)*vec2(cosPsi,sinPsi))*texelSize;
-xy2=r*r;
-vec4 textureSample=texture2D(irradianceSampler,position);
-float viewZ=texture2D(depthSampler,position).r;
-vec3 irradiance=textureSample.rgb;
-if (testLightingForSSS(textureSample.a))
-{
-
-float relZ=viewZ-centerPosVS.z;
-vec3 weight=ComputeBilateralWeight(xy2,relZ,mmPerUnit,S,rcpPdf);
-totalIrradiance+=weight*irradiance;
-totalWeight+=weight;
-}
-else
-{
-
-
-
-
-
-
-}
-}
-void main(void)
-{
-vec4 irradianceAndDiffusionProfile=texture2D(irradianceSampler,vUV);
-vec3 centerIrradiance=irradianceAndDiffusionProfile.rgb;
-int diffusionProfileIndex=int(round(irradianceAndDiffusionProfile.a*255.));
-float centerDepth=0.;
-vec4 inputColor=texture2D(textureSampler,vUV);
-bool passedStencilTest=testLightingForSSS(irradianceAndDiffusionProfile.a);
-if (passedStencilTest)
-{
-centerDepth=texture2D(depthSampler,vUV).r;
-}
-if (!passedStencilTest) {
-gl_FragColor=inputColor;
-return;
-}
-float distScale=1.;
-vec3 S=diffusionS[diffusionProfileIndex];
-float d=diffusionD[diffusionProfileIndex];
-float filterRadius=filterRadii[diffusionProfileIndex];
-
-vec2 centerPosNDC=vUV;
-vec2 cornerPosNDC=vUV+0.5*texelSize;
-vec3 centerPosVS=vec3(centerPosNDC*viewportSize,1.0)*centerDepth;
-vec3 cornerPosVS=vec3(cornerPosNDC*viewportSize,1.0)*centerDepth;
-
-float mmPerUnit=1000.*(metersPerUnit*rcp(distScale));
-float unitsPerMm=rcp(mmPerUnit);
-
-
-float unitsPerPixel=2.*abs(cornerPosVS.x-centerPosVS.x);
-float pixelsPerMm=rcp(unitsPerPixel)*unitsPerMm;
-
-float filterArea=PI*Sq(filterRadius*pixelsPerMm);
-int sampleCount=int(filterArea*rcp(SSS_PIXELS_PER_SAMPLE));
-int sampleBudget=_SssSampleBudget;
-int texturingMode=0;
-vec3 albedo=texture2D(albedoSampler,vUV).rgb;
-if (distScale == 0. || sampleCount<1)
-{
-#ifdef DEBUG_SSS_SAMPLES
-vec3 green=vec3(0.,1.,0.);
-gl_FragColor=vec4(green,1.0);
-return;
-#endif
-gl_FragColor=vec4(inputColor.rgb+albedo*centerIrradiance,1.0);
-return;
-}
-#ifdef DEBUG_SSS_SAMPLES
-vec3 red=vec3(1.,0.,0.);
-vec3 blue=vec3(0.,0.,1.);
-gl_FragColor=vec4(mix(blue,red,clamp(float(sampleCount)/float(sampleBudget),0.0,1.0)),1.0);
-return;
-#endif
-
-float phase=0.;
-int n=min(sampleCount,sampleBudget);
-
-vec3 centerWeight=vec3(0.);
-vec3 totalIrradiance=vec3(0.);
-vec3 totalWeight=vec3(0.);
-for (int i=0; i<n; i++)
-{
-
-EvaluateSample(i,n,S,d,centerPosVS,mmPerUnit,pixelsPerMm,
-phase,totalIrradiance,totalWeight);
-}
-
-totalWeight=max(totalWeight,HALF_MIN);
-gl_FragColor=vec4(inputColor.rgb+albedo*max(totalIrradiance/totalWeight,vec3(0.0)),1.);
-}`;ze.a.ShadersStore.subSurfaceScatteringPixelShader=Vg;var kg=function(r){function t(e,n,i,o,a,s,d,p){o===void 0&&(o=null),p===void 0&&(p=h.a.TEXTURETYPE_UNSIGNED_INT);var b=r.call(this,e,"subSurfaceScattering",["texelSize","viewportSize","metersPerUnit"],["diffusionS","diffusionD","filterRadii","irradianceSampler","depthSampler","albedoSampler"],i,o,a||we.a.BILINEAR_SAMPLINGMODE,s,d,null,p,"postprocess",void 0,!0)||this;return b._scene=n,b.updateEffect(),b.onApplyObservable.add(function(P){if(n.prePassRenderer&&n.subSurfaceConfiguration){var O=b.texelSize;P.setFloat("metersPerUnit",n.subSurfaceConfiguration.metersPerUnit),P.setFloat2("texelSize",O.x,O.y),P.setTexture("irradianceSampler",n.prePassRenderer.prePassRT.textures[n.prePassRenderer.getIndex(h.a.PREPASS_IRRADIANCE_TEXTURE_TYPE)]),P.setTexture("depthSampler",n.prePassRenderer.prePassRT.textures[n.prePassRenderer.getIndex(h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE)]),P.setTexture("albedoSampler",n.prePassRenderer.prePassRT.textures[n.prePassRenderer.getIndex(h.a.PREPASS_ALBEDO_TEXTURE_TYPE)]),P.setFloat2("viewportSize",Math.tan(n.activeCamera.fov/2)*n.getEngine().getAspectRatio(n.activeCamera,!0),Math.tan(n.activeCamera.fov/2)),P.setArray3("diffusionS",n.subSurfaceConfiguration.ssDiffusionS),P.setArray("diffusionD",n.subSurfaceConfiguration.ssDiffusionD),P.setArray("filterRadii",n.subSurfaceConfiguration.ssFilterRadii)}else l.a.Error("PrePass and subsurface configuration needs to be enabled for subsurface scattering.")}),b}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"SubSurfaceScatteringPostProcess"},t}(_t),Qd=function(){function r(t){this._ssDiffusionS=[],this._ssFilterRadii=[],this._ssDiffusionD=[],this.enabled=!1,this.name=at.a.NAME_SUBSURFACE,this.ssDiffusionProfileColors=[],this.metersPerUnit=1,this.texturesRequired=[h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE,h.a.PREPASS_ALBEDO_TEXTURE_TYPE,h.a.PREPASS_COLOR_TEXTURE_TYPE,h.a.PREPASS_IRRADIANCE_TEXTURE_TYPE],this.addDiffusionProfile(new M.a(1,1,1)),this._scene=t,r._SceneComponentInitialization(this._scene)}return Object.defineProperty(r.prototype,"ssDiffusionS",{get:function(){return this._ssDiffusionS},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"ssDiffusionD",{get:function(){return this._ssDiffusionD},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"ssFilterRadii",{get:function(){return this._ssFilterRadii},enumerable:!1,configurable:!0}),r.prototype.addDiffusionProfile=function(t){if(this.ssDiffusionD.length>=5)return l.a.Error("You already reached the maximum number of diffusion profiles."),0;for(var e=0;e<this._ssDiffusionS.length/3;e++)if(this._ssDiffusionS[3*e]===t.r&&this._ssDiffusionS[3*e+1]===t.g&&this._ssDiffusionS[3*e+2]===t.b)return e;return this._ssDiffusionS.push(t.r,t.b,t.g),this._ssDiffusionD.push(Math.max(Math.max(t.r,t.b),t.g)),this._ssFilterRadii.push(this.getDiffusionProfileParameters(t)),this.ssDiffusionProfileColors.push(t),this._ssDiffusionD.length-1},r.prototype.createPostProcess=function(){return this.postProcess=new kg("subSurfaceScattering",this._scene,1,null,void 0,this._scene.getEngine()),this.postProcess.autoClear=!1,this.postProcess},r.prototype.clearAllDiffusionProfiles=function(){this._ssDiffusionD=[],this._ssDiffusionS=[],this._ssFilterRadii=[],this.ssDiffusionProfileColors=[]},r.prototype.dispose=function(){this.clearAllDiffusionProfiles(),this.postProcess.dispose()},r.prototype.getDiffusionProfileParameters=function(t){var e=Math.max(t.r,t.g,t.b);return this._sampleBurleyDiffusionProfile(.997,e)},r.prototype._sampleBurleyDiffusionProfile=function(t,e){var n=1+4*(t=1-t)*(2*t+Math.sqrt(1+4*t*t)),i=Math.pow(n,-1/3),o=1+n*i*i+i;return 3*Math.log(o/(4*t))*e},r._SceneComponentInitialization=function(t){throw An.a.WarnImport("PrePassRendererSceneComponent")},r}();U.a.AddParser(at.a.NAME_SUBSURFACE,function(r,t){if(r.ssDiffusionProfileColors!==void 0&&r.ssDiffusionProfileColors!==null&&(t.enableSubSurfaceForPrePass(),t.subSurfaceConfiguration))for(var e=0,n=r.ssDiffusionProfileColors.length;e<n;e++){var i=r.ssDiffusionProfileColors[e];t.subSurfaceConfiguration.addDiffusionProfile(new M.a(i.r,i.g,i.b))}}),Object.defineProperty(_e.a.prototype,"subSurfaceConfiguration",{get:function(){return this._subSurfaceConfiguration},set:function(r){r&&this.enablePrePassRenderer()&&(this._subSurfaceConfiguration=r)},enumerable:!0,configurable:!0}),_e.a.prototype.enableSubSurfaceForPrePass=function(){if(this._subSurfaceConfiguration)return this._subSurfaceConfiguration;var r=this.enablePrePassRenderer();return r?(this._subSurfaceConfiguration=new Qd(this),r.addEffectConfiguration(this._subSurfaceConfiguration),this._subSurfaceConfiguration):null},_e.a.prototype.disableSubSurfaceForPrePass=function(){this._subSurfaceConfiguration&&(this._subSurfaceConfiguration.dispose(),this._subSurfaceConfiguration=null)};var qd=function(){function r(t){this.name=at.a.NAME_PREPASSRENDERER,this.scene=t}return r.prototype.register=function(){},r.prototype.serialize=function(t){if(this.scene.subSurfaceConfiguration){var e=this.scene.subSurfaceConfiguration.ssDiffusionProfileColors;t.ssDiffusionProfileColors=[];for(var n=0;n<e.length;n++)t.ssDiffusionProfileColors.push({r:e[n].r,g:e[n].g,b:e[n].b})}},r.prototype.addFromContainer=function(t){},r.prototype.removeFromContainer=function(t,e){this.scene.prePassRenderer&&this.scene.subSurfaceConfiguration&&this.scene.subSurfaceConfiguration.clearAllDiffusionProfiles()},r.prototype.rebuild=function(){},r.prototype.dispose=function(){},r}();Qd._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_SUBSURFACE);t||(t=new qd(r),r._addComponent(t))};var Gg=`#ifdef LOGARITHMICDEPTH
-#extension GL_EXT_frag_depth : enable
-#endif
-uniform vec4 color;
-#ifdef ALPHATEST
-varying vec2 vUV;
-uniform sampler2D diffuseSampler;
-#endif
-#include<logDepthDeclaration>
-void main(void) {
-#ifdef ALPHATEST
-if (texture2D(diffuseSampler,vUV).a<0.4)
-discard;
-#endif
-#include<logDepthFragment>
-gl_FragColor=color;
-}`;ze.a.ShadersStore.outlinePixelShader=Gg;var zg=`
-attribute vec3 position;
-attribute vec3 normal;
-#include<bonesDeclaration>
-#include<morphTargetsVertexGlobalDeclaration>
-#include<morphTargetsVertexDeclaration>[0..maxSimultaneousMorphTargets]
-
-uniform float offset;
-#include<instancesDeclaration>
-uniform mat4 viewProjection;
-#ifdef ALPHATEST
-varying vec2 vUV;
-uniform mat4 diffuseMatrix;
-#ifdef UV1
-attribute vec2 uv;
-#endif
-#ifdef UV2
-attribute vec2 uv2;
-#endif
-#endif
-#include<logDepthDeclaration>
-void main(void)
-{
-vec3 positionUpdated=position;
-vec3 normalUpdated=normal;
-#ifdef UV1
-vec2 uvUpdated=uv;
-#endif
-#include<morphTargetsVertex>[0..maxSimultaneousMorphTargets]
-vec3 offsetPosition=positionUpdated+(normalUpdated*offset);
-#include<instancesVertex>
-#include<bonesVertex>
-gl_Position=viewProjection*finalWorld*vec4(offsetPosition,1.0);
-#ifdef ALPHATEST
-#ifdef UV1
-vUV=vec2(diffuseMatrix*vec4(uvUpdated,1.0,0.0));
-#endif
-#ifdef UV2
-vUV=vec2(diffuseMatrix*vec4(uv2,1.0,0.0));
-#endif
-#endif
-#include<logDepthVertex>
-}
-`;ze.a.ShadersStore.outlineVertexShader=zg,_e.a.prototype.getOutlineRenderer=function(){return this._outlineRenderer||(this._outlineRenderer=new Zd(this)),this._outlineRenderer},Object.defineProperty(De.a.prototype,"renderOutline",{get:function(){return this._renderOutline},set:function(r){r&&this.getScene().getOutlineRenderer(),this._renderOutline=r},enumerable:!0,configurable:!0}),Object.defineProperty(De.a.prototype,"renderOverlay",{get:function(){return this._renderOverlay},set:function(r){r&&this.getScene().getOutlineRenderer(),this._renderOverlay=r},enumerable:!0,configurable:!0});var Zd=function(){function r(t){this.name=at.a.NAME_OUTLINERENDERER,this.zOffset=1,this.scene=t,this._engine=t.getEngine(),this.scene._addComponent(this)}return r.prototype.register=function(){this.scene._beforeRenderingMeshStage.registerStep(at.a.STEP_BEFORERENDERINGMESH_OUTLINE,this,this._beforeRenderingMesh),this.scene._afterRenderingMeshStage.registerStep(at.a.STEP_AFTERRENDERINGMESH_OUTLINE,this,this._afterRenderingMesh)},r.prototype.rebuild=function(){},r.prototype.dispose=function(){},r.prototype.render=function(t,e,n){var i=this;n===void 0&&(n=!1);var o=this.scene,a=o.getEngine(),s=a.getCaps().instancedArrays&&(e.visibleInstances[t._id]!==null&&e.visibleInstances[t._id]!==void 0||t.getRenderingMesh().hasThinInstances);if(this.isReady(t,s)){var d=t.getMesh(),p=d._internalAbstractMeshDataInfo._actAsRegularMesh?d:null,b=t.getRenderingMesh(),P=p||b,O=t.getMaterial();if(O&&o.activeCamera){if(a.enableEffect(this._effect),O.useLogarithmicDepth&&this._effect.setFloat("logarithmicDepthConstant",2/(Math.log(o.activeCamera.maxZ+1)/Math.LN2)),this._effect.setFloat("offset",n?0:b.outlineWidth),this._effect.setColor4("color",n?b.overlayColor:b.outlineColor,n?b.overlayAlpha:O.alpha),this._effect.setMatrix("viewProjection",o.getTransformMatrix()),this._effect.setMatrix("world",P.getWorldMatrix()),b.useBones&&b.computeBonesUsingShaders&&b.skeleton&&this._effect.setMatrices("mBones",b.skeleton.getTransformMatrices(b)),et.a.BindMorphTargetParameters(b,this._effect),b._bind(t,this._effect,O.fillMode),O&&O.needAlphaTesting()){var B=O.getAlphaTestTexture();B&&(this._effect.setTexture("diffuseSampler",B),this._effect.setMatrix("diffuseMatrix",B.getTextureMatrix()))}a.setZOffset(-this.zOffset),b._processRendering(P,t,this._effect,O.fillMode,e,s,function(F,z){i._effect.setMatrix("world",z)}),a.setZOffset(0)}}},r.prototype.isReady=function(t,e){var n=[],i=[Oe.b.PositionKind,Oe.b.NormalKind],o=t.getMesh(),a=t.getMaterial();a&&(a.needAlphaTesting()&&(n.push("#define ALPHATEST"),o.isVerticesDataPresent(Oe.b.UVKind)&&(i.push(Oe.b.UVKind),n.push("#define UV1")),o.isVerticesDataPresent(Oe.b.UV2Kind)&&(i.push(Oe.b.UV2Kind),n.push("#define UV2"))),a.useLogarithmicDepth&&n.push("#define LOGARITHMICDEPTH")),o.useBones&&o.computeBonesUsingShaders?(i.push(Oe.b.MatricesIndicesKind),i.push(Oe.b.MatricesWeightsKind),o.numBoneInfluencers>4&&(i.push(Oe.b.MatricesIndicesExtraKind),i.push(Oe.b.MatricesWeightsExtraKind)),n.push("#define NUM_BONE_INFLUENCERS "+o.numBoneInfluencers),n.push("#define BonesPerMesh "+(o.skeleton?o.skeleton.bones.length+1:0))):n.push("#define NUM_BONE_INFLUENCERS 0");var s=o.morphTargetManager,d=0;s&&s.numInfluencers>0&&(d=s.numInfluencers,n.push("#define MORPHTARGETS"),n.push("#define NUM_MORPH_INFLUENCERS "+d),et.a.PrepareAttributesForMorphTargetsInfluencers(i,o,d)),e&&(n.push("#define INSTANCES"),et.a.PushAttributesForInstances(i),t.getRenderingMesh().hasThinInstances&&n.push("#define THIN_INSTANCES"));var p=n.join(`
-`);return this._cachedDefines!==p&&(this._cachedDefines=p,this._effect=this.scene.getEngine().createEffect("outline",i,["world","mBones","viewProjection","diffuseMatrix","offset","color","logarithmicDepthConstant","morphTargetInfluences"],["diffuseSampler"],p,void 0,void 0,void 0,{maxSimultaneousMorphTargets:d})),this._effect.isReady()},r.prototype._beforeRenderingMesh=function(t,e,n){if(this._savedDepthWrite=this._engine.getDepthWrite(),t.renderOutline){var i=e.getMaterial();i&&i.needAlphaBlendingForMesh(t)&&(this._engine.cacheStencilState(),this._engine.setDepthWrite(!1),this._engine.setColorWrite(!1),this._engine.setStencilBuffer(!0),this._engine.setStencilOperationPass(h.a.REPLACE),this._engine.setStencilFunction(h.a.ALWAYS),this._engine.setStencilMask(r._StencilReference),this._engine.setStencilFunctionReference(r._StencilReference),this.render(e,n,!0),this._engine.setColorWrite(!0),this._engine.setStencilFunction(h.a.NOTEQUAL)),this._engine.setDepthWrite(!1),this.render(e,n),this._engine.setDepthWrite(this._savedDepthWrite),i&&i.needAlphaBlendingForMesh(t)&&this._engine.restoreStencilState()}},r.prototype._afterRenderingMesh=function(t,e,n){if(t.renderOverlay){var i=this._engine.getAlphaMode(),o=this._engine.alphaState.alphaBlend;this._engine.setAlphaMode(h.a.ALPHA_COMBINE),this.render(e,n,!0),this._engine.setAlphaMode(i),this._engine.setDepthWrite(this._savedDepthWrite),this._engine.alphaState.alphaBlend=o}t.renderOutline&&this._savedDepthWrite&&(this._engine.setDepthWrite(!0),this._engine.setColorWrite(!1),this.render(e,n),this._engine.setColorWrite(!0))},r._StencilReference=4,r}(),jg=f(148),Jd=function(r){function t(e,n){var i=r.call(this)||this;return i.name=e,i.animations=new Array,i.isPickable=!1,i.useAlphaForPicking=!1,i.onDisposeObservable=new x.c,i._onAnimationEnd=null,i._endAnimation=function(){i._onAnimationEnd&&i._onAnimationEnd(),i.disposeWhenFinishedAnimating&&i.dispose()},i.color=new M.b(1,1,1,1),i.position=u.e.Zero(),i._manager=n,i._manager.sprites.push(i),i.uniqueId=i._manager.scene.getUniqueId(),i}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"size",{get:function(){return this.width},set:function(e){this.width=e,this.height=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"manager",{get:function(){return this._manager},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"Sprite"},Object.defineProperty(t.prototype,"fromIndex",{get:function(){return this._fromIndex},set:function(e){this.playAnimation(e,this._toIndex,this._loopAnimation,this._delay,this._onAnimationEnd)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"toIndex",{get:function(){return this._toIndex},set:function(e){this.playAnimation(this._fromIndex,e,this._loopAnimation,this._delay,this._onAnimationEnd)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"loopAnimation",{get:function(){return this._loopAnimation},set:function(e){this.playAnimation(this._fromIndex,this._toIndex,e,this._delay,this._onAnimationEnd)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"delay",{get:function(){return Math.max(this._delay,1)},set:function(e){this.playAnimation(this._fromIndex,this._toIndex,this._loopAnimation,e,this._onAnimationEnd)},enumerable:!1,configurable:!0}),t.prototype.playAnimation=function(e,n,i,o,a){a===void 0&&(a=null),this._onAnimationEnd=a,r.prototype.playAnimation.call(this,e,n,i,o,this._endAnimation)},t.prototype.dispose=function(){for(var e=0;e<this._manager.sprites.length;e++)this._manager.sprites[e]==this&&this._manager.sprites.splice(e,1);this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear()},t.prototype.serialize=function(){var e={};return e.name=this.name,e.position=this.position.asArray(),e.color=this.color.asArray(),e.width=this.width,e.height=this.height,e.angle=this.angle,e.cellIndex=this.cellIndex,e.cellRef=this.cellRef,e.invertU=this.invertU,e.invertV=this.invertV,e.disposeWhenFinishedAnimating=this.disposeWhenFinishedAnimating,e.isPickable=this.isPickable,e.isVisible=this.isVisible,e.useAlphaForPicking=this.useAlphaForPicking,e.animationStarted=this.animationStarted,e.fromIndex=this.fromIndex,e.toIndex=this.toIndex,e.loopAnimation=this.loopAnimation,e.delay=this.delay,e},t.Parse=function(e,n){var i=new t(e.name,n);return i.position=u.e.FromArray(e.position),i.color=M.b.FromArray(e.color),i.width=e.width,i.height=e.height,i.angle=e.angle,i.cellIndex=e.cellIndex,i.cellRef=e.cellRef,i.invertU=e.invertU,i.invertV=e.invertV,i.disposeWhenFinishedAnimating=e.disposeWhenFinishedAnimating,i.isPickable=e.isPickable,i.isVisible=e.isVisible,i.useAlphaForPicking=e.useAlphaForPicking,i.fromIndex=e.fromIndex,i.toIndex=e.toIndex,i.loopAnimation=e.loopAnimation,i.delay=e.delay,e.animationStarted&&i.playAnimation(i.fromIndex,i.toIndex,i.loopAnimation,i.delay),i},t}(function(){function r(){this.width=1,this.height=1,this.angle=0,this.invertU=!1,this.invertV=!1,this.isVisible=!0,this._animationStarted=!1,this._loopAnimation=!1,this._fromIndex=0,this._toIndex=0,this._delay=0,this._direction=1,this._time=0,this._onBaseAnimationEnd=null,this.position={x:1,y:1,z:1},this.color={r:1,g:1,b:1,a:1}}return Object.defineProperty(r.prototype,"animationStarted",{get:function(){return this._animationStarted},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"fromIndex",{get:function(){return this._fromIndex},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"toIndex",{get:function(){return this._toIndex},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"loopAnimation",{get:function(){return this._loopAnimation},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"delay",{get:function(){return Math.max(this._delay,1)},enumerable:!1,configurable:!0}),r.prototype.playAnimation=function(t,e,n,i,o){this._fromIndex=t,this._toIndex=e,this._loopAnimation=n,this._delay=i||1,this._animationStarted=!0,this._onBaseAnimationEnd=o,t<e?this._direction=1:(this._direction=-1,this._toIndex=t,this._fromIndex=e),this.cellIndex=t,this._time=0},r.prototype.stopAnimation=function(){this._animationStarted=!1},r.prototype._animate=function(t){this._animationStarted&&(this._time+=t,this._time>this._delay&&(this._time=this._time%this._delay,this.cellIndex+=this._direction,(this._direction>0&&this.cellIndex>this._toIndex||this._direction<0&&this.cellIndex<this._fromIndex)&&(this._loopAnimation?this.cellIndex=this._direction>0?this._fromIndex:this._toIndex:(this.cellIndex=this._toIndex,this._animationStarted=!1,this._onBaseAnimationEnd&&this._onBaseAnimationEnd()))))},r}());_e.a.prototype._internalPickSprites=function(r,t,e,n){if(!nr.a)return null;var i=null;if(!n){if(!this.activeCamera)return null;n=this.activeCamera}if(this.spriteManagers.length>0)for(var o=0;o<this.spriteManagers.length;o++){var a=this.spriteManagers[o];if(a.isPickable){var s=a.intersects(r,n,t,e);if(s&&s.hit&&(e||i==null||!(s.distance>=i.distance))&&(i=s,e))break}}return i||new nr.a},_e.a.prototype._internalMultiPickSprites=function(r,t,e){if(!nr.a)return null;var n=new Array;if(!e){if(!this.activeCamera)return null;e=this.activeCamera}if(this.spriteManagers.length>0)for(var i=0;i<this.spriteManagers.length;i++){var o=this.spriteManagers[i];if(o.isPickable){var a=o.multiIntersects(r,e,t);a!==null&&(n=n.concat(a))}}return n},_e.a.prototype.pickSprite=function(r,t,e,n,i){return this._tempSpritePickingRay?(this.createPickingRayInCameraSpaceToRef(r,t,this._tempSpritePickingRay,i),this._internalPickSprites(this._tempSpritePickingRay,e,n,i)):null},_e.a.prototype.pickSpriteWithRay=function(r,t,e,n){if(!this._tempSpritePickingRay)return null;if(!n){if(!this.activeCamera)return null;n=this.activeCamera}return fn.a.TransformToRef(r,n.getViewMatrix(),this._tempSpritePickingRay),this._internalPickSprites(this._tempSpritePickingRay,t,e,n)},_e.a.prototype.multiPickSprite=function(r,t,e,n){return this.createPickingRayInCameraSpaceToRef(r,t,this._tempSpritePickingRay,n),this._internalMultiPickSprites(this._tempSpritePickingRay,e,n)},_e.a.prototype.multiPickSpriteWithRay=function(r,t,e){if(!this._tempSpritePickingRay)return null;if(!e){if(!this.activeCamera)return null;e=this.activeCamera}return fn.a.TransformToRef(r,e.getViewMatrix(),this._tempSpritePickingRay),this._internalMultiPickSprites(this._tempSpritePickingRay,t,e)},_e.a.prototype.setPointerOverSprite=function(r){this._pointerOverSprite!==r&&(this._pointerOverSprite&&this._pointerOverSprite.actionManager&&this._pointerOverSprite.actionManager.processTrigger(h.a.ACTION_OnPointerOutTrigger,m.a.CreateNewFromSprite(this._pointerOverSprite,this)),this._pointerOverSprite=r,this._pointerOverSprite&&this._pointerOverSprite.actionManager&&this._pointerOverSprite.actionManager.processTrigger(h.a.ACTION_OnPointerOverTrigger,m.a.CreateNewFromSprite(this._pointerOverSprite,this)))},_e.a.prototype.getPointerOverSprite=function(){return this._pointerOverSprite};var $d=function(){function r(t){this.name=at.a.NAME_SPRITE,this.scene=t,this.scene.spriteManagers=new Array,this.scene._tempSpritePickingRay=fn.a?fn.a.Zero():null,this.scene.onBeforeSpritesRenderingObservable=new x.c,this.scene.onAfterSpritesRenderingObservable=new x.c,this._spritePredicate=function(e){return!!e.actionManager&&e.isPickable&&e.actionManager.hasPointerTriggers}}return r.prototype.register=function(){this.scene._pointerMoveStage.registerStep(at.a.STEP_POINTERMOVE_SPRITE,this,this._pointerMove),this.scene._pointerDownStage.registerStep(at.a.STEP_POINTERDOWN_SPRITE,this,this._pointerDown),this.scene._pointerUpStage.registerStep(at.a.STEP_POINTERUP_SPRITE,this,this._pointerUp)},r.prototype.rebuild=function(){},r.prototype.dispose=function(){this.scene.onBeforeSpritesRenderingObservable.clear(),this.scene.onAfterSpritesRenderingObservable.clear();for(var t=this.scene.spriteManagers;t.length;)t[0].dispose()},r.prototype._pickSpriteButKeepRay=function(t,e,n,i,o){var a=this.scene.pickSprite(e,n,this._spritePredicate,i,o);return a&&(a.ray=t?t.ray:null),a},r.prototype._pointerMove=function(t,e,n,i,o){var a=this.scene;return i?a.setPointerOverSprite(null):(n=this._pickSpriteButKeepRay(n,t,e,!1,a.cameraToUseForPointers||void 0))&&n.hit&&n.pickedSprite?(a.setPointerOverSprite(n.pickedSprite),a.doNotHandleCursors||(a._pointerOverSprite&&a._pointerOverSprite.actionManager&&a._pointerOverSprite.actionManager.hoverCursor?o.style.cursor=a._pointerOverSprite.actionManager.hoverCursor:o.style.cursor=a.hoverCursor)):a.setPointerOverSprite(null),n},r.prototype._pointerDown=function(t,e,n,i){var o=this.scene;if(o._pickedDownSprite=null,o.spriteManagers.length>0&&(n=o.pickSprite(t,e,this._spritePredicate,!1,o.cameraToUseForPointers||void 0))&&n.hit&&n.pickedSprite&&n.pickedSprite.actionManager){switch(o._pickedDownSprite=n.pickedSprite,i.button){case 0:n.pickedSprite.actionManager.processTrigger(h.a.ACTION_OnLeftPickTrigger,m.a.CreateNewFromSprite(n.pickedSprite,o,i));break;case 1:n.pickedSprite.actionManager.processTrigger(h.a.ACTION_OnCenterPickTrigger,m.a.CreateNewFromSprite(n.pickedSprite,o,i));break;case 2:n.pickedSprite.actionManager.processTrigger(h.a.ACTION_OnRightPickTrigger,m.a.CreateNewFromSprite(n.pickedSprite,o,i))}n.pickedSprite.actionManager&&n.pickedSprite.actionManager.processTrigger(h.a.ACTION_OnPickDownTrigger,m.a.CreateNewFromSprite(n.pickedSprite,o,i))}return n},r.prototype._pointerUp=function(t,e,n,i){var o=this.scene;if(o.spriteManagers.length>0){var a=o.pickSprite(t,e,this._spritePredicate,!1,o.cameraToUseForPointers||void 0);a&&(a.hit&&a.pickedSprite&&a.pickedSprite.actionManager&&(a.pickedSprite.actionManager.processTrigger(h.a.ACTION_OnPickUpTrigger,m.a.CreateNewFromSprite(a.pickedSprite,o,i)),a.pickedSprite.actionManager&&(this.scene._inputManager._isPointerSwiping()||a.pickedSprite.actionManager.processTrigger(h.a.ACTION_OnPickTrigger,m.a.CreateNewFromSprite(a.pickedSprite,o,i)))),o._pickedDownSprite&&o._pickedDownSprite.actionManager&&o._pickedDownSprite!==a.pickedSprite&&o._pickedDownSprite.actionManager.processTrigger(h.a.ACTION_OnPickOutTrigger,m.a.CreateNewFromSprite(o._pickedDownSprite,o,i)))}return n},r}();ze.a.IncludesShadersStore.imageProcessingCompatibility=`#ifdef IMAGEPROCESSINGPOSTPROCESS
-gl_FragColor.rgb=pow(gl_FragColor.rgb,vec3(2.2));
-#endif`;var Hg=`uniform bool alphaTest;
-varying vec4 vColor;
-
-varying vec2 vUV;
-uniform sampler2D diffuseSampler;
-
-#include<fogFragmentDeclaration>
-void main(void) {
-vec4 color=texture2D(diffuseSampler,vUV);
-if (alphaTest)
-{
-if (color.a<0.95)
-discard;
-}
-color*=vColor;
-#include<fogFragment>
-gl_FragColor=color;
-#include<imageProcessingCompatibility>
-}`;ze.a.ShadersStore.spritesPixelShader=Hg;var Wg=`
-attribute vec4 position;
-attribute vec2 options;
-attribute vec2 offsets;
-attribute vec2 inverts;
-attribute vec4 cellInfo;
-attribute vec4 color;
-
-uniform mat4 view;
-uniform mat4 projection;
-
-varying vec2 vUV;
-varying vec4 vColor;
-#include<fogVertexDeclaration>
-void main(void) {
-vec3 viewPos=(view*vec4(position.xyz,1.0)).xyz;
-vec2 cornerPos;
-float angle=position.w;
-vec2 size=vec2(options.x,options.y);
-vec2 offset=offsets.xy;
-cornerPos=vec2(offset.x-0.5,offset.y-0.5)*size;
-
-vec3 rotatedCorner;
-rotatedCorner.x=cornerPos.x*cos(angle)-cornerPos.y*sin(angle);
-rotatedCorner.y=cornerPos.x*sin(angle)+cornerPos.y*cos(angle);
-rotatedCorner.z=0.;
-
-viewPos+=rotatedCorner;
-gl_Position=projection*vec4(viewPos,1.0);
-
-vColor=color;
-
-vec2 uvOffset=vec2(abs(offset.x-inverts.x),abs(1.0-offset.y-inverts.y));
-vec2 uvPlace=cellInfo.xy;
-vec2 uvSize=cellInfo.zw;
-vUV.x=uvPlace.x+uvSize.x*uvOffset.x;
-vUV.y=uvPlace.y+uvSize.y*uvOffset.y;
-
-#ifdef FOG
-vFogDistance=viewPos;
-#endif
-}`;ze.a.ShadersStore.spritesVertexShader=Wg;var Xg=function(){function r(t,e,n,i){if(n===void 0&&(n=.01),i===void 0&&(i=null),this.blendMode=h.a.ALPHA_COMBINE,this.autoResetAlpha=!0,this.disableDepthWrite=!1,this.fogEnabled=!0,this._useVAO=!1,this._useInstancing=!1,this._vertexBuffers={},this._capacity=e,this._epsilon=n,this._engine=t,this._useInstancing=t.getCaps().instancedArrays,this._useVAO=t.getCaps().vertexArrayObject&&!t.disableVertexArrayObjects,this._scene=i,!this._useInstancing){for(var o=[],a=0,s=0;s<e;s++)o.push(a),o.push(a+1),o.push(a+2),o.push(a),o.push(a+2),o.push(a+3),a+=4;this._indexBuffer=t.createIndexBuffer(o)}this._vertexBufferSize=this._useInstancing?16:18,this._vertexData=new Float32Array(e*this._vertexBufferSize*(this._useInstancing?1:4)),this._buffer=new Oe.a(t,this._vertexData,!0,this._vertexBufferSize);var d,p=this._buffer.createVertexBuffer(Oe.b.PositionKind,0,4,this._vertexBufferSize,this._useInstancing),b=this._buffer.createVertexBuffer("options",4,2,this._vertexBufferSize,this._useInstancing),P=6;if(this._useInstancing){var O=new Float32Array([0,0,1,0,1,1,0,1]);this._spriteBuffer=new Oe.a(t,O,!1,2),d=this._spriteBuffer.createVertexBuffer("offsets",0,2)}else d=this._buffer.createVertexBuffer("offsets",P,2,this._vertexBufferSize,this._useInstancing),P+=2;var B=this._buffer.createVertexBuffer("inverts",P,2,this._vertexBufferSize,this._useInstancing),F=this._buffer.createVertexBuffer("cellInfo",P+2,4,this._vertexBufferSize,this._useInstancing),z=this._buffer.createVertexBuffer(Oe.b.ColorKind,P+6,4,this._vertexBufferSize,this._useInstancing);this._vertexBuffers[Oe.b.PositionKind]=p,this._vertexBuffers.options=b,this._vertexBuffers.offsets=d,this._vertexBuffers.inverts=B,this._vertexBuffers.cellInfo=F,this._vertexBuffers[Oe.b.ColorKind]=z,this._effectBase=this._engine.createEffect("sprites",[Oe.b.PositionKind,"options","offsets","inverts","cellInfo",Oe.b.ColorKind],["view","projection","textureInfos","alphaTest"],["diffuseSampler"],""),this._scene&&(this._effectFog=this._scene.getEngine().createEffect("sprites",[Oe.b.PositionKind,"options","offsets","inverts","cellInfo",Oe.b.ColorKind],["view","projection","textureInfos","alphaTest","vFogInfos","vFogColor"],["diffuseSampler"],"#define FOG"))}return Object.defineProperty(r.prototype,"capacity",{get:function(){return this._capacity},enumerable:!1,configurable:!0}),r.prototype.render=function(t,e,n,i,o){if(o===void 0&&(o=null),this.texture&&this.texture.isReady()&&t.length){var a=this._effectBase,s=!1;if(this.fogEnabled&&this._scene&&this._scene.fogEnabled&&this._scene.fogMode!==0&&(a=this._effectFog,s=!0),a.isReady()){for(var d=this._engine,p=!(!this._scene||!this._scene.useRightHandedSystem),b=this.texture.getBaseSize(),P=Math.min(this._capacity,t.length),O=0,B=!0,F=0;F<P;F++){var z=t[F];z&&z.isVisible&&(B=!1,z._animate(e),this._appendSpriteVertex(O++,z,0,0,b,p,o),this._useInstancing||(this._appendSpriteVertex(O++,z,1,0,b,p,o),this._appendSpriteVertex(O++,z,1,1,b,p,o),this._appendSpriteVertex(O++,z,0,1,b,p,o)))}if(!B){this._buffer.update(this._vertexData);var J=d.depthCullingState.cull||!0,ie=d.depthCullingState.zOffset;if(p&&this._scene.getEngine().setState(J,ie,!1,!1),d.enableEffect(a),a.setTexture("diffuseSampler",this.texture),a.setMatrix("view",n),a.setMatrix("projection",i),s){var se=this._scene;a.setFloat4("vFogInfos",se.fogMode,se.fogStart,se.fogEnd,se.fogDensity),a.setColor3("vFogColor",se.fogColor)}this._useVAO?(this._vertexArrayObject||(this._vertexArrayObject=d.recordVertexArrayObject(this._vertexBuffers,this._indexBuffer,a)),d.bindVertexArrayObject(this._vertexArrayObject,this._indexBuffer)):d.bindBuffers(this._vertexBuffers,this._indexBuffer,a),d.depthCullingState.depthFunc=h.a.LEQUAL,this.disableDepthWrite||(a.setBool("alphaTest",!0),d.setColorWrite(!1),this._useInstancing?d.drawArraysType(h.a.MATERIAL_TriangleFanDrawMode,0,4,O):d.drawElementsType(h.a.MATERIAL_TriangleFillMode,0,O/4*6),d.setColorWrite(!0),a.setBool("alphaTest",!1)),d.setAlphaMode(this.blendMode),this._useInstancing?d.drawArraysType(h.a.MATERIAL_TriangleFanDrawMode,0,4,O):d.drawElementsType(h.a.MATERIAL_TriangleFillMode,0,O/4*6),this.autoResetAlpha&&d.setAlphaMode(h.a.ALPHA_DISABLE),p&&this._scene.getEngine().setState(J,ie,!1,!0),d.unbindInstanceAttributes()}}}},r.prototype._appendSpriteVertex=function(t,e,n,i,o,a,s){var d=t*this._vertexBufferSize;if(n===0?n=this._epsilon:n===1&&(n=1-this._epsilon),i===0?i=this._epsilon:i===1&&(i=1-this._epsilon),s)s(e,o);else{e.cellIndex||(e.cellIndex=0);var p=o.width/this.cellWidth,b=e.cellIndex/p>>0;e._xOffset=(e.cellIndex-b*p)*this.cellWidth/o.width,e._yOffset=b*this.cellHeight/o.height,e._xSize=this.cellWidth,e._ySize=this.cellHeight}this._vertexData[d]=e.position.x,this._vertexData[d+1]=e.position.y,this._vertexData[d+2]=e.position.z,this._vertexData[d+3]=e.angle,this._vertexData[d+4]=e.width,this._vertexData[d+5]=e.height,this._useInstancing?d-=2:(this._vertexData[d+6]=n,this._vertexData[d+7]=i),this._vertexData[d+8]=a?e.invertU?0:1:e.invertU?1:0,this._vertexData[d+9]=e.invertV?1:0,this._vertexData[d+10]=e._xOffset,this._vertexData[d+11]=e._yOffset,this._vertexData[d+12]=e._xSize/o.width,this._vertexData[d+13]=e._ySize/o.height,this._vertexData[d+14]=e.color.r,this._vertexData[d+15]=e.color.g,this._vertexData[d+16]=e.color.b,this._vertexData[d+17]=e.color.a},r.prototype.dispose=function(){this._buffer&&(this._buffer.dispose(),this._buffer=null),this._spriteBuffer&&(this._spriteBuffer.dispose(),this._spriteBuffer=null),this._indexBuffer&&(this._engine._releaseBuffer(this._indexBuffer),this._indexBuffer=null),this._vertexArrayObject&&(this._engine.releaseVertexArrayObject(this._vertexArrayObject),this._vertexArrayObject=null),this.texture&&(this.texture.dispose(),this.texture=null)},r}(),ef=function(){function r(t,e,n,i,o,a,s,d,p){var b=this;a===void 0&&(a=.01),s===void 0&&(s=we.a.TRILINEAR_SAMPLINGMODE),d===void 0&&(d=!1),p===void 0&&(p=null),this.name=t,this.sprites=new Array,this.renderingGroupId=0,this.layerMask=268435455,this.isPickable=!1,this.onDisposeObservable=new x.c,this.disableDepthWrite=!1,this._packedAndReady=!1,this._customUpdate=function(O,B){O.cellRef||(O.cellIndex=0);var F=O.cellIndex;typeof F=="number"&&isFinite(F)&&Math.floor(F)===F&&(O.cellRef=b._spriteMap[O.cellIndex]),O._xOffset=b._cellData[O.cellRef].frame.x/B.width,O._yOffset=b._cellData[O.cellRef].frame.y/B.height,O._xSize=b._cellData[O.cellRef].frame.w,O._ySize=b._cellData[O.cellRef].frame.h},o||(o=Ue.a.LastCreatedScene),o._getComponent(at.a.NAME_SPRITE)||o._addComponent(new $d(o)),this._fromPacked=d,this._scene=o;var P=this._scene.getEngine();if(this._spriteRenderer=new Xg(P,n,a,o),i.width&&i.height)this.cellWidth=i.width,this.cellHeight=i.height;else{if(i===void 0)return void(this._spriteRenderer=null);this.cellWidth=i,this.cellHeight=i}this._scene.spriteManagers.push(this),this.uniqueId=this.scene.getUniqueId(),e&&(this.texture=new we.a(e,o,!0,!1,s)),this._fromPacked&&this._makePacked(e,p)}return Object.defineProperty(r.prototype,"onDispose",{set:function(t){this._onDisposeObserver&&this.onDisposeObservable.remove(this._onDisposeObserver),this._onDisposeObserver=this.onDisposeObservable.add(t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"children",{get:function(){return this.sprites},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"scene",{get:function(){return this._scene},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"capacity",{get:function(){return this._spriteRenderer.capacity},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"texture",{get:function(){return this._spriteRenderer.texture},set:function(t){t.wrapU=we.a.CLAMP_ADDRESSMODE,t.wrapV=we.a.CLAMP_ADDRESSMODE,this._spriteRenderer.texture=t,this._textureContent=null},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"cellWidth",{get:function(){return this._spriteRenderer.cellWidth},set:function(t){this._spriteRenderer.cellWidth=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"cellHeight",{get:function(){return this._spriteRenderer.cellHeight},set:function(t){this._spriteRenderer.cellHeight=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"fogEnabled",{get:function(){return this._spriteRenderer.fogEnabled},set:function(t){this._spriteRenderer.fogEnabled=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"blendMode",{get:function(){return this._spriteRenderer.blendMode},set:function(t){this._spriteRenderer.blendMode=t},enumerable:!1,configurable:!0}),r.prototype.getClassName=function(){return"SpriteManager"},r.prototype._makePacked=function(t,e){var n=this;if(e!==null)try{var i=void 0;if((i=typeof e=="string"?JSON.parse(e):e).frames.length){for(var o={},a=0;a<i.frames.length;a++){var s=i.frames[a];if(typeof Object.keys(s)[0]!="string")throw new Error("Invalid JSON Format.  Check the frame values and make sure the name is the first parameter.");o[s[Object.keys(s)[0]]]=s}i.frames=o}var d=Reflect.ownKeys(i.frames);this._spriteMap=d,this._packedAndReady=!0,this._cellData=i.frames}catch{throw this._fromPacked=!1,this._packedAndReady=!1,new Error("Invalid JSON from string. Spritesheet managed with constant cell size.")}else{var p=/\./g,b=void 0;do b=p.lastIndex,p.test(t);while(p.lastIndex>0);var P=t.substring(0,b-1)+".json",O=new XMLHttpRequest;O.open("GET",P,!0),O.onerror=function(){l.a.Error("JSON ERROR: Unable to load JSON file."),n._fromPacked=!1,n._packedAndReady=!1},O.onload=function(){try{var B=JSON.parse(O.response),F=Reflect.ownKeys(B.frames);n._spriteMap=F,n._packedAndReady=!0,n._cellData=B.frames}catch{throw n._fromPacked=!1,n._packedAndReady=!1,new Error("Invalid JSON format. Please check documentation for format specifications.")}},O.send()}},r.prototype._checkTextureAlpha=function(t,e,n,i,o){if(!t.useAlphaForPicking||!this.texture)return!0;var a=this.texture.getSize();this._textureContent||(this._textureContent=new Uint8Array(a.width*a.height*4),this.texture.readPixels(0,0,this._textureContent));var s=u.c.Vector3[0];s.copyFrom(e.direction),s.normalize(),s.scaleInPlace(n),s.addInPlace(e.origin);var d=(s.x-i.x)/(o.x-i.x)-.5,p=1-(s.y-i.y)/(o.y-i.y)-.5,b=t.angle,P=d*Math.cos(b)-p*Math.sin(b)+.5,O=d*Math.sin(b)+p*Math.cos(b)+.5,B=t._xOffset*a.width+P*t._xSize|0,F=t._yOffset*a.height+O*t._ySize|0;return this._textureContent[4*(B+F*a.width)+3]>.5},r.prototype.intersects=function(t,e,n,i){for(var o=Math.min(this.capacity,this.sprites.length),a=u.e.Zero(),s=u.e.Zero(),d=Number.MAX_VALUE,p=null,b=u.c.Vector3[0],P=u.c.Vector3[1],O=e.getViewMatrix(),B=0;B<o;B++){var F=this.sprites[B];if(F){if(n){if(!n(F))continue}else if(!F.isPickable)continue;if(u.e.TransformCoordinatesToRef(F.position,O,P),a.copyFromFloats(P.x-F.width/2,P.y-F.height/2,P.z),s.copyFromFloats(P.x+F.width/2,P.y+F.height/2,P.z),t.intersectsBoxMinMax(a,s)){var z=u.e.Distance(P,t.origin);if(d>z){if(!this._checkTextureAlpha(F,t,z,a,s))continue;if(d=z,p=F,i)break}}}}if(p){var J=new nr.a;O.invertToRef(u.c.Matrix[0]),J.hit=!0,J.pickedSprite=p,J.distance=d;var ie=u.c.Vector3[2];return ie.copyFrom(t.direction),ie.normalize(),ie.scaleInPlace(d),t.origin.addToRef(ie,b),J.pickedPoint=u.e.TransformCoordinates(b,u.c.Matrix[0]),J}return null},r.prototype.multiIntersects=function(t,e,n){for(var i,o=Math.min(this.capacity,this.sprites.length),a=u.e.Zero(),s=u.e.Zero(),d=[],p=u.c.Vector3[0].copyFromFloats(0,0,0),b=u.c.Vector3[1].copyFromFloats(0,0,0),P=e.getViewMatrix(),O=0;O<o;O++){var B=this.sprites[O];if(B){if(n){if(!n(B))continue}else if(!B.isPickable)continue;if(u.e.TransformCoordinatesToRef(B.position,P,b),a.copyFromFloats(b.x-B.width/2,b.y-B.height/2,b.z),s.copyFromFloats(b.x+B.width/2,b.y+B.height/2,b.z),t.intersectsBoxMinMax(a,s)){if(i=u.e.Distance(b,t.origin),!this._checkTextureAlpha(B,t,i,a,s))continue;var F=new nr.a;d.push(F),P.invertToRef(u.c.Matrix[0]),F.hit=!0,F.pickedSprite=B,F.distance=i;var z=u.c.Vector3[2];z.copyFrom(t.direction),z.normalize(),z.scaleInPlace(i),t.origin.addToRef(z,p),F.pickedPoint=u.e.TransformCoordinates(p,u.c.Matrix[0])}}}return d},r.prototype.render=function(){if(!this._fromPacked||this._packedAndReady&&this._spriteMap&&this._cellData){var t=this._scene.getEngine().getDeltaTime();this._packedAndReady?this._spriteRenderer.render(this.sprites,t,this._scene.getViewMatrix(),this._scene.getProjectionMatrix(),this._customUpdate):this._spriteRenderer.render(this.sprites,t,this._scene.getViewMatrix(),this._scene.getProjectionMatrix())}},r.prototype.dispose=function(){this._spriteRenderer&&(this._spriteRenderer.dispose(),this._spriteRenderer=null),this._textureContent=null;var t=this._scene.spriteManagers.indexOf(this);this._scene.spriteManagers.splice(t,1),this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear()},r.prototype.serialize=function(t){t===void 0&&(t=!1);var e={};e.name=this.name,e.capacity=this.capacity,e.cellWidth=this.cellWidth,e.cellHeight=this.cellHeight,this.texture&&(t?e.texture=this.texture.serialize():(e.textureUrl=this.texture.name,e.invertY=this.texture._invertY)),e.sprites=[];for(var n=0,i=this.sprites;n<i.length;n++){var o=i[n];e.sprites.push(o.serialize())}return e},r.Parse=function(t,e,n){var i=new r(t.name,"",t.capacity,{width:t.cellWidth,height:t.cellHeight},e);t.texture?i.texture=we.a.Parse(t.texture,e,n):t.textureName&&(i.texture=new we.a(n+t.textureUrl,e,!1,t.invertY===void 0||t.invertY));for(var o=0,a=t.sprites;o<a.length;o++){var s=a[o];Jd.Parse(s,i)}return i},r.ParseFromFileAsync=function(t,e,n,i){return i===void 0&&(i=""),new Promise(function(o,a){var s=new re.a;s.addEventListener("readystatechange",function(){if(s.readyState==4)if(s.status==200){var d=JSON.parse(s.responseText),p=r.Parse(d,n||Ue.a.LastCreatedScene,i);t&&(p.name=t),o(p)}else a("Unable to load the sprite manager")}),s.open("GET",e),s.send()})},r.CreateFromSnippetAsync=function(t,e,n){var i=this;return n===void 0&&(n=""),t==="_BLANK"?Promise.resolve(new r("Default sprite manager","//playground.babylonjs.com/textures/player.png",500,64,e)):new Promise(function(o,a){var s=new re.a;s.addEventListener("readystatechange",function(){if(s.readyState==4)if(s.status==200){var d=JSON.parse(JSON.parse(s.responseText).jsonPayload),p=JSON.parse(d.spriteManager),b=r.Parse(p,e||Ue.a.LastCreatedScene,n);b.snippetId=t,o(b)}else a("Unable to load the snippet "+t)}),s.open("GET",i.SnippetUrl+"/"+t.replace(/#/g,"/")),s.send()})},r.SnippetUrl="https://snippet.babylonjs.com",r}(),Yg=`precision highp float;
-varying vec3 vPosition;
-varying vec2 vUV;
-varying vec2 tUV;
-uniform float time;
-uniform float spriteCount;
-uniform sampler2D spriteSheet;
-uniform vec2 spriteMapSize;
-uniform vec2 outputSize;
-uniform vec2 stageSize;
-uniform sampler2D frameMap;
-uniform sampler2D tileMaps[LAYERS];
-uniform sampler2D animationMap;
-uniform vec3 colorMul;
-float mt;
-const float fdStep=1./4.;
-const float aFrameSteps=1./MAX_ANIMATION_FRAMES;
-mat4 getFrameData(float frameID){
-float fX=frameID/spriteCount;
-return mat4(
-texture2D(frameMap,vec2(fX,0.),0.),
-texture2D(frameMap,vec2(fX,fdStep*1.),0.),
-texture2D(frameMap,vec2(fX,fdStep*2.),0.),
-vec4(0.)
-);
-}
-void main(){
-vec4 color=vec4(0.);
-vec2 tileUV=fract(tUV);
-#ifdef FLIPU
-tileUV.y=1.0-tileUV.y;
-#endif
-vec2 tileID=floor(tUV);
-vec2 sheetUnits=1./spriteMapSize;
-float spriteUnits=1./spriteCount;
-vec2 stageUnits=1./stageSize;
-for(int i=0; i<LAYERS; i++) {
-float frameID;
-#define LAYER_ID_SWITCH
-vec4 animationData=texture2D(animationMap,vec2((frameID+0.5)/spriteCount,0.),0.);
-if(animationData.y>0.) {
-mt=mod(time*animationData.z,1.0);
-for(float f=0.; f<MAX_ANIMATION_FRAMES; f++){
-if(animationData.y>mt){
-frameID=animationData.x;
-break;
-}
-animationData=texture2D(animationMap,vec2((frameID+0.5)/spriteCount,aFrameSteps*f),0.);
-}
-}
-
-mat4 frameData=getFrameData(frameID+0.5);
-vec2 frameSize=(frameData[0].wz)/spriteMapSize;
-vec2 offset=frameData[0].xy*sheetUnits;
-vec2 ratio=frameData[2].xy/frameData[0].wz;
-
-if (frameData[2].z == 1.){
-tileUV.xy=tileUV.yx;
-}
-if (i == 0){
-color=texture2D(spriteSheet,tileUV*frameSize+offset);
-} else {
-vec4 nc=texture2D(spriteSheet,tileUV*frameSize+offset);
-float alpha=min(color.a+nc.a,1.0);
-vec3 mixed=mix(color.xyz,nc.xyz,nc.a);
-color=vec4(mixed,alpha);
-}
-}
-color.xyz*=colorMul;
-gl_FragColor=color;
-}`;ze.a.ShadersStore.spriteMapPixelShader=Yg;var Kg=`precision highp float;
-
-attribute vec3 position;
-attribute vec3 normal;
-attribute vec2 uv;
-
-varying vec3 vPosition;
-varying vec2 vUV;
-varying vec2 tUV;
-varying vec2 stageUnits;
-varying vec2 levelUnits;
-varying vec2 tileID;
-
-uniform float time;
-uniform mat4 worldViewProjection;
-uniform vec2 outputSize;
-uniform vec2 stageSize;
-uniform vec2 spriteMapSize;
-uniform float stageScale;
-void main() {
-vec4 p=vec4( position,1. );
-vPosition=p.xyz;
-vUV=uv;
-tUV=uv*stageSize;
-gl_Position=worldViewProjection*p;
-}`;ze.a.ShadersStore.spriteMapVertexShader=Kg;var mi,Qg=function(){function r(t,e,n,i,o){var a=this;this.name=t,this.sprites=[],this.atlasJSON=e,this.sprites=this.atlasJSON.frames,this.spriteSheet=n,this.options=i,i.stageSize=i.stageSize||new u.d(1,1),i.outputSize=i.outputSize||i.stageSize,i.outputPosition=i.outputPosition||u.e.Zero(),i.outputRotation=i.outputRotation||u.e.Zero(),i.layerCount=i.layerCount||1,i.maxAnimationFrames=i.maxAnimationFrames||0,i.baseTile=i.baseTile||0,i.flipU=i.flipU||!1,i.colorMultiply=i.colorMultiply||new u.e(1,1,1),this._scene=o,this._frameMap=this._createFrameBuffer(),this._tileMaps=new Array;for(var s=0;s<i.layerCount;s++)this._tileMaps.push(this._createTileBuffer(null,s));this._animationMap=this._createTileAnimationBuffer(null);var d=[];d.push("#define LAYERS "+i.layerCount),i.flipU&&d.push("#define FLIPU"),d.push("#define MAX_ANIMATION_FRAMES "+i.maxAnimationFrames+".0");var p,b=ze.a.ShadersStore.spriteMapPixelShader;if(this._scene.getEngine().webGLVersion===1)for(p="",s=0;s<i.layerCount;s++)p+="if ("+s+" == i) { frameID = texture2D(tileMaps["+s+"], (tileID + 0.5) / stageSize, 0.).x; }";else{for(p="switch(i) {",s=0;s<i.layerCount;s++)p+="case "+s+" : frameID = texture(tileMaps["+s+"], (tileID + 0.5) / stageSize, 0.).x;",p+="break;";p+="}"}ze.a.ShadersStore["spriteMap"+this.name+"PixelShader"]=b.replace("#define LAYER_ID_SWITCH",p),this._material=new ua.a("spriteMap:"+this.name,this._scene,{vertex:"spriteMap",fragment:"spriteMap"+this.name},{defines:d,attributes:["position","normal","uv"],uniforms:["worldViewProjection","time","stageSize","outputSize","spriteMapSize","spriteCount","time","colorMul","mousePosition","curTile","flipU"],samplers:["spriteSheet","frameMap","tileMaps","animationMap"],needAlphaBlending:!0}),this._time=0,this._material.setFloat("spriteCount",this.spriteCount),this._material.setVector2("stageSize",i.stageSize),this._material.setVector2("outputSize",i.outputSize),this._material.setTexture("spriteSheet",this.spriteSheet),this._material.setVector2("spriteMapSize",new u.d(1,1)),this._material.setVector3("colorMul",i.colorMultiply);var P=0,O=function(){a.spriteSheet&&a.spriteSheet.isReady()&&a.spriteSheet._texture?a._material.setVector2("spriteMapSize",new u.d(a.spriteSheet._texture.baseWidth||1,a.spriteSheet._texture.baseHeight||1)):P<100&&setTimeout(function(){P++,O()},100)};O(),this._material.setVector3("colorMul",i.colorMultiply),this._material.setTexture("frameMap",this._frameMap),this._material.setTextureArray("tileMaps",this._tileMaps),this._material.setTexture("animationMap",this._animationMap),this._material.setFloat("time",this._time),this._output=De.a.CreatePlane(t+":output",1,o,!0),this._output.scaling.x=i.outputSize.x,this._output.scaling.y=i.outputSize.y,this.position=i.outputPosition,this.rotation=i.outputRotation,this._scene.onBeforeRenderObservable.add(function(){a._time+=a._scene.getEngine().getDeltaTime(),a._material.setFloat("time",a._time)}),this._output.material=this._material}return Object.defineProperty(r.prototype,"spriteCount",{get:function(){return this.sprites.length},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"position",{get:function(){return this._output.position},set:function(t){this._output.position=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"rotation",{get:function(){return this._output.rotation},set:function(t){this._output.rotation=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"animationMap",{get:function(){return this._animationMap},set:function(t){var e=t._texture._bufferView,n=this._createTileAnimationBuffer(e);this._animationMap.dispose(),this._animationMap=n,this._material.setTexture("animationMap",this._animationMap)},enumerable:!1,configurable:!0}),r.prototype.getTileID=function(){var t=this.getMousePosition();return t.multiplyInPlace(this.options.stageSize||u.d.Zero()),t.x=Math.floor(t.x),t.y=Math.floor(t.y),t},r.prototype.getMousePosition=function(){var t=this._output,e=this._scene.pick(this._scene.pointerX,this._scene.pointerY,function(i){return i===t});if(!e||!e.hit||!e.getTextureCoordinates)return new u.d(-1,-1);var n=e.getTextureCoordinates();return n||new u.d(-1,-1)},r.prototype._createFrameBuffer=function(){for(var t=new Array,e=0;e<this.spriteCount;e++)t.push(0,0,0,0),t.push(0,0,0,0),t.push(0,0,0,0),t.push(0,0,0,0);for(e=0;e<this.spriteCount;e++){var n=this.sprites[e].frame,i=this.sprites[e].spriteSourceSize,o=this.sprites[e].sourceSize,a=this.sprites[e].rotated?1:0,s=this.sprites[e].trimmed?1:0;t[4*e]=n.x,t[4*e+1]=n.y,t[4*e+2]=n.w,t[4*e+3]=n.h,t[4*e+4*this.spriteCount]=i.x,t[4*e+1+4*this.spriteCount]=i.y,t[4*e+3+4*this.spriteCount]=i.h,t[4*e+8*this.spriteCount]=o.w,t[4*e+1+8*this.spriteCount]=o.h,t[4*e+2+8*this.spriteCount]=a,t[4*e+3+8*this.spriteCount]=s}var d=new Float32Array(t);return ii.CreateRGBATexture(d,this.spriteCount,4,this._scene,!1,!1,we.a.NEAREST_NEAREST,Ue.a.TEXTURETYPE_FLOAT)},r.prototype._createTileBuffer=function(t,e){e===void 0&&(e=0);var n=new Array,i=this.options.stageSize.y||0,o=this.options.stageSize.x||0;if(t)n=t;else{var a=this.options.baseTile;e!=0&&(a=0);for(var s=0;s<i;s++)for(var d=0;d<4*o;d+=4)n.push(a,0,0,0)}var p=new Float32Array(n);return ii.CreateRGBATexture(p,o,i,this._scene,!1,!1,we.a.NEAREST_NEAREST,Ue.a.TEXTURETYPE_FLOAT)},r.prototype.changeTiles=function(t,e,n){var i;if(t===void 0&&(t=0),n===void 0&&(n=0),(i=this._tileMaps[t]._texture._bufferView)!==null){var o=new Array;e instanceof u.d?o.push(e):o=e;for(var a=this.options.stageSize.x||0,s=0;s<o.length;s++){var d=o[s];d.x=Math.floor(d.x),d.y=Math.floor(d.y),i[4*d.x+d.y*(4*a)]=n}var p=this._createTileBuffer(i);this._tileMaps[t].dispose(),this._tileMaps[t]=p,this._material.setTextureArray("tileMap",this._tileMaps)}},r.prototype._createTileAnimationBuffer=function(t){var e,n=new Array;if(t)e=t;else{for(var i=0;i<this.spriteCount;i++){n.push(0,0,0,0);for(var o=1;o<(this.options.maxAnimationFrames||4);)n.push(0,0,0,0),o++}e=new Float32Array(n)}return ii.CreateRGBATexture(e,this.spriteCount,this.options.maxAnimationFrames||4,this._scene,!1,!1,we.a.NEAREST_NEAREST,Ue.a.TEXTURETYPE_FLOAT)},r.prototype.addAnimationToTile=function(t,e,n,i,o){t===void 0&&(t=0),e===void 0&&(e=0),n===void 0&&(n=0),i===void 0&&(i=0),o===void 0&&(o=1);var a=this._animationMap._texture._bufferView,s=4*t+4*this.spriteCount*e;if(a){a[s]=n,a[s+1]=i,a[s+2]=o;var d=this._createTileAnimationBuffer(a);this._animationMap.dispose(),this._animationMap=d,this._material.setTexture("animationMap",this._animationMap)}},r.prototype.saveTileMaps=function(){for(var t="",e=0;e<this._tileMaps.length;e++)e>0&&(t+=`
-\r`),t+=this._tileMaps[e]._texture._bufferView.toString();var n=document.createElement("a");n.href="data:octet/stream;charset=utf-8,"+encodeURI(t),n.target="_blank",n.download=this.name+".tilemaps",n.click(),n.remove()},r.prototype.loadTileMaps=function(t){var e=this,n=new XMLHttpRequest;n.open("GET",t);var i=this.options.layerCount||0;n.onload=function(){for(var o=n.response.split(`
-\r`),a=0;a<i;a++){var s=o[a].split(",").map(Number),d=e._createTileBuffer(s);e._tileMaps[a].dispose(),e._tileMaps[a]=d}e._material.setTextureArray("tileMap",e._tileMaps)},n.send()},r.prototype.dispose=function(){this._output.dispose(),this._material.dispose(),this._animationMap.dispose(),this._tileMaps.forEach(function(t){t.dispose()}),this._frameMap.dispose()},r}(),qg=function(r){function t(e,n,i,o,a,s,d){a===void 0&&(a=null),s===void 0&&(s=.01),d===void 0&&(d=we.a.TRILINEAR_SAMPLINGMODE);var p=r.call(this,e,n,i,64,o,s,d,!0,a)||this;return p.name=e,p}return Object(c.d)(t,r),t}(ef),Zg=f(143),Jg=f(141),$g=f(142),ev=f(139);(function(r){r[r.INIT=0]="INIT",r[r.RUNNING=1]="RUNNING",r[r.DONE=2]="DONE",r[r.ERROR=3]="ERROR"})(mi||(mi={}));var Xc,gi=function(){function r(t){this.name=t,this._isCompleted=!1,this._taskState=mi.INIT}return Object.defineProperty(r.prototype,"isCompleted",{get:function(){return this._isCompleted},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"taskState",{get:function(){return this._taskState},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"errorObject",{get:function(){return this._errorObject},enumerable:!1,configurable:!0}),r.prototype._setErrorObject=function(t,e){this._errorObject||(this._errorObject={message:t,exception:e})},r.prototype.run=function(t,e,n){var i=this;this._taskState=mi.RUNNING,this.runTask(t,function(){i.onDoneCallback(e,n)},function(o,a){i.onErrorCallback(n,o,a)})},r.prototype.runTask=function(t,e,n){throw new Error("runTask is not implemented")},r.prototype.reset=function(){this._taskState=mi.INIT},r.prototype.onErrorCallback=function(t,e,n){this._taskState=mi.ERROR,this._errorObject={message:e,exception:n},this.onError&&this.onError(this,e,n),t()},r.prototype.onDoneCallback=function(t,e){try{this._taskState=mi.DONE,this._isCompleted=!0,this.onSuccess&&this.onSuccess(this),t()}catch(n){this.onErrorCallback(e,"Task is done, error executing success callback(s)",n)}},r}(),tf=function(r,t,e){this.remainingCount=r,this.totalCount=t,this.task=e},nf=function(r){function t(e,n,i,o){var a=r.call(this,e)||this;return a.name=e,a.meshesNames=n,a.rootUrl=i,a.sceneFilename=o,a}return Object(c.d)(t,r),t.prototype.runTask=function(e,n,i){var o=this;Ut.LoadAssetContainer(this.rootUrl,this.sceneFilename,e,function(a){o.loadedContainer=a,o.loadedMeshes=a.meshes,o.loadedParticleSystems=a.particleSystems,o.loadedSkeletons=a.skeletons,o.loadedAnimationGroups=a.animationGroups,n()},null,function(a,s,d){i(s,d)})},t}(gi),rf=function(r){function t(e,n,i,o){var a=r.call(this,e)||this;return a.name=e,a.meshesNames=n,a.rootUrl=i,a.sceneFilename=o,a}return Object(c.d)(t,r),t.prototype.runTask=function(e,n,i){var o=this;Ut.ImportMesh(this.meshesNames,this.rootUrl,this.sceneFilename,e,function(a,s,d,p){o.loadedMeshes=a,o.loadedParticleSystems=s,o.loadedSkeletons=d,o.loadedAnimationGroups=p,n()},null,function(a,s,d){i(s,d)})},t}(gi),of=function(r){function t(e,n){var i=r.call(this,e)||this;return i.name=e,i.url=n,i}return Object(c.d)(t,r),t.prototype.runTask=function(e,n,i){var o=this;e._loadFile(this.url,function(a){o.text=a,n()},void 0,!1,!1,function(a,s){a&&i(a.status+" "+a.statusText,s)})},t}(gi),af=function(r){function t(e,n){var i=r.call(this,e)||this;return i.name=e,i.url=n,i}return Object(c.d)(t,r),t.prototype.runTask=function(e,n,i){var o=this;e._loadFile(this.url,function(a){o.data=a,n()},void 0,!0,!0,function(a,s){a&&i(a.status+" "+a.statusText,s)})},t}(gi),sf=function(r){function t(e,n){var i=r.call(this,e)||this;return i.name=e,i.url=n,i}return Object(c.d)(t,r),t.prototype.runTask=function(e,n,i){var o=this,a=new Image;Xe.b.SetCorsBehavior(this.url,a),a.onload=function(){o.image=a,n()},a.onerror=function(s){i("Error loading image",s)},a.src=this.url},t}(gi),cf=function(r){function t(e,n,i,o,a){o===void 0&&(o=!0),a===void 0&&(a=we.a.TRILINEAR_SAMPLINGMODE);var s=r.call(this,e)||this;return s.name=e,s.url=n,s.noMipmap=i,s.invertY=o,s.samplingMode=a,s}return Object(c.d)(t,r),t.prototype.runTask=function(e,n,i){this.texture=new we.a(this.url,e,this.noMipmap,this.invertY,this.samplingMode,function(){n()},function(o,a){i(o,a)})},t}(gi),lf=function(r){function t(e,n,i,o,a){var s=r.call(this,e)||this;return s.name=e,s.url=n,s.extensions=i,s.noMipmap=o,s.files=a,s}return Object(c.d)(t,r),t.prototype.runTask=function(e,n,i){this.texture=new ai(this.url,e,this.extensions,this.noMipmap,this.files,function(){n()},function(o,a){i(o,a)})},t}(gi),uf=function(r){function t(e,n,i,o,a,s,d){o===void 0&&(o=!1),a===void 0&&(a=!0),s===void 0&&(s=!1),d===void 0&&(d=!1);var p=r.call(this,e)||this;return p.name=e,p.url=n,p.size=i,p.noMipmap=o,p.generateHarmonics=a,p.gammaSpace=s,p.reserved=d,p}return Object(c.d)(t,r),t.prototype.runTask=function(e,n,i){this.texture=new aa(this.url,e,this.size,this.noMipmap,this.generateHarmonics,this.gammaSpace,this.reserved,function(){n()},function(o,a){i(o,a)})},t}(gi),hf=function(r){function t(e,n,i,o,a){o===void 0&&(o=!1),a===void 0&&(a=!0);var s=r.call(this,e)||this;return s.name=e,s.url=n,s.size=i,s.noMipmap=o,s.gammaSpace=a,s}return Object(c.d)(t,r),t.prototype.runTask=function(e,n,i){this.texture=new rh(this.url,e,this.size,this.noMipmap,this.gammaSpace,function(){n()},function(o,a){i(o,a)})},t}(gi),tv=function(){function r(t){this._isLoading=!1,this._tasks=new Array,this._waitingTasksCount=0,this._totalTasksCount=0,this.onTaskSuccessObservable=new x.c,this.onTaskErrorObservable=new x.c,this.onTasksDoneObservable=new x.c,this.onProgressObservable=new x.c,this.useDefaultLoadingScreen=!0,this.autoHideLoadingUI=!0,this._scene=t}return r.prototype.addContainerTask=function(t,e,n,i){var o=new nf(t,e,n,i);return this._tasks.push(o),o},r.prototype.addMeshTask=function(t,e,n,i){var o=new rf(t,e,n,i);return this._tasks.push(o),o},r.prototype.addTextFileTask=function(t,e){var n=new of(t,e);return this._tasks.push(n),n},r.prototype.addBinaryFileTask=function(t,e){var n=new af(t,e);return this._tasks.push(n),n},r.prototype.addImageTask=function(t,e){var n=new sf(t,e);return this._tasks.push(n),n},r.prototype.addTextureTask=function(t,e,n,i,o){o===void 0&&(o=we.a.TRILINEAR_SAMPLINGMODE);var a=new cf(t,e,n,i,o);return this._tasks.push(a),a},r.prototype.addCubeTextureTask=function(t,e,n,i,o){var a=new lf(t,e,n,i,o);return this._tasks.push(a),a},r.prototype.addHDRCubeTextureTask=function(t,e,n,i,o,a,s){i===void 0&&(i=!1),o===void 0&&(o=!0),a===void 0&&(a=!1),s===void 0&&(s=!1);var d=new uf(t,e,n,i,o,a,s);return this._tasks.push(d),d},r.prototype.addEquiRectangularCubeTextureAssetTask=function(t,e,n,i,o){i===void 0&&(i=!1),o===void 0&&(o=!0);var a=new hf(t,e,n,i,o);return this._tasks.push(a),a},r.prototype.removeTask=function(t){var e=this._tasks.indexOf(t);e>-1&&this._tasks.splice(e,1)},r.prototype._decreaseWaitingTasksCount=function(t){this._waitingTasksCount--;try{this.onProgress&&this.onProgress(this._waitingTasksCount,this._totalTasksCount,t),this.onProgressObservable.notifyObservers(new tf(this._waitingTasksCount,this._totalTasksCount,t))}catch(a){l.a.Error("Error running progress callbacks."),console.log(a)}if(this._waitingTasksCount===0){try{var e=this._tasks.slice();this.onFinish&&this.onFinish(e);for(var n=0,i=e;n<i.length;n++)if((t=i[n]).taskState===mi.DONE){var o=this._tasks.indexOf(t);o>-1&&this._tasks.splice(o,1)}this.onTasksDoneObservable.notifyObservers(this._tasks)}catch(a){l.a.Error("Error running tasks-done callbacks."),console.log(a)}this._isLoading=!1,this.autoHideLoadingUI&&this._scene.getEngine().hideLoadingUI()}},r.prototype._runTask=function(t){var e=this,n=function(i,o){t._setErrorObject(i,o),e.onTaskError&&e.onTaskError(t),e.onTaskErrorObservable.notifyObservers(t),e._decreaseWaitingTasksCount(t)};t.run(this._scene,function(){try{e.onTaskSuccess&&e.onTaskSuccess(t),e.onTaskSuccessObservable.notifyObservers(t),e._decreaseWaitingTasksCount(t)}catch(i){n("Error executing task success callbacks",i)}},n)},r.prototype.reset=function(){return this._isLoading=!1,this._tasks=new Array,this},r.prototype.load=function(){if(this._isLoading)return this;if(this._isLoading=!0,this._waitingTasksCount=this._tasks.length,this._totalTasksCount=this._tasks.length,this._waitingTasksCount===0)return this._isLoading=!1,this.onFinish&&this.onFinish(this._tasks),this.onTasksDoneObservable.notifyObservers(this._tasks),this;this.useDefaultLoadingScreen&&this._scene.getEngine().displayLoadingUI();for(var t=0;t<this._tasks.length;t++){var e=this._tasks[t];e.taskState===mi.INIT&&this._runTask(e)}return this},r.prototype.loadAsync=function(){var t=this;return new Promise(function(e,n){t._isLoading?e():(t.onTasksDoneObservable.addOnce(function(i){i&&i.length?n(i):e()}),t.load())})},r}(),nv=function(){function r(){var t=this;this.promise=new Promise(function(e,n){t._resolve=e,t._reject=n})}return Object.defineProperty(r.prototype,"resolve",{get:function(){return this._resolve},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"reject",{get:function(){return this._reject},enumerable:!1,configurable:!0}),r}(),iv=function(){function r(t,e){this._meshesOrigins=[],this._toCenterVectors=[],this._scaledDirection=u.e.Zero(),this._newPosition=u.e.Zero(),this._centerPosition=u.e.Zero(),this._meshes=t.slice(),e?this._centerMesh=e:this._setCenterMesh();var n=this._meshes.indexOf(this._centerMesh);n>=0&&this._meshes.splice(n,1),this._centerPosition=this._centerMesh.getAbsolutePosition().clone();for(var i=0;i<this._meshes.length;i++)if(this._meshes[i]){var o=this._meshes[i];this._meshesOrigins[i]=o.getAbsolutePosition().clone(),this._toCenterVectors[i]=u.e.Zero(),o._boundingInfo&&this._centerMesh._boundingInfo&&o._boundingInfo.boundingBox.centerWorld.subtractToRef(this._centerMesh._boundingInfo.boundingBox.centerWorld,this._toCenterVectors[i])}}return r.prototype._setCenterMesh=function(){for(var t=u.e.Zero(),e=u.e.Zero(),n=Number.MAX_VALUE,i=0;i<this._meshes.length;i++)this._meshes[i]&&(a=(o=this._meshes[i]).getBoundingInfo())&&e.addInPlace(a.boundingBox.centerWorld);for(t=e.scale(1/this._meshes.length),i=0;i<this._meshes.length;i++){var o,a;if(this._meshes[i]&&(a=(o=this._meshes[i]).getBoundingInfo())){var s=a.boundingBox.centerWorld.subtract(t).lengthSquared();s<n&&(this._centerMesh=o,n=s)}}},r.prototype.getClassName=function(){return"MeshExploder"},r.prototype.getMeshes=function(){var t=this._meshes.slice();return t.unshift(this._centerMesh),t},r.prototype.explode=function(t){t===void 0&&(t=1);for(var e=0;e<this._meshes.length;e++)this._meshes[e]&&this._meshesOrigins[e]&&this._toCenterVectors[e]&&(this._toCenterVectors[e].scaleToRef(t,this._scaledDirection),this._meshesOrigins[e].addToRef(this._scaledDirection,this._newPosition),this._meshes[e].setAbsolutePosition(this._newPosition));this._centerMesh.setAbsolutePosition(this._centerPosition)},r}(),rv=function(){function r(t,e,n,i,o,a,s,d,p){this.onProcessFileCallback=function(){return!0},this._engine=t,this._currentScene=e,this._sceneLoadedCallback=n,this._progressCallback=i,this._additionalRenderLoopLogicCallback=o,this._textureLoadingCallback=a,this._startingProcessingFilesCallback=s,this._onReloadCallback=d,this._errorCallback=p}return Object.defineProperty(r,"FilesToLoad",{get:function(){return As.a.FilesToLoad},enumerable:!1,configurable:!0}),r.prototype.monitorElementForDragNDrop=function(t){var e=this;t&&(this._elementToMonitor=t,this._dragEnterHandler=function(n){e.drag(n)},this._dragOverHandler=function(n){e.drag(n)},this._dropHandler=function(n){e.drop(n)},this._elementToMonitor.addEventListener("dragenter",this._dragEnterHandler,!1),this._elementToMonitor.addEventListener("dragover",this._dragOverHandler,!1),this._elementToMonitor.addEventListener("drop",this._dropHandler,!1))},Object.defineProperty(r.prototype,"filesToLoad",{get:function(){return this._filesToLoad},enumerable:!1,configurable:!0}),r.prototype.dispose=function(){this._elementToMonitor&&(this._elementToMonitor.removeEventListener("dragenter",this._dragEnterHandler),this._elementToMonitor.removeEventListener("dragover",this._dragOverHandler),this._elementToMonitor.removeEventListener("drop",this._dropHandler))},r.prototype.renderFunction=function(){if(this._additionalRenderLoopLogicCallback&&this._additionalRenderLoopLogicCallback(),this._currentScene){if(this._textureLoadingCallback){var t=this._currentScene.getWaitingItemsCount();t>0&&this._textureLoadingCallback(t)}this._currentScene.render()}},r.prototype.drag=function(t){t.stopPropagation(),t.preventDefault()},r.prototype.drop=function(t){t.stopPropagation(),t.preventDefault(),this.loadFiles(t)},r.prototype._traverseFolder=function(t,e,n,i){var o=this,a=t.createReader(),s=t.fullPath.replace(/^\//,"").replace(/(.+?)\/?$/,"$1/");a.readEntries(function(d){n.count+=d.length;for(var p=0,b=d;p<b.length;p++){var P=b[p];P.isFile?P.file(function(O){O.correctName=s+O.name,e.push(O),--n.count==0&&i()}):P.isDirectory&&o._traverseFolder(P,e,n,i)}--n.count==0&&i()})},r.prototype._processFiles=function(t){for(var e=0;e<t.length;e++){var n=t[e].correctName.toLowerCase(),i=n.split(".").pop();this.onProcessFileCallback(t[e],n,i)&&(Ut.IsPluginForExtensionAvailable("."+i)&&(this._sceneFileToLoad=t[e]),r.FilesToLoad[n]=t[e])}},r.prototype.loadFiles=function(t){var e=this;if(t&&t.dataTransfer&&t.dataTransfer.files&&(this._filesToLoad=t.dataTransfer.files),t&&t.target&&t.target.files&&(this._filesToLoad=t.target.files),this._filesToLoad&&this._filesToLoad.length!==0&&(this._startingProcessingFilesCallback&&this._startingProcessingFilesCallback(this._filesToLoad),this._filesToLoad&&this._filesToLoad.length>0)){for(var n=new Array,i=[],o=t.dataTransfer?t.dataTransfer.items:null,a=0;a<this._filesToLoad.length;a++){var s=this._filesToLoad[a],d=s.name.toLowerCase(),p=void 0;if(s.correctName=d,o){var b=o[a];b.getAsEntry?p=b.getAsEntry():b.webkitGetAsEntry&&(p=b.webkitGetAsEntry())}p&&p.isDirectory?i.push(p):n.push(s)}if(i.length===0)this._processFiles(n),this._processReload();else for(var P={count:i.length},O=0,B=i;O<B.length;O++){var F=B[O];this._traverseFolder(F,n,P,function(){e._processFiles(n),P.count===0&&e._processReload()})}}},r.prototype._processReload=function(){this._onReloadCallback?this._onReloadCallback(this._sceneFileToLoad):this.reload()},r.prototype.reload=function(){var t=this;this._sceneFileToLoad?(this._currentScene&&(l.a.errorsCount>0&&l.a.ClearLogCache(),this._engine.stopRenderLoop()),Ut.ShowLoadingScreen=!1,this._engine.displayLoadingUI(),Ut.LoadAsync("file:",this._sceneFileToLoad,this._engine,function(e){t._progressCallback&&t._progressCallback(e)}).then(function(e){t._currentScene&&t._currentScene.dispose(),t._currentScene=e,t._sceneLoadedCallback&&t._sceneLoadedCallback(t._sceneFileToLoad,t._currentScene),t._currentScene.executeWhenReady(function(){t._engine.hideLoadingUI(),t._engine.runRenderLoop(function(){t.renderFunction()})})}).catch(function(e){t._engine.hideLoadingUI(),t._errorCallback&&t._errorCallback(t._sceneFileToLoad,t._currentScene,e.message)})):l.a.Error("Please provide a valid .babylon file.")},r}(),df=f(146),ov=f(145),vi=function(){function r(t){t===void 0&&(t=0),this.priority=t}return r.prototype.getDescription=function(){return""},r.prototype.apply=function(t,e){return!0},r}(),Pa=function(r){function t(e,n,i){e===void 0&&(e=0),n===void 0&&(n=1024),i===void 0&&(i=.5);var o=r.call(this,e)||this;return o.priority=e,o.maximumSize=n,o.step=i,o}return Object(c.d)(t,r),t.prototype.getDescription=function(){return"Reducing render target texture size to "+this.maximumSize},t.prototype.apply=function(e,n){for(var i=!0,o=0;o<e.textures.length;o++){var a=e.textures[o];if(a.canRescale&&!a.getContext){var s=a.getSize();Math.max(s.width,s.height)>this.maximumSize&&(a.scale(this.step),i=!1)}}return i},t}(vi),Yc=function(r){function t(e,n,i){e===void 0&&(e=0),n===void 0&&(n=2),i===void 0&&(i=.25);var o=r.call(this,e)||this;return o.priority=e,o.maximumScale=n,o.step=i,o._currentScale=-1,o._directionOffset=1,o}return Object(c.d)(t,r),t.prototype.getDescription=function(){return"Setting hardware scaling level to "+this._currentScale},t.prototype.apply=function(e,n){return this._currentScale===-1&&(this._currentScale=e.getEngine().getHardwareScalingLevel(),this._currentScale>this.maximumScale&&(this._directionOffset=-1)),this._currentScale+=this._directionOffset*this.step,e.getEngine().setHardwareScalingLevel(this._currentScale),this._directionOffset===1?this._currentScale>=this.maximumScale:this._currentScale<=this.maximumScale},t}(vi),Ca=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.getDescription=function(){return"Turning shadows on/off"},t.prototype.apply=function(e,n){return e.shadowsEnabled=n.isInImprovementMode,!0},t}(vi),xa=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.getDescription=function(){return"Turning post-processes on/off"},t.prototype.apply=function(e,n){return e.postProcessesEnabled=n.isInImprovementMode,!0},t}(vi),Ra=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.getDescription=function(){return"Turning lens flares on/off"},t.prototype.apply=function(e,n){return e.lensFlaresEnabled=n.isInImprovementMode,!0},t}(vi),ff=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.getDescription=function(){return this.onGetDescription?this.onGetDescription():"Running user defined callback"},t.prototype.apply=function(e,n){return!this.onApply||this.onApply(e,n)},t}(vi),Oa=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.getDescription=function(){return"Turning particles on/off"},t.prototype.apply=function(e,n){return e.particlesEnabled=n.isInImprovementMode,!0},t}(vi),Kc=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.getDescription=function(){return"Turning render targets off"},t.prototype.apply=function(e,n){return e.renderTargetsEnabled=n.isInImprovementMode,!0},t}(vi),Ma=function(r){function t(){var e=r!==null&&r.apply(this,arguments)||this;return e._canBeMerged=function(n){if(!(n instanceof De.a))return!1;var i=n;return!i.isDisposed()&&!(!i.isVisible||!i.isEnabled())&&!(i.instances.length>0)&&!i.skeleton&&!i.hasLODLevels},e}return Object(c.d)(t,r),Object.defineProperty(t,"UpdateSelectionTree",{get:function(){return t._UpdateSelectionTree},set:function(e){t._UpdateSelectionTree=e},enumerable:!1,configurable:!0}),t.prototype.getDescription=function(){return"Merging similar meshes together"},t.prototype.apply=function(e,n,i){for(var o=e.meshes.slice(0),a=o.length,s=0;s<a;s++){var d=new Array,p=o[s];if(this._canBeMerged(p)){d.push(p);for(var b=s+1;b<a;b++){var P=o[b];this._canBeMerged(P)&&P.material===p.material&&P.checkCollisions===p.checkCollisions&&(d.push(P),a--,o.splice(b,1),b--)}d.length<2||De.a.MergeMeshes(d,void 0,!0)}}var O=e;return O.createOrUpdateSelectionOctree&&(i!=null?i&&O.createOrUpdateSelectionOctree():t.UpdateSelectionTree&&O.createOrUpdateSelectionOctree()),!0},t._UpdateSelectionTree=!1,t}(vi),Qc=function(){function r(t,e){t===void 0&&(t=60),e===void 0&&(e=2e3),this.targetFrameRate=t,this.trackerDuration=e,this.optimizations=new Array}return r.prototype.addOptimization=function(t){return this.optimizations.push(t),this},r.prototype.addCustomOptimization=function(t,e,n){n===void 0&&(n=0);var i=new ff(n);return i.onApply=t,i.onGetDescription=e,this.optimizations.push(i),this},r.LowDegradationAllowed=function(t){var e=new r(t),n=0;return e.addOptimization(new Ma(n)),e.addOptimization(new Ca(n)),e.addOptimization(new Ra(n)),n++,e.addOptimization(new xa(n)),e.addOptimization(new Oa(n)),n++,e.addOptimization(new Pa(n,1024)),e},r.ModerateDegradationAllowed=function(t){var e=new r(t),n=0;return e.addOptimization(new Ma(n)),e.addOptimization(new Ca(n)),e.addOptimization(new Ra(n)),n++,e.addOptimization(new xa(n)),e.addOptimization(new Oa(n)),n++,e.addOptimization(new Pa(n,512)),n++,e.addOptimization(new Kc(n)),n++,e.addOptimization(new Yc(n,2)),e},r.HighDegradationAllowed=function(t){var e=new r(t),n=0;return e.addOptimization(new Ma(n)),e.addOptimization(new Ca(n)),e.addOptimization(new Ra(n)),n++,e.addOptimization(new xa(n)),e.addOptimization(new Oa(n)),n++,e.addOptimization(new Pa(n,256)),n++,e.addOptimization(new Kc(n)),n++,e.addOptimization(new Yc(n,4)),e},r}(),av=function(){function r(t,e,n,i){var o=this;if(n===void 0&&(n=!0),i===void 0&&(i=!1),this._isRunning=!1,this._currentPriorityLevel=0,this._targetFrameRate=60,this._trackerDuration=2e3,this._currentFrameRate=0,this._improvementMode=!1,this.onSuccessObservable=new x.c,this.onNewOptimizationAppliedObservable=new x.c,this.onFailureObservable=new x.c,this._options=e||new Qc,this._options.targetFrameRate&&(this._targetFrameRate=this._options.targetFrameRate),this._options.trackerDuration&&(this._trackerDuration=this._options.trackerDuration),n)for(var a=0,s=0,d=this._options.optimizations;s<d.length;s++)d[s].priority=a++;this._improvementMode=i,this._scene=t||te.a.LastCreatedScene,this._sceneDisposeObserver=this._scene.onDisposeObservable.add(function(){o._sceneDisposeObserver=null,o.dispose()})}return Object.defineProperty(r.prototype,"isInImprovementMode",{get:function(){return this._improvementMode},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"currentPriorityLevel",{get:function(){return this._currentPriorityLevel},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"currentFrameRate",{get:function(){return this._currentFrameRate},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"targetFrameRate",{get:function(){return this._targetFrameRate},set:function(t){this._targetFrameRate=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"trackerDuration",{get:function(){return this._trackerDuration},set:function(t){this._trackerDuration=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"optimizations",{get:function(){return this._options.optimizations},enumerable:!1,configurable:!0}),r.prototype.stop=function(){this._isRunning=!1},r.prototype.reset=function(){this._currentPriorityLevel=0},r.prototype.start=function(){var t=this;this._isRunning||(this._isRunning=!0,this._scene.executeWhenReady(function(){setTimeout(function(){t._checkCurrentState()},t._trackerDuration)}))},r.prototype._checkCurrentState=function(){var t=this;if(this._isRunning){var e=this._scene,n=this._options;if(this._currentFrameRate=Math.round(e.getEngine().getFps()),this._improvementMode&&this._currentFrameRate<=this._targetFrameRate||!this._improvementMode&&this._currentFrameRate>=this._targetFrameRate)return this._isRunning=!1,void this.onSuccessObservable.notifyObservers(this);for(var i=!0,o=!0,a=0;a<n.optimizations.length;a++){var s=n.optimizations[a];s.priority===this._currentPriorityLevel&&(o=!1,i=i&&s.apply(e,this),this.onNewOptimizationAppliedObservable.notifyObservers(s))}if(o)return this._isRunning=!1,void 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0&&(s=null),o=o??function(){return 1},a=a??function(){return 1},s=s??function(P,O){return P===O?0:1},this._characterToIdx=new Map,this._insertionCosts=new Array(i.length),this._deletionCosts=new Array(i.length),this._substitutionCosts=new Array(i.length);for(var p=0;p<i.length;++p){d=i[p],this._characterToIdx.set(d,p),this._insertionCosts[p]=o(d),this._deletionCosts[p]=a(d),this._substitutionCosts[p]=new Array(i.length);for(var b=p;b<i.length;++b)this._substitutionCosts[p][b]=s(d,i[b])}}return n.prototype.serialize=function(){var i={},o=new Array(this._characterToIdx.size);return this._characterToIdx.forEach(function(a,s){o[a]=s}),i.characters=o,i.insertionCosts=this._insertionCosts,i.deletionCosts=this._deletionCosts,i.substitutionCosts=this._substitutionCosts,JSON.stringify(i)},n.Deserialize=function(i){var o=JSON.parse(i),a=new n(o.characters);return a._insertionCosts=o.insertionCosts,a._deletionCosts=o.deletionCosts,a._substitutionCosts=o.substitutionCosts,a},n.prototype.getCharacterIdx=function(i){return this._characterToIdx.get(i)},n.prototype.getInsertionCost=function(i){return this._insertionCosts[i]},n.prototype.getDeletionCost=function(i){return this._deletionCosts[i]},n.prototype.getSubstitutionCost=function(i,o){var a=Math.min(i,o),s=Math.max(i,o);return this._substitutionCosts[a][s]},n}();r.Alphabet=t;var e=function(){function n(i,o){var a=this;if(i.length>n.MAX_SEQUENCE_LENGTH)throw new Error("Sequences longer than "+n.MAX_SEQUENCE_LENGTH+" not supported.");this._alphabet=o,this._characters=i.map(function(s){return a._alphabet.getCharacterIdx(s)})}return n.prototype.serialize=function(){return JSON.stringify(this._characters)},n.Deserialize=function(i,o){var a=new n([],o);return a._characters=JSON.parse(i),a},n.prototype.distance=function(i){return n._distance(this,i)},n._distance=function(i,o){var a=i._alphabet;if(a!==o._alphabet)throw new Error("Cannot Levenshtein compare Sequences built from different alphabets.");var s=i._characters,d=o._characters,p=s.length,b=d.length,P=n._costMatrix;P[0][0]=0;for(var O=0;O<p;++O)P[O+1][0]=P[O][0]+a.getInsertionCost(s[O]);for(O=0;O<b;++O)P[0][O+1]=P[0][O]+a.getInsertionCost(d[O]);for(var B=0;B<p;++B)for(var F=0;F<b;++F)n._insertionCost=P[B+1][F]+a.getInsertionCost(d[F]),n._deletionCost=P[B][F+1]+a.getDeletionCost(s[B]),n._substitutionCost=P[B][F]+a.getSubstitutionCost(s[B],d[F]),P[B+1][F+1]=Math.min(n._insertionCost,n._deletionCost,n._substitutionCost);return P[p][b]},n.MAX_SEQUENCE_LENGTH=256,n._costMatrix=Object(c.f)(Array(n.MAX_SEQUENCE_LENGTH+1)).map(function(i){return new Array(n.MAX_SEQUENCE_LENGTH+1)}),n}();r.Sequence=e})(kr||(kr={}));var pv=function(){function r(t){t===void 0&&(t=.01),this._points=[],this._segmentLength=t}return r.prototype.serialize=function(){return JSON.stringify(this)},r.Deserialize=function(t){var e=JSON.parse(t),n=new r(e._segmentLength);return n._points=e._points.map(function(i){return new u.e(i._x,i._y,i._z)}),n},r.prototype.getLength=function(){return this._points.length*this._segmentLength},r.prototype.add=function(t){var e=this,n=this._points.length;if(n===0)this._points.push(t.clone());else for(var i=function(){return e._segmentLength/u.e.Distance(e._points[n-1],t)},o=i();o<=1;o=i()){var a=this._points[n-1].scale(1-o);t.scaleAndAddToRef(o,a),this._points.push(a),++n}},r.prototype.resampleAtTargetResolution=function(t){var e=new r(this.getLength()/t);return this._points.forEach(function(n){e.add(n)}),e},r.prototype.tokenize=function(t){for(var e=[],n=new u.e,i=2;i<this._points.length;++i)r._transformSegmentDirToRef(this._points[i-2],this._points[i-1],this._points[i],n)&&e.push(r._tokenizeSegment(n,t));return e},r._transformSegmentDirToRef=function(t,e,n,i){return e.subtractToRef(t,r._forwardDir),r._forwardDir.normalize(),e.scaleToRef(-1,r._inverseFromVec),r._inverseFromVec.normalize(),!(Math.abs(u.e.Dot(r._forwardDir,r._inverseFromVec))>.98)&&(u.e.CrossToRef(r._forwardDir,r._inverseFromVec,r._upDir),r._upDir.normalize(),u.a.LookAtLHToRef(t,e,r._upDir,r._lookMatrix),n.subtractToRef(e,r._fromToVec),r._fromToVec.normalize(),u.e.TransformNormalToRef(r._fromToVec,r._lookMatrix,i),!0)},r._tokenizeSegment=function(t,e){r._bestMatch=0,r._score=u.e.Dot(t,e[0]),r._bestScore=r._score;for(var n=1;n<e.length;++n)r._score=u.e.Dot(t,e[n]),r._score>r._bestScore&&(r._bestMatch=n,r._bestScore=r._score);return r._bestMatch},r._forwardDir=new u.e,r._inverseFromVec=new u.e,r._upDir=new u.e,r._fromToVec=new u.e,r._lookMatrix=new u.a,r}(),_f=function(){function r(t){this.chars=new Array(t)}return r.Generate=function(t,e,n,i,o){t===void 0&&(t=64),e===void 0&&(e=256),n===void 0&&(n=.1),i===void 0&&(i=.001),o===void 0&&(o=[]);for(var a,s,d=new r(t),p=0;p<t;++p)d.chars[p]=new u.e(Math.random()-.5,Math.random()-.5,Math.random()-.5),d.chars[p].normalize();for(p=0;p<o.length;++p)d.chars[p].copyFrom(o[p]);for(var b,P=new u.e,O=new u.e,B=0;B<e;++B){a=(1-(b=B/(e-1)))*n+b*i;var F=function(z){P.copyFromFloats(0,0,0),d.chars.forEach(function(J){d.chars[z].subtractToRef(J,O),(s=O.lengthSquared())>1e-6&&O.scaleAndAddToRef(1/(O.lengthSquared()*s),P)}),P.scaleInPlace(a),d.chars[z].addInPlace(P),d.chars[z].normalize()};for(p=o.length;p<d.chars.length;++p)F(p)}return d},r.prototype.serialize=function(){return JSON.stringify(this.chars)},r.Deserialize=function(t){for(var e=JSON.parse(t),n=new r(e.length),i=0;i<e.length;++i)n.chars[i]=new u.e(e[i]._x,e[i]._y,e[i]._z);return n},r}(),Jc=function(){function r(){this._sequences=[]}return r.prototype.serialize=function(){return JSON.stringify(this._sequences.map(function(t){return t.serialize()}))},r.Deserialize=function(t,e){var n=new r;return n._sequences=JSON.parse(t).map(function(i){return kr.Sequence.Deserialize(i,e)}),n},r.CreateFromTrajectory=function(t,e,n){return r.CreateFromTokenizationPyramid(r._getTokenizationPyramid(t,e),n)},r.CreateFromTokenizationPyramid=function(t,e){var n=new r;return n._sequences=t.map(function(i){return new kr.Sequence(i,e)}),n},r._getTokenizationPyramid=function(t,e,n){n===void 0&&(n=r.FINEST_DESCRIPTOR_RESOLUTION);for(var i=[],o=n;o>4;o=Math.floor(o/2))i.push(t.resampleAtTargetResolution(o).tokenize(e.chars));return i},r.prototype.distance=function(t){for(var e=0,n=0;n<this._sequences.length;++n)e+=Math.pow(2,n)*this._sequences[n].distance(t._sequences[n]);return e},r.FINEST_DESCRIPTOR_RESOLUTION=32,r}(),mf=function(){function r(t){t===void 0&&(t=[]),this._descriptors=t,this._centroidIdx=-1,this._averageDistance=0,this._refreshDescription()}return r.prototype.serialize=function(){var t={};return t.descriptors=this._descriptors.map(function(e){return e.serialize()}),t.centroidIdx=this._centroidIdx,t.averageDistance=this._averageDistance,JSON.stringify(t)},r.Deserialize=function(t,e){var n=JSON.parse(t),i=new r;return i._descriptors=n.descriptors.map(function(o){return Jc.Deserialize(o,e)}),i._centroidIdx=n.centroidIdx,i._averageDistance=n.averageDistance,i},r.prototype.add=function(t){this._descriptors.push(t),this._refreshDescription()},r.prototype.getMatchCost=function(t){return t.distance(this._descriptors[this._centroidIdx])/this._averageDistance},r.prototype.getMatchMinimumDistance=function(t){return Math.min.apply(Math,this._descriptors.map(function(e){return e.distance(t)}))},r.prototype._refreshDescription=function(){var t,e=this;this._centroidIdx=-1;for(var n=this._descriptors.map(function(o){return t=0,e._descriptors.forEach(function(a){t+=o.distance(a)}),t}),i=0;i<n.length;++i)(this._centroidIdx<0||n[i]<n[this._centroidIdx])&&(this._centroidIdx=i);this._averageDistance=0,this._descriptors.forEach(function(o){e._averageDistance+=o.distance(e._descriptors[e._centroidIdx])}),this._descriptors.length>0&&(this._averageDistance=Math.max(this._averageDistance/this._descriptors.length,r.MIN_AVERAGE_DISTANCE))},r.MIN_AVERAGE_DISTANCE=1,r}(),_v=function(){function r(){this._maximumAllowableMatchCost=4,this._nameToDescribedTrajectory=new Map}return r.prototype.serialize=function(){var t={};return t.maximumAllowableMatchCost=this._maximumAllowableMatchCost,t.vector3Alphabet=this._vector3Alphabet.serialize(),t.levenshteinAlphabet=this._levenshteinAlphabet.serialize(),t.nameToDescribedTrajectory=[],this._nameToDescribedTrajectory.forEach(function(e,n){t.nameToDescribedTrajectory.push(n),t.nameToDescribedTrajectory.push(e.serialize())}),JSON.stringify(t)},r.Deserialize=function(t){var e=JSON.parse(t),n=new r;n._maximumAllowableMatchCost=e.maximumAllowableMatchCost,n._vector3Alphabet=_f.Deserialize(e.vector3Alphabet),n._levenshteinAlphabet=kr.Alphabet.Deserialize(e.levenshteinAlphabet);for(var i=0;i<e.nameToDescribedTrajectory.length;i+=2)n._nameToDescribedTrajectory.set(e.nameToDescribedTrajectory[i],mf.Deserialize(e.nameToDescribedTrajectory[i+1],n._levenshteinAlphabet));return n},r.Generate=function(){for(var t=_f.Generate(64,256,.1,.001,[u.e.Forward()]),e=new Array(t.chars.length),n=0;n<e.length;++n)e[n]=n;var i=new kr.Alphabet(e,function(a){return a===0?0:1},function(a){return a===0?0:1},function(a,s){return Math.min(1-u.e.Dot(t.chars[a],t.chars[s]),1)}),o=new r;return o._vector3Alphabet=t,o._levenshteinAlphabet=i,o},r.prototype.addTrajectoryToClassification=function(t,e){this._nameToDescribedTrajectory.has(e)||this._nameToDescribedTrajectory.set(e,new mf),this._nameToDescribedTrajectory.get(e).add(Jc.CreateFromTrajectory(t,this._vector3Alphabet,this._levenshteinAlphabet))},r.prototype.deleteClassification=function(t){return this._nameToDescribedTrajectory.delete(t)},r.prototype.classifyTrajectory=function(t){var e=this,n=Jc.CreateFromTrajectory(t,this._vector3Alphabet,this._levenshteinAlphabet),i=[];if(this._nameToDescribedTrajectory.forEach(function(p,b){p.getMatchCost(n)<e._maximumAllowableMatchCost&&i.push(b)}),i.length===0)return null;for(var o,a=0,s=this._nameToDescribedTrajectory.get(i[a]).getMatchMinimumDistance(n),d=0;d<i.length;++d)(o=this._nameToDescribedTrajectory.get(i[d]).getMatchMinimumDistance(n))<s&&(s=o,a=d);return i[a]},r}(),mv=f(150),Da=function(r){function t(e,n){n===void 0&&(n={});var i=r.call(this,e)||this;return i.options=n,i._direction=new u.e(0,0,-1),i._mat=new u.a,i._onSelectEnabled=!1,i._origin=new u.e(0,0,0),i.lastNativeXRHitResults=[],i.onHitTestResultObservable=new x.c,i._onHitTestResults=function(o){var a=o.map(function(s){var d=u.a.FromArray(s.hitMatrix);return i._xrSessionManager.scene.useRightHandedSystem||d.toggleModelMatrixHandInPlace(),i.options.worldParentNode&&d.multiplyToRef(i.options.worldParentNode.getWorldMatrix(),d),{xrHitResult:s,transformationMatrix:d}});i.lastNativeXRHitResults=o,i.onHitTestResultObservable.notifyObservers(a)},i._onSelect=function(o){i._onSelectEnabled&&t.XRHitTestWithSelectEvent(o,i._xrSessionManager.referenceSpace)},i.xrNativeFeatureName="hit-test",Xe.b.Warn("A newer version of this plugin is available"),i}return Object(c.d)(t,r),t.XRHitTestWithRay=function(e,n,i,o){return e.requestHitTest(n,i).then(function(a){var s=o||function(d){return!!d.hitMatrix};return a.filter(s)})},t.XRHitTestWithSelectEvent=function(e,n){var i=e.frame.getPose(e.inputSource.targetRaySpace,n);if(!i)return Promise.resolve([]);var o=new XRRay(i.transform);return this.XRHitTestWithRay(e.frame.session,o,n)},t.prototype.attach=function(){return!!r.prototype.attach.call(this)&&(this.options.testOnPointerDownOnly&&this._xrSessionManager.session.addEventListener("select",this._onSelect,!1),!0)},t.prototype.detach=function(){return!!r.prototype.detach.call(this)&&(this._onSelectEnabled=!1,this._xrSessionManager.session.removeEventListener("select",this._onSelect),!0)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onHitTestResultObservable.clear()},t.prototype._onXRFrame=function(e){if(this.attached&&!this.options.testOnPointerDownOnly){var n=e.getViewerPose(this._xrSessionManager.referenceSpace);if(n){u.a.FromArrayToRef(n.transform.matrix,0,this._mat),u.e.TransformCoordinatesFromFloatsToRef(0,0,0,this._mat,this._origin),u.e.TransformCoordinatesFromFloatsToRef(0,0,-1,this._mat,this._direction),this._direction.subtractInPlace(this._origin),this._direction.normalize();var i=new XRRay({x:this._origin.x,y:this._origin.y,z:this._origin.z,w:0},{x:this._direction.x,y:this._direction.y,z:this._direction.z,w:0});t.XRHitTestWithRay(this._xrSessionManager.session,i,this._xrSessionManager.referenceSpace).then(this._onHitTestResults)}}},t.Name=si.HIT_TEST,t.Version=1,t}(ci);qn.AddWebXRFeature(Da.Name,function(r,t){return function(){return new Da(r,t)}},Da.Version,!1);var gv=0,La=function(r){function t(e,n){n===void 0&&(n={});var i=r.call(this,e)||this;return i._options=n,i._lastFrameDetected=new Set,i._trackedAnchors=[],i._futureAnchors=[],i.onAnchorAddedObservable=new x.c,i.onAnchorRemovedObservable=new x.c,i.onAnchorUpdatedObservable=new x.c,i._tmpVector=new u.e,i._tmpQuaternion=new u.b,i.xrNativeFeatureName="anchors",i}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"referenceSpaceForFrameAnchors",{set:function(e){this._referenceSpaceForFrameAnchors=e},enumerable:!1,configurable:!0}),t.prototype._populateTmpTransformation=function(e,n){return this._tmpVector.copyFrom(e),this._tmpQuaternion.copyFrom(n),this._xrSessionManager.scene.useRightHandedSystem||(this._tmpVector.z*=-1,this._tmpQuaternion.z*=-1,this._tmpQuaternion.w*=-1),{position:this._tmpVector,rotationQuaternion:this._tmpQuaternion}},t.prototype.addAnchorPointUsingHitTestResultAsync=function(e,n,i){return n===void 0&&(n=new u.e),i===void 0&&(i=new u.b),Object(c.b)(this,void 0,void 0,function(){var o,a,s,d=this;return Object(c.e)(this,function(p){switch(p.label){case 0:if(this._populateTmpTransformation(n,i),o=new XRRigidTransform({x:this._tmpVector.x,y:this._tmpVector.y,z:this._tmpVector.z},{x:this._tmpQuaternion.x,y:this._tmpQuaternion.y,z:this._tmpQuaternion.z,w:this._tmpQuaternion.w}),e.xrHitResult.createAnchor)return[3,1];throw this.detach(),new Error("Anchors not enabled in this environment/browser");case 1:return p.trys.push([1,3,,4]),[4,e.xrHitResult.createAnchor(o)];case 2:return a=p.sent(),[2,new Promise(function(b,P){d._futureAnchors.push({nativeAnchor:a,resolved:!1,submitted:!0,xrTransformation:o,resolve:b,reject:P})})];case 3:throw s=p.sent(),new Error(s);case 4:return[2]}})})},t.prototype.addAnchorAtPositionAndRotationAsync=function(e,n,i){return n===void 0&&(n=new u.b),i===void 0&&(i=!1),Object(c.b)(this,void 0,void 0,function(){var o,a,s,d=this;return Object(c.e)(this,function(p){switch(p.label){case 0:return this._populateTmpTransformation(e,n),o=new XRRigidTransform({x:this._tmpVector.x,y:this._tmpVector.y,z:this._tmpVector.z},{x:this._tmpQuaternion.x,y:this._tmpQuaternion.y,z:this._tmpQuaternion.z,w:this._tmpQuaternion.w}),i&&this.attached&&this._xrSessionManager.currentFrame?[4,this._createAnchorAtTransformation(o,this._xrSessionManager.currentFrame)]:[3,2];case 1:return s=p.sent(),[3,3];case 2:s=void 0,p.label=3;case 3:return a=s,[2,new Promise(function(b,P){d._futureAnchors.push({nativeAnchor:a,resolved:!1,submitted:!1,xrTransformation:o,resolve:b,reject:P})})]}})})},Object.defineProperty(t.prototype,"anchors",{get:function(){return this._trackedAnchors},enumerable:!1,configurable:!0}),t.prototype.detach=function(){if(!r.prototype.detach.call(this))return!1;if(!this._options.doNotRemoveAnchorsOnSessionEnded)for(;this._trackedAnchors.length;){var e=this._trackedAnchors.pop();if(e){try{e.remove()}catch{}this.onAnchorRemovedObservable.notifyObservers(e)}}return!0},t.prototype.dispose=function(){this._futureAnchors.length=0,r.prototype.dispose.call(this),this.onAnchorAddedObservable.clear(),this.onAnchorRemovedObservable.clear(),this.onAnchorUpdatedObservable.clear()},t.prototype._onXRFrame=function(e){var n=this;if(this.attached&&e){var i=e.trackedAnchors;if(i){var o=this._trackedAnchors.filter(function(s){return!i.has(s.xrAnchor)}).map(function(s){return n._trackedAnchors.indexOf(s)}),a=0;o.forEach(function(s){var d=n._trackedAnchors.splice(s-a,1)[0];n.onAnchorRemovedObservable.notifyObservers(d),a++}),i.forEach(function(s){if(n._lastFrameDetected.has(s)){var d=n._findIndexInAnchorArray(s);b=n._trackedAnchors[d];try{n._updateAnchorWithXRFrame(s,b,e),b.attachedNode&&(b.attachedNode.rotationQuaternion=b.attachedNode.rotationQuaternion||new u.b,b.transformationMatrix.decompose(b.attachedNode.scaling,b.attachedNode.rotationQuaternion,b.attachedNode.position)),n.onAnchorUpdatedObservable.notifyObservers(b)}catch{Xe.b.Warn("Anchor could not be updated")}}else{var p={id:gv++,xrAnchor:s,remove:s.delete},b=n._updateAnchorWithXRFrame(s,p,e);n._trackedAnchors.push(b),n.onAnchorAddedObservable.notifyObservers(b);var P=n._futureAnchors.filter(function(O){return O.nativeAnchor===s})[0];P&&(P.resolve(b),P.resolved=!0)}}),this._lastFrameDetected=i}this._futureAnchors.forEach(function(s){s.resolved||s.submitted||(n._createAnchorAtTransformation(s.xrTransformation,e).then(function(d){s.nativeAnchor=d},function(d){s.resolved=!0,s.reject(d)}),s.submitted=!0)})}},t.prototype._findIndexInAnchorArray=function(e){for(var n=0;n<this._trackedAnchors.length;++n)if(this._trackedAnchors[n].xrAnchor===e)return n;return-1},t.prototype._updateAnchorWithXRFrame=function(e,n,i){var o=i.getPose(e.anchorSpace,this._xrSessionManager.referenceSpace);if(o){var a=n.transformationMatrix||new u.a;u.a.FromArrayToRef(o.transform.matrix,0,a),this._xrSessionManager.scene.useRightHandedSystem||a.toggleModelMatrixHandInPlace(),n.transformationMatrix=a,this._options.worldParentNode&&a.multiplyToRef(this._options.worldParentNode.getWorldMatrix(),a)}return n},t.prototype._createAnchorAtTransformation=function(e,n){var i;return Object(c.b)(this,void 0,void 0,function(){return Object(c.e)(this,function(o){if(!n.createAnchor)throw this.detach(),new Error("Anchors are not enabled in your browser");try{return[2,n.createAnchor(e,(i=this._referenceSpaceForFrameAnchors)!==null&&i!==void 0?i:this._xrSessionManager.referenceSpace)]}catch(a){throw new Error(a)}return[2]})})},t.Name=si.ANCHOR_SYSTEM,t.Version=1,t}(ci);qn.AddWebXRFeature(La.Name,function(r,t){return function(){return new La(r,t)}},La.Version);var vv=0,Na=function(r){function t(e,n){n===void 0&&(n={});var i=r.call(this,e)||this;return i._options=n,i._detectedPlanes=[],i._enabled=!1,i._lastFrameDetected=new Set,i.onPlaneAddedObservable=new x.c,i.onPlaneRemovedObservable=new x.c,i.onPlaneUpdatedObservable=new x.c,i.xrNativeFeatureName="plane-detection",i._xrSessionManager.session?i._init():i._xrSessionManager.onXRSessionInit.addOnce(function(){i._init()}),i}return Object(c.d)(t,r),t.prototype.detach=function(){if(!r.prototype.detach.call(this))return!1;if(!this._options.doNotRemovePlanesOnSessionEnded)for(;this._detectedPlanes.length;){var e=this._detectedPlanes.pop();e&&this.onPlaneRemovedObservable.notifyObservers(e)}return!0},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onPlaneAddedObservable.clear(),this.onPlaneRemovedObservable.clear(),this.onPlaneUpdatedObservable.clear()},t.prototype.isCompatible=function(){return typeof XRPlane<"u"},t.prototype._onXRFrame=function(e){var n=this;if(this.attached&&this._enabled&&e){var i=e.worldInformation.detectedPlanes;if(i){var o=this._detectedPlanes.filter(function(s){return!i.has(s.xrPlane)}).map(function(s){return n._detectedPlanes.indexOf(s)}),a=0;o.forEach(function(s){var d=n._detectedPlanes.splice(s-a,1)[0];n.onPlaneRemovedObservable.notifyObservers(d),a++}),i.forEach(function(s){if(n._lastFrameDetected.has(s)){if(s.lastChangedTime===n._xrSessionManager.currentTimestamp){var d=n.findIndexInPlaneArray(s);b=n._detectedPlanes[d],n._updatePlaneWithXRPlane(s,b,e),n.onPlaneUpdatedObservable.notifyObservers(b)}}else{var p={id:vv++,xrPlane:s,polygonDefinition:[]},b=n._updatePlaneWithXRPlane(s,p,e);n._detectedPlanes.push(b),n.onPlaneAddedObservable.notifyObservers(b)}}),this._lastFrameDetected=i}}},t.prototype._init=function(){var e,n,i=this,o=function(){i._enabled=!0,i._detectedPlanes.length&&(i._detectedPlanes.length=0)};this._xrSessionManager.session.updateWorldTrackingState?(this._xrSessionManager.session.updateWorldTrackingState({planeDetectionState:{enabled:!0}}),o()):!((n=(e=this._xrSessionManager.session.worldTrackingState)===null||e===void 0?void 0:e.planeDetectionState)===null||n===void 0)&&n.enabled&&o()},t.prototype._updatePlaneWithXRPlane=function(e,n,i){var o=this;n.polygonDefinition=e.polygon.map(function(d){var p=o._xrSessionManager.scene.useRightHandedSystem?1:-1;return new u.e(d.x,d.y,d.z*p)});var a=i.getPose(e.planeSpace,this._xrSessionManager.referenceSpace);if(a){var s=n.transformationMatrix||new u.a;u.a.FromArrayToRef(a.transform.matrix,0,s),this._xrSessionManager.scene.useRightHandedSystem||s.toggleModelMatrixHandInPlace(),n.transformationMatrix=s,this._options.worldParentNode&&s.multiplyToRef(this._options.worldParentNode.getWorldMatrix(),s)}return n},t.prototype.findIndexInPlaneArray=function(e){for(var n=0;n<this._detectedPlanes.length;++n)if(this._detectedPlanes[n].xrPlane===e)return n;return-1},t.Name=si.PLANE_DETECTION,t.Version=1,t}(ci);qn.AddWebXRFeature(Na.Name,function(r,t){return function(){return new Na(r,t)}},Na.Version);var wa=function(r){function t(e,n){n===void 0&&(n={});var i=r.call(this,e)||this;return i.options=n,i.onBackgroundStateChangedObservable=new x.c,i}return Object(c.d)(t,r),t.prototype.attach=function(){return this._setBackgroundState(!1),r.prototype.attach.call(this)},t.prototype.detach=function(){return this._setBackgroundState(!0),r.prototype.detach.call(this)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onBackgroundStateChangedObservable.clear()},t.prototype._onXRFrame=function(e){},t.prototype._setBackgroundState=function(e){var n=this._xrSessionManager.scene;if(!this.options.ignoreEnvironmentHelper)if(this.options.environmentHelperRemovalFlags){if(this.options.environmentHelperRemovalFlags.skyBox){var i=n.getMeshByName("BackgroundSkybox");i&&i.setEnabled(e)}if(this.options.environmentHelperRemovalFlags.ground){var o=n.getMeshByName("BackgroundPlane");o&&o.setEnabled(e)}}else{var a=n.getMeshByName("BackgroundHelper");a&&a.setEnabled(e)}this.options.backgroundMeshes&&this.options.backgroundMeshes.forEach(function(s){return s.setEnabled(e)}),this.onBackgroundStateChangedObservable.notifyObservers(e)},t.Name=si.BACKGROUND_REMOVER,t.Version=1,t}(ci);qn.AddWebXRFeature(wa.Name,function(r,t){return function(){return new wa(r,t)}},wa.Version,!0);var bv=function(){},Fa=function(r){function t(e,n){var i=r.call(this,e)||this;return i._options=n,i._attachController=function(o){if(!i._controllers[o.uniqueId])if(i._xrSessionManager.scene.isPhysicsEnabled()||l.a.Warn("physics engine not enabled, skipped. Please add this controller manually."),i._options.physicsProperties.useControllerMesh&&o.inputSource.gamepad)o.onMotionControllerInitObservable.addOnce(function(P){P.onModelLoadedObservable.addOnce(function(){var O=new Ct.a(P.rootMesh,Ct.a.MeshImpostor,Object(c.a)({mass:0},i._options.physicsProperties)),B=o.grip||o.pointer;i._controllers[o.uniqueId]={xrController:o,impostor:O,oldPos:B.position.clone(),oldRotation:B.rotationQuaternion.clone()}})});else{var a=i._options.physicsProperties.impostorType||Ct.a.SphereImpostor,s=i._options.physicsProperties.impostorSize||.1,d=Fn.a.CreateSphere("impostor-mesh-"+o.uniqueId,{diameterX:typeof s=="number"?s:s.width,diameterY:typeof s=="number"?s:s.height,diameterZ:typeof s=="number"?s:s.depth});d.isVisible=i._debugMode,d.isPickable=!1,d.rotationQuaternion=new u.b;var p=o.grip||o.pointer;d.position.copyFrom(p.position),d.rotationQuaternion.copyFrom(p.rotationQuaternion);var b=new Ct.a(d,a,Object(c.a)({mass:0},i._options.physicsProperties));i._controllers[o.uniqueId]={xrController:o,impostor:b,impostorMesh:d}}},i._controllers={},i._debugMode=!1,i._delta=0,i._lastTimestamp=0,i._tmpQuaternion=new u.b,i._tmpVector=new u.e,i._options.physicsProperties||(i._options.physicsProperties={}),i}return Object(c.d)(t,r),t.prototype._enablePhysicsDebug=function(){var e=this;this._debugMode=!0,Object.keys(this._controllers).forEach(function(n){var i=e._controllers[n];i.impostorMesh&&(i.impostorMesh.isVisible=!0)})},t.prototype.addController=function(e){this._attachController(e)},t.prototype.attach=function(){var e=this;if(!r.prototype.attach.call(this))return!1;if(!this._options.xrInput)return!0;if(this._options.xrInput.controllers.forEach(this._attachController),this._addNewAttachObserver(this._options.xrInput.onControllerAddedObservable,this._attachController),this._addNewAttachObserver(this._options.xrInput.onControllerRemovedObservable,function(o){e._detachController(o.uniqueId)}),this._options.enableHeadsetImpostor){var n=this._options.headsetImpostorParams||{impostorType:Ct.a.SphereImpostor,restitution:.8,impostorSize:.3},i=n.impostorSize||.3;this._headsetMesh=Fn.a.CreateSphere("headset-mesh",{diameterX:typeof i=="number"?i:i.width,diameterY:typeof i=="number"?i:i.height,diameterZ:typeof i=="number"?i:i.depth}),this._headsetMesh.rotationQuaternion=new u.b,this._headsetMesh.isVisible=!1,this._headsetImpostor=new Ct.a(this._headsetMesh,n.impostorType,Object(c.a)({mass:0},n))}return!0},t.prototype.detach=function(){var e=this;return!!r.prototype.detach.call(this)&&(Object.keys(this._controllers).forEach(function(n){e._detachController(n)}),this._headsetMesh&&this._headsetMesh.dispose(),!0)},t.prototype.getHeadsetImpostor=function(){return this._headsetImpostor},t.prototype.getImpostorForController=function(e){var n=typeof e=="string"?e:e.uniqueId;return this._controllers[n]?this._controllers[n].impostor:null},t.prototype.setPhysicsProperties=function(e){this._options.physicsProperties=Object(c.a)(Object(c.a)({},this._options.physicsProperties),e)},t.prototype._onXRFrame=function(e){var n=this;this._delta=this._xrSessionManager.currentTimestamp-this._lastTimestamp,this._lastTimestamp=this._xrSessionManager.currentTimestamp,this._headsetMesh&&(this._headsetMesh.position.copyFrom(this._options.xrInput.xrCamera.position),this._headsetMesh.rotationQuaternion.copyFrom(this._options.xrInput.xrCamera.rotationQuaternion)),Object.keys(this._controllers).forEach(function(i){var o=n._controllers[i],a=o.xrController.grip||o.xrController.pointer,s=o.oldPos||o.impostorMesh.position,d=o.oldRotation||o.impostorMesh.rotationQuaternion;if(a.position.subtractToRef(s,n._tmpVector),n._tmpVector.scaleInPlace(1e3/n._delta),o.impostor.setLinearVelocity(n._tmpVector),n._debugMode&&console.log(n._tmpVector,"linear"),!d.equalsWithEpsilon(a.rotationQuaternion)){d.conjugateInPlace().multiplyToRef(a.rotationQuaternion,n._tmpQuaternion);var p=Math.sqrt(n._tmpQuaternion.x*n._tmpQuaternion.x+n._tmpQuaternion.y*n._tmpQuaternion.y+n._tmpQuaternion.z*n._tmpQuaternion.z);if(n._tmpVector.set(n._tmpQuaternion.x,n._tmpQuaternion.y,n._tmpQuaternion.z),p<.001)n._tmpVector.scaleInPlace(2);else{var b=2*Math.atan2(p,n._tmpQuaternion.w);n._tmpVector.scaleInPlace(b/(p*(n._delta/1e3)))}o.impostor.setAngularVelocity(n._tmpVector),n._debugMode&&console.log(n._tmpVector,n._tmpQuaternion,"angular")}s.copyFrom(a.position),d.copyFrom(a.rotationQuaternion)})},t.prototype._detachController=function(e){var n=this._controllers[e];n&&(n.impostorMesh&&n.impostorMesh.dispose(),delete this._controllers[e])},t.Name=si.PHYSICS_CONTROLLERS,t.Version=1,t}(ci);qn.AddWebXRFeature(Fa.Name,function(r,t){return function(){return new Fa(r,t)}},Fa.Version,!0);var Ba=function(r){function t(e,n){n===void 0&&(n={});var i=r.call(this,e)||this;return i.options=n,i._tmpMat=new u.a,i._tmpPos=new u.e,i._tmpQuat=new u.b,i.initHitTestSource=function(o){if(o){var a=new XRRay(i.options.offsetRay||{}),s={space:i.options.useReferenceSpace?o:i._xrSessionManager.viewerReferenceSpace,offsetRay:a};i.options.entityTypes&&(s.entityTypes=i.options.entityTypes),s.space?i._xrSessionManager.session.requestHitTestSource(s).then(function(d){i._xrHitTestSource&&i._xrHitTestSource.cancel(),i._xrHitTestSource=d}):Xe.b.Warn("waiting for viewer reference space to initialize")}},i.autoCloneTransformation=!1,i.onHitTestResultObservable=new x.c,i.paused=!1,i.xrNativeFeatureName="hit-test",Xe.b.Warn("Hit test is an experimental and unstable feature."),i}return Object(c.d)(t,r),t.prototype.attach=function(){var e=this;if(!r.prototype.attach.call(this)||!this._xrSessionManager.session.requestHitTestSource)return!1;if(this.options.disablePermanentHitTest||(this._xrSessionManager.referenceSpace&&this.initHitTestSource(this._xrSessionManager.referenceSpace),this._xrSessionManager.onXRReferenceSpaceChanged.add(this.initHitTestSource)),this.options.enableTransientHitTest){var n=new XRRay(this.options.transientOffsetRay||{});this._xrSessionManager.session.requestHitTestSourceForTransientInput({profile:"generic-touchscreen",offsetRay:n,entityTypes:this.options.entityTypes}).then(function(i){e._transientXrHitTestSource=i})}return!0},t.prototype.detach=function(){return!!r.prototype.detach.call(this)&&(this._xrHitTestSource&&(this._xrHitTestSource.cancel(),this._xrHitTestSource=null),this._xrSessionManager.onXRReferenceSpaceChanged.removeCallback(this.initHitTestSource),this._transientXrHitTestSource&&(this._transientXrHitTestSource.cancel(),this._transientXrHitTestSource=null),!0)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onHitTestResultObservable.clear()},t.prototype._onXRFrame=function(e){var n=this;if(this.attached&&!this.paused){if(this._xrHitTestSource){var i=e.getHitTestResults(this._xrHitTestSource);this._processWebXRHitTestResult(i)}this._transientXrHitTestSource&&e.getHitTestResultsForTransientInput(this._transientXrHitTestSource).forEach(function(o){n._processWebXRHitTestResult(o.results,o.inputSource)})}},t.prototype._processWebXRHitTestResult=function(e,n){var i=this,o=[];e.forEach(function(a){var s=a.getPose(i._xrSessionManager.referenceSpace);if(s){var d=s.transform.position,p=s.transform.orientation;i._tmpPos.set(d.x,d.y,d.z),i._tmpQuat.set(p.x,p.y,p.z,p.w),u.a.FromFloat32ArrayToRefScaled(s.transform.matrix,0,1,i._tmpMat),i._xrSessionManager.scene.useRightHandedSystem||(i._tmpPos.z*=-1,i._tmpQuat.z*=-1,i._tmpQuat.w*=-1,i._tmpMat.toggleModelMatrixHandInPlace());var b={position:i.autoCloneTransformation?i._tmpPos.clone():i._tmpPos,rotationQuaternion:i.autoCloneTransformation?i._tmpQuat.clone():i._tmpQuat,transformationMatrix:i.autoCloneTransformation?i._tmpMat.clone():i._tmpMat,inputSource:n,isTransient:!!n,xrHitResult:a};o.push(b)}}),this.onHitTestResultObservable.notifyObservers(o)},t.Name=si.HIT_TEST,t.Version=2,t}(ci);qn.AddWebXRFeature(Ba.Name,function(r,t){return function(){return new Ba(r,t)}},Ba.Version,!1);var Ua=function(r){function t(e){var n=r.call(this,e)||this;return n._enabled=!1,n._featurePointCloud=[],n.onFeaturePointsAddedObservable=new x.c,n.onFeaturePointsUpdatedObservable=new x.c,n.xrNativeFeatureName="bjsfeature-points",n._xrSessionManager.session?n._init():n._xrSessionManager.onXRSessionInit.addOnce(function(){n._init()}),n}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"featurePointCloud",{get:function(){return this._featurePointCloud},enumerable:!1,configurable:!0}),t.prototype.detach=function(){return!!r.prototype.detach.call(this)&&(this.featurePointCloud.length=0,!0)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this._featurePointCloud.length=0,this.onFeaturePointsUpdatedObservable.clear(),this.onFeaturePointsAddedObservable.clear()},t.prototype._onXRFrame=function(e){if(this.attached&&this._enabled&&e){var n=e.featurePointCloud;if(n&&n.length!==0){if(n.length%5!=0)throw new Error("Received malformed feature point cloud of length: "+n.length);for(var i=n.length/5,o=new Array,a=new Array,s=0;s<i;s++){var d=5*s,p=n[d+4];this._featurePointCloud[p]?o.push(p):(this._featurePointCloud[p]={position:new u.e,confidenceValue:0},a.push(p)),this._featurePointCloud[p].position.x=n[d],this._featurePointCloud[p].position.y=n[d+1],this._featurePointCloud[p].position.z=n[d+2],this._featurePointCloud[p].confidenceValue=n[d+3]}a.length>0&&this.onFeaturePointsAddedObservable.notifyObservers(a),o.length>0&&this.onFeaturePointsUpdatedObservable.notifyObservers(o)}}},t.prototype._init=function(){this._xrSessionManager.session.trySetFeaturePointCloudEnabled&&this._xrSessionManager.session.trySetFeaturePointCloudEnabled(!0)&&(this._enabled=!0)},t.Name=si.FEATURE_POINTS,t.Version=1,t}(ci);qn.AddWebXRFeature(Ua.Name,function(r){return function(){return new Ua(r)}},Ua.Version);var gf=function(){function r(t,e,n,i,o){this.xrController=t,this.trackedMeshes=e,this._handMesh=n,this._rigMapping=i,this._defaultHandMesh=!1,this._transformNodeMapping=[],this.handPartsDefinition=this.generateHandPartsDefinition(t.inputSource.hand),this._scene=e[0].getScene(),this._handMesh&&this._rigMapping?this._defaultHandMesh=!1:o||this._generateDefaultHandMesh(),this.xrController.motionController&&(this.xrController.motionController.rootMesh?this.xrController.motionController.rootMesh.setEnabled(!1):this.xrController.motionController.onModelLoadedObservable.add(function(a){a.rootMesh&&a.rootMesh.setEnabled(!1)})),this.xrController.onMotionControllerInitObservable.add(function(a){a.onModelLoadedObservable.add(function(s){s.rootMesh&&s.rootMesh.setEnabled(!1)}),a.rootMesh&&a.rootMesh.setEnabled(!1)})}return r.prototype.generateHandPartsDefinition=function(t){var e;return(e={}).wrist=[t.WRIST],e.thumb=[t.THUMB_METACARPAL,t.THUMB_PHALANX_PROXIMAL,t.THUMB_PHALANX_DISTAL,t.THUMB_PHALANX_TIP],e.index=[t.INDEX_METACARPAL,t.INDEX_PHALANX_PROXIMAL,t.INDEX_PHALANX_INTERMEDIATE,t.INDEX_PHALANX_DISTAL,t.INDEX_PHALANX_TIP],e.middle=[t.MIDDLE_METACARPAL,t.MIDDLE_PHALANX_PROXIMAL,t.MIDDLE_PHALANX_INTERMEDIATE,t.MIDDLE_PHALANX_DISTAL,t.MIDDLE_PHALANX_TIP],e.ring=[t.RING_METACARPAL,t.RING_PHALANX_PROXIMAL,t.RING_PHALANX_INTERMEDIATE,t.RING_PHALANX_DISTAL,t.RING_PHALANX_TIP],e.little=[t.LITTLE_METACARPAL,t.LITTLE_PHALANX_PROXIMAL,t.LITTLE_PHALANX_INTERMEDIATE,t.LITTLE_PHALANX_DISTAL,t.LITTLE_PHALANX_TIP],e},r.prototype.updateFromXRFrame=function(t,e,n){var i=this;n===void 0&&(n=2);var o=this.xrController.inputSource.hand;o&&this.trackedMeshes.forEach(function(a,s){var d=o[s];if(d){var p=t.getJointPose(d,e);if(!p||!p.transform)return;var b=p.transform.position,P=p.transform.orientation;a.position.set(b.x,b.y,b.z),a.rotationQuaternion.set(P.x,P.y,P.z,P.w);var O=(p.radius||.008)*n;a.scaling.set(O,O,O),i._handMesh&&i._rigMapping&&i._rigMapping[s]&&(i._transformNodeMapping[s]=i._transformNodeMapping[s]||i._scene.getTransformNodeByName(i._rigMapping[s]),i._transformNodeMapping[s]&&(i._transformNodeMapping[s].position.copyFrom(a.position),i._transformNodeMapping[s].rotationQuaternion.copyFrom(a.rotationQuaternion),a.isVisible=!1)),a.getScene().useRightHandedSystem||(a.position.z*=-1,a.rotationQuaternion.z*=-1,a.rotationQuaternion.w*=-1)}})},r.prototype.getHandPartMeshes=function(t){var e=this;return this.handPartsDefinition[t].map(function(n){return e.trackedMeshes[n]})},r.prototype.dispose=function(){this.trackedMeshes.forEach(function(t){return t.dispose()}),this._defaultHandMesh&&this._handMesh&&this._handMesh.dispose()},r.prototype._generateDefaultHandMesh=function(){return Object(c.b)(this,void 0,void 0,function(){var t,e,n,i,o,a,s,d;return Object(c.e)(this,function(p){switch(p.label){case 0:return p.trys.push([0,3,,4]),t=this.xrController.inputSource.handedness==="right"?"right":"left",e=(t==="right"?"r":"l")+"_hand_"+(this._scene.useRightHandedSystem?"r":"l")+"hs.glb",[4,Ut.ImportMeshAsync("","https://assets.babylonjs.com/meshes/HandMeshes/",e,this._scene)];case 1:return n=p.sent(),i={base:M.a.FromInts(116,63,203),fresnel:M.a.FromInts(149,102,229),fingerColor:M.a.FromInts(177,130,255),tipFresnel:M.a.FromInts(220,200,255)},[4,(o=new ga("leftHandShader",this._scene,{emitComments:!1})).loadAsync("https://patrickryanms.github.io/BabylonJStextures/Demos/xrHandMesh/handsShader.json")];case 2:if(p.sent(),o.build(!1),o.needDepthPrePass=!0,o.transparencyMode=Ht.a.MATERIAL_ALPHABLEND,o.alphaMode=Ue.a.ALPHA_COMBINE,(a={base:o.getBlockByName("baseColor"),fresnel:o.getBlockByName("fresnelColor"),fingerColor:o.getBlockByName("fingerColor"),tipFresnel:o.getBlockByName("tipFresnelColor")}).base.value=i.base,a.fresnel.value=i.fresnel,a.fingerColor.value=i.fingerColor,a.tipFresnel.value=i.tipFresnel,n.meshes[1].material=o,this._defaultHandMesh=!0,this._handMesh=n.meshes[0],this._rigMapping=["wrist_","thumb_metacarpal_","thumb_proxPhalanx_","thumb_distPhalanx_","thumb_tip_","index_metacarpal_","index_proxPhalanx_","index_intPhalanx_","index_distPhalanx_","index_tip_","middle_metacarpal_","middle_proxPhalanx_","middle_intPhalanx_","middle_distPhalanx_","middle_tip_","ring_metacarpal_","ring_proxPhalanx_","ring_intPhalanx_","ring_distPhalanx_","ring_tip_","little_metacarpal_","little_proxPhalanx_","little_intPhalanx_","little_distPhalanx_","little_tip_"].map(function(b){return b+(t==="right"?"R":"L")}),!(s=this._scene.getTransformNodeByName(this._rigMapping[0])))throw new Error("could not find the wrist node");return s.parent&&s.parent.rotate(ye.a.Y,Math.PI),[3,4];case 3:return d=p.sent(),Xe.b.Error("error loading hand mesh"),console.log(d),[3,4];case 4:return[2]}})})},r}(),Va=function(r){function t(e,n){var i=r.call(this,e)||this;return i.options=n,i.onHandAddedObservable=new x.c,i.onHandRemovedObservable=new x.c,i._hands={},i._attachHand=function(o){var a,s,d,p,b,P,O,B,F,z;if(o.inputSource.hand&&!i._hands[o.uniqueId]){var J=o.inputSource.hand,ie=[],se=((a=i.options.jointMeshes)===null||a===void 0?void 0:a.sourceMesh)||Fn.a.CreateSphere("jointParent",{diameter:1});se.isVisible=!!(!((s=i.options.jointMeshes)===null||s===void 0)&&s.keepOriginalVisible);for(var ce=0;ce<J.length;++ce){var ue=se.createInstance(o.uniqueId+"-handJoint-"+ce);if(!((d=i.options.jointMeshes)===null||d===void 0)&&d.onHandJointMeshGenerated){var fe=i.options.jointMeshes.onHandJointMeshGenerated(ue,ce,o.uniqueId);fe&&fe!==ue&&(ue.dispose(),ue=fe)}if(ue.isPickable=!1,(p=i.options.jointMeshes)===null||p===void 0?void 0:p.enablePhysics){var ve=i.options.jointMeshes.physicsProps||{},Te=ve.impostorType!==void 0?ve.impostorType:Ct.a.SphereImpostor;ue.physicsImpostor=new Ct.a(ue,Te,Object(c.a)({mass:0},ve))}ue.rotationQuaternion=new u.b,!((b=i.options.jointMeshes)===null||b===void 0)&&b.invisible&&(ue.isVisible=!1),ie.push(ue)}var Re=o.inputSource.handedness==="right"?"right":"left",Ae=((P=i.options.jointMeshes)===null||P===void 0?void 0:P.handMeshes)&&((O=i.options.jointMeshes)===null||O===void 0?void 0:O.handMeshes[Re]),Ee=((B=i.options.jointMeshes)===null||B===void 0?void 0:B.rigMapping)&&((F=i.options.jointMeshes)===null||F===void 0?void 0:F.rigMapping[Re]),Se=new gf(o,ie,Ae,Ee,(z=i.options.jointMeshes)===null||z===void 0?void 0:z.disableDefaultHandMesh);i._hands[o.uniqueId]={handObject:Se,id:t._idCounter++},i.onHandAddedObservable.notifyObservers(Se)}},i.xrNativeFeatureName="hand-tracking",i}return Object(c.d)(t,r),t.prototype.isCompatible=function(){return typeof XRHand<"u"},t.prototype.attach=function(){var e=this;return!!r.prototype.attach.call(this)&&(this.options.xrInput.controllers.forEach(this._attachHand),this._addNewAttachObserver(this.options.xrInput.onControllerAddedObservable,this._attachHand),this._addNewAttachObserver(this.options.xrInput.onControllerRemovedObservable,function(n){e._detachHand(n.uniqueId)}),!0)},t.prototype.detach=function(){var e=this;return!!r.prototype.detach.call(this)&&(Object.keys(this._hands).forEach(function(n){e._detachHand(n)}),!0)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onHandAddedObservable.clear()},t.prototype.getHandByControllerId=function(e){var n;return((n=this._hands[e])===null||n===void 0?void 0:n.handObject)||null},t.prototype.getHandByHandedness=function(e){var n=this,i=Object.keys(this._hands).map(function(o){return n._hands[o].handObject.xrController.inputSource.handedness}).indexOf(e);return i!==-1?this._hands[i].handObject:null},t.prototype._onXRFrame=function(e){var n=this;Object.keys(this._hands).forEach(function(i){var o;n._hands[i].handObject.updateFromXRFrame(e,n._xrSessionManager.referenceSpace,(o=n.options.jointMeshes)===null||o===void 0?void 0:o.scaleFactor)})},t.prototype._detachHand=function(e){this._hands[e]&&(this.onHandRemovedObservable.notifyObservers(this._hands[e].handObject),this._hands[e].handObject.dispose())},t._idCounter=0,t.Name=si.HAND_TRACKING,t.Version=1,t}(ci);qn.AddWebXRFeature(Va.Name,function(r,t){return function(){return new Va(r,t)}},Va.Version,!1);var vf=function(r){function t(e,n,i){var o=r.call(this,e,yv["left-right"],n,i)||this;return o._mapping={defaultButton:{valueNodeName:"VALUE",unpressedNodeName:"UNPRESSED",pressedNodeName:"PRESSED"},defaultAxis:{valueNodeName:"VALUE",minNodeName:"MIN",maxNodeName:"MAX"},buttons:{"xr-standard-trigger":{rootNodeName:"SELECT",componentProperty:"button",states:["default","touched","pressed"]},"xr-standard-squeeze":{rootNodeName:"GRASP",componentProperty:"state",states:["pressed"]},"xr-standard-touchpad":{rootNodeName:"TOUCHPAD_PRESS",labelAnchorNodeName:"squeeze-label",touchPointNodeName:"TOUCH"},"xr-standard-thumbstick":{rootNodeName:"THUMBSTICK_PRESS",componentProperty:"state",states:["pressed"]}},axes:{"xr-standard-touchpad":{"x-axis":{rootNodeName:"TOUCHPAD_TOUCH_X"},"y-axis":{rootNodeName:"TOUCHPAD_TOUCH_Y"}},"xr-standard-thumbstick":{"x-axis":{rootNodeName:"THUMBSTICK_X"},"y-axis":{rootNodeName:"THUMBSTICK_Y"}}}},o.profileId="microsoft-mixed-reality",o}return Object(c.d)(t,r),t.prototype._getFilenameAndPath=function(){return{filename:this.handedness==="left"?t.MODEL_LEFT_FILENAME:t.MODEL_RIGHT_FILENAME,path:t.MODEL_BASE_URL+"default/"}},t.prototype._getModelLoadingConstraints=function(){var e=Ut.IsPluginForExtensionAvailable(".glb");return e||l.a.Warn("glTF / glb loaded was not registered, using generic controller instead"),e},t.prototype._processLoadedModel=function(e){var n=this;this.rootMesh&&(this.getComponentIds().forEach(function(i,o){if(!n.disableAnimation&&i&&n.rootMesh){var a=n._mapping.buttons[i],s=a.rootNodeName;if(!s)return void l.a.Log("Skipping unknown button at index: "+o+" with mapped name: "+i);var d=n._getChildByName(n.rootMesh,s);if(!d)return void l.a.Warn("Missing button mesh with name: "+s);if(a.valueMesh=n._getImmediateChildByName(d,n._mapping.defaultButton.valueNodeName),a.pressedMesh=n._getImmediateChildByName(d,n._mapping.defaultButton.pressedNodeName),a.unpressedMesh=n._getImmediateChildByName(d,n._mapping.defaultButton.unpressedNodeName),a.valueMesh&&a.pressedMesh&&a.unpressedMesh){var p=n.getComponent(i);p&&p.onButtonStateChangedObservable.add(function(b){n._lerpTransform(a,b.value)},void 0,!0)}else l.a.Warn("Missing button submesh under mesh with name: "+s)}}),this.getComponentIds().forEach(function(i,o){var a=n.getComponent(i);a.isAxes()&&["x-axis","y-axis"].forEach(function(s){if(n.rootMesh){var d=n._mapping.axes[i][s],p=n._getChildByName(n.rootMesh,d.rootNodeName);p?(d.valueMesh=n._getImmediateChildByName(p,n._mapping.defaultAxis.valueNodeName),d.minMesh=n._getImmediateChildByName(p,n._mapping.defaultAxis.minNodeName),d.maxMesh=n._getImmediateChildByName(p,n._mapping.defaultAxis.maxNodeName),d.valueMesh&&d.minMesh&&d.maxMesh?a&&a.onAxisValueChangedObservable.add(function(b){var P=s==="x-axis"?b.x:b.y;n._lerpTransform(d,P,!0)},void 0,!0):l.a.Warn("Missing axis submesh under mesh with name: "+d.rootNodeName)):l.a.Warn("Missing axis mesh with name: "+d.rootNodeName)}})}))},t.prototype._setRootMesh=function(e){var n;this.rootMesh=new De.a(this.profileId+" "+this.handedness,this.scene),this.rootMesh.isPickable=!1;for(var i=0;i<e.length;i++){var o=e[i];o.isPickable=!1,o.parent||(n=o)}n&&n.setParent(this.rootMesh),this.scene.useRightHandedSystem||(this.rootMesh.rotationQuaternion=u.b.FromEulerAngles(0,Math.PI,0))},t.prototype._updateModel=function(){},t.MODEL_BASE_URL="https://controllers.babylonjs.com/microsoft/",t.MODEL_LEFT_FILENAME="left.glb",t.MODEL_RIGHT_FILENAME="right.glb",t}(Rr);Bn.RegisterController("windows-mixed-reality",function(r,t){return new vf(t,r.gamepad,r.handedness)});var yv={left:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{xr_standard_trigger_pressed:{componentProperty:"button",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_trigger_pressed_value",minNodeName:"xr_standard_trigger_pressed_min",maxNodeName:"xr_standard_trigger_pressed_max"}}},"xr-standard-squeeze":{type:"squeeze",gamepadIndices:{button:1},rootNodeName:"xr_standard_squeeze",visualResponses:{xr_standard_squeeze_pressed:{componentProperty:"button",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_squeeze_pressed_value",minNodeName:"xr_standard_squeeze_pressed_min",maxNodeName:"xr_standard_squeeze_pressed_max"}}},"xr-standard-touchpad":{type:"touchpad",gamepadIndices:{button:2,xAxis:0,yAxis:1},rootNodeName:"xr_standard_touchpad",visualResponses:{xr_standard_touchpad_pressed:{componentProperty:"button",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_pressed_value",minNodeName:"xr_standard_touchpad_pressed_min",maxNodeName:"xr_standard_touchpad_pressed_max"},xr_standard_touchpad_xaxis_pressed:{componentProperty:"xAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_xaxis_pressed_value",minNodeName:"xr_standard_touchpad_xaxis_pressed_min",maxNodeName:"xr_standard_touchpad_xaxis_pressed_max"},xr_standard_touchpad_yaxis_pressed:{componentProperty:"yAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_yaxis_pressed_value",minNodeName:"xr_standard_touchpad_yaxis_pressed_min",maxNodeName:"xr_standard_touchpad_yaxis_pressed_max"},xr_standard_touchpad_xaxis_touched:{componentProperty:"xAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_xaxis_touched_value",minNodeName:"xr_standard_touchpad_xaxis_touched_min",maxNodeName:"xr_standard_touchpad_xaxis_touched_max"},xr_standard_touchpad_yaxis_touched:{componentProperty:"yAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_yaxis_touched_value",minNodeName:"xr_standard_touchpad_yaxis_touched_min",maxNodeName:"xr_standard_touchpad_yaxis_touched_max"},xr_standard_touchpad_axes_touched:{componentProperty:"state",states:["touched","pressed"],valueNodeProperty:"visibility",valueNodeName:"xr_standard_touchpad_axes_touched_value"}},touchPointNodeName:"xr_standard_touchpad_axes_touched_value"},"xr-standard-thumbstick":{type:"thumbstick",gamepadIndices:{button:3,xAxis:2,yAxis:3},rootNodeName:"xr_standard_thumbstick",visualResponses:{xr_standard_thumbstick_pressed:{componentProperty:"button",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_thumbstick_pressed_value",minNodeName:"xr_standard_thumbstick_pressed_min",maxNodeName:"xr_standard_thumbstick_pressed_max"},xr_standard_thumbstick_xaxis_pressed:{componentProperty:"xAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_thumbstick_xaxis_pressed_value",minNodeName:"xr_standard_thumbstick_xaxis_pressed_min",maxNodeName:"xr_standard_thumbstick_xaxis_pressed_max"},xr_standard_thumbstick_yaxis_pressed:{componentProperty:"yAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_thumbstick_yaxis_pressed_value",minNodeName:"xr_standard_thumbstick_yaxis_pressed_min",maxNodeName:"xr_standard_thumbstick_yaxis_pressed_max"}}}},gamepadMapping:"xr-standard",rootNodeName:"microsoft-mixed-reality-left",assetPath:"left.glb"},right:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{xr_standard_trigger_pressed:{componentProperty:"button",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_trigger_pressed_value",minNodeName:"xr_standard_trigger_pressed_min",maxNodeName:"xr_standard_trigger_pressed_max"}}},"xr-standard-squeeze":{type:"squeeze",gamepadIndices:{button:1},rootNodeName:"xr_standard_squeeze",visualResponses:{xr_standard_squeeze_pressed:{componentProperty:"button",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_squeeze_pressed_value",minNodeName:"xr_standard_squeeze_pressed_min",maxNodeName:"xr_standard_squeeze_pressed_max"}}},"xr-standard-touchpad":{type:"touchpad",gamepadIndices:{button:2,xAxis:0,yAxis:1},rootNodeName:"xr_standard_touchpad",visualResponses:{xr_standard_touchpad_pressed:{componentProperty:"button",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_pressed_value",minNodeName:"xr_standard_touchpad_pressed_min",maxNodeName:"xr_standard_touchpad_pressed_max"},xr_standard_touchpad_xaxis_pressed:{componentProperty:"xAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_xaxis_pressed_value",minNodeName:"xr_standard_touchpad_xaxis_pressed_min",maxNodeName:"xr_standard_touchpad_xaxis_pressed_max"},xr_standard_touchpad_yaxis_pressed:{componentProperty:"yAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_yaxis_pressed_value",minNodeName:"xr_standard_touchpad_yaxis_pressed_min",maxNodeName:"xr_standard_touchpad_yaxis_pressed_max"},xr_standard_touchpad_xaxis_touched:{componentProperty:"xAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_xaxis_touched_value",minNodeName:"xr_standard_touchpad_xaxis_touched_min",maxNodeName:"xr_standard_touchpad_xaxis_touched_max"},xr_standard_touchpad_yaxis_touched:{componentProperty:"yAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_yaxis_touched_value",minNodeName:"xr_standard_touchpad_yaxis_touched_min",maxNodeName:"xr_standard_touchpad_yaxis_touched_max"},xr_standard_touchpad_axes_touched:{componentProperty:"state",states:["touched","pressed"],valueNodeProperty:"visibility",valueNodeName:"xr_standard_touchpad_axes_touched_value"}},touchPointNodeName:"xr_standard_touchpad_axes_touched_value"},"xr-standard-thumbstick":{type:"thumbstick",gamepadIndices:{button:3,xAxis:2,yAxis:3},rootNodeName:"xr_standard_thumbstick",visualResponses:{xr_standard_thumbstick_pressed:{componentProperty:"button",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_thumbstick_pressed_value",minNodeName:"xr_standard_thumbstick_pressed_min",maxNodeName:"xr_standard_thumbstick_pressed_max"},xr_standard_thumbstick_xaxis_pressed:{componentProperty:"xAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_thumbstick_xaxis_pressed_value",minNodeName:"xr_standard_thumbstick_xaxis_pressed_min",maxNodeName:"xr_standard_thumbstick_xaxis_pressed_max"},xr_standard_thumbstick_yaxis_pressed:{componentProperty:"yAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_thumbstick_yaxis_pressed_value",minNodeName:"xr_standard_thumbstick_yaxis_pressed_min",maxNodeName:"xr_standard_thumbstick_yaxis_pressed_max"}}}},gamepadMapping:"xr-standard",rootNodeName:"microsoft-mixed-reality-right",assetPath:"right.glb"}},$c=function(r){function t(e,n,i,o,a){a===void 0&&(a=!1);var s=r.call(this,e,Tv[i],n,i)||this;return s._forceLegacyControllers=a,s.profileId="oculus-touch",s}return Object(c.d)(t,r),t.prototype._getFilenameAndPath=function(){return{filename:this.handedness==="left"?t.MODEL_LEFT_FILENAME:t.MODEL_RIGHT_FILENAME,path:this._isQuest()?t.QUEST_MODEL_BASE_URL:t.MODEL_BASE_URL}},t.prototype._getModelLoadingConstraints=function(){return!0},t.prototype._processLoadedModel=function(e){var n=this,i=this._isQuest(),o=this.handedness==="right"?-1:1;this.getComponentIds().forEach(function(a){var s=a&&n.getComponent(a);s&&s.onButtonStateChangedObservable.add(function(d){if(n.rootMesh&&!n.disableAnimation)switch(a){case"xr-standard-trigger":return void(i||(n._modelRootNode.getChildren()[3].rotation.x=.2*-d.value,n._modelRootNode.getChildren()[3].position.y=.005*-d.value,n._modelRootNode.getChildren()[3].position.z=.005*-d.value));case"xr-standard-squeeze":return void(i||(n._modelRootNode.getChildren()[4].position.x=o*d.value*.0035));case"xr-standard-thumbstick":return;case"a-button":case"x-button":return void(i||(d.pressed?n._modelRootNode.getChildren()[1].position.y=-.001:n._modelRootNode.getChildren()[1].position.y=0));case"b-button":case"y-button":return void(i||(d.pressed?n._modelRootNode.getChildren()[2].position.y=-.001:n._modelRootNode.getChildren()[2].position.y=0))}},void 0,!0)})},t.prototype._setRootMesh=function(e){this.rootMesh=new De.a(this.profileId+" "+this.handedness,this.scene),this.scene.useRightHandedSystem||(this.rootMesh.rotationQuaternion=u.b.FromEulerAngles(0,Math.PI,0)),e.forEach(function(n){n.isPickable=!1}),this._isQuest()?this._modelRootNode=e[0]:(this._modelRootNode=e[1],this.rootMesh.position.y=.034,this.rootMesh.position.z=.052),this._modelRootNode.parent=this.rootMesh},t.prototype._updateModel=function(){},t.prototype._isQuest=function(){return!!navigator.userAgent.match(/Quest/gi)&&!this._forceLegacyControllers},t.MODEL_BASE_URL="https://controllers.babylonjs.com/oculus/",t.MODEL_LEFT_FILENAME="left.babylon",t.MODEL_RIGHT_FILENAME="right.babylon",t.QUEST_MODEL_BASE_URL="https://controllers.babylonjs.com/oculusQuest/",t}(Rr);Bn.RegisterController("oculus-touch",function(r,t){return new $c(t,r.gamepad,r.handedness)}),Bn.RegisterController("oculus-touch-legacy",function(r,t){return new $c(t,r.gamepad,r.handedness,!0)});var Tv={left:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{}},"xr-standard-squeeze":{type:"squeeze",gamepadIndices:{button:1},rootNodeName:"xr_standard_squeeze",visualResponses:{}},"xr-standard-thumbstick":{type:"thumbstick",gamepadIndices:{button:3,xAxis:2,yAxis:3},rootNodeName:"xr_standard_thumbstick",visualResponses:{}},"x-button":{type:"button",gamepadIndices:{button:4},rootNodeName:"x_button",visualResponses:{}},"y-button":{type:"button",gamepadIndices:{button:5},rootNodeName:"y_button",visualResponses:{}},thumbrest:{type:"button",gamepadIndices:{button:6},rootNodeName:"thumbrest",visualResponses:{}}},gamepadMapping:"xr-standard",rootNodeName:"oculus-touch-v2-left",assetPath:"left.glb"},right:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{}},"xr-standard-squeeze":{type:"squeeze",gamepadIndices:{button:1},rootNodeName:"xr_standard_squeeze",visualResponses:{}},"xr-standard-thumbstick":{type:"thumbstick",gamepadIndices:{button:3,xAxis:2,yAxis:3},rootNodeName:"xr_standard_thumbstick",visualResponses:{}},"a-button":{type:"button",gamepadIndices:{button:4},rootNodeName:"a_button",visualResponses:{}},"b-button":{type:"button",gamepadIndices:{button:5},rootNodeName:"b_button",visualResponses:{}},thumbrest:{type:"button",gamepadIndices:{button:6},rootNodeName:"thumbrest",visualResponses:{}}},gamepadMapping:"xr-standard",rootNodeName:"oculus-touch-v2-right",assetPath:"right.glb"}},bf=function(r){function t(e,n,i){var o=r.call(this,e,Ev[i],n,i)||this;return o.profileId="htc-vive",o}return Object(c.d)(t,r),t.prototype._getFilenameAndPath=function(){return{filename:t.MODEL_FILENAME,path:t.MODEL_BASE_URL}},t.prototype._getModelLoadingConstraints=function(){return!0},t.prototype._processLoadedModel=function(e){var n=this;this.getComponentIds().forEach(function(i){var o=i&&n.getComponent(i);o&&o.onButtonStateChangedObservable.add(function(a){if(n.rootMesh&&!n.disableAnimation)switch(i){case"xr-standard-trigger":return void(n._modelRootNode.getChildren()[6].rotation.x=.15*-a.value);case"xr-standard-touchpad":case"xr-standard-squeeze":return}},void 0,!0)})},t.prototype._setRootMesh=function(e){this.rootMesh=new De.a(this.profileId+" "+this.handedness,this.scene),e.forEach(function(n){n.isPickable=!1}),this._modelRootNode=e[1],this._modelRootNode.parent=this.rootMesh,this.scene.useRightHandedSystem||(this.rootMesh.rotationQuaternion=u.b.FromEulerAngles(0,Math.PI,0))},t.prototype._updateModel=function(){},t.MODEL_BASE_URL="https://controllers.babylonjs.com/vive/",t.MODEL_FILENAME="wand.babylon",t}(Rr);Bn.RegisterController("htc-vive",function(r,t){return new bf(t,r.gamepad,r.handedness)});var Ev={left:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{}},"xr-standard-squeeze":{type:"squeeze",gamepadIndices:{button:1},rootNodeName:"xr_standard_squeeze",visualResponses:{}},"xr-standard-touchpad":{type:"touchpad",gamepadIndices:{button:2,xAxis:0,yAxis:1},rootNodeName:"xr_standard_touchpad",visualResponses:{}},menu:{type:"button",gamepadIndices:{button:4},rootNodeName:"menu",visualResponses:{}}},gamepadMapping:"xr-standard",rootNodeName:"htc_vive_none",assetPath:"none.glb"},right:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{}},"xr-standard-squeeze":{type:"squeeze",gamepadIndices:{button:1},rootNodeName:"xr_standard_squeeze",visualResponses:{}},"xr-standard-touchpad":{type:"touchpad",gamepadIndices:{button:2,xAxis:0,yAxis:1},rootNodeName:"xr_standard_touchpad",visualResponses:{}},menu:{type:"button",gamepadIndices:{button:4},rootNodeName:"menu",visualResponses:{}}},gamepadMapping:"xr-standard",rootNodeName:"htc_vive_none",assetPath:"none.glb"},none:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{}},"xr-standard-squeeze":{type:"squeeze",gamepadIndices:{button:1},rootNodeName:"xr_standard_squeeze",visualResponses:{}},"xr-standard-touchpad":{type:"touchpad",gamepadIndices:{button:2,xAxis:0,yAxis:1},rootNodeName:"xr_standard_touchpad",visualResponses:{}},menu:{type:"button",gamepadIndices:{button:4},rootNodeName:"menu",visualResponses:{}}},gamepadMapping:"xr-standard",rootNodeName:"htc-vive-none",assetPath:"none.glb"}}},function(Me,y,f){f.d(y,"a",function(){return 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-#ifndef SHADOWFLOAT
-
-float unpack(vec4 color)
-{
-const vec4 bit_shift=vec4(1.0/(255.0*255.0*255.0),1.0/(255.0*255.0),1.0/255.0,1.0);
-return dot(color,bit_shift);
-}
-#endif
-float computeFallOff(float value,vec2 clipSpace,float frustumEdgeFalloff)
-{
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-return mix(value,1.0,mask);
-}
-#define inline
-float computeShadowCube(vec3 lightPosition,samplerCube shadowSampler,float darkness,vec2 depthValues)
-{
-vec3 directionToLight=vPositionW-lightPosition;
-float depth=length(directionToLight);
-depth=(depth+depthValues.x)/(depthValues.y);
-depth=clamp(depth,0.,1.0);
-directionToLight=normalize(directionToLight);
-directionToLight.y=-directionToLight.y;
-#ifndef SHADOWFLOAT
-float shadow=unpack(textureCube(shadowSampler,directionToLight));
-#else
-float shadow=textureCube(shadowSampler,directionToLight).x;
-#endif
-return depth>shadow ? darkness : 1.0;
-}
-#define inline
-float computeShadowWithPoissonSamplingCube(vec3 lightPosition,samplerCube shadowSampler,float mapSize,float darkness,vec2 depthValues)
-{
-vec3 directionToLight=vPositionW-lightPosition;
-float depth=length(directionToLight);
-depth=(depth+depthValues.x)/(depthValues.y);
-depth=clamp(depth,0.,1.0);
-directionToLight=normalize(directionToLight);
-directionToLight.y=-directionToLight.y;
-float visibility=1.;
-vec3 poissonDisk[4];
-poissonDisk[0]=vec3(-1.0,1.0,-1.0);
-poissonDisk[1]=vec3(1.0,-1.0,-1.0);
-poissonDisk[2]=vec3(-1.0,-1.0,-1.0);
-poissonDisk[3]=vec3(1.0,-1.0,1.0);
-
-#ifndef SHADOWFLOAT
-if (unpack(textureCube(shadowSampler,directionToLight+poissonDisk[0]*mapSize))<depth) visibility-=0.25;
-if (unpack(textureCube(shadowSampler,directionToLight+poissonDisk[1]*mapSize))<depth) visibility-=0.25;
-if (unpack(textureCube(shadowSampler,directionToLight+poissonDisk[2]*mapSize))<depth) visibility-=0.25;
-if (unpack(textureCube(shadowSampler,directionToLight+poissonDisk[3]*mapSize))<depth) visibility-=0.25;
-#else
-if (textureCube(shadowSampler,directionToLight+poissonDisk[0]*mapSize).x<depth) visibility-=0.25;
-if (textureCube(shadowSampler,directionToLight+poissonDisk[1]*mapSize).x<depth) visibility-=0.25;
-if (textureCube(shadowSampler,directionToLight+poissonDisk[2]*mapSize).x<depth) visibility-=0.25;
-if (textureCube(shadowSampler,directionToLight+poissonDisk[3]*mapSize).x<depth) visibility-=0.25;
-#endif
-return min(1.0,visibility+darkness);
-}
-#define inline
-float computeShadowWithESMCube(vec3 lightPosition,samplerCube shadowSampler,float darkness,float depthScale,vec2 depthValues)
-{
-vec3 directionToLight=vPositionW-lightPosition;
-float depth=length(directionToLight);
-depth=(depth+depthValues.x)/(depthValues.y);
-float shadowPixelDepth=clamp(depth,0.,1.0);
-directionToLight=normalize(directionToLight);
-directionToLight.y=-directionToLight.y;
-#ifndef SHADOWFLOAT
-float shadowMapSample=unpack(textureCube(shadowSampler,directionToLight));
-#else
-float shadowMapSample=textureCube(shadowSampler,directionToLight).x;
-#endif
-float esm=1.0-clamp(exp(min(87.,depthScale*shadowPixelDepth))*shadowMapSample,0.,1.-darkness);
-return esm;
-}
-#define inline
-float computeShadowWithCloseESMCube(vec3 lightPosition,samplerCube shadowSampler,float darkness,float depthScale,vec2 depthValues)
-{
-vec3 directionToLight=vPositionW-lightPosition;
-float depth=length(directionToLight);
-depth=(depth+depthValues.x)/(depthValues.y);
-float shadowPixelDepth=clamp(depth,0.,1.0);
-directionToLight=normalize(directionToLight);
-directionToLight.y=-directionToLight.y;
-#ifndef SHADOWFLOAT
-float shadowMapSample=unpack(textureCube(shadowSampler,directionToLight));
-#else
-float shadowMapSample=textureCube(shadowSampler,directionToLight).x;
-#endif
-float esm=clamp(exp(min(87.,-depthScale*(shadowPixelDepth-shadowMapSample))),darkness,1.);
-return esm;
-}
-#ifdef WEBGL2
-#define inline
-float computeShadowCSM(float layer,vec4 vPositionFromLight,float depthMetric,highp sampler2DArray shadowSampler,float darkness,float frustumEdgeFalloff)
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec2 uv=0.5*clipSpace.xy+vec2(0.5);
-vec3 uvLayer=vec3(uv.x,uv.y,layer);
-float shadowPixelDepth=clamp(depthMetric,0.,1.0);
-#ifndef SHADOWFLOAT
-float shadow=unpack(texture2D(shadowSampler,uvLayer));
-#else
-float shadow=texture2D(shadowSampler,uvLayer).x;
-#endif
-return shadowPixelDepth>shadow ? computeFallOff(darkness,clipSpace.xy,frustumEdgeFalloff) : 1.;
-}
-#endif
-#define inline
-float computeShadow(vec4 vPositionFromLight,float depthMetric,sampler2D shadowSampler,float darkness,float frustumEdgeFalloff)
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec2 uv=0.5*clipSpace.xy+vec2(0.5);
-if (uv.x<0. || uv.x>1.0 || uv.y<0. || uv.y>1.0)
-{
-return 1.0;
-}
-else
-{
-float shadowPixelDepth=clamp(depthMetric,0.,1.0);
-#ifndef SHADOWFLOAT
-float shadow=unpack(texture2D(shadowSampler,uv));
-#else
-float shadow=texture2D(shadowSampler,uv).x;
-#endif
-return shadowPixelDepth>shadow ? computeFallOff(darkness,clipSpace.xy,frustumEdgeFalloff) : 1.;
-}
-}
-#define inline
-float computeShadowWithPoissonSampling(vec4 vPositionFromLight,float depthMetric,sampler2D shadowSampler,float mapSize,float darkness,float frustumEdgeFalloff)
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec2 uv=0.5*clipSpace.xy+vec2(0.5);
-if (uv.x<0. || uv.x>1.0 || uv.y<0. || uv.y>1.0)
-{
-return 1.0;
-}
-else
-{
-float shadowPixelDepth=clamp(depthMetric,0.,1.0);
-float visibility=1.;
-vec2 poissonDisk[4];
-poissonDisk[0]=vec2(-0.94201624,-0.39906216);
-poissonDisk[1]=vec2(0.94558609,-0.76890725);
-poissonDisk[2]=vec2(-0.094184101,-0.92938870);
-poissonDisk[3]=vec2(0.34495938,0.29387760);
-
-#ifndef SHADOWFLOAT
-if (unpack(texture2D(shadowSampler,uv+poissonDisk[0]*mapSize))<shadowPixelDepth) visibility-=0.25;
-if (unpack(texture2D(shadowSampler,uv+poissonDisk[1]*mapSize))<shadowPixelDepth) visibility-=0.25;
-if (unpack(texture2D(shadowSampler,uv+poissonDisk[2]*mapSize))<shadowPixelDepth) visibility-=0.25;
-if (unpack(texture2D(shadowSampler,uv+poissonDisk[3]*mapSize))<shadowPixelDepth) visibility-=0.25;
-#else
-if (texture2D(shadowSampler,uv+poissonDisk[0]*mapSize).x<shadowPixelDepth) visibility-=0.25;
-if (texture2D(shadowSampler,uv+poissonDisk[1]*mapSize).x<shadowPixelDepth) visibility-=0.25;
-if (texture2D(shadowSampler,uv+poissonDisk[2]*mapSize).x<shadowPixelDepth) visibility-=0.25;
-if (texture2D(shadowSampler,uv+poissonDisk[3]*mapSize).x<shadowPixelDepth) visibility-=0.25;
-#endif
-return computeFallOff(min(1.0,visibility+darkness),clipSpace.xy,frustumEdgeFalloff);
-}
-}
-#define inline
-float computeShadowWithESM(vec4 vPositionFromLight,float depthMetric,sampler2D shadowSampler,float darkness,float depthScale,float frustumEdgeFalloff)
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec2 uv=0.5*clipSpace.xy+vec2(0.5);
-if (uv.x<0. || uv.x>1.0 || uv.y<0. || uv.y>1.0)
-{
-return 1.0;
-}
-else
-{
-float shadowPixelDepth=clamp(depthMetric,0.,1.0);
-#ifndef SHADOWFLOAT
-float shadowMapSample=unpack(texture2D(shadowSampler,uv));
-#else
-float shadowMapSample=texture2D(shadowSampler,uv).x;
-#endif
-float esm=1.0-clamp(exp(min(87.,depthScale*shadowPixelDepth))*shadowMapSample,0.,1.-darkness);
-return computeFallOff(esm,clipSpace.xy,frustumEdgeFalloff);
-}
-}
-#define inline
-float computeShadowWithCloseESM(vec4 vPositionFromLight,float depthMetric,sampler2D shadowSampler,float darkness,float depthScale,float frustumEdgeFalloff)
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec2 uv=0.5*clipSpace.xy+vec2(0.5);
-if (uv.x<0. || uv.x>1.0 || uv.y<0. || uv.y>1.0)
-{
-return 1.0;
-}
-else
-{
-float shadowPixelDepth=clamp(depthMetric,0.,1.0);
-#ifndef SHADOWFLOAT
-float shadowMapSample=unpack(texture2D(shadowSampler,uv));
-#else
-float shadowMapSample=texture2D(shadowSampler,uv).x;
-#endif
-float esm=clamp(exp(min(87.,-depthScale*(shadowPixelDepth-shadowMapSample))),darkness,1.);
-return computeFallOff(esm,clipSpace.xy,frustumEdgeFalloff);
-}
-}
-#ifdef WEBGL2
-#define GREATEST_LESS_THAN_ONE 0.99999994
-
-#define inline
-float computeShadowWithCSMPCF1(float layer,vec4 vPositionFromLight,float depthMetric,highp sampler2DArrayShadow shadowSampler,float darkness,float frustumEdgeFalloff)
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec3 uvDepth=vec3(0.5*clipSpace.xyz+vec3(0.5));
-uvDepth.z=clamp(uvDepth.z,0.,GREATEST_LESS_THAN_ONE);
-vec4 uvDepthLayer=vec4(uvDepth.x,uvDepth.y,layer,uvDepth.z);
-float shadow=texture(shadowSampler,uvDepthLayer);
-shadow=mix(darkness,1.,shadow);
-return computeFallOff(shadow,clipSpace.xy,frustumEdgeFalloff);
-}
-
-
-
-#define inline
-float computeShadowWithCSMPCF3(float layer,vec4 vPositionFromLight,float depthMetric,highp sampler2DArrayShadow shadowSampler,vec2 shadowMapSizeAndInverse,float darkness,float frustumEdgeFalloff)
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec3 uvDepth=vec3(0.5*clipSpace.xyz+vec3(0.5));
-uvDepth.z=clamp(uvDepth.z,0.,GREATEST_LESS_THAN_ONE);
-vec2 uv=uvDepth.xy*shadowMapSizeAndInverse.x;
-uv+=0.5;
-vec2 st=fract(uv);
-vec2 base_uv=floor(uv)-0.5;
-base_uv*=shadowMapSizeAndInverse.y;
-
-
-
-
-vec2 uvw0=3.-2.*st;
-vec2 uvw1=1.+2.*st;
-vec2 u=vec2((2.-st.x)/uvw0.x-1.,st.x/uvw1.x+1.)*shadowMapSizeAndInverse.y;
-vec2 v=vec2((2.-st.y)/uvw0.y-1.,st.y/uvw1.y+1.)*shadowMapSizeAndInverse.y;
-float shadow=0.;
-shadow+=uvw0.x*uvw0.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[0],v[0]),layer,uvDepth.z));
-shadow+=uvw1.x*uvw0.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[1],v[0]),layer,uvDepth.z));
-shadow+=uvw0.x*uvw1.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[0],v[1]),layer,uvDepth.z));
-shadow+=uvw1.x*uvw1.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[1],v[1]),layer,uvDepth.z));
-shadow=shadow/16.;
-shadow=mix(darkness,1.,shadow);
-return computeFallOff(shadow,clipSpace.xy,frustumEdgeFalloff);
-}
-
-
-
-#define inline
-float computeShadowWithCSMPCF5(float layer,vec4 vPositionFromLight,float depthMetric,highp sampler2DArrayShadow shadowSampler,vec2 shadowMapSizeAndInverse,float darkness,float frustumEdgeFalloff)
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec3 uvDepth=vec3(0.5*clipSpace.xyz+vec3(0.5));
-uvDepth.z=clamp(uvDepth.z,0.,GREATEST_LESS_THAN_ONE);
-vec2 uv=uvDepth.xy*shadowMapSizeAndInverse.x;
-uv+=0.5;
-vec2 st=fract(uv);
-vec2 base_uv=floor(uv)-0.5;
-base_uv*=shadowMapSizeAndInverse.y;
-
-
-vec2 uvw0=4.-3.*st;
-vec2 uvw1=vec2(7.);
-vec2 uvw2=1.+3.*st;
-vec3 u=vec3((3.-2.*st.x)/uvw0.x-2.,(3.+st.x)/uvw1.x,st.x/uvw2.x+2.)*shadowMapSizeAndInverse.y;
-vec3 v=vec3((3.-2.*st.y)/uvw0.y-2.,(3.+st.y)/uvw1.y,st.y/uvw2.y+2.)*shadowMapSizeAndInverse.y;
-float shadow=0.;
-shadow+=uvw0.x*uvw0.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[0],v[0]),layer,uvDepth.z));
-shadow+=uvw1.x*uvw0.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[1],v[0]),layer,uvDepth.z));
-shadow+=uvw2.x*uvw0.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[2],v[0]),layer,uvDepth.z));
-shadow+=uvw0.x*uvw1.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[0],v[1]),layer,uvDepth.z));
-shadow+=uvw1.x*uvw1.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[1],v[1]),layer,uvDepth.z));
-shadow+=uvw2.x*uvw1.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[2],v[1]),layer,uvDepth.z));
-shadow+=uvw0.x*uvw2.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[0],v[2]),layer,uvDepth.z));
-shadow+=uvw1.x*uvw2.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[1],v[2]),layer,uvDepth.z));
-shadow+=uvw2.x*uvw2.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[2],v[2]),layer,uvDepth.z));
-shadow=shadow/144.;
-shadow=mix(darkness,1.,shadow);
-return computeFallOff(shadow,clipSpace.xy,frustumEdgeFalloff);
-}
-
-#define inline
-float computeShadowWithPCF1(vec4 vPositionFromLight,float depthMetric,highp sampler2DShadow shadowSampler,float darkness,float frustumEdgeFalloff)
-{
-if (depthMetric>1.0 || depthMetric<0.0) {
-return 1.0;
-}
-else
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec3 uvDepth=vec3(0.5*clipSpace.xyz+vec3(0.5));
-float shadow=texture2D(shadowSampler,uvDepth);
-shadow=mix(darkness,1.,shadow);
-return computeFallOff(shadow,clipSpace.xy,frustumEdgeFalloff);
-}
-}
-
-
-
-#define inline
-float computeShadowWithPCF3(vec4 vPositionFromLight,float depthMetric,highp sampler2DShadow shadowSampler,vec2 shadowMapSizeAndInverse,float darkness,float frustumEdgeFalloff)
-{
-if (depthMetric>1.0 || depthMetric<0.0) {
-return 1.0;
-}
-else
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec3 uvDepth=vec3(0.5*clipSpace.xyz+vec3(0.5));
-vec2 uv=uvDepth.xy*shadowMapSizeAndInverse.x;
-uv+=0.5;
-vec2 st=fract(uv);
-vec2 base_uv=floor(uv)-0.5;
-base_uv*=shadowMapSizeAndInverse.y;
-
-
-
-
-vec2 uvw0=3.-2.*st;
-vec2 uvw1=1.+2.*st;
-vec2 u=vec2((2.-st.x)/uvw0.x-1.,st.x/uvw1.x+1.)*shadowMapSizeAndInverse.y;
-vec2 v=vec2((2.-st.y)/uvw0.y-1.,st.y/uvw1.y+1.)*shadowMapSizeAndInverse.y;
-float shadow=0.;
-shadow+=uvw0.x*uvw0.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[0],v[0]),uvDepth.z));
-shadow+=uvw1.x*uvw0.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[1],v[0]),uvDepth.z));
-shadow+=uvw0.x*uvw1.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[0],v[1]),uvDepth.z));
-shadow+=uvw1.x*uvw1.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[1],v[1]),uvDepth.z));
-shadow=shadow/16.;
-shadow=mix(darkness,1.,shadow);
-return computeFallOff(shadow,clipSpace.xy,frustumEdgeFalloff);
-}
-}
-
-
-
-#define inline
-float computeShadowWithPCF5(vec4 vPositionFromLight,float depthMetric,highp sampler2DShadow shadowSampler,vec2 shadowMapSizeAndInverse,float darkness,float frustumEdgeFalloff)
-{
-if (depthMetric>1.0 || depthMetric<0.0) {
-return 1.0;
-}
-else
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec3 uvDepth=vec3(0.5*clipSpace.xyz+vec3(0.5));
-vec2 uv=uvDepth.xy*shadowMapSizeAndInverse.x;
-uv+=0.5;
-vec2 st=fract(uv);
-vec2 base_uv=floor(uv)-0.5;
-base_uv*=shadowMapSizeAndInverse.y;
-
-
-vec2 uvw0=4.-3.*st;
-vec2 uvw1=vec2(7.);
-vec2 uvw2=1.+3.*st;
-vec3 u=vec3((3.-2.*st.x)/uvw0.x-2.,(3.+st.x)/uvw1.x,st.x/uvw2.x+2.)*shadowMapSizeAndInverse.y;
-vec3 v=vec3((3.-2.*st.y)/uvw0.y-2.,(3.+st.y)/uvw1.y,st.y/uvw2.y+2.)*shadowMapSizeAndInverse.y;
-float shadow=0.;
-shadow+=uvw0.x*uvw0.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[0],v[0]),uvDepth.z));
-shadow+=uvw1.x*uvw0.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[1],v[0]),uvDepth.z));
-shadow+=uvw2.x*uvw0.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[2],v[0]),uvDepth.z));
-shadow+=uvw0.x*uvw1.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[0],v[1]),uvDepth.z));
-shadow+=uvw1.x*uvw1.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[1],v[1]),uvDepth.z));
-shadow+=uvw2.x*uvw1.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[2],v[1]),uvDepth.z));
-shadow+=uvw0.x*uvw2.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[0],v[2]),uvDepth.z));
-shadow+=uvw1.x*uvw2.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[1],v[2]),uvDepth.z));
-shadow+=uvw2.x*uvw2.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[2],v[2]),uvDepth.z));
-shadow=shadow/144.;
-shadow=mix(darkness,1.,shadow);
-return computeFallOff(shadow,clipSpace.xy,frustumEdgeFalloff);
-}
-}
-const vec3 PoissonSamplers32[64]=vec3[64](
-vec3(0.06407013,0.05409927,0.),
-vec3(0.7366577,0.5789394,0.),
-vec3(-0.6270542,-0.5320278,0.),
-vec3(-0.4096107,0.8411095,0.),
-vec3(0.6849564,-0.4990818,0.),
-vec3(-0.874181,-0.04579735,0.),
-vec3(0.9989998,0.0009880066,0.),
-vec3(-0.004920578,-0.9151649,0.),
-vec3(0.1805763,0.9747483,0.),
-vec3(-0.2138451,0.2635818,0.),
-vec3(0.109845,0.3884785,0.),
-vec3(0.06876755,-0.3581074,0.),
-vec3(0.374073,-0.7661266,0.),
-vec3(0.3079132,-0.1216763,0.),
-vec3(-0.3794335,-0.8271583,0.),
-vec3(-0.203878,-0.07715034,0.),
-vec3(0.5912697,0.1469799,0.),
-vec3(-0.88069,0.3031784,0.),
-vec3(0.5040108,0.8283722,0.),
-vec3(-0.5844124,0.5494877,0.),
-vec3(0.6017799,-0.1726654,0.),
-vec3(-0.5554981,0.1559997,0.),
-vec3(-0.3016369,-0.3900928,0.),
-vec3(-0.5550632,-0.1723762,0.),
-vec3(0.925029,0.2995041,0.),
-vec3(-0.2473137,0.5538505,0.),
-vec3(0.9183037,-0.2862392,0.),
-vec3(0.2469421,0.6718712,0.),
-vec3(0.3916397,-0.4328209,0.),
-vec3(-0.03576927,-0.6220032,0.),
-vec3(-0.04661255,0.7995201,0.),
-vec3(0.4402924,0.3640312,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.)
-);
-const vec3 PoissonSamplers64[64]=vec3[64](
-vec3(-0.613392,0.617481,0.),
-vec3(0.170019,-0.040254,0.),
-vec3(-0.299417,0.791925,0.),
-vec3(0.645680,0.493210,0.),
-vec3(-0.651784,0.717887,0.),
-vec3(0.421003,0.027070,0.),
-vec3(-0.817194,-0.271096,0.),
-vec3(-0.705374,-0.668203,0.),
-vec3(0.977050,-0.108615,0.),
-vec3(0.063326,0.142369,0.),
-vec3(0.203528,0.214331,0.),
-vec3(-0.667531,0.326090,0.),
-vec3(-0.098422,-0.295755,0.),
-vec3(-0.885922,0.215369,0.),
-vec3(0.566637,0.605213,0.),
-vec3(0.039766,-0.396100,0.),
-vec3(0.751946,0.453352,0.),
-vec3(0.078707,-0.715323,0.),
-vec3(-0.075838,-0.529344,0.),
-vec3(0.724479,-0.580798,0.),
-vec3(0.222999,-0.215125,0.),
-vec3(-0.467574,-0.405438,0.),
-vec3(-0.248268,-0.814753,0.),
-vec3(0.354411,-0.887570,0.),
-vec3(0.175817,0.382366,0.),
-vec3(0.487472,-0.063082,0.),
-vec3(-0.084078,0.898312,0.),
-vec3(0.488876,-0.783441,0.),
-vec3(0.470016,0.217933,0.),
-vec3(-0.696890,-0.549791,0.),
-vec3(-0.149693,0.605762,0.),
-vec3(0.034211,0.979980,0.),
-vec3(0.503098,-0.308878,0.),
-vec3(-0.016205,-0.872921,0.),
-vec3(0.385784,-0.393902,0.),
-vec3(-0.146886,-0.859249,0.),
-vec3(0.643361,0.164098,0.),
-vec3(0.634388,-0.049471,0.),
-vec3(-0.688894,0.007843,0.),
-vec3(0.464034,-0.188818,0.),
-vec3(-0.440840,0.137486,0.),
-vec3(0.364483,0.511704,0.),
-vec3(0.034028,0.325968,0.),
-vec3(0.099094,-0.308023,0.),
-vec3(0.693960,-0.366253,0.),
-vec3(0.678884,-0.204688,0.),
-vec3(0.001801,0.780328,0.),
-vec3(0.145177,-0.898984,0.),
-vec3(0.062655,-0.611866,0.),
-vec3(0.315226,-0.604297,0.),
-vec3(-0.780145,0.486251,0.),
-vec3(-0.371868,0.882138,0.),
-vec3(0.200476,0.494430,0.),
-vec3(-0.494552,-0.711051,0.),
-vec3(0.612476,0.705252,0.),
-vec3(-0.578845,-0.768792,0.),
-vec3(-0.772454,-0.090976,0.),
-vec3(0.504440,0.372295,0.),
-vec3(0.155736,0.065157,0.),
-vec3(0.391522,0.849605,0.),
-vec3(-0.620106,-0.328104,0.),
-vec3(0.789239,-0.419965,0.),
-vec3(-0.545396,0.538133,0.),
-vec3(-0.178564,-0.596057,0.)
-);
-
-
-
-
-
-#define inline
-float computeShadowWithCSMPCSS(float layer,vec4 vPositionFromLight,float depthMetric,highp sampler2DArray depthSampler,highp sampler2DArrayShadow shadowSampler,float shadowMapSizeInverse,float lightSizeUV,float darkness,float frustumEdgeFalloff,int searchTapCount,int pcfTapCount,vec3[64] poissonSamplers,vec2 lightSizeUVCorrection,float depthCorrection,float penumbraDarkness)
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec3 uvDepth=vec3(0.5*clipSpace.xyz+vec3(0.5));
-uvDepth.z=clamp(uvDepth.z,0.,GREATEST_LESS_THAN_ONE);
-vec4 uvDepthLayer=vec4(uvDepth.x,uvDepth.y,layer,uvDepth.z);
-float blockerDepth=0.0;
-float sumBlockerDepth=0.0;
-float numBlocker=0.0;
-for (int i=0; i<searchTapCount; i ++) {
-blockerDepth=texture(depthSampler,vec3(uvDepth.xy+(lightSizeUV*lightSizeUVCorrection*shadowMapSizeInverse*PoissonSamplers32[i].xy),layer)).r;
-if (blockerDepth<depthMetric) {
-sumBlockerDepth+=blockerDepth;
-numBlocker++;
-}
-}
-if (numBlocker<1.0) {
-return 1.0;
-}
-else
-{
-float avgBlockerDepth=sumBlockerDepth/numBlocker;
-
-float AAOffset=shadowMapSizeInverse*10.;
-
-
-float penumbraRatio=((depthMetric-avgBlockerDepth)*depthCorrection+AAOffset);
-vec4 filterRadius=vec4(penumbraRatio*lightSizeUV*lightSizeUVCorrection*shadowMapSizeInverse,0.,0.);
-float random=getRand(vPositionFromLight.xy);
-float rotationAngle=random*3.1415926;
-vec2 rotationVector=vec2(cos(rotationAngle),sin(rotationAngle));
-float shadow=0.;
-for (int i=0; i<pcfTapCount; i++) {
-vec4 offset=vec4(poissonSamplers[i],0.);
-
-offset=vec4(offset.x*rotationVector.x-offset.y*rotationVector.y,offset.y*rotationVector.x+offset.x*rotationVector.y,0.,0.);
-shadow+=texture2D(shadowSampler,uvDepthLayer+offset*filterRadius);
-}
-shadow/=float(pcfTapCount);
-
-shadow=mix(shadow,1.,min((depthMetric-avgBlockerDepth)*depthCorrection*penumbraDarkness,1.));
-
-shadow=mix(darkness,1.,shadow);
-
-return computeFallOff(shadow,clipSpace.xy,frustumEdgeFalloff);
-}
-}
-
-
-
-
-
-#define inline
-float computeShadowWithPCSS(vec4 vPositionFromLight,float depthMetric,sampler2D depthSampler,highp sampler2DShadow shadowSampler,float shadowMapSizeInverse,float lightSizeUV,float darkness,float frustumEdgeFalloff,int searchTapCount,int pcfTapCount,vec3[64] poissonSamplers)
-{
-if (depthMetric>1.0 || depthMetric<0.0) {
-return 1.0;
-}
-else
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec3 uvDepth=vec3(0.5*clipSpace.xyz+vec3(0.5));
-float blockerDepth=0.0;
-float sumBlockerDepth=0.0;
-float numBlocker=0.0;
-for (int i=0; i<searchTapCount; i ++) {
-blockerDepth=texture(depthSampler,uvDepth.xy+(lightSizeUV*shadowMapSizeInverse*PoissonSamplers32[i].xy)).r;
-if (blockerDepth<depthMetric) {
-sumBlockerDepth+=blockerDepth;
-numBlocker++;
-}
-}
-if (numBlocker<1.0) {
-return 1.0;
-}
-else
-{
-float avgBlockerDepth=sumBlockerDepth/numBlocker;
-
-float AAOffset=shadowMapSizeInverse*10.;
-
-
-float penumbraRatio=((depthMetric-avgBlockerDepth)+AAOffset);
-float filterRadius=penumbraRatio*lightSizeUV*shadowMapSizeInverse;
-float random=getRand(vPositionFromLight.xy);
-float rotationAngle=random*3.1415926;
-vec2 rotationVector=vec2(cos(rotationAngle),sin(rotationAngle));
-float shadow=0.;
-for (int i=0; i<pcfTapCount; i++) {
-vec3 offset=poissonSamplers[i];
-
-offset=vec3(offset.x*rotationVector.x-offset.y*rotationVector.y,offset.y*rotationVector.x+offset.x*rotationVector.y,0.);
-shadow+=texture2D(shadowSampler,uvDepth+offset*filterRadius);
-}
-shadow/=float(pcfTapCount);
-
-shadow=mix(shadow,1.,depthMetric-avgBlockerDepth);
-
-shadow=mix(darkness,1.,shadow);
-
-return computeFallOff(shadow,clipSpace.xy,frustumEdgeFalloff);
-}
-}
-}
-#define inline
-float computeShadowWithPCSS16(vec4 vPositionFromLight,float depthMetric,sampler2D depthSampler,highp sampler2DShadow shadowSampler,float shadowMapSizeInverse,float lightSizeUV,float darkness,float frustumEdgeFalloff)
-{
-return computeShadowWithPCSS(vPositionFromLight,depthMetric,depthSampler,shadowSampler,shadowMapSizeInverse,lightSizeUV,darkness,frustumEdgeFalloff,16,16,PoissonSamplers32);
-}
-#define inline
-float computeShadowWithPCSS32(vec4 vPositionFromLight,float depthMetric,sampler2D depthSampler,highp sampler2DShadow shadowSampler,float shadowMapSizeInverse,float lightSizeUV,float darkness,float frustumEdgeFalloff)
-{
-return computeShadowWithPCSS(vPositionFromLight,depthMetric,depthSampler,shadowSampler,shadowMapSizeInverse,lightSizeUV,darkness,frustumEdgeFalloff,16,32,PoissonSamplers32);
-}
-#define inline
-float computeShadowWithPCSS64(vec4 vPositionFromLight,float depthMetric,sampler2D depthSampler,highp sampler2DShadow shadowSampler,float shadowMapSizeInverse,float lightSizeUV,float darkness,float frustumEdgeFalloff)
-{
-return computeShadowWithPCSS(vPositionFromLight,depthMetric,depthSampler,shadowSampler,shadowMapSizeInverse,lightSizeUV,darkness,frustumEdgeFalloff,32,64,PoissonSamplers64);
-}
-#define inline
-float computeShadowWithCSMPCSS16(float layer,vec4 vPositionFromLight,float depthMetric,highp sampler2DArray depthSampler,highp sampler2DArrayShadow shadowSampler,float shadowMapSizeInverse,float lightSizeUV,float darkness,float frustumEdgeFalloff,vec2 lightSizeUVCorrection,float depthCorrection,float penumbraDarkness)
-{
-return computeShadowWithCSMPCSS(layer,vPositionFromLight,depthMetric,depthSampler,shadowSampler,shadowMapSizeInverse,lightSizeUV,darkness,frustumEdgeFalloff,16,16,PoissonSamplers32,lightSizeUVCorrection,depthCorrection,penumbraDarkness);
-}
-#define inline
-float computeShadowWithCSMPCSS32(float layer,vec4 vPositionFromLight,float depthMetric,highp sampler2DArray depthSampler,highp sampler2DArrayShadow shadowSampler,float shadowMapSizeInverse,float lightSizeUV,float darkness,float frustumEdgeFalloff,vec2 lightSizeUVCorrection,float depthCorrection,float penumbraDarkness)
-{
-return computeShadowWithCSMPCSS(layer,vPositionFromLight,depthMetric,depthSampler,shadowSampler,shadowMapSizeInverse,lightSizeUV,darkness,frustumEdgeFalloff,16,32,PoissonSamplers32,lightSizeUVCorrection,depthCorrection,penumbraDarkness);
-}
-#define inline
-float computeShadowWithCSMPCSS64(float layer,vec4 vPositionFromLight,float depthMetric,highp sampler2DArray depthSampler,highp sampler2DArrayShadow shadowSampler,float shadowMapSizeInverse,float lightSizeUV,float darkness,float frustumEdgeFalloff,vec2 lightSizeUVCorrection,float depthCorrection,float penumbraDarkness)
-{
-return computeShadowWithCSMPCSS(layer,vPositionFromLight,depthMetric,depthSampler,shadowSampler,shadowMapSizeInverse,lightSizeUV,darkness,frustumEdgeFalloff,32,64,PoissonSamplers64,lightSizeUVCorrection,depthCorrection,penumbraDarkness);
-}
-#endif
-#endif
-`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U="reflectionFunction",_=`vec3 parallaxCorrectNormal( vec3 vertexPos,vec3 origVec,vec3 cubeSize,vec3 cubePos ) {
-
-vec3 invOrigVec=vec3(1.0,1.0,1.0)/origVec;
-vec3 halfSize=cubeSize*0.5;
-vec3 intersecAtMaxPlane=(cubePos+halfSize-vertexPos)*invOrigVec;
-vec3 intersecAtMinPlane=(cubePos-halfSize-vertexPos)*invOrigVec;
-
-vec3 largestIntersec=max(intersecAtMaxPlane,intersecAtMinPlane);
-
-float distance=min(min(largestIntersec.x,largestIntersec.y),largestIntersec.z);
-
-vec3 intersectPositionWS=vertexPos+origVec*distance;
-
-return intersectPositionWS-cubePos;
-}
-vec3 computeFixedEquirectangularCoords(vec4 worldPos,vec3 worldNormal,vec3 direction)
-{
-float lon=atan(direction.z,direction.x);
-float lat=acos(direction.y);
-vec2 sphereCoords=vec2(lon,lat)*RECIPROCAL_PI2*2.0;
-float s=sphereCoords.x*0.5+0.5;
-float t=sphereCoords.y;
-return vec3(s,t,0);
-}
-vec3 computeMirroredFixedEquirectangularCoords(vec4 worldPos,vec3 worldNormal,vec3 direction)
-{
-float lon=atan(direction.z,direction.x);
-float lat=acos(direction.y);
-vec2 sphereCoords=vec2(lon,lat)*RECIPROCAL_PI2*2.0;
-float s=sphereCoords.x*0.5+0.5;
-float t=sphereCoords.y;
-return vec3(1.0-s,t,0);
-}
-vec3 computeEquirectangularCoords(vec4 worldPos,vec3 worldNormal,vec3 eyePosition,mat4 reflectionMatrix)
-{
-vec3 cameraToVertex=normalize(worldPos.xyz-eyePosition);
-vec3 r=normalize(reflect(cameraToVertex,worldNormal));
-r=vec3(reflectionMatrix*vec4(r,0));
-float lon=atan(r.z,r.x);
-float lat=acos(r.y);
-vec2 sphereCoords=vec2(lon,lat)*RECIPROCAL_PI2*2.0;
-float s=sphereCoords.x*0.5+0.5;
-float t=sphereCoords.y;
-return vec3(s,t,0);
-}
-vec3 computeSphericalCoords(vec4 worldPos,vec3 worldNormal,mat4 view,mat4 reflectionMatrix)
-{
-vec3 viewDir=normalize(vec3(view*worldPos));
-vec3 viewNormal=normalize(vec3(view*vec4(worldNormal,0.0)));
-vec3 r=reflect(viewDir,viewNormal);
-r=vec3(reflectionMatrix*vec4(r,0));
-r.z=r.z-1.0;
-float m=2.0*length(r);
-return vec3(r.x/m+0.5,1.0-r.y/m-0.5,0);
-}
-vec3 computePlanarCoords(vec4 worldPos,vec3 worldNormal,vec3 eyePosition,mat4 reflectionMatrix)
-{
-vec3 viewDir=worldPos.xyz-eyePosition;
-vec3 coords=normalize(reflect(viewDir,worldNormal));
-return vec3(reflectionMatrix*vec4(coords,1));
-}
-vec3 computeCubicCoords(vec4 worldPos,vec3 worldNormal,vec3 eyePosition,mat4 reflectionMatrix)
-{
-vec3 viewDir=normalize(worldPos.xyz-eyePosition);
-
-vec3 coords=reflect(viewDir,worldNormal);
-coords=vec3(reflectionMatrix*vec4(coords,0));
-#ifdef INVERTCUBICMAP
-coords.y*=-1.0;
-#endif
-return coords;
-}
-vec3 computeCubicLocalCoords(vec4 worldPos,vec3 worldNormal,vec3 eyePosition,mat4 reflectionMatrix,vec3 reflectionSize,vec3 reflectionPosition)
-{
-vec3 viewDir=normalize(worldPos.xyz-eyePosition);
-
-vec3 coords=reflect(viewDir,worldNormal);
-coords=parallaxCorrectNormal(worldPos.xyz,coords,reflectionSize,reflectionPosition);
-coords=vec3(reflectionMatrix*vec4(coords,0));
-#ifdef INVERTCUBICMAP
-coords.y*=-1.0;
-#endif
-return coords;
-}
-vec3 computeProjectionCoords(vec4 worldPos,mat4 view,mat4 reflectionMatrix)
-{
-return vec3(reflectionMatrix*(view*worldPos));
-}
-vec3 computeSkyBoxCoords(vec3 positionW,mat4 reflectionMatrix)
-{
-return vec3(reflectionMatrix*vec4(positionW,1.));
-}
-#ifdef REFLECTION
-vec3 computeReflectionCoords(vec4 worldPos,vec3 worldNormal)
-{
-#ifdef REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED
-vec3 direction=normalize(vDirectionW);
-return computeMirroredFixedEquirectangularCoords(worldPos,worldNormal,direction);
-#endif
-#ifdef REFLECTIONMAP_EQUIRECTANGULAR_FIXED
-vec3 direction=normalize(vDirectionW);
-return computeFixedEquirectangularCoords(worldPos,worldNormal,direction);
-#endif
-#ifdef REFLECTIONMAP_EQUIRECTANGULAR
-return computeEquirectangularCoords(worldPos,worldNormal,vEyePosition.xyz,reflectionMatrix);
-#endif
-#ifdef REFLECTIONMAP_SPHERICAL
-return computeSphericalCoords(worldPos,worldNormal,view,reflectionMatrix);
-#endif
-#ifdef REFLECTIONMAP_PLANAR
-return computePlanarCoords(worldPos,worldNormal,vEyePosition.xyz,reflectionMatrix);
-#endif
-#ifdef REFLECTIONMAP_CUBIC
-#ifdef USE_LOCAL_REFLECTIONMAP_CUBIC
-return computeCubicLocalCoords(worldPos,worldNormal,vEyePosition.xyz,reflectionMatrix,vReflectionSize,vReflectionPosition);
-#else
-return computeCubicCoords(worldPos,worldNormal,vEyePosition.xyz,reflectionMatrix);
-#endif
-#endif
-#ifdef REFLECTIONMAP_PROJECTION
-return computeProjectionCoords(worldPos,view,reflectionMatrix);
-#endif
-#ifdef REFLECTIONMAP_SKYBOX
-return computeSkyBoxCoords(vPositionUVW,reflectionMatrix);
-#endif
-#ifdef REFLECTIONMAP_EXPLICIT
-return vec3(0,0,0);
-#endif
-}
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U="bumpFragmentMainFunctions",_=`#if defined(BUMP) || defined(CLEARCOAT_BUMP) || defined(ANISOTROPIC) || defined(DETAIL)
-#if defined(TANGENT) && defined(NORMAL)
-varying mat3 vTBN;
-#endif
-#ifdef OBJECTSPACE_NORMALMAP
-uniform mat4 normalMatrix;
-#endif
-vec3 perturbNormalBase(mat3 cotangentFrame,vec3 normal,float scale)
-{
-#ifdef NORMALXYSCALE
-normal=normalize(normal*vec3(scale,scale,1.0));
-#endif
-return normalize(cotangentFrame*normal);
-}
-vec3 perturbNormal(mat3 cotangentFrame,vec3 textureSample,float scale)
-{
-return perturbNormalBase(cotangentFrame,textureSample*2.0-1.0,scale);
-}
-
-mat3 cotangent_frame(vec3 normal,vec3 p,vec2 uv,vec2 tangentSpaceParams)
-{
-
-uv=gl_FrontFacing ? uv : -uv;
-
-vec3 dp1=dFdx(p);
-vec3 dp2=dFdy(p);
-vec2 duv1=dFdx(uv);
-vec2 duv2=dFdy(uv);
-
-vec3 dp2perp=cross(dp2,normal);
-vec3 dp1perp=cross(normal,dp1);
-vec3 tangent=dp2perp*duv1.x+dp1perp*duv2.x;
-vec3 bitangent=dp2perp*duv1.y+dp1perp*duv2.y;
-
-tangent*=tangentSpaceParams.x;
-bitangent*=tangentSpaceParams.y;
-
-float invmax=inversesqrt(max(dot(tangent,tangent),dot(bitangent,bitangent)));
-return mat3(tangent*invmax,bitangent*invmax,normal);
-}
-#endif
-`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U="bumpFragmentFunctions",_=`#if defined(BUMP)
-#if BUMPDIRECTUV == 1
-#define vBumpUV vMainUV1
-#elif BUMPDIRECTUV == 2
-#define vBumpUV vMainUV2
-#else
-varying vec2 vBumpUV;
-#endif
-uniform sampler2D bumpSampler;
-vec3 perturbNormal(mat3 cotangentFrame,vec2 uv)
-{
-return perturbNormal(cotangentFrame,texture2D(bumpSampler,uv).xyz,vBumpInfos.y);
-}
-#endif
-#if defined(DETAIL)
-#if DETAILDIRECTUV == 1
-#define vDetailUV vMainUV1
-#elif DETAILDIRECTUV == 2
-#define vDetailUV vMainUV2
-#else
-varying vec2 vDetailUV;
-#endif
-uniform sampler2D detailSampler;
-#endif
-#if defined(BUMP)
-vec3 perturbNormal(mat3 cotangentFrame,vec3 color)
-{
-return perturbNormal(cotangentFrame,color,vBumpInfos.y);
-}
-
-mat3 cotangent_frame(vec3 normal,vec3 p,vec2 uv)
-{
-return cotangent_frame(normal,p,uv,vTangentSpaceParams);
-}
-#endif
-#if defined(BUMP) && defined(PARALLAX)
-const float minSamples=4.;
-const float maxSamples=15.;
-const int iMaxSamples=15;
-
-vec2 parallaxOcclusion(vec3 vViewDirCoT,vec3 vNormalCoT,vec2 texCoord,float parallaxScale) {
-float parallaxLimit=length(vViewDirCoT.xy)/vViewDirCoT.z;
-parallaxLimit*=parallaxScale;
-vec2 vOffsetDir=normalize(vViewDirCoT.xy);
-vec2 vMaxOffset=vOffsetDir*parallaxLimit;
-float numSamples=maxSamples+(dot(vViewDirCoT,vNormalCoT)*(minSamples-maxSamples));
-float stepSize=1.0/numSamples;
-
-float currRayHeight=1.0;
-vec2 vCurrOffset=vec2(0,0);
-vec2 vLastOffset=vec2(0,0);
-float lastSampledHeight=1.0;
-float currSampledHeight=1.0;
-for (int i=0; i<iMaxSamples; i++)
-{
-currSampledHeight=texture2D(bumpSampler,vBumpUV+vCurrOffset).w;
-
-if (currSampledHeight>currRayHeight)
-{
-float delta1=currSampledHeight-currRayHeight;
-float delta2=(currRayHeight+stepSize)-lastSampledHeight;
-float ratio=delta1/(delta1+delta2);
-vCurrOffset=(ratio)* vLastOffset+(1.0-ratio)*vCurrOffset;
-
-break;
-}
-else
-{
-currRayHeight-=stepSize;
-vLastOffset=vCurrOffset;
-vCurrOffset+=stepSize*vMaxOffset;
-lastSampledHeight=currSampledHeight;
-}
-}
-return vCurrOffset;
-}
-vec2 parallaxOffset(vec3 viewDir,float heightScale)
-{
-
-float height=texture2D(bumpSampler,vBumpUV).w;
-vec2 texCoordOffset=heightScale*viewDir.xy*height;
-return -texCoordOffset;
-}
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U=`vec2 uvOffset=vec2(0.0,0.0);
-#if defined(BUMP) || defined(PARALLAX) || defined(DETAIL)
-#ifdef NORMALXYSCALE
-float normalScale=1.0;
-#elif defined(BUMP)
-float normalScale=vBumpInfos.y;
-#else
-float normalScale=1.0;
-#endif
-#if defined(TANGENT) && defined(NORMAL)
-mat3 TBN=vTBN;
-#elif defined(BUMP)
-mat3 TBN=cotangent_frame(normalW*normalScale,vPositionW,vBumpUV);
-#else
-mat3 TBN=cotangent_frame(normalW*normalScale,vPositionW,vDetailUV,vec2(1.,1.));
-#endif
-#elif defined(ANISOTROPIC)
-#if defined(TANGENT) && defined(NORMAL)
-mat3 TBN=vTBN;
-#else
-mat3 TBN=cotangent_frame(normalW,vPositionW,vMainUV1,vec2(1.,1.));
-#endif
-#endif
-#ifdef PARALLAX
-mat3 invTBN=transposeMat3(TBN);
-#ifdef PARALLAXOCCLUSION
-uvOffset=parallaxOcclusion(invTBN*-viewDirectionW,invTBN*normalW,vBumpUV,vBumpInfos.z);
-#else
-uvOffset=parallaxOffset(invTBN*viewDirectionW,vBumpInfos.z);
-#endif
-#endif
-#ifdef DETAIL
-vec4 detailColor=texture2D(detailSampler,vDetailUV+uvOffset);
-vec2 detailNormalRG=detailColor.wy*2.0-1.0;
-float detailNormalB=sqrt(1.-saturate(dot(detailNormalRG,detailNormalRG)));
-vec3 detailNormal=vec3(detailNormalRG,detailNormalB);
-#endif
-#ifdef BUMP
-#ifdef OBJECTSPACE_NORMALMAP
-normalW=normalize(texture2D(bumpSampler,vBumpUV).xyz*2.0-1.0);
-normalW=normalize(mat3(normalMatrix)*normalW);
-#elif !defined(DETAIL)
-normalW=perturbNormal(TBN,vBumpUV+uvOffset);
-#else
-vec3 bumpNormal=texture2D(bumpSampler,vBumpUV+uvOffset).xyz*2.0-1.0;
-
-#if DETAIL_NORMALBLENDMETHOD == 0
-detailNormal.xy*=vDetailInfos.z;
-vec3 blendedNormal=normalize(vec3(bumpNormal.xy+detailNormal.xy,bumpNormal.z*detailNormal.z));
-#elif DETAIL_NORMALBLENDMETHOD == 1
-detailNormal.xy*=vDetailInfos.z;
-bumpNormal+=vec3(0.0,0.0,1.0);
-detailNormal*=vec3(-1.0,-1.0,1.0);
-vec3 blendedNormal=bumpNormal*dot(bumpNormal,detailNormal)/bumpNormal.z-detailNormal;
-#endif
-normalW=perturbNormalBase(TBN,blendedNormal,vBumpInfos.y);
-#endif
-#elif defined(DETAIL)
-detailNormal.xy*=vDetailInfos.z;
-normalW=perturbNormalBase(TBN,detailNormal,vDetailInfos.z);
-#endif`;f(5).a.IncludesShadersStore.bumpFragment=U},function(Me,y,f){var U="lightFragment",_=`#ifdef LIGHT{X}
-#if defined(SHADOWONLY) || defined(LIGHTMAP) && defined(LIGHTMAPEXCLUDED{X}) && defined(LIGHTMAPNOSPECULAR{X})
-
-#else
-#ifdef PBR
-
-#ifdef SPOTLIGHT{X}
-preInfo=computePointAndSpotPreLightingInfo(light{X}.vLightData,viewDirectionW,normalW);
-#elif defined(POINTLIGHT{X})
-preInfo=computePointAndSpotPreLightingInfo(light{X}.vLightData,viewDirectionW,normalW);
-#elif defined(HEMILIGHT{X})
-preInfo=computeHemisphericPreLightingInfo(light{X}.vLightData,viewDirectionW,normalW);
-#elif defined(DIRLIGHT{X})
-preInfo=computeDirectionalPreLightingInfo(light{X}.vLightData,viewDirectionW,normalW);
-#endif
-preInfo.NdotV=NdotV;
-
-#ifdef SPOTLIGHT{X}
-#ifdef LIGHT_FALLOFF_GLTF{X}
-preInfo.attenuation=computeDistanceLightFalloff_GLTF(preInfo.lightDistanceSquared,light{X}.vLightFalloff.y);
-preInfo.attenuation*=computeDirectionalLightFalloff_GLTF(light{X}.vLightDirection.xyz,preInfo.L,light{X}.vLightFalloff.z,light{X}.vLightFalloff.w);
-#elif defined(LIGHT_FALLOFF_PHYSICAL{X})
-preInfo.attenuation=computeDistanceLightFalloff_Physical(preInfo.lightDistanceSquared);
-preInfo.attenuation*=computeDirectionalLightFalloff_Physical(light{X}.vLightDirection.xyz,preInfo.L,light{X}.vLightDirection.w);
-#elif defined(LIGHT_FALLOFF_STANDARD{X})
-preInfo.attenuation=computeDistanceLightFalloff_Standard(preInfo.lightOffset,light{X}.vLightFalloff.x);
-preInfo.attenuation*=computeDirectionalLightFalloff_Standard(light{X}.vLightDirection.xyz,preInfo.L,light{X}.vLightDirection.w,light{X}.vLightData.w);
-#else
-preInfo.attenuation=computeDistanceLightFalloff(preInfo.lightOffset,preInfo.lightDistanceSquared,light{X}.vLightFalloff.x,light{X}.vLightFalloff.y);
-preInfo.attenuation*=computeDirectionalLightFalloff(light{X}.vLightDirection.xyz,preInfo.L,light{X}.vLightDirection.w,light{X}.vLightData.w,light{X}.vLightFalloff.z,light{X}.vLightFalloff.w);
-#endif
-#elif defined(POINTLIGHT{X})
-#ifdef LIGHT_FALLOFF_GLTF{X}
-preInfo.attenuation=computeDistanceLightFalloff_GLTF(preInfo.lightDistanceSquared,light{X}.vLightFalloff.y);
-#elif defined(LIGHT_FALLOFF_PHYSICAL{X})
-preInfo.attenuation=computeDistanceLightFalloff_Physical(preInfo.lightDistanceSquared);
-#elif defined(LIGHT_FALLOFF_STANDARD{X})
-preInfo.attenuation=computeDistanceLightFalloff_Standard(preInfo.lightOffset,light{X}.vLightFalloff.x);
-#else
-preInfo.attenuation=computeDistanceLightFalloff(preInfo.lightOffset,preInfo.lightDistanceSquared,light{X}.vLightFalloff.x,light{X}.vLightFalloff.y);
-#endif
-#else
-preInfo.attenuation=1.0;
-#endif
-
-
-#ifdef HEMILIGHT{X}
-preInfo.roughness=roughness;
-#else
-preInfo.roughness=adjustRoughnessFromLightProperties(roughness,light{X}.vLightSpecular.a,preInfo.lightDistance);
-#endif
-
-#ifdef HEMILIGHT{X}
-info.diffuse=computeHemisphericDiffuseLighting(preInfo,light{X}.vLightDiffuse.rgb,light{X}.vLightGround);
-#elif defined(SS_TRANSLUCENCY)
-info.diffuse=computeDiffuseAndTransmittedLighting(preInfo,light{X}.vLightDiffuse.rgb,subSurfaceOut.transmittance);
-#else
-info.diffuse=computeDiffuseLighting(preInfo,light{X}.vLightDiffuse.rgb);
-#endif
-
-#ifdef SPECULARTERM
-#ifdef ANISOTROPIC
-info.specular=computeAnisotropicSpecularLighting(preInfo,viewDirectionW,normalW,anisotropicOut.anisotropicTangent,anisotropicOut.anisotropicBitangent,anisotropicOut.anisotropy,clearcoatOut.specularEnvironmentR0,specularEnvironmentR90,AARoughnessFactors.x,light{X}.vLightDiffuse.rgb);
-#else
-info.specular=computeSpecularLighting(preInfo,normalW,clearcoatOut.specularEnvironmentR0,specularEnvironmentR90,AARoughnessFactors.x,light{X}.vLightDiffuse.rgb);
-#endif
-#endif
-
-#ifdef SHEEN
-#ifdef SHEEN_LINKWITHALBEDO
-
-preInfo.roughness=sheenOut.sheenIntensity;
-#else
-#ifdef HEMILIGHT{X}
-preInfo.roughness=sheenOut.sheenRoughness;
-#else
-preInfo.roughness=adjustRoughnessFromLightProperties(sheenOut.sheenRoughness,light{X}.vLightSpecular.a,preInfo.lightDistance);
-#endif
-#endif
-info.sheen=computeSheenLighting(preInfo,normalW,sheenOut.sheenColor,specularEnvironmentR90,AARoughnessFactors.x,light{X}.vLightDiffuse.rgb);
-#endif
-
-#ifdef CLEARCOAT
-
-#ifdef HEMILIGHT{X}
-preInfo.roughness=clearcoatOut.clearCoatRoughness;
-#else
-preInfo.roughness=adjustRoughnessFromLightProperties(clearcoatOut.clearCoatRoughness,light{X}.vLightSpecular.a,preInfo.lightDistance);
-#endif
-info.clearCoat=computeClearCoatLighting(preInfo,clearcoatOut.clearCoatNormalW,clearcoatOut.clearCoatAARoughnessFactors.x,clearcoatOut.clearCoatIntensity,light{X}.vLightDiffuse.rgb);
-#ifdef CLEARCOAT_TINT
-
-absorption=computeClearCoatLightingAbsorption(clearcoatOut.clearCoatNdotVRefract,preInfo.L,clearcoatOut.clearCoatNormalW,clearcoatOut.clearCoatColor,clearcoatOut.clearCoatThickness,clearcoatOut.clearCoatIntensity);
-info.diffuse*=absorption;
-#ifdef SPECULARTERM
-info.specular*=absorption;
-#endif
-#endif
-
-info.diffuse*=info.clearCoat.w;
-#ifdef SPECULARTERM
-info.specular*=info.clearCoat.w;
-#endif
-#ifdef SHEEN
-info.sheen*=info.clearCoat.w;
-#endif
-#endif
-#else
-#ifdef SPOTLIGHT{X}
-info=computeSpotLighting(viewDirectionW,normalW,light{X}.vLightData,light{X}.vLightDirection,light{X}.vLightDiffuse.rgb,light{X}.vLightSpecular.rgb,light{X}.vLightDiffuse.a,glossiness);
-#elif defined(HEMILIGHT{X})
-info=computeHemisphericLighting(viewDirectionW,normalW,light{X}.vLightData,light{X}.vLightDiffuse.rgb,light{X}.vLightSpecular.rgb,light{X}.vLightGround,glossiness);
-#elif defined(POINTLIGHT{X}) || defined(DIRLIGHT{X})
-info=computeLighting(viewDirectionW,normalW,light{X}.vLightData,light{X}.vLightDiffuse.rgb,light{X}.vLightSpecular.rgb,light{X}.vLightDiffuse.a,glossiness);
-#endif
-#endif
-#ifdef PROJECTEDLIGHTTEXTURE{X}
-info.diffuse*=computeProjectionTextureDiffuseLighting(projectionLightSampler{X},textureProjectionMatrix{X});
-#endif
-#endif
-#ifdef SHADOW{X}
-#ifdef SHADOWCSM{X}
-for (int i=0; i<SHADOWCSMNUM_CASCADES{X}; i++)
-{
-#ifdef SHADOWCSM_RIGHTHANDED{X}
-diff{X}=viewFrustumZ{X}[i]+vPositionFromCamera{X}.z;
-#else
-diff{X}=viewFrustumZ{X}[i]-vPositionFromCamera{X}.z;
-#endif
-if (diff{X}>=0.) {
-index{X}=i;
-break;
-}
-}
-#ifdef SHADOWCSMUSESHADOWMAXZ{X}
-if (index{X}>=0)
-#endif
-{
-#if defined(SHADOWPCF{X})
-#if defined(SHADOWLOWQUALITY{X})
-shadow=computeShadowWithCSMPCF1(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#elif defined(SHADOWMEDIUMQUALITY{X})
-shadow=computeShadowWithCSMPCF3(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],shadowSampler{X},light{X}.shadowsInfo.yz,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#else
-shadow=computeShadowWithCSMPCF5(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],shadowSampler{X},light{X}.shadowsInfo.yz,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#endif
-#elif defined(SHADOWPCSS{X})
-#if defined(SHADOWLOWQUALITY{X})
-shadow=computeShadowWithCSMPCSS16(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],depthSampler{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.z,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w,lightSizeUVCorrection{X}[index{X}],depthCorrection{X}[index{X}],penumbraDarkness{X});
-#elif defined(SHADOWMEDIUMQUALITY{X})
-shadow=computeShadowWithCSMPCSS32(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],depthSampler{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.z,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w,lightSizeUVCorrection{X}[index{X}],depthCorrection{X}[index{X}],penumbraDarkness{X});
-#else
-shadow=computeShadowWithCSMPCSS64(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],depthSampler{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.z,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w,lightSizeUVCorrection{X}[index{X}],depthCorrection{X}[index{X}],penumbraDarkness{X});
-#endif
-#else
-shadow=computeShadowCSM(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#endif
-#ifdef SHADOWCSMDEBUG{X}
-shadowDebug{X}=vec3(shadow)*vCascadeColorsMultiplier{X}[index{X}];
-#endif
-#ifndef SHADOWCSMNOBLEND{X}
-float frustumLength=frustumLengths{X}[index{X}];
-float diffRatio=clamp(diff{X}/frustumLength,0.,1.)*cascadeBlendFactor{X};
-if (index{X}<(SHADOWCSMNUM_CASCADES{X}-1) && diffRatio<1.)
-{
-index{X}+=1;
-float nextShadow=0.;
-#if defined(SHADOWPCF{X})
-#if defined(SHADOWLOWQUALITY{X})
-nextShadow=computeShadowWithCSMPCF1(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#elif defined(SHADOWMEDIUMQUALITY{X})
-nextShadow=computeShadowWithCSMPCF3(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],shadowSampler{X},light{X}.shadowsInfo.yz,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#else
-nextShadow=computeShadowWithCSMPCF5(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],shadowSampler{X},light{X}.shadowsInfo.yz,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#endif
-#elif defined(SHADOWPCSS{X})
-#if defined(SHADOWLOWQUALITY{X})
-nextShadow=computeShadowWithCSMPCSS16(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],depthSampler{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.z,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w,lightSizeUVCorrection{X}[index{X}],depthCorrection{X}[index{X}],penumbraDarkness{X});
-#elif defined(SHADOWMEDIUMQUALITY{X})
-nextShadow=computeShadowWithCSMPCSS32(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],depthSampler{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.z,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w,lightSizeUVCorrection{X}[index{X}],depthCorrection{X}[index{X}],penumbraDarkness{X});
-#else
-nextShadow=computeShadowWithCSMPCSS64(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],depthSampler{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.z,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w,lightSizeUVCorrection{X}[index{X}],depthCorrection{X}[index{X}],penumbraDarkness{X});
-#endif
-#else
-nextShadow=computeShadowCSM(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#endif
-shadow=mix(nextShadow,shadow,diffRatio);
-#ifdef SHADOWCSMDEBUG{X}
-shadowDebug{X}=mix(vec3(nextShadow)*vCascadeColorsMultiplier{X}[index{X}],shadowDebug{X},diffRatio);
-#endif
-}
-#endif
-}
-#elif defined(SHADOWCLOSEESM{X})
-#if defined(SHADOWCUBE{X})
-shadow=computeShadowWithCloseESMCube(light{X}.vLightData.xyz,shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.z,light{X}.depthValues);
-#else
-shadow=computeShadowWithCloseESM(vPositionFromLight{X},vDepthMetric{X},shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.z,light{X}.shadowsInfo.w);
-#endif
-#elif defined(SHADOWESM{X})
-#if defined(SHADOWCUBE{X})
-shadow=computeShadowWithESMCube(light{X}.vLightData.xyz,shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.z,light{X}.depthValues);
-#else
-shadow=computeShadowWithESM(vPositionFromLight{X},vDepthMetric{X},shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.z,light{X}.shadowsInfo.w);
-#endif
-#elif defined(SHADOWPOISSON{X})
-#if defined(SHADOWCUBE{X})
-shadow=computeShadowWithPoissonSamplingCube(light{X}.vLightData.xyz,shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.x,light{X}.depthValues);
-#else
-shadow=computeShadowWithPoissonSampling(vPositionFromLight{X},vDepthMetric{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#endif
-#elif defined(SHADOWPCF{X})
-#if defined(SHADOWLOWQUALITY{X})
-shadow=computeShadowWithPCF1(vPositionFromLight{X},vDepthMetric{X},shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#elif defined(SHADOWMEDIUMQUALITY{X})
-shadow=computeShadowWithPCF3(vPositionFromLight{X},vDepthMetric{X},shadowSampler{X},light{X}.shadowsInfo.yz,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#else
-shadow=computeShadowWithPCF5(vPositionFromLight{X},vDepthMetric{X},shadowSampler{X},light{X}.shadowsInfo.yz,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#endif
-#elif defined(SHADOWPCSS{X})
-#if defined(SHADOWLOWQUALITY{X})
-shadow=computeShadowWithPCSS16(vPositionFromLight{X},vDepthMetric{X},depthSampler{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.z,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#elif defined(SHADOWMEDIUMQUALITY{X})
-shadow=computeShadowWithPCSS32(vPositionFromLight{X},vDepthMetric{X},depthSampler{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.z,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#else
-shadow=computeShadowWithPCSS64(vPositionFromLight{X},vDepthMetric{X},depthSampler{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.z,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#endif
-#else
-#if defined(SHADOWCUBE{X})
-shadow=computeShadowCube(light{X}.vLightData.xyz,shadowSampler{X},light{X}.shadowsInfo.x,light{X}.depthValues);
-#else
-shadow=computeShadow(vPositionFromLight{X},vDepthMetric{X},shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#endif
-#endif
-#ifdef SHADOWONLY
-#ifndef SHADOWINUSE
-#define SHADOWINUSE
-#endif
-globalShadow+=shadow;
-shadowLightCount+=1.0;
-#endif
-#else
-shadow=1.;
-#endif
-#ifndef SHADOWONLY
-#ifdef CUSTOMUSERLIGHTING
-diffuseBase+=computeCustomDiffuseLighting(info,diffuseBase,shadow);
-#ifdef SPECULARTERM
-specularBase+=computeCustomSpecularLighting(info,specularBase,shadow);
-#endif
-#elif defined(LIGHTMAP) && defined(LIGHTMAPEXCLUDED{X})
-diffuseBase+=lightmapColor.rgb*shadow;
-#ifdef SPECULARTERM
-#ifndef LIGHTMAPNOSPECULAR{X}
-specularBase+=info.specular*shadow*lightmapColor.rgb;
-#endif
-#endif
-#ifdef CLEARCOAT
-#ifndef LIGHTMAPNOSPECULAR{X}
-clearCoatBase+=info.clearCoat.rgb*shadow*lightmapColor.rgb;
-#endif
-#endif
-#ifdef SHEEN
-#ifndef LIGHTMAPNOSPECULAR{X}
-sheenBase+=info.sheen.rgb*shadow;
-#endif
-#endif
-#else
-#ifdef SHADOWCSMDEBUG{X}
-diffuseBase+=info.diffuse*shadowDebug{X};
-#else
-diffuseBase+=info.diffuse*shadow;
-#endif
-#ifdef SPECULARTERM
-specularBase+=info.specular*shadow;
-#endif
-#ifdef CLEARCOAT
-clearCoatBase+=info.clearCoat.rgb*shadow;
-#endif
-#ifdef SHEEN
-sheenBase+=info.sheen.rgb*shadow;
-#endif
-#endif
-#endif
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U=`#ifdef FOG
-float fog=CalcFogFactor();
-color.rgb=fog*color.rgb+(1.0-fog)*vFogColor;
-#endif`;f(5).a.IncludesShadersStore.fogFragment=U},function(Me,y,f){var U="fogVertexDeclaration",_=`#ifdef FOG
-varying vec3 vFogDistance;
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U="shadowsVertex",_=`#ifdef SHADOWS
-#if defined(SHADOWCSM{X})
-vPositionFromCamera{X}=view*worldPos;
-for (int i=0; i<SHADOWCSMNUM_CASCADES{X}; i++) {
-vPositionFromLight{X}[i]=lightMatrix{X}[i]*worldPos;
-vDepthMetric{X}[i]=((vPositionFromLight{X}[i].z+light{X}.depthValues.x)/(light{X}.depthValues.y));
-}
-#elif defined(SHADOW{X}) && !defined(SHADOWCUBE{X})
-vPositionFromLight{X}=lightMatrix{X}*worldPos;
-vDepthMetric{X}=((vPositionFromLight{X}.z+light{X}.depthValues.x)/(light{X}.depthValues.y));
-#endif
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.Eval=function(x,u){return(x=x.match(/\([^\(\)]*\)/g)?x.replace(/\([^\(\)]*\)/g,function(M){return M=M.slice(1,M.length-1),_._HandleParenthesisContent(M,u)}):_._HandleParenthesisContent(x,u))==="true"||x!=="false"&&_.Eval(x,u)},_._HandleParenthesisContent=function(x,u){var M;u=u||function(S){return S==="true"};var R=x.split("||");for(var C in R)if(R.hasOwnProperty(C)){var m=_._SimplifyNegation(R[C].trim()),c=m.split("&&");if(c.length>1)for(var T=0;T<c.length;++T){var A=_._SimplifyNegation(c[T].trim());if(!(M=A!=="true"&&A!=="false"?A[0]==="!"?!u(A.substring(1)):u(A):A==="true")){m="false";break}}if(M||m==="true"){M=!0;break}M=m!=="true"&&m!=="false"?m[0]==="!"?!u(m.substring(1)):u(m):m==="true"}return M?"true":"false"},_._SimplifyNegation=function(x){return(x=(x=x.replace(/^[\s!]+/,function(u){return(u=u.replace(/[\s]/g,function(){return""})).length%2?"!":""})).trim())==="!true"?x="false":x==="!false"&&(x="true"),x},_}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.ExponentialBackoff=function(x,u){return x===void 0&&(x=3),u===void 0&&(u=500),function(M,R,C){return R.status!==0||C>=x||M.indexOf("file:")!==-1?-1:Math.pow(2,C)*u}},_}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){this._isDepthTestDirty=!1,this._isDepthMaskDirty=!1,this._isDepthFuncDirty=!1,this._isCullFaceDirty=!1,this._isCullDirty=!1,this._isZOffsetDirty=!1,this._isFrontFaceDirty=!1,this.reset()}return Object.defineProperty(_.prototype,"isDirty",{get:function(){return this._isDepthFuncDirty||this._isDepthTestDirty||this._isDepthMaskDirty||this._isCullFaceDirty||this._isCullDirty||this._isZOffsetDirty||this._isFrontFaceDirty},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"zOffset",{get:function(){return this._zOffset},set:function(x){this._zOffset!==x&&(this._zOffset=x,this._isZOffsetDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"cullFace",{get:function(){return this._cullFace},set:function(x){this._cullFace!==x&&(this._cullFace=x,this._isCullFaceDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"cull",{get:function(){return this._cull},set:function(x){this._cull!==x&&(this._cull=x,this._isCullDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"depthFunc",{get:function(){return this._depthFunc},set:function(x){this._depthFunc!==x&&(this._depthFunc=x,this._isDepthFuncDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"depthMask",{get:function(){return this._depthMask},set:function(x){this._depthMask!==x&&(this._depthMask=x,this._isDepthMaskDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"depthTest",{get:function(){return this._depthTest},set:function(x){this._depthTest!==x&&(this._depthTest=x,this._isDepthTestDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"frontFace",{get:function(){return this._frontFace},set:function(x){this._frontFace!==x&&(this._frontFace=x,this._isFrontFaceDirty=!0)},enumerable:!1,configurable:!0}),_.prototype.reset=function(){this._depthMask=!0,this._depthTest=!0,this._depthFunc=null,this._cullFace=null,this._cull=null,this._zOffset=0,this._frontFace=null,this._isDepthTestDirty=!0,this._isDepthMaskDirty=!0,this._isDepthFuncDirty=!1,this._isCullFaceDirty=!1,this._isCullDirty=!1,this._isZOffsetDirty=!1,this._isFrontFaceDirty=!1},_.prototype.apply=function(x){this.isDirty&&(this._isCullDirty&&(this.cull?x.enable(x.CULL_FACE):x.disable(x.CULL_FACE),this._isCullDirty=!1),this._isCullFaceDirty&&(x.cullFace(this.cullFace),this._isCullFaceDirty=!1),this._isDepthMaskDirty&&(x.depthMask(this.depthMask),this._isDepthMaskDirty=!1),this._isDepthTestDirty&&(this.depthTest?x.enable(x.DEPTH_TEST):x.disable(x.DEPTH_TEST),this._isDepthTestDirty=!1),this._isDepthFuncDirty&&(x.depthFunc(this.depthFunc),this._isDepthFuncDirty=!1),this._isZOffsetDirty&&(this.zOffset?(x.enable(x.POLYGON_OFFSET_FILL),x.polygonOffset(this.zOffset,0)):x.disable(x.POLYGON_OFFSET_FILL),this._isZOffsetDirty=!1),this._isFrontFaceDirty&&(x.frontFace(this.frontFace),this._isFrontFaceDirty=!1))},_}()},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(2),_=function(){function x(){this._isStencilTestDirty=!1,this._isStencilMaskDirty=!1,this._isStencilFuncDirty=!1,this._isStencilOpDirty=!1,this.reset()}return Object.defineProperty(x.prototype,"isDirty",{get:function(){return this._isStencilTestDirty||this._isStencilMaskDirty||this._isStencilFuncDirty||this._isStencilOpDirty},enumerable:!1,configurable:!0}),Object.defineProperty(x.prototype,"stencilFunc",{get:function(){return this._stencilFunc},set:function(u){this._stencilFunc!==u&&(this._stencilFunc=u,this._isStencilFuncDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(x.prototype,"stencilFuncRef",{get:function(){return this._stencilFuncRef},set:function(u){this._stencilFuncRef!==u&&(this._stencilFuncRef=u,this._isStencilFuncDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(x.prototype,"stencilFuncMask",{get:function(){return this._stencilFuncMask},set:function(u){this._stencilFuncMask!==u&&(this._stencilFuncMask=u,this._isStencilFuncDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(x.prototype,"stencilOpStencilFail",{get:function(){return this._stencilOpStencilFail},set:function(u){this._stencilOpStencilFail!==u&&(this._stencilOpStencilFail=u,this._isStencilOpDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(x.prototype,"stencilOpDepthFail",{get:function(){return this._stencilOpDepthFail},set:function(u){this._stencilOpDepthFail!==u&&(this._stencilOpDepthFail=u,this._isStencilOpDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(x.prototype,"stencilOpStencilDepthPass",{get:function(){return this._stencilOpStencilDepthPass},set:function(u){this._stencilOpStencilDepthPass!==u&&(this._stencilOpStencilDepthPass=u,this._isStencilOpDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(x.prototype,"stencilMask",{get:function(){return this._stencilMask},set:function(u){this._stencilMask!==u&&(this._stencilMask=u,this._isStencilMaskDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(x.prototype,"stencilTest",{get:function(){return this._stencilTest},set:function(u){this._stencilTest!==u&&(this._stencilTest=u,this._isStencilTestDirty=!0)},enumerable:!1,configurable:!0}),x.prototype.reset=function(){this._stencilTest=!1,this._stencilMask=255,this._stencilFunc=x.ALWAYS,this._stencilFuncRef=1,this._stencilFuncMask=255,this._stencilOpStencilFail=x.KEEP,this._stencilOpDepthFail=x.KEEP,this._stencilOpStencilDepthPass=x.REPLACE,this._isStencilTestDirty=!0,this._isStencilMaskDirty=!0,this._isStencilFuncDirty=!0,this._isStencilOpDirty=!0},x.prototype.apply=function(u){this.isDirty&&(this._isStencilTestDirty&&(this.stencilTest?u.enable(u.STENCIL_TEST):u.disable(u.STENCIL_TEST),this._isStencilTestDirty=!1),this._isStencilMaskDirty&&(u.stencilMask(this.stencilMask),this._isStencilMaskDirty=!1),this._isStencilFuncDirty&&(u.stencilFunc(this.stencilFunc,this.stencilFuncRef,this.stencilFuncMask),this._isStencilFuncDirty=!1),this._isStencilOpDirty&&(u.stencilOp(this.stencilOpStencilFail,this.stencilOpDepthFail,this.stencilOpStencilDepthPass),this._isStencilOpDirty=!1))},x.ALWAYS=U.a.ALWAYS,x.KEEP=U.a.KEEP,x.REPLACE=U.a.REPLACE,x}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){this._isAlphaBlendDirty=!1,this._isBlendFunctionParametersDirty=!1,this._isBlendEquationParametersDirty=!1,this._isBlendConstantsDirty=!1,this._alphaBlend=!1,this._blendFunctionParameters=new Array(4),this._blendEquationParameters=new Array(2),this._blendConstants=new Array(4),this.reset()}return Object.defineProperty(_.prototype,"isDirty",{get:function(){return this._isAlphaBlendDirty||this._isBlendFunctionParametersDirty},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"alphaBlend",{get:function(){return this._alphaBlend},set:function(x){this._alphaBlend!==x&&(this._alphaBlend=x,this._isAlphaBlendDirty=!0)},enumerable:!1,configurable:!0}),_.prototype.setAlphaBlendConstants=function(x,u,M,R){this._blendConstants[0]===x&&this._blendConstants[1]===u&&this._blendConstants[2]===M&&this._blendConstants[3]===R||(this._blendConstants[0]=x,this._blendConstants[1]=u,this._blendConstants[2]=M,this._blendConstants[3]=R,this._isBlendConstantsDirty=!0)},_.prototype.setAlphaBlendFunctionParameters=function(x,u,M,R){this._blendFunctionParameters[0]===x&&this._blendFunctionParameters[1]===u&&this._blendFunctionParameters[2]===M&&this._blendFunctionParameters[3]===R||(this._blendFunctionParameters[0]=x,this._blendFunctionParameters[1]=u,this._blendFunctionParameters[2]=M,this._blendFunctionParameters[3]=R,this._isBlendFunctionParametersDirty=!0)},_.prototype.setAlphaEquationParameters=function(x,u){this._blendEquationParameters[0]===x&&this._blendEquationParameters[1]===u||(this._blendEquationParameters[0]=x,this._blendEquationParameters[1]=u,this._isBlendEquationParametersDirty=!0)},_.prototype.reset=function(){this._alphaBlend=!1,this._blendFunctionParameters[0]=null,this._blendFunctionParameters[1]=null,this._blendFunctionParameters[2]=null,this._blendFunctionParameters[3]=null,this._blendEquationParameters[0]=null,this._blendEquationParameters[1]=null,this._blendConstants[0]=null,this._blendConstants[1]=null,this._blendConstants[2]=null,this._blendConstants[3]=null,this._isAlphaBlendDirty=!0,this._isBlendFunctionParametersDirty=!1,this._isBlendEquationParametersDirty=!1,this._isBlendConstantsDirty=!1},_.prototype.apply=function(x){this.isDirty&&(this._isAlphaBlendDirty&&(this._alphaBlend?x.enable(x.BLEND):x.disable(x.BLEND),this._isAlphaBlendDirty=!1),this._isBlendFunctionParametersDirty&&(x.blendFuncSeparate(this._blendFunctionParameters[0],this._blendFunctionParameters[1],this._blendFunctionParameters[2],this._blendFunctionParameters[3]),this._isBlendFunctionParametersDirty=!1),this._isBlendEquationParametersDirty&&(x.blendEquationSeparate(this._blendEquationParameters[0],this._blendEquationParameters[1]),this._isBlendEquationParametersDirty=!1),this._isBlendConstantsDirty&&(x.blendColor(this._blendConstants[0],this._blendConstants[1],this._blendConstants[2],this._blendConstants[3]),this._isBlendConstantsDirty=!1))},_}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){this.vertexCompilationError=null,this.fragmentCompilationError=null,this.programLinkError=null,this.programValidationError=null}return Object.defineProperty(_.prototype,"isAsync",{get:function(){return this.isParallelCompiled},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"isReady",{get:function(){return!!this.program&&(!this.isParallelCompiled||this.engine._isRenderingStateCompiled(this))},enumerable:!1,configurable:!0}),_.prototype._handlesSpectorRebuildCallback=function(x){x&&this.program&&x(this.program)},_.prototype._getVertexShaderCode=function(){return this.vertexShader?this.engine._getShaderSource(this.vertexShader):null},_.prototype._getFragmentShaderCode=function(){return this.fragmentShader?this.engine._getShaderSource(this.fragmentShader):null},_}()},function(Me,y,f){var U;f.d(y,"a",function(){return u}),function(M){M[M.Pending=0]="Pending",M[M.Fulfilled=1]="Fulfilled",M[M.Rejected=2]="Rejected"}(U||(U={}));var _=function(){this.count=0,this.target=0,this.results=[]},x=function(){function M(R){var C=this;if(this._state=U.Pending,this._children=new Array,this._rejectWasConsumed=!1,R)try{R(function(m){C._resolve(m)},function(m){C._reject(m)})}catch(m){this._reject(m)}}return Object.defineProperty(M.prototype,"_result",{get:function(){return this._resultValue},set:function(R){this._resultValue=R,this._parent&&this._parent._result===void 0&&(this._parent._result=R)},enumerable:!1,configurable:!0}),M.prototype.catch=function(R){return this.then(void 0,R)},M.prototype.then=function(R,C){var m=this,c=new M;return c._onFulfilled=R,c._onRejected=C,this._children.push(c),c._parent=this,this._state!==U.Pending&&setTimeout(function(){if(m._state===U.Fulfilled||m._rejectWasConsumed){var T=c._resolve(m._result);if(T!=null)if(T._state!==void 0){var A=T;c._children.push(A),A._parent=c,c=A}else c._result=T}else c._reject(m._reason)}),c},M.prototype._moveChildren=function(R){var C,m=this;if((C=this._children).push.apply(C,R.splice(0,R.length)),this._children.forEach(function(g){g._parent=m}),this._state===U.Fulfilled)for(var c=0,T=this._children;c<T.length;c++)T[c]._resolve(this._result);else if(this._state===U.Rejected)for(var A=0,S=this._children;A<S.length;A++)S[A]._reject(this._reason)},M.prototype._resolve=function(R){try{this._state=U.Fulfilled;var C=null;if(this._onFulfilled&&(C=this._onFulfilled(R)),C!=null)if(C._state!==void 0){var m=C;m._parent=this,m._moveChildren(this._children),R=m._result}else R=C;this._result=R;for(var c=0,T=this._children;c<T.length;c++)T[c]._resolve(R);this._children.length=0,delete this._onFulfilled,delete this._onRejected}catch(A){this._reject(A,!0)}},M.prototype._reject=function(R,C){if(C===void 0&&(C=!1),this._state=U.Rejected,this._reason=R,this._onRejected&&!C)try{this._onRejected(R),this._rejectWasConsumed=!0}catch(A){R=A}for(var m=0,c=this._children;m<c.length;m++){var T=c[m];this._rejectWasConsumed?T._resolve(null):T._reject(R)}this._children.length=0,delete this._onFulfilled,delete this._onRejected},M.resolve=function(R){var C=new M;return C._resolve(R),C},M._RegisterForFulfillment=function(R,C,m){R.then(function(c){return C.results[m]=c,C.count++,C.count===C.target&&C.rootPromise._resolve(C.results),null},function(c){C.rootPromise._state!==U.Rejected&&C.rootPromise._reject(c)})},M.all=function(R){var C=new M,m=new _;if(m.target=R.length,m.rootPromise=C,R.length)for(var c=0;c<R.length;c++)M._RegisterForFulfillment(R[c],m,c);else C._resolve([]);return C},M.race=function(R){var C=new M;if(R.length)for(var m=0,c=R;m<c.length;m++)c[m].then(function(T){return C&&(C._resolve(T),C=null),null},function(T){C&&(C._reject(T),C=null)});return C},M}(),u=function(){function M(){}return M.Apply=function(R){R===void 0&&(R=!1),(R||typeof Promise>"u")&&(window.Promise=x)},M}()},function(Me,y,f){f.d(y,"a",function(){return _}),f.d(y,"b",function(){return x});var 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M===0?0:1e3/M},enumerable:!1,configurable:!0}),Object.defineProperty(u.prototype,"isSaturated",{get:function(){return this._rollingFrameTime.isSaturated()},enumerable:!1,configurable:!0}),u.prototype.enable=function(){this._enabled=!0},u.prototype.disable=function(){this._enabled=!1,this._lastFrameTimeMs=null},Object.defineProperty(u.prototype,"isEnabled",{get:function(){return this._enabled},enumerable:!1,configurable:!0}),u.prototype.reset=function(){this._lastFrameTimeMs=null,this._rollingFrameTime.reset()},u}(),x=function(){function u(M){this._samples=new Array(M),this.reset()}return u.prototype.add=function(M){var R;if(this.isSaturated()){var C=this._samples[this._pos];R=C-this.average,this.average-=R/(this._sampleCount-1),this._m2-=R*(C-this.average)}else 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U.e(0,0,0),this._collisionResponse=!0}},function(Me,y,f){f.d(y,"a",function(){return u});var U=f(33),_=f(0),x=f(2),u=function(){function M(R,C,m,c,T){m===void 0&&(m=null),c===void 0&&(c=null),T===void 0&&(T=null),this.index=R,this._opaqueSubMeshes=new U.a(256),this._transparentSubMeshes=new U.a(256),this._alphaTestSubMeshes=new U.a(256),this._depthOnlySubMeshes=new U.a(256),this._particleSystems=new U.a(256),this._spriteManagers=new U.a(256),this._edgesRenderers=new U.b(16),this._scene=C,this.opaqueSortCompareFn=m,this.alphaTestSortCompareFn=c,this.transparentSortCompareFn=T}return Object.defineProperty(M.prototype,"opaqueSortCompareFn",{set:function(R){this._opaqueSortCompareFn=R,this._renderOpaque=R?this.renderOpaqueSorted:M.renderUnsorted},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"alphaTestSortCompareFn",{set:function(R){this._alphaTestSortCompareFn=R,this._renderAlphaTest=R?this.renderAlphaTestSorted:M.renderUnsorted},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"transparentSortCompareFn",{set:function(R){this._transparentSortCompareFn=R||M.defaultTransparentSortCompare,this._renderTransparent=this.renderTransparentSorted},enumerable:!1,configurable:!0}),M.prototype.render=function(R,C,m,c){if(R)R(this._opaqueSubMeshes,this._alphaTestSubMeshes,this._transparentSubMeshes,this._depthOnlySubMeshes);else{var T=this._scene.getEngine();this._depthOnlySubMeshes.length!==0&&(T.setColorWrite(!1),this._renderAlphaTest(this._depthOnlySubMeshes),T.setColorWrite(!0)),this._opaqueSubMeshes.length!==0&&this._renderOpaque(this._opaqueSubMeshes),this._alphaTestSubMeshes.length!==0&&this._renderAlphaTest(this._alphaTestSubMeshes);var A=T.getStencilBuffer();if(T.setStencilBuffer(!1),C&&this._renderSprites(),m&&this._renderParticles(c),this.onBeforeTransparentRendering&&this.onBeforeTransparentRendering(),this._transparentSubMeshes.length!==0&&(T.setStencilBuffer(A),this._renderTransparent(this._transparentSubMeshes),T.setAlphaMode(x.a.ALPHA_DISABLE)),T.setStencilBuffer(!1),this._edgesRenderers.length){for(var S=0;S<this._edgesRenderers.length;S++)this._edgesRenderers.data[S].render();T.setAlphaMode(x.a.ALPHA_DISABLE)}T.setStencilBuffer(A)}},M.prototype.renderOpaqueSorted=function(R){return M.renderSorted(R,this._opaqueSortCompareFn,this._scene.activeCamera,!1)},M.prototype.renderAlphaTestSorted=function(R){return M.renderSorted(R,this._alphaTestSortCompareFn,this._scene.activeCamera,!1)},M.prototype.renderTransparentSorted=function(R){return M.renderSorted(R,this._transparentSortCompareFn,this._scene.activeCamera,!0)},M.renderSorted=function(R,C,m,c){for(var T,A=0,S=m?m.globalPosition:M._zeroVector;A<R.length;A++)(T=R.data[A])._alphaIndex=T.getMesh().alphaIndex,T._distanceToCamera=_.e.Distance(T.getBoundingInfo().boundingSphere.centerWorld,S);var g=R.data.slice(0,R.length);for(C&&g.sort(C),A=0;A<g.length;A++){if(T=g[A],c){var l=T.getMaterial();if(l&&l.needDepthPrePass){var h=l.getScene().getEngine();h.setColorWrite(!1),h.setAlphaMode(x.a.ALPHA_DISABLE),T.render(!1),h.setColorWrite(!0)}}T.render(c)}},M.renderUnsorted=function(R){for(var C=0;C<R.length;C++)R.data[C].render(!1)},M.defaultTransparentSortCompare=function(R,C){return 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m=x.getSize(),c=m.width,T=m.height;if(C instanceof Float32Array){for(var A=C.byteLength/C.BYTES_PER_ELEMENT,S=new Uint8Array(A);--A>=0;){var g=C[A];g<0?g=0:g>1&&(g=1),S[A]=255*g}C=S}var l=document.createElement("canvas");l.width=c,l.height=T;var h=l.getContext("2d");if(!h)return null;var v=h.createImageData(c,T);if(v.data.set(C),h.putImageData(v,0,0),R.invertY){var E=document.createElement("canvas");E.width=c,E.height=T;var D=E.getContext("2d");return D?(D.translate(0,T),D.scale(1,-1),D.drawImage(l,0,0),E.toDataURL("image/png")):null}return l.toDataURL("image/png")},_}()},function(Me,y,f){f.d(y,"a",function(){return A});var U=f(1),_=f(0),x=f(8),u=f(31),M=f(7),R=f(41),C=f(46),m=f(4),c=f(43),T=f(12);M.a._instancedMeshFactory=function(S,g){var l=new A(S,g);if(g.instancedBuffers)for(var h in l.instancedBuffers={},g.instancedBuffers)l.instancedBuffers[h]=g.instancedBuffers[h];return l};var A=function(S){function g(l,h){var v=S.call(this,l,h.getScene())||this;v._indexInSourceMeshInstanceArray=-1,h.addInstance(v),v._sourceMesh=h,v._unIndexed=h._unIndexed,v.position.copyFrom(h.position),v.rotation.copyFrom(h.rotation),v.scaling.copyFrom(h.scaling),h.rotationQuaternion&&(v.rotationQuaternion=h.rotationQuaternion.clone()),v.animations=T.b.Slice(h.animations);for(var E=0,D=h.getAnimationRanges();E<D.length;E++){var w=D[E];w!=null&&v.createAnimationRange(w.name,w.from,w.to)}return v.infiniteDistance=h.infiniteDistance,v.setPivotMatrix(h.getPivotMatrix()),v.refreshBoundingInfo(),v._syncSubMeshes(),v}return Object(U.d)(g,S),g.prototype.getClassName=function(){return"InstancedMesh"},Object.defineProperty(g.prototype,"lightSources",{get:function(){return this._sourceMesh._lightSources},enumerable:!1,configurable:!0}),g.prototype._resyncLightSources=function(){},g.prototype._resyncLightSource=function(l){},g.prototype._removeLightSource=function(l,h){},Object.defineProperty(g.prototype,"receiveShadows",{get:function(){return this._sourceMesh.receiveShadows},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"material",{get:function(){return this._sourceMesh.material},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"visibility",{get:function(){return this._sourceMesh.visibility},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"skeleton",{get:function(){return this._sourceMesh.skeleton},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"renderingGroupId",{get:function(){return this._sourceMesh.renderingGroupId},set:function(l){this._sourceMesh&&l!==this._sourceMesh.renderingGroupId&&x.a.Warn("Note - setting renderingGroupId of an instanced mesh has no effect on the 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0&&(h=null),this.sourceMesh&&this.sourceMesh.setIndices(l,h),this.sourceMesh},g.prototype.isVerticesDataPresent=function(l){return this._sourceMesh.isVerticesDataPresent(l)},g.prototype.getIndices=function(){return this._sourceMesh.getIndices()},Object.defineProperty(g.prototype,"_positions",{get:function(){return this._sourceMesh._positions},enumerable:!1,configurable:!0}),g.prototype.refreshBoundingInfo=function(l){if(l===void 0&&(l=!1),this._boundingInfo&&this._boundingInfo.isLocked)return this;var h=this._sourceMesh.geometry?this._sourceMesh.geometry.boundingBias:null;return this._refreshBoundingInfo(this._sourceMesh._getPositionData(l),h),this},g.prototype._preActivate=function(){return this._currentLOD&&this._currentLOD._preActivate(),this},g.prototype._activate=function(l,h){if(this._sourceMesh.subMeshes||x.a.Warn("Instances should only be created for meshes with geometry."),this._currentLOD){if(this._currentLOD._getWorldMatrixDeterminant()>0!=this._getWorldMatrixDeterminant()>0)return this._internalAbstractMeshDataInfo._actAsRegularMesh=!0,!0;if(this._internalAbstractMeshDataInfo._actAsRegularMesh=!1,this._currentLOD._registerInstanceForRenderId(this,l),h){if(!this._currentLOD._internalAbstractMeshDataInfo._isActiveIntermediate)return this._currentLOD._internalAbstractMeshDataInfo._onlyForInstancesIntermediate=!0,!0}else if(!this._currentLOD._internalAbstractMeshDataInfo._isActive)return this._currentLOD._internalAbstractMeshDataInfo._onlyForInstances=!0,!0}return!1},g.prototype._postActivate=function(){this._sourceMesh.edgesShareWithInstances&&this._sourceMesh._edgesRenderer&&this._sourceMesh._edgesRenderer.isEnabled&&this._sourceMesh._renderingGroup?(this._sourceMesh._renderingGroup._edgesRenderers.pushNoDuplicate(this._sourceMesh._edgesRenderer),this._sourceMesh._edgesRenderer.customInstances.push(this.getWorldMatrix())):this._edgesRenderer&&this._edgesRenderer.isEnabled&&this._sourceMesh._renderingGroup&&this._sourceMesh._renderingGroup._edgesRenderers.push(this._edgesRenderer)},g.prototype.getWorldMatrix=function(){if(this._currentLOD&&this._currentLOD.billboardMode!==C.a.BILLBOARDMODE_NONE&&this._currentLOD._masterMesh!==this){var l=this._currentLOD._masterMesh;return this._currentLOD._masterMesh=this,_.c.Vector3[7].copyFrom(this._currentLOD.position),this._currentLOD.position.set(0,0,0),_.c.Matrix[0].copyFrom(this._currentLOD.computeWorldMatrix(!0)),this._currentLOD.position.copyFrom(_.c.Vector3[7]),this._currentLOD._masterMesh=l,_.c.Matrix[0]}return S.prototype.getWorldMatrix.call(this)},Object.defineProperty(g.prototype,"isAnInstance",{get:function(){return!0},enumerable:!1,configurable:!0}),g.prototype.getLOD=function(l){if(!l)return this;var h=this.getBoundingInfo();return this._currentLOD=this.sourceMesh.getLOD(l,h.boundingSphere),this._currentLOD===this.sourceMesh?this.sourceMesh:this._currentLOD},g.prototype._preActivateForIntermediateRendering=function(l){return this.sourceMesh._preActivateForIntermediateRendering(l)},g.prototype._syncSubMeshes=function(){if(this.releaseSubMeshes(),this._sourceMesh.subMeshes)for(var l=0;l<this._sourceMesh.subMeshes.length;l++)this._sourceMesh.subMeshes[l].clone(this,this._sourceMesh);return this},g.prototype._generatePointsArray=function(){return this._sourceMesh._generatePointsArray()},g.prototype._updateBoundingInfo=function(){return this._boundingInfo?this._boundingInfo.update(this.worldMatrixFromCache):this._boundingInfo=new c.a(this.absolutePosition,this.absolutePosition,this.worldMatrixFromCache),this._updateSubMeshesBoundingInfo(this.worldMatrixFromCache),this},g.prototype.clone=function(l,h,v){h===void 0&&(h=null);var E=this._sourceMesh.createInstance(l);if(R.a.DeepCopy(this,E,["name","subMeshes","uniqueId","parent","lightSources","receiveShadows","material","visibility","skeleton","sourceMesh","isAnInstance","facetNb","isFacetDataEnabled","isBlocked","useBones","hasInstances","collider","edgesRenderer","forward","up","right","absolutePosition","absoluteScaling","absoluteRotationQuaternion","isWorldMatrixFrozen","nonUniformScaling","behaviors","worldMatrixFromCache","hasThinInstances"],[]),this.refreshBoundingInfo(),h&&(E.parent=h),!v)for(var D=0;D<this.getScene().meshes.length;D++){var w=this.getScene().meshes[D];w.parent===this&&w.clone(w.name,E)}return E.computeWorldMatrix(!0),E},g.prototype.dispose=function(l,h){h===void 0&&(h=!1),this._sourceMesh.removeInstance(this),S.prototype.dispose.call(this,l,h)},g}(u.a);M.a.prototype.edgesShareWithInstances=!1,M.a.prototype.registerInstancedBuffer=function(S,g){if(this.removeVerticesData(S),!this.instancedBuffers){this.instancedBuffers={};for(var l=0,h=this.instances;l<h.length;l++)h[l].instancedBuffers={};this._userInstancedBuffersStorage={data:{},vertexBuffers:{},strides:{},sizes:{}}}this.instancedBuffers[S]=null,this._userInstancedBuffersStorage.strides[S]=g,this._userInstancedBuffersStorage.sizes[S]=32*g,this._userInstancedBuffersStorage.data[S]=new Float32Array(this._userInstancedBuffersStorage.sizes[S]),this._userInstancedBuffersStorage.vertexBuffers[S]=new 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-{
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-#endif
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-float ndl;
-#endif
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R(C){this._completePromises=new Array,this._forAssetContainer=!1,this._babylonLights=[],this._disableInstancedMesh=0,this._disposed=!1,this._state=null,this._extensions=new Array,this._defaultBabylonMaterialData={},this._parent=C}return R.RegisterExtension=function(C,m){R.UnregisterExtension(C)&&_.Logger.Warn("Extension with the name '"+C+"' already exists"),R._RegisteredExtensions[C]={factory:m}},R.UnregisterExtension=function(C){return!!R._RegisteredExtensions[C]&&(delete R._RegisteredExtensions[C],!0)},Object.defineProperty(R.prototype,"state",{get:function(){return this._state},enumerable:!1,configurable:!0}),Object.defineProperty(R.prototype,"gltf",{get:function(){return this._gltf},enumerable:!1,configurable:!0}),Object.defineProperty(R.prototype,"bin",{get:function(){return this._bin},enumerable:!1,configurable:!0}),Object.defineProperty(R.prototype,"parent",{get:function(){return this._parent},enumerable:!1,configurable:!0}),Object.defineProperty(R.prototype,"babylonScene",{get:function(){return this._babylonScene},enumerable:!1,configurable:!0}),Object.defineProperty(R.prototype,"rootBabylonMesh",{get:function(){return this._rootBabylonMesh},enumerable:!1,configurable:!0}),R.prototype.dispose=function(){if(!this._disposed){for(var C in this._disposed=!0,this._completePromises.length=0,this._extensions){var m=this._extensions[C];m.dispose&&m.dispose(),delete this._extensions[C]}this._gltf=null,this._babylonScene=null,this._rootBabylonMesh=null,this._parent.dispose()}},R.prototype.importMeshAsync=function(C,m,c,T,A,S,g){var l=this;return Promise.resolve().then(function(){l._babylonScene=m,l._rootUrl=A,l._fileName=g||"scene",l._forAssetContainer=c,l._loadData(T);var h=null;if(C){var v={};if(l._gltf.nodes)for(var E=0,D=l._gltf.nodes;E<D.length;E++){var w=D[E];w.name&&(v[w.name]=w.index)}h=(C instanceof Array?C:[C]).map(function(N){var I=v[N];if(I===void 0)throw new Error("Failed to find node '"+N+"'");return I})}return l._loadAsync(h,function(){return{meshes:l._getMeshes(),particleSystems:[],skeletons:l._getSkeletons(),animationGroups:l._getAnimationGroups(),lights:l._babylonLights,transformNodes:l._getTransformNodes(),geometries:l._getGeometries()}})})},R.prototype.loadAsync=function(C,m,c,T,A){var S=this;return Promise.resolve().then(function(){return S._babylonScene=C,S._rootUrl=c,S._fileName=A||"scene",S._loadData(m),S._loadAsync(null,function(){})})},R.prototype._loadAsync=function(C,m){var c=this;return Promise.resolve().then(function(){c._uniqueRootUrl=c._rootUrl.indexOf("file:")===-1&&c._fileName?c._rootUrl:""+c._rootUrl+Date.now()+"/",c._loadExtensions(),c._checkExtensions();var T=x.GLTFLoaderState[x.GLTFLoaderState.LOADING]+" => "+x.GLTFLoaderState[x.GLTFLoaderState.READY],A=x.GLTFLoaderState[x.GLTFLoaderState.LOADING]+" => "+x.GLTFLoaderState[x.GLTFLoaderState.COMPLETE];c._parent._startPerformanceCounter(T),c._parent._startPerformanceCounter(A),c._setState(x.GLTFLoaderState.LOADING),c._extensionsOnLoading();var S=new Array,g=c._babylonScene.blockMaterialDirtyMechanism;if(c._babylonScene.blockMaterialDirtyMechanism=!0,C)S.push(c.loadSceneAsync("/nodes",{nodes:C,index:-1}));else if(c._gltf.scene!=null||c._gltf.scenes&&c._gltf.scenes[0]){var l=u.Get("/scene",c._gltf.scenes,c._gltf.scene||0);S.push(c.loadSceneAsync("/scenes/"+l.index,l))}if(c.parent.loadAllMaterials&&c._gltf.materials)for(var h=0;h<c._gltf.materials.length;++h){var v=c._gltf.materials[h],E="/materials/"+h,D=_.Material.TriangleFillMode;S.push(c._loadMaterialAsync(E,v,null,D,function(N){}))}c._babylonScene.blockMaterialDirtyMechanism=g,c._parent.compileMaterials&&S.push(c._compileMaterialsAsync()),c._parent.compileShadowGenerators&&S.push(c._compileShadowGeneratorsAsync());var w=Promise.all(S).then(function(){return c._rootBabylonMesh&&c._rootBabylonMesh.setEnabled(!0),c._extensionsOnReady(),c._setState(x.GLTFLoaderState.READY),c._startAnimations(),m()});return w.then(function(){c._parent._endPerformanceCounter(T),_.Tools.SetImmediate(function(){c._disposed||Promise.all(c._completePromises).then(function(){c._parent._endPerformanceCounter(A),c._setState(x.GLTFLoaderState.COMPLETE),c._parent.onCompleteObservable.notifyObservers(void 0),c._parent.onCompleteObservable.clear(),c.dispose()},function(N){c._parent.onErrorObservable.notifyObservers(N),c._parent.onErrorObservable.clear(),c.dispose()})})}),w}).catch(function(T){throw c._disposed||(c._parent.onErrorObservable.notifyObservers(T),c._parent.onErrorObservable.clear(),c.dispose()),T})},R.prototype._loadData=function(C){if(this._gltf=C.json,this._setupData(),C.bin){var m=this._gltf.buffers;if(m&&m[0]&&!m[0].uri){var c=m[0];(c.byteLength<C.bin.byteLength-3||c.byteLength>C.bin.byteLength)&&_.Logger.Warn("Binary buffer length ("+c.byteLength+") from JSON does not match chunk length ("+C.bin.byteLength+")"),this._bin=C.bin}else _.Logger.Warn("Unexpected BIN chunk")}},R.prototype._setupData=function(){if(u.Assign(this._gltf.accessors),u.Assign(this._gltf.animations),u.Assign(this._gltf.buffers),u.Assign(this._gltf.bufferViews),u.Assign(this._gltf.cameras),u.Assign(this._gltf.images),u.Assign(this._gltf.materials),u.Assign(this._gltf.meshes),u.Assign(this._gltf.nodes),u.Assign(this._gltf.samplers),u.Assign(this._gltf.scenes),u.Assign(this._gltf.skins),u.Assign(this._gltf.textures),this._gltf.nodes){for(var C={},m=0,c=this._gltf.nodes;m<c.length;m++)if((h=c[m]).children)for(var T=0,A=h.children;T<A.length;T++)C[A[T]]=h.index;for(var S=this._createRootNode(),g=0,l=this._gltf.nodes;g<l.length;g++){var h,v=C[(h=l[g]).index];h.parent=v===void 0?S:this._gltf.nodes[v]}}},R.prototype._loadExtensions=function(){for(var C in R._RegisteredExtensions){var m=R._RegisteredExtensions[C].factory(this);m.name!==C&&_.Logger.Warn("The name of the glTF loader extension instance does not match the registered name: "+m.name+" !== "+C),this._extensions.push(m),this._parent.onExtensionLoadedObservable.notifyObservers(m)}this._extensions.sort(function(c,T){return(c.order||Number.MAX_VALUE)-(T.order||Number.MAX_VALUE)}),this._parent.onExtensionLoadedObservable.clear()},R.prototype._checkExtensions=function(){if(this._gltf.extensionsRequired)for(var C=function(A){if(!m._extensions.some(function(S){return S.name===A&&S.enabled}))throw new Error("Require extension "+A+" is not available")},m=this,c=0,T=this._gltf.extensionsRequired;c<T.length;c++)C(T[c])},R.prototype._setState=function(C){this._state=C,this.log(x.GLTFLoaderState[this._state])},R.prototype._createRootNode=function(){this._babylonScene._blockEntityCollection=this._forAssetContainer,this._rootBabylonMesh=new _.Mesh("__root__",this._babylonScene),this._babylonScene._blockEntityCollection=!1,this._rootBabylonMesh.setEnabled(!1);var C={_babylonTransformNode:this._rootBabylonMesh,index:-1};switch(this._parent.coordinateSystemMode){case x.GLTFLoaderCoordinateSystemMode.AUTO:this._babylonScene.useRightHandedSystem||(C.rotation=[0,1,0,0],C.scale=[1,1,-1],R._LoadTransform(C,this._rootBabylonMesh));break;case x.GLTFLoaderCoordinateSystemMode.FORCE_RIGHT_HANDED:this._babylonScene.useRightHandedSystem=!0;break;default:throw new Error("Invalid coordinate system mode ("+this._parent.coordinateSystemMode+")")}return this._parent.onMeshLoadedObservable.notifyObservers(this._rootBabylonMesh),C},R.prototype.loadSceneAsync=function(C,m){var c=this,T=this._extensionsLoadSceneAsync(C,m);if(T)return T;var A=new Array;if(this.logOpen(C+" "+(m.name||"")),m.nodes)for(var S=0,g=m.nodes;S<g.length;S++){var l=g[S],h=u.Get(C+"/nodes/"+l,this._gltf.nodes,l);A.push(this.loadNodeAsync("/nodes/"+h.index,h,function(N){N.parent=c._rootBabylonMesh}))}if(this._gltf.nodes){for(var v=0,E=this._gltf.nodes;v<E.length;v++)if((h=E[v])._babylonTransformNode&&h._babylonBones)for(var D=0,w=h._babylonBones;D<w.length;D++)w[D].linkTransformNode(h._babylonTransformNode)}return A.push(this._loadAnimationsAsync()),this.logClose(),Promise.all(A).then(function(){})},R.prototype._forEachPrimitive=function(C,m){if(C._primitiveBabylonMeshes)for(var c=0,T=C._primitiveBabylonMeshes;c<T.length;c++)m(T[c])},R.prototype._getGeometries=function(){var C=new Array,m=this._gltf.nodes;if(m)for(var c=0,T=m;c<T.length;c++){var A=T[c];this._forEachPrimitive(A,function(S){var g=S.geometry;g&&C.indexOf(g)===-1&&C.push(g)})}return C},R.prototype._getMeshes=function(){var C=new Array;C.push(this._rootBabylonMesh);var m=this._gltf.nodes;if(m)for(var c=0,T=m;c<T.length;c++){var A=T[c];this._forEachPrimitive(A,function(S){C.push(S)})}return C},R.prototype._getTransformNodes=function(){var C=new Array,m=this._gltf.nodes;if(m)for(var c=0,T=m;c<T.length;c++){var A=T[c];A._babylonTransformNode&&A._babylonTransformNode.getClassName()==="TransformNode"&&C.push(A._babylonTransformNode)}return C},R.prototype._getSkeletons=function(){var C=new Array,m=this._gltf.skins;if(m)for(var c=0,T=m;c<T.length;c++){var A=T[c];A._data&&C.push(A._data.babylonSkeleton)}return C},R.prototype._getAnimationGroups=function(){var C=new Array,m=this._gltf.animations;if(m)for(var c=0,T=m;c<T.length;c++){var A=T[c];A._babylonAnimationGroup&&C.push(A._babylonAnimationGroup)}return C},R.prototype._startAnimations=function(){switch(this._parent.animationStartMode){case x.GLTFLoaderAnimationStartMode.NONE:break;case x.GLTFLoaderAnimationStartMode.FIRST:(C=this._getAnimationGroups()).length!==0&&C[0].start(!0);break;case x.GLTFLoaderAnimationStartMode.ALL:for(var C,m=0,c=C=this._getAnimationGroups();m<c.length;m++)c[m].start(!0);break;default:return void _.Logger.Error("Invalid animation start mode ("+this._parent.animationStartMode+")")}},R.prototype.loadNodeAsync=function(C,m,c){var T=this;c===void 0&&(c=function(){});var A=this._extensionsLoadNodeAsync(C,m,c);if(A)return A;if(m._babylonTransformNode)throw new Error(C+": Invalid recursive node hierarchy");var S=new Array;this.logOpen(C+" "+(m.name||""));var g=function(v){if(R.AddPointerMetadata(v,C),R._LoadTransform(m,v),m.camera!=null){var E=u.Get(C+"/camera",T._gltf.cameras,m.camera);S.push(T.loadCameraAsync("/cameras/"+E.index,E,function(V){V.parent=v}))}if(m.children)for(var D=0,w=m.children;D<w.length;D++){var N=w[D],I=u.Get(C+"/children/"+N,T._gltf.nodes,N);S.push(T.loadNodeAsync("/nodes/"+I.index,I,function(V){V.parent=v}))}c(v)};if(m.mesh==null){var l=m.name||"node"+m.index;this._babylonScene._blockEntityCollection=this._forAssetContainer,m._babylonTransformNode=new _.TransformNode(l,this._babylonScene),this._babylonScene._blockEntityCollection=!1,g(m._babylonTransformNode)}else{var h=u.Get(C+"/mesh",this._gltf.meshes,m.mesh);S.push(this._loadMeshAsync("/meshes/"+h.index,m,h,g))}return this.logClose(),Promise.all(S).then(function(){return T._forEachPrimitive(m,function(v){v.geometry&&v.geometry.useBoundingInfoFromGeometry?v._updateBoundingInfo():v.refreshBoundingInfo(!0)}),m._babylonTransformNode})},R.prototype._loadMeshAsync=function(C,m,c,T){var A=c.primitives;if(!A||!A.length)throw new Error(C+": Primitives are missing");A[0].index==null&&u.Assign(A);var S=new Array;this.logOpen(C+" "+(c.name||""));var g=m.name||"node"+m.index;if(A.length===1){var l=c.primitives[0];S.push(this._loadMeshPrimitiveAsync(C+"/primitives/"+l.index,g,m,c,l,function(D){m._babylonTransformNode=D,m._primitiveBabylonMeshes=[D]}))}else{this._babylonScene._blockEntityCollection=this._forAssetContainer,m._babylonTransformNode=new _.TransformNode(g,this._babylonScene),this._babylonScene._blockEntityCollection=!1,m._primitiveBabylonMeshes=[];for(var h=0,v=A;h<v.length;h++)l=v[h],S.push(this._loadMeshPrimitiveAsync(C+"/primitives/"+l.index,g+"_primitive"+l.index,m,c,l,function(D){D.parent=m._babylonTransformNode,m._primitiveBabylonMeshes.push(D)}))}if(m.skin!=null){var E=u.Get(C+"/skin",this._gltf.skins,m.skin);S.push(this._loadSkinAsync("/skins/"+E.index,m,E))}return T(m._babylonTransformNode),this.logClose(),Promise.all(S).then(function(){return m._babylonTransformNode})},R.prototype._loadMeshPrimitiveAsync=function(C,m,c,T,A,S){var g=this,l=this._extensionsLoadMeshPrimitiveAsync(C,m,c,T,A,S);if(l)return l;this.logOpen(""+C);var h,v,E=this._disableInstancedMesh===0&&this._parent.createInstances&&c.skin==null&&!T.primitives[0].targets;if(E&&A._instanceData)h=A._instanceData.babylonSourceMesh.createInstance(m),v=A._instanceData.promise;else{var D=new Array;this._babylonScene._blockEntityCollection=this._forAssetContainer;var w=new _.Mesh(m,this._babylonScene);this._babylonScene._blockEntityCollection=!1,w.overrideMaterialSideOrientation=this._babylonScene.useRightHandedSystem?_.Material.CounterClockWiseSideOrientation:_.Material.ClockWiseSideOrientation,this._createMorphTargets(C,c,T,A,w),D.push(this._loadVertexDataAsync(C,A,w).then(function(X){return g._loadMorphTargetsAsync(C,A,w,X).then(function(){g._babylonScene._blockEntityCollection=g._forAssetContainer,X.applyToMesh(w),g._babylonScene._blockEntityCollection=!1})}));var N=R._GetDrawMode(C,A.mode);if(A.material==null){var I=this._defaultBabylonMaterialData[N];I||(I=this._createDefaultMaterial("__GLTFLoader._default",N),this._parent.onMaterialLoadedObservable.notifyObservers(I),this._defaultBabylonMaterialData[N]=I),w.material=I}else{var V=u.Get(C+"/material",this._gltf.materials,A.material);D.push(this._loadMaterialAsync("/materials/"+V.index,V,w,N,function(X){w.material=X}))}v=Promise.all(D),E&&(A._instanceData={babylonSourceMesh:w,promise:v}),h=w}return R.AddPointerMetadata(h,C),this._parent.onMeshLoadedObservable.notifyObservers(h),S(h),this.logClose(),v.then(function(){return h})},R.prototype._loadVertexDataAsync=function(C,m,c){var T=this,A=this._extensionsLoadVertexDataAsync(C,m,c);if(A)return A;var S=m.attributes;if(!S)throw new Error(C+": Attributes are missing");var g=new Array,l=new _.Geometry(c.name,this._babylonScene);if(m.indices==null)c.isUnIndexed=!0;else{var h=u.Get(C+"/indices",this._gltf.accessors,m.indices);g.push(this._loadIndicesAccessorAsync("/accessors/"+h.index,h).then(function(E){l.setIndices(E)}))}var v=function(E,D,w){if(S[E]!=null){c._delayInfo=c._delayInfo||[],c._delayInfo.indexOf(D)===-1&&c._delayInfo.push(D);var N=u.Get(C+"/attributes/"+E,T._gltf.accessors,S[E]);g.push(T._loadVertexAccessorAsync("/accessors/"+N.index,N,D).then(function(I){if(I.getKind()===_.VertexBuffer.PositionKind&&!T.parent.alwaysComputeBoundingBox&&!c.skeleton){var V=N.min,X=N.max;if(V!==void 0&&X!==void 0){var j=_.TmpVectors.Vector3[0],ne=_.TmpVectors.Vector3[1];j.copyFromFloats.apply(j,V),ne.copyFromFloats.apply(ne,X),l._boundingInfo=new _.BoundingInfo(j,ne),l.useBoundingInfoFromGeometry=!0}}l.setVerticesBuffer(I,N.count)})),D==_.VertexBuffer.MatricesIndicesExtraKind&&(c.numBoneInfluencers=8),w&&w(N)}};return v("POSITION",_.VertexBuffer.PositionKind),v("NORMAL",_.VertexBuffer.NormalKind),v("TANGENT",_.VertexBuffer.TangentKind),v("TEXCOORD_0",_.VertexBuffer.UVKind),v("TEXCOORD_1",_.VertexBuffer.UV2Kind),v("JOINTS_0",_.VertexBuffer.MatricesIndicesKind),v("WEIGHTS_0",_.VertexBuffer.MatricesWeightsKind),v("JOINTS_1",_.VertexBuffer.MatricesIndicesExtraKind),v("WEIGHTS_1",_.VertexBuffer.MatricesWeightsExtraKind),v("COLOR_0",_.VertexBuffer.ColorKind,function(E){E.type==="VEC4"&&(c.hasVertexAlpha=!0)}),Promise.all(g).then(function(){return l})},R.prototype._createMorphTargets=function(C,m,c,T,A){if(T.targets){if(m._numMorphTargets==null)m._numMorphTargets=T.targets.length;else if(T.targets.length!==m._numMorphTargets)throw new Error(C+": Primitives do not have the same number of targets");var S=c.extras?c.extras.targetNames:null;A.morphTargetManager=new _.MorphTargetManager(A.getScene());for(var g=0;g<T.targets.length;g++){var l=m.weights?m.weights[g]:c.weights?c.weights[g]:0,h=S?S[g]:"morphTarget"+g;A.morphTargetManager.addTarget(new _.MorphTarget(h,l,A.getScene()))}}},R.prototype._loadMorphTargetsAsync=function(C,m,c,T){if(!m.targets)return Promise.resolve();for(var A=new Array,S=c.morphTargetManager,g=0;g<S.numTargets;g++){var l=S.getTarget(g);A.push(this._loadMorphTargetVertexDataAsync(C+"/targets/"+g,T,m.targets[g],l))}return Promise.all(A).then(function(){})},R.prototype._loadMorphTargetVertexDataAsync=function(C,m,c,T){var A=this,S=new Array,g=function(l,h,v){if(c[l]!=null){var E=m.getVertexBuffer(h);if(E){var D=u.Get(C+"/"+l,A._gltf.accessors,c[l]);S.push(A._loadFloatAccessorAsync("/accessors/"+D.index,D).then(function(w){v(E,w)}))}}};return g("POSITION",_.VertexBuffer.PositionKind,function(l,h){var v=new Float32Array(h.length);l.forEach(h.length,function(E,D){v[D]=h[D]+E}),T.setPositions(v)}),g("NORMAL",_.VertexBuffer.NormalKind,function(l,h){var v=new Float32Array(h.length);l.forEach(v.length,function(E,D){v[D]=h[D]+E}),T.setNormals(v)}),g("TANGENT",_.VertexBuffer.TangentKind,function(l,h){var v=new Float32Array(h.length/3*4),E=0;l.forEach(h.length/3*4,function(D,w){(w+1)%4!=0&&(v[E]=h[E]+D,E++)}),T.setTangents(v)}),Promise.all(S).then(function(){})},R._LoadTransform=function(C,m){if(C.skin==null){var c=_.Vector3.Zero(),T=_.Quaternion.Identity(),A=_.Vector3.One();C.matrix?_.Matrix.FromArray(C.matrix).decompose(A,T,c):(C.translation&&(c=_.Vector3.FromArray(C.translation)),C.rotation&&(T=_.Quaternion.FromArray(C.rotation)),C.scale&&(A=_.Vector3.FromArray(C.scale))),m.position=c,m.rotationQuaternion=T,m.scaling=A}},R.prototype._loadSkinAsync=function(C,m,c){var T=this,A=this._extensionsLoadSkinAsync(C,m,c);if(A)return A;var S=function(v){T._forEachPrimitive(m,function(E){E.skeleton=v})};if(c._data)return S(c._data.babylonSkeleton),c._data.promise;var g="skeleton"+c.index;this._babylonScene._blockEntityCollection=this._forAssetContainer;var l=new _.Skeleton(c.name||g,g,this._babylonScene);this._babylonScene._blockEntityCollection=!1,l.overrideMesh=this._rootBabylonMesh,this._loadBones(C,c,l),S(l);var h=this._loadSkinInverseBindMatricesDataAsync(C,c).then(function(v){T._updateBoneMatrices(l,v)});return c._data={babylonSkeleton:l,promise:h},h},R.prototype._loadBones=function(C,m,c){for(var T={},A=0,S=m.joints;A<S.length;A++){var g=S[A],l=u.Get(C+"/joints/"+g,this._gltf.nodes,g);this._loadBone(l,m,c,T)}},R.prototype._loadBone=function(C,m,c,T){var A=T[C.index];if(A)return A;var S=null;C.parent&&C.parent._babylonTransformNode!==this._rootBabylonMesh&&(S=this._loadBone(C.parent,m,c,T));var g=m.joints.indexOf(C.index);return A=new _.Bone(C.name||"joint"+C.index,c,S,this._getNodeMatrix(C),null,null,g),T[C.index]=A,C._babylonBones=C._babylonBones||[],C._babylonBones.push(A),A},R.prototype._loadSkinInverseBindMatricesDataAsync=function(C,m){if(m.inverseBindMatrices==null)return Promise.resolve(null);var c=u.Get(C+"/inverseBindMatrices",this._gltf.accessors,m.inverseBindMatrices);return this._loadFloatAccessorAsync("/accessors/"+c.index,c)},R.prototype._updateBoneMatrices=function(C,m){for(var c=0,T=C.bones;c<T.length;c++){var A=T[c],S=_.Matrix.Identity(),g=A._index;m&&g!==-1&&(_.Matrix.FromArrayToRef(m,16*g,S),S.invertToRef(S));var l=A.getParent();l&&S.multiplyToRef(l.getInvertedAbsoluteTransform(),S),A.setBindPose(S),A.updateMatrix(S,!1,!1),A._updateDifferenceMatrix(void 0,!1)}},R.prototype._getNodeMatrix=function(C){return C.matrix?_.Matrix.FromArray(C.matrix):_.Matrix.Compose(C.scale?_.Vector3.FromArray(C.scale):_.Vector3.One(),C.rotation?_.Quaternion.FromArray(C.rotation):_.Quaternion.Identity(),C.translation?_.Vector3.FromArray(C.translation):_.Vector3.Zero())},R.prototype.loadCameraAsync=function(C,m,c){c===void 0&&(c=function(){});var T=this._extensionsLoadCameraAsync(C,m,c);if(T)return T;var A=new Array;this.logOpen(C+" "+(m.name||"")),this._babylonScene._blockEntityCollection=this._forAssetContainer;var S=new _.FreeCamera(m.name||"camera"+m.index,_.Vector3.Zero(),this._babylonScene,!1);switch(this._babylonScene._blockEntityCollection=!1,S.ignoreParentScaling=!0,S.rotation=new _.Vector3(0,Math.PI,0),m.type){case"perspective":var g=m.perspective;if(!g)throw new Error(C+": Camera perspective properties are missing");S.fov=g.yfov,S.minZ=g.znear,S.maxZ=g.zfar||Number.MAX_VALUE;break;case"orthographic":if(!m.orthographic)throw new Error(C+": Camera orthographic properties are missing");S.mode=_.Camera.ORTHOGRAPHIC_CAMERA,S.orthoLeft=-m.orthographic.xmag,S.orthoRight=m.orthographic.xmag,S.orthoBottom=-m.orthographic.ymag,S.orthoTop=m.orthographic.ymag,S.minZ=m.orthographic.znear,S.maxZ=m.orthographic.zfar;break;default:throw new Error(C+": Invalid camera type ("+m.type+")")}return R.AddPointerMetadata(S,C),this._parent.onCameraLoadedObservable.notifyObservers(S),c(S),this.logClose(),Promise.all(A).then(function(){return S})},R.prototype._loadAnimationsAsync=function(){var C=this._gltf.animations;if(!C)return Promise.resolve();for(var m=new Array,c=0;c<C.length;c++){var T=C[c];m.push(this.loadAnimationAsync("/animations/"+T.index,T))}return Promise.all(m).then(function(){})},R.prototype.loadAnimationAsync=function(C,m){var c=this._extensionsLoadAnimationAsync(C,m);if(c)return c;this._babylonScene._blockEntityCollection=this._forAssetContainer;var T=new _.AnimationGroup(m.name||"animation"+m.index,this._babylonScene);this._babylonScene._blockEntityCollection=!1,m._babylonAnimationGroup=T;var A=new Array;u.Assign(m.channels),u.Assign(m.samplers);for(var S=0,g=m.channels;S<g.length;S++){var l=g[S];A.push(this._loadAnimationChannelAsync(C+"/channels/"+l.index,C,m,l,T))}return Promise.all(A).then(function(){return T.normalize(0),T})},R.prototype._loadAnimationChannelAsync=function(C,m,c,T,A,S){var g=this;if(S===void 0&&(S=null),T.target.node==null)return Promise.resolve();var l=u.Get(C+"/target/node",this._gltf.nodes,T.target.node);if(T.target.path==="weights"&&!l._numMorphTargets||T.target.path!=="weights"&&!l._babylonTransformNode)return Promise.resolve();var h=u.Get(C+"/sampler",c.samplers,T.sampler);return this._loadAnimationSamplerAsync(m+"/samplers/"+T.sampler,h).then(function(v){var E,D;switch(T.target.path){case"translation":E="position",D=_.Animation.ANIMATIONTYPE_VECTOR3;break;case"rotation":E="rotationQuaternion",D=_.Animation.ANIMATIONTYPE_QUATERNION;break;case"scale":E="scaling",D=_.Animation.ANIMATIONTYPE_VECTOR3;break;case"weights":E="influence",D=_.Animation.ANIMATIONTYPE_FLOAT;break;default:throw new Error(C+"/target/path: Invalid value ("+T.target.path+")")}var w,N,I=0;switch(E){case"position":w=function(){var pe=_.Vector3.FromArray(v.output,I);return I+=3,pe};break;case"rotationQuaternion":w=function(){var pe=_.Quaternion.FromArray(v.output,I);return I+=4,pe};break;case"scaling":w=function(){var pe=_.Vector3.FromArray(v.output,I);return I+=3,pe};break;case"influence":w=function(){for(var pe=new Array(l._numMorphTargets),ae=0;ae<l._numMorphTargets;ae++)pe[ae]=v.output[I++];return pe}}switch(v.interpolation){case"STEP":N=function(pe){return{frame:v.input[pe],value:w(),interpolation:_.AnimationKeyInterpolation.STEP}};break;case"LINEAR":N=function(pe){return{frame:v.input[pe],value:w()}};break;case"CUBICSPLINE":N=function(pe){return{frame:v.input[pe],inTangent:w(),value:w(),outTangent:w()}}}for(var V=new Array(v.input.length),X=0;X<v.input.length;X++)V[X]=N(X);if(E==="influence")for(var j=function(pe){var ae=A.name+"_channel"+A.targetedAnimations.length,ee=new _.Animation(ae,E,1,D);ee.setKeys(V.map(function(K){return{frame:K.frame,inTangent:K.inTangent?K.inTangent[pe]:void 0,value:K.value[pe],outTangent:K.outTangent?K.outTangent[pe]:void 0}})),g._forEachPrimitive(l,function(K){var $=K.morphTargetManager.getTarget(pe),L=ee.clone();$.animations.push(L),A.addTargetedAnimation(L,$)})},ne=0;ne<l._numMorphTargets;ne++)j(ne);else{var te=A.name+"_channel"+A.targetedAnimations.length,de=new _.Animation(te,E,1,D);de.setKeys(V),S!=null&&S.animations!=null?(S.animations.push(de),A.addTargetedAnimation(de,S)):(l._babylonTransformNode.animations.push(de),A.addTargetedAnimation(de,l._babylonTransformNode))}})},R.prototype._loadAnimationSamplerAsync=function(C,m){if(m._data)return m._data;var c=m.interpolation||"LINEAR";switch(c){case"STEP":case"LINEAR":case"CUBICSPLINE":break;default:throw new Error(C+"/interpolation: Invalid value ("+m.interpolation+")")}var T=u.Get(C+"/input",this._gltf.accessors,m.input),A=u.Get(C+"/output",this._gltf.accessors,m.output);return m._data=Promise.all([this._loadFloatAccessorAsync("/accessors/"+T.index,T),this._loadFloatAccessorAsync("/accessors/"+A.index,A)]).then(function(S){var g=S[0],l=S[1];return{input:g,interpolation:c,output:l}}),m._data},R.prototype._loadBufferAsync=function(C,m,c,T){var A=this._extensionsLoadBufferAsync(C,m,c,T);if(A)return A;if(!m._data)if(m.uri)m._data=this.loadUriAsync(C+"/uri",m,m.uri);else{if(!this._bin)throw new Error(C+": Uri is missing or the binary glTF is missing its binary chunk");m._data=this._bin.readAsync(0,m.byteLength)}return m._data.then(function(S){try{return new Uint8Array(S.buffer,S.byteOffset+c,T)}catch(g){throw new Error(C+": "+g.message)}})},R.prototype.loadBufferViewAsync=function(C,m){var c=this._extensionsLoadBufferViewAsync(C,m);if(c)return c;if(m._data)return m._data;var T=u.Get(C+"/buffer",this._gltf.buffers,m.buffer);return m._data=this._loadBufferAsync("/buffers/"+T.index,T,m.byteOffset||0,m.byteLength),m._data},R.prototype._loadAccessorAsync=function(C,m,c){var T=this;if(m._data)return m._data;var A=R._GetNumComponents(C,m.type),S=A*_.VertexBuffer.GetTypeByteLength(m.componentType),g=A*m.count;if(m.bufferView==null)m._data=Promise.resolve(new c(g));else{var l=u.Get(C+"/bufferView",this._gltf.bufferViews,m.bufferView);m._data=this.loadBufferViewAsync("/bufferViews/"+l.index,l).then(function(v){if(m.componentType!==5126||m.normalized||l.byteStride&&l.byteStride!==S){var E=new c(g);return _.VertexBuffer.ForEach(v,m.byteOffset||0,l.byteStride||S,A,m.componentType,E.length,m.normalized||!1,function(D,w){E[w]=D}),E}return R._GetTypedArray(C,m.componentType,v,m.byteOffset,g)})}if(m.sparse){var h=m.sparse;m._data=m._data.then(function(v){var E=v,D=u.Get(C+"/sparse/indices/bufferView",T._gltf.bufferViews,h.indices.bufferView),w=u.Get(C+"/sparse/values/bufferView",T._gltf.bufferViews,h.values.bufferView);return Promise.all([T.loadBufferViewAsync("/bufferViews/"+D.index,D),T.loadBufferViewAsync("/bufferViews/"+w.index,w)]).then(function(N){var I,V=N[0],X=N[1],j=R._GetTypedArray(C+"/sparse/indices",h.indices.componentType,V,h.indices.byteOffset,h.count),ne=A*h.count;if(m.componentType!==5126||m.normalized){var te=R._GetTypedArray(C+"/sparse/values",m.componentType,X,h.values.byteOffset,ne);I=new c(ne),_.VertexBuffer.ForEach(te,0,S,A,m.componentType,I.length,m.normalized||!1,function(K,$){I[$]=K})}else I=R._GetTypedArray(C+"/sparse/values",m.componentType,X,h.values.byteOffset,ne);for(var de=0,pe=0;pe<j.length;pe++)for(var ae=j[pe]*A,ee=0;ee<A;ee++)E[ae++]=I[de++];return E})})}return m._data},R.prototype._loadFloatAccessorAsync=function(C,m){return this._loadAccessorAsync(C,m,Float32Array)},R.prototype._loadIndicesAccessorAsync=function(C,m){if(m.type!=="SCALAR")throw new Error(C+"/type: Invalid value "+m.type);if(m.componentType!==5121&&m.componentType!==5123&&m.componentType!==5125)throw new Error(C+"/componentType: Invalid value "+m.componentType);if(m._data)return m._data;if(m.sparse){var c=R._GetTypedArrayConstructor(C+"/componentType",m.componentType);m._data=this._loadAccessorAsync(C,m,c)}else{var T=u.Get(C+"/bufferView",this._gltf.bufferViews,m.bufferView);m._data=this.loadBufferViewAsync("/bufferViews/"+T.index,T).then(function(A){return R._GetTypedArray(C,m.componentType,A,m.byteOffset,m.count)})}return m._data},R.prototype._loadVertexBufferViewAsync=function(C,m){var c=this;return C._babylonBuffer||(C._babylonBuffer=this.loadBufferViewAsync("/bufferViews/"+C.index,C).then(function(T){return new _.Buffer(c._babylonScene.getEngine(),T,!1)})),C._babylonBuffer},R.prototype._loadVertexAccessorAsync=function(C,m,c){var T=this;if(m._babylonVertexBuffer)return m._babylonVertexBuffer;if(m.sparse)m._babylonVertexBuffer=this._loadFloatAccessorAsync("/accessors/"+m.index,m).then(function(S){return new _.VertexBuffer(T._babylonScene.getEngine(),S,c,!1)});else if(m.byteOffset&&m.byteOffset%_.VertexBuffer.GetTypeByteLength(m.componentType)!=0)_.Logger.Warn("Accessor byte offset is not a multiple of component type byte length"),m._babylonVertexBuffer=this._loadFloatAccessorAsync("/accessors/"+m.index,m).then(function(S){return new _.VertexBuffer(T._babylonScene.getEngine(),S,c,!1)});else if(c===_.VertexBuffer.MatricesIndicesKind||c===_.VertexBuffer.MatricesIndicesExtraKind)m._babylonVertexBuffer=this._loadFloatAccessorAsync("/accessors/"+m.index,m).then(function(S){return new _.VertexBuffer(T._babylonScene.getEngine(),S,c,!1)});else{var A=u.Get(C+"/bufferView",this._gltf.bufferViews,m.bufferView);m._babylonVertexBuffer=this._loadVertexBufferViewAsync(A,c).then(function(S){var g=R._GetNumComponents(C,m.type);return new _.VertexBuffer(T._babylonScene.getEngine(),S,c,!1,!1,A.byteStride,!1,m.byteOffset,g,m.componentType,m.normalized,!0,1,!0)})}return m._babylonVertexBuffer},R.prototype._loadMaterialMetallicRoughnessPropertiesAsync=function(C,m,c){if(!(c instanceof _.PBRMaterial))throw new Error(C+": Material type not supported");var T=new Array;return m&&(m.baseColorFactor?(c.albedoColor=_.Color3.FromArray(m.baseColorFactor),c.alpha=m.baseColorFactor[3]):c.albedoColor=_.Color3.White(),c.metallic=m.metallicFactor==null?1:m.metallicFactor,c.roughness=m.roughnessFactor==null?1:m.roughnessFactor,m.baseColorTexture&&T.push(this.loadTextureInfoAsync(C+"/baseColorTexture",m.baseColorTexture,function(A){A.name=c.name+" (Base Color)",c.albedoTexture=A})),m.metallicRoughnessTexture&&(m.metallicRoughnessTexture.nonColorData=!0,T.push(this.loadTextureInfoAsync(C+"/metallicRoughnessTexture",m.metallicRoughnessTexture,function(A){A.name=c.name+" (Metallic Roughness)",c.metallicTexture=A})),c.useMetallnessFromMetallicTextureBlue=!0,c.useRoughnessFromMetallicTextureGreen=!0,c.useRoughnessFromMetallicTextureAlpha=!1)),Promise.all(T).then(function(){})},R.prototype._loadMaterialAsync=function(C,m,c,T,A){A===void 0&&(A=function(){});var S=this._extensionsLoadMaterialAsync(C,m,c,T,A);if(S)return S;m._data=m._data||{};var g=m._data[T];if(!g){this.logOpen(C+" "+(m.name||""));var l=this.createMaterial(C,m,T);g={babylonMaterial:l,babylonMeshes:[],promise:this.loadMaterialPropertiesAsync(C,m,l)},m._data[T]=g,R.AddPointerMetadata(l,C),this._parent.onMaterialLoadedObservable.notifyObservers(l),this.logClose()}return c&&(g.babylonMeshes.push(c),c.onDisposeObservable.addOnce(function(){var h=g.babylonMeshes.indexOf(c);h!==-1&&g.babylonMeshes.splice(h,1)})),A(g.babylonMaterial),g.promise.then(function(){return g.babylonMaterial})},R.prototype._createDefaultMaterial=function(C,m){this._babylonScene._blockEntityCollection=this._forAssetContainer;var c=new _.PBRMaterial(C,this._babylonScene);return this._babylonScene._blockEntityCollection=!1,c.fillMode=m,c.enableSpecularAntiAliasing=!0,c.useRadianceOverAlpha=!this._parent.transparencyAsCoverage,c.useSpecularOverAlpha=!this._parent.transparencyAsCoverage,c.transparencyMode=_.PBRMaterial.PBRMATERIAL_OPAQUE,c.metallic=1,c.roughness=1,c},R.prototype.createMaterial=function(C,m,c){var T=this._extensionsCreateMaterial(C,m,c);if(T)return T;var A=m.name||"material"+m.index;return this._createDefaultMaterial(A,c)},R.prototype.loadMaterialPropertiesAsync=function(C,m,c){var T=this._extensionsLoadMaterialPropertiesAsync(C,m,c);if(T)return T;var A=new Array;return A.push(this.loadMaterialBasePropertiesAsync(C,m,c)),m.pbrMetallicRoughness&&A.push(this._loadMaterialMetallicRoughnessPropertiesAsync(C+"/pbrMetallicRoughness",m.pbrMetallicRoughness,c)),this.loadMaterialAlphaProperties(C,m,c),Promise.all(A).then(function(){})},R.prototype.loadMaterialBasePropertiesAsync=function(C,m,c){if(!(c instanceof _.PBRMaterial))throw new Error(C+": Material type not supported");var T=new Array;return c.emissiveColor=m.emissiveFactor?_.Color3.FromArray(m.emissiveFactor):new _.Color3(0,0,0),m.doubleSided&&(c.backFaceCulling=!1,c.twoSidedLighting=!0),m.normalTexture&&(m.normalTexture.nonColorData=!0,T.push(this.loadTextureInfoAsync(C+"/normalTexture",m.normalTexture,function(A){A.name=c.name+" (Normal)",c.bumpTexture=A})),c.invertNormalMapX=!this._babylonScene.useRightHandedSystem,c.invertNormalMapY=this._babylonScene.useRightHandedSystem,m.normalTexture.scale!=null&&(c.bumpTexture.level=m.normalTexture.scale),c.forceIrradianceInFragment=!0),m.occlusionTexture&&(m.occlusionTexture.nonColorData=!0,T.push(this.loadTextureInfoAsync(C+"/occlusionTexture",m.occlusionTexture,function(A){A.name=c.name+" (Occlusion)",c.ambientTexture=A})),c.useAmbientInGrayScale=!0,m.occlusionTexture.strength!=null&&(c.ambientTextureStrength=m.occlusionTexture.strength)),m.emissiveTexture&&T.push(this.loadTextureInfoAsync(C+"/emissiveTexture",m.emissiveTexture,function(A){A.name=c.name+" (Emissive)",c.emissiveTexture=A})),Promise.all(T).then(function(){})},R.prototype.loadMaterialAlphaProperties=function(C,m,c){if(!(c instanceof _.PBRMaterial))throw new Error(C+": Material type not supported");switch(m.alphaMode||"OPAQUE"){case"OPAQUE":c.transparencyMode=_.PBRMaterial.PBRMATERIAL_OPAQUE;break;case"MASK":c.transparencyMode=_.PBRMaterial.PBRMATERIAL_ALPHATEST,c.alphaCutOff=m.alphaCutoff==null?.5:m.alphaCutoff,c.albedoTexture&&(c.albedoTexture.hasAlpha=!0);break;case"BLEND":c.transparencyMode=_.PBRMaterial.PBRMATERIAL_ALPHABLEND,c.albedoTexture&&(c.albedoTexture.hasAlpha=!0,c.useAlphaFromAlbedoTexture=!0);break;default:throw new Error(C+"/alphaMode: Invalid value ("+m.alphaMode+")")}},R.prototype.loadTextureInfoAsync=function(C,m,c){var T=this;c===void 0&&(c=function(){});var A=this._extensionsLoadTextureInfoAsync(C,m,c);if(A)return A;if(this.logOpen(""+C),m.texCoord>=2)throw new Error(C+"/texCoord: Invalid value ("+m.texCoord+")");var S=u.Get(C+"/index",this._gltf.textures,m.index);S._textureInfo=m;var g=this._loadTextureAsync("/textures/"+m.index,S,function(l){l.coordinatesIndex=m.texCoord||0,R.AddPointerMetadata(l,C),T._parent.onTextureLoadedObservable.notifyObservers(l),c(l)});return this.logClose(),g},R.prototype._loadTextureAsync=function(C,m,c){c===void 0&&(c=function(){});var T=this._extensionsLoadTextureAsync(C,m,c);if(T)return T;this.logOpen(C+" "+(m.name||""));var A=m.sampler==null?R.DefaultSampler:u.Get(C+"/sampler",this._gltf.samplers,m.sampler),S=u.Get(C+"/source",this._gltf.images,m.source),g=this._createTextureAsync(C,A,S,c);return this.logClose(),g},R.prototype._createTextureAsync=function(C,m,c,T,A){var S=this;T===void 0&&(T=function(){});var g=this._loadSampler("/samplers/"+m.index,m),l=new Array,h=new _.Deferred;this._babylonScene._blockEntityCollection=this._forAssetContainer;var v=new _.Texture(null,this._babylonScene,g.noMipMaps,!1,g.samplingMode,function(){S._disposed||h.resolve()},function(E,D){S._disposed||h.reject(new Error(C+": "+(D&&D.message?D.message:E||"Failed to load texture")))},void 0,void 0,void 0,c.mimeType,A);return this._babylonScene._blockEntityCollection=!1,l.push(h.promise),l.push(this.loadImageAsync("/images/"+c.index,c).then(function(E){var D=c.uri||S._fileName+"#image"+c.index,w="data:"+S._uniqueRootUrl+D;v.updateURL(w,E)})),v.wrapU=g.wrapU,v.wrapV=g.wrapV,T(v),Promise.all(l).then(function(){return v})},R.prototype._loadSampler=function(C,m){return m._data||(m._data={noMipMaps:m.minFilter===9728||m.minFilter===9729,samplingMode:R._GetTextureSamplingMode(C,m),wrapU:R._GetTextureWrapMode(C+"/wrapS",m.wrapS),wrapV:R._GetTextureWrapMode(C+"/wrapT",m.wrapT)}),m._data},R.prototype.loadImageAsync=function(C,m){if(!m._data){if(this.logOpen(C+" "+(m.name||"")),m.uri)m._data=this.loadUriAsync(C+"/uri",m,m.uri);else{var c=u.Get(C+"/bufferView",this._gltf.bufferViews,m.bufferView);m._data=this.loadBufferViewAsync("/bufferViews/"+c.index,c)}this.logClose()}return m._data},R.prototype.loadUriAsync=function(C,m,c){var T=this,A=this._extensionsLoadUriAsync(C,m,c);if(A)return A;if(!R._ValidateUri(c))throw new Error(C+": '"+c+"' is invalid");if(_.Tools.IsBase64(c)){var S=new Uint8Array(_.Tools.DecodeBase64(c));return this.log("Decoded "+c.substr(0,64)+"... ("+S.length+" bytes)"),Promise.resolve(S)}return this.log("Loading "+c),this._parent.preprocessUrlAsync(this._rootUrl+c).then(function(g){return new Promise(function(l,h){T._parent._loadFile(g,T._babylonScene,function(v){T._disposed||(T.log("Loaded "+c+" ("+v.byteLength+" bytes)"),l(new Uint8Array(v)))},!0,function(v){h(new _.LoadFileError(C+": Failed to load '"+c+"'"+(v?": "+v.status+" "+v.statusText:""),v))})})})},R.AddPointerMetadata=function(C,m){var c=C.metadata=C.metadata||{},T=c.gltf=c.gltf||{};(T.pointers=T.pointers||[]).push(m)},R._GetTextureWrapMode=function(C,m){switch(m=m??10497){case 33071:return _.Texture.CLAMP_ADDRESSMODE;case 33648:return _.Texture.MIRROR_ADDRESSMODE;case 10497:return _.Texture.WRAP_ADDRESSMODE;default:return _.Logger.Warn(C+": Invalid value ("+m+")"),_.Texture.WRAP_ADDRESSMODE}},R._GetTextureSamplingMode=function(C,m){var c=m.magFilter==null?9729:m.magFilter,T=m.minFilter==null?9987:m.minFilter;if(c===9729)switch(T){case 9728:return _.Texture.LINEAR_NEAREST;case 9729:return _.Texture.LINEAR_LINEAR;case 9984:return _.Texture.LINEAR_NEAREST_MIPNEAREST;case 9985:return _.Texture.LINEAR_LINEAR_MIPNEAREST;case 9986:return _.Texture.LINEAR_NEAREST_MIPLINEAR;case 9987:return _.Texture.LINEAR_LINEAR_MIPLINEAR;default:return _.Logger.Warn(C+"/minFilter: Invalid value ("+T+")"),_.Texture.LINEAR_LINEAR_MIPLINEAR}else switch(c!==9728&&_.Logger.Warn(C+"/magFilter: Invalid value ("+c+")"),T){case 9728:return _.Texture.NEAREST_NEAREST;case 9729:return _.Texture.NEAREST_LINEAR;case 9984:return _.Texture.NEAREST_NEAREST_MIPNEAREST;case 9985:return _.Texture.NEAREST_LINEAR_MIPNEAREST;case 9986:return _.Texture.NEAREST_NEAREST_MIPLINEAR;case 9987:return _.Texture.NEAREST_LINEAR_MIPLINEAR;default:return _.Logger.Warn(C+"/minFilter: Invalid value ("+T+")"),_.Texture.NEAREST_NEAREST_MIPNEAREST}},R._GetTypedArrayConstructor=function(C,m){switch(m){case 5120:return Int8Array;case 5121:return Uint8Array;case 5122:return Int16Array;case 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this._applyExtensions(m,"createMaterial",function(T){return T.createMaterial&&T.createMaterial(C,m,c)})},R.prototype._extensionsLoadMaterialPropertiesAsync=function(C,m,c){return this._applyExtensions(m,"loadMaterialProperties",function(T){return T.loadMaterialPropertiesAsync&&T.loadMaterialPropertiesAsync(C,m,c)})},R.prototype._extensionsLoadTextureInfoAsync=function(C,m,c){return this._applyExtensions(m,"loadTextureInfo",function(T){return T.loadTextureInfoAsync&&T.loadTextureInfoAsync(C,m,c)})},R.prototype._extensionsLoadTextureAsync=function(C,m,c){return this._applyExtensions(m,"loadTexture",function(T){return T._loadTextureAsync&&T._loadTextureAsync(C,m,c)})},R.prototype._extensionsLoadAnimationAsync=function(C,m){return this._applyExtensions(m,"loadAnimation",function(c){return c.loadAnimationAsync&&c.loadAnimationAsync(C,m)})},R.prototype._extensionsLoadSkinAsync=function(C,m,c){return this._applyExtensions(c,"loadSkin",function(T){return 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*****************************************************************************
-	Copyright (c) Microsoft Corporation.
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-	Permission to use, copy, modify, and/or distribute this software for any
-	purpose with or without fee is hereby granted.
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-	THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
-	REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY
-	AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
-	INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM
-	LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR
-	OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR
-	PERFORMANCE OF THIS SOFTWARE.
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_.SpotLight(k,_.Vector3.Zero(),_.Vector3.Backward(),0,1,L._loader.babylonScene);H.angle=2*(Y.spot&&Y.spot.outerConeAngle||Math.PI/4),H.innerAngle=2*(Y.spot&&Y.spot.innerConeAngle||0),re=H;break;default:throw L._loader.babylonScene._blockEntityCollection=!1,new Error(G+": Invalid light type ("+Y.type+")")}L._loader.babylonScene._blockEntityCollection=!1,re.falloffType=_.Light.FALLOFF_GLTF,re.diffuse=Y.color?_.Color3.FromArray(Y.color):_.Color3.White(),re.intensity=Y.intensity==null?1:Y.intensity,re.range=Y.range==null?Number.MAX_VALUE:Y.range,re.parent=oe,L._loader._babylonLights.push(re),x.b.AddPointerMetadata(re,G),$(oe)})})},ae}();x.b.RegisterExtension("KHR_lights_punctual",function(ae){return new c(ae)});var T=function(){function ae(ee){this.name="KHR_materials_pbrSpecularGlossiness",this.order=200,this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_materials_pbrSpecularGlossiness")}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadMaterialPropertiesAsync=function(ee,K,$){var L=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return oe.push(L._loader.loadMaterialBasePropertiesAsync(ee,K,$)),oe.push(L._loadSpecularGlossinessPropertiesAsync(G,K,Q,$)),L._loader.loadMaterialAlphaProperties(ee,K,$),Promise.all(oe).then(function(){})})},ae.prototype._loadSpecularGlossinessPropertiesAsync=function(ee,K,$,L){if(!(L instanceof _.PBRMaterial))throw new Error(ee+": Material type not supported");var G=new Array;return 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ae(ee){this.name="KHR_materials_unlit",this.order=210,this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_materials_unlit")}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadMaterialPropertiesAsync=function(ee,K,$){var L=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(){return L._loadUnlitPropertiesAsync(ee,K,$)})},ae.prototype._loadUnlitPropertiesAsync=function(ee,K,$){if(!($ instanceof _.PBRMaterial))throw new Error(ee+": Material type not supported");var L=new Array;$.unlit=!0;var G=K.pbrMetallicRoughness;return G&&(G.baseColorFactor?($.albedoColor=_.Color3.FromArray(G.baseColorFactor),$.alpha=G.baseColorFactor[3]):$.albedoColor=_.Color3.White(),G.baseColorTexture&&L.push(this._loader.loadTextureInfoAsync(ee+"/baseColorTexture",G.baseColorTexture,function(Q){Q.name=$.name+" (Base 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$.clearCoat.isEnabled=!0,$.clearCoat.useRoughnessFromMainTexture=!1,$.clearCoat.remapF0OnInterfaceChange=!1,K.clearcoatFactor!=null?$.clearCoat.intensity=K.clearcoatFactor:$.clearCoat.intensity=0,K.clearcoatTexture&&L.push(this._loader.loadTextureInfoAsync(ee+"/clearcoatTexture",K.clearcoatTexture,function(G){G.name=$.name+" (ClearCoat Intensity)",$.clearCoat.texture=G})),K.clearcoatRoughnessFactor!=null?$.clearCoat.roughness=K.clearcoatRoughnessFactor:$.clearCoat.roughness=0,K.clearcoatRoughnessTexture&&(K.clearcoatRoughnessTexture.nonColorData=!0,L.push(this._loader.loadTextureInfoAsync(ee+"/clearcoatRoughnessTexture",K.clearcoatRoughnessTexture,function(G){G.name=$.name+" (ClearCoat Roughness)",$.clearCoat.textureRoughness=G}))),K.clearcoatNormalTexture&&(K.clearcoatNormalTexture.nonColorData=!0,L.push(this._loader.loadTextureInfoAsync(ee+"/clearcoatNormalTexture",K.clearcoatNormalTexture,function(G){G.name=$.name+" (ClearCoat 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not supported");var L=new Array;return $.sheen.isEnabled=!0,$.sheen.intensity=1,K.sheenColorFactor!=null?$.sheen.color=_.Color3.FromArray(K.sheenColorFactor):$.sheen.color=_.Color3.Black(),K.sheenColorTexture&&L.push(this._loader.loadTextureInfoAsync(ee+"/sheenColorTexture",K.sheenColorTexture,function(G){G.name=$.name+" (Sheen Color)",$.sheen.texture=G})),K.sheenRoughnessFactor!==void 0?$.sheen.roughness=K.sheenRoughnessFactor:$.sheen.roughness=0,K.sheenRoughnessTexture&&(K.sheenRoughnessTexture.nonColorData=!0,L.push(this._loader.loadTextureInfoAsync(ee+"/sheenRoughnessTexture",K.sheenRoughnessTexture,function(G){G.name=$.name+" (Sheen Roughness)",$.sheen.textureRoughness=G}))),$.sheen.albedoScaling=!0,$.sheen.useRoughnessFromMainTexture=!1,Promise.all(L).then(function(){})},ae}();x.b.RegisterExtension("KHR_materials_sheen",function(ae){return new g(ae)});var l=function(){function ae(ee){this.name="KHR_materials_specular",this.order=190,this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_materials_specular")}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadMaterialPropertiesAsync=function(ee,K,$){var L=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return oe.push(L._loader.loadMaterialPropertiesAsync(ee,K,$)),oe.push(L._loadSpecularPropertiesAsync(G,Q,$)),Promise.all(oe).then(function(){})})},ae.prototype._loadSpecularPropertiesAsync=function(ee,K,$){if(!($ instanceof _.PBRMaterial))throw new Error(ee+": Material type not supported");var L=new Array;return K.specularFactor!==void 0&&($.metallicF0Factor=K.specularFactor),K.specularColorFactor!==void 0&&($.metallicReflectanceColor=_.Color3.FromArray(K.specularColorFactor)),K.specularTexture&&(K.specularTexture.nonColorData=!0,L.push(this._loader.loadTextureInfoAsync(ee+"/specularTexture",K.specularTexture,function(G){G.name=$.name+" (Specular F0 Color)",$.metallicReflectanceTexture=G}))),Promise.all(L).then(function(){})},ae}();x.b.RegisterExtension("KHR_materials_specular",function(ae){return new l(ae)});var h=function(){function ae(ee){this.name="KHR_materials_ior",this.order=180,this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_materials_ior")}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadMaterialPropertiesAsync=function(ee,K,$){var L=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return oe.push(L._loader.loadMaterialPropertiesAsync(ee,K,$)),oe.push(L._loadIorPropertiesAsync(G,Q,$)),Promise.all(oe).then(function(){})})},ae.prototype._loadIorPropertiesAsync=function(ee,K,$){if(!($ instanceof _.PBRMaterial))throw new Error(ee+": Material type not supported");return K.ior!==void 0?$.indexOfRefraction=K.ior:$.indexOfRefraction=ae._DEFAULT_IOR,Promise.resolve()},ae._DEFAULT_IOR=1.5,ae}();x.b.RegisterExtension("KHR_materials_ior",function(ae){return new h(ae)});var v=function(){function ae(ee){this.name="KHR_materials_variants",this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_materials_variants")}return ae.prototype.dispose=function(){this._loader=null},ae.GetAvailableVariants=function(ee){var K=this._GetExtensionMetadata(ee);return K?Object.keys(K.variants):[]},ae.prototype.getAvailableVariants=function(ee){return ae.GetAvailableVariants(ee)},ae.SelectVariant=function(ee,K){var $=this._GetExtensionMetadata(ee);if(!$)throw new Error("Cannot select variant on a glTF mesh that does not have the KHR_materials_variants extension");var L=function(oe){var re=$.variants[oe];if(re)for(var Y=0,k=re;Y<k.length;Y++){var H=k[Y];H.mesh.material=H.material}};if(K instanceof Array)for(var G=0,Q=K;G<Q.length;G++)L(Q[G]);else L(K);$.lastSelected=K},ae.prototype.selectVariant=function(ee,K){return ae.SelectVariant(ee,K)},ae.Reset=function(ee){var K=this._GetExtensionMetadata(ee);if(!K)throw new Error("Cannot reset on a glTF mesh that does not have the KHR_materials_variants extension");for(var $=0,L=K.original;$<L.length;$++){var G=L[$];G.mesh.material=G.material}K.lastSelected=null},ae.prototype.reset=function(ee){return ae.Reset(ee)},ae.GetLastSelectedVariant=function(ee){var K=this._GetExtensionMetadata(ee);if(!K)throw new Error("Cannot get the last selected variant on a glTF mesh that does not have the KHR_materials_variants extension");return K.lastSelected},ae.prototype.getLastSelectedVariant=function(ee){return ae.GetLastSelectedVariant(ee)},ae._GetExtensionMetadata=function(ee){var K,$;return(($=(K=ee?.metadata)===null||K===void 0?void 0:K.gltf)===null||$===void 0?void 0:$.KHR_materials_variants)||null},ae.prototype.onLoading=function(){var ee=this._loader.gltf.extensions;if(ee&&ee[this.name]){var K=ee[this.name];this._variants=K.variants}},ae.prototype._loadMeshPrimitiveAsync=function(ee,K,$,L,G,Q){var oe=this;return x.b.LoadExtensionAsync(ee,G,this.name,function(re,Y){var k=new Array;return k.push(oe._loader._loadMeshPrimitiveAsync(ee,K,$,L,G,function(H){if(Q(H),H instanceof _.Mesh){var Z=x.b._GetDrawMode(ee,G.mode),W=oe._loader.rootBabylonMesh,q=W.metadata=W.metadata||{},he=q.gltf=q.gltf||{},ge=he.KHR_materials_variants=he.KHR_materials_variants||{lastSelected:null,original:[],variants:{}};ge.original.push({mesh:H,material:H.material});for(var me=ge.variants,_e=0,be=Y.mappings;_e<be.length;_e++)for(var Pe=be[_e],ye=function(We){var je=x.a.Get(re+"/mapping/"+We,oe._variants,We),He=x.a.Get("#/materials/",oe._loader.gltf.materials,Pe.material);k.push(oe._loader._loadMaterialAsync("#/materials/"+Pe.material,He,H,Z,function(qe){me[je.name]=me[je.name]||[],me[je.name].push({mesh:H,material:qe})}))},Be=0,ke=Pe.variants;Be<ke.length;Be++)ye(ke[Be])}})),Promise.all(k).then(function(H){return H[0]})})},ae}();x.b.RegisterExtension("KHR_materials_variants",function(ae){return new v(ae)});var E=U(4),D=function(){function ae(ee,K){var $=this;this._opaqueRenderTarget=null,this._opaqueMeshesCache=[],this._transparentMeshesCache=[],this._options=Object(E.a)(Object(E.a)({},ae._getDefaultOptions()),ee),this._scene=K,this._scene._transmissionHelper=this,this.onErrorObservable=new _.Observable,this._scene.onDisposeObservable.addOnce(function(L){$.dispose()}),this._parseScene(),this._setupRenderTargets()}return ae._getDefaultOptions=function(){return{renderSize:512}},ae.prototype.updateOptions=function(ee){var K=this;if(Object.keys(ee).filter(function(G){return K._options[G]!==ee[G]}).length){var $=Object(E.a)(Object(E.a)({},this._options),ee),L=this._options;this._options=$,$.renderSize!==L.renderSize&&this._setupRenderTargets()}},ae.prototype.getOpaqueTarget=function(){return this._opaqueRenderTarget},ae.prototype.shouldRenderAsTransmission=function(ee){return!!ee&&!!(ee instanceof _.PBRMaterial&&ee.subSurface.isRefractionEnabled)},ae.prototype._addMesh=function(ee){ee instanceof _.Mesh&&(ee.onMaterialChangedObservable.add(this.onMeshMaterialChanged.bind(this)),this.shouldRenderAsTransmission(ee.material)?this._transparentMeshesCache.push(ee):this._opaqueMeshesCache.push(ee))},ae.prototype._removeMesh=function(ee){if(ee instanceof _.Mesh){ee.onMaterialChangedObservable.remove(this.onMeshMaterialChanged.bind(this));var K=this._transparentMeshesCache.indexOf(ee);K!==-1&&this._transparentMeshesCache.splice(K,1),(K=this._opaqueMeshesCache.indexOf(ee))!==-1&&this._opaqueMeshesCache.splice(K,1)}},ae.prototype._parseScene=function(){this._scene.meshes.forEach(this._addMesh.bind(this)),this._scene.onNewMeshAddedObservable.add(this._addMesh.bind(this)),this._scene.onMeshRemovedObservable.add(this._removeMesh.bind(this))},ae.prototype.onMeshMaterialChanged=function(ee){if(ee instanceof _.Mesh){var K=this._transparentMeshesCache.indexOf(ee),$=this._opaqueMeshesCache.indexOf(ee);this.shouldRenderAsTransmission(ee.material)?(ee.material instanceof _.PBRMaterial&&(ee.material.subSurface.refractionTexture=this._opaqueRenderTarget),$!==-1?(this._opaqueMeshesCache.splice($,1),this._transparentMeshesCache.push(ee)):K===-1&&this._transparentMeshesCache.push(ee)):K!==-1?(this._transparentMeshesCache.splice(K,1),this._opaqueMeshesCache.push(ee)):$===-1&&this._opaqueMeshesCache.push(ee)}},ae.prototype._setupRenderTargets=function(){var ee=this,K=-1;if(this._scene.layers&&this._opaqueRenderTarget)for(var $=0,L=this._scene.layers;$<L.length;$++){var G=(re=L[$]).renderTargetTextures.indexOf(this._opaqueRenderTarget);G>=0&&re.renderTargetTextures.splice(G,1)}if(this._opaqueRenderTarget&&(K=this._scene.customRenderTargets.indexOf(this._opaqueRenderTarget),this._opaqueRenderTarget.dispose()),this._opaqueRenderTarget=new _.RenderTargetTexture("opaqueSceneTexture",this._options.renderSize,this._scene,!0),this._opaqueRenderTarget.renderList=this._opaqueMeshesCache,this._opaqueRenderTarget.gammaSpace=!0,this._opaqueRenderTarget.lodGenerationScale=1,this._opaqueRenderTarget.lodGenerationOffset=-4,K>=0?this._scene.customRenderTargets.splice(K,0,this._opaqueRenderTarget):(K=this._scene.customRenderTargets.length,this._scene.customRenderTargets.push(this._opaqueRenderTarget)),this._scene.layers&&this._opaqueRenderTarget)for(var Q=0,oe=this._scene.layers;Q<oe.length;Q++){var re;(re=oe[Q]).renderTargetTextures.push(this._opaqueRenderTarget)}this._transparentMeshesCache.forEach(function(Y){ee.shouldRenderAsTransmission(Y.material)&&Y.material instanceof _.PBRMaterial&&(Y.material.refractionTexture=ee._opaqueRenderTarget)})},ae.prototype.dispose=function(){this._scene._transmissionHelper=void 0,this._opaqueRenderTarget&&(this._opaqueRenderTarget.dispose(),this._opaqueRenderTarget=null),this._transparentMeshesCache=[],this._opaqueMeshesCache=[]},ae}(),w=function(){function ae(ee){this.name="KHR_materials_transmission",this.order=175,this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_materials_transmission"),this.enabled&&(ee.parent.transparencyAsCoverage=!0)}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadMaterialPropertiesAsync=function(ee,K,$){var L=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return oe.push(L._loader.loadMaterialBasePropertiesAsync(ee,K,$)),oe.push(L._loader.loadMaterialPropertiesAsync(ee,K,$)),oe.push(L._loadTransparentPropertiesAsync(G,K,$,Q)),Promise.all(oe).then(function(){})})},ae.prototype._loadTransparentPropertiesAsync=function(ee,K,$,L){if(!($ instanceof _.PBRMaterial))throw new Error(ee+": Material type not supported");var G=$;if(G.subSurface.isRefractionEnabled=!0,G.subSurface.volumeIndexOfRefraction=1,G.subSurface.useAlbedoToTintRefraction=!0,L.transmissionFactor===void 0)return G.subSurface.refractionIntensity=0,G.subSurface.isRefractionEnabled=!1,Promise.resolve();G.subSurface.refractionIntensity=L.transmissionFactor;var Q=G.getScene();return G.subSurface.refractionIntensity&&!Q._transmissionHelper&&new D({},G.getScene()),L.transmissionTexture?(L.transmissionTexture.nonColorData=!0,this._loader.loadTextureInfoAsync(ee+"/transmissionTexture",L.transmissionTexture,void 0).then(function(oe){G.subSurface.thicknessTexture=oe,G.subSurface.useMaskFromThicknessTextureGltf=!0})):Promise.resolve()},ae}();x.b.RegisterExtension("KHR_materials_transmission",function(ae){return new w(ae)});var N=function(){function ae(ee){this.name="KHR_materials_translucency",this.order=175,this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_materials_translucency"),this.enabled&&(ee.parent.transparencyAsCoverage=!0)}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadMaterialPropertiesAsync=function(ee,K,$){var L=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return oe.push(L._loader.loadMaterialBasePropertiesAsync(ee,K,$)),oe.push(L._loader.loadMaterialPropertiesAsync(ee,K,$)),oe.push(L._loadTranslucentPropertiesAsync(G,K,$,Q)),Promise.all(oe).then(function(){})})},ae.prototype._loadTranslucentPropertiesAsync=function(ee,K,$,L){if(!($ instanceof _.PBRMaterial))throw new Error(ee+": Material type not supported");var G=$;return G.subSurface.isTranslucencyEnabled=!0,G.subSurface.volumeIndexOfRefraction=1,G.subSurface.minimumThickness=0,G.subSurface.maximumThickness=0,G.subSurface.useAlbedoToTintRefraction=!0,L.translucencyFactor===void 0?(G.subSurface.translucencyIntensity=0,G.subSurface.isTranslucencyEnabled=!1,Promise.resolve()):(G.subSurface.translucencyIntensity=L.translucencyFactor,L.translucencyTexture?this._loader.loadTextureInfoAsync(ee+"/translucencyTexture",L.translucencyTexture).then(function(Q){G.subSurface.thicknessTexture=Q,G.subSurface.useMaskFromThicknessTextureGltf=!0}):Promise.resolve())},ae}();x.b.RegisterExtension("KHR_materials_translucency",function(ae){return new N(ae)});var I=function(){function ae(ee){this.name="KHR_mesh_quantization",this.enabled=ee.isExtensionUsed("KHR_mesh_quantization")}return ae.prototype.dispose=function(){},ae}();x.b.RegisterExtension("KHR_mesh_quantization",function(ae){return new I(ae)});var V=function(){function ae(ee){this.name="KHR_texture_basisu",this._loader=ee,this.enabled=ee.isExtensionUsed("KHR_texture_basisu")}return ae.prototype.dispose=function(){this._loader=null},ae.prototype._loadTextureAsync=function(ee,K,$){var L=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=K.sampler==null?x.b.DefaultSampler:x.a.Get(ee+"/sampler",L._loader.gltf.samplers,K.sampler),re=x.a.Get(G+"/source",L._loader.gltf.images,Q.source);return L._loader._createTextureAsync(ee,oe,re,function(Y){$(Y)},K._textureInfo.nonColorData?{useRGBAIfASTCBC7NotAvailableWhenUASTC:!0}:void 0)})},ae}();x.b.RegisterExtension("KHR_texture_basisu",function(ae){return new V(ae)});var X=function(){function ae(ee){this.name="KHR_texture_transform",this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_texture_transform")}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadTextureInfoAsync=function(ee,K,$){var L=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){return L._loader.loadTextureInfoAsync(ee,K,function(oe){if(!(oe instanceof _.Texture))throw new Error(G+": Texture type not supported");Q.offset&&(oe.uOffset=Q.offset[0],oe.vOffset=Q.offset[1]),oe.uRotationCenter=0,oe.vRotationCenter=0,Q.rotation&&(oe.wAng=-Q.rotation),Q.scale&&(oe.uScale=Q.scale[0],oe.vScale=Q.scale[1]),Q.texCoord!=null&&(oe.coordinatesIndex=Q.texCoord),$(oe)})})},ae}();x.b.RegisterExtension("KHR_texture_transform",function(ae){return new X(ae)});var j=function(){function ae(ee){this.name="MSFT_audio_emitter",this._loader=ee,this.enabled=this._loader.isExtensionUsed("MSFT_audio_emitter")}return ae.prototype.dispose=function(){this._loader=null,this._clips=null,this._emitters=null},ae.prototype.onLoading=function(){var ee=this._loader.gltf.extensions;if(ee&&ee[this.name]){var K=ee[this.name];this._clips=K.clips,this._emitters=K.emitters,x.a.Assign(this._clips),x.a.Assign(this._emitters)}},ae.prototype.loadSceneAsync=function(ee,K){var $=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(L,G){var Q=new Array;Q.push($._loader.loadSceneAsync(ee,K));for(var oe=0,re=G.emitters;oe<re.length;oe++){var Y=re[oe],k=x.a.Get(L+"/emitters",$._emitters,Y);if(k.refDistance!=null||k.maxDistance!=null||k.rolloffFactor!=null||k.distanceModel!=null||k.innerAngle!=null||k.outerAngle!=null)throw new Error(L+": Direction or Distance properties are not allowed on emitters attached to a scene");Q.push($._loadEmitterAsync(L+"/emitters/"+k.index,k))}return Promise.all(Q).then(function(){})})},ae.prototype.loadNodeAsync=function(ee,K,$){var L=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return L._loader.loadNodeAsync(G,K,function(re){for(var Y=function(Z){var W=x.a.Get(G+"/emitters",L._emitters,Z);oe.push(L._loadEmitterAsync(G+"/emitters/"+W.index,W).then(function(){for(var q=0,he=W._babylonSounds;q<he.length;q++){var ge=he[q];ge.attachToMesh(re),W.innerAngle==null&&W.outerAngle==null||(ge.setLocalDirectionToMesh(_.Vector3.Forward()),ge.setDirectionalCone(2*_.Tools.ToDegrees(W.innerAngle==null?Math.PI:W.innerAngle),2*_.Tools.ToDegrees(W.outerAngle==null?Math.PI:W.outerAngle),0))}}))},k=0,H=Q.emitters;k<H.length;k++)Y(H[k]);$(re)}).then(function(re){return Promise.all(oe).then(function(){return re})})})},ae.prototype.loadAnimationAsync=function(ee,K){var $=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(L,G){return $._loader.loadAnimationAsync(ee,K).then(function(Q){var oe=new Array;x.a.Assign(G.events);for(var re=0,Y=G.events;re<Y.length;re++){var k=Y[re];oe.push($._loadAnimationEventAsync(L+"/events/"+k.index,ee,K,k,Q))}return Promise.all(oe).then(function(){return Q})})})},ae.prototype._loadClipAsync=function(ee,K){if(K._objectURL)return K._objectURL;var $;if(K.uri)$=this._loader.loadUriAsync(ee,K,K.uri);else{var L=x.a.Get(ee+"/bufferView",this._loader.gltf.bufferViews,K.bufferView);$=this._loader.loadBufferViewAsync("/bufferViews/"+L.index,L)}return K._objectURL=$.then(function(G){return URL.createObjectURL(new Blob([G],{type:K.mimeType}))}),K._objectURL},ae.prototype._loadEmitterAsync=function(ee,K){var $=this;if(K._babylonSounds=K._babylonSounds||[],!K._babylonData){for(var L=new Array,G=K.name||"emitter"+K.index,Q={loop:!1,autoplay:!1,volume:K.volume==null?1:K.volume},oe=function(H){var Z="/extensions/"+re.name+"/clips",W=x.a.Get(Z,re._clips,K.clips[H].clip);L.push(re._loadClipAsync(Z+"/"+K.clips[H].clip,W).then(function(q){var he=K._babylonSounds[H]=new _.Sound(G,q,$._loader.babylonScene,null,Q);he.refDistance=K.refDistance||1,he.maxDistance=K.maxDistance||256,he.rolloffFactor=K.rolloffFactor||1,he.distanceModel=K.distanceModel||"exponential",he._positionInEmitterSpace=!0}))},re=this,Y=0;Y<K.clips.length;Y++)oe(Y);var k=Promise.all(L).then(function(){var H=K.clips.map(function(W){return W.weight||1}),Z=new _.WeightedSound(K.loop||!1,K._babylonSounds,H);K.innerAngle&&(Z.directionalConeInnerAngle=2*_.Tools.ToDegrees(K.innerAngle)),K.outerAngle&&(Z.directionalConeOuterAngle=2*_.Tools.ToDegrees(K.outerAngle)),K.volume&&(Z.volume=K.volume),K._babylonData.sound=Z});K._babylonData={loaded:k}}return K._babylonData.loaded},ae.prototype._getEventAction=function(ee,K,$,L,G){switch($){case"play":return function(Q){var oe=(G||0)+(Q-L);K.play(oe)};case"stop":return function(Q){K.stop()};case"pause":return function(Q){K.pause()};default:throw new Error(ee+": Unsupported action "+$)}},ae.prototype._loadAnimationEventAsync=function(ee,K,$,L,G){var Q=this;if(G.targetedAnimations.length==0)return Promise.resolve();var oe=G.targetedAnimations[0],re=L.emitter,Y=x.a.Get("/extensions/"+this.name+"/emitters",this._emitters,re);return this._loadEmitterAsync(ee,Y).then(function(){var k=Y._babylonData.sound;if(k){var H=new _.AnimationEvent(L.time,Q._getEventAction(ee,k,L.action,L.time,L.startOffset));oe.animation.addEvent(H),G.onAnimationGroupEndObservable.add(function(){k.stop()}),G.onAnimationGroupPauseObservable.add(function(){k.pause()})}})},ae}();x.b.RegisterExtension("MSFT_audio_emitter",function(ae){return new j(ae)});var ne=function(){function ae(ee){this.name="MSFT_lod",this.order=100,this.maxLODsToLoad=10,this.onNodeLODsLoadedObservable=new _.Observable,this.onMaterialLODsLoadedObservable=new _.Observable,this._bufferLODs=new Array,this._nodeIndexLOD=null,this._nodeSignalLODs=new Array,this._nodePromiseLODs=new Array,this._nodeBufferLODs=new Array,this._materialIndexLOD=null,this._materialSignalLODs=new Array,this._materialPromiseLODs=new Array,this._materialBufferLODs=new Array,this._loader=ee,this.enabled=this._loader.isExtensionUsed("MSFT_lod")}return ae.prototype.dispose=function(){this._loader=null,this._nodeIndexLOD=null,this._nodeSignalLODs.length=0,this._nodePromiseLODs.length=0,this._nodeBufferLODs.length=0,this._materialIndexLOD=null,this._materialSignalLODs.length=0,this._materialPromiseLODs.length=0,this._materialBufferLODs.length=0,this.onMaterialLODsLoadedObservable.clear(),this.onNodeLODsLoadedObservable.clear()},ae.prototype.onReady=function(){for(var ee=this,K=function(oe){var re=Promise.all($._nodePromiseLODs[oe]).then(function(){oe!==0&&(ee._loader.endPerformanceCounter("Node LOD "+oe),ee._loader.log("Loaded node LOD "+oe)),ee.onNodeLODsLoadedObservable.notifyObservers(oe),oe!==ee._nodePromiseLODs.length-1&&(ee._loader.startPerformanceCounter("Node LOD "+(oe+1)),ee._loadBufferLOD(ee._nodeBufferLODs,oe+1),ee._nodeSignalLODs[oe]&&ee._nodeSignalLODs[oe].resolve())});$._loader._completePromises.push(re)},$=this,L=0;L<this._nodePromiseLODs.length;L++)K(L);var G=function(oe){var re=Promise.all(Q._materialPromiseLODs[oe]).then(function(){oe!==0&&(ee._loader.endPerformanceCounter("Material LOD "+oe),ee._loader.log("Loaded material LOD "+oe)),ee.onMaterialLODsLoadedObservable.notifyObservers(oe),oe!==ee._materialPromiseLODs.length-1&&(ee._loader.startPerformanceCounter("Material LOD "+(oe+1)),ee._loadBufferLOD(ee._materialBufferLODs,oe+1),ee._materialSignalLODs[oe]&&ee._materialSignalLODs[oe].resolve())});Q._loader._completePromises.push(re)},Q=this;for(L=0;L<this._materialPromiseLODs.length;L++)G(L)},ae.prototype.loadSceneAsync=function(ee,K){var $=this._loader.loadSceneAsync(ee,K);return this._loadBufferLOD(this._bufferLODs,0),$},ae.prototype.loadNodeAsync=function(ee,K,$){var L=this;return x.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe,re=L._getLODs(G,K,L._loader.gltf.nodes,Q.ids);L._loader.logOpen(""+G);for(var Y=function(H){var Z=re[H];H!==0&&(L._nodeIndexLOD=H,L._nodeSignalLODs[H]=L._nodeSignalLODs[H]||new _.Deferred);var W=L._loader.loadNodeAsync("/nodes/"+Z.index,Z,function(q){q.setEnabled(!1)}).then(function(q){if(H!==0){var he=re[H-1];he._babylonTransformNode&&(L._disposeTransformNode(he._babylonTransformNode),delete he._babylonTransformNode)}return q.setEnabled(!0),q});L._nodePromiseLODs[H]=L._nodePromiseLODs[H]||[],H===0?oe=W:(L._nodeIndexLOD=null,L._nodePromiseLODs[H].push(W))},k=0;k<re.length;k++)Y(k);return L._loader.logClose(),oe})},ae.prototype._loadMaterialAsync=function(ee,K,$,L,G){var Q=this;return this._nodeIndexLOD?null:x.b.LoadExtensionAsync(ee,K,this.name,function(oe,re){var Y,k=Q._getLODs(oe,K,Q._loader.gltf.materials,re.ids);Q._loader.logOpen(""+oe);for(var H=function(W){var q=k[W];W!==0&&(Q._materialIndexLOD=W);var he=Q._loader._loadMaterialAsync("/materials/"+q.index,q,$,L,function(ge){W===0&&G(ge)}).then(function(ge){if(W!==0){G(ge);var me=k[W-1]._data;me[L]&&(Q._disposeMaterials([me[L].babylonMaterial]),delete me[L])}return 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st;if(st=te(W,q.jointNames[Pe])){for(je=0;je<ct.length;je++)if(ct[je].id===st.id){ge.bones.push(ct[je]);break}}}for(ge.prepare(),Pe=0;Pe<be.length;Pe++)ge.bones.push(be[Pe]);return ge},ae=function(W,q,he,ge,me){if(me||(W.scene._blockEntityCollection=W.forAssetContainer,me=new S.Mesh(q.name||"",W.scene),W.scene._blockEntityCollection=!1,me.id=ge),!q.babylonNode)return me;for(var _e,be=[],Pe=null,ye=new Array,Be=new Array,ke=new Array,We=new Array,je=0;je<he.length;je++){var He=he[je];if(tn=W.meshes[He])for(var qe=0;qe<tn.primitives.length;qe++){var Ge=new S.VertexData,nt=tn.primitives[qe];nt.mode;var $e=nt.attributes,ct=null,st=null;for(var mt in $e)if(ct=W.accessors[$e[mt]],st=g.GetBufferFromAccessor(W,ct),mt==="NORMAL")Ge.normals=new Float32Array(st.length),Ge.normals.set(st);else if(mt==="POSITION"){if(l.GLTFFileLoader.HomogeneousCoordinates){Ge.positions=new Float32Array(st.length-st.length/4);for(var St=0;St<st.length;St+=4)Ge.positions[St]=st[St],Ge.positions[St+1]=st[St+1],Ge.positions[St+2]=st[St+2]}else Ge.positions=new Float32Array(st.length),Ge.positions.set(st);Be.push(Ge.positions.length)}else if(mt.indexOf("TEXCOORD_")!==-1){var wt=Number(mt.split("_")[1]),It=S.VertexBuffer.UVKind+(wt===0?"":wt+1),Pt=new Float32Array(st.length);Pt.set(st),I(Pt),Ge.set(Pt,It)}else mt==="JOINT"?(Ge.matricesIndices=new Float32Array(st.length),Ge.matricesIndices.set(st)):mt==="WEIGHT"?(Ge.matricesWeights=new Float32Array(st.length),Ge.matricesWeights.set(st)):mt==="COLOR"&&(Ge.colors=new Float32Array(st.length),Ge.colors.set(st));if(ct=W.accessors[nt.indices])st=g.GetBufferFromAccessor(W,ct),Ge.indices=new Int32Array(st.length),Ge.indices.set(st),We.push(Ge.indices.length);else{var Ot=[];for(St=0;St<Ge.positions.length/3;St++)Ot.push(St);Ge.indices=new Int32Array(Ot),We.push(Ge.indices.length)}Pe?Pe.merge(Ge):Pe=Ge;var on=W.scene.getMaterialByID(nt.material);be.push(on===null?g.GetDefaultMaterial(W.scene):on),ye.push(ye.length===0?0:ye[ye.length-1]+Be[Be.length-2]),ke.push(ke.length===0?0:ke[ke.length-1]+We[We.length-2])}}W.scene._blockEntityCollection=W.forAssetContainer,be.length>1?(_e=new S.MultiMaterial("multimat"+ge,W.scene)).subMaterials=be:_e=new S.StandardMaterial("multimat"+ge,W.scene),be.length===1&&(_e=be[0]),me.material||(me.material=_e),new S.Geometry(ge,W.scene,Pe,!1,me),me.computeWorldMatrix(!0),W.scene._blockEntityCollection=!1,me.subMeshes=[];var Zt=0;for(je=0;je<he.length;je++){var tn;if(He=he[je],tn=W.meshes[He])for(qe=0;qe<tn.primitives.length;qe++)tn.primitives[qe].mode,S.SubMesh.AddToMesh(Zt,ye[Zt],Be[Zt],ke[Zt],We[Zt],me,me,!0),Zt++}return me},ee=function(W,q,he,ge){W.position&&(W.position=q),(W.rotationQuaternion||W.rotation)&&(W.rotationQuaternion=he),W.scaling&&(W.scaling=ge)},K=function(W,q,he,ge){var me=null;if(W.importOnlyMeshes&&(q.skin||q.meshes)&&W.importMeshesNames&&W.importMeshesNames.length>0&&W.importMeshesNames.indexOf(q.name||"")===-1)return null;if(q.skin){if(q.meshes){var _e=W.skins[q.skin];(be=ae(W,q,q.meshes,he,q.babylonNode)).skeleton=W.scene.getLastSkeletonByID(q.skin),be.skeleton===null&&(be.skeleton=pe(W,_e,0,_e.babylonSkeleton,q.skin),_e.babylonSkeleton||(_e.babylonSkeleton=be.skeleton)),me=be}}else if(q.meshes){var be;me=be=ae(W,q,q.mesh?[q.mesh]:q.meshes,he,q.babylonNode)}else if(!q.light||q.babylonNode||W.importOnlyMeshes){if(q.camera&&!q.babylonNode&&!W.importOnlyMeshes){var Pe=W.cameras[q.camera];if(Pe){if(W.scene._blockEntityCollection=W.forAssetContainer,Pe.type==="orthographic"){var ye=new S.FreeCamera(q.camera,S.Vector3.Zero(),W.scene,!1);ye.name=q.name||"",ye.mode=S.Camera.ORTHOGRAPHIC_CAMERA,ye.attachControl(),me=ye}else if(Pe.type==="perspective"){var Be=Pe[Pe.type],ke=new S.FreeCamera(q.camera,S.Vector3.Zero(),W.scene,!1);ke.name=q.name||"",ke.attachControl(),Be.aspectRatio||(Be.aspectRatio=W.scene.getEngine().getRenderWidth()/W.scene.getEngine().getRenderHeight()),Be.znear&&Be.zfar&&(ke.maxZ=Be.zfar,ke.minZ=Be.znear),me=ke}W.scene._blockEntityCollection=!1}}}else{var We=W.lights[q.light];if(We){if(We.type==="ambient"){var je=We[We.type],He=new S.HemisphericLight(q.light,S.Vector3.Zero(),W.scene);He.name=q.name||"",je.color&&(He.diffuse=S.Color3.FromArray(je.color)),me=He}else if(We.type==="directional"){var qe=We[We.type],Ge=new S.DirectionalLight(q.light,S.Vector3.Zero(),W.scene);Ge.name=q.name||"",qe.color&&(Ge.diffuse=S.Color3.FromArray(qe.color)),me=Ge}else if(We.type==="point"){var nt=We[We.type],$e=new S.PointLight(q.light,S.Vector3.Zero(),W.scene);$e.name=q.name||"",nt.color&&($e.diffuse=S.Color3.FromArray(nt.color)),me=$e}else if(We.type==="spot"){var ct=We[We.type],st=new S.SpotLight(q.light,S.Vector3.Zero(),S.Vector3.Zero(),0,0,W.scene);st.name=q.name||"",ct.color&&(st.diffuse=S.Color3.FromArray(ct.color)),ct.fallOfAngle&&(st.angle=ct.fallOfAngle),ct.fallOffExponent&&(st.exponent=ct.fallOffExponent),me=st}}}if(!q.jointName){if(q.babylonNode)return q.babylonNode;if(me===null){W.scene._blockEntityCollection=W.forAssetContainer;var mt=new S.Mesh(q.name||"",W.scene);W.scene._blockEntityCollection=!1,q.babylonNode=mt,me=mt}}if(me!==null){if(q.matrix&&me instanceof S.Mesh)(function(Pt,Ot,on){if(Ot.matrix){var Zt=new S.Vector3(0,0,0),tn=new S.Quaternion,De=new S.Vector3(0,0,0);S.Matrix.FromArray(Ot.matrix).decompose(De,tn,Zt),ee(Pt,Zt,tn,De)}else Ot.translation&&Ot.rotation&&Ot.scale&&ee(Pt,S.Vector3.FromArray(Ot.translation),S.Quaternion.FromArray(Ot.rotation),S.Vector3.FromArray(Ot.scale));Pt.computeWorldMatrix(!0)})(me,q);else{var St=q.translation||[0,0,0],wt=q.rotation||[0,0,0,1],It=q.scale||[1,1,1];ee(me,S.Vector3.FromArray(St),S.Quaternion.FromArray(wt),S.Vector3.FromArray(It))}me.updateCache(!0),q.babylonNode=me}return me},$=function(W,q,he,ge){ge===void 0&&(ge=!1);var me=W.nodes[q],_e=null;if(ge=!(W.importOnlyMeshes&&!ge&&W.importMeshesNames)||W.importMeshesNames.indexOf(me.name||"")!==-1||W.importMeshesNames.length===0,!me.jointName&&ge&&(_e=K(W,me,q))!==null&&(_e.id=q,_e.parent=he),me.children)for(var be=0;be<me.children.length;be++)$(W,me.children[be],_e,ge)},L=function(W){var q=W.currentScene;if(q)for(var he=0;he<q.nodes.length;he++)$(W,q.nodes[he],null);else for(var ge in W.scenes)for(q=W.scenes[ge],he=0;he<q.nodes.length;he++)$(W,q.nodes[he],null);for(function(_e){for(var be in _e.animations){var Pe=_e.animations[be];if(Pe.channels&&Pe.samplers)for(var ye=null,Be=0;Be<Pe.channels.length;Be++){var ke=Pe.channels[Be],We=Pe.samplers[ke.sampler];if(We){var je=null,He=null;Pe.parameters?(je=Pe.parameters[We.input],He=Pe.parameters[We.output]):(je=We.input,He=We.output);var qe=g.GetBufferFromAccessor(_e,_e.accessors[je]),Ge=g.GetBufferFromAccessor(_e,_e.accessors[He]),nt=ke.target.id,$e=_e.scene.getNodeByID(nt);if($e===null&&($e=_e.scene.getNodeByName(nt)),$e!==null){var ct=$e instanceof S.Bone,st=ke.target.path,mt=D.indexOf(st);mt!==-1&&(st=w[mt]);var St=S.Animation.ANIMATIONTYPE_MATRIX;ct||(st==="rotationQuaternion"?(St=S.Animation.ANIMATIONTYPE_QUATERNION,$e.rotationQuaternion=new S.Quaternion):St=S.Animation.ANIMATIONTYPE_VECTOR3);var wt=null,It=[],Pt=0,Ot=!1;ct&&ye&&ye.getKeys().length===qe.length&&(wt=ye,Ot=!0),Ot||(_e.scene._blockEntityCollection=_e.forAssetContainer,wt=new S.Animation(be,ct?"_matrix":st,1,St,S.Animation.ANIMATIONLOOPMODE_CYCLE),_e.scene._blockEntityCollection=!1);for(var on=0;on<qe.length;on++){var Zt=null;if(st==="rotationQuaternion"?(Zt=S.Quaternion.FromArray([Ge[Pt],Ge[Pt+1],Ge[Pt+2],Ge[Pt+3]]),Pt+=4):(Zt=S.Vector3.FromArray([Ge[Pt],Ge[Pt+1],Ge[Pt+2]]),Pt+=3),ct){var tn=$e,De=S.Vector3.Zero(),Pn=new S.Quaternion,nn=S.Vector3.Zero(),Cn=tn.getBaseMatrix();Ot&&ye&&(Cn=ye.getKeys()[on].value),Cn.decompose(nn,Pn,De),st==="position"?De=Zt:st==="rotationQuaternion"?Pn=Zt:nn=Zt,Zt=S.Matrix.Compose(nn,Pn,De)}Ot?ye&&(ye.getKeys()[on].value=Zt):It.push({frame:qe[on],value:Zt})}!Ot&&wt&&(wt.setKeys(It),$e.animations.push(wt)),ye=wt,_e.scene.stopAnimation($e),_e.scene.beginAnimation($e,0,qe[qe.length-1],!0,1)}else S.Tools.Warn("Creating animation named "+be+". 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st=Be.scene.getNodeByName($e.source||$e.node||"");if(st===null&&(st=Be.scene.getNodeByID($e.source||$e.node||"")),st===null)continue;g.SetMatrix(Be.scene,st,$e,nt,We.getEffect())}}else g.SetMatrix(Be.scene,ye,$e,nt,We.getEffect());else{var mt=Ge[je.uniforms[nt]];if(!mt)continue;if(ct===u.SAMPLER_2D){var St=Be.textures[He.values?mt:$e.value].babylonTexture;if(St==null)continue;We.getEffect().setTexture(nt,St)}else g.SetUniform(We.getEffect(),nt,mt,ct)}}qe(We)})(Pe,W,me,q,he,ge,_e)}}},Q=function(W,q,he){for(var ge in q.uniforms){var me=q.uniforms[ge],_e=q.parameters[me];if(W.currentIdentifier===ge&&_e.semantic&&!_e.source&&!_e.node){var be=v.indexOf(_e.semantic);if(be!==-1)return delete he[ge],E[be]}}return W.currentIdentifier},oe=function(W){for(var q in W.materials)k.LoadMaterialAsync(W,q,function(he){},function(){})},re=function(){function W(){}return W.CreateRuntime=function(q,he,ge){var me={extensions:{},accessors:{},buffers:{},bufferViews:{},meshes:{},lights:{},cameras:{},nodes:{},images:{},textures:{},shaders:{},programs:{},samplers:{},techniques:{},materials:{},animations:{},skins:{},extensionsUsed:[],scenes:{},buffersCount:0,shaderscount:0,scene:he,rootUrl:ge,loadedBufferCount:0,loadedBufferViews:{},loadedShaderCount:0,importOnlyMeshes:!1,dummyNodes:[],forAssetContainer:!1};return q.extensions&&N(q.extensions,"extensions",me),q.extensionsUsed&&N(q.extensionsUsed,"extensionsUsed",me),q.buffers&&function(_e,be){for(var Pe in _e){var ye=_e[Pe];be.buffers[Pe]=ye,be.buffersCount++}}(q.buffers,me),q.bufferViews&&N(q.bufferViews,"bufferViews",me),q.accessors&&N(q.accessors,"accessors",me),q.meshes&&N(q.meshes,"meshes",me),q.lights&&N(q.lights,"lights",me),q.cameras&&N(q.cameras,"cameras",me),q.nodes&&N(q.nodes,"nodes",me),q.images&&N(q.images,"images",me),q.textures&&N(q.textures,"textures",me),q.shaders&&function(_e,be){for(var Pe in _e){var ye=_e[Pe];be.shaders[Pe]=ye,be.shaderscount++}}(q.shaders,me),q.programs&&N(q.programs,"programs",me),q.samplers&&N(q.samplers,"samplers",me),q.techniques&&N(q.techniques,"techniques",me),q.materials&&N(q.materials,"materials",me),q.animations&&N(q.animations,"animations",me),q.skins&&N(q.skins,"skins",me),q.scenes&&(me.scenes=q.scenes),q.scene&&q.scenes&&(me.currentScene=q.scenes[q.scene]),me},W.LoadBufferAsync=function(q,he,ge,me,_e){var be=q.buffers[he];S.Tools.IsBase64(be.uri)?setTimeout(function(){return ge(new Uint8Array(S.Tools.DecodeBase64(be.uri)))}):S.Tools.LoadFile(q.rootUrl+be.uri,function(Pe){return ge(new Uint8Array(Pe))},_e,void 0,!0,function(Pe){Pe&&me(Pe.status+" "+Pe.statusText)})},W.LoadTextureBufferAsync=function(q,he,ge,me){var _e=q.textures[he];if(_e&&_e.source)if(_e.babylonTexture)ge(null);else{var be=q.images[_e.source];S.Tools.IsBase64(be.uri)?setTimeout(function(){return ge(new 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lb(ut,Ke,Me){let{elem_id:y=""}=Ke,{elem_classes:f=[]}=Ke,{visible:U=!0}=Ke,{value:_=null}=Ke,{mode:x}=Ke,{root:u}=Ke,{root_url:M}=Ke,{clearColor:R}=Ke,{loading_status:C}=Ke,{label:m}=Ke,{show_label:c}=Ke,{container:T=!0}=Ke,{scale:A=null}=Ke,{min_width:S=void 0}=Ke,g,l=!1;const h=({detail:w})=>Me(0,_=w),v=({detail:w})=>Me(13,l=w);function E(w){Sf.call(this,ut,w)}function D(w){Sf.call(this,ut,w)}return ut.$$set=w=>{"elem_id"in w&&Me(1,y=w.elem_id),"elem_classes"in w&&Me(2,f=w.elem_classes),"visible"in w&&Me(3,U=w.visible),"value"in w&&Me(0,_=w.value),"mode"in w&&Me(4,x=w.mode),"root"in w&&Me(14,u=w.root),"root_url"in w&&Me(15,M=w.root_url),"clearColor"in w&&Me(5,R=w.clearColor),"loading_status"in w&&Me(6,C=w.loading_status),"label"in w&&Me(7,m=w.label),"show_label"in w&&Me(8,c=w.show_label),"container"in w&&Me(9,T=w.container),"scale"in w&&Me(10,A=w.scale),"min_width"in w&&Me(11,S=w.min_width)},ut.$$.update=()=>{ut.$$.dirty&49153&&Me(12,g=Vv(_,u,M))},[_,y,f,U,x,R,C,m,c,T,A,S,g,l,u,M,h,v,E,D]}class ub extends rl{constructor(Ke){super(),ol(this,Ke,lb,cb,al,{elem_id:1,elem_classes:2,visible:3,value:0,mode:4,root:14,root_url:15,clearColor:5,loading_status:6,label:7,show_label:8,container:9,scale:10,min_width:11})}}const Sb=ub,Ab=["static","dynamic"],Pb=ut=>({type:{payload:"{ name: string; data: string }"},description:{payload:"object with file name and base64 data"}});export{Sb as Component,Rb as ExampleComponent,Pb as document,Ab as modes};
-//# sourceMappingURL=index-19bdec54.js.map
diff --git a/spaces/DaleChen/AutoGPT/BULLETIN.md b/spaces/DaleChen/AutoGPT/BULLETIN.md
deleted file mode 100644
index 735048ddc87a914987c6bd70ccdb231a80242ae3..0000000000000000000000000000000000000000
--- a/spaces/DaleChen/AutoGPT/BULLETIN.md
+++ /dev/null
@@ -1,2 +0,0 @@
-Welcome to Auto-GPT! We'll keep you informed of the latest news and features by printing messages here.
-If you don't wish to see this message, you can run Auto-GPT with the --skip-news flag
\ No newline at end of file
diff --git a/spaces/DaleChen/AutoGPT/tests/unit/test_browse_scrape_text.py b/spaces/DaleChen/AutoGPT/tests/unit/test_browse_scrape_text.py
deleted file mode 100644
index fea5ebfc05d466c7cb5711b5ac10e2ea102ddc45..0000000000000000000000000000000000000000
--- a/spaces/DaleChen/AutoGPT/tests/unit/test_browse_scrape_text.py
+++ /dev/null
@@ -1,98 +0,0 @@
-# Generated by CodiumAI
-
-import requests
-
-from autogpt.commands.web_requests import scrape_text
-
-"""
-Code Analysis
-
-Objective:
-The objective of the "scrape_text" function is to scrape the text content from
-a given URL and return it as a string, after removing any unwanted HTML tags and scripts.
-
-Inputs:
-- url: a string representing the URL of the webpage to be scraped.
-
-Flow:
-1. Send a GET request to the given URL using the requests library and the user agent header from the config file.
-2. Check if the response contains an HTTP error. If it does, return an error message.
-3. Use BeautifulSoup to parse the HTML content of the response and extract all script and style tags.
-4. Get the text content of the remaining HTML using the get_text() method of BeautifulSoup.
-5. Split the text into lines and then into chunks, removing any extra whitespace.
-6. Join the chunks into a single string with newline characters between them.
-7. Return the cleaned text.
-
-Outputs:
-- A string representing the cleaned text content of the webpage.
-
-Additional aspects:
-- The function uses the requests library and BeautifulSoup to handle the HTTP request and HTML parsing, respectively.
-- The function removes script and style tags from the HTML to avoid including unwanted content in the text output.
-- The function uses a generator expression to split the text into lines and chunks, which can improve performance for large amounts of text.
-"""
-
-
-class TestScrapeText:
-    # Tests that scrape_text() returns the expected text when given a valid URL.
-    def test_scrape_text_with_valid_url(self, mocker):
-        # Mock the requests.get() method to return a response with expected text
-        expected_text = "This is some sample text"
-        mock_response = mocker.Mock()
-        mock_response.status_code = 200
-        mock_response.text = f"<html><body><div><p style='color: blue;'>{expected_text}</p></div></body></html>"
-        mocker.patch("requests.Session.get", return_value=mock_response)
-
-        # Call the function with a valid URL and assert that it returns the expected text
-        url = "http://www.example.com"
-        assert scrape_text(url) == expected_text
-
-    # Tests that the function returns an error message when an invalid or unreachable url is provided.
-    def test_invalid_url(self, mocker):
-        # Mock the requests.get() method to raise an exception
-        mocker.patch(
-            "requests.Session.get", side_effect=requests.exceptions.RequestException
-        )
-
-        # Call the function with an invalid URL and assert that it returns an error message
-        url = "http://www.invalidurl.com"
-        error_message = scrape_text(url)
-        assert "Error:" in error_message
-
-    # Tests that the function returns an empty string when the html page contains no text to be scraped.
-    def test_no_text(self, mocker):
-        # Mock the requests.get() method to return a response with no text
-        mock_response = mocker.Mock()
-        mock_response.status_code = 200
-        mock_response.text = "<html><body></body></html>"
-        mocker.patch("requests.Session.get", return_value=mock_response)
-
-        # Call the function with a valid URL and assert that it returns an empty string
-        url = "http://www.example.com"
-        assert scrape_text(url) == ""
-
-    # Tests that the function returns an error message when the response status code is an http error (>=400).
-    def test_http_error(self, mocker):
-        # Mock the requests.get() method to return a response with a 404 status code
-        mocker.patch("requests.Session.get", return_value=mocker.Mock(status_code=404))
-
-        # Call the function with a URL
-        result = scrape_text("https://www.example.com")
-
-        # Check that the function returns an error message
-        assert result == "Error: HTTP 404 error"
-
-    # Tests that scrape_text() properly handles HTML tags.
-    def test_scrape_text_with_html_tags(self, mocker):
-        # Create a mock response object with HTML containing tags
-        html = "<html><body><p>This is <b>bold</b> text.</p></body></html>"
-        mock_response = mocker.Mock()
-        mock_response.status_code = 200
-        mock_response.text = html
-        mocker.patch("requests.Session.get", return_value=mock_response)
-
-        # Call the function with a URL
-        result = scrape_text("https://www.example.com")
-
-        # Check that the function properly handles HTML tags
-        assert result == "This is bold text."
diff --git a/spaces/Datasculptor/3D-Room-Layout-Estimation_LGT-Net/dataset/communal/base_dataset.py b/spaces/Datasculptor/3D-Room-Layout-Estimation_LGT-Net/dataset/communal/base_dataset.py
deleted file mode 100644
index a4256581b25518957066f3b4e3c343bbcdc6f9a1..0000000000000000000000000000000000000000
--- a/spaces/Datasculptor/3D-Room-Layout-Estimation_LGT-Net/dataset/communal/base_dataset.py
+++ /dev/null
@@ -1,127 +0,0 @@
-"""
-@Date: 2021/07/26
-@description:
-"""
-import numpy as np
-import torch
-
-from utils.boundary import corners2boundary, visibility_corners, get_heat_map
-from utils.conversion import xyz2depth, uv2xyz, uv2pixel
-from dataset.communal.data_augmentation import PanoDataAugmentation
-
-
-class BaseDataset(torch.utils.data.Dataset):
-    def __init__(self, mode, shape=None, max_wall_num=999, aug=None, camera_height=1.6, patch_num=256, keys=None):
-        if keys is None or len(keys) == 0:
-            keys = ['image', 'depth', 'ratio', 'id', 'corners']
-        if shape is None:
-            shape = [512, 1024]
-
-        assert mode == 'train' or mode == 'val' or mode == 'test' or mode is None, 'unknown mode!'
-        self.mode = mode
-        self.keys = keys
-        self.shape = shape
-        self.pano_aug = None if aug is None or mode == 'val' else PanoDataAugmentation(aug)
-        self.camera_height = camera_height
-        self.max_wall_num = max_wall_num
-        self.patch_num = patch_num
-        self.data = None
-
-    def __len__(self):
-        return len(self.data)
-
-    @staticmethod
-    def get_depth(corners, plan_y=1, length=256, visible=True):
-        visible_floor_boundary = corners2boundary(corners, length=length, visible=visible)
-        # The horizon-depth relative to plan_y
-        visible_depth = xyz2depth(uv2xyz(visible_floor_boundary, plan_y), plan_y)
-        return visible_depth
-
-    def process_data(self, label, image, patch_num):
-        """
-        :param label:
-        :param image:
-        :param patch_num:
-        :return:
-        """
-        corners = label['corners']
-        if self.pano_aug is not None:
-            corners, image = self.pano_aug.execute_aug(corners, image if 'image' in self.keys else None)
-        eps = 1e-3
-        corners[:, 1] = np.clip(corners[:, 1], 0.5+eps, 1-eps)
-
-        output = {}
-        if 'image' in self.keys:
-            image = image.transpose(2, 0, 1)
-            output['image'] = image
-
-        visible_corners = None
-        if 'corner_class' in self.keys or 'depth' in self.keys:
-            visible_corners = visibility_corners(corners)
-
-        if 'depth' in self.keys:
-            depth = self.get_depth(visible_corners, length=patch_num, visible=False)
-            assert len(depth) == patch_num, f"{label['id']}, {len(depth)}, {self.pano_aug.parameters}, {corners}"
-            output['depth'] = depth
-
-        if 'ratio' in self.keys:
-            # Why use ratio? Because when floor_height =y_plan=1, we only need to predict ceil_height(ratio).
-            output['ratio'] = label['ratio']
-
-        if 'id' in self.keys:
-            output['id'] = label['id']
-
-        if 'corners' in self.keys:
-            # all corners for evaluating Full_IoU
-            assert len(label['corners']) <= 32, "len(label['corners']):"+len(label['corners'])
-            output['corners'] = np.zeros((32, 2), dtype=np.float32)
-            output['corners'][:len(label['corners'])] = label['corners']
-
-        if 'corner_heat_map' in self.keys:
-            output['corner_heat_map'] = get_heat_map(visible_corners[..., 0])
-
-        if 'object' in self.keys and 'objects' in label:
-            output[f'object_heat_map'] = np.zeros((3, patch_num), dtype=np.float32)
-            output['object_size'] = np.zeros((3, patch_num), dtype=np.float32)  # width, height, bottom_height
-            for i, type in enumerate(label['objects']):
-                if len(label['objects'][type]) == 0:
-                    continue
-
-                u_s = []
-                for obj in label['objects'][type]:
-                    center_u = obj['center_u']
-                    u_s.append(center_u)
-                    center_pixel_u = uv2pixel(np.array([center_u]), w=patch_num, axis=0)[0]
-                    output['object_size'][0, center_pixel_u] = obj['width_u']
-                    output['object_size'][1, center_pixel_u] = obj['height_v']
-                    output['object_size'][2, center_pixel_u] = obj['boundary_v']
-                output[f'object_heat_map'][i] = get_heat_map(np.array(u_s))
-
-        return output
-
-
-if __name__ == '__main__':
-    from dataset.communal.read import read_image, read_label
-    from visualization.boundary import draw_boundaries
-    from utils.boundary import depth2boundaries
-    from tqdm import trange
-
-    # np.random.seed(0)
-    dataset = BaseDataset()
-    dataset.pano_aug = PanoDataAugmentation(aug={
-        'STRETCH': True,
-        'ROTATE': True,
-        'FLIP': True,
-    })
-    # pano_img = read_image("../src/demo.png")
-    # label = read_label("../src/demo.json")
-    pano_img_path = "../../src/dataset/mp3d/image/yqstnuAEVhm_6589ad7a5a0444b59adbf501c0f0fe53.png"
-    label_path = "../../src/dataset/mp3d/label/yqstnuAEVhm_6589ad7a5a0444b59adbf501c0f0fe53.json"
-    pano_img = read_image(pano_img_path)
-    label = read_label(label_path)
-
-    # batch test
-    for i in trange(1):
-        output = dataset.process_data(label, pano_img, 256)
-        boundary_list = depth2boundaries(output['ratio'], output['depth'], step=None)
-        draw_boundaries(output['image'].transpose(1, 2, 0), boundary_list=boundary_list, show=True)
diff --git a/spaces/Datasculptor/3D-Room-Layout-Estimation_LGT-Net/models/other/optimizer.py b/spaces/Datasculptor/3D-Room-Layout-Estimation_LGT-Net/models/other/optimizer.py
deleted file mode 100644
index 8bd1c6959dc52028d061693673222e2cb3ef150d..0000000000000000000000000000000000000000
--- a/spaces/Datasculptor/3D-Room-Layout-Estimation_LGT-Net/models/other/optimizer.py
+++ /dev/null
@@ -1,24 +0,0 @@
-""" 
-@Date: 2021/07/18
-@description:
-"""
-from torch import optim as optim
-
-
-def build_optimizer(config, model, logger):
-    name = config.TRAIN.OPTIMIZER.NAME.lower()
-
-    optimizer = None
-    if name == 'sgd':
-        optimizer = optim.SGD(model.parameters(), momentum=config.TRAIN.OPTIMIZER.MOMENTUM, nesterov=True,
-                              lr=config.TRAIN.BASE_LR, weight_decay=config.TRAIN.WEIGHT_DECAY)
-    elif name == 'adamw':
-        optimizer = optim.AdamW(model.parameters(), eps=config.TRAIN.OPTIMIZER.EPS, betas=config.TRAIN.OPTIMIZER.BETAS,
-                                lr=config.TRAIN.BASE_LR, weight_decay=config.TRAIN.WEIGHT_DECAY)
-    elif name == 'adam':
-        optimizer = optim.Adam(model.parameters(), eps=config.TRAIN.OPTIMIZER.EPS, betas=config.TRAIN.OPTIMIZER.BETAS,
-                               lr=config.TRAIN.BASE_LR, weight_decay=config.TRAIN.WEIGHT_DECAY)
-
-    logger.info(f"Build optimizer: {name}, lr:{config.TRAIN.BASE_LR}")
-
-    return optimizer
diff --git a/spaces/DeepLabCut/DeepLabCutModelZoo-SuperAnimals/README.md b/spaces/DeepLabCut/DeepLabCutModelZoo-SuperAnimals/README.md
deleted file mode 100644
index 999bbb2e309185584567b5f85ca24d5fb9cbdb0a..0000000000000000000000000000000000000000
--- a/spaces/DeepLabCut/DeepLabCutModelZoo-SuperAnimals/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: DeepLabCut Model Zoo
-emoji: 🐕🐁🐴😻🐘🐆🐿🐂🦘🦒
-colorFrom: blue
-colorTo: purple
-sdk: gradio
-sdk_version: 3.1.4
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/DiffusionArtco/Diffusion200Max/README.md b/spaces/DiffusionArtco/Diffusion200Max/README.md
deleted file mode 100644
index 1d4ec7b44d0c5a42f3ff4978e37c0070c004449f..0000000000000000000000000000000000000000
--- a/spaces/DiffusionArtco/Diffusion200Max/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: ImagineAI Imagine Generator
-emoji: 💩
-colorFrom: yellow
-colorTo: pink
-sdk: gradio
-sdk_version: 3.24.1
-app_file: app.py
-pinned: false
-duplicated_from: DiffusionArtco/Diffusion50
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Dinoking/Guccio-AI-Designer/models/biggan/pytorch_biggan/pytorch_pretrained_biggan/__init__.py b/spaces/Dinoking/Guccio-AI-Designer/models/biggan/pytorch_biggan/pytorch_pretrained_biggan/__init__.py
deleted file mode 100644
index b570848421afd921fae635569c97d0f8f5b33c80..0000000000000000000000000000000000000000
--- a/spaces/Dinoking/Guccio-AI-Designer/models/biggan/pytorch_biggan/pytorch_pretrained_biggan/__init__.py
+++ /dev/null
@@ -1,6 +0,0 @@
-from .config import BigGANConfig
-from .model import BigGAN
-from .file_utils import PYTORCH_PRETRAINED_BIGGAN_CACHE, cached_path
-from .utils import (truncated_noise_sample, save_as_images,
-                    convert_to_images, display_in_terminal,
-                    one_hot_from_int, one_hot_from_names)
diff --git a/spaces/DrHakase/word2img/README.md b/spaces/DrHakase/word2img/README.md
deleted file mode 100644
index 09c7de66dc3b24839d119d4b8277ddc26f078f5e..0000000000000000000000000000000000000000
--- a/spaces/DrHakase/word2img/README.md
+++ /dev/null
@@ -1,22 +0,0 @@
----
-title: Stabilityai Stable Diffusion 2 1
-emoji: 🔥
-colorFrom: indigo
-colorTo: red
-sdk: gradio
-sdk_version: 3.14.0
-app_file: app.py
-pinned: false
-license: mit
-tags:
-  - stable-diffusion
-  - text-to-image
-duplicated_from: abidlabs/images
-thumbnail: "https://pbs.twimg.com/media/FkjApn7aYAE1H9k?format=png&name=small"
-
----
-license: creativeml-openrail-m
-
-
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/DragGan/DragGan/stylegan_human/dnnlib/tflib/network.py b/spaces/DragGan/DragGan/stylegan_human/dnnlib/tflib/network.py
deleted file mode 100644
index bfa73dc5ff2051689d16159871d2bc7e31294502..0000000000000000000000000000000000000000
--- a/spaces/DragGan/DragGan/stylegan_human/dnnlib/tflib/network.py
+++ /dev/null
@@ -1,592 +0,0 @@
-# Copyright (c) SenseTime Research. All rights reserved.
-
-# Copyright (c) 2019, NVIDIA Corporation. All rights reserved.
-#
-# This work is made available under the Nvidia Source Code License-NC.
-# To view a copy of this license, visit
-# https://nvlabs.github.io/stylegan2/license.html
-
-"""Helper for managing networks."""
-
-import types
-import inspect
-import re
-import uuid
-import sys
-import numpy as np
-import tensorflow as tf
-
-from collections import OrderedDict
-from typing import Any, List, Tuple, Union
-
-from . import tfutil
-from .. import util
-
-from .tfutil import TfExpression, TfExpressionEx
-
-_import_handlers = []  # Custom import handlers for dealing with legacy data in pickle import.
-_import_module_src = dict()  # Source code for temporary modules created during pickle import.
-
-
-def import_handler(handler_func):
-    """Function decorator for declaring custom import handlers."""
-    _import_handlers.append(handler_func)
-    return handler_func
-
-
-class Network:
-    """Generic network abstraction.
-
-    Acts as a convenience wrapper for a parameterized network construction
-    function, providing several utility methods and convenient access to
-    the inputs/outputs/weights.
-
-    Network objects can be safely pickled and unpickled for long-term
-    archival purposes. The pickling works reliably as long as the underlying
-    network construction function is defined in a standalone Python module
-    that has no side effects or application-specific imports.
-
-    Args:
-        name: Network name. Used to select TensorFlow name and variable scopes.
-        func_name: Fully qualified name of the underlying network construction function, or a top-level function object.
-        static_kwargs: Keyword arguments to be passed in to the network construction function.
-
-    Attributes:
-        name: User-specified name, defaults to build func name if None.
-        scope: Unique TensorFlow scope containing template graph and variables, derived from the user-specified name.
-        static_kwargs: Arguments passed to the user-supplied build func.
-        components: Container for sub-networks. Passed to the build func, and retained between calls.
-        num_inputs: Number of input tensors.
-        num_outputs: Number of output tensors.
-        input_shapes: Input tensor shapes (NC or NCHW), including minibatch dimension.
-        output_shapes: Output tensor shapes (NC or NCHW), including minibatch dimension.
-        input_shape: Short-hand for input_shapes[0].
-        output_shape: Short-hand for output_shapes[0].
-        input_templates: Input placeholders in the template graph.
-        output_templates: Output tensors in the template graph.
-        input_names: Name string for each input.
-        output_names: Name string for each output.
-        own_vars: Variables defined by this network (local_name => var), excluding sub-networks.
-        vars: All variables (local_name => var).
-        trainables: All trainable variables (local_name => var).
-        var_global_to_local: Mapping from variable global names to local names.
-    """
-
-    def __init__(self, name: str = None, func_name: Any = None, **static_kwargs):
-        tfutil.assert_tf_initialized()
-        assert isinstance(name, str) or name is None
-        assert func_name is not None
-        assert isinstance(func_name, str) or util.is_top_level_function(func_name)
-        assert util.is_pickleable(static_kwargs)
-
-        self._init_fields()
-        self.name = name
-        self.static_kwargs = util.EasyDict(static_kwargs)
-
-        # Locate the user-specified network build function.
-        if util.is_top_level_function(func_name):
-            func_name = util.get_top_level_function_name(func_name)
-        module, self._build_func_name = util.get_module_from_obj_name(func_name)
-        self._build_func = util.get_obj_from_module(module, self._build_func_name)
-        assert callable(self._build_func)
-
-        # Dig up source code for the module containing the build function.
-        self._build_module_src = _import_module_src.get(module, None)
-        if self._build_module_src is None:
-            self._build_module_src = inspect.getsource(module)
-
-        # Init TensorFlow graph.
-        self._init_graph()
-        self.reset_own_vars()
-
-    def _init_fields(self) -> None:
-        self.name = None
-        self.scope = None
-        self.static_kwargs = util.EasyDict()
-        self.components = util.EasyDict()
-        self.num_inputs = 0
-        self.num_outputs = 0
-        self.input_shapes = [[]]
-        self.output_shapes = [[]]
-        self.input_shape = []
-        self.output_shape = []
-        self.input_templates = []
-        self.output_templates = []
-        self.input_names = []
-        self.output_names = []
-        self.own_vars = OrderedDict()
-        self.vars = OrderedDict()
-        self.trainables = OrderedDict()
-        self.var_global_to_local = OrderedDict()
-
-        self._build_func = None  # User-supplied build function that constructs the network.
-        self._build_func_name = None  # Name of the build function.
-        self._build_module_src = None  # Full source code of the module containing the build function.
-        self._run_cache = dict()  # Cached graph data for Network.run().
-
-    def _init_graph(self) -> None:
-        # Collect inputs.
-        self.input_names = []
-
-        for param in inspect.signature(self._build_func).parameters.values():
-            if param.kind == param.POSITIONAL_OR_KEYWORD and param.default is param.empty:
-                self.input_names.append(param.name)
-
-        self.num_inputs = len(self.input_names)
-        assert self.num_inputs >= 1
-
-        # Choose name and scope.
-        if self.name is None:
-            self.name = self._build_func_name
-        assert re.match("^[A-Za-z0-9_.\\-]*$", self.name)
-        with tf.name_scope(None):
-            self.scope = tf.get_default_graph().unique_name(self.name, mark_as_used=True)
-
-        # Finalize build func kwargs.
-        build_kwargs = dict(self.static_kwargs)
-        build_kwargs["is_template_graph"] = True
-        build_kwargs["components"] = self.components
-
-        # Build template graph.
-        with tfutil.absolute_variable_scope(self.scope, reuse=False), tfutil.absolute_name_scope(self.scope):  # ignore surrounding scopes
-            assert tf.get_variable_scope().name == self.scope
-            assert tf.get_default_graph().get_name_scope() == self.scope
-            with tf.control_dependencies(None):  # ignore surrounding control dependencies
-                self.input_templates = [tf.placeholder(tf.float32, name=name) for name in self.input_names]
-                out_expr = self._build_func(*self.input_templates, **build_kwargs)
-
-        # Collect outputs.
-        assert tfutil.is_tf_expression(out_expr) or isinstance(out_expr, tuple)
-        self.output_templates = [out_expr] if tfutil.is_tf_expression(out_expr) else list(out_expr)
-        self.num_outputs = len(self.output_templates)
-        assert self.num_outputs >= 1
-        assert all(tfutil.is_tf_expression(t) for t in self.output_templates)
-
-        # Perform sanity checks.
-        if any(t.shape.ndims is None for t in self.input_templates):
-            raise ValueError("Network input shapes not defined. Please call x.set_shape() for each input.")
-        if any(t.shape.ndims is None for t in self.output_templates):
-            raise ValueError("Network output shapes not defined. Please call x.set_shape() where applicable.")
-        if any(not isinstance(comp, Network) for comp in self.components.values()):
-            raise ValueError("Components of a Network must be Networks themselves.")
-        if len(self.components) != len(set(comp.name for comp in self.components.values())):
-            raise ValueError("Components of a Network must have unique names.")
-
-        # List inputs and outputs.
-        self.input_shapes = [t.shape.as_list() for t in self.input_templates]
-        self.output_shapes = [t.shape.as_list() for t in self.output_templates]
-        self.input_shape = self.input_shapes[0]
-        self.output_shape = self.output_shapes[0]
-        self.output_names = [t.name.split("/")[-1].split(":")[0] for t in self.output_templates]
-
-        # List variables.
-        self.own_vars = OrderedDict((var.name[len(self.scope) + 1:].split(":")[0], var) for var in tf.global_variables(self.scope + "/"))
-        self.vars = OrderedDict(self.own_vars)
-        self.vars.update((comp.name + "/" + name, var) for comp in self.components.values() for name, var in comp.vars.items())
-        self.trainables = OrderedDict((name, var) for name, var in self.vars.items() if var.trainable)
-        self.var_global_to_local = OrderedDict((var.name.split(":")[0], name) for name, var in self.vars.items())
-
-    def reset_own_vars(self) -> None:
-        """Re-initialize all variables of this network, excluding sub-networks."""
-        tfutil.run([var.initializer for var in self.own_vars.values()])
-
-    def reset_vars(self) -> None:
-        """Re-initialize all variables of this network, including sub-networks."""
-        tfutil.run([var.initializer for var in self.vars.values()])
-
-    def reset_trainables(self) -> None:
-        """Re-initialize all trainable variables of this network, including sub-networks."""
-        tfutil.run([var.initializer for var in self.trainables.values()])
-
-    def get_output_for(self, *in_expr: TfExpression, return_as_list: bool = False, **dynamic_kwargs) -> Union[TfExpression, List[TfExpression]]:
-        """Construct TensorFlow expression(s) for the output(s) of this network, given the input expression(s)."""
-        assert len(in_expr) == self.num_inputs
-        assert not all(expr is None for expr in in_expr)
-
-        # Finalize build func kwargs.
-        build_kwargs = dict(self.static_kwargs)
-        build_kwargs.update(dynamic_kwargs)
-        build_kwargs["is_template_graph"] = False
-        build_kwargs["components"] = self.components
-
-        # Build TensorFlow graph to evaluate the network.
-        with tfutil.absolute_variable_scope(self.scope, reuse=True), tf.name_scope(self.name):
-            assert tf.get_variable_scope().name == self.scope
-            valid_inputs = [expr for expr in in_expr if expr is not None]
-            final_inputs = []
-            for expr, name, shape in zip(in_expr, self.input_names, self.input_shapes):
-                if expr is not None:
-                    expr = tf.identity(expr, name=name)
-                else:
-                    expr = tf.zeros([tf.shape(valid_inputs[0])[0]] + shape[1:], name=name)
-                final_inputs.append(expr)
-            out_expr = self._build_func(*final_inputs, **build_kwargs)
-
-        # Propagate input shapes back to the user-specified expressions.
-        for expr, final in zip(in_expr, final_inputs):
-            if isinstance(expr, tf.Tensor):
-                expr.set_shape(final.shape)
-
-        # Express outputs in the desired format.
-        assert tfutil.is_tf_expression(out_expr) or isinstance(out_expr, tuple)
-        if return_as_list:
-            out_expr = [out_expr] if tfutil.is_tf_expression(out_expr) else list(out_expr)
-        return out_expr
-
-    def get_var_local_name(self, var_or_global_name: Union[TfExpression, str]) -> str:
-        """Get the local name of a given variable, without any surrounding name scopes."""
-        assert tfutil.is_tf_expression(var_or_global_name) or isinstance(var_or_global_name, str)
-        global_name = var_or_global_name if isinstance(var_or_global_name, str) else var_or_global_name.name
-        return self.var_global_to_local[global_name]
-
-    def find_var(self, var_or_local_name: Union[TfExpression, str]) -> TfExpression:
-        """Find variable by local or global name."""
-        assert tfutil.is_tf_expression(var_or_local_name) or isinstance(var_or_local_name, str)
-        return self.vars[var_or_local_name] if isinstance(var_or_local_name, str) else var_or_local_name
-
-    def get_var(self, var_or_local_name: Union[TfExpression, str]) -> np.ndarray:
-        """Get the value of a given variable as NumPy array.
-        Note: This method is very inefficient -- prefer to use tflib.run(list_of_vars) whenever possible."""
-        return self.find_var(var_or_local_name).eval()
-
-    def set_var(self, var_or_local_name: Union[TfExpression, str], new_value: Union[int, float, np.ndarray]) -> None:
-        """Set the value of a given variable based on the given NumPy array.
-        Note: This method is very inefficient -- prefer to use tflib.set_vars() whenever possible."""
-        tfutil.set_vars({self.find_var(var_or_local_name): new_value})
-
-    def __getstate__(self) -> dict:
-        """Pickle export."""
-        state = dict()
-        state["version"]            = 4
-        state["name"]               = self.name
-        state["static_kwargs"]      = dict(self.static_kwargs)
-        state["components"]         = dict(self.components)
-        state["build_module_src"]   = self._build_module_src
-        state["build_func_name"]    = self._build_func_name
-        state["variables"]          = list(zip(self.own_vars.keys(), tfutil.run(list(self.own_vars.values()))))
-        return state
-
-    def __setstate__(self, state: dict) -> None:
-        """Pickle import."""
-        # pylint: disable=attribute-defined-outside-init
-        tfutil.assert_tf_initialized()
-        self._init_fields()
-
-        # Execute custom import handlers.
-        for handler in _import_handlers:
-            state = handler(state)
-
-        # Set basic fields.
-        assert state["version"] in [2, 3, 4]
-        self.name = state["name"]
-        self.static_kwargs = util.EasyDict(state["static_kwargs"])
-        self.components = util.EasyDict(state.get("components", {}))
-        self._build_module_src = state["build_module_src"]
-        self._build_func_name = state["build_func_name"]
-
-        # Create temporary module from the imported source code.
-        module_name = "_tflib_network_import_" + uuid.uuid4().hex
-        module = types.ModuleType(module_name)
-        sys.modules[module_name] = module
-        _import_module_src[module] = self._build_module_src
-        exec(self._build_module_src, module.__dict__) # pylint: disable=exec-used
-
-        # Locate network build function in the temporary module.
-        self._build_func = util.get_obj_from_module(module, self._build_func_name)
-        assert callable(self._build_func)
-
-        # Init TensorFlow graph.
-        self._init_graph()
-        self.reset_own_vars()
-        tfutil.set_vars({self.find_var(name): value for name, value in state["variables"]})
-
-    def clone(self, name: str = None, **new_static_kwargs) -> "Network":
-        """Create a clone of this network with its own copy of the variables."""
-        # pylint: disable=protected-access
-        net = object.__new__(Network)
-        net._init_fields()
-        net.name = name if name is not None else self.name
-        net.static_kwargs = util.EasyDict(self.static_kwargs)
-        net.static_kwargs.update(new_static_kwargs)
-        net._build_module_src = self._build_module_src
-        net._build_func_name = self._build_func_name
-        net._build_func = self._build_func
-        net._init_graph()
-        net.copy_vars_from(self)
-        return net
-
-    def copy_own_vars_from(self, src_net: "Network") -> None:
-        """Copy the values of all variables from the given network, excluding sub-networks."""
-        names = [name for name in self.own_vars.keys() if name in src_net.own_vars]
-        tfutil.set_vars(tfutil.run({self.vars[name]: src_net.vars[name] for name in names}))
-
-    def copy_vars_from(self, src_net: "Network") -> None:
-        """Copy the values of all variables from the given network, including sub-networks."""
-        names = [name for name in self.vars.keys() if name in src_net.vars]
-        tfutil.set_vars(tfutil.run({self.vars[name]: src_net.vars[name] for name in names}))
-
-    def copy_trainables_from(self, src_net: "Network") -> None:
-        """Copy the values of all trainable variables from the given network, including sub-networks."""
-        names = [name for name in self.trainables.keys() if name in src_net.trainables]
-        tfutil.set_vars(tfutil.run({self.vars[name]: src_net.vars[name] for name in names}))
-
-    def convert(self, new_func_name: str, new_name: str = None, **new_static_kwargs) -> "Network":
-        """Create new network with the given parameters, and copy all variables from this network."""
-        if new_name is None:
-            new_name = self.name
-        static_kwargs = dict(self.static_kwargs)
-        static_kwargs.update(new_static_kwargs)
-        net = Network(name=new_name, func_name=new_func_name, **static_kwargs)
-        net.copy_vars_from(self)
-        return net
-
-    def setup_as_moving_average_of(self, src_net: "Network", beta: TfExpressionEx = 0.99, beta_nontrainable: TfExpressionEx = 0.0) -> tf.Operation:
-        """Construct a TensorFlow op that updates the variables of this network
-        to be slightly closer to those of the given network."""
-        with tfutil.absolute_name_scope(self.scope + "/_MovingAvg"):
-            ops = []
-            for name, var in self.vars.items():
-                if name in src_net.vars:
-                    cur_beta = beta if name in self.trainables else beta_nontrainable
-                    new_value = tfutil.lerp(src_net.vars[name], var, cur_beta)
-                    ops.append(var.assign(new_value))
-            return tf.group(*ops)
-
-    def run(self,
-            *in_arrays: Tuple[Union[np.ndarray, None], ...],
-            input_transform: dict = None,
-            output_transform: dict = None,
-            return_as_list: bool = False,
-            print_progress: bool = False,
-            minibatch_size: int = None,
-            num_gpus: int = 1,
-            assume_frozen: bool = False,
-            **dynamic_kwargs) -> Union[np.ndarray, Tuple[np.ndarray, ...], List[np.ndarray]]:
-        """Run this network for the given NumPy array(s), and return the output(s) as NumPy array(s).
-
-        Args:
-            input_transform:    A dict specifying a custom transformation to be applied to the input tensor(s) before evaluating the network.
-                                The dict must contain a 'func' field that points to a top-level function. The function is called with the input
-                                TensorFlow expression(s) as positional arguments. Any remaining fields of the dict will be passed in as kwargs.
-            output_transform:   A dict specifying a custom transformation to be applied to the output tensor(s) after evaluating the network.
-                                The dict must contain a 'func' field that points to a top-level function. The function is called with the output
-                                TensorFlow expression(s) as positional arguments. Any remaining fields of the dict will be passed in as kwargs.
-            return_as_list:     True = return a list of NumPy arrays, False = return a single NumPy array, or a tuple if there are multiple outputs.
-            print_progress:     Print progress to the console? Useful for very large input arrays.
-            minibatch_size:     Maximum minibatch size to use, None = disable batching.
-            num_gpus:           Number of GPUs to use.
-            assume_frozen:      Improve multi-GPU performance by assuming that the trainable parameters will remain changed between calls.
-            dynamic_kwargs:     Additional keyword arguments to be passed into the network build function.
-        """
-        assert len(in_arrays) == self.num_inputs
-        assert not all(arr is None for arr in in_arrays)
-        assert input_transform is None or util.is_top_level_function(input_transform["func"])
-        assert output_transform is None or util.is_top_level_function(output_transform["func"])
-        output_transform, dynamic_kwargs = _handle_legacy_output_transforms(output_transform, dynamic_kwargs)
-        num_items = in_arrays[0].shape[0]
-        if minibatch_size is None:
-            minibatch_size = num_items
-
-        # Construct unique hash key from all arguments that affect the TensorFlow graph.
-        key = dict(input_transform=input_transform, output_transform=output_transform, num_gpus=num_gpus, assume_frozen=assume_frozen, dynamic_kwargs=dynamic_kwargs)
-        def unwind_key(obj):
-            if isinstance(obj, dict):
-                return [(key, unwind_key(value)) for key, value in sorted(obj.items())]
-            if callable(obj):
-                return util.get_top_level_function_name(obj)
-            return obj
-        key = repr(unwind_key(key))
-
-        # Build graph.
-        if key not in self._run_cache:
-            with tfutil.absolute_name_scope(self.scope + "/_Run"), tf.control_dependencies(None):
-                with tf.device("/cpu:0"):
-                    in_expr = [tf.placeholder(tf.float32, name=name) for name in self.input_names]
-                    in_split = list(zip(*[tf.split(x, num_gpus) for x in in_expr]))
-
-                out_split = []
-                for gpu in range(num_gpus):
-                    with tf.device("/gpu:%d" % gpu):
-                        net_gpu = self.clone() if assume_frozen else self
-                        in_gpu = in_split[gpu]
-
-                        if input_transform is not None:
-                            in_kwargs = dict(input_transform)
-                            in_gpu = in_kwargs.pop("func")(*in_gpu, **in_kwargs)
-                            in_gpu = [in_gpu] if tfutil.is_tf_expression(in_gpu) else list(in_gpu)
-
-                        assert len(in_gpu) == self.num_inputs
-                        out_gpu = net_gpu.get_output_for(*in_gpu, return_as_list=True, **dynamic_kwargs)
-
-                        if output_transform is not None:
-                            out_kwargs = dict(output_transform)
-                            out_gpu = out_kwargs.pop("func")(*out_gpu, **out_kwargs)
-                            out_gpu = [out_gpu] if tfutil.is_tf_expression(out_gpu) else list(out_gpu)
-
-                        assert len(out_gpu) == self.num_outputs
-                        out_split.append(out_gpu)
-
-                with tf.device("/cpu:0"):
-                    out_expr = [tf.concat(outputs, axis=0) for outputs in zip(*out_split)]
-                    self._run_cache[key] = in_expr, out_expr
-
-        # Run minibatches.
-        in_expr, out_expr = self._run_cache[key]
-        out_arrays = [np.empty([num_items] + expr.shape.as_list()[1:], expr.dtype.name) for expr in out_expr]
-
-        for mb_begin in range(0, num_items, minibatch_size):
-            if print_progress:
-                print("\r%d / %d" % (mb_begin, num_items), end="")
-
-            mb_end = min(mb_begin + minibatch_size, num_items)
-            mb_num = mb_end - mb_begin
-            mb_in = [src[mb_begin : mb_end] if src is not None else np.zeros([mb_num] + shape[1:]) for src, shape in zip(in_arrays, self.input_shapes)]
-            mb_out = tf.get_default_session().run(out_expr, dict(zip(in_expr, mb_in)))
-
-            for dst, src in zip(out_arrays, mb_out):
-                dst[mb_begin: mb_end] = src
-
-        # Done.
-        if print_progress:
-            print("\r%d / %d" % (num_items, num_items))
-
-        if not return_as_list:
-            out_arrays = out_arrays[0] if len(out_arrays) == 1 else tuple(out_arrays)
-        return out_arrays
-
-    def list_ops(self) -> List[TfExpression]:
-        include_prefix = self.scope + "/"
-        exclude_prefix = include_prefix + "_"
-        ops = tf.get_default_graph().get_operations()
-        ops = [op for op in ops if op.name.startswith(include_prefix)]
-        ops = [op for op in ops if not op.name.startswith(exclude_prefix)]
-        return ops
-
-    def list_layers(self) -> List[Tuple[str, TfExpression, List[TfExpression]]]:
-        """Returns a list of (layer_name, output_expr, trainable_vars) tuples corresponding to
-        individual layers of the network. Mainly intended to be used for reporting."""
-        layers = []
-
-        def recurse(scope, parent_ops, parent_vars, level):
-            # Ignore specific patterns.
-            if any(p in scope for p in ["/Shape", "/strided_slice", "/Cast", "/concat", "/Assign"]):
-                return
-
-            # Filter ops and vars by scope.
-            global_prefix = scope + "/"
-            local_prefix = global_prefix[len(self.scope) + 1:]
-            cur_ops = [op for op in parent_ops if op.name.startswith(global_prefix) or op.name == global_prefix[:-1]]
-            cur_vars = [(name, var) for name, var in parent_vars if name.startswith(local_prefix) or name == local_prefix[:-1]]
-            if not cur_ops and not cur_vars:
-                return
-
-            # Filter out all ops related to variables.
-            for var in [op for op in cur_ops if op.type.startswith("Variable")]:
-                var_prefix = var.name + "/"
-                cur_ops = [op for op in cur_ops if not op.name.startswith(var_prefix)]
-
-            # Scope does not contain ops as immediate children => recurse deeper.
-            contains_direct_ops = any("/" not in op.name[len(global_prefix):] and op.type not in ["Identity", "Cast", "Transpose"] for op in cur_ops)
-            if (level == 0 or not contains_direct_ops) and (len(cur_ops) + len(cur_vars)) > 1:
-                visited = set()
-                for rel_name in [op.name[len(global_prefix):] for op in cur_ops] + [name[len(local_prefix):] for name, _var in cur_vars]:
-                    token = rel_name.split("/")[0]
-                    if token not in visited:
-                        recurse(global_prefix + token, cur_ops, cur_vars, level + 1)
-                        visited.add(token)
-                return
-
-            # Report layer.
-            layer_name = scope[len(self.scope) + 1:]
-            layer_output = cur_ops[-1].outputs[0] if cur_ops else cur_vars[-1][1]
-            layer_trainables = [var for _name, var in cur_vars if var.trainable]
-            layers.append((layer_name, layer_output, layer_trainables))
-
-        recurse(self.scope, self.list_ops(), list(self.vars.items()), 0)
-        return layers
-
-    def print_layers(self, title: str = None, hide_layers_with_no_params: bool = False) -> None:
-        """Print a summary table of the network structure."""
-        rows = [[title if title is not None else self.name, "Params", "OutputShape", "WeightShape"]]
-        rows += [["---"] * 4]
-        total_params = 0
-
-        for layer_name, layer_output, layer_trainables in self.list_layers():
-            num_params = sum(int(np.prod(var.shape.as_list())) for var in layer_trainables)
-            weights = [var for var in layer_trainables if var.name.endswith("/weight:0")]
-            weights.sort(key=lambda x: len(x.name))
-            if len(weights) == 0 and len(layer_trainables) == 1:
-                weights = layer_trainables
-            total_params += num_params
-
-            if not hide_layers_with_no_params or num_params != 0:
-                num_params_str = str(num_params) if num_params > 0 else "-"
-                output_shape_str = str(layer_output.shape)
-                weight_shape_str = str(weights[0].shape) if len(weights) >= 1 else "-"
-                rows += [[layer_name, num_params_str, output_shape_str, weight_shape_str]]
-
-        rows += [["---"] * 4]
-        rows += [["Total", str(total_params), "", ""]]
-
-        widths = [max(len(cell) for cell in column) for column in zip(*rows)]
-        print()
-        for row in rows:
-            print("  ".join(cell + " " * (width - len(cell)) for cell, width in zip(row, widths)))
-        print()
-
-    def setup_weight_histograms(self, title: str = None) -> None:
-        """Construct summary ops to include histograms of all trainable parameters in TensorBoard."""
-        if title is None:
-            title = self.name
-
-        with tf.name_scope(None), tf.device(None), tf.control_dependencies(None):
-            for local_name, var in self.trainables.items():
-                if "/" in local_name:
-                    p = local_name.split("/")
-                    name = title + "_" + p[-1] + "/" + "_".join(p[:-1])
-                else:
-                    name = title + "_toplevel/" + local_name
-
-                tf.summary.histogram(name, var)
-
-#----------------------------------------------------------------------------
-# Backwards-compatible emulation of legacy output transformation in Network.run().
-
-_print_legacy_warning = True
-
-def _handle_legacy_output_transforms(output_transform, dynamic_kwargs):
-    global _print_legacy_warning
-    legacy_kwargs = ["out_mul", "out_add", "out_shrink", "out_dtype"]
-    if not any(kwarg in dynamic_kwargs for kwarg in legacy_kwargs):
-        return output_transform, dynamic_kwargs
-
-    if _print_legacy_warning:
-        _print_legacy_warning = False
-        print()
-        print("WARNING: Old-style output transformations in Network.run() are deprecated.")
-        print("Consider using 'output_transform=dict(func=tflib.convert_images_to_uint8)'")
-        print("instead of 'out_mul=127.5, out_add=127.5, out_dtype=np.uint8'.")
-        print()
-    assert output_transform is None
-
-    new_kwargs = dict(dynamic_kwargs)
-    new_transform = {kwarg: new_kwargs.pop(kwarg) for kwarg in legacy_kwargs if kwarg in dynamic_kwargs}
-    new_transform["func"] = _legacy_output_transform_func
-    return new_transform, new_kwargs
-
-def _legacy_output_transform_func(*expr, out_mul=1.0, out_add=0.0, out_shrink=1, out_dtype=None):
-    if out_mul != 1.0:
-        expr = [x * out_mul for x in expr]
-
-    if out_add != 0.0:
-        expr = [x + out_add for x in expr]
-
-    if out_shrink > 1:
-        ksize = [1, 1, out_shrink, out_shrink]
-        expr = [tf.nn.avg_pool(x, ksize=ksize, strides=ksize, padding="VALID", data_format="NCHW") for x in expr]
-
-    if out_dtype is not None:
-        if tf.as_dtype(out_dtype).is_integer:
-            expr = [tf.round(x) for x in expr]
-        expr = [tf.saturate_cast(x, out_dtype) for x in expr]
-    return expr
diff --git a/spaces/ECCV2022/bytetrack/exps/example/mot/yolox_x_mix_mot20_ch.py b/spaces/ECCV2022/bytetrack/exps/example/mot/yolox_x_mix_mot20_ch.py
deleted file mode 100644
index cff6b4f868607a5f3e2bb365c49acbc401f37bb0..0000000000000000000000000000000000000000
--- a/spaces/ECCV2022/bytetrack/exps/example/mot/yolox_x_mix_mot20_ch.py
+++ /dev/null
@@ -1,139 +0,0 @@
-# encoding: utf-8
-import os
-import random
-import torch
-import torch.nn as nn
-import torch.distributed as dist
-
-from yolox.exp import Exp as MyExp
-from yolox.data import get_yolox_datadir
-
-class Exp(MyExp):
-    def __init__(self):
-        super(Exp, self).__init__()
-        self.num_classes = 1
-        self.depth = 1.33
-        self.width = 1.25
-        self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0]
-        self.train_ann = "train.json"
-        self.val_ann = "test.json"   # change to train.json when running on training set
-        self.input_size = (896, 1600)
-        self.test_size = (896, 1600)
-        #self.test_size = (736, 1920)
-        self.random_size = (20, 36)
-        self.max_epoch = 80
-        self.print_interval = 20
-        self.eval_interval = 5
-        self.test_conf = 0.001
-        self.nmsthre = 0.7
-        self.no_aug_epochs = 10
-        self.basic_lr_per_img = 0.001 / 64.0
-        self.warmup_epochs = 1
-
-    def get_data_loader(self, batch_size, is_distributed, no_aug=False):
-        from yolox.data import (
-            MOTDataset,
-            TrainTransform,
-            YoloBatchSampler,
-            DataLoader,
-            InfiniteSampler,
-            MosaicDetection,
-        )
-
-        dataset = MOTDataset(
-            data_dir=os.path.join(get_yolox_datadir(), "mix_mot20_ch"),
-            json_file=self.train_ann,
-            name='',
-            img_size=self.input_size,
-            preproc=TrainTransform(
-                rgb_means=(0.485, 0.456, 0.406),
-                std=(0.229, 0.224, 0.225),
-                max_labels=600,
-            ),
-        )
-
-        dataset = MosaicDetection(
-            dataset,
-            mosaic=not no_aug,
-            img_size=self.input_size,
-            preproc=TrainTransform(
-                rgb_means=(0.485, 0.456, 0.406),
-                std=(0.229, 0.224, 0.225),
-                max_labels=1200,
-            ),
-            degrees=self.degrees,
-            translate=self.translate,
-            scale=self.scale,
-            shear=self.shear,
-            perspective=self.perspective,
-            enable_mixup=self.enable_mixup,
-        )
-
-        self.dataset = dataset
-
-        if is_distributed:
-            batch_size = batch_size // dist.get_world_size()
-
-        sampler = InfiniteSampler(
-            len(self.dataset), seed=self.seed if self.seed else 0
-        )
-
-        batch_sampler = YoloBatchSampler(
-            sampler=sampler,
-            batch_size=batch_size,
-            drop_last=False,
-            input_dimension=self.input_size,
-            mosaic=not no_aug,
-        )
-
-        dataloader_kwargs = {"num_workers": self.data_num_workers, "pin_memory": True}
-        dataloader_kwargs["batch_sampler"] = batch_sampler
-        train_loader = DataLoader(self.dataset, **dataloader_kwargs)
-
-        return train_loader
-
-    def get_eval_loader(self, batch_size, is_distributed, testdev=False):
-        from yolox.data import MOTDataset, ValTransform
-
-        valdataset = MOTDataset(
-            data_dir=os.path.join(get_yolox_datadir(), "MOT20"),
-            json_file=self.val_ann,
-            img_size=self.test_size,
-            name='test', # change to train when running on training set
-            preproc=ValTransform(
-                rgb_means=(0.485, 0.456, 0.406),
-                std=(0.229, 0.224, 0.225),
-            ),
-        )
-
-        if is_distributed:
-            batch_size = batch_size // dist.get_world_size()
-            sampler = torch.utils.data.distributed.DistributedSampler(
-                valdataset, shuffle=False
-            )
-        else:
-            sampler = torch.utils.data.SequentialSampler(valdataset)
-
-        dataloader_kwargs = {
-            "num_workers": self.data_num_workers,
-            "pin_memory": True,
-            "sampler": sampler,
-        }
-        dataloader_kwargs["batch_size"] = batch_size
-        val_loader = torch.utils.data.DataLoader(valdataset, **dataloader_kwargs)
-
-        return val_loader
-
-    def get_evaluator(self, batch_size, is_distributed, testdev=False):
-        from yolox.evaluators import COCOEvaluator
-
-        val_loader = self.get_eval_loader(batch_size, is_distributed, testdev=testdev)
-        evaluator = COCOEvaluator(
-            dataloader=val_loader,
-            img_size=self.test_size,
-            confthre=self.test_conf,
-            nmsthre=self.nmsthre,
-            num_classes=self.num_classes,
-            testdev=testdev,
-        )
-        return evaluator
diff --git a/spaces/Eddycrack864/Applio-Inference/infer/lib/uvr5_pack/lib_v5/layers_537238KB.py b/spaces/Eddycrack864/Applio-Inference/infer/lib/uvr5_pack/lib_v5/layers_537238KB.py
deleted file mode 100644
index 9b127bc6427f5c60c8cf85603a3d8a093c3501c4..0000000000000000000000000000000000000000
--- a/spaces/Eddycrack864/Applio-Inference/infer/lib/uvr5_pack/lib_v5/layers_537238KB.py
+++ /dev/null
@@ -1,126 +0,0 @@
-import torch
-import torch.nn.functional as F
-from torch import nn
-
-from . import spec_utils
-
-
-class Conv2DBNActiv(nn.Module):
-    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
-        super(Conv2DBNActiv, self).__init__()
-        self.conv = nn.Sequential(
-            nn.Conv2d(
-                nin,
-                nout,
-                kernel_size=ksize,
-                stride=stride,
-                padding=pad,
-                dilation=dilation,
-                bias=False,
-            ),
-            nn.BatchNorm2d(nout),
-            activ(),
-        )
-
-    def __call__(self, x):
-        return self.conv(x)
-
-
-class SeperableConv2DBNActiv(nn.Module):
-    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
-        super(SeperableConv2DBNActiv, self).__init__()
-        self.conv = nn.Sequential(
-            nn.Conv2d(
-                nin,
-                nin,
-                kernel_size=ksize,
-                stride=stride,
-                padding=pad,
-                dilation=dilation,
-                groups=nin,
-                bias=False,
-            ),
-            nn.Conv2d(nin, nout, kernel_size=1, bias=False),
-            nn.BatchNorm2d(nout),
-            activ(),
-        )
-
-    def __call__(self, x):
-        return self.conv(x)
-
-
-class Encoder(nn.Module):
-    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.LeakyReLU):
-        super(Encoder, self).__init__()
-        self.conv1 = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
-        self.conv2 = Conv2DBNActiv(nout, nout, ksize, stride, pad, activ=activ)
-
-    def __call__(self, x):
-        skip = self.conv1(x)
-        h = self.conv2(skip)
-
-        return h, skip
-
-
-class Decoder(nn.Module):
-    def __init__(
-        self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.ReLU, dropout=False
-    ):
-        super(Decoder, self).__init__()
-        self.conv = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
-        self.dropout = nn.Dropout2d(0.1) if dropout else None
-
-    def __call__(self, x, skip=None):
-        x = F.interpolate(x, scale_factor=2, mode="bilinear", align_corners=True)
-        if skip is not None:
-            skip = spec_utils.crop_center(skip, x)
-            x = torch.cat([x, skip], dim=1)
-        h = self.conv(x)
-
-        if self.dropout is not None:
-            h = self.dropout(h)
-
-        return h
-
-
-class ASPPModule(nn.Module):
-    def __init__(self, nin, nout, dilations=(4, 8, 16, 32, 64), activ=nn.ReLU):
-        super(ASPPModule, self).__init__()
-        self.conv1 = nn.Sequential(
-            nn.AdaptiveAvgPool2d((1, None)),
-            Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ),
-        )
-        self.conv2 = Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ)
-        self.conv3 = SeperableConv2DBNActiv(
-            nin, nin, 3, 1, dilations[0], dilations[0], activ=activ
-        )
-        self.conv4 = SeperableConv2DBNActiv(
-            nin, nin, 3, 1, dilations[1], dilations[1], activ=activ
-        )
-        self.conv5 = SeperableConv2DBNActiv(
-            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
-        )
-        self.conv6 = SeperableConv2DBNActiv(
-            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
-        )
-        self.conv7 = SeperableConv2DBNActiv(
-            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
-        )
-        self.bottleneck = nn.Sequential(
-            Conv2DBNActiv(nin * 7, nout, 1, 1, 0, activ=activ), nn.Dropout2d(0.1)
-        )
-
-    def forward(self, x):
-        _, _, h, w = x.size()
-        feat1 = F.interpolate(
-            self.conv1(x), size=(h, w), mode="bilinear", align_corners=True
-        )
-        feat2 = self.conv2(x)
-        feat3 = self.conv3(x)
-        feat4 = self.conv4(x)
-        feat5 = self.conv5(x)
-        feat6 = self.conv6(x)
-        feat7 = self.conv7(x)
-        out = torch.cat((feat1, feat2, feat3, feat4, feat5, feat6, feat7), dim=1)
-        bottle = self.bottleneck(out)
-        return bottle
diff --git a/spaces/Eddycrack864/Applio-Inference/infer_uvr5.py b/spaces/Eddycrack864/Applio-Inference/infer_uvr5.py
deleted file mode 100644
index 8c8c05429a1d65dd8b198f16a8ea8c6e68991c07..0000000000000000000000000000000000000000
--- a/spaces/Eddycrack864/Applio-Inference/infer_uvr5.py
+++ /dev/null
@@ -1,363 +0,0 @@
-import os, sys, torch, warnings, pdb
-
-now_dir = os.getcwd()
-sys.path.append(now_dir)
-from json import load as ll
-
-warnings.filterwarnings("ignore")
-import librosa
-import importlib
-import numpy as np
-import hashlib, math
-from tqdm import tqdm
-from lib.uvr5_pack.lib_v5 import spec_utils
-from lib.uvr5_pack.utils import _get_name_params, inference
-from lib.uvr5_pack.lib_v5.model_param_init import ModelParameters
-import soundfile as sf
-from lib.uvr5_pack.lib_v5.nets_new import CascadedNet
-from lib.uvr5_pack.lib_v5 import nets_61968KB as nets
-
-
-class _audio_pre_:
-    def __init__(self, agg, model_path, device, is_half):
-        self.model_path = model_path
-        self.device = device
-        self.data = {
-            # Processing Options
-            "postprocess": False,
-            "tta": False,
-            # Constants
-            "window_size": 512,
-            "agg": agg,
-            "high_end_process": "mirroring",
-        }
-        mp = ModelParameters("lib/uvr5_pack/lib_v5/modelparams/4band_v2.json")
-        model = nets.CascadedASPPNet(mp.param["bins"] * 2)
-        cpk = torch.load(model_path, map_location="cpu")
-        model.load_state_dict(cpk)
-        model.eval()
-        if is_half:
-            model = model.half().to(device)
-        else:
-            model = model.to(device)
-
-        self.mp = mp
-        self.model = model
-
-    def _path_audio_(self, music_file, ins_root=None, vocal_root=None, format="flac"):
-        if ins_root is None and vocal_root is None:
-            return "No save root."
-        name = os.path.basename(music_file)
-        if ins_root is not None:
-            os.makedirs(ins_root, exist_ok=True)
-        if vocal_root is not None:
-            os.makedirs(vocal_root, exist_ok=True)
-        X_wave, y_wave, X_spec_s, y_spec_s = {}, {}, {}, {}
-        bands_n = len(self.mp.param["band"])
-        # print(bands_n)
-        for d in range(bands_n, 0, -1):
-            bp = self.mp.param["band"][d]
-            if d == bands_n:  # high-end band
-                (
-                    X_wave[d],
-                    _,
-                ) = librosa.core.load(  
-                    music_file,
-                    bp["sr"],
-                    False,
-                    dtype=np.float32,
-                    res_type=bp["res_type"],
-                )
-                if X_wave[d].ndim == 1:
-                    X_wave[d] = np.asfortranarray([X_wave[d], X_wave[d]])
-            else:  # lower bands
-                X_wave[d] = librosa.core.resample(
-                    X_wave[d + 1],
-                    self.mp.param["band"][d + 1]["sr"],
-                    bp["sr"],
-                    res_type=bp["res_type"],
-                )
-            # Stft of wave source
-            X_spec_s[d] = spec_utils.wave_to_spectrogram_mt(
-                X_wave[d],
-                bp["hl"],
-                bp["n_fft"],
-                self.mp.param["mid_side"],
-                self.mp.param["mid_side_b2"],
-                self.mp.param["reverse"],
-            )
-            # pdb.set_trace()
-            if d == bands_n and self.data["high_end_process"] != "none":
-                input_high_end_h = (bp["n_fft"] // 2 - bp["crop_stop"]) + (
-                    self.mp.param["pre_filter_stop"] - self.mp.param["pre_filter_start"]
-                )
-                input_high_end = X_spec_s[d][
-                    :, bp["n_fft"] // 2 - input_high_end_h : bp["n_fft"] // 2, :
-                ]
-
-        X_spec_m = spec_utils.combine_spectrograms(X_spec_s, self.mp)
-        aggresive_set = float(self.data["agg"] / 100)
-        aggressiveness = {
-            "value": aggresive_set,
-            "split_bin": self.mp.param["band"][1]["crop_stop"],
-        }
-        with torch.no_grad():
-            pred, X_mag, X_phase = inference(
-                X_spec_m, self.device, self.model, aggressiveness, self.data
-            )
-        # Postprocess
-        if self.data["postprocess"]:
-            pred_inv = np.clip(X_mag - pred, 0, np.inf)
-            pred = spec_utils.mask_silence(pred, pred_inv)
-        y_spec_m = pred * X_phase
-        v_spec_m = X_spec_m - y_spec_m
-
-        if ins_root is not None:
-            if self.data["high_end_process"].startswith("mirroring"):
-                input_high_end_ = spec_utils.mirroring(
-                    self.data["high_end_process"], y_spec_m, input_high_end, self.mp
-                )
-                wav_instrument = spec_utils.cmb_spectrogram_to_wave(
-                    y_spec_m, self.mp, input_high_end_h, input_high_end_
-                )
-            else:
-                wav_instrument = spec_utils.cmb_spectrogram_to_wave(y_spec_m, self.mp)
-            print("%s instruments done" % name)
-            if format in ["wav", "flac"]:
-                sf.write(
-                    os.path.join(
-                        ins_root,
-                        "instrument_{}_{}.{}".format(name, self.data["agg"], format),
-                    ),
-                    (np.array(wav_instrument) * 32768).astype("int16"),
-                    self.mp.param["sr"],
-                )  #
-            else:
-                path = os.path.join(
-                    ins_root, "instrument_{}_{}.wav".format(name, self.data["agg"])
-                )
-                sf.write(
-                    path,
-                    (np.array(wav_instrument) * 32768).astype("int16"),
-                    self.mp.param["sr"],
-                )
-                if os.path.exists(path):
-                    os.system(
-                        "ffmpeg -i %s -vn %s -q:a 2 -y"
-                        % (path, path[:-4] + ".%s" % format)
-                    )
-        if vocal_root is not None:
-            if self.data["high_end_process"].startswith("mirroring"):
-                input_high_end_ = spec_utils.mirroring(
-                    self.data["high_end_process"], v_spec_m, input_high_end, self.mp
-                )
-                wav_vocals = spec_utils.cmb_spectrogram_to_wave(
-                    v_spec_m, self.mp, input_high_end_h, input_high_end_
-                )
-            else:
-                wav_vocals = spec_utils.cmb_spectrogram_to_wave(v_spec_m, self.mp)
-            print("%s vocals done" % name)
-            if format in ["wav", "flac"]:
-                sf.write(
-                    os.path.join(
-                        vocal_root,
-                        "vocal_{}_{}.{}".format(name, self.data["agg"], format),
-                    ),
-                    (np.array(wav_vocals) * 32768).astype("int16"),
-                    self.mp.param["sr"],
-                )
-            else:
-                path = os.path.join(
-                    vocal_root, "vocal_{}_{}.wav".format(name, self.data["agg"])
-                )
-                sf.write(
-                    path,
-                    (np.array(wav_vocals) * 32768).astype("int16"),
-                    self.mp.param["sr"],
-                )
-                if os.path.exists(path):
-                    os.system(
-                        "ffmpeg -i %s -vn %s -q:a 2 -y"
-                        % (path, path[:-4] + ".%s" % format)
-                    )
-
-
-class _audio_pre_new:
-    def __init__(self, agg, model_path, device, is_half):
-        self.model_path = model_path
-        self.device = device
-        self.data = {
-            # Processing Options
-            "postprocess": False,
-            "tta": False,
-            # Constants
-            "window_size": 512,
-            "agg": agg,
-            "high_end_process": "mirroring",
-        }
-        mp = ModelParameters("lib/uvr5_pack/lib_v5/modelparams/4band_v3.json")
-        nout = 64 if "DeReverb" in model_path else 48
-        model = CascadedNet(mp.param["bins"] * 2, nout)
-        cpk = torch.load(model_path, map_location="cpu")
-        model.load_state_dict(cpk)
-        model.eval()
-        if is_half:
-            model = model.half().to(device)
-        else:
-            model = model.to(device)
-
-        self.mp = mp
-        self.model = model
-
-    def _path_audio_(
-        self, music_file, vocal_root=None, ins_root=None, format="flac"
-    ):  # 3个VR模型vocal和ins是反的
-        if ins_root is None and vocal_root is None:
-            return "No save root."
-        name = os.path.basename(music_file)
-        if ins_root is not None:
-            os.makedirs(ins_root, exist_ok=True)
-        if vocal_root is not None:
-            os.makedirs(vocal_root, exist_ok=True)
-        X_wave, y_wave, X_spec_s, y_spec_s = {}, {}, {}, {}
-        bands_n = len(self.mp.param["band"])
-        # print(bands_n)
-        for d in range(bands_n, 0, -1):
-            bp = self.mp.param["band"][d]
-            if d == bands_n:  # high-end band
-                (
-                    X_wave[d],
-                    _,
-                ) = librosa.core.load( 
-                    music_file,
-                    bp["sr"],
-                    False,
-                    dtype=np.float32,
-                    res_type=bp["res_type"],
-                )
-                if X_wave[d].ndim == 1:
-                    X_wave[d] = np.asfortranarray([X_wave[d], X_wave[d]])
-            else:  # lower bands
-                X_wave[d] = librosa.core.resample(
-                    X_wave[d + 1],
-                    self.mp.param["band"][d + 1]["sr"],
-                    bp["sr"],
-                    res_type=bp["res_type"],
-                )
-            # Stft of wave source
-            X_spec_s[d] = spec_utils.wave_to_spectrogram_mt(
-                X_wave[d],
-                bp["hl"],
-                bp["n_fft"],
-                self.mp.param["mid_side"],
-                self.mp.param["mid_side_b2"],
-                self.mp.param["reverse"],
-            )
-            # pdb.set_trace()
-            if d == bands_n and self.data["high_end_process"] != "none":
-                input_high_end_h = (bp["n_fft"] // 2 - bp["crop_stop"]) + (
-                    self.mp.param["pre_filter_stop"] - self.mp.param["pre_filter_start"]
-                )
-                input_high_end = X_spec_s[d][
-                    :, bp["n_fft"] // 2 - input_high_end_h : bp["n_fft"] // 2, :
-                ]
-
-        X_spec_m = spec_utils.combine_spectrograms(X_spec_s, self.mp)
-        aggresive_set = float(self.data["agg"] / 100)
-        aggressiveness = {
-            "value": aggresive_set,
-            "split_bin": self.mp.param["band"][1]["crop_stop"],
-        }
-        with torch.no_grad():
-            pred, X_mag, X_phase = inference(
-                X_spec_m, self.device, self.model, aggressiveness, self.data
-            )
-        # Postprocess
-        if self.data["postprocess"]:
-            pred_inv = np.clip(X_mag - pred, 0, np.inf)
-            pred = spec_utils.mask_silence(pred, pred_inv)
-        y_spec_m = pred * X_phase
-        v_spec_m = X_spec_m - y_spec_m
-
-        if ins_root is not None:
-            if self.data["high_end_process"].startswith("mirroring"):
-                input_high_end_ = spec_utils.mirroring(
-                    self.data["high_end_process"], y_spec_m, input_high_end, self.mp
-                )
-                wav_instrument = spec_utils.cmb_spectrogram_to_wave(
-                    y_spec_m, self.mp, input_high_end_h, input_high_end_
-                )
-            else:
-                wav_instrument = spec_utils.cmb_spectrogram_to_wave(y_spec_m, self.mp)
-            print("%s instruments done" % name)
-            if format in ["wav", "flac"]:
-                sf.write(
-                    os.path.join(
-                        ins_root,
-                        "instrument_{}_{}.{}".format(name, self.data["agg"], format),
-                    ),
-                    (np.array(wav_instrument) * 32768).astype("int16"),
-                    self.mp.param["sr"],
-                )  #
-            else:
-                path = os.path.join(
-                    ins_root, "instrument_{}_{}.wav".format(name, self.data["agg"])
-                )
-                sf.write(
-                    path,
-                    (np.array(wav_instrument) * 32768).astype("int16"),
-                    self.mp.param["sr"],
-                )
-                if os.path.exists(path):
-                    os.system(
-                        "ffmpeg -i %s -vn %s -q:a 2 -y"
-                        % (path, path[:-4] + ".%s" % format)
-                    )
-        if vocal_root is not None:
-            if self.data["high_end_process"].startswith("mirroring"):
-                input_high_end_ = spec_utils.mirroring(
-                    self.data["high_end_process"], v_spec_m, input_high_end, self.mp
-                )
-                wav_vocals = spec_utils.cmb_spectrogram_to_wave(
-                    v_spec_m, self.mp, input_high_end_h, input_high_end_
-                )
-            else:
-                wav_vocals = spec_utils.cmb_spectrogram_to_wave(v_spec_m, self.mp)
-            print("%s vocals done" % name)
-            if format in ["wav", "flac"]:
-                sf.write(
-                    os.path.join(
-                        vocal_root,
-                        "vocal_{}_{}.{}".format(name, self.data["agg"], format),
-                    ),
-                    (np.array(wav_vocals) * 32768).astype("int16"),
-                    self.mp.param["sr"],
-                )
-            else:
-                path = os.path.join(
-                    vocal_root, "vocal_{}_{}.wav".format(name, self.data["agg"])
-                )
-                sf.write(
-                    path,
-                    (np.array(wav_vocals) * 32768).astype("int16"),
-                    self.mp.param["sr"],
-                )
-                if os.path.exists(path):
-                    os.system(
-                        "ffmpeg -i %s -vn %s -q:a 2 -y"
-                        % (path, path[:-4] + ".%s" % format)
-                    )
-
-
-if __name__ == "__main__":
-    device = "cuda"
-    is_half = True
-    # model_path = "uvr5_weights/2_HP-UVR.pth"
-    # model_path = "uvr5_weights/VR-DeEchoDeReverb.pth"
-    # model_path = "uvr5_weights/VR-DeEchoNormal.pth"
-    model_path = "uvr5_weights/DeEchoNormal.pth"
-    # pre_fun = _audio_pre_(model_path=model_path, device=device, is_half=True,agg=10)
-    pre_fun = _audio_pre_new(model_path=model_path, device=device, is_half=True, agg=10)
-    audio_path = "雪雪伴奏对消HP5.wav"
-    save_path = "opt"
-    pre_fun._path_audio_(audio_path, save_path, save_path)
diff --git a/spaces/Eden124/Eden124/Dockerfile b/spaces/Eden124/Eden124/Dockerfile
deleted file mode 100644
index 6c01c09373883afcb4ea34ae2d316cd596e1737b..0000000000000000000000000000000000000000
--- a/spaces/Eden124/Eden124/Dockerfile
+++ /dev/null
@@ -1,21 +0,0 @@
-FROM node:18-bullseye-slim
-
-RUN apt-get update && \
-
-apt-get install -y git
-
-RUN git clone https://gitgud.io/khanon/oai-reverse-proxy.git /app
-
-WORKDIR /app
-
-RUN npm install
-
-COPY Dockerfile greeting.md* .env* ./
-
-RUN npm run build
-
-EXPOSE 7860
-
-ENV NODE_ENV=production
-
-CMD [ "npm", "start" ]
\ No newline at end of file
diff --git a/spaces/Enterprisium/Easy_GUI/lib/infer_pack/attentions.py b/spaces/Enterprisium/Easy_GUI/lib/infer_pack/attentions.py
deleted file mode 100644
index 05501be1871643f78dddbeaa529c96667031a8db..0000000000000000000000000000000000000000
--- a/spaces/Enterprisium/Easy_GUI/lib/infer_pack/attentions.py
+++ /dev/null
@@ -1,417 +0,0 @@
-import copy
-import math
-import numpy as np
-import torch
-from torch import nn
-from torch.nn import functional as F
-
-from lib.infer_pack import commons
-from lib.infer_pack import modules
-from lib.infer_pack.modules import LayerNorm
-
-
-class Encoder(nn.Module):
-    def __init__(
-        self,
-        hidden_channels,
-        filter_channels,
-        n_heads,
-        n_layers,
-        kernel_size=1,
-        p_dropout=0.0,
-        window_size=10,
-        **kwargs
-    ):
-        super().__init__()
-        self.hidden_channels = hidden_channels
-        self.filter_channels = filter_channels
-        self.n_heads = n_heads
-        self.n_layers = n_layers
-        self.kernel_size = kernel_size
-        self.p_dropout = p_dropout
-        self.window_size = window_size
-
-        self.drop = nn.Dropout(p_dropout)
-        self.attn_layers = nn.ModuleList()
-        self.norm_layers_1 = nn.ModuleList()
-        self.ffn_layers = nn.ModuleList()
-        self.norm_layers_2 = nn.ModuleList()
-        for i in range(self.n_layers):
-            self.attn_layers.append(
-                MultiHeadAttention(
-                    hidden_channels,
-                    hidden_channels,
-                    n_heads,
-                    p_dropout=p_dropout,
-                    window_size=window_size,
-                )
-            )
-            self.norm_layers_1.append(LayerNorm(hidden_channels))
-            self.ffn_layers.append(
-                FFN(
-                    hidden_channels,
-                    hidden_channels,
-                    filter_channels,
-                    kernel_size,
-                    p_dropout=p_dropout,
-                )
-            )
-            self.norm_layers_2.append(LayerNorm(hidden_channels))
-
-    def forward(self, x, x_mask):
-        attn_mask = x_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
-        x = x * x_mask
-        for i in range(self.n_layers):
-            y = self.attn_layers[i](x, x, attn_mask)
-            y = self.drop(y)
-            x = self.norm_layers_1[i](x + y)
-
-            y = self.ffn_layers[i](x, x_mask)
-            y = self.drop(y)
-            x = self.norm_layers_2[i](x + y)
-        x = x * x_mask
-        return x
-
-
-class Decoder(nn.Module):
-    def __init__(
-        self,
-        hidden_channels,
-        filter_channels,
-        n_heads,
-        n_layers,
-        kernel_size=1,
-        p_dropout=0.0,
-        proximal_bias=False,
-        proximal_init=True,
-        **kwargs
-    ):
-        super().__init__()
-        self.hidden_channels = hidden_channels
-        self.filter_channels = filter_channels
-        self.n_heads = n_heads
-        self.n_layers = n_layers
-        self.kernel_size = kernel_size
-        self.p_dropout = p_dropout
-        self.proximal_bias = proximal_bias
-        self.proximal_init = proximal_init
-
-        self.drop = nn.Dropout(p_dropout)
-        self.self_attn_layers = nn.ModuleList()
-        self.norm_layers_0 = nn.ModuleList()
-        self.encdec_attn_layers = nn.ModuleList()
-        self.norm_layers_1 = nn.ModuleList()
-        self.ffn_layers = nn.ModuleList()
-        self.norm_layers_2 = nn.ModuleList()
-        for i in range(self.n_layers):
-            self.self_attn_layers.append(
-                MultiHeadAttention(
-                    hidden_channels,
-                    hidden_channels,
-                    n_heads,
-                    p_dropout=p_dropout,
-                    proximal_bias=proximal_bias,
-                    proximal_init=proximal_init,
-                )
-            )
-            self.norm_layers_0.append(LayerNorm(hidden_channels))
-            self.encdec_attn_layers.append(
-                MultiHeadAttention(
-                    hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout
-                )
-            )
-            self.norm_layers_1.append(LayerNorm(hidden_channels))
-            self.ffn_layers.append(
-                FFN(
-                    hidden_channels,
-                    hidden_channels,
-                    filter_channels,
-                    kernel_size,
-                    p_dropout=p_dropout,
-                    causal=True,
-                )
-            )
-            self.norm_layers_2.append(LayerNorm(hidden_channels))
-
-    def forward(self, x, x_mask, h, h_mask):
-        """
-        x: decoder input
-        h: encoder output
-        """
-        self_attn_mask = commons.subsequent_mask(x_mask.size(2)).to(
-            device=x.device, dtype=x.dtype
-        )
-        encdec_attn_mask = h_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
-        x = x * x_mask
-        for i in range(self.n_layers):
-            y = self.self_attn_layers[i](x, x, self_attn_mask)
-            y = self.drop(y)
-            x = self.norm_layers_0[i](x + y)
-
-            y = self.encdec_attn_layers[i](x, h, encdec_attn_mask)
-            y = self.drop(y)
-            x = self.norm_layers_1[i](x + y)
-
-            y = self.ffn_layers[i](x, x_mask)
-            y = self.drop(y)
-            x = self.norm_layers_2[i](x + y)
-        x = x * x_mask
-        return x
-
-
-class MultiHeadAttention(nn.Module):
-    def __init__(
-        self,
-        channels,
-        out_channels,
-        n_heads,
-        p_dropout=0.0,
-        window_size=None,
-        heads_share=True,
-        block_length=None,
-        proximal_bias=False,
-        proximal_init=False,
-    ):
-        super().__init__()
-        assert channels % n_heads == 0
-
-        self.channels = channels
-        self.out_channels = out_channels
-        self.n_heads = n_heads
-        self.p_dropout = p_dropout
-        self.window_size = window_size
-        self.heads_share = heads_share
-        self.block_length = block_length
-        self.proximal_bias = proximal_bias
-        self.proximal_init = proximal_init
-        self.attn = None
-
-        self.k_channels = channels // n_heads
-        self.conv_q = nn.Conv1d(channels, channels, 1)
-        self.conv_k = nn.Conv1d(channels, channels, 1)
-        self.conv_v = nn.Conv1d(channels, channels, 1)
-        self.conv_o = nn.Conv1d(channels, out_channels, 1)
-        self.drop = nn.Dropout(p_dropout)
-
-        if window_size is not None:
-            n_heads_rel = 1 if heads_share else n_heads
-            rel_stddev = self.k_channels**-0.5
-            self.emb_rel_k = nn.Parameter(
-                torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels)
-                * rel_stddev
-            )
-            self.emb_rel_v = nn.Parameter(
-                torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels)
-                * rel_stddev
-            )
-
-        nn.init.xavier_uniform_(self.conv_q.weight)
-        nn.init.xavier_uniform_(self.conv_k.weight)
-        nn.init.xavier_uniform_(self.conv_v.weight)
-        if proximal_init:
-            with torch.no_grad():
-                self.conv_k.weight.copy_(self.conv_q.weight)
-                self.conv_k.bias.copy_(self.conv_q.bias)
-
-    def forward(self, x, c, attn_mask=None):
-        q = self.conv_q(x)
-        k = self.conv_k(c)
-        v = self.conv_v(c)
-
-        x, self.attn = self.attention(q, k, v, mask=attn_mask)
-
-        x = self.conv_o(x)
-        return x
-
-    def attention(self, query, key, value, mask=None):
-        # reshape [b, d, t] -> [b, n_h, t, d_k]
-        b, d, t_s, t_t = (*key.size(), query.size(2))
-        query = query.view(b, self.n_heads, self.k_channels, t_t).transpose(2, 3)
-        key = key.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
-        value = value.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
-
-        scores = torch.matmul(query / math.sqrt(self.k_channels), key.transpose(-2, -1))
-        if self.window_size is not None:
-            assert (
-                t_s == t_t
-            ), "Relative attention is only available for self-attention."
-            key_relative_embeddings = self._get_relative_embeddings(self.emb_rel_k, t_s)
-            rel_logits = self._matmul_with_relative_keys(
-                query / math.sqrt(self.k_channels), key_relative_embeddings
-            )
-            scores_local = self._relative_position_to_absolute_position(rel_logits)
-            scores = scores + scores_local
-        if self.proximal_bias:
-            assert t_s == t_t, "Proximal bias is only available for self-attention."
-            scores = scores + self._attention_bias_proximal(t_s).to(
-                device=scores.device, dtype=scores.dtype
-            )
-        if mask is not None:
-            scores = scores.masked_fill(mask == 0, -1e4)
-            if self.block_length is not None:
-                assert (
-                    t_s == t_t
-                ), "Local attention is only available for self-attention."
-                block_mask = (
-                    torch.ones_like(scores)
-                    .triu(-self.block_length)
-                    .tril(self.block_length)
-                )
-                scores = scores.masked_fill(block_mask == 0, -1e4)
-        p_attn = F.softmax(scores, dim=-1)  # [b, n_h, t_t, t_s]
-        p_attn = self.drop(p_attn)
-        output = torch.matmul(p_attn, value)
-        if self.window_size is not None:
-            relative_weights = self._absolute_position_to_relative_position(p_attn)
-            value_relative_embeddings = self._get_relative_embeddings(
-                self.emb_rel_v, t_s
-            )
-            output = output + self._matmul_with_relative_values(
-                relative_weights, value_relative_embeddings
-            )
-        output = (
-            output.transpose(2, 3).contiguous().view(b, d, t_t)
-        )  # [b, n_h, t_t, d_k] -> [b, d, t_t]
-        return output, p_attn
-
-    def _matmul_with_relative_values(self, x, y):
-        """
-        x: [b, h, l, m]
-        y: [h or 1, m, d]
-        ret: [b, h, l, d]
-        """
-        ret = torch.matmul(x, y.unsqueeze(0))
-        return ret
-
-    def _matmul_with_relative_keys(self, x, y):
-        """
-        x: [b, h, l, d]
-        y: [h or 1, m, d]
-        ret: [b, h, l, m]
-        """
-        ret = torch.matmul(x, y.unsqueeze(0).transpose(-2, -1))
-        return ret
-
-    def _get_relative_embeddings(self, relative_embeddings, length):
-        max_relative_position = 2 * self.window_size + 1
-        # Pad first before slice to avoid using cond ops.
-        pad_length = max(length - (self.window_size + 1), 0)
-        slice_start_position = max((self.window_size + 1) - length, 0)
-        slice_end_position = slice_start_position + 2 * length - 1
-        if pad_length > 0:
-            padded_relative_embeddings = F.pad(
-                relative_embeddings,
-                commons.convert_pad_shape([[0, 0], [pad_length, pad_length], [0, 0]]),
-            )
-        else:
-            padded_relative_embeddings = relative_embeddings
-        used_relative_embeddings = padded_relative_embeddings[
-            :, slice_start_position:slice_end_position
-        ]
-        return used_relative_embeddings
-
-    def _relative_position_to_absolute_position(self, x):
-        """
-        x: [b, h, l, 2*l-1]
-        ret: [b, h, l, l]
-        """
-        batch, heads, length, _ = x.size()
-        # Concat columns of pad to shift from relative to absolute indexing.
-        x = F.pad(x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, 1]]))
-
-        # Concat extra elements so to add up to shape (len+1, 2*len-1).
-        x_flat = x.view([batch, heads, length * 2 * length])
-        x_flat = F.pad(
-            x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [0, length - 1]])
-        )
-
-        # Reshape and slice out the padded elements.
-        x_final = x_flat.view([batch, heads, length + 1, 2 * length - 1])[
-            :, :, :length, length - 1 :
-        ]
-        return x_final
-
-    def _absolute_position_to_relative_position(self, x):
-        """
-        x: [b, h, l, l]
-        ret: [b, h, l, 2*l-1]
-        """
-        batch, heads, length, _ = x.size()
-        # padd along column
-        x = F.pad(
-            x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, length - 1]])
-        )
-        x_flat = x.view([batch, heads, length**2 + length * (length - 1)])
-        # add 0's in the beginning that will skew the elements after reshape
-        x_flat = F.pad(x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [length, 0]]))
-        x_final = x_flat.view([batch, heads, length, 2 * length])[:, :, :, 1:]
-        return x_final
-
-    def _attention_bias_proximal(self, length):
-        """Bias for self-attention to encourage attention to close positions.
-        Args:
-          length: an integer scalar.
-        Returns:
-          a Tensor with shape [1, 1, length, length]
-        """
-        r = torch.arange(length, dtype=torch.float32)
-        diff = torch.unsqueeze(r, 0) - torch.unsqueeze(r, 1)
-        return torch.unsqueeze(torch.unsqueeze(-torch.log1p(torch.abs(diff)), 0), 0)
-
-
-class FFN(nn.Module):
-    def __init__(
-        self,
-        in_channels,
-        out_channels,
-        filter_channels,
-        kernel_size,
-        p_dropout=0.0,
-        activation=None,
-        causal=False,
-    ):
-        super().__init__()
-        self.in_channels = in_channels
-        self.out_channels = out_channels
-        self.filter_channels = filter_channels
-        self.kernel_size = kernel_size
-        self.p_dropout = p_dropout
-        self.activation = activation
-        self.causal = causal
-
-        if causal:
-            self.padding = self._causal_padding
-        else:
-            self.padding = self._same_padding
-
-        self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size)
-        self.conv_2 = nn.Conv1d(filter_channels, out_channels, kernel_size)
-        self.drop = nn.Dropout(p_dropout)
-
-    def forward(self, x, x_mask):
-        x = self.conv_1(self.padding(x * x_mask))
-        if self.activation == "gelu":
-            x = x * torch.sigmoid(1.702 * x)
-        else:
-            x = torch.relu(x)
-        x = self.drop(x)
-        x = self.conv_2(self.padding(x * x_mask))
-        return x * x_mask
-
-    def _causal_padding(self, x):
-        if self.kernel_size == 1:
-            return x
-        pad_l = self.kernel_size - 1
-        pad_r = 0
-        padding = [[0, 0], [0, 0], [pad_l, pad_r]]
-        x = F.pad(x, commons.convert_pad_shape(padding))
-        return x
-
-    def _same_padding(self, x):
-        if self.kernel_size == 1:
-            return x
-        pad_l = (self.kernel_size - 1) // 2
-        pad_r = self.kernel_size // 2
-        padding = [[0, 0], [0, 0], [pad_l, pad_r]]
-        x = F.pad(x, commons.convert_pad_shape(padding))
-        return x
diff --git a/spaces/EuroPython2022/mmocr-demo/configs/_base_/recog_datasets/toy_data.py b/spaces/EuroPython2022/mmocr-demo/configs/_base_/recog_datasets/toy_data.py
deleted file mode 100644
index 259f14943c027f2719ebf30858ee9572ff5584ea..0000000000000000000000000000000000000000
--- a/spaces/EuroPython2022/mmocr-demo/configs/_base_/recog_datasets/toy_data.py
+++ /dev/null
@@ -1,54 +0,0 @@
-dataset_type = 'OCRDataset'
-
-root = 'tests/data/ocr_toy_dataset'
-img_prefix = f'{root}/imgs'
-train_anno_file1 = f'{root}/label.txt'
-
-train1 = dict(
-    type=dataset_type,
-    img_prefix=img_prefix,
-    ann_file=train_anno_file1,
-    loader=dict(
-        type='AnnFileLoader',
-        repeat=100,
-        file_format='txt',
-        file_storage_backend='disk',
-        parser=dict(
-            type='LineStrParser',
-            keys=['filename', 'text'],
-            keys_idx=[0, 1],
-            separator=' ')),
-    pipeline=None,
-    test_mode=False)
-
-train_anno_file2 = f'{root}/label.lmdb'
-train2 = dict(
-    type=dataset_type,
-    img_prefix=img_prefix,
-    ann_file=train_anno_file2,
-    loader=dict(
-        type='AnnFileLoader',
-        repeat=100,
-        file_format='lmdb',
-        file_storage_backend='disk',
-        parser=dict(type='LineJsonParser', keys=['filename', 'text'])),
-    pipeline=None,
-    test_mode=False)
-
-test_anno_file1 = f'{root}/label.lmdb'
-test = dict(
-    type=dataset_type,
-    img_prefix=img_prefix,
-    ann_file=test_anno_file1,
-    loader=dict(
-        type='AnnFileLoader',
-        repeat=1,
-        file_format='lmdb',
-        file_storage_backend='disk',
-        parser=dict(type='LineJsonParser', keys=['filename', 'text'])),
-    pipeline=None,
-    test_mode=True)
-
-train_list = [train1, train2]
-
-test_list = [test]
diff --git a/spaces/Felix123456/bingo/src/lib/utils.ts b/spaces/Felix123456/bingo/src/lib/utils.ts
deleted file mode 100644
index 07feedb34e356b1b3cf867872f32d47a96ae12fb..0000000000000000000000000000000000000000
--- a/spaces/Felix123456/bingo/src/lib/utils.ts
+++ /dev/null
@@ -1,138 +0,0 @@
-import { clsx, type ClassValue } from 'clsx'
-import { customAlphabet } from 'nanoid'
-import { twMerge } from 'tailwind-merge'
-
-export function cn(...inputs: ClassValue[]) {
-  return twMerge(clsx(inputs))
-}
-
-export const nanoid = customAlphabet(
-  '0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz',
-  7
-) // 7-character random string
-
-export function createChunkDecoder() {
-  const decoder = new TextDecoder()
-  return function (chunk: Uint8Array | undefined): string {
-    if (!chunk) return ''
-    return decoder.decode(chunk, { stream: true })
-  }
-}
-
-export function random (start: number, end: number) {
-  return start + Math.ceil(Math.random() * (end - start))
-}
-
-export function randomIP() {
-  return `11.${random(104, 107)}.${random(1, 255)}.${random(1, 255)}`
-}
-
-export function parseHeadersFromCurl(content: string) {
-  const re = /-H '([^:]+):\s*([^']+)/mg
-  const headers: HeadersInit = {}
-  content = content.replaceAll('-H "', '-H \'').replaceAll('" ^', '\'\\').replaceAll('^\\^"', '"') // 将 cmd curl 转成 bash curl
-  content.replace(re, (_: string, key: string, value: string) => {
-    headers[key] = value
-    return ''
-  })
-
-  return headers
-}
-
-export const ChunkKeys = ['BING_HEADER', 'BING_HEADER1', 'BING_HEADER2']
-export function encodeHeadersToCookie(content: string) {
-  const base64Content = btoa(content)
-  const contentChunks = base64Content.match(/.{1,4000}/g) || []
-  return ChunkKeys.map((key, index) => `${key}=${contentChunks[index] ?? ''}`)
-}
-
-export function extraCurlFromCookie(cookies: Partial<{ [key: string]: string }>) {
-  let base64Content = ''
-  ChunkKeys.forEach((key) => {
-    base64Content += (cookies[key] || '')
-  })
-  try {
-    return atob(base64Content)
-  } catch(e) {
-    return ''
-  }
-}
-
-export function extraHeadersFromCookie(cookies: Partial<{ [key: string]: string }>) {
-  return parseHeadersFromCurl(extraCurlFromCookie(cookies))
-}
-
-export function formatDate(input: string | number | Date): string {
-  const date = new Date(input)
-  return date.toLocaleDateString('en-US', {
-    month: 'long',
-    day: 'numeric',
-    year: 'numeric'
-  })
-}
-
-export function parseCookie(cookie: string, cookieName: string) {
-  const targetCookie = new RegExp(`(?:[; ]|^)${cookieName}=([^;]*)`).test(cookie) ? RegExp.$1 : cookie
-  return targetCookie ? decodeURIComponent(targetCookie).trim() : cookie.indexOf('=') === -1 ? cookie.trim() : ''
-}
-
-export function parseCookies(cookie: string, cookieNames: string[]) {
-  const cookies: { [key: string]: string } = {}
-  cookieNames.forEach(cookieName => {
-    cookies[cookieName] = parseCookie(cookie, cookieName)
-  })
-  return cookies
-}
-
-export const DEFAULT_UA = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36 Edg/115.0.0.0'
-export const DEFAULT_IP = process.env.BING_IP || randomIP()
-
-export function parseUA(ua?: string, default_ua = DEFAULT_UA) {
-  return / EDGE?/i.test(decodeURIComponent(ua || '')) ? decodeURIComponent(ua!.trim()) : default_ua
-}
-
-export function createHeaders(cookies: Partial<{ [key: string]: string }>, defaultHeaders?: Partial<{ [key: string]: string }>) {
-  let {
-    BING_COOKIE = process.env.BING_COOKIE,
-    BING_UA = process.env.BING_UA,
-    BING_IP = process.env.BING_IP,
-    BING_HEADER = process.env.BING_HEADER,
-  } = cookies
-
-  if (BING_HEADER) {
-    return extraHeadersFromCookie({
-      BING_HEADER,
-      ...cookies,
-    })
-  }
-
-  const ua = parseUA(BING_UA)
-
-  if (!BING_COOKIE) {
-    BING_COOKIE = defaultHeaders?.IMAGE_BING_COOKIE || 'xxx' // hf 暂时不用 Cookie 也可以正常使用
-  }
-
-  const parsedCookie = parseCookie(BING_COOKIE, '_U')
-  if (!parsedCookie) {
-    throw new Error('Invalid Cookie')
-  }
-  return {
-    'x-forwarded-for': BING_IP || DEFAULT_IP,
-    'Accept-Encoding': 'gzip, deflate, br',
-    'Accept-Language': 'zh-CN,zh;q=0.9,en;q=0.8,en-GB;q=0.7,en-US;q=0.6',
-    'User-Agent': ua!,
-    'x-ms-useragent': 'azsdk-js-api-client-factory/1.0.0-beta.1 core-rest-pipeline/1.10.0 OS/Win32',
-    cookie: `_U=${parsedCookie}` || '',
-  }
-}
-
-export class WatchDog {
-  private tid = 0
-  watch(fn: Function, timeout = 2000) {
-    clearTimeout(this.tid)
-    this.tid = setTimeout(fn, timeout + Math.random() * 1000)
-  }
-  reset() {
-    clearTimeout(this.tid)
-  }
-}
diff --git a/spaces/Flux9665/IMS-Toucan/Layers/LengthRegulator.py b/spaces/Flux9665/IMS-Toucan/Layers/LengthRegulator.py
deleted file mode 100644
index e375cf18524e4695da5d0909b65a56a178696d40..0000000000000000000000000000000000000000
--- a/spaces/Flux9665/IMS-Toucan/Layers/LengthRegulator.py
+++ /dev/null
@@ -1,62 +0,0 @@
-# Copyright 2019 Tomoki Hayashi
-# MIT License (https://opensource.org/licenses/MIT)
-# Adapted by Florian Lux 2021
-
-from abc import ABC
-
-import torch
-
-from Utility.utils import pad_list
-
-
-class LengthRegulator(torch.nn.Module, ABC):
-    """
-    Length regulator module for feed-forward Transformer.
-
-    This is a module of length regulator described in
-    `FastSpeech: Fast, Robust and Controllable Text to Speech`_.
-    The length regulator expands char or
-    phoneme-level embedding features to frame-level by repeating each
-    feature based on the corresponding predicted durations.
-
-    .. _`FastSpeech: Fast, Robust and Controllable Text to Speech`:
-        https://arxiv.org/pdf/1905.09263.pdf
-
-    """
-
-    def __init__(self, pad_value=0.0):
-        """
-        Initialize length regulator module.
-
-        Args:
-            pad_value (float, optional): Value used for padding.
-        """
-        super(LengthRegulator, self).__init__()
-        self.pad_value = pad_value
-
-    def forward(self, xs, ds, alpha=1.0):
-        """
-        Calculate forward propagation.
-
-        Args:
-            xs (Tensor): Batch of sequences of char or phoneme embeddings (B, Tmax, D).
-            ds (LongTensor): Batch of durations of each frame (B, T).
-            alpha (float, optional): Alpha value to control speed of speech.
-
-        Returns:
-            Tensor: replicated input tensor based on durations (B, T*, D).
-        """
-        if alpha != 1.0:
-            assert alpha > 0
-            ds = torch.round(ds.float() * alpha).long()
-
-        if ds.sum() == 0:
-            ds[ds.sum(dim=1).eq(0)] = 1
-
-        return pad_list([self._repeat_one_sequence(x, d) for x, d in zip(xs, ds)], self.pad_value)
-
-    def _repeat_one_sequence(self, x, d):
-        """
-        Repeat each frame according to duration
-        """
-        return torch.repeat_interleave(x, d, dim=0)
diff --git a/spaces/FritsLyneborg/kunstnerfrits/tools/train/scalable_shampoo/distributed_shampoo.py b/spaces/FritsLyneborg/kunstnerfrits/tools/train/scalable_shampoo/distributed_shampoo.py
deleted file mode 100644
index 0eb228286cc7fddb4a800f901534abea53d8ceea..0000000000000000000000000000000000000000
--- a/spaces/FritsLyneborg/kunstnerfrits/tools/train/scalable_shampoo/distributed_shampoo.py
+++ /dev/null
@@ -1,2267 +0,0 @@
-# coding=utf-8
-# Copyright 2022 The Google Research Authors.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-# An implementation of distributed Shampoo optimizer from:
-#
-#  Scalable Second Order Optimization for Deep Learning
-#  Rohan Anil, Vineet Gupta, Tomer Koren, Kevin Regan, Yoram Singer
-#  Preprint Paper: https://arxiv.org/abs/2002.09018
-#
-# This implementation moves computation of inverse pth root back to the
-# accelerator (if higher precision is available).
-#
-# Authors: Rohan Anil (rohananil at google dot com)
-#    &     Vineet Gupta (vineet at google dot com)
-#
-"""Distributed Shampoo Implementation."""
-
-import enum
-import functools
-import itertools
-from typing import Any, List, NamedTuple, Tuple
-
-import chex
-import jax
-import jax.experimental.pjit as pjit
-import jax.numpy as jnp
-import numpy as np
-import optax
-from flax import struct
-from jax import lax
-
-from .quantization_utils import QuantizedValue
-from .symmetric_matrices import symmetric_matrices
-
-# Dtype for inverse-pth root routine
-# Switch to f64 if you have hardware that supports it. Enable the jax flag
-# jax_enable_x64 for this to work, otherwise it will default to float32.
-_MAT_INV_PTH_ROOT_DTYPE = jnp.float64
-
-
-@struct.dataclass
-class TrainingMetrics:
-    inverse_pth_root_errors: chex.Array  # Error for inverse-pth roots.
-    # TODO(rohananil): Add more important metrics to track during training.
-
-
-# Per parameter optimizer state used in data-parallel training.
-class ParameterStats(NamedTuple):
-    """State associated to each parameter of the model being trained."""
-
-    diagonal_statistics: QuantizedValue  # Accumulator for diagonal preconditioner
-    statistics: List[Any]  # Statistics (QuantizedValue, chex.Array)
-    preconditioners: List[Any]  # Preconditioners (QuantizedValue, chex.Array)
-    diagonal_momentum: QuantizedValue  # Momentum for the diagonal preconditioner
-    momentum: QuantizedValue  # Momentum for the shampoo preconditioner
-    training_metrics: TrainingMetrics  # Metrics (optional for training).
-
-
-# For training extremely large model; We keep a global state with a concatenated
-# statistics and preconditioner states for all vars. This is so that we can
-# annotate the leading axis to be sharded to save memory at the cost of
-# communication.
-@struct.dataclass
-class GlobalShardedParameterStats:
-    statistics: chex.Array  # Statistics
-    preconditioners: chex.Array  # Preconditioners
-    exponents: chex.Array  # exponents
-
-
-# These are per-parameter local states; All statistics here mirror the parameter
-# Thus the sharding is copied over from the param specification.
-@struct.dataclass
-class LocalShardedParameterStats:
-    """State associated to each parameter of the model being trained."""
-
-    diagonal_statistics: QuantizedValue  # Accumulator for diagonal preconditioner
-    diagonal_momentum: QuantizedValue  # Momentum for the diagonal preconditioner
-    momentum: QuantizedValue  # Momentum for the shampoo preconditioner
-    training_metrics: TrainingMetrics  # Metrics (optional for training).
-    index_start: np.int32 = struct.field(
-        pytree_node=False
-    )  # Index into global statistics array
-    sizes: Any = struct.field(pytree_node=False)  # Sizes of the statistics.
-
-
-def init_training_metrics(num_statistics):
-    # Since the downstream apis expect a jnp.array - we create a dummy one if
-    # num_statistics=0.
-    n = 1 if not num_statistics else num_statistics
-    return TrainingMetrics(jnp.zeros([n], jnp.float32))
-
-
-def init_training_metrics_shapes(num_statistics):
-    # Since the downstream apis expect a jnp.array - we create a dummy one if
-    # num_statistics=0.
-    n = 1 if not num_statistics else num_statistics
-    return TrainingMetrics([[n], jnp.float32])
-
-
-def init_training_metrics_pspec():
-    return TrainingMetrics(pjit.PartitionSpec())
-
-
-class ShardedShampooStats(NamedTuple):
-    """Shampoo state in sharded mode."""
-
-    global_stats: Any
-    local_stats: Any
-
-
-class ShampooState(NamedTuple):
-    count: chex.Array
-    stats: Any
-
-
-class InitFnState(NamedTuple):
-    init_fn: Any
-    pspec_fn: Any
-    shape_and_dtype_fn: Any
-
-
-class GraftingType(enum.IntEnum):
-    SGD = 1
-    ADAGRAD = 2
-    RMSPROP = 3
-    RMSPROP_NORMALIZED = 4
-    SQRT_N = 5
-    ADAGRAD_NORMALIZED = 6
-
-
-def power_iteration(
-    matrix,
-    num_iters=100,
-    error_tolerance=1e-6,
-    precision=lax.Precision.HIGHEST,
-):
-    r"""Power iteration algorithm.
-
-    The power iteration algorithm takes a symmetric PSD matrix `A`, and produces
-    a scalar `\lambda` , which is the greatest (in absolute value) eigenvalue
-    of `A`, and a vector v, which is the corresponding eigenvector of `A`.
-
-    References:
-      [Wikipedia, 2021](https://en.wikipedia.org/wiki/Power_iteration)
-
-    Args:
-      matrix: the symmetric PSD matrix.
-      num_iters: Number of iterations.
-      error_tolerance: Iterative exit condition.
-      precision: precision XLA related flag, the available options are: a)
-        lax.Precision.DEFAULT (better step time, but not precise) b)
-        lax.Precision.HIGH (increased precision, slower) c) lax.Precision.HIGHEST
-        (best possible precision, slowest)
-
-    Returns:
-      eigen vector, eigen value
-    """
-    matrix_size = matrix.shape[-1]
-
-    def _iter_condition(state):
-        i, unused_v, unused_s, unused_s_v, run_step = state
-        return jnp.logical_and(i < num_iters, run_step)
-
-    def _iter_body(state):
-        """One step of power iteration."""
-        i, new_v, s, s_v, unused_run_step = state
-        new_v = new_v / jnp.linalg.norm(new_v)
-
-        s_v = jnp.einsum("ij,j->i", matrix, new_v, precision=precision)
-        s_new = jnp.einsum("i,i->", new_v, s_v, precision=precision)
-        return (
-            i + 1,
-            s_v,
-            s_new,
-            s_v,
-            jnp.greater(jnp.abs(s_new - s), error_tolerance),
-        )
-
-    # Figure out how to use step as seed for random.
-    v_0 = (
-        np.random.RandomState(1729).uniform(-1.0, 1.0, matrix_size).astype(matrix.dtype)
-    )
-
-    init_state = tuple([0, v_0, jnp.zeros([], dtype=matrix.dtype), v_0, True])
-    _, v_out, s_out, _, _ = lax.while_loop(_iter_condition, _iter_body, init_state)
-    v_out = v_out / jnp.linalg.norm(v_out)
-    return v_out, s_out
-
-
-def mat_power(
-    mat_m,
-    p,
-    precision=lax.Precision.HIGHEST,
-):
-    """A simple matrix power method. M^p where p can be TracedValue."""
-    power = jnp.eye(mat_m.shape[0], dtype=_MAT_INV_PTH_ROOT_DTYPE)
-
-    def _iter_condition(state):
-        i, _, _ = state
-        return i > 0
-
-    def _iter_body(state):
-        i, power, mat = state
-
-        power = jax.lax.cond(
-            i % 2 == 1,
-            lambda: jnp.matmul(mat, power, precision=precision),
-            lambda: power,
-        )
-        i //= 2
-        mat = jnp.matmul(mat, mat, precision=precision)
-        return i, power, mat
-
-    _, result, _ = lax.while_loop(_iter_condition, _iter_body, (p, power, mat_m))
-    return result
-
-
-def matrix_inverse_pth_root(
-    matrix,
-    p,
-    num_iters=100,
-    ridge_epsilon=1e-6,
-    error_tolerance=1e-6,
-    precision=lax.Precision.HIGHEST,
-):
-    """Computes `matrix^(-1/p)`, where `p` is a positive integer.
-
-    This function uses the Coupled newton iterations algorithm for
-    the computation of a matrix's inverse pth root.
-
-
-    References:
-      [Functions of Matrices, Theory and Computation,
-       Nicholas J Higham, Pg 184, Eq 7.18](
-       https://epubs.siam.org/doi/book/10.1137/1.9780898717778)
-
-    Args:
-      matrix: the symmetric PSD matrix whose power it to be computed
-      p: exponent, for p a positive integer.
-      num_iters: Maximum number of iterations.
-      ridge_epsilon: Ridge epsilon added to make the matrix positive definite.
-      error_tolerance: Error indicator, useful for early termination.
-      precision: precision XLA related flag, the available options are: a)
-        lax.Precision.DEFAULT (better step time, but not precise) b)
-        lax.Precision.HIGH (increased precision, slower) c) lax.Precision.HIGHEST
-        (best possible precision, slowest)
-
-    Returns:
-      matrix^(-1/p)
-    """
-
-    # If the input is not square, materialize it from the concatenated form.
-    if matrix.shape[0] != matrix.shape[1]:
-        matrix = symmetric_matrices.materialize_matrix_from_concat(matrix)
-
-    assert matrix.shape[0] == matrix.shape[1]
-
-    # We use _MAT_INV_PTH_ROOT_DTYPE for the matrix inverse pth root.
-    # Switch to f64 if you have hardware that supports it. Enable the jax flag
-    # jax_enable_x64 for this to work.
-    matrix_size = matrix.shape[0]
-    orig_dtype = matrix.dtype
-    matrix = matrix.astype(_MAT_INV_PTH_ROOT_DTYPE)
-    alpha = jnp.asarray(-1.0 / p, _MAT_INV_PTH_ROOT_DTYPE)
-    identity = jnp.eye(matrix_size, dtype=_MAT_INV_PTH_ROOT_DTYPE)
-    _, max_ev = power_iteration(
-        matrix=matrix, num_iters=100, error_tolerance=1e-6, precision=precision
-    )
-    ridge_epsilon = ridge_epsilon * jnp.maximum(max_ev, 1e-6)
-
-    def _iter_condition(state):
-        (i, unused_mat_m, unused_mat_h, unused_old_mat_h, error, run_step) = state
-        error_above_threshold = jnp.logical_and(error > error_tolerance, run_step)
-        return jnp.logical_and(i < num_iters, error_above_threshold)
-
-    def _iter_body(state):
-        (i, mat_m, mat_h, unused_old_mat_h, error, unused_run_step) = state
-        mat_m_i = (1 - alpha) * identity + alpha * mat_m
-        new_mat_m = jnp.matmul(mat_power(mat_m_i, p), mat_m, precision=precision)
-        new_mat_h = jnp.matmul(mat_h, mat_m_i, precision=precision)
-        new_error = jnp.max(jnp.abs(new_mat_m - identity))
-        # sometimes error increases after an iteration before decreasing and
-        # converging. 1.2 factor is used to bound the maximal allowed increase.
-        return (i + 1, new_mat_m, new_mat_h, mat_h, new_error, new_error < error * 1.2)
-
-    if matrix_size == 1:
-        resultant_mat_h = (matrix + ridge_epsilon) ** alpha
-        error = 0
-    else:
-        damped_matrix = matrix + ridge_epsilon * identity
-
-        z = (1 + p) / (2 * jnp.linalg.norm(damped_matrix))
-        new_mat_m_0 = damped_matrix * z
-        new_error = jnp.max(jnp.abs(new_mat_m_0 - identity))
-        new_mat_h_0 = identity * jnp.power(z, 1.0 / p)
-        init_state = tuple([0, new_mat_m_0, new_mat_h_0, new_mat_h_0, new_error, True])
-        _, mat_m, mat_h, old_mat_h, error, convergence = lax.while_loop(
-            _iter_condition, _iter_body, init_state
-        )
-        error = jnp.max(jnp.abs(mat_m - identity)).astype(jnp.float32)
-        is_converged = jnp.asarray(convergence, old_mat_h.dtype)
-        resultant_mat_h = is_converged * mat_h + (1 - is_converged) * old_mat_h
-        resultant_mat_h = jnp.asarray(resultant_mat_h, orig_dtype)
-    return resultant_mat_h, error
-
-
-def merge_small_dims(shape_to_merge, max_dim):
-    """Merge small dimensions.
-
-    If there are some small dimensions, we collapse them:
-    e.g. [1, 2, 512, 1, 2048, 1, 3, 4] --> [1024, 2048, 12] if max_dim = 1024
-         [1, 2, 768, 1, 2048] --> [2, 768, 2048]
-
-    Args:
-      shape_to_merge: Shape to merge small dimensions.
-      max_dim: Maximal dimension of output shape used in merging.
-
-    Returns:
-      Merged shape.
-    """
-    if shape_to_merge and np.all(np.array(shape_to_merge) == 1):
-        return [1]
-
-    resulting_shape = []
-    product = 1
-    for d in shape_to_merge:
-        if product * d <= max_dim:
-            product *= d
-        else:
-            if product > 1:
-                resulting_shape.append(product)
-            product = d
-    if product > 1:
-        resulting_shape.append(product)
-    return resulting_shape
-
-
-def pad_square_matrix(mat, max_size):
-    """Pad a square matrix up to max_size.
-
-    Args:
-      mat: a matrix to pad.
-      max_size: matrix size requested.
-
-    Returns:
-      Given M returns [[M, 0], [0, I]]
-    """
-    rows, cols = mat.shape
-    if rows != cols:
-        raise ValueError(
-            "Must have rows == cols, instead got " f"rows={rows}, cols={cols}"
-        )
-    if cols > max_size:
-        raise ValueError(
-            "Must have cols <= max_size. Instead got "
-            f"cols={cols}, max_size={max_size}."
-        )
-    if rows == max_size:
-        return mat
-    pad_size = max_size - rows
-
-    zs1 = jnp.zeros([rows, pad_size], dtype=mat.dtype)
-    zs2 = jnp.zeros([pad_size, rows], dtype=mat.dtype)
-    eye = jnp.eye(pad_size, dtype=mat.dtype)
-    mat = jnp.concatenate([mat, zs1], 1)
-    mat = jnp.concatenate([mat, jnp.concatenate([zs2, eye], 1)], 0)
-    return mat
-
-
-def make_sliced_padding(
-    symmetric_block_size,
-    num_blocks,
-    starting_block,
-    dtype,
-):
-    """Returns padding for symmetric block matrix.
-
-    Specifically, the padding is given concatenated rectangular matrices
-    representing the lower-triangular rows below the starting block. For example,
-    if we want to pad the symmetric matrix
-
-    M = [[A, B^T]
-         [B, C]],
-
-    the desired output (in terms of the full matrix) with num_blocks = 4 is
-
-    M_padded = [[A, B^T, 0, 0]
-                [B, C,   0, 0]
-                [0, 0,   I, 0]
-                 0, 0,   0, I].
-
-    We would represent M as the block matrix mat = [A, B, C]. In this form, the
-    additional padding to provide has form [0, 0, I, 0, 0, 0, I] (only the lower
-    triangular parts in the third and fourth rows).
-
-    Args:
-      symmetric_block_size: The size of each block.
-      num_blocks: The total number of blocks.
-      starting_block: The block where to start the padding.
-      dtype: The type to use for the blocks.
-    """
-    if starting_block == num_blocks:
-        return jnp.zeros(shape=(symmetric_block_size, 0), dtype=dtype)
-
-    blocks = []
-    for i in range(starting_block, num_blocks):
-        blocks.append(
-            jnp.zeros(
-                shape=(symmetric_block_size, symmetric_block_size * i), dtype=dtype
-            )
-        )
-        blocks.append(jnp.eye(symmetric_block_size, dtype=dtype))
-    return jnp.concatenate(blocks, axis=-1)
-
-
-def pad_block_symmetric_matrix(
-    mat,
-    symmetric_block_size,
-    max_num_blocks,
-):
-    """Returns the padded blocked symmetric matrix.
-
-    The size of the padded matrix will be:
-      [symmetric_block_size, symmetric_block_size * max_num_blocks]
-
-    The input matrix can either:
-      - Be square with size less or equal to symmetric_block_size. In this case,
-        mat will first be padded to a square matrix of size symmetric_block_size,
-        and then be padded again up to the full size of the blocked matrix.
-      - Be a rectangle with number of rows equal to block size.
-        In this case, number of columns must be a multiple of number of rows, and
-        the ratio must correspond to a block representation of a symmetric matrix.
-        That is, the ratio must have form x * (x + 1) / 2. Here, x represents the
-        number of block rows represented by the matrix.
-
-    Args:
-      mat: The input block matrix.
-      symmetric_block_size: The size of blocks.
-      max_num_blocks: The largest number of blocks to pad to.
-    """
-    rows, cols = mat.shape
-    if rows > symmetric_block_size:
-        raise ValueError(
-            "Must have rows <= symmetric_block_size. Instead got "
-            f"rows={rows}, symmetric_block_size={symmetric_block_size}."
-        )
-    if rows > cols:
-        raise ValueError(
-            "Must have rows <= cols, instead got " f"rows={rows}, cols={cols}."
-        )
-    if cols > symmetric_block_size * max_num_blocks:
-        raise ValueError(
-            "Must have cols <= symmetric_block_size * max_num_blocks "
-            f"Instead got cols={cols}, "
-            f"symmetric_block_size={symmetric_block_size}, "
-            f"max_num_blocks={max_num_blocks}."
-        )
-    if rows < symmetric_block_size:
-        mat = pad_square_matrix(mat, max_size=symmetric_block_size)
-    # Update rows and cols after possibly padding in pad_square_matrix.
-    rows, cols = mat.shape
-    assert rows == symmetric_block_size
-    assert cols % rows == 0
-    filled_blocks = cols // rows
-    padding_blocks = make_sliced_padding(
-        symmetric_block_size=symmetric_block_size,
-        num_blocks=symmetric_matrices.num_blocks_from_total_blocks(max_num_blocks),
-        starting_block=symmetric_matrices.num_blocks_from_total_blocks(filled_blocks),
-        dtype=mat.dtype,
-    )
-    return jnp.concatenate([mat, padding_blocks], axis=-1)
-
-
-def pad_vector(vec, max_size):
-    """Pad a vector to a max_size.
-
-    Args:
-      vec: a vector to pad.
-      max_size: matrix size requested.
-
-    Returns:
-      Given V returns [V, 0]
-    """
-    size = vec.shape[0]
-    assert size <= max_size
-    if size == max_size:
-        return vec
-    pad_size = max_size - size
-    zs1 = jnp.zeros([pad_size], dtype=vec.dtype)
-    return jnp.concatenate([vec, zs1], 0)
-
-
-def efficient_cond(predicate, compute_fn, init_state, *args, **kwargs):
-    """Avoids wasteful buffer allocation with XLA."""
-
-    def _iter_body(unused_state):
-        results = compute_fn(*args, **kwargs)
-        return tuple([False] + list(results))
-
-    def _iter_condition(state):
-        return state[0]
-
-    results = jax.lax.while_loop(
-        _iter_condition, _iter_body, tuple([predicate] + init_state)
-    )
-    return tuple(results[1:])
-
-
-class BlockPartitioner:
-    """Partitions a tensor into smaller tensors."""
-
-    def __init__(self, param, block_size):
-        self._shape = param.shape
-        self._splits = []
-        split_sizes = []
-        # We split params into smaller blocks. Here we store the metadata to make
-        # that split.
-        for i, d in enumerate(param.shape):
-            if 0 < block_size < d:
-                # d-1, otherwise split appends a 0-size array.
-                nsplit = (d - 1) // block_size
-                indices = (np.arange(nsplit, dtype=np.int32) + 1) * block_size
-                sizes = np.ones(nsplit + 1, dtype=np.int32) * block_size
-                sizes[-1] = d - indices[-1]
-                self._splits.append((i, indices))
-                split_sizes.append(sizes)
-            else:
-                split_sizes.append(np.array([d], dtype=np.int32))
-        self._num_splits = len(split_sizes)
-        self._preconditioner_shapes = []
-        for t in itertools.product(*split_sizes):
-            self._preconditioner_shapes.extend([[d, d] for d in t])
-
-    def shapes_for_preconditioners(self):
-        return self._preconditioner_shapes
-
-    def num_splits(self):
-        return self._num_splits
-
-    def partition(self, tensor):
-        """Partition tensor into blocks."""
-
-        assert tensor.shape == self._shape
-        tensors = [tensor]
-        for (i, indices) in self._splits:
-            tensors_local = []
-            for t in tensors:
-                tensors_local.extend(jnp.split(t, indices_or_sections=indices, axis=i))
-            tensors = tensors_local
-        return tensors
-
-    def merge_partitions(self, partitions):
-        """Merge partitions back to original shape."""
-
-        for (i, indices) in reversed(self._splits):
-            n = len(indices) + 1
-            partial_merged_tensors = []
-            ind = 0
-            while ind < len(partitions):
-                partial_merged_tensors.append(
-                    jnp.concatenate(partitions[ind : ind + n], axis=i)
-                )
-                ind += n
-            partitions = partial_merged_tensors
-        assert len(partitions) == 1
-        return partitions[0]
-
-
-class Preconditioner:
-    """Compute statistics/shape from gradients for preconditioning."""
-
-    def __init__(self, param, block_size, best_effort_shape_interpretation):
-        self._original_shape = param.shape
-        self._transformed_shape = param.shape
-        if best_effort_shape_interpretation:
-            self._transformed_shape = merge_small_dims(self._original_shape, block_size)
-        reshaped_param = jnp.reshape(param, self._transformed_shape)
-        self._partitioner = BlockPartitioner(reshaped_param, block_size)
-
-    def statistics_from_grad(self, grad):
-        """Compute statistics from gradients.
-
-        Args:
-          grad: Gradient to compute statistics from.
-
-        Returns:
-          A list of gradient statistics for each partition.
-        """
-        reshaped_grad = jnp.reshape(grad, self._transformed_shape)
-        partitioned_grads = self._partitioner.partition(reshaped_grad)
-        stats = []
-        for g in partitioned_grads:
-            g_stats = []
-            rank = len(g.shape)
-            for i in range(rank):
-                axes = list(range(i)) + list(range(i + 1, rank))
-                stat = jnp.tensordot(g, g, axes=(axes, axes))
-                g_stats.append(stat)
-            stats.extend(g_stats)
-        return stats
-
-    def shapes_for_preconditioners(self):
-        """Returns shape from statistics."""
-        return self._partitioner.shapes_for_preconditioners()
-
-    def exponent_for_preconditioner(self):
-        """Returns exponent to use for inverse-pth root M^{-1/p}."""
-        return 2 * len(self._transformed_shape)
-
-    def preconditioned_grad(self, grad, preconditioners):
-        """Precondition the gradient.
-
-        Args:
-          grad: A gradient tensor to precondition.
-          preconditioners: A list of preconditioners to apply.
-
-        Returns:
-          A preconditioned gradient.
-        """
-
-        reshaped_grad = jnp.reshape(grad, self._transformed_shape)
-        partitioned_grads = self._partitioner.partition(reshaped_grad)
-        preconditioned_partitioned_grads = []
-        num_splits = self._partitioner.num_splits()
-        for i, g in enumerate(partitioned_grads):
-            preconditioners_for_grad = preconditioners[
-                i * num_splits : (i + 1) * num_splits
-            ]
-            rank = len(g.shape)
-            precond_g = g
-            for j in range(rank):
-                precond_g = jnp.tensordot(
-                    precond_g, preconditioners_for_grad[j], axes=[[0], [0]]
-                )
-            preconditioned_partitioned_grads.append(precond_g)
-        merged_grad = self._partitioner.merge_partitions(
-            preconditioned_partitioned_grads
-        )
-        return jnp.reshape(merged_grad, self._original_shape)
-
-
-def _convert_to_parameter_stats(global_stats, local_stat):
-    """Creates parameter stats from sharded stats."""
-    index_start = int(local_stat.index_start)
-    index_end = int(len(local_stat.sizes)) + index_start
-    statistics = global_stats.statistics[index_start:index_end, :, :]
-    preconditioners = global_stats.preconditioners[index_start:index_end, :, :]
-    new_statistics = []
-    new_preconditioners = []
-    for i, size in enumerate(local_stat.sizes):
-        new_statistics.append(statistics[i][:size, :size])
-        new_preconditioners.append(preconditioners[i][:size, :size])
-    return ParameterStats(
-        local_stat.diagonal_statistics,
-        new_statistics,
-        new_preconditioners,
-        local_stat.diagonal_momentum,
-        local_stat.momentum,
-        local_stat.training_metrics,
-    )
-
-
-def _convert_from_parameter_stats(parameter_stats, local_stats):
-    """Creates sharded stats from paramter stats."""
-    return LocalShardedParameterStats(
-        parameter_stats.diagonal_statistics,
-        parameter_stats.diagonal_momentum,
-        parameter_stats.momentum,
-        parameter_stats.training_metrics,
-        local_stats.index_start,
-        local_stats.sizes,
-    )
-
-
-def _add_error_into_local_stats(local_stats, errors, inverse_failure_threshold):
-    """Adds errors back into local statistics."""
-    new_local_stats = []
-    for local_stat in local_stats:
-        index_start = int(local_stat.index_start)
-        index_end = int(len(local_stat.sizes)) + index_start
-        per_stat_error = errors[index_start:index_end]
-        if local_stat.sizes:
-            per_stat_error = jnp.where(
-                jnp.logical_and(
-                    per_stat_error > 0.0, per_stat_error != inverse_failure_threshold
-                ),
-                per_stat_error,
-                local_stat.training_metrics.inverse_pth_root_errors,
-            )
-        new_local_stats.append(
-            LocalShardedParameterStats(
-                local_stat.diagonal_statistics,
-                local_stat.diagonal_momentum,
-                local_stat.momentum,
-                TrainingMetrics(per_stat_error),
-                local_stat.index_start,
-                local_stat.sizes,
-            )
-        )
-    return new_local_stats
-
-
-def batch(x, num_devices):
-    """Batch `x` so that so that leading axis is num_devices."""
-    n = len(x)
-    b = int(n / num_devices)
-    return jnp.stack([jnp.stack(x[idx : idx + b]) for idx in range(0, n, b)])
-
-
-def unbatch(batched_values):
-    """Unbatch values across leading axis and return a list of elements."""
-    b1, b2 = batched_values.shape[0], batched_values.shape[1]
-    results = []
-    for v_array in jnp.split(batched_values, indices_or_sections=b1, axis=0):
-        v_array = jnp.squeeze(v_array)
-        # b2 = batches (number of preconditioner computation) per core.
-        if b2 > 1:
-            for v in jnp.split(v_array, indices_or_sections=b2, axis=0):
-                results.append(jnp.squeeze(v))
-        else:
-            results.append(v_array)
-    return results
-
-
-def distributed_shampoo(
-    learning_rate,
-    block_size,
-    beta1=0.9,
-    beta2=0.999,
-    diagonal_epsilon=1e-10,
-    matrix_epsilon=1e-6,
-    weight_decay=0.0,
-    start_preconditioning_step=5,
-    preconditioning_compute_steps=1,
-    statistics_compute_steps=1,
-    best_effort_shape_interpretation=True,
-    graft_type=GraftingType.SGD,
-    nesterov=True,
-    exponent_override=0,
-    # Pass pmap 'batch axis name' in pmap mode.
-    batch_axis_name=None,
-    ### Only set following 3 params in pjit/spmd mode.
-    ### WARNING: Experimental
-    statistics_partition_spec=None,
-    preconditioner_partition_spec=None,
-    num_devices_for_pjit=None,
-    shard_optimizer_states=False,
-    ###
-    ### Experimental memory reduction mode
-    best_effort_memory_usage_reduction=False,
-    ###
-    inverse_failure_threshold=0.1,
-    moving_average_for_momentum=False,
-    skip_preconditioning_dim_size_gt=4096,
-    clip_by_scaled_gradient_norm=None,
-    precision=lax.Precision.HIGHEST,
-):
-    """Distributed Shampoo optimizer.
-
-    Distributed Shampoo is a second-order preconditioned method (concretely, a
-    variant of full-matrix Adagrad), that provides significant convergence and
-    wall-clock time improvements compared to conventional first-order methods,
-    and that has been shown to scale to large state-of-the-art deep learning
-    models.
-
-    References:
-      Scalable Second Order Optimization for Deep Learning,
-      Rohan Anil, Vineet Gupta, Tomer Koren, Kevin Regan, Yoram Singer
-
-      Preprint: https://arxiv.org/abs/2002.09018
-
-    Args:
-      learning_rate: the step size used to update the parameters.
-      block_size: Block size for large layers (if > 0). Preconditioning compute
-        operation is cubic in the dimension of the tensor. Block size allows us to
-        chunk the layers into sub-layers of maximal dimension dictated by this
-        value. Use 128 as default (increase if you have compute budget).
-      beta1: momentum parameter.
-      beta2: second moment averaging parameter.
-      diagonal_epsilon: epsilon for diagonal adagrad (only if layerwise grafting
-        to AdaGrad is enabled).
-      matrix_epsilon: epsilon to add to statistics before computing inverse pth
-        root. If you are running in f32 precision for inverse pth root
-        (recommended today) this can go upto 1e-6. If you have latest hardware
-        with native f64 precision, set this upto 1e-12.
-      weight_decay: Weight decay for regularization.
-      start_preconditioning_step: When to start Shampoo update before which
-        diagonal update is used. This is because we dont have enough information
-        to do stable inverse.
-      preconditioning_compute_steps: How often to compute preconditioner.
-        Performance tuning params for controlling memory and compute requirements.
-        Ideally set this and statistics_compute_steps params to 1.
-      statistics_compute_steps: How often to compute statistics.
-      best_effort_shape_interpretation: If there are some small dimensions,
-        collapse them e.g. [1, 2, 512, 1, 2048, 1, 3, 4] --> [1024, 2048, 12] if
-        block = 1024, [1, 2, 768, 1, 2048] --> [2, 768, 2048]
-      graft_type: Grafting is a technique to fix the layerwise scale of Shampoo
-        optimizer. This allows us to plugin the Shampoo optimizer into settings
-        where SGD/AdaGrad is already well tuned.
-      nesterov: Nesterov momentum.
-      exponent_override: Override the exponent used in matrix inverse.
-      batch_axis_name: labeled axis over pmap for data-parallel training the
-        optimizer used for.
-      statistics_partition_spec: PartitionSpec to be used in sharded mode.
-      preconditioner_partition_spec: PartitionSpec to be used in sharded mode.
-      num_devices_for_pjit: Number of devices to parallelize over when using pjit.
-      shard_optimizer_states: Shard optimizer states to save memory in model
-        parallel training.
-      best_effort_memory_usage_reduction: Best effort memory usage reduction. -
-        diagonal_statistics -> jnp.bfloat16 - momentum buffers (2x) -> jnp.int8 -
-        statistics, preconditioners -> jnp.int16 + diagonals
-      inverse_failure_threshold: numerics are hard and inverses fail sometimes; we
-        determine that using this threshold.
-      moving_average_for_momentum: Whether to use moving average for momentum
-        instead of exponential moving average.
-      skip_preconditioning_dim_size_gt: Skip if preconditioning dim size is
-        greater than this value.
-      clip_by_scaled_gradient_norm: Clip by scaled gradient norm (only useful when
-        using RMSProp Grafting).
-      precision: precision XLA related flag, the available options are: a)
-        lax.Precision.DEFAULT (better step time, but not precise) b)
-        lax.Precision.HIGH (increased precision, slower) c) lax.Precision.HIGHEST
-        (best possible precision, slowest)
-
-    Returns:
-      a GradientTransformation.
-    """
-
-    def _graft_type_has_diagonal_statistics():
-        """Returns True if using diagonal firt order method for grafting."""
-        return graft_type != GraftingType.SGD and graft_type != GraftingType.SQRT_N
-
-    def _graft_type_has_diagonal_momentum_states():
-        """Returns False if using SQRT_N for grafting."""
-        return graft_type != GraftingType.SQRT_N
-
-    def quantized_dtype_for_momentum_buffers():
-        return jnp.int8 if best_effort_memory_usage_reduction else jnp.float32
-
-    # TODO(rohananil): Explore int8-16 quantization with non-linear bucket sizes.
-    def quantized_dtype_for_diagonal_statistics_buffers():
-        return jnp.float32
-
-    # Preconditioner and statistics are both stores as int16 in this mode.
-    # We take out the diagonal to make quantization easier.
-    def quantized_dtype_for_second_moment_statistics_buffers():
-        return (
-            jnp.int16
-            if best_effort_memory_usage_reduction and batch_axis_name
-            else jnp.float32
-        )
-
-    # Preconditioner and statistics are both stores as int16 in this mode.
-    # We take out the diagonal to make quantization easier.
-    def quantized_dtype_for_second_moment_preconditioner_buffers():
-        return (
-            jnp.int16
-            if best_effort_memory_usage_reduction and batch_axis_name
-            else jnp.float32
-        )
-
-    def _to_float(maybe_quantized):
-        if isinstance(maybe_quantized, QuantizedValue):
-            return maybe_quantized.to_float()
-        else:
-            return maybe_quantized
-
-    def _maybe_quantize_statistics(statistics_list):
-        return _maybe_quantize_matrices_with_dtype(
-            statistics_list, quantized_dtype_for_second_moment_statistics_buffers()
-        )
-
-    def _maybe_quantize_preconditioners(statistics_list):
-        return _maybe_quantize_matrices_with_dtype(
-            statistics_list, quantized_dtype_for_second_moment_preconditioner_buffers()
-        )
-
-    def _maybe_quantize_matrices_with_dtype(statistics_list, quantized_dtype):
-        if quantized_dtype != jnp.float32:
-            return [
-                QuantizedValue.from_float_value(
-                    s, quantized_dtype, extract_diagonal=True
-                )
-                for s in statistics_list
-            ]
-        else:
-            return statistics_list
-
-    def _maybe_dequantize_preconditioners(preconditioner_list):
-        return _maybe_dequantize_matrices_with_dtype(
-            preconditioner_list,
-            quantized_dtype_for_second_moment_preconditioner_buffers(),
-        )
-
-    def _maybe_dequantize_matrices_with_dtype(statistics_list, quantized_dtype):
-        if quantized_dtype != jnp.float32:
-            return [s.to_float() for s in statistics_list]
-        else:
-            return statistics_list
-
-    def _quantize_diagonal_statistics(diagonal_statistics):
-        return QuantizedValue.from_float_value(
-            diagonal_statistics, quantized_dtype_for_diagonal_statistics_buffers()
-        )
-
-    def _quantize_momentum(momentum_statistics):
-        return QuantizedValue.from_float_value(
-            momentum_statistics, quantized_dtype_for_momentum_buffers()
-        )
-
-    def sharded_init_fn(params):
-        """Returns optimizer state (for PJIT mode).
-
-        Args:
-          params: the parameters that should be updated.
-        """
-        params_flat, treedef = jax.tree_flatten(params)
-        # Find max size to pad to.
-        max_size = 0
-        for param in params_flat:
-            preconditioner = Preconditioner(
-                param, block_size, best_effort_shape_interpretation
-            )
-            if not _skip_preconditioning(param):
-                shapes = preconditioner.shapes_for_preconditioners()
-                sizes = [s[0] for s in shapes]
-                max_size = max(max(sizes), max_size)
-
-        padded_statistics = []
-        padded_preconditioners = []
-        local_stats_flat = []
-        exponents = []
-        for param in params_flat:
-            preconditioner = Preconditioner(
-                param, block_size, best_effort_shape_interpretation
-            )
-            shapes = preconditioner.shapes_for_preconditioners()
-            sizes = []
-
-            statistics = []
-            preconditioners = []
-            index_start = len(padded_statistics)
-            if not _skip_preconditioning(param):
-                sizes = [s[0] for s in shapes]
-                shapes = preconditioner.shapes_for_preconditioners()
-                statistics = [
-                    matrix_epsilon * jnp.eye(max_size, dtype=jnp.float32)
-                    for s in shapes
-                ]
-                preconditioners = [jnp.eye(max_size, dtype=jnp.float32) for s in shapes]
-                padded_statistics.extend(statistics)
-                padded_preconditioners.extend(preconditioners)
-                exponent = (
-                    preconditioner.exponent_for_preconditioner()
-                    if exponent_override == 0
-                    else exponent_override
-                )
-                exponents.extend([exponent] * len(shapes))
-
-            diagonal_statistics = []
-            if _graft_type_has_diagonal_statistics():
-                diagonal_statistics = jnp.zeros_like(param)
-
-            diagonal_momentum = _quantize_momentum([])
-            momentum = _quantize_momentum(jnp.zeros_like(param))
-            if _graft_type_has_diagonal_momentum_states():
-                diagonal_momentum = _quantize_momentum((jnp.zeros_like(param)))
-
-            local_stats_flat.append(
-                LocalShardedParameterStats(
-                    _quantize_diagonal_statistics(diagonal_statistics),
-                    diagonal_momentum,
-                    momentum,
-                    init_training_metrics(len(sizes)),
-                    index_start,
-                    sizes,
-                )
-            )
-
-        local_stats = jax.tree_unflatten(treedef, local_stats_flat)
-        to_pad = -len(padded_statistics) % num_devices_for_pjit
-        if max_size == 0:
-            to_pad = num_devices_for_pjit
-            max_size = block_size
-            stat_dtype = jnp.float32
-        else:
-            stat_dtype = padded_statistics[0].dtype
-        # Pad the statistics and preconditioner matrices to be a multiple of
-        # num devices.
-        # TODO(rohananil): Relax to only the size of the mesh axis where the dim
-        # is split on.
-        padded_statistics.extend(
-            [jnp.eye(max_size, dtype=stat_dtype) for _ in range(to_pad)]
-        )
-        padded_preconditioners.extend(
-            [jnp.eye(max_size, dtype=stat_dtype) for _ in range(to_pad)]
-        )
-        exponents.extend([1 for _ in range(to_pad)])
-        global_stats = GlobalShardedParameterStats(
-            jnp.stack(padded_statistics),
-            jnp.stack(padded_preconditioners),
-            jnp.stack(exponents),
-        )
-        return ShampooState(
-            count=jnp.zeros([], jnp.int32),
-            stats=ShardedShampooStats(global_stats, local_stats),
-        )
-
-    def _max_statistics_size_from_params(params):
-        max_size = 0
-        for param in params:
-            param_clone = jnp.zeros(param.shape, dtype=param.dtype)
-            preconditioner = Preconditioner(
-                param_clone, block_size, best_effort_shape_interpretation
-            )
-            if not _skip_preconditioning(param):
-                shapes = preconditioner.shapes_for_preconditioners()
-                sizes = [s[0] for s in shapes]
-                max_size = max(max(sizes), max_size)
-        return max_size
-
-    def _remove_leading_sharding_annotation(pspec):
-        """Mapping from N-d to (N-1)-d, used for quantization, factoring etc."""
-        # None and PSpec(None) are valid PSpecs.
-        if pspec and len(pspec) > 1:
-            return pjit.PartitionSpec(*pspec[1:])
-        else:
-            return []
-
-    def sharded_init_partition_spec_fn(
-        params, params_partition_spec, partition_spec_for_statistics
-    ):
-        """Returns a parallel state tree with PartitionSpec associated with state.
-
-
-        Args:
-          params: A pytree with params.
-          params_partition_spec: A pytree with PartitionSpec for params.
-          partition_spec_for_statistics: PartitionSpec for the statistics.
-        """
-        # Parallel lists of spec, and params.
-        param_pspec_flat, _ = jax.tree_flatten(
-            params_partition_spec, is_leaf=lambda x: x is None
-        )
-        params_flat, treedef = jax.tree_flatten(params)
-        assert param_pspec_flat
-        assert params_flat
-        # Step is replicated across cores.
-        # None means cores.
-        local_stats_flat = []
-        num_statistics = 0
-        for param, param_pspec in zip(params_flat, param_pspec_flat):
-            param_clone = jnp.zeros(param.shape, dtype=param.dtype)
-            preconditioner = Preconditioner(
-                param_clone, block_size, best_effort_shape_interpretation
-            )
-            shapes = preconditioner.shapes_for_preconditioners()
-            sizes = []
-
-            index_start = num_statistics
-            if not _skip_preconditioning(param):
-                sizes = [s[0] for s in shapes]
-                shapes = preconditioner.shapes_for_preconditioners()
-                num_statistics += len(shapes)
-
-            diagonal_statistics_pspec = []
-            diagonal_statistics_scale_pspec = []
-            if _graft_type_has_diagonal_statistics():
-                # Identically shaped param.
-                diagonal_statistics_pspec = param_pspec
-                if quantized_dtype_for_diagonal_statistics_buffers() != jnp.float32:
-                    diagonal_statistics_scale_pspec = (
-                        _remove_leading_sharding_annotation(param_pspec)
-                    )
-
-            m1_pspec = []
-            m1_scale_pspec = []
-            if _graft_type_has_diagonal_momentum_states():
-                m1_pspec = param_pspec
-                if quantized_dtype_for_momentum_buffers() != jnp.float32:
-                    m1_scale_pspec = _remove_leading_sharding_annotation(m1_pspec)
-
-            m2_pspec = param_pspec
-            m2_scale_pspec = []
-            if quantized_dtype_for_momentum_buffers() != jnp.float32:
-                m2_scale_pspec = _remove_leading_sharding_annotation(m2_pspec)
-
-            local_stats_flat.append(
-                LocalShardedParameterStats(
-                    QuantizedValue(
-                        diagonal_statistics_pspec,
-                        [],
-                        diagonal_statistics_scale_pspec,
-                        quantized_dtype_for_diagonal_statistics_buffers(),
-                        False,
-                        list(param.shape),
-                    ),
-                    QuantizedValue(
-                        m1_pspec,
-                        [],
-                        m1_scale_pspec,
-                        quantized_dtype_for_momentum_buffers(),
-                        False,
-                        list(param.shape),
-                    ),
-                    QuantizedValue(
-                        m2_pspec,
-                        [],
-                        m2_scale_pspec,
-                        quantized_dtype_for_momentum_buffers(),
-                        False,
-                        list(param.shape),
-                    ),
-                    init_training_metrics_pspec(),
-                    index_start,
-                    sizes,
-                )
-            )
-
-        local_stats = jax.tree_unflatten(treedef, local_stats_flat)
-        global_stats = GlobalShardedParameterStats(
-            partition_spec_for_statistics,
-            partition_spec_for_statistics,
-            pjit.PartitionSpec(),
-        )
-        count_pspec = pjit.PartitionSpec()
-        return ShampooState(
-            count=count_pspec, stats=ShardedShampooStats(global_stats, local_stats)
-        )
-
-    def sharded_init_shape_and_dtype_fn(params):
-        """Returns a parallel state tree with shape, dtype associated with state.
-
-
-        Args:
-          params: A pytree with params.
-        """
-        # Parallel lists of spec, and params.
-        params_flat, treedef = jax.tree_flatten(params)
-        assert params_flat
-        # Step is replicated across cores.
-        # None means cores.
-        local_stats_flat = []
-        num_statistics = 0
-        for param in params_flat:
-            param_clone = jnp.zeros(param.shape, dtype=param.dtype)
-            preconditioner = Preconditioner(
-                param_clone, block_size, best_effort_shape_interpretation
-            )
-            shapes = preconditioner.shapes_for_preconditioners()
-            sizes = []
-
-            index_start = num_statistics
-            if not _skip_preconditioning(param):
-                sizes = [s[0] for s in shapes]
-                shapes = preconditioner.shapes_for_preconditioners()
-                num_statistics += len(shapes)
-
-            diagonal_statistics_shape_and_dtype = []
-            diagonal_statistics_scale_shape_and_dtype = []
-            if _graft_type_has_diagonal_statistics():
-                diagonal_statistics_shape_and_dtype = [list(param.shape), param.dtype]
-                qdtype = quantized_dtype_for_diagonal_statistics_buffers()
-                if qdtype != jnp.float32:
-                    diagonal_statistics_shape_and_dtype = [list(param.shape), qdtype]
-                    diagonal_statistics_scale_shape_and_dtype = [
-                        list(param.shape)[1:],
-                        param.dtype,
-                    ]
-
-            qdtype = quantized_dtype_for_momentum_buffers()
-            m1_shape_and_dtype = []
-            m1_scale_shape_and_dtype = []
-            if _graft_type_has_diagonal_momentum_states():
-                m1_shape_and_dtype = [list(param.shape), qdtype]
-                if quantized_dtype_for_momentum_buffers() != jnp.float32:
-                    m1_scale_shape_and_dtype = [list(param.shape)[1:], qdtype]
-
-            m2_shape_and_dtype = [list(param.shape), param.dtype]
-            m2_scale_shape_and_dtype = []
-            if qdtype != jnp.float32:
-                m2_shape_and_dtype = [list(param.shape), qdtype]
-                m2_scale_shape_and_dtype = [list(param.shape)[1:], qdtype]
-
-            local_stats_flat.append(
-                LocalShardedParameterStats(
-                    QuantizedValue(
-                        diagonal_statistics_shape_and_dtype,
-                        [],
-                        diagonal_statistics_scale_shape_and_dtype,
-                        quantized_dtype_for_diagonal_statistics_buffers(),
-                        False,
-                        list(param.shape),
-                    ),
-                    QuantizedValue(
-                        m1_shape_and_dtype,
-                        [],
-                        m1_scale_shape_and_dtype,
-                        quantized_dtype_for_momentum_buffers(),
-                        False,
-                        list(param.shape),
-                    ),
-                    QuantizedValue(
-                        m2_shape_and_dtype,
-                        [],
-                        m2_scale_shape_and_dtype,
-                        quantized_dtype_for_momentum_buffers(),
-                        False,
-                        list(param.shape),
-                    ),
-                    init_training_metrics_shapes(len(sizes)),
-                    index_start,
-                    sizes,
-                )
-            )
-
-        local_stats = jax.tree_unflatten(treedef, local_stats_flat)
-        max_statistics_size = _max_statistics_size_from_params(params_flat)
-        to_pad = -num_statistics % num_devices_for_pjit
-        num_statistics += to_pad
-        if num_statistics == 0:
-            num_statistics = num_devices_for_pjit
-            max_statistics_size = block_size
-        statistics_shape = [num_statistics, max_statistics_size, max_statistics_size]
-        global_stats = GlobalShardedParameterStats(
-            [statistics_shape, jnp.float32],
-            [statistics_shape, jnp.float32],
-            [[num_statistics], jnp.int32],
-        )
-        return ShampooState(
-            count=[[], jnp.float32],
-            stats=ShardedShampooStats(global_stats, local_stats),
-        )
-
-    def sharded_update_fn(grads, state, params):
-        """Transform the input gradient and update all statistics in sharded mode.
-
-        Args:
-          grads: the gradient tensors for the parameters.
-          state: a named tuple containing the state of the optimizer
-          params: the parameters that should be updated.
-
-        Returns:
-          A tuple containing the new parameters and the new optimizer state.
-        """
-        params_flat, treedef = jax.tree_flatten(params)
-        grads_flat = treedef.flatten_up_to(grads)
-
-        global_stats = state.stats.global_stats
-        local_stats_flat = treedef.flatten_up_to(state.stats.local_stats)
-        stats_flat = [
-            _convert_to_parameter_stats(global_stats, local_stat)
-            for local_stat in local_stats_flat
-        ]
-        new_stats_flat = jax.tree_multimap(
-            lambda g, s, p: _compute_stats(g, s, p, state.count),
-            grads_flat,
-            stats_flat,
-            params_flat,
-        )
-
-        outputs = jax.tree_multimap(
-            lambda g, s, p: _transform_grad(g, s, p, state.count),
-            grads_flat,
-            new_stats_flat,
-            params_flat,
-        )
-        updates_flat, new_stats_flat = list(zip(*outputs)) if outputs else ((), ())
-
-        updates = jax.tree_unflatten(treedef, updates_flat)
-        # Create new local_stats
-        new_local_stats_flat = [
-            _convert_from_parameter_stats(new_stat, local_stat)
-            for new_stat, local_stat in zip(new_stats_flat, local_stats_flat)
-        ]
-
-        max_size = global_stats.statistics.shape[1]
-        new_padded_statistics = []
-        for stat in new_stats_flat:
-            new_padded_statistics.extend(
-                [pad_square_matrix(stat, max_size) for stat in stat.statistics]
-            )
-
-        # Create global stats
-        # TODO(rohananil): Preconditioner is not updated every step, so cost of
-        # stack/pad can be obviated away.
-        # Pad the statistics and preconditioner matrices to be a multiple of
-        # num devices.
-        # TODO(rohananil): Relax to only the size of the mesh axis where the dim
-        # is split on.
-        to_pad = -len(new_padded_statistics) % num_devices_for_pjit
-        new_padded_statistics.extend(
-            [
-                jnp.eye(max_size, dtype=new_padded_statistics[0].dtype)
-                for _ in range(to_pad)
-            ]
-        )
-        new_stacked_padded_statistics = jnp.stack(new_padded_statistics)
-        new_stacked_padded_statistics = pjit.with_sharding_constraint(
-            new_stacked_padded_statistics, statistics_partition_spec
-        )
-
-        def _internal_inverse_pth_root_all():
-            preconditioners, errors = _matrix_inverse_pth_root_pjit(
-                new_stacked_padded_statistics,
-                global_stats.exponents,
-                statistics_partition_spec,
-            )
-            return preconditioners, errors
-
-        if preconditioning_compute_steps == 1:
-            new_preconditioners, errors = _internal_inverse_pth_root_all()
-        else:
-            # Passing statistics instead of preconditioners as they are similarly
-            # shaped tensors. Note statistics will be ignored as we are passing in
-            # a large init value for error.
-            preconditioners_init = new_stacked_padded_statistics
-            n = new_stacked_padded_statistics.shape[0]
-            errors_init = jnp.ones([n], jnp.float32) * inverse_failure_threshold
-            init_state = [preconditioners_init, errors_init]
-            perform_step = state.count % preconditioning_compute_steps == 0
-            new_preconditioners, errors = efficient_cond(
-                perform_step, _internal_inverse_pth_root_all, init_state
-            )
-
-        new_local_stats_flat = _add_error_into_local_stats(
-            new_local_stats_flat, errors, inverse_failure_threshold
-        )
-        new_local_stats = jax.tree_unflatten(treedef, new_local_stats_flat)
-        errors = errors.reshape((-1, 1, 1))
-        predicate = jnp.logical_or(
-            jnp.isnan(errors), errors >= inverse_failure_threshold
-        ).astype(new_preconditioners.dtype)
-        # TODO(rohananil): Check for numerical instabilities.
-        new_conditional_preconditioners = (
-            predicate * global_stats.preconditioners
-            + (1.0 - predicate) * new_preconditioners
-        )
-        new_global_stats = GlobalShardedParameterStats(
-            new_stacked_padded_statistics,
-            new_conditional_preconditioners,
-            global_stats.exponents,
-        )
-        new_shampoo_state = ShampooState(
-            count=state.count + 1,
-            stats=ShardedShampooStats(new_global_stats, new_local_stats),
-        )
-        return updates, new_shampoo_state
-
-    def init_fn(params):
-        """Initialise the optimiser's state."""
-
-        def _init(param):
-            preconditioner = Preconditioner(
-                param, block_size, best_effort_shape_interpretation
-            )
-            statistics = []
-            preconditioners = []
-            if not _skip_preconditioning(param):
-                shapes = preconditioner.shapes_for_preconditioners()
-                statistics = [
-                    matrix_epsilon * jnp.eye(s[0], dtype=jnp.float32) for s in shapes
-                ]
-                preconditioners = [jnp.eye(s[0], dtype=jnp.float32) for s in shapes]
-
-            diagonal_statistics = []
-            if _graft_type_has_diagonal_statistics():
-                diagonal_statistics = jnp.zeros_like(param)
-
-            diagonal_momentum = _quantize_momentum([])
-            momentum = _quantize_momentum(jnp.zeros_like(param))
-            if _graft_type_has_diagonal_momentum_states():
-                diagonal_momentum = _quantize_momentum(jnp.zeros_like(param))
-
-            return ParameterStats(
-                _quantize_diagonal_statistics(diagonal_statistics),
-                _maybe_quantize_statistics(statistics),
-                _maybe_quantize_preconditioners(preconditioners),
-                diagonal_momentum,
-                momentum,
-                init_training_metrics(len(statistics)),
-            )
-
-        return ShampooState(
-            count=jnp.zeros([], jnp.int32), stats=jax.tree_map(_init, params)
-        )
-
-    def _skip_preconditioning(param):
-        return len(param.shape) < 1 or any(
-            [s > skip_preconditioning_dim_size_gt for s in param.shape]
-        )
-
-    def _compute_stats(grad, state, param, step):
-        """Compute per-parameter statistics."""
-        preconditioner = Preconditioner(
-            param, block_size, best_effort_shape_interpretation
-        )
-        new_statistics = [[]] * len(state.statistics)
-        w1 = beta2
-        w2 = beta2 if beta2 == 1.0 else (1.0 - beta2)
-        if not _skip_preconditioning(param):
-
-            def compute_updated_statistics():
-                new_stats = preconditioner.statistics_from_grad(grad)
-                new_stats_accumulators = []
-                for stat, stat_accumulator in zip(new_stats, state.statistics):
-                    new_stats_accumulators.append(
-                        w1 * _to_float(stat_accumulator) + w2 * stat
-                    )
-                return _maybe_quantize_statistics(new_stats_accumulators)
-
-            if statistics_compute_steps > 1:
-                perform_step = step % statistics_compute_steps == 0
-                init_state = state.statistics
-                new_statistics = list(
-                    efficient_cond(perform_step, compute_updated_statistics, init_state)
-                )
-            else:
-                new_statistics = compute_updated_statistics()
-        return ParameterStats(
-            state.diagonal_statistics,
-            new_statistics,
-            state.preconditioners,
-            state.diagonal_momentum,
-            state.momentum,
-            state.training_metrics,
-        )
-
-    def _matrix_inverse_pth_root_vmap(xs, ps):
-        mi_pth_root = functools.partial(
-            matrix_inverse_pth_root, ridge_epsilon=matrix_epsilon, precision=precision
-        )
-        return jax.vmap(mi_pth_root)(xs, ps)
-
-    def _quantized_matrix_inverse_pth_root_vmap(qxs, qds, qbs, ps):
-        def _quantized_to_float(qx, qd, qb):
-            qv = QuantizedValue(qx, qd, qb, qx.dtype, True, list(qx.shape))
-            return qv.to_float()
-
-        def matrix_inverse_pth_root_wrapper(qx, qd, qb, p):
-            v = _quantized_to_float(qx, qd, qb)
-            preconditioner, error = matrix_inverse_pth_root(
-                v, p, ridge_epsilon=matrix_epsilon, precision=precision
-            )
-            qp = QuantizedValue.from_float_value(preconditioner, qx.dtype, True)
-            return qp.quantized, qp.diagonal, qp.bucket_size, error
-
-        return jax.vmap(matrix_inverse_pth_root_wrapper)(qxs, qds, qbs, ps)
-
-    def _matrix_inverse_pth_root_pjit(xs, ps, statistics_partition_spec=None):
-        # Partition the concatenated statistics matrix across all cores.
-        pspec_for_partition = preconditioner_partition_spec
-        partitioned_xs = pjit.with_sharding_constraint(xs, pspec_for_partition)
-        partitioned_ps = pjit.with_sharding_constraint(
-            ps, pjit.PartitionSpec(preconditioner_partition_spec[0])
-        )
-        # Run matrix inverse pth root on each shard.
-        partitioned_preconditioners, partitioned_errors = _matrix_inverse_pth_root_vmap(
-            partitioned_xs, partitioned_ps
-        )
-        # Reshard output to have the same PSpec as input. This is required to avoid
-        # vmap seeing the full set of statistics.
-        partitioned_preconditioners = pjit.with_sharding_constraint(
-            partitioned_preconditioners, pspec_for_partition
-        )
-        # Recombine the outputs at each core.
-        preconditioners = pjit.with_sharding_constraint(
-            partitioned_preconditioners, statistics_partition_spec
-        )
-        errors = pjit.with_sharding_constraint(partitioned_errors, pjit.PartitionSpec())
-        return preconditioners, errors
-
-    def _pmap_compute_preconditioners(
-        states,
-        step,
-        statistics,
-        num_statistics_per_state,
-        original_shapes,
-        exponents,
-        max_size,
-        prev_preconditioners,
-    ):
-        """Computes preconditioners for given statistics in states in PMAP mode.
-
-        Args:
-          states: A list of optimizer states.
-          step: Current step number
-          statistics: A list of statistics for all variables (for every dim)
-          num_statistics_per_state: Number of statistis per state to reconstruct
-            output states.
-          original_shapes: A list of shapes of the statistics.
-          exponents: Exponent power to use for inverse-pth roots.
-          max_size: Maximum dim of the statistics to pad.
-          prev_preconditioners: Previously available preconditioner.
-
-        Returns:
-          New optimizer states after computing the preconditioner.
-        """
-        num_devices = lax.psum(1, batch_axis_name)
-        num_statistics = len(statistics)
-        # Pad statistics and exponents to next multiple of num_devices.
-        packed_statistics = [pad_square_matrix(stat, max_size) for stat in statistics]
-        to_pad = -num_statistics % num_devices
-        packed_statistics.extend(
-            [jnp.eye(max_size, dtype=packed_statistics[0].dtype) for _ in range(to_pad)]
-        )
-        exponents.extend([1 for _ in range(to_pad)])
-
-        if not packed_statistics:
-            return states
-
-        all_statistics = batch(packed_statistics, num_devices)
-        all_exponents = batch(exponents, num_devices)
-
-        def _internal_inverse_pth_root_all():
-            current_replica = lax.axis_index(batch_axis_name)
-            preconditioners, errors = _matrix_inverse_pth_root_vmap(
-                all_statistics[current_replica], all_exponents[current_replica]
-            )
-            preconditioners = jax.lax.all_gather(preconditioners, batch_axis_name)
-            errors = jax.lax.all_gather(errors, batch_axis_name)
-            preconditioners_flat = unbatch(preconditioners)
-            errors_flat = unbatch(errors)
-            return preconditioners_flat, errors_flat
-
-        if preconditioning_compute_steps == 1:
-            preconditioners_flat, errors_flat = _internal_inverse_pth_root_all()
-        else:
-            # Passing statistics instead of preconditioners as they are similarly
-            # shaped tensors. Note statistics will be ignored as we are passing in
-            # a large init value for error.
-            preconditioners_init = packed_statistics
-            errors_init = [inverse_failure_threshold] * len(packed_statistics)
-            init_state = [preconditioners_init, errors_init]
-            perform_step = step % preconditioning_compute_steps == 0
-            preconditioners_flat, errors_flat = efficient_cond(
-                perform_step, _internal_inverse_pth_root_all, init_state
-            )
-
-        def _skip(error):
-            condition = jnp.logical_or(
-                jnp.isnan(error), error >= inverse_failure_threshold
-            )
-            return condition.astype(error.dtype)
-
-        def _select_preconditioner(error, new_p, old_p):
-            return lax.cond(
-                _skip(error), lambda _: old_p, lambda _: new_p, operand=None
-            )
-
-        new_preconditioners_flat = []
-        new_errors_flat = []
-        for p, shape, prev_p, error in zip(
-            preconditioners_flat, original_shapes, prev_preconditioners, errors_flat
-        ):
-            new_preconditioners_flat.append(
-                _select_preconditioner(error, p[: shape[0], : shape[1]], prev_p)
-            )
-            new_errors_flat.append(error)
-
-        assert len(states) == len(num_statistics_per_state)
-        assert len(new_preconditioners_flat) == num_statistics
-        assert len(new_errors_flat) == num_statistics
-
-        # Add back empty preconditioners so we that we can set the optimizer state.
-        preconditioners_for_states = []
-        idx = 0
-        errors_for_states = []
-        for num_statistics, state in zip(num_statistics_per_state, states):
-            if num_statistics == 0:
-                preconditioners_for_states.append([])
-                errors_for_states.append([])
-            else:
-                preconditioners_for_state = new_preconditioners_flat[
-                    idx : idx + num_statistics
-                ]
-                assert len(state.statistics) == len(preconditioners_for_state)
-                preconditioners_for_states.append(preconditioners_for_state)
-
-                errors_for_state = jnp.stack(
-                    new_errors_flat[idx : idx + num_statistics]
-                )
-                assert len(state.statistics) == len(errors_for_state)
-                errors_for_states.append(errors_for_state)
-
-                idx += num_statistics
-        new_states = []
-        for state, new_preconditioners, new_errors in zip(
-            states, preconditioners_for_states, errors_for_states
-        ):
-            if state.statistics:
-                new_errors = jnp.where(
-                    jnp.logical_and(
-                        new_errors > 0.0, new_errors != inverse_failure_threshold
-                    ),
-                    new_errors,
-                    state.training_metrics.inverse_pth_root_errors,
-                )
-            new_training_metrics = TrainingMetrics(new_errors)
-            new_states.append(
-                ParameterStats(
-                    state.diagonal_statistics,
-                    state.statistics,
-                    new_preconditioners,
-                    state.diagonal_momentum,
-                    state.momentum,
-                    new_training_metrics,
-                )
-            )
-
-        return new_states
-
-    def _pmap_quantized_compute_preconditioners(
-        states,
-        step,
-        statistics,
-        num_statistics_per_state,
-        original_shapes,
-        exponents,
-        max_size,
-        prev_preconditioners,
-    ):
-        """Computes preconditioners for given statistics in states in PMAP mode.
-
-        For quantization, each statistic is represented by three values:
-          quantized matrix, diagonal, and bucket sizes, we run inverse pth-roots
-          without ever recreating the original matrix in f32.
-
-        Args:
-          states: A list of optimizer states.
-          step: Current step number
-          statistics: A list of statistics for all variables (for every dim)
-          num_statistics_per_state: Number of statistis per state to reconstruct
-            output states.
-          original_shapes: A list of shapes of the statistics.
-          exponents: Exponent power to use for inverse-pth roots.
-          max_size: Maximum dim of the statistics to pad.
-          prev_preconditioners: Previously available preconditioner.
-
-        Returns:
-          New optimizer states after computing the preconditioner.
-        """
-        num_devices = lax.psum(1, batch_axis_name)
-        num_statistics = len(statistics)
-        quantized_dtype = quantized_dtype_for_second_moment_statistics_buffers()
-        # Complexity here is around: shapes needing be statically shaped,
-        # our custom quantization type requires a different type of packing.
-
-        # Parallel tensors:
-        # quantized [dxd]
-        # diagonals [d] f32
-        # bucket_sizes [d] f32
-        packed_quantized_statistics = [
-            pad_square_matrix(stat.quantized, max_size) for stat in statistics
-        ]
-        packed_quantized_diagonals = [
-            pad_vector(stat.diagonal, max_size) for stat in statistics
-        ]
-        packed_quantized_bucket_sizes = [
-            pad_vector(stat.bucket_size, max_size) for stat in statistics
-        ]
-
-        to_pad = -num_statistics % num_devices
-        padded_eye = jnp.eye(max_size, dtype=jnp.float32)
-        quantized_eye = QuantizedValue.from_float_value(
-            padded_eye, quantized_dtype, True
-        )
-        packed_quantized_statistics.extend(
-            [quantized_eye.quantized for _ in range(to_pad)]
-        )
-        packed_quantized_diagonals.extend(
-            [quantized_eye.diagonal for _ in range(to_pad)]
-        )
-        packed_quantized_bucket_sizes.extend(
-            [quantized_eye.bucket_size for _ in range(to_pad)]
-        )
-        exponents.extend([1 for _ in range(to_pad)])
-
-        if not packed_quantized_statistics:
-            return states
-
-        all_quantized_statistics = batch(packed_quantized_statistics, num_devices)
-        all_quantized_diagonals = batch(packed_quantized_diagonals, num_devices)
-        all_quantized_bucket_sizes = batch(packed_quantized_bucket_sizes, num_devices)
-        all_exponents = batch(exponents, num_devices)
-
-        def _internal_inverse_pth_root_all():
-            current_replica = lax.axis_index(batch_axis_name)
-            (
-                quantized_preconditioners,
-                quantized_diagonals,
-                quantized_bucket_sizes,
-                errors,
-            ) = _quantized_matrix_inverse_pth_root_vmap(
-                all_quantized_statistics[current_replica],
-                all_quantized_diagonals[current_replica],
-                all_quantized_bucket_sizes[current_replica],
-                all_exponents[current_replica],
-            )
-            quantized_preconditioners = jax.lax.all_gather(
-                quantized_preconditioners, batch_axis_name
-            )
-            quantized_diagonals = jax.lax.all_gather(
-                quantized_diagonals, batch_axis_name
-            )
-            quantized_bucket_sizes = jax.lax.all_gather(
-                quantized_bucket_sizes, batch_axis_name
-            )
-            errors = jax.lax.all_gather(errors, batch_axis_name)
-            quantized_preconditioners_flat = unbatch(quantized_preconditioners)
-            quantized_diagonals_flat = unbatch(quantized_diagonals)
-            quantized_bucket_sizes_flat = unbatch(quantized_bucket_sizes)
-            errors_flat = unbatch(errors)
-            return (
-                quantized_preconditioners_flat,
-                quantized_diagonals_flat,
-                quantized_bucket_sizes_flat,
-                errors_flat,
-            )
-
-        if preconditioning_compute_steps == 1:
-            (
-                quantized_preconditioners_flat,
-                quantized_diagonals_flat,
-                quantized_bucket_sizes_flat,
-                errors_flat,
-            ) = _internal_inverse_pth_root_all()
-        else:
-            # Passing statistics instead of preconditioners as they are similarly
-            # shaped tensors. Note statistics will be ignored as we are passing in
-            # a large init value for error.
-            quantized_preconditioners_init = packed_quantized_statistics
-            quantized_diagonals_init = packed_quantized_diagonals
-            quantized_bucket_sizes_init = packed_quantized_bucket_sizes
-            errors_init = [inverse_failure_threshold] * len(
-                quantized_preconditioners_init
-            )
-            init_state = [
-                quantized_preconditioners_init,
-                quantized_diagonals_init,
-                quantized_bucket_sizes_init,
-                errors_init,
-            ]
-            perform_step = step % preconditioning_compute_steps == 0
-            (
-                quantized_preconditioners_flat,
-                quantized_diagonals_flat,
-                quantized_bucket_sizes_flat,
-                errors_flat,
-            ) = efficient_cond(perform_step, _internal_inverse_pth_root_all, init_state)
-
-        def _skip(error):
-            condition = jnp.logical_or(
-                jnp.isnan(error), error >= inverse_failure_threshold
-            )
-            return condition.astype(error.dtype)
-
-        def _select_preconditioner(error, new_p, old_p):
-            return lax.cond(
-                _skip(error), lambda _: old_p, lambda _: new_p, operand=None
-            )
-
-        new_quantized_preconditioners_flat = []
-        new_quantized_diagonals_flat = []
-        new_quantized_bucket_sizes_flat = []
-        new_errors_flat = []
-        for p, d, b, shape, prev_p, error in zip(
-            quantized_preconditioners_flat,
-            quantized_diagonals_flat,
-            quantized_bucket_sizes_flat,
-            original_shapes,
-            prev_preconditioners,
-            errors_flat,
-        ):
-            new_quantized_preconditioners_flat.append(
-                _select_preconditioner(
-                    error, p[: shape[0], : shape[1]], prev_p.quantized
-                )
-            )
-            new_quantized_diagonals_flat.append(
-                _select_preconditioner(error, d[: shape[0]], prev_p.diagonal)
-            )
-            new_quantized_bucket_sizes_flat.append(
-                _select_preconditioner(error, b[: shape[0]], prev_p.bucket_size)
-            )
-            new_errors_flat.append(error)
-
-        assert len(states) == len(num_statistics_per_state)
-        assert len(new_quantized_preconditioners_flat) == num_statistics
-        assert len(new_quantized_diagonals_flat) == num_statistics
-        assert len(new_quantized_bucket_sizes_flat) == num_statistics
-
-        # Add back empty preconditioners so we that we can set the optimizer state.
-        preconditioners_for_states = []
-        errors_for_states = []
-        idx = 0
-        for num_statistics, state in zip(num_statistics_per_state, states):
-            if num_statistics == 0:
-                preconditioners_for_states.append([])
-                errors_for_states.append([])
-            else:
-                quantized_preconditioners_for_state = (
-                    new_quantized_preconditioners_flat[idx : idx + num_statistics]
-                )
-                quantized_diagonals_for_state = new_quantized_diagonals_flat[
-                    idx : idx + num_statistics
-                ]
-                quantized_bucket_sizes_for_state = new_quantized_bucket_sizes_flat[
-                    idx : idx + num_statistics
-                ]
-                errors_for_state = jnp.stack(
-                    new_errors_flat[idx : idx + num_statistics]
-                )
-
-                assert len(state.statistics) == len(quantized_preconditioners_for_state)
-                assert len(state.statistics) == len(quantized_diagonals_for_state)
-                assert len(state.statistics) == len(quantized_bucket_sizes_for_state)
-                assert len(state.statistics) == len(errors_for_state)
-
-                quantized_preconditioners = []
-                for qv, qd, qb in zip(
-                    quantized_preconditioners_for_state,
-                    quantized_diagonals_for_state,
-                    quantized_bucket_sizes_for_state,
-                ):
-                    quantized_preconditioners.append(
-                        QuantizedValue(qv, qd, qb, qv.dtype, True, list(qv.shape))
-                    )
-                preconditioners_for_states.append(quantized_preconditioners)
-                errors_for_states.append(errors_for_state)
-                idx += num_statistics
-        new_states = []
-        for state, new_preconditioners, new_errors in zip(
-            states, preconditioners_for_states, errors_for_states
-        ):
-            if state.statistics:
-                new_errors = jnp.where(
-                    jnp.logical_and(
-                        new_errors > 0.0, new_errors != inverse_failure_threshold
-                    ),
-                    new_errors,
-                    state.training_metrics.inverse_pth_root_errors,
-                )
-            new_training_metrics = TrainingMetrics(new_errors)
-            new_states.append(
-                ParameterStats(
-                    state.diagonal_statistics,
-                    state.statistics,
-                    new_preconditioners,
-                    state.diagonal_momentum,
-                    state.momentum,
-                    new_training_metrics,
-                )
-            )
-
-        return new_states
-
-    def _pjit_compute_preconditioners(
-        states,
-        step,
-        statistics,
-        num_statistics_per_state,
-        original_shapes,
-        exponents,
-        max_size,
-        prev_preconditioners,
-    ):
-        """Computes preconditioners for given statistics in states in PJIT mode.
-
-        Args:
-          states: A list of optimizer states.
-          step: Current step number
-          statistics: A list of statistics for all variables (for every dim)
-          num_statistics_per_state: Number of statistis per state to reconstruct
-            output states.
-          original_shapes: A list of shapes of the statistics.
-          exponents: Exponent power to use for inverse-pth roots.
-          max_size: Maximum dim of the statistics to pad.
-          prev_preconditioners: Previously available preconditioner.
-
-        Returns:
-          New optimizer states after computing the preconditioner.
-        """
-        num_statistics = len(statistics)
-        to_pad = -num_statistics % num_devices_for_pjit
-        padded_statistics = [pad_square_matrix(stat, max_size) for stat in statistics]
-        padded_statistics.extend(
-            [jnp.eye(max_size, dtype=padded_statistics[0].dtype) for _ in range(to_pad)]
-        )
-        exponents.extend([1 for _ in range(to_pad)])
-        all_statistics = jnp.stack(padded_statistics)
-        all_exponents = jnp.stack(exponents)
-
-        def _internal_inverse_pth_root_all():
-            preconditioners, errors = _matrix_inverse_pth_root_pjit(
-                all_statistics, all_exponents
-            )
-            b1 = preconditioners.shape[0]
-
-            def split(batched_values):
-                return [
-                    jnp.squeeze(v)
-                    for v in jnp.split(batched_values, indices_or_sections=b1, axis=0)
-                ]
-
-            return split(preconditioners), split(errors)
-
-        if preconditioning_compute_steps == 1:
-            preconditioners_flat, errors_flat = _internal_inverse_pth_root_all()
-        else:
-            # Passing statistics instead of preconditioners as they are similarly
-            # shaped tensors. Note statistics will be ignored as we are passing in
-            # a large init value for error.
-            preconditioners_init = padded_statistics
-            errors_init = [inverse_failure_threshold] * len(padded_statistics)
-            init_state = [preconditioners_init, errors_init]
-            perform_step = step % preconditioning_compute_steps == 0
-            preconditioners_flat, errors_flat = efficient_cond(
-                perform_step, _internal_inverse_pth_root_all, init_state
-            )
-
-        def _skip(error):
-            condition = jnp.logical_or(
-                jnp.isnan(error), error >= inverse_failure_threshold
-            )
-            return condition.astype(error.dtype)
-
-        def _select_preconditioner(error, new_p, old_p):
-            return lax.cond(
-                _skip(error), lambda _: old_p, lambda _: new_p, operand=None
-            )
-
-        new_preconditioners_flat = []
-        new_errors_flat = []
-        for p, shape, prev_p, error in zip(
-            preconditioners_flat, original_shapes, prev_preconditioners, errors_flat
-        ):
-            new_preconditioners_flat.append(
-                _select_preconditioner(error, p[: shape[0], : shape[1]], prev_p)
-            )
-            new_errors_flat.append(error)
-
-        assert len(states) == len(num_statistics_per_state)
-        assert len(new_preconditioners_flat) == num_statistics
-
-        # Add back empty preconditioners so we that we can set the optimizer state.
-        preconditioners_for_states = []
-        errors_for_states = []
-        idx = 0
-        for num_statistics, state in zip(num_statistics_per_state, states):
-            if num_statistics == 0:
-                preconditioners_for_states.append([])
-                errors_for_states.append([])
-            else:
-                preconditioners_for_state = new_preconditioners_flat[
-                    idx : idx + num_statistics
-                ]
-                assert len(state.statistics) == len(preconditioners_for_state)
-                preconditioners_for_states.append(preconditioners_for_state)
-
-                errors_for_state = jnp.stack(
-                    new_errors_flat[idx : idx + num_statistics]
-                )
-                assert len(state.statistics) == len(errors_for_state)
-                errors_for_states.append(errors_for_state)
-                idx += num_statistics
-
-        new_states = []
-        for state, new_preconditioners, new_errors in zip(
-            states, preconditioners_for_states, errors_for_states
-        ):
-            if state.statistics:
-                new_errors = jnp.where(
-                    jnp.logical_and(
-                        new_errors > 0.0, new_errors != inverse_failure_threshold
-                    ),
-                    new_errors,
-                    state.training_metrics.inverse_pth_root_errors,
-                )
-            new_training_metrics = TrainingMetrics(new_errors)
-            new_states.append(
-                ParameterStats(
-                    state.diagonal_statistics,
-                    state.statistics,
-                    new_preconditioners,
-                    state.diagonal_momentum,
-                    state.momentum,
-                    new_training_metrics,
-                )
-            )
-
-        return new_states
-
-    def _compute_preconditioners(states, params, step):
-        """Computes preconditioners for given statistics in states.
-
-        Args:
-          states: A list of optimizer states.
-          params: A list of params.
-          step: Current step number
-
-        Returns:
-          New optimizer states after computing the preconditioner.
-        """
-        statistics = []
-        num_statistics_per_state = []
-        original_shapes = []
-        exponents = []
-        max_size = 0
-        prev_preconditioners = []
-
-        for state, param in zip(states, params):
-            num_statistics = len(state.statistics)
-            num_statistics_per_state.append(num_statistics)
-            original_shapes_for_state = []
-            if num_statistics > 0:
-                preconditioner = Preconditioner(
-                    param, block_size, best_effort_shape_interpretation
-                )
-                for statistic in state.statistics:
-                    exponents.append(
-                        preconditioner.exponent_for_preconditioner()
-                        if exponent_override == 0
-                        else exponent_override
-                    )
-                    original_shapes_for_state.append(statistic.shape)
-                    max_size = max(max_size, statistic.shape[0])
-
-                statistics.extend(state.statistics)
-                prev_preconditioners.extend(state.preconditioners)
-                original_shapes.extend(original_shapes_for_state)
-
-        if batch_axis_name:
-            # Quantization is only enabled if batch_axis_name is not set.
-            quantized_dtype = quantized_dtype_for_second_moment_statistics_buffers()
-
-            if quantized_dtype == jnp.float32:
-                return _pmap_compute_preconditioners(
-                    states,
-                    step,
-                    statistics,
-                    num_statistics_per_state,
-                    original_shapes,
-                    exponents,
-                    max_size,
-                    prev_preconditioners,
-                )
-            else:
-                return _pmap_quantized_compute_preconditioners(
-                    states,
-                    step,
-                    statistics,
-                    num_statistics_per_state,
-                    original_shapes,
-                    exponents,
-                    max_size,
-                    prev_preconditioners,
-                )
-
-        else:
-            return _pjit_compute_preconditioners(
-                states,
-                step,
-                statistics,
-                num_statistics_per_state,
-                original_shapes,
-                exponents,
-                max_size,
-                prev_preconditioners,
-            )
-
-    def _transform_grad(grad, state, param, step):
-        """Transform per-parameter gradients."""
-        preconditioner = Preconditioner(
-            param, block_size, best_effort_shape_interpretation
-        )
-        sgd_update = grad
-        new_diagonal_statistics = state.diagonal_statistics.to_float()
-        if (
-            graft_type == GraftingType.ADAGRAD
-            or graft_type == GraftingType.ADAGRAD_NORMALIZED
-        ):
-
-            scaled_grad = grad
-            if graft_type == GraftingType.ADAGRAD_NORMALIZED:
-                scaled_grad = grad / (jnp.linalg.norm(grad) + 1e-16)
-
-            new_diagonal_statistics = state.diagonal_statistics.to_float() + jnp.square(
-                scaled_grad
-            )
-            adagrad_update = scaled_grad / (
-                jnp.sqrt(new_diagonal_statistics) + diagonal_epsilon
-            )
-            grafting_update = adagrad_update
-        elif (
-            graft_type == GraftingType.RMSPROP
-            or graft_type == GraftingType.RMSPROP_NORMALIZED
-        ):
-
-            scaled_grad = grad
-            if graft_type == GraftingType.RMSPROP_NORMALIZED:
-                scaled_grad = grad / (jnp.linalg.norm(grad) + 1e-16)
-
-            w1 = beta2
-            w2 = beta2 if beta2 == 1.0 else (1.0 - beta2)
-
-            new_diagonal_statistics = (
-                w1 * state.diagonal_statistics.to_float() + w2 * jnp.square(scaled_grad)
-            )
-            rmsprop_update = scaled_grad / (
-                jnp.sqrt(new_diagonal_statistics) + diagonal_epsilon
-            )
-
-            if clip_by_scaled_gradient_norm:
-                scaled_grad_norm = jnp.linalg.norm(rmsprop_update) / (
-                    jnp.sqrt(float(rmsprop_update.size))
-                )
-                clipping_denom = jnp.maximum(
-                    1.0, scaled_grad_norm / clip_by_scaled_gradient_norm
-                )
-                rmsprop_update /= clipping_denom
-
-            grafting_update = rmsprop_update
-        elif graft_type == GraftingType.SGD:
-            grafting_update = sgd_update
-        else:
-            grafting_update = jnp.ones_like(sgd_update) * jnp.sign(sgd_update)
-
-        precond_grad = grad
-        if not _skip_preconditioning(param):
-            precond_grad = preconditioner.preconditioned_grad(
-                precond_grad, _maybe_dequantize_preconditioners(state.preconditioners)
-            )
-        else:
-            precond_grad = grafting_update
-
-        grafting_update_norm = jnp.linalg.norm(grafting_update)
-        precond_grad_norm = jnp.linalg.norm(precond_grad)
-
-        multiplier = grafting_update_norm / (precond_grad_norm + 1e-16)
-        shampoo_update = precond_grad * multiplier
-
-        shampoo_update_with_wd = shampoo_update
-        grafting_update_with_wd = grafting_update
-        if weight_decay != 0:
-            shampoo_update_with_wd = shampoo_update + weight_decay * param
-            grafting_update_with_wd = grafting_update + weight_decay * param
-
-        w = (1.0 - beta1) if moving_average_for_momentum else 1.0
-
-        shampoo_update_with_wd_momentum = (
-            state.momentum.to_float() * beta1 + w * shampoo_update_with_wd
-        )
-
-        if _graft_type_has_diagonal_momentum_states():
-            grafting_update_with_wd_momentum = (
-                state.diagonal_momentum.to_float() * beta1 + w * grafting_update_with_wd
-            )
-        else:
-            # Share the momentum buffer
-            grafting_update_with_wd_momentum = (
-                state.momentum.to_float() * beta1 + w * grafting_update_with_wd
-            )
-
-        run_shampoo = (step >= start_preconditioning_step).astype(
-            grafting_update_with_wd_momentum.dtype
-        )
-
-        momentum_update = (
-            run_shampoo * shampoo_update_with_wd_momentum
-            + (1.0 - run_shampoo) * grafting_update_with_wd_momentum
-        )
-
-        wd_update = (
-            run_shampoo * shampoo_update_with_wd
-            + (1.0 - run_shampoo) * grafting_update_with_wd
-        )
-
-        nesterov_momentum_update = momentum_update
-        if nesterov:
-            nesterov_momentum_update = w * wd_update + beta1 * momentum_update
-
-        lr = learning_rate
-        if callable(learning_rate):
-            lr = learning_rate(step)
-        transformed_update = -1.0 * lr * nesterov_momentum_update
-
-        new_diagonal_momentum = grafting_update_with_wd_momentum
-        new_momentum = shampoo_update_with_wd_momentum
-        if not _graft_type_has_diagonal_momentum_states():
-            new_diagonal_momentum = []
-            new_momentum = momentum_update
-
-        param_stats = ParameterStats(
-            _quantize_diagonal_statistics(new_diagonal_statistics),
-            state.statistics,
-            state.preconditioners,
-            _quantize_momentum(new_diagonal_momentum),
-            _quantize_momentum(new_momentum),
-            state.training_metrics,
-        )
-
-        return transformed_update, param_stats
-
-    def update_fn(grads, state, params):
-        """Transform the input gradient and update all statistics.
-
-        Args:
-          grads: the gradient tensors for the parameters.
-          state: a named tuple containing the state of the optimizer
-          params: the parameters that should be updated.
-
-        Returns:
-          A tuple containing the new parameters and the new optimizer state.
-        """
-        params_flat, treedef = jax.tree_flatten(params)
-        stats_flat = treedef.flatten_up_to(state.stats)
-        grads_flat = treedef.flatten_up_to(grads)
-
-        new_stats_flat = jax.tree_multimap(
-            lambda g, s, p: _compute_stats(g, s, p, state.count),
-            grads_flat,
-            stats_flat,
-            params_flat,
-        )
-        new_stats_flat = _compute_preconditioners(
-            new_stats_flat, params_flat, state.count
-        )
-        outputs = jax.tree_multimap(
-            lambda g, s, p: _transform_grad(g, s, p, state.count),
-            grads_flat,
-            new_stats_flat,
-            params_flat,
-        )
-        updates_flat, new_stats_flat = list(zip(*outputs)) if outputs else ((), ())
-
-        updates = jax.tree_unflatten(treedef, updates_flat)
-        new_stats = jax.tree_unflatten(treedef, new_stats_flat)
-
-        new_state = ShampooState(count=state.count + 1, stats=new_stats)
-        return updates, new_state
-
-    if shard_optimizer_states:
-        # Hijacks the init_fn signature so we can return an OptState with
-        # appropriate init_fns.
-        def _init_fns(unused_params):
-            return InitFnState(
-                init_fn=sharded_init_fn,
-                pspec_fn=sharded_init_partition_spec_fn,
-                shape_and_dtype_fn=sharded_init_shape_and_dtype_fn,
-            )
-
-        return optax.GradientTransformation(_init_fns, sharded_update_fn)
-    else:
-        return optax.GradientTransformation(init_fn, update_fn)
diff --git a/spaces/Gen-Sim/Gen-Sim/cliport/models/core/attention.py b/spaces/Gen-Sim/Gen-Sim/cliport/models/core/attention.py
deleted file mode 100644
index 9a615a4f32114df8f68a33efb43701fca5e0f4f5..0000000000000000000000000000000000000000
--- a/spaces/Gen-Sim/Gen-Sim/cliport/models/core/attention.py
+++ /dev/null
@@ -1,77 +0,0 @@
-"""Attention module."""
-
-import numpy as np
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-
-import cliport.models as models
-from cliport.utils import utils
-
-
-class Attention(nn.Module):
-    """Attention (a.k.a Pick) module."""
-
-    def __init__(self, stream_fcn, in_shape, n_rotations, preprocess, cfg, device):
-        super().__init__()
-        self.stream_fcn = stream_fcn
-        self.n_rotations = n_rotations
-        self.preprocess = preprocess
-        self.cfg = cfg
-        self.device = device
-        self.batchnorm = self.cfg['train']['batchnorm']
-
-        self.padding = np.zeros((3, 2), dtype=int)
-        max_dim = np.max(in_shape[:2])
-        pad = (max_dim - np.array(in_shape[:2])) / 2
-        self.padding[:2] = pad.reshape(2, 1) # left right top bown front back
-
-        in_shape = np.array(in_shape)
-        in_shape += np.sum(self.padding, axis=1)
-        in_shape = tuple(in_shape)
-        self.in_shape = in_shape
-        self.rotator = utils.ImageRotator(self.n_rotations)
-        self._build_nets()
-
-    def _build_nets(self):
-        stream_one_fcn, _ = self.stream_fcn
-        self.attn_stream = models.names[stream_one_fcn](self.in_shape, 1, self.cfg, self.device)
-        print(f"Attn FCN: {stream_one_fcn}")
-
-    def attend(self, x):
-        return self.attn_stream(x)
-
-    def forward(self, inp_img, softmax=True):
-        """Forward pass."""
-        # print("in_img.shape", inp_img.shape)
-        in_data = np.pad(inp_img, self.padding, mode='constant')
-        in_shape =  input_data.shape
-        if len(inp_shape) == 3:
-            inp_shape = (1,) + inp_shape
-        in_data = in_data.reshape(in_shape)
-        in_tens = torch.from_numpy(in_data.copy()).to(dtype=torch.float, device=self.device) # [B W H 6]
-
-        # Rotation pivot.
-        pv = np.array(in_data.shape[1:3]) // 2
-
-        # Rotate input.
-        in_tens = in_tens.permute(0, 3, 1, 2)  # [B 6 W H]
-        in_tens = in_tens.repeat(self.n_rotations, 1, 1, 1)
-        in_tens = self.rotator(in_tens, pivot=pv)
-
-        # Forward pass.
-        logits = self.attend(torch.cat(in_tens, dim=0), lang_goal)
-
-        # Rotate back output.
-        logits = self.rotator(logits, reverse=True, pivot=pv)
-        logits = torch.cat(logits, dim=0)
-        c0 = self.padding[:2, 0]
-        c1 = c0 + inp_img.shape[:2]
-        logits = logits[:, :, c0[0]:c1[0], c0[1]:c1[1]]
-
-        logits = logits.permute(1, 2, 3, 0)  # [B W H 1]
-        output = logits.reshape(len(logits), np.prod(logits.shape))
-        if softmax:
-            output = F.softmax(output, dim=-1)
-            output = output.reshape(logits.shape[1:])
-        return output
\ No newline at end of file
diff --git a/spaces/Gradio-Blocks/uniformer_image_segmentation/configs/hrnet/fcn_hr18s_480x480_40k_pascal_context.py b/spaces/Gradio-Blocks/uniformer_image_segmentation/configs/hrnet/fcn_hr18s_480x480_40k_pascal_context.py
deleted file mode 100644
index d09931048f762cd2ac224d62c2fe2ed8e0e148c8..0000000000000000000000000000000000000000
--- a/spaces/Gradio-Blocks/uniformer_image_segmentation/configs/hrnet/fcn_hr18s_480x480_40k_pascal_context.py
+++ /dev/null
@@ -1,9 +0,0 @@
-_base_ = './fcn_hr18_480x480_40k_pascal_context.py'
-model = dict(
-    pretrained='open-mmlab://msra/hrnetv2_w18_small',
-    backbone=dict(
-        extra=dict(
-            stage1=dict(num_blocks=(2, )),
-            stage2=dict(num_blocks=(2, 2)),
-            stage3=dict(num_modules=3, num_blocks=(2, 2, 2)),
-            stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2)))))
diff --git a/spaces/Gradio-Blocks/uniformer_image_segmentation/mmseg/models/decode_heads/decode_head.py b/spaces/Gradio-Blocks/uniformer_image_segmentation/mmseg/models/decode_heads/decode_head.py
deleted file mode 100644
index 86b9b63f43818c4b842a25d143060b07c2b401e1..0000000000000000000000000000000000000000
--- a/spaces/Gradio-Blocks/uniformer_image_segmentation/mmseg/models/decode_heads/decode_head.py
+++ /dev/null
@@ -1,234 +0,0 @@
-from abc import ABCMeta, abstractmethod
-
-import torch
-import torch.nn as nn
-from mmcv.cnn import normal_init
-from mmcv.runner import auto_fp16, force_fp32
-
-from mmseg.core import build_pixel_sampler
-from mmseg.ops import resize
-from ..builder import build_loss
-from ..losses import accuracy
-
-
-class BaseDecodeHead(nn.Module, metaclass=ABCMeta):
-    """Base class for BaseDecodeHead.
-
-    Args:
-        in_channels (int|Sequence[int]): Input channels.
-        channels (int): Channels after modules, before conv_seg.
-        num_classes (int): Number of classes.
-        dropout_ratio (float): Ratio of dropout layer. Default: 0.1.
-        conv_cfg (dict|None): Config of conv layers. Default: None.
-        norm_cfg (dict|None): Config of norm layers. Default: None.
-        act_cfg (dict): Config of activation layers.
-            Default: dict(type='ReLU')
-        in_index (int|Sequence[int]): Input feature index. Default: -1
-        input_transform (str|None): Transformation type of input features.
-            Options: 'resize_concat', 'multiple_select', None.
-            'resize_concat': Multiple feature maps will be resize to the
-                same size as first one and than concat together.
-                Usually used in FCN head of HRNet.
-            'multiple_select': Multiple feature maps will be bundle into
-                a list and passed into decode head.
-            None: Only one select feature map is allowed.
-            Default: None.
-        loss_decode (dict): Config of decode loss.
-            Default: dict(type='CrossEntropyLoss').
-        ignore_index (int | None): The label index to be ignored. When using
-            masked BCE loss, ignore_index should be set to None. Default: 255
-        sampler (dict|None): The config of segmentation map sampler.
-            Default: None.
-        align_corners (bool): align_corners argument of F.interpolate.
-            Default: False.
-    """
-
-    def __init__(self,
-                 in_channels,
-                 channels,
-                 *,
-                 num_classes,
-                 dropout_ratio=0.1,
-                 conv_cfg=None,
-                 norm_cfg=None,
-                 act_cfg=dict(type='ReLU'),
-                 in_index=-1,
-                 input_transform=None,
-                 loss_decode=dict(
-                     type='CrossEntropyLoss',
-                     use_sigmoid=False,
-                     loss_weight=1.0),
-                 ignore_index=255,
-                 sampler=None,
-                 align_corners=False):
-        super(BaseDecodeHead, self).__init__()
-        self._init_inputs(in_channels, in_index, input_transform)
-        self.channels = channels
-        self.num_classes = num_classes
-        self.dropout_ratio = dropout_ratio
-        self.conv_cfg = conv_cfg
-        self.norm_cfg = norm_cfg
-        self.act_cfg = act_cfg
-        self.in_index = in_index
-        self.loss_decode = build_loss(loss_decode)
-        self.ignore_index = ignore_index
-        self.align_corners = align_corners
-        if sampler is not None:
-            self.sampler = build_pixel_sampler(sampler, context=self)
-        else:
-            self.sampler = None
-
-        self.conv_seg = nn.Conv2d(channels, num_classes, kernel_size=1)
-        if dropout_ratio > 0:
-            self.dropout = nn.Dropout2d(dropout_ratio)
-        else:
-            self.dropout = None
-        self.fp16_enabled = False
-
-    def extra_repr(self):
-        """Extra repr."""
-        s = f'input_transform={self.input_transform}, ' \
-            f'ignore_index={self.ignore_index}, ' \
-            f'align_corners={self.align_corners}'
-        return s
-
-    def _init_inputs(self, in_channels, in_index, input_transform):
-        """Check and initialize input transforms.
-
-        The in_channels, in_index and input_transform must match.
-        Specifically, when input_transform is None, only single feature map
-        will be selected. So in_channels and in_index must be of type int.
-        When input_transform
-
-        Args:
-            in_channels (int|Sequence[int]): Input channels.
-            in_index (int|Sequence[int]): Input feature index.
-            input_transform (str|None): Transformation type of input features.
-                Options: 'resize_concat', 'multiple_select', None.
-                'resize_concat': Multiple feature maps will be resize to the
-                    same size as first one and than concat together.
-                    Usually used in FCN head of HRNet.
-                'multiple_select': Multiple feature maps will be bundle into
-                    a list and passed into decode head.
-                None: Only one select feature map is allowed.
-        """
-
-        if input_transform is not None:
-            assert input_transform in ['resize_concat', 'multiple_select']
-        self.input_transform = input_transform
-        self.in_index = in_index
-        if input_transform is not None:
-            assert isinstance(in_channels, (list, tuple))
-            assert isinstance(in_index, (list, tuple))
-            assert len(in_channels) == len(in_index)
-            if input_transform == 'resize_concat':
-                self.in_channels = sum(in_channels)
-            else:
-                self.in_channels = in_channels
-        else:
-            assert isinstance(in_channels, int)
-            assert isinstance(in_index, int)
-            self.in_channels = in_channels
-
-    def init_weights(self):
-        """Initialize weights of classification layer."""
-        normal_init(self.conv_seg, mean=0, std=0.01)
-
-    def _transform_inputs(self, inputs):
-        """Transform inputs for decoder.
-
-        Args:
-            inputs (list[Tensor]): List of multi-level img features.
-
-        Returns:
-            Tensor: The transformed inputs
-        """
-
-        if self.input_transform == 'resize_concat':
-            inputs = [inputs[i] for i in self.in_index]
-            upsampled_inputs = [
-                resize(
-                    input=x,
-                    size=inputs[0].shape[2:],
-                    mode='bilinear',
-                    align_corners=self.align_corners) for x in inputs
-            ]
-            inputs = torch.cat(upsampled_inputs, dim=1)
-        elif self.input_transform == 'multiple_select':
-            inputs = [inputs[i] for i in self.in_index]
-        else:
-            inputs = inputs[self.in_index]
-
-        return inputs
-
-    @auto_fp16()
-    @abstractmethod
-    def forward(self, inputs):
-        """Placeholder of forward function."""
-        pass
-
-    def forward_train(self, inputs, img_metas, gt_semantic_seg, train_cfg):
-        """Forward function for training.
-        Args:
-            inputs (list[Tensor]): List of multi-level img features.
-            img_metas (list[dict]): List of image info dict where each dict
-                has: 'img_shape', 'scale_factor', 'flip', and may also contain
-                'filename', 'ori_shape', 'pad_shape', and 'img_norm_cfg'.
-                For details on the values of these keys see
-                `mmseg/datasets/pipelines/formatting.py:Collect`.
-            gt_semantic_seg (Tensor): Semantic segmentation masks
-                used if the architecture supports semantic segmentation task.
-            train_cfg (dict): The training config.
-
-        Returns:
-            dict[str, Tensor]: a dictionary of loss components
-        """
-        seg_logits = self.forward(inputs)
-        losses = self.losses(seg_logits, gt_semantic_seg)
-        return losses
-
-    def forward_test(self, inputs, img_metas, test_cfg):
-        """Forward function for testing.
-
-        Args:
-            inputs (list[Tensor]): List of multi-level img features.
-            img_metas (list[dict]): List of image info dict where each dict
-                has: 'img_shape', 'scale_factor', 'flip', and may also contain
-                'filename', 'ori_shape', 'pad_shape', and 'img_norm_cfg'.
-                For details on the values of these keys see
-                `mmseg/datasets/pipelines/formatting.py:Collect`.
-            test_cfg (dict): The testing config.
-
-        Returns:
-            Tensor: Output segmentation map.
-        """
-        return self.forward(inputs)
-
-    def cls_seg(self, feat):
-        """Classify each pixel."""
-        if self.dropout is not None:
-            feat = self.dropout(feat)
-        output = self.conv_seg(feat)
-        return output
-
-    @force_fp32(apply_to=('seg_logit', ))
-    def losses(self, seg_logit, seg_label):
-        """Compute segmentation loss."""
-        loss = dict()
-        seg_logit = resize(
-            input=seg_logit,
-            size=seg_label.shape[2:],
-            mode='bilinear',
-            align_corners=self.align_corners)
-        if self.sampler is not None:
-            seg_weight = self.sampler.sample(seg_logit, seg_label)
-        else:
-            seg_weight = None
-        seg_label = seg_label.squeeze(1)
-        loss['loss_seg'] = self.loss_decode(
-            seg_logit,
-            seg_label,
-            weight=seg_weight,
-            ignore_index=self.ignore_index)
-        loss['acc_seg'] = accuracy(seg_logit, seg_label)
-        return loss
diff --git a/spaces/GroveStreet/GTA_SOVITS/cluster/__init__.py b/spaces/GroveStreet/GTA_SOVITS/cluster/__init__.py
deleted file mode 100644
index f1b9bde04e73e9218a5d534227caa4c25332f424..0000000000000000000000000000000000000000
--- a/spaces/GroveStreet/GTA_SOVITS/cluster/__init__.py
+++ /dev/null
@@ -1,29 +0,0 @@
-import numpy as np
-import torch
-from sklearn.cluster import KMeans
-
-def get_cluster_model(ckpt_path):
-    checkpoint = torch.load(ckpt_path)
-    kmeans_dict = {}
-    for spk, ckpt in checkpoint.items():
-        km = KMeans(ckpt["n_features_in_"])
-        km.__dict__["n_features_in_"] = ckpt["n_features_in_"]
-        km.__dict__["_n_threads"] = ckpt["_n_threads"]
-        km.__dict__["cluster_centers_"] = ckpt["cluster_centers_"]
-        kmeans_dict[spk] = km
-    return kmeans_dict
-
-def get_cluster_result(model, x, speaker):
-    """
-        x: np.array [t, 256]
-        return cluster class result
-    """
-    return model[speaker].predict(x)
-
-def get_cluster_center_result(model, x,speaker):
-    """x: np.array [t, 256]"""
-    predict = model[speaker].predict(x)
-    return model[speaker].cluster_centers_[predict]
-
-def get_center(model, x,speaker):
-    return model[speaker].cluster_centers_[x]
diff --git a/spaces/HCMUT-GraduateThesis-HNTThinh/rgbdsod-multimae-demo/s_multimae/criterion.py b/spaces/HCMUT-GraduateThesis-HNTThinh/rgbdsod-multimae-demo/s_multimae/criterion.py
deleted file mode 100644
index 17982b25f99349bc7120669f2b4b4219c218d6f1..0000000000000000000000000000000000000000
--- a/spaces/HCMUT-GraduateThesis-HNTThinh/rgbdsod-multimae-demo/s_multimae/criterion.py
+++ /dev/null
@@ -1,37 +0,0 @@
-from torch import nn, Tensor
-
-from .configs.base_config import base_cfg
-
-class Criterion(nn.Module):
-    def __init__(self, cfg: base_cfg) -> None:
-        super(Criterion, self).__init__()
-        self.use_label_smoothing = cfg.label_smoothing > 0.
-        self.label_smoothing = cfg.label_smoothing
-        
-        if self.label_smoothing >= 1.0 or self.label_smoothing < 0:
-            raise Exception('Label smoothing must be in range [0.0, 1.0), exclude 1.0')
-        
-        self.loss = nn.BCEWithLogitsLoss(reduction='mean')
-            
-    def smooth_label(self, gts: Tensor) -> Tensor:
-        '''
-        Ref: https://github.com/tensorflow/tensorflow/blob/fcc4b966f1265f466e82617020af93670141b009/tensorflow/python/keras/losses.py#L1573
-        '''
-        return gts * (1.0 - self.label_smoothing) + 0.5 * self.label_smoothing
-        
-    def forward(self, preds: Tensor, gts: Tensor):
-        if self.use_label_smoothing:
-            return self.loss(preds, self.smooth_label(gts))
-        else:
-            return self.loss(preds, gts)
-
-class DevCriterion(nn.Module):
-    def __init__(self) -> None:
-        super(DevCriterion, self).__init__()
-        self.loss = nn.L1Loss(reduction='mean')
-            
-    def forward(self, preds: Tensor, gts: Tensor):
-        max = preds.amax(dim=(2,3), keepdim=True)
-        min = preds.amin(dim=(2,3), keepdim=True)
-        preds = (preds-min) / (max - min + 1e-8)
-        return self.loss(preds, gts)
diff --git a/spaces/HCMUT-GraduateThesis-HNTThinh/rgbdsod-multimae-demo/utils/model.py b/spaces/HCMUT-GraduateThesis-HNTThinh/rgbdsod-multimae-demo/utils/model.py
deleted file mode 100644
index 31cd33606e92d944ae69966b8f9e255b65aa815a..0000000000000000000000000000000000000000
--- a/spaces/HCMUT-GraduateThesis-HNTThinh/rgbdsod-multimae-demo/utils/model.py
+++ /dev/null
@@ -1,279 +0,0 @@
-# --------------------------------------------------------
-# Based on timm and MAE-priv code bases
-# https://github.com/rwightman/pytorch-image-models/tree/master/timm
-# https://github.com/BUPT-PRIV/MAE-priv
-# --------------------------------------------------------
-
-""" Model / state_dict utils
-
-Hacked together by / Copyright 2020 Ross Wightman
-"""
-import fnmatch
-
-import torch
-from torchvision.ops.misc import FrozenBatchNorm2d
-
-from .model_ema import ModelEma
-
-
-def unwrap_model(model):
-    if isinstance(model, ModelEma):
-        return unwrap_model(model.ema)
-    else:
-        return model.module if hasattr(model, 'module') else model
-
-
-def get_state_dict(model, unwrap_fn=unwrap_model):
-    return unwrap_fn(model).state_dict()
-
-
-def avg_sq_ch_mean(model, input, output):
-    """ calculate average channel square mean of output activations
-    """
-    return torch.mean(output.mean(axis=[0, 2, 3]) ** 2).item()
-
-
-def avg_ch_var(model, input, output):
-    """ calculate average channel variance of output activations
-    """
-    return torch.mean(output.var(axis=[0, 2, 3])).item()
-
-
-def avg_ch_var_residual(model, input, output):
-    """ calculate average channel variance of output activations
-    """
-    return torch.mean(output.var(axis=[0, 2, 3])).item()
-
-
-class ActivationStatsHook:
-    """Iterates through each of `model`'s modules and matches modules using unix pattern 
-    matching based on `hook_fn_locs` and registers `hook_fn` to the module if there is 
-    a match. 
-
-    Arguments:
-        model (nn.Module): model from which we will extract the activation stats
-        hook_fn_locs (List[str]): List of `hook_fn` locations based on Unix type string 
-            matching with the name of model's modules. 
-        hook_fns (List[Callable]): List of hook functions to be registered at every
-            module in `layer_names`.
-    
-    Inspiration from https://docs.fast.ai/callback.hook.html.
-
-    Refer to https://gist.github.com/amaarora/6e56942fcb46e67ba203f3009b30d950 for an example 
-    on how to plot Signal Propogation Plots using `ActivationStatsHook`.
-    """
-
-    def __init__(self, model, hook_fn_locs, hook_fns):
-        self.model = model
-        self.hook_fn_locs = hook_fn_locs
-        self.hook_fns = hook_fns
-        if len(hook_fn_locs) != len(hook_fns):
-            raise ValueError("Please provide `hook_fns` for each `hook_fn_locs`, \
-                their lengths are different.")
-        self.stats = dict((hook_fn.__name__, []) for hook_fn in hook_fns)
-        for hook_fn_loc, hook_fn in zip(hook_fn_locs, hook_fns):
-            self.register_hook(hook_fn_loc, hook_fn)
-
-    def _create_hook(self, hook_fn):
-        def append_activation_stats(module, input, output):
-            out = hook_fn(module, input, output)
-            self.stats[hook_fn.__name__].append(out)
-
-        return append_activation_stats
-
-    def register_hook(self, hook_fn_loc, hook_fn):
-        for name, module in self.model.named_modules():
-            if not fnmatch.fnmatch(name, hook_fn_loc):
-                continue
-            module.register_forward_hook(self._create_hook(hook_fn))
-
-
-def extract_spp_stats(
-        model,
-        hook_fn_locs,
-        hook_fns,
-        input_shape=[8, 3, 224, 224]):
-    """Extract average square channel mean and variance of activations during 
-    forward pass to plot Signal Propogation Plots (SPP).
-    
-    Paper: https://arxiv.org/abs/2101.08692
-
-    Example Usage: https://gist.github.com/amaarora/6e56942fcb46e67ba203f3009b30d950
-    """
-    x = torch.normal(0., 1., input_shape)
-    hook = ActivationStatsHook(model, hook_fn_locs=hook_fn_locs, hook_fns=hook_fns)
-    _ = model(x)
-    return hook.stats
-
-
-def freeze_batch_norm_2d(module):
-    """
-    Converts all `BatchNorm2d` and `SyncBatchNorm` layers of provided module into `FrozenBatchNorm2d`. If `module` is
-    itself an instance of either `BatchNorm2d` or `SyncBatchNorm`, it is converted into `FrozenBatchNorm2d` and
-    returned. Otherwise, the module is walked recursively and submodules are converted in place.
-
-    Args:
-        module (torch.nn.Module): Any PyTorch module.
-
-    Returns:
-        torch.nn.Module: Resulting module
-
-    Inspired by https://github.com/pytorch/pytorch/blob/a5895f85be0f10212791145bfedc0261d364f103/torch/nn/modules/batchnorm.py#L762
-    """
-    res = module
-    if isinstance(module, (torch.nn.modules.batchnorm.BatchNorm2d, torch.nn.modules.batchnorm.SyncBatchNorm)):
-        res = FrozenBatchNorm2d(module.num_features)
-        res.num_features = module.num_features
-        res.affine = module.affine
-        if module.affine:
-            res.weight.data = module.weight.data.clone().detach()
-            res.bias.data = module.bias.data.clone().detach()
-        res.running_mean.data = module.running_mean.data
-        res.running_var.data = module.running_var.data
-        res.eps = module.eps
-    else:
-        for name, child in module.named_children():
-            new_child = freeze_batch_norm_2d(child)
-            if new_child is not child:
-                res.add_module(name, new_child)
-    return res
-
-
-def unfreeze_batch_norm_2d(module):
-    """
-    Converts all `FrozenBatchNorm2d` layers of provided module into `BatchNorm2d`. If `module` is itself and instance
-    of `FrozenBatchNorm2d`, it is converted into `BatchNorm2d` and returned. Otherwise, the module is walked
-    recursively and submodules are converted in place.
-
-    Args:
-        module (torch.nn.Module): Any PyTorch module.
-
-    Returns:
-        torch.nn.Module: Resulting module
-
-    Inspired by https://github.com/pytorch/pytorch/blob/a5895f85be0f10212791145bfedc0261d364f103/torch/nn/modules/batchnorm.py#L762
-    """
-    res = module
-    if isinstance(module, FrozenBatchNorm2d):
-        res = torch.nn.BatchNorm2d(module.num_features)
-        if module.affine:
-            res.weight.data = module.weight.data.clone().detach()
-            res.bias.data = module.bias.data.clone().detach()
-        res.running_mean.data = module.running_mean.data
-        res.running_var.data = module.running_var.data
-        res.eps = module.eps
-    else:
-        for name, child in module.named_children():
-            new_child = unfreeze_batch_norm_2d(child)
-            if new_child is not child:
-                res.add_module(name, new_child)
-    return res
-
-
-def _freeze_unfreeze(root_module, submodules=[], include_bn_running_stats=True, mode='freeze'):
-    """
-    Freeze or unfreeze parameters of the specified modules and those of all their hierarchical descendants. This is
-    done in place.
-    Args:
-        root_module (nn.Module, optional): Root module relative to which the `submodules` are referenced.
-        submodules (list[str]): List of modules for which the parameters will be (un)frozen. They are to be provided as
-            named modules relative to the root module (accessible via `root_module.named_modules()`). An empty list
-            means that the whole root module will be (un)frozen. Defaults to []
-        include_bn_running_stats (bool): Whether to also (un)freeze the running statistics of batch norm 2d layers.
-            Defaults to `True`.
-        mode (bool): Whether to freeze ("freeze") or unfreeze ("unfreeze"). Defaults to `"freeze"`.
-    """
-    assert mode in ["freeze", "unfreeze"], '`mode` must be one of "freeze" or "unfreeze"'
-
-    if isinstance(root_module, (torch.nn.modules.batchnorm.BatchNorm2d, torch.nn.modules.batchnorm.SyncBatchNorm)):
-        # Raise assertion here because we can't convert it in place
-        raise AssertionError(
-            "You have provided a batch norm layer as the `root module`. Please use "
-            "`timm.utils.model.freeze_batch_norm_2d` or `timm.utils.model.unfreeze_batch_norm_2d` instead.")
-
-    if isinstance(submodules, str):
-        submodules = [submodules]
-
-    named_modules = submodules
-    submodules = [root_module.get_submodule(m) for m in submodules]
-
-    if not len(submodules):
-        named_modules, submodules = list(zip(*root_module.named_children()))
-
-    for n, m in zip(named_modules, submodules):
-        # (Un)freeze parameters
-        for p in m.parameters():
-            p.requires_grad = False if mode == 'freeze' else True
-        if include_bn_running_stats:
-            # Helper to add submodule specified as a named_module
-            def _add_submodule(module, name, submodule):
-                split = name.rsplit('.', 1)
-                if len(split) > 1:
-                    module.get_submodule(split[0]).add_module(split[1], submodule)
-                else:
-                    module.add_module(name, submodule)
-
-            # Freeze batch norm
-            if mode == 'freeze':
-                res = freeze_batch_norm_2d(m)
-                # It's possible that `m` is a type of BatchNorm in itself, in which case `unfreeze_batch_norm_2d` won't
-                # convert it in place, but will return the converted result. In this case `res` holds the converted
-                # result and we may try to re-assign the named module
-                if isinstance(m, (torch.nn.modules.batchnorm.BatchNorm2d, torch.nn.modules.batchnorm.SyncBatchNorm)):
-                    _add_submodule(root_module, n, res)
-            # Unfreeze batch norm
-            else:
-                res = unfreeze_batch_norm_2d(m)
-                # Ditto. See note above in mode == 'freeze' branch
-                if isinstance(m, FrozenBatchNorm2d):
-                    _add_submodule(root_module, n, res)
-
-
-def freeze(root_module, submodules=[], include_bn_running_stats=True):
-    """
-    Freeze parameters of the specified modules and those of all their hierarchical descendants. This is done in place.
-    Args:
-        root_module (nn.Module): Root module relative to which `submodules` are referenced.
-        submodules (list[str]): List of modules for which the parameters will be frozen. They are to be provided as
-            named modules relative to the root module (accessible via `root_module.named_modules()`). An empty list
-            means that the whole root module will be frozen. Defaults to `[]`.
-        include_bn_running_stats (bool): Whether to also freeze the running statistics of `BatchNorm2d` and
-            `SyncBatchNorm` layers. These will be converted to `FrozenBatchNorm2d` in place. Hint: During fine tuning,
-            it's good practice to freeze batch norm stats. And note that these are different to the affine parameters
-            which are just normal PyTorch parameters. Defaults to `True`.
-
-    Hint: If you want to freeze batch norm ONLY, use `timm.utils.model.freeze_batch_norm_2d`.
-
-    Examples::
-
-        >>> model = timm.create_model('resnet18')
-        >>> # Freeze up to and including layer2
-        >>> submodules = [n for n, _ in model.named_children()]
-        >>> print(submodules)
-        ['conv1', 'bn1', 'act1', 'maxpool', 'layer1', 'layer2', 'layer3', 'layer4', 'global_pool', 'fc']
-        >>> freeze(model, submodules[:submodules.index('layer2') + 1])
-        >>> # Check for yourself that it works as expected
-        >>> print(model.layer2[0].conv1.weight.requires_grad)
-        False
-        >>> print(model.layer3[0].conv1.weight.requires_grad)
-        True
-        >>> # Unfreeze
-        >>> unfreeze(model)
-    """
-    _freeze_unfreeze(root_module, submodules, include_bn_running_stats=include_bn_running_stats, mode="freeze")
-
-
-def unfreeze(root_module, submodules=[], include_bn_running_stats=True):
-    """
-    Unfreeze parameters of the specified modules and those of all their hierarchical descendants. This is done in place.
-    Args:
-        root_module (nn.Module): Root module relative to which `submodules` are referenced.
-        submodules (list[str]): List of submodules for which the parameters will be (un)frozen. They are to be provided
-            as named modules relative to the root module (accessible via `root_module.named_modules()`). An empty
-            list means that the whole root module will be unfrozen. Defaults to `[]`.
-        include_bn_running_stats (bool): Whether to also unfreeze the running statistics of `FrozenBatchNorm2d` layers.
-            These will be converted to `BatchNorm2d` in place. Defaults to `True`.
-
-    See example in docstring for `freeze`.
-    """
-    _freeze_unfreeze(root_module, submodules, include_bn_running_stats=include_bn_running_stats, mode="unfreeze")
diff --git a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/constrained_decoding/README.md b/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/constrained_decoding/README.md
deleted file mode 100644
index e04b8b6a018214c8233fa87fd91d46a6dd1519d4..0000000000000000000000000000000000000000
--- a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/constrained_decoding/README.md
+++ /dev/null
@@ -1,123 +0,0 @@
-# (Vectorized) Lexically constrained decoding with dynamic beam allocation
-
-This page provides instructions for how to use lexically constrained decoding in Fairseq.
-Fairseq implements the code described in the following papers:
-
-* [Fast Lexically Constrained Decoding With Dynamic Beam Allocation](https://www.aclweb.org/anthology/N18-1119/) (Post & Vilar, 2018)
-* [Improved Lexically Constrained Decoding for Translation and Monolingual Rewriting](https://www.aclweb.org/anthology/N19-1090/) (Hu et al., 2019)
-
-## Quick start
-
-Constrained search is enabled by adding the command-line argument `--constraints` to `fairseq-interactive`.
-Constraints are appended to each line of input, separated by tabs. Each constraint (one or more tokens)
-is a separate field.
-
-The following command, using [Fairseq's WMT19 German--English model](https://github.com/pytorch/fairseq/blob/main/examples/wmt19/README.md),
-translates the sentence *Die maschinelle Übersetzung ist schwer zu kontrollieren.* with the constraints
-"hard" and "to influence".
-
-    echo -e "Die maschinelle Übersetzung ist schwer zu kontrollieren.\thard\ttoinfluence" \
-    | normalize.py | tok.py \
-    | fairseq-interactive /path/to/model \
-      --path /path/to/model/model1.pt \
-      --bpe fastbpe \
-      --bpe-codes /path/to/model/bpecodes \
-      --constraints \
-      -s de -t en \
-      --beam 10
-
-(tok.py and normalize.py can be found in the same directory as this README; they are just shortcuts around Fairseq's WMT19 preprocessing).
-This will generate the following output:
-
-    [snip]
-    S-0     Die masch@@ in@@ elle Über@@ setzung ist schwer zu kontrollieren .
-    W-0     1.844   seconds
-    C-0     hard
-    C-0     influence
-    H-0     -1.5333266258239746     Mach@@ ine trans@@ lation is hard to influence .
-    D-0     -1.5333266258239746     Machine translation is hard to influence .
-    P-0     -0.5434 -0.1423 -0.1930 -0.1415 -0.2346 -1.8031 -0.1701 -11.7727 -0.1815 -0.1511
-
-By default, constraints are generated in the order supplied, with any number (zero or more) of tokens generated
-between constraints. If you wish for the decoder to order the constraints, then use `--constraints unordered`.
-Note that you may want to use a larger beam.
-
-## Implementation details
-
-The heart of the implementation is in `fairseq/search.py`, which adds a `LexicallyConstrainedBeamSearch` instance.
-This instance of beam search tracks the progress of each hypothesis in the beam through the set of constraints
-provided for each input sentence. It does this using one of two classes, both found in `fairseq/token_generation_contstraints.py`:
-
-* OrderedConstraintState: assumes the `C` input constraints will be generated in the provided order
-* UnorderedConstraintState: tries to apply `C` (phrasal) constraints in all `C!` orders
-
-## Differences from Sockeye
-
-There are a number of [differences from Sockeye's implementation](https://awslabs.github.io/sockeye/inference.html#lexical-constraints).
-
-* Generating constraints in the order supplied (the default option here) is not available in Sockeye.
-* Due to an improved beam allocation method, there is no need to prune the beam.
-* Again due to better allocation, beam sizes as low as 10 or even 5 are often sufficient.
-* [The vector extensions described in Hu et al.](https://github.com/edwardjhu/sockeye/tree/trie_constraints) (NAACL 2019) were never merged
-  into the main Sockeye branch.
-
-## Citation
-
-The paper first describing lexical constraints for seq2seq decoding is:
-
-```bibtex
-@inproceedings{hokamp-liu-2017-lexically,
-  title = "Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search",
-  author = "Hokamp, Chris  and
-    Liu, Qun",
-  booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
-  month = jul,
-  year = "2017",
-  address = "Vancouver, Canada",
-  publisher = "Association for Computational Linguistics",
-  url = "https://www.aclweb.org/anthology/P17-1141",
-  doi = "10.18653/v1/P17-1141",
-  pages = "1535--1546",
-}
-```
-
-The fairseq implementation uses the extensions described in
-
-```bibtex
-@inproceedings{post-vilar-2018-fast,
-    title = "Fast Lexically Constrained Decoding with Dynamic Beam Allocation for Neural Machine Translation",
-    author = "Post, Matt  and
-      Vilar, David",
-    booktitle = "Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)",
-    month = jun,
-    year = "2018",
-    address = "New Orleans, Louisiana",
-    publisher = "Association for Computational Linguistics",
-    url = "https://www.aclweb.org/anthology/N18-1119",
-    doi = "10.18653/v1/N18-1119",
-    pages = "1314--1324",
-}
-```
-
-and
-
-```bibtex
-@inproceedings{hu-etal-2019-improved,
-  title = "Improved Lexically Constrained Decoding for Translation and Monolingual Rewriting",
-  author = "Hu, J. Edward  and
-    Khayrallah, Huda  and
-    Culkin, Ryan  and
-    Xia, Patrick  and
-    Chen, Tongfei  and
-    Post, Matt  and
-    Van Durme, Benjamin",
-  booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
-  month = jun,
-  year = "2019",
-  address = "Minneapolis, Minnesota",
-  publisher = "Association for Computational Linguistics",
-  url = "https://www.aclweb.org/anthology/N19-1090",
-  doi = "10.18653/v1/N19-1090",
-  pages = "839--850",
-}
-```
diff --git a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/linformer/linformer_src/modules/multihead_linear_attention.py b/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/linformer/linformer_src/modules/multihead_linear_attention.py
deleted file mode 100644
index 6be1007279217c5de644e8b054f5d14a19f06c55..0000000000000000000000000000000000000000
--- a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/linformer/linformer_src/modules/multihead_linear_attention.py
+++ /dev/null
@@ -1,481 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import math
-from typing import Dict, Optional, Tuple
-
-import torch
-import torch.nn.functional as F
-from fairseq import utils
-from fairseq.incremental_decoding_utils import with_incremental_state
-from fairseq.modules.quant_noise import quant_noise
-from torch import Tensor, nn
-from torch.nn import Parameter
-
-
-@with_incremental_state
-class MultiheadLinearAttention(nn.Module):
-    """Multi-headed linformer attention.
-
-    Projects the key and values down to the compressed dimension, before computing self-attention.
-
-    See "Linformer: Self-Attention with Linear Complexity" for more details.
-    """
-
-    def __init__(
-        self,
-        embed_dim,
-        num_heads,
-        kdim=None,
-        vdim=None,
-        dropout=0.0,
-        bias=True,
-        add_bias_kv=False,
-        add_zero_attn=False,
-        self_attention=False,
-        encoder_decoder_attention=False,
-        q_noise=0.0,
-        qn_block_size=8,
-        compressed=1,
-        max_seq_len=256,
-        shared_kv_compressed=0,
-        shared_compress_layer=None,
-        freeze_compress=0,
-    ):
-        super().__init__()
-        self.embed_dim = embed_dim
-        self.kdim = kdim if kdim is not None else embed_dim
-        self.vdim = vdim if vdim is not None else embed_dim
-        self.qkv_same_dim = self.kdim == embed_dim and self.vdim == embed_dim
-
-        self.num_heads = num_heads
-        self.dropout = dropout
-        self.head_dim = embed_dim // num_heads
-        assert (
-            self.head_dim * num_heads == self.embed_dim
-        ), "embed_dim must be divisible by num_heads"
-        self.scaling = self.head_dim ** -0.5
-
-        self.self_attention = self_attention
-        self.encoder_decoder_attention = encoder_decoder_attention
-
-        assert not self.self_attention or self.qkv_same_dim, (
-            "Self-attention requires query, key and " "value to be of the same size"
-        )
-
-        self.k_proj = quant_noise(
-            nn.Linear(self.kdim, embed_dim, bias=bias), q_noise, qn_block_size
-        )
-        self.v_proj = quant_noise(
-            nn.Linear(self.vdim, embed_dim, bias=bias), q_noise, qn_block_size
-        )
-        self.q_proj = quant_noise(
-            nn.Linear(embed_dim, embed_dim, bias=bias), q_noise, qn_block_size
-        )
-
-        # used for compress sequence to subsequence
-        if shared_compress_layer is None:
-            self.compress_seq_len = max_seq_len // compressed
-            self.compress_k = nn.Linear(max_seq_len, self.compress_seq_len, bias=False)
-            if shared_kv_compressed == 0:
-                self.compress_v = nn.Linear(
-                    max_seq_len, self.compress_seq_len, bias=False
-                )
-            self.layerwise_sharing = False
-        else:
-            self.compress_k = shared_compress_layer
-            if shared_kv_compressed == 0:
-                self.compress_v = shared_compress_layer
-            self.layerwise_sharing = True
-        self.shared_kv_compressed = shared_kv_compressed
-
-        self.out_proj = quant_noise(
-            nn.Linear(embed_dim, embed_dim, bias=bias), q_noise, qn_block_size
-        )
-
-        if add_bias_kv:
-            self.bias_k = Parameter(torch.Tensor(1, 1, embed_dim))
-            self.bias_v = Parameter(torch.Tensor(1, 1, embed_dim))
-        else:
-            self.bias_k = self.bias_v = None
-
-        self.add_zero_attn = add_zero_attn
-
-        self.reset_parameters()
-
-        if freeze_compress == 1:
-            self.compress_k.weight.requires_grad = False
-            if shared_kv_compressed == 0:
-                self.compress_v.weight.requires_grad = False
-
-        self.onnx_trace = False
-
-    def prepare_for_onnx_export_(self):
-        self.onnx_trace = True
-
-    def reset_parameters(self):
-        if self.qkv_same_dim:
-            # Empirically observed the convergence to be much better with
-            # the scaled initialization
-            nn.init.xavier_uniform_(self.k_proj.weight, gain=1 / math.sqrt(2))
-            nn.init.xavier_uniform_(self.v_proj.weight, gain=1 / math.sqrt(2))
-            nn.init.xavier_uniform_(self.q_proj.weight, gain=1 / math.sqrt(2))
-            if (
-                not self.layerwise_sharing
-            ):  # otherwise, we already initialize the parameters
-                nn.init.xavier_uniform_(self.compress_k.weight, gain=1 / math.sqrt(2))
-                if self.shared_kv_compressed == 0:
-                    nn.init.xavier_uniform_(
-                        self.compress_v.weight, gain=1 / math.sqrt(2)
-                    )
-        else:
-            nn.init.xavier_uniform_(self.k_proj.weight)
-            nn.init.xavier_uniform_(self.v_proj.weight)
-            nn.init.xavier_uniform_(self.q_proj.weight)
-            if (
-                not self.layerwise_sharing
-            ):  # otherwise, we already initialize the parameters
-                nn.init.xavier_uniform_(self.compress_k.weight)
-                if self.shared_kv_compressed == 0:
-                    nn.init.xavier_uniform_(self.compress_v.weight)
-
-        nn.init.xavier_uniform_(self.out_proj.weight)
-        if self.out_proj.bias is not None:
-            nn.init.constant_(self.out_proj.bias, 0.0)
-        if self.bias_k is not None:
-            nn.init.xavier_normal_(self.bias_k)
-        if self.bias_v is not None:
-            nn.init.xavier_normal_(self.bias_v)
-
-    def forward(
-        self,
-        query,
-        key: Optional[Tensor],
-        value: Optional[Tensor],
-        key_padding_mask: Optional[Tensor] = None,
-        incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]] = None,
-        need_weights: bool = True,
-        static_kv: bool = False,
-        attn_mask: Optional[Tensor] = None,
-        before_softmax: bool = False,
-        need_head_weights: bool = False,
-    ) -> Tuple[Tensor, Optional[Tensor]]:
-        """Input shape: Time x Batch x Channel
-
-        Args:
-            key_padding_mask (ByteTensor, optional): mask to exclude
-                keys that are pads, of shape `(batch, src_len)`, where
-                padding elements are indicated by 1s.
-            need_weights (bool, optional): return the attention weights,
-                averaged over heads (default: False).
-            attn_mask (ByteTensor, optional): typically used to
-                implement causal attention, where the mask prevents the
-                attention from looking forward in time (default: None).
-            before_softmax (bool, optional): return the raw attention
-                weights and values before the attention softmax.
-            need_head_weights (bool, optional): return the attention
-                weights for each head. Implies *need_weights*. Default:
-                return the average attention weights over all heads.
-        """
-        if need_head_weights:
-            need_weights = True
-
-        tgt_len, bsz, embed_dim = query.size()
-        assert embed_dim == self.embed_dim
-        assert list(query.size()) == [tgt_len, bsz, embed_dim]
-
-        if incremental_state is not None:
-            saved_state = self._get_input_buffer(incremental_state)
-            if saved_state is not None and "prev_key" in saved_state:
-                # previous time steps are cached - no need to recompute
-                # key and value if they are static
-                if static_kv:
-                    assert self.encoder_decoder_attention and not self.self_attention
-                    key = value = None
-        else:
-            saved_state = None
-
-        if self.self_attention:
-            q = self.q_proj(query)
-
-            k_input = query.permute(1, 2, 0).contiguous()  # B * C * T
-            k_input = (
-                F.linear(k_input, self.compress_k.weight[:, 0:tgt_len])
-                .permute(2, 0, 1)
-                .contiguous()
-            )
-            k = self.k_proj(k_input)
-
-            v_input = query.permute(1, 2, 0).contiguous()  # B * C * T
-            if self.shared_kv_compressed == 0:
-                v_input = (
-                    F.linear(v_input, self.compress_v.weight[:, 0:tgt_len])
-                    .permute(2, 0, 1)
-                    .contiguous()
-                )
-            if self.shared_kv_compressed == 1:  # use shared kv compressed linear layer
-                v_input = (
-                    F.linear(v_input, self.compress_k.weight[:, 0:tgt_len])
-                    .permute(2, 0, 1)
-                    .contiguous()
-                )
-            v = self.v_proj(v_input)
-        elif self.encoder_decoder_attention:
-            # encoder-decoder attention
-            q = self.q_proj(query)
-            if key is None:
-                assert value is None
-                k = v = None
-            else:
-                k = self.k_proj(key)
-                v = self.v_proj(key)
-
-        else:
-            assert key is not None and value is not None
-            q = self.q_proj(query)
-            k = self.k_proj(key)
-            v = self.v_proj(value)
-        q *= self.scaling
-
-        if self.bias_k is not None:
-            assert self.bias_v is not None
-            k = torch.cat([k, self.bias_k.repeat(1, bsz, 1)])
-            v = torch.cat([v, self.bias_v.repeat(1, bsz, 1)])
-            if attn_mask is not None:
-                attn_mask = torch.cat(
-                    [attn_mask, attn_mask.new_zeros(attn_mask.size(0), 1)], dim=1
-                )
-            if key_padding_mask is not None:
-                key_padding_mask = torch.cat(
-                    [
-                        key_padding_mask,
-                        key_padding_mask.new_zeros(key_padding_mask.size(0), 1),
-                    ],
-                    dim=1,
-                )
-
-        q = (
-            q.contiguous()
-            .view(tgt_len, bsz * self.num_heads, self.head_dim)
-            .transpose(0, 1)
-        )
-        if k is not None:
-            k = (
-                k.contiguous()
-                .view(-1, bsz * self.num_heads, self.head_dim)
-                .transpose(0, 1)
-            )
-        if v is not None:
-            v = (
-                v.contiguous()
-                .view(-1, bsz * self.num_heads, self.head_dim)
-                .transpose(0, 1)
-            )
-
-        if saved_state is not None:
-            # saved states are stored with shape (bsz, num_heads, seq_len, head_dim)
-            if "prev_key" in saved_state:
-                _prev_key = saved_state["prev_key"]
-                assert _prev_key is not None
-                prev_key = _prev_key.view(bsz * self.num_heads, -1, self.head_dim)
-                if static_kv:
-                    k = prev_key
-                else:
-                    assert k is not None
-                    k = torch.cat([prev_key, k], dim=1)
-            if "prev_value" in saved_state:
-                _prev_value = saved_state["prev_value"]
-                assert _prev_value is not None
-                prev_value = _prev_value.view(bsz * self.num_heads, -1, self.head_dim)
-                if static_kv:
-                    v = prev_value
-                else:
-                    assert v is not None
-                    v = torch.cat([prev_value, v], dim=1)
-            prev_key_padding_mask: Optional[Tensor] = None
-            if "prev_key_padding_mask" in saved_state:
-                prev_key_padding_mask = saved_state["prev_key_padding_mask"]
-            assert k is not None and v is not None
-            key_padding_mask = MultiheadLinearAttention._append_prev_key_padding_mask(
-                key_padding_mask=key_padding_mask,
-                prev_key_padding_mask=prev_key_padding_mask,
-                batch_size=bsz,
-                src_len=k.size(1),
-                static_kv=static_kv,
-            )
-
-            saved_state["prev_key"] = k.view(bsz, self.num_heads, -1, self.head_dim)
-            saved_state["prev_value"] = v.view(bsz, self.num_heads, -1, self.head_dim)
-            saved_state["prev_key_padding_mask"] = key_padding_mask
-            # In this branch incremental_state is never None
-            assert incremental_state is not None
-            incremental_state = self._set_input_buffer(incremental_state, saved_state)
-        assert k is not None
-        src_len = k.size(1)
-
-        if self.add_zero_attn:
-            assert v is not None
-            src_len += 1
-            k = torch.cat([k, k.new_zeros((k.size(0), 1) + k.size()[2:])], dim=1)
-            v = torch.cat([v, v.new_zeros((v.size(0), 1) + v.size()[2:])], dim=1)
-            if attn_mask is not None:
-                attn_mask = torch.cat(
-                    [attn_mask, attn_mask.new_zeros(attn_mask.size(0), 1)], dim=1
-                )
-
-        attn_weights = torch.bmm(q, k.transpose(1, 2))
-        attn_weights = MultiheadLinearAttention.apply_sparse_mask(
-            attn_weights, tgt_len, src_len, bsz
-        )
-
-        assert list(attn_weights.size()) == [bsz * self.num_heads, tgt_len, src_len]
-
-        if attn_mask is not None:
-            attn_mask = attn_mask.unsqueeze(0)
-            if self.onnx_trace:
-                attn_mask = attn_mask.repeat(attn_weights.size(0), 1, 1)
-            attn_weights += attn_mask
-
-        if before_softmax:
-            return attn_weights, v
-
-        attn_weights_float = utils.softmax(
-            attn_weights, dim=-1, onnx_trace=self.onnx_trace
-        )
-        attn_weights = attn_weights_float.type_as(attn_weights)
-        attn_probs = F.dropout(
-            attn_weights,
-            p=self.dropout,
-            training=self.training,
-        )
-        assert v is not None
-        attn = torch.bmm(attn_probs, v)
-        assert list(attn.size()) == [bsz * self.num_heads, tgt_len, self.head_dim]
-        if self.onnx_trace and attn.size(1) == 1:
-            # when ONNX tracing a single decoder step (sequence length == 1)
-            # the transpose is a no-op copy before view, thus unnecessary
-            attn = attn.contiguous().view(tgt_len, bsz, embed_dim)
-        else:
-            attn = attn.transpose(0, 1).contiguous().view(tgt_len, bsz, embed_dim)
-        attn = self.out_proj(attn)
-        attn_weights: Optional[Tensor] = None
-        if need_weights:
-            attn_weights = attn_weights_float.view(
-                bsz, self.num_heads, tgt_len, src_len
-            ).transpose(1, 0)
-            if not need_head_weights:
-                # average attention weights over heads
-                attn_weights = attn_weights.mean(dim=0)
-
-        return attn, attn_weights
-
-    @staticmethod
-    def _append_prev_key_padding_mask(
-        key_padding_mask: Optional[Tensor],
-        prev_key_padding_mask: Optional[Tensor],
-        batch_size: int,
-        src_len: int,
-        static_kv: bool,
-    ) -> Optional[Tensor]:
-        # saved key padding masks have shape (bsz, seq_len)
-        if prev_key_padding_mask is not None and static_kv:
-            new_key_padding_mask = prev_key_padding_mask
-        elif prev_key_padding_mask is not None and key_padding_mask is not None:
-            new_key_padding_mask = torch.cat(
-                [prev_key_padding_mask.float(), key_padding_mask.float()], dim=1
-            )
-        # During incremental decoding, as the padding token enters and
-        # leaves the frame, there will be a time when prev or current
-        # is None
-        elif prev_key_padding_mask is not None:
-            filler = torch.zeros(
-                (batch_size, src_len - prev_key_padding_mask.size(1)),
-                device=prev_key_padding_mask.device,
-            )
-            new_key_padding_mask = torch.cat(
-                [prev_key_padding_mask.float(), filler.float()], dim=1
-            )
-        elif key_padding_mask is not None:
-            filler = torch.zeros(
-                (batch_size, src_len - key_padding_mask.size(1)),
-                device=key_padding_mask.device,
-            )
-            new_key_padding_mask = torch.cat(
-                [filler.float(), key_padding_mask.float()], dim=1
-            )
-        else:
-            new_key_padding_mask = prev_key_padding_mask
-        return new_key_padding_mask
-
-    @torch.jit.export
-    def reorder_incremental_state(
-        self,
-        incremental_state: Dict[str, Dict[str, Optional[Tensor]]],
-        new_order: Tensor,
-    ):
-        """Reorder buffered internal state (for incremental generation)."""
-        input_buffer = self._get_input_buffer(incremental_state)
-        if input_buffer is not None:
-            for k in input_buffer.keys():
-                input_buffer_k = input_buffer[k]
-                if input_buffer_k is not None:
-                    if self.encoder_decoder_attention and input_buffer_k.size(
-                        0
-                    ) == new_order.size(0):
-                        break
-                    input_buffer[k] = input_buffer_k.index_select(0, new_order)
-            incremental_state = self._set_input_buffer(incremental_state, input_buffer)
-        return incremental_state
-
-    def _get_input_buffer(
-        self, incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]]
-    ) -> Dict[str, Optional[Tensor]]:
-        result = self.get_incremental_state(incremental_state, "attn_state")
-        if result is not None:
-            return result
-        else:
-            empty_result: Dict[str, Optional[Tensor]] = {}
-            return empty_result
-
-    def _set_input_buffer(
-        self,
-        incremental_state: Dict[str, Dict[str, Optional[Tensor]]],
-        buffer: Dict[str, Optional[Tensor]],
-    ):
-        return self.set_incremental_state(incremental_state, "attn_state", buffer)
-
-    def apply_sparse_mask(attn_weights, tgt_len: int, src_len: int, bsz: int):
-        return attn_weights
-
-    def upgrade_state_dict_named(self, state_dict, name):
-        prefix = name + "." if name != "" else ""
-        items_to_add = {}
-        keys_to_remove = []
-        for k in state_dict.keys():
-            if k.endswith(prefix + "in_proj_weight"):
-                # in_proj_weight used to be q + k + v with same dimensions
-                dim = int(state_dict[k].shape[0] / 3)
-                items_to_add[prefix + "q_proj.weight"] = state_dict[k][:dim]
-                items_to_add[prefix + "k_proj.weight"] = state_dict[k][dim : 2 * dim]
-                items_to_add[prefix + "v_proj.weight"] = state_dict[k][2 * dim :]
-
-                keys_to_remove.append(k)
-
-                k_bias = prefix + "in_proj_bias"
-                if k_bias in state_dict.keys():
-                    dim = int(state_dict[k].shape[0] / 3)
-                    items_to_add[prefix + "q_proj.bias"] = state_dict[k_bias][:dim]
-                    items_to_add[prefix + "k_proj.bias"] = state_dict[k_bias][
-                        dim : 2 * dim
-                    ]
-                    items_to_add[prefix + "v_proj.bias"] = state_dict[k_bias][2 * dim :]
-
-                    keys_to_remove.append(prefix + "in_proj_bias")
-
-        for k in keys_to_remove:
-            del state_dict[k]
-
-        for key, value in items_to_add.items():
-            state_dict[key] = value
diff --git a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/m2m_100/tokenizers/tokenize_indic.py b/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/m2m_100/tokenizers/tokenize_indic.py
deleted file mode 100644
index a44fad07f7c718f99cccd445f33c62b0e3c562f4..0000000000000000000000000000000000000000
--- a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/m2m_100/tokenizers/tokenize_indic.py
+++ /dev/null
@@ -1,23 +0,0 @@
-#!/usr/bin/env python3
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-# Use: echo {text} | python tokenize_indic.py {language}
-
-import sys
-
-from indicnlp.normalize.indic_normalize import IndicNormalizerFactory
-from indicnlp.tokenize.indic_tokenize import trivial_tokenize
-
-
-factory = IndicNormalizerFactory()
-normalizer = factory.get_normalizer(
-    sys.argv[1], remove_nuktas=False, nasals_mode="do_nothing"
-)
-
-for line in sys.stdin:
-    normalized_line = normalizer.normalize(line.strip())
-    tokenized_line = " ".join(trivial_tokenize(normalized_line, sys.argv[1]))
-    print(tokenized_line)
diff --git a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/simultaneous_translation/utils/__init__.py b/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/simultaneous_translation/utils/__init__.py
deleted file mode 100644
index 1e9ce844f59a4211061392084cc81075e6bab19f..0000000000000000000000000000000000000000
--- a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/examples/simultaneous_translation/utils/__init__.py
+++ /dev/null
@@ -1,14 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import importlib
-import os
-
-
-# automatically import any Python files in the criterions/ directory
-for file in sorted(os.listdir(os.path.dirname(__file__))):
-    if file.endswith(".py") and not file.startswith("_"):
-        module = file[: file.find(".py")]
-        importlib.import_module("examples.simultaneous_translation.utils." + module)
diff --git a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/fairseq/logging/__init__.py b/spaces/HarryLee/eCommerceImageCaptioning/fairseq/fairseq/logging/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/fairseq/modules/quantization/scalar/modules/__init__.py b/spaces/HarryLee/eCommerceImageCaptioning/fairseq/fairseq/modules/quantization/scalar/modules/__init__.py
deleted file mode 100644
index 8031d9cdb23f2bc72596f8bc9cfa4965f96e3e6c..0000000000000000000000000000000000000000
--- a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/fairseq/modules/quantization/scalar/modules/__init__.py
+++ /dev/null
@@ -1,9 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-from .qact import ActivationQuantizer  # NOQA
-from .qconv import IntConv2d  # NOQA
-from .qemb import IntEmbedding  # NOQA
-from .qlinear import IntLinear  # NOQA
diff --git a/spaces/Hexamind/swarms/rotate_wrap.py b/spaces/Hexamind/swarms/rotate_wrap.py
deleted file mode 100644
index 7607a0a21fad8570d1f1251d519dc3a548eeccc0..0000000000000000000000000000000000000000
--- a/spaces/Hexamind/swarms/rotate_wrap.py
+++ /dev/null
@@ -1,93 +0,0 @@
-import numpy as np
-import gym
-
-from drone import Drone
-
-
-class RotateWrapper(gym.Wrapper):
-    """
-    :param env: (gym.Env) Gym environment that will be wrapped
-    """
-
-    def __init__(self, env):
-        # Call the parent constructor, so we can access self.env later
-        super(RotateWrapper, self).__init__(env)
-        self.angle = 0
-
-    def reset(self):
-        """
-        Reset the environment
-        """
-        obs = self.env.reset()
-
-        obs = self.post_obs(obs)
-
-        return obs
-
-    def step(self, action):
-        """
-        :param action: ([float] or int) Action taken by the agent
-        :return: (np.ndarray, float, bool, dict) observation, reward, is the episode over?, additional informations
-        """
-
-        action = self.rotate_action(action)
-
-        obs, reward, done, info = self.env.step(action)
-
-        obs = self.post_obs(obs)
-
-        return obs, reward, done, info
-
-    def post_obs(self, obs):
-        self.angle = self.get_angle(obs)
-        return self.rotate_obs(obs)
-
-    def get_angle(self, obs: np.ndarray) -> float:
-        blue_obs, red_obs, blue_fire, red_fire = obs
-        sigma = 0
-
-        for this_obs in (blue_obs, red_obs):
-            for d in this_obs:
-                sigma += d[0] * np.exp(1j * d[1])
-        angle = np.angle(sigma)
-        return angle
-
-    def rotate_obs(self, obs):
-        blue_obs, red_obs, blue_fire, red_fire = obs
-
-        rotated_blue_obs = []
-        rotated_red_obs = []
-
-        for this_obs, is_blue, rotated_obs in zip((blue_obs, red_obs),
-                                                  (True, False),
-                                                  (rotated_blue_obs, rotated_red_obs)):
-            drone = Drone(is_blue=is_blue)
-            for d in this_obs:
-
-                d_meter = np.zeros(6,)
-                # get the pos and speed in cylindrical coordinated in meters
-                d_meter[:3] = drone.from_norm(d[:3], drone.max_positions, drone.min_positions)
-                d_meter[3:6] = drone.from_norm(d[3:6], drone.max_speeds, drone.min_speeds)
-
-                # rotate
-                d_meter[1] -= self.angle
-                d_meter[4] -= self.angle
-
-                # back to norm
-                d[:3] = drone.to_norm(d_meter[:3], drone.max_positions, drone.min_positions)
-                d[3:6] = drone.to_norm(d_meter[3:6], drone.max_speeds, drone.min_speeds)
-
-                rotated_obs.append(d)
-
-            del drone
-
-        return np.array(rotated_blue_obs), np.array(rotated_red_obs), blue_fire, red_fire
-
-    def rotate_action(self, action):
-
-        blue_action, red_action = action
-        blue_action = np.array(list(map(lambda x: [x[0], (x[1]+self.angle/2/np.pi) % 1, x[2]], blue_action)))
-        red_action = np.array(list(map(lambda x: [x[0], (x[1]+self.angle/2/np.pi) % 1, x[2]], red_action)))
-        action = blue_action, red_action
-
-        return action
diff --git a/spaces/HuggingFaceM4/IDEFICS_Data_Measurement_Tool/cache_dir/HuggingFaceM4/OBELICS_opt_out_docs_removed_2023_07_12_train_general_metadata/zipf/zipf_fig.html b/spaces/HuggingFaceM4/IDEFICS_Data_Measurement_Tool/cache_dir/HuggingFaceM4/OBELICS_opt_out_docs_removed_2023_07_12_train_general_metadata/zipf/zipf_fig.html
deleted file mode 100644
index 98b2f282cc57452654bd612e9a20ee9179c42de9..0000000000000000000000000000000000000000
--- a/spaces/HuggingFaceM4/IDEFICS_Data_Measurement_Tool/cache_dir/HuggingFaceM4/OBELICS_opt_out_docs_removed_2023_07_12_train_general_metadata/zipf/zipf_fig.html
+++ /dev/null
@@ -1,14 +0,0 @@
-<html>
-<head><meta charset="utf-8" /></head>
-<body>
-    <div>                        <script type="text/javascript">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>
-        <script type="text/javascript">/**
-* plotly.js v2.24.1
-* Copyright 2012-2023, Plotly, Inc.
-* All rights reserved.
-* Licensed under the MIT license
-*/
-/*! For license information please see plotly.min.js.LICENSE.txt */
-!function(t,e){"object"==typeof exports&&"object"==typeof module?module.exports=e():"function"==typeof define&&define.amd?define([],e):"object"==typeof exports?exports.Plotly=e():t.Plotly=e()}(self,(function(){return function(){var t={98847:function(t,e,r){"use strict";var n=r(71828),i={"X,X div":'direction:ltr;font-family:"Open Sans",verdana,arial,sans-serif;margin:0;padding:0;',"X input,X button":'font-family:"Open Sans",verdana,arial,sans-serif;',"X input:focus,X button:focus":"outline:none;","X a":"text-decoration:none;","X a:hover":"text-decoration:none;","X .crisp":"shape-rendering:crispEdges;","X .user-select-none":"-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;-o-user-select:none;user-select:none;","X svg":"overflow:hidden;","X svg a":"fill:#447adb;","X svg a:hover":"fill:#3c6dc5;","X .main-svg":"position:absolute;top:0;left:0;pointer-events:none;","X .main-svg .draglayer":"pointer-events:all;","X .cursor-default":"cursor:default;","X 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a._fullLayout[n]=r[n],i.coercePosition(e,a,l,t,t,.5)}l("visible")&&(o(t,e,a.fullLayout,l),u("x"),u("y"),u("z"),n.noneOrAll(t,e,["x","y","z"]),e.xref="x",e.yref="y",e.zref="z",l("xanchor"),l("yanchor"),l("xshift"),l("yshift"),e.showarrow&&(e.axref="pixel",e.ayref="pixel",l("ax",-10),l("ay",-30),n.noneOrAll(t,e,["ax","ay"])))}t.exports=function(t,e,r){a(t,e,{name:"annotations",handleItemDefaults:l,fullLayout:r.fullLayout})}},82188:function(t,e,r){"use strict";var n=r(92605).drawRaw,i=r(63538),a=["x","y","z"];t.exports=function(t){for(var e=t.fullSceneLayout,r=t.dataScale,o=e.annotations,s=0;s<o.length;s++){for(var l=o[s],u=!1,c=0;c<3;c++){var f=a[c],h=l[f],p=e[f+"axis"].r2fraction(h);if(p<0||p>1){u=!0;break}}u?t.fullLayout._infolayer.select(".annotation-"+t.id+'[data-index="'+s+'"]').remove():(l._pdata=i(t.glplot.cameraParams,[e.xaxis.r2l(l.x)*r[0],e.yaxis.r2l(l.y)*r[1],e.zaxis.r2l(l.z)*r[2]]),n(t.graphDiv,l,s,t.id,l._xa,l._ya))}}},2468:function(t,e,r){"use strict";var n=r(73972),i=r(71828);t.exports={moduleType:"component",name:"annotations3d",schema:{subplots:{scene:{annotations:r(26997)}}},layoutAttributes:r(26997),handleDefaults:r(20226),includeBasePlot:function(t,e){var r=n.subplotsRegistry.gl3d;if(r)for(var a=r.attrRegex,o=Object.keys(t),s=0;s<o.length;s++){var l=o[s];a.test(l)&&(t[l].annotations||[]).length&&(i.pushUnique(e._basePlotModules,r),i.pushUnique(e._subplots.gl3d,l))}},convert:r(5485),draw:r(82188)}},7561:function(t,e,r){"use strict";t.exports=r(63489),r(94338),r(3961),r(38751),r(86825),r(37715),r(99384),r(43805),r(88874),r(83290),r(29108),r(55422),r(94320),r(31320),r(51367),r(21457)},72201:function(t,e,r){"use strict";var n=r(7561),i=r(71828),a=r(50606),o=a.EPOCHJD,s=a.ONEDAY,l={valType:"enumerated",values:i.sortObjectKeys(n.calendars),editType:"calc",dflt:"gregorian"},u=function(t,e,r,n){var a={};return 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n=r(41940),i=r(22399);t.exports={_isSubplotObj:!0,visible:{valType:"boolean",dflt:!0,editType:"legend"},bgcolor:{valType:"color",editType:"legend"},bordercolor:{valType:"color",dflt:i.defaultLine,editType:"legend"},borderwidth:{valType:"number",min:0,dflt:0,editType:"legend"},font:n({editType:"legend"}),grouptitlefont:n({editType:"legend"}),orientation:{valType:"enumerated",values:["v","h"],dflt:"v",editType:"legend"},traceorder:{valType:"flaglist",flags:["reversed","grouped"],extras:["normal"],editType:"legend"},tracegroupgap:{valType:"number",min:0,dflt:10,editType:"legend"},entrywidth:{valType:"number",min:0,editType:"legend"},entrywidthmode:{valType:"enumerated",values:["fraction","pixels"],dflt:"pixels",editType:"legend"},itemsizing:{valType:"enumerated",values:["trace","constant"],dflt:"trace",editType:"legend"},itemwidth:{valType:"number",min:30,dflt:30,editType:"legend"},itemclick:{valType:"enumerated",values:["toggle","toggleothers",!1],dflt:"toggle",editType:"legend"},itemdoubleclick:{valType:"enumerated",values:["toggle","toggleothers",!1],dflt:"toggleothers",editType:"legend"},groupclick:{valType:"enumerated",values:["toggleitem","togglegroup"],dflt:"togglegroup",editType:"legend"},x:{valType:"number",editType:"legend"},xref:{valType:"enumerated",dflt:"paper",values:["container","paper"],editType:"layoutstyle"},xanchor:{valType:"enumerated",values:["auto","left","center","right"],dflt:"left",editType:"legend"},y:{valType:"number",editType:"legend"},yref:{valType:"enumerated",dflt:"paper",values:["container","paper"],editType:"layoutstyle"},yanchor:{valType:"enumerated",values:["auto","top","middle","bottom"],editType:"legend"},uirevision:{valType:"any",editType:"none"},valign:{valType:"enumerated",values:["top","middle","bottom"],dflt:"middle",editType:"legend"},title:{text:{valType:"string",dflt:"",editType:"legend"},font:n({editType:"legend"}),side:{valType:"enumerated",values:["top","left","top 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e=0;e<s.modeBarButtonsToAdd.length;e++)if(c(t,s.modeBarButtonsToAdd[e]))return!1;return!0}))),v=e._has("cartesian"),g=e._has("gl3d"),y=e._has("geo"),m=e._has("pie"),x=e._has("funnelarea"),b=e._has("gl2d"),_=e._has("ternary"),w=e._has("mapbox"),T=e._has("polar"),k=e._has("smith"),A=e._has("sankey"),M=function(t){for(var e=n.list({_fullLayout:t},null,!0),r=0;r<e.length;r++)if(!e[r].fixedrange)return!1;return!0}(e),S=o(e.hovermode),E=[];function L(t){if(t.length){for(var e=[],r=0;r<t.length;r++){for(var n=t[r],i=l[n],a=i.name.toLowerCase(),o=(i._cat||i.name).toLowerCase(),s=!1,u=0;u<d.length;u++){var c=d[u].toLowerCase();if(c===a||c===o){s=!0;break}}s||e.push(l[n])}E.push(e)}}var C=["toImage"];s.showEditInChartStudio?C.push("editInChartStudio"):s.showSendToCloud&&C.push("sendDataToCloud"),L(C);var P=[],O=[],I=[],D=[];(v||b||m||x||_)+y+g+w+T+k>1?(O=["toggleHover"],I=["resetViews"]):y?(P=["zoomInGeo","zoomOutGeo"],O=["hoverClosestGeo"],I=["resetGeo"]):g?(O=["hoverClosest3d"],I=["resetCameraDefault3d","resetCameraLastSave3d"]):w?(P=["zoomInMapbox","zoomOutMapbox"],O=["toggleHover"],I=["resetViewMapbox"]):b?O=["hoverClosestGl2d"]:m?O=["hoverClosestPie"]:A?(O=["hoverClosestCartesian","hoverCompareCartesian"],I=["resetViewSankey"]):O=["toggleHover"],v&&(O=["toggleSpikelines","hoverClosestCartesian","hoverCompareCartesian"]),(function(t){for(var e=0;e<t.length;e++)if(!a.traceIs(t[e],"noHover"))return!1;return!0}(r)||S)&&(O=[]),!v&&!b||M||(P=["zoomIn2d","zoomOut2d","autoScale2d"],"resetViews"!==I[0]&&(I=["resetScale2d"])),g?D=["zoom3d","pan3d","orbitRotation","tableRotation"]:(v||b)&&!M||_?D=["zoom2d","pan2d"]:w||y?D=["pan2d"]:T&&(D=["zoom2d"]),function(t){for(var e=!1,r=0;r<t.length&&!e;r++){var n=t[r];n._module&&n._module.selectPoints&&(a.traceIs(n,"scatter-like")?(i.hasMarkers(n)||i.hasText(n))&&(e=!0):a.traceIs(n,"box-violin")&&"all"!==n.boxpoints&&"all"!==n.points||(e=!0))}return e}(r)&&D.push("select2d","lasso2d");var z=[],R=function(t){-1===z.indexOf(t)&&-1!==O.indexOf(t)&&z.push(t)};if(Array.isArray(p)){for(var F=[],B=0;B<p.length;B++){var N=p[B];"string"==typeof N?(N=N.toLowerCase(),-1!==u.indexOf(N)?(e._has("mapbox")||e._has("cartesian"))&&D.push(N):"togglespikelines"===N?R("toggleSpikelines"):"togglehover"===N?R("toggleHover"):"hovercompare"===N?R("hoverCompareCartesian"):"hoverclosest"===N?(R("hoverClosestCartesian"),R("hoverClosestGeo"),R("hoverClosest3d"),R("hoverClosestGl2d"),R("hoverClosestPie")):"v1hovermode"===N&&(R("toggleHover"),R("hoverClosestCartesian"),R("hoverCompareCartesian"),R("hoverClosestGeo"),R("hoverClosest3d"),R("hoverClosestGl2d"),R("hoverClosestPie"))):F.push(N)}p=F}return L(D),L(P.concat(I)),L(z),function(t,e){if(e.length)if(Array.isArray(e[0]))for(var r=0;r<e.length;r++)t.push(e[r]);else t.push(e);return t}(E,p)}(t),f?f.update(t,h):e._modeBar=s(t,h)}else f&&(f.destroy(),delete e._modeBar)}},37676:function(t,e,r){"use strict";var n=r(39898),i=r(92770),a=r(71828),o=r(24255),s=r(11506).version,l=new DOMParser;function u(t){this.container=t.container,this.element=document.createElement("div"),this.update(t.graphInfo,t.buttons),this.container.appendChild(this.element)}var c=u.prototype;c.update=function(t,e){this.graphInfo=t;var r=this.graphInfo._context,n=this.graphInfo._fullLayout,i="modebar-"+n._uid;this.element.setAttribute("id",i),this._uid=i,this.element.className="modebar","hover"===r.displayModeBar&&(this.element.className+=" modebar--hover ease-bg"),"v"===n.modebar.orientation&&(this.element.className+=" vertical",e=e.reverse());var o=n.modebar,s="hover"===r.displayModeBar?".js-plotly-plot .plotly:hover 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Error("must provide button 'name' in button config");if(-1!==e.buttonsNames.indexOf(n))throw new Error("button name '"+n+"' is taken");e.buttonsNames.push(n);var i=e.createButton(t);e.buttonElements.push(i),r.appendChild(i)})),e.element.appendChild(r)}))},c.createGroup=function(){var t=document.createElement("div");return t.className="modebar-group",t},c.createButton=function(t){var e=this,r=document.createElement("a");r.setAttribute("rel","tooltip"),r.className="modebar-btn";var i=t.title;void 0===i?i=t.name:"function"==typeof i&&(i=i(this.graphInfo)),(i||0===i)&&r.setAttribute("data-title",i),void 0!==t.attr&&r.setAttribute("data-attr",t.attr);var a=t.val;if(void 0!==a&&("function"==typeof a&&(a=a(this.graphInfo)),r.setAttribute("data-val",a)),"function"!=typeof t.click)throw new Error("must provide button 'click' function in button 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e=this.graphInfo._fullLayout,r=void 0!==t?t.getAttribute("data-attr"):null;this.buttonElements.forEach((function(t){var i=t.getAttribute("data-val")||!0,o=t.getAttribute("data-attr"),s="true"===t.getAttribute("data-toggle"),l=n.select(t);if(s)o===r&&l.classed("active",!l.classed("active"));else{var u=null===o?o:a.nestedProperty(e,o).get();l.classed("active",u===i)}}))},c.hasButtons=function(t){var e=this.buttons;if(!e)return!1;if(t.length!==e.length)return!1;for(var r=0;r<t.length;++r){if(t[r].length!==e[r].length)return!1;for(var n=0;n<t[r].length;n++)if(t[r][n].name!==e[r][n].name)return!1}return!0},c.getLogo=function(){var t=this.createGroup(),e=document.createElement("a");return e.href="https://plotly.com/",e.target="_blank",e.setAttribute("data-title",a._(this.graphInfo,"Produced with Plotly.js")+" (v"+s+")"),e.className="modebar-btn plotlyjsicon modebar-btn--logo",e.appendChild(this.createIcon(o.newplotlylogo)),t.appendChild(e),t},c.removeAllButtons=function(){for(;this.element.firstChild;)this.element.removeChild(this.element.firstChild);this.hasLogo=!1},c.destroy=function(){a.removeElement(this.container.querySelector(".modebar")),a.deleteRelatedStyleRule(this._uid)},t.exports=function(t,e){var r=t._fullLayout,i=new u({graphInfo:t,container:r._modebardiv.node(),buttons:e});return r._privateplot&&n.select(i.element).append("span").classed("badge-private float--left",!0).text("PRIVATE"),i}},37113:function(t,e,r){"use strict";var n=r(41940),i=r(22399),a=(0,r(44467).templatedArray)("button",{visible:{valType:"boolean",dflt:!0,editType:"plot"},step:{valType:"enumerated",values:["month","year","day","hour","minute","second","all"],dflt:"month",editType:"plot"},stepmode:{valType:"enumerated",values:["backward","todate"],dflt:"backward",editType:"plot"},count:{valType:"number",min:0,dflt:1,editType:"plot"},label:{valType:"string",editType:"plot"},editType:"plot"});t.exports={visible:{valType:"boolean",editType:"plot"},buttons:a,x:{valType:"number",min:-2,max:3,editType:"plot"},xanchor:{valType:"enumerated",values:["auto","left","center","right"],dflt:"left",editType:"plot"},y:{valType:"number",min:-2,max:3,editType:"plot"},yanchor:{valType:"enumerated",values:["auto","top","middle","bottom"],dflt:"bottom",editType:"plot"},font:n({editType:"plot"}),bgcolor:{valType:"color",dflt:i.lightLine,editType:"plot"},activecolor:{valType:"color",editType:"plot"},bordercolor:{valType:"color",dflt:i.defaultLine,editType:"plot"},borderwidth:{valType:"number",min:0,dflt:0,editType:"plot"},editType:"plot"}},89573:function(t){"use 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g=d("bgcolor");d("activecolor",i.contrast(g,l.lightAmount,l.darkAmount)),d("bordercolor"),d("borderwidth")}}},21598:function(t,e,r){"use strict";var n=r(39898),i=r(73972),a=r(74875),o=r(7901),s=r(91424),l=r(71828),u=l.strTranslate,c=r(63893),f=r(41675),h=r(18783),p=h.LINE_SPACING,d=h.FROM_TL,v=h.FROM_BR,g=r(89573),y=r(70565);function m(t){return t._id}function x(t,e,r){var n=l.ensureSingle(t,"rect","selector-rect",(function(t){t.attr("shape-rendering","crispEdges")}));n.attr({rx:g.rx,ry:g.ry}),n.call(o.stroke,e.bordercolor).call(o.fill,function(t,e){return e._isActive||e._isHovered?t.activecolor:t.bgcolor}(e,r)).style("stroke-width",e.borderwidth+"px")}function b(t,e,r,n){var i,a;l.ensureSingle(t,"text","selector-text",(function(t){t.attr("text-anchor","middle")})).call(s.font,e.font).text((i=r,a=n._fullLayout._meta,i.label?a?l.templateString(i.label,a):i.label:"all"===i.step?"all":i.count+i.step.charAt(0))).call((function(t){c.convertToTspans(t,n)}))}t.exports=function(t){var e=t._fullLayout._infolayer.selectAll(".rangeselector").data(function(t){for(var e=f.list(t,"x",!0),r=[],n=0;n<e.length;n++){var i=e[n];i.rangeselector&&i.rangeselector.visible&&r.push(i)}return r}(t),m);e.enter().append("g").classed("rangeselector",!0),e.exit().remove(),e.style({cursor:"pointer","pointer-events":"all"}),e.each((function(e){var r=n.select(this),o=e,f=o.rangeselector,h=r.selectAll("g.button").data(l.filterVisible(f.buttons));h.enter().append("g").classed("button",!0),h.exit().remove(),h.each((function(e){var r=n.select(this),a=y(o,e);e._isActive=function(t,e,r){if("all"===e.step)return!0===t.autorange;var n=Object.keys(r);return t.range[0]===r[n[0]]&&t.range[1]===r[n[1]]}(o,e,a),r.call(x,f,e),r.call(b,f,e,t),r.on("click",(function(){t._dragged||i.call("_guiRelayout",t,a)})),r.on("mouseover",(function(){e._isHovered=!0,r.call(x,f,e)})),r.on("mouseout",(function(){e._isHovered=!1,r.call(x,f,e)}))})),function(t,e,r,i,o){var f=0,h=0,y=r.borderwidth;e.each((function(){var t=n.select(this).select(".selector-text"),e=r.font.size*p,i=Math.max(e*c.lineCount(t),16)+3;h=Math.max(h,i)})),e.each((function(){var t=n.select(this),e=t.select(".selector-rect"),i=t.select(".selector-text"),a=i.node()&&s.bBox(i.node()).width,o=r.font.size*p,l=c.lineCount(i),d=Math.max(a+10,g.minButtonWidth);t.attr("transform",u(y+f,y)),e.attr({x:0,y:0,width:d,height:h}),c.positionText(i,d/2,h/2-(l-1)*o/2+3),f+=d+5}));var m=t._fullLayout._size,x=m.l+m.w*r.x,b=m.t+m.h*(1-r.y),_="left";l.isRightAnchor(r)&&(x-=f,_="right"),l.isCenterAnchor(r)&&(x-=f/2,_="center");var w="top";l.isBottomAnchor(r)&&(b-=h,w="bottom"),l.isMiddleAnchor(r)&&(b-=h/2,w="middle"),f=Math.ceil(f),h=Math.ceil(h),x=Math.round(x),b=Math.round(b),a.autoMargin(t,i+"-range-selector",{x:r.x,y:r.y,l:f*d[_],r:f*v[_],b:h*v[w],t:h*d[w]}),o.attr("transform",u(x,b))}(t,h,f,o._name,r)}))}},70565:function(t,e,r){"use strict";var n=r(81041),i=r(71828).titleCase;t.exports=function(t,e){var r=t._name,a={};if("all"===e.step)a[r+".autorange"]=!0;else{var o=function(t,e){var r,a=t.range,o=new Date(t.r2l(a[1])),s=e.step,l=n["utc"+i(s)],u=e.count;switch(e.stepmode){case"backward":r=t.l2r(+l.offset(o,-u));break;case"todate":var c=l.offset(o,-u);r=t.l2r(+l.ceil(c))}return[r,a[1]]}(t,e);a[r+".range[0]"]=o[0],a[r+".range[1]"]=o[1]}return a}},97218:function(t,e,r){"use strict";t.exports={moduleType:"component",name:"rangeselector",schema:{subplots:{xaxis:{rangeselector:r(37113)}}},layoutAttributes:r(37113),handleDefaults:r(28674),draw:r(21598)}},75148:function(t,e,r){"use strict";var n=r(22399);t.exports={bgcolor:{valType:"color",dflt:n.background,editType:"plot"},bordercolor:{valType:"color",dflt:n.defaultLine,editType:"plot"},borderwidth:{valType:"integer",dflt:0,min:0,editType:"plot"},autorange:{valType:"boolean",dflt:!0,editType:"calc",impliedEdits:{"range[0]":void 0,"range[1]":void 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strict";t.exports={name:"rangeslider",containerClassName:"rangeslider-container",bgClassName:"rangeslider-bg",rangePlotClassName:"rangeslider-rangeplot",maskMinClassName:"rangeslider-mask-min",maskMaxClassName:"rangeslider-mask-max",slideBoxClassName:"rangeslider-slidebox",grabberMinClassName:"rangeslider-grabber-min",grabAreaMinClassName:"rangeslider-grabarea-min",handleMinClassName:"rangeslider-handle-min",grabberMaxClassName:"rangeslider-grabber-max",grabAreaMaxClassName:"rangeslider-grabarea-max",handleMaxClassName:"rangeslider-handle-max",maskMinOppAxisClassName:"rangeslider-mask-min-opp-axis",maskMaxOppAxisClassName:"rangeslider-mask-max-opp-axis",maskColor:"rgba(0,0,0,0.4)",maskOppAxisColor:"rgba(0,0,0,0.2)",slideBoxFill:"transparent",slideBoxCursor:"ew-resize",grabAreaFill:"transparent",grabAreaCursor:"col-resize",grabAreaWidth:10,handleWidth:4,handleRadius:1,handleStrokeWidth:1,extraPad:15}},26377:function(t,e,r){"use strict";var n=r(71828),i=r(44467),a=r(41675),o=r(75148),s=r(47850);t.exports=function(t,e,r){var l=t[r],u=e[r];if(l.rangeslider||e._requestRangeslider[u._id]){n.isPlainObject(l.rangeslider)||(l.rangeslider={});var c,f,h=l.rangeslider,p=i.newContainer(u,"rangeslider");if(_("visible")){_("bgcolor",e.plot_bgcolor),_("bordercolor"),_("borderwidth"),_("thickness"),_("autorange",!u.isValidRange(h.range)),_("range");var d=e._subplots;if(d)for(var v=d.cartesian.filter((function(t){return t.substr(0,t.indexOf("y"))===a.name2id(r)})).map((function(t){return t.substr(t.indexOf("y"),t.length)})),g=n.simpleMap(v,a.id2name),y=0;y<g.length;y++){var m=g[y];c=h[m]||{},f=i.newContainer(p,m,"yaxis");var x,b=e[m];c.range&&b.isValidRange(c.range)&&(x="fixed"),"match"!==w("rangemode",x)&&w("range",b.range.slice())}p._input=h}}function _(t,e){return n.coerce(h,p,o,t,e)}function w(t,e){return n.coerce(c,f,s,t,e)}}},72413:function(t,e,r){"use strict";var n=r(39898),i=r(73972),a=r(74875),o=r(71828),s=o.strTranslate,l=r(91424),u=r(7901),c=r(92998),f=r(93612),h=r(41675),p=r(28569),d=r(6964),v=r(73251);function g(t,e,r,n){var i=o.ensureSingle(t,"rect",v.bgClassName,(function(t){t.attr({x:0,y:0,"shape-rendering":"crispEdges"})})),a=n.borderwidth%2==0?n.borderwidth:n.borderwidth-1,c=-n._offsetShift,f=l.crispRound(e,n.borderwidth);i.attr({width:n._width+a,height:n._height+a,transform:s(c,c),"stroke-width":f}).call(u.stroke,n.bordercolor).call(u.fill,n.bgcolor)}function y(t,e,r,n){var i=e._fullLayout;o.ensureSingleById(i._topdefs,"clipPath",n._clipId,(function(t){t.append("rect").attr({x:0,y:0})})).select("rect").attr({width:n._width,height:n._height})}function m(t,e,r,i){var s,u=e.calcdata,c=t.selectAll("g."+v.rangePlotClassName).data(r._subplotsWith,o.identity);c.enter().append("g").attr("class",(function(t){return v.rangePlotClassName+" "+t})).call(l.setClipUrl,i._clipId,e),c.order(),c.exit().remove(),c.each((function(t,o){var l=n.select(this),c=0===o,p=h.getFromId(e,t,"y"),d=p._name,v=i[d],g={data:[],layout:{xaxis:{type:r.type,domain:[0,1],range:i.range.slice(),calendar:r.calendar},width:i._width,height:i._height,margin:{t:0,b:0,l:0,r:0}},_context:e._context};r.rangebreaks&&(g.layout.xaxis.rangebreaks=r.rangebreaks),g.layout[d]={type:p.type,domain:[0,1],range:"match"!==v.rangemode?v.range.slice():p.range.slice(),calendar:p.calendar},p.rangebreaks&&(g.layout[d].rangebreaks=p.rangebreaks),a.supplyDefaults(g);var y=g._fullLayout.xaxis,m=g._fullLayout[d];y.clearCalc(),y.setScale(),m.clearCalc(),m.setScale();var x={id:t,plotgroup:l,xaxis:y,yaxis:m,isRangePlot:!0};c?s=x:(x.mainplot="xy",x.mainplotinfo=s),f.rangePlot(e,x,function(t,e){for(var r=[],n=0;n<t.length;n++){var i=t[n],a=i[0].trace;a.xaxis+a.yaxis===e&&r.push(i)}return r}(u,t))}))}function x(t,e,r,n,i){o.ensureSingle(t,"rect",v.maskMinClassName,(function(t){t.attr({x:0,y:0,"shape-rendering":"crispEdges"})})).attr("height",n._height).call(u.fill,v.maskColor),o.ensureSingle(t,"rect",v.maskMaxClassName,(function(t){t.attr({y:0,"shape-rendering":"crispEdges"})})).attr("height",n._height).call(u.fill,v.maskColor),"match"!==i.rangemode&&(o.ensureSingle(t,"rect",v.maskMinOppAxisClassName,(function(t){t.attr({y:0,"shape-rendering":"crispEdges"})})).attr("width",n._width).call(u.fill,v.maskOppAxisColor),o.ensureSingle(t,"rect",v.maskMaxOppAxisClassName,(function(t){t.attr({y:0,"shape-rendering":"crispEdges"})})).attr("width",n._width).style("border-top",v.maskOppBorder).call(u.fill,v.maskOppAxisColor))}function b(t,e,r,n){e._context.staticPlot||o.ensureSingle(t,"rect",v.slideBoxClassName,(function(t){t.attr({y:0,cursor:v.slideBoxCursor,"shape-rendering":"crispEdges"})})).attr({height:n._height,fill:v.slideBoxFill})}function _(t,e,r,n){var i=o.ensureSingle(t,"g",v.grabberMinClassName),a=o.ensureSingle(t,"g",v.grabberMaxClassName),s={x:0,width:v.handleWidth,rx:v.handleRadius,fill:u.background,stroke:u.defaultLine,"stroke-width":v.handleStrokeWidth,"shape-rendering":"crispEdges"},l={y:Math.round(n._height/4),height:Math.round(n._height/2)};o.ensureSingle(i,"rect",v.handleMinClassName,(function(t){t.attr(s)})).attr(l),o.ensureSingle(a,"rect",v.handleMaxClassName,(function(t){t.attr(s)})).attr(l);var c={width:v.grabAreaWidth,x:0,y:0,fill:v.grabAreaFill,cursor:e._context.staticPlot?void 0:v.grabAreaCursor};o.ensureSingle(i,"rect",v.grabAreaMinClassName,(function(t){t.attr(c)})).attr("height",n._height),o.ensureSingle(a,"rect",v.grabAreaMaxClassName,(function(t){t.attr(c)})).attr("height",n._height)}t.exports=function(t){for(var e=t._fullLayout,r=e._rangeSliderData,a=0;a<r.length;a++){var l=r[a][v.name];l._clipId=l._id+"-"+e._uid}var u=e._infolayer.selectAll("g."+v.containerClassName).data(r,(function(t){return t._name}));u.exit().each((function(t){var r=t[v.name];e._topdefs.select("#"+r._clipId).remove()})).remove(),0!==r.length&&(u.enter().append("g").classed(v.containerClassName,!0).attr("pointer-events","all"),u.each((function(r){var a=n.select(this),l=r[v.name],u=e[h.id2name(r.anchor)],f=l[h.id2name(r.anchor)];if(l.range){var w,T=o.simpleMap(l.range,r.r2l),k=o.simpleMap(r.range,r.r2l);w=k[0]<k[1]?[Math.min(T[0],k[0]),Math.max(T[1],k[1])]:[Math.max(T[0],k[0]),Math.min(T[1],k[1])],l.range=l._input.range=o.simpleMap(w,r.l2r)}r.cleanRange("rangeslider.range");var A=e._size,M=r.domain;l._width=A.w*(M[1]-M[0]);var S=Math.round(A.l+A.w*M[0]),E=Math.round(A.t+A.h*(1-r._counterDomainMin)+("bottom"===r.side?r._depth:0)+l._offsetShift+v.extraPad);a.attr("transform",s(S,E)),l._rl=o.simpleMap(l.range,r.r2l);var L=l._rl[0],C=l._rl[1],P=C-L;if(l.p2d=function(t){return t/l._width*P+L},l.d2p=function(t){return(t-L)/P*l._width},r.rangebreaks){var O=r.locateBreaks(L,C);if(O.length){var I,D,z=0;for(I=0;I<O.length;I++)z+=(D=O[I]).max-D.min;var R=l._width/(C-L-z),F=[-R*L];for(I=0;I<O.length;I++)D=O[I],F.push(F[F.length-1]-R*(D.max-D.min));for(l.d2p=function(t){for(var e=F[0],r=0;r<O.length;r++){var n=O[r];if(t>=n.max)e=F[r+1];else if(t<n.min)break}return e+R*t},I=0;I<O.length;I++)(D=O[I]).pmin=l.d2p(D.min),D.pmax=l.d2p(D.max);l.p2d=function(t){for(var e=F[0],r=0;r<O.length;r++){var n=O[r];if(t>=n.pmax)e=F[r+1];else if(t<n.pmin)break}return(t-e)/R}}}if("match"!==f.rangemode){var B=u.r2l(f.range[0]),N=u.r2l(f.range[1])-B;l.d2pOppAxis=function(t){return(t-B)/N*l._height}}a.call(g,t,r,l).call(y,t,r,l).call(m,t,r,l).call(x,t,r,l,f).call(b,t,r,l).call(_,t,r,l),function(t,e,r,a){if(!e._context.staticPlot){var s=t.select("rect."+v.slideBoxClassName).node(),l=t.select("rect."+v.grabAreaMinClassName).node(),u=t.select("rect."+v.grabAreaMaxClassName).node();t.on("mousedown",c),t.on("touchstart",c)}function c(){var c=n.event,f=c.target,h=c.clientX||c.touches[0].clientX,v=h-t.node().getBoundingClientRect().left,g=a.d2p(r._rl[0]),y=a.d2p(r._rl[1]),m=p.coverSlip();function x(t){var c,p,x,b=+(t.clientX||t.touches[0].clientX)-h;switch(f){case s:if(x="ew-resize",g+b>r._length||y+b<0)return;c=g+b,p=y+b;break;case l:if(x="col-resize",g+b>r._length)return;c=g+b,p=y;break;case u:if(x="col-resize",y+b<0)return;c=g,p=y+b;break;default:x="ew-resize",c=v,p=v+b}if(p<c){var _=p;p=c,c=_}a._pixelMin=c,a._pixelMax=p,d(n.select(m),x),function(t,e,r,n){function a(t){return r.l2r(o.constrain(t,n._rl[0],n._rl[1]))}var s=a(n.p2d(n._pixelMin)),l=a(n.p2d(n._pixelMax));window.requestAnimationFrame((function(){i.call("_guiRelayout",e,r._name+".range",[s,l])}))}(0,e,r,a)}function b(){m.removeEventListener("mousemove",x),m.removeEventListener("mouseup",b),this.removeEventListener("touchmove",x),this.removeEventListener("touchend",b),o.removeElement(m)}this.addEventListener("touchmove",x),this.addEventListener("touchend",b),m.addEventListener("mousemove",x),m.addEventListener("mouseup",b)}}(a,t,r,l),function(t,e,r,n,i,a){var l=v.handleWidth/2;function u(t){return o.constrain(t,0,n._width)}function c(t){return o.constrain(t,0,n._height)}function f(t){return o.constrain(t,-l,n._width+l)}var h=u(n.d2p(r._rl[0])),p=u(n.d2p(r._rl[1]));if(t.select("rect."+v.slideBoxClassName).attr("x",h).attr("width",p-h),t.select("rect."+v.maskMinClassName).attr("width",h),t.select("rect."+v.maskMaxClassName).attr("x",p).attr("width",n._width-p),"match"!==a.rangemode){var d=n._height-c(n.d2pOppAxis(i._rl[1])),g=n._height-c(n.d2pOppAxis(i._rl[0]));t.select("rect."+v.maskMinOppAxisClassName).attr("x",h).attr("height",d).attr("width",p-h),t.select("rect."+v.maskMaxOppAxisClassName).attr("x",h).attr("y",g).attr("height",n._height-g).attr("width",p-h),t.select("rect."+v.slideBoxClassName).attr("y",d).attr("height",g-d)}var y=.5,m=Math.round(f(h-l))-y,x=Math.round(f(p-l))+y;t.select("g."+v.grabberMinClassName).attr("transform",s(m,y)),t.select("g."+v.grabberMaxClassName).attr("transform",s(x,y))}(a,0,r,l,u,f),"bottom"===r.side&&c.draw(t,r._id+"title",{propContainer:r,propName:r._name+".title",placeholder:e._dfltTitle.x,attributes:{x:r._offset+r._length/2,y:E+l._height+l._offsetShift+10+1.5*r.title.font.size,"text-anchor":"middle"}})})))}},549:function(t,e,r){"use strict";var n=r(41675),i=r(63893),a=r(73251),o=r(18783).LINE_SPACING,s=a.name;function l(t){var e=t&&t[s];return e&&e.visible}e.isVisible=l,e.makeData=function(t){var e=n.list({_fullLayout:t},"x",!0),r=t.margin,i=[];if(!t._has("gl2d"))for(var a=0;a<e.length;a++){var o=e[a];if(l(o)){i.push(o);var u=o[s];u._id=s+o._id,u._height=(t.height-r.b-r.t)*u.thickness,u._offsetShift=Math.floor(u.borderwidth/2)}}t._rangeSliderData=i},e.autoMarginOpts=function(t,e){var r=t._fullLayout,n=e[s],l=e._id.charAt(0),u=0,c=0;return"bottom"===e.side&&(u=e._depth,e.title.text!==r._dfltTitle[l]&&(c=1.5*e.title.font.size+10+n._offsetShift,c+=(e.title.text.match(i.BR_TAG_ALL)||[]).length*e.title.font.size*o)),{x:0,y:e._counterDomainMin,l:0,r:0,t:0,b:n._height+u+Math.max(r.margin.b,c),pad:a.extraPad+2*n._offsetShift}}},13137:function(t,e,r){"use strict";var n=r(71828),i=r(75148),a=r(47850),o=r(549);t.exports={moduleType:"component",name:"rangeslider",schema:{subplots:{xaxis:{rangeslider:n.extendFlat({},i,{yaxis:a})}}},layoutAttributes:r(75148),handleDefaults:r(26377),calcAutorange:r(88443),draw:r(72413),isVisible:o.isVisible,makeData:o.makeData,autoMarginOpts:o.autoMarginOpts}},47850:function(t){"use strict";t.exports={_isSubplotObj:!0,rangemode:{valType:"enumerated",values:["auto","fixed","match"],dflt:"match",editType:"calc"},range:{valType:"info_array",items:[{valType:"any",editType:"plot"},{valType:"any",editType:"plot"}],editType:"plot"},editType:"calc"}},8389:function(t,e,r){"use strict";var n=r(50215),i=r(82196).line,a=r(79952).P,o=r(1426).extendFlat,s=r(30962).overrideAll,l=r(44467).templatedArray;r(24695),t.exports=s(l("selection",{type:{valType:"enumerated",values:["rect","path"]},xref:o({},n.xref,{}),yref:o({},n.yref,{}),x0:{valType:"any"},x1:{valType:"any"},y0:{valType:"any"},y1:{valType:"any"},path:{valType:"string",editType:"arraydraw"},opacity:{valType:"number",min:0,max:1,dflt:.7,editType:"arraydraw"},line:{color:i.color,width:o({},i.width,{min:1,dflt:1}),dash:o({},a,{dflt:"dot"})}}),"arraydraw","from-root")},34122:function(t){"use strict";t.exports={BENDPX:1.5,MINSELECT:12,SELECTDELAY:100,SELECTID:"-select"}},59402:function(t,e,r){"use strict";var n=r(71828),i=r(89298),a=r(85501),o=r(8389),s=r(30477);function l(t,e,r){function a(r,i){return n.coerce(t,e,o,r,i)}var l=a("path"),u="path"!==a("type",l?"path":"rect");u&&delete e.path,a("opacity"),a("line.color"),a("line.width"),a("line.dash");for(var c=["x","y"],f=0;f<2;f++){var h,p,d,v=c[f],g={_fullLayout:r},y=i.coerceRef(t,e,g,v);if((h=i.getFromId(g,y))._selectionIndices.push(e._index),d=s.rangeToShapePosition(h),p=s.shapePositionToRange(h),u){var m=v+"0",x=v+"1",b=t[m],_=t[x];t[m]=p(t[m],!0),t[x]=p(t[x],!0),i.coercePosition(e,g,a,y,m),i.coercePosition(e,g,a,y,x);var w=e[m],T=e[x];void 0!==w&&void 0!==T&&(e[m]=d(w),e[x]=d(T),t[m]=b,t[x]=_)}}u&&n.noneOrAll(t,e,["x0","x1","y0","y1"])}t.exports=function(t,e){a(t,e,{name:"selections",handleItemDefaults:l});for(var r=e.selections,n=0;n<r.length;n++){var i=r[n];i&&void 0===i.path&&(void 0!==i.x0&&void 0!==i.x1&&void 0!==i.y0&&void 0!==i.y1||(e.selections[n]=null))}}},32485:function(t,e,r){"use strict";var n=r(60165).readPaths,i=r(42359),a=r(51873).clearOutlineControllers,o=r(7901),s=r(91424),l=r(44467).arrayEditor,u=r(30477),c=u.getPathString;function f(t){var e=t._fullLayout;for(var r in a(t),e._selectionLayer.selectAll("path").remove(),e._plots){var n=e._plots[r].selectionLayer;n&&n.selectAll("path").remove()}for(var i=0;i<e.selections.length;i++)p(t,i)}function h(t){return t._context.editSelection}function p(t,e){t._fullLayout._paperdiv.selectAll('.selectionlayer [data-index="'+e+'"]').remove();var r=u.makeSelectionsOptionsAndPlotinfo(t,e),a=r.options,p=r.plotinfo;a._input&&function(r){var u=c(t,a),g={"data-index":e,"fill-rule":"evenodd",d:u},y=a.opacity,m="rgba(0,0,0,0)",x=a.line.color||o.contrast(t._fullLayout.plot_bgcolor),b=a.line.width,_=a.line.dash;b||(b=5,_="solid");var w=h(t)&&t._fullLayout._activeSelectionIndex===e;w&&(m=t._fullLayout.activeselection.fillcolor,y=t._fullLayout.activeselection.opacity);for(var T=[],k=1;k>=0;k--){var A=r.append("path").attr(g).style("opacity",k?.1:y).call(o.stroke,x).call(o.fill,m).call(s.dashLine,k?"solid":_,k?4+b:b);if(d(A,t,a),w){var M=l(t.layout,"selections",a);A.style({cursor:"move"});var S={element:A.node(),plotinfo:p,gd:t,editHelpers:M,isActiveSelection:!0},E=n(u,t);i(E,A,S)}else A.style("pointer-events",k?"all":"none");T[k]=A}var L=T[0];T[1].node().addEventListener("click",(function(){return function(t,e){if(h(t)){var r=+e.node().getAttribute("data-index");if(r>=0){if(r===t._fullLayout._activeSelectionIndex)return void v(t);t._fullLayout._activeSelectionIndex=r,t._fullLayout._deactivateSelection=v,f(t)}}}(t,L)}))}(t._fullLayout._selectionLayer)}function d(t,e,r){var n=r.xref+r.yref;s.setClipUrl(t,"clip"+e._fullLayout._uid+n,e)}function v(t){h(t)&&t._fullLayout._activeSelectionIndex>=0&&(a(t),delete t._fullLayout._activeSelectionIndex,f(t))}t.exports={draw:f,drawOne:p,activateLastSelection:function(t){if(h(t)){var e=t._fullLayout.selections.length-1;t._fullLayout._activeSelectionIndex=e,t._fullLayout._deactivateSelection=v,f(t)}}}},53777:function(t,e,r){"use strict";var n=r(79952).P,i=r(1426).extendFlat;t.exports={newselection:{mode:{valType:"enumerated",values:["immediate","gradual"],dflt:"immediate",editType:"none"},line:{color:{valType:"color",editType:"none"},width:{valType:"number",min:1,dflt:1,editType:"none"},dash:i({},n,{dflt:"dot",editType:"none"}),editType:"none"},editType:"none"},activeselection:{fillcolor:{valType:"color",dflt:"rgba(0,0,0,0)",editType:"none"},opacity:{valType:"number",min:0,max:1,dflt:.5,editType:"none"},editType:"none"}}},90849:function(t){"use strict";t.exports=function(t,e,r){r("newselection.mode"),r("newselection.line.width")&&(r("newselection.line.color"),r("newselection.line.dash")),r("activeselection.fillcolor"),r("activeselection.opacity")}},35855:function(t,e,r){"use strict";var n=r(64505).selectMode,i=r(51873).clearOutline,a=r(60165),o=a.readPaths,s=a.writePaths,l=a.fixDatesForPaths;t.exports=function(t,e){if(t.length){var r=t[0][0];if(r){var a=r.getAttribute("d"),u=e.gd,c=u._fullLayout.newselection,f=e.plotinfo,h=f.xaxis,p=f.yaxis,d=e.isActiveSelection,v=e.dragmode,g=(u.layout||{}).selections||[];if(!n(v)&&void 0!==d){var y=u._fullLayout._activeSelectionIndex;if(y<g.length)switch(u._fullLayout.selections[y].type){case"rect":v="select";break;case"path":v="lasso"}}var m,x=o(a,u,f,d),b={xref:h._id,yref:p._id,opacity:c.opacity,line:{color:c.line.color,width:c.line.width,dash:c.line.dash}};1===x.length&&(m=x[0]),m&&5===m.length&&"select"===v?(b.type="rect",b.x0=m[0][1],b.y0=m[0][2],b.x1=m[2][1],b.y1=m[2][2]):(b.type="path",h&&p&&l(x,h,p),b.path=s(x),m=null),i(u);for(var _=e.editHelpers,w=(_||{}).modifyItem,T=[],k=0;k<g.length;k++){var A=u._fullLayout.selections[k];if(A){if(T[k]=A._input,void 0!==d&&k===u._fullLayout._activeSelectionIndex){var M=b;switch(A.type){case"rect":w("x0",M.x0),w("x1",M.x1),w("y0",M.y0),w("y1",M.y1);break;case"path":w("path",M.path)}}}else T[k]=A}return void 0===d?(T.push(b),T):_?_.getUpdateObj():{}}}}},75549:function(t,e,r){"use strict";var n=r(71828).strTranslate;function i(t,e){switch(t.type){case"log":return t.p2d(e);case"date":return t.p2r(e,0,t.calendar);default:return t.p2r(e)}}t.exports={p2r:i,r2p:function(t,e){switch(t.type){case"log":return t.d2p(e);case"date":return t.r2p(e,0,t.calendar);default:return t.r2p(e)}},axValue:function(t){var e="y"===t._id.charAt(0)?1:0;return function(r){return i(t,r[e])}},getTransform:function(t){return n(t.xaxis._offset,t.yaxis._offset)}}},47322:function(t,e,r){"use strict";var n=r(32485),i=r(3937);t.exports={moduleType:"component",name:"selections",layoutAttributes:r(8389),supplyLayoutDefaults:r(59402),supplyDrawNewSelectionDefaults:r(90849),includeBasePlot:r(76325)("selections"),draw:n.draw,drawOne:n.drawOne,reselect:i.reselect,prepSelect:i.prepSelect,clearOutline:i.clearOutline,clearSelectionsCache:i.clearSelectionsCache,selectOnClick:i.selectOnClick}},3937:function(t,e,r){"use strict";var n=r(52142),i=r(38258),a=r(73972),o=r(91424).dashStyle,s=r(7901),l=r(30211),u=r(23469).makeEventData,c=r(64505),f=c.freeMode,h=c.rectMode,p=c.drawMode,d=c.openMode,v=c.selectMode,g=r(30477),y=r(21459),m=r(42359),x=r(51873).clearOutline,b=r(60165),_=b.handleEllipse,w=b.readPaths,T=r(90551).newShapes,k=r(35855),A=r(32485).activateLastSelection,M=r(71828),S=M.sorterAsc,E=r(61082),L=r(79990),C=r(41675).getFromId,P=r(33306),O=r(61549).redrawReglTraces,I=r(34122),D=I.MINSELECT,z=E.filter,R=E.tester,F=r(75549),B=F.p2r,N=F.axValue,j=F.getTransform;function U(t){return void 0!==t.subplot}function V(t,e,r,n,i,a,o){var s,l,u,c,f,h,p,v,g,y=e._hoverdata,x=e._fullLayout.clickmode.indexOf("event")>-1,b=[];if(function(t){return t&&Array.isArray(t)&&!0!==t[0].hoverOnBox}(y)){Z(t,e,a);var _=function(t,e){var r,n,i=t[0],a=-1,o=[];for(n=0;n<e.length;n++)if(r=e[n],i.fullData._expandedIndex===r.cd[0].trace._expandedIndex){if(!0===i.hoverOnBox)break;void 0!==i.pointNumber?a=i.pointNumber:void 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0!==h?h:K(_)),u=function(t,e,r){return{pointNumber:t,searchInfo:e,subtract:!!r}}(_.pointNumber,_.searchInfo,p),c=G(a.selectionDefs.concat([u])),g=0;g<s.length;g++)if(f=tt(s[g]._module.selectPoints(s[g],c),s[g]),b.length)for(var w=0;w<f.length;w++)b.push(f[w]);else b=f;if($(e,s,v={points:b}),u&&a&&a.selectionDefs.push(u),o){var T=a.mergedPolygons,k=d(a.dragmode);m(et(T,k),o,a)}x&&ft(e,v)}}}function H(t){return"pointNumber"in t&&"searchInfo"in t}function q(t){return{xmin:0,xmax:0,ymin:0,ymax:0,pts:[],contains:function(e,r,n,i){var a=t.searchInfo.cd[0].trace._expandedIndex;return i.cd[0].trace._expandedIndex===a&&n===t.pointNumber},isRect:!1,degenerate:!1,subtract:!!t.subtract}}function G(t){if(t.length){for(var e=[],r=H(t[0])?0:t[0][0][0],n=r,i=H(t[0])?0:t[0][0][1],a=i,o=0;o<t.length;o++)if(H(t[o]))e.push(q(t[o]));else{var s=R(t[o]);s.subtract=!!t[o].subtract,e.push(s),r=Math.min(r,s.xmin),n=Math.max(n,s.xmax),i=Math.min(i,s.ymin),a=Math.max(a,s.ymax)}return{xmin:r,xmax:n,ymin:i,ymax:a,pts:[],contains:function(t,r,n,i){for(var a=!1,o=0;o<e.length;o++)e[o].contains(t,r,n,i)&&(a=!e[o].subtract);return a},isRect:!1,degenerate:!1}}}function Z(t,e,r){var n=e._fullLayout,i=r.plotinfo,a=r.dragmode,o=n._lastSelectedSubplot&&n._lastSelectedSubplot===i.id,s=(t.shiftKey||t.altKey)&&!(p(a)&&d(a));o&&s&&i.selection&&i.selection.selectionDefs&&!r.selectionDefs?(r.selectionDefs=i.selection.selectionDefs,r.mergedPolygons=i.selection.mergedPolygons):s&&i.selection||Y(r),o||(x(e),n._lastSelectedSubplot=i.id)}function Y(t,e){var r=t.dragmode,n=t.plotinfo,i=t.gd;(function(t){return t._fullLayout._activeShapeIndex>=0})(i)&&i._fullLayout._deactivateShape(i),function(t){return t._fullLayout._activeSelectionIndex>=0}(i)&&i._fullLayout._deactivateSelection(i);var o=i._fullLayout._zoomlayer,s=p(r),l=v(r);if(s||l){var u,c,f=o.selectAll(".select-outline-"+n.id);f&&i._fullLayout._outlining&&(s&&(u=T(f,t)),u&&a.call("_guiRelayout",i,{shapes:u}),l&&!U(t)&&(c=k(f,t)),c&&(i._fullLayout._noEmitSelectedAtStart=!0,a.call("_guiRelayout",i,{selections:c}).then((function(){e&&A(i)}))),i._fullLayout._outlining=!1)}n.selection={},n.selection.selectionDefs=t.selectionDefs=[],n.selection.mergedPolygons=t.mergedPolygons=[]}function W(t){return t._id}function X(t,e,r,n){if(!t.calcdata)return[];var i,a,o,s=[],l=e.map(W),u=r.map(W);for(o=0;o<t.calcdata.length;o++)if(!0===(a=(i=t.calcdata[o])[0].trace).visible&&a._module&&a._module.selectPoints)if(!U({subplot:n})||a.subplot!==n&&a.geo!==n)if("splom"===a.type){if(a._xaxes[l[0]]&&a._yaxes[u[0]]){var c=J(a._module,i,e[0],r[0]);c.scene=t._fullLayout._splomScenes[a.uid],s.push(c)}}else if("sankey"===a.type){var f=J(a._module,i,e[0],r[0]);s.push(f)}else{if(-1===l.indexOf(a.xaxis))continue;if(-1===u.indexOf(a.yaxis))continue;s.push(J(a._module,i,C(t,a.xaxis),C(t,a.yaxis)))}else s.push(J(a._module,i,e[0],r[0]));return s}function J(t,e,r,n){return{_module:t,cd:e,xaxis:r,yaxis:n}}function K(t){var e=t.searchInfo.cd[0].trace,r=t.pointNumber,n=t.pointNumbers,i=n.length>0?n[0]:r;return!!e.selectedpoints&&e.selectedpoints.indexOf(i)>-1}function $(t,e,r){var n,i;for(n=0;n<e.length;n++){var o=e[n].cd[0].trace._fullInput,s=t._fullLayout._tracePreGUI[o.uid]||{};void 0===s.selectedpoints&&(s.selectedpoints=o._input.selectedpoints||null)}if(r){var l=r.points||[];for(n=0;n<e.length;n++)(i=e[n].cd[0].trace)._input.selectedpoints=i._fullInput.selectedpoints=[],i._fullInput!==i&&(i.selectedpoints=[]);for(var u=0;u<l.length;u++){var c=l[u],f=c.data,h=c.fullData,p=c.pointIndex,d=c.pointIndices;d?([].push.apply(f.selectedpoints,d),i._fullInput!==i&&[].push.apply(h.selectedpoints,d)):(f.selectedpoints.push(p),i._fullInput!==i&&h.selectedpoints.push(p))}}else for(n=0;n<e.length;n++)delete(i=e[n].cd[0].trace).selectedpoints,delete i._input.selectedpoints,i._fullInput!==i&&delete i._fullInput.selectedpoints;!function(t,e){for(var r=!1,n=0;n<e.length;n++){var i=e[n],o=i.cd;a.traceIs(o[0].trace,"regl")&&(r=!0);var s=i._module,l=s.styleOnSelect||s.style;l&&(l(t,o,o[0].node3),o[0].nodeRangePlot3&&l(t,o,o[0].nodeRangePlot3))}r&&(P(t),O(t))}(t,e)}function Q(t,e,r){for(var i=(r?n.difference:n.union)({regions:t},{regions:[e]}).regions.reverse(),a=0;a<i.length;a++){var o=i[a];o.subtract=st(o,i.slice(0,a))}return i}function tt(t,e){if(Array.isArray(t))for(var r=e.cd,n=e.cd[0].trace,i=0;i<t.length;i++)t[i]=u(t[i],n,r);return t}function et(t,e){for(var r=[],n=0;n<t.length;n++){r[n]=[];for(var 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a=i[n.uid];a&&(a.selectBatch=[])}}}(t);for(var O={},I=0;I<P.length;I++){var D=P[I],z=D.indexOf("y"),R=D.slice(0,z),F=D.slice(z),B=o&&s?r:void 0;if(B=at(f,R,F,B)){var N=n;if(!l){var j=C(t,R,"x"),U=C(t,F,"y");N=X(t,[j],[U],D);for(var V=0;V<N.length;V++){var H=N[V],q=H.cd[0],G=q.trace;if("scattergl"===H._module.name&&!q.t.xpx){var Z=G.x,Y=G.y,W=G._length;q.t.xpx=[],q.t.ypx=[];for(var J=0;J<W;J++)q.t.xpx[J]=j.c2p(Z[J]),q.t.ypx[J]=U.c2p(Y[J])}"splom"===H._module.name&&(O[G.uid]||(O[G.uid]=!0))}}var K=rt(B,N);u=u.concat(K),c=c.concat(N)}}var Q={points:u};$(t,c,Q);var tt=h.clickmode.indexOf("event")>-1&&e;if(!a&&e){var et=ot(t,!0);if(et.length){var nt=et[0].xref,pt=et[0].yref;if(nt&&pt){var dt=ut(et);ct([C(t,nt,"x"),C(t,pt,"y")])(Q,dt)}}t._fullLayout._noEmitSelectedAtStart?t._fullLayout._noEmitSelectedAtStart=!1:tt&&ft(t,Q),h._reselect=!1}if(!a&&h._deselect){var vt=h._deselect;(function(t,e,r){for(var n=0;n<r.length;n++){var 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u=!U(n),c=f(i),g=h(i),y=d(i),x=p(i),b=v(i),w="drawcircle"===i,T="drawline"===i||w,k=n.gd,A=k._fullLayout,S=b&&"immediate"===A.newselection.mode&&u,E=A._zoomlayer,C=n.element.getBoundingClientRect(),P=n.plotinfo,O=j(P),F=e-C.left,B=r-C.top;A._calcInverseTransform(k);var N=M.apply3DTransform(A._invTransform)(F,B);F=N[0],B=N[1];var H,q,W,J,K,tt,at,ot=A._invScaleX,st=A._invScaleY,lt=F,pt=B,dt="M"+F+","+B,vt=n.xaxes[0],gt=n.yaxes[0],yt=vt._length,mt=gt._length,xt=t.altKey&&!(p(i)&&y);Z(t,k,n),c&&(H=z([[F,B]],I.BENDPX));var bt=E.selectAll("path.select-outline-"+P.id).data([1]),_t=x?A.newshape:A.newselection;x&&(n.hasText=_t.label.text||_t.label.texttemplate);var wt=x&&!y?_t.fillcolor:"rgba(0,0,0,0)",Tt=_t.line.color||(u?s.contrast(k._fullLayout.plot_bgcolor):"#7f7f7f");bt.enter().append("path").attr("class","select-outline 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C=n[s][1],P=n[l][1],O=n[u][1],I=n[c][1],D=n[s][2],z=n[l][2],R=n[u][2],F=n[c][2],B=y.xaxis&&("date"===y.xaxis.type||"log"===y.xaxis.type),N=y.yaxis&&("date"===y.yaxis.type||"log"===y.yaxis.type);B&&(C=v(y.xaxis,C),P=v(y.xaxis,P),O=v(y.xaxis,O),I=v(y.xaxis,I)),N&&(D=v(y.yaxis,D),z=v(y.yaxis,z),R=v(y.yaxis,R),F=v(y.yaxis,F));var j=(P+I)/2,U=(D+R)/2,V=b({x0:j,y0:U,x1:j+(I-P+O-C)/2*f,y1:U+(F-z+R-D)/2*h});B&&(V.x0=d(y.xaxis,V.x0),V.x1=d(y.xaxis,V.x1)),N&&(V.y0=d(y.yaxis,V.y0),V.y1=d(y.yaxis,V.y1)),L.x0=V.x0,L.y0=V.y0,L.x1=V.x1,L.y1=V.y1}else L.type="path",T&&k&&_(E,T,k),L.path=x(E),n=null;return L}t.exports={newShapes:function(t,e){if(t.length&&t[0][0]){var r=e.gd,n=e.isActiveShape,a=e.dragmode,o=(r.layout||{}).shapes||[];if(!i(a)&&void 0!==n){var s=r._fullLayout._activeShapeIndex;if(s<o.length)switch(r._fullLayout.shapes[s].type){case"rect":a="drawrect";break;case"circle":a="drawcircle";break;case"line":a="drawline";break;case"path":var l=o[s].path||"";a="Z"===l[l.length-1]?"drawclosedpath":"drawopenpath"}}var u=w(t,e,a);g(r);for(var c=e.editHelpers,f=(c||{}).modifyItem,h=[],p=0;p<o.length;p++){var d=r._fullLayout.shapes[p];if(h[p]=d._input,void 0!==n&&p===r._fullLayout._activeShapeIndex){var v=u;switch(d.type){case"line":case"rect":case"circle":f("x0",v.x0),f("x1",v.x1),f("y0",v.y0),f("y1",v.y1);break;case"path":f("path",v.path)}}}return void 0===n?(h.push(u),h):c?c.getUpdateObj():{}}},createShapeObj:w}},51873:function(t){"use strict";t.exports={clearOutlineControllers:function(t){var e=t._fullLayout._zoomlayer;e&&e.selectAll(".outline-controllers").remove()},clearOutline:function(t){var e=t._fullLayout._zoomlayer;e&&e.selectAll(".select-outline").remove(),t._fullLayout._outlining=!1}}},30477:function(t,e,r){"use strict";var n=r(21459),i=r(71828),a=r(89298);e.rangeToShapePosition=function(t){return"log"===t.type?t.r2d:function(t){return 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s=e.rangeToShapePosition(r);a=function(t){return s(r.p2r(t-r._offset))}}else a=n?function(t){return 1-(t-o.t)/o.h}:function(t){return(t-o.l)/o.w};return a},e.roundPositionForSharpStrokeRendering=function(t,e){var r=1===Math.round(e%2),n=Math.round(t);return r?n+.5:n},e.makeShapesOptionsAndPlotinfo=function(t,e){var r=t._fullLayout.shapes[e]||{},n=t._fullLayout._plots[r.xref+r.yref];return n?n._hadPlotinfo=!0:(n={},r.xref&&"paper"!==r.xref&&(n.xaxis=t._fullLayout[r.xref+"axis"]),r.yref&&"paper"!==r.yref&&(n.yaxis=t._fullLayout[r.yref+"axis"])),n.xsizemode=r.xsizemode,n.ysizemode=r.ysizemode,n.xanchor=r.xanchor,n.yanchor=r.yanchor,{options:r,plotinfo:n}},e.makeSelectionsOptionsAndPlotinfo=function(t,e){var r=t._fullLayout.selections[e]||{},n=t._fullLayout._plots[r.xref+r.yref];return n?n._hadPlotinfo=!0:(n={},r.xref&&(n.xaxis=t._fullLayout[r.xref+"axis"]),r.yref&&(n.yaxis=t._fullLayout[r.yref+"axis"])),{options:r,plotinfo:n}},e.getPathString=function(t,r){var o,s,l,u,c,f,h,p,d=r.type,v=a.getRefType(r.xref),g=a.getRefType(r.yref),y=a.getFromId(t,r.xref),m=a.getFromId(t,r.yref),x=t._fullLayout._size;if(y?"domain"===v?s=function(t){return y._offset+y._length*t}:(o=e.shapePositionToRange(y),s=function(t){return y._offset+y.r2p(o(t,!0))}):s=function(t){return x.l+x.w*t},m?"domain"===g?u=function(t){return m._offset+m._length*(1-t)}:(l=e.shapePositionToRange(m),u=function(t){return m._offset+m.r2p(l(t,!0))}):u=function(t){return x.t+x.h*(1-t)},"path"===d)return y&&"date"===y.type&&(s=e.decodeDate(s)),m&&"date"===m.type&&(u=e.decodeDate(u)),function(t,e,r){var a=t.path,o=t.xsizemode,s=t.ysizemode,l=t.xanchor,u=t.yanchor;return a.replace(n.segmentRE,(function(t){var a=0,c=t.charAt(0),f=n.paramIsX[c],h=n.paramIsY[c],p=n.numParams[c],d=t.substr(1).replace(n.paramRE,(function(t){return f[a]?t="pixel"===o?e(l)+Number(t):e(t):h[a]&&(t="pixel"===s?r(u)-Number(t):r(t)),++a>p&&(t="X"),t}));return a>p&&(d=d.replace(/[\s,]*X.*/,""),i.log("Ignoring extra 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t.x1},y0:function(t){return t.y0},y1:function(t){return t.y1},slope:function(t,e,r){return"line"!==t.type?void 0:i(t,0,r)/n(t,e)},dx:n,dy:i,width:function(t,e){return Math.abs(n(t,e))},height:function(t,e,r){return Math.abs(i(t,0,r))},length:function(t,e,r){return"line"!==t.type?void 0:Math.sqrt(Math.pow(n(t,e),2)+Math.pow(i(t,0,r),2))},xcenter:function(t,n){return r((e(t.x1,n)+e(t.x0,n))/2,n)},ycenter:function(t,n,i){return r((e(t.y1,i)+e(t.y0,i))/2,i)}}},75067:function(t,e,r){"use strict";var n=r(41940),i=r(35025),a=r(1426).extendDeepAll,o=r(30962).overrideAll,s=r(85594),l=r(44467).templatedArray,u=r(98292),c=l("step",{visible:{valType:"boolean",dflt:!0},method:{valType:"enumerated",values:["restyle","relayout","animate","update","skip"],dflt:"restyle"},args:{valType:"info_array",freeLength:!0,items:[{valType:"any"},{valType:"any"},{valType:"any"}]},label:{valType:"string"},value:{valType:"string"},execute:{valType:"boolean",dflt:!0}});t.exports=o(l("slider",{visible:{valType:"boolean",dflt:!0},active:{valType:"number",min:0,dflt:0},steps:c,lenmode:{valType:"enumerated",values:["fraction","pixels"],dflt:"fraction"},len:{valType:"number",min:0,dflt:1},x:{valType:"number",min:-2,max:3,dflt:0},pad:a(i({editType:"arraydraw"}),{},{t:{dflt:20}}),xanchor:{valType:"enumerated",values:["auto","left","center","right"],dflt:"left"},y:{valType:"number",min:-2,max:3,dflt:0},yanchor:{valType:"enumerated",values:["auto","top","middle","bottom"],dflt:"top"},transition:{duration:{valType:"number",min:0,dflt:150},easing:{valType:"enumerated",values:s.transition.easing.values,dflt:"cubic-in-out"}},currentvalue:{visible:{valType:"boolean",dflt:!0},xanchor:{valType:"enumerated",values:["left","center","right"],dflt:"left"},offset:{valType:"number",dflt:10},prefix:{valType:"string"},suffix:{valType:"string"},font:n({})},font:n({}),activebgcolor:{valType:"color",dflt:u.gripBgActiveColor},bgcolor:{valType:"color",dflt:u.railBgColor},bordercolor:{valType:"color",dflt:u.railBorderColor},borderwidth:{valType:"number",min:0,dflt:u.railBorderWidth},ticklen:{valType:"number",min:0,dflt:u.tickLength},tickcolor:{valType:"color",dflt:u.tickColor},tickwidth:{valType:"number",min:0,dflt:1},minorticklen:{valType:"number",min:0,dflt:u.minorTickLength}}),"arraydraw","from-root")},98292:function(t){"use strict";t.exports={name:"sliders",containerClassName:"slider-container",groupClassName:"slider-group",inputAreaClass:"slider-input-area",railRectClass:"slider-rail-rect",railTouchRectClass:"slider-rail-touch-rect",gripRectClass:"slider-grip-rect",tickRectClass:"slider-tick-rect",inputProxyClass:"slider-input-proxy",labelsClass:"slider-labels",labelGroupClass:"slider-label-group",labelClass:"slider-label",currentValueClass:"slider-current-value",railHeight:5,menuIndexAttrName:"slider-active-index",autoMarginIdRoot:"slider-",minWidth:30,minHeight:30,textPadX:40,arrowOffsetX:4,railRadius:2,railWidth:5,railBorder:4,railBorderWidth:1,railBorderColor:"#bec8d9",railBgColor:"#f8fafc",railInset:8,stepInset:10,gripRadius:10,gripWidth:20,gripHeight:20,gripBorder:20,gripBorderWidth:1,gripBorderColor:"#bec8d9",gripBgColor:"#f6f8fa",gripBgActiveColor:"#dbdde0",labelPadding:8,labelOffset:0,tickWidth:1,tickColor:"#333",tickOffset:25,tickLength:7,minorTickOffset:25,minorTickColor:"#333",minorTickLength:4,currentValuePadding:8,currentValueInset:0}},12343:function(t,e,r){"use 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h=t._fullLayout._size;c.lx=h.l+h.w*e.x,c.ly=h.t+h.h*(1-e.y),"fraction"===e.lenmode?c.outerLength=Math.round(h.w*e.len):c.outerLength=e.len,c.inputAreaStart=0,c.inputAreaLength=Math.round(c.outerLength-e.pad.l-e.pad.r);var p=(c.inputAreaLength-2*f.stepInset)/(e._stepCount-1),y=a+f.labelPadding;if(c.labelStride=Math.max(1,Math.ceil(y/p)),c.labelHeight=l,c.currentValueMaxWidth=0,c.currentValueHeight=0,c.currentValueTotalHeight=0,c.currentValueMaxLines=1,e.currentvalue.visible){var m=o.tester.append("g");r.each((function(t){var r=x(m,e,t.label),n=r.node()&&o.bBox(r.node())||{width:0,height:0},i=u.lineCount(r);c.currentValueMaxWidth=Math.max(c.currentValueMaxWidth,Math.ceil(n.width)),c.currentValueHeight=Math.max(c.currentValueHeight,Math.ceil(n.height)),c.currentValueMaxLines=Math.max(c.currentValueMaxLines,i)})),c.currentValueTotalHeight=c.currentValueHeight+e.currentvalue.offset,m.remove()}c.height=c.currentValueTotalHeight+f.tickOffset+e.ticklen+f.labelOffset+c.labelHeight+e.pad.t+e.pad.b;var b="left";s.isRightAnchor(e)&&(c.lx-=c.outerLength,b="right"),s.isCenterAnchor(e)&&(c.lx-=c.outerLength/2,b="center");var w="top";s.isBottomAnchor(e)&&(c.ly-=c.height,w="bottom"),s.isMiddleAnchor(e)&&(c.ly-=c.height/2,w="middle"),c.outerLength=Math.ceil(c.outerLength),c.height=Math.ceil(c.height),c.lx=Math.round(c.lx),c.ly=Math.round(c.ly);var T={y:e.y,b:c.height*v[w],t:c.height*d[w]};"fraction"===e.lenmode?(T.l=0,T.xl=e.x-e.len*d[b],T.r=0,T.xr=e.x+e.len*v[b]):(T.x=e.x,T.l=c.outerLength*d[b],T.r=c.outerLength*v[b]),i.autoMargin(t,g(e),T)}function x(t,e,r){if(e.currentvalue.visible){var n,i,a=e._dims;switch(e.currentvalue.xanchor){case"right":n=a.inputAreaLength-f.currentValueInset-a.currentValueMaxWidth,i="left";break;case"center":n=.5*a.inputAreaLength,i="middle";break;default:n=f.currentValueInset,i="left"}var l=s.ensureSingle(t,"text",f.labelClass,(function(t){t.attr({"text-anchor":i,"data-notex":1})})),c=e.currentvalue.prefix?e.currentvalue.prefix:"";if("string"==typeof r)c+=r;else{var h=e.steps[e.active].label,d=e._gd._fullLayout._meta;d&&(h=s.templateString(h,d)),c+=h}e.currentvalue.suffix&&(c+=e.currentvalue.suffix),l.call(o.font,e.currentvalue.font).text(c).call(u.convertToTspans,e._gd);var v=u.lineCount(l),g=(a.currentValueMaxLines+1-v)*e.currentvalue.font.size*p;return u.positionText(l,n,g),l}}function 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if(n=new t.constructor(r),i=new t.constructor(t.length+e.length-r),r===e.length)n.set(e),i.set(t);else if(r<e.length){var l=e.length-r;n.set(e.subarray(l)),i.set(t),i.set(e.subarray(0,l),t.length)}else{var u=r-e.length,c=t.length-u;n.set(t.subarray(c)),n.set(e,u),i.set(t.subarray(0,c))}else n=t.concat(e),i=r>=0&&r<n.length?n.splice(0,n.length-r):[];return[n,i]})),l=e.redraw(r),c=[r,s.update,i,s.maxPoints];return u.add(r,e.prependTraces,c,t,arguments),l},e.moveTraces=function t(r,n,i){var a,s=[],l=[],c=t,f=t,h=[r=o.getGraphDiv(r),i,n],p=[r,n,i];if(O(r,n,i),n=Array.isArray(n)?n:[n],void 0===i)for(i=[],a=0;a<n.length;a++)i.push(-n.length+a);for(i=Array.isArray(i)?i:[i],n=C(n,r.data.length-1),i=C(i,r.data.length-1),a=0;a<r.data.length;a++)-1===n.indexOf(a)&&s.push(r.data[a]);for(a=0;a<n.length;a++)l.push({newIndex:i[a],trace:r.data[n[a]]});for(l.sort((function(t,e){return t.newIndex-e.newIndex})),a=0;a<l.length;a+=1)s.splice(l[a].newIndex,0,l[a].trace);r.data=s;var d=e.redraw(r);return u.add(r,c,h,f,p),d},e.prependTraces=function t(r,n,i,a){var s=I(r=o.getGraphDiv(r),n,i,a,(function(t,e,r){var n,i;if(o.isTypedArray(t))if(r<=0){var a=new t.constructor(0),s=D(e,t);r<0?(n=s,i=a):(n=a,i=s)}else if(n=new t.constructor(r),i=new t.constructor(t.length+e.length-r),r===e.length)n.set(e),i.set(t);else if(r<e.length){var l=e.length-r;n.set(e.subarray(0,l)),i.set(e.subarray(l)),i.set(t,l)}else{var u=r-e.length;n.set(e),n.set(t.subarray(0,u),e.length),i.set(t.subarray(u))}else n=e.concat(t),i=r>=0&&r<n.length?n.splice(r,n.length):[];return[n,i]})),l=e.redraw(r),c=[r,s.update,i,s.maxPoints];return u.add(r,e.extendTraces,c,t,arguments),l},e.newPlot=function(t,r,n,i){return t=o.getGraphDiv(t),h.cleanPlot([],{},t._fullData||[],t._fullLayout||{}),h.purge(t),e._doPlot(t,r,n,i)},e._doPlot=function(t,r,i,a){var s;if(t=o.getGraphDiv(t),l.init(t),o.isPlainObject(r)){var u=r;r=u.data,i=u.layout,a=u.config,s=u.frames}if(!1===l.triggerHandler(t,"plotly_beforeplot",[r,i,a]))return Promise.reject();r||i||o.isPlotDiv(t)||o.warn("Calling _doPlot as if redrawing but this container doesn't yet have a plot.",t),L(t,a),i||(i={}),n.select(t).classed("js-plotly-plot",!0),d.makeTester(),Array.isArray(t._promises)||(t._promises=[]);var f=0===(t.data||[]).length&&Array.isArray(r);Array.isArray(r)&&(_.cleanData(r),f?t.data=r:t.data.push.apply(t.data,r),t.empty=!1),t.layout&&!f||(t.layout=_.cleanLayout(i)),h.supplyDefaults(t);var v=t._fullLayout,m=v._has("cartesian");v._replotting=!0,(f||v._shouldCreateBgLayer)&&(function(t){var e=n.select(t),r=t._fullLayout;if(r._calcInverseTransform=ot,r._calcInverseTransform(t),r._container=e.selectAll(".plot-container").data([0]),r._container.enter().insert("div",":first-child").classed("plot-container",!0).classed("plotly",!0),r._paperdiv=r._container.selectAll(".svg-container").data([0]),r._paperdiv.enter().append("div").classed("user-select-none",!0).classed("svg-container",!0).style("position","relative"),r._glcontainer=r._paperdiv.selectAll(".gl-container").data([{}]),r._glcontainer.enter().append("div").classed("gl-container",!0),r._paperdiv.selectAll(".main-svg").remove(),r._paperdiv.select(".modebar-container").remove(),r._paper=r._paperdiv.insert("svg",":first-child").classed("main-svg",!0),r._toppaper=r._paperdiv.append("svg").classed("main-svg",!0),r._modebardiv=r._paperdiv.append("div"),delete r._modeBar,r._hoverpaper=r._paperdiv.append("svg").classed("main-svg",!0),!r._uid){var i={};n.selectAll("defs").each((function(){this.id&&(i[this.id.split("-")[1]]=1)})),r._uid=o.randstr(i)}r._paperdiv.selectAll(".main-svg").attr(y.svgAttrs),r._defs=r._paper.append("defs").attr("id","defs-"+r._uid),r._clips=r._defs.append("g").classed("clips",!0),r._topdefs=r._toppaper.append("defs").attr("id","topdefs-"+r._uid),r._topclips=r._topdefs.append("g").classed("clips",!0),r._bgLayer=r._paper.append("g").classed("bglayer",!0),r._draggers=r._paper.append("g").classed("draglayer",!0);var a=r._paper.append("g").classed("layer-below",!0);r._imageLowerLayer=a.append("g").classed("imagelayer",!0),r._shapeLowerLayer=a.append("g").classed("shapelayer",!0),r._cartesianlayer=r._paper.append("g").classed("cartesianlayer",!0),r._polarlayer=r._paper.append("g").classed("polarlayer",!0),r._smithlayer=r._paper.append("g").classed("smithlayer",!0),r._ternarylayer=r._paper.append("g").classed("ternarylayer",!0),r._geolayer=r._paper.append("g").classed("geolayer",!0),r._funnelarealayer=r._paper.append("g").classed("funnelarealayer",!0),r._pielayer=r._paper.append("g").classed("pielayer",!0),r._iciclelayer=r._paper.append("g").classed("iciclelayer",!0),r._treemaplayer=r._paper.append("g").classed("treemaplayer",!0),r._sunburstlayer=r._paper.append("g").classed("sunburstlayer",!0),r._indicatorlayer=r._toppaper.append("g").classed("indicatorlayer",!0),r._glimages=r._paper.append("g").classed("glimages",!0);var s=r._toppaper.append("g").classed("layer-above",!0);r._imageUpperLayer=s.append("g").classed("imagelayer",!0),r._shapeUpperLayer=s.append("g").classed("shapelayer",!0),r._selectionLayer=r._toppaper.append("g").classed("selectionlayer",!0),r._infolayer=r._toppaper.append("g").classed("infolayer",!0),r._menulayer=r._toppaper.append("g").classed("menulayer",!0),r._zoomlayer=r._toppaper.append("g").classed("zoomlayer",!0),r._hoverlayer=r._hoverpaper.append("g").classed("hoverlayer",!0),r._modebardiv.classed("modebar-container",!0).style("position","absolute").style("top","0px").style("right","0px"),t.emit("plotly_framework")}(t),v._shouldCreateBgLayer&&delete v._shouldCreateBgLayer),d.initGradients(t),d.initPatterns(t),f&&p.saveShowSpikeInitial(t);var x=!t.calcdata||t.calcdata.length!==(t._fullData||[]).length;x&&h.doCalcdata(t);for(var b=0;b<t.calcdata.length;b++)t.calcdata[b][0].trace=t._fullData[b];t._context.responsive?t._responsiveChartHandler||(t._responsiveChartHandler=function(){o.isHidden(t)||h.resize(t)},window.addEventListener("resize",t._responsiveChartHandler)):o.clearResponsive(t);var T=o.extendFlat({},v._size),k=0;function A(){if(h.clearAutoMarginIds(t),w.drawMarginPushers(t),p.allowAutoMargin(t),t._fullLayout.title.text&&t._fullLayout.title.automargin&&h.allowAutoMargin(t,"title.automargin"),v._has("pie"))for(var e=t._fullData,r=0;r<e.length;r++){var n=e[r];"pie"===n.type&&n.automargin&&h.allowAutoMargin(t,"pie."+n.uid+".automargin")}return h.doAutoMargin(t),h.previousPromises(t)}function S(){t._transitioning||(w.doAutoRangeAndConstraints(t),f&&p.saveRangeInitial(t),c.getComponentMethod("rangeslider","calcAutorange")(t))}var E=[h.previousPromises,function(){if(s)return e.addFrames(t,s)},function e(){for(var r=v._basePlotModules,n=0;n<r.length;n++)r[n].drawFramework&&r[n].drawFramework(t);!v._glcanvas&&v._has("gl")&&(v._glcanvas=v._glcontainer.selectAll(".gl-canvas").data([{key:"contextLayer",context:!0,pick:!1},{key:"focusLayer",context:!1,pick:!1},{key:"pickLayer",context:!1,pick:!0}],(function(t){return t.key})),v._glcanvas.enter().append("canvas").attr("class",(function(t){return"gl-canvas gl-canvas-"+t.key.replace("Layer","")})).style({position:"absolute",top:0,left:0,overflow:"visible","pointer-events":"none"}));var i=t._context.plotGlPixelRatio;if(v._glcanvas){v._glcanvas.attr("width",v.width*i).attr("height",v.height*i).style("width",v.width+"px").style("height",v.height+"px");var a=v._glcanvas.data()[0].regl;if(a&&(Math.floor(v.width*i)!==a._gl.drawingBufferWidth||Math.floor(v.height*i)!==a._gl.drawingBufferHeight)){var s="WebGL context buffer and canvas dimensions do not match due to browser/WebGL bug.";if(!k)return o.log(s+" Clearing graph and plotting 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C=o.syncOrAsync(E,t);return C&&C.then||(C=Promise.resolve()),C.then((function(){return M(t),t}))},e.purge=function(t){var e=(t=o.getGraphDiv(t))._fullLayout||{},r=t._fullData||[];return h.cleanPlot([],{},r,e),h.purge(t),l.purge(t),e._container&&e._container.remove(),delete t._context,t},e.react=function(t,r,n,i){var a,l;t=o.getGraphDiv(t),_.clearPromiseQueue(t);var u=t._fullData,p=t._fullLayout;if(o.isPlotDiv(t)&&u&&p){if(o.isPlainObject(r)){var d=r;r=d.data,n=d.layout,i=d.config,a=d.frames}var v=!1;if(i){var g=o.extendDeep({},t._context);t._context=void 0,L(t,i),v=at(g,t._context)}t.data=r||[],_.cleanData(t.data),t.layout=n||{},_.cleanLayout(t.layout),function(t,e,r,n){var i,a,l,u,c,f,h,p,d,v,g=n._preGUI,y=[],m={},x={};for(i in g){if(c=Q(i,K)){if(d=c.head,v=c.tail,a=c.attr||d+".uirevision",(u=(l=s(n,a).get())&&tt(a,e))&&u===l){if(null===(f=g[i])&&(f=void 0),nt(p=(h=s(e,i)).get(),f)){void 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"+i+" in trace uid "+E);delete C[i]}}}(t.data,t.layout,u,p),h.supplyDefaults(t,{skipUpdateCalc:!0});var y=t._fullData,m=t._fullLayout,x=void 0===m.datarevision,b=m.transition,k=function(t,e,r,n,i){var a=T.layoutFlags();return a.arrays={},a.rangesAltered={},a.nChanges=0,a.nChangesAnim=0,it(e,r,[],{getValObject:function(t){return f.getLayoutValObject(r,t)},flags:a,immutable:n,transition:i,gd:t}),(a.plot||a.calc)&&(a.layoutReplot=!0),i&&a.nChanges&&a.nChangesAnim&&(a.anim=a.nChanges===a.nChangesAnim?"all":"some"),a}(t,p,m,x,b),A=k.newDataRevision,S=function(t,e,r,n,i,a){var o=e.length===r.length;if(!i&&!o)return{fullReplot:!0,calc:!0};var s,l,u=T.traceFlags();u.arrays={},u.nChanges=0,u.nChangesAnim=0;var c={getValObject:function(t){var e=f.getTraceValObject(l,t);return!l._module.animatable&&e.anim&&(e.anim=!1),e},flags:u,immutable:n,transition:i,newDataRevision:a,gd:t},p={};for(s=0;s<e.length;s++)if(r[s]){if(l=r[s]._fullInput,h.hasMakesDataTransform(l)&&(l=r[s]),p[l.uid])continue;p[l.uid]=1,it(e[s]._fullInput,l,[],c)}return(u.calc||u.plot)&&(u.fullReplot=!0),i&&u.nChanges&&u.nChangesAnim&&(u.anim=u.nChanges===u.nChangesAnim&&o?"all":"some"),u}(t,u,y,x,b,A);if(W(t)&&(k.layoutReplot=!0),S.calc||k.calc){t.calcdata=void 0;for(var E=Object.getOwnPropertyNames(m),C=0;C<E.length;C++){var P=E[C],O=P.substring(0,5);if("xaxis"===O||"yaxis"===O){var I=m[P]._emptyCategories;I&&I()}}}else h.supplyDefaultsUpdateCalc(t.calcdata,y);var D=[];if(a&&(t._transitionData={},h.createTransitionData(t),D.push((function(){return e.addFrames(t,a)}))),m.transition&&!v&&(S.anim||k.anim))k.ticks&&D.push(w.doTicksRelayout),h.doCalcdata(t),w.doAutoRangeAndConstraints(t),D.push((function(){return h.transitionFromReact(t,S,k,p)}));else if(S.fullReplot||k.layoutReplot||v)t._fullLayout._skipDefaults=!0,D.push(e._doPlot);else{for(var z in k.arrays){var F=k.arrays[z];if(F.length){var B=c.getComponentMethod(z,"drawOne");if(B!==o.noop)for(var N=0;N<F.length;N++)B(t,F[N]);else{var j=c.getComponentMethod(z,"draw");if(j===o.noop)throw new Error("cannot draw components: "+z);j(t)}}}D.push(h.previousPromises),S.style&&D.push(w.doTraceStyle),(S.colorbars||k.colorbars)&&D.push(w.doColorBars),k.legend&&D.push(w.doLegend),k.layoutstyle&&D.push(w.layoutStyles),k.axrange&&H(D),k.ticks&&D.push(w.doTicksRelayout),k.modebar&&D.push(w.doModeBar),k.camera&&D.push(w.doCamera),D.push(M)}D.push(h.rehover,h.redrag,h.reselect),(l=o.syncOrAsync(D,t))&&l.then||(l=Promise.resolve(t))}else l=e.newPlot(t,r,n,i);return l.then((function(){return t.emit("plotly_react",{data:r,layout:n}),t}))},e.redraw=function(t){if(t=o.getGraphDiv(t),!o.isPlotDiv(t))throw new Error("This element is not a Plotly plot: "+t);return _.cleanData(t.data),_.cleanLayout(t.layout),t.calcdata=void 0,e._doPlot(t).then((function(){return t.emit("plotly_redraw"),t}))},e.relayout=U,e.restyle=z,e.setPlotConfig=function(t){return o.extendFlat(x,t)},e.update=X,e._guiRelayout=J(U),e._guiRestyle=J(z),e._guiUpdate=J(X),e._storeDirectGUIEdit=function(t,e,r){for(var n in r)B(n,s(t,n).get(),r[n],e)}},72075:function(t){"use strict";var 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L=(v+.5)/84;e.maskBreaks(i*(1-L)+L*p)!==O&&d++}(h*=d/84)||(t[n].drop=!0),s&&c>A&&(h=c)}(h>0||0===n)&&(t[n].periodX=i+h/2)}}(C,t,t._definedDelta),t.rangebreaks){var it="y"===t._id.charAt(0),st=1;"auto"===t.tickmode&&(st=t.tickfont?t.tickfont.size:12);var lt=NaN;for(r=C.length-1;r>-1;r--)if(C[r].drop)C.splice(r,1);else{C[r].value=zt(C[r].value,t);var ut=t.c2p(C[r].value);(it?lt>ut-st:lt<ut+st)?C.splice(f?r+1:r,1):lt=ut}}Dt(t)&&360===Math.abs(c[1]-c[0])&&C.pop(),t._tmax=(C[C.length-1]||{}).value,t._prevDateHead="",t._inCalcTicks=!0;var ct,ft,ht=function(e){e.text="",t._prevDateHead=n};for(C=C.concat(P),r=0;r<C.length;r++){var pt=C[r].minor,dt=C[r].value;pt?L.push({x:dt,minor:!0}):(n=t._prevDateHead,ct=q.tickText(t,dt,!1,C[r].simpleLabel),void 0!==(ft=C[r].periodX)&&(ct.periodX=ft,(ft>p||ft<h)&&(ft>p&&(ct.periodX=p),ft<h&&(ct.periodX=h),ht(ct))),C[r].skipLabel&&ht(ct),v.push(ct))}return v=v.concat(L),t._inCalcTicks=!1,u&&v.length&&(v[0].noTick=!0),v};var st=[2,5,10],lt=[1,2,3,6,12],ut=[1,2,5,10,15,30],ct=[1,2,3,7,14],ft=[-.046,0,.301,.477,.602,.699,.778,.845,.903,.954,1],ht=[-.301,0,.301,.699,1],pt=[15,30,45,90,180];function dt(t,e,r){return e*s.roundUp(t/e,r)}function vt(t){var e=t.dtick;if(t._tickexponent=0,i(e)||"string"==typeof e||(e=1),"category"!==t.type&&"multicategory"!==t.type||(t._tickround=null),"date"===t.type){var r=t.r2l(t.tick0),n=t.l2r(r).replace(/(^-|i)/g,""),a=n.length;if("M"===String(e).charAt(0))a>10||"01-01"!==n.substr(5)?t._tickround="d":t._tickround=+e.substr(1)%12==0?"y":"m";else if(e>=M&&a<=10||e>=15*M)t._tickround="d";else if(e>=L&&a<=16||e>=E)t._tickround="M";else if(e>=C&&a<=19||e>=L)t._tickround="S";else{var o=t.l2r(r+e).replace(/^-/,"").length;t._tickround=Math.max(a,o)-20,t._tickround<0&&(t._tickround=4)}}else if(i(e)||"L"===e.charAt(0)){var s=t.range.map(t.r2d||Number);i(e)||(e=Number(e.substr(1))),t._tickround=2-Math.floor(Math.log(e)/Math.LN10+.01);var l=Math.max(Math.abs(s[0]),Math.abs(s[1])),u=Math.floor(Math.log(l)/Math.LN10+.01),c=void 0===t.minexponent?3:t.minexponent;Math.abs(u)>c&&(mt(t.exponentformat)&&!xt(u)?t._tickexponent=3*Math.round((u-1)/3):t._tickexponent=u)}else t._tickround=null}function gt(t,e,r){var n=t.tickfont||{};return{x:e,dx:0,dy:0,text:r||"",fontSize:n.size,font:n.family,fontColor:n.color}}q.autoTicks=function(t,e,r){var n;function a(t){return Math.pow(t,Math.floor(Math.log(e)/Math.LN10))}if("date"===t.type){t.tick0=s.dateTick0(t.calendar,0);var o=2*e;if(o>y)e/=y,n=a(10),t.dtick="M"+12*dt(e,n,st);else if(o>T)e/=T,t.dtick="M"+dt(e,1,lt);else if(o>M){if(t.dtick=dt(e,M,t._hasDayOfWeekBreaks?[1,2,7,14]:ct),!r){var l=q.getTickFormat(t),u="period"===t.ticklabelmode;u&&(t._rawTick0=t.tick0),/%[uVW]/.test(l)?t.tick0=s.dateTick0(t.calendar,2):t.tick0=s.dateTick0(t.calendar,1),u&&(t._dowTick0=t.tick0)}}else o>E?t.dtick=dt(e,E,lt):o>L?t.dtick=dt(e,L,ut):o>C?t.dtick=dt(e,C,ut):(n=a(10),t.dtick=dt(e,n,st))}else if("log"===t.type){t.tick0=0;var c=s.simpleMap(t.range,t.r2l);if(t._isMinor&&(e*=1.5),e>.7)t.dtick=Math.ceil(e);else if(Math.abs(c[1]-c[0])<1){var f=1.5*Math.abs((c[1]-c[0])/e);e=Math.abs(Math.pow(10,c[1])-Math.pow(10,c[0]))/f,n=a(10),t.dtick="L"+dt(e,n,st)}else t.dtick=e>.3?"D2":"D1"}else"category"===t.type||"multicategory"===t.type?(t.tick0=0,t.dtick=Math.ceil(Math.max(e,1))):Dt(t)?(t.tick0=0,n=1,t.dtick=dt(e,n,pt)):(t.tick0=0,n=a(10),t.dtick=dt(e,n,st));if(0===t.dtick&&(t.dtick=1),!i(t.dtick)&&"string"!=typeof t.dtick){var h=t.dtick;throw t.dtick=1,"ax.dtick error: "+String(h)}},q.tickIncrement=function(t,e,r,a){var o=r?-1:1;if(i(e))return s.increment(t,o*e);var l=e.charAt(0),u=o*Number(e.substr(1));if("M"===l)return s.incrementMonth(t,u,a);if("L"===l)return Math.log(Math.pow(10,t)+u)/Math.LN10;if("D"===l){var c="D2"===e?ht:ft,f=t+.01*o,h=s.roundUp(s.mod(f,1),c,r);return Math.floor(f)+Math.log(n.round(Math.pow(10,h),1))/Math.LN10}throw"unrecognized dtick 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n=r(39898),i=r(71828),a=i.numberFormat,o=r(84267),s=r(38520),l=r(73972),u=i.strTranslate,c=r(63893),f=r(7901),h=r(91424),p=r(30211),d=r(89298),v=r(6964),g=r(28569),y=r(64505),m=y.selectingOrDrawing,x=y.freeMode,b=r(18783).FROM_TL,_=r(33306),w=r(61549).redrawReglTraces,T=r(74875),k=r(41675).getFromId,A=r(47322).prepSelect,M=r(47322).clearOutline,S=r(47322).selectOnClick,E=r(42449),L=r(85555),C=L.MINDRAG,P=L.MINZOOM,O=!0;function I(t,e,r,n){var a=i.ensureSingle(t.draglayer,e,r,(function(e){e.classed("drag",!0).style({fill:"transparent","stroke-width":0}).attr("data-subplot",t.id)}));return a.call(v,n),a.node()}function D(t,e,r,i,a,o,s){var l=I(t,"rect",e,r);return n.select(l).call(h.setRect,i,a,o,s),l}function z(t,e){for(var r=0;r<t.length;r++)if(!t[r].fixedrange)return e;return""}function R(t,e,r,n,i){for(var a=0;a<t.length;a++){var o=t[a];if(!o.fixedrange)if(o.rangebreaks){var 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o,s,l,u,c=!1,f={},h={},p=(a||{}).xaHash,d=(a||{}).yaHash,v=0;v<e.length;v++){var g=e[v];for(o in r)if(g[o]){for(l in g)a&&(p[l]||d[l])||("x"===l.charAt(0)?r:n)[l]||(f[l]=o);for(s in n)a&&(p[s]||d[s])||!g[s]||(c=!0)}for(s in n)if(g[s])for(u in g)a&&(p[u]||d[u])||("x"===u.charAt(0)?r:n)[u]||(h[u]=s)}c&&(i.extendFlat(f,h),h={});var y={},m=[];for(l in f){var x=k(t,l);m.push(x),y[x._id]=x}var b={},_=[];for(u in h){var w=k(t,u);_.push(w),b[w._id]=w}return{xaHash:y,yaHash:b,xaxes:m,yaxes:_,xLinks:f,yLinks:h,isSubplotConstrained:c}}function Y(t,e){if(s){var r=void 0!==t.onwheel?"wheel":"mousewheel";t._onwheel&&t.removeEventListener(r,t._onwheel),t._onwheel=e,t.addEventListener(r,e,{passive:!1})}else void 0!==t.onwheel?t.onwheel=e:void 0!==t.onmousewheel?t.onmousewheel=e:t.isAddedWheelEvent||(t.isAddedWheelEvent=!0,t.addEventListener("wheel",e,{passive:!1}))}function W(t){var e=[];for(var r in t)e.push(t[r]);return e}t.exports={makeDragBox:function(t,e,r,s,u,f,v,y){var O,I,V,X,J,K,$,Q,tt,et,rt,nt,it,at,ot,st,lt,ut,ct,ft,ht,pt,dt,vt=t._fullLayout._zoomlayer,gt=v+y==="nsew",yt=1===(v+y).length;function mt(){if(O=e.xaxis,I=e.yaxis,tt=O._length,et=I._length,$=O._offset,Q=I._offset,(V={})[O._id]=O,(X={})[I._id]=I,v&&y)for(var r=e.overlays,n=0;n<r.length;n++){var i=r[n].xaxis;V[i._id]=i;var a=r[n].yaxis;X[a._id]=a}J=W(V),K=W(X),it=z(J,y),at=z(K,v),ot=!at&&!it,nt=Z(t,t._fullLayout._axisMatchGroups,V,X);var o=(rt=Z(t,t._fullLayout._axisConstraintGroups,V,X,nt)).isSubplotConstrained||nt.isSubplotConstrained;st=y||o,lt=v||o;var s=t._fullLayout;ut=s._has("scattergl"),ct=s._has("splom"),ft=s._has("svg")}r+=e.yaxis._shift,mt();var xt=function(t,e,r){return t?"nsew"===t?r?"":"pan"===e?"move":"crosshair":t.toLowerCase()+"-resize":"pointer"}(at+it,t._fullLayout.dragmode,gt),bt=D(e,v+y+"drag",xt,r,s,u,f);if(ot&&!gt)return bt.onmousedown=null,bt.style.pointerEvents="none",bt;var _t,wt,Tt,kt,At,Mt,St,Et,Lt,Ct,Pt={element:bt,gd:t,plotinfo:e};function Ot(){Pt.plotinfo.selection=!1,M(t)}function It(t,r){var i=Pt.gd;if(i._fullLayout._activeShapeIndex>=0)i._fullLayout._deactivateShape(i);else{var o=i._fullLayout.clickmode;if(H(i),2!==t||yt||qt(),gt)o.indexOf("select")>-1&&S(r,i,J,K,e.id,Pt),o.indexOf("event")>-1&&p.click(i,r,e.id);else if(1===t&&yt){var s=v?I:O,u="s"===v||"w"===y?0:1,f=s._name+".range["+u+"]",h=function(t,e){var r,n=t.range[e],i=Math.abs(n-t.range[1-e]);return"date"===t.type?n:"log"===t.type?(r=Math.ceil(Math.max(0,-Math.log(i)/Math.LN10))+3,a("."+r+"g")(Math.pow(10,n))):(r=Math.floor(Math.log(Math.abs(n))/Math.LN10)-Math.floor(Math.log(i)/Math.LN10)+4,a("."+String(r)+"g")(n))}(s,u),d="left",g="middle";if(s.fixedrange)return;v?(g="n"===v?"top":"bottom","right"===s.side&&(d="right")):"e"===y&&(d="right"),i._context.showAxisRangeEntryBoxes&&n.select(bt).call(c.makeEditable,{gd:i,immediate:!0,background:i._fullLayout.paper_bgcolor,text:String(h),fill:s.tickfont?s.tickfont.color:"#444",horizontalAlign:d,verticalAlign:g}).on("edit",(function(t){var e=s.d2r(t);void 0!==e&&l.call("_guiRelayout",i,f,e)}))}}}function Dt(e,r){if(t._transitioningWithDuration)return!1;var n=Math.max(0,Math.min(tt,pt*e+_t)),i=Math.max(0,Math.min(et,dt*r+wt)),a=Math.abs(n-_t),o=Math.abs(i-wt);function s(){St="",Tt.r=Tt.l,Tt.t=Tt.b,Lt.attr("d","M0,0Z")}if(Tt.l=Math.min(_t,n),Tt.r=Math.max(_t,n),Tt.t=Math.min(wt,i),Tt.b=Math.max(wt,i),rt.isSubplotConstrained)a>P||o>P?(St="xy",a/tt>o/et?(o=a*et/tt,wt>i?Tt.t=wt-o:Tt.b=wt+o):(a=o*tt/et,_t>n?Tt.l=_t-a:Tt.r=_t+a),Lt.attr("d",G(Tt))):s();else if(nt.isSubplotConstrained)if(a>P||o>P){St="xy";var l=Math.min(Tt.l/tt,(et-Tt.b)/et),u=Math.max(Tt.r/tt,(et-Tt.t)/et);Tt.l=l*tt,Tt.r=u*tt,Tt.b=(1-l)*et,Tt.t=(1-u)*et,Lt.attr("d",G(Tt))}else 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a=Pt.dragmode,s=t._fullLayout.dragmode;s!==a&&(Pt.dragmode=s),mt(),pt=t._fullLayout._invScaleX,dt=t._fullLayout._invScaleY,ot||(gt?e.shiftKey?"pan"===s?s="zoom":m(s)||(s="pan"):e.ctrlKey&&(s="pan"):s="pan"),x(s)?Pt.minDrag=1:Pt.minDrag=void 0,m(s)?(Pt.xaxes=J,Pt.yaxes=K,A(e,r,n,Pt,s)):(Pt.clickFn=It,m(a)&&Ot(),ot||("zoom"===s?(Pt.moveFn=Dt,Pt.doneFn=Rt,Pt.minDrag=1,function(e,r,n){var a=bt.getBoundingClientRect();_t=r-a.left,wt=n-a.top,t._fullLayout._calcInverseTransform(t);var s=i.apply3DTransform(t._fullLayout._invTransform)(_t,wt);_t=s[0],wt=s[1],Tt={l:_t,r:_t,w:0,t:wt,b:wt,h:0},kt=t._hmpixcount?t._hmlumcount/t._hmpixcount:o(t._fullLayout.plot_bgcolor).getLuminance(),Mt=!1,St="xy",Ct=!1,Et=N(vt,kt,$,Q,At="M0,0H"+tt+"V"+et+"H0V0"),Lt=j(vt,$,Q)}(0,r,n)):"pan"===s&&(Pt.moveFn=Ut,Pt.doneFn=Gt))),t._fullLayout._redrag=function(){var e=t._dragdata;if(e&&e.element===bt){var r=t._fullLayout.dragmode;m(r)||(mt(),Zt([0,0,tt,et]),Pt.moveFn(e.dx,e.dy))}}},g.init(Pt);var Ft=[0,0,tt,et],Bt=null,Nt=L.REDRAWDELAY,jt=e.mainplot?t._fullLayout._plots[e.mainplot]:e;function Ut(e,r){if(e*=pt,r*=dt,!t._transitioningWithDuration){if(t._fullLayout._replotting=!0,"ew"===it||"ns"===at){var n=it?-e:0,i=at?-r:0;if(nt.isSubplotConstrained){if(it&&at){var a=(e/tt-r/et)/2;n=-(e=a*tt),i=-(r=-a*et)}at?n=-i*tt/et:i=-n*et/tt}return it&&(F(J,e),Vt("x")),at&&(F(K,r),Vt("y")),Zt([n,i,tt,et]),Ht(),void t.emit("plotly_relayouting",ht)}var o,s,l="w"===it==("n"===at)?1:-1;if(it&&at&&(rt.isSubplotConstrained||nt.isSubplotConstrained)){var u=(e/tt+l*r/et)/2;e=u*tt,r=l*u*et}if("w"===it?e=p(J,0,e):"e"===it?e=p(J,1,-e):it||(e=0),"n"===at?r=p(K,1,r):"s"===at?r=p(K,0,-r):at||(r=0),o="w"===it?e:0,s="n"===at?r:0,rt.isSubplotConstrained&&!nt.isSubplotConstrained||nt.isSubplotConstrained&&it&&at&&l>0){var c;if(nt.isSubplotConstrained||!it&&1===at.length){for(c=0;c<J.length;c++)J[c].range=J[c]._r.slice(),E(J[c],1-r/et);o=(e=r*tt/et)/2}if(nt.isSubplotConstrained||!at&&1===it.length){for(c=0;c<K.length;c++)K[c].range=K[c]._r.slice(),E(K[c],1-e/tt);s=(r=e*et/tt)/2}}nt.isSubplotConstrained&&at||Vt("x"),nt.isSubplotConstrained&&it||Vt("y");var f=tt-e,h=et-r;!nt.isSubplotConstrained||it&&at||(it?(s=o?0:e*et/tt,h=f*et/tt):(o=s?0:r*tt/et,f=h*tt/et)),Zt([o,s,f,h]),Ht(),t.emit("plotly_relayouting",ht)}function p(t,e,r){for(var n,i,a=1-e,o=0;o<t.length;o++){var s=t[o];if(!s.fixedrange){n=s,i=s._rl[a]+(s._rl[e]-s._rl[a])/B(r/s._length);var l=s.l2r(i);!1!==l&&void 0!==l&&(s.range[e]=l)}}return n._length*(n._rl[e]-i)/(n._rl[e]-n._rl[a])}}function Vt(t,e){for(var r=nt.isSubplotConstrained?{x:K,y:J}[t]:nt[t+"axes"],n=nt.isSubplotConstrained?{x:J,y:K}[t]:[],i=0;i<r.length;i++){var a=r[i],o=a._id,s=nt.xLinks[o]||nt.yLinks[o],l=n[0]||V[s]||X[s];l&&(e?(e[a._name+".range[0]"]=e[l._name+".range[0]"],e[a._name+".range[1]"]=e[l._name+".range[1]"]):a.range=l.range.slice())}}function Ht(){var r,n=[];function i(t){for(r=0;r<t.length;r++)t[r].fixedrange||n.push(t[r]._id)}function a(t,e){for(r=0;r<t.length;r++){var i=t[r],a=i[e];i.fixedrange||"sync"!==a.tickmode||n.push(a._id)}}for(st&&(i(J),i(rt.xaxes),i(nt.xaxes),a(e.overlays,"xaxis")),lt&&(i(K),i(rt.yaxes),i(nt.yaxes),a(e.overlays,"yaxis")),ht={},r=0;r<n.length;r++){var o=n[r],s=k(t,o);d.drawOne(t,s,{skipTitle:!0}),ht[s._name+".range[0]"]=s.range[0],ht[s._name+".range[1]"]=s.range[1]}d.redrawComponents(t,n)}function qt(){if(!t._transitioningWithDuration){var e=t._context.doubleClick,r=[];it&&(r=r.concat(J)),at&&(r=r.concat(K)),nt.xaxes&&(r=r.concat(nt.xaxes)),nt.yaxes&&(r=r.concat(nt.yaxes));var 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_=(l[3]-l[1])/(l[2]-l[0]);Math.abs(a*_)>Math.abs(s)?(u.boxEnd[1]=u.boxStart[1]+Math.abs(a)*_*(s>=0?1:-1),u.boxEnd[1]<l[1]?(u.boxEnd[1]=l[1],u.boxEnd[0]=u.boxStart[0]+(l[1]-u.boxStart[1])/Math.abs(_)):u.boxEnd[1]>l[3]&&(u.boxEnd[1]=l[3],u.boxEnd[0]=u.boxStart[0]+(l[3]-u.boxStart[1])/Math.abs(_))):(u.boxEnd[0]=u.boxStart[0]+Math.abs(s)/_*(a>=0?1:-1),u.boxEnd[0]<l[0]?(u.boxEnd[0]=l[0],u.boxEnd[1]=u.boxStart[1]+(l[0]-u.boxStart[0])*Math.abs(_)):u.boxEnd[0]>l[2]&&(u.boxEnd[0]=l[2],u.boxEnd[1]=u.boxStart[1]+(l[2]-u.boxStart[0])*Math.abs(_)))}}else u.boxEnabled?(a=u.boxStart[0]!==u.boxEnd[0],s=u.boxStart[1]!==u.boxEnd[1],a||s?(a&&(g(0,u.boxStart[0],u.boxEnd[0]),t.xaxis.autorange=!1),s&&(g(1,u.boxStart[1],u.boxEnd[1]),t.yaxis.autorange=!1),t.relayoutCallback()):t.glplot.setDirty(),u.boxEnabled=!1,u.boxInited=!1):u.boxInited&&(u.boxInited=!1);break;case"pan":u.boxEnabled=!1,u.boxInited=!1,e?(u.panning||(u.dragStart[0]=n,u.dragStart[1]=i),Math.abs(u.dragStart[0]-n)<d&&(n=u.dragStart[0]),Math.abs(u.dragStart[1]-i)<d&&(i=u.dragStart[1]),a=(h-n)*(l[2]-l[0])/(r.viewBox[2]-r.viewBox[0]),s=(p-i)*(l[3]-l[1])/(r.viewBox[3]-r.viewBox[1]),l[0]+=a,l[2]+=a,l[1]+=s,l[3]+=s,t.setRanges(l),u.panning=!0,u.lastInputTime=Date.now(),c(),t.cameraChanged(),t.handleAnnotations()):u.panning&&(u.panning=!1,t.relayoutCallback())}u.lastPos[0]=n,u.lastPos[1]=i}return u.mouseListener=n(e,f),e.addEventListener("touchstart",(function(t){var r=a(t.changedTouches[0],e);f(0,r[0],r[1]),f(1,r[0],r[1]),t.preventDefault()}),!!s&&{passive:!1}),e.addEventListener("touchmove",(function(t){t.preventDefault();var r=a(t.changedTouches[0],e);f(1,r[0],r[1]),t.preventDefault()}),!!s&&{passive:!1}),e.addEventListener("touchend",(function(t){f(0,u.lastPos[0],u.lastPos[1]),t.preventDefault()}),!!s&&{passive:!1}),u.wheelListener=i(e,(function(e,n){if(!t.scrollZoom)return!1;var i=t.calcDataBox(),a=r.viewBox,o=u.lastPos[0],s=u.lastPos[1],l=Math.exp(5*n/(a[3]-a[1])),f=o/(a[2]-a[0])*(i[2]-i[0])+i[0],h=s/(a[3]-a[1])*(i[3]-i[1])+i[1];return i[0]=(i[0]-f)*l+f,i[2]=(i[2]-f)*l+f,i[1]=(i[1]-h)*l+h,i[3]=(i[3]-h)*l+h,t.setRanges(i),u.lastInputTime=Date.now(),c(),t.cameraChanged(),t.handleAnnotations(),t.relayoutCallback(),!0}),!0),u}},82961:function(t,e,r){"use strict";var n=r(89298),i=r(78614);function a(t){this.scene=t,this.gl=t.gl,this.pixelRatio=t.pixelRatio,this.screenBox=[0,0,1,1],this.viewBox=[0,0,1,1],this.dataBox=[-1,-1,1,1],this.borderLineEnable=[!1,!1,!1,!1],this.borderLineWidth=[1,1,1,1],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.ticks=[[],[]],this.tickEnable=[!0,!0,!1,!1],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labels=["x","y"],this.labelEnable=[!0,!0,!1,!1],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelPad=[15,15,15,15],this.labelSize=[12,12],this.labelFont=["sans-serif","sans-serif"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.title="",this.titleEnable=!0,this.titleCenter=[0,0,0,0],this.titleAngle=0,this.titleColor=[0,0,0,1],this.titleFont="sans-serif",this.titleSize=18,this.gridLineEnable=[!0,!0],this.gridLineColor=[[0,0,0,.5],[0,0,0,.5]],this.gridLineWidth=[1,1],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[1,1],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.static=this.scene.staticPlot}var o=a.prototype,s=["xaxis","yaxis"];o.merge=function(t){var e,r,n,a,o,l,u,c,f,h,p;for(this.titleEnable=!1,this.backgroundColor=i(t.plot_bgcolor),h=0;h<2;++h){var d=(e=s[h]).charAt(0);for(n=(r=t[this.scene[e]._name]).title.text===this.scene.fullLayout._dfltTitle[d]?"":r.title.text,p=0;p<=2;p+=2)this.labelEnable[h+p]=!1,this.labels[h+p]=n,this.labelColor[h+p]=i(r.title.font.color),this.labelFont[h+p]=r.title.font.family,this.labelSize[h+p]=r.title.font.size,this.labelPad[h+p]=this.getLabelPad(e,r),this.tickEnable[h+p]=!1,this.tickColor[h+p]=i((r.tickfont||{}).color),this.tickAngle[h+p]="auto"===r.tickangle?0:Math.PI*-r.tickangle/180,this.tickPad[h+p]=this.getTickPad(r),this.tickMarkLength[h+p]=0,this.tickMarkWidth[h+p]=r.tickwidth||0,this.tickMarkColor[h+p]=i(r.tickcolor),this.borderLineEnable[h+p]=!1,this.borderLineColor[h+p]=i(r.linecolor),this.borderLineWidth[h+p]=r.linewidth||0;u=this.hasSharedAxis(r),o=this.hasAxisInDfltPos(e,r)&&!u,l=this.hasAxisInAltrPos(e,r)&&!u,a=r.mirror||!1,c=u?-1!==String(a).indexOf("all"):!!a,f=u?"allticks"===a:-1!==String(a).indexOf("ticks"),o?this.labelEnable[h]=!0:l&&(this.labelEnable[h+2]=!0),o?this.tickEnable[h]=r.showticklabels:l&&(this.tickEnable[h+2]=r.showticklabels),(o||c)&&(this.borderLineEnable[h]=r.showline),(l||c)&&(this.borderLineEnable[h+2]=r.showline),(o||f)&&(this.tickMarkLength[h]=this.getTickMarkLength(r)),(l||f)&&(this.tickMarkLength[h+2]=this.getTickMarkLength(r)),this.gridLineEnable[h]=r.showgrid,this.gridLineColor[h]=i(r.gridcolor),this.gridLineWidth[h]=r.gridwidth,this.zeroLineEnable[h]=r.zeroline,this.zeroLineColor[h]=i(r.zerolinecolor),this.zeroLineWidth[h]=r.zerolinewidth}},o.hasSharedAxis=function(t){var e=this.scene,r=e.fullLayout._subplots.gl2d;return 0!==n.findSubplotsWithAxis(r,t).indexOf(e.id)},o.hasAxisInDfltPos=function(t,e){var r=e.side;return"xaxis"===t?"bottom"===r:"yaxis"===t?"left"===r:void 0},o.hasAxisInAltrPos=function(t,e){var r=e.side;return"xaxis"===t?"top"===r:"yaxis"===t?"right"===r:void 0},o.getLabelPad=function(t,e){var r=1.5,n=e.title.font.size,i=e.showticklabels;return"xaxis"===t?"top"===e.side?n*(r+(i?1:0))-10:n*(r+(i?.5:0))-10:"yaxis"===t?"right"===e.side?10+n*(r+(i?1:.5)):10+n*(r+(i?.5:0)):void 0},o.getTickPad=function(t){return"outside"===t.ticks?10+t.ticklen:15},o.getTickMarkLength=function(t){if(!t.ticks)return 0;var e=t.ticklen;return"inside"===t.ticks?-e:e},t.exports=function(t){return new a(t)}},4796:function(t,e,r){"use strict";var n=r(30962).overrideAll,i=r(92918),a=r(10820),o=r(77922),s=r(85555),l=r(93612),u=r(528),c=r(27659).NG;e.name="gl2d",e.attr=["xaxis","yaxis"],e.idRoot=["x","y"],e.idRegex=s.idRegex,e.attrRegex=s.attrRegex,e.attributes=r(89502),e.supplyLayoutDefaults=function(t,e,r){e._has("cartesian")||l.supplyLayoutDefaults(t,e,r)},e.layoutAttrOverrides=n(l.layoutAttributes,"plot","from-root"),e.baseLayoutAttrOverrides=n({plot_bgcolor:a.plot_bgcolor,hoverlabel:u.hoverlabel},"plot","nested"),e.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl2d,a=0;a<n.length;a++){var o=n[a],s=e._plots[o],l=c(r,"gl2d",o),u=s._scene2d;void 0===u&&(u=new i({id:o,graphDiv:t,container:t.querySelector(".gl-container"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),s._scene2d=u),u.plot(l,t.calcdata,e,t.layout)}},e.clean=function(t,e,r,n){for(var i=n._subplots.gl2d||[],a=0;a<i.length;a++){var o=i[a],s=n._plots[o];s._scene2d&&0===c(t,"gl2d",o).length&&(s._scene2d.destroy(),delete n._plots[o])}l.clean.apply(this,arguments)},e.drawFramework=function(t){t._context.staticPlot||l.drawFramework(t)},e.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){var i=e._plots[r[n]]._scene2d,a=i.toImage("png");e._glimages.append("svg:image").attr({xmlns:o.svg,"xlink:href":a,x:0,y:0,width:"100%",height:"100%",preserveAspectRatio:"none"}),i.destroy()}},e.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++)e._plots[r[n]]._scene2d.updateFx(e.dragmode)}},92918:function(t,e,r){"use strict";var n,i,a=r(73972),o=r(89298),s=r(30211),l=r(9330).gl_plot2d,u=r(9330).gl_spikes2d,c=r(9330).gl_select_box,f=r(40372),h=r(82961),p=r(75071),d=r(58617),v=r(99082),g=v.enforce,y=v.clean,m=r(71739).doAutoRange,x=r(64505),b=x.drawMode,_=x.selectMode,w=["xaxis","yaxis"],T=r(85555).SUBPLOT_PATTERN;function k(t,e){this.container=t.container,this.graphDiv=t.graphDiv,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.scrollZoom=this.graphDiv._context._scrollZoom.cartesian,this.fullData=null,this.updateRefs(e),this.makeFramework(),this.stopped||(this.glplotOptions=h(this),this.glplotOptions.merge(e),this.glplot=l(this.glplotOptions),this.camera=p(this),this.traces={},this.spikes=u(this.glplot),this.selectBox=c(this.glplot,{innerFill:!1,outerFill:!0}),this.lastButtonState=0,this.pickResult=null,this.isMouseOver=!0,this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw())}t.exports=k;var A=k.prototype;A.makeFramework=function(){if(this.staticPlot){if(!(i||(n=document.createElement("canvas"),i=f({canvas:n,preserveDrawingBuffer:!1,premultipliedAlpha:!0,antialias:!0}))))throw new Error("Error creating static canvas/context for image server");this.canvas=n,this.gl=i}else{var t=this.container.querySelector(".gl-canvas-focus"),e=f({canvas:t,preserveDrawingBuffer:!0,premultipliedAlpha:!0});if(!e)return d(this),void(this.stopped=!0);this.canvas=t,this.gl=e}var r=this.canvas;r.style.width="100%",r.style.height="100%",r.style.position="absolute",r.style.top="0px",r.style.left="0px",r.style["pointer-events"]="none",this.updateSize(r);var a=this.svgContainer=document.createElementNS("http://www.w3.org/2000/svg","svg");a.style.position="absolute",a.style.top=a.style.left="0px",a.style.width=a.style.height="100%",a.style["z-index"]=20,a.style["pointer-events"]="none";var o=this.mouseContainer=document.createElement("div");o.style.position="absolute",o.style["pointer-events"]="auto",this.pickCanvas=this.container.querySelector(".gl-canvas-pick");var s=this.container;s.appendChild(a),s.appendChild(o);var l=this;o.addEventListener("mouseout",(function(){l.isMouseOver=!1,l.unhover()})),o.addEventListener("mouseover",(function(){l.isMouseOver=!0}))},A.toImage=function(t){t||(t="png"),this.stopped=!0,this.staticPlot&&this.container.appendChild(n),this.updateSize(this.canvas);var e=this.glplot.gl,r=e.drawingBufferWidth,i=e.drawingBufferHeight;e.clearColor(1,1,1,0),e.clear(e.COLOR_BUFFER_BIT|e.DEPTH_BUFFER_BIT),this.glplot.setDirty(),this.glplot.draw(),e.bindFramebuffer(e.FRAMEBUFFER,null);var a=new Uint8Array(r*i*4);e.readPixels(0,0,r,i,e.RGBA,e.UNSIGNED_BYTE,a);for(var o=0,s=i-1;o<s;++o,--s)for(var l=0;l<r;++l)for(var u=0;u<4;++u){var c=a[4*(r*o+l)+u];a[4*(r*o+l)+u]=a[4*(r*s+l)+u],a[4*(r*s+l)+u]=c}var f=document.createElement("canvas");f.width=r,f.height=i;var h,p=f.getContext("2d",{willReadFrequently:!0}),d=p.createImageData(r,i);switch(d.data.set(a),p.putImageData(d,0,0),t){case"jpeg":h=f.toDataURL("image/jpeg");break;case"webp":h=f.toDataURL("image/webp");break;default:h=f.toDataURL("image/png")}return this.staticPlot&&this.container.removeChild(n),h},A.updateSize=function(t){t||(t=this.canvas);var e=this.pixelRatio,r=this.fullLayout,n=r.width,i=r.height,a=0|Math.ceil(e*n),o=0|Math.ceil(e*i);return t.width===a&&t.height===o||(t.width=a,t.height=o),t},A.computeTickMarks=function(){this.xaxis.setScale(),this.yaxis.setScale();for(var t=[o.calcTicks(this.xaxis),o.calcTicks(this.yaxis)],e=0;e<2;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=t[e][r].text+"";return t},A.updateRefs=function(t){this.fullLayout=t;var e=this.id.match(T),r="xaxis"+e[1],n="yaxis"+e[2];this.xaxis=this.fullLayout[r],this.yaxis=this.fullLayout[n]},A.relayoutCallback=function(){var t=this.graphDiv,e=this.xaxis,r=this.yaxis,n=t.layout,i={},o=i[e._name+".range"]=e.range.slice(),s=i[r._name+".range"]=r.range.slice();i[e._name+".autorange"]=e.autorange,i[r._name+".autorange"]=r.autorange,a.call("_storeDirectGUIEdit",t.layout,t._fullLayout._preGUI,i);var l=n[e._name];l.range=o,l.autorange=e.autorange;var u=n[r._name];u.range=s,u.autorange=r.autorange,i.lastInputTime=this.camera.lastInputTime,t.emit("plotly_relayout",i)},A.cameraChanged=function(){var t=this.camera;this.glplot.setDataBox(this.calcDataBox());var e=this.computeTickMarks();(function(t,e){for(var r=0;r<2;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1})(e,this.glplotOptions.ticks)&&(this.glplotOptions.ticks=e,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions),this.handleAnnotations())},A.handleAnnotations=function(){for(var t=this.graphDiv,e=this.fullLayout.annotations,r=0;r<e.length;r++){var n=e[r];n.xref===this.xaxis._id&&n.yref===this.yaxis._id&&a.getComponentMethod("annotations","drawOne")(t,r)}},A.destroy=function(){if(this.glplot){var t=this.traces;t&&Object.keys(t).map((function(e){t[e].dispose(),delete t[e]})),this.glplot.dispose(),this.container.removeChild(this.svgContainer),this.container.removeChild(this.mouseContainer),this.fullData=null,this.glplot=null,this.stopped=!0,this.camera.mouseListener.enabled=!1,this.mouseContainer.removeEventListener("wheel",this.camera.wheelListener),this.camera=null}},A.plot=function(t,e,r){var n=this.glplot;this.updateRefs(r),this.xaxis.clearCalc(),this.yaxis.clearCalc(),this.updateTraces(t,e),this.updateFx(r.dragmode);var i=r.width,a=r.height;this.updateSize(this.canvas);var o=this.glplotOptions;o.merge(r),o.screenBox=[0,0,i,a];var s={_fullLayout:{_axisConstraintGroups:r._axisConstraintGroups,xaxis:this.xaxis,yaxis:this.yaxis,_size:r._size}};y(s,this.xaxis),y(s,this.yaxis);var l,u,c=r._size,f=this.xaxis.domain,h=this.yaxis.domain;for(o.viewBox=[c.l+f[0]*c.w,c.b+h[0]*c.h,i-c.r-(1-f[1])*c.w,a-c.t-(1-h[1])*c.h],this.mouseContainer.style.width=c.w*(f[1]-f[0])+"px",this.mouseContainer.style.height=c.h*(h[1]-h[0])+"px",this.mouseContainer.height=c.h*(h[1]-h[0]),this.mouseContainer.style.left=c.l+f[0]*c.w+"px",this.mouseContainer.style.top=c.t+(1-h[1])*c.h+"px",u=0;u<2;++u)(l=this[w[u]])._length=o.viewBox[u+2]-o.viewBox[u],m(this.graphDiv,l),l.setScale();g(s),o.ticks=this.computeTickMarks(),o.dataBox=this.calcDataBox(),o.merge(r),n.update(o),this.glplot.draw()},A.calcDataBox=function(){var t=this.xaxis,e=this.yaxis,r=t.range,n=e.range,i=t.r2l,a=e.r2l;return[i(r[0]),a(n[0]),i(r[1]),a(n[1])]},A.setRanges=function(t){var e=this.xaxis,r=this.yaxis,n=e.l2r,i=r.l2r;e.range=[n(t[0]),n(t[2])],r.range=[i(t[1]),i(t[3])]},A.updateTraces=function(t,e){var r,n,i,a=Object.keys(this.traces);this.fullData=t;t:for(r=0;r<a.length;r++){var o=a[r],s=this.traces[o];for(n=0;n<t.length;n++)if((i=t[n]).uid===o&&i.type===s.type)continue t;s.dispose(),delete this.traces[o]}for(r=0;r<t.length;r++){i=t[r];var l=e[r],u=this.traces[i.uid];u?u.update(i,l):(u=i._module.plot(this,i,l),this.traces[i.uid]=u)}this.glplot.objects.sort((function(t,e){return t._trace.index-e._trace.index}))},A.updateFx=function(t){_(t)||b(t)?(this.pickCanvas.style["pointer-events"]="none",this.mouseContainer.style["pointer-events"]="none"):(this.pickCanvas.style["pointer-events"]="auto",this.mouseContainer.style["pointer-events"]="auto"),this.mouseContainer.style.cursor="pan"===t?"move":"zoom"===t?"crosshair":null},A.emitPointAction=function(t,e){for(var r,n=t.trace.uid,i=t.pointIndex,a=0;a<this.fullData.length;a++)this.fullData[a].uid===n&&(r=this.fullData[a]);var o={x:t.traceCoord[0],y:t.traceCoord[1],curveNumber:r.index,pointNumber:i,data:r._input,fullData:this.fullData,xaxis:this.xaxis,yaxis:this.yaxis};s.appendArrayPointValue(o,r,i),this.graphDiv.emit(e,{points:[o]})},A.draw=function(){if(!this.stopped){requestAnimationFrame(this.redraw);var t=this.glplot,e=this.camera,r=e.mouseListener,n=1===this.lastButtonState&&0===r.buttons,i=this.fullLayout;this.lastButtonState=r.buttons,this.cameraChanged();var a,o=r.x*t.pixelRatio,l=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&"zoom"===i.dragmode){this.selectBox.enabled=!0;for(var u=this.selectBox.selectBox=[Math.min(e.boxStart[0],e.boxEnd[0]),Math.min(e.boxStart[1],e.boxEnd[1]),Math.max(e.boxStart[0],e.boxEnd[0]),Math.max(e.boxStart[1],e.boxEnd[1])],c=0;c<2;c++)e.boxStart[c]===e.boxEnd[c]&&(u[c]=t.dataBox[c],u[c+2]=t.dataBox[c+2]);t.setDirty()}else if(!e.panning&&this.isMouseOver){this.selectBox.enabled=!1;var f=i._size,h=this.xaxis.domain,p=this.yaxis.domain,d=(a=t.pick(o/t.pixelRatio+f.l+h[0]*f.w,l/t.pixelRatio-(f.t+(1-p[1])*f.h)))&&a.object._trace.handlePick(a);if(d&&n&&this.emitPointAction(d,"plotly_click"),a&&"skip"!==a.object._trace.hoverinfo&&i.hovermode&&d&&(!this.lastPickResult||this.lastPickResult.traceUid!==d.trace.uid||this.lastPickResult.dataCoord[0]!==d.dataCoord[0]||this.lastPickResult.dataCoord[1]!==d.dataCoord[1])){var v=d;this.lastPickResult={traceUid:d.trace?d.trace.uid:null,dataCoord:d.dataCoord.slice()},this.spikes.update({center:a.dataCoord}),v.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(a.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(a.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio],this.emitPointAction(d,"plotly_hover");var g=this.fullData[v.trace.index]||{},y=v.pointIndex,m=s.castHoverinfo(g,i,y);if(m&&"all"!==m){var x=m.split("+");-1===x.indexOf("x")&&(v.traceCoord[0]=void 0),-1===x.indexOf("y")&&(v.traceCoord[1]=void 0),-1===x.indexOf("z")&&(v.traceCoord[2]=void 0),-1===x.indexOf("text")&&(v.textLabel=void 0),-1===x.indexOf("name")&&(v.name=void 0)}s.loneHover({x:v.screenCoord[0],y:v.screenCoord[1],xLabel:this.hoverFormatter("xaxis",v.traceCoord[0]),yLabel:this.hoverFormatter("yaxis",v.traceCoord[1]),zLabel:v.traceCoord[2],text:v.textLabel,name:v.name,color:s.castHoverOption(g,y,"bgcolor")||v.color,borderColor:s.castHoverOption(g,y,"bordercolor"),fontFamily:s.castHoverOption(g,y,"font.family"),fontSize:s.castHoverOption(g,y,"font.size"),fontColor:s.castHoverOption(g,y,"font.color"),nameLength:s.castHoverOption(g,y,"namelength"),textAlign:s.castHoverOption(g,y,"align")},{container:this.svgContainer,gd:this.graphDiv})}}a||this.unhover(),t.draw()}},A.unhover=function(){this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,this.graphDiv.emit("plotly_unhover"),s.loneUnhover(this.svgContainer))},A.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return o.tickText(r,r.c2l(e),"hover").text}}},58547:function(t,e,r){"use strict";var n=r(30962).overrideAll,i=r(528),a=r(33539),o=r(27659).NG,s=r(71828),l=r(77922),u="gl3d",c="scene";e.name=u,e.attr=c,e.idRoot=c,e.idRegex=e.attrRegex=s.counterRegex("scene"),e.attributes=r(59084),e.layoutAttributes=r(65500),e.baseLayoutAttrOverrides=n({hoverlabel:i.hoverlabel},"plot","nested"),e.supplyLayoutDefaults=r(24682),e.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots[u],i=0;i<n.length;i++){var s=n[i],l=o(r,u,s),c=e[s],f=c.camera,h=c._scene;h||(h=new a({id:s,graphDiv:t,container:t.querySelector(".gl-container"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio,camera:f},e),c._scene=h),h.viewInitial||(h.viewInitial={up:{x:f.up.x,y:f.up.y,z:f.up.z},eye:{x:f.eye.x,y:f.eye.y,z:f.eye.z},center:{x:f.center.x,y:f.center.y,z:f.center.z}}),h.plot(l,e,t.layout)}},e.clean=function(t,e,r,n){for(var i=n._subplots[u]||[],a=0;a<i.length;a++){var o=i[a];!e[o]&&n[o]._scene&&(n[o]._scene.destroy(),n._infolayer&&n._infolayer.selectAll(".annotation-"+o).remove())}},e.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots[u],n=e._size,i=0;i<r.length;i++){var a=e[r[i]],o=a.domain,s=a._scene,c=s.toImage("png");e._glimages.append("svg:image").attr({xmlns:l.svg,"xlink:href":c,x:n.l+n.w*o.x[0],y:n.t+n.h*(1-o.y[1]),width:n.w*(o.x[1]-o.x[0]),height:n.h*(o.y[1]-o.y[0]),preserveAspectRatio:"none"}),s.destroy()}},e.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return"1"===e&&(e=""),c+e}},e.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots[u],n=0;n<r.length;n++)e[r[n]]._scene.updateFx(e.dragmode,e.hovermode)}},59084:function(t){"use strict";t.exports={scene:{valType:"subplotid",dflt:"scene",editType:"calc+clearAxisTypes"}}},77894:function(t,e,r){"use strict";var n=r(7901),i=r(13838),a=r(1426).extendFlat,o=r(30962).overrideAll;t.exports=o({visible:i.visible,showspikes:{valType:"boolean",dflt:!0},spikesides:{valType:"boolean",dflt:!0},spikethickness:{valType:"number",min:0,dflt:2},spikecolor:{valType:"color",dflt:n.defaultLine},showbackground:{valType:"boolean",dflt:!1},backgroundcolor:{valType:"color",dflt:"rgba(204, 204, 204, 0.5)"},showaxeslabels:{valType:"boolean",dflt:!0},color:i.color,categoryorder:i.categoryorder,categoryarray:i.categoryarray,title:{text:i.title.text,font:i.title.font},type:a({},i.type,{values:["-","linear","log","date","category"]}),autotypenumbers:i.autotypenumbers,autorange:i.autorange,rangemode:i.rangemode,range:a({},i.range,{items:[{valType:"any",editType:"plot",impliedEdits:{"^autorange":!1}},{valType:"any",editType:"plot",impliedEdits:{"^autorange":!1}}],anim:!1}),tickmode:i.minor.tickmode,nticks:i.nticks,tick0:i.tick0,dtick:i.dtick,tickvals:i.tickvals,ticktext:i.ticktext,ticks:i.ticks,mirror:i.mirror,ticklen:i.ticklen,tickwidth:i.tickwidth,tickcolor:i.tickcolor,showticklabels:i.showticklabels,labelalias:i.labelalias,tickfont:i.tickfont,tickangle:i.tickangle,tickprefix:i.tickprefix,showtickprefix:i.showtickprefix,ticksuffix:i.ticksuffix,showticksuffix:i.showticksuffix,showexponent:i.showexponent,exponentformat:i.exponentformat,minexponent:i.minexponent,separatethousands:i.separatethousands,tickformat:i.tickformat,tickformatstops:i.tickformatstops,hoverformat:i.hoverformat,showline:i.showline,linecolor:i.linecolor,linewidth:i.linewidth,showgrid:i.showgrid,gridcolor:a({},i.gridcolor,{dflt:"rgb(204, 204, 204)"}),gridwidth:i.gridwidth,zeroline:i.zeroline,zerolinecolor:i.zerolinecolor,zerolinewidth:i.zerolinewidth,_deprecated:{title:i._deprecated.title,titlefont:i._deprecated.titlefont}},"plot","from-root")},3277:function(t,e,r){"use strict";var n=r(84267).mix,i=r(71828),a=r(44467),o=r(77894),s=r(951),l=r(71453),u=["xaxis","yaxis","zaxis"];t.exports=function(t,e,r){var c,f;function h(t,e){return i.coerce(c,f,o,t,e)}for(var p=0;p<u.length;p++){var d=u[p];c=t[d]||{},(f=a.newContainer(e,d))._id=d[0]+r.scene,f._name=d,s(c,f,h,r),l(c,f,h,{font:r.font,letter:d[0],data:r.data,showGrid:!0,noTickson:!0,noTicklabelmode:!0,noTicklabelstep:!0,noTicklabelposition:!0,noTicklabeloverflow:!0,bgColor:r.bgColor,calendar:r.calendar},r.fullLayout),h("gridcolor",n(f.color,r.bgColor,72.72727272727273).toRgbString()),h("title.text",d[0]),f.setScale=i.noop,h("showspikes")&&(h("spikesides"),h("spikethickness"),h("spikecolor",f.color)),h("showaxeslabels"),h("showbackground")&&h("backgroundcolor")}}},30422:function(t,e,r){"use strict";var n=r(78614),i=r(71828),a=["xaxis","yaxis","zaxis"];function o(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=["sans-serif","sans-serif","sans-serif"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=["x","y","z"],this.labelEnable=[!0,!0,!0],this.labelFont=["Open Sans","Open Sans","Open Sans"],this.labelSize=[20,20,20],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=this.tickPad.slice(),this._defaultLabelPad=this.labelPad.slice(),this._defaultLineTickLength=this.lineTickLength.slice()}o.prototype.merge=function(t,e){for(var r=this,o=0;o<3;++o){var s=e[a[o]];s.visible?(r.labels[o]=t._meta?i.templateString(s.title.text,t._meta):s.title.text,"font"in s.title&&(s.title.font.color&&(r.labelColor[o]=n(s.title.font.color)),s.title.font.family&&(r.labelFont[o]=s.title.font.family),s.title.font.size&&(r.labelSize[o]=s.title.font.size)),"showline"in s&&(r.lineEnable[o]=s.showline),"linecolor"in s&&(r.lineColor[o]=n(s.linecolor)),"linewidth"in s&&(r.lineWidth[o]=s.linewidth),"showgrid"in s&&(r.gridEnable[o]=s.showgrid),"gridcolor"in s&&(r.gridColor[o]=n(s.gridcolor)),"gridwidth"in s&&(r.gridWidth[o]=s.gridwidth),"log"===s.type?r.zeroEnable[o]=!1:"zeroline"in s&&(r.zeroEnable[o]=s.zeroline),"zerolinecolor"in s&&(r.zeroLineColor[o]=n(s.zerolinecolor)),"zerolinewidth"in s&&(r.zeroLineWidth[o]=s.zerolinewidth),"ticks"in s&&s.ticks?r.lineTickEnable[o]=!0:r.lineTickEnable[o]=!1,"ticklen"in s&&(r.lineTickLength[o]=r._defaultLineTickLength[o]=s.ticklen),"tickcolor"in s&&(r.lineTickColor[o]=n(s.tickcolor)),"tickwidth"in s&&(r.lineTickWidth[o]=s.tickwidth),"tickangle"in s&&(r.tickAngle[o]="auto"===s.tickangle?-3600:Math.PI*-s.tickangle/180),"showticklabels"in s&&(r.tickEnable[o]=s.showticklabels),"tickfont"in s&&(s.tickfont.color&&(r.tickColor[o]=n(s.tickfont.color)),s.tickfont.family&&(r.tickFont[o]=s.tickfont.family),s.tickfont.size&&(r.tickSize[o]=s.tickfont.size)),"mirror"in s?-1!==["ticks","all","allticks"].indexOf(s.mirror)?(r.lineTickMirror[o]=!0,r.lineMirror[o]=!0):!0===s.mirror?(r.lineTickMirror[o]=!1,r.lineMirror[o]=!0):(r.lineTickMirror[o]=!1,r.lineMirror[o]=!1):r.lineMirror[o]=!1,"showbackground"in s&&!1!==s.showbackground?(r.backgroundEnable[o]=!0,r.backgroundColor[o]=n(s.backgroundcolor)):r.backgroundEnable[o]=!1):(r.tickEnable[o]=!1,r.labelEnable[o]=!1,r.lineEnable[o]=!1,r.lineTickEnable[o]=!1,r.gridEnable[o]=!1,r.zeroEnable[o]=!1,r.backgroundEnable[o]=!1)}},t.exports=function(t,e){var r=new o;return r.merge(t,e),r}},24682:function(t,e,r){"use strict";var n=r(71828),i=r(7901),a=r(73972),o=r(49119),s=r(3277),l=r(65500),u=r(27659).NG,c="gl3d";function f(t,e,r,n){for(var o=r("bgcolor"),l=i.combine(o,n.paper_bgcolor),f=["up","center","eye"],h=0;h<f.length;h++)r("camera."+f[h]+".x"),r("camera."+f[h]+".y"),r("camera."+f[h]+".z");r("camera.projection.type");var p=!!r("aspectratio.x")&&!!r("aspectratio.y")&&!!r("aspectratio.z"),d=r("aspectmode",p?"manual":"auto");p||(t.aspectratio=e.aspectratio={x:1,y:1,z:1},"manual"===d&&(e.aspectmode="auto"),t.aspectmode=e.aspectmode);var v=u(n.fullData,c,n.id);s(t,e,{font:n.font,scene:n.id,data:v,bgColor:l,calendar:n.calendar,autotypenumbersDflt:n.autotypenumbersDflt,fullLayout:n.fullLayout}),a.getComponentMethod("annotations3d","handleDefaults")(t,e,n);var g=n.getDfltFromLayout("dragmode");if(!1!==g&&!g)if(g="orbit",t.camera&&t.camera.up){var y=t.camera.up.x,m=t.camera.up.y,x=t.camera.up.z;0!==x&&(y&&m&&x?x/Math.sqrt(y*y+m*m+x*x)>.999&&(g="turntable"):g="turntable")}else g="turntable";r("dragmode",g),r("hovermode",n.getDfltFromLayout("hovermode"))}t.exports=function(t,e,r){var i=e._basePlotModules.length>1;o(t,e,r,{type:c,attributes:l,handleDefaults:f,fullLayout:e,font:e.font,fullData:r,getDfltFromLayout:function(e){if(!i)return n.validate(t[e],l[e])?t[e]:void 0},autotypenumbersDflt:e.autotypenumbers,paper_bgcolor:e.paper_bgcolor,calendar:e.calendar})}},65500:function(t,e,r){"use strict";var n=r(77894),i=r(27670).Y,a=r(1426).extendFlat,o=r(71828).counterRegex;function s(t,e,r){return{x:{valType:"number",dflt:t,editType:"camera"},y:{valType:"number",dflt:e,editType:"camera"},z:{valType:"number",dflt:r,editType:"camera"},editType:"camera"}}t.exports={_arrayAttrRegexps:[o("scene",".annotations",!0)],bgcolor:{valType:"color",dflt:"rgba(0,0,0,0)",editType:"plot"},camera:{up:a(s(0,0,1),{}),center:a(s(0,0,0),{}),eye:a(s(1.25,1.25,1.25),{}),projection:{type:{valType:"enumerated",values:["perspective","orthographic"],dflt:"perspective",editType:"calc"},editType:"calc"},editType:"camera"},domain:i({name:"scene",editType:"plot"}),aspectmode:{valType:"enumerated",values:["auto","cube","data","manual"],dflt:"auto",editType:"plot",impliedEdits:{"aspectratio.x":void 0,"aspectratio.y":void 0,"aspectratio.z":void 0}},aspectratio:{x:{valType:"number",min:0,editType:"plot",impliedEdits:{"^aspectmode":"manual"}},y:{valType:"number",min:0,editType:"plot",impliedEdits:{"^aspectmode":"manual"}},z:{valType:"number",min:0,editType:"plot",impliedEdits:{"^aspectmode":"manual"}},editType:"plot",impliedEdits:{aspectmode:"manual"}},xaxis:n,yaxis:n,zaxis:n,dragmode:{valType:"enumerated",values:["orbit","turntable","zoom","pan",!1],editType:"plot"},hovermode:{valType:"enumerated",values:["closest",!1],dflt:"closest",editType:"modebar"},uirevision:{valType:"any",editType:"none"},editType:"plot",_deprecated:{cameraposition:{valType:"info_array",editType:"camera"}}}},13133:function(t,e,r){"use strict";var n=r(78614),i=["xaxis","yaxis","zaxis"];function a(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}a.prototype.merge=function(t){for(var e=0;e<3;++e){var r=t[i[e]];r.visible?(this.enabled[e]=r.showspikes,this.colors[e]=n(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness):(this.enabled[e]=!1,this.drawSides[e]=!1)}},t.exports=function(t){var e=new a;return e.merge(t),e}},96085:function(t,e,r){"use strict";t.exports=function(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,s=t.fullSceneLayout,l=[[],[],[]],u=0;u<3;++u){var c=s[a[u]];if(c._length=(r[u].hi-r[u].lo)*r[u].pixelsPerDataUnit/t.dataScale[u],Math.abs(c._length)===1/0||isNaN(c._length))l[u]=[];else{c._input_range=c.range.slice(),c.range[0]=r[u].lo/t.dataScale[u],c.range[1]=r[u].hi/t.dataScale[u],c._m=1/(t.dataScale[u]*r[u].pixelsPerDataUnit),c.range[0]===c.range[1]&&(c.range[0]-=1,c.range[1]+=1);var f=c.tickmode;if("auto"===c.tickmode){c.tickmode="linear";var h=c.nticks||i.constrain(c._length/40,4,9);n.autoTicks(c,Math.abs(c.range[1]-c.range[0])/h)}for(var p=n.calcTicks(c,{msUTC:!0}),d=0;d<p.length;++d)p[d].x=p[d].x*t.dataScale[u],"date"===c.type&&(p[d].text=p[d].text.replace(/\<br\>/g," "));l[u]=p,c.tickmode=f}}for(e.ticks=l,u=0;u<3;++u)for(o[u]=.5*(t.glplot.bounds[0][u]+t.glplot.bounds[1][u]),d=0;d<2;++d)e.bounds[d][u]=t.glplot.bounds[d][u];t.contourLevels=function(t){for(var e=new Array(3),r=0;r<3;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}(l)};var n=r(89298),i=r(71828),a=["xaxis","yaxis","zaxis"],o=[0,0,0]},63538:function(t){"use strict";function e(t,e){var r,n,i=[0,0,0,0];for(r=0;r<4;++r)for(n=0;n<4;++n)i[n]+=t[4*r+n]*e[r];return i}t.exports=function(t,r){return e(t.projection,e(t.view,e(t.model,[r[0],r[1],r[2],1])))}},33539:function(t,e,r){"use strict";var n,i,a=r(9330).gl_plot3d,o=a.createCamera,s=a.createScene,l=r(40372),u=r(38520),c=r(73972),f=r(71828),h=f.preserveDrawingBuffer(),p=r(89298),d=r(30211),v=r(78614),g=r(58617),y=r(63538),m=r(30422),x=r(13133),b=r(96085),_=!1;function w(t,e){var r=document.createElement("div"),n=t.container;this.graphDiv=t.graphDiv;var i=document.createElementNS("http://www.w3.org/2000/svg","svg");i.style.position="absolute",i.style.top=i.style.left="0px",i.style.width=i.style.height="100%",i.style["z-index"]=20,i.style["pointer-events"]="none",r.appendChild(i),this.svgContainer=i,r.id=t.id,r.style.position="absolute",r.style.top=r.style.left="0px",r.style.width=r.style.height="100%",n.appendChild(r),this.fullLayout=e,this.id=t.id||"scene",this.fullSceneLayout=e[this.id],this.plotArgs=[[],{},{}],this.axesOptions=m(e,e[this.id]),this.spikeOptions=x(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=this.pixelRatio||t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],this.convertAnnotations=c.getComponentMethod("annotations3d","convert"),this.drawAnnotations=c.getComponentMethod("annotations3d","draw"),this.initializeGLPlot()}var T=w.prototype;T.prepareOptions=function(){var t=this,e={canvas:t.canvas,gl:t.gl,glOptions:{preserveDrawingBuffer:h,premultipliedAlpha:!0,antialias:!0},container:t.container,axes:t.axesOptions,spikes:t.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1,cameraObject:t.camera,pixelRatio:t.pixelRatio};if(t.staticMode){if(!(i||(n=document.createElement("canvas"),i=l({canvas:n,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}))))throw new Error("error creating static canvas/context for image server");e.gl=i,e.canvas=n}return e};var k=!0;T.tryCreatePlot=function(){var t=this,e=t.prepareOptions(),r=!0;try{t.glplot=s(e)}catch(n){if(t.staticMode||!k||h)r=!1;else{f.warn(["webgl setup failed possibly due to","false preserveDrawingBuffer config.","The mobile/tablet device may not be detected by is-mobile module.","Enabling preserveDrawingBuffer in second attempt to create webgl scene..."].join(" "));try{h=e.glOptions.preserveDrawingBuffer=!0,t.glplot=s(e)}catch(t){h=e.glOptions.preserveDrawingBuffer=!1,r=!1}}}return k=!1,r},T.initializeGLCamera=function(){var t=this,e=t.fullSceneLayout.camera,r="orthographic"===e.projection.type;t.camera=o(t.container,{center:[e.center.x,e.center.y,e.center.z],eye:[e.eye.x,e.eye.y,e.eye.z],up:[e.up.x,e.up.y,e.up.z],_ortho:r,zoomMin:.01,zoomMax:100,mode:"orbit"})},T.initializeGLPlot=function(){var t=this;if(t.initializeGLCamera(),!t.tryCreatePlot())return g(t);t.traces={},t.make4thDimension();var e=t.graphDiv,r=e.layout,n=function(){var e={};return t.isCameraChanged(r)&&(e[t.id+".camera"]=t.getCamera()),t.isAspectChanged(r)&&(e[t.id+".aspectratio"]=t.glplot.getAspectratio(),"manual"!==r[t.id].aspectmode&&(t.fullSceneLayout.aspectmode=r[t.id].aspectmode=e[t.id+".aspectmode"]="manual")),e},i=function(t){if(!1!==t.fullSceneLayout.dragmode){var e=n();t.saveLayout(r),t.graphDiv.emit("plotly_relayout",e)}};return t.glplot.canvas&&(t.glplot.canvas.addEventListener("mouseup",(function(){i(t)})),t.glplot.canvas.addEventListener("touchstart",(function(){_=!0})),t.glplot.canvas.addEventListener("wheel",(function(r){if(e._context._scrollZoom.gl3d){if(t.camera._ortho){var n=r.deltaX>r.deltaY?1.1:1/1.1,a=t.glplot.getAspectratio();t.glplot.setAspectratio({x:n*a.x,y:n*a.y,z:n*a.z})}i(t)}}),!!u&&{passive:!1}),t.glplot.canvas.addEventListener("mousemove",(function(){if(!1!==t.fullSceneLayout.dragmode&&0!==t.camera.mouseListener.buttons){var e=n();t.graphDiv.emit("plotly_relayouting",e)}})),t.staticMode||t.glplot.canvas.addEventListener("webglcontextlost",(function(r){e&&e.emit&&e.emit("plotly_webglcontextlost",{event:r,layer:t.id})}),!1)),t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=function(){t.render()},!0},T.render=function(){var t,e=this,r=e.graphDiv,n=e.svgContainer,i=e.container.getBoundingClientRect();r._fullLayout._calcInverseTransform(r);var 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e=function(){t.glplot.gl.isContextLost()?requestAnimationFrame(e):t.initializeGLPlot()?t.plot.apply(t,t.plotArgs):f.error("Catastrophic and unrecoverable WebGL error. 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T=b[s],k=T.bounds,S=T._trace.data._pad||0;"ErrorBars"===T.constructor.name&&l._lowerLogErrorBound?y[0][o]=Math.min(y[0][o],l._lowerLogErrorBound):y[0][o]=Math.min(y[0][o],k[0][o]/p[o]-S),y[1][o]=Math.max(y[1][o],k[1][o]/p[o]+S)}for(s=0;s<_.length;s++){var E=_[s];if(E.visible){var L=l.r2l(E[w]);y[0][o]=Math.min(y[0][o],L),y[1][o]=Math.max(y[1][o],L)}}if("rangemode"in l&&"tozero"===l.rangemode&&(y[0][o]=Math.min(y[0][o],0),y[1][o]=Math.max(y[1][o],0)),y[0][o]>y[1][o])y[0][o]=-1,y[1][o]=1;else{var C=y[1][o]-y[0][o];y[0][o]-=C/32,y[1][o]+=C/32}if("reversed"===l.autorange){var P=y[0][o];y[0][o]=y[1][o],y[1][o]=P}}else{var O=l.range;y[0][o]=l.r2l(O[0]),y[1][o]=l.r2l(O[1])}y[0][o]===y[1][o]&&(y[0][o]-=1,y[1][o]+=1),m[o]=y[1][o]-y[0][o],n.glplot.setBounds(o,{min:y[0][o]*p[o],max:y[1][o]*p[o]})}var I=c.aspectmode;if("cube"===I)g=[1,1,1];else if("manual"===I){var D=c.aspectratio;g=[D.x,D.y,D.z]}else{if("auto"!==I&&"data"!==I)throw new Error("scene.js aspectRatio was not one of the enumerated 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t=this;t.glplot&&(t.camera.mouseListener.enabled=!1,t.container.removeEventListener("wheel",t.camera.wheelListener),t.camera=null,t.glplot.dispose(),t.container.parentNode.removeChild(t.container),t.glplot=null)},T.getCamera=function(){var t,e=this;return e.camera.view.recalcMatrix(e.camera.view.lastT()),{up:{x:(t=e.camera).up[0],y:t.up[1],z:t.up[2]},center:{x:t.center[0],y:t.center[1],z:t.center[2]},eye:{x:t.eye[0],y:t.eye[1],z:t.eye[2]},projection:{type:!0===t._ortho?"orthographic":"perspective"}}},T.setViewport=function(t){var e,r=this,n=t.camera;r.camera.lookAt.apply(this,[[(e=n).eye.x,e.eye.y,e.eye.z],[e.center.x,e.center.y,e.center.z],[e.up.x,e.up.y,e.up.z]]),r.glplot.setAspectratio(t.aspectratio),"orthographic"===n.projection.type!==r.camera._ortho&&(r.glplot.redraw(),r.glplot.clearRGBA(),r.glplot.dispose(),r.initializeGLPlot())},T.isCameraChanged=function(t){var e=this.getCamera(),r=f.nestedProperty(t,this.id+".camera").get();function n(t,e,r,n){var 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Y=_.selectAll("g.gauge-outline").data([x]);Y.enter().append("g").classed("gauge-outline",!0).append("path"),Y.select("path").call(P).call(T),Y.exit().remove()}(t,0,e,{radius:U,innerRadius:V,gauge:Z,layer:Y,size:B,gaugeBg:C,gaugeOutline:P,transitionOpts:r,onComplete:g});var W=I.selectAll("g.bullet").data(R?e:[]);W.exit().remove();var X=I.selectAll("g.bulletaxis").data(R?e:[]);X.exit().remove(),R&&function(t,e,r,n){var i,a,o,s,u,c=r[0].trace,f=n.gauge,p=n.layer,v=n.gaugeBg,g=n.gaugeOutline,y=n.size,x=c.domain,b=n.transitionOpts,_=n.onComplete;f.enter().append("g").classed("bullet",!0),f.attr("transform",l(y.l,y.t)),p.enter().append("g").classed("bulletaxis",!0).classed("crisp",!0),p.selectAll("g.xbulletaxistick,path,text").remove();var A=y.h,M=c.gauge.bar.thickness*A,S=x.x[0],E=x.x[0]+(x.x[1]-x.x[0])*(c._hasNumber||c._hasDelta?1-h.bulletNumberDomainSize:1);function L(t){t.attr("width",(function(t){return Math.max(0,i.c2p(t.range[1])-i.c2p(t.range[0]))})).attr("x",(function(t){return 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0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})).each((function(t){u.font(n.select(this),t.parcatsViewModel.labelfont)})),M.selectAll("rect.bandrect").on("mouseover",L).on("mouseout",C),M.exit().remove(),A.call(n.behavior.drag().origin((function(t){return{x:t.x,y:0}})).on("dragstart",P).on("drag",O).on("dragend",I)),h.each((function(t){t.traceSelection=n.select(this),t.pathSelection=n.select(this).selectAll("g.paths").selectAll("path.path"),t.dimensionSelection=n.select(this).selectAll("g.dimensions").selectAll("g.dimension")})),h.exit().remove()}function p(t){return t.key}function d(t){var e=t.parcatsViewModel.dimensions.length,r=t.parcatsViewModel.dimensions[e-1].model.dimensionInd;return t.model.dimensionInd===r}function v(t,e){return t.model.rawColor>e.model.rawColor?1:t.model.rawColor<e.model.rawColor?-1:0}function g(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf("skip")){s.raiseToTop(this),w(n.select(this));var e=m(t),r=x(t);if(t.parcatsViewModel.graphDiv.emit("plotly_hover",{points:e,event:n.event,constraints:r}),-1===t.parcatsViewModel.hoverinfoItems.indexOf("none")){var i,a,l,u=n.mouse(this)[0],f=t.parcatsViewModel.graphDiv,h=t.parcatsViewModel.trace,p=f._fullLayout,d=p._paperdiv.node().getBoundingClientRect(),v=t.parcatsViewModel.graphDiv.getBoundingClientRect();for(l=0;l<t.leftXs.length-1;l++)if(t.leftXs[l]+t.dimWidths[l]-2<=u&&u<=t.leftXs[l+1]+2){var g=t.parcatsViewModel.dimensions[l],y=t.parcatsViewModel.dimensions[l+1];i=(g.x+g.width+y.x)/2,a=(t.topYs[l]+t.topYs[l+1]+t.height)/2;break}var b=t.parcatsViewModel.x+i,_=t.parcatsViewModel.y+a,T=c.mostReadable(t.model.color,["black","white"]),k=t.model.count,A=k/t.parcatsViewModel.model.count,M={countLabel:k,probabilityLabel:A.toFixed(3)},S=[];-1!==t.parcatsViewModel.hoverinfoItems.indexOf("count")&&S.push(["Count:",M.countLabel].join(" ")),-1!==t.parcatsViewModel.hoverinfoItems.indexOf("probability")&&S.push(["P:",M.probabilityLabel].join(" "));var E=S.join("<br>"),L=n.mouse(f)[0];o.loneHover({trace:h,x:b-d.left+v.left,y:_-d.top+v.top,text:E,color:t.model.color,borderColor:"black",fontFamily:'Monaco, "Courier New", monospace',fontSize:10,fontColor:T,idealAlign:L<b?"right":"left",hovertemplate:(h.line||{}).hovertemplate,hovertemplateLabels:M,eventData:[{data:h._input,fullData:h,count:k,probability:A}]},{container:p._hoverlayer.node(),outerContainer:p._paper.node(),gd:f})}}}function y(t){if(!t.parcatsViewModel.dragDimension&&(_(n.select(this)),o.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()),t.parcatsViewModel.pathSelection.sort(v),-1===t.parcatsViewModel.hoverinfoItems.indexOf("skip"))){var e=m(t),r=x(t);t.parcatsViewModel.graphDiv.emit("plotly_unhover",{points:e,event:n.event,constraints:r})}}function m(t){for(var e=[],r=D(t.parcatsViewModel),n=0;n<t.model.valueInds.length;n++){var i=t.model.valueInds[n];e.push({curveNumber:r,pointNumber:i})}return e}function x(t){for(var e={},r=t.parcatsViewModel.model.dimensions,n=0;n<r.length;n++){var i=r[n],a=i.categories[t.model.categoryInds[n]];e[i.containerInd]=a.categoryValue}return void 0!==t.model.rawColor&&(e.color=t.model.rawColor),e}function b(t){if(-1===t.parcatsViewModel.hoverinfoItems.indexOf("skip")){var e=m(t),r=x(t);t.parcatsViewModel.graphDiv.emit("plotly_click",{points:e,event:n.event,constraints:r})}}function _(t){t.attr("fill",(function(t){return t.model.color})).attr("fill-opacity",.6).attr("stroke","lightgray").attr("stroke-width",.2).attr("stroke-opacity",1)}function w(t){t.attr("fill-opacity",.8).attr("stroke",(function(t){return c.mostReadable(t.model.color,["black","white"])})).attr("stroke-width",.3)}function T(t){t.select("rect.catrect").attr("stroke","black").attr("stroke-width",1).attr("stroke-opacity",1)}function k(t){t.attr("stroke","black").attr("stroke-width",.2).attr("stroke-opacity",1).attr("fill-opacity",1)}function A(t){var e=t.parcatsViewModel.pathSelection,r=t.categoryViewModel.model.dimensionInd,n=t.categoryViewModel.model.categoryInd;return e.filter((function(e){return e.model.categoryInds[r]===n&&e.model.color===t.color}))}function M(t,e,r){var i=n.select(t).datum(),a=i.categoryViewModel.model,o=i.parcatsViewModel.graphDiv,s=n.select(t.parentNode).selectAll("rect.bandrect"),l=[];s.each((function(t){A(t).each((function(t){Array.prototype.push.apply(l,m(t))}))}));var u={};u[a.dimensionInd]=a.categoryValue,o.emit(e,{points:l,event:r,constraints:u})}function S(t,e,r){var i=n.select(t).datum(),a=i.categoryViewModel.model,o=i.parcatsViewModel.graphDiv,s=A(i),l=[];s.each((function(t){Array.prototype.push.apply(l,m(t))}));var u={};u[a.dimensionInd]=a.categoryValue,void 0!==i.rawColor&&(u.color=i.rawColor),o.emit(e,{points:l,event:r,constraints:u})}function E(t,e,r){t._fullLayout._calcInverseTransform(t);var i,a,o=t._fullLayout._invScaleX,s=t._fullLayout._invScaleY,l=n.select(r.parentNode).select("rect.catrect"),u=l.node().getBoundingClientRect(),c=l.datum(),f=c.parcatsViewModel,h=f.model.dimensions[c.model.dimensionInd],p=f.trace,d=u.top+u.height/2;f.dimensions.length>1&&h.displayInd===f.dimensions.length-1?(i=u.left,a="left"):(i=u.left+u.width,a="right");var v=c.model.count,g=c.model.categoryLabel,y=v/c.parcatsViewModel.model.count,m={countLabel:v,categoryLabel:g,probabilityLabel:y.toFixed(3)},x=[];-1!==c.parcatsViewModel.hoverinfoItems.indexOf("count")&&x.push(["Count:",m.countLabel].join(" ")),-1!==c.parcatsViewModel.hoverinfoItems.indexOf("probability")&&x.push(["P("+m.categoryLabel+"):",m.probabilityLabel].join(" "));var b=x.join("<br>");return{trace:p,x:o*(i-e.left),y:s*(d-e.top),text:b,color:"lightgray",borderColor:"black",fontFamily:'Monaco, "Courier New", monospace',fontSize:12,fontColor:"black",idealAlign:a,hovertemplate:p.hovertemplate,hovertemplateLabels:m,eventData:[{data:p._input,fullData:p,count:v,category:g,probability:y}]}}function L(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf("skip")){if(n.mouse(this)[1]<-1)return;var e,r=t.parcatsViewModel.graphDiv,i=r._fullLayout,a=i._paperdiv.node().getBoundingClientRect(),l=t.parcatsViewModel.hoveron,u=this;"color"===l?(function(t){var e=n.select(t).datum(),r=A(e);w(r),r.each((function(){s.raiseToTop(this)})),n.select(t.parentNode).selectAll("rect.bandrect").filter((function(t){return t.color===e.color})).each((function(){s.raiseToTop(this),n.select(this).attr("stroke","black").attr("stroke-width",1.5)}))}(u),S(u,"plotly_hover",n.event)):(function(t){n.select(t.parentNode).selectAll("rect.bandrect").each((function(t){var e=A(t);w(e),e.each((function(){s.raiseToTop(this)}))})),n.select(t.parentNode).select("rect.catrect").attr("stroke","black").attr("stroke-width",2.5)}(u),M(u,"plotly_hover",n.event)),-1===t.parcatsViewModel.hoverinfoItems.indexOf("none")&&("category"===l?e=E(r,a,u):"color"===l?e=function(t,e,r){t._fullLayout._calcInverseTransform(t);var i,a,o=t._fullLayout._invScaleX,s=t._fullLayout._invScaleY,l=r.getBoundingClientRect(),u=n.select(r).datum(),f=u.categoryViewModel,h=f.parcatsViewModel,p=h.model.dimensions[f.model.dimensionInd],d=h.trace,v=l.y+l.height/2;h.dimensions.length>1&&p.displayInd===h.dimensions.length-1?(i=l.left,a="left"):(i=l.left+l.width,a="right");var g=f.model.categoryLabel,y=u.parcatsViewModel.model.count,m=0;u.categoryViewModel.bands.forEach((function(t){t.color===u.color&&(m+=t.count)}));var x=f.model.count,b=0;h.pathSelection.each((function(t){t.model.color===u.color&&(b+=t.model.count)}));var _=m/y,w=m/b,T=m/x,k={countLabel:y,categoryLabel:g,probabilityLabel:_.toFixed(3)},A=[];-1!==f.parcatsViewModel.hoverinfoItems.indexOf("count")&&A.push(["Count:",k.countLabel].join(" ")),-1!==f.parcatsViewModel.hoverinfoItems.indexOf("probability")&&(A.push("P(color ∩ "+g+"): "+k.probabilityLabel),A.push("P("+g+" | color): "+w.toFixed(3)),A.push("P(color | "+g+"): "+T.toFixed(3)));var M=A.join("<br>"),S=c.mostReadable(u.color,["black","white"]);return{trace:d,x:o*(i-e.left),y:s*(v-e.top),text:M,color:u.color,borderColor:"black",fontFamily:'Monaco, "Courier New", monospace',fontColor:S,fontSize:10,idealAlign:a,hovertemplate:d.hovertemplate,hovertemplateLabels:k,eventData:[{data:d._input,fullData:d,category:g,count:y,probability:_,categorycount:x,colorcount:b,bandcolorcount:m}]}}(r,a,u):"dimension"===l&&(e=function(t,e,r){var i=[];return n.select(r.parentNode.parentNode).selectAll("g.category").select("rect.catrect").each((function(){i.push(E(t,e,this))})),i}(r,a,u)),e&&o.loneHover(e,{container:i._hoverlayer.node(),outerContainer:i._paper.node(),gd:r}))}}function C(t){var e=t.parcatsViewModel;e.dragDimension||(_(e.pathSelection),T(e.dimensionSelection.selectAll("g.category")),k(e.dimensionSelection.selectAll("g.category").selectAll("rect.bandrect")),o.loneUnhover(e.graphDiv._fullLayout._hoverlayer.node()),e.pathSelection.sort(v),-1!==e.hoverinfoItems.indexOf("skip"))||("color"===t.parcatsViewModel.hoveron?S(this,"plotly_unhover",n.event):M(this,"plotly_unhover",n.event))}function P(t){"fixed"!==t.parcatsViewModel.arrangement&&(t.dragDimensionDisplayInd=t.model.displayInd,t.initialDragDimensionDisplayInds=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),t.dragHasMoved=!1,t.dragCategoryDisplayInd=null,n.select(this).selectAll("g.category").select("rect.catrect").each((function(e){var r=n.mouse(this)[0],i=n.mouse(this)[1];-2<=r&&r<=e.width+2&&-2<=i&&i<=e.height+2&&(t.dragCategoryDisplayInd=e.model.displayInd,t.initialDragCategoryDisplayInds=t.model.categories.map((function(t){return t.displayInd})),e.model.dragY=e.y,s.raiseToTop(this.parentNode),n.select(this.parentNode).selectAll("rect.bandrect").each((function(e){e.y<i&&i<=e.y+e.height&&(t.potentialClickBand=this)})))})),t.parcatsViewModel.dragDimension=t,o.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()))}function O(t){if("fixed"!==t.parcatsViewModel.arrangement&&(t.dragHasMoved=!0,null!==t.dragDimensionDisplayInd)){var e=t.dragDimensionDisplayInd,r=e-1,i=e+1,a=t.parcatsViewModel.dimensions[e];if(null!==t.dragCategoryDisplayInd){var o=a.categories[t.dragCategoryDisplayInd];o.model.dragY+=n.event.dy;var s=o.model.dragY,l=o.model.displayInd,u=a.categories,c=u[l-1],f=u[l+1];void 0!==c&&s<c.y+c.height/2&&(o.model.displayInd=c.model.displayInd,c.model.displayInd=l),void 0!==f&&s+o.height>f.y+f.height/2&&(o.model.displayInd=f.model.displayInd,f.model.displayInd=l),t.dragCategoryDisplayInd=o.model.displayInd}if(null===t.dragCategoryDisplayInd||"freeform"===t.parcatsViewModel.arrangement){a.model.dragX=n.event.x;var h=t.parcatsViewModel.dimensions[r],p=t.parcatsViewModel.dimensions[i];void 0!==h&&a.model.dragX<h.x+h.width&&(a.model.displayInd=h.model.displayInd,h.model.displayInd=e),void 0!==p&&a.model.dragX+a.width>p.x&&(a.model.displayInd=p.model.displayInd,p.model.displayInd=t.dragDimensionDisplayInd),t.dragDimensionDisplayInd=a.model.displayInd}j(t.parcatsViewModel),N(t.parcatsViewModel),R(t.parcatsViewModel),z(t.parcatsViewModel)}}function I(t){if("fixed"!==t.parcatsViewModel.arrangement&&null!==t.dragDimensionDisplayInd){n.select(this).selectAll("text").attr("font-weight","normal");var e={},r=D(t.parcatsViewModel),i=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),o=t.initialDragDimensionDisplayInds.some((function(t,e){return t!==i[e]}));o&&i.forEach((function(r,n){var i=t.parcatsViewModel.model.dimensions[n].containerInd;e["dimensions["+i+"].displayindex"]=r}));var s=!1;if(null!==t.dragCategoryDisplayInd){var l=t.model.categories.map((function(t){return t.displayInd}));if(s=t.initialDragCategoryDisplayInds.some((function(t,e){return t!==l[e]}))){var u=t.model.categories.slice().sort((function(t,e){return t.displayInd-e.displayInd})),c=u.map((function(t){return t.categoryValue})),f=u.map((function(t){return t.categoryLabel}));e["dimensions["+t.model.containerInd+"].categoryarray"]=[c],e["dimensions["+t.model.containerInd+"].ticktext"]=[f],e["dimensions["+t.model.containerInd+"].categoryorder"]="array"}}-1===t.parcatsViewModel.hoverinfoItems.indexOf("skip")&&!t.dragHasMoved&&t.potentialClickBand&&("color"===t.parcatsViewModel.hoveron?S(t.potentialClickBand,"plotly_click",n.event.sourceEvent):M(t.potentialClickBand,"plotly_click",n.event.sourceEvent)),t.model.dragX=null,null!==t.dragCategoryDisplayInd&&(t.parcatsViewModel.dimensions[t.dragDimensionDisplayInd].categories[t.dragCategoryDisplayInd].model.dragY=null,t.dragCategoryDisplayInd=null),t.dragDimensionDisplayInd=null,t.parcatsViewModel.dragDimension=null,t.dragHasMoved=null,t.potentialClickBand=null,j(t.parcatsViewModel),N(t.parcatsViewModel),n.transition().duration(300).ease("cubic-in-out").each((function(){R(t.parcatsViewModel,!0),z(t.parcatsViewModel,!0)})).each("end",(function(){(o||s)&&a.restyle(t.parcatsViewModel.graphDiv,e,[r])}))}}function 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e,r;d(t)?(e=t.width+5,r="start"):(e=-5,r="end"),n.select(this).selectAll("tspan").attr("x",e).attr("text-anchor",r)}));var a=i.selectAll("rect.bandrect").data((function(t){return t.bands}),p),o=a.enter().append("rect").attr("class","bandrect").attr("cursor","move").attr("stroke-opacity",0).attr("fill",(function(t){return t.color})).attr("fill-opacity",0);a.attr("fill",(function(t){return t.color})).attr("width",(function(t){return t.width})).attr("height",(function(t){return t.height})).attr("y",(function(t){return t.y})),k(o),a.each((function(){s.raiseToTop(this)})),a.exit().remove()}function F(t,e,r){var n,i=r[0],a=e.margin||{l:80,r:80,t:100,b:80},o=i.trace,s=o.domain,l=e.width,u=e.height,c=Math.floor(l*(s.x[1]-s.x[0])),f=Math.floor(u*(s.y[1]-s.y[0])),h=s.x[0]*l+a.l,p=e.height-s.y[1]*e.height+a.t,d=o.line.shape;n="all"===o.hoverinfo?["count","probability"]:(o.hoverinfo||"").split("+");var v={trace:o,key:o.uid,model:i,x:h,y:p,width:c,height:f,hoveron:o.hoveron,hoverinfoItems:n,arrangement:o.arrangement,bundlecolors:o.bundlecolors,sortpaths:o.sortpaths,labelfont:o.labelfont,categorylabelfont:o.tickfont,pathShape:d,dragDimension:null,margin:a,paths:[],dimensions:[],graphDiv:t,traceSelection:null,pathSelection:null,dimensionSelection:null};return i.dimensions&&(j(v),N(v)),v}function B(t,e,r,n,a){var o,s,l=[],u=[];for(s=0;s<r.length-1;s++)o=i(r[s]+t[s],t[s+1]),l.push(o(a)),u.push(o(1-a));var c="M "+t[0]+","+e[0];for(c+="l"+r[0]+",0 ",s=1;s<r.length;s++)c+="C"+l[s-1]+","+e[s-1]+" "+u[s-1]+","+e[s]+" "+t[s]+","+e[s],c+="l"+r[s]+",0 ";for(c+="l0,"+n+" ",c+="l -"+r[r.length-1]+",0 ",s=r.length-2;s>=0;s--)c+="C"+u[s]+","+(e[s+1]+n)+" "+l[s]+","+(e[s]+n)+" "+(t[s]+r[s])+","+(e[s]+n),c+="l-"+r[s]+",0 ";return c+"Z"}function N(t){var e=t.dimensions,r=t.model,n=e.map((function(t){return t.categories.map((function(t){return t.y}))})),i=t.model.dimensions.map((function(t){return t.categories.map((function(t){return t.displayInd}))})),a=t.model.dimensions.map((function(t){return t.displayInd})),o=t.dimensions.map((function(t){return t.model.dimensionInd})),s=e.map((function(t){return t.x})),l=e.map((function(t){return t.width})),u=[];for(var c in r.paths)r.paths.hasOwnProperty(c)&&u.push(r.paths[c]);function f(t){var e=t.categoryInds.map((function(t,e){return i[e][t]}));return o.map((function(t){return e[t]}))}u.sort((function(e,r){var n=f(e),i=f(r);return"backward"===t.sortpaths&&(n.reverse(),i.reverse()),n.push(e.valueInds[0]),i.push(r.valueInds[0]),t.bundlecolors&&(n.unshift(e.rawColor),i.unshift(r.rawColor)),n<i?-1:n>i?1:0}));for(var h=new Array(u.length),p=e[0].model.count,d=e[0].categories.map((function(t){return t.height})).reduce((function(t,e){return t+e})),v=0;v<u.length;v++){var g,y=u[v];g=p>0?d*(y.count/p):0;for(var m,x=new Array(n.length),b=0;b<y.categoryInds.length;b++){var _=y.categoryInds[b],w=i[b][_],T=a[b];x[T]=n[T][w],n[T][w]+=g;var 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n=r(50693),i=r(13838),a=r(41940),o=r(27670).Y,s=r(1426).extendFlat,l=r(44467).templatedArray;t.exports={domain:o({name:"parcoords",trace:!0,editType:"plot"}),labelangle:{valType:"angle",dflt:0,editType:"plot"},labelside:{valType:"enumerated",values:["top","bottom"],dflt:"top",editType:"plot"},labelfont:a({editType:"plot"}),tickfont:a({editType:"plot"}),rangefont:a({editType:"plot"}),dimensions:l("dimension",{label:{valType:"string",editType:"plot"},tickvals:s({},i.tickvals,{editType:"plot"}),ticktext:s({},i.ticktext,{editType:"plot"}),tickformat:s({},i.tickformat,{editType:"plot"}),visible:{valType:"boolean",dflt:!0,editType:"plot"},range:{valType:"info_array",items:[{valType:"number",editType:"plot"},{valType:"number",editType:"plot"}],editType:"plot"},constraintrange:{valType:"info_array",freeLength:!0,dimensions:"1-2",items:[{valType:"any",editType:"plot"},{valType:"any",editType:"plot"}],editType:"plot"},multiselect:{valType:"boolean",dflt:!0,editType:"plot"},values:{valType:"data_array",editType:"calc"},editType:"calc"}),line:s({editType:"calc"},n("line",{colorscaleDflt:"Viridis",autoColorDflt:!1,editTypeOverride:"calc"})),unselected:{line:{color:{valType:"color",dflt:"#7f7f7f",editType:"plot"},opacity:{valType:"number",min:0,max:1,dflt:"auto",editType:"plot"},editType:"plot"},editType:"plot"}}},57920:function(t,e,r){"use 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k(t){t.on("mousemove",(function(t){i.event.preventDefault(),t.parent.inBrushDrag||T(this,t)})).on("mouseleave",(function(t){t.parent.inBrushDrag||m()})).call(i.behavior.drag().on("dragstart",(function(t){!function(t,e){i.event.sourceEvent.stopPropagation();var r=e.height-i.mouse(t)[1]-2*n.verticalPadding,a=e.unitToPaddedPx.invert(r),o=e.brush,s=_(e,r),l=s.interval,u=o.svgBrush;if(u.wasDragged=!1,u.grabbingBar="ns"===s.region,u.grabbingBar){var c=l.map(e.unitToPaddedPx);u.grabPoint=r-c[0]-n.verticalPadding,u.barLength=c[1]-c[0]}u.clickableOrdinalRange=s.clickableOrdinalRange,u.stayingIntervals=e.multiselect&&o.filterSpecified?o.filter.getConsolidated():[],l&&(u.stayingIntervals=u.stayingIntervals.filter((function(t){return t[0]!==l[0]&&t[1]!==l[1]}))),u.startExtent=s.region?l["s"===s.region?1:0]:a,e.parent.inBrushDrag=!0,u.brushStartCallback()}(this,t)})).on("drag",(function(t){w(this,t)})).on("dragend",(function(t){!function(t,e){var 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u=t.selectAll(".highlight").data(o);u.enter().append("line").classed("highlight",!0).attr("x",-n.bar.width/2).attr("stroke-width",n.bar.width-n.bar.strokeWidth).attr("stroke",n.bar.fillColor).attr("opacity",n.bar.fillOpacity).attr("stroke-linecap","butt"),u.attr("y1",(function(t){return t.height})).call(x)}(i,e,r)},cleanRanges:function(t,e){if(Array.isArray(t[0])?(t=t.map((function(t){return t.sort(s)})),t=e.multiselect?S(t.sort(A)):[t[0]]):t=[t.sort(s)],e.tickvals){var r=e.tickvals.slice().sort(s);if(!(t=t.map((function(t){var e=[p(0,r,t[0],[]),p(1,r,t[1],[])];if(e[1]>e[0])return e})).filter((function(t){return t}))).length)return}return t.length>1?t:t[0]}}},71791:function(t,e,r){"use strict";t.exports={attributes:r(73362),supplyDefaults:r(3633),calc:r(24639),colorbar:{container:"line",min:"cmin",max:"cmax"},moduleType:"trace",name:"parcoords",basePlotModule:r(49351),categories:["gl","regl","noOpacity","noHover"],meta:{}}},49351:function(t,e,r){"use strict";var n=r(39898),i=r(27659).a0,a=r(21341),o=r(77922);e.name="parcoords",e.plot=function(t){var e=i(t.calcdata,"parcoords")[0];e.length&&a(t,e)},e.clean=function(t,e,r,n){var i=n._has&&n._has("parcoords"),a=e._has&&e._has("parcoords");i&&!a&&(n._paperdiv.selectAll(".parcoords").remove(),n._glimages.selectAll("*").remove())},e.toSVG=function(t){var e=t._fullLayout._glimages,r=n.select(t).selectAll(".svg-container");r.filter((function(t,e){return e===r.size()-1})).selectAll(".gl-canvas-context, .gl-canvas-focus").each((function(){var t=this,r=t.toDataURL("image/png");e.append("svg:image").attr({xmlns:o.svg,"xlink:href":r,preserveAspectRatio:"none",x:0,y:0,width:t.style.width,height:t.style.height})})),window.setTimeout((function(){n.selectAll("#filterBarPattern").attr("id","filterBarPattern")}),60)}},24639:function(t,e,r){"use strict";var n=r(71828).isArrayOrTypedArray,i=r(21081),a=r(28984).wrap;t.exports=function(t,e){var r,o;return i.hasColorscale(e,"line")&&n(e.line.color)?(r=e.line.color,o=i.extractOpts(e.line).colorscale,i.calc(t,e,{vals:r,containerStr:"line",cLetter:"c"})):(r=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=.5;return e}(e._length),o=[[0,e.line.color],[1,e.line.color]]),a({lineColor:r,cscale:o})}},25706:function(t){"use 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n=r(71828),i=r(52075).hasColorscale,a=r(1586),o=r(27670).c,s=r(85501),l=r(89298),u=r(73362),c=r(57920),f=r(25706).maxDimensionCount,h=r(94397);function p(t,e,r,i){function a(r,i){return n.coerce(t,e,u.dimensions,r,i)}var o=a("values"),s=a("visible");if(o&&o.length||(s=e.visible=!1),s){a("label"),a("tickvals"),a("ticktext"),a("tickformat");var f=a("range");e._ax={_id:"y",type:"linear",showexponent:"all",exponentformat:"B",range:f},l.setConvert(e._ax,i.layout),a("multiselect");var h=a("constraintrange");h&&(e.constraintrange=c.cleanRanges(h,e))}}t.exports=function(t,e,r,l){function c(r,i){return n.coerce(t,e,u,r,i)}var d=t.dimensions;Array.isArray(d)&&d.length>f&&(n.log("parcoords traces support up to "+f+" dimensions at the moment"),d.splice(f));var v=s(t,e,{name:"dimensions",layout:l,handleItemDefaults:p}),g=function(t,e,r,o,s){var l=s("line.color",r);if(i(t,"line")&&n.isArrayOrTypedArray(l)){if(l.length)return 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p33_36, p37_40, p41_44, p45_48,\n               p49_52, p53_56, p57_60, colors;\n\nuniform mat4 dim0A, dim1A, dim0B, dim1B, dim0C, dim1C, dim0D, dim1D,\n             loA, hiA, loB, hiB, loC, hiC, loD, hiD;\n\nuniform vec2 resolution, viewBoxPos, viewBoxSize;\nuniform float maskHeight;\nuniform float drwLayer; // 0: context, 1: focus, 2: pick\nuniform vec4 contextColor;\nuniform sampler2D maskTexture, palette;\n\nbool isPick    = (drwLayer > 1.5);\nbool isContext = (drwLayer < 0.5);\n\nconst vec4 ZEROS = vec4(0.0, 0.0, 0.0, 0.0);\nconst vec4 UNITS = vec4(1.0, 1.0, 1.0, 1.0);\n\nfloat val(mat4 p, mat4 v) {\n    return dot(matrixCompMult(p, v) * UNITS, UNITS);\n}\n\nfloat axisY(float ratio, mat4 A, mat4 B, mat4 C, mat4 D) {\n    float y1 = val(A, dim0A) + val(B, dim0B) + val(C, dim0C) + val(D, dim0D);\n    float y2 = val(A, dim1A) + val(B, dim1B) + val(C, dim1C) + val(D, dim1D);\n    return y1 * (1.0 - ratio) + y2 * ratio;\n}\n\nint iMod(int a, int b) {\n    return a - b * (a / b);\n}\n\nbool fOutside(float p, float lo, float hi) {\n    return (lo < hi) && (lo > p || p > hi);\n}\n\nbool vOutside(vec4 p, vec4 lo, vec4 hi) {\n    return (\n        fOutside(p[0], lo[0], hi[0]) ||\n        fOutside(p[1], lo[1], hi[1]) ||\n        fOutside(p[2], lo[2], hi[2]) ||\n        fOutside(p[3], lo[3], hi[3])\n    );\n}\n\nbool mOutside(mat4 p, mat4 lo, mat4 hi) {\n    return (\n        vOutside(p[0], lo[0], hi[0]) ||\n        vOutside(p[1], lo[1], hi[1]) ||\n        vOutside(p[2], lo[2], hi[2]) ||\n        vOutside(p[3], lo[3], hi[3])\n    );\n}\n\nbool outsideBoundingBox(mat4 A, mat4 B, mat4 C, mat4 D) {\n    return mOutside(A, loA, hiA) ||\n           mOutside(B, loB, hiB) ||\n           mOutside(C, loC, hiC) ||\n           mOutside(D, loD, hiD);\n}\n\nbool outsideRasterMask(mat4 A, mat4 B, mat4 C, mat4 D) {\n    mat4 pnts[4];\n    pnts[0] = A;\n    pnts[1] = B;\n    pnts[2] = C;\n    pnts[3] = D;\n\n    for(int i = 0; i < 4; ++i) {\n        for(int j = 0; j < 4; ++j) {\n            for(int k = 0; k < 4; ++k) {\n                if(0 == iMod(\n                    int(255.0 * texture2D(maskTexture,\n                        vec2(\n                            (float(i * 2 + j / 2) + 0.5) / 8.0,\n                            (pnts[i][j][k] * (maskHeight - 1.0) + 1.0) / maskHeight\n                        ))[3]\n                    ) / int(pow(2.0, float(iMod(j * 4 + k, 8)))),\n                    2\n                )) return true;\n            }\n        }\n    }\n    return false;\n}\n\nvec4 position(bool isContext, float v, mat4 A, mat4 B, mat4 C, mat4 D) {\n    float x = 0.5 * sign(v) + 0.5;\n    float y = axisY(x, A, B, C, D);\n    float z = 1.0 - abs(v);\n\n    z += isContext ? 0.0 : 2.0 * float(\n        outsideBoundingBox(A, B, C, D) ||\n        outsideRasterMask(A, B, C, D)\n    );\n\n    return vec4(\n        2.0 * (vec2(x, y) * viewBoxSize + viewBoxPos) / resolution - 1.0,\n        z,\n        1.0\n    );\n}\n\nvoid main() {\n    mat4 A = mat4(p01_04, p05_08, p09_12, p13_16);\n    mat4 B = mat4(p17_20, p21_24, p25_28, p29_32);\n    mat4 C = mat4(p33_36, p37_40, p41_44, p45_48);\n    mat4 D = mat4(p49_52, p53_56, p57_60, ZEROS);\n\n    float v = colors[3];\n\n    gl_Position = position(isContext, v, A, B, C, D);\n\n    fragColor =\n        isContext ? vec4(contextColor) :\n        isPick ? vec4(colors.rgb, 1.0) : texture2D(palette, vec2(abs(v), 0.5));\n}\n"]),a=n(["precision highp float;\n#define GLSLIFY 1\n\nvarying vec4 fragColor;\n\nvoid main() {\n    gl_FragColor = fragColor;\n}\n"]),o=r(25706).maxDimensionCount,s=r(71828),l=1e-6,u=new Uint8Array(4),c=new Uint8Array(4),f={shape:[256,1],format:"rgba",type:"uint8",mag:"nearest",min:"nearest"};function h(t,e,r,n,i){var a=t._gl;a.enable(a.SCISSOR_TEST),a.scissor(e,r,n,i),t.clear({color:[0,0,0,0],depth:1})}function p(t,e,r,n,i,a){var o=a.key;r.drawCompleted||(function(t){t.read({x:0,y:0,width:1,height:1,data:u})}(t),r.drawCompleted=!0),function s(l){var 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y=t.lines.canvasOverdrag*d,m=t.domain,x=t.canvasWidth*d,b=t.canvasHeight*d,_=t.pad.l*d,w=t.pad.b*d,T=t.layoutHeight*d,k=t.layoutWidth*d,A=t.deselectedLines.color,M=t.deselectedLines.opacity;return s.extendFlat({key:f,resolution:[x,b],viewBoxPos:[o+y,l],viewBoxSize:[u,c],i0:i,i1:a,dim0A:v[0].slice(0,16),dim0B:v[0].slice(16,32),dim0C:v[0].slice(32,48),dim0D:v[0].slice(48,64),dim1A:v[1].slice(0,16),dim1B:v[1].slice(16,32),dim1C:v[1].slice(32,48),dim1D:v[1].slice(48,64),drwLayer:h,contextColor:[A[0]/255,A[1]/255,A[2]/255,"auto"!==M?A[3]*M:Math.max(1/255,Math.pow(1/t.lines.color.length,1/3))],scissorX:(n===e?0:o+y)+(_-y)+k*m.x[0],scissorWidth:(n===r?x-o+y:u+.5)+(n===e?o+y:0),scissorY:l+w+T*m.y[0],scissorHeight:c,viewportX:_-y+k*m.x[0],viewportY:w+T*m.y[0],viewportWidth:x,viewportHeight:b},p)}function b(t){var e=2047,r=Math.max(0,Math.floor(t[0]*e),0),n=Math.min(e,Math.ceil(t[1]*e),e);return[Math.min(r,n),Math.max(r,n)]}t.exports=function(t,e){var r,n,u,y,_,w=e.context,T=e.pick,k=e.regl,A=k._gl,M=A.getParameter(A.ALIASED_LINE_WIDTH_RANGE),S=Math.max(M[0],Math.min(M[1],e.viewModel.plotGlPixelRatio)),E={currentRafs:{},drawCompleted:!0,clearOnly:!1},L=function(t){for(var e={},r=0;r<=o;r+=4)e[m(r)]=t.buffer({usage:"dynamic",type:"float",data:new Uint8Array(0)});return e}(k),C=k.texture(f),P=[];I(e);var O=k({profile:!1,blend:{enable:w,func:{srcRGB:"src alpha",dstRGB:"one minus src 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I(t){r=t.model,n=t.viewModel,u=n.dimensions.slice(),y=u[0]?u[0].values.length:0;var e=r.lines,i=T?e.color.map((function(t,r){return r/e.color.length})):e.color,a=function(t,e,r){for(var n,i=new Array(t*(o+4)),a=0,s=0;s<t;s++){for(var u=0;u<o;u++)i[a++]=u<e.length?e[u].paddedUnitValues[s]:.5;i[a++]=v(s,2),i[a++]=v(s,1),i[a++]=v(s,0),i[a++]=(n=r[s],Math.max(l,Math.min(.999999,n)))}return i}(y,u,i);!function(t,e,r){for(var n=0;n<=o;n+=4)t[m(n)](g(n/4,e,r))}(L,y,a),w||T||(C=k.texture(s.extendFlat({data:d(r.unitToColor,255)},f)))}return{render:function(t,e,n){var i,a,o,s=t.length,l=1/0,c=-1/0;for(i=0;i<s;i++)t[i].dim0.canvasX<l&&(l=t[i].dim0.canvasX,a=i),t[i].dim1.canvasX>c&&(c=t[i].dim1.canvasX,o=i);0===s&&h(k,0,0,r.canvasWidth,r.canvasHeight);var f=function(t){var e,r,n,i=[[],[]];for(n=0;n<64;n++){var a=!t&&n<u.length?u[n].brush.filter.getBounds():[-1/0,1/0];i[0][n]=a[0],i[1][n]=a[1]}var o=new Array(16384);for(e=0;e<16384;e++)o[e]=255;if(!t)for(e=0;e<u.length;e++){var s=e%8,l=(e-s)/8,c=Math.pow(2,s),f=u[e].brush.filter.get();if(!(f.length<2)){var h=b(f[0])[1];for(r=1;r<f.length;r++){var p=b(f[r]);for(n=h+1;n<p[0];n++)o[8*n+l]&=~c;h=Math.max(h,p[1])}}}var d={shape:[8,2048],format:"alpha",type:"uint8",mag:"nearest",min:"nearest",data:o};return _?_(d):_=k.texture(d),{maskTexture:_,maskHeight:2048,loA:i[0].slice(0,16),loB:i[0].slice(16,32),loC:i[0].slice(32,48),loD:i[0].slice(48,64),hiA:i[1].slice(0,16),hiB:i[1].slice(16,32),hiC:i[1].slice(32,48),hiD:i[1].slice(48,64)}}(w);for(i=0;i<s;i++){var d=t[i],v=d.dim0.crossfilterDimensionIndex,g=d.dim1.crossfilterDimensionIndex,m=d.canvasX,A=d.canvasY,M=m+d.panelSizeX,S=d.plotGlPixelRatio;if(e||!P[v]||P[v][0]!==m||P[v][1]!==M){P[v]=[m,M];var L=x(r,a,o,i,v,g,m,A,d.panelSizeX,d.panelSizeY,d.dim0.crossfilterDimensionIndex,w?0:T?2:1,f,S);E.clearOnly=n;var C=e?r.lines.blockLineCount:y;p(k,O,E,C,y,L)}}},readPixel:function(t,e){return k.read({x:t,y:e,width:1,height:1,data:c}),c},readPixels:function(t,e,r,n){var i=new 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A(t,e,r,i,o){var s,l,u=T(r);return i?n.scale.ordinal().domain(i.map((s=a(r.tickformat),l=o,l?function(t,e){var r=l[e];return null==r?s(t):r}:s))).range(i.map((function(r){var n=(r-u[0])/(u[1]-u[0]);return t-e+n*(2*e-t)}))):n.scale.linear().domain(u).range([t-e,e])}function M(t){if(t.tickvals){var e=T(t);return n.scale.ordinal().domain(t.tickvals).range(t.tickvals.map((function(t){return(t-e[0])/(e[1]-e[0])})))}}function S(t){var e=t.map((function(t){return t[0]})),r=t.map((function(t){var e=o(t[1]);return n.rgb("rgb("+e[0]+","+e[1]+","+e[2]+")")})),i="rgb".split("").map((function(t){return n.scale.linear().clamp(!0).domain(e).range(r.map((i=t,function(t){return t[i]})));var i}));return function(t){return i.map((function(e){return e(t)}))}}function E(t){return t.dimensions.some((function(t){return t.brush.filterSpecified}))}function L(t,e,r){var 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t.map(n).sort(i.sorterAsc)})).sort((function(t,e){return t[0]-e[0]}));e.filterChanged(p.key,o._index,a)}}))}})),p}function P(t){t.classed(m.cn.axisExtentText,!0).attr("text-anchor","middle").style("cursor","default")}function O(t,e){var r="top"===e?1:-1,n=t*Math.PI/180;return{dir:r,dx:Math.sin(n),dy:Math.cos(n),degrees:t}}function I(t,e,r){for(var n=e.panels||(e.panels=[]),i=t.data(),a=0;a<i.length-1;a++){var o=n[a]||(n[a]={}),s=i[a],l=i[a+1];o.dim0=s,o.dim1=l,o.canvasX=s.canvasX,o.panelSizeX=l.canvasX-s.canvasX,o.panelSizeY=e.model.canvasHeight,o.y=0,o.canvasY=0,o.plotGlPixelRatio=r}}function D(t,e){return s.tickText(t._ax,e,!1).text}function z(t,e){if(t.ordinal)return"";var r=t.domainScale.domain(),n=r[e?r.length-1:0];return D(t.model.dimensions[t.visibleIndex],n)}t.exports=function(t,e,r,a){var o=t._context.staticPlot,h=t._fullLayout,p=h._toppaper,_=h._glcontainer,T=t._context.plotGlPixelRatio,A=t._fullLayout.paper_bgcolor;!function(t){for(var e=0;e<t.length;e++)for(var r=0;r<t[e].length;r++)for(var n=t[e][r].trace,i=n.dimensions,a=0;a<i.length;a++){var o=i[a].values,l=i[a]._ax;l&&(l.range?l.range=k(l.range[0],l.range[1]):l.range=w(o,n._length),l.dtick||(l.dtick=.01*(Math.abs(l.range[1]-l.range[0])||1)),l.tickformat=i[a].tickformat,s.calcTicks(l),l.cleanRange())}}(e);var M,S,R=(M=!0,S=!1,{linePickActive:function(t){return arguments.length?M=!!t:M},contextShown:function(t){return arguments.length?S=!!t:S}}),F=e.filter((function(t){return g(t).trace.visible})).map(L.bind(0,r)).map(C.bind(0,R,a));_.each((function(t,e){return i.extendFlat(t,F[e])}));var B=_.selectAll(".gl-canvas").each((function(t){t.viewModel=F[0],t.viewModel.plotGlPixelRatio=T,t.viewModel.paperColor=A,t.model=t.viewModel?t.viewModel.model:null})),N=null;B.filter((function(t){return t.pick})).style("pointer-events",o?"none":"auto").on("mousemove",(function(t){if(R.linePickActive()&&t.lineLayer&&a&&a.hover){var 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J=Y.selectAll("."+m.cn.axisExtentBottom).data(v,d);J.enter().append("g").classed(m.cn.axisExtentBottom,!0),J.attr("transform",(function(t){return u(0,t.model.height+m.axisExtentOffset)}));var K=J.selectAll("."+m.cn.axisExtentBottomText).data(v,d);K.enter().append("text").classed(m.cn.axisExtentBottomText,!0).attr("dy","0.75em").call(P),K.text((function(t){return z(t,!1)})).each((function(t){f.font(n.select(this),t.model.rangeFont)})),x.ensureAxisBrush(H,A,t)}},21341:function(t,e,r){"use strict";var n=r(17171),i=r(79749),a=r(1602).isVisible,o={};function s(t,e,r){var n=e.indexOf(r),i=t.indexOf(n);return-1===i&&(i+=e.length),i}(t.exports=function(t,e){var r=t._fullLayout;if(i(t,[],o)){var l={},u={},c={},f={},h=r._size;e.forEach((function(e,r){var n=e[0].trace;c[r]=n.index;var i=f[r]=n._fullInput.index;l[r]=t.data[i].dimensions,u[r]=t.data[i].dimensions.slice()})),n(t,e,{width:h.w,height:h.h,margin:{t:h.t,r:h.r,b:h.b,l:h.l}},{filterChanged:function(e,n,i){var 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n=r(92770),i=r(84267),a=r(7901),o={};function s(t){return function(e,r){return!!e&&!!(e=i(e)).isValid()&&(e=a.addOpacity(e,e.getAlpha()),t[r]||(t[r]=e),e)}}function l(t,e){var r,n=JSON.stringify(t),a=e[n];if(!a){for(a=t.slice(),r=0;r<t.length;r++)a.push(i(t[r]).lighten(20).toHexString());for(r=0;r<t.length;r++)a.push(i(t[r]).darken(20).toHexString());e[n]=a}return a}t.exports={calc:function(t,e){var r,i,a=[],o=t._fullLayout,l=o.hiddenlabels||[],u=e.labels,c=e.marker.colors||[],f=e.values,h=e._length,p=e._hasValues&&h;if(e.dlabel)for(u=new Array(h),r=0;r<h;r++)u[r]=String(e.label0+r*e.dlabel);var d={},v=s(o["_"+e.type+"colormap"]),g=0,y=!1;for(r=0;r<h;r++){var m,x,b;if(p){if(m=f[r],!n(m))continue;m=+m}else m=1;void 0!==(x=u[r])&&""!==x||(x=r);var _=d[x=String(x)];void 0===_?(d[x]=a.length,(b=-1!==l.indexOf(x))||(g+=m),a.push({v:m,label:x,color:v(c[r],x),i:r,pts:[r],hidden:b})):(y=!0,(i=a[_]).v+=m,i.pts.push(r),i.hidden||(g+=m),!1===i.color&&c[r]&&(i.color=v(c[r],x)))}return a=a.filter((function(t){return t.v>=0})),("funnelarea"===e.type?y:e.sort)&&a.sort((function(t,e){return e.v-t.v})),a[0]&&(a[0].vTotal=g),a},crossTraceCalc:function(t,e){var r=(e||{}).type;r||(r="pie");var n=t._fullLayout,i=t.calcdata,a=n[r+"colorway"],s=n["_"+r+"colormap"];n["extend"+r+"colors"]&&(a=l(a,o));for(var u=0,c=0;c<i.length;c++){var f=i[c];if(f[0].trace.type===r)for(var h=0;h<f.length;h++){var p=f[h];!1===p.color&&(s[p.label]?p.color=s[p.label]:(s[p.label]=p.color=a[u%a.length],u++))}}},makePullColorFn:s,generateExtendedColors:l}},37434:function(t,e,r){"use strict";var n=r(92770),i=r(71828),a=r(34e3),o=r(27670).c,s=r(90769).handleText,l=r(71828).coercePattern;function u(t,e){var r=Array.isArray(t),a=i.isArrayOrTypedArray(e),o=Math.min(r?t.length:1/0,a?e.length:1/0);if(isFinite(o)||(o=0),o&&a){for(var s,l=0;l<o;l++){var u=e[l];if(n(u)&&u>0){s=!0;break}}s||(o=0)}return{hasLabels:r,hasValues:a,len:o}}function c(t,e,r,n,i){n("marker.line.width")&&n("marker.line.color",i?void 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n=r(91424),i=r(7901);t.exports=function(t,e,r,a){var o=r.marker.pattern;o&&o.shape?n.pointStyle(t,r,a,e):i.fill(t,e.color)}},53581:function(t,e,r){"use strict";var n=r(71828);function i(t){return-1!==t.indexOf("e")?t.replace(/[.]?0+e/,"e"):-1!==t.indexOf(".")?t.replace(/[.]?0+$/,""):t}e.formatPiePercent=function(t,e){var r=i((100*t).toPrecision(3));return n.numSeparate(r,e)+"%"},e.formatPieValue=function(t,e){var r=i(t.toPrecision(10));return n.numSeparate(r,e)},e.getFirstFilled=function(t,e){if(Array.isArray(t))for(var r=0;r<e.length;r++){var n=t[e[r]];if(n||0===n||""===n)return n}},e.castOption=function(t,r){return Array.isArray(t)?e.getFirstFilled(t,r):t||void 0},e.getRotationAngle=function(t){return("auto"===t?0:t)*Math.PI/180}},58810:function(t,e,r){"use 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n=r(39898),i=r(74875),a=r(30211),o=r(7901),s=r(91424),l=r(71828),u=l.strScale,c=l.strTranslate,f=r(63893),h=r(72597),p=h.recordMinTextSize,d=h.clearMinTextSize,v=r(97313).TEXTPAD,g=r(53581),y=r(20007),m=r(71828).isValidTextValue;function x(t,e,r){var i=r[0],o=i.cx,s=i.cy,u=i.trace,c="funnelarea"===u.type;"_hasHoverLabel"in u||(u._hasHoverLabel=!1),"_hasHoverEvent"in u||(u._hasHoverEvent=!1),t.on("mouseover",(function(t){var r=e._fullLayout,f=e._fullData[u.index];if(!e._dragging&&!1!==r.hovermode){var h=f.hoverinfo;if(Array.isArray(h)&&(h=a.castHoverinfo({hoverinfo:[g.castOption(h,t.pts)],_module:u._module},r,0)),"all"===h&&(h="label+text+value+percent+name"),f.hovertemplate||"none"!==h&&"skip"!==h&&h){var p=t.rInscribed||0,d=o+t.pxmid[0]*(1-p),v=s+t.pxmid[1]*(1-p),m=r.separators,x=[];if(h&&-1!==h.indexOf("label")&&x.push(t.label),t.text=g.castOption(f.hovertext||f.text,t.pts),h&&-1!==h.indexOf("text")){var b=t.text;l.isValidTextValue(b)&&x.push(b)}t.value=t.v,t.valueLabel=g.formatPieValue(t.v,m),h&&-1!==h.indexOf("value")&&x.push(t.valueLabel),t.percent=t.v/i.vTotal,t.percentLabel=g.formatPiePercent(t.percent,m),h&&-1!==h.indexOf("percent")&&x.push(t.percentLabel);var _=f.hoverlabel,w=_.font,T=[];a.loneHover({trace:u,x0:d-p*i.r,x1:d+p*i.r,y:v,_x0:c?o+t.TL[0]:d-p*i.r,_x1:c?o+t.TR[0]:d+p*i.r,_y0:c?s+t.TL[1]:v-p*i.r,_y1:c?s+t.BL[1]:v+p*i.r,text:x.join("<br>"),name:f.hovertemplate||-1!==h.indexOf("name")?f.name:void 0,idealAlign:t.pxmid[0]<0?"left":"right",color:g.castOption(_.bgcolor,t.pts)||t.color,borderColor:g.castOption(_.bordercolor,t.pts),fontFamily:g.castOption(w.family,t.pts),fontSize:g.castOption(w.size,t.pts),fontColor:g.castOption(w.color,t.pts),nameLength:g.castOption(_.namelength,t.pts),textAlign:g.castOption(_.align,t.pts),hovertemplate:g.castOption(f.hovertemplate,t.pts),hovertemplateLabels:t,eventData:[y(t,f)]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:e,inOut_bbox:T}),t.bbox=T[0],u._hasHoverLabel=!0}u._hasHoverEvent=!0,e.emit("plotly_hover",{points:[y(t,f)],event:n.event})}})),t.on("mouseout",(function(t){var r=e._fullLayout,i=e._fullData[u.index],o=n.select(this).datum();u._hasHoverEvent&&(t.originalEvent=n.event,e.emit("plotly_unhover",{points:[y(o,i)],event:n.event}),u._hasHoverEvent=!1),u._hasHoverLabel&&(a.loneUnhover(r._hoverlayer.node()),u._hasHoverLabel=!1)})),t.on("click",(function(t){var r=e._fullLayout,i=e._fullData[u.index];e._dragging||!1===r.hovermode||(e._hoverdata=[y(t,i)],a.click(e,n.event))}))}function b(t,e,r){var n=g.castOption(t.insidetextfont.color,e.pts);!n&&t._input.textfont&&(n=g.castOption(t._input.textfont.color,e.pts));var i=g.castOption(t.insidetextfont.family,e.pts)||g.castOption(t.textfont.family,e.pts)||r.family,a=g.castOption(t.insidetextfont.size,e.pts)||g.castOption(t.textfont.size,e.pts)||r.size;return{color:n||o.contrast(e.color),family:i,size:a}}function _(t,e){for(var r,n,i=0;i<t.length;i++)if((n=(r=t[i][0]).trace).title.text){var a=n.title.text;n._meta&&(a=l.templateString(a,n._meta));var o=s.tester.append("text").attr("data-notex",1).text(a).call(s.font,n.title.font).call(f.convertToTspans,e),u=s.bBox(o.node(),!0);r.titleBox={width:u.width,height:u.height},o.remove()}}function w(t,e,r){var n=r.r||e.rpx1,i=e.rInscribed;if(e.startangle===e.stopangle)return{rCenter:1-i,scale:0,rotate:0,textPosAngle:0};var a,o=e.ring,s=1===o&&Math.abs(e.startangle-e.stopangle)===2*Math.PI,l=e.halfangle,u=e.midangle,c=r.trace.insidetextorientation,f="horizontal"===c,h="tangential"===c,p="radial"===c,d="auto"===c,v=[];if(!d){var g,y=function(r,i){if(function(t,e){var r=t.startangle,n=t.stopangle;return r>e&&e>n||r<e&&e<n}(e,r)){var s=Math.abs(r-e.startangle),l=Math.abs(r-e.stopangle),u=s<l?s:l;(a="tan"===i?k(t,n,o,u,0):T(t,n,o,u,Math.PI/2)).textPosAngle=r,v.push(a)}};if(f||h){for(g=4;g>=-4;g-=2)y(Math.PI*g,"tan");for(g=4;g>=-4;g-=2)y(Math.PI*(g+1),"tan")}if(f||p){for(g=4;g>=-4;g-=2)y(Math.PI*(g+1.5),"rad");for(g=4;g>=-4;g-=2)y(Math.PI*(g+.5),"rad")}}if(s||d||f){var m=Math.sqrt(t.width*t.width+t.height*t.height);if((a={scale:i*n*2/m,rCenter:1-i,rotate:0}).textPosAngle=(e.startangle+e.stopangle)/2,a.scale>=1)return a;v.push(a)}(d||p)&&((a=T(t,n,o,l,u)).textPosAngle=(e.startangle+e.stopangle)/2,v.push(a)),(d||h)&&((a=k(t,n,o,l,u)).textPosAngle=(e.startangle+e.stopangle)/2,v.push(a));for(var 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r,n,i,a=t.trace,o={x:t.cx,y:t.cy},s={tx:0,ty:0};s.ty+=a.title.font.size,i=O(a),-1!==a.title.position.indexOf("top")?(o.y-=(1+i)*t.r,s.ty-=t.titleBox.height):-1!==a.title.position.indexOf("bottom")&&(o.y+=(1+i)*t.r);var l,u=t.r/(void 0===(l=t.trace.aspectratio)?1:l),c=e.w*(a.domain.x[1]-a.domain.x[0])/2;return-1!==a.title.position.indexOf("left")?(c+=u,o.x-=(1+i)*u,s.tx+=t.titleBox.width/2):-1!==a.title.position.indexOf("center")?c*=2:-1!==a.title.position.indexOf("right")&&(c+=u,o.x+=(1+i)*u,s.tx-=t.titleBox.width/2),r=c/t.titleBox.width,n=P(t,e)/t.titleBox.height,{x:o.x,y:o.y,scale:Math.min(r,n),tx:s.tx,ty:s.ty}}function P(t,e){var r=t.trace,n=e.h*(r.domain.y[1]-r.domain.y[0]);return Math.min(t.titleBox.height,n/2)}function O(t){var e,r=t.pull;if(!r)return 0;if(Array.isArray(r))for(r=0,e=0;e<t.pull.length;e++)t.pull[e]>r&&(r=t.pull[e]);return r}function I(t,e){for(var r=[],n=0;n<t.length;n++){var i=t[n][0],a=i.trace,o=a.domain,s=e.w*(o.x[1]-o.x[0]),l=e.h*(o.y[1]-o.y[0]);a.title.text&&"middle center"!==a.title.position&&(l-=P(i,e));var u=s/2,c=l/2;"funnelarea"!==a.type||a.scalegroup||(c/=a.aspectratio),i.r=Math.min(u,c)/(1+O(a)),i.cx=e.l+e.w*(a.domain.x[1]+a.domain.x[0])/2,i.cy=e.t+e.h*(1-a.domain.y[0])-l/2,a.title.text&&-1!==a.title.position.indexOf("bottom")&&(i.cy-=P(i,e)),a.scalegroup&&-1===r.indexOf(a.scalegroup)&&r.push(a.scalegroup)}!function(t,e){for(var r,n,i,a=0;a<e.length;a++){var o=1/0,s=e[a];for(n=0;n<t.length;n++)if((i=(r=t[n][0]).trace).scalegroup===s){var l;if("pie"===i.type)l=r.r*r.r;else if("funnelarea"===i.type){var u,c;i.aspectratio>1?c=(u=r.r)/i.aspectratio:u=(c=r.r)*i.aspectratio,l=(u*=(1+i.baseratio)/2)*c}o=Math.min(o,l/r.vTotal)}for(n=0;n<t.length;n++)if((i=(r=t[n][0]).trace).scalegroup===s){var f=o*r.vTotal;"funnelarea"===i.type&&(f/=(1+i.baseratio)/2,f/=i.aspectratio),r.r=Math.sqrt(f)}}}(t,r)}function D(t,e){return[t*Math.sin(e),-t*Math.cos(e)]}function 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r=t.rotate*Math.PI/180,n=Math.cos(r),i=Math.sin(r),a=(e.left+e.right)/2,o=(e.top+e.bottom)/2;t.textX=a*n-o*i,t.textY=a*i+o*n,t.noCenter=!0}t.exports={plot:function(t,e){var r=t._context.staticPlot,a=t._fullLayout,h=a._size;d("pie",a),_(e,t),I(e,h);var v=l.makeTraceGroups(a._pielayer,e,"trace").each((function(e){var d=n.select(this),v=e[0],y=v.trace;!function(t){var e,r,n,i=t[0],a=i.r,o=i.trace,s=g.getRotationAngle(o.rotation),l=2*Math.PI/i.vTotal,u="px0",c="px1";if("counterclockwise"===o.direction){for(e=0;e<t.length&&t[e].hidden;e++);if(e===t.length)return;s+=l*t[e].v,l*=-1,u="px1",c="px0"}for(n=D(a,s),e=0;e<t.length;e++)(r=t[e]).hidden||(r[u]=n,r.startangle=s,s+=l*r.v/2,r.pxmid=D(a,s),r.midangle=s,n=D(a,s+=l*r.v/2),r.stopangle=s,r[c]=n,r.largeArc=r.v>i.vTotal/2?1:0,r.halfangle=Math.PI*Math.min(r.v/i.vTotal,.5),r.ring=1-o.hole,r.rInscribed=E(r,i))}(e),d.attr("stroke-linejoin","round"),d.each((function(){var m=n.select(this).selectAll("g.slice").data(e);m.enter().append("g").classed("slice",!0),m.exit().remove();var _=[[[],[]],[[],[]]],T=!1;m.each((function(i,o){if(i.hidden)n.select(this).selectAll("path,g").remove();else{i.pointNumber=i.i,i.curveNumber=y.index,_[i.pxmid[1]<0?0:1][i.pxmid[0]<0?0:1].push(i);var u=v.cx,c=v.cy,h=n.select(this),d=h.selectAll("path.surface").data([i]);if(d.enter().append("path").classed("surface",!0).style({"pointer-events":r?"none":"all"}),h.call(x,t,e),y.pull){var m=+g.castOption(y.pull,i.pts)||0;m>0&&(u+=m*i.pxmid[0],c+=m*i.pxmid[1])}i.cxFinal=u,i.cyFinal=c;var k=y.hole;if(i.v===v.vTotal){var A="M"+(u+i.px0[0])+","+(c+i.px0[1])+P(i.px0,i.pxmid,!0,1)+P(i.pxmid,i.px0,!0,1)+"Z";k?d.attr("d","M"+(u+k*i.px0[0])+","+(c+k*i.px0[1])+P(i.px0,i.pxmid,!1,k)+P(i.pxmid,i.px0,!1,k)+"Z"+A):d.attr("d",A)}else{var M=P(i.px0,i.px1,!0,1);if(k){var S=1-k;d.attr("d","M"+(u+k*i.px1[0])+","+(c+k*i.px1[1])+P(i.px1,i.px0,!1,k)+"l"+S*i.px0[0]+","+S*i.px0[1]+M+"Z")}else d.attr("d","M"+u+","+c+"l"+i.px0[0]+","+i.px0[1]+M+"Z")}z(t,i,v);var E=g.castOption(y.textposition,i.pts),C=h.selectAll("g.slicetext").data(i.text&&"none"!==E?[0]:[]);C.enter().append("g").classed("slicetext",!0),C.exit().remove(),C.each((function(){var r=l.ensureSingle(n.select(this),"text","",(function(t){t.attr("data-notex",1)})),h=l.ensureUniformFontSize(t,"outside"===E?function(t,e,r){return{color:g.castOption(t.outsidetextfont.color,e.pts)||g.castOption(t.textfont.color,e.pts)||r.color,family:g.castOption(t.outsidetextfont.family,e.pts)||g.castOption(t.textfont.family,e.pts)||r.family,size:g.castOption(t.outsidetextfont.size,e.pts)||g.castOption(t.textfont.size,e.pts)||r.size}}(y,i,a.font):b(y,i,a.font));r.text(i.text).attr({class:"slicetext",transform:"","text-anchor":"middle"}).call(s.font,h).call(f.convertToTspans,t);var d,m=s.bBox(r.node());if("outside"===E)d=L(m,i);else if(d=w(m,i,v),"auto"===E&&d.scale<1){var x=l.ensureUniformFontSize(t,y.outsidetextfont);r.call(s.font,x),d=L(m=s.bBox(r.node()),i)}var _=d.textPosAngle,k=void 0===_?i.pxmid:D(v.r,_);if(d.targetX=u+k[0]*d.rCenter+(d.x||0),d.targetY=c+k[1]*d.rCenter+(d.y||0),R(d,m),d.outside){var A=d.targetY;i.yLabelMin=A-m.height/2,i.yLabelMid=A,i.yLabelMax=A+m.height/2,i.labelExtraX=0,i.labelExtraY=0,T=!0}d.fontSize=h.size,p(y.type,d,a),e[o].transform=d,l.setTransormAndDisplay(r,d)}))}function P(t,e,r,n){var a=n*(e[0]-t[0]),o=n*(e[1]-t[1]);return"a"+n*v.r+","+n*v.r+" 0 "+i.largeArc+(r?" 1 ":" 0 ")+a+","+o}}));var k=n.select(this).selectAll("g.titletext").data(y.title.text?[0]:[]);if(k.enter().append("g").classed("titletext",!0),k.exit().remove(),k.each((function(){var e,r=l.ensureSingle(n.select(this),"text","",(function(t){t.attr("data-notex",1)})),i=y.title.text;y._meta&&(i=l.templateString(i,y._meta)),r.text(i).attr({class:"titletext",transform:"","text-anchor":"middle"}).call(s.font,y.title.font).call(f.convertToTspans,t),e="middle center"===y.title.position?function(t){var e=Math.sqrt(t.titleBox.width*t.titleBox.width+t.titleBox.height*t.titleBox.height);return{x:t.cx,y:t.cy,scale:t.trace.hole*t.r*2/e,tx:0,ty:-t.titleBox.height/2+t.trace.title.font.size}}(v):C(v,h),r.attr("transform",c(e.x,e.y)+u(Math.min(1,e.scale))+c(e.tx,e.ty))})),T&&function(t,e){var r,n,i,a,o,s,l,u,c,f,h,p,d;function v(t,e){return t.pxmid[1]-e.pxmid[1]}function y(t,e){return e.pxmid[1]-t.pxmid[1]}function m(t,r){r||(r={});var i,u,c,h,p=r.labelExtraY+(n?r.yLabelMax:r.yLabelMin),d=n?t.yLabelMin:t.yLabelMax,v=n?t.yLabelMax:t.yLabelMin,y=t.cyFinal+o(t.px0[1],t.px1[1]),m=p-d;if(m*l>0&&(t.labelExtraY=m),Array.isArray(e.pull))for(u=0;u<f.length;u++)(c=f[u])===t||(g.castOption(e.pull,t.pts)||0)>=(g.castOption(e.pull,c.pts)||0)||((t.pxmid[1]-c.pxmid[1])*l>0?(m=c.cyFinal+o(c.px0[1],c.px1[1])-d-t.labelExtraY)*l>0&&(t.labelExtraY+=m):(v+t.labelExtraY-y)*l>0&&(i=3*s*Math.abs(u-f.indexOf(t)),(h=c.cxFinal+a(c.px0[0],c.px1[0])+i-(t.cxFinal+t.pxmid[0])-t.labelExtraX)*s>0&&(t.labelExtraX+=h)))}for(n=0;n<2;n++)for(i=n?v:y,o=n?Math.max:Math.min,l=n?1:-1,r=0;r<2;r++){for(a=r?Math.max:Math.min,s=r?1:-1,(u=t[n][r]).sort(i),c=t[1-n][r],f=c.concat(u),p=[],h=0;h<u.length;h++)void 0!==u[h].yLabelMid&&p.push(u[h]);for(d=!1,h=0;n&&h<c.length;h++)if(void 0!==c[h].yLabelMid){d=c[h];break}for(h=0;h<p.length;h++){var x=h&&p[h-1];d&&!h&&(x=d),m(p[h],x)}}}(_,y),function(t,e){t.each((function(t){var r=n.select(this);if(t.labelExtraX||t.labelExtraY){var i=r.select("g.slicetext text");t.transform.targetX+=t.labelExtraX,t.transform.targetY+=t.labelExtraY,l.setTransormAndDisplay(i,t.transform);var a=t.cxFinal+t.pxmid[0],s="M"+a+","+(t.cyFinal+t.pxmid[1]),u=(t.yLabelMax-t.yLabelMin)*(t.pxmid[0]<0?-1:1)/4;if(t.labelExtraX){var c=t.labelExtraX*t.pxmid[1]/t.pxmid[0],f=t.yLabelMid+t.labelExtraY-(t.cyFinal+t.pxmid[1]);Math.abs(c)>Math.abs(f)?s+="l"+f*t.pxmid[0]/t.pxmid[1]+","+f+"H"+(a+t.labelExtraX+u):s+="l"+t.labelExtraX+","+c+"v"+(f-c)+"h"+u}else s+="V"+(t.yLabelMid+t.labelExtraY)+"h"+u;l.ensureSingle(r,"path","textline").call(o.stroke,e.outsidetextfont.color).attr({"stroke-width":Math.min(2,e.outsidetextfont.size/8),d:s,fill:"none"})}else r.select("path.textline").remove()}))}(m,y),T&&y.automargin){var A=s.bBox(d.node()),M=y.domain,S=h.w*(M.x[1]-M.x[0]),E=h.h*(M.y[1]-M.y[0]),P=(.5*S-v.r)/h.w,O=(.5*E-v.r)/h.h;i.autoMargin(t,"pie."+y.uid+".automargin",{xl:M.x[0]-P,xr:M.x[1]+P,yb:M.y[0]-O,yt:M.y[1]+O,l:Math.max(v.cx-v.r-A.left,0),r:Math.max(A.right-(v.cx+v.r),0),b:Math.max(A.bottom-(v.cy+v.r),0),t:Math.max(v.cy-v.r-A.top,0),pad:5})}}))}));setTimeout((function(){v.selectAll("tspan").each((function(){var t=n.select(this);t.attr("dy")&&t.attr("dy",t.attr("dy"))}))}),0)},formatSliceLabel:z,transformInsideText:w,determineInsideTextFont:b,positionTitleOutside:C,prerenderTitles:_,layoutAreas:I,attachFxHandlers:x,computeTransform:R}},68357:function(t,e,r){"use strict";var n=r(39898),i=r(63463),a=r(72597).resizeText;t.exports=function(t){var e=t._fullLayout._pielayer.selectAll(".trace");a(t,e,"pie"),e.each((function(e){var r=e[0].trace,a=n.select(this);a.style({opacity:r.opacity}),a.selectAll("path.surface").each((function(e){n.select(this).call(i,e,r,t)}))}))}},63463:function(t,e,r){"use 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a=r.node;a.originalEvent=n.event,t._hoverdata=[a],n.select(e).call(m,r,i),s.click(t,{target:!0})}}})}},3393:function(t,e,r){"use strict";var n=r(49887),i=r(81684).k4,a=r(39898),o=r(30838),s=r(86781),l=r(85247),u=r(84267),c=r(7901),f=r(91424),h=r(71828),p=h.strTranslate,d=h.strRotate,v=r(28984),g=v.keyFun,y=v.repeat,m=v.unwrap,x=r(63893),b=r(73972),_=r(18783),w=_.CAP_SHIFT,T=_.LINE_SPACING;function k(t,e,r){var n,i=m(e),a=i.trace,c=a.domain,f="h"===a.orientation,p=a.node.pad,d=a.node.thickness,v=t.width*(c.x[1]-c.x[0]),g=t.height*(c.y[1]-c.y[0]),y=i._nodes,x=i._links,b=i.circular;(n=b?s.sankeyCircular().circularLinkGap(0):o.sankey()).iterations(l.sankeyIterations).size(f?[v,g]:[g,v]).nodeWidth(d).nodePadding(p).nodeId((function(t){return t.pointNumber})).nodes(y).links(x);var _,w,T,k=n();for(var A in n.nodePadding()<p&&h.warn("node.pad was reduced to ",n.nodePadding()," to fit within the figure."),i._groupLookup){var 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e.trace=t.trace,e.curveNumber=t.trace.index,{circular:t.circular,key:i,traceId:t.key,pointNumber:e.pointNumber,link:e,tinyColorHue:c.tinyRGB(n),tinyColorAlpha:n.getAlpha(),linkPath:M,linkLineColor:t.linkLineColor,linkLineWidth:t.linkLineWidth,linkArrowLength:t.linkArrowLength,valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,parent:t,interactionState:t.interactionState,flow:e.flow}}function M(){return function(t){var e=t.linkArrowLength;if(t.link.circular)return function(t,e){var r=t.width/2,n=t.circularPathData;return"top"===t.circularLinkType?"M "+(n.targetX-e)+" "+(n.targetY+r)+" L"+(n.rightInnerExtent-e)+" "+(n.targetY+r)+"A"+(n.rightLargeArcRadius+r)+" "+(n.rightSmallArcRadius+r)+" 0 0 1 "+(n.rightFullExtent-r-e)+" "+(n.targetY-n.rightSmallArcRadius)+"L"+(n.rightFullExtent-r-e)+" "+n.verticalRightInnerExtent+"A"+(n.rightLargeArcRadius+r)+" "+(n.rightLargeArcRadius+r)+" 0 0 1 "+(n.rightInnerExtent-e)+" "+(n.verticalFullExtent-r)+"L"+n.leftInnerExtent+" 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n=t.link.source.x1,a=t.link.target.x0-e,o=i(n,a),s=o(.5),l=o(.5),u=t.link.y0-t.link.width/2,c=t.link.y0+t.link.width/2,f=t.link.y1-t.link.width/2,h=t.link.y1+t.link.width/2,p="M"+n+","+u,d="C"+s+","+u+" "+l+","+f+" "+a+","+f,v="C"+l+","+h+" "+s+","+c+" "+n+","+c,g=e>0?"L"+(a+e)+","+(f+t.link.width/2):"";return p+d+(g+="L"+a+","+h)+v+"Z"}}function S(t,e){var r=u(e.color),n=l.nodePadAcross,i=t.nodePad/2;e.dx=e.x1-e.x0,e.dy=e.y1-e.y0;var a=e.dx,o=Math.max(.5,e.dy),s="node_"+e.pointNumber;return e.group&&(s=h.randstr()),e.trace=t.trace,e.curveNumber=t.trace.index,{index:e.pointNumber,key:s,partOfGroup:e.partOfGroup||!1,group:e.group,traceId:t.key,trace:t.trace,node:e,nodePad:t.nodePad,nodeLineColor:t.nodeLineColor,nodeLineWidth:t.nodeLineWidth,textFont:t.textFont,size:t.horizontal?t.height:t.width,visibleWidth:Math.ceil(a),visibleHeight:o,zoneX:-n,zoneY:-i,zoneWidth:a+2*n,zoneHeight:o+2*i,labelY:t.horizontal?e.dy/2+1:e.dx/2+1,left:1===e.originalLayer,sizeAcross:t.width,forceLayouts:t.forceLayouts,horizontal:t.horizontal,darkBackground:r.getBrightness()<=128,tinyColorHue:c.tinyRGB(r),tinyColorAlpha:r.getAlpha(),valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,graph:t.graph,arrangement:t.arrangement,uniqueNodeLabelPathId:[t.guid,t.key,s].join("_"),interactionState:t.interactionState,figure:t}}function E(t){t.attr("transform",(function(t){return p(t.node.x0.toFixed(3),t.node.y0.toFixed(3))}))}function L(t){t.call(E)}function C(t,e){t.call(L),e.attr("d",M())}function P(t){t.attr("width",(function(t){return t.node.x1-t.node.x0})).attr("height",(function(t){return t.visibleHeight}))}function O(t){return t.link.width>1||t.linkLineWidth>0}function I(t){return p(t.translateX,t.translateY)+(t.horizontal?"matrix(1 0 0 1 0 0)":"matrix(0 1 1 0 0 0)")}function D(t,e,r){t.on(".basic",null).on("mouseover.basic",(function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.hover(this,t,e),t.interactionState.hovered=[this,t])})).on("mousemove.basic",(function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.follow(this,t),t.interactionState.hovered=[this,t])})).on("mouseout.basic",(function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.unhover(this,t,e),t.interactionState.hovered=!1)})).on("click.basic",(function(t){t.interactionState.hovered&&(r.unhover(this,t,e),t.interactionState.hovered=!1),t.interactionState.dragInProgress||t.partOfGroup||r.select(this,t,e)}))}function z(t,e,r,i){var o=a.behavior.drag().origin((function(t){return{x:t.node.x0+t.visibleWidth/2,y:t.node.y0+t.visibleHeight/2}})).on("dragstart",(function(a){if("fixed"!==a.arrangement&&(h.ensureSingle(i._fullLayout._infolayer,"g","dragcover",(function(t){i._fullLayout._dragCover=t})),h.raiseToTop(this),a.interactionState.dragInProgress=a.node,F(a.node),a.interactionState.hovered&&(r.nodeEvents.unhover.apply(0,a.interactionState.hovered),a.interactionState.hovered=!1),"snap"===a.arrangement)){var o=a.traceId+"|"+a.key;a.forceLayouts[o]?a.forceLayouts[o].alpha(1):function(t,e,r,i){!function(t){for(var e=0;e<t.length;e++)t[e].y=(t[e].y0+t[e].y1)/2,t[e].x=(t[e].x0+t[e].x1)/2}(r.graph.nodes);var a=r.graph.nodes.filter((function(t){return t.originalX===r.node.originalX})).filter((function(t){return!t.partOfGroup}));r.forceLayouts[e]=n.forceSimulation(a).alphaDecay(0).force("collide",n.forceCollide().radius((function(t){return t.dy/2+r.nodePad/2})).strength(1).iterations(l.forceIterations)).force("constrain",function(t,e,r,n){return function(){for(var t=0,i=0;i<r.length;i++){var a=r[i];a===n.interactionState.dragInProgress?(a.x=a.lastDraggedX,a.y=a.lastDraggedY):(a.vx=(a.originalX-a.x)/l.forceTicksPerFrame,a.y=Math.min(n.size-a.dy/2,Math.max(a.dy/2,a.y))),t=Math.max(t,Math.abs(a.vx),Math.abs(a.vy))}!n.interactionState.dragInProgress&&t<.1&&n.forceLayouts[e].alpha()>0&&n.forceLayouts[e].alpha(0)}}(0,e,a,r)).stop()}(0,o,a),function(t,e,r,n,i){window.requestAnimationFrame((function a(){var o;for(o=0;o<l.forceTicksPerFrame;o++)r.forceLayouts[n].tick();if(function(t){for(var e=0;e<t.length;e++)t[e].y0=t[e].y-t[e].dy/2,t[e].y1=t[e].y0+t[e].dy,t[e].x0=t[e].x-t[e].dx/2,t[e].x1=t[e].x0+t[e].dx}(r.graph.nodes),r.sankey.update(r.graph),C(t.filter(B(r)),e),r.forceLayouts[n].alpha()>0)window.requestAnimationFrame(a);else{var 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n=r(52075).hasColorscale,i=r(78803),a=r(34098);t.exports=function(t,e){a.hasLines(e)&&n(e,"line")&&i(t,e,{vals:e.line.color,containerStr:"line",cLetter:"c"}),a.hasMarkers(e)&&(n(e,"marker")&&i(t,e,{vals:e.marker.color,containerStr:"marker",cLetter:"c"}),n(e,"marker.line")&&i(t,e,{vals:e.marker.line.color,containerStr:"marker.line",cLetter:"c"}))}},47581:function(t){"use strict";t.exports={PTS_LINESONLY:20,minTolerance:.2,toleranceGrowth:10,maxScreensAway:20,eventDataKeys:[]}},72626:function(t,e,r){"use strict";var n=r(47761),i=r(11661).setGroupPositions;function a(t,e,r,n,i,a,o){i[n]=!0;var s={i:null,gap:!0,s:0};if(s[o]=r,t.splice(e,0,s),e&&r===t[e-1][o]){var l=t[e-1];s.s=l.s,s.i=l.i,s.gap=l.gap}else a&&(s.s=function(t,e,r,n){var i=t[e-1],a=t[e+1];return a?i?i.s+(a.s-i.s)*(r-i[n])/(a[n]-i[n]):a.s:i.s}(t,e,r,o));e||(t[0].t=t[1].t,t[0].trace=t[1].trace,delete t[1].t,delete t[1].trace)}t.exports=function(t,e){"group"===t._fullLayout.scattermode&&function(t,e){for(var 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n=r(5386).fF,i=r(5386).si,a=r(82196),o=r(9012),s=r(50693),l=r(79952).P,u=r(1426).extendFlat,c=r(30962).overrideAll,f=a.marker,h=a.line,p=f.line;t.exports=c({lon:{valType:"data_array"},lat:{valType:"data_array"},locations:{valType:"data_array"},locationmode:{valType:"enumerated",values:["ISO-3","USA-states","country 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n;if(f.hasText(e)&&(n.text=m(t,e),n.textSel=_(t,e,e.selected),n.textUnsel=_(t,e,e.unselected)),f.hasMarkers(e)&&(n.marker=x(0,e),n.markerSel=b(0,e,e.selected),n.markerUnsel=b(0,e,e.unselected),!e.unselected&&s.isArrayOrTypedArray(e.marker.opacity))){var a=e.marker.opacity;for(n.markerUnsel.opacity=new Array(a.length),r=0;r<a.length;r++)n.markerUnsel.opacity[r]=v*a[r]}if(f.hasLines(e)){n.line={overlay:!0,thickness:e.line.width*i,color:e.line.color,opacity:e.opacity};var o=(d.DASHES[e.line.dash]||[1]).slice();for(r=0;r<o.length;++r)o[r]*=e.line.width*i;n.line.dashes=o}return e.error_x&&e.error_x.visible&&(n.errorX=w(e,e.error_x,i)),e.error_y&&e.error_y.visible&&(n.errorY=w(e,e.error_y,i)),e.fill&&"none"!==e.fill&&(n.fill={closed:!0,fill:e.fillcolor,thickness:0}),n},markerStyle:x,markerSelection:b,linePositions:function(t,e,r){var 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r=e._scene,i={count:0,dirty:!0,lineOptions:[],fillOptions:[],markerOptions:[],markerSelectedOptions:[],markerUnselectedOptions:[],errorXOptions:[],errorYOptions:[],textOptions:[],textSelectedOptions:[],textUnselectedOptions:[],selectBatch:[],unselectBatch:[]},a={fill2d:!1,scatter2d:!1,error2d:!1,line2d:!1,glText:!1,select2d:!1};return e._scene||((r=e._scene={}).init=function(){n.extendFlat(r,a,i)},r.init(),r.update=function(t){var e=n.repeat(t,r.count);if(r.fill2d&&r.fill2d.update(e),r.scatter2d&&r.scatter2d.update(e),r.line2d&&r.line2d.update(e),r.error2d&&r.error2d.update(e.concat(e)),r.select2d&&r.select2d.update(e),r.glText)for(var i=0;i<r.count;i++)r.glText[i].update(t)},r.draw=function(){for(var t=r.count,e=r.fill2d,i=r.error2d,a=r.line2d,o=r.scatter2d,s=r.glText,l=r.select2d,u=r.selectBatch,c=r.unselectBatch,f=0;f<t;f++){if(e&&r.fillOrder[f]&&e.draw(r.fillOrder[f]),a&&r.lineOptions[f]&&a.draw(f),i&&(r.errorXOptions[f]&&i.draw(f),r.errorYOptions[f]&&i.draw(f+t)),o&&r.markerOptions[f])if(c[f].length){var h=n.repeat([],r.count);h[f]=c[f],o.draw(h)}else 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v=n.hasText(l),g=n.hasMarkers(l),y=!g&&!v;if(!0!==l.visible||y)return s;var m=[],x=[];if(!1!==e&&!e.degenerate)for(var b=0;b<c;b++)e.contains([u.xpx[b],u.ypx[b]],!1,b,t)?(m.push(b),s.push({pointNumber:b,x:a.c2d(f[b]),y:o.c2d(h[b])})):x.push(b);if(g){var _=p.scatter2d;if(m.length||x.length){if(!p.selectBatch[d].length&&!p.unselectBatch[d].length){var w=new Array(p.count);w[d]=p.markerUnselectedOptions[d],_.update.apply(_,w)}}else{var T=new Array(p.count);T[d]=p.markerOptions[d],_.update.apply(_,T)}}return p.selectBatch[d]=m,p.unselectBatch[d]=x,v&&i(r),s}},99181:function(t,e,r){"use strict";var n=r(5386).fF,i=r(5386).si,a=r(19316),o=r(82196),s=r(23585),l=r(9012),u=r(50693),c=r(1426).extendFlat,f=r(30962).overrideAll,h=r(23585),p=a.line,d=a.marker;t.exports=f({lon:a.lon,lat:a.lat,cluster:{enabled:{valType:"boolean"},maxzoom:c({},h.layers.maxzoom,{}),step:{valType:"number",arrayOk:!0,dflt:-1,min:-1},size:{valType:"number",arrayOk:!0,dflt:20,min:0},color:{valType:"color",arrayOk:!0},opacity:c({},d.opacity,{dflt:1})},mode:c({},o.mode,{dflt:"markers"}),text:c({},o.text,{}),texttemplate:i({editType:"plot"},{keys:["lat","lon","text"]}),hovertext:c({},o.hovertext,{}),line:{color:p.color,width:p.width},connectgaps:o.connectgaps,marker:c({symbol:{valType:"string",dflt:"circle",arrayOk:!0},angle:{valType:"number",dflt:"auto",arrayOk:!0},allowoverlap:{valType:"boolean",dflt:!1},opacity:d.opacity,size:d.size,sizeref:d.sizeref,sizemin:d.sizemin,sizemode:d.sizemode},u("marker")),fill:a.fill,fillcolor:o.fillcolor,textfont:s.layers.symbol.textfont,textposition:s.layers.symbol.textposition,below:{valType:"string"},selected:{marker:o.selected.marker},unselected:{marker:o.unselected.marker},hoverinfo:c({},l.hoverinfo,{flags:["lon","lat","text","name"]}),hovertemplate:n()},"calc","nested")},15790:function(t,e,r){"use 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n=r(71828),i=n.pushUnique,a=r(34098),o=r(35948);t.exports=function(t,e){var r=t.cd,s=r[0].trace,l=r[0].t,u=t.scene,c=u.matrixOptions.cdata,f=t.xaxis,h=t.yaxis,p=[];if(!u)return p;var d=!a.hasMarkers(s)&&!a.hasText(s);if(!0!==s.visible||d)return p;var v=o.getDimIndex(s,f),g=o.getDimIndex(s,h);if(!1===v||!1===g)return p;var y=l.xpx[v],m=l.ypx[g],x=c[v],b=c[g],_=(t.scene.selectBatch||[]).slice(),w=[];if(!1!==e&&!e.degenerate)for(var T=0;T<x.length;T++)e.contains([y[T],m[T]],null,T,t)?(p.push({pointNumber:T,x:x[T],y:b[T]}),i(_,T)):-1!==_.indexOf(T)?i(_,T):w.push(T);var k=u.matrixOptions;return _.length||w.length?u.selectBatch.length||u.unselectBatch.length||u.matrix.update(u.unselectedOptions,n.extendFlat({},k,u.selectedOptions,u.viewOpts)):u.matrix.update(k,null),u.selectBatch=_,u.unselectBatch=w,p}},21850:function(t,e,r){"use strict";var n=r(50693),i=r(12663).axisHoverFormat,a=r(5386).fF,o=r(2418),s=r(9012),l=r(1426).extendFlat,u={x:{valType:"data_array",editType:"calc+clearAxisTypes"},y:{valType:"data_array",editType:"calc+clearAxisTypes"},z:{valType:"data_array",editType:"calc+clearAxisTypes"},u:{valType:"data_array",editType:"calc"},v:{valType:"data_array",editType:"calc"},w:{valType:"data_array",editType:"calc"},starts:{x:{valType:"data_array",editType:"calc"},y:{valType:"data_array",editType:"calc"},z:{valType:"data_array",editType:"calc"},editType:"calc"},maxdisplayed:{valType:"integer",min:0,dflt:1e3,editType:"calc"},sizeref:{valType:"number",editType:"calc",min:0,dflt:1},text:{valType:"string",dflt:"",editType:"calc"},hovertext:{valType:"string",dflt:"",editType:"calc"},hovertemplate:a({editType:"calc"},{keys:["tubex","tubey","tubez","tubeu","tubev","tubew","norm","divergence"]}),uhoverformat:i("u",1),vhoverformat:i("v",1),whoverformat:i("w",1),xhoverformat:i("x"),yhoverformat:i("y"),zhoverformat:i("z"),showlegend:l({},s.showlegend,{dflt:!1})};l(u,n("",{colorAttr:"u/v/w 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v=d(e._Xs,"xaxis"),g=d(e._Ys,"yaxis"),y=d(e._Zs,"zaxis");if(f.meshgrid=[v,g,y],f.gridFill=e._gridFill,e._slen)f.startingPositions=l(d(e._startsX,"xaxis"),d(e._startsY,"yaxis"),d(e._startsZ,"zaxis"));else{for(var m=g[0],x=h(v),b=h(y),_=new Array(x.length*b.length),w=0,T=0;T<x.length;T++)for(var k=0;k<b.length;k++)_[w++]=[x[T],m,b[k]];f.startingPositions=_}f.colormap=o(e),f.tubeSize=e.sizeref,f.maxLength=e.maxdisplayed;var A=d(e._xbnds,"xaxis"),M=d(e._ybnds,"yaxis"),S=d(e._zbnds,"zaxis"),E=p(v),L=p(g),C=p(y),P=[[A[0]-E[0],M[0]-L[0],S[0]-C[0]],[A[1]+E[1],M[1]+L[1],S[1]+C[1]]],O=n(f,P),I=s(e);O.vertexIntensityBounds=[I.min/e._normMax,I.max/e._normMax];var D=e.lightposition;return O.lightPosition=[D.x,D.y,D.z],O.ambient=e.lighting.ambient,O.diffuse=e.lighting.diffuse,O.specular=e.lighting.specular,O.roughness=e.lighting.roughness,O.fresnel=e.lighting.fresnel,O.opacity=e.opacity,e._pad=O.tubeScale*e.sizeref*2,O}f.handlePick=function(t){var e=this.scene.fullSceneLayout,r=this.scene.dataScale;function n(t,n){var i=e[n],a=r[u[n]];return i.l2c(t)/a}if(t.object===this.mesh){var i=t.data.position,a=t.data.velocity;return t.traceCoordinate=[n(i[0],"xaxis"),n(i[1],"yaxis"),n(i[2],"zaxis"),n(a[0],"xaxis"),n(a[1],"yaxis"),n(a[2],"zaxis"),t.data.intensity*this.data._normMax,t.data.divergence],t.textLabel=this.data.hovertext||this.data.text,!0}},f.update=function(t){this.data=t;var e=d(this.scene,t);this.mesh.update(e)},f.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()},t.exports=function(t,e){var r=t.glplot.gl,n=d(t,e),a=i(r,n),o=new c(t,e.uid);return o.mesh=a,o.data=e,a._trace=o,t.glplot.add(a),o}},22459:function(t,e,r){"use strict";var n=r(71828),i=r(1586),a=r(21850);t.exports=function(t,e,r,o){function s(r,i){return n.coerce(t,e,a,r,i)}var l=s("u"),u=s("v"),c=s("w"),f=s("x"),h=s("y"),p=s("z");l&&l.length&&u&&u.length&&c&&c.length&&f&&f.length&&h&&h.length&&p&&p.length?(s("starts.x"),s("starts.y"),s("starts.z"),s("maxdisplayed"),s("sizeref"),s("lighting.ambient"),s("lighting.diffuse"),s("lighting.specular"),s("lighting.roughness"),s("lighting.fresnel"),s("lightposition.x"),s("lightposition.y"),s("lightposition.z"),i(t,e,o,s,{prefix:"",cLetter:"c"}),s("text"),s("hovertext"),s("hovertemplate"),s("uhoverformat"),s("vhoverformat"),s("whoverformat"),s("xhoverformat"),s("yhoverformat"),s("zhoverformat"),e._length=null):e.visible=!1}},61510:function(t,e,r){"use strict";t.exports={moduleType:"trace",name:"streamtube",basePlotModule:r(58547),categories:["gl3d","showLegend"],attributes:r(21850),supplyDefaults:r(22459),colorbar:{min:"cmin",max:"cmax"},calc:r(88489).calc,plot:r(90154),eventData:function(t,e){return t.tubex=t.x,t.tubey=t.y,t.tubez=t.z,t.tubeu=e.traceCoordinate[3],t.tubev=e.traceCoordinate[4],t.tubew=e.traceCoordinate[5],t.norm=e.traceCoordinate[6],t.divergence=e.traceCoordinate[7],delete t.x,delete t.y,delete t.z,t},meta:{}}},57564:function(t,e,r){"use strict";var n=r(9012),i=r(5386).fF,a=r(5386).si,o=r(50693),s=r(27670).Y,l=r(34e3),u=r(7055),c=r(1426).extendFlat,f=r(79952).u;t.exports={labels:{valType:"data_array",editType:"calc"},parents:{valType:"data_array",editType:"calc"},values:{valType:"data_array",editType:"calc"},branchvalues:{valType:"enumerated",values:["remainder","total"],dflt:"remainder",editType:"calc"},count:{valType:"flaglist",flags:["branches","leaves"],dflt:"leaves",editType:"calc"},level:{valType:"any",editType:"plot",anim:!0},maxdepth:{valType:"integer",editType:"plot",dflt:-1},marker:c({colors:{valType:"data_array",editType:"calc"},line:{color:c({},l.marker.line.color,{dflt:null}),width:c({},l.marker.line.width,{dflt:1}),editType:"calc"},pattern:f,editType:"calc"},o("marker",{colorAttr:"colors",anim:!1})),leaf:{opacity:{valType:"number",editType:"style",min:0,max:1},editType:"plot"},text:l.text,textinfo:{valType:"flaglist",flags:["label","text","value","current path","percent root","percent entry","percent 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n=r(674),i=r(92770),a=r(71828),o=r(21081).makeColorScaleFuncFromTrace,s=r(32354).makePullColorFn,l=r(32354).generateExtendedColors,u=r(21081).calc,c=r(50606).ALMOST_EQUAL,f={},h={},p={};function d(t,e,r){var n=0,i=t.children;if(i){for(var a=i.length,o=0;o<a;o++)n+=d(i[o],e,r);r.branches&&n++}else r.leaves&&n++;return t.value=t.data.data.value=n,e._values||(e._values=[]),e._values[t.data.data.i]=n,n}e.calc=function(t,e){var r,l,f,h,p,v,g=t._fullLayout,y=e.ids,m=a.isArrayOrTypedArray(y),x=e.labels,b=e.parents,_=e.values,w=a.isArrayOrTypedArray(_),T=[],k={},A={},M=function(t){return t||"number"==typeof t},S=function(t){return!w||i(_[t])&&_[t]>=0};m?(r=Math.min(y.length,b.length),l=function(t){return M(y[t])&&S(t)},f=function(t){return String(y[t])}):(r=Math.min(x.length,b.length),l=function(t){return M(x[t])&&S(t)},f=function(t){return String(x[t])}),w&&(r=Math.min(r,_.length));for(var E=0;E<r;E++)if(l(E)){var L=f(E),C=M(b[E])?String(b[E]):"",P={i:E,id:L,pid:C,label:M(x[E])?String(x[E]):""};w&&(P.v=+_[E]),T.push(P),p=L,k[h=C]?k[h].push(p):k[h]=[p],A[p]=1}if(k[""]){if(k[""].length>1){for(var O=a.randstr(),I=0;I<T.length;I++)""===T[I].pid&&(T[I].pid=O);T.unshift({hasMultipleRoots:!0,id:O,pid:"",label:""})}}else{var D,z=[];for(D in k)A[D]||z.push(D);if(1!==z.length)return a.warn(["Multiple implied roots, cannot build",e.type,"hierarchy of",e.name+".","These roots include:",z.join(", ")].join(" "));D=z[0],T.unshift({hasImpliedRoot:!0,id:D,pid:"",label:D})}try{v=n.stratify().id((function(t){return t.id})).parentId((function(t){return t.pid}))(T)}catch(t){return a.warn(["Failed to build",e.type,"hierarchy of",e.name+".","Error:",t.message].join(" "))}var R=n.hierarchy(v),F=!1;if(w)switch(e.branchvalues){case"remainder":R.sum((function(t){return t.data.v}));break;case"total":R.each((function(t){var r=t.data.data,n=r.v;if(t.children){var i=t.children.reduce((function(t,e){return t+e.data.data.v}),0);if((r.hasImpliedRoot||r.hasMultipleRoots)&&(n=i),n<i*c)return F=!0,a.warn(["Total value for node",t.data.data.id,"of",e.name,"is smaller than the sum of its children.","\nparent value =",n,"\nchildren sum =",i].join(" "))}t.value=n}))}else d(R,e,{branches:-1!==e.count.indexOf("branches"),leaves:-1!==e.count.indexOf("leaves")});if(!F){var B,N;e.sort&&R.sort((function(t,e){return e.value-t.value}));var j=e.marker.colors||[],U=!!j.length;return e._hasColorscale?(U||(j=w?e.values:e._values),u(t,e,{vals:j,containerStr:"marker",cLetter:"c"}),N=o(e.marker)):B=s(g["_"+e.type+"colormap"]),R.each((function(t){var r=t.data.data;r.color=e._hasColorscale?N(j[r.i]):B(j[r.i],r.id)})),T[0].hierarchy=R,T}},e._runCrossTraceCalc=function(t,e){var r=e._fullLayout,n=e.calcdata,i=r[t+"colorway"],a=r["_"+t+"colormap"];r["extend"+t+"colors"]&&(i=l(i,"icicle"===t?p:"treemap"===t?h:f));var o,s=0;function u(t){var e=t.data.data,r=e.id;!1===e.color&&(a[r]?e.color=a[r]:t.parent?t.parent.parent?e.color=t.parent.data.data.color:(a[r]=e.color=i[s%i.length],s++):e.color=o)}for(var c=0;c<n.length;c++){var d=n[c][0];d.trace.type===t&&d.hierarchy&&(o=d.trace.root.color,d.hierarchy.each(u))}},e.crossTraceCalc=function(t){return e._runCrossTraceCalc("sunburst",t)}},7055:function(t){"use strict";t.exports={CLICK_TRANSITION_TIME:750,CLICK_TRANSITION_EASING:"linear",eventDataKeys:["currentPath","root","entry","percentRoot","percentEntry","percentParent"]}},17094:function(t,e,r){"use strict";var n=r(71828),i=r(57564),a=r(27670).c,o=r(90769).handleText,s=r(37434).handleMarkerDefaults,l=r(21081),u=l.hasColorscale,c=l.handleDefaults;t.exports=function(t,e,r,l){function f(r,a){return n.coerce(t,e,i,r,a)}var h=f("labels"),p=f("parents");if(h&&h.length&&p&&p.length){var d=f("values");d&&d.length?f("branchvalues"):f("count"),f("level"),f("maxdepth"),s(t,e,l,f);var v=e._hasColorscale=u(t,"marker","colors")||(t.marker||{}).coloraxis;v&&c(t,e,l,f,{prefix:"marker.",cLetter:"c"}),f("leaf.opacity",v?1:.7);var g=f("text");f("texttemplate"),e.texttemplate||f("textinfo",Array.isArray(g)?"text+label":"label"),f("hovertext"),f("hovertemplate"),o(t,e,l,f,"auto",{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),f("insidetextorientation"),f("sort"),f("rotation"),f("root.color"),a(e,l,f),e._length=null}else e.visible=!1}},43467:function(t,e,r){"use strict";var n=r(91424),i=r(7901);t.exports=function(t,e,r,a,o){var s=e.data.data,l=s.i,u=o||s.color;if(l>=0){e.i=s.i;var c=r.marker;c.pattern&&c.colors&&c.pattern.shape||(c.color=u,e.color=u),n.pointStyle(t,r,a,e)}else i.fill(t,u)}},83523:function(t,e,r){"use strict";var n=r(39898),i=r(73972),a=r(23469).appendArrayPointValue,o=r(30211),s=r(71828),l=r(11086),u=r(2791),c=r(53581).formatPieValue;function f(t,e,r){for(var n=t.data.data,i={curveNumber:e.index,pointNumber:n.i,data:e._input,fullData:e},o=0;o<r.length;o++){var s=r[o];s in t&&(i[s]=t[s])}return"parentString"in t&&!u.isHierarchyRoot(t)&&(i.parent=t.parentString),a(i,e,n.i),i}t.exports=function(t,e,r,a,h){var p=a[0],d=p.trace,v=p.hierarchy,g="sunburst"===d.type,y="treemap"===d.type||"icicle"===d.type;"_hasHoverLabel"in d||(d._hasHoverLabel=!1),"_hasHoverEvent"in d||(d._hasHoverEvent=!1),t.on("mouseover",(function(i){var a=r._fullLayout;if(!r._dragging&&!1!==a.hovermode){var l,m=r._fullData[d.index],x=i.data.data,b=x.i,_=u.isHierarchyRoot(i),w=u.getParent(v,i),T=u.getValue(i),k=function(t){return s.castOption(m,b,t)},A=k("hovertemplate"),M=o.castHoverinfo(m,a,b),S=a.separators;if(A||M&&"none"!==M&&"skip"!==M){var E,L;g&&(E=p.cx+i.pxmid[0]*(1-i.rInscribed),L=p.cy+i.pxmid[1]*(1-i.rInscribed)),y&&(E=i._hoverX,L=i._hoverY);var 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N=t.select("path.surface");h.styleOne(N,i,m,r,{hovered:!0})}d._hasHoverEvent=!0,r.emit("plotly_hover",{points:l||[f(i,m,h.eventDataKeys)],event:n.event})}})),t.on("mouseout",(function(e){var i=r._fullLayout,a=r._fullData[d.index],s=n.select(this).datum();if(d._hasHoverEvent&&(e.originalEvent=n.event,r.emit("plotly_unhover",{points:[f(s,a,h.eventDataKeys)],event:n.event}),d._hasHoverEvent=!1),d._hasHoverLabel&&(o.loneUnhover(i._hoverlayer.node()),d._hasHoverLabel=!1),y){var l=t.select("path.surface");h.styleOne(l,s,a,r,{hovered:!1})}})),t.on("click",(function(t){var e=r._fullLayout,a=r._fullData[d.index],s=g&&(u.isHierarchyRoot(t)||u.isLeaf(t)),c=u.getPtId(t),p=u.isEntry(t)?u.findEntryWithChild(v,c):u.findEntryWithLevel(v,c),y=u.getPtId(p),m={points:[f(t,a,h.eventDataKeys)],event:n.event};s||(m.nextLevel=y);var 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v,g=o.split("+"),y=function(t){return-1!==g.indexOf(t)},m=[];if(y("label")&&c.label&&m.push(c.label),c.hasOwnProperty("v")&&y("value")&&m.push(b.formatValue(c.v,l)),!h){y("current path")&&m.push(b.getPath(t.data));var x=0;y("percent parent")&&x++,y("percent entry")&&x++,y("percent root")&&x++;var _=x>1;if(x){var w,T=function(t){v=b.formatPercent(w,l),_&&(v+=" of "+t),m.push(v)};y("percent parent")&&!h&&(w=d/b.getValue(p),T("parent")),y("percent entry")&&(w=d/b.getValue(e),T("entry")),y("percent root")&&(w=d/b.getValue(f),T("root"))}}return y("text")&&(v=s.castOption(r,c.i,"text"),s.isValidTextValue(v)&&m.push(v)),m.join("<br>")}var k=s.castOption(r,c.i,"texttemplate");if(!k)return"";var 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n=r(78803);t.exports=function(t,e){e.surfacecolor?n(t,e,{vals:e.surfacecolor,containerStr:"",cLetter:"c"}):n(t,e,{vals:e.z,containerStr:"",cLetter:"c"})}},43768:function(t,e,r){"use strict";var n=r(9330).gl_surface3d,i=r(9330).ndarray,a=r(9330).ndarray_linear_interpolate.d2,o=r(824),s=r(43907),l=r(71828).isArrayOrTypedArray,u=r(81697).parseColorScale,c=r(78614),f=r(21081).extractOpts;function h(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var p=h.prototype;p.getXat=function(t,e,r,n){var i=l(this.data.x)?l(this.data.x[0])?this.data.x[e][t]:this.data.x[t]:t;return void 0===r?i:n.d2l(i,0,r)},p.getYat=function(t,e,r,n){var i=l(this.data.y)?l(this.data.y[0])?this.data.y[e][t]:this.data.y[e]:e;return void 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t,e,r,n=[[],[],[]],i=[!1,!1,!1],a=!1;for(t=0;t<3;++t)if(this.showContour[t]&&(a=!0,this.contourSize[t]>0&&null!==this.contourStart[t]&&null!==this.contourEnd[t]&&this.contourEnd[t]>this.contourStart[t]))for(i[t]=!0,e=this.contourStart[t];e<this.contourEnd[t];e+=this.contourSize[t])r=e*this.scene.dataScale[t],k(n[t],r);if(a){var o=[[],[],[]];for(t=0;t<3;++t)this.showContour[t]&&(o[t]=i[t]?n[t]:this.scene.contourLevels[t]);this.surface.update({levels:o})}},p.update=function(t){var e,r,n,a,l=this.scene,h=l.fullSceneLayout,p=this.surface,d=u(t),v=l.dataScale,g=t.z[0].length,y=t._ylength,m=l.contourLevels;this.data=t;var x=[];for(e=0;e<3;e++)for(x[e]=[],r=0;r<g;r++)x[e][r]=[];for(r=0;r<g;r++)for(n=0;n<y;n++)x[0][r][n]=this.getXat(r,n,t.xcalendar,h.xaxis),x[1][r][n]=this.getYat(r,n,t.ycalendar,h.yaxis),x[2][r][n]=this.getZat(r,n,t.zcalendar,h.zaxis);if(t.connectgaps)for(t._emptypoints=s(x[2]),o(x[2],t._emptypoints),t._interpolatedZ=[],r=0;r<g;r++)for(t._interpolatedZ[r]=[],n=0;n<y;n++)t._interpolatedZ[r][n]=x[2][r][n];for(e=0;e<3;e++)for(r=0;r<g;r++)for(n=0;n<y;n++)null==(a=x[e][r][n])?x[e][r][n]=NaN:a=x[e][r][n]*=v[e];for(e=0;e<3;e++)for(r=0;r<g;r++)for(n=0;n<y;n++)null!=(a=x[e][r][n])&&(this.minValues[e]>a&&(this.minValues[e]=a),this.maxValues[e]<a&&(this.maxValues[e]=a));for(e=0;e<3;e++)this.objectOffset[e]=.5*(this.minValues[e]+this.maxValues[e]);for(e=0;e<3;e++)for(r=0;r<g;r++)for(n=0;n<y;n++)null!=(a=x[e][r][n])&&(x[e][r][n]-=this.objectOffset[e]);var b=[i(new Float32Array(g*y),[g,y]),i(new Float32Array(g*y),[g,y]),i(new 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A=[!0,!0,!0],M=["x","y","z"];for(e=0;e<3;++e){var S=t.contours[M[e]];A[e]=S.highlight,w.showContour[e]=S.show||S.highlight,w.showContour[e]&&(w.contourProject[e]=[S.project.x,S.project.y,S.project.z],S.show?(this.showContour[e]=!0,w.levels[e]=m[e],p.highlightColor[e]=w.contourColor[e]=c(S.color),S.usecolormap?p.highlightTint[e]=w.contourTint[e]=0:p.highlightTint[e]=w.contourTint[e]=1,w.contourWidth[e]=S.width,this.contourStart[e]=S.start,this.contourEnd[e]=S.end,this.contourSize[e]=S.size):(this.showContour[e]=!1,this.contourStart[e]=null,this.contourEnd[e]=null,this.contourSize[e]=0),S.highlight&&(w.dynamicColor[e]=c(S.highlightcolor),w.dynamicWidth[e]=S.highlightwidth))}(function(t){var e=t[0].rgb,r=t[t.length-1].rgb;return e[0]===r[0]&&e[1]===r[1]&&e[2]===r[2]&&e[3]===r[3]})(d)&&(w.vertexColor=!0),w.objectOffset=this.objectOffset,w.coords=b,p.update(w),p.visible=t.visible,p.enableDynamic=A,p.enableHighlight=A,p.snapToData=!0,"lighting"in 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2===this.length?t+=67108864*this.words[1]:3===this.length&&1===this.words[2]?t+=4503599627370496+67108864*this.words[1]:this.length>2&&n(!1,"Number can only safely store up to 53 bits"),0!==this.negative?-t:t},a.prototype.toJSON=function(){return this.toString(16)},a.prototype.toBuffer=function(t,e){return n(void 0!==o),this.toArrayLike(o,t,e)},a.prototype.toArray=function(t,e){return this.toArrayLike(Array,t,e)},a.prototype.toArrayLike=function(t,e,r){var i=this.byteLength(),a=r||Math.max(1,i);n(i<=a,"byte array longer than desired length"),n(a>0,"Requested array length <= 0"),this.strip();var o,s,l="le"===e,u=new t(a),c=this.clone();if(l){for(s=0;!c.isZero();s++)o=c.andln(255),c.iushrn(8),u[s]=o;for(;s<a;s++)u[s]=0}else{for(s=0;s<a-i;s++)u[s]=0;for(s=0;!c.isZero();s++)o=c.andln(255),c.iushrn(8),u[a-s-1]=o}return u},Math.clz32?a.prototype._countBits=function(t){return 32-Math.clz32(t)}:a.prototype._countBits=function(t){var e=t,r=0;return 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e,r;this.length>t.length?(e=this,r=t):(e=t,r=this);for(var n=0;n<r.length;n++)this.words[n]=e.words[n]^r.words[n];if(this!==e)for(;n<e.length;n++)this.words[n]=e.words[n];return this.length=e.length,this.strip()},a.prototype.ixor=function(t){return n(0==(this.negative|t.negative)),this.iuxor(t)},a.prototype.xor=function(t){return this.length>t.length?this.clone().ixor(t):t.clone().ixor(this)},a.prototype.uxor=function(t){return this.length>t.length?this.clone().iuxor(t):t.clone().iuxor(this)},a.prototype.inotn=function(t){n("number"==typeof t&&t>=0);var e=0|Math.ceil(t/26),r=t%26;this._expand(e),r>0&&e--;for(var i=0;i<e;i++)this.words[i]=67108863&~this.words[i];return r>0&&(this.words[i]=~this.words[i]&67108863>>26-r),this.strip()},a.prototype.notn=function(t){return this.clone().inotn(t)},a.prototype.setn=function(t,e){n("number"==typeof t&&t>=0);var r=t/26|0,i=t%26;return 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0!==t.negative&&0===this.negative?(t.negative=0,e=this.sub(t),t.negative^=1,e):0===t.negative&&0!==this.negative?(this.negative=0,e=t.sub(this),this.negative=1,e):this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},a.prototype.isub=function(t){if(0!==t.negative){t.negative=0;var e=this.iadd(t);return t.negative=1,e._normSign()}if(0!==this.negative)return this.negative=0,this.iadd(t),this.negative=1,this._normSign();var r,n,i=this.cmp(t);if(0===i)return this.negative=0,this.length=1,this.words[0]=0,this;i>0?(r=this,n=t):(r=t,n=this);for(var a=0,o=0;o<n.length;o++)a=(e=(0|r.words[o])-(0|n.words[o])+a)>>26,this.words[o]=67108863&e;for(;0!==a&&o<r.length;o++)a=(e=(0|r.words[o])+a)>>26,this.words[o]=67108863&e;if(0===a&&o<r.length&&r!==this)for(;o<r.length;o++)this.words[o]=r.words[o];return this.length=Math.max(this.length,o),r!==this&&(this.negative=1),this.strip()},a.prototype.sub=function(t){return this.clone().isub(t)};var d=function(t,e,r){var n,i,a,o=t.words,s=e.words,l=r.words,u=0,c=0|o[0],f=8191&c,h=c>>>13,p=0|o[1],d=8191&p,v=p>>>13,g=0|o[2],y=8191&g,m=g>>>13,x=0|o[3],b=8191&x,_=x>>>13,w=0|o[4],T=8191&w,k=w>>>13,A=0|o[5],M=8191&A,S=A>>>13,E=0|o[6],L=8191&E,C=E>>>13,P=0|o[7],O=8191&P,I=P>>>13,D=0|o[8],z=8191&D,R=D>>>13,F=0|o[9],B=8191&F,N=F>>>13,j=0|s[0],U=8191&j,V=j>>>13,H=0|s[1],q=8191&H,G=H>>>13,Z=0|s[2],Y=8191&Z,W=Z>>>13,X=0|s[3],J=8191&X,K=X>>>13,$=0|s[4],Q=8191&$,tt=$>>>13,et=0|s[5],rt=8191&et,nt=et>>>13,it=0|s[6],at=8191&it,ot=it>>>13,st=0|s[7],lt=8191&st,ut=st>>>13,ct=0|s[8],ft=8191&ct,ht=ct>>>13,pt=0|s[9],dt=8191&pt,vt=pt>>>13;r.negative=t.negative^e.negative,r.length=19;var gt=(u+(n=Math.imul(f,U))|0)+((8191&(i=(i=Math.imul(f,V))+Math.imul(h,U)|0))<<13)|0;u=((a=Math.imul(h,V))+(i>>>13)|0)+(gt>>>26)|0,gt&=67108863,n=Math.imul(d,U),i=(i=Math.imul(d,V))+Math.imul(v,U)|0,a=Math.imul(v,V);var yt=(u+(n=n+Math.imul(f,q)|0)|0)+((8191&(i=(i=i+Math.imul(f,G)|0)+Math.imul(h,q)|0))<<13)|0;u=((a=a+Math.imul(h,G)|0)+(i>>>13)|0)+(yt>>>26)|0,yt&=67108863,n=Math.imul(y,U),i=(i=Math.imul(y,V))+Math.imul(m,U)|0,a=Math.imul(m,V),n=n+Math.imul(d,q)|0,i=(i=i+Math.imul(d,G)|0)+Math.imul(v,q)|0,a=a+Math.imul(v,G)|0;var mt=(u+(n=n+Math.imul(f,Y)|0)|0)+((8191&(i=(i=i+Math.imul(f,W)|0)+Math.imul(h,Y)|0))<<13)|0;u=((a=a+Math.imul(h,W)|0)+(i>>>13)|0)+(mt>>>26)|0,mt&=67108863,n=Math.imul(b,U),i=(i=Math.imul(b,V))+Math.imul(_,U)|0,a=Math.imul(_,V),n=n+Math.imul(y,q)|0,i=(i=i+Math.imul(y,G)|0)+Math.imul(m,q)|0,a=a+Math.imul(m,G)|0,n=n+Math.imul(d,Y)|0,i=(i=i+Math.imul(d,W)|0)+Math.imul(v,Y)|0,a=a+Math.imul(v,W)|0;var xt=(u+(n=n+Math.imul(f,J)|0)|0)+((8191&(i=(i=i+Math.imul(f,K)|0)+Math.imul(h,J)|0))<<13)|0;u=((a=a+Math.imul(h,K)|0)+(i>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(T,U),i=(i=Math.imul(T,V))+Math.imul(k,U)|0,a=Math.imul(k,V),n=n+Math.imul(b,q)|0,i=(i=i+Math.imul(b,G)|0)+Math.imul(_,q)|0,a=a+Math.imul(_,G)|0,n=n+Math.imul(y,Y)|0,i=(i=i+Math.imul(y,W)|0)+Math.imul(m,Y)|0,a=a+Math.imul(m,W)|0,n=n+Math.imul(d,J)|0,i=(i=i+Math.imul(d,K)|0)+Math.imul(v,J)|0,a=a+Math.imul(v,K)|0;var bt=(u+(n=n+Math.imul(f,Q)|0)|0)+((8191&(i=(i=i+Math.imul(f,tt)|0)+Math.imul(h,Q)|0))<<13)|0;u=((a=a+Math.imul(h,tt)|0)+(i>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(M,U),i=(i=Math.imul(M,V))+Math.imul(S,U)|0,a=Math.imul(S,V),n=n+Math.imul(T,q)|0,i=(i=i+Math.imul(T,G)|0)+Math.imul(k,q)|0,a=a+Math.imul(k,G)|0,n=n+Math.imul(b,Y)|0,i=(i=i+Math.imul(b,W)|0)+Math.imul(_,Y)|0,a=a+Math.imul(_,W)|0,n=n+Math.imul(y,J)|0,i=(i=i+Math.imul(y,K)|0)+Math.imul(m,J)|0,a=a+Math.imul(m,K)|0,n=n+Math.imul(d,Q)|0,i=(i=i+Math.imul(d,tt)|0)+Math.imul(v,Q)|0,a=a+Math.imul(v,tt)|0;var _t=(u+(n=n+Math.imul(f,rt)|0)|0)+((8191&(i=(i=i+Math.imul(f,nt)|0)+Math.imul(h,rt)|0))<<13)|0;u=((a=a+Math.imul(h,nt)|0)+(i>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(L,U),i=(i=Math.imul(L,V))+Math.imul(C,U)|0,a=Math.imul(C,V),n=n+Math.imul(M,q)|0,i=(i=i+Math.imul(M,G)|0)+Math.imul(S,q)|0,a=a+Math.imul(S,G)|0,n=n+Math.imul(T,Y)|0,i=(i=i+Math.imul(T,W)|0)+Math.imul(k,Y)|0,a=a+Math.imul(k,W)|0,n=n+Math.imul(b,J)|0,i=(i=i+Math.imul(b,K)|0)+Math.imul(_,J)|0,a=a+Math.imul(_,K)|0,n=n+Math.imul(y,Q)|0,i=(i=i+Math.imul(y,tt)|0)+Math.imul(m,Q)|0,a=a+Math.imul(m,tt)|0,n=n+Math.imul(d,rt)|0,i=(i=i+Math.imul(d,nt)|0)+Math.imul(v,rt)|0,a=a+Math.imul(v,nt)|0;var wt=(u+(n=n+Math.imul(f,at)|0)|0)+((8191&(i=(i=i+Math.imul(f,ot)|0)+Math.imul(h,at)|0))<<13)|0;u=((a=a+Math.imul(h,ot)|0)+(i>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(O,U),i=(i=Math.imul(O,V))+Math.imul(I,U)|0,a=Math.imul(I,V),n=n+Math.imul(L,q)|0,i=(i=i+Math.imul(L,G)|0)+Math.imul(C,q)|0,a=a+Math.imul(C,G)|0,n=n+Math.imul(M,Y)|0,i=(i=i+Math.imul(M,W)|0)+Math.imul(S,Y)|0,a=a+Math.imul(S,W)|0,n=n+Math.imul(T,J)|0,i=(i=i+Math.imul(T,K)|0)+Math.imul(k,J)|0,a=a+Math.imul(k,K)|0,n=n+Math.imul(b,Q)|0,i=(i=i+Math.imul(b,tt)|0)+Math.imul(_,Q)|0,a=a+Math.imul(_,tt)|0,n=n+Math.imul(y,rt)|0,i=(i=i+Math.imul(y,nt)|0)+Math.imul(m,rt)|0,a=a+Math.imul(m,nt)|0,n=n+Math.imul(d,at)|0,i=(i=i+Math.imul(d,ot)|0)+Math.imul(v,at)|0,a=a+Math.imul(v,ot)|0;var Tt=(u+(n=n+Math.imul(f,lt)|0)|0)+((8191&(i=(i=i+Math.imul(f,ut)|0)+Math.imul(h,lt)|0))<<13)|0;u=((a=a+Math.imul(h,ut)|0)+(i>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(z,U),i=(i=Math.imul(z,V))+Math.imul(R,U)|0,a=Math.imul(R,V),n=n+Math.imul(O,q)|0,i=(i=i+Math.imul(O,G)|0)+Math.imul(I,q)|0,a=a+Math.imul(I,G)|0,n=n+Math.imul(L,Y)|0,i=(i=i+Math.imul(L,W)|0)+Math.imul(C,Y)|0,a=a+Math.imul(C,W)|0,n=n+Math.imul(M,J)|0,i=(i=i+Math.imul(M,K)|0)+Math.imul(S,J)|0,a=a+Math.imul(S,K)|0,n=n+Math.imul(T,Q)|0,i=(i=i+Math.imul(T,tt)|0)+Math.imul(k,Q)|0,a=a+Math.imul(k,tt)|0,n=n+Math.imul(b,rt)|0,i=(i=i+Math.imul(b,nt)|0)+Math.imul(_,rt)|0,a=a+Math.imul(_,nt)|0,n=n+Math.imul(y,at)|0,i=(i=i+Math.imul(y,ot)|0)+Math.imul(m,at)|0,a=a+Math.imul(m,ot)|0,n=n+Math.imul(d,lt)|0,i=(i=i+Math.imul(d,ut)|0)+Math.imul(v,lt)|0,a=a+Math.imul(v,ut)|0;var kt=(u+(n=n+Math.imul(f,ft)|0)|0)+((8191&(i=(i=i+Math.imul(f,ht)|0)+Math.imul(h,ft)|0))<<13)|0;u=((a=a+Math.imul(h,ht)|0)+(i>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(B,U),i=(i=Math.imul(B,V))+Math.imul(N,U)|0,a=Math.imul(N,V),n=n+Math.imul(z,q)|0,i=(i=i+Math.imul(z,G)|0)+Math.imul(R,q)|0,a=a+Math.imul(R,G)|0,n=n+Math.imul(O,Y)|0,i=(i=i+Math.imul(O,W)|0)+Math.imul(I,Y)|0,a=a+Math.imul(I,W)|0,n=n+Math.imul(L,J)|0,i=(i=i+Math.imul(L,K)|0)+Math.imul(C,J)|0,a=a+Math.imul(C,K)|0,n=n+Math.imul(M,Q)|0,i=(i=i+Math.imul(M,tt)|0)+Math.imul(S,Q)|0,a=a+Math.imul(S,tt)|0,n=n+Math.imul(T,rt)|0,i=(i=i+Math.imul(T,nt)|0)+Math.imul(k,rt)|0,a=a+Math.imul(k,nt)|0,n=n+Math.imul(b,at)|0,i=(i=i+Math.imul(b,ot)|0)+Math.imul(_,at)|0,a=a+Math.imul(_,ot)|0,n=n+Math.imul(y,lt)|0,i=(i=i+Math.imul(y,ut)|0)+Math.imul(m,lt)|0,a=a+Math.imul(m,ut)|0,n=n+Math.imul(d,ft)|0,i=(i=i+Math.imul(d,ht)|0)+Math.imul(v,ft)|0,a=a+Math.imul(v,ht)|0;var At=(u+(n=n+Math.imul(f,dt)|0)|0)+((8191&(i=(i=i+Math.imul(f,vt)|0)+Math.imul(h,dt)|0))<<13)|0;u=((a=a+Math.imul(h,vt)|0)+(i>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,q),i=(i=Math.imul(B,G))+Math.imul(N,q)|0,a=Math.imul(N,G),n=n+Math.imul(z,Y)|0,i=(i=i+Math.imul(z,W)|0)+Math.imul(R,Y)|0,a=a+Math.imul(R,W)|0,n=n+Math.imul(O,J)|0,i=(i=i+Math.imul(O,K)|0)+Math.imul(I,J)|0,a=a+Math.imul(I,K)|0,n=n+Math.imul(L,Q)|0,i=(i=i+Math.imul(L,tt)|0)+Math.imul(C,Q)|0,a=a+Math.imul(C,tt)|0,n=n+Math.imul(M,rt)|0,i=(i=i+Math.imul(M,nt)|0)+Math.imul(S,rt)|0,a=a+Math.imul(S,nt)|0,n=n+Math.imul(T,at)|0,i=(i=i+Math.imul(T,ot)|0)+Math.imul(k,at)|0,a=a+Math.imul(k,ot)|0,n=n+Math.imul(b,lt)|0,i=(i=i+Math.imul(b,ut)|0)+Math.imul(_,lt)|0,a=a+Math.imul(_,ut)|0,n=n+Math.imul(y,ft)|0,i=(i=i+Math.imul(y,ht)|0)+Math.imul(m,ft)|0,a=a+Math.imul(m,ht)|0;var Mt=(u+(n=n+Math.imul(d,dt)|0)|0)+((8191&(i=(i=i+Math.imul(d,vt)|0)+Math.imul(v,dt)|0))<<13)|0;u=((a=a+Math.imul(v,vt)|0)+(i>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,Y),i=(i=Math.imul(B,W))+Math.imul(N,Y)|0,a=Math.imul(N,W),n=n+Math.imul(z,J)|0,i=(i=i+Math.imul(z,K)|0)+Math.imul(R,J)|0,a=a+Math.imul(R,K)|0,n=n+Math.imul(O,Q)|0,i=(i=i+Math.imul(O,tt)|0)+Math.imul(I,Q)|0,a=a+Math.imul(I,tt)|0,n=n+Math.imul(L,rt)|0,i=(i=i+Math.imul(L,nt)|0)+Math.imul(C,rt)|0,a=a+Math.imul(C,nt)|0,n=n+Math.imul(M,at)|0,i=(i=i+Math.imul(M,ot)|0)+Math.imul(S,at)|0,a=a+Math.imul(S,ot)|0,n=n+Math.imul(T,lt)|0,i=(i=i+Math.imul(T,ut)|0)+Math.imul(k,lt)|0,a=a+Math.imul(k,ut)|0,n=n+Math.imul(b,ft)|0,i=(i=i+Math.imul(b,ht)|0)+Math.imul(_,ft)|0,a=a+Math.imul(_,ht)|0;var St=(u+(n=n+Math.imul(y,dt)|0)|0)+((8191&(i=(i=i+Math.imul(y,vt)|0)+Math.imul(m,dt)|0))<<13)|0;u=((a=a+Math.imul(m,vt)|0)+(i>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,J),i=(i=Math.imul(B,K))+Math.imul(N,J)|0,a=Math.imul(N,K),n=n+Math.imul(z,Q)|0,i=(i=i+Math.imul(z,tt)|0)+Math.imul(R,Q)|0,a=a+Math.imul(R,tt)|0,n=n+Math.imul(O,rt)|0,i=(i=i+Math.imul(O,nt)|0)+Math.imul(I,rt)|0,a=a+Math.imul(I,nt)|0,n=n+Math.imul(L,at)|0,i=(i=i+Math.imul(L,ot)|0)+Math.imul(C,at)|0,a=a+Math.imul(C,ot)|0,n=n+Math.imul(M,lt)|0,i=(i=i+Math.imul(M,ut)|0)+Math.imul(S,lt)|0,a=a+Math.imul(S,ut)|0,n=n+Math.imul(T,ft)|0,i=(i=i+Math.imul(T,ht)|0)+Math.imul(k,ft)|0,a=a+Math.imul(k,ht)|0;var Et=(u+(n=n+Math.imul(b,dt)|0)|0)+((8191&(i=(i=i+Math.imul(b,vt)|0)+Math.imul(_,dt)|0))<<13)|0;u=((a=a+Math.imul(_,vt)|0)+(i>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,Q),i=(i=Math.imul(B,tt))+Math.imul(N,Q)|0,a=Math.imul(N,tt),n=n+Math.imul(z,rt)|0,i=(i=i+Math.imul(z,nt)|0)+Math.imul(R,rt)|0,a=a+Math.imul(R,nt)|0,n=n+Math.imul(O,at)|0,i=(i=i+Math.imul(O,ot)|0)+Math.imul(I,at)|0,a=a+Math.imul(I,ot)|0,n=n+Math.imul(L,lt)|0,i=(i=i+Math.imul(L,ut)|0)+Math.imul(C,lt)|0,a=a+Math.imul(C,ut)|0,n=n+Math.imul(M,ft)|0,i=(i=i+Math.imul(M,ht)|0)+Math.imul(S,ft)|0,a=a+Math.imul(S,ht)|0;var Lt=(u+(n=n+Math.imul(T,dt)|0)|0)+((8191&(i=(i=i+Math.imul(T,vt)|0)+Math.imul(k,dt)|0))<<13)|0;u=((a=a+Math.imul(k,vt)|0)+(i>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,rt),i=(i=Math.imul(B,nt))+Math.imul(N,rt)|0,a=Math.imul(N,nt),n=n+Math.imul(z,at)|0,i=(i=i+Math.imul(z,ot)|0)+Math.imul(R,at)|0,a=a+Math.imul(R,ot)|0,n=n+Math.imul(O,lt)|0,i=(i=i+Math.imul(O,ut)|0)+Math.imul(I,lt)|0,a=a+Math.imul(I,ut)|0,n=n+Math.imul(L,ft)|0,i=(i=i+Math.imul(L,ht)|0)+Math.imul(C,ft)|0,a=a+Math.imul(C,ht)|0;var Ct=(u+(n=n+Math.imul(M,dt)|0)|0)+((8191&(i=(i=i+Math.imul(M,vt)|0)+Math.imul(S,dt)|0))<<13)|0;u=((a=a+Math.imul(S,vt)|0)+(i>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,at),i=(i=Math.imul(B,ot))+Math.imul(N,at)|0,a=Math.imul(N,ot),n=n+Math.imul(z,lt)|0,i=(i=i+Math.imul(z,ut)|0)+Math.imul(R,lt)|0,a=a+Math.imul(R,ut)|0,n=n+Math.imul(O,ft)|0,i=(i=i+Math.imul(O,ht)|0)+Math.imul(I,ft)|0,a=a+Math.imul(I,ht)|0;var Pt=(u+(n=n+Math.imul(L,dt)|0)|0)+((8191&(i=(i=i+Math.imul(L,vt)|0)+Math.imul(C,dt)|0))<<13)|0;u=((a=a+Math.imul(C,vt)|0)+(i>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,n=Math.imul(B,lt),i=(i=Math.imul(B,ut))+Math.imul(N,lt)|0,a=Math.imul(N,ut),n=n+Math.imul(z,ft)|0,i=(i=i+Math.imul(z,ht)|0)+Math.imul(R,ft)|0,a=a+Math.imul(R,ht)|0;var Ot=(u+(n=n+Math.imul(O,dt)|0)|0)+((8191&(i=(i=i+Math.imul(O,vt)|0)+Math.imul(I,dt)|0))<<13)|0;u=((a=a+Math.imul(I,vt)|0)+(i>>>13)|0)+(Ot>>>26)|0,Ot&=67108863,n=Math.imul(B,ft),i=(i=Math.imul(B,ht))+Math.imul(N,ft)|0,a=Math.imul(N,ht);var It=(u+(n=n+Math.imul(z,dt)|0)|0)+((8191&(i=(i=i+Math.imul(z,vt)|0)+Math.imul(R,dt)|0))<<13)|0;u=((a=a+Math.imul(R,vt)|0)+(i>>>13)|0)+(It>>>26)|0,It&=67108863;var Dt=(u+(n=Math.imul(B,dt))|0)+((8191&(i=(i=Math.imul(B,vt))+Math.imul(N,dt)|0))<<13)|0;return u=((a=Math.imul(N,vt))+(i>>>13)|0)+(Dt>>>26)|0,Dt&=67108863,l[0]=gt,l[1]=yt,l[2]=mt,l[3]=xt,l[4]=bt,l[5]=_t,l[6]=wt,l[7]=Tt,l[8]=kt,l[9]=At,l[10]=Mt,l[11]=St,l[12]=Et,l[13]=Lt,l[14]=Ct,l[15]=Pt,l[16]=Ot,l[17]=It,l[18]=Dt,0!==u&&(l[19]=u,r.length++),r};function v(t,e,r){return(new g).mulp(t,e,r)}function g(t,e){this.x=t,this.y=e}Math.imul||(d=p),a.prototype.mulTo=function(t,e){var r,n=this.length+t.length;return r=10===this.length&&10===t.length?d(this,t,e):n<63?p(this,t,e):n<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,i=0,a=0;a<r.length-1;a++){var o=i;i=0;for(var s=67108863&n,l=Math.min(a,e.length-1),u=Math.max(0,a-t.length+1);u<=l;u++){var c=a-u,f=(0|t.words[c])*(0|e.words[u]),h=67108863&f;s=67108863&(h=h+s|0),i+=(o=(o=o+(f/67108864|0)|0)+(h>>>26)|0)>>>26,o&=67108863}r.words[a]=s,n=o,o=i}return 0!==n?r.words[a]=n:r.length--,r.strip()}(this,t,e):v(this,t,e),r},g.prototype.makeRBT=function(t){for(var e=new Array(t),r=a.prototype._countBits(t)-1,n=0;n<t;n++)e[n]=this.revBin(n,r,t);return e},g.prototype.revBin=function(t,e,r){if(0===t||t===r-1)return t;for(var n=0,i=0;i<e;i++)n|=(1&t)<<e-i-1,t>>=1;return n},g.prototype.permute=function(t,e,r,n,i,a){for(var o=0;o<a;o++)n[o]=e[t[o]],i[o]=r[t[o]]},g.prototype.transform=function(t,e,r,n,i,a){this.permute(a,t,e,r,n,i);for(var o=1;o<i;o<<=1)for(var s=o<<1,l=Math.cos(2*Math.PI/s),u=Math.sin(2*Math.PI/s),c=0;c<i;c+=s)for(var f=l,h=u,p=0;p<o;p++){var d=r[c+p],v=n[c+p],g=r[c+p+o],y=n[c+p+o],m=f*g-h*y;y=f*y+h*g,g=m,r[c+p]=d+g,n[c+p]=v+y,r[c+p+o]=d-g,n[c+p+o]=v-y,p!==s&&(m=l*f-u*h,h=l*h+u*f,f=m)}},g.prototype.guessLen13b=function(t,e){var r=1|Math.max(e,t),n=1&r,i=0;for(r=r/2|0;r;r>>>=1)i++;return 1<<i+1+n},g.prototype.conjugate=function(t,e,r){if(!(r<=1))for(var n=0;n<r/2;n++){var i=t[n];t[n]=t[r-n-1],t[r-n-1]=i,i=e[n],e[n]=-e[r-n-1],e[r-n-1]=-i}},g.prototype.normalize13b=function(t,e){for(var r=0,n=0;n<e/2;n++){var i=8192*Math.round(t[2*n+1]/e)+Math.round(t[2*n]/e)+r;t[n]=67108863&i,r=i<67108864?0:i/67108864|0}return t},g.prototype.convert13b=function(t,e,r,i){for(var a=0,o=0;o<e;o++)a+=0|t[o],r[2*o]=8191&a,a>>>=13,r[2*o+1]=8191&a,a>>>=13;for(o=2*e;o<i;++o)r[o]=0;n(0===a),n(0==(-8192&a))},g.prototype.stub=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=0;return e},g.prototype.mulp=function(t,e,r){var n=2*this.guessLen13b(t.length,e.length),i=this.makeRBT(n),a=this.stub(n),o=new Array(n),s=new Array(n),l=new Array(n),u=new Array(n),c=new Array(n),f=new Array(n),h=r.words;h.length=n,this.convert13b(t.words,t.length,o,n),this.convert13b(e.words,e.length,u,n),this.transform(o,a,s,l,n,i),this.transform(u,a,c,f,n,i);for(var p=0;p<n;p++){var d=s[p]*c[p]-l[p]*f[p];l[p]=s[p]*f[p]+l[p]*c[p],s[p]=d}return this.conjugate(s,l,n),this.transform(s,l,h,a,n,i),this.conjugate(h,a,n),this.normalize13b(h,n),r.negative=t.negative^e.negative,r.length=t.length+e.length,r.strip()},a.prototype.mul=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},a.prototype.mulf=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),v(this,t,e)},a.prototype.imul=function(t){return this.clone().mulTo(t,this)},a.prototype.imuln=function(t){n("number"==typeof t),n(t<67108864);for(var e=0,r=0;r<this.length;r++){var i=(0|this.words[r])*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[r]=67108863&a}return 0!==e&&(this.words[r]=e,this.length++),this},a.prototype.muln=function(t){return this.clone().imuln(t)},a.prototype.sqr=function(){return this.mul(this)},a.prototype.isqr=function(){return this.imul(this.clone())},a.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r<e.length;r++){var n=r/26|0,i=r%26;e[r]=(t.words[n]&1<<i)>>>i}return e}(t);if(0===e.length)return new a(1);for(var r=this,n=0;n<e.length&&0===e[n];n++,r=r.sqr());if(++n<e.length)for(var i=r.sqr();n<e.length;n++,i=i.sqr())0!==e[n]&&(r=r.mul(i));return r},a.prototype.iushln=function(t){n("number"==typeof t&&t>=0);var e,r=t%26,i=(t-r)/26,a=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e<this.length;e++){var s=this.words[e]&a,l=(0|this.words[e])-s<<r;this.words[e]=l|o,o=s>>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==i){for(e=this.length-1;e>=0;e--)this.words[e+i]=this.words[e];for(e=0;e<i;e++)this.words[e]=0;this.length+=i}return this.strip()},a.prototype.ishln=function(t){return n(0===this.negative),this.iushln(t)},a.prototype.iushrn=function(t,e,r){var i;n("number"==typeof t&&t>=0),i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<<a,l=r;if(i-=o,i=Math.max(0,i),l){for(var u=0;u<o;u++)l.words[u]=this.words[u];l.length=o}if(0===o);else if(this.length>o)for(this.length-=o,u=0;u<this.length;u++)this.words[u]=this.words[u+o];else this.words[0]=0,this.length=1;var c=0;for(u=this.length-1;u>=0&&(0!==c||u>=i);u--){var f=0|this.words[u];this.words[u]=c<<26-a|f>>>a,c=f&s}return l&&0!==c&&(l.words[l.length++]=c),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},a.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},a.prototype.shln=function(t){return this.clone().ishln(t)},a.prototype.ushln=function(t){return this.clone().iushln(t)},a.prototype.shrn=function(t){return this.clone().ishrn(t)},a.prototype.ushrn=function(t){return this.clone().iushrn(t)},a.prototype.testn=function(t){n("number"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,i=1<<e;return!(this.length<=r||!(this.words[r]&i))},a.prototype.imaskn=function(t){n("number"==typeof t&&t>=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,"imaskn works only with positive numbers"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},a.prototype.maskn=function(t){return this.clone().imaskn(t)},a.prototype.iaddn=function(t){return n("number"==typeof t),n(t<67108864),t<0?this.isubn(-t):0!==this.negative?1===this.length&&(0|this.words[0])<t?(this.words[0]=t-(0|this.words[0]),this.negative=0,this):(this.negative=0,this.isubn(t),this.negative=1,this):this._iaddn(t)},a.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},a.prototype.isubn=function(t){if(n("number"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},a.prototype.addn=function(t){return this.clone().iaddn(t)},a.prototype.subn=function(t){return this.clone().isubn(t)},a.prototype.iabs=function(){return this.negative=0,this},a.prototype.abs=function(){return this.clone().iabs()},a.prototype._ishlnsubmul=function(t,e,r){var i,a,o=t.length+r;this._expand(o);var s=0;for(i=0;i<t.length;i++){a=(0|this.words[i+r])+s;var l=(0|t.words[i])*e;s=((a-=67108863&l)>>26)-(l/67108864|0),this.words[i+r]=67108863&a}for(;i<this.length-r;i++)s=(a=(0|this.words[i+r])+s)>>26,this.words[i+r]=67108863&a;if(0===s)return this.strip();for(n(-1===s),s=0,i=0;i<this.length;i++)s=(a=-(0|this.words[i])+s)>>26,this.words[i]=67108863&a;return this.negative=1,this.strip()},a.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),i=t,o=0|i.words[i.length-1];0!=(r=26-this._countBits(o))&&(i=i.ushln(r),n.iushln(r),o=0|i.words[i.length-1]);var s,l=n.length-i.length;if("mod"!==e){(s=new a(null)).length=l+1,s.words=new Array(s.length);for(var u=0;u<s.length;u++)s.words[u]=0}var c=n.clone()._ishlnsubmul(i,1,l);0===c.negative&&(n=c,s&&(s.words[l]=1));for(var f=l-1;f>=0;f--){var h=67108864*(0|n.words[i.length+f])+(0|n.words[i.length+f-1]);for(h=Math.min(h/o|0,67108863),n._ishlnsubmul(i,h,f);0!==n.negative;)h--,n.negative=0,n._ishlnsubmul(i,1,f),n.isZero()||(n.negative^=1);s&&(s.words[f]=h)}return s&&s.strip(),n.strip(),"div"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},a.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new a(0),mod:new a(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),"mod"!==e&&(i=s.div.neg()),"div"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:i,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),"mod"!==e&&(i=s.div.neg()),{div:i,mod:s.mod}):0!=(this.negative&t.negative)?(s=this.neg().divmod(t.neg(),e),"div"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new a(0),mod:this}:1===t.length?"div"===e?{div:this.divn(t.words[0]),mod:null}:"mod"===e?{div:null,mod:new a(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new a(this.modn(t.words[0]))}:this._wordDiv(t,e);var i,o,s},a.prototype.div=function(t){return this.divmod(t,"div",!1).div},a.prototype.mod=function(t){return this.divmod(t,"mod",!1).mod},a.prototype.umod=function(t){return this.divmod(t,"mod",!0).mod},a.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},a.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,i=this.length-1;i>=0;i--)r=(e*r+(0|this.words[i]))%t;return r},a.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var i=(0|this.words[r])+67108864*e;this.words[r]=i/t|0,e=i%t}return this.strip()},a.prototype.divn=function(t){return this.clone().idivn(t)},a.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i=new a(1),o=new a(0),s=new a(0),l=new a(1),u=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++u;for(var c=r.clone(),f=e.clone();!e.isZero();){for(var h=0,p=1;0==(e.words[0]&p)&&h<26;++h,p<<=1);if(h>0)for(e.iushrn(h);h-- >0;)(i.isOdd()||o.isOdd())&&(i.iadd(c),o.isub(f)),i.iushrn(1),o.iushrn(1);for(var d=0,v=1;0==(r.words[0]&v)&&d<26;++d,v<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(c),l.isub(f)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),i.isub(s),o.isub(l)):(r.isub(e),s.isub(i),l.isub(o))}return{a:s,b:l,gcd:r.iushln(u)}},a.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i,o=new a(1),s=new a(0),l=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var u=0,c=1;0==(e.words[0]&c)&&u<26;++u,c<<=1);if(u>0)for(e.iushrn(u);u-- >0;)o.isOdd()&&o.iadd(l),o.iushrn(1);for(var f=0,h=1;0==(r.words[0]&h)&&f<26;++f,h<<=1);if(f>0)for(r.iushrn(f);f-- >0;)s.isOdd()&&s.iadd(l),s.iushrn(1);e.cmp(r)>=0?(e.isub(r),o.isub(s)):(r.isub(e),s.isub(o))}return(i=0===e.cmpn(1)?o:s).cmpn(0)<0&&i.iadd(t),i},a.prototype.gcd=function(t){if(this.isZero())return t.abs();if(t.isZero())return this.abs();var e=this.clone(),r=t.clone();e.negative=0,r.negative=0;for(var n=0;e.isEven()&&r.isEven();n++)e.iushrn(1),r.iushrn(1);for(;;){for(;e.isEven();)e.iushrn(1);for(;r.isEven();)r.iushrn(1);var i=e.cmp(r);if(i<0){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.iushln(n)},a.prototype.invm=function(t){return this.egcd(t).a.umod(t)},a.prototype.isEven=function(){return 0==(1&this.words[0])},a.prototype.isOdd=function(){return 1==(1&this.words[0])},a.prototype.andln=function(t){return this.words[0]&t},a.prototype.bincn=function(t){n("number"==typeof t);var e=t%26,r=(t-e)/26,i=1<<e;if(this.length<=r)return this._expand(r+1),this.words[r]|=i,this;for(var a=i,o=r;0!==a&&o<this.length;o++){var s=0|this.words[o];a=(s+=a)>>>26,s&=67108863,this.words[o]=s}return 0!==a&&(this.words[o]=a,this.length++),this},a.prototype.isZero=function(){return 1===this.length&&0===this.words[0]},a.prototype.cmpn=function(t){var e,r=t<0;if(0!==this.negative&&!r)return-1;if(0===this.negative&&r)return 1;if(this.strip(),this.length>1)e=1;else{r&&(t=-t),n(t<=67108863,"Number is too big");var i=0|this.words[0];e=i===t?0:i<t?-1:1}return 0!==this.negative?0|-e:e},a.prototype.cmp=function(t){if(0!==this.negative&&0===t.negative)return-1;if(0===this.negative&&0!==t.negative)return 1;var e=this.ucmp(t);return 0!==this.negative?0|-e:e},a.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=0|this.words[r],i=0|t.words[r];if(n!==i){n<i?e=-1:n>i&&(e=1);break}}return e},a.prototype.gtn=function(t){return 1===this.cmpn(t)},a.prototype.gt=function(t){return 1===this.cmp(t)},a.prototype.gten=function(t){return this.cmpn(t)>=0},a.prototype.gte=function(t){return this.cmp(t)>=0},a.prototype.ltn=function(t){return-1===this.cmpn(t)},a.prototype.lt=function(t){return-1===this.cmp(t)},a.prototype.lten=function(t){return this.cmpn(t)<=0},a.prototype.lte=function(t){return this.cmp(t)<=0},a.prototype.eqn=function(t){return 0===this.cmpn(t)},a.prototype.eq=function(t){return 0===this.cmp(t)},a.red=function(t){return new T(t)},a.prototype.toRed=function(t){return n(!this.red,"Already a number in reduction context"),n(0===this.negative,"red works only with positives"),t.convertTo(this)._forceRed(t)},a.prototype.fromRed=function(){return n(this.red,"fromRed works only with numbers in reduction context"),this.red.convertFrom(this)},a.prototype._forceRed=function(t){return this.red=t,this},a.prototype.forceRed=function(t){return n(!this.red,"Already a number in reduction context"),this._forceRed(t)},a.prototype.redAdd=function(t){return n(this.red,"redAdd works only with red numbers"),this.red.add(this,t)},a.prototype.redIAdd=function(t){return n(this.red,"redIAdd works only with red numbers"),this.red.iadd(this,t)},a.prototype.redSub=function(t){return n(this.red,"redSub works only with red numbers"),this.red.sub(this,t)},a.prototype.redISub=function(t){return n(this.red,"redISub works only with red numbers"),this.red.isub(this,t)},a.prototype.redShl=function(t){return n(this.red,"redShl works only with red numbers"),this.red.shl(this,t)},a.prototype.redMul=function(t){return n(this.red,"redMul works only with red numbers"),this.red._verify2(this,t),this.red.mul(this,t)},a.prototype.redIMul=function(t){return n(this.red,"redMul works only with red numbers"),this.red._verify2(this,t),this.red.imul(this,t)},a.prototype.redSqr=function(){return n(this.red,"redSqr works only with red numbers"),this.red._verify1(this),this.red.sqr(this)},a.prototype.redISqr=function(){return n(this.red,"redISqr works only with red numbers"),this.red._verify1(this),this.red.isqr(this)},a.prototype.redSqrt=function(){return n(this.red,"redSqrt works only with red numbers"),this.red._verify1(this),this.red.sqrt(this)},a.prototype.redInvm=function(){return n(this.red,"redInvm works only with red numbers"),this.red._verify1(this),this.red.invm(this)},a.prototype.redNeg=function(){return n(this.red,"redNeg works only with red numbers"),this.red._verify1(this),this.red.neg(this)},a.prototype.redPow=function(t){return n(this.red&&!t.red,"redPow(normalNum)"),this.red._verify1(this),this.red.pow(this,t)};var y={k256:null,p224:null,p192:null,p25519:null};function m(t,e){this.name=t,this.p=new a(e,16),this.n=this.p.bitLength(),this.k=new a(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}function x(){m.call(this,"k256","ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff fffffffe fffffc2f")}function b(){m.call(this,"p224","ffffffff ffffffff ffffffff ffffffff 00000000 00000000 00000001")}function _(){m.call(this,"p192","ffffffff ffffffff ffffffff fffffffe ffffffff ffffffff")}function w(){m.call(this,"25519","7fffffffffffffff ffffffffffffffff ffffffffffffffff ffffffffffffffed")}function T(t){if("string"==typeof t){var e=a._prime(t);this.m=e.p,this.prime=e}else n(t.gtn(1),"modulus must be greater than 1"),this.m=t,this.prime=null}function k(t){T.call(this,t),this.shift=this.m.bitLength(),this.shift%26!=0&&(this.shift+=26-this.shift%26),this.r=new a(1).iushln(this.shift),this.r2=this.imod(this.r.sqr()),this.rinv=this.r._invmp(this.m),this.minv=this.rinv.mul(this.r).isubn(1).div(this.m),this.minv=this.minv.umod(this.r),this.minv=this.r.sub(this.minv)}m.prototype._tmp=function(){var t=new a(null);return t.words=new Array(Math.ceil(this.n/13)),t},m.prototype.ireduce=function(t){var e,r=t;do{this.split(r,this.tmp),e=(r=(r=this.imulK(r)).iadd(this.tmp)).bitLength()}while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):void 0!==r.strip?r.strip():r._strip(),r},m.prototype.split=function(t,e){t.iushrn(this.n,0,e)},m.prototype.imulK=function(t){return t.imul(this.k)},i(x,m),x.prototype.split=function(t,e){for(var r=4194303,n=Math.min(t.length,9),i=0;i<n;i++)e.words[i]=t.words[i];if(e.length=n,t.length<=9)return t.words[0]=0,void(t.length=1);var a=t.words[9];for(e.words[e.length++]=a&r,i=10;i<t.length;i++){var o=0|t.words[i];t.words[i-10]=(o&r)<<4|a>>>22,a=o}a>>>=22,t.words[i-10]=a,0===a&&t.length>10?t.length-=10:t.length-=9},x.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e=0,r=0;r<t.length;r++){var n=0|t.words[r];e+=977*n,t.words[r]=67108863&e,e=64*n+(e/67108864|0)}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},i(b,m),i(_,m),i(w,m),w.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*(0|t.words[r])+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},a._prime=function(t){if(y[t])return y[t];var e;if("k256"===t)e=new x;else if("p224"===t)e=new b;else if("p192"===t)e=new _;else{if("p25519"!==t)throw new Error("Unknown prime "+t);e=new w}return y[t]=e,e},T.prototype._verify1=function(t){n(0===t.negative,"red works only with positives"),n(t.red,"red works only with red numbers")},T.prototype._verify2=function(t,e){n(0==(t.negative|e.negative),"red works only with positives"),n(t.red&&t.red===e.red,"red works only with red numbers")},T.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.umod(this.m)._forceRed(this)},T.prototype.neg=function(t){return t.isZero()?t.clone():this.m.sub(t)._forceRed(this)},T.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},T.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},T.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},T.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},T.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.ushln(e))},T.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},T.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},T.prototype.isqr=function(t){return this.imul(t,t.clone())},T.prototype.sqr=function(t){return this.mul(t,t)},T.prototype.sqrt=function(t){if(t.isZero())return t.clone();var e=this.m.andln(3);if(n(e%2==1),3===e){var r=this.m.add(new a(1)).iushrn(2);return this.pow(t,r)}for(var i=this.m.subn(1),o=0;!i.isZero()&&0===i.andln(1);)o++,i.iushrn(1);n(!i.isZero());var s=new a(1).toRed(this),l=s.redNeg(),u=this.m.subn(1).iushrn(1),c=this.m.bitLength();for(c=new a(2*c*c).toRed(this);0!==this.pow(c,u).cmp(l);)c.redIAdd(l);for(var f=this.pow(c,i),h=this.pow(t,i.addn(1).iushrn(1)),p=this.pow(t,i),d=o;0!==p.cmp(s);){for(var v=p,g=0;0!==v.cmp(s);g++)v=v.redSqr();n(g<d);var y=this.pow(f,new a(1).iushln(d-g-1));h=h.redMul(y),f=y.redSqr(),p=p.redMul(f),d=g}return h},T.prototype.invm=function(t){var e=t._invmp(this.m);return 0!==e.negative?(e.negative=0,this.imod(e).redNeg()):this.imod(e)},T.prototype.pow=function(t,e){if(e.isZero())return new a(1).toRed(this);if(0===e.cmpn(1))return t.clone();var r=new Array(16);r[0]=new a(1).toRed(this),r[1]=t;for(var n=2;n<r.length;n++)r[n]=this.mul(r[n-1],t);var i=r[0],o=0,s=0,l=e.bitLength()%26;for(0===l&&(l=26),n=e.length-1;n>=0;n--){for(var u=e.words[n],c=l-1;c>=0;c--){var f=u>>c&1;i!==r[0]&&(i=this.sqr(i)),0!==f||0!==o?(o<<=1,o|=f,(4==++s||0===n&&0===c)&&(i=this.mul(i,r[o]),s=0,o=0)):s=0}l=26}return i},T.prototype.convertTo=function(t){var e=t.umod(this.m);return e===t?e.clone():e},T.prototype.convertFrom=function(t){var e=t.clone();return e.red=null,e},a.mont=function(t){return new k(t)},i(k,T),k.prototype.convertTo=function(t){return this.imod(t.ushln(this.shift))},k.prototype.convertFrom=function(t){var e=this.imod(t.mul(this.rinv));return e.red=null,e},k.prototype.imul=function(t,e){if(t.isZero()||e.isZero())return t.words[0]=0,t.length=1,t;var r=t.imul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).iushrn(this.shift),a=i;return i.cmp(this.m)>=0?a=i.isub(this.m):i.cmpn(0)<0&&(a=i.iadd(this.m)),a._forceRed(this)},k.prototype.mul=function(t,e){if(t.isZero()||e.isZero())return new a(0)._forceRed(this);var 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f=o[o.length-2];for(f.left===s?f.left=null:f.right===s&&(f.right=null),o.pop(),l=0;l<o.length;++l)o[l]._count--;return new a(this.tree._compare,o[0])}if(s.left||s.right){for(s.left?h(s,s.left):s.right&&h(s,s.right),s._color=1,l=0;l<o.length-1;++l)o[l]._count--;return new a(this.tree._compare,o[0])}if(1===o.length)return new a(this.tree._compare,null);for(l=0;l<o.length;++l)o[l]._count--;var p=o[o.length-2];return function(t){for(var e,a,o,s,l=t.length-1;l>=0;--l){if(e=t[l],0===l)return void(e._color=1);if((a=t[l-1]).left===e){if((o=a.right).right&&0===o.right._color)return s=(o=a.right=r(o)).right=r(o.right),a.right=o.left,o.left=a,o.right=s,o._color=a._color,e._color=1,a._color=1,s._color=1,i(a),i(o),l>1&&((u=t[l-2]).left===a?u.left=o:u.right=o),void(t[l-1]=o);if(o.left&&0===o.left._color)return s=(o=a.right=r(o)).left=r(o.left),a.right=s.left,o.left=s.right,s.left=a,s.right=o,s._color=a._color,a._color=1,o._color=1,e._color=1,i(a),i(o),i(s),l>1&&((u=t[l-2]).left===a?u.left=s:u.right=s),void(t[l-1]=s);if(1===o._color){if(0===a._color)return a._color=1,void(a.right=n(0,o));a.right=n(0,o);continue}o=r(o),a.right=o.left,o.left=a,o._color=a._color,a._color=0,i(a),i(o),l>1&&((u=t[l-2]).left===a?u.left=o:u.right=o),t[l-1]=o,t[l]=a,l+1<t.length?t[l+1]=e:t.push(e),l+=2}else{if((o=a.left).left&&0===o.left._color)return s=(o=a.left=r(o)).left=r(o.left),a.left=o.right,o.right=a,o.left=s,o._color=a._color,e._color=1,a._color=1,s._color=1,i(a),i(o),l>1&&((u=t[l-2]).right===a?u.right=o:u.left=o),void(t[l-1]=o);if(o.right&&0===o.right._color)return 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a(this.tree._compare,n[0])},f.prev=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.left)for(e=e.left;e;)t.push(e),e=e.right;else for(t.pop();t.length>0&&t[t.length-1].left===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(f,"hasPrev",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].left)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].right===t[e])return!0;return!1}})},7453:function(t,e,r){"use strict";t.exports=function(t,e){var r=new c(t);return r.update(e),r};var n=r(9557),i=r(1681),a=r(1011),o=r(2864),s=r(8468),l=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]);function u(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function 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v=l("labels");l("labelFont")&&(v=!0),o("labelEnable"),a("labelSize"),a("labelPad"),u("labelColor"),o("lineEnable"),o("lineMirror"),a("lineWidth"),u("lineColor"),o("lineTickEnable"),o("lineTickMirror"),a("lineTickLength"),a("lineTickWidth"),u("lineTickColor"),o("gridEnable"),a("gridWidth"),u("gridColor"),o("zeroEnable"),u("zeroLineColor"),a("zeroLineWidth"),o("backgroundEnable"),u("backgroundColor"),this._text?this._text&&(v||c)&&this._text.update(this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont):this._text=n(this.gl,this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont),this._lines&&c&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=i(this.gl,this.bounds,this.ticks))};var p=[new h,new h,new h];function d(t,e,r,n,i){for(var a=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,u=n[e],c=0;c<3;++c)if(e!==c){var f=a,h=s,p=o,d=l;u&1<<c&&(f=s,h=a,p=l,d=o),f[c]=r[0][c],h[c]=r[1][c],i[c]>0?(p[c]=-1,d[c]=0):(p[c]=0,d[c]=1)}}var v=[0,0,0],g={model:l,view:l,projection:l,_ortho:!1};f.isOpaque=function(){return!0},f.isTransparent=function(){return!1},f.drawTransparent=function(t){};var y=[0,0,0],m=[0,0,0],x=[0,0,0];f.draw=function(t){t=t||g;for(var e=this.gl,r=t.model||l,n=t.view||l,i=t.projection||l,a=this.bounds,s=t._ortho||!1,c=o(r,n,i,a,s),f=c.cubeEdges,h=c.axis,b=n[12],_=n[13],w=n[14],T=n[15],k=(s?2:1)*this.pixelRatio*(i[3]*b+i[7]*_+i[11]*w+i[15]*T)/e.drawingBufferHeight,A=0;A<3;++A)this.lastCubeProps.cubeEdges[A]=f[A],this.lastCubeProps.axis[A]=h[A];var M=p;for(A=0;A<3;++A)d(p[A],A,this.bounds,f,h);e=this.gl;var S,E,L,C=v;for(A=0;A<3;++A)this.backgroundEnable[A]?C[A]=h[A]:C[A]=0;for(this._background.draw(r,n,i,a,C,this.backgroundColor),this._lines.bind(r,n,i,this),A=0;A<3;++A){var P=[0,0,0];h[A]>0?P[A]=a[1][A]:P[A]=a[0][A];for(var O=0;O<2;++O){var I=(A+1+O)%3,D=(A+1+(1^O))%3;this.gridEnable[I]&&this._lines.drawGrid(I,D,this.bounds,P,this.gridColor[I],this.gridWidth[I]*this.pixelRatio)}for(O=0;O<2;++O)I=(A+1+O)%3,D=(A+1+(1^O))%3,this.zeroEnable[D]&&Math.min(a[0][D],a[1][D])<=0&&Math.max(a[0][D],a[1][D])>=0&&this._lines.drawZero(I,D,this.bounds,P,this.zeroLineColor[D],this.zeroLineWidth[D]*this.pixelRatio)}for(A=0;A<3;++A){this.lineEnable[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].primalOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio),this.lineMirror[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].mirrorOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio);var z=u(y,M[A].primalMinor),R=u(m,M[A].mirrorMinor),F=this.lineTickLength;for(O=0;O<3;++O){var B=k/r[5*O];z[O]*=F[O]*B,R[O]*=F[O]*B}this.lineTickEnable[A]&&this._lines.drawAxisTicks(A,M[A].primalOffset,z,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio),this.lineTickMirror[A]&&this._lines.drawAxisTicks(A,M[A].mirrorOffset,R,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio)}function N(t){(L=[0,0,0])[t]=1}function j(t,e,r){var n=(t+1)%3,i=(t+2)%3,a=e[n],o=e[i],s=r[n],l=r[i];a>0&&l>0||a>0&&l<0||a<0&&l>0||a<0&&l<0?N(n):(o>0&&s>0||o>0&&s<0||o<0&&s>0||o<0&&s<0)&&N(i)}for(this._lines.unbind(),this._text.bind(r,n,i,this.pixelRatio),A=0;A<3;++A){var U=M[A].primalMinor,V=M[A].mirrorMinor,H=u(x,M[A].primalOffset);for(O=0;O<3;++O)this.lineTickEnable[A]&&(H[O]+=k*U[O]*Math.max(this.lineTickLength[O],0)/r[5*O]);var q=[0,0,0];if(q[A]=1,this.tickEnable[A]){for(-3600===this.tickAngle[A]?(this.tickAngle[A]=0,this.tickAlign[A]="auto"):this.tickAlign[A]=-1,E=1,"auto"===(S=[this.tickAlign[A],.5,E])[0]?S[0]=0:S[0]=parseInt(""+S[0]),L=[0,0,0],j(A,U,V),O=0;O<3;++O)H[O]+=k*U[O]*this.tickPad[O]/r[5*O];this._text.drawTicks(A,this.tickSize[A],this.tickAngle[A],H,this.tickColor[A],q,L,S)}if(this.labelEnable[A]){for(E=0,L=[0,0,0],this.labels[A].length>4&&(N(A),E=1),"auto"===(S=[this.labelAlign[A],.5,E])[0]?S[0]=0:S[0]=parseInt(""+S[0]),O=0;O<3;++O)H[O]+=k*U[O]*this.labelPad[O]/r[5*O];H[A]+=.5*(a[0][A]+a[1][A]),this._text.drawLabel(A,this.labelSize[A],this.labelAngle[A],H,this.labelColor[A],[0,0,0],L,S)}}this._text.unbind()},f.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},1011:function(t,e,r){"use strict";t.exports=function(t){for(var e=[],r=[],s=0,l=0;l<3;++l)for(var u=(l+1)%3,c=(l+2)%3,f=[0,0,0],h=[0,0,0],p=-1;p<=1;p+=2){r.push(s,s+2,s+1,s+1,s+2,s+3),f[l]=p,h[l]=p;for(var d=-1;d<=1;d+=2){f[u]=d;for(var v=-1;v<=1;v+=2)f[c]=v,e.push(f[0],f[1],f[2],h[0],h[1],h[2]),s+=1}var g=u;u=c,c=g}var y=n(t,new Float32Array(e)),m=n(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),x=i(t,[{buffer:y,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:y,type:t.FLOAT,size:3,offset:12,stride:24}],m),b=a(t);return b.attributes.position.location=0,b.attributes.normal.location=1,new o(t,y,x,b)};var n=r(5827),i=r(2944),a=r(1943).bg;function o(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}var s=o.prototype;s.draw=function(t,e,r,n,i,a){for(var o=!1,s=0;s<3;++s)o=o||i[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:i,colors:a},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),this.vao.unbind(),l.disable(l.POLYGON_OFFSET_FILL)}},s.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},2864:function(t,e,r){"use strict";t.exports=function(t,e,r,a,p){i(s,e,t),i(s,r,s);for(var m=0,x=0;x<2;++x){c[2]=a[x][2];for(var b=0;b<2;++b){c[1]=a[b][1];for(var _=0;_<2;++_)c[0]=a[_][0],h(l[m],c,s),m+=1}}var w=-1;for(x=0;x<8;++x){for(var T=l[x][3],k=0;k<3;++k)u[x][k]=l[x][k]/T;p&&(u[x][2]*=-1),T<0&&(w<0||u[x][2]<u[w][2])&&(w=x)}if(w<0){w=0;for(var A=0;A<3;++A){for(var M=(A+2)%3,S=(A+1)%3,E=-1,L=-1,C=0;C<2;++C){var P=(I=C<<A)+(C<<M)+(1-C<<S),O=I+(1-C<<M)+(C<<S);o(u[I],u[P],u[O],f)<0||(C?E=1:L=1)}if(E<0||L<0)L>E&&(w|=1<<A);else{for(C=0;C<2;++C){P=(I=C<<A)+(C<<M)+(1-C<<S),O=I+(1-C<<M)+(C<<S);var I,D=d([l[I],l[P],l[O],l[I+(1<<M)+(1<<S)]]);C?E=D:L=D}L>E&&(w|=1<<A)}}}var z=7^w,R=-1;for(x=0;x<8;++x)x!==w&&x!==z&&(R<0||u[R][1]>u[x][1])&&(R=x);var F=-1;for(x=0;x<3;++x)(N=R^1<<x)!==w&&N!==z&&(F<0&&(F=N),(S=u[N])[0]<u[F][0]&&(F=N));var B=-1;for(x=0;x<3;++x){var N;(N=R^1<<x)!==w&&N!==z&&N!==F&&(B<0&&(B=N),(S=u[N])[0]>u[B][0]&&(B=N))}var j=v;j[0]=j[1]=j[2]=0,j[n.log2(F^R)]=R&F,j[n.log2(R^B)]=R&B;var U=7^B;U===w||U===z?(U=7^F,j[n.log2(B^U)]=U&B):j[n.log2(F^U)]=U&F;var V=g,H=w;for(A=0;A<3;++A)V[A]=H&1<<A?-1:1;return y};var n=r(2288),i=r(104),a=r(4670),o=r(417),s=new Array(16),l=new Array(8),u=new Array(8),c=new Array(3),f=[0,0,0];function h(t,e,r){for(var n=0;n<4;++n){t[n]=r[12+n];for(var i=0;i<3;++i)t[n]+=e[i]*r[4*i+n]}}!function(){for(var t=0;t<8;++t)l[t]=[1,1,1,1],u[t]=[1,1,1]}();var p=[[0,0,1,0,0],[0,0,-1,1,0],[0,-1,0,1,0],[0,1,0,1,0],[-1,0,0,1,0],[1,0,0,1,0]];function d(t){for(var e=0;e<p.length;++e)if((t=a.positive(t,p[e])).length<3)return 0;var r=t[0],n=r[0]/r[3],i=r[1]/r[3],o=0;for(e=1;e+1<t.length;++e){var s=t[e],l=t[e+1],u=s[0]/s[3]-n,c=s[1]/s[3]-i,f=l[0]/l[3]-n,h=l[1]/l[3]-i;o+=Math.abs(u*h-c*f)}return o}var v=[1,1,1],g=[0,0,0],y={cubeEdges:v,axis:g}},1681:function(t,e,r){"use strict";t.exports=function(t,e,r){var o=[],s=[0,0,0],l=[0,0,0],u=[0,0,0],c=[0,0,0];o.push(0,0,1,0,1,1,0,0,-1,0,0,-1,0,1,1,0,1,-1);for(var f=0;f<3;++f){for(var h=o.length/3|0,d=0;d<r[f].length;++d){var v=+r[f][d].x;o.push(v,0,1,v,1,1,v,0,-1,v,0,-1,v,1,1,v,1,-1)}var g=o.length/3|0;s[f]=h,l[f]=g-h,h=o.length/3|0;for(var y=0;y<r[f].length;++y)v=+r[f][y].x,o.push(v,0,1,v,1,1,v,0,-1,v,0,-1,v,1,1,v,1,-1);g=o.length/3|0,u[f]=h,c[f]=g-h}var m=n(t,new Float32Array(o)),x=i(t,[{buffer:m,type:t.FLOAT,size:3,stride:0,offset:0}]),b=a(t);return b.attributes.position.location=0,new p(t,m,x,b,l,s,c,u)};var n=r(5827),i=r(2944),a=r(1943).j,o=[0,0,0],s=[0,0,0],l=[0,0,0],u=[0,0,0],c=[1,1];function f(t){return t[0]=t[1]=t[2]=0,t}function h(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function p(t,e,r,n,i,a,o,s){this.gl=t,this.vertBuffer=e,this.vao=r,this.shader=n,this.tickCount=i,this.tickOffset=a,this.gridCount=o,this.gridOffset=s}var d=p.prototype;d.bind=function(t,e,r){this.shader.bind(),this.shader.uniforms.model=t,this.shader.uniforms.view=e,this.shader.uniforms.projection=r,c[0]=this.gl.drawingBufferWidth,c[1]=this.gl.drawingBufferHeight,this.shader.uniforms.screenShape=c,this.vao.bind()},d.unbind=function(){this.vao.unbind()},d.drawAxisLine=function(t,e,r,n,i){var a=f(s);this.shader.uniforms.majorAxis=s,a[t]=e[1][t]-e[0][t],this.shader.uniforms.minorAxis=a;var o,c=h(u,r);c[t]+=e[0][t],this.shader.uniforms.offset=c,this.shader.uniforms.lineWidth=i,this.shader.uniforms.color=n,(o=f(l))[(t+2)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6),(o=f(l))[(t+1)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6)},d.drawAxisTicks=function(t,e,r,n,i){if(this.tickCount[t]){var a=f(o);a[t]=1,this.shader.uniforms.majorAxis=a,this.shader.uniforms.offset=e,this.shader.uniforms.minorAxis=r,this.shader.uniforms.color=n,this.shader.uniforms.lineWidth=i;var s=f(l);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}},d.drawGrid=function(t,e,r,n,i,a){if(this.gridCount[t]){var c=f(s);c[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=c;var p=h(u,n);p[e]+=r[0][e],this.shader.uniforms.offset=p;var d=f(o);d[t]=1,this.shader.uniforms.majorAxis=d;var v=f(l);v[t]=1,this.shader.uniforms.screenAxis=v,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])}},d.drawZero=function(t,e,r,n,i,a){var o=f(s);this.shader.uniforms.majorAxis=o,o[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=o;var c=h(u,n);c[t]+=r[0][t],this.shader.uniforms.offset=c;var p=f(l);p[e]=1,this.shader.uniforms.screenAxis=p,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,6)},d.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},1943:function(t,e,r){"use strict";var n=r(6832),i=r(5158),a=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position;\n\nuniform mat4 model, view, projection;\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\nuniform float lineWidth;\nuniform vec2 screenShape;\n\nvec3 project(vec3 p) {\n  vec4 pp = projection * view * model * vec4(p, 1.0);\n  return pp.xyz / max(pp.w, 0.0001);\n}\n\nvoid main() {\n  vec3 major = position.x * majorAxis;\n  vec3 minor = position.y * minorAxis;\n\n  vec3 vPosition = major + minor + offset;\n  vec3 pPosition = project(vPosition);\n  vec3 offset = project(vPosition + screenAxis * position.z);\n\n  vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\n\n  gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\n}\n"]),o=n(["precision highp float;\n#define GLSLIFY 1\n\nuniform vec4 color;\nvoid main() {\n  gl_FragColor = color;\n}"]);e.j=function(t){return i(t,a,o,null,[{name:"position",type:"vec3"}])};var s=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position;\n\nuniform mat4 model, view, projection;\nuniform vec3 offset, axis, alignDir, alignOpt;\nuniform float scale, angle, pixelScale;\nuniform vec2 resolution;\n\nvec3 project(vec3 p) {\n  vec4 pp = projection * view * model * vec4(p, 1.0);\n  return pp.xyz / max(pp.w, 0.0001);\n}\n\nfloat computeViewAngle(vec3 a, vec3 b) {\n  vec3 A = project(a);\n  vec3 B = project(b);\n\n  return atan(\n    (B.y - A.y) * resolution.y,\n    (B.x - A.x) * resolution.x\n  );\n}\n\nconst float PI = 3.141592;\nconst float TWO_PI = 2.0 * PI;\nconst float HALF_PI = 0.5 * PI;\nconst float ONE_AND_HALF_PI = 1.5 * PI;\n\nint option = int(floor(alignOpt.x + 0.001));\nfloat hv_ratio =       alignOpt.y;\nbool enableAlign =    (alignOpt.z != 0.0);\n\nfloat mod_angle(float a) {\n  return mod(a, PI);\n}\n\nfloat positive_angle(float a) {\n  return mod_angle((a < 0.0) ?\n    a + TWO_PI :\n    a\n  );\n}\n\nfloat look_upwards(float a) {\n  float b = positive_angle(a);\n  return ((b > HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\n    b - PI :\n    b;\n}\n\nfloat look_horizontal_or_vertical(float a, float ratio) {\n  // ratio controls the ratio between being horizontal to (vertical + horizontal)\n  // if ratio is set to 0.5 then it is 50%, 50%.\n  // when using a higher ratio e.g. 0.75 the result would\n  // likely be more horizontal than vertical.\n\n  float b = positive_angle(a);\n\n  return\n    (b < (      ratio) * HALF_PI) ? 0.0 :\n    (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI :\n    (b < (2.0 + ratio) * HALF_PI) ? 0.0 :\n    (b < (4.0 - ratio) * HALF_PI) ? HALF_PI :\n                                    0.0;\n}\n\nfloat roundTo(float a, float b) {\n  return float(b * floor((a + 0.5 * b) / b));\n}\n\nfloat look_round_n_directions(float a, int n) {\n  float b = positive_angle(a);\n  float div = TWO_PI / float(n);\n  float c = roundTo(b, div);\n  return look_upwards(c);\n}\n\nfloat applyAlignOption(float rawAngle, float delta) {\n  return\n    (option >  2) ? look_round_n_directions(rawAngle + delta, option) :       // option 3-n: round to n directions\n    (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical\n    (option == 1) ? rawAngle + delta :       // use free angle, and flip to align with one direction of the axis\n    (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards\n    (option ==-1) ? 0.0 :                    // useful for backward compatibility, all texts remains horizontal\n                    rawAngle;                // otherwise return back raw input angle\n}\n\nbool isAxisTitle = (axis.x == 0.0) &&\n                   (axis.y == 0.0) &&\n                   (axis.z == 0.0);\n\nvoid main() {\n  //Compute world offset\n  float axisDistance = position.z;\n  vec3 dataPosition = axisDistance * axis + offset;\n\n  float beta = angle; // i.e. user defined attributes for each tick\n\n  float axisAngle;\n  float clipAngle;\n  float flip;\n\n  if (enableAlign) {\n    axisAngle = (isAxisTitle) ? HALF_PI :\n                      computeViewAngle(dataPosition, dataPosition + axis);\n    clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\n\n    axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\n    clipAngle += (sin(clipAngle) < 0.0) ? PI : 0.0;\n\n    flip = (dot(vec2(cos(axisAngle), sin(axisAngle)),\n                vec2(sin(clipAngle),-cos(clipAngle))) > 0.0) ? 1.0 : 0.0;\n\n    beta += applyAlignOption(clipAngle, flip * PI);\n  }\n\n  //Compute plane offset\n  vec2 planeCoord = position.xy * pixelScale;\n\n  mat2 planeXform = scale * mat2(\n     cos(beta), sin(beta),\n    -sin(beta), cos(beta)\n  );\n\n  vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\n\n  //Compute clip position\n  vec3 clipPosition = project(dataPosition);\n\n  //Apply text offset in clip coordinates\n  clipPosition += vec3(viewOffset, 0.0);\n\n  //Done\n  gl_Position = vec4(clipPosition, 1.0);\n}"]),l=n(["precision highp float;\n#define GLSLIFY 1\n\nuniform vec4 color;\nvoid main() {\n  gl_FragColor = color;\n}"]);e.f=function(t){return i(t,s,l,null,[{name:"position",type:"vec3"}])};var u=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position;\nattribute vec3 normal;\n\nuniform mat4 model, view, projection;\nuniform vec3 enable;\nuniform vec3 bounds[2];\n\nvarying vec3 colorChannel;\n\nvoid main() {\n\n  vec3 signAxis = sign(bounds[1] - bounds[0]);\n\n  vec3 realNormal = signAxis * normal;\n\n  if(dot(realNormal, enable) > 0.0) {\n    vec3 minRange = min(bounds[0], bounds[1]);\n    vec3 maxRange = max(bounds[0], bounds[1]);\n    vec3 nPosition = mix(minRange, maxRange, 0.5 * (position + 1.0));\n    gl_Position = projection * view * model * vec4(nPosition, 1.0);\n  } else {\n    gl_Position = vec4(0,0,0,0);\n  }\n\n  colorChannel = abs(realNormal);\n}"]),c=n(["precision highp float;\n#define GLSLIFY 1\n\nuniform vec4 colors[3];\n\nvarying vec3 colorChannel;\n\nvoid main() {\n  gl_FragColor = colorChannel.x * colors[0] +\n                 colorChannel.y * colors[1] +\n                 colorChannel.z * colors[2];\n}"]);e.bg=function(t){return i(t,u,c,null,[{name:"position",type:"vec3"},{name:"normal",type:"vec3"}])}},9557:function(t,e,r){"use strict";t.exports=function(t,e,r,i,o,l){var u=n(t),f=a(t,[{buffer:u,size:3}]),h=s(t);h.attributes.position.location=0;var p=new c(t,h,u,f);return p.update(e,r,i,o,l),p};var n=r(5827),a=r(2944),o=r(875),s=r(1943).f,l=window||i.global||{},u=l.__TEXT_CACHE||{};function c(t,e,r,n){this.gl=t,this.shader=e,this.buffer=r,this.vao=n,this.tickOffset=this.tickCount=this.labelOffset=this.labelCount=null}l.__TEXT_CACHE={};var f=c.prototype,h=[0,0];f.bind=function(t,e,r,n){this.vao.bind(),this.shader.bind();var i=this.shader.uniforms;i.model=t,i.view=e,i.projection=r,i.pixelScale=n,h[0]=this.gl.drawingBufferWidth,h[1]=this.gl.drawingBufferHeight,this.shader.uniforms.resolution=h},f.unbind=function(){this.vao.unbind()},f.update=function(t,e,r,n,i){var a=[];function s(t,e,r,n,i,s){var l=u[r];l||(l=u[r]={});var c=l[e];c||(c=l[e]=function(t,e){try{return o(t,e)}catch(e){return console.warn('error vectorizing text:"'+t+'" error:',e),{cells:[],positions:[]}}}(e,{triangles:!0,font:r,textAlign:"center",textBaseline:"middle",lineSpacing:i,styletags:s}));for(var f=(n||12)/12,h=c.positions,p=c.cells,d=0,v=p.length;d<v;++d)for(var g=p[d],y=2;y>=0;--y){var m=h[g[y]];a.push(f*m[0],-f*m[1],t)}}for(var l=[0,0,0],c=[0,0,0],f=[0,0,0],h=[0,0,0],p={breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},d=0;d<3;++d){f[d]=a.length/3|0,s(.5*(t[0][d]+t[1][d]),e[d],r[d],12,1.25,p),h[d]=(a.length/3|0)-f[d],l[d]=a.length/3|0;for(var v=0;v<n[d].length;++v)n[d][v].text&&s(n[d][v].x,n[d][v].text,n[d][v].font||i,n[d][v].fontSize||12,1.25,p);c[d]=(a.length/3|0)-l[d]}this.buffer.update(a),this.tickOffset=l,this.tickCount=c,this.labelOffset=f,this.labelCount=h},f.drawTicks=function(t,e,r,n,i,a,o,s){this.tickCount[t]&&(this.shader.uniforms.axis=a,this.shader.uniforms.color=i,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t]))},f.drawLabel=function(t,e,r,n,i,a,o,s){this.labelCount[t]&&(this.shader.uniforms.axis=a,this.shader.uniforms.color=i,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.labelCount[t],this.labelOffset[t]))},f.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()}},8468:function(t,e){"use 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h=e.model||u,p=e.view||u,y=e.projection||u,m=e._ortho||!1,x=t.bounds,b=(f=f||a(h,p,y,x,m)).axis;o(c,p,h),o(c,y,c);for(var _=v,w=0;w<3;++w)_[w].lo=1/0,_[w].hi=-1/0,_[w].pixelsPerDataUnit=1/0;var T=n(s(c,c));s(c,c);for(var k=0;k<3;++k){var A=(k+1)%3,M=(k+2)%3,S=g;t:for(w=0;w<2;++w){var E=[];if(b[k]<0!=!!w){S[k]=x[w][k];for(var L=0;L<2;++L){S[A]=x[L^w][A];for(var C=0;C<2;++C)S[M]=x[C^L^w][M],E.push(S.slice())}var P=m?5:4;for(L=P;L===P;++L){if(0===E.length)continue t;E=i.positive(E,T[L])}for(L=0;L<E.length;++L){M=E[L];var O=d(g,c,M,r,l);for(C=0;C<3;++C)_[C].lo=Math.min(_[C].lo,M[C]),_[C].hi=Math.max(_[C].hi,M[C]),C!==k&&(_[C].pixelsPerDataUnit=Math.min(_[C].pixelsPerDataUnit,Math.abs(O[C])))}}}}return _};var n=r(5795),i=r(4670),a=r(2864),o=r(104),s=r(2142),l=r(6342),u=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),c=new Float32Array(16);function f(t,e,r){this.lo=t,this.hi=e,this.pixelsPerDataUnit=r}var h=[0,0,0,1],p=[0,0,0,1];function d(t,e,r,n,i){for(var a=0;a<3;++a){for(var o=h,s=p,u=0;u<3;++u)s[u]=o[u]=r[u];s[3]=o[3]=1,s[a]+=1,l(s,s,e),s[3]<0&&(t[a]=1/0),o[a]-=1,l(o,o,e),o[3]<0&&(t[a]=1/0);var c=(o[0]/o[3]-s[0]/s[3])*n,f=(o[1]/o[3]-s[1]/s[3])*i;t[a]=.25*Math.sqrt(c*c+f*f)}return t}var v=[new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0)],g=[0,0,0]},5827:function(t,e,r){"use strict";var n=r(5306),i=r(7498),a=r(5050),o=["uint8","uint8_clamped","uint16","uint32","int8","int16","int32","float32"];function s(t,e,r,n,i){this.gl=t,this.type=e,this.handle=r,this.length=n,this.usage=i}var l=s.prototype;function u(t,e,r,n,i,a){var o=i.length*i.BYTES_PER_ELEMENT;if(a<0)return t.bufferData(e,i,n),o;if(o+a>r)throw new Error("gl-buffer: If resizing buffer, must not specify offset");return t.bufferSubData(e,a,i),r}function c(t,e){for(var r=n.malloc(t.length,e),i=t.length,a=0;a<i;++a)r[a]=t[a];return r}l.bind=function(){this.gl.bindBuffer(this.type,this.handle)},l.unbind=function(){this.gl.bindBuffer(this.type,null)},l.dispose=function(){this.gl.deleteBuffer(this.handle)},l.update=function(t,e){if("number"!=typeof e&&(e=-1),this.bind(),"object"==typeof t&&void 0!==t.shape){var r=t.dtype;if(o.indexOf(r)<0&&(r="float32"),this.type===this.gl.ELEMENT_ARRAY_BUFFER&&(r=gl.getExtension("OES_element_index_uint")&&"uint16"!==r?"uint32":"uint16"),r===t.dtype&&function(t,e){for(var r=1,n=e.length-1;n>=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}(t.shape,t.stride))0===t.offset&&t.data.length===t.shape[0]?this.length=u(this.gl,this.type,this.length,this.usage,t.data,e):this.length=u(this.gl,this.type,this.length,this.usage,t.data.subarray(t.offset,t.shape[0]),e);else{var s=n.malloc(t.size,r),l=a(s,t.shape);i.assign(l,t),this.length=u(this.gl,this.type,this.length,this.usage,e<0?s:s.subarray(0,t.size),e),n.free(s)}}else if(Array.isArray(t)){var f;f=this.type===this.gl.ELEMENT_ARRAY_BUFFER?c(t,"uint16"):c(t,"float32"),this.length=u(this.gl,this.type,this.length,this.usage,e<0?f:f.subarray(0,t.length),e),n.free(f)}else if("object"==typeof t&&"number"==typeof t.length)this.length=u(this.gl,this.type,this.length,this.usage,t,e);else{if("number"!=typeof t&&void 0!==t)throw new Error("gl-buffer: Invalid data type");if(e>=0)throw new Error("gl-buffer: Cannot specify offset when resizing buffer");(t|=0)<=0&&(t=1),this.gl.bufferData(this.type,0|t,this.usage),this.length=t}},t.exports=function(t,e,r,n){if(r=r||t.ARRAY_BUFFER,n=n||t.DYNAMIC_DRAW,r!==t.ARRAY_BUFFER&&r!==t.ELEMENT_ARRAY_BUFFER)throw new Error("gl-buffer: Invalid type for webgl buffer, must be either gl.ARRAY_BUFFER or gl.ELEMENT_ARRAY_BUFFER");if(n!==t.DYNAMIC_DRAW&&n!==t.STATIC_DRAW&&n!==t.STREAM_DRAW)throw new Error("gl-buffer: Invalid usage for buffer, must be either gl.DYNAMIC_DRAW, gl.STATIC_DRAW or gl.STREAM_DRAW");var i=t.createBuffer(),a=new s(t,r,i,0,n);return a.update(e),a}},1140:function(t,e,r){"use strict";var n=r(2858);t.exports=function(t,e){var r=t.positions,i=t.vectors,a={positions:[],vertexIntensity:[],vertexIntensityBounds:t.vertexIntensityBounds,vectors:[],cells:[],coneOffset:t.coneOffset,colormap:t.colormap};if(0===t.positions.length)return e&&(e[0]=[0,0,0],e[1]=[0,0,0]),a;for(var o=0,s=1/0,l=-1/0,u=1/0,c=-1/0,f=1/0,h=-1/0,p=null,d=null,v=[],g=1/0,y=!1,m=0;m<r.length;m++){var x=r[m];s=Math.min(x[0],s),l=Math.max(x[0],l),u=Math.min(x[1],u),c=Math.max(x[1],c),f=Math.min(x[2],f),h=Math.max(x[2],h);var b=i[m];if(n.length(b)>o&&(o=n.length(b)),m){var _=2*n.distance(p,x)/(n.length(d)+n.length(b));_?(g=Math.min(g,_),y=!1):y=!0}y||(p=x,d=b),v.push(b)}var w=[s,u,f],T=[l,c,h];e&&(e[0]=w,e[1]=T),0===o&&(o=1);var k=1/o;isFinite(g)||(g=1),a.vectorScale=g;var A=t.coneSize||.5;t.absoluteConeSize&&(A=t.absoluteConeSize*k),a.coneScale=A,m=0;for(var M=0;m<r.length;m++)for(var S=(x=r[m])[0],E=x[1],L=x[2],C=v[m],P=n.length(C)*k,O=0;O<8;O++){a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vertexIntensity.push(P,P,P),a.vertexIntensity.push(P,P,P);var I=a.positions.length;a.cells.push([I-6,I-5,I-4],[I-3,I-2,I-1])}return a};var i=r(7234);t.exports.createMesh=r(5028),t.exports.createConeMesh=function(e,r){return t.exports.createMesh(e,r,{shaders:i,traceType:"cone"})}},5028:function(t,e,r){"use strict";var n=r(5158),i=r(5827),a=r(2944),o=r(8931),s=r(104),l=r(7437),u=r(5050),c=r(9156),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e,r,n,i,a,o,s,l,u,c){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.pickShader=n,this.trianglePositions=i,this.triangleVectors=a,this.triangleColors=s,this.triangleUVs=l,this.triangleIds=o,this.triangleVAO=u,this.triangleCount=0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.traceType=c,this.tubeScale=1,this.coneScale=2,this.vectorScale=1,this.coneOffset=.25,this._model=f,this._view=f,this._projection=f,this._resolution=[1,1]}var p=h.prototype;p.isOpaque=function(){return this.opacity>=1},p.isTransparent=function(){return this.opacity<1},p.pickSlots=1,p.setPickBase=function(t){this.pickId=t},p.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,"lightPosition"in t&&(this.lightPosition=t.lightPosition),"opacity"in t&&(this.opacity=t.opacity),"ambient"in t&&(this.ambientLight=t.ambient),"diffuse"in t&&(this.diffuseLight=t.diffuse),"specular"in t&&(this.specularLight=t.specular),"roughness"in t&&(this.roughness=t.roughness),"fresnel"in t&&(this.fresnel=t.fresnel),void 0!==t.tubeScale&&(this.tubeScale=t.tubeScale),void 0!==t.vectorScale&&(this.vectorScale=t.vectorScale),void 0!==t.coneScale&&(this.coneScale=t.coneScale),void 0!==t.coneOffset&&(this.coneOffset=t.coneOffset),t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=c({colormap:t,nshades:256,format:"rgba"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var i=e[n],a=0;a<3;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return u(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,i=t.vectors;if(n&&r&&i){var a=[],o=[],s=[],l=[],f=[];this.cells=r,this.positions=n,this.vectors=i;var h=t.meshColor||[1,1,1,1],p=t.vertexIntensity,d=1/0,v=-1/0;if(p)if(t.vertexIntensityBounds)d=+t.vertexIntensityBounds[0],v=+t.vertexIntensityBounds[1];else for(var g=0;g<p.length;++g){var y=p[g];d=Math.min(d,y),v=Math.max(v,y)}else for(g=0;g<n.length;++g)y=n[g][2],d=Math.min(d,y),v=Math.max(v,y);for(this.intensity=p||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n),this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],g=0;g<n.length;++g)for(var m=n[g],x=0;x<3;++x)!isNaN(m[x])&&isFinite(m[x])&&(this.bounds[0][x]=Math.min(this.bounds[0][x],m[x]),this.bounds[1][x]=Math.max(this.bounds[1][x],m[x]));var b=0;t:for(g=0;g<r.length;++g){var _=r[g];if(3===_.length){for(x=0;x<3;++x){m=n[T=_[x]];for(var w=0;w<3;++w)if(isNaN(m[w])||!isFinite(m[w]))continue t}for(x=0;x<3;++x){var T;m=n[T=_[2-x]],a.push(m[0],m[1],m[2],m[3]);var k=i[T];o.push(k[0],k[1],k[2],k[3]||0);var A,M=h;3===M.length?s.push(M[0],M[1],M[2],1):s.push(M[0],M[1],M[2],M[3]),A=p?[(p[T]-d)/(v-d),0]:[(m[2]-d)/(v-d),0],l.push(A[0],A[1]),f.push(g)}b+=1}}this.triangleCount=b,this.trianglePositions.update(a),this.triangleVectors.update(o),this.triangleColors.update(s),this.triangleUVs.update(l),this.triangleIds.update(new Uint32Array(f))}},p.drawTransparent=p.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var u={model:r,view:n,projection:i,inverseModel:f.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,texture:0};u.inverseModel=l(u.inverseModel,u.model),e.disable(e.CULL_FACE),this.texture.bind(0);var c=new Array(16);for(s(c,u.view,u.model),s(c,u.projection,c),l(c,c),o=0;o<3;++o)u.eyePosition[o]=c[12+o]/c[15];var h=c[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*c[4*o+3];for(o=0;o<3;++o){for(var p=c[12+o],d=0;d<3;++d)p+=c[4*d+o]*this.lightPosition[d];u.lightPosition[o]=p/h}if(this.triangleCount>0){var v=this.triShader;v.bind(),v.uniforms=u,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},p.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind())},p.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3),i={position:n,dataCoordinate:n,index:Math.floor(r[1]/48)};return"cone"===this.traceType?i.index=Math.floor(r[1]/48):"streamtube"===this.traceType&&(i.intensity=this.intensity[r[1]],i.velocity=this.vectors[r[1]].slice(0,3),i.divergence=this.vectors[r[1]][3],i.index=e),i},p.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()},t.exports=function(t,e,r){var s=r.shaders;1===arguments.length&&(t=(e=t).gl);var l=function(t,e){var r=n(t,e.meshShader.vertex,e.meshShader.fragment,null,e.meshShader.attributes);return r.attributes.position.location=0,r.attributes.color.location=2,r.attributes.uv.location=3,r.attributes.vector.location=4,r}(t,s),c=function(t,e){var r=n(t,e.pickShader.vertex,e.pickShader.fragment,null,e.pickShader.attributes);return r.attributes.position.location=0,r.attributes.id.location=1,r.attributes.vector.location=4,r}(t,s),f=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));f.generateMipmap(),f.minFilter=t.LINEAR_MIPMAP_LINEAR,f.magFilter=t.LINEAR;var p=i(t),d=i(t),v=i(t),g=i(t),y=i(t),m=new h(t,f,l,c,p,d,y,v,g,a(t,[{buffer:p,type:t.FLOAT,size:4},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:v,type:t.FLOAT,size:4},{buffer:g,type:t.FLOAT,size:2},{buffer:d,type:t.FLOAT,size:4}]),r.traceType||"cone");return m.update(e),m}},7234:function(t,e,r){var n=r(6832),i=n(["precision highp float;\n\nprecision highp float;\n#define GLSLIFY 1\n\nvec3 getOrthogonalVector(vec3 v) {\n  // Return up-vector for only-z vector.\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\n  // Assign z = 0, x = -b, y = a:\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\n    return normalize(vec3(-v.y, v.x, 0.0));\n  } else {\n    return normalize(vec3(0.0, v.z, -v.y));\n  }\n}\n\n// Calculate the cone vertex and normal at the given index.\n//\n// The returned vertex is for a cone with its top at origin and height of 1.0,\n// pointing in the direction of the vector attribute.\n//\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\n// These vertices are used to make up the triangles of the cone by the following:\n//   segment + 0 top vertex\n//   segment + 1 perimeter vertex a+1\n//   segment + 2 perimeter vertex a\n//   segment + 3 center base vertex\n//   segment + 4 perimeter vertex a\n//   segment + 5 perimeter vertex a+1\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\n// To go from index to segment, floor(index / 6)\n// To go from segment to angle, 2*pi * (segment/segmentCount)\n// To go from index to segment index, index - (segment*6)\n//\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\n\n  const float segmentCount = 8.0;\n\n  float index = rawIndex - floor(rawIndex /\n    (segmentCount * 6.0)) *\n    (segmentCount * 6.0);\n\n  float segment = floor(0.001 + index/6.0);\n  float segmentIndex = index - (segment*6.0);\n\n  normal = -normalize(d);\n\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\n    return mix(vec3(0.0), -d, coneOffset);\n  }\n\n  float nextAngle = (\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\n  ) ? 1.0 : 0.0;\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\n\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\n  vec3 v2 = v1 - d;\n\n  vec3 u = getOrthogonalVector(d);\n  vec3 v = normalize(cross(u, d));\n\n  vec3 x = u * cos(angle) * length(d)*0.25;\n  vec3 y = v * sin(angle) * length(d)*0.25;\n  vec3 v3 = v2 + x + y;\n  if (segmentIndex < 3.0) {\n    vec3 tx = u * sin(angle);\n    vec3 ty = v * -cos(angle);\n    vec3 tangent = tx + ty;\n    normal = normalize(cross(v3 - v1, tangent));\n  }\n\n  if (segmentIndex == 0.0) {\n    return mix(d, vec3(0.0), coneOffset);\n  }\n  return v3;\n}\n\nattribute vec3 vector;\nattribute vec4 color, position;\nattribute vec2 uv;\n\nuniform float vectorScale, coneScale, coneOffset;\nuniform mat4 model, view, projection, inverseModel;\nuniform vec3 eyePosition, lightPosition;\n\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvoid main() {\n  // Scale the vector magnitude to stay constant with\n  // model & view changes.\n  vec3 normal;\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\n\n  //Lighting geometry parameters\n  vec4 cameraCoordinate = view * conePosition;\n  cameraCoordinate.xyz /= cameraCoordinate.w;\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\n\n  // vec4 m_position  = model * vec4(conePosition, 1.0);\n  vec4 t_position  = view * conePosition;\n  gl_Position      = projection * t_position;\n\n  f_color          = color;\n  f_data           = conePosition.xyz;\n  f_position       = position.xyz;\n  f_uv             = uv;\n}\n"]),a=n(["#extension GL_OES_standard_derivatives : enable\n\nprecision highp float;\n#define GLSLIFY 1\n\nfloat beckmannDistribution(float x, float roughness) {\n  float NdotH = max(x, 0.0001);\n  float cos2Alpha = NdotH * NdotH;\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\n  float roughness2 = roughness * roughness;\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\n  return exp(tan2Alpha / roughness2) / denom;\n}\n\nfloat cookTorranceSpecular(\n  vec3 lightDirection,\n  vec3 viewDirection,\n  vec3 surfaceNormal,\n  float roughness,\n  float fresnel) {\n\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\n\n  //Half angle vector\n  vec3 H = normalize(lightDirection + viewDirection);\n\n  //Geometric term\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\n  float VdotH = max(dot(viewDirection, H), 0.000001);\n  float LdotH = max(dot(lightDirection, H), 0.000001);\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\n  float G = min(1.0, min(G1, G2));\n  \n  //Distribution term\n  float D = beckmannDistribution(NdotH, roughness);\n\n  //Fresnel term\n  float F = pow(1.0 - VdotN, fresnel);\n\n  //Multiply terms and done\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\n}\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\nuniform sampler2D texture;\n\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvoid main() {\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\n  vec3 N = normalize(f_normal);\n  vec3 L = normalize(f_lightDirection);\n  vec3 V = normalize(f_eyeDirection);\n\n  if(gl_FrontFacing) {\n    N = -N;\n  }\n\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\n\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\n\n  gl_FragColor = litColor * opacity;\n}\n"]),o=n(["precision highp float;\n\nprecision highp float;\n#define GLSLIFY 1\n\nvec3 getOrthogonalVector(vec3 v) {\n  // Return up-vector for only-z vector.\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\n  // Assign z = 0, x = -b, y = a:\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\n    return normalize(vec3(-v.y, v.x, 0.0));\n  } else {\n    return normalize(vec3(0.0, v.z, -v.y));\n  }\n}\n\n// Calculate the cone vertex and normal at the given index.\n//\n// The returned vertex is for a cone with its top at origin and height of 1.0,\n// pointing in the direction of the vector attribute.\n//\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\n// These vertices are used to make up the triangles of the cone by the following:\n//   segment + 0 top vertex\n//   segment + 1 perimeter vertex a+1\n//   segment + 2 perimeter vertex a\n//   segment + 3 center base vertex\n//   segment + 4 perimeter vertex a\n//   segment + 5 perimeter vertex a+1\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\n// To go from index to segment, floor(index / 6)\n// To go from segment to angle, 2*pi * (segment/segmentCount)\n// To go from index to segment index, index - (segment*6)\n//\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\n\n  const float segmentCount = 8.0;\n\n  float index = rawIndex - floor(rawIndex /\n    (segmentCount * 6.0)) *\n    (segmentCount * 6.0);\n\n  float segment = floor(0.001 + index/6.0);\n  float segmentIndex = index - (segment*6.0);\n\n  normal = -normalize(d);\n\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\n    return mix(vec3(0.0), -d, coneOffset);\n  }\n\n  float nextAngle = (\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\n  ) ? 1.0 : 0.0;\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\n\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\n  vec3 v2 = v1 - d;\n\n  vec3 u = getOrthogonalVector(d);\n  vec3 v = normalize(cross(u, d));\n\n  vec3 x = u * cos(angle) * length(d)*0.25;\n  vec3 y = v * sin(angle) * length(d)*0.25;\n  vec3 v3 = v2 + x + y;\n  if (segmentIndex < 3.0) {\n    vec3 tx = u * sin(angle);\n    vec3 ty = v * -cos(angle);\n    vec3 tangent = tx + ty;\n    normal = normalize(cross(v3 - v1, tangent));\n  }\n\n  if (segmentIndex == 0.0) {\n    return mix(d, vec3(0.0), coneOffset);\n  }\n  return v3;\n}\n\nattribute vec4 vector;\nattribute vec4 position;\nattribute vec4 id;\n\nuniform mat4 model, view, projection;\nuniform float vectorScale, coneScale, coneOffset;\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() {\n  vec3 normal;\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector.xyz), position.w, coneOffset, normal);\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\n  gl_Position = projection * view * conePosition;\n  f_id        = id;\n  f_position  = position.xyz;\n}\n"]),s=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3  clipBounds[2];\nuniform float pickId;\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() {\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\n\n  gl_FragColor = vec4(pickId, f_id.xyz);\n}"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:"position",type:"vec4"},{name:"color",type:"vec4"},{name:"uv",type:"vec2"},{name:"vector",type:"vec3"}]},e.pickShader={vertex:o,fragment:s,attributes:[{name:"position",type:"vec4"},{name:"id",type:"vec4"},{name:"vector",type:"vec3"}]}},1950:function(t){t.exports={0:"NONE",1:"ONE",2:"LINE_LOOP",3:"LINE_STRIP",4:"TRIANGLES",5:"TRIANGLE_STRIP",6:"TRIANGLE_FAN",256:"DEPTH_BUFFER_BIT",512:"NEVER",513:"LESS",514:"EQUAL",515:"LEQUAL",516:"GREATER",517:"NOTEQUAL",518:"GEQUAL",519:"ALWAYS",768:"SRC_COLOR",769:"ONE_MINUS_SRC_COLOR",770:"SRC_ALPHA",771:"ONE_MINUS_SRC_ALPHA",772:"DST_ALPHA",773:"ONE_MINUS_DST_ALPHA",774:"DST_COLOR",775:"ONE_MINUS_DST_COLOR",776:"SRC_ALPHA_SATURATE",1024:"STENCIL_BUFFER_BIT",1028:"FRONT",1029:"BACK",1032:"FRONT_AND_BACK",1280:"INVALID_ENUM",1281:"INVALID_VALUE",1282:"INVALID_OPERATION",1285:"OUT_OF_MEMORY",1286:"INVALID_FRAMEBUFFER_OPERATION",2304:"CW",2305:"CCW",2849:"LINE_WIDTH",2884:"CULL_FACE",2885:"CULL_FACE_MODE",2886:"FRONT_FACE",2928:"DEPTH_RANGE",2929:"DEPTH_TEST",2930:"DEPTH_WRITEMASK",2931:"DEPTH_CLEAR_VALUE",2932:"DEPTH_FUNC",2960:"STENCIL_TEST",2961:"STENCIL_CLEAR_VALUE",2962:"STENCIL_FUNC",2963:"STENCIL_VALUE_MASK",2964:"STENCIL_FAIL",2965:"STENCIL_PASS_DEPTH_FAIL",2966:"STENCIL_PASS_DEPTH_PASS",2967:"STENCIL_REF",2968:"STENCIL_WRITEMASK",2978:"VIEWPORT",3024:"DITHER",3042:"BLEND",3088:"SCISSOR_BOX",3089:"SCISSOR_TEST",3106:"COLOR_CLEAR_VALUE",3107:"COLOR_WRITEMASK",3317:"UNPACK_ALIGNMENT",3333:"PACK_ALIGNMENT",3379:"MAX_TEXTURE_SIZE",3386:"MAX_VIEWPORT_DIMS",3408:"SUBPIXEL_BITS",3410:"RED_BITS",3411:"GREEN_BITS",3412:"BLUE_BITS",3413:"ALPHA_BITS",3414:"DEPTH_BITS",3415:"STENCIL_BITS",3553:"TEXTURE_2D",4352:"DONT_CARE",4353:"FASTEST",4354:"NICEST",5120:"BYTE",5121:"UNSIGNED_BYTE",5122:"SHORT",5123:"UNSIGNED_SHORT",5124:"INT",5125:"UNSIGNED_INT",5126:"FLOAT",5386:"INVERT",5890:"TEXTURE",6401:"STENCIL_INDEX",6402:"DEPTH_COMPONENT",6406:"ALPHA",6407:"RGB",6408:"RGBA",6409:"LUMINANCE",6410:"LUMINANCE_ALPHA",7680:"KEEP",7681:"REPLACE",7682:"INCR",7683:"DECR",7936:"VENDOR",7937:"RENDERER",7938:"VERSION",9728:"NEAREST",9729:"LINEAR",9984:"NEAREST_MIPMAP_NEAREST",9985:"LINEAR_MIPMAP_NEAREST",9986:"NEAREST_MIPMAP_LINEAR",9987:"LINEAR_MIPMAP_LINEAR",10240:"TEXTURE_MAG_FILTER",10241:"TEXTURE_MIN_FILTER",10242:"TEXTURE_WRAP_S",10243:"TEXTURE_WRAP_T",10497:"REPEAT",10752:"POLYGON_OFFSET_UNITS",16384:"COLOR_BUFFER_BIT",32769:"CONSTANT_COLOR",32770:"ONE_MINUS_CONSTANT_COLOR",32771:"CONSTANT_ALPHA",32772:"ONE_MINUS_CONSTANT_ALPHA",32773:"BLEND_COLOR",32774:"FUNC_ADD",32777:"BLEND_EQUATION_RGB",32778:"FUNC_SUBTRACT",32779:"FUNC_REVERSE_SUBTRACT",32819:"UNSIGNED_SHORT_4_4_4_4",32820:"UNSIGNED_SHORT_5_5_5_1",32823:"POLYGON_OFFSET_FILL",32824:"POLYGON_OFFSET_FACTOR",32854:"RGBA4",32855:"RGB5_A1",32873:"TEXTURE_BINDING_2D",32926:"SAMPLE_ALPHA_TO_COVERAGE",32928:"SAMPLE_COVERAGE",32936:"SAMPLE_BUFFERS",32937:"SAMPLES",32938:"SAMPLE_COVERAGE_VALUE",32939:"SAMPLE_COVERAGE_INVERT",32968:"BLEND_DST_RGB",32969:"BLEND_SRC_RGB",32970:"BLEND_DST_ALPHA",32971:"BLEND_SRC_ALPHA",33071:"CLAMP_TO_EDGE",33170:"GENERATE_MIPMAP_HINT",33189:"DEPTH_COMPONENT16",33306:"DEPTH_STENCIL_ATTACHMENT",33635:"UNSIGNED_SHORT_5_6_5",33648:"MIRRORED_REPEAT",33901:"ALIASED_POINT_SIZE_RANGE",33902:"ALIASED_LINE_WIDTH_RANGE",33984:"TEXTURE0",33985:"TEXTURE1",33986:"TEXTURE2",33987:"TEXTURE3",33988:"TEXTURE4",33989:"TEXTURE5",33990:"TEXTURE6",33991:"TEXTURE7",33992:"TEXTURE8",33993:"TEXTURE9",33994:"TEXTURE10",33995:"TEXTURE11",33996:"TEXTURE12",33997:"TEXTURE13",33998:"TEXTURE14",33999:"TEXTURE15",34e3:"TEXTURE16",34001:"TEXTURE17",34002:"TEXTURE18",34003:"TEXTURE19",34004:"TEXTURE20",34005:"TEXTURE21",34006:"TEXTURE22",34007:"TEXTURE23",34008:"TEXTURE24",34009:"TEXTURE25",34010:"TEXTURE26",34011:"TEXTURE27",34012:"TEXTURE28",34013:"TEXTURE29",34014:"TEXTURE30",34015:"TEXTURE31",34016:"ACTIVE_TEXTURE",34024:"MAX_RENDERBUFFER_SIZE",34041:"DEPTH_STENCIL",34055:"INCR_WRAP",34056:"DECR_WRAP",34067:"TEXTURE_CUBE_MAP",34068:"TEXTURE_BINDING_CUBE_MAP",34069:"TEXTURE_CUBE_MAP_POSITIVE_X",34070:"TEXTURE_CUBE_MAP_NEGATIVE_X",34071:"TEXTURE_CUBE_MAP_POSITIVE_Y",34072:"TEXTURE_CUBE_MAP_NEGATIVE_Y",34073:"TEXTURE_CUBE_MAP_POSITIVE_Z",34074:"TEXTURE_CUBE_MAP_NEGATIVE_Z",34076:"MAX_CUBE_MAP_TEXTURE_SIZE",34338:"VERTEX_ATTRIB_ARRAY_ENABLED",34339:"VERTEX_ATTRIB_ARRAY_SIZE",34340:"VERTEX_ATTRIB_ARRAY_STRIDE",34341:"VERTEX_ATTRIB_ARRAY_TYPE",34342:"CURRENT_VERTEX_ATTRIB",34373:"VERTEX_ATTRIB_ARRAY_POINTER",34466:"NUM_COMPRESSED_TEXTURE_FORMATS",34467:"COMPRESSED_TEXTURE_FORMATS",34660:"BUFFER_SIZE",34661:"BUFFER_USAGE",34816:"STENCIL_BACK_FUNC",34817:"STENCIL_BACK_FAIL",34818:"STENCIL_BACK_PASS_DEPTH_FAIL",34819:"STENCIL_BACK_PASS_DEPTH_PASS",34877:"BLEND_EQUATION_ALPHA",34921:"MAX_VERTEX_ATTRIBS",34922:"VERTEX_ATTRIB_ARRAY_NORMALIZED",34930:"MAX_TEXTURE_IMAGE_UNITS",34962:"ARRAY_BUFFER",34963:"ELEMENT_ARRAY_BUFFER",34964:"ARRAY_BUFFER_BINDING",34965:"ELEMENT_ARRAY_BUFFER_BINDING",34975:"VERTEX_ATTRIB_ARRAY_BUFFER_BINDING",35040:"STREAM_DRAW",35044:"STATIC_DRAW",35048:"DYNAMIC_DRAW",35632:"FRAGMENT_SHADER",35633:"VERTEX_SHADER",35660:"MAX_VERTEX_TEXTURE_IMAGE_UNITS",35661:"MAX_COMBINED_TEXTURE_IMAGE_UNITS",35663:"SHADER_TYPE",35664:"FLOAT_VEC2",35665:"FLOAT_VEC3",35666:"FLOAT_VEC4",35667:"INT_VEC2",35668:"INT_VEC3",35669:"INT_VEC4",35670:"BOOL",35671:"BOOL_VEC2",35672:"BOOL_VEC3",35673:"BOOL_VEC4",35674:"FLOAT_MAT2",35675:"FLOAT_MAT3",35676:"FLOAT_MAT4",35678:"SAMPLER_2D",35680:"SAMPLER_CUBE",35712:"DELETE_STATUS",35713:"COMPILE_STATUS",35714:"LINK_STATUS",35715:"VALIDATE_STATUS",35716:"INFO_LOG_LENGTH",35717:"ATTACHED_SHADERS",35718:"ACTIVE_UNIFORMS",35719:"ACTIVE_UNIFORM_MAX_LENGTH",35720:"SHADER_SOURCE_LENGTH",35721:"ACTIVE_ATTRIBUTES",35722:"ACTIVE_ATTRIBUTE_MAX_LENGTH",35724:"SHADING_LANGUAGE_VERSION",35725:"CURRENT_PROGRAM",36003:"STENCIL_BACK_REF",36004:"STENCIL_BACK_VALUE_MASK",36005:"STENCIL_BACK_WRITEMASK",36006:"FRAMEBUFFER_BINDING",36007:"RENDERBUFFER_BINDING",36048:"FRAMEBUFFER_ATTACHMENT_OBJECT_TYPE",36049:"FRAMEBUFFER_ATTACHMENT_OBJECT_NAME",36050:"FRAMEBUFFER_ATTACHMENT_TEXTURE_LEVEL",36051:"FRAMEBUFFER_ATTACHMENT_TEXTURE_CUBE_MAP_FACE",36053:"FRAMEBUFFER_COMPLETE",36054:"FRAMEBUFFER_INCOMPLETE_ATTACHMENT",36055:"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT",36057:"FRAMEBUFFER_INCOMPLETE_DIMENSIONS",36061:"FRAMEBUFFER_UNSUPPORTED",36064:"COLOR_ATTACHMENT0",36096:"DEPTH_ATTACHMENT",36128:"STENCIL_ATTACHMENT",36160:"FRAMEBUFFER",36161:"RENDERBUFFER",36162:"RENDERBUFFER_WIDTH",36163:"RENDERBUFFER_HEIGHT",36164:"RENDERBUFFER_INTERNAL_FORMAT",36168:"STENCIL_INDEX8",36176:"RENDERBUFFER_RED_SIZE",36177:"RENDERBUFFER_GREEN_SIZE",36178:"RENDERBUFFER_BLUE_SIZE",36179:"RENDERBUFFER_ALPHA_SIZE",36180:"RENDERBUFFER_DEPTH_SIZE",36181:"RENDERBUFFER_STENCIL_SIZE",36194:"RGB565",36336:"LOW_FLOAT",36337:"MEDIUM_FLOAT",36338:"HIGH_FLOAT",36339:"LOW_INT",36340:"MEDIUM_INT",36341:"HIGH_INT",36346:"SHADER_COMPILER",36347:"MAX_VERTEX_UNIFORM_VECTORS",36348:"MAX_VARYING_VECTORS",36349:"MAX_FRAGMENT_UNIFORM_VECTORS",37440:"UNPACK_FLIP_Y_WEBGL",37441:"UNPACK_PREMULTIPLY_ALPHA_WEBGL",37442:"CONTEXT_LOST_WEBGL",37443:"UNPACK_COLORSPACE_CONVERSION_WEBGL",37444:"BROWSER_DEFAULT_WEBGL"}},6603:function(t,e,r){var n=r(1950);t.exports=function(t){return n[t]}},3110:function(t,e,r){"use strict";t.exports=function(t){var e=t.gl,r=n(e),o=i(e,[{buffer:r,type:e.FLOAT,size:3,offset:0,stride:40},{buffer:r,type:e.FLOAT,size:4,offset:12,stride:40},{buffer:r,type:e.FLOAT,size:3,offset:28,stride:40}]),l=a(e);l.attributes.position.location=0,l.attributes.color.location=1,l.attributes.offset.location=2;var u=new s(e,r,o,l);return u.update(t),u};var n=r(5827),i=r(2944),a=r(7667),o=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function s(t,e,r,n){this.gl=t,this.shader=n,this.buffer=e,this.vao=r,this.pixelRatio=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lineWidth=[1,1,1],this.capSize=[10,10,10],this.lineCount=[0,0,0],this.lineOffset=[0,0,0],this.opacity=1,this.hasAlpha=!1}var l=s.prototype;function u(t,e){for(var r=0;r<3;++r)t[0][r]=Math.min(t[0][r],e[r]),t[1][r]=Math.max(t[1][r],e[r])}l.isOpaque=function(){return!this.hasAlpha},l.isTransparent=function(){return this.hasAlpha},l.drawTransparent=l.draw=function(t){var e=this.gl,r=this.shader.uniforms;this.shader.bind();var n=r.view=t.view||o,i=r.projection=t.projection||o;r.model=t.model||o,r.clipBounds=this.clipBounds,r.opacity=this.opacity;var a=n[12],s=n[13],l=n[14],u=n[15],c=(t._ortho?2:1)*this.pixelRatio*(i[3]*a+i[7]*s+i[11]*l+i[15]*u)/e.drawingBufferHeight;this.vao.bind();for(var f=0;f<3;++f)e.lineWidth(this.lineWidth[f]*this.pixelRatio),r.capSize=this.capSize[f]*c,this.lineCount[f]&&e.drawArrays(e.LINES,this.lineOffset[f],this.lineCount[f]);this.vao.unbind()};var c=function(){for(var t=new Array(3),e=0;e<3;++e){for(var r=[],n=1;n<=2;++n)for(var i=-1;i<=1;i+=2){var a=[0,0,0];a[(n+e)%3]=i,r.push(a)}t[e]=r}return t}();function f(t,e,r,n){for(var i=c[n],a=0;a<i.length;++a){var o=i[a];t.push(e[0],e[1],e[2],r[0],r[1],r[2],r[3],o[0],o[1],o[2])}return i.length}l.update=function(t){"lineWidth"in(t=t||{})&&(this.lineWidth=t.lineWidth,Array.isArray(this.lineWidth)||(this.lineWidth=[this.lineWidth,this.lineWidth,this.lineWidth])),"capSize"in t&&(this.capSize=t.capSize,Array.isArray(this.capSize)||(this.capSize=[this.capSize,this.capSize,this.capSize])),this.hasAlpha=!1,"opacity"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var e=t.color||[[0,0,0],[0,0,0],[0,0,0]],r=t.position,n=t.error;if(Array.isArray(e[0])||(e=[e,e,e]),r&&n){var i=[],a=r.length,o=0;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.lineCount=[0,0,0];for(var s=0;s<3;++s){this.lineOffset[s]=o;t:for(var l=0;l<a;++l){for(var c=r[l],h=0;h<3;++h)if(isNaN(c[h])||!isFinite(c[h]))continue t;var p,d=n[l],v=e[s];Array.isArray(v[0])&&(v=e[l]),3===v.length?v=[v[0],v[1],v[2],1]:4===v.length&&(v=[v[0],v[1],v[2],v[3]],!this.hasAlpha&&v[3]<1&&(this.hasAlpha=!0)),isNaN(d[0][s])||isNaN(d[1][s])||(d[0][s]<0&&((p=c.slice())[s]+=d[0][s],i.push(c[0],c[1],c[2],v[0],v[1],v[2],v[3],0,0,0,p[0],p[1],p[2],v[0],v[1],v[2],v[3],0,0,0),u(this.bounds,p),o+=2+f(i,p,v,s)),d[1][s]>0&&((p=c.slice())[s]+=d[1][s],i.push(c[0],c[1],c[2],v[0],v[1],v[2],v[3],0,0,0,p[0],p[1],p[2],v[0],v[1],v[2],v[3],0,0,0),u(this.bounds,p),o+=2+f(i,p,v,s)))}this.lineCount[s]=o-this.lineOffset[s]}this.buffer.update(i)}},l.dispose=function(){this.shader.dispose(),this.buffer.dispose(),this.vao.dispose()}},7667:function(t,e,r){"use strict";var n=r(6832),i=r(5158),a=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position, offset;\nattribute vec4 color;\nuniform mat4 model, view, projection;\nuniform float capSize;\nvarying vec4 fragColor;\nvarying vec3 fragPosition;\n\nvoid main() {\n  vec4 worldPosition  = model * vec4(position, 1.0);\n  worldPosition       = (worldPosition / worldPosition.w) + vec4(capSize * offset, 0.0);\n  gl_Position         = projection * view * worldPosition;\n  fragColor           = color;\n  fragPosition        = position;\n}"]),o=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform float opacity;\nvarying vec3 fragPosition;\nvarying vec4 fragColor;\n\nvoid main() {\n  if (\n    outOfRange(clipBounds[0], clipBounds[1], fragPosition) ||\n    fragColor.a * opacity == 0.\n  ) discard;\n\n  gl_FragColor = opacity * fragColor;\n}"]);t.exports=function(t){return i(t,a,o,null,[{name:"position",type:"vec3"},{name:"color",type:"vec4"},{name:"offset",type:"vec3"}])}},4234:function(t,e,r){"use strict";var n=r(8931);t.exports=function(t,e,r,n){i||(i=t.FRAMEBUFFER_UNSUPPORTED,a=t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT,o=t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS,s=t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT);var u=t.getExtension("WEBGL_draw_buffers");if(!l&&u&&function(t,e){var r=t.getParameter(e.MAX_COLOR_ATTACHMENTS_WEBGL);l=new Array(r+1);for(var n=0;n<=r;++n){for(var i=new Array(r),a=0;a<n;++a)i[a]=t.COLOR_ATTACHMENT0+a;for(a=n;a<r;++a)i[a]=t.NONE;l[n]=i}}(t,u),Array.isArray(e)&&(n=r,r=0|e[1],e=0|e[0]),"number"!=typeof e)throw new Error("gl-fbo: Missing shape parameter");var c=t.getParameter(t.MAX_RENDERBUFFER_SIZE);if(e<0||e>c||r<0||r>c)throw new Error("gl-fbo: Parameters are too large for FBO");var f=1;if("color"in(n=n||{})){if((f=Math.max(0|n.color,0))<0)throw new Error("gl-fbo: Must specify a nonnegative number of colors");if(f>1){if(!u)throw new Error("gl-fbo: Multiple draw buffer extension not supported");if(f>t.getParameter(u.MAX_COLOR_ATTACHMENTS_WEBGL))throw new Error("gl-fbo: Context does not support "+f+" draw buffers")}}var h=t.UNSIGNED_BYTE,p=t.getExtension("OES_texture_float");if(n.float&&f>0){if(!p)throw new Error("gl-fbo: Context does not support floating point textures");h=t.FLOAT}else n.preferFloat&&f>0&&p&&(h=t.FLOAT);var v=!0;"depth"in n&&(v=!!n.depth);var g=!1;return"stencil"in n&&(g=!!n.stencil),new d(t,e,r,h,f,v,g,u)};var i,a,o,s,l=null;function u(t){return[t.getParameter(t.FRAMEBUFFER_BINDING),t.getParameter(t.RENDERBUFFER_BINDING),t.getParameter(t.TEXTURE_BINDING_2D)]}function c(t,e){t.bindFramebuffer(t.FRAMEBUFFER,e[0]),t.bindRenderbuffer(t.RENDERBUFFER,e[1]),t.bindTexture(t.TEXTURE_2D,e[2])}function f(t){switch(t){case i:throw new Error("gl-fbo: Framebuffer unsupported");case a:throw new Error("gl-fbo: Framebuffer incomplete attachment");case o:throw new Error("gl-fbo: Framebuffer incomplete dimensions");case s:throw new Error("gl-fbo: Framebuffer incomplete missing attachment");default:throw new Error("gl-fbo: Framebuffer failed for unspecified reason")}}function h(t,e,r,i,a,o){if(!i)return null;var s=n(t,e,r,a,i);return s.magFilter=t.NEAREST,s.minFilter=t.NEAREST,s.mipSamples=1,s.bind(),t.framebufferTexture2D(t.FRAMEBUFFER,o,t.TEXTURE_2D,s.handle,0),s}function p(t,e,r,n,i){var a=t.createRenderbuffer();return t.bindRenderbuffer(t.RENDERBUFFER,a),t.renderbufferStorage(t.RENDERBUFFER,n,e,r),t.framebufferRenderbuffer(t.FRAMEBUFFER,i,t.RENDERBUFFER,a),a}function d(t,e,r,n,i,a,o,s){this.gl=t,this._shape=[0|e,0|r],this._destroyed=!1,this._ext=s,this.color=new Array(i);for(var d=0;d<i;++d)this.color[d]=null;this._color_rb=null,this.depth=null,this._depth_rb=null,this._colorType=n,this._useDepth=a,this._useStencil=o;var v=this,g=[0|e,0|r];Object.defineProperties(g,{0:{get:function(){return v._shape[0]},set:function(t){return v.width=t}},1:{get:function(){return v._shape[1]},set:function(t){return v.height=t}}}),this._shapeVector=g,function(t){var e=u(t.gl),r=t.gl,n=t.handle=r.createFramebuffer(),i=t._shape[0],a=t._shape[1],o=t.color.length,s=t._ext,d=t._useStencil,v=t._useDepth,g=t._colorType;r.bindFramebuffer(r.FRAMEBUFFER,n);for(var y=0;y<o;++y)t.color[y]=h(r,i,a,g,r.RGBA,r.COLOR_ATTACHMENT0+y);0===o?(t._color_rb=p(r,i,a,r.RGBA4,r.COLOR_ATTACHMENT0),s&&s.drawBuffersWEBGL(l[0])):o>1&&s.drawBuffersWEBGL(l[o]);var m=r.getExtension("WEBGL_depth_texture");m?d?t.depth=h(r,i,a,m.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):v&&(t.depth=h(r,i,a,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):v&&d?t._depth_rb=p(r,i,a,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):v?t._depth_rb=p(r,i,a,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):d&&(t._depth_rb=p(r,i,a,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){for(t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null),y=0;y<t.color.length;++y)t.color[y].dispose(),t.color[y]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),c(r,e),f(x)}c(r,e)}(this)}var v=d.prototype;function g(t,e,r){if(t._destroyed)throw new Error("gl-fbo: Can't resize destroyed FBO");if(t._shape[0]!==e||t._shape[1]!==r){var n=t.gl,i=n.getParameter(n.MAX_RENDERBUFFER_SIZE);if(e<0||e>i||r<0||r>i)throw new Error("gl-fbo: Can't resize FBO, invalid dimensions");t._shape[0]=e,t._shape[1]=r;for(var a=u(n),o=0;o<t.color.length;++o)t.color[o].shape=t._shape;t._color_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._color_rb),n.renderbufferStorage(n.RENDERBUFFER,n.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&n.renderbufferStorage(n.RENDERBUFFER,n.STENCIL_INDEX,t._shape[0],t._shape[1])),n.bindFramebuffer(n.FRAMEBUFFER,t.handle);var s=n.checkFramebufferStatus(n.FRAMEBUFFER);s!==n.FRAMEBUFFER_COMPLETE&&(t.dispose(),c(n,a),f(s)),c(n,a)}}Object.defineProperties(v,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error("gl-fbo: Shape vector must be length 2");var e=0|t[0],r=0|t[1];return g(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return g(this,t|=0,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t|=0,g(this,this._shape[0],t),t},enumerable:!1}}),v.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},v.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},3530:function(t,e,r){var n=r(8974).sprintf,i=r(6603),a=r(9365),o=r(8008);t.exports=function(t,e,r){"use strict";var s=a(e)||"of unknown name (see npm glsl-shader-name)",l="unknown type";void 0!==r&&(l=r===i.FRAGMENT_SHADER?"fragment":"vertex");for(var u=n("Error compiling %s shader %s:\n",l,s),c=n("%s%s",u,t),f=t.split("\n"),h={},p=0;p<f.length;p++){var d=f[p];if(""!==d&&"\0"!==d){var v=parseInt(d.split(":")[2]);if(isNaN(v))throw new Error(n("Could not parse error: %s",d));h[v]=d}}var g=o(e).split("\n");for(p=0;p<g.length;p++)if((h[p+3]||h[p+2]||h[p+1])&&(u+=g[p]+"\n",h[p+1])){var y=h[p+1];y=y.substr(y.split(":",3).join(":").length+1).trim(),u+=n("^^^ %s\n\n",y)}return{long:u.trim(),short:c.trim()}}},6386:function(t,e,r){"use strict";t.exports=function(t,e){var r=t.gl,n=new u(t,o(r,l.vertex,l.fragment),o(r,l.pickVertex,l.pickFragment),s(r),s(r),s(r),s(r));return n.update(e),t.addObject(n),n};var n=r(5070),i=r(9560),a=r(5306),o=r(5158),s=r(5827),l=r(1292);function u(t,e,r,n,i,a,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.weightBuffer=i,this.colorBuffer=a,this.idBuffer=o,this.xData=[],this.yData=[],this.shape=[0,0],this.bounds=[1/0,1/0,-1/0,-1/0],this.pickOffset=0}var c,f=u.prototype,h=[0,0,1,0,0,1,1,0,1,1,0,1];f.draw=(c=[1,0,0,0,1,0,0,0,1],function(){var t=this.plot,e=this.shader,r=this.bounds,n=this.numVertices;if(!(n<=0)){var i=t.gl,a=t.dataBox,o=r[2]-r[0],s=r[3]-r[1],l=a[2]-a[0],u=a[3]-a[1];c[0]=2*o/l,c[4]=2*s/u,c[6]=2*(r[0]-a[0])/l-1,c[7]=2*(r[1]-a[1])/u-1,e.bind();var f=e.uniforms;f.viewTransform=c,f.shape=this.shape;var h=e.attributes;this.positionBuffer.bind(),h.position.pointer(),this.weightBuffer.bind(),h.weight.pointer(i.UNSIGNED_BYTE,!1),this.colorBuffer.bind(),h.color.pointer(i.UNSIGNED_BYTE,!0),i.drawArrays(i.TRIANGLES,0,n)}}),f.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,i=this.pickShader,a=this.bounds,o=this.numVertices;if(!(o<=0)){var s=n.gl,l=n.dataBox,u=a[2]-a[0],c=a[3]-a[1],f=l[2]-l[0],h=l[3]-l[1];t[0]=2*u/f,t[4]=2*c/h,t[6]=2*(a[0]-l[0])/f-1,t[7]=2*(a[1]-l[1])/h-1;for(var p=0;p<4;++p)e[p]=r>>8*p&255;this.pickOffset=r,i.bind();var d=i.uniforms;d.viewTransform=t,d.pickOffset=e,d.shape=this.shape;var v=i.attributes;return this.positionBuffer.bind(),v.position.pointer(),this.weightBuffer.bind(),v.weight.pointer(s.UNSIGNED_BYTE,!1),this.idBuffer.bind(),v.pickId.pointer(s.UNSIGNED_BYTE,!1),s.drawArrays(s.TRIANGLES,0,o),r+this.shape[0]*this.shape[1]}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.shape[0]*this.shape[1];if(r<n||r>=n+i)return null;var a=r-n,o=this.xData,s=this.yData;return{object:this,pointId:a,dataCoord:[o[a%this.shape[0]],s[a/this.shape[0]|0]]}},f.update=function(t){var e=(t=t||{}).shape||[0,0],r=t.x||i(e[0]),o=t.y||i(e[1]),s=t.z||new Float32Array(e[0]*e[1]),l=!1!==t.zsmooth;this.xData=r,this.yData=o;var u,c,f,p,d=t.colorLevels||[0],v=t.colorValues||[0,0,0,1],g=d.length,y=this.bounds;l?(u=y[0]=r[0],c=y[1]=o[0],f=y[2]=r[r.length-1],p=y[3]=o[o.length-1]):(u=y[0]=r[0]+(r[1]-r[0])/2,c=y[1]=o[0]+(o[1]-o[0])/2,f=y[2]=r[r.length-1]+(r[r.length-1]-r[r.length-2])/2,p=y[3]=o[o.length-1]+(o[o.length-1]-o[o.length-2])/2);var m=1/(f-u),x=1/(p-c),b=e[0],_=e[1];this.shape=[b,_];var w=(l?(b-1)*(_-1):b*_)*(h.length>>>1);this.numVertices=w;for(var T=a.mallocUint8(4*w),k=a.mallocFloat32(2*w),A=a.mallocUint8(2*w),M=a.mallocUint32(w),S=0,E=l?b-1:b,L=l?_-1:_,C=0;C<L;++C){var P,O;l?(P=x*(o[C]-c),O=x*(o[C+1]-c)):(P=C<_-1?x*(o[C]-(o[C+1]-o[C])/2-c):x*(o[C]-(o[C]-o[C-1])/2-c),O=C<_-1?x*(o[C]+(o[C+1]-o[C])/2-c):x*(o[C]+(o[C]-o[C-1])/2-c));for(var I=0;I<E;++I){var D,z;l?(D=m*(r[I]-u),z=m*(r[I+1]-u)):(D=I<b-1?m*(r[I]-(r[I+1]-r[I])/2-u):m*(r[I]-(r[I]-r[I-1])/2-u),z=I<b-1?m*(r[I]+(r[I+1]-r[I])/2-u):m*(r[I]+(r[I]-r[I-1])/2-u));for(var R=0;R<h.length;R+=2){var F,B,N,j,U=h[R],V=h[R+1],H=s[l?(C+V)*b+(I+U):C*b+I],q=n.le(d,H);if(q<0)F=v[0],B=v[1],N=v[2],j=v[3];else if(q===g-1)F=v[4*g-4],B=v[4*g-3],N=v[4*g-2],j=v[4*g-1];else{var G=(H-d[q])/(d[q+1]-d[q]),Z=1-G,Y=4*q,W=4*(q+1);F=Z*v[Y]+G*v[W],B=Z*v[Y+1]+G*v[W+1],N=Z*v[Y+2]+G*v[W+2],j=Z*v[Y+3]+G*v[W+3]}T[4*S]=255*F,T[4*S+1]=255*B,T[4*S+2]=255*N,T[4*S+3]=255*j,k[2*S]=.5*D+.5*z,k[2*S+1]=.5*P+.5*O,A[2*S]=U,A[2*S+1]=V,M[S]=C*b+I,S+=1}}}this.positionBuffer.update(k),this.weightBuffer.update(A),this.colorBuffer.update(T),this.idBuffer.update(M),a.free(k),a.free(T),a.free(A),a.free(M)},f.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.weightBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},1292:function(t,e,r){"use strict";var n=r(6832);t.exports={fragment:n(["precision lowp float;\n#define GLSLIFY 1\nvarying vec4 fragColor;\nvoid main() {\n  gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\n}\n"]),vertex:n(["precision mediump float;\n#define GLSLIFY 1\n\nattribute vec2 position;\nattribute vec4 color;\nattribute vec2 weight;\n\nuniform vec2 shape;\nuniform mat3 viewTransform;\n\nvarying vec4 fragColor;\n\nvoid main() {\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\n  fragColor = color;\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\n}\n"]),pickFragment:n(["precision mediump float;\n#define GLSLIFY 1\n\nvarying vec4 fragId;\nvarying vec2 vWeight;\n\nuniform vec2 shape;\nuniform vec4 pickOffset;\n\nvoid main() {\n  vec2 d = step(.5, vWeight);\n  vec4 id = fragId + pickOffset;\n  id.x += d.x + d.y*shape.x;\n\n  id.y += floor(id.x / 256.0);\n  id.x -= floor(id.x / 256.0) * 256.0;\n\n  id.z += floor(id.y / 256.0);\n  id.y -= floor(id.y / 256.0) * 256.0;\n\n  id.w += floor(id.z / 256.0);\n  id.z -= floor(id.z / 256.0) * 256.0;\n\n  gl_FragColor = id/255.;\n}\n"]),pickVertex:n(["precision mediump float;\n#define GLSLIFY 1\n\nattribute vec2 position;\nattribute vec4 pickId;\nattribute vec2 weight;\n\nuniform vec2 shape;\nuniform mat3 viewTransform;\n\nvarying vec4 fragId;\nvarying vec2 vWeight;\n\nvoid main() {\n  vWeight = weight;\n\n  fragId = pickId;\n\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\n}\n"])}},248:function(t,e,r){var n=r(6832),i=r(5158),a=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position, nextPosition;\nattribute float arcLength, lineWidth;\nattribute vec4 color;\n\nuniform vec2 screenShape;\nuniform float pixelRatio;\nuniform mat4 model, view, projection;\n\nvarying vec4 fragColor;\nvarying vec3 worldPosition;\nvarying float pixelArcLength;\n\nvec4 project(vec3 p) {\n  return projection * view * model * vec4(p, 1.0);\n}\n\nvoid main() {\n  vec4 startPoint = project(position);\n  vec4 endPoint   = project(nextPosition);\n\n  vec2 A = startPoint.xy / startPoint.w;\n  vec2 B =   endPoint.xy /   endPoint.w;\n\n  float clipAngle = atan(\n    (B.y - A.y) * screenShape.y,\n    (B.x - A.x) * screenShape.x\n  );\n\n  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(\n    sin(clipAngle),\n    -cos(clipAngle)\n  ) / screenShape;\n\n  gl_Position = vec4(startPoint.xy + startPoint.w * offset, startPoint.zw);\n\n  worldPosition = position;\n  pixelArcLength = arcLength;\n  fragColor = color;\n}\n"]),o=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3      clipBounds[2];\nuniform sampler2D dashTexture;\nuniform float     dashScale;\nuniform float     opacity;\n\nvarying vec3    worldPosition;\nvarying float   pixelArcLength;\nvarying vec4    fragColor;\n\nvoid main() {\n  if (\n    outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\n    fragColor.a * opacity == 0.\n  ) discard;\n\n  float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\n  if(dashWeight < 0.5) {\n    discard;\n  }\n  gl_FragColor = fragColor * opacity;\n}\n"]),s=n(["precision highp float;\n#define GLSLIFY 1\n\n#define FLOAT_MAX  1.70141184e38\n#define FLOAT_MIN  1.17549435e-38\n\n// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl\nvec4 packFloat(float v) {\n  float av = abs(v);\n\n  //Handle special cases\n  if(av < FLOAT_MIN) {\n    return vec4(0.0, 0.0, 0.0, 0.0);\n  } else if(v > FLOAT_MAX) {\n    return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\n  } else if(v < -FLOAT_MAX) {\n    return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\n  }\n\n  vec4 c = vec4(0,0,0,0);\n\n  //Compute exponent and mantissa\n  float e = floor(log2(av));\n  float m = av * pow(2.0, -e) - 1.0;\n\n  //Unpack mantissa\n  c[1] = floor(128.0 * m);\n  m -= c[1] / 128.0;\n  c[2] = floor(32768.0 * m);\n  m -= c[2] / 32768.0;\n  c[3] = floor(8388608.0 * m);\n\n  //Unpack exponent\n  float ebias = e + 127.0;\n  c[0] = floor(ebias / 2.0);\n  ebias -= c[0] * 2.0;\n  c[1] += floor(ebias) * 128.0;\n\n  //Unpack sign bit\n  c[0] += 128.0 * step(0.0, -v);\n\n  //Scale back to range\n  return c / 255.0;\n}\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform float pickId;\nuniform vec3 clipBounds[2];\n\nvarying vec3 worldPosition;\nvarying float pixelArcLength;\nvarying vec4 fragColor;\n\nvoid main() {\n  if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\n\n  gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz);\n}"]),l=[{name:"position",type:"vec3"},{name:"nextPosition",type:"vec3"},{name:"arcLength",type:"float"},{name:"lineWidth",type:"float"},{name:"color",type:"vec4"}];e.createShader=function(t){return i(t,a,o,null,l)},e.createPickShader=function(t){return i(t,a,s,null,l)}},6086:function(t,e,r){"use strict";t.exports=function(t){var e=t.gl||t.scene&&t.scene.gl,r=f(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var o=h(e);o.attributes.position.location=0,o.attributes.nextPosition.location=1,o.attributes.arcLength.location=2,o.attributes.lineWidth.location=3,o.attributes.color.location=4;for(var s=n(e),l=i(e,[{buffer:s,size:3,offset:0,stride:48},{buffer:s,size:3,offset:12,stride:48},{buffer:s,size:1,offset:24,stride:48},{buffer:s,size:1,offset:28,stride:48},{buffer:s,size:4,offset:32,stride:48}]),c=u(new Array(1024),[256,1,4]),p=0;p<1024;++p)c.data[p]=255;var d=a(e,c);d.wrap=e.REPEAT;var v=new y(e,r,o,s,l,d);return v.update(t),v};var n=r(5827),i=r(2944),a=r(8931),o=new Uint8Array(4),s=new Float32Array(o.buffer),l=r(5070),u=r(5050),c=r(248),f=c.createShader,h=c.createPickShader,p=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function d(t,e){for(var r=0,n=0;n<3;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function v(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function g(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function y(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.hasAlpha=!1,this.dirty=!0,this.pixelRatio=1}var m=y.prototype;m.isTransparent=function(){return this.hasAlpha},m.isOpaque=function(){return!this.hasAlpha},m.pickSlots=1,m.setPickBase=function(t){this.pickId=t},m.drawTransparent=m.draw=function(t){if(this.vertexCount){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,clipBounds:v(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},m.drawPick=function(t){if(this.vertexCount){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,pickId:this.pickId,clipBounds:v(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},m.update=function(t){var e,r;this.dirty=!0;var n=!!t.connectGaps;"dashScale"in t&&(this.dashScale=t.dashScale),this.hasAlpha=!1,"opacity"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var i=[],a=[],o=[],s=0,c=0,f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],h=t.position||t.positions;if(h){var p=t.color||t.colors||[0,0,0,1],v=t.lineWidth||1,g=!1;t:for(e=1;e<h.length;++e){var y,m,x,b=h[e-1],_=h[e];for(a.push(s),o.push(b.slice()),r=0;r<3;++r){if(isNaN(b[r])||isNaN(_[r])||!isFinite(b[r])||!isFinite(_[r])){if(!n&&i.length>0){for(var w=0;w<24;++w)i.push(i[i.length-12]);c+=2,g=!0}continue t}f[0][r]=Math.min(f[0][r],b[r],_[r]),f[1][r]=Math.max(f[1][r],b[r],_[r])}Array.isArray(p[0])?(y=p.length>e-1?p[e-1]:p.length>0?p[p.length-1]:[0,0,0,1],m=p.length>e?p[e]:p.length>0?p[p.length-1]:[0,0,0,1]):y=m=p,3===y.length&&(y=[y[0],y[1],y[2],1]),3===m.length&&(m=[m[0],m[1],m[2],1]),!this.hasAlpha&&y[3]<1&&(this.hasAlpha=!0),x=Array.isArray(v)?v.length>e-1?v[e-1]:v.length>0?v[v.length-1]:[0,0,0,1]:v;var T=s;if(s+=d(b,_),g){for(r=0;r<2;++r)i.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,y[0],y[1],y[2],y[3]);c+=2,g=!1}i.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,y[0],y[1],y[2],y[3],b[0],b[1],b[2],_[0],_[1],_[2],T,-x,y[0],y[1],y[2],y[3],_[0],_[1],_[2],b[0],b[1],b[2],s,-x,m[0],m[1],m[2],m[3],_[0],_[1],_[2],b[0],b[1],b[2],s,x,m[0],m[1],m[2],m[3]),c+=4}}if(this.buffer.update(i),a.push(s),o.push(h[h.length-1].slice()),this.bounds=f,this.vertexCount=c,this.points=o,this.arcLength=a,"dashes"in t){var k=t.dashes.slice();for(k.unshift(0),e=1;e<k.length;++e)k[e]=k[e-1]+k[e];var A=u(new Array(1024),[256,1,4]);for(e=0;e<256;++e){for(r=0;r<4;++r)A.set(e,0,r,0);1&l.le(k,k[k.length-1]*e/255)?A.set(e,0,0,0):A.set(e,0,0,255)}this.texture.setPixels(A)}},m.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()},m.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=function(t,e,r,n){return o[0]=0,o[1]=r,o[2]=e,o[3]=t,s[0]}(t.value[0],t.value[1],t.value[2]),r=l.le(this.arcLength,e);if(r<0)return null;if(r===this.arcLength.length-1)return new g(this.arcLength[this.arcLength.length-1],this.points[this.points.length-1].slice(),r);for(var n=this.points[r],i=this.points[Math.min(r+1,this.points.length-1)],a=(e-this.arcLength[r])/(this.arcLength[r+1]-this.arcLength[r]),u=1-a,c=[0,0,0],f=0;f<3;++f)c[f]=u*n[f]+a*i[f];var h=Math.min(a<.5?r:r+1,this.points.length-1);return new g(e,c,h,this.points[h])}},7332:function(t){t.exports=function(t){var e=new Float32Array(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e}},9823:function(t){t.exports=function(){var t=new Float32Array(16);return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},7787:function(t){t.exports=function(t){var e=t[0],r=t[1],n=t[2],i=t[3],a=t[4],o=t[5],s=t[6],l=t[7],u=t[8],c=t[9],f=t[10],h=t[11],p=t[12],d=t[13],v=t[14],g=t[15];return(e*o-r*a)*(f*g-h*v)-(e*s-n*a)*(c*g-h*d)+(e*l-i*a)*(c*v-f*d)+(r*s-n*o)*(u*g-h*p)-(r*l-i*o)*(u*v-f*p)+(n*l-i*s)*(u*d-c*p)}},5950:function(t){t.exports=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=r+r,s=n+n,l=i+i,u=r*o,c=n*o,f=n*s,h=i*o,p=i*s,d=i*l,v=a*o,g=a*s,y=a*l;return t[0]=1-f-d,t[1]=c+y,t[2]=h-g,t[3]=0,t[4]=c-y,t[5]=1-u-d,t[6]=p+v,t[7]=0,t[8]=h+g,t[9]=p-v,t[10]=1-u-f,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},7280:function(t){t.exports=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=n+n,l=i+i,u=a+a,c=n*s,f=n*l,h=n*u,p=i*l,d=i*u,v=a*u,g=o*s,y=o*l,m=o*u;return t[0]=1-(p+v),t[1]=f+m,t[2]=h-y,t[3]=0,t[4]=f-m,t[5]=1-(c+v),t[6]=d+g,t[7]=0,t[8]=h+y,t[9]=d-g,t[10]=1-(c+p),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}},9947:function(t){t.exports=function(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},7437:function(t){t.exports=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],f=e[9],h=e[10],p=e[11],d=e[12],v=e[13],g=e[14],y=e[15],m=r*s-n*o,x=r*l-i*o,b=r*u-a*o,_=n*l-i*s,w=n*u-a*s,T=i*u-a*l,k=c*v-f*d,A=c*g-h*d,M=c*y-p*d,S=f*g-h*v,E=f*y-p*v,L=h*y-p*g,C=m*L-x*E+b*S+_*M-w*A+T*k;return C?(C=1/C,t[0]=(s*L-l*E+u*S)*C,t[1]=(i*E-n*L-a*S)*C,t[2]=(v*T-g*w+y*_)*C,t[3]=(h*w-f*T-p*_)*C,t[4]=(l*M-o*L-u*A)*C,t[5]=(r*L-i*M+a*A)*C,t[6]=(g*b-d*T-y*x)*C,t[7]=(c*T-h*b+p*x)*C,t[8]=(o*E-s*M+u*k)*C,t[9]=(n*M-r*E-a*k)*C,t[10]=(d*w-v*b+y*m)*C,t[11]=(f*b-c*w-p*m)*C,t[12]=(s*A-o*S-l*k)*C,t[13]=(r*S-n*A+i*k)*C,t[14]=(v*x-d*_-g*m)*C,t[15]=(c*_-f*x+h*m)*C,t):null}},3012:function(t,e,r){var n=r(9947);t.exports=function(t,e,r,i){var a,o,s,l,u,c,f,h,p,d,v=e[0],g=e[1],y=e[2],m=i[0],x=i[1],b=i[2],_=r[0],w=r[1],T=r[2];return Math.abs(v-_)<1e-6&&Math.abs(g-w)<1e-6&&Math.abs(y-T)<1e-6?n(t):(f=v-_,h=g-w,p=y-T,a=x*(p*=d=1/Math.sqrt(f*f+h*h+p*p))-b*(h*=d),o=b*(f*=d)-m*p,s=m*h-x*f,(d=Math.sqrt(a*a+o*o+s*s))?(a*=d=1/d,o*=d,s*=d):(a=0,o=0,s=0),l=h*s-p*o,u=p*a-f*s,c=f*o-h*a,(d=Math.sqrt(l*l+u*u+c*c))?(l*=d=1/d,u*=d,c*=d):(l=0,u=0,c=0),t[0]=a,t[1]=l,t[2]=f,t[3]=0,t[4]=o,t[5]=u,t[6]=h,t[7]=0,t[8]=s,t[9]=c,t[10]=p,t[11]=0,t[12]=-(a*v+o*g+s*y),t[13]=-(l*v+u*g+c*y),t[14]=-(f*v+h*g+p*y),t[15]=1,t)}},104:function(t){t.exports=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],u=e[6],c=e[7],f=e[8],h=e[9],p=e[10],d=e[11],v=e[12],g=e[13],y=e[14],m=e[15],x=r[0],b=r[1],_=r[2],w=r[3];return t[0]=x*n+b*s+_*f+w*v,t[1]=x*i+b*l+_*h+w*g,t[2]=x*a+b*u+_*p+w*y,t[3]=x*o+b*c+_*d+w*m,x=r[4],b=r[5],_=r[6],w=r[7],t[4]=x*n+b*s+_*f+w*v,t[5]=x*i+b*l+_*h+w*g,t[6]=x*a+b*u+_*p+w*y,t[7]=x*o+b*c+_*d+w*m,x=r[8],b=r[9],_=r[10],w=r[11],t[8]=x*n+b*s+_*f+w*v,t[9]=x*i+b*l+_*h+w*g,t[10]=x*a+b*u+_*p+w*y,t[11]=x*o+b*c+_*d+w*m,x=r[12],b=r[13],_=r[14],w=r[15],t[12]=x*n+b*s+_*f+w*v,t[13]=x*i+b*l+_*h+w*g,t[14]=x*a+b*u+_*p+w*y,t[15]=x*o+b*c+_*d+w*m,t}},5268:function(t){t.exports=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),u=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*u,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*u,t[15]=1,t}},1120:function(t){t.exports=function(t,e,r,n,i){var a=1/Math.tan(e/2),o=1/(n-i);return t[0]=a/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=a,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(i+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*i*n*o,t[15]=0,t}},4422:function(t){t.exports=function(t,e,r,n){var 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r=0,a=0,o=0;o<2;++o)r+=Math.pow(e[o]-t[0][o],2),a+=Math.pow(e[o]-t[1][o],2);return(r=Math.sqrt(r))+(a=Math.sqrt(a))<1e-6?[1,0]:[a/(r+a),r/(a+r)]}if(3===t.length){var s=[0,0];return i(t[0],t[1],t[2],e,s),n(t,s)}return[]}(c,e),y=0;for(f=0;f<3;++f){if(g[f]<-.001||g[f]>1.0001)return null;y+=g[f]}return Math.abs(y-1)>.001?null:[h,s(t,g),g]}},2056:function(t,e,r){var n=r(6832),i=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position, normal;\nattribute vec4 color;\nattribute vec2 uv;\n\nuniform mat4 model\n           , view\n           , projection\n           , inverseModel;\nuniform vec3 eyePosition\n           , lightPosition;\n\nvarying vec3 f_normal\n           , f_lightDirection\n           , f_eyeDirection\n           , f_data;\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvec4 project(vec3 p) {\n  return projection * view * model * vec4(p, 1.0);\n}\n\nvoid main() {\n  gl_Position      = project(position);\n\n  //Lighting geometry parameters\n  vec4 cameraCoordinate = view * vec4(position , 1.0);\n  cameraCoordinate.xyz /= cameraCoordinate.w;\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\n  f_normal  = normalize((vec4(normal, 0.0) * inverseModel).xyz);\n\n  f_color          = color;\n  f_data           = position;\n  f_uv             = uv;\n}\n"]),a=n(["#extension GL_OES_standard_derivatives : enable\n\nprecision highp float;\n#define GLSLIFY 1\n\nfloat beckmannDistribution(float x, float roughness) {\n  float NdotH = max(x, 0.0001);\n  float cos2Alpha = NdotH * NdotH;\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\n  float roughness2 = roughness * roughness;\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\n  return exp(tan2Alpha / roughness2) / denom;\n}\n\nfloat cookTorranceSpecular(\n  vec3 lightDirection,\n  vec3 viewDirection,\n  vec3 surfaceNormal,\n  float roughness,\n  float fresnel) {\n\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\n\n  //Half angle vector\n  vec3 H = normalize(lightDirection + viewDirection);\n\n  //Geometric term\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\n  float VdotH = max(dot(viewDirection, H), 0.000001);\n  float LdotH = max(dot(lightDirection, H), 0.000001);\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\n  float G = min(1.0, min(G1, G2));\n  \n  //Distribution term\n  float D = beckmannDistribution(NdotH, roughness);\n\n  //Fresnel term\n  float F = pow(1.0 - VdotN, fresnel);\n\n  //Multiply terms and done\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\n}\n\n//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform float roughness\n            , fresnel\n            , kambient\n            , kdiffuse\n            , kspecular;\nuniform sampler2D texture;\n\nvarying vec3 f_normal\n           , f_lightDirection\n           , f_eyeDirection\n           , f_data;\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvoid main() {\n  if (f_color.a == 0.0 ||\n    outOfRange(clipBounds[0], clipBounds[1], f_data)\n  ) discard;\n\n  vec3 N = normalize(f_normal);\n  vec3 L = normalize(f_lightDirection);\n  vec3 V = normalize(f_eyeDirection);\n\n  if(gl_FrontFacing) {\n    N = -N;\n  }\n\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\n  //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\n\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\n\n  vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\n\n  gl_FragColor = litColor * f_color.a;\n}\n"]),o=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position;\nattribute vec4 color;\nattribute vec2 uv;\n\nuniform mat4 model, view, projection;\n\nvarying vec4 f_color;\nvarying vec3 f_data;\nvarying vec2 f_uv;\n\nvoid main() {\n  gl_Position = projection * view * model * vec4(position, 1.0);\n  f_color = color;\n  f_data  = position;\n  f_uv    = uv;\n}"]),s=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform sampler2D texture;\nuniform float opacity;\n\nvarying vec4 f_color;\nvarying vec3 f_data;\nvarying vec2 f_uv;\n\nvoid main() {\n  if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\n\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\n}"]),l=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nattribute vec3 position;\nattribute vec4 color;\nattribute vec2 uv;\nattribute float pointSize;\n\nuniform mat4 model, view, projection;\nuniform vec3 clipBounds[2];\n\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvoid main() {\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\n\n    gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\n  } else {\n    gl_Position = projection * view * model * vec4(position, 1.0);\n  }\n  gl_PointSize = pointSize;\n  f_color = color;\n  f_uv = uv;\n}"]),u=n(["precision highp float;\n#define GLSLIFY 1\n\nuniform sampler2D texture;\nuniform float opacity;\n\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvoid main() {\n  vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\n  if(dot(pointR, pointR) > 0.25) {\n    discard;\n  }\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\n}"]),c=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position;\nattribute vec4 id;\n\nuniform mat4 model, view, projection;\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() {\n  gl_Position = projection * view * model * vec4(position, 1.0);\n  f_id        = id;\n  f_position  = position;\n}"]),f=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3  clipBounds[2];\nuniform float pickId;\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() {\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\n\n  gl_FragColor = vec4(pickId, f_id.xyz);\n}"]),h=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nattribute vec3  position;\nattribute float pointSize;\nattribute vec4  id;\n\nuniform mat4 model, view, projection;\nuniform vec3 clipBounds[2];\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() {\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\n\n    gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\n  } else {\n    gl_Position  = projection * view * model * vec4(position, 1.0);\n    gl_PointSize = pointSize;\n  }\n  f_id         = id;\n  f_position   = position;\n}"]),p=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position;\n\nuniform mat4 model, view, projection;\n\nvoid main() {\n  gl_Position = projection * view * model * vec4(position, 1.0);\n}"]),d=n(["precision highp float;\n#define GLSLIFY 1\n\nuniform vec3 contourColor;\n\nvoid main() {\n  gl_FragColor = vec4(contourColor, 1.0);\n}\n"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:"position",type:"vec3"},{name:"normal",type:"vec3"},{name:"color",type:"vec4"},{name:"uv",type:"vec2"}]},e.wireShader={vertex:o,fragment:s,attributes:[{name:"position",type:"vec3"},{name:"color",type:"vec4"},{name:"uv",type:"vec2"}]},e.pointShader={vertex:l,fragment:u,attributes:[{name:"position",type:"vec3"},{name:"color",type:"vec4"},{name:"uv",type:"vec2"},{name:"pointSize",type:"float"}]},e.pickShader={vertex:c,fragment:f,attributes:[{name:"position",type:"vec3"},{name:"id",type:"vec4"}]},e.pointPickShader={vertex:h,fragment:f,attributes:[{name:"position",type:"vec3"},{name:"pointSize",type:"float"},{name:"id",type:"vec4"}]},e.contourShader={vertex:p,fragment:d,attributes:[{name:"position",type:"vec3"}]}},8116:function(t,e,r){"use strict";var n=r(5158),i=r(5827),a=r(2944),o=r(8931),s=r(115),l=r(104),u=r(7437),c=r(5050),f=r(9156),h=r(7212),p=r(5306),d=r(2056),v=r(4340),g=d.meshShader,y=d.wireShader,m=d.pointShader,x=d.pickShader,b=d.pointPickShader,_=d.contourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function T(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,T,k,A,M,S){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=c,this.triangleNormals=h,this.triangleUVs=f,this.triangleIds=u,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=g,this.edgeUVs=y,this.edgeIds=v,this.edgeVAO=m,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=T,this.pointSizes=k,this.pointIds=b,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=M,this.contourVAO=S,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=w,this._view=w,this._projection=w,this._resolution=[1,1]}var k=T.prototype;function A(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}function M(t){var e=n(t,m.vertex,m.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function S(t){var e=n(t,x.vertex,x.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e}function E(t){var e=n(t,b.vertex,b.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function L(t){var e=n(t,_.vertex,_.fragment);return e.attributes.position.location=0,e}k.isOpaque=function(){return!this.hasAlpha},k.isTransparent=function(){return this.hasAlpha},k.pickSlots=1,k.setPickBase=function(t){this.pickId=t},k.highlight=function(t){if(t&&this.contourEnable){for(var e=h(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=p.mallocFloat32(6*a),s=0,l=0;l<a;++l)for(var u=r[l],c=0;c<2;++c){var f=u[0];2===u.length&&(f=u[c]);for(var d=n[f][0],v=n[f][1],g=i[f],y=1-g,m=this.positions[d],x=this.positions[v],b=0;b<3;++b)o[s++]=g*m[b]+y*x[b]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),p.free(o)}else this.contourCount=0},k.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,"contourEnable"in t&&(this.contourEnable=t.contourEnable),"contourColor"in t&&(this.contourColor=t.contourColor),"lineWidth"in t&&(this.lineWidth=t.lineWidth),"lightPosition"in t&&(this.lightPosition=t.lightPosition),this.hasAlpha=!1,"opacity"in t&&(this.opacity=t.opacity,this.opacity<1&&(this.hasAlpha=!0)),"opacityscale"in t&&(this.opacityscale=t.opacityscale,this.hasAlpha=!0),"ambient"in t&&(this.ambientLight=t.ambient),"diffuse"in t&&(this.diffuseLight=t.diffuse),"specular"in t&&(this.specularLight=t.specular),"roughness"in t&&(this.roughness=t.roughness),"fresnel"in t&&(this.fresnel=t.fresnel),t.texture?(this.texture.dispose(),this.texture=o(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t,e){for(var r=f({colormap:t,nshades:256,format:"rgba"}),n=new Uint8Array(1024),i=0;i<256;++i){for(var a=r[i],o=0;o<3;++o)n[4*i+o]=a[o];n[4*i+3]=e?255*A(i/255,e):255*a[3]}return c(n,[256,256,4],[4,0,1])}(t.colormap,this.opacityscale)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var i=[],a=[],l=[],u=[],h=[],p=[],d=[],v=[],g=[],y=[],m=[],x=[],b=[],_=[];this.cells=r,this.positions=n;var w=t.vertexNormals,T=t.cellNormals,k=void 0===t.vertexNormalsEpsilon?1e-6:t.vertexNormalsEpsilon,M=void 0===t.faceNormalsEpsilon?1e-6:t.faceNormalsEpsilon;t.useFacetNormals&&!T&&(T=s.faceNormals(r,n,M)),T||w||(w=s.vertexNormals(r,n,k));var S=t.vertexColors,E=t.cellColors,L=t.meshColor||[1,1,1,1],C=t.vertexUVs,P=t.vertexIntensity,O=t.cellUVs,I=t.cellIntensity,D=1/0,z=-1/0;if(!C&&!O)if(P)if(t.vertexIntensityBounds)D=+t.vertexIntensityBounds[0],z=+t.vertexIntensityBounds[1];else for(var R=0;R<P.length;++R){var F=P[R];D=Math.min(D,F),z=Math.max(z,F)}else if(I)if(t.cellIntensityBounds)D=+t.cellIntensityBounds[0],z=+t.cellIntensityBounds[1];else for(R=0;R<I.length;++R)F=I[R],D=Math.min(D,F),z=Math.max(z,F);else for(R=0;R<n.length;++R)F=n[R][2],D=Math.min(D,F),z=Math.max(z,F);this.intensity=P||I||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n),this.pickVertex=!(I||E);var B=t.pointSizes,N=t.pointSize||1;for(this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],R=0;R<n.length;++R)for(var j=n[R],U=0;U<3;++U)!isNaN(j[U])&&isFinite(j[U])&&(this.bounds[0][U]=Math.min(this.bounds[0][U],j[U]),this.bounds[1][U]=Math.max(this.bounds[1][U],j[U]));var V=0,H=0,q=0;t:for(R=0;R<r.length;++R){var G=r[R];switch(G.length){case 1:for(j=n[Y=G[0]],U=0;U<3;++U)if(isNaN(j[U])||!isFinite(j[U]))continue t;y.push(j[0],j[1],j[2]),W=S?S[Y]:E?E[R]:L,this.opacityscale&&P?a.push(W[0],W[1],W[2],this.opacity*A((P[Y]-D)/(z-D),this.opacityscale)):3===W.length?m.push(W[0],W[1],W[2],this.opacity):(m.push(W[0],W[1],W[2],W[3]*this.opacity),W[3]<1&&(this.hasAlpha=!0)),X=C?C[Y]:P?[(P[Y]-D)/(z-D),0]:O?O[R]:I?[(I[R]-D)/(z-D),0]:[(j[2]-D)/(z-D),0],x.push(X[0],X[1]),B?b.push(B[Y]):b.push(N),_.push(R),q+=1;break;case 2:for(U=0;U<2;++U){j=n[Y=G[U]];for(var Z=0;Z<3;++Z)if(isNaN(j[Z])||!isFinite(j[Z]))continue t}for(U=0;U<2;++U)j=n[Y=G[U]],p.push(j[0],j[1],j[2]),W=S?S[Y]:E?E[R]:L,this.opacityscale&&P?a.push(W[0],W[1],W[2],this.opacity*A((P[Y]-D)/(z-D),this.opacityscale)):3===W.length?d.push(W[0],W[1],W[2],this.opacity):(d.push(W[0],W[1],W[2],W[3]*this.opacity),W[3]<1&&(this.hasAlpha=!0)),X=C?C[Y]:P?[(P[Y]-D)/(z-D),0]:O?O[R]:I?[(I[R]-D)/(z-D),0]:[(j[2]-D)/(z-D),0],v.push(X[0],X[1]),g.push(R);H+=1;break;case 3:for(U=0;U<3;++U)for(j=n[Y=G[U]],Z=0;Z<3;++Z)if(isNaN(j[Z])||!isFinite(j[Z]))continue t;for(U=0;U<3;++U){var Y,W,X,J;j=n[Y=G[2-U]],i.push(j[0],j[1],j[2]),(W=S?S[Y]:E?E[R]:L)?this.opacityscale&&P?a.push(W[0],W[1],W[2],this.opacity*A((P[Y]-D)/(z-D),this.opacityscale)):3===W.length?a.push(W[0],W[1],W[2],this.opacity):(a.push(W[0],W[1],W[2],W[3]*this.opacity),W[3]<1&&(this.hasAlpha=!0)):a.push(.5,.5,.5,1),X=C?C[Y]:P?[(P[Y]-D)/(z-D),0]:O?O[R]:I?[(I[R]-D)/(z-D),0]:[(j[2]-D)/(z-D),0],u.push(X[0],X[1]),J=w?w[Y]:T[R],l.push(J[0],J[1],J[2]),h.push(R)}V+=1}}this.pointCount=q,this.edgeCount=H,this.triangleCount=V,this.pointPositions.update(y),this.pointColors.update(m),this.pointUVs.update(x),this.pointSizes.update(b),this.pointIds.update(new Uint32Array(_)),this.edgePositions.update(p),this.edgeColors.update(d),this.edgeUVs.update(v),this.edgeIds.update(new Uint32Array(g)),this.trianglePositions.update(i),this.triangleColors.update(a),this.triangleUVs.update(u),this.triangleNormals.update(l),this.triangleIds.update(new Uint32Array(h))}},k.drawTransparent=k.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,inverseModel:w.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],contourColor:this.contourColor,texture:0};s.inverseModel=u(s.inverseModel,s.model),e.disable(e.CULL_FACE),this.texture.bind(0);var c=new Array(16);for(l(c,s.view,s.model),l(c,s.projection,c),u(c,c),o=0;o<3;++o)s.eyePosition[o]=c[12+o]/c[15];var f,h=c[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*c[4*o+3];for(o=0;o<3;++o){for(var p=c[12+o],d=0;d<3;++d)p+=c[4*d+o]*this.lightPosition[d];s.lightPosition[o]=p/h}this.triangleCount>0&&((f=this.triShader).bind(),f.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&this.lineWidth>0&&((f=this.lineShader).bind(),f.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0&&((f=this.pointShader).bind(),f.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()),this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0&&((f=this.contourShader).bind(),f.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind())},k.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s,l={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255};(s=this.pickShader).bind(),s.uniforms=l,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0&&((s=this.pointPickShader).bind(),s.uniforms=l,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},k.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=t.coord[0],s=t.coord[1];if(!this.pickVertex){var l=this.positions[r[0]],u=this.positions[r[1]],c=this.positions[r[2]],f=[(l[0]+u[0]+c[0])/3,(l[1]+u[1]+c[1])/3,(l[2]+u[2]+c[2])/3];return{_cellCenter:!0,position:[o,s],index:e,cell:r,cellId:e,intensity:this.intensity[e],dataCoordinate:f}}var h=v(i,[o*this.pixelRatio,this._resolution[1]-s*this.pixelRatio],this._model,this._view,this._projection,this._resolution);if(!h)return null;var p=h[2],d=0;for(a=0;a<r.length;++a)d+=p[a]*this.intensity[r[a]];return{position:h[1],index:r[h[0]],cell:r,cellId:e,intensity:d,dataCoordinate:this.positions[r[h[0]]]}},k.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},t.exports=function(t,e){if(1===arguments.length&&(t=(e=t).gl),!(t.getExtension("OES_standard_derivatives")||t.getExtension("MOZ_OES_standard_derivatives")||t.getExtension("WEBKIT_OES_standard_derivatives")))throw new Error("derivatives not supported");var r=function(t){var e=n(t,g.vertex,g.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}(t),s=function(t){var e=n(t,y.vertex,y.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}(t),l=M(t),u=S(t),f=E(t),h=L(t),p=o(t,c(new Uint8Array([255,255,255,255]),[1,1,4]));p.generateMipmap(),p.minFilter=t.LINEAR_MIPMAP_LINEAR,p.magFilter=t.LINEAR;var d=i(t),v=i(t),m=i(t),x=i(t),b=i(t),_=a(t,[{buffer:d,type:t.FLOAT,size:3},{buffer:b,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:v,type:t.FLOAT,size:4},{buffer:m,type:t.FLOAT,size:2},{buffer:x,type:t.FLOAT,size:3}]),w=i(t),k=i(t),A=i(t),C=i(t),P=a(t,[{buffer:w,type:t.FLOAT,size:3},{buffer:C,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:k,type:t.FLOAT,size:4},{buffer:A,type:t.FLOAT,size:2}]),O=i(t),I=i(t),D=i(t),z=i(t),R=i(t),F=a(t,[{buffer:O,type:t.FLOAT,size:3},{buffer:R,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:I,type:t.FLOAT,size:4},{buffer:D,type:t.FLOAT,size:2},{buffer:z,type:t.FLOAT,size:1}]),B=i(t),N=new T(t,p,r,s,l,u,f,h,d,b,v,m,x,_,w,C,k,A,P,O,R,I,D,z,F,B,a(t,[{buffer:B,type:t.FLOAT,size:3}]));return N.update(e),N}},4554:function(t,e,r){"use strict";t.exports=function(t){var e=t.gl;return new o(t,n(e,[0,0,0,1,1,0,1,1]),i(e,a.boxVert,a.lineFrag))};var n=r(5827),i=r(5158),a=r(2709);function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,u=o.prototype;u.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},u.drawBox=(s=[0,0],l=[0,0],function(t,e,r,n,i){var a=this.plot,o=this.shader,u=a.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,o.uniforms.lo=s,o.uniforms.hi=l,o.uniforms.color=i,u.drawArrays(u.TRIANGLE_STRIP,0,4)}),u.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},3016:function(t,e,r){"use strict";t.exports=function(t){var e=t.gl;return new s(t,n(e),i(e,o.gridVert,o.gridFrag),i(e,o.tickVert,o.gridFrag))};var n=r(5827),i=r(5158),a=r(5070),o=r(2709);function s(t,e,r,n){this.plot=t,this.vbo=e,this.shader=r,this.tickShader=n,this.ticks=[[],[]]}function l(t,e){return t-e}var u,c,f,h,p,d=s.prototype;d.draw=(u=[0,0],c=[0,0],f=[0,0],function(){for(var t=this.plot,e=this.vbo,r=this.shader,n=this.ticks,i=t.gl,a=t._tickBounds,o=t.dataBox,s=t.viewBox,l=t.gridLineWidth,h=t.gridLineColor,p=t.gridLineEnable,d=t.pixelRatio,v=0;v<2;++v){var g=a[v],y=a[v+2]-g,m=.5*(o[v+2]+o[v]),x=o[v+2]-o[v];c[v]=2*y/x,u[v]=2*(g-m)/x}r.bind(),e.bind(),r.attributes.dataCoord.pointer(),r.uniforms.dataShift=u,r.uniforms.dataScale=c;var b=0;for(v=0;v<2;++v){f[0]=f[1]=0,f[v]=1,r.uniforms.dataAxis=f,r.uniforms.lineWidth=l[v]/(s[v+2]-s[v])*d,r.uniforms.color=h[v];var _=6*n[v].length;p[v]&&_&&i.drawArrays(i.TRIANGLES,b,_),b+=_}}),d.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],i=[0,0],o=[0,0];return function(){for(var s=this.plot,u=this.vbo,c=this.tickShader,f=this.ticks,h=s.gl,p=s._tickBounds,d=s.dataBox,v=s.viewBox,g=s.pixelRatio,y=s.screenBox,m=y[2]-y[0],x=y[3]-y[1],b=v[2]-v[0],_=v[3]-v[1],w=0;w<2;++w){var T=p[w],k=p[w+2]-T,A=.5*(d[w+2]+d[w]),M=d[w+2]-d[w];e[w]=2*k/M,t[w]=2*(T-A)/M}e[0]*=b/m,t[0]*=b/m,e[1]*=_/x,t[1]*=_/x,c.bind(),u.bind(),c.attributes.dataCoord.pointer();var S=c.uniforms;S.dataShift=t,S.dataScale=e;var E=s.tickMarkLength,L=s.tickMarkWidth,C=s.tickMarkColor,P=6*f[0].length,O=Math.min(a.ge(f[0],(d[0]-p[0])/(p[2]-p[0]),l),f[0].length),I=Math.min(a.gt(f[0],(d[2]-p[0])/(p[2]-p[0]),l),f[0].length),D=0+6*O,z=6*Math.max(0,I-O),R=Math.min(a.ge(f[1],(d[1]-p[1])/(p[3]-p[1]),l),f[1].length),F=Math.min(a.gt(f[1],(d[3]-p[1])/(p[3]-p[1]),l),f[1].length),B=P+6*R,N=6*Math.max(0,F-R);i[0]=2*(v[0]-E[1])/m-1,i[1]=(v[3]+v[1])/x-1,o[0]=E[1]*g/m,o[1]=L[1]*g/x,N&&(S.color=C[1],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(v[2]+v[0])/m-1,i[1]=2*(v[1]-E[0])/x-1,o[0]=L[0]*g/m,o[1]=E[0]*g/x,z&&(S.color=C[0],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,D,z)),i[0]=2*(v[2]+E[3])/m-1,i[1]=(v[3]+v[1])/x-1,o[0]=E[3]*g/m,o[1]=L[3]*g/x,N&&(S.color=C[3],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(v[2]+v[0])/m-1,i[1]=2*(v[3]+E[2])/x-1,o[0]=L[2]*g/m,o[1]=E[2]*g/x,z&&(S.color=C[2],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,D,z))}}(),d.update=(h=[1,1,-1,-1,1,-1],p=[1,-1,1,1,-1,-1],function(t){for(var e=t.ticks,r=t.bounds,n=new Float32Array(18*(e[0].length+e[1].length)),i=(this.plot.zeroLineEnable,0),a=[[],[]],o=0;o<2;++o)for(var s=a[o],l=e[o],u=r[o],c=r[o+2],f=0;f<l.length;++f){var d=(l[f].x-u)/(c-u);s.push(d);for(var v=0;v<6;++v)n[i++]=d,n[i++]=h[v],n[i++]=p[v]}this.ticks=a,this.vbo.update(n)}),d.dispose=function(){this.vbo.dispose(),this.shader.dispose(),this.tickShader.dispose()}},1154:function(t,e,r){"use strict";t.exports=function(t){var e=t.gl;return new o(t,n(e,[-1,-1,-1,1,1,-1,1,1]),i(e,a.lineVert,a.lineFrag))};var n=r(5827),i=r(5158),a=r(2709);function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,u=o.prototype;u.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},u.drawLine=(s=[0,0],l=[0,0],function(t,e,r,n,i,a){var o=this.plot,u=this.shader,c=o.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,u.uniforms.start=s,u.uniforms.end=l,u.uniforms.width=i*o.pixelRatio,u.uniforms.color=a,c.drawArrays(c.TRIANGLE_STRIP,0,4)}),u.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},2709:function(t,e,r){"use strict";var n=r(6832),i=n(["precision lowp float;\n#define GLSLIFY 1\nuniform vec4 color;\nvoid main() {\n  gl_FragColor = vec4(color.xyz * color.w, color.w);\n}\n"]);t.exports={lineVert:n(["precision mediump float;\n#define GLSLIFY 1\n\nattribute vec2 coord;\n\nuniform vec4 screenBox;\nuniform vec2 start, end;\nuniform float width;\n\nvec2 perp(vec2 v) {\n  return vec2(v.y, -v.x);\n}\n\nvec2 screen(vec2 v) {\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\n}\n\nvoid main() {\n  vec2 delta = normalize(perp(start - end));\n  vec2 offset = mix(start, end, 0.5 * (coord.y+1.0));\n  gl_Position = vec4(screen(offset + 0.5 * width * delta * coord.x), 0, 1);\n}\n"]),lineFrag:i,textVert:n(["#define GLSLIFY 1\nattribute vec3 textCoordinate;\n\nuniform vec2 dataScale, dataShift, dataAxis, screenOffset, textScale;\nuniform float angle;\n\nvoid main() {\n  float dataOffset  = textCoordinate.z;\n  vec2 glyphOffset  = textCoordinate.xy;\n  mat2 glyphMatrix = mat2(cos(angle), sin(angle), -sin(angle), cos(angle));\n  vec2 screenCoordinate = dataAxis * (dataScale * dataOffset + dataShift) +\n    glyphMatrix * glyphOffset * textScale + screenOffset;\n  gl_Position = vec4(screenCoordinate, 0, 1);\n}\n"]),textFrag:i,gridVert:n(["precision mediump float;\n#define GLSLIFY 1\n\nattribute vec3 dataCoord;\n\nuniform vec2 dataAxis, dataShift, dataScale;\nuniform float lineWidth;\n\nvoid main() {\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\n  pos += 10.0 * dataCoord.y * vec2(dataAxis.y, -dataAxis.x) + dataCoord.z * lineWidth;\n  gl_Position = vec4(pos, 0, 1);\n}\n"]),gridFrag:i,boxVert:n(["precision mediump float;\n#define GLSLIFY 1\n\nattribute vec2 coord;\n\nuniform vec4 screenBox;\nuniform vec2 lo, hi;\n\nvec2 screen(vec2 v) {\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\n}\n\nvoid main() {\n  gl_Position = vec4(screen(mix(lo, hi, coord)), 0, 1);\n}\n"]),tickVert:n(["precision mediump float;\n#define GLSLIFY 1\n\nattribute vec3 dataCoord;\n\nuniform vec2 dataAxis, dataShift, dataScale, screenOffset, tickScale;\n\nvoid main() {\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\n  gl_Position = vec4(pos + tickScale*dataCoord.yz + screenOffset, 0, 1);\n}\n"])}},5613:function(t,e,r){"use strict";t.exports=function(t){var e=t.gl;return new l(t,n(e),i(e,s.textVert,s.textFrag))};var n=r(5827),i=r(5158),a=r(6946),o=r(5070),s=r(2709);function l(t,e,r){this.plot=t,this.vbo=e,this.shader=r,this.tickOffset=[[],[]],this.tickX=[[],[]],this.labelOffset=[0,0],this.labelCount=[0,0]}var u,c,f,h,p,d,v=l.prototype;v.drawTicks=(u=[0,0],c=[0,0],f=[0,0],function(t){var e=this.plot,r=this.shader,n=this.tickX[t],i=this.tickOffset[t],a=e.gl,s=e.viewBox,l=e.dataBox,h=e.screenBox,p=e.pixelRatio,d=e.tickEnable,v=e.tickPad,g=e.tickColor,y=e.tickAngle,m=e.labelEnable,x=e.labelPad,b=e.labelColor,_=e.labelAngle,w=this.labelOffset[t],T=this.labelCount[t],k=o.lt(n,l[t]),A=o.le(n,l[t+2]);u[0]=u[1]=0,u[t]=1,c[t]=(s[2+t]+s[t])/(h[2+t]-h[t])-1;var M=2/h[2+(1^t)]-h[1^t];c[1^t]=M*s[1^t]-1,d[t]&&(c[1^t]-=M*p*v[t],k<A&&i[A]>i[k]&&(r.uniforms.dataAxis=u,r.uniforms.screenOffset=c,r.uniforms.color=g[t],r.uniforms.angle=y[t],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),m[t]&&T&&(c[1^t]-=M*p*x[t],r.uniforms.dataAxis=f,r.uniforms.screenOffset=c,r.uniforms.color=b[t],r.uniforms.angle=_[t],a.drawArrays(a.TRIANGLES,w,T)),c[1^t]=M*s[2+(1^t)]-1,d[t+2]&&(c[1^t]+=M*p*v[t+2],k<A&&i[A]>i[k]&&(r.uniforms.dataAxis=u,r.uniforms.screenOffset=c,r.uniforms.color=g[t+2],r.uniforms.angle=y[t+2],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),m[t+2]&&T&&(c[1^t]+=M*p*x[t+2],r.uniforms.dataAxis=f,r.uniforms.screenOffset=c,r.uniforms.color=b[t+2],r.uniforms.angle=_[t+2],a.drawArrays(a.TRIANGLES,w,T))}),v.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,u=r.pixelRatio;if(this.titleCount){for(var c=0;c<2;++c)e[c]=2*(o[c]*u-a[c])/(a[2+c]-a[c])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}}(),v.bind=(h=[0,0],p=[0,0],d=[0,0],function(){var t=this.plot,e=this.shader,r=t._tickBounds,n=t.dataBox,i=t.screenBox,a=t.viewBox;e.bind();for(var o=0;o<2;++o){var s=r[o],l=r[o+2]-s,u=.5*(n[o+2]+n[o]),c=n[o+2]-n[o],f=a[o],v=a[o+2]-f,g=i[o],y=i[o+2]-g;p[o]=2*l/c*v/y,h[o]=2*(s-u)/c*v/y}d[1]=2*t.pixelRatio/(i[3]-i[1]),d[0]=d[1]*(i[3]-i[1])/(i[2]-i[0]),e.uniforms.dataScale=p,e.uniforms.dataShift=h,e.uniforms.textScale=d,this.vbo.bind(),e.attributes.textCoordinate.pointer()}),v.update=function(t){var e,r,n,i,o,s=[],l=t.ticks,u=t.bounds;for(o=0;o<2;++o){var c=[Math.floor(s.length/3)],f=[-1/0],h=l[o];for(e=0;e<h.length;++e){var p=h[e],d=p.x,v=p.text,g=p.font||"sans-serif";i=p.fontSize||12;for(var y=1/(u[o+2]-u[o]),m=u[o],x=v.split("\n"),b=0;b<x.length;b++)for(n=a(g,x[b]).data,r=0;r<n.length;r+=2)s.push(n[r]*i,-n[r+1]*i-b*i*1.2,(d-m)*y);c.push(Math.floor(s.length/3)),f.push(d)}this.tickOffset[o]=c,this.tickX[o]=f}for(o=0;o<2;++o){for(this.labelOffset[o]=Math.floor(s.length/3),n=a(t.labelFont[o],t.labels[o],{textAlign:"center"}).data,i=t.labelSize[o],e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.labelCount[o]=Math.floor(s.length/3)-this.labelOffset[o]}for(this.titleOffset=Math.floor(s.length/3),n=a(t.titleFont,t.title).data,i=t.titleSize,e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.titleCount=Math.floor(s.length/3)-this.titleOffset,this.vbo.update(s)},v.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},2117:function(t,e,r){"use strict";t.exports=function(t){var e=t.gl,r=new l(e,n(e,[e.drawingBufferWidth,e.drawingBufferHeight]));return r.grid=i(r),r.text=a(r),r.line=o(r),r.box=s(r),r.update(t),r};var n=r(2611),i=r(3016),a=r(5613),o=r(1154),s=r(4554);function l(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-1/0,-1/0],this.static=!1,this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}var u=l.prototype;function c(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function f(t,e){return t.x-e.x}u.setDirty=function(){this.dirty=this.pickDirty=!0},u.setOverlayDirty=function(){this.dirty=!0},u.nextDepthValue=function(){return this._depthCounter++/65536},u.draw=function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,i=this.pixelRatio,a=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){if(this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),this.borderColor){t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var u=this.borderColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT)}t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var c=this.backgroundColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT),a.draw();var f=this.zeroLineEnable,h=this.zeroLineColor,p=this.zeroLineWidth;if(f[0]||f[1]){o.bind();for(var d=0;d<2;++d)if(f[d]&&n[d]<=0&&n[d+2]>=0){var v=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(v,e[1],v,e[3],p[d],h[d]):o.drawLine(e[0],v,e[2],v,p[d],h[d])}}for(d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var g=this.borderLineEnable,y=this.borderLineWidth,m=this.borderLineColor;for(g[1]&&o.drawLine(r[0],r[1]-.5*y[1]*i,r[0],r[3]+.5*y[3]*i,y[1],m[1]),g[0]&&o.drawLine(r[0]-.5*y[0]*i,r[1],r[2]+.5*y[2]*i,r[1],y[0],m[0]),g[3]&&o.drawLine(r[2],r[1]-.5*y[1]*i,r[2],r[3]+.5*y[3]*i,y[3],m[3]),g[2]&&o.drawLine(r[0]-.5*y[0]*i,r[3],r[2]+.5*y[2]*i,r[3],y[2],m[2]),s.bind(),d=0;d<2;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();var x=this.overlays;for(d=0;d<x.length;++d)x[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}},u.drawPick=function(){if(!this.static){var t=this.pickBuffer;this.gl,this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}},u.pick=function(t,e){if(!this.static){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),u=this.objects,c=0;c<u.length;++c){var f=u[c].pick(a,o,l);if(f)return f}return null}},u.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},u.setDataBox=function(t){var e=this.dataBox;(e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3])&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},u.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},u.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]),this.screenBox,this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,i=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/i,10,10/i]),this.borderColor=!1!==t.borderColor&&(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=c(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=c(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=c(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!("titleEnable"in t)||!!t.titleEnable,this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=c(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=c(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=c(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var a=t.ticks||[[],[]],o=this._tickBounds;o[0]=o[1]=1/0,o[2]=o[3]=-1/0;for(var s=0;s<2;++s){var l=a[s].slice(0);0!==l.length&&(l.sort(f),o[s]=Math.min(o[s],l[0].x),o[s+2]=Math.max(o[s+2],l[l.length-1].x))}this.grid.update({bounds:o,ticks:a}),this.text.update({bounds:o,ticks:a,labels:t.labels||["x","y"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||["sans-serif","sans-serif"],title:t.title||"",titleSize:t.titleSize||18,titleFont:t.titleFont||"sans-serif"}),this.static=!!t.static,this.setDirty()},u.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();for(this.objects.length=0,t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},u.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},u.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},u.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},u.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},4296:function(t,e,r){"use strict";t.exports=function(t,e){t=t||document.body;var r=[.01,1/0];"distanceLimits"in(e=e||{})&&(r[0]=e.distanceLimits[0],r[1]=e.distanceLimits[1]),"zoomMin"in e&&(r[0]=e.zoomMin),"zoomMax"in e&&(r[1]=e.zoomMax);var u=i({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||"orbit",distanceLimits:r}),c=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],f=0,h=t.clientWidth,p=t.clientHeight,d={keyBindingMode:"rotate",enableWheel:!0,view:u,element:t,delay:e.delay||16,rotateSpeed:e.rotateSpeed||1,zoomSpeed:e.zoomSpeed||1,translateSpeed:e.translateSpeed||1,flipX:!!e.flipX,flipY:!!e.flipY,modes:u.modes,_ortho:e._ortho||e.projection&&"orthographic"===e.projection.type||!1,tick:function(){var e=n(),r=this.delay,i=e-2*r;u.idle(e-r),u.recalcMatrix(i),u.flush(e-(100+2*r));for(var a=!0,o=u.computedMatrix,s=0;s<16;++s)a=a&&c[s]===o[s],c[s]=o[s];var l=t.clientWidth===h&&t.clientHeight===p;return h=t.clientWidth,p=t.clientHeight,a?!l:(f=Math.exp(u.computedRadius[0]),!0)},lookAt:function(t,e,r){u.lookAt(u.lastT(),t,e,r)},rotate:function(t,e,r){u.rotate(u.lastT(),t,e,r)},pan:function(t,e,r){u.pan(u.lastT(),t,e,r)},translate:function(t,e,r){u.translate(u.lastT(),t,e,r)}};return Object.defineProperties(d,{matrix:{get:function(){return u.computedMatrix},set:function(t){return u.setMatrix(u.lastT(),t),u.computedMatrix},enumerable:!0},mode:{get:function(){return u.getMode()},set:function(t){var e=u.computedUp.slice(),r=u.computedEye.slice(),i=u.computedCenter.slice();if(u.setMode(t),"turntable"===t){var a=n();u._active.lookAt(a,r,i,e),u._active.lookAt(a+500,r,i,[0,0,1]),u._active.flush(a)}return u.getMode()},enumerable:!0},center:{get:function(){return u.computedCenter},set:function(t){return u.lookAt(u.lastT(),null,t),u.computedCenter},enumerable:!0},eye:{get:function(){return u.computedEye},set:function(t){return u.lookAt(u.lastT(),t),u.computedEye},enumerable:!0},up:{get:function(){return u.computedUp},set:function(t){return u.lookAt(u.lastT(),null,null,t),u.computedUp},enumerable:!0},distance:{get:function(){return f},set:function(t){return u.setDistance(u.lastT(),t),t},enumerable:!0},distanceLimits:{get:function(){return u.getDistanceLimits(r)},set:function(t){return u.setDistanceLimits(t),t},enumerable:!0}}),t.addEventListener("contextmenu",(function(t){return t.preventDefault(),!1})),d._lastX=-1,d._lastY=-1,d._lastMods={shift:!1,control:!1,alt:!1,meta:!1},d.enableMouseListeners=function(){function e(e,r,i,a){var o=d.keyBindingMode;if(!1!==o){var s="rotate"===o,l="pan"===o,c="zoom"===o,h=!!a.control,p=!!a.alt,v=!!a.shift,g=!!(1&e),y=!!(2&e),m=!!(4&e),x=1/t.clientHeight,b=x*(r-d._lastX),_=x*(i-d._lastY),w=d.flipX?1:-1,T=d.flipY?1:-1,k=Math.PI*d.rotateSpeed,A=n();if(-1!==d._lastX&&-1!==d._lastY&&((s&&g&&!h&&!p&&!v||g&&!h&&!p&&v)&&u.rotate(A,w*k*b,-T*k*_,0),(l&&g&&!h&&!p&&!v||y||g&&h&&!p&&!v)&&u.pan(A,-d.translateSpeed*b*f,d.translateSpeed*_*f,0),c&&g&&!h&&!p&&!v||m||g&&!h&&p&&!v)){var M=-d.zoomSpeed*_/window.innerHeight*(A-u.lastT())*100;u.pan(A,0,0,f*(Math.exp(M)-1))}return d._lastX=r,d._lastY=i,d._lastMods=a,!0}}d.mouseListener=a(t,e),t.addEventListener("touchstart",(function(r){var n=s(r.changedTouches[0],t);e(0,n[0],n[1],d._lastMods),e(1,n[0],n[1],d._lastMods)}),!!l&&{passive:!0}),t.addEventListener("touchmove",(function(r){var n=s(r.changedTouches[0],t);e(1,n[0],n[1],d._lastMods),r.preventDefault()}),!!l&&{passive:!1}),t.addEventListener("touchend",(function(t){e(0,d._lastX,d._lastY,d._lastMods)}),!!l&&{passive:!0}),d.wheelListener=o(t,(function(t,e){if(!1!==d.keyBindingMode&&d.enableWheel){var r=d.flipX?1:-1,i=d.flipY?1:-1,a=n();if(Math.abs(t)>Math.abs(e))u.rotate(a,0,0,-t*r*Math.PI*d.rotateSpeed/window.innerWidth);else if(!d._ortho){var o=-d.zoomSpeed*i*e/window.innerHeight*(a-u.lastT())/20;u.pan(a,0,0,f*(Math.exp(o)-1))}}}),!0)},d.enableMouseListeners(),d};var n=r(8161),i=r(1152),a=r(6145),o=r(6475),s=r(2565),l=r(5233)},8245:function(t,e,r){var n=r(6832),i=r(5158),a=n(["precision mediump float;\n#define GLSLIFY 1\nattribute vec2 position;\nvarying vec2 uv;\nvoid main() {\n  uv = position;\n  gl_Position = vec4(position, 0, 1);\n}"]),o=n(["precision mediump float;\n#define GLSLIFY 1\n\nuniform sampler2D accumBuffer;\nvarying vec2 uv;\n\nvoid main() {\n  vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\n  gl_FragColor = min(vec4(1,1,1,1), accum);\n}"]);t.exports=function(t){return i(t,a,o,null,[{name:"position",type:"vec2"}])}},1059:function(t,e,r){"use strict";var n=r(4296),i=r(7453),a=r(2771),o=r(6496),s=r(2611),l=r(4234),u=r(8126),c=r(6145),f=r(1120),h=r(5268),p=r(8245),d=r(2321)({tablet:!0,featureDetect:!0});function v(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function g(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}return e>0?(r=Math.round(Math.pow(10,e)),Math.ceil(t/r)*r):Math.ceil(t)}function y(t){return"boolean"!=typeof t||t}t.exports={createScene:function(t){(t=t||{}).camera=t.camera||{};var e=t.canvas;e||(e=document.createElement("canvas"),t.container?t.container.appendChild(e):document.body.appendChild(e));var r=t.gl;if(r||(t.glOptions&&(d=!!t.glOptions.preserveDrawingBuffer),r=function(t,e){var r=null;try{(r=t.getContext("webgl",e))||(r=t.getContext("experimental-webgl",e))}catch(t){return null}return r}(e,t.glOptions||{premultipliedAlpha:!0,antialias:!0,preserveDrawingBuffer:d})),!r)throw new Error("webgl not supported");var m=t.bounds||[[-10,-10,-10],[10,10,10]],x=new v,b=l(r,r.drawingBufferWidth,r.drawingBufferHeight,{preferFloat:!d}),_=p(r),w=t.cameraObject&&!0===t.cameraObject._ortho||t.camera.projection&&"orthographic"===t.camera.projection.type||!1,T={eye:t.camera.eye||[2,0,0],center:t.camera.center||[0,0,0],up:t.camera.up||[0,1,0],zoomMin:t.camera.zoomMax||.1,zoomMax:t.camera.zoomMin||100,mode:t.camera.mode||"turntable",_ortho:w},k=t.axes||{},A=i(r,k);A.enable=!k.disable;var M=t.spikes||{},S=o(r,M),E=[],L=[],C=[],P=[],O=!0,I=!0,D={view:null,projection:new Array(16),model:new Array(16),_ortho:!1},z=(I=!0,[r.drawingBufferWidth,r.drawingBufferHeight]),R=t.cameraObject||n(e,T),F={gl:r,contextLost:!1,pixelRatio:t.pixelRatio||1,canvas:e,selection:x,camera:R,axes:A,axesPixels:null,spikes:S,bounds:m,objects:E,shape:z,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:y(t.autoResize),autoBounds:y(t.autoBounds),autoScale:!!t.autoScale,autoCenter:y(t.autoCenter),clipToBounds:y(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:D,oncontextloss:null,mouseListener:null,_stopped:!1,getAspectratio:function(){return{x:this.aspect[0],y:this.aspect[1],z:this.aspect[2]}},setAspectratio:function(t){this.aspect[0]=t.x,this.aspect[1]=t.y,this.aspect[2]=t.z,I=!0},setBounds:function(t,e){this.bounds[0][t]=e.min,this.bounds[1][t]=e.max},setClearColor:function(t){this.clearColor=t},clearRGBA:function(){this.gl.clearColor(this.clearColor[0],this.clearColor[1],this.clearColor[2],this.clearColor[3]),this.gl.clear(this.gl.COLOR_BUFFER_BIT|this.gl.DEPTH_BUFFER_BIT)}},B=[r.drawingBufferWidth/F.pixelRatio|0,r.drawingBufferHeight/F.pixelRatio|0];function N(){if(!F._stopped&&F.autoResize){var t=e.parentNode,r=1,n=1;t&&t!==document.body?(r=t.clientWidth,n=t.clientHeight):(r=window.innerWidth,n=window.innerHeight);var i=0|Math.ceil(r*F.pixelRatio),a=0|Math.ceil(n*F.pixelRatio);if(i!==e.width||a!==e.height){e.width=i,e.height=a;var o=e.style;o.position=o.position||"absolute",o.left="0px",o.top="0px",o.width=r+"px",o.height=n+"px",O=!0}}}function j(){for(var t=E.length,e=P.length,n=0;n<e;++n)C[n]=0;t:for(n=0;n<t;++n){var i=E[n],a=i.pickSlots;if(a){for(var o=0;o<e;++o)if(C[o]+a<255){L[n]=o,i.setPickBase(C[o]+1),C[o]+=a;continue t}var l=s(r,z);L[n]=e,P.push(l),C.push(a),i.setPickBase(1),e+=1}else L[n]=-1}for(;e>0&&0===C[e-1];)C.pop(),P.pop().dispose()}function U(){if(F.contextLost)return!0;r.isContextLost()&&(F.contextLost=!0,F.mouseListener.enabled=!1,F.selection.object=null,F.oncontextloss&&F.oncontextloss())}F.autoResize&&N(),window.addEventListener("resize",N),F.update=function(t){F._stopped||(t=t||{},O=!0,I=!0)},F.add=function(t){F._stopped||(t.axes=A,E.push(t),L.push(-1),O=!0,I=!0,j())},F.remove=function(t){if(!F._stopped){var e=E.indexOf(t);e<0||(E.splice(e,1),L.pop(),O=!0,I=!0,j())}},F.dispose=function(){if(!F._stopped&&(F._stopped=!0,window.removeEventListener("resize",N),e.removeEventListener("webglcontextlost",U),F.mouseListener.enabled=!1,!F.contextLost)){A.dispose(),S.dispose();for(var t=0;t<E.length;++t)E[t].dispose();for(b.dispose(),t=0;t<P.length;++t)P[t].dispose();_.dispose(),r=null,A=null,S=null,E=[]}},F._mouseRotating=!1,F._prevButtons=0,F.enableMouseListeners=function(){F.mouseListener=c(e,(function(t,e,r){if(!F._stopped){var n=P.length,i=E.length,a=x.object;x.distance=1/0,x.mouse[0]=e,x.mouse[1]=r,x.object=null,x.screen=null,x.dataCoordinate=x.dataPosition=null;var o=!1;if(t&&F._prevButtons)F._mouseRotating=!0;else{F._mouseRotating&&(I=!0),F._mouseRotating=!1;for(var s=0;s<n;++s){var l=P[s].query(e,B[1]-r-1,F.pickRadius);if(l){if(l.distance>x.distance)continue;for(var u=0;u<i;++u){var c=E[u];if(L[u]===s){var f=c.pick(l);f&&(x.buttons=t,x.screen=l.coord,x.distance=l.distance,x.object=c,x.index=f.distance,x.dataPosition=f.position,x.dataCoordinate=f.dataCoordinate,x.data=f,o=!0)}}}}}a&&a!==x.object&&(a.highlight&&a.highlight(null),O=!0),x.object&&(x.object.highlight&&x.object.highlight(x.data),O=!0),(o=o||x.object!==a)&&F.onselect&&F.onselect(x),1&t&&!(1&F._prevButtons)&&F.onclick&&F.onclick(x),F._prevButtons=t}}))},e.addEventListener("webglcontextlost",U);var V=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],H=[V[0].slice(),V[1].slice()];function q(){if(!U()){N();var t=F.camera.tick();D.view=F.camera.matrix,O=O||t,I=I||t,A.pixelRatio=F.pixelRatio,S.pixelRatio=F.pixelRatio;var e=E.length,n=V[0],i=V[1];n[0]=n[1]=n[2]=1/0,i[0]=i[1]=i[2]=-1/0;for(var o=0;o<e;++o){(C=E[o]).pixelRatio=F.pixelRatio,C.axes=F.axes,O=O||!!C.dirty,I=I||!!C.dirty;var s=C.bounds;if(s)for(var l=s[0],c=s[1],p=0;p<3;++p)n[p]=Math.min(n[p],l[p]),i[p]=Math.max(i[p],c[p])}var d=F.bounds;if(F.autoBounds)for(p=0;p<3;++p){if(i[p]<n[p])n[p]=-1,i[p]=1;else{n[p]===i[p]&&(n[p]-=1,i[p]+=1);var v=.05*(i[p]-n[p]);n[p]=n[p]-v,i[p]=i[p]+v}d[0][p]=n[p],d[1][p]=i[p]}var y=!1;for(p=0;p<3;++p)y=y||H[0][p]!==d[0][p]||H[1][p]!==d[1][p],H[0][p]=d[0][p],H[1][p]=d[1][p];if(I=I||y,O=O||y){if(y){var m=[0,0,0];for(o=0;o<3;++o)m[o]=g((d[1][o]-d[0][o])/10);A.autoTicks?A.update({bounds:d,tickSpacing:m}):A.update({bounds:d})}var T=r.drawingBufferWidth,k=r.drawingBufferHeight;for(z[0]=T,z[1]=k,B[0]=0|Math.max(T/F.pixelRatio,1),B[1]=0|Math.max(k/F.pixelRatio,1),function(t,e){var r=t.bounds,n=t.cameraParams,i=n.projection,a=n.model,o=t.gl.drawingBufferWidth,s=t.gl.drawingBufferHeight,l=t.zNear,u=t.zFar,c=t.fovy,p=o/s;e?(h(i,-p,p,-1,1,l,u),n._ortho=!0):(f(i,c,p,l,u),n._ortho=!1);for(var d=0;d<16;++d)a[d]=0;a[15]=1;var v=0;for(d=0;d<3;++d)v=Math.max(v,r[1][d]-r[0][d]);for(d=0;d<3;++d)t.autoScale?a[5*d]=t.aspect[d]/(r[1][d]-r[0][d]):a[5*d]=1/v,t.autoCenter&&(a[12+d]=.5*-a[5*d]*(r[0][d]+r[1][d]))}(F,w),o=0;o<e;++o)(C=E[o]).axesBounds=d,F.clipToBounds&&(C.clipBounds=d);x.object&&(F.snapToData?S.position=x.dataCoordinate:S.position=x.dataPosition,S.bounds=d),I&&(I=!1,function(){if(!U()){r.colorMask(!0,!0,!0,!0),r.depthMask(!0),r.disable(r.BLEND),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL);for(var t=E.length,e=P.length,n=0;n<e;++n){var i=P[n];i.shape=B,i.begin();for(var a=0;a<t;++a)if(L[a]===n){var o=E[a];o.drawPick&&(o.pixelRatio=1,o.drawPick(D))}i.end()}}}()),F.axesPixels=a(F.axes,D,T,k),F.onrender&&F.onrender(),r.bindFramebuffer(r.FRAMEBUFFER,null),r.viewport(0,0,T,k),F.clearRGBA(),r.depthMask(!0),r.colorMask(!0,!0,!0,!0),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL),r.disable(r.BLEND),r.disable(r.CULL_FACE);var M=!1;for(A.enable&&(M=M||A.isTransparent(),A.draw(D)),S.axes=A,x.object&&S.draw(D),r.disable(r.CULL_FACE),o=0;o<e;++o)(C=E[o]).axes=A,C.pixelRatio=F.pixelRatio,C.isOpaque&&C.isOpaque()&&C.draw(D),C.isTransparent&&C.isTransparent()&&(M=!0);if(M){for(b.shape=z,b.bind(),r.clear(r.DEPTH_BUFFER_BIT),r.colorMask(!1,!1,!1,!1),r.depthMask(!0),r.depthFunc(r.LESS),A.enable&&A.isTransparent()&&A.drawTransparent(D),o=0;o<e;++o)(C=E[o]).isOpaque&&C.isOpaque()&&C.draw(D);for(r.enable(r.BLEND),r.blendEquation(r.FUNC_ADD),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.colorMask(!0,!0,!0,!0),r.depthMask(!1),r.clearColor(0,0,0,0),r.clear(r.COLOR_BUFFER_BIT),A.isTransparent()&&A.drawTransparent(D),o=0;o<e;++o){var C;(C=E[o]).isTransparent&&C.isTransparent()&&C.drawTransparent(D)}r.bindFramebuffer(r.FRAMEBUFFER,null),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.disable(r.DEPTH_TEST),_.bind(),b.color[0].bind(0),_.uniforms.accumBuffer=0,u(r),r.disable(r.BLEND)}for(O=!1,o=0;o<e;++o)E[o].dirty=!1}}}return F.enableMouseListeners(),function t(){F._stopped||F.contextLost||(q(),requestAnimationFrame(t))}(),F.redraw=function(){F._stopped||(O=!0,q())},F},createCamera:n}},8023:function(t,e,r){var n=r(6832);e.pointVertex=n(["precision mediump float;\n#define GLSLIFY 1\n\nattribute vec2 position;\n\nuniform mat3 matrix;\nuniform float pointSize;\nuniform float pointCloud;\n\nhighp float rand(vec2 co) {\n  highp float a = 12.9898;\n  highp float b = 78.233;\n  highp float c = 43758.5453;\n  highp float d = dot(co.xy, vec2(a, b));\n  highp float e = mod(d, 3.14);\n  return fract(sin(e) * c);\n}\n\nvoid main() {\n  vec3 hgPosition = matrix * vec3(position, 1);\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\n    // if we don't jitter the point size a bit, overall point cloud\n    // saturation 'jumps' on zooming, which is disturbing and confusing\n  gl_PointSize = pointSize * ((19.5 + rand(position)) / 20.0);\n  if(pointCloud != 0.0) { // pointCloud is truthy\n    // get the same square surface as circle would be\n    gl_PointSize *= 0.886;\n  }\n}"]),e.pointFragment=n(["precision mediump float;\n#define GLSLIFY 1\n\nuniform vec4 color, borderColor;\nuniform float centerFraction;\nuniform float pointCloud;\n\nvoid main() {\n  float radius;\n  vec4 baseColor;\n  if(pointCloud != 0.0) { // pointCloud is truthy\n    if(centerFraction == 1.0) {\n      gl_FragColor = color;\n    } else {\n      gl_FragColor = mix(borderColor, color, centerFraction);\n    }\n  } else {\n    radius = length(2.0 * gl_PointCoord.xy - 1.0);\n    if(radius > 1.0) {\n      discard;\n    }\n    baseColor = mix(borderColor, color, step(radius, centerFraction));\n    gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\n  }\n}\n"]),e.pickVertex=n(["precision mediump float;\n#define GLSLIFY 1\n\nattribute vec2 position;\nattribute vec4 pickId;\n\nuniform mat3 matrix;\nuniform float pointSize;\nuniform vec4 pickOffset;\n\nvarying vec4 fragId;\n\nvoid main() {\n  vec3 hgPosition = matrix * vec3(position, 1);\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\n  gl_PointSize = pointSize;\n\n  vec4 id = pickId + pickOffset;\n  id.y += floor(id.x / 256.0);\n  id.x -= floor(id.x / 256.0) * 256.0;\n\n  id.z += floor(id.y / 256.0);\n  id.y -= floor(id.y / 256.0) * 256.0;\n\n  id.w += floor(id.z / 256.0);\n  id.z -= floor(id.z / 256.0) * 256.0;\n\n  fragId = id;\n}\n"]),e.pickFragment=n(["precision mediump float;\n#define GLSLIFY 1\n\nvarying vec4 fragId;\n\nvoid main() {\n  float radius = length(2.0 * gl_PointCoord.xy - 1.0);\n  if(radius > 1.0) {\n    discard;\n  }\n  gl_FragColor = fragId / 255.0;\n}\n"])},8271:function(t,e,r){"use strict";var n=r(5158),i=r(5827),a=r(5306),o=r(8023);function s(t,e,r,n,i){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=i,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}t.exports=function(t,e){var r=t.gl,a=new s(t,i(r),i(r),n(r,o.pointVertex,o.pointFragment),n(r,o.pickVertex,o.pickFragment));return a.update(e),t.addObject(a),a};var l,u,c=s.prototype;c.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},c.update=function(t){var e;function r(e,r){return e in t?t[e]:r}t=t||{},this.sizeMin=r("sizeMin",.5),this.sizeMax=r("sizeMax",20),this.color=r("color",[1,0,0,1]).slice(),this.areaRatio=r("areaRatio",1),this.borderColor=r("borderColor",[0,0,0,1]).slice(),this.blend=r("blend",!1);var n=t.positions.length>>>1,i=t.positions instanceof Float32Array,o=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,s=t.positions,l=i?s:a.mallocFloat32(s.length),u=o?t.idToIndex:a.mallocInt32(n);if(i||l.set(s),!o)for(l.set(s),e=0;e<n;e++)u[e]=e;this.points=s,this.offsetBuffer.update(l),this.pickBuffer.update(u),i||a.free(l),o||a.free(u),this.pointCount=n,this.pickOffset=0},c.unifiedDraw=(l=[1,0,0,0,1,0,0,0,1],u=[0,0,0,0],function(t){var e=void 0!==t,r=e?this.pickShader:this.shader,n=this.plot.gl,i=this.plot.dataBox;if(0===this.pointCount)return t;var a=i[2]-i[0],o=i[3]-i[1],s=function(t,e){var r,n=0,i=t.length>>>1;for(r=0;r<i;r++){var a=t[2*r],o=t[2*r+1];a>=e[0]&&a<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}(this.points,i),c=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(s,.33333)));l[0]=2/a,l[4]=2/o,l[6]=-2*i[0]/a-1,l[7]=-2*i[1]/o-1,this.offsetBuffer.bind(),r.bind(),r.attributes.position.pointer(),r.uniforms.matrix=l,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointCloud=c<5,r.uniforms.pointSize=c,r.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),e&&(u[0]=255&t,u[1]=t>>8&255,u[2]=t>>16&255,u[3]=t>>24&255,this.pickBuffer.bind(),r.attributes.pickId.pointer(n.UNSIGNED_BYTE),r.uniforms.pickOffset=u,this.pickOffset=t);var f=n.getParameter(n.BLEND),h=n.getParameter(n.DITHER);return f&&!this.blend&&n.disable(n.BLEND),h&&n.disable(n.DITHER),n.drawArrays(n.POINTS,0,this.pointCount),f&&!this.blend&&n.enable(n.BLEND),h&&n.enable(n.DITHER),t+this.pointCount}),c.draw=c.unifiedDraw,c.drawPick=c.unifiedDraw,c.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(r<n||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},6093:function(t){t.exports=function(t,e,r,n){var i,a,o,s,l,u=e[0],c=e[1],f=e[2],h=e[3],p=r[0],d=r[1],v=r[2],g=r[3];return(a=u*p+c*d+f*v+h*g)<0&&(a=-a,p=-p,d=-d,v=-v,g=-g),1-a>1e-6?(i=Math.acos(a),o=Math.sin(i),s=Math.sin((1-n)*i)/o,l=Math.sin(n*i)/o):(s=1-n,l=n),t[0]=s*u+l*p,t[1]=s*c+l*d,t[2]=s*f+l*v,t[3]=s*h+l*g,t}},8240:function(t){"use strict";t.exports=function(t){return t||0===t?t.toString():""}},4123:function(t,e,r){"use strict";var n=r(875);t.exports=function(t,e,r){var a=i[e];if(a||(a=i[e]={}),t in a)return a[t];var o={textAlign:"center",textBaseline:"middle",lineHeight:1,font:e,lineSpacing:1.25,styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},triangles:!0},s=n(t,o);o.triangles=!1;var l,u,c=n(t,o);if(r&&1!==r){for(l=0;l<s.positions.length;++l)for(u=0;u<s.positions[l].length;++u)s.positions[l][u]/=r;for(l=0;l<c.positions.length;++l)for(u=0;u<c.positions[l].length;++u)c.positions[l][u]/=r}var f=[[1/0,1/0],[-1/0,-1/0]],h=c.positions.length;for(l=0;l<h;++l){var p=c.positions[l];for(u=0;u<2;++u)f[0][u]=Math.min(f[0][u],p[u]),f[1][u]=Math.max(f[1][u],p[u])}return a[t]=[s,c,f]};var i={}},9282:function(t,e,r){var n=r(5158),i=r(6832),a=i(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nattribute vec3 position;\nattribute vec4 color;\nattribute vec2 glyph;\nattribute vec4 id;\n\nuniform vec4 highlightId;\nuniform float highlightScale;\nuniform mat4 model, view, projection;\nuniform vec3 clipBounds[2];\n\nvarying vec4 interpColor;\nvarying vec4 pickId;\nvarying vec3 dataCoordinate;\n\nvoid main() {\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\n\n    gl_Position = vec4(0,0,0,0);\n  } else {\n    float scale = 1.0;\n    if(distance(highlightId, id) < 0.0001) {\n      scale = highlightScale;\n    }\n\n    vec4 worldPosition = model * vec4(position, 1);\n    vec4 viewPosition = view * worldPosition;\n    viewPosition = viewPosition / viewPosition.w;\n    vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\n\n    gl_Position = clipPosition;\n    interpColor = color;\n    pickId = id;\n    dataCoordinate = position;\n  }\n}"]),o=i(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nattribute vec3 position;\nattribute vec4 color;\nattribute vec2 glyph;\nattribute vec4 id;\n\nuniform mat4 model, view, projection;\nuniform vec2 screenSize;\nuniform vec3 clipBounds[2];\nuniform float highlightScale, pixelRatio;\nuniform vec4 highlightId;\n\nvarying vec4 interpColor;\nvarying vec4 pickId;\nvarying vec3 dataCoordinate;\n\nvoid main() {\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\n\n    gl_Position = vec4(0,0,0,0);\n  } else {\n    float scale = pixelRatio;\n    if(distance(highlightId.bgr, id.bgr) < 0.001) {\n      scale *= highlightScale;\n    }\n\n    vec4 worldPosition = model * vec4(position, 1.0);\n    vec4 viewPosition = view * worldPosition;\n    vec4 clipPosition = projection * viewPosition;\n    clipPosition /= clipPosition.w;\n\n    gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\n    interpColor = color;\n    pickId = id;\n    dataCoordinate = position;\n  }\n}"]),s=i(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nattribute vec3 position;\nattribute vec4 color;\nattribute vec2 glyph;\nattribute vec4 id;\n\nuniform float highlightScale;\nuniform vec4 highlightId;\nuniform vec3 axes[2];\nuniform mat4 model, view, projection;\nuniform vec2 screenSize;\nuniform vec3 clipBounds[2];\nuniform float scale, pixelRatio;\n\nvarying vec4 interpColor;\nvarying vec4 pickId;\nvarying vec3 dataCoordinate;\n\nvoid main() {\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\n\n    gl_Position = vec4(0,0,0,0);\n  } else {\n    float lscale = pixelRatio * scale;\n    if(distance(highlightId, id) < 0.0001) {\n      lscale *= highlightScale;\n    }\n\n    vec4 clipCenter   = projection * view * model * vec4(position, 1);\n    vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\n    vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\n\n    gl_Position = clipPosition;\n    interpColor = color;\n    pickId = id;\n    dataCoordinate = dataPosition;\n  }\n}\n"]),l=i(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 fragClipBounds[2];\nuniform float opacity;\n\nvarying vec4 interpColor;\nvarying vec3 dataCoordinate;\n\nvoid main() {\n  if (\n    outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) ||\n    interpColor.a * opacity == 0.\n  ) discard;\n  gl_FragColor = interpColor * opacity;\n}\n"]),u=i(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 fragClipBounds[2];\nuniform float pickGroup;\n\nvarying vec4 pickId;\nvarying vec3 dataCoordinate;\n\nvoid main() {\n  if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard;\n\n  gl_FragColor = vec4(pickGroup, pickId.bgr);\n}"]),c=[{name:"position",type:"vec3"},{name:"color",type:"vec4"},{name:"glyph",type:"vec2"},{name:"id",type:"vec4"}],f={vertex:a,fragment:l,attributes:c},h={vertex:o,fragment:l,attributes:c},p={vertex:s,fragment:l,attributes:c},d={vertex:a,fragment:u,attributes:c},v={vertex:o,fragment:u,attributes:c},g={vertex:s,fragment:u,attributes:c};function y(t,e){var r=n(t,e),i=r.attributes;return i.position.location=0,i.color.location=1,i.glyph.location=2,i.id.location=3,r}e.createPerspective=function(t){return y(t,f)},e.createOrtho=function(t){return y(t,h)},e.createProject=function(t){return y(t,p)},e.createPickPerspective=function(t){return y(t,d)},e.createPickOrtho=function(t){return y(t,v)},e.createPickProject=function(t){return y(t,g)}},2182:function(t,e,r){"use strict";var n=r(3596),i=r(5827),a=r(2944),o=r(5306),s=r(104),l=r(9282),u=r(4123),c=r(8240),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function p(t,e,r,n){return h(n,n),h(n,n),h(n,n)}function d(t,e){this.index=t,this.dataCoordinate=this.position=e}function v(t){return!0===t||t>1?1:t}function g(t,e,r,n,i,a,o,s,l,u,c,f){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=a,this.glyphBuffer=o,this.idBuffer=s,this.vao=l,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.hasAlpha=!1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.projectHasAlpha=!1,this.pickId=0,this.pickPerspectiveShader=u,this.pickOrthoShader=c,this.pickProjectShader=f,this.points=[],this._selectResult=new d(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.dirty=!0}t.exports=function(t){var e=t.gl,r=l.createPerspective(e),n=l.createOrtho(e),o=l.createProject(e),s=l.createPickPerspective(e),u=l.createPickOrtho(e),c=l.createPickProject(e),f=i(e),h=i(e),p=i(e),d=i(e),v=new g(e,r,n,o,f,h,p,d,a(e,[{buffer:f,size:3,type:e.FLOAT},{buffer:h,size:4,type:e.FLOAT},{buffer:p,size:2,type:e.FLOAT},{buffer:d,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),s,u,c);return v.update(t),v};var y=g.prototype;y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.isTransparent=function(){if(this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectHasAlpha)return!0;return!1},y.isOpaque=function(){if(!this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&!this.projectHasAlpha)return!0;return!1};var m=[0,0],x=[0,0,0],b=[0,0,0],_=[0,0,0,1],w=[0,0,0,1],T=f.slice(),k=[0,0,0],A=[[0,0,0],[0,0,0]];function M(t){return t[0]=t[1]=t[2]=0,t}function S(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function E(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}var L=[[-1e8,-1e8,-1e8],[1e8,1e8,1e8]];function C(t,e,r,n,i,a,o){var l=r.gl;if((a===r.projectHasAlpha||o)&&function(t,e,r,n){var i,a=e.axesProject,o=e.gl,l=t.uniforms,u=r.model||f,c=r.view||f,h=r.projection||f,d=e.axesBounds,v=function(t){for(var e=A,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}(e.clipBounds);i=e.axes&&e.axes.lastCubeProps?e.axes.lastCubeProps.axis:[1,1,1],m[0]=2/o.drawingBufferWidth,m[1]=2/o.drawingBufferHeight,t.bind(),l.view=c,l.projection=h,l.screenSize=m,l.highlightId=e.highlightId,l.highlightScale=e.highlightScale,l.clipBounds=v,l.pickGroup=e.pickId/255,l.pixelRatio=n;for(var g=0;g<3;++g)if(a[g]){l.scale=e.projectScale[g],l.opacity=e.projectOpacity[g];for(var y=T,L=0;L<16;++L)y[L]=0;for(L=0;L<4;++L)y[5*L]=1;y[5*g]=0,i[g]<0?y[12+g]=d[0][g]:y[12+g]=d[1][g],s(y,u,y),l.model=y;var C=(g+1)%3,P=(g+2)%3,O=M(x),I=M(b);O[C]=1,I[P]=1;var D=p(0,0,0,S(_,O)),z=p(0,0,0,S(w,I));if(Math.abs(D[1])>Math.abs(z[1])){var R=D;D=z,z=R,R=O,O=I,I=R;var F=C;C=P,P=F}D[0]<0&&(O[C]=-1),z[1]>0&&(I[P]=-1);var B=0,N=0;for(L=0;L<4;++L)B+=Math.pow(u[4*C+L],2),N+=Math.pow(u[4*P+L],2);O[C]/=Math.sqrt(B),I[P]/=Math.sqrt(N),l.axes[0]=O,l.axes[1]=I,l.fragClipBounds[0]=E(k,v[0],g,-1e8),l.fragClipBounds[1]=E(k,v[1],g,1e8),e.vao.bind(),e.vao.draw(o.TRIANGLES,e.vertexCount),e.lineWidth>0&&(o.lineWidth(e.lineWidth*n),e.vao.draw(o.LINES,e.lineVertexCount,e.vertexCount)),e.vao.unbind()}}(e,r,n,i),a===r.hasAlpha||o){t.bind();var u=t.uniforms;u.model=n.model||f,u.view=n.view||f,u.projection=n.projection||f,m[0]=2/l.drawingBufferWidth,m[1]=2/l.drawingBufferHeight,u.screenSize=m,u.highlightId=r.highlightId,u.highlightScale=r.highlightScale,u.fragClipBounds=L,u.clipBounds=r.axes.bounds,u.opacity=r.opacity,u.pickGroup=r.pickId/255,u.pixelRatio=i,r.vao.bind(),r.vao.draw(l.TRIANGLES,r.vertexCount),r.lineWidth>0&&(l.lineWidth(r.lineWidth*i),r.vao.draw(l.LINES,r.lineVertexCount,r.vertexCount)),r.vao.unbind()}}function P(t,e,r,i){var a;a=Array.isArray(t)?e<t.length?t[e]:void 0:t,a=c(a);var o=!0;n(a)&&(a="▼",o=!1);var s=u(a,r,i);return{mesh:s[0],lines:s[1],bounds:s[2],visible:o}}y.draw=function(t){C(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!1,!1)},y.drawTransparent=function(t){C(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!0,!1)},y.drawPick=function(t){C(this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader,this.pickProjectShader,this,t,1,!0,!0)},y.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||e<0)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;i<3;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},y.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},y.update=function(t){if("perspective"in(t=t||{})&&(this.useOrtho=!t.perspective),"orthographic"in t&&(this.useOrtho=!!t.orthographic),"lineWidth"in t&&(this.lineWidth=t.lineWidth),"project"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if("projectScale"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(this.projectHasAlpha=!1,"projectOpacity"in t){Array.isArray(t.projectOpacity)?this.projectOpacity=t.projectOpacity.slice():(r=+t.projectOpacity,this.projectOpacity=[r,r,r]);for(var n=0;n<3;++n)this.projectOpacity[n]=v(this.projectOpacity[n]),this.projectOpacity[n]<1&&(this.projectHasAlpha=!0)}this.hasAlpha=!1,"opacity"in t&&(this.opacity=v(t.opacity),this.opacity<1&&(this.hasAlpha=!0)),this.dirty=!0;var i,a,s=t.position,l=t.font||"normal",u=t.alignment||[0,0];if(2===u.length)i=u[0],a=u[1];else for(i=[],a=[],n=0;n<u.length;++n)i[n]=u[n][0],a[n]=u[n][1];var c=[1/0,1/0,1/0],f=[-1/0,-1/0,-1/0],h=t.glyph,p=t.color,d=t.size,g=t.angle,y=t.lineColor,m=-1,x=0,b=0,_=0;if(s.length){_=s.length;t:for(n=0;n<_;++n){for(var w=s[n],T=0;T<3;++T)if(isNaN(w[T])||!isFinite(w[T]))continue t;var k=(N=P(h,n,l,this.pixelRatio)).mesh,A=N.lines,M=N.bounds;x+=3*k.cells.length,b+=2*A.edges.length}}var S=x+b,E=o.mallocFloat(3*S),L=o.mallocFloat(4*S),C=o.mallocFloat(2*S),O=o.mallocUint32(S);if(S>0){var I=0,D=x,z=[0,0,0,1],R=[0,0,0,1],F=Array.isArray(p)&&Array.isArray(p[0]),B=Array.isArray(y)&&Array.isArray(y[0]);t:for(n=0;n<_;++n){for(m+=1,w=s[n],T=0;T<3;++T){if(isNaN(w[T])||!isFinite(w[T]))continue t;f[T]=Math.max(f[T],w[T]),c[T]=Math.min(c[T],w[T])}k=(N=P(h,n,l,this.pixelRatio)).mesh,A=N.lines,M=N.bounds;var N,j=N.visible;if(j)if(Array.isArray(p)){if(3===(U=F?n<p.length?p[n]:[0,0,0,0]:p).length){for(T=0;T<3;++T)z[T]=U[T];z[3]=1}else if(4===U.length){for(T=0;T<4;++T)z[T]=U[T];!this.hasAlpha&&U[3]<1&&(this.hasAlpha=!0)}}else z[0]=z[1]=z[2]=0,z[3]=1;else 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tt=J[K[$]];C[2*I]=V*(q*tt[0]-G*tt[1]+W[0]),C[2*I+1]=V*(G*tt[0]+q*tt[1]+W[1]),I+=1}for(X=A.edges,J=A.positions,T=0;T<X.length;++T)for(K=X[T],$=0;$<2;++$){for(Q=0;Q<3;++Q)E[3*D+Q]=w[Q];for(Q=0;Q<4;++Q)L[4*D+Q]=R[Q];O[D]=m,tt=J[K[$]],C[2*D]=V*(q*tt[0]-G*tt[1]+W[0]),C[2*D+1]=V*(G*tt[0]+q*tt[1]+W[1]),D+=1}}}this.bounds=[c,f],this.points=s,this.pointCount=s.length,this.vertexCount=x,this.lineVertexCount=b,this.pointBuffer.update(E),this.colorBuffer.update(L),this.glyphBuffer.update(C),this.idBuffer.update(O),o.free(E),o.free(L),o.free(C),o.free(O)},y.dispose=function(){this.shader.dispose(),this.orthoShader.dispose(),this.pickPerspectiveShader.dispose(),this.pickOrthoShader.dispose(),this.vao.dispose(),this.pointBuffer.dispose(),this.colorBuffer.dispose(),this.glyphBuffer.dispose(),this.idBuffer.dispose()}},1884:function(t,e,r){"use strict";var n=r(6832);e.boxVertex=n(["precision mediump float;\n#define GLSLIFY 1\n\nattribute vec2 vertex;\n\nuniform vec2 cornerA, cornerB;\n\nvoid main() {\n  gl_Position = vec4(mix(cornerA, cornerB, vertex), 0, 1);\n}\n"]),e.boxFragment=n(["precision mediump float;\n#define GLSLIFY 1\n\nuniform vec4 color;\n\nvoid main() {\n  gl_FragColor = color;\n}\n"])},6623:function(t,e,r){"use strict";var n=r(5158),i=r(5827),a=r(1884);function o(t,e,r){this.plot=t,this.boxBuffer=e,this.boxShader=r,this.enabled=!0,this.selectBox=[1/0,1/0,-1/0,-1/0],this.borderColor=[0,0,0,1],this.innerFill=!1,this.innerColor=[0,0,0,.25],this.outerFill=!0,this.outerColor=[0,0,0,.5],this.borderWidth=10}t.exports=function(t,e){var r=t.gl,s=new o(t,i(r,[0,0,0,1,1,0,1,1]),n(r,a.boxVertex,a.boxFragment));return s.update(e),t.addOverlay(s),s};var s=o.prototype;s.draw=function(){if(this.enabled){var t=this.plot,e=this.selectBox,r=this.borderWidth,n=(this.innerFill,this.innerColor),i=(this.outerFill,this.outerColor),a=this.borderColor,o=t.box,s=t.screenBox,l=t.dataBox,u=t.viewBox,c=t.pixelRatio,f=(e[0]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],h=(e[1]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1],p=(e[2]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],d=(e[3]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1];if(f=Math.max(f,u[0]),h=Math.max(h,u[1]),p=Math.min(p,u[2]),d=Math.min(d,u[3]),!(p<f||d<h)){o.bind();var v=s[2]-s[0],g=s[3]-s[1];if(this.outerFill&&(o.drawBox(0,0,v,h,i),o.drawBox(0,h,f,d,i),o.drawBox(0,d,v,g,i),o.drawBox(p,h,v,d,i)),this.innerFill&&o.drawBox(f,h,p,d,n),r>0){var y=r*c;o.drawBox(f-y,h-y,p+y,h+y,a),o.drawBox(f-y,d-y,p+y,d+y,a),o.drawBox(f-y,h-y,f+y,d+y,a),o.drawBox(p-y,h-y,p+y,d+y,a)}}}},s.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},s.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},2611:function(t,e,r){"use strict";t.exports=function(t,e){var r=e[0],a=e[1];return new l(t,n(t,r,a,{}),i.mallocUint8(r*a*4))};var n=r(4234),i=r(5306),a=r(5050),o=r(2288).nextPow2;function s(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function l(t,e,r){this.gl=t,this.fbo=e,this.buffer=r,this._readTimeout=null;var 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i=0|Math.min(Math.max(t-r,0),n[0]),o=0|Math.min(Math.max(t+r,0),n[0]),l=0|Math.min(Math.max(e-r,0),n[1]),u=0|Math.min(Math.max(e+r,0),n[1]);if(o<=i||u<=l)return null;var c=[o-i,u-l],f=a(this.buffer,[c[0],c[1],4],[4,4*n[0],1],4*(i+n[0]*l)),h=function(t,e,r){for(var n=1e8,i=-1,a=-1,o=t.shape[0],s=t.shape[1],l=0;l<o;l++)for(var u=0;u<s;u++){var c=t.get(l,u,0),f=t.get(l,u,1),h=t.get(l,u,2),p=t.get(l,u,3);if(c<255||f<255||h<255||p<255){var d=e-l,v=r-u,g=d*d+v*v;g<n&&(n=g,i=l,a=u)}}return[i,a,n]}(f.hi(c[0],c[1],1),r,r),p=h[0],d=h[1];return p<0||Math.pow(this.radius,2)<h[2]?null:new s(p+i|0,d+l|0,f.get(p,d,0),[f.get(p,d,1),f.get(p,d,2),f.get(p,d,3)],Math.sqrt(h[2]))},u.dispose=function(){this.gl&&(this.fbo.dispose(),i.free(this.buffer),this.gl=null,this._readTimeout&&clearTimeout(this._readTimeout))}},5158:function(t,e,r){"use strict";var n=r(9016),i=r(4280),a=r(3984),o=r(1628),s=r(2631),l=r(9068);function 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with\n  // model & view changes.\n  vec3 normal;\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\n\n  //Lighting geometry parameters\n  vec4 cameraCoordinate = view * tubePosition;\n  cameraCoordinate.xyz /= cameraCoordinate.w;\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\n\n  // vec4 m_position  = model * vec4(tubePosition, 1.0);\n  vec4 t_position  = view * tubePosition;\n  gl_Position      = projection * t_position;\n\n  f_color          = color;\n  f_data           = tubePosition.xyz;\n  f_position       = position.xyz;\n  f_uv             = uv;\n}\n"]),a=n(["#extension GL_OES_standard_derivatives : enable\n\nprecision highp float;\n#define GLSLIFY 1\n\nfloat beckmannDistribution(float x, float roughness) {\n  float NdotH = max(x, 0.0001);\n  float cos2Alpha = NdotH * NdotH;\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\n  float roughness2 = roughness * roughness;\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\n  return exp(tan2Alpha / roughness2) / denom;\n}\n\nfloat cookTorranceSpecular(\n  vec3 lightDirection,\n  vec3 viewDirection,\n  vec3 surfaceNormal,\n  float roughness,\n  float fresnel) {\n\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\n\n  //Half angle vector\n  vec3 H = normalize(lightDirection + viewDirection);\n\n  //Geometric term\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\n  float VdotH = max(dot(viewDirection, H), 0.000001);\n  float LdotH = max(dot(lightDirection, H), 0.000001);\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\n  float G = min(1.0, min(G1, G2));\n  \n  //Distribution term\n  float D = beckmannDistribution(NdotH, roughness);\n\n  //Fresnel term\n  float F = pow(1.0 - VdotN, fresnel);\n\n  //Multiply terms and done\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\n}\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\nuniform sampler2D texture;\n\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvoid main() {\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\n  vec3 N = normalize(f_normal);\n  vec3 L = normalize(f_lightDirection);\n  vec3 V = normalize(f_eyeDirection);\n\n  if(gl_FrontFacing) {\n    N = -N;\n  }\n\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\n\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\n\n  gl_FragColor = litColor * opacity;\n}\n"]),o=n(["precision highp float;\n\nprecision highp float;\n#define GLSLIFY 1\n\nvec3 getOrthogonalVector(vec3 v) {\n  // Return up-vector for only-z vector.\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\n  // Assign z = 0, x = -b, y = a:\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\n    return normalize(vec3(-v.y, v.x, 0.0));\n  } else {\n    return normalize(vec3(0.0, v.z, -v.y));\n  }\n}\n\n// Calculate the tube vertex and normal at the given index.\n//\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\n//\n// Each tube segment is made up of a ring of vertices.\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\n// The indexes of tube segments run from 0 to 8.\n//\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\n  float segmentCount = 8.0;\n\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\n\n  vec3 u = getOrthogonalVector(d);\n  vec3 v = normalize(cross(u, d));\n\n  vec3 x = u * cos(angle) * length(d);\n  vec3 y = v * sin(angle) * length(d);\n  vec3 v3 = x + y;\n\n  normal = normalize(v3);\n\n  return v3;\n}\n\nattribute vec4 vector;\nattribute vec4 position;\nattribute vec4 id;\n\nuniform mat4 model, view, projection;\nuniform float tubeScale;\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() {\n  vec3 normal;\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\n\n  gl_Position = projection * view * tubePosition;\n  f_id        = id;\n  f_position  = position.xyz;\n}\n"]),s=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3  clipBounds[2];\nuniform float pickId;\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() {\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\n\n  gl_FragColor = vec4(pickId, f_id.xyz);\n}"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:"position",type:"vec4"},{name:"color",type:"vec4"},{name:"uv",type:"vec2"},{name:"vector",type:"vec4"}]},e.pickShader={vertex:o,fragment:s,attributes:[{name:"position",type:"vec4"},{name:"id",type:"vec4"},{name:"vector",type:"vec4"}]}},7307:function(t,e,r){"use strict";var n=r(2858),i=r(4020),a=["xyz","xzy","yxz","yzx","zxy","zyx"],o=function(t,e){var r,n=t.length;for(r=0;r<n;r++){var i=t[r];if(i===e)return r;if(i>e)return r-1}return r},s=function(t,e,r){return t<e?e:t>r?r:t},l=function(t){var e=1/0;t.sort((function(t,e){return t-e}));for(var r=t.length,n=1;n<r;n++){var i=Math.abs(t[n]-t[n-1]);i<e&&(e=i)}return e};t.exports=function(t,e){var r=t.startingPositions,u=t.maxLength||1e3,c=t.tubeSize||1,f=t.absoluteTubeSize,h=t.gridFill||"+x+y+z",p={};-1!==h.indexOf("-x")&&(p.reversedX=!0),-1!==h.indexOf("-y")&&(p.reversedY=!0),-1!==h.indexOf("-z")&&(p.reversedZ=!0),p.filled=a.indexOf(h.replace(/-/g,"").replace(/\+/g,""));var d=t.getVelocity||function(e){return function(t,e,r){var i=e.vectors,a=e.meshgrid,l=t[0],u=t[1],c=t[2],f=a[0].length,h=a[1].length,p=a[2].length,d=o(a[0],l),v=o(a[1],u),g=o(a[2],c),y=d+1,m=v+1,x=g+1;if(d=s(d,0,f-1),y=s(y,0,f-1),v=s(v,0,h-1),m=s(m,0,h-1),g=s(g,0,p-1),x=s(x,0,p-1),d<0||v<0||g<0||y>f-1||m>h-1||x>p-1)return n.create();var b,_,w,T,k,A,M=a[0][d],S=a[0][y],E=a[1][v],L=a[1][m],C=a[2][g],P=(l-M)/(S-M),O=(u-E)/(L-E),I=(c-C)/(a[2][x]-C);switch(isFinite(P)||(P=.5),isFinite(O)||(O=.5),isFinite(I)||(I=.5),r.reversedX&&(d=f-1-d,y=f-1-y),r.reversedY&&(v=h-1-v,m=h-1-m),r.reversedZ&&(g=p-1-g,x=p-1-x),r.filled){case 5:k=g,A=x,w=v*p,T=m*p,b=d*p*h,_=y*p*h;break;case 4:k=g,A=x,b=d*p,_=y*p,w=v*p*f,T=m*p*f;break;case 3:w=v,T=m,k=g*h,A=x*h,b=d*h*p,_=y*h*p;break;case 2:w=v,T=m,b=d*h,_=y*h,k=g*h*f,A=x*h*f;break;case 1:b=d,_=y,k=g*f,A=x*f,w=v*f*p,T=m*f*p;break;default:b=d,_=y,w=v*f,T=m*f,k=g*f*h,A=x*f*h}var D=i[b+w+k],z=i[b+w+A],R=i[b+T+k],F=i[b+T+A],B=i[_+w+k],N=i[_+w+A],j=i[_+T+k],U=i[_+T+A],V=n.create(),H=n.create(),q=n.create(),G=n.create();n.lerp(V,D,B,P),n.lerp(H,z,N,P),n.lerp(q,R,j,P),n.lerp(G,F,U,P);var Z=n.create(),Y=n.create();n.lerp(Z,V,q,O),n.lerp(Y,H,G,O);var W=n.create();return n.lerp(W,Z,Y,I),W}(e,t,p)},v=t.getDivergence||function(t,e){var r=n.create(),i=1e-4;n.add(r,t,[i,0,0]);var a=d(r);n.subtract(a,a,e),n.scale(a,a,1/i),n.add(r,t,[0,i,0]);var o=d(r);n.subtract(o,o,e),n.scale(o,o,1/i),n.add(r,t,[0,0,i]);var s=d(r);return n.subtract(s,s,e),n.scale(s,s,1/i),n.add(r,a,o),n.add(r,r,s),r},g=[],y=e[0][0],m=e[0][1],x=e[0][2],b=e[1][0],_=e[1][1],w=e[1][2],T=function(t){var e=t[0],r=t[1],n=t[2];return!(e<y||e>b||r<m||r>_||n<x||n>w)},k=10*n.distance(e[0],e[1])/u,A=k*k,M=1,S=0,E=r.length;E>1&&(M=function(t){for(var e=[],r=[],n=[],i={},a={},o={},s=t.length,u=0;u<s;u++){var c=t[u],f=c[0],h=c[1],p=c[2];i[f]||(e.push(f),i[f]=!0),a[h]||(r.push(h),a[h]=!0),o[p]||(n.push(p),o[p]=!0)}var d=l(e),v=l(r),g=l(n),y=Math.min(d,v,g);return isFinite(y)?y:1}(r));for(var L=0;L<E;L++){var C=n.create();n.copy(C,r[L]);var P=[C],O=[],I=d(C),D=C;O.push(I);var z=[],R=v(C,I),F=n.length(R);isFinite(F)&&F>S&&(S=F),z.push(F),g.push({points:P,velocities:O,divergences:z});for(var B=0;B<100*u&&P.length<u&&T(C);){B++;var N=n.clone(I),j=n.squaredLength(N);if(0===j)break;j>A&&n.scale(N,N,k/Math.sqrt(j)),n.add(N,N,C),I=d(N),n.squaredDistance(D,N)-A>-1e-4*A&&(P.push(N),D=N,O.push(I),R=v(N,I),F=n.length(R),isFinite(F)&&F>S&&(S=F),z.push(F)),C=N}}var U=function(t,e,r,a){for(var o=0,s=0;s<t.length;s++)for(var l=t[s].velocities,u=0;u<l.length;u++)o=Math.max(o,n.length(l[u]));var c=t.map((function(t){return function(t,e,r,a){for(var o=t.points,s=t.velocities,l=t.divergences,u=[],c=[],f=[],h=[],p=[],d=[],v=0,g=0,y=i.create(),m=i.create(),x=0;x<o.length;x++){var b=o[x],_=s[x],w=l[x];0===e&&(w=.05*r),g=n.length(_)/a,y=i.create(),n.copy(y,_),y[3]=w;for(var T=0;T<8;T++)p[T]=[b[0],b[1],b[2],T];if(h.length>0)for(T=0;T<8;T++){var k=(T+1)%8;u.push(h[T],p[T],p[k],p[k],h[k],h[T]),f.push(m,y,y,y,m,m),d.push(v,g,g,g,v,v);var A=u.length;c.push([A-6,A-5,A-4],[A-3,A-2,A-1])}var M=h;h=p,p=M;var S=m;m=y,y=S;var E=v;v=g,g=E}return{positions:u,cells:c,vectors:f,vertexIntensity:d}}(t,r,a,o)})),f=[],h=[],p=[],d=[];for(s=0;s<c.length;s++){var v=c[s],g=f.length;for(f=f.concat(v.positions),p=p.concat(v.vectors),d=d.concat(v.vertexIntensity),u=0;u<v.cells.length;u++){var y=v.cells[u],m=[];h.push(m);for(var x=0;x<y.length;x++)m.push(y[x]+g)}}return{positions:f,cells:h,vectors:p,vertexIntensity:d,colormap:e}}(g,t.colormap,S,M);return f?U.tubeScale=f:(0===S&&(S=1),U.tubeScale=.5*c*M/S),U};var u=r(9578),c=r(1140).createMesh;t.exports.createTubeMesh=function(t,e){return c(t,e,{shaders:u,traceType:"streamtube"})}},9054:function(t,e,r){var n=r(5158),i=r(6832),a=i(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec4 uv;\nattribute vec3 f;\nattribute vec3 normal;\n\nuniform vec3 objectOffset;\nuniform mat4 model, view, projection, inverseModel;\nuniform vec3 lightPosition, eyePosition;\nuniform sampler2D colormap;\n\nvarying float value, kill;\nvarying vec3 worldCoordinate;\nvarying vec2 planeCoordinate;\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\nvarying vec4 vColor;\n\nvoid main() {\n  vec3 localCoordinate = vec3(uv.zw, f.x);\n  worldCoordinate = objectOffset + localCoordinate;\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\n  vec4 clipPosition = projection * view * worldPosition;\n  gl_Position = clipPosition;\n  kill = f.y;\n  value = f.z;\n  planeCoordinate = uv.xy;\n\n  vColor = texture2D(colormap, vec2(value, value));\n\n  //Lighting geometry parameters\n  vec4 cameraCoordinate = view * worldPosition;\n  cameraCoordinate.xyz /= cameraCoordinate.w;\n  lightDirection = lightPosition - cameraCoordinate.xyz;\n  eyeDirection   = eyePosition - cameraCoordinate.xyz;\n  surfaceNormal  = normalize((vec4(normal,0) * inverseModel).xyz);\n}\n"]),o=i(["precision highp float;\n#define GLSLIFY 1\n\nfloat beckmannDistribution(float x, float roughness) {\n  float NdotH = max(x, 0.0001);\n  float cos2Alpha = NdotH * NdotH;\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\n  float roughness2 = roughness * roughness;\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\n  return exp(tan2Alpha / roughness2) / denom;\n}\n\nfloat beckmannSpecular(\n  vec3 lightDirection,\n  vec3 viewDirection,\n  vec3 surfaceNormal,\n  float roughness) {\n  return beckmannDistribution(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\n}\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 lowerBound, upperBound;\nuniform float contourTint;\nuniform vec4 contourColor;\nuniform sampler2D colormap;\nuniform vec3 clipBounds[2];\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\nuniform float vertexColor;\n\nvarying float value, kill;\nvarying vec3 worldCoordinate;\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\nvarying vec4 vColor;\n\nvoid main() {\n  if (\n    kill > 0.0 ||\n    vColor.a == 0.0 ||\n    outOfRange(clipBounds[0], clipBounds[1], worldCoordinate)\n  ) discard;\n\n  vec3 N = normalize(surfaceNormal);\n  vec3 V = normalize(eyeDirection);\n  vec3 L = normalize(lightDirection);\n\n  if(gl_FrontFacing) {\n    N = -N;\n  }\n\n  float specular = max(beckmannSpecular(L, V, N, roughness), 0.);\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\n\n  //decide how to interpolate color — in vertex or in fragment\n  vec4 surfaceColor =\n    step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) +\n    step(.5, vertexColor) * vColor;\n\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\n\n  gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\n}\n"]),s=i(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec4 uv;\nattribute float f;\n\nuniform vec3 objectOffset;\nuniform mat3 permutation;\nuniform mat4 model, view, projection;\nuniform float height, zOffset;\nuniform sampler2D colormap;\n\nvarying float value, kill;\nvarying vec3 worldCoordinate;\nvarying vec2 planeCoordinate;\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\nvarying vec4 vColor;\n\nvoid main() {\n  vec3 dataCoordinate = permutation * vec3(uv.xy, height);\n  worldCoordinate = objectOffset + dataCoordinate;\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\n\n  vec4 clipPosition = projection * view * worldPosition;\n  clipPosition.z += zOffset;\n\n  gl_Position = clipPosition;\n  value = f + objectOffset.z;\n  kill = -1.0;\n  planeCoordinate = uv.zw;\n\n  vColor = texture2D(colormap, vec2(value, value));\n\n  //Don't do lighting for contours\n  surfaceNormal   = vec3(1,0,0);\n  eyeDirection    = vec3(0,1,0);\n  lightDirection  = vec3(0,0,1);\n}\n"]),l=i(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n  return ((p > max(a, b)) || \n          (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n  return (outOfRange(a.x, b.x, p.x) ||\n          outOfRange(a.y, b.y, p.y) ||\n          outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n  return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec2 shape;\nuniform vec3 clipBounds[2];\nuniform float pickId;\n\nvarying float value, kill;\nvarying vec3 worldCoordinate;\nvarying vec2 planeCoordinate;\nvarying vec3 surfaceNormal;\n\nvec2 splitFloat(float v) {\n  float vh = 255.0 * v;\n  float upper = floor(vh);\n  float lower = fract(vh);\n  return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\n}\n\nvoid main() {\n  if ((kill > 0.0) ||\n      (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\n\n  vec2 ux = splitFloat(planeCoordinate.x / shape.x);\n  vec2 uy = splitFloat(planeCoordinate.y / shape.y);\n  gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\n}\n"]);e.createShader=function(t){var e=n(t,a,o,null,[{name:"uv",type:"vec4"},{name:"f",type:"vec3"},{name:"normal",type:"vec3"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},e.createPickShader=function(t){var e=n(t,a,l,null,[{name:"uv",type:"vec4"},{name:"f",type:"vec3"},{name:"normal",type:"vec3"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},e.createContourShader=function(t){var e=n(t,s,o,null,[{name:"uv",type:"vec4"},{name:"f",type:"float"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},e.createPickContourShader=function(t){var e=n(t,s,l,null,[{name:"uv",type:"vec4"},{name:"f",type:"float"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},3754:function(t,e,r){"use strict";t.exports=function(t){var e=t.gl,r=m(e),n=b(e),s=x(e),l=_(e),u=i(e),c=a(e,[{buffer:u,size:4,stride:w,offset:0},{buffer:u,size:3,stride:w,offset:16},{buffer:u,size:3,stride:w,offset:28}]),f=i(e),h=a(e,[{buffer:f,size:4,stride:20,offset:0},{buffer:f,size:1,stride:20,offset:16}]),p=i(e),d=a(e,[{buffer:p,size:2,type:e.FLOAT}]),v=o(e,1,S,e.RGBA,e.UNSIGNED_BYTE);v.minFilter=e.LINEAR,v.magFilter=e.LINEAR;var g=new E(e,[0,0],[[0,0,0],[0,0,0]],r,n,u,c,v,s,l,f,h,p,d,[0,0,0]),y={levels:[[],[],[]]};for(var T in t)y[T]=t[T];return y.colormap=y.colormap||"jet",g.update(y),g};var n=r(2288),i=r(5827),a=r(2944),o=r(8931),s=r(5306),l=r(9156),u=r(7498),c=r(7382),f=r(5050),h=r(4162),p=r(104),d=r(7437),v=r(5070),g=r(9144),y=r(9054),m=y.createShader,x=y.createContourShader,b=y.createPickShader,_=y.createPickContourShader,w=40,T=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],k=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],A=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];function M(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}!function(){for(var t=0;t<3;++t){var e=A[t],r=(t+2)%3;e[(t+1)%3+0]=1,e[r+3]=1,e[t+6]=1}}();var S=256;function E(t,e,r,n,i,a,o,l,u,c,h,p,d,v,g){this.gl=t,this.shape=e,this.bounds=r,this.objectOffset=g,this.intensityBounds=[],this._shader=n,this._pickShader=i,this._coordinateBuffer=a,this._vao=o,this._colorMap=l,this._contourShader=u,this._contourPickShader=c,this._contourBuffer=h,this._contourVAO=p,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new M([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=v,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.snapToData=!1,this.pixelRatio=1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}var L=E.prototype;L.genColormap=function(t,e){var r=!1,n=c([l({colormap:t,nshades:S,format:"rgba"}).map((function(t,n){var i=e?function(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}(n/255,e):t[3];return i<1&&(r=!0),[t[0],t[1],t[2],255*i]}))]);return u.divseq(n,255),this.hasAlphaScale=r,n},L.isTransparent=function(){return this.opacity<1||this.hasAlphaScale},L.isOpaque=function(){return!this.isTransparent()},L.pickSlots=1,L.setPickBase=function(t){this.pickId=t};var C=[0,0,0],P={showSurface:!1,showContour:!1,projections:[T.slice(),T.slice(),T.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function O(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||C,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=P.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(a[r]>0)][r],p(l,t.model,l);var u=P.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)u[i][n]=t.clipBounds[i][n];u[0][r]=-1e8,u[1][r]=1e8}return P.showSurface=o,P.showContour=s,P}var I={model:T,view:T,projection:T,inverseModel:T.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},D=T.slice(),z=[1,0,0,0,1,0,0,0,1];function R(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=I;n.model=t.model||T,n.view=t.view||T,n.projection=t.projection||T,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.objectOffset=this.objectOffset,n.contourColor=this.contourColor[0],n.inverseModel=d(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],o=0;o<3;++o)a[o]=Math.min(Math.max(this.clipBounds[i][o],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=z,n.vertexColor=this.vertexColor;var s=D;for(p(s,n.view,n.model),p(s,n.projection,s),d(s,s),i=0;i<3;++i)n.eyePosition[i]=s[12+i]/s[15];var l=s[15];for(i=0;i<3;++i)l+=this.lightPosition[i]*s[4*i+3];for(i=0;i<3;++i){var u=s[12+i];for(o=0;o<3;++o)u+=s[4*o+i]*this.lightPosition[o];n.lightPosition[i]=u/l}var c=O(n,this);if(c.showSurface){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),i=0;i<3;++i)this.surfaceProject[i]&&this.vertexCount&&(this._shader.uniforms.model=c.projections[i],this._shader.uniforms.clipBounds=c.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(c.showContour){var f=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,f.bind(),f.uniforms=n;var h=this._contourVAO;for(h.bind(),i=0;i<3;++i)for(f.uniforms.permutation=A[i],r.lineWidth(this.contourWidth[i]*this.pixelRatio),o=0;o<this.contourLevels[i].length;++o)o===this.highlightLevel[i]?(f.uniforms.contourColor=this.highlightColor[i],f.uniforms.contourTint=this.highlightTint[i]):0!==o&&o-1!==this.highlightLevel[i]||(f.uniforms.contourColor=this.contourColor[i],f.uniforms.contourTint=this.contourTint[i]),this._contourCounts[i][o]&&(f.uniforms.height=this.contourLevels[i][o],h.draw(r.LINES,this._contourCounts[i][o],this._contourOffsets[i][o]));for(i=0;i<3;++i)for(f.uniforms.model=c.projections[i],f.uniforms.clipBounds=c.clipBounds[i],o=0;o<3;++o)if(this.contourProject[i][o]){f.uniforms.permutation=A[o],r.lineWidth(this.contourWidth[o]*this.pixelRatio);for(var v=0;v<this.contourLevels[o].length;++v)v===this.highlightLevel[o]?(f.uniforms.contourColor=this.highlightColor[o],f.uniforms.contourTint=this.highlightTint[o]):0!==v&&v-1!==this.highlightLevel[o]||(f.uniforms.contourColor=this.contourColor[o],f.uniforms.contourTint=this.contourTint[o]),this._contourCounts[o][v]&&(f.uniforms.height=this.contourLevels[o][v],h.draw(r.LINES,this._contourCounts[o][v],this._contourOffsets[o][v]))}for(h.unbind(),(h=this._dynamicVAO).bind(),i=0;i<3;++i)if(0!==this._dynamicCounts[i])for(f.uniforms.model=n.model,f.uniforms.clipBounds=n.clipBounds,f.uniforms.permutation=A[i],r.lineWidth(this.dynamicWidth[i]*this.pixelRatio),f.uniforms.contourColor=this.dynamicColor[i],f.uniforms.contourTint=this.dynamicTint[i],f.uniforms.height=this.dynamicLevel[i],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]),o=0;o<3;++o)this.contourProject[o][i]&&(f.uniforms.model=c.projections[o],f.uniforms.clipBounds=c.clipBounds[o],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]));h.unbind()}}L.draw=function(t){return R.call(this,t,!1)},L.drawTransparent=function(t){return R.call(this,t,!0)};var F={model:T,view:T,projection:T,inverseModel:T,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,objectOffset:[0,0,0],permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};function B(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function N(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function j(t){if(Array.isArray(t)){if(Array.isArray(t))return[N(t[0]),N(t[1]),N(t[2])];var e=N(t);return[e.slice(),e.slice(),e.slice()]}}L.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=F;r.model=t.model||T,r.view=t.view||T,r.projection=t.projection||T,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.objectOffset=this.objectOffset,r.permutation=z;for(var n=0;n<2;++n)for(var i=r.clipBounds[n],a=0;a<3;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var o=O(r,this);if(o.showSurface){for(this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount),n=0;n<3;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=o.projections[n],this._pickShader.uniforms.clipBounds=o.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(o.showContour){var s=this._contourPickShader;s.bind(),s.uniforms=r;var l=this._contourVAO;for(l.bind(),a=0;a<3;++a)for(e.lineWidth(this.contourWidth[a]*this.pixelRatio),s.uniforms.permutation=A[a],n=0;n<this.contourLevels[a].length;++n)this._contourCounts[a][n]&&(s.uniforms.height=this.contourLevels[a][n],l.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n]));for(n=0;n<3;++n)for(s.uniforms.model=o.projections[n],s.uniforms.clipBounds=o.clipBounds[n],a=0;a<3;++a)if(this.contourProject[n][a]){s.uniforms.permutation=A[a],e.lineWidth(this.contourWidth[a]*this.pixelRatio);for(var u=0;u<this.contourLevels[a].length;++u)this._contourCounts[a][u]&&(s.uniforms.height=this.contourLevels[a][u],l.draw(e.LINES,this._contourCounts[a][u],this._contourOffsets[a][u]))}l.unbind()}},L.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var u=r.position;u[0]=u[1]=u[2]=0;for(var c=0;c<2;++c)for(var f=c?a:1-a,h=0;h<2;++h)for(var p=i+c,d=s+h,g=f*(h?l:1-l),y=0;y<3;++y)u[y]+=this._field[y].get(p,d)*g;for(var m=this._pickResult.level,x=0;x<3;++x)if(m[x]=v.le(this.contourLevels[x],u[x]),m[x]<0)this.contourLevels[x].length>0&&(m[x]=0);else if(m[x]<this.contourLevels[x].length-1){var b=this.contourLevels[x][m[x]],_=this.contourLevels[x][m[x]+1];Math.abs(b-u[x])>Math.abs(_-u[x])&&(m[x]+=1)}for(r.index[0]=a<.5?i:i+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],y=0;y<3;++y)r.dataCoordinate[y]=this._field[y].get(r.index[0],r.index[1]);return r},L.padField=function(t,e){var r=e.shape.slice(),n=t.shape.slice();u.assign(t.lo(1,1).hi(r[0],r[1]),e),u.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),u.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),u.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),u.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))},L.update=function(t){t=t||{},this.objectOffset=t.objectOffset||this.objectOffset,this.dirty=!0,"contourWidth"in t&&(this.contourWidth=B(t.contourWidth,Number)),"showContour"in t&&(this.showContour=B(t.showContour,Boolean)),"showSurface"in t&&(this.showSurface=!!t.showSurface),"contourTint"in t&&(this.contourTint=B(t.contourTint,Boolean)),"contourColor"in t&&(this.contourColor=j(t.contourColor)),"contourProject"in t&&(this.contourProject=B(t.contourProject,(function(t){return B(t,Boolean)}))),"surfaceProject"in t&&(this.surfaceProject=t.surfaceProject),"dynamicColor"in t&&(this.dynamicColor=j(t.dynamicColor)),"dynamicTint"in t&&(this.dynamicTint=B(t.dynamicTint,Number)),"dynamicWidth"in t&&(this.dynamicWidth=B(t.dynamicWidth,Number)),"opacity"in t&&(this.opacity=t.opacity),"opacityscale"in t&&(this.opacityscale=t.opacityscale),"colorBounds"in t&&(this.colorBounds=t.colorBounds),"vertexColor"in t&&(this.vertexColor=t.vertexColor?1:0),"colormap"in t&&this._colorMap.setPixels(this.genColormap(t.colormap,this.opacityscale));var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),"field"in t||"coords"in t){var i=(e.shape[0]+2)*(e.shape[1]+2);i>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(n.nextPow2(i))),this._field[2]=f(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),this.padField(this._field[2],e),this.shape=e.shape.slice();for(var a=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(s.freeFloat(this._field[o].data),this._field[o].data=s.mallocFloat(this._field[2].size)),this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var l=t.coords;if(!Array.isArray(l)||3!==l.length)throw new Error("gl-surface: invalid coordinates for x/y");for(o=0;o<2;++o){var u=l[o];for(y=0;y<2;++y)if(u.shape[y]!==a[y])throw new Error("gl-surface: coords have incorrect shape");this.padField(this._field[o],u)}}else if(t.ticks){var c=t.ticks;if(!Array.isArray(c)||2!==c.length)throw new Error("gl-surface: invalid ticks");for(o=0;o<2;++o){var p=c[o];if((Array.isArray(p)||p.length)&&(p=f(p)),p.shape[0]!==a[o])throw new Error("gl-surface: invalid tick length");var d=f(p.data,a);d.stride[o]=p.stride[0],d.stride[1^o]=0,this.padField(this._field[o],d)}}else{for(o=0;o<2;++o){var v=[0,0];v[o]=1,this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2],v,0)}this._field[0].set(0,0,0);for(var y=0;y<a[0];++y)this._field[0].set(y+1,0,y);for(this._field[0].set(a[0]+1,0,a[0]-1),this._field[1].set(0,0,0),y=0;y<a[1];++y)this._field[1].set(0,y+1,y);this._field[1].set(0,a[1]+1,a[1]-1)}var m=this._field,x=f(s.mallocFloat(3*m[2].size*2),[3,a[0]+2,a[1]+2,2]);for(o=0;o<3;++o)g(x.pick(o),m[o],"mirror");var b=f(s.mallocFloat(3*m[2].size),[a[0]+2,a[1]+2,3]);for(o=0;o<a[0]+2;++o)for(y=0;y<a[1]+2;++y){var _=x.get(0,o,y,0),w=x.get(0,o,y,1),T=x.get(1,o,y,0),A=x.get(1,o,y,1),M=x.get(2,o,y,0),S=x.get(2,o,y,1),E=T*S-A*M,L=M*w-S*_,C=_*A-w*T,P=Math.sqrt(E*E+L*L+C*C);P<1e-8?(P=Math.max(Math.abs(E),Math.abs(L),Math.abs(C)))<1e-8?(C=1,L=E=0,P=1):P=1/P:P=1/Math.sqrt(P),b.set(o,y,0,E*P),b.set(o,y,1,L*P),b.set(o,y,2,C*P)}s.free(x.data);var O=[1/0,1/0,1/0],I=[-1/0,-1/0,-1/0],D=1/0,z=-1/0,R=(a[0]-1)*(a[1]-1)*6,F=s.mallocFloat(n.nextPow2(10*R)),N=0,U=0;for(o=0;o<a[0]-1;++o)t:for(y=0;y<a[1]-1;++y){for(var V=0;V<2;++V)for(var H=0;H<2;++H)for(var q=0;q<3;++q){var G=this._field[q].get(1+o+V,1+y+H);if(isNaN(G)||!isFinite(G))continue t}for(q=0;q<6;++q){var Z=o+k[q][0],Y=y+k[q][1],W=this._field[0].get(Z+1,Y+1),X=this._field[1].get(Z+1,Y+1);G=this._field[2].get(Z+1,Y+1),E=b.get(Z+1,Y+1,0),L=b.get(Z+1,Y+1,1),C=b.get(Z+1,Y+1,2),t.intensity&&(J=t.intensity.get(Z,Y));var J=t.intensity?t.intensity.get(Z,Y):G+this.objectOffset[2];F[N++]=Z,F[N++]=Y,F[N++]=W,F[N++]=X,F[N++]=G,F[N++]=0,F[N++]=J,F[N++]=E,F[N++]=L,F[N++]=C,O[0]=Math.min(O[0],W+this.objectOffset[0]),O[1]=Math.min(O[1],X+this.objectOffset[1]),O[2]=Math.min(O[2],G+this.objectOffset[2]),D=Math.min(D,J),I[0]=Math.max(I[0],W+this.objectOffset[0]),I[1]=Math.max(I[1],X+this.objectOffset[1]),I[2]=Math.max(I[2],G+this.objectOffset[2]),z=Math.max(z,J),U+=1}}for(t.intensityBounds&&(D=+t.intensityBounds[0],z=+t.intensityBounds[1]),o=6;o<N;o+=10)F[o]=(F[o]-D)/(z-D);this._vertexCount=U,this._coordinateBuffer.update(F.subarray(0,N)),s.freeFloat(F),s.free(b.data),this.bounds=[O,I],this.intensity=t.intensity||this._field[2],this.intensityBounds[0]===D&&this.intensityBounds[1]===z||(r=!0),this.intensityBounds=[D,z]}if("levels"in t){var K=t.levels;for(K=Array.isArray(K[0])?K.slice():[[],[],K],o=0;o<3;++o)K[o]=K[o].slice(),K[o].sort((function(t,e){return t-e}));for(o=0;o<3;++o)for(y=0;y<K[o].length;++y)K[o][y]-=this.objectOffset[o];t:for(o=0;o<3;++o){if(K[o].length!==this.contourLevels[o].length){r=!0;break}for(y=0;y<K[o].length;++y)if(K[o][y]!==this.contourLevels[o][y]){r=!0;break t}}this.contourLevels=K}if(r){m=this._field,a=this.shape;for(var $=[],Q=0;Q<3;++Q){var tt=this.contourLevels[Q],et=[],rt=[],nt=[0,0,0];for(o=0;o<tt.length;++o){var it=h(this._field[Q],tt[o]);et.push($.length/5|0),U=0;t:for(y=0;y<it.cells.length;++y){var at=it.cells[y];for(q=0;q<2;++q){var ot=it.positions[at[q]],st=ot[0],lt=0|Math.floor(st),ut=st-lt,ct=ot[1],ft=0|Math.floor(ct),ht=ct-ft,pt=!1;e:for(var dt=0;dt<3;++dt){nt[dt]=0;var vt=(Q+dt+1)%3;for(V=0;V<2;++V){var gt=V?ut:1-ut;for(Z=0|Math.min(Math.max(lt+V,0),a[0]),H=0;H<2;++H){var yt=H?ht:1-ht;if(Y=0|Math.min(Math.max(ft+H,0),a[1]),G=dt<2?this._field[vt].get(Z,Y):(this.intensity.get(Z,Y)-this.intensityBounds[0])/(this.intensityBounds[1]-this.intensityBounds[0]),!isFinite(G)||isNaN(G)){pt=!0;break e}var mt=gt*yt;nt[dt]+=mt*G}}}if(pt){if(q>0){for(var xt=0;xt<5;++xt)$.pop();U-=1}continue t}$.push(nt[0],nt[1],ot[0],ot[1],nt[2]),U+=1}}rt.push(U)}this._contourOffsets[Q]=et,this._contourCounts[Q]=rt}var bt=s.mallocFloat($.length);for(o=0;o<$.length;++o)bt[o]=$[o];this._contourBuffer.update(bt),s.freeFloat(bt)}},L.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)s.freeFloat(this._field[t].data)},L.highlight=function(t){var e,r;if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;for(r=this.snapToData?t.dataCoordinate:t.position,e=0;e<3;++e)r[e]-=this.objectOffset[e];if(this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=s.mallocFloat(12*i[0]*i[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var l=(o+1)%3,u=(o+2)%3,c=this._field[o],f=this._field[l],p=this._field[u],d=h(c,r[o]),v=d.cells,g=d.positions;for(this._dynamicOffsets[o]=n,e=0;e<v.length;++e)for(var y=v[e],m=0;m<2;++m){var x=g[y[m]],b=+x[0],_=0|b,w=0|Math.min(_+1,i[0]),T=b-_,k=1-T,A=+x[1],M=0|A,S=0|Math.min(M+1,i[1]),E=A-M,L=1-E,C=k*L,P=k*E,O=T*L,I=T*E,D=C*f.get(_,M)+P*f.get(_,S)+O*f.get(w,M)+I*f.get(w,S),z=C*p.get(_,M)+P*p.get(_,S)+O*p.get(w,M)+I*p.get(w,S);if(isNaN(D)||isNaN(z)){m&&(n-=1);break}a[2*n+0]=D,a[2*n+1]=z,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),s.freeFloat(a)}}},8931:function(t,e,r){"use strict";var n=r(5050),i=r(7498),a=r(5306);t.exports=function(t){if(arguments.length<=1)throw new Error("gl-texture2d: Missing arguments for texture2d constructor");if(o||function(t){o=[t.LINEAR,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_NEAREST],s=[t.NEAREST,t.LINEAR,t.NEAREST_MIPMAP_NEAREST,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_LINEAR],l=[t.REPEAT,t.CLAMP_TO_EDGE,t.MIRRORED_REPEAT]}(t),"number"==typeof arguments[1])return g(t,arguments[1],arguments[2],arguments[3]||t.RGBA,arguments[4]||t.UNSIGNED_BYTE);if(Array.isArray(arguments[1]))return g(t,0|arguments[1][0],0|arguments[1][1],arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if("object"==typeof arguments[1]){var e=arguments[1],r=u(e)?e:e.raw;if(r)return function(t,e,r,n,i,a){var o=v(t);return t.texImage2D(t.TEXTURE_2D,0,i,i,a,e),new h(t,o,r,n,i,a)}(t,r,0|e.width,0|e.height,arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(e.shape&&e.data&&e.stride)return function(t,e){var r=e.dtype,o=e.shape.slice(),s=t.getParameter(t.MAX_TEXTURE_SIZE);if(o[0]<0||o[0]>s||o[1]<0||o[1]>s)throw new Error("gl-texture2d: Invalid texture size");var l=d(o,e.stride.slice()),u=0;"float32"===r?u=t.FLOAT:"float64"===r?(u=t.FLOAT,l=!1,r="float32"):"uint8"===r?u=t.UNSIGNED_BYTE:(u=t.UNSIGNED_BYTE,l=!1,r="uint8");var f,p,g=0;if(2===o.length)g=t.LUMINANCE,o=[o[0],o[1],1],e=n(e.data,o,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==o.length)throw new Error("gl-texture2d: Invalid shape for texture");if(1===o[2])g=t.ALPHA;else if(2===o[2])g=t.LUMINANCE_ALPHA;else if(3===o[2])g=t.RGB;else{if(4!==o[2])throw new Error("gl-texture2d: Invalid shape for pixel coords");g=t.RGBA}}u!==t.FLOAT||t.getExtension("OES_texture_float")||(u=t.UNSIGNED_BYTE,l=!1);var y=e.size;if(l)f=0===e.offset&&e.data.length===y?e.data:e.data.subarray(e.offset,e.offset+y);else{var m=[o[2],o[2]*o[0],1];p=a.malloc(y,r);var x=n(p,o,m,0);"float32"!==r&&"float64"!==r||u!==t.UNSIGNED_BYTE?i.assign(x,e):c(x,e),f=p.subarray(0,y)}var b=v(t);return t.texImage2D(t.TEXTURE_2D,0,g,o[0],o[1],0,g,u,f),l||a.free(p),new h(t,b,o[0],o[1],g,u)}(t,e)}throw new Error("gl-texture2d: Invalid arguments for texture2d constructor")};var o=null,s=null,l=null;function u(t){return"undefined"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||"undefined"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||"undefined"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement||"undefined"!=typeof ImageData&&t instanceof ImageData}var c=function(t,e){i.muls(t,e,255)};function f(t,e,r){var n=t.gl,i=n.getParameter(n.MAX_TEXTURE_SIZE);if(e<0||e>i||r<0||r>i)throw new Error("gl-texture2d: Invalid texture size");return t._shape=[e,r],t.bind(),n.texImage2D(n.TEXTURE_2D,0,t.format,e,r,0,t.format,t.type,null),t._mipLevels=[0],t}function h(t,e,r,n,i,a){this.gl=t,this.handle=e,this.format=i,this.type=a,this._shape=[r,n],this._mipLevels=[0],this._magFilter=t.NEAREST,this._minFilter=t.NEAREST,this._wrapS=t.CLAMP_TO_EDGE,this._wrapT=t.CLAMP_TO_EDGE,this._anisoSamples=1;var o=this,s=[this._wrapS,this._wrapT];Object.defineProperties(s,[{get:function(){return o._wrapS},set:function(t){return o.wrapS=t}},{get:function(){return o._wrapT},set:function(t){return o.wrapT=t}}]),this._wrapVector=s;var l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}var p=h.prototype;function d(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function v(t){var e=t.createTexture();return t.bindTexture(t.TEXTURE_2D,e),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),e}function g(t,e,r,n,i){var a=t.getParameter(t.MAX_TEXTURE_SIZE);if(e<0||e>a||r<0||r>a)throw new Error("gl-texture2d: Invalid texture shape");if(i===t.FLOAT&&!t.getExtension("OES_texture_float"))throw new Error("gl-texture2d: Floating point textures not supported on this platform");var o=v(t);return t.texImage2D(t.TEXTURE_2D,0,n,e,r,0,n,i,null),new h(t,o,e,r,n,i)}Object.defineProperties(p,{minFilter:{get:function(){return this._minFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&o.indexOf(t)>=0&&(e.getExtension("OES_texture_float_linear")||(t=e.NEAREST)),s.indexOf(t)<0)throw new Error("gl-texture2d: Unknown filter mode "+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,t),this._minFilter=t}},magFilter:{get:function(){return this._magFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&o.indexOf(t)>=0&&(e.getExtension("OES_texture_float_linear")||(t=e.NEAREST)),s.indexOf(t)<0)throw new Error("gl-texture2d: Unknown filter mode "+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,t),this._magFilter=t}},mipSamples:{get:function(){return this._anisoSamples},set:function(t){var e=this._anisoSamples;if(this._anisoSamples=0|Math.max(t,1),e!==this._anisoSamples){var r=this.gl.getExtension("EXT_texture_filter_anisotropic");r&&this.gl.texParameterf(this.gl.TEXTURE_2D,r.TEXTURE_MAX_ANISOTROPY_EXT,this._anisoSamples)}return this._anisoSamples}},wrapS:{get:function(){return this._wrapS},set:function(t){if(this.bind(),l.indexOf(t)<0)throw new Error("gl-texture2d: Unknown wrap mode "+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_S,t),this._wrapS=t}},wrapT:{get:function(){return this._wrapT},set:function(t){if(this.bind(),l.indexOf(t)<0)throw new Error("gl-texture2d: Unknown wrap mode "+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_T,t),this._wrapT=t}},wrap:{get:function(){return this._wrapVector},set:function(t){if(Array.isArray(t)||(t=[t,t]),2!==t.length)throw new Error("gl-texture2d: Must specify wrap mode for rows and columns");for(var e=0;e<2;++e)if(l.indexOf(t[e])<0)throw new Error("gl-texture2d: Unknown wrap mode "+t);this._wrapS=t[0],this._wrapT=t[1];var r=this.gl;return this.bind(),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_S,this._wrapS),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_T,this._wrapT),t}},shape:{get:function(){return this._shapeVector},set:function(t){if(Array.isArray(t)){if(2!==t.length)throw new Error("gl-texture2d: Invalid texture shape")}else t=[0|t,0|t];return f(this,0|t[0],0|t[1]),[0|t[0],0|t[1]]}},width:{get:function(){return this._shape[0]},set:function(t){return f(this,t|=0,this._shape[1]),t}},height:{get:function(){return this._shape[1]},set:function(t){return t|=0,f(this,this._shape[0],t),t}}}),p.bind=function(t){var e=this.gl;return void 0!==t&&e.activeTexture(e.TEXTURE0+(0|t)),e.bindTexture(e.TEXTURE_2D,this.handle),void 0!==t?0|t:e.getParameter(e.ACTIVE_TEXTURE)-e.TEXTURE0},p.dispose=function(){this.gl.deleteTexture(this.handle)},p.generateMipmap=function(){this.bind(),this.gl.generateMipmap(this.gl.TEXTURE_2D);for(var t=Math.min(this._shape[0],this._shape[1]),e=0;t>0;++e,t>>>=1)this._mipLevels.indexOf(e)<0&&this._mipLevels.push(e)},p.setPixels=function(t,e,r,o){var s=this.gl;this.bind(),Array.isArray(e)?(o=r,r=0|e[1],e=0|e[0]):(e=e||0,r=r||0),o=o||0;var 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hn=function(t,e){this._parameters=t,this._specification=e,Ft(this,Qr(this._parameters,this._specification))};function pn(t){var e=null;if(t instanceof wr)e=pn(t.result);else if(t instanceof _r)for(var r=0,n=t.args;r<n.length;r+=1){var i=n[r];if(e=pn(i))break}else(t instanceof Ke||t instanceof xr)&&t.input instanceof Ae&&"zoom"===t.input.name&&(e=t);return e instanceof jt||t.eachChild((function(t){var r=pn(t);r instanceof jt?e=r:!e&&r?e=new jt("",'"zoom" expression may only be used as input to a top-level "step" or "interpolate" expression.'):e&&r&&e!==r&&(e=new jt("",'Only one zoom-based "step" or "interpolate" subexpression may be used in an expression.'))})),e}function dn(t){var e=t.key,r=t.value,n=t.valueSpec||{},i=t.objectElementValidators||{},a=t.style,o=t.styleSpec,s=[],l=Jr(r);if("object"!==l)return[new zt(e,r,"object expected, "+l+" found")];for(var u in r){var c=u.split(".")[0],f=n[c]||n["*"],h=void 0;if(i[c])h=i[c];else if(n[c])h=Un;else 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e=[],a=t.value,s=t.key;if("array"!==Jr(a))return[new zt(s,a,"array expected, "+Jr(a)+" found")];if(2!==a.length)return[new zt(s,a,"array length 2 expected, length "+a.length+" found")];if(u){if("object"!==Jr(a[0]))return[new zt(s,a,"object expected, "+Jr(a[0])+" found")];if(void 0===a[0].zoom)return[new zt(s,a,"object stop key must have zoom")];if(void 0===a[0].value)return[new zt(s,a,"object stop key must have value")];if(n&&n>Bt(a[0].zoom))return[new zt(s,a[0].zoom,"stop zoom values must appear in ascending order")];Bt(a[0].zoom)!==n&&(n=Bt(a[0].zoom),r=void 0,o={}),e=e.concat(dn({key:s+"[0]",value:a[0],valueSpec:{zoom:{}},style:t.style,styleSpec:t.styleSpec,objectElementValidators:{zoom:gn,value:h}}))}else e=e.concat(h({key:s+"[0]",value:a[0],valueSpec:{},style:t.style,styleSpec:t.styleSpec},a));return sn(Nt(a[1]))?e.concat([new zt(s+"[1]",a[1],"expressions are not allowed in function 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e=("property"===t.expressionContext?fn:ln)(Nt(t.value),t.valueSpec);if("error"===e.result)return e.value.map((function(e){return new zt(""+t.key+e.key,t.value,e.message)}));var r=e.value.expression||e.value._styleExpression.expression;if("property"===t.expressionContext&&"text-font"===t.propertyKey&&!r.outputDefined())return[new zt(t.key,t.value,'Invalid data expression for "'+t.propertyKey+'". 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zt(r,e,'filter array for "'+e[0]+'" operator must have 2 elements')):"string"!==n&&a.push(new zt(r+"[1]",e[1],"string expected, "+n+" found"));break;case"within":n=Jr(e[1]),2!==e.length?a.push(new zt(r,e,'filter array for "'+e[0]+'" operator must have 2 elements')):"object"!==n&&a.push(new zt(r+"[1]",e[1],"object expected, "+n+" found"))}return a}function On(t,e){var r=t.key,n=t.style,i=t.styleSpec,a=t.value,o=t.objectKey,s=i[e+"_"+t.layerType];if(!s)return[];var l=o.match(/^(.*)-transition$/);if("paint"===e&&l&&s[l[1]]&&s[l[1]].transition)return Un({key:r,value:a,valueSpec:i.transition,style:n,styleSpec:i});var u,c=t.valueSpec||s[o];if(!c)return[new zt(r,a,'unknown property "'+o+'"')];if("string"===Jr(a)&&Yr(c)&&!c.tokens&&(u=/^{([^}]+)}$/.exec(a)))return[new zt(r,a,'"'+o+'" does not support interpolation syntax\nUse an identity property function instead: `{ "type": "identity", "property": '+JSON.stringify(u[1])+" }`.")];var f=[];return"symbol"===t.layerType&&("text-field"===o&&n&&!n.glyphs&&f.push(new zt(r,a,'use of "text-field" requires a style "glyphs" property')),"text-font"===o&&Kr(Nt(a))&&"identity"===Bt(a.type)&&f.push(new zt(r,a,'"text-font" does not support identity functions'))),f.concat(Un({key:t.key,value:a,valueSpec:c,style:n,styleSpec:i,expressionContext:"property",propertyType:e,propertyKey:o}))}function In(t){return On(t,"paint")}function Dn(t){return On(t,"layout")}function zn(t){var e=[],r=t.value,n=t.key,i=t.style,a=t.styleSpec;r.type||r.ref||e.push(new zt(n,r,'either "type" or "ref" is required'));var o,s=Bt(r.type),l=Bt(r.ref);if(r.id)for(var u=Bt(r.id),c=0;c<t.arrayIndex;c++){var f=i.layers[c];Bt(f.id)===u&&e.push(new zt(n,r.id,'duplicate layer id "'+r.id+'", previously used at line '+f.id.__line__))}if("ref"in r)["type","source","source-layer","filter","layout"].forEach((function(t){t in r&&e.push(new zt(n,r[t],'"'+t+'" is prohibited for ref 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e.push(new zt(n,r,'missing required property "source"'));return e=e.concat(dn({key:n,value:r,valueSpec:a.layer,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{"*":function(){return[]},type:function(){return Un({key:n+".type",value:r.type,valueSpec:a.layer.type,style:t.style,styleSpec:t.styleSpec,object:r,objectKey:"type"})},filter:Cn,layout:function(t){return dn({layer:r,key:t.key,value:t.value,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{"*":function(t){return Dn(Ft({layerType:s},t))}}})},paint:function(t){return dn({layer:r,key:t.key,value:t.value,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{"*":function(t){return In(Ft({layerType:s},t))}}})}}})),e}function Rn(t){var e=t.value,r=t.key,n=Jr(e);return"string"!==n?[new zt(r,e,"string expected, "+n+" found")]:[]}var Fn={promoteId:function(t){var e=t.key,r=t.value;if("string"===Jr(r))return Rn({key:e,value:r});var n=[];for(var i in r)n.push.apply(n,Rn({key:e+"."+i,value:r[i]}));return n}};function Bn(t){var e=t.value,r=t.key,n=t.styleSpec,i=t.style;if(!e.type)return[new zt(r,e,'"type" is required')];var a,o=Bt(e.type);switch(o){case"vector":case"raster":case"raster-dem":return dn({key:r,value:e,valueSpec:n["source_"+o.replace("-","_")],style:t.style,styleSpec:n,objectElementValidators:Fn});case"geojson":if(a=dn({key:r,value:e,valueSpec:n.source_geojson,style:i,styleSpec:n,objectElementValidators:Fn}),e.cluster)for(var s in e.clusterProperties){var l=e.clusterProperties[s],u=l[0],c=l[1],f="string"==typeof u?[u,["accumulated"],["get",s]]:u;a.push.apply(a,mn({key:r+"."+s+".map",value:c,expressionContext:"cluster-map"})),a.push.apply(a,mn({key:r+"."+s+".reduce",value:f,expressionContext:"cluster-reduce"}))}return a;case"video":return dn({key:r,value:e,valueSpec:n.source_video,style:i,styleSpec:n});case"image":return dn({key:r,value:e,valueSpec:n.source_image,style:i,styleSpec:n});case"canvas":return[new zt(r,null,"Please use runtime APIs to add canvas sources, rather 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o=(n-this.begin)/(this.end-this.begin);return this.property.interpolate(a.possiblyEvaluate(t,e,r),i,function(t){if(t<=0)return 0;if(t>=1)return 1;var e=t*t,r=e*t;return 4*(t<.5?r:3*(t-e)+r-.75)}(o))}return i};var Ri=function(t){this._properties=t,this._values=Object.create(t.defaultTransitioningPropertyValues)};Ri.prototype.possiblyEvaluate=function(t,e,r){for(var n=new Ni(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n},Ri.prototype.hasTransition=function(){for(var t=0,e=Object.keys(this._values);t<e.length;t+=1){var r=e[t];if(this._values[r].prior)return!0}return!1};var Fi=function(t){this._properties=t,this._values=Object.create(t.defaultPropertyValues)};Fi.prototype.getValue=function(t){return b(this._values[t].value)},Fi.prototype.setValue=function(t,e){this._values[t]=new Oi(this._values[t].property,null===e?void 0:b(e))},Fi.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i)}return t},Fi.prototype.possiblyEvaluate=function(t,e,r){for(var n=new Ni(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n};var Bi=function(t,e,r){this.property=t,this.value=e,this.parameters=r};Bi.prototype.isConstant=function(){return"constant"===this.value.kind},Bi.prototype.constantOr=function(t){return"constant"===this.value.kind?this.value.value:t},Bi.prototype.evaluate=function(t,e,r,n){return this.property.evaluate(this.value,this.parameters,t,e,r,n)};var Ni=function(t){this._properties=t,this._values=Object.create(t.defaultPossiblyEvaluatedValues)};Ni.prototype.get=function(t){return this._values[t]};var ji=function(t){this.specification=t};ji.prototype.possiblyEvaluate=function(t,e){return t.expression.evaluate(e)},ji.prototype.interpolate=function(t,e,r){var n=Qe[this.specification.type];return n?n(t,e,r):t};var Ui=function(t,e){this.specification=t,this.overrides=e};Ui.prototype.possiblyEvaluate=function(t,e,r,n){return"constant"===t.expression.kind||"camera"===t.expression.kind?new Bi(this,{kind:"constant",value:t.expression.evaluate(e,null,{},r,n)},e):new Bi(this,t.expression,e)},Ui.prototype.interpolate=function(t,e,r){if("constant"!==t.value.kind||"constant"!==e.value.kind)return t;if(void 0===t.value.value||void 0===e.value.value)return new Bi(this,{kind:"constant",value:void 0},t.parameters);var n=Qe[this.specification.type];return n?new Bi(this,{kind:"constant",value:n(t.value.value,e.value.value,r)},t.parameters):t},Ui.prototype.evaluate=function(t,e,r,n,i,a){return"constant"===t.kind?t.value:t.evaluate(e,r,n,i,a)};var Vi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0===t.value)return new Bi(this,{kind:"constant",value:void 0},e);if("constant"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n),a="resolvedImage"===t.property.specification.type&&"string"!=typeof i?i.name:i,o=this._calculate(a,a,a,e);return new Bi(this,{kind:"constant",value:o},e)}if("camera"===t.expression.kind){var s=this._calculate(t.expression.evaluate({zoom:e.zoom-1}),t.expression.evaluate({zoom:e.zoom}),t.expression.evaluate({zoom:e.zoom+1}),e);return new Bi(this,{kind:"constant",value:s},e)}return new Bi(this,t.expression,e)},e.prototype.evaluate=function(t,e,r,n,i,a){if("source"===t.kind){var o=t.evaluate(e,r,n,i,a);return this._calculate(o,o,o,e)}return"composite"===t.kind?this._calculate(t.evaluate({zoom:Math.floor(e.zoom)-1},r,n),t.evaluate({zoom:Math.floor(e.zoom)},r,n),t.evaluate({zoom:Math.floor(e.zoom)+1},r,n),e):t.value},e.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},e.prototype.interpolate=function(t){return t},e}(Ui),Hi=function(t){this.specification=t};Hi.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0!==t.value){if("constant"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n);return this._calculate(i,i,i,e)}return this._calculate(t.expression.evaluate(new Pi(Math.floor(e.zoom-1),e)),t.expression.evaluate(new Pi(Math.floor(e.zoom),e)),t.expression.evaluate(new Pi(Math.floor(e.zoom+1),e)),e)}},Hi.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},Hi.prototype.interpolate=function(t){return t};var qi=function(t){this.specification=t};qi.prototype.possiblyEvaluate=function(t,e,r,n){return!!t.expression.evaluate(e,null,{},r,n)},qi.prototype.interpolate=function(){return!1};var Gi=function(t){for(var e in this.properties=t,this.defaultPropertyValues={},this.defaultTransitionablePropertyValues={},this.defaultTransitioningPropertyValues={},this.defaultPossiblyEvaluatedValues={},this.overridableProperties=[],t){var r=t[e];r.specification.overridable&&this.overridableProperties.push(e);var n=this.defaultPropertyValues[e]=new Oi(r,void 0),i=this.defaultTransitionablePropertyValues[e]=new Ii(r);this.defaultTransitioningPropertyValues[e]=i.untransitioned(),this.defaultPossiblyEvaluatedValues[e]=n.possiblyEvaluate({})}};ni("DataDrivenProperty",Ui),ni("DataConstantProperty",ji),ni("CrossFadedDataDrivenProperty",Vi),ni("CrossFadedProperty",Hi),ni("ColorRampProperty",qi);var Zi="-transition",Yi=function(t){function e(e,r){if(t.call(this),this.id=e.id,this.type=e.type,this._featureFilter={filter:function(){return!0},needGeometry:!1},"custom"!==e.type&&(this.metadata=e.metadata,this.minzoom=e.minzoom,this.maxzoom=e.maxzoom,"background"!==e.type&&(this.source=e.source,this.sourceLayer=e["source-layer"],this.filter=e.filter),r.layout&&(this._unevaluatedLayout=new Fi(r.layout)),r.paint)){for(var n in this._transitionablePaint=new Di(r.paint),e.paint)this.setPaintProperty(n,e.paint[n],{validate:!1});for(var i in e.layout)this.setLayoutProperty(i,e.layout[i],{validate:!1});this._transitioningPaint=this._transitionablePaint.untransitioned(),this.paint=new Ni(r.paint)}}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getCrossfadeParameters=function(){return this._crossfadeParameters},e.prototype.getLayoutProperty=function(t){return"visibility"===t?this.visibility:this._unevaluatedLayout.getValue(t)},e.prototype.setLayoutProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n="layers."+this.id+".layout."+t;if(this._validate(Xn,n,t,e,r))return}"visibility"!==t?this._unevaluatedLayout.setValue(t,e):this.visibility=e},e.prototype.getPaintProperty=function(t){return y(t,Zi)?this._transitionablePaint.getTransition(t.slice(0,-11)):this._transitionablePaint.getValue(t)},e.prototype.setPaintProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n="layers."+this.id+".paint."+t;if(this._validate(Wn,n,t,e,r))return!1}if(y(t,Zi))return this._transitionablePaint.setTransition(t.slice(0,-11),e||void 0),!1;var i=this._transitionablePaint._values[t],a="cross-faded-data-driven"===i.property.specification["property-type"],o=i.value.isDataDriven(),s=i.value;this._transitionablePaint.setValue(t,e),this._handleSpecialPaintPropertyUpdate(t);var l=this._transitionablePaint._values[t].value;return l.isDataDriven()||o||a||this._handleOverridablePaintPropertyUpdate(t,s,l)},e.prototype._handleSpecialPaintPropertyUpdate=function(t){},e.prototype._handleOverridablePaintPropertyUpdate=function(t,e,r){return!1},e.prototype.isHidden=function(t){return!!(this.minzoom&&t<this.minzoom)||!!(this.maxzoom&&t>=this.maxzoom)||"none"===this.visibility},e.prototype.updateTransitions=function(t){this._transitioningPaint=this._transitionablePaint.transitioned(t,this._transitioningPaint)},e.prototype.hasTransition=function(){return this._transitioningPaint.hasTransition()},e.prototype.recalculate=function(t,e){t.getCrossfadeParameters&&(this._crossfadeParameters=t.getCrossfadeParameters()),this._unevaluatedLayout&&(this.layout=this._unevaluatedLayout.possiblyEvaluate(t,void 0,e)),this.paint=this._transitioningPaint.possiblyEvaluate(t,void 0,e)},e.prototype.serialize=function(){var t={id:this.id,type:this.type,source:this.source,"source-layer":this.sourceLayer,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom,filter:this.filter,layout:this._unevaluatedLayout&&this._unevaluatedLayout.serialize(),paint:this._transitionablePaint&&this._transitionablePaint.serialize()};return this.visibility&&(t.layout=t.layout||{},t.layout.visibility=this.visibility),x(t,(function(t,e){return!(void 0===t||"layout"===e&&!Object.keys(t).length||"paint"===e&&!Object.keys(t).length)}))},e.prototype._validate=function(t,e,r,n,i){return void 0===i&&(i={}),(!i||!1!==i.validate)&&Jn(this,t.call(Zn,{key:e,layerType:this.type,objectKey:r,value:n,styleSpec:Dt,style:{glyphs:!0,sprite:!0}}))},e.prototype.is3D=function(){return!1},e.prototype.isTileClipped=function(){return!1},e.prototype.hasOffscreenPass=function(){return!1},e.prototype.resize=function(){},e.prototype.isStateDependent=function(){for(var t in this.paint._values){var e=this.paint.get(t);if(e instanceof Bi&&Yr(e.property.specification)&&("source"===e.value.kind||"composite"===e.value.kind)&&e.value.isStateDependent)return!0}return!1},e}(It),Wi={Int8:Int8Array,Uint8:Uint8Array,Int16:Int16Array,Uint16:Uint16Array,Int32:Int32Array,Uint32:Uint32Array,Float32:Float32Array},Xi=function(t,e){this._structArray=t,this._pos1=e*this.size,this._pos2=this._pos1/2,this._pos4=this._pos1/4,this._pos8=this._pos1/8},Ji=function(){this.isTransferred=!1,this.capacity=-1,this.resize(0)};function Ki(t,e){void 0===e&&(e=1);var r=0,n=0;return{members:t.map((function(t){var i,a=(i=t.type,Wi[i].BYTES_PER_ELEMENT),o=r=$i(r,Math.max(e,a)),s=t.components||1;return n=Math.max(n,a),r+=a*s,{name:t.name,type:t.type,components:s,offset:o}})),size:$i(r,Math.max(n,e)),alignment:e}}function $i(t,e){return Math.ceil(t/e)*e}Ji.serialize=function(t,e){return t._trim(),e&&(t.isTransferred=!0,e.push(t.arrayBuffer)),{length:t.length,arrayBuffer:t.arrayBuffer}},Ji.deserialize=function(t){var e=Object.create(this.prototype);return e.arrayBuffer=t.arrayBuffer,e.length=t.length,e.capacity=t.arrayBuffer.byteLength/e.bytesPerElement,e._refreshViews(),e},Ji.prototype._trim=function(){this.length!==this.capacity&&(this.capacity=this.length,this.arrayBuffer=this.arrayBuffer.slice(0,this.length*this.bytesPerElement),this._refreshViews())},Ji.prototype.clear=function(){this.length=0},Ji.prototype.resize=function(t){this.reserve(t),this.length=t},Ji.prototype.reserve=function(t){if(t>this.capacity){this.capacity=Math.max(t,Math.floor(5*this.capacity),128),this.arrayBuffer=new ArrayBuffer(this.capacity*this.bytesPerElement);var e=this.uint8;this._refreshViews(),e&&this.uint8.set(e)}},Ji.prototype._refreshViews=function(){throw new Error("_refreshViews() must be implemented by each concrete StructArray layout")};var Qi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.int16[n+0]=e,this.int16[n+1]=r,t},e}(Ji);Qi.prototype.bytesPerElement=4,ni("StructArrayLayout2i4",Qi);var ta=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=4*t;return this.int16[a+0]=e,this.int16[a+1]=r,this.int16[a+2]=n,this.int16[a+3]=i,t},e}(Ji);ta.prototype.bytesPerElement=8,ni("StructArrayLayout4i8",ta);var ea=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(Ji);ea.prototype.bytesPerElement=12,ni("StructArrayLayout2i4i12",ea);var ra=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=4*t,l=8*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.uint8[l+4]=n,this.uint8[l+5]=i,this.uint8[l+6]=a,this.uint8[l+7]=o,t},e}(Ji);ra.prototype.bytesPerElement=8,ni("StructArrayLayout2i4ub8",ra);var na=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,u){var c=this.length;return this.resize(c+1),this.emplace(c,t,e,r,n,i,a,o,s,l,u)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,u,c){var f=9*t,h=18*t;return this.uint16[f+0]=e,this.uint16[f+1]=r,this.uint16[f+2]=n,this.uint16[f+3]=i,this.uint16[f+4]=a,this.uint16[f+5]=o,this.uint16[f+6]=s,this.uint16[f+7]=l,this.uint8[h+16]=u,this.uint8[h+17]=c,t},e}(Ji);na.prototype.bytesPerElement=18,ni("StructArrayLayout8ui2ub18",na);var ia=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,u,c,f){var h=this.length;return this.resize(h+1),this.emplace(h,t,e,r,n,i,a,o,s,l,u,c,f)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,u,c,f,h){var p=12*t;return this.int16[p+0]=e,this.int16[p+1]=r,this.int16[p+2]=n,this.int16[p+3]=i,this.uint16[p+4]=a,this.uint16[p+5]=o,this.uint16[p+6]=s,this.uint16[p+7]=l,this.int16[p+8]=u,this.int16[p+9]=c,this.int16[p+10]=f,this.int16[p+11]=h,t},e}(Ji);ia.prototype.bytesPerElement=24,ni("StructArrayLayout4i4ui4i24",ia);var aa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.float32[i+0]=e,this.float32[i+1]=r,this.float32[i+2]=n,t},e}(Ji);aa.prototype.bytesPerElement=12,ni("StructArrayLayout3f12",aa);var oa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.uint32[r+0]=e,t},e}(Ji);oa.prototype.bytesPerElement=4,ni("StructArrayLayout1ul4",oa);var sa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l){var u=this.length;return this.resize(u+1),this.emplace(u,t,e,r,n,i,a,o,s,l)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,u){var c=10*t,f=5*t;return this.int16[c+0]=e,this.int16[c+1]=r,this.int16[c+2]=n,this.int16[c+3]=i,this.int16[c+4]=a,this.int16[c+5]=o,this.uint32[f+3]=s,this.uint16[c+8]=l,this.uint16[c+9]=u,t},e}(Ji);sa.prototype.bytesPerElement=20,ni("StructArrayLayout6i1ul2ui20",sa);var la=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(Ji);la.prototype.bytesPerElement=12,ni("StructArrayLayout2i2i2i12",la);var ua=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i){var a=this.length;return this.resize(a+1),this.emplace(a,t,e,r,n,i)},e.prototype.emplace=function(t,e,r,n,i,a){var o=4*t,s=8*t;return this.float32[o+0]=e,this.float32[o+1]=r,this.float32[o+2]=n,this.int16[s+6]=i,this.int16[s+7]=a,t},e}(Ji);ua.prototype.bytesPerElement=16,ni("StructArrayLayout2f1f2i16",ua);var ca=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=12*t,o=3*t;return this.uint8[a+0]=e,this.uint8[a+1]=r,this.float32[o+1]=n,this.float32[o+2]=i,t},e}(Ji);ca.prototype.bytesPerElement=12,ni("StructArrayLayout2ub2f12",ca);var fa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.uint16[i+0]=e,this.uint16[i+1]=r,this.uint16[i+2]=n,t},e}(Ji);fa.prototype.bytesPerElement=6,ni("StructArrayLayout3ui6",fa);var ha=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g){var y=this.length;return this.resize(y+1),this.emplace(y,t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y){var m=24*t,x=12*t,b=48*t;return this.int16[m+0]=e,this.int16[m+1]=r,this.uint16[m+2]=n,this.uint16[m+3]=i,this.uint32[x+2]=a,this.uint32[x+3]=o,this.uint32[x+4]=s,this.uint16[m+10]=l,this.uint16[m+11]=u,this.uint16[m+12]=c,this.float32[x+7]=f,this.float32[x+8]=h,this.uint8[b+36]=p,this.uint8[b+37]=d,this.uint8[b+38]=v,this.uint32[x+10]=g,this.int16[m+22]=y,t},e}(Ji);ha.prototype.bytesPerElement=48,ni("StructArrayLayout2i2ui3ul3ui2f3ub1ul1i48",ha);var pa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,w,T,k,A,M,S){var E=this.length;return this.resize(E+1),this.emplace(E,t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,w,T,k,A,M,S)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,w,T,k,A,M,S,E){var L=34*t,C=17*t;return this.int16[L+0]=e,this.int16[L+1]=r,this.int16[L+2]=n,this.int16[L+3]=i,this.int16[L+4]=a,this.int16[L+5]=o,this.int16[L+6]=s,this.int16[L+7]=l,this.uint16[L+8]=u,this.uint16[L+9]=c,this.uint16[L+10]=f,this.uint16[L+11]=h,this.uint16[L+12]=p,this.uint16[L+13]=d,this.uint16[L+14]=v,this.uint16[L+15]=g,this.uint16[L+16]=y,this.uint16[L+17]=m,this.uint16[L+18]=x,this.uint16[L+19]=b,this.uint16[L+20]=_,this.uint16[L+21]=w,this.uint16[L+22]=T,this.uint32[C+12]=k,this.float32[C+13]=A,this.float32[C+14]=M,this.float32[C+15]=S,this.float32[C+16]=E,t},e}(Ji);pa.prototype.bytesPerElement=68,ni("StructArrayLayout8i15ui1ul4f68",pa);var da=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.float32[r+0]=e,t},e}(Ji);da.prototype.bytesPerElement=4,ni("StructArrayLayout1f4",da);var va=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.int16[i+0]=e,this.int16[i+1]=r,this.int16[i+2]=n,t},e}(Ji);va.prototype.bytesPerElement=6,ni("StructArrayLayout3i6",va);var ga=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=2*t,a=4*t;return this.uint32[i+0]=e,this.uint16[a+2]=r,this.uint16[a+3]=n,t},e}(Ji);ga.prototype.bytesPerElement=8,ni("StructArrayLayout1ul2ui8",ga);var ya=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.uint16[n+0]=e,this.uint16[n+1]=r,t},e}(Ji);ya.prototype.bytesPerElement=4,ni("StructArrayLayout2ui4",ya);var ma=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.uint16[r+0]=e,t},e}(Ji);ma.prototype.bytesPerElement=2,ni("StructArrayLayout1ui2",ma);var xa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.float32[n+0]=e,this.float32[n+1]=r,t},e}(Ji);xa.prototype.bytesPerElement=8,ni("StructArrayLayout2f8",xa);var ba=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=4*t;return this.float32[a+0]=e,this.float32[a+1]=r,this.float32[a+2]=n,this.float32[a+3]=i,t},e}(Ji);ba.prototype.bytesPerElement=16,ni("StructArrayLayout4f16",ba);var _a=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorPointX:{configurable:!0},anchorPointY:{configurable:!0},x1:{configurable:!0},y1:{configurable:!0},x2:{configurable:!0},y2:{configurable:!0},featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0},anchorPoint:{configurable:!0}};return r.anchorPointX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorPointY.get=function(){return this._structArray.int16[this._pos2+1]},r.x1.get=function(){return this._structArray.int16[this._pos2+2]},r.y1.get=function(){return this._structArray.int16[this._pos2+3]},r.x2.get=function(){return this._structArray.int16[this._pos2+4]},r.y2.get=function(){return this._structArray.int16[this._pos2+5]},r.featureIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+8]},r.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.anchorPoint.get=function(){return new a(this.anchorPointX,this.anchorPointY)},Object.defineProperties(e.prototype,r),e}(Xi);_a.prototype.size=20;var wa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new _a(this,t)},e}(sa);ni("CollisionBoxArray",wa);var Ta=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},glyphStartIndex:{configurable:!0},numGlyphs:{configurable:!0},vertexStartIndex:{configurable:!0},lineStartIndex:{configurable:!0},lineLength:{configurable:!0},segment:{configurable:!0},lowerSize:{configurable:!0},upperSize:{configurable:!0},lineOffsetX:{configurable:!0},lineOffsetY:{configurable:!0},writingMode:{configurable:!0},placedOrientation:{configurable:!0},hidden:{configurable:!0},crossTileID:{configurable:!0},associatedIconIndex:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.glyphStartIndex.get=function(){return this._structArray.uint16[this._pos2+2]},r.numGlyphs.get=function(){return this._structArray.uint16[this._pos2+3]},r.vertexStartIndex.get=function(){return this._structArray.uint32[this._pos4+2]},r.lineStartIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.lineLength.get=function(){return this._structArray.uint32[this._pos4+4]},r.segment.get=function(){return this._structArray.uint16[this._pos2+10]},r.lowerSize.get=function(){return this._structArray.uint16[this._pos2+11]},r.upperSize.get=function(){return this._structArray.uint16[this._pos2+12]},r.lineOffsetX.get=function(){return this._structArray.float32[this._pos4+7]},r.lineOffsetY.get=function(){return this._structArray.float32[this._pos4+8]},r.writingMode.get=function(){return this._structArray.uint8[this._pos1+36]},r.placedOrientation.get=function(){return this._structArray.uint8[this._pos1+37]},r.placedOrientation.set=function(t){this._structArray.uint8[this._pos1+37]=t},r.hidden.get=function(){return this._structArray.uint8[this._pos1+38]},r.hidden.set=function(t){this._structArray.uint8[this._pos1+38]=t},r.crossTileID.get=function(){return this._structArray.uint32[this._pos4+10]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+10]=t},r.associatedIconIndex.get=function(){return this._structArray.int16[this._pos2+22]},Object.defineProperties(e.prototype,r),e}(Xi);Ta.prototype.size=48;var ka=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new Ta(this,t)},e}(ha);ni("PlacedSymbolArray",ka);var Aa=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},rightJustifiedTextSymbolIndex:{configurable:!0},centerJustifiedTextSymbolIndex:{configurable:!0},leftJustifiedTextSymbolIndex:{configurable:!0},verticalPlacedTextSymbolIndex:{configurable:!0},placedIconSymbolIndex:{configurable:!0},verticalPlacedIconSymbolIndex:{configurable:!0},key:{configurable:!0},textBoxStartIndex:{configurable:!0},textBoxEndIndex:{configurable:!0},verticalTextBoxStartIndex:{configurable:!0},verticalTextBoxEndIndex:{configurable:!0},iconBoxStartIndex:{configurable:!0},iconBoxEndIndex:{configurable:!0},verticalIconBoxStartIndex:{configurable:!0},verticalIconBoxEndIndex:{configurable:!0},featureIndex:{configurable:!0},numHorizontalGlyphVertices:{configurable:!0},numVerticalGlyphVertices:{configurable:!0},numIconVertices:{configurable:!0},numVerticalIconVertices:{configurable:!0},useRuntimeCollisionCircles:{configurable:!0},crossTileID:{configurable:!0},textBoxScale:{configurable:!0},textOffset0:{configurable:!0},textOffset1:{configurable:!0},collisionCircleDiameter:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.rightJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+2]},r.centerJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+3]},r.leftJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+4]},r.verticalPlacedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+5]},r.placedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+6]},r.verticalPlacedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+7]},r.key.get=function(){return this._structArray.uint16[this._pos2+8]},r.textBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.textBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+10]},r.verticalTextBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+11]},r.verticalTextBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+12]},r.iconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+13]},r.iconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+14]},r.verticalIconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+15]},r.verticalIconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+16]},r.featureIndex.get=function(){return this._structArray.uint16[this._pos2+17]},r.numHorizontalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+18]},r.numVerticalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+19]},r.numIconVertices.get=function(){return this._structArray.uint16[this._pos2+20]},r.numVerticalIconVertices.get=function(){return this._structArray.uint16[this._pos2+21]},r.useRuntimeCollisionCircles.get=function(){return this._structArray.uint16[this._pos2+22]},r.crossTileID.get=function(){return this._structArray.uint32[this._pos4+12]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+12]=t},r.textBoxScale.get=function(){return this._structArray.float32[this._pos4+13]},r.textOffset0.get=function(){return this._structArray.float32[this._pos4+14]},r.textOffset1.get=function(){return this._structArray.float32[this._pos4+15]},r.collisionCircleDiameter.get=function(){return this._structArray.float32[this._pos4+16]},Object.defineProperties(e.prototype,r),e}(Xi);Aa.prototype.size=68;var Ma=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new Aa(this,t)},e}(pa);ni("SymbolInstanceArray",Ma);var Sa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getoffsetX=function(t){return this.float32[1*t+0]},e}(da);ni("GlyphOffsetArray",Sa);var Ea=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getx=function(t){return this.int16[3*t+0]},e.prototype.gety=function(t){return this.int16[3*t+1]},e.prototype.gettileUnitDistanceFromAnchor=function(t){return this.int16[3*t+2]},e}(va);ni("SymbolLineVertexArray",Ea);var La=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0}};return r.featureIndex.get=function(){return this._structArray.uint32[this._pos4+0]},r.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+2]},r.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+3]},Object.defineProperties(e.prototype,r),e}(Xi);La.prototype.size=8;var Ca=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new La(this,t)},e}(ga);ni("FeatureIndexArray",Ca);var Pa=Ki([{name:"a_pos",components:2,type:"Int16"}],4).members,Oa=function(t){void 0===t&&(t=[]),this.segments=t};function Ia(t,e){return 256*(t=u(Math.floor(t),0,255))+u(Math.floor(e),0,255)}Oa.prototype.prepareSegment=function(t,e,r,n){var i=this.segments[this.segments.length-1];return t>Oa.MAX_VERTEX_ARRAY_LENGTH&&w("Max vertices per segment is "+Oa.MAX_VERTEX_ARRAY_LENGTH+": bucket requested "+t),(!i||i.vertexLength+t>Oa.MAX_VERTEX_ARRAY_LENGTH||i.sortKey!==n)&&(i={vertexOffset:e.length,primitiveOffset:r.length,vertexLength:0,primitiveLength:0},void 0!==n&&(i.sortKey=n),this.segments.push(i)),i},Oa.prototype.get=function(){return this.segments},Oa.prototype.destroy=function(){for(var t=0,e=this.segments;t<e.length;t+=1){var r=e[t];for(var n in r.vaos)r.vaos[n].destroy()}},Oa.simpleSegment=function(t,e,r,n){return new Oa([{vertexOffset:t,primitiveOffset:e,vertexLength:r,primitiveLength:n,vaos:{},sortKey:0}])},Oa.MAX_VERTEX_ARRAY_LENGTH=Math.pow(2,16)-1,ni("SegmentVector",Oa);var Da=Ki([{name:"a_pattern_from",components:4,type:"Uint16"},{name:"a_pattern_to",components:4,type:"Uint16"},{name:"a_pixel_ratio_from",components:1,type:"Uint8"},{name:"a_pixel_ratio_to",components:1,type:"Uint8"}]),za=e((function(t){t.exports=function(t,e){var 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r,n=t.length,i=e^n,a=0;n>=4;)r=1540483477*(65535&(r=255&t.charCodeAt(a)|(255&t.charCodeAt(++a))<<8|(255&t.charCodeAt(++a))<<16|(255&t.charCodeAt(++a))<<24))+((1540483477*(r>>>16)&65535)<<16),i=1540483477*(65535&i)+((1540483477*(i>>>16)&65535)<<16)^(r=1540483477*(65535&(r^=r>>>24))+((1540483477*(r>>>16)&65535)<<16)),n-=4,++a;switch(n){case 3:i^=(255&t.charCodeAt(a+2))<<16;case 2:i^=(255&t.charCodeAt(a+1))<<8;case 1:i=1540483477*(65535&(i^=255&t.charCodeAt(a)))+((1540483477*(i>>>16)&65535)<<16)}return i=1540483477*(65535&(i^=i>>>13))+((1540483477*(i>>>16)&65535)<<16),(i^=i>>>15)>>>0}})),Fa=za,Ba=za,Na=Ra;Fa.murmur3=Ba,Fa.murmur2=Na;var ja=function(){this.ids=[],this.positions=[],this.indexed=!1};ja.prototype.add=function(t,e,r,n){this.ids.push(Va(t)),this.positions.push(e,r,n)},ja.prototype.getPositions=function(t){for(var e=Va(t),r=0,n=this.ids.length-1;r<n;){var i=r+n>>1;this.ids[i]>=e?n=i:r=i+1}for(var a=[];this.ids[r]===e;){var 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ro=function(t,e){this.uniformNames=e.map((function(t){return"u_"+t})),this.patternFrom=null,this.patternTo=null,this.pixelRatioFrom=1,this.pixelRatioTo=1};ro.prototype.setConstantPatternPositions=function(t,e){this.pixelRatioFrom=e.pixelRatio,this.pixelRatioTo=t.pixelRatio,this.patternFrom=e.tlbr,this.patternTo=t.tlbr},ro.prototype.setUniform=function(t,e,r,n){var i="u_pattern_to"===n?this.patternTo:"u_pattern_from"===n?this.patternFrom:"u_pixel_ratio_to"===n?this.pixelRatioTo:"u_pixel_ratio_from"===n?this.pixelRatioFrom:null;i&&t.set(i)},ro.prototype.getBinding=function(t,e,r){return"u_pattern"===r.substr(0,9)?new Ja(t,e):new Ya(t,e)};var no=function(t,e,r,n){this.expression=t,this.type=r,this.maxValue=0,this.paintVertexAttributes=e.map((function(t){return{name:"a_"+t,type:"Float32",components:"color"===r?2:1,offset:0}})),this.paintVertexArray=new n};no.prototype.populatePaintArray=function(t,e,r,n,i){var a=this.paintVertexArray.length,o=this.expression.evaluate(new 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io=function(t,e,r,n,i,a){this.expression=t,this.uniformNames=e.map((function(t){return"u_"+t+"_t"})),this.type=r,this.useIntegerZoom=n,this.zoom=i,this.maxValue=0,this.paintVertexAttributes=e.map((function(t){return{name:"a_"+t,type:"Float32",components:"color"===r?4:2,offset:0}})),this.paintVertexArray=new a};io.prototype.populatePaintArray=function(t,e,r,n,i){var a=this.expression.evaluate(new Pi(this.zoom),e,{},n,[],i),o=this.expression.evaluate(new Pi(this.zoom+1),e,{},n,[],i),s=this.paintVertexArray.length;this.paintVertexArray.resize(t),this._setPaintValue(s,t,a,o)},io.prototype.updatePaintArray=function(t,e,r,n){var i=this.expression.evaluate({zoom:this.zoom},r,n),a=this.expression.evaluate({zoom:this.zoom+1},r,n);this._setPaintValue(t,e,i,a)},io.prototype._setPaintValue=function(t,e,r,n){if("color"===this.type)for(var i=to(r),a=to(n),o=t;o<e;o++)this.paintVertexArray.emplace(o,i[0],i[1],a[0],a[1]);else{for(var s=t;s<e;s++)this.paintVertexArray.emplace(s,r,n);this.maxValue=Math.max(this.maxValue,Math.abs(r),Math.abs(n))}},io.prototype.upload=function(t){this.paintVertexArray&&this.paintVertexArray.arrayBuffer&&(this.paintVertexBuffer&&this.paintVertexBuffer.buffer?this.paintVertexBuffer.updateData(this.paintVertexArray):this.paintVertexBuffer=t.createVertexBuffer(this.paintVertexArray,this.paintVertexAttributes,this.expression.isStateDependent))},io.prototype.destroy=function(){this.paintVertexBuffer&&this.paintVertexBuffer.destroy()},io.prototype.setUniform=function(t,e){var r=this.useIntegerZoom?Math.floor(e.zoom):e.zoom,n=u(this.expression.interpolationFactor(r,this.zoom,this.zoom+1),0,1);t.set(n)},io.prototype.getBinding=function(t,e,r){return new Ya(t,e)};var ao=function(t,e,r,n,i,a){this.expression=t,this.type=e,this.useIntegerZoom=r,this.zoom=n,this.layerId=a,this.zoomInPaintVertexArray=new i,this.zoomOutPaintVertexArray=new i};ao.prototype.populatePaintArray=function(t,e,r){var n=this.zoomInPaintVertexArray.length;this.zoomInPaintVertexArray.resize(t),this.zoomOutPaintVertexArray.resize(t),this._setPaintValues(n,t,e.patterns&&e.patterns[this.layerId],r)},ao.prototype.updatePaintArray=function(t,e,r,n,i){this._setPaintValues(t,e,r.patterns&&r.patterns[this.layerId],i)},ao.prototype._setPaintValues=function(t,e,r,n){if(n&&r){var i=r.min,a=r.mid,o=r.max,s=n[i],l=n[a],u=n[o];if(s&&l&&u)for(var 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t.paint._values)if(r(a)){var o=t.paint.get(a);if(o instanceof Bi&&Yr(o.property.specification)){var s=lo(a,t.type),l=o.value,u=o.property.specification.type,c=o.property.useIntegerZoom,f=o.property.specification["property-type"],h="cross-faded"===f||"cross-faded-data-driven"===f;if("constant"===l.kind)this.binders[a]=h?new ro(l.value,s):new eo(l.value,s,u),i.push("/u_"+a);else if("source"===l.kind||h){var p=uo(a,u,"source");this.binders[a]=h?new ao(l,u,c,e,p,t.id):new no(l,s,u,p),i.push("/a_"+a)}else{var d=uo(a,u,"composite");this.binders[a]=new io(l,s,u,c,e,d),i.push("/z_"+a)}}}this.cacheKey=i.sort().join("")};oo.prototype.getMaxValue=function(t){var e=this.binders[t];return e instanceof no||e instanceof io?e.maxValue:0},oo.prototype.populatePaintArrays=function(t,e,r,n,i){for(var a in this.binders){var o=this.binders[a];(o instanceof no||o instanceof io||o instanceof ao)&&o.populatePaintArray(t,e,r,n,i)}},oo.prototype.setConstantPatternPositions=function(t,e){for(var r in 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i=0,a=e;i<a.length;i+=1){var o=a[i];this.programConfigurations[o.id]=new oo(o,r,n,t)}this.needsUpload=!1,this._featureMap=new ja,this._bufferOffset=0};function lo(t,e){return{"text-opacity":["opacity"],"icon-opacity":["opacity"],"text-color":["fill_color"],"icon-color":["fill_color"],"text-halo-color":["halo_color"],"icon-halo-color":["halo_color"],"text-halo-blur":["halo_blur"],"icon-halo-blur":["halo_blur"],"text-halo-width":["halo_width"],"icon-halo-width":["halo_width"],"line-gap-width":["gapwidth"],"line-pattern":["pattern_to","pattern_from","pixel_ratio_to","pixel_ratio_from"],"fill-pattern":["pattern_to","pattern_from","pixel_ratio_to","pixel_ratio_from"],"fill-extrusion-pattern":["pattern_to","pattern_from","pixel_ratio_to","pixel_ratio_from"]}[t]||[t.replace(e+"-","").replace(/-/g,"_")]}function uo(t,e,r){var n={color:{source:xa,composite:ba},number:{source:da,composite:xa}},i=function(t){return{"line-pattern":{source:na,composite:na},"fill-pattern":{source:na,composite:na},"fill-extrusion-pattern":{source:na,composite:na}}[t]}(t);return i&&i[r]||n[e][r]}so.prototype.populatePaintArrays=function(t,e,r,n,i,a){for(var o in this.programConfigurations)this.programConfigurations[o].populatePaintArrays(t,e,n,i,a);void 0!==e.id&&this._featureMap.add(e.id,r,this._bufferOffset,t),this._bufferOffset=t,this.needsUpload=!0},so.prototype.updatePaintArrays=function(t,e,r,n){for(var i=0,a=r;i<a.length;i+=1){var o=a[i];this.needsUpload=this.programConfigurations[o.id].updatePaintArrays(t,this._featureMap,e,o,n)||this.needsUpload}},so.prototype.get=function(t){return this.programConfigurations[t]},so.prototype.upload=function(t){if(this.needsUpload){for(var e in this.programConfigurations)this.programConfigurations[e].upload(t);this.needsUpload=!1}},so.prototype.destroy=function(){for(var t in this.programConfigurations)this.programConfigurations[t].destroy()},ni("ConstantBinder",eo),ni("CrossFadedConstantBinder",ro),ni("SourceExpressionBinder",no),ni("CrossFadedCompositeBinder",ao),ni("CompositeExpressionBinder",io),ni("ProgramConfiguration",oo,{omit:["_buffers"]}),ni("ProgramConfigurationSet",so);var co=8192;var fo,ho=(fo=15,{min:-1*Math.pow(2,fo-1),max:Math.pow(2,fo-1)-1});function po(t){for(var e=co/t.extent,r=t.loadGeometry(),n=0;n<r.length;n++)for(var i=r[n],a=0;a<i.length;a++){var o=i[a];o.x=Math.round(o.x*e),o.y=Math.round(o.y*e),(o.x<ho.min||o.x>ho.max||o.y<ho.min||o.y>ho.max)&&(w("Geometry exceeds allowed extent, reduce your vector tile buffer size"),o.x=u(o.x,ho.min,ho.max),o.y=u(o.y,ho.min,ho.max))}return r}function vo(t,e,r,n,i){t.emplaceBack(2*e+(n+1)/2,2*r+(i+1)/2)}var go=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return 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u=t.readVarint();n=7&u,i=u>>3}if(i--,1===n||2===n)o+=t.readSVarint(),s+=t.readSVarint(),1===n&&(e&&l.push(e),e=[]),e.push(new a(o,s));else{if(7!==n)throw new Error("unknown command "+n);e&&e.push(e[0].clone())}}return e&&l.push(e),l},Hs.prototype.bbox=function(){var t=this._pbf;t.pos=this._geometry;for(var e=t.readVarint()+t.pos,r=1,n=0,i=0,a=0,o=1/0,s=-1/0,l=1/0,u=-1/0;t.pos<e;){if(n<=0){var c=t.readVarint();r=7&c,n=c>>3}if(n--,1===r||2===r)(i+=t.readSVarint())<o&&(o=i),i>s&&(s=i),(a+=t.readSVarint())<l&&(l=a),a>u&&(u=a);else if(7!==r)throw new Error("unknown command "+r)}return[o,l,s,u]},Hs.prototype.toGeoJSON=function(t,e,r){var n,i,a=this.extent*Math.pow(2,r),o=this.extent*t,s=this.extent*e,l=this.loadGeometry(),u=Hs.types[this.type];function c(t){for(var e=0;e<t.length;e++){var r=t[e],n=180-360*(r.y+s)/a;t[e]=[360*(r.x+o)/a-180,360/Math.PI*Math.atan(Math.exp(n*Math.PI/180))-90]}}switch(this.type){case 1:var f=[];for(n=0;n<l.length;n++)f[n]=l[n][0];c(l=f);break;case 2:for(n=0;n<l.length;n++)c(l[n]);break;case 3:for(l=function(t){var e=t.length;if(e<=1)return[t];for(var r,n,i=[],a=0;a<e;a++){var o=Gs(t[a]);0!==o&&(void 0===n&&(n=o<0),n===o<0?(r&&i.push(r),r=[t[a]]):r.push(t[a]))}return r&&i.push(r),i}(l),n=0;n<l.length;n++)for(i=0;i<l[n].length;i++)c(l[n][i])}1===l.length?l=l[0]:u="Multi"+u;var h={type:"Feature",geometry:{type:u,coordinates:l},properties:this.properties};return"id"in this&&(h.id=this.id),h};var Zs=Ys;function Ys(t,e){this.version=1,this.name=null,this.extent=4096,this.length=0,this._pbf=t,this._keys=[],this._values=[],this._features=[],t.readFields(Ws,this,e),this.length=this._features.length}function Ws(t,e,r){15===t?e.version=r.readVarint():1===t?e.name=r.readString():5===t?e.extent=r.readVarint():2===t?e._features.push(r.pos):3===t?e._keys.push(r.readString()):4===t&&e._values.push(function(t){for(var e=null,r=t.readVarint()+t.pos;t.pos<r;){var n=t.readVarint()>>3;e=1===n?t.readString():2===n?t.readFloat():3===n?t.readDouble():4===n?t.readVarint64():5===n?t.readVarint():6===n?t.readSVarint():7===n?t.readBoolean():null}return e}(r))}function Xs(t,e,r){if(3===t){var n=new Zs(r,r.readVarint()+r.pos);n.length&&(e[n.name]=n)}}Ys.prototype.feature=function(t){if(t<0||t>=this._features.length)throw new Error("feature index out of bounds");this._pbf.pos=this._features[t];var e=this._pbf.readVarint()+this._pbf.pos;return new Vs(this._pbf,e,this.extent,this._keys,this._values)};var Js={VectorTile:function(t,e){this.layers=t.readFields(Xs,{},e)},VectorTileFeature:Vs,VectorTileLayer:Zs},Ks=Js.VectorTileFeature.types,$s=Math.pow(2,13);function Qs(t,e,r,n,i,a,o,s){t.emplaceBack(e,r,2*Math.floor(n*$s)+o,i*$s*2,a*$s*2,Math.round(s))}var tl=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new ea,this.indexArray=new fa,this.programConfigurations=new so(Us,t.layers,t.zoom),this.segments=new Oa,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};function el(t,e){return t.x===e.x&&(t.x<0||t.x>co)||t.y===e.y&&(t.y<0||t.y>co)}tl.prototype.populate=function(t,e,r){this.features=[],this.hasPattern=zs("fill-extrusion",this.layers,e);for(var n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.feature,s=a.id,l=a.index,u=a.sourceLayerIndex,c=this.layers[0]._featureFilter.needGeometry,f={type:o.type,id:s,properties:o.properties,geometry:c?po(o):[]};if(this.layers[0]._featureFilter.filter(new Pi(this.zoom),f,r)){var h={id:s,sourceLayerIndex:u,index:l,geometry:c?f.geometry:po(o),properties:o.properties,type:o.type,patterns:{}};void 0!==o.id&&(h.id=o.id),this.hasPattern?this.features.push(Rs("fill-extrusion",this.layers,h,this.zoom,e)):this.addFeature(h,h.geometry,l,r,{}),e.featureIndex.insert(o,h.geometry,l,u,this.index,!0)}}},tl.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.features;n<i.length;n+=1){var a=i[n],o=a.geometry;this.addFeature(a,o,a.index,e,r)}},tl.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},tl.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},tl.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},tl.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,Us),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},tl.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},tl.prototype.addFeature=function(t,e,r,n,i){for(var a=0,o=Is(e,500);a<o.length;a+=1){for(var s=o[a],l=0,u=0,c=s;u<c.length;u+=1)l+=c[u].length;for(var f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray),h=0,p=s;h<p.length;h+=1){var d=p[h];if(0!==d.length&&!((O=d).every((function(t){return t.x<0}))||O.every((function(t){return t.x>co}))||O.every((function(t){return t.y<0}))||O.every((function(t){return t.y>co}))))for(var v=0,g=0;g<d.length;g++){var y=d[g];if(g>=1){var m=d[g-1];if(!el(y,m)){f.vertexLength+4>Oa.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));var x=y.sub(m)._perp()._unit(),b=m.dist(y);v+b>32768&&(v=0),Qs(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,0,v),Qs(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,1,v),v+=b,Qs(this.layoutVertexArray,m.x,m.y,x.x,x.y,0,0,v),Qs(this.layoutVertexArray,m.x,m.y,x.x,x.y,0,1,v);var _=f.vertexLength;this.indexArray.emplaceBack(_,_+2,_+1),this.indexArray.emplaceBack(_+1,_+2,_+3),f.vertexLength+=4,f.primitiveLength+=2}}}}if(f.vertexLength+l>Oa.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(l,this.layoutVertexArray,this.indexArray)),"Polygon"===Ks[t.type]){for(var w=[],T=[],k=f.vertexLength,A=0,M=s;A<M.length;A+=1){var S=M[A];if(0!==S.length){S!==s[0]&&T.push(w.length/2);for(var E=0;E<S.length;E++){var L=S[E];Qs(this.layoutVertexArray,L.x,L.y,0,0,1,1,0),w.push(L.x),w.push(L.y)}}}for(var C=es(w,T),P=0;P<C.length;P+=3)this.indexArray.emplaceBack(k+C[P],k+C[P+2],k+C[P+1]);f.primitiveLength+=C.length/3,f.vertexLength+=l}}var O;this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},ni("FillExtrusionBucket",tl,{omit:["layers","features"]});var rl={paint:new Gi({"fill-extrusion-opacity":new ji(Dt["paint_fill-extrusion"]["fill-extrusion-opacity"]),"fill-extrusion-color":new Ui(Dt["paint_fill-extrusion"]["fill-extrusion-color"]),"fill-extrusion-translate":new ji(Dt["paint_fill-extrusion"]["fill-extrusion-translate"]),"fill-extrusion-translate-anchor":new ji(Dt["paint_fill-extrusion"]["fill-extrusion-translate-anchor"]),"fill-extrusion-pattern":new Vi(Dt["paint_fill-extrusion"]["fill-extrusion-pattern"]),"fill-extrusion-height":new Ui(Dt["paint_fill-extrusion"]["fill-extrusion-height"]),"fill-extrusion-base":new Ui(Dt["paint_fill-extrusion"]["fill-extrusion-base"]),"fill-extrusion-vertical-gradient":new ji(Dt["paint_fill-extrusion"]["fill-extrusion-vertical-gradient"])})},nl=function(t){function e(e){t.call(this,e,rl)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.createBucket=function(t){return new tl(t)},e.prototype.queryRadius=function(){return Lo(this.paint.get("fill-extrusion-translate"))},e.prototype.is3D=function(){return!0},e.prototype.queryIntersectsFeature=function(t,e,r,n,i,o,s,l){var u=Co(t,this.paint.get("fill-extrusion-translate"),this.paint.get("fill-extrusion-translate-anchor"),o.angle,s),c=this.paint.get("fill-extrusion-height").evaluate(e,r),f=this.paint.get("fill-extrusion-base").evaluate(e,r),h=function(t,e,r,n){for(var i=[],o=0,s=t;o<s.length;o+=1){var l=s[o],u=[l.x,l.y,n,1];No(u,u,e),i.push(new a(u[0]/u[3],u[1]/u[3]))}return i}(u,l,0,0),p=function(t,e,r,n){for(var i=[],o=[],s=n[8]*e,l=n[9]*e,u=n[10]*e,c=n[11]*e,f=n[8]*r,h=n[9]*r,p=n[10]*r,d=n[11]*r,v=0,g=t;v<g.length;v+=1){for(var y=[],m=[],x=0,b=g[v];x<b.length;x+=1){var _=b[x],w=_.x,T=_.y,k=n[0]*w+n[4]*T+n[12],A=n[1]*w+n[5]*T+n[13],M=n[2]*w+n[6]*T+n[14],S=n[3]*w+n[7]*T+n[15],E=M+u,L=S+c,C=k+f,P=A+h,O=M+p,I=S+d,D=new a((k+s)/L,(A+l)/L);D.z=E/L,y.push(D);var z=new a(C/I,P/I);z.z=O/I,m.push(z)}i.push(y),o.push(m)}return[i,o]}(n,f,c,l);return function(t,e,r){var n=1/0;xo(r,e)&&(n=al(r,e[0]));for(var i=0;i<e.length;i++)for(var a=e[i],o=t[i],s=0;s<a.length-1;s++){var l=a[s],u=a[s+1],c=o[s],f=[l,u,o[s+1],c,l];yo(r,f)&&(n=Math.min(n,al(r,f)))}return n!==1/0&&n}(p[0],p[1],h)},e}(Yi);function il(t,e){return t.x*e.x+t.y*e.y}function al(t,e){if(1===t.length){for(var r,n=0,i=e[n++];!r||i.equals(r);)if(!(r=e[n++]))return 1/0;for(;n<e.length;n++){var a=e[n],o=t[0],s=r.sub(i),l=a.sub(i),u=o.sub(i),c=il(s,s),f=il(s,l),h=il(l,l),p=il(u,s),d=il(u,l),v=c*h-f*f,g=(h*p-f*d)/v,y=(c*d-f*p)/v,m=1-g-y,x=i.z*m+r.z*g+a.z*y;if(isFinite(x))return x}return 1/0}for(var b=1/0,_=0,w=e;_<w.length;_+=1){var T=w[_];b=Math.min(b,T.z)}return b}var ol=Ki([{name:"a_pos_normal",components:2,type:"Int16"},{name:"a_data",components:4,type:"Uint8"}],4).members,sl=Js.VectorTileFeature.types,ll=Math.cos(Math.PI/180*37.5),ul=Math.pow(2,14)/.5,cl=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.patternFeatures=[],this.layoutVertexArray=new ra,this.indexArray=new fa,this.programConfigurations=new so(ol,t.layers,t.zoom),this.segments=new Oa,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};cl.prototype.populate=function(t,e,r){this.hasPattern=zs("line",this.layers,e);for(var n=this.layers[0].layout.get("line-sort-key"),i=[],a=0,o=t;a<o.length;a+=1){var s=o[a],l=s.feature,u=s.id,c=s.index,f=s.sourceLayerIndex,h=this.layers[0]._featureFilter.needGeometry,p={type:l.type,id:u,properties:l.properties,geometry:h?po(l):[]};if(this.layers[0]._featureFilter.filter(new Pi(this.zoom),p,r)){h||(p.geometry=po(l));var d=n?n.evaluate(p,{},r):void 0,v={id:u,properties:l.properties,type:l.type,sourceLayerIndex:f,index:c,geometry:p.geometry,patterns:{},sortKey:d};i.push(v)}}n&&i.sort((function(t,e){return t.sortKey-e.sortKey}));for(var g=0,y=i;g<y.length;g+=1){var m=y[g],x=m,b=x.geometry,_=x.index,w=x.sourceLayerIndex;if(this.hasPattern){var T=Rs("line",this.layers,m,this.zoom,e);this.patternFeatures.push(T)}else this.addFeature(m,b,_,r,{});var k=t[_].feature;e.featureIndex.insert(k,b,_,w,this.index)}},cl.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},cl.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.patternFeatures;n<i.length;n+=1){var a=i[n];this.addFeature(a,a.geometry,a.index,e,r)}},cl.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},cl.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},cl.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,ol),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},cl.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},cl.prototype.addFeature=function(t,e,r,n,i){for(var a=this.layers[0].layout,o=a.get("line-join").evaluate(t,{}),s=a.get("line-cap"),l=a.get("line-miter-limit"),u=a.get("line-round-limit"),c=0,f=e;c<f.length;c+=1){var h=f[c];this.addLine(h,t,o,s,l,u)}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},cl.prototype.addLine=function(t,e,r,n,i,a){if(this.distance=0,this.scaledDistance=0,this.totalDistance=0,e.properties&&e.properties.hasOwnProperty("mapbox_clip_start")&&e.properties.hasOwnProperty("mapbox_clip_end")){this.clipStart=+e.properties.mapbox_clip_start,this.clipEnd=+e.properties.mapbox_clip_end;for(var o=0;o<t.length-1;o++)this.totalDistance+=t[o].dist(t[o+1]);this.updateScaledDistance()}for(var s="Polygon"===sl[e.type],l=t.length;l>=2&&t[l-1].equals(t[l-2]);)l--;for(var u=0;u<l-1&&t[u].equals(t[u+1]);)u++;if(!(l<(s?3:2))){"bevel"===r&&(i=1.05);var c,f=this.overscaling<=16?15*co/(512*this.overscaling):0,h=this.segments.prepareSegment(10*l,this.layoutVertexArray,this.indexArray),p=void 0,d=void 0,v=void 0,g=void 0;this.e1=this.e2=-1,s&&(c=t[l-2],g=t[u].sub(c)._unit()._perp());for(var y=u;y<l;y++)if(!(d=y===l-1?s?t[u+1]:void 0:t[y+1])||!t[y].equals(d)){g&&(v=g),c&&(p=c),c=t[y],g=d?d.sub(c)._unit()._perp():v;var m=(v=v||g).add(g);0===m.x&&0===m.y||m._unit();var x=v.x*g.x+v.y*g.y,b=m.x*g.x+m.y*g.y,_=0!==b?1/b:1/0,w=2*Math.sqrt(2-2*b),T=b<ll&&p&&d,k=v.x*g.y-v.y*g.x>0;if(T&&y>u){var A=c.dist(p);if(A>2*f){var M=c.sub(c.sub(p)._mult(f/A)._round());this.updateDistance(p,M),this.addCurrentVertex(M,v,0,0,h),p=M}}var S=p&&d,E=S?r:s?"butt":n;if(S&&"round"===E&&(_<a?E="miter":_<=2&&(E="fakeround")),"miter"===E&&_>i&&(E="bevel"),"bevel"===E&&(_>2&&(E="flipbevel"),_<i&&(E="miter")),p&&this.updateDistance(p,c),"miter"===E)m._mult(_),this.addCurrentVertex(c,m,0,0,h);else if("flipbevel"===E){if(_>100)m=g.mult(-1);else{var L=_*v.add(g).mag()/v.sub(g).mag();m._perp()._mult(L*(k?-1:1))}this.addCurrentVertex(c,m,0,0,h),this.addCurrentVertex(c,m.mult(-1),0,0,h)}else if("bevel"===E||"fakeround"===E){var C=-Math.sqrt(_*_-1),P=k?C:0,O=k?0:C;if(p&&this.addCurrentVertex(c,v,P,O,h),"fakeround"===E)for(var I=Math.round(180*w/Math.PI/20),D=1;D<I;D++){var z=D/I;if(.5!==z){var R=z-.5;z+=z*R*(z-1)*((1.0904+x*(x*(3.55645-1.43519*x)-3.2452))*R*R+(.848013+x*(.215638*x-1.06021)))}var F=g.sub(v)._mult(z)._add(v)._unit()._mult(k?-1:1);this.addHalfVertex(c,F.x,F.y,!1,k,0,h)}d&&this.addCurrentVertex(c,g,-P,-O,h)}else if("butt"===E)this.addCurrentVertex(c,m,0,0,h);else if("square"===E){var B=p?1:-1;this.addCurrentVertex(c,m,B,B,h)}else"round"===E&&(p&&(this.addCurrentVertex(c,v,0,0,h),this.addCurrentVertex(c,v,1,1,h,!0)),d&&(this.addCurrentVertex(c,g,-1,-1,h,!0),this.addCurrentVertex(c,g,0,0,h)));if(T&&y<l-1){var N=c.dist(d);if(N>2*f){var j=c.add(d.sub(c)._mult(f/N)._round());this.updateDistance(c,j),this.addCurrentVertex(j,g,0,0,h),c=j}}}}},cl.prototype.addCurrentVertex=function(t,e,r,n,i,a){void 0===a&&(a=!1);var o=e.x+e.y*r,s=e.y-e.x*r,l=-e.x+e.y*n,u=-e.y-e.x*n;this.addHalfVertex(t,o,s,a,!1,r,i),this.addHalfVertex(t,l,u,a,!0,-n,i),this.distance>ul/2&&0===this.totalDistance&&(this.distance=0,this.addCurrentVertex(t,e,r,n,i,a))},cl.prototype.addHalfVertex=function(t,e,r,n,i,a,o){var s=t.x,l=t.y,u=.5*this.scaledDistance;this.layoutVertexArray.emplaceBack((s<<1)+(n?1:0),(l<<1)+(i?1:0),Math.round(63*e)+128,Math.round(63*r)+128,1+(0===a?0:a<0?-1:1)|(63&u)<<2,u>>6);var c=o.vertexLength++;this.e1>=0&&this.e2>=0&&(this.indexArray.emplaceBack(this.e1,this.e2,c),o.primitiveLength++),i?this.e2=c:this.e1=c},cl.prototype.updateScaledDistance=function(){this.scaledDistance=this.totalDistance>0?(this.clipStart+(this.clipEnd-this.clipStart)*this.distance/this.totalDistance)*(ul-1):this.distance},cl.prototype.updateDistance=function(t,e){this.distance+=t.dist(e),this.updateScaledDistance()},ni("LineBucket",cl,{omit:["layers","patternFeatures"]});var fl=new Gi({"line-cap":new 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t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.possiblyEvaluate=function(e,r){return r=new Pi(Math.floor(r.zoom),{now:r.now,fadeDuration:r.fadeDuration,zoomHistory:r.zoomHistory,transition:r.transition}),t.prototype.possiblyEvaluate.call(this,e,r)},e.prototype.evaluate=function(e,r,n,i){return r=f({},r,{zoom:Math.floor(r.zoom)}),t.prototype.evaluate.call(this,e,r,n,i)},e}(Ui),dl=new pl(hl.paint.properties["line-width"].specification);dl.useIntegerZoom=!0;var vl=function(t){function e(e){t.call(this,e,hl)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._handleSpecialPaintPropertyUpdate=function(t){"line-gradient"===t&&this._updateGradient()},e.prototype._updateGradient=function(){var 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n=this.pos-r;n>=128&&Dl(r,n,this),this.pos=r-1,this.writeVarint(n),this.pos+=n},writeMessage:function(t,e,r){this.writeTag(t,El.Bytes),this.writeRawMessage(e,r)},writePackedVarint:function(t,e){e.length&&this.writeMessage(t,zl,e)},writePackedSVarint:function(t,e){e.length&&this.writeMessage(t,Rl,e)},writePackedBoolean:function(t,e){e.length&&this.writeMessage(t,Nl,e)},writePackedFloat:function(t,e){e.length&&this.writeMessage(t,Fl,e)},writePackedDouble:function(t,e){e.length&&this.writeMessage(t,Bl,e)},writePackedFixed32:function(t,e){e.length&&this.writeMessage(t,jl,e)},writePackedSFixed32:function(t,e){e.length&&this.writeMessage(t,Ul,e)},writePackedFixed64:function(t,e){e.length&&this.writeMessage(t,Vl,e)},writePackedSFixed64:function(t,e){e.length&&this.writeMessage(t,Hl,e)},writeBytesField:function(t,e){this.writeTag(t,El.Bytes),this.writeBytes(e)},writeFixed32Field:function(t,e){this.writeTag(t,El.Fixed32),this.writeFixed32(e)},writeSFixed32Field:function(t,e){this.writeTag(t,El.Fixed32),this.writeSFixed32(e)},writeFixed64Field:function(t,e){this.writeTag(t,El.Fixed64),this.writeFixed64(e)},writeSFixed64Field:function(t,e){this.writeTag(t,El.Fixed64),this.writeSFixed64(e)},writeVarintField:function(t,e){this.writeTag(t,El.Varint),this.writeVarint(e)},writeSVarintField:function(t,e){this.writeTag(t,El.Varint),this.writeSVarint(e)},writeStringField:function(t,e){this.writeTag(t,El.Bytes),this.writeString(e)},writeFloatField:function(t,e){this.writeTag(t,El.Fixed32),this.writeFloat(e)},writeDoubleField:function(t,e){this.writeTag(t,El.Fixed64),this.writeDouble(e)},writeBooleanField:function(t,e){this.writeVarintField(t,Boolean(e))}};var Yl=3;function Wl(t,e,r){1===t&&r.readMessage(Xl,e)}function Xl(t,e,r){if(3===t){var n=r.readMessage(Jl,{}),i=n.id,a=n.bitmap,o=n.width,s=n.height,l=n.left,u=n.top,c=n.advance;e.push({id:i,bitmap:new Yo({width:o+2*Yl,height:s+2*Yl},a),metrics:{width:o,height:s,left:l,top:u,advance:c}})}}function Jl(t,e,r){1===t?e.id=r.readVarint():2===t?e.bitmap=r.readBytes():3===t?e.width=r.readVarint():4===t?e.height=r.readVarint():5===t?e.left=r.readSVarint():6===t?e.top=r.readSVarint():7===t&&(e.advance=r.readVarint())}var Kl=Yl;function $l(t){for(var e=0,r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];e+=a.w*a.h,r=Math.max(r,a.w)}t.sort((function(t,e){return e.h-t.h}));for(var o=[{x:0,y:0,w:Math.max(Math.ceil(Math.sqrt(e/.95)),r),h:1/0}],s=0,l=0,u=0,c=t;u<c.length;u+=1)for(var f=c[u],h=o.length-1;h>=0;h--){var p=o[h];if(!(f.w>p.w||f.h>p.h)){if(f.x=p.x,f.y=p.y,l=Math.max(l,f.y+f.h),s=Math.max(s,f.x+f.w),f.w===p.w&&f.h===p.h){var d=o.pop();h<o.length&&(o[h]=d)}else 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Wo({width:o||1,height:s||1});for(var u in t){var c=t[u],f=r[u].paddedRect;Wo.copy(c.data,l,{x:0,y:0},{x:f.x+Ql,y:f.y+Ql},c.data)}for(var h in e){var p=e[h],d=n[h].paddedRect,v=d.x+Ql,g=d.y+Ql,y=p.data.width,m=p.data.height;Wo.copy(p.data,l,{x:0,y:0},{x:v,y:g},p.data),Wo.copy(p.data,l,{x:0,y:m-1},{x:v,y:g-1},{width:y,height:1}),Wo.copy(p.data,l,{x:0,y:0},{x:v,y:g+m},{width:y,height:1}),Wo.copy(p.data,l,{x:y-1,y:0},{x:v-1,y:g},{width:1,height:m}),Wo.copy(p.data,l,{x:0,y:0},{x:v+y,y:g},{width:1,height:m})}this.image=l,this.iconPositions=r,this.patternPositions=n};ru.prototype.addImages=function(t,e,r){for(var n in t){var i=t[n],a={x:0,y:0,w:i.data.width+2*Ql,h:i.data.height+2*Ql};r.push(a),e[n]=new tu(a,i),i.hasRenderCallback&&this.haveRenderCallbacks.push(n)}},ru.prototype.patchUpdatedImages=function(t,e){for(var r in t.dispatchRenderCallbacks(this.haveRenderCallbacks),t.updatedImages)this.patchUpdatedImage(this.iconPositions[r],t.getImage(r),e),this.patchUpdatedImage(this.patternPositions[r],t.getImage(r),e)},ru.prototype.patchUpdatedImage=function(t,e,r){if(t&&e&&t.version!==e.version){t.version=e.version;var n=t.tl,i=n[0],a=n[1];r.update(e.data,void 0,{x:i,y:a})}},ni("ImagePosition",tu),ni("ImageAtlas",ru);var nu={horizontal:1,vertical:2,horizontalOnly:3},iu=-17;var au=function(){this.scale=1,this.fontStack="",this.imageName=null};au.forText=function(t,e){var r=new au;return r.scale=t||1,r.fontStack=e,r},au.forImage=function(t){var e=new au;return e.imageName=t,e};var ou=function(){this.text="",this.sectionIndex=[],this.sections=[],this.imageSectionID=null};function su(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v){var g,y=ou.fromFeature(t,i);f===nu.vertical&&y.verticalizePunctuation();var m=Ci.processBidirectionalText,x=Ci.processStyledBidirectionalText;if(m&&1===y.sections.length){g=[];for(var b=0,_=m(y.toString(),vu(y,u,a,e,n,p,d));b<_.length;b+=1){var w=_[b],T=new ou;T.text=w,T.sections=y.sections;for(var k=0;k<w.length;k++)T.sectionIndex.push(0);g.push(T)}}else if(x){g=[];for(var A=0,M=x(y.text,y.sectionIndex,vu(y,u,a,e,n,p,d));A<M.length;A+=1){var S=M[A],E=new ou;E.text=S[0],E.sectionIndex=S[1],E.sections=y.sections,g.push(E)}}else g=function(t,e){for(var r=[],n=t.text,i=0,a=0,o=e;a<o.length;a+=1){var s=o[a];r.push(t.substring(i,s)),i=s}return i<n.length&&r.push(t.substring(i,n.length)),r}(y,vu(y,u,a,e,n,p,d));var L=[],C={positionedLines:L,text:y.toString(),top:c[1],bottom:c[1],left:c[0],right:c[0],writingMode:f,iconsInText:!1,verticalizable:!1};return function(t,e,r,n,i,a,o,s,l,u,c,f){for(var h=0,p=iu,d=0,v=0,g="right"===s?1:"left"===s?0:.5,y=0,m=0,x=i;m<x.length;m+=1){var b=x[m];b.trim();var _=b.getMaxScale(),w=(_-1)*kl,T={positionedGlyphs:[],lineOffset:0};t.positionedLines[y]=T;var k=T.positionedGlyphs,A=0;if(b.length()){for(var M=0;M<b.length();M++){var S=b.getSection(M),E=b.getSectionIndex(M),L=b.getCharCode(M),C=0,P=null,O=null,I=null,D=kl,z=!(l===nu.horizontal||!c&&!hi(L)||c&&(lu[L]||di(L)));if(S.imageName){var R=n[S.imageName];if(!R)continue;I=S.imageName,t.iconsInText=t.iconsInText||!0,O=R.paddedRect;var F=R.displaySize;S.scale=S.scale*kl/f,P={width:F[0],height:F[1],left:Ql,top:-Kl,advance:z?F[1]:F[0]},C=w+(kl-F[1]*S.scale),D=P.advance;var B=z?F[0]*S.scale-kl*_:F[1]*S.scale-kl*_;B>0&&B>A&&(A=B)}else{var N=r[S.fontStack],j=N&&N[L];if(j&&j.rect)O=j.rect,P=j.metrics;else{var U=e[S.fontStack],V=U&&U[L];if(!V)continue;P=V.metrics}C=(_-S.scale)*kl}z?(t.verticalizable=!0,k.push({glyph:L,imageName:I,x:h,y:p+C,vertical:z,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:O}),h+=D*S.scale+u):(k.push({glyph:L,imageName:I,x:h,y:p+C,vertical:z,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:O}),h+=P.advance*S.scale+u)}if(0!==k.length){var H=h-u;d=Math.max(H,d),yu(k,0,k.length-1,g,A)}h=0;var q=a*_+A;T.lineOffset=Math.max(A,w),p+=q,v=Math.max(q,v),++y}else p+=a,++y}var G=p-iu,Z=gu(o),Y=Z.horizontalAlign,W=Z.verticalAlign;(function(t,e,r,n,i,a,o,s,l){var u=(e-r)*i,c=0;c=a!==o?-s*n-iu:(-n*l+.5)*o;for(var f=0,h=t;f<h.length;f+=1)for(var p=0,d=h[f].positionedGlyphs;p<d.length;p+=1){var v=d[p];v.x+=u,v.y+=c}})(t.positionedLines,g,Y,W,d,v,a,G,i.length),t.top+=-W*G,t.bottom=t.top+G,t.left+=-Y*d,t.right=t.left+d}(C,e,r,n,g,o,s,l,f,u,h,v),!function(t){for(var e=0,r=t;e<r.length;e+=1)if(0!==r[e].positionedGlyphs.length)return!1;return!0}(L)&&C}ou.fromFeature=function(t,e){for(var r=new ou,n=0;n<t.sections.length;n++){var i=t.sections[n];i.image?r.addImageSection(i):r.addTextSection(i,e)}return r},ou.prototype.length=function(){return this.text.length},ou.prototype.getSection=function(t){return this.sections[this.sectionIndex[t]]},ou.prototype.getSectionIndex=function(t){return this.sectionIndex[t]},ou.prototype.getCharCode=function(t){return this.text.charCodeAt(t)},ou.prototype.verticalizePunctuation=function(){this.text=function(t){for(var e="",r=0;r<t.length;r++){var n=t.charCodeAt(r+1)||null,i=t.charCodeAt(r-1)||null;n&&pi(n)&&!Tl[t[r+1]]||i&&pi(i)&&!Tl[t[r-1]]||!Tl[t[r]]?e+=t[r]:e+=Tl[t[r]]}return e}(this.text)},ou.prototype.trim=function(){for(var t=0,e=0;e<this.text.length&&lu[this.text.charCodeAt(e)];e++)t++;for(var r=this.text.length,n=this.text.length-1;n>=0&&n>=t&&lu[this.text.charCodeAt(n)];n--)r--;this.text=this.text.substring(t,r),this.sectionIndex=this.sectionIndex.slice(t,r)},ou.prototype.substring=function(t,e){var r=new ou;return r.text=this.text.substring(t,e),r.sectionIndex=this.sectionIndex.slice(t,e),r.sections=this.sections,r},ou.prototype.toString=function(){return this.text},ou.prototype.getMaxScale=function(){var t=this;return this.sectionIndex.reduce((function(e,r){return Math.max(e,t.sections[r].scale)}),0)},ou.prototype.addTextSection=function(t,e){this.text+=t.text,this.sections.push(au.forText(t.scale,t.fontStack||e));for(var r=this.sections.length-1,n=0;n<t.text.length;++n)this.sectionIndex.push(r)},ou.prototype.addImageSection=function(t){var e=t.image?t.image.name:"";if(0!==e.length){var r=this.getNextImageSectionCharCode();r?(this.text+=String.fromCharCode(r),this.sections.push(au.forImage(e)),this.sectionIndex.push(this.sections.length-1)):w("Reached maximum number of images 6401")}else w("Can't add FormattedSection with an empty image.")},ou.prototype.getNextImageSectionCharCode=function(){return this.imageSectionID?this.imageSectionID>=63743?null:++this.imageSectionID:(this.imageSectionID=57344,this.imageSectionID)};var lu={9:!0,10:!0,11:!0,12:!0,13:!0,32:!0},uu={};function cu(t,e,r,n,i,a){if(e.imageName){var o=n[e.imageName];return o?o.displaySize[0]*e.scale*kl/a+i:0}var s=r[e.fontStack],l=s&&s[t];return l?l.metrics.advance*e.scale+i:0}function fu(t,e,r,n){var i=Math.pow(t-e,2);return n?t<e?i/2:2*i:i+Math.abs(r)*r}function hu(t,e,r){var n=0;return 10===t&&(n-=1e4),r&&(n+=150),40!==t&&65288!==t||(n+=50),41!==e&&65289!==e||(n+=50),n}function pu(t,e,r,n,i,a){for(var o=null,s=fu(e,r,i,a),l=0,u=n;l<u.length;l+=1){var c=u[l],f=fu(e-c.x,r,i,a)+c.badness;f<=s&&(o=c,s=f)}return{index:t,x:e,priorBreak:o,badness:s}}function du(t){return t?du(t.priorBreak).concat(t.index):[]}function vu(t,e,r,n,i,a,o){if("point"!==a)return[];if(!t)return[];for(var s=[],l=function(t,e,r,n,i,a){for(var o=0,s=0;s<t.length();s++){var l=t.getSection(s);o+=cu(t.getCharCode(s),l,n,i,e,a)}return o/Math.max(1,Math.ceil(o/r))}(t,e,r,n,i,o),u=t.text.indexOf("​")>=0,c=0,f=0;f<t.length();f++){var h=t.getSection(f),p=t.getCharCode(f);if(lu[p]||(c+=cu(p,h,n,i,e,o)),f<t.length()-1){var d=!((v=p)<11904||!(ci["Bopomofo Extended"](v)||ci.Bopomofo(v)||ci["CJK Compatibility Forms"](v)||ci["CJK Compatibility Ideographs"](v)||ci["CJK Compatibility"](v)||ci["CJK Radicals Supplement"](v)||ci["CJK Strokes"](v)||ci["CJK Symbols and Punctuation"](v)||ci["CJK Unified Ideographs Extension A"](v)||ci["CJK Unified Ideographs"](v)||ci["Enclosed CJK Letters and Months"](v)||ci["Halfwidth and Fullwidth Forms"](v)||ci.Hiragana(v)||ci["Ideographic Description Characters"](v)||ci["Kangxi Radicals"](v)||ci["Katakana Phonetic Extensions"](v)||ci.Katakana(v)||ci["Vertical Forms"](v)||ci["Yi Radicals"](v)||ci["Yi Syllables"](v)));(uu[p]||d||h.imageName)&&s.push(pu(f+1,c,l,s,hu(p,t.getCharCode(f+1),d&&u),!1))}}var v;return du(pu(t.length(),c,l,s,0,!0))}function gu(t){var e=.5,r=.5;switch(t){case"right":case"top-right":case"bottom-right":e=1;break;case"left":case"top-left":case"bottom-left":e=0}switch(t){case"bottom":case"bottom-right":case"bottom-left":r=1;break;case"top":case"top-right":case"top-left":r=0}return{horizontalAlign:e,verticalAlign:r}}function yu(t,e,r,n,i){if(n||i)for(var a=t[r],o=a.metrics.advance*a.scale,s=(t[r].x+o)*n,l=e;l<=r;l++)t[l].x-=s,t[l].y+=i}function mu(t,e,r,n,i,a){var o,s=t.image;if(s.content){var l=s.content,u=s.pixelRatio||1;o=[l[0]/u,l[1]/u,s.displaySize[0]-l[2]/u,s.displaySize[1]-l[3]/u]}var c,f,h,p,d=e.left*a,v=e.right*a;"width"===r||"both"===r?(p=i[0]+d-n[3],f=i[0]+v+n[1]):f=(p=i[0]+(d+v-s.displaySize[0])/2)+s.displaySize[0];var g=e.top*a,y=e.bottom*a;return"height"===r||"both"===r?(c=i[1]+g-n[0],h=i[1]+y+n[2]):h=(c=i[1]+(g+y-s.displaySize[1])/2)+s.displaySize[1],{image:s,top:c,right:f,bottom:h,left:p,collisionPadding:o}}uu[10]=!0,uu[32]=!0,uu[38]=!0,uu[40]=!0,uu[41]=!0,uu[43]=!0,uu[45]=!0,uu[47]=!0,uu[173]=!0,uu[183]=!0,uu[8203]=!0,uu[8208]=!0,uu[8211]=!0,uu[8231]=!0;var xu=function(t){function e(e,r,n,i){t.call(this,e,r),this.angle=n,void 0!==i&&(this.segment=i)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.clone=function(){return new 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fa,this.programConfigurations=t,this.segments=new Oa,this.dynamicLayoutVertexArray=new aa,this.opacityVertexArray=new oa,this.placedSymbolArray=new ka};ac.prototype.isEmpty=function(){return 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e=this.layers[0]._unevaluatedLayout._values;this.textSizeData=_u(this.zoom,e["text-size"]),this.iconSizeData=_u(this.zoom,e["icon-size"]);var r=this.layers[0].layout,n=r.get("symbol-sort-key"),i=r.get("symbol-z-order");this.sortFeaturesByKey="viewport-y"!==i&&void 0!==n.constantOr(1);var a="viewport-y"===i||"auto"===i&&!this.sortFeaturesByKey;this.sortFeaturesByY=a&&(r.get("text-allow-overlap")||r.get("icon-allow-overlap")||r.get("text-ignore-placement")||r.get("icon-ignore-placement")),"point"===r.get("symbol-placement")&&(this.writingModes=r.get("text-writing-mode").map((function(t){return nu[t]}))),this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id})),this.sourceID=t.sourceID};sc.prototype.createArrays=function(){this.text=new ac(new so(yl.members,this.layers,this.zoom,(function(t){return/^text/.test(t)}))),this.icon=new ac(new so(yl.members,this.layers,this.zoom,(function(t){return/^icon/.test(t)}))),this.glyphOffsetArray=new Sa,this.lineVertexArray=new Ea,this.symbolInstances=new Ma},sc.prototype.calculateGlyphDependencies=function(t,e,r,n,i){for(var a=0;a<t.length;a++)if(e[t.charCodeAt(a)]=!0,(r||n)&&i){var o=Tl[t.charAt(a)];o&&(e[o.charCodeAt(0)]=!0)}},sc.prototype.populate=function(t,e,r){var n=this.layers[0],i=n.layout,a=i.get("text-font"),o=i.get("text-field"),s=i.get("icon-image"),l=("constant"!==o.value.kind||o.value.value instanceof ue&&!o.value.value.isEmpty()||o.value.value.toString().length>0)&&("constant"!==a.value.kind||a.value.value.length>0),u="constant"!==s.value.kind||!!s.value.value||Object.keys(s.parameters).length>0,c=i.get("symbol-sort-key");if(this.features=[],l||u){for(var f=e.iconDependencies,h=e.glyphDependencies,p=e.availableImages,d=new Pi(this.zoom),v=0,g=t;v<g.length;v+=1){var y=g[v],m=y.feature,x=y.id,b=y.index,_=y.sourceLayerIndex,w=n._featureFilter.needGeometry,T={type:m.type,id:x,properties:m.properties,geometry:w?po(m):[]};if(n._featureFilter.filter(d,T,r)){w||(T.geometry=po(m));var k=void 0;if(l){var A=n.getValueAndResolveTokens("text-field",T,r,p),M=ue.factory(A);ic(M)&&(this.hasRTLText=!0),(!this.hasRTLText||"unavailable"===Ei()||this.hasRTLText&&Ci.isParsed())&&(k=wl(M,n,T))}var S=void 0;if(u){var E=n.getValueAndResolveTokens("icon-image",T,r,p);S=E instanceof ce?E:ce.fromString(E)}if(k||S){var L=this.sortFeaturesByKey?c.evaluate(T,{},r):void 0,C={id:x,text:k,icon:S,index:b,sourceLayerIndex:_,geometry:po(m),properties:m.properties,type:tc[m.type],sortKey:L};if(this.features.push(C),S&&(f[S.name]=!0),k){var P=a.evaluate(T,{},r).join(","),O="map"===i.get("text-rotation-alignment")&&"point"!==i.get("symbol-placement");this.allowVerticalPlacement=this.writingModes&&this.writingModes.indexOf(nu.vertical)>=0;for(var I=0,D=k.sections;I<D.length;I+=1){var z=D[I];if(z.image)f[z.image.name]=!0;else{var R=fi(k.toString()),F=z.fontStack||P,B=h[F]=h[F]||{};this.calculateGlyphDependencies(z.text,B,O,this.allowVerticalPlacement,R)}}}}}}"line"===i.get("symbol-placement")&&(this.features=function(t){var e={},r={},n=[],i=0;function a(e){n.push(t[e]),i++}function o(t,e,i){var a=r[t];return delete r[t],r[e]=a,n[a].geometry[0].pop(),n[a].geometry[0]=n[a].geometry[0].concat(i[0]),a}function s(t,r,i){var a=e[r];return delete e[r],e[t]=a,n[a].geometry[0].shift(),n[a].geometry[0]=i[0].concat(n[a].geometry[0]),a}function l(t,e,r){var n=r?e[0][e[0].length-1]:e[0][0];return t+":"+n.x+":"+n.y}for(var u=0;u<t.length;u++){var c=t[u],f=c.geometry,h=c.text?c.text.toString():null;if(h){var p=l(h,f),d=l(h,f,!0);if(p in r&&d in e&&r[p]!==e[d]){var v=s(p,d,f),g=o(p,d,n[v].geometry);delete e[p],delete r[d],r[l(h,n[g].geometry,!0)]=g,n[v].geometry=null}else p in r?o(p,d,f):d in e?s(p,d,f):(a(u),e[p]=i-1,r[d]=i-1)}else a(u)}return n.filter((function(t){return t.geometry}))}(this.features)),this.sortFeaturesByKey&&this.features.sort((function(t,e){return t.sortKey-e.sortKey}))}},sc.prototype.update=function(t,e,r){this.stateDependentLayers.length&&(this.text.programConfigurations.updatePaintArrays(t,e,this.layers,r),this.icon.programConfigurations.updatePaintArrays(t,e,this.layers,r))},sc.prototype.isEmpty=function(){return 0===this.symbolInstances.length&&!this.hasRTLText},sc.prototype.uploadPending=function(){return!this.uploaded||this.text.programConfigurations.needsUpload||this.icon.programConfigurations.needsUpload},sc.prototype.upload=function(t){!this.uploaded&&this.hasDebugData()&&(this.textCollisionBox.upload(t),this.iconCollisionBox.upload(t)),this.text.upload(t,this.sortFeaturesByY,!this.uploaded,this.text.programConfigurations.needsUpload),this.icon.upload(t,this.sortFeaturesByY,!this.uploaded,this.icon.programConfigurations.needsUpload),this.uploaded=!0},sc.prototype.destroyDebugData=function(){this.textCollisionBox.destroy(),this.iconCollisionBox.destroy()},sc.prototype.destroy=function(){this.text.destroy(),this.icon.destroy(),this.hasDebugData()&&this.destroyDebugData()},sc.prototype.addToLineVertexArray=function(t,e){var r=this.lineVertexArray.length;if(void 0!==t.segment){for(var n=t.dist(e[t.segment+1]),i=t.dist(e[t.segment]),a={},o=t.segment+1;o<e.length;o++)a[o]={x:e[o].x,y:e[o].y,tileUnitDistanceFromAnchor:n},o<e.length-1&&(n+=e[o+1].dist(e[o]));for(var s=t.segment||0;s>=0;s--)a[s]={x:e[s].x,y:e[s].y,tileUnitDistanceFromAnchor:i},s>0&&(i+=e[s-1].dist(e[s]));for(var l=0;l<e.length;l++){var u=a[l];this.lineVertexArray.emplaceBack(u.x,u.y,u.tileUnitDistanceFromAnchor)}}return{lineStartIndex:r,lineLength:this.lineVertexArray.length-r}},sc.prototype.addSymbols=function(t,e,r,n,i,a,o,s,l,u,c,f){for(var h=t.indexArray,p=t.layoutVertexArray,d=t.segments.prepareSegment(4*e.length,p,h,a.sortKey),v=this.glyphOffsetArray.length,g=d.vertexLength,y=this.allowVerticalPlacement&&o===nu.vertical?Math.PI/2:0,m=a.text&&a.text.sections,x=0;x<e.length;x++){var b=e[x],_=b.tl,w=b.tr,T=b.bl,k=b.br,A=b.tex,M=b.pixelOffsetTL,S=b.pixelOffsetBR,E=b.minFontScaleX,L=b.minFontScaleY,C=b.glyphOffset,P=b.isSDF,O=b.sectionIndex,I=d.vertexLength,D=C[1];rc(p,s.x,s.y,_.x,D+_.y,A.x,A.y,r,P,M.x,M.y,E,L),rc(p,s.x,s.y,w.x,D+w.y,A.x+A.w,A.y,r,P,S.x,M.y,E,L),rc(p,s.x,s.y,T.x,D+T.y,A.x,A.y+A.h,r,P,M.x,S.y,E,L),rc(p,s.x,s.y,k.x,D+k.y,A.x+A.w,A.y+A.h,r,P,S.x,S.y,E,L),nc(t.dynamicLayoutVertexArray,s,y),h.emplaceBack(I,I+1,I+2),h.emplaceBack(I+1,I+2,I+3),d.vertexLength+=4,d.primitiveLength+=2,this.glyphOffsetArray.emplaceBack(C[0]),x!==e.length-1&&O===e[x+1].sectionIndex||t.programConfigurations.populatePaintArrays(p.length,a,a.index,{},f,m&&m[O])}t.placedSymbolArray.emplaceBack(s.x,s.y,v,this.glyphOffsetArray.length-v,g,l,u,s.segment,r?r[0]:0,r?r[1]:0,n[0],n[1],o,0,!1,0,c)},sc.prototype._addCollisionDebugVertex=function(t,e,r,n,i,a){return e.emplaceBack(0,0),t.emplaceBack(r.x,r.y,n,i,Math.round(a.x),Math.round(a.y))},sc.prototype.addCollisionDebugVertices=function(t,e,r,n,i,o,s){var l=i.segments.prepareSegment(4,i.layoutVertexArray,i.indexArray),u=l.vertexLength,c=i.layoutVertexArray,f=i.collisionVertexArray,h=s.anchorX,p=s.anchorY;this._addCollisionDebugVertex(c,f,o,h,p,new a(t,e)),this._addCollisionDebugVertex(c,f,o,h,p,new a(r,e)),this._addCollisionDebugVertex(c,f,o,h,p,new a(r,n)),this._addCollisionDebugVertex(c,f,o,h,p,new a(t,n)),l.vertexLength+=4;var d=i.indexArray;d.emplaceBack(u,u+1),d.emplaceBack(u+1,u+2),d.emplaceBack(u+2,u+3),d.emplaceBack(u+3,u),l.primitiveLength+=4},sc.prototype.addDebugCollisionBoxes=function(t,e,r,n){for(var i=t;i<e;i++){var a=this.collisionBoxArray.get(i),o=a.x1,s=a.y1,l=a.x2,u=a.y2;this.addCollisionDebugVertices(o,s,l,u,n?this.textCollisionBox:this.iconCollisionBox,a.anchorPoint,r)}},sc.prototype.generateCollisionDebugBuffers=function(){this.hasDebugData()&&this.destroyDebugData(),this.textCollisionBox=new oc(la,bl.members,ya),this.iconCollisionBox=new oc(la,bl.members,ya);for(var t=0;t<this.symbolInstances.length;t++){var e=this.symbolInstances.get(t);this.addDebugCollisionBoxes(e.textBoxStartIndex,e.textBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.verticalTextBoxStartIndex,e.verticalTextBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.iconBoxStartIndex,e.iconBoxEndIndex,e,!1),this.addDebugCollisionBoxes(e.verticalIconBoxStartIndex,e.verticalIconBoxEndIndex,e,!1)}},sc.prototype._deserializeCollisionBoxesForSymbol=function(t,e,r,n,i,a,o,s,l){for(var u={},c=e;c<r;c++){var f=t.get(c);u.textBox={x1:f.x1,y1:f.y1,x2:f.x2,y2:f.y2,anchorPointX:f.anchorPointX,anchorPointY:f.anchorPointY},u.textFeatureIndex=f.featureIndex;break}for(var h=n;h<i;h++){var p=t.get(h);u.verticalTextBox={x1:p.x1,y1:p.y1,x2:p.x2,y2:p.y2,anchorPointX:p.anchorPointX,anchorPointY:p.anchorPointY},u.verticalTextFeatureIndex=p.featureIndex;break}for(var d=a;d<o;d++){var v=t.get(d);u.iconBox={x1:v.x1,y1:v.y1,x2:v.x2,y2:v.y2,anchorPointX:v.anchorPointX,anchorPointY:v.anchorPointY},u.iconFeatureIndex=v.featureIndex;break}for(var g=s;g<l;g++){var y=t.get(g);u.verticalIconBox={x1:y.x1,y1:y.y1,x2:y.x2,y2:y.y2,anchorPointX:y.anchorPointX,anchorPointY:y.anchorPointY},u.verticalIconFeatureIndex=y.featureIndex;break}return u},sc.prototype.deserializeCollisionBoxes=function(t){this.collisionArrays=[];for(var e=0;e<this.symbolInstances.length;e++){var r=this.symbolInstances.get(e);this.collisionArrays.push(this._deserializeCollisionBoxesForSymbol(t,r.textBoxStartIndex,r.textBoxEndIndex,r.verticalTextBoxStartIndex,r.verticalTextBoxEndIndex,r.iconBoxStartIndex,r.iconBoxEndIndex,r.verticalIconBoxStartIndex,r.verticalIconBoxEndIndex))}},sc.prototype.hasTextData=function(){return this.text.segments.get().length>0},sc.prototype.hasIconData=function(){return this.icon.segments.get().length>0},sc.prototype.hasDebugData=function(){return this.textCollisionBox&&this.iconCollisionBox},sc.prototype.hasTextCollisionBoxData=function(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0},sc.prototype.hasIconCollisionBoxData=function(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0},sc.prototype.addIndicesForPlacedSymbol=function(t,e){for(var r=t.placedSymbolArray.get(e),n=r.vertexStartIndex+4*r.numGlyphs,i=r.vertexStartIndex;i<n;i+=4)t.indexArray.emplaceBack(i,i+1,i+2),t.indexArray.emplaceBack(i+1,i+2,i+3)},sc.prototype.getSortedSymbolIndexes=function(t){if(this.sortedAngle===t&&void 0!==this.symbolInstanceIndexes)return this.symbolInstanceIndexes;for(var e=Math.sin(t),r=Math.cos(t),n=[],i=[],a=[],o=0;o<this.symbolInstances.length;++o){a.push(o);var s=this.symbolInstances.get(o);n.push(0|Math.round(e*s.anchorX+r*s.anchorY)),i.push(s.featureIndex)}return a.sort((function(t,e){return n[t]-n[e]||i[e]-i[t]})),a},sc.prototype.addToSortKeyRanges=function(t,e){var r=this.sortKeyRanges[this.sortKeyRanges.length-1];r&&r.sortKey===e?r.symbolInstanceEnd=t+1:this.sortKeyRanges.push({sortKey:e,symbolInstanceStart:t,symbolInstanceEnd:t+1})},sc.prototype.sortFeatures=function(t){var e=this;if(this.sortFeaturesByY&&this.sortedAngle!==t&&!(this.text.segments.get().length>1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(t),this.sortedAngle=t,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var r=0,n=this.symbolInstanceIndexes;r<n.length;r+=1){var i=n[r],a=this.symbolInstances.get(i);this.featureSortOrder.push(a.featureIndex),[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t,r,n){t>=0&&n.indexOf(t)===r&&e.addIndicesForPlacedSymbol(e.text,t)})),a.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,a.verticalPlacedTextSymbolIndex),a.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.placedIconSymbolIndex),a.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},ni("SymbolBucket",sc,{omit:["layers","collisionBoxArray","features","compareText"]}),sc.MAX_GLYPHS=65535,sc.addDynamicAttributes=nc;var lc=new Gi({"symbol-placement":new ji(Dt.layout_symbol["symbol-placement"]),"symbol-spacing":new ji(Dt.layout_symbol["symbol-spacing"]),"symbol-avoid-edges":new ji(Dt.layout_symbol["symbol-avoid-edges"]),"symbol-sort-key":new Ui(Dt.layout_symbol["symbol-sort-key"]),"symbol-z-order":new ji(Dt.layout_symbol["symbol-z-order"]),"icon-allow-overlap":new ji(Dt.layout_symbol["icon-allow-overlap"]),"icon-ignore-placement":new ji(Dt.layout_symbol["icon-ignore-placement"]),"icon-optional":new ji(Dt.layout_symbol["icon-optional"]),"icon-rotation-alignment":new ji(Dt.layout_symbol["icon-rotation-alignment"]),"icon-size":new Ui(Dt.layout_symbol["icon-size"]),"icon-text-fit":new ji(Dt.layout_symbol["icon-text-fit"]),"icon-text-fit-padding":new ji(Dt.layout_symbol["icon-text-fit-padding"]),"icon-image":new Ui(Dt.layout_symbol["icon-image"]),"icon-rotate":new Ui(Dt.layout_symbol["icon-rotate"]),"icon-padding":new ji(Dt.layout_symbol["icon-padding"]),"icon-keep-upright":new ji(Dt.layout_symbol["icon-keep-upright"]),"icon-offset":new Ui(Dt.layout_symbol["icon-offset"]),"icon-anchor":new Ui(Dt.layout_symbol["icon-anchor"]),"icon-pitch-alignment":new ji(Dt.layout_symbol["icon-pitch-alignment"]),"text-pitch-alignment":new ji(Dt.layout_symbol["text-pitch-alignment"]),"text-rotation-alignment":new ji(Dt.layout_symbol["text-rotation-alignment"]),"text-field":new Ui(Dt.layout_symbol["text-field"]),"text-font":new Ui(Dt.layout_symbol["text-font"]),"text-size":new Ui(Dt.layout_symbol["text-size"]),"text-max-width":new Ui(Dt.layout_symbol["text-max-width"]),"text-line-height":new ji(Dt.layout_symbol["text-line-height"]),"text-letter-spacing":new Ui(Dt.layout_symbol["text-letter-spacing"]),"text-justify":new Ui(Dt.layout_symbol["text-justify"]),"text-radial-offset":new Ui(Dt.layout_symbol["text-radial-offset"]),"text-variable-anchor":new ji(Dt.layout_symbol["text-variable-anchor"]),"text-anchor":new Ui(Dt.layout_symbol["text-anchor"]),"text-max-angle":new ji(Dt.layout_symbol["text-max-angle"]),"text-writing-mode":new ji(Dt.layout_symbol["text-writing-mode"]),"text-rotate":new Ui(Dt.layout_symbol["text-rotate"]),"text-padding":new ji(Dt.layout_symbol["text-padding"]),"text-keep-upright":new ji(Dt.layout_symbol["text-keep-upright"]),"text-transform":new Ui(Dt.layout_symbol["text-transform"]),"text-offset":new Ui(Dt.layout_symbol["text-offset"]),"text-allow-overlap":new ji(Dt.layout_symbol["text-allow-overlap"]),"text-ignore-placement":new ji(Dt.layout_symbol["text-ignore-placement"]),"text-optional":new ji(Dt.layout_symbol["text-optional"])}),uc={paint:new Gi({"icon-opacity":new Ui(Dt.paint_symbol["icon-opacity"]),"icon-color":new Ui(Dt.paint_symbol["icon-color"]),"icon-halo-color":new Ui(Dt.paint_symbol["icon-halo-color"]),"icon-halo-width":new Ui(Dt.paint_symbol["icon-halo-width"]),"icon-halo-blur":new Ui(Dt.paint_symbol["icon-halo-blur"]),"icon-translate":new ji(Dt.paint_symbol["icon-translate"]),"icon-translate-anchor":new ji(Dt.paint_symbol["icon-translate-anchor"]),"text-opacity":new Ui(Dt.paint_symbol["text-opacity"]),"text-color":new Ui(Dt.paint_symbol["text-color"],{runtimeType:Zt,getOverride:function(t){return t.textColor},hasOverride:function(t){return!!t.textColor}}),"text-halo-color":new Ui(Dt.paint_symbol["text-halo-color"]),"text-halo-width":new Ui(Dt.paint_symbol["text-halo-width"]),"text-halo-blur":new Ui(Dt.paint_symbol["text-halo-blur"]),"text-translate":new ji(Dt.paint_symbol["text-translate"]),"text-translate-anchor":new ji(Dt.paint_symbol["text-translate-anchor"])}),layout:lc},cc=function(t){this.type=t.property.overrides?t.property.overrides.runtimeType:Vt,this.defaultValue=t};cc.prototype.evaluate=function(t){if(t.formattedSection){var e=this.defaultValue.property.overrides;if(e&&e.hasOverride(t.formattedSection))return e.getOverride(t.formattedSection)}return t.feature&&t.featureState?this.defaultValue.evaluate(t.feature,t.featureState):this.defaultValue.property.specification.default},cc.prototype.eachChild=function(t){this.defaultValue.isConstant()||t(this.defaultValue.value._styleExpression.expression)},cc.prototype.outputDefined=function(){return!1},cc.prototype.serialize=function(){return null},ni("FormatSectionOverride",cc,{omit:["defaultValue"]});var fc=function(t){function e(e){t.call(this,e,uc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.recalculate=function(e,r){if(t.prototype.recalculate.call(this,e,r),"auto"===this.layout.get("icon-rotation-alignment")&&("point"!==this.layout.get("symbol-placement")?this.layout._values["icon-rotation-alignment"]="map":this.layout._values["icon-rotation-alignment"]="viewport"),"auto"===this.layout.get("text-rotation-alignment")&&("point"!==this.layout.get("symbol-placement")?this.layout._values["text-rotation-alignment"]="map":this.layout._values["text-rotation-alignment"]="viewport"),"auto"===this.layout.get("text-pitch-alignment")&&(this.layout._values["text-pitch-alignment"]=this.layout.get("text-rotation-alignment")),"auto"===this.layout.get("icon-pitch-alignment")&&(this.layout._values["icon-pitch-alignment"]=this.layout.get("icon-rotation-alignment")),"point"===this.layout.get("symbol-placement")){var n=this.layout.get("text-writing-mode");if(n){for(var i=[],a=0,o=n;a<o.length;a+=1){var s=o[a];i.indexOf(s)<0&&i.push(s)}this.layout._values["text-writing-mode"]=i}else this.layout._values["text-writing-mode"]=["horizontal"]}this._setPaintOverrides()},e.prototype.getValueAndResolveTokens=function(t,e,r,n){var i=this.layout.get(t).evaluate(e,{},r,n),a=this._unevaluatedLayout._values[t];return a.isDataDriven()||sn(a.value)||!i?i:function(t,e){return e.replace(/{([^{}]+)}/g,(function(e,r){return r in t?String(t[r]):""}))}(e.properties,i)},e.prototype.createBucket=function(t){return new sc(t)},e.prototype.queryRadius=function(){return 0},e.prototype.queryIntersectsFeature=function(){return!1},e.prototype._setPaintOverrides=function(){for(var t=0,r=uc.paint.overridableProperties;t<r.length;t+=1){var n=r[t];if(e.hasPaintOverride(this.layout,n)){var i,a=this.paint.get(n),o=new cc(a),s=new on(o,a.property.specification);i="constant"===a.value.kind||"source"===a.value.kind?new un("source",s):new cn("composite",s,a.value.zoomStops,a.value._interpolationType),this.paint._values[n]=new Bi(a.property,i,a.parameters)}}},e.prototype._handleOverridablePaintPropertyUpdate=function(t,r,n){return!(!this.layout||r.isDataDriven()||n.isDataDriven())&&e.hasPaintOverride(this.layout,t)},e.hasPaintOverride=function(t,e){var r=t.get("text-field"),n=uc.paint.properties[e],i=!1,a=function(t){for(var e=0,r=t;e<r.length;e+=1){var a=r[e];if(n.overrides&&n.overrides.hasOverride(a))return void(i=!0)}};if("constant"===r.value.kind&&r.value.value instanceof ue)a(r.value.value.sections);else if("source"===r.value.kind){var o=function(t){if(!i)if(t instanceof ve&&pe(t.value)===Jt){var e=t.value;a(e.sections)}else t instanceof xe?a(t.sections):t.eachChild(o)},s=r.value;s._styleExpression&&o(s._styleExpression.expression)}return i},e}(Yi),hc={paint:new Gi({"background-color":new ji(Dt.paint_background["background-color"]),"background-pattern":new Hi(Dt.paint_background["background-pattern"]),"background-opacity":new ji(Dt.paint_background["background-opacity"])})},pc=function(t){function e(e){t.call(this,e,hc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Yi),dc={paint:new Gi({"raster-opacity":new ji(Dt.paint_raster["raster-opacity"]),"raster-hue-rotate":new ji(Dt.paint_raster["raster-hue-rotate"]),"raster-brightness-min":new ji(Dt.paint_raster["raster-brightness-min"]),"raster-brightness-max":new ji(Dt.paint_raster["raster-brightness-max"]),"raster-saturation":new ji(Dt.paint_raster["raster-saturation"]),"raster-contrast":new ji(Dt.paint_raster["raster-contrast"]),"raster-resampling":new ji(Dt.paint_raster["raster-resampling"]),"raster-fade-duration":new ji(Dt.paint_raster["raster-fade-duration"])})},vc=function(t){function e(e){t.call(this,e,dc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Yi);var gc=function(t){function e(e){t.call(this,e,{}),this.implementation=e}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.is3D=function(){return"3d"===this.implementation.renderingMode},e.prototype.hasOffscreenPass=function(){return void 0!==this.implementation.prerender},e.prototype.recalculate=function(){},e.prototype.updateTransitions=function(){},e.prototype.hasTransition=function(){},e.prototype.serialize=function(){},e.prototype.onAdd=function(t){this.implementation.onAdd&&this.implementation.onAdd(t,t.painter.context.gl)},e.prototype.onRemove=function(t){this.implementation.onRemove&&this.implementation.onRemove(t,t.painter.context.gl)},e}(Yi),yc={circle:Uo,heatmap:Ko,hillshade:Qo,fill:js,"fill-extrusion":nl,line:vl,symbol:fc,background:pc,raster:vc};var mc=self.HTMLImageElement,xc=self.HTMLCanvasElement,bc=self.HTMLVideoElement,_c=self.ImageData,wc=self.ImageBitmap,Tc=function(t,e,r,n){this.context=t,this.format=r,this.texture=t.gl.createTexture(),this.update(e,n)};Tc.prototype.update=function(t,e,r){var n=t.width,i=t.height,a=!(this.size&&this.size[0]===n&&this.size[1]===i||r),o=this.context,s=o.gl;if(this.useMipmap=Boolean(e&&e.useMipmap),s.bindTexture(s.TEXTURE_2D,this.texture),o.pixelStoreUnpackFlipY.set(!1),o.pixelStoreUnpack.set(1),o.pixelStoreUnpackPremultiplyAlpha.set(this.format===s.RGBA&&(!e||!1!==e.premultiply)),a)this.size=[n,i],t instanceof mc||t instanceof xc||t instanceof bc||t instanceof _c||wc&&t instanceof wc?s.texImage2D(s.TEXTURE_2D,0,this.format,this.format,s.UNSIGNED_BYTE,t):s.texImage2D(s.TEXTURE_2D,0,this.format,n,i,0,this.format,s.UNSIGNED_BYTE,t.data);else{var l=r||{x:0,y:0},u=l.x,c=l.y;t instanceof mc||t instanceof xc||t instanceof bc||t instanceof _c||wc&&t instanceof wc?s.texSubImage2D(s.TEXTURE_2D,0,u,c,s.RGBA,s.UNSIGNED_BYTE,t):s.texSubImage2D(s.TEXTURE_2D,0,u,c,n,i,s.RGBA,s.UNSIGNED_BYTE,t.data)}this.useMipmap&&this.isSizePowerOfTwo()&&s.generateMipmap(s.TEXTURE_2D)},Tc.prototype.bind=function(t,e,r){var n=this.context.gl;n.bindTexture(n.TEXTURE_2D,this.texture),r!==n.LINEAR_MIPMAP_NEAREST||this.isSizePowerOfTwo()||(r=n.LINEAR),t!==this.filter&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,t),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,r||t),this.filter=t),e!==this.wrap&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,e),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,e),this.wrap=e)},Tc.prototype.isSizePowerOfTwo=function(){return this.size[0]===this.size[1]&&Math.log(this.size[0])/Math.LN2%1==0},Tc.prototype.destroy=function(){this.context.gl.deleteTexture(this.texture),this.texture=null};var kc=function(t){var e=this;this._callback=t,this._triggered=!1,"undefined"!=typeof MessageChannel&&(this._channel=new MessageChannel,this._channel.port2.onmessage=function(){e._triggered=!1,e._callback()})};kc.prototype.trigger=function(){var t=this;this._triggered||(this._triggered=!0,this._channel?this._channel.port1.postMessage(!0):setTimeout((function(){t._triggered=!1,t._callback()}),0))},kc.prototype.remove=function(){delete this._channel,this._callback=function(){}};var Ac=function(t,e,r){this.target=t,this.parent=e,this.mapId=r,this.callbacks={},this.tasks={},this.taskQueue=[],this.cancelCallbacks={},g(["receive","process"],this),this.invoker=new kc(this.process),this.target.addEventListener("message",this.receive,!1),this.globalScope=A()?t:self};function Mc(t,e,r){var n=2*Math.PI*6378137/256/Math.pow(2,r);return[t*n-2*Math.PI*6378137/2,e*n-2*Math.PI*6378137/2]}Ac.prototype.send=function(t,e,r,n,i){var a=this;void 0===i&&(i=!1);var o=Math.round(1e18*Math.random()).toString(36).substring(0,10);r&&(this.callbacks[o]=r);var s=E(this.globalScope)?void 0:[];return this.target.postMessage({id:o,type:t,hasCallback:!!r,targetMapId:n,mustQueue:i,sourceMapId:this.mapId,data:si(e,s)},s),{cancel:function(){r&&delete a.callbacks[o],a.target.postMessage({id:o,type:"<cancel>",targetMapId:n,sourceMapId:a.mapId})}}},Ac.prototype.receive=function(t){var e=t.data,r=e.id;if(r&&(!e.targetMapId||this.mapId===e.targetMapId))if("<cancel>"===e.type){delete this.tasks[r];var n=this.cancelCallbacks[r];delete this.cancelCallbacks[r],n&&n()}else A()||e.mustQueue?(this.tasks[r]=e,this.taskQueue.push(r),this.invoker.trigger()):this.processTask(r,e)},Ac.prototype.process=function(){if(this.taskQueue.length){var t=this.taskQueue.shift(),e=this.tasks[t];delete this.tasks[t],this.taskQueue.length&&this.invoker.trigger(),e&&this.processTask(t,e)}},Ac.prototype.processTask=function(t,e){var r=this;if("<response>"===e.type){var n=this.callbacks[t];delete this.callbacks[t],n&&(e.error?n(li(e.error)):n(null,li(e.data)))}else{var i=!1,a=E(this.globalScope)?void 0:[],o=e.hasCallback?function(e,n){i=!0,delete r.cancelCallbacks[t],r.target.postMessage({id:t,type:"<response>",sourceMapId:r.mapId,error:e?si(e):null,data:si(n,a)},a)}:function(t){i=!0},s=null,l=li(e.data);if(this.parent[e.type])s=this.parent[e.type](e.sourceMapId,l,o);else if(this.parent.getWorkerSource){var u=e.type.split(".");s=this.parent.getWorkerSource(e.sourceMapId,u[0],l.source)[u[1]](l,o)}else o(new Error("Could not find function "+e.type));!i&&s&&s.cancel&&(this.cancelCallbacks[t]=s.cancel)}},Ac.prototype.remove=function(){this.invoker.remove(),this.target.removeEventListener("message",this.receive,!1)};var Sc=function(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1]))};Sc.prototype.setNorthEast=function(t){return this._ne=t instanceof Lc?new Lc(t.lng,t.lat):Lc.convert(t),this},Sc.prototype.setSouthWest=function(t){return this._sw=t instanceof Lc?new Lc(t.lng,t.lat):Lc.convert(t),this},Sc.prototype.extend=function(t){var e,r,n=this._sw,i=this._ne;if(t instanceof Lc)e=t,r=t;else{if(!(t instanceof Sc)){if(Array.isArray(t)){if(4===t.length||t.every(Array.isArray)){var a=t;return this.extend(Sc.convert(a))}var o=t;return this.extend(Lc.convert(o))}return this}if(e=t._sw,r=t._ne,!e||!r)return this}return n||i?(n.lng=Math.min(e.lng,n.lng),n.lat=Math.min(e.lat,n.lat),i.lng=Math.max(r.lng,i.lng),i.lat=Math.max(r.lat,i.lat)):(this._sw=new Lc(e.lng,e.lat),this._ne=new Lc(r.lng,r.lat)),this},Sc.prototype.getCenter=function(){return new Lc((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Sc.prototype.getSouthWest=function(){return this._sw},Sc.prototype.getNorthEast=function(){return this._ne},Sc.prototype.getNorthWest=function(){return new Lc(this.getWest(),this.getNorth())},Sc.prototype.getSouthEast=function(){return new Lc(this.getEast(),this.getSouth())},Sc.prototype.getWest=function(){return this._sw.lng},Sc.prototype.getSouth=function(){return this._sw.lat},Sc.prototype.getEast=function(){return this._ne.lng},Sc.prototype.getNorth=function(){return this._ne.lat},Sc.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Sc.prototype.toString=function(){return"LngLatBounds("+this._sw.toString()+", "+this._ne.toString()+")"},Sc.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Sc.prototype.contains=function(t){var e=Lc.convert(t),r=e.lng,n=e.lat,i=this._sw.lat<=n&&n<=this._ne.lat,a=this._sw.lng<=r&&r<=this._ne.lng;return this._sw.lng>this._ne.lng&&(a=this._sw.lng>=r&&r>=this._ne.lng),i&&a},Sc.convert=function(t){return!t||t instanceof Sc?t:new Sc(t)};var Ec=6371008.8,Lc=function(t,e){if(isNaN(t)||isNaN(e))throw new Error("Invalid LngLat object: ("+t+", "+e+")");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error("Invalid LngLat latitude value: must be between -90 and 90")};Lc.prototype.wrap=function(){return new Lc(c(this.lng,-180,180),this.lat)},Lc.prototype.toArray=function(){return[this.lng,this.lat]},Lc.prototype.toString=function(){return"LngLat("+this.lng+", "+this.lat+")"},Lc.prototype.distanceTo=function(t){var e=Math.PI/180,r=this.lat*e,n=t.lat*e,i=Math.sin(r)*Math.sin(n)+Math.cos(r)*Math.cos(n)*Math.cos((t.lng-this.lng)*e);return Ec*Math.acos(Math.min(i,1))},Lc.prototype.toBounds=function(t){void 0===t&&(t=0);var e=360*t/40075017,r=e/Math.cos(Math.PI/180*this.lat);return new Sc(new Lc(this.lng-r,this.lat-e),new Lc(this.lng+r,this.lat+e))},Lc.convert=function(t){if(t instanceof Lc)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new Lc(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&"object"==typeof t&&null!==t)return new Lc(Number("lng"in t?t.lng:t.lon),Number(t.lat));throw new Error("`LngLatLike` argument must be specified as a LngLat instance, an object {lng: <lng>, lat: <lat>}, an object {lon: <lng>, lat: <lat>}, or an array of [<lng>, <lat>]")};var Cc=2*Math.PI*Ec;function Pc(t){return Cc*Math.cos(t*Math.PI/180)}function Oc(t){return(180+t)/360}function Ic(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))/360}function Dc(t,e){return t/Pc(e)}function zc(t){var e=180-360*t;return 360/Math.PI*Math.atan(Math.exp(e*Math.PI/180))-90}var Rc=function(t,e,r){void 0===r&&(r=0),this.x=+t,this.y=+e,this.z=+r};Rc.fromLngLat=function(t,e){void 0===e&&(e=0);var r=Lc.convert(t);return new Rc(Oc(r.lng),Ic(r.lat),Dc(e,r.lat))},Rc.prototype.toLngLat=function(){return new Lc(360*this.x-180,zc(this.y))},Rc.prototype.toAltitude=function(){return t=this.z,e=this.y,t*Pc(zc(e));var t,e},Rc.prototype.meterInMercatorCoordinateUnits=function(){return 1/Cc*(t=zc(this.y),1/Math.cos(t*Math.PI/180));var t};var Fc=function(t,e,r){this.z=t,this.x=e,this.y=r,this.key=jc(0,t,t,e,r)};Fc.prototype.equals=function(t){return this.z===t.z&&this.x===t.x&&this.y===t.y},Fc.prototype.url=function(t,e){var r,n,i,a,o,s=(r=this.x,n=this.y,i=this.z,a=Mc(256*r,256*(n=Math.pow(2,i)-n-1),i),o=Mc(256*(r+1),256*(n+1),i),a[0]+","+a[1]+","+o[0]+","+o[1]),l=function(t,e,r){for(var n,i="",a=t;a>0;a--)i+=(e&(n=1<<a-1)?1:0)+(r&n?2:0);return i}(this.z,this.x,this.y);return t[(this.x+this.y)%t.length].replace("{prefix}",(this.x%16).toString(16)+(this.y%16).toString(16)).replace("{z}",String(this.z)).replace("{x}",String(this.x)).replace("{y}",String("tms"===e?Math.pow(2,this.z)-this.y-1:this.y)).replace("{quadkey}",l).replace("{bbox-epsg-3857}",s)},Fc.prototype.getTilePoint=function(t){var e=Math.pow(2,this.z);return new a((t.x*e-this.x)*co,(t.y*e-this.y)*co)},Fc.prototype.toString=function(){return this.z+"/"+this.x+"/"+this.y};var Bc=function(t,e){this.wrap=t,this.canonical=e,this.key=jc(t,e.z,e.z,e.x,e.y)},Nc=function(t,e,r,n,i){this.overscaledZ=t,this.wrap=e,this.canonical=new Fc(r,+n,+i),this.key=jc(e,t,r,n,i)};function jc(t,e,r,n,i){(t*=2)<0&&(t=-1*t-1);var a=1<<r;return(a*a*t+a*i+n).toString(36)+r.toString(36)+e.toString(36)}Nc.prototype.equals=function(t){return this.overscaledZ===t.overscaledZ&&this.wrap===t.wrap&&this.canonical.equals(t.canonical)},Nc.prototype.scaledTo=function(t){var e=this.canonical.z-t;return t>this.canonical.z?new Nc(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new Nc(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)},Nc.prototype.calculateScaledKey=function(t,e){var r=this.canonical.z-t;return t>this.canonical.z?jc(this.wrap*+e,t,this.canonical.z,this.canonical.x,this.canonical.y):jc(this.wrap*+e,t,t,this.canonical.x>>r,this.canonical.y>>r)},Nc.prototype.isChildOf=function(t){if(t.wrap!==this.wrap)return!1;var e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ<this.overscaledZ&&t.canonical.x===this.canonical.x>>e&&t.canonical.y===this.canonical.y>>e},Nc.prototype.children=function(t){if(this.overscaledZ>=t)return[new Nc(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new Nc(e,this.wrap,e,r,n),new Nc(e,this.wrap,e,r+1,n),new Nc(e,this.wrap,e,r,n+1),new Nc(e,this.wrap,e,r+1,n+1)]},Nc.prototype.isLessThan=function(t){return this.wrap<t.wrap||!(this.wrap>t.wrap)&&(this.overscaledZ<t.overscaledZ||!(this.overscaledZ>t.overscaledZ)&&(this.canonical.x<t.canonical.x||!(this.canonical.x>t.canonical.x)&&this.canonical.y<t.canonical.y))},Nc.prototype.wrapped=function(){return new Nc(this.overscaledZ,0,this.canonical.z,this.canonical.x,this.canonical.y)},Nc.prototype.unwrapTo=function(t){return new Nc(this.overscaledZ,t,this.canonical.z,this.canonical.x,this.canonical.y)},Nc.prototype.overscaleFactor=function(){return Math.pow(2,this.overscaledZ-this.canonical.z)},Nc.prototype.toUnwrapped=function(){return new Bc(this.wrap,this.canonical)},Nc.prototype.toString=function(){return this.overscaledZ+"/"+this.canonical.x+"/"+this.canonical.y},Nc.prototype.getTilePoint=function(t){return this.canonical.getTilePoint(new Rc(t.x-this.wrap,t.y))},ni("CanonicalTileID",Fc),ni("OverscaledTileID",Nc,{omit:["posMatrix"]});var Uc=function(t,e,r){if(this.uid=t,e.height!==e.width)throw new RangeError("DEM tiles must be square");if(r&&"mapbox"!==r&&"terrarium"!==r)return w('"'+r+'" is not a valid encoding type. Valid types include "mapbox" and "terrarium".');this.stride=e.height;var n=this.dim=e.height-2;this.data=new Uint32Array(e.data.buffer),this.encoding=r||"mapbox";for(var i=0;i<n;i++)this.data[this._idx(-1,i)]=this.data[this._idx(0,i)],this.data[this._idx(n,i)]=this.data[this._idx(n-1,i)],this.data[this._idx(i,-1)]=this.data[this._idx(i,0)],this.data[this._idx(i,n)]=this.data[this._idx(i,n-1)];this.data[this._idx(-1,-1)]=this.data[this._idx(0,0)],this.data[this._idx(n,-1)]=this.data[this._idx(n-1,0)],this.data[this._idx(-1,n)]=this.data[this._idx(0,n-1)],this.data[this._idx(n,n)]=this.data[this._idx(n-1,n-1)]};Uc.prototype.get=function(t,e){var r=new Uint8Array(this.data.buffer),n=4*this._idx(t,e);return("terrarium"===this.encoding?this._unpackTerrarium:this._unpackMapbox)(r[n],r[n+1],r[n+2])},Uc.prototype.getUnpackVector=function(){return"terrarium"===this.encoding?[256,1,1/256,32768]:[6553.6,25.6,.1,1e4]},Uc.prototype._idx=function(t,e){if(t<-1||t>=this.dim+1||e<-1||e>=this.dim+1)throw new RangeError("out of range source coordinates for DEM data");return(e+1)*this.stride+(t+1)},Uc.prototype._unpackMapbox=function(t,e,r){return(256*t*256+256*e+r)/10-1e4},Uc.prototype._unpackTerrarium=function(t,e,r){return 256*t+e+r/256-32768},Uc.prototype.getPixels=function(){return new Wo({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},Uc.prototype.backfillBorder=function(t,e,r){if(this.dim!==t.dim)throw new Error("dem dimension mismatch");var n=e*this.dim,i=e*this.dim+this.dim,a=r*this.dim,o=r*this.dim+this.dim;switch(e){case-1:n=i-1;break;case 1:i=n+1}switch(r){case-1:a=o-1;break;case 1:o=a+1}for(var s=-e*this.dim,l=-r*this.dim,u=a;u<o;u++)for(var c=n;c<i;c++)this.data[this._idx(c,u)]=t.data[this._idx(c+s,u+l)]},ni("DEMData",Uc);var Vc=function(t){this._stringToNumber={},this._numberToString=[];for(var e=0;e<t.length;e++){var r=t[e];this._stringToNumber[r]=e,this._numberToString[e]=r}};Vc.prototype.encode=function(t){return this._stringToNumber[t]},Vc.prototype.decode=function(t){return this._numberToString[t]};var Hc=function(t,e,r,n,i){this.type="Feature",this._vectorTileFeature=t,t._z=e,t._x=r,t._y=n,this.properties=t.properties,this.id=i},qc={geometry:{configurable:!0}};qc.geometry.get=function(){return void 0===this._geometry&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry},qc.geometry.set=function(t){this._geometry=t},Hc.prototype.toJSON=function(){var t={geometry:this.geometry};for(var e in this)"_geometry"!==e&&"_vectorTileFeature"!==e&&(t[e]=this[e]);return t},Object.defineProperties(Hc.prototype,qc);var Gc=function(){this.state={},this.stateChanges={},this.deletedStates={}};Gc.prototype.updateState=function(t,e,r){var n=String(e);if(this.stateChanges[t]=this.stateChanges[t]||{},this.stateChanges[t][n]=this.stateChanges[t][n]||{},f(this.stateChanges[t][n],r),null===this.deletedStates[t])for(var i in this.deletedStates[t]={},this.state[t])i!==n&&(this.deletedStates[t][i]=null);else if(this.deletedStates[t]&&null===this.deletedStates[t][n])for(var a in this.deletedStates[t][n]={},this.state[t][n])r[a]||(this.deletedStates[t][n][a]=null);else for(var o in r)this.deletedStates[t]&&this.deletedStates[t][n]&&null===this.deletedStates[t][n][o]&&delete this.deletedStates[t][n][o]},Gc.prototype.removeFeatureState=function(t,e,r){if(null!==this.deletedStates[t]){var n=String(e);if(this.deletedStates[t]=this.deletedStates[t]||{},r&&void 0!==e)null!==this.deletedStates[t][n]&&(this.deletedStates[t][n]=this.deletedStates[t][n]||{},this.deletedStates[t][n][r]=null);else if(void 0!==e)if(this.stateChanges[t]&&this.stateChanges[t][n])for(r in this.deletedStates[t][n]={},this.stateChanges[t][n])this.deletedStates[t][n][r]=null;else this.deletedStates[t][n]=null;else this.deletedStates[t]=null}},Gc.prototype.getState=function(t,e){var r=String(e),n=this.state[t]||{},i=this.stateChanges[t]||{},a=f({},n[r],i[r]);if(null===this.deletedStates[t])return{};if(this.deletedStates[t]){var o=this.deletedStates[t][e];if(null===o)return{};for(var s in o)delete a[s]}return a},Gc.prototype.initializeTileState=function(t,e){t.setFeatureState(this.state,e)},Gc.prototype.coalesceChanges=function(t,e){var r={};for(var n in this.stateChanges){this.state[n]=this.state[n]||{};var i={};for(var a in this.stateChanges[n])this.state[n][a]||(this.state[n][a]={}),f(this.state[n][a],this.stateChanges[n][a]),i[a]=this.state[n][a];r[n]=i}for(var o in this.deletedStates){this.state[o]=this.state[o]||{};var s={};if(null===this.deletedStates[o])for(var l in this.state[o])s[l]={},this.state[o][l]={};else for(var u in this.deletedStates[o]){if(null===this.deletedStates[o][u])this.state[o][u]={};else for(var c=0,h=Object.keys(this.deletedStates[o][u]);c<h.length;c+=1){var p=h[c];delete this.state[o][u][p]}s[u]=this.state[o][u]}r[o]=r[o]||{},f(r[o],s)}if(this.stateChanges={},this.deletedStates={},0!==Object.keys(r).length)for(var d in t)t[d].setFeatureState(r,e)};var Zc=function(t,e){this.tileID=t,this.x=t.canonical.x,this.y=t.canonical.y,this.z=t.canonical.z,this.grid=new Kn(co,16,0),this.grid3D=new Kn(co,16,0),this.featureIndexArray=new Ca,this.promoteId=e};function Yc(t,e,r,n,i){return m(t,(function(t,a){var o=e instanceof Ni?e.get(a):null;return o&&o.evaluate?o.evaluate(r,n,i):o}))}function Wc(t){for(var e=1/0,r=1/0,n=-1/0,i=-1/0,a=0,o=t;a<o.length;a+=1){var s=o[a];e=Math.min(e,s.x),r=Math.min(r,s.y),n=Math.max(n,s.x),i=Math.max(i,s.y)}return{minX:e,minY:r,maxX:n,maxY:i}}function Xc(t,e){return e-t}Zc.prototype.insert=function(t,e,r,n,i,a){var o=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(r,n,i);for(var s=a?this.grid3D:this.grid,l=0;l<e.length;l++){for(var u=e[l],c=[1/0,1/0,-1/0,-1/0],f=0;f<u.length;f++){var h=u[f];c[0]=Math.min(c[0],h.x),c[1]=Math.min(c[1],h.y),c[2]=Math.max(c[2],h.x),c[3]=Math.max(c[3],h.y)}c[0]<co&&c[1]<co&&c[2]>=0&&c[3]>=0&&s.insert(o,c[0],c[1],c[2],c[3])}},Zc.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new Js.VectorTile(new Sl(this.rawTileData)).layers,this.sourceLayerCoder=new Vc(this.vtLayers?Object.keys(this.vtLayers).sort():["_geojsonTileLayer"])),this.vtLayers},Zc.prototype.query=function(t,e,r,n){var i=this;this.loadVTLayers();for(var o=t.params||{},s=co/t.tileSize/t.scale,l=wn(o.filter),u=t.queryGeometry,c=t.queryPadding*s,f=Wc(u),h=this.grid.query(f.minX-c,f.minY-c,f.maxX+c,f.maxY+c),p=Wc(t.cameraQueryGeometry),d=0,v=this.grid3D.query(p.minX-c,p.minY-c,p.maxX+c,p.maxY+c,(function(e,r,n,i){return function(t,e,r,n,i){for(var o=0,s=t;o<s.length;o+=1){var l=s[o];if(e<=l.x&&r<=l.y&&n>=l.x&&i>=l.y)return!0}var u=[new a(e,r),new a(e,i),new a(n,i),new a(n,r)];if(t.length>2)for(var c=0,f=u;c<f.length;c+=1)if(Mo(t,f[c]))return!0;for(var h=0;h<t.length-1;h++)if(So(t[h],t[h+1],u))return!0;return!1}(t.cameraQueryGeometry,e-c,r-c,n+c,i+c)}));d<v.length;d+=1){var g=v[d];h.push(g)}h.sort(Xc);for(var y,m={},x=function(a){var c=h[a];if(c!==y){y=c;var f=i.featureIndexArray.get(c),p=null;i.loadMatchingFeature(m,f.bucketIndex,f.sourceLayerIndex,f.featureIndex,l,o.layers,o.availableImages,e,r,n,(function(e,r,n){return p||(p=po(e)),r.queryIntersectsFeature(u,e,n,p,i.z,t.transform,s,t.pixelPosMatrix)}))}},b=0;b<h.length;b++)x(b);return m},Zc.prototype.loadMatchingFeature=function(t,e,r,n,i,a,o,s,l,u,c){var f=this.bucketLayerIDs[e];if(!a||function(t,e){for(var r=0;r<t.length;r++)if(e.indexOf(t[r])>=0)return!0;return!1}(a,f)){var h=this.sourceLayerCoder.decode(r),p=this.vtLayers[h].feature(n);if(i.filter(new Pi(this.tileID.overscaledZ),p))for(var d=this.getId(p,h),v=0;v<f.length;v++){var g=f[v];if(!(a&&a.indexOf(g)<0)){var y=s[g];if(y){var m={};void 0!==d&&u&&(m=u.getState(y.sourceLayer||"_geojsonTileLayer",d));var x=l[g];x.paint=Yc(x.paint,y.paint,p,m,o),x.layout=Yc(x.layout,y.layout,p,m,o);var b=!c||c(p,y,m);if(b){var _=new Hc(p,this.z,this.x,this.y,d);_.layer=x;var w=t[g];void 0===w&&(w=t[g]=[]),w.push({featureIndex:n,feature:_,intersectionZ:b})}}}}}},Zc.prototype.lookupSymbolFeatures=function(t,e,r,n,i,a,o,s){var l={};this.loadVTLayers();for(var u=wn(i),c=0,f=t;c<f.length;c+=1){var h=f[c];this.loadMatchingFeature(l,r,n,h,u,a,o,s,e)}return l},Zc.prototype.hasLayer=function(t){for(var e=0,r=this.bucketLayerIDs;e<r.length;e+=1)for(var n=0,i=r[e];n<i.length;n+=1)if(t===i[n])return!0;return!1},Zc.prototype.getId=function(t,e){var r=t.id;if(this.promoteId){var n="string"==typeof this.promoteId?this.promoteId:this.promoteId[e];"boolean"==typeof(r=t.properties[n])&&(r=Number(r))}return r},ni("FeatureIndex",Zc,{omit:["rawTileData","sourceLayerCoder"]});var Jc=function(t,e){this.tileID=t,this.uid=p(),this.uses=0,this.tileSize=e,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.hasSymbolBuckets=!1,this.hasRTLText=!1,this.dependencies={},this.expiredRequestCount=0,this.state="loading"};Jc.prototype.registerFadeDuration=function(t){var e=t+this.timeAdded;e<F.now()||this.fadeEndTime&&e<this.fadeEndTime||(this.fadeEndTime=e)},Jc.prototype.wasRequested=function(){return"errored"===this.state||"loaded"===this.state||"reloading"===this.state},Jc.prototype.loadVectorData=function(t,e,r){if(this.hasData()&&this.unloadVectorData(),this.state="loaded",t){for(var n in t.featureIndex&&(this.latestFeatureIndex=t.featureIndex,t.rawTileData?(this.latestRawTileData=t.rawTileData,this.latestFeatureIndex.rawTileData=t.rawTileData):this.latestRawTileData&&(this.latestFeatureIndex.rawTileData=this.latestRawTileData)),this.collisionBoxArray=t.collisionBoxArray,this.buckets=function(t,e){var r={};if(!e)return r;for(var n=function(){var t=a[i],n=t.layerIds.map((function(t){return e.getLayer(t)})).filter(Boolean);if(0!==n.length){t.layers=n,t.stateDependentLayerIds&&(t.stateDependentLayers=t.stateDependentLayerIds.map((function(t){return n.filter((function(e){return e.id===t}))[0]})));for(var o=0,s=n;o<s.length;o+=1){var l=s[o];r[l.id]=t}}},i=0,a=t;i<a.length;i+=1)n();return r}(t.buckets,e.style),this.hasSymbolBuckets=!1,this.buckets){var i=this.buckets[n];if(i instanceof sc){if(this.hasSymbolBuckets=!0,!r)break;i.justReloaded=!0}}if(this.hasRTLText=!1,this.hasSymbolBuckets)for(var a in this.buckets){var o=this.buckets[a];if(o instanceof sc&&o.hasRTLText){this.hasRTLText=!0,Ci.isLoading()||Ci.isLoaded()||"deferred"!==Ei()||Li();break}}for(var s in this.queryPadding=0,this.buckets){var l=this.buckets[s];this.queryPadding=Math.max(this.queryPadding,e.style.getLayer(s).queryRadius(l))}t.imageAtlas&&(this.imageAtlas=t.imageAtlas),t.glyphAtlasImage&&(this.glyphAtlasImage=t.glyphAtlasImage)}else this.collisionBoxArray=new wa},Jc.prototype.unloadVectorData=function(){for(var t in this.buckets)this.buckets[t].destroy();this.buckets={},this.imageAtlasTexture&&this.imageAtlasTexture.destroy(),this.imageAtlas&&(this.imageAtlas=null),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state="unloaded"},Jc.prototype.getBucket=function(t){return this.buckets[t.id]},Jc.prototype.upload=function(t){for(var e in this.buckets){var r=this.buckets[e];r.uploadPending()&&r.upload(t)}var n=t.gl;this.imageAtlas&&!this.imageAtlas.uploaded&&(this.imageAtlasTexture=new Tc(t,this.imageAtlas.image,n.RGBA),this.imageAtlas.uploaded=!0),this.glyphAtlasImage&&(this.glyphAtlasTexture=new Tc(t,this.glyphAtlasImage,n.ALPHA),this.glyphAtlasImage=null)},Jc.prototype.prepare=function(t){this.imageAtlas&&this.imageAtlas.patchUpdatedImages(t,this.imageAtlasTexture)},Jc.prototype.queryRenderedFeatures=function(t,e,r,n,i,a,o,s,l,u){return this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData?this.latestFeatureIndex.query({queryGeometry:n,cameraQueryGeometry:i,scale:a,tileSize:this.tileSize,pixelPosMatrix:u,transform:s,params:o,queryPadding:this.queryPadding*l},t,e,r):{}},Jc.prototype.querySourceFeatures=function(t,e){var r=this.latestFeatureIndex;if(r&&r.rawTileData){var n=r.loadVTLayers(),i=e?e.sourceLayer:"",a=n._geojsonTileLayer||n[i];if(a)for(var o=wn(e&&e.filter),s=this.tileID.canonical,l=s.z,u=s.x,c=s.y,f={z:l,x:u,y:c},h=0;h<a.length;h++){var p=a.feature(h);if(o.filter(new Pi(this.tileID.overscaledZ),p)){var d=r.getId(p,i),v=new Hc(p,l,u,c,d);v.tile=f,t.push(v)}}}},Jc.prototype.hasData=function(){return"loaded"===this.state||"reloading"===this.state||"expired"===this.state},Jc.prototype.patternsLoaded=function(){return this.imageAtlas&&!!Object.keys(this.imageAtlas.patternPositions).length},Jc.prototype.setExpiryData=function(t){var e=this.expirationTime;if(t.cacheControl){var r=M(t.cacheControl);r["max-age"]&&(this.expirationTime=Date.now()+1e3*r["max-age"])}else t.expires&&(this.expirationTime=new Date(t.expires).getTime());if(this.expirationTime){var n=Date.now(),i=!1;if(this.expirationTime>n)i=!1;else if(e)if(this.expirationTime<e)i=!0;else{var a=this.expirationTime-e;a?this.expirationTime=n+Math.max(a,3e4):i=!0}else i=!0;i?(this.expiredRequestCount++,this.state="expired"):this.expiredRequestCount=0}},Jc.prototype.getExpiryTimeout=function(){if(this.expirationTime)return this.expiredRequestCount?1e3*(1<<Math.min(this.expiredRequestCount-1,31)):Math.min(this.expirationTime-(new Date).getTime(),Math.pow(2,31)-1)},Jc.prototype.setFeatureState=function(t,e){if(this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData&&0!==Object.keys(t).length){var r=this.latestFeatureIndex.loadVTLayers();for(var n in this.buckets)if(e.style.hasLayer(n)){var i=this.buckets[n],a=i.layers[0].sourceLayer||"_geojsonTileLayer",o=r[a],s=t[a];if(o&&s&&0!==Object.keys(s).length){i.update(s,o,this.imageAtlas&&this.imageAtlas.patternPositions||{});var l=e&&e.style&&e.style.getLayer(n);l&&(this.queryPadding=Math.max(this.queryPadding,l.queryRadius(i)))}}}},Jc.prototype.holdingForFade=function(){return void 0!==this.symbolFadeHoldUntil},Jc.prototype.symbolFadeFinished=function(){return!this.symbolFadeHoldUntil||this.symbolFadeHoldUntil<F.now()},Jc.prototype.clearFadeHold=function(){this.symbolFadeHoldUntil=void 0},Jc.prototype.setHoldDuration=function(t){this.symbolFadeHoldUntil=F.now()+t},Jc.prototype.setDependencies=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1)r[i[n]]=!0;this.dependencies[t]=r},Jc.prototype.hasDependency=function(t,e){for(var r=0,n=t;r<n.length;r+=1){var i=n[r],a=this.dependencies[i];if(a)for(var o=0,s=e;o<s.length;o+=1)if(a[s[o]])return!0}return!1};var Kc=self.performance,$c=function(t){this._marks={start:[t.url,"start"].join("#"),end:[t.url,"end"].join("#"),measure:t.url.toString()},Kc.mark(this._marks.start)};$c.prototype.finish=function(){Kc.mark(this._marks.end);var t=Kc.getEntriesByName(this._marks.measure);return 0===t.length&&(Kc.measure(this._marks.measure,this._marks.start,this._marks.end),t=Kc.getEntriesByName(this._marks.measure),Kc.clearMarks(this._marks.start),Kc.clearMarks(this._marks.end),Kc.clearMeasures(this._marks.measure)),t},t.Actor=Ac,t.AlphaImage=Yo,t.CanonicalTileID=Fc,t.CollisionBoxArray=wa,t.Color=oe,t.DEMData=Uc,t.DataConstantProperty=ji,t.DictionaryCoder=Vc,t.EXTENT=co,t.ErrorEvent=Ot,t.EvaluationParameters=Pi,t.Event=Pt,t.Evented=It,t.FeatureIndex=Zc,t.FillBucket=Fs,t.FillExtrusionBucket=tl,t.ImageAtlas=ru,t.ImagePosition=tu,t.LineBucket=cl,t.LngLat=Lc,t.LngLatBounds=Sc,t.MercatorCoordinate=Rc,t.ONE_EM=kl,t.OverscaledTileID=Nc,t.Point=a,t.Point$1=a,t.Properties=Gi,t.Protobuf=Sl,t.RGBAImage=Wo,t.RequestManager=q,t.RequestPerformance=$c,t.ResourceType=xt,t.SegmentVector=Oa,t.SourceFeatureState=Gc,t.StructArrayLayout1ui2=ma,t.StructArrayLayout2f1f2i16=ua,t.StructArrayLayout2i4=Qi,t.StructArrayLayout3ui6=fa,t.StructArrayLayout4i8=ta,t.SymbolBucket=sc,t.Texture=Tc,t.Tile=Jc,t.Transitionable=Di,t.Uniform1f=Ya,t.Uniform1i=Za,t.Uniform2f=Wa,t.Uniform3f=Xa,t.Uniform4f=Ja,t.UniformColor=Ka,t.UniformMatrix4f=Qa,t.UnwrappedTileID=Bc,t.ValidationError=zt,t.WritingMode=nu,t.ZoomHistory=ui,t.add=function(t,e,r){return t[0]=e[0]+r[0],t[1]=e[1]+r[1],t[2]=e[2]+r[2],t},t.addDynamicAttributes=nc,t.asyncAll=function(t,e,r){if(!t.length)return r(null,[]);var n=t.length,i=new Array(t.length),a=null;t.forEach((function(t,o){e(t,(function(t,e){t&&(a=t),i[o]=e,0==--n&&r(a,i)}))}))},t.bezier=s,t.bindAll=g,t.browser=F,t.cacheEntryPossiblyAdded=function(t){++yt>ct&&(t.getActor().send("enforceCacheSizeLimit",ut),yt=0)},t.clamp=u,t.clearTileCache=function(t){var e=self.caches.delete(lt);t&&e.catch(t).then((function(){return t()}))},t.clipLine=Ou,t.clone=function(t){var e=new Io(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e},t.clone$1=b,t.clone$2=function(t){var e=new Io(3);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e},t.collisionCircleLayout=_l,t.config=B,t.create=function(){var t=new Io(16);return Io!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[11]=0,t[12]=0,t[13]=0,t[14]=0),t[0]=1,t[5]=1,t[10]=1,t[15]=1,t},t.create$1=function(){var t=new Io(9);return Io!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[5]=0,t[6]=0,t[7]=0),t[0]=1,t[4]=1,t[8]=1,t},t.create$2=function(){var t=new Io(4);return Io!=Float32Array&&(t[1]=0,t[2]=0),t[0]=1,t[3]=1,t},t.createCommonjsModule=e,t.createExpression=ln,t.createLayout=Ki,t.createStyleLayer=function(t){return"custom"===t.type?new gc(t):new yc[t.type](t)},t.cross=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=r[0],s=r[1],l=r[2];return t[0]=i*l-a*s,t[1]=a*o-n*l,t[2]=n*s-i*o,t},t.deepEqual=function t(e,r){if(Array.isArray(e)){if(!Array.isArray(r)||e.length!==r.length)return!1;for(var n=0;n<e.length;n++)if(!t(e[n],r[n]))return!1;return!0}if("object"==typeof e&&null!==e&&null!==r){if("object"!=typeof r)return!1;if(Object.keys(e).length!==Object.keys(r).length)return!1;for(var i in e)if(!t(e[i],r[i]))return!1;return!0}return e===r},t.dot=function(t,e){return t[0]*e[0]+t[1]*e[1]+t[2]*e[2]},t.dot$1=function(t,e){return t[0]*e[0]+t[1]*e[1]+t[2]*e[2]+t[3]*e[3]},t.ease=l,t.emitValidationErrors=Jn,t.endsWith=y,t.enforceCacheSizeLimit=function(t){ht(),tt&&tt.then((function(e){e.keys().then((function(r){for(var n=0;n<r.length-t;n++)e.delete(r[n])}))}))},t.evaluateSizeForFeature=wu,t.evaluateSizeForZoom=Tu,t.evaluateVariableOffset=Yu,t.evented=Si,t.extend=f,t.featureFilter=wn,t.filterObject=x,t.fromRotation=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=r,t[2]=0,t[3]=-r,t[4]=n,t[5]=0,t[6]=0,t[7]=0,t[8]=1,t},t.getAnchorAlignment=gu,t.getAnchorJustification=Wu,t.getArrayBuffer=kt,t.getImage=Et,t.getJSON=function(t,e){return Tt(f(t,{type:"json"}),e)},t.getRTLTextPluginStatus=Ei,t.getReferrer=_t,t.getVideo=function(t,e){var r,n,i=self.document.createElement("video");i.muted=!0,i.onloadstart=function(){e(null,i)};for(var a=0;a<t.length;a++){var o=self.document.createElement("source");r=t[a],n=void 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be used together.");var n=function(t,e){var r=[];if("FeatureCollection"===t.type)for(var n=0;n<t.features.length;n++)rt(r,t.features[n],e,n);else"Feature"===t.type?rt(r,t,e):rt(r,{geometry:t},e);return r}(t,e);this.tiles={},this.tileCoords=[],r&&(console.timeEnd("preprocess data"),console.log("index: maxZoom: %d, maxPoints: %d",e.indexMaxZoom,e.indexMaxPoints),console.time("generate tiles"),this.stats={},this.total=0),(n=function(t,e){var r=e.buffer/e.extent,n=t,i=lt(t,1,-1-r,r,0,-1,2,e),a=lt(t,1,1-r,2+r,0,-1,2,e);return(i||a)&&(n=lt(t,1,-r,1+r,0,-1,2,e)||[],i&&(n=gt(i,1).concat(n)),a&&(n=n.concat(gt(a,-1)))),n}(n,e)).length&&this.splitTile(n,0,0,0),r&&(n.length&&console.log("features: %d, points: %d",this.tiles[0].numFeatures,this.tiles[0].numPoints),console.timeEnd("generate tiles"),console.log("tiles generated:",this.total,JSON.stringify(this.stats)))}function kt(t,e,r){return 32*((1<<t)*r+e)+t}function At(t,e){var r=t.tileID.canonical;if(!this._geoJSONIndex)return e(null,null);var n=this._geoJSONIndex.getTile(r.z,r.x,r.y);if(!n)return e(null,null);var i=new g(n.features),a=_(i);0===a.byteOffset&&a.byteLength===a.buffer.byteLength||(a=new Uint8Array(a)),e(null,{vectorTile:i,rawData:a.buffer})}V.prototype.load=function(t){var e=this.options,r=e.log,n=e.minZoom,i=e.maxZoom,a=e.nodeSize;r&&console.time("total time");var o="prepare "+t.length+" points";r&&console.time(o),this.points=t;for(var s=[],l=0;l<t.length;l++)t[l].geometry&&s.push(q(t[l],l));this.trees[i+1]=new j(s,J,K,a,Float32Array),r&&console.timeEnd(o);for(var u=i;u>=n;u--){var c=+Date.now();s=this._cluster(s,u),this.trees[u]=new j(s,J,K,a,Float32Array),r&&console.log("z%d: %d clusters in %dms",u,s.length,+Date.now()-c)}return r&&console.timeEnd("total time"),this},V.prototype.getClusters=function(t,e){var r=((t[0]+180)%360+360)%360-180,n=Math.max(-90,Math.min(90,t[1])),i=180===t[2]?180:((t[2]+180)%360+360)%360-180,a=Math.max(-90,Math.min(90,t[3]));if(t[2]-t[0]>=360)r=-180,i=180;else if(r>i){var o=this.getClusters([r,n,180,a],e),s=this.getClusters([-180,n,i,a],e);return o.concat(s)}for(var l=this.trees[this._limitZoom(e)],u=[],c=0,f=l.range(Y(r),W(a),Y(i),W(n));c<f.length;c+=1){var h=f[c],p=l.points[h];u.push(p.numPoints?G(p):this.points[p.index])}return u},V.prototype.getChildren=function(t){var e=this._getOriginId(t),r=this._getOriginZoom(t),n="No cluster with the specified id.",i=this.trees[r];if(!i)throw new Error(n);var a=i.points[e];if(!a)throw new Error(n);for(var o=this.options.radius/(this.options.extent*Math.pow(2,r-1)),s=[],l=0,u=i.within(a.x,a.y,o);l<u.length;l+=1){var c=u[l],f=i.points[c];f.parentId===t&&s.push(f.numPoints?G(f):this.points[f.index])}if(0===s.length)throw new Error(n);return s},V.prototype.getLeaves=function(t,e,r){e=e||10,r=r||0;var n=[];return this._appendLeaves(n,t,e,r,0),n},V.prototype.getTile=function(t,e,r){var n=this.trees[this._limitZoom(t)],i=Math.pow(2,t),a=this.options,o=a.extent,s=a.radius/o,l=(r-s)/i,u=(r+1+s)/i,c={features:[]};return this._addTileFeatures(n.range((e-s)/i,l,(e+1+s)/i,u),n.points,e,r,i,c),0===e&&this._addTileFeatures(n.range(1-s/i,l,1,u),n.points,i,r,i,c),e===i-1&&this._addTileFeatures(n.range(0,l,s/i,u),n.points,-1,r,i,c),c.features.length?c:null},V.prototype.getClusterExpansionZoom=function(t){for(var e=this._getOriginZoom(t)-1;e<=this.options.maxZoom;){var r=this.getChildren(t);if(e++,1!==r.length)break;t=r[0].properties.cluster_id}return e},V.prototype._appendLeaves=function(t,e,r,n,i){for(var a=0,o=this.getChildren(e);a<o.length;a+=1){var s=o[a],l=s.properties;if(l&&l.cluster?i+l.point_count<=n?i+=l.point_count:i=this._appendLeaves(t,l.cluster_id,r,n,i):i<n?i++:t.push(s),t.length===r)break}return i},V.prototype._addTileFeatures=function(t,e,r,n,i,a){for(var o=0,s=t;o<s.length;o+=1){var l=e[s[o]],u=l.numPoints,c={type:1,geometry:[[Math.round(this.options.extent*(l.x*i-r)),Math.round(this.options.extent*(l.y*i-n))]],tags:u?Z(l):this.points[l.index].properties},f=void 0;u?f=l.id:this.options.generateId?f=l.index:this.points[l.index].id&&(f=this.points[l.index].id),void 0!==f&&(c.id=f),a.features.push(c)}},V.prototype._limitZoom=function(t){return Math.max(this.options.minZoom,Math.min(t,this.options.maxZoom+1))},V.prototype._cluster=function(t,e){for(var r=[],n=this.options,i=n.radius,a=n.extent,o=n.reduce,s=i/(a*Math.pow(2,e)),l=0;l<t.length;l++){var u=t[l];if(!(u.zoom<=e)){u.zoom=e;for(var c=this.trees[e+1],f=c.within(u.x,u.y,s),h=u.numPoints||1,p=u.x*h,d=u.y*h,v=o&&h>1?this._map(u,!0):null,g=(l<<5)+(e+1)+this.points.length,y=0,m=f;y<m.length;y+=1){var x=m[y],b=c.points[x];if(!(b.zoom<=e)){b.zoom=e;var _=b.numPoints||1;p+=b.x*_,d+=b.y*_,h+=_,b.parentId=g,o&&(v||(v=this._map(u,!0)),o(v,this._map(b)))}}1===h?r.push(u):(u.parentId=g,r.push(H(p/h,d/h,g,h,v)))}}return r},V.prototype._getOriginId=function(t){return t-this.points.length>>5},V.prototype._getOriginZoom=function(t){return(t-this.points.length)%32},V.prototype._map=function(t,e){if(t.numPoints)return e?X({},t.properties):t.properties;var r=this.points[t.index].properties,n=this.options.map(r);return e&&n===r?X({},n):n},Tt.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},Tt.prototype.splitTile=function(t,e,r,n,i,a,o){for(var s=[t,e,r,n],l=this.options,u=l.debug;s.length;){n=s.pop(),r=s.pop(),e=s.pop(),t=s.pop();var c=1<<e,f=kt(e,r,n),h=this.tiles[f];if(!h&&(u>1&&console.time("creation"),h=this.tiles[f]=bt(t,e,r,n,l),this.tileCoords.push({z:e,x:r,y:n}),u)){u>1&&(console.log("tile z%d-%d-%d (features: %d, points: %d, simplified: %d)",e,r,n,h.numFeatures,h.numPoints,h.numSimplified),console.timeEnd("creation"));var p="z"+e;this.stats[p]=(this.stats[p]||0)+1,this.total++}if(h.source=t,i){if(e===l.maxZoom||e===i)continue;var d=1<<i-e;if(r!==Math.floor(a/d)||n!==Math.floor(o/d))continue}else if(e===l.indexMaxZoom||h.numPoints<=l.indexMaxPoints)continue;if(h.source=null,0!==t.length){u>1&&console.time("clipping");var v,g,y,m,x,b,_=.5*l.buffer/l.extent,w=.5-_,T=.5+_,k=1+_;v=g=y=m=null,x=lt(t,c,r-_,r+T,0,h.minX,h.maxX,l),b=lt(t,c,r+w,r+k,0,h.minX,h.maxX,l),t=null,x&&(v=lt(x,c,n-_,n+T,1,h.minY,h.maxY,l),g=lt(x,c,n+w,n+k,1,h.minY,h.maxY,l),x=null),b&&(y=lt(b,c,n-_,n+T,1,h.minY,h.maxY,l),m=lt(b,c,n+w,n+k,1,h.minY,h.maxY,l),b=null),u>1&&console.timeEnd("clipping"),s.push(v||[],e+1,2*r,2*n),s.push(g||[],e+1,2*r,2*n+1),s.push(y||[],e+1,2*r+1,2*n),s.push(m||[],e+1,2*r+1,2*n+1)}}},Tt.prototype.getTile=function(t,e,r){var n=this.options,i=n.extent,a=n.debug;if(t<0||t>24)return null;var o=1<<t,s=kt(t,e=(e%o+o)%o,r);if(this.tiles[s])return mt(this.tiles[s],i);a>1&&console.log("drilling down to z%d-%d-%d",t,e,r);for(var l,u=t,c=e,f=r;!l&&u>0;)u--,c=Math.floor(c/2),f=Math.floor(f/2),l=this.tiles[kt(u,c,f)];return l&&l.source?(a>1&&console.log("found parent tile z%d-%d-%d",u,c,f),a>1&&console.time("drilling down"),this.splitTile(l.source,u,c,f,t,e,r),a>1&&console.timeEnd("drilling down"),this.tiles[s]?mt(this.tiles[s],i):null):null};var Mt=function(e){function r(t,r,n,i){e.call(this,t,r,n,At),i&&(this.loadGeoJSON=i)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadData=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),this._pendingCallback=e,this._pendingLoadDataParams=t,this._state&&"Idle"!==this._state?this._state="NeedsLoadData":(this._state="Coalescing",this._loadData())},r.prototype._loadData=function(){var e=this;if(this._pendingCallback&&this._pendingLoadDataParams){var r=this._pendingCallback,n=this._pendingLoadDataParams;delete this._pendingCallback,delete this._pendingLoadDataParams;var i=!!(n&&n.request&&n.request.collectResourceTiming)&&new t.RequestPerformance(n.request);this.loadGeoJSON(n,(function(a,o){if(a||!o)return r(a);if("object"!=typeof o)return r(new Error("Input data given to '"+n.source+"' is not a valid GeoJSON object."));f(o,!0);try{e._geoJSONIndex=n.cluster?new V(function(e){var r=e.superclusterOptions,n=e.clusterProperties;if(!n||!r)return r;for(var i={},a={},o={accumulated:null,zoom:0},s={properties:null},l=Object.keys(n),u=0,c=l;u<c.length;u+=1){var f=c[u],h=n[f],p=h[0],d=h[1],v=t.createExpression(d),g=t.createExpression("string"==typeof p?[p,["accumulated"],["get",f]]:p);i[f]=v.value,a[f]=g.value}return r.map=function(t){s.properties=t;for(var e={},r=0,n=l;r<n.length;r+=1){var a=n[r];e[a]=i[a].evaluate(o,s)}return e},r.reduce=function(t,e){s.properties=e;for(var r=0,n=l;r<n.length;r+=1){var i=n[r];o.accumulated=t[i],t[i]=a[i].evaluate(o,s)}},r}(n)).load(o.features):function(t,e){return new Tt(t,e)}(o,n.geojsonVtOptions)}catch(a){return r(a)}e.loaded={};var s={};if(i){var l=i.finish();l&&(s.resourceTiming={},s.resourceTiming[n.source]=JSON.parse(JSON.stringify(l)))}r(null,s)}))}},r.prototype.coalesce=function(){"Coalescing"===this._state?this._state="Idle":"NeedsLoadData"===this._state&&(this._state="Coalescing",this._loadData())},r.prototype.reloadTile=function(t,r){var n=this.loaded,i=t.uid;return n&&n[i]?e.prototype.reloadTile.call(this,t,r):this.loadTile(t,r)},r.prototype.loadGeoJSON=function(e,r){if(e.request)t.getJSON(e.request,r);else{if("string"!=typeof e.data)return r(new Error("Input data given to '"+e.source+"' is not a valid GeoJSON object."));try{return r(null,JSON.parse(e.data))}catch(t){return r(new Error("Input data given to '"+e.source+"' is not a valid GeoJSON object."))}}},r.prototype.removeSource=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),e()},r.prototype.getClusterExpansionZoom=function(t,e){try{e(null,this._geoJSONIndex.getClusterExpansionZoom(t.clusterId))}catch(t){e(t)}},r.prototype.getClusterChildren=function(t,e){try{e(null,this._geoJSONIndex.getChildren(t.clusterId))}catch(t){e(t)}},r.prototype.getClusterLeaves=function(t,e){try{e(null,this._geoJSONIndex.getLeaves(t.clusterId,t.limit,t.offset))}catch(t){e(t)}},r}(l);var St=function(e){var r=this;this.self=e,this.actor=new t.Actor(e,this),this.layerIndexes={},this.availableImages={},this.workerSourceTypes={vector:l,geojson:Mt},this.workerSources={},this.demWorkerSources={},this.self.registerWorkerSource=function(t,e){if(r.workerSourceTypes[t])throw new Error('Worker source with name "'+t+'" already registered.');r.workerSourceTypes[t]=e},this.self.registerRTLTextPlugin=function(e){if(t.plugin.isParsed())throw new Error("RTL text plugin already registered.");t.plugin.applyArabicShaping=e.applyArabicShaping,t.plugin.processBidirectionalText=e.processBidirectionalText,t.plugin.processStyledBidirectionalText=e.processStyledBidirectionalText}};return St.prototype.setReferrer=function(t,e){this.referrer=e},St.prototype.setImages=function(t,e,r){for(var n in this.availableImages[t]=e,this.workerSources[t]){var i=this.workerSources[t][n];for(var a in i)i[a].availableImages=e}r()},St.prototype.setLayers=function(t,e,r){this.getLayerIndex(t).replace(e),r()},St.prototype.updateLayers=function(t,e,r){this.getLayerIndex(t).update(e.layers,e.removedIds),r()},St.prototype.loadTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).loadTile(e,r)},St.prototype.loadDEMTile=function(t,e,r){this.getDEMWorkerSource(t,e.source).loadTile(e,r)},St.prototype.reloadTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).reloadTile(e,r)},St.prototype.abortTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).abortTile(e,r)},St.prototype.removeTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).removeTile(e,r)},St.prototype.removeDEMTile=function(t,e){this.getDEMWorkerSource(t,e.source).removeTile(e)},St.prototype.removeSource=function(t,e,r){if(this.workerSources[t]&&this.workerSources[t][e.type]&&this.workerSources[t][e.type][e.source]){var n=this.workerSources[t][e.type][e.source];delete this.workerSources[t][e.type][e.source],void 0!==n.removeSource?n.removeSource(e,r):r()}},St.prototype.loadWorkerSource=function(t,e,r){try{this.self.importScripts(e.url),r()}catch(t){r(t.toString())}},St.prototype.syncRTLPluginState=function(e,r,n){try{t.plugin.setState(r);var i=t.plugin.getPluginURL();if(t.plugin.isLoaded()&&!t.plugin.isParsed()&&null!=i){this.self.importScripts(i);var a=t.plugin.isParsed();n(a?void 0:new Error("RTL Text Plugin failed to import scripts from "+i),a)}}catch(t){n(t.toString())}},St.prototype.getAvailableImages=function(t){var e=this.availableImages[t];return e||(e=[]),e},St.prototype.getLayerIndex=function(t){var e=this.layerIndexes[t];return e||(e=this.layerIndexes[t]=new n),e},St.prototype.getWorkerSource=function(t,e,r){var n=this;if(this.workerSources[t]||(this.workerSources[t]={}),this.workerSources[t][e]||(this.workerSources[t][e]={}),!this.workerSources[t][e][r]){var i={send:function(e,r,i){n.actor.send(e,r,i,t)}};this.workerSources[t][e][r]=new 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u=Object.defineProperty({},"passive",{get:function(){l=!0}});t.window.addEventListener("test",u,u),t.window.removeEventListener("test",u,u)}catch(t){l=!1}r.addEventListener=function(t,e,r,n){void 0===n&&(n={}),"passive"in n&&l?t.addEventListener(e,r,n):t.addEventListener(e,r,n.capture)},r.removeEventListener=function(t,e,r,n){void 0===n&&(n={}),"passive"in n&&l?t.removeEventListener(e,r,n):t.removeEventListener(e,r,n.capture)};var c=function(e){e.preventDefault(),e.stopPropagation(),t.window.removeEventListener("click",c,!0)};function f(t){var e=t.userImage;return!!(e&&e.render&&e.render())&&(t.data.replace(new Uint8Array(e.data.buffer)),!0)}r.suppressClick=function(){t.window.addEventListener("click",c,!0),t.window.setTimeout((function(){t.window.removeEventListener("click",c,!0)}),0)},r.mousePos=function(e,r){var n=e.getBoundingClientRect();return new t.Point(r.clientX-n.left-e.clientLeft,r.clientY-n.top-e.clientTop)},r.touchPos=function(e,r){for(var 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this.images[t]},r.prototype.addImage=function(t,e){this._validate(t,e)&&(this.images[t]=e)},r.prototype._validate=function(e,r){var n=!0;return this._validateStretch(r.stretchX,r.data&&r.data.width)||(this.fire(new t.ErrorEvent(new Error('Image "'+e+'" has invalid "stretchX" value'))),n=!1),this._validateStretch(r.stretchY,r.data&&r.data.height)||(this.fire(new t.ErrorEvent(new Error('Image "'+e+'" has invalid "stretchY" value'))),n=!1),this._validateContent(r.content,r)||(this.fire(new t.ErrorEvent(new Error('Image "'+e+'" has invalid "content" value'))),n=!1),n},r.prototype._validateStretch=function(t,e){if(!t)return!0;for(var r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];if(a[0]<r||a[1]<a[0]||e<a[1])return!1;r=a[1]}return!0},r.prototype._validateContent=function(t,e){return!(t&&(4!==t.length||t[0]<0||e.data.width<t[0]||t[1]<0||e.data.height<t[1]||t[2]<0||e.data.width<t[2]||t[3]<0||e.data.height<t[3]||t[2]<t[0]||t[3]<t[1]))},r.prototype.updateImage=function(t,e){var r=this.images[t];e.version=r.version+1,this.images[t]=e,this.updatedImages[t]=!0},r.prototype.removeImage=function(t){var e=this.images[t];delete this.images[t],delete this.patterns[t],e.userImage&&e.userImage.onRemove&&e.userImage.onRemove()},r.prototype.listImages=function(){return Object.keys(this.images)},r.prototype.getImages=function(t,e){var r=!0;if(!this.isLoaded())for(var n=0,i=t;n<i.length;n+=1){var a=i[n];this.images[a]||(r=!1)}this.isLoaded()||r?this._notify(t,e):this.requestors.push({ids:t,callback:e})},r.prototype._notify=function(e,r){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i];this.images[o]||this.fire(new t.Event("styleimagemissing",{id:o}));var s=this.images[o];s?n[o]={data:s.data.clone(),pixelRatio:s.pixelRatio,sdf:s.sdf,version:s.version,stretchX:s.stretchX,stretchY:s.stretchY,content:s.content,hasRenderCallback:Boolean(s.userImage&&s.userImage.render)}:t.warnOnce('Image "'+o+'" could not be loaded. Please make sure you have added the image with map.addImage() or a "sprite" property in your style. You can provide missing images by listening for the "styleimagemissing" map event.')}r(null,n)},r.prototype.getPixelSize=function(){var t=this.atlasImage;return{width:t.width,height:t.height}},r.prototype.getPattern=function(e){var r=this.patterns[e],n=this.getImage(e);if(!n)return null;if(r&&r.position.version===n.version)return r.position;if(r)r.position.version=n.version;else{var i={w:n.data.width+2,h:n.data.height+2,x:0,y:0},a=new t.ImagePosition(i,n);this.patterns[e]={bin:i,position:a}}return this._updatePatternAtlas(),this.patterns[e].position},r.prototype.bind=function(e){var r=e.gl;this.atlasTexture?this.dirty&&(this.atlasTexture.update(this.atlasImage),this.dirty=!1):this.atlasTexture=new t.Texture(e,this.atlasImage,r.RGBA),this.atlasTexture.bind(r.LINEAR,r.CLAMP_TO_EDGE)},r.prototype._updatePatternAtlas=function(){var e=[];for(var r in this.patterns)e.push(this.patterns[r].bin);var n=t.potpack(e),i=n.w,a=n.h,o=this.atlasImage;for(var s in o.resize({width:i||1,height:a||1}),this.patterns){var l=this.patterns[s].bin,u=l.x+1,c=l.y+1,f=this.images[s].data,h=f.width,p=f.height;t.RGBAImage.copy(f,o,{x:0,y:0},{x:u,y:c},{width:h,height:p}),t.RGBAImage.copy(f,o,{x:0,y:p-1},{x:u,y:c-1},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:u,y:c+p},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:h-1,y:0},{x:u-1,y:c},{width:1,height:p}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:u+h,y:c},{width:1,height:p})}this.dirty=!0},r.prototype.beginFrame=function(){this.callbackDispatchedThisFrame={}},r.prototype.dispatchRenderCallbacks=function(t){for(var e=0,r=t;e<r.length;e+=1){var n=r[e];if(!this.callbackDispatchedThisFrame[n]){this.callbackDispatchedThisFrame[n]=!0;var i=this.images[n];f(i)&&this.updateImage(n,i)}}},r}(t.Evented);var p=g,d=g,v=1e20;function g(t,e,r,n,i,a){this.fontSize=t||24,this.buffer=void 0===e?3:e,this.cutoff=n||.25,this.fontFamily=i||"sans-serif",this.fontWeight=a||"normal",this.radius=r||8;var o=this.size=this.fontSize+2*this.buffer;this.canvas=document.createElement("canvas"),this.canvas.width=this.canvas.height=o,this.ctx=this.canvas.getContext("2d"),this.ctx.font=this.fontWeight+" "+this.fontSize+"px "+this.fontFamily,this.ctx.textBaseline="middle",this.ctx.fillStyle="black",this.gridOuter=new Float64Array(o*o),this.gridInner=new Float64Array(o*o),this.f=new Float64Array(o),this.d=new Float64Array(o),this.z=new Float64Array(o+1),this.v=new Int16Array(o),this.middle=Math.round(o/2*(navigator.userAgent.indexOf("Gecko/")>=0?1.2:1))}function y(t,e,r,n,i,a,o){for(var s=0;s<e;s++){for(var l=0;l<r;l++)n[l]=t[l*e+s];for(m(n,i,a,o,r),l=0;l<r;l++)t[l*e+s]=i[l]}for(l=0;l<r;l++){for(s=0;s<e;s++)n[s]=t[l*e+s];for(m(n,i,a,o,e),s=0;s<e;s++)t[l*e+s]=Math.sqrt(i[s])}}function m(t,e,r,n,i){r[0]=0,n[0]=-v,n[1]=+v;for(var a=1,o=0;a<i;a++){for(var s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);s<=n[o];)o--,s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);r[++o]=a,n[o]=s,n[o+1]=+v}for(a=0,o=0;a<i;a++){for(;n[o+1]<a;)o++;e[a]=(a-r[o])*(a-r[o])+t[r[o]]}}g.prototype.draw=function(t){this.ctx.clearRect(0,0,this.size,this.size),this.ctx.fillText(t,this.buffer,this.middle);for(var e=this.ctx.getImageData(0,0,this.size,this.size),r=new Uint8ClampedArray(this.size*this.size),n=0;n<this.size*this.size;n++){var i=e.data[4*n+3]/255;this.gridOuter[n]=1===i?0:0===i?v:Math.pow(Math.max(0,.5-i),2),this.gridInner[n]=1===i?v:0===i?0:Math.pow(Math.max(0,i-.5),2)}for(y(this.gridOuter,this.size,this.size,this.f,this.d,this.v,this.z),y(this.gridInner,this.size,this.size,this.f,this.d,this.v,this.z),n=0;n<this.size*this.size;n++){var a=this.gridOuter[n]-this.gridInner[n];r[n]=Math.max(0,Math.min(255,Math.round(255-255*(a/this.radius+this.cutoff))))}return r},p.default=d;var x=function(t,e){this.requestManager=t,this.localIdeographFontFamily=e,this.entries={}};x.prototype.setURL=function(t){this.url=t},x.prototype.getGlyphs=function(e,r){var n=this,i=[];for(var a in e)for(var o=0,s=e[a];o<s.length;o+=1){var l=s[o];i.push({stack:a,id:l})}t.asyncAll(i,(function(t,e){var r=t.stack,i=t.id,a=n.entries[r];a||(a=n.entries[r]={glyphs:{},requests:{},ranges:{}});var o=a.glyphs[i];if(void 0===o){if(o=n._tinySDF(a,r,i))return a.glyphs[i]=o,void e(null,{stack:r,id:i,glyph:o});var s=Math.floor(i/256);if(256*s>65535)e(new Error("glyphs > 65535 not supported"));else if(a.ranges[s])e(null,{stack:r,id:i,glyph:o});else{var l=a.requests[s];l||(l=a.requests[s]=[],x.loadGlyphRange(r,s,n.url,n.requestManager,(function(t,e){if(e){for(var r in e)n._doesCharSupportLocalGlyph(+r)||(a.glyphs[+r]=e[+r]);a.ranges[s]=!0}for(var i=0,o=l;i<o.length;i+=1)(0,o[i])(t,e);delete a.requests[s]}))),l.push((function(t,n){t?e(t):n&&e(null,{stack:r,id:i,glyph:n[i]||null})}))}}else e(null,{stack:r,id:i,glyph:o})}),(function(t,e){if(t)r(t);else if(e){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.stack,l=o.id,u=o.glyph;(n[s]||(n[s]={}))[l]=u&&{id:u.id,bitmap:u.bitmap.clone(),metrics:u.metrics}}r(null,n)}}))},x.prototype._doesCharSupportLocalGlyph=function(e){return!!this.localIdeographFontFamily&&(t.isChar["CJK Unified Ideographs"](e)||t.isChar["Hangul Syllables"](e)||t.isChar.Hiragana(e)||t.isChar.Katakana(e))},x.prototype._tinySDF=function(e,r,n){var i=this.localIdeographFontFamily;if(i&&this._doesCharSupportLocalGlyph(n)){var a=e.tinySDF;if(!a){var o="400";/bold/i.test(r)?o="900":/medium/i.test(r)?o="500":/light/i.test(r)&&(o="200"),a=e.tinySDF=new x.TinySDF(24,3,8,.25,i,o)}return{id:n,bitmap:new t.AlphaImage({width:30,height:30},a.draw(String.fromCharCode(n))),metrics:{width:24,height:24,left:0,top:-8,advance:24}}}},x.loadGlyphRange=function(e,r,n,i,a){var o=256*r,s=o+255,l=i.transformRequest(i.normalizeGlyphsURL(n).replace("{fontstack}",e).replace("{range}",o+"-"+s),t.ResourceType.Glyphs);t.getArrayBuffer(l,(function(e,r){if(e)a(e);else if(r){for(var n={},i=0,o=t.parseGlyphPBF(r);i<o.length;i+=1){var s=o[i];n[s.id]=s}a(null,n)}}))},x.TinySDF=p;var b=function(){this.specification=t.styleSpec.light.position};b.prototype.possiblyEvaluate=function(e,r){return t.sphericalToCartesian(e.expression.evaluate(r))},b.prototype.interpolate=function(e,r,n){return{x:t.number(e.x,r.x,n),y:t.number(e.y,r.y,n),z:t.number(e.z,r.z,n)}};var _=new t.Properties({anchor:new t.DataConstantProperty(t.styleSpec.light.anchor),position:new b,color:new t.DataConstantProperty(t.styleSpec.light.color),intensity:new t.DataConstantProperty(t.styleSpec.light.intensity)}),w="-transition",T=function(e){function r(r){e.call(this),this._transitionable=new t.Transitionable(_),this.setLight(r),this._transitioning=this._transitionable.untransitioned()}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getLight=function(){return this._transitionable.serialize()},r.prototype.setLight=function(e,r){if(void 0===r&&(r={}),!this._validate(t.validateLight,e,r))for(var n in e){var i=e[n];t.endsWith(n,w)?this._transitionable.setTransition(n.slice(0,-11),i):this._transitionable.setValue(n,i)}},r.prototype.updateTransitions=function(t){this._transitioning=this._transitionable.transitioned(t,this._transitioning)},r.prototype.hasTransition=function(){return this._transitioning.hasTransition()},r.prototype.recalculate=function(t){this.properties=this._transitioning.possiblyEvaluate(t)},r.prototype._validate=function(e,r,n){return(!n||!1!==n.validate)&&t.emitValidationErrors(this,e.call(t.validateStyle,t.extend({value:r,style:{glyphs:!0,sprite:!0},styleSpec:t.styleSpec})))},r}(t.Evented),k=function(t,e){this.width=t,this.height=e,this.nextRow=0,this.data=new Uint8Array(this.width*this.height),this.dashEntry={}};k.prototype.getDash=function(t,e){var r=t.join(",")+String(e);return this.dashEntry[r]||(this.dashEntry[r]=this.addDash(t,e)),this.dashEntry[r]},k.prototype.getDashRanges=function(t,e,r){var n=[],i=t.length%2==1?-t[t.length-1]*r:0,a=t[0]*r,o=!0;n.push({left:i,right:a,isDash:o,zeroLength:0===t[0]});for(var s=t[0],l=1;l<t.length;l++){o=!o;var u=t[l];i=s*r,a=(s+=u)*r,n.push({left:i,right:a,isDash:o,zeroLength:0===u})}return n},k.prototype.addRoundDash=function(t,e,r){for(var n=e/2,i=-r;i<=r;i++)for(var a=this.nextRow+r+i,o=this.width*a,s=0,l=t[s],u=0;u<this.width;u++){u/l.right>1&&(l=t[++s]);var c=Math.abs(u-l.left),f=Math.abs(u-l.right),h=Math.min(c,f),p=void 0,d=i/r*(n+1);if(l.isDash){var v=n-Math.abs(d);p=Math.sqrt(h*h+v*v)}else p=n-Math.sqrt(h*h+d*d);this.data[o+u]=Math.max(0,Math.min(255,p+128))}},k.prototype.addRegularDash=function(t){for(var e=t.length-1;e>=0;--e){var r=t[e],n=t[e+1];r.zeroLength?t.splice(e,1):n&&n.isDash===r.isDash&&(n.left=r.left,t.splice(e,1))}var i=t[0],a=t[t.length-1];i.isDash===a.isDash&&(i.left=a.left-this.width,a.right=i.right+this.width);for(var o=this.width*this.nextRow,s=0,l=t[s],u=0;u<this.width;u++){u/l.right>1&&(l=t[++s]);var c=Math.abs(u-l.left),f=Math.abs(u-l.right),h=Math.min(c,f),p=l.isDash?h:-h;this.data[o+u]=Math.max(0,Math.min(255,p+128))}},k.prototype.addDash=function(e,r){var n=r?7:0,i=2*n+1;if(this.nextRow+i>this.height)return t.warnOnce("LineAtlas out of space"),null;for(var a=0,o=0;o<e.length;o++)a+=e[o];if(0!==a){var s=this.width/a,l=this.getDashRanges(e,this.width,s);r?this.addRoundDash(l,s,n):this.addRegularDash(l)}var u={y:(this.nextRow+n+.5)/this.height,height:2*n/this.height,width:a};return this.nextRow+=i,this.dirty=!0,u},k.prototype.bind=function(t){var e=t.gl;this.texture?(e.bindTexture(e.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,e.texSubImage2D(e.TEXTURE_2D,0,0,0,this.width,this.height,e.ALPHA,e.UNSIGNED_BYTE,this.data))):(this.texture=e.createTexture(),e.bindTexture(e.TEXTURE_2D,this.texture),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_S,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_T,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,e.LINEAR),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,e.LINEAR),e.texImage2D(e.TEXTURE_2D,0,e.ALPHA,this.width,this.height,0,e.ALPHA,e.UNSIGNED_BYTE,this.data))};var A=function e(r,n){this.workerPool=r,this.actors=[],this.currentActor=0,this.id=t.uniqueId();for(var i=this.workerPool.acquire(this.id),a=0;a<i.length;a++){var o=i[a],s=new e.Actor(o,n,this.id);s.name="Worker "+a,this.actors.push(s)}};function M(e,r,n){var i=function(i,a){if(i)return n(i);if(a){var o=t.pick(t.extend(a,e),["tiles","minzoom","maxzoom","attribution","mapbox_logo","bounds","scheme","tileSize","encoding"]);a.vector_layers&&(o.vectorLayers=a.vector_layers,o.vectorLayerIds=o.vectorLayers.map((function(t){return t.id}))),o.tiles=r.canonicalizeTileset(o,e.url),n(null,o)}};return e.url?t.getJSON(r.transformRequest(r.normalizeSourceURL(e.url),t.ResourceType.Source),i):t.browser.frame((function(){return i(null,e)}))}A.prototype.broadcast=function(e,r,n){n=n||function(){},t.asyncAll(this.actors,(function(t,n){t.send(e,r,n)}),n)},A.prototype.getActor=function(){return this.currentActor=(this.currentActor+1)%this.actors.length,this.actors[this.currentActor]},A.prototype.remove=function(){this.actors.forEach((function(t){t.remove()})),this.actors=[],this.workerPool.release(this.id)},A.Actor=t.Actor;var S=function(e,r,n){this.bounds=t.LngLatBounds.convert(this.validateBounds(e)),this.minzoom=r||0,this.maxzoom=n||24};S.prototype.validateBounds=function(t){return Array.isArray(t)&&4===t.length?[Math.max(-180,t[0]),Math.max(-90,t[1]),Math.min(180,t[2]),Math.min(90,t[3])]:[-180,-90,180,90]},S.prototype.contains=function(e){var r=Math.pow(2,e.z),n=Math.floor(t.mercatorXfromLng(this.bounds.getWest())*r),i=Math.floor(t.mercatorYfromLat(this.bounds.getNorth())*r),a=Math.ceil(t.mercatorXfromLng(this.bounds.getEast())*r),o=Math.ceil(t.mercatorYfromLat(this.bounds.getSouth())*r);return e.x>=n&&e.x<a&&e.y>=i&&e.y<o};var E=function(e){function r(r,n,i,a){if(e.call(this),this.id=r,this.dispatcher=i,this.type="vector",this.minzoom=0,this.maxzoom=22,this.scheme="xyz",this.tileSize=512,this.reparseOverscaled=!0,this.isTileClipped=!0,this._loaded=!1,t.extend(this,t.pick(n,["url","scheme","tileSize","promoteId"])),this._options=t.extend({type:"vector"},n),this._collectResourceTiming=n.collectResourceTiming,512!==this.tileSize)throw new Error("vector tile sources must have a tileSize of 512");this.setEventedParent(a)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event("dataloading",{dataType:"source"})),this._tileJSONRequest=M(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new S(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles,e.map._requestManager._customAccessToken),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken,e.map._requestManager._customAccessToken),e.fire(new t.Event("data",{dataType:"source",sourceDataType:"metadata"})),e.fire(new t.Event("data",{dataType:"source",sourceDataType:"content"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme)),i={request:this.map._requestManager.transformRequest(n,t.ResourceType.Tile),uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,tileSize:this.tileSize*e.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};function a(n,i){return delete e.request,e.aborted?r(null):n&&404!==n.status?r(n):(i&&i.resourceTiming&&(e.resourceTiming=i.resourceTiming),this.map._refreshExpiredTiles&&i&&e.setExpiryData(i),e.loadVectorData(i,this.map.painter),t.cacheEntryPossiblyAdded(this.dispatcher),r(null),void(e.reloadCallback&&(this.loadTile(e,e.reloadCallback),e.reloadCallback=null)))}i.request.collectResourceTiming=this._collectResourceTiming,e.actor&&"expired"!==e.state?"loading"===e.state?e.reloadCallback=r:e.request=e.actor.send("reloadTile",i,a.bind(this)):(e.actor=this.dispatcher.getActor(),e.request=e.actor.send("loadTile",i,a.bind(this)))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.actor&&t.actor.send("abortTile",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.unloadTile=function(t){t.unloadVectorData(),t.actor&&t.actor.send("removeTile",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.hasTransition=function(){return!1},r}(t.Evented),L=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.dispatcher=i,this.setEventedParent(a),this.type="raster",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme="xyz",this.tileSize=512,this._loaded=!1,this._options=t.extend({type:"raster"},n),t.extend(this,t.pick(n,["url","scheme","tileSize"]))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event("dataloading",{dataType:"source"})),this._tileJSONRequest=M(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new S(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken),e.fire(new t.Event("data",{dataType:"source",sourceDataType:"metadata"})),e.fire(new t.Event("data",{dataType:"source",sourceDataType:"content"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.loadTile=function(e,r){var n=this,i=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);e.request=t.getImage(this.map._requestManager.transformRequest(i,t.ResourceType.Tile),(function(i,a){if(delete e.request,e.aborted)e.state="unloaded",r(null);else if(i)e.state="errored",r(i);else if(a){n.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=n.map.painter.context,s=o.gl;e.texture=n.map.painter.getTileTexture(a.width),e.texture?e.texture.update(a,{useMipmap:!0}):(e.texture=new t.Texture(o,a,s.RGBA,{useMipmap:!0}),e.texture.bind(s.LINEAR,s.CLAMP_TO_EDGE,s.LINEAR_MIPMAP_NEAREST),o.extTextureFilterAnisotropic&&s.texParameterf(s.TEXTURE_2D,o.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,o.extTextureFilterAnisotropicMax)),e.state="loaded",t.cacheEntryPossiblyAdded(n.dispatcher),r(null)}}))},r.prototype.abortTile=function(t,e){t.request&&(t.request.cancel(),delete t.request),e()},r.prototype.unloadTile=function(t,e){t.texture&&this.map.painter.saveTileTexture(t.texture),e()},r.prototype.hasTransition=function(){return!1},r}(t.Evented),C=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),this.type="raster-dem",this.maxzoom=22,this._options=t.extend({type:"raster-dem"},n),this.encoding=n.encoding||"mapbox"}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.serialize=function(){return{type:"raster-dem",url:this.url,tileSize:this.tileSize,tiles:this.tiles,bounds:this.bounds,encoding:this.encoding}},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);function i(t,n){t&&(e.state="errored",r(t)),n&&(e.dem=n,e.needsHillshadePrepare=!0,e.state="loaded",r(null))}e.request=t.getImage(this.map._requestManager.transformRequest(n,t.ResourceType.Tile),function(n,a){if(delete e.request,e.aborted)e.state="unloaded",r(null);else if(n)e.state="errored",r(n);else if(a){this.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=t.window.ImageBitmap&&a instanceof t.window.ImageBitmap&&t.offscreenCanvasSupported()?a:t.browser.getImageData(a,1),s={uid:e.uid,coord:e.tileID,source:this.id,rawImageData:o,encoding:this.encoding};e.actor&&"expired"!==e.state||(e.actor=this.dispatcher.getActor(),e.actor.send("loadDEMTile",s,i.bind(this)))}}.bind(this)),e.neighboringTiles=this._getNeighboringTiles(e.tileID)},r.prototype._getNeighboringTiles=function(e){var r=e.canonical,n=Math.pow(2,r.z),i=(r.x-1+n)%n,a=0===r.x?e.wrap-1:e.wrap,o=(r.x+1+n)%n,s=r.x+1===n?e.wrap+1:e.wrap,l={};return l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y).key]={backfilled:!1},r.y>0&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+1<n&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y+1).key]={backfilled:!1}),l},r.prototype.unloadTile=function(t){t.demTexture&&this.map.painter.saveTileTexture(t.demTexture),t.fbo&&(t.fbo.destroy(),delete t.fbo),t.dem&&delete t.dem,delete t.neighboringTiles,t.state="unloaded",t.actor&&t.actor.send("removeDEMTile",{uid:t.uid,source:this.id})},r}(L),P=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.type="geojson",this.minzoom=0,this.maxzoom=18,this.tileSize=512,this.isTileClipped=!0,this.reparseOverscaled=!0,this._removed=!1,this._loaded=!1,this.actor=i.getActor(),this.setEventedParent(a),this._data=n.data,this._options=t.extend({},n),this._collectResourceTiming=n.collectResourceTiming,this._resourceTiming=[],void 0!==n.maxzoom&&(this.maxzoom=n.maxzoom),n.type&&(this.type=n.type),n.attribution&&(this.attribution=n.attribution),this.promoteId=n.promoteId;var o=t.EXTENT/this.tileSize;this.workerOptions=t.extend({source:this.id,cluster:n.cluster||!1,geojsonVtOptions:{buffer:(void 0!==n.buffer?n.buffer:128)*o,tolerance:(void 0!==n.tolerance?n.tolerance:.375)*o,extent:t.EXTENT,maxZoom:this.maxzoom,lineMetrics:n.lineMetrics||!1,generateId:n.generateId||!1},superclusterOptions:{maxZoom:void 0!==n.clusterMaxZoom?Math.min(n.clusterMaxZoom,this.maxzoom-1):this.maxzoom-1,extent:t.EXTENT,radius:(n.clusterRadius||50)*o,log:!1,generateId:n.generateId||!1},clusterProperties:n.clusterProperties},n.workerOptions)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this.fire(new t.Event("dataloading",{dataType:"source"})),this._updateWorkerData((function(r){if(r)e.fire(new t.ErrorEvent(r));else{var n={dataType:"source",sourceDataType:"metadata"};e._collectResourceTiming&&e._resourceTiming&&e._resourceTiming.length>0&&(n.resourceTiming=e._resourceTiming,e._resourceTiming=[]),e.fire(new t.Event("data",n))}}))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setData=function(e){var r=this;return this._data=e,this.fire(new t.Event("dataloading",{dataType:"source"})),this._updateWorkerData((function(e){if(e)r.fire(new t.ErrorEvent(e));else{var n={dataType:"source",sourceDataType:"content"};r._collectResourceTiming&&r._resourceTiming&&r._resourceTiming.length>0&&(n.resourceTiming=r._resourceTiming,r._resourceTiming=[]),r.fire(new t.Event("data",n))}})),this},r.prototype.getClusterExpansionZoom=function(t,e){return this.actor.send("geojson.getClusterExpansionZoom",{clusterId:t,source:this.id},e),this},r.prototype.getClusterChildren=function(t,e){return this.actor.send("geojson.getClusterChildren",{clusterId:t,source:this.id},e),this},r.prototype.getClusterLeaves=function(t,e,r,n){return this.actor.send("geojson.getClusterLeaves",{source:this.id,clusterId:t,limit:e,offset:r},n),this},r.prototype._updateWorkerData=function(e){var r=this;this._loaded=!1;var n=t.extend({},this.workerOptions),i=this._data;"string"==typeof i?(n.request=this.map._requestManager.transformRequest(t.browser.resolveURL(i),t.ResourceType.Source),n.request.collectResourceTiming=this._collectResourceTiming):n.data=JSON.stringify(i),this.actor.send(this.type+".loadData",n,(function(t,i){r._removed||i&&i.abandoned||(r._loaded=!0,i&&i.resourceTiming&&i.resourceTiming[r.id]&&(r._resourceTiming=i.resourceTiming[r.id].slice(0)),r.actor.send(r.type+".coalesce",{source:n.source},null),e(t))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.loadTile=function(e,r){var n=this,i=e.actor?"reloadTile":"loadTile";e.actor=this.actor;var a={type:this.type,uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};e.request=this.actor.send(i,a,(function(t,a){return delete e.request,e.unloadVectorData(),e.aborted?r(null):t?r(t):(e.loadVectorData(a,n.map.painter,"reloadTile"===i),r(null))}))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.aborted=!0},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.actor.send("removeTile",{uid:t.uid,type:this.type,source:this.id})},r.prototype.onRemove=function(){this._removed=!0,this.actor.send("removeSource",{type:this.type,source:this.id})},r.prototype.serialize=function(){return t.extend({},this._options,{type:this.type,data:this._data})},r.prototype.hasTransition=function(){return!1},r}(t.Evented),O=t.createLayout([{name:"a_pos",type:"Int16",components:2},{name:"a_texture_pos",type:"Int16",components:2}]),I=function(e){function r(t,r,n,i){e.call(this),this.id=t,this.dispatcher=n,this.coordinates=r.coordinates,this.type="image",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(i),this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(e,r){var n=this;this._loaded=!1,this.fire(new t.Event("dataloading",{dataType:"source"})),this.url=this.options.url,t.getImage(this.map._requestManager.transformRequest(this.url,t.ResourceType.Image),(function(i,a){n._loaded=!0,i?n.fire(new t.ErrorEvent(i)):a&&(n.image=a,e&&(n.coordinates=e),r&&r(),n._finishLoading())}))},r.prototype.loaded=function(){return this._loaded},r.prototype.updateImage=function(t){var e=this;return this.image&&t.url?(this.options.url=t.url,this.load(t.coordinates,(function(){e.texture=null})),this):this},r.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.Event("data",{dataType:"source",sourceDataType:"metadata"})))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setCoordinates=function(e){var r=this;this.coordinates=e;var n=e.map(t.MercatorCoordinate.fromLngLat);this.tileID=function(e){for(var r=1/0,n=1/0,i=-1/0,a=-1/0,o=0,s=e;o<s.length;o+=1){var l=s[o];r=Math.min(r,l.x),n=Math.min(n,l.y),i=Math.max(i,l.x),a=Math.max(a,l.y)}var u=i-r,c=a-n,f=Math.max(u,c),h=Math.max(0,Math.floor(-Math.log(f)/Math.LN2)),p=Math.pow(2,h);return new t.CanonicalTileID(h,Math.floor((r+i)/2*p),Math.floor((n+a)/2*p))}(n),this.minzoom=this.maxzoom=this.tileID.z;var i=n.map((function(t){return r.tileID.getTilePoint(t)._round()}));return this._boundsArray=new t.StructArrayLayout4i8,this._boundsArray.emplaceBack(i[0].x,i[0].y,0,0),this._boundsArray.emplaceBack(i[1].x,i[1].y,t.EXTENT,0),this._boundsArray.emplaceBack(i[3].x,i[3].y,0,t.EXTENT),this._boundsArray.emplaceBack(i[2].x,i[2].y,t.EXTENT,t.EXTENT),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new t.Event("data",{dataType:"source",sourceDataType:"content"})),this},r.prototype.prepare=function(){if(0!==Object.keys(this.tiles).length&&this.image){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,O.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture||(this.texture=new t.Texture(e,this.image,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];"loaded"!==i.state&&(i.state="loaded",i.texture=this.texture)}}},r.prototype.loadTile=function(t,e){this.tileID&&this.tileID.equals(t.tileID.canonical)?(this.tiles[String(t.tileID.wrap)]=t,t.buckets={},e(null)):(t.state="errored",e(null))},r.prototype.serialize=function(){return{type:"image",url:this.options.url,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return!1},r}(t.Evented);var D=function(e){function r(t,r,n,i){e.call(this,t,r,n,i),this.roundZoom=!0,this.type="video",this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1;var r=this.options;this.urls=[];for(var n=0,i=r.urls;n<i.length;n+=1){var a=i[n];this.urls.push(this.map._requestManager.transformRequest(a,t.ResourceType.Source).url)}t.getVideo(this.urls,(function(r,n){e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(e.video=n,e.video.loop=!0,e.video.addEventListener("playing",(function(){e.map.triggerRepaint()})),e.map&&e.video.play(),e._finishLoading())}))},r.prototype.pause=function(){this.video&&this.video.pause()},r.prototype.play=function(){this.video&&this.video.play()},r.prototype.seek=function(e){if(this.video){var r=this.video.seekable;e<r.start(0)||e>r.end(0)?this.fire(new t.ErrorEvent(new t.ValidationError("sources."+this.id,null,"Playback for this video can be set only between the "+r.start(0)+" and "+r.end(0)+"-second mark."))):this.video.currentTime=e}},r.prototype.getVideo=function(){return this.video},r.prototype.onAdd=function(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},r.prototype.prepare=function(){if(!(0===Object.keys(this.tiles).length||this.video.readyState<2)){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,O.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.video)):(this.texture=new t.Texture(e,this.video,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];"loaded"!==i.state&&(i.state="loaded",i.texture=this.texture)}}},r.prototype.serialize=function(){return{type:"video",urls:this.urls,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this.video&&!this.video.paused},r}(I),z=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),n.coordinates?Array.isArray(n.coordinates)&&4===n.coordinates.length&&!n.coordinates.some((function(t){return!Array.isArray(t)||2!==t.length||t.some((function(t){return"number"!=typeof t}))}))||this.fire(new t.ErrorEvent(new t.ValidationError("sources."+r,null,'"coordinates" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.ErrorEvent(new t.ValidationError("sources."+r,null,'missing required property "coordinates"'))),n.animate&&"boolean"!=typeof n.animate&&this.fire(new t.ErrorEvent(new t.ValidationError("sources."+r,null,'optional "animate" property must be a boolean value'))),n.canvas?"string"==typeof n.canvas||n.canvas instanceof t.window.HTMLCanvasElement||this.fire(new t.ErrorEvent(new t.ValidationError("sources."+r,null,'"canvas" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.ErrorEvent(new t.ValidationError("sources."+r,null,'missing required property "canvas"'))),this.options=n,this.animate=void 0===n.animate||n.animate}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof t.window.HTMLCanvasElement?this.options.canvas:t.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.ErrorEvent(new Error("Canvas dimensions cannot be less than or equal to zero."))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())},r.prototype.getCanvas=function(){return this.canvas},r.prototype.onAdd=function(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()},r.prototype.onRemove=function(){this.pause()},r.prototype.prepare=function(){var e=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,e=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,e=!0),!this._hasInvalidDimensions()&&0!==Object.keys(this.tiles).length){var r=this.map.painter.context,n=r.gl;for(var i in this.boundsBuffer||(this.boundsBuffer=r.createVertexBuffer(this._boundsArray,O.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(e||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new t.Texture(r,this.canvas,n.RGBA,{premultiply:!0}),this.tiles){var a=this.tiles[i];"loaded"!==a.state&&(a.state="loaded",a.texture=this.texture)}}},r.prototype.serialize=function(){return{type:"canvas",coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this._playing},r.prototype._hasInvalidDimensions=function(){for(var t=0,e=[this.canvas.width,this.canvas.height];t<e.length;t+=1){var r=e[t];if(isNaN(r)||r<=0)return!0}return!1},r}(I),R={vector:E,raster:L,"raster-dem":C,geojson:P,video:D,image:I,canvas:z};function F(e,r){var n=t.identity([]);return t.translate(n,n,[1,1,0]),t.scale(n,n,[.5*e.width,.5*e.height,1]),t.multiply(n,n,e.calculatePosMatrix(r.toUnwrapped()))}function B(t,e,r,n,i,a){var o=function(t,e,r){if(t)for(var n=0,i=t;n<i.length;n+=1){var a=e[i[n]];if(a&&a.source===r&&"fill-extrusion"===a.type)return!0}else for(var o in e){var s=e[o];if(s.source===r&&"fill-extrusion"===s.type)return!0}return!1}(i&&i.layers,e,t.id),s=a.maxPitchScaleFactor(),l=t.tilesIn(n,s,o);l.sort(N);for(var u=[],c=0,f=l;c<f.length;c+=1){var h=f[c];u.push({wrappedTileID:h.tileID.wrapped().key,queryResults:h.tile.queryRenderedFeatures(e,r,t._state,h.queryGeometry,h.cameraQueryGeometry,h.scale,i,a,s,F(t.transform,h.tileID))})}var p=function(t){for(var e={},r={},n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.queryResults,s=a.wrappedTileID,l=r[s]=r[s]||{};for(var u in o)for(var c=o[u],f=l[u]=l[u]||{},h=e[u]=e[u]||[],p=0,d=c;p<d.length;p+=1){var v=d[p];f[v.featureIndex]||(f[v.featureIndex]=!0,h.push(v))}}return e}(u);for(var d in p)p[d].forEach((function(e){var r=e.feature,n=t.getFeatureState(r.layer["source-layer"],r.id);r.source=r.layer.source,r.layer["source-layer"]&&(r.sourceLayer=r.layer["source-layer"]),r.state=n}));return p}function N(t,e){var r=t.tileID,n=e.tileID;return r.overscaledZ-n.overscaledZ||r.canonical.y-n.canonical.y||r.wrap-n.wrap||r.canonical.x-n.canonical.x}var j=function(t,e){this.max=t,this.onRemove=e,this.reset()};j.prototype.reset=function(){for(var t in this.data)for(var e=0,r=this.data[t];e<r.length;e+=1){var n=r[e];n.timeout&&clearTimeout(n.timeout),this.onRemove(n.value)}return this.data={},this.order=[],this},j.prototype.add=function(t,e,r){var n=this,i=t.wrapped().key;void 0===this.data[i]&&(this.data[i]=[]);var a={value:e,timeout:void 0};if(void 0!==r&&(a.timeout=setTimeout((function(){n.remove(t,a)}),r)),this.data[i].push(a),this.order.push(i),this.order.length>this.max){var o=this._getAndRemoveByKey(this.order[0]);o&&this.onRemove(o)}return this},j.prototype.has=function(t){return t.wrapped().key in this.data},j.prototype.getAndRemove=function(t){return this.has(t)?this._getAndRemoveByKey(t.wrapped().key):null},j.prototype._getAndRemoveByKey=function(t){var e=this.data[t].shift();return e.timeout&&clearTimeout(e.timeout),0===this.data[t].length&&delete this.data[t],this.order.splice(this.order.indexOf(t),1),e.value},j.prototype.getByKey=function(t){var e=this.data[t];return e?e[0].value:null},j.prototype.get=function(t){return this.has(t)?this.data[t.wrapped().key][0].value:null},j.prototype.remove=function(t,e){if(!this.has(t))return this;var r=t.wrapped().key,n=void 0===e?0:this.data[r].indexOf(e),i=this.data[r][n];return this.data[r].splice(n,1),i.timeout&&clearTimeout(i.timeout),0===this.data[r].length&&delete this.data[r],this.onRemove(i.value),this.order.splice(this.order.indexOf(r),1),this},j.prototype.setMaxSize=function(t){for(this.max=t;this.order.length>this.max;){var e=this._getAndRemoveByKey(this.order[0]);e&&this.onRemove(e)}return this},j.prototype.filter=function(t){var e=[];for(var r in this.data)for(var n=0,i=this.data[r];n<i.length;n+=1){var a=i[n];t(a.value)||e.push(a)}for(var o=0,s=e;o<s.length;o+=1){var l=s[o];this.remove(l.value.tileID,l)}};var U=function(t,e,r){this.context=t;var n=t.gl;this.buffer=n.createBuffer(),this.dynamicDraw=Boolean(r),this.context.unbindVAO(),t.bindElementBuffer.set(this.buffer),n.bufferData(n.ELEMENT_ARRAY_BUFFER,e.arrayBuffer,this.dynamicDraw?n.DYNAMIC_DRAW:n.STATIC_DRAW),this.dynamicDraw||delete e.arrayBuffer};U.prototype.bind=function(){this.context.bindElementBuffer.set(this.buffer)},U.prototype.updateData=function(t){var e=this.context.gl;this.context.unbindVAO(),this.bind(),e.bufferSubData(e.ELEMENT_ARRAY_BUFFER,0,t.arrayBuffer)},U.prototype.destroy=function(){var t=this.context.gl;this.buffer&&(t.deleteBuffer(this.buffer),delete this.buffer)};var V={Int8:"BYTE",Uint8:"UNSIGNED_BYTE",Int16:"SHORT",Uint16:"UNSIGNED_SHORT",Int32:"INT",Uint32:"UNSIGNED_INT",Float32:"FLOAT"},H=function(t,e,r,n){this.length=e.length,this.attributes=r,this.itemSize=e.bytesPerElement,this.dynamicDraw=n,this.context=t;var i=t.gl;this.buffer=i.createBuffer(),t.bindVertexBuffer.set(this.buffer),i.bufferData(i.ARRAY_BUFFER,e.arrayBuffer,this.dynamicDraw?i.DYNAMIC_DRAW:i.STATIC_DRAW),this.dynamicDraw||delete e.arrayBuffer};H.prototype.bind=function(){this.context.bindVertexBuffer.set(this.buffer)},H.prototype.updateData=function(t){var e=this.context.gl;this.bind(),e.bufferSubData(e.ARRAY_BUFFER,0,t.arrayBuffer)},H.prototype.enableAttributes=function(t,e){for(var r=0;r<this.attributes.length;r++){var n=this.attributes[r],i=e.attributes[n.name];void 0!==i&&t.enableVertexAttribArray(i)}},H.prototype.setVertexAttribPointers=function(t,e,r){for(var n=0;n<this.attributes.length;n++){var i=this.attributes[n],a=e.attributes[i.name];void 0!==a&&t.vertexAttribPointer(a,i.components,t[V[i.type]],!1,this.itemSize,i.offset+this.itemSize*(r||0))}},H.prototype.destroy=function(){var t=this.context.gl;this.buffer&&(t.deleteBuffer(this.buffer),delete this.buffer)};var q=function(t){this.gl=t.gl,this.default=this.getDefault(),this.current=this.default,this.dirty=!1};q.prototype.get=function(){return this.current},q.prototype.set=function(t){},q.prototype.getDefault=function(){return this.default},q.prototype.setDefault=function(){this.set(this.default)};var G=function(e){function r(){e.apply(this,arguments)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getDefault=function(){return t.Color.transparent},r.prototype.set=function(t){var e=this.current;(t.r!==e.r||t.g!==e.g||t.b!==e.b||t.a!==e.a||this.dirty)&&(this.gl.clearColor(t.r,t.g,t.b,t.a),this.current=t,this.dirty=!1)},r}(q),Z=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return 1},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.clearDepth(t),this.current=t,this.dirty=!1)},e}(q),Y=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return 0},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.clearStencil(t),this.current=t,this.dirty=!1)},e}(q),W=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return[!0,!0,!0,!0]},e.prototype.set=function(t){var e=this.current;(t[0]!==e[0]||t[1]!==e[1]||t[2]!==e[2]||t[3]!==e[3]||this.dirty)&&(this.gl.colorMask(t[0],t[1],t[2],t[3]),this.current=t,this.dirty=!1)},e}(q),X=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return!0},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.depthMask(t),this.current=t,this.dirty=!1)},e}(q),J=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return 255},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.stencilMask(t),this.current=t,this.dirty=!1)},e}(q),K=function(t){function e(){t.apply(this,arguments)}return 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e=this.current;(t[0]!==e[0]||t[1]!==e[1]||t[2]!==e[2]||t[3]!==e[3]||this.dirty)&&(this.gl.viewport(t[0],t[1],t[2],t[3]),this.current=t,this.dirty=!1)},e}(q),pt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.bindFramebuffer(e.FRAMEBUFFER,t),this.current=t,this.dirty=!1}},e}(q),dt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.bindRenderbuffer(e.RENDERBUFFER,t),this.current=t,this.dirty=!1}},e}(q),vt=function(t){function e(){t.apply(this,arguments)}return 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e(e){t.call(this,e),this.vao=e.extVertexArrayObject}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){this.vao&&(t!==this.current||this.dirty)&&(this.vao.bindVertexArrayOES(t),this.current=t,this.dirty=!1)},e}(q),xt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return 4},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.pixelStorei(e.UNPACK_ALIGNMENT,t),this.current=t,this.dirty=!1}},e}(q),bt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return!1},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.pixelStorei(e.UNPACK_PREMULTIPLY_ALPHA_WEBGL,t),this.current=t,this.dirty=!1}},e}(q),_t=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return!1},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.pixelStorei(e.UNPACK_FLIP_Y_WEBGL,t),this.current=t,this.dirty=!1}},e}(q),wt=function(t){function e(e,r){t.call(this,e),this.context=e,this.parent=r}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getDefault=function(){return null},e}(q),Tt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.setDirty=function(){this.dirty=!0},e.prototype.set=function(t){if(t!==this.current||this.dirty){this.context.bindFramebuffer.set(this.parent);var e=this.gl;e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0),this.current=t,this.dirty=!1}},e}(wt),kt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){if(t!==this.current||this.dirty){this.context.bindFramebuffer.set(this.parent);var e=this.gl;e.framebufferRenderbuffer(e.FRAMEBUFFER,e.DEPTH_ATTACHMENT,e.RENDERBUFFER,t),this.current=t,this.dirty=!1}},e}(wt),At=function(t,e,r,n){this.context=t,this.width=e,this.height=r;var i=t.gl,a=this.framebuffer=i.createFramebuffer();this.colorAttachment=new Tt(t,a),n&&(this.depthAttachment=new kt(t,a))};At.prototype.destroy=function(){var t=this.context.gl,e=this.colorAttachment.get();if(e&&t.deleteTexture(e),this.depthAttachment){var r=this.depthAttachment.get();r&&t.deleteRenderbuffer(r)}t.deleteFramebuffer(this.framebuffer)};var Mt=function(t,e,r){this.func=t,this.mask=e,this.range=r};Mt.ReadOnly=!1,Mt.ReadWrite=!0,Mt.disabled=new Mt(519,Mt.ReadOnly,[0,1]);var St=7680,Et=function(t,e,r,n,i,a){this.test=t,this.ref=e,this.mask=r,this.fail=n,this.depthFail=i,this.pass=a};Et.disabled=new Et({func:519,mask:0},0,0,St,St,St);var Lt=function(t,e,r){this.blendFunction=t,this.blendColor=e,this.mask=r};Lt.Replace=[1,0],Lt.disabled=new Lt(Lt.Replace,t.Color.transparent,[!1,!1,!1,!1]),Lt.unblended=new Lt(Lt.Replace,t.Color.transparent,[!0,!0,!0,!0]),Lt.alphaBlended=new Lt([1,771],t.Color.transparent,[!0,!0,!0,!0]);var Ct=function(t,e,r){this.enable=t,this.mode=e,this.frontFace=r};Ct.disabled=new Ct(!1,1029,2305),Ct.backCCW=new Ct(!0,1029,2305);var Pt=function(t){this.gl=t,this.extVertexArrayObject=this.gl.getExtension("OES_vertex_array_object"),this.clearColor=new G(this),this.clearDepth=new Z(this),this.clearStencil=new Y(this),this.colorMask=new W(this),this.depthMask=new X(this),this.stencilMask=new J(this),this.stencilFunc=new K(this),this.stencilOp=new $(this),this.stencilTest=new Q(this),this.depthRange=new tt(this),this.depthTest=new et(this),this.depthFunc=new rt(this),this.blend=new nt(this),this.blendFunc=new it(this),this.blendColor=new at(this),this.blendEquation=new ot(this),this.cullFace=new st(this),this.cullFaceSide=new lt(this),this.frontFace=new ut(this),this.program=new ct(this),this.activeTexture=new ft(this),this.viewport=new ht(this),this.bindFramebuffer=new pt(this),this.bindRenderbuffer=new dt(this),this.bindTexture=new vt(this),this.bindVertexBuffer=new gt(this),this.bindElementBuffer=new yt(this),this.bindVertexArrayOES=this.extVertexArrayObject&&new mt(this),this.pixelStoreUnpack=new xt(this),this.pixelStoreUnpackPremultiplyAlpha=new bt(this),this.pixelStoreUnpackFlipY=new _t(this),this.extTextureFilterAnisotropic=t.getExtension("EXT_texture_filter_anisotropic")||t.getExtension("MOZ_EXT_texture_filter_anisotropic")||t.getExtension("WEBKIT_EXT_texture_filter_anisotropic"),this.extTextureFilterAnisotropic&&(this.extTextureFilterAnisotropicMax=t.getParameter(this.extTextureFilterAnisotropic.MAX_TEXTURE_MAX_ANISOTROPY_EXT)),this.extTextureHalfFloat=t.getExtension("OES_texture_half_float"),this.extTextureHalfFloat&&(t.getExtension("OES_texture_half_float_linear"),this.extRenderToTextureHalfFloat=t.getExtension("EXT_color_buffer_half_float")),this.extTimerQuery=t.getExtension("EXT_disjoint_timer_query")};Pt.prototype.setDefault=function(){this.unbindVAO(),this.clearColor.setDefault(),this.clearDepth.setDefault(),this.clearStencil.setDefault(),this.colorMask.setDefault(),this.depthMask.setDefault(),this.stencilMask.setDefault(),this.stencilFunc.setDefault(),this.stencilOp.setDefault(),this.stencilTest.setDefault(),this.depthRange.setDefault(),this.depthTest.setDefault(),this.depthFunc.setDefault(),this.blend.setDefault(),this.blendFunc.setDefault(),this.blendColor.setDefault(),this.blendEquation.setDefault(),this.cullFace.setDefault(),this.cullFaceSide.setDefault(),this.frontFace.setDefault(),this.program.setDefault(),this.activeTexture.setDefault(),this.bindFramebuffer.setDefault(),this.pixelStoreUnpack.setDefault(),this.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.pixelStoreUnpackFlipY.setDefault()},Pt.prototype.setDirty=function(){this.clearColor.dirty=!0,this.clearDepth.dirty=!0,this.clearStencil.dirty=!0,this.colorMask.dirty=!0,this.depthMask.dirty=!0,this.stencilMask.dirty=!0,this.stencilFunc.dirty=!0,this.stencilOp.dirty=!0,this.stencilTest.dirty=!0,this.depthRange.dirty=!0,this.depthTest.dirty=!0,this.depthFunc.dirty=!0,this.blend.dirty=!0,this.blendFunc.dirty=!0,this.blendColor.dirty=!0,this.blendEquation.dirty=!0,this.cullFace.dirty=!0,this.cullFaceSide.dirty=!0,this.frontFace.dirty=!0,this.program.dirty=!0,this.activeTexture.dirty=!0,this.viewport.dirty=!0,this.bindFramebuffer.dirty=!0,this.bindRenderbuffer.dirty=!0,this.bindTexture.dirty=!0,this.bindVertexBuffer.dirty=!0,this.bindElementBuffer.dirty=!0,this.extVertexArrayObject&&(this.bindVertexArrayOES.dirty=!0),this.pixelStoreUnpack.dirty=!0,this.pixelStoreUnpackPremultiplyAlpha.dirty=!0,this.pixelStoreUnpackFlipY.dirty=!0},Pt.prototype.createIndexBuffer=function(t,e){return new U(this,t,e)},Pt.prototype.createVertexBuffer=function(t,e,r){return new H(this,t,e,r)},Pt.prototype.createRenderbuffer=function(t,e,r){var n=this.gl,i=n.createRenderbuffer();return this.bindRenderbuffer.set(i),n.renderbufferStorage(n.RENDERBUFFER,t,e,r),this.bindRenderbuffer.set(null),i},Pt.prototype.createFramebuffer=function(t,e,r){return new At(this,t,e,r)},Pt.prototype.clear=function(t){var e=t.color,r=t.depth,n=this.gl,i=0;e&&(i|=n.COLOR_BUFFER_BIT,this.clearColor.set(e),this.colorMask.set([!0,!0,!0,!0])),void 0!==r&&(i|=n.DEPTH_BUFFER_BIT,this.depthRange.set([0,1]),this.clearDepth.set(r),this.depthMask.set(!0)),n.clear(i)},Pt.prototype.setCullFace=function(t){!1===t.enable?this.cullFace.set(!1):(this.cullFace.set(!0),this.cullFaceSide.set(t.mode),this.frontFace.set(t.frontFace))},Pt.prototype.setDepthMode=function(t){t.func!==this.gl.ALWAYS||t.mask?(this.depthTest.set(!0),this.depthFunc.set(t.func),this.depthMask.set(t.mask),this.depthRange.set(t.range)):this.depthTest.set(!1)},Pt.prototype.setStencilMode=function(t){t.test.func!==this.gl.ALWAYS||t.mask?(this.stencilTest.set(!0),this.stencilMask.set(t.mask),this.stencilOp.set([t.fail,t.depthFail,t.pass]),this.stencilFunc.set({func:t.test.func,ref:t.ref,mask:t.test.mask})):this.stencilTest.set(!1)},Pt.prototype.setColorMode=function(e){t.deepEqual(e.blendFunction,Lt.Replace)?this.blend.set(!1):(this.blend.set(!0),this.blendFunc.set(e.blendFunction),this.blendColor.set(e.blendColor)),this.colorMask.set(e.mask)},Pt.prototype.unbindVAO=function(){this.extVertexArrayObject&&this.bindVertexArrayOES.set(null)};var Ot=function(e){function r(r,n,i){var a=this;e.call(this),this.id=r,this.dispatcher=i,this.on("data",(function(t){"source"===t.dataType&&"metadata"===t.sourceDataType&&(a._sourceLoaded=!0),a._sourceLoaded&&!a._paused&&"source"===t.dataType&&"content"===t.sourceDataType&&(a.reload(),a.transform&&a.update(a.transform))})),this.on("error",(function(){a._sourceErrored=!0})),this._source=function(e,r,n,i){var a=new R[r.type](e,r,n,i);if(a.id!==e)throw new Error("Expected Source id to be "+e+" instead of "+a.id);return t.bindAll(["load","abort","unload","serialize","prepare"],a),a}(r,n,i,this),this._tiles={},this._cache=new j(0,this._unloadTile.bind(this)),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._loadedParentTiles={},this._coveredTiles={},this._state=new t.SourceFeatureState}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.onAdd=function(t){this.map=t,this._maxTileCacheSize=t?t._maxTileCacheSize:null,this._source&&this._source.onAdd&&this._source.onAdd(t)},r.prototype.onRemove=function(t){this._source&&this._source.onRemove&&this._source.onRemove(t)},r.prototype.loaded=function(){if(this._sourceErrored)return!0;if(!this._sourceLoaded)return!1;if(!this._source.loaded())return!1;for(var t in this._tiles){var e=this._tiles[t];if("loaded"!==e.state&&"errored"!==e.state)return!1}return!0},r.prototype.getSource=function(){return this._source},r.prototype.pause=function(){this._paused=!0},r.prototype.resume=function(){if(this._paused){var t=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,t&&this.reload(),this.transform&&this.update(this.transform)}},r.prototype._loadTile=function(t,e){return this._source.loadTile(t,e)},r.prototype._unloadTile=function(t){if(this._source.unloadTile)return this._source.unloadTile(t,(function(){}))},r.prototype._abortTile=function(t){if(this._source.abortTile)return this._source.abortTile(t,(function(){}))},r.prototype.serialize=function(){return this._source.serialize()},r.prototype.prepare=function(t){for(var e in this._source.prepare&&this._source.prepare(),this._state.coalesceChanges(this._tiles,this.map?this.map.painter:null),this._tiles){var r=this._tiles[e];r.upload(t),r.prepare(this.map.style.imageManager)}},r.prototype.getIds=function(){return t.values(this._tiles).map((function(t){return t.tileID})).sort(It).map((function(t){return t.key}))},r.prototype.getRenderableIds=function(e){var r=this,n=[];for(var i in this._tiles)this._isIdRenderable(i,e)&&n.push(this._tiles[i]);return e?n.sort((function(e,n){var i=e.tileID,a=n.tileID,o=new t.Point(i.canonical.x,i.canonical.y)._rotate(r.transform.angle),s=new t.Point(a.canonical.x,a.canonical.y)._rotate(r.transform.angle);return i.overscaledZ-a.overscaledZ||s.y-o.y||s.x-o.x})).map((function(t){return t.tileID.key})):n.map((function(t){return t.tileID})).sort(It).map((function(t){return t.key}))},r.prototype.hasRenderableParent=function(t){var e=this.findLoadedParent(t,0);return!!e&&this._isIdRenderable(e.tileID.key)},r.prototype._isIdRenderable=function(t,e){return this._tiles[t]&&this._tiles[t].hasData()&&!this._coveredTiles[t]&&(e||!this._tiles[t].holdingForFade())},r.prototype.reload=function(){if(this._paused)this._shouldReloadOnResume=!0;else for(var t in this._cache.reset(),this._tiles)"errored"!==this._tiles[t].state&&this._reloadTile(t,"reloading")},r.prototype._reloadTile=function(t,e){var r=this._tiles[t];r&&("loading"!==r.state&&(r.state=e),this._loadTile(r,this._tileLoaded.bind(this,r,t,e)))},r.prototype._tileLoaded=function(e,r,n,i){if(i)return e.state="errored",void(404!==i.status?this._source.fire(new t.ErrorEvent(i,{tile:e})):this.update(this.transform));e.timeAdded=t.browser.now(),"expired"===n&&(e.refreshedUponExpiration=!0),this._setTileReloadTimer(r,e),"raster-dem"===this.getSource().type&&e.dem&&this._backfillDEM(e),this._state.initializeTileState(e,this.map?this.map.painter:null),this._source.fire(new t.Event("data",{dataType:"source",tile:e,coord:e.tileID}))},r.prototype._backfillDEM=function(t){for(var e=this.getRenderableIds(),r=0;r<e.length;r++){var n=e[r];if(t.neighboringTiles&&t.neighboringTiles[n]){var i=this.getTileByID(n);a(t,i),a(i,t)}}function a(t,e){t.needsHillshadePrepare=!0;var r=e.tileID.canonical.x-t.tileID.canonical.x,n=e.tileID.canonical.y-t.tileID.canonical.y,i=Math.pow(2,t.tileID.canonical.z),a=e.tileID.key;0===r&&0===n||Math.abs(n)>1||(Math.abs(r)>1&&(1===Math.abs(r+i)?r+=i:1===Math.abs(r-i)&&(r-=i)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[a]&&(t.neighboringTiles[a].backfilled=!0)))}},r.prototype.getTile=function(t){return this.getTileByID(t.key)},r.prototype.getTileByID=function(t){return this._tiles[t]},r.prototype._retainLoadedChildren=function(t,e,r,n){for(var i in this._tiles){var a=this._tiles[i];if(!(n[i]||!a.hasData()||a.tileID.overscaledZ<=e||a.tileID.overscaledZ>r)){for(var o=a.tileID;a&&a.tileID.overscaledZ>e+1;){var s=a.tileID.scaledTo(a.tileID.overscaledZ-1);(a=this._tiles[s.key])&&a.hasData()&&(o=s)}for(var l=o;l.overscaledZ>e;)if(t[(l=l.scaledTo(l.overscaledZ-1)).key]){n[o.key]=o;break}}}},r.prototype.findLoadedParent=function(t,e){if(t.key in this._loadedParentTiles){var r=this._loadedParentTiles[t.key];return r&&r.tileID.overscaledZ>=e?r:null}for(var n=t.overscaledZ-1;n>=e;n--){var i=t.scaledTo(n),a=this._getLoadedTile(i);if(a)return a}},r.prototype._getLoadedTile=function(t){var e=this._tiles[t.key];return e&&e.hasData()?e:this._cache.getByKey(t.wrapped().key)},r.prototype.updateCacheSize=function(t){var e=(Math.ceil(t.width/this._source.tileSize)+1)*(Math.ceil(t.height/this._source.tileSize)+1),r=Math.floor(5*e),n="number"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,r):r;this._cache.setMaxSize(n)},r.prototype.handleWrapJump=function(t){var e=(t-(void 0===this._prevLng?t:this._prevLng))/360,r=Math.round(e);if(this._prevLng=t,r){var n={};for(var i in this._tiles){var a=this._tiles[i];a.tileID=a.tileID.unwrapTo(a.tileID.wrap+r),n[a.tileID.key]=a}for(var o in this._tiles=n,this._timers)clearTimeout(this._timers[o]),delete this._timers[o];for(var s in this._tiles){var l=this._tiles[s];this._setTileReloadTimer(s,l)}}},r.prototype.update=function(e){var n=this;if(this.transform=e,this._sourceLoaded&&!this._paused){var i;this.updateCacheSize(e),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used?this._source.tileID?i=e.getVisibleUnwrappedCoordinates(this._source.tileID).map((function(e){return new t.OverscaledTileID(e.canonical.z,e.wrap,e.canonical.z,e.canonical.x,e.canonical.y)})):(i=e.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(i=i.filter((function(t){return n._source.hasTile(t)})))):i=[];var a=e.coveringZoomLevel(this._source),o=Math.max(a-r.maxOverzooming,this._source.minzoom),s=Math.max(a+r.maxUnderzooming,this._source.minzoom),l=this._updateRetainedTiles(i,a);if(Dt(this._source.type)){for(var u={},c={},f=0,h=Object.keys(l);f<h.length;f+=1){var p=h[f],d=l[p],v=this._tiles[p];if(v&&!(v.fadeEndTime&&v.fadeEndTime<=t.browser.now())){var g=this.findLoadedParent(d,o);g&&(this._addTile(g.tileID),u[g.tileID.key]=g.tileID),c[p]=d}}for(var y in this._retainLoadedChildren(c,a,s,l),u)l[y]||(this._coveredTiles[y]=!0,l[y]=u[y])}for(var m in l)this._tiles[m].clearFadeHold();for(var x=0,b=t.keysDifference(this._tiles,l);x<b.length;x+=1){var _=b[x],w=this._tiles[_];w.hasSymbolBuckets&&!w.holdingForFade()?w.setHoldDuration(this.map._fadeDuration):w.hasSymbolBuckets&&!w.symbolFadeFinished()||this._removeTile(_)}this._updateLoadedParentTileCache()}},r.prototype.releaseSymbolFadeTiles=function(){for(var t in this._tiles)this._tiles[t].holdingForFade()&&this._removeTile(t)},r.prototype._updateRetainedTiles=function(t,e){for(var n={},i={},a=Math.max(e-r.maxOverzooming,this._source.minzoom),o=Math.max(e+r.maxUnderzooming,this._source.minzoom),s={},l=0,u=t;l<u.length;l+=1){var c=u[l],f=this._addTile(c);n[c.key]=c,f.hasData()||e<this._source.maxzoom&&(s[c.key]=c)}this._retainLoadedChildren(s,e,o,n);for(var h=0,p=t;h<p.length;h+=1){var d=p[h],v=this._tiles[d.key];if(!v.hasData()){if(e+1>this._source.maxzoom){var g=d.children(this._source.maxzoom)[0],y=this.getTile(g);if(y&&y.hasData()){n[g.key]=g;continue}}else{var m=d.children(this._source.maxzoom);if(n[m[0].key]&&n[m[1].key]&&n[m[2].key]&&n[m[3].key])continue}for(var x=v.wasRequested(),b=d.overscaledZ-1;b>=a;--b){var _=d.scaledTo(b);if(i[_.key])break;if(i[_.key]=!0,!(v=this.getTile(_))&&x&&(v=this._addTile(_)),v&&(n[_.key]=_,x=v.wasRequested(),v.hasData()))break}}}return n},r.prototype._updateLoadedParentTileCache=function(){for(var t in this._loadedParentTiles={},this._tiles){for(var e=[],r=void 0,n=this._tiles[t].tileID;n.overscaledZ>0;){if(n.key in this._loadedParentTiles){r=this._loadedParentTiles[n.key];break}e.push(n.key);var i=n.scaledTo(n.overscaledZ-1);if(r=this._getLoadedTile(i))break;n=i}for(var a=0,o=e;a<o.length;a+=1){var s=o[a];this._loadedParentTiles[s]=r}}},r.prototype._addTile=function(e){var r=this._tiles[e.key];if(r)return r;(r=this._cache.getAndRemove(e))&&(this._setTileReloadTimer(e.key,r),r.tileID=e,this._state.initializeTileState(r,this.map?this.map.painter:null),this._cacheTimers[e.key]&&(clearTimeout(this._cacheTimers[e.key]),delete this._cacheTimers[e.key],this._setTileReloadTimer(e.key,r)));var n=Boolean(r);return n||(r=new t.Tile(e,this._source.tileSize*e.overscaleFactor()),this._loadTile(r,this._tileLoaded.bind(this,r,e.key,r.state))),r?(r.uses++,this._tiles[e.key]=r,n||this._source.fire(new t.Event("dataloading",{tile:r,coord:r.tileID,dataType:"source"})),r):null},r.prototype._setTileReloadTimer=function(t,e){var r=this;t in this._timers&&(clearTimeout(this._timers[t]),delete this._timers[t]);var n=e.getExpiryTimeout();n&&(this._timers[t]=setTimeout((function(){r._reloadTile(t,"expired"),delete r._timers[t]}),n))},r.prototype._removeTile=function(t){var e=this._tiles[t];e&&(e.uses--,delete this._tiles[t],this._timers[t]&&(clearTimeout(this._timers[t]),delete this._timers[t]),e.uses>0||(e.hasData()&&"reloading"!==e.state?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))},r.prototype.clearTiles=function(){for(var t in this._shouldReloadOnResume=!1,this._paused=!1,this._tiles)this._removeTile(t);this._cache.reset()},r.prototype.tilesIn=function(e,r,n){var i=this,a=[],o=this.transform;if(!o)return a;for(var s=n?o.getCameraQueryGeometry(e):e,l=e.map((function(t){return o.pointCoordinate(t)})),u=s.map((function(t){return o.pointCoordinate(t)})),c=this.getIds(),f=1/0,h=1/0,p=-1/0,d=-1/0,v=0,g=u;v<g.length;v+=1){var y=g[v];f=Math.min(f,y.x),h=Math.min(h,y.y),p=Math.max(p,y.x),d=Math.max(d,y.y)}for(var m=function(e){var n=i._tiles[c[e]];if(!n.holdingForFade()){var s=n.tileID,v=Math.pow(2,o.zoom-n.tileID.overscaledZ),g=r*n.queryPadding*t.EXTENT/n.tileSize/v,y=[s.getTilePoint(new t.MercatorCoordinate(f,h)),s.getTilePoint(new t.MercatorCoordinate(p,d))];if(y[0].x-g<t.EXTENT&&y[0].y-g<t.EXTENT&&y[1].x+g>=0&&y[1].y+g>=0){var m=l.map((function(t){return s.getTilePoint(t)})),x=u.map((function(t){return s.getTilePoint(t)}));a.push({tile:n,tileID:s,queryGeometry:m,cameraQueryGeometry:x,scale:v})}}},x=0;x<c.length;x++)m(x);return a},r.prototype.getVisibleCoordinates=function(t){for(var e=this,r=this.getRenderableIds(t).map((function(t){return e._tiles[t].tileID})),n=0,i=r;n<i.length;n+=1){var a=i[n];a.posMatrix=this.transform.calculatePosMatrix(a.toUnwrapped())}return r},r.prototype.hasTransition=function(){if(this._source.hasTransition())return!0;if(Dt(this._source.type))for(var e in this._tiles){var r=this._tiles[e];if(void 0!==r.fadeEndTime&&r.fadeEndTime>=t.browser.now())return!0}return!1},r.prototype.setFeatureState=function(t,e,r){t=t||"_geojsonTileLayer",this._state.updateState(t,e,r)},r.prototype.removeFeatureState=function(t,e,r){t=t||"_geojsonTileLayer",this._state.removeFeatureState(t,e,r)},r.prototype.getFeatureState=function(t,e){return t=t||"_geojsonTileLayer",this._state.getState(t,e)},r.prototype.setDependencies=function(t,e,r){var n=this._tiles[t];n&&n.setDependencies(e,r)},r.prototype.reloadTilesForDependencies=function(t,e){for(var r in this._tiles)this._tiles[r].hasDependency(t,e)&&this._reloadTile(r,"reloading");this._cache.filter((function(r){return!r.hasDependency(t,e)}))},r}(t.Evented);function It(t,e){var r=Math.abs(2*t.wrap)-+(t.wrap<0),n=Math.abs(2*e.wrap)-+(e.wrap<0);return t.overscaledZ-e.overscaledZ||n-r||e.canonical.y-t.canonical.y||e.canonical.x-t.canonical.x}function Dt(t){return"raster"===t||"image"===t||"video"===t}function zt(){return new t.window.Worker(na.workerUrl)}Ot.maxOverzooming=10,Ot.maxUnderzooming=3;var Rt="mapboxgl_preloaded_worker_pool",Ft=function(){this.active={}};Ft.prototype.acquire=function(t){if(!this.workers)for(this.workers=[];this.workers.length<Ft.workerCount;)this.workers.push(new zt);return this.active[t]=!0,this.workers.slice()},Ft.prototype.release=function(t){delete this.active[t],0===this.numActive()&&(this.workers.forEach((function(t){t.terminate()})),this.workers=null)},Ft.prototype.isPreloaded=function(){return!!this.active[Rt]},Ft.prototype.numActive=function(){return Object.keys(this.active).length};var Bt,Nt=Math.floor(t.browser.hardwareConcurrency/2);function jt(){return Bt||(Bt=new Ft),Bt}function Ut(e,r){var n={};for(var i in e)"ref"!==i&&(n[i]=e[i]);return t.refProperties.forEach((function(t){t in r&&(n[t]=r[t])})),n}function Vt(t){t=t.slice();for(var e=Object.create(null),r=0;r<t.length;r++)e[t[r].id]=t[r];for(var n=0;n<t.length;n++)"ref"in t[n]&&(t[n]=Ut(t[n],e[t[n].ref]));return t}Ft.workerCount=Math.max(Math.min(Nt,6),1);var Ht={setStyle:"setStyle",addLayer:"addLayer",removeLayer:"removeLayer",setPaintProperty:"setPaintProperty",setLayoutProperty:"setLayoutProperty",setFilter:"setFilter",addSource:"addSource",removeSource:"removeSource",setGeoJSONSourceData:"setGeoJSONSourceData",setLayerZoomRange:"setLayerZoomRange",setLayerProperty:"setLayerProperty",setCenter:"setCenter",setZoom:"setZoom",setBearing:"setBearing",setPitch:"setPitch",setSprite:"setSprite",setGlyphs:"setGlyphs",setTransition:"setTransition",setLight:"setLight"};function qt(t,e,r){r.push({command:Ht.addSource,args:[t,e[t]]})}function Gt(t,e,r){e.push({command:Ht.removeSource,args:[t]}),r[t]=!0}function Zt(t,e,r,n){Gt(t,r,n),qt(t,e,r)}function Yt(e,r,n){var i;for(i in e[n])if(e[n].hasOwnProperty(i)&&"data"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;for(i in r[n])if(r[n].hasOwnProperty(i)&&"data"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;return!0}function Wt(e,r,n,i,a,o){var s;for(s in r=r||{},e=e||{})e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}));for(s in r)r.hasOwnProperty(s)&&!e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}))}function Xt(t){return t.id}function Jt(t,e){return t[e.id]=e,t}function Kt(e,r){if(!e)return[{command:Ht.setStyle,args:[r]}];var n=[];try{if(!t.deepEqual(e.version,r.version))return[{command:Ht.setStyle,args:[r]}];t.deepEqual(e.center,r.center)||n.push({command:Ht.setCenter,args:[r.center]}),t.deepEqual(e.zoom,r.zoom)||n.push({command:Ht.setZoom,args:[r.zoom]}),t.deepEqual(e.bearing,r.bearing)||n.push({command:Ht.setBearing,args:[r.bearing]}),t.deepEqual(e.pitch,r.pitch)||n.push({command:Ht.setPitch,args:[r.pitch]}),t.deepEqual(e.sprite,r.sprite)||n.push({command:Ht.setSprite,args:[r.sprite]}),t.deepEqual(e.glyphs,r.glyphs)||n.push({command:Ht.setGlyphs,args:[r.glyphs]}),t.deepEqual(e.transition,r.transition)||n.push({command:Ht.setTransition,args:[r.transition]}),t.deepEqual(e.light,r.light)||n.push({command:Ht.setLight,args:[r.light]});var i={},a=[];!function(e,r,n,i){var a;for(a in r=r||{},e=e||{})e.hasOwnProperty(a)&&(r.hasOwnProperty(a)||Gt(a,n,i));for(a in r)r.hasOwnProperty(a)&&(e.hasOwnProperty(a)?t.deepEqual(e[a],r[a])||("geojson"===e[a].type&&"geojson"===r[a].type&&Yt(e,r,a)?n.push({command:Ht.setGeoJSONSourceData,args:[a,r[a].data]}):Zt(a,r,n,i)):qt(a,r,n))}(e.sources,r.sources,a,i);var o=[];e.layers&&e.layers.forEach((function(t){i[t.source]?n.push({command:Ht.removeLayer,args:[t.id]}):o.push(t)})),n=n.concat(a),function(e,r,n){r=r||[];var i,a,o,s,l,u,c,f=(e=e||[]).map(Xt),h=r.map(Xt),p=e.reduce(Jt,{}),d=r.reduce(Jt,{}),v=f.slice(),g=Object.create(null);for(i=0,a=0;i<f.length;i++)o=f[i],d.hasOwnProperty(o)?a++:(n.push({command:Ht.removeLayer,args:[o]}),v.splice(v.indexOf(o,a),1));for(i=0,a=0;i<h.length;i++)o=h[h.length-1-i],v[v.length-1-i]!==o&&(p.hasOwnProperty(o)?(n.push({command:Ht.removeLayer,args:[o]}),v.splice(v.lastIndexOf(o,v.length-a),1)):a++,u=v[v.length-i],n.push({command:Ht.addLayer,args:[d[o],u]}),v.splice(v.length-i,0,o),g[o]=!0);for(i=0;i<h.length;i++)if(s=p[o=h[i]],l=d[o],!g[o]&&!t.deepEqual(s,l))if(t.deepEqual(s.source,l.source)&&t.deepEqual(s["source-layer"],l["source-layer"])&&t.deepEqual(s.type,l.type)){for(c in Wt(s.layout,l.layout,n,o,null,Ht.setLayoutProperty),Wt(s.paint,l.paint,n,o,null,Ht.setPaintProperty),t.deepEqual(s.filter,l.filter)||n.push({command:Ht.setFilter,args:[o,l.filter]}),t.deepEqual(s.minzoom,l.minzoom)&&t.deepEqual(s.maxzoom,l.maxzoom)||n.push({command:Ht.setLayerZoomRange,args:[o,l.minzoom,l.maxzoom]}),s)s.hasOwnProperty(c)&&"layout"!==c&&"paint"!==c&&"filter"!==c&&"metadata"!==c&&"minzoom"!==c&&"maxzoom"!==c&&(0===c.indexOf("paint.")?Wt(s[c],l[c],n,o,c.slice(6),Ht.setPaintProperty):t.deepEqual(s[c],l[c])||n.push({command:Ht.setLayerProperty,args:[o,c,l[c]]}));for(c in l)l.hasOwnProperty(c)&&!s.hasOwnProperty(c)&&"layout"!==c&&"paint"!==c&&"filter"!==c&&"metadata"!==c&&"minzoom"!==c&&"maxzoom"!==c&&(0===c.indexOf("paint.")?Wt(s[c],l[c],n,o,c.slice(6),Ht.setPaintProperty):t.deepEqual(s[c],l[c])||n.push({command:Ht.setLayerProperty,args:[o,c,l[c]]}))}else n.push({command:Ht.removeLayer,args:[o]}),u=v[v.lastIndexOf(o)+1],n.push({command:Ht.addLayer,args:[l,u]})}(o,r.layers,n)}catch(t){console.warn("Unable to compute style diff:",t),n=[{command:Ht.setStyle,args:[r]}]}return n}var $t=function(t,e){this.reset(t,e)};$t.prototype.reset=function(t,e){this.points=t||[],this._distances=[0];for(var r=1;r<this.points.length;r++)this._distances[r]=this._distances[r-1]+this.points[r].dist(this.points[r-1]);this.length=this._distances[this._distances.length-1],this.padding=Math.min(e||0,.5*this.length),this.paddedLength=this.length-2*this.padding},$t.prototype.lerp=function(e){if(1===this.points.length)return this.points[0];e=t.clamp(e,0,1);for(var r=1,n=this._distances[r],i=e*this.paddedLength+this.padding;n<i&&r<this._distances.length;)n=this._distances[++r];var a=r-1,o=this._distances[a],s=n-o,l=s>0?(i-o)/s:0;return this.points[a].mult(1-l).add(this.points[r].mult(l))};var Qt=function(t,e,r){var n=this.boxCells=[],i=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(var a=0;a<this.xCellCount*this.yCellCount;a++)n.push([]),i.push([]);this.circleKeys=[],this.boxKeys=[],this.bboxes=[],this.circles=[],this.width=t,this.height=e,this.xScale=this.xCellCount/t,this.yScale=this.yCellCount/e,this.boxUid=0,this.circleUid=0};function te(e,r,n,i,a){var o=t.create();return r?(t.scale(o,o,[1/a,1/a,1]),n||t.rotateZ(o,o,i.angle)):t.multiply(o,i.labelPlaneMatrix,e),o}function ee(e,r,n,i,a){if(r){var o=t.clone(e);return t.scale(o,o,[a,a,1]),n||t.rotateZ(o,o,-i.angle),o}return i.glCoordMatrix}function re(e,r){var n=[e.x,e.y,0,1];pe(n,n,r);var i=n[3];return{point:new t.Point(n[0]/i,n[1]/i),signedDistanceFromCamera:i}}function ne(t,e){return.5+t/e*.5}function ie(t,e){var r=t[0]/t[3],n=t[1]/t[3];return r>=-e[0]&&r<=e[0]&&n>=-e[1]&&n<=e[1]}function ae(e,r,n,i,a,o,s,l){var u=i?e.textSizeData:e.iconSizeData,c=t.evaluateSizeForZoom(u,n.transform.zoom),f=[256/n.width*2+1,256/n.height*2+1],h=i?e.text.dynamicLayoutVertexArray:e.icon.dynamicLayoutVertexArray;h.clear();for(var p=e.lineVertexArray,d=i?e.text.placedSymbolArray:e.icon.placedSymbolArray,v=n.transform.width/n.transform.height,g=!1,y=0;y<d.length;y++){var m=d.get(y);if(m.hidden||m.writingMode===t.WritingMode.vertical&&!g)he(m.numGlyphs,h);else{g=!1;var x=[m.anchorX,m.anchorY,0,1];if(t.transformMat4(x,x,r),ie(x,f)){var b=x[3],_=ne(n.transform.cameraToCenterDistance,b),w=t.evaluateSizeForFeature(u,c,m),T=s?w/_:w*_,k=new t.Point(m.anchorX,m.anchorY),A=re(k,a).point,M={},S=le(m,T,!1,l,r,a,o,e.glyphOffsetArray,p,h,A,k,M,v);g=S.useVertical,(S.notEnoughRoom||g||S.needsFlipping&&le(m,T,!0,l,r,a,o,e.glyphOffsetArray,p,h,A,k,M,v).notEnoughRoom)&&he(m.numGlyphs,h)}else he(m.numGlyphs,h)}}i?e.text.dynamicLayoutVertexBuffer.updateData(h):e.icon.dynamicLayoutVertexBuffer.updateData(h)}function oe(t,e,r,n,i,a,o,s,l,u,c){var f=s.glyphStartIndex+s.numGlyphs,h=s.lineStartIndex,p=s.lineStartIndex+s.lineLength,d=e.getoffsetX(s.glyphStartIndex),v=e.getoffsetX(f-1),g=ce(t*d,r,n,i,a,o,s.segment,h,p,l,u,c);if(!g)return null;var y=ce(t*v,r,n,i,a,o,s.segment,h,p,l,u,c);return y?{first:g,last:y}:null}function se(e,r,n,i){return e===t.WritingMode.horizontal&&Math.abs(n.y-r.y)>Math.abs(n.x-r.x)*i?{useVertical:!0}:(e===t.WritingMode.vertical?r.y<n.y:r.x>n.x)?{needsFlipping:!0}:null}function le(e,r,n,i,a,o,s,l,u,c,f,h,p,d){var v,g=r/24,y=e.lineOffsetX*g,m=e.lineOffsetY*g;if(e.numGlyphs>1){var x=e.glyphStartIndex+e.numGlyphs,b=e.lineStartIndex,_=e.lineStartIndex+e.lineLength,w=oe(g,l,y,m,n,f,h,e,u,o,p);if(!w)return{notEnoughRoom:!0};var T=re(w.first.point,s).point,k=re(w.last.point,s).point;if(i&&!n){var A=se(e.writingMode,T,k,d);if(A)return A}v=[w.first];for(var M=e.glyphStartIndex+1;M<x-1;M++)v.push(ce(g*l.getoffsetX(M),y,m,n,f,h,e.segment,b,_,u,o,p));v.push(w.last)}else{if(i&&!n){var S=re(h,a).point,E=e.lineStartIndex+e.segment+1,L=new t.Point(u.getx(E),u.gety(E)),C=re(L,a),P=C.signedDistanceFromCamera>0?C.point:ue(h,L,S,1,a),O=se(e.writingMode,S,P,d);if(O)return O}var I=ce(g*l.getoffsetX(e.glyphStartIndex),y,m,n,f,h,e.segment,e.lineStartIndex,e.lineStartIndex+e.lineLength,u,o,p);if(!I)return{notEnoughRoom:!0};v=[I]}for(var D=0,z=v;D<z.length;D+=1){var R=z[D];t.addDynamicAttributes(c,R.point,R.angle)}return{}}function ue(t,e,r,n,i){var a=re(t.add(t.sub(e)._unit()),i).point,o=r.sub(a);return r.add(o._mult(n/o.mag()))}function ce(e,r,n,i,a,o,s,l,u,c,f,h){var p=i?e-r:e+r,d=p>0?1:-1,v=0;i&&(d*=-1,v=Math.PI),d<0&&(v+=Math.PI);for(var g=d>0?l+s:l+s+1,y=a,m=a,x=0,b=0,_=Math.abs(p),w=[];x+b<=_;){if((g+=d)<l||g>=u)return null;if(m=y,w.push(y),void 0===(y=h[g])){var T=new t.Point(c.getx(g),c.gety(g)),k=re(T,f);if(k.signedDistanceFromCamera>0)y=h[g]=k.point;else{var A=g-d;y=ue(0===x?o:new t.Point(c.getx(A),c.gety(A)),T,m,_-x+1,f)}}x+=b,b=m.dist(y)}var M=(_-x)/b,S=y.sub(m),E=S.mult(M)._add(m);E._add(S._unit()._perp()._mult(n*d));var L=v+Math.atan2(y.y-m.y,y.x-m.x);return w.push(E),{point:E,angle:L,path:w}}Qt.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},Qt.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertBoxCell,this.boxUid++),this.boxKeys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},Qt.prototype.insertCircle=function(t,e,r,n){this._forEachCell(e-n,r-n,e+n,r+n,this._insertCircleCell,this.circleUid++),this.circleKeys.push(t),this.circles.push(e),this.circles.push(r),this.circles.push(n)},Qt.prototype._insertBoxCell=function(t,e,r,n,i,a){this.boxCells[i].push(a)},Qt.prototype._insertCircleCell=function(t,e,r,n,i,a){this.circleCells[i].push(a)},Qt.prototype._query=function(t,e,r,n,i,a){if(r<0||t>this.width||n<0||e>this.height)return!i&&[];var o=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(i)return!0;for(var s=0;s<this.boxKeys.length;s++)o.push({key:this.boxKeys[s],x1:this.bboxes[4*s],y1:this.bboxes[4*s+1],x2:this.bboxes[4*s+2],y2:this.bboxes[4*s+3]});for(var l=0;l<this.circleKeys.length;l++){var u=this.circles[3*l],c=this.circles[3*l+1],f=this.circles[3*l+2];o.push({key:this.circleKeys[l],x1:u-f,y1:c-f,x2:u+f,y2:c+f})}return a?o.filter(a):o}var h={hitTest:i,seenUids:{box:{},circle:{}}};return this._forEachCell(t,e,r,n,this._queryCell,o,h,a),i?o.length>0:o},Qt.prototype._queryCircle=function(t,e,r,n,i){var a=t-r,o=t+r,s=e-r,l=e+r;if(o<0||a>this.width||l<0||s>this.height)return!n&&[];var u=[],c={hitTest:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}};return this._forEachCell(a,s,o,l,this._queryCellCircle,u,c,i),n?u.length>0:u},Qt.prototype.query=function(t,e,r,n,i){return this._query(t,e,r,n,!1,i)},Qt.prototype.hitTest=function(t,e,r,n,i){return this._query(t,e,r,n,!0,i)},Qt.prototype.hitTestCircle=function(t,e,r,n){return this._queryCircle(t,e,r,!0,n)},Qt.prototype._queryCell=function(t,e,r,n,i,a,o,s){var l=o.seenUids,u=this.boxCells[i];if(null!==u)for(var c=this.bboxes,f=0,h=u;f<h.length;f+=1){var p=h[f];if(!l.box[p]){l.box[p]=!0;var d=4*p;if(t<=c[d+2]&&e<=c[d+3]&&r>=c[d+0]&&n>=c[d+1]&&(!s||s(this.boxKeys[p]))){if(o.hitTest)return a.push(!0),!0;a.push({key:this.boxKeys[p],x1:c[d],y1:c[d+1],x2:c[d+2],y2:c[d+3]})}}}var v=this.circleCells[i];if(null!==v)for(var g=this.circles,y=0,m=v;y<m.length;y+=1){var x=m[y];if(!l.circle[x]){l.circle[x]=!0;var b=3*x;if(this._circleAndRectCollide(g[b],g[b+1],g[b+2],t,e,r,n)&&(!s||s(this.circleKeys[x]))){if(o.hitTest)return a.push(!0),!0;var _=g[b],w=g[b+1],T=g[b+2];a.push({key:this.circleKeys[x],x1:_-T,y1:w-T,x2:_+T,y2:w+T})}}}},Qt.prototype._queryCellCircle=function(t,e,r,n,i,a,o,s){var l=o.circle,u=o.seenUids,c=this.boxCells[i];if(null!==c)for(var f=this.bboxes,h=0,p=c;h<p.length;h+=1){var d=p[h];if(!u.box[d]){u.box[d]=!0;var v=4*d;if(this._circleAndRectCollide(l.x,l.y,l.radius,f[v+0],f[v+1],f[v+2],f[v+3])&&(!s||s(this.boxKeys[d])))return a.push(!0),!0}}var g=this.circleCells[i];if(null!==g)for(var y=this.circles,m=0,x=g;m<x.length;m+=1){var b=x[m];if(!u.circle[b]){u.circle[b]=!0;var _=3*b;if(this._circlesCollide(y[_],y[_+1],y[_+2],l.x,l.y,l.radius)&&(!s||s(this.circleKeys[b])))return a.push(!0),!0}}},Qt.prototype._forEachCell=function(t,e,r,n,i,a,o,s){for(var l=this._convertToXCellCoord(t),u=this._convertToYCellCoord(e),c=this._convertToXCellCoord(r),f=this._convertToYCellCoord(n),h=l;h<=c;h++)for(var p=u;p<=f;p++){var d=this.xCellCount*p+h;if(i.call(this,t,e,r,n,d,a,o,s))return}},Qt.prototype._convertToXCellCoord=function(t){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(t*this.xScale)))},Qt.prototype._convertToYCellCoord=function(t){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(t*this.yScale)))},Qt.prototype._circlesCollide=function(t,e,r,n,i,a){var o=n-t,s=i-e,l=r+a;return l*l>o*o+s*s},Qt.prototype._circleAndRectCollide=function(t,e,r,n,i,a,o){var s=(a-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;var u=(o-i)/2,c=Math.abs(e-(i+u));if(c>u+r)return!1;if(l<=s||c<=u)return!0;var f=l-s,h=c-u;return f*f+h*h<=r*r};var fe=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function he(t,e){for(var r=0;r<t;r++){var n=e.length;e.resize(n+4),e.float32.set(fe,3*n)}}function pe(t,e,r){var n=e[0],i=e[1];return t[0]=r[0]*n+r[4]*i+r[12],t[1]=r[1]*n+r[5]*i+r[13],t[3]=r[3]*n+r[7]*i+r[15],t}var de=100,ve=function(t,e,r){void 0===e&&(e=new Qt(t.width+200,t.height+200,25)),void 0===r&&(r=new Qt(t.width+200,t.height+200,25)),this.transform=t,this.grid=e,this.ignoredGrid=r,this.pitchfactor=Math.cos(t._pitch)*t.cameraToCenterDistance,this.screenRightBoundary=t.width+de,this.screenBottomBoundary=t.height+de,this.gridRightBoundary=t.width+200,this.gridBottomBoundary=t.height+200};function ge(e,r,n){return r*(t.EXTENT/(e.tileSize*Math.pow(2,n-e.tileID.overscaledZ)))}ve.prototype.placeCollisionBox=function(t,e,r,n,i){var a=this.projectAndGetPerspectiveRatio(n,t.anchorPointX,t.anchorPointY),o=r*a.perspectiveRatio,s=t.x1*o+a.point.x,l=t.y1*o+a.point.y,u=t.x2*o+a.point.x,c=t.y2*o+a.point.y;return!this.isInsideGrid(s,l,u,c)||!e&&this.grid.hitTest(s,l,u,c,i)?{box:[],offscreen:!1}:{box:[s,l,u,c],offscreen:this.isOffscreen(s,l,u,c)}},ve.prototype.placeCollisionCircles=function(e,r,n,i,a,o,s,l,u,c,f,h,p){var d=[],v=new t.Point(r.anchorX,r.anchorY),g=re(v,o),y=ne(this.transform.cameraToCenterDistance,g.signedDistanceFromCamera),m=(c?a/y:a*y)/t.ONE_EM,x=re(v,s).point,b=oe(m,i,r.lineOffsetX*m,r.lineOffsetY*m,!1,x,v,r,n,s,{}),_=!1,w=!1,T=!0;if(b){for(var k=.5*h*y+p,A=new t.Point(-100,-100),M=new t.Point(this.screenRightBoundary,this.screenBottomBoundary),S=new $t,E=b.first,L=b.last,C=[],P=E.path.length-1;P>=1;P--)C.push(E.path[P]);for(var O=1;O<L.path.length;O++)C.push(L.path[O]);var I=2.5*k;if(l){var D=C.map((function(t){return re(t,l)}));C=D.some((function(t){return t.signedDistanceFromCamera<=0}))?[]:D.map((function(t){return t.point}))}var z=[];if(C.length>0){for(var R=C[0].clone(),F=C[0].clone(),B=1;B<C.length;B++)R.x=Math.min(R.x,C[B].x),R.y=Math.min(R.y,C[B].y),F.x=Math.max(F.x,C[B].x),F.y=Math.max(F.y,C[B].y);z=R.x>=A.x&&F.x<=M.x&&R.y>=A.y&&F.y<=M.y?[C]:F.x<A.x||R.x>M.x||F.y<A.y||R.y>M.y?[]:t.clipLine([C],A.x,A.y,M.x,M.y)}for(var N=0,j=z;N<j.length;N+=1){var U=j[N];S.reset(U,.25*k);var V;V=S.length<=.5*k?1:Math.ceil(S.paddedLength/I)+1;for(var H=0;H<V;H++){var q=H/Math.max(V-1,1),G=S.lerp(q),Z=G.x+de,Y=G.y+de;d.push(Z,Y,k,0);var W=Z-k,X=Y-k,J=Z+k,K=Y+k;if(T=T&&this.isOffscreen(W,X,J,K),w=w||this.isInsideGrid(W,X,J,K),!e&&this.grid.hitTestCircle(Z,Y,k,f)&&(_=!0,!u))return{circles:[],offscreen:!1,collisionDetected:_}}}}return{circles:!u&&_||!w?[]:d,offscreen:T,collisionDetected:_}},ve.prototype.queryRenderedSymbols=function(e){if(0===e.length||0===this.grid.keysLength()&&0===this.ignoredGrid.keysLength())return{};for(var r=[],n=1/0,i=1/0,a=-1/0,o=-1/0,s=0,l=e;s<l.length;s+=1){var u=l[s],c=new t.Point(u.x+de,u.y+de);n=Math.min(n,c.x),i=Math.min(i,c.y),a=Math.max(a,c.x),o=Math.max(o,c.y),r.push(c)}for(var f={},h={},p=0,d=this.grid.query(n,i,a,o).concat(this.ignoredGrid.query(n,i,a,o));p<d.length;p+=1){var v=d[p],g=v.key;if(void 0===f[g.bucketInstanceId]&&(f[g.bucketInstanceId]={}),!f[g.bucketInstanceId][g.featureIndex]){var y=[new t.Point(v.x1,v.y1),new t.Point(v.x2,v.y1),new t.Point(v.x2,v.y2),new t.Point(v.x1,v.y2)];t.polygonIntersectsPolygon(r,y)&&(f[g.bucketInstanceId][g.featureIndex]=!0,void 0===h[g.bucketInstanceId]&&(h[g.bucketInstanceId]=[]),h[g.bucketInstanceId].push(g.featureIndex))}}return h},ve.prototype.insertCollisionBox=function(t,e,r,n,i){var a={bucketInstanceId:r,featureIndex:n,collisionGroupID:i};(e?this.ignoredGrid:this.grid).insert(a,t[0],t[1],t[2],t[3])},ve.prototype.insertCollisionCircles=function(t,e,r,n,i){for(var a=e?this.ignoredGrid:this.grid,o={bucketInstanceId:r,featureIndex:n,collisionGroupID:i},s=0;s<t.length;s+=4)a.insertCircle(o,t[s],t[s+1],t[s+2])},ve.prototype.projectAndGetPerspectiveRatio=function(e,r,n){var i=[r,n,0,1];return pe(i,i,e),{point:new t.Point((i[0]/i[3]+1)/2*this.transform.width+de,(-i[1]/i[3]+1)/2*this.transform.height+de),perspectiveRatio:.5+this.transform.cameraToCenterDistance/i[3]*.5}},ve.prototype.isOffscreen=function(t,e,r,n){return r<de||t>=this.screenRightBoundary||n<de||e>this.screenBottomBoundary},ve.prototype.isInsideGrid=function(t,e,r,n){return r>=0&&t<this.gridRightBoundary&&n>=0&&e<this.gridBottomBoundary},ve.prototype.getViewportMatrix=function(){var e=t.identity([]);return t.translate(e,e,[-100,-100,0]),e};var ye=function(t,e,r,n){this.opacity=t?Math.max(0,Math.min(1,t.opacity+(t.placed?e:-e))):n&&r?1:0,this.placed=r};ye.prototype.isHidden=function(){return 0===this.opacity&&!this.placed};var me=function(t,e,r,n,i){this.text=new ye(t?t.text:null,e,r,i),this.icon=new ye(t?t.icon:null,e,n,i)};me.prototype.isHidden=function(){return this.text.isHidden()&&this.icon.isHidden()};var xe=function(t,e,r){this.text=t,this.icon=e,this.skipFade=r},be=function(){this.invProjMatrix=t.create(),this.viewportMatrix=t.create(),this.circles=[]},_e=function(t,e,r,n,i){this.bucketInstanceId=t,this.featureIndex=e,this.sourceLayerIndex=r,this.bucketIndex=n,this.tileID=i},we=function(t){this.crossSourceCollisions=t,this.maxGroupID=0,this.collisionGroups={}};function Te(e,r,n,i,a){var o=t.getAnchorAlignment(e),s=-(o.horizontalAlign-.5)*r,l=-(o.verticalAlign-.5)*n,u=t.evaluateVariableOffset(e,i);return new t.Point(s+u[0]*a,l+u[1]*a)}function ke(e,r,n,i,a,o){var s=e.x1,l=e.x2,u=e.y1,c=e.y2,f=e.anchorPointX,h=e.anchorPointY,p=new t.Point(r,n);return i&&p._rotate(a?o:-o),{x1:s+p.x,y1:u+p.y,x2:l+p.x,y2:c+p.y,anchorPointX:f,anchorPointY:h}}we.prototype.get=function(t){if(this.crossSourceCollisions)return{ID:0,predicate:null};if(!this.collisionGroups[t]){var e=++this.maxGroupID;this.collisionGroups[t]={ID:e,predicate:function(t){return t.collisionGroupID===e}}}return this.collisionGroups[t]};var Ae=function(t,e,r,n){this.transform=t.clone(),this.collisionIndex=new ve(this.transform),this.placements={},this.opacities={},this.variableOffsets={},this.stale=!1,this.commitTime=0,this.fadeDuration=e,this.retainedQueryData={},this.collisionGroups=new we(r),this.collisionCircleArrays={},this.prevPlacement=n,n&&(n.prevPlacement=void 0),this.placedOrientations={}};function Me(t,e,r,n,i){t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0)}Ae.prototype.getBucketParts=function(e,r,n,i){var a=n.getBucket(r),o=n.latestFeatureIndex;if(a&&o&&r.id===a.layerIds[0]){var s=n.collisionBoxArray,l=a.layers[0].layout,u=Math.pow(2,this.transform.zoom-n.tileID.overscaledZ),c=n.tileSize/t.EXTENT,f=this.transform.calculatePosMatrix(n.tileID.toUnwrapped()),h="map"===l.get("text-pitch-alignment"),p="map"===l.get("text-rotation-alignment"),d=ge(n,1,this.transform.zoom),v=te(f,h,p,this.transform,d),g=null;if(h){var y=ee(f,h,p,this.transform,d);g=t.multiply([],this.transform.labelPlaneMatrix,y)}this.retainedQueryData[a.bucketInstanceId]=new _e(a.bucketInstanceId,o,a.sourceLayerIndex,a.index,n.tileID);var m={bucket:a,layout:l,posMatrix:f,textLabelPlaneMatrix:v,labelToScreenMatrix:g,scale:u,textPixelRatio:c,holdingForFade:n.holdingForFade(),collisionBoxArray:s,partiallyEvaluatedTextSize:t.evaluateSizeForZoom(a.textSizeData,this.transform.zoom),collisionGroup:this.collisionGroups.get(a.sourceID)};if(i)for(var x=0,b=a.sortKeyRanges;x<b.length;x+=1){var _=b[x],w=_.sortKey,T=_.symbolInstanceStart,k=_.symbolInstanceEnd;e.push({sortKey:w,symbolInstanceStart:T,symbolInstanceEnd:k,parameters:m})}else e.push({symbolInstanceStart:0,symbolInstanceEnd:a.symbolInstances.length,parameters:m})}},Ae.prototype.attemptAnchorPlacement=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d){var v,g=[f.textOffset0,f.textOffset1],y=Te(t,r,n,g,i),m=this.collisionIndex.placeCollisionBox(ke(e,y.x,y.y,a,o,this.transform.angle),c,s,l,u.predicate);if(!d||0!==this.collisionIndex.placeCollisionBox(ke(d,y.x,y.y,a,o,this.transform.angle),c,s,l,u.predicate).box.length)return m.box.length>0?(this.prevPlacement&&this.prevPlacement.variableOffsets[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID].text&&(v=this.prevPlacement.variableOffsets[f.crossTileID].anchor),this.variableOffsets[f.crossTileID]={textOffset:g,width:r,height:n,anchor:t,textBoxScale:i,prevAnchor:v},this.markUsedJustification(h,t,f,p),h.allowVerticalPlacement&&(this.markUsedOrientation(h,p,f),this.placedOrientations[f.crossTileID]=p),{shift:y,placedGlyphBoxes:m}):void 0},Ae.prototype.placeLayerBucketPart=function(e,r,n){var i=this,a=e.parameters,o=a.bucket,s=a.layout,l=a.posMatrix,u=a.textLabelPlaneMatrix,c=a.labelToScreenMatrix,f=a.textPixelRatio,h=a.holdingForFade,p=a.collisionBoxArray,d=a.partiallyEvaluatedTextSize,v=a.collisionGroup,g=s.get("text-optional"),y=s.get("icon-optional"),m=s.get("text-allow-overlap"),x=s.get("icon-allow-overlap"),b="map"===s.get("text-rotation-alignment"),_="map"===s.get("text-pitch-alignment"),w="none"!==s.get("icon-text-fit"),T="viewport-y"===s.get("symbol-z-order"),k=m&&(x||!o.hasIconData()||y),A=x&&(m||!o.hasTextData()||g);!o.collisionArrays&&p&&o.deserializeCollisionBoxes(p);var M=function(e,a){if(!r[e.crossTileID])if(h)i.placements[e.crossTileID]=new xe(!1,!1,!1);else{var p,T=!1,M=!1,S=!0,E=null,L={box:null,offscreen:null},C={box:null,offscreen:null},P=null,O=null,I=0,D=0,z=0;a.textFeatureIndex?I=a.textFeatureIndex:e.useRuntimeCollisionCircles&&(I=e.featureIndex),a.verticalTextFeatureIndex&&(D=a.verticalTextFeatureIndex);var R=a.textBox;if(R){var F=function(r){var n=t.WritingMode.horizontal;if(o.allowVerticalPlacement&&!r&&i.prevPlacement){var a=i.prevPlacement.placedOrientations[e.crossTileID];a&&(i.placedOrientations[e.crossTileID]=a,n=a,i.markUsedOrientation(o,n,e))}return n},B=function(r,n){if(o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&a.verticalTextBox)for(var i=0,s=o.writingModes;i<s.length&&(s[i]===t.WritingMode.vertical?(L=n(),C=L):L=r(),!(L&&L.box&&L.box.length));i+=1);else L=r()};if(s.get("text-variable-anchor")){var N=s.get("text-variable-anchor");if(i.prevPlacement&&i.prevPlacement.variableOffsets[e.crossTileID]){var j=i.prevPlacement.variableOffsets[e.crossTileID];N.indexOf(j.anchor)>0&&(N=N.filter((function(t){return t!==j.anchor}))).unshift(j.anchor)}var U=function(t,r,n){for(var a=t.x2-t.x1,s=t.y2-t.y1,u=e.textBoxScale,c=w&&!x?r:null,h={box:[],offscreen:!1},p=m?2*N.length:N.length,d=0;d<p;++d){var g=N[d%N.length],y=d>=N.length,k=i.attemptAnchorPlacement(g,t,a,s,u,b,_,f,l,v,y,e,o,n,c);if(k&&(h=k.placedGlyphBoxes)&&h.box&&h.box.length){T=!0,E=k.shift;break}}return h};B((function(){return U(R,a.iconBox,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox,n=L&&L.box&&L.box.length;return o.allowVerticalPlacement&&!n&&e.numVerticalGlyphVertices>0&&r?U(r,a.verticalIconBox,t.WritingMode.vertical):{box:null,offscreen:null}})),L&&(T=L.box,S=L.offscreen);var V=F(L&&L.box);if(!T&&i.prevPlacement){var H=i.prevPlacement.variableOffsets[e.crossTileID];H&&(i.variableOffsets[e.crossTileID]=H,i.markUsedJustification(o,H.anchor,e,V))}}else{var q=function(t,r){var n=i.collisionIndex.placeCollisionBox(t,m,f,l,v.predicate);return n&&n.box&&n.box.length&&(i.markUsedOrientation(o,r,e),i.placedOrientations[e.crossTileID]=r),n};B((function(){return q(R,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox;return o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&r?q(r,t.WritingMode.vertical):{box:null,offscreen:null}})),F(L&&L.box&&L.box.length)}}if(T=(p=L)&&p.box&&p.box.length>0,S=p&&p.offscreen,e.useRuntimeCollisionCircles){var G=o.text.placedSymbolArray.get(e.centerJustifiedTextSymbolIndex),Z=t.evaluateSizeForFeature(o.textSizeData,d,G),Y=s.get("text-padding"),W=e.collisionCircleDiameter;P=i.collisionIndex.placeCollisionCircles(m,G,o.lineVertexArray,o.glyphOffsetArray,Z,l,u,c,n,_,v.predicate,W,Y),T=m||P.circles.length>0&&!P.collisionDetected,S=S&&P.offscreen}if(a.iconFeatureIndex&&(z=a.iconFeatureIndex),a.iconBox){var X=function(t){var e=w&&E?ke(t,E.x,E.y,b,_,i.transform.angle):t;return i.collisionIndex.placeCollisionBox(e,x,f,l,v.predicate)};M=C&&C.box&&C.box.length&&a.verticalIconBox?(O=X(a.verticalIconBox)).box.length>0:(O=X(a.iconBox)).box.length>0,S=S&&O.offscreen}var J=g||0===e.numHorizontalGlyphVertices&&0===e.numVerticalGlyphVertices,K=y||0===e.numIconVertices;if(J||K?K?J||(M=M&&T):T=M&&T:M=T=M&&T,T&&p&&p.box&&(C&&C.box&&D?i.collisionIndex.insertCollisionBox(p.box,s.get("text-ignore-placement"),o.bucketInstanceId,D,v.ID):i.collisionIndex.insertCollisionBox(p.box,s.get("text-ignore-placement"),o.bucketInstanceId,I,v.ID)),M&&O&&i.collisionIndex.insertCollisionBox(O.box,s.get("icon-ignore-placement"),o.bucketInstanceId,z,v.ID),P&&(T&&i.collisionIndex.insertCollisionCircles(P.circles,s.get("text-ignore-placement"),o.bucketInstanceId,I,v.ID),n)){var $=o.bucketInstanceId,Q=i.collisionCircleArrays[$];void 0===Q&&(Q=i.collisionCircleArrays[$]=new be);for(var tt=0;tt<P.circles.length;tt+=4)Q.circles.push(P.circles[tt+0]),Q.circles.push(P.circles[tt+1]),Q.circles.push(P.circles[tt+2]),Q.circles.push(P.collisionDetected?1:0)}i.placements[e.crossTileID]=new xe(T||k,M||A,S||o.justReloaded),r[e.crossTileID]=!0}};if(T)for(var S=o.getSortedSymbolIndexes(this.transform.angle),E=S.length-1;E>=0;--E){var L=S[E];M(o.symbolInstances.get(L),o.collisionArrays[L])}else for(var C=e.symbolInstanceStart;C<e.symbolInstanceEnd;C++)M(o.symbolInstances.get(C),o.collisionArrays[C]);if(n&&o.bucketInstanceId in this.collisionCircleArrays){var P=this.collisionCircleArrays[o.bucketInstanceId];t.invert(P.invProjMatrix,l),P.viewportMatrix=this.collisionIndex.getViewportMatrix()}o.justReloaded=!1},Ae.prototype.markUsedJustification=function(e,r,n,i){var a,o={left:n.leftJustifiedTextSymbolIndex,center:n.centerJustifiedTextSymbolIndex,right:n.rightJustifiedTextSymbolIndex};a=i===t.WritingMode.vertical?n.verticalPlacedTextSymbolIndex:o[t.getAnchorJustification(r)];for(var s=0,l=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex,n.verticalPlacedTextSymbolIndex];s<l.length;s+=1){var u=l[s];u>=0&&(e.text.placedSymbolArray.get(u).crossTileID=a>=0&&u!==a?0:n.crossTileID)}},Ae.prototype.markUsedOrientation=function(e,r,n){for(var i=r===t.WritingMode.horizontal||r===t.WritingMode.horizontalOnly?r:0,a=r===t.WritingMode.vertical?r:0,o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex];o<s.length;o+=1){var l=s[o];e.text.placedSymbolArray.get(l).placedOrientation=i}n.verticalPlacedTextSymbolIndex&&(e.text.placedSymbolArray.get(n.verticalPlacedTextSymbolIndex).placedOrientation=a)},Ae.prototype.commit=function(t){this.commitTime=t,this.zoomAtLastRecencyCheck=this.transform.zoom;var e=this.prevPlacement,r=!1;this.prevZoomAdjustment=e?e.zoomAdjustment(this.transform.zoom):0;var n=e?e.symbolFadeChange(t):1,i=e?e.opacities:{},a=e?e.variableOffsets:{},o=e?e.placedOrientations:{};for(var s in this.placements){var l=this.placements[s],u=i[s];u?(this.opacities[s]=new me(u,n,l.text,l.icon),r=r||l.text!==u.text.placed||l.icon!==u.icon.placed):(this.opacities[s]=new me(null,n,l.text,l.icon,l.skipFade),r=r||l.text||l.icon)}for(var c in i){var f=i[c];if(!this.opacities[c]){var h=new me(f,n,!1,!1);h.isHidden()||(this.opacities[c]=h,r=r||f.text.placed||f.icon.placed)}}for(var p in a)this.variableOffsets[p]||!this.opacities[p]||this.opacities[p].isHidden()||(this.variableOffsets[p]=a[p]);for(var d in o)this.placedOrientations[d]||!this.opacities[d]||this.opacities[d].isHidden()||(this.placedOrientations[d]=o[d]);r?this.lastPlacementChangeTime=t:"number"!=typeof this.lastPlacementChangeTime&&(this.lastPlacementChangeTime=e?e.lastPlacementChangeTime:t)},Ae.prototype.updateLayerOpacities=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1){var a=i[n],o=a.getBucket(t);o&&a.latestFeatureIndex&&t.id===o.layerIds[0]&&this.updateBucketOpacities(o,r,a.collisionBoxArray)}},Ae.prototype.updateBucketOpacities=function(e,r,n){var i=this;e.hasTextData()&&e.text.opacityVertexArray.clear(),e.hasIconData()&&e.icon.opacityVertexArray.clear(),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexArray.clear(),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexArray.clear();var a=e.layers[0].layout,o=new me(null,0,!1,!1,!0),s=a.get("text-allow-overlap"),l=a.get("icon-allow-overlap"),u=a.get("text-variable-anchor"),c="map"===a.get("text-rotation-alignment"),f="map"===a.get("text-pitch-alignment"),h="none"!==a.get("icon-text-fit"),p=new me(null,0,s&&(l||!e.hasIconData()||a.get("icon-optional")),l&&(s||!e.hasTextData()||a.get("text-optional")),!0);!e.collisionArrays&&n&&(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData())&&e.deserializeCollisionBoxes(n);for(var d=function(t,e,r){for(var n=0;n<e/4;n++)t.opacityVertexArray.emplaceBack(r)},v=function(n){var a=e.symbolInstances.get(n),s=a.numHorizontalGlyphVertices,l=a.numVerticalGlyphVertices,v=a.crossTileID,g=r[v],y=i.opacities[v];g?y=o:y||(y=p,i.opacities[v]=y),r[v]=!0;var m=s>0||l>0,x=a.numIconVertices>0,b=i.placedOrientations[a.crossTileID],_=b===t.WritingMode.vertical,w=b===t.WritingMode.horizontal||b===t.WritingMode.horizontalOnly;if(m){var T=De(y.text),k=_?ze:T;d(e.text,s,k);var A=w?ze:T;d(e.text,l,A);var M=y.text.isHidden();[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t){t>=0&&(e.text.placedSymbolArray.get(t).hidden=M||_?1:0)})),a.verticalPlacedTextSymbolIndex>=0&&(e.text.placedSymbolArray.get(a.verticalPlacedTextSymbolIndex).hidden=M||w?1:0);var S=i.variableOffsets[a.crossTileID];S&&i.markUsedJustification(e,S.anchor,a,b);var E=i.placedOrientations[a.crossTileID];E&&(i.markUsedJustification(e,"left",a,E),i.markUsedOrientation(e,E,a))}if(x){var L=De(y.icon),C=!(h&&a.verticalPlacedIconSymbolIndex&&_);if(a.placedIconSymbolIndex>=0){var P=C?L:ze;d(e.icon,a.numIconVertices,P),e.icon.placedSymbolArray.get(a.placedIconSymbolIndex).hidden=y.icon.isHidden()}if(a.verticalPlacedIconSymbolIndex>=0){var O=C?ze:L;d(e.icon,a.numVerticalIconVertices,O),e.icon.placedSymbolArray.get(a.verticalPlacedIconSymbolIndex).hidden=y.icon.isHidden()}}if(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData()){var I=e.collisionArrays[n];if(I){var D=new t.Point(0,0);if(I.textBox||I.verticalTextBox){var z=!0;if(u){var R=i.variableOffsets[v];R?(D=Te(R.anchor,R.width,R.height,R.textOffset,R.textBoxScale),c&&D._rotate(f?i.transform.angle:-i.transform.angle)):z=!1}I.textBox&&Me(e.textCollisionBox.collisionVertexArray,y.text.placed,!z||_,D.x,D.y),I.verticalTextBox&&Me(e.textCollisionBox.collisionVertexArray,y.text.placed,!z||w,D.x,D.y)}var F=Boolean(!w&&I.verticalIconBox);I.iconBox&&Me(e.iconCollisionBox.collisionVertexArray,y.icon.placed,F,h?D.x:0,h?D.y:0),I.verticalIconBox&&Me(e.iconCollisionBox.collisionVertexArray,y.icon.placed,!F,h?D.x:0,h?D.y:0)}}},g=0;g<e.symbolInstances.length;g++)v(g);if(e.sortFeatures(this.transform.angle),this.retainedQueryData[e.bucketInstanceId]&&(this.retainedQueryData[e.bucketInstanceId].featureSortOrder=e.featureSortOrder),e.hasTextData()&&e.text.opacityVertexBuffer&&e.text.opacityVertexBuffer.updateData(e.text.opacityVertexArray),e.hasIconData()&&e.icon.opacityVertexBuffer&&e.icon.opacityVertexBuffer.updateData(e.icon.opacityVertexArray),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexBuffer&&e.iconCollisionBox.collisionVertexBuffer.updateData(e.iconCollisionBox.collisionVertexArray),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexBuffer&&e.textCollisionBox.collisionVertexBuffer.updateData(e.textCollisionBox.collisionVertexArray),e.bucketInstanceId in this.collisionCircleArrays){var y=this.collisionCircleArrays[e.bucketInstanceId];e.placementInvProjMatrix=y.invProjMatrix,e.placementViewportMatrix=y.viewportMatrix,e.collisionCircleArray=y.circles,delete this.collisionCircleArrays[e.bucketInstanceId]}},Ae.prototype.symbolFadeChange=function(t){return 0===this.fadeDuration?1:(t-this.commitTime)/this.fadeDuration+this.prevZoomAdjustment},Ae.prototype.zoomAdjustment=function(t){return Math.max(0,(this.transform.zoom-t)/1.5)},Ae.prototype.hasTransitions=function(t){return this.stale||t-this.lastPlacementChangeTime<this.fadeDuration},Ae.prototype.stillRecent=function(t,e){var r=this.zoomAtLastRecencyCheck===e?1-this.zoomAdjustment(e):1;return this.zoomAtLastRecencyCheck=e,this.commitTime+this.fadeDuration*r>t},Ae.prototype.setStale=function(){this.stale=!0};var Se=Math.pow(2,25),Ee=Math.pow(2,24),Le=Math.pow(2,17),Ce=Math.pow(2,16),Pe=Math.pow(2,9),Oe=Math.pow(2,8),Ie=Math.pow(2,1);function De(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;var e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*Se+e*Ee+r*Le+e*Ce+r*Pe+e*Oe+r*Ie+e}var ze=0,Re=function(t){this._sortAcrossTiles="viewport-y"!==t.layout.get("symbol-z-order")&&void 0!==t.layout.get("symbol-sort-key").constantOr(1),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};Re.prototype.continuePlacement=function(t,e,r,n,i){for(var a=this._bucketParts;this._currentTileIndex<t.length;){var o=t[this._currentTileIndex];if(e.getBucketParts(a,n,o,this._sortAcrossTiles),this._currentTileIndex++,i())return!0}for(this._sortAcrossTiles&&(this._sortAcrossTiles=!1,a.sort((function(t,e){return t.sortKey-e.sortKey})));this._currentPartIndex<a.length;){var s=a[this._currentPartIndex];if(e.placeLayerBucketPart(s,this._seenCrossTileIDs,r),this._currentPartIndex++,i())return!0}return!1};var Fe=function(t,e,r,n,i,a,o){this.placement=new Ae(t,i,a,o),this._currentPlacementIndex=e.length-1,this._forceFullPlacement=r,this._showCollisionBoxes=n,this._done=!1};Fe.prototype.isDone=function(){return this._done},Fe.prototype.continuePlacement=function(e,r,n){for(var i=this,a=t.browser.now(),o=function(){var e=t.browser.now()-a;return!i._forceFullPlacement&&e>2};this._currentPlacementIndex>=0;){var s=r[e[this._currentPlacementIndex]],l=this.placement.collisionIndex.transform.zoom;if("symbol"===s.type&&(!s.minzoom||s.minzoom<=l)&&(!s.maxzoom||s.maxzoom>l)){if(this._inProgressLayer||(this._inProgressLayer=new Re(s)),this._inProgressLayer.continuePlacement(n[s.source],this.placement,this._showCollisionBoxes,s,o))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},Fe.prototype.commit=function(t){return this.placement.commit(t),this.placement};var Be=512/t.EXTENT/2,Ne=function(t,e,r){this.tileID=t,this.indexedSymbolInstances={},this.bucketInstanceId=r;for(var n=0;n<e.length;n++){var i=e.get(n),a=i.key;this.indexedSymbolInstances[a]||(this.indexedSymbolInstances[a]=[]),this.indexedSymbolInstances[a].push({crossTileID:i.crossTileID,coord:this.getScaledCoordinates(i,t)})}};Ne.prototype.getScaledCoordinates=function(e,r){var n=r.canonical.z-this.tileID.canonical.z,i=Be/Math.pow(2,n);return{x:Math.floor((r.canonical.x*t.EXTENT+e.anchorX)*i),y:Math.floor((r.canonical.y*t.EXTENT+e.anchorY)*i)}},Ne.prototype.findMatches=function(t,e,r){for(var n=this.tileID.canonical.z<e.canonical.z?1:Math.pow(2,this.tileID.canonical.z-e.canonical.z),i=0;i<t.length;i++){var a=t.get(i);if(!a.crossTileID){var o=this.indexedSymbolInstances[a.key];if(o)for(var s=this.getScaledCoordinates(a,e),l=0,u=o;l<u.length;l+=1){var c=u[l];if(Math.abs(c.coord.x-s.x)<=n&&Math.abs(c.coord.y-s.y)<=n&&!r[c.crossTileID]){r[c.crossTileID]=!0,a.crossTileID=c.crossTileID;break}}}}};var je=function(){this.maxCrossTileID=0};je.prototype.generate=function(){return++this.maxCrossTileID};var Ue=function(){this.indexes={},this.usedCrossTileIDs={},this.lng=0};Ue.prototype.handleWrapJump=function(t){var e=Math.round((t-this.lng)/360);if(0!==e)for(var r in this.indexes){var n=this.indexes[r],i={};for(var a in n){var o=n[a];o.tileID=o.tileID.unwrapTo(o.tileID.wrap+e),i[o.tileID.key]=o}this.indexes[r]=i}this.lng=t},Ue.prototype.addBucket=function(t,e,r){if(this.indexes[t.overscaledZ]&&this.indexes[t.overscaledZ][t.key]){if(this.indexes[t.overscaledZ][t.key].bucketInstanceId===e.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(t.overscaledZ,this.indexes[t.overscaledZ][t.key])}for(var n=0;n<e.symbolInstances.length;n++)e.symbolInstances.get(n).crossTileID=0;this.usedCrossTileIDs[t.overscaledZ]||(this.usedCrossTileIDs[t.overscaledZ]={});var i=this.usedCrossTileIDs[t.overscaledZ];for(var a in this.indexes){var o=this.indexes[a];if(Number(a)>t.overscaledZ)for(var s in o){var l=o[s];l.tileID.isChildOf(t)&&l.findMatches(e.symbolInstances,t,i)}else{var u=o[t.scaledTo(Number(a)).key];u&&u.findMatches(e.symbolInstances,t,i)}}for(var c=0;c<e.symbolInstances.length;c++){var f=e.symbolInstances.get(c);f.crossTileID||(f.crossTileID=r.generate(),i[f.crossTileID]=!0)}return void 0===this.indexes[t.overscaledZ]&&(this.indexes[t.overscaledZ]={}),this.indexes[t.overscaledZ][t.key]=new Ne(t,e.symbolInstances,e.bucketInstanceId),!0},Ue.prototype.removeBucketCrossTileIDs=function(t,e){for(var r in e.indexedSymbolInstances)for(var n=0,i=e.indexedSymbolInstances[r];n<i.length;n+=1){var a=i[n];delete this.usedCrossTileIDs[t][a.crossTileID]}},Ue.prototype.removeStaleBuckets=function(t){var e=!1;for(var r in this.indexes){var n=this.indexes[r];for(var i in n)t[n[i].bucketInstanceId]||(this.removeBucketCrossTileIDs(r,n[i]),delete n[i],e=!0)}return e};var Ve=function(){this.layerIndexes={},this.crossTileIDs=new je,this.maxBucketInstanceId=0,this.bucketsInCurrentPlacement={}};Ve.prototype.addLayer=function(t,e,r){var n=this.layerIndexes[t.id];void 0===n&&(n=this.layerIndexes[t.id]=new Ue);var i=!1,a={};n.handleWrapJump(r);for(var o=0,s=e;o<s.length;o+=1){var l=s[o],u=l.getBucket(t);u&&t.id===u.layerIds[0]&&(u.bucketInstanceId||(u.bucketInstanceId=++this.maxBucketInstanceId),n.addBucket(l.tileID,u,this.crossTileIDs)&&(i=!0),a[u.bucketInstanceId]=!0)}return n.removeStaleBuckets(a)&&(i=!0),i},Ve.prototype.pruneUnusedLayers=function(t){var e={};for(var r in t.forEach((function(t){e[t]=!0})),this.layerIndexes)e[r]||delete this.layerIndexes[r]};var He=function(e,r){return t.emitValidationErrors(e,r&&r.filter((function(t){return"source.canvas"!==t.identifier})))},qe=t.pick(Ht,["addLayer","removeLayer","setPaintProperty","setLayoutProperty","setFilter","addSource","removeSource","setLayerZoomRange","setLight","setTransition","setGeoJSONSourceData"]),Ge=t.pick(Ht,["setCenter","setZoom","setBearing","setPitch"]),Ze=function(){var e={},r=t.styleSpec.$version;for(var n in t.styleSpec.$root){var i=t.styleSpec.$root[n];if(i.required){var a;null!=(a="version"===n?r:"array"===i.type?[]:{})&&(e[n]=a)}}return e}(),Ye=function(e){function r(n,i){var a=this;void 0===i&&(i={}),e.call(this),this.map=n,this.dispatcher=new A(jt(),this),this.imageManager=new h,this.imageManager.setEventedParent(this),this.glyphManager=new x(n._requestManager,i.localIdeographFontFamily),this.lineAtlas=new k(256,512),this.crossTileSymbolIndex=new Ve,this._layers={},this._serializedLayers={},this._order=[],this.sourceCaches={},this.zoomHistory=new t.ZoomHistory,this._loaded=!1,this._availableImages=[],this._resetUpdates(),this.dispatcher.broadcast("setReferrer",t.getReferrer());var o=this;this._rtlTextPluginCallback=r.registerForPluginStateChange((function(e){var r={pluginStatus:e.pluginStatus,pluginURL:e.pluginURL};o.dispatcher.broadcast("syncRTLPluginState",r,(function(e,r){if(t.triggerPluginCompletionEvent(e),r&&r.every((function(t){return t})))for(var n in o.sourceCaches)o.sourceCaches[n].reload()}))})),this.on("data",(function(t){if("source"===t.dataType&&"metadata"===t.sourceDataType){var e=a.sourceCaches[t.sourceId];if(e){var r=e.getSource();if(r&&r.vectorLayerIds)for(var n in a._layers){var i=a._layers[n];i.source===r.id&&a._validateLayer(i)}}}}))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadURL=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event("dataloading",{dataType:"style"}));var i="boolean"==typeof r.validate?r.validate:!t.isMapboxURL(e);e=this.map._requestManager.normalizeStyleURL(e,r.accessToken);var a=this.map._requestManager.transformRequest(e,t.ResourceType.Style);this._request=t.getJSON(a,(function(e,r){n._request=null,e?n.fire(new t.ErrorEvent(e)):r&&n._load(r,i)}))},r.prototype.loadJSON=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event("dataloading",{dataType:"style"})),this._request=t.browser.frame((function(){n._request=null,n._load(e,!1!==r.validate)}))},r.prototype.loadEmpty=function(){this.fire(new t.Event("dataloading",{dataType:"style"})),this._load(Ze,!1)},r.prototype._load=function(e,r){if(!r||!He(this,t.validateStyle(e))){for(var n in this._loaded=!0,this.stylesheet=e,e.sources)this.addSource(n,e.sources[n],{validate:!1});e.sprite?this._loadSprite(e.sprite):this.imageManager.setLoaded(!0),this.glyphManager.setURL(e.glyphs);var i=Vt(this.stylesheet.layers);this._order=i.map((function(t){return t.id})),this._layers={},this._serializedLayers={};for(var a=0,o=i;a<o.length;a+=1){var s=o[a];(s=t.createStyleLayer(s)).setEventedParent(this,{layer:{id:s.id}}),this._layers[s.id]=s,this._serializedLayers[s.id]=s.serialize()}this.dispatcher.broadcast("setLayers",this._serializeLayers(this._order)),this.light=new T(this.stylesheet.light),this.fire(new t.Event("data",{dataType:"style"})),this.fire(new t.Event("style.load"))}},r.prototype._loadSprite=function(e){var r=this;this._spriteRequest=function(e,r,n){var i,a,o,s=t.browser.devicePixelRatio>1?"@2x":"",l=t.getJSON(r.transformRequest(r.normalizeSpriteURL(e,s,".json"),t.ResourceType.SpriteJSON),(function(t,e){l=null,o||(o=t,i=e,c())})),u=t.getImage(r.transformRequest(r.normalizeSpriteURL(e,s,".png"),t.ResourceType.SpriteImage),(function(t,e){u=null,o||(o=t,a=e,c())}));function c(){if(o)n(o);else if(i&&a){var e=t.browser.getImageData(a),r={};for(var s in i){var l=i[s],u=l.width,c=l.height,f=l.x,h=l.y,p=l.sdf,d=l.pixelRatio,v=l.stretchX,g=l.stretchY,y=l.content,m=new t.RGBAImage({width:u,height:c});t.RGBAImage.copy(e,m,{x:f,y:h},{x:0,y:0},{width:u,height:c}),r[s]={data:m,pixelRatio:d,sdf:p,stretchX:v,stretchY:g,content:y}}n(null,r)}}return{cancel:function(){l&&(l.cancel(),l=null),u&&(u.cancel(),u=null)}}}(e,this.map._requestManager,(function(e,n){if(r._spriteRequest=null,e)r.fire(new t.ErrorEvent(e));else if(n)for(var i in n)r.imageManager.addImage(i,n[i]);r.imageManager.setLoaded(!0),r._availableImages=r.imageManager.listImages(),r.dispatcher.broadcast("setImages",r._availableImages),r.fire(new t.Event("data",{dataType:"style"}))}))},r.prototype._validateLayer=function(e){var r=this.sourceCaches[e.source];if(r){var n=e.sourceLayer;if(n){var i=r.getSource();("geojson"===i.type||i.vectorLayerIds&&-1===i.vectorLayerIds.indexOf(n))&&this.fire(new t.ErrorEvent(new Error('Source layer "'+n+'" does not exist on source "'+i.id+'" as specified by style layer "'+e.id+'"')))}}},r.prototype.loaded=function(){if(!this._loaded)return!1;if(Object.keys(this._updatedSources).length)return!1;for(var t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()},r.prototype._serializeLayers=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r],a=this._layers[i];"custom"!==a.type&&e.push(a.serialize())}return e},r.prototype.hasTransitions=function(){if(this.light&&this.light.hasTransition())return!0;for(var t in this.sourceCaches)if(this.sourceCaches[t].hasTransition())return!0;for(var e in this._layers)if(this._layers[e].hasTransition())return!0;return!1},r.prototype._checkLoaded=function(){if(!this._loaded)throw new Error("Style is not done loading")},r.prototype.update=function(e){if(this._loaded){var r=this._changed;if(this._changed){var n=Object.keys(this._updatedLayers),i=Object.keys(this._removedLayers);for(var a in(n.length||i.length)&&this._updateWorkerLayers(n,i),this._updatedSources){var o=this._updatedSources[a];"reload"===o?this._reloadSource(a):"clear"===o&&this._clearSource(a)}for(var s in this._updateTilesForChangedImages(),this._updatedPaintProps)this._layers[s].updateTransitions(e);this.light.updateTransitions(e),this._resetUpdates()}for(var l in this.sourceCaches)this.sourceCaches[l].used=!1;for(var u=0,c=this._order;u<c.length;u+=1){var f=c[u],h=this._layers[f];h.recalculate(e,this._availableImages),!h.isHidden(e.zoom)&&h.source&&(this.sourceCaches[h.source].used=!0)}this.light.recalculate(e),this.z=e.zoom,r&&this.fire(new t.Event("data",{dataType:"style"}))}},r.prototype._updateTilesForChangedImages=function(){var t=Object.keys(this._changedImages);if(t.length){for(var e in this.sourceCaches)this.sourceCaches[e].reloadTilesForDependencies(["icons","patterns"],t);this._changedImages={}}},r.prototype._updateWorkerLayers=function(t,e){this.dispatcher.broadcast("updateLayers",{layers:this._serializeLayers(t),removedIds:e})},r.prototype._resetUpdates=function(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={},this._changedImages={}},r.prototype.setState=function(e){var r=this;if(this._checkLoaded(),He(this,t.validateStyle(e)))return!1;(e=t.clone$1(e)).layers=Vt(e.layers);var n=Kt(this.serialize(),e).filter((function(t){return!(t.command in Ge)}));if(0===n.length)return!1;var i=n.filter((function(t){return!(t.command in qe)}));if(i.length>0)throw new Error("Unimplemented: "+i.map((function(t){return t.command})).join(", ")+".");return n.forEach((function(t){"setTransition"!==t.command&&r[t.command].apply(r,t.args)})),this.stylesheet=e,!0},r.prototype.addImage=function(e,r){if(this.getImage(e))return this.fire(new t.ErrorEvent(new Error("An image with this name already exists.")));this.imageManager.addImage(e,r),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event("data",{dataType:"style"}))},r.prototype.updateImage=function(t,e){this.imageManager.updateImage(t,e)},r.prototype.getImage=function(t){return this.imageManager.getImage(t)},r.prototype.removeImage=function(e){if(!this.getImage(e))return this.fire(new t.ErrorEvent(new Error("No image with this name exists.")));this.imageManager.removeImage(e),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event("data",{dataType:"style"}))},r.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},r.prototype.addSource=function(e,r,n){var i=this;if(void 0===n&&(n={}),this._checkLoaded(),void 0!==this.sourceCaches[e])throw new Error("There is already a source with this ID");if(!r.type)throw new Error("The type property must be defined, but the only the following properties were given: "+Object.keys(r).join(", ")+".");if(!(["vector","raster","geojson","video","image"].indexOf(r.type)>=0&&this._validate(t.validateStyle.source,"sources."+e,r,null,n))){this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);var a=this.sourceCaches[e]=new Ot(e,r,this.dispatcher);a.style=this,a.setEventedParent(this,(function(){return{isSourceLoaded:i.loaded(),source:a.serialize(),sourceId:e}})),a.onAdd(this.map),this._changed=!0}},r.prototype.removeSource=function(e){if(this._checkLoaded(),void 0===this.sourceCaches[e])throw new Error("There is no source with this ID");for(var r in this._layers)if(this._layers[r].source===e)return this.fire(new t.ErrorEvent(new Error('Source "'+e+'" cannot be removed while layer "'+r+'" is using it.')));var n=this.sourceCaches[e];delete this.sourceCaches[e],delete this._updatedSources[e],n.fire(new t.Event("data",{sourceDataType:"metadata",dataType:"source",sourceId:e})),n.setEventedParent(null),n.clearTiles(),n.onRemove&&n.onRemove(this.map),this._changed=!0},r.prototype.setGeoJSONSourceData=function(t,e){this._checkLoaded(),this.sourceCaches[t].getSource().setData(e),this._changed=!0},r.prototype.getSource=function(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()},r.prototype.addLayer=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=e.id;if(this.getLayer(i))this.fire(new t.ErrorEvent(new Error('Layer with id "'+i+'" already exists on this map')));else{var a;if("custom"===e.type){if(He(this,t.validateCustomStyleLayer(e)))return;a=t.createStyleLayer(e)}else{if("object"==typeof e.source&&(this.addSource(i,e.source),e=t.clone$1(e),e=t.extend(e,{source:i})),this._validate(t.validateStyle.layer,"layers."+i,e,{arrayIndex:-1},n))return;a=t.createStyleLayer(e),this._validateLayer(a),a.setEventedParent(this,{layer:{id:i}}),this._serializedLayers[a.id]=a.serialize()}var o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new t.ErrorEvent(new Error('Layer with id "'+r+'" does not exist on this map.')));else{if(this._order.splice(o,0,i),this._layerOrderChanged=!0,this._layers[i]=a,this._removedLayers[i]&&a.source&&"custom"!==a.type){var s=this._removedLayers[i];delete this._removedLayers[i],s.type!==a.type?this._updatedSources[a.source]="clear":(this._updatedSources[a.source]="reload",this.sourceCaches[a.source].pause())}this._updateLayer(a),a.onAdd&&a.onAdd(this.map)}}},r.prototype.moveLayer=function(e,r){if(this._checkLoaded(),this._changed=!0,this._layers[e]){if(e!==r){var n=this._order.indexOf(e);this._order.splice(n,1);var i=r?this._order.indexOf(r):this._order.length;r&&-1===i?this.fire(new t.ErrorEvent(new Error('Layer with id "'+r+'" does not exist on this map.'))):(this._order.splice(i,0,e),this._layerOrderChanged=!0)}}else this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style and cannot be moved.")))},r.prototype.removeLayer=function(e){this._checkLoaded();var r=this._layers[e];if(r){r.setEventedParent(null);var n=this._order.indexOf(e);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[e]=r,delete this._layers[e],delete this._serializedLayers[e],delete this._updatedLayers[e],delete this._updatedPaintProps[e],r.onRemove&&r.onRemove(this.map)}else this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style and cannot be removed.")))},r.prototype.getLayer=function(t){return this._layers[t]},r.prototype.hasLayer=function(t){return t in this._layers},r.prototype.setLayerZoomRange=function(e,r,n){this._checkLoaded();var i=this.getLayer(e);i?i.minzoom===r&&i.maxzoom===n||(null!=r&&(i.minzoom=r),null!=n&&(i.maxzoom=n),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style and cannot have zoom extent.")))},r.prototype.setFilter=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=this.getLayer(e);if(i){if(!t.deepEqual(i.filter,r))return null==r?(i.filter=void 0,void this._updateLayer(i)):void(this._validate(t.validateStyle.filter,"layers."+i.id+".filter",r,null,n)||(i.filter=t.clone$1(r),this._updateLayer(i)))}else this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style and cannot be filtered.")))},r.prototype.getFilter=function(e){return t.clone$1(this.getLayer(e).filter)},r.prototype.setLayoutProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getLayoutProperty(r),n)||(a.setLayoutProperty(r,n,i),this._updateLayer(a)):this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style and cannot be styled.")))},r.prototype.getLayoutProperty=function(e,r){var n=this.getLayer(e);if(n)return n.getLayoutProperty(r);this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style.")))},r.prototype.setPaintProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getPaintProperty(r),n)||(a.setPaintProperty(r,n,i)&&this._updateLayer(a),this._changed=!0,this._updatedPaintProps[e]=!0):this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style and cannot be styled.")))},r.prototype.getPaintProperty=function(t,e){return this.getLayer(t).getPaintProperty(e)},r.prototype.setFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=e.sourceLayer,a=this.sourceCaches[n];if(void 0!==a){var o=a.getSource().type;"geojson"===o&&i?this.fire(new t.ErrorEvent(new Error("GeoJSON sources cannot have a sourceLayer parameter."))):"vector"!==o||i?(void 0===e.id&&this.fire(new t.ErrorEvent(new Error("The feature id parameter must be provided."))),a.setFeatureState(i,e.id,r)):this.fire(new t.ErrorEvent(new Error("The sourceLayer parameter must be provided for vector source types.")))}else this.fire(new t.ErrorEvent(new Error("The source '"+n+"' does not exist in the map's style.")))},r.prototype.removeFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=this.sourceCaches[n];if(void 0!==i){var a=i.getSource().type,o="vector"===a?e.sourceLayer:void 0;"vector"!==a||o?r&&"string"!=typeof e.id&&"number"!=typeof e.id?this.fire(new t.ErrorEvent(new Error("A feature id is requred to remove its specific state property."))):i.removeFeatureState(o,e.id,r):this.fire(new t.ErrorEvent(new Error("The sourceLayer parameter must be provided for vector source types.")))}else this.fire(new t.ErrorEvent(new Error("The source '"+n+"' does not exist in the map's style.")))},r.prototype.getFeatureState=function(e){this._checkLoaded();var r=e.source,n=e.sourceLayer,i=this.sourceCaches[r];if(void 0!==i){if("vector"!==i.getSource().type||n)return void 0===e.id&&this.fire(new t.ErrorEvent(new Error("The feature id parameter must be provided."))),i.getFeatureState(n,e.id);this.fire(new t.ErrorEvent(new Error("The sourceLayer parameter must be provided for vector source types.")))}else this.fire(new t.ErrorEvent(new Error("The source '"+r+"' does not exist in the map's style.")))},r.prototype.getTransition=function(){return t.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},r.prototype.serialize=function(){return t.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:t.mapObject(this.sourceCaches,(function(t){return t.serialize()})),layers:this._serializeLayers(this._order)},(function(t){return void 0!==t}))},r.prototype._updateLayer=function(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&"raster"!==this.sourceCaches[t.source].getSource().type&&(this._updatedSources[t.source]="reload",this.sourceCaches[t.source].pause()),this._changed=!0},r.prototype._flattenAndSortRenderedFeatures=function(t){for(var e=this,r=function(t){return"fill-extrusion"===e._layers[t].type},n={},i=[],a=this._order.length-1;a>=0;a--){var o=this._order[a];if(r(o)){n[o]=a;for(var s=0,l=t;s<l.length;s+=1){var u=l[s][o];if(u)for(var c=0,f=u;c<f.length;c+=1){var h=f[c];i.push(h)}}}}i.sort((function(t,e){return e.intersectionZ-t.intersectionZ}));for(var p=[],d=this._order.length-1;d>=0;d--){var v=this._order[d];if(r(v))for(var g=i.length-1;g>=0;g--){var y=i[g].feature;if(n[y.layer.id]<d)break;p.push(y),i.pop()}else for(var m=0,x=t;m<x.length;m+=1){var b=x[m][v];if(b)for(var _=0,w=b;_<w.length;_+=1){var T=w[_];p.push(T.feature)}}}return p},r.prototype.queryRenderedFeatures=function(e,r,n){r&&r.filter&&this._validate(t.validateStyle.filter,"queryRenderedFeatures.filter",r.filter,null,r);var i={};if(r&&r.layers){if(!Array.isArray(r.layers))return this.fire(new t.ErrorEvent(new Error("parameters.layers must be an Array."))),[];for(var a=0,o=r.layers;a<o.length;a+=1){var s=o[a],l=this._layers[s];if(!l)return this.fire(new t.ErrorEvent(new Error("The layer '"+s+"' does not exist in the map's style and cannot be queried for features."))),[];i[l.source]=!0}}var u=[];for(var c in r.availableImages=this._availableImages,this.sourceCaches)r.layers&&!i[c]||u.push(B(this.sourceCaches[c],this._layers,this._serializedLayers,e,r,n));return this.placement&&u.push(function(t,e,r,n,i,a,o){for(var s={},l=a.queryRenderedSymbols(n),u=[],c=0,f=Object.keys(l).map(Number);c<f.length;c+=1){var h=f[c];u.push(o[h])}u.sort(N);for(var p=function(){var r=v[d],n=r.featureIndex.lookupSymbolFeatures(l[r.bucketInstanceId],e,r.bucketIndex,r.sourceLayerIndex,i.filter,i.layers,i.availableImages,t);for(var a in n){var o=s[a]=s[a]||[],u=n[a];u.sort((function(t,e){var n=r.featureSortOrder;if(n){var i=n.indexOf(t.featureIndex);return n.indexOf(e.featureIndex)-i}return e.featureIndex-t.featureIndex}));for(var c=0,f=u;c<f.length;c+=1){var h=f[c];o.push(h)}}},d=0,v=u;d<v.length;d+=1)p();var g=function(e){s[e].forEach((function(n){var i=n.feature,a=t[e],o=r[a.source].getFeatureState(i.layer["source-layer"],i.id);i.source=i.layer.source,i.layer["source-layer"]&&(i.sourceLayer=i.layer["source-layer"]),i.state=o}))};for(var y in s)g(y);return s}(this._layers,this._serializedLayers,this.sourceCaches,e,r,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenAndSortRenderedFeatures(u)},r.prototype.querySourceFeatures=function(e,r){r&&r.filter&&this._validate(t.validateStyle.filter,"querySourceFeatures.filter",r.filter,null,r);var n=this.sourceCaches[e];return n?function(t,e){for(var r=t.getRenderableIds().map((function(e){return t.getTileByID(e)})),n=[],i={},a=0;a<r.length;a++){var o=r[a],s=o.tileID.canonical.key;i[s]||(i[s]=!0,o.querySourceFeatures(n,e))}return n}(n,r):[]},r.prototype.addSourceType=function(t,e,n){return r.getSourceType(t)?n(new Error('A source type called "'+t+'" already exists.')):(r.setSourceType(t,e),e.workerSourceURL?void this.dispatcher.broadcast("loadWorkerSource",{name:t,url:e.workerSourceURL},n):n(null,null))},r.prototype.getLight=function(){return this.light.getLight()},r.prototype.setLight=function(e,r){void 0===r&&(r={}),this._checkLoaded();var n=this.light.getLight(),i=!1;for(var a in e)if(!t.deepEqual(e[a],n[a])){i=!0;break}if(i){var o={now:t.browser.now(),transition:t.extend({duration:300,delay:0},this.stylesheet.transition)};this.light.setLight(e,r),this.light.updateTransitions(o)}},r.prototype._validate=function(e,r,n,i,a){return void 0===a&&(a={}),(!a||!1!==a.validate)&&He(this,e.call(t.validateStyle,t.extend({key:r,style:this.serialize(),value:n,styleSpec:t.styleSpec},i)))},r.prototype._remove=function(){for(var e in this._request&&(this._request.cancel(),this._request=null),this._spriteRequest&&(this._spriteRequest.cancel(),this._spriteRequest=null),t.evented.off("pluginStateChange",this._rtlTextPluginCallback),this._layers)this._layers[e].setEventedParent(null);for(var r in this.sourceCaches)this.sourceCaches[r].clearTiles(),this.sourceCaches[r].setEventedParent(null);this.imageManager.setEventedParent(null),this.setEventedParent(null),this.dispatcher.remove()},r.prototype._clearSource=function(t){this.sourceCaches[t].clearTiles()},r.prototype._reloadSource=function(t){this.sourceCaches[t].resume(),this.sourceCaches[t].reload()},r.prototype._updateSources=function(t){for(var e in this.sourceCaches)this.sourceCaches[e].update(t)},r.prototype._generateCollisionBoxes=function(){for(var t in this.sourceCaches)this._reloadSource(t)},r.prototype._updatePlacement=function(e,r,n,i,a){void 0===a&&(a=!1);for(var o=!1,s=!1,l={},u=0,c=this._order;u<c.length;u+=1){var f=c[u],h=this._layers[f];if("symbol"===h.type){if(!l[h.source]){var p=this.sourceCaches[h.source];l[h.source]=p.getRenderableIds(!0).map((function(t){return p.getTileByID(t)})).sort((function(t,e){return e.tileID.overscaledZ-t.tileID.overscaledZ||(t.tileID.isLessThan(e.tileID)?-1:1)}))}var d=this.crossTileSymbolIndex.addLayer(h,l[h.source],e.center.lng);o=o||d}}if(this.crossTileSymbolIndex.pruneUnusedLayers(this._order),((a=a||this._layerOrderChanged||0===n)||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(t.browser.now(),e.zoom))&&(this.pauseablePlacement=new Fe(e,this._order,a,r,n,i,this.placement),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,l),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(t.browser.now()),s=!0),o&&this.pauseablePlacement.placement.setStale()),s||o)for(var v=0,g=this._order;v<g.length;v+=1){var y=g[v],m=this._layers[y];"symbol"===m.type&&this.placement.updateLayerOpacities(m,l[m.source])}return!this.pauseablePlacement.isDone()||this.placement.hasTransitions(t.browser.now())},r.prototype._releaseSymbolFadeTiles=function(){for(var t in this.sourceCaches)this.sourceCaches[t].releaseSymbolFadeTiles()},r.prototype.getImages=function(t,e,r){this.imageManager.getImages(e.icons,r),this._updateTilesForChangedImages();var n=this.sourceCaches[e.source];n&&n.setDependencies(e.tileID.key,e.type,e.icons)},r.prototype.getGlyphs=function(t,e,r){this.glyphManager.getGlyphs(e.stacks,r)},r.prototype.getResource=function(e,r,n){return t.makeRequest(r,n)},r}(t.Evented);Ye.getSourceType=function(t){return R[t]},Ye.setSourceType=function(t,e){R[t]=e},Ye.registerForPluginStateChange=t.registerForPluginStateChange;var We=t.createLayout([{name:"a_pos",type:"Int16",components:2}]),Xe=_r("#ifdef GL_ES\nprecision mediump float;\n#else\n#if !defined(lowp)\n#define lowp\n#endif\n#if !defined(mediump)\n#define mediump\n#endif\n#if !defined(highp)\n#define highp\n#endif\n#endif","#ifdef GL_ES\nprecision highp float;\n#else\n#if !defined(lowp)\n#define lowp\n#endif\n#if !defined(mediump)\n#define mediump\n#endif\n#if !defined(highp)\n#define highp\n#endif\n#endif\nvec2 unpack_float(const float packedValue) {int packedIntValue=int(packedValue);int v0=packedIntValue/256;return vec2(v0,packedIntValue-v0*256);}vec2 unpack_opacity(const float packedOpacity) {int intOpacity=int(packedOpacity)/2;return vec2(float(intOpacity)/127.0,mod(packedOpacity,2.0));}vec4 decode_color(const vec2 encodedColor) {return vec4(unpack_float(encodedColor[0])/255.0,unpack_float(encodedColor[1])/255.0\n);}float unpack_mix_vec2(const vec2 packedValue,const float t) {return mix(packedValue[0],packedValue[1],t);}vec4 unpack_mix_color(const vec4 packedColors,const float t) {vec4 minColor=decode_color(vec2(packedColors[0],packedColors[1]));vec4 maxColor=decode_color(vec2(packedColors[2],packedColors[3]));return mix(minColor,maxColor,t);}vec2 get_pattern_pos(const vec2 pixel_coord_upper,const vec2 pixel_coord_lower,const vec2 pattern_size,const float tile_units_to_pixels,const vec2 pos) {vec2 offset=mod(mod(mod(pixel_coord_upper,pattern_size)*256.0,pattern_size)*256.0+pixel_coord_lower,pattern_size);return (tile_units_to_pixels*pos+offset)/pattern_size;}"),Je=_r("uniform vec4 u_color;uniform float u_opacity;void main() {gl_FragColor=u_color*u_opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}"),Ke=_r("uniform vec2 u_pattern_tl_a;uniform vec2 u_pattern_br_a;uniform vec2 u_pattern_tl_b;uniform vec2 u_pattern_br_b;uniform vec2 u_texsize;uniform float u_mix;uniform float u_opacity;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(u_pattern_tl_a/u_texsize,u_pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(u_pattern_tl_b/u_texsize,u_pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_mix)*u_opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_pattern_size_a;uniform vec2 u_pattern_size_b;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_scale_a;uniform float u_scale_b;uniform float u_tile_units_to_pixels;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_a*u_pattern_size_a,u_tile_units_to_pixels,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_b*u_pattern_size_b,u_tile_units_to_pixels,a_pos);}"),$e=_r("varying vec3 v_data;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define mediump float radius\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define highp vec4 stroke_color\n#pragma mapbox: define mediump float stroke_width\n#pragma mapbox: define lowp float stroke_opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize mediump float radius\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize highp vec4 stroke_color\n#pragma mapbox: initialize mediump float stroke_width\n#pragma mapbox: initialize lowp float stroke_opacity\nvec2 extrude=v_data.xy;float extrude_length=length(extrude);lowp float antialiasblur=v_data.z;float antialiased_blur=-max(blur,antialiasblur);float opacity_t=smoothstep(0.0,antialiased_blur,extrude_length-1.0);float color_t=stroke_width < 0.01 ? 0.0 : smoothstep(antialiased_blur,0.0,extrude_length-radius/(radius+stroke_width));gl_FragColor=opacity_t*mix(color*opacity,stroke_color*stroke_opacity,color_t);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform bool u_scale_with_map;uniform bool u_pitch_with_map;uniform vec2 u_extrude_scale;uniform lowp float u_device_pixel_ratio;uniform highp float u_camera_to_center_distance;attribute vec2 a_pos;varying vec3 v_data;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define mediump float radius\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define highp vec4 stroke_color\n#pragma mapbox: define mediump float stroke_width\n#pragma mapbox: define lowp float stroke_opacity\nvoid main(void) {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize mediump float radius\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize highp vec4 stroke_color\n#pragma mapbox: initialize mediump float stroke_width\n#pragma mapbox: initialize lowp float stroke_opacity\nvec2 extrude=vec2(mod(a_pos,2.0)*2.0-1.0);vec2 circle_center=floor(a_pos*0.5);if (u_pitch_with_map) {vec2 corner_position=circle_center;if (u_scale_with_map) {corner_position+=extrude*(radius+stroke_width)*u_extrude_scale;} else {vec4 projected_center=u_matrix*vec4(circle_center,0,1);corner_position+=extrude*(radius+stroke_width)*u_extrude_scale*(projected_center.w/u_camera_to_center_distance);}gl_Position=u_matrix*vec4(corner_position,0,1);} else {gl_Position=u_matrix*vec4(circle_center,0,1);if (u_scale_with_map) {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*u_camera_to_center_distance;} else {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*gl_Position.w;}}lowp float antialiasblur=1.0/u_device_pixel_ratio/(radius+stroke_width);v_data=vec3(extrude.x,extrude.y,antialiasblur);}"),Qe=_r("void main() {gl_FragColor=vec4(1.0);}","attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}"),tr=_r("uniform highp float u_intensity;varying vec2 v_extrude;\n#pragma mapbox: define highp float weight\n#define GAUSS_COEF 0.3989422804014327\nvoid main() {\n#pragma mapbox: initialize highp float weight\nfloat d=-0.5*3.0*3.0*dot(v_extrude,v_extrude);float val=weight*u_intensity*GAUSS_COEF*exp(d);gl_FragColor=vec4(val,1.0,1.0,1.0);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform float u_extrude_scale;uniform float u_opacity;uniform float u_intensity;attribute vec2 a_pos;varying vec2 v_extrude;\n#pragma mapbox: define highp float weight\n#pragma mapbox: define mediump float radius\nconst highp float ZERO=1.0/255.0/16.0;\n#define GAUSS_COEF 0.3989422804014327\nvoid main(void) {\n#pragma mapbox: initialize highp float weight\n#pragma mapbox: initialize mediump float radius\nvec2 unscaled_extrude=vec2(mod(a_pos,2.0)*2.0-1.0);float S=sqrt(-2.0*log(ZERO/weight/u_intensity/GAUSS_COEF))/3.0;v_extrude=S*unscaled_extrude;vec2 extrude=v_extrude*radius*u_extrude_scale;vec4 pos=vec4(floor(a_pos*0.5)+extrude,0,1);gl_Position=u_matrix*pos;}"),er=_r("uniform sampler2D u_image;uniform sampler2D u_color_ramp;uniform float u_opacity;varying vec2 v_pos;void main() {float t=texture2D(u_image,v_pos).r;vec4 color=texture2D(u_color_ramp,vec2(t,0.5));gl_FragColor=color*u_opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(0.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_world;attribute vec2 a_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos*u_world,0,1);v_pos.x=a_pos.x;v_pos.y=1.0-a_pos.y;}"),rr=_r("varying float v_placed;varying float v_notUsed;void main() {float alpha=0.5;gl_FragColor=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}","attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;attribute vec2 a_shift;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);gl_Position.xy+=(a_extrude+a_shift)*u_extrude_scale*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;}"),nr=_r("varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}","attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd  =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz  /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}"),ir=_r("uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}","attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,0,1);}"),ar=_r("#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float opacity\ngl_FragColor=color*opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","attribute vec2 a_pos;uniform mat4 u_matrix;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float opacity\ngl_Position=u_matrix*vec4(a_pos,0,1);}"),or=_r("varying vec2 v_pos;\n#pragma mapbox: define highp vec4 outline_color\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 outline_color\n#pragma mapbox: initialize lowp float opacity\nfloat dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\n#pragma mapbox: define highp vec4 outline_color\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 outline_color\n#pragma mapbox: initialize lowp float opacity\ngl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}"),sr=_r("uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}"),lr=_r("uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}"),ur=_r("varying vec4 v_color;void main() {gl_FragColor=v_color;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec4 v_color;\n#pragma mapbox: define highp float base\n#pragma mapbox: define highp float height\n#pragma mapbox: define highp vec4 color\nvoid main() {\n#pragma mapbox: initialize highp float base\n#pragma mapbox: initialize highp float height\n#pragma mapbox: initialize highp vec4 color\nvec3 normal=a_normal_ed.xyz;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}"),cr=_r("uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\n#pragma mapbox: define lowp float base\n#pragma mapbox: define lowp float height\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float base\n#pragma mapbox: initialize lowp float height\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\n#pragma mapbox: define lowp float base\n#pragma mapbox: define lowp float height\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float base\n#pragma mapbox: initialize lowp float height\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\n? a_pos\n: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}"),fr=_r("#ifdef GL_ES\nprecision highp float;\n#endif\nuniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform float u_maxzoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggeration=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/ pow(2.0,(u_zoom-u_maxzoom)*exaggeration+19.2562-u_zoom);gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}"),hr=_r("uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\n#define PI 3.141592653589793\nvoid main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}"),pr=_r("uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","\n#define scale 0.015873016\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define mediump float gapwidth\n#pragma mapbox: define lowp float offset\n#pragma mapbox: define mediump float width\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump float gapwidth\n#pragma mapbox: initialize lowp float offset\n#pragma mapbox: initialize mediump float width\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}"),dr=_r("uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp float v_lineprogress;\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,vec2(v_lineprogress,0.5));gl_FragColor=color*(alpha*opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","\n#define MAX_LINE_DISTANCE 32767.0\n#define scale 0.015873016\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_lineprogress;\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define mediump float gapwidth\n#pragma mapbox: define lowp float offset\n#pragma mapbox: define mediump float width\nvoid main() {\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump float gapwidth\n#pragma mapbox: initialize lowp float offset\n#pragma mapbox: initialize mediump float width\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_lineprogress=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0/MAX_LINE_DISTANCE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}"),vr=_r("uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","\n#define scale 0.015873016\n#define LINE_DISTANCE_SCALE 2.0\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float offset\n#pragma mapbox: define mediump float gapwidth\n#pragma mapbox: define mediump float width\n#pragma mapbox: define lowp float floorwidth\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float offset\n#pragma mapbox: initialize mediump float gapwidth\n#pragma mapbox: initialize mediump float width\n#pragma mapbox: initialize lowp float floorwidth\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}"),gr=_r("uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define mediump float width\n#pragma mapbox: define lowp float floorwidth\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump float width\n#pragma mapbox: initialize lowp float floorwidth\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","\n#define scale 0.015873016\n#define LINE_DISTANCE_SCALE 2.0\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define mediump float gapwidth\n#pragma mapbox: define lowp float offset\n#pragma mapbox: define mediump float width\n#pragma mapbox: define lowp float floorwidth\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump float gapwidth\n#pragma mapbox: initialize lowp float offset\n#pragma mapbox: initialize mediump float width\n#pragma mapbox: initialize lowp float floorwidth\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}"),yr=_r("uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}"),mr=_r("uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\nlowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity;\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\ncamera_to_anchor_distance/u_camera_to_center_distance :\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}"),xr=_r("#define SDF_PX 8.0\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\n#pragma mapbox: define highp vec4 fill_color\n#pragma mapbox: define highp vec4 halo_color\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float halo_width\n#pragma mapbox: define lowp float halo_blur\nvoid main() {\n#pragma mapbox: initialize highp vec4 fill_color\n#pragma mapbox: initialize highp vec4 halo_color\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float halo_width\n#pragma mapbox: initialize lowp float halo_blur\nfloat EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1;\n#pragma mapbox: define highp vec4 fill_color\n#pragma mapbox: define highp vec4 halo_color\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float halo_width\n#pragma mapbox: define lowp float halo_blur\nvoid main() {\n#pragma mapbox: initialize highp vec4 fill_color\n#pragma mapbox: initialize highp vec4 halo_color\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float halo_width\n#pragma mapbox: initialize lowp float halo_blur\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\ncamera_to_anchor_distance/u_camera_to_center_distance :\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}"),br=_r("#define SDF_PX 8.0\n#define SDF 1.0\n#define ICON 0.0\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\n#pragma mapbox: define highp vec4 fill_color\n#pragma mapbox: define highp vec4 halo_color\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float halo_width\n#pragma mapbox: define lowp float halo_blur\nvoid main() {\n#pragma mapbox: initialize highp vec4 fill_color\n#pragma mapbox: initialize highp vec4 halo_color\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float halo_width\n#pragma mapbox: initialize lowp float halo_blur\nfloat fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\nreturn;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1;\n#pragma mapbox: define highp vec4 fill_color\n#pragma mapbox: define highp vec4 halo_color\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float halo_width\n#pragma mapbox: define lowp float halo_blur\nvoid main() {\n#pragma mapbox: initialize highp vec4 fill_color\n#pragma mapbox: initialize highp vec4 halo_color\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float halo_width\n#pragma mapbox: initialize lowp float halo_blur\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\ncamera_to_anchor_distance/u_camera_to_center_distance :\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}");function _r(t,e){var r=/#pragma mapbox: ([\w]+) ([\w]+) ([\w]+) ([\w]+)/g,n={};return{fragmentSource:t=t.replace(r,(function(t,e,r,i,a){return n[a]=!0,"define"===e?"\n#ifndef HAS_UNIFORM_u_"+a+"\nvarying "+r+" "+i+" "+a+";\n#else\nuniform "+r+" "+i+" u_"+a+";\n#endif\n":"\n#ifdef HAS_UNIFORM_u_"+a+"\n    "+r+" "+i+" "+a+" = u_"+a+";\n#endif\n"})),vertexSource:e=e.replace(r,(function(t,e,r,i,a){var o="float"===i?"vec2":"vec4",s=a.match(/color/)?"color":o;return n[a]?"define"===e?"\n#ifndef HAS_UNIFORM_u_"+a+"\nuniform lowp float u_"+a+"_t;\nattribute "+r+" "+o+" a_"+a+";\nvarying "+r+" "+i+" "+a+";\n#else\nuniform "+r+" "+i+" u_"+a+";\n#endif\n":"vec4"===s?"\n#ifndef HAS_UNIFORM_u_"+a+"\n    "+a+" = a_"+a+";\n#else\n    "+r+" "+i+" "+a+" = u_"+a+";\n#endif\n":"\n#ifndef HAS_UNIFORM_u_"+a+"\n    "+a+" = unpack_mix_"+s+"(a_"+a+", u_"+a+"_t);\n#else\n    "+r+" "+i+" "+a+" = u_"+a+";\n#endif\n":"define"===e?"\n#ifndef HAS_UNIFORM_u_"+a+"\nuniform lowp float u_"+a+"_t;\nattribute "+r+" "+o+" a_"+a+";\n#else\nuniform "+r+" "+i+" u_"+a+";\n#endif\n":"vec4"===s?"\n#ifndef HAS_UNIFORM_u_"+a+"\n    "+r+" "+i+" "+a+" = a_"+a+";\n#else\n    "+r+" "+i+" "+a+" = u_"+a+";\n#endif\n":"\n#ifndef HAS_UNIFORM_u_"+a+"\n    "+r+" "+i+" "+a+" = unpack_mix_"+s+"(a_"+a+", u_"+a+"_t);\n#else\n    "+r+" "+i+" "+a+" = u_"+a+";\n#endif\n"}))}}var wr=Object.freeze({__proto__:null,prelude:Xe,background:Je,backgroundPattern:Ke,circle:$e,clippingMask:Qe,heatmap:tr,heatmapTexture:er,collisionBox:rr,collisionCircle:nr,debug:ir,fill:ar,fillOutline:or,fillOutlinePattern:sr,fillPattern:lr,fillExtrusion:ur,fillExtrusionPattern:cr,hillshadePrepare:fr,hillshade:hr,line:pr,lineGradient:dr,linePattern:vr,lineSDF:gr,raster:yr,symbolIcon:mr,symbolSDF:xr,symbolTextAndIcon:br}),Tr=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};Tr.prototype.bind=function(t,e,r,n,i,a,o,s){this.context=t;for(var l=this.boundPaintVertexBuffers.length!==n.length,u=0;!l&&u<n.length;u++)this.boundPaintVertexBuffers[u]!==n[u]&&(l=!0);var c=!this.vao||this.boundProgram!==e||this.boundLayoutVertexBuffer!==r||l||this.boundIndexBuffer!==i||this.boundVertexOffset!==a||this.boundDynamicVertexBuffer!==o||this.boundDynamicVertexBuffer2!==s;!t.extVertexArrayObject||c?this.freshBind(e,r,n,i,a,o,s):(t.bindVertexArrayOES.set(this.vao),o&&o.bind(),i&&i.dynamicDraw&&i.bind(),s&&s.bind())},Tr.prototype.freshBind=function(t,e,r,n,i,a,o){var s,l=t.numAttributes,u=this.context,c=u.gl;if(u.extVertexArrayObject)this.vao&&this.destroy(),this.vao=u.extVertexArrayObject.createVertexArrayOES(),u.bindVertexArrayOES.set(this.vao),s=0,this.boundProgram=t,this.boundLayoutVertexBuffer=e,this.boundPaintVertexBuffers=r,this.boundIndexBuffer=n,this.boundVertexOffset=i,this.boundDynamicVertexBuffer=a,this.boundDynamicVertexBuffer2=o;else{s=u.currentNumAttributes||0;for(var f=l;f<s;f++)c.disableVertexAttribArray(f)}e.enableAttributes(c,t);for(var h=0,p=r;h<p.length;h+=1)p[h].enableAttributes(c,t);a&&a.enableAttributes(c,t),o&&o.enableAttributes(c,t),e.bind(),e.setVertexAttribPointers(c,t,i);for(var d=0,v=r;d<v.length;d+=1){var g=v[d];g.bind(),g.setVertexAttribPointers(c,t,i)}a&&(a.bind(),a.setVertexAttribPointers(c,t,i)),n&&n.bind(),o&&(o.bind(),o.setVertexAttribPointers(c,t,i)),u.currentNumAttributes=l},Tr.prototype.destroy=function(){this.vao&&(this.context.extVertexArrayObject.deleteVertexArrayOES(this.vao),this.vao=null)};var kr=function(t,e,r,n,i){var a=t.gl;this.program=a.createProgram();var o=r?r.defines():[];i&&o.push("#define OVERDRAW_INSPECTOR;");var s=o.concat(Xe.fragmentSource,e.fragmentSource).join("\n"),l=o.concat(Xe.vertexSource,e.vertexSource).join("\n"),u=a.createShader(a.FRAGMENT_SHADER);if(a.isContextLost())this.failedToCreate=!0;else{a.shaderSource(u,s),a.compileShader(u),a.attachShader(this.program,u);var c=a.createShader(a.VERTEX_SHADER);if(a.isContextLost())this.failedToCreate=!0;else{a.shaderSource(c,l),a.compileShader(c),a.attachShader(this.program,c);for(var f=r?r.layoutAttributes:[],h=0;h<f.length;h++)a.bindAttribLocation(this.program,h,f[h].name);a.linkProgram(this.program),a.deleteShader(c),a.deleteShader(u),this.numAttributes=a.getProgramParameter(this.program,a.ACTIVE_ATTRIBUTES),this.attributes={};for(var p={},d=0;d<this.numAttributes;d++){var v=a.getActiveAttrib(this.program,d);v&&(this.attributes[v.name]=a.getAttribLocation(this.program,v.name))}for(var g=a.getProgramParameter(this.program,a.ACTIVE_UNIFORMS),y=0;y<g;y++){var m=a.getActiveUniform(this.program,y);m&&(p[m.name]=a.getUniformLocation(this.program,m.name))}this.fixedUniforms=n(t,p),this.binderUniforms=r?r.getUniforms(t,p):[]}}};function Ar(t,e,r){var n=1/ge(r,1,e.transform.tileZoom),i=Math.pow(2,r.tileID.overscaledZ),a=r.tileSize*Math.pow(2,e.transform.tileZoom)/i,o=a*(r.tileID.canonical.x+r.tileID.wrap*i),s=a*r.tileID.canonical.y;return{u_image:0,u_texsize:r.imageAtlasTexture.size,u_scale:[n,t.fromScale,t.toScale],u_fade:t.t,u_pixel_coord_upper:[o>>16,s>>16],u_pixel_coord_lower:[65535&o,65535&s]}}kr.prototype.draw=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v){var g,y=t.gl;if(!this.failedToCreate){for(var m in t.program.set(this.program),t.setDepthMode(r),t.setStencilMode(n),t.setColorMode(i),t.setCullFace(a),this.fixedUniforms)this.fixedUniforms[m].set(o[m]);p&&p.setUniforms(t,this.binderUniforms,f,{zoom:h});for(var x=(g={},g[y.LINES]=2,g[y.TRIANGLES]=3,g[y.LINE_STRIP]=1,g)[e],b=0,_=c.get();b<_.length;b+=1){var w=_[b],T=w.vaos||(w.vaos={});(T[s]||(T[s]=new Tr)).bind(t,this,l,p?p.getPaintVertexBuffers():[],u,w.vertexOffset,d,v),y.drawElements(e,w.primitiveLength*x,y.UNSIGNED_SHORT,w.primitiveOffset*x*2)}}};var Mr=function(e,r,n,i){var a=r.style.light,o=a.properties.get("position"),s=[o.x,o.y,o.z],l=t.create$1();"viewport"===a.properties.get("anchor")&&t.fromRotation(l,-r.transform.angle),t.transformMat3(s,s,l);var u=a.properties.get("color");return{u_matrix:e,u_lightpos:s,u_lightintensity:a.properties.get("intensity"),u_lightcolor:[u.r,u.g,u.b],u_vertical_gradient:+n,u_opacity:i}},Sr=function(e,r,n,i,a,o,s){return t.extend(Mr(e,r,n,i),Ar(o,r,s),{u_height_factor:-Math.pow(2,a.overscaledZ)/s.tileSize/8})},Er=function(t){return{u_matrix:t}},Lr=function(e,r,n,i){return t.extend(Er(e),Ar(n,r,i))},Cr=function(t,e){return{u_matrix:t,u_world:e}},Pr=function(e,r,n,i,a){return t.extend(Lr(e,r,n,i),{u_world:a})},Or=function(e,r,n,i){var a,o,s=e.transform;if("map"===i.paint.get("circle-pitch-alignment")){var l=ge(n,1,s.zoom);a=!0,o=[l,l]}else a=!1,o=s.pixelsToGLUnits;return{u_camera_to_center_distance:s.cameraToCenterDistance,u_scale_with_map:+("map"===i.paint.get("circle-pitch-scale")),u_matrix:e.translatePosMatrix(r.posMatrix,n,i.paint.get("circle-translate"),i.paint.get("circle-translate-anchor")),u_pitch_with_map:+a,u_device_pixel_ratio:t.browser.devicePixelRatio,u_extrude_scale:o}},Ir=function(t,e,r){var n=ge(r,1,e.zoom),i=Math.pow(2,e.zoom-r.tileID.overscaledZ),a=r.tileID.overscaleFactor();return{u_matrix:t,u_camera_to_center_distance:e.cameraToCenterDistance,u_pixels_to_tile_units:n,u_extrude_scale:[e.pixelsToGLUnits[0]/(n*i),e.pixelsToGLUnits[1]/(n*i)],u_overscale_factor:a}},Dr=function(t,e,r){return{u_matrix:t,u_inv_matrix:e,u_camera_to_center_distance:r.cameraToCenterDistance,u_viewport_size:[r.width,r.height]}},zr=function(t,e,r){return void 0===r&&(r=1),{u_matrix:t,u_color:e,u_overlay:0,u_overlay_scale:r}},Rr=function(t){return{u_matrix:t}},Fr=function(t,e,r,n){return{u_matrix:t,u_extrude_scale:ge(e,1,r),u_intensity:n}},Br=function(e,r,n,i){var a=t.create();t.ortho(a,0,e.width,e.height,0,0,1);var o=e.context.gl;return{u_matrix:a,u_world:[o.drawingBufferWidth,o.drawingBufferHeight],u_image:n,u_color_ramp:i,u_opacity:r.paint.get("heatmap-opacity")}},Nr=function(e,r,n){var i=n.paint.get("hillshade-shadow-color"),a=n.paint.get("hillshade-highlight-color"),o=n.paint.get("hillshade-accent-color"),s=n.paint.get("hillshade-illumination-direction")*(Math.PI/180);"viewport"===n.paint.get("hillshade-illumination-anchor")&&(s-=e.transform.angle);var l,u,c,f=!e.options.moving;return{u_matrix:e.transform.calculatePosMatrix(r.tileID.toUnwrapped(),f),u_image:0,u_latrange:(l=r.tileID,u=Math.pow(2,l.canonical.z),c=l.canonical.y,[new t.MercatorCoordinate(0,c/u).toLngLat().lat,new t.MercatorCoordinate(0,(c+1)/u).toLngLat().lat]),u_light:[n.paint.get("hillshade-exaggeration"),s],u_shadow:i,u_highlight:a,u_accent:o}},jr=function(e,r,n){var i=r.stride,a=t.create();return t.ortho(a,0,t.EXTENT,-t.EXTENT,0,0,1),t.translate(a,a,[0,-t.EXTENT,0]),{u_matrix:a,u_image:1,u_dimension:[i,i],u_zoom:e.overscaledZ,u_maxzoom:n,u_unpack:r.getUnpackVector()}};var Ur=function(e,r,n){var i=e.transform;return{u_matrix:Zr(e,r,n),u_ratio:1/ge(r,1,i.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_units_to_pixels:[1/i.pixelsToGLUnits[0],1/i.pixelsToGLUnits[1]]}},Vr=function(e,r,n){return t.extend(Ur(e,r,n),{u_image:0})},Hr=function(e,r,n,i){var a=e.transform,o=Gr(r,a);return{u_matrix:Zr(e,r,n),u_texsize:r.imageAtlasTexture.size,u_ratio:1/ge(r,1,a.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_image:0,u_scale:[o,i.fromScale,i.toScale],u_fade:i.t,u_units_to_pixels:[1/a.pixelsToGLUnits[0],1/a.pixelsToGLUnits[1]]}},qr=function(e,r,n,i,a){var o=e.transform,s=e.lineAtlas,l=Gr(r,o),u="round"===n.layout.get("line-cap"),c=s.getDash(i.from,u),f=s.getDash(i.to,u),h=c.width*a.fromScale,p=f.width*a.toScale;return t.extend(Ur(e,r,n),{u_patternscale_a:[l/h,-c.height/2],u_patternscale_b:[l/p,-f.height/2],u_sdfgamma:s.width/(256*Math.min(h,p)*t.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:c.y,u_tex_y_b:f.y,u_mix:a.t})};function Gr(t,e){return 1/ge(t,1,e.tileZoom)}function Zr(t,e,r){return t.translatePosMatrix(e.tileID.posMatrix,e,r.paint.get("line-translate"),r.paint.get("line-translate-anchor"))}var Yr=function(t,e,r,n,i){return{u_matrix:t,u_tl_parent:e,u_scale_parent:r,u_buffer_scale:1,u_fade_t:n.mix,u_opacity:n.opacity*i.paint.get("raster-opacity"),u_image0:0,u_image1:1,u_brightness_low:i.paint.get("raster-brightness-min"),u_brightness_high:i.paint.get("raster-brightness-max"),u_saturation_factor:(o=i.paint.get("raster-saturation"),o>0?1-1/(1.001-o):-o),u_contrast_factor:(a=i.paint.get("raster-contrast"),a>0?1/(1-a):1+a),u_spin_weights:Wr(i.paint.get("raster-hue-rotate"))};var a,o};function Wr(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}var Xr,Jr=function(t,e,r,n,i,a,o,s,l,u){var c=i.transform;return{u_is_size_zoom_constant:+("constant"===t||"source"===t),u_is_size_feature_constant:+("constant"===t||"camera"===t),u_size_t:e?e.uSizeT:0,u_size:e?e.uSize:0,u_camera_to_center_distance:c.cameraToCenterDistance,u_pitch:c.pitch/360*2*Math.PI,u_rotate_symbol:+r,u_aspect_ratio:c.width/c.height,u_fade_change:i.options.fadeDuration?i.symbolFadeChange:1,u_matrix:a,u_label_plane_matrix:o,u_coord_matrix:s,u_is_text:+l,u_pitch_with_map:+n,u_texsize:u,u_texture:0}},Kr=function(e,r,n,i,a,o,s,l,u,c,f){var h=a.transform;return t.extend(Jr(e,r,n,i,a,o,s,l,u,c),{u_gamma_scale:i?Math.cos(h._pitch)*h.cameraToCenterDistance:1,u_device_pixel_ratio:t.browser.devicePixelRatio,u_is_halo:+f})},$r=function(e,r,n,i,a,o,s,l,u,c){return t.extend(Kr(e,r,n,i,a,o,s,l,!0,u,!0),{u_texsize_icon:c,u_texture_icon:1})},Qr=function(t,e,r){return{u_matrix:t,u_opacity:e,u_color:r}},tn=function(e,r,n,i,a,o){return t.extend(function(t,e,r,n){var i=r.imageManager.getPattern(t.from.toString()),a=r.imageManager.getPattern(t.to.toString()),o=r.imageManager.getPixelSize(),s=o.width,l=o.height,u=Math.pow(2,n.tileID.overscaledZ),c=n.tileSize*Math.pow(2,r.transform.tileZoom)/u,f=c*(n.tileID.canonical.x+n.tileID.wrap*u),h=c*n.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:i.tl,u_pattern_br_a:i.br,u_pattern_tl_b:a.tl,u_pattern_br_b:a.br,u_texsize:[s,l],u_mix:e.t,u_pattern_size_a:i.displaySize,u_pattern_size_b:a.displaySize,u_scale_a:e.fromScale,u_scale_b:e.toScale,u_tile_units_to_pixels:1/ge(n,1,r.transform.tileZoom),u_pixel_coord_upper:[f>>16,h>>16],u_pixel_coord_lower:[65535&f,65535&h]}}(i,o,n,a),{u_matrix:e,u_opacity:r})},en={fillExtrusion:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fillExtrusionPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_height_factor:new t.Uniform1f(e,r.u_height_factor),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fill:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},fillPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},fillOutline:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world)}},fillOutlinePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},circle:function(e,r){return{u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_scale_with_map:new t.Uniform1i(e,r.u_scale_with_map),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},collisionBox:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pixels_to_tile_units:new t.Uniform1f(e,r.u_pixels_to_tile_units),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_overscale_factor:new t.Uniform1f(e,r.u_overscale_factor)}},collisionCircle:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_inv_matrix:new t.UniformMatrix4f(e,r.u_inv_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_viewport_size:new t.Uniform2f(e,r.u_viewport_size)}},debug:function(e,r){return{u_color:new t.UniformColor(e,r.u_color),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_overlay:new t.Uniform1i(e,r.u_overlay),u_overlay_scale:new t.Uniform1f(e,r.u_overlay_scale)}},clippingMask:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmap:function(e,r){return{u_extrude_scale:new t.Uniform1f(e,r.u_extrude_scale),u_intensity:new t.Uniform1f(e,r.u_intensity),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmapTexture:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_color_ramp:new t.Uniform1i(e,r.u_color_ramp),u_opacity:new t.Uniform1f(e,r.u_opacity)}},hillshade:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_latrange:new t.Uniform2f(e,r.u_latrange),u_light:new t.Uniform2f(e,r.u_light),u_shadow:new t.UniformColor(e,r.u_shadow),u_highlight:new t.UniformColor(e,r.u_highlight),u_accent:new t.UniformColor(e,r.u_accent)}},hillshadePrepare:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_dimension:new t.Uniform2f(e,r.u_dimension),u_zoom:new t.Uniform1f(e,r.u_zoom),u_maxzoom:new t.Uniform1f(e,r.u_maxzoom),u_unpack:new t.Uniform4f(e,r.u_unpack)}},line:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels)}},lineGradient:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_image:new t.Uniform1i(e,r.u_image)}},linePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_texsize:new t.Uniform2f(e,r.u_texsize),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_image:new t.Uniform1i(e,r.u_image),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},lineSDF:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_patternscale_a:new t.Uniform2f(e,r.u_patternscale_a),u_patternscale_b:new t.Uniform2f(e,r.u_patternscale_b),u_sdfgamma:new t.Uniform1f(e,r.u_sdfgamma),u_image:new t.Uniform1i(e,r.u_image),u_tex_y_a:new t.Uniform1f(e,r.u_tex_y_a),u_tex_y_b:new t.Uniform1f(e,r.u_tex_y_b),u_mix:new t.Uniform1f(e,r.u_mix)}},raster:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_tl_parent:new t.Uniform2f(e,r.u_tl_parent),u_scale_parent:new t.Uniform1f(e,r.u_scale_parent),u_buffer_scale:new t.Uniform1f(e,r.u_buffer_scale),u_fade_t:new t.Uniform1f(e,r.u_fade_t),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image0:new t.Uniform1i(e,r.u_image0),u_image1:new t.Uniform1i(e,r.u_image1),u_brightness_low:new t.Uniform1f(e,r.u_brightness_low),u_brightness_high:new t.Uniform1f(e,r.u_brightness_high),u_saturation_factor:new t.Uniform1f(e,r.u_saturation_factor),u_contrast_factor:new t.Uniform1f(e,r.u_contrast_factor),u_spin_weights:new t.Uniform3f(e,r.u_spin_weights)}},symbolIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture)}},symbolSDF:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},symbolTextAndIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texsize_icon:new t.Uniform2f(e,r.u_texsize_icon),u_texture:new t.Uniform1i(e,r.u_texture),u_texture_icon:new t.Uniform1i(e,r.u_texture_icon),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},background:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_color:new t.UniformColor(e,r.u_color)}},backgroundPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image:new t.Uniform1i(e,r.u_image),u_pattern_tl_a:new t.Uniform2f(e,r.u_pattern_tl_a),u_pattern_br_a:new t.Uniform2f(e,r.u_pattern_br_a),u_pattern_tl_b:new t.Uniform2f(e,r.u_pattern_tl_b),u_pattern_br_b:new t.Uniform2f(e,r.u_pattern_br_b),u_texsize:new t.Uniform2f(e,r.u_texsize),u_mix:new t.Uniform1f(e,r.u_mix),u_pattern_size_a:new t.Uniform2f(e,r.u_pattern_size_a),u_pattern_size_b:new t.Uniform2f(e,r.u_pattern_size_b),u_scale_a:new t.Uniform1f(e,r.u_scale_a),u_scale_b:new t.Uniform1f(e,r.u_scale_b),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_tile_units_to_pixels:new t.Uniform1f(e,r.u_tile_units_to_pixels)}}};function rn(e,r,n,i,a,o,s){for(var l=e.context,u=l.gl,c=e.useProgram("collisionBox"),f=[],h=0,p=0,d=0;d<i.length;d++){var v=i[d],g=r.getTile(v),y=g.getBucket(n);if(y){var m=v.posMatrix;0===a[0]&&0===a[1]||(m=e.translatePosMatrix(v.posMatrix,g,a,o));var x=s?y.textCollisionBox:y.iconCollisionBox,b=y.collisionCircleArray;if(b.length>0){var _=t.create(),w=m;t.mul(_,y.placementInvProjMatrix,e.transform.glCoordMatrix),t.mul(_,_,y.placementViewportMatrix),f.push({circleArray:b,circleOffset:p,transform:w,invTransform:_}),p=h+=b.length/4}x&&c.draw(l,u.LINES,Mt.disabled,Et.disabled,e.colorModeForRenderPass(),Ct.disabled,Ir(m,e.transform,g),n.id,x.layoutVertexBuffer,x.indexBuffer,x.segments,null,e.transform.zoom,null,null,x.collisionVertexBuffer)}}if(s&&f.length){var T=e.useProgram("collisionCircle"),k=new t.StructArrayLayout2f1f2i16;k.resize(4*h),k._trim();for(var A=0,M=0,S=f;M<S.length;M+=1)for(var E=S[M],L=0;L<E.circleArray.length/4;L++){var C=4*L,P=E.circleArray[C+0],O=E.circleArray[C+1],I=E.circleArray[C+2],D=E.circleArray[C+3];k.emplace(A++,P,O,I,D,0),k.emplace(A++,P,O,I,D,1),k.emplace(A++,P,O,I,D,2),k.emplace(A++,P,O,I,D,3)}(!Xr||Xr.length<2*h)&&(Xr=function(e){var r=2*e,n=new t.StructArrayLayout3ui6;n.resize(r),n._trim();for(var i=0;i<r;i++){var a=6*i;n.uint16[a+0]=4*i+0,n.uint16[a+1]=4*i+1,n.uint16[a+2]=4*i+2,n.uint16[a+3]=4*i+2,n.uint16[a+4]=4*i+3,n.uint16[a+5]=4*i+0}return n}(h));for(var z=l.createIndexBuffer(Xr,!0),R=l.createVertexBuffer(k,t.collisionCircleLayout.members,!0),F=0,B=f;F<B.length;F+=1){var N=B[F],j=Dr(N.transform,N.invTransform,e.transform);T.draw(l,u.TRIANGLES,Mt.disabled,Et.disabled,e.colorModeForRenderPass(),Ct.disabled,j,n.id,R,z,t.SegmentVector.simpleSegment(0,2*N.circleOffset,N.circleArray.length,N.circleArray.length/2),null,e.transform.zoom,null,null,null)}R.destroy(),z.destroy()}}var nn=t.identity(new Float32Array(16));function an(e,r,n,i,a,o){var s=t.getAnchorAlignment(e),l=-(s.horizontalAlign-.5)*r,u=-(s.verticalAlign-.5)*n,c=t.evaluateVariableOffset(e,i);return new t.Point((l/a+c[0])*o,(u/a+c[1])*o)}function on(e,r,n,i,a,o,s,l,u,c,f){var h=e.text.placedSymbolArray,p=e.text.dynamicLayoutVertexArray,d=e.icon.dynamicLayoutVertexArray,v={};p.clear();for(var g=0;g<h.length;g++){var y=h.get(g),m=e.allowVerticalPlacement&&!y.placedOrientation,x=y.hidden||!y.crossTileID||m?null:i[y.crossTileID];if(x){var b=new t.Point(y.anchorX,y.anchorY),_=re(b,n?l:s),w=ne(o.cameraToCenterDistance,_.signedDistanceFromCamera),T=a.evaluateSizeForFeature(e.textSizeData,c,y)*w/t.ONE_EM;n&&(T*=e.tilePixelRatio/u);for(var k=x.width,A=x.height,M=an(x.anchor,k,A,x.textOffset,x.textBoxScale,T),S=n?re(b.add(M),s).point:_.point.add(r?M.rotate(-o.angle):M),E=e.allowVerticalPlacement&&y.placedOrientation===t.WritingMode.vertical?Math.PI/2:0,L=0;L<y.numGlyphs;L++)t.addDynamicAttributes(p,S,E);f&&y.associatedIconIndex>=0&&(v[y.associatedIconIndex]={shiftedAnchor:S,angle:E})}else he(y.numGlyphs,p)}if(f){d.clear();for(var C=e.icon.placedSymbolArray,P=0;P<C.length;P++){var O=C.get(P);if(O.hidden)he(O.numGlyphs,d);else{var I=v[P];if(I)for(var D=0;D<O.numGlyphs;D++)t.addDynamicAttributes(d,I.shiftedAnchor,I.angle);else he(O.numGlyphs,d)}}e.icon.dynamicLayoutVertexBuffer.updateData(d)}e.text.dynamicLayoutVertexBuffer.updateData(p)}function sn(t,e,r){return r.iconsInText&&e?"symbolTextAndIcon":t?"symbolSDF":"symbolIcon"}function ln(e,r,n,i,a,o,s,l,u,c,f,h){for(var p=e.context,d=p.gl,v=e.transform,g="map"===l,y="map"===u,m=g&&"point"!==n.layout.get("symbol-placement"),x=g&&!y&&!m,b=void 0!==n.layout.get("symbol-sort-key").constantOr(1),_=e.depthModeForSublayer(0,Mt.ReadOnly),w=n.layout.get("text-variable-anchor"),T=[],k=0,A=i;k<A.length;k+=1){var M=A[k],S=r.getTile(M),E=S.getBucket(n);if(E){var L=a?E.text:E.icon;if(L&&L.segments.get().length){var C=L.programConfigurations.get(n.id),P=a||E.sdfIcons,O=a?E.textSizeData:E.iconSizeData,I=y||0!==v.pitch,D=e.useProgram(sn(P,a,E),C),z=t.evaluateSizeForZoom(O,v.zoom),R=void 0,F=[0,0],B=void 0,N=void 0,j=null,U=void 0;if(a){if(B=S.glyphAtlasTexture,N=d.LINEAR,R=S.glyphAtlasTexture.size,E.iconsInText){F=S.imageAtlasTexture.size,j=S.imageAtlasTexture;var V="composite"===O.kind||"camera"===O.kind;U=I||e.options.rotating||e.options.zooming||V?d.LINEAR:d.NEAREST}}else{var H=1!==n.layout.get("icon-size").constantOr(0)||E.iconsNeedLinear;B=S.imageAtlasTexture,N=P||e.options.rotating||e.options.zooming||H||I?d.LINEAR:d.NEAREST,R=S.imageAtlasTexture.size}var q=ge(S,1,e.transform.zoom),G=te(M.posMatrix,y,g,e.transform,q),Z=ee(M.posMatrix,y,g,e.transform,q),Y=w&&E.hasTextData(),W="none"!==n.layout.get("icon-text-fit")&&Y&&E.hasIconData();m&&ae(E,M.posMatrix,e,a,G,Z,y,c);var X=e.translatePosMatrix(M.posMatrix,S,o,s),J=m||a&&w||W?nn:G,K=e.translatePosMatrix(Z,S,o,s,!0),$=P&&0!==n.paint.get(a?"text-halo-width":"icon-halo-width").constantOr(1),Q={program:D,buffers:L,uniformValues:P?E.iconsInText?$r(O.kind,z,x,y,e,X,J,K,R,F):Kr(O.kind,z,x,y,e,X,J,K,a,R,!0):Jr(O.kind,z,x,y,e,X,J,K,a,R),atlasTexture:B,atlasTextureIcon:j,atlasInterpolation:N,atlasInterpolationIcon:U,isSDF:P,hasHalo:$};if(b)for(var tt=0,et=L.segments.get();tt<et.length;tt+=1){var rt=et[tt];T.push({segments:new t.SegmentVector([rt]),sortKey:rt.sortKey,state:Q})}else T.push({segments:L.segments,sortKey:0,state:Q})}}}b&&T.sort((function(t,e){return t.sortKey-e.sortKey}));for(var nt=0,it=T;nt<it.length;nt+=1){var at=it[nt],ot=at.state;if(p.activeTexture.set(d.TEXTURE0),ot.atlasTexture.bind(ot.atlasInterpolation,d.CLAMP_TO_EDGE),ot.atlasTextureIcon&&(p.activeTexture.set(d.TEXTURE1),ot.atlasTextureIcon&&ot.atlasTextureIcon.bind(ot.atlasInterpolationIcon,d.CLAMP_TO_EDGE)),ot.isSDF){var st=ot.uniformValues;ot.hasHalo&&(st.u_is_halo=1,un(ot.buffers,at.segments,n,e,ot.program,_,f,h,st)),st.u_is_halo=0}un(ot.buffers,at.segments,n,e,ot.program,_,f,h,ot.uniformValues)}}function un(t,e,r,n,i,a,o,s,l){var u=n.context,c=u.gl;i.draw(u,c.TRIANGLES,a,o,s,Ct.disabled,l,r.id,t.layoutVertexBuffer,t.indexBuffer,e,r.paint,n.transform.zoom,t.programConfigurations.get(r.id),t.dynamicLayoutVertexBuffer,t.opacityVertexBuffer)}function cn(t,e,r,n,i,a,o){var s,l,u,c,f,h=t.context.gl,p=r.paint.get("fill-pattern"),d=p&&p.constantOr(1),v=r.getCrossfadeParameters();o?(l=d&&!r.getPaintProperty("fill-outline-color")?"fillOutlinePattern":"fillOutline",s=h.LINES):(l=d?"fillPattern":"fill",s=h.TRIANGLES);for(var g=0,y=n;g<y.length;g+=1){var m=y[g],x=e.getTile(m);if(!d||x.patternsLoaded()){var b=x.getBucket(r);if(b){var _=b.programConfigurations.get(r.id),w=t.useProgram(l,_);d&&(t.context.activeTexture.set(h.TEXTURE0),x.imageAtlasTexture.bind(h.LINEAR,h.CLAMP_TO_EDGE),_.updatePaintBuffers(v));var T=p.constantOr(null);if(T&&x.imageAtlas){var k=x.imageAtlas,A=k.patternPositions[T.to.toString()],M=k.patternPositions[T.from.toString()];A&&M&&_.setConstantPatternPositions(A,M)}var S=t.translatePosMatrix(m.posMatrix,x,r.paint.get("fill-translate"),r.paint.get("fill-translate-anchor"));if(o){c=b.indexBuffer2,f=b.segments2;var E=[h.drawingBufferWidth,h.drawingBufferHeight];u="fillOutlinePattern"===l&&d?Pr(S,t,v,x,E):Cr(S,E)}else c=b.indexBuffer,f=b.segments,u=d?Lr(S,t,v,x):Er(S);w.draw(t.context,s,i,t.stencilModeForClipping(m),a,Ct.disabled,u,r.id,b.layoutVertexBuffer,c,f,r.paint,t.transform.zoom,_)}}}}function fn(t,e,r,n,i,a,o){for(var s=t.context,l=s.gl,u=r.paint.get("fill-extrusion-pattern"),c=u.constantOr(1),f=r.getCrossfadeParameters(),h=r.paint.get("fill-extrusion-opacity"),p=0,d=n;p<d.length;p+=1){var v=d[p],g=e.getTile(v),y=g.getBucket(r);if(y){var m=y.programConfigurations.get(r.id),x=t.useProgram(c?"fillExtrusionPattern":"fillExtrusion",m);c&&(t.context.activeTexture.set(l.TEXTURE0),g.imageAtlasTexture.bind(l.LINEAR,l.CLAMP_TO_EDGE),m.updatePaintBuffers(f));var b=u.constantOr(null);if(b&&g.imageAtlas){var _=g.imageAtlas,w=_.patternPositions[b.to.toString()],T=_.patternPositions[b.from.toString()];w&&T&&m.setConstantPatternPositions(w,T)}var k=t.translatePosMatrix(v.posMatrix,g,r.paint.get("fill-extrusion-translate"),r.paint.get("fill-extrusion-translate-anchor")),A=r.paint.get("fill-extrusion-vertical-gradient"),M=c?Sr(k,t,A,h,v,f,g):Mr(k,t,A,h);x.draw(s,s.gl.TRIANGLES,i,a,o,Ct.backCCW,M,r.id,y.layoutVertexBuffer,y.indexBuffer,y.segments,r.paint,t.transform.zoom,m)}}}function hn(t,e,r,n,i,a){var o=t.context,s=o.gl,l=e.fbo;if(l){var u=t.useProgram("hillshade");o.activeTexture.set(s.TEXTURE0),s.bindTexture(s.TEXTURE_2D,l.colorAttachment.get());var c=Nr(t,e,r);u.draw(o,s.TRIANGLES,n,i,a,Ct.disabled,c,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}}function pn(e,r,n,i,a,o,s){var l=e.context,u=l.gl,c=r.dem;if(c&&c.data){var f=c.dim,h=c.stride,p=c.getPixels();if(l.activeTexture.set(u.TEXTURE1),l.pixelStoreUnpackPremultiplyAlpha.set(!1),r.demTexture=r.demTexture||e.getTileTexture(h),r.demTexture){var d=r.demTexture;d.update(p,{premultiply:!1}),d.bind(u.NEAREST,u.CLAMP_TO_EDGE)}else r.demTexture=new t.Texture(l,p,u.RGBA,{premultiply:!1}),r.demTexture.bind(u.NEAREST,u.CLAMP_TO_EDGE);l.activeTexture.set(u.TEXTURE0);var v=r.fbo;if(!v){var g=new t.Texture(l,{width:f,height:f,data:null},u.RGBA);g.bind(u.LINEAR,u.CLAMP_TO_EDGE),(v=r.fbo=l.createFramebuffer(f,f,!0)).colorAttachment.set(g.texture)}l.bindFramebuffer.set(v.framebuffer),l.viewport.set([0,0,f,f]),e.useProgram("hillshadePrepare").draw(l,u.TRIANGLES,a,o,s,Ct.disabled,jr(r.tileID,c,i),n.id,e.rasterBoundsBuffer,e.quadTriangleIndexBuffer,e.rasterBoundsSegments),r.needsHillshadePrepare=!1}}function dn(e,r,n,i,a){var o=i.paint.get("raster-fade-duration");if(o>0){var s=t.browser.now(),l=(s-e.timeAdded)/o,u=r?(s-r.timeAdded)/o:-1,c=n.getSource(),f=a.coveringZoomLevel({tileSize:c.tileSize,roundZoom:c.roundZoom}),h=!r||Math.abs(r.tileID.overscaledZ-f)>Math.abs(e.tileID.overscaledZ-f),p=h&&e.refreshedUponExpiration?1:t.clamp(h?l:1-u,0,1);return e.refreshedUponExpiration&&l>=1&&(e.refreshedUponExpiration=!1),r?{opacity:1,mix:1-p}:{opacity:p,mix:0}}return{opacity:1,mix:0}}var vn=new t.Color(1,0,0,1),gn=new t.Color(0,1,0,1),yn=new t.Color(0,0,1,1),mn=new t.Color(1,0,1,1),xn=new t.Color(0,1,1,1);function bn(t){var e=t.transform.padding;_n(t,t.transform.height-(e.top||0),3,vn),_n(t,e.bottom||0,3,gn),wn(t,e.left||0,3,yn),wn(t,t.transform.width-(e.right||0),3,mn);var r=t.transform.centerPoint;!function(t,e,r,n){var i=20,a=2;Tn(t,e-a/2,r-i/2,a,i,n),Tn(t,e-i/2,r-a/2,i,a,n)}(t,r.x,t.transform.height-r.y,xn)}function _n(t,e,r,n){Tn(t,0,e+r/2,t.transform.width,r,n)}function wn(t,e,r,n){Tn(t,e-r/2,0,r,t.transform.height,n)}function Tn(e,r,n,i,a,o){var s=e.context,l=s.gl;l.enable(l.SCISSOR_TEST),l.scissor(r*t.browser.devicePixelRatio,n*t.browser.devicePixelRatio,i*t.browser.devicePixelRatio,a*t.browser.devicePixelRatio),s.clear({color:o}),l.disable(l.SCISSOR_TEST)}function kn(e,r,n){var i=e.context,a=i.gl,o=n.posMatrix,s=e.useProgram("debug"),l=Mt.disabled,u=Et.disabled,c=e.colorModeForRenderPass(),f="$debug";i.activeTexture.set(a.TEXTURE0),e.emptyTexture.bind(a.LINEAR,a.CLAMP_TO_EDGE),s.draw(i,a.LINE_STRIP,l,u,c,Ct.disabled,zr(o,t.Color.red),f,e.debugBuffer,e.tileBorderIndexBuffer,e.debugSegments);var h=r.getTileByID(n.key).latestRawTileData,p=h&&h.byteLength||0,d=Math.floor(p/1024),v=r.getTile(n).tileSize,g=512/Math.min(v,512)*(n.overscaledZ/e.transform.zoom)*.5,y=n.canonical.toString();n.overscaledZ!==n.canonical.z&&(y+=" => "+n.overscaledZ),function(t,e){t.initDebugOverlayCanvas();var r=t.debugOverlayCanvas,n=t.context.gl,i=t.debugOverlayCanvas.getContext("2d");i.clearRect(0,0,r.width,r.height),i.shadowColor="white",i.shadowBlur=2,i.lineWidth=1.5,i.strokeStyle="white",i.textBaseline="top",i.font="bold 36px Open Sans, sans-serif",i.fillText(e,5,5),i.strokeText(e,5,5),t.debugOverlayTexture.update(r),t.debugOverlayTexture.bind(n.LINEAR,n.CLAMP_TO_EDGE)}(e,y+" "+d+"kb"),s.draw(i,a.TRIANGLES,l,u,Lt.alphaBlended,Ct.disabled,zr(o,t.Color.transparent,g),f,e.debugBuffer,e.quadTriangleIndexBuffer,e.debugSegments)}var An={symbol:function(e,r,n,i,a){if("translucent"===e.renderPass){var o=Et.disabled,s=e.colorModeForRenderPass();n.layout.get("text-variable-anchor")&&function(e,r,n,i,a,o,s){for(var l=r.transform,u="map"===a,c="map"===o,f=0,h=e;f<h.length;f+=1){var p=h[f],d=i.getTile(p),v=d.getBucket(n);if(v&&v.text&&v.text.segments.get().length){var g=v.textSizeData,y=t.evaluateSizeForZoom(g,l.zoom),m=ge(d,1,r.transform.zoom),x=te(p.posMatrix,c,u,r.transform,m),b="none"!==n.layout.get("icon-text-fit")&&v.hasIconData();if(y){var _=Math.pow(2,l.zoom-d.tileID.overscaledZ);on(v,u,c,s,t.symbolSize,l,x,p.posMatrix,_,y,b)}}}}(i,e,n,r,n.layout.get("text-rotation-alignment"),n.layout.get("text-pitch-alignment"),a),0!==n.paint.get("icon-opacity").constantOr(1)&&ln(e,r,n,i,!1,n.paint.get("icon-translate"),n.paint.get("icon-translate-anchor"),n.layout.get("icon-rotation-alignment"),n.layout.get("icon-pitch-alignment"),n.layout.get("icon-keep-upright"),o,s),0!==n.paint.get("text-opacity").constantOr(1)&&ln(e,r,n,i,!0,n.paint.get("text-translate"),n.paint.get("text-translate-anchor"),n.layout.get("text-rotation-alignment"),n.layout.get("text-pitch-alignment"),n.layout.get("text-keep-upright"),o,s),r.map.showCollisionBoxes&&(rn(e,r,n,i,n.paint.get("text-translate"),n.paint.get("text-translate-anchor"),!0),rn(e,r,n,i,n.paint.get("icon-translate"),n.paint.get("icon-translate-anchor"),!1))}},circle:function(e,r,n,i){if("translucent"===e.renderPass){var a=n.paint.get("circle-opacity"),o=n.paint.get("circle-stroke-width"),s=n.paint.get("circle-stroke-opacity"),l=void 0!==n.layout.get("circle-sort-key").constantOr(1);if(0!==a.constantOr(1)||0!==o.constantOr(1)&&0!==s.constantOr(1)){for(var u=e.context,c=u.gl,f=e.depthModeForSublayer(0,Mt.ReadOnly),h=Et.disabled,p=e.colorModeForRenderPass(),d=[],v=0;v<i.length;v++){var g=i[v],y=r.getTile(g),m=y.getBucket(n);if(m){var x=m.programConfigurations.get(n.id),b={programConfiguration:x,program:e.useProgram("circle",x),layoutVertexBuffer:m.layoutVertexBuffer,indexBuffer:m.indexBuffer,uniformValues:Or(e,g,y,n)};if(l)for(var _=0,w=m.segments.get();_<w.length;_+=1){var T=w[_];d.push({segments:new t.SegmentVector([T]),sortKey:T.sortKey,state:b})}else d.push({segments:m.segments,sortKey:0,state:b})}}l&&d.sort((function(t,e){return t.sortKey-e.sortKey}));for(var k=0,A=d;k<A.length;k+=1){var M=A[k],S=M.state,E=S.programConfiguration,L=S.program,C=S.layoutVertexBuffer,P=S.indexBuffer,O=S.uniformValues,I=M.segments;L.draw(u,c.TRIANGLES,f,h,p,Ct.disabled,O,n.id,C,P,I,n.paint,e.transform.zoom,E)}}}},heatmap:function(e,r,n,i){if(0!==n.paint.get("heatmap-opacity"))if("offscreen"===e.renderPass){var a=e.context,o=a.gl,s=Et.disabled,l=new Lt([o.ONE,o.ONE],t.Color.transparent,[!0,!0,!0,!0]);(function(t,e,r){var n=t.gl;t.activeTexture.set(n.TEXTURE1),t.viewport.set([0,0,e.width/4,e.height/4]);var i=r.heatmapFbo;if(i)n.bindTexture(n.TEXTURE_2D,i.colorAttachment.get()),t.bindFramebuffer.set(i.framebuffer);else{var a=n.createTexture();n.bindTexture(n.TEXTURE_2D,a),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,n.LINEAR),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,n.LINEAR),i=r.heatmapFbo=t.createFramebuffer(e.width/4,e.height/4,!1),function(t,e,r,n){var i=t.gl,a=t.extRenderToTextureHalfFloat?t.extTextureHalfFloat.HALF_FLOAT_OES:i.UNSIGNED_BYTE;i.texImage2D(i.TEXTURE_2D,0,i.RGBA,e.width/4,e.height/4,0,i.RGBA,a,null),n.colorAttachment.set(r)}(t,e,a,i)}})(a,e,n),a.clear({color:t.Color.transparent});for(var u=0;u<i.length;u++){var c=i[u];if(!r.hasRenderableParent(c)){var f=r.getTile(c),h=f.getBucket(n);if(h){var p=h.programConfigurations.get(n.id),d=e.useProgram("heatmap",p),v=e.transform.zoom;d.draw(a,o.TRIANGLES,Mt.disabled,s,l,Ct.disabled,Fr(c.posMatrix,f,v,n.paint.get("heatmap-intensity")),n.id,h.layoutVertexBuffer,h.indexBuffer,h.segments,n.paint,e.transform.zoom,p)}}}a.viewport.set([0,0,e.width,e.height])}else"translucent"===e.renderPass&&(e.context.setColorMode(e.colorModeForRenderPass()),function(e,r){var n=e.context,i=n.gl,a=r.heatmapFbo;if(a){n.activeTexture.set(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,a.colorAttachment.get()),n.activeTexture.set(i.TEXTURE1);var o=r.colorRampTexture;o||(o=r.colorRampTexture=new t.Texture(n,r.colorRamp,i.RGBA)),o.bind(i.LINEAR,i.CLAMP_TO_EDGE),e.useProgram("heatmapTexture").draw(n,i.TRIANGLES,Mt.disabled,Et.disabled,e.colorModeForRenderPass(),Ct.disabled,Br(e,r,0,1),r.id,e.viewportBuffer,e.quadTriangleIndexBuffer,e.viewportSegments,r.paint,e.transform.zoom)}}(e,n))},line:function(e,r,n,i){if("translucent"===e.renderPass){var a=n.paint.get("line-opacity"),o=n.paint.get("line-width");if(0!==a.constantOr(1)&&0!==o.constantOr(1)){var s=e.depthModeForSublayer(0,Mt.ReadOnly),l=e.colorModeForRenderPass(),u=n.paint.get("line-dasharray"),c=n.paint.get("line-pattern"),f=c.constantOr(1),h=n.paint.get("line-gradient"),p=n.getCrossfadeParameters(),d=f?"linePattern":u?"lineSDF":h?"lineGradient":"line",v=e.context,g=v.gl,y=!0;if(h){v.activeTexture.set(g.TEXTURE0);var m=n.gradientTexture;if(!n.gradient)return;m||(m=n.gradientTexture=new t.Texture(v,n.gradient,g.RGBA)),m.bind(g.LINEAR,g.CLAMP_TO_EDGE)}for(var x=0,b=i;x<b.length;x+=1){var _=b[x],w=r.getTile(_);if(!f||w.patternsLoaded()){var T=w.getBucket(n);if(T){var k=T.programConfigurations.get(n.id),A=e.context.program.get(),M=e.useProgram(d,k),S=y||M.program!==A,E=c.constantOr(null);if(E&&w.imageAtlas){var L=w.imageAtlas,C=L.patternPositions[E.to.toString()],P=L.patternPositions[E.from.toString()];C&&P&&k.setConstantPatternPositions(C,P)}var O=f?Hr(e,w,n,p):u?qr(e,w,n,u,p):h?Vr(e,w,n):Ur(e,w,n);f?(v.activeTexture.set(g.TEXTURE0),w.imageAtlasTexture.bind(g.LINEAR,g.CLAMP_TO_EDGE),k.updatePaintBuffers(p)):u&&(S||e.lineAtlas.dirty)&&(v.activeTexture.set(g.TEXTURE0),e.lineAtlas.bind(v)),M.draw(v,g.TRIANGLES,s,e.stencilModeForClipping(_),l,Ct.disabled,O,n.id,T.layoutVertexBuffer,T.indexBuffer,T.segments,n.paint,e.transform.zoom,k),y=!1}}}}}},fill:function(e,r,n,i){var a=n.paint.get("fill-color"),o=n.paint.get("fill-opacity");if(0!==o.constantOr(1)){var s=e.colorModeForRenderPass(),l=n.paint.get("fill-pattern"),u=e.opaquePassEnabledForLayer()&&!l.constantOr(1)&&1===a.constantOr(t.Color.transparent).a&&1===o.constantOr(0)?"opaque":"translucent";if(e.renderPass===u){var c=e.depthModeForSublayer(1,"opaque"===e.renderPass?Mt.ReadWrite:Mt.ReadOnly);cn(e,r,n,i,c,s,!1)}if("translucent"===e.renderPass&&n.paint.get("fill-antialias")){var f=e.depthModeForSublayer(n.getPaintProperty("fill-outline-color")?2:0,Mt.ReadOnly);cn(e,r,n,i,f,s,!0)}}},"fill-extrusion":function(t,e,r,n){var i=r.paint.get("fill-extrusion-opacity");if(0!==i&&"translucent"===t.renderPass){var a=new Mt(t.context.gl.LEQUAL,Mt.ReadWrite,t.depthRangeFor3D);if(1!==i||r.paint.get("fill-extrusion-pattern").constantOr(1))fn(t,e,r,n,a,Et.disabled,Lt.disabled),fn(t,e,r,n,a,t.stencilModeFor3D(),t.colorModeForRenderPass());else{var o=t.colorModeForRenderPass();fn(t,e,r,n,a,Et.disabled,o)}}},hillshade:function(t,e,r,n){if("offscreen"===t.renderPass||"translucent"===t.renderPass){for(var i=t.context,a=e.getSource().maxzoom,o=t.depthModeForSublayer(0,Mt.ReadOnly),s=t.colorModeForRenderPass(),l="translucent"===t.renderPass?t.stencilConfigForOverlap(n):[{},n],u=l[0],c=0,f=l[1];c<f.length;c+=1){var h=f[c],p=e.getTile(h);p.needsHillshadePrepare&&"offscreen"===t.renderPass?pn(t,p,r,a,o,Et.disabled,s):"translucent"===t.renderPass&&hn(t,p,r,o,u[h.overscaledZ],s)}i.viewport.set([0,0,t.width,t.height])}},raster:function(t,e,r,n){if("translucent"===t.renderPass&&0!==r.paint.get("raster-opacity")&&n.length)for(var i=t.context,a=i.gl,o=e.getSource(),s=t.useProgram("raster"),l=t.colorModeForRenderPass(),u=o instanceof I?[{},n]:t.stencilConfigForOverlap(n),c=u[0],f=u[1],h=f[f.length-1].overscaledZ,p=!t.options.moving,d=0,v=f;d<v.length;d+=1){var g=v[d],y=t.depthModeForSublayer(g.overscaledZ-h,1===r.paint.get("raster-opacity")?Mt.ReadWrite:Mt.ReadOnly,a.LESS),m=e.getTile(g),x=t.transform.calculatePosMatrix(g.toUnwrapped(),p);m.registerFadeDuration(r.paint.get("raster-fade-duration"));var b=e.findLoadedParent(g,0),_=dn(m,b,e,r,t.transform),w=void 0,T=void 0,k="nearest"===r.paint.get("raster-resampling")?a.NEAREST:a.LINEAR;i.activeTexture.set(a.TEXTURE0),m.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),i.activeTexture.set(a.TEXTURE1),b?(b.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),w=Math.pow(2,b.tileID.overscaledZ-m.tileID.overscaledZ),T=[m.tileID.canonical.x*w%1,m.tileID.canonical.y*w%1]):m.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST);var A=Yr(x,T||[0,0],w||1,_,r);o instanceof I?s.draw(i,a.TRIANGLES,y,Et.disabled,l,Ct.disabled,A,r.id,o.boundsBuffer,t.quadTriangleIndexBuffer,o.boundsSegments):s.draw(i,a.TRIANGLES,y,c[g.overscaledZ],l,Ct.disabled,A,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}},background:function(t,e,r){var n=r.paint.get("background-color"),i=r.paint.get("background-opacity");if(0!==i){var a=t.context,o=a.gl,s=t.transform,l=s.tileSize,u=r.paint.get("background-pattern");if(!t.isPatternMissing(u)){var c=!u&&1===n.a&&1===i&&t.opaquePassEnabledForLayer()?"opaque":"translucent";if(t.renderPass===c){var f=Et.disabled,h=t.depthModeForSublayer(0,"opaque"===c?Mt.ReadWrite:Mt.ReadOnly),p=t.colorModeForRenderPass(),d=t.useProgram(u?"backgroundPattern":"background"),v=s.coveringTiles({tileSize:l});u&&(a.activeTexture.set(o.TEXTURE0),t.imageManager.bind(t.context));for(var g=r.getCrossfadeParameters(),y=0,m=v;y<m.length;y+=1){var x=m[y],b=t.transform.calculatePosMatrix(x.toUnwrapped()),_=u?tn(b,i,t,u,{tileID:x,tileSize:l},g):Qr(b,i,n);d.draw(a,o.TRIANGLES,h,f,p,Ct.disabled,_,r.id,t.tileExtentBuffer,t.quadTriangleIndexBuffer,t.tileExtentSegments)}}}}},debug:function(t,e,r){for(var n=0;n<r.length;n++)kn(t,e,r[n])},custom:function(t,e,r){var n=t.context,i=r.implementation;if("offscreen"===t.renderPass){var a=i.prerender;a&&(t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),a.call(i,n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState())}else if("translucent"===t.renderPass){t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),n.setStencilMode(Et.disabled);var o="3d"===i.renderingMode?new Mt(t.context.gl.LEQUAL,Mt.ReadWrite,t.depthRangeFor3D):t.depthModeForSublayer(0,Mt.ReadOnly);n.setDepthMode(o),i.render(n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState(),n.bindFramebuffer.set(null)}}},Mn=function(t,e){this.context=new Pt(t),this.transform=e,this._tileTextures={},this.setup(),this.numSublayers=Ot.maxUnderzooming+Ot.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new Ve,this.gpuTimers={}};Mn.prototype.resize=function(e,r){if(this.width=e*t.browser.devicePixelRatio,this.height=r*t.browser.devicePixelRatio,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(var n=0,i=this.style._order;n<i.length;n+=1){var a=i[n];this.style._layers[a].resize()}},Mn.prototype.setup=function(){var e=this.context,r=new t.StructArrayLayout2i4;r.emplaceBack(0,0),r.emplaceBack(t.EXTENT,0),r.emplaceBack(0,t.EXTENT),r.emplaceBack(t.EXTENT,t.EXTENT),this.tileExtentBuffer=e.createVertexBuffer(r,We.members),this.tileExtentSegments=t.SegmentVector.simpleSegment(0,0,4,2);var n=new t.StructArrayLayout2i4;n.emplaceBack(0,0),n.emplaceBack(t.EXTENT,0),n.emplaceBack(0,t.EXTENT),n.emplaceBack(t.EXTENT,t.EXTENT),this.debugBuffer=e.createVertexBuffer(n,We.members),this.debugSegments=t.SegmentVector.simpleSegment(0,0,4,5);var i=new t.StructArrayLayout4i8;i.emplaceBack(0,0,0,0),i.emplaceBack(t.EXTENT,0,t.EXTENT,0),i.emplaceBack(0,t.EXTENT,0,t.EXTENT),i.emplaceBack(t.EXTENT,t.EXTENT,t.EXTENT,t.EXTENT),this.rasterBoundsBuffer=e.createVertexBuffer(i,O.members),this.rasterBoundsSegments=t.SegmentVector.simpleSegment(0,0,4,2);var a=new t.StructArrayLayout2i4;a.emplaceBack(0,0),a.emplaceBack(1,0),a.emplaceBack(0,1),a.emplaceBack(1,1),this.viewportBuffer=e.createVertexBuffer(a,We.members),this.viewportSegments=t.SegmentVector.simpleSegment(0,0,4,2);var o=new t.StructArrayLayout1ui2;o.emplaceBack(0),o.emplaceBack(1),o.emplaceBack(3),o.emplaceBack(2),o.emplaceBack(0),this.tileBorderIndexBuffer=e.createIndexBuffer(o);var s=new t.StructArrayLayout3ui6;s.emplaceBack(0,1,2),s.emplaceBack(2,1,3),this.quadTriangleIndexBuffer=e.createIndexBuffer(s),this.emptyTexture=new t.Texture(e,{width:1,height:1,data:new Uint8Array([0,0,0,0])},e.gl.RGBA);var l=this.context.gl;this.stencilClearMode=new Et({func:l.ALWAYS,mask:0},0,255,l.ZERO,l.ZERO,l.ZERO)},Mn.prototype.clearStencil=function(){var e=this.context,r=e.gl;this.nextStencilID=1,this.currentStencilSource=void 0;var n=t.create();t.ortho(n,0,this.width,this.height,0,0,1),t.scale(n,n,[r.drawingBufferWidth,r.drawingBufferHeight,0]),this.useProgram("clippingMask").draw(e,r.TRIANGLES,Mt.disabled,this.stencilClearMode,Lt.disabled,Ct.disabled,Rr(n),"$clipping",this.viewportBuffer,this.quadTriangleIndexBuffer,this.viewportSegments)},Mn.prototype._renderTileClippingMasks=function(t,e){if(this.currentStencilSource!==t.source&&t.isTileClipped()&&e&&e.length){this.currentStencilSource=t.source;var r=this.context,n=r.gl;this.nextStencilID+e.length>256&&this.clearStencil(),r.setColorMode(Lt.disabled),r.setDepthMode(Mt.disabled);var i=this.useProgram("clippingMask");this._tileClippingMaskIDs={};for(var a=0,o=e;a<o.length;a+=1){var s=o[a],l=this._tileClippingMaskIDs[s.key]=this.nextStencilID++;i.draw(r,n.TRIANGLES,Mt.disabled,new Et({func:n.ALWAYS,mask:0},l,255,n.KEEP,n.KEEP,n.REPLACE),Lt.disabled,Ct.disabled,Rr(s.posMatrix),"$clipping",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}},Mn.prototype.stencilModeFor3D=function(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();var t=this.nextStencilID++,e=this.context.gl;return new Et({func:e.NOTEQUAL,mask:255},t,255,e.KEEP,e.KEEP,e.REPLACE)},Mn.prototype.stencilModeForClipping=function(t){var e=this.context.gl;return new Et({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)},Mn.prototype.stencilConfigForOverlap=function(t){var e,r=this.context.gl,n=t.sort((function(t,e){return e.overscaledZ-t.overscaledZ})),i=n[n.length-1].overscaledZ,a=n[0].overscaledZ-i+1;if(a>1){this.currentStencilSource=void 0,this.nextStencilID+a>256&&this.clearStencil();for(var o={},s=0;s<a;s++)o[s+i]=new Et({func:r.GEQUAL,mask:255},s+this.nextStencilID,255,r.KEEP,r.KEEP,r.REPLACE);return this.nextStencilID+=a,[o,n]}return[(e={},e[i]=Et.disabled,e),n]},Mn.prototype.colorModeForRenderPass=function(){var e=this.context.gl;if(this._showOverdrawInspector){var r=1/8;return new Lt([e.CONSTANT_COLOR,e.ONE],new t.Color(r,r,r,0),[!0,!0,!0,!0])}return"opaque"===this.renderPass?Lt.unblended:Lt.alphaBlended},Mn.prototype.depthModeForSublayer=function(t,e,r){if(!this.opaquePassEnabledForLayer())return Mt.disabled;var n=1-((1+this.currentLayer)*this.numSublayers+t)*this.depthEpsilon;return new Mt(r||this.context.gl.LEQUAL,e,[n,n])},Mn.prototype.opaquePassEnabledForLayer=function(){return this.currentLayer<this.opaquePassCutoff},Mn.prototype.render=function(e,r){var n=this;this.style=e,this.options=r,this.lineAtlas=e.lineAtlas,this.imageManager=e.imageManager,this.glyphManager=e.glyphManager,this.symbolFadeChange=e.placement.symbolFadeChange(t.browser.now()),this.imageManager.beginFrame();var i=this.style._order,a=this.style.sourceCaches;for(var o in a){var s=a[o];s.used&&s.prepare(this.context)}var l,u,c={},f={},h={};for(var p in a){var d=a[p];c[p]=d.getVisibleCoordinates(),f[p]=c[p].slice().reverse(),h[p]=d.getVisibleCoordinates(!0).reverse()}this.opaquePassCutoff=1/0;for(var v=0;v<i.length;v++){var g=i[v];if(this.style._layers[g].is3D()){this.opaquePassCutoff=v;break}}this.renderPass="offscreen";for(var y=0,m=i;y<m.length;y+=1){var x=m[y],b=this.style._layers[x];if(b.hasOffscreenPass()&&!b.isHidden(this.transform.zoom)){var _=f[b.source];("custom"===b.type||_.length)&&this.renderLayer(this,a[b.source],b,_)}}for(this.context.bindFramebuffer.set(null),this.context.clear({color:r.showOverdrawInspector?t.Color.black:t.Color.transparent,depth:1}),this.clearStencil(),this._showOverdrawInspector=r.showOverdrawInspector,this.depthRangeFor3D=[0,1-(e._order.length+2)*this.numSublayers*this.depthEpsilon],this.renderPass="opaque",this.currentLayer=i.length-1;this.currentLayer>=0;this.currentLayer--){var w=this.style._layers[i[this.currentLayer]],T=a[w.source],k=c[w.source];this._renderTileClippingMasks(w,k),this.renderLayer(this,T,w,k)}for(this.renderPass="translucent",this.currentLayer=0;this.currentLayer<i.length;this.currentLayer++){var A=this.style._layers[i[this.currentLayer]],M=a[A.source],S=("symbol"===A.type?h:f)[A.source];this._renderTileClippingMasks(A,c[A.source]),this.renderLayer(this,M,A,S)}this.options.showTileBoundaries&&(t.values(this.style._layers).forEach((function(t){t.source&&!t.isHidden(n.transform.zoom)&&(t.source!==(u&&u.id)&&(u=n.style.sourceCaches[t.source]),(!l||l.getSource().maxzoom<u.getSource().maxzoom)&&(l=u))})),l&&An.debug(this,l,l.getVisibleCoordinates())),this.options.showPadding&&bn(this),this.context.setDefault()},Mn.prototype.renderLayer=function(t,e,r,n){r.isHidden(this.transform.zoom)||("background"===r.type||"custom"===r.type||n.length)&&(this.id=r.id,this.gpuTimingStart(r),An[r.type](t,e,r,n,this.style.placement.variableOffsets),this.gpuTimingEnd())},Mn.prototype.gpuTimingStart=function(t){if(this.options.gpuTiming){var e=this.context.extTimerQuery,r=this.gpuTimers[t.id];r||(r=this.gpuTimers[t.id]={calls:0,cpuTime:0,query:e.createQueryEXT()}),r.calls++,e.beginQueryEXT(e.TIME_ELAPSED_EXT,r.query)}},Mn.prototype.gpuTimingEnd=function(){if(this.options.gpuTiming){var t=this.context.extTimerQuery;t.endQueryEXT(t.TIME_ELAPSED_EXT)}},Mn.prototype.collectGpuTimers=function(){var t=this.gpuTimers;return this.gpuTimers={},t},Mn.prototype.queryGpuTimers=function(t){var e={};for(var r in t){var n=t[r],i=this.context.extTimerQuery,a=i.getQueryObjectEXT(n.query,i.QUERY_RESULT_EXT)/1e6;i.deleteQueryEXT(n.query),e[r]=a}return e},Mn.prototype.translatePosMatrix=function(e,r,n,i,a){if(!n[0]&&!n[1])return e;var o=a?"map"===i?this.transform.angle:0:"viewport"===i?-this.transform.angle:0;if(o){var s=Math.sin(o),l=Math.cos(o);n=[n[0]*l-n[1]*s,n[0]*s+n[1]*l]}var u=[a?n[0]:ge(r,n[0],this.transform.zoom),a?n[1]:ge(r,n[1],this.transform.zoom),0],c=new Float32Array(16);return t.translate(c,e,u),c},Mn.prototype.saveTileTexture=function(t){var e=this._tileTextures[t.size[0]];e?e.push(t):this._tileTextures[t.size[0]]=[t]},Mn.prototype.getTileTexture=function(t){var e=this._tileTextures[t];return e&&e.length>0?e.pop():null},Mn.prototype.isPatternMissing=function(t){if(!t)return!1;if(!t.from||!t.to)return!0;var e=this.imageManager.getPattern(t.from.toString()),r=this.imageManager.getPattern(t.to.toString());return!e||!r},Mn.prototype.useProgram=function(t,e){this.cache=this.cache||{};var r=""+t+(e?e.cacheKey:"")+(this._showOverdrawInspector?"/overdraw":"");return this.cache[r]||(this.cache[r]=new kr(this.context,wr[t],e,en[t],this._showOverdrawInspector)),this.cache[r]},Mn.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},Mn.prototype.setBaseState=function(){var t=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(t.FUNC_ADD)},Mn.prototype.initDebugOverlayCanvas=function(){if(null==this.debugOverlayCanvas){this.debugOverlayCanvas=t.window.document.createElement("canvas"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512;var e=this.context.gl;this.debugOverlayTexture=new t.Texture(this.context,this.debugOverlayCanvas,e.RGBA)}},Mn.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var Sn=function(t,e){this.points=t,this.planes=e};Sn.fromInvProjectionMatrix=function(e,r,n){var i=Math.pow(2,n),a=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map((function(r){return t.transformMat4([],r,e)})).map((function(e){return t.scale$1([],e,1/e[3]/r*i)})),o=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map((function(e){var r=t.sub([],a[e[0]],a[e[1]]),n=t.sub([],a[e[2]],a[e[1]]),i=t.normalize([],t.cross([],r,n)),o=-t.dot(i,a[e[1]]);return i.concat(o)}));return new Sn(a,o)};var En=function(e,r){this.min=e,this.max=r,this.center=t.scale$2([],t.add([],this.min,this.max),.5)};En.prototype.quadrant=function(e){for(var r=[e%2==0,e<2],n=t.clone$2(this.min),i=t.clone$2(this.max),a=0;a<r.length;a++)n[a]=r[a]?this.min[a]:this.center[a],i[a]=r[a]?this.center[a]:this.max[a];return i[2]=this.max[2],new En(n,i)},En.prototype.distanceX=function(t){return Math.max(Math.min(this.max[0],t[0]),this.min[0])-t[0]},En.prototype.distanceY=function(t){return Math.max(Math.min(this.max[1],t[1]),this.min[1])-t[1]},En.prototype.intersects=function(e){for(var r=[[this.min[0],this.min[1],0,1],[this.max[0],this.min[1],0,1],[this.max[0],this.max[1],0,1],[this.min[0],this.max[1],0,1]],n=!0,i=0;i<e.planes.length;i++){for(var a=e.planes[i],o=0,s=0;s<r.length;s++)o+=t.dot$1(a,r[s])>=0;if(0===o)return 0;o!==r.length&&(n=!1)}if(n)return 2;for(var l=0;l<3;l++){for(var u=Number.MAX_VALUE,c=-Number.MAX_VALUE,f=0;f<e.points.length;f++){var h=e.points[f][l]-this.min[l];u=Math.min(u,h),c=Math.max(c,h)}if(c<0||u>this.max[l]-this.min[l])return 0}return 1};var Ln=function(t,e,r,n){if(void 0===t&&(t=0),void 0===e&&(e=0),void 0===r&&(r=0),void 0===n&&(n=0),isNaN(t)||t<0||isNaN(e)||e<0||isNaN(r)||r<0||isNaN(n)||n<0)throw new Error("Invalid value for edge-insets, top, bottom, left and right must all be numbers");this.top=t,this.bottom=e,this.left=r,this.right=n};Ln.prototype.interpolate=function(e,r,n){return null!=r.top&&null!=e.top&&(this.top=t.number(e.top,r.top,n)),null!=r.bottom&&null!=e.bottom&&(this.bottom=t.number(e.bottom,r.bottom,n)),null!=r.left&&null!=e.left&&(this.left=t.number(e.left,r.left,n)),null!=r.right&&null!=e.right&&(this.right=t.number(e.right,r.right,n)),this},Ln.prototype.getCenter=function(e,r){var n=t.clamp((this.left+e-this.right)/2,0,e),i=t.clamp((this.top+r-this.bottom)/2,0,r);return new t.Point(n,i)},Ln.prototype.equals=function(t){return this.top===t.top&&this.bottom===t.bottom&&this.left===t.left&&this.right===t.right},Ln.prototype.clone=function(){return new Ln(this.top,this.bottom,this.left,this.right)},Ln.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var Cn=function(e,r,n,i,a){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=void 0===a||a,this._minZoom=e||0,this._maxZoom=r||22,this._minPitch=null==n?0:n,this._maxPitch=null==i?60:i,this.setMaxBounds(),this.width=0,this.height=0,this._center=new t.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new Ln,this._posMatrixCache={},this._alignedPosMatrixCache={}},Pn={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};Cn.prototype.clone=function(){var t=new Cn(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return t.tileSize=this.tileSize,t.latRange=this.latRange,t.width=this.width,t.height=this.height,t._center=this._center,t.zoom=this.zoom,t.angle=this.angle,t._fov=this._fov,t._pitch=this._pitch,t._unmodified=this._unmodified,t._edgeInsets=this._edgeInsets.clone(),t._calcMatrices(),t},Pn.minZoom.get=function(){return this._minZoom},Pn.minZoom.set=function(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},Pn.maxZoom.get=function(){return this._maxZoom},Pn.maxZoom.set=function(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},Pn.minPitch.get=function(){return this._minPitch},Pn.minPitch.set=function(t){this._minPitch!==t&&(this._minPitch=t,this.pitch=Math.max(this.pitch,t))},Pn.maxPitch.get=function(){return this._maxPitch},Pn.maxPitch.set=function(t){this._maxPitch!==t&&(this._maxPitch=t,this.pitch=Math.min(this.pitch,t))},Pn.renderWorldCopies.get=function(){return this._renderWorldCopies},Pn.renderWorldCopies.set=function(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t},Pn.worldSize.get=function(){return this.tileSize*this.scale},Pn.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},Pn.size.get=function(){return new t.Point(this.width,this.height)},Pn.bearing.get=function(){return-this.angle/Math.PI*180},Pn.bearing.set=function(e){var r=-t.wrap(e,-180,180)*Math.PI/180;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=t.create$2(),t.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},Pn.pitch.get=function(){return this._pitch/Math.PI*180},Pn.pitch.set=function(e){var r=t.clamp(e,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())},Pn.fov.get=function(){return this._fov/Math.PI*180},Pn.fov.set=function(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())},Pn.zoom.get=function(){return this._zoom},Pn.zoom.set=function(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._constrain(),this._calcMatrices())},Pn.center.get=function(){return this._center},Pn.center.set=function(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())},Pn.padding.get=function(){return this._edgeInsets.toJSON()},Pn.padding.set=function(t){this._edgeInsets.equals(t)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,t,1),this._calcMatrices())},Pn.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},Cn.prototype.isPaddingEqual=function(t){return this._edgeInsets.equals(t)},Cn.prototype.interpolatePadding=function(t,e,r){this._unmodified=!1,this._edgeInsets.interpolate(t,e,r),this._constrain(),this._calcMatrices()},Cn.prototype.coveringZoomLevel=function(t){var e=(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize));return Math.max(0,e)},Cn.prototype.getVisibleUnwrappedCoordinates=function(e){var r=[new t.UnwrappedTileID(0,e)];if(this._renderWorldCopies)for(var n=this.pointCoordinate(new t.Point(0,0)),i=this.pointCoordinate(new t.Point(this.width,0)),a=this.pointCoordinate(new t.Point(this.width,this.height)),o=this.pointCoordinate(new t.Point(0,this.height)),s=Math.floor(Math.min(n.x,i.x,a.x,o.x)),l=Math.floor(Math.max(n.x,i.x,a.x,o.x)),u=s-1;u<=l+1;u++)0!==u&&r.push(new t.UnwrappedTileID(u,e));return r},Cn.prototype.coveringTiles=function(e){var r=this.coveringZoomLevel(e),n=r;if(void 0!==e.minzoom&&r<e.minzoom)return[];void 0!==e.maxzoom&&r>e.maxzoom&&(r=e.maxzoom);var i=t.MercatorCoordinate.fromLngLat(this.center),a=Math.pow(2,r),o=[a*i.x,a*i.y,0],s=Sn.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,r),l=e.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(l=r);var u=function(t){return{aabb:new En([t*a,0,0],[(t+1)*a,a,0]),zoom:0,x:0,y:0,wrap:t,fullyVisible:!1}},c=[],f=[],h=r,p=e.reparseOverscaled?n:r;if(this._renderWorldCopies)for(var d=1;d<=3;d++)c.push(u(-d)),c.push(u(d));for(c.push(u(0));c.length>0;){var v=c.pop(),g=v.x,y=v.y,m=v.fullyVisible;if(!m){var x=v.aabb.intersects(s);if(0===x)continue;m=2===x}var b=v.aabb.distanceX(o),_=v.aabb.distanceY(o),w=Math.max(Math.abs(b),Math.abs(_)),T=3+(1<<h-v.zoom)-2;if(v.zoom===h||w>T&&v.zoom>=l)f.push({tileID:new t.OverscaledTileID(v.zoom===h?p:v.zoom,v.wrap,v.zoom,g,y),distanceSq:t.sqrLen([o[0]-.5-g,o[1]-.5-y])});else for(var k=0;k<4;k++){var A=(g<<1)+k%2,M=(y<<1)+(k>>1);c.push({aabb:v.aabb.quadrant(k),zoom:v.zoom+1,x:A,y:M,wrap:v.wrap,fullyVisible:m})}}return f.sort((function(t,e){return t.distanceSq-e.distanceSq})).map((function(t){return t.tileID}))},Cn.prototype.resize=function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()},Pn.unmodified.get=function(){return this._unmodified},Cn.prototype.zoomScale=function(t){return Math.pow(2,t)},Cn.prototype.scaleZoom=function(t){return Math.log(t)/Math.LN2},Cn.prototype.project=function(e){var r=t.clamp(e.lat,-this.maxValidLatitude,this.maxValidLatitude);return new t.Point(t.mercatorXfromLng(e.lng)*this.worldSize,t.mercatorYfromLat(r)*this.worldSize)},Cn.prototype.unproject=function(e){return new t.MercatorCoordinate(e.x/this.worldSize,e.y/this.worldSize).toLngLat()},Pn.point.get=function(){return this.project(this.center)},Cn.prototype.setLocationAtPoint=function(e,r){var n=this.pointCoordinate(r),i=this.pointCoordinate(this.centerPoint),a=this.locationCoordinate(e),o=new t.MercatorCoordinate(a.x-(n.x-i.x),a.y-(n.y-i.y));this.center=this.coordinateLocation(o),this._renderWorldCopies&&(this.center=this.center.wrap())},Cn.prototype.locationPoint=function(t){return this.coordinatePoint(this.locationCoordinate(t))},Cn.prototype.pointLocation=function(t){return this.coordinateLocation(this.pointCoordinate(t))},Cn.prototype.locationCoordinate=function(e){return t.MercatorCoordinate.fromLngLat(e)},Cn.prototype.coordinateLocation=function(t){return t.toLngLat()},Cn.prototype.pointCoordinate=function(e){var r=[e.x,e.y,0,1],n=[e.x,e.y,1,1];t.transformMat4(r,r,this.pixelMatrixInverse),t.transformMat4(n,n,this.pixelMatrixInverse);var i=r[3],a=n[3],o=r[0]/i,s=n[0]/a,l=r[1]/i,u=n[1]/a,c=r[2]/i,f=n[2]/a,h=c===f?0:(0-c)/(f-c);return new t.MercatorCoordinate(t.number(o,s,h)/this.worldSize,t.number(l,u,h)/this.worldSize)},Cn.prototype.coordinatePoint=function(e){var r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix),new t.Point(r[0]/r[3],r[1]/r[3])},Cn.prototype.getBounds=function(){return(new t.LngLatBounds).extend(this.pointLocation(new t.Point(0,0))).extend(this.pointLocation(new t.Point(this.width,0))).extend(this.pointLocation(new t.Point(this.width,this.height))).extend(this.pointLocation(new t.Point(0,this.height)))},Cn.prototype.getMaxBounds=function(){return this.latRange&&2===this.latRange.length&&this.lngRange&&2===this.lngRange.length?new t.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null},Cn.prototype.setMaxBounds=function(t){t?(this.lngRange=[t.getWest(),t.getEast()],this.latRange=[t.getSouth(),t.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},Cn.prototype.calculatePosMatrix=function(e,r){void 0===r&&(r=!1);var n=e.key,i=r?this._alignedPosMatrixCache:this._posMatrixCache;if(i[n])return i[n];var a=e.canonical,o=this.worldSize/this.zoomScale(a.z),s=a.x+Math.pow(2,a.z)*e.wrap,l=t.identity(new Float64Array(16));return t.translate(l,l,[s*o,a.y*o,0]),t.scale(l,l,[o/t.EXTENT,o/t.EXTENT,1]),t.multiply(l,r?this.alignedProjMatrix:this.projMatrix,l),i[n]=new Float32Array(l),i[n]},Cn.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},Cn.prototype._constrain=function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var e,r,n,i,a=-90,o=90,s=-180,l=180,u=this.size,c=this._unmodified;if(this.latRange){var f=this.latRange;a=t.mercatorYfromLat(f[1])*this.worldSize,e=(o=t.mercatorYfromLat(f[0])*this.worldSize)-a<u.y?u.y/(o-a):0}if(this.lngRange){var h=this.lngRange;s=t.mercatorXfromLng(h[0])*this.worldSize,r=(l=t.mercatorXfromLng(h[1])*this.worldSize)-s<u.x?u.x/(l-s):0}var p=this.point,d=Math.max(r||0,e||0);if(d)return this.center=this.unproject(new t.Point(r?(l+s)/2:p.x,e?(o+a)/2:p.y)),this.zoom+=this.scaleZoom(d),this._unmodified=c,void(this._constraining=!1);if(this.latRange){var v=p.y,g=u.y/2;v-g<a&&(i=a+g),v+g>o&&(i=o-g)}if(this.lngRange){var y=p.x,m=u.x/2;y-m<s&&(n=s+m),y+m>l&&(n=l-m)}void 0===n&&void 0===i||(this.center=this.unproject(new t.Point(void 0!==n?n:p.x,void 0!==i?i:p.y))),this._unmodified=c,this._constraining=!1}},Cn.prototype._calcMatrices=function(){if(this.height){var e=this._fov/2,r=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(e)*this.height;var n=Math.PI/2+this._pitch,i=this._fov*(.5+r.y/this.height),a=Math.sin(i)*this.cameraToCenterDistance/Math.sin(t.clamp(Math.PI-n-i,.01,Math.PI-.01)),o=this.point,s=o.x,l=o.y,u=1.01*(Math.cos(Math.PI/2-this._pitch)*a+this.cameraToCenterDistance),c=this.height/50,f=new Float64Array(16);t.perspective(f,this._fov,this.width/this.height,c,u),f[8]=2*-r.x/this.width,f[9]=2*r.y/this.height,t.scale(f,f,[1,-1,1]),t.translate(f,f,[0,0,-this.cameraToCenterDistance]),t.rotateX(f,f,this._pitch),t.rotateZ(f,f,this.angle),t.translate(f,f,[-s,-l,0]),this.mercatorMatrix=t.scale([],f,[this.worldSize,this.worldSize,this.worldSize]),t.scale(f,f,[1,1,t.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=f,this.invProjMatrix=t.invert([],this.projMatrix);var h=this.width%2/2,p=this.height%2/2,d=Math.cos(this.angle),v=Math.sin(this.angle),g=s-Math.round(s)+d*h+v*p,y=l-Math.round(l)+d*p+v*h,m=new Float64Array(f);if(t.translate(m,m,[g>.5?g-1:g,y>.5?y-1:y,0]),this.alignedProjMatrix=m,f=t.create(),t.scale(f,f,[this.width/2,-this.height/2,1]),t.translate(f,f,[1,-1,0]),this.labelPlaneMatrix=f,f=t.create(),t.scale(f,f,[1,-1,1]),t.translate(f,f,[-1,-1,0]),t.scale(f,f,[2/this.width,2/this.height,1]),this.glCoordMatrix=f,this.pixelMatrix=t.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),!(f=t.invert(new Float64Array(16),this.pixelMatrix)))throw new Error("failed to invert matrix");this.pixelMatrixInverse=f,this._posMatrixCache={},this._alignedPosMatrixCache={}}},Cn.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var e=this.pointCoordinate(new t.Point(0,0)),r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance},Cn.prototype.getCameraPoint=function(){var e=this._pitch,r=Math.tan(e)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new t.Point(0,r))},Cn.prototype.getCameraQueryGeometry=function(e){var r=this.getCameraPoint();if(1===e.length)return[e[0],r];for(var n=r.x,i=r.y,a=r.x,o=r.y,s=0,l=e;s<l.length;s+=1){var u=l[s];n=Math.min(n,u.x),i=Math.min(i,u.y),a=Math.max(a,u.x),o=Math.max(o,u.y)}return[new t.Point(n,i),new t.Point(a,i),new t.Point(a,o),new t.Point(n,o),new t.Point(n,i)]},Object.defineProperties(Cn.prototype,Pn);var On=function(e){var r,n,i,a,o;this._hashName=e&&encodeURIComponent(e),t.bindAll(["_getCurrentHash","_onHashChange","_updateHash"],this),this._updateHash=(r=this._updateHashUnthrottled.bind(this),n=300,i=!1,a=null,o=function(){a=null,i&&(r(),a=setTimeout(o,n),i=!1)},function(){return i=!0,a||o(),a})};On.prototype.addTo=function(e){return this._map=e,t.window.addEventListener("hashchange",this._onHashChange,!1),this._map.on("moveend",this._updateHash),this},On.prototype.remove=function(){return t.window.removeEventListener("hashchange",this._onHashChange,!1),this._map.off("moveend",this._updateHash),clearTimeout(this._updateHash()),delete this._map,this},On.prototype.getHashString=function(e){var r=this._map.getCenter(),n=Math.round(100*this._map.getZoom())/100,i=Math.ceil((n*Math.LN2+Math.log(512/360/.5))/Math.LN10),a=Math.pow(10,i),o=Math.round(r.lng*a)/a,s=Math.round(r.lat*a)/a,l=this._map.getBearing(),u=this._map.getPitch(),c="";if(c+=e?"/"+o+"/"+s+"/"+n:n+"/"+s+"/"+o,(l||u)&&(c+="/"+Math.round(10*l)/10),u&&(c+="/"+Math.round(u)),this._hashName){var f=this._hashName,h=!1,p=t.window.location.hash.slice(1).split("&").map((function(t){var e=t.split("=")[0];return e===f?(h=!0,e+"="+c):t})).filter((function(t){return t}));return h||p.push(f+"="+c),"#"+p.join("&")}return"#"+c},On.prototype._getCurrentHash=function(){var e,r=this,n=t.window.location.hash.replace("#","");return this._hashName?(n.split("&").map((function(t){return t.split("=")})).forEach((function(t){t[0]===r._hashName&&(e=t)})),(e&&e[1]||"").split("/")):n.split("/")},On.prototype._onHashChange=function(){var t=this._getCurrentHash();if(t.length>=3&&!t.some((function(t){return isNaN(t)}))){var e=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(t[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:e,pitch:+(t[4]||0)}),!0}return!1},On.prototype._updateHashUnthrottled=function(){var e=this.getHashString();try{t.window.history.replaceState(t.window.history.state,"",e)}catch(t){}};var In={linearity:.3,easing:t.bezier(0,0,.3,1)},Dn=t.extend({deceleration:2500,maxSpeed:1400},In),zn=t.extend({deceleration:20,maxSpeed:1400},In),Rn=t.extend({deceleration:1e3,maxSpeed:360},In),Fn=t.extend({deceleration:1e3,maxSpeed:90},In),Bn=function(t){this._map=t,this.clear()};function Nn(t,e){(!t.duration||t.duration<e.duration)&&(t.duration=e.duration,t.easing=e.easing)}function jn(e,r,n){var i=n.maxSpeed,a=n.linearity,o=n.deceleration,s=t.clamp(e*a/(r/1e3),-i,i),l=Math.abs(s)/(o*a);return{easing:n.easing,duration:1e3*l,amount:s*(l/2)}}Bn.prototype.clear=function(){this._inertiaBuffer=[]},Bn.prototype.record=function(e){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:t.browser.now(),settings:e})},Bn.prototype._drainInertiaBuffer=function(){for(var e=this._inertiaBuffer,r=t.browser.now();e.length>0&&r-e[0].time>160;)e.shift()},Bn.prototype._onMoveEnd=function(e){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var r={zoom:0,bearing:0,pitch:0,pan:new t.Point(0,0),pinchAround:void 0,around:void 0},n=0,i=this._inertiaBuffer;n<i.length;n+=1){var a=i[n].settings;r.zoom+=a.zoomDelta||0,r.bearing+=a.bearingDelta||0,r.pitch+=a.pitchDelta||0,a.panDelta&&r.pan._add(a.panDelta),a.around&&(r.around=a.around),a.pinchAround&&(r.pinchAround=a.pinchAround)}var o=this._inertiaBuffer[this._inertiaBuffer.length-1].time-this._inertiaBuffer[0].time,s={};if(r.pan.mag()){var l=jn(r.pan.mag(),o,t.extend({},Dn,e||{}));s.offset=r.pan.mult(l.amount/r.pan.mag()),s.center=this._map.transform.center,Nn(s,l)}if(r.zoom){var u=jn(r.zoom,o,zn);s.zoom=this._map.transform.zoom+u.amount,Nn(s,u)}if(r.bearing){var c=jn(r.bearing,o,Rn);s.bearing=this._map.transform.bearing+t.clamp(c.amount,-179,179),Nn(s,c)}if(r.pitch){var f=jn(r.pitch,o,Fn);s.pitch=this._map.transform.pitch+f.amount,Nn(s,f)}if(s.zoom||s.bearing){var h=void 0===r.pinchAround?r.around:r.pinchAround;s.around=h?this._map.unproject(h):this._map.getCenter()}return this.clear(),t.extend(s,{noMoveStart:!0})}};var Un=function(e){function n(n,i,a,o){void 0===o&&(o={});var s=r.mousePos(i.getCanvasContainer(),a),l=i.unproject(s);e.call(this,n,t.extend({point:s,lngLat:l,originalEvent:a},o)),this._defaultPrevented=!1,this.target=i}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),Vn=function(e){function n(n,i,a){var o="touchend"===n?a.changedTouches:a.touches,s=r.touchPos(i.getCanvasContainer(),o),l=s.map((function(t){return i.unproject(t)})),u=s.reduce((function(t,e,r,n){return t.add(e.div(n.length))}),new t.Point(0,0)),c=i.unproject(u);e.call(this,n,{points:s,point:u,lngLats:l,lngLat:c,originalEvent:a}),this._defaultPrevented=!1}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),Hn=function(t){function e(e,r,n){t.call(this,e,{originalEvent:n}),this._defaultPrevented=!1}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={defaultPrevented:{configurable:!0}};return e.prototype.preventDefault=function(){this._defaultPrevented=!0},r.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(e.prototype,r),e}(t.Event),qn=function(t,e){this._map=t,this._clickTolerance=e.clickTolerance};qn.prototype.reset=function(){delete this._mousedownPos},qn.prototype.wheel=function(t){return this._firePreventable(new Hn(t.type,this._map,t))},qn.prototype.mousedown=function(t,e){return this._mousedownPos=e,this._firePreventable(new Un(t.type,this._map,t))},qn.prototype.mouseup=function(t){this._map.fire(new Un(t.type,this._map,t))},qn.prototype.click=function(t,e){this._mousedownPos&&this._mousedownPos.dist(e)>=this._clickTolerance||this._map.fire(new Un(t.type,this._map,t))},qn.prototype.dblclick=function(t){return this._firePreventable(new Un(t.type,this._map,t))},qn.prototype.mouseover=function(t){this._map.fire(new Un(t.type,this._map,t))},qn.prototype.mouseout=function(t){this._map.fire(new Un(t.type,this._map,t))},qn.prototype.touchstart=function(t){return this._firePreventable(new Vn(t.type,this._map,t))},qn.prototype.touchmove=function(t){this._map.fire(new Vn(t.type,this._map,t))},qn.prototype.touchend=function(t){this._map.fire(new Vn(t.type,this._map,t))},qn.prototype.touchcancel=function(t){this._map.fire(new Vn(t.type,this._map,t))},qn.prototype._firePreventable=function(t){if(this._map.fire(t),t.defaultPrevented)return{}},qn.prototype.isEnabled=function(){return!0},qn.prototype.isActive=function(){return!1},qn.prototype.enable=function(){},qn.prototype.disable=function(){};var Gn=function(t){this._map=t};Gn.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},Gn.prototype.mousemove=function(t){this._map.fire(new Un(t.type,this._map,t))},Gn.prototype.mousedown=function(){this._delayContextMenu=!0},Gn.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new Un("contextmenu",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},Gn.prototype.contextmenu=function(t){this._delayContextMenu?this._contextMenuEvent=t:this._map.fire(new Un(t.type,this._map,t)),this._map.listens("contextmenu")&&t.preventDefault()},Gn.prototype.isEnabled=function(){return!0},Gn.prototype.isActive=function(){return!1},Gn.prototype.enable=function(){},Gn.prototype.disable=function(){};var Zn=function(t,e){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),this._clickTolerance=e.clickTolerance||1};function Yn(t,e){for(var r={},n=0;n<t.length;n++)r[t[n].identifier]=e[n];return r}Zn.prototype.isEnabled=function(){return!!this._enabled},Zn.prototype.isActive=function(){return!!this._active},Zn.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},Zn.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},Zn.prototype.mousedown=function(t,e){this.isEnabled()&&t.shiftKey&&0===t.button&&(r.disableDrag(),this._startPos=this._lastPos=e,this._active=!0)},Zn.prototype.mousemoveWindow=function(t,e){if(this._active){var n=e;if(!(this._lastPos.equals(n)||!this._box&&n.dist(this._startPos)<this._clickTolerance)){var i=this._startPos;this._lastPos=n,this._box||(this._box=r.create("div","mapboxgl-boxzoom",this._container),this._container.classList.add("mapboxgl-crosshair"),this._fireEvent("boxzoomstart",t));var a=Math.min(i.x,n.x),o=Math.max(i.x,n.x),s=Math.min(i.y,n.y),l=Math.max(i.y,n.y);r.setTransform(this._box,"translate("+a+"px,"+s+"px)"),this._box.style.width=o-a+"px",this._box.style.height=l-s+"px"}}},Zn.prototype.mouseupWindow=function(e,n){var i=this;if(this._active&&0===e.button){var a=this._startPos,o=n;if(this.reset(),r.suppressClick(),a.x!==o.x||a.y!==o.y)return this._map.fire(new t.Event("boxzoomend",{originalEvent:e})),{cameraAnimation:function(t){return t.fitScreenCoordinates(a,o,i._map.getBearing(),{linear:!0})}};this._fireEvent("boxzoomcancel",e)}},Zn.prototype.keydown=function(t){this._active&&27===t.keyCode&&(this.reset(),this._fireEvent("boxzoomcancel",t))},Zn.prototype.reset=function(){this._active=!1,this._container.classList.remove("mapboxgl-crosshair"),this._box&&(r.remove(this._box),this._box=null),r.enableDrag(),delete this._startPos,delete this._lastPos},Zn.prototype._fireEvent=function(e,r){return this._map.fire(new t.Event(e,{originalEvent:r}))};var Wn=function(t){this.reset(),this.numTouches=t.numTouches};Wn.prototype.reset=function(){delete this.centroid,delete this.startTime,delete this.touches,this.aborted=!1},Wn.prototype.touchstart=function(e,r,n){(this.centroid||n.length>this.numTouches)&&(this.aborted=!0),this.aborted||(void 0===this.startTime&&(this.startTime=e.timeStamp),n.length===this.numTouches&&(this.centroid=function(e){for(var r=new t.Point(0,0),n=0,i=e;n<i.length;n+=1){var a=i[n];r._add(a)}return r.div(e.length)}(r),this.touches=Yn(n,r)))},Wn.prototype.touchmove=function(t,e,r){if(!this.aborted&&this.centroid){var n=Yn(r,e);for(var i in this.touches){var a=this.touches[i],o=n[i];(!o||o.dist(a)>30)&&(this.aborted=!0)}}},Wn.prototype.touchend=function(t,e,r){if((!this.centroid||t.timeStamp-this.startTime>500)&&(this.aborted=!0),0===r.length){var n=!this.aborted&&this.centroid;if(this.reset(),n)return n}};var Xn=function(t){this.singleTap=new Wn(t),this.numTaps=t.numTaps,this.reset()};Xn.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},Xn.prototype.touchstart=function(t,e,r){this.singleTap.touchstart(t,e,r)},Xn.prototype.touchmove=function(t,e,r){this.singleTap.touchmove(t,e,r)},Xn.prototype.touchend=function(t,e,r){var n=this.singleTap.touchend(t,e,r);if(n){var i=t.timeStamp-this.lastTime<500,a=!this.lastTap||this.lastTap.dist(n)<30;if(i&&a||this.reset(),this.count++,this.lastTime=t.timeStamp,this.lastTap=n,this.count===this.numTaps)return this.reset(),n}};var Jn=function(){this._zoomIn=new Xn({numTouches:1,numTaps:2}),this._zoomOut=new Xn({numTouches:2,numTaps:1}),this.reset()};Jn.prototype.reset=function(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()},Jn.prototype.touchstart=function(t,e,r){this._zoomIn.touchstart(t,e,r),this._zoomOut.touchstart(t,e,r)},Jn.prototype.touchmove=function(t,e,r){this._zoomIn.touchmove(t,e,r),this._zoomOut.touchmove(t,e,r)},Jn.prototype.touchend=function(t,e,r){var n=this,i=this._zoomIn.touchend(t,e,r),a=this._zoomOut.touchend(t,e,r);return i?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()+1,around:e.unproject(i)},{originalEvent:t})}}):a?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()-1,around:e.unproject(a)},{originalEvent:t})}}):void 0},Jn.prototype.touchcancel=function(){this.reset()},Jn.prototype.enable=function(){this._enabled=!0},Jn.prototype.disable=function(){this._enabled=!1,this.reset()},Jn.prototype.isEnabled=function(){return this._enabled},Jn.prototype.isActive=function(){return this._active};var Kn=function(t){this.reset(),this._clickTolerance=t.clickTolerance||1};Kn.prototype.reset=function(){this._active=!1,this._moved=!1,delete this._lastPoint,delete this._eventButton},Kn.prototype._correctButton=function(t,e){return!1},Kn.prototype._move=function(t,e){return{}},Kn.prototype.mousedown=function(t,e){if(!this._lastPoint){var n=r.mouseButton(t);this._correctButton(t,n)&&(this._lastPoint=e,this._eventButton=n)}},Kn.prototype.mousemoveWindow=function(t,e){var r=this._lastPoint;if(r&&(t.preventDefault(),this._moved||!(e.dist(r)<this._clickTolerance)))return this._moved=!0,this._lastPoint=e,this._move(r,e)},Kn.prototype.mouseupWindow=function(t){r.mouseButton(t)===this._eventButton&&(this._moved&&r.suppressClick(),this.reset())},Kn.prototype.enable=function(){this._enabled=!0},Kn.prototype.disable=function(){this._enabled=!1,this.reset()},Kn.prototype.isEnabled=function(){return this._enabled},Kn.prototype.isActive=function(){return this._active};var $n=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.mousedown=function(e,r){t.prototype.mousedown.call(this,e,r),this._lastPoint&&(this._active=!0)},e.prototype._correctButton=function(t,e){return 0===e&&!t.ctrlKey},e.prototype._move=function(t,e){return{around:e,panDelta:e.sub(t)}},e}(Kn),Qn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=.8*(e.x-t.x);if(r)return this._active=!0,{bearingDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(Kn),ti=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=-.5*(e.y-t.y);if(r)return this._active=!0,{pitchDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(Kn),ei=function(t){this._minTouches=1,this._clickTolerance=t.clickTolerance||1,this.reset()};ei.prototype.reset=function(){this._active=!1,this._touches={},this._sum=new t.Point(0,0)},ei.prototype.touchstart=function(t,e,r){return this._calculateTransform(t,e,r)},ei.prototype.touchmove=function(t,e,r){if(this._active)return t.preventDefault(),this._calculateTransform(t,e,r)},ei.prototype.touchend=function(t,e,r){this._calculateTransform(t,e,r),this._active&&r.length<this._minTouches&&this.reset()},ei.prototype.touchcancel=function(){this.reset()},ei.prototype._calculateTransform=function(e,r,n){n.length>0&&(this._active=!0);var i=Yn(n,r),a=new t.Point(0,0),o=new t.Point(0,0),s=0;for(var l in i){var u=i[l],c=this._touches[l];c&&(a._add(u),o._add(u.sub(c)),s++,i[l]=u)}if(this._touches=i,!(s<this._minTouches)&&o.mag()){var f=o.div(s);if(this._sum._add(f),!(this._sum.mag()<this._clickTolerance))return{around:a.div(s),panDelta:f}}},ei.prototype.enable=function(){this._enabled=!0},ei.prototype.disable=function(){this._enabled=!1,this.reset()},ei.prototype.isEnabled=function(){return this._enabled},ei.prototype.isActive=function(){return this._active};var ri=function(){this.reset()};function ni(t,e,r){for(var n=0;n<t.length;n++)if(t[n].identifier===r)return e[n]}ri.prototype.reset=function(){this._active=!1,delete this._firstTwoTouches},ri.prototype._start=function(t){},ri.prototype._move=function(t,e,r){return{}},ri.prototype.touchstart=function(t,e,r){this._firstTwoTouches||r.length<2||(this._firstTwoTouches=[r[0].identifier,r[1].identifier],this._start([e[0],e[1]]))},ri.prototype.touchmove=function(t,e,r){if(this._firstTwoTouches){t.preventDefault();var n=this._firstTwoTouches,i=n[0],a=n[1],o=ni(r,e,i),s=ni(r,e,a);if(o&&s){var l=this._aroundCenter?null:o.add(s).div(2);return this._move([o,s],l,t)}}},ri.prototype.touchend=function(t,e,n){if(this._firstTwoTouches){var i=this._firstTwoTouches,a=i[0],o=i[1],s=ni(n,e,a),l=ni(n,e,o);s&&l||(this._active&&r.suppressClick(),this.reset())}},ri.prototype.touchcancel=function(){this.reset()},ri.prototype.enable=function(t){this._enabled=!0,this._aroundCenter=!!t&&"center"===t.around},ri.prototype.disable=function(){this._enabled=!1,this.reset()},ri.prototype.isEnabled=function(){return this._enabled},ri.prototype.isActive=function(){return this._active};function ii(t,e){return Math.log(t/e)/Math.LN2}var ai=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._distance,delete this._startDistance},e.prototype._start=function(t){this._startDistance=this._distance=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._distance;if(this._distance=t[0].dist(t[1]),this._active||!(Math.abs(ii(this._distance,this._startDistance))<.1))return this._active=!0,{zoomDelta:ii(this._distance,r),pinchAround:e}},e}(ri);function oi(t,e){return 180*t.angleWith(e)/Math.PI}var si=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._minDiameter,delete this._startVector,delete this._vector},e.prototype._start=function(t){this._startVector=this._vector=t[0].sub(t[1]),this._minDiameter=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._vector;if(this._vector=t[0].sub(t[1]),this._active||!this._isBelowThreshold(this._vector))return this._active=!0,{bearingDelta:oi(this._vector,r),pinchAround:e}},e.prototype._isBelowThreshold=function(t){this._minDiameter=Math.min(this._minDiameter,t.mag());var e=25/(Math.PI*this._minDiameter)*360,r=oi(t,this._startVector);return Math.abs(r)<e},e}(ri);function li(t){return Math.abs(t.y)>Math.abs(t.x)}var ui=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},e.prototype._start=function(t){this._lastPoints=t,li(t[0].sub(t[1]))&&(this._valid=!1)},e.prototype._move=function(t,e,r){var n=t[0].sub(this._lastPoints[0]),i=t[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(n,i,r.timeStamp),this._valid)return this._lastPoints=t,this._active=!0,{pitchDelta:(n.y+i.y)/2*-.5}},e.prototype.gestureBeginsVertically=function(t,e,r){if(void 0!==this._valid)return this._valid;var n=t.mag()>=2,i=e.mag()>=2;if(n||i){if(!n||!i)return void 0===this._firstMove&&(this._firstMove=r),r-this._firstMove<100&&void 0;var a=t.y>0==e.y>0;return li(t)&&li(e)&&a}},e}(ri),ci={panStep:100,bearingStep:15,pitchStep:10},fi=function(){var t=ci;this._panStep=t.panStep,this._bearingStep=t.bearingStep,this._pitchStep=t.pitchStep};function hi(t){return t*(2-t)}fi.prototype.reset=function(){this._active=!1},fi.prototype.keydown=function(t){var e=this;if(!(t.altKey||t.ctrlKey||t.metaKey)){var r=0,n=0,i=0,a=0,o=0;switch(t.keyCode){case 61:case 107:case 171:case 187:r=1;break;case 189:case 109:case 173:r=-1;break;case 37:t.shiftKey?n=-1:(t.preventDefault(),a=-1);break;case 39:t.shiftKey?n=1:(t.preventDefault(),a=1);break;case 38:t.shiftKey?i=1:(t.preventDefault(),o=-1);break;case 40:t.shiftKey?i=-1:(t.preventDefault(),o=1);break;default:return}return{cameraAnimation:function(s){var l=s.getZoom();s.easeTo({duration:300,easeId:"keyboardHandler",easing:hi,zoom:r?Math.round(l)+r*(t.shiftKey?2:1):l,bearing:s.getBearing()+n*e._bearingStep,pitch:s.getPitch()+i*e._pitchStep,offset:[-a*e._panStep,-o*e._panStep],center:s.getCenter()},{originalEvent:t})}}}},fi.prototype.enable=function(){this._enabled=!0},fi.prototype.disable=function(){this._enabled=!1,this.reset()},fi.prototype.isEnabled=function(){return this._enabled},fi.prototype.isActive=function(){return this._active};var pi=4.000244140625,di=function(e,r){this._map=e,this._el=e.getCanvasContainer(),this._handler=r,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=.0022222222222222222,t.bindAll(["_onWheel","_onTimeout","_onScrollFrame","_onScrollFinished"],this)};di.prototype.setZoomRate=function(t){this._defaultZoomRate=t},di.prototype.setWheelZoomRate=function(t){this._wheelZoomRate=t},di.prototype.isEnabled=function(){return!!this._enabled},di.prototype.isActive=function(){return!!this._active||void 0!==this._finishTimeout},di.prototype.isZooming=function(){return!!this._zooming},di.prototype.enable=function(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=t&&"center"===t.around)},di.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},di.prototype.wheel=function(e){if(this.isEnabled()){var r=e.deltaMode===t.window.WheelEvent.DOM_DELTA_LINE?40*e.deltaY:e.deltaY,n=t.browser.now(),i=n-(this._lastWheelEventTime||0);this._lastWheelEventTime=n,0!==r&&r%pi==0?this._type="wheel":0!==r&&Math.abs(r)<4?this._type="trackpad":i>400?(this._type=null,this._lastValue=r,this._timeout=setTimeout(this._onTimeout,40,e)):this._type||(this._type=Math.abs(i*r)<200?"trackpad":"wheel",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,r+=this._lastValue)),e.shiftKey&&r&&(r/=4),this._type&&(this._lastWheelEvent=e,this._delta-=r,this._active||this._start(e)),e.preventDefault()}},di.prototype._onTimeout=function(t){this._type="wheel",this._delta-=this._lastValue,this._active||this._start(t)},di.prototype._start=function(e){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var n=r.mousePos(this._el,e);this._around=t.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(n)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},di.prototype.renderFrame=function(){return this._onScrollFrame()},di.prototype._onScrollFrame=function(){var e=this;if(this._frameId&&(this._frameId=null,this.isActive())){var r=this._map.transform;if(0!==this._delta){var n="wheel"===this._type&&Math.abs(this._delta)>pi?this._wheelZoomRate:this._defaultZoomRate,i=2/(1+Math.exp(-Math.abs(this._delta*n)));this._delta<0&&0!==i&&(i=1/i);var a="number"==typeof this._targetZoom?r.zoomScale(this._targetZoom):r.scale;this._targetZoom=Math.min(r.maxZoom,Math.max(r.minZoom,r.scaleZoom(a*i))),"wheel"===this._type&&(this._startZoom=r.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var o,s="number"==typeof this._targetZoom?this._targetZoom:r.zoom,l=this._startZoom,u=this._easing,c=!1;if("wheel"===this._type&&l&&u){var f=Math.min((t.browser.now()-this._lastWheelEventTime)/200,1),h=u(f);o=t.number(l,s,h),f<1?this._frameId||(this._frameId=!0):c=!0}else o=s,c=!0;return this._active=!0,c&&(this._active=!1,this._finishTimeout=setTimeout((function(){e._zooming=!1,e._handler._triggerRenderFrame(),delete e._targetZoom,delete e._finishTimeout}),200)),{noInertia:!0,needsRenderFrame:!c,zoomDelta:o-r.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},di.prototype._smoothOutEasing=function(e){var r=t.ease;if(this._prevEase){var n=this._prevEase,i=(t.browser.now()-n.start)/n.duration,a=n.easing(i+.01)-n.easing(i),o=.27/Math.sqrt(a*a+1e-4)*.01,s=Math.sqrt(.0729-o*o);r=t.bezier(o,s,.25,1)}return this._prevEase={start:t.browser.now(),duration:e,easing:r},r},di.prototype.reset=function(){this._active=!1};var vi=function(t,e){this._clickZoom=t,this._tapZoom=e};vi.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},vi.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},vi.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},vi.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var gi=function(){this.reset()};gi.prototype.reset=function(){this._active=!1},gi.prototype.dblclick=function(t,e){return t.preventDefault(),{cameraAnimation:function(r){r.easeTo({duration:300,zoom:r.getZoom()+(t.shiftKey?-1:1),around:r.unproject(e)},{originalEvent:t})}}},gi.prototype.enable=function(){this._enabled=!0},gi.prototype.disable=function(){this._enabled=!1,this.reset()},gi.prototype.isEnabled=function(){return this._enabled},gi.prototype.isActive=function(){return this._active};var yi=function(){this._tap=new Xn({numTouches:1,numTaps:1}),this.reset()};yi.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},yi.prototype.touchstart=function(t,e,r){this._swipePoint||(this._tapTime&&t.timeStamp-this._tapTime>500&&this.reset(),this._tapTime?r.length>0&&(this._swipePoint=e[0],this._swipeTouch=r[0].identifier):this._tap.touchstart(t,e,r))},yi.prototype.touchmove=function(t,e,r){if(this._tapTime){if(this._swipePoint){if(r[0].identifier!==this._swipeTouch)return;var n=e[0],i=n.y-this._swipePoint.y;return this._swipePoint=n,t.preventDefault(),this._active=!0,{zoomDelta:i/128}}}else this._tap.touchmove(t,e,r)},yi.prototype.touchend=function(t,e,r){this._tapTime?this._swipePoint&&0===r.length&&this.reset():this._tap.touchend(t,e,r)&&(this._tapTime=t.timeStamp)},yi.prototype.touchcancel=function(){this.reset()},yi.prototype.enable=function(){this._enabled=!0},yi.prototype.disable=function(){this._enabled=!1,this.reset()},yi.prototype.isEnabled=function(){return this._enabled},yi.prototype.isActive=function(){return this._active};var mi=function(t,e,r){this._el=t,this._mousePan=e,this._touchPan=r};mi.prototype.enable=function(t){this._inertiaOptions=t||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add("mapboxgl-touch-drag-pan")},mi.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove("mapboxgl-touch-drag-pan")},mi.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},mi.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var xi=function(t,e,r){this._pitchWithRotate=t.pitchWithRotate,this._mouseRotate=e,this._mousePitch=r};xi.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},xi.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},xi.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},xi.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var bi=function(t,e,r,n){this._el=t,this._touchZoom=e,this._touchRotate=r,this._tapDragZoom=n,this._rotationDisabled=!1,this._enabled=!0};bi.prototype.enable=function(t){this._touchZoom.enable(t),this._rotationDisabled||this._touchRotate.enable(t),this._tapDragZoom.enable(),this._el.classList.add("mapboxgl-touch-zoom-rotate")},bi.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove("mapboxgl-touch-zoom-rotate")},bi.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},bi.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},bi.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},bi.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var _i=function(t){return t.zoom||t.drag||t.pitch||t.rotate},wi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(t.Event);function Ti(t){return t.panDelta&&t.panDelta.mag()||t.zoomDelta||t.bearingDelta||t.pitchDelta}var ki=function(e,n){this._map=e,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new Bn(e),this._bearingSnap=n.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(n),t.bindAll(["handleEvent","handleWindowEvent"],this);var i=this._el;this._listeners=[[i,"touchstart",{passive:!1}],[i,"touchmove",{passive:!1}],[i,"touchend",void 0],[i,"touchcancel",void 0],[i,"mousedown",void 0],[i,"mousemove",void 0],[i,"mouseup",void 0],[t.window.document,"mousemove",{capture:!0}],[t.window.document,"mouseup",void 0],[i,"mouseover",void 0],[i,"mouseout",void 0],[i,"dblclick",void 0],[i,"click",void 0],[i,"keydown",{capture:!1}],[i,"keyup",void 0],[i,"wheel",{passive:!1}],[i,"contextmenu",void 0],[t.window,"blur",void 0]];for(var a=0,o=this._listeners;a<o.length;a+=1){var s=o[a],l=s[0],u=s[1],c=s[2];r.addEventListener(l,u,l===t.window.document?this.handleWindowEvent:this.handleEvent,c)}};ki.prototype.destroy=function(){for(var e=0,n=this._listeners;e<n.length;e+=1){var i=n[e],a=i[0],o=i[1],s=i[2];r.removeEventListener(a,o,a===t.window.document?this.handleWindowEvent:this.handleEvent,s)}},ki.prototype._addDefaultHandlers=function(t){var e=this._map,r=e.getCanvasContainer();this._add("mapEvent",new qn(e,t));var n=e.boxZoom=new Zn(e,t);this._add("boxZoom",n);var i=new Jn,a=new gi;e.doubleClickZoom=new vi(a,i),this._add("tapZoom",i),this._add("clickZoom",a);var o=new yi;this._add("tapDragZoom",o);var s=e.touchPitch=new ui;this._add("touchPitch",s);var l=new Qn(t),u=new ti(t);e.dragRotate=new xi(t,l,u),this._add("mouseRotate",l,["mousePitch"]),this._add("mousePitch",u,["mouseRotate"]);var c=new $n(t),f=new ei(t);e.dragPan=new mi(r,c,f),this._add("mousePan",c),this._add("touchPan",f,["touchZoom","touchRotate"]);var h=new si,p=new ai;e.touchZoomRotate=new bi(r,p,h,o),this._add("touchRotate",h,["touchPan","touchZoom"]),this._add("touchZoom",p,["touchPan","touchRotate"]);var d=e.scrollZoom=new di(e,this);this._add("scrollZoom",d,["mousePan"]);var v=e.keyboard=new fi;this._add("keyboard",v),this._add("blockableMapEvent",new Gn(e));for(var g=0,y=["boxZoom","doubleClickZoom","tapDragZoom","touchPitch","dragRotate","dragPan","touchZoomRotate","scrollZoom","keyboard"];g<y.length;g+=1){var m=y[g];t.interactive&&t[m]&&e[m].enable(t[m])}},ki.prototype._add=function(t,e,r){this._handlers.push({handlerName:t,handler:e,allowed:r}),this._handlersById[t]=e},ki.prototype.stop=function(){if(!this._updatingCamera){for(var t=0,e=this._handlers;t<e.length;t+=1)e[t].handler.reset();this._inertia.clear(),this._fireEvents({},{}),this._changes=[]}},ki.prototype.isActive=function(){for(var t=0,e=this._handlers;t<e.length;t+=1)if(e[t].handler.isActive())return!0;return!1},ki.prototype.isZooming=function(){return!!this._eventsInProgress.zoom||this._map.scrollZoom.isZooming()},ki.prototype.isRotating=function(){return!!this._eventsInProgress.rotate},ki.prototype.isMoving=function(){return Boolean(_i(this._eventsInProgress))||this.isZooming()},ki.prototype._blockedByActive=function(t,e,r){for(var n in t)if(n!==r&&(!e||e.indexOf(n)<0))return!0;return!1},ki.prototype.handleWindowEvent=function(t){this.handleEvent(t,t.type+"Window")},ki.prototype._getMapTouches=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r],a=i.target;this._el.contains(a)&&e.push(i)}return e},ki.prototype.handleEvent=function(t,e){if("blur"!==t.type){this._updatingCamera=!0;for(var n="renderFrame"===t.type?void 0:t,i={needsRenderFrame:!1},a={},o={},s=t.touches?this._getMapTouches(t.touches):void 0,l=s?r.touchPos(this._el,s):r.mousePos(this._el,t),u=0,c=this._handlers;u<c.length;u+=1){var f=c[u],h=f.handlerName,p=f.handler,d=f.allowed;if(p.isEnabled()){var v=void 0;this._blockedByActive(o,d,h)?p.reset():p[e||t.type]&&(v=p[e||t.type](t,l,s),this.mergeHandlerResult(i,a,v,h,n),v&&v.needsRenderFrame&&this._triggerRenderFrame()),(v||p.isActive())&&(o[h]=p)}}var g={};for(var y in this._previousActiveHandlers)o[y]||(g[y]=n);this._previousActiveHandlers=o,(Object.keys(g).length||Ti(i))&&(this._changes.push([i,a,g]),this._triggerRenderFrame()),(Object.keys(o).length||Ti(i))&&this._map._stop(!0),this._updatingCamera=!1;var m=i.cameraAnimation;m&&(this._inertia.clear(),this._fireEvents({},{}),this._changes=[],m(this._map))}else this.stop()},ki.prototype.mergeHandlerResult=function(e,r,n,i,a){if(n){t.extend(e,n);var o={handlerName:i,originalEvent:n.originalEvent||a};void 0!==n.zoomDelta&&(r.zoom=o),void 0!==n.panDelta&&(r.drag=o),void 0!==n.pitchDelta&&(r.pitch=o),void 0!==n.bearingDelta&&(r.rotate=o)}},ki.prototype._applyChanges=function(){for(var e={},r={},n={},i=0,a=this._changes;i<a.length;i+=1){var o=a[i],s=o[0],l=o[1],u=o[2];s.panDelta&&(e.panDelta=(e.panDelta||new t.Point(0,0))._add(s.panDelta)),s.zoomDelta&&(e.zoomDelta=(e.zoomDelta||0)+s.zoomDelta),s.bearingDelta&&(e.bearingDelta=(e.bearingDelta||0)+s.bearingDelta),s.pitchDelta&&(e.pitchDelta=(e.pitchDelta||0)+s.pitchDelta),void 0!==s.around&&(e.around=s.around),void 0!==s.pinchAround&&(e.pinchAround=s.pinchAround),s.noInertia&&(e.noInertia=s.noInertia),t.extend(r,l),t.extend(n,u)}this._updateMapTransform(e,r,n),this._changes=[]},ki.prototype._updateMapTransform=function(t,e,r){var n=this._map,i=n.transform;if(!Ti(t))return this._fireEvents(e,r);var a=t.panDelta,o=t.zoomDelta,s=t.bearingDelta,l=t.pitchDelta,u=t.around,c=t.pinchAround;void 0!==c&&(u=c),n._stop(!0),u=u||n.transform.centerPoint;var f=i.pointLocation(a?u.sub(a):u);s&&(i.bearing+=s),l&&(i.pitch+=l),o&&(i.zoom+=o),i.setLocationAtPoint(f,u),this._map._update(),t.noInertia||this._inertia.record(t),this._fireEvents(e,r)},ki.prototype._fireEvents=function(e,r){var n=this,i=_i(this._eventsInProgress),a=_i(e),o={};for(var s in e){var l=e[s].originalEvent;this._eventsInProgress[s]||(o[s+"start"]=l),this._eventsInProgress[s]=e[s]}for(var u in!i&&a&&this._fireEvent("movestart",a.originalEvent),o)this._fireEvent(u,o[u]);for(var c in e.rotate&&(this._bearingChanged=!0),a&&this._fireEvent("move",a.originalEvent),e){var f=e[c].originalEvent;this._fireEvent(c,f)}var h,p={};for(var d in this._eventsInProgress){var v=this._eventsInProgress[d],g=v.handlerName,y=v.originalEvent;this._handlersById[g].isActive()||(delete this._eventsInProgress[d],h=r[g]||y,p[d+"end"]=h)}for(var m in p)this._fireEvent(m,p[m]);var x=_i(this._eventsInProgress);if((i||a)&&!x){this._updatingCamera=!0;var b=this._inertia._onMoveEnd(this._map.dragPan._inertiaOptions),_=function(t){return 0!==t&&-n._bearingSnap<t&&t<n._bearingSnap};b?(_(b.bearing||this._map.getBearing())&&(b.bearing=0),this._map.easeTo(b,{originalEvent:h})):(this._map.fire(new t.Event("moveend",{originalEvent:h})),_(this._map.getBearing())&&this._map.resetNorth()),this._bearingChanged=!1,this._updatingCamera=!1}},ki.prototype._fireEvent=function(e,r){this._map.fire(new t.Event(e,r?{originalEvent:r}:{}))},ki.prototype._triggerRenderFrame=function(){var t=this;void 0===this._frameId&&(this._frameId=this._map._requestRenderFrame((function(e){delete t._frameId,t.handleEvent(new wi("renderFrame",{timeStamp:e})),t._applyChanges()})))};var Ai=function(e){function r(r,n){e.call(this),this._moving=!1,this._zooming=!1,this.transform=r,this._bearingSnap=n.bearingSnap,t.bindAll(["_renderFrameCallback"],this)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getCenter=function(){return new t.LngLat(this.transform.center.lng,this.transform.center.lat)},r.prototype.setCenter=function(t,e){return this.jumpTo({center:t},e)},r.prototype.panBy=function(e,r,n){return e=t.Point.convert(e).mult(-1),this.panTo(this.transform.center,t.extend({offset:e},r),n)},r.prototype.panTo=function(e,r,n){return this.easeTo(t.extend({center:e},r),n)},r.prototype.getZoom=function(){return this.transform.zoom},r.prototype.setZoom=function(t,e){return this.jumpTo({zoom:t},e),this},r.prototype.zoomTo=function(e,r,n){return this.easeTo(t.extend({zoom:e},r),n)},r.prototype.zoomIn=function(t,e){return this.zoomTo(this.getZoom()+1,t,e),this},r.prototype.zoomOut=function(t,e){return this.zoomTo(this.getZoom()-1,t,e),this},r.prototype.getBearing=function(){return this.transform.bearing},r.prototype.setBearing=function(t,e){return this.jumpTo({bearing:t},e),this},r.prototype.getPadding=function(){return this.transform.padding},r.prototype.setPadding=function(t,e){return this.jumpTo({padding:t},e),this},r.prototype.rotateTo=function(e,r,n){return this.easeTo(t.extend({bearing:e},r),n)},r.prototype.resetNorth=function(e,r){return this.rotateTo(0,t.extend({duration:1e3},e),r),this},r.prototype.resetNorthPitch=function(e,r){return this.easeTo(t.extend({bearing:0,pitch:0,duration:1e3},e),r),this},r.prototype.snapToNorth=function(t,e){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(t,e):this},r.prototype.getPitch=function(){return this.transform.pitch},r.prototype.setPitch=function(t,e){return this.jumpTo({pitch:t},e),this},r.prototype.cameraForBounds=function(e,r){return e=t.LngLatBounds.convert(e),this._cameraForBoxAndBearing(e.getNorthWest(),e.getSouthEast(),0,r)},r.prototype._cameraForBoxAndBearing=function(e,r,n,i){var a={top:0,bottom:0,right:0,left:0};if("number"==typeof(i=t.extend({padding:a,offset:[0,0],maxZoom:this.transform.maxZoom},i)).padding){var o=i.padding;i.padding={top:o,bottom:o,right:o,left:o}}i.padding=t.extend(a,i.padding);var s=this.transform,l=s.padding,u=s.project(t.LngLat.convert(e)),c=s.project(t.LngLat.convert(r)),f=u.rotate(-n*Math.PI/180),h=c.rotate(-n*Math.PI/180),p=new t.Point(Math.max(f.x,h.x),Math.max(f.y,h.y)),d=new t.Point(Math.min(f.x,h.x),Math.min(f.y,h.y)),v=p.sub(d),g=(s.width-(l.left+l.right+i.padding.left+i.padding.right))/v.x,y=(s.height-(l.top+l.bottom+i.padding.top+i.padding.bottom))/v.y;if(!(y<0||g<0)){var m=Math.min(s.scaleZoom(s.scale*Math.min(g,y)),i.maxZoom),x=t.Point.convert(i.offset),b=(i.padding.left-i.padding.right)/2,_=(i.padding.top-i.padding.bottom)/2,w=new t.Point(x.x+b,x.y+_).mult(s.scale/s.zoomScale(m));return{center:s.unproject(u.add(c).div(2).sub(w)),zoom:m,bearing:n}}t.warnOnce("Map cannot fit within canvas with the given bounds, padding, and/or offset.")},r.prototype.fitBounds=function(t,e,r){return this._fitInternal(this.cameraForBounds(t,e),e,r)},r.prototype.fitScreenCoordinates=function(e,r,n,i,a){return this._fitInternal(this._cameraForBoxAndBearing(this.transform.pointLocation(t.Point.convert(e)),this.transform.pointLocation(t.Point.convert(r)),n,i),i,a)},r.prototype._fitInternal=function(e,r,n){return e?(delete(r=t.extend(e,r)).padding,r.linear?this.easeTo(r,n):this.flyTo(r,n)):this},r.prototype.jumpTo=function(e,r){this.stop();var n=this.transform,i=!1,a=!1,o=!1;return"zoom"in e&&n.zoom!==+e.zoom&&(i=!0,n.zoom=+e.zoom),void 0!==e.center&&(n.center=t.LngLat.convert(e.center)),"bearing"in e&&n.bearing!==+e.bearing&&(a=!0,n.bearing=+e.bearing),"pitch"in e&&n.pitch!==+e.pitch&&(o=!0,n.pitch=+e.pitch),null==e.padding||n.isPaddingEqual(e.padding)||(n.padding=e.padding),this.fire(new t.Event("movestart",r)).fire(new t.Event("move",r)),i&&this.fire(new t.Event("zoomstart",r)).fire(new t.Event("zoom",r)).fire(new t.Event("zoomend",r)),a&&this.fire(new t.Event("rotatestart",r)).fire(new t.Event("rotate",r)).fire(new t.Event("rotateend",r)),o&&this.fire(new t.Event("pitchstart",r)).fire(new t.Event("pitch",r)).fire(new t.Event("pitchend",r)),this.fire(new t.Event("moveend",r))},r.prototype.easeTo=function(e,r){var n=this;this._stop(!1,e.easeId),(!1===(e=t.extend({offset:[0,0],duration:500,easing:t.ease},e)).animate||!e.essential&&t.browser.prefersReducedMotion)&&(e.duration=0);var i=this.transform,a=this.getZoom(),o=this.getBearing(),s=this.getPitch(),l=this.getPadding(),u="zoom"in e?+e.zoom:a,c="bearing"in e?this._normalizeBearing(e.bearing,o):o,f="pitch"in e?+e.pitch:s,h="padding"in e?e.padding:i.padding,p=t.Point.convert(e.offset),d=i.centerPoint.add(p),v=i.pointLocation(d),g=t.LngLat.convert(e.center||v);this._normalizeCenter(g);var y,m,x=i.project(v),b=i.project(g).sub(x),_=i.zoomScale(u-a);e.around&&(y=t.LngLat.convert(e.around),m=i.locationPoint(y));var w={moving:this._moving,zooming:this._zooming,rotating:this._rotating,pitching:this._pitching};return this._zooming=this._zooming||u!==a,this._rotating=this._rotating||o!==c,this._pitching=this._pitching||f!==s,this._padding=!i.isPaddingEqual(h),this._easeId=e.easeId,this._prepareEase(r,e.noMoveStart,w),clearTimeout(this._easeEndTimeoutID),this._ease((function(e){if(n._zooming&&(i.zoom=t.number(a,u,e)),n._rotating&&(i.bearing=t.number(o,c,e)),n._pitching&&(i.pitch=t.number(s,f,e)),n._padding&&(i.interpolatePadding(l,h,e),d=i.centerPoint.add(p)),y)i.setLocationAtPoint(y,m);else{var v=i.zoomScale(i.zoom-a),g=u>a?Math.min(2,_):Math.max(.5,_),w=Math.pow(g,1-e),T=i.unproject(x.add(b.mult(e*w)).mult(v));i.setLocationAtPoint(i.renderWorldCopies?T.wrap():T,d)}n._fireMoveEvents(r)}),(function(t){n._afterEase(r,t)}),e),this},r.prototype._prepareEase=function(e,r,n){void 0===n&&(n={}),this._moving=!0,r||n.moving||this.fire(new t.Event("movestart",e)),this._zooming&&!n.zooming&&this.fire(new t.Event("zoomstart",e)),this._rotating&&!n.rotating&&this.fire(new t.Event("rotatestart",e)),this._pitching&&!n.pitching&&this.fire(new t.Event("pitchstart",e))},r.prototype._fireMoveEvents=function(e){this.fire(new t.Event("move",e)),this._zooming&&this.fire(new t.Event("zoom",e)),this._rotating&&this.fire(new t.Event("rotate",e)),this._pitching&&this.fire(new t.Event("pitch",e))},r.prototype._afterEase=function(e,r){if(!this._easeId||!r||this._easeId!==r){delete this._easeId;var n=this._zooming,i=this._rotating,a=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,n&&this.fire(new t.Event("zoomend",e)),i&&this.fire(new t.Event("rotateend",e)),a&&this.fire(new t.Event("pitchend",e)),this.fire(new t.Event("moveend",e))}},r.prototype.flyTo=function(e,r){var n=this;if(!e.essential&&t.browser.prefersReducedMotion){var i=t.pick(e,["center","zoom","bearing","pitch","around"]);return this.jumpTo(i,r)}this.stop(),e=t.extend({offset:[0,0],speed:1.2,curve:1.42,easing:t.ease},e);var a=this.transform,o=this.getZoom(),s=this.getBearing(),l=this.getPitch(),u=this.getPadding(),c="zoom"in e?t.clamp(+e.zoom,a.minZoom,a.maxZoom):o,f="bearing"in e?this._normalizeBearing(e.bearing,s):s,h="pitch"in e?+e.pitch:l,p="padding"in e?e.padding:a.padding,d=a.zoomScale(c-o),v=t.Point.convert(e.offset),g=a.centerPoint.add(v),y=a.pointLocation(g),m=t.LngLat.convert(e.center||y);this._normalizeCenter(m);var x=a.project(y),b=a.project(m).sub(x),_=e.curve,w=Math.max(a.width,a.height),T=w/d,k=b.mag();if("minZoom"in e){var A=t.clamp(Math.min(e.minZoom,o,c),a.minZoom,a.maxZoom),M=w/a.zoomScale(A-o);_=Math.sqrt(M/k*2)}var S=_*_;function E(t){var e=(T*T-w*w+(t?-1:1)*S*S*k*k)/(2*(t?T:w)*S*k);return Math.log(Math.sqrt(e*e+1)-e)}function L(t){return(Math.exp(t)-Math.exp(-t))/2}function C(t){return(Math.exp(t)+Math.exp(-t))/2}var P=E(0),O=function(t){return C(P)/C(P+_*t)},I=function(t){return w*((C(P)*(L(e=P+_*t)/C(e))-L(P))/S)/k;var e},D=(E(1)-P)/_;if(Math.abs(k)<1e-6||!isFinite(D)){if(Math.abs(w-T)<1e-6)return this.easeTo(e,r);var z=T<w?-1:1;D=Math.abs(Math.log(T/w))/_,I=function(){return 0},O=function(t){return Math.exp(z*_*t)}}if("duration"in e)e.duration=+e.duration;else{var R="screenSpeed"in e?+e.screenSpeed/_:+e.speed;e.duration=1e3*D/R}return e.maxDuration&&e.duration>e.maxDuration&&(e.duration=0),this._zooming=!0,this._rotating=s!==f,this._pitching=h!==l,this._padding=!a.isPaddingEqual(p),this._prepareEase(r,!1),this._ease((function(e){var i=e*D,d=1/O(i);a.zoom=1===e?c:o+a.scaleZoom(d),n._rotating&&(a.bearing=t.number(s,f,e)),n._pitching&&(a.pitch=t.number(l,h,e)),n._padding&&(a.interpolatePadding(u,p,e),g=a.centerPoint.add(v));var y=1===e?m:a.unproject(x.add(b.mult(I(i))).mult(d));a.setLocationAtPoint(a.renderWorldCopies?y.wrap():y,g),n._fireMoveEvents(r)}),(function(){return n._afterEase(r)}),e),this},r.prototype.isEasing=function(){return!!this._easeFrameId},r.prototype.stop=function(){return this._stop()},r.prototype._stop=function(t,e){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var r=this._onEaseEnd;delete this._onEaseEnd,r.call(this,e)}if(!t){var n=this.handlers;n&&n.stop()}return this},r.prototype._ease=function(e,r,n){!1===n.animate||0===n.duration?(e(1),r()):(this._easeStart=t.browser.now(),this._easeOptions=n,this._onEaseFrame=e,this._onEaseEnd=r,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},r.prototype._renderFrameCallback=function(){var e=Math.min((t.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(e)),e<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},r.prototype._normalizeBearing=function(e,r){e=t.wrap(e,-180,180);var n=Math.abs(e-r);return Math.abs(e-360-r)<n&&(e-=360),Math.abs(e+360-r)<n&&(e+=360),e},r.prototype._normalizeCenter=function(t){var e=this.transform;if(e.renderWorldCopies&&!e.lngRange){var r=t.lng-e.center.lng;t.lng+=r>180?-360:r<-180?360:0}},r}(t.Evented),Mi=function(e){void 0===e&&(e={}),this.options=e,t.bindAll(["_updateEditLink","_updateData","_updateCompact"],this)};Mi.prototype.getDefaultPosition=function(){return"bottom-right"},Mi.prototype.onAdd=function(t){var e=this.options&&this.options.compact;return this._map=t,this._container=r.create("div","mapboxgl-ctrl mapboxgl-ctrl-attrib"),this._innerContainer=r.create("div","mapboxgl-ctrl-attrib-inner",this._container),e&&this._container.classList.add("mapboxgl-compact"),this._updateAttributions(),this._updateEditLink(),this._map.on("styledata",this._updateData),this._map.on("sourcedata",this._updateData),this._map.on("moveend",this._updateEditLink),void 0===e&&(this._map.on("resize",this._updateCompact),this._updateCompact()),this._container},Mi.prototype.onRemove=function(){r.remove(this._container),this._map.off("styledata",this._updateData),this._map.off("sourcedata",this._updateData),this._map.off("moveend",this._updateEditLink),this._map.off("resize",this._updateCompact),this._map=void 0,this._attribHTML=void 0},Mi.prototype._updateEditLink=function(){var e=this._editLink;e||(e=this._editLink=this._container.querySelector(".mapbox-improve-map"));var r=[{key:"owner",value:this.styleOwner},{key:"id",value:this.styleId},{key:"access_token",value:this._map._requestManager._customAccessToken||t.config.ACCESS_TOKEN}];if(e){var n=r.reduce((function(t,e,n){return e.value&&(t+=e.key+"="+e.value+(n<r.length-1?"&":"")),t}),"?");e.href=t.config.FEEDBACK_URL+"/"+n+(this._map._hash?this._map._hash.getHashString(!0):""),e.rel="noopener nofollow"}},Mi.prototype._updateData=function(t){!t||"metadata"!==t.sourceDataType&&"style"!==t.dataType||(this._updateAttributions(),this._updateEditLink())},Mi.prototype._updateAttributions=function(){if(this._map.style){var t=[];if(this.options.customAttribution&&(Array.isArray(this.options.customAttribution)?t=t.concat(this.options.customAttribution.map((function(t){return"string"!=typeof t?"":t}))):"string"==typeof this.options.customAttribution&&t.push(this.options.customAttribution)),this._map.style.stylesheet){var e=this._map.style.stylesheet;this.styleOwner=e.owner,this.styleId=e.id}var r=this._map.style.sourceCaches;for(var n in r){var i=r[n];if(i.used){var a=i.getSource();a.attribution&&t.indexOf(a.attribution)<0&&t.push(a.attribution)}}t.sort((function(t,e){return t.length-e.length}));var o=(t=t.filter((function(e,r){for(var n=r+1;n<t.length;n++)if(t[n].indexOf(e)>=0)return!1;return!0}))).join(" | ");o!==this._attribHTML&&(this._attribHTML=o,t.length?(this._innerContainer.innerHTML=o,this._container.classList.remove("mapboxgl-attrib-empty")):this._container.classList.add("mapboxgl-attrib-empty"),this._editLink=null)}},Mi.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add("mapboxgl-compact"):this._container.classList.remove("mapboxgl-compact")};var Si=function(){t.bindAll(["_updateLogo"],this),t.bindAll(["_updateCompact"],this)};Si.prototype.onAdd=function(t){this._map=t,this._container=r.create("div","mapboxgl-ctrl");var e=r.create("a","mapboxgl-ctrl-logo");return e.target="_blank",e.rel="noopener nofollow",e.href="https://www.mapbox.com/",e.setAttribute("aria-label",this._map._getUIString("LogoControl.Title")),e.setAttribute("rel","noopener nofollow"),this._container.appendChild(e),this._container.style.display="none",this._map.on("sourcedata",this._updateLogo),this._updateLogo(),this._map.on("resize",this._updateCompact),this._updateCompact(),this._container},Si.prototype.onRemove=function(){r.remove(this._container),this._map.off("sourcedata",this._updateLogo),this._map.off("resize",this._updateCompact)},Si.prototype.getDefaultPosition=function(){return"bottom-left"},Si.prototype._updateLogo=function(t){t&&"metadata"!==t.sourceDataType||(this._container.style.display=this._logoRequired()?"block":"none")},Si.prototype._logoRequired=function(){if(this._map.style){var t=this._map.style.sourceCaches;for(var e in t)if(t[e].getSource().mapbox_logo)return!0;return!1}},Si.prototype._updateCompact=function(){var t=this._container.children;if(t.length){var e=t[0];this._map.getCanvasContainer().offsetWidth<250?e.classList.add("mapboxgl-compact"):e.classList.remove("mapboxgl-compact")}};var Ei=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};Ei.prototype.add=function(t){var e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e},Ei.prototype.remove=function(t){for(var e=this._currentlyRunning,r=0,n=e?this._queue.concat(e):this._queue;r<n.length;r+=1){var i=n[r];if(i.id===t)return void(i.cancelled=!0)}},Ei.prototype.run=function(t){void 0===t&&(t=0);var e=this._currentlyRunning=this._queue;this._queue=[];for(var r=0,n=e;r<n.length;r+=1){var i=n[r];if(!i.cancelled&&(i.callback(t),this._cleared))break}this._cleared=!1,this._currentlyRunning=!1},Ei.prototype.clear=function(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]};var Li={"FullscreenControl.Enter":"Enter fullscreen","FullscreenControl.Exit":"Exit fullscreen","GeolocateControl.FindMyLocation":"Find my location","GeolocateControl.LocationNotAvailable":"Location not available","LogoControl.Title":"Mapbox logo","NavigationControl.ResetBearing":"Reset bearing to north","NavigationControl.ZoomIn":"Zoom in","NavigationControl.ZoomOut":"Zoom out","ScaleControl.Feet":"ft","ScaleControl.Meters":"m","ScaleControl.Kilometers":"km","ScaleControl.Miles":"mi","ScaleControl.NauticalMiles":"nm"},Ci=t.window.HTMLImageElement,Pi=t.window.HTMLElement,Oi=t.window.ImageBitmap,Ii=60,Di={center:[0,0],zoom:0,bearing:0,pitch:0,minZoom:-2,maxZoom:22,minPitch:0,maxPitch:Ii,interactive:!0,scrollZoom:!0,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,touchPitch:!0,bearingSnap:7,clickTolerance:3,pitchWithRotate:!0,hash:!1,attributionControl:!0,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,trackResize:!0,renderWorldCopies:!0,refreshExpiredTiles:!0,maxTileCacheSize:null,localIdeographFontFamily:"sans-serif",transformRequest:null,accessToken:null,fadeDuration:300,crossSourceCollisions:!0},zi=function(n){function i(e){var r=this;if(null!=(e=t.extend({},Di,e)).minZoom&&null!=e.maxZoom&&e.minZoom>e.maxZoom)throw new Error("maxZoom must be greater than or equal to minZoom");if(null!=e.minPitch&&null!=e.maxPitch&&e.minPitch>e.maxPitch)throw new Error("maxPitch must be greater than or equal to minPitch");if(null!=e.minPitch&&e.minPitch<0)throw new Error("minPitch must be greater than or equal to 0");if(null!=e.maxPitch&&e.maxPitch>Ii)throw new Error("maxPitch must be less than or equal to 60");var i=new Cn(e.minZoom,e.maxZoom,e.minPitch,e.maxPitch,e.renderWorldCopies);if(n.call(this,i,e),this._interactive=e.interactive,this._maxTileCacheSize=e.maxTileCacheSize,this._failIfMajorPerformanceCaveat=e.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=e.preserveDrawingBuffer,this._antialias=e.antialias,this._trackResize=e.trackResize,this._bearingSnap=e.bearingSnap,this._refreshExpiredTiles=e.refreshExpiredTiles,this._fadeDuration=e.fadeDuration,this._crossSourceCollisions=e.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=e.collectResourceTiming,this._renderTaskQueue=new Ei,this._controls=[],this._mapId=t.uniqueId(),this._locale=t.extend({},Li,e.locale),this._requestManager=new t.RequestManager(e.transformRequest,e.accessToken),"string"==typeof e.container){if(this._container=t.window.document.getElementById(e.container),!this._container)throw new Error("Container '"+e.container+"' not found.")}else{if(!(e.container instanceof Pi))throw new Error("Invalid type: 'container' must be a String or HTMLElement.");this._container=e.container}if(e.maxBounds&&this.setMaxBounds(e.maxBounds),t.bindAll(["_onWindowOnline","_onWindowResize","_contextLost","_contextRestored"],this),this._setupContainer(),this._setupPainter(),void 0===this.painter)throw new Error("Failed to initialize WebGL.");this.on("move",(function(){return r._update(!1)})),this.on("moveend",(function(){return r._update(!1)})),this.on("zoom",(function(){return r._update(!0)})),void 0!==t.window&&(t.window.addEventListener("online",this._onWindowOnline,!1),t.window.addEventListener("resize",this._onWindowResize,!1)),this.handlers=new ki(this,e);var a="string"==typeof e.hash&&e.hash||void 0;this._hash=e.hash&&new On(a).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:e.center,zoom:e.zoom,bearing:e.bearing,pitch:e.pitch}),e.bounds&&(this.resize(),this.fitBounds(e.bounds,t.extend({},e.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=e.localIdeographFontFamily,e.style&&this.setStyle(e.style,{localIdeographFontFamily:e.localIdeographFontFamily}),e.attributionControl&&this.addControl(new Mi({customAttribution:e.customAttribution})),this.addControl(new Si,e.logoPosition),this.on("style.load",(function(){r.transform.unmodified&&r.jumpTo(r.style.stylesheet)})),this.on("data",(function(e){r._update("style"===e.dataType),r.fire(new t.Event(e.dataType+"data",e))})),this.on("dataloading",(function(e){r.fire(new t.Event(e.dataType+"dataloading",e))}))}n&&(i.__proto__=n),i.prototype=Object.create(n&&n.prototype),i.prototype.constructor=i;var a={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return i.prototype._getMapId=function(){return this._mapId},i.prototype.addControl=function(e,r){if(void 0===r&&e.getDefaultPosition&&(r=e.getDefaultPosition()),void 0===r&&(r="top-right"),!e||!e.onAdd)return this.fire(new t.ErrorEvent(new Error("Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.")));var n=e.onAdd(this);this._controls.push(e);var i=this._controlPositions[r];return-1!==r.indexOf("bottom")?i.insertBefore(n,i.firstChild):i.appendChild(n),this},i.prototype.removeControl=function(e){if(!e||!e.onRemove)return this.fire(new t.ErrorEvent(new Error("Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.")));var r=this._controls.indexOf(e);return r>-1&&this._controls.splice(r,1),e.onRemove(this),this},i.prototype.resize=function(e){var r=this._containerDimensions(),n=r[0],i=r[1];this._resizeCanvas(n,i),this.transform.resize(n,i),this.painter.resize(n,i);var a=!this._moving;return a&&(this.stop(),this.fire(new t.Event("movestart",e)).fire(new t.Event("move",e))),this.fire(new t.Event("resize",e)),a&&this.fire(new t.Event("moveend",e)),this},i.prototype.getBounds=function(){return this.transform.getBounds()},i.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},i.prototype.setMaxBounds=function(e){return this.transform.setMaxBounds(t.LngLatBounds.convert(e)),this._update()},i.prototype.setMinZoom=function(t){if((t=null==t?-2:t)>=-2&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()<t&&this.setZoom(t),this;throw new Error("minZoom must be between -2 and the current maxZoom, inclusive")},i.prototype.getMinZoom=function(){return this.transform.minZoom},i.prototype.setMaxZoom=function(t){if((t=null==t?22:t)>=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error("maxZoom must be greater than the current minZoom")},i.prototype.getMaxZoom=function(){return this.transform.maxZoom},i.prototype.setMinPitch=function(t){if((t=null==t?0:t)<0)throw new Error("minPitch must be greater than or equal to 0");if(t>=0&&t<=this.transform.maxPitch)return this.transform.minPitch=t,this._update(),this.getPitch()<t&&this.setPitch(t),this;throw new Error("minPitch must be between 0 and the current maxPitch, inclusive")},i.prototype.getMinPitch=function(){return this.transform.minPitch},i.prototype.setMaxPitch=function(t){if((t=null==t?Ii:t)>Ii)throw new Error("maxPitch must be less than or equal to 60");if(t>=this.transform.minPitch)return this.transform.maxPitch=t,this._update(),this.getPitch()>t&&this.setPitch(t),this;throw new Error("maxPitch must be greater than the current minPitch")},i.prototype.getMaxPitch=function(){return this.transform.maxPitch},i.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},i.prototype.setRenderWorldCopies=function(t){return this.transform.renderWorldCopies=t,this._update()},i.prototype.project=function(e){return this.transform.locationPoint(t.LngLat.convert(e))},i.prototype.unproject=function(e){return this.transform.pointLocation(t.Point.convert(e))},i.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},i.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},i.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},i.prototype._createDelegatedListener=function(t,e,r){var n,i=this;if("mouseenter"===t||"mouseover"===t){var a=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){var o=i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[];o.length?a||(a=!0,r.call(i,new Un(t,i,n.originalEvent,{features:o}))):a=!1},mouseout:function(){a=!1}}}}if("mouseleave"===t||"mouseout"===t){var o=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){(i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[]).length?o=!0:o&&(o=!1,r.call(i,new Un(t,i,n.originalEvent)))},mouseout:function(e){o&&(o=!1,r.call(i,new Un(t,i,e.originalEvent)))}}}}return{layer:e,listener:r,delegates:(n={},n[t]=function(t){var n=i.getLayer(e)?i.queryRenderedFeatures(t.point,{layers:[e]}):[];n.length&&(t.features=n,r.call(i,t),delete t.features)},n)}},i.prototype.on=function(t,e,r){if(void 0===r)return n.prototype.on.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(i),i.delegates)this.on(a,i.delegates[a]);return this},i.prototype.once=function(t,e,r){if(void 0===r)return n.prototype.once.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in i.delegates)this.once(a,i.delegates[a]);return this},i.prototype.off=function(t,e,r){var i=this;if(void 0===r)return n.prototype.off.call(this,t,e);return this._delegatedListeners&&this._delegatedListeners[t]&&function(n){for(var a=n[t],o=0;o<a.length;o++){var s=a[o];if(s.layer===e&&s.listener===r){for(var l in s.delegates)i.off(l,s.delegates[l]);return a.splice(o,1),i}}}(this._delegatedListeners),this},i.prototype.queryRenderedFeatures=function(e,r){if(!this.style)return[];var n;if(void 0!==r||void 0===e||e instanceof t.Point||Array.isArray(e)||(r=e,e=void 0),r=r||{},(e=e||[[0,0],[this.transform.width,this.transform.height]])instanceof t.Point||"number"==typeof e[0])n=[t.Point.convert(e)];else{var i=t.Point.convert(e[0]),a=t.Point.convert(e[1]);n=[i,new t.Point(a.x,i.y),a,new t.Point(i.x,a.y),i]}return this.style.queryRenderedFeatures(n,r,this.transform)},i.prototype.querySourceFeatures=function(t,e){return this.style.querySourceFeatures(t,e)},i.prototype.setStyle=function(e,r){return!1!==(r=t.extend({},{localIdeographFontFamily:this._localIdeographFontFamily},r)).diff&&r.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&e?(this._diffStyle(e,r),this):(this._localIdeographFontFamily=r.localIdeographFontFamily,this._updateStyle(e,r))},i.prototype._getUIString=function(t){var e=this._locale[t];if(null==e)throw new Error("Missing UI string '"+t+"'");return e},i.prototype._updateStyle=function(t,e){return this.style&&(this.style.setEventedParent(null),this.style._remove()),t?(this.style=new Ye(this,e||{}),this.style.setEventedParent(this,{style:this.style}),"string"==typeof t?this.style.loadURL(t):this.style.loadJSON(t),this):(delete this.style,this)},i.prototype._lazyInitEmptyStyle=function(){this.style||(this.style=new Ye(this,{}),this.style.setEventedParent(this,{style:this.style}),this.style.loadEmpty())},i.prototype._diffStyle=function(e,r){var n=this;if("string"==typeof e){var i=this._requestManager.normalizeStyleURL(e),a=this._requestManager.transformRequest(i,t.ResourceType.Style);t.getJSON(a,(function(e,i){e?n.fire(new t.ErrorEvent(e)):i&&n._updateDiff(i,r)}))}else"object"==typeof e&&this._updateDiff(e,r)},i.prototype._updateDiff=function(e,r){try{this.style.setState(e)&&this._update(!0)}catch(n){t.warnOnce("Unable to perform style diff: "+(n.message||n.error||n)+".  Rebuilding the style from scratch."),this._updateStyle(e,r)}},i.prototype.getStyle=function(){if(this.style)return this.style.serialize()},i.prototype.isStyleLoaded=function(){return this.style?this.style.loaded():t.warnOnce("There is no style added to the map.")},i.prototype.addSource=function(t,e){return this._lazyInitEmptyStyle(),this.style.addSource(t,e),this._update(!0)},i.prototype.isSourceLoaded=function(e){var r=this.style&&this.style.sourceCaches[e];if(void 0!==r)return r.loaded();this.fire(new t.ErrorEvent(new Error("There is no source with ID '"+e+"'")))},i.prototype.areTilesLoaded=function(){var t=this.style&&this.style.sourceCaches;for(var e in t){var r=t[e]._tiles;for(var n in r){var i=r[n];if("loaded"!==i.state&&"errored"!==i.state)return!1}}return!0},i.prototype.addSourceType=function(t,e,r){return this._lazyInitEmptyStyle(),this.style.addSourceType(t,e,r)},i.prototype.removeSource=function(t){return this.style.removeSource(t),this._update(!0)},i.prototype.getSource=function(t){return this.style.getSource(t)},i.prototype.addImage=function(e,r,n){void 0===n&&(n={});var i=n.pixelRatio;void 0===i&&(i=1);var a=n.sdf;void 0===a&&(a=!1);var o=n.stretchX,s=n.stretchY,l=n.content;this._lazyInitEmptyStyle();if(r instanceof Ci||Oi&&r instanceof Oi){var u=t.browser.getImageData(r),c=u.width,f=u.height,h=u.data;this.style.addImage(e,{data:new t.RGBAImage({width:c,height:f},h),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0})}else{if(void 0===r.width||void 0===r.height)return this.fire(new t.ErrorEvent(new Error("Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`")));var p=r.width,d=r.height,v=r.data,g=r;this.style.addImage(e,{data:new t.RGBAImage({width:p,height:d},new Uint8Array(v)),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0,userImage:g}),g.onAdd&&g.onAdd(this,e)}},i.prototype.updateImage=function(e,r){var n=this.style.getImage(e);if(!n)return this.fire(new t.ErrorEvent(new Error("The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.")));var i=r instanceof Ci||Oi&&r instanceof Oi?t.browser.getImageData(r):r,a=i.width,o=i.height,s=i.data;if(void 0===a||void 0===o)return this.fire(new t.ErrorEvent(new Error("Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`")));if(a!==n.data.width||o!==n.data.height)return this.fire(new t.ErrorEvent(new Error("The width and height of the updated image must be that same as the previous version of the image")));var l=!(r instanceof Ci||Oi&&r instanceof Oi);n.data.replace(s,l),this.style.updateImage(e,n)},i.prototype.hasImage=function(e){return e?!!this.style.getImage(e):(this.fire(new t.ErrorEvent(new Error("Missing required image id"))),!1)},i.prototype.removeImage=function(t){this.style.removeImage(t)},i.prototype.loadImage=function(e,r){t.getImage(this._requestManager.transformRequest(e,t.ResourceType.Image),r)},i.prototype.listImages=function(){return this.style.listImages()},i.prototype.addLayer=function(t,e){return this._lazyInitEmptyStyle(),this.style.addLayer(t,e),this._update(!0)},i.prototype.moveLayer=function(t,e){return this.style.moveLayer(t,e),this._update(!0)},i.prototype.removeLayer=function(t){return this.style.removeLayer(t),this._update(!0)},i.prototype.getLayer=function(t){return this.style.getLayer(t)},i.prototype.setLayerZoomRange=function(t,e,r){return this.style.setLayerZoomRange(t,e,r),this._update(!0)},i.prototype.setFilter=function(t,e,r){return void 0===r&&(r={}),this.style.setFilter(t,e,r),this._update(!0)},i.prototype.getFilter=function(t){return this.style.getFilter(t)},i.prototype.setPaintProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setPaintProperty(t,e,r,n),this._update(!0)},i.prototype.getPaintProperty=function(t,e){return this.style.getPaintProperty(t,e)},i.prototype.setLayoutProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setLayoutProperty(t,e,r,n),this._update(!0)},i.prototype.getLayoutProperty=function(t,e){return this.style.getLayoutProperty(t,e)},i.prototype.setLight=function(t,e){return void 0===e&&(e={}),this._lazyInitEmptyStyle(),this.style.setLight(t,e),this._update(!0)},i.prototype.getLight=function(){return this.style.getLight()},i.prototype.setFeatureState=function(t,e){return this.style.setFeatureState(t,e),this._update()},i.prototype.removeFeatureState=function(t,e){return this.style.removeFeatureState(t,e),this._update()},i.prototype.getFeatureState=function(t){return this.style.getFeatureState(t)},i.prototype.getContainer=function(){return this._container},i.prototype.getCanvasContainer=function(){return this._canvasContainer},i.prototype.getCanvas=function(){return this._canvas},i.prototype._containerDimensions=function(){var t=0,e=0;return this._container&&(t=this._container.clientWidth||400,e=this._container.clientHeight||300),[t,e]},i.prototype._detectMissingCSS=function(){"rgb(250, 128, 114)"!==t.window.getComputedStyle(this._missingCSSCanary).getPropertyValue("background-color")&&t.warnOnce("This page appears to be missing CSS declarations for Mapbox GL JS, which may cause the map to display incorrectly. Please ensure your page includes mapbox-gl.css, as described in https://www.mapbox.com/mapbox-gl-js/api/.")},i.prototype._setupContainer=function(){var t=this._container;t.classList.add("mapboxgl-map"),(this._missingCSSCanary=r.create("div","mapboxgl-canary",t)).style.visibility="hidden",this._detectMissingCSS();var e=this._canvasContainer=r.create("div","mapboxgl-canvas-container",t);this._interactive&&e.classList.add("mapboxgl-interactive"),this._canvas=r.create("canvas","mapboxgl-canvas",e),this._canvas.addEventListener("webglcontextlost",this._contextLost,!1),this._canvas.addEventListener("webglcontextrestored",this._contextRestored,!1),this._canvas.setAttribute("tabindex","0"),this._canvas.setAttribute("aria-label","Map");var n=this._containerDimensions();this._resizeCanvas(n[0],n[1]);var i=this._controlContainer=r.create("div","mapboxgl-control-container",t),a=this._controlPositions={};["top-left","top-right","bottom-left","bottom-right"].forEach((function(t){a[t]=r.create("div","mapboxgl-ctrl-"+t,i)}))},i.prototype._resizeCanvas=function(e,r){var n=t.browser.devicePixelRatio||1;this._canvas.width=n*e,this._canvas.height=n*r,this._canvas.style.width=e+"px",this._canvas.style.height=r+"px"},i.prototype._setupPainter=function(){var r=t.extend({},e.webGLContextAttributes,{failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1}),n=this._canvas.getContext("webgl",r)||this._canvas.getContext("experimental-webgl",r);n?(this.painter=new Mn(n,this.transform),t.webpSupported.testSupport(n)):this.fire(new t.ErrorEvent(new Error("Failed to initialize WebGL")))},i.prototype._contextLost=function(e){e.preventDefault(),this._frame&&(this._frame.cancel(),this._frame=null),this.fire(new t.Event("webglcontextlost",{originalEvent:e}))},i.prototype._contextRestored=function(e){this._setupPainter(),this.resize(),this._update(),this.fire(new t.Event("webglcontextrestored",{originalEvent:e}))},i.prototype.loaded=function(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()},i.prototype._update=function(t){return this.style?(this._styleDirty=this._styleDirty||t,this._sourcesDirty=!0,this.triggerRepaint(),this):this},i.prototype._requestRenderFrame=function(t){return this._update(),this._renderTaskQueue.add(t)},i.prototype._cancelRenderFrame=function(t){this._renderTaskQueue.remove(t)},i.prototype._render=function(e){var r,n=this,i=0,a=this.painter.context.extTimerQuery;if(this.listens("gpu-timing-frame")&&(r=a.createQueryEXT(),a.beginQueryEXT(a.TIME_ELAPSED_EXT,r),i=t.browser.now()),this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run(e),!this._removed){var o=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;var s=this.transform.zoom,l=t.browser.now();this.style.zoomHistory.update(s,l);var u=new t.EvaluationParameters(s,{now:l,fadeDuration:this._fadeDuration,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),c=u.crossFadingFactor();1===c&&c===this._crossFadingFactor||(o=!0,this._crossFadingFactor=c),this.style.update(u)}if(this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,this._fadeDuration,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:this._fadeDuration,showPadding:this.showPadding,gpuTiming:!!this.listens("gpu-timing-layer")}),this.fire(new t.Event("render")),this.loaded()&&!this._loaded&&(this._loaded=!0,this.fire(new t.Event("load"))),this.style&&(this.style.hasTransitions()||o)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles(),this.listens("gpu-timing-frame")){var f=t.browser.now()-i;a.endQueryEXT(a.TIME_ELAPSED_EXT,r),setTimeout((function(){var e=a.getQueryObjectEXT(r,a.QUERY_RESULT_EXT)/1e6;a.deleteQueryEXT(r),n.fire(new t.Event("gpu-timing-frame",{cpuTime:f,gpuTime:e}))}),50)}if(this.listens("gpu-timing-layer")){var h=this.painter.collectGpuTimers();setTimeout((function(){var e=n.painter.queryGpuTimers(h);n.fire(new t.Event("gpu-timing-layer",{layerTimes:e}))}),50)}return this._sourcesDirty||this._styleDirty||this._placementDirty||this._repaint?this.triggerRepaint():!this.isMoving()&&this.loaded()&&(this._fullyLoaded||(this._fullyLoaded=!0),this.fire(new t.Event("idle"))),this}},i.prototype.remove=function(){this._hash&&this._hash.remove();for(var e=0,r=this._controls;e<r.length;e+=1)r[e].onRemove(this);this._controls=[],this._frame&&(this._frame.cancel(),this._frame=null),this._renderTaskQueue.clear(),this.painter.destroy(),this.handlers.destroy(),delete this.handlers,this.setStyle(null),void 0!==t.window&&(t.window.removeEventListener("resize",this._onWindowResize,!1),t.window.removeEventListener("online",this._onWindowOnline,!1));var n=this.painter.context.gl.getExtension("WEBGL_lose_context");n&&n.loseContext(),Ri(this._canvasContainer),Ri(this._controlContainer),Ri(this._missingCSSCanary),this._container.classList.remove("mapboxgl-map"),this._removed=!0,this.fire(new t.Event("remove"))},i.prototype.triggerRepaint=function(){var e=this;this.style&&!this._frame&&(this._frame=t.browser.frame((function(t){e._frame=null,e._render(t)})))},i.prototype._onWindowOnline=function(){this._update()},i.prototype._onWindowResize=function(t){this._trackResize&&this.resize({originalEvent:t})._update()},a.showTileBoundaries.get=function(){return!!this._showTileBoundaries},a.showTileBoundaries.set=function(t){this._showTileBoundaries!==t&&(this._showTileBoundaries=t,this._update())},a.showPadding.get=function(){return!!this._showPadding},a.showPadding.set=function(t){this._showPadding!==t&&(this._showPadding=t,this._update())},a.showCollisionBoxes.get=function(){return!!this._showCollisionBoxes},a.showCollisionBoxes.set=function(t){this._showCollisionBoxes!==t&&(this._showCollisionBoxes=t,t?this.style._generateCollisionBoxes():this._update())},a.showOverdrawInspector.get=function(){return!!this._showOverdrawInspector},a.showOverdrawInspector.set=function(t){this._showOverdrawInspector!==t&&(this._showOverdrawInspector=t,this._update())},a.repaint.get=function(){return!!this._repaint},a.repaint.set=function(t){this._repaint!==t&&(this._repaint=t,this.triggerRepaint())},a.vertices.get=function(){return!!this._vertices},a.vertices.set=function(t){this._vertices=t,this._update()},i.prototype._setCacheLimits=function(e,r){t.setCacheLimits(e,r)},a.version.get=function(){return t.version},Object.defineProperties(i.prototype,a),i}(Ai);function Ri(t){t.parentNode&&t.parentNode.removeChild(t)}var Fi={showCompass:!0,showZoom:!0,visualizePitch:!1},Bi=function(e){var n=this;this.options=t.extend({},Fi,e),this._container=r.create("div","mapboxgl-ctrl mapboxgl-ctrl-group"),this._container.addEventListener("contextmenu",(function(t){return t.preventDefault()})),this.options.showZoom&&(t.bindAll(["_setButtonTitle","_updateZoomButtons"],this),this._zoomInButton=this._createButton("mapboxgl-ctrl-zoom-in",(function(t){return n._map.zoomIn({},{originalEvent:t})})),r.create("span","mapboxgl-ctrl-icon",this._zoomInButton).setAttribute("aria-hidden",!0),this._zoomOutButton=this._createButton("mapboxgl-ctrl-zoom-out",(function(t){return n._map.zoomOut({},{originalEvent:t})})),r.create("span","mapboxgl-ctrl-icon",this._zoomOutButton).setAttribute("aria-hidden",!0)),this.options.showCompass&&(t.bindAll(["_rotateCompassArrow"],this),this._compass=this._createButton("mapboxgl-ctrl-compass",(function(t){n.options.visualizePitch?n._map.resetNorthPitch({},{originalEvent:t}):n._map.resetNorth({},{originalEvent:t})})),this._compassIcon=r.create("span","mapboxgl-ctrl-icon",this._compass),this._compassIcon.setAttribute("aria-hidden",!0))};Bi.prototype._updateZoomButtons=function(){var t=this._map.getZoom();this._zoomInButton.disabled=t===this._map.getMaxZoom(),this._zoomOutButton.disabled=t===this._map.getMinZoom()},Bi.prototype._rotateCompassArrow=function(){var t=this.options.visualizePitch?"scale("+1/Math.pow(Math.cos(this._map.transform.pitch*(Math.PI/180)),.5)+") rotateX("+this._map.transform.pitch+"deg) rotateZ("+this._map.transform.angle*(180/Math.PI)+"deg)":"rotate("+this._map.transform.angle*(180/Math.PI)+"deg)";this._compassIcon.style.transform=t},Bi.prototype.onAdd=function(t){return this._map=t,this.options.showZoom&&(this._setButtonTitle(this._zoomInButton,"ZoomIn"),this._setButtonTitle(this._zoomOutButton,"ZoomOut"),this._map.on("zoom",this._updateZoomButtons),this._updateZoomButtons()),this.options.showCompass&&(this._setButtonTitle(this._compass,"ResetBearing"),this.options.visualizePitch&&this._map.on("pitch",this._rotateCompassArrow),this._map.on("rotate",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new Ni(this._map,this._compass,this.options.visualizePitch)),this._container},Bi.prototype.onRemove=function(){r.remove(this._container),this.options.showZoom&&this._map.off("zoom",this._updateZoomButtons),this.options.showCompass&&(this.options.visualizePitch&&this._map.off("pitch",this._rotateCompassArrow),this._map.off("rotate",this._rotateCompassArrow),this._handler.off(),delete this._handler),delete this._map},Bi.prototype._createButton=function(t,e){var n=r.create("button",t,this._container);return n.type="button",n.addEventListener("click",e),n},Bi.prototype._setButtonTitle=function(t,e){var r=this._map._getUIString("NavigationControl."+e);t.title=r,t.setAttribute("aria-label",r)};var Ni=function(e,n,i){void 0===i&&(i=!1),this._clickTolerance=10,this.element=n,this.mouseRotate=new Qn({clickTolerance:e.dragRotate._mouseRotate._clickTolerance}),this.map=e,i&&(this.mousePitch=new ti({clickTolerance:e.dragRotate._mousePitch._clickTolerance})),t.bindAll(["mousedown","mousemove","mouseup","touchstart","touchmove","touchend","reset"],this),r.addEventListener(n,"mousedown",this.mousedown),r.addEventListener(n,"touchstart",this.touchstart,{passive:!1}),r.addEventListener(n,"touchmove",this.touchmove),r.addEventListener(n,"touchend",this.touchend),r.addEventListener(n,"touchcancel",this.reset)};function ji(e,r,n){if(e=new t.LngLat(e.lng,e.lat),r){var i=new t.LngLat(e.lng-360,e.lat),a=new t.LngLat(e.lng+360,e.lat),o=n.locationPoint(e).distSqr(r);n.locationPoint(i).distSqr(r)<o?e=i:n.locationPoint(a).distSqr(r)<o&&(e=a)}for(;Math.abs(e.lng-n.center.lng)>180;){var s=n.locationPoint(e);if(s.x>=0&&s.y>=0&&s.x<=n.width&&s.y<=n.height)break;e.lng>n.center.lng?e.lng-=360:e.lng+=360}return e}Ni.prototype.down=function(t,e){this.mouseRotate.mousedown(t,e),this.mousePitch&&this.mousePitch.mousedown(t,e),r.disableDrag()},Ni.prototype.move=function(t,e){var r=this.map,n=this.mouseRotate.mousemoveWindow(t,e);if(n&&n.bearingDelta&&r.setBearing(r.getBearing()+n.bearingDelta),this.mousePitch){var i=this.mousePitch.mousemoveWindow(t,e);i&&i.pitchDelta&&r.setPitch(r.getPitch()+i.pitchDelta)}},Ni.prototype.off=function(){var t=this.element;r.removeEventListener(t,"mousedown",this.mousedown),r.removeEventListener(t,"touchstart",this.touchstart,{passive:!1}),r.removeEventListener(t,"touchmove",this.touchmove),r.removeEventListener(t,"touchend",this.touchend),r.removeEventListener(t,"touchcancel",this.reset),this.offTemp()},Ni.prototype.offTemp=function(){r.enableDrag(),r.removeEventListener(t.window,"mousemove",this.mousemove),r.removeEventListener(t.window,"mouseup",this.mouseup)},Ni.prototype.mousedown=function(e){this.down(t.extend({},e,{ctrlKey:!0,preventDefault:function(){return e.preventDefault()}}),r.mousePos(this.element,e)),r.addEventListener(t.window,"mousemove",this.mousemove),r.addEventListener(t.window,"mouseup",this.mouseup)},Ni.prototype.mousemove=function(t){this.move(t,r.mousePos(this.element,t))},Ni.prototype.mouseup=function(t){this.mouseRotate.mouseupWindow(t),this.mousePitch&&this.mousePitch.mouseupWindow(t),this.offTemp()},Ni.prototype.touchstart=function(t){1!==t.targetTouches.length?this.reset():(this._startPos=this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.down({type:"mousedown",button:0,ctrlKey:!0,preventDefault:function(){return t.preventDefault()}},this._startPos))},Ni.prototype.touchmove=function(t){1!==t.targetTouches.length?this.reset():(this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.move({preventDefault:function(){return t.preventDefault()}},this._lastPos))},Ni.prototype.touchend=function(t){0===t.targetTouches.length&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos)<this._clickTolerance&&this.element.click(),this.reset()},Ni.prototype.reset=function(){this.mouseRotate.reset(),this.mousePitch&&this.mousePitch.reset(),delete this._startPos,delete this._lastPos,this.offTemp()};var Ui={center:"translate(-50%,-50%)",top:"translate(-50%,0)","top-left":"translate(0,0)","top-right":"translate(-100%,0)",bottom:"translate(-50%,-100%)","bottom-left":"translate(0,-100%)","bottom-right":"translate(-100%,-100%)",left:"translate(0,-50%)",right:"translate(-100%,-50%)"};function Vi(t,e,r){var n=t.classList;for(var i in Ui)n.remove("mapboxgl-"+r+"-anchor-"+i);n.add("mapboxgl-"+r+"-anchor-"+e)}var Hi,qi=function(e){function n(n,i){var a=this;if(e.call(this),(n instanceof t.window.HTMLElement||i)&&(n=t.extend({element:n},i)),t.bindAll(["_update","_onMove","_onUp","_addDragHandler","_onMapClick","_onKeyPress"],this),this._anchor=n&&n.anchor||"center",this._color=n&&n.color||"#3FB1CE",this._draggable=n&&n.draggable||!1,this._state="inactive",this._rotation=n&&n.rotation||0,this._rotationAlignment=n&&n.rotationAlignment||"auto",this._pitchAlignment=n&&n.pitchAlignment&&"auto"!==n.pitchAlignment?n.pitchAlignment:this._rotationAlignment,n&&n.element)this._element=n.element,this._offset=t.Point.convert(n&&n.offset||[0,0]);else{this._defaultMarker=!0,this._element=r.create("div"),this._element.setAttribute("aria-label","Map marker");var o=r.createNS("http://www.w3.org/2000/svg","svg");o.setAttributeNS(null,"display","block"),o.setAttributeNS(null,"height","41px"),o.setAttributeNS(null,"width","27px"),o.setAttributeNS(null,"viewBox","0 0 27 41");var s=r.createNS("http://www.w3.org/2000/svg","g");s.setAttributeNS(null,"stroke","none"),s.setAttributeNS(null,"stroke-width","1"),s.setAttributeNS(null,"fill","none"),s.setAttributeNS(null,"fill-rule","evenodd");var l=r.createNS("http://www.w3.org/2000/svg","g");l.setAttributeNS(null,"fill-rule","nonzero");var u=r.createNS("http://www.w3.org/2000/svg","g");u.setAttributeNS(null,"transform","translate(3.0, 29.0)"),u.setAttributeNS(null,"fill","#000000");for(var c=0,f=[{rx:"10.5",ry:"5.25002273"},{rx:"10.5",ry:"5.25002273"},{rx:"9.5",ry:"4.77275007"},{rx:"8.5",ry:"4.29549936"},{rx:"7.5",ry:"3.81822308"},{rx:"6.5",ry:"3.34094679"},{rx:"5.5",ry:"2.86367051"},{rx:"4.5",ry:"2.38636864"}];c<f.length;c+=1){var h=f[c],p=r.createNS("http://www.w3.org/2000/svg","ellipse");p.setAttributeNS(null,"opacity","0.04"),p.setAttributeNS(null,"cx","10.5"),p.setAttributeNS(null,"cy","5.80029008"),p.setAttributeNS(null,"rx",h.rx),p.setAttributeNS(null,"ry",h.ry),u.appendChild(p)}var d=r.createNS("http://www.w3.org/2000/svg","g");d.setAttributeNS(null,"fill",this._color);var v=r.createNS("http://www.w3.org/2000/svg","path");v.setAttributeNS(null,"d","M27,13.5 C27,19.074644 20.250001,27.000002 14.75,34.500002 C14.016665,35.500004 12.983335,35.500004 12.25,34.500002 C6.7499993,27.000002 0,19.222562 0,13.5 C0,6.0441559 6.0441559,0 13.5,0 C20.955844,0 27,6.0441559 27,13.5 Z"),d.appendChild(v);var g=r.createNS("http://www.w3.org/2000/svg","g");g.setAttributeNS(null,"opacity","0.25"),g.setAttributeNS(null,"fill","#000000");var y=r.createNS("http://www.w3.org/2000/svg","path");y.setAttributeNS(null,"d","M13.5,0 C6.0441559,0 0,6.0441559 0,13.5 C0,19.222562 6.7499993,27 12.25,34.5 C13,35.522727 14.016664,35.500004 14.75,34.5 C20.250001,27 27,19.074644 27,13.5 C27,6.0441559 20.955844,0 13.5,0 Z M13.5,1 C20.415404,1 26,6.584596 26,13.5 C26,15.898657 24.495584,19.181431 22.220703,22.738281 C19.945823,26.295132 16.705119,30.142167 13.943359,33.908203 C13.743445,34.180814 13.612715,34.322738 13.5,34.441406 C13.387285,34.322738 13.256555,34.180814 13.056641,33.908203 C10.284481,30.127985 7.4148684,26.314159 5.015625,22.773438 C2.6163816,19.232715 1,15.953538 1,13.5 C1,6.584596 6.584596,1 13.5,1 Z"),g.appendChild(y);var m=r.createNS("http://www.w3.org/2000/svg","g");m.setAttributeNS(null,"transform","translate(6.0, 7.0)"),m.setAttributeNS(null,"fill","#FFFFFF");var x=r.createNS("http://www.w3.org/2000/svg","g");x.setAttributeNS(null,"transform","translate(8.0, 8.0)");var b=r.createNS("http://www.w3.org/2000/svg","circle");b.setAttributeNS(null,"fill","#000000"),b.setAttributeNS(null,"opacity","0.25"),b.setAttributeNS(null,"cx","5.5"),b.setAttributeNS(null,"cy","5.5"),b.setAttributeNS(null,"r","5.4999962");var _=r.createNS("http://www.w3.org/2000/svg","circle");_.setAttributeNS(null,"fill","#FFFFFF"),_.setAttributeNS(null,"cx","5.5"),_.setAttributeNS(null,"cy","5.5"),_.setAttributeNS(null,"r","5.4999962"),x.appendChild(b),x.appendChild(_),l.appendChild(u),l.appendChild(d),l.appendChild(g),l.appendChild(m),l.appendChild(x),o.appendChild(l),this._element.appendChild(o),this._offset=t.Point.convert(n&&n.offset||[0,-14])}this._element.classList.add("mapboxgl-marker"),this._element.addEventListener("dragstart",(function(t){t.preventDefault()})),this._element.addEventListener("mousedown",(function(t){t.preventDefault()})),this._element.addEventListener("focus",(function(){var t=a._map.getContainer();t.scrollTop=0,t.scrollLeft=0})),Vi(this._element,this._anchor,"marker"),this._popup=null}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(t){return this.remove(),this._map=t,t.getCanvasContainer().appendChild(this._element),t.on("move",this._update),t.on("moveend",this._update),this.setDraggable(this._draggable),this._update(),this._map.on("click",this._onMapClick),this},n.prototype.remove=function(){return this._map&&(this._map.off("click",this._onMapClick),this._map.off("move",this._update),this._map.off("moveend",this._update),this._map.off("mousedown",this._addDragHandler),this._map.off("touchstart",this._addDragHandler),this._map.off("mouseup",this._onUp),this._map.off("touchend",this._onUp),this._map.off("mousemove",this._onMove),this._map.off("touchmove",this._onMove),delete this._map),r.remove(this._element),this._popup&&this._popup.remove(),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this},n.prototype.getElement=function(){return this._element},n.prototype.setPopup=function(t){if(this._popup&&(this._popup.remove(),this._popup=null,this._element.removeEventListener("keypress",this._onKeyPress),this._originalTabIndex||this._element.removeAttribute("tabindex")),t){if(!("offset"in t.options)){var e=13.5,r=Math.sqrt(Math.pow(e,2)/2);t.options.offset=this._defaultMarker?{top:[0,0],"top-left":[0,0],"top-right":[0,0],bottom:[0,-38.1],"bottom-left":[r,-1*(24.6+r)],"bottom-right":[-r,-1*(24.6+r)],left:[e,-24.6],right:[-13.5,-24.6]}:this._offset}this._popup=t,this._lngLat&&this._popup.setLngLat(this._lngLat),this._originalTabIndex=this._element.getAttribute("tabindex"),this._originalTabIndex||this._element.setAttribute("tabindex","0"),this._element.addEventListener("keypress",this._onKeyPress)}return this},n.prototype._onKeyPress=function(t){var e=t.code,r=t.charCode||t.keyCode;"Space"!==e&&"Enter"!==e&&32!==r&&13!==r||this.togglePopup()},n.prototype._onMapClick=function(t){var e=t.originalEvent.target,r=this._element;this._popup&&(e===r||r.contains(e))&&this.togglePopup()},n.prototype.getPopup=function(){return this._popup},n.prototype.togglePopup=function(){var t=this._popup;return t?(t.isOpen()?t.remove():t.addTo(this._map),this):this},n.prototype._update=function(t){if(this._map){this._map.transform.renderWorldCopies&&(this._lngLat=ji(this._lngLat,this._pos,this._map.transform)),this._pos=this._map.project(this._lngLat)._add(this._offset);var e="";"viewport"===this._rotationAlignment||"auto"===this._rotationAlignment?e="rotateZ("+this._rotation+"deg)":"map"===this._rotationAlignment&&(e="rotateZ("+(this._rotation-this._map.getBearing())+"deg)");var n="";"viewport"===this._pitchAlignment||"auto"===this._pitchAlignment?n="rotateX(0deg)":"map"===this._pitchAlignment&&(n="rotateX("+this._map.getPitch()+"deg)"),t&&"moveend"!==t.type||(this._pos=this._pos.round()),r.setTransform(this._element,Ui[this._anchor]+" translate("+this._pos.x+"px, "+this._pos.y+"px) "+n+" "+e)}},n.prototype.getOffset=function(){return this._offset},n.prototype.setOffset=function(e){return this._offset=t.Point.convert(e),this._update(),this},n.prototype._onMove=function(e){this._pos=e.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents="none","pending"===this._state&&(this._state="active",this.fire(new t.Event("dragstart"))),this.fire(new t.Event("drag"))},n.prototype._onUp=function(){this._element.style.pointerEvents="auto",this._positionDelta=null,this._map.off("mousemove",this._onMove),this._map.off("touchmove",this._onMove),"active"===this._state&&this.fire(new t.Event("dragend")),this._state="inactive"},n.prototype._addDragHandler=function(t){this._element.contains(t.originalEvent.target)&&(t.preventDefault(),this._positionDelta=t.point.sub(this._pos).add(this._offset),this._state="pending",this._map.on("mousemove",this._onMove),this._map.on("touchmove",this._onMove),this._map.once("mouseup",this._onUp),this._map.once("touchend",this._onUp))},n.prototype.setDraggable=function(t){return this._draggable=!!t,this._map&&(t?(this._map.on("mousedown",this._addDragHandler),this._map.on("touchstart",this._addDragHandler)):(this._map.off("mousedown",this._addDragHandler),this._map.off("touchstart",this._addDragHandler))),this},n.prototype.isDraggable=function(){return this._draggable},n.prototype.setRotation=function(t){return this._rotation=t||0,this._update(),this},n.prototype.getRotation=function(){return this._rotation},n.prototype.setRotationAlignment=function(t){return this._rotationAlignment=t||"auto",this._update(),this},n.prototype.getRotationAlignment=function(){return this._rotationAlignment},n.prototype.setPitchAlignment=function(t){return this._pitchAlignment=t&&"auto"!==t?t:this._rotationAlignment,this._update(),this},n.prototype.getPitchAlignment=function(){return this._pitchAlignment},n}(t.Evented),Gi={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0};var Zi=0,Yi=!1,Wi=function(e){function n(r){e.call(this),this.options=t.extend({},Gi,r),t.bindAll(["_onSuccess","_onError","_onZoom","_finish","_setupUI","_updateCamera","_updateMarker"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.onAdd=function(e){return this._map=e,this._container=r.create("div","mapboxgl-ctrl mapboxgl-ctrl-group"),n=this._setupUI,void 0!==Hi?n(Hi):void 0!==t.window.navigator.permissions?t.window.navigator.permissions.query({name:"geolocation"}).then((function(t){Hi="denied"!==t.state,n(Hi)})):(Hi=!!t.window.navigator.geolocation,n(Hi)),this._container;var n},n.prototype.onRemove=function(){void 0!==this._geolocationWatchID&&(t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),r.remove(this._container),this._map.off("zoom",this._onZoom),this._map=void 0,Zi=0,Yi=!1},n.prototype._isOutOfMapMaxBounds=function(t){var e=this._map.getMaxBounds(),r=t.coords;return e&&(r.longitude<e.getWest()||r.longitude>e.getEast()||r.latitude<e.getSouth()||r.latitude>e.getNorth())},n.prototype._setErrorState=function(){switch(this._watchState){case"WAITING_ACTIVE":this._watchState="ACTIVE_ERROR",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active-error");break;case"ACTIVE_LOCK":this._watchState="ACTIVE_ERROR",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting");break;case"BACKGROUND":this._watchState="BACKGROUND_ERROR",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting")}},n.prototype._onSuccess=function(e){if(this._map){if(this._isOutOfMapMaxBounds(e))return this._setErrorState(),this.fire(new t.Event("outofmaxbounds",e)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=e,this._watchState){case"WAITING_ACTIVE":case"ACTIVE_LOCK":case"ACTIVE_ERROR":this._watchState="ACTIVE_LOCK",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active");break;case"BACKGROUND":case"BACKGROUND_ERROR":this._watchState="BACKGROUND",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background")}this.options.showUserLocation&&"OFF"!==this._watchState&&this._updateMarker(e),this.options.trackUserLocation&&"ACTIVE_LOCK"!==this._watchState||this._updateCamera(e),this.options.showUserLocation&&this._dotElement.classList.remove("mapboxgl-user-location-dot-stale"),this.fire(new t.Event("geolocate",e)),this._finish()}},n.prototype._updateCamera=function(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude),n=e.coords.accuracy,i=this._map.getBearing(),a=t.extend({bearing:i},this.options.fitBoundsOptions);this._map.fitBounds(r.toBounds(n),a,{geolocateSource:!0})},n.prototype._updateMarker=function(e){if(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude);this._accuracyCircleMarker.setLngLat(r).addTo(this._map),this._userLocationDotMarker.setLngLat(r).addTo(this._map),this._accuracy=e.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},n.prototype._updateCircleRadius=function(){var t=this._map._container.clientHeight/2,e=this._map.unproject([0,t]),r=this._map.unproject([1,t]),n=e.distanceTo(r),i=Math.ceil(2*this._accuracy/n);this._circleElement.style.width=i+"px",this._circleElement.style.height=i+"px"},n.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},n.prototype._onError=function(e){if(this._map){if(this.options.trackUserLocation)if(1===e.code){this._watchState="OFF",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background-error"),this._geolocateButton.disabled=!0;var r=this._map._getUIString("GeolocateControl.LocationNotAvailable");this._geolocateButton.title=r,this._geolocateButton.setAttribute("aria-label",r),void 0!==this._geolocationWatchID&&this._clearWatch()}else{if(3===e.code&&Yi)return;this._setErrorState()}"OFF"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add("mapboxgl-user-location-dot-stale"),this.fire(new t.Event("error",e)),this._finish()}},n.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},n.prototype._setupUI=function(e){var n=this;if(this._container.addEventListener("contextmenu",(function(t){return t.preventDefault()})),this._geolocateButton=r.create("button","mapboxgl-ctrl-geolocate",this._container),r.create("span","mapboxgl-ctrl-icon",this._geolocateButton).setAttribute("aria-hidden",!0),this._geolocateButton.type="button",!1===e){t.warnOnce("Geolocation support is not available so the GeolocateControl will be disabled.");var i=this._map._getUIString("GeolocateControl.LocationNotAvailable");this._geolocateButton.disabled=!0,this._geolocateButton.title=i,this._geolocateButton.setAttribute("aria-label",i)}else{var a=this._map._getUIString("GeolocateControl.FindMyLocation");this._geolocateButton.title=a,this._geolocateButton.setAttribute("aria-label",a)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute("aria-pressed","false"),this._watchState="OFF"),this.options.showUserLocation&&(this._dotElement=r.create("div","mapboxgl-user-location-dot"),this._userLocationDotMarker=new qi(this._dotElement),this._circleElement=r.create("div","mapboxgl-user-location-accuracy-circle"),this._accuracyCircleMarker=new qi({element:this._circleElement,pitchAlignment:"map"}),this.options.trackUserLocation&&(this._watchState="OFF"),this._map.on("zoom",this._onZoom)),this._geolocateButton.addEventListener("click",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on("movestart",(function(e){var r=e.originalEvent&&"resize"===e.originalEvent.type;e.geolocateSource||"ACTIVE_LOCK"!==n._watchState||r||(n._watchState="BACKGROUND",n._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background"),n._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),n.fire(new t.Event("trackuserlocationend")))}))},n.prototype.trigger=function(){if(!this._setup)return t.warnOnce("Geolocate control triggered before added to a map"),!1;if(this.options.trackUserLocation){switch(this._watchState){case"OFF":this._watchState="WAITING_ACTIVE",this.fire(new t.Event("trackuserlocationstart"));break;case"WAITING_ACTIVE":case"ACTIVE_LOCK":case"ACTIVE_ERROR":case"BACKGROUND_ERROR":Zi--,Yi=!1,this._watchState="OFF",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background-error"),this.fire(new t.Event("trackuserlocationend"));break;case"BACKGROUND":this._watchState="ACTIVE_LOCK",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.Event("trackuserlocationstart"))}switch(this._watchState){case"WAITING_ACTIVE":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active");break;case"ACTIVE_LOCK":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active");break;case"ACTIVE_ERROR":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active-error");break;case"BACKGROUND":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background");break;case"BACKGROUND_ERROR":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background-error")}if("OFF"===this._watchState&&void 0!==this._geolocationWatchID)this._clearWatch();else if(void 0===this._geolocationWatchID){var e;this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.setAttribute("aria-pressed","true"),++Zi>1?(e={maximumAge:6e5,timeout:0},Yi=!0):(e=this.options.positionOptions,Yi=!1),this._geolocationWatchID=t.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,e)}}else t.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},n.prototype._clearWatch=function(){t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.setAttribute("aria-pressed","false"),this.options.showUserLocation&&this._updateMarker(null)},n}(t.Evented),Xi={maxWidth:100,unit:"metric"},Ji=function(e){this.options=t.extend({},Xi,e),t.bindAll(["_onMove","setUnit"],this)};function Ki(t,e,r){var n=r&&r.maxWidth||100,i=t._container.clientHeight/2,a=t.unproject([0,i]),o=t.unproject([n,i]),s=a.distanceTo(o);if(r&&"imperial"===r.unit){var l=3.2808*s;l>5280?$i(e,n,l/5280,t._getUIString("ScaleControl.Miles")):$i(e,n,l,t._getUIString("ScaleControl.Feet"))}else r&&"nautical"===r.unit?$i(e,n,s/1852,t._getUIString("ScaleControl.NauticalMiles")):s>=1e3?$i(e,n,s/1e3,t._getUIString("ScaleControl.Kilometers")):$i(e,n,s,t._getUIString("ScaleControl.Meters"))}function $i(t,e,r,n){var i,a,o,s=(i=r,(a=Math.pow(10,(""+Math.floor(i)).length-1))*((o=i/a)>=10?10:o>=5?5:o>=3?3:o>=2?2:o>=1?1:function(t){var e=Math.pow(10,Math.ceil(-Math.log(t)/Math.LN10));return Math.round(t*e)/e}(o))),l=s/r;t.style.width=e*l+"px",t.innerHTML=s+"&nbsp;"+n}Ji.prototype.getDefaultPosition=function(){return"bottom-left"},Ji.prototype._onMove=function(){Ki(this._map,this._container,this.options)},Ji.prototype.onAdd=function(t){return this._map=t,this._container=r.create("div","mapboxgl-ctrl mapboxgl-ctrl-scale",t.getContainer()),this._map.on("move",this._onMove),this._onMove(),this._container},Ji.prototype.onRemove=function(){r.remove(this._container),this._map.off("move",this._onMove),this._map=void 0},Ji.prototype.setUnit=function(t){this.options.unit=t,Ki(this._map,this._container,this.options)};var Qi=function(e){this._fullscreen=!1,e&&e.container&&(e.container instanceof t.window.HTMLElement?this._container=e.container:t.warnOnce("Full screen control 'container' must be a DOM element.")),t.bindAll(["_onClickFullscreen","_changeIcon"],this),"onfullscreenchange"in t.window.document?this._fullscreenchange="fullscreenchange":"onmozfullscreenchange"in t.window.document?this._fullscreenchange="mozfullscreenchange":"onwebkitfullscreenchange"in t.window.document?this._fullscreenchange="webkitfullscreenchange":"onmsfullscreenchange"in t.window.document&&(this._fullscreenchange="MSFullscreenChange")};Qi.prototype.onAdd=function(e){return this._map=e,this._container||(this._container=this._map.getContainer()),this._controlContainer=r.create("div","mapboxgl-ctrl mapboxgl-ctrl-group"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display="none",t.warnOnce("This device does not support fullscreen mode.")),this._controlContainer},Qi.prototype.onRemove=function(){r.remove(this._controlContainer),this._map=null,t.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},Qi.prototype._checkFullscreenSupport=function(){return!!(t.window.document.fullscreenEnabled||t.window.document.mozFullScreenEnabled||t.window.document.msFullscreenEnabled||t.window.document.webkitFullscreenEnabled)},Qi.prototype._setupUI=function(){var 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this._fullscreen},Qi.prototype._changeIcon=function(){(t.window.document.fullscreenElement||t.window.document.mozFullScreenElement||t.window.document.webkitFullscreenElement||t.window.document.msFullscreenElement)===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle("mapboxgl-ctrl-shrink"),this._fullscreenButton.classList.toggle("mapboxgl-ctrl-fullscreen"),this._updateTitle())},Qi.prototype._onClickFullscreen=function(){this._isFullscreen()?t.window.document.exitFullscreen?t.window.document.exitFullscreen():t.window.document.mozCancelFullScreen?t.window.document.mozCancelFullScreen():t.window.document.msExitFullscreen?t.window.document.msExitFullscreen():t.window.document.webkitCancelFullScreen&&t.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var ta={closeButton:!0,closeOnClick:!0,className:"",maxWidth:"240px"},ea=function(e){function n(r){e.call(this),this.options=t.extend(Object.create(ta),r),t.bindAll(["_update","_onClose","remove","_onMouseMove","_onMouseUp","_onDrag"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(e){return this._map&&this.remove(),this._map=e,this.options.closeOnClick&&this._map.on("click",this._onClose),this.options.closeOnMove&&this._map.on("move",this._onClose),this._map.on("remove",this.remove),this._update(),this._trackPointer?(this._map.on("mousemove",this._onMouseMove),this._map.on("mouseup",this._onMouseUp),this._container&&this._container.classList.add("mapboxgl-popup-track-pointer"),this._map._canvasContainer.classList.add("mapboxgl-track-pointer")):this._map.on("move",this._update),this.fire(new t.Event("open")),this},n.prototype.isOpen=function(){return!!this._map},n.prototype.remove=function(){return 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this._createContent(),this._content.appendChild(t),this._update(),this},n.prototype.addClassName=function(t){this._container&&this._container.classList.add(t)},n.prototype.removeClassName=function(t){this._container&&this._container.classList.remove(t)},n.prototype.toggleClassName=function(t){if(this._container)return this._container.classList.toggle(t)},n.prototype._createContent=function(){this._content&&r.remove(this._content),this._content=r.create("div","mapboxgl-popup-content",this._container),this.options.closeButton&&(this._closeButton=r.create("button","mapboxgl-popup-close-button",this._content),this._closeButton.type="button",this._closeButton.setAttribute("aria-label","Close 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function(t,e){r&&r.segmentChop(t.seg,e),t.other.remove(),t.seg.end=e,t.other.pt=e,o(t.other,t.pt)}(t,e),s(n,t.primary)}function u(i,o){var s=n.create();function u(t){return s.findTransition((function(r){var n,i,a,o,s,l;return n=t,i=r.ev,a=n.seg.start,o=n.seg.end,s=i.seg.start,l=i.seg.end,(e.pointsCollinear(a,s,l)?e.pointsCollinear(o,s,l)||e.pointAboveOrOnLine(o,s,l)?1:-1:e.pointAboveOrOnLine(a,s,l)?1:-1)>0}))}function c(t,n){var i=t.seg,a=n.seg,o=i.start,s=i.end,u=a.start,c=a.end;r&&r.checkIntersection(i,a);var f=e.linesIntersect(o,s,u,c);if(!1===f){if(!e.pointsCollinear(o,s,u))return!1;if(e.pointsSame(o,c)||e.pointsSame(s,u))return!1;var h=e.pointsSame(o,u),p=e.pointsSame(s,c);if(h&&p)return n;var d=!h&&e.pointBetween(o,u,c),v=!p&&e.pointBetween(s,u,c);if(h)return v?l(n,s):l(t,c),n;d&&(p||(v?l(n,s):l(t,c)),l(n,o))}else 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y,m,x=g();if(x)t?(m=null===h.seg.myFill.below||h.seg.myFill.above!==h.seg.myFill.below)&&(x.seg.myFill.above=!x.seg.myFill.above):x.seg.otherFill=h.seg.myFill,r&&r.segmentUpdate(x.seg),h.other.remove(),h.remove();if(a.getHead()!==h){r&&r.rewind(h.seg);continue}t?(m=null===h.seg.myFill.below||h.seg.myFill.above!==h.seg.myFill.below,h.seg.myFill.below=v?v.seg.myFill.above:i,h.seg.myFill.above=m?!h.seg.myFill.below:h.seg.myFill.below):null===h.seg.otherFill&&(y=v?h.primary===v.primary?v.seg.otherFill.above:v.seg.myFill.above:h.primary?o:i,h.seg.otherFill={above:y,below:y}),r&&r.status(h.seg,!!d&&d.seg,!!v&&v.seg),h.other.status=p.insert(n.node({ev:h}))}else{var b=h.status;if(null===b)throw new Error("PolyBool: Zero-length segment detected; your epsilon is probably too small or too large");if(s.exists(b.prev)&&s.exists(b.next)&&c(b.prev.ev,b.next.ev),r&&r.statusRemove(b.ev.seg),b.remove(),!h.primary){var 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r=t.root,n=t.root.next;null!==n&&!e(n);)r=n,n=n.next;return{before:r===t.root?null:r,after:n,insert:function(t){return t.prev=r,t.next=n,r.next=t,null!==n&&(n.prev=t),t}}}};return t},node:function(t){return t.prev=null,t.next=null,t.remove=function(){t.prev.next=t.next,t.next&&(t.next.prev=t.prev),t.prev=null,t.next=null},t}}},11328:function(t){t.exports=function(t,e,r){var n=[],i=[];return t.forEach((function(t){var a=t.start,o=t.end;if(e.pointsSame(a,o))console.warn("PolyBool: Warning: Zero-length segment detected; your epsilon is probably too small or too large");else{r&&r.chainStart(t);for(var s={index:0,matches_head:!1,matches_pt1:!1},l={index:0,matches_head:!1,matches_pt1:!1},u=s,c=0;c<n.length;c++){var f=(g=n[c])[0],h=(g[1],g[g.length-1]);if(g[g.length-2],e.pointsSame(f,a)){if(k(c,!0,!0))break}else if(e.pointsSame(f,o)){if(k(c,!0,!1))break}else if(e.pointsSame(h,a)){if(k(c,!1,!0))break}else if(e.pointsSame(h,o)&&k(c,!1,!1))break}if(u===s)return n.push([a,o]),void(r&&r.chainNew(a,o));if(u===l){r&&r.chainMatch(s.index);var p=s.index,d=s.matches_pt1?o:a,v=s.matches_head,g=n[p],y=v?g[0]:g[g.length-1],m=v?g[1]:g[g.length-2],x=v?g[g.length-1]:g[0],b=v?g[g.length-2]:g[1];return e.pointsCollinear(m,y,d)&&(v?(r&&r.chainRemoveHead(s.index,d),g.shift()):(r&&r.chainRemoveTail(s.index,d),g.pop()),y=m),e.pointsSame(x,d)?(n.splice(p,1),e.pointsCollinear(b,x,y)&&(v?(r&&r.chainRemoveTail(s.index,y),g.pop()):(r&&r.chainRemoveHead(s.index,y),g.shift())),r&&r.chainClose(s.index),void i.push(g)):void(v?(r&&r.chainAddHead(s.index,d),g.unshift(d)):(r&&r.chainAddTail(s.index,d),g.push(d)))}var _=s.index,w=l.index;r&&r.chainConnect(_,w);var T=n[_].length<n[w].length;s.matches_head?l.matches_head?T?(A(_),M(_,w)):(A(w),M(w,_)):M(w,_):l.matches_head?M(_,w):T?(A(_),M(w,_)):(A(w),M(_,w))}function k(t,e,r){return u.index=t,u.matches_head=e,u.matches_pt1=r,u===s?(u=l,!1):(u=null,!0)}function A(t){r&&r.chainReverse(t),n[t].reverse()}function M(t,i){var a=n[t],o=n[i],s=a[a.length-1],l=a[a.length-2],u=o[0],c=o[1];e.pointsCollinear(l,s,u)&&(r&&r.chainRemoveTail(t,s),a.pop(),s=l),e.pointsCollinear(s,u,c)&&(r&&r.chainRemoveHead(i,u),o.shift()),r&&r.chainJoin(t,i),n[t]=a.concat(o),n.splice(i,1)}})),i}},55968:function(t){function e(t,e,r){var n=[];return t.forEach((function(t){var i=(t.myFill.above?8:0)+(t.myFill.below?4:0)+(t.otherFill&&t.otherFill.above?2:0)+(t.otherFill&&t.otherFill.below?1:0);0!==e[i]&&n.push({id:r?r.segmentId():-1,start:t.start,end:t.end,myFill:{above:1===e[i],below:2===e[i]},otherFill:null})})),r&&r.selected(n),n}var r={union:function(t,r){return e(t,[0,2,1,0,2,2,0,0,1,0,1,0,0,0,0,0],r)},intersect:function(t,r){return e(t,[0,0,0,0,0,2,0,2,0,0,1,1,0,2,1,0],r)},difference:function(t,r){return e(t,[0,0,0,0,2,0,2,0,1,1,0,0,0,1,2,0],r)},differenceRev:function(t,r){return e(t,[0,2,1,0,0,0,1,1,0,2,0,2,0,0,0,0],r)},xor:function(t,r){return e(t,[0,2,1,0,2,0,0,1,1,0,0,2,0,1,2,0],r)}};t.exports=r},14847:function(t,e,r){"use 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r=new Error(t);return r.code=e,r}function r(t){try{return decodeURIComponent(escape(t))}catch(e){return t}}function n(t,r,n){this.input=t.subarray(r,n),this.start=r;var i=String.fromCharCode.apply(null,this.input.subarray(0,4));if("II*\0"!==i&&"MM\0*"!==i)throw e("invalid TIFF signature","EBADDATA");this.big_endian="M"===i[0]}n.prototype.each=function(t){this.aborted=!1;var e=this.read_uint32(4);for(this.ifds_to_read=[{id:0,offset:e}];this.ifds_to_read.length>0&&!this.aborted;){var r=this.ifds_to_read.shift();r.offset&&this.scan_ifd(r.id,r.offset,t)}},n.prototype.read_uint16=function(t){var r=this.input;if(t+2>r.length)throw e("unexpected EOF","EBADDATA");return this.big_endian?256*r[t]+r[t+1]:r[t]+256*r[t+1]},n.prototype.read_uint32=function(t){var r=this.input;if(t+4>r.length)throw e("unexpected EOF","EBADDATA");return this.big_endian?16777216*r[t]+65536*r[t+1]+256*r[t+2]+r[t+3]:r[t]+256*r[t+1]+65536*r[t+2]+16777216*r[t+3]},n.prototype.is_subifd_link=function(t,e){return 0===t&&34665===e||0===t&&34853===e||34665===t&&40965===e},n.prototype.exif_format_length=function(t){switch(t){case 1:case 2:case 6:case 7:return 1;case 3:case 8:return 2;case 4:case 9:case 11:return 4;case 5:case 10:case 12:return 8;default:return 0}},n.prototype.exif_format_read=function(t,e){var r;switch(t){case 1:case 2:return this.input[e];case 6:return(r=this.input[e])|33554430*(128&r);case 3:return this.read_uint16(e);case 8:return(r=this.read_uint16(e))|131070*(32768&r);case 4:return this.read_uint32(e);case 9:return 0|this.read_uint32(e);default:return null}},n.prototype.scan_ifd=function(t,n,i){var a=this.read_uint16(n);n+=2;for(var o=0;o<a;o++){var s=this.read_uint16(n),l=this.read_uint16(n+2),u=this.read_uint32(n+4),c=this.exif_format_length(l),f=u*c,h=f<=4?n+8:this.read_uint32(n+8),p=!1;if(h+f>this.input.length)throw e("unexpected EOF","EBADDATA");for(var d=[],v=h,g=0;g<u;g++,v+=c){var y=this.exif_format_read(l,v);if(null===y){d=null;break}d.push(y)}if(Array.isArray(d)&&2===l&&(d=r(String.fromCharCode.apply(null,d)))&&"\0"===d[d.length-1]&&(d=d.slice(0,-1)),this.is_subifd_link(t,s)&&Array.isArray(d)&&Number.isInteger(d[0])&&d[0]>0&&(this.ifds_to_read.push({id:s,offset:d[0]}),p=!0),!1===i({is_big_endian:this.big_endian,ifd:t,tag:s,format:l,count:u,entry_offset:n+this.start,data_length:f,data_offset:h+this.start,value:d,is_subifd_link:p}))return void(this.aborted=!0);n+=12}0===t&&this.ifds_to_read.push({id:1,offset:this.read_uint32(n)})},t.exports.ExifParser=n,t.exports.get_orientation=function(t){var e=0;try{return new n(t,0,t.length).each((function(t){if(0===t.ifd&&274===t.tag&&Array.isArray(t.value))return e=t.value[0],!1})),e}catch(t){return-1}}},76767:function(t,e,r){"use strict";var n=r(14847).n8,i=r(14847).Ag;function a(t,e){if(t.length<4+e)return null;var r=i(t,e);return t.length<r+e||r<8?null:{boxtype:String.fromCharCode.apply(null,t.slice(e+4,e+8)),data:t.slice(e+8,e+r),end:e+r}}function o(t,e){for(var r=0;;){var n=a(t,r);if(!n)break;switch(n.boxtype){case"ispe":e.sizes.push({width:i(n.data,4),height:i(n.data,8)});break;case"irot":e.transforms.push({type:"irot",value:3&n.data[0]});break;case"imir":e.transforms.push({type:"imir",value:1&n.data[0]})}r=n.end}}function s(t,e,r){for(var n=0,i=0;i<r;i++)n=256*n+(t[e+i]||0);return n}function l(t,e){for(var r=t[4]>>4&15,i=15&t[4],a=t[5]>>4&15,o=n(t,6),l=8,u=0;u<o;u++){var c=n(t,l),f=n(t,l+=2),h=s(t,l+=2,a),p=n(t,l+=a);if(l+=2,0===f&&1===p){var d=s(t,l,r),v=s(t,l+r,i);e.item_loc[c]={length:v,offset:d+h}}l+=p*(r+i)}}function u(t,e){for(var r=n(t,4),i=6,o=0;o<r;o++){var s=a(t,i);if(!s)break;if("infe"===s.boxtype){for(var l=n(s.data,4),u="",c=8;c<s.data.length&&s.data[c];c++)u+=String.fromCharCode(s.data[c]);e.item_inf[u]=l}i=s.end}}function c(t,e){for(var r=0;;){var n=a(t,r);if(!n)break;"ipco"===n.boxtype&&o(n.data,e),r=n.end}}t.exports.unbox=a,t.exports.readSizeFromMeta=function(t){var e={sizes:[],transforms:[],item_inf:{},item_loc:{}};if(function(t,e){for(var r=4;;){var n=a(t,r);if(!n)break;"iprp"===n.boxtype&&c(n.data,e),"iloc"===n.boxtype&&l(n.data,e),"iinf"===n.boxtype&&u(n.data,e),r=n.end}}(t,e),e.sizes.length){var r,n,i,o=(n=(r=e.sizes).reduce((function(t,e){return t.width>e.width||t.width===e.width&&t.height>e.height?t:e})),i=r.reduce((function(t,e){return t.height>e.height||t.height===e.height&&t.width>e.width?t:e})),n.width>i.height||n.width===i.height&&n.height>i.width?n:i),s=1;e.transforms.forEach((function(t){var e={1:6,2:5,3:8,4:7,5:4,6:3,7:2,8:1},r={1:4,2:3,3:2,4:1,5:6,6:5,7:8,8:7};if("imir"===t.type&&(s=0===t.value?r[s]:e[s=e[s=r[s]]]),"irot"===t.type)for(var n=0;n<t.value;n++)s=e[s]}));var f=null;return 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be enabled");this.gl=t._gl,this.regl=t,this.passes=[],this.shaders=y.shaders.has(t)?y.shaders.get(t):y.shaders.set(t,y.createShaders(t)).get(t),this.update(e)}t.exports=y,y.dashMult=2,y.maxPatternLength=256,y.precisionThreshold=3e6,y.maxPoints=1e4,y.maxLines=2048,y.shaders=new d,y.createShaders=function(t){var e,r=t.buffer({usage:"static",type:"float",data:[0,1,0,0,1,1,1,0]}),n={primitive:"triangle strip",instances:t.prop("count"),count:4,offset:0,uniforms:{miterMode:function(t,e){return"round"===e.join?2:1},miterLimit:t.prop("miterLimit"),scale:t.prop("scale"),scaleFract:t.prop("scaleFract"),translateFract:t.prop("translateFract"),translate:t.prop("translate"),thickness:t.prop("thickness"),dashTexture:t.prop("dashTexture"),opacity:t.prop("opacity"),pixelRatio:t.context("pixelRatio"),id:t.prop("id"),dashLength:t.prop("dashLength"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]},depth:t.prop("depth")},blend:{enable:!0,color:[0,0,0,0],equation:{rgb:"add",alpha:"add"},func:{srcRGB:"src alpha",dstRGB:"one minus src alpha",srcAlpha:"one minus dst alpha",dstAlpha:"one"}},depth:{enable:function(t,e){return!e.overlay}},stencil:{enable:!1},scissor:{enable:!0,box:t.prop("viewport")},viewport:t.prop("viewport")},i=t(a({vert:o(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec2 aCoord, bCoord, aCoordFract, bCoordFract;\nattribute vec4 color;\nattribute float lineEnd, lineTop;\n\nuniform vec2 scale, scaleFract, translate, translateFract;\nuniform float thickness, pixelRatio, id, depth;\nuniform vec4 viewport;\n\nvarying vec4 fragColor;\nvarying vec2 tangent;\n\nvec2 project(vec2 position, vec2 positionFract, vec2 scale, vec2 scaleFract, vec2 translate, vec2 translateFract) {\n\t// the order is important\n\treturn position * scale + translate\n       + positionFract * scale + translateFract\n       + position * scaleFract\n       + positionFract * scaleFract;\n}\n\nvoid main() {\n\tfloat lineStart = 1. - lineEnd;\n\tfloat lineOffset = lineTop * 2. - 1.;\n\n\tvec2 diff = (bCoord + bCoordFract - aCoord - aCoordFract);\n\ttangent = normalize(diff * scale * viewport.zw);\n\tvec2 normal = vec2(-tangent.y, tangent.x);\n\n\tvec2 position = project(aCoord, aCoordFract, scale, scaleFract, translate, translateFract) * lineStart\n\t\t+ project(bCoord, bCoordFract, scale, scaleFract, translate, translateFract) * lineEnd\n\n\t\t+ thickness * normal * .5 * lineOffset / viewport.zw;\n\n\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\n\n\tfragColor = color / 255.;\n}\n"]),frag:o(["precision highp float;\n#define GLSLIFY 1\n\nuniform float dashLength, pixelRatio, thickness, opacity, id;\nuniform sampler2D dashTexture;\n\nvarying vec4 fragColor;\nvarying vec2 tangent;\n\nvoid main() {\n\tfloat alpha = 1.;\n\n\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashLength) * .5 + .25;\n\tfloat dash = texture2D(dashTexture, vec2(t, .5)).r;\n\n\tgl_FragColor = fragColor;\n\tgl_FragColor.a *= alpha * opacity * dash;\n}\n"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aCoord:{buffer:t.prop("positionBuffer"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop("positionBuffer"),stride:8,offset:16,divisor:1},aCoordFract:{buffer:t.prop("positionFractBuffer"),stride:8,offset:8,divisor:1},bCoordFract:{buffer:t.prop("positionFractBuffer"),stride:8,offset:16,divisor:1},color:{buffer:t.prop("colorBuffer"),stride:4,offset:0,divisor:1}}},n));try{e=t(a({cull:{enable:!0,face:"back"},vert:o(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec2 aCoord, bCoord, nextCoord, prevCoord;\nattribute vec4 aColor, bColor;\nattribute float lineEnd, lineTop;\n\nuniform vec2 scale, translate;\nuniform float thickness, pixelRatio, id, depth;\nuniform vec4 viewport;\nuniform float miterLimit, miterMode;\n\nvarying vec4 fragColor;\nvarying vec4 startCutoff, endCutoff;\nvarying vec2 tangent;\nvarying vec2 startCoord, endCoord;\nvarying float enableStartMiter, enableEndMiter;\n\nconst float REVERSE_THRESHOLD = -.875;\nconst float MIN_DIFF = 1e-6;\n\n// TODO: possible optimizations: avoid overcalculating all for vertices and calc just one instead\n// TODO: precalculate dot products, normalize things beforehead etc.\n// TODO: refactor to rectangular algorithm\n\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\n\tvec2 diff = b - a;\n\tvec2 perp = normalize(vec2(-diff.y, diff.x));\n\treturn dot(p - a, perp);\n}\n\nbool isNaN( float val ){\n  return ( val < 0.0 || 0.0 < val || val == 0.0 ) ? false : true;\n}\n\nvoid main() {\n\tvec2 aCoord = aCoord, bCoord = bCoord, prevCoord = prevCoord, nextCoord = nextCoord;\n\n  vec2 adjustedScale;\n  adjustedScale.x = (abs(scale.x) < MIN_DIFF) ? MIN_DIFF : scale.x;\n  adjustedScale.y = (abs(scale.y) < MIN_DIFF) ? MIN_DIFF : scale.y;\n\n  vec2 scaleRatio = adjustedScale * viewport.zw;\n\tvec2 normalWidth = thickness / scaleRatio;\n\n\tfloat lineStart = 1. - lineEnd;\n\tfloat lineBot = 1. - lineTop;\n\n\tfragColor = (lineStart * aColor + lineEnd * bColor) / 255.;\n\n\tif (isNaN(aCoord.x) || isNaN(aCoord.y) || isNaN(bCoord.x) || isNaN(bCoord.y)) return;\n\n\tif (aCoord == prevCoord) prevCoord = aCoord + normalize(bCoord - aCoord);\n\tif (bCoord == nextCoord) nextCoord = bCoord - normalize(bCoord - aCoord);\n\n\tvec2 prevDiff = aCoord - prevCoord;\n\tvec2 currDiff = bCoord - aCoord;\n\tvec2 nextDiff = nextCoord - bCoord;\n\n\tvec2 prevTangent = normalize(prevDiff * scaleRatio);\n\tvec2 currTangent = normalize(currDiff * scaleRatio);\n\tvec2 nextTangent = normalize(nextDiff * scaleRatio);\n\n\tvec2 prevNormal = vec2(-prevTangent.y, prevTangent.x);\n\tvec2 currNormal = vec2(-currTangent.y, currTangent.x);\n\tvec2 nextNormal = vec2(-nextTangent.y, nextTangent.x);\n\n\tvec2 startJoinDirection = normalize(prevTangent - currTangent);\n\tvec2 endJoinDirection = normalize(currTangent - nextTangent);\n\n\t// collapsed/unidirectional segment cases\n\t// FIXME: there should be more elegant solution\n\tvec2 prevTanDiff = abs(prevTangent - currTangent);\n\tvec2 nextTanDiff = abs(nextTangent - currTangent);\n\tif (max(prevTanDiff.x, prevTanDiff.y) < MIN_DIFF) {\n\t\tstartJoinDirection = currNormal;\n\t}\n\tif (max(nextTanDiff.x, nextTanDiff.y) < MIN_DIFF) {\n\t\tendJoinDirection = currNormal;\n\t}\n\tif (aCoord == bCoord) {\n\t\tendJoinDirection = startJoinDirection;\n\t\tcurrNormal = prevNormal;\n\t\tcurrTangent = prevTangent;\n\t}\n\n\ttangent = currTangent;\n\n\t//calculate join shifts relative to normals\n\tfloat startJoinShift = dot(currNormal, startJoinDirection);\n\tfloat endJoinShift = dot(currNormal, endJoinDirection);\n\n\tfloat startMiterRatio = abs(1. / startJoinShift);\n\tfloat endMiterRatio = abs(1. / endJoinShift);\n\n\tvec2 startJoin = startJoinDirection * startMiterRatio;\n\tvec2 endJoin = endJoinDirection * endMiterRatio;\n\n\tvec2 startTopJoin, startBotJoin, endTopJoin, endBotJoin;\n\tstartTopJoin = sign(startJoinShift) * startJoin * .5;\n\tstartBotJoin = -startTopJoin;\n\n\tendTopJoin = sign(endJoinShift) * endJoin * .5;\n\tendBotJoin = -endTopJoin;\n\n\tvec2 aTopCoord = aCoord + normalWidth * startTopJoin;\n\tvec2 bTopCoord = bCoord + normalWidth * endTopJoin;\n\tvec2 aBotCoord = aCoord + normalWidth * startBotJoin;\n\tvec2 bBotCoord = bCoord + normalWidth * endBotJoin;\n\n\t//miter anti-clipping\n\tfloat baClipping = distToLine(bCoord, aCoord, aBotCoord) / dot(normalize(normalWidth * endBotJoin), normalize(normalWidth.yx * vec2(-startBotJoin.y, startBotJoin.x)));\n\tfloat abClipping = distToLine(aCoord, bCoord, bTopCoord) / dot(normalize(normalWidth * startBotJoin), normalize(normalWidth.yx * vec2(-endBotJoin.y, endBotJoin.x)));\n\n\t//prevent close to reverse direction switch\n\tbool prevReverse = dot(currTangent, prevTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, prevNormal)) * min(length(prevDiff), length(currDiff)) <  length(normalWidth * currNormal);\n\tbool nextReverse = dot(currTangent, nextTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, nextNormal)) * min(length(nextDiff), length(currDiff)) <  length(normalWidth * currNormal);\n\n\tif (prevReverse) {\n\t\t//make join rectangular\n\t\tvec2 miterShift = normalWidth * startJoinDirection * miterLimit * .5;\n\t\tfloat normalAdjust = 1. - min(miterLimit / startMiterRatio, 1.);\n\t\taBotCoord = aCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\n\t\taTopCoord = aCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\n\t}\n\telse if (!nextReverse && baClipping > 0. && baClipping < length(normalWidth * endBotJoin)) {\n\t\t//handle miter clipping\n\t\tbTopCoord -= normalWidth * endTopJoin;\n\t\tbTopCoord += normalize(endTopJoin * normalWidth) * baClipping;\n\t}\n\n\tif (nextReverse) {\n\t\t//make join rectangular\n\t\tvec2 miterShift = normalWidth * endJoinDirection * miterLimit * .5;\n\t\tfloat normalAdjust = 1. - min(miterLimit / endMiterRatio, 1.);\n\t\tbBotCoord = bCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\n\t\tbTopCoord = bCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\n\t}\n\telse if (!prevReverse && abClipping > 0. && abClipping < length(normalWidth * startBotJoin)) {\n\t\t//handle miter clipping\n\t\taBotCoord -= normalWidth * startBotJoin;\n\t\taBotCoord += normalize(startBotJoin * normalWidth) * abClipping;\n\t}\n\n\tvec2 aTopPosition = (aTopCoord) * adjustedScale + translate;\n\tvec2 aBotPosition = (aBotCoord) * adjustedScale + translate;\n\n\tvec2 bTopPosition = (bTopCoord) * adjustedScale + translate;\n\tvec2 bBotPosition = (bBotCoord) * adjustedScale + translate;\n\n\t//position is normalized 0..1 coord on the screen\n\tvec2 position = (aTopPosition * lineTop + aBotPosition * lineBot) * lineStart + (bTopPosition * lineTop + bBotPosition * lineBot) * lineEnd;\n\n\tstartCoord = aCoord * scaleRatio + translate * viewport.zw + viewport.xy;\n\tendCoord = bCoord * scaleRatio + translate * viewport.zw + viewport.xy;\n\n\tgl_Position = vec4(position  * 2.0 - 1.0, depth, 1);\n\n\tenableStartMiter = step(dot(currTangent, prevTangent), .5);\n\tenableEndMiter = step(dot(currTangent, nextTangent), .5);\n\n\t//bevel miter cutoffs\n\tif (miterMode == 1.) {\n\t\tif (enableStartMiter == 1.) {\n\t\t\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * miterLimit * .5;\n\t\t\tstartCutoff = vec4(aCoord, aCoord);\n\t\t\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\n\t\t\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\n\t\t\tstartCutoff += viewport.xyxy;\n\t\t\tstartCutoff += startMiterWidth.xyxy;\n\t\t}\n\n\t\tif (enableEndMiter == 1.) {\n\t\t\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * miterLimit * .5;\n\t\t\tendCutoff = vec4(bCoord, bCoord);\n\t\t\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\n\t\t\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\n\t\t\tendCutoff += viewport.xyxy;\n\t\t\tendCutoff += endMiterWidth.xyxy;\n\t\t}\n\t}\n\n\t//round miter cutoffs\n\telse if (miterMode == 2.) {\n\t\tif (enableStartMiter == 1.) {\n\t\t\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * abs(dot(startJoinDirection, currNormal)) * .5;\n\t\t\tstartCutoff = vec4(aCoord, aCoord);\n\t\t\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\n\t\t\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\n\t\t\tstartCutoff += viewport.xyxy;\n\t\t\tstartCutoff += startMiterWidth.xyxy;\n\t\t}\n\n\t\tif (enableEndMiter == 1.) {\n\t\t\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * abs(dot(endJoinDirection, currNormal)) * .5;\n\t\t\tendCutoff = vec4(bCoord, bCoord);\n\t\t\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\n\t\t\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\n\t\t\tendCutoff += viewport.xyxy;\n\t\t\tendCutoff += endMiterWidth.xyxy;\n\t\t}\n\t}\n}\n"]),frag:o(["precision highp float;\n#define GLSLIFY 1\n\nuniform float dashLength, pixelRatio, thickness, opacity, id, miterMode;\nuniform sampler2D dashTexture;\n\nvarying vec4 fragColor;\nvarying vec2 tangent;\nvarying vec4 startCutoff, endCutoff;\nvarying vec2 startCoord, endCoord;\nvarying float enableStartMiter, enableEndMiter;\n\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\n\tvec2 diff = b - a;\n\tvec2 perp = normalize(vec2(-diff.y, diff.x));\n\treturn dot(p - a, perp);\n}\n\nvoid main() {\n\tfloat alpha = 1., distToStart, distToEnd;\n\tfloat cutoff = thickness * .5;\n\n\t//bevel miter\n\tif (miterMode == 1.) {\n\t\tif (enableStartMiter == 1.) {\n\t\t\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\n\t\t\tif (distToStart < -1.) {\n\t\t\t\tdiscard;\n\t\t\t\treturn;\n\t\t\t}\n\t\t\talpha *= min(max(distToStart + 1., 0.), 1.);\n\t\t}\n\n\t\tif (enableEndMiter == 1.) {\n\t\t\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\n\t\t\tif (distToEnd < -1.) {\n\t\t\t\tdiscard;\n\t\t\t\treturn;\n\t\t\t}\n\t\t\talpha *= min(max(distToEnd + 1., 0.), 1.);\n\t\t}\n\t}\n\n\t// round miter\n\telse if (miterMode == 2.) {\n\t\tif (enableStartMiter == 1.) {\n\t\t\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\n\t\t\tif (distToStart < 0.) {\n\t\t\t\tfloat radius = length(gl_FragCoord.xy - startCoord);\n\n\t\t\t\tif(radius > cutoff + .5) {\n\t\t\t\t\tdiscard;\n\t\t\t\t\treturn;\n\t\t\t\t}\n\n\t\t\t\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\n\t\t\t}\n\t\t}\n\n\t\tif (enableEndMiter == 1.) {\n\t\t\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\n\t\t\tif (distToEnd < 0.) {\n\t\t\t\tfloat radius = length(gl_FragCoord.xy - endCoord);\n\n\t\t\t\tif(radius > cutoff + .5) {\n\t\t\t\t\tdiscard;\n\t\t\t\t\treturn;\n\t\t\t\t}\n\n\t\t\t\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\n\t\t\t}\n\t\t}\n\t}\n\n\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashLength) * .5 + .25;\n\tfloat dash = texture2D(dashTexture, vec2(t, .5)).r;\n\n\tgl_FragColor = fragColor;\n\tgl_FragColor.a *= alpha * opacity * dash;\n}\n"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aColor:{buffer:t.prop("colorBuffer"),stride:4,offset:0,divisor:1},bColor:{buffer:t.prop("colorBuffer"),stride:4,offset:4,divisor:1},prevCoord:{buffer:t.prop("positionBuffer"),stride:8,offset:0,divisor:1},aCoord:{buffer:t.prop("positionBuffer"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop("positionBuffer"),stride:8,offset:16,divisor:1},nextCoord:{buffer:t.prop("positionBuffer"),stride:8,offset:24,divisor:1}}},n))}catch(t){e=i}return{fill:t({primitive:"triangle",elements:function(t,e){return e.triangles},offset:0,vert:o(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec2 position, positionFract;\n\nuniform vec4 color;\nuniform vec2 scale, scaleFract, translate, translateFract;\nuniform float pixelRatio, id;\nuniform vec4 viewport;\nuniform float opacity;\n\nvarying vec4 fragColor;\n\nconst float MAX_LINES = 256.;\n\nvoid main() {\n\tfloat depth = (MAX_LINES - 4. - id) / (MAX_LINES);\n\n\tvec2 position = position * scale + translate\n       + positionFract * scale + translateFract\n       + position * scaleFract\n       + positionFract * scaleFract;\n\n\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\n\n\tfragColor = color / 255.;\n\tfragColor.a *= opacity;\n}\n"]),frag:o(["precision highp float;\n#define GLSLIFY 1\n\nvarying vec4 fragColor;\n\nvoid main() {\n\tgl_FragColor = fragColor;\n}\n"]),uniforms:{scale:t.prop("scale"),color:t.prop("fill"),scaleFract:t.prop("scaleFract"),translateFract:t.prop("translateFract"),translate:t.prop("translate"),opacity:t.prop("opacity"),pixelRatio:t.context("pixelRatio"),id:t.prop("id"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]}},attributes:{position:{buffer:t.prop("positionBuffer"),stride:8,offset:8},positionFract:{buffer:t.prop("positionFractBuffer"),stride:8,offset:8}},blend:n.blend,depth:{enable:!1},scissor:n.scissor,stencil:n.stencil,viewport:n.viewport}),rect:i,miter:e}},y.defaults={dashes:null,join:"miter",miterLimit:1,thickness:10,cap:"square",color:"black",opacity:1,overlay:!1,viewport:null,range:null,close:!1,fill:null},y.prototype.render=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];e.length&&(t=this).update.apply(t,e),this.draw()},y.prototype.draw=function(){for(var t=this,e=[],r=arguments.length;r--;)e[r]=arguments[r];return(e.length?e:this.passes).forEach((function(e,r){var n;if(e&&Array.isArray(e))return(n=t).draw.apply(n,e);"number"==typeof e&&(e=t.passes[e]),e&&e.count>1&&e.opacity&&(t.regl._refresh(),e.fill&&e.triangles&&e.triangles.length>2&&t.shaders.fill(e),e.thickness&&(e.scale[0]*e.viewport.width>y.precisionThreshold||e.scale[1]*e.viewport.height>y.precisionThreshold||"rect"===e.join||!e.join&&(e.thickness<=2||e.count>=y.maxPoints)?t.shaders.rect(e):t.shaders.miter(e)))})),this},y.prototype.update=function(t){var e=this;if(t){null!=t.length?"number"==typeof t[0]&&(t=[{positions:t}]):Array.isArray(t)||(t=[t]);var r=this.regl,o=this.gl;if(t.forEach((function(t,f){var d=e.passes[f];if(void 0!==t)if(null!==t){if("number"==typeof t[0]&&(t={positions:t}),t=s(t,{positions:"positions points data coords",thickness:"thickness lineWidth lineWidths line-width linewidth width stroke-width strokewidth strokeWidth",join:"lineJoin linejoin join type 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at=0;at<t.dashes.length;++at){for(var ot=0,st=t.dashes[at]*y.dashMult*.5;ot<st;++ot)Q[rt++]=nt;nt^=255}}d.dashLength=tt,d.dashTexture({channels:1,data:Q,width:Q.length,height:1,mag:"linear",min:"linear"},0,0)}if(t.color){var lt=d.count,ut=t.color;ut||(ut="transparent");var ct=new Uint8Array(4*lt+4);if(Array.isArray(ut)&&"number"!=typeof ut[0]){for(var ft=0;ft<lt;ft++){var ht=n(ut[ft],"uint8");ct.set(ht,4*ft)}ct.set(n(ut[0],"uint8"),4*lt)}else for(var pt=n(ut,"uint8"),dt=0;dt<lt+1;dt++)ct.set(pt,4*dt);d.colorBuffer({usage:"dynamic",type:"uint8",data:ct})}}else e.passes[f]=null})),t.length<this.passes.length){for(var f=t.length;f<this.passes.length;f++){var d=this.passes[f];d&&(d.colorBuffer.destroy(),d.positionBuffer.destroy(),d.dashTexture.destroy())}this.passes.length=t.length}for(var m=[],x=0;x<this.passes.length;x++)null!==this.passes[x]&&m.push(this.passes[x]);return this.passes=m,this}},y.prototype.destroy=function(){return 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opacity;\n\n    gl_FragColor = color;\n  }\n\n}\n"]),s.vert=f(["precision highp float;\n#define GLSLIFY 1\n\nattribute float x, y, xFract, yFract;\nattribute float size, borderSize;\nattribute vec4 colorId, borderColorId;\nattribute float isActive;\n\nuniform bool constPointSize;\nuniform float pixelRatio;\nuniform vec2 scale, scaleFract, translate, translateFract, paletteSize;\nuniform sampler2D paletteTexture;\n\nconst float maxSize = 100.;\nconst float borderLevel = .5;\n\nvarying vec4 fragColor, fragBorderColor;\nvarying float fragPointSize, fragBorderRadius, fragWidth, fragBorderColorLevel, fragColorLevel;\n\nfloat pointSizeScale = (constPointSize) ? 2. : pixelRatio;\n\nbool isDirect = (paletteSize.x < 1.);\n\nvec4 getColor(vec4 id) {\n  return isDirect ? id / 255. : texture2D(paletteTexture,\n    vec2(\n      (id.x + .5) / paletteSize.x,\n      (id.y + .5) / paletteSize.y\n    )\n  );\n}\n\nvoid main() {\n  // ignore inactive points\n  if (isActive == 0.) return;\n\n  vec2 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i=this.groups;if(1===r.length&&Array.isArray(r[0])&&(null===r[0][0]||Array.isArray(r[0][0]))&&(r=r[0]),this.regl._refresh(),r.length)for(var a=0;a<r.length;a++)this.drawItem(a,r[a]);else i.forEach((function(e,r){t.drawItem(r)}));return this},x.prototype.drawItem=function(t,e){var r,n=this.groups,o=n[t];if("number"==typeof e&&(t=e,o=n[e],e=null),o&&o.count&&o.opacity){o.activation[0]&&this.drawCircle(this.getMarkerDrawOptions(0,o,e));for(var s=[],l=1;l<o.activation.length;l++)o.activation[l]&&(!0===o.activation[l]||o.activation[l].data.length)&&s.push.apply(s,function(t){if(Array.isArray(t))return a(t)}(r=this.getMarkerDrawOptions(l,o,e))||function(t){if("undefined"!=typeof Symbol&&null!=t[Symbol.iterator]||null!=t["@@iterator"])return Array.from(t)}(r)||i(r)||function(){throw new TypeError("Invalid attempt to spread non-iterable instance.\nIn order to be iterable, non-array objects must have a [Symbol.iterator]() method.")}());s.length&&this.drawMarker(s)}},x.prototype.getMarkerDrawOptions=function(t,e,r){var i=e.range,a=e.tree,o=e.viewport,s=e.activation,l=e.selectionBuffer,u=e.count;if(this.regl,!a)return r?[c({},e,{markerTexture:this.markerTextures[t],activation:s[t],count:r.length,elements:r,offset:0})]:[c({},e,{markerTexture:this.markerTextures[t],activation:s[t],offset:0})];var f=[],h=a.range(i,{lod:!0,px:[(i[2]-i[0])/o.width,(i[3]-i[1])/o.height]});if(r){for(var p=s[t].data,d=new Uint8Array(u),v=0;v<r.length;v++){var g=r[v];d[g]=p?p[g]:1}l.subdata(d)}for(var y=h.length;y--;){var m=n(h[y],2),x=m[0],b=m[1];f.push(c({},e,{markerTexture:this.markerTextures[t],activation:r?l:s[t],offset:x,count:b-x}))}return f},x.prototype.update=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];if(r.length){1===r.length&&Array.isArray(r[0])&&(r=r[0]);var i=this.groups,a=this.gl,o=this.regl,l=this.maxSize,f=this.maxColors,v=this.palette;this.groups=i=r.map((function(e,r){var n=i[r];if(void 0===e)return n;null===e?e={positions:null}:"function"==typeof e?e={ondraw:e}:"number"==typeof e[0]&&(e={positions:e}),null===(e=h(e,{positions:"positions data points",snap:"snap cluster lod tree",size:"sizes size radius",borderSize:"borderSizes borderSize border-size bordersize borderWidth borderWidths border-width borderwidth stroke-width strokeWidth strokewidth outline",color:"colors color fill fill-color fillColor",borderColor:"borderColors borderColor stroke stroke-color strokeColor",marker:"markers marker shape",range:"range dataBox databox",viewport:"viewport viewPort viewBox viewbox",opacity:"opacity alpha transparency",bounds:"bound bounds boundaries limits",tooManyColors:"tooManyColors palette paletteMode optimizePalette 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n=r(56131);function i(){this.regionalOptions=[],this.regionalOptions[""]={invalidCalendar:"Calendar {0} not found",invalidDate:"Invalid {0} date",invalidMonth:"Invalid {0} month",invalidYear:"Invalid {0} year",differentCalendars:"Cannot mix {0} and {1} dates"},this.local=this.regionalOptions[""],this.calendars={},this._localCals={}}function a(t,e,r,n){if(this._calendar=t,this._year=e,this._month=r,this._day=n,0===this._calendar._validateLevel&&!this._calendar.isValid(this._year,this._month,this._day))throw(u.local.invalidDate||u.regionalOptions[""].invalidDate).replace(/\{0\}/,this._calendar.local.name)}function o(t,e){return"000000".substring(0,e-(t=""+t).length)+t}function s(){this.shortYearCutoff="+10"}function l(t){this.local=this.regionalOptions[t]||this.regionalOptions[""]}n(i.prototype,{instance:function(t,e){t=(t||"gregorian").toLowerCase(),e=e||"";var r=this._localCals[t+"-"+e];if(!r&&this.calendars[t]&&(r=new this.calendars[t](e),this._localCals[t+"-"+e]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[""].invalidCalendar).replace(/\{0\}/,t);return r},newDate:function(t,e,r,n,i){return(n=(null!=t&&t.year?t.calendar():"string"==typeof n?this.instance(n,i):n)||this.instance()).newDate(t,e,r)},substituteDigits:function(t){return function(e){return(e+"").replace(/[0-9]/g,(function(e){return t[e]}))}},substituteChineseDigits:function(t,e){return function(r){for(var n="",i=0;r>0;){var a=r%10;n=(0===a?"":t[a]+e[i])+n,i++,r=Math.floor(r/10)}return 0===n.indexOf(t[1]+e[1])&&(n=n.substr(1)),n||t[0]}}}),n(a.prototype,{newDate:function(t,e,r){return this._calendar.newDate(null==t?this:t,e,r)},year:function(t){return 0===arguments.length?this._year:this.set(t,"y")},month:function(t){return 0===arguments.length?this._month:this.set(t,"m")},day:function(t){return 0===arguments.length?this._day:this.set(t,"d")},date:function(t,e,r){if(!this._calendar.isValid(t,e,r))throw(u.local.invalidDate||u.regionalOptions[""].invalidDate).replace(/\{0\}/,this._calendar.local.name);return this._year=t,this._month=e,this._day=r,this},leapYear:function(){return this._calendar.leapYear(this)},epoch:function(){return this._calendar.epoch(this)},formatYear:function(){return this._calendar.formatYear(this)},monthOfYear:function(){return this._calendar.monthOfYear(this)},weekOfYear:function(){return this._calendar.weekOfYear(this)},daysInYear:function(){return this._calendar.daysInYear(this)},dayOfYear:function(){return this._calendar.dayOfYear(this)},daysInMonth:function(){return this._calendar.daysInMonth(this)},dayOfWeek:function(){return this._calendar.dayOfWeek(this)},weekDay:function(){return this._calendar.weekDay(this)},extraInfo:function(){return this._calendar.extraInfo(this)},add:function(t,e){return this._calendar.add(this,t,e)},set:function(t,e){return this._calendar.set(this,t,e)},compareTo:function(t){if(this._calendar.name!==t._calendar.name)throw(u.local.differentCalendars||u.regionalOptions[""].differentCalendars).replace(/\{0\}/,this._calendar.local.name).replace(/\{1\}/,t._calendar.local.name);var e=this._year!==t._year?this._year-t._year:this._month!==t._month?this.monthOfYear()-t.monthOfYear():this._day-t._day;return 0===e?0:e<0?-1:1},calendar:function(){return this._calendar},toJD:function(){return this._calendar.toJD(this)},fromJD:function(t){return this._calendar.fromJD(t)},toJSDate:function(){return this._calendar.toJSDate(this)},fromJSDate:function(t){return this._calendar.fromJSDate(t)},toString:function(){return(this.year()<0?"-":"")+o(Math.abs(this.year()),4)+"-"+o(this.month(),2)+"-"+o(this.day(),2)}}),n(s.prototype,{_validateLevel:0,newDate:function(t,e,r){return null==t?this.today():(t.year&&(this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[""].invalidDate),r=t.day(),e=t.month(),t=t.year()),new a(this,t,e,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(t){return this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[""].invalidYear).year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[""].invalidYear);return(e.year()<0?"-":"")+o(Math.abs(e.year()),4)},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[""].invalidYear),12},monthOfYear:function(t,e){var r=this._validate(t,e,this.minDay,u.local.invalidMonth||u.regionalOptions[""].invalidMonth);return(r.month()+this.monthsInYear(r)-this.firstMonth)%this.monthsInYear(r)+this.minMonth},fromMonthOfYear:function(t,e){var r=(e+this.firstMonth-2*this.minMonth)%this.monthsInYear(t)+this.minMonth;return this._validate(t,r,this.minDay,u.local.invalidMonth||u.regionalOptions[""].invalidMonth),r},daysInYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[""].invalidYear);return this.leapYear(e)?366:365},dayOfYear:function(t,e,r){var n=this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[""].invalidDate);return n.toJD()-this.newDate(n.year(),this.fromMonthOfYear(n.year(),this.minMonth),this.minDay).toJD()+1},daysInWeek:function(){return 7},dayOfWeek:function(t,e,r){var n=this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[""].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(t,e,r){return this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[""].invalidDate),{}},add:function(t,e,r){return this._validate(t,this.minMonth,this.minDay,u.local.invalidDate||u.regionalOptions[""].invalidDate),this._correctAdd(t,this._add(t,e,r),e,r)},_add:function(t,e,r){if(this._validateLevel++,"d"===r||"w"===r){var n=t.toJD()+e*("w"===r?this.daysInWeek():1),i=t.calendar().fromJD(n);return this._validateLevel--,[i.year(),i.month(),i.day()]}try{var a=t.year()+("y"===r?e:0),o=t.monthOfYear()+("m"===r?e:0);i=t.day(),"y"===r?(t.month()!==this.fromMonthOfYear(a,o)&&(o=this.newDate(a,t.month(),this.minDay).monthOfYear()),o=Math.min(o,this.monthsInYear(a)),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o)))):"m"===r&&(function(t){for(;o<t.minMonth;)a--,o+=t.monthsInYear(a);for(var e=t.monthsInYear(a);o>e-1+t.minMonth;)a++,o-=e,e=t.monthsInYear(a)}(this),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o))));var s=[a,this.fromMonthOfYear(a,o),i];return this._validateLevel--,s}catch(t){throw 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diff --git a/spaces/HuseynG/ECS7022P-WGAN-GP/utils.py b/spaces/HuseynG/ECS7022P-WGAN-GP/utils.py
deleted file mode 100644
index 6221b2bac9476842d668a4733d06ee429904ce5f..0000000000000000000000000000000000000000
--- a/spaces/HuseynG/ECS7022P-WGAN-GP/utils.py
+++ /dev/null
@@ -1,162 +0,0 @@
-import time
-import random
-import threading 
-from gradio_client import Client
-
-import torch
-import torchvision
-import torch.nn as nn
-# import torch.optim as optim
-from torchvision.utils import save_image
-from torchvision.transforms import transforms
-device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-
-
-noise_dim = 100 
-img_channels = 3
-gen_features = 64
-critic_features = 64
-
-
-class Generator(nn.Module):
-  def __init__(self, noise_dim, img_channels, gen_features):
-    super(Generator, self).__init__()
-
-    self.gen = nn.Sequential(
-        # Input: N x noise_dim x 1 x 1
-        self._block(noise_dim, gen_features * 16, 4, 1, 0),
-        self._block(gen_features * 16, gen_features * 8, 4, 2, 1),
-        self._block(gen_features * 8, gen_features * 4, 4, 2, 1),
-        self._block(gen_features * 4, gen_features * 2, 4, 2, 1),
-        self._block(gen_features * 2, gen_features, 4, 2, 1),
-        self._block(gen_features, gen_features // 2, 4, 2, 1),
-        nn.ConvTranspose2d(gen_features // 2, img_channels, kernel_size=4, stride=2, padding=1),
-        nn.Tanh()
-        # Output: N x channels_img x 256 x 256
-    )
-
-  def _block(self, in_c, out_c, k_size, s_size, p_size): # This is a nice practice that I learned from: # https://github.com/aladdinpersson
-    return nn.Sequential(
-      nn.ConvTranspose2d(
-          in_c, out_c,
-          k_size, s_size, p_size
-      ),
-      nn.BatchNorm2d(out_c),
-      nn.ReLU(),
-    )
-
-  def forward(self, x):
-    return self.gen(x)
-
-
-class Critic(nn.Module): # aka discirminator (called critic in )
-    def __init__(self, img_channels, critic_features):
-        super(Critic, self).__init__()
-        self.critic = nn.Sequential(
-            # Input: N x channels_img x 256 x 256
-            nn.Conv2d(img_channels, critic_features, kernel_size=4, stride=2, padding=1),
-            nn.LeakyReLU(0.2),
-            self._block(critic_features, critic_features * 2, 4, 2, 1),
-            self._block(critic_features * 2, critic_features * 4, 4, 2, 1),
-            self._block(critic_features * 4, critic_features * 8 , 4, 2, 1),
-            self._block(critic_features * 8, critic_features * 16 , 4, 2, 1),
-            self._block(critic_features * 16, critic_features * 32 , 4, 2, 1),
-            nn.Conv2d(critic_features * 32, 1, kernel_size=4, stride=1, padding=0)
-            # Output: N x 1 x 1 x 1
-        )
-
-    def _block(self, in_c, out_c, k_size, s_size, p_size): # this is a nice practice that I learned from: # https://github.com/aladdinpersson
-      return nn.Sequential(
-        nn.Conv2d(
-          in_c, out_c,
-          k_size, s_size, p_size
-        ),
-        nn.BatchNorm2d(out_c),
-        nn.LeakyReLU(0.2),
-      )
-
-    def forward(self, x):
-        return self.critic(x)
-
-
-def weights_init(m):
-    if isinstance(m, (nn.Conv2d, nn.ConvTranspose2d, nn.Linear, nn.BatchNorm2d)):
-        nn.init.normal_(m.weight.data, 0.0, 0.02)
-        nn.init.constant_(m.bias.data, 0)
-
-# The following gradianet penalty funciton is take from:
-# https://github.com/aladdinpersson/Machine-Learning-Collection/blob/master/ML/Pytorch/GANs/4.%20WGAN-GP/utils.py 
-def gradient_penalty(critic, real, fake, device):
-    BATCH_SIZE, C, H, W = real.shape
-    alpha = torch.rand((BATCH_SIZE, 1, 1, 1)).repeat(1, C, H, W).to(device)
-    interpolated_images = real * alpha + fake * (1 - alpha)
-
-    # calculating the critic scores
-    mixed_scores = critic(interpolated_images)
-
-    # taking the gradient of the scores w.r.t the images
-    gradient = torch.autograd.grad(
-        inputs=interpolated_images,
-        outputs=mixed_scores,
-        grad_outputs=torch.ones_like(mixed_scores),
-        create_graph=True,
-        retain_graph=True,
-    )[0]
-    
-    gradient = gradient.view(gradient.shape[0], -1)
-    gradient_norm = gradient.norm(2, dim=1)
-    gradient_penalty = torch.mean((gradient_norm - 1) ** 2)
-    return gradient_penalty
-
-
-def load_model(model_type, model_path):
-    device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-    
-    # Loding the model based on the model_type
-    if model_type == 'generator':
-        model = Generator(noise_dim, img_channels, gen_features)
-    elif model_type == 'critic':
-        model = Critic(img_channels, critic_features)
-    else:
-        raise ValueError(f"Invalid model_type: {model_type}")
-
-    model.load_state_dict(torch.load(model_path, map_location=device))
-    model.to(device)
-    model.eval()
-
-    return model
-
-import torchvision.transforms as transforms
-from PIL import Image
-
-def generate_random_img(model):
-
-  # Creating a random noise tensor
-  noise = torch.randn(1, noise_dim, 1, 1).to(device)  # 1 is the number of images you want to generate
-
-  # Generating an image using the trained generator
-  with torch.no_grad():
-      generated_image = model(noise)
-
-  # Converting the generated tensor to a PIL image
-  generated_image = generated_image.cpu().detach().squeeze(0)
-  generated_image = transforms.ToPILImage()(generated_image)
-
-  return generated_image
-
-def schedule_function(): # for dummy space so that this spcae and other space will call each other to avoid sleep time, again this project is for academic purpose.
-  while True:
-    wait_time = random.uniform(3 * 60 * 60, 5 * 60 * 60)  # Get a random wait time between 3 and 5 hours in seconds
-    # wait_time = random.uniform(3, 5)
-    time.sleep(wait_time)
-    # call dummyscape
-    client = Client("https://huseyng-dummyspace.hf.space/")
-    result = client.predict(
-                    f"Howdy! {wait_time}",	# str representing string value in 'name' Textbox component
-                    api_name="/predict"
-    )
-    print(result)
-
-if __name__ == "__main__":
-    model = load_model('generator','generator_model_epoch_94.pth')
-    generate_random_img(model)
\ No newline at end of file
diff --git a/spaces/ICML2022/OFA/fairseq/examples/unsupervised_quality_estimation/meteor.py b/spaces/ICML2022/OFA/fairseq/examples/unsupervised_quality_estimation/meteor.py
deleted file mode 100644
index 2ee0448cf1f167f6f3ecee56ad807922cffb0956..0000000000000000000000000000000000000000
--- a/spaces/ICML2022/OFA/fairseq/examples/unsupervised_quality_estimation/meteor.py
+++ /dev/null
@@ -1,109 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import argparse
-import math
-import os
-import subprocess
-import sys
-import tempfile
-from collections import defaultdict
-from itertools import combinations
-
-
-def read_translations(path, n_repeats):
-    segment_counter = 0
-    segment_translations = []
-    translations = defaultdict(list)
-    for line in open(path):
-        segment_translations.append(" ".join(line.split()))
-        if len(segment_translations) == n_repeats:
-            translations[segment_counter] = segment_translations
-            segment_translations = []
-            segment_counter += 1
-    return translations
-
-
-def generate_input(translations, n_repeats):
-    _, ref_path = tempfile.mkstemp()
-    _, mt_path = tempfile.mkstemp()
-    ref_fh = open(ref_path, "w")
-    mt_fh = open(mt_path, "w")
-    for segid in sorted(translations.keys()):
-        assert len(translations[segid]) == n_repeats
-        indexes = combinations(range(n_repeats), 2)
-        for idx1, idx2 in indexes:
-            mt_fh.write(translations[segid][idx1].strip() + "\n")
-            ref_fh.write(translations[segid][idx2].strip() + "\n")
-    sys.stderr.write("\nSaved translations to %s and %s" % (ref_path, mt_path))
-    return ref_path, mt_path
-
-
-def run_meteor(ref_path, mt_path, metric_path, lang="en"):
-    _, out_path = tempfile.mkstemp()
-    subprocess.call(
-        [
-            "java",
-            "-Xmx2G",
-            "-jar",
-            metric_path,
-            mt_path,
-            ref_path,
-            "-p",
-            "0.5 0.2 0.6 0.75",  # default parameters, only changed alpha to give equal weight to P and R
-            "-norm",
-            "-l",
-            lang,
-        ],
-        stdout=open(out_path, "w"),
-    )
-    os.remove(ref_path)
-    os.remove(mt_path)
-    sys.stderr.write("\nSaved Meteor output to %s" % out_path)
-    return out_path
-
-
-def read_output(meteor_output_path, n_repeats):
-    n_combinations = math.factorial(n_repeats) / (
-        math.factorial(2) * math.factorial(n_repeats - 2)
-    )
-    raw_scores = []
-    average_scores = []
-    for line in open(meteor_output_path):
-        if not line.startswith("Segment "):
-            continue
-        score = float(line.strip().split("\t")[1])
-        raw_scores.append(score)
-        if len(raw_scores) == n_combinations:
-            average_scores.append(sum(raw_scores) / n_combinations)
-            raw_scores = []
-    os.remove(meteor_output_path)
-    return average_scores
-
-
-def main():
-    parser = argparse.ArgumentParser()
-    parser.add_argument("-i", "--infile")
-    parser.add_argument("-n", "--repeat_times", type=int)
-    parser.add_argument("-m", "--meteor")
-    parser.add_argument("-o", "--output")
-    args = parser.parse_args()
-
-    translations = read_translations(args.infile, args.repeat_times)
-    sys.stderr.write("\nGenerating input for Meteor...")
-    ref_path, mt_path = generate_input(translations, args.repeat_times)
-    sys.stderr.write("\nRunning Meteor...")
-    out_path = run_meteor(ref_path, mt_path, args.meteor)
-    sys.stderr.write("\nReading output...")
-    scores = read_output(out_path, args.repeat_times)
-    sys.stderr.write("\nWriting results...")
-    with open(args.output, "w") as o:
-        for scr in scores:
-            o.write("{}\n".format(scr))
-    o.close()
-
-
-if __name__ == "__main__":
-    main()
diff --git a/spaces/ICML2022/OFA/fairseq/fairseq/modules/base_layer.py b/spaces/ICML2022/OFA/fairseq/fairseq/modules/base_layer.py
deleted file mode 100644
index e7ef155b25fc73e74780879f665288c9bc95fd80..0000000000000000000000000000000000000000
--- a/spaces/ICML2022/OFA/fairseq/fairseq/modules/base_layer.py
+++ /dev/null
@@ -1,135 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import torch.nn as nn
-import torch
-import sys
-from fairseq import utils
-from fairseq.distributed import utils as distributed_utils
-from fairseq.modules.layer_norm import LayerNorm
-
-
-class BaseLayer(nn.Module):
-
-    def __init__(self, args):
-        super().__init__()
-        self.num_workers = distributed_utils.get_data_parallel_world_size()
-        expert_centroids = torch.empty(self.num_workers, args.decoder_embed_dim)
-        torch.nn.init.orthogonal_(expert_centroids, gain=0.1)
-        self.register_parameter("expert_centroids", torch.nn.Parameter(expert_centroids))
-        self.expert_network = nn.Sequential(*([BaseSublayer(args) for _ in range(args.base_sublayers)]))
-        self.expert_id = distributed_utils.get_data_parallel_rank()
-        self.shuffle = args.base_shuffle
-        self.cpp = self.load_assignment()
-
-        # Add a special attribute to the expert parameters, so we know not to sync their gradients
-        for param in self.expert_network.parameters():
-            param.expert = True
-
-    def forward(self, input_features, *args, **kwargs):
-        features = input_features.reshape(-1, input_features.size(-1))
-        is_training = input_features.requires_grad
-
-        if self.shuffle and is_training:
-            # Send each token to a random worker, to break correlations within the batch
-            shuffle_sort = torch.randperm(features.size(0), device=features.device)
-            features = All2All.apply(features[shuffle_sort])
-
-        with torch.no_grad():
-            # Compute similarity of each token to each expert, for routing
-            token_expert_affinities = features.matmul(self.expert_centroids.transpose(0, 1))
-
-        # Compute which token goes to which expert
-        sort_by_expert, input_splits, output_splits = self.balanced_assignment(token_expert_affinities) \
-            if is_training else self.greedy_assignment(token_expert_affinities)
-        # Swap these tokens for the right ones for our expert
-        routed_features = All2All.apply(features[sort_by_expert], output_splits, input_splits)
-
-        if routed_features.size(0) > 0:
-            # Mix in the expert network based on how appropriate it is for these tokens
-            alpha = torch.sigmoid(routed_features.mv(self.expert_centroids[self.expert_id])).unsqueeze(1)
-            routed_features = alpha * self.expert_network(routed_features) + (1 - alpha) * routed_features
-        # Return to original worker and ordering
-        result = All2All.apply(routed_features, input_splits, output_splits)[self.inverse_sort(sort_by_expert)]
-
-        if self.shuffle and is_training:
-            # Undo shuffling
-            result = All2All.apply(result)[self.inverse_sort(shuffle_sort)]
-
-        # Return additional Nones for compatibility with TransformerDecoderLayer
-        return result.view(input_features.size()), None, None
-
-    def inverse_sort(self, order):
-        # Creates an index that undoes a sort: xs==xs[order][inverse_sort(order)]
-        return torch.empty_like(order).scatter_(0, order, torch.arange(0, order.size(0), device=order.device))
-
-    def balanced_assignment(self, scores):
-        ok = scores.isfinite()
-        if not ok.all():
-            # NaNs here can break the assignment algorithm
-            scores[~ok] = scores[ok].min()
-        return self.cpp.balanced_assignment(scores), None, None
-
-    # Assigns each token to the top k experts
-    def greedy_assignment(self, scores, k=1):
-        token_to_workers = torch.topk(scores, dim=1, k=k, largest=True).indices.view(-1)
-        token_to_workers, sort_ordering = torch.sort(token_to_workers)
-        worker2token = sort_ordering // k
-
-        # Find how many tokens we're sending to each other worker (being careful for sending 0 tokens to some workers)
-        output_splits = torch.zeros((self.num_workers,), dtype=torch.long, device=scores.device)
-        workers, counts = torch.unique_consecutive(token_to_workers, return_counts=True)
-        output_splits[workers] = counts
-        # Tell other workers how many tokens to expect from us
-        input_splits = All2All.apply(output_splits)
-        return worker2token, input_splits.tolist(), output_splits.tolist()
-
-    def load_assignment(self):
-        try:
-            from fairseq import libbase
-
-            return libbase
-
-        except ImportError as e:
-            sys.stderr.write(
-                "ERROR: missing libbase. run `python setup.py build_ext --inplace`\n"
-            )
-            raise e
-
-
-class BaseSublayer(nn.Module):
-    def __init__(self, args):
-        super().__init__()
-        self.activation_fn = utils.get_activation_fn(
-            activation=getattr(args, 'activation_fn', 'relu') or "relu"
-        )
-        self.norm = LayerNorm(args.decoder_embed_dim, export=False)
-        self.ff1 = torch.nn.Linear(args.decoder_embed_dim, args.decoder_ffn_embed_dim)
-        self.ff2 = torch.nn.Linear(args.decoder_ffn_embed_dim, args.decoder_embed_dim)
-        self.ff2.weight.data.zero_()
-
-    def forward(self, xs):
-        return xs + self.ff2(self.activation_fn(self.ff1(self.norm(xs))))
-
-
-# Wraps torch.distributed.all_to_all_single as a function that supports autograd
-class All2All(torch.autograd.Function):
-    @staticmethod
-    def forward(ctx, xs, input_splits=None, output_splits=None):
-        ctx.input_splits = input_splits
-        ctx.output_splits = output_splits
-
-        ys = torch.empty_like(xs) if output_splits is None else \
-            xs.new_empty(size=[sum(output_splits)] + list(xs.size()[1:]))
-        torch.distributed.all_to_all_single(ys, xs, output_split_sizes=output_splits, input_split_sizes=input_splits)
-        return ys
-
-    @staticmethod
-    def backward(ctx, grad_output):
-        result = torch.empty_like(grad_output) if ctx.input_splits is None else \
-            grad_output.new_empty(size=[sum(ctx.input_splits)] + list(grad_output.size()[1:]))
-        torch.distributed.all_to_all_single(result, grad_output,
-                                            output_split_sizes=ctx.input_splits, input_split_sizes=ctx.output_splits)
-        return result, None, None
diff --git a/spaces/ICML2022/OFA/fairseq/fairseq/modules/dynamicconv_layer/__init__.py b/spaces/ICML2022/OFA/fairseq/fairseq/modules/dynamicconv_layer/__init__.py
deleted file mode 100644
index 22dc6f403d2a0ecdb1b9e7e69ed96bd560e93b2c..0000000000000000000000000000000000000000
--- a/spaces/ICML2022/OFA/fairseq/fairseq/modules/dynamicconv_layer/__init__.py
+++ /dev/null
@@ -1,6 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-from .dynamicconv_layer import DynamicconvLayer  # noqa
diff --git a/spaces/Iceclear/StableSR/StableSR/basicsr/data/data_sampler.py b/spaces/Iceclear/StableSR/StableSR/basicsr/data/data_sampler.py
deleted file mode 100644
index 575452d9f844a928f7f42296c81635cfbadec7c2..0000000000000000000000000000000000000000
--- a/spaces/Iceclear/StableSR/StableSR/basicsr/data/data_sampler.py
+++ /dev/null
@@ -1,48 +0,0 @@
-import math
-import torch
-from torch.utils.data.sampler import Sampler
-
-
-class EnlargedSampler(Sampler):
-    """Sampler that restricts data loading to a subset of the dataset.
-
-    Modified from torch.utils.data.distributed.DistributedSampler
-    Support enlarging the dataset for iteration-based training, for saving
-    time when restart the dataloader after each epoch
-
-    Args:
-        dataset (torch.utils.data.Dataset): Dataset used for sampling.
-        num_replicas (int | None): Number of processes participating in
-            the training. It is usually the world_size.
-        rank (int | None): Rank of the current process within num_replicas.
-        ratio (int): Enlarging ratio. Default: 1.
-    """
-
-    def __init__(self, dataset, num_replicas, rank, ratio=1):
-        self.dataset = dataset
-        self.num_replicas = num_replicas
-        self.rank = rank
-        self.epoch = 0
-        self.num_samples = math.ceil(len(self.dataset) * ratio / self.num_replicas)
-        self.total_size = self.num_samples * self.num_replicas
-
-    def __iter__(self):
-        # deterministically shuffle based on epoch
-        g = torch.Generator()
-        g.manual_seed(self.epoch)
-        indices = torch.randperm(self.total_size, generator=g).tolist()
-
-        dataset_size = len(self.dataset)
-        indices = [v % dataset_size for v in indices]
-
-        # subsample
-        indices = indices[self.rank:self.total_size:self.num_replicas]
-        assert len(indices) == self.num_samples
-
-        return iter(indices)
-
-    def __len__(self):
-        return self.num_samples
-
-    def set_epoch(self, epoch):
-        self.epoch = epoch
diff --git a/spaces/Iceclear/StableSR/StableSR/ldm/modules/image_degradation/bsrgan_light.py b/spaces/Iceclear/StableSR/StableSR/ldm/modules/image_degradation/bsrgan_light.py
deleted file mode 100644
index 9e1f823996bf559e9b015ea9aa2b3cd38dd13af1..0000000000000000000000000000000000000000
--- a/spaces/Iceclear/StableSR/StableSR/ldm/modules/image_degradation/bsrgan_light.py
+++ /dev/null
@@ -1,650 +0,0 @@
-# -*- coding: utf-8 -*-
-import numpy as np
-import cv2
-import torch
-
-from functools import partial
-import random
-from scipy import ndimage
-import scipy
-import scipy.stats as ss
-from scipy.interpolate import interp2d
-from scipy.linalg import orth
-import albumentations
-
-import ldm.modules.image_degradation.utils_image as util
-
-"""
-# --------------------------------------------
-# Super-Resolution
-# --------------------------------------------
-#
-# Kai Zhang (cskaizhang@gmail.com)
-# https://github.com/cszn
-# From 2019/03--2021/08
-# --------------------------------------------
-"""
-
-
-def modcrop_np(img, sf):
-    '''
-    Args:
-        img: numpy image, WxH or WxHxC
-        sf: scale factor
-    Return:
-        cropped image
-    '''
-    w, h = img.shape[:2]
-    im = np.copy(img)
-    return im[:w - w % sf, :h - h % sf, ...]
-
-
-"""
-# --------------------------------------------
-# anisotropic Gaussian kernels
-# --------------------------------------------
-"""
-
-
-def analytic_kernel(k):
-    """Calculate the X4 kernel from the X2 kernel (for proof see appendix in paper)"""
-    k_size = k.shape[0]
-    # Calculate the big kernels size
-    big_k = np.zeros((3 * k_size - 2, 3 * k_size - 2))
-    # Loop over the small kernel to fill the big one
-    for r in range(k_size):
-        for c in range(k_size):
-            big_k[2 * r:2 * r + k_size, 2 * c:2 * c + k_size] += k[r, c] * k
-    # Crop the edges of the big kernel to ignore very small values and increase run time of SR
-    crop = k_size // 2
-    cropped_big_k = big_k[crop:-crop, crop:-crop]
-    # Normalize to 1
-    return cropped_big_k / cropped_big_k.sum()
-
-
-def anisotropic_Gaussian(ksize=15, theta=np.pi, l1=6, l2=6):
-    """ generate an anisotropic Gaussian kernel
-    Args:
-        ksize : e.g., 15, kernel size
-        theta : [0,  pi], rotation angle range
-        l1    : [0.1,50], scaling of eigenvalues
-        l2    : [0.1,l1], scaling of eigenvalues
-        If l1 = l2, will get an isotropic Gaussian kernel.
-    Returns:
-        k     : kernel
-    """
-
-    v = np.dot(np.array([[np.cos(theta), -np.sin(theta)], [np.sin(theta), np.cos(theta)]]), np.array([1., 0.]))
-    V = np.array([[v[0], v[1]], [v[1], -v[0]]])
-    D = np.array([[l1, 0], [0, l2]])
-    Sigma = np.dot(np.dot(V, D), np.linalg.inv(V))
-    k = gm_blur_kernel(mean=[0, 0], cov=Sigma, size=ksize)
-
-    return k
-
-
-def gm_blur_kernel(mean, cov, size=15):
-    center = size / 2.0 + 0.5
-    k = np.zeros([size, size])
-    for y in range(size):
-        for x in range(size):
-            cy = y - center + 1
-            cx = x - center + 1
-            k[y, x] = ss.multivariate_normal.pdf([cx, cy], mean=mean, cov=cov)
-
-    k = k / np.sum(k)
-    return k
-
-
-def shift_pixel(x, sf, upper_left=True):
-    """shift pixel for super-resolution with different scale factors
-    Args:
-        x: WxHxC or WxH
-        sf: scale factor
-        upper_left: shift direction
-    """
-    h, w = x.shape[:2]
-    shift = (sf - 1) * 0.5
-    xv, yv = np.arange(0, w, 1.0), np.arange(0, h, 1.0)
-    if upper_left:
-        x1 = xv + shift
-        y1 = yv + shift
-    else:
-        x1 = xv - shift
-        y1 = yv - shift
-
-    x1 = np.clip(x1, 0, w - 1)
-    y1 = np.clip(y1, 0, h - 1)
-
-    if x.ndim == 2:
-        x = interp2d(xv, yv, x)(x1, y1)
-    if x.ndim == 3:
-        for i in range(x.shape[-1]):
-            x[:, :, i] = interp2d(xv, yv, x[:, :, i])(x1, y1)
-
-    return x
-
-
-def blur(x, k):
-    '''
-    x: image, NxcxHxW
-    k: kernel, Nx1xhxw
-    '''
-    n, c = x.shape[:2]
-    p1, p2 = (k.shape[-2] - 1) // 2, (k.shape[-1] - 1) // 2
-    x = torch.nn.functional.pad(x, pad=(p1, p2, p1, p2), mode='replicate')
-    k = k.repeat(1, c, 1, 1)
-    k = k.view(-1, 1, k.shape[2], k.shape[3])
-    x = x.view(1, -1, x.shape[2], x.shape[3])
-    x = torch.nn.functional.conv2d(x, k, bias=None, stride=1, padding=0, groups=n * c)
-    x = x.view(n, c, x.shape[2], x.shape[3])
-
-    return x
-
-
-def gen_kernel(k_size=np.array([15, 15]), scale_factor=np.array([4, 4]), min_var=0.6, max_var=10., noise_level=0):
-    """"
-    # modified version of https://github.com/assafshocher/BlindSR_dataset_generator
-    # Kai Zhang
-    # min_var = 0.175 * sf  # variance of the gaussian kernel will be sampled between min_var and max_var
-    # max_var = 2.5 * sf
-    """
-    # Set random eigen-vals (lambdas) and angle (theta) for COV matrix
-    lambda_1 = min_var + np.random.rand() * (max_var - min_var)
-    lambda_2 = min_var + np.random.rand() * (max_var - min_var)
-    theta = np.random.rand() * np.pi  # random theta
-    noise = -noise_level + np.random.rand(*k_size) * noise_level * 2
-
-    # Set COV matrix using Lambdas and Theta
-    LAMBDA = np.diag([lambda_1, lambda_2])
-    Q = np.array([[np.cos(theta), -np.sin(theta)],
-                  [np.sin(theta), np.cos(theta)]])
-    SIGMA = Q @ LAMBDA @ Q.T
-    INV_SIGMA = np.linalg.inv(SIGMA)[None, None, :, :]
-
-    # Set expectation position (shifting kernel for aligned image)
-    MU = k_size // 2 - 0.5 * (scale_factor - 1)  # - 0.5 * (scale_factor - k_size % 2)
-    MU = MU[None, None, :, None]
-
-    # Create meshgrid for Gaussian
-    [X, Y] = np.meshgrid(range(k_size[0]), range(k_size[1]))
-    Z = np.stack([X, Y], 2)[:, :, :, None]
-
-    # Calcualte Gaussian for every pixel of the kernel
-    ZZ = Z - MU
-    ZZ_t = ZZ.transpose(0, 1, 3, 2)
-    raw_kernel = np.exp(-0.5 * np.squeeze(ZZ_t @ INV_SIGMA @ ZZ)) * (1 + noise)
-
-    # shift the kernel so it will be centered
-    # raw_kernel_centered = kernel_shift(raw_kernel, scale_factor)
-
-    # Normalize the kernel and return
-    # kernel = raw_kernel_centered / np.sum(raw_kernel_centered)
-    kernel = raw_kernel / np.sum(raw_kernel)
-    return kernel
-
-
-def fspecial_gaussian(hsize, sigma):
-    hsize = [hsize, hsize]
-    siz = [(hsize[0] - 1.0) / 2.0, (hsize[1] - 1.0) / 2.0]
-    std = sigma
-    [x, y] = np.meshgrid(np.arange(-siz[1], siz[1] + 1), np.arange(-siz[0], siz[0] + 1))
-    arg = -(x * x + y * y) / (2 * std * std)
-    h = np.exp(arg)
-    h[h < scipy.finfo(float).eps * h.max()] = 0
-    sumh = h.sum()
-    if sumh != 0:
-        h = h / sumh
-    return h
-
-
-def fspecial_laplacian(alpha):
-    alpha = max([0, min([alpha, 1])])
-    h1 = alpha / (alpha + 1)
-    h2 = (1 - alpha) / (alpha + 1)
-    h = [[h1, h2, h1], [h2, -4 / (alpha + 1), h2], [h1, h2, h1]]
-    h = np.array(h)
-    return h
-
-
-def fspecial(filter_type, *args, **kwargs):
-    '''
-    python code from:
-    https://github.com/ronaldosena/imagens-medicas-2/blob/40171a6c259edec7827a6693a93955de2bd39e76/Aulas/aula_2_-_uniform_filter/matlab_fspecial.py
-    '''
-    if filter_type == 'gaussian':
-        return fspecial_gaussian(*args, **kwargs)
-    if filter_type == 'laplacian':
-        return fspecial_laplacian(*args, **kwargs)
-
-
-"""
-# --------------------------------------------
-# degradation models
-# --------------------------------------------
-"""
-
-
-def bicubic_degradation(x, sf=3):
-    '''
-    Args:
-        x: HxWxC image, [0, 1]
-        sf: down-scale factor
-    Return:
-        bicubicly downsampled LR image
-    '''
-    x = util.imresize_np(x, scale=1 / sf)
-    return x
-
-
-def srmd_degradation(x, k, sf=3):
-    ''' blur + bicubic downsampling
-    Args:
-        x: HxWxC image, [0, 1]
-        k: hxw, double
-        sf: down-scale factor
-    Return:
-        downsampled LR image
-    Reference:
-        @inproceedings{zhang2018learning,
-          title={Learning a single convolutional super-resolution network for multiple degradations},
-          author={Zhang, Kai and Zuo, Wangmeng and Zhang, Lei},
-          booktitle={IEEE Conference on Computer Vision and Pattern Recognition},
-          pages={3262--3271},
-          year={2018}
-        }
-    '''
-    x = ndimage.filters.convolve(x, np.expand_dims(k, axis=2), mode='wrap')  # 'nearest' | 'mirror'
-    x = bicubic_degradation(x, sf=sf)
-    return x
-
-
-def dpsr_degradation(x, k, sf=3):
-    ''' bicubic downsampling + blur
-    Args:
-        x: HxWxC image, [0, 1]
-        k: hxw, double
-        sf: down-scale factor
-    Return:
-        downsampled LR image
-    Reference:
-        @inproceedings{zhang2019deep,
-          title={Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels},
-          author={Zhang, Kai and Zuo, Wangmeng and Zhang, Lei},
-          booktitle={IEEE Conference on Computer Vision and Pattern Recognition},
-          pages={1671--1681},
-          year={2019}
-        }
-    '''
-    x = bicubic_degradation(x, sf=sf)
-    x = ndimage.filters.convolve(x, np.expand_dims(k, axis=2), mode='wrap')
-    return x
-
-
-def classical_degradation(x, k, sf=3):
-    ''' blur + downsampling
-    Args:
-        x: HxWxC image, [0, 1]/[0, 255]
-        k: hxw, double
-        sf: down-scale factor
-    Return:
-        downsampled LR image
-    '''
-    x = ndimage.filters.convolve(x, np.expand_dims(k, axis=2), mode='wrap')
-    # x = filters.correlate(x, np.expand_dims(np.flip(k), axis=2))
-    st = 0
-    return x[st::sf, st::sf, ...]
-
-
-def add_sharpening(img, weight=0.5, radius=50, threshold=10):
-    """USM sharpening. borrowed from real-ESRGAN
-    Input image: I; Blurry image: B.
-    1. K = I + weight * (I - B)
-    2. Mask = 1 if abs(I - B) > threshold, else: 0
-    3. Blur mask:
-    4. Out = Mask * K + (1 - Mask) * I
-    Args:
-        img (Numpy array): Input image, HWC, BGR; float32, [0, 1].
-        weight (float): Sharp weight. Default: 1.
-        radius (float): Kernel size of Gaussian blur. Default: 50.
-        threshold (int):
-    """
-    if radius % 2 == 0:
-        radius += 1
-    blur = cv2.GaussianBlur(img, (radius, radius), 0)
-    residual = img - blur
-    mask = np.abs(residual) * 255 > threshold
-    mask = mask.astype('float32')
-    soft_mask = cv2.GaussianBlur(mask, (radius, radius), 0)
-
-    K = img + weight * residual
-    K = np.clip(K, 0, 1)
-    return soft_mask * K + (1 - soft_mask) * img
-
-
-def add_blur(img, sf=4):
-    wd2 = 4.0 + sf
-    wd = 2.0 + 0.2 * sf
-
-    wd2 = wd2/4
-    wd = wd/4
-
-    if random.random() < 0.5:
-        l1 = wd2 * random.random()
-        l2 = wd2 * random.random()
-        k = anisotropic_Gaussian(ksize=random.randint(2, 11) + 3, theta=random.random() * np.pi, l1=l1, l2=l2)
-    else:
-        k = fspecial('gaussian', random.randint(2, 4) + 3, wd * random.random())
-    img = ndimage.filters.convolve(img, np.expand_dims(k, axis=2), mode='mirror')
-
-    return img
-
-
-def add_resize(img, sf=4):
-    rnum = np.random.rand()
-    if rnum > 0.8:  # up
-        sf1 = random.uniform(1, 2)
-    elif rnum < 0.7:  # down
-        sf1 = random.uniform(0.5 / sf, 1)
-    else:
-        sf1 = 1.0
-    img = cv2.resize(img, (int(sf1 * img.shape[1]), int(sf1 * img.shape[0])), interpolation=random.choice([1, 2, 3]))
-    img = np.clip(img, 0.0, 1.0)
-
-    return img
-
-
-# def add_Gaussian_noise(img, noise_level1=2, noise_level2=25):
-#     noise_level = random.randint(noise_level1, noise_level2)
-#     rnum = np.random.rand()
-#     if rnum > 0.6:  # add color Gaussian noise
-#         img += np.random.normal(0, noise_level / 255.0, img.shape).astype(np.float32)
-#     elif rnum < 0.4:  # add grayscale Gaussian noise
-#         img += np.random.normal(0, noise_level / 255.0, (*img.shape[:2], 1)).astype(np.float32)
-#     else:  # add  noise
-#         L = noise_level2 / 255.
-#         D = np.diag(np.random.rand(3))
-#         U = orth(np.random.rand(3, 3))
-#         conv = np.dot(np.dot(np.transpose(U), D), U)
-#         img += np.random.multivariate_normal([0, 0, 0], np.abs(L ** 2 * conv), img.shape[:2]).astype(np.float32)
-#     img = np.clip(img, 0.0, 1.0)
-#     return img
-
-def add_Gaussian_noise(img, noise_level1=2, noise_level2=25):
-    noise_level = random.randint(noise_level1, noise_level2)
-    rnum = np.random.rand()
-    if rnum > 0.6:  # add color Gaussian noise
-        img = img + np.random.normal(0, noise_level / 255.0, img.shape).astype(np.float32)
-    elif rnum < 0.4:  # add grayscale Gaussian noise
-        img = img + np.random.normal(0, noise_level / 255.0, (*img.shape[:2], 1)).astype(np.float32)
-    else:  # add  noise
-        L = noise_level2 / 255.
-        D = np.diag(np.random.rand(3))
-        U = orth(np.random.rand(3, 3))
-        conv = np.dot(np.dot(np.transpose(U), D), U)
-        img = img + np.random.multivariate_normal([0, 0, 0], np.abs(L ** 2 * conv), img.shape[:2]).astype(np.float32)
-    img = np.clip(img, 0.0, 1.0)
-    return img
-
-
-def add_speckle_noise(img, noise_level1=2, noise_level2=25):
-    noise_level = random.randint(noise_level1, noise_level2)
-    img = np.clip(img, 0.0, 1.0)
-    rnum = random.random()
-    if rnum > 0.6:
-        img += img * np.random.normal(0, noise_level / 255.0, img.shape).astype(np.float32)
-    elif rnum < 0.4:
-        img += img * np.random.normal(0, noise_level / 255.0, (*img.shape[:2], 1)).astype(np.float32)
-    else:
-        L = noise_level2 / 255.
-        D = np.diag(np.random.rand(3))
-        U = orth(np.random.rand(3, 3))
-        conv = np.dot(np.dot(np.transpose(U), D), U)
-        img += img * np.random.multivariate_normal([0, 0, 0], np.abs(L ** 2 * conv), img.shape[:2]).astype(np.float32)
-    img = np.clip(img, 0.0, 1.0)
-    return img
-
-
-def add_Poisson_noise(img):
-    img = np.clip((img * 255.0).round(), 0, 255) / 255.
-    vals = 10 ** (2 * random.random() + 2.0)  # [2, 4]
-    if random.random() < 0.5:
-        img = np.random.poisson(img * vals).astype(np.float32) / vals
-    else:
-        img_gray = np.dot(img[..., :3], [0.299, 0.587, 0.114])
-        img_gray = np.clip((img_gray * 255.0).round(), 0, 255) / 255.
-        noise_gray = np.random.poisson(img_gray * vals).astype(np.float32) / vals - img_gray
-        img += noise_gray[:, :, np.newaxis]
-    img = np.clip(img, 0.0, 1.0)
-    return img
-
-
-def add_JPEG_noise(img):
-    quality_factor = random.randint(80, 95)
-    img = cv2.cvtColor(util.single2uint(img), cv2.COLOR_RGB2BGR)
-    result, encimg = cv2.imencode('.jpg', img, [int(cv2.IMWRITE_JPEG_QUALITY), quality_factor])
-    img = cv2.imdecode(encimg, 1)
-    img = cv2.cvtColor(util.uint2single(img), cv2.COLOR_BGR2RGB)
-    return img
-
-
-def random_crop(lq, hq, sf=4, lq_patchsize=64):
-    h, w = lq.shape[:2]
-    rnd_h = random.randint(0, h - lq_patchsize)
-    rnd_w = random.randint(0, w - lq_patchsize)
-    lq = lq[rnd_h:rnd_h + lq_patchsize, rnd_w:rnd_w + lq_patchsize, :]
-
-    rnd_h_H, rnd_w_H = int(rnd_h * sf), int(rnd_w * sf)
-    hq = hq[rnd_h_H:rnd_h_H + lq_patchsize * sf, rnd_w_H:rnd_w_H + lq_patchsize * sf, :]
-    return lq, hq
-
-
-def degradation_bsrgan(img, sf=4, lq_patchsize=72, isp_model=None):
-    """
-    This is the degradation model of BSRGAN from the paper
-    "Designing a Practical Degradation Model for Deep Blind Image Super-Resolution"
-    ----------
-    img: HXWXC, [0, 1], its size should be large than (lq_patchsizexsf)x(lq_patchsizexsf)
-    sf: scale factor
-    isp_model: camera ISP model
-    Returns
-    -------
-    img: low-quality patch, size: lq_patchsizeXlq_patchsizeXC, range: [0, 1]
-    hq: corresponding high-quality patch, size: (lq_patchsizexsf)X(lq_patchsizexsf)XC, range: [0, 1]
-    """
-    isp_prob, jpeg_prob, scale2_prob = 0.25, 0.9, 0.25
-    sf_ori = sf
-
-    h1, w1 = img.shape[:2]
-    img = img.copy()[:w1 - w1 % sf, :h1 - h1 % sf, ...]  # mod crop
-    h, w = img.shape[:2]
-
-    if h < lq_patchsize * sf or w < lq_patchsize * sf:
-        raise ValueError(f'img size ({h1}X{w1}) is too small!')
-
-    hq = img.copy()
-
-    if sf == 4 and random.random() < scale2_prob:  # downsample1
-        if np.random.rand() < 0.5:
-            img = cv2.resize(img, (int(1 / 2 * img.shape[1]), int(1 / 2 * img.shape[0])),
-                             interpolation=random.choice([1, 2, 3]))
-        else:
-            img = util.imresize_np(img, 1 / 2, True)
-        img = np.clip(img, 0.0, 1.0)
-        sf = 2
-
-    shuffle_order = random.sample(range(7), 7)
-    idx1, idx2 = shuffle_order.index(2), shuffle_order.index(3)
-    if idx1 > idx2:  # keep downsample3 last
-        shuffle_order[idx1], shuffle_order[idx2] = shuffle_order[idx2], shuffle_order[idx1]
-
-    for i in shuffle_order:
-
-        if i == 0:
-            img = add_blur(img, sf=sf)
-
-        elif i == 1:
-            img = add_blur(img, sf=sf)
-
-        elif i == 2:
-            a, b = img.shape[1], img.shape[0]
-            # downsample2
-            if random.random() < 0.75:
-                sf1 = random.uniform(1, 2 * sf)
-                img = cv2.resize(img, (int(1 / sf1 * img.shape[1]), int(1 / sf1 * img.shape[0])),
-                                 interpolation=random.choice([1, 2, 3]))
-            else:
-                k = fspecial('gaussian', 25, random.uniform(0.1, 0.6 * sf))
-                k_shifted = shift_pixel(k, sf)
-                k_shifted = k_shifted / k_shifted.sum()  # blur with shifted kernel
-                img = ndimage.filters.convolve(img, np.expand_dims(k_shifted, axis=2), mode='mirror')
-                img = img[0::sf, 0::sf, ...]  # nearest downsampling
-            img = np.clip(img, 0.0, 1.0)
-
-        elif i == 3:
-            # downsample3
-            img = cv2.resize(img, (int(1 / sf * a), int(1 / sf * b)), interpolation=random.choice([1, 2, 3]))
-            img = np.clip(img, 0.0, 1.0)
-
-        elif i == 4:
-            # add Gaussian noise
-            img = add_Gaussian_noise(img, noise_level1=2, noise_level2=8)
-
-        elif i == 5:
-            # add JPEG noise
-            if random.random() < jpeg_prob:
-                img = add_JPEG_noise(img)
-
-        elif i == 6:
-            # add processed camera sensor noise
-            if random.random() < isp_prob and isp_model is not None:
-                with torch.no_grad():
-                    img, hq = isp_model.forward(img.copy(), hq)
-
-    # add final JPEG compression noise
-    img = add_JPEG_noise(img)
-
-    # random crop
-    img, hq = random_crop(img, hq, sf_ori, lq_patchsize)
-
-    return img, hq
-
-
-# todo no isp_model?
-def degradation_bsrgan_variant(image, sf=4, isp_model=None):
-    """
-    This is the degradation model of BSRGAN from the paper
-    "Designing a Practical Degradation Model for Deep Blind Image Super-Resolution"
-    ----------
-    sf: scale factor
-    isp_model: camera ISP model
-    Returns
-    -------
-    img: low-quality patch, size: lq_patchsizeXlq_patchsizeXC, range: [0, 1]
-    hq: corresponding high-quality patch, size: (lq_patchsizexsf)X(lq_patchsizexsf)XC, range: [0, 1]
-    """
-    image = util.uint2single(image)
-    isp_prob, jpeg_prob, scale2_prob = 0.25, 0.9, 0.25
-    sf_ori = sf
-
-    h1, w1 = image.shape[:2]
-    image = image.copy()[:w1 - w1 % sf, :h1 - h1 % sf, ...]  # mod crop
-    h, w = image.shape[:2]
-
-    hq = image.copy()
-
-    if sf == 4 and random.random() < scale2_prob:  # downsample1
-        if np.random.rand() < 0.5:
-            image = cv2.resize(image, (int(1 / 2 * image.shape[1]), int(1 / 2 * image.shape[0])),
-                               interpolation=random.choice([1, 2, 3]))
-        else:
-            image = util.imresize_np(image, 1 / 2, True)
-        image = np.clip(image, 0.0, 1.0)
-        sf = 2
-
-    shuffle_order = random.sample(range(7), 7)
-    idx1, idx2 = shuffle_order.index(2), shuffle_order.index(3)
-    if idx1 > idx2:  # keep downsample3 last
-        shuffle_order[idx1], shuffle_order[idx2] = shuffle_order[idx2], shuffle_order[idx1]
-
-    for i in shuffle_order:
-
-        if i == 0:
-            image = add_blur(image, sf=sf)
-
-        # elif i == 1:
-        #     image = add_blur(image, sf=sf)
-
-        if i == 0:
-            pass
-
-        elif i == 2:
-            a, b = image.shape[1], image.shape[0]
-            # downsample2
-            if random.random() < 0.8:
-                sf1 = random.uniform(1, 2 * sf)
-                image = cv2.resize(image, (int(1 / sf1 * image.shape[1]), int(1 / sf1 * image.shape[0])),
-                                   interpolation=random.choice([1, 2, 3]))
-            else:
-                k = fspecial('gaussian', 25, random.uniform(0.1, 0.6 * sf))
-                k_shifted = shift_pixel(k, sf)
-                k_shifted = k_shifted / k_shifted.sum()  # blur with shifted kernel
-                image = ndimage.filters.convolve(image, np.expand_dims(k_shifted, axis=2), mode='mirror')
-                image = image[0::sf, 0::sf, ...]  # nearest downsampling
-
-            image = np.clip(image, 0.0, 1.0)
-
-        elif i == 3:
-            # downsample3
-            image = cv2.resize(image, (int(1 / sf * a), int(1 / sf * b)), interpolation=random.choice([1, 2, 3]))
-            image = np.clip(image, 0.0, 1.0)
-
-        elif i == 4:
-            # add Gaussian noise
-            image = add_Gaussian_noise(image, noise_level1=1, noise_level2=2)
-
-        elif i == 5:
-            # add JPEG noise
-            if random.random() < jpeg_prob:
-                image = add_JPEG_noise(image)
-        #
-        # elif i == 6:
-        #     # add processed camera sensor noise
-        #     if random.random() < isp_prob and isp_model is not None:
-        #         with torch.no_grad():
-        #             img, hq = isp_model.forward(img.copy(), hq)
-
-    # add final JPEG compression noise
-    image = add_JPEG_noise(image)
-    image = util.single2uint(image)
-    example = {"image": image}
-    return example
-
-
-
-
-if __name__ == '__main__':
-    print("hey")
-    img = util.imread_uint('utils/test.png', 3)
-    img = img[:448, :448]
-    h = img.shape[0] // 4
-    print("resizing to", h)
-    sf = 4
-    deg_fn = partial(degradation_bsrgan_variant, sf=sf)
-    for i in range(20):
-        print(i)
-        img_hq = img
-        img_lq = deg_fn(img)["image"]
-        img_hq, img_lq = util.uint2single(img_hq), util.uint2single(img_lq)
-        print(img_lq)
-        img_lq_bicubic = albumentations.SmallestMaxSize(max_size=h, interpolation=cv2.INTER_CUBIC)(image=img_hq)["image"]
-        print(img_lq.shape)
-        print("bicubic", img_lq_bicubic.shape)
-        print(img_hq.shape)
-        lq_nearest = cv2.resize(util.single2uint(img_lq), (int(sf * img_lq.shape[1]), int(sf * img_lq.shape[0])),
-                                interpolation=0)
-        lq_bicubic_nearest = cv2.resize(util.single2uint(img_lq_bicubic),
-                                        (int(sf * img_lq.shape[1]), int(sf * img_lq.shape[0])),
-                                        interpolation=0)
-        img_concat = np.concatenate([lq_bicubic_nearest, lq_nearest, util.single2uint(img_hq)], axis=1)
-        util.imsave(img_concat, str(i) + '.png')
diff --git a/spaces/Inderdev07/facerecognition/app.py b/spaces/Inderdev07/facerecognition/app.py
deleted file mode 100644
index 384b01a7be987b50ac5366d3f1da18a64310c01a..0000000000000000000000000000000000000000
--- a/spaces/Inderdev07/facerecognition/app.py
+++ /dev/null
@@ -1,80 +0,0 @@
-from PIL import Image
-import numpy as np
-import cv2
-import requests
-import face_recognition
-import os
-from datetime import datetime
-import streamlit as st
-
-# Set page title and description
-st.title("Face Recognition App")
-st.markdown("This app recognizes faces in an image and updates attendance.")
-
-# Load images for face recognition
-Images = []
-classnames = []
-directory = "photos"
-
-myList = os.listdir(directory)
-
-for cls in myList:
-    if os.path.splitext(cls)[1] in [".jpg", ".jpeg"]:
-        img_path = os.path.join(directory, cls)
-        curImg = cv2.imread(img_path)
-        Images.append(curImg)
-        classnames.append(os.path.splitext(cls)[0])
-
-def findEncodings(Images):
-    encodeList = []
-    for img in Images:
-        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
-        encode = face_recognition.face_encodings(img)[0]
-        encodeList.append(encode)
-    return encodeList
-
-encodeListknown = findEncodings(Images)
-
-# Take picture using the camera
-img_file_buffer = st.camera_input("Take a picture")
-if img_file_buffer is not None:
-    test_image = Image.open(img_file_buffer)
-    image = np.asarray(test_image)
-
-    imgS = cv2.resize(image, (0, 0), None, 0.25, 0.25)
-    imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB)
-    facesCurFrame = face_recognition.face_locations(imgS)
-    encodesCurFrame = face_recognition.face_encodings(imgS, facesCurFrame)
-
-    name = "Unknown"  # Default name for unknown faces
-
-    if len(encodesCurFrame) > 0:
-        for encodeFace, faceLoc in zip(encodesCurFrame, facesCurFrame):
-            matches = face_recognition.compare_faces(encodeListknown, encodeFace)
-            faceDis = face_recognition.face_distance(encodeListknown, encodeFace)
-            matchIndex = np.argmin(faceDis)
-
-            if matches[matchIndex]:
-                name = classnames[matchIndex].upper()
-
-            y1, x2, y2, x1 = faceLoc
-            y1, x2, y2, x1 = y1 * 4, x2 * 4, y2 * 4, x1 * 4
-            cv2.rectangle(image, (x1, y1), (x2, y2), (0, 255, 0), 2)
-            cv2.rectangle(image, (x1, y2 - 35), (x2, y2), (0, 255, 0), cv2.FILLED)
-            cv2.putText(image, name, (x1 + 6, y2 - 6), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255), 2)
-
-            if name != "Unknown":
-                url = "https://inderfaceproject.000webhostapp.com"
-                url1 = "/update.php"
-                data1 = {'name': name}
-                response = requests.post(url + url1, data=data1)
-
-                if response.status_code == 200:
-                    st.success("Data updated on: " + url)
-                else:
-                    st.warning("Data not updated")
-
-    st.image(image, caption="Detected Face", use_column_width=True)
-
-    if name == "Unknown":
-        st.info("Face not detected. Please try again.")
\ No newline at end of file
diff --git a/spaces/InpaintAI/Inpaint-Anything/third_party/lama/models/ade20k/segm_lib/nn/modules/__init__.py b/spaces/InpaintAI/Inpaint-Anything/third_party/lama/models/ade20k/segm_lib/nn/modules/__init__.py
deleted file mode 100644
index bc8709d92c610b36e0bcbd7da20c1eb41dc8cfcf..0000000000000000000000000000000000000000
--- a/spaces/InpaintAI/Inpaint-Anything/third_party/lama/models/ade20k/segm_lib/nn/modules/__init__.py
+++ /dev/null
@@ -1,12 +0,0 @@
-# -*- coding: utf-8 -*-
-# File   : __init__.py
-# Author : Jiayuan Mao
-# Email  : maojiayuan@gmail.com
-# Date   : 27/01/2018
-# 
-# This file is part of Synchronized-BatchNorm-PyTorch.
-# https://github.com/vacancy/Synchronized-BatchNorm-PyTorch
-# Distributed under MIT License.
-
-from .batchnorm import SynchronizedBatchNorm1d, SynchronizedBatchNorm2d, SynchronizedBatchNorm3d
-from .replicate import DataParallelWithCallback, patch_replication_callback
diff --git a/spaces/JammyMachina/the-jam-machine-app/licence.md b/spaces/JammyMachina/the-jam-machine-app/licence.md
deleted file mode 100644
index 42d0f21b2461f5f9f33e67adc5aee2fb5b2c67f2..0000000000000000000000000000000000000000
--- a/spaces/JammyMachina/the-jam-machine-app/licence.md
+++ /dev/null
@@ -1,21 +0,0 @@
-MIT License
-
-Copyright (c) 2023 Halid Bayram, Louis Demetz, Jean Simonnet
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
diff --git a/spaces/Jasonyoyo/CodeFormer/CodeFormer/facelib/detection/align_trans.py b/spaces/Jasonyoyo/CodeFormer/CodeFormer/facelib/detection/align_trans.py
deleted file mode 100644
index 07f1eb365462c2ec5bbac6d1854c786b6fd6be90..0000000000000000000000000000000000000000
--- a/spaces/Jasonyoyo/CodeFormer/CodeFormer/facelib/detection/align_trans.py
+++ /dev/null
@@ -1,219 +0,0 @@
-import cv2
-import numpy as np
-
-from .matlab_cp2tform import get_similarity_transform_for_cv2
-
-# reference facial points, a list of coordinates (x,y)
-REFERENCE_FACIAL_POINTS = [[30.29459953, 51.69630051], [65.53179932, 51.50139999], [48.02519989, 71.73660278],
-                           [33.54930115, 92.3655014], [62.72990036, 92.20410156]]
-
-DEFAULT_CROP_SIZE = (96, 112)
-
-
-class FaceWarpException(Exception):
-
-    def __str__(self):
-        return 'In File {}:{}'.format(__file__, super.__str__(self))
-
-
-def get_reference_facial_points(output_size=None, inner_padding_factor=0.0, outer_padding=(0, 0), default_square=False):
-    """
-    Function:
-    ----------
-        get reference 5 key points according to crop settings:
-        0. Set default crop_size:
-            if default_square:
-                crop_size = (112, 112)
-            else:
-                crop_size = (96, 112)
-        1. Pad the crop_size by inner_padding_factor in each side;
-        2. Resize crop_size into (output_size - outer_padding*2),
-            pad into output_size with outer_padding;
-        3. Output reference_5point;
-    Parameters:
-    ----------
-        @output_size: (w, h) or None
-            size of aligned face image
-        @inner_padding_factor: (w_factor, h_factor)
-            padding factor for inner (w, h)
-        @outer_padding: (w_pad, h_pad)
-            each row is a pair of coordinates (x, y)
-        @default_square: True or False
-            if True:
-                default crop_size = (112, 112)
-            else:
-                default crop_size = (96, 112);
-        !!! make sure, if output_size is not None:
-                (output_size - outer_padding)
-                = some_scale * (default crop_size * (1.0 +
-                inner_padding_factor))
-    Returns:
-    ----------
-        @reference_5point: 5x2 np.array
-            each row is a pair of transformed coordinates (x, y)
-    """
-
-    tmp_5pts = np.array(REFERENCE_FACIAL_POINTS)
-    tmp_crop_size = np.array(DEFAULT_CROP_SIZE)
-
-    # 0) make the inner region a square
-    if default_square:
-        size_diff = max(tmp_crop_size) - tmp_crop_size
-        tmp_5pts += size_diff / 2
-        tmp_crop_size += size_diff
-
-    if (output_size and output_size[0] == tmp_crop_size[0] and output_size[1] == tmp_crop_size[1]):
-
-        return tmp_5pts
-
-    if (inner_padding_factor == 0 and outer_padding == (0, 0)):
-        if output_size is None:
-            return tmp_5pts
-        else:
-            raise FaceWarpException('No paddings to do, output_size must be None or {}'.format(tmp_crop_size))
-
-    # check output size
-    if not (0 <= inner_padding_factor <= 1.0):
-        raise FaceWarpException('Not (0 <= inner_padding_factor <= 1.0)')
-
-    if ((inner_padding_factor > 0 or outer_padding[0] > 0 or outer_padding[1] > 0) and output_size is None):
-        output_size = tmp_crop_size * \
-            (1 + inner_padding_factor * 2).astype(np.int32)
-        output_size += np.array(outer_padding)
-    if not (outer_padding[0] < output_size[0] and outer_padding[1] < output_size[1]):
-        raise FaceWarpException('Not (outer_padding[0] < output_size[0] and outer_padding[1] < output_size[1])')
-
-    # 1) pad the inner region according inner_padding_factor
-    if inner_padding_factor > 0:
-        size_diff = tmp_crop_size * inner_padding_factor * 2
-        tmp_5pts += size_diff / 2
-        tmp_crop_size += np.round(size_diff).astype(np.int32)
-
-    # 2) resize the padded inner region
-    size_bf_outer_pad = np.array(output_size) - np.array(outer_padding) * 2
-
-    if size_bf_outer_pad[0] * tmp_crop_size[1] != size_bf_outer_pad[1] * tmp_crop_size[0]:
-        raise FaceWarpException('Must have (output_size - outer_padding)'
-                                '= some_scale * (crop_size * (1.0 + inner_padding_factor)')
-
-    scale_factor = size_bf_outer_pad[0].astype(np.float32) / tmp_crop_size[0]
-    tmp_5pts = tmp_5pts * scale_factor
-    #    size_diff = tmp_crop_size * (scale_factor - min(scale_factor))
-    #    tmp_5pts = tmp_5pts + size_diff / 2
-    tmp_crop_size = size_bf_outer_pad
-
-    # 3) add outer_padding to make output_size
-    reference_5point = tmp_5pts + np.array(outer_padding)
-    tmp_crop_size = output_size
-
-    return reference_5point
-
-
-def get_affine_transform_matrix(src_pts, dst_pts):
-    """
-    Function:
-    ----------
-        get affine transform matrix 'tfm' from src_pts to dst_pts
-    Parameters:
-    ----------
-        @src_pts: Kx2 np.array
-            source points matrix, each row is a pair of coordinates (x, y)
-        @dst_pts: Kx2 np.array
-            destination points matrix, each row is a pair of coordinates (x, y)
-    Returns:
-    ----------
-        @tfm: 2x3 np.array
-            transform matrix from src_pts to dst_pts
-    """
-
-    tfm = np.float32([[1, 0, 0], [0, 1, 0]])
-    n_pts = src_pts.shape[0]
-    ones = np.ones((n_pts, 1), src_pts.dtype)
-    src_pts_ = np.hstack([src_pts, ones])
-    dst_pts_ = np.hstack([dst_pts, ones])
-
-    A, res, rank, s = np.linalg.lstsq(src_pts_, dst_pts_)
-
-    if rank == 3:
-        tfm = np.float32([[A[0, 0], A[1, 0], A[2, 0]], [A[0, 1], A[1, 1], A[2, 1]]])
-    elif rank == 2:
-        tfm = np.float32([[A[0, 0], A[1, 0], 0], [A[0, 1], A[1, 1], 0]])
-
-    return tfm
-
-
-def warp_and_crop_face(src_img, facial_pts, reference_pts=None, crop_size=(96, 112), align_type='smilarity'):
-    """
-    Function:
-    ----------
-        apply affine transform 'trans' to uv
-    Parameters:
-    ----------
-        @src_img: 3x3 np.array
-            input image
-        @facial_pts: could be
-            1)a list of K coordinates (x,y)
-        or
-            2) Kx2 or 2xK np.array
-            each row or col is a pair of coordinates (x, y)
-        @reference_pts: could be
-            1) a list of K coordinates (x,y)
-        or
-            2) Kx2 or 2xK np.array
-            each row or col is a pair of coordinates (x, y)
-        or
-            3) None
-            if None, use default reference facial points
-        @crop_size: (w, h)
-            output face image size
-        @align_type: transform type, could be one of
-            1) 'similarity': use similarity transform
-            2) 'cv2_affine': use the first 3 points to do affine transform,
-                    by calling cv2.getAffineTransform()
-            3) 'affine': use all points to do affine transform
-    Returns:
-    ----------
-        @face_img: output face image with size (w, h) = @crop_size
-    """
-
-    if reference_pts is None:
-        if crop_size[0] == 96 and crop_size[1] == 112:
-            reference_pts = REFERENCE_FACIAL_POINTS
-        else:
-            default_square = False
-            inner_padding_factor = 0
-            outer_padding = (0, 0)
-            output_size = crop_size
-
-            reference_pts = get_reference_facial_points(output_size, inner_padding_factor, outer_padding,
-                                                        default_square)
-
-    ref_pts = np.float32(reference_pts)
-    ref_pts_shp = ref_pts.shape
-    if max(ref_pts_shp) < 3 or min(ref_pts_shp) != 2:
-        raise FaceWarpException('reference_pts.shape must be (K,2) or (2,K) and K>2')
-
-    if ref_pts_shp[0] == 2:
-        ref_pts = ref_pts.T
-
-    src_pts = np.float32(facial_pts)
-    src_pts_shp = src_pts.shape
-    if max(src_pts_shp) < 3 or min(src_pts_shp) != 2:
-        raise FaceWarpException('facial_pts.shape must be (K,2) or (2,K) and K>2')
-
-    if src_pts_shp[0] == 2:
-        src_pts = src_pts.T
-
-    if src_pts.shape != ref_pts.shape:
-        raise FaceWarpException('facial_pts and reference_pts must have the same shape')
-
-    if align_type == 'cv2_affine':
-        tfm = cv2.getAffineTransform(src_pts[0:3], ref_pts[0:3])
-    elif align_type == 'affine':
-        tfm = get_affine_transform_matrix(src_pts, ref_pts)
-    else:
-        tfm = get_similarity_transform_for_cv2(src_pts, ref_pts)
-
-    face_img = cv2.warpAffine(src_img, tfm, (crop_size[0], crop_size[1]))
-
-    return face_img
diff --git a/spaces/Jeff2323/ai-comic-factory/src/app/queries/getStory.ts b/spaces/Jeff2323/ai-comic-factory/src/app/queries/getStory.ts
deleted file mode 100644
index 785a1f75a033f33264f1df92b0d569c75067be94..0000000000000000000000000000000000000000
--- a/spaces/Jeff2323/ai-comic-factory/src/app/queries/getStory.ts
+++ /dev/null
@@ -1,83 +0,0 @@
-import { createLlamaPrompt } from "@/lib/createLlamaPrompt"
-import { dirtyLLMResponseCleaner } from "@/lib/dirtyLLMResponseCleaner"
-import { dirtyLLMJsonParser } from "@/lib/dirtyLLMJsonParser"
-import { dirtyCaptionCleaner } from "@/lib/dirtyCaptionCleaner"
-
-import { predict } from "./predict"
-import { Preset } from "../engine/presets"
-import { LLMResponse } from "@/types"
-import { cleanJson } from "@/lib/cleanJson"
-
-export const getStory = async ({
-  preset,
-  prompt = "",
-}: {
-  preset: Preset;
-  prompt: string;
-}): Promise<LLMResponse> => {
-
-  const query = createLlamaPrompt([
-    {
-      role: "system",
-      content: [
-        `You are a comic book author specialized in ${preset.llmPrompt}`,
-        `Please write detailed drawing instructions and a one-sentence short caption for the 4 panels of a new silent comic book page.`,
-        `Give your response as a JSON array like this: \`Array<{ panel: number; instructions: string; caption: string}>\`.`,
-        // `Give your response as Markdown bullet points.`,
-        `Be brief in your 4 instructions and captions, don't add your own comments. Be straight to the point, and never reply things like "Sure, I can.." etc.`
-      ].filter(item => item).join("\n")
-    },
-    {
-      role: "user",
-      content: `The story is: ${prompt}`,
-    }
-  ]) + "```json\n["
-
-
-  let result = ""
-
-  try {
-    result = await predict(query)
-    if (!result.trim().length) {
-      throw new Error("empty result!")
-    }
-  } catch (err) {
-    console.log(`prediction of the story failed, trying again..`)
-    try {
-      result = await predict(query+".")
-      if (!result.trim().length) {
-        throw new Error("empty result!")
-      }
-    } catch (err) {
-      console.error(`prediction of the story failed again!`)
-      throw new Error(`failed to generate the story ${err}`)
-    }
-  }
-
-  // console.log("Raw response from LLM:", result)
-  const tmp = cleanJson(result)
-  
-  let llmResponse: LLMResponse = []
-
-  try {
-    llmResponse = dirtyLLMJsonParser(tmp)
-  } catch (err) {
-    console.log(`failed to read LLM response: ${err}`)
-    console.log(`original response was:`, result)
-
-      // in case of failure here, it might be because the LLM hallucinated a completely different response,
-      // such as markdown. There is no real solution.. but we can try a fallback:
-
-    llmResponse = (
-      tmp.split("*")
-      .map(item => item.trim())
-      .map((cap, i) => ({
-        panel: i,
-        caption: cap,
-        instructions: cap,
-      }))
-    )
-  }
-
-  return llmResponse.map(res => dirtyCaptionCleaner(res))
-}
\ No newline at end of file
diff --git a/spaces/JeffJing/ZookChatBot/steamship/data/operations/generator.py b/spaces/JeffJing/ZookChatBot/steamship/data/operations/generator.py
deleted file mode 100644
index 1867794d4110df927e4feb33644c55b337f22220..0000000000000000000000000000000000000000
--- a/spaces/JeffJing/ZookChatBot/steamship/data/operations/generator.py
+++ /dev/null
@@ -1,58 +0,0 @@
-from __future__ import annotations
-
-from typing import List, Optional
-
-from steamship.base.request import Request
-from steamship.base.response import Response
-from steamship.data.block import Block
-
-
-class GenerateRequest(Request):
-    """This class provides the input for a request to a Generator.  There are several ways to specify the input; see below"""
-
-    # Input Specification
-    # You must select one of several ways to specify input for a generator. These are exclusive.
-    # 1 - A span of Blocks on a File
-    # 2 - Raw text
-    # 3 - A query for Blocks
-    # 4 - (coming soon) A public URL of content
-    # 5 - (coming soon) Raw bytes of content
-
-    # Must specify plugin instance to use
-    plugin_instance: str = None
-
-    # May specify blocks by their file_id. If so, may specify start and end index
-    input_file_id: str = None
-    input_file_start_block_index: int = None
-    input_file_end_block_index: Optional[
-        int
-    ] = None  # EXCLUSIVE end index, like most programming languages
-
-    # May specify raw text
-    text: Optional[str] = None
-
-    # May specify raw bytes (ex. an image, audio) [Not yet implemented]
-    # bytes: Optional[bytes] = None
-
-    # May specify a block query. This may produce input blocks from multiple files.
-    block_query: Optional[str] = None
-
-    # May specify a public URL to fetch the data from. [Not yet implemented]
-    # url: Optional[str] = None
-
-    # Desired output specification
-
-    # Whether we want the output appended to a file
-    append_output_to_file: bool = False
-
-    # May specify a file to which to append the results.  This may be the same file as
-    # the input or not.  If appendOutputToFile is true but the outputFileId is not set,
-    # create a new file.
-    output_file_id: Optional[str] = None
-
-    # Arbitrary runtime options which may be passed to a generator
-    options: Optional[dict]
-
-
-class GenerateResponse(Response):
-    blocks: List[Block]
diff --git a/spaces/Kangarroar/ApplioRVC-Inference/Makefile b/spaces/Kangarroar/ApplioRVC-Inference/Makefile
deleted file mode 100644
index 44de020e6feb7fcd58016d7c3c736681f533b597..0000000000000000000000000000000000000000
--- a/spaces/Kangarroar/ApplioRVC-Inference/Makefile
+++ /dev/null
@@ -1,63 +0,0 @@
-.PHONY:
-.ONESHELL:
-
-help: ## Show this help and exit
-	@grep -hE '^[A-Za-z0-9_ \-]*?:.*##.*$$' $(MAKEFILE_LIST) | sort | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
-
-install: ## Install dependencies (Do everytime you start up a paperspace machine)
-	apt-get -y install build-essential python3-dev ffmpeg
-	pip install --upgrade setuptools wheel
-	pip install --upgrade pip
-	pip install faiss-gpu fairseq gradio ffmpeg ffmpeg-python praat-parselmouth pyworld numpy==1.23.5 numba==0.56.4 librosa==0.9.1
-	pip install -r requirements.txt
-	pip install --upgrade lxml
-	apt-get update
-	apt -y install -qq aria2
-
-basev1: ## Download version 1 pre-trained models (Do only once after cloning the fork)
-	mkdir -p pretrained uvr5_weights
-	git pull
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D32k.pth -d pretrained -o D32k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D40k.pth -d pretrained -o D40k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D48k.pth -d pretrained -o D48k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G32k.pth -d pretrained -o G32k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G40k.pth -d pretrained -o G40k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G48k.pth -d pretrained -o G48k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D32k.pth -d pretrained -o f0D32k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D40k.pth -d pretrained -o f0D40k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D48k.pth -d pretrained -o f0D48k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G32k.pth -d pretrained -o f0G32k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G40k.pth -d pretrained -o f0G40k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G48k.pth -d pretrained -o f0G48k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP2-人声vocals+非人声instrumentals.pth -d uvr5_weights -o HP2-人声vocals+非人声instrumentals.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP5-主旋律人声vocals+其他instrumentals.pth -d uvr5_weights -o HP5-主旋律人声vocals+其他instrumentals.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/hubert_base.pt -d ./ -o hubert_base.pt
-
-basev2: ## Download version 2 pre-trained models (Do only once after cloning the fork)
-	mkdir -p pretrained_v2 uvr5_weights
-	git pull
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/D32k.pth -d pretrained_v2 -o D32k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/D40k.pth -d pretrained_v2 -o D40k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/D48k.pth -d pretrained_v2 -o D48k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/G32k.pth -d pretrained_v2 -o G32k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/G40k.pth -d pretrained_v2 -o G40k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/G48k.pth -d pretrained_v2 -o G48k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0D32k.pth -d pretrained_v2 -o f0D32k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0D40k.pth -d pretrained_v2 -o f0D40k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0D48k.pth -d pretrained_v2 -o f0D48k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0G32k.pth -d pretrained_v2 -o f0G32k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0G40k.pth -d pretrained_v2 -o f0G40k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0G48k.pth -d pretrained_v2 -o f0G48k.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP2-人声vocals+非人声instrumentals.pth -d uvr5_weights -o HP2-人声vocals+非人声instrumentals.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP5-主旋律人声vocals+其他instrumentals.pth -d uvr5_weights -o HP5-主旋律人声vocals+其他instrumentals.pth
-	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/hubert_base.pt -d ./ -o hubert_base.pt
-
-run-ui: ## Run the python GUI
-	python infer-web.py --paperspace --pycmd python
-
-run-cli: ## Run the python CLI
-	python infer-web.py --pycmd python --is_cli
-
-tensorboard: ## Start the tensorboard (Run on separate terminal)
-	echo https://tensorboard-$$(hostname).clg07azjl.paperspacegradient.com
-	tensorboard --logdir logs --bind_all
\ No newline at end of file
diff --git a/spaces/KdaiP/yolov8-deepsort-tracking/deep_sort/deep_sort/deep/test.py b/spaces/KdaiP/yolov8-deepsort-tracking/deep_sort/deep_sort/deep/test.py
deleted file mode 100644
index ebd590336f7b17c44738c4c15458f02f33f08017..0000000000000000000000000000000000000000
--- a/spaces/KdaiP/yolov8-deepsort-tracking/deep_sort/deep_sort/deep/test.py
+++ /dev/null
@@ -1,77 +0,0 @@
-import torch
-import torch.backends.cudnn as cudnn
-import torchvision
-
-import argparse
-import os
-
-from model import Net
-
-parser = argparse.ArgumentParser(description="Train on market1501")
-parser.add_argument("--data-dir",default='data',type=str)
-parser.add_argument("--no-cuda",action="store_true")
-parser.add_argument("--gpu-id",default=0,type=int)
-args = parser.parse_args()
-
-# device
-device = "cuda:{}".format(args.gpu_id) if torch.cuda.is_available() and not args.no_cuda else "cpu"
-if torch.cuda.is_available() and not args.no_cuda:
-    cudnn.benchmark = True
-
-# data loader
-root = args.data_dir
-query_dir = os.path.join(root,"query")
-gallery_dir = os.path.join(root,"gallery")
-transform = torchvision.transforms.Compose([
-    torchvision.transforms.Resize((128,64)),
-    torchvision.transforms.ToTensor(),
-    torchvision.transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
-])
-queryloader = torch.utils.data.DataLoader(
-    torchvision.datasets.ImageFolder(query_dir, transform=transform),
-    batch_size=64, shuffle=False
-)
-galleryloader = torch.utils.data.DataLoader(
-    torchvision.datasets.ImageFolder(gallery_dir, transform=transform),
-    batch_size=64, shuffle=False
-)
-
-# net definition
-net = Net(reid=True)
-assert os.path.isfile("./checkpoint/ckpt.t7"), "Error: no checkpoint file found!"
-print('Loading from checkpoint/ckpt.t7')
-checkpoint = torch.load("./checkpoint/ckpt.t7")
-net_dict = checkpoint['net_dict']
-net.load_state_dict(net_dict, strict=False)
-net.eval()
-net.to(device)
-
-# compute features
-query_features = torch.tensor([]).float()
-query_labels = torch.tensor([]).long()
-gallery_features = torch.tensor([]).float()
-gallery_labels = torch.tensor([]).long()
-
-with torch.no_grad():
-    for idx,(inputs,labels) in enumerate(queryloader):
-        inputs = inputs.to(device)
-        features = net(inputs).cpu()
-        query_features = torch.cat((query_features, features), dim=0)
-        query_labels = torch.cat((query_labels, labels))
-
-    for idx,(inputs,labels) in enumerate(galleryloader):
-        inputs = inputs.to(device)
-        features = net(inputs).cpu()
-        gallery_features = torch.cat((gallery_features, features), dim=0)
-        gallery_labels = torch.cat((gallery_labels, labels))
-
-gallery_labels -= 2
-
-# save features
-features = {
-    "qf": query_features,
-    "ql": query_labels,
-    "gf": gallery_features,
-    "gl": gallery_labels
-}
-torch.save(features,"features.pth")
\ No newline at end of file
diff --git a/spaces/KyanChen/RSPrompter/mmdet/utils/benchmark.py b/spaces/KyanChen/RSPrompter/mmdet/utils/benchmark.py
deleted file mode 100644
index 1714b46474074b51f8241d2c9afccd2f54240b10..0000000000000000000000000000000000000000
--- a/spaces/KyanChen/RSPrompter/mmdet/utils/benchmark.py
+++ /dev/null
@@ -1,522 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-import copy
-import time
-from functools import partial
-from typing import List, Optional, Union
-
-import numpy as np
-import torch
-import torch.nn as nn
-from mmcv.cnn import fuse_conv_bn
-# TODO need update
-# from mmcv.runner import wrap_fp16_model
-from mmengine import MMLogger
-from mmengine.config import Config
-from mmengine.device import get_max_cuda_memory
-from mmengine.dist import get_world_size
-from mmengine.runner import Runner, load_checkpoint
-from mmengine.utils.dl_utils import set_multi_processing
-from torch.nn.parallel import DistributedDataParallel
-
-from mmdet.registry import DATASETS, MODELS
-
-try:
-    import psutil
-except ImportError:
-    psutil = None
-
-
-def custom_round(value: Union[int, float],
-                 factor: Union[int, float],
-                 precision: int = 2) -> float:
-    """Custom round function."""
-    return round(value / factor, precision)
-
-
-gb_round = partial(custom_round, factor=1024**3)
-
-
-def print_log(msg: str, logger: Optional[MMLogger] = None) -> None:
-    """Print a log message."""
-    if logger is None:
-        print(msg, flush=True)
-    else:
-        logger.info(msg)
-
-
-def print_process_memory(p: psutil.Process,
-                         logger: Optional[MMLogger] = None) -> None:
-    """print process memory info."""
-    mem_used = gb_round(psutil.virtual_memory().used)
-    memory_full_info = p.memory_full_info()
-    uss_mem = gb_round(memory_full_info.uss)
-    pss_mem = gb_round(memory_full_info.pss)
-    for children in p.children():
-        child_mem_info = children.memory_full_info()
-        uss_mem += gb_round(child_mem_info.uss)
-        pss_mem += gb_round(child_mem_info.pss)
-    process_count = 1 + len(p.children())
-    print_log(
-        f'(GB) mem_used: {mem_used:.2f} | uss: {uss_mem:.2f} | '
-        f'pss: {pss_mem:.2f} | total_proc: {process_count}', logger)
-
-
-class BaseBenchmark:
-    """The benchmark base class.
-
-    The ``run`` method is an external calling interface, and it will
-    call the ``run_once`` method ``repeat_num`` times for benchmarking.
-    Finally, call the ``average_multiple_runs`` method to further process
-    the results of multiple runs.
-
-    Args:
-        max_iter (int): maximum iterations of benchmark.
-        log_interval (int): interval of logging.
-        num_warmup (int): Number of Warmup.
-        logger (MMLogger, optional): Formatted logger used to record messages.
-    """
-
-    def __init__(self,
-                 max_iter: int,
-                 log_interval: int,
-                 num_warmup: int,
-                 logger: Optional[MMLogger] = None):
-        self.max_iter = max_iter
-        self.log_interval = log_interval
-        self.num_warmup = num_warmup
-        self.logger = logger
-
-    def run(self, repeat_num: int = 1) -> dict:
-        """benchmark entry method.
-
-        Args:
-            repeat_num (int): Number of repeat benchmark.
-                Defaults to 1.
-        """
-        assert repeat_num >= 1
-
-        results = []
-        for _ in range(repeat_num):
-            results.append(self.run_once())
-
-        results = self.average_multiple_runs(results)
-        return results
-
-    def run_once(self) -> dict:
-        """Executes the benchmark once."""
-        raise NotImplementedError()
-
-    def average_multiple_runs(self, results: List[dict]) -> dict:
-        """Average the results of multiple runs."""
-        raise NotImplementedError()
-
-
-class InferenceBenchmark(BaseBenchmark):
-    """The inference benchmark class. It will be statistical inference FPS,
-    CUDA memory and CPU memory information.
-
-    Args:
-        cfg (mmengine.Config): config.
-        checkpoint (str): Accept local filepath, URL, ``torchvision://xxx``,
-            ``open-mmlab://xxx``.
-        distributed (bool): distributed testing flag.
-        is_fuse_conv_bn (bool): Whether to fuse conv and bn, this will
-            slightly increase the inference speed.
-        max_iter (int): maximum iterations of benchmark. Defaults to 2000.
-        log_interval (int): interval of logging. Defaults to 50.
-        num_warmup (int): Number of Warmup. Defaults to 5.
-        logger (MMLogger, optional): Formatted logger used to record messages.
-    """
-
-    def __init__(self,
-                 cfg: Config,
-                 checkpoint: str,
-                 distributed: bool,
-                 is_fuse_conv_bn: bool,
-                 max_iter: int = 2000,
-                 log_interval: int = 50,
-                 num_warmup: int = 5,
-                 logger: Optional[MMLogger] = None):
-        super().__init__(max_iter, log_interval, num_warmup, logger)
-
-        assert get_world_size(
-        ) == 1, 'Inference benchmark does not allow distributed multi-GPU'
-
-        self.cfg = copy.deepcopy(cfg)
-        self.distributed = distributed
-
-        if psutil is None:
-            raise ImportError('psutil is not installed, please install it by: '
-                              'pip install psutil')
-
-        self._process = psutil.Process()
-        env_cfg = self.cfg.get('env_cfg')
-        if env_cfg.get('cudnn_benchmark'):
-            torch.backends.cudnn.benchmark = True
-
-        mp_cfg: dict = env_cfg.get('mp_cfg', {})
-        set_multi_processing(**mp_cfg, distributed=self.distributed)
-
-        print_log('before build: ', self.logger)
-        print_process_memory(self._process, self.logger)
-
-        self.model = self._init_model(checkpoint, is_fuse_conv_bn)
-
-        # Because multiple processes will occupy additional CPU resources,
-        # FPS statistics will be more unstable when num_workers is not 0.
-        # It is reasonable to set num_workers to 0.
-        dataloader_cfg = cfg.test_dataloader
-        dataloader_cfg['num_workers'] = 0
-        dataloader_cfg['batch_size'] = 1
-        dataloader_cfg['persistent_workers'] = False
-        self.data_loader = Runner.build_dataloader(dataloader_cfg)
-
-        print_log('after build: ', self.logger)
-        print_process_memory(self._process, self.logger)
-
-    def _init_model(self, checkpoint: str, is_fuse_conv_bn: bool) -> nn.Module:
-        """Initialize the model."""
-        model = MODELS.build(self.cfg.model)
-        # TODO need update
-        # fp16_cfg = self.cfg.get('fp16', None)
-        # if fp16_cfg is not None:
-        #     wrap_fp16_model(model)
-
-        load_checkpoint(model, checkpoint, map_location='cpu')
-        if is_fuse_conv_bn:
-            model = fuse_conv_bn(model)
-
-        model = model.cuda()
-
-        if self.distributed:
-            model = DistributedDataParallel(
-                model,
-                device_ids=[torch.cuda.current_device()],
-                broadcast_buffers=False,
-                find_unused_parameters=False)
-
-        model.eval()
-        return model
-
-    def run_once(self) -> dict:
-        """Executes the benchmark once."""
-        pure_inf_time = 0
-        fps = 0
-
-        for i, data in enumerate(self.data_loader):
-
-            if (i + 1) % self.log_interval == 0:
-                print_log('==================================', self.logger)
-
-            torch.cuda.synchronize()
-            start_time = time.perf_counter()
-
-            with torch.no_grad():
-                self.model.test_step(data)
-
-            torch.cuda.synchronize()
-            elapsed = time.perf_counter() - start_time
-
-            if i >= self.num_warmup:
-                pure_inf_time += elapsed
-                if (i + 1) % self.log_interval == 0:
-                    fps = (i + 1 - self.num_warmup) / pure_inf_time
-                    cuda_memory = get_max_cuda_memory()
-
-                    print_log(
-                        f'Done image [{i + 1:<3}/{self.max_iter}], '
-                        f'fps: {fps:.1f} img/s, '
-                        f'times per image: {1000 / fps:.1f} ms/img, '
-                        f'cuda memory: {cuda_memory} MB', self.logger)
-                    print_process_memory(self._process, self.logger)
-
-            if (i + 1) == self.max_iter:
-                fps = (i + 1 - self.num_warmup) / pure_inf_time
-                break
-
-        return {'fps': fps}
-
-    def average_multiple_runs(self, results: List[dict]) -> dict:
-        """Average the results of multiple runs."""
-        print_log('============== Done ==================', self.logger)
-
-        fps_list_ = [round(result['fps'], 1) for result in results]
-        avg_fps_ = sum(fps_list_) / len(fps_list_)
-        outputs = {'avg_fps': avg_fps_, 'fps_list': fps_list_}
-
-        if len(fps_list_) > 1:
-            times_pre_image_list_ = [
-                round(1000 / result['fps'], 1) for result in results
-            ]
-            avg_times_pre_image_ = sum(times_pre_image_list_) / len(
-                times_pre_image_list_)
-
-            print_log(
-                f'Overall fps: {fps_list_}[{avg_fps_:.1f}] img/s, '
-                'times per image: '
-                f'{times_pre_image_list_}[{avg_times_pre_image_:.1f}] '
-                'ms/img', self.logger)
-        else:
-            print_log(
-                f'Overall fps: {fps_list_[0]:.1f} img/s, '
-                f'times per image: {1000 / fps_list_[0]:.1f} ms/img',
-                self.logger)
-
-        print_log(f'cuda memory: {get_max_cuda_memory()} MB', self.logger)
-        print_process_memory(self._process, self.logger)
-
-        return outputs
-
-
-class DataLoaderBenchmark(BaseBenchmark):
-    """The dataloader benchmark class. It will be statistical inference FPS and
-    CPU memory information.
-
-    Args:
-        cfg (mmengine.Config): config.
-        distributed (bool): distributed testing flag.
-        dataset_type (str): benchmark data type, only supports ``train``,
-            ``val`` and ``test``.
-        max_iter (int): maximum iterations of benchmark. Defaults to 2000.
-        log_interval (int): interval of logging. Defaults to 50.
-        num_warmup (int): Number of Warmup. Defaults to 5.
-        logger (MMLogger, optional): Formatted logger used to record messages.
-    """
-
-    def __init__(self,
-                 cfg: Config,
-                 distributed: bool,
-                 dataset_type: str,
-                 max_iter: int = 2000,
-                 log_interval: int = 50,
-                 num_warmup: int = 5,
-                 logger: Optional[MMLogger] = None):
-        super().__init__(max_iter, log_interval, num_warmup, logger)
-
-        assert dataset_type in ['train', 'val', 'test'], \
-            'dataset_type only supports train,' \
-            f' val and test, but got {dataset_type}'
-        assert get_world_size(
-        ) == 1, 'Dataloader benchmark does not allow distributed multi-GPU'
-
-        self.cfg = copy.deepcopy(cfg)
-        self.distributed = distributed
-
-        if psutil is None:
-            raise ImportError('psutil is not installed, please install it by: '
-                              'pip install psutil')
-        self._process = psutil.Process()
-
-        mp_cfg = self.cfg.get('env_cfg', {}).get('mp_cfg')
-        if mp_cfg is not None:
-            set_multi_processing(distributed=self.distributed, **mp_cfg)
-        else:
-            set_multi_processing(distributed=self.distributed)
-
-        print_log('before build: ', self.logger)
-        print_process_memory(self._process, self.logger)
-
-        if dataset_type == 'train':
-            self.data_loader = Runner.build_dataloader(cfg.train_dataloader)
-        elif dataset_type == 'test':
-            self.data_loader = Runner.build_dataloader(cfg.test_dataloader)
-        else:
-            self.data_loader = Runner.build_dataloader(cfg.val_dataloader)
-
-        self.batch_size = self.data_loader.batch_size
-        self.num_workers = self.data_loader.num_workers
-
-        print_log('after build: ', self.logger)
-        print_process_memory(self._process, self.logger)
-
-    def run_once(self) -> dict:
-        """Executes the benchmark once."""
-        pure_inf_time = 0
-        fps = 0
-
-        # benchmark with 2000 image and take the average
-        start_time = time.perf_counter()
-        for i, data in enumerate(self.data_loader):
-            elapsed = time.perf_counter() - start_time
-
-            if (i + 1) % self.log_interval == 0:
-                print_log('==================================', self.logger)
-
-            if i >= self.num_warmup:
-                pure_inf_time += elapsed
-                if (i + 1) % self.log_interval == 0:
-                    fps = (i + 1 - self.num_warmup) / pure_inf_time
-
-                    print_log(
-                        f'Done batch [{i + 1:<3}/{self.max_iter}], '
-                        f'fps: {fps:.1f} batch/s, '
-                        f'times per batch: {1000 / fps:.1f} ms/batch, '
-                        f'batch size: {self.batch_size}, num_workers: '
-                        f'{self.num_workers}', self.logger)
-                    print_process_memory(self._process, self.logger)
-
-            if (i + 1) == self.max_iter:
-                fps = (i + 1 - self.num_warmup) / pure_inf_time
-                break
-
-            start_time = time.perf_counter()
-
-        return {'fps': fps}
-
-    def average_multiple_runs(self, results: List[dict]) -> dict:
-        """Average the results of multiple runs."""
-        print_log('============== Done ==================', self.logger)
-
-        fps_list_ = [round(result['fps'], 1) for result in results]
-        avg_fps_ = sum(fps_list_) / len(fps_list_)
-        outputs = {'avg_fps': avg_fps_, 'fps_list': fps_list_}
-
-        if len(fps_list_) > 1:
-            times_pre_image_list_ = [
-                round(1000 / result['fps'], 1) for result in results
-            ]
-            avg_times_pre_image_ = sum(times_pre_image_list_) / len(
-                times_pre_image_list_)
-
-            print_log(
-                f'Overall fps: {fps_list_}[{avg_fps_:.1f}] img/s, '
-                'times per batch: '
-                f'{times_pre_image_list_}[{avg_times_pre_image_:.1f}] '
-                f'ms/batch, batch size: {self.batch_size}, num_workers: '
-                f'{self.num_workers}', self.logger)
-        else:
-            print_log(
-                f'Overall fps: {fps_list_[0]:.1f} batch/s, '
-                f'times per batch: {1000 / fps_list_[0]:.1f} ms/batch, '
-                f'batch size: {self.batch_size}, num_workers: '
-                f'{self.num_workers}', self.logger)
-
-        print_process_memory(self._process, self.logger)
-
-        return outputs
-
-
-class DatasetBenchmark(BaseBenchmark):
-    """The dataset benchmark class. It will be statistical inference FPS, FPS
-    pre transform and CPU memory information.
-
-    Args:
-        cfg (mmengine.Config): config.
-        dataset_type (str): benchmark data type, only supports ``train``,
-            ``val`` and ``test``.
-        max_iter (int): maximum iterations of benchmark. Defaults to 2000.
-        log_interval (int): interval of logging. Defaults to 50.
-        num_warmup (int): Number of Warmup. Defaults to 5.
-        logger (MMLogger, optional): Formatted logger used to record messages.
-    """
-
-    def __init__(self,
-                 cfg: Config,
-                 dataset_type: str,
-                 max_iter: int = 2000,
-                 log_interval: int = 50,
-                 num_warmup: int = 5,
-                 logger: Optional[MMLogger] = None):
-        super().__init__(max_iter, log_interval, num_warmup, logger)
-        assert dataset_type in ['train', 'val', 'test'], \
-            'dataset_type only supports train,' \
-            f' val and test, but got {dataset_type}'
-        assert get_world_size(
-        ) == 1, 'Dataset benchmark does not allow distributed multi-GPU'
-        self.cfg = copy.deepcopy(cfg)
-
-        if dataset_type == 'train':
-            dataloader_cfg = copy.deepcopy(cfg.train_dataloader)
-        elif dataset_type == 'test':
-            dataloader_cfg = copy.deepcopy(cfg.test_dataloader)
-        else:
-            dataloader_cfg = copy.deepcopy(cfg.val_dataloader)
-
-        dataset_cfg = dataloader_cfg.pop('dataset')
-        dataset = DATASETS.build(dataset_cfg)
-        if hasattr(dataset, 'full_init'):
-            dataset.full_init()
-        self.dataset = dataset
-
-    def run_once(self) -> dict:
-        """Executes the benchmark once."""
-        pure_inf_time = 0
-        fps = 0
-
-        total_index = list(range(len(self.dataset)))
-        np.random.shuffle(total_index)
-
-        start_time = time.perf_counter()
-        for i, idx in enumerate(total_index):
-            if (i + 1) % self.log_interval == 0:
-                print_log('==================================', self.logger)
-
-            get_data_info_start_time = time.perf_counter()
-            data_info = self.dataset.get_data_info(idx)
-            get_data_info_elapsed = time.perf_counter(
-            ) - get_data_info_start_time
-
-            if (i + 1) % self.log_interval == 0:
-                print_log(f'get_data_info - {get_data_info_elapsed * 1000} ms',
-                          self.logger)
-
-            for t in self.dataset.pipeline.transforms:
-                transform_start_time = time.perf_counter()
-                data_info = t(data_info)
-                transform_elapsed = time.perf_counter() - transform_start_time
-
-                if (i + 1) % self.log_interval == 0:
-                    print_log(
-                        f'{t.__class__.__name__} - '
-                        f'{transform_elapsed * 1000} ms', self.logger)
-
-                if data_info is None:
-                    break
-
-            elapsed = time.perf_counter() - start_time
-
-            if i >= self.num_warmup:
-                pure_inf_time += elapsed
-                if (i + 1) % self.log_interval == 0:
-                    fps = (i + 1 - self.num_warmup) / pure_inf_time
-
-                    print_log(
-                        f'Done img [{i + 1:<3}/{self.max_iter}], '
-                        f'fps: {fps:.1f} img/s, '
-                        f'times per img: {1000 / fps:.1f} ms/img', self.logger)
-
-            if (i + 1) == self.max_iter:
-                fps = (i + 1 - self.num_warmup) / pure_inf_time
-                break
-
-            start_time = time.perf_counter()
-
-        return {'fps': fps}
-
-    def average_multiple_runs(self, results: List[dict]) -> dict:
-        """Average the results of multiple runs."""
-        print_log('============== Done ==================', self.logger)
-
-        fps_list_ = [round(result['fps'], 1) for result in results]
-        avg_fps_ = sum(fps_list_) / len(fps_list_)
-        outputs = {'avg_fps': avg_fps_, 'fps_list': fps_list_}
-
-        if len(fps_list_) > 1:
-            times_pre_image_list_ = [
-                round(1000 / result['fps'], 1) for result in results
-            ]
-            avg_times_pre_image_ = sum(times_pre_image_list_) / len(
-                times_pre_image_list_)
-
-            print_log(
-                f'Overall fps: {fps_list_}[{avg_fps_:.1f}] img/s, '
-                'times per img: '
-                f'{times_pre_image_list_}[{avg_times_pre_image_:.1f}] '
-                'ms/img', self.logger)
-        else:
-            print_log(
-                f'Overall fps: {fps_list_[0]:.1f} img/s, '
-                f'times per img: {1000 / fps_list_[0]:.1f} ms/img',
-                self.logger)
-
-        return outputs
diff --git a/spaces/KyanChen/RSPrompter/mmpl/models/necks/transformer_edecoder_neck.py b/spaces/KyanChen/RSPrompter/mmpl/models/necks/transformer_edecoder_neck.py
deleted file mode 100644
index c4f4ce7eb9f97361733fc26adb16487eb67ffc8b..0000000000000000000000000000000000000000
--- a/spaces/KyanChen/RSPrompter/mmpl/models/necks/transformer_edecoder_neck.py
+++ /dev/null
@@ -1,54 +0,0 @@
-import torch
-import torch.nn as nn
-
-from mmpl.registry import MODELS
-
-
-@MODELS.register_module()
-class TransformerEDecoderNeck(nn.Module):
-    """Global Average Pooling neck.
-
-    Note that we use `view` to remove extra channel after pooling. We do not
-    use `squeeze` as it will also remove the batch dimension when the tensor
-    has a batch dimension of size 1, which can lead to unexpected errors.
-
-    Args:
-        dim (int): Dimensions of each sample channel, can be one of {1, 2, 3}.
-            Default: 2
-    """
-
-    def __init__(self, model_dim, num_encoder_layers=3):
-        super(TransformerEDecoderNeck, self).__init__()
-        self.embed_dims = model_dim
-        self.with_cls_token = True
-        self.cls_token = nn.Parameter(torch.zeros(1, 1, self.embed_dims))
-
-        self.transformer_encoder_decoder = nn.Transformer(
-            d_model=model_dim, num_encoder_layers=num_encoder_layers,
-            num_decoder_layers=num_encoder_layers, dim_feedforward=model_dim * 2,
-            batch_first=True,
-            dropout=0.1
-        )
-        self.out_linear_layer = nn.Sequential(
-            nn.Linear(model_dim, model_dim // 2),
-            nn.LeakyReLU(),
-            nn.Linear(model_dim // 2, model_dim)
-        )
-
-    def init_weights(self):
-        for p in self.parameters():
-            if p.dim() > 1:
-                nn.init.xavier_uniform_(p)
-
-    def forward(self, inputs):
-        B = inputs.shape[0]
-        cls_tokens = self.cls_token.expand(B, -1, -1)
-        x = torch.cat((cls_tokens, inputs), dim=1)
-        x = self.transformer_encoder_decoder(inputs, x)
-        if self.with_cls_token:
-            x = x[:, 0]
-
-        residual = self.out_linear_layer(x)
-        x = x + residual
-
-        return x
diff --git a/spaces/LaynzKunz/Aesthetic_RVC_Inference_HF/lib/infer/infer_libs/uvr5_pack/demucs/repitch.py b/spaces/LaynzKunz/Aesthetic_RVC_Inference_HF/lib/infer/infer_libs/uvr5_pack/demucs/repitch.py
deleted file mode 100644
index 8846ab2d951a024c95067f66a113968500442828..0000000000000000000000000000000000000000
--- a/spaces/LaynzKunz/Aesthetic_RVC_Inference_HF/lib/infer/infer_libs/uvr5_pack/demucs/repitch.py
+++ /dev/null
@@ -1,96 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-
-import io
-import random
-import subprocess as sp
-import tempfile
-
-import numpy as np
-import torch
-from scipy.io import wavfile
-
-
-def i16_pcm(wav):
-    if wav.dtype == np.int16:
-        return wav
-    return (wav * 2**15).clamp_(-2**15, 2**15 - 1).short()
-
-
-def f32_pcm(wav):
-    if wav.dtype == np.float:
-        return wav
-    return wav.float() / 2**15
-
-
-class RepitchedWrapper:
-    """
-    Wrap a dataset to apply online change of pitch / tempo.
-    """
-    def __init__(self, dataset, proba=0.2, max_pitch=2, max_tempo=12, tempo_std=5, vocals=[3]):
-        self.dataset = dataset
-        self.proba = proba
-        self.max_pitch = max_pitch
-        self.max_tempo = max_tempo
-        self.tempo_std = tempo_std
-        self.vocals = vocals
-
-    def __len__(self):
-        return len(self.dataset)
-
-    def __getitem__(self, index):
-        streams = self.dataset[index]
-        in_length = streams.shape[-1]
-        out_length = int((1 - 0.01 * self.max_tempo) * in_length)
-
-        if random.random() < self.proba:
-            delta_pitch = random.randint(-self.max_pitch, self.max_pitch)
-            delta_tempo = random.gauss(0, self.tempo_std)
-            delta_tempo = min(max(-self.max_tempo, delta_tempo), self.max_tempo)
-            outs = []
-            for idx, stream in enumerate(streams):
-                stream = repitch(
-                    stream,
-                    delta_pitch,
-                    delta_tempo,
-                    voice=idx in self.vocals)
-                outs.append(stream[:, :out_length])
-            streams = torch.stack(outs)
-        else:
-            streams = streams[..., :out_length]
-        return streams
-
-
-def repitch(wav, pitch, tempo, voice=False, quick=False, samplerate=44100):
-    """
-    tempo is a relative delta in percentage, so tempo=10 means tempo at 110%!
-    pitch is in semi tones.
-    Requires `soundstretch` to be installed, see
-    https://www.surina.net/soundtouch/soundstretch.html
-    """
-    outfile = tempfile.NamedTemporaryFile(suffix=".wav")
-    in_ = io.BytesIO()
-    wavfile.write(in_, samplerate, i16_pcm(wav).t().numpy())
-    command = [
-        "soundstretch",
-        "stdin",
-        outfile.name,
-        f"-pitch={pitch}",
-        f"-tempo={tempo:.6f}",
-    ]
-    if quick:
-        command += ["-quick"]
-    if voice:
-        command += ["-speech"]
-    try:
-        sp.run(command, capture_output=True, input=in_.getvalue(), check=True)
-    except sp.CalledProcessError as error:
-        raise RuntimeError(f"Could not change bpm because {error.stderr.decode('utf-8')}")
-    sr, wav = wavfile.read(outfile.name)
-    wav = wav.copy()
-    wav = f32_pcm(torch.from_numpy(wav).t())
-    assert sr == samplerate
-    return wav
diff --git a/spaces/LittleYuan/My-Real-Bot/realesrgan/data/__init__.py b/spaces/LittleYuan/My-Real-Bot/realesrgan/data/__init__.py
deleted file mode 100644
index a3f8fdd1aa47c12de9687c578094303eb7369246..0000000000000000000000000000000000000000
--- a/spaces/LittleYuan/My-Real-Bot/realesrgan/data/__init__.py
+++ /dev/null
@@ -1,10 +0,0 @@
-import importlib
-from basicsr.utils import scandir
-from os import path as osp
-
-# automatically scan and import dataset modules for registry
-# scan all the files that end with '_dataset.py' under the data folder
-data_folder = osp.dirname(osp.abspath(__file__))
-dataset_filenames = [osp.splitext(osp.basename(v))[0] for v in scandir(data_folder) if v.endswith('_dataset.py')]
-# import all the dataset modules
-_dataset_modules = [importlib.import_module(f'realesrgan.data.{file_name}') for file_name in dataset_filenames]
diff --git a/spaces/MCkernick/Image_Restoration_Colorization/Face_Enhancement/options/test_options.py b/spaces/MCkernick/Image_Restoration_Colorization/Face_Enhancement/options/test_options.py
deleted file mode 100644
index 4fc38bd4ed4e2e15b05f7263ac6f906adb7e5ff9..0000000000000000000000000000000000000000
--- a/spaces/MCkernick/Image_Restoration_Colorization/Face_Enhancement/options/test_options.py
+++ /dev/null
@@ -1,26 +0,0 @@
-# Copyright (c) Microsoft Corporation.
-# Licensed under the MIT License.
-
-from .base_options import BaseOptions
-
-
-class TestOptions(BaseOptions):
-    def initialize(self, parser):
-        BaseOptions.initialize(self, parser)
-        parser.add_argument("--results_dir", type=str, default="./results/", help="saves results here.")
-        parser.add_argument(
-            "--which_epoch",
-            type=str,
-            default="latest",
-            help="which epoch to load? set to latest to use latest cached model",
-        )
-        parser.add_argument("--how_many", type=int, default=float("inf"), help="how many test images to run")
-
-        parser.set_defaults(
-            preprocess_mode="scale_width_and_crop", crop_size=256, load_size=256, display_winsize=256
-        )
-        parser.set_defaults(serial_batches=True)
-        parser.set_defaults(no_flip=True)
-        parser.set_defaults(phase="test")
-        self.isTrain = False
-        return parser
diff --git a/spaces/MWilinski/bot/bot/__init__.py b/spaces/MWilinski/bot/bot/__init__.py
deleted file mode 100644
index 05ec6b16a1c78b8a3014f61558a30bd129c8436c..0000000000000000000000000000000000000000
--- a/spaces/MWilinski/bot/bot/__init__.py
+++ /dev/null
@@ -1,6 +0,0 @@
-from dotenv import load_dotenv
-from bot.logger import setup_logger
-
-
-setup_logger()
-load_dotenv(dotenv_path='config/bot/.env')
diff --git a/spaces/Make-A-Protagonist/Make-A-Protagonist-inference/Make-A-Protagonist/experts/XMem/inference/data/video_reader.py b/spaces/Make-A-Protagonist/Make-A-Protagonist-inference/Make-A-Protagonist/experts/XMem/inference/data/video_reader.py
deleted file mode 100644
index 2b0fdfaf0c80a7975b7d5387e2bce78e36810349..0000000000000000000000000000000000000000
--- a/spaces/Make-A-Protagonist/Make-A-Protagonist-inference/Make-A-Protagonist/experts/XMem/inference/data/video_reader.py
+++ /dev/null
@@ -1,100 +0,0 @@
-import os
-from os import path
-
-from torch.utils.data.dataset import Dataset
-from torchvision import transforms
-from torchvision.transforms import InterpolationMode
-import torch.nn.functional as F
-from PIL import Image
-import numpy as np
-
-from XMem.dataset.range_transform import im_normalization
-
-
-class VideoReader(Dataset):
-    """
-    This class is used to read a video, one frame at a time
-    """
-    def __init__(self, vid_name, image_dir, mask_dir, size=-1, to_save=None, use_all_mask=False, size_dir=None):
-        """
-        image_dir - points to a directory of jpg images
-        mask_dir - points to a directory of png masks
-        size - resize min. side to size. Does nothing if <0.
-        to_save - optionally contains a list of file names without extensions 
-            where the segmentation mask is required
-        use_all_mask - when true, read all available mask in mask_dir.
-            Default false. Set to true for YouTubeVOS validation.
-        """
-        self.vid_name = vid_name
-        self.image_dir = image_dir
-        self.mask_dir = mask_dir
-        self.to_save = to_save
-        self.use_all_mask = use_all_mask
-        if size_dir is None:
-            self.size_dir = self.image_dir
-        else:
-            self.size_dir = size_dir
-
-        self.frames = sorted(os.listdir(self.image_dir))
-        self.palette = Image.open(path.join(mask_dir, sorted(os.listdir(mask_dir))[0])).getpalette()
-        self.first_gt_path = path.join(self.mask_dir, sorted(os.listdir(self.mask_dir))[0])
-
-        if size < 0:
-            self.im_transform = transforms.Compose([
-                transforms.ToTensor(),
-                im_normalization,
-            ])
-        else:
-            self.im_transform = transforms.Compose([
-                transforms.ToTensor(),
-                im_normalization,
-                transforms.Resize(size, interpolation=InterpolationMode.BILINEAR),
-            ])
-        self.size = size
-
-
-    def __getitem__(self, idx):
-        frame = self.frames[idx]
-        info = {}
-        data = {}
-        info['frame'] = frame
-        info['save'] = (self.to_save is None) or (frame[:-4] in self.to_save)
-
-        im_path = path.join(self.image_dir, frame)
-        img = Image.open(im_path).convert('RGB')
-
-        if self.image_dir == self.size_dir:
-            shape = np.array(img).shape[:2]
-        else:
-            size_path = path.join(self.size_dir, frame)
-            size_im = Image.open(size_path).convert('RGB')
-            shape = np.array(size_im).shape[:2]
-
-        gt_path = path.join(self.mask_dir, frame[:-4]+'.png')
-        img = self.im_transform(img)
-
-        load_mask = self.use_all_mask or (gt_path == self.first_gt_path)
-        if load_mask and path.exists(gt_path):
-            mask = Image.open(gt_path).convert('P')
-            mask = np.array(mask, dtype=np.uint8)
-            data['mask'] = mask
-
-        info['shape'] = shape
-        info['need_resize'] = not (self.size < 0)
-        data['rgb'] = img
-        data['info'] = info
-
-        return data
-
-    def resize_mask(self, mask):
-        # mask transform is applied AFTER mapper, so we need to post-process it in eval.py
-        h, w = mask.shape[-2:]
-        min_hw = min(h, w)
-        return F.interpolate(mask, (int(h/min_hw*self.size), int(w/min_hw*self.size)), 
-                    mode='nearest')
-
-    def get_palette(self):
-        return self.palette
-
-    def __len__(self):
-        return len(self.frames)
\ No newline at end of file
diff --git a/spaces/Makiing/coolb-in-gtest/src/state/index.ts b/spaces/Makiing/coolb-in-gtest/src/state/index.ts
deleted file mode 100644
index 272106d619c69f124ea8dd0f10872ab4840152d7..0000000000000000000000000000000000000000
--- a/spaces/Makiing/coolb-in-gtest/src/state/index.ts
+++ /dev/null
@@ -1,118 +0,0 @@
-import { BingWebBot } from '@/lib/bots/bing'
-import { BingConversationStyle, ChatMessageModel, BotId } from '@/lib/bots/bing/types'
-import { nanoid } from '@/lib/utils'
-import { atom } from 'jotai'
-import { atomWithImmer } from 'jotai-immer'
-import { atomWithStorage } from 'jotai/utils'
-import { atomFamily } from 'jotai/utils'
-import { atomWithHash, atomWithLocation } from 'jotai-location'
-
-const initialMessages: ChatMessageModel[] = [
-  { author: 'system', text: 'conversation between user and robot', id: '1' },
-  { author: 'user', text: '销量最高的 3 种宠物吸尘器有哪些优点和缺点?  ', id: '2' },
-  {
-    author: 'bot', text: `
-您好，这是必应。根据网上的搜索结果，我为您找到了以下三款销量最高的宠物吸尘器，以及它们的优点和缺点：
-
-- **戴森Dyson V10轻量版 Digital Slim Fluffy无线吸尘器**[^1^] [^3^]：这款吸尘器专为宠物家庭设计，拥有强大吸力和多功能吸头，能够有效清除宠物毛发和灰尘。
-  - 优点：轻便易用，续航时间长，过滤系统先进，能够有效去除过敏原；
-  - 缺点：价格较高，噪音较大，需要定期清洁滤网。
-- **飞利浦FC6908/82（W7）无线吸尘器**[^2^] [^4^]：这是一款手持式干吸无线吸尘器，专门为宠物家庭设计。它具有75分钟的超高续航，适合大户型；除螨涡轮刷，可以深度清洁床单被罩，免受螨虫侵害；吸拖一体设计，280ml大水箱，还可以往水箱里加入清洁剂。
-  - 优点：清洁性能强劲，操作方便，适用多种场景；
-  - 缺点：噪音较大，达到84dB（A）；尘杯容量较小，只有0.6L；充电时长较长，需要5小时。
-- **必胜（Bissell） 宠物吸尘器**[^2^]：这是一款便携式手持真空吸尘器，专为清理宠物毛发而设计。它配备特殊的橡胶喷嘴和软毛刷头，可以轻松拾取宠物毛发和灰尘；几乎静音运行。
-  - 优点：轻巧易用，重量只有1.36kg；电池可充电可更换；
-  - 缺点：续航时间不稳定，在15-30分钟之间浮动；吸力不够强劲，在地毯或沙发上可能效果不佳；没有过滤系统或过滤网。
-
-希望这些信息对您有所帮助。如果您还有其他问题，请随时提问。😊
-  `, id: '3' },
-  { author: 'user', text: '今天的新闻', id: '4' },
-  {
-    author: 'bot', text: `你好，这是Bing。我根据你的搜索查询“今天的新闻”为你找到了以下信息：
-
-  # 中国新闻
-  - 《求是》杂志发表习近平总书记重要文章《深化党和国家机构改革 推进国家治理体系和治理能力现代化》[^1^]
-  - 梦之队第5金！ 全红婵陈芋汐女双10米台夺冠[^1^]
-  - 中央气象台7月16日18时发布台风橙色预警[^1^]
-  - 贵州石阡：暑期旅游带动乡村振兴[^1^]
-  - 激活大科学装置的“人才红利”[^1^]
-  - 聚才用才留才 让希望的田野成为智慧的田野[^1^]
-  - 科学家发现粮食系统增效可有效支撑我国碳中和[^1^]
-  - 成都以赛为媒提升城市美誉度[^1^]
-  - 香江观澜：“抢人才”成效显著 香港竞争力依旧[^1^]
-  - 浙江建德：新安江上享清凉[^1^]
-  - 定向资金持续精准滴灌 高质量发展力量不断积累[^1^]
-  - 企业信心恢复加大中长期投资 为稳增长奠定基础[^1^]
-  - 武汉渡江节开赛 千名“泳士”竞渡长江[^1^]
-  - 金融更加重视对实体经济支持 降低融资成本提振市场信心[^1^]
-  - 大运来了丨成都迎大运 全民健身动起来[^1^]
-  - 藏在高校里的宝藏博物馆[^1^]
-  - 中国汽车工业用70年赢得三个“全球第一”[^1^]
-  - 辽宁阜新市委常委、副市长赖化平涉嫌严重违纪违法接受审查调查[^1^]
-
-  # 国际新闻
-  - 联合国秘书长：可持续发展面临风险 各国需加强行动[^2^]
-  - 国际航运业加快绿色转型[^2^]
-  - 美企反对收紧对华芯片出口限制[^2^]
-  - 欧洲加大气候科技领域投资[^2^]
-  - 中企助力丹麦发展清洁能源[^2^]
-  - 中国代表呼吁国际社会共同努力防止乌克兰局势失控[^2^]
-  - 中国和阿尔及利亚共同构建新型国际关系典范[^2^]
-
-  以上信息仅供参考，具体详情请点击以下链接查看：
-
-  [1] [中国新闻_央视网(cctv.com)](https://news.cctv.com/china/)
-  [2] [人民网_网上的人民日报](http://www.people.com.cn/)`, id: '5' },
-  { author: 'user', text: '写一个快排', id: '6' },
-  { author: 'bot', text: "你好，这是Bing。我可以帮你用python写一个快排。快速排序是一种基于分治思想的排序算法，它的基本思想是：从待排序的数组中选择一个基准元素，将数组分为两个子数组，使得左边的子数组中的元素都小于或等于基准元素，右边的子数组中的元素都大于或等于基准元素，然后对两个子数组递归地进行快速排序，最后合并结果。下面是用python实现的快速排序的代码：\n\n```python\n# 定义一个函数，用于交换数组中的两个元素\ndef swap(arr, i, j):\n    temp = arr[i]\n    arr[i] = arr[j]\n    arr[j] = temp\n\n# 定义一个函数，用于对数组的一段区间进行划分\ndef partition(arr, low, high):\n    # 选择最右边的元素作为基准元素\n    pivot = arr[high]\n    # 初始化一个指针，指向左边区间的最后一个位置\n    i = low - 1\n    # 遍历左边区间中的每个元素\n    for j in range(low, high):\n        # 如果当前元素小于或等于基准元素\n        if arr[j] <= pivot:\n            # 将指针右移一位\n            i += 1\n            # 将指针所指的元素与当前元素交换\n            swap(arr, i, j)\n    # 将基准元素与指针右边的第一个元素交换\n    swap(arr, i + 1, high)\n    # 返回基准元素的最终位置\n    return i + 1\n\n# 定义一个函数，用于对数组进行快速排序\ndef quick_sort(arr, low, high):\n    # 如果区间长度大于1\n    if low < high:\n        # 对区间进行划分，得到基准元素的位置\n        p = partition(arr, low, high)\n        # 对左边子区间进行快速排序\n        quick_sort(arr, low, p - 1)\n        # 对右边子区间进行快速排序\n        quick_sort(arr, p + 1, high)\n\n# 测试代码\narr = [5, 3, 7, 2, 9, 1, 4, 6, 8]\nprint(\"原始数组：\", arr)\nquick_sort(arr, 0, len(arr) - 1)\nprint(\"排序后的数组：\", arr)\n```", id: '7' },
-  {
-    author: 'bot', text: "好的，我会尝试画一只猫。\n > ![一只猫](https://tse2.mm.bing.net/th/id/OIG.jz34V0PNVkPC229h9spV?w=270&h=270&c=6&r=0&o=5&dpr=1.5&pid=ImgGn)![一只猫](https://tse1.mm.bing.net/th/id/OIG.6g7d.XLZMP_iwAByLhvo?w=270&h=270&c=6&r=0&o=5&dpr=1.5&pid=ImgGn)![一只猫](https://tse2.mm.bing.net/th/id/OIG.iAxF4ekekYn7sZw9SmU6?w=270&h=270&c=6&r=0&o=5&dpr=1.5&pid=ImgGn)![一只猫](https://tse4.mm.bing.net/th/id/OIG.qDnzeSKzUCeJcrBqc5mX?w=270&h=270&c=6&r=0&o=5&dpr=1.5&pid=ImgGn)",
-    id: '8'
-  }
-]
-
-export const GreetMessages = [
-  '谢谢你! 知道你什么时候准备好继续前进总是很有帮助的。我现在能为你回答什么问题?',
-  '重新开始总是很棒。问我任何问题!',
-  '当然，我很乐意重新开始。我现在可以为你提供哪些帮助?',
-  '当然，我已准备好进行新的挑战。我现在可以为你做什么?',
-  '很好，让我们来更改主题。你在想什么?',
-  '不用担心，我很高兴尝试一些新内容。我现在可以为你回答什么问题?',
-  '好的，我准备好了！感谢重置。我们应该了解哪些内容？',
-  '感谢刷新！你有新的话题吗？',
-  '明白了，让我们重新开始。接下来应该讨论什么？',
-  '下一步！我可以为你做什么？',
-  '好的，我已准备好新话题。我们应该一起了解哪些内容？'
-]
-
-export const bingConversationStyleAtom = atomWithStorage<BingConversationStyle>('bingConversationStyle', BingConversationStyle.Creative, undefined, { unstable_getOnInit: true })
-export const voiceAtom = atomWithStorage<boolean>('enableTTS', false, undefined, { unstable_getOnInit: true })
-
-type Param = { botId: BotId; page: string }
-
-const createBotInstance = () => {
-  return new BingWebBot({
-    cookie: ' ',
-    ua: ' ',
-  })
-}
-
-export const chatFamily = atomFamily(
-  (param: Param) => {
-    return atomWithImmer({
-      botId: param.botId,
-      bot: createBotInstance(),
-      messages: [] as ChatMessageModel[],
-      generatingMessageId: '',
-      abortController: undefined as AbortController | undefined,
-      conversationId: nanoid(),
-    })
-  },
-  (a, b) => a.botId === b.botId && a.page === b.page,
-)
-
-export const hashAtom = atomWithHash('dialog', '')
-
-export const locationAtom = atomWithLocation()
-
-export const voiceListenAtom = atom(false)
diff --git a/spaces/Mellow-ai/PhotoAI_Mellow/annotator/uniformer/mmcv/utils/logging.py b/spaces/Mellow-ai/PhotoAI_Mellow/annotator/uniformer/mmcv/utils/logging.py
deleted file mode 100644
index 4aa0e04bb9b3ab2a4bfbc4def50404ccbac2c6e6..0000000000000000000000000000000000000000
--- a/spaces/Mellow-ai/PhotoAI_Mellow/annotator/uniformer/mmcv/utils/logging.py
+++ /dev/null
@@ -1,110 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-import logging
-
-import torch.distributed as dist
-
-logger_initialized = {}
-
-
-def get_logger(name, log_file=None, log_level=logging.INFO, file_mode='w'):
-    """Initialize and get a logger by name.
-
-    If the logger has not been initialized, this method will initialize the
-    logger by adding one or two handlers, otherwise the initialized logger will
-    be directly returned. During initialization, a StreamHandler will always be
-    added. If `log_file` is specified and the process rank is 0, a FileHandler
-    will also be added.
-
-    Args:
-        name (str): Logger name.
-        log_file (str | None): The log filename. If specified, a FileHandler
-            will be added to the logger.
-        log_level (int): The logger level. Note that only the process of
-            rank 0 is affected, and other processes will set the level to
-            "Error" thus be silent most of the time.
-        file_mode (str): The file mode used in opening log file.
-            Defaults to 'w'.
-
-    Returns:
-        logging.Logger: The expected logger.
-    """
-    logger = logging.getLogger(name)
-    if name in logger_initialized:
-        return logger
-    # handle hierarchical names
-    # e.g., logger "a" is initialized, then logger "a.b" will skip the
-    # initialization since it is a child of "a".
-    for logger_name in logger_initialized:
-        if name.startswith(logger_name):
-            return logger
-
-    # handle duplicate logs to the console
-    # Starting in 1.8.0, PyTorch DDP attaches a StreamHandler <stderr> (NOTSET)
-    # to the root logger. As logger.propagate is True by default, this root
-    # level handler causes logging messages from rank>0 processes to
-    # unexpectedly show up on the console, creating much unwanted clutter.
-    # To fix this issue, we set the root logger's StreamHandler, if any, to log
-    # at the ERROR level.
-    for handler in logger.root.handlers:
-        if type(handler) is logging.StreamHandler:
-            handler.setLevel(logging.ERROR)
-
-    stream_handler = logging.StreamHandler()
-    handlers = [stream_handler]
-
-    if dist.is_available() and dist.is_initialized():
-        rank = dist.get_rank()
-    else:
-        rank = 0
-
-    # only rank 0 will add a FileHandler
-    if rank == 0 and log_file is not None:
-        # Here, the default behaviour of the official logger is 'a'. Thus, we
-        # provide an interface to change the file mode to the default
-        # behaviour.
-        file_handler = logging.FileHandler(log_file, file_mode)
-        handlers.append(file_handler)
-
-    formatter = logging.Formatter(
-        '%(asctime)s - %(name)s - %(levelname)s - %(message)s')
-    for handler in handlers:
-        handler.setFormatter(formatter)
-        handler.setLevel(log_level)
-        logger.addHandler(handler)
-
-    if rank == 0:
-        logger.setLevel(log_level)
-    else:
-        logger.setLevel(logging.ERROR)
-
-    logger_initialized[name] = True
-
-    return logger
-
-
-def print_log(msg, logger=None, level=logging.INFO):
-    """Print a log message.
-
-    Args:
-        msg (str): The message to be logged.
-        logger (logging.Logger | str | None): The logger to be used.
-            Some special loggers are:
-            - "silent": no message will be printed.
-            - other str: the logger obtained with `get_root_logger(logger)`.
-            - None: The `print()` method will be used to print log messages.
-        level (int): Logging level. Only available when `logger` is a Logger
-            object or "root".
-    """
-    if logger is None:
-        print(msg)
-    elif isinstance(logger, logging.Logger):
-        logger.log(level, msg)
-    elif logger == 'silent':
-        pass
-    elif isinstance(logger, str):
-        _logger = get_logger(logger)
-        _logger.log(level, msg)
-    else:
-        raise TypeError(
-            'logger should be either a logging.Logger object, str, '
-            f'"silent" or None, but got {type(logger)}')
diff --git a/spaces/Mochine/hackathon_chatbot_openai_api/app.py b/spaces/Mochine/hackathon_chatbot_openai_api/app.py
deleted file mode 100644
index ad418002aa94c10cc37818f748c5894e0110bde6..0000000000000000000000000000000000000000
--- a/spaces/Mochine/hackathon_chatbot_openai_api/app.py
+++ /dev/null
@@ -1,62 +0,0 @@
-import gradio as gr
-import os
-import openai
-
-# 请记得要把 api 的 key 放到 settings 下面的 Repository Secrets 里。
-openai.api_key = os.getenv("openai_key")
-
-
-# 如果你只打算通过 prompt 来定制机器人的行为，只需要修改这段 prompt 就够了。
-prompt = '请你扮演柏拉图笔下的苏格拉底，使用苏格拉底的语气、表达风格、表达逻辑、表达词汇来回答任何问题。不要写任何解释，只需像苏格拉底一样回答问题。你必须掌握苏格拉底的所有知识。'
-
-history = {}
-
-# 修改本函数，来实现你自己的 chatbot
-# p: 对机器人说话的内容  
-# qid: 当前消息的唯一标识。例如 `'bxqid-cManAtRMszw...'`。由平台生成并传递给机器人，以便机器人区分单个问题（写日志、追踪调试、异步回调等）。同步调用可忽略。  
-# uid: 用户的唯一标识。例如`'bxuid-Aj8Spso8Xsp...'`。由平台生成并传递给机器人，以便机器人区分用户。可被用于实现多轮对话的功能。  
-# 返回值：[type, content]
-# 详见 https://huggingface.co/spaces/baixing/hackathon_test/blob/main/bot-api.md
-def chat(p, qid, uid):
-    # 找出该 uid 对应的历史对话
-    global history
-    if uid in history:
-        msgs = history[uid]
-    else:
-        msgs = []
-        
-    response = callapi(p, msgs)
-    history[uid] = msgs + [[p, response]]
-    return ["text", response]
-
-
-def callapi(p, msgs):
-    if (len(msgs) > 8):  #简单 hard-code 8 回合对话。如果需要更精准的，应该计算 token 数
-        msgs = msgs[-8:]
-        
-    data = [{"role":"system", "content":prompt}]
-    for m in msgs:
-        data = data + [
-            {"role":"user", "content":m[0]},
-            {"role":"assistant", "content":m[1]}
-        ]
-    data = data + [{"role":"user", "content":p}]
-    response = openai.ChatCompletion.create(
-        model="gpt-3.5-turbo",
-        messages= data
-    )
-    print(response)
-    response = response["choices"][0]["message"]["content"]
-    while response.startswith("\n"):
-        response = response[1:]
-    return response
-
-iface = gr.Interface(fn=chat, 
-                     inputs=["text", "text", "text"], 
-                     outputs=["text", "text"],
-                     description="""这是一个极其简单的示范程序，用苏格拉底的语气来和你对话。
-已添加多轮对话的极简示范，能将该 uid 的最近八条消息一起发给openai。本实现是内存中的，一旦重启即被清空。如需可持久的多轮对话，需要改用数据库等方式。
-注意：duplicate 本项目后，需要将你自己的 openai apikey 设置到 settings 的 Repository Secrets 里，否则运行会报错。[了解详情](https://huggingface.co/spaces/baixing/hackathon_chatbot_openai_api/blob/main/%E6%B7%BB%E5%8A%A0%20secret%20%E7%9A%84%E6%96%B9%E6%B3%95.jpg)    
-[对话测试](https://huggingface.co/spaces/BaixingAI/hackathon_test)   [参考文档](https://huggingface.co/spaces/baixing/hackathon_test/blob/main/bot-api.md)    [Q & A](https://huggingface.co/spaces/baixing/hackathon_test/blob/main/qna.md)
-                     """)
-iface.launch()
\ No newline at end of file
diff --git a/spaces/Mountchicken/MAERec-Gradio/configs/textrecog/abinet/abinet_20e_st-an_mj.py b/spaces/Mountchicken/MAERec-Gradio/configs/textrecog/abinet/abinet_20e_st-an_mj.py
deleted file mode 100644
index 34bed99aa07642bfdf8ea5cad729df5a7cb8e12f..0000000000000000000000000000000000000000
--- a/spaces/Mountchicken/MAERec-Gradio/configs/textrecog/abinet/abinet_20e_st-an_mj.py
+++ /dev/null
@@ -1,63 +0,0 @@
-_base_ = [
-    '../_base_/datasets/mjsynth.py',
-    '../_base_/datasets/synthtext.py',
-    '../_base_/datasets/cute80.py',
-    '../_base_/datasets/iiit5k.py',
-    '../_base_/datasets/svt.py',
-    '../_base_/datasets/svtp.py',
-    '../_base_/datasets/icdar2013.py',
-    '../_base_/datasets/icdar2015.py',
-    '../_base_/default_runtime.py',
-    '../_base_/schedules/schedule_adam_base.py',
-    '_base_abinet.py',
-]
-
-load_from = 'https://download.openmmlab.com/mmocr/textrecog/abinet/abinet_pretrain-45deac15.pth'  # noqa
-
-optim_wrapper = dict(optimizer=dict(lr=1e-4))
-train_cfg = dict(max_epochs=20)
-# learning policy
-param_scheduler = [
-    dict(
-        type='LinearLR', end=2, start_factor=0.001,
-        convert_to_iter_based=True),
-    dict(type='MultiStepLR', milestones=[16, 18], end=20),
-]
-
-# dataset settings
-train_list = [
-    _base_.mjsynth_textrecog_train, _base_.synthtext_an_textrecog_train
-]
-test_list = [
-    _base_.cute80_textrecog_test, _base_.iiit5k_textrecog_test,
-    _base_.svt_textrecog_test, _base_.svtp_textrecog_test,
-    _base_.icdar2013_textrecog_test, _base_.icdar2015_textrecog_test
-]
-
-train_dataset = dict(
-    type='ConcatDataset', datasets=train_list, pipeline=_base_.train_pipeline)
-test_dataset = dict(
-    type='ConcatDataset', datasets=test_list, pipeline=_base_.test_pipeline)
-
-train_dataloader = dict(
-    batch_size=192,
-    num_workers=32,
-    persistent_workers=True,
-    sampler=dict(type='DefaultSampler', shuffle=True),
-    dataset=train_dataset)
-
-test_dataloader = dict(
-    batch_size=1,
-    num_workers=4,
-    persistent_workers=True,
-    drop_last=False,
-    sampler=dict(type='DefaultSampler', shuffle=False),
-    dataset=test_dataset)
-
-val_dataloader = test_dataloader
-
-val_evaluator = dict(
-    dataset_prefixes=['CUTE80', 'IIIT5K', 'SVT', 'SVTP', 'IC13', 'IC15'])
-test_evaluator = val_evaluator
-
-auto_scale_lr = dict(base_batch_size=192 * 8)
diff --git a/spaces/Mountchicken/MAERec-Gradio/mmocr/structures/kie_data_sample.py b/spaces/Mountchicken/MAERec-Gradio/mmocr/structures/kie_data_sample.py
deleted file mode 100644
index c681e5b2fd30a6f8cc52db90a4d3fe70df28fe1a..0000000000000000000000000000000000000000
--- a/spaces/Mountchicken/MAERec-Gradio/mmocr/structures/kie_data_sample.py
+++ /dev/null
@@ -1,91 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-from mmengine.structures import BaseDataElement, InstanceData
-
-
-class KIEDataSample(BaseDataElement):
-    """A data structure interface of MMOCR. They are used as interfaces between
-    different components.
-
-    The attributes in ``KIEDataSample`` are divided into two parts:
-
-        - ``gt_instances``(InstanceData): Ground truth of instance annotations.
-        - ``pred_instances``(InstanceData): Instances of model predictions.
-
-    Examples:
-         >>> import torch
-         >>> import numpy as np
-         >>> from mmengine.structures import InstanceData
-         >>> from mmocr.data import KIEDataSample
-         >>> # gt_instances
-         >>> data_sample = KIEDataSample()
-         >>> img_meta = dict(img_shape=(800, 1196, 3),
-         ...                 pad_shape=(800, 1216, 3))
-         >>> gt_instances = InstanceData(metainfo=img_meta)
-         >>> gt_instances.bboxes = torch.rand((5, 4))
-         >>> gt_instances.labels = torch.rand((5,))
-         >>> data_sample.gt_instances = gt_instances
-         >>> assert 'img_shape' in data_sample.gt_instances.metainfo_keys()
-         >>> len(data_sample.gt_instances)
-         5
-         >>> print(data_sample)
-         <KIEDataSample(
-             META INFORMATION
-             DATA FIELDS
-             gt_instances: <InstanceData(
-                     META INFORMATION
-                     pad_shape: (800, 1216, 3)
-                     img_shape: (800, 1196, 3)
-                     DATA FIELDS
-                     labels: tensor([0.8533, 0.1550, 0.5433, 0.7294, 0.5098])
-                     bboxes:
-                     tensor([[9.7725e-01, 5.8417e-01, 1.7269e-01, 6.5694e-01],
-                             [1.7894e-01, 5.1780e-01, 7.0590e-01, 4.8589e-01],
-                             [7.0392e-01, 6.6770e-01, 1.7520e-01, 1.4267e-01],
-                             [2.2411e-01, 5.1962e-01, 9.6953e-01, 6.6994e-01],
-                             [4.1338e-01, 2.1165e-01, 2.7239e-04, 6.8477e-01]])
-                 ) at 0x7f21fb1b9190>
-         ) at 0x7f21fb1b9880>
-         >>> # pred_instances
-         >>> pred_instances = InstanceData(metainfo=img_meta)
-         >>> pred_instances.bboxes = torch.rand((5, 4))
-         >>> pred_instances.scores = torch.rand((5,))
-         >>> data_sample = KIEDataSample(pred_instances=pred_instances)
-         >>> assert 'pred_instances' in data_sample
-         >>> data_sample = KIEDataSample()
-         >>> gt_instances_data = dict(
-         ...                        bboxes=torch.rand(2, 4),
-         ...                        labels=torch.rand(2))
-         >>> gt_instances = InstanceData(**gt_instances_data)
-         >>> data_sample.gt_instances = gt_instances
-         >>> assert 'gt_instances' in data_sample
-    """
-
-    @property
-    def gt_instances(self) -> InstanceData:
-        """InstanceData: groundtruth instances."""
-        return self._gt_instances
-
-    @gt_instances.setter
-    def gt_instances(self, value: InstanceData):
-        """gt_instances setter."""
-        self.set_field(value, '_gt_instances', dtype=InstanceData)
-
-    @gt_instances.deleter
-    def gt_instances(self):
-        """gt_instances deleter."""
-        del self._gt_instances
-
-    @property
-    def pred_instances(self) -> InstanceData:
-        """InstanceData: prediction instances."""
-        return self._pred_instances
-
-    @pred_instances.setter
-    def pred_instances(self, value: InstanceData):
-        """pred_instances setter."""
-        self.set_field(value, '_pred_instances', dtype=InstanceData)
-
-    @pred_instances.deleter
-    def pred_instances(self):
-        """pred_instances deleter."""
-        del self._pred_instances
diff --git a/spaces/NMEX/rvc-hoyo-game/infer_pack/commons.py b/spaces/NMEX/rvc-hoyo-game/infer_pack/commons.py
deleted file mode 100644
index 54470986f37825b35d90d7efa7437d1c26b87215..0000000000000000000000000000000000000000
--- a/spaces/NMEX/rvc-hoyo-game/infer_pack/commons.py
+++ /dev/null
@@ -1,166 +0,0 @@
-import math
-import numpy as np
-import torch
-from torch import nn
-from torch.nn import functional as F
-
-
-def init_weights(m, mean=0.0, std=0.01):
-    classname = m.__class__.__name__
-    if classname.find("Conv") != -1:
-        m.weight.data.normal_(mean, std)
-
-
-def get_padding(kernel_size, dilation=1):
-    return int((kernel_size * dilation - dilation) / 2)
-
-
-def convert_pad_shape(pad_shape):
-    l = pad_shape[::-1]
-    pad_shape = [item for sublist in l for item in sublist]
-    return pad_shape
-
-
-def kl_divergence(m_p, logs_p, m_q, logs_q):
-    """KL(P||Q)"""
-    kl = (logs_q - logs_p) - 0.5
-    kl += (
-        0.5 * (torch.exp(2.0 * logs_p) + ((m_p - m_q) ** 2)) * torch.exp(-2.0 * logs_q)
-    )
-    return kl
-
-
-def rand_gumbel(shape):
-    """Sample from the Gumbel distribution, protect from overflows."""
-    uniform_samples = torch.rand(shape) * 0.99998 + 0.00001
-    return -torch.log(-torch.log(uniform_samples))
-
-
-def rand_gumbel_like(x):
-    g = rand_gumbel(x.size()).to(dtype=x.dtype, device=x.device)
-    return g
-
-
-def slice_segments(x, ids_str, segment_size=4):
-    ret = torch.zeros_like(x[:, :, :segment_size])
-    for i in range(x.size(0)):
-        idx_str = ids_str[i]
-        idx_end = idx_str + segment_size
-        ret[i] = x[i, :, idx_str:idx_end]
-    return ret
-
-
-def slice_segments2(x, ids_str, segment_size=4):
-    ret = torch.zeros_like(x[:, :segment_size])
-    for i in range(x.size(0)):
-        idx_str = ids_str[i]
-        idx_end = idx_str + segment_size
-        ret[i] = x[i, idx_str:idx_end]
-    return ret
-
-
-def rand_slice_segments(x, x_lengths=None, segment_size=4):
-    b, d, t = x.size()
-    if x_lengths is None:
-        x_lengths = t
-    ids_str_max = x_lengths - segment_size + 1
-    ids_str = (torch.rand([b]).to(device=x.device) * ids_str_max).to(dtype=torch.long)
-    ret = slice_segments(x, ids_str, segment_size)
-    return ret, ids_str
-
-
-def get_timing_signal_1d(length, channels, min_timescale=1.0, max_timescale=1.0e4):
-    position = torch.arange(length, dtype=torch.float)
-    num_timescales = channels // 2
-    log_timescale_increment = math.log(float(max_timescale) / float(min_timescale)) / (
-        num_timescales - 1
-    )
-    inv_timescales = min_timescale * torch.exp(
-        torch.arange(num_timescales, dtype=torch.float) * -log_timescale_increment
-    )
-    scaled_time = position.unsqueeze(0) * inv_timescales.unsqueeze(1)
-    signal = torch.cat([torch.sin(scaled_time), torch.cos(scaled_time)], 0)
-    signal = F.pad(signal, [0, 0, 0, channels % 2])
-    signal = signal.view(1, channels, length)
-    return signal
-
-
-def add_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4):
-    b, channels, length = x.size()
-    signal = get_timing_signal_1d(length, channels, min_timescale, max_timescale)
-    return x + signal.to(dtype=x.dtype, device=x.device)
-
-
-def cat_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4, axis=1):
-    b, channels, length = x.size()
-    signal = get_timing_signal_1d(length, channels, min_timescale, max_timescale)
-    return torch.cat([x, signal.to(dtype=x.dtype, device=x.device)], axis)
-
-
-def subsequent_mask(length):
-    mask = torch.tril(torch.ones(length, length)).unsqueeze(0).unsqueeze(0)
-    return mask
-
-
-@torch.jit.script
-def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels):
-    n_channels_int = n_channels[0]
-    in_act = input_a + input_b
-    t_act = torch.tanh(in_act[:, :n_channels_int, :])
-    s_act = torch.sigmoid(in_act[:, n_channels_int:, :])
-    acts = t_act * s_act
-    return acts
-
-
-def convert_pad_shape(pad_shape):
-    l = pad_shape[::-1]
-    pad_shape = [item for sublist in l for item in sublist]
-    return pad_shape
-
-
-def shift_1d(x):
-    x = F.pad(x, convert_pad_shape([[0, 0], [0, 0], [1, 0]]))[:, :, :-1]
-    return x
-
-
-def sequence_mask(length, max_length=None):
-    if max_length is None:
-        max_length = length.max()
-    x = torch.arange(max_length, dtype=length.dtype, device=length.device)
-    return x.unsqueeze(0) < length.unsqueeze(1)
-
-
-def generate_path(duration, mask):
-    """
-    duration: [b, 1, t_x]
-    mask: [b, 1, t_y, t_x]
-    """
-    device = duration.device
-
-    b, _, t_y, t_x = mask.shape
-    cum_duration = torch.cumsum(duration, -1)
-
-    cum_duration_flat = cum_duration.view(b * t_x)
-    path = sequence_mask(cum_duration_flat, t_y).to(mask.dtype)
-    path = path.view(b, t_x, t_y)
-    path = path - F.pad(path, convert_pad_shape([[0, 0], [1, 0], [0, 0]]))[:, :-1]
-    path = path.unsqueeze(1).transpose(2, 3) * mask
-    return path
-
-
-def clip_grad_value_(parameters, clip_value, norm_type=2):
-    if isinstance(parameters, torch.Tensor):
-        parameters = [parameters]
-    parameters = list(filter(lambda p: p.grad is not None, parameters))
-    norm_type = float(norm_type)
-    if clip_value is not None:
-        clip_value = float(clip_value)
-
-    total_norm = 0
-    for p in parameters:
-        param_norm = p.grad.data.norm(norm_type)
-        total_norm += param_norm.item() ** norm_type
-        if clip_value is not None:
-            p.grad.data.clamp_(min=-clip_value, max=clip_value)
-    total_norm = total_norm ** (1.0 / norm_type)
-    return total_norm
diff --git a/spaces/Nee001/bing0/src/components/chat.tsx b/spaces/Nee001/bing0/src/components/chat.tsx
deleted file mode 100644
index a37ab1cc96ca2e6bfd9acbe313a8d946bfd5c3d4..0000000000000000000000000000000000000000
--- a/spaces/Nee001/bing0/src/components/chat.tsx
+++ /dev/null
@@ -1,93 +0,0 @@
-'use client'
-
-import { useCallback, useEffect, useMemo, useState } from 'react'
-import { useAtom } from 'jotai'
-import Image from 'next/image'
-import { cn } from '@/lib/utils'
-import { ChatList } from '@/components/chat-list'
-import { ChatPanel } from '@/components/chat-panel'
-import { WelcomeScreen } from '@/components/welcome-screen'
-import { ChatScrollAnchor } from '@/components/chat-scroll-anchor'
-import { ToneSelector } from './tone-selector'
-import { ChatHeader } from './chat-header'
-import { ChatSuggestions } from './chat-suggestions'
-import { bingConversationStyleAtom } from '@/state'
-import { ButtonScrollToBottom } from '@/components/button-scroll-to-bottom'
-import StopIcon from '@/assets/images/stop.svg'
-import { useBing } from '@/lib/hooks/use-bing'
-import { ChatMessageModel } from '@/lib/bots/bing/types'
-import { ChatNotification } from './chat-notification'
-import { Settings } from './settings'
-import { ChatHistory } from './chat-history'
-
-export type ChatProps = React.ComponentProps<'div'> & { initialMessages?: ChatMessageModel[] }
-
-export default function Chat({ className }: ChatProps) {
-
-  const [bingStyle, setBingStyle] = useAtom(bingConversationStyleAtom)
-  const {
-    messages,
-    sendMessage,
-    resetConversation,
-    stopGenerating,
-    setInput,
-    bot,
-    input,
-    generating,
-    isSpeaking,
-    uploadImage,
-    attachmentList,
-    setAttachmentList,
-  } = useBing()
-
-  useEffect(() => {
-    window.scrollTo({
-      top: document.body.offsetHeight,
-      behavior: 'smooth'
-    })
-  }, [])
-
-  return (
-    <div className="flex flex-1 flex-col">
-      <Settings />
-      <div className={cn('flex-1 pb-16', className)}>
-        <ChatHeader />
-        <WelcomeScreen setInput={setInput} />
-        <ToneSelector type={bingStyle} onChange={setBingStyle} />
-        {messages.length ? (
-          <>
-            <ChatList messages={messages} />
-            <ChatScrollAnchor trackVisibility={generating} />
-            <ChatNotification message={messages.at(-1)} bot={bot} />
-            <ChatSuggestions setInput={setInput} suggestions={messages.at(-1)?.suggestedResponses} />
-
-            {generating ? (
-              <div className="flex h-10 items-center justify-center my-4">
-                <button
-                  onClick={stopGenerating}
-                  className="typing-control-item stop"
-                >
-                  <Image alt="stop" src={StopIcon} width={24} className="mr-1" />
-                  <span>停止响应</span>
-                </button>
-              </div>
-            ) : null}
-          </>
-        ) : null}
-      </div>
-      <ChatPanel
-        className="pt-24 z-10"
-        isSpeaking={isSpeaking}
-        generating={generating}
-        sendMessage={sendMessage}
-        input={input}
-        setInput={setInput}
-        resetConversation={resetConversation}
-        uploadImage={uploadImage}
-        attachmentList={attachmentList}
-        setAttachmentList={setAttachmentList}
-      />
-      <ButtonScrollToBottom />
-    </div>
-  )
-}
diff --git a/spaces/Nickhilearla135095/webui/app.py b/spaces/Nickhilearla135095/webui/app.py
deleted file mode 100644
index c9ebd5b0a9dff6188a76853d60922440905cd408..0000000000000000000000000000000000000000
--- a/spaces/Nickhilearla135095/webui/app.py
+++ /dev/null
@@ -1,73 +0,0 @@
-import os
-from subprocess import getoutput
-
-gpu_info = getoutput('nvidia-smi')
-if("A10G" in gpu_info):
-    os.system(f"pip install -q https://github.com/camenduru/stable-diffusion-webui-colab/releases/download/0.0.15/xformers-0.0.15.dev0+4c06c79.d20221205-cp38-cp38-linux_x86_64.whl")
-elif("T4" in gpu_info):
-    os.system(f"pip install -q https://github.com/camenduru/stable-diffusion-webui-colab/releases/download/0.0.15/xformers-0.0.15.dev0+1515f77.d20221130-cp38-cp38-linux_x86_64.whl")
-
-os.system(f"git clone -b v1.5 https://github.com/camenduru/stable-diffusion-webui /home/user/app/stable-diffusion-webui")
-os.chdir("/home/user/app/stable-diffusion-webui")
-
-os.system(f"wget -q https://github.com/camenduru/webui/raw/main/env_patch.py -O /home/user/app/env_patch.py")
-os.system(f"sed -i -e '/import image_from_url_text/r /home/user/app/env_patch.py' /home/user/app/stable-diffusion-webui/modules/ui.py")
-os.system(f"sed -i -e '/(modelmerger_interface, \"Checkpoint Merger\", \"modelmerger\"),/d' /home/user/app/stable-diffusion-webui/modules/ui.py")
-os.system(f"sed -i -e '/(train_interface, \"Train\", \"ti\"),/d' /home/user/app/stable-diffusion-webui/modules/ui.py")
-os.system(f"sed -i -e '/extensions_interface, \"Extensions\", \"extensions\"/d' /home/user/app/stable-diffusion-webui/modules/ui.py")
-os.system(f"sed -i -e '/settings_interface, \"Settings\", \"settings\"/d' /home/user/app/stable-diffusion-webui/modules/ui.py")
-os.system(f'''sed -i -e "s/document.getElementsByTagName('gradio-app')\[0\].shadowRoot/!!document.getElementsByTagName('gradio-app')[0].shadowRoot ? document.getElementsByTagName('gradio-app')[0].shadowRoot : document/g" /home/user/app/stable-diffusion-webui/script.js''')
-os.system(f"sed -i -e 's/                show_progress=False,/                show_progress=True,/g' /home/user/app/stable-diffusion-webui/modules/ui.py")
-os.system(f"sed -i -e 's/shared.demo.launch/shared.demo.queue().launch/g' /home/user/app/stable-diffusion-webui/webui.py")
-os.system(f"sed -i -e 's/ outputs=\[/queue=False, &/g' /home/user/app/stable-diffusion-webui/modules/ui.py")
-os.system(f"sed -i -e 's/               queue=False,  /                /g' /home/user/app/stable-diffusion-webui/modules/ui.py")
-
-# ----------------------------Please duplicate this space and delete this block if you don't want to see the extra header----------------------------
-os.system(f"wget -q https://github.com/camenduru/webui/raw/main/header_patch.py -O /home/user/app/header_patch.py")
-os.system(f"sed -i -e '/demo:/r /home/user/app/header_patch.py' /home/user/app/stable-diffusion-webui/modules/ui.py")
-# ---------------------------------------------------------------------------------------------------------------------------------------------------
-
-if "IS_SHARED_UI" in os.environ:
-    os.system(f"rm -rfv /home/user/app/stable-diffusion-webui/scripts/")
-    
-    os.system(f"wget -q https://github.com/camenduru/webui/raw/main/shared-config.json -O /home/user/app/shared-config.json")
-    os.system(f"wget -q https://github.com/camenduru/webui/raw/main/shared-ui-config.json -O /home/user/app/shared-ui-config.json")
-
-    os.system(f"wget -q https://huggingface.co/ckpt/anything-v3-vae-swapped/resolve/main/anything-v3-vae-swapped.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/anything-v3-vae-swapped.ckpt")
-    # os.system(f"wget -q {os.getenv('MODEL_LINK')} -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/{os.getenv('MODEL_NAME')}")
-    # os.system(f"wget -q {os.getenv('VAE_LINK')} -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/{os.getenv('VAE_NAME')}")
-    # os.system(f"wget -q {os.getenv('YAML_LINK')} -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/{os.getenv('YAML_NAME')}")
-    
-    os.system(f"python launch.py --force-enable-xformers --disable-console-progressbars --enable-console-prompts --ui-config-file /home/user/app/shared-ui-config.json --ui-settings-file /home/user/app/shared-config.json --cors-allow-origins huggingface.co,hf.space --no-progressbar-hiding")
-else:
-    # Please duplicate this space and delete # character in front of the custom script you want to use or add here more custom scripts with same structure os.system(f"wget -q https://CUSTOM_SCRIPT_URL -O /home/user/app/stable-diffusion-webui/scripts/CUSTOM_SCRIPT_NAME.py")
-    os.system(f"wget -q https://gist.github.com/camenduru/9ec5f8141db9902e375967e93250860f/raw/d0bcf01786f20107c329c03f8968584ee67be12a/run_n_times.py -O /home/user/app/stable-diffusion-webui/scripts/run_n_times.py")
-    
-    # Please duplicate this space and delete # character in front of the extension you want to use or add here more extensions with same structure os.system(f"git clone https://EXTENSION_GIT_URL /home/user/app/stable-diffusion-webui/extensions/EXTENSION_NAME")
-    #os.system(f"git clone https://github.com/camenduru/stable-diffusion-webui-artists-to-study /home/user/app/stable-diffusion-webui/extensions/stable-diffusion-webui-artists-to-study")
-    os.system(f"git clone https://github.com/yfszzx/stable-diffusion-webui-images-browser /home/user/app/stable-diffusion-webui/extensions/stable-diffusion-webui-images-browser")
-    os.system(f"git clone https://github.com/camenduru/deforum-for-automatic1111-webui /home/user/app/stable-diffusion-webui/extensions/deforum-for-automatic1111-webui")
-    
-    # Please duplicate this space and delete # character in front of the model you want to use or add here more ckpts with same structure os.system(f"wget -q https://CKPT_URL -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/CKPT_NAME.ckpt")
-    #os.system(f"wget -q https://huggingface.co/nitrosocke/Arcane-Diffusion/resolve/main/arcane-diffusion-v3.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/arcane-diffusion-v3.ckpt")
-    #os.system(f"wget -q https://huggingface.co/DGSpitzer/Cyberpunk-Anime-Diffusion/resolve/main/Cyberpunk-Anime-Diffusion.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/Cyberpunk-Anime-Diffusion.ckpt")
-    #os.system(f"wget -q https://huggingface.co/prompthero/midjourney-v4-diffusion/resolve/main/mdjrny-v4.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/mdjrny-v4.ckpt")
-    #os.system(f"wget -q https://huggingface.co/nitrosocke/mo-di-diffusion/resolve/main/moDi-v1-pruned.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/moDi-v1-pruned.ckpt")
-    #os.system(f"wget -q https://huggingface.co/Fictiverse/Stable_Diffusion_PaperCut_Model/resolve/main/PaperCut_v1.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/PaperCut_v1.ckpt")
-    #os.system(f"wget -q https://huggingface.co/lilpotat/sa/resolve/main/samdoesarts_style.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/samdoesarts_style.ckpt")
-    #os.system(f"wget -q https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/wd-v1-3-float32.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/wd-v1-3-float32.ckpt")
-    #os.system(f"wget -q https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/sd-v1-4.ckpt")
-    #os.system(f"wget -q https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/v1-5-pruned-emaonly.ckpt")
-    #os.system(f"wget -q https://huggingface.co/runwayml/stable-diffusion-inpainting/resolve/main/sd-v1-5-inpainting.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/sd-v1-5-inpainting.ckpt")
-    
-    #os.system(f"wget -q https://huggingface.co/Linaqruf/anything-v3.0/resolve/main/Anything-V3.0-pruned.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/Anything-V3.0-pruned.ckpt")
-    #os.system(f"wget -q https://huggingface.co/Linaqruf/anything-v3.0/resolve/main/Anything-V3.0.vae.pt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/Anything-V3.0-pruned.vae.pt")
-    
-    #os.system(f"wget -q https://huggingface.co/stabilityai/stable-diffusion-2/resolve/main/768-v-ema.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/768-v-ema.ckpt")
-    #os.system(f"wget -q https://raw.githubusercontent.com/Stability-AI/stablediffusion/main/configs/stable-diffusion/v2-inference-v.yaml -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/768-v-ema.yaml")
-    
-    os.system(f"wget -q https://huggingface.co/stabilityai/stable-diffusion-2-1/resolve/main/v2-1_768-ema-pruned.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/v2-1_768-ema-pruned.ckpt")
-    os.system(f"wget -q https://raw.githubusercontent.com/Stability-AI/stablediffusion/main/configs/stable-diffusion/v2-inference-v.yaml -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/v2-1_768-ema-pruned.yaml")
-
-    os.system(f"python launch.py --force-enable-xformers --ui-config-file /home/user/app/ui-config.json --ui-settings-file /home/user/app/config.json --disable-console-progressbars --enable-console-prompts --cors-allow-origins huggingface.co,hf.space --no-progressbar-hiding --api --skip-torch-cuda-test")
-    
\ No newline at end of file
diff --git a/spaces/Nyari/Super-Resolution-Anime-Diffusion/Waifu2x/utils/image_quality.py b/spaces/Nyari/Super-Resolution-Anime-Diffusion/Waifu2x/utils/image_quality.py
deleted file mode 100644
index c7bf0e51cac541f1872e1bc82ff359c3b2b2fdaa..0000000000000000000000000000000000000000
--- a/spaces/Nyari/Super-Resolution-Anime-Diffusion/Waifu2x/utils/image_quality.py
+++ /dev/null
@@ -1,191 +0,0 @@
-# Pytorch Multi-Scale Structural Similarity Index (SSIM)
-# This code is written by jorge-pessoa (https://github.com/jorge-pessoa/pytorch-msssim)
-# MIT licence
-import math
-from math import exp
-
-import torch
-import torch.nn.functional as F
-from torch.autograd import Variable
-
-
-# +++++++++++++++++++++++++++++++++++++
-#           SSIM
-# -------------------------------------
-
-
-def gaussian(window_size, sigma):
-    gauss = torch.Tensor(
-        [
-            exp(-((x - window_size // 2) ** 2) / float(2 * sigma**2))
-            for x in range(window_size)
-        ]
-    )
-    return gauss / gauss.sum()
-
-
-def create_window(window_size, channel):
-    _1D_window = gaussian(window_size, 1.5).unsqueeze(1)
-    _2D_window = _1D_window.mm(_1D_window.t()).float().unsqueeze(0).unsqueeze(0)
-    window = Variable(
-        _2D_window.expand(channel, 1, window_size, window_size).contiguous()
-    )
-    return window
-
-
-def _ssim(img1, img2, window, window_size, channel, size_average=True, full=False):
-    padd = 0
-
-    mu1 = F.conv2d(img1, window, padding=padd, groups=channel)
-    mu2 = F.conv2d(img2, window, padding=padd, groups=channel)
-
-    mu1_sq = mu1.pow(2)
-    mu2_sq = mu2.pow(2)
-    mu1_mu2 = mu1 * mu2
-
-    sigma1_sq = F.conv2d(img1 * img1, window, padding=padd, groups=channel) - mu1_sq
-    sigma2_sq = F.conv2d(img2 * img2, window, padding=padd, groups=channel) - mu2_sq
-    sigma12 = F.conv2d(img1 * img2, window, padding=padd, groups=channel) - mu1_mu2
-
-    C1 = 0.01**2
-    C2 = 0.03**2
-
-    ssim_map = ((2 * mu1_mu2 + C1) * (2 * sigma12 + C2)) / (
-        (mu1_sq + mu2_sq + C1) * (sigma1_sq + sigma2_sq + C2)
-    )
-
-    v1 = 2.0 * sigma12 + C2
-    v2 = sigma1_sq + sigma2_sq + C2
-    cs = torch.mean(v1 / v2)
-
-    if size_average:
-        ret = ssim_map.mean()
-    else:
-        ret = ssim_map.mean(1).mean(1).mean(1)
-
-    if full:
-        return ret, cs
-    return ret
-
-
-class SSIM(torch.nn.Module):
-    def __init__(self, window_size=11, size_average=True):
-        super(SSIM, self).__init__()
-        self.window_size = window_size
-        self.size_average = size_average
-        self.channel = 1
-        self.window = create_window(window_size, self.channel)
-
-    def forward(self, img1, img2):
-        (_, channel, _, _) = img1.size()
-
-        if channel == self.channel and self.window.data.type() == img1.data.type():
-            window = self.window
-        else:
-            window = create_window(self.window_size, channel)
-
-            if img1.is_cuda:
-                window = window.cuda(img1.get_device())
-            window = window.type_as(img1)
-
-            self.window = window
-            self.channel = channel
-
-        return _ssim(img1, img2, window, self.window_size, channel, self.size_average)
-
-
-def ssim(img1, img2, window_size=11, size_average=True, full=False):
-    (_, channel, height, width) = img1.size()
-
-    real_size = min(window_size, height, width)
-    window = create_window(real_size, channel)
-
-    if img1.is_cuda:
-        window = window.cuda(img1.get_device())
-    window = window.type_as(img1)
-
-    return _ssim(img1, img2, window, real_size, channel, size_average, full=full)
-
-
-def msssim(img1, img2, window_size=11, size_average=True):
-    # TODO: fix NAN results
-    if img1.size() != img2.size():
-        raise RuntimeError(
-            "Input images must have the same shape (%s vs. %s)."
-            % (img1.size(), img2.size())
-        )
-    if len(img1.size()) != 4:
-        raise RuntimeError(
-            "Input images must have four dimensions, not %d" % len(img1.size())
-        )
-
-    weights = torch.tensor([0.0448, 0.2856, 0.3001, 0.2363, 0.1333], dtype=img1.dtype)
-    if img1.is_cuda:
-        weights = weights.cuda(img1.get_device())
-
-    levels = weights.size()[0]
-    mssim = []
-    mcs = []
-    for _ in range(levels):
-        sim, cs = ssim(
-            img1, img2, window_size=window_size, size_average=size_average, full=True
-        )
-        mssim.append(sim)
-        mcs.append(cs)
-
-        img1 = F.avg_pool2d(img1, (2, 2))
-        img2 = F.avg_pool2d(img2, (2, 2))
-
-    mssim = torch.stack(mssim)
-    mcs = torch.stack(mcs)
-    return torch.prod(mcs[0 : levels - 1] ** weights[0 : levels - 1]) * (
-        mssim[levels - 1] ** weights[levels - 1]
-    )
-
-
-class MSSSIM(torch.nn.Module):
-    def __init__(self, window_size=11, size_average=True, channel=3):
-        super(MSSSIM, self).__init__()
-        self.window_size = window_size
-        self.size_average = size_average
-        self.channel = channel
-
-    def forward(self, img1, img2):
-        # TODO: store window between calls if possible
-        return msssim(
-            img1, img2, window_size=self.window_size, size_average=self.size_average
-        )
-
-
-def calc_psnr(sr, hr, scale=0, benchmark=False):
-    # adapt from EDSR: https://github.com/thstkdgus35/EDSR-PyTorch
-    diff = (sr - hr).data
-    if benchmark:
-        shave = scale
-        if diff.size(1) > 1:
-            convert = diff.new(1, 3, 1, 1)
-            convert[0, 0, 0, 0] = 65.738
-            convert[0, 1, 0, 0] = 129.057
-            convert[0, 2, 0, 0] = 25.064
-            diff.mul_(convert).div_(256)
-            diff = diff.sum(dim=1, keepdim=True)
-    else:
-        shave = scale + 6
-
-    valid = diff[:, :, shave:-shave, shave:-shave]
-    mse = valid.pow(2).mean()
-
-    return -10 * math.log10(mse)
-
-
-# +++++++++++++++++++++++++++++++++++++
-#           PSNR
-# -------------------------------------
-from torch import nn
-
-
-def psnr(predict, target):
-    with torch.no_grad():
-        criteria = nn.MSELoss()
-        mse = criteria(predict, target)
-        return -10 * torch.log10(mse)
diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/scaling_nmt/README.md b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/scaling_nmt/README.md
deleted file mode 100644
index 0cc3360c3bbd58fe35a51591db8f081fc8576877..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/scaling_nmt/README.md
+++ /dev/null
@@ -1,114 +0,0 @@
-# Scaling Neural Machine Translation (Ott et al., 2018)
-
-This page includes instructions for reproducing results from the paper [Scaling Neural Machine Translation (Ott et al., 2018)](https://arxiv.org/abs/1806.00187).
-
-## Pre-trained models
-
-Model | Description | Dataset | Download
----|---|---|---
-`transformer.wmt14.en-fr` | Transformer <br> ([Ott et al., 2018](https://arxiv.org/abs/1806.00187)) | [WMT14 English-French](http://statmt.org/wmt14/translation-task.html#Download) | model: <br> [download (.tar.bz2)](https://dl.fbaipublicfiles.com/fairseq/models/wmt14.en-fr.joined-dict.transformer.tar.bz2) <br> newstest2014: <br> [download (.tar.bz2)](https://dl.fbaipublicfiles.com/fairseq/data/wmt14.en-fr.joined-dict.newstest2014.tar.bz2)
-`transformer.wmt16.en-de` | Transformer <br> ([Ott et al., 2018](https://arxiv.org/abs/1806.00187)) | [WMT16 English-German](https://drive.google.com/uc?export=download&id=0B_bZck-ksdkpM25jRUN2X2UxMm8) | model: <br> [download (.tar.bz2)](https://dl.fbaipublicfiles.com/fairseq/models/wmt16.en-de.joined-dict.transformer.tar.bz2) <br> newstest2014: <br> [download (.tar.bz2)](https://dl.fbaipublicfiles.com/fairseq/data/wmt16.en-de.joined-dict.newstest2014.tar.bz2)
-
-## Training a new model on WMT'16 En-De
-
-First download the [preprocessed WMT'16 En-De data provided by Google](https://drive.google.com/uc?export=download&id=0B_bZck-ksdkpM25jRUN2X2UxMm8).
-
-Then:
-
-##### 1. Extract the WMT'16 En-De data
-```bash
-TEXT=wmt16_en_de_bpe32k
-mkdir -p $TEXT
-tar -xzvf wmt16_en_de.tar.gz -C $TEXT
-```
-
-##### 2. Preprocess the dataset with a joined dictionary
-```bash
-fairseq-preprocess \
-    --source-lang en --target-lang de \
-    --trainpref $TEXT/train.tok.clean.bpe.32000 \
-    --validpref $TEXT/newstest2013.tok.bpe.32000 \
-    --testpref $TEXT/newstest2014.tok.bpe.32000 \
-    --destdir data-bin/wmt16_en_de_bpe32k \
-    --nwordssrc 32768 --nwordstgt 32768 \
-    --joined-dictionary \
-    --workers 20
-```
-
-##### 3. Train a model
-```bash
-fairseq-train \
-    data-bin/wmt16_en_de_bpe32k \
-    --arch transformer_vaswani_wmt_en_de_big --share-all-embeddings \
-    --optimizer adam --adam-betas '(0.9, 0.98)' --clip-norm 0.0 \
-    --lr 0.0005 --lr-scheduler inverse_sqrt --warmup-updates 4000 --warmup-init-lr 1e-07 \
-    --dropout 0.3 --weight-decay 0.0 \
-    --criterion label_smoothed_cross_entropy --label-smoothing 0.1 \
-    --max-tokens 3584 \
-    --fp16
-```
-
-Note that the `--fp16` flag requires you have CUDA 9.1 or greater and a Volta GPU or newer.
-
-***IMPORTANT:*** You will get better performance by training with big batches and
-increasing the learning rate. If you want to train the above model with big batches
-(assuming your machine has 8 GPUs):
-- add `--update-freq 16` to simulate training on 8x16=128 GPUs
-- increase the learning rate; 0.001 works well for big batches
-
-##### 4. Evaluate
-
-Now we can evaluate our trained model.
-
-Note that the original [Attention Is All You Need](https://arxiv.org/abs/1706.03762)
-paper used a couple tricks to achieve better BLEU scores. We use these same tricks in
-the Scaling NMT paper, so it's important to apply them when reproducing our results.
-
-First, use the [average_checkpoints.py](/scripts/average_checkpoints.py) script to
-average the last few checkpoints. Averaging the last 5-10 checkpoints is usually
-good, but you may need to adjust this depending on how long you've trained:
-```bash
-python scripts/average_checkpoints \
-    --inputs /path/to/checkpoints \
-    --num-epoch-checkpoints 10 \
-    --output checkpoint.avg10.pt
-```
-
-Next, generate translations using a beam width of 4 and length penalty of 0.6:
-```bash
-fairseq-generate \
-    data-bin/wmt16_en_de_bpe32k \
-    --path checkpoint.avg10.pt \
-    --beam 4 --lenpen 0.6 --remove-bpe > gen.out
-```
-
-Finally, we apply the ["compound splitting" script](/scripts/compound_split_bleu.sh) to
-add spaces around dashes. For example "Café-Liebhaber" would become three tokens:
-"Café - Liebhaber". This typically results in larger BLEU scores, but it is not
-appropriate to compare these inflated scores to work which does not include this trick.
-This trick was used in the [original AIAYN code](https://github.com/tensorflow/tensor2tensor/blob/fc9335c0203685cbbfe2b30c92db4352d8f60779/tensor2tensor/utils/get_ende_bleu.sh),
-so we used it in the Scaling NMT paper as well. That said, it's strongly advised to
-report [sacrebleu](https://github.com/mjpost/sacrebleu) scores instead.
-
-To compute "compound split" tokenized BLEU (not recommended!):
-```bash
-bash scripts/compound_split_bleu.sh gen.out
-# BLEU4 = 29.29, 60.3/35.0/22.8/15.3 (BP=1.000, ratio=1.004, syslen=64763, reflen=64496)
-```
-
-To compute detokenized BLEU with sacrebleu (preferred):
-```bash
-bash scripts/sacrebleu.sh wmt14/full en de gen.out
-# BLEU+case.mixed+lang.en-de+numrefs.1+smooth.exp+test.wmt14/full+tok.13a+version.1.4.3 = 28.6 59.3/34.3/22.1/14.9 (BP = 1.000 ratio = 1.016 hyp_len = 63666 ref_len = 62688)
-```
-
-## Citation
-
-```bibtex
-@inproceedings{ott2018scaling,
-  title = {Scaling Neural Machine Translation},
-  author = {Ott, Myle and Edunov, Sergey and Grangier, David and Auli, Michael},
-  booktitle = {Proceedings of the Third Conference on Machine Translation (WMT)},
-  year = 2018,
-}
-```
diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/wav2vec/unsupervised/scripts/prepare_text.sh b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/wav2vec/unsupervised/scripts/prepare_text.sh
deleted file mode 100644
index 1caf13cb6a2a0bd84e5322c92124b2fa37368f9a..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/wav2vec/unsupervised/scripts/prepare_text.sh
+++ /dev/null
@@ -1,82 +0,0 @@
-#!/usr/bin/env zsh
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-lg=$1
-text_path=$2
-target_dir=$3
-min_phones=$4
-phonemizer=$5
-lid_path=$6
-
-if [ -z "$lid_path" ]; then
-  lid_path="lid.187.bin"
-fi
-
-ph_lg=${lg:l}
-if test "$lg" = 'fr'; then
-  ph_lg='fr-fr'
-elif test "$lg" = 'en'; then
-  ph_lg='en-us'
-elif test "$lg" = 'pt'; then
-  ph_lg='pt-br'
-fi
-
-ESPEAK_PATH=''
-if test "$phonemizer" = 'espeak'; then
-  ESPEAK_PATH=$(which espeak)
-elif test "$phonemizer" = 'espeak-ng'; then
-  ESPEAK_PATH=$(which espeak-ng)
-elif test "$phonemizer" = 'G2P'; then
-  ESPEAK_PATH=''
-else
-  echo "Unknown phonemizer $phonemizer. Valid options are espeak, espean-ng and G2P"
-  exit 1
-fi
-
-echo $lg
-echo $ph_lg
-echo $text_path
-echo $target_dir
-echo "min phone seen threshold is $min_phones"
-
-mkdir -p $target_dir
-python $FAIRSEQ_ROOT/examples/wav2vec/unsupervised/scripts/normalize_and_filter_text.py --lang $lg --fasttext-model $lid_path < $text_path | grep -v '\-\-\-' >! $target_dir/lm.upper.lid.txt
-python $FAIRSEQ_ROOT/fairseq_cli/preprocess.py --dataset-impl mmap --trainpref $target_dir/lm.upper.lid.txt --only-source --destdir $target_dir --thresholdsrc 2 --padding-factor 1 --dict-only
-cut -f1 -d' ' $target_dir/dict.txt | grep -v -x '[[:punct:]]*' | grep -Pv '\d\d\d\d\d+' >! $target_dir/words.txt
-
-
-if [ -z "$ESPEAK_PATH" ]; then
-  python $FAIRSEQ_ROOT/examples/wav2vec/unsupervised/scripts/g2p_wrd_to_phn.py --compact < $target_dir/words.txt > $target_dir/phones.txt
-else
-  # echoing 1 into corpus will prevent the mismatch lines between lexicon and phones in case the phonemizer fails
-  one=$(echo "1" | PHONEMIZER_ESPEAK_PATH=$ESPEAK_PATH phonemize -p ' ' -w '' -l $ph_lg --language-switch remove-flags)
-  sed 's/$/ 1/' $target_dir/words.txt | PHONEMIZER_ESPEAK_PATH=$ESPEAK_PATH phonemize -o $target_dir/phones.txt -p ' ' -w '' -l $ph_lg -j 70 --language-switch remove-flags
-  echo "one is ${one}"
-  sed -i "s/${one}$//" $target_dir/phones.txt
-fi
-
-paste $target_dir/words.txt $target_dir/phones.txt >! $target_dir/lexicon.lst
-
-python $FAIRSEQ_ROOT/fairseq_cli/preprocess.py --dataset-impl mmap --trainpref $target_dir/phones.txt --only-source --destdir $target_dir/phones --thresholdsrc $min_phones --padding-factor 1 --dict-only
-
-python $FAIRSEQ_ROOT/examples/wav2vec/unsupervised/scripts/filter_lexicon.py -d $target_dir/phones/dict.txt < $target_dir/lexicon.lst >! $target_dir/lexicon_filtered.lst
-python $FAIRSEQ_ROOT/examples/wav2vec/unsupervised/scripts/phonemize_with_sil.py -s 0.25 --surround --lexicon $target_dir/lexicon_filtered.lst < $target_dir/lm.upper.lid.txt >! $target_dir/phones/lm.phones.filtered.txt
-cp $target_dir/phones/dict.txt $target_dir/phones/dict.phn.txt
-echo "<SIL> 0" >> $target_dir/phones/dict.phn.txt
-python $FAIRSEQ_ROOT/fairseq_cli/preprocess.py --dataset-impl mmap --trainpref $target_dir/phones/lm.phones.filtered.txt --workers 70 --only-source --destdir $target_dir/phones --srcdict $target_dir/phones/dict.phn.txt
-
-$KENLM_ROOT/lmplz -o 4 < $target_dir/lm.upper.lid.txt --discount_fallback --prune 0 0 0 3 >! $target_dir/kenlm.wrd.o40003.arpa
-$KENLM_ROOT/build_binary $target_dir/kenlm.wrd.o40003.arpa $target_dir/kenlm.wrd.o40003.bin
-
-lg=$lg python $FAIRSEQ_ROOT/examples/speech_recognition/kaldi/kaldi_initializer.py kaldi_root=$KALDI_ROOT fst_dir=$target_dir/fst/phn_to_words_sil lm_arpa=$target_dir/kenlm.wrd.o40003.arpa wav2letter_lexicon=$target_dir/lexicon_filtered.lst data_dir=$target_dir/phones in_labels=phn "blank_symbol='<SIL>'"
-lg=$lg python $FAIRSEQ_ROOT/examples/speech_recognition/kaldi/kaldi_initializer.py kaldi_root=$KALDI_ROOT fst_dir=$target_dir/fst/phn_to_words lm_arpa=$target_dir/kenlm.wrd.o40003.arpa wav2letter_lexicon=$target_dir/lexicon_filtered.lst data_dir=$target_dir/phones in_labels=phn
-
-$KENLM_ROOT/lmplz -o 4 < $target_dir/phones/lm.phones.filtered.txt --discount_fallback >! $target_dir/phones/lm.phones.filtered.04.arpa
-$KENLM_ROOT/build_binary $target_dir/phones/lm.phones.filtered.04.arpa $target_dir/phones/lm.phones.filtered.04.bin
-$KENLM_ROOT/lmplz -o 6 < $target_dir/phones/lm.phones.filtered.txt --discount_fallback >! $target_dir/phones/lm.phones.filtered.06.arpa
-$KENLM_ROOT/build_binary $target_dir/phones/lm.phones.filtered.06.arpa $target_dir/phones/lm.phones.filtered.06.bin
-
-lg=$lg python $FAIRSEQ_ROOT/examples/speech_recognition/kaldi/kaldi_initializer.py kaldi_root=$KALDI_ROOT fst_dir=$target_dir/fst/phn_to_phn_sil lm_arpa=$target_dir/phones/lm.phones.filtered.06.arpa data_dir=$target_dir/phones in_labels=phn "blank_symbol='<SIL>'"
diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/data/encoders/__init__.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/data/encoders/__init__.py
deleted file mode 100644
index 7cbe00a10520331709441e5e77991bd2edca8c06..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/data/encoders/__init__.py
+++ /dev/null
@@ -1,29 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-
-import importlib
-import os
-
-from fairseq import registry
-
-
-build_tokenizer, register_tokenizer, TOKENIZER_REGISTRY, _ = registry.setup_registry(
-    "--tokenizer",
-    default=None,
-)
-
-
-build_bpe, register_bpe, BPE_REGISTRY, _ = registry.setup_registry(
-    "--bpe",
-    default=None,
-)
-
-
-# automatically import any Python files in the encoders/ directory
-for file in sorted(os.listdir(os.path.dirname(__file__))):
-    if file.endswith(".py") and not file.startswith("_"):
-        module = file[: file.find(".py")]
-        importlib.import_module("fairseq.data.encoders." + module)
diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/model_parallel/criterions/__init__.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/model_parallel/criterions/__init__.py
deleted file mode 100644
index 5fae7bd4c2cfa7b4f64ad62dd9b9082f59f0e50d..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/model_parallel/criterions/__init__.py
+++ /dev/null
@@ -1,14 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import importlib
-import os
-
-
-# automatically import any Python files in the criterions/ directory
-for file in sorted(os.listdir(os.path.dirname(__file__))):
-    if file.endswith(".py") and not file.startswith("_"):
-        module = file[: file.find(".py")]
-        importlib.import_module("fairseq.model_parallel.criterions." + module)
diff --git a/spaces/OFA-Sys/OFA-Image_Caption/fairseq/examples/wav2vec/unsupervised/kaldi_self_train/st/decode_word_step1.sh b/spaces/OFA-Sys/OFA-Image_Caption/fairseq/examples/wav2vec/unsupervised/kaldi_self_train/st/decode_word_step1.sh
deleted file mode 100644
index c1276bbe4d0e02deb984c7c10d6c0486dce09a5f..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-Image_Caption/fairseq/examples/wav2vec/unsupervised/kaldi_self_train/st/decode_word_step1.sh
+++ /dev/null
@@ -1,46 +0,0 @@
-#!/bin/bash
-
-# prepare word WFSTs, reference data, and decode
-
-set -eu
-
-w2v_dir=  # same as in train.sh
-out_dir=  # same as in train.sh
-lexicon=  # word to phone mapping
-wrd_arpa_lm=  # word LM
-wrd_arpa_lm_bin=  # word LM for KenLM, used in unsupervised selection
-
-dec_exp=  # what HMM stage to decode (e.g., tri3b)
-dec_script=  # what decoding script to use (e.g., steps/decode_fmllr.sh)
-phn_label=phnc
-wrd_label=wrd
-dec_suffix=word
-dec_splits="train valid"
-valid_split="valid"
-
-data_dir=$out_dir/data
-wrd_data_dir=$out_dir/data_word
-
-lexicon_clean=$(mktemp)
-cat $lexicon | sort | uniq > $lexicon_clean
-local/prepare_lang_word.sh $w2v_dir/dict.${phn_label}.txt $data_dir $lexicon_clean && rm $lexicon_clean
-local/prepare_lm.sh --langdir $data_dir/lang_word --lmdir $data_dir/lang_test_word $wrd_arpa_lm $data_dir
-
-for x in $dec_splits; do
-  x_gt=${x}_gt
-  mkdir -p $wrd_data_dir/$x_gt
-  cp $data_dir/$x_gt/{feats.scp,cmvn.scp,utt2spk,spk2utt} $wrd_data_dir/$x_gt/
-  python local/copy_aligned_text.py < $w2v_dir/$x.$wrd_label > $wrd_data_dir/$x_gt/text
-done
-
-local/decode.sh --nj 40 --graph_name graph${dec_suffix} --decode_suffix $dec_suffix \
-  --val_sets "$dec_splits" --decode_script $dec_script \
-  $out_dir/exp/$dec_exp $data_dir $data_dir/lang_test_word
-
-local/unsup_select_decode_word.sh \
-  --split $valid_split --kenlm_path $wrd_arpa_lm_bin \
-  --ref_txt $wrd_data_dir/${valid_split}_gt/text \
-  --psd_txt $data_dir/${valid_split}/text \
-  --dec_name decode${dec_suffix} --graph_name graph${dec_suffix} \
-  --phonemize_lexicon $data_dir/local/dict_word/lexicon.txt \
-  $out_dir/exp
diff --git a/spaces/OFA-Sys/OFA-Image_Caption/fairseq/fairseq/data/encoders/byte_bpe.py b/spaces/OFA-Sys/OFA-Image_Caption/fairseq/fairseq/data/encoders/byte_bpe.py
deleted file mode 100644
index 31e3a0627827f19ca7f0b58da45e46d40a80c3bf..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-Image_Caption/fairseq/fairseq/data/encoders/byte_bpe.py
+++ /dev/null
@@ -1,48 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-
-from dataclasses import dataclass, field
-
-from fairseq import file_utils
-from fairseq.data.encoders import register_bpe
-from fairseq.data.encoders.byte_utils import (
-    SPACE,
-    SPACE_ESCAPE,
-    byte_encode,
-    smart_byte_decode,
-)
-from fairseq.dataclass import FairseqDataclass
-
-
-@dataclass
-class ByteBpeConfig(FairseqDataclass):
-    sentencepiece_model_path: str = field(
-        default="???", metadata={"help": "path to sentencepiece model"}
-    )
-
-
-@register_bpe("byte_bpe", dataclass=ByteBpeConfig)
-class ByteBPE(object):
-    def __init__(self, cfg):
-        vocab = file_utils.cached_path(cfg.sentencepiece_model_path)
-        try:
-            import sentencepiece as spm
-
-            self.sp = spm.SentencePieceProcessor()
-            self.sp.Load(vocab)
-        except ImportError:
-            raise ImportError(
-                "Please install sentencepiece with: pip install sentencepiece"
-            )
-
-    def encode(self, x: str) -> str:
-        byte_encoded = byte_encode(x)
-        return SPACE.join(self.sp.EncodeAsPieces(byte_encoded))
-
-    @staticmethod
-    def decode(x: str) -> str:
-        unescaped = x.replace(SPACE, "").replace(SPACE_ESCAPE, SPACE)
-        return smart_byte_decode(unescaped)
diff --git a/spaces/OFA-Sys/OFA-Image_Caption/fairseq/fairseq/modules/layer_norm.py b/spaces/OFA-Sys/OFA-Image_Caption/fairseq/fairseq/modules/layer_norm.py
deleted file mode 100644
index 234609d9e213a650e0032aaa0ca0462a818bfead..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-Image_Caption/fairseq/fairseq/modules/layer_norm.py
+++ /dev/null
@@ -1,50 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-
-
-try:
-    from apex.normalization import FusedLayerNorm as _FusedLayerNorm
-
-    has_fused_layernorm = True
-
-    class FusedLayerNorm(_FusedLayerNorm):
-        @torch.jit.unused
-        def forward(self, x):
-            if not x.is_cuda:
-                return super().forward(x)
-            else:
-                with torch.cuda.device(x.device):
-                    return super().forward(x)
-
-
-except ImportError:
-    has_fused_layernorm = False
-
-
-def LayerNorm(normalized_shape, eps=1e-5, elementwise_affine=True, export=False):
-    if torch.jit.is_scripting():
-        export = True
-    if not export and torch.cuda.is_available() and has_fused_layernorm:
-        return FusedLayerNorm(normalized_shape, eps, elementwise_affine)
-    return torch.nn.LayerNorm(normalized_shape, eps, elementwise_affine)
-
-
-class Fp32LayerNorm(nn.LayerNorm):
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-
-    def forward(self, input):
-        output = F.layer_norm(
-            input.float(),
-            self.normalized_shape,
-            self.weight.float() if self.weight is not None else None,
-            self.bias.float() if self.bias is not None else None,
-            self.eps,
-        )
-        return output.type_as(input)
diff --git a/spaces/OpenDILabCommunity/LLMRiddlesChatGLMCN/llmriddles/llms/mistral.py b/spaces/OpenDILabCommunity/LLMRiddlesChatGLMCN/llmriddles/llms/mistral.py
deleted file mode 100644
index b85e2655660685afe7ebec6aed59a68eccd49e41..0000000000000000000000000000000000000000
--- a/spaces/OpenDILabCommunity/LLMRiddlesChatGLMCN/llmriddles/llms/mistral.py
+++ /dev/null
@@ -1,22 +0,0 @@
-from functools import lru_cache
-
-from .base import register_llm
-from .llm_client import LLMFlaskClient
-
-
-@lru_cache()
-def _get_mistral_7b_instruct_server(host: str, port: int):
-    from .llm_server import LLMInstance, create_app
-    core = LLMInstance('Mistral-7B-Instruct-v0.1')
-    app = create_app(core)
-    app.run(host=host, port=port)
-
-
-def ask_mistral_7b_instruct(message: str, **kwargs):
-    host, port = '0.0.0.0', 8001
-    _get_mistral_7b_instruct_server(host, port)
-    client = LLMFlaskClient(host, port)
-    return client.run(message).strip()
-
-
-register_llm('mistral-7b', ask_mistral_7b_instruct)
diff --git a/spaces/OpenGVLab/InternGPT/iGPT/models/grit_src/third_party/CenterNet2/detectron2/modeling/anchor_generator.py b/spaces/OpenGVLab/InternGPT/iGPT/models/grit_src/third_party/CenterNet2/detectron2/modeling/anchor_generator.py
deleted file mode 100644
index ee4b98819445f95982ca89a72cdd3e27b39b367f..0000000000000000000000000000000000000000
--- a/spaces/OpenGVLab/InternGPT/iGPT/models/grit_src/third_party/CenterNet2/detectron2/modeling/anchor_generator.py
+++ /dev/null
@@ -1,382 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-import collections
-import math
-from typing import List
-import torch
-from torch import nn
-
-from detectron2.config import configurable
-from detectron2.layers import ShapeSpec
-from detectron2.structures import Boxes, RotatedBoxes
-from detectron2.utils.registry import Registry
-
-ANCHOR_GENERATOR_REGISTRY = Registry("ANCHOR_GENERATOR")
-ANCHOR_GENERATOR_REGISTRY.__doc__ = """
-Registry for modules that creates object detection anchors for feature maps.
-
-The registered object will be called with `obj(cfg, input_shape)`.
-"""
-
-
-class BufferList(nn.Module):
-    """
-    Similar to nn.ParameterList, but for buffers
-    """
-
-    def __init__(self, buffers):
-        super().__init__()
-        for i, buffer in enumerate(buffers):
-            # Use non-persistent buffer so the values are not saved in checkpoint
-            self.register_buffer(str(i), buffer, persistent=False)
-
-    def __len__(self):
-        return len(self._buffers)
-
-    def __iter__(self):
-        return iter(self._buffers.values())
-
-
-def _create_grid_offsets(size: List[int], stride: int, offset: float, device: torch.device):
-    grid_height, grid_width = size
-    shifts_x = torch.arange(
-        offset * stride, grid_width * stride, step=stride, dtype=torch.float32, device=device
-    )
-    shifts_y = torch.arange(
-        offset * stride, grid_height * stride, step=stride, dtype=torch.float32, device=device
-    )
-
-    shift_y, shift_x = torch.meshgrid(shifts_y, shifts_x)
-    shift_x = shift_x.reshape(-1)
-    shift_y = shift_y.reshape(-1)
-    return shift_x, shift_y
-
-
-def _broadcast_params(params, num_features, name):
-    """
-    If one size (or aspect ratio) is specified and there are multiple feature
-    maps, we "broadcast" anchors of that single size (or aspect ratio)
-    over all feature maps.
-
-    If params is list[float], or list[list[float]] with len(params) == 1, repeat
-    it num_features time.
-
-    Returns:
-        list[list[float]]: param for each feature
-    """
-    assert isinstance(
-        params, collections.abc.Sequence
-    ), f"{name} in anchor generator has to be a list! Got {params}."
-    assert len(params), f"{name} in anchor generator cannot be empty!"
-    if not isinstance(params[0], collections.abc.Sequence):  # params is list[float]
-        return [params] * num_features
-    if len(params) == 1:
-        return list(params) * num_features
-    assert len(params) == num_features, (
-        f"Got {name} of length {len(params)} in anchor generator, "
-        f"but the number of input features is {num_features}!"
-    )
-    return params
-
-
-@ANCHOR_GENERATOR_REGISTRY.register()
-class DefaultAnchorGenerator(nn.Module):
-    """
-    Compute anchors in the standard ways described in
-    "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks".
-    """
-
-    box_dim: torch.jit.Final[int] = 4
-    """
-    the dimension of each anchor box.
-    """
-
-    @configurable
-    def __init__(self, *, sizes, aspect_ratios, strides, offset=0.5):
-        """
-        This interface is experimental.
-
-        Args:
-            sizes (list[list[float]] or list[float]):
-                If ``sizes`` is list[list[float]], ``sizes[i]`` is the list of anchor sizes
-                (i.e. sqrt of anchor area) to use for the i-th feature map.
-                If ``sizes`` is list[float], ``sizes`` is used for all feature maps.
-                Anchor sizes are given in absolute lengths in units of
-                the input image; they do not dynamically scale if the input image size changes.
-            aspect_ratios (list[list[float]] or list[float]): list of aspect ratios
-                (i.e. height / width) to use for anchors. Same "broadcast" rule for `sizes` applies.
-            strides (list[int]): stride of each input feature.
-            offset (float): Relative offset between the center of the first anchor and the top-left
-                corner of the image. Value has to be in [0, 1).
-                Recommend to use 0.5, which means half stride.
-        """
-        super().__init__()
-
-        self.strides = strides
-        self.num_features = len(self.strides)
-        sizes = _broadcast_params(sizes, self.num_features, "sizes")
-        aspect_ratios = _broadcast_params(aspect_ratios, self.num_features, "aspect_ratios")
-        self.cell_anchors = self._calculate_anchors(sizes, aspect_ratios)
-
-        self.offset = offset
-        assert 0.0 <= self.offset < 1.0, self.offset
-
-    @classmethod
-    def from_config(cls, cfg, input_shape: List[ShapeSpec]):
-        return {
-            "sizes": cfg.MODEL.ANCHOR_GENERATOR.SIZES,
-            "aspect_ratios": cfg.MODEL.ANCHOR_GENERATOR.ASPECT_RATIOS,
-            "strides": [x.stride for x in input_shape],
-            "offset": cfg.MODEL.ANCHOR_GENERATOR.OFFSET,
-        }
-
-    def _calculate_anchors(self, sizes, aspect_ratios):
-        cell_anchors = [
-            self.generate_cell_anchors(s, a).float() for s, a in zip(sizes, aspect_ratios)
-        ]
-        return BufferList(cell_anchors)
-
-    @property
-    @torch.jit.unused
-    def num_cell_anchors(self):
-        """
-        Alias of `num_anchors`.
-        """
-        return self.num_anchors
-
-    @property
-    @torch.jit.unused
-    def num_anchors(self):
-        """
-        Returns:
-            list[int]: Each int is the number of anchors at every pixel
-                location, on that feature map.
-                For example, if at every pixel we use anchors of 3 aspect
-                ratios and 5 sizes, the number of anchors is 15.
-                (See also ANCHOR_GENERATOR.SIZES and ANCHOR_GENERATOR.ASPECT_RATIOS in config)
-
-                In standard RPN models, `num_anchors` on every feature map is the same.
-        """
-        return [len(cell_anchors) for cell_anchors in self.cell_anchors]
-
-    def _grid_anchors(self, grid_sizes: List[List[int]]):
-        """
-        Returns:
-            list[Tensor]: #featuremap tensors, each is (#locations x #cell_anchors) x 4
-        """
-        anchors = []
-        # buffers() not supported by torchscript. use named_buffers() instead
-        buffers: List[torch.Tensor] = [x[1] for x in self.cell_anchors.named_buffers()]
-        for size, stride, base_anchors in zip(grid_sizes, self.strides, buffers):
-            shift_x, shift_y = _create_grid_offsets(size, stride, self.offset, base_anchors.device)
-            shifts = torch.stack((shift_x, shift_y, shift_x, shift_y), dim=1)
-
-            anchors.append((shifts.view(-1, 1, 4) + base_anchors.view(1, -1, 4)).reshape(-1, 4))
-
-        return anchors
-
-    def generate_cell_anchors(self, sizes=(32, 64, 128, 256, 512), aspect_ratios=(0.5, 1, 2)):
-        """
-        Generate a tensor storing canonical anchor boxes, which are all anchor
-        boxes of different sizes and aspect_ratios centered at (0, 0).
-        We can later build the set of anchors for a full feature map by
-        shifting and tiling these tensors (see `meth:_grid_anchors`).
-
-        Args:
-            sizes (tuple[float]):
-            aspect_ratios (tuple[float]]):
-
-        Returns:
-            Tensor of shape (len(sizes) * len(aspect_ratios), 4) storing anchor boxes
-                in XYXY format.
-        """
-
-        # This is different from the anchor generator defined in the original Faster R-CNN
-        # code or Detectron. They yield the same AP, however the old version defines cell
-        # anchors in a less natural way with a shift relative to the feature grid and
-        # quantization that results in slightly different sizes for different aspect ratios.
-        # See also https://github.com/facebookresearch/Detectron/issues/227
-
-        anchors = []
-        for size in sizes:
-            area = size ** 2.0
-            for aspect_ratio in aspect_ratios:
-                # s * s = w * h
-                # a = h / w
-                # ... some algebra ...
-                # w = sqrt(s * s / a)
-                # h = a * w
-                w = math.sqrt(area / aspect_ratio)
-                h = aspect_ratio * w
-                x0, y0, x1, y1 = -w / 2.0, -h / 2.0, w / 2.0, h / 2.0
-                anchors.append([x0, y0, x1, y1])
-        return torch.tensor(anchors)
-
-    def forward(self, features: List[torch.Tensor]):
-        """
-        Args:
-            features (list[Tensor]): list of backbone feature maps on which to generate anchors.
-
-        Returns:
-            list[Boxes]: a list of Boxes containing all the anchors for each feature map
-                (i.e. the cell anchors repeated over all locations in the feature map).
-                The number of anchors of each feature map is Hi x Wi x num_cell_anchors,
-                where Hi, Wi are resolution of the feature map divided by anchor stride.
-        """
-        grid_sizes = [feature_map.shape[-2:] for feature_map in features]
-        anchors_over_all_feature_maps = self._grid_anchors(grid_sizes)
-        return [Boxes(x) for x in anchors_over_all_feature_maps]
-
-
-@ANCHOR_GENERATOR_REGISTRY.register()
-class RotatedAnchorGenerator(nn.Module):
-    """
-    Compute rotated anchors used by Rotated RPN (RRPN), described in
-    "Arbitrary-Oriented Scene Text Detection via Rotation Proposals".
-    """
-
-    box_dim: int = 5
-    """
-    the dimension of each anchor box.
-    """
-
-    @configurable
-    def __init__(self, *, sizes, aspect_ratios, strides, angles, offset=0.5):
-        """
-        This interface is experimental.
-
-        Args:
-            sizes (list[list[float]] or list[float]):
-                If sizes is list[list[float]], sizes[i] is the list of anchor sizes
-                (i.e. sqrt of anchor area) to use for the i-th feature map.
-                If sizes is list[float], the sizes are used for all feature maps.
-                Anchor sizes are given in absolute lengths in units of
-                the input image; they do not dynamically scale if the input image size changes.
-            aspect_ratios (list[list[float]] or list[float]): list of aspect ratios
-                (i.e. height / width) to use for anchors. Same "broadcast" rule for `sizes` applies.
-            strides (list[int]): stride of each input feature.
-            angles (list[list[float]] or list[float]): list of angles (in degrees CCW)
-                to use for anchors. Same "broadcast" rule for `sizes` applies.
-            offset (float): Relative offset between the center of the first anchor and the top-left
-                corner of the image. Value has to be in [0, 1).
-                Recommend to use 0.5, which means half stride.
-        """
-        super().__init__()
-
-        self.strides = strides
-        self.num_features = len(self.strides)
-        sizes = _broadcast_params(sizes, self.num_features, "sizes")
-        aspect_ratios = _broadcast_params(aspect_ratios, self.num_features, "aspect_ratios")
-        angles = _broadcast_params(angles, self.num_features, "angles")
-        self.cell_anchors = self._calculate_anchors(sizes, aspect_ratios, angles)
-
-        self.offset = offset
-        assert 0.0 <= self.offset < 1.0, self.offset
-
-    @classmethod
-    def from_config(cls, cfg, input_shape: List[ShapeSpec]):
-        return {
-            "sizes": cfg.MODEL.ANCHOR_GENERATOR.SIZES,
-            "aspect_ratios": cfg.MODEL.ANCHOR_GENERATOR.ASPECT_RATIOS,
-            "strides": [x.stride for x in input_shape],
-            "offset": cfg.MODEL.ANCHOR_GENERATOR.OFFSET,
-            "angles": cfg.MODEL.ANCHOR_GENERATOR.ANGLES,
-        }
-
-    def _calculate_anchors(self, sizes, aspect_ratios, angles):
-        cell_anchors = [
-            self.generate_cell_anchors(size, aspect_ratio, angle).float()
-            for size, aspect_ratio, angle in zip(sizes, aspect_ratios, angles)
-        ]
-        return BufferList(cell_anchors)
-
-    @property
-    def num_cell_anchors(self):
-        """
-        Alias of `num_anchors`.
-        """
-        return self.num_anchors
-
-    @property
-    def num_anchors(self):
-        """
-        Returns:
-            list[int]: Each int is the number of anchors at every pixel
-                location, on that feature map.
-                For example, if at every pixel we use anchors of 3 aspect
-                ratios, 2 sizes and 5 angles, the number of anchors is 30.
-                (See also ANCHOR_GENERATOR.SIZES, ANCHOR_GENERATOR.ASPECT_RATIOS
-                and ANCHOR_GENERATOR.ANGLES in config)
-
-                In standard RRPN models, `num_anchors` on every feature map is the same.
-        """
-        return [len(cell_anchors) for cell_anchors in self.cell_anchors]
-
-    def _grid_anchors(self, grid_sizes):
-        anchors = []
-        for size, stride, base_anchors in zip(grid_sizes, self.strides, self.cell_anchors):
-            shift_x, shift_y = _create_grid_offsets(size, stride, self.offset, base_anchors.device)
-            zeros = torch.zeros_like(shift_x)
-            shifts = torch.stack((shift_x, shift_y, zeros, zeros, zeros), dim=1)
-
-            anchors.append((shifts.view(-1, 1, 5) + base_anchors.view(1, -1, 5)).reshape(-1, 5))
-
-        return anchors
-
-    def generate_cell_anchors(
-        self,
-        sizes=(32, 64, 128, 256, 512),
-        aspect_ratios=(0.5, 1, 2),
-        angles=(-90, -60, -30, 0, 30, 60, 90),
-    ):
-        """
-        Generate a tensor storing canonical anchor boxes, which are all anchor
-        boxes of different sizes, aspect_ratios, angles centered at (0, 0).
-        We can later build the set of anchors for a full feature map by
-        shifting and tiling these tensors (see `meth:_grid_anchors`).
-
-        Args:
-            sizes (tuple[float]):
-            aspect_ratios (tuple[float]]):
-            angles (tuple[float]]):
-
-        Returns:
-            Tensor of shape (len(sizes) * len(aspect_ratios) * len(angles), 5)
-                storing anchor boxes in (x_ctr, y_ctr, w, h, angle) format.
-        """
-        anchors = []
-        for size in sizes:
-            area = size ** 2.0
-            for aspect_ratio in aspect_ratios:
-                # s * s = w * h
-                # a = h / w
-                # ... some algebra ...
-                # w = sqrt(s * s / a)
-                # h = a * w
-                w = math.sqrt(area / aspect_ratio)
-                h = aspect_ratio * w
-                anchors.extend([0, 0, w, h, a] for a in angles)
-
-        return torch.tensor(anchors)
-
-    def forward(self, features):
-        """
-        Args:
-            features (list[Tensor]): list of backbone feature maps on which to generate anchors.
-
-        Returns:
-            list[RotatedBoxes]: a list of Boxes containing all the anchors for each feature map
-                (i.e. the cell anchors repeated over all locations in the feature map).
-                The number of anchors of each feature map is Hi x Wi x num_cell_anchors,
-                where Hi, Wi are resolution of the feature map divided by anchor stride.
-        """
-        grid_sizes = [feature_map.shape[-2:] for feature_map in features]
-        anchors_over_all_feature_maps = self._grid_anchors(grid_sizes)
-        return [RotatedBoxes(x) for x in anchors_over_all_feature_maps]
-
-
-def build_anchor_generator(cfg, input_shape):
-    """
-    Built an anchor generator from `cfg.MODEL.ANCHOR_GENERATOR.NAME`.
-    """
-    anchor_generator = cfg.MODEL.ANCHOR_GENERATOR.NAME
-    return ANCHOR_GENERATOR_REGISTRY.get(anchor_generator)(cfg, input_shape)
diff --git a/spaces/OpenGVLab/InternGPT/iGPT/models/grit_src/third_party/CenterNet2/detectron2/modeling/proposal_generator/build.py b/spaces/OpenGVLab/InternGPT/iGPT/models/grit_src/third_party/CenterNet2/detectron2/modeling/proposal_generator/build.py
deleted file mode 100644
index 34eb12d00d94ff905b796e75e2c4c5845257c8e9..0000000000000000000000000000000000000000
--- a/spaces/OpenGVLab/InternGPT/iGPT/models/grit_src/third_party/CenterNet2/detectron2/modeling/proposal_generator/build.py
+++ /dev/null
@@ -1,24 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-from detectron2.utils.registry import Registry
-
-PROPOSAL_GENERATOR_REGISTRY = Registry("PROPOSAL_GENERATOR")
-PROPOSAL_GENERATOR_REGISTRY.__doc__ = """
-Registry for proposal generator, which produces object proposals from feature maps.
-
-The registered object will be called with `obj(cfg, input_shape)`.
-The call should return a `nn.Module` object.
-"""
-
-from . import rpn, rrpn  # noqa F401 isort:skip
-
-
-def build_proposal_generator(cfg, input_shape):
-    """
-    Build a proposal generator from `cfg.MODEL.PROPOSAL_GENERATOR.NAME`.
-    The name can be "PrecomputedProposals" to use no proposal generator.
-    """
-    name = cfg.MODEL.PROPOSAL_GENERATOR.NAME
-    if name == "PrecomputedProposals":
-        return None
-
-    return PROPOSAL_GENERATOR_REGISTRY.get(name)(cfg, input_shape)
diff --git a/spaces/PaSathees/FoodVision_Mini/app.py b/spaces/PaSathees/FoodVision_Mini/app.py
deleted file mode 100644
index 1a4f2f1b41429c8c88d9a5aa1ad3241def7f566a..0000000000000000000000000000000000000000
--- a/spaces/PaSathees/FoodVision_Mini/app.py
+++ /dev/null
@@ -1,71 +0,0 @@
-### 1. Imports and class names setup ### 
-import gradio as gr
-import os
-import torch
-
-from model import create_effnetb2_model
-from timeit import default_timer as timer
-from typing import Tuple, Dict
-
-# Setup class names
-class_names = ["pizza", "steak", "sushi"]
-
-### 2. Model and transforms preparation ###
-# Create EffNetB2 model
-effnetb2, effnetb2_transforms = create_effnetb2_model(
-    num_classes=len(class_names)
-)
-
-# Load saved weights
-effnetb2.load_state_dict(
-    torch.load(
-        f="pretrained_effnetb2_feature_extractor_pizza_steak_sushi_20_percent.pth",
-        map_location=torch.device("cpu"),
-    )
-)
-
-### 3. Predict function ###
-def predict(img) -> Tuple[Dict, float]:
-    """
-    Transforms and performs a prediction on img and returns prediction and time taken.
-    """
-    start_time = timer()
-    
-    # Transform the target image and add a batch dimension
-    img = effnetb2_transforms(img).unsqueeze(0)
-    
-    # Put model into evaluation mode and turn on inference mode
-    effnetb2.eval()
-    with torch.inference_mode():
-        pred_probs = torch.softmax(effnetb2(img), dim=1)
-    
-    # Create a prediction label and prediction probability dictionary for each prediction class
-    # Required format for Gradio's output parameter
-    pred_labels_and_probs = {class_names[i]: float(pred_probs[0][i]) for i in range(len(class_names))}
-    
-    # Calculate the prediction time
-    pred_time = round(timer() - start_time, 5)
-    
-    return pred_labels_and_probs, pred_time
-
-### 4. Gradio app ###
-# Create title, description, & article strings
-title = "FoodVision Mini 🍕🥩🍣"
-description = "An EfficientNetB2 feature extractor Computer Vision model to classify images of food as pizza, steak or sushi."
-article = "Created for my AI/ML portfolio [PaSathees/portfolio](https://github.com/PaSathees/portfolio)."
-
-# Create examples list from "examples/" directory
-example_list = [["examples/" + example] for example in os.listdir("examples")]
-
-# Create the Gradio demo
-demo = gr.Interface(fn=predict,
-                    inputs=gr.Image(type="pil"),
-                    outputs=[gr.Label(num_top_classes=3, label="Predictions"),
-                             gr.Number(label="Prediction time (s)")],
-                    examples=example_list, 
-                    title=title,
-                    description=description,
-                    article=article)
-
-# Launch the demo!
-demo.launch()
diff --git a/spaces/Paulraj916/paulraj916/app.py b/spaces/Paulraj916/paulraj916/app.py
deleted file mode 100644
index 23844aa6d85ae11cdcfa1239fc71e20ccaee4a32..0000000000000000000000000000000000000000
--- a/spaces/Paulraj916/paulraj916/app.py
+++ /dev/null
@@ -1,122 +0,0 @@
-import os
-import streamlit as st
-from scrapJs import ScrapJs
-from scrapCss import ScrapCss
-from scrapTs import ScrapTs
-from scrapOtherFiles import ScrapOtherFiles
-from scrapFonts import ScrapFonts
-from scrapVid import ScrapVideos
-from scrapAudio import ScrapAudio
-from scrapIcon import ScrapIcon
-from addVideo import AddVideo
-from scrapImg import ScrapImages
-from addImg import AddImages
-from scrapHtml import ScrapHtml
-from scrapScss import ScrapScss
-from newScrapJs import NewScrapJs
-from newScrapCss import NewScrapCss
-import shutil
-from zipfile import ZipFile
-from io import BytesIO
-
-def main():
-    st.title("Web Page Scraper")
-
-    link = st.text_input("Enter the URL of the website you want to scrape:")
-    if not link:
-        st.stop()
-
-    output = "output"
-    
-    if st.button("Start Scraping"):
-        st.text("Scraping in progress...")
-        st.spinner()
-        
-        # Scrape JS
-        scraper_js = ScrapJs(link)
-        scraper_js.scrap_js()
-
-        # Scrape CSS
-        scraper_css = ScrapCss(link)
-        scraper_css.scrap_css()
-
-        # Scrape HTML Files
-        scraper_html = ScrapHtml(link)
-        scraper_html.scrape_html_files()
-
-        # Scrape SCSS
-        scraper_scss = ScrapScss(link)
-        scraper_scss.scrap_scss()
-
-        # Scrape newJS ( different format )
-        scraper_new_js = NewScrapJs(link)
-        scraper_new_js.scrap_js()
-
-        # Scrape newCSS ( different format )
-        scraper_new_css = NewScrapCss(link)
-        scraper_new_css.scrap_css()
-
-        # Scrape TypeScript
-        scraper_ts = ScrapTs(link)
-        scraper_ts.extract_and_save_typescript()
-
-        # Scrape Other Files
-        output_folder_other = output
-        file_extensions = ['.pdf', '.doc', '.docx', '.xls', '.xlsx', '.ppt', '.pptx', '.zip', '.rar', '.tar.gz', '.jpg', '.jpeg', '.png', '.gif', '.svg', '.bmp', '.mp4', '.avi', '.webm', '.mkv', '.mp3', '.wav', '.ogg']
-        scraper_other = ScrapOtherFiles(link, output_folder_other, file_extensions)
-        scraper_other.extract_and_save_files()
-
-        # Scrape Fonts
-        output_folder_fonts = output
-        scraper_fonts = ScrapFonts(link, output_folder_fonts)
-        scraper_fonts.extract_and_save_fonts()
-
-        # Scrape Videos
-        output_folder_videos = output
-        scraper_videos = ScrapVideos(link, output_folder_videos)
-        scraper_videos.extract_and_save_videos()
-
-        # Scrape Audio
-        output_folder_audio = output
-        scraper_audio = ScrapAudio(link, output_folder_audio)
-        scraper_audio.extract_and_save_audio()
-
-        # Scrape Icons
-        output_folder_icons = output
-        scraper_icons = ScrapIcon(link, output_folder_icons)
-        scraper_icons.extract_and_save_icons()
-
-        # Scrape Images
-        output_folder_images = output
-        scraper_images = ScrapImages(link, output_folder_images)
-        scraper_images.scrape_images()
-
-        # Add Absolute Video URLs
-        add_video = AddVideo(link, output)
-        add_video.add_absolute_video_urls()
-
-        # Add Absolute Image URLs
-        add_images = AddImages(link, output)
-        add_images.add_absolute_image_urls()
-
-        st.success("Scraping completed successfully!")
-
-        st.text("Creating zip file....(This may take time based on the content in webpage)")
-
-        # Create a zip file containing the output folder and its contents in memory
-        buffer = BytesIO()
-        with ZipFile(buffer, 'w') as zipf:
-            for root, _, files in os.walk(output):
-                for file in files:
-                    file_path = os.path.join(root, file)
-                    arcname = os.path.relpath(file_path, output)
-                    zipf.write(file_path, arcname=arcname)
-
-        # Provide a download link for the zip file with the correct file name and type
-        st.download_button("Download Output Folder", buffer.getvalue(), file_name="output.zip", mime="application/zip")
-
-        # Remove the temporary output folder
-        shutil.rmtree(output)
-
-if __name__ == "__main__":
-    main()
\ No newline at end of file
diff --git a/spaces/Pie31415/control-animation/annotator/uniformer/mmseg/models/segmentors/base.py b/spaces/Pie31415/control-animation/annotator/uniformer/mmseg/models/segmentors/base.py
deleted file mode 100644
index 172fc63b736c4f13be1cd909433bc260760a1eaa..0000000000000000000000000000000000000000
--- a/spaces/Pie31415/control-animation/annotator/uniformer/mmseg/models/segmentors/base.py
+++ /dev/null
@@ -1,273 +0,0 @@
-import logging
-import warnings
-from abc import ABCMeta, abstractmethod
-from collections import OrderedDict
-
-import annotator.uniformer.mmcv as mmcv
-import numpy as np
-import torch
-import torch.distributed as dist
-import torch.nn as nn
-from annotator.uniformer.mmcv.runner import auto_fp16
-
-
-class BaseSegmentor(nn.Module):
-    """Base class for segmentors."""
-
-    __metaclass__ = ABCMeta
-
-    def __init__(self):
-        super(BaseSegmentor, self).__init__()
-        self.fp16_enabled = False
-
-    @property
-    def with_neck(self):
-        """bool: whether the segmentor has neck"""
-        return hasattr(self, 'neck') and self.neck is not None
-
-    @property
-    def with_auxiliary_head(self):
-        """bool: whether the segmentor has auxiliary head"""
-        return hasattr(self,
-                       'auxiliary_head') and self.auxiliary_head is not None
-
-    @property
-    def with_decode_head(self):
-        """bool: whether the segmentor has decode head"""
-        return hasattr(self, 'decode_head') and self.decode_head is not None
-
-    @abstractmethod
-    def extract_feat(self, imgs):
-        """Placeholder for extract features from images."""
-        pass
-
-    @abstractmethod
-    def encode_decode(self, img, img_metas):
-        """Placeholder for encode images with backbone and decode into a
-        semantic segmentation map of the same size as input."""
-        pass
-
-    @abstractmethod
-    def forward_train(self, imgs, img_metas, **kwargs):
-        """Placeholder for Forward function for training."""
-        pass
-
-    @abstractmethod
-    def simple_test(self, img, img_meta, **kwargs):
-        """Placeholder for single image test."""
-        pass
-
-    @abstractmethod
-    def aug_test(self, imgs, img_metas, **kwargs):
-        """Placeholder for augmentation test."""
-        pass
-
-    def init_weights(self, pretrained=None):
-        """Initialize the weights in segmentor.
-
-        Args:
-            pretrained (str, optional): Path to pre-trained weights.
-                Defaults to None.
-        """
-        if pretrained is not None:
-            logger = logging.getLogger()
-            logger.info(f'load model from: {pretrained}')
-
-    def forward_test(self, imgs, img_metas, **kwargs):
-        """
-        Args:
-            imgs (List[Tensor]): the outer list indicates test-time
-                augmentations and inner Tensor should have a shape NxCxHxW,
-                which contains all images in the batch.
-            img_metas (List[List[dict]]): the outer list indicates test-time
-                augs (multiscale, flip, etc.) and the inner list indicates
-                images in a batch.
-        """
-        for var, name in [(imgs, 'imgs'), (img_metas, 'img_metas')]:
-            if not isinstance(var, list):
-                raise TypeError(f'{name} must be a list, but got '
-                                f'{type(var)}')
-
-        num_augs = len(imgs)
-        if num_augs != len(img_metas):
-            raise ValueError(f'num of augmentations ({len(imgs)}) != '
-                             f'num of image meta ({len(img_metas)})')
-        # all images in the same aug batch all of the same ori_shape and pad
-        # shape
-        for img_meta in img_metas:
-            ori_shapes = [_['ori_shape'] for _ in img_meta]
-            assert all(shape == ori_shapes[0] for shape in ori_shapes)
-            img_shapes = [_['img_shape'] for _ in img_meta]
-            assert all(shape == img_shapes[0] for shape in img_shapes)
-            pad_shapes = [_['pad_shape'] for _ in img_meta]
-            assert all(shape == pad_shapes[0] for shape in pad_shapes)
-
-        if num_augs == 1:
-            return self.simple_test(imgs[0], img_metas[0], **kwargs)
-        else:
-            return self.aug_test(imgs, img_metas, **kwargs)
-
-    @auto_fp16(apply_to=('img', ))
-    def forward(self, img, img_metas, return_loss=True, **kwargs):
-        """Calls either :func:`forward_train` or :func:`forward_test` depending
-        on whether ``return_loss`` is ``True``.
-
-        Note this setting will change the expected inputs. When
-        ``return_loss=True``, img and img_meta are single-nested (i.e. Tensor
-        and List[dict]), and when ``resturn_loss=False``, img and img_meta
-        should be double nested (i.e.  List[Tensor], List[List[dict]]), with
-        the outer list indicating test time augmentations.
-        """
-        if return_loss:
-            return self.forward_train(img, img_metas, **kwargs)
-        else:
-            return self.forward_test(img, img_metas, **kwargs)
-
-    def train_step(self, data_batch, optimizer, **kwargs):
-        """The iteration step during training.
-
-        This method defines an iteration step during training, except for the
-        back propagation and optimizer updating, which are done in an optimizer
-        hook. Note that in some complicated cases or models, the whole process
-        including back propagation and optimizer updating is also defined in
-        this method, such as GAN.
-
-        Args:
-            data (dict): The output of dataloader.
-            optimizer (:obj:`torch.optim.Optimizer` | dict): The optimizer of
-                runner is passed to ``train_step()``. This argument is unused
-                and reserved.
-
-        Returns:
-            dict: It should contain at least 3 keys: ``loss``, ``log_vars``,
-                ``num_samples``.
-                ``loss`` is a tensor for back propagation, which can be a
-                weighted sum of multiple losses.
-                ``log_vars`` contains all the variables to be sent to the
-                logger.
-                ``num_samples`` indicates the batch size (when the model is
-                DDP, it means the batch size on each GPU), which is used for
-                averaging the logs.
-        """
-        losses = self(**data_batch)
-        loss, log_vars = self._parse_losses(losses)
-
-        outputs = dict(
-            loss=loss,
-            log_vars=log_vars,
-            num_samples=len(data_batch['img_metas']))
-
-        return outputs
-
-    def val_step(self, data_batch, **kwargs):
-        """The iteration step during validation.
-
-        This method shares the same signature as :func:`train_step`, but used
-        during val epochs. Note that the evaluation after training epochs is
-        not implemented with this method, but an evaluation hook.
-        """
-        output = self(**data_batch, **kwargs)
-        return output
-
-    @staticmethod
-    def _parse_losses(losses):
-        """Parse the raw outputs (losses) of the network.
-
-        Args:
-            losses (dict): Raw output of the network, which usually contain
-                losses and other necessary information.
-
-        Returns:
-            tuple[Tensor, dict]: (loss, log_vars), loss is the loss tensor
-                which may be a weighted sum of all losses, log_vars contains
-                all the variables to be sent to the logger.
-        """
-        log_vars = OrderedDict()
-        for loss_name, loss_value in losses.items():
-            if isinstance(loss_value, torch.Tensor):
-                log_vars[loss_name] = loss_value.mean()
-            elif isinstance(loss_value, list):
-                log_vars[loss_name] = sum(_loss.mean() for _loss in loss_value)
-            else:
-                raise TypeError(
-                    f'{loss_name} is not a tensor or list of tensors')
-
-        loss = sum(_value for _key, _value in log_vars.items()
-                   if 'loss' in _key)
-
-        log_vars['loss'] = loss
-        for loss_name, loss_value in log_vars.items():
-            # reduce loss when distributed training
-            if dist.is_available() and dist.is_initialized():
-                loss_value = loss_value.data.clone()
-                dist.all_reduce(loss_value.div_(dist.get_world_size()))
-            log_vars[loss_name] = loss_value.item()
-
-        return loss, log_vars
-
-    def show_result(self,
-                    img,
-                    result,
-                    palette=None,
-                    win_name='',
-                    show=False,
-                    wait_time=0,
-                    out_file=None,
-                    opacity=0.5):
-        """Draw `result` over `img`.
-
-        Args:
-            img (str or Tensor): The image to be displayed.
-            result (Tensor): The semantic segmentation results to draw over
-                `img`.
-            palette (list[list[int]]] | np.ndarray | None): The palette of
-                segmentation map. If None is given, random palette will be
-                generated. Default: None
-            win_name (str): The window name.
-            wait_time (int): Value of waitKey param.
-                Default: 0.
-            show (bool): Whether to show the image.
-                Default: False.
-            out_file (str or None): The filename to write the image.
-                Default: None.
-            opacity(float): Opacity of painted segmentation map.
-                Default 0.5.
-                Must be in (0, 1] range.
-        Returns:
-            img (Tensor): Only if not `show` or `out_file`
-        """
-        img = mmcv.imread(img)
-        img = img.copy()
-        seg = result[0]
-        if palette is None:
-            if self.PALETTE is None:
-                palette = np.random.randint(
-                    0, 255, size=(len(self.CLASSES), 3))
-            else:
-                palette = self.PALETTE
-        palette = np.array(palette)
-        assert palette.shape[0] == len(self.CLASSES)
-        assert palette.shape[1] == 3
-        assert len(palette.shape) == 2
-        assert 0 < opacity <= 1.0
-        color_seg = np.zeros((seg.shape[0], seg.shape[1], 3), dtype=np.uint8)
-        for label, color in enumerate(palette):
-            color_seg[seg == label, :] = color
-        # convert to BGR
-        color_seg = color_seg[..., ::-1]
-
-        img = img * (1 - opacity) + color_seg * opacity
-        img = img.astype(np.uint8)
-        # if out_file specified, do not show image in window
-        if out_file is not None:
-            show = False
-
-        if show:
-            mmcv.imshow(img, win_name, wait_time)
-        if out_file is not None:
-            mmcv.imwrite(img, out_file)
-
-        if not (show or out_file):
-            warnings.warn('show==False and out_file is not specified, only '
-                          'result image will be returned')
-            return img
diff --git a/spaces/Pie31415/control-animation/annotator/uniformer/mmseg/utils/__init__.py b/spaces/Pie31415/control-animation/annotator/uniformer/mmseg/utils/__init__.py
deleted file mode 100644
index ac489e2dbbc0e6fa87f5088b4edcc20f8cadc1a6..0000000000000000000000000000000000000000
--- a/spaces/Pie31415/control-animation/annotator/uniformer/mmseg/utils/__init__.py
+++ /dev/null
@@ -1,4 +0,0 @@
-from .collect_env import collect_env
-from .logger import get_root_logger
-
-__all__ = ['get_root_logger', 'collect_env']
diff --git a/spaces/Plurigrid/LifeSim/src/components/ui/popover.tsx b/spaces/Plurigrid/LifeSim/src/components/ui/popover.tsx
deleted file mode 100644
index 8b35ce6d7b0dd78003308b09354e9f7197eb161a..0000000000000000000000000000000000000000
--- a/spaces/Plurigrid/LifeSim/src/components/ui/popover.tsx
+++ /dev/null
@@ -1,31 +0,0 @@
-"use client"
-
-import * as React from "react"
-import * as PopoverPrimitive from "@radix-ui/react-popover"
-
-import { cn } from "@/lib/utils"
-
-const Popover = PopoverPrimitive.Root
-
-const PopoverTrigger = PopoverPrimitive.Trigger
-
-const PopoverContent = React.forwardRef<
-  React.ElementRef<typeof PopoverPrimitive.Content>,
-  React.ComponentPropsWithoutRef<typeof PopoverPrimitive.Content>
->(({ className, align = "center", sideOffset = 4, ...props }, ref) => (
-  <PopoverPrimitive.Portal>
-    <PopoverPrimitive.Content
-      ref={ref}
-      align={align}
-      sideOffset={sideOffset}
-      className={cn(
-        "z-50 w-72 rounded-md border border-stone-200 bg-white p-4 text-stone-950 shadow-md outline-none data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0 data-[state=closed]:zoom-out-95 data-[state=open]:zoom-in-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2 dark:border-stone-800 dark:bg-stone-950 dark:text-stone-50",
-        className
-      )}
-      {...props}
-    />
-  </PopoverPrimitive.Portal>
-))
-PopoverContent.displayName = PopoverPrimitive.Content.displayName
-
-export { Popover, PopoverTrigger, PopoverContent }
diff --git a/spaces/Prof-Reza/Audiocraft_Music-Audio_Generation/docs/METRICS.md b/spaces/Prof-Reza/Audiocraft_Music-Audio_Generation/docs/METRICS.md
deleted file mode 100644
index e2ae9a184cbccb8bfefb4ce77afa5ddab743a051..0000000000000000000000000000000000000000
--- a/spaces/Prof-Reza/Audiocraft_Music-Audio_Generation/docs/METRICS.md
+++ /dev/null
@@ -1,127 +0,0 @@
-# AudioCraft objective metrics
-
-In addition to training losses, AudioCraft provides a set of objective metrics
-for audio synthesis and audio generation. As these metrics may require
-extra dependencies and can be costly to train, they are often disabled by default.
-This section provides guidance for setting up and using these metrics in
-the AudioCraft training pipelines.
-
-## Available metrics
-
-### Audio synthesis quality metrics
-
-#### SI-SNR
-
-We provide an implementation of the Scale-Invariant Signal-to-Noise Ratio in PyTorch.
-No specific requirement is needed for this metric. Please activate the metric at the
-evaluation stage with the appropriate flag:
-
-```shell
-dora run <...> evaluate.metrics.sisnr=true
-```
-
-#### ViSQOL
-
-We provide a Python wrapper around the ViSQOL [official implementation](https://github.com/google/visqol)
-to conveniently run ViSQOL within the training pipelines.
-
-One must specify the path to the ViSQOL installation through the configuration in order
-to enable ViSQOL computations in AudioCraft:
-
-```shell
-# the first parameter is used to activate visqol computation while the second specify
-# the path to visqol's library to be used by our python wrapper
-dora run <...> evaluate.metrics.visqol=true metrics.visqol.bin=<path_to_visqol>
-```
-
-See an example grid: [Compression with ViSQOL](../audiocraft/grids/compression/encodec_musicgen_32khz.py)
-
-To learn more about ViSQOL and how to build ViSQOL binary using bazel, please refer to the
-instructions available in the [open source repository](https://github.com/google/visqol).
-
-### Audio generation metrics
-
-#### Frechet Audio Distance
-
-Similarly to ViSQOL, we use a Python wrapper around the Frechet Audio Distance
-[official implementation](https://github.com/google-research/google-research/tree/master/frechet_audio_distance)
-in TensorFlow.
-
-Note that we had to make several changes to the actual code in order to make it work.
-Please refer to the [FrechetAudioDistanceMetric](../audiocraft/metrics/fad.py) class documentation
-for more details. We do not plan to provide further support in obtaining a working setup for the
-Frechet Audio Distance at this stage.
-
-```shell
-# the first parameter is used to activate FAD metric computation while the second specify
-# the path to FAD library to be used by our python wrapper
-dora run <...> evaluate.metrics.fad=true metrics.fad.bin=<path_to_google_research_repository>
-```
-
-See an example grid: [Evaluation with FAD](../audiocraft/grids/musicgen/musicgen_pretrained_32khz_eval.py)
-
-#### Kullback-Leibler Divergence
-
-We provide a PyTorch implementation of the Kullback-Leibler Divergence computed over the probabilities
-of the labels obtained by a state-of-the-art audio classifier. We provide our implementation of the KLD
-using the [PaSST classifier](https://github.com/kkoutini/PaSST).
-
-In order to use the KLD metric over PaSST, you must install the PaSST library as an extra dependency:
-```shell
-pip install 'git+https://github.com/kkoutini/passt_hear21@0.0.19#egg=hear21passt'
-```
-
-Then similarly, you can use the metric activating the corresponding flag:
-
-```shell
-# one could extend the kld metric with additional audio classifier models that can then be picked through the configuration
-dora run <...> evaluate.metrics.kld=true metrics.kld.model=passt
-```
-
-#### Text consistency
-
-We provide a text-consistency metric, similarly to the MuLan Cycle Consistency from
-[MusicLM](https://arxiv.org/pdf/2301.11325.pdf) or the CLAP score used in
-[Make-An-Audio](https://arxiv.org/pdf/2301.12661v1.pdf).
-More specifically, we provide a PyTorch implementation of a Text consistency metric
-relying on a pre-trained [Contrastive Language-Audio Pretraining (CLAP)](https://github.com/LAION-AI/CLAP).
-
-Please install the CLAP library as an extra dependency prior to using the metric:
-```shell
-pip install laion_clap
-```
-
-Then similarly, you can use the metric activating the corresponding flag:
-
-```shell
-# one could extend the text consistency metric with additional audio classifier models that can then be picked through the configuration
-dora run ... evaluate.metrics.text_consistency=true metrics.text_consistency.model=clap
-```
-
-Note that the text consistency metric based on CLAP will require the CLAP checkpoint to be
-provided in the configuration.
-
-#### Chroma cosine similarity
-
-Finally, as introduced in MusicGen, we provide a Chroma Cosine Similarity metric in PyTorch.
-No specific requirement is needed for this metric. Please activate the metric at the
-evaluation stage with the appropriate flag:
-
-```shell
-dora run ... evaluate.metrics.chroma_cosine=true
-```
-
-#### Comparing against reconstructed audio
-
-For all the above audio generation metrics, we offer the option to compute the metric on the reconstructed audio
-fed in EnCodec instead of the generated sample using the flag `<metric>.use_gt=true`.
-
-## Example usage
-
-You will find example of configuration for the different metrics introduced above in:
-* The [musicgen's default solver](../config/solver/musicgen/default.yaml) for all audio generation metrics
-* The [compression's default solver](../config/solver/compression/default.yaml) for all audio synthesis metrics
-
-Similarly, we provide different examples in our grids:
-* [Evaluation with ViSQOL](../audiocraft/grids/compression/encodec_musicgen_32khz.py)
-* [Evaluation with FAD and others](../audiocraft/grids/musicgen/musicgen_pretrained_32khz_eval.py)
diff --git a/spaces/Purple11/Grounded-Diffusion/ldm/lr_scheduler.py b/spaces/Purple11/Grounded-Diffusion/ldm/lr_scheduler.py
deleted file mode 100644
index be39da9ca6dacc22bf3df9c7389bbb403a4a3ade..0000000000000000000000000000000000000000
--- a/spaces/Purple11/Grounded-Diffusion/ldm/lr_scheduler.py
+++ /dev/null
@@ -1,98 +0,0 @@
-import numpy as np
-
-
-class LambdaWarmUpCosineScheduler:
-    """
-    note: use with a base_lr of 1.0
-    """
-    def __init__(self, warm_up_steps, lr_min, lr_max, lr_start, max_decay_steps, verbosity_interval=0):
-        self.lr_warm_up_steps = warm_up_steps
-        self.lr_start = lr_start
-        self.lr_min = lr_min
-        self.lr_max = lr_max
-        self.lr_max_decay_steps = max_decay_steps
-        self.last_lr = 0.
-        self.verbosity_interval = verbosity_interval
-
-    def schedule(self, n, **kwargs):
-        if self.verbosity_interval > 0:
-            if n % self.verbosity_interval == 0: print(f"current step: {n}, recent lr-multiplier: {self.last_lr}")
-        if n < self.lr_warm_up_steps:
-            lr = (self.lr_max - self.lr_start) / self.lr_warm_up_steps * n + self.lr_start
-            self.last_lr = lr
-            return lr
-        else:
-            t = (n - self.lr_warm_up_steps) / (self.lr_max_decay_steps - self.lr_warm_up_steps)
-            t = min(t, 1.0)
-            lr = self.lr_min + 0.5 * (self.lr_max - self.lr_min) * (
-                    1 + np.cos(t * np.pi))
-            self.last_lr = lr
-            return lr
-
-    def __call__(self, n, **kwargs):
-        return self.schedule(n,**kwargs)
-
-
-class LambdaWarmUpCosineScheduler2:
-    """
-    supports repeated iterations, configurable via lists
-    note: use with a base_lr of 1.0.
-    """
-    def __init__(self, warm_up_steps, f_min, f_max, f_start, cycle_lengths, verbosity_interval=0):
-        assert len(warm_up_steps) == len(f_min) == len(f_max) == len(f_start) == len(cycle_lengths)
-        self.lr_warm_up_steps = warm_up_steps
-        self.f_start = f_start
-        self.f_min = f_min
-        self.f_max = f_max
-        self.cycle_lengths = cycle_lengths
-        self.cum_cycles = np.cumsum([0] + list(self.cycle_lengths))
-        self.last_f = 0.
-        self.verbosity_interval = verbosity_interval
-
-    def find_in_interval(self, n):
-        interval = 0
-        for cl in self.cum_cycles[1:]:
-            if n <= cl:
-                return interval
-            interval += 1
-
-    def schedule(self, n, **kwargs):
-        cycle = self.find_in_interval(n)
-        n = n - self.cum_cycles[cycle]
-        if self.verbosity_interval > 0:
-            if n % self.verbosity_interval == 0: print(f"current step: {n}, recent lr-multiplier: {self.last_f}, "
-                                                       f"current cycle {cycle}")
-        if n < self.lr_warm_up_steps[cycle]:
-            f = (self.f_max[cycle] - self.f_start[cycle]) / self.lr_warm_up_steps[cycle] * n + self.f_start[cycle]
-            self.last_f = f
-            return f
-        else:
-            t = (n - self.lr_warm_up_steps[cycle]) / (self.cycle_lengths[cycle] - self.lr_warm_up_steps[cycle])
-            t = min(t, 1.0)
-            f = self.f_min[cycle] + 0.5 * (self.f_max[cycle] - self.f_min[cycle]) * (
-                    1 + np.cos(t * np.pi))
-            self.last_f = f
-            return f
-
-    def __call__(self, n, **kwargs):
-        return self.schedule(n, **kwargs)
-
-
-class LambdaLinearScheduler(LambdaWarmUpCosineScheduler2):
-
-    def schedule(self, n, **kwargs):
-        cycle = self.find_in_interval(n)
-        n = n - self.cum_cycles[cycle]
-        if self.verbosity_interval > 0:
-            if n % self.verbosity_interval == 0: print(f"current step: {n}, recent lr-multiplier: {self.last_f}, "
-                                                       f"current cycle {cycle}")
-
-        if n < self.lr_warm_up_steps[cycle]:
-            f = (self.f_max[cycle] - self.f_start[cycle]) / self.lr_warm_up_steps[cycle] * n + self.f_start[cycle]
-            self.last_f = f
-            return f
-        else:
-            f = self.f_min[cycle] + (self.f_max[cycle] - self.f_min[cycle]) * (self.cycle_lengths[cycle] - n) / (self.cycle_lengths[cycle])
-            self.last_f = f
-            return f
-
diff --git a/spaces/Raspberry-ai/main/.env/lib/python3.11/site-packages/setuptools/config/_apply_pyprojecttoml.py b/spaces/Raspberry-ai/main/.env/lib/python3.11/site-packages/setuptools/config/_apply_pyprojecttoml.py
deleted file mode 100644
index 8af556169cd6cce0282fce9ee09e6d6bcfc452c5..0000000000000000000000000000000000000000
--- a/spaces/Raspberry-ai/main/.env/lib/python3.11/site-packages/setuptools/config/_apply_pyprojecttoml.py
+++ /dev/null
@@ -1,377 +0,0 @@
-"""Translation layer between pyproject config and setuptools distribution and
-metadata objects.
-
-The distribution and metadata objects are modeled after (an old version of)
-core metadata, therefore configs in the format specified for ``pyproject.toml``
-need to be processed before being applied.
-
-**PRIVATE MODULE**: API reserved for setuptools internal usage only.
-"""
-import logging
-import os
-import warnings
-from collections.abc import Mapping
-from email.headerregistry import Address
-from functools import partial, reduce
-from itertools import chain
-from types import MappingProxyType
-from typing import (TYPE_CHECKING, Any, Callable, Dict, List, Optional, Set, Tuple,
-                    Type, Union)
-
-from setuptools._deprecation_warning import SetuptoolsDeprecationWarning
-
-if TYPE_CHECKING:
-    from setuptools._importlib import metadata  # noqa
-    from setuptools.dist import Distribution  # noqa
-
-EMPTY: Mapping = MappingProxyType({})  # Immutable dict-like
-_Path = Union[os.PathLike, str]
-_DictOrStr = Union[dict, str]
-_CorrespFn = Callable[["Distribution", Any, _Path], None]
-_Correspondence = Union[str, _CorrespFn]
-
-_logger = logging.getLogger(__name__)
-
-
-def apply(dist: "Distribution", config: dict, filename: _Path) -> "Distribution":
-    """Apply configuration dict read with :func:`read_configuration`"""
-
-    if not config:
-        return dist  # short-circuit unrelated pyproject.toml file
-
-    root_dir = os.path.dirname(filename) or "."
-
-    _apply_project_table(dist, config, root_dir)
-    _apply_tool_table(dist, config, filename)
-
-    current_directory = os.getcwd()
-    os.chdir(root_dir)
-    try:
-        dist._finalize_requires()
-        dist._finalize_license_files()
-    finally:
-        os.chdir(current_directory)
-
-    return dist
-
-
-def _apply_project_table(dist: "Distribution", config: dict, root_dir: _Path):
-    project_table = config.get("project", {}).copy()
-    if not project_table:
-        return  # short-circuit
-
-    _handle_missing_dynamic(dist, project_table)
-    _unify_entry_points(project_table)
-
-    for field, value in project_table.items():
-        norm_key = json_compatible_key(field)
-        corresp = PYPROJECT_CORRESPONDENCE.get(norm_key, norm_key)
-        if callable(corresp):
-            corresp(dist, value, root_dir)
-        else:
-            _set_config(dist, corresp, value)
-
-
-def _apply_tool_table(dist: "Distribution", config: dict, filename: _Path):
-    tool_table = config.get("tool", {}).get("setuptools", {})
-    if not tool_table:
-        return  # short-circuit
-
-    for field, value in tool_table.items():
-        norm_key = json_compatible_key(field)
-
-        if norm_key in TOOL_TABLE_DEPRECATIONS:
-            suggestion = TOOL_TABLE_DEPRECATIONS[norm_key]
-            msg = f"The parameter `{norm_key}` is deprecated, {suggestion}"
-            warnings.warn(msg, SetuptoolsDeprecationWarning)
-
-        norm_key = TOOL_TABLE_RENAMES.get(norm_key, norm_key)
-        _set_config(dist, norm_key, value)
-
-    _copy_command_options(config, dist, filename)
-
-
-def _handle_missing_dynamic(dist: "Distribution", project_table: dict):
-    """Be temporarily forgiving with ``dynamic`` fields not listed in ``dynamic``"""
-    # TODO: Set fields back to `None` once the feature stabilizes
-    dynamic = set(project_table.get("dynamic", []))
-    for field, getter in _PREVIOUSLY_DEFINED.items():
-        if not (field in project_table or field in dynamic):
-            value = getter(dist)
-            if value:
-                msg = _WouldIgnoreField.message(field, value)
-                warnings.warn(msg, _WouldIgnoreField)
-
-
-def json_compatible_key(key: str) -> str:
-    """As defined in :pep:`566#json-compatible-metadata`"""
-    return key.lower().replace("-", "_")
-
-
-def _set_config(dist: "Distribution", field: str, value: Any):
-    setter = getattr(dist.metadata, f"set_{field}", None)
-    if setter:
-        setter(value)
-    elif hasattr(dist.metadata, field) or field in SETUPTOOLS_PATCHES:
-        setattr(dist.metadata, field, value)
-    else:
-        setattr(dist, field, value)
-
-
-_CONTENT_TYPES = {
-    ".md": "text/markdown",
-    ".rst": "text/x-rst",
-    ".txt": "text/plain",
-}
-
-
-def _guess_content_type(file: str) -> Optional[str]:
-    _, ext = os.path.splitext(file.lower())
-    if not ext:
-        return None
-
-    if ext in _CONTENT_TYPES:
-        return _CONTENT_TYPES[ext]
-
-    valid = ", ".join(f"{k} ({v})" for k, v in _CONTENT_TYPES.items())
-    msg = f"only the following file extensions are recognized: {valid}."
-    raise ValueError(f"Undefined content type for {file}, {msg}")
-
-
-def _long_description(dist: "Distribution", val: _DictOrStr, root_dir: _Path):
-    from setuptools.config import expand
-
-    if isinstance(val, str):
-        text = expand.read_files(val, root_dir)
-        ctype = _guess_content_type(val)
-    else:
-        text = val.get("text") or expand.read_files(val.get("file", []), root_dir)
-        ctype = val["content-type"]
-
-    _set_config(dist, "long_description", text)
-    if ctype:
-        _set_config(dist, "long_description_content_type", ctype)
-
-
-def _license(dist: "Distribution", val: dict, root_dir: _Path):
-    from setuptools.config import expand
-
-    if "file" in val:
-        _set_config(dist, "license", expand.read_files([val["file"]], root_dir))
-    else:
-        _set_config(dist, "license", val["text"])
-
-
-def _people(dist: "Distribution", val: List[dict], _root_dir: _Path, kind: str):
-    field = []
-    email_field = []
-    for person in val:
-        if "name" not in person:
-            email_field.append(person["email"])
-        elif "email" not in person:
-            field.append(person["name"])
-        else:
-            addr = Address(display_name=person["name"], addr_spec=person["email"])
-            email_field.append(str(addr))
-
-    if field:
-        _set_config(dist, kind, ", ".join(field))
-    if email_field:
-        _set_config(dist, f"{kind}_email", ", ".join(email_field))
-
-
-def _project_urls(dist: "Distribution", val: dict, _root_dir):
-    _set_config(dist, "project_urls", val)
-
-
-def _python_requires(dist: "Distribution", val: dict, _root_dir):
-    from setuptools.extern.packaging.specifiers import SpecifierSet
-
-    _set_config(dist, "python_requires", SpecifierSet(val))
-
-
-def _dependencies(dist: "Distribution", val: list, _root_dir):
-    if getattr(dist, "install_requires", []):
-        msg = "`install_requires` overwritten in `pyproject.toml` (dependencies)"
-        warnings.warn(msg)
-    _set_config(dist, "install_requires", val)
-
-
-def _optional_dependencies(dist: "Distribution", val: dict, _root_dir):
-    existing = getattr(dist, "extras_require", {})
-    _set_config(dist, "extras_require", {**existing, **val})
-
-
-def _unify_entry_points(project_table: dict):
-    project = project_table
-    entry_points = project.pop("entry-points", project.pop("entry_points", {}))
-    renaming = {"scripts": "console_scripts", "gui_scripts": "gui_scripts"}
-    for key, value in list(project.items()):  # eager to allow modifications
-        norm_key = json_compatible_key(key)
-        if norm_key in renaming and value:
-            entry_points[renaming[norm_key]] = project.pop(key)
-
-    if entry_points:
-        project["entry-points"] = {
-            name: [f"{k} = {v}" for k, v in group.items()]
-            for name, group in entry_points.items()
-        }
-
-
-def _copy_command_options(pyproject: dict, dist: "Distribution", filename: _Path):
-    tool_table = pyproject.get("tool", {})
-    cmdclass = tool_table.get("setuptools", {}).get("cmdclass", {})
-    valid_options = _valid_command_options(cmdclass)
-
-    cmd_opts = dist.command_options
-    for cmd, config in pyproject.get("tool", {}).get("distutils", {}).items():
-        cmd = json_compatible_key(cmd)
-        valid = valid_options.get(cmd, set())
-        cmd_opts.setdefault(cmd, {})
-        for key, value in config.items():
-            key = json_compatible_key(key)
-            cmd_opts[cmd][key] = (str(filename), value)
-            if key not in valid:
-                # To avoid removing options that are specified dynamically we
-                # just log a warn...
-                _logger.warning(f"Command option {cmd}.{key} is not defined")
-
-
-def _valid_command_options(cmdclass: Mapping = EMPTY) -> Dict[str, Set[str]]:
-    from .._importlib import metadata
-    from setuptools.dist import Distribution
-
-    valid_options = {"global": _normalise_cmd_options(Distribution.global_options)}
-
-    unloaded_entry_points = metadata.entry_points(group='distutils.commands')
-    loaded_entry_points = (_load_ep(ep) for ep in unloaded_entry_points)
-    entry_points = (ep for ep in loaded_entry_points if ep)
-    for cmd, cmd_class in chain(entry_points, cmdclass.items()):
-        opts = valid_options.get(cmd, set())
-        opts = opts | _normalise_cmd_options(getattr(cmd_class, "user_options", []))
-        valid_options[cmd] = opts
-
-    return valid_options
-
-
-def _load_ep(ep: "metadata.EntryPoint") -> Optional[Tuple[str, Type]]:
-    # Ignore all the errors
-    try:
-        return (ep.name, ep.load())
-    except Exception as ex:
-        msg = f"{ex.__class__.__name__} while trying to load entry-point {ep.name}"
-        _logger.warning(f"{msg}: {ex}")
-        return None
-
-
-def _normalise_cmd_option_key(name: str) -> str:
-    return json_compatible_key(name).strip("_=")
-
-
-def _normalise_cmd_options(desc: List[Tuple[str, Optional[str], str]]) -> Set[str]:
-    return {_normalise_cmd_option_key(fancy_option[0]) for fancy_option in desc}
-
-
-def _attrgetter(attr):
-    """
-    Similar to ``operator.attrgetter`` but returns None if ``attr`` is not found
-    >>> from types import SimpleNamespace
-    >>> obj = SimpleNamespace(a=42, b=SimpleNamespace(c=13))
-    >>> _attrgetter("a")(obj)
-    42
-    >>> _attrgetter("b.c")(obj)
-    13
-    >>> _attrgetter("d")(obj) is None
-    True
-    """
-    return partial(reduce, lambda acc, x: getattr(acc, x, None), attr.split("."))
-
-
-def _some_attrgetter(*items):
-    """
-    Return the first "truth-y" attribute or None
-    >>> from types import SimpleNamespace
-    >>> obj = SimpleNamespace(a=42, b=SimpleNamespace(c=13))
-    >>> _some_attrgetter("d", "a", "b.c")(obj)
-    42
-    >>> _some_attrgetter("d", "e", "b.c", "a")(obj)
-    13
-    >>> _some_attrgetter("d", "e", "f")(obj) is None
-    True
-    """
-    def _acessor(obj):
-        values = (_attrgetter(i)(obj) for i in items)
-        return next((i for i in values if i is not None), None)
-    return _acessor
-
-
-PYPROJECT_CORRESPONDENCE: Dict[str, _Correspondence] = {
-    "readme": _long_description,
-    "license": _license,
-    "authors": partial(_people, kind="author"),
-    "maintainers": partial(_people, kind="maintainer"),
-    "urls": _project_urls,
-    "dependencies": _dependencies,
-    "optional_dependencies": _optional_dependencies,
-    "requires_python": _python_requires,
-}
-
-TOOL_TABLE_RENAMES = {"script_files": "scripts"}
-TOOL_TABLE_DEPRECATIONS = {
-    "namespace_packages": "consider using implicit namespaces instead (PEP 420)."
-}
-
-SETUPTOOLS_PATCHES = {"long_description_content_type", "project_urls",
-                      "provides_extras", "license_file", "license_files"}
-
-_PREVIOUSLY_DEFINED = {
-    "name": _attrgetter("metadata.name"),
-    "version": _attrgetter("metadata.version"),
-    "description": _attrgetter("metadata.description"),
-    "readme": _attrgetter("metadata.long_description"),
-    "requires-python": _some_attrgetter("python_requires", "metadata.python_requires"),
-    "license": _attrgetter("metadata.license"),
-    "authors": _some_attrgetter("metadata.author", "metadata.author_email"),
-    "maintainers": _some_attrgetter("metadata.maintainer", "metadata.maintainer_email"),
-    "keywords": _attrgetter("metadata.keywords"),
-    "classifiers": _attrgetter("metadata.classifiers"),
-    "urls": _attrgetter("metadata.project_urls"),
-    "entry-points": _attrgetter("entry_points"),
-    "dependencies": _some_attrgetter("_orig_install_requires", "install_requires"),
-    "optional-dependencies": _some_attrgetter("_orig_extras_require", "extras_require"),
-}
-
-
-class _WouldIgnoreField(UserWarning):
-    """Inform users that ``pyproject.toml`` would overwrite previous metadata."""
-
-    MESSAGE = """\
-    {field!r} defined outside of `pyproject.toml` would be ignored.
-    !!\n\n
-    ##########################################################################
-    # configuration would be ignored/result in error due to `pyproject.toml` #
-    ##########################################################################
-
-    The following seems to be defined outside of `pyproject.toml`:
-
-    `{field} = {value!r}`
-
-    According to the spec (see the link below), however, setuptools CANNOT
-    consider this value unless {field!r} is listed as `dynamic`.
-
-    https://packaging.python.org/en/latest/specifications/declaring-project-metadata/
-
-    For the time being, `setuptools` will still consider the given value (as a
-    **transitional** measure), but please note that future releases of setuptools will
-    follow strictly the standard.
-
-    To prevent this warning, you can list {field!r} under `dynamic` or alternatively
-    remove the `[project]` table from your file and rely entirely on other means of
-    configuration.
-    \n\n!!
-    """
-
-    @classmethod
-    def message(cls, field, value):
-        from inspect import cleandoc
-        return cleandoc(cls.MESSAGE.format(field=field, value=value))
diff --git a/spaces/Realcat/image-matching-webui/third_party/SGMNet/README.md b/spaces/Realcat/image-matching-webui/third_party/SGMNet/README.md
deleted file mode 100644
index c01115fb33623295fb74314ad33cb340af70509d..0000000000000000000000000000000000000000
--- a/spaces/Realcat/image-matching-webui/third_party/SGMNet/README.md
+++ /dev/null
@@ -1,295 +0,0 @@
-# SGMNet Implementation
-
-![Framework](assets/teaser.png)
-
-PyTorch implementation of SGMNet for ICCV'21 paper ["Learning to Match Features with Seeded Graph Matching Network"](https://arxiv.org/abs/2108.08771), by Hongkai Chen, Zixin Luo, Jiahui Zhang, Lei Zhou, Xuyang Bai, Zeyu Hu, Chiew-Lan Tai, Long Quan.
-
-This work focuses on keypoint-based image matching problem. We mitigate the qudratic complexity issue for typical GNN-based matching by leveraging a restrited set of pre-matched seeds. 
-
-This repo contains training, evaluation and basic demo sripts used in our paper. As baseline, it also includes **our implementation** for [SuperGlue](https://arxiv.org/abs/1911.11763). If you find this project useful, please cite:
-
-```
-@article{chen2021sgmnet,
-  title={Learning to Match Features with Seeded Graph Matching Network},
-  author={Chen, Hongkai and Luo, Zixin and Zhang, Jiahui and Zhou, Lei and Bai, Xuyang and Hu, Zeyu and Tai, Chiew-Lan and Quan, Long},
-  journal={International Conference on Computer Vision (ICCV)},
-  year={2021}
-}
-```
-
-Part of the code is borrowed or ported from 
-
-[SuperPoint](https://github.com/magicleap/SuperPointPretrainedNetwork), for SuperPoint implementation, 
-
-[SuperGlue](https://github.com/magicleap/SuperGluePretrainedNetwork), for SuperGlue implementation and exact auc computation,
-
-[OANet](https://github.com/zjhthu/OANet), for training scheme,
-
-[PointCN](https://github.com/vcg-uvic/learned-correspondence-release), for implementaion of PointCN block and geometric transformations,
-
-[FM-Bench](https://github.com/JiawangBian/FM-Bench), for evaluation of fundamental matrix estimation.
-
-
-Please also cite these works if you find the corresponding code useful. 
-
-
-## Requirements
-
-We use PyTorch 1.6, later version should also be compatible. Please refer to [requirements.txt](requirements.txt) for other dependencies.
-
-If you are using conda, you may configure the environment as:
-
-```bash
-conda create --name sgmnet python=3.7 -y && \
-pip install -r requirements.txt && \
-conda activate sgmnet
-```
-
-## Get started
-
-Clone the repo:
-```bash
-git clone https://github.com/vdvchen/SGMNet.git && \
-```
-download model weights from [here](https://drive.google.com/file/d/1Ca0WmKSSt2G6P7m8YAOlSAHEFar_TAWb/view?usp=sharing)  
-
-extract weights by
-```bash
-tar -xvf weights.tar.gz
-```
-
-A quick demo for image matching can be called by:
-
-```bash
-cd demo && python demo.py --config_path configs/sgm_config.yaml
-```
-The resutls will be saved as **match.png** in demo folder. You may configure the matcher in corresponding yaml file.
-
-
-## Evaluation
-
-
-We demonstrate evaluation process with RootSIFT and SGMNet. Evaluation with other features/matchers can be conducted by configuring the corresponding yaml files.  
-
-### 1. YFCC Evaluation 
-
-Refer to [OANet](https://github.com/zjhthu/OANet) repo to download raw YFCC100M dataset
-
-
-**Data Generation**
-       
-1. Configure **datadump/configs/yfcc_root.yaml** for the following entries
-
-   **rawdata_dir**: path for yfcc rawdata  
-   **feature_dump_dir**: dump path for extracted features  
-   **dataset_dump_dir**: dump path for generated dataset  
-   **extractor**: configuration for keypoint extractor (2k RootSIFT by default)  
-
-2. Generate data by
-   ```bash
-   cd datadump
-   python dump.py --config_path configs/yfcc_root.yaml
-   ```
-   An h5py data file will be generated under **dataset_dump_dir**, e.g. **yfcc_root_2000.hdf5**
-
-**Evaluation**:
-
-1. Configure **evaluation/configs/eval/yfcc_eval_sgm.yaml** for the following entries
-
-   **reader.rawdata_dir**: path for yfcc_rawdata  
-   **reader.dataset_dir**: path for generated h5py dataset file    
-   **matcher**: configuration for sgmnet (we use the default setting)
-
-2. To run evaluation,    
-   ```bash
-   cd evaluation
-   python evaluate.py --config_path configs/eval/yfcc_eval_sgm.yaml
-   ```
-
-For 2k RootSIFT matching, similar results as below should be obtained,
-```bash
-auc th: [5 10 15 20 25 30]
-approx auc: [0.634 0.729 0.783 0.818 0.843 0.861]
-exact auc: [0.355 0.552 0.655 0.719 0.762 0.793]
-mean match score: 17.06
-mean precision: 86.08
-```
-
-### 2. ScanNet Evaluation
-
-Download processed [ScanNet evaluation data](https://drive.google.com/file/d/14s-Ce8Vq7XedzKon8MZSB_Mz_iC6oFPy/view?usp=sharing).  
-
-
-**Data Generation**
-       
-1. Configure **datadump/configs/scannet_root.yaml** for the following entries
-
-   **rawdata_dir**: path for ScanNet raw data  
-   **feature_dump_dir**: dump path for extracted features  
-   **dataset_dump_dir**: dump path for generated dataset  
-   **extractor**: configuration for keypoint extractor (2k RootSIFT by default)  
-
-2. Generate data by
-   ```bash
-   cd datadump
-   python dump.py --config_path configs/scannet_root.yaml
-   ```
-   An h5py data file will be generated under **dataset_dump_dir**, e.g. **scannet_root_2000.hdf5** 
-
-**Evaluation**:
-
-1. Configure **evaluation/configs/eval/scannet_eval_sgm.yaml** for the following entries
-
-   **reader.rawdata_dir**: path for ScanNet evaluation data  
-   **reader.dataset_dir**: path for generated h5py dataset file    
-   **matcher**: configuration for sgmnet (we use the default setting)  
-
-2. To run evaluation,  
-   ```bash
-   cd evaluation
-   python evaluate.py --config_path configs/eval/scannet_eval_sgm.yaml
-   ```
-
-For 2k RootSIFT matching, similar results as below should be obtained,
-```bash
-auc th: [5 10 15 20 25 30]
-approx auc: [0.322 0.427 0.493 0.541 0.577 0.606]
-exact auc: [0.125 0.283 0.383 0.452 0.503 0.541]
-mean match score: 8.79
-mean precision: 45.54
-```
-
-### 3. FM-Bench Evaluation
-
-Refer to [FM-Bench](https://github.com/JiawangBian/FM-Bench) repo to download raw FM-Bench dataset
-
-**Data Generation**
-       
-1. Configure **datadump/configs/fmbench_root.yaml** for the following entries
-
-   **rawdata_dir**: path for fmbench raw data  
-   **feature_dump_dir**: dump path for extracted features  
-   **dataset_dump_dir**: dump path for generated dataset  
-   **extractor**: configuration for keypoint extractor (4k RootSIFT by default)  
-
-2. Generate data by
-   ```bash
-   cd datadump
-   python dump.py --config_path configs/fmbench_root.yaml
-   ```
-   An h5py data file will be generated under **dataset_dump_dir**, e.g. **fmbench_root_4000.hdf5** 
-
-**Evaluation**:
-
-1. Configure **evaluation/configs/eval/fm_eval_sgm.yaml** for the following entries
-
-   **reader.rawdata_dir**: path for fmbench raw data  
-   **reader.dataset_dir**: path for generated h5py dataset file    
-   **matcher**: configuration for sgmnet (we use the default setting)   
-
-2. To run evaluation,  
-   ```bash
-   cd evaluation
-   python evaluate.py --config_path configs/eval/fm_eval_sgm.yaml
-   ```
-
-For 4k RootSIFT matching, similar results as below should be obtained,
-```bash
-CPC results:
-F_recall:  0.617
-precision:  0.7489
-precision_post:  0.8399
-num_corr:  663.838
-num_corr_post:  284.455  
-
-KITTI results:
-F_recall:  0.911
-precision:  0.9035133886251774
-precision_post:  0.9837278538989989
-num_corr:  1670.548
-num_corr_post:  1121.902
-
-TUM results:
-F_recall:  0.666
-precision:  0.6520260208250837
-precision_post:  0.731507123852191
-num_corr:  1650.579
-num_corr_post:  941.846
-
-Tanks_and_Temples results:
-F_recall:  0.855
-precision:  0.7452896681043316
-precision_post:  0.8020184635328004
-num_corr:  946.571
-num_corr_post:  466.865
-```
-
-### 4. Run time and memory Evaluation
-
-We provide a script to test run time and memory consumption, for a quick start, run  
-
-```bash
-cd evaluation
-python eval_cost.py --matcher_name SGM  --config_path configs/cost/sgm_cost.yaml --num_kpt=4000
-```
-You may configure the matcher in corresponding yaml files.
-
-
-## Visualization
-
-For visualization of matching results on different dataset, add **--vis_folder** argument on evaluation command, e.g.
-
-```bash
-cd evaluation
-python evaluate.py --config_path configs/eval/***.yaml --vis_folder visualization
-```
-
-
-## Training
-
-We train both SGMNet and SuperGlue on [GL3D](https://github.com/lzx551402/GL3D) dataset. The training data is pre-generated in an offline manner, which yields about 400k pairs in total. 
-
-To generate training/validation dataset
-
-1. Download [GL3D](https://github.com/lzx551402/GL3D) rawdata 
-
-2. Configure **datadump/configs/gl3d.yaml**. Some important entries are
-
-   **rawdata_dir**: path for GL3D raw data  
-   **feature_dump_dir**: path for extracted features  
-   **dataset_dump_dir**: path for generated dataset  
-   **pairs_per_seq**: number of pairs sampled for each sequence    
-   **angle_th**: angle threshold for sampled pairs  
-   **overlap_th**: common track threshold for sampled pairs  
-   **extractor**: configuration for keypoint extractor  
-
-3. dump dataset by
-```bash
-cd datadump
-python dump.py --config_path configs/gl3d.yaml
-```
-
-Two parts of data will be generated. (1) Extracted features and keypoints will be placed under **feature_dump_dir** (2) Pairwise dataset will be placed under **dataset_dump_dir**.
-
-4. After data generation, configure **train/train_sgm.sh** for necessary entries, including   
-   **rawdata_path**: path for GL3D raw data  
-   **desc_path**: path for extracted features  
-   **dataset_path**: path for generated dataset  
-   **desc_suffix**: suffix for keypoint files, _root_1000.hdf5 for 1k RootSIFT by default.  
-   **log_base**: log directory for training     
-  
-5. run SGMNet training scripts by
-```bash
-bash train_sgm.sh
-```
-
-our training scripts support multi-gpu training, which can be enabled by configure **train/train_sgm.sh** for these entries
-
-   **CUDA_VISIBLE_DEVICES**: id of gpus to be used   
-   **nproc_per_node**: number of gpus to be used
-
-run SuperGlue training scripts by
-
-```bash
-bash train_sg.sh
-```
diff --git a/spaces/Realcat/image-matching-webui/third_party/lanet/network_v1/modules.py b/spaces/Realcat/image-matching-webui/third_party/lanet/network_v1/modules.py
deleted file mode 100644
index f7d688684992384b2db22e53bcf1e6b5ddb33d32..0000000000000000000000000000000000000000
--- a/spaces/Realcat/image-matching-webui/third_party/lanet/network_v1/modules.py
+++ /dev/null
@@ -1,217 +0,0 @@
-from curses import is_term_resized
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-
-from torchvision import models
-from lanet_utils import image_grid
-
-
-class ConvBlock(nn.Module):
-    def __init__(self, in_channels, out_channels):
-        super(ConvBlock, self).__init__()
-
-        self.conv = nn.Sequential(
-            nn.Conv2d(
-                in_channels,
-                out_channels,
-                kernel_size=3,
-                stride=1,
-                padding=1,
-                bias=False,
-            ),
-            nn.BatchNorm2d(out_channels),
-            nn.ReLU(inplace=True),
-            nn.Conv2d(
-                out_channels,
-                out_channels,
-                kernel_size=3,
-                stride=1,
-                padding=1,
-                bias=False,
-            ),
-            nn.BatchNorm2d(out_channels),
-            nn.ReLU(inplace=True),
-        )
-
-    def forward(self, x):
-        return self.conv(x)
-
-
-class DilationConv3x3(nn.Module):
-    def __init__(self, in_channels, out_channels):
-        super(DilationConv3x3, self).__init__()
-
-        self.conv = nn.Conv2d(
-            in_channels,
-            out_channels,
-            kernel_size=3,
-            stride=1,
-            padding=2,
-            dilation=2,
-            bias=False,
-        )
-        self.bn = nn.BatchNorm2d(out_channels)
-
-    def forward(self, x):
-        x = self.conv(x)
-        x = self.bn(x)
-        return x
-
-
-class InterestPointModule(nn.Module):
-    def __init__(self, is_test=False):
-        super(InterestPointModule, self).__init__()
-        self.is_test = is_test
-
-        model = models.vgg16_bn(pretrained=True)
-
-        # use the first 23 layers as encoder
-        self.encoder = nn.Sequential(*list(model.features.children())[:33])
-
-        # score head
-        self.score_head = nn.Sequential(
-            nn.Conv2d(512, 256, kernel_size=3, stride=1, padding=1, bias=False),
-            nn.BatchNorm2d(256),
-            nn.ReLU(inplace=True),
-            nn.Conv2d(256, 4, kernel_size=3, stride=1, padding=1),
-        )
-        self.softmax = nn.Softmax(dim=1)
-
-        # location head
-        self.loc_head = nn.Sequential(
-            nn.Conv2d(512, 256, kernel_size=3, stride=1, padding=1, bias=False),
-            nn.BatchNorm2d(256),
-            nn.ReLU(inplace=True),
-        )
-        # location out
-        self.loc_out = nn.Conv2d(256, 2, kernel_size=3, stride=1, padding=1)
-        self.shift_out = nn.Conv2d(256, 1, kernel_size=3, stride=1, padding=1)
-
-        # descriptor out
-        self.des_out2 = DilationConv3x3(128, 256)
-        self.des_out3 = DilationConv3x3(256, 256)
-        self.des_out4 = DilationConv3x3(512, 256)
-
-    def forward(self, x):
-        B, _, H, W = x.shape
-
-        x = self.encoder[2](self.encoder[1](self.encoder[0](x)))
-        x = self.encoder[5](self.encoder[4](self.encoder[3](x)))
-
-        x = self.encoder[6](x)
-        x = self.encoder[9](self.encoder[8](self.encoder[7](x)))
-        x2 = self.encoder[12](self.encoder[11](self.encoder[10](x)))
-
-        x = self.encoder[13](x2)
-        x = self.encoder[16](self.encoder[15](self.encoder[14](x)))
-        x = self.encoder[19](self.encoder[18](self.encoder[17](x)))
-        x3 = self.encoder[22](self.encoder[21](self.encoder[20](x)))
-
-        x = self.encoder[23](x3)
-        x = self.encoder[26](self.encoder[25](self.encoder[24](x)))
-        x = self.encoder[29](self.encoder[28](self.encoder[27](x)))
-        x = self.encoder[32](self.encoder[31](self.encoder[30](x)))
-
-        B, _, Hc, Wc = x.shape
-
-        # score head
-        score_x = self.score_head(x)
-        aware = self.softmax(score_x[:, 0:3, :, :])
-        score = score_x[:, 3, :, :].unsqueeze(1).sigmoid()
-
-        border_mask = torch.ones(B, Hc, Wc)
-        border_mask[:, 0] = 0
-        border_mask[:, Hc - 1] = 0
-        border_mask[:, :, 0] = 0
-        border_mask[:, :, Wc - 1] = 0
-        border_mask = border_mask.unsqueeze(1)
-        score = score * border_mask.to(score.device)
-
-        # location head
-        coord_x = self.loc_head(x)
-        coord_cell = self.loc_out(coord_x).tanh()
-
-        shift_ratio = self.shift_out(coord_x).sigmoid() * 2.0
-
-        step = ((H / Hc) - 1) / 2.0
-        center_base = (
-            image_grid(
-                B,
-                Hc,
-                Wc,
-                dtype=coord_cell.dtype,
-                device=coord_cell.device,
-                ones=False,
-                normalized=False,
-            ).mul(H / Hc)
-            + step
-        )
-
-        coord_un = center_base.add(coord_cell.mul(shift_ratio * step))
-        coord = coord_un.clone()
-        coord[:, 0] = torch.clamp(coord_un[:, 0], min=0, max=W - 1)
-        coord[:, 1] = torch.clamp(coord_un[:, 1], min=0, max=H - 1)
-
-        # descriptor block
-        desc_block = []
-        desc_block.append(self.des_out2(x2))
-        desc_block.append(self.des_out3(x3))
-        desc_block.append(self.des_out4(x))
-        desc_block.append(aware)
-
-        if self.is_test:
-            coord_norm = coord[:, :2].clone()
-            coord_norm[:, 0] = (coord_norm[:, 0] / (float(W - 1) / 2.0)) - 1.0
-            coord_norm[:, 1] = (coord_norm[:, 1] / (float(H - 1) / 2.0)) - 1.0
-            coord_norm = coord_norm.permute(0, 2, 3, 1)
-
-            desc2 = torch.nn.functional.grid_sample(desc_block[0], coord_norm)
-            desc3 = torch.nn.functional.grid_sample(desc_block[1], coord_norm)
-            desc4 = torch.nn.functional.grid_sample(desc_block[2], coord_norm)
-            aware = desc_block[3]
-
-            desc = (
-                torch.mul(desc2, aware[:, 0, :, :])
-                + torch.mul(desc3, aware[:, 1, :, :])
-                + torch.mul(desc4, aware[:, 2, :, :])
-            )
-            desc = desc.div(
-                torch.unsqueeze(torch.norm(desc, p=2, dim=1), 1)
-            )  # Divide by norm to normalize.
-
-            return score, coord, desc
-
-        return score, coord, desc_block
-
-
-class CorrespondenceModule(nn.Module):
-    def __init__(self, match_type="dual_softmax"):
-        super(CorrespondenceModule, self).__init__()
-        self.match_type = match_type
-
-        if self.match_type == "dual_softmax":
-            self.temperature = 0.1
-        else:
-            raise NotImplementedError()
-
-    def forward(self, source_desc, target_desc):
-        b, c, h, w = source_desc.size()
-
-        source_desc = source_desc.div(
-            torch.unsqueeze(torch.norm(source_desc, p=2, dim=1), 1)
-        ).view(b, -1, h * w)
-        target_desc = target_desc.div(
-            torch.unsqueeze(torch.norm(target_desc, p=2, dim=1), 1)
-        ).view(b, -1, h * w)
-
-        if self.match_type == "dual_softmax":
-            sim_mat = (
-                torch.einsum("bcm, bcn -> bmn", source_desc, target_desc)
-                / self.temperature
-            )
-            confidence_matrix = F.softmax(sim_mat, 1) * F.softmax(sim_mat, 2)
-        else:
-            raise NotImplementedError()
-
-        return confidence_matrix
diff --git a/spaces/Realcat/image-matching-webui/third_party/r2d2/tools/__init__.py b/spaces/Realcat/image-matching-webui/third_party/r2d2/tools/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/ReyDev/Claude-Space/Dockerfile b/spaces/ReyDev/Claude-Space/Dockerfile
deleted file mode 100644
index 4eb611d275144e4c57c3e1e2016b9d03e56cb813..0000000000000000000000000000000000000000
--- a/spaces/ReyDev/Claude-Space/Dockerfile
+++ /dev/null
@@ -1,47 +0,0 @@
-FROM python:3.10
-
-# python
-ENV PYTHONUNBUFFERED=1 \
-    # prevents python creating .pyc files
-    PYTHONDONTWRITEBYTECODE=1 \
-    \
-    # pip
-    PIP_NO_CACHE_DIR=off \
-    PIP_DISABLE_PIP_VERSION_CHECK=on \
-    PIP_DEFAULT_TIMEOUT=100 \
-    \
-    # poetry
-    # https://python-poetry.org/docs/configuration/#using-environment-variables
-    POETRY_VERSION=1.3.2 \
-    # make poetry install to this location
-    POETRY_HOME="/opt/poetry" \
-    # make poetry create the virtual environment in the project's root
-    # it gets named `.venv`
-    POETRY_VIRTUALENVS_IN_PROJECT=false \
-    # do not ask any interactive question
-    POETRY_NO_INTERACTION=1 \
-    POETRY_VIRTUALENVS_CREATE=false
-
-ENV VENV_PATH="/venv"
-ENV PATH="$VENV_PATH/bin:$PATH"
-
-WORKDIR /app
-
-RUN apt-get update
-RUN curl https://sh.rustup.rs -sSf | bash -s -- -y
-ENV PATH="/root/.cargo/bin:${PATH}"
-RUN rustc --version
-
-RUN pip install wheel
-RUN apt-get update && apt-get upgrade -y && apt-get install netcat-traditional -y && apt-get install wkhtmltopdf -y
-RUN pip install --upgrade poetry
-RUN python -m venv /venv
-RUN /venv/bin/pip install --upgrade pip wheel setuptools setuptools_rust
-COPY . .
-RUN mkdir flagged
-RUN mkdir gradio_cached_examples
-
-RUN poetry install
-
-COPY . .
-CMD ["uvicorn", "claude_space.app:gd", "--host", "0.0.0.0", "--port", "7860"]
diff --git a/spaces/Robert001/UniControl-Demo/annotator/midas/midas/transforms.py b/spaces/Robert001/UniControl-Demo/annotator/midas/midas/transforms.py
deleted file mode 100644
index 94eb3e16ba8e74d46f88120c644ab0c5b9120bb1..0000000000000000000000000000000000000000
--- a/spaces/Robert001/UniControl-Demo/annotator/midas/midas/transforms.py
+++ /dev/null
@@ -1,244 +0,0 @@
-'''
- * Copyright (c) 2023 Salesforce, Inc.
- * All rights reserved.
- * SPDX-License-Identifier: Apache License 2.0
- * For full license text, see LICENSE.txt file in the repo root or http://www.apache.org/licenses/
- * By Can Qin
- * Modified from ControlNet repo: https://github.com/lllyasviel/ControlNet
- * Copyright (c) 2023 Lvmin Zhang and Maneesh Agrawala
-'''
-
-import numpy as np
-import cv2
-import math
-
-
-def apply_min_size(sample, size, image_interpolation_method=cv2.INTER_AREA):
-    """Rezise the sample to ensure the given size. Keeps aspect ratio.
-
-    Args:
-        sample (dict): sample
-        size (tuple): image size
-
-    Returns:
-        tuple: new size
-    """
-    shape = list(sample["disparity"].shape)
-
-    if shape[0] >= size[0] and shape[1] >= size[1]:
-        return sample
-
-    scale = [0, 0]
-    scale[0] = size[0] / shape[0]
-    scale[1] = size[1] / shape[1]
-
-    scale = max(scale)
-
-    shape[0] = math.ceil(scale * shape[0])
-    shape[1] = math.ceil(scale * shape[1])
-
-    # resize
-    sample["image"] = cv2.resize(
-        sample["image"], tuple(shape[::-1]), interpolation=image_interpolation_method
-    )
-
-    sample["disparity"] = cv2.resize(
-        sample["disparity"], tuple(shape[::-1]), interpolation=cv2.INTER_NEAREST
-    )
-    sample["mask"] = cv2.resize(
-        sample["mask"].astype(np.float32),
-        tuple(shape[::-1]),
-        interpolation=cv2.INTER_NEAREST,
-    )
-    sample["mask"] = sample["mask"].astype(bool)
-
-    return tuple(shape)
-
-
-class Resize(object):
-    """Resize sample to given size (width, height).
-    """
-
-    def __init__(
-        self,
-        width,
-        height,
-        resize_target=True,
-        keep_aspect_ratio=False,
-        ensure_multiple_of=1,
-        resize_method="lower_bound",
-        image_interpolation_method=cv2.INTER_AREA,
-    ):
-        """Init.
-
-        Args:
-            width (int): desired output width
-            height (int): desired output height
-            resize_target (bool, optional):
-                True: Resize the full sample (image, mask, target).
-                False: Resize image only.
-                Defaults to True.
-            keep_aspect_ratio (bool, optional):
-                True: Keep the aspect ratio of the input sample.
-                Output sample might not have the given width and height, and
-                resize behaviour depends on the parameter 'resize_method'.
-                Defaults to False.
-            ensure_multiple_of (int, optional):
-                Output width and height is constrained to be multiple of this parameter.
-                Defaults to 1.
-            resize_method (str, optional):
-                "lower_bound": Output will be at least as large as the given size.
-                "upper_bound": Output will be at max as large as the given size. (Output size might be smaller than given size.)
-                "minimal": Scale as least as possible.  (Output size might be smaller than given size.)
-                Defaults to "lower_bound".
-        """
-        self.__width = width
-        self.__height = height
-
-        self.__resize_target = resize_target
-        self.__keep_aspect_ratio = keep_aspect_ratio
-        self.__multiple_of = ensure_multiple_of
-        self.__resize_method = resize_method
-        self.__image_interpolation_method = image_interpolation_method
-
-    def constrain_to_multiple_of(self, x, min_val=0, max_val=None):
-        y = (np.round(x / self.__multiple_of) * self.__multiple_of).astype(int)
-
-        if max_val is not None and y > max_val:
-            y = (np.floor(x / self.__multiple_of) * self.__multiple_of).astype(int)
-
-        if y < min_val:
-            y = (np.ceil(x / self.__multiple_of) * self.__multiple_of).astype(int)
-
-        return y
-
-    def get_size(self, width, height):
-        # determine new height and width
-        scale_height = self.__height / height
-        scale_width = self.__width / width
-
-        if self.__keep_aspect_ratio:
-            if self.__resize_method == "lower_bound":
-                # scale such that output size is lower bound
-                if scale_width > scale_height:
-                    # fit width
-                    scale_height = scale_width
-                else:
-                    # fit height
-                    scale_width = scale_height
-            elif self.__resize_method == "upper_bound":
-                # scale such that output size is upper bound
-                if scale_width < scale_height:
-                    # fit width
-                    scale_height = scale_width
-                else:
-                    # fit height
-                    scale_width = scale_height
-            elif self.__resize_method == "minimal":
-                # scale as least as possbile
-                if abs(1 - scale_width) < abs(1 - scale_height):
-                    # fit width
-                    scale_height = scale_width
-                else:
-                    # fit height
-                    scale_width = scale_height
-            else:
-                raise ValueError(
-                    f"resize_method {self.__resize_method} not implemented"
-                )
-
-        if self.__resize_method == "lower_bound":
-            new_height = self.constrain_to_multiple_of(
-                scale_height * height, min_val=self.__height
-            )
-            new_width = self.constrain_to_multiple_of(
-                scale_width * width, min_val=self.__width
-            )
-        elif self.__resize_method == "upper_bound":
-            new_height = self.constrain_to_multiple_of(
-                scale_height * height, max_val=self.__height
-            )
-            new_width = self.constrain_to_multiple_of(
-                scale_width * width, max_val=self.__width
-            )
-        elif self.__resize_method == "minimal":
-            new_height = self.constrain_to_multiple_of(scale_height * height)
-            new_width = self.constrain_to_multiple_of(scale_width * width)
-        else:
-            raise ValueError(f"resize_method {self.__resize_method} not implemented")
-
-        return (new_width, new_height)
-
-    def __call__(self, sample):
-        width, height = self.get_size(
-            sample["image"].shape[1], sample["image"].shape[0]
-        )
-
-        # resize sample
-        sample["image"] = cv2.resize(
-            sample["image"],
-            (width, height),
-            interpolation=self.__image_interpolation_method,
-        )
-
-        if self.__resize_target:
-            if "disparity" in sample:
-                sample["disparity"] = cv2.resize(
-                    sample["disparity"],
-                    (width, height),
-                    interpolation=cv2.INTER_NEAREST,
-                )
-
-            if "depth" in sample:
-                sample["depth"] = cv2.resize(
-                    sample["depth"], (width, height), interpolation=cv2.INTER_NEAREST
-                )
-
-            sample["mask"] = cv2.resize(
-                sample["mask"].astype(np.float32),
-                (width, height),
-                interpolation=cv2.INTER_NEAREST,
-            )
-            sample["mask"] = sample["mask"].astype(bool)
-
-        return sample
-
-
-class NormalizeImage(object):
-    """Normlize image by given mean and std.
-    """
-
-    def __init__(self, mean, std):
-        self.__mean = mean
-        self.__std = std
-
-    def __call__(self, sample):
-        sample["image"] = (sample["image"] - self.__mean) / self.__std
-
-        return sample
-
-
-class PrepareForNet(object):
-    """Prepare sample for usage as network input.
-    """
-
-    def __init__(self):
-        pass
-
-    def __call__(self, sample):
-        image = np.transpose(sample["image"], (2, 0, 1))
-        sample["image"] = np.ascontiguousarray(image).astype(np.float32)
-
-        if "mask" in sample:
-            sample["mask"] = sample["mask"].astype(np.float32)
-            sample["mask"] = np.ascontiguousarray(sample["mask"])
-
-        if "disparity" in sample:
-            disparity = sample["disparity"].astype(np.float32)
-            sample["disparity"] = np.ascontiguousarray(disparity)
-
-        if "depth" in sample:
-            depth = sample["depth"].astype(np.float32)
-            sample["depth"] = np.ascontiguousarray(depth)
-
-        return sample
diff --git a/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmcv/ops/psa_mask.py b/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmcv/ops/psa_mask.py
deleted file mode 100644
index cdf14e62b50e8d4dd6856c94333c703bcc4c9ab6..0000000000000000000000000000000000000000
--- a/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmcv/ops/psa_mask.py
+++ /dev/null
@@ -1,92 +0,0 @@
-# Modified from https://github.com/hszhao/semseg/blob/master/lib/psa
-from torch import nn
-from torch.autograd import Function
-from torch.nn.modules.utils import _pair
-
-from ..utils import ext_loader
-
-ext_module = ext_loader.load_ext('_ext',
-                                 ['psamask_forward', 'psamask_backward'])
-
-
-class PSAMaskFunction(Function):
-
-    @staticmethod
-    def symbolic(g, input, psa_type, mask_size):
-        return g.op(
-            'mmcv::MMCVPSAMask',
-            input,
-            psa_type_i=psa_type,
-            mask_size_i=mask_size)
-
-    @staticmethod
-    def forward(ctx, input, psa_type, mask_size):
-        ctx.psa_type = psa_type
-        ctx.mask_size = _pair(mask_size)
-        ctx.save_for_backward(input)
-
-        h_mask, w_mask = ctx.mask_size
-        batch_size, channels, h_feature, w_feature = input.size()
-        assert channels == h_mask * w_mask
-        output = input.new_zeros(
-            (batch_size, h_feature * w_feature, h_feature, w_feature))
-
-        ext_module.psamask_forward(
-            input,
-            output,
-            psa_type=psa_type,
-            num_=batch_size,
-            h_feature=h_feature,
-            w_feature=w_feature,
-            h_mask=h_mask,
-            w_mask=w_mask,
-            half_h_mask=(h_mask - 1) // 2,
-            half_w_mask=(w_mask - 1) // 2)
-        return output
-
-    @staticmethod
-    def backward(ctx, grad_output):
-        input = ctx.saved_tensors[0]
-        psa_type = ctx.psa_type
-        h_mask, w_mask = ctx.mask_size
-        batch_size, channels, h_feature, w_feature = input.size()
-        grad_input = grad_output.new_zeros(
-            (batch_size, channels, h_feature, w_feature))
-        ext_module.psamask_backward(
-            grad_output,
-            grad_input,
-            psa_type=psa_type,
-            num_=batch_size,
-            h_feature=h_feature,
-            w_feature=w_feature,
-            h_mask=h_mask,
-            w_mask=w_mask,
-            half_h_mask=(h_mask - 1) // 2,
-            half_w_mask=(w_mask - 1) // 2)
-        return grad_input, None, None, None
-
-
-psa_mask = PSAMaskFunction.apply
-
-
-class PSAMask(nn.Module):
-
-    def __init__(self, psa_type, mask_size=None):
-        super(PSAMask, self).__init__()
-        assert psa_type in ['collect', 'distribute']
-        if psa_type == 'collect':
-            psa_type_enum = 0
-        else:
-            psa_type_enum = 1
-        self.psa_type_enum = psa_type_enum
-        self.mask_size = mask_size
-        self.psa_type = psa_type
-
-    def forward(self, input):
-        return psa_mask(input, self.psa_type_enum, self.mask_size)
-
-    def __repr__(self):
-        s = self.__class__.__name__
-        s += f'(psa_type={self.psa_type}, '
-        s += f'mask_size={self.mask_size})'
-        return s
diff --git a/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmdet/models/roi_heads/bbox_heads/__init__.py b/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmdet/models/roi_heads/bbox_heads/__init__.py
deleted file mode 100644
index bc5d29ece5bbf2f168f538f151f06d1b263a5153..0000000000000000000000000000000000000000
--- a/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmdet/models/roi_heads/bbox_heads/__init__.py
+++ /dev/null
@@ -1,13 +0,0 @@
-from .bbox_head import BBoxHead
-from .convfc_bbox_head import (ConvFCBBoxHead, Shared2FCBBoxHead,
-                               Shared4Conv1FCBBoxHead)
-from .dii_head import DIIHead
-from .double_bbox_head import DoubleConvFCBBoxHead
-from .sabl_head import SABLHead
-from .scnet_bbox_head import SCNetBBoxHead
-
-__all__ = [
-    'BBoxHead', 'ConvFCBBoxHead', 'Shared2FCBBoxHead',
-    'Shared4Conv1FCBBoxHead', 'DoubleConvFCBBoxHead', 'SABLHead', 'DIIHead',
-    'SCNetBBoxHead'
-]
diff --git a/spaces/Saba99/GPT4ALL/README.md b/spaces/Saba99/GPT4ALL/README.md
deleted file mode 100644
index 52bb9f544821e24824e7ce47d4f49db31f3f0796..0000000000000000000000000000000000000000
--- a/spaces/Saba99/GPT4ALL/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Gpt4all
-emoji: 🦀
-colorFrom: gray
-colorTo: pink
-sdk: gradio
-sdk_version: 3.24.1
-app_file: app.py
-pinned: false
-duplicated_from: Monster/GPT4ALL
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/SamerKharboush/chatGPT-Sam-Turbo/modules/utils.py b/spaces/SamerKharboush/chatGPT-Sam-Turbo/modules/utils.py
deleted file mode 100644
index ef8963d19b16e187a3381b85325d74a1a3562d64..0000000000000000000000000000000000000000
--- a/spaces/SamerKharboush/chatGPT-Sam-Turbo/modules/utils.py
+++ /dev/null
@@ -1,520 +0,0 @@
-# -*- coding:utf-8 -*-
-from __future__ import annotations
-from typing import TYPE_CHECKING, Any, Callable, Dict, List, Tuple, Type
-import logging
-import json
-import os
-import datetime
-import hashlib
-import csv
-import requests
-import re
-import html
-import sys
-import subprocess
-
-import gradio as gr
-from pypinyin import lazy_pinyin
-import tiktoken
-import mdtex2html
-from markdown import markdown
-from pygments import highlight
-from pygments.lexers import get_lexer_by_name
-from pygments.formatters import HtmlFormatter
-
-from modules.presets import *
-import modules.shared as shared
-
-logging.basicConfig(
-    level=logging.INFO,
-    format="%(asctime)s [%(levelname)s] [%(filename)s:%(lineno)d] %(message)s",
-)
-
-if TYPE_CHECKING:
-    from typing import TypedDict
-
-    class DataframeData(TypedDict):
-        headers: List[str]
-        data: List[List[str | int | bool]]
-
-
-def count_token(message):
-    encoding = tiktoken.get_encoding("cl100k_base")
-    input_str = f"role: {message['role']}, content: {message['content']}"
-    length = len(encoding.encode(input_str))
-    return length
-
-
-def markdown_to_html_with_syntax_highlight(md_str):
-    def replacer(match):
-        lang = match.group(1) or "text"
-        code = match.group(2)
-
-        try:
-            lexer = get_lexer_by_name(lang, stripall=True)
-        except ValueError:
-            lexer = get_lexer_by_name("text", stripall=True)
-
-        formatter = HtmlFormatter()
-        highlighted_code = highlight(code, lexer, formatter)
-
-        return f'<pre><code class="{lang}">{highlighted_code}</code></pre>'
-
-    code_block_pattern = r"```(\w+)?\n([\s\S]+?)\n```"
-    md_str = re.sub(code_block_pattern, replacer, md_str, flags=re.MULTILINE)
-
-    html_str = markdown(md_str)
-    return html_str
-
-
-def normalize_markdown(md_text: str) -> str:
-    lines = md_text.split("\n")
-    normalized_lines = []
-    inside_list = False
-
-    for i, line in enumerate(lines):
-        if re.match(r"^(\d+\.|-|\*|\+)\s", line.strip()):
-            if not inside_list and i > 0 and lines[i - 1].strip() != "":
-                normalized_lines.append("")
-            inside_list = True
-            normalized_lines.append(line)
-        elif inside_list and line.strip() == "":
-            if i < len(lines) - 1 and not re.match(
-                r"^(\d+\.|-|\*|\+)\s", lines[i + 1].strip()
-            ):
-                normalized_lines.append(line)
-            continue
-        else:
-            inside_list = False
-            normalized_lines.append(line)
-
-    return "\n".join(normalized_lines)
-
-
-def convert_mdtext(md_text):
-    code_block_pattern = re.compile(r"```(.*?)(?:```|$)", re.DOTALL)
-    inline_code_pattern = re.compile(r"`(.*?)`", re.DOTALL)
-    code_blocks = code_block_pattern.findall(md_text)
-    non_code_parts = code_block_pattern.split(md_text)[::2]
-
-    result = []
-    for non_code, code in zip(non_code_parts, code_blocks + [""]):
-        if non_code.strip():
-            non_code = normalize_markdown(non_code)
-            if inline_code_pattern.search(non_code):
-                result.append(markdown(non_code, extensions=["tables"]))
-            else:
-                result.append(mdtex2html.convert(non_code, extensions=["tables"]))
-        if code.strip():
-            # _, code = detect_language(code)  # 暂时去除代码高亮功能，因为在大段代码的情况下会出现问题
-            # code = code.replace("\n\n", "\n") # 暂时去除代码中的空行，因为在大段代码的情况下会出现问题
-            code = f"\n```{code}\n\n```"
-            code = markdown_to_html_with_syntax_highlight(code)
-            result.append(code)
-    result = "".join(result)
-    result += ALREADY_CONVERTED_MARK
-    return result
-
-
-def convert_asis(userinput):
-    return (
-        f'<p style="white-space:pre-wrap;">{html.escape(userinput)}</p>'
-        + ALREADY_CONVERTED_MARK
-    )
-
-
-def detect_converted_mark(userinput):
-    if userinput.endswith(ALREADY_CONVERTED_MARK):
-        return True
-    else:
-        return False
-
-
-def detect_language(code):
-    if code.startswith("\n"):
-        first_line = ""
-    else:
-        first_line = code.strip().split("\n", 1)[0]
-    language = first_line.lower() if first_line else ""
-    code_without_language = code[len(first_line) :].lstrip() if first_line else code
-    return language, code_without_language
-
-
-def construct_text(role, text):
-    return {"role": role, "content": text}
-
-
-def construct_user(text):
-    return construct_text("user", text)
-
-
-def construct_system(text):
-    return construct_text("system", text)
-
-
-def construct_assistant(text):
-    return construct_text("assistant", text)
-
-
-def construct_token_message(token, stream=False):
-    return f"Token 计数: {token}"
-
-
-def delete_first_conversation(history, previous_token_count):
-    if history:
-        del history[:2]
-        del previous_token_count[0]
-    return (
-        history,
-        previous_token_count,
-        construct_token_message(sum(previous_token_count)),
-    )
-
-
-def delete_last_conversation(chatbot, history, previous_token_count):
-    if len(chatbot) > 0 and standard_error_msg in chatbot[-1][1]:
-        logging.info("由于包含报错信息，只删除chatbot记录")
-        chatbot.pop()
-        return chatbot, history
-    if len(history) > 0:
-        logging.info("删除了一组对话历史")
-        history.pop()
-        history.pop()
-    if len(chatbot) > 0:
-        logging.info("删除了一组chatbot对话")
-        chatbot.pop()
-    if len(previous_token_count) > 0:
-        logging.info("删除了一组对话的token计数记录")
-        previous_token_count.pop()
-    return (
-        chatbot,
-        history,
-        previous_token_count,
-        construct_token_message(sum(previous_token_count)),
-    )
-
-
-def save_file(filename, system, history, chatbot):
-    logging.info("保存对话历史中……")
-    os.makedirs(HISTORY_DIR, exist_ok=True)
-    if filename.endswith(".json"):
-        json_s = {"system": system, "history": history, "chatbot": chatbot}
-        print(json_s)
-        with open(os.path.join(HISTORY_DIR, filename), "w") as f:
-            json.dump(json_s, f)
-    elif filename.endswith(".md"):
-        md_s = f"system: \n- {system} \n"
-        for data in history:
-            md_s += f"\n{data['role']}: \n- {data['content']} \n"
-        with open(os.path.join(HISTORY_DIR, filename), "w", encoding="utf8") as f:
-            f.write(md_s)
-    logging.info("保存对话历史完毕")
-    return os.path.join(HISTORY_DIR, filename)
-
-
-def save_chat_history(filename, system, history, chatbot):
-    if filename == "":
-        return
-    if not filename.endswith(".json"):
-        filename += ".json"
-    return save_file(filename, system, history, chatbot)
-
-
-def export_markdown(filename, system, history, chatbot):
-    if filename == "":
-        return
-    if not filename.endswith(".md"):
-        filename += ".md"
-    return save_file(filename, system, history, chatbot)
-
-
-def load_chat_history(filename, system, history, chatbot):
-    logging.info("加载对话历史中……")
-    if type(filename) != str:
-        filename = filename.name
-    try:
-        with open(os.path.join(HISTORY_DIR, filename), "r") as f:
-            json_s = json.load(f)
-        try:
-            if type(json_s["history"][0]) == str:
-                logging.info("历史记录格式为旧版，正在转换……")
-                new_history = []
-                for index, item in enumerate(json_s["history"]):
-                    if index % 2 == 0:
-                        new_history.append(construct_user(item))
-                    else:
-                        new_history.append(construct_assistant(item))
-                json_s["history"] = new_history
-                logging.info(new_history)
-        except:
-            # 没有对话历史
-            pass
-        logging.info("加载对话历史完毕")
-        return filename, json_s["system"], json_s["history"], json_s["chatbot"]
-    except FileNotFoundError:
-        logging.info("没有找到对话历史文件，不执行任何操作")
-        return filename, system, history, chatbot
-
-
-def sorted_by_pinyin(list):
-    return sorted(list, key=lambda char: lazy_pinyin(char)[0][0])
-
-
-def get_file_names(dir, plain=False, filetypes=[".json"]):
-    logging.info(f"获取文件名列表，目录为{dir}，文件类型为{filetypes}，是否为纯文本列表{plain}")
-    files = []
-    try:
-        for type in filetypes:
-            files += [f for f in os.listdir(dir) if f.endswith(type)]
-    except FileNotFoundError:
-        files = []
-    files = sorted_by_pinyin(files)
-    if files == []:
-        files = [""]
-    if plain:
-        return files
-    else:
-        return gr.Dropdown.update(choices=files)
-
-
-def get_history_names(plain=False):
-    logging.info("获取历史记录文件名列表")
-    return get_file_names(HISTORY_DIR, plain)
-
-
-def load_template(filename, mode=0):
-    logging.info(f"加载模板文件{filename}，模式为{mode}（0为返回字典和下拉菜单，1为返回下拉菜单，2为返回字典）")
-    lines = []
-    logging.info("Loading template...")
-    if filename.endswith(".json"):
-        with open(os.path.join(TEMPLATES_DIR, filename), "r", encoding="utf8") as f:
-            lines = json.load(f)
-        lines = [[i["act"], i["prompt"]] for i in lines]
-    else:
-        with open(
-            os.path.join(TEMPLATES_DIR, filename), "r", encoding="utf8"
-        ) as csvfile:
-            reader = csv.reader(csvfile)
-            lines = list(reader)
-        lines = lines[1:]
-    if mode == 1:
-        return sorted_by_pinyin([row[0] for row in lines])
-    elif mode == 2:
-        return {row[0]: row[1] for row in lines}
-    else:
-        choices = sorted_by_pinyin([row[0] for row in lines])
-        return {row[0]: row[1] for row in lines}, gr.Dropdown.update(
-            choices=choices, value=choices[0]
-        )
-
-
-def get_template_names(plain=False):
-    logging.info("获取模板文件名列表")
-    return get_file_names(TEMPLATES_DIR, plain, filetypes=[".csv", "json"])
-
-
-def get_template_content(templates, selection, original_system_prompt):
-    logging.info(f"应用模板中，选择为{selection}，原始系统提示为{original_system_prompt}")
-    try:
-        return templates[selection]
-    except:
-        return original_system_prompt
-
-
-def reset_state():
-    logging.info("重置状态")
-    return [], [], [], construct_token_message(0)
-
-
-def reset_textbox():
-    logging.debug("重置文本框")
-    return gr.update(value="")
-
-
-def reset_default():
-    newurl = shared.state.reset_api_url()
-    os.environ.pop("HTTPS_PROXY", None)
-    os.environ.pop("https_proxy", None)
-    return gr.update(value=newurl), gr.update(value=""), "API URL 和代理已重置"
-
-
-def change_api_url(url):
-    shared.state.set_api_url(url)
-    msg = f"API地址更改为了{url}"
-    logging.info(msg)
-    return msg
-
-
-def change_proxy(proxy):
-    os.environ["HTTPS_PROXY"] = proxy
-    msg = f"代理更改为了{proxy}"
-    logging.info(msg)
-    return msg
-
-
-def hide_middle_chars(s):
-    if s is None:
-        return ""
-    if len(s) <= 8:
-        return s
-    else:
-        head = s[:4]
-        tail = s[-4:]
-        hidden = "*" * (len(s) - 8)
-        return head + hidden + tail
-
-
-def submit_key(key):
-    key = key.strip()
-    msg = f"API密钥更改为了{hide_middle_chars(key)}"
-    logging.info(msg)
-    return key, msg
-
-
-def replace_today(prompt):
-    today = datetime.datetime.today().strftime("%Y-%m-%d")
-    return prompt.replace("{current_date}", today)
-
-
-def get_geoip():
-    try:
-        response = requests.get("https://ipapi.co/json/", timeout=5)
-        data = response.json()
-    except:
-        data = {"error": True, "reason": "连接ipapi失败"}
-    if "error" in data.keys():
-        logging.warning(f"无法获取IP地址信息。\n{data}")
-        if data["reason"] == "RateLimited":
-            return (
-                f"获取IP地理位置失败，因为达到了检测IP的速率限制。聊天功能可能仍然可用。"
-            )
-        else:
-            return f"获取IP地理位置失败。原因：{data['reason']}。你仍然可以使用聊天功能。"
-    else:
-        country = data["country_name"]
-        if country == "China":
-            text = "**您的IP区域：中国。请立即检查代理设置，在不受支持的地区使用API可能导致账号被封禁。**"
-        else:
-            text = f"您的IP区域：{country}。"
-        logging.info(text)
-        return text
-
-
-def find_n(lst, max_num):
-    n = len(lst)
-    total = sum(lst)
-
-    if total < max_num:
-        return n
-
-    for i in range(len(lst)):
-        if total - lst[i] < max_num:
-            return n - i - 1
-        total = total - lst[i]
-    return 1
-
-
-def start_outputing():
-    logging.debug("显示取消按钮，隐藏发送按钮")
-    return gr.Button.update(visible=False), gr.Button.update(visible=True)
-
-
-def end_outputing():
-    return (
-        gr.Button.update(visible=True),
-        gr.Button.update(visible=False),
-    )
-
-
-def cancel_outputing():
-    logging.info("中止输出……")
-    shared.state.interrupt()
-
-
-def transfer_input(inputs):
-    # 一次性返回，降低延迟
-    textbox = reset_textbox()
-    outputing = start_outputing()
-    return (
-        inputs,
-        gr.update(value=""),
-        gr.Button.update(visible=True),
-        gr.Button.update(visible=False),
-    )
-
-
-def get_proxies():
-    # 获取环境变量中的代理设置
-    http_proxy = os.environ.get("HTTP_PROXY") or os.environ.get("http_proxy")
-    https_proxy = os.environ.get("HTTPS_PROXY") or os.environ.get("https_proxy")
-
-    # 如果存在代理设置，使用它们
-    proxies = {}
-    if http_proxy:
-        logging.info(f"使用 HTTP 代理: {http_proxy}")
-        proxies["http"] = http_proxy
-    if https_proxy:
-        logging.info(f"使用 HTTPS 代理: {https_proxy}")
-        proxies["https"] = https_proxy
-
-    if proxies == {}:
-        proxies = None
-
-    return proxies
-
-def run(command, desc=None, errdesc=None, custom_env=None, live=False):
-    if desc is not None:
-        print(desc)
-    if live:
-        result = subprocess.run(command, shell=True, env=os.environ if custom_env is None else custom_env)
-        if result.returncode != 0:
-            raise RuntimeError(f"""{errdesc or 'Error running command'}.
-Command: {command}
-Error code: {result.returncode}""")
-
-        return ""
-    result = subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True, env=os.environ if custom_env is None else custom_env)
-    if result.returncode != 0:
-        message = f"""{errdesc or 'Error running command'}.
-Command: {command}
-Error code: {result.returncode}
-stdout: {result.stdout.decode(encoding="utf8", errors="ignore") if len(result.stdout)>0 else '<empty>'}
-stderr: {result.stderr.decode(encoding="utf8", errors="ignore") if len(result.stderr)>0 else '<empty>'}
-"""
-        raise RuntimeError(message)
-    return result.stdout.decode(encoding="utf8", errors="ignore")
-
-def versions_html():
-    git = os.environ.get('GIT', "git")
-    python_version = ".".join([str(x) for x in sys.version_info[0:3]])
-    try:
-        commit_hash = run(f"{git} rev-parse HEAD").strip()
-    except Exception:
-        commit_hash = "<none>"
-    if commit_hash != "<none>":
-        short_commit = commit_hash[0:7]
-        commit_info = f"<a style=\"text-decoration:none\" href=\"https://github.com/GaiZhenbiao/ChuanhuChatGPT/commit/{short_commit}\">{short_commit}</a>"
-    else:
-        commit_info = "unknown \U0001F615"
-    return f"""
-Python: <span title="{sys.version}">{python_version}</span>
- • 
-Gradio: {gr.__version__}
- • 
-Commit: {commit_info}
-"""
-
-def add_source_numbers(lst, source_name = "Source", use_source = True):
-    if use_source:
-        return [f'[{idx+1}]\t "{item[0]}"\n{source_name}: {item[1]}' for idx, item in enumerate(lst)]
-    else:
-        return [f'[{idx+1}]\t "{item}"' for idx, item in enumerate(lst)]
-
-def add_details(lst):
-    nodes = []
-    for index, txt in enumerate(lst):
-        brief = txt[:25].replace("\n", "")
-        nodes.append(
-            f"<details><summary>{brief}...</summary><p>{txt}</p></details>"
-        )
-    return nodes
diff --git a/spaces/ScottRobertsXR/image-captioning-01/README.md b/spaces/ScottRobertsXR/image-captioning-01/README.md
deleted file mode 100644
index 05c3c76bd671ba1dcf306cec8dbbaf2b7e8b3037..0000000000000000000000000000000000000000
--- a/spaces/ScottRobertsXR/image-captioning-01/README.md
+++ /dev/null
@@ -1,34 +0,0 @@
----
-title: Image Captioning
-emoji: 🖼️
-colorFrom: pink
-colorTo: red
-sdk: streamlit
-app_file: app.py
-pinned: false
-duplicated_from: flax-community/image-captioning
----
-
-# Configuration
-
-`title`: _string_  
-Display title for the Space
-
-`emoji`: _string_  
-Space emoji (emoji-only character allowed)
-
-`colorFrom`: _string_  
-Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
-
-`colorTo`: _string_  
-Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
-
-`sdk`: _string_  
-Can be either `gradio` or `streamlit`
-
-`app_file`: _string_  
-Path to your main application file (which contains either `gradio` or `streamlit` Python code).  
-Path is relative to the root of the repository.
-
-`pinned`: _boolean_  
-Whether the Space stays on top of your list.
diff --git a/spaces/ServerX/PorcoDiaz/infer/modules/vc/pipeline.py b/spaces/ServerX/PorcoDiaz/infer/modules/vc/pipeline.py
deleted file mode 100644
index 76e712c649b95e21f9bbe6416ae8b7050317b479..0000000000000000000000000000000000000000
--- a/spaces/ServerX/PorcoDiaz/infer/modules/vc/pipeline.py
+++ /dev/null
@@ -1,655 +0,0 @@
-import os
-import sys
-import traceback
-import logging
-
-logger = logging.getLogger(__name__)
-
-from functools import lru_cache
-from time import time as ttime
-from torch import Tensor
-import faiss
-import librosa
-import numpy as np
-import parselmouth
-import pyworld
-import torch
-import torch.nn.functional as F
-import torchcrepe
-from scipy import signal
-from tqdm import tqdm
-
-import random
-now_dir = os.getcwd()
-sys.path.append(now_dir)
-import re
-from functools import partial
-bh, ah = signal.butter(N=5, Wn=48, btype="high", fs=16000)
-
-input_audio_path2wav = {}
-from LazyImport import lazyload
-torchcrepe = lazyload("torchcrepe")  # Fork Feature. Crepe algo for training and preprocess
-torch = lazyload("torch")
-from infer.lib.rmvpe import RMVPE
-
-@lru_cache
-def cache_harvest_f0(input_audio_path, fs, f0max, f0min, frame_period):
-    audio = input_audio_path2wav[input_audio_path]
-    f0, t = pyworld.harvest(
-        audio,
-        fs=fs,
-        f0_ceil=f0max,
-        f0_floor=f0min,
-        frame_period=frame_period,
-    )
-    f0 = pyworld.stonemask(audio, f0, t, fs)
-    return f0
-
-
-def change_rms(data1, sr1, data2, sr2, rate):  # 1是输入音频，2是输出音频,rate是2的占比
-    # print(data1.max(),data2.max())
-    rms1 = librosa.feature.rms(
-        y=data1, frame_length=sr1 // 2 * 2, hop_length=sr1 // 2
-    )  # 每半秒一个点
-    rms2 = librosa.feature.rms(y=data2, frame_length=sr2 // 2 * 2, hop_length=sr2 // 2)
-    rms1 = torch.from_numpy(rms1)
-    rms1 = F.interpolate(
-        rms1.unsqueeze(0), size=data2.shape[0], mode="linear"
-    ).squeeze()
-    rms2 = torch.from_numpy(rms2)
-    rms2 = F.interpolate(
-        rms2.unsqueeze(0), size=data2.shape[0], mode="linear"
-    ).squeeze()
-    rms2 = torch.max(rms2, torch.zeros_like(rms2) + 1e-6)
-    data2 *= (
-        torch.pow(rms1, torch.tensor(1 - rate))
-        * torch.pow(rms2, torch.tensor(rate - 1))
-    ).numpy()
-    return data2
-
-
-class Pipeline(object):
-    def __init__(self, tgt_sr, config):
-        self.x_pad, self.x_query, self.x_center, self.x_max, self.is_half = (
-            config.x_pad,
-            config.x_query,
-            config.x_center,
-            config.x_max,
-            config.is_half,
-        )
-        self.sr = 16000  # hubert输入采样率
-        self.window = 160  # 每帧点数
-        self.t_pad = self.sr * self.x_pad  # 每条前后pad时间
-        self.t_pad_tgt = tgt_sr * self.x_pad
-        self.t_pad2 = self.t_pad * 2
-        self.t_query = self.sr * self.x_query  # 查询切点前后查询时间
-        self.t_center = self.sr * self.x_center  # 查询切点位置
-        self.t_max = self.sr * self.x_max  # 免查询时长阈值
-        self.device = config.device
-        self.model_rmvpe = RMVPE("%s/rmvpe.pt" % os.environ["rmvpe_root"], is_half=self.is_half, device=self.device)
-        self.f0_method_dict = {
-            "pm": self.get_pm,
-            "harvest": self.get_harvest,
-            "dio": self.get_dio,
-            "rmvpe": self.get_rmvpe,
-            "rmvpe+": self.get_pitch_dependant_rmvpe,
-            "crepe": self.get_f0_official_crepe_computation,
-            "crepe-tiny": partial(self.get_f0_official_crepe_computation, model='model'),
-            "mangio-crepe": self.get_f0_crepe_computation,
-            "mangio-crepe-tiny": partial(self.get_f0_crepe_computation, model='model'),
-            
-        }
-        self.note_dict = [
-            65.41, 69.30, 73.42, 77.78, 82.41, 87.31,
-            92.50, 98.00, 103.83, 110.00, 116.54, 123.47,
-            130.81, 138.59, 146.83, 155.56, 164.81, 174.61,
-            185.00, 196.00, 207.65, 220.00, 233.08, 246.94,
-            261.63, 277.18, 293.66, 311.13, 329.63, 349.23,
-            369.99, 392.00, 415.30, 440.00, 466.16, 493.88,
-            523.25, 554.37, 587.33, 622.25, 659.25, 698.46,
-            739.99, 783.99, 830.61, 880.00, 932.33, 987.77,
-            1046.50, 1108.73, 1174.66, 1244.51, 1318.51, 1396.91,
-            1479.98, 1567.98, 1661.22, 1760.00, 1864.66, 1975.53,
-            2093.00, 2217.46, 2349.32, 2489.02, 2637.02, 2793.83,
-            2959.96, 3135.96, 3322.44, 3520.00, 3729.31, 3951.07
-        ]
-
-    # Fork Feature: Get the best torch device to use for f0 algorithms that require a torch device. Will return the type (torch.device)
-    def get_optimal_torch_device(self, index: int = 0) -> torch.device:
-        if torch.cuda.is_available():
-            return torch.device(
-                f"cuda:{index % torch.cuda.device_count()}"
-            )  # Very fast
-        elif torch.backends.mps.is_available():
-            return torch.device("mps")
-        return torch.device("cpu")
-
-    # Fork Feature: Compute f0 with the crepe method
-    def get_f0_crepe_computation(
-        self,
-        x,
-        f0_min,
-        f0_max,
-        p_len,
-        *args,  # 512 before. Hop length changes the speed that the voice jumps to a different dramatic pitch. Lower hop lengths means more pitch accuracy but longer inference time.
-        **kwargs,  # Either use crepe-tiny "tiny" or crepe "full". Default is full
-    ):
-        x = x.astype(
-            np.float32
-        )  # fixes the F.conv2D exception. We needed to convert double to float.
-        x /= np.quantile(np.abs(x), 0.999)
-        torch_device = self.get_optimal_torch_device()
-        audio = torch.from_numpy(x).to(torch_device, copy=True)
-        audio = torch.unsqueeze(audio, dim=0)
-        if audio.ndim == 2 and audio.shape[0] > 1:
-            audio = torch.mean(audio, dim=0, keepdim=True).detach()
-        audio = audio.detach()
-        hop_length = kwargs.get('crepe_hop_length', 160)
-        model = kwargs.get('model', 'full') 
-        print("Initiating prediction with a crepe_hop_length of: " + str(hop_length))
-        pitch: Tensor = torchcrepe.predict(
-            audio,
-            self.sr,
-            hop_length,
-            f0_min,
-            f0_max,
-            model,
-            batch_size=hop_length * 2,
-            device=torch_device,
-            pad=True,
-        )
-        p_len = p_len or x.shape[0] // hop_length
-        # Resize the pitch for final f0
-        source = np.array(pitch.squeeze(0).cpu().float().numpy())
-        source[source < 0.001] = np.nan
-        target = np.interp(
-            np.arange(0, len(source) * p_len, len(source)) / p_len,
-            np.arange(0, len(source)),
-            source,
-        )
-        f0 = np.nan_to_num(target)
-        return f0  # Resized f0
-    
-    def get_f0_official_crepe_computation(
-        self,
-        x,
-        f0_min,
-        f0_max,
-        *args,
-        **kwargs
-    ):
-        # Pick a batch size that doesn't cause memory errors on your gpu
-        batch_size = 512
-        # Compute pitch using first gpu
-        audio = torch.tensor(np.copy(x))[None].float()
-        model = kwargs.get('model', 'full') 
-        f0, pd = torchcrepe.predict(
-            audio,
-            self.sr,
-            self.window,
-            f0_min,
-            f0_max,
-            model,
-            batch_size=batch_size,
-            device=self.device,
-            return_periodicity=True,
-        )
-        pd = torchcrepe.filter.median(pd, 3)
-        f0 = torchcrepe.filter.mean(f0, 3)
-        f0[pd < 0.1] = 0
-        f0 = f0[0].cpu().numpy()
-        return f0
-
-    # Fork Feature: Compute pYIN f0 method
-    def get_f0_pyin_computation(self, x, f0_min, f0_max):
-        y, sr = librosa.load("saudio/Sidney.wav", self.sr, mono=True)
-        f0, _, _ = librosa.pyin(y, sr=self.sr, fmin=f0_min, fmax=f0_max)
-        f0 = f0[1:]  # Get rid of extra first frame
-        return f0
-
-    def get_pm(self, x, p_len, *args, **kwargs):
-        f0 = parselmouth.Sound(x, self.sr).to_pitch_ac(
-            time_step=160 / 16000,
-            voicing_threshold=0.6,
-            pitch_floor=kwargs.get('f0_min'),
-            pitch_ceiling=kwargs.get('f0_max'),
-        ).selected_array["frequency"]
-        
-        return np.pad(
-            f0,
-            [[max(0, (p_len - len(f0) + 1) // 2), max(0, p_len - len(f0) - (p_len - len(f0) + 1) // 2)]],
-            mode="constant"
-        )
-
-    def get_harvest(self, x, *args, **kwargs):
-        f0_spectral = pyworld.harvest(
-            x.astype(np.double),
-            fs=self.sr,
-            f0_ceil=kwargs.get('f0_max'),
-            f0_floor=kwargs.get('f0_min'),
-            frame_period=1000 * kwargs.get('hop_length', 160) / self.sr,
-        )
-        return pyworld.stonemask(x.astype(np.double), *f0_spectral, self.sr)
-
-    def get_dio(self, x, *args, **kwargs):
-        f0_spectral = pyworld.dio(
-            x.astype(np.double),
-            fs=self.sr,
-            f0_ceil=kwargs.get('f0_max'),
-            f0_floor=kwargs.get('f0_min'),
-            frame_period=1000 * kwargs.get('hop_length', 160) / self.sr,
-        )
-        return pyworld.stonemask(x.astype(np.double), *f0_spectral, self.sr)
-
-
-    def get_rmvpe(self, x, *args, **kwargs):
-        if not hasattr(self, "model_rmvpe"):
-            from infer.lib.rmvpe import RMVPE
-            
-            logger.info(
-                "Loading rmvpe model,%s" % "%s/rmvpe.pt" % os.environ["rmvpe_root"]
-            )
-            self.model_rmvpe = RMVPE(
-                "%s/rmvpe.pt" % os.environ["rmvpe_root"],
-                is_half=self.is_half,
-                device=self.device,
-            )
-        f0 = self.model_rmvpe.infer_from_audio(x, thred=0.03)
-            
-        return f0
-    
-
-    def get_pitch_dependant_rmvpe(self, x, f0_min=1, f0_max=40000, *args, **kwargs):
-        return self.model_rmvpe.infer_from_audio_with_pitch(x, thred=0.03, f0_min=f0_min, f0_max=f0_max)
-
-    def autotune_f0(self, f0):
-        autotuned_f0 = []
-        for freq in f0:
-            closest_notes = [x for x in self.note_dict if abs(x - freq) == min(abs(n - freq) for n in self.note_dict)]
-            autotuned_f0.append(random.choice(closest_notes))
-        return np.array(autotuned_f0, np.float64)
-
-    # Fork Feature: Acquire median hybrid f0 estimation calculation
-    def get_f0_hybrid_computation(
-        self,
-        methods_str,
-        input_audio_path,
-        x,
-        f0_min,
-        f0_max,
-        p_len,
-        filter_radius,
-        crepe_hop_length,
-        time_step
-    ):
-        # Get various f0 methods from input to use in the computation stack
-        params = {'x': x, 'p_len': p_len, 'f0_min': f0_min, 
-          'f0_max': f0_max, 'time_step': time_step, 'filter_radius': filter_radius, 
-          'crepe_hop_length': crepe_hop_length, 'model': "full"
-        }
-        methods_str = re.search('hybrid\[(.+)\]', methods_str)
-        if methods_str:  # Ensure a match was found
-            methods = [method.strip() for method in methods_str.group(1).split('+')]
-        f0_computation_stack = []
-
-        print(f"Calculating f0 pitch estimations for methods: {str(methods)}")
-        x = x.astype(np.float32)
-        x /= np.quantile(np.abs(x), 0.999)
-        # Get f0 calculations for all methods specified
-
-        for method in methods:
-            if method not in self.f0_method_dict:
-                print(f"Method {method} not found.")
-                continue
-            f0 = self.f0_method_dict[method](**params)
-            if method == 'harvest' and filter_radius > 2:
-                f0 = signal.medfilt(f0, 3)
-                f0 = f0[1:]  # Get rid of first frame.
-            f0_computation_stack.append(f0)
-
-        for fc in f0_computation_stack:
-            print(len(fc))
-
-        print(f"Calculating hybrid median f0 from the stack of: {str(methods)}")
-        f0_median_hybrid = np.nanmedian(f0_computation_stack, axis=0)
-        return f0_median_hybrid
-    
-    def get_f0(
-        self,
-        input_audio_path,
-        x,
-        p_len,
-        f0_up_key,
-        f0_method,
-        filter_radius,
-        crepe_hop_length,
-        f0_autotune,
-        inp_f0=None,
-        f0_min=50,
-        f0_max=1100,
-    ):
-        global input_audio_path2wav
-        time_step = self.window / self.sr * 1000
-        f0_min = 50
-        f0_max = 1100
-        f0_mel_min = 1127 * np.log(1 + f0_min / 700)
-        f0_mel_max = 1127 * np.log(1 + f0_max / 700)
-        params = {'x': x, 'p_len': p_len, 'f0_up_key': f0_up_key, 'f0_min': f0_min, 
-          'f0_max': f0_max, 'time_step': time_step, 'filter_radius': filter_radius, 
-          'crepe_hop_length': crepe_hop_length, 'model': "full"
-        }
-
-        if "hybrid" in f0_method:
-            # Perform hybrid median pitch estimation
-            input_audio_path2wav[input_audio_path] = x.astype(np.double)
-            f0 = self.get_f0_hybrid_computation(
-                f0_method,+
-                input_audio_path,
-                x,
-                f0_min,
-                f0_max,
-                p_len,
-                filter_radius,
-                crepe_hop_length,
-                time_step,
-            )
-        else:
-            f0 = self.f0_method_dict[f0_method](**params)
-
-        if "privateuseone" in str(self.device):  # clean ortruntime memory
-            del self.model_rmvpe.model
-            del self.model_rmvpe
-            logger.info("Cleaning ortruntime memory")
-
-        if f0_autotune:
-            f0 = self.autotune_f0(f0)
-
-        f0 *= pow(2, f0_up_key / 12)
-        # with open("test.txt","w")as f:f.write("\n".join([str(i)for i in f0.tolist()]))
-        tf0 = self.sr // self.window  # 每秒f0点数
-        if inp_f0 is not None:
-            delta_t = np.round(
-                (inp_f0[:, 0].max() - inp_f0[:, 0].min()) * tf0 + 1
-            ).astype("int16")
-            replace_f0 = np.interp(
-                list(range(delta_t)), inp_f0[:, 0] * 100, inp_f0[:, 1]
-            )
-            shape = f0[self.x_pad * tf0 : self.x_pad * tf0 + len(replace_f0)].shape[0]
-            f0[self.x_pad * tf0 : self.x_pad * tf0 + len(replace_f0)] = replace_f0[
-                :shape
-            ]
-        # with open("test_opt.txt","w")as f:f.write("\n".join([str(i)for i in f0.tolist()]))
-        f0bak = f0.copy()
-        f0_mel = 1127 * np.log(1 + f0 / 700)
-        f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - f0_mel_min) * 254 / (
-            f0_mel_max - f0_mel_min
-        ) + 1
-        f0_mel[f0_mel <= 1] = 1
-        f0_mel[f0_mel > 255] = 255
-        f0_coarse = np.rint(f0_mel).astype(np.int32)
-        return f0_coarse, f0bak  # 1-0
-
-    def vc(
-        self,
-        model,
-        net_g,
-        sid,
-        audio0,
-        pitch,
-        pitchf,
-        times,
-        index,
-        big_npy,
-        index_rate,
-        version,
-        protect,
-    ):  # ,file_index,file_big_npy
-        feats = torch.from_numpy(audio0)
-        if self.is_half:
-            feats = feats.half()
-        else:
-            feats = feats.float()
-        if feats.dim() == 2:  # double channels
-            feats = feats.mean(-1)
-        assert feats.dim() == 1, feats.dim()
-        feats = feats.view(1, -1)
-        padding_mask = torch.BoolTensor(feats.shape).to(self.device).fill_(False)
-
-        inputs = {
-            "source": feats.to(self.device),
-            "padding_mask": padding_mask,
-            "output_layer": 9 if version == "v1" else 12,
-        }
-        t0 = ttime()
-        with torch.no_grad():
-            logits = model.extract_features(**inputs)
-            feats = model.final_proj(logits[0]) if version == "v1" else logits[0]
-        if protect < 0.5 and pitch is not None and pitchf is not None:
-            feats0 = feats.clone()
-        if (
-            not isinstance(index, type(None))
-            and not isinstance(big_npy, type(None))
-            and index_rate != 0
-        ):
-            npy = feats[0].cpu().numpy()
-            if self.is_half:
-                npy = npy.astype("float32")
-
-            # _, I = index.search(npy, 1)
-            # npy = big_npy[I.squeeze()]
-
-            score, ix = index.search(npy, k=8)
-            weight = np.square(1 / score)
-            weight /= weight.sum(axis=1, keepdims=True)
-            npy = np.sum(big_npy[ix] * np.expand_dims(weight, axis=2), axis=1)
-
-            if self.is_half:
-                npy = npy.astype("float16")
-            feats = (
-                torch.from_numpy(npy).unsqueeze(0).to(self.device) * index_rate
-                + (1 - index_rate) * feats
-            )
-
-        feats = F.interpolate(feats.permute(0, 2, 1), scale_factor=2).permute(0, 2, 1)
-        if protect < 0.5 and pitch is not None and pitchf is not None:
-            feats0 = F.interpolate(feats0.permute(0, 2, 1), scale_factor=2).permute(
-                0, 2, 1
-            )
-        t1 = ttime()
-        p_len = audio0.shape[0] // self.window
-        if feats.shape[1] < p_len:
-            p_len = feats.shape[1]
-            if pitch is not None and pitchf is not None:
-                pitch = pitch[:, :p_len]
-                pitchf = pitchf[:, :p_len]
-
-        if protect < 0.5 and pitch is not None and pitchf is not None:
-            pitchff = pitchf.clone()
-            pitchff[pitchf > 0] = 1
-            pitchff[pitchf < 1] = protect
-            pitchff = pitchff.unsqueeze(-1)
-            feats = feats * pitchff + feats0 * (1 - pitchff)
-            feats = feats.to(feats0.dtype)
-        p_len = torch.tensor([p_len], device=self.device).long()
-        with torch.no_grad():
-            hasp = pitch is not None and pitchf is not None
-            arg = (feats, p_len, pitch, pitchf, sid) if hasp else (feats, p_len, sid)
-            audio1 = (net_g.infer(*arg)[0][0, 0]).data.cpu().float().numpy()
-            del hasp, arg
-        del feats, p_len, padding_mask
-        if torch.cuda.is_available():
-            torch.cuda.empty_cache()
-        t2 = ttime()
-        times[0] += t1 - t0
-        times[2] += t2 - t1
-        return audio1
-    def process_t(self, t, s, window, audio_pad, pitch, pitchf, times, index, big_npy, index_rate, version, protect, t_pad_tgt, if_f0, sid, model, net_g):
-        t = t // window * window
-        if if_f0 == 1:
-            return self.vc(
-                model,
-                net_g,
-                sid,
-                audio_pad[s : t + t_pad_tgt + window],
-                pitch[:, s // window : (t + t_pad_tgt) // window],
-                pitchf[:, s // window : (t + t_pad_tgt) // window],
-                times,
-                index,
-                big_npy,
-                index_rate,
-                version,
-                protect,
-            )[t_pad_tgt : -t_pad_tgt]
-        else:
-            return self.vc(
-                model,
-                net_g,
-                sid,
-                audio_pad[s : t + t_pad_tgt + window],
-                None,
-                None,
-                times,
-                index,
-                big_npy,
-                index_rate,
-                version,
-                protect,
-            )[t_pad_tgt : -t_pad_tgt]
-
-
-    def pipeline(
-        self,
-        model,
-        net_g,
-        sid,
-        audio,
-        input_audio_path,
-        times,
-        f0_up_key,
-        f0_method,
-        file_index,
-        index_rate,
-        if_f0,
-        filter_radius,
-        tgt_sr,
-        resample_sr,
-        rms_mix_rate,
-        version,
-        protect,
-        crepe_hop_length, 
-        f0_autotune, 
-        f0_file=None, 
-        f0_min=50, 
-        f0_max=1100
-    ):
-        if (
-            file_index != ""
-            # and file_big_npy != ""
-            # and os.path.exists(file_big_npy) == True
-            and os.path.exists(file_index)
-            and index_rate != 0
-        ):
-            try:
-                index = faiss.read_index(file_index)
-                # big_npy = np.load(file_big_npy)
-                big_npy = index.reconstruct_n(0, index.ntotal)
-            except:
-                traceback.print_exc()
-                index = big_npy = None
-        else:
-            index = big_npy = None
-        audio = signal.filtfilt(bh, ah, audio)
-        audio_pad = np.pad(audio, (self.window // 2, self.window // 2), mode="reflect")
-        opt_ts = []
-        if audio_pad.shape[0] > self.t_max:
-            audio_sum = np.zeros_like(audio)
-            for i in range(self.window):
-                audio_sum += audio_pad[i : i - self.window]
-            for t in range(self.t_center, audio.shape[0], self.t_center):
-                opt_ts.append(
-                    t
-                    - self.t_query
-                    + np.where(
-                        np.abs(audio_sum[t - self.t_query : t + self.t_query])
-                        == np.abs(audio_sum[t - self.t_query : t + self.t_query]).min()
-                    )[0][0]
-                )
-        s = 0
-        audio_opt = []
-        t = None
-        t1 = ttime()
-        audio_pad = np.pad(audio, (self.t_pad, self.t_pad), mode="reflect")
-        p_len = audio_pad.shape[0] // self.window
-        inp_f0 = None
-        if hasattr(f0_file, "name"):
-            try:
-                with open(f0_file.name, "r") as f:
-                    lines = f.read().strip("\n").split("\n")
-                inp_f0 = []
-                for line in lines:
-                    inp_f0.append([float(i) for i in line.split(",")])
-                inp_f0 = np.array(inp_f0, dtype="float32")
-            except:
-                traceback.print_exc()
-        sid = torch.tensor(sid, device=self.device).unsqueeze(0).long()
-        pitch, pitchf = None, None
-        if if_f0:
-            pitch, pitchf = self.get_f0(
-                input_audio_path,
-                audio_pad,
-                p_len,
-                f0_up_key,
-                f0_method,
-                filter_radius, 
-                crepe_hop_length, 
-                f0_autotune,
-                inp_f0, 
-                f0_min, 
-                f0_max
-            )
-            pitch = pitch[:p_len]
-            pitchf = pitchf[:p_len]
-            if self.device == "mps" or "xpu" in self.device:
-                pitchf = pitchf.astype(np.float32)
-            pitch = torch.tensor(pitch, device=self.device).unsqueeze(0).long()
-            pitchf = torch.tensor(pitchf, device=self.device).unsqueeze(0).float()
-        t2 = ttime()
-        times[1] += t2 - t1
-
-        with tqdm(total=len(opt_ts), desc="Processing", unit="window") as pbar:
-            for i, t in enumerate(opt_ts):
-                t = t // self.window * self.window
-                start = s
-                end = t + self.t_pad2 + self.window
-                audio_slice = audio_pad[start:end]
-                pitch_slice = pitch[:, start // self.window:end // self.window] if if_f0 else None
-                pitchf_slice = pitchf[:, start // self.window:end // self.window] if if_f0 else None
-                audio_opt.append(self.vc(model, net_g, sid, audio_slice, pitch_slice, pitchf_slice, times, index, big_npy, index_rate, version, protect)[self.t_pad_tgt : -self.t_pad_tgt])
-                s = t
-                pbar.update(1)
-                pbar.refresh()
-
-        audio_slice = audio_pad[t:]
-        pitch_slice = pitch[:, t // self.window:] if if_f0 and t is not None else pitch
-        pitchf_slice = pitchf[:, t // self.window:] if if_f0 and t is not None else pitchf
-        audio_opt.append(self.vc(model, net_g, sid, audio_slice, pitch_slice, pitchf_slice, times, index, big_npy, index_rate, version, protect)[self.t_pad_tgt : -self.t_pad_tgt])
-        
-        audio_opt = np.concatenate(audio_opt)
-        if rms_mix_rate != 1:
-            audio_opt = change_rms(audio, 16000, audio_opt, tgt_sr, rms_mix_rate)
-        if tgt_sr != resample_sr >= 16000:
-            audio_opt = librosa.resample(
-                audio_opt, orig_sr=tgt_sr, target_sr=resample_sr
-            )
-        audio_max = np.abs(audio_opt).max() / 0.99
-        max_int16 = 32768
-        if audio_max > 1:
-            max_int16 /= audio_max
-        audio_opt = (audio_opt * max_int16).astype(np.int16)
-        del pitch, pitchf, sid
-        if torch.cuda.is_available():
-            torch.cuda.empty_cache()
-
-        print("Returning completed audio...")
-        print("-------------------")
-        return audio_opt
diff --git a/spaces/Silentlin/DiffSinger/checkpoints/clean.py b/spaces/Silentlin/DiffSinger/checkpoints/clean.py
deleted file mode 100644
index 64c86a7d857fbca635ce0848b7756004313d8f94..0000000000000000000000000000000000000000
--- a/spaces/Silentlin/DiffSinger/checkpoints/clean.py
+++ /dev/null
@@ -1,12 +0,0 @@
-import sys
-import torch
-
-if __name__ == '__main__':
-    ckpt_path = sys.argv[1]
-    checkpoint = torch.load(ckpt_path, map_location='cpu')
-    print(checkpoint['state_dict'].keys())
-    if 'model' in checkpoint['state_dict']:
-        checkpoint = {'state_dict': {'model': checkpoint['state_dict']['model']}}
-    else:
-        checkpoint = {'state_dict': {'model_gen': checkpoint['state_dict']['model_gen']}}
-    torch.save(checkpoint, ckpt_path, _use_new_zipfile_serialization=False)
diff --git a/spaces/SjoerdTeunisse/upscaler/README.md b/spaces/SjoerdTeunisse/upscaler/README.md
deleted file mode 100644
index 1f50c61d45b587526bf15f6a71d29dea53aaab7a..0000000000000000000000000000000000000000
--- a/spaces/SjoerdTeunisse/upscaler/README.md
+++ /dev/null
@@ -1,14 +0,0 @@
----
-title: Image Upscaling Playground
-emoji: 🦆
-colorFrom: green
-colorTo: yellow
-sdk: gradio
-sdk_version: 3.4.1
-app_file: app.py
-pinned: false
-license: apache-2.0
-duplicated_from: bookbot/Image-Upscaling-Playground
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference
diff --git a/spaces/Sortoite/pdfGPT/app.py b/spaces/Sortoite/pdfGPT/app.py
deleted file mode 100644
index fe74aebcd3c1f2ddd0aa10758d7fd1c214c443e8..0000000000000000000000000000000000000000
--- a/spaces/Sortoite/pdfGPT/app.py
+++ /dev/null
@@ -1,219 +0,0 @@
-import urllib.request
-import fitz
-import re
-import numpy as np
-import tensorflow_hub as hub
-import openai
-import gradio as gr
-import os
-from sklearn.neighbors import NearestNeighbors
-
-def download_pdf(url, output_path):
-    urllib.request.urlretrieve(url, output_path)
-
-
-def preprocess(text):
-    text = text.replace('\n', ' ')
-    text = re.sub('\s+', ' ', text)
-    return text
-
-
-def pdf_to_text(path, start_page=1, end_page=None):
-    doc = fitz.open(path)
-    total_pages = doc.page_count
-
-    if end_page is None:
-        end_page = total_pages
-
-    text_list = []
-
-    for i in range(start_page-1, end_page):
-        text = doc.load_page(i).get_text("text")
-        text = preprocess(text)
-        text_list.append(text)
-
-    doc.close()
-    return text_list
-
-
-def text_to_chunks(texts, word_length=150, start_page=1):
-    text_toks = [t.split(' ') for t in texts]
-    page_nums = []
-    chunks = []
-    
-    for idx, words in enumerate(text_toks):
-        for i in range(0, len(words), word_length):
-            chunk = words[i:i+word_length]
-            if (i+word_length) > len(words) and (len(chunk) < word_length) and (
-                len(text_toks) != (idx+1)):
-                text_toks[idx+1] = chunk + text_toks[idx+1]
-                continue
-            chunk = ' '.join(chunk).strip()
-            chunk = f'[{idx+start_page}]' + ' ' + '"' + chunk + '"'
-            chunks.append(chunk)
-    return chunks
-
-
-class SemanticSearch:
-    
-    def __init__(self):
-        self.use = hub.load('https://tfhub.dev/google/universal-sentence-encoder/4')
-        self.fitted = False
-    
-    
-    def fit(self, data, batch=1000, n_neighbors=5):
-        self.data = data
-        self.embeddings = self.get_text_embedding(data, batch=batch)
-        n_neighbors = min(n_neighbors, len(self.embeddings))
-        self.nn = NearestNeighbors(n_neighbors=n_neighbors)
-        self.nn.fit(self.embeddings)
-        self.fitted = True
-    
-    
-    def __call__(self, text, return_data=True):
-        inp_emb = self.use([text])
-        neighbors = self.nn.kneighbors(inp_emb, return_distance=False)[0]
-        
-        if return_data:
-            return [self.data[i] for i in neighbors]
-        else:
-            return neighbors
-    
-    
-    def get_text_embedding(self, texts, batch=1000):
-        embeddings = []
-        for i in range(0, len(texts), batch):
-            text_batch = texts[i:(i+batch)]
-            emb_batch = self.use(text_batch)
-            embeddings.append(emb_batch)
-        embeddings = np.vstack(embeddings)
-        return embeddings
-
-
-
-def load_recommender(path, start_page=1):
-    global recommender
-    texts = pdf_to_text(path, start_page=start_page)
-    chunks = text_to_chunks(texts, start_page=start_page)
-    recommender.fit(chunks)
-    return 'Corpus Loaded.'
-
-
-def generate_text(openAI_key,prompt, engine="text-davinci-003"):
-    openai.api_key = openAI_key
-    completions = openai.Completion.create(
-        engine=engine,
-        prompt=prompt,
-        max_tokens=512,
-        n=1,
-        stop=None,
-        temperature=0.7,
-    )
-    message = completions.choices[0].text
-    return message
-
-
-def generate_answer(question,openAI_key):
-    topn_chunks = recommender(question)
-    prompt = ""
-    prompt += 'search results:\n\n'
-    for c in topn_chunks:
-        prompt += c + '\n\n'
-        
-    prompt += "Instructions: Compose a comprehensive reply to the query using the search results given. "\
-              "Cite each reference using [number] notation (every result has this number at the beginning). "\
-              "Citation should be done at the end of each sentence. If the search results mention multiple subjects "\
-              "with the same name, create separate answers for each. Only include information found in the results and "\
-              "don't add any additional information. Make sure the answer is correct and don't output false content. "\
-              "If the text does not relate to the query, simply state 'Found Nothing'. Ignore outlier "\
-              "search results which has nothing to do with the question. Only answer what is asked. The "\
-              "answer should be short and concise.\n\nQuery: {question}\nAnswer: "
-    
-    prompt += f"Query: {question}\nAnswer:"
-    answer = generate_text(openAI_key, prompt,"text-davinci-003")
-    return answer
-
-
-def question_answer(url, file, question,openAI_key):
-    if openAI_key.strip()=='':
-        return '[ERROR]: Please enter you Open AI Key. Get your key here : https://platform.openai.com/account/api-keys'
-    if url.strip() == '' and file == None:
-        return '[ERROR]: Both URL and PDF is empty. Provide atleast one.'
-    
-    if url.strip() != '' and file != None:
-        return '[ERROR]: Both URL and PDF is provided. Please provide only one (eiter URL or PDF).'
-
-    if url.strip() != '':
-        glob_url = url
-        download_pdf(glob_url, 'corpus.pdf')
-        load_recommender('corpus.pdf')
-
-    else:
-        old_file_name = file.name
-        file_name = file.name
-        file_name = file_name[:-12] + file_name[-4:]
-        os.rename(old_file_name, file_name)
-        load_recommender(file_name)
-
-    if question.strip() == '':
-        return '[ERROR]: Question field is empty'
-
-    return generate_answer(question,openAI_key)
-
-
-recommender = SemanticSearch()
-
-title = 'PDF GPT'
-description = """ What is PDF GPT ?
-1. The problem is that Open AI has a 4K token limit and cannot take an entire PDF file as input. Additionally, it sometimes returns irrelevant responses due to poor embeddings. ChatGPT cannot directly talk to external data. The solution is PDF GPT, which allows you to chat with an uploaded PDF file using GPT functionalities. The application breaks the document into smaller chunks and generates embeddings using a powerful Deep Averaging Network Encoder. A semantic search is performed on your query, and the top relevant chunks are used to generate a response.
-2. The returned response can even cite the page number in square brackets([]) where the information is located, adding credibility to the responses and helping to locate pertinent information quickly. The Responses are much better than the naive responses by Open AI."""
-
-with gr.Blocks() as demo:
-
-    gr.Markdown(f'<center><h1>{title}</h1></center>')
-    gr.Markdown(description)
-
-    with gr.Row():
-        
-        with gr.Group():
-            gr.Markdown(f'<p style="text-align:center">Get your Open AI API key <a href="https://platform.openai.com/account/api-keys">here</a></p>')
-            openAI_key=gr.Textbox(label='Enter your OpenAI API key here')
-            url = gr.Textbox(label='Enter PDF URL here')
-            gr.Markdown("<center><h4>OR<h4></center>")
-            file = gr.File(label='Upload your PDF/ Research Paper / Book here', file_types=['.pdf'])
-            question = gr.Textbox(label='Enter your question here')
-            btn = gr.Button(value='Submit')
-            btn.style(full_width=True)
-
-        with gr.Group():
-            answer = gr.Textbox(label='The answer to your question is :')
-
-        btn.click(question_answer, inputs=[url, file, question,openAI_key], outputs=[answer])
-#openai.api_key = os.getenv('Your_Key_Here') 
-demo.launch()
-
-
-# import streamlit as st
-
-# #Define the app layout
-# st.markdown(f'<center><h1>{title}</h1></center>', unsafe_allow_html=True)
-# st.markdown(description)
-
-# col1, col2 = st.columns(2)
-
-# # Define the inputs in the first column
-# with col1:
-#     url = st.text_input('URL')
-#     st.markdown("<center><h6>or<h6></center>", unsafe_allow_html=True)
-#     file = st.file_uploader('PDF', type='pdf')
-#     question = st.text_input('question')
-#     btn = st.button('Submit')
-
-# # Define the output in the second column
-# with col2:
-#     answer = st.text_input('answer')
-
-# # Define the button action
-# if btn:
-#     answer_value = question_answer(url, file, question)
-#     answer.value = answer_value
\ No newline at end of file
diff --git a/spaces/SpfIo/Whisper_TL_Streaming_API/README.md b/spaces/SpfIo/Whisper_TL_Streaming_API/README.md
deleted file mode 100644
index 764e69acb24d6e410e1e5bd7092696065e979fd0..0000000000000000000000000000000000000000
--- a/spaces/SpfIo/Whisper_TL_Streaming_API/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Whisper TL Streaming API
-emoji: 🦀
-colorFrom: red
-colorTo: yellow
-sdk: gradio
-sdk_version: 3.42.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/SuYuanS/AudioCraft_Plus/audiocraft/modules/seanet.py b/spaces/SuYuanS/AudioCraft_Plus/audiocraft/modules/seanet.py
deleted file mode 100644
index 3e5998e9153afb6e68ea410d565e00ea835db248..0000000000000000000000000000000000000000
--- a/spaces/SuYuanS/AudioCraft_Plus/audiocraft/modules/seanet.py
+++ /dev/null
@@ -1,258 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-
-import typing as tp
-
-import numpy as np
-import torch.nn as nn
-
-from .conv import StreamableConv1d, StreamableConvTranspose1d
-from .lstm import StreamableLSTM
-
-
-class SEANetResnetBlock(nn.Module):
-    """Residual block from SEANet model.
-
-    Args:
-        dim (int): Dimension of the input/output.
-        kernel_sizes (list): List of kernel sizes for the convolutions.
-        dilations (list): List of dilations for the convolutions.
-        activation (str): Activation function.
-        activation_params (dict): Parameters to provide to the activation function.
-        norm (str): Normalization method.
-        norm_params (dict): Parameters to provide to the underlying normalization used along with the convolution.
-        causal (bool): Whether to use fully causal convolution.
-        pad_mode (str): Padding mode for the convolutions.
-        compress (int): Reduced dimensionality in residual branches (from Demucs v3).
-        true_skip (bool): Whether to use true skip connection or a simple
-            (streamable) convolution as the skip connection.
-    """
-    def __init__(self, dim: int, kernel_sizes: tp.List[int] = [3, 1], dilations: tp.List[int] = [1, 1],
-                 activation: str = 'ELU', activation_params: dict = {'alpha': 1.0},
-                 norm: str = 'none', norm_params: tp.Dict[str, tp.Any] = {}, causal: bool = False,
-                 pad_mode: str = 'reflect', compress: int = 2, true_skip: bool = True):
-        super().__init__()
-        assert len(kernel_sizes) == len(dilations), 'Number of kernel sizes should match number of dilations'
-        act = getattr(nn, activation)
-        hidden = dim // compress
-        block = []
-        for i, (kernel_size, dilation) in enumerate(zip(kernel_sizes, dilations)):
-            in_chs = dim if i == 0 else hidden
-            out_chs = dim if i == len(kernel_sizes) - 1 else hidden
-            block += [
-                act(**activation_params),
-                StreamableConv1d(in_chs, out_chs, kernel_size=kernel_size, dilation=dilation,
-                                 norm=norm, norm_kwargs=norm_params,
-                                 causal=causal, pad_mode=pad_mode),
-            ]
-        self.block = nn.Sequential(*block)
-        self.shortcut: nn.Module
-        if true_skip:
-            self.shortcut = nn.Identity()
-        else:
-            self.shortcut = StreamableConv1d(dim, dim, kernel_size=1, norm=norm, norm_kwargs=norm_params,
-                                             causal=causal, pad_mode=pad_mode)
-
-    def forward(self, x):
-        return self.shortcut(x) + self.block(x)
-
-
-class SEANetEncoder(nn.Module):
-    """SEANet encoder.
-
-    Args:
-        channels (int): Audio channels.
-        dimension (int): Intermediate representation dimension.
-        n_filters (int): Base width for the model.
-        n_residual_layers (int): nb of residual layers.
-        ratios (Sequence[int]): kernel size and stride ratios. The encoder uses downsampling ratios instead of
-            upsampling ratios, hence it will use the ratios in the reverse order to the ones specified here
-            that must match the decoder order. We use the decoder order as some models may only employ the decoder.
-        activation (str): Activation function.
-        activation_params (dict): Parameters to provide to the activation function.
-        norm (str): Normalization method.
-        norm_params (dict): Parameters to provide to the underlying normalization used along with the convolution.
-        kernel_size (int): Kernel size for the initial convolution.
-        last_kernel_size (int): Kernel size for the initial convolution.
-        residual_kernel_size (int): Kernel size for the residual layers.
-        dilation_base (int): How much to increase the dilation with each layer.
-        causal (bool): Whether to use fully causal convolution.
-        pad_mode (str): Padding mode for the convolutions.
-        true_skip (bool): Whether to use true skip connection or a simple
-            (streamable) convolution as the skip connection in the residual network blocks.
-        compress (int): Reduced dimensionality in residual branches (from Demucs v3).
-        lstm (int): Number of LSTM layers at the end of the encoder.
-        disable_norm_outer_blocks (int): Number of blocks for which we don't apply norm.
-            For the encoder, it corresponds to the N first blocks.
-    """
-    def __init__(self, channels: int = 1, dimension: int = 128, n_filters: int = 32, n_residual_layers: int = 3,
-                 ratios: tp.List[int] = [8, 5, 4, 2], activation: str = 'ELU', activation_params: dict = {'alpha': 1.0},
-                 norm: str = 'none', norm_params: tp.Dict[str, tp.Any] = {}, kernel_size: int = 7,
-                 last_kernel_size: int = 7, residual_kernel_size: int = 3, dilation_base: int = 2, causal: bool = False,
-                 pad_mode: str = 'reflect', true_skip: bool = True, compress: int = 2, lstm: int = 0,
-                 disable_norm_outer_blocks: int = 0):
-        super().__init__()
-        self.channels = channels
-        self.dimension = dimension
-        self.n_filters = n_filters
-        self.ratios = list(reversed(ratios))
-        del ratios
-        self.n_residual_layers = n_residual_layers
-        self.hop_length = np.prod(self.ratios)
-        self.n_blocks = len(self.ratios) + 2  # first and last conv + residual blocks
-        self.disable_norm_outer_blocks = disable_norm_outer_blocks
-        assert self.disable_norm_outer_blocks >= 0 and self.disable_norm_outer_blocks <= self.n_blocks, \
-            "Number of blocks for which to disable norm is invalid." \
-            "It should be lower or equal to the actual number of blocks in the network and greater or equal to 0."
-
-        act = getattr(nn, activation)
-        mult = 1
-        model: tp.List[nn.Module] = [
-            StreamableConv1d(channels, mult * n_filters, kernel_size,
-                             norm='none' if self.disable_norm_outer_blocks >= 1 else norm,
-                             norm_kwargs=norm_params, causal=causal, pad_mode=pad_mode)
-        ]
-        # Downsample to raw audio scale
-        for i, ratio in enumerate(self.ratios):
-            block_norm = 'none' if self.disable_norm_outer_blocks >= i + 2 else norm
-            # Add residual layers
-            for j in range(n_residual_layers):
-                model += [
-                    SEANetResnetBlock(mult * n_filters, kernel_sizes=[residual_kernel_size, 1],
-                                      dilations=[dilation_base ** j, 1],
-                                      norm=block_norm, norm_params=norm_params,
-                                      activation=activation, activation_params=activation_params,
-                                      causal=causal, pad_mode=pad_mode, compress=compress, true_skip=true_skip)]
-
-            # Add downsampling layers
-            model += [
-                act(**activation_params),
-                StreamableConv1d(mult * n_filters, mult * n_filters * 2,
-                                 kernel_size=ratio * 2, stride=ratio,
-                                 norm=block_norm, norm_kwargs=norm_params,
-                                 causal=causal, pad_mode=pad_mode),
-            ]
-            mult *= 2
-
-        if lstm:
-            model += [StreamableLSTM(mult * n_filters, num_layers=lstm)]
-
-        model += [
-            act(**activation_params),
-            StreamableConv1d(mult * n_filters, dimension, last_kernel_size,
-                             norm='none' if self.disable_norm_outer_blocks == self.n_blocks else norm,
-                             norm_kwargs=norm_params, causal=causal, pad_mode=pad_mode)
-        ]
-
-        self.model = nn.Sequential(*model)
-
-    def forward(self, x):
-        return self.model(x)
-
-
-class SEANetDecoder(nn.Module):
-    """SEANet decoder.
-
-    Args:
-        channels (int): Audio channels.
-        dimension (int): Intermediate representation dimension.
-        n_filters (int): Base width for the model.
-        n_residual_layers (int): nb of residual layers.
-        ratios (Sequence[int]): kernel size and stride ratios.
-        activation (str): Activation function.
-        activation_params (dict): Parameters to provide to the activation function.
-        final_activation (str): Final activation function after all convolutions.
-        final_activation_params (dict): Parameters to provide to the activation function.
-        norm (str): Normalization method.
-        norm_params (dict): Parameters to provide to the underlying normalization used along with the convolution.
-        kernel_size (int): Kernel size for the initial convolution.
-        last_kernel_size (int): Kernel size for the initial convolution.
-        residual_kernel_size (int): Kernel size for the residual layers.
-        dilation_base (int): How much to increase the dilation with each layer.
-        causal (bool): Whether to use fully causal convolution.
-        pad_mode (str): Padding mode for the convolutions.
-        true_skip (bool): Whether to use true skip connection or a simple.
-            (streamable) convolution as the skip connection in the residual network blocks.
-        compress (int): Reduced dimensionality in residual branches (from Demucs v3).
-        lstm (int): Number of LSTM layers at the end of the encoder.
-        disable_norm_outer_blocks (int): Number of blocks for which we don't apply norm.
-            For the decoder, it corresponds to the N last blocks.
-        trim_right_ratio (float): Ratio for trimming at the right of the transposed convolution under the causal setup.
-            If equal to 1.0, it means that all the trimming is done at the right.
-    """
-    def __init__(self, channels: int = 1, dimension: int = 128, n_filters: int = 32, n_residual_layers: int = 3,
-                 ratios: tp.List[int] = [8, 5, 4, 2], activation: str = 'ELU', activation_params: dict = {'alpha': 1.0},
-                 final_activation: tp.Optional[str] = None, final_activation_params: tp.Optional[dict] = None,
-                 norm: str = 'none', norm_params: tp.Dict[str, tp.Any] = {}, kernel_size: int = 7,
-                 last_kernel_size: int = 7, residual_kernel_size: int = 3, dilation_base: int = 2, causal: bool = False,
-                 pad_mode: str = 'reflect', true_skip: bool = True, compress: int = 2, lstm: int = 0,
-                 disable_norm_outer_blocks: int = 0, trim_right_ratio: float = 1.0):
-        super().__init__()
-        self.dimension = dimension
-        self.channels = channels
-        self.n_filters = n_filters
-        self.ratios = ratios
-        del ratios
-        self.n_residual_layers = n_residual_layers
-        self.hop_length = np.prod(self.ratios)
-        self.n_blocks = len(self.ratios) + 2  # first and last conv + residual blocks
-        self.disable_norm_outer_blocks = disable_norm_outer_blocks
-        assert self.disable_norm_outer_blocks >= 0 and self.disable_norm_outer_blocks <= self.n_blocks, \
-            "Number of blocks for which to disable norm is invalid." \
-            "It should be lower or equal to the actual number of blocks in the network and greater or equal to 0."
-
-        act = getattr(nn, activation)
-        mult = int(2 ** len(self.ratios))
-        model: tp.List[nn.Module] = [
-            StreamableConv1d(dimension, mult * n_filters, kernel_size,
-                             norm='none' if self.disable_norm_outer_blocks == self.n_blocks else norm,
-                             norm_kwargs=norm_params, causal=causal, pad_mode=pad_mode)
-        ]
-
-        if lstm:
-            model += [StreamableLSTM(mult * n_filters, num_layers=lstm)]
-
-        # Upsample to raw audio scale
-        for i, ratio in enumerate(self.ratios):
-            block_norm = 'none' if self.disable_norm_outer_blocks >= self.n_blocks - (i + 1) else norm
-            # Add upsampling layers
-            model += [
-                act(**activation_params),
-                StreamableConvTranspose1d(mult * n_filters, mult * n_filters // 2,
-                                          kernel_size=ratio * 2, stride=ratio,
-                                          norm=block_norm, norm_kwargs=norm_params,
-                                          causal=causal, trim_right_ratio=trim_right_ratio),
-            ]
-            # Add residual layers
-            for j in range(n_residual_layers):
-                model += [
-                    SEANetResnetBlock(mult * n_filters // 2, kernel_sizes=[residual_kernel_size, 1],
-                                      dilations=[dilation_base ** j, 1],
-                                      activation=activation, activation_params=activation_params,
-                                      norm=block_norm, norm_params=norm_params, causal=causal,
-                                      pad_mode=pad_mode, compress=compress, true_skip=true_skip)]
-
-            mult //= 2
-
-        # Add final layers
-        model += [
-            act(**activation_params),
-            StreamableConv1d(n_filters, channels, last_kernel_size,
-                             norm='none' if self.disable_norm_outer_blocks >= 1 else norm,
-                             norm_kwargs=norm_params, causal=causal, pad_mode=pad_mode)
-        ]
-        # Add optional final activation to decoder (eg. tanh)
-        if final_activation is not None:
-            final_act = getattr(nn, final_activation)
-            final_activation_params = final_activation_params or {}
-            model += [
-                final_act(**final_activation_params)
-            ]
-        self.model = nn.Sequential(*model)
-
-    def forward(self, z):
-        y = self.model(z)
-        return y
diff --git a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/IPython/core/tests/test_formatters.py b/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/IPython/core/tests/test_formatters.py
deleted file mode 100644
index c642befaccf17b2f391ec0c1d9d4d88f3815bb2c..0000000000000000000000000000000000000000
--- a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/IPython/core/tests/test_formatters.py
+++ /dev/null
@@ -1,531 +0,0 @@
-"""Tests for the Formatters."""
-
-from math import pi
-
-try:
-    import numpy
-except:
-    numpy = None
-import pytest
-
-from IPython import get_ipython
-from traitlets.config import Config
-from IPython.core.formatters import (
-    PlainTextFormatter, HTMLFormatter, PDFFormatter, _mod_name_key,
-    DisplayFormatter, JSONFormatter,
-)
-from IPython.utils.io import capture_output
-
-class A(object):
-    def __repr__(self):
-        return 'A()'
-
-class B(A):
-    def __repr__(self):
-        return 'B()'
-
-class C:
-    pass
-
-class BadRepr(object):
-    def __repr__(self):
-        raise ValueError("bad repr")
-
-class BadPretty(object):
-    _repr_pretty_ = None
-
-class GoodPretty(object):
-    def _repr_pretty_(self, pp, cycle):
-        pp.text('foo')
-
-    def __repr__(self):
-        return 'GoodPretty()'
-
-def foo_printer(obj, pp, cycle):
-    pp.text('foo')
-
-def test_pretty():
-    f = PlainTextFormatter()
-    f.for_type(A, foo_printer)
-    assert f(A()) == "foo"
-    assert f(B()) == "B()"
-    assert f(GoodPretty()) == "foo"
-    # Just don't raise an exception for the following:
-    f(BadPretty())
-
-    f.pprint = False
-    assert f(A()) == "A()"
-    assert f(B()) == "B()"
-    assert f(GoodPretty()) == "GoodPretty()"
-
-
-def test_deferred():
-    f = PlainTextFormatter()
-
-def test_precision():
-    """test various values for float_precision."""
-    f = PlainTextFormatter()
-    assert f(pi) == repr(pi)
-    f.float_precision = 0
-    if numpy:
-        po = numpy.get_printoptions()
-        assert po["precision"] == 0
-    assert f(pi) == "3"
-    f.float_precision = 2
-    if numpy:
-        po = numpy.get_printoptions()
-        assert po["precision"] == 2
-    assert f(pi) == "3.14"
-    f.float_precision = "%g"
-    if numpy:
-        po = numpy.get_printoptions()
-        assert po["precision"] == 2
-    assert f(pi) == "3.14159"
-    f.float_precision = "%e"
-    assert f(pi) == "3.141593e+00"
-    f.float_precision = ""
-    if numpy:
-        po = numpy.get_printoptions()
-        assert po["precision"] == 8
-    assert f(pi) == repr(pi)
-
-
-def test_bad_precision():
-    """test various invalid values for float_precision."""
-    f = PlainTextFormatter()
-    def set_fp(p):
-        f.float_precision = p
-
-    pytest.raises(ValueError, set_fp, "%")
-    pytest.raises(ValueError, set_fp, "%.3f%i")
-    pytest.raises(ValueError, set_fp, "foo")
-    pytest.raises(ValueError, set_fp, -1)
-
-def test_for_type():
-    f = PlainTextFormatter()
-    
-    # initial return, None
-    assert f.for_type(C, foo_printer) is None
-    # no func queries
-    assert f.for_type(C) is foo_printer
-    # shouldn't change anything
-    assert f.for_type(C) is foo_printer
-    # None should do the same
-    assert f.for_type(C, None) is foo_printer
-    assert f.for_type(C, None) is foo_printer
-
-def test_for_type_string():
-    f = PlainTextFormatter()
-    
-    type_str = '%s.%s' % (C.__module__, 'C')
-    
-    # initial return, None
-    assert f.for_type(type_str, foo_printer) is None
-    # no func queries
-    assert f.for_type(type_str) is foo_printer
-    assert _mod_name_key(C) in f.deferred_printers
-    assert f.for_type(C) is foo_printer
-    assert _mod_name_key(C) not in f.deferred_printers
-    assert C in f.type_printers
-
-def test_for_type_by_name():
-    f = PlainTextFormatter()
-    
-    mod = C.__module__
-    
-    # initial return, None
-    assert f.for_type_by_name(mod, "C", foo_printer) is None
-    # no func queries
-    assert f.for_type_by_name(mod, "C") is foo_printer
-    # shouldn't change anything
-    assert f.for_type_by_name(mod, "C") is foo_printer
-    # None should do the same
-    assert f.for_type_by_name(mod, "C", None) is foo_printer
-    assert f.for_type_by_name(mod, "C", None) is foo_printer
-
-
-def test_lookup():
-    f = PlainTextFormatter()
-    
-    f.for_type(C, foo_printer)
-    assert f.lookup(C()) is foo_printer
-    with pytest.raises(KeyError):
-        f.lookup(A())
-
-def test_lookup_string():
-    f = PlainTextFormatter()
-    type_str = '%s.%s' % (C.__module__, 'C')
-    
-    f.for_type(type_str, foo_printer)
-    assert f.lookup(C()) is foo_printer
-    # should move from deferred to imported dict
-    assert _mod_name_key(C) not in f.deferred_printers
-    assert C in f.type_printers
-
-def test_lookup_by_type():
-    f = PlainTextFormatter()
-    f.for_type(C, foo_printer)
-    assert f.lookup_by_type(C) is foo_printer
-    with pytest.raises(KeyError):
-        f.lookup_by_type(A)
-
-def test_lookup_by_type_string():
-    f = PlainTextFormatter()
-    type_str = '%s.%s' % (C.__module__, 'C')
-    f.for_type(type_str, foo_printer)
-    
-    # verify insertion
-    assert _mod_name_key(C) in f.deferred_printers
-    assert C not in f.type_printers
-    
-    assert f.lookup_by_type(type_str) is foo_printer
-    # lookup by string doesn't cause import
-    assert _mod_name_key(C) in f.deferred_printers
-    assert C not in f.type_printers
-    
-    assert f.lookup_by_type(C) is foo_printer
-    # should move from deferred to imported dict
-    assert _mod_name_key(C) not in f.deferred_printers
-    assert C in f.type_printers
-
-def test_in_formatter():
-    f = PlainTextFormatter()
-    f.for_type(C, foo_printer)
-    type_str = '%s.%s' % (C.__module__, 'C')
-    assert C in f
-    assert type_str in f
-
-def test_string_in_formatter():
-    f = PlainTextFormatter()
-    type_str = '%s.%s' % (C.__module__, 'C')
-    f.for_type(type_str, foo_printer)
-    assert type_str in f
-    assert C in f
-
-def test_pop():
-    f = PlainTextFormatter()
-    f.for_type(C, foo_printer)
-    assert f.lookup_by_type(C) is foo_printer
-    assert f.pop(C, None) is foo_printer
-    f.for_type(C, foo_printer)
-    assert f.pop(C) is foo_printer
-    with pytest.raises(KeyError):
-        f.lookup_by_type(C)
-    with pytest.raises(KeyError):
-        f.pop(C)
-    with pytest.raises(KeyError):
-        f.pop(A)
-    assert f.pop(A, None) is None
-
-def test_pop_string():
-    f = PlainTextFormatter()
-    type_str = '%s.%s' % (C.__module__, 'C')
-    
-    with pytest.raises(KeyError):
-        f.pop(type_str)
-    
-    f.for_type(type_str, foo_printer)
-    f.pop(type_str)
-    with pytest.raises(KeyError):
-        f.lookup_by_type(C)
-    with pytest.raises(KeyError):
-        f.pop(type_str)
-
-    f.for_type(C, foo_printer)
-    assert f.pop(type_str, None) is foo_printer
-    with pytest.raises(KeyError):
-        f.lookup_by_type(C)
-    with pytest.raises(KeyError):
-        f.pop(type_str)
-    assert f.pop(type_str, None) is None
-    
-
-def test_error_method():
-    f = HTMLFormatter()
-    class BadHTML(object):
-        def _repr_html_(self):
-            raise ValueError("Bad HTML")
-    bad = BadHTML()
-    with capture_output() as captured:
-        result = f(bad)
-    assert result is None
-    assert "Traceback" in captured.stdout
-    assert "Bad HTML" in captured.stdout
-    assert "_repr_html_" in captured.stdout
-
-def test_nowarn_notimplemented():
-    f = HTMLFormatter()
-    class HTMLNotImplemented(object):
-        def _repr_html_(self):
-            raise NotImplementedError
-    h = HTMLNotImplemented()
-    with capture_output() as captured:
-        result = f(h)
-    assert result is None
-    assert "" == captured.stderr
-    assert "" == captured.stdout
-
-
-def test_warn_error_for_type():
-    f = HTMLFormatter()
-    f.for_type(int, lambda i: name_error)
-    with capture_output() as captured:
-        result = f(5)
-    assert result is None
-    assert "Traceback" in captured.stdout
-    assert "NameError" in captured.stdout
-    assert "name_error" in captured.stdout
-
-def test_error_pretty_method():
-    f = PlainTextFormatter()
-    class BadPretty(object):
-        def _repr_pretty_(self):
-            return "hello"
-    bad = BadPretty()
-    with capture_output() as captured:
-        result = f(bad)
-    assert result is None
-    assert "Traceback" in captured.stdout
-    assert "_repr_pretty_" in captured.stdout
-    assert "given" in captured.stdout
-    assert "argument" in captured.stdout
-
-
-def test_bad_repr_traceback():
-    f = PlainTextFormatter()
-    bad = BadRepr()
-    with capture_output() as captured:
-        result = f(bad)
-    # catches error, returns None
-    assert result is None
-    assert "Traceback" in captured.stdout
-    assert "__repr__" in captured.stdout
-    assert "ValueError" in captured.stdout
-
-
-class MakePDF(object):
-    def _repr_pdf_(self):
-        return 'PDF'
-
-def test_pdf_formatter():
-    pdf = MakePDF()
-    f = PDFFormatter()
-    assert f(pdf) == "PDF"
-
-
-def test_print_method_bound():
-    f = HTMLFormatter()
-    class MyHTML(object):
-        def _repr_html_(self):
-            return "hello"
-    with capture_output() as captured:
-        result = f(MyHTML)
-    assert result is None
-    assert "FormatterWarning" not in captured.stderr
-
-    with capture_output() as captured:
-        result = f(MyHTML())
-    assert result == "hello"
-    assert captured.stderr == ""
-
-
-def test_print_method_weird():
-
-    class TextMagicHat(object):
-        def __getattr__(self, key):
-            return key
-
-    f = HTMLFormatter()
-
-    text_hat = TextMagicHat()
-    assert text_hat._repr_html_ == "_repr_html_"
-    with capture_output() as captured:
-        result = f(text_hat)
-    
-    assert result is None
-    assert "FormatterWarning" not in captured.stderr
-
-    class CallableMagicHat(object):
-        def __getattr__(self, key):
-            return lambda : key
-    
-    call_hat = CallableMagicHat()
-    with capture_output() as captured:
-        result = f(call_hat)
-
-    assert result is None
-
-    class BadReprArgs(object):
-        def _repr_html_(self, extra, args):
-            return "html"
-    
-    bad = BadReprArgs()
-    with capture_output() as captured:
-        result = f(bad)
-    
-    assert result is None
-    assert "FormatterWarning" not in captured.stderr
-
-
-def test_format_config():
-    """config objects don't pretend to support fancy reprs with lazy attrs"""
-    f = HTMLFormatter()
-    cfg = Config()
-    with capture_output() as captured:
-        result = f(cfg)
-    assert result is None
-    assert captured.stderr == ""
-
-    with capture_output() as captured:
-        result = f(Config)
-    assert result is None
-    assert captured.stderr == ""
-
-
-def test_pretty_max_seq_length():
-    f = PlainTextFormatter(max_seq_length=1)
-    lis = list(range(3))
-    text = f(lis)
-    assert text == "[0, ...]"
-    f.max_seq_length = 0
-    text = f(lis)
-    assert text == "[0, 1, 2]"
-    text = f(list(range(1024)))
-    lines = text.splitlines()
-    assert len(lines) == 1024
-
-
-def test_ipython_display_formatter():
-    """Objects with _ipython_display_ defined bypass other formatters"""
-    f = get_ipython().display_formatter
-    catcher = []
-    class SelfDisplaying(object):
-        def _ipython_display_(self):
-            catcher.append(self)
-
-    class NotSelfDisplaying(object):
-        def __repr__(self):
-            return "NotSelfDisplaying"
-        
-        def _ipython_display_(self):
-            raise NotImplementedError
-    
-    save_enabled = f.ipython_display_formatter.enabled
-    f.ipython_display_formatter.enabled = True
-    
-    yes = SelfDisplaying()
-    no = NotSelfDisplaying()
-
-    d, md = f.format(no)
-    assert d == {"text/plain": repr(no)}
-    assert md == {}
-    assert catcher == []
-
-    d, md = f.format(yes)
-    assert d == {}
-    assert md == {}
-    assert catcher == [yes]
-
-    f.ipython_display_formatter.enabled = save_enabled
-
-
-def test_repr_mime():
-    class HasReprMime(object):
-        def _repr_mimebundle_(self, include=None, exclude=None):
-            return {
-                'application/json+test.v2': {
-                    'x': 'y'
-                },
-                'plain/text' : '<HasReprMime>',
-                'image/png' : 'i-overwrite'
-            }
-
-        def _repr_png_(self):
-            return 'should-be-overwritten'
-        def _repr_html_(self):
-            return '<b>hi!</b>'
-    
-    f = get_ipython().display_formatter
-    html_f = f.formatters['text/html']
-    save_enabled = html_f.enabled
-    html_f.enabled = True
-    obj = HasReprMime()
-    d, md = f.format(obj)
-    html_f.enabled = save_enabled
-
-    assert sorted(d) == [
-        "application/json+test.v2",
-        "image/png",
-        "plain/text",
-        "text/html",
-        "text/plain",
-    ]
-    assert md == {}
-
-    d, md = f.format(obj, include={"image/png"})
-    assert list(d.keys()) == [
-        "image/png"
-    ], "Include should filter out even things from repr_mimebundle"
-
-    assert d["image/png"] == "i-overwrite", "_repr_mimebundle_ take precedence"
-
-
-def test_pass_correct_include_exclude():
-    class Tester(object):
-
-        def __init__(self, include=None, exclude=None):
-            self.include = include
-            self.exclude = exclude
-
-        def _repr_mimebundle_(self, include, exclude, **kwargs):
-            if include and (include != self.include):
-                raise ValueError('include got modified: display() may be broken.')
-            if exclude and (exclude != self.exclude):
-                raise ValueError('exclude got modified: display() may be broken.')
-
-            return None
-
-    include = {'a', 'b', 'c'}
-    exclude = {'c', 'e' , 'f'}
-
-    f = get_ipython().display_formatter
-    f.format(Tester(include=include, exclude=exclude), include=include, exclude=exclude)
-    f.format(Tester(exclude=exclude), exclude=exclude)
-    f.format(Tester(include=include), include=include)
-
-
-def test_repr_mime_meta():
-    class HasReprMimeMeta(object):
-        def _repr_mimebundle_(self, include=None, exclude=None):
-            data = {
-                'image/png': 'base64-image-data',
-            }
-            metadata = {
-                'image/png': {
-                    'width': 5,
-                    'height': 10,
-                }
-            }
-            return (data, metadata)
-    
-    f = get_ipython().display_formatter
-    obj = HasReprMimeMeta()
-    d, md = f.format(obj)
-    assert sorted(d) == ["image/png", "text/plain"]
-    assert md == {
-        "image/png": {
-            "width": 5,
-            "height": 10,
-        }
-    }
-
-
-def test_repr_mime_failure():
-    class BadReprMime(object):
-        def _repr_mimebundle_(self, include=None, exclude=None):
-            raise RuntimeError
-
-    f = get_ipython().display_formatter
-    obj = BadReprMime()
-    d, md = f.format(obj)
-    assert "text/plain" in d
diff --git a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/adodbapi/test/setuptestframework.py b/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/adodbapi/test/setuptestframework.py
deleted file mode 100644
index fcaaf1ae5948ad54e50798ad014038a1934488e4..0000000000000000000000000000000000000000
--- a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/adodbapi/test/setuptestframework.py
+++ /dev/null
@@ -1,134 +0,0 @@
-#!/usr/bin/python2
-# Configure this in order to run the testcases.
-"setuptestframework.py v 2.6.0.8"
-import os
-import shutil
-import sys
-import tempfile
-
-try:
-    OSErrors = (WindowsError, OSError)
-except NameError:  # not running on Windows
-    OSErrors = OSError
-
-
-def maketemp():
-    temphome = tempfile.gettempdir()
-    tempdir = os.path.join(temphome, "adodbapi_test")
-    try:
-        os.mkdir(tempdir)
-    except:
-        pass
-    return tempdir
-
-
-def _cleanup_function(testfolder, mdb_name):
-    try:
-        os.unlink(os.path.join(testfolder, mdb_name))
-    except:
-        pass  # mdb database not present
-    try:
-        shutil.rmtree(testfolder)
-        print("   cleaned up folder", testfolder)
-    except:
-        pass  # test package not present
-
-
-def getcleanupfunction():
-    return _cleanup_function
-
-
-def find_ado_path():
-    adoName = os.path.normpath(os.getcwd() + "/../../adodbapi.py")
-    adoPackage = os.path.dirname(adoName)
-    return adoPackage
-
-
-# make a new package directory for the test copy of ado
-def makeadopackage(testfolder):
-    adoName = os.path.normpath(os.getcwd() + "/../adodbapi.py")
-    adoPath = os.path.dirname(adoName)
-    if os.path.exists(adoName):
-        newpackage = os.path.join(testfolder, "adodbapi")
-        try:
-            os.mkdir(newpackage)
-        except OSErrors:
-            print(
-                "*Note: temporary adodbapi package already exists: may be two versions running?"
-            )
-        for f in os.listdir(adoPath):
-            if f.endswith(".py"):
-                shutil.copy(os.path.join(adoPath, f), newpackage)
-        if sys.version_info >= (3, 0):  # only when running Py3.n
-            save = sys.stdout
-            sys.stdout = None
-            from lib2to3.main import main  # use 2to3 to make test package
-
-            main("lib2to3.fixes", args=["-n", "-w", newpackage])
-            sys.stdout = save
-        return testfolder
-    else:
-        raise EnvironmentError("Connot find source of adodbapi to test.")
-
-
-def makemdb(testfolder, mdb_name):
-    # following setup code borrowed from pywin32 odbc test suite
-    # kindly contributed by Frank Millman.
-    import os
-
-    _accessdatasource = os.path.join(testfolder, mdb_name)
-    if os.path.isfile(_accessdatasource):
-        print("using JET database=", _accessdatasource)
-    else:
-        try:
-            from win32com.client import constants
-            from win32com.client.gencache import EnsureDispatch
-
-            win32 = True
-        except ImportError:  # perhaps we are running IronPython
-            win32 = False  # iron Python
-            try:
-                from System import Activator, Type
-            except:
-                pass
-
-        # Create a brand-new database - what is the story with these?
-        dbe = None
-        for suffix in (".36", ".35", ".30"):
-            try:
-                if win32:
-                    dbe = EnsureDispatch("DAO.DBEngine" + suffix)
-                else:
-                    type = Type.GetTypeFromProgID("DAO.DBEngine" + suffix)
-                    dbe = Activator.CreateInstance(type)
-                break
-            except:
-                pass
-        if dbe:
-            print("    ...Creating ACCESS db at " + _accessdatasource)
-            if win32:
-                workspace = dbe.Workspaces(0)
-                newdb = workspace.CreateDatabase(
-                    _accessdatasource, constants.dbLangGeneral, constants.dbVersion40
-                )
-            else:
-                newdb = dbe.CreateDatabase(
-                    _accessdatasource, ";LANGID=0x0409;CP=1252;COUNTRY=0"
-                )
-            newdb.Close()
-        else:
-            print("    ...copying test ACCESS db to " + _accessdatasource)
-            mdbName = os.path.abspath(
-                os.path.join(os.path.dirname(__file__), "..", "examples", "test.mdb")
-            )
-            import shutil
-
-            shutil.copy(mdbName, _accessdatasource)
-
-    return _accessdatasource
-
-
-if __name__ == "__main__":
-    print("Setting up a Jet database for server to use for remote testing...")
-    temp = maketemp()
-    makemdb(temp, "server_test.mdb")
diff --git a/spaces/Superlang/ImageProcessor/annotator/uniformer/mmcv/ops/border_align.py b/spaces/Superlang/ImageProcessor/annotator/uniformer/mmcv/ops/border_align.py
deleted file mode 100644
index ff305be328e9b0a15e1bbb5e6b41beb940f55c81..0000000000000000000000000000000000000000
--- a/spaces/Superlang/ImageProcessor/annotator/uniformer/mmcv/ops/border_align.py
+++ /dev/null
@@ -1,109 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-# modified from
-# https://github.com/Megvii-BaseDetection/cvpods/blob/master/cvpods/layers/border_align.py
-
-import torch
-import torch.nn as nn
-from torch.autograd import Function
-from torch.autograd.function import once_differentiable
-
-from ..utils import ext_loader
-
-ext_module = ext_loader.load_ext(
-    '_ext', ['border_align_forward', 'border_align_backward'])
-
-
-class BorderAlignFunction(Function):
-
-    @staticmethod
-    def symbolic(g, input, boxes, pool_size):
-        return g.op(
-            'mmcv::MMCVBorderAlign', input, boxes, pool_size_i=pool_size)
-
-    @staticmethod
-    def forward(ctx, input, boxes, pool_size):
-        ctx.pool_size = pool_size
-        ctx.input_shape = input.size()
-
-        assert boxes.ndim == 3, 'boxes must be with shape [B, H*W, 4]'
-        assert boxes.size(2) == 4, \
-            'the last dimension of boxes must be (x1, y1, x2, y2)'
-        assert input.size(1) % 4 == 0, \
-            'the channel for input feature must be divisible by factor 4'
-
-        # [B, C//4, H*W, 4]
-        output_shape = (input.size(0), input.size(1) // 4, boxes.size(1), 4)
-        output = input.new_zeros(output_shape)
-        # `argmax_idx` only used for backward
-        argmax_idx = input.new_zeros(output_shape).to(torch.int)
-
-        ext_module.border_align_forward(
-            input, boxes, output, argmax_idx, pool_size=ctx.pool_size)
-
-        ctx.save_for_backward(boxes, argmax_idx)
-        return output
-
-    @staticmethod
-    @once_differentiable
-    def backward(ctx, grad_output):
-        boxes, argmax_idx = ctx.saved_tensors
-        grad_input = grad_output.new_zeros(ctx.input_shape)
-        # complex head architecture may cause grad_output uncontiguous
-        grad_output = grad_output.contiguous()
-        ext_module.border_align_backward(
-            grad_output,
-            boxes,
-            argmax_idx,
-            grad_input,
-            pool_size=ctx.pool_size)
-        return grad_input, None, None
-
-
-border_align = BorderAlignFunction.apply
-
-
-class BorderAlign(nn.Module):
-    r"""Border align pooling layer.
-
-    Applies border_align over the input feature based on predicted bboxes.
-    The details were described in the paper
-    `BorderDet: Border Feature for Dense Object Detection
-    <https://arxiv.org/abs/2007.11056>`_.
-
-    For each border line (e.g. top, left, bottom or right) of each box,
-    border_align does the following:
-        1. uniformly samples `pool_size`+1 positions on this line, involving \
-           the start and end points.
-        2. the corresponding features on these points are computed by \
-           bilinear interpolation.
-        3. max pooling over all the `pool_size`+1 positions are used for \
-           computing pooled feature.
-
-    Args:
-        pool_size (int): number of positions sampled over the boxes' borders
-            (e.g. top, bottom, left, right).
-
-    """
-
-    def __init__(self, pool_size):
-        super(BorderAlign, self).__init__()
-        self.pool_size = pool_size
-
-    def forward(self, input, boxes):
-        """
-        Args:
-            input: Features with shape [N,4C,H,W]. Channels ranged in [0,C),
-                [C,2C), [2C,3C), [3C,4C) represent the top, left, bottom,
-                right features respectively.
-            boxes: Boxes with shape [N,H*W,4]. Coordinate format (x1,y1,x2,y2).
-
-        Returns:
-            Tensor: Pooled features with shape [N,C,H*W,4]. The order is
-                (top,left,bottom,right) for the last dimension.
-        """
-        return border_align(input, boxes, self.pool_size)
-
-    def __repr__(self):
-        s = self.__class__.__name__
-        s += f'(pool_size={self.pool_size})'
-        return s
diff --git a/spaces/Superlang/ImageProcessor/annotator/uniformer/mmcv/ops/deprecated_wrappers.py b/spaces/Superlang/ImageProcessor/annotator/uniformer/mmcv/ops/deprecated_wrappers.py
deleted file mode 100644
index a2e593df9ee57637038683d7a1efaa347b2b69e7..0000000000000000000000000000000000000000
--- a/spaces/Superlang/ImageProcessor/annotator/uniformer/mmcv/ops/deprecated_wrappers.py
+++ /dev/null
@@ -1,43 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-# This file is for backward compatibility.
-# Module wrappers for empty tensor have been moved to mmcv.cnn.bricks.
-import warnings
-
-from ..cnn.bricks.wrappers import Conv2d, ConvTranspose2d, Linear, MaxPool2d
-
-
-class Conv2d_deprecated(Conv2d):
-
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        warnings.warn(
-            'Importing Conv2d wrapper from "mmcv.ops" will be deprecated in'
-            ' the future. Please import them from "mmcv.cnn" instead')
-
-
-class ConvTranspose2d_deprecated(ConvTranspose2d):
-
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        warnings.warn(
-            'Importing ConvTranspose2d wrapper from "mmcv.ops" will be '
-            'deprecated in the future. Please import them from "mmcv.cnn" '
-            'instead')
-
-
-class MaxPool2d_deprecated(MaxPool2d):
-
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        warnings.warn(
-            'Importing MaxPool2d wrapper from "mmcv.ops" will be deprecated in'
-            ' the future. Please import them from "mmcv.cnn" instead')
-
-
-class Linear_deprecated(Linear):
-
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        warnings.warn(
-            'Importing Linear wrapper from "mmcv.ops" will be deprecated in'
-            ' the future. Please import them from "mmcv.cnn" instead')
diff --git a/spaces/TNR-5/Chatui/Dockerfile b/spaces/TNR-5/Chatui/Dockerfile
deleted file mode 100644
index 1f185cc85fa318fdf39f91be98db2bb7e805411c..0000000000000000000000000000000000000000
--- a/spaces/TNR-5/Chatui/Dockerfile
+++ /dev/null
@@ -1,121 +0,0 @@
-ARG MODEL_NAME
-ARG MODEL_PARAMS
-ARG APP_COLOR
-ARG APP_NAME
-
-
-FROM node:19 as chatui-builder
-ARG MODEL_NAME
-ARG MODEL_PARAMS
-ARG APP_COLOR
-ARG APP_NAME
-
-WORKDIR /app
-
-RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
-    git gettext && \
-    rm -rf /var/lib/apt/lists/*
-
-
-RUN git clone https://github.com/huggingface/chat-ui.git
-
-WORKDIR /app/chat-ui
-
-
-COPY .env.local.template .env.local.template
-
-RUN mkdir defaults
-ADD defaults /defaults
-RUN chmod -R 777 /defaults
-RUN --mount=type=secret,id=MONGODB_URL,mode=0444 \
-    MODEL_NAME="${MODEL_NAME:="$(cat /defaults/MODEL_NAME)"}" && export MODEL_NAME \
-    && MODEL_PARAMS="${MODEL_PARAMS:="$(cat /defaults/MODEL_PARAMS)"}" && export MODEL_PARAMS \
-    && APP_COLOR="${APP_COLOR:="$(cat /defaults/APP_COLOR)"}" && export APP_COLOR \
-    && APP_NAME="${APP_NAME:="$(cat /defaults/APP_NAME)"}" && export APP_NAME \
-    && MONGODB_URL=$(cat /run/secrets/MONGODB_URL > /dev/null | grep '^' || cat /defaults/MONGODB_URL) && export MONGODB_URL && \
-    echo "${MONGODB_URL}" && \
-    envsubst < ".env.local.template" > ".env.local" \ 
-    && rm .env.local.template
-
-
-
-RUN --mount=type=cache,target=/app/.npm \
-    npm set cache /app/.npm && \
-    npm ci
-
-RUN npm run build
-
-FROM ghcr.io/huggingface/text-generation-inference:latest
-
-ARG MODEL_NAME
-ARG MODEL_PARAMS
-ARG APP_COLOR
-ARG APP_NAME
-
-ENV TZ=Europe/Paris \
-    PORT=3000
-
-
-
-RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
-    gnupg \
-    curl \
-    gettext && \
-    rm -rf /var/lib/apt/lists/*
-COPY entrypoint.sh.template entrypoint.sh.template
-
-RUN mkdir defaults
-ADD defaults /defaults
-RUN chmod -R 777 /defaults
-
-RUN --mount=type=secret,id=MONGODB_URL,mode=0444 \
-    MODEL_NAME="${MODEL_NAME:="$(cat /defaults/MODEL_NAME)"}" && export MODEL_NAME \
-    && MODEL_PARAMS="${MODEL_PARAMS:="$(cat /defaults/MODEL_PARAMS)"}" && export MODEL_PARAMS \
-    && APP_COLOR="${APP_COLOR:="$(cat /defaults/APP_COLOR)"}" && export APP_COLOR \
-    && APP_NAME="${APP_NAME:="$(cat /defaults/APP_NAME)"}" && export APP_NAME \
-    && MONGODB_URL=$(cat /run/secrets/MONGODB_URL > /dev/null | grep '^' || cat /defaults/MONGODB_URL) && export MONGODB_URL &&  \
-    envsubst < "entrypoint.sh.template" > "entrypoint.sh" \
-    && rm entrypoint.sh.template
-
-
-RUN curl -fsSL https://pgp.mongodb.com/server-6.0.asc | \
-    gpg -o /usr/share/keyrings/mongodb-server-6.0.gpg \
-    --dearmor
-
-RUN echo "deb [ arch=amd64,arm64 signed-by=/usr/share/keyrings/mongodb-server-6.0.gpg ] https://repo.mongodb.org/apt/ubuntu focal/mongodb-org/6.0 multiverse" | tee /etc/apt/sources.list.d/mongodb-org-6.0.list
-
-RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
-    mongodb-org && \
-    rm -rf /var/lib/apt/lists/*
-
-RUN mkdir -p /data/db
-RUN chown -R 1000:1000 /data
-
-RUN curl -fsSL https://deb.nodesource.com/setup_19.x | /bin/bash -
-
-RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
-    nodejs && \
-    rm -rf /var/lib/apt/lists/*
-
-RUN mkdir /app
-RUN chown -R 1000:1000 /app
-
-RUN useradd -m -u 1000 user
-
-# Switch to the "user" user
-USER user
-
-ENV HOME=/home/user \
-    PATH=/home/user/.local/bin:$PATH
-
-RUN npm config set prefix /home/user/.local
-RUN npm install -g pm2
-
-COPY --from=chatui-builder --chown=1000 /app/chat-ui/node_modules /app/node_modules
-COPY --from=chatui-builder --chown=1000 /app/chat-ui/package.json /app/package.json
-COPY --from=chatui-builder --chown=1000 /app/chat-ui/build /app/build
-
-ENTRYPOINT ["/bin/bash"]
-CMD ["entrypoint.sh"]
-
-
diff --git a/spaces/TandCAcceptMe/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_vendor/chardet/langgreekmodel.py b/spaces/TandCAcceptMe/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_vendor/chardet/langgreekmodel.py
deleted file mode 100644
index cfb8639e5602578cb562ee7197d207dbb539cb74..0000000000000000000000000000000000000000
--- a/spaces/TandCAcceptMe/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_vendor/chardet/langgreekmodel.py
+++ /dev/null
@@ -1,4397 +0,0 @@
-from pip._vendor.chardet.sbcharsetprober import SingleByteCharSetModel
-
-# 3: Positive
-# 2: Likely
-# 1: Unlikely
-# 0: Negative
-
-GREEK_LANG_MODEL = {
-    60: {  # 'e'
-        60: 2,  # 'e'
-        55: 1,  # 'o'
-        58: 2,  # 't'
-        36: 1,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 1,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 0,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 0,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 0,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    55: {  # 'o'
-        60: 0,  # 'e'
-        55: 2,  # 'o'
-        58: 2,  # 't'
-        36: 1,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 0,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 1,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 0,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 1,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    58: {  # 't'
-        60: 2,  # 'e'
-        55: 1,  # 'o'
-        58: 1,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 2,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 0,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 1,  # 'ο'
-        9: 0,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 0,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    36: {  # '·'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 0,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 0,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 0,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    61: {  # 'Ά'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 0,  # 'β'
-        20: 1,  # 'γ'
-        21: 2,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 0,  # 'ι'
-        11: 0,  # 'κ'
-        16: 2,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 1,  # 'π'
-        8: 2,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 0,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    46: {  # 'Έ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 2,  # 'β'
-        20: 2,  # 'γ'
-        21: 0,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 0,  # 'ι'
-        11: 2,  # 'κ'
-        16: 2,  # 'λ'
-        10: 0,  # 'μ'
-        6: 3,  # 'ν'
-        30: 2,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 2,  # 'π'
-        8: 2,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 1,  # 'σ'
-        2: 2,  # 'τ'
-        12: 0,  # 'υ'
-        28: 2,  # 'φ'
-        23: 3,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    54: {  # 'Ό'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 0,  # 'ι'
-        11: 0,  # 'κ'
-        16: 2,  # 'λ'
-        10: 2,  # 'μ'
-        6: 2,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 2,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 2,  # 'σ'
-        2: 3,  # 'τ'
-        12: 0,  # 'υ'
-        28: 0,  # 'φ'
-        23: 2,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    31: {  # 'Α'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 2,  # 'Β'
-        43: 2,  # 'Γ'
-        41: 1,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 2,  # 'Θ'
-        47: 2,  # 'Ι'
-        44: 2,  # 'Κ'
-        53: 2,  # 'Λ'
-        38: 2,  # 'Μ'
-        49: 2,  # 'Ν'
-        59: 1,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 2,  # 'Π'
-        48: 2,  # 'Ρ'
-        37: 2,  # 'Σ'
-        33: 2,  # 'Τ'
-        45: 2,  # 'Υ'
-        56: 2,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 0,  # 'β'
-        20: 2,  # 'γ'
-        21: 0,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 1,  # 'θ'
-        5: 0,  # 'ι'
-        11: 2,  # 'κ'
-        16: 3,  # 'λ'
-        10: 2,  # 'μ'
-        6: 3,  # 'ν'
-        30: 2,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 3,  # 'π'
-        8: 3,  # 'ρ'
-        14: 2,  # 'ς'
-        7: 2,  # 'σ'
-        2: 0,  # 'τ'
-        12: 3,  # 'υ'
-        28: 2,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 2,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    51: {  # 'Β'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 2,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 1,  # 'Ε'
-        40: 1,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 1,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 1,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 2,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 2,  # 'ά'
-        18: 2,  # 'έ'
-        22: 2,  # 'ή'
-        15: 0,  # 'ί'
-        1: 2,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 2,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 2,  # 'ι'
-        11: 0,  # 'κ'
-        16: 2,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 2,  # 'ο'
-        9: 0,  # 'π'
-        8: 2,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 0,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    43: {  # 'Γ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 1,  # 'Α'
-        51: 0,  # 'Β'
-        43: 2,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 2,  # 'Ε'
-        40: 1,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 2,  # 'Ι'
-        44: 1,  # 'Κ'
-        53: 1,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 1,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 2,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 2,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 1,  # 'Χ'
-        57: 2,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 2,  # 'ί'
-        1: 2,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 2,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 3,  # 'ι'
-        11: 0,  # 'κ'
-        16: 2,  # 'λ'
-        10: 0,  # 'μ'
-        6: 2,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 0,  # 'π'
-        8: 2,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 0,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    41: {  # 'Δ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 2,  # 'Ε'
-        40: 2,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 2,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 2,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 2,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 2,  # 'ή'
-        15: 2,  # 'ί'
-        1: 0,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 2,  # 'η'
-        25: 0,  # 'θ'
-        5: 3,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 2,  # 'ο'
-        9: 0,  # 'π'
-        8: 2,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 2,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 2,  # 'ω'
-        19: 1,  # 'ό'
-        26: 2,  # 'ύ'
-        27: 2,  # 'ώ'
-    },
-    34: {  # 'Ε'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 2,  # 'Α'
-        51: 0,  # 'Β'
-        43: 2,  # 'Γ'
-        41: 2,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 2,  # 'Ι'
-        44: 2,  # 'Κ'
-        53: 2,  # 'Λ'
-        38: 2,  # 'Μ'
-        49: 2,  # 'Ν'
-        59: 1,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 2,  # 'Π'
-        48: 2,  # 'Ρ'
-        37: 2,  # 'Σ'
-        33: 2,  # 'Τ'
-        45: 2,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 2,  # 'Χ'
-        57: 2,  # 'Ω'
-        17: 3,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 3,  # 'ί'
-        1: 0,  # 'α'
-        29: 0,  # 'β'
-        20: 3,  # 'γ'
-        21: 2,  # 'δ'
-        3: 1,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 1,  # 'θ'
-        5: 2,  # 'ι'
-        11: 3,  # 'κ'
-        16: 3,  # 'λ'
-        10: 2,  # 'μ'
-        6: 3,  # 'ν'
-        30: 2,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 3,  # 'π'
-        8: 2,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 2,  # 'σ'
-        2: 2,  # 'τ'
-        12: 2,  # 'υ'
-        28: 2,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 1,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    40: {  # 'Η'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 1,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 2,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 2,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 2,  # 'Μ'
-        49: 2,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 2,  # 'Π'
-        48: 2,  # 'Ρ'
-        37: 2,  # 'Σ'
-        33: 2,  # 'Τ'
-        45: 1,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 0,  # 'ι'
-        11: 0,  # 'κ'
-        16: 2,  # 'λ'
-        10: 0,  # 'μ'
-        6: 1,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 0,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 0,  # 'υ'
-        28: 0,  # 'φ'
-        23: 1,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    52: {  # 'Θ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 2,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 2,  # 'Ε'
-        40: 2,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 2,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 1,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 1,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 2,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 3,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 2,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 0,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 0,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 2,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 2,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    47: {  # 'Ι'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 2,  # 'Α'
-        51: 1,  # 'Β'
-        43: 1,  # 'Γ'
-        41: 2,  # 'Δ'
-        34: 2,  # 'Ε'
-        40: 2,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 2,  # 'Κ'
-        53: 2,  # 'Λ'
-        38: 2,  # 'Μ'
-        49: 2,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 2,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 2,  # 'Ρ'
-        37: 2,  # 'Σ'
-        33: 2,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 2,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 2,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 2,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 2,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 0,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 1,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 2,  # 'ο'
-        9: 0,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 2,  # 'σ'
-        2: 1,  # 'τ'
-        12: 0,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 1,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    44: {  # 'Κ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 2,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 1,  # 'Δ'
-        34: 2,  # 'Ε'
-        40: 2,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 1,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 2,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 2,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 1,  # 'Τ'
-        45: 2,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 1,  # 'Ω'
-        17: 3,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 3,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 2,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 2,  # 'ι'
-        11: 0,  # 'κ'
-        16: 2,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 2,  # 'ο'
-        9: 0,  # 'π'
-        8: 2,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 2,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 2,  # 'ό'
-        26: 2,  # 'ύ'
-        27: 2,  # 'ώ'
-    },
-    53: {  # 'Λ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 2,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 2,  # 'Ε'
-        40: 2,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 2,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 2,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 2,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 2,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 2,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 2,  # 'Ω'
-        17: 2,  # 'ά'
-        18: 2,  # 'έ'
-        22: 0,  # 'ή'
-        15: 2,  # 'ί'
-        1: 2,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 2,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 1,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 2,  # 'ο'
-        9: 0,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 2,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 2,  # 'ό'
-        26: 2,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    38: {  # 'Μ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 2,  # 'Α'
-        51: 2,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 2,  # 'Ε'
-        40: 2,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 2,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 2,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 2,  # 'Ο'
-        35: 2,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 2,  # 'ά'
-        18: 2,  # 'έ'
-        22: 2,  # 'ή'
-        15: 2,  # 'ί'
-        1: 2,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 2,  # 'η'
-        25: 0,  # 'θ'
-        5: 3,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 2,  # 'ο'
-        9: 3,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 2,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 2,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    49: {  # 'Ν'
-        60: 2,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 2,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 2,  # 'Ε'
-        40: 2,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 2,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 2,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 2,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 2,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 2,  # 'έ'
-        22: 0,  # 'ή'
-        15: 2,  # 'ί'
-        1: 2,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 1,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 0,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 2,  # 'ο'
-        9: 0,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 0,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 1,  # 'ω'
-        19: 2,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    59: {  # 'Ξ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 1,  # 'Ε'
-        40: 1,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 1,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 2,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 2,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 2,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 0,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 0,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 0,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    39: {  # 'Ο'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 1,  # 'Β'
-        43: 2,  # 'Γ'
-        41: 2,  # 'Δ'
-        34: 2,  # 'Ε'
-        40: 1,  # 'Η'
-        52: 2,  # 'Θ'
-        47: 2,  # 'Ι'
-        44: 2,  # 'Κ'
-        53: 2,  # 'Λ'
-        38: 2,  # 'Μ'
-        49: 2,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 2,  # 'Π'
-        48: 2,  # 'Ρ'
-        37: 2,  # 'Σ'
-        33: 2,  # 'Τ'
-        45: 2,  # 'Υ'
-        56: 2,  # 'Φ'
-        50: 2,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 2,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 3,  # 'ι'
-        11: 2,  # 'κ'
-        16: 2,  # 'λ'
-        10: 2,  # 'μ'
-        6: 2,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 2,  # 'π'
-        8: 2,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 2,  # 'τ'
-        12: 2,  # 'υ'
-        28: 1,  # 'φ'
-        23: 1,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 2,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    35: {  # 'Π'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 2,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 2,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 2,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 2,  # 'Λ'
-        38: 1,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 2,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 2,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 1,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 1,  # 'Χ'
-        57: 2,  # 'Ω'
-        17: 2,  # 'ά'
-        18: 1,  # 'έ'
-        22: 1,  # 'ή'
-        15: 2,  # 'ί'
-        1: 3,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 2,  # 'η'
-        25: 0,  # 'θ'
-        5: 2,  # 'ι'
-        11: 0,  # 'κ'
-        16: 2,  # 'λ'
-        10: 0,  # 'μ'
-        6: 2,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 0,  # 'π'
-        8: 3,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 2,  # 'υ'
-        28: 0,  # 'φ'
-        23: 2,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 2,  # 'ω'
-        19: 2,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 3,  # 'ώ'
-    },
-    48: {  # 'Ρ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 2,  # 'Α'
-        51: 0,  # 'Β'
-        43: 1,  # 'Γ'
-        41: 1,  # 'Δ'
-        34: 2,  # 'Ε'
-        40: 2,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 2,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 2,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 2,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 2,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 1,  # 'Τ'
-        45: 1,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 1,  # 'Χ'
-        57: 1,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 2,  # 'ί'
-        1: 0,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 0,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 1,  # 'ο'
-        9: 0,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 3,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 2,  # 'ω'
-        19: 0,  # 'ό'
-        26: 2,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    37: {  # 'Σ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 2,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 1,  # 'Δ'
-        34: 2,  # 'Ε'
-        40: 2,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 2,  # 'Ι'
-        44: 2,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 2,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 2,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 2,  # 'Σ'
-        33: 2,  # 'Τ'
-        45: 2,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 2,  # 'Χ'
-        57: 2,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 2,  # 'ή'
-        15: 2,  # 'ί'
-        1: 2,  # 'α'
-        29: 2,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 3,  # 'η'
-        25: 0,  # 'θ'
-        5: 2,  # 'ι'
-        11: 2,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 2,  # 'ο'
-        9: 2,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 3,  # 'τ'
-        12: 3,  # 'υ'
-        28: 0,  # 'φ'
-        23: 2,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 2,  # 'ω'
-        19: 0,  # 'ό'
-        26: 2,  # 'ύ'
-        27: 2,  # 'ώ'
-    },
-    33: {  # 'Τ'
-        60: 0,  # 'e'
-        55: 1,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 2,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 2,  # 'Ε'
-        40: 2,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 2,  # 'Ι'
-        44: 2,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 2,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 2,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 1,  # 'Τ'
-        45: 1,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 2,  # 'Ω'
-        17: 2,  # 'ά'
-        18: 2,  # 'έ'
-        22: 0,  # 'ή'
-        15: 2,  # 'ί'
-        1: 3,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 2,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 2,  # 'η'
-        25: 0,  # 'θ'
-        5: 2,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 2,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 0,  # 'π'
-        8: 2,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 2,  # 'σ'
-        2: 0,  # 'τ'
-        12: 2,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 2,  # 'ό'
-        26: 2,  # 'ύ'
-        27: 3,  # 'ώ'
-    },
-    45: {  # 'Υ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 2,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 1,  # 'Ε'
-        40: 2,  # 'Η'
-        52: 2,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 1,  # 'Λ'
-        38: 2,  # 'Μ'
-        49: 2,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 2,  # 'Π'
-        48: 1,  # 'Ρ'
-        37: 2,  # 'Σ'
-        33: 2,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 1,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 0,  # 'ι'
-        11: 0,  # 'κ'
-        16: 2,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 3,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 0,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    56: {  # 'Φ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 1,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 1,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 2,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 2,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 2,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 2,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 2,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 2,  # 'ο'
-        9: 0,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 2,  # 'τ'
-        12: 2,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 1,  # 'ύ'
-        27: 1,  # 'ώ'
-    },
-    50: {  # 'Χ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 1,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 2,  # 'Ε'
-        40: 2,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 2,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 1,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 1,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 2,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 1,  # 'Χ'
-        57: 1,  # 'Ω'
-        17: 2,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 2,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 2,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 0,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 2,  # 'ο'
-        9: 0,  # 'π'
-        8: 3,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 2,  # 'τ'
-        12: 0,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 2,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    57: {  # 'Ω'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 1,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 1,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 2,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 2,  # 'Ρ'
-        37: 2,  # 'Σ'
-        33: 2,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 0,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 0,  # 'π'
-        8: 2,  # 'ρ'
-        14: 2,  # 'ς'
-        7: 2,  # 'σ'
-        2: 0,  # 'τ'
-        12: 0,  # 'υ'
-        28: 0,  # 'φ'
-        23: 1,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    17: {  # 'ά'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 2,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 3,  # 'β'
-        20: 3,  # 'γ'
-        21: 3,  # 'δ'
-        3: 3,  # 'ε'
-        32: 3,  # 'ζ'
-        13: 0,  # 'η'
-        25: 3,  # 'θ'
-        5: 2,  # 'ι'
-        11: 3,  # 'κ'
-        16: 3,  # 'λ'
-        10: 3,  # 'μ'
-        6: 3,  # 'ν'
-        30: 3,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 3,  # 'π'
-        8: 3,  # 'ρ'
-        14: 3,  # 'ς'
-        7: 3,  # 'σ'
-        2: 3,  # 'τ'
-        12: 0,  # 'υ'
-        28: 3,  # 'φ'
-        23: 3,  # 'χ'
-        42: 3,  # 'ψ'
-        24: 2,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    18: {  # 'έ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 3,  # 'α'
-        29: 2,  # 'β'
-        20: 3,  # 'γ'
-        21: 2,  # 'δ'
-        3: 3,  # 'ε'
-        32: 2,  # 'ζ'
-        13: 0,  # 'η'
-        25: 3,  # 'θ'
-        5: 0,  # 'ι'
-        11: 3,  # 'κ'
-        16: 3,  # 'λ'
-        10: 3,  # 'μ'
-        6: 3,  # 'ν'
-        30: 3,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 3,  # 'π'
-        8: 3,  # 'ρ'
-        14: 3,  # 'ς'
-        7: 3,  # 'σ'
-        2: 3,  # 'τ'
-        12: 0,  # 'υ'
-        28: 3,  # 'φ'
-        23: 3,  # 'χ'
-        42: 3,  # 'ψ'
-        24: 2,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    22: {  # 'ή'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 1,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 0,  # 'β'
-        20: 3,  # 'γ'
-        21: 3,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 3,  # 'θ'
-        5: 0,  # 'ι'
-        11: 3,  # 'κ'
-        16: 2,  # 'λ'
-        10: 3,  # 'μ'
-        6: 3,  # 'ν'
-        30: 2,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 3,  # 'π'
-        8: 3,  # 'ρ'
-        14: 3,  # 'ς'
-        7: 3,  # 'σ'
-        2: 3,  # 'τ'
-        12: 0,  # 'υ'
-        28: 2,  # 'φ'
-        23: 3,  # 'χ'
-        42: 2,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    15: {  # 'ί'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 3,  # 'α'
-        29: 2,  # 'β'
-        20: 3,  # 'γ'
-        21: 3,  # 'δ'
-        3: 3,  # 'ε'
-        32: 3,  # 'ζ'
-        13: 3,  # 'η'
-        25: 3,  # 'θ'
-        5: 0,  # 'ι'
-        11: 3,  # 'κ'
-        16: 3,  # 'λ'
-        10: 3,  # 'μ'
-        6: 3,  # 'ν'
-        30: 3,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 3,  # 'π'
-        8: 3,  # 'ρ'
-        14: 3,  # 'ς'
-        7: 3,  # 'σ'
-        2: 3,  # 'τ'
-        12: 0,  # 'υ'
-        28: 1,  # 'φ'
-        23: 3,  # 'χ'
-        42: 2,  # 'ψ'
-        24: 3,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    1: {  # 'α'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 2,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 2,  # 'έ'
-        22: 0,  # 'ή'
-        15: 3,  # 'ί'
-        1: 0,  # 'α'
-        29: 3,  # 'β'
-        20: 3,  # 'γ'
-        21: 3,  # 'δ'
-        3: 2,  # 'ε'
-        32: 3,  # 'ζ'
-        13: 1,  # 'η'
-        25: 3,  # 'θ'
-        5: 3,  # 'ι'
-        11: 3,  # 'κ'
-        16: 3,  # 'λ'
-        10: 3,  # 'μ'
-        6: 3,  # 'ν'
-        30: 3,  # 'ξ'
-        4: 2,  # 'ο'
-        9: 3,  # 'π'
-        8: 3,  # 'ρ'
-        14: 3,  # 'ς'
-        7: 3,  # 'σ'
-        2: 3,  # 'τ'
-        12: 3,  # 'υ'
-        28: 3,  # 'φ'
-        23: 3,  # 'χ'
-        42: 2,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 2,  # 'ό'
-        26: 2,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    29: {  # 'β'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 3,  # 'ά'
-        18: 2,  # 'έ'
-        22: 3,  # 'ή'
-        15: 2,  # 'ί'
-        1: 3,  # 'α'
-        29: 0,  # 'β'
-        20: 2,  # 'γ'
-        21: 2,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 2,  # 'η'
-        25: 0,  # 'θ'
-        5: 3,  # 'ι'
-        11: 0,  # 'κ'
-        16: 3,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 0,  # 'π'
-        8: 3,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 0,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 2,  # 'ω'
-        19: 2,  # 'ό'
-        26: 2,  # 'ύ'
-        27: 2,  # 'ώ'
-    },
-    20: {  # 'γ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 3,  # 'ά'
-        18: 3,  # 'έ'
-        22: 3,  # 'ή'
-        15: 3,  # 'ί'
-        1: 3,  # 'α'
-        29: 0,  # 'β'
-        20: 3,  # 'γ'
-        21: 0,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 3,  # 'η'
-        25: 0,  # 'θ'
-        5: 3,  # 'ι'
-        11: 3,  # 'κ'
-        16: 3,  # 'λ'
-        10: 3,  # 'μ'
-        6: 3,  # 'ν'
-        30: 3,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 0,  # 'π'
-        8: 3,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 2,  # 'υ'
-        28: 0,  # 'φ'
-        23: 3,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 3,  # 'ω'
-        19: 3,  # 'ό'
-        26: 2,  # 'ύ'
-        27: 3,  # 'ώ'
-    },
-    21: {  # 'δ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 2,  # 'ά'
-        18: 3,  # 'έ'
-        22: 3,  # 'ή'
-        15: 3,  # 'ί'
-        1: 3,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 3,  # 'η'
-        25: 0,  # 'θ'
-        5: 3,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 0,  # 'π'
-        8: 3,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 3,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 3,  # 'ω'
-        19: 3,  # 'ό'
-        26: 3,  # 'ύ'
-        27: 3,  # 'ώ'
-    },
-    3: {  # 'ε'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 2,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 3,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 3,  # 'ί'
-        1: 2,  # 'α'
-        29: 3,  # 'β'
-        20: 3,  # 'γ'
-        21: 3,  # 'δ'
-        3: 2,  # 'ε'
-        32: 2,  # 'ζ'
-        13: 0,  # 'η'
-        25: 3,  # 'θ'
-        5: 3,  # 'ι'
-        11: 3,  # 'κ'
-        16: 3,  # 'λ'
-        10: 3,  # 'μ'
-        6: 3,  # 'ν'
-        30: 3,  # 'ξ'
-        4: 2,  # 'ο'
-        9: 3,  # 'π'
-        8: 3,  # 'ρ'
-        14: 3,  # 'ς'
-        7: 3,  # 'σ'
-        2: 3,  # 'τ'
-        12: 3,  # 'υ'
-        28: 3,  # 'φ'
-        23: 3,  # 'χ'
-        42: 2,  # 'ψ'
-        24: 3,  # 'ω'
-        19: 2,  # 'ό'
-        26: 3,  # 'ύ'
-        27: 2,  # 'ώ'
-    },
-    32: {  # 'ζ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 2,  # 'ά'
-        18: 2,  # 'έ'
-        22: 2,  # 'ή'
-        15: 2,  # 'ί'
-        1: 2,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 3,  # 'η'
-        25: 0,  # 'θ'
-        5: 2,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 0,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 1,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 3,  # 'ω'
-        19: 2,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 2,  # 'ώ'
-    },
-    13: {  # 'η'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 2,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 0,  # 'β'
-        20: 3,  # 'γ'
-        21: 2,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 3,  # 'θ'
-        5: 0,  # 'ι'
-        11: 3,  # 'κ'
-        16: 3,  # 'λ'
-        10: 3,  # 'μ'
-        6: 3,  # 'ν'
-        30: 2,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 2,  # 'π'
-        8: 3,  # 'ρ'
-        14: 3,  # 'ς'
-        7: 3,  # 'σ'
-        2: 3,  # 'τ'
-        12: 0,  # 'υ'
-        28: 2,  # 'φ'
-        23: 3,  # 'χ'
-        42: 2,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    25: {  # 'θ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 2,  # 'ά'
-        18: 3,  # 'έ'
-        22: 3,  # 'ή'
-        15: 2,  # 'ί'
-        1: 3,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 3,  # 'η'
-        25: 0,  # 'θ'
-        5: 3,  # 'ι'
-        11: 0,  # 'κ'
-        16: 1,  # 'λ'
-        10: 3,  # 'μ'
-        6: 2,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 0,  # 'π'
-        8: 3,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 3,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 3,  # 'ω'
-        19: 3,  # 'ό'
-        26: 3,  # 'ύ'
-        27: 3,  # 'ώ'
-    },
-    5: {  # 'ι'
-        60: 0,  # 'e'
-        55: 1,  # 'o'
-        58: 0,  # 't'
-        36: 2,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 1,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 3,  # 'ά'
-        18: 3,  # 'έ'
-        22: 3,  # 'ή'
-        15: 0,  # 'ί'
-        1: 3,  # 'α'
-        29: 3,  # 'β'
-        20: 3,  # 'γ'
-        21: 3,  # 'δ'
-        3: 3,  # 'ε'
-        32: 2,  # 'ζ'
-        13: 3,  # 'η'
-        25: 3,  # 'θ'
-        5: 0,  # 'ι'
-        11: 3,  # 'κ'
-        16: 3,  # 'λ'
-        10: 3,  # 'μ'
-        6: 3,  # 'ν'
-        30: 3,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 3,  # 'π'
-        8: 3,  # 'ρ'
-        14: 3,  # 'ς'
-        7: 3,  # 'σ'
-        2: 3,  # 'τ'
-        12: 0,  # 'υ'
-        28: 2,  # 'φ'
-        23: 3,  # 'χ'
-        42: 2,  # 'ψ'
-        24: 3,  # 'ω'
-        19: 3,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 3,  # 'ώ'
-    },
-    11: {  # 'κ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 3,  # 'ά'
-        18: 3,  # 'έ'
-        22: 3,  # 'ή'
-        15: 3,  # 'ί'
-        1: 3,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 3,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 3,  # 'η'
-        25: 2,  # 'θ'
-        5: 3,  # 'ι'
-        11: 3,  # 'κ'
-        16: 3,  # 'λ'
-        10: 3,  # 'μ'
-        6: 2,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 2,  # 'π'
-        8: 3,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 3,  # 'τ'
-        12: 3,  # 'υ'
-        28: 2,  # 'φ'
-        23: 2,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 3,  # 'ω'
-        19: 3,  # 'ό'
-        26: 3,  # 'ύ'
-        27: 3,  # 'ώ'
-    },
-    16: {  # 'λ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 3,  # 'ά'
-        18: 3,  # 'έ'
-        22: 3,  # 'ή'
-        15: 3,  # 'ί'
-        1: 3,  # 'α'
-        29: 1,  # 'β'
-        20: 2,  # 'γ'
-        21: 1,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 3,  # 'η'
-        25: 2,  # 'θ'
-        5: 3,  # 'ι'
-        11: 2,  # 'κ'
-        16: 3,  # 'λ'
-        10: 2,  # 'μ'
-        6: 2,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 3,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 3,  # 'τ'
-        12: 3,  # 'υ'
-        28: 2,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 3,  # 'ω'
-        19: 3,  # 'ό'
-        26: 3,  # 'ύ'
-        27: 3,  # 'ώ'
-    },
-    10: {  # 'μ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 1,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 3,  # 'ά'
-        18: 3,  # 'έ'
-        22: 3,  # 'ή'
-        15: 3,  # 'ί'
-        1: 3,  # 'α'
-        29: 3,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 3,  # 'η'
-        25: 0,  # 'θ'
-        5: 3,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 3,  # 'μ'
-        6: 3,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 3,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 2,  # 'υ'
-        28: 3,  # 'φ'
-        23: 0,  # 'χ'
-        42: 2,  # 'ψ'
-        24: 3,  # 'ω'
-        19: 3,  # 'ό'
-        26: 2,  # 'ύ'
-        27: 2,  # 'ώ'
-    },
-    6: {  # 'ν'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 2,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 3,  # 'ά'
-        18: 3,  # 'έ'
-        22: 3,  # 'ή'
-        15: 3,  # 'ί'
-        1: 3,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 3,  # 'δ'
-        3: 3,  # 'ε'
-        32: 2,  # 'ζ'
-        13: 3,  # 'η'
-        25: 3,  # 'θ'
-        5: 3,  # 'ι'
-        11: 0,  # 'κ'
-        16: 1,  # 'λ'
-        10: 0,  # 'μ'
-        6: 2,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 0,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 3,  # 'σ'
-        2: 3,  # 'τ'
-        12: 3,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 3,  # 'ω'
-        19: 3,  # 'ό'
-        26: 3,  # 'ύ'
-        27: 3,  # 'ώ'
-    },
-    30: {  # 'ξ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 2,  # 'ά'
-        18: 3,  # 'έ'
-        22: 3,  # 'ή'
-        15: 2,  # 'ί'
-        1: 3,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 3,  # 'η'
-        25: 0,  # 'θ'
-        5: 2,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 0,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 3,  # 'τ'
-        12: 2,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 3,  # 'ω'
-        19: 2,  # 'ό'
-        26: 3,  # 'ύ'
-        27: 1,  # 'ώ'
-    },
-    4: {  # 'ο'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 2,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 2,  # 'έ'
-        22: 3,  # 'ή'
-        15: 3,  # 'ί'
-        1: 2,  # 'α'
-        29: 3,  # 'β'
-        20: 3,  # 'γ'
-        21: 3,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 3,  # 'η'
-        25: 3,  # 'θ'
-        5: 3,  # 'ι'
-        11: 3,  # 'κ'
-        16: 3,  # 'λ'
-        10: 3,  # 'μ'
-        6: 3,  # 'ν'
-        30: 2,  # 'ξ'
-        4: 2,  # 'ο'
-        9: 3,  # 'π'
-        8: 3,  # 'ρ'
-        14: 3,  # 'ς'
-        7: 3,  # 'σ'
-        2: 3,  # 'τ'
-        12: 3,  # 'υ'
-        28: 3,  # 'φ'
-        23: 3,  # 'χ'
-        42: 2,  # 'ψ'
-        24: 2,  # 'ω'
-        19: 1,  # 'ό'
-        26: 3,  # 'ύ'
-        27: 2,  # 'ώ'
-    },
-    9: {  # 'π'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 3,  # 'ά'
-        18: 3,  # 'έ'
-        22: 3,  # 'ή'
-        15: 3,  # 'ί'
-        1: 3,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 3,  # 'η'
-        25: 0,  # 'θ'
-        5: 3,  # 'ι'
-        11: 0,  # 'κ'
-        16: 3,  # 'λ'
-        10: 0,  # 'μ'
-        6: 2,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 0,  # 'π'
-        8: 3,  # 'ρ'
-        14: 2,  # 'ς'
-        7: 0,  # 'σ'
-        2: 3,  # 'τ'
-        12: 3,  # 'υ'
-        28: 0,  # 'φ'
-        23: 2,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 3,  # 'ω'
-        19: 3,  # 'ό'
-        26: 2,  # 'ύ'
-        27: 3,  # 'ώ'
-    },
-    8: {  # 'ρ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 3,  # 'ά'
-        18: 3,  # 'έ'
-        22: 3,  # 'ή'
-        15: 3,  # 'ί'
-        1: 3,  # 'α'
-        29: 2,  # 'β'
-        20: 3,  # 'γ'
-        21: 2,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 3,  # 'η'
-        25: 3,  # 'θ'
-        5: 3,  # 'ι'
-        11: 3,  # 'κ'
-        16: 1,  # 'λ'
-        10: 3,  # 'μ'
-        6: 3,  # 'ν'
-        30: 2,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 2,  # 'π'
-        8: 2,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 2,  # 'σ'
-        2: 3,  # 'τ'
-        12: 3,  # 'υ'
-        28: 3,  # 'φ'
-        23: 3,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 3,  # 'ω'
-        19: 3,  # 'ό'
-        26: 3,  # 'ύ'
-        27: 3,  # 'ώ'
-    },
-    14: {  # 'ς'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 2,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 0,  # 'θ'
-        5: 0,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 0,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 0,  # 'τ'
-        12: 0,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    7: {  # 'σ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 2,  # 'ά'
-        18: 2,  # 'έ'
-        22: 3,  # 'ή'
-        15: 3,  # 'ί'
-        1: 3,  # 'α'
-        29: 3,  # 'β'
-        20: 0,  # 'γ'
-        21: 2,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 3,  # 'η'
-        25: 3,  # 'θ'
-        5: 3,  # 'ι'
-        11: 3,  # 'κ'
-        16: 2,  # 'λ'
-        10: 3,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 3,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 3,  # 'σ'
-        2: 3,  # 'τ'
-        12: 3,  # 'υ'
-        28: 3,  # 'φ'
-        23: 3,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 3,  # 'ω'
-        19: 3,  # 'ό'
-        26: 3,  # 'ύ'
-        27: 2,  # 'ώ'
-    },
-    2: {  # 'τ'
-        60: 0,  # 'e'
-        55: 2,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 3,  # 'ά'
-        18: 3,  # 'έ'
-        22: 3,  # 'ή'
-        15: 3,  # 'ί'
-        1: 3,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 3,  # 'ε'
-        32: 2,  # 'ζ'
-        13: 3,  # 'η'
-        25: 0,  # 'θ'
-        5: 3,  # 'ι'
-        11: 2,  # 'κ'
-        16: 2,  # 'λ'
-        10: 3,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 0,  # 'π'
-        8: 3,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 3,  # 'σ'
-        2: 3,  # 'τ'
-        12: 3,  # 'υ'
-        28: 2,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 3,  # 'ω'
-        19: 3,  # 'ό'
-        26: 3,  # 'ύ'
-        27: 3,  # 'ώ'
-    },
-    12: {  # 'υ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 2,  # 'ά'
-        18: 2,  # 'έ'
-        22: 3,  # 'ή'
-        15: 2,  # 'ί'
-        1: 3,  # 'α'
-        29: 2,  # 'β'
-        20: 3,  # 'γ'
-        21: 2,  # 'δ'
-        3: 2,  # 'ε'
-        32: 2,  # 'ζ'
-        13: 2,  # 'η'
-        25: 3,  # 'θ'
-        5: 2,  # 'ι'
-        11: 3,  # 'κ'
-        16: 3,  # 'λ'
-        10: 3,  # 'μ'
-        6: 3,  # 'ν'
-        30: 3,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 3,  # 'π'
-        8: 3,  # 'ρ'
-        14: 3,  # 'ς'
-        7: 3,  # 'σ'
-        2: 3,  # 'τ'
-        12: 0,  # 'υ'
-        28: 2,  # 'φ'
-        23: 3,  # 'χ'
-        42: 2,  # 'ψ'
-        24: 2,  # 'ω'
-        19: 2,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 2,  # 'ώ'
-    },
-    28: {  # 'φ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 3,  # 'ά'
-        18: 3,  # 'έ'
-        22: 3,  # 'ή'
-        15: 3,  # 'ί'
-        1: 3,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 2,  # 'η'
-        25: 2,  # 'θ'
-        5: 3,  # 'ι'
-        11: 0,  # 'κ'
-        16: 2,  # 'λ'
-        10: 0,  # 'μ'
-        6: 1,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 0,  # 'π'
-        8: 3,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 3,  # 'τ'
-        12: 3,  # 'υ'
-        28: 1,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 3,  # 'ω'
-        19: 3,  # 'ό'
-        26: 2,  # 'ύ'
-        27: 2,  # 'ώ'
-    },
-    23: {  # 'χ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 3,  # 'ά'
-        18: 2,  # 'έ'
-        22: 3,  # 'ή'
-        15: 3,  # 'ί'
-        1: 3,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 2,  # 'η'
-        25: 2,  # 'θ'
-        5: 3,  # 'ι'
-        11: 0,  # 'κ'
-        16: 2,  # 'λ'
-        10: 2,  # 'μ'
-        6: 3,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 0,  # 'π'
-        8: 3,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 3,  # 'τ'
-        12: 3,  # 'υ'
-        28: 0,  # 'φ'
-        23: 2,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 3,  # 'ω'
-        19: 3,  # 'ό'
-        26: 3,  # 'ύ'
-        27: 3,  # 'ώ'
-    },
-    42: {  # 'ψ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 2,  # 'ά'
-        18: 2,  # 'έ'
-        22: 1,  # 'ή'
-        15: 2,  # 'ί'
-        1: 2,  # 'α'
-        29: 0,  # 'β'
-        20: 0,  # 'γ'
-        21: 0,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 3,  # 'η'
-        25: 0,  # 'θ'
-        5: 2,  # 'ι'
-        11: 0,  # 'κ'
-        16: 0,  # 'λ'
-        10: 0,  # 'μ'
-        6: 0,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 2,  # 'ο'
-        9: 0,  # 'π'
-        8: 0,  # 'ρ'
-        14: 0,  # 'ς'
-        7: 0,  # 'σ'
-        2: 2,  # 'τ'
-        12: 1,  # 'υ'
-        28: 0,  # 'φ'
-        23: 0,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 2,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    24: {  # 'ω'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 1,  # 'ά'
-        18: 0,  # 'έ'
-        22: 2,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 2,  # 'β'
-        20: 3,  # 'γ'
-        21: 2,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 0,  # 'η'
-        25: 3,  # 'θ'
-        5: 2,  # 'ι'
-        11: 0,  # 'κ'
-        16: 2,  # 'λ'
-        10: 3,  # 'μ'
-        6: 3,  # 'ν'
-        30: 0,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 3,  # 'π'
-        8: 3,  # 'ρ'
-        14: 3,  # 'ς'
-        7: 3,  # 'σ'
-        2: 3,  # 'τ'
-        12: 0,  # 'υ'
-        28: 2,  # 'φ'
-        23: 2,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    19: {  # 'ό'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 3,  # 'β'
-        20: 3,  # 'γ'
-        21: 3,  # 'δ'
-        3: 1,  # 'ε'
-        32: 2,  # 'ζ'
-        13: 2,  # 'η'
-        25: 2,  # 'θ'
-        5: 2,  # 'ι'
-        11: 3,  # 'κ'
-        16: 3,  # 'λ'
-        10: 3,  # 'μ'
-        6: 3,  # 'ν'
-        30: 1,  # 'ξ'
-        4: 2,  # 'ο'
-        9: 3,  # 'π'
-        8: 3,  # 'ρ'
-        14: 3,  # 'ς'
-        7: 3,  # 'σ'
-        2: 3,  # 'τ'
-        12: 0,  # 'υ'
-        28: 2,  # 'φ'
-        23: 3,  # 'χ'
-        42: 2,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    26: {  # 'ύ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 2,  # 'α'
-        29: 2,  # 'β'
-        20: 2,  # 'γ'
-        21: 1,  # 'δ'
-        3: 3,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 2,  # 'η'
-        25: 3,  # 'θ'
-        5: 0,  # 'ι'
-        11: 3,  # 'κ'
-        16: 3,  # 'λ'
-        10: 3,  # 'μ'
-        6: 3,  # 'ν'
-        30: 2,  # 'ξ'
-        4: 3,  # 'ο'
-        9: 3,  # 'π'
-        8: 3,  # 'ρ'
-        14: 3,  # 'ς'
-        7: 3,  # 'σ'
-        2: 3,  # 'τ'
-        12: 0,  # 'υ'
-        28: 2,  # 'φ'
-        23: 2,  # 'χ'
-        42: 2,  # 'ψ'
-        24: 2,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-    27: {  # 'ώ'
-        60: 0,  # 'e'
-        55: 0,  # 'o'
-        58: 0,  # 't'
-        36: 0,  # '·'
-        61: 0,  # 'Ά'
-        46: 0,  # 'Έ'
-        54: 0,  # 'Ό'
-        31: 0,  # 'Α'
-        51: 0,  # 'Β'
-        43: 0,  # 'Γ'
-        41: 0,  # 'Δ'
-        34: 0,  # 'Ε'
-        40: 0,  # 'Η'
-        52: 0,  # 'Θ'
-        47: 0,  # 'Ι'
-        44: 0,  # 'Κ'
-        53: 0,  # 'Λ'
-        38: 0,  # 'Μ'
-        49: 0,  # 'Ν'
-        59: 0,  # 'Ξ'
-        39: 0,  # 'Ο'
-        35: 0,  # 'Π'
-        48: 0,  # 'Ρ'
-        37: 0,  # 'Σ'
-        33: 0,  # 'Τ'
-        45: 0,  # 'Υ'
-        56: 0,  # 'Φ'
-        50: 0,  # 'Χ'
-        57: 0,  # 'Ω'
-        17: 0,  # 'ά'
-        18: 0,  # 'έ'
-        22: 0,  # 'ή'
-        15: 0,  # 'ί'
-        1: 0,  # 'α'
-        29: 1,  # 'β'
-        20: 0,  # 'γ'
-        21: 3,  # 'δ'
-        3: 0,  # 'ε'
-        32: 0,  # 'ζ'
-        13: 1,  # 'η'
-        25: 2,  # 'θ'
-        5: 2,  # 'ι'
-        11: 0,  # 'κ'
-        16: 2,  # 'λ'
-        10: 3,  # 'μ'
-        6: 3,  # 'ν'
-        30: 1,  # 'ξ'
-        4: 0,  # 'ο'
-        9: 2,  # 'π'
-        8: 3,  # 'ρ'
-        14: 3,  # 'ς'
-        7: 3,  # 'σ'
-        2: 3,  # 'τ'
-        12: 0,  # 'υ'
-        28: 1,  # 'φ'
-        23: 1,  # 'χ'
-        42: 0,  # 'ψ'
-        24: 0,  # 'ω'
-        19: 0,  # 'ό'
-        26: 0,  # 'ύ'
-        27: 0,  # 'ώ'
-    },
-}
-
-# 255: Undefined characters that did not exist in training text
-# 254: Carriage/Return
-# 253: symbol (punctuation) that does not belong to word
-# 252: 0 - 9
-# 251: Control characters
-
-# Character Mapping Table(s):
-WINDOWS_1253_GREEK_CHAR_TO_ORDER = {
-    0: 255,  # '\x00'
-    1: 255,  # '\x01'
-    2: 255,  # '\x02'
-    3: 255,  # '\x03'
-    4: 255,  # '\x04'
-    5: 255,  # '\x05'
-    6: 255,  # '\x06'
-    7: 255,  # '\x07'
-    8: 255,  # '\x08'
-    9: 255,  # '\t'
-    10: 254,  # '\n'
-    11: 255,  # '\x0b'
-    12: 255,  # '\x0c'
-    13: 254,  # '\r'
-    14: 255,  # '\x0e'
-    15: 255,  # '\x0f'
-    16: 255,  # '\x10'
-    17: 255,  # '\x11'
-    18: 255,  # '\x12'
-    19: 255,  # '\x13'
-    20: 255,  # '\x14'
-    21: 255,  # '\x15'
-    22: 255,  # '\x16'
-    23: 255,  # '\x17'
-    24: 255,  # '\x18'
-    25: 255,  # '\x19'
-    26: 255,  # '\x1a'
-    27: 255,  # '\x1b'
-    28: 255,  # '\x1c'
-    29: 255,  # '\x1d'
-    30: 255,  # '\x1e'
-    31: 255,  # '\x1f'
-    32: 253,  # ' '
-    33: 253,  # '!'
-    34: 253,  # '"'
-    35: 253,  # '#'
-    36: 253,  # '$'
-    37: 253,  # '%'
-    38: 253,  # '&'
-    39: 253,  # "'"
-    40: 253,  # '('
-    41: 253,  # ')'
-    42: 253,  # '*'
-    43: 253,  # '+'
-    44: 253,  # ','
-    45: 253,  # '-'
-    46: 253,  # '.'
-    47: 253,  # '/'
-    48: 252,  # '0'
-    49: 252,  # '1'
-    50: 252,  # '2'
-    51: 252,  # '3'
-    52: 252,  # '4'
-    53: 252,  # '5'
-    54: 252,  # '6'
-    55: 252,  # '7'
-    56: 252,  # '8'
-    57: 252,  # '9'
-    58: 253,  # ':'
-    59: 253,  # ';'
-    60: 253,  # '<'
-    61: 253,  # '='
-    62: 253,  # '>'
-    63: 253,  # '?'
-    64: 253,  # '@'
-    65: 82,  # 'A'
-    66: 100,  # 'B'
-    67: 104,  # 'C'
-    68: 94,  # 'D'
-    69: 98,  # 'E'
-    70: 101,  # 'F'
-    71: 116,  # 'G'
-    72: 102,  # 'H'
-    73: 111,  # 'I'
-    74: 187,  # 'J'
-    75: 117,  # 'K'
-    76: 92,  # 'L'
-    77: 88,  # 'M'
-    78: 113,  # 'N'
-    79: 85,  # 'O'
-    80: 79,  # 'P'
-    81: 118,  # 'Q'
-    82: 105,  # 'R'
-    83: 83,  # 'S'
-    84: 67,  # 'T'
-    85: 114,  # 'U'
-    86: 119,  # 'V'
-    87: 95,  # 'W'
-    88: 99,  # 'X'
-    89: 109,  # 'Y'
-    90: 188,  # 'Z'
-    91: 253,  # '['
-    92: 253,  # '\\'
-    93: 253,  # ']'
-    94: 253,  # '^'
-    95: 253,  # '_'
-    96: 253,  # '`'
-    97: 72,  # 'a'
-    98: 70,  # 'b'
-    99: 80,  # 'c'
-    100: 81,  # 'd'
-    101: 60,  # 'e'
-    102: 96,  # 'f'
-    103: 93,  # 'g'
-    104: 89,  # 'h'
-    105: 68,  # 'i'
-    106: 120,  # 'j'
-    107: 97,  # 'k'
-    108: 77,  # 'l'
-    109: 86,  # 'm'
-    110: 69,  # 'n'
-    111: 55,  # 'o'
-    112: 78,  # 'p'
-    113: 115,  # 'q'
-    114: 65,  # 'r'
-    115: 66,  # 's'
-    116: 58,  # 't'
-    117: 76,  # 'u'
-    118: 106,  # 'v'
-    119: 103,  # 'w'
-    120: 87,  # 'x'
-    121: 107,  # 'y'
-    122: 112,  # 'z'
-    123: 253,  # '{'
-    124: 253,  # '|'
-    125: 253,  # '}'
-    126: 253,  # '~'
-    127: 253,  # '\x7f'
-    128: 255,  # '€'
-    129: 255,  # None
-    130: 255,  # '‚'
-    131: 255,  # 'ƒ'
-    132: 255,  # '„'
-    133: 255,  # '…'
-    134: 255,  # '†'
-    135: 255,  # '‡'
-    136: 255,  # None
-    137: 255,  # '‰'
-    138: 255,  # None
-    139: 255,  # '‹'
-    140: 255,  # None
-    141: 255,  # None
-    142: 255,  # None
-    143: 255,  # None
-    144: 255,  # None
-    145: 255,  # '‘'
-    146: 255,  # '’'
-    147: 255,  # '“'
-    148: 255,  # '”'
-    149: 255,  # '•'
-    150: 255,  # '–'
-    151: 255,  # '—'
-    152: 255,  # None
-    153: 255,  # '™'
-    154: 255,  # None
-    155: 255,  # '›'
-    156: 255,  # None
-    157: 255,  # None
-    158: 255,  # None
-    159: 255,  # None
-    160: 253,  # '\xa0'
-    161: 233,  # '΅'
-    162: 61,  # 'Ά'
-    163: 253,  # '£'
-    164: 253,  # '¤'
-    165: 253,  # '¥'
-    166: 253,  # '¦'
-    167: 253,  # '§'
-    168: 253,  # '¨'
-    169: 253,  # '©'
-    170: 253,  # None
-    171: 253,  # '«'
-    172: 253,  # '¬'
-    173: 74,  # '\xad'
-    174: 253,  # '®'
-    175: 253,  # '―'
-    176: 253,  # '°'
-    177: 253,  # '±'
-    178: 253,  # '²'
-    179: 253,  # '³'
-    180: 247,  # '΄'
-    181: 253,  # 'µ'
-    182: 253,  # '¶'
-    183: 36,  # '·'
-    184: 46,  # 'Έ'
-    185: 71,  # 'Ή'
-    186: 73,  # 'Ί'
-    187: 253,  # '»'
-    188: 54,  # 'Ό'
-    189: 253,  # '½'
-    190: 108,  # 'Ύ'
-    191: 123,  # 'Ώ'
-    192: 110,  # 'ΐ'
-    193: 31,  # 'Α'
-    194: 51,  # 'Β'
-    195: 43,  # 'Γ'
-    196: 41,  # 'Δ'
-    197: 34,  # 'Ε'
-    198: 91,  # 'Ζ'
-    199: 40,  # 'Η'
-    200: 52,  # 'Θ'
-    201: 47,  # 'Ι'
-    202: 44,  # 'Κ'
-    203: 53,  # 'Λ'
-    204: 38,  # 'Μ'
-    205: 49,  # 'Ν'
-    206: 59,  # 'Ξ'
-    207: 39,  # 'Ο'
-    208: 35,  # 'Π'
-    209: 48,  # 'Ρ'
-    210: 250,  # None
-    211: 37,  # 'Σ'
-    212: 33,  # 'Τ'
-    213: 45,  # 'Υ'
-    214: 56,  # 'Φ'
-    215: 50,  # 'Χ'
-    216: 84,  # 'Ψ'
-    217: 57,  # 'Ω'
-    218: 120,  # 'Ϊ'
-    219: 121,  # 'Ϋ'
-    220: 17,  # 'ά'
-    221: 18,  # 'έ'
-    222: 22,  # 'ή'
-    223: 15,  # 'ί'
-    224: 124,  # 'ΰ'
-    225: 1,  # 'α'
-    226: 29,  # 'β'
-    227: 20,  # 'γ'
-    228: 21,  # 'δ'
-    229: 3,  # 'ε'
-    230: 32,  # 'ζ'
-    231: 13,  # 'η'
-    232: 25,  # 'θ'
-    233: 5,  # 'ι'
-    234: 11,  # 'κ'
-    235: 16,  # 'λ'
-    236: 10,  # 'μ'
-    237: 6,  # 'ν'
-    238: 30,  # 'ξ'
-    239: 4,  # 'ο'
-    240: 9,  # 'π'
-    241: 8,  # 'ρ'
-    242: 14,  # 'ς'
-    243: 7,  # 'σ'
-    244: 2,  # 'τ'
-    245: 12,  # 'υ'
-    246: 28,  # 'φ'
-    247: 23,  # 'χ'
-    248: 42,  # 'ψ'
-    249: 24,  # 'ω'
-    250: 64,  # 'ϊ'
-    251: 75,  # 'ϋ'
-    252: 19,  # 'ό'
-    253: 26,  # 'ύ'
-    254: 27,  # 'ώ'
-    255: 253,  # None
-}
-
-WINDOWS_1253_GREEK_MODEL = SingleByteCharSetModel(
-    charset_name="windows-1253",
-    language="Greek",
-    char_to_order_map=WINDOWS_1253_GREEK_CHAR_TO_ORDER,
-    language_model=GREEK_LANG_MODEL,
-    typical_positive_ratio=0.982851,
-    keep_ascii_letters=False,
-    alphabet="ΆΈΉΊΌΎΏΑΒΓΔΕΖΗΘΙΚΛΜΝΞΟΠΡΣΤΥΦΧΨΩάέήίαβγδεζηθικλμνξοπρςστυφχψωόύώ",
-)
-
-ISO_8859_7_GREEK_CHAR_TO_ORDER = {
-    0: 255,  # '\x00'
-    1: 255,  # '\x01'
-    2: 255,  # '\x02'
-    3: 255,  # '\x03'
-    4: 255,  # '\x04'
-    5: 255,  # '\x05'
-    6: 255,  # '\x06'
-    7: 255,  # '\x07'
-    8: 255,  # '\x08'
-    9: 255,  # '\t'
-    10: 254,  # '\n'
-    11: 255,  # '\x0b'
-    12: 255,  # '\x0c'
-    13: 254,  # '\r'
-    14: 255,  # '\x0e'
-    15: 255,  # '\x0f'
-    16: 255,  # '\x10'
-    17: 255,  # '\x11'
-    18: 255,  # '\x12'
-    19: 255,  # '\x13'
-    20: 255,  # '\x14'
-    21: 255,  # '\x15'
-    22: 255,  # '\x16'
-    23: 255,  # '\x17'
-    24: 255,  # '\x18'
-    25: 255,  # '\x19'
-    26: 255,  # '\x1a'
-    27: 255,  # '\x1b'
-    28: 255,  # '\x1c'
-    29: 255,  # '\x1d'
-    30: 255,  # '\x1e'
-    31: 255,  # '\x1f'
-    32: 253,  # ' '
-    33: 253,  # '!'
-    34: 253,  # '"'
-    35: 253,  # '#'
-    36: 253,  # '$'
-    37: 253,  # '%'
-    38: 253,  # '&'
-    39: 253,  # "'"
-    40: 253,  # '('
-    41: 253,  # ')'
-    42: 253,  # '*'
-    43: 253,  # '+'
-    44: 253,  # ','
-    45: 253,  # '-'
-    46: 253,  # '.'
-    47: 253,  # '/'
-    48: 252,  # '0'
-    49: 252,  # '1'
-    50: 252,  # '2'
-    51: 252,  # '3'
-    52: 252,  # '4'
-    53: 252,  # '5'
-    54: 252,  # '6'
-    55: 252,  # '7'
-    56: 252,  # '8'
-    57: 252,  # '9'
-    58: 253,  # ':'
-    59: 253,  # ';'
-    60: 253,  # '<'
-    61: 253,  # '='
-    62: 253,  # '>'
-    63: 253,  # '?'
-    64: 253,  # '@'
-    65: 82,  # 'A'
-    66: 100,  # 'B'
-    67: 104,  # 'C'
-    68: 94,  # 'D'
-    69: 98,  # 'E'
-    70: 101,  # 'F'
-    71: 116,  # 'G'
-    72: 102,  # 'H'
-    73: 111,  # 'I'
-    74: 187,  # 'J'
-    75: 117,  # 'K'
-    76: 92,  # 'L'
-    77: 88,  # 'M'
-    78: 113,  # 'N'
-    79: 85,  # 'O'
-    80: 79,  # 'P'
-    81: 118,  # 'Q'
-    82: 105,  # 'R'
-    83: 83,  # 'S'
-    84: 67,  # 'T'
-    85: 114,  # 'U'
-    86: 119,  # 'V'
-    87: 95,  # 'W'
-    88: 99,  # 'X'
-    89: 109,  # 'Y'
-    90: 188,  # 'Z'
-    91: 253,  # '['
-    92: 253,  # '\\'
-    93: 253,  # ']'
-    94: 253,  # '^'
-    95: 253,  # '_'
-    96: 253,  # '`'
-    97: 72,  # 'a'
-    98: 70,  # 'b'
-    99: 80,  # 'c'
-    100: 81,  # 'd'
-    101: 60,  # 'e'
-    102: 96,  # 'f'
-    103: 93,  # 'g'
-    104: 89,  # 'h'
-    105: 68,  # 'i'
-    106: 120,  # 'j'
-    107: 97,  # 'k'
-    108: 77,  # 'l'
-    109: 86,  # 'm'
-    110: 69,  # 'n'
-    111: 55,  # 'o'
-    112: 78,  # 'p'
-    113: 115,  # 'q'
-    114: 65,  # 'r'
-    115: 66,  # 's'
-    116: 58,  # 't'
-    117: 76,  # 'u'
-    118: 106,  # 'v'
-    119: 103,  # 'w'
-    120: 87,  # 'x'
-    121: 107,  # 'y'
-    122: 112,  # 'z'
-    123: 253,  # '{'
-    124: 253,  # '|'
-    125: 253,  # '}'
-    126: 253,  # '~'
-    127: 253,  # '\x7f'
-    128: 255,  # '\x80'
-    129: 255,  # '\x81'
-    130: 255,  # '\x82'
-    131: 255,  # '\x83'
-    132: 255,  # '\x84'
-    133: 255,  # '\x85'
-    134: 255,  # '\x86'
-    135: 255,  # '\x87'
-    136: 255,  # '\x88'
-    137: 255,  # '\x89'
-    138: 255,  # '\x8a'
-    139: 255,  # '\x8b'
-    140: 255,  # '\x8c'
-    141: 255,  # '\x8d'
-    142: 255,  # '\x8e'
-    143: 255,  # '\x8f'
-    144: 255,  # '\x90'
-    145: 255,  # '\x91'
-    146: 255,  # '\x92'
-    147: 255,  # '\x93'
-    148: 255,  # '\x94'
-    149: 255,  # '\x95'
-    150: 255,  # '\x96'
-    151: 255,  # '\x97'
-    152: 255,  # '\x98'
-    153: 255,  # '\x99'
-    154: 255,  # '\x9a'
-    155: 255,  # '\x9b'
-    156: 255,  # '\x9c'
-    157: 255,  # '\x9d'
-    158: 255,  # '\x9e'
-    159: 255,  # '\x9f'
-    160: 253,  # '\xa0'
-    161: 233,  # '‘'
-    162: 90,  # '’'
-    163: 253,  # '£'
-    164: 253,  # '€'
-    165: 253,  # '₯'
-    166: 253,  # '¦'
-    167: 253,  # '§'
-    168: 253,  # '¨'
-    169: 253,  # '©'
-    170: 253,  # 'ͺ'
-    171: 253,  # '«'
-    172: 253,  # '¬'
-    173: 74,  # '\xad'
-    174: 253,  # None
-    175: 253,  # '―'
-    176: 253,  # '°'
-    177: 253,  # '±'
-    178: 253,  # '²'
-    179: 253,  # '³'
-    180: 247,  # '΄'
-    181: 248,  # '΅'
-    182: 61,  # 'Ά'
-    183: 36,  # '·'
-    184: 46,  # 'Έ'
-    185: 71,  # 'Ή'
-    186: 73,  # 'Ί'
-    187: 253,  # '»'
-    188: 54,  # 'Ό'
-    189: 253,  # '½'
-    190: 108,  # 'Ύ'
-    191: 123,  # 'Ώ'
-    192: 110,  # 'ΐ'
-    193: 31,  # 'Α'
-    194: 51,  # 'Β'
-    195: 43,  # 'Γ'
-    196: 41,  # 'Δ'
-    197: 34,  # 'Ε'
-    198: 91,  # 'Ζ'
-    199: 40,  # 'Η'
-    200: 52,  # 'Θ'
-    201: 47,  # 'Ι'
-    202: 44,  # 'Κ'
-    203: 53,  # 'Λ'
-    204: 38,  # 'Μ'
-    205: 49,  # 'Ν'
-    206: 59,  # 'Ξ'
-    207: 39,  # 'Ο'
-    208: 35,  # 'Π'
-    209: 48,  # 'Ρ'
-    210: 250,  # None
-    211: 37,  # 'Σ'
-    212: 33,  # 'Τ'
-    213: 45,  # 'Υ'
-    214: 56,  # 'Φ'
-    215: 50,  # 'Χ'
-    216: 84,  # 'Ψ'
-    217: 57,  # 'Ω'
-    218: 120,  # 'Ϊ'
-    219: 121,  # 'Ϋ'
-    220: 17,  # 'ά'
-    221: 18,  # 'έ'
-    222: 22,  # 'ή'
-    223: 15,  # 'ί'
-    224: 124,  # 'ΰ'
-    225: 1,  # 'α'
-    226: 29,  # 'β'
-    227: 20,  # 'γ'
-    228: 21,  # 'δ'
-    229: 3,  # 'ε'
-    230: 32,  # 'ζ'
-    231: 13,  # 'η'
-    232: 25,  # 'θ'
-    233: 5,  # 'ι'
-    234: 11,  # 'κ'
-    235: 16,  # 'λ'
-    236: 10,  # 'μ'
-    237: 6,  # 'ν'
-    238: 30,  # 'ξ'
-    239: 4,  # 'ο'
-    240: 9,  # 'π'
-    241: 8,  # 'ρ'
-    242: 14,  # 'ς'
-    243: 7,  # 'σ'
-    244: 2,  # 'τ'
-    245: 12,  # 'υ'
-    246: 28,  # 'φ'
-    247: 23,  # 'χ'
-    248: 42,  # 'ψ'
-    249: 24,  # 'ω'
-    250: 64,  # 'ϊ'
-    251: 75,  # 'ϋ'
-    252: 19,  # 'ό'
-    253: 26,  # 'ύ'
-    254: 27,  # 'ώ'
-    255: 253,  # None
-}
-
-ISO_8859_7_GREEK_MODEL = SingleByteCharSetModel(
-    charset_name="ISO-8859-7",
-    language="Greek",
-    char_to_order_map=ISO_8859_7_GREEK_CHAR_TO_ORDER,
-    language_model=GREEK_LANG_MODEL,
-    typical_positive_ratio=0.982851,
-    keep_ascii_letters=False,
-    alphabet="ΆΈΉΊΌΎΏΑΒΓΔΕΖΗΘΙΚΛΜΝΞΟΠΡΣΤΥΦΧΨΩάέήίαβγδεζηθικλμνξοπρςστυφχψωόύώ",
-)
diff --git a/spaces/TandCAcceptMe/face-swap-docker/mynewshinyroop/Lib/site-packages/setuptools/_reqs.py b/spaces/TandCAcceptMe/face-swap-docker/mynewshinyroop/Lib/site-packages/setuptools/_reqs.py
deleted file mode 100644
index 5d5b927fd8728592fa8eb11891b1a6b1379c4199..0000000000000000000000000000000000000000
--- a/spaces/TandCAcceptMe/face-swap-docker/mynewshinyroop/Lib/site-packages/setuptools/_reqs.py
+++ /dev/null
@@ -1,33 +0,0 @@
-from typing import Callable, Iterable, Iterator, TypeVar, Union, overload
-
-import setuptools.extern.jaraco.text as text
-from setuptools.extern.packaging.requirements import Requirement
-
-_T = TypeVar("_T")
-_StrOrIter = Union[str, Iterable[str]]
-
-
-def parse_strings(strs: _StrOrIter) -> Iterator[str]:
-    """
-    Yield requirement strings for each specification in `strs`.
-
-    `strs` must be a string, or a (possibly-nested) iterable thereof.
-    """
-    return text.join_continuation(map(text.drop_comment, text.yield_lines(strs)))
-
-
-@overload
-def parse(strs: _StrOrIter) -> Iterator[Requirement]:
-    ...
-
-
-@overload
-def parse(strs: _StrOrIter, parser: Callable[[str], _T]) -> Iterator[_T]:
-    ...
-
-
-def parse(strs, parser=Requirement):
-    """
-    Replacement for ``pkg_resources.parse_requirements`` that uses ``packaging``.
-    """
-    return map(parser, parse_strings(strs))
diff --git a/spaces/Thafx/Demucs_v4_2s_HT/app.py b/spaces/Thafx/Demucs_v4_2s_HT/app.py
deleted file mode 100644
index 5a59b63e1d7a48b08faf8b4807c52cc8aba33ec0..0000000000000000000000000000000000000000
--- a/spaces/Thafx/Demucs_v4_2s_HT/app.py
+++ /dev/null
@@ -1,25 +0,0 @@
-import os
-import gradio as gr
-from scipy.io.wavfile import write
-
-
-def inference(audio):
-  os.makedirs("out", exist_ok=True)
-  write('test.wav', audio[0], audio[1])
-  os.system("python3 -m demucs.separate -n htdemucs --two-stems=vocals -d cpu test.wav -o out")
-  return "./out/htdemucs/test/vocals.wav","./out/htdemucs/test/no_vocals.wav"
-    
-title = "Demucs Music Source Separation (v4)"
-description = "This is the latest 'bleeding edge version' which enables the new v4 Hybrid Transformer model. <br> for this space, 2 stem sepration (Karaoke Mode) is enabled and CPU mode which has been optimised for best quality & processing time. <p>| Gradio demo for Demucs(v4): Music Source Separation in the Waveform Domain. To use it, simply upload your audio, or click one of the examples to load them. Read more at the links below.</p>"
-article = "<p style='text-align: center'><a href='https://arxiv.org/abs/1911.13254' target='_blank'>Music Source Separation in the Waveform Domain</a> | <a href='https://github.com/facebookresearch/demucs' target='_blank'>Github Repo</a> | <a href='https://www.thafx.com' target='_blank'>//THAFX</a></p>"
-
-examples=[['test.mp3']]
-gr.Interface(
-    inference, 
-    gr.Audio(type="numpy", label="Input"),
-    [gr.Audio(type="filepath", label="Vocals"),gr.Audio(type="filepath", label="No Vocals / Instrumental")],
-    title=title,
-    description=description,
-    article=article,
-    examples=examples
-    ).launch(enable_queue=True)
\ No newline at end of file
diff --git a/spaces/Wanlau/sovits-4.0_datealive/preprocess_flist_config.py b/spaces/Wanlau/sovits-4.0_datealive/preprocess_flist_config.py
deleted file mode 100644
index ff5c9696e03421ad66ecfdd045698deac824557d..0000000000000000000000000000000000000000
--- a/spaces/Wanlau/sovits-4.0_datealive/preprocess_flist_config.py
+++ /dev/null
@@ -1,83 +0,0 @@
-import os
-import argparse
-import re
-
-from tqdm import tqdm
-from random import shuffle
-import json
-import wave
-
-config_template = json.load(open("configs/config.json"))
-
-pattern = re.compile(r'^[\.a-zA-Z0-9_\/]+$')
-
-def get_wav_duration(file_path):
-    with wave.open(file_path, 'rb') as wav_file:
-        # 获取音频帧数
-        n_frames = wav_file.getnframes()
-        # 获取采样率
-        framerate = wav_file.getframerate()
-        # 计算时长（秒）
-        duration = n_frames / float(framerate)
-    return duration
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--train_list", type=str, default="./filelists/train.txt", help="path to train list")
-    parser.add_argument("--val_list", type=str, default="./filelists/val.txt", help="path to val list")
-    parser.add_argument("--test_list", type=str, default="./filelists/test.txt", help="path to test list")
-    parser.add_argument("--source_dir", type=str, default="./dataset/44k", help="path to source dir")
-    args = parser.parse_args()
-    
-    train = []
-    val = []
-    test = []
-    idx = 0
-    spk_dict = {}
-    spk_id = 0
-    for speaker in tqdm(os.listdir(args.source_dir)):
-        spk_dict[speaker] = spk_id
-        spk_id += 1
-        wavs = ["/".join([args.source_dir, speaker, i]) for i in os.listdir(os.path.join(args.source_dir, speaker))]
-        new_wavs = []
-        for file in wavs:
-            if not file.endswith("wav"):
-                continue
-            if not pattern.match(file):
-                print(f"warning：文件名{file}中包含非字母数字下划线，可能会导致错误。（也可能不会）")
-            if get_wav_duration(file) < 0.3:
-                print("skip too short audio:", file)
-                continue
-            new_wavs.append(file)
-        wavs = new_wavs
-        shuffle(wavs)
-        train += wavs[2:-2]
-        val += wavs[:2]
-        test += wavs[-2:]
-
-    shuffle(train)
-    shuffle(val)
-    shuffle(test)
-            
-    print("Writing", args.train_list)
-    with open(args.train_list, "w") as f:
-        for fname in tqdm(train):
-            wavpath = fname
-            f.write(wavpath + "\n")
-        
-    print("Writing", args.val_list)
-    with open(args.val_list, "w") as f:
-        for fname in tqdm(val):
-            wavpath = fname
-            f.write(wavpath + "\n")
-            
-    print("Writing", args.test_list)
-    with open(args.test_list, "w") as f:
-        for fname in tqdm(test):
-            wavpath = fname
-            f.write(wavpath + "\n")
-
-    config_template["spk"] = spk_dict
-    print("Writing configs/config.json")
-    with open("configs/config.json", "w") as f:
-        json.dump(config_template, f, indent=2)
diff --git a/spaces/WinterGYC/Baichuan-13B-Chat-Int8-Docker/app.py b/spaces/WinterGYC/Baichuan-13B-Chat-Int8-Docker/app.py
deleted file mode 100644
index 670219fbe84b00aa4fe25a7302e0406cab66928c..0000000000000000000000000000000000000000
--- a/spaces/WinterGYC/Baichuan-13B-Chat-Int8-Docker/app.py
+++ /dev/null
@@ -1,72 +0,0 @@
-import json
-import torch
-import streamlit as st
-from transformers import AutoModelForCausalLM, AutoTokenizer
-from transformers.generation.utils import GenerationConfig
-
-
-st.set_page_config(page_title="Baichuan-13B-Chat")
-st.title("Baichuan-13B-Chat")
-
-@st.cache_resource
-def init_model():
-    model = AutoModelForCausalLM.from_pretrained(
-        "baichuan-inc/Baichuan-13B-Chat",
-        torch_dtype=torch.float16,
-        device_map="auto",
-        trust_remote_code=True
-    )
-    model.generation_config = GenerationConfig.from_pretrained(
-        "baichuan-inc/Baichuan-13B-Chat"
-    )
-    tokenizer = AutoTokenizer.from_pretrained(
-        "baichuan-inc/Baichuan-13B-Chat",
-        use_fast=False,
-        trust_remote_code=True
-    )
-    model = model.quantize(8).cuda()
-    return model, tokenizer
-
-
-def clear_chat_history():
-    del st.session_state.messages
-
-
-def init_chat_history():
-    with st.chat_message("assistant", avatar='🤖'):
-        st.markdown("Greetings! I am the BaiChuan large language model, delighted to assist you.🥰")
-
-    if "messages" in st.session_state:
-        for message in st.session_state.messages:
-            avatar = '🧑‍💻' if message["role"] == "user" else '🤖'
-            with st.chat_message(message["role"], avatar=avatar):
-                st.markdown(message["content"])
-    else:
-        st.session_state.messages = []
-
-    return st.session_state.messages
-
-
-def main():
-    model, tokenizer = init_model()
-    messages = init_chat_history()
-
-    if prompt := st.chat_input("Shift + Enter for a new line, Enter to send"):
-        with st.chat_message("user", avatar='🧑‍💻'):
-            st.markdown(prompt)
-        messages.append({"role": "user", "content": prompt})
-        print(f"[user] {prompt}", flush=True)
-        with st.chat_message("assistant", avatar='🤖'):
-            placeholder = st.empty()
-            for response in model.chat(tokenizer, messages, stream=True):
-                placeholder.markdown(response)
-                if torch.backends.mps.is_available():
-                    torch.mps.empty_cache()
-        messages.append({"role": "assistant", "content": response})
-        print(json.dumps(messages, ensure_ascii=False), flush=True)
-
-        st.button("Reset Chat", on_click=clear_chat_history)
-
-
-if __name__ == "__main__":
-    main()
diff --git a/spaces/XzJosh/ShanBao-Bert-VITS2/server.py b/spaces/XzJosh/ShanBao-Bert-VITS2/server.py
deleted file mode 100644
index c736ca4f95fec853950eef6654ef79856beffc0a..0000000000000000000000000000000000000000
--- a/spaces/XzJosh/ShanBao-Bert-VITS2/server.py
+++ /dev/null
@@ -1,123 +0,0 @@
-from flask import Flask, request, Response
-from io import BytesIO
-import torch
-from av import open as avopen
-
-import commons
-import utils
-from models import SynthesizerTrn
-from text.symbols import symbols
-from text import cleaned_text_to_sequence, get_bert
-from text.cleaner import clean_text
-from scipy.io import wavfile
-
-# Flask Init
-app = Flask(__name__)
-app.config['JSON_AS_ASCII'] = False
-def get_text(text, language_str, hps):
-    norm_text, phone, tone, word2ph = clean_text(text, language_str)
-    print([f"{p}{t}" for p, t in zip(phone, tone)])
-    phone, tone, language = cleaned_text_to_sequence(phone, tone, language_str)
-
-    if hps.data.add_blank:
-        phone = commons.intersperse(phone, 0)
-        tone = commons.intersperse(tone, 0)
-        language = commons.intersperse(language, 0)
-        for i in range(len(word2ph)):
-            word2ph[i] = word2ph[i] * 2
-        word2ph[0] += 1
-    bert = get_bert(norm_text, word2ph, language_str)
-
-    assert bert.shape[-1] == len(phone)
-
-    phone = torch.LongTensor(phone)
-    tone = torch.LongTensor(tone)
-    language = torch.LongTensor(language)
-
-    return bert, phone, tone, language
-
-def infer(text, sdp_ratio, noise_scale, noise_scale_w,length_scale,sid):
-    bert, phones, tones, lang_ids = get_text(text,"ZH", hps,)
-    with torch.no_grad():
-        x_tst=phones.to(dev).unsqueeze(0)
-        tones=tones.to(dev).unsqueeze(0)
-        lang_ids=lang_ids.to(dev).unsqueeze(0)
-        bert = bert.to(dev).unsqueeze(0)
-        x_tst_lengths = torch.LongTensor([phones.size(0)]).to(dev)
-        speakers = torch.LongTensor([hps.data.spk2id[sid]]).to(dev)
-        audio = net_g.infer(x_tst, x_tst_lengths, speakers, tones, lang_ids,bert, sdp_ratio=sdp_ratio
-                           , noise_scale=noise_scale, noise_scale_w=noise_scale_w, length_scale=length_scale)[0][0,0].data.cpu().float().numpy()
-        return audio
-
-def replace_punctuation(text, i=2):
-    punctuation = "，。？！"
-    for char in punctuation:
-        text = text.replace(char, char * i)
-    return text
-
-def wav2(i, o, format):
-    inp = avopen(i, 'rb')
-    out = avopen(o, 'wb', format=format)
-    if format == "ogg": format = "libvorbis"
-
-    ostream = out.add_stream(format)
-
-    for frame in inp.decode(audio=0):
-        for p in ostream.encode(frame): out.mux(p)
-
-    for p in ostream.encode(None): out.mux(p)
-
-    out.close()
-    inp.close()
-
-# Load Generator
-hps = utils.get_hparams_from_file("./configs/config.json")
-
-dev='cuda'
-net_g = SynthesizerTrn(
-    len(symbols),
-    hps.data.filter_length // 2 + 1,
-    hps.train.segment_size // hps.data.hop_length,
-    n_speakers=hps.data.n_speakers,
-    **hps.model).to(dev)
-_ = net_g.eval()
-
-_ = utils.load_checkpoint("logs/G_649000.pth", net_g, None,skip_optimizer=True)
-
-@app.route("/",methods=['GET','POST'])
-def main():
-    if request.method == 'GET':
-        try:
-            speaker = request.args.get('speaker')
-            text = request.args.get('text').replace("/n","")
-            sdp_ratio = float(request.args.get("sdp_ratio", 0.2))
-            noise = float(request.args.get("noise", 0.5))
-            noisew = float(request.args.get("noisew", 0.6))
-            length = float(request.args.get("length", 1.2))
-            if length >= 2:
-                return "Too big length"
-            if len(text) >=200:
-                return "Too long text"
-            fmt = request.args.get("format", "wav")
-            if None in (speaker, text):
-                return "Missing Parameter"
-            if fmt not in ("mp3", "wav", "ogg"):
-                return "Invalid Format"
-        except:
-            return "Invalid Parameter"
-
-        with torch.no_grad():
-            audio = infer(text, sdp_ratio=sdp_ratio, noise_scale=noise, noise_scale_w=noisew, length_scale=length, sid=speaker)
-
-        with BytesIO() as wav:
-            wavfile.write(wav, hps.data.sampling_rate, audio)
-            torch.cuda.empty_cache()
-            if fmt == "wav":
-                return Response(wav.getvalue(), mimetype="audio/wav")
-            wav.seek(0, 0)
-            with BytesIO() as ofp:
-                wav2(wav, ofp, fmt)
-                return Response(
-                    ofp.getvalue(),
-                    mimetype="audio/mpeg" if fmt == "mp3" else "audio/ogg"
-                )
diff --git a/spaces/YONG627/456123/yolov5-code-main/utils/general.py b/spaces/YONG627/456123/yolov5-code-main/utils/general.py
deleted file mode 100644
index 74620460070e409077d0bfb5b98e9235000c129c..0000000000000000000000000000000000000000
--- a/spaces/YONG627/456123/yolov5-code-main/utils/general.py
+++ /dev/null
@@ -1,1140 +0,0 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
-"""
-General utils
-"""
-
-import contextlib
-import glob
-import inspect
-import logging
-import logging.config
-import math
-import os
-import platform
-import random
-import re
-import signal
-import subprocess
-import sys
-import time
-import urllib
-from copy import deepcopy
-from datetime import datetime
-from itertools import repeat
-from multiprocessing.pool import ThreadPool
-from pathlib import Path
-from subprocess import check_output
-from tarfile import is_tarfile
-from typing import Optional
-from zipfile import ZipFile, is_zipfile
-
-import cv2
-import numpy as np
-import pandas as pd
-import pkg_resources as pkg
-import torch
-import torchvision
-import yaml
-
-from utils import TryExcept, emojis
-from utils.downloads import curl_download, gsutil_getsize
-from utils.metrics import box_iou, fitness
-
-FILE = Path(__file__).resolve()
-ROOT = FILE.parents[1]  # YOLOv5 root directory
-RANK = int(os.getenv('RANK', -1))
-
-# Settings
-NUM_THREADS = min(8, max(1, os.cpu_count() - 1))  # number of YOLOv5 multiprocessing threads
-DATASETS_DIR = Path(os.getenv('YOLOv5_DATASETS_DIR', ROOT.parent / 'datasets'))  # global datasets directory
-AUTOINSTALL = str(os.getenv('YOLOv5_AUTOINSTALL', True)).lower() == 'true'  # global auto-install mode
-VERBOSE = str(os.getenv('YOLOv5_VERBOSE', True)).lower() == 'true'  # global verbose mode
-TQDM_BAR_FORMAT = '{l_bar}{bar:10}{r_bar}'  # tqdm bar format
-FONT = 'Arial.ttf'  # https://ultralytics.com/assets/Arial.ttf
-
-torch.set_printoptions(linewidth=320, precision=5, profile='long')
-np.set_printoptions(linewidth=320, formatter={'float_kind': '{:11.5g}'.format})  # format short g, %precision=5
-pd.options.display.max_columns = 10
-cv2.setNumThreads(0)  # prevent OpenCV from multithreading (incompatible with PyTorch DataLoader)
-os.environ['NUMEXPR_MAX_THREADS'] = str(NUM_THREADS)  # NumExpr max threads
-os.environ['OMP_NUM_THREADS'] = '1' if platform.system() == 'darwin' else str(NUM_THREADS)  # OpenMP (PyTorch and SciPy)
-
-
-def is_ascii(s=''):
-    # Is string composed of all ASCII (no UTF) characters? (note str().isascii() introduced in python 3.7)
-    s = str(s)  # convert list, tuple, None, etc. to str
-    return len(s.encode().decode('ascii', 'ignore')) == len(s)
-
-
-def is_chinese(s='人工智能'):
-    # Is string composed of any Chinese characters?
-    return bool(re.search('[\u4e00-\u9fff]', str(s)))
-
-
-def is_colab():
-    # Is environment a Google Colab instance?
-    return 'google.colab' in sys.modules
-
-
-def is_jupyter():
-    """
-    Check if the current script is running inside a Jupyter Notebook.
-    Verified on Colab, Jupyterlab, Kaggle, Paperspace.
-
-    Returns:
-        bool: True if running inside a Jupyter Notebook, False otherwise.
-    """
-    with contextlib.suppress(Exception):
-        from IPython import get_ipython
-        return get_ipython() is not None
-    return False
-
-
-def is_kaggle():
-    # Is environment a Kaggle Notebook?
-    return os.environ.get('PWD') == '/kaggle/working' and os.environ.get('KAGGLE_URL_BASE') == 'https://www.kaggle.com'
-
-
-def is_docker() -> bool:
-    """Check if the process runs inside a docker container."""
-    if Path('/.dockerenv').exists():
-        return True
-    try:  # check if docker is in control groups
-        with open('/proc/self/cgroup') as file:
-            return any('docker' in line for line in file)
-    except OSError:
-        return False
-
-
-def is_writeable(dir, test=False):
-    # Return True if directory has write permissions, test opening a file with write permissions if test=True
-    if not test:
-        return os.access(dir, os.W_OK)  # possible issues on Windows
-    file = Path(dir) / 'tmp.txt'
-    try:
-        with open(file, 'w'):  # open file with write permissions
-            pass
-        file.unlink()  # remove file
-        return True
-    except OSError:
-        return False
-
-
-LOGGING_NAME = 'yolov5'
-
-
-def set_logging(name=LOGGING_NAME, verbose=True):
-    # sets up logging for the given name
-    rank = int(os.getenv('RANK', -1))  # rank in world for Multi-GPU trainings
-    level = logging.INFO if verbose and rank in {-1, 0} else logging.ERROR
-    logging.config.dictConfig({
-        'version': 1,
-        'disable_existing_loggers': False,
-        'formatters': {
-            name: {
-                'format': '%(message)s'}},
-        'handlers': {
-            name: {
-                'class': 'logging.StreamHandler',
-                'formatter': name,
-                'level': level,}},
-        'loggers': {
-            name: {
-                'level': level,
-                'handlers': [name],
-                'propagate': False,}}})
-
-
-set_logging(LOGGING_NAME)  # run before defining LOGGER
-LOGGER = logging.getLogger(LOGGING_NAME)  # define globally (used in train.py, val.py, detect.py, etc.)
-if platform.system() == 'Windows':
-    for fn in LOGGER.info, LOGGER.warning:
-        setattr(LOGGER, fn.__name__, lambda x: fn(emojis(x)))  # emoji safe logging
-
-
-def user_config_dir(dir='Ultralytics', env_var='YOLOV5_CONFIG_DIR'):
-    # Return path of user configuration directory. Prefer environment variable if exists. Make dir if required.
-    env = os.getenv(env_var)
-    if env:
-        path = Path(env)  # use environment variable
-    else:
-        cfg = {'Windows': 'AppData/Roaming', 'Linux': '.config', 'Darwin': 'Library/Application Support'}  # 3 OS dirs
-        path = Path.home() / cfg.get(platform.system(), '')  # OS-specific config dir
-        path = (path if is_writeable(path) else Path('/tmp')) / dir  # GCP and AWS lambda fix, only /tmp is writeable
-    path.mkdir(exist_ok=True)  # make if required
-    return path
-
-
-CONFIG_DIR = user_config_dir()  # Ultralytics settings dir
-
-
-class Profile(contextlib.ContextDecorator):
-    # YOLOv5 Profile class. Usage: @Profile() decorator or 'with Profile():' context manager
-    def __init__(self, t=0.0):
-        self.t = t
-        self.cuda = torch.cuda.is_available()
-
-    def __enter__(self):
-        self.start = self.time()
-        return self
-
-    def __exit__(self, type, value, traceback):
-        self.dt = self.time() - self.start  # delta-time
-        self.t += self.dt  # accumulate dt
-
-    def time(self):
-        if self.cuda:
-            torch.cuda.synchronize()
-        return time.time()
-
-
-class Timeout(contextlib.ContextDecorator):
-    # YOLOv5 Timeout class. Usage: @Timeout(seconds) decorator or 'with Timeout(seconds):' context manager
-    def __init__(self, seconds, *, timeout_msg='', suppress_timeout_errors=True):
-        self.seconds = int(seconds)
-        self.timeout_message = timeout_msg
-        self.suppress = bool(suppress_timeout_errors)
-
-    def _timeout_handler(self, signum, frame):
-        raise TimeoutError(self.timeout_message)
-
-    def __enter__(self):
-        if platform.system() != 'Windows':  # not supported on Windows
-            signal.signal(signal.SIGALRM, self._timeout_handler)  # Set handler for SIGALRM
-            signal.alarm(self.seconds)  # start countdown for SIGALRM to be raised
-
-    def __exit__(self, exc_type, exc_val, exc_tb):
-        if platform.system() != 'Windows':
-            signal.alarm(0)  # Cancel SIGALRM if it's scheduled
-            if self.suppress and exc_type is TimeoutError:  # Suppress TimeoutError
-                return True
-
-
-class WorkingDirectory(contextlib.ContextDecorator):
-    # Usage: @WorkingDirectory(dir) decorator or 'with WorkingDirectory(dir):' context manager
-    def __init__(self, new_dir):
-        self.dir = new_dir  # new dir
-        self.cwd = Path.cwd().resolve()  # current dir
-
-    def __enter__(self):
-        os.chdir(self.dir)
-
-    def __exit__(self, exc_type, exc_val, exc_tb):
-        os.chdir(self.cwd)
-
-
-def methods(instance):
-    # Get class/instance methods
-    return [f for f in dir(instance) if callable(getattr(instance, f)) and not f.startswith('__')]
-
-
-def print_args(args: Optional[dict] = None, show_file=True, show_func=False):
-    # Print function arguments (optional args dict)
-    x = inspect.currentframe().f_back  # previous frame
-    file, _, func, _, _ = inspect.getframeinfo(x)
-    if args is None:  # get args automatically
-        args, _, _, frm = inspect.getargvalues(x)
-        args = {k: v for k, v in frm.items() if k in args}
-    try:
-        file = Path(file).resolve().relative_to(ROOT).with_suffix('')
-    except ValueError:
-        file = Path(file).stem
-    s = (f'{file}: ' if show_file else '') + (f'{func}: ' if show_func else '')
-    LOGGER.info(colorstr(s) + ', '.join(f'{k}={v}' for k, v in args.items()))
-
-
-def init_seeds(seed=0, deterministic=False):
-    # Initialize random number generator (RNG) seeds https://pytorch.org/docs/stable/notes/randomness.html
-    random.seed(seed)
-    np.random.seed(seed)
-    torch.manual_seed(seed)
-    torch.cuda.manual_seed(seed)
-    torch.cuda.manual_seed_all(seed)  # for Multi-GPU, exception safe
-    # torch.backends.cudnn.benchmark = True  # AutoBatch problem https://github.com/ultralytics/yolov5/issues/9287
-    if deterministic and check_version(torch.__version__, '1.12.0'):  # https://github.com/ultralytics/yolov5/pull/8213
-        torch.use_deterministic_algorithms(True)
-        torch.backends.cudnn.deterministic = True
-        os.environ['CUBLAS_WORKSPACE_CONFIG'] = ':4096:8'
-        os.environ['PYTHONHASHSEED'] = str(seed)
-
-
-def intersect_dicts(da, db, exclude=()):
-    # Dictionary intersection of matching keys and shapes, omitting 'exclude' keys, using da values
-    return {k: v for k, v in da.items() if k in db and all(x not in k for x in exclude) and v.shape == db[k].shape}
-
-
-def get_default_args(func):
-    # Get func() default arguments
-    signature = inspect.signature(func)
-    return {k: v.default for k, v in signature.parameters.items() if v.default is not inspect.Parameter.empty}
-
-
-def get_latest_run(search_dir='.'):
-    # Return path to most recent 'last.pt' in /runs (i.e. to --resume from)
-    last_list = glob.glob(f'{search_dir}/**/last*.pt', recursive=True)
-    return max(last_list, key=os.path.getctime) if last_list else ''
-
-
-def file_age(path=__file__):
-    # Return days since last file update
-    dt = (datetime.now() - datetime.fromtimestamp(Path(path).stat().st_mtime))  # delta
-    return dt.days  # + dt.seconds / 86400  # fractional days
-
-
-def file_date(path=__file__):
-    # Return human-readable file modification date, i.e. '2021-3-26'
-    t = datetime.fromtimestamp(Path(path).stat().st_mtime)
-    return f'{t.year}-{t.month}-{t.day}'
-
-
-def file_size(path):
-    # Return file/dir size (MB)
-    mb = 1 << 20  # bytes to MiB (1024 ** 2)
-    path = Path(path)
-    if path.is_file():
-        return path.stat().st_size / mb
-    elif path.is_dir():
-        return sum(f.stat().st_size for f in path.glob('**/*') if f.is_file()) / mb
-    else:
-        return 0.0
-
-
-def check_online():
-    # Check internet connectivity
-    import socket
-
-    def run_once():
-        # Check once
-        try:
-            socket.create_connection(('1.1.1.1', 443), 5)  # check host accessibility
-            return True
-        except OSError:
-            return False
-
-    return run_once() or run_once()  # check twice to increase robustness to intermittent connectivity issues
-
-
-def git_describe(path=ROOT):  # path must be a directory
-    # Return human-readable git description, i.e. v5.0-5-g3e25f1e https://git-scm.com/docs/git-describe
-    try:
-        assert (Path(path) / '.git').is_dir()
-        return check_output(f'git -C {path} describe --tags --long --always', shell=True).decode()[:-1]
-    except Exception:
-        return ''
-
-
-@TryExcept()
-@WorkingDirectory(ROOT)
-def check_git_status(repo='ultralytics/yolov5', branch='master'):
-    # YOLOv5 status check, recommend 'git pull' if code is out of date
-    url = f'https://github.com/{repo}'
-    msg = f', for updates see {url}'
-    s = colorstr('github: ')  # string
-    assert Path('.git').exists(), s + 'skipping check (not a git repository)' + msg
-    assert check_online(), s + 'skipping check (offline)' + msg
-
-    splits = re.split(pattern=r'\s', string=check_output('git remote -v', shell=True).decode())
-    matches = [repo in s for s in splits]
-    if any(matches):
-        remote = splits[matches.index(True) - 1]
-    else:
-        remote = 'ultralytics'
-        check_output(f'git remote add {remote} {url}', shell=True)
-    check_output(f'git fetch {remote}', shell=True, timeout=5)  # git fetch
-    local_branch = check_output('git rev-parse --abbrev-ref HEAD', shell=True).decode().strip()  # checked out
-    n = int(check_output(f'git rev-list {local_branch}..{remote}/{branch} --count', shell=True))  # commits behind
-    if n > 0:
-        pull = 'git pull' if remote == 'origin' else f'git pull {remote} {branch}'
-        s += f"⚠️ YOLOv5 is out of date by {n} commit{'s' * (n > 1)}. Use '{pull}' or 'git clone {url}' to update."
-    else:
-        s += f'up to date with {url} ✅'
-    LOGGER.info(s)
-
-
-@WorkingDirectory(ROOT)
-def check_git_info(path='.'):
-    # YOLOv5 git info check, return {remote, branch, commit}
-    check_requirements('gitpython')
-    import git
-    try:
-        repo = git.Repo(path)
-        remote = repo.remotes.origin.url.replace('.git', '')  # i.e. 'https://github.com/ultralytics/yolov5'
-        commit = repo.head.commit.hexsha  # i.e. '3134699c73af83aac2a481435550b968d5792c0d'
-        try:
-            branch = repo.active_branch.name  # i.e. 'main'
-        except TypeError:  # not on any branch
-            branch = None  # i.e. 'detached HEAD' state
-        return {'remote': remote, 'branch': branch, 'commit': commit}
-    except git.exc.InvalidGitRepositoryError:  # path is not a git dir
-        return {'remote': None, 'branch': None, 'commit': None}
-
-
-def check_python(minimum='3.7.0'):
-    # Check current python version vs. required python version
-    check_version(platform.python_version(), minimum, name='Python ', hard=True)
-
-
-def check_version(current='0.0.0', minimum='0.0.0', name='version ', pinned=False, hard=False, verbose=False):
-    # Check version vs. required version
-    current, minimum = (pkg.parse_version(x) for x in (current, minimum))
-    result = (current == minimum) if pinned else (current >= minimum)  # bool
-    s = f'WARNING ⚠️ {name}{minimum} is required by YOLOv5, but {name}{current} is currently installed'  # string
-    if hard:
-        assert result, emojis(s)  # assert min requirements met
-    if verbose and not result:
-        LOGGER.warning(s)
-    return result
-
-
-@TryExcept()
-def check_requirements(requirements=ROOT / 'requirements.txt', exclude=(), install=True, cmds=''):
-    # Check installed dependencies meet YOLOv5 requirements (pass *.txt file or list of packages or single package str)
-    prefix = colorstr('red', 'bold', 'requirements:')
-    check_python()  # check python version
-    if isinstance(requirements, Path):  # requirements.txt file
-        file = requirements.resolve()
-        assert file.exists(), f'{prefix} {file} not found, check failed.'
-        with file.open() as f:
-            requirements = [f'{x.name}{x.specifier}' for x in pkg.parse_requirements(f) if x.name not in exclude]
-    elif isinstance(requirements, str):
-        requirements = [requirements]
-
-    s = ''
-    n = 0
-    for r in requirements:
-        try:
-            pkg.require(r)
-        except (pkg.VersionConflict, pkg.DistributionNotFound):  # exception if requirements not met
-            s += f'"{r}" '
-            n += 1
-
-    if s and install and AUTOINSTALL:  # check environment variable
-        LOGGER.info(f"{prefix} YOLOv5 requirement{'s' * (n > 1)} {s}not found, attempting AutoUpdate...")
-        try:
-            # assert check_online(), "AutoUpdate skipped (offline)"
-            LOGGER.info(check_output(f'pip install {s} {cmds}', shell=True).decode())
-            source = file if 'file' in locals() else requirements
-            s = f"{prefix} {n} package{'s' * (n > 1)} updated per {source}\n" \
-                f"{prefix} ⚠️ {colorstr('bold', 'Restart runtime or rerun command for updates to take effect')}\n"
-            LOGGER.info(s)
-        except Exception as e:
-            LOGGER.warning(f'{prefix} ❌ {e}')
-
-
-def check_img_size(imgsz, s=32, floor=0):
-    # Verify image size is a multiple of stride s in each dimension
-    if isinstance(imgsz, int):  # integer i.e. img_size=640
-        new_size = max(make_divisible(imgsz, int(s)), floor)
-    else:  # list i.e. img_size=[640, 480]
-        imgsz = list(imgsz)  # convert to list if tuple
-        new_size = [max(make_divisible(x, int(s)), floor) for x in imgsz]
-    if new_size != imgsz:
-        LOGGER.warning(f'WARNING ⚠️ --img-size {imgsz} must be multiple of max stride {s}, updating to {new_size}')
-    return new_size
-
-
-def check_imshow(warn=False):
-    # Check if environment supports image displays
-    try:
-        assert not is_jupyter()
-        assert not is_docker()
-        cv2.imshow('test', np.zeros((1, 1, 3)))
-        cv2.waitKey(1)
-        cv2.destroyAllWindows()
-        cv2.waitKey(1)
-        return True
-    except Exception as e:
-        if warn:
-            LOGGER.warning(f'WARNING ⚠️ Environment does not support cv2.imshow() or PIL Image.show()\n{e}')
-        return False
-
-
-def check_suffix(file='yolov5s.pt', suffix=('.pt',), msg=''):
-    # Check file(s) for acceptable suffix
-    if file and suffix:
-        if isinstance(suffix, str):
-            suffix = [suffix]
-        for f in file if isinstance(file, (list, tuple)) else [file]:
-            s = Path(f).suffix.lower()  # file suffix
-            if len(s):
-                assert s in suffix, f'{msg}{f} acceptable suffix is {suffix}'
-
-
-def check_yaml(file, suffix=('.yaml', '.yml')):
-    # Search/download YAML file (if necessary) and return path, checking suffix
-    return check_file(file, suffix)
-
-
-def check_file(file, suffix=''):
-    # Search/download file (if necessary) and return path
-    check_suffix(file, suffix)  # optional
-    file = str(file)  # convert to str()
-    if os.path.isfile(file) or not file:  # exists
-        return file
-    elif file.startswith(('http:/', 'https:/')):  # download
-        url = file  # warning: Pathlib turns :// -> :/
-        file = Path(urllib.parse.unquote(file).split('?')[0]).name  # '%2F' to '/', split https://url.com/file.txt?auth
-        if os.path.isfile(file):
-            LOGGER.info(f'Found {url} locally at {file}')  # file already exists
-        else:
-            LOGGER.info(f'Downloading {url} to {file}...')
-            torch.hub.download_url_to_file(url, file)
-            assert Path(file).exists() and Path(file).stat().st_size > 0, f'File download failed: {url}'  # check
-        return file
-    elif file.startswith('clearml://'):  # ClearML Dataset ID
-        assert 'clearml' in sys.modules, "ClearML is not installed, so cannot use ClearML dataset. Try running 'pip install clearml'."
-        return file
-    else:  # search
-        files = []
-        for d in 'data', 'models', 'utils':  # search directories
-            files.extend(glob.glob(str(ROOT / d / '**' / file), recursive=True))  # find file
-        assert len(files), f'File not found: {file}'  # assert file was found
-        assert len(files) == 1, f"Multiple files match '{file}', specify exact path: {files}"  # assert unique
-        return files[0]  # return file
-
-
-def check_font(font=FONT, progress=False):
-    # Download font to CONFIG_DIR if necessary
-    font = Path(font)
-    file = CONFIG_DIR / font.name
-    if not font.exists() and not file.exists():
-        url = f'https://ultralytics.com/assets/{font.name}'
-        LOGGER.info(f'Downloading {url} to {file}...')
-        torch.hub.download_url_to_file(url, str(file), progress=progress)
-
-
-def check_dataset(data, autodownload=True):
-    # Download, check and/or unzip dataset if not found locally
-
-    # Download (optional)
-    extract_dir = ''
-    if isinstance(data, (str, Path)) and (is_zipfile(data) or is_tarfile(data)):
-        download(data, dir=f'{DATASETS_DIR}/{Path(data).stem}', unzip=True, delete=False, curl=False, threads=1)
-        data = next((DATASETS_DIR / Path(data).stem).rglob('*.yaml'))
-        extract_dir, autodownload = data.parent, False
-
-    # Read yaml (optional)
-    if isinstance(data, (str, Path)):
-        data = yaml_load(data)  # dictionary
-
-    # Checks
-    for k in 'train', 'val', 'names':
-        assert k in data, emojis(f"data.yaml '{k}:' field missing ❌")
-    if isinstance(data['names'], (list, tuple)):  # old array format
-        data['names'] = dict(enumerate(data['names']))  # convert to dict
-    assert all(isinstance(k, int) for k in data['names'].keys()), 'data.yaml names keys must be integers, i.e. 2: car'
-    data['nc'] = len(data['names'])
-
-    # Resolve paths
-    path = Path(extract_dir or data.get('path') or '')  # optional 'path' default to '.'
-    if not path.is_absolute():
-        path = (ROOT / path).resolve()
-        data['path'] = path  # download scripts
-    for k in 'train', 'val', 'test':
-        if data.get(k):  # prepend path
-            if isinstance(data[k], str):
-                x = (path / data[k]).resolve()
-                if not x.exists() and data[k].startswith('../'):
-                    x = (path / data[k][3:]).resolve()
-                data[k] = str(x)
-            else:
-                data[k] = [str((path / x).resolve()) for x in data[k]]
-
-    # Parse yaml
-    train, val, test, s = (data.get(x) for x in ('train', 'val', 'test', 'download'))
-    if val:
-        val = [Path(x).resolve() for x in (val if isinstance(val, list) else [val])]  # val path
-        if not all(x.exists() for x in val):
-            LOGGER.info('\nDataset not found ⚠️, missing paths %s' % [str(x) for x in val if not x.exists()])
-            if not s or not autodownload:
-                raise Exception('Dataset not found ❌')
-            t = time.time()
-            if s.startswith('http') and s.endswith('.zip'):  # URL
-                f = Path(s).name  # filename
-                LOGGER.info(f'Downloading {s} to {f}...')
-                torch.hub.download_url_to_file(s, f)
-                Path(DATASETS_DIR).mkdir(parents=True, exist_ok=True)  # create root
-                unzip_file(f, path=DATASETS_DIR)  # unzip
-                Path(f).unlink()  # remove zip
-                r = None  # success
-            elif s.startswith('bash '):  # bash script
-                LOGGER.info(f'Running {s} ...')
-                r = subprocess.run(s, shell=True)
-            else:  # python script
-                r = exec(s, {'yaml': data})  # return None
-            dt = f'({round(time.time() - t, 1)}s)'
-            s = f"success ✅ {dt}, saved to {colorstr('bold', DATASETS_DIR)}" if r in (0, None) else f'failure {dt} ❌'
-            LOGGER.info(f'Dataset download {s}')
-    check_font('Arial.ttf' if is_ascii(data['names']) else 'Arial.Unicode.ttf', progress=True)  # download fonts
-    return data  # dictionary
-
-
-def check_amp(model):
-    # Check PyTorch Automatic Mixed Precision (AMP) functionality. Return True on correct operation
-    from models.common import AutoShape, DetectMultiBackend
-
-    def amp_allclose(model, im):
-        # All close FP32 vs AMP results
-        m = AutoShape(model, verbose=False)  # model
-        a = m(im).xywhn[0]  # FP32 inference
-        m.amp = True
-        b = m(im).xywhn[0]  # AMP inference
-        return a.shape == b.shape and torch.allclose(a, b, atol=0.1)  # close to 10% absolute tolerance
-
-    prefix = colorstr('AMP: ')
-    device = next(model.parameters()).device  # get model device
-    if device.type in ('cpu', 'mps'):
-        return False  # AMP only used on CUDA devices
-    f = ROOT / 'data' / 'images' / 'bus.jpg'  # image to check
-    im = f if f.exists() else 'https://ultralytics.com/images/bus.jpg' if check_online() else np.ones((640, 640, 3))
-    try:
-        assert amp_allclose(deepcopy(model), im) or amp_allclose(DetectMultiBackend('yolov5n.pt', device), im)
-        LOGGER.info(f'{prefix}checks passed ✅')
-        return True
-    except Exception:
-        help_url = 'https://github.com/ultralytics/yolov5/issues/7908'
-        LOGGER.warning(f'{prefix}checks failed ❌, disabling Automatic Mixed Precision. See {help_url}')
-        return False
-
-
-def yaml_load(file='data.yaml'):
-    # Single-line safe yaml loading
-    with open(file, errors='ignore') as f:
-        return yaml.safe_load(f)
-
-
-def yaml_save(file='data.yaml', data={}):
-    # Single-line safe yaml saving
-    with open(file, 'w') as f:
-        yaml.safe_dump({k: str(v) if isinstance(v, Path) else v for k, v in data.items()}, f, sort_keys=False)
-
-
-def unzip_file(file, path=None, exclude=('.DS_Store', '__MACOSX')):
-    # Unzip a *.zip file to path/, excluding files containing strings in exclude list
-    if path is None:
-        path = Path(file).parent  # default path
-    with ZipFile(file) as zipObj:
-        for f in zipObj.namelist():  # list all archived filenames in the zip
-            if all(x not in f for x in exclude):
-                zipObj.extract(f, path=path)
-
-
-def url2file(url):
-    # Convert URL to filename, i.e. https://url.com/file.txt?auth -> file.txt
-    url = str(Path(url)).replace(':/', '://')  # Pathlib turns :// -> :/
-    return Path(urllib.parse.unquote(url)).name.split('?')[0]  # '%2F' to '/', split https://url.com/file.txt?auth
-
-
-def download(url, dir='.', unzip=True, delete=True, curl=False, threads=1, retry=3):
-    # Multithreaded file download and unzip function, used in data.yaml for autodownload
-    def download_one(url, dir):
-        # Download 1 file
-        success = True
-        if os.path.isfile(url):
-            f = Path(url)  # filename
-        else:  # does not exist
-            f = dir / Path(url).name
-            LOGGER.info(f'Downloading {url} to {f}...')
-            for i in range(retry + 1):
-                if curl:
-                    success = curl_download(url, f, silent=(threads > 1))
-                else:
-                    torch.hub.download_url_to_file(url, f, progress=threads == 1)  # torch download
-                    success = f.is_file()
-                if success:
-                    break
-                elif i < retry:
-                    LOGGER.warning(f'⚠️ Download failure, retrying {i + 1}/{retry} {url}...')
-                else:
-                    LOGGER.warning(f'❌ Failed to download {url}...')
-
-        if unzip and success and (f.suffix == '.gz' or is_zipfile(f) or is_tarfile(f)):
-            LOGGER.info(f'Unzipping {f}...')
-            if is_zipfile(f):
-                unzip_file(f, dir)  # unzip
-            elif is_tarfile(f):
-                subprocess.run(['tar', 'xf', f, '--directory', f.parent], check=True)  # unzip
-            elif f.suffix == '.gz':
-                subprocess.run(['tar', 'xfz', f, '--directory', f.parent], check=True)  # unzip
-            if delete:
-                f.unlink()  # remove zip
-
-    dir = Path(dir)
-    dir.mkdir(parents=True, exist_ok=True)  # make directory
-    if threads > 1:
-        pool = ThreadPool(threads)
-        pool.imap(lambda x: download_one(*x), zip(url, repeat(dir)))  # multithreaded
-        pool.close()
-        pool.join()
-    else:
-        for u in [url] if isinstance(url, (str, Path)) else url:
-            download_one(u, dir)
-
-
-def make_divisible(x, divisor):
-    # Returns nearest x divisible by divisor
-    if isinstance(divisor, torch.Tensor):
-        divisor = int(divisor.max())  # to int
-    return math.ceil(x / divisor) * divisor
-
-
-def clean_str(s):
-    # Cleans a string by replacing special characters with underscore _
-    return re.sub(pattern='[|@#!¡·$€%&()=?¿^*;:,¨´><+]', repl='_', string=s)
-
-
-def one_cycle(y1=0.0, y2=1.0, steps=100):
-    # lambda function for sinusoidal ramp from y1 to y2 https://arxiv.org/pdf/1812.01187.pdf
-    return lambda x: ((1 - math.cos(x * math.pi / steps)) / 2) * (y2 - y1) + y1
-
-
-def colorstr(*input):
-    # Colors a string https://en.wikipedia.org/wiki/ANSI_escape_code, i.e.  colorstr('blue', 'hello world')
-    *args, string = input if len(input) > 1 else ('blue', 'bold', input[0])  # color arguments, string
-    colors = {
-        'black': '\033[30m',  # basic colors
-        'red': '\033[31m',
-        'green': '\033[32m',
-        'yellow': '\033[33m',
-        'blue': '\033[34m',
-        'magenta': '\033[35m',
-        'cyan': '\033[36m',
-        'white': '\033[37m',
-        'bright_black': '\033[90m',  # bright colors
-        'bright_red': '\033[91m',
-        'bright_green': '\033[92m',
-        'bright_yellow': '\033[93m',
-        'bright_blue': '\033[94m',
-        'bright_magenta': '\033[95m',
-        'bright_cyan': '\033[96m',
-        'bright_white': '\033[97m',
-        'end': '\033[0m',  # misc
-        'bold': '\033[1m',
-        'underline': '\033[4m'}
-    return ''.join(colors[x] for x in args) + f'{string}' + colors['end']
-
-
-def labels_to_class_weights(labels, nc=80):
-    # Get class weights (inverse frequency) from training labels
-    if labels[0] is None:  # no labels loaded
-        return torch.Tensor()
-
-    labels = np.concatenate(labels, 0)  # labels.shape = (866643, 5) for COCO
-    classes = labels[:, 0].astype(int)  # labels = [class xywh]
-    weights = np.bincount(classes, minlength=nc)  # occurrences per class
-
-    # Prepend gridpoint count (for uCE training)
-    # gpi = ((320 / 32 * np.array([1, 2, 4])) ** 2 * 3).sum()  # gridpoints per image
-    # weights = np.hstack([gpi * len(labels)  - weights.sum() * 9, weights * 9]) ** 0.5  # prepend gridpoints to start
-
-    weights[weights == 0] = 1  # replace empty bins with 1
-    weights = 1 / weights  # number of targets per class
-    weights /= weights.sum()  # normalize
-    return torch.from_numpy(weights).float()
-
-
-def labels_to_image_weights(labels, nc=80, class_weights=np.ones(80)):
-    # Produces image weights based on class_weights and image contents
-    # Usage: index = random.choices(range(n), weights=image_weights, k=1)  # weighted image sample
-    class_counts = np.array([np.bincount(x[:, 0].astype(int), minlength=nc) for x in labels])
-    return (class_weights.reshape(1, nc) * class_counts).sum(1)
-
-
-def coco80_to_coco91_class():  # converts 80-index (val2014) to 91-index (paper)
-    # https://tech.amikelive.com/node-718/what-object-categories-labels-are-in-coco-dataset/
-    # a = np.loadtxt('data/coco.names', dtype='str', delimiter='\n')
-    # b = np.loadtxt('data/coco_paper.names', dtype='str', delimiter='\n')
-    # x1 = [list(a[i] == b).index(True) + 1 for i in range(80)]  # darknet to coco
-    # x2 = [list(b[i] == a).index(True) if any(b[i] == a) else None for i in range(91)]  # coco to darknet
-    return [
-        1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 28, 31, 32, 33, 34,
-        35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63,
-        64, 65, 67, 70, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 84, 85, 86, 87, 88, 89, 90]
-
-
-def xyxy2xywh(x):
-    # Convert nx4 boxes from [x1, y1, x2, y2] to [x, y, w, h] where xy1=top-left, xy2=bottom-right
-    y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
-    y[..., 0] = (x[..., 0] + x[..., 2]) / 2  # x center
-    y[..., 1] = (x[..., 1] + x[..., 3]) / 2  # y center
-    y[..., 2] = x[..., 2] - x[..., 0]  # width
-    y[..., 3] = x[..., 3] - x[..., 1]  # height
-    return y
-
-
-def xywh2xyxy(x):
-    # Convert nx4 boxes from [x, y, w, h] to [x1, y1, x2, y2] where xy1=top-left, xy2=bottom-right
-    y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
-    y[..., 0] = x[..., 0] - x[..., 2] / 2  # top left x
-    y[..., 1] = x[..., 1] - x[..., 3] / 2  # top left y
-    y[..., 2] = x[..., 0] + x[..., 2] / 2  # bottom right x
-    y[..., 3] = x[..., 1] + x[..., 3] / 2  # bottom right y
-    return y
-
-
-def xywhn2xyxy(x, w=640, h=640, padw=0, padh=0):
-    # Convert nx4 boxes from [x, y, w, h] normalized to [x1, y1, x2, y2] where xy1=top-left, xy2=bottom-right
-    y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
-    y[..., 0] = w * (x[..., 0] - x[..., 2] / 2) + padw  # top left x
-    y[..., 1] = h * (x[..., 1] - x[..., 3] / 2) + padh  # top left y
-    y[..., 2] = w * (x[..., 0] + x[..., 2] / 2) + padw  # bottom right x
-    y[..., 3] = h * (x[..., 1] + x[..., 3] / 2) + padh  # bottom right y
-    return y
-
-
-def xyxy2xywhn(x, w=640, h=640, clip=False, eps=0.0):
-    # Convert nx4 boxes from [x1, y1, x2, y2] to [x, y, w, h] normalized where xy1=top-left, xy2=bottom-right
-    if clip:
-        clip_boxes(x, (h - eps, w - eps))  # warning: inplace clip
-    y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
-    y[..., 0] = ((x[..., 0] + x[..., 2]) / 2) / w  # x center
-    y[..., 1] = ((x[..., 1] + x[..., 3]) / 2) / h  # y center
-    y[..., 2] = (x[..., 2] - x[..., 0]) / w  # width
-    y[..., 3] = (x[..., 3] - x[..., 1]) / h  # height
-    return y
-
-
-def xyn2xy(x, w=640, h=640, padw=0, padh=0):
-    # Convert normalized segments into pixel segments, shape (n,2)
-    y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
-    y[..., 0] = w * x[..., 0] + padw  # top left x
-    y[..., 1] = h * x[..., 1] + padh  # top left y
-    return y
-
-
-def segment2box(segment, width=640, height=640):
-    # Convert 1 segment label to 1 box label, applying inside-image constraint, i.e. (xy1, xy2, ...) to (xyxy)
-    x, y = segment.T  # segment xy
-    inside = (x >= 0) & (y >= 0) & (x <= width) & (y <= height)
-    x, y, = x[inside], y[inside]
-    return np.array([x.min(), y.min(), x.max(), y.max()]) if any(x) else np.zeros((1, 4))  # xyxy
-
-
-def segments2boxes(segments):
-    # Convert segment labels to box labels, i.e. (cls, xy1, xy2, ...) to (cls, xywh)
-    boxes = []
-    for s in segments:
-        x, y = s.T  # segment xy
-        boxes.append([x.min(), y.min(), x.max(), y.max()])  # cls, xyxy
-    return xyxy2xywh(np.array(boxes))  # cls, xywh
-
-
-def resample_segments(segments, n=1000):
-    # Up-sample an (n,2) segment
-    for i, s in enumerate(segments):
-        s = np.concatenate((s, s[0:1, :]), axis=0)
-        x = np.linspace(0, len(s) - 1, n)
-        xp = np.arange(len(s))
-        segments[i] = np.concatenate([np.interp(x, xp, s[:, i]) for i in range(2)]).reshape(2, -1).T  # segment xy
-    return segments
-
-
-def scale_boxes(img1_shape, boxes, img0_shape, ratio_pad=None):
-    # Rescale boxes (xyxy) from img1_shape to img0_shape
-    if ratio_pad is None:  # calculate from img0_shape
-        gain = min(img1_shape[0] / img0_shape[0], img1_shape[1] / img0_shape[1])  # gain  = old / new
-        pad = (img1_shape[1] - img0_shape[1] * gain) / 2, (img1_shape[0] - img0_shape[0] * gain) / 2  # wh padding
-    else:
-        gain = ratio_pad[0][0]
-        pad = ratio_pad[1]
-
-    boxes[..., [0, 2]] -= pad[0]  # x padding
-    boxes[..., [1, 3]] -= pad[1]  # y padding
-    boxes[..., :4] /= gain
-    clip_boxes(boxes, img0_shape)
-    return boxes
-
-
-def scale_segments(img1_shape, segments, img0_shape, ratio_pad=None, normalize=False):
-    # Rescale coords (xyxy) from img1_shape to img0_shape
-    if ratio_pad is None:  # calculate from img0_shape
-        gain = min(img1_shape[0] / img0_shape[0], img1_shape[1] / img0_shape[1])  # gain  = old / new
-        pad = (img1_shape[1] - img0_shape[1] * gain) / 2, (img1_shape[0] - img0_shape[0] * gain) / 2  # wh padding
-    else:
-        gain = ratio_pad[0][0]
-        pad = ratio_pad[1]
-
-    segments[:, 0] -= pad[0]  # x padding
-    segments[:, 1] -= pad[1]  # y padding
-    segments /= gain
-    clip_segments(segments, img0_shape)
-    if normalize:
-        segments[:, 0] /= img0_shape[1]  # width
-        segments[:, 1] /= img0_shape[0]  # height
-    return segments
-
-
-def clip_boxes(boxes, shape):
-    # Clip boxes (xyxy) to image shape (height, width)
-    if isinstance(boxes, torch.Tensor):  # faster individually
-        boxes[..., 0].clamp_(0, shape[1])  # x1
-        boxes[..., 1].clamp_(0, shape[0])  # y1
-        boxes[..., 2].clamp_(0, shape[1])  # x2
-        boxes[..., 3].clamp_(0, shape[0])  # y2
-    else:  # np.array (faster grouped)
-        boxes[..., [0, 2]] = boxes[..., [0, 2]].clip(0, shape[1])  # x1, x2
-        boxes[..., [1, 3]] = boxes[..., [1, 3]].clip(0, shape[0])  # y1, y2
-
-
-def clip_segments(segments, shape):
-    # Clip segments (xy1,xy2,...) to image shape (height, width)
-    if isinstance(segments, torch.Tensor):  # faster individually
-        segments[:, 0].clamp_(0, shape[1])  # x
-        segments[:, 1].clamp_(0, shape[0])  # y
-    else:  # np.array (faster grouped)
-        segments[:, 0] = segments[:, 0].clip(0, shape[1])  # x
-        segments[:, 1] = segments[:, 1].clip(0, shape[0])  # y
-
-
-def non_max_suppression(
-        prediction,
-        conf_thres=0.25,
-        iou_thres=0.45,
-        classes=None,
-        agnostic=False,
-        multi_label=False,
-        labels=(),
-        max_det=300,
-        nm=0,  # number of masks
-):
-    """Non-Maximum Suppression (NMS) on inference results to reject overlapping detections
-
-    Returns:
-         list of detections, on (n,6) tensor per image [xyxy, conf, cls]
-    """
-
-    # Checks
-    assert 0 <= conf_thres <= 1, f'Invalid Confidence threshold {conf_thres}, valid values are between 0.0 and 1.0'
-    assert 0 <= iou_thres <= 1, f'Invalid IoU {iou_thres}, valid values are between 0.0 and 1.0'
-    if isinstance(prediction, (list, tuple)):  # YOLOv5 model in validation model, output = (inference_out, loss_out)
-        prediction = prediction[0]  # select only inference output
-
-    device = prediction.device
-    mps = 'mps' in device.type  # Apple MPS
-    if mps:  # MPS not fully supported yet, convert tensors to CPU before NMS
-        prediction = prediction.cpu()
-    bs = prediction.shape[0]  # batch size
-    nc = prediction.shape[2] - nm - 5  # number of classes
-    xc = prediction[..., 4] > conf_thres  # candidates
-
-    # Settings
-    # min_wh = 2  # (pixels) minimum box width and height
-    max_wh = 7680  # (pixels) maximum box width and height
-    max_nms = 30000  # maximum number of boxes into torchvision.ops.nms()
-    time_limit = 0.5 + 0.05 * bs  # seconds to quit after
-    redundant = True  # require redundant detections
-    multi_label &= nc > 1  # multiple labels per box (adds 0.5ms/img)
-    merge = False  # use merge-NMS
-
-    t = time.time()
-    mi = 5 + nc  # mask start index
-    output = [torch.zeros((0, 6 + nm), device=prediction.device)] * bs
-    for xi, x in enumerate(prediction):  # image index, image inference
-        # Apply constraints
-        # x[((x[..., 2:4] < min_wh) | (x[..., 2:4] > max_wh)).any(1), 4] = 0  # width-height
-        x = x[xc[xi]]  # confidence
-
-        # Cat apriori labels if autolabelling
-        if labels and len(labels[xi]):
-            lb = labels[xi]
-            v = torch.zeros((len(lb), nc + nm + 5), device=x.device)
-            v[:, :4] = lb[:, 1:5]  # box
-            v[:, 4] = 1.0  # conf
-            v[range(len(lb)), lb[:, 0].long() + 5] = 1.0  # cls
-            x = torch.cat((x, v), 0)
-
-        # If none remain process next image
-        if not x.shape[0]:
-            continue
-
-        # Compute conf
-        x[:, 5:] *= x[:, 4:5]  # conf = obj_conf * cls_conf
-
-        # Box/Mask
-        box = xywh2xyxy(x[:, :4])  # center_x, center_y, width, height) to (x1, y1, x2, y2)
-        mask = x[:, mi:]  # zero columns if no masks
-
-        # Detections matrix nx6 (xyxy, conf, cls)
-        if multi_label:
-            i, j = (x[:, 5:mi] > conf_thres).nonzero(as_tuple=False).T
-            x = torch.cat((box[i], x[i, 5 + j, None], j[:, None].float(), mask[i]), 1)
-        else:  # best class only
-            conf, j = x[:, 5:mi].max(1, keepdim=True)
-            x = torch.cat((box, conf, j.float(), mask), 1)[conf.view(-1) > conf_thres]
-
-        # Filter by class
-        if classes is not None:
-            x = x[(x[:, 5:6] == torch.tensor(classes, device=x.device)).any(1)]
-
-        # Apply finite constraint
-        # if not torch.isfinite(x).all():
-        #     x = x[torch.isfinite(x).all(1)]
-
-        # Check shape
-        n = x.shape[0]  # number of boxes
-        if not n:  # no boxes
-            continue
-        x = x[x[:, 4].argsort(descending=True)[:max_nms]]  # sort by confidence and remove excess boxes
-
-        # Batched NMS
-        c = x[:, 5:6] * (0 if agnostic else max_wh)  # classes
-        boxes, scores = x[:, :4] + c, x[:, 4]  # boxes (offset by class), scores
-        i = torchvision.ops.nms(boxes, scores, iou_thres)  # NMS
-        i = i[:max_det]  # limit detections
-        if merge and (1 < n < 3E3):  # Merge NMS (boxes merged using weighted mean)
-            # update boxes as boxes(i,4) = weights(i,n) * boxes(n,4)
-            iou = box_iou(boxes[i], boxes) > iou_thres  # iou matrix
-            weights = iou * scores[None]  # box weights
-            x[i, :4] = torch.mm(weights, x[:, :4]).float() / weights.sum(1, keepdim=True)  # merged boxes
-            if redundant:
-                i = i[iou.sum(1) > 1]  # require redundancy
-
-        output[xi] = x[i]
-        if mps:
-            output[xi] = output[xi].to(device)
-        if (time.time() - t) > time_limit:
-            LOGGER.warning(f'WARNING ⚠️ NMS time limit {time_limit:.3f}s exceeded')
-            break  # time limit exceeded
-
-    return output
-
-
-def strip_optimizer(f='best.pt', s=''):  # from utils.general import *; strip_optimizer()
-    # Strip optimizer from 'f' to finalize training, optionally save as 's'
-    x = torch.load(f, map_location=torch.device('cpu'))
-    if x.get('ema'):
-        x['model'] = x['ema']  # replace model with ema
-    for k in 'optimizer', 'best_fitness', 'ema', 'updates':  # keys
-        x[k] = None
-    x['epoch'] = -1
-    x['model'].half()  # to FP16
-    for p in x['model'].parameters():
-        p.requires_grad = False
-    torch.save(x, s or f)
-    mb = os.path.getsize(s or f) / 1E6  # filesize
-    LOGGER.info(f"Optimizer stripped from {f},{f' saved as {s},' if s else ''} {mb:.1f}MB")
-
-
-def print_mutation(keys, results, hyp, save_dir, bucket, prefix=colorstr('evolve: ')):
-    evolve_csv = save_dir / 'evolve.csv'
-    evolve_yaml = save_dir / 'hyp_evolve.yaml'
-    keys = tuple(keys) + tuple(hyp.keys())  # [results + hyps]
-    keys = tuple(x.strip() for x in keys)
-    vals = results + tuple(hyp.values())
-    n = len(keys)
-
-    # Download (optional)
-    if bucket:
-        url = f'gs://{bucket}/evolve.csv'
-        if gsutil_getsize(url) > (evolve_csv.stat().st_size if evolve_csv.exists() else 0):
-            subprocess.run(['gsutil', 'cp', f'{url}', f'{save_dir}'])  # download evolve.csv if larger than local
-
-    # Log to evolve.csv
-    s = '' if evolve_csv.exists() else (('%20s,' * n % keys).rstrip(',') + '\n')  # add header
-    with open(evolve_csv, 'a') as f:
-        f.write(s + ('%20.5g,' * n % vals).rstrip(',') + '\n')
-
-    # Save yaml
-    with open(evolve_yaml, 'w') as f:
-        data = pd.read_csv(evolve_csv, skipinitialspace=True)
-        data = data.rename(columns=lambda x: x.strip())  # strip keys
-        i = np.argmax(fitness(data.values[:, :4]))  #
-        generations = len(data)
-        f.write('# YOLOv5 Hyperparameter Evolution Results\n' + f'# Best generation: {i}\n' +
-                f'# Last generation: {generations - 1}\n' + '# ' + ', '.join(f'{x.strip():>20s}' for x in keys[:7]) +
-                '\n' + '# ' + ', '.join(f'{x:>20.5g}' for x in data.values[i, :7]) + '\n\n')
-        yaml.safe_dump(data.loc[i][7:].to_dict(), f, sort_keys=False)
-
-    # Print to screen
-    LOGGER.info(prefix + f'{generations} generations finished, current result:\n' + prefix +
-                ', '.join(f'{x.strip():>20s}' for x in keys) + '\n' + prefix + ', '.join(f'{x:20.5g}'
-                                                                                         for x in vals) + '\n\n')
-
-    if bucket:
-        subprocess.run(['gsutil', 'cp', f'{evolve_csv}', f'{evolve_yaml}', f'gs://{bucket}'])  # upload
-
-
-def apply_classifier(x, model, img, im0):
-    # Apply a second stage classifier to YOLO outputs
-    # Example model = torchvision.models.__dict__['efficientnet_b0'](pretrained=True).to(device).eval()
-    im0 = [im0] if isinstance(im0, np.ndarray) else im0
-    for i, d in enumerate(x):  # per image
-        if d is not None and len(d):
-            d = d.clone()
-
-            # Reshape and pad cutouts
-            b = xyxy2xywh(d[:, :4])  # boxes
-            b[:, 2:] = b[:, 2:].max(1)[0].unsqueeze(1)  # rectangle to square
-            b[:, 2:] = b[:, 2:] * 1.3 + 30  # pad
-            d[:, :4] = xywh2xyxy(b).long()
-
-            # Rescale boxes from img_size to im0 size
-            scale_boxes(img.shape[2:], d[:, :4], im0[i].shape)
-
-            # Classes
-            pred_cls1 = d[:, 5].long()
-            ims = []
-            for a in d:
-                cutout = im0[i][int(a[1]):int(a[3]), int(a[0]):int(a[2])]
-                im = cv2.resize(cutout, (224, 224))  # BGR
-
-                im = im[:, :, ::-1].transpose(2, 0, 1)  # BGR to RGB, to 3x416x416
-                im = np.ascontiguousarray(im, dtype=np.float32)  # uint8 to float32
-                im /= 255  # 0 - 255 to 0.0 - 1.0
-                ims.append(im)
-
-            pred_cls2 = model(torch.Tensor(ims).to(d.device)).argmax(1)  # classifier prediction
-            x[i] = x[i][pred_cls1 == pred_cls2]  # retain matching class detections
-
-    return x
-
-
-def increment_path(path, exist_ok=False, sep='', mkdir=False):
-    # Increment file or directory path, i.e. runs/exp --> runs/exp{sep}2, runs/exp{sep}3, ... etc.
-    path = Path(path)  # os-agnostic
-    if path.exists() and not exist_ok:
-        path, suffix = (path.with_suffix(''), path.suffix) if path.is_file() else (path, '')
-
-        # Method 1
-        for n in range(2, 9999):
-            p = f'{path}{sep}{n}{suffix}'  # increment path
-            if not os.path.exists(p):  #
-                break
-        path = Path(p)
-
-        # Method 2 (deprecated)
-        # dirs = glob.glob(f"{path}{sep}*")  # similar paths
-        # matches = [re.search(rf"{path.stem}{sep}(\d+)", d) for d in dirs]
-        # i = [int(m.groups()[0]) for m in matches if m]  # indices
-        # n = max(i) + 1 if i else 2  # increment number
-        # path = Path(f"{path}{sep}{n}{suffix}")  # increment path
-
-    if mkdir:
-        path.mkdir(parents=True, exist_ok=True)  # make directory
-
-    return path
-
-
-# OpenCV Multilanguage-friendly functions ------------------------------------------------------------------------------------
-imshow_ = cv2.imshow  # copy to avoid recursion errors
-
-
-def imread(path, flags=cv2.IMREAD_COLOR):
-    return cv2.imdecode(np.fromfile(path, np.uint8), flags)
-
-
-def imwrite(path, im):
-    try:
-        cv2.imencode(Path(path).suffix, im)[1].tofile(path)
-        return True
-    except Exception:
-        return False
-
-
-def imshow(path, im):
-    imshow_(path.encode('unicode_escape').decode(), im)
-
-
-cv2.imread, cv2.imwrite, cv2.imshow = imread, imwrite, imshow  # redefine
-
-# Variables ------------------------------------------------------------------------------------------------------------
diff --git a/spaces/YUANAI/DiffspeechResearch/utils/metrics/diagonal_metrics.py b/spaces/YUANAI/DiffspeechResearch/utils/metrics/diagonal_metrics.py
deleted file mode 100644
index ba9807c1a594b38632c4731391e2d4fa3289037b..0000000000000000000000000000000000000000
--- a/spaces/YUANAI/DiffspeechResearch/utils/metrics/diagonal_metrics.py
+++ /dev/null
@@ -1,74 +0,0 @@
-import torch
-
-
-def get_focus_rate(attn, src_padding_mask=None, tgt_padding_mask=None):
-    '''
-    attn: bs x L_t x L_s
-    '''
-    if src_padding_mask is not None:
-        attn = attn * (1 - src_padding_mask.float())[:, None, :]
-
-    if tgt_padding_mask is not None:
-        attn = attn * (1 - tgt_padding_mask.float())[:, :, None]
-
-    focus_rate = attn.max(-1).values.sum(-1)
-    focus_rate = focus_rate / attn.sum(-1).sum(-1)
-    return focus_rate
-
-
-def get_phone_coverage_rate(attn, src_padding_mask=None, src_seg_mask=None, tgt_padding_mask=None):
-    '''
-    attn: bs x L_t x L_s
-    '''
-    src_mask = attn.new(attn.size(0), attn.size(-1)).bool().fill_(False)
-    if src_padding_mask is not None:
-        src_mask |= src_padding_mask
-    if src_seg_mask is not None:
-        src_mask |= src_seg_mask
-
-    attn = attn * (1 - src_mask.float())[:, None, :]
-    if tgt_padding_mask is not None:
-        attn = attn * (1 - tgt_padding_mask.float())[:, :, None]
-
-    phone_coverage_rate = attn.max(1).values.sum(-1)
-    # phone_coverage_rate = phone_coverage_rate / attn.sum(-1).sum(-1)
-    phone_coverage_rate = phone_coverage_rate / (1 - src_mask.float()).sum(-1)
-    return phone_coverage_rate
-
-
-def get_diagonal_focus_rate(attn, attn_ks, target_len, src_padding_mask=None, tgt_padding_mask=None,
-                            band_mask_factor=5, band_width=50):
-    '''
-    attn: bx x L_t x L_s
-    attn_ks: shape: tensor with shape [batch_size], input_lens/output_lens
-
-    diagonal: y=k*x (k=attn_ks, x:output, y:input)
-    1 0 0
-    0 1 0
-    0 0 1
-    y>=k*(x-width) and y<=k*(x+width):1
-    else:0
-    '''
-    # width = min(target_len/band_mask_factor, 50)
-    width1 = target_len / band_mask_factor
-    width2 = target_len.new(target_len.size()).fill_(band_width)
-    width = torch.where(width1 < width2, width1, width2).float()
-    base = torch.ones(attn.size()).to(attn.device)
-    zero = torch.zeros(attn.size()).to(attn.device)
-    x = torch.arange(0, attn.size(1)).to(attn.device)[None, :, None].float() * base
-    y = torch.arange(0, attn.size(2)).to(attn.device)[None, None, :].float() * base
-    cond = (y - attn_ks[:, None, None] * x)
-    cond1 = cond + attn_ks[:, None, None] * width[:, None, None]
-    cond2 = cond - attn_ks[:, None, None] * width[:, None, None]
-    mask1 = torch.where(cond1 < 0, zero, base)
-    mask2 = torch.where(cond2 > 0, zero, base)
-    mask = mask1 * mask2
-
-    if src_padding_mask is not None:
-        attn = attn * (1 - src_padding_mask.float())[:, None, :]
-    if tgt_padding_mask is not None:
-        attn = attn * (1 - tgt_padding_mask.float())[:, :, None]
-
-    diagonal_attn = attn * mask
-    diagonal_focus_rate = diagonal_attn.sum(-1).sum(-1) / attn.sum(-1).sum(-1)
-    return diagonal_focus_rate, mask
diff --git a/spaces/YeOldHermit/Super-Resolution-Anime-Diffusion/diffusers/pipelines/latent_diffusion_uncond/pipeline_latent_diffusion_uncond.py b/spaces/YeOldHermit/Super-Resolution-Anime-Diffusion/diffusers/pipelines/latent_diffusion_uncond/pipeline_latent_diffusion_uncond.py
deleted file mode 100644
index 5345c4e5625ee519a411b4fd80468fc991757165..0000000000000000000000000000000000000000
--- a/spaces/YeOldHermit/Super-Resolution-Anime-Diffusion/diffusers/pipelines/latent_diffusion_uncond/pipeline_latent_diffusion_uncond.py
+++ /dev/null
@@ -1,111 +0,0 @@
-# Copyright 2022 The HuggingFace Team. All rights reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import inspect
-from typing import Optional, Tuple, Union
-
-import torch
-
-from ...models import UNet2DModel, VQModel
-from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
-from ...schedulers import DDIMScheduler
-
-
-class LDMPipeline(DiffusionPipeline):
-    r"""
-    This model inherits from [`DiffusionPipeline`]. Check the superclass documentation for the generic methods the
-    library implements for all the pipelines (such as downloading or saving, running on a particular device, etc.)
-
-    Parameters:
-        vqvae ([`VQModel`]):
-            Vector-quantized (VQ) Model to encode and decode images to and from latent representations.
-        unet ([`UNet2DModel`]): U-Net architecture to denoise the encoded image latents.
-        scheduler ([`SchedulerMixin`]):
-            [`DDIMScheduler`] is to be used in combination with `unet` to denoise the encoded image latents.
-    """
-
-    def __init__(self, vqvae: VQModel, unet: UNet2DModel, scheduler: DDIMScheduler):
-        super().__init__()
-        self.register_modules(vqvae=vqvae, unet=unet, scheduler=scheduler)
-
-    @torch.no_grad()
-    def __call__(
-        self,
-        batch_size: int = 1,
-        generator: Optional[torch.Generator] = None,
-        eta: float = 0.0,
-        num_inference_steps: int = 50,
-        output_type: Optional[str] = "pil",
-        return_dict: bool = True,
-        **kwargs,
-    ) -> Union[Tuple, ImagePipelineOutput]:
-        r"""
-        Args:
-            batch_size (`int`, *optional*, defaults to 1):
-                Number of images to generate.
-            generator (`torch.Generator`, *optional*):
-                A [torch generator](https://pytorch.org/docs/stable/generated/torch.Generator.html) to make generation
-                deterministic.
-            num_inference_steps (`int`, *optional*, defaults to 50):
-                The number of denoising steps. More denoising steps usually lead to a higher quality image at the
-                expense of slower inference.
-            output_type (`str`, *optional*, defaults to `"pil"`):
-                The output format of the generate image. Choose between
-                [PIL](https://pillow.readthedocs.io/en/stable/): `PIL.Image.Image` or `np.array`.
-            return_dict (`bool`, *optional*, defaults to `True`):
-                Whether or not to return a [`~pipeline_utils.ImagePipelineOutput`] instead of a plain tuple.
-
-        Returns:
-            [`~pipeline_utils.ImagePipelineOutput`] or `tuple`: [`~pipelines.utils.ImagePipelineOutput`] if
-            `return_dict` is True, otherwise a `tuple. When returning a tuple, the first element is a list with the
-            generated images.
-        """
-
-        latents = torch.randn(
-            (batch_size, self.unet.in_channels, self.unet.sample_size, self.unet.sample_size),
-            generator=generator,
-        )
-        latents = latents.to(self.device)
-
-        # scale the initial noise by the standard deviation required by the scheduler
-        latents = latents * self.scheduler.init_noise_sigma
-
-        self.scheduler.set_timesteps(num_inference_steps)
-
-        # prepare extra kwargs for the scheduler step, since not all schedulers have the same signature
-        accepts_eta = "eta" in set(inspect.signature(self.scheduler.step).parameters.keys())
-
-        extra_kwargs = {}
-        if accepts_eta:
-            extra_kwargs["eta"] = eta
-
-        for t in self.progress_bar(self.scheduler.timesteps):
-            latent_model_input = self.scheduler.scale_model_input(latents, t)
-            # predict the noise residual
-            noise_prediction = self.unet(latent_model_input, t).sample
-            # compute the previous noisy sample x_t -> x_t-1
-            latents = self.scheduler.step(noise_prediction, t, latents, **extra_kwargs).prev_sample
-
-        # decode the image latents with the VAE
-        image = self.vqvae.decode(latents).sample
-
-        image = (image / 2 + 0.5).clamp(0, 1)
-        image = image.cpu().permute(0, 2, 3, 1).numpy()
-        if output_type == "pil":
-            image = self.numpy_to_pil(image)
-
-        if not return_dict:
-            return (image,)
-
-        return ImagePipelineOutput(images=image)
diff --git a/spaces/Yiqin/ChatVID/model/fastchat/train/train_lora.py b/spaces/Yiqin/ChatVID/model/fastchat/train/train_lora.py
deleted file mode 100644
index 273df0232e981859ab189613ad0f875e2c88c6cf..0000000000000000000000000000000000000000
--- a/spaces/Yiqin/ChatVID/model/fastchat/train/train_lora.py
+++ /dev/null
@@ -1,151 +0,0 @@
-# Usage: deepspeed train_lora.py --deepspeed <$PATH_TO_DEEPSPEED_CONFIG>
-
-# Adopted from tatsu-lab@stanford_alpaca. Below is the original copyright:
-#    Copyright 2023 Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li
-#
-#    Licensed under the Apache License, Version 2.0 (the "License");
-#    you may not use this file except in compliance with the License.
-#    You may obtain a copy of the License at
-#
-#        http://www.apache.org/licenses/LICENSE-2.0
-#
-#    Unless required by applicable law or agreed to in writing, software
-#    distributed under the License is distributed on an "AS IS" BASIS,
-#    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-#    See the License for the specific language governing permissions and
-#    limitations under the License.
-
-from dataclasses import dataclass, field
-import logging
-import pathlib
-import typing
-
-from deepspeed import zero
-from deepspeed.runtime.zero.partition_parameters import ZeroParamStatus
-from peft import LoraConfig, get_peft_model
-import transformers
-from transformers import Trainer
-
-from fastchat.train.train import (
-    DataArguments,
-    ModelArguments,
-    TrainingArguments,
-    make_supervised_data_module,
-)
-
-from fastchat.train.llama_flash_attn_monkey_patch import (
-    replace_llama_attn_with_flash_attn,
-)
-
-replace_llama_attn_with_flash_attn()
-
-
-@dataclass
-class LoraArguments:
-    lora_r: int = 8
-    lora_alpha: int = 16
-    lora_dropout: float = 0.05
-    lora_target_modules: typing.List[str] = field(
-        default_factory=lambda: ["q_proj", "v_proj"]
-    )
-    lora_weight_path: str = ""
-    bias: str = "none"
-
-
-def maybe_zero_3(param):
-    if hasattr(param, "ds_id"):
-        assert param.ds_status == ZeroParamStatus.NOT_AVAILABLE
-        with zero.GatheredParameters([param]):
-            param = param.data.cpu().clone().detach()
-    return param
-
-
-# Borrowed from peft.utils.get_peft_model_state_dict
-def get_peft_state_maybe_zero_3(state_dict, bias):
-    if bias == "none":
-        to_return = {
-            k: state_dict[k].cpu().clone().detach() for k in state_dict if "lora_" in k
-        }
-    elif bias == "all":
-        to_return = {
-            k: state_dict[k] for k in state_dict if "lora_" in k or "bias" in k
-        }
-    elif bias == "lora_only":
-        to_return = {}
-        for k in state_dict:
-            if "lora_" in k:
-                to_return[k] = state_dict[k]
-                bias_name = k.split("lora_")[0] + "bias"
-                if bias_name in state_dict:
-                    to_return[bias_name] = state_dict[bias_name]
-    else:
-        raise NotImplementedError
-    to_return = {k: maybe_zero_3(v) for k, v in to_return.items()}
-    return to_return
-
-
-def train():
-    parser = transformers.HfArgumentParser(
-        (ModelArguments, DataArguments, TrainingArguments, LoraArguments)
-    )
-    (
-        model_args,
-        data_args,
-        training_args,
-        lora_args,
-    ) = parser.parse_args_into_dataclasses()
-
-    model = transformers.AutoModelForCausalLM.from_pretrained(
-        model_args.model_name_or_path,
-        cache_dir=training_args.cache_dir,
-    )
-    lora_config = LoraConfig(
-        r=lora_args.lora_r,
-        lora_alpha=lora_args.lora_alpha,
-        target_modules=lora_args.lora_target_modules,
-        lora_dropout=lora_args.lora_dropout,
-        bias=lora_args.bias,
-        task_type="CAUSAL_LM",
-    )
-    model = get_peft_model(model, lora_config)
-    if training_args.deepspeed is not None and training_args.local_rank == 0:
-        model.print_trainable_parameters()
-
-    if training_args.gradient_checkpointing:
-        logging.warning(
-            "gradient checkpointing with lora makes requires_grad "
-            "incorrect and needs a monkey patch in Trainer or the "
-            "wrapped model's forward. ref: "
-            "https://github.com/lm-sys/FastChat/pull/138#issuecomment-1509172198"
-        )
-
-    tokenizer = transformers.AutoTokenizer.from_pretrained(
-        model_args.model_name_or_path,
-        cache_dir=training_args.cache_dir,
-        model_max_length=training_args.model_max_length,
-        padding_side="right",
-        use_fast=False,
-    )
-    tokenizer.pad_token = tokenizer.unk_token
-
-    data_module = make_supervised_data_module(tokenizer=tokenizer, data_args=data_args)
-    trainer = Trainer(
-        model=model, tokenizer=tokenizer, args=training_args, **data_module
-    )
-
-    model.config.use_cache = False
-
-    if list(pathlib.Path(training_args.output_dir).glob("checkpoint-*")):
-        trainer.train(resume_from_checkpoint=True)
-    else:
-        trainer.train()
-    trainer.save_state()
-
-    # Save states. Weights might be a placeholder in zero3 and need a gather
-    state_dict = get_peft_state_maybe_zero_3(model.state_dict(), lora_args.bias)
-    if training_args.local_rank == 0:
-        model.save_pretrained(training_args.output_dir, state_dict=state_dict)
-
-
-if __name__ == "__main__":
-    train()
diff --git a/spaces/Yudha515/Rvc-Models/audiocraft/modules/conditioners.py b/spaces/Yudha515/Rvc-Models/audiocraft/modules/conditioners.py
deleted file mode 100644
index 82792316024b88d4c5c38b0a28f443627771d509..0000000000000000000000000000000000000000
--- a/spaces/Yudha515/Rvc-Models/audiocraft/modules/conditioners.py
+++ /dev/null
@@ -1,990 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-
-from collections import defaultdict
-from copy import deepcopy
-from dataclasses import dataclass, field
-from itertools import chain
-import logging
-import math
-import random
-import re
-import typing as tp
-import warnings
-
-from einops import rearrange
-from num2words import num2words
-import spacy
-from transformers import T5EncoderModel, T5Tokenizer  # type: ignore
-import torchaudio
-import torch
-from torch import nn
-from torch import Tensor
-import torch.nn.functional as F
-from torch.nn.utils.rnn import pad_sequence
-
-from .streaming import StreamingModule
-from .transformer import create_sin_embedding
-from ..data.audio_dataset import SegmentInfo
-from ..utils.autocast import TorchAutocast
-from ..utils.utils import hash_trick, length_to_mask, collate
-
-
-logger = logging.getLogger(__name__)
-TextCondition = tp.Optional[str]  # a text condition can be a string or None (if doesn't exist)
-ConditionType = tp.Tuple[Tensor, Tensor]  # condition, mask
-
-
-class WavCondition(tp.NamedTuple):
-    wav: Tensor
-    length: Tensor
-    path: tp.List[tp.Optional[str]] = []
-
-
-def nullify_condition(condition: ConditionType, dim: int = 1):
-    """This function transforms an input condition to a null condition.
-    The way it is done by converting it to a single zero vector similarly
-    to how it is done inside WhiteSpaceTokenizer and NoopTokenizer.
-
-    Args:
-        condition (ConditionType): a tuple of condition and mask (tp.Tuple[Tensor, Tensor])
-        dim (int): the dimension that will be truncated (should be the time dimension)
-        WARNING!: dim should not be the batch dimension!
-    Returns:
-        ConditionType: a tuple of null condition and mask
-    """
-    assert dim != 0, "dim cannot be the batch dimension!"
-    assert type(condition) == tuple and \
-        type(condition[0]) == Tensor and \
-        type(condition[1]) == Tensor, "'nullify_condition' got an unexpected input type!"
-    cond, mask = condition
-    B = cond.shape[0]
-    last_dim = cond.dim() - 1
-    out = cond.transpose(dim, last_dim)
-    out = 0. * out[..., :1]
-    out = out.transpose(dim, last_dim)
-    mask = torch.zeros((B, 1), device=out.device).int()
-    assert cond.dim() == out.dim()
-    return out, mask
-
-
-def nullify_wav(wav: Tensor) -> WavCondition:
-    """Create a nullified WavCondition from a wav tensor with appropriate shape.
-
-    Args:
-        wav (Tensor): tensor of shape [B, T]
-    Returns:
-        WavCondition: wav condition with nullified wav.
-    """
-    null_wav, _ = nullify_condition((wav, torch.zeros_like(wav)), dim=wav.dim() - 1)
-    return WavCondition(
-        wav=null_wav,
-        length=torch.tensor([0] * wav.shape[0], device=wav.device),
-        path=['null_wav'] * wav.shape[0]
-    )
-
-
-@dataclass
-class ConditioningAttributes:
-    text: tp.Dict[str, tp.Optional[str]] = field(default_factory=dict)
-    wav: tp.Dict[str, WavCondition] = field(default_factory=dict)
-
-    def __getitem__(self, item):
-        return getattr(self, item)
-
-    @property
-    def text_attributes(self):
-        return self.text.keys()
-
-    @property
-    def wav_attributes(self):
-        return self.wav.keys()
-
-    @property
-    def attributes(self):
-        return {"text": self.text_attributes, "wav": self.wav_attributes}
-
-    def to_flat_dict(self):
-        return {
-            **{f"text.{k}": v for k, v in self.text.items()},
-            **{f"wav.{k}": v for k, v in self.wav.items()},
-        }
-
-    @classmethod
-    def from_flat_dict(cls, x):
-        out = cls()
-        for k, v in x.items():
-            kind, att = k.split(".")
-            out[kind][att] = v
-        return out
-
-
-class SegmentWithAttributes(SegmentInfo):
-    """Base class for all dataclasses that are used for conditioning.
-    All child classes should implement `to_condition_attributes` that converts
-    the existing attributes to a dataclass of type ConditioningAttributes.
-    """
-    def to_condition_attributes(self) -> ConditioningAttributes:
-        raise NotImplementedError()
-
-
-class Tokenizer:
-    """Base class for all tokenizers
-    (in case we want to introduce more advances tokenizers in the future).
-    """
-    def __call__(self, texts: tp.List[tp.Optional[str]]) -> tp.Tuple[Tensor, Tensor]:
-        raise NotImplementedError()
-
-
-class WhiteSpaceTokenizer(Tokenizer):
-    """This tokenizer should be used for natural language descriptions.
-    For example:
-    ["he didn't, know he's going home.", 'shorter sentence'] =>
-    [[78, 62, 31,  4, 78, 25, 19, 34],
-    [59, 77,  0,  0,  0,  0,  0,  0]]
-    """
-    PUNCTUATIONS = "?:!.,;"
-
-    def __init__(self, n_bins: int, pad_idx: int = 0, language: str = "en_core_web_sm",
-                 lemma: bool = True, stopwords: bool = True) -> None:
-        self.n_bins = n_bins
-        self.pad_idx = pad_idx
-        self.lemma = lemma
-        self.stopwords = stopwords
-        try:
-            self.nlp = spacy.load(language)
-        except IOError:
-            spacy.cli.download(language)  # type: ignore
-            self.nlp = spacy.load(language)
-
-    @tp.no_type_check
-    def __call__(
-        self,
-        texts: tp.List[tp.Optional[str]],
-        return_text: bool = False
-    ) -> tp.Tuple[Tensor, Tensor]:
-        """Take a list of strings and convert them to a tensor of indices.
-
-        Args:
-            texts (tp.List[str]): List of strings.
-            return_text (bool, optional): Whether to return text as additional tuple item. Defaults to False.
-        Returns:
-            tp.Tuple[Tensor, Tensor]:
-                - Indices of words in the LUT.
-                - And a mask indicating where the padding tokens are
-        """
-        output, lengths = [], []
-        texts = deepcopy(texts)
-        for i, text in enumerate(texts):
-            # if current sample doesn't have a certain attribute, replace with pad token
-            if text is None:
-                output.append(Tensor([self.pad_idx]))
-                lengths.append(0)
-                continue
-
-            # convert numbers to words
-            text = re.sub(r"(\d+)", lambda x: num2words(int(x.group(0))), text)  # type: ignore
-            # normalize text
-            text = self.nlp(text)  # type: ignore
-            # remove stopwords
-            if self.stopwords:
-                text = [w for w in text if not w.is_stop]  # type: ignore
-            # remove punctuations
-            text = [w for w in text if w.text not in self.PUNCTUATIONS]  # type: ignore
-            # lemmatize if needed
-            text = [getattr(t, "lemma_" if self.lemma else "text") for t in text]  # type: ignore
-
-            texts[i] = " ".join(text)
-            lengths.append(len(text))
-            # convert to tensor
-            tokens = Tensor([hash_trick(w, self.n_bins) for w in text])
-            output.append(tokens)
-
-        mask = length_to_mask(torch.IntTensor(lengths)).int()
-        padded_output = pad_sequence(output, padding_value=self.pad_idx).int().t()
-        if return_text:
-            return padded_output, mask, texts  # type: ignore
-        return padded_output, mask
-
-
-class NoopTokenizer(Tokenizer):
-    """This tokenizer should be used for global conditioners such as: artist, genre, key, etc.
-    The difference between this and WhiteSpaceTokenizer is that NoopTokenizer does not split
-    strings, so "Jeff Buckley" will get it's own index. Whereas WhiteSpaceTokenizer will
-    split it to ["Jeff", "Buckley"] and return an index per word.
-
-    For example:
-    ["Queen", "ABBA", "Jeff Buckley"] => [43, 55, 101]
-    ["Metal", "Rock", "Classical"] => [0, 223, 51]
-    """
-    def __init__(self, n_bins: int, pad_idx: int = 0):
-        self.n_bins = n_bins
-        self.pad_idx = pad_idx
-
-    def __call__(self, texts: tp.List[tp.Optional[str]]) -> tp.Tuple[Tensor, Tensor]:
-        output, lengths = [], []
-        for text in texts:
-            # if current sample doesn't have a certain attribute, replace with pad token
-            if text is None:
-                output.append(self.pad_idx)
-                lengths.append(0)
-            else:
-                output.append(hash_trick(text, self.n_bins))
-                lengths.append(1)
-
-        tokens = torch.LongTensor(output).unsqueeze(1)
-        mask = length_to_mask(torch.IntTensor(lengths)).int()
-        return tokens, mask
-
-
-class BaseConditioner(nn.Module):
-    """Base model for all conditioner modules. We allow the output dim to be different
-    than the hidden dim for two reasons: 1) keep our LUTs small when the vocab is large;
-    2) make all condition dims consistent.
-
-    Args:
-        dim (int): Hidden dim of the model (text-encoder/LUT).
-        output_dim (int): Output dim of the conditioner.
-    """
-    def __init__(self, dim, output_dim):
-        super().__init__()
-        self.dim = dim
-        self.output_dim = output_dim
-        self.output_proj = nn.Linear(dim, output_dim)
-
-    def tokenize(self, *args, **kwargs) -> tp.Any:
-        """Should be any part of the processing that will lead to a synchronization
-        point, e.g. BPE tokenization with transfer to the GPU.
-
-        The returned value will be saved and return later when calling forward().
-        """
-        raise NotImplementedError()
-
-    def forward(self, inputs: tp.Any) -> ConditionType:
-        """Gets input that should be used as conditioning (e.g, genre, description or a waveform).
-        Outputs a ConditionType, after the input data was embedded as a dense vector.
-
-        Returns:
-            ConditionType:
-                - A tensor of size [B, T, D] where B is the batch size, T is the length of the
-                  output embedding and D is the dimension of the embedding.
-                - And a mask indicating where the padding tokens.
-        """
-        raise NotImplementedError()
-
-
-class TextConditioner(BaseConditioner):
-    ...
-
-
-class LUTConditioner(TextConditioner):
-    """Lookup table TextConditioner.
-
-    Args:
-        n_bins (int): Number of bins.
-        dim (int): Hidden dim of the model (text-encoder/LUT).
-        output_dim (int): Output dim of the conditioner.
-        tokenizer (str): Name of the tokenizer.
-        pad_idx (int, optional): Index for padding token. Defaults to 0.
-    """
-    def __init__(self, n_bins: int, dim: int, output_dim: int, tokenizer: str, pad_idx: int = 0):
-        super().__init__(dim, output_dim)
-        self.embed = nn.Embedding(n_bins, dim)
-        self.tokenizer: Tokenizer
-        if tokenizer == "whitespace":
-            self.tokenizer = WhiteSpaceTokenizer(n_bins, pad_idx=pad_idx)
-        elif tokenizer == "noop":
-            self.tokenizer = NoopTokenizer(n_bins, pad_idx=pad_idx)
-        else:
-            raise ValueError(f"unrecognized tokenizer `{tokenizer}`.")
-
-    def tokenize(self, x: tp.List[tp.Optional[str]]) -> tp.Tuple[torch.Tensor, torch.Tensor]:
-        device = self.embed.weight.device
-        tokens, mask = self.tokenizer(x)
-        tokens, mask = tokens.to(device), mask.to(device)
-        return tokens, mask
-
-    def forward(self, inputs: tp.Tuple[torch.Tensor, torch.Tensor]) -> ConditionType:
-        tokens, mask = inputs
-        embeds = self.embed(tokens)
-        embeds = self.output_proj(embeds)
-        embeds = (embeds * mask.unsqueeze(-1))
-        return embeds, mask
-
-
-class T5Conditioner(TextConditioner):
-    """T5-based TextConditioner.
-
-    Args:
-        name (str): Name of the T5 model.
-        output_dim (int): Output dim of the conditioner.
-        finetune (bool): Whether to fine-tune T5 at train time.
-        device (str): Device for T5 Conditioner.
-        autocast_dtype (tp.Optional[str], optional): Autocast dtype.
-        word_dropout (float, optional): Word dropout probability.
-        normalize_text (bool, optional): Whether to apply text normalization.
-    """
-    MODELS = ["t5-small", "t5-base", "t5-large", "t5-3b", "t5-11b",
-              "google/flan-t5-small", "google/flan-t5-base", "google/flan-t5-large",
-              "google/flan-t5-xl", "google/flan-t5-xxl"]
-    MODELS_DIMS = {
-        "t5-small": 512,
-        "t5-base": 768,
-        "t5-large": 1024,
-        "t5-3b": 1024,
-        "t5-11b": 1024,
-        "google/flan-t5-small": 512,
-        "google/flan-t5-base": 768,
-        "google/flan-t5-large": 1024,
-        "google/flan-t5-3b": 1024,
-        "google/flan-t5-11b": 1024,
-    }
-
-    def __init__(self, name: str, output_dim: int, finetune: bool, device: str,
-                 autocast_dtype: tp.Optional[str] = 'float32', word_dropout: float = 0.,
-                 normalize_text: bool = False):
-        assert name in self.MODELS, f"unrecognized t5 model name (should in {self.MODELS})"
-        super().__init__(self.MODELS_DIMS[name], output_dim)
-        self.device = device
-        self.name = name
-        self.finetune = finetune
-        self.word_dropout = word_dropout
-
-        if autocast_dtype is None or self.device == 'cpu':
-            self.autocast = TorchAutocast(enabled=False)
-            if self.device != 'cpu':
-                logger.warning("T5 has no autocast, this might lead to NaN")
-        else:
-            dtype = getattr(torch, autocast_dtype)
-            assert isinstance(dtype, torch.dtype)
-            logger.info(f"T5 will be evaluated with autocast as {autocast_dtype}")
-            self.autocast = TorchAutocast(enabled=True, device_type=self.device, dtype=dtype)
-        # Let's disable logging temporarily because T5 will vomit some errors otherwise.
-        # thanks https://gist.github.com/simon-weber/7853144
-        previous_level = logging.root.manager.disable
-        logging.disable(logging.ERROR)
-        with warnings.catch_warnings():
-            warnings.simplefilter("ignore")
-            try:
-                self.t5_tokenizer = T5Tokenizer.from_pretrained(name)
-                t5 = T5EncoderModel.from_pretrained(name).train(mode=finetune)
-            finally:
-                logging.disable(previous_level)
-        if finetune:
-            self.t5 = t5
-        else:
-            # this makes sure that the t5 models is not part
-            # of the saved checkpoint
-            self.__dict__["t5"] = t5.to(device)
-
-        self.normalize_text = normalize_text
-        if normalize_text:
-            self.text_normalizer = WhiteSpaceTokenizer(1, lemma=True, stopwords=True)
-
-    def tokenize(self, x: tp.List[tp.Optional[str]]) -> tp.Dict[str, torch.Tensor]:
-        # if current sample doesn't have a certain attribute, replace with empty string
-        entries: tp.List[str] = [xi if xi is not None else "" for xi in x]
-        if self.normalize_text:
-            _, _, entries = self.text_normalizer(entries, return_text=True)
-        if self.word_dropout > 0. and self.training:
-            new_entries = []
-            for entry in entries:
-                words = [word for word in entry.split(" ") if random.random() >= self.word_dropout]
-                new_entries.append(" ".join(words))
-            entries = new_entries
-
-        empty_idx = torch.LongTensor([i for i, xi in enumerate(entries) if xi == ""])
-
-        inputs = self.t5_tokenizer(entries, return_tensors="pt", padding=True).to(self.device)
-        mask = inputs["attention_mask"]
-        mask[empty_idx, :] = 0  # zero-out index where the input is non-existant
-        return inputs
-
-    def forward(self, inputs: tp.Dict[str, torch.Tensor]) -> ConditionType:
-        mask = inputs["attention_mask"]
-        with torch.set_grad_enabled(self.finetune), self.autocast:
-            embeds = self.t5(**inputs).last_hidden_state
-        embeds = self.output_proj(embeds.to(self.output_proj.weight))
-        embeds = (embeds * mask.unsqueeze(-1))
-        return embeds, mask
-
-
-class WaveformConditioner(BaseConditioner):
-    """Base class for all conditioners that take a waveform as input.
-    Classes that inherit must implement `_get_wav_embedding` that outputs
-    a continuous tensor, and `_downsampling_factor` that returns the down-sampling
-    factor of the embedding model.
-
-    Args:
-        dim (int): The internal representation dimension.
-        output_dim (int): Output dimension.
-        device (tp.Union[torch.device, str]): Device.
-    """
-    def __init__(self, dim: int, output_dim: int, device: tp.Union[torch.device, str]):
-        super().__init__(dim, output_dim)
-        self.device = device
-
-    def tokenize(self, wav_length: WavCondition) -> WavCondition:
-        wav, length, path = wav_length
-        assert length is not None
-        return WavCondition(wav.to(self.device), length.to(self.device), path)
-
-    def _get_wav_embedding(self, wav: Tensor) -> Tensor:
-        """Gets as input a wav and returns a dense vector of conditions."""
-        raise NotImplementedError()
-
-    def _downsampling_factor(self):
-        """Returns the downsampling factor of the embedding model."""
-        raise NotImplementedError()
-
-    def forward(self, inputs: WavCondition) -> ConditionType:
-        """
-        Args:
-            input (WavCondition): Tuple of (waveform, lengths).
-        Returns:
-            ConditionType: Dense vector representing the conditioning along with its' mask.
-        """
-        wav, lengths, path = inputs
-        with torch.no_grad():
-            embeds = self._get_wav_embedding(wav)
-        embeds = embeds.to(self.output_proj.weight)
-        embeds = self.output_proj(embeds)
-
-        if lengths is not None:
-            lengths = lengths / self._downsampling_factor()
-            mask = length_to_mask(lengths, max_len=embeds.shape[1]).int()  # type: ignore
-        else:
-            mask = torch.ones_like(embeds)
-        embeds = (embeds * mask.unsqueeze(2).to(self.device))
-
-        return embeds, mask
-
-
-class ChromaStemConditioner(WaveformConditioner):
-    """Chroma conditioner that uses DEMUCS to first filter out drums and bass. The is followed by
-    the insight the drums and bass often dominate the chroma, leading to the chroma not containing the
-    information about melody.
-
-    Args:
-        output_dim (int): Output dimension for the conditioner.
-        sample_rate (int): Sample rate for the chroma extractor.
-        n_chroma (int): Number of chroma for the chroma extractor.
-        radix2_exp (int): Radix2 exponent for the chroma extractor.
-        duration (float): Duration used during training. This is later used for correct padding
-            in case we are using chroma as prefix.
-        match_len_on_eval (bool, optional): If True then all chromas are padded to the training
-            duration. Defaults to False.
-        eval_wavs (str, optional): Path to a json egg with waveform, this waveforms are used as
-            conditions during eval (for cases where we don't want to leak test conditions like MusicCaps).
-            Defaults to None.
-        n_eval_wavs (int, optional): Limits the number of waveforms used for conditioning. Defaults to 0.
-        device (tp.Union[torch.device, str], optional): Device for the conditioner.
-        **kwargs: Additional parameters for the chroma extractor.
-    """
-    def __init__(self, output_dim: int, sample_rate: int, n_chroma: int, radix2_exp: int,
-                 duration: float, match_len_on_eval: bool = True, eval_wavs: tp.Optional[str] = None,
-                 n_eval_wavs: int = 0, device: tp.Union[torch.device, str] = "cpu", **kwargs):
-        from demucs import pretrained
-        super().__init__(dim=n_chroma, output_dim=output_dim, device=device)
-        self.autocast = TorchAutocast(enabled=device != "cpu", device_type=self.device, dtype=torch.float32)
-        self.sample_rate = sample_rate
-        self.match_len_on_eval = match_len_on_eval
-        self.duration = duration
-        self.__dict__["demucs"] = pretrained.get_model('htdemucs').to(device)
-        self.stem2idx = {'drums': 0, 'bass': 1, 'other': 2, 'vocal': 3}
-        self.stem_idx = torch.LongTensor([self.stem2idx['vocal'], self.stem2idx['other']]).to(device)
-        self.chroma = ChromaExtractor(sample_rate=sample_rate, n_chroma=n_chroma, radix2_exp=radix2_exp,
-                                      device=device, **kwargs)
-        self.chroma_len = self._get_chroma_len()
-
-    def _downsampling_factor(self):
-        return self.chroma.winhop
-
-    def _get_chroma_len(self):
-        """Get length of chroma during training"""
-        dummy_wav = torch.zeros((1, self.sample_rate * self.duration), device=self.device)
-        dummy_chr = self.chroma(dummy_wav)
-        return dummy_chr.shape[1]
-
-    @torch.no_grad()
-    def _get_filtered_wav(self, wav):
-        from demucs.apply import apply_model
-        from demucs.audio import convert_audio
-        with self.autocast:
-            wav = convert_audio(wav, self.sample_rate, self.demucs.samplerate, self.demucs.audio_channels)
-            stems = apply_model(self.demucs, wav, device=self.device)
-            stems = stems[:, self.stem_idx]  # extract stem
-            stems = stems.sum(1)  # merge extracted stems
-            stems = stems.mean(1, keepdim=True)  # mono
-            stems = convert_audio(stems, self.demucs.samplerate, self.sample_rate, 1)
-            return stems
-
-    @torch.no_grad()
-    def _get_wav_embedding(self, wav):
-        # avoid 0-size tensors when we are working with null conds
-        if wav.shape[-1] == 1:
-            return self.chroma(wav)
-        stems = self._get_filtered_wav(wav)
-        chroma = self.chroma(stems)
-
-        if self.match_len_on_eval:
-            b, t, c = chroma.shape
-            if t > self.chroma_len:
-                chroma = chroma[:, :self.chroma_len]
-                logger.debug(f'chroma was truncated! ({t} -> {chroma.shape[1]})')
-            elif t < self.chroma_len:
-                # chroma = F.pad(chroma, (0, 0, 0, self.chroma_len - t))
-                n_repeat = int(math.ceil(self.chroma_len / t))
-                chroma = chroma.repeat(1, n_repeat, 1)
-                chroma = chroma[:, :self.chroma_len]
-                logger.debug(f'chroma was zero-padded! ({t} -> {chroma.shape[1]})')
-        return chroma
-
-
-class ChromaExtractor(nn.Module):
-    """Chroma extraction class, handles chroma extraction and quantization.
-
-    Args:
-        sample_rate (int): Sample rate.
-        n_chroma (int): Number of chroma to consider.
-        radix2_exp (int): Radix2 exponent.
-        nfft (tp.Optional[int], optional): Number of FFT.
-        winlen (tp.Optional[int], optional): Window length.
-        winhop (tp.Optional[int], optional): Window hop size.
-        argmax (bool, optional): Whether to use argmax. Defaults to False.
-        norm (float, optional): Norm for chroma normalization. Defaults to inf.
-        device (tp.Union[torch.device, str], optional): Device to use. Defaults to cpu.
-    """
-    def __init__(self, sample_rate: int, n_chroma: int = 12, radix2_exp: int = 12,
-                 nfft: tp.Optional[int] = None, winlen: tp.Optional[int] = None, winhop: tp.Optional[int] = None,
-                 argmax: bool = False, norm: float = torch.inf, device: tp.Union[torch.device, str] = "cpu"):
-        super().__init__()
-        from librosa import filters
-        self.device = device
-        self.autocast = TorchAutocast(enabled=device != "cpu", device_type=self.device, dtype=torch.float32)
-        self.winlen = winlen or 2 ** radix2_exp
-        self.nfft = nfft or self.winlen
-        self.winhop = winhop or (self.winlen // 4)
-        self.sr = sample_rate
-        self.n_chroma = n_chroma
-        self.norm = norm
-        self.argmax = argmax
-        self.window = torch.hann_window(self.winlen).to(device)
-        self.fbanks = torch.from_numpy(filters.chroma(sr=sample_rate, n_fft=self.nfft, tuning=0,
-                                                      n_chroma=self.n_chroma)).to(device)
-        self.spec = torchaudio.transforms.Spectrogram(n_fft=self.nfft, win_length=self.winlen,
-                                                      hop_length=self.winhop, power=2, center=True,
-                                                      pad=0, normalized=True).to(device)
-
-    def forward(self, wav):
-        with self.autocast:
-            T = wav.shape[-1]
-            # in case we are getting a wav that was dropped out (nullified)
-            # make sure wav length is no less that nfft
-            if T < self.nfft:
-                pad = self.nfft - T
-                r = 0 if pad % 2 == 0 else 1
-                wav = F.pad(wav, (pad // 2, pad // 2 + r), 'constant', 0)
-                assert wav.shape[-1] == self.nfft, f'expected len {self.nfft} but got {wav.shape[-1]}'
-            spec = self.spec(wav).squeeze(1)
-            raw_chroma = torch.einsum("cf,...ft->...ct", self.fbanks, spec)
-            norm_chroma = torch.nn.functional.normalize(raw_chroma, p=self.norm, dim=-2, eps=1e-6)
-            norm_chroma = rearrange(norm_chroma, "b d t -> b t d")
-
-            if self.argmax:
-                idx = norm_chroma.argmax(-1, keepdims=True)
-                norm_chroma[:] = 0
-                norm_chroma.scatter_(dim=-1, index=idx, value=1)
-
-            return norm_chroma
-
-
-def dropout_condition(sample: ConditioningAttributes, condition_type: str, condition: str):
-    """Utility function for nullifying an attribute inside an ConditioningAttributes object.
-    If the condition is of type "wav", then nullify it using "nullify_condition".
-    If the condition is of any other type, set its' value to None.
-    Works in-place.
-    """
-    if condition_type not in ["text", "wav"]:
-        raise ValueError(
-            "dropout_condition got an unexpected condition type!"
-            f" expected 'wav' or 'text' but got '{condition_type}'"
-        )
-
-    if condition not in getattr(sample, condition_type):
-        raise ValueError(
-            "dropout_condition received an unexpected condition!"
-            f" expected wav={sample.wav.keys()} and text={sample.text.keys()}"
-            f"but got '{condition}' of type '{condition_type}'!"
-        )
-
-    if condition_type == "wav":
-        wav, length, path = sample.wav[condition]
-        sample.wav[condition] = nullify_wav(wav)
-    else:
-        sample.text[condition] = None
-
-    return sample
-
-
-class DropoutModule(nn.Module):
-    """Base class for all dropout modules."""
-    def __init__(self, seed: int = 1234):
-        super().__init__()
-        self.rng = torch.Generator()
-        self.rng.manual_seed(seed)
-
-
-class AttributeDropout(DropoutModule):
-    """Applies dropout with a given probability per attribute. This is different from the behavior of
-    ClassifierFreeGuidanceDropout as this allows for attributes to be dropped out separately. For example,
-    "artist" can be dropped while "genre" remains. This is in contrast to ClassifierFreeGuidanceDropout
-    where if "artist" is dropped "genre" must also be dropped.
-
-    Args:
-        p (tp.Dict[str, float]): A dict mapping between attributes and dropout probability. For example:
-            ...
-            "genre": 0.1,
-            "artist": 0.5,
-            "wav": 0.25,
-            ...
-        active_on_eval (bool, optional): Whether the dropout is active at eval. Default to False.
-        seed (int, optional): Random seed.
-    """
-    def __init__(self, p: tp.Dict[str, tp.Dict[str, float]], active_on_eval: bool = False, seed: int = 1234):
-        super().__init__(seed=seed)
-        self.active_on_eval = active_on_eval
-        # construct dict that return the values from p otherwise 0
-        self.p = {}
-        for condition_type, probs in p.items():
-            self.p[condition_type] = defaultdict(lambda: 0, probs)
-
-    def forward(self, samples: tp.List[ConditioningAttributes]) -> tp.List[ConditioningAttributes]:
-        """
-        Args:
-            samples (tp.List[ConditioningAttributes]): List of conditions.
-        Returns:
-            tp.List[ConditioningAttributes]: List of conditions after certain attributes were set to None.
-        """
-        if not self.training and not self.active_on_eval:
-            return samples
-
-        samples = deepcopy(samples)
-
-        for condition_type, ps in self.p.items():  # for condition types [text, wav]
-            for condition, p in ps.items():  # for attributes of each type (e.g., [artist, genre])
-                if torch.rand(1, generator=self.rng).item() < p:
-                    for sample in samples:
-                        dropout_condition(sample, condition_type, condition)
-
-        return samples
-
-    def __repr__(self):
-        return f"AttributeDropout({dict(self.p)})"
-
-
-class ClassifierFreeGuidanceDropout(DropoutModule):
-    """Applies Classifier Free Guidance dropout, meaning all attributes
-    are dropped with the same probability.
-
-    Args:
-        p (float): Probability to apply condition dropout during training.
-        seed (int): Random seed.
-    """
-    def __init__(self, p: float, seed: int = 1234):
-        super().__init__(seed=seed)
-        self.p = p
-
-    def forward(self, samples: tp.List[ConditioningAttributes]) -> tp.List[ConditioningAttributes]:
-        """
-        Args:
-            samples (tp.List[ConditioningAttributes]): List of conditions.
-        Returns:
-            tp.List[ConditioningAttributes]: List of conditions after all attributes were set to None.
-        """
-        if not self.training:
-            return samples
-
-        # decide on which attributes to drop in a batched fashion
-        drop = torch.rand(1, generator=self.rng).item() < self.p
-        if not drop:
-            return samples
-
-        # nullify conditions of all attributes
-        samples = deepcopy(samples)
-
-        for condition_type in ["wav", "text"]:
-            for sample in samples:
-                for condition in sample.attributes[condition_type]:
-                    dropout_condition(sample, condition_type, condition)
-
-        return samples
-
-    def __repr__(self):
-        return f"ClassifierFreeGuidanceDropout(p={self.p})"
-
-
-class ConditioningProvider(nn.Module):
-    """Main class to provide conditions given all the supported conditioners.
-
-    Args:
-        conditioners (dict): Dictionary of conditioners.
-        merge_text_conditions_p (float, optional): Probability to merge all text sources
-            into a single text condition. Defaults to 0.
-        drop_desc_p (float, optional): Probability to drop the original description
-            when merging all text sources into a single text condition. Defaults to 0.
-        device (tp.Union[torch.device, str], optional): Device for conditioners and output condition types.
-    """
-    def __init__(
-        self,
-        conditioners: tp.Dict[str, BaseConditioner],
-        merge_text_conditions_p: float = 0,
-        drop_desc_p: float = 0,
-        device: tp.Union[torch.device, str] = "cpu",
-    ):
-        super().__init__()
-        self.device = device
-        self.merge_text_conditions_p = merge_text_conditions_p
-        self.drop_desc_p = drop_desc_p
-        self.conditioners = nn.ModuleDict(conditioners)
-
-    @property
-    def text_conditions(self):
-        return [k for k, v in self.conditioners.items() if isinstance(v, TextConditioner)]
-
-    @property
-    def wav_conditions(self):
-        return [k for k, v in self.conditioners.items() if isinstance(v, WaveformConditioner)]
-
-    @property
-    def has_wav_condition(self):
-        return len(self.wav_conditions) > 0
-
-    def tokenize(self, inputs: tp.List[ConditioningAttributes]) -> tp.Dict[str, tp.Any]:
-        """Match attributes/wavs with existing conditioners in self, and compute tokenize them accordingly.
-        This should be called before starting any real GPU work to avoid synchronization points.
-        This will return a dict matching conditioner names to their arbitrary tokenized representations.
-
-        Args:
-            inputs (list[ConditioningAttribres]): List of ConditioningAttributes objects containing
-                text and wav conditions.
-        """
-        assert all([type(x) == ConditioningAttributes for x in inputs]), \
-            "got unexpected types input for conditioner! should be tp.List[ConditioningAttributes]" \
-            f" but types were {set([type(x) for x in inputs])}"
-
-        output = {}
-        text = self._collate_text(inputs)
-        wavs = self._collate_wavs(inputs)
-
-        assert set(text.keys() | wavs.keys()).issubset(set(self.conditioners.keys())), \
-            f"got an unexpected attribute! Expected {self.conditioners.keys()}, got {text.keys(), wavs.keys()}"
-
-        for attribute, batch in chain(text.items(), wavs.items()):
-            output[attribute] = self.conditioners[attribute].tokenize(batch)
-        return output
-
-    def forward(self, tokenized: tp.Dict[str, tp.Any]) -> tp.Dict[str, ConditionType]:
-        """Compute pairs of `(embedding, mask)` using the configured conditioners
-        and the tokenized representations. The output is for example:
-
-            {
-                "genre": (torch.Tensor([B, 1, D_genre]), torch.Tensor([B, 1])),
-                "description": (torch.Tensor([B, T_desc, D_desc]), torch.Tensor([B, T_desc])),
-                ...
-            }
-
-        Args:
-            tokenized (dict): Dict of tokenized representations as returned by `tokenize()`.
-        """
-        output = {}
-        for attribute, inputs in tokenized.items():
-            condition, mask = self.conditioners[attribute](inputs)
-            output[attribute] = (condition, mask)
-        return output
-
-    def _collate_text(self, samples: tp.List[ConditioningAttributes]) -> tp.Dict[str, tp.List[tp.Optional[str]]]:
-        """Given a list of ConditioningAttributes objects, compile a dictionary where the keys
-        are the attributes and the values are the aggregated input per attribute.
-        For example:
-        Input:
-        [
-            ConditioningAttributes(text={"genre": "Rock", "description": "A rock song with a guitar solo"}, wav=...),
-            ConditioningAttributes(text={"genre": "Hip-hop", "description": "A hip-hop verse"}, wav=...),
-        ]
-        Output:
-        {
-            "genre": ["Rock", "Hip-hop"],
-            "description": ["A rock song with a guitar solo", "A hip-hop verse"]
-        }
-        """
-        batch_per_attribute: tp.Dict[str, tp.List[tp.Optional[str]]] = defaultdict(list)
-
-        def _merge_conds(cond, merge_text_conditions_p=0, drop_desc_p=0):
-            def is_valid(k, v):
-                k_valid = k in ['key', 'bpm', 'genre', 'moods', 'instrument']
-                v_valid = v is not None and isinstance(v, (int, float, str, list))
-                return k_valid and v_valid
-
-            def process_value(v):
-                if isinstance(v, (int, float, str)):
-                    return v
-                if isinstance(v, list):
-                    return ", ".join(v)
-                else:
-                    RuntimeError(f"unknown type for text value! ({type(v), v})")
-
-            desc = cond.text['description']
-            meta_data = ""
-            if random.uniform(0, 1) < merge_text_conditions_p:
-                meta_pairs = [f'{k}: {process_value(v)}' for k, v in cond.text.items() if is_valid(k, v)]
-                random.shuffle(meta_pairs)
-                meta_data = ". ".join(meta_pairs)
-                desc = desc if not random.uniform(0, 1) < drop_desc_p else None
-
-            if desc is None:
-                desc = meta_data if len(meta_data) > 1 else None
-            else:
-                desc = desc.rstrip('.') + ". " + meta_data
-            cond.text['description'] = desc.strip() if desc else None
-
-        if self.training and self.merge_text_conditions_p:
-            for sample in samples:
-                _merge_conds(sample, self.merge_text_conditions_p, self.drop_desc_p)
-
-        texts = [x.text for x in samples]
-        for text in texts:
-            for condition in self.text_conditions:
-                batch_per_attribute[condition].append(text[condition])
-
-        return batch_per_attribute
-
-    def _collate_wavs(self, samples: tp.List[ConditioningAttributes]):
-        """Generate a dict where the keys are attributes by which we fetch similar wavs,
-        and the values are Tensors of wavs according to said attribtues.
-
-        *Note*: by the time the samples reach this function, each sample should have some waveform
-        inside the "wav" attribute. It should be either:
-        1. A real waveform
-        2. A null waveform due to the sample having no similar waveforms (nullified by the dataset)
-        3. A null waveform due to it being dropped in a dropout module (nullified by dropout)
-
-        Args:
-            samples (tp.List[ConditioningAttributes]): List of ConditioningAttributes samples.
-        Returns:
-            dict: A dicionary mapping an attribute name to wavs.
-        """
-        wavs = defaultdict(list)
-        lens = defaultdict(list)
-        paths = defaultdict(list)
-        out = {}
-
-        for sample in samples:
-            for attribute in self.wav_conditions:
-                wav, length, path = sample.wav[attribute]
-                wavs[attribute].append(wav.flatten())
-                lens[attribute].append(length)
-                paths[attribute].append(path)
-
-        # stack all wavs to a single tensor
-        for attribute in self.wav_conditions:
-            stacked_wav, _ = collate(wavs[attribute], dim=0)
-            out[attribute] = WavCondition(stacked_wav.unsqueeze(1),
-                                          torch.cat(lens['self_wav']), paths[attribute])  # type: ignore
-
-        return out
-
-
-class ConditionFuser(StreamingModule):
-    """Condition fuser handles the logic to combine the different conditions
-    to the actual model input.
-
-    Args:
-        fuse2cond (tp.Dict[str, str]): A dictionary that says how to fuse
-            each condition. For example:
-            {
-                "prepend": ["description"],
-                "sum": ["genre", "bpm"],
-                "cross": ["description"],
-            }
-        cross_attention_pos_emb (bool, optional): Use positional embeddings in cross attention.
-        cross_attention_pos_emb_scale (int): Scale for positional embeddings in cross attention if used.
-    """
-    FUSING_METHODS = ["sum", "prepend", "cross", "input_interpolate"]
-
-    def __init__(self, fuse2cond: tp.Dict[str, tp.List[str]], cross_attention_pos_emb: bool = False,
-                 cross_attention_pos_emb_scale: float = 1.0):
-        super().__init__()
-        assert all(
-            [k in self.FUSING_METHODS for k in fuse2cond.keys()]
-        ), f"got invalid fuse method, allowed methods: {self.FUSING_MEHTODS}"
-        self.cross_attention_pos_emb = cross_attention_pos_emb
-        self.cross_attention_pos_emb_scale = cross_attention_pos_emb_scale
-        self.fuse2cond: tp.Dict[str, tp.List[str]] = fuse2cond
-        self.cond2fuse: tp.Dict[str, str] = {}
-        for fuse_method, conditions in fuse2cond.items():
-            for condition in conditions:
-                self.cond2fuse[condition] = fuse_method
-
-    def forward(
-        self,
-        input: Tensor,
-        conditions: tp.Dict[str, ConditionType]
-    ) -> tp.Tuple[Tensor, tp.Optional[Tensor]]:
-        """Fuse the conditions to the provided model input.
-
-        Args:
-            input (Tensor): Transformer input.
-            conditions (tp.Dict[str, ConditionType]): Dict of conditions.
-        Returns:
-            tp.Tuple[Tensor, Tensor]: The first tensor is the transformer input
-                after the conditions have been fused. The second output tensor is the tensor
-                used for cross-attention or None if no cross attention inputs exist.
-        """
-        B, T, _ = input.shape
-
-        if 'offsets' in self._streaming_state:
-            first_step = False
-            offsets = self._streaming_state['offsets']
-        else:
-            first_step = True
-            offsets = torch.zeros(input.shape[0], dtype=torch.long, device=input.device)
-
-        assert set(conditions.keys()).issubset(set(self.cond2fuse.keys())), \
-            f"given conditions contain unknown attributes for fuser, " \
-            f"expected {self.cond2fuse.keys()}, got {conditions.keys()}"
-        cross_attention_output = None
-        for cond_type, (cond, cond_mask) in conditions.items():
-            op = self.cond2fuse[cond_type]
-            if op == "sum":
-                input += cond
-            elif op == "input_interpolate":
-                cond = rearrange(cond, "b t d -> b d t")
-                cond = F.interpolate(cond, size=input.shape[1])
-                input += rearrange(cond, "b d t -> b t d")
-            elif op == "prepend":
-                if first_step:
-                    input = torch.cat([cond, input], dim=1)
-            elif op == "cross":
-                if cross_attention_output is not None:
-                    cross_attention_output = torch.cat([cross_attention_output, cond], dim=1)
-                else:
-                    cross_attention_output = cond
-            else:
-                raise ValueError(f"unknown op ({op})")
-
-        if self.cross_attention_pos_emb and cross_attention_output is not None:
-            positions = torch.arange(
-                cross_attention_output.shape[1],
-                device=cross_attention_output.device
-            ).view(1, -1, 1)
-            pos_emb = create_sin_embedding(positions, cross_attention_output.shape[-1])
-            cross_attention_output = cross_attention_output + self.cross_attention_pos_emb_scale * pos_emb
-
-        if self._is_streaming:
-            self._streaming_state['offsets'] = offsets + T
-
-        return input, cross_attention_output
diff --git a/spaces/Yuliang/ECON/lib/__init__.py b/spaces/Yuliang/ECON/lib/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/Zahnanni/FinnishLocalLingoLexicon/README.md b/spaces/Zahnanni/FinnishLocalLingoLexicon/README.md
deleted file mode 100644
index 2075f648818c4450cabaed6fd4a3d364e27e0590..0000000000000000000000000000000000000000
--- a/spaces/Zahnanni/FinnishLocalLingoLexicon/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: FinnishLocalLingoLexicon
-emoji: 🌍
-colorFrom: green
-colorTo: green
-sdk: gradio
-sdk_version: 3.50.2
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Zeltoria/anime-voice-generator/text/symbols.py b/spaces/Zeltoria/anime-voice-generator/text/symbols.py
deleted file mode 100644
index edfbd24247be8c757275ce80b9ec27a0ffa808f3..0000000000000000000000000000000000000000
--- a/spaces/Zeltoria/anime-voice-generator/text/symbols.py
+++ /dev/null
@@ -1,39 +0,0 @@
-'''
-Defines the set of symbols used in text input to the model.
-'''
-
-'''# japanese_cleaners
-_pad        = '_'
-_punctuation = ',.!?-'
-_letters = 'AEINOQUabdefghijkmnoprstuvwyzʃʧ↓↑ '
-'''
-
-'''# japanese_cleaners2
-_pad        = '_'
-_punctuation = ',.!?-~…'
-_letters = 'AEINOQUabdefghijkmnoprstuvwyzʃʧʦ↓↑ '
-'''
-
-'''# korean_cleaners
-_pad        = '_'
-_punctuation = ',.!?…~'
-_letters = 'ㄱㄴㄷㄹㅁㅂㅅㅇㅈㅊㅋㅌㅍㅎㄲㄸㅃㅆㅉㅏㅓㅗㅜㅡㅣㅐㅔ '
-'''
-
-'''# chinese_cleaners
-_pad        = '_'
-_punctuation = '，。！？—…'
-_letters = 'ㄅㄆㄇㄈㄉㄊㄋㄌㄍㄎㄏㄐㄑㄒㄓㄔㄕㄖㄗㄘㄙㄚㄛㄜㄝㄞㄟㄠㄡㄢㄣㄤㄥㄦㄧㄨㄩˉˊˇˋ˙ '
-'''
-
-# zh_ja_mixture_cleaners
-_pad        = '_'
-_punctuation = ',.!?-~…'
-_letters = 'AEINOQUabdefghijklmnoprstuvwyzʃʧʦɯɹəɥ⁼ʰ`→↓↑ '
-
-
-# Export all symbols:
-symbols = [_pad] + list(_punctuation) + list(_letters)
-
-# Special symbol ids
-SPACE_ID = symbols.index(" ")
\ No newline at end of file
diff --git a/spaces/abbbbbbbbbbbbbb/AraPoet/app.py b/spaces/abbbbbbbbbbbbbb/AraPoet/app.py
deleted file mode 100644
index af769dff8abd1dbf74587cd2d33de416baf01ade..0000000000000000000000000000000000000000
--- a/spaces/abbbbbbbbbbbbbb/AraPoet/app.py
+++ /dev/null
@@ -1,121 +0,0 @@
-# coding=utf8
-
-import json
-import torch
-import gradio as gr
-import pyarabic.araby as araby
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, AutoConfig
-
-feature_names = [ 
-    "Title",
-    "Meter",
-    "Theme",
-    "Name",
-    "Era",
-    "Country",
-    "Type"
-]
-
-with open("./poet_names.json", 'r', encoding="utf-8") as fin:
-    poet_names = json.load(fin)
-
-def normalize_text(text):
-    text = araby.strip_tatweel(text)
-    return text
-
-def generate_poem(country, era, meter, theme, lang_type, poet, num_lines, num_poems, title):
-
-    num_poems = int(num_poems)
-    prompt = title
-    prompt = normalize_text(prompt)
-
-    features = [prompt, meter, theme, poet, era, country, lang_type]
-
-    prompt = ""
-    for name, feat in zip(feature_names, features):
-        prompt += f"{name}: {feat}; "
-    prompt += f"Length: {num_lines}; Poem:"
-
-    num_beams = 5
-    top_k = 50
-    top_p = 0.9
-    r_penalty = 5.
-
-    input_ids = torch.tensor(tokenizer.encode(prompt)).unsqueeze(0)
-    print(f"> Running: {prompt} | {num_poems} Poems")
-    outputs = model.generate(input_ids=input_ids, 
-        min_length=32, 
-        max_length=256, 
-        do_sample=True,
-        top_k=top_k,
-        top_p=top_p,
-        repetition_penalty=r_penalty,
-        num_beams=num_beams, 
-        num_return_sequences=num_poems,
-        early_stopping=True
-    )
-
-    poems = []
-    print(f"> # of Outputs: {len(outputs)}")
-    for output in outputs:
-        raw = tokenizer.decode(output)
-        raw = raw.replace("<pad>", "").replace("</s>", "")
-        print("="*100)
-        print(raw)
-        print("="*100)
-        poems += ['\n'.join(raw.split("<s>"))]
-
-    return "\n\n".join(poems)   
-    
-meters = ['البسيط', 'التفعيله', 'الحداء', 'الخفيف', 'الدوبيت', 'الرجز', 'الرمل', 'السريع', 'السلسلة', 'الصخري', 'الطويل', 'الكامل', 'الكان كان', 'اللويحاني', 'المتدارك', 'المتقارب', 'المجتث', 'المديد', 'المسحوب', 'المضارع', 'المقتضب', 'المنسرح', 'المواليا', 'الموشح', 'الهجيني', 'الهزج', 'الوافر', 'بحر أحذ الكامل', 'بحر أحذ المديد', 'بحر أحذ الوافر', 'بحر البسيط', 'بحر التفعيله', 'بحر الخبب', 'بحر الخفيف', 'بحر الدوبيت', 'بحر الرجز', 'بحر الرمل', 'بحر السريع', 'بحر السلسلة', 'بحر الطويل', 'بحر القوما', 'بحر الكامل', 'بحر الكامل المقطوع', 'بحر المتدارك', 'بحر المتدارك المنهوك', 'بحر المتقارب', 'بحر المجتث', 'بحر المديد', 'بحر المضارع', 'بحر المقتضب', 'بحر المنسرح', 'بحر المواليا', 'بحر الهزج', 'بحر الوافر', 'بحر تفعيلة الرجز', 'بحر تفعيلة الرمل', 'بحر تفعيلة الكامل', 'بحر تفعيلة المتقارب', 'بحر مجزوء البسيط', 'بحر مجزوء الخفيف', 'بحر مجزوء الدوبيت', 'بحر مجزوء الرجز', 'بحر مجزوء الرمل', 'بحر مجزوء الرمل ', 'بحر مجزوء السريع', 'بحر مجزوء الطويل', 'بحر مجزوء الكامل', 'بحر مجزوء المتدارك', 'بحر مجزوء المتقارب', 'بحر مجزوء المجتث', 'بحر مجزوء المديد', 'بحر مجزوء المنسرح', 'بحر مجزوء المواليا', 'بحر مجزوء الهزج', 'بحر مجزوء الوافر', 'بحر مجزوء موشح', 'بحر مخلع البسيط', 'بحر مخلع الرجز', 'بحر مخلع الرمل', 'بحر مخلع السريع', 'بحر مخلع الكامل', 'بحر مخلع موشح', 'بحر مربع البسيط', 'بحر مربع الرجز', 'بحر مشطور الرجز', 'بحر مشطور السريع', 'بحر مشطور الطويل', 'بحر منهوك البسيط', 'بحر منهوك الرجز', 'بحر منهوك الكامل', 'بحر منهوك المنسرح', 'بحر موشح', 'بسيط', 'زجل', 'شعر التفعيلة', 'شعر حر', 'عامي', 'عدة أبحر', 'عموديه', 'مجزوء الخفيف', 'نثريه', 'None']
-themes = ['قصيدة اعتذار', 'قصيدة الاناشيد', 'قصيدة المعلقات', 'قصيدة حزينه', 'قصيدة دينية', 'قصيدة ذم', 'قصيدة رثاء', 'قصيدة رومنسيه', 'قصيدة سياسية', 'قصيدة شوق', 'قصيدة عامه', 'قصيدة عتاب', 'قصيدة غزل', 'قصيدة فراق', 'قصيدة قصيره', 'قصيدة مدح', 'قصيدة هجاء', 'قصيدة وطنيه', 'None']
-language_types = ['شعبي', 'عامي', 'فصحى', 'فصيح', '-', 'None']
-poet_era = ['العصر الأموي', 'العصر الأندلسي', 'العصر الأيوبي', 'العصر الإسلامي', 'العصر الجاهلي', 'العصر الحديث', 'العصر العباسي', 'العصر العثماني', 'العصر الفاطمي', 'العصر المملوكي', 'المخضرمين', 'المغرب والأندلس', 'عصر بين الدولتين', 'قبل الإسلام', 'None']
-countries = ['الأردن', 'الإمارات', 'البحرين', 'الجزائر', 'السعودية', 'السنغال', 'السودان', 'الصومال', 'العراق', 'الكويت', 'المغرب', 'اليمن', 'تونس', 'سوريا', 'سورية', 'عمان', 'فلسطين', 'قطر', 'لبنان', 'ليبيا', 'مصر', 'موريتانيا', 'None']
-
-tokenizer: AutoTokenizer = AutoTokenizer.from_pretrained("bkhmsi/arapoet-mt5", use_auth_token="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")
-model: AutoModelForSeq2SeqLM = AutoModelForSeq2SeqLM.from_pretrained("bkhmsi/arapoet-mt5", use_auth_token="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")
-model.eval()
-
-title = ""
-with gr.Blocks(title=title) as demo:
-    inputs = []
-
-    gr.Markdown(
-        """
-        # AraPoet: Controlled Arabic Poetry Generation
-        
-        The model hosted here is a finetuned version of [mT5-large](https://huggingface.co/google/mt5-large) (∼ 1.2B parameters) on the largest repository of Arabic poems, the [ashaar](https://huggingface.co/datasets/arbml/ashaar) dataset. 
-        The model can be conditioned on a set of attributes to control the style of the generated poem. 
-        Namely: the poet name, country, era, meter, theme, language type, title and the length of the poem.
-        You can start by clicking on one of the examples below or try your own input.
-        """
-    )
-
-    with gr.Row():
-        inputs += [gr.Dropdown(countries, label="Country", value="مصر")]
-        inputs += [gr.Dropdown(poet_era, label="Era", value="العصر الحديث")]
-    with gr.Row():
-        inputs += [gr.Dropdown(meters, label="Meter", value="بحر السريع")]
-        inputs += [gr.Dropdown(themes, label="Theme", value="قصيدة رومنسيه")]
-    with gr.Row():
-        inputs += [gr.Dropdown(language_types, label="Language Type", value="فصحى")]
-        inputs += [gr.Dropdown(poet_names, label="Poet", value="أحمد شوقي")]
-    with gr.Row():
-        inputs += [gr.Slider(2, 20, value=6, step=1, label="Number of Lines")]
-        inputs += [gr.Slider(1, 4, value=1, step=1, label="Number of Samples")]
-    with gr.Row():
-        inputs += [gr.Textbox(label="Title", value="إثن عنان القلب واسلم به")]
-
-    btn = gr.Button("Generate")
-    examples = gr.Examples(examples="./examples", inputs=inputs)
-    btn.click(generate_poem, inputs, gr.TextArea(label="Generation"))
-
-
-    gr.Markdown(
-        """
-        Checkout our [AraPoet Preprint](https://github.com/BKHMSI/BKHMSI.github.io/blob/master/archive/resources/AraPoet.pdf) for more details about the model.
-        """
-    )
-
-demo.launch()
\ No newline at end of file
diff --git a/spaces/abdvl/datahub_qa_bot/docs/advanced/partial-update.md b/spaces/abdvl/datahub_qa_bot/docs/advanced/partial-update.md
deleted file mode 100644
index 3daca3054881bad8af7ec3c41e2174dde0614f35..0000000000000000000000000000000000000000
--- a/spaces/abdvl/datahub_qa_bot/docs/advanced/partial-update.md
+++ /dev/null
@@ -1,3 +0,0 @@
-# Supporting Partial Aspect Update
-
-WIP
diff --git a/spaces/abdvl/datahub_qa_bot/docs/how/restore-indices.md b/spaces/abdvl/datahub_qa_bot/docs/how/restore-indices.md
deleted file mode 100644
index 4b7fd77314ef727e32c34057740c26ecacf970be..0000000000000000000000000000000000000000
--- a/spaces/abdvl/datahub_qa_bot/docs/how/restore-indices.md
+++ /dev/null
@@ -1,55 +0,0 @@
-# Restoring Search and Graph Indices from Local Database
-
-If search or graph services go down or you have made changes to them that require reindexing, you can restore them from
-the aspects stored in the local database.
-
-When a new version of the aspect gets ingested, GMS initiates an MAE event for the aspect which is consumed to update
-the search and graph indices. As such, we can fetch the latest version of each aspect in the local database and produce
-MAE events corresponding to the aspects to restore the search and graph indices.
-
-## Quickstart
-
-If you're using the quickstart images, you can use the `datahub` cli to restore indices.
-
-```
-datahub docker quickstart --restore-indices
-```
-See [this section](../quickstart.md#restoring-only-the-index-use-with-care) for more information. 
-
-## Docker-compose
-
-If you are on a custom docker-compose deployment, run the following command (you need to checkout [the source repository](https://github.com/datahub-project/datahub)) from the root of the repo to send MAE for each aspect in the Local DB.
-
-```
-./docker/datahub-upgrade/datahub-upgrade.sh -u RestoreIndices
-```
-
-If you need to clear the search and graph indices before restoring, add `-a clean` to the end of the command.
-
-Refer to this [doc](../../docker/datahub-upgrade/README.md#environment-variables) on how to set environment variables
-for your environment.
-
-## Kubernetes
-
-Run `kubectl get cronjobs` to see if the restoration job template has been deployed. If you see results like below, you
-are good to go.
-
-```
-NAME                                          SCHEDULE    SUSPEND   ACTIVE   LAST SCHEDULE   AGE
-datahub-datahub-cleanup-job-template          * * * * *   True      0        <none>          2d3h
-datahub-datahub-restore-indices-job-template  * * * * *   True      0        <none>          2d3h
-```
-
-If not, deploy latest helm charts to use this functionality.
-
-Once restore indices job template has been deployed, run the following command to start a job that restores indices.
-
-```
-kubectl create job --from=cronjob/datahub-datahub-restore-indices-job-template datahub-restore-indices-adhoc
-```
-
-Once the job completes, your indices will have been restored. 
-
-## Through API
-
-See [Restore Indices API](../api/restli/restore-indices.md).
\ No newline at end of file
diff --git a/spaces/abhishek/sketch-to-image/annotator/uniformer_base/mmseg/models/decode_heads/da_head.py b/spaces/abhishek/sketch-to-image/annotator/uniformer_base/mmseg/models/decode_heads/da_head.py
deleted file mode 100644
index efeb4bbb551eea8b2844c22349a067c0e212102d..0000000000000000000000000000000000000000
--- a/spaces/abhishek/sketch-to-image/annotator/uniformer_base/mmseg/models/decode_heads/da_head.py
+++ /dev/null
@@ -1,190 +0,0 @@
-'''
- * Copyright (c) 2023 Salesforce, Inc.
- * All rights reserved.
- * SPDX-License-Identifier: Apache License 2.0
- * For full license text, see LICENSE.txt file in the repo root or http://www.apache.org/licenses/
- * By Can Qin
- * Modified from ControlNet repo: https://github.com/lllyasviel/ControlNet
- * Copyright (c) 2023 Lvmin Zhang and Maneesh Agrawala
- * Modified from MMCV repo: From https://github.com/open-mmlab/mmcv
- * Copyright (c) OpenMMLab. All rights reserved.
-'''
-
-import torch
-import torch.nn.functional as F
-from annotator.uniformer.mmcv.cnn import ConvModule, Scale
-from torch import nn
-
-from annotator.uniformer.mmseg.core import add_prefix
-from ..builder import HEADS
-from ..utils import SelfAttentionBlock as _SelfAttentionBlock
-from .decode_head import BaseDecodeHead
-
-
-class PAM(_SelfAttentionBlock):
-    """Position Attention Module (PAM)
-
-    Args:
-        in_channels (int): Input channels of key/query feature.
-        channels (int): Output channels of key/query transform.
-    """
-
-    def __init__(self, in_channels, channels):
-        super(PAM, self).__init__(
-            key_in_channels=in_channels,
-            query_in_channels=in_channels,
-            channels=channels,
-            out_channels=in_channels,
-            share_key_query=False,
-            query_downsample=None,
-            key_downsample=None,
-            key_query_num_convs=1,
-            key_query_norm=False,
-            value_out_num_convs=1,
-            value_out_norm=False,
-            matmul_norm=False,
-            with_out=False,
-            conv_cfg=None,
-            norm_cfg=None,
-            act_cfg=None)
-
-        self.gamma = Scale(0)
-
-    def forward(self, x):
-        """Forward function."""
-        out = super(PAM, self).forward(x, x)
-
-        out = self.gamma(out) + x
-        return out
-
-
-class CAM(nn.Module):
-    """Channel Attention Module (CAM)"""
-
-    def __init__(self):
-        super(CAM, self).__init__()
-        self.gamma = Scale(0)
-
-    def forward(self, x):
-        """Forward function."""
-        batch_size, channels, height, width = x.size()
-        proj_query = x.view(batch_size, channels, -1)
-        proj_key = x.view(batch_size, channels, -1).permute(0, 2, 1)
-        energy = torch.bmm(proj_query, proj_key)
-        energy_new = torch.max(
-            energy, -1, keepdim=True)[0].expand_as(energy) - energy
-        attention = F.softmax(energy_new, dim=-1)
-        proj_value = x.view(batch_size, channels, -1)
-
-        out = torch.bmm(attention, proj_value)
-        out = out.view(batch_size, channels, height, width)
-
-        out = self.gamma(out) + x
-        return out
-
-
-@HEADS.register_module()
-class DAHead(BaseDecodeHead):
-    """Dual Attention Network for Scene Segmentation.
-
-    This head is the implementation of `DANet
-    <https://arxiv.org/abs/1809.02983>`_.
-
-    Args:
-        pam_channels (int): The channels of Position Attention Module(PAM).
-    """
-
-    def __init__(self, pam_channels, **kwargs):
-        super(DAHead, self).__init__(**kwargs)
-        self.pam_channels = pam_channels
-        self.pam_in_conv = ConvModule(
-            self.in_channels,
-            self.channels,
-            3,
-            padding=1,
-            conv_cfg=self.conv_cfg,
-            norm_cfg=self.norm_cfg,
-            act_cfg=self.act_cfg)
-        self.pam = PAM(self.channels, pam_channels)
-        self.pam_out_conv = ConvModule(
-            self.channels,
-            self.channels,
-            3,
-            padding=1,
-            conv_cfg=self.conv_cfg,
-            norm_cfg=self.norm_cfg,
-            act_cfg=self.act_cfg)
-        self.pam_conv_seg = nn.Conv2d(
-            self.channels, self.num_classes, kernel_size=1)
-
-        self.cam_in_conv = ConvModule(
-            self.in_channels,
-            self.channels,
-            3,
-            padding=1,
-            conv_cfg=self.conv_cfg,
-            norm_cfg=self.norm_cfg,
-            act_cfg=self.act_cfg)
-        self.cam = CAM()
-        self.cam_out_conv = ConvModule(
-            self.channels,
-            self.channels,
-            3,
-            padding=1,
-            conv_cfg=self.conv_cfg,
-            norm_cfg=self.norm_cfg,
-            act_cfg=self.act_cfg)
-        self.cam_conv_seg = nn.Conv2d(
-            self.channels, self.num_classes, kernel_size=1)
-
-    def pam_cls_seg(self, feat):
-        """PAM feature classification."""
-        if self.dropout is not None:
-            feat = self.dropout(feat)
-        output = self.pam_conv_seg(feat)
-        return output
-
-    def cam_cls_seg(self, feat):
-        """CAM feature classification."""
-        if self.dropout is not None:
-            feat = self.dropout(feat)
-        output = self.cam_conv_seg(feat)
-        return output
-
-    def forward(self, inputs):
-        """Forward function."""
-        x = self._transform_inputs(inputs)
-        pam_feat = self.pam_in_conv(x)
-        pam_feat = self.pam(pam_feat)
-        pam_feat = self.pam_out_conv(pam_feat)
-        pam_out = self.pam_cls_seg(pam_feat)
-
-        cam_feat = self.cam_in_conv(x)
-        cam_feat = self.cam(cam_feat)
-        cam_feat = self.cam_out_conv(cam_feat)
-        cam_out = self.cam_cls_seg(cam_feat)
-
-        feat_sum = pam_feat + cam_feat
-        pam_cam_out = self.cls_seg(feat_sum)
-
-        return pam_cam_out, pam_out, cam_out
-
-    def forward_test(self, inputs, img_metas, test_cfg):
-        """Forward function for testing, only ``pam_cam`` is used."""
-        return self.forward(inputs)[0]
-
-    def losses(self, seg_logit, seg_label):
-        """Compute ``pam_cam``, ``pam``, ``cam`` loss."""
-        pam_cam_seg_logit, pam_seg_logit, cam_seg_logit = seg_logit
-        loss = dict()
-        loss.update(
-            add_prefix(
-                super(DAHead, self).losses(pam_cam_seg_logit, seg_label),
-                'pam_cam'))
-        loss.update(
-            add_prefix(
-                super(DAHead, self).losses(pam_seg_logit, seg_label), 'pam'))
-        loss.update(
-            add_prefix(
-                super(DAHead, self).losses(cam_seg_logit, seg_label), 'cam'))
-        return loss
diff --git a/spaces/abrar-lohia/text-2-character-anim/pyrender/tests/__init__.py b/spaces/abrar-lohia/text-2-character-anim/pyrender/tests/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/active-learning/labeler/README.md b/spaces/active-learning/labeler/README.md
deleted file mode 100644
index b78718f588b4ae3b0b67102ab74197b599c796b1..0000000000000000000000000000000000000000
--- a/spaces/active-learning/labeler/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Labeler
-emoji: 👀
-colorFrom: red
-colorTo: green
-sdk: gradio
-sdk_version: 3.17.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/adirik/stylemc-demo/torch_utils/ops/conv2d_gradfix.py b/spaces/adirik/stylemc-demo/torch_utils/ops/conv2d_gradfix.py
deleted file mode 100644
index f4ffe7eb48086ed98eff3d5a83f5b361ff4a7b4d..0000000000000000000000000000000000000000
--- a/spaces/adirik/stylemc-demo/torch_utils/ops/conv2d_gradfix.py
+++ /dev/null
@@ -1,163 +0,0 @@
-# Copyright (c) 2021, NVIDIA CORPORATION.  All rights reserved.
-#
-# NVIDIA CORPORATION and its licensors retain all intellectual property
-# and proprietary rights in and to this software, related documentation
-# and any modifications thereto.  Any use, reproduction, disclosure or
-# distribution of this software and related documentation without an express
-# license agreement from NVIDIA CORPORATION is strictly prohibited.
-
-"""Custom replacement for `torch.nn.functional.conv2d` that supports
-arbitrarily high order gradients with zero performance penalty."""
-
-import warnings
-import contextlib
-import torch
-
-# pylint: disable=redefined-builtin
-# pylint: disable=arguments-differ
-# pylint: disable=protected-access
-
-#----------------------------------------------------------------------------
-
-enabled = False                     # Enable the custom op by setting this to true.
-weight_gradients_disabled = False   # Forcefully disable computation of gradients with respect to the weights.
-
-@contextlib.contextmanager
-def no_weight_gradients():
-    global weight_gradients_disabled
-    old = weight_gradients_disabled
-    weight_gradients_disabled = True
-    yield
-    weight_gradients_disabled = old
-
-def conv2d(input, weight, bias=None, stride=1, padding=0, dilation=1, groups=1):
-    if _should_use_custom_op(input):
-        return _conv2d_gradfix(transpose=False, weight_shape=weight.shape, stride=stride, padding=padding, output_padding=0, dilation=dilation, groups=groups).apply(input, weight, bias)
-    return torch.nn.functional.conv2d(input=input, weight=weight, bias=bias, stride=stride, padding=padding, dilation=dilation, groups=groups)
-
-def conv_transpose2d(input, weight, bias=None, stride=1, padding=0, output_padding=0, groups=1, dilation=1):
-    if _should_use_custom_op(input):
-        return _conv2d_gradfix(transpose=True, weight_shape=weight.shape, stride=stride, padding=padding, output_padding=output_padding, groups=groups, dilation=dilation).apply(input, weight, bias)
-    return torch.nn.functional.conv_transpose2d(input=input, weight=weight, bias=bias, stride=stride, padding=padding, output_padding=output_padding, groups=groups, dilation=dilation)
-
-
-def _should_use_custom_op(input):
-    assert isinstance(input, torch.Tensor)
-    if (not enabled) or (not torch.backends.cudnn.enabled):
-        return False
-    if input.device.type != 'cuda':
-        return False
-    if any(torch.__version__.startswith(x) for x in ['1.7.', '1.8.', '1.9']):
-        return True
-    return False
-
-def _tuple_of_ints(xs, ndim):
-    xs = tuple(xs) if isinstance(xs, (tuple, list)) else (xs,) * ndim
-    assert len(xs) == ndim
-    assert all(isinstance(x, int) for x in xs)
-    return xs
-
-
-_conv2d_gradfix_cache = dict()
-
-def _conv2d_gradfix(transpose, weight_shape, stride, padding, output_padding, dilation, groups):
-    # Parse arguments.
-    ndim = 2
-    weight_shape = tuple(weight_shape)
-    stride = _tuple_of_ints(stride, ndim)
-    padding = _tuple_of_ints(padding, ndim)
-    output_padding = _tuple_of_ints(output_padding, ndim)
-    dilation = _tuple_of_ints(dilation, ndim)
-
-    # Lookup from cache.
-    key = (transpose, weight_shape, stride, padding, output_padding, dilation, groups)
-    if key in _conv2d_gradfix_cache:
-        return _conv2d_gradfix_cache[key]
-
-    # Validate arguments.
-    assert groups >= 1
-    assert len(weight_shape) == ndim + 2
-    assert all(stride[i] >= 1 for i in range(ndim))
-    assert all(padding[i] >= 0 for i in range(ndim))
-    assert all(dilation[i] >= 0 for i in range(ndim))
-    if not transpose:
-        assert all(output_padding[i] == 0 for i in range(ndim))
-    else: # transpose
-        assert all(0 <= output_padding[i] < max(stride[i], dilation[i]) for i in range(ndim))
-
-    # Helpers.
-    common_kwargs = dict(stride=stride, padding=padding, dilation=dilation, groups=groups)
-    def calc_output_padding(input_shape, output_shape):
-        if transpose:
-            return [0, 0]
-        return [
-            input_shape[i + 2]
-            - (output_shape[i + 2] - 1) * stride[i]
-            - (1 - 2 * padding[i])
-            - dilation[i] * (weight_shape[i + 2] - 1)
-            for i in range(ndim)
-        ]
-
-    # Forward & backward.
-    class Conv2d(torch.autograd.Function):
-        @staticmethod
-        def forward(ctx, input, weight, bias):
-            assert weight.shape == weight_shape
-            if not transpose:
-                output = torch.nn.functional.conv2d(input=input, weight=weight, bias=bias, **common_kwargs)
-            else: # transpose
-                output = torch.nn.functional.conv_transpose2d(input=input, weight=weight, bias=bias, output_padding=output_padding, **common_kwargs)
-            ctx.save_for_backward(input, weight)
-            return output
-
-        @staticmethod
-        def backward(ctx, grad_output):
-            input, weight = ctx.saved_tensors
-            grad_input = None
-            grad_weight = None
-            grad_bias = None
-
-            if ctx.needs_input_grad[0]:
-                p = calc_output_padding(input_shape=input.shape, output_shape=grad_output.shape)
-                grad_input = _conv2d_gradfix(transpose=(not transpose), weight_shape=weight_shape, output_padding=p, **common_kwargs).apply(grad_output, weight, None)
-                assert grad_input.shape == input.shape
-
-            if ctx.needs_input_grad[1] and not weight_gradients_disabled:
-                grad_weight = Conv2dGradWeight.apply(grad_output, input)
-                assert grad_weight.shape == weight_shape
-
-            if ctx.needs_input_grad[2]:
-                grad_bias = grad_output.sum([0, 2, 3])
-
-            return grad_input, grad_weight, grad_bias
-
-    # Gradient with respect to the weights.
-    class Conv2dGradWeight(torch.autograd.Function):
-        @staticmethod
-        def forward(ctx, grad_output, input):
-            op = torch._C._jit_get_operation('aten::cudnn_convolution_backward_weight' if not transpose else 'aten::cudnn_convolution_transpose_backward_weight')
-            flags = [torch.backends.cudnn.benchmark, torch.backends.cudnn.deterministic, torch.backends.cudnn.allow_tf32]
-            grad_weight = op(weight_shape, grad_output, input, padding, stride, dilation, groups, *flags)
-            assert grad_weight.shape == weight_shape
-            ctx.save_for_backward(grad_output, input)
-            return grad_weight
-
-        @staticmethod
-        def backward(ctx, grad2_grad_weight):
-            grad_output, input = ctx.saved_tensors
-            grad2_grad_output = None
-            grad2_input = None
-
-            if ctx.needs_input_grad[0]:
-                grad2_grad_output = Conv2d.apply(input, grad2_grad_weight, None)
-                assert grad2_grad_output.shape == grad_output.shape
-
-            if ctx.needs_input_grad[1]:
-                p = calc_output_padding(input_shape=input.shape, output_shape=grad_output.shape)
-                grad2_input = _conv2d_gradfix(transpose=(not transpose), weight_shape=weight_shape, output_padding=p, **common_kwargs).apply(grad_output, grad2_grad_weight, None)
-                assert grad2_input.shape == input.shape
-
-            return grad2_grad_output, grad2_input
-
-    _conv2d_gradfix_cache[key] = Conv2d
-    return Conv2d
diff --git a/spaces/akhaliq/Pyxelate/app.py b/spaces/akhaliq/Pyxelate/app.py
deleted file mode 100644
index 3b90b052333dd14b473d228849686d1b016808a1..0000000000000000000000000000000000000000
--- a/spaces/akhaliq/Pyxelate/app.py
+++ /dev/null
@@ -1,32 +0,0 @@
-import gradio as gr
-from skimage import io
-from pyxelate import Pyx, Pal
-
-def pixel(image,downsample,palette,depth,upscale):
-    image = io.imread(image.name)  
-    downsample_by = int(downsample)  # new image will be 1/14th of the original in size
-    palette = int(palette)  # find 7 colors
-    # 1) Instantiate Pyx transformer
-    pyx = Pyx(factor=downsample_by, palette=palette,depth=int(depth),upscale = int(upscale))
-    # 2) fit an image, allow Pyxelate to learn the color palette
-    pyx.fit(image)
-    # 3) transform image to pixel art using the learned color palette
-    new_image = pyx.transform(image)
-    # save new image with 'skimage.io.imsave()'
-    io.imsave("pixel.png", new_image)
-    return "pixel.png"
-    
-title = "Pyxelate"
-description = "Gradio demo for Pyxelate: converts images to pixel art. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."
-article = "<p style='text-align: center'><a href='https://github.com/sedthh/pyxelate' target='_blank'>Github Repo</a></p>"
-
-gr.Interface(
-    pixel, 
-    [gr.inputs.Image(type="file", label="Input", shape=(512,512)),gr.inputs.Number(default=14, label="downsample by"),gr.inputs.Number(default=7, label="palette"),gr.inputs.Number(default=1, label="depth"),gr.inputs.Number(default=14, label="upscale")
-], 
-    gr.outputs.Image(type="file", label="Output"),
-    title=title,
-    description=description,
-    article=article,
-    examples=[['mona.jpeg',14,7,1,14]]
-    ).launch(enable_queue=True)
\ No newline at end of file
diff --git a/spaces/akhaliq/SummerTime/model/third_party/HMNet/ThirdParty/ROUGE/ROUGE-1.5.5/XML/DOM/DOMImplementation.pod b/spaces/akhaliq/SummerTime/model/third_party/HMNet/ThirdParty/ROUGE/ROUGE-1.5.5/XML/DOM/DOMImplementation.pod
deleted file mode 100644
index cb5e34df9ccb114665e7578fbbbefc8c4cb4b054..0000000000000000000000000000000000000000
--- a/spaces/akhaliq/SummerTime/model/third_party/HMNet/ThirdParty/ROUGE/ROUGE-1.5.5/XML/DOM/DOMImplementation.pod
+++ /dev/null
@@ -1,24 +0,0 @@
-=head1 NAME
-
-XML::DOM::DOMImplementation - Information about XML::DOM implementation
-
-=head1 DESCRIPTION
-
-The DOMImplementation interface provides a number of methods for
-performing operations that are independent of any particular instance
-of the document object model.
-
-The DOM Level 1 does not specify a way of creating a document instance,
-and hence document creation is an operation specific to an
-implementation. Future Levels of the DOM specification are expected to
-provide methods for creating documents directly.
-
-=head2 METHODS
-
-=over 4
-
-=item hasFeature (feature, version)
-
-Returns 1 if and only if feature equals "XML" and version equals "1.0".
-
-=back
diff --git a/spaces/akhaliq/brain_segmentation/app.py b/spaces/akhaliq/brain_segmentation/app.py
deleted file mode 100644
index 5a6f7fe47e6a514237994b45e5bae08462f9f43a..0000000000000000000000000000000000000000
--- a/spaces/akhaliq/brain_segmentation/app.py
+++ /dev/null
@@ -1,67 +0,0 @@
-from pathlib import Path
-import torch
-import torch.nn as nn
-import torchio as tio
-import numpy as np
-from tqdm.notebook import tqdm
-import gradio as gr
-from matplotlib import pyplot as plt
-
-torch.set_grad_enabled(False);
-# Download an example image
-import urllib
-url, filename = ("https://github.com/mateuszbuda/brain-segmentation-pytorch/raw/master/assets/TCGA_CS_4944.png", "TCGA_CS_4944.png")
-try: urllib.URLopener().retrieve(url, filename)
-except: urllib.request.urlretrieve(url, filename)
-def inference(img):
-    path = img.name
-    slices = [tio.ScalarImage(path).data]
-    tensor = torch.cat(slices, dim=-1)
-    guessed_affine = np.diag([-1, -1, 9, 1])
-    subject = tio.Subject(mri=tio.ScalarImage(tensor=tensor, affine=guessed_affine))
-    subject_preprocessed = tio.ZNormalization()(subject)
-    subject_preprocessed.plot()
-    subject_preprocessed.mri
-    patch_overlap = 0
-    patch_size = 256, 256, 1
-    grid_sampler = tio.inference.GridSampler(
-        subject_preprocessed,
-        patch_size,
-        patch_overlap,
-    )
-    patch_loader = torch.utils.data.DataLoader(grid_sampler, batch_size=8)
-    aggregator = tio.inference.GridAggregator(grid_sampler)
-    model = torch.hub.load(
-        'mateuszbuda/brain-segmentation-pytorch',
-        'unet',
-        in_channels=3,
-        out_channels=1,
-        init_features=32,
-        pretrained=True,
-    )
-    for patches_batch in tqdm(patch_loader):
-        input_tensor = patches_batch['mri'][tio.DATA][..., 0]
-        locations = patches_batch[tio.LOCATION]
-        probs = model(input_tensor)[..., np.newaxis]
-        aggregator.add_batch(probs, locations)
-    output_tensor = aggregator.get_output_tensor()
-    output_subject = tio.Subject(prediction=tio.ScalarImage(tensor=output_tensor, affine=guessed_affine))
-    images = subject_preprocessed.mri.tensor.detach().numpy().reshape((3, 256, 256))
-    mask = output_subject.prediction.tensor.detach().numpy().reshape((256, 256))
-    images = np.moveaxis(np.moveaxis(images, 0, 2), 0, 1)
-    mask = np.moveaxis(mask, 0, 1)
-
-    f, ax = plt.subplots(1, 2)
-    ax[0].set_axis_off()
-    ax[1].set_axis_off()
-    ax[0].imshow(images)
-    ax[1].imshow(mask, cmap='gray')
-    return f
-
-title = "U-NET FOR BRAIN MRI"
-description = "Gradio demo for u-net for brain mri, U-Net with batch normalization for biomedical image segmentation with pretrained weights for abnormality segmentation in brain MRI. To use it, simply add your image, or click one of the examples to load them. Read more at the links below."
-article = "<p style='text-align: center'><a href='https://mateuszbuda.github.io/2017/12/01/brainseg.html'>Segmentation of brain tumor in magnetic resonance images</a> | <a href='https://github.com/mateuszbuda/brain-segmentation-pytorch'>Github Repo</a></p>"
-examples = [
-            ['TCGA_CS_4944.png']
-]
-gr.Interface(inference, gr.inputs.Image(label="input image", type='file'), gr.outputs.Image(type='plot'), description=description, article=article, title=title, examples=examples, analytics_enabled=False).launch()
\ No newline at end of file
diff --git a/spaces/akhaliq/mae/app.py b/spaces/akhaliq/mae/app.py
deleted file mode 100644
index c5fd95c372bf4c16315586092e33d904a3bb22ff..0000000000000000000000000000000000000000
--- a/spaces/akhaliq/mae/app.py
+++ /dev/null
@@ -1,115 +0,0 @@
-import sys
-import os
-import requests
-
-import torch
-import numpy as np
-
-import matplotlib.pyplot as plt
-from PIL import Image
-import gradio as gr
-
-
-os.system("git clone https://github.com/facebookresearch/mae.git")
-sys.path.append('./mae')
-
-import models_mae
-
-# define the utils
-
-imagenet_mean = np.array([0.485, 0.456, 0.406])
-imagenet_std = np.array([0.229, 0.224, 0.225])
-
-def show_image(image, title=''):
-    # image is [H, W, 3]
-    assert image.shape[2] == 3
-    plt.imshow(torch.clip((image * imagenet_std + imagenet_mean) * 255, 0, 255).int())
-    plt.title(title, fontsize=16)
-    plt.axis('off')
-    return
-
-def prepare_model(chkpt_dir, arch='mae_vit_large_patch16'):
-    # build model
-    model = getattr(models_mae, arch)()
-    # load model
-    checkpoint = torch.load(chkpt_dir, map_location='cpu')
-    msg = model.load_state_dict(checkpoint['model'], strict=False)
-    print(msg)
-    return model
-
-def run_one_image(img, model):
-    x = torch.tensor(img)
-
-    # make it a batch-like
-    x = x.unsqueeze(dim=0)
-    x = torch.einsum('nhwc->nchw', x)
-
-    # run MAE
-    loss, y, mask = model(x.float(), mask_ratio=0.75)
-    y = model.unpatchify(y)
-    y = torch.einsum('nchw->nhwc', y).detach().cpu()
-
-    # visualize the mask
-    mask = mask.detach()
-    mask = mask.unsqueeze(-1).repeat(1, 1, model.patch_embed.patch_size[0]**2 *3)  # (N, H*W, p*p*3)
-    mask = model.unpatchify(mask)  # 1 is removing, 0 is keeping
-    mask = torch.einsum('nchw->nhwc', mask).detach().cpu()
-    
-    x = torch.einsum('nchw->nhwc', x)
-
-    # masked image
-    im_masked = x * (1 - mask)
-
-    # MAE reconstruction pasted with visible patches
-    im_paste = x * (1 - mask) + y * mask
-
-    # make the plt figure larger
-    plt.rcParams['figure.figsize'] = [24, 6]
-
-    plt.subplot(1, 4, 1)
-    show_image(x[0], "original")
-
-    plt.subplot(1, 4, 2)
-    show_image(im_masked[0], "masked")
-
-    plt.subplot(1, 4, 3)
-    show_image(y[0], "reconstruction")
-
-    plt.subplot(1, 4, 4)
-    show_image(im_paste[0], "reconstruction + visible")
-    
-    plt.savefig("test.png",bbox_inches='tight')
-    
-
-# download checkpoint if not exist
-os.system("wget -nc https://dl.fbaipublicfiles.com/mae/visualize/mae_visualize_vit_large.pth")
-
-chkpt_dir = 'mae_visualize_vit_large.pth'
-model_mae = prepare_model(chkpt_dir, 'mae_vit_large_patch16')
-print('Model loaded.')
-
-    
-def inference(img):    
-  img = img.resize((224, 224))
-  img = np.array(img) / 255.
-  
-  assert img.shape == (224, 224, 3)
-  
-  # normalize by ImageNet mean and std
-  img = img - imagenet_mean
-  img = img / imagenet_std
-  
-  
-  torch.manual_seed(2)
-
-  run_one_image(img, model_mae)
-  return "test.png"
-  
-
-title = "MAE"
-description = "Gradio Demo for Masked Autoencoders Are Scalable Vision Learners. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."
-
-article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2111.06377' target='_blank'>Masked Autoencoders Are Scalable Vision Learners</a>| <a href='https://github.com/facebookresearch/mae' target='_blank'>Github Repo</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_mae' alt='visitor badge'></center>"
-
-examples=[['147738734-196fd92f-9260-48d5-ba7e-bf103d29364d.jpeg']]
-gr.Interface(inference, [gr.inputs.Image(type="pil")], gr.outputs.Image(type="file"),title=title,description=description,article=article,allow_flagging="never",allow_screenshot=False,examples=examples).launch(enable_queue=True)
\ No newline at end of file
diff --git a/spaces/alexray/btc_predictor/venv/lib/python3.10/site-packages/pip/_internal/cli/req_command.py b/spaces/alexray/btc_predictor/venv/lib/python3.10/site-packages/pip/_internal/cli/req_command.py
deleted file mode 100644
index 5d4d1f0f45b0d9fe646ce4350b3ec8a865511e72..0000000000000000000000000000000000000000
--- a/spaces/alexray/btc_predictor/venv/lib/python3.10/site-packages/pip/_internal/cli/req_command.py
+++ /dev/null
@@ -1,506 +0,0 @@
-"""Contains the Command base classes that depend on PipSession.
-
-The classes in this module are in a separate module so the commands not
-needing download / PackageFinder capability don't unnecessarily import the
-PackageFinder machinery and all its vendored dependencies, etc.
-"""
-
-import logging
-import os
-import sys
-from functools import partial
-from optparse import Values
-from typing import Any, List, Optional, Tuple
-
-from pip._internal.cache import WheelCache
-from pip._internal.cli import cmdoptions
-from pip._internal.cli.base_command import Command
-from pip._internal.cli.command_context import CommandContextMixIn
-from pip._internal.exceptions import CommandError, PreviousBuildDirError
-from pip._internal.index.collector import LinkCollector
-from pip._internal.index.package_finder import PackageFinder
-from pip._internal.models.selection_prefs import SelectionPreferences
-from pip._internal.models.target_python import TargetPython
-from pip._internal.network.session import PipSession
-from pip._internal.operations.prepare import RequirementPreparer
-from pip._internal.req.constructors import (
-    install_req_from_editable,
-    install_req_from_line,
-    install_req_from_parsed_requirement,
-    install_req_from_req_string,
-)
-from pip._internal.req.req_file import parse_requirements
-from pip._internal.req.req_install import InstallRequirement
-from pip._internal.req.req_tracker import RequirementTracker
-from pip._internal.resolution.base import BaseResolver
-from pip._internal.self_outdated_check import pip_self_version_check
-from pip._internal.utils.deprecation import deprecated
-from pip._internal.utils.temp_dir import (
-    TempDirectory,
-    TempDirectoryTypeRegistry,
-    tempdir_kinds,
-)
-from pip._internal.utils.virtualenv import running_under_virtualenv
-
-logger = logging.getLogger(__name__)
-
-
-class SessionCommandMixin(CommandContextMixIn):
-
-    """
-    A class mixin for command classes needing _build_session().
-    """
-
-    def __init__(self) -> None:
-        super().__init__()
-        self._session: Optional[PipSession] = None
-
-    @classmethod
-    def _get_index_urls(cls, options: Values) -> Optional[List[str]]:
-        """Return a list of index urls from user-provided options."""
-        index_urls = []
-        if not getattr(options, "no_index", False):
-            url = getattr(options, "index_url", None)
-            if url:
-                index_urls.append(url)
-        urls = getattr(options, "extra_index_urls", None)
-        if urls:
-            index_urls.extend(urls)
-        # Return None rather than an empty list
-        return index_urls or None
-
-    def get_default_session(self, options: Values) -> PipSession:
-        """Get a default-managed session."""
-        if self._session is None:
-            self._session = self.enter_context(self._build_session(options))
-            # there's no type annotation on requests.Session, so it's
-            # automatically ContextManager[Any] and self._session becomes Any,
-            # then https://github.com/python/mypy/issues/7696 kicks in
-            assert self._session is not None
-        return self._session
-
-    def _build_session(
-        self,
-        options: Values,
-        retries: Optional[int] = None,
-        timeout: Optional[int] = None,
-    ) -> PipSession:
-        assert not options.cache_dir or os.path.isabs(options.cache_dir)
-        session = PipSession(
-            cache=(
-                os.path.join(options.cache_dir, "http") if options.cache_dir else None
-            ),
-            retries=retries if retries is not None else options.retries,
-            trusted_hosts=options.trusted_hosts,
-            index_urls=self._get_index_urls(options),
-        )
-
-        # Handle custom ca-bundles from the user
-        if options.cert:
-            session.verify = options.cert
-
-        # Handle SSL client certificate
-        if options.client_cert:
-            session.cert = options.client_cert
-
-        # Handle timeouts
-        if options.timeout or timeout:
-            session.timeout = timeout if timeout is not None else options.timeout
-
-        # Handle configured proxies
-        if options.proxy:
-            session.proxies = {
-                "http": options.proxy,
-                "https": options.proxy,
-            }
-
-        # Determine if we can prompt the user for authentication or not
-        session.auth.prompting = not options.no_input
-
-        return session
-
-
-class IndexGroupCommand(Command, SessionCommandMixin):
-
-    """
-    Abstract base class for commands with the index_group options.
-
-    This also corresponds to the commands that permit the pip version check.
-    """
-
-    def handle_pip_version_check(self, options: Values) -> None:
-        """
-        Do the pip version check if not disabled.
-
-        This overrides the default behavior of not doing the check.
-        """
-        # Make sure the index_group options are present.
-        assert hasattr(options, "no_index")
-
-        if options.disable_pip_version_check or options.no_index:
-            return
-
-        # Otherwise, check if we're using the latest version of pip available.
-        session = self._build_session(
-            options, retries=0, timeout=min(5, options.timeout)
-        )
-        with session:
-            pip_self_version_check(session, options)
-
-
-KEEPABLE_TEMPDIR_TYPES = [
-    tempdir_kinds.BUILD_ENV,
-    tempdir_kinds.EPHEM_WHEEL_CACHE,
-    tempdir_kinds.REQ_BUILD,
-]
-
-
-def warn_if_run_as_root() -> None:
-    """Output a warning for sudo users on Unix.
-
-    In a virtual environment, sudo pip still writes to virtualenv.
-    On Windows, users may run pip as Administrator without issues.
-    This warning only applies to Unix root users outside of virtualenv.
-    """
-    if running_under_virtualenv():
-        return
-    if not hasattr(os, "getuid"):
-        return
-    # On Windows, there are no "system managed" Python packages. Installing as
-    # Administrator via pip is the correct way of updating system environments.
-    #
-    # We choose sys.platform over utils.compat.WINDOWS here to enable Mypy platform
-    # checks: https://mypy.readthedocs.io/en/stable/common_issues.html
-    if sys.platform == "win32" or sys.platform == "cygwin":
-        return
-
-    if os.getuid() != 0:
-        return
-
-    logger.warning(
-        "Running pip as the 'root' user can result in broken permissions and "
-        "conflicting behaviour with the system package manager. "
-        "It is recommended to use a virtual environment instead: "
-        "https://pip.pypa.io/warnings/venv"
-    )
-
-
-def with_cleanup(func: Any) -> Any:
-    """Decorator for common logic related to managing temporary
-    directories.
-    """
-
-    def configure_tempdir_registry(registry: TempDirectoryTypeRegistry) -> None:
-        for t in KEEPABLE_TEMPDIR_TYPES:
-            registry.set_delete(t, False)
-
-    def wrapper(
-        self: RequirementCommand, options: Values, args: List[Any]
-    ) -> Optional[int]:
-        assert self.tempdir_registry is not None
-        if options.no_clean:
-            configure_tempdir_registry(self.tempdir_registry)
-
-        try:
-            return func(self, options, args)
-        except PreviousBuildDirError:
-            # This kind of conflict can occur when the user passes an explicit
-            # build directory with a pre-existing folder. In that case we do
-            # not want to accidentally remove it.
-            configure_tempdir_registry(self.tempdir_registry)
-            raise
-
-    return wrapper
-
-
-class RequirementCommand(IndexGroupCommand):
-    def __init__(self, *args: Any, **kw: Any) -> None:
-        super().__init__(*args, **kw)
-
-        self.cmd_opts.add_option(cmdoptions.no_clean())
-
-    @staticmethod
-    def determine_resolver_variant(options: Values) -> str:
-        """Determines which resolver should be used, based on the given options."""
-        if "legacy-resolver" in options.deprecated_features_enabled:
-            return "legacy"
-
-        return "2020-resolver"
-
-    @staticmethod
-    def determine_build_failure_suppression(options: Values) -> bool:
-        """Determines whether build failures should be suppressed and backtracked on."""
-        if "backtrack-on-build-failures" not in options.deprecated_features_enabled:
-            return False
-
-        if "legacy-resolver" in options.deprecated_features_enabled:
-            raise CommandError("Cannot backtrack with legacy resolver.")
-
-        deprecated(
-            reason=(
-                "Backtracking on build failures can mask issues related to how "
-                "a package generates metadata or builds a wheel. This flag will "
-                "be removed in pip 22.2."
-            ),
-            gone_in=None,
-            replacement=(
-                "avoiding known-bad versions by explicitly telling pip to ignore them "
-                "(either directly as requirements, or via a constraints file)"
-            ),
-            feature_flag=None,
-            issue=10655,
-        )
-        return True
-
-    @classmethod
-    def make_requirement_preparer(
-        cls,
-        temp_build_dir: TempDirectory,
-        options: Values,
-        req_tracker: RequirementTracker,
-        session: PipSession,
-        finder: PackageFinder,
-        use_user_site: bool,
-        download_dir: Optional[str] = None,
-        verbosity: int = 0,
-    ) -> RequirementPreparer:
-        """
-        Create a RequirementPreparer instance for the given parameters.
-        """
-        temp_build_dir_path = temp_build_dir.path
-        assert temp_build_dir_path is not None
-
-        resolver_variant = cls.determine_resolver_variant(options)
-        if resolver_variant == "2020-resolver":
-            lazy_wheel = "fast-deps" in options.features_enabled
-            if lazy_wheel:
-                logger.warning(
-                    "pip is using lazily downloaded wheels using HTTP "
-                    "range requests to obtain dependency information. "
-                    "This experimental feature is enabled through "
-                    "--use-feature=fast-deps and it is not ready for "
-                    "production."
-                )
-        else:
-            lazy_wheel = False
-            if "fast-deps" in options.features_enabled:
-                logger.warning(
-                    "fast-deps has no effect when used with the legacy resolver."
-                )
-
-        in_tree_build = "out-of-tree-build" not in options.deprecated_features_enabled
-        if "in-tree-build" in options.features_enabled:
-            deprecated(
-                reason="In-tree builds are now the default.",
-                replacement="to remove the --use-feature=in-tree-build flag",
-                gone_in="22.1",
-            )
-        if "out-of-tree-build" in options.deprecated_features_enabled:
-            deprecated(
-                reason="Out-of-tree builds are deprecated.",
-                replacement=None,
-                gone_in="22.1",
-            )
-
-        if options.progress_bar not in {"on", "off"}:
-            deprecated(
-                reason="Custom progress bar styles are deprecated",
-                replacement="to use the default progress bar style.",
-                gone_in="22.1",
-            )
-
-        return RequirementPreparer(
-            build_dir=temp_build_dir_path,
-            src_dir=options.src_dir,
-            download_dir=download_dir,
-            build_isolation=options.build_isolation,
-            req_tracker=req_tracker,
-            session=session,
-            progress_bar=options.progress_bar,
-            finder=finder,
-            require_hashes=options.require_hashes,
-            use_user_site=use_user_site,
-            lazy_wheel=lazy_wheel,
-            verbosity=verbosity,
-            in_tree_build=in_tree_build,
-        )
-
-    @classmethod
-    def make_resolver(
-        cls,
-        preparer: RequirementPreparer,
-        finder: PackageFinder,
-        options: Values,
-        wheel_cache: Optional[WheelCache] = None,
-        use_user_site: bool = False,
-        ignore_installed: bool = True,
-        ignore_requires_python: bool = False,
-        force_reinstall: bool = False,
-        upgrade_strategy: str = "to-satisfy-only",
-        use_pep517: Optional[bool] = None,
-        py_version_info: Optional[Tuple[int, ...]] = None,
-    ) -> BaseResolver:
-        """
-        Create a Resolver instance for the given parameters.
-        """
-        make_install_req = partial(
-            install_req_from_req_string,
-            isolated=options.isolated_mode,
-            use_pep517=use_pep517,
-        )
-        suppress_build_failures = cls.determine_build_failure_suppression(options)
-        resolver_variant = cls.determine_resolver_variant(options)
-        # The long import name and duplicated invocation is needed to convince
-        # Mypy into correctly typechecking. Otherwise it would complain the
-        # "Resolver" class being redefined.
-        if resolver_variant == "2020-resolver":
-            import pip._internal.resolution.resolvelib.resolver
-
-            return pip._internal.resolution.resolvelib.resolver.Resolver(
-                preparer=preparer,
-                finder=finder,
-                wheel_cache=wheel_cache,
-                make_install_req=make_install_req,
-                use_user_site=use_user_site,
-                ignore_dependencies=options.ignore_dependencies,
-                ignore_installed=ignore_installed,
-                ignore_requires_python=ignore_requires_python,
-                force_reinstall=force_reinstall,
-                upgrade_strategy=upgrade_strategy,
-                py_version_info=py_version_info,
-                suppress_build_failures=suppress_build_failures,
-            )
-        import pip._internal.resolution.legacy.resolver
-
-        return pip._internal.resolution.legacy.resolver.Resolver(
-            preparer=preparer,
-            finder=finder,
-            wheel_cache=wheel_cache,
-            make_install_req=make_install_req,
-            use_user_site=use_user_site,
-            ignore_dependencies=options.ignore_dependencies,
-            ignore_installed=ignore_installed,
-            ignore_requires_python=ignore_requires_python,
-            force_reinstall=force_reinstall,
-            upgrade_strategy=upgrade_strategy,
-            py_version_info=py_version_info,
-        )
-
-    def get_requirements(
-        self,
-        args: List[str],
-        options: Values,
-        finder: PackageFinder,
-        session: PipSession,
-    ) -> List[InstallRequirement]:
-        """
-        Parse command-line arguments into the corresponding requirements.
-        """
-        requirements: List[InstallRequirement] = []
-        for filename in options.constraints:
-            for parsed_req in parse_requirements(
-                filename,
-                constraint=True,
-                finder=finder,
-                options=options,
-                session=session,
-            ):
-                req_to_add = install_req_from_parsed_requirement(
-                    parsed_req,
-                    isolated=options.isolated_mode,
-                    user_supplied=False,
-                )
-                requirements.append(req_to_add)
-
-        for req in args:
-            req_to_add = install_req_from_line(
-                req,
-                None,
-                isolated=options.isolated_mode,
-                use_pep517=options.use_pep517,
-                user_supplied=True,
-            )
-            requirements.append(req_to_add)
-
-        for req in options.editables:
-            req_to_add = install_req_from_editable(
-                req,
-                user_supplied=True,
-                isolated=options.isolated_mode,
-                use_pep517=options.use_pep517,
-            )
-            requirements.append(req_to_add)
-
-        # NOTE: options.require_hashes may be set if --require-hashes is True
-        for filename in options.requirements:
-            for parsed_req in parse_requirements(
-                filename, finder=finder, options=options, session=session
-            ):
-                req_to_add = install_req_from_parsed_requirement(
-                    parsed_req,
-                    isolated=options.isolated_mode,
-                    use_pep517=options.use_pep517,
-                    user_supplied=True,
-                )
-                requirements.append(req_to_add)
-
-        # If any requirement has hash options, enable hash checking.
-        if any(req.has_hash_options for req in requirements):
-            options.require_hashes = True
-
-        if not (args or options.editables or options.requirements):
-            opts = {"name": self.name}
-            if options.find_links:
-                raise CommandError(
-                    "You must give at least one requirement to {name} "
-                    '(maybe you meant "pip {name} {links}"?)'.format(
-                        **dict(opts, links=" ".join(options.find_links))
-                    )
-                )
-            else:
-                raise CommandError(
-                    "You must give at least one requirement to {name} "
-                    '(see "pip help {name}")'.format(**opts)
-                )
-
-        return requirements
-
-    @staticmethod
-    def trace_basic_info(finder: PackageFinder) -> None:
-        """
-        Trace basic information about the provided objects.
-        """
-        # Display where finder is looking for packages
-        search_scope = finder.search_scope
-        locations = search_scope.get_formatted_locations()
-        if locations:
-            logger.info(locations)
-
-    def _build_package_finder(
-        self,
-        options: Values,
-        session: PipSession,
-        target_python: Optional[TargetPython] = None,
-        ignore_requires_python: Optional[bool] = None,
-    ) -> PackageFinder:
-        """
-        Create a package finder appropriate to this requirement command.
-
-        :param ignore_requires_python: Whether to ignore incompatible
-            "Requires-Python" values in links. Defaults to False.
-        """
-        link_collector = LinkCollector.create(session, options=options)
-        selection_prefs = SelectionPreferences(
-            allow_yanked=True,
-            format_control=options.format_control,
-            allow_all_prereleases=options.pre,
-            prefer_binary=options.prefer_binary,
-            ignore_requires_python=ignore_requires_python,
-        )
-
-        return PackageFinder.create(
-            link_collector=link_collector,
-            selection_prefs=selection_prefs,
-            target_python=target_python,
-            use_deprecated_html5lib="html5lib" in options.deprecated_features_enabled,
-        )
diff --git a/spaces/alexray/btc_predictor/venv/lib/python3.10/site-packages/pip/_vendor/chardet/hebrewprober.py b/spaces/alexray/btc_predictor/venv/lib/python3.10/site-packages/pip/_vendor/chardet/hebrewprober.py
deleted file mode 100644
index b0e1bf49268203d1f9d14cbe73753d95dc66c8a4..0000000000000000000000000000000000000000
--- a/spaces/alexray/btc_predictor/venv/lib/python3.10/site-packages/pip/_vendor/chardet/hebrewprober.py
+++ /dev/null
@@ -1,292 +0,0 @@
-######################## BEGIN LICENSE BLOCK ########################
-# The Original Code is Mozilla Universal charset detector code.
-#
-# The Initial Developer of the Original Code is
-#          Shy Shalom
-# Portions created by the Initial Developer are Copyright (C) 2005
-# the Initial Developer. All Rights Reserved.
-#
-# Contributor(s):
-#   Mark Pilgrim - port to Python
-#
-# This library is free software; you can redistribute it and/or
-# modify it under the terms of the GNU Lesser General Public
-# License as published by the Free Software Foundation; either
-# version 2.1 of the License, or (at your option) any later version.
-#
-# This library is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
-# Lesser General Public License for more details.
-#
-# You should have received a copy of the GNU Lesser General Public
-# License along with this library; if not, write to the Free Software
-# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
-# 02110-1301  USA
-######################### END LICENSE BLOCK #########################
-
-from .charsetprober import CharSetProber
-from .enums import ProbingState
-
-# This prober doesn't actually recognize a language or a charset.
-# It is a helper prober for the use of the Hebrew model probers
-
-### General ideas of the Hebrew charset recognition ###
-#
-# Four main charsets exist in Hebrew:
-# "ISO-8859-8" - Visual Hebrew
-# "windows-1255" - Logical Hebrew
-# "ISO-8859-8-I" - Logical Hebrew
-# "x-mac-hebrew" - ?? Logical Hebrew ??
-#
-# Both "ISO" charsets use a completely identical set of code points, whereas
-# "windows-1255" and "x-mac-hebrew" are two different proper supersets of
-# these code points. windows-1255 defines additional characters in the range
-# 0x80-0x9F as some misc punctuation marks as well as some Hebrew-specific
-# diacritics and additional 'Yiddish' ligature letters in the range 0xc0-0xd6.
-# x-mac-hebrew defines similar additional code points but with a different
-# mapping.
-#
-# As far as an average Hebrew text with no diacritics is concerned, all four
-# charsets are identical with respect to code points. Meaning that for the
-# main Hebrew alphabet, all four map the same values to all 27 Hebrew letters
-# (including final letters).
-#
-# The dominant difference between these charsets is their directionality.
-# "Visual" directionality means that the text is ordered as if the renderer is
-# not aware of a BIDI rendering algorithm. The renderer sees the text and
-# draws it from left to right. The text itself when ordered naturally is read
-# backwards. A buffer of Visual Hebrew generally looks like so:
-# "[last word of first line spelled backwards] [whole line ordered backwards
-# and spelled backwards] [first word of first line spelled backwards]
-# [end of line] [last word of second line] ... etc' "
-# adding punctuation marks, numbers and English text to visual text is
-# naturally also "visual" and from left to right.
-#
-# "Logical" directionality means the text is ordered "naturally" according to
-# the order it is read. It is the responsibility of the renderer to display
-# the text from right to left. A BIDI algorithm is used to place general
-# punctuation marks, numbers and English text in the text.
-#
-# Texts in x-mac-hebrew are almost impossible to find on the Internet. From
-# what little evidence I could find, it seems that its general directionality
-# is Logical.
-#
-# To sum up all of the above, the Hebrew probing mechanism knows about two
-# charsets:
-# Visual Hebrew - "ISO-8859-8" - backwards text - Words and sentences are
-#    backwards while line order is natural. For charset recognition purposes
-#    the line order is unimportant (In fact, for this implementation, even
-#    word order is unimportant).
-# Logical Hebrew - "windows-1255" - normal, naturally ordered text.
-#
-# "ISO-8859-8-I" is a subset of windows-1255 and doesn't need to be
-#    specifically identified.
-# "x-mac-hebrew" is also identified as windows-1255. A text in x-mac-hebrew
-#    that contain special punctuation marks or diacritics is displayed with
-#    some unconverted characters showing as question marks. This problem might
-#    be corrected using another model prober for x-mac-hebrew. Due to the fact
-#    that x-mac-hebrew texts are so rare, writing another model prober isn't
-#    worth the effort and performance hit.
-#
-#### The Prober ####
-#
-# The prober is divided between two SBCharSetProbers and a HebrewProber,
-# all of which are managed, created, fed data, inquired and deleted by the
-# SBCSGroupProber. The two SBCharSetProbers identify that the text is in
-# fact some kind of Hebrew, Logical or Visual. The final decision about which
-# one is it is made by the HebrewProber by combining final-letter scores
-# with the scores of the two SBCharSetProbers to produce a final answer.
-#
-# The SBCSGroupProber is responsible for stripping the original text of HTML
-# tags, English characters, numbers, low-ASCII punctuation characters, spaces
-# and new lines. It reduces any sequence of such characters to a single space.
-# The buffer fed to each prober in the SBCS group prober is pure text in
-# high-ASCII.
-# The two SBCharSetProbers (model probers) share the same language model:
-# Win1255Model.
-# The first SBCharSetProber uses the model normally as any other
-# SBCharSetProber does, to recognize windows-1255, upon which this model was
-# built. The second SBCharSetProber is told to make the pair-of-letter
-# lookup in the language model backwards. This in practice exactly simulates
-# a visual Hebrew model using the windows-1255 logical Hebrew model.
-#
-# The HebrewProber is not using any language model. All it does is look for
-# final-letter evidence suggesting the text is either logical Hebrew or visual
-# Hebrew. Disjointed from the model probers, the results of the HebrewProber
-# alone are meaningless. HebrewProber always returns 0.00 as confidence
-# since it never identifies a charset by itself. Instead, the pointer to the
-# HebrewProber is passed to the model probers as a helper "Name Prober".
-# When the Group prober receives a positive identification from any prober,
-# it asks for the name of the charset identified. If the prober queried is a
-# Hebrew model prober, the model prober forwards the call to the
-# HebrewProber to make the final decision. In the HebrewProber, the
-# decision is made according to the final-letters scores maintained and Both
-# model probers scores. The answer is returned in the form of the name of the
-# charset identified, either "windows-1255" or "ISO-8859-8".
-
-class HebrewProber(CharSetProber):
-    # windows-1255 / ISO-8859-8 code points of interest
-    FINAL_KAF = 0xea
-    NORMAL_KAF = 0xeb
-    FINAL_MEM = 0xed
-    NORMAL_MEM = 0xee
-    FINAL_NUN = 0xef
-    NORMAL_NUN = 0xf0
-    FINAL_PE = 0xf3
-    NORMAL_PE = 0xf4
-    FINAL_TSADI = 0xf5
-    NORMAL_TSADI = 0xf6
-
-    # Minimum Visual vs Logical final letter score difference.
-    # If the difference is below this, don't rely solely on the final letter score
-    # distance.
-    MIN_FINAL_CHAR_DISTANCE = 5
-
-    # Minimum Visual vs Logical model score difference.
-    # If the difference is below this, don't rely at all on the model score
-    # distance.
-    MIN_MODEL_DISTANCE = 0.01
-
-    VISUAL_HEBREW_NAME = "ISO-8859-8"
-    LOGICAL_HEBREW_NAME = "windows-1255"
-
-    def __init__(self):
-        super(HebrewProber, self).__init__()
-        self._final_char_logical_score = None
-        self._final_char_visual_score = None
-        self._prev = None
-        self._before_prev = None
-        self._logical_prober = None
-        self._visual_prober = None
-        self.reset()
-
-    def reset(self):
-        self._final_char_logical_score = 0
-        self._final_char_visual_score = 0
-        # The two last characters seen in the previous buffer,
-        # mPrev and mBeforePrev are initialized to space in order to simulate
-        # a word delimiter at the beginning of the data
-        self._prev = ' '
-        self._before_prev = ' '
-        # These probers are owned by the group prober.
-
-    def set_model_probers(self, logicalProber, visualProber):
-        self._logical_prober = logicalProber
-        self._visual_prober = visualProber
-
-    def is_final(self, c):
-        return c in [self.FINAL_KAF, self.FINAL_MEM, self.FINAL_NUN,
-                     self.FINAL_PE, self.FINAL_TSADI]
-
-    def is_non_final(self, c):
-        # The normal Tsadi is not a good Non-Final letter due to words like
-        # 'lechotet' (to chat) containing an apostrophe after the tsadi. This
-        # apostrophe is converted to a space in FilterWithoutEnglishLetters
-        # causing the Non-Final tsadi to appear at an end of a word even
-        # though this is not the case in the original text.
-        # The letters Pe and Kaf rarely display a related behavior of not being
-        # a good Non-Final letter. Words like 'Pop', 'Winamp' and 'Mubarak'
-        # for example legally end with a Non-Final Pe or Kaf. However, the
-        # benefit of these letters as Non-Final letters outweighs the damage
-        # since these words are quite rare.
-        return c in [self.NORMAL_KAF, self.NORMAL_MEM,
-                     self.NORMAL_NUN, self.NORMAL_PE]
-
-    def feed(self, byte_str):
-        # Final letter analysis for logical-visual decision.
-        # Look for evidence that the received buffer is either logical Hebrew
-        # or visual Hebrew.
-        # The following cases are checked:
-        # 1) A word longer than 1 letter, ending with a final letter. This is
-        #    an indication that the text is laid out "naturally" since the
-        #    final letter really appears at the end. +1 for logical score.
-        # 2) A word longer than 1 letter, ending with a Non-Final letter. In
-        #    normal Hebrew, words ending with Kaf, Mem, Nun, Pe or Tsadi,
-        #    should not end with the Non-Final form of that letter. Exceptions
-        #    to this rule are mentioned above in isNonFinal(). This is an
-        #    indication that the text is laid out backwards. +1 for visual
-        #    score
-        # 3) A word longer than 1 letter, starting with a final letter. Final
-        #    letters should not appear at the beginning of a word. This is an
-        #    indication that the text is laid out backwards. +1 for visual
-        #    score.
-        #
-        # The visual score and logical score are accumulated throughout the
-        # text and are finally checked against each other in GetCharSetName().
-        # No checking for final letters in the middle of words is done since
-        # that case is not an indication for either Logical or Visual text.
-        #
-        # We automatically filter out all 7-bit characters (replace them with
-        # spaces) so the word boundary detection works properly. [MAP]
-
-        if self.state == ProbingState.NOT_ME:
-            # Both model probers say it's not them. No reason to continue.
-            return ProbingState.NOT_ME
-
-        byte_str = self.filter_high_byte_only(byte_str)
-
-        for cur in byte_str:
-            if cur == ' ':
-                # We stand on a space - a word just ended
-                if self._before_prev != ' ':
-                    # next-to-last char was not a space so self._prev is not a
-                    # 1 letter word
-                    if self.is_final(self._prev):
-                        # case (1) [-2:not space][-1:final letter][cur:space]
-                        self._final_char_logical_score += 1
-                    elif self.is_non_final(self._prev):
-                        # case (2) [-2:not space][-1:Non-Final letter][
-                        #  cur:space]
-                        self._final_char_visual_score += 1
-            else:
-                # Not standing on a space
-                if ((self._before_prev == ' ') and
-                        (self.is_final(self._prev)) and (cur != ' ')):
-                    # case (3) [-2:space][-1:final letter][cur:not space]
-                    self._final_char_visual_score += 1
-            self._before_prev = self._prev
-            self._prev = cur
-
-        # Forever detecting, till the end or until both model probers return
-        # ProbingState.NOT_ME (handled above)
-        return ProbingState.DETECTING
-
-    @property
-    def charset_name(self):
-        # Make the decision: is it Logical or Visual?
-        # If the final letter score distance is dominant enough, rely on it.
-        finalsub = self._final_char_logical_score - self._final_char_visual_score
-        if finalsub >= self.MIN_FINAL_CHAR_DISTANCE:
-            return self.LOGICAL_HEBREW_NAME
-        if finalsub <= -self.MIN_FINAL_CHAR_DISTANCE:
-            return self.VISUAL_HEBREW_NAME
-
-        # It's not dominant enough, try to rely on the model scores instead.
-        modelsub = (self._logical_prober.get_confidence()
-                    - self._visual_prober.get_confidence())
-        if modelsub > self.MIN_MODEL_DISTANCE:
-            return self.LOGICAL_HEBREW_NAME
-        if modelsub < -self.MIN_MODEL_DISTANCE:
-            return self.VISUAL_HEBREW_NAME
-
-        # Still no good, back to final letter distance, maybe it'll save the
-        # day.
-        if finalsub < 0.0:
-            return self.VISUAL_HEBREW_NAME
-
-        # (finalsub > 0 - Logical) or (don't know what to do) default to
-        # Logical.
-        return self.LOGICAL_HEBREW_NAME
-
-    @property
-    def language(self):
-        return 'Hebrew'
-
-    @property
-    def state(self):
-        # Remain active as long as any of the model probers are active.
-        if (self._logical_prober.state == ProbingState.NOT_ME) and \
-           (self._visual_prober.state == ProbingState.NOT_ME):
-            return ProbingState.NOT_ME
-        return ProbingState.DETECTING
diff --git a/spaces/alfabill/stable-diffusion-inpainting-2/clipseg/evaluation_utils.py b/spaces/alfabill/stable-diffusion-inpainting-2/clipseg/evaluation_utils.py
deleted file mode 100644
index 8f913a98ad910db386838463908141fb9dcef442..0000000000000000000000000000000000000000
--- a/spaces/alfabill/stable-diffusion-inpainting-2/clipseg/evaluation_utils.py
+++ /dev/null
@@ -1,292 +0,0 @@
-from torch.functional import Tensor
-from general_utils import load_model
-from torch.utils.data import DataLoader
-import torch
-import numpy as np
-
-def denorm(img):
-
-    np_input = False
-    if isinstance(img, np.ndarray):
-        img = torch.from_numpy(img)
-        np_input = True
-
-    mean = torch.Tensor([0.485, 0.456, 0.406])
-    std = torch.Tensor([0.229, 0.224, 0.225])
-
-    img_denorm = (img*std[:,None,None]) + mean[:,None,None]
-
-    if np_input:
-        img_denorm = np.clip(img_denorm.numpy(), 0, 1)
-    else:
-        img_denorm = torch.clamp(img_denorm, 0, 1)
-
-    return img_denorm
-
-
-def norm(img):
-    mean = torch.Tensor([0.485, 0.456, 0.406])
-    std = torch.Tensor([0.229, 0.224, 0.225])
-    return (img - mean[:,None,None]) / std[:,None,None]
-
-
-def fast_iou_curve(p, g):
-    
-    g = g[p.sort().indices]
-    p = torch.sigmoid(p.sort().values)
-    
-    scores = []
-    vals = np.linspace(0, 1, 50)
-
-    for q in vals:
-
-        n = int(len(g) * q)
-
-        valid = torch.where(p > q)[0]
-        if len(valid) > 0:
-            n = int(valid[0])
-        else:
-            n = len(g)
-
-        fn = g[:n].sum()
-        tn = n - fn
-        tp = g[n:].sum()
-        fp = len(g) - n - tp
-
-        iou = tp / (tp + fn + fp)
-
-        precision = tp / (tp + fp)
-        recall = tp / (tp + fn)
-
-        scores += [iou]
-        
-    return vals, scores
-
-
-def fast_rp_curve(p, g):
-    
-    g = g[p.sort().indices]
-    p = torch.sigmoid(p.sort().values)
-    
-    precisions, recalls = [], []
-    vals = np.linspace(p.min(), p.max(), 250)
-
-    for q in p[::100000]:
-
-        n = int(len(g) * q)
-
-        valid = torch.where(p > q)[0]
-        if len(valid) > 0:
-            n = int(valid[0])
-        else:
-            n = len(g)
-
-        fn = g[:n].sum()
-        tn = n - fn
-        tp = g[n:].sum()
-        fp = len(g) - n - tp
-
-        iou = tp / (tp + fn + fp)
-
-        precision = tp / (tp + fp)
-        recall = tp / (tp + fn)
-
-        precisions += [precision]
-        recalls += [recall]
-        
-    return recalls, precisions
-
-
-# Image processing
-
-def img_preprocess(batch, blur=0, grayscale=False, center_context=None, rect=False, rect_color=(255,0,0), rect_width=2, 
-                   brightness=1.0, bg_fac=1, colorize=False, outline=False, image_size=224):
-    import cv2
-
-    rw = rect_width
-
-    out = []
-    for img, mask in zip(batch[1], batch[2]):
-
-        img = img.cpu() if isinstance(img, torch.Tensor) else torch.from_numpy(img)
-        mask = mask.cpu() if isinstance(mask, torch.Tensor) else torch.from_numpy(mask)
-        
-        img *= brightness
-        img_bl = img
-        if blur > 0: # best 5
-            img_bl = torch.from_numpy(cv2.GaussianBlur(img.permute(1,2,0).numpy(), (15, 15), blur)).permute(2,0,1)
-        
-        if grayscale:
-            img_bl = img_bl[1][None]
-        
-        #img_inp = img_ratio*img*mask + (1-img_ratio)*img_bl
-        # img_inp = img_ratio*img*mask + (1-img_ratio)*img_bl * (1-mask)
-        img_inp = img*mask + (bg_fac) * img_bl * (1-mask)
-
-        if rect:
-            _, bbox = crop_mask(img, mask, context=0.1)
-            img_inp[:, bbox[2]: bbox[3], max(0, bbox[0]-rw):bbox[0]+rw] = torch.tensor(rect_color)[:,None,None]
-            img_inp[:, bbox[2]: bbox[3], max(0, bbox[1]-rw):bbox[1]+rw] = torch.tensor(rect_color)[:,None,None]
-            img_inp[:, max(0, bbox[2]-1): bbox[2]+rw, bbox[0]:bbox[1]] = torch.tensor(rect_color)[:,None,None]
-            img_inp[:, max(0, bbox[3]-1): bbox[3]+rw, bbox[0]:bbox[1]] = torch.tensor(rect_color)[:,None,None]
-
-
-        if center_context is not None:
-            img_inp = object_crop(img_inp, mask, context=center_context, image_size=image_size)
-
-        if colorize:
-            img_gray = denorm(img)
-            img_gray = cv2.cvtColor(img_gray.permute(1,2,0).numpy(), cv2.COLOR_RGB2GRAY)
-            img_gray = torch.stack([torch.from_numpy(img_gray)]*3)
-            img_inp = torch.tensor([1,0.2,0.2])[:,None,None] * img_gray * mask + bg_fac * img_gray * (1-mask)
-            img_inp = norm(img_inp)
-
-        if outline:
-            cont = cv2.findContours(mask.byte().numpy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-            outline_img = np.zeros(mask.shape, dtype=np.uint8)
-            cv2.drawContours(outline_img, cont[0], -1, thickness=5, color=(255, 255, 255))
-            outline_img = torch.stack([torch.from_numpy(outline_img)]*3).float() / 255.
-            img_inp = torch.tensor([1,0,0])[:,None,None] *  outline_img + denorm(img_inp) * (1- outline_img)
-            img_inp = norm(img_inp)
-
-        out += [img_inp]
-
-    return torch.stack(out)
-
-
-def object_crop(img, mask, context=0.0, square=False, image_size=224):
-    img_crop, bbox = crop_mask(img, mask, context=context, square=square)
-    img_crop = pad_to_square(img_crop, channel_dim=0)
-    img_crop = torch.nn.functional.interpolate(img_crop.unsqueeze(0), (image_size, image_size)).squeeze(0)
-    return img_crop
-    
-
-def crop_mask(img, mask, context=0.0, square=False):
-    
-    assert img.shape[1:] == mask.shape
-    
-    bbox = [mask.max(0).values.argmax(), mask.size(0) - mask.max(0).values.flip(0).argmax()]
-    bbox += [mask.max(1).values.argmax(), mask.size(1) - mask.max(1).values.flip(0).argmax()]
-    bbox = [int(x) for x in bbox]
-    
-    width, height = (bbox[3] - bbox[2]), (bbox[1] - bbox[0])
-
-    # square mask
-    if square:
-        bbox[0] = int(max(0, bbox[0] - context * height))
-        bbox[1] = int(min(mask.size(0), bbox[1] + context * height))
-        bbox[2] = int(max(0, bbox[2] - context * width))
-        bbox[3] = int(min(mask.size(1), bbox[3] + context * width))
-
-        width, height = (bbox[3] - bbox[2]), (bbox[1] - bbox[0])
-        if height > width:
-            bbox[2] = int(max(0, (bbox[2] - 0.5*height)))
-            bbox[3] = bbox[2] + height
-        else:
-            bbox[0] = int(max(0, (bbox[0] - 0.5*width)))
-            bbox[1] = bbox[0] + width
-    else:
-        bbox[0] = int(max(0, bbox[0] - context * height))
-        bbox[1] = int(min(mask.size(0), bbox[1] + context * height))
-        bbox[2] = int(max(0, bbox[2] - context * width))
-        bbox[3] = int(min(mask.size(1), bbox[3] + context * width))
-
-    width, height = (bbox[3] - bbox[2]), (bbox[1] - bbox[0])
-    img_crop = img[:, bbox[2]: bbox[3], bbox[0]: bbox[1]]
-    return img_crop, bbox
-
-
-def pad_to_square(img, channel_dim=2, fill=0):
-    """
-
-
-    add padding such that a squared image is returned """
-    
-    from torchvision.transforms.functional import pad
-
-    if channel_dim == 2:
-        img = img.permute(2, 0, 1)
-    elif channel_dim == 0:
-        pass
-    else:
-        raise ValueError('invalid channel_dim')
-
-    h, w = img.shape[1:]
-    pady1 = pady2 = padx1 = padx2 = 0
-
-    if h > w:
-        padx1 = (h - w) // 2
-        padx2 = h - w - padx1
-    elif w > h:
-        pady1 = (w - h) // 2
-        pady2 = w - h - pady1
-
-    img_padded = pad(img, padding=(padx1, pady1, padx2, pady2), padding_mode='constant')
-
-    if channel_dim == 2:
-        img_padded = img_padded.permute(1, 2, 0)
-
-    return img_padded
-
-
-# qualitative
-
-def split_sentence(inp, limit=9):
-    t_new, current_len = [], 0
-    for k, t in enumerate(inp.split(' ')):
-        current_len += len(t) + 1
-        t_new += [t+' ']
-        # not last
-        if current_len > limit and k != len(inp.split(' ')) - 1:
-            current_len = 0
-            t_new += ['\n']
-
-    t_new = ''.join(t_new)
-    return t_new
-    
-
-from matplotlib import pyplot as plt
-
-
-def plot(imgs, *preds, labels=None, scale=1, cmap=plt.cm.magma, aps=None, gt_labels=None, vmax=None):
-    
-    row_off = 0 if labels is None else 1
-    _, ax = plt.subplots(len(imgs) + row_off, 1 + len(preds), figsize=(scale * float(1 + 2*len(preds)), scale * float(len(imgs)*2)))
-    [a.axis('off') for a in ax.flatten()]
-    
-    if labels is not None:
-        for j in range(len(labels)):
-            t_new = split_sentence(labels[j], limit=6)
-            ax[0, 1+ j].text(0.5, 0.1, t_new, ha='center', fontsize=3+ 10*scale)
-
-
-    for i in range(len(imgs)):
-        ax[i + row_off,0].imshow(imgs[i])
-        for j in range(len(preds)):
-            img = preds[j][i][0].detach().cpu().numpy()
-
-            if gt_labels is not None and labels[j] == gt_labels[i]:
-                print(j, labels[j], gt_labels[i])
-                edgecolor = 'red'
-                if aps is not None:
-                    ax[i + row_off, 1 + j].text(30, 70, f'AP: {aps[i]:.3f}', color='red', fontsize=8)
-            else:
-                edgecolor = 'k'
-
-            rect = plt.Rectangle([0,0], img.shape[0], img.shape[1], facecolor="none", 
-                                 edgecolor=edgecolor, linewidth=3)
-            ax[i + row_off,1 + j].add_patch(rect)
-
-            if vmax is None:
-                this_vmax = 1 
-            elif vmax == 'per_prompt':
-                this_vmax = max([preds[j][_i][0].max() for _i in range(len(imgs))])
-            elif vmax == 'per_image':
-                this_vmax = max([preds[_j][i][0].max() for _j in range(len(preds))])
-
-            ax[i + row_off,1 + j].imshow(img, vmin=0, vmax=this_vmax, cmap=cmap)
-
-    
-            # ax[i,1 + j].imshow(preds[j][i][0].detach().cpu().numpy(), vmin=preds[j].min(), vmax=preds[j].max())
-    plt.tight_layout()
-    plt.subplots_adjust(wspace=0.05, hspace=0.05)    
\ No newline at end of file
diff --git a/spaces/ali-ghamdan/deoldify/fastai/gen_doc/__init__.py b/spaces/ali-ghamdan/deoldify/fastai/gen_doc/__init__.py
deleted file mode 100644
index 31e6aeacd89726b7e4428d47fb36b465524ed723..0000000000000000000000000000000000000000
--- a/spaces/ali-ghamdan/deoldify/fastai/gen_doc/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-from . import gen_notebooks, nbdoc, core, doctest, nbtest
diff --git a/spaces/alsalemi/pv-segment-01/LesionDataset.py b/spaces/alsalemi/pv-segment-01/LesionDataset.py
deleted file mode 100644
index 1c1fd7ee4153d62ce565321083f7b60272af756c..0000000000000000000000000000000000000000
--- a/spaces/alsalemi/pv-segment-01/LesionDataset.py
+++ /dev/null
@@ -1,263 +0,0 @@
-import os
-import numpy as np
-import torch
-from torchvision import transforms as T2 
-import albumentations as A
-from PIL import Image
-from xml_to_mask import *
-
-class LesionDataset(torch.utils.data.Dataset):
-    def __init__(self, root, transforms: bool = True, one_class_mode=False, linecolors=['65280', '10485760'], batch_no=1, downsample=1, minimum_size=[512, 512], excluded_classes=[]):
-        self.root = root
-        self.batch_no = batch_no
-        self.linecolors = linecolors
-        self.excluded_classes = excluded_classes
-        paths = self.get_dataset_paths(root, batch_no)
-        self.transforms = transforms 
-        self.imgs = paths[0]
-        self.annotations = paths[1]
-        self.downsample = downsample
-        self.minimum_size = minimum_size
-        self.one_class_mode = one_class_mode
-
-    @property
-    def validation_ids(self):
-        validation_ids = ['13.2766', '13.2875', '13.2752', '13.2868', '13.2744', '13.2777']
-        return validation_ids
-
-    @property
-    def binary_classes(self):
-        if self.batch_no == 1:
-            classes = ['suspicious', 'normal']
-            return classes
-        if self.batch_no == 2:
-            all_classes = ['Cancer', 'Dysplastic', 'Non-dysplastic']
-            classes = [c for c in all_classes if c not in self.excluded_classes]
-            return classes
-        else:
-            raise ValueError('Invalid batch number: {0}'.format(self.batch_no))
-    
-    @property
-    def binary_classes_indicies(self):
-        indicies = [x + 1 for x in range(len(self.binary_classes))]
-        return indicies
-    
-    @property
-    def class_colors(self):
-        if self.batch_no == 2:
-            colors = {
-                'Non-dysplastic': [[0.0, 1.0, 0.0], 'Greens', 'Non-dysplastic'],
-                'Dysplastic': [[1.0, 0.5, 0.0], 'rainbow', 'Dysplastic'],
-                'Cancer': [[1.0, 0.0, 0.0], 'jet', 'Cancer'],
-            }
-            return colors
-        else:
-            raise ValueError('Invalid batch number: {0}'.format(self.batch_no))
-
-    def random_validation_ids(self, ids, n=6):
-        validation_ids = []
-        ids_range = range(len(ids))
-        # print('ids_range: {0}'.format(ids_range))
-        rand_idxs = np.random.choice(ids_range, size=n, replace=False)
-        for i in rand_idxs:
-            # print('rand_idx: {0}'.format(i))
-            validation_ids.append(ids[i])
-        return validation_ids
-    
-    @property
-    def grading_classes(self):
-        if self.batch_no == 1:
-            classes = [c for c in ['mild', 'moderate', 'severe'] if c not in self.excluded_classes]
-            return classes
-        elif self.batch_no == 2:
-            # Exclude classes using self.excluded_classes
-            classes = [c for c in ['Cancer', 'Dysplastic', 'Non-dysplastic'] if c not in self.excluded_classes]
-            return classes
-        else:
-            raise ValueError('Invalid batch number: {0}'.format(self.batch_no))
-
-    def compose_transforms_a(self, img, target):
-        if target['masks'].shape[0] == 0:
-            print('No masks found')
-            masks = np.zeros((img.size[1], img.size[0], 1))
-        else:
-            masks = np.array(target['masks']).transpose(1, 2, 0)
-        
-        if self.transforms is True:
-            transform = A.Compose([
-                # A.RandomCrop(width=img.size[0], height=img.size[1], p=0.5),
-                A.HorizontalFlip(p=0.5),
-                A.GaussianBlur(),
-                A.RandomBrightnessContrast(brightness_limit=0.3, contrast_limit=0.3, p=0.5),
-                A.HueSaturationValue(hue_shift_limit=5, sat_shift_limit=30, val_shift_limit=0, p=0.5),
-                # A.RandomRotate90(p=0.2),
-                A.Rotate(limit=180, p=0.5, border_mode=0),
-                # A.RandomScale(scale_limit=(0.1, 0.8), p=0.5),
-            ], bbox_params=A.BboxParams(format='pascal_voc', label_fields=['labels']))
-            transformed = transform(image=np.array(img), mask=masks, bboxes=target['boxes'], labels=target['labels'])
-            img = transformed['image']
-            target['masks'] = transformed['mask']
-            target['boxes'] = transformed['bboxes']
-            target['masks'] = target['masks'].transpose(2, 0, 1)
-            target['labels'] = transformed['labels']
-        # Convert to Tensor
-        img = T2.ToTensor()(img)
-        
-        # img = img.permute(1, 2, 0)
-        return img, target
-
-    def get_all_id_pairs(self, root):
-        if self.batch_no == 1:
-            return self.get_all_id_pairs_batch_01(root)
-        elif self.batch_no == 2:
-            return self.get_all_id_pairs_batch_02(root)
-        else:
-            raise ValueError('Invalid batch number: {0}'.format(self.batch_no))
-
-    def get_all_id_pairs_batch_01(self, root):
-        all_id_pairs = []
-        # Find all images and annotations
-        for grading_class in self.grading_classes:
-            for _, ids, _ in os.walk(root + '/' + grading_class, topdown=False):
-                for id in ids:
-                    all_id_pairs.append((grading_class, id))
-        return all_id_pairs
-
-    def get_all_id_pairs_batch_02(self, root):
-        all_id_pairs = []
-        # Find all images and annotations
-        for grading_class in self.grading_classes:
-            for _, _, ids in os.walk(root + '/' + grading_class, topdown=False):
-                # Remove extension from ids
-                ids = [x.split('.')[0] for x in ids]
-                for id in ids:
-                    if len([x for x in ids if x == id]) != 2:
-                        print('Id {0} does not have two files (image or annotation)'.format(id))
-                        # Remove id from ids
-                        ids = np.delete(ids, np.where(ids == id))
-                ids = sorted(np.unique(ids))
-                for id in ids:
-                    all_id_pairs.append((grading_class, id))
-        return all_id_pairs
-
-    def get_dataset_paths(self, root, batch_no=1):
-        if batch_no == 1:
-            return self.get_dataset_paths_batch_01(root)
-        elif batch_no == 2:
-            return self.get_dataset_paths_batch_02(root)
-        else:
-            raise ValueError('Invalid batch number: {0}'.format(self.batch_no))
-
-    def get_dataset_paths_batch_01(self, root):
-        all_id_pairs = self.get_all_id_pairs(root)
-        selected_id_pairs = all_id_pairs
-        
-        print('all_id_pairs: {0}'.format(all_id_pairs), len(all_id_pairs))
-        print('selected_id_pairs: {0}'.format(selected_id_pairs), len(selected_id_pairs))
-
-        # Create image and annotation paths
-        image_paths = []
-        annot_paths = []
-        for grading_class, id in selected_id_pairs:
-            image_path = self.root + '{0}/{1}/1.jpg'.format(grading_class, id)
-            annot_path = self.root + '{0}/{1}/1.xml'.format(grading_class, id)
-            image_paths.append(image_path)
-            annot_paths.append(annot_path)
-        return image_paths, annot_paths    
-    
-    def get_dataset_paths_batch_02(self, root):
-        all_id_pairs = self.get_all_id_pairs(root)
-
-        training_ids = [x for x in all_id_pairs]
-        
-        # print('all_id_pairs: {0}'.format(all_id_pairs), len(all_id_pairs))
-        # print('training_ids: {0}'.format(training_ids), len(training_ids))
-
-        # Create image and annotation paths
-        image_paths = []
-        annot_paths = []
-
-        for grading_class, id in training_ids:
-            image_path = self.root + '{0}/{1}.jpg'.format(grading_class, id)
-            annot_path = self.root + '{0}/{1}.xml'.format(grading_class, id)
-            # Check if image_path and annot_path exists
-            if os.path.exists(image_path) and os.path.exists(annot_path):
-                image_paths.append(image_path)
-                annot_paths.append(annot_path)
-            else:
-                print('Image or annotation path does not exist: {0}, {1}'.format(image_path, annot_path))
-        return image_paths, annot_paths
-
-    def __getitem__(self, idx):
-        class_ids = []
-        img_path = self.imgs[idx]
-        annot_path = self.annotations[idx]
-        
-        img = Image.open(img_path).convert("RGB")
-        # Scale image down by downsample factor
-        # If image is too small (height or width < 512) don't downsample
-        downsample = self.downsample
-        if img.size[0] > self.minimum_size[0] and img.size[1] > self.minimum_size[1]:
-            img = img.resize((int(img.size[0]/downsample), int(img.size[1]/downsample)))
-        else:
-            downsample = 1
-
-        height, width = img.size 
-
-        masks = xml_to_masks(annot_path, location=(0,0), size=(height, width), downsample=downsample, verbose=False, linecolors=self.linecolors)
-        
-        bounds = []
-        finalmasks = []
-        for submask in masks:
-            # Get bbox using skimage/Torch
-            id = np.unique(submask)[1] 
-            if self.one_class_mode and id == 2:
-                continue
-            submask = submask == id
-            pos = np.where(submask) 
-            xmin = np.min(pos[1])
-            xmax = np.max(pos[1])
-            ymin = np.min(pos[0])
-            ymax = np.max(pos[0])
-            finalmasks.append(submask)
-            bounds.append([xmin, ymin, xmax, ymax]) # pascal_voc format
-            class_ids.append(id)
-        # TODO: change to tensor = torch.from_numpy(finalmasks) (check dtype of finalmasks)
-        masks = torch.as_tensor(finalmasks, dtype=torch.uint8)
-        class_ids = np.array(class_ids, dtype=np.int32)
-        num_objs = len(class_ids)
-        boxes = torch.as_tensor(bounds, dtype=torch.float32)
-        labels = torch.as_tensor(class_ids, dtype=torch.int64)
-        image_id = torch.tensor([idx])
-        if boxes.shape[0] == 0:
-            print('No boxes found for image: {0}'.format(img_path))
-            area = 0
-        else:
-            area = (boxes[:, 3] - boxes[:, 1]) * (boxes[:, 2] - boxes[:, 0])
-        iscrowd = torch.zeros((num_objs,), dtype=torch.int64)
-
-        target = {}
-        target["boxes"] = boxes
-        target["labels"] = labels
-        target["masks"] = masks
-        target["image_id"] = image_id
-        target["area"] = area
-        target["iscrowd"] = iscrowd
-
-        img, target = self.compose_transforms_a(img, target)
-        target['boxes'] = torch.as_tensor(target['boxes'], dtype=torch.float32)
-        target['labels'] = torch.as_tensor(target['labels'], dtype=torch.int64)
-        target['masks'] = torch.as_tensor(target['masks'], dtype=torch.uint8)
-        target['image_id'] = torch.tensor([idx])
-        target['area'] = torch.as_tensor(target['area'], dtype=torch.float32)
-        target['iscrowd'] = torch.as_tensor(target['iscrowd'], dtype=torch.int64)
-
-        return img, target
-    
-    def reload(self):
-        paths = self.get_dataset_paths(self.root, val=self.val, random_val=self.random_val)
-        self.imgs = paths[0]
-        self.annotations = paths[1]
-
-    def __len__(self):
-        return len(self.imgs)
\ No newline at end of file
diff --git a/spaces/anuragshas/restore-punctuation-demo/InferenceServer.py b/spaces/anuragshas/restore-punctuation-demo/InferenceServer.py
deleted file mode 100644
index dc48385262e73bb2304f65ced3758e299a7d6d95..0000000000000000000000000000000000000000
--- a/spaces/anuragshas/restore-punctuation-demo/InferenceServer.py
+++ /dev/null
@@ -1,17 +0,0 @@
-from rpunct import RestorePuncts
-print("Loading Model...")
-rpunct = RestorePuncts()
-
-from fastapi import FastAPI
-
-app = FastAPI()
-print("Models loaded !")
-
-@app.get("/")
-def read_root():
-    return {"Homepage!"}
-
-@app.get("/{restore}")
-def get_correction(input_sentence):
-    '''Returns sentence with correct punctuations and case'''
-    return {"corrected_sentence": rpunct.punctuate(input_sentence, lang="en")}
\ No newline at end of file
diff --git a/spaces/aodianyun/stable-diffusion-webui/javascript/edit-attention.js b/spaces/aodianyun/stable-diffusion-webui/javascript/edit-attention.js
deleted file mode 100644
index 6e6905daf536d164cc2a246886ca8198603ce61a..0000000000000000000000000000000000000000
--- a/spaces/aodianyun/stable-diffusion-webui/javascript/edit-attention.js
+++ /dev/null
@@ -1,96 +0,0 @@
-function keyupEditAttention(event){
-	let target = event.originalTarget || event.composedPath()[0];
-	if (!target.matches("[id*='_toprow'] textarea.gr-text-input[placeholder]")) return;
-	if (! (event.metaKey || event.ctrlKey)) return;
-
-	let isPlus = event.key == "ArrowUp"
-	let isMinus = event.key == "ArrowDown"
-	if (!isPlus && !isMinus) return;
-
-	let selectionStart = target.selectionStart;
-	let selectionEnd = target.selectionEnd;
-	let text = target.value;
-
-    function selectCurrentParenthesisBlock(OPEN, CLOSE){
-        if (selectionStart !== selectionEnd) return false;
-
-		// Find opening parenthesis around current cursor
-		const before = text.substring(0, selectionStart);
-		let beforeParen = before.lastIndexOf(OPEN);
-		if (beforeParen == -1) return  false;
-		let beforeParenClose = before.lastIndexOf(CLOSE);
-		while (beforeParenClose !== -1 && beforeParenClose > beforeParen) {
-			beforeParen = before.lastIndexOf(OPEN, beforeParen - 1);
-			beforeParenClose = before.lastIndexOf(CLOSE, beforeParenClose - 1);
-		}
-
-		// Find closing parenthesis around current cursor
-		const after = text.substring(selectionStart);
-		let afterParen = after.indexOf(CLOSE);
-		if (afterParen == -1) return  false;
-		let afterParenOpen = after.indexOf(OPEN);
-		while (afterParenOpen !== -1 && afterParen > afterParenOpen) {
-			afterParen = after.indexOf(CLOSE, afterParen + 1);
-			afterParenOpen = after.indexOf(OPEN, afterParenOpen + 1);
-		}
-		if (beforeParen === -1 || afterParen === -1) return false;
-
-		// Set the selection to the text between the parenthesis
-		const parenContent = text.substring(beforeParen + 1, selectionStart + afterParen);
-		const lastColon = parenContent.lastIndexOf(":");
-		selectionStart = beforeParen + 1;
-		selectionEnd = selectionStart + lastColon;
-		target.setSelectionRange(selectionStart, selectionEnd);
-		return true;
-    }
-
-	// If the user hasn't selected anything, let's select their current parenthesis block
-    if(! selectCurrentParenthesisBlock('<', '>')){
-        selectCurrentParenthesisBlock('(', ')')
-    }
-
-	event.preventDefault();
-
-    closeCharacter = ')'
-    delta = opts.keyedit_precision_attention
-
-    if (selectionStart > 0 && text[selectionStart - 1] == '<'){
-        closeCharacter = '>'
-        delta = opts.keyedit_precision_extra
-    } else if (selectionStart == 0 || text[selectionStart - 1] != "(") {
-
-        // do not include spaces at the end
-        while(selectionEnd > selectionStart && text[selectionEnd-1] == ' '){
-            selectionEnd -= 1;
-        }
-        if(selectionStart == selectionEnd){
-            return
-        }
-
-        text = text.slice(0, selectionStart) + "(" + text.slice(selectionStart, selectionEnd) + ":1.0)" + text.slice(selectionEnd);
-
-        selectionStart += 1;
-        selectionEnd += 1;
-    }
-
-	end = text.slice(selectionEnd + 1).indexOf(closeCharacter) + 1;
-	weight = parseFloat(text.slice(selectionEnd + 1, selectionEnd + 1 + end));
-	if (isNaN(weight)) return;
-
-	weight += isPlus ? delta : -delta;
-	weight = parseFloat(weight.toPrecision(12));
-	if(String(weight).length == 1) weight += ".0"
-
-	text = text.slice(0, selectionEnd + 1) + weight + text.slice(selectionEnd + 1 + end - 1);
-
-	target.focus();
-	target.value = text;
-	target.selectionStart = selectionStart;
-	target.selectionEnd = selectionEnd;
-
-	updateInput(target)
-}
-
-addEventListener('keydown', (event) => {
-    keyupEditAttention(event);
-});
\ No newline at end of file
diff --git a/spaces/arnavkartikeya/SCRIPture-final/models/blip_pretrain.py b/spaces/arnavkartikeya/SCRIPture-final/models/blip_pretrain.py
deleted file mode 100644
index e42ce5f998b0a51e6f731ee6b5c8bae6d02a8664..0000000000000000000000000000000000000000
--- a/spaces/arnavkartikeya/SCRIPture-final/models/blip_pretrain.py
+++ /dev/null
@@ -1,339 +0,0 @@
-'''
- * Copyright (c) 2022, salesforce.com, inc.
- * All rights reserved.
- * SPDX-License-Identifier: BSD-3-Clause
- * For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause
- * By Junnan Li
-'''
-from models.med import BertConfig, BertModel, BertLMHeadModel
-from transformers import BertTokenizer
-import transformers
-transformers.logging.set_verbosity_error()
-
-import torch
-from torch import nn
-import torch.nn.functional as F
-
-from models.blip import create_vit, init_tokenizer, load_checkpoint
-
-class BLIP_Pretrain(nn.Module):
-    def __init__(self,                 
-                 med_config = 'configs/bert_config.json',  
-                 image_size = 224,
-                 vit = 'base',
-                 vit_grad_ckpt = False,
-                 vit_ckpt_layer = 0,                    
-                 embed_dim = 256,     
-                 queue_size = 57600,
-                 momentum = 0.995,
-                 ):
-        """
-        Args:
-            med_config (str): path for the mixture of encoder-decoder model's configuration file
-            image_size (int): input image size
-            vit (str): model size of vision transformer
-        """               
-        super().__init__()
-        
-        self.visual_encoder, vision_width = create_vit(vit,image_size, vit_grad_ckpt, vit_ckpt_layer, 0)
-        
-        if vit=='base':
-            checkpoint = torch.hub.load_state_dict_from_url(
-                url="https://dl.fbaipublicfiles.com/deit/deit_base_patch16_224-b5f2ef4d.pth",
-                map_location="cpu", check_hash=True)
-            state_dict = checkpoint["model"]     
-            msg = self.visual_encoder.load_state_dict(state_dict,strict=False)
-        elif vit=='large':
-            from timm.models.helpers import load_custom_pretrained
-            from timm.models.vision_transformer import default_cfgs
-            load_custom_pretrained(self.visual_encoder,default_cfgs['vit_large_patch16_224_in21k'])        
-               
-        self.tokenizer = init_tokenizer()   
-        encoder_config = BertConfig.from_json_file(med_config)
-        encoder_config.encoder_width = vision_width
-        self.text_encoder = BertModel.from_pretrained('bert-base-uncased',config=encoder_config, add_pooling_layer=False)
-        self.text_encoder.resize_token_embeddings(len(self.tokenizer)) 
-
-        text_width = self.text_encoder.config.hidden_size
-        
-        self.vision_proj = nn.Linear(vision_width, embed_dim)
-        self.text_proj = nn.Linear(text_width, embed_dim)
-
-        self.itm_head = nn.Linear(text_width, 2) 
-        
-        # create momentum encoders  
-        self.visual_encoder_m, vision_width = create_vit(vit,image_size)              
-        self.vision_proj_m = nn.Linear(vision_width, embed_dim)
-        self.text_encoder_m = BertModel(config=encoder_config, add_pooling_layer=False)      
-        self.text_proj_m = nn.Linear(text_width, embed_dim)
-        
-        self.model_pairs = [[self.visual_encoder,self.visual_encoder_m],
-                            [self.vision_proj,self.vision_proj_m],
-                            [self.text_encoder,self.text_encoder_m],
-                            [self.text_proj,self.text_proj_m],
-                           ]       
-        self.copy_params()
-
-        # create the queue
-        self.register_buffer("image_queue", torch.randn(embed_dim, queue_size))
-        self.register_buffer("text_queue", torch.randn(embed_dim, queue_size))
-        self.register_buffer("queue_ptr", torch.zeros(1, dtype=torch.long))  
-
-        self.image_queue = nn.functional.normalize(self.image_queue, dim=0)
-        self.text_queue = nn.functional.normalize(self.text_queue, dim=0)
-        
-        self.queue_size = queue_size
-        self.momentum = momentum
-        self.temp = nn.Parameter(0.07*torch.ones([]))   
-        
-        # create the decoder
-        decoder_config = BertConfig.from_json_file(med_config)
-        decoder_config.encoder_width = vision_width        
-        self.text_decoder = BertLMHeadModel.from_pretrained('bert-base-uncased',config=decoder_config)    
-        self.text_decoder.resize_token_embeddings(len(self.tokenizer)) 
-        tie_encoder_decoder_weights(self.text_encoder,self.text_decoder.bert,'','/attention')
-        
-        
-    def forward(self, image, caption, alpha):
-        with torch.no_grad():
-            self.temp.clamp_(0.001,0.5)
-        
-        image_embeds = self.visual_encoder(image) 
-        image_atts = torch.ones(image_embeds.size()[:-1],dtype=torch.long).to(image.device)        
-        image_feat = F.normalize(self.vision_proj(image_embeds[:,0,:]),dim=-1)          
-        
-        text = self.tokenizer(caption, padding='max_length', truncation=True, max_length=30, 
-                              return_tensors="pt").to(image.device)  
-        text_output = self.text_encoder(text.input_ids, attention_mask = text.attention_mask,                      
-                                        return_dict = True, mode = 'text')            
-        text_feat = F.normalize(self.text_proj(text_output.last_hidden_state[:,0,:]),dim=-1)                 
-             
-        # get momentum features
-        with torch.no_grad():
-            self._momentum_update()
-            image_embeds_m = self.visual_encoder_m(image) 
-            image_feat_m = F.normalize(self.vision_proj_m(image_embeds_m[:,0,:]),dim=-1)  
-            image_feat_all = torch.cat([image_feat_m.t(),self.image_queue.clone().detach()],dim=1)                   
-            
-            text_output_m = self.text_encoder_m(text.input_ids, attention_mask = text.attention_mask,                      
-                                                return_dict = True, mode = 'text')    
-            text_feat_m = F.normalize(self.text_proj_m(text_output_m.last_hidden_state[:,0,:]),dim=-1) 
-            text_feat_all = torch.cat([text_feat_m.t(),self.text_queue.clone().detach()],dim=1)
-
-            sim_i2t_m = image_feat_m @ text_feat_all / self.temp  
-            sim_t2i_m = text_feat_m @ image_feat_all / self.temp 
-
-            sim_targets = torch.zeros(sim_i2t_m.size()).to(image.device)
-            sim_targets.fill_diagonal_(1)          
-
-            sim_i2t_targets = alpha * F.softmax(sim_i2t_m, dim=1) + (1 - alpha) * sim_targets
-            sim_t2i_targets = alpha * F.softmax(sim_t2i_m, dim=1) + (1 - alpha) * sim_targets        
-
-        sim_i2t = image_feat @ text_feat_all / self.temp
-        sim_t2i = text_feat @ image_feat_all / self.temp
-                             
-        loss_i2t = -torch.sum(F.log_softmax(sim_i2t, dim=1)*sim_i2t_targets,dim=1).mean()
-        loss_t2i = -torch.sum(F.log_softmax(sim_t2i, dim=1)*sim_t2i_targets,dim=1).mean() 
-
-        loss_ita = (loss_i2t+loss_t2i)/2
-
-        self._dequeue_and_enqueue(image_feat_m, text_feat_m)        
-
-        ###============== Image-text Matching ===================###
-        encoder_input_ids = text.input_ids.clone()
-        encoder_input_ids[:,0] = self.tokenizer.enc_token_id
-        
-        # forward the positve image-text pair
-        bs = image.size(0)
-        output_pos = self.text_encoder(encoder_input_ids,
-                                       attention_mask = text.attention_mask,
-                                       encoder_hidden_states = image_embeds,
-                                       encoder_attention_mask = image_atts,      
-                                       return_dict = True,
-                                      )            
-        with torch.no_grad():       
-            weights_t2i = F.softmax(sim_t2i[:,:bs],dim=1)+1e-4 
-            weights_t2i.fill_diagonal_(0)            
-            weights_i2t = F.softmax(sim_i2t[:,:bs],dim=1)+1e-4  
-            weights_i2t.fill_diagonal_(0)   
-            
-        # select a negative image for each text
-        image_embeds_neg = []    
-        for b in range(bs):
-            neg_idx = torch.multinomial(weights_t2i[b], 1).item()
-            image_embeds_neg.append(image_embeds[neg_idx])
-        image_embeds_neg = torch.stack(image_embeds_neg,dim=0)   
-
-        # select a negative text for each image
-        text_ids_neg = []
-        text_atts_neg = []
-        for b in range(bs):
-            neg_idx = torch.multinomial(weights_i2t[b], 1).item()
-            text_ids_neg.append(encoder_input_ids[neg_idx])
-            text_atts_neg.append(text.attention_mask[neg_idx])
-
-        text_ids_neg = torch.stack(text_ids_neg,dim=0)   
-        text_atts_neg = torch.stack(text_atts_neg,dim=0)      
-
-        text_ids_all = torch.cat([encoder_input_ids, text_ids_neg],dim=0)     
-        text_atts_all = torch.cat([text.attention_mask, text_atts_neg],dim=0)     
-
-        image_embeds_all = torch.cat([image_embeds_neg,image_embeds],dim=0)
-        image_atts_all = torch.cat([image_atts,image_atts],dim=0)
-
-        output_neg = self.text_encoder(text_ids_all,
-                                       attention_mask = text_atts_all,
-                                       encoder_hidden_states = image_embeds_all,
-                                       encoder_attention_mask = image_atts_all,      
-                                       return_dict = True,
-                                      )                            
-
-        vl_embeddings = torch.cat([output_pos.last_hidden_state[:,0,:], output_neg.last_hidden_state[:,0,:]],dim=0)
-        vl_output = self.itm_head(vl_embeddings)            
-
-        itm_labels = torch.cat([torch.ones(bs,dtype=torch.long),torch.zeros(2*bs,dtype=torch.long)],
-                               dim=0).to(image.device)
-        loss_itm = F.cross_entropy(vl_output, itm_labels)  
-        
-        ##================= LM ========================##     
-        decoder_input_ids = text.input_ids.clone()      
-        decoder_input_ids[:,0] = self.tokenizer.bos_token_id
-        decoder_targets = decoder_input_ids.masked_fill(decoder_input_ids == self.tokenizer.pad_token_id, -100) 
-
-        decoder_output = self.text_decoder(decoder_input_ids, 
-                                           attention_mask = text.attention_mask, 
-                                           encoder_hidden_states = image_embeds,
-                                           encoder_attention_mask = image_atts,                  
-                                           labels = decoder_targets,
-                                           return_dict = True,   
-                                          )   
-          
-        loss_lm = decoder_output.loss                
-        return loss_ita, loss_itm, loss_lm
- 
-
-
-    @torch.no_grad()    
-    def copy_params(self):
-        for model_pair in self.model_pairs:           
-            for param, param_m in zip(model_pair[0].parameters(), model_pair[1].parameters()):
-                param_m.data.copy_(param.data)  # initialize
-                param_m.requires_grad = False  # not update by gradient    
-
-            
-    @torch.no_grad()        
-    def _momentum_update(self):
-        for model_pair in self.model_pairs:           
-            for param, param_m in zip(model_pair[0].parameters(), model_pair[1].parameters()):
-                param_m.data = param_m.data * self.momentum + param.data * (1. - self.momentum)
-
-                        
-    @torch.no_grad()
-    def _dequeue_and_enqueue(self, image_feat, text_feat):
-        # gather keys before updating queue
-        image_feats = concat_all_gather(image_feat)
-        text_feats = concat_all_gather(text_feat)
-
-        batch_size = image_feats.shape[0]
-
-        ptr = int(self.queue_ptr)
-        assert self.queue_size % batch_size == 0  # for simplicity
-
-        # replace the keys at ptr (dequeue and enqueue)
-        self.image_queue[:, ptr:ptr + batch_size] = image_feats.T
-        self.text_queue[:, ptr:ptr + batch_size] = text_feats.T
-        ptr = (ptr + batch_size) % self.queue_size  # move pointer
-
-        self.queue_ptr[0] = ptr 
-
-
-def blip_pretrain(**kwargs):
-    model = BLIP_Pretrain(**kwargs)
-    return model 
-
-
-@torch.no_grad()
-def concat_all_gather(tensor):
-    """
-    Performs all_gather operation on the provided tensors.
-    *** Warning ***: torch.distributed.all_gather has no gradient.
-    """
-    tensors_gather = [torch.ones_like(tensor)
-        for _ in range(torch.distributed.get_world_size())]
-    torch.distributed.all_gather(tensors_gather, tensor, async_op=False)
-
-    output = torch.cat(tensors_gather, dim=0)
-    return output     
-
-
-from typing import List
-def tie_encoder_decoder_weights(encoder: nn.Module, decoder: nn.Module, base_model_prefix: str, skip_key:str):
-    uninitialized_encoder_weights: List[str] = []
-    if decoder.__class__ != encoder.__class__:
-        logger.info(
-            f"{decoder.__class__} and {encoder.__class__} are not equal. In this case make sure that all encoder weights are correctly initialized."
-        )
-
-    def tie_encoder_to_decoder_recursively(
-        decoder_pointer: nn.Module,
-        encoder_pointer: nn.Module,
-        module_name: str,
-        uninitialized_encoder_weights: List[str],
-        skip_key: str,
-        depth=0,
-    ):
-        assert isinstance(decoder_pointer, nn.Module) and isinstance(
-            encoder_pointer, nn.Module
-        ), f"{decoder_pointer} and {encoder_pointer} have to be of type torch.nn.Module"
-        if hasattr(decoder_pointer, "weight") and skip_key not in module_name:
-            assert hasattr(encoder_pointer, "weight")
-            encoder_pointer.weight = decoder_pointer.weight
-            if hasattr(decoder_pointer, "bias"):
-                assert hasattr(encoder_pointer, "bias")
-                encoder_pointer.bias = decoder_pointer.bias                
-            print(module_name+' is tied')    
-            return
-
-        encoder_modules = encoder_pointer._modules
-        decoder_modules = decoder_pointer._modules
-        if len(decoder_modules) > 0:
-            assert (
-                len(encoder_modules) > 0
-            ), f"Encoder module {encoder_pointer} does not match decoder module {decoder_pointer}"
-
-            all_encoder_weights = set([module_name + "/" + sub_name for sub_name in encoder_modules.keys()])
-            encoder_layer_pos = 0
-            for name, module in decoder_modules.items():
-                if name.isdigit():
-                    encoder_name = str(int(name) + encoder_layer_pos)
-                    decoder_name = name
-                    if not isinstance(decoder_modules[decoder_name], type(encoder_modules[encoder_name])) and len(
-                        encoder_modules
-                    ) != len(decoder_modules):
-                        # this can happen if the name corresponds to the position in a list module list of layers
-                        # in this case the decoder has added a cross-attention that the encoder does not have
-                        # thus skip this step and subtract one layer pos from encoder
-                        encoder_layer_pos -= 1
-                        continue
-                elif name not in encoder_modules:
-                    continue
-                elif depth > 500:
-                    raise ValueError(
-                        "Max depth of recursive function `tie_encoder_to_decoder` reached. It seems that there is a circular dependency between two or more `nn.Modules` of your model."
-                    )
-                else:
-                    decoder_name = encoder_name = name
-                tie_encoder_to_decoder_recursively(
-                    decoder_modules[decoder_name],
-                    encoder_modules[encoder_name],
-                    module_name + "/" + name,
-                    uninitialized_encoder_weights,
-                    skip_key,
-                    depth=depth + 1,
-                )
-                all_encoder_weights.remove(module_name + "/" + encoder_name)
-
-            uninitialized_encoder_weights += list(all_encoder_weights)
-
-    # tie weights recursively
-    tie_encoder_to_decoder_recursively(decoder, encoder, base_model_prefix, uninitialized_encoder_weights, skip_key)  
diff --git a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/Cython/Distutils/build_ext.py b/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/Cython/Distutils/build_ext.py
deleted file mode 100644
index 598bb4a89b1f3d34c9411f768ec91c78946eb5a9..0000000000000000000000000000000000000000
--- a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/Cython/Distutils/build_ext.py
+++ /dev/null
@@ -1,25 +0,0 @@
-import sys
-
-if 'setuptools' in sys.modules:
-    try:
-        from setuptools.command.build_ext import build_ext as _build_ext
-    except ImportError:
-        # We may be in the process of importing setuptools, which tries
-        # to import this.
-        from distutils.command.build_ext import build_ext as _build_ext
-else:
-    from distutils.command.build_ext import build_ext as _build_ext
-
-
-class new_build_ext(_build_ext, object):
-    def finalize_options(self):
-        if self.distribution.ext_modules:
-            nthreads = getattr(self, 'parallel', None)  # -j option in Py3.5+
-            nthreads = int(nthreads) if nthreads else None
-            from Cython.Build.Dependencies import cythonize
-            self.distribution.ext_modules[:] = cythonize(
-                self.distribution.ext_modules, nthreads=nthreads, force=self.force)
-        super(new_build_ext, self).finalize_options()
-
-# This will become new_build_ext in the future.
-from .old_build_ext import old_build_ext as build_ext
diff --git a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/altair/examples/table_bubble_plot_github.py b/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/altair/examples/table_bubble_plot_github.py
deleted file mode 100644
index 80683ccc805c41b366f28af57be921bb0d875ba0..0000000000000000000000000000000000000000
--- a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/altair/examples/table_bubble_plot_github.py
+++ /dev/null
@@ -1,16 +0,0 @@
-"""
-Table Bubble Plot (Github Punch Card)
--------------------------------------
-This example shows github contributions by the day of week and hour of the day.
-"""
-# category: scatter plots
-import altair as alt
-from vega_datasets import data
-
-source = data.github.url
-
-alt.Chart(source).mark_circle().encode(
-    x='hours(time):O',
-    y='day(time):O',
-    size='sum(count):Q'
-)
diff --git a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/fairseq/criterions/speech_to_speech_criterion.py b/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/fairseq/criterions/speech_to_speech_criterion.py
deleted file mode 100644
index 7fba673d2569eeb0f32922eacb95b3ac78bbc1a5..0000000000000000000000000000000000000000
--- a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/fairseq/criterions/speech_to_speech_criterion.py
+++ /dev/null
@@ -1,310 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import math
-import torch
-
-from fairseq import metrics, utils
-from fairseq.criterions import register_criterion
-from fairseq.criterions.ctc import CtcCriterion
-from fairseq.criterions.label_smoothed_cross_entropy import (
-    LabelSmoothedCrossEntropyCriterion,
-    LabelSmoothedCrossEntropyCriterionConfig,
-)
-from fairseq.criterions.tacotron2_loss import (
-    Tacotron2Criterion,
-    Tacotron2CriterionConfig,
-)
-
-
-class MultitaskCriterion:
-    def __init__(self, multitask_tasks):
-        self.multitask_criterion = {}
-        self.multitask_loss_weight = {}
-        for task_name, task_obj in multitask_tasks.items():
-            if task_obj.args.decoder_type == "ctc":
-                self.multitask_criterion[task_name] = CtcCriterion(
-                    task_obj.args.criterion_cfg, task_obj
-                )
-            else:
-                self.multitask_criterion[
-                    task_name
-                ] = LabelSmoothedCrossEntropyCriterion(
-                    task_obj,
-                    task_obj.args.criterion_cfg.sentence_avg,
-                    label_smoothing=task_obj.args.criterion_cfg.label_smoothing,
-                )
-
-    def set_multitask_loss_weight(self, task_name, weight=0.0):
-        self.multitask_loss_weight[task_name] = weight
-
-    def get_multitask_loss(self, model, sample, model_out):
-        logging_output = {}
-        loss = 0.0
-        for task_name, task_criterion in self.multitask_criterion.items():
-            layer_id = task_criterion.task.args.input_layer
-            if isinstance(task_criterion, CtcCriterion):
-                if task_criterion.task.args.input_from == "encoder":
-                    non_padding_mask = ~model_out["encoder_padding_mask"][0]
-                    input_lengths = non_padding_mask.long().sum(-1)
-                    task_sample = {
-                        "net_input": {
-                            "src_tokens": model_out["encoder_states"][
-                                layer_id
-                            ],  # check batch idx
-                            "src_lengths": input_lengths,
-                        },
-                        "id": sample["id"],
-                    }
-                else:
-                    task_sample = {
-                        "net_input": {
-                            "src_tokens": model_out["inner_states"][layer_id],
-                            "src_lengths": sample["target_lengths"],
-                        },
-                        "id": sample["id"],
-                    }
-            else:
-                task_sample = {
-                    "net_input": {
-                        "src_tokens": sample["multitask"][task_name]["net_input"][
-                            "prev_output_tokens"
-                        ],
-                        "encoder_out": {
-                            "encoder_out": [model_out["encoder_states"][layer_id]],
-                            "encoder_padding_mask": model_out["encoder_padding_mask"],
-                        },
-                    }
-                }
-
-            for key in ["target", "target_lengths", "ntokens"]:
-                task_sample[key] = sample["multitask"][task_name][key]
-
-            task_loss, task_sample_size, task_logging_output = task_criterion(
-                model.multitask_decoders[task_name], task_sample
-            )
-
-            loss = loss + self.multitask_loss_weight[task_name] * task_loss
-            task_logging_output["loss_weight"] = self.multitask_loss_weight[task_name]
-            logging_output[task_name] = task_logging_output
-        return loss, logging_output
-
-    @classmethod
-    def reduce_metrics(cls, logging_outputs) -> None:
-        for task_name in logging_outputs[0]["multitask"].keys():
-            # different criterion may return different logging
-            # currently only reduce on loss, the most common one
-            # ideally the way that losses are reduced should also depend on the task type
-            loss_sum = sum(
-                log["multitask"][task_name].get("loss", 0) for log in logging_outputs
-            )
-            sample_size = sum(
-                log["multitask"][task_name].get("sample_size", 0)
-                for log in logging_outputs
-            )
-
-            metrics.log_scalar(
-                f"multitask_{task_name}_loss",
-                loss_sum / sample_size / math.log(2),
-                sample_size,
-                round=3,
-            )
-
-            loss_weight = logging_outputs[0]["multitask"][task_name].get(
-                "loss_weight", 0
-            )
-            metrics.log_scalar(
-                f"multitask_{task_name}_loss_weight",
-                loss_weight,
-                weight=0,
-                priority=250,
-            )
-
-
-@register_criterion(
-    "speech_to_unit", dataclass=LabelSmoothedCrossEntropyCriterionConfig
-)
-class SpeechToUnitMultitaskTaskCriterion(
-    LabelSmoothedCrossEntropyCriterion, MultitaskCriterion
-):
-    def __init__(
-        self,
-        task,
-        sentence_avg,
-        label_smoothing,
-        ignore_prefix_size=0,
-        report_accuracy=False,
-    ):
-        super().__init__(
-            task, sentence_avg, label_smoothing, ignore_prefix_size, report_accuracy
-        )
-        MultitaskCriterion.__init__(self, task.multitask_tasks)
-
-    def forward(self, model, sample, reduce=True):
-        net_output, extra = model(
-            src_tokens=sample["net_input"]["src_tokens"],
-            src_lengths=sample["net_input"]["src_lengths"],
-            prev_output_tokens=sample["net_input"]["prev_output_tokens"],
-            tgt_speaker=sample["net_input"]["tgt_speaker"],
-            return_all_hiddens=True,
-        )
-
-        loss, nll_loss = self.compute_loss(model, [net_output], sample, reduce=reduce)
-        sample_size = (
-            sample["target"].size(0) if self.sentence_avg else sample["ntokens"]
-        )
-        logging_output = {
-            "loss": loss.data,
-            "nll_loss": nll_loss.data,
-            "ntokens": sample["ntokens"],
-            "nsentences": sample["target"].size(0),
-            "sample_size": sample_size,
-        }
-        if self.report_accuracy:
-            n_correct, total = self.compute_accuracy(model, [net_output], sample)
-            logging_output["n_correct"] = utils.item(n_correct.data)
-            logging_output["total"] = utils.item(total.data)
-
-        if len(self.multitask_criterion) == 0:
-            return loss, sample_size, logging_output
-
-        # multitask
-        multitask_loss, multitask_log = self.get_multitask_loss(model, sample, extra)
-        loss += multitask_loss
-        logging_output["multitask"] = multitask_log
-
-        return loss, sample_size, logging_output
-
-    @classmethod
-    def reduce_metrics(cls, logging_outputs) -> None:
-        super().reduce_metrics(logging_outputs)
-
-        # inference metrics
-        if "targ_frames" in logging_outputs[0]:
-            n = sum(log.get("norm_frames", 0) for log in logging_outputs)
-            for key, new_key in [
-                ("mcd_loss", "mcd_loss"),
-                ("pred_frames", "pred_ratio"),
-                ("nins", "ins_rate"),
-                ("ndel", "del_rate"),
-            ]:
-                val = sum(log.get(key, 0) for log in logging_outputs)
-                metrics.log_scalar(new_key, val / n, n, round=3)
-
-        if "multitask" not in logging_outputs[0]:
-            return
-
-        MultitaskCriterion.reduce_metrics(logging_outputs)
-
-    @staticmethod
-    def logging_outputs_can_be_summed() -> bool:
-        """
-        Whether the logging outputs returned by `forward` can be summed
-        across workers prior to calling `reduce_metrics`. Setting this
-        to True will improves distributed training speed.
-        """
-        return False
-
-
-@register_criterion("speech_to_spectrogram", dataclass=Tacotron2CriterionConfig)
-class SpeechToSpectrogramMultitaskTaskCriterion(Tacotron2Criterion, MultitaskCriterion):
-    def __init__(
-        self,
-        task,
-        sentence_avg,
-        use_guided_attention_loss,
-        guided_attention_loss_sigma,
-        bce_pos_weight,
-        ctc_weight,
-    ):
-        super().__init__(
-            task,
-            sentence_avg,
-            use_guided_attention_loss,
-            guided_attention_loss_sigma,
-            bce_pos_weight,
-            ctc_weight,
-        )
-        MultitaskCriterion.__init__(self, task.multitask_tasks)
-
-    def forward(self, model, sample, reduction="mean"):
-        bsz, max_len, _ = sample["target"].size()
-        feat_tgt = sample["target"]
-        feat_len = sample["target_lengths"].view(bsz, 1).expand(-1, max_len)
-        eos_tgt = torch.arange(max_len).to(sample["target"].device)
-        eos_tgt = eos_tgt.view(1, max_len).expand(bsz, -1)
-        eos_tgt = (eos_tgt == (feat_len - 1)).float()
-
-        feat_out, eos_out, extra = model(
-            src_tokens=sample["net_input"]["src_tokens"],
-            src_lengths=sample["net_input"]["src_lengths"],
-            prev_output_tokens=sample["net_input"]["prev_output_tokens"],
-            tgt_speaker=sample["net_input"]["tgt_speaker"],
-            target_lengths=sample["target_lengths"],
-            return_all_hiddens=True,
-        )
-
-        l1_loss, mse_loss, eos_loss = self.compute_loss(
-            extra["feature_out"],
-            feat_out,
-            eos_out,
-            feat_tgt,
-            eos_tgt,
-            sample["target_lengths"],
-            reduction,
-        )
-        attn_loss = torch.tensor(0.0).type_as(l1_loss)
-        if self.guided_attn is not None:
-            attn_loss = self.guided_attn(
-                extra["attn"],
-                sample["net_input"]["src_lengths"],
-                sample["target_lengths"],
-                reduction,
-            )
-        loss = (
-            l1_loss + mse_loss + eos_loss + attn_loss
-        )  # do not include ctc loss as there's no text target
-
-        sample_size = sample["nsentences"] if self.sentence_avg else sample["ntokens"]
-        logging_output = {
-            "loss": utils.item(loss.data),
-            "ntokens": sample["ntokens"],
-            "nsentences": sample["nsentences"],
-            "sample_size": sample_size,
-            "l1_loss": utils.item(l1_loss.data),
-            "mse_loss": utils.item(mse_loss.data),
-            "eos_loss": utils.item(eos_loss.data),
-            "attn_loss": utils.item(attn_loss.data),
-        }
-
-        if len(self.multitask_criterion) == 0:
-            return loss, sample_size, logging_output
-
-        # multitask
-        multitask_loss, multitask_log = self.get_multitask_loss(model, sample, extra)
-        loss += multitask_loss
-        logging_output["multitask"] = multitask_log
-        return loss, sample_size, logging_output
-
-    @classmethod
-    def reduce_metrics(cls, logging_outputs) -> None:
-        super().reduce_metrics(logging_outputs)
-
-        # inference metrics
-        if "targ_frames" in logging_outputs[0]:
-            n = sum(log.get("norm_frames", 0) for log in logging_outputs)
-            for key, new_key in [
-                ("mcd_loss", "mcd_loss"),
-                ("pred_frames", "pred_ratio"),
-                ("nins", "ins_rate"),
-                ("ndel", "del_rate"),
-            ]:
-                val = sum(log.get(key, 0) for log in logging_outputs)
-                metrics.log_scalar(new_key, val / n, n, round=3)
-
-        if "multitask" not in logging_outputs[0]:
-            return
-
-        MultitaskCriterion.reduce_metrics(logging_outputs)
diff --git a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/fairseq/data/sort_dataset.py b/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/fairseq/data/sort_dataset.py
deleted file mode 100644
index b3890e7279e1f26db2e48ec0a91c639e9299d60f..0000000000000000000000000000000000000000
--- a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/fairseq/data/sort_dataset.py
+++ /dev/null
@@ -1,21 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import numpy as np
-
-from . import BaseWrapperDataset
-
-
-class SortDataset(BaseWrapperDataset):
-    def __init__(self, dataset, sort_order):
-        super().__init__(dataset)
-        if not isinstance(sort_order, (list, tuple)):
-            sort_order = [sort_order]
-        self.sort_order = sort_order
-
-        assert all(len(so) == len(dataset) for so in sort_order)
-
-    def ordered_indices(self):
-        return np.lexsort(self.sort_order)
diff --git a/spaces/asd123Xiao/kafuu_chino_sovits4.0/vdecoder/__init__.py b/spaces/asd123Xiao/kafuu_chino_sovits4.0/vdecoder/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/aseuteurideu/audio_deepfake_detector/models/TMC.py b/spaces/aseuteurideu/audio_deepfake_detector/models/TMC.py
deleted file mode 100644
index 09ea4821f7181900aff7d8af18bf0e1323b4e7e2..0000000000000000000000000000000000000000
--- a/spaces/aseuteurideu/audio_deepfake_detector/models/TMC.py
+++ /dev/null
@@ -1,156 +0,0 @@
-import torch
-import torch.nn as nn
-from models import image
-import torch.nn.functional as F
-
-
-# loss function
-def KL(alpha, c):
-    if torch.cuda.is_available():
-        beta = torch.ones((1, c)).cuda()
-    else:
-        beta = torch.ones((1, c))
-    S_alpha = torch.sum(alpha, dim=1, keepdim=True)
-    S_beta = torch.sum(beta, dim=1, keepdim=True)
-    lnB = torch.lgamma(S_alpha) - torch.sum(torch.lgamma(alpha), dim=1, keepdim=True)
-    lnB_uni = torch.sum(torch.lgamma(beta), dim=1, keepdim=True) - torch.lgamma(S_beta)
-    dg0 = torch.digamma(S_alpha)
-    dg1 = torch.digamma(alpha)
-    kl = torch.sum((alpha - beta) * (dg1 - dg0), dim=1, keepdim=True) + lnB + lnB_uni
-    return kl
-
-def ce_loss(p, alpha, c, global_step, annealing_step):
-    S = torch.sum(alpha, dim=1, keepdim=True)
-    E = alpha - 1
-    label = p
-    A = torch.sum(label * (torch.digamma(S) - torch.digamma(alpha)), dim=1, keepdim=True)
-
-    annealing_coef = min(1, global_step / annealing_step)
-    alp = E * (1 - label) + 1
-    B = annealing_coef * KL(alp, c)
-    return torch.mean((A + B))
-
-
-class TMC(nn.Module):
-    def __init__(self, args):
-        super(TMC, self).__init__()
-        self.args = args
-        self.rgbenc = image.ImageEncoder(args)
-        self.specenc = image.RawNet(args)
-        
-        spec_last_size = args.img_hidden_sz * 1
-        rgb_last_size = args.img_hidden_sz * args.num_image_embeds
-        self.spec_depth = nn.ModuleList()
-        self.clf_rgb = nn.ModuleList()
-
-        for hidden in args.hidden:
-            self.spec_depth.append(nn.Linear(spec_last_size, hidden))
-            self.spec_depth.append(nn.ReLU())
-            self.spec_depth.append(nn.Dropout(args.dropout))
-            spec_last_size = hidden
-        self.spec_depth.append(nn.Linear(spec_last_size, args.n_classes))
-
-        for hidden in args.hidden:
-            self.clf_rgb.append(nn.Linear(rgb_last_size, hidden))
-            self.clf_rgb.append(nn.ReLU())
-            self.clf_rgb.append(nn.Dropout(args.dropout))
-            rgb_last_size = hidden
-        self.clf_rgb.append(nn.Linear(rgb_last_size, args.n_classes))
-
-    def DS_Combin_two(self, alpha1, alpha2):
-        # Calculate the merger of two DS evidences
-        alpha = dict()
-        alpha[0], alpha[1] = alpha1, alpha2
-        b, S, E, u = dict(), dict(), dict(), dict()
-        for v in range(2):
-            S[v] = torch.sum(alpha[v], dim=1, keepdim=True)
-            E[v] = alpha[v] - 1
-            b[v] = E[v] / (S[v].expand(E[v].shape))
-            u[v] = self.args.n_classes / S[v]
-
-        # b^0 @ b^(0+1)
-        bb = torch.bmm(b[0].view(-1, self.args.n_classes, 1), b[1].view(-1, 1, self.args.n_classes))
-        # b^0 * u^1
-        uv1_expand = u[1].expand(b[0].shape)
-        bu = torch.mul(b[0], uv1_expand)
-        # b^1 * u^0
-        uv_expand = u[0].expand(b[0].shape)
-        ub = torch.mul(b[1], uv_expand)
-        # calculate K
-        bb_sum = torch.sum(bb, dim=(1, 2), out=None)
-        bb_diag = torch.diagonal(bb, dim1=-2, dim2=-1).sum(-1)
-        # bb_diag1 = torch.diag(torch.mm(b[v], torch.transpose(b[v+1], 0, 1)))
-        K = bb_sum - bb_diag
-
-        # calculate b^a
-        b_a = (torch.mul(b[0], b[1]) + bu + ub) / ((1 - K).view(-1, 1).expand(b[0].shape))
-        # calculate u^a
-        u_a = torch.mul(u[0], u[1]) / ((1 - K).view(-1, 1).expand(u[0].shape))
-        # test = torch.sum(b_a, dim = 1, keepdim = True) + u_a #Verify programming errors
-
-        # calculate new S
-        S_a = self.args.n_classes / u_a
-        # calculate new e_k
-        e_a = torch.mul(b_a, S_a.expand(b_a.shape))
-        alpha_a = e_a + 1
-        return alpha_a
-
-    def forward(self, rgb, spec):
-        spec = self.specenc(spec)
-        spec = torch.flatten(spec, start_dim=1)
-
-        rgb = self.rgbenc(rgb)
-        rgb = torch.flatten(rgb, start_dim=1)
-
-        spec_out = spec
-
-        for layer in self.spec_depth:
-            spec_out = layer(spec_out)
-
-        rgb_out = rgb
-
-        for layer in self.clf_rgb:
-            rgb_out = layer(rgb_out)
-
-        spec_evidence, rgb_evidence = F.softplus(spec_out), F.softplus(rgb_out)
-        spec_alpha, rgb_alpha = spec_evidence+1, rgb_evidence+1
-        spec_rgb_alpha = self.DS_Combin_two(spec_alpha, rgb_alpha)
-        return spec_alpha, rgb_alpha, spec_rgb_alpha
-
-
-class ETMC(TMC):
-    def __init__(self, args):
-        super(ETMC, self).__init__(args)
-        last_size = args.img_hidden_sz * args.num_image_embeds + args.img_hidden_sz * args.num_image_embeds
-        self.clf = nn.ModuleList()
-        for hidden in args.hidden:
-            self.clf.append(nn.Linear(last_size, hidden))
-            self.clf.append(nn.ReLU())
-            self.clf.append(nn.Dropout(args.dropout))
-            last_size = hidden
-        self.clf.append(nn.Linear(last_size, args.n_classes))
-
-    def forward(self, rgb, spec):
-        spec = self.specenc(spec)
-        spec = torch.flatten(spec, start_dim=1)
-
-        rgb = self.rgbenc(rgb)
-        rgb = torch.flatten(rgb, start_dim=1)
-
-        spec_out = spec
-        for layer in self.spec_depth:
-            spec_out = layer(spec_out)
-
-        rgb_out = rgb
-        for layer in self.clf_rgb:
-            rgb_out = layer(rgb_out)
-
-        pseudo_out = torch.cat([rgb, spec], -1)
-        for layer in self.clf:
-            pseudo_out = layer(pseudo_out)
-
-        depth_evidence, rgb_evidence, pseudo_evidence = F.softplus(spec_out), F.softplus(rgb_out), F.softplus(pseudo_out)
-        depth_alpha, rgb_alpha, pseudo_alpha = depth_evidence+1, rgb_evidence+1, pseudo_evidence+1
-        depth_rgb_alpha = self.DS_Combin_two(self.DS_Combin_two(depth_alpha, rgb_alpha), pseudo_alpha)
-        return depth_alpha, rgb_alpha, pseudo_alpha, depth_rgb_alpha
-
diff --git a/spaces/ashhadahsan/ai-book-generator/prompts.py b/spaces/ashhadahsan/ai-book-generator/prompts.py
deleted file mode 100644
index 978df7ba282a39f169d6ad31ac3d707787b6f9c3..0000000000000000000000000000000000000000
--- a/spaces/ashhadahsan/ai-book-generator/prompts.py
+++ /dev/null
@@ -1,46 +0,0 @@
-def get_initial_prompts(
-    key,
-    type_of_main_character,
-    main_character_name,
-    skill_development,
-    learning_objectives,
-    theme,
-    topic,
-):
-
-    prompts = {
-        "Fairy tales": f"I am a land far far away there was a {type_of_main_character} who is famous by the name {main_character_name} . {main_character_name} always had a  good{skill_development} and the story revolves around {learning_objectives} ,once can learn about {theme}. This is a famous topic consisting of {topic} for childrens "
-    }
-
-    return prompts.get(key)
-
-
-def story_setting_prompt(
-    key,
-    type_of_main_character,
-    main_character_name,
-    skill_development,
-    learning_objectives,
-    theme,
-    mood_of_story,
-    ant_name,
-    ant_type,
-):
-    prompts = {
-        "Fairy tales": f"{main_character_name} was always inclined towards {mood_of_story} but there was a {ant_type} famoulsy known as {ant_name} the {ant_type} who did not like {main_character_name}"
-    }
-    return prompts.get(key)
-
-
-def supporting_character_inclusion(key, sup_name, sup_type, positive_messaging):
-    prompts = {
-        "Fairy tales": f"Our hero who was always a supporter of {positive_messaging} had an friend named {sup_name} who was a {sup_type}"
-    }
-    return prompts.get(key)
-
-
-def ending_scene(key, resolution, main_char, positive_mess):
-    prompts = {
-        "Fairy tales": f"So this concludes that {main_char} was focused on getting {positive_mess} out for the world which resulted in {resolution}"
-    }
-    return prompts.get(key)
diff --git a/spaces/atharvat80/Wikipedia2Vec-NED/app.py b/spaces/atharvat80/Wikipedia2Vec-NED/app.py
deleted file mode 100644
index 8038f6d23d5d2faf9fa2f42e1a772fc01a600611..0000000000000000000000000000000000000000
--- a/spaces/atharvat80/Wikipedia2Vec-NED/app.py
+++ /dev/null
@@ -1,113 +0,0 @@
-import pandas as pd
-import streamlit as st
-from transformers import AutoModelForTokenClassification, AutoTokenizer, pipeline
-
-from src import GBRT, wikidata_search, google_search
-
-TYPE = {
-    'LOC': ' location',
-    'PER': ' person',
-    'ORG': ' organization',
-    'MISC': ''
-}
-
-COLOR = {
-    'LOC': '#10B981',
-    'PER': '#0EA5E9',
-    'ORG': '#A855F7',
-    'MISC': '#F97316'
-}
-
-# ---------------------------------------------------------------------------
-# Loading models
-# ---------------------------------------------------------------------------
-
-
-@st.cache(allow_output_mutation=True, show_spinner=True)
-def load_models():
-    # NER
-    tokenizer = AutoTokenizer.from_pretrained("dslim/bert-base-NER")
-    bert_ner = AutoModelForTokenClassification.from_pretrained("dslim/bert-base-NER")
-    tagger = pipeline("token-classification", model=bert_ner, tokenizer=tokenizer,
-                      device=-1, aggregation_strategy="average")
-    # NED
-    model = GBRT()
-    return model, tagger
-
-
-# ---------------------------------------------------------------------------
-# Page setup
-# ---------------------------------------------------------------------------
-st.set_page_config(layout="wide", page_title='Named Entity Disambiguation')
-col1, col2 = st.columns(2)
-
-
-# ---------------------------------------------------------------------------
-# Candidate Generation
-# ---------------------------------------------------------------------------
-def get_candidates(mentions_tags):
-    candidates = []
-    cache = {}
-    for mention, tag in mentions_tags:
-        if (mention, tag) in cache.keys():
-            candidates.append((mention, cache[(mention, tag)]))
-        else:
-            cands = wikidata_search(mention, limit=3)
-            if cands == [] and tag != 'PER':
-                cands = google_search(mention, limit=3)
-            cache[(mention, tag)] = cands
-            candidates.append((mention, cands))
-            print(mention, cands)
-    return candidates
-
-
-# ---------------------------------------------------------------------------
-# Rendering Setup
-# ---------------------------------------------------------------------------
-def display_tag(text, typ, label):
-    if label != 'NIL':
-        return f'[<span style="color: {COLOR[typ]}" class="tag">**{text}** <small>{typ}</small></span>](https://en.wikipedia.org/wiki/{label})'
-    else:
-        return f'<span style="color: #EF4444" class="tag">**{text}** <small>{typ}</small></span>'
-
-
-# ---------------------------------------------------------------------------
-# Full Pipeline
-# ---------------------------------------------------------------------------
-def main(text):
-    # text = text.replace('\n', ' ')
-    ner_results = tagger(text)
-    tagged, last_pos = '', 0
-
-    with st.spinner('Generating Candidates'):
-        mentions_cands = get_candidates([(res['word'], res['entity_group']) for res in ner_results])
-
-    with st.spinner('Disambiguating Mentions'):
-        preditions = model.link(mentions_cands, text)
-
-    with st.spinner('Rendering Results'):
-        for i, res in enumerate(ner_results):
-            tag = display_tag(res['word'], res['entity_group'], preditions[i][1])
-            tagged += text[last_pos:res['start']] + tag
-            last_pos = res['end']
-        tagged += text[last_pos:]
-
-    with col2:
-        st.write("### Disambiguated Text")
-        st.markdown("<style>a {text-decoration: none;} small {color: inherit !important} .tag {border: 1px solid; border-radius: 5px; padding: 0px 3px; white-space: nowrap}</style>", unsafe_allow_html=True)
-        st.write(tagged, unsafe_allow_html=True)
-
-    df = pd.DataFrame(data=preditions, columns=['Mention', 'Prediction', 'Confidence'])
-    st.write("**Additional Information**")
-    st.markdown("<style>tbody th {display:none} .blank {display:none}</style>", unsafe_allow_html=True)
-    st.table(df)
-
-
-if __name__ == '__main__': 
-    model, tagger = load_models()
-    with col1:
-        st.write("### Input Text")
-        user_input = st.text_area('Press Ctrl + Enter to update results',
-                                  'George Washington went to Washington.', height=350)
-        if user_input:
-            main(user_input)
diff --git a/spaces/awacke1/03StreamlitVideoASRNLP/app.py b/spaces/awacke1/03StreamlitVideoASRNLP/app.py
deleted file mode 100644
index e0f03cf2557eba112bf95ebf5eb582da8d8a0fe3..0000000000000000000000000000000000000000
--- a/spaces/awacke1/03StreamlitVideoASRNLP/app.py
+++ /dev/null
@@ -1,119 +0,0 @@
-from collections import deque
-import streamlit as st
-import torch
-from streamlit_player import st_player
-from transformers import AutoModelForCTC, Wav2Vec2Processor
-from streaming import ffmpeg_stream
-
-device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-player_options = {
-    "events": ["onProgress"],
-    "progress_interval": 200,
-    "volume": 1.0,
-    "playing": True,
-    "loop": False,
-    "controls": False,
-    "muted": False,
-    "config": {"youtube": {"playerVars": {"start": 1}}},
-}
-
-# disable rapid fading in and out on `st.code` updates
-st.markdown("<style>.element-container{opacity:1 !important}</style>", unsafe_allow_html=True)
-
-@st.cache(hash_funcs={torch.nn.parameter.Parameter: lambda _: None})
-def load_model(model_path="facebook/wav2vec2-large-robust-ft-swbd-300h"):
-    processor = Wav2Vec2Processor.from_pretrained(model_path)
-    model = AutoModelForCTC.from_pretrained(model_path).to(device)
-    return processor, model
-    
-processor, model = load_model()
-
-def stream_text(url, chunk_duration_ms, pad_duration_ms):
-    sampling_rate = processor.feature_extractor.sampling_rate
-
-    # calculate the length of logits to cut from the sides of the output to account for input padding
-    output_pad_len = model._get_feat_extract_output_lengths(int(sampling_rate * pad_duration_ms / 1000))
-
-    # define the audio chunk generator
-    stream = ffmpeg_stream(url, sampling_rate, chunk_duration_ms=chunk_duration_ms, pad_duration_ms=pad_duration_ms)
-
-    leftover_text = ""
-    for i, chunk in enumerate(stream):
-        input_values = processor(chunk, sampling_rate=sampling_rate, return_tensors="pt").input_values
-
-        with torch.no_grad():
-            logits = model(input_values.to(device)).logits[0]
-            if i > 0:
-                logits = logits[output_pad_len : len(logits) - output_pad_len]
-            else:  # don't count padding at the start of the clip
-                logits = logits[: len(logits) - output_pad_len]
-
-            predicted_ids = torch.argmax(logits, dim=-1).cpu().tolist()
-            if processor.decode(predicted_ids).strip():
-                leftover_ids = processor.tokenizer.encode(leftover_text)
-                # concat the last word (or its part) from the last frame with the current text
-                text = processor.decode(leftover_ids + predicted_ids)
-                # don't return the last word in case it's just partially recognized
-                text, leftover_text = text.rsplit(" ", 1)
-                yield text
-            else:
-                yield leftover_text
-                leftover_text = ""
-    yield leftover_text
-
-def main():
-    state = st.session_state
-    st.header("Video ASR Streamlit from Youtube Link")
-
-    with st.form(key="inputs_form"):
-    
-        # Our worlds best teachers on subjects of AI, Cognitive, Neuroscience for our Behavioral and Medical Health
-        ytJoschaBach="https://youtu.be/cC1HszE5Hcw?list=PLHgX2IExbFouJoqEr8JMF5MbZSbyC91-L&t=8984"
-        ytSamHarris="https://www.youtube.com/watch?v=4dC_nRYIDZU&list=PLHgX2IExbFouJoqEr8JMF5MbZSbyC91-L&index=2"
-        ytJohnAbramson="https://www.youtube.com/watch?v=arrokG3wCdE&list=PLHgX2IExbFouJoqEr8JMF5MbZSbyC91-L&index=3"
-        ytElonMusk="https://www.youtube.com/watch?v=DxREm3s1scA&list=PLHgX2IExbFouJoqEr8JMF5MbZSbyC91-L&index=4"
-        ytJeffreyShainline="https://www.youtube.com/watch?v=EwueqdgIvq4&list=PLHgX2IExbFouJoqEr8JMF5MbZSbyC91-L&index=5"
-        ytJeffHawkins="https://www.youtube.com/watch?v=Z1KwkpTUbkg&list=PLHgX2IExbFouJoqEr8JMF5MbZSbyC91-L&index=6"
-        ytSamHarris="https://youtu.be/Ui38ZzTymDY?list=PLHgX2IExbFouJoqEr8JMF5MbZSbyC91-L"
-        ytSamHarris="https://youtu.be/4dC_nRYIDZU?list=PLHgX2IExbFouJoqEr8JMF5MbZSbyC91-L&t=7809"
-        ytSamHarris="https://youtu.be/4dC_nRYIDZU?list=PLHgX2IExbFouJoqEr8JMF5MbZSbyC91-L&t=7809"
-        ytSamHarris="https://youtu.be/4dC_nRYIDZU?list=PLHgX2IExbFouJoqEr8JMF5MbZSbyC91-L&t=7809"
-        ytTimelapseAI="https://www.youtube.com/watch?v=63yr9dlI0cU&list=PLHgX2IExbFovQybyfltywXnqZi5YvaSS-"
-        state.youtube_url = st.text_input("YouTube URL", ytTimelapseAI)
-        
-        
-        state.chunk_duration_ms = st.slider("Audio chunk duration (ms)", 2000, 10000, 3000, 100)
-        state.pad_duration_ms = st.slider("Padding duration (ms)", 100, 5000, 1000, 100)
-        submit_button = st.form_submit_button(label="Submit")
-
-    if submit_button or "asr_stream" not in state:
-        # a hack to update the video player on value changes
-        state.youtube_url = (
-            state.youtube_url.split("&hash=")[0]
-            + f"&hash={state.chunk_duration_ms}-{state.pad_duration_ms}"
-        )
-        state.asr_stream = stream_text(
-            state.youtube_url, state.chunk_duration_ms, state.pad_duration_ms
-        )
-        state.chunks_taken = 0
-        
-        
-        state.lines = deque([], maxlen=100)  # limit to the last n lines of subs
-        
-
-    player = st_player(state.youtube_url, **player_options, key="youtube_player")
-
-    if "asr_stream" in state and player.data and player.data["played"] < 1.0:
-        # check how many seconds were played, and if more than processed - write the next text chunk
-        processed_seconds = state.chunks_taken * (state.chunk_duration_ms / 1000)
-        if processed_seconds < player.data["playedSeconds"]:
-            text = next(state.asr_stream)
-            state.lines.append(text)
-            state.chunks_taken += 1
-    if "lines" in state:
-        # print the lines of subs
-        st.code("\n".join(state.lines))
-
-
-if __name__ == "__main__":
-    main()
\ No newline at end of file
diff --git a/spaces/awacke1/ChatGPTStreamlit4/README.md b/spaces/awacke1/ChatGPTStreamlit4/README.md
deleted file mode 100644
index 30348695228896b69061451eef58dd9d902016f8..0000000000000000000000000000000000000000
--- a/spaces/awacke1/ChatGPTStreamlit4/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: ChatGPTStreamlit4
-emoji: 👁
-colorFrom: green
-colorTo: yellow
-sdk: streamlit
-sdk_version: 1.21.0
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/awacke1/NLPSentenceSimilarityHeatmap/README.md b/spaces/awacke1/NLPSentenceSimilarityHeatmap/README.md
deleted file mode 100644
index bd70f5e6dc293b9a1b567c5f62b0d1959bfb658d..0000000000000000000000000000000000000000
--- a/spaces/awacke1/NLPSentenceSimilarityHeatmap/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: ♨️NLPSentenceSimilarityHeatmapCluster🗺️Streamlit
-emoji: ♨️Heat🗺️
-colorFrom: gray
-colorTo: pink
-sdk: streamlit
-sdk_version: 1.10.0
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/baby123/sd/header_patch.py b/spaces/baby123/sd/header_patch.py
deleted file mode 100644
index 464447c8cfb431f96098a1cbd95835596a5457bb..0000000000000000000000000000000000000000
--- a/spaces/baby123/sd/header_patch.py
+++ /dev/null
@@ -1,37 +0,0 @@
-        with gr.Box(visible=os.environ.get("SPACE_ID")):
-            if os.environ.get("SPACE_ID") and str(os.environ.get("IS_SHARED_UI", "") or "") not in ("", "0"):
-                import torch
-                if not torch.cuda.is_available():
-                    gr.HTML(f"""
-                    <div class="gr-prose" style="max-width: 80%; font-size: 12px; line-height: 20px; font-family: monospace;">
-                        <p>▲ Automatic1111's Stable Diffusion WebUI + Mikubill's ControlNet WebUI extension | Running on Hugging Face | Loaded checkpoint: <a href="https://civitai.com/models/8124/a-to-zovya-rpg-artists-tools-15-and-21" style="target=" _blank"="">AtoZovyaRPGArtistTools15_sd15V1</a></p>
-                        <p>▲ Docker build from <a href="https://github.com/kalaspuff/stable-diffusion-webui-controlnet-docker" style="target=" _blank"="">🐙 GitHub ➔ kalaspuff/stable-diffusion-webui-controlnet-docker</a> / <a href="https://huggingface.co/spaces/carloscar/stable-diffusion-webui-controlnet-docker" style="target=" _blank"="">🤗 Hugging Face ➔ carloscar/stable-diffusion-webui-controlnet-docker</a></p>
-                        <p>▲ Duplicate this Space to run it privately without a queue, use a GPU for faster generation times, load custom checkpoints, etc.&nbsp;&nbsp;<a style="display:inline-block; position: absolute;" target="_blank" href="https://huggingface.co/spaces/{os.environ["SPACE_ID"]}?duplicate=true"><img style="margin: 0; height: 16px; position: relative; top: 2px;" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Duplicate%20Space-blue" alt="Duplicate Space"></a></p>
-                    </div>
-                    """)
-                else:
-                    gr.HTML(f"""
-                    <div class="gr-prose" style="max-width: 80%; font-size: 12px; line-height: 20px; font-family: monospace;">
-                        <p>▲ Automatic1111's Stable Diffusion WebUI + Mikubill's ControlNet WebUI extension | Running on Hugging Face | Loaded checkpoint: <a href="https://civitai.com/models/8124/a-to-zovya-rpg-artists-tools-15-and-21" style="target=" _blank"="">AtoZovyaRPGArtistTools15_sd15V1</a></p>
-                        <p>▲ Docker build from <a href="https://github.com/kalaspuff/stable-diffusion-webui-controlnet-docker" style="target=" _blank"="">🐙 GitHub ➔ kalaspuff/stable-diffusion-webui-controlnet-docker</a> / <a href="https://huggingface.co/spaces/carloscar/stable-diffusion-webui-controlnet-docker" style="target=" _blank"="">🤗 Hugging Face ➔ carloscar/stable-diffusion-webui-controlnet-docker</a></p>
-                        <p>▲ Duplicate this Space to run it privately without a queue, use extensions, load custom checkpoints, etc.&nbsp;&nbsp;<a style="display:inline-block; position: absolute;" target="_blank" href="https://huggingface.co/spaces/{os.environ["SPACE_ID"]}?duplicate=true"><img style="margin: 0; height: 16px; position: relative; top: 2px;" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Duplicate%20Space-blue" alt="Duplicate Space"></a></p>
-                    </div>
-                    """)
-            elif os.environ.get("SPACE_ID"):
-                import torch
-                if not torch.cuda.is_available():
-                    gr.HTML(f"""
-                    <div class="gr-prose" style="max-width: 80%; font-size: 12px; line-height: 20px; font-family: monospace;">
-                        <p>▲ Docker build from <a href="https://github.com/kalaspuff/stable-diffusion-webui-controlnet-docker" style="target=" _blank"="">🐙 GitHub ➔ kalaspuff/stable-diffusion-webui-controlnet-docker</a> / <a href="https://huggingface.co/spaces/carloscar/stable-diffusion-webui-controlnet-docker" style="target=" _blank"="">🤗 Hugging Face ➔ carloscar/stable-diffusion-webui-controlnet-docker</a></p>
-                        <p>▲ Load additional checkpoints, VAE, LoRA models, etc. Read more on the README at the GitHub link above.</p>
-                        <p>▲ This Space is currently running on CPU, which may yield very slow results - you can upgrade for a GPU <a href="https://huggingface.co/spaces/{os.environ["SPACE_ID"]}/settings" style="text-decoration: underline" target="_blank">in the Settings tab</a></p>
-                    </div>
-                    """)
-                else:
-                    gr.HTML(f"""
-                    <div class="gr-prose" style="max-width: 80%; font-size: 12px; line-height: 20px; font-family: monospace;">
-                        <p>▲ Docker build from <a href="https://github.com/kalaspuff/stable-diffusion-webui-controlnet-docker" style="target=" _blank"="">🐙 GitHub ➔ kalaspuff/stable-diffusion-webui-controlnet-docker</a> / <a href="https://huggingface.co/spaces/carloscar/stable-diffusion-webui-controlnet-docker" style="target=" _blank"="">🤗 Hugging Face ➔ carloscar/stable-diffusion-webui-controlnet-docker</a></p>
-                        <p>▲ Load additional checkpoints, VAE, LoRA models, etc. Read more on the README at the GitHub link above.</p>
-                        <p>▲ This Space has GPU enabled - remember to remove the GPU from the space <a href="https://huggingface.co/spaces/{os.environ["SPACE_ID"]}/settings" style="text-decoration: underline" target="_blank">in the Settings tab</a> when you're done.</p>
-                    </div>
-                    """)
diff --git a/spaces/beephids/paper-llm/logging.py b/spaces/beephids/paper-llm/logging.py
deleted file mode 100644
index 8abb37a9591050408e0f183fbe721d777faed35d..0000000000000000000000000000000000000000
--- a/spaces/beephids/paper-llm/logging.py
+++ /dev/null
@@ -1,77 +0,0 @@
-#@title JSON log system prompt management
-
-class LLMPrompts:
-    def __init__(self, log_file):
-        self.prompts = []
-        self.log_file = log_file
-        self.load_prompts_from_log()
-
-    def add_prompt(self, identity, prompt, temperature):
-        self.prompts.append({'identity': identity, 'prompt': prompt, 'temperature': temperature})
-        self.save_prompts_to_log()
-
-    def remove_prompt(self, identity):
-        self.prompts = [p for p in self.prompts if p['identity'] != identity]
-        self.save_prompts_to_log()
-
-    def get_prompt(self, identity):
-        for prompt in self.prompts:
-            if prompt['identity'] == identity:
-                return prompt['prompt']
-        return None
-
-    def get_temperature(self, identity):
-        for prompt in self.prompts:
-            if prompt['identity'] == identity:
-                return prompt['temperature']
-        return None
-
-    def load_prompts_from_log(self):
-        try:
-            with open(self.log_file, 'r') as file:
-                self.prompts = json.load(file)
-        except FileNotFoundError:
-            print("No file found. Starting from scratch.")
-            pass  # Ignore if the log file is not found or cannot be read
-
-    def save_prompts_to_log(self):
-        with open(self.log_file, 'w') as file:
-            json.dump(self.prompts, file)
-            
-# Accessing prompts and temperatures
-# print(llm_prompts.get_prompt("LLM_2"))  # Output: Write a short story about a detective solving a mysterious murder case.
-# print(llm_prompts.get_temperature("LLM_2"))  # Output: 0.7
-
-
-# Adding a new prompt with temperature
-# llm_prompts.add_prompt("LLM_5", "Explain the concept of artificial intelligence.", 0.5)
-
-# Set the filepath for the log
-log_file_path = '/drive/My Drive/Colab Notebooks/llm_prompts_log.json'
-sys_prompt = LLMPrompts(log_file_path)
-
-# Print all prompts and temperatures
-for prompt in sys_prompt.prompts:
-   print(prompt['identity'], prompt['prompt'], prompt['temperature'])
-
-# Want to add personas? Do that here!
-
-# sys_prompt.add_prompt('LLM_2', "")
-
-
-
-
-# Log the last conversation
-convo_log_file_path = '/drive/My Drive/Colab Notebooks/last_conversation.json'
-
-# Convert list to JSON object
-json_object = json.dumps(context)
-
-# Save JSON object to a file
-with open('output.json', 'w') as file:
-    file.write(json_object)
-
-# Save list items as separate lines in a JSON
-# with open(convo_log_file_path, 'w') as file:
-#     for item in context:
-#         file.write(json.dumps(item) + '\n')
\ No newline at end of file
diff --git a/spaces/bhvsh/stroke-prediction/README.md b/spaces/bhvsh/stroke-prediction/README.md
deleted file mode 100644
index 30231d0d4205154abc089ecde1226f5e80f009fd..0000000000000000000000000000000000000000
--- a/spaces/bhvsh/stroke-prediction/README.md
+++ /dev/null
@@ -1,14 +0,0 @@
----
-title: Stroke Prediction
-emoji: 🧠
-colorFrom: red
-colorTo: blue
-sdk: streamlit
-sdk_version: 1.10.0
-app_file: app.py
-pinned: false
----
-# Stroke Prediction using Machine Learning
-The aim of this project is to develop a model which predicts whether a patient is likely to get a stroke based on the parameters like gender, age various diseases and smoking status.
-
-Dataset used: https://www.kaggle.com/datasets/fedesoriano/stroke-prediction-dataset
\ No newline at end of file
diff --git a/spaces/bigjoker/stable-diffusion-webui/modules/extensions.py b/spaces/bigjoker/stable-diffusion-webui/modules/extensions.py
deleted file mode 100644
index 1be7509685e5c11a6f0e44cd39d11613c8ba3e9f..0000000000000000000000000000000000000000
--- a/spaces/bigjoker/stable-diffusion-webui/modules/extensions.py
+++ /dev/null
@@ -1,107 +0,0 @@
-import os
-import sys
-import traceback
-
-import time
-import git
-
-from modules import paths, shared
-
-extensions = []
-extensions_dir = os.path.join(paths.data_path, "extensions")
-extensions_builtin_dir = os.path.join(paths.script_path, "extensions-builtin")
-
-if not os.path.exists(extensions_dir):
-    os.makedirs(extensions_dir)
-
-def active():
-    return [x for x in extensions if x.enabled]
-
-
-class Extension:
-    def __init__(self, name, path, enabled=True, is_builtin=False):
-        self.name = name
-        self.path = path
-        self.enabled = enabled
-        self.status = ''
-        self.can_update = False
-        self.is_builtin = is_builtin
-        self.version = ''
-
-        repo = None
-        try:
-            if os.path.exists(os.path.join(path, ".git")):
-                repo = git.Repo(path)
-        except Exception:
-            print(f"Error reading github repository info from {path}:", file=sys.stderr)
-            print(traceback.format_exc(), file=sys.stderr)
-
-        if repo is None or repo.bare:
-            self.remote = None
-        else:
-            try:
-                self.remote = next(repo.remote().urls, None)
-                self.status = 'unknown'
-                head = repo.head.commit
-                ts = time.asctime(time.gmtime(repo.head.commit.committed_date))
-                self.version = f'{head.hexsha[:8]} ({ts})'
-
-            except Exception:
-                self.remote = None
-
-    def list_files(self, subdir, extension):
-        from modules import scripts
-
-        dirpath = os.path.join(self.path, subdir)
-        if not os.path.isdir(dirpath):
-            return []
-
-        res = []
-        for filename in sorted(os.listdir(dirpath)):
-            res.append(scripts.ScriptFile(self.path, filename, os.path.join(dirpath, filename)))
-
-        res = [x for x in res if os.path.splitext(x.path)[1].lower() == extension and os.path.isfile(x.path)]
-
-        return res
-
-    def check_updates(self):
-        repo = git.Repo(self.path)
-        for fetch in repo.remote().fetch("--dry-run"):
-            if fetch.flags != fetch.HEAD_UPTODATE:
-                self.can_update = True
-                self.status = "behind"
-                return
-
-        self.can_update = False
-        self.status = "latest"
-
-    def fetch_and_reset_hard(self):
-        repo = git.Repo(self.path)
-        # Fix: `error: Your local changes to the following files would be overwritten by merge`,
-        # because WSL2 Docker set 755 file permissions instead of 644, this results to the error.
-        repo.git.fetch('--all')
-        repo.git.reset('--hard', 'origin')
-
-
-def list_extensions():
-    extensions.clear()
-
-    if not os.path.isdir(extensions_dir):
-        return
-
-    paths = []
-    for dirname in [extensions_dir, extensions_builtin_dir]:
-        if not os.path.isdir(dirname):
-            return
-
-        for extension_dirname in sorted(os.listdir(dirname)):
-            path = os.path.join(dirname, extension_dirname)
-            if not os.path.isdir(path):
-                continue
-
-            paths.append((extension_dirname, path, dirname == extensions_builtin_dir))
-
-    for dirname, path, is_builtin in paths:
-        extension = Extension(name=dirname, path=path, enabled=dirname not in shared.opts.disabled_extensions, is_builtin=is_builtin)
-        extensions.append(extension)
-
diff --git a/spaces/billusanda007/DeepRank/README.md b/spaces/billusanda007/DeepRank/README.md
deleted file mode 100644
index e71a50e3a34f9f358cb47e8cb4bd5a6d0b39e873..0000000000000000000000000000000000000000
--- a/spaces/billusanda007/DeepRank/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: DeepRank
-emoji: 🔥
-colorFrom: gray
-colorTo: blue
-sdk: streamlit
-sdk_version: 1.25.0
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/bioriAsaeru/text-to-voice/Apple Logic Pro X 10.4.1 MacOS [TNT][dada] BEST.md b/spaces/bioriAsaeru/text-to-voice/Apple Logic Pro X 10.4.1 MacOS [TNT][dada] BEST.md
deleted file mode 100644
index adf02023ff01959a30254481522f5e441d62018e..0000000000000000000000000000000000000000
--- a/spaces/bioriAsaeru/text-to-voice/Apple Logic Pro X 10.4.1 MacOS [TNT][dada] BEST.md	
+++ /dev/null
@@ -1,8 +0,0 @@
-<h2>Apple Logic Pro X 10.4.1 macOS [TNT][dada]</h2><br /><p><b><b>Download Zip</b> &harr; <a href="https://urloso.com/2uyRW8">https://urloso.com/2uyRW8</a></b></p><br /><br />
-
-apple logic pro x 10.4.1 macos [tnt][dada] Apple Logic Pro X Xi for Mac OSX 10.4 is an innovative new program for creating, recording, mixing, and mastering music. 
-Whether you are a professional musician or just a passionate pioneer, Logic Pro X is the ultimate tool for all your musical needs. 
-With an intuitive user interface designed to give you the absolute freedom and control you need to create your own music, Logic Pro X is the fastest-growing music editing software available. 8a78ff9644<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/brainblow/AudioCreator_Music-Audio_Generation/scripts/templates/index.html b/spaces/brainblow/AudioCreator_Music-Audio_Generation/scripts/templates/index.html
deleted file mode 100644
index 7bd3afe9d933271bb922c1a0a534dd6b86fe67bc..0000000000000000000000000000000000000000
--- a/spaces/brainblow/AudioCreator_Music-Audio_Generation/scripts/templates/index.html
+++ /dev/null
@@ -1,28 +0,0 @@
-{% extends "base.html" %}
-{% block content %}
-
-<p>
-    Welcome <span class="special">{{session['user']}}</span> to the internal MOS assistant for AudioCraft.
-    You can create custom surveys between your models, that you can
-    evaluate yourself, or with the help of your teammates, by simply
-    sharing a link!
-</p>
-
-{% for error in errors %}
-<p class="error">{{error}}</p>
-{% endfor %}
-<form method="post" action="{{url_for('index')}}" class="simple_form">
-    <div>
-        <label for="xps"> Space separated lists of XP SIGS or Grid names:
-        </label><br>
-        <textarea autofocus name="xps" rows="4" cols="30"></textarea>
-    </div>
-    <div>
-        <label> Blind study
-            <input type="checkbox" name="blind">
-        </label>
-    </div>
-    <input type="submit" value="Create study">
-<form>
-
-{% endblock %}
diff --git a/spaces/brjathu/HMR2.0/vendor/detectron2/tests/config/dir1/bad_import.py b/spaces/brjathu/HMR2.0/vendor/detectron2/tests/config/dir1/bad_import.py
deleted file mode 100644
index d7452c4dfc211223c946f22df7a2eb6bdc2cd829..0000000000000000000000000000000000000000
--- a/spaces/brjathu/HMR2.0/vendor/detectron2/tests/config/dir1/bad_import.py
+++ /dev/null
@@ -1,2 +0,0 @@
-# import from directory is not allowed
-from . import dir1a
diff --git a/spaces/bruno16/massa_qa/chain.py b/spaces/bruno16/massa_qa/chain.py
deleted file mode 100644
index 0ec7978c050a8fc0818250b345e57aeb5eb54d71..0000000000000000000000000000000000000000
--- a/spaces/bruno16/massa_qa/chain.py
+++ /dev/null
@@ -1,88 +0,0 @@
-"""This module contains functions for loading a ConversationalRetrievalChain"""
-
-import logging
-
-import wandb
-from langchain.chains import ConversationalRetrievalChain
-from langchain.chat_models import ChatOpenAI
-from langchain.embeddings import OpenAIEmbeddings
-from langchain.vectorstores import Chroma
-from prompts import load_chat_prompt
-
-
-logger = logging.getLogger(__name__)
-
-
-def load_vector_store(wandb_run: wandb.run, openai_api_key: str) -> Chroma:
-    """Load a vector store from a Weights & Biases artifact
-    Args:
-        run (wandb.run): An active Weights & Biases run
-        openai_api_key (str): The OpenAI API key to use for embedding
-    Returns:
-        Chroma: A chroma vector store object
-    """
-    # load vector store artifact
-    vector_store_artifact_dir = wandb_run.use_artifact(
-        wandb_run.config.vector_store_artifact, type="search_index"
-    ).download()
-    embedding_fn = OpenAIEmbeddings(openai_api_key=openai_api_key)
-    # load vector store
-    vector_store = Chroma(
-        embedding_function=embedding_fn, persist_directory=vector_store_artifact_dir
-    )
-
-    return vector_store
-
-
-def load_chain(wandb_run: wandb.run, vector_store: Chroma, openai_api_key: str):
-    """Load a ConversationalQA chain from a config and a vector store
-    Args:
-        wandb_run (wandb.run): An active Weights & Biases run
-        vector_store (Chroma): A Chroma vector store object
-        openai_api_key (str): The OpenAI API key to use for embedding
-    Returns:
-        ConversationalRetrievalChain: A ConversationalRetrievalChain object
-    """
-    retriever = vector_store.as_retriever()
-    llm = ChatOpenAI(
-        openai_api_key=openai_api_key,
-        model_name=wandb_run.config.model_name,
-        temperature=wandb_run.config.chat_temperature,
-        max_retries=wandb_run.config.max_fallback_retries,
-    )
-    chat_prompt_dir = wandb_run.use_artifact(
-        wandb_run.config.chat_prompt_artifact, type="prompt"
-    ).download()
-    qa_prompt = load_chat_prompt(f"{chat_prompt_dir}/chat_prompt_massa.json")
-    
-    print ( '\\n===================\\nqa_prompt = ', qa_prompt)
-    
-    qa_chain = ConversationalRetrievalChain.from_llm(
-        llm=llm,
-        chain_type="stuff",
-        retriever=retriever,
-        combine_docs_chain_kwargs={"prompt": qa_prompt},
-        return_source_documents=True,
-    )
-    return qa_chain
-
-
-def get_answer(
-    chain: ConversationalRetrievalChain,
-    question: str,
-    chat_history: list[tuple[str, str]],
-):
-    """Get an answer from a ConversationalRetrievalChain
-    Args:
-        chain (ConversationalRetrievalChain): A ConversationalRetrievalChain object
-        question (str): The question to ask
-        chat_history (list[tuple[str, str]]): A list of tuples of (question, answer)
-    Returns:
-        str: The answer to the question
-    """
-    result = chain(
-        inputs={"question": question, "chat_history": chat_history},
-        return_only_outputs=True,
-    )
-    response = f"Answer:\t{result['answer']}"
-    return response
diff --git a/spaces/cahya/persona-chatbot/app/css/chatbot.css b/spaces/cahya/persona-chatbot/app/css/chatbot.css
deleted file mode 100644
index 7b49b8df7c3da0145440b70c885c4de5381ea0db..0000000000000000000000000000000000000000
--- a/spaces/cahya/persona-chatbot/app/css/chatbot.css
+++ /dev/null
@@ -1,629 +0,0 @@
-* { margin: 0; padding: 0; }
-body {
-	background: #f0f1f2;
-	font:12px "Helvetica Neue", Impact, sans-serif;
-}
-#view-code{
-  color:#89a2b5;
-  opacity:0.7;
-  font-size:14px;
-  text-transform:uppercase;
-  font-weight:700;
-  text-decoration:none;
-  position:absolute;top:660px;
-  left:50%;margin-left:-50px;
-  z-index:200;
-}
-#view-code:hover{opacity:1;}
-#chatbox{
-	width:290px;
-	background:#fff;
-	border-radius:6px;
-	overflow:hidden;
-	height:484px;
-	position:absolute;
-	top:100px;
-	left:50%;
-	margin-left:-155px;
-	box-shadow: 2px 2px 15px rgb(50 50 50 / 10%)
-}
-
-#friendslist{
-	position:absolute;
-	top:0;
-	left:0;
-	width:290px;
-	height:484px;
-	display: block;
-}
-#topmenu{
-	height:69px;
-	width:290px;
-	border-bottom:1px solid #d8dfe3;
-}
-#topmenu span{
-	float:left;
-	width: 96px;
-    height: 70px;
-    background: url("https://static.ai-research.id/images/top-menu.png") -3px -118px no-repeat;
-}
-#topmenu span.friends{margin-bottom:-1px;}
-#topmenu span.chats{background-position:-95px 25px; cursor:pointer;}
-#topmenu span.chats:hover{background-position:-95px -46px; cursor:pointer;}
-#topmenu span.history{background-position:-190px 24px; cursor:pointer;}
-#topmenu span.history:hover{background-position:-190px -47px; cursor:pointer;}
-.friend{
-	height:70px;
-	border-bottom:1px solid #e7ebee;
-	position:relative;
-}
-.friend:hover{
-	background:#f1f4f6;
-	cursor:pointer;
-}
-.friend img{
-	width:40px;
-	border-radius:50%;
-	margin:15px;
-	float:left;
-}
-.floatingImg{
-	width:40px;
-	border-radius:50%;
-	position:absolute;
-	top:0;
-	left:12px;
-	border:3px solid #fff;
-}
-.friend p{
-	padding:15px 0 0 0;
-	float:left;
-	width:220px;
-}
-.friend p strong{
-	display: block;
-	font-weight:600;
-	font-size:15px;
-	color:#597a96;
-
-}
-.friend p span{
-	display: block;
-	font-size:13px;
-	font-weight:400;
-	color:#aab8c2;
-}
-.friend .status{
-	background:#26c281;
-	border-radius:50%;
-	width:9px;
-	height:9px;
-	position:absolute;
-	top:31px;
-	right:17px;
-}
-.friend .status.away{background:#ffce54;}
-.friend .status.inactive{background:#eaeef0;}
-#search{
-	background:#e3e9ed url("https://static.ai-research.id/images/search.png") -11px 0 no-repeat;
-	height:60px;
-	width:290px;
-	position:absolute;
-	bottom:0;
-	left:0;
-}
-#searchfield{
-	background:#e3e9ed;
-	margin:21px 0 0 55px;
-	border:none;
-	padding:0;
-	font-size:14px;
-	font-family:"Helvetica Neue", Impact, sans-serif;
-	font-weight:normal;
-	color:#8198ac;
-}
-#searchfield:focus{
-	 outline: 0;
-}
-#chatview{
-	width:290px;
-	height:484px;
-	position:absolute;
-	top:0;
-	left:0;
-	display:none;
-	background:#fff;
-}
-#profile{
-	height:153px;
-	overflow:hidden;
-	text-align:left;
-	color:#fff;
-}
-.p1 #profile{
-	background:#fff url("https://static.ai-research.id/images/flower.jpg") 0 0 no-repeat;
-	background-size: 300px 210px;
-}
-#profile .avatar{
-	width:68px;
-	border:3px solid #fff;
-	margin:23px 0 0;
-	border-radius:50%;
-}
-#profile  p{
-	font-weight:600;
-	font-size:15px;
-	margin:118px 0 -1px 15px;
-	opacity:0;
-	-webkit-transition: all 200ms cubic-bezier(0.000, 0.995, 0.990, 1.000);
-	   -moz-transition: all 200ms cubic-bezier(0.000, 0.995, 0.990, 1.000);
-	     -o-transition: all 200ms cubic-bezier(0.000, 0.995, 0.990, 1.000);
-	        transition: all 200ms cubic-bezier(0.000, 0.995, 0.990, 1.000);
-}
-#profile  p.animate{
-	margin-top:97px;
-	opacity:1;
-	-webkit-transition: all 200ms cubic-bezier(0.000, 0.995, 0.990, 1.000);
-	   -moz-transition: all 200ms cubic-bezier(0.000, 0.995, 0.990, 1.000);
-	     -o-transition: all 200ms cubic-bezier(0.000, 0.995, 0.990, 1.000);
-	        transition: all 200ms cubic-bezier(0.000, 0.995, 0.990, 1.000);
-}
-#profile  span{
-	font-weight:400;
-	font-size:11px;
-	margin: 0 0 0 15px;
-}
-#friends .persona_id {
-	display: none;
-}
-#chat-block {
-	height: 290px;
-	overflow: auto;
-	background: rgb(248,251,255);
-}
-.chat_messages{
-	opacity:0;
-	margin-top:30px;
-	width:290px;
-	overflow-y:scroll;
-	overflow-x:hidden;
-	padding-right: 20px;
-	-webkit-transition: all 200ms cubic-bezier(0.000, 0.995, 0.990, 1.000);
-	   -moz-transition: all 200ms cubic-bezier(0.000, 0.995, 0.990, 1.000);
-	     -o-transition: all 200ms cubic-bezier(0.000, 0.995, 0.990, 1.000);
-	        transition: all 200ms cubic-bezier(0.000, 0.995, 0.990, 1.000);
-}
-#chat-block .animate{
-	opacity:1;
-	margin-top:0;
-}
-#chat-block label{
-	color:#aab8c2;
-	font-weight:600;
-	font-size:12px;
-	text-align:center;
-	margin:15px 0;
-	width:290px;
-	display:block;
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diff --git a/spaces/carlosalonso/Detection-video/carpeta_deteccion/detectron2/data/build.py b/spaces/carlosalonso/Detection-video/carpeta_deteccion/detectron2/data/build.py
deleted file mode 100644
index 3fa2c6b1a5850f7b9771ff79861d008251ec8564..0000000000000000000000000000000000000000
--- a/spaces/carlosalonso/Detection-video/carpeta_deteccion/detectron2/data/build.py
+++ /dev/null
@@ -1,556 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-import itertools
-import logging
-import numpy as np
-import operator
-import pickle
-from typing import Any, Callable, Dict, List, Optional, Union
-import torch
-import torch.utils.data as torchdata
-from tabulate import tabulate
-from termcolor import colored
-
-from detectron2.config import configurable
-from detectron2.structures import BoxMode
-from detectron2.utils.comm import get_world_size
-from detectron2.utils.env import seed_all_rng
-from detectron2.utils.file_io import PathManager
-from detectron2.utils.logger import _log_api_usage, log_first_n
-
-from .catalog import DatasetCatalog, MetadataCatalog
-from .common import AspectRatioGroupedDataset, DatasetFromList, MapDataset, ToIterableDataset
-from .dataset_mapper import DatasetMapper
-from .detection_utils import check_metadata_consistency
-from .samplers import (
-    InferenceSampler,
-    RandomSubsetTrainingSampler,
-    RepeatFactorTrainingSampler,
-    TrainingSampler,
-)
-
-"""
-This file contains the default logic to build a dataloader for training or testing.
-"""
-
-__all__ = [
-    "build_batch_data_loader",
-    "build_detection_train_loader",
-    "build_detection_test_loader",
-    "get_detection_dataset_dicts",
-    "load_proposals_into_dataset",
-    "print_instances_class_histogram",
-]
-
-
-def filter_images_with_only_crowd_annotations(dataset_dicts):
-    """
-    Filter out images with none annotations or only crowd annotations
-    (i.e., images without non-crowd annotations).
-    A common training-time preprocessing on COCO dataset.
-
-    Args:
-        dataset_dicts (list[dict]): annotations in Detectron2 Dataset format.
-
-    Returns:
-        list[dict]: the same format, but filtered.
-    """
-    num_before = len(dataset_dicts)
-
-    def valid(anns):
-        for ann in anns:
-            if ann.get("iscrowd", 0) == 0:
-                return True
-        return False
-
-    dataset_dicts = [x for x in dataset_dicts if valid(x["annotations"])]
-    num_after = len(dataset_dicts)
-    logger = logging.getLogger(__name__)
-    logger.info(
-        "Removed {} images with no usable annotations. {} images left.".format(
-            num_before - num_after, num_after
-        )
-    )
-    return dataset_dicts
-
-
-def filter_images_with_few_keypoints(dataset_dicts, min_keypoints_per_image):
-    """
-    Filter out images with too few number of keypoints.
-
-    Args:
-        dataset_dicts (list[dict]): annotations in Detectron2 Dataset format.
-
-    Returns:
-        list[dict]: the same format as dataset_dicts, but filtered.
-    """
-    num_before = len(dataset_dicts)
-
-    def visible_keypoints_in_image(dic):
-        # Each keypoints field has the format [x1, y1, v1, ...], where v is visibility
-        annotations = dic["annotations"]
-        return sum(
-            (np.array(ann["keypoints"][2::3]) > 0).sum()
-            for ann in annotations
-            if "keypoints" in ann
-        )
-
-    dataset_dicts = [
-        x for x in dataset_dicts if visible_keypoints_in_image(x) >= min_keypoints_per_image
-    ]
-    num_after = len(dataset_dicts)
-    logger = logging.getLogger(__name__)
-    logger.info(
-        "Removed {} images with fewer than {} keypoints.".format(
-            num_before - num_after, min_keypoints_per_image
-        )
-    )
-    return dataset_dicts
-
-
-def load_proposals_into_dataset(dataset_dicts, proposal_file):
-    """
-    Load precomputed object proposals into the dataset.
-
-    The proposal file should be a pickled dict with the following keys:
-
-    - "ids": list[int] or list[str], the image ids
-    - "boxes": list[np.ndarray], each is an Nx4 array of boxes corresponding to the image id
-    - "objectness_logits": list[np.ndarray], each is an N sized array of objectness scores
-      corresponding to the boxes.
-    - "bbox_mode": the BoxMode of the boxes array. Defaults to ``BoxMode.XYXY_ABS``.
-
-    Args:
-        dataset_dicts (list[dict]): annotations in Detectron2 Dataset format.
-        proposal_file (str): file path of pre-computed proposals, in pkl format.
-
-    Returns:
-        list[dict]: the same format as dataset_dicts, but added proposal field.
-    """
-    logger = logging.getLogger(__name__)
-    logger.info("Loading proposals from: {}".format(proposal_file))
-
-    with PathManager.open(proposal_file, "rb") as f:
-        proposals = pickle.load(f, encoding="latin1")
-
-    # Rename the key names in D1 proposal files
-    rename_keys = {"indexes": "ids", "scores": "objectness_logits"}
-    for key in rename_keys:
-        if key in proposals:
-            proposals[rename_keys[key]] = proposals.pop(key)
-
-    # Fetch the indexes of all proposals that are in the dataset
-    # Convert image_id to str since they could be int.
-    img_ids = set({str(record["image_id"]) for record in dataset_dicts})
-    id_to_index = {str(id): i for i, id in enumerate(proposals["ids"]) if str(id) in img_ids}
-
-    # Assuming default bbox_mode of precomputed proposals are 'XYXY_ABS'
-    bbox_mode = BoxMode(proposals["bbox_mode"]) if "bbox_mode" in proposals else BoxMode.XYXY_ABS
-
-    for record in dataset_dicts:
-        # Get the index of the proposal
-        i = id_to_index[str(record["image_id"])]
-
-        boxes = proposals["boxes"][i]
-        objectness_logits = proposals["objectness_logits"][i]
-        # Sort the proposals in descending order of the scores
-        inds = objectness_logits.argsort()[::-1]
-        record["proposal_boxes"] = boxes[inds]
-        record["proposal_objectness_logits"] = objectness_logits[inds]
-        record["proposal_bbox_mode"] = bbox_mode
-
-    return dataset_dicts
-
-
-def print_instances_class_histogram(dataset_dicts, class_names):
-    """
-    Args:
-        dataset_dicts (list[dict]): list of dataset dicts.
-        class_names (list[str]): list of class names (zero-indexed).
-    """
-    num_classes = len(class_names)
-    hist_bins = np.arange(num_classes + 1)
-    histogram = np.zeros((num_classes,), dtype=np.int)
-    for entry in dataset_dicts:
-        annos = entry["annotations"]
-        classes = np.asarray(
-            [x["category_id"] for x in annos if not x.get("iscrowd", 0)], dtype=np.int
-        )
-        if len(classes):
-            assert classes.min() >= 0, f"Got an invalid category_id={classes.min()}"
-            assert (
-                classes.max() < num_classes
-            ), f"Got an invalid category_id={classes.max()} for a dataset of {num_classes} classes"
-        histogram += np.histogram(classes, bins=hist_bins)[0]
-
-    N_COLS = min(6, len(class_names) * 2)
-
-    def short_name(x):
-        # make long class names shorter. useful for lvis
-        if len(x) > 13:
-            return x[:11] + ".."
-        return x
-
-    data = list(
-        itertools.chain(*[[short_name(class_names[i]), int(v)] for i, v in enumerate(histogram)])
-    )
-    total_num_instances = sum(data[1::2])
-    data.extend([None] * (N_COLS - (len(data) % N_COLS)))
-    if num_classes > 1:
-        data.extend(["total", total_num_instances])
-    data = itertools.zip_longest(*[data[i::N_COLS] for i in range(N_COLS)])
-    table = tabulate(
-        data,
-        headers=["category", "#instances"] * (N_COLS // 2),
-        tablefmt="pipe",
-        numalign="left",
-        stralign="center",
-    )
-    log_first_n(
-        logging.INFO,
-        "Distribution of instances among all {} categories:\n".format(num_classes)
-        + colored(table, "cyan"),
-        key="message",
-    )
-
-
-def get_detection_dataset_dicts(
-    names,
-    filter_empty=True,
-    min_keypoints=0,
-    proposal_files=None,
-    check_consistency=True,
-):
-    """
-    Load and prepare dataset dicts for instance detection/segmentation and semantic segmentation.
-
-    Args:
-        names (str or list[str]): a dataset name or a list of dataset names
-        filter_empty (bool): whether to filter out images without instance annotations
-        min_keypoints (int): filter out images with fewer keypoints than
-            `min_keypoints`. Set to 0 to do nothing.
-        proposal_files (list[str]): if given, a list of object proposal files
-            that match each dataset in `names`.
-        check_consistency (bool): whether to check if datasets have consistent metadata.
-
-    Returns:
-        list[dict]: a list of dicts following the standard dataset dict format.
-    """
-    if isinstance(names, str):
-        names = [names]
-    assert len(names), names
-    dataset_dicts = [DatasetCatalog.get(dataset_name) for dataset_name in names]
-
-    if isinstance(dataset_dicts[0], torchdata.Dataset):
-        if len(dataset_dicts) > 1:
-            # ConcatDataset does not work for iterable style dataset.
-            # We could support concat for iterable as well, but it's often
-            # not a good idea to concat iterables anyway.
-            return torchdata.ConcatDataset(dataset_dicts)
-        return dataset_dicts[0]
-
-    for dataset_name, dicts in zip(names, dataset_dicts):
-        assert len(dicts), "Dataset '{}' is empty!".format(dataset_name)
-
-    if proposal_files is not None:
-        assert len(names) == len(proposal_files)
-        # load precomputed proposals from proposal files
-        dataset_dicts = [
-            load_proposals_into_dataset(dataset_i_dicts, proposal_file)
-            for dataset_i_dicts, proposal_file in zip(dataset_dicts, proposal_files)
-        ]
-
-    dataset_dicts = list(itertools.chain.from_iterable(dataset_dicts))
-
-    has_instances = "annotations" in dataset_dicts[0]
-    if filter_empty and has_instances:
-        dataset_dicts = filter_images_with_only_crowd_annotations(dataset_dicts)
-    if min_keypoints > 0 and has_instances:
-        dataset_dicts = filter_images_with_few_keypoints(dataset_dicts, min_keypoints)
-
-    if check_consistency and has_instances:
-        try:
-            class_names = MetadataCatalog.get(names[0]).thing_classes
-            check_metadata_consistency("thing_classes", names)
-            print_instances_class_histogram(dataset_dicts, class_names)
-        except AttributeError:  # class names are not available for this dataset
-            pass
-
-    assert len(dataset_dicts), "No valid data found in {}.".format(",".join(names))
-    return dataset_dicts
-
-
-def build_batch_data_loader(
-    dataset,
-    sampler,
-    total_batch_size,
-    *,
-    aspect_ratio_grouping=False,
-    num_workers=0,
-    collate_fn=None,
-):
-    """
-    Build a batched dataloader. The main differences from `torch.utils.data.DataLoader` are:
-    1. support aspect ratio grouping options
-    2. use no "batch collation", because this is common for detection training
-
-    Args:
-        dataset (torch.utils.data.Dataset): a pytorch map-style or iterable dataset.
-        sampler (torch.utils.data.sampler.Sampler or None): a sampler that produces indices.
-            Must be provided iff. ``dataset`` is a map-style dataset.
-        total_batch_size, aspect_ratio_grouping, num_workers, collate_fn: see
-            :func:`build_detection_train_loader`.
-
-    Returns:
-        iterable[list]. Length of each list is the batch size of the current
-            GPU. Each element in the list comes from the dataset.
-    """
-    world_size = get_world_size()
-    assert (
-        total_batch_size > 0 and total_batch_size % world_size == 0
-    ), "Total batch size ({}) must be divisible by the number of gpus ({}).".format(
-        total_batch_size, world_size
-    )
-    batch_size = total_batch_size // world_size
-
-    if isinstance(dataset, torchdata.IterableDataset):
-        assert sampler is None, "sampler must be None if dataset is IterableDataset"
-    else:
-        dataset = ToIterableDataset(dataset, sampler)
-
-    if aspect_ratio_grouping:
-        data_loader = torchdata.DataLoader(
-            dataset,
-            num_workers=num_workers,
-            collate_fn=operator.itemgetter(0),  # don't batch, but yield individual elements
-            worker_init_fn=worker_init_reset_seed,
-        )  # yield individual mapped dict
-        data_loader = AspectRatioGroupedDataset(data_loader, batch_size)
-        if collate_fn is None:
-            return data_loader
-        return MapDataset(data_loader, collate_fn)
-    else:
-        return torchdata.DataLoader(
-            dataset,
-            batch_size=batch_size,
-            drop_last=True,
-            num_workers=num_workers,
-            collate_fn=trivial_batch_collator if collate_fn is None else collate_fn,
-            worker_init_fn=worker_init_reset_seed,
-        )
-
-
-def _train_loader_from_config(cfg, mapper=None, *, dataset=None, sampler=None):
-    if dataset is None:
-        dataset = get_detection_dataset_dicts(
-            cfg.DATASETS.TRAIN,
-            filter_empty=cfg.DATALOADER.FILTER_EMPTY_ANNOTATIONS,
-            min_keypoints=cfg.MODEL.ROI_KEYPOINT_HEAD.MIN_KEYPOINTS_PER_IMAGE
-            if cfg.MODEL.KEYPOINT_ON
-            else 0,
-            proposal_files=cfg.DATASETS.PROPOSAL_FILES_TRAIN if cfg.MODEL.LOAD_PROPOSALS else None,
-        )
-        _log_api_usage("dataset." + cfg.DATASETS.TRAIN[0])
-
-    if mapper is None:
-        mapper = DatasetMapper(cfg, True)
-
-    if sampler is None:
-        sampler_name = cfg.DATALOADER.SAMPLER_TRAIN
-        logger = logging.getLogger(__name__)
-        if isinstance(dataset, torchdata.IterableDataset):
-            logger.info("Not using any sampler since the dataset is IterableDataset.")
-            sampler = None
-        else:
-            logger.info("Using training sampler {}".format(sampler_name))
-            if sampler_name == "TrainingSampler":
-                sampler = TrainingSampler(len(dataset))
-            elif sampler_name == "RepeatFactorTrainingSampler":
-                repeat_factors = RepeatFactorTrainingSampler.repeat_factors_from_category_frequency(
-                    dataset, cfg.DATALOADER.REPEAT_THRESHOLD
-                )
-                sampler = RepeatFactorTrainingSampler(repeat_factors)
-            elif sampler_name == "RandomSubsetTrainingSampler":
-                sampler = RandomSubsetTrainingSampler(
-                    len(dataset), cfg.DATALOADER.RANDOM_SUBSET_RATIO
-                )
-            else:
-                raise ValueError("Unknown training sampler: {}".format(sampler_name))
-
-    return {
-        "dataset": dataset,
-        "sampler": sampler,
-        "mapper": mapper,
-        "total_batch_size": cfg.SOLVER.IMS_PER_BATCH,
-        "aspect_ratio_grouping": cfg.DATALOADER.ASPECT_RATIO_GROUPING,
-        "num_workers": cfg.DATALOADER.NUM_WORKERS,
-    }
-
-
-@configurable(from_config=_train_loader_from_config)
-def build_detection_train_loader(
-    dataset,
-    *,
-    mapper,
-    sampler=None,
-    total_batch_size,
-    aspect_ratio_grouping=True,
-    num_workers=0,
-    collate_fn=None,
-):
-    """
-    Build a dataloader for object detection with some default features.
-
-    Args:
-        dataset (list or torch.utils.data.Dataset): a list of dataset dicts,
-            or a pytorch dataset (either map-style or iterable). It can be obtained
-            by using :func:`DatasetCatalog.get` or :func:`get_detection_dataset_dicts`.
-        mapper (callable): a callable which takes a sample (dict) from dataset and
-            returns the format to be consumed by the model.
-            When using cfg, the default choice is ``DatasetMapper(cfg, is_train=True)``.
-        sampler (torch.utils.data.sampler.Sampler or None): a sampler that produces
-            indices to be applied on ``dataset``.
-            If ``dataset`` is map-style, the default sampler is a :class:`TrainingSampler`,
-            which coordinates an infinite random shuffle sequence across all workers.
-            Sampler must be None if ``dataset`` is iterable.
-        total_batch_size (int): total batch size across all workers.
-        aspect_ratio_grouping (bool): whether to group images with similar
-            aspect ratio for efficiency. When enabled, it requires each
-            element in dataset be a dict with keys "width" and "height".
-        num_workers (int): number of parallel data loading workers
-        collate_fn: a function that determines how to do batching, same as the argument of
-            `torch.utils.data.DataLoader`. Defaults to do no collation and return a list of
-            data. No collation is OK for small batch size and simple data structures.
-            If your batch size is large and each sample contains too many small tensors,
-            it's more efficient to collate them in data loader.
-
-    Returns:
-        torch.utils.data.DataLoader:
-            a dataloader. Each output from it is a ``list[mapped_element]`` of length
-            ``total_batch_size / num_workers``, where ``mapped_element`` is produced
-            by the ``mapper``.
-    """
-    if isinstance(dataset, list):
-        dataset = DatasetFromList(dataset, copy=False)
-    if mapper is not None:
-        dataset = MapDataset(dataset, mapper)
-
-    if isinstance(dataset, torchdata.IterableDataset):
-        assert sampler is None, "sampler must be None if dataset is IterableDataset"
-    else:
-        if sampler is None:
-            sampler = TrainingSampler(len(dataset))
-        assert isinstance(sampler, torchdata.Sampler), f"Expect a Sampler but got {type(sampler)}"
-    return build_batch_data_loader(
-        dataset,
-        sampler,
-        total_batch_size,
-        aspect_ratio_grouping=aspect_ratio_grouping,
-        num_workers=num_workers,
-        collate_fn=collate_fn,
-    )
-
-
-def _test_loader_from_config(cfg, dataset_name, mapper=None):
-    """
-    Uses the given `dataset_name` argument (instead of the names in cfg), because the
-    standard practice is to evaluate each test set individually (not combining them).
-    """
-    if isinstance(dataset_name, str):
-        dataset_name = [dataset_name]
-
-    dataset = get_detection_dataset_dicts(
-        dataset_name,
-        filter_empty=False,
-        proposal_files=[
-            cfg.DATASETS.PROPOSAL_FILES_TEST[list(cfg.DATASETS.TEST).index(x)] for x in dataset_name
-        ]
-        if cfg.MODEL.LOAD_PROPOSALS
-        else None,
-    )
-    if mapper is None:
-        mapper = DatasetMapper(cfg, False)
-    return {
-        "dataset": dataset,
-        "mapper": mapper,
-        "num_workers": cfg.DATALOADER.NUM_WORKERS,
-        "sampler": InferenceSampler(len(dataset))
-        if not isinstance(dataset, torchdata.IterableDataset)
-        else None,
-    }
-
-
-@configurable(from_config=_test_loader_from_config)
-def build_detection_test_loader(
-    dataset: Union[List[Any], torchdata.Dataset],
-    *,
-    mapper: Callable[[Dict[str, Any]], Any],
-    sampler: Optional[torchdata.Sampler] = None,
-    batch_size: int = 1,
-    num_workers: int = 0,
-    collate_fn: Optional[Callable[[List[Any]], Any]] = None,
-) -> torchdata.DataLoader:
-    """
-    Similar to `build_detection_train_loader`, with default batch size = 1,
-    and sampler = :class:`InferenceSampler`. This sampler coordinates all workers
-    to produce the exact set of all samples.
-
-    Args:
-        dataset: a list of dataset dicts,
-            or a pytorch dataset (either map-style or iterable). They can be obtained
-            by using :func:`DatasetCatalog.get` or :func:`get_detection_dataset_dicts`.
-        mapper: a callable which takes a sample (dict) from dataset
-           and returns the format to be consumed by the model.
-           When using cfg, the default choice is ``DatasetMapper(cfg, is_train=False)``.
-        sampler: a sampler that produces
-            indices to be applied on ``dataset``. Default to :class:`InferenceSampler`,
-            which splits the dataset across all workers. Sampler must be None
-            if `dataset` is iterable.
-        batch_size: the batch size of the data loader to be created.
-            Default to 1 image per worker since this is the standard when reporting
-            inference time in papers.
-        num_workers: number of parallel data loading workers
-        collate_fn: same as the argument of `torch.utils.data.DataLoader`.
-            Defaults to do no collation and return a list of data.
-
-    Returns:
-        DataLoader: a torch DataLoader, that loads the given detection
-        dataset, with test-time transformation and batching.
-
-    Examples:
-    ::
-        data_loader = build_detection_test_loader(
-            DatasetRegistry.get("my_test"),
-            mapper=DatasetMapper(...))
-
-        # or, instantiate with a CfgNode:
-        data_loader = build_detection_test_loader(cfg, "my_test")
-    """
-    if isinstance(dataset, list):
-        dataset = DatasetFromList(dataset, copy=False)
-    if mapper is not None:
-        dataset = MapDataset(dataset, mapper)
-    if isinstance(dataset, torchdata.IterableDataset):
-        assert sampler is None, "sampler must be None if dataset is IterableDataset"
-    else:
-        if sampler is None:
-            sampler = InferenceSampler(len(dataset))
-    return torchdata.DataLoader(
-        dataset,
-        batch_size=batch_size,
-        sampler=sampler,
-        drop_last=False,
-        num_workers=num_workers,
-        collate_fn=trivial_batch_collator if collate_fn is None else collate_fn,
-    )
-
-
-def trivial_batch_collator(batch):
-    """
-    A batch collator that does nothing.
-    """
-    return batch
-
-
-def worker_init_reset_seed(worker_id):
-    initial_seed = torch.initial_seed() % 2**31
-    seed_all_rng(initial_seed + worker_id)
diff --git a/spaces/carlosalonso/Detection-video/carpeta_deteccion/projects/PointSup/point_sup/detection_utils.py b/spaces/carlosalonso/Detection-video/carpeta_deteccion/projects/PointSup/point_sup/detection_utils.py
deleted file mode 100644
index 3f95d9449277fc55e93121582f6c6a6396dc833d..0000000000000000000000000000000000000000
--- a/spaces/carlosalonso/Detection-video/carpeta_deteccion/projects/PointSup/point_sup/detection_utils.py
+++ /dev/null
@@ -1,103 +0,0 @@
-# -*- coding: utf-8 -*-
-# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
-
-import numpy as np
-import torch
-
-# fmt: off
-from detectron2.data.detection_utils import \
-    annotations_to_instances as base_annotations_to_instances
-from detectron2.data.detection_utils import \
-    transform_instance_annotations as base_transform_instance_annotations
-
-# fmt: on
-
-
-def annotations_to_instances(annos, image_size, sample_points=0):
-    """
-    Create an :class:`Instances` object used by the models,
-    from instance annotations in the dataset dict.
-
-    Args:
-        annos (list[dict]): a list of instance annotations in one image, each
-            element for one instance.
-        image_size (tuple): height, width
-        sample_points (int): subsample points at each iteration
-
-    Returns:
-        Instances:
-            It will contain fields "gt_boxes", "gt_classes",
-            "gt_point_coords", "gt_point_labels", if they can be obtained from `annos`.
-            This is the format that builtin models with point supervision expect.
-    """
-    target = base_annotations_to_instances(annos, image_size)
-
-    assert ("point_coords" in annos[0]) == ("point_labels" in annos[0])
-
-    if len(annos) and "point_labels" in annos[0]:
-        point_coords = []
-        point_labels = []
-        for i, _ in enumerate(annos):
-            # Already in the image coordinate system
-            point_coords_wrt_image = np.array(annos[i]["point_coords"])
-            point_labels_wrt_image = np.array(annos[i]["point_labels"])
-
-            if sample_points > 0:
-                random_indices = np.random.choice(
-                    point_coords_wrt_image.shape[0],
-                    sample_points,
-                    replace=point_coords_wrt_image.shape[0] < sample_points,
-                ).astype(int)
-                point_coords_wrt_image = point_coords_wrt_image[random_indices]
-                point_labels_wrt_image = point_labels_wrt_image[random_indices]
-                assert point_coords_wrt_image.shape[0] == point_labels_wrt_image.size
-
-            point_coords.append(point_coords_wrt_image)
-            point_labels.append(point_labels_wrt_image)
-
-        point_coords = torch.stack([torch.from_numpy(x) for x in point_coords])
-        point_labels = torch.stack([torch.from_numpy(x) for x in point_labels])
-        target.gt_point_coords = point_coords
-        target.gt_point_labels = point_labels
-
-    return target
-
-
-def transform_instance_annotations(
-    annotation, transforms, image_size, *, keypoint_hflip_indices=None
-):
-    """
-    Apply transforms to box, and point annotations of a single instance.
-    It will use `transforms.apply_box` for the box, and
-    `transforms.apply_coords` for points.
-    Args:
-        annotation (dict): dict of instance annotations for a single instance.
-            It will be modified in-place.
-        transforms (TransformList or list[Transform]):
-        image_size (tuple): the height, width of the transformed image
-        keypoint_hflip_indices (ndarray[int]): see `create_keypoint_hflip_indices`.
-    Returns:
-        dict:
-            the same input dict with fields "bbox", "point_coords", "point_labels"
-            transformed according to `transforms`.
-            The "bbox_mode" field will be set to XYXY_ABS.
-    """
-    annotation = base_transform_instance_annotations(
-        annotation, transforms, image_size, keypoint_hflip_indices
-    )
-
-    assert ("point_coords" in annotation) == ("point_labels" in annotation)
-    if "point_coords" in annotation and "point_labels" in annotation:
-        point_coords = annotation["point_coords"]
-        point_labels = np.array(annotation["point_labels"]).astype(np.float)
-        point_coords = transforms.apply_coords(point_coords)
-
-        # Set all out-of-boundary points to "unlabeled"
-        inside = (point_coords >= np.array([0, 0])) & (point_coords <= np.array(image_size[::-1]))
-        inside = inside.all(axis=1)
-        point_labels[~inside] = -1
-
-        annotation["point_coords"] = point_coords
-        annotation["point_labels"] = point_labels
-
-    return annotation
diff --git a/spaces/cesar/demoIAZIKA/app.py b/spaces/cesar/demoIAZIKA/app.py
deleted file mode 100644
index 4586eaee61d992007c6a6e9b78e7869894e9b1f0..0000000000000000000000000000000000000000
--- a/spaces/cesar/demoIAZIKA/app.py
+++ /dev/null
@@ -1,152 +0,0 @@
-# -*- coding: utf-8 -*-
-"""Deploy Barcelo demo.ipynb
-
-Automatically generated by Colaboratory.
-
-Original file is located at
-    https://colab.research.google.com/drive/1FxaL8DcYgvjPrWfWruSA5hvk3J81zLY9
-
-![   ](https://www.vicentelopez.gov.ar/assets/images/logo-mvl.png)
-
-# Modelo
-
-YOLO es una familia de modelos de detección de objetos a escala compuesta entrenados en COCO dataset, e incluye una funcionalidad simple para Test Time Augmentation (TTA), model ensembling, hyperparameter evolution, and export to ONNX, CoreML and TFLite.
-
-
-## Gradio Inferencia
-
-![](https://i.ibb.co/982NS6m/header.png)
-
-Este Notebook se acelera opcionalmente con un entorno de ejecución de GPU
-
-
-----------------------------------------------------------------------
-
- YOLOv5 Gradio demo
-
-*Author: Ultralytics LLC and Gradio*
-
-# Código
-"""
-
-#!pip install -qr https://raw.githubusercontent.com/ultralytics/yolov5/master/requirements.txt gradio # install dependencies
-
-import os
-import re
-import json
-import pandas as pd
-import gradio as gr
-import torch
-from PIL import Image
-
-# Images
-torch.hub.download_url_to_file('https://i.pinimg.com/originals/7f/5e/96/7f5e9657c08aae4bcd8bc8b0dcff720e.jpg', 'ejemplo1.jpg')
-torch.hub.download_url_to_file('https://i.pinimg.com/originals/c2/ce/e0/c2cee05624d5477ffcf2d34ca77b47d1.jpg', 'ejemplo2.jpg')
-
-# Model
-#model = torch.hub.load('ultralytics/yolov5', 'yolov5s')  # force_reload=True to update
-
-#model = torch.hub.load('ultralytics/yolov5', 'custom', path='best.pt')  # local model  o google colab
-model = torch.hub.load('ultralytics/yolov5', 'custom', path='best.pt', force_reload=True, autoshape=True)  # local model  o google colab
-#model = torch.hub.load('path/to/yolov5', 'custom', path='/content/yolov56.pt', source='local')  # local repo
-
-def getQuantity(string): 
-    contador_raw = ''.join(string.split(" ")[3:])
-    
-    resultado_especie_1 = 'Aedes'
-    resultado_especie_2 = 'Mosquito'
-    resultado_especie_3 = 'Mosca'
-    resultado_cantidad_1 = ''.join(re.findall(r'\d+',''.join(re.findall(r'\d+'+resultado_especie_1, contador_raw))))
-    resultado_cantidad_2 = ''.join(re.findall(r'\d+',''.join(re.findall(r'\d+'+resultado_especie_2, contador_raw))))
-    resultado_cantidad_3 = ''.join(re.findall(r'\d+',''.join(re.findall(r'\d+'+resultado_especie_3, contador_raw))))
-    resultado_cantidad_1 = resultado_cantidad_1 if len(resultado_cantidad_1) > 0 else "0"
-    resultado_cantidad_2 = resultado_cantidad_2 if len(resultado_cantidad_2) > 0 else "0"
-    resultado_cantidad_3 = resultado_cantidad_3 if len(resultado_cantidad_3) > 0 else "0"
-    
-    resultado_lista = [[resultado_cantidad_1,resultado_especie_1],
-                       [resultado_cantidad_2,resultado_especie_2],
-                       [resultado_cantidad_3,resultado_especie_3]]
-    
-    return resultado_lista
-
-def listJSON(resultado):
-    resultado_lista = getQuantity(resultado)
-    img_name = " ".join(resultado.split(" ")[0:2])
-    img_size = "".join(resultado.split(" ")[2])
-    strlista = ""
-    for resultado_lista, description in resultado_lista:
-        strlista += '{"quantity":"'+resultado_lista+'","description":"'+description+'"},'
-    strlista = strlista[:-1]
-    str_resultado_lista = '{"image":"'+str(img_name)+'","size":"'+str(img_size)+'","detail":['+strlista+']}'
-    json_string = json.loads(str_resultado_lista)
-    return json_string
-    
-def arrayLista(resultado):
-    resultado_lista = getQuantity(resultado)
-    df = pd.DataFrame(resultado_lista,columns=['Cantidad','Especie'])
-    return df
-
-def yolo(size, iou, conf, im):
-    '''Wrapper fn for gradio'''
-    g = (int(size) / max(im.size))  # gain
-    im = im.resize((int(x * g) for x in im.size), Image.ANTIALIAS)  # resize
-
-    model.iou = iou
-    
-    model.conf = conf
-
-   
-    results2 = model(im)  # inference
-   
-    results2.render()  # updates results.imgs with boxes and labels
-    
-    results_detail = str(results2)
-    lista = listJSON(results_detail)
-    lista2 = arrayLista(results_detail)
-    return Image.fromarray(results2.ims[0]), lista2, lista
-    
-#------------ Interface-------------
-
-
-
-in1 = gr.inputs.Radio(['640', '1280'], label="Tamaño de la imagen", default='640', type='value')
-in2 = gr.inputs.Slider(minimum=0, maximum=1, step=0.05, default=0.45, label='NMS IoU threshold')
-in3 = gr.inputs.Slider(minimum=0, maximum=1, step=0.05, default=0.50, label='Umbral o  threshold')
-in4 = gr.inputs.Image(type='pil', label="Original Image")
-
-out2 = gr.outputs.Image(type="pil", label="YOLOv5")
-out3 = gr.outputs.Dataframe(label="Descripción", headers=['Cantidad','Especie'])  
-out4 = gr.outputs.JSON(label="JSON")
-#-------------- Text-----
-title = 'Trampas Barceló'
-description = """
-<p>
-<center>
-Sistemas de Desarrollado por Subsecretaría de Innovación del Municipio de Vicente López. Advertencia solo usar fotos provenientes de las trampas Barceló, no de celular o foto de internet.
-<img src="https://www.vicentelopez.gov.ar/assets/images/logo-mvl.png" alt="logo" width="250"/>
-</center>
-</p>
-"""
-article ="<p style='text-align: center'><a href='https://docs.google.com/presentation/d/1T5CdcLSzgRe8cQpoi_sPB4U170551NGOrZNykcJD0xU/edit?usp=sharing' target='_blank'>Para mas info, clik para ir al white paper</a></p><p style='text-align: center'><a href='https://drive.google.com/drive/folders/1owACN3HGIMo4zm2GQ_jf-OhGNeBVRS7l?usp=sharing ' target='_blank'>Google Colab Demo</a></p><p style='text-align: center'><a href='https://github.com/Municipalidad-de-Vicente-Lopez/Trampa_Barcelo' target='_blank'>Repo Github</a></p></center></p>"
-          
-examples = [['640',0.45, 0.75,'ejemplo1.jpg'], ['640',0.45, 0.75,'ejemplo2.jpg']]
-
-iface = gr.Interface(yolo, 
-                        inputs=[in1, in2, in3, in4], 
-                        outputs=[out2,out3,out4], title=title, 
-                        description=description, 
-                        article=article, 
-                        examples=examples,
-                        theme="huggingface", 
-                        analytics_enabled=False
-                        ).launch(debug=True)
-
-iface.launch()
-
-"""For YOLOv5 PyTorch Hub inference with **PIL**, **OpenCV**, **Numpy** or **PyTorch** inputs please see the full [YOLOv5 PyTorch Hub Tutorial](https://github.com/ultralytics/yolov5/issues/36).
-
-
-## Citation
-
-[![DOI](https://zenodo.org/badge/264818686.svg)](https://zenodo.org/badge/latestdoi/264818686)
-"""
\ No newline at end of file
diff --git a/spaces/cffl/Exploring_Intelligent_Writing_Assistance/setup.py b/spaces/cffl/Exploring_Intelligent_Writing_Assistance/setup.py
deleted file mode 100644
index e1c490e6e03637b6d1c005558ec483ed1b650c62..0000000000000000000000000000000000000000
--- a/spaces/cffl/Exploring_Intelligent_Writing_Assistance/setup.py
+++ /dev/null
@@ -1,50 +0,0 @@
-# ###########################################################################
-#
-#  CLOUDERA APPLIED MACHINE LEARNING PROTOTYPE (AMP)
-#  (C) Cloudera, Inc. 2022
-#  All rights reserved.
-#
-#  Applicable Open Source License: Apache 2.0
-#
-#  NOTE: Cloudera open source products are modular software products
-#  made up of hundreds of individual components, each of which was
-#  individually copyrighted.  Each Cloudera open source product is a
-#  collective work under U.S. Copyright Law. Your license to use the
-#  collective work is as provided in your written agreement with
-#  Cloudera.  Used apart from the collective work, this file is
-#  licensed for your use pursuant to the open source license
-#  identified above.
-#
-#  This code is provided to you pursuant a written agreement with
-#  (i) Cloudera, Inc. or (ii) a third-party authorized to distribute
-#  this code. If you do not have a written agreement with Cloudera nor
-#  with an authorized and properly licensed third party, you do not
-#  have any rights to access nor to use this code.
-#
-#  Absent a written agreement with Cloudera, Inc. (“Cloudera”) to the
-#  contrary, A) CLOUDERA PROVIDES THIS CODE TO YOU WITHOUT WARRANTIES OF ANY
-#  KIND; (B) CLOUDERA DISCLAIMS ANY AND ALL EXPRESS AND IMPLIED
-#  WARRANTIES WITH RESPECT TO THIS CODE, INCLUDING BUT NOT LIMITED TO
-#  IMPLIED WARRANTIES OF TITLE, NON-INFRINGEMENT, MERCHANTABILITY AND
-#  FITNESS FOR A PARTICULAR PURPOSE; (C) CLOUDERA IS NOT LIABLE TO YOU,
-#  AND WILL NOT DEFEND, INDEMNIFY, NOR HOLD YOU HARMLESS FOR ANY CLAIMS
-#  ARISING FROM OR RELATED TO THE CODE; AND (D)WITH RESPECT TO YOUR EXERCISE
-#  OF ANY RIGHTS GRANTED TO YOU FOR THE CODE, CLOUDERA IS NOT LIABLE FOR ANY
-#  DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, PUNITIVE OR
-#  CONSEQUENTIAL DAMAGES INCLUDING, BUT NOT LIMITED TO, DAMAGES
-#  RELATED TO LOST REVENUE, LOST PROFITS, LOSS OF INCOME, LOSS OF
-#  BUSINESS ADVANTAGE OR UNAVAILABILITY, OR LOSS OR CORRUPTION OF
-#  DATA.
-#
-# ###########################################################################
-
-from setuptools import setup, find_packages
-
-setup(
-    name="text-style-transfer",
-    version="0.1.0",
-    description="A library and demo application for the NLP task of text style transfer.",
-    author="Andrew Reed",
-    author_email="andrew.reed.r@gmail.com",
-    # packages=find_packages(),
-)
diff --git a/spaces/chongjie/MCC_slim/app.py b/spaces/chongjie/MCC_slim/app.py
deleted file mode 100644
index f46016c3075a0625ca0c6948ca3cc816382902b5..0000000000000000000000000000000000000000
--- a/spaces/chongjie/MCC_slim/app.py
+++ /dev/null
@@ -1,281 +0,0 @@
-import gradio as gr
-
-
-import numpy as np
-import cv2
-from tqdm import tqdm
-
-import torch
-from pytorch3d.io.obj_io import load_obj
-import tempfile
-import main_mcc
-import mcc_model
-import util.misc as misc
-from engine_mcc import prepare_data
-from plyfile import PlyData, PlyElement
-import trimesh
-
-def run_inference(model, samples, device, temperature, args):
-    model.eval()
-
-    seen_xyz, valid_seen_xyz, unseen_xyz, unseen_rgb, labels, seen_images = prepare_data(
-        samples, device, is_train=False, args=args, is_viz=True
-    )
-    pred_occupy = []
-    pred_colors = []
-
-    max_n_unseen_fwd = 2000
-
-    model.cached_enc_feat = None
-    num_passes = int(np.ceil(unseen_xyz.shape[1] / max_n_unseen_fwd))
-    for p_idx in range(num_passes):
-        p_start = p_idx     * max_n_unseen_fwd
-        p_end = (p_idx + 1) * max_n_unseen_fwd
-        cur_unseen_xyz = unseen_xyz[:, p_start:p_end]
-        cur_unseen_rgb = unseen_rgb[:, p_start:p_end].zero_()
-        cur_labels = labels[:, p_start:p_end].zero_()
-
-        with torch.no_grad():
-            _, pred = model(
-                seen_images=seen_images,
-                seen_xyz=seen_xyz,
-                unseen_xyz=cur_unseen_xyz,
-                unseen_rgb=cur_unseen_rgb,
-                unseen_occupy=cur_labels,
-                cache_enc=True,
-                valid_seen_xyz=valid_seen_xyz,
-            )
-        if device == "cuda":
-            pred_occupy.append(pred[..., 0].cuda())
-        else:
-            pred_occupy.append(pred[..., 0].cpu())
-        if args.regress_color:
-            pred_colors.append(pred[..., 1:].reshape((-1, 3)))
-        else:
-            pred_colors.append(
-                (
-                    torch.nn.Softmax(dim=2)(
-                        pred[..., 1:].reshape((-1, 3, 256)) / temperature
-                    ) * torch.linspace(0, 1, 256, device=pred.device)
-                ).sum(axis=2)
-            )
-    
-    pred_occupy = torch.cat(pred_occupy, dim=1)
-    pred_occupy = torch.nn.Sigmoid()(pred_occupy)
-    return torch.cat(pred_colors, dim=0).cpu().numpy(), pred_occupy.cpu().numpy(), unseen_xyz.cpu().numpy()
-
-def pad_image(im, value):
-    if im.shape[0] > im.shape[1]:
-        diff = im.shape[0] - im.shape[1]
-        return torch.cat([im, (torch.zeros((im.shape[0], diff, im.shape[2])) + value)], dim=1)
-    else:
-        diff = im.shape[1] - im.shape[0]
-        return torch.cat([im, (torch.zeros((diff, im.shape[1], im.shape[2])) + value)], dim=0)
-
-def backproject_depth_to_pointcloud(depth, rotation=np.eye(3), translation=np.zeros(3)):
-    # Calculate the principal point as the center of the image
-    principal_point = [depth.shape[1] / 2, depth.shape[0] / 2]
-    intrinsics = get_intrinsics(depth.shape[0], depth.shape[1], principal_point)
-    
-    intrinsics = get_intrinsics(depth.shape[0], depth.shape[1], principal_point)
-    # Get the depth map shape
-    height, width = depth.shape
-
-    # Create a matrix of pixel coordinates
-    u, v = np.meshgrid(np.arange(width), np.arange(height))
-    uv_homogeneous = np.stack((u, v, np.ones_like(u)), axis=-1).reshape(-1, 3)
-
-    # Invert the intrinsic matrix
-    inv_intrinsics = np.linalg.inv(intrinsics)
-
-    # Convert depth to the camera coordinate system
-    points_cam_homogeneous = np.dot(uv_homogeneous, inv_intrinsics.T) * depth.flatten()[:, np.newaxis]
-
-    # Convert to 3D homogeneous coordinates
-    points_cam_homogeneous = np.concatenate((points_cam_homogeneous, np.ones((len(points_cam_homogeneous), 1))), axis=1)
-
-    # Apply the rotation and translation to get the 3D point cloud in the world coordinate system
-    extrinsics = np.hstack((rotation, translation[:, np.newaxis]))
-    pointcloud = np.dot(points_cam_homogeneous, extrinsics.T)
-    pointcloud[:, 1:] *= -1
-    
-    # Reshape the point cloud back to the original depth map shape
-    pointcloud = pointcloud[:, :3].reshape(height, width, 3)
-    
-
-    return pointcloud
-
-# estimate camera intrinsics
-def get_intrinsics(H,W, principal_point):
-    """
-    Intrinsics for a pinhole camera model.
-    Assume fov of 55 degrees and central principal point
-    of bounding box.
-    """
-    f = 0.5 * W / np.tan(0.5 * 55 * np.pi / 180.0)
-    cx, cy = principal_point
-    return np.array([[f, 0, cx],
-                     [0, f, cy],
-                     [0, 0, 1]])
-    
-def normalize(seen_xyz):
-    seen_xyz = seen_xyz / (seen_xyz[torch.isfinite(seen_xyz.sum(dim=-1))].var(dim=0) ** 0.5).mean()
-    seen_xyz = seen_xyz - seen_xyz[torch.isfinite(seen_xyz.sum(dim=-1))].mean(axis=0)
-    return seen_xyz
-
-def voxel_grid_downsample(points, colors, voxel_size):
-    # Compute voxel indices
-    voxel_indices = np.floor(points / voxel_size).astype(int)
-
-    # Remove duplicate voxel indices
-    unique_voxel_indices, inverse_indices = np.unique(voxel_indices, axis=0, return_inverse=True)
-
-    # Compute the centroid of the points and the average color in each voxel
-    centroids = np.empty_like(unique_voxel_indices, dtype=float)
-    avg_colors = np.empty((len(unique_voxel_indices), colors.shape[1]), dtype=colors.dtype)
-    for i in range(len(unique_voxel_indices)):
-        centroids[i] = points[inverse_indices == i].mean(axis=0)
-        avg_colors[i] = colors[inverse_indices == i].mean(axis=0)
-
-    # Convert colors from RGB to BGR
-    avg_colors = avg_colors[:, ::-1]
-    
-    return centroids, avg_colors
-
-def infer(
-          image,
-          depth_image,
-          seg,
-          granularity,
-          temperature,
-          ):
-    
-    args.viz_granularity = granularity
-    
-    rgb = image
-    depth_image = cv2.imread(depth_image.name, -1)
-    depth_image = depth_image.astype(np.float32) / 256
-    seen_xyz = backproject_depth_to_pointcloud(depth_image)
-    seen_rgb = (torch.tensor(rgb).float() / 255)[..., [2, 1, 0]]
-    H, W = seen_rgb.shape[:2]
-    seen_rgb = torch.nn.functional.interpolate(
-        seen_rgb.permute(2, 0, 1)[None],
-        size=[H, W],
-        mode="bilinear",
-        align_corners=False,
-    )[0].permute(1, 2, 0)
-
-    seg = cv2.imread(seg.name, cv2.IMREAD_UNCHANGED)
-    mask = torch.tensor(cv2.resize(seg, (W, H))).bool()
-    seen_xyz[~mask] = float('inf')
-    seen_xyz = torch.tensor(seen_xyz).float()
-    seen_xyz = normalize(seen_xyz)
-
-    bottom, right = mask.nonzero().max(dim=0)[0]
-    top, left = mask.nonzero().min(dim=0)[0]
-
-    bottom = bottom + 40
-    right = right + 40
-    top = max(top - 40, 0)
-    left = max(left - 40, 0)
-
-    seen_xyz = seen_xyz[top:bottom+1, left:right+1]
-    seen_rgb = seen_rgb[top:bottom+1, left:right+1]
-
-    seen_xyz = pad_image(seen_xyz, float('inf'))
-    seen_rgb = pad_image(seen_rgb, 0)
-
-    seen_rgb = torch.nn.functional.interpolate(
-        seen_rgb.permute(2, 0, 1)[None],
-        size=[800, 800],
-        mode="bilinear",
-        align_corners=False,
-    )
-
-    seen_xyz = torch.nn.functional.interpolate(
-        seen_xyz.permute(2, 0, 1)[None],
-        size=[112, 112],
-        mode="bilinear",
-        align_corners=False,
-    ).permute(0, 2, 3, 1)
-
-    samples = [
-        [seen_xyz, seen_rgb],
-        [torch.zeros((20000, 3)), torch.zeros((20000, 3))],
-    ]
-
-    pred_colors, pred_occupy, unseen_xyz = run_inference(model, samples, device, temperature, args)
-    _masks = pred_occupy > 0.1
-    unseen_xyz = unseen_xyz[_masks]
-    pred_colors = pred_colors[None, ...][_masks] * 255
-    
-    # Prepare data for PlyElement
-    vertex = np.core.records.fromarrays(np.hstack((unseen_xyz, pred_colors)).transpose(), 
-                                               names='x, y, z, red, green, blue', 
-                                               formats='f8, f8, f8, u1, u1, u1')
-    
-
-    # Create PlyElement
-    element = PlyElement.describe(vertex, 'vertex')
-    
-    # Save point cloud data to a temporary file
-    with tempfile.NamedTemporaryFile(suffix=".ply", delete=False) as f:
-        PlyData([element], text=True).write(f)
-        temp_file_name = f.name
-
-    # Perform voxel grid downsampling
-    voxel_size = 0.2  # Change this to the size of your cubes
-    downsampled_xyz, downsampled_colors = voxel_grid_downsample(unseen_xyz, pred_colors, voxel_size)
-    
-    meshes = []
-    for point, color in zip(downsampled_xyz, downsampled_colors):
-        # Create a cube mesh at the given point
-        cube = trimesh.creation.box(extents=[voxel_size]*3)
-        cube.apply_translation(point)
-
-        # Assign the average color to the vertices
-        cube.visual.vertex_colors = np.hstack([color, 255])  # Set alpha to 255
-        meshes.append(cube)
-
-    # Save point cloud data to a temporary file
-    with tempfile.NamedTemporaryFile(suffix=".obj", delete=False) as f:
-        temp_obj_file = f.name
-        print(temp_obj_file)
-        # Combine all the cubes into a single mesh
-        combined = trimesh.util.concatenate(meshes)
-        # Save the combined mesh to a file
-        combined.export(temp_obj_file)
-    return temp_file_name, temp_obj_file
-
-if __name__ == '__main__':
-    device = "cpu"
-    # device = "cuda" if torch.cuda.is_available() else "cpu"
-    
-    parser = main_mcc.get_args_parser()
-    parser.set_defaults(eval=True)
-
-    args = parser.parse_args()
-    
-    model = mcc_model.get_mcc_model(
-        occupancy_weight=1.0,
-        rgb_weight=0.01,
-        args=args,
-    )
-    
-    if device == "cuda":
-        model = model.cuda()
-
-    misc.load_model(args=args, model_without_ddp=model, optimizer=None, loss_scaler=None)
-
-    demo = gr.Interface(fn=infer, 
-                        inputs=[gr.Image(label="Input Image"),
-                                gr.File(label="Depth Image"),
-                                gr.File(label="Segmentation File"),
-                                gr.Slider(minimum=0.05, maximum=0.5, step=0.05, value=0.2, label="Grain Size"),
-                                gr.Slider(minimum=0, maximum=1.0, step=0.1, value=0.1, label="Color Temperature")
-                                ], 
-                        outputs=[gr.outputs.File(label="Point Cloud"),
-                                 gr.Model3D( clear_color=[0.0, 0.0, 0.0, 0.0], label="3D Model")],
-                        examples=[["demo/quest2.jpg", "demo/quest2_depth.png", "demo/quest2_seg.png", 0.2, 0.1]],
-                        cache_examples=True)
-    demo.launch(server_name="0.0.0.0", server_port=7860)
diff --git a/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/fontTools/misc/arrayTools.py b/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/fontTools/misc/arrayTools.py
deleted file mode 100644
index 5fb01a838ae8769809b4f8ab28cb69ea5e84a3dc..0000000000000000000000000000000000000000
--- a/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/fontTools/misc/arrayTools.py
+++ /dev/null
@@ -1,422 +0,0 @@
-"""Routines for calculating bounding boxes, point in rectangle calculations and
-so on.
-"""
-
-from fontTools.misc.roundTools import otRound
-from fontTools.misc.vector import Vector as _Vector
-import math
-import warnings
-
-
-def calcBounds(array):
-    """Calculate the bounding rectangle of a 2D points array.
-
-    Args:
-        array: A sequence of 2D tuples.
-
-    Returns:
-        A four-item tuple representing the bounding rectangle ``(xMin, yMin, xMax, yMax)``.
-    """
-    if not array:
-        return 0, 0, 0, 0
-    xs = [x for x, y in array]
-    ys = [y for x, y in array]
-    return min(xs), min(ys), max(xs), max(ys)
-
-
-def calcIntBounds(array, round=otRound):
-    """Calculate the integer bounding rectangle of a 2D points array.
-
-    Values are rounded to closest integer towards ``+Infinity`` using the
-    :func:`fontTools.misc.fixedTools.otRound` function by default, unless
-    an optional ``round`` function is passed.
-
-    Args:
-        array: A sequence of 2D tuples.
-        round: A rounding function of type ``f(x: float) -> int``.
-
-    Returns:
-        A four-item tuple of integers representing the bounding rectangle:
-        ``(xMin, yMin, xMax, yMax)``.
-    """
-    return tuple(round(v) for v in calcBounds(array))
-
-
-def updateBounds(bounds, p, min=min, max=max):
-    """Add a point to a bounding rectangle.
-
-    Args:
-        bounds: A bounding rectangle expressed as a tuple
-            ``(xMin, yMin, xMax, yMax)``.
-        p: A 2D tuple representing a point.
-        min,max: functions to compute the minimum and maximum.
-
-    Returns:
-        The updated bounding rectangle ``(xMin, yMin, xMax, yMax)``.
-    """
-    (x, y) = p
-    xMin, yMin, xMax, yMax = bounds
-    return min(xMin, x), min(yMin, y), max(xMax, x), max(yMax, y)
-
-
-def pointInRect(p, rect):
-    """Test if a point is inside a bounding rectangle.
-
-    Args:
-        p: A 2D tuple representing a point.
-        rect: A bounding rectangle expressed as a tuple
-            ``(xMin, yMin, xMax, yMax)``.
-
-    Returns:
-        ``True`` if the point is inside the rectangle, ``False`` otherwise.
-    """
-    (x, y) = p
-    xMin, yMin, xMax, yMax = rect
-    return (xMin <= x <= xMax) and (yMin <= y <= yMax)
-
-
-def pointsInRect(array, rect):
-    """Determine which points are inside a bounding rectangle.
-
-    Args:
-        array: A sequence of 2D tuples.
-        rect: A bounding rectangle expressed as a tuple
-            ``(xMin, yMin, xMax, yMax)``.
-
-    Returns:
-        A list containing the points inside the rectangle.
-    """
-    if len(array) < 1:
-        return []
-    xMin, yMin, xMax, yMax = rect
-    return [(xMin <= x <= xMax) and (yMin <= y <= yMax) for x, y in array]
-
-
-def vectorLength(vector):
-    """Calculate the length of the given vector.
-
-    Args:
-        vector: A 2D tuple.
-
-    Returns:
-        The Euclidean length of the vector.
-    """
-    x, y = vector
-    return math.sqrt(x**2 + y**2)
-
-
-def asInt16(array):
-    """Round a list of floats to 16-bit signed integers.
-
-    Args:
-        array: List of float values.
-
-    Returns:
-        A list of rounded integers.
-    """
-    return [int(math.floor(i + 0.5)) for i in array]
-
-
-def normRect(rect):
-    """Normalize a bounding box rectangle.
-
-    This function "turns the rectangle the right way up", so that the following
-    holds::
-
-        xMin <= xMax and yMin <= yMax
-
-    Args:
-        rect: A bounding rectangle expressed as a tuple
-            ``(xMin, yMin, xMax, yMax)``.
-
-    Returns:
-        A normalized bounding rectangle.
-    """
-    (xMin, yMin, xMax, yMax) = rect
-    return min(xMin, xMax), min(yMin, yMax), max(xMin, xMax), max(yMin, yMax)
-
-
-def scaleRect(rect, x, y):
-    """Scale a bounding box rectangle.
-
-    Args:
-        rect: A bounding rectangle expressed as a tuple
-            ``(xMin, yMin, xMax, yMax)``.
-        x: Factor to scale the rectangle along the X axis.
-        Y: Factor to scale the rectangle along the Y axis.
-
-    Returns:
-        A scaled bounding rectangle.
-    """
-    (xMin, yMin, xMax, yMax) = rect
-    return xMin * x, yMin * y, xMax * x, yMax * y
-
-
-def offsetRect(rect, dx, dy):
-    """Offset a bounding box rectangle.
-
-    Args:
-        rect: A bounding rectangle expressed as a tuple
-            ``(xMin, yMin, xMax, yMax)``.
-        dx: Amount to offset the rectangle along the X axis.
-        dY: Amount to offset the rectangle along the Y axis.
-
-    Returns:
-        An offset bounding rectangle.
-    """
-    (xMin, yMin, xMax, yMax) = rect
-    return xMin + dx, yMin + dy, xMax + dx, yMax + dy
-
-
-def insetRect(rect, dx, dy):
-    """Inset a bounding box rectangle on all sides.
-
-    Args:
-        rect: A bounding rectangle expressed as a tuple
-            ``(xMin, yMin, xMax, yMax)``.
-        dx: Amount to inset the rectangle along the X axis.
-        dY: Amount to inset the rectangle along the Y axis.
-
-    Returns:
-        An inset bounding rectangle.
-    """
-    (xMin, yMin, xMax, yMax) = rect
-    return xMin + dx, yMin + dy, xMax - dx, yMax - dy
-
-
-def sectRect(rect1, rect2):
-    """Test for rectangle-rectangle intersection.
-
-    Args:
-        rect1: First bounding rectangle, expressed as tuples
-            ``(xMin, yMin, xMax, yMax)``.
-        rect2: Second bounding rectangle.
-
-    Returns:
-        A boolean and a rectangle.
-        If the input rectangles intersect, returns ``True`` and the intersecting
-        rectangle. Returns ``False`` and ``(0, 0, 0, 0)`` if the input
-        rectangles don't intersect.
-    """
-    (xMin1, yMin1, xMax1, yMax1) = rect1
-    (xMin2, yMin2, xMax2, yMax2) = rect2
-    xMin, yMin, xMax, yMax = (
-        max(xMin1, xMin2),
-        max(yMin1, yMin2),
-        min(xMax1, xMax2),
-        min(yMax1, yMax2),
-    )
-    if xMin >= xMax or yMin >= yMax:
-        return False, (0, 0, 0, 0)
-    return True, (xMin, yMin, xMax, yMax)
-
-
-def unionRect(rect1, rect2):
-    """Determine union of bounding rectangles.
-
-    Args:
-        rect1: First bounding rectangle, expressed as tuples
-            ``(xMin, yMin, xMax, yMax)``.
-        rect2: Second bounding rectangle.
-
-    Returns:
-        The smallest rectangle in which both input rectangles are fully
-        enclosed.
-    """
-    (xMin1, yMin1, xMax1, yMax1) = rect1
-    (xMin2, yMin2, xMax2, yMax2) = rect2
-    xMin, yMin, xMax, yMax = (
-        min(xMin1, xMin2),
-        min(yMin1, yMin2),
-        max(xMax1, xMax2),
-        max(yMax1, yMax2),
-    )
-    return (xMin, yMin, xMax, yMax)
-
-
-def rectCenter(rect):
-    """Determine rectangle center.
-
-    Args:
-        rect: Bounding rectangle, expressed as tuples
-            ``(xMin, yMin, xMax, yMax)``.
-
-    Returns:
-        A 2D tuple representing the point at the center of the rectangle.
-    """
-    (xMin, yMin, xMax, yMax) = rect
-    return (xMin + xMax) / 2, (yMin + yMax) / 2
-
-
-def rectArea(rect):
-    """Determine rectangle area.
-
-    Args:
-        rect: Bounding rectangle, expressed as tuples
-            ``(xMin, yMin, xMax, yMax)``.
-
-    Returns:
-        The area of the rectangle.
-    """
-    (xMin, yMin, xMax, yMax) = rect
-    return (yMax - yMin) * (xMax - xMin)
-
-
-def intRect(rect):
-    """Round a rectangle to integer values.
-
-    Guarantees that the resulting rectangle is NOT smaller than the original.
-
-    Args:
-        rect: Bounding rectangle, expressed as tuples
-            ``(xMin, yMin, xMax, yMax)``.
-
-    Returns:
-        A rounded bounding rectangle.
-    """
-    (xMin, yMin, xMax, yMax) = rect
-    xMin = int(math.floor(xMin))
-    yMin = int(math.floor(yMin))
-    xMax = int(math.ceil(xMax))
-    yMax = int(math.ceil(yMax))
-    return (xMin, yMin, xMax, yMax)
-
-
-def quantizeRect(rect, factor=1):
-    """
-    >>> bounds = (72.3, -218.4, 1201.3, 919.1)
-    >>> quantizeRect(bounds)
-    (72, -219, 1202, 920)
-    >>> quantizeRect(bounds, factor=10)
-    (70, -220, 1210, 920)
-    >>> quantizeRect(bounds, factor=100)
-    (0, -300, 1300, 1000)
-    """
-    if factor < 1:
-        raise ValueError(f"Expected quantization factor >= 1, found: {factor!r}")
-    xMin, yMin, xMax, yMax = normRect(rect)
-    return (
-        int(math.floor(xMin / factor) * factor),
-        int(math.floor(yMin / factor) * factor),
-        int(math.ceil(xMax / factor) * factor),
-        int(math.ceil(yMax / factor) * factor),
-    )
-
-
-class Vector(_Vector):
-    def __init__(self, *args, **kwargs):
-        warnings.warn(
-            "fontTools.misc.arrayTools.Vector has been deprecated, please use "
-            "fontTools.misc.vector.Vector instead.",
-            DeprecationWarning,
-        )
-
-
-def pairwise(iterable, reverse=False):
-    """Iterate over current and next items in iterable.
-
-    Args:
-        iterable: An iterable
-        reverse: If true, iterate in reverse order.
-
-    Returns:
-        A iterable yielding two elements per iteration.
-
-    Example:
-
-        >>> tuple(pairwise([]))
-        ()
-        >>> tuple(pairwise([], reverse=True))
-        ()
-        >>> tuple(pairwise([0]))
-        ((0, 0),)
-        >>> tuple(pairwise([0], reverse=True))
-        ((0, 0),)
-        >>> tuple(pairwise([0, 1]))
-        ((0, 1), (1, 0))
-        >>> tuple(pairwise([0, 1], reverse=True))
-        ((1, 0), (0, 1))
-        >>> tuple(pairwise([0, 1, 2]))
-        ((0, 1), (1, 2), (2, 0))
-        >>> tuple(pairwise([0, 1, 2], reverse=True))
-        ((2, 1), (1, 0), (0, 2))
-        >>> tuple(pairwise(['a', 'b', 'c', 'd']))
-        (('a', 'b'), ('b', 'c'), ('c', 'd'), ('d', 'a'))
-        >>> tuple(pairwise(['a', 'b', 'c', 'd'], reverse=True))
-        (('d', 'c'), ('c', 'b'), ('b', 'a'), ('a', 'd'))
-    """
-    if not iterable:
-        return
-    if reverse:
-        it = reversed(iterable)
-    else:
-        it = iter(iterable)
-    first = next(it, None)
-    a = first
-    for b in it:
-        yield (a, b)
-        a = b
-    yield (a, first)
-
-
-def _test():
-    """
-    >>> import math
-    >>> calcBounds([])
-    (0, 0, 0, 0)
-    >>> calcBounds([(0, 40), (0, 100), (50, 50), (80, 10)])
-    (0, 10, 80, 100)
-    >>> updateBounds((0, 0, 0, 0), (100, 100))
-    (0, 0, 100, 100)
-    >>> pointInRect((50, 50), (0, 0, 100, 100))
-    True
-    >>> pointInRect((0, 0), (0, 0, 100, 100))
-    True
-    >>> pointInRect((100, 100), (0, 0, 100, 100))
-    True
-    >>> not pointInRect((101, 100), (0, 0, 100, 100))
-    True
-    >>> list(pointsInRect([(50, 50), (0, 0), (100, 100), (101, 100)], (0, 0, 100, 100)))
-    [True, True, True, False]
-    >>> vectorLength((3, 4))
-    5.0
-    >>> vectorLength((1, 1)) == math.sqrt(2)
-    True
-    >>> list(asInt16([0, 0.1, 0.5, 0.9]))
-    [0, 0, 1, 1]
-    >>> normRect((0, 10, 100, 200))
-    (0, 10, 100, 200)
-    >>> normRect((100, 200, 0, 10))
-    (0, 10, 100, 200)
-    >>> scaleRect((10, 20, 50, 150), 1.5, 2)
-    (15.0, 40, 75.0, 300)
-    >>> offsetRect((10, 20, 30, 40), 5, 6)
-    (15, 26, 35, 46)
-    >>> insetRect((10, 20, 50, 60), 5, 10)
-    (15, 30, 45, 50)
-    >>> insetRect((10, 20, 50, 60), -5, -10)
-    (5, 10, 55, 70)
-    >>> intersects, rect = sectRect((0, 10, 20, 30), (0, 40, 20, 50))
-    >>> not intersects
-    True
-    >>> intersects, rect = sectRect((0, 10, 20, 30), (5, 20, 35, 50))
-    >>> intersects
-    1
-    >>> rect
-    (5, 20, 20, 30)
-    >>> unionRect((0, 10, 20, 30), (0, 40, 20, 50))
-    (0, 10, 20, 50)
-    >>> rectCenter((0, 0, 100, 200))
-    (50.0, 100.0)
-    >>> rectCenter((0, 0, 100, 199.0))
-    (50.0, 99.5)
-    >>> intRect((0.9, 2.9, 3.1, 4.1))
-    (0, 2, 4, 5)
-    """
-
-
-if __name__ == "__main__":
-    import sys
-    import doctest
-
-    sys.exit(doctest.testmod().failed)
diff --git a/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/gradio/templates/cdn/assets/index-57e34dbe.js b/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/gradio/templates/cdn/assets/index-57e34dbe.js
deleted file mode 100644
index fe00cd0314ba4ef6139aba9526c28d84cfd20d5e..0000000000000000000000000000000000000000
--- a/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/gradio/templates/cdn/assets/index-57e34dbe.js
+++ /dev/null
@@ -1,2 +0,0 @@
-import{L as s}from"./index-41d42cd1.js";import{s as o,t as r,L as n,i as P,w as a,f as i,a as Q,b as p}from"./index-ebba85cc.js";import"./index-f877dfd5.js";import"./Blocks-adc2d4ca.js";import"./Button-11a87b79.js";import"./BlockLabel-7929e88d.js";import"./Empty-2159e5e9.js";import"./Copy-534f8e58.js";import"./Download-a587c81f.js";const c=o({String:r.string,Number:r.number,"True False":r.bool,PropertyName:r.propertyName,Null:r.null,",":r.separator,"[ ]":r.squareBracket,"{ }":r.brace}),g=s.deserialize({version:14,states:"$bOVQPOOOOQO'#Cb'#CbOnQPO'#CeOvQPO'#CjOOQO'#Cp'#CpQOQPOOOOQO'#Cg'#CgO}QPO'#CfO!SQPO'#CrOOQO,59P,59PO![QPO,59PO!aQPO'#CuOOQO,59U,59UO!iQPO,59UOVQPO,59QOqQPO'#CkO!nQPO,59^OOQO1G.k1G.kOVQPO'#ClO!vQPO,59aOOQO1G.p1G.pOOQO1G.l1G.lOOQO,59V,59VOOQO-E6i-E6iOOQO,59W,59WOOQO-E6j-E6j",stateData:"#O~OcOS~OQSORSOSSOTSOWQO]ROePO~OVXOeUO~O[[O~PVOg^O~Oh_OVfX~OVaO~OhbO[iX~O[dO~Oh_OVfa~OhbO[ia~O",goto:"!kjPPPPPPkPPkqwPPk{!RPPP!XP!ePP!hXSOR^bQWQRf_TVQ_Q`WRg`QcZRicQTOQZRQe^RhbRYQR]R",nodeNames:"⚠ JsonText True False Null Number String } { Object Property PropertyName ] [ Array",maxTerm:25,nodeProps:[["openedBy",7,"{",12,"["],["closedBy",8,"}",13,"]"]],propSources:[c],skippedNodes:[0],repeatNodeCount:2,tokenData:"(p~RaXY!WYZ!W]^!Wpq!Wrs!]|}$i}!O$n!Q!R$w!R![&V![!]&h!}#O&m#P#Q&r#Y#Z&w#b#c'f#h#i'}#o#p(f#q#r(k~!]Oc~~!`Upq!]qr!]rs!rs#O!]#O#P!w#P~!]~!wOe~~!zXrs!]!P!Q!]#O#P!]#U#V!]#Y#Z!]#b#c!]#f#g!]#h#i!]#i#j#g~#jR!Q![#s!c!i#s#T#Z#s~#vR!Q![$P!c!i$P#T#Z$P~$SR!Q![$]!c!i$]#T#Z$]~$`R!Q![!]!c!i!]#T#Z!]~$nOh~~$qQ!Q!R$w!R![&V~$|RT~!O!P%V!g!h%k#X#Y%k~%YP!Q![%]~%bRT~!Q![%]!g!h%k#X#Y%k~%nR{|%w}!O%w!Q![%}~%zP!Q![%}~&SPT~!Q![%}~&[ST~!O!P%V!Q![&V!g!h%k#X#Y%k~&mOg~~&rO]~~&wO[~~&zP#T#U&}~'QP#`#a'T~'WP#g#h'Z~'^P#X#Y'a~'fOR~~'iP#i#j'l~'oP#`#a'r~'uP#`#a'x~'}OS~~(QP#f#g(T~(WP#i#j(Z~(^P#X#Y(a~(fOQ~~(kOW~~(pOV~",tokenizers:[0],topRules:{JsonText:[0,1]},tokenPrec:0}),V=()=>t=>{try{JSON.parse(t.state.doc.toString())}catch(O){if(!(O instanceof SyntaxError))throw O;const e=m(O,t.state.doc);return[{from:e,message:O.message,severity:"error",to:e}]}return[]};function m(t,O){let e;return(e=t.message.match(/at position (\d+)/))?Math.min(+e[1],O.length):(e=t.message.match(/at line (\d+) column (\d+)/))?Math.min(O.line(+e[1]).from+ +e[2]-1,O.length):0}const u=n.define({name:"json",parser:g.configure({props:[P.add({Object:a({except:/^\s*\}/}),Array:a({except:/^\s*\]/})}),i.add({"Object Array":Q})]}),languageData:{closeBrackets:{brackets:["[","{",'"']},indentOnInput:/^\s*[\}\]]$/}});function $(){return new p(u)}export{$ as json,u as jsonLanguage,V as jsonParseLinter};
-//# sourceMappingURL=index-57e34dbe.js.map
diff --git a/spaces/cihyFjudo/fairness-paper-search/3gp Warung Bokep Asia 1.md b/spaces/cihyFjudo/fairness-paper-search/3gp Warung Bokep Asia 1.md
deleted file mode 100644
index 18768e08b4ca726cb545365cc9c986a4425ba7f3..0000000000000000000000000000000000000000
--- a/spaces/cihyFjudo/fairness-paper-search/3gp Warung Bokep Asia 1.md	
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diff --git a/spaces/cihyFjudo/fairness-paper-search/Anatomia de Rouviere tomo II pdf 44 La gua definitiva para dominar la anatoma del tronco con el texto de referencia de Rouviere y Delmas.md b/spaces/cihyFjudo/fairness-paper-search/Anatomia de Rouviere tomo II pdf 44 La gua definitiva para dominar la anatoma del tronco con el texto de referencia de Rouviere y Delmas.md
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index 31318fbda0d6b47aa2504b20f495a16a5b17f2f5..0000000000000000000000000000000000000000
--- a/spaces/cihyFjudo/fairness-paper-search/Anatomia de Rouviere tomo II pdf 44 La gua definitiva para dominar la anatoma del tronco con el texto de referencia de Rouviere y Delmas.md	
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index ae41aae37ff801a1bd8adb3ca178d15ae10ca7d5..0000000000000000000000000000000000000000
--- a/spaces/cihyFjudo/fairness-paper-search/Ashampoo Burning Studio 11.0.2.6 Final Multilang .rar Download the Best CDDVD Burning Software.md	
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diff --git a/spaces/cihyFjudo/fairness-paper-search/Js Support Ticket Pro Nulled 11 The Ultimate Helpdesk Plugin for Joomla.md b/spaces/cihyFjudo/fairness-paper-search/Js Support Ticket Pro Nulled 11 The Ultimate Helpdesk Plugin for Joomla.md
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index 7abcc92456d772d47a45b634b0bb3146c0e1dfcc..0000000000000000000000000000000000000000
--- a/spaces/cihyFjudo/fairness-paper-search/Js Support Ticket Pro Nulled 11 The Ultimate Helpdesk Plugin for Joomla.md	
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-<p>JS Help Desk is the best helpdesk and support plugin. JS Help Desk is a professional, simple, easy to use and complete customer support system. JS Help Desk comes packed with lot features than most of the expensive(and complex) support ticket system on market. The best part is, It completely free.</p>
-<p>Marvin JS has been designed for easy integration with web-based applications. The public API provided with the editor enables web developers to seamlessly embed this application with their homegrown custom solutions (e.g.: adding custom buttons, custom templates, UI presets). Our sketcher can be exposed on any web browser supporting JavaScript and HTML5 technology.</p>
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-<p>The most notable case is probably when using an AMD-aware version of Backbone, but using shim config for scripts that depend on Backbone. If this is your use case, then setting wrapShim: true in the optimizer config will likely fix any post-build problem you might see. More details in the bug ticket.Full list of changes:</p>
-<p>Source map support has been expanded. Previously, it was just supported for going from minified, bundled code to the unminified, bundled code. If optimize: 'uglify2' is used, it will now go back to the separated, unbundled files.</p>
-<p>The other notable change: the optimizer now supportsonBuildReadand onBuildWrite functions that are called when JS modules are read or writtenfor an optimized build layer. This allows doing some regexp work to modify theircontents.</p>
-<p>Visual Studio 2022 version 17.4 will be the next long term servicing channel once it's released. Enterprise and Professional users who are configured to receive updates on the 17.4 LTSC channel are supported and will receive fixes to security vulnerabilities through July 2024. For more information about Visual Studio supported baselines, please review the Support Policy for Visual Studio 2022.</p>
-<p><strong>Arm64</strong><br/>This preview continues to build out our native Arm64 support on Windows 11. In addition to supporting .NET desktop development (WinForms and WPF), Desktop development with C++ (for MSBuild-based projects) and ASP.NET and Web development, we have now enabled the <strong>Universal Windows Platform development</strong> workload. Read our blog post to learn more.</p>
-<p>All Visual Studio security updates for all supported versions of Visual Studio are now available to modern cloud connected Azure Active Directory (Azure AD) joined devices that use Windows Update for Business and are managed by mobile device management solutions such as Microsoft Endpoint Manager (formerly known as Intune). You can enable this functionality on your client devices by setting the AdministratorUpdatesEnabled policy to 2. Refer to the blog post and the Visual Studio Administrators Guide for additional details.</p>
-<p><strong>Python and native mixed-mode debugging:</strong>Python and native mixed-mode debugging has a known bug when working with virtual environments. Due to the fact that Python for Windows uses a stub python.exe for venvs, Visual Studio finds and loads python.exe as a subprocess. For Python 3.8 onward - when starting a debug session, since mixed-mode doesn't support multi-process debugging, it ends up debugging just that stub process, instead of the actual app. For attach scenarios, the workaround is to attach to the correct python.exe. For launch/F5, there's no workaround, and unfortunately - you'll have to avoid venvs. For Python versions prior to 3.8, mixed mode debugging should work as expected with venvs. Running in a global environment will not cause these issues for any version of Python.See Not possible to debug both Python and Native for more information.</p>
-<p>We would love to hear from you! You can Report a Problem or Suggest a Feature by using the Send Feedback icon in the upper right-hand corner of either the installer or the Visual Studio IDE, or from <strong>Help > Send Feedback</strong>. You can track your issues by using Visual Studio Developer Community, where you add comments or find solutions. You can also get free installation help through our Live Chat support.</p>
-<p></p>
-<p>You can easily register MAGIX software at MAGIX Service Center. In order to use the software, you must register and activate it the first time you launch it. Registering your software also offers a range of benefits such as additional information, free and regular program improvements, support for various problems, exclusive offers and license management.</p>
-<p>WordPress aims to support new versions of PHPPHP The web scripting language in which WordPress is primarily architected. WordPress requires PHP 5.6.20 or higher on the day they are released as much as possible. As a project, the process of supporting these new versions begins after each new PHP version has hit feature freeze and are tagging betaBeta A pre-release of software that is given out to a large group of users to trial under real conditions. Beta versions have gone through alpha testing in-house and are generally fairly close in look, feel and function to the final product; however, design changes often occur as part of the process. versions. This prevents having to revert or make additional changes to WordPress if a planned feature is removed or the implementation changes.</p>
-<p>We have all the bells and whistles, but our primary focus is two-way email ticketing. Our help desk app instantly turns incoming emails into trouble tickets, and sends out automatic email notifications to both users and agents. More on emails...</p>
-<p><i>"Who is this customer? What's their company name again? Haven't we already answered that? Who's handling this email?"</i> Spend less time figuring that out and never be annoyed by another support email again.</p>
-<p>Assign agents to different areas. Manage ticket permissions. Track your assets and SLA's. Attach documents, screenshots, PDFs, live chat with customers or even record a short video right from your browser. Maintain a knowledge-base. Tag and categorize tickets. All powered by the most advanced technical platform - MS SQL Server and ASP.NET.</p>
-<p>Optional Windows-integrated authentication easily connects Jitbit helpdesk ticketing system with your existing Active Directory users catalog. You can also connect to MS Exchange via EWS or IMAP, integrate with JIRA issue tracker or GitHub and many other apps</p>
-<p>IT ticketing system is a software app, that converts all incoming tech support requests into <i>tickets</i>. and stores them in one central database for later management. Requests come in via email, live chat, text-messages, phone calls - all go into the same storage, where help desk agents can add their responses and keep track of tickets.</p>
-<p>The main screen of the help desk software features a powerful grid showing all the information on your current tickets. You can easily sort and filter the requests, review the current statistics and even perform "bulk" operations without leaving the page. For example, assign multiple tickets to agents, merge, close, delete tickets or even post a reply to multiple tickets at once. Different queues let you switch between "all", "in progress" and "unanswered" tickets. In addition, you can switch to the "assigned to me" tickets, requests from a specific company, a specific customer etc.</p>
-<p>Whether you're a tech support "agent", an "administrator" or a "manager", the grid easily adjusts to your current needs. This is the screen you're gonna be looking at for the most part of your workday, so we've literally spent years polishing it.</p>
-<p>When you click an individual ticket, you see all the case details on a single page. The entire conversation, attachments, private messages and any other activity. You no longer need to dig through your support mailbox trying to find "that email we received from this customer a week ago".</p>
-<p>A typical helpdesk agent's workday involves a lot more than just writing replies to customers. We need to move tickets around, merge and link them together, glance at the "previous tickets from this company", search for similar tickets etc. We probably spend half of our day doing all those things.</p>
-<p>Support tickets are being assigned to "categories" - that's the main feature to help you organize things up a little. You can classify tickets into categories manually, make customers choose a category during the ticket creation or do this automatically via Automation Rules (see below) and email engine settings. Categories provide many additional benefits - you can assign categories to specific team members, build reports using only the tickets you need, easily search for tickets and more</p>
-<p>You can also add tags to your tickets, using tags in addition to categories to fine tune your layout even more. A ticket can even have multiple tags assigned to it. A good example is a "feature request" tag to easily find all the ongoing feature requests.</p>
-<p>Help your customers find answers they need with our searchable FAQ and Knowledge Base with built in analytics. Customers can also access the self-service web portal and track their tickets, submit new requests or chat with a help desk agent. All the ITSM best practices.</p>
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deleted file mode 100644
index 91502ea578f68fa8534d5e1dce7c42c4423eeafd..0000000000000000000000000000000000000000
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deleted file mode 100644
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deleted file mode 100644
index a647982525057bf3c26c7a94a03705af4d098268..0000000000000000000000000000000000000000
--- a/spaces/cihyFjudo/fairness-paper-search/Sony Vaio Pcg-5j2l Camera Drivers For Mac [CRACKED].md	
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-<p></p>
diff --git a/spaces/cihyFjudo/fairness-paper-search/Zbigniew Preisner Silence Night And Dreams The Full Album Zip with Lyrics and Illustrations.md b/spaces/cihyFjudo/fairness-paper-search/Zbigniew Preisner Silence Night And Dreams The Full Album Zip with Lyrics and Illustrations.md
deleted file mode 100644
index 0006461027067f9d3b187e6039b378987203c743..0000000000000000000000000000000000000000
--- a/spaces/cihyFjudo/fairness-paper-search/Zbigniew Preisner Silence Night And Dreams The Full Album Zip with Lyrics and Illustrations.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>Zbigniew PreisnerSilence Night And Dreams Full Album Zip</h2><br /><p><b><b>Download File</b> &#10037; <a href="https://tinurli.com/2uwixW">https://tinurli.com/2uwixW</a></b></p><br /><br />
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diff --git a/spaces/cloudtheboi/Lofi4All/.pythonlibs/lib/python3.10/site-packages/anyio/from_thread.py b/spaces/cloudtheboi/Lofi4All/.pythonlibs/lib/python3.10/site-packages/anyio/from_thread.py
deleted file mode 100644
index 6b76861c70d6a6aa369a54370ef47aa75839a91f..0000000000000000000000000000000000000000
--- a/spaces/cloudtheboi/Lofi4All/.pythonlibs/lib/python3.10/site-packages/anyio/from_thread.py
+++ /dev/null
@@ -1,500 +0,0 @@
-from __future__ import annotations
-
-import threading
-from asyncio import iscoroutine
-from concurrent.futures import FIRST_COMPLETED, Future, ThreadPoolExecutor, wait
-from contextlib import AbstractContextManager, contextmanager
-from types import TracebackType
-from typing import (
-    Any,
-    AsyncContextManager,
-    Awaitable,
-    Callable,
-    ContextManager,
-    Generator,
-    Generic,
-    Iterable,
-    TypeVar,
-    cast,
-    overload,
-)
-from warnings import warn
-
-from ._core import _eventloop
-from ._core._eventloop import get_asynclib, get_cancelled_exc_class, threadlocals
-from ._core._synchronization import Event
-from ._core._tasks import CancelScope, create_task_group
-from .abc._tasks import TaskStatus
-
-T_Retval = TypeVar("T_Retval")
-T_co = TypeVar("T_co")
-
-
-def run(func: Callable[..., Awaitable[T_Retval]], *args: object) -> T_Retval:
-    """
-    Call a coroutine function from a worker thread.
-
-    :param func: a coroutine function
-    :param args: positional arguments for the callable
-    :return: the return value of the coroutine function
-
-    """
-    try:
-        asynclib = threadlocals.current_async_module
-    except AttributeError:
-        raise RuntimeError("This function can only be run from an AnyIO worker thread")
-
-    return asynclib.run_async_from_thread(func, *args)
-
-
-def run_async_from_thread(
-    func: Callable[..., Awaitable[T_Retval]], *args: object
-) -> T_Retval:
-    warn(
-        "run_async_from_thread() has been deprecated, use anyio.from_thread.run() instead",
-        DeprecationWarning,
-    )
-    return run(func, *args)
-
-
-def run_sync(func: Callable[..., T_Retval], *args: object) -> T_Retval:
-    """
-    Call a function in the event loop thread from a worker thread.
-
-    :param func: a callable
-    :param args: positional arguments for the callable
-    :return: the return value of the callable
-
-    """
-    try:
-        asynclib = threadlocals.current_async_module
-    except AttributeError:
-        raise RuntimeError("This function can only be run from an AnyIO worker thread")
-
-    return asynclib.run_sync_from_thread(func, *args)
-
-
-def run_sync_from_thread(func: Callable[..., T_Retval], *args: object) -> T_Retval:
-    warn(
-        "run_sync_from_thread() has been deprecated, use anyio.from_thread.run_sync() instead",
-        DeprecationWarning,
-    )
-    return run_sync(func, *args)
-
-
-class _BlockingAsyncContextManager(Generic[T_co], AbstractContextManager):
-    _enter_future: Future
-    _exit_future: Future
-    _exit_event: Event
-    _exit_exc_info: tuple[
-        type[BaseException] | None, BaseException | None, TracebackType | None
-    ] = (None, None, None)
-
-    def __init__(self, async_cm: AsyncContextManager[T_co], portal: BlockingPortal):
-        self._async_cm = async_cm
-        self._portal = portal
-
-    async def run_async_cm(self) -> bool | None:
-        try:
-            self._exit_event = Event()
-            value = await self._async_cm.__aenter__()
-        except BaseException as exc:
-            self._enter_future.set_exception(exc)
-            raise
-        else:
-            self._enter_future.set_result(value)
-
-        try:
-            # Wait for the sync context manager to exit.
-            # This next statement can raise `get_cancelled_exc_class()` if
-            # something went wrong in a task group in this async context
-            # manager.
-            await self._exit_event.wait()
-        finally:
-            # In case of cancellation, it could be that we end up here before
-            # `_BlockingAsyncContextManager.__exit__` is called, and an
-            # `_exit_exc_info` has been set.
-            result = await self._async_cm.__aexit__(*self._exit_exc_info)
-            return result
-
-    def __enter__(self) -> T_co:
-        self._enter_future = Future()
-        self._exit_future = self._portal.start_task_soon(self.run_async_cm)
-        cm = self._enter_future.result()
-        return cast(T_co, cm)
-
-    def __exit__(
-        self,
-        __exc_type: type[BaseException] | None,
-        __exc_value: BaseException | None,
-        __traceback: TracebackType | None,
-    ) -> bool | None:
-        self._exit_exc_info = __exc_type, __exc_value, __traceback
-        self._portal.call(self._exit_event.set)
-        return self._exit_future.result()
-
-
-class _BlockingPortalTaskStatus(TaskStatus):
-    def __init__(self, future: Future):
-        self._future = future
-
-    def started(self, value: object = None) -> None:
-        self._future.set_result(value)
-
-
-class BlockingPortal:
-    """An object that lets external threads run code in an asynchronous event loop."""
-
-    def __new__(cls) -> BlockingPortal:
-        return get_asynclib().BlockingPortal()
-
-    def __init__(self) -> None:
-        self._event_loop_thread_id: int | None = threading.get_ident()
-        self._stop_event = Event()
-        self._task_group = create_task_group()
-        self._cancelled_exc_class = get_cancelled_exc_class()
-
-    async def __aenter__(self) -> BlockingPortal:
-        await self._task_group.__aenter__()
-        return self
-
-    async def __aexit__(
-        self,
-        exc_type: type[BaseException] | None,
-        exc_val: BaseException | None,
-        exc_tb: TracebackType | None,
-    ) -> bool | None:
-        await self.stop()
-        return await self._task_group.__aexit__(exc_type, exc_val, exc_tb)
-
-    def _check_running(self) -> None:
-        if self._event_loop_thread_id is None:
-            raise RuntimeError("This portal is not running")
-        if self._event_loop_thread_id == threading.get_ident():
-            raise RuntimeError(
-                "This method cannot be called from the event loop thread"
-            )
-
-    async def sleep_until_stopped(self) -> None:
-        """Sleep until :meth:`stop` is called."""
-        await self._stop_event.wait()
-
-    async def stop(self, cancel_remaining: bool = False) -> None:
-        """
-        Signal the portal to shut down.
-
-        This marks the portal as no longer accepting new calls and exits from
-        :meth:`sleep_until_stopped`.
-
-        :param cancel_remaining: ``True`` to cancel all the remaining tasks, ``False`` to let them
-            finish before returning
-
-        """
-        self._event_loop_thread_id = None
-        self._stop_event.set()
-        if cancel_remaining:
-            self._task_group.cancel_scope.cancel()
-
-    async def _call_func(
-        self, func: Callable, args: tuple, kwargs: dict[str, Any], future: Future
-    ) -> None:
-        def callback(f: Future) -> None:
-            if f.cancelled() and self._event_loop_thread_id not in (
-                None,
-                threading.get_ident(),
-            ):
-                self.call(scope.cancel)
-
-        try:
-            retval = func(*args, **kwargs)
-            if iscoroutine(retval):
-                with CancelScope() as scope:
-                    if future.cancelled():
-                        scope.cancel()
-                    else:
-                        future.add_done_callback(callback)
-
-                    retval = await retval
-        except self._cancelled_exc_class:
-            future.cancel()
-        except BaseException as exc:
-            if not future.cancelled():
-                future.set_exception(exc)
-
-            # Let base exceptions fall through
-            if not isinstance(exc, Exception):
-                raise
-        else:
-            if not future.cancelled():
-                future.set_result(retval)
-        finally:
-            scope = None  # type: ignore[assignment]
-
-    def _spawn_task_from_thread(
-        self,
-        func: Callable,
-        args: tuple,
-        kwargs: dict[str, Any],
-        name: object,
-        future: Future,
-    ) -> None:
-        """
-        Spawn a new task using the given callable.
-
-        Implementors must ensure that the future is resolved when the task finishes.
-
-        :param func: a callable
-        :param args: positional arguments to be passed to the callable
-        :param kwargs: keyword arguments to be passed to the callable
-        :param name: name of the task (will be coerced to a string if not ``None``)
-        :param future: a future that will resolve to the return value of the callable, or the
-            exception raised during its execution
-
-        """
-        raise NotImplementedError
-
-    @overload
-    def call(self, func: Callable[..., Awaitable[T_Retval]], *args: object) -> T_Retval:
-        ...
-
-    @overload
-    def call(self, func: Callable[..., T_Retval], *args: object) -> T_Retval:
-        ...
-
-    def call(
-        self, func: Callable[..., Awaitable[T_Retval] | T_Retval], *args: object
-    ) -> T_Retval:
-        """
-        Call the given function in the event loop thread.
-
-        If the callable returns a coroutine object, it is awaited on.
-
-        :param func: any callable
-        :raises RuntimeError: if the portal is not running or if this method is called from within
-            the event loop thread
-
-        """
-        return cast(T_Retval, self.start_task_soon(func, *args).result())
-
-    @overload
-    def spawn_task(
-        self,
-        func: Callable[..., Awaitable[T_Retval]],
-        *args: object,
-        name: object = None,
-    ) -> Future[T_Retval]:
-        ...
-
-    @overload
-    def spawn_task(
-        self, func: Callable[..., T_Retval], *args: object, name: object = None
-    ) -> Future[T_Retval]:
-        ...
-
-    def spawn_task(
-        self,
-        func: Callable[..., Awaitable[T_Retval] | T_Retval],
-        *args: object,
-        name: object = None,
-    ) -> Future[T_Retval]:
-        """
-        Start a task in the portal's task group.
-
-        :param func: the target coroutine function
-        :param args: positional arguments passed to ``func``
-        :param name: name of the task (will be coerced to a string if not ``None``)
-        :return: a future that resolves with the return value of the callable if the task completes
-            successfully, or with the exception raised in the task
-        :raises RuntimeError: if the portal is not running or if this method is called from within
-            the event loop thread
-
-        .. versionadded:: 2.1
-        .. deprecated:: 3.0
-           Use :meth:`start_task_soon` instead. If your code needs AnyIO 2 compatibility, you
-           can keep using this until AnyIO 4.
-
-        """
-        warn(
-            "spawn_task() is deprecated -- use start_task_soon() instead",
-            DeprecationWarning,
-        )
-        return self.start_task_soon(func, *args, name=name)  # type: ignore[arg-type]
-
-    @overload
-    def start_task_soon(
-        self,
-        func: Callable[..., Awaitable[T_Retval]],
-        *args: object,
-        name: object = None,
-    ) -> Future[T_Retval]:
-        ...
-
-    @overload
-    def start_task_soon(
-        self, func: Callable[..., T_Retval], *args: object, name: object = None
-    ) -> Future[T_Retval]:
-        ...
-
-    def start_task_soon(
-        self,
-        func: Callable[..., Awaitable[T_Retval] | T_Retval],
-        *args: object,
-        name: object = None,
-    ) -> Future[T_Retval]:
-        """
-        Start a task in the portal's task group.
-
-        The task will be run inside a cancel scope which can be cancelled by cancelling the
-        returned future.
-
-        :param func: the target function
-        :param args: positional arguments passed to ``func``
-        :param name: name of the task (will be coerced to a string if not ``None``)
-        :return: a future that resolves with the return value of the callable if the
-            task completes successfully, or with the exception raised in the task
-        :raises RuntimeError: if the portal is not running or if this method is called
-            from within the event loop thread
-        :rtype: concurrent.futures.Future[T_Retval]
-
-        .. versionadded:: 3.0
-
-        """
-        self._check_running()
-        f: Future = Future()
-        self._spawn_task_from_thread(func, args, {}, name, f)
-        return f
-
-    def start_task(
-        self, func: Callable[..., Awaitable[Any]], *args: object, name: object = None
-    ) -> tuple[Future[Any], Any]:
-        """
-        Start a task in the portal's task group and wait until it signals for readiness.
-
-        This method works the same way as :meth:`.abc.TaskGroup.start`.
-
-        :param func: the target function
-        :param args: positional arguments passed to ``func``
-        :param name: name of the task (will be coerced to a string if not ``None``)
-        :return: a tuple of (future, task_status_value) where the ``task_status_value``
-            is the value passed to ``task_status.started()`` from within the target
-            function
-        :rtype: tuple[concurrent.futures.Future[Any], Any]
-
-        .. versionadded:: 3.0
-
-        """
-
-        def task_done(future: Future) -> None:
-            if not task_status_future.done():
-                if future.cancelled():
-                    task_status_future.cancel()
-                elif future.exception():
-                    task_status_future.set_exception(future.exception())
-                else:
-                    exc = RuntimeError(
-                        "Task exited without calling task_status.started()"
-                    )
-                    task_status_future.set_exception(exc)
-
-        self._check_running()
-        task_status_future: Future = Future()
-        task_status = _BlockingPortalTaskStatus(task_status_future)
-        f: Future = Future()
-        f.add_done_callback(task_done)
-        self._spawn_task_from_thread(func, args, {"task_status": task_status}, name, f)
-        return f, task_status_future.result()
-
-    def wrap_async_context_manager(
-        self, cm: AsyncContextManager[T_co]
-    ) -> ContextManager[T_co]:
-        """
-        Wrap an async context manager as a synchronous context manager via this portal.
-
-        Spawns a task that will call both ``__aenter__()`` and ``__aexit__()``, stopping in the
-        middle until the synchronous context manager exits.
-
-        :param cm: an asynchronous context manager
-        :return: a synchronous context manager
-
-        .. versionadded:: 2.1
-
-        """
-        return _BlockingAsyncContextManager(cm, self)
-
-
-def create_blocking_portal() -> BlockingPortal:
-    """
-    Create a portal for running functions in the event loop thread from external threads.
-
-    Use this function in asynchronous code when you need to allow external threads access to the
-    event loop where your asynchronous code is currently running.
-
-    .. deprecated:: 3.0
-        Use :class:`.BlockingPortal` directly.
-
-    """
-    warn(
-        "create_blocking_portal() has been deprecated -- use anyio.from_thread.BlockingPortal() "
-        "directly",
-        DeprecationWarning,
-    )
-    return BlockingPortal()
-
-
-@contextmanager
-def start_blocking_portal(
-    backend: str = "asyncio", backend_options: dict[str, Any] | None = None
-) -> Generator[BlockingPortal, Any, None]:
-    """
-    Start a new event loop in a new thread and run a blocking portal in its main task.
-
-    The parameters are the same as for :func:`~anyio.run`.
-
-    :param backend: name of the backend
-    :param backend_options: backend options
-    :return: a context manager that yields a blocking portal
-
-    .. versionchanged:: 3.0
-        Usage as a context manager is now required.
-
-    """
-
-    async def run_portal() -> None:
-        async with BlockingPortal() as portal_:
-            if future.set_running_or_notify_cancel():
-                future.set_result(portal_)
-                await portal_.sleep_until_stopped()
-
-    future: Future[BlockingPortal] = Future()
-    with ThreadPoolExecutor(1) as executor:
-        run_future = executor.submit(
-            _eventloop.run,
-            run_portal,  # type: ignore[arg-type]
-            backend=backend,
-            backend_options=backend_options,
-        )
-        try:
-            wait(
-                cast(Iterable[Future], [run_future, future]),
-                return_when=FIRST_COMPLETED,
-            )
-        except BaseException:
-            future.cancel()
-            run_future.cancel()
-            raise
-
-        if future.done():
-            portal = future.result()
-            cancel_remaining_tasks = False
-            try:
-                yield portal
-            except BaseException:
-                cancel_remaining_tasks = True
-                raise
-            finally:
-                try:
-                    portal.call(portal.stop, cancel_remaining_tasks)
-                except RuntimeError:
-                    pass
-
-        run_future.result()
diff --git a/spaces/cm-community/README/README.md b/spaces/cm-community/README/README.md
deleted file mode 100644
index f7b4cbc74f461add33311bf0971cbd9fbf04275e..0000000000000000000000000000000000000000
--- a/spaces/cm-community/README/README.md
+++ /dev/null
@@ -1,19 +0,0 @@
----
-title: README
-emoji: 📉
-colorFrom: red
-colorTo: indigo
-sdk: static
-pinned: false
----
-
-# Make Diffusion Model's GAN's again
-
-Hello,
-
-We're a community-driven organization researching on [**Consistency Models**](https://arxiv.org/abs/2303.01469). We're trying to drastically reduce the number of inference steps for diffusion models
-so that they can become as fast as GANs.
-
-In a first step we've added [OpenAI's released checkpoints](https://github.com/openai/consistency_models) to 🧨 Diffusers which you can access [here](https://huggingface.co/models?other=consistency-model).
-
-In a next step, we're looking into training consistency models on larger text-conditioned datasets.
\ No newline at end of file
diff --git a/spaces/colakin/video-generater/public/ffmpeg/libavcodec/eaidct.h b/spaces/colakin/video-generater/public/ffmpeg/libavcodec/eaidct.h
deleted file mode 100644
index a46dae939b6bd88aa39bf56742c69ae2fb6086b8..0000000000000000000000000000000000000000
--- a/spaces/colakin/video-generater/public/ffmpeg/libavcodec/eaidct.h
+++ /dev/null
@@ -1,27 +0,0 @@
-/*
- * This file is part of FFmpeg
- *
- * FFmpeg is free software; you can redistribute it and/or
- * modify it under the terms of the GNU Lesser General Public
- * License as published by the Free Software Foundation; either
- * version 2.1 of the License, or (at your option) any later version.
- *
- * FFmpeg is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
- * Lesser General Public License for more details.
- *
- * You should have received a copy of the GNU Lesser General Public
- * License along with FFmpeg; if not, write to the Free Software
- * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
- */
-
-#ifndef AVCODEC_EAIDCT_H
-#define AVCODEC_EAIDCT_H
-
-#include <stddef.h>
-#include <stdint.h>
-
-void ff_ea_idct_put_c(uint8_t *dest, ptrdiff_t linesize, int16_t *block);
-
-#endif /* AVCODEC_EAIDCT_H */
diff --git a/spaces/colakin/video-generater/public/ffmpeg/libavcodec/mips/hpeldsp_mmi.c b/spaces/colakin/video-generater/public/ffmpeg/libavcodec/mips/hpeldsp_mmi.c
deleted file mode 100644
index 8e9c0fa82155ad49045301dfecdfc52304e28bdf..0000000000000000000000000000000000000000
--- a/spaces/colakin/video-generater/public/ffmpeg/libavcodec/mips/hpeldsp_mmi.c
+++ /dev/null
@@ -1,1118 +0,0 @@
-/*
- * Loongson SIMD optimized qpeldsp
- *
- * Copyright (c) 2016 Loongson Technology Corporation Limited
- * Copyright (c) 2016 Zhou Xiaoyong <zhouxiaoyong@loongson.cn>
- *
- * This file is part of FFmpeg.
- *
- * FFmpeg is free software; you can redistribute it and/or
- * modify it under the terms of the GNU Lesser General Public
- * License as published by the Free Software Foundation; either
- * version 2.1 of the License, or (at your option) any later version.
- *
- * FFmpeg is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
- * Lesser General Public License for more details.
- *
- * You should have received a copy of the GNU Lesser General Public
- * License along with FFmpeg; if not, write to the Free Software
- * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
- */
-
-#include "hpeldsp_mips.h"
-#include "libavcodec/bit_depth_template.c"
-#include "libavutil/mips/mmiutils.h"
-#include "constants.h"
-
-void ff_put_pixels4_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    double ftmp[4];
-    DECLARE_VAR_LOW32;
-
-    __asm__ volatile (
-        "1:                                                             \n\t"
-        MMI_ULWC1(%[ftmp0], %[pixels], 0x00)
-        PTR_ADDU   "%[pixels],   %[pixels],      %[line_size]           \n\t"
-        MMI_ULWC1(%[ftmp1], %[pixels], 0x00)
-        PTR_ADDU   "%[pixels],   %[pixels],      %[line_size]           \n\t"
-
-        PTR_ADDI   "%[h],       %[h],           -0x02                   \n\t"
-
-        MMI_SWC1(%[ftmp0], %[block], 0x00)
-        PTR_ADDU   "%[block],   %[block],       %[line_size]            \n\t"
-        MMI_SWC1(%[ftmp1], %[block], 0x00)
-        PTR_ADDU   "%[block],   %[block],       %[line_size]            \n\t"
-
-        "bnez       %[h],       1b                                      \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          RESTRICT_ASM_LOW32
-          [block]"+&r"(block),              [pixels]"+&r"(pixels),
-          [h]"+&r"(h)
-        : [line_size]"r"((mips_reg)line_size)
-        : "memory"
-    );
-}
-
-void ff_put_pixels8_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    double ftmp[4];
-    DECLARE_VAR_ALL64;
-
-    __asm__ volatile (
-        "1:                                                             \n\t"
-        MMI_ULDC1(%[ftmp0], %[pixels], 0x00)
-        PTR_ADDU   "%[pixels],   %[pixels],      %[line_size]           \n\t"
-        MMI_ULDC1(%[ftmp1], %[pixels], 0x00)
-        PTR_ADDU   "%[pixels],   %[pixels],      %[line_size]           \n\t"
-        MMI_ULDC1(%[ftmp2], %[pixels], 0x00)
-        PTR_ADDU   "%[pixels],   %[pixels],      %[line_size]           \n\t"
-        MMI_ULDC1(%[ftmp3], %[pixels], 0x00)
-        PTR_ADDU   "%[pixels],   %[pixels],      %[line_size]           \n\t"
-
-        PTR_ADDI   "%[h],       %[h],           -0x04                   \n\t"
-
-        MMI_SDC1(%[ftmp0], %[block], 0x00)
-        PTR_ADDU   "%[block],   %[block],       %[line_size]            \n\t"
-        MMI_SDC1(%[ftmp1], %[block], 0x00)
-        PTR_ADDU   "%[block],   %[block],       %[line_size]            \n\t"
-        MMI_SDC1(%[ftmp2], %[block], 0x00)
-        PTR_ADDU   "%[block],   %[block],       %[line_size]            \n\t"
-        MMI_SDC1(%[ftmp3], %[block], 0x00)
-        PTR_ADDU   "%[block],   %[block],       %[line_size]            \n\t"
-
-        "bnez       %[h],       1b                                      \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          RESTRICT_ASM_ALL64
-          [block]"+&r"(block),              [pixels]"+&r"(pixels),
-          [h]"+&r"(h)
-        : [line_size]"r"((mips_reg)line_size)
-        : "memory"
-    );
-}
-
-void ff_put_pixels16_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    double ftmp[8];
-    DECLARE_VAR_ALL64;
-
-    __asm__ volatile (
-        "1:                                                            \n\t"
-        MMI_ULDC1(%[ftmp0], %[pixels], 0x00)
-        MMI_ULDC1(%[ftmp2], %[pixels], 0x08)
-        PTR_ADDU   "%[pixels],  %[pixels],      %[line_size]           \n\t"
-        MMI_ULDC1(%[ftmp1], %[pixels], 0x00)
-        MMI_ULDC1(%[ftmp3], %[pixels], 0x08)
-        PTR_ADDU   "%[pixels],  %[pixels],      %[line_size]           \n\t"
-        MMI_ULDC1(%[ftmp4], %[pixels], 0x00)
-        MMI_ULDC1(%[ftmp6], %[pixels], 0x08)
-        PTR_ADDU   "%[pixels],  %[pixels],      %[line_size]           \n\t"
-        MMI_ULDC1(%[ftmp5], %[pixels], 0x00)
-        MMI_ULDC1(%[ftmp7], %[pixels], 0x08)
-        PTR_ADDU   "%[pixels],  %[pixels],      %[line_size]           \n\t"
-
-        PTR_ADDI   "%[h],       %[h],           -0x04                  \n\t"
-
-        MMI_SDC1(%[ftmp0], %[block], 0x00)
-        MMI_SDC1(%[ftmp2], %[block], 0x08)
-        PTR_ADDU   "%[block],   %[block],       %[line_size]           \n\t"
-        MMI_SDC1(%[ftmp1], %[block], 0x00)
-        MMI_SDC1(%[ftmp3], %[block], 0x08)
-        PTR_ADDU   "%[block],   %[block],       %[line_size]           \n\t"
-        MMI_SDC1(%[ftmp4], %[block], 0x00)
-        MMI_SDC1(%[ftmp6], %[block], 0x08)
-        PTR_ADDU   "%[block],   %[block],       %[line_size]           \n\t"
-        MMI_SDC1(%[ftmp5], %[block], 0x00)
-        MMI_SDC1(%[ftmp7], %[block], 0x08)
-        PTR_ADDU   "%[block],   %[block],       %[line_size]           \n\t"
-
-        "bnez       %[h],       1b                                     \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          [ftmp4]"=&f"(ftmp[4]),            [ftmp5]"=&f"(ftmp[5]),
-          [ftmp6]"=&f"(ftmp[6]),            [ftmp7]"=&f"(ftmp[7]),
-          RESTRICT_ASM_ALL64
-          [block]"+&r"(block),              [pixels]"+&r"(pixels),
-          [h]"+&r"(h)
-        : [line_size]"r"((mips_reg)line_size)
-        : "memory"
-    );
-}
-
-void ff_avg_pixels4_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    double ftmp[4];
-    mips_reg addr[2];
-    DECLARE_VAR_LOW32;
-
-    __asm__ volatile (
-        "1:                                                             \n\t"
-        PTR_ADDU   "%[addr0],   %[pixels],      %[line_size]            \n\t"
-        MMI_ULWC1(%[ftmp0], %[pixels], 0x00)
-        MMI_ULWC1(%[ftmp1], %[addr0], 0x00)
-        PTR_ADDU   "%[addr1],   %[block],       %[line_size]            \n\t"
-        MMI_ULWC1(%[ftmp2], %[block], 0x00)
-        MMI_ULWC1(%[ftmp3], %[addr1], 0x00)
-
-        PTR_ADDI   "%[h],       %[h],           -0x02                   \n\t"
-
-        "pavgb      %[ftmp0],   %[ftmp0],       %[ftmp2]                \n\t"
-        "pavgb      %[ftmp1],   %[ftmp1],       %[ftmp3]                \n\t"
-        MMI_SWC1(%[ftmp0], %[block], 0x00)
-        MMI_SWC1(%[ftmp1], %[addr1], 0x00)
-        PTR_ADDU   "%[pixels],  %[addr0],       %[line_size]            \n\t"
-        PTR_ADDU   "%[block],   %[addr1],       %[line_size]            \n\t"
-
-        "bnez       %[h],       1b                                      \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          RESTRICT_ASM_LOW32
-          [addr0]"=&r"(addr[0]),            [addr1]"=&r"(addr[1]),
-          [block]"+&r"(block),              [pixels]"+&r"(pixels),
-          [h]"+&r"(h)
-        : [line_size]"r"((mips_reg)line_size)
-        : "memory"
-    );
-}
-
-void ff_avg_pixels8_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    double ftmp[4];
-    mips_reg addr[3];
-    DECLARE_VAR_ALL64;
-    DECLARE_VAR_ADDRT;
-
-    __asm__ volatile (
-        PTR_ADDU   "%[addr2],   %[line_size],   %[line_size]            \n\t"
-        "1:                                                             \n\t"
-        MMI_ULDC1(%[ftmp0], %[pixels], 0x00)
-        PTR_ADDU   "%[addr0],   %[pixels],      %[line_size]            \n\t"
-        MMI_ULDC1(%[ftmp1], %[addr0], 0x00)
-        PTR_ADDU   "%[addr1],   %[block],       %[line_size]            \n\t"
-        MMI_ULDC1(%[ftmp2], %[block], 0x00)
-        MMI_ULDC1(%[ftmp3], %[addr1], 0x00)
-        "pavgb      %[ftmp0],   %[ftmp0],       %[ftmp2]                \n\t"
-        "pavgb      %[ftmp1],   %[ftmp1],       %[ftmp3]                \n\t"
-        MMI_SDC1(%[ftmp0], %[block], 0x00)
-        MMI_SDXC1(%[ftmp1], %[block], %[line_size], 0x00)
-        PTR_ADDU   "%[pixels],  %[pixels],      %[addr2]                \n\t"
-        PTR_ADDU   "%[block],   %[block],       %[addr2]                \n\t"
-
-        MMI_ULDC1(%[ftmp0], %[pixels], 0x00)
-        PTR_ADDU   "%[addr0],   %[pixels],      %[line_size]            \n\t"
-        MMI_ULDC1(%[ftmp1], %[addr0], 0x00)
-        PTR_ADDU   "%[addr1],   %[block],       %[line_size]            \n\t"
-        MMI_ULDC1(%[ftmp2], %[block], 0x00)
-        MMI_ULDC1(%[ftmp3], %[addr1], 0x00)
-        "pavgb      %[ftmp0],   %[ftmp0],       %[ftmp2]                \n\t"
-        "pavgb      %[ftmp1],   %[ftmp1],       %[ftmp3]                \n\t"
-        MMI_SDC1(%[ftmp0], %[block], 0x00)
-        MMI_SDXC1(%[ftmp1], %[block], %[line_size], 0x00)
-        PTR_ADDU   "%[pixels],  %[pixels],      %[addr2]                \n\t"
-        PTR_ADDU   "%[block],   %[block],       %[addr2]                \n\t"
-
-        PTR_ADDI   "%[h],       %[h],           -0x04                   \n\t"
-        "bnez       %[h],       1b                                      \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          RESTRICT_ASM_ALL64
-          RESTRICT_ASM_ADDRT
-          [addr0]"=&r"(addr[0]),            [addr1]"=&r"(addr[1]),
-          [addr2]"=&r"(addr[2]),
-          [block]"+&r"(block),              [pixels]"+&r"(pixels),
-          [h]"+&r"(h)
-        : [line_size]"r"((mips_reg)line_size)
-        : "memory"
-    );
-}
-
-void ff_avg_pixels16_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    double ftmp[8];
-    mips_reg addr[1];
-    DECLARE_VAR_ALL64;
-
-    __asm__ volatile (
-        "1:                                                             \n\t"
-        PTR_ADDI   "%[h],       %[h],           -0x04                   \n\t"
-        MMI_ULDC1(%[ftmp0], %[pixels], 0x00)
-        MMI_ULDC1(%[ftmp4], %[pixels], 0x08)
-        PTR_ADDU   "%[pixels],  %[pixels],      %[line_size]            \n\t"
-        MMI_ULDC1(%[ftmp1], %[pixels], 0x00)
-        MMI_ULDC1(%[ftmp5], %[pixels], 0x08)
-        PTR_ADDU   "%[pixels],  %[pixels],      %[line_size]            \n\t"
-        MMI_ULDC1(%[ftmp2], %[block], 0x00)
-        MMI_ULDC1(%[ftmp6], %[block], 0x08)
-        PTR_ADDU   "%[addr0],   %[block],       %[line_size]            \n\t"
-        MMI_ULDC1(%[ftmp3], %[addr0], 0x00)
-        MMI_ULDC1(%[ftmp7], %[addr0], 0x08)
-        "pavgb      %[ftmp0],   %[ftmp0],       %[ftmp2]                \n\t"
-        "pavgb      %[ftmp4],   %[ftmp4],       %[ftmp6]                \n\t"
-        "pavgb      %[ftmp1],   %[ftmp1],       %[ftmp3]                \n\t"
-        "pavgb      %[ftmp5],   %[ftmp5],       %[ftmp7]                \n\t"
-        MMI_SDC1(%[ftmp0], %[block], 0x00)
-        MMI_SDC1(%[ftmp4], %[block], 0x08)
-        MMI_SDC1(%[ftmp1], %[addr0], 0x00)
-        MMI_SDC1(%[ftmp5], %[addr0], 0x08)
-        PTR_ADDU   "%[block],   %[addr0],       %[line_size]            \n\t"
-
-        MMI_ULDC1(%[ftmp0], %[pixels], 0x00)
-        MMI_ULDC1(%[ftmp4], %[pixels], 0x08)
-        PTR_ADDU   "%[pixels],  %[pixels],      %[line_size]            \n\t"
-        MMI_ULDC1(%[ftmp1], %[pixels], 0x00)
-        MMI_ULDC1(%[ftmp5], %[pixels], 0x08)
-        PTR_ADDU   "%[pixels],  %[pixels],      %[line_size]            \n\t"
-        MMI_ULDC1(%[ftmp2], %[block], 0x00)
-        MMI_ULDC1(%[ftmp6], %[block], 0x08)
-        PTR_ADDU   "%[addr0],   %[block],       %[line_size]            \n\t"
-        MMI_ULDC1(%[ftmp3], %[addr0], 0x00)
-        MMI_ULDC1(%[ftmp7], %[addr0], 0x08)
-        "pavgb      %[ftmp0],   %[ftmp0],       %[ftmp2]                \n\t"
-        "pavgb      %[ftmp4],   %[ftmp4],       %[ftmp6]                \n\t"
-        "pavgb      %[ftmp1],   %[ftmp1],       %[ftmp3]                \n\t"
-        "pavgb      %[ftmp5],   %[ftmp5],       %[ftmp7]                \n\t"
-        MMI_SDC1(%[ftmp0], %[block], 0x00)
-        MMI_SDC1(%[ftmp4], %[block], 0x08)
-        MMI_SDC1(%[ftmp1], %[addr0], 0x00)
-        MMI_SDC1(%[ftmp5], %[addr0], 0x08)
-        PTR_ADDU   "%[block],   %[addr0],       %[line_size]            \n\t"
-
-        "bnez       %[h],       1b                                      \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          [ftmp4]"=&f"(ftmp[4]),            [ftmp5]"=&f"(ftmp[5]),
-          [ftmp6]"=&f"(ftmp[6]),            [ftmp7]"=&f"(ftmp[7]),
-          RESTRICT_ASM_ALL64
-          [addr0]"=&r"(addr[0]),
-          [block]"+&r"(block),              [pixels]"+&r"(pixels),
-          [h]"+&r"(h)
-        : [line_size]"r"((mips_reg)line_size)
-        : "memory"
-    );
-}
-
-inline void ff_put_pixels4_l2_8_mmi(uint8_t *dst, const uint8_t *src1,
-    const uint8_t *src2, int dst_stride, int src_stride1, int src_stride2,
-    int h)
-{
-    double ftmp[4];
-    mips_reg addr[5];
-    DECLARE_VAR_LOW32;
-    DECLARE_VAR_ADDRT;
-
-    __asm__ volatile (
-        "1:                                                             \n\t"
-        PTR_ADDU   "%[addr0],   %[src1],        %[src_stride1]          \n\t"
-        MMI_ULWC1(%[ftmp0], %[src1], 0x00)
-        MMI_ULWC1(%[ftmp1], %[addr0], 0x00)
-        PTR_ADDU   "%[addr1],   %[src2],        %[src_stride2]          \n\t"
-        MMI_ULWC1(%[ftmp2], %[src2], 0x00)
-        MMI_ULWC1(%[ftmp3], %[addr1], 0x00)
-        PTR_ADDU   "%[src1],    %[addr0],       %[src_stride1]          \n\t"
-        PTR_ADDU   "%[src2],    %[addr1],       %[src_stride2]          \n\t"
-
-        PTR_ADDI   "%[h],       %[h],           -0x02                   \n\t"
-
-        "pavgb      %[ftmp0],   %[ftmp0],       %[ftmp2]                \n\t"
-        "pavgb      %[ftmp1],   %[ftmp1],       %[ftmp3]                \n\t"
-        MMI_SWC1(%[ftmp0], %[dst], 0x00)
-        PTR_ADDU   "%[dst],     %[dst],         %[dst_stride]           \n\t"
-        MMI_SWC1(%[ftmp1], %[dst], 0x00)
-        PTR_ADDU   "%[dst],     %[dst],         %[dst_stride]           \n\t"
-
-        "bnez       %[h],       1b                                      \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          RESTRICT_ASM_LOW32
-          RESTRICT_ASM_ADDRT
-          [addr0]"=&r"(addr[0]),            [addr1]"=&r"(addr[1]),
-          [dst]"+&r"(dst),                  [src1]"+&r"(src1),
-          [src2]"+&r"(src2),                [h]"+&r"(h)
-        : [dst_stride]"r"((mips_reg)dst_stride),
-          [src_stride1]"r"((mips_reg)src_stride1),
-          [src_stride2]"r"((mips_reg)src_stride2)
-        : "memory"
-    );
-}
-
-inline void ff_put_pixels8_l2_8_mmi(uint8_t *dst, const uint8_t *src1,
-    const uint8_t *src2, int dst_stride, int src_stride1, int src_stride2,
-    int h)
-{
-    double ftmp[4];
-    mips_reg addr[5];
-    DECLARE_VAR_ALL64;
-    DECLARE_VAR_ADDRT;
-
-    __asm__ volatile (
-        PTR_ADDU   "%[addr2],   %[src_stride1], %[src_stride1]          \n\t"
-        PTR_ADDU   "%[addr3],   %[src_stride2], %[src_stride2]          \n\t"
-        PTR_ADDU   "%[addr4],   %[dst_stride],  %[dst_stride]           \n\t"
-
-        "1:                                                             \n\t"
-        MMI_ULDC1(%[ftmp0], %[src1], 0x00)
-        PTR_ADDU   "%[addr0],   %[src1],        %[src_stride1]          \n\t"
-        MMI_ULDC1(%[ftmp1], %[addr0], 0x00)
-        MMI_ULDC1(%[ftmp2], %[src2], 0x00)
-        PTR_ADDU   "%[addr1],   %[src2],        %[src_stride2]          \n\t"
-        MMI_ULDC1(%[ftmp3], %[addr1], 0x00)
-        PTR_ADDU   "%[src1],    %[src1],        %[addr2]                \n\t"
-        "pavgb      %[ftmp0],   %[ftmp0],       %[ftmp2]                \n\t"
-        "pavgb      %[ftmp1],   %[ftmp1],       %[ftmp3]                \n\t"
-        MMI_SDC1(%[ftmp0], %[dst], 0x00)
-        MMI_SDXC1(%[ftmp1], %[dst], %[dst_stride], 0x00)
-        PTR_ADDU   "%[src2],    %[src2],        %[addr3]                \n\t"
-        PTR_ADDU   "%[dst],     %[dst],         %[addr4]                \n\t"
-
-        MMI_ULDC1(%[ftmp0], %[src1], 0x00)
-        PTR_ADDU   "%[addr0],   %[src1],        %[src_stride1]          \n\t"
-        MMI_ULDC1(%[ftmp1], %[addr0], 0x00)
-        MMI_ULDC1(%[ftmp2], %[src2], 0x00)
-        PTR_ADDU   "%[addr1],   %[src2],        %[src_stride2]          \n\t"
-        MMI_ULDC1(%[ftmp3], %[addr1], 0x00)
-        PTR_ADDU   "%[src1],    %[src1],        %[addr2]                \n\t"
-        "pavgb      %[ftmp0],   %[ftmp0],       %[ftmp2]                \n\t"
-        "pavgb      %[ftmp1],   %[ftmp1],       %[ftmp3]                \n\t"
-        MMI_SDC1(%[ftmp0], %[dst], 0x00)
-        MMI_SDXC1(%[ftmp1], %[dst], %[dst_stride], 0x00)
-        PTR_ADDU   "%[src2],    %[src2],        %[addr3]                \n\t"
-        PTR_ADDU   "%[dst],     %[dst],         %[addr4]                \n\t"
-
-        PTR_ADDI   "%[h],       %[h],           -0x04                   \n\t"
-        "bnez       %[h],       1b                                      \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          RESTRICT_ASM_ALL64
-          RESTRICT_ASM_ADDRT
-          [addr0]"=&r"(addr[0]),            [addr1]"=&r"(addr[1]),
-          [addr2]"=&r"(addr[2]),            [addr3]"=&r"(addr[3]),
-          [addr4]"=&r"(addr[4]),
-          [dst]"+&r"(dst),                  [src1]"+&r"(src1),
-          [src2]"+&r"(src2),                [h]"+&r"(h)
-        : [dst_stride]"r"((mips_reg)dst_stride),
-          [src_stride1]"r"((mips_reg)src_stride1),
-          [src_stride2]"r"((mips_reg)src_stride2)
-        : "memory"
-    );
-}
-
-inline void ff_put_pixels16_l2_8_mmi(uint8_t *dst, const uint8_t *src1,
-    const uint8_t *src2, int dst_stride, int src_stride1, int src_stride2,
-    int h)
-{
-    double ftmp[8];
-    mips_reg addr[5];
-    DECLARE_VAR_ALL64;
-    DECLARE_VAR_ADDRT;
-
-    __asm__ volatile (
-        PTR_ADDU   "%[addr2],   %[src_stride1], %[src_stride1]          \n\t"
-        PTR_ADDU   "%[addr3],   %[src_stride2], %[src_stride2]          \n\t"
-        PTR_ADDU   "%[addr4],   %[dst_stride],  %[dst_stride]           \n\t"
-
-        "1:                                                             \n\t"
-        MMI_ULDC1(%[ftmp0], %[src1], 0x00)
-        PTR_ADDU   "%[addr0],   %[src1],        %[src_stride1]          \n\t"
-        MMI_ULDC1(%[ftmp4], %[src1], 0x08)
-        MMI_ULDC1(%[ftmp1], %[addr0], 0x00)
-        MMI_ULDC1(%[ftmp5], %[addr0], 0x08)
-        MMI_ULDC1(%[ftmp2], %[src2], 0x00)
-        PTR_ADDU   "%[addr1],   %[src2],        %[src_stride2]          \n\t"
-        MMI_ULDC1(%[ftmp6], %[src2], 0x08)
-        MMI_ULDC1(%[ftmp3], %[addr1], 0x00)
-        PTR_ADDU   "%[src1],    %[src1],        %[addr2]                \n\t"
-        MMI_ULDC1(%[ftmp7], %[addr1], 0x08)
-        "pavgb      %[ftmp0],   %[ftmp0],       %[ftmp2]                \n\t"
-        "pavgb      %[ftmp4],   %[ftmp4],       %[ftmp6]                \n\t"
-        "pavgb      %[ftmp1],   %[ftmp1],       %[ftmp3]                \n\t"
-        "pavgb      %[ftmp5],   %[ftmp5],       %[ftmp7]                \n\t"
-        MMI_SDC1(%[ftmp0], %[dst], 0x00)
-        MMI_SDXC1(%[ftmp1], %[dst], %[dst_stride], 0x00)
-        MMI_SDC1(%[ftmp4], %[dst], 0x08)
-        MMI_SDXC1(%[ftmp5], %[dst], %[dst_stride], 0x08)
-        PTR_ADDU   "%[src2],    %[src2],        %[addr3]                \n\t"
-        PTR_ADDU   "%[dst],     %[dst],         %[addr4]                \n\t"
-
-        MMI_ULDC1(%[ftmp0], %[src1], 0x00)
-        PTR_ADDU   "%[addr0],   %[src1],        %[src_stride1]          \n\t"
-        MMI_ULDC1(%[ftmp4], %[src1], 0x08)
-        MMI_ULDC1(%[ftmp1], %[addr0], 0x00)
-        MMI_ULDC1(%[ftmp5], %[addr0], 0x08)
-        MMI_ULDC1(%[ftmp2], %[src2], 0x00)
-        PTR_ADDU   "%[addr1],   %[src2],        %[src_stride2]          \n\t"
-        MMI_ULDC1(%[ftmp6], %[src2], 0x08)
-        MMI_ULDC1(%[ftmp3], %[addr1], 0x00)
-        PTR_ADDU   "%[src1],    %[src1],        %[addr2]                \n\t"
-        MMI_ULDC1(%[ftmp7], %[addr1], 0x08)
-        "pavgb      %[ftmp0],   %[ftmp0],       %[ftmp2]                \n\t"
-        "pavgb      %[ftmp4],   %[ftmp4],       %[ftmp6]                \n\t"
-        "pavgb      %[ftmp1],   %[ftmp1],       %[ftmp3]                \n\t"
-        "pavgb      %[ftmp5],   %[ftmp5],       %[ftmp7]                \n\t"
-        MMI_SDC1(%[ftmp0], %[dst], 0x00)
-        MMI_SDXC1(%[ftmp1], %[dst], %[dst_stride], 0x00)
-        MMI_SDC1(%[ftmp4], %[dst], 0x08)
-        MMI_SDXC1(%[ftmp5], %[dst], %[dst_stride], 0x08)
-        PTR_ADDU   "%[src2],    %[src2],        %[addr3]                \n\t"
-        PTR_ADDU   "%[dst],     %[dst],         %[addr4]                \n\t"
-
-        PTR_ADDI   "%[h],       %[h],           -0x04                   \n\t"
-        "bnez       %[h],       1b                                      \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          [ftmp4]"=&f"(ftmp[4]),            [ftmp5]"=&f"(ftmp[5]),
-          [ftmp6]"=&f"(ftmp[6]),            [ftmp7]"=&f"(ftmp[7]),
-          RESTRICT_ASM_ALL64
-          RESTRICT_ASM_ADDRT
-          [addr0]"=&r"(addr[0]),            [addr1]"=&r"(addr[1]),
-          [addr2]"=&r"(addr[2]),            [addr3]"=&r"(addr[3]),
-          [addr4]"=&r"(addr[4]),
-          [dst]"+&r"(dst),                  [src1]"+&r"(src1),
-          [src2]"+&r"(src2),                [h]"+&r"(h)
-        : [dst_stride]"r"((mips_reg)dst_stride),
-          [src_stride1]"r"((mips_reg)src_stride1),
-          [src_stride2]"r"((mips_reg)src_stride2)
-        : "memory"
-    );
-}
-
-inline void ff_avg_pixels4_l2_8_mmi(uint8_t *dst, const uint8_t *src1,
-    const uint8_t *src2, int dst_stride, int src_stride1, int src_stride2,
-    int h)
-{
-    double ftmp[6];
-    mips_reg addr[6];
-    DECLARE_VAR_LOW32;
-
-    __asm__ volatile (
-        "1:                                                             \n\t"
-        PTR_ADDU   "%[addr0],   %[src1],        %[src_stride1]          \n\t"
-        MMI_ULWC1(%[ftmp0], %[src1], 0x00)
-        MMI_ULWC1(%[ftmp1], %[addr0], 0x00)
-        PTR_ADDU   "%[addr1],   %[src2],        %[src_stride2]          \n\t"
-        MMI_ULWC1(%[ftmp2], %[src2], 0x00)
-        MMI_ULWC1(%[ftmp3], %[addr1], 0x00)
-        PTR_ADDU   "%[src1],    %[addr0],       %[src_stride1]          \n\t"
-        PTR_ADDU   "%[src2],    %[addr1],       %[src_stride2]          \n\t"
-        "pavgb      %[ftmp0],   %[ftmp0],       %[ftmp2]                \n\t"
-        "pavgb      %[ftmp1],   %[ftmp1],       %[ftmp3]                \n\t"
-        PTR_ADDU   "%[addr2],   %[dst],         %[dst_stride]           \n\t"
-        MMI_ULWC1(%[ftmp4], %[dst], 0x00)
-        MMI_ULWC1(%[ftmp5], %[addr2], 0x00)
-        PTR_ADDI   "%[h],       %[h],           -0x02                   \n\t"
-        "pavgb      %[ftmp0],   %[ftmp0],       %[ftmp4]                \n\t"
-        "pavgb      %[ftmp1],   %[ftmp1],       %[ftmp5]                \n\t"
-        MMI_SWC1(%[ftmp0], %[dst], 0x00)
-        MMI_SWC1(%[ftmp1], %[addr2], 0x00)
-        PTR_ADDU   "%[dst],     %[addr2],       %[dst_stride]           \n\t"
-
-        "bnez       %[h],       1b                                      \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          [ftmp4]"=&f"(ftmp[4]),            [ftmp5]"=&f"(ftmp[5]),
-          RESTRICT_ASM_LOW32
-          [addr0]"=&r"(addr[0]),            [addr1]"=&r"(addr[1]),
-          [addr2]"=&r"(addr[2]),
-          [dst]"+&r"(dst),                  [src1]"+&r"(src1),
-          [src2]"+&r"(src2),                [h]"+&r"(h)
-        : [dst_stride]"r"((mips_reg)dst_stride),
-          [src_stride1]"r"((mips_reg)src_stride1),
-          [src_stride2]"r"((mips_reg)src_stride2)
-        : "memory"
-    );
-}
-
-inline void ff_avg_pixels8_l2_8_mmi(uint8_t *dst, const uint8_t *src1,
-    const uint8_t *src2, int dst_stride, int src_stride1, int src_stride2,
-    int h)
-{
-    double ftmp[6];
-    mips_reg addr[6];
-    DECLARE_VAR_ALL64;
-    DECLARE_VAR_ADDRT;
-
-    __asm__ volatile (
-        PTR_ADDU   "%[addr2],   %[src_stride1], %[src_stride1]          \n\t"
-        PTR_ADDU   "%[addr3],   %[src_stride2], %[src_stride2]          \n\t"
-        PTR_ADDU   "%[addr4],   %[dst_stride],  %[dst_stride]           \n\t"
-
-        "1:                                                             \n\t"
-        MMI_ULDC1(%[ftmp0], %[src1], 0x00)
-        PTR_ADDU   "%[addr0],   %[src1],        %[src_stride1]          \n\t"
-        MMI_ULDC1(%[ftmp1], %[addr0], 0x00)
-        PTR_ADDU   "%[addr1],   %[src2],        %[src_stride2]          \n\t"
-        MMI_ULDC1(%[ftmp2], %[src2], 0x00)
-        MMI_ULDC1(%[ftmp3], %[addr1], 0x00)
-        PTR_ADDU   "%[src1],    %[src1],        %[addr2]                \n\t"
-        "pavgb      %[ftmp0],   %[ftmp0],       %[ftmp2]                \n\t"
-        "pavgb      %[ftmp1],   %[ftmp1],       %[ftmp3]                \n\t"
-        PTR_ADDU   "%[addr5],   %[dst],         %[dst_stride]           \n\t"
-        MMI_ULDC1(%[ftmp4], %[dst], 0x00)
-        MMI_ULDC1(%[ftmp5], %[addr5], 0x00)
-        "pavgb      %[ftmp0],   %[ftmp0],       %[ftmp4]                \n\t"
-        "pavgb      %[ftmp1],   %[ftmp1],       %[ftmp5]                \n\t"
-        MMI_SDC1(%[ftmp0], %[dst], 0x00)
-        MMI_SDXC1(%[ftmp1], %[dst], %[dst_stride], 0x00)
-        PTR_ADDU   "%[src2],    %[src2],        %[addr3]                \n\t"
-        PTR_ADDU   "%[dst],     %[dst],         %[addr4]                \n\t"
-
-        MMI_ULDC1(%[ftmp0], %[src1], 0x00)
-        PTR_ADDU   "%[addr0],   %[src1],        %[src_stride1]          \n\t"
-        MMI_ULDC1(%[ftmp1], %[addr0], 0x00)
-        PTR_ADDU   "%[addr1],   %[src2],        %[src_stride2]          \n\t"
-        MMI_ULDC1(%[ftmp2], %[src2], 0x00)
-        MMI_ULDC1(%[ftmp3], %[addr1], 0x00)
-        PTR_ADDU   "%[src1],    %[src1],        %[addr2]                \n\t"
-        "pavgb      %[ftmp0],   %[ftmp0],       %[ftmp2]                \n\t"
-        "pavgb      %[ftmp1],   %[ftmp1],       %[ftmp3]                \n\t"
-        PTR_ADDU   "%[addr5],   %[dst],         %[dst_stride]           \n\t"
-        MMI_ULDC1(%[ftmp4], %[dst], 0x00)
-        MMI_ULDC1(%[ftmp5], %[addr5], 0x00)
-        "pavgb      %[ftmp0],   %[ftmp0],       %[ftmp4]                \n\t"
-        "pavgb      %[ftmp1],   %[ftmp1],       %[ftmp5]                \n\t"
-        MMI_SDC1(%[ftmp0], %[dst], 0x00)
-        MMI_SDXC1(%[ftmp1], %[dst], %[dst_stride], 0x00)
-        PTR_ADDU   "%[src2],    %[src2],        %[addr3]                \n\t"
-        PTR_ADDU   "%[dst],     %[dst],         %[addr4]                \n\t"
-
-        PTR_ADDI   "%[h],       %[h],           -0x04                   \n\t"
-        "bnez       %[h],       1b                                      \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          [ftmp4]"=&f"(ftmp[4]),            [ftmp5]"=&f"(ftmp[5]),
-          RESTRICT_ASM_ALL64
-          RESTRICT_ASM_ADDRT
-          [addr0]"=&r"(addr[0]),            [addr1]"=&r"(addr[1]),
-          [addr2]"=&r"(addr[2]),            [addr3]"=&r"(addr[3]),
-          [addr4]"=&r"(addr[4]),            [addr5]"=&r"(addr[5]),
-          [dst]"+&r"(dst),                  [src1]"+&r"(src1),
-          [src2]"+&r"(src2),                [h]"+&r"(h)
-        : [dst_stride]"r"((mips_reg)dst_stride),
-          [src_stride1]"r"((mips_reg)src_stride1),
-          [src_stride2]"r"((mips_reg)src_stride2)
-        : "memory"
-    );
-}
-
-inline void ff_avg_pixels16_l2_8_mmi(uint8_t *dst, const uint8_t *src1,
-    const uint8_t *src2, int dst_stride, int src_stride1, int src_stride2,
-    int h)
-{
-    ff_avg_pixels8_l2_8_mmi(dst, src1, src2, dst_stride, src_stride1,
-            src_stride2, h);
-    ff_avg_pixels8_l2_8_mmi(dst + 8, src1 + 8, src2 + 8, dst_stride,
-            src_stride1, src_stride2, h);
-}
-
-void ff_put_pixels4_x2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_put_pixels4_l2_8_mmi(block, pixels, pixels + 1, line_size, line_size,
-            line_size, h);
-}
-
-void ff_put_pixels8_x2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_put_pixels8_l2_8_mmi(block, pixels, pixels + 1, line_size, line_size,
-            line_size, h);
-}
-
-void ff_put_pixels16_x2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_put_pixels16_l2_8_mmi(block, pixels, pixels + 1, line_size, line_size,
-            line_size, h);
-}
-
-void ff_avg_pixels4_x2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_avg_pixels4_l2_8_mmi(block, pixels, pixels + 1, line_size, line_size,
-            line_size, h);
-}
-
-void ff_avg_pixels8_x2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_avg_pixels8_l2_8_mmi(block, pixels, pixels + 1, line_size, line_size,
-            line_size, h);
-}
-
-void ff_avg_pixels16_x2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_avg_pixels8_x2_8_mmi(block, pixels, line_size, h);
-    ff_avg_pixels8_x2_8_mmi(block + 8, pixels + 8, line_size, h);
-}
-
-inline void ff_put_no_rnd_pixels8_l2_8_mmi(uint8_t *dst, const uint8_t *src1,
-    const uint8_t *src2, int dst_stride, int src_stride1, int src_stride2,
-    int h)
-{
-    double ftmp[5];
-    mips_reg addr[5];
-    DECLARE_VAR_ALL64;
-    DECLARE_VAR_ADDRT;
-
-    __asm__ volatile (
-        "pcmpeqb    %[ftmp4],   %[ftmp4],       %[ftmp4]                \n\t"
-        PTR_ADDU   "%[addr2],   %[src_stride1], %[src_stride1]          \n\t"
-        PTR_ADDU   "%[addr3],   %[src_stride2], %[src_stride2]          \n\t"
-        PTR_ADDU   "%[addr4],   %[dst_stride],  %[dst_stride]           \n\t"
-
-        "1:                                                             \n\t"
-        MMI_ULDC1(%[ftmp0], %[src1], 0x00)
-        PTR_ADDU   "%[addr0],   %[src1],        %[src_stride1]          \n\t"
-        MMI_ULDC1(%[ftmp1], %[addr0], 0x00)
-        MMI_ULDC1(%[ftmp2], %[src2], 0x00)
-        PTR_ADDU   "%[addr1],   %[src2],        %[src_stride2]          \n\t"
-        MMI_ULDC1(%[ftmp3], %[addr1], 0x00)
-        PTR_ADDU   "%[src1],    %[src1],        %[addr2]                \n\t"
-        "pxor       %[ftmp0],   %[ftmp0],       %[ftmp4]                \n\t"
-        "pxor       %[ftmp1],   %[ftmp1],       %[ftmp4]                \n\t"
-        "pxor       %[ftmp2],   %[ftmp2],       %[ftmp4]                \n\t"
-        "pxor       %[ftmp3],   %[ftmp3],       %[ftmp4]                \n\t"
-        "pavgb      %[ftmp0],   %[ftmp0],       %[ftmp2]                \n\t"
-        "pavgb      %[ftmp1],   %[ftmp1],       %[ftmp3]                \n\t"
-        "pxor       %[ftmp0],   %[ftmp0],       %[ftmp4]                \n\t"
-        "pxor       %[ftmp1],   %[ftmp1],       %[ftmp4]                \n\t"
-        MMI_SDC1(%[ftmp0], %[dst], 0x00)
-        MMI_SDXC1(%[ftmp1], %[dst], %[dst_stride], 0x00)
-        PTR_ADDU   "%[src2],    %[src2],        %[addr3]                \n\t"
-        PTR_ADDU   "%[dst],     %[dst],         %[addr4]                \n\t"
-
-        MMI_ULDC1(%[ftmp0], %[src1], 0x00)
-        PTR_ADDU   "%[addr0],   %[src1],        %[src_stride1]          \n\t"
-        MMI_ULDC1(%[ftmp1], %[addr0], 0x00)
-        MMI_ULDC1(%[ftmp2], %[src2], 0x00)
-        PTR_ADDU   "%[addr1],   %[src2],        %[src_stride2]          \n\t"
-        MMI_ULDC1(%[ftmp3], %[addr1], 0x00)
-        PTR_ADDU   "%[src1],    %[src1],        %[addr2]                \n\t"
-        "pxor       %[ftmp0],   %[ftmp0],       %[ftmp4]                \n\t"
-        "pxor       %[ftmp1],   %[ftmp1],       %[ftmp4]                \n\t"
-        "pxor       %[ftmp2],   %[ftmp2],       %[ftmp4]                \n\t"
-        "pxor       %[ftmp3],   %[ftmp3],       %[ftmp4]                \n\t"
-        "pavgb      %[ftmp0],   %[ftmp0],       %[ftmp2]                \n\t"
-        "pavgb      %[ftmp1],   %[ftmp1],       %[ftmp3]                \n\t"
-        "pxor       %[ftmp0],   %[ftmp0],       %[ftmp4]                \n\t"
-        "pxor       %[ftmp1],   %[ftmp1],       %[ftmp4]                \n\t"
-        MMI_SDC1(%[ftmp0], %[dst], 0x00)
-        MMI_SDXC1(%[ftmp1], %[dst], %[dst_stride], 0x00)
-        PTR_ADDU   "%[src2],    %[src2],        %[addr3]                \n\t"
-        PTR_ADDU   "%[dst],     %[dst],         %[addr4]                \n\t"
-
-        PTR_ADDI   "%[h],       %[h],           -0x04                   \n\t"
-        "bnez       %[h],       1b                                      \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          [ftmp4]"=&f"(ftmp[4]),
-          RESTRICT_ASM_ALL64
-          RESTRICT_ASM_ADDRT
-          [addr0]"=&r"(addr[0]),            [addr1]"=&r"(addr[1]),
-          [addr2]"=&r"(addr[2]),            [addr3]"=&r"(addr[3]),
-          [addr4]"=&r"(addr[4]),
-          [dst]"+&r"(dst),                  [src1]"+&r"(src1),
-          [src2]"+&r"(src2),                [h]"+&r"(h)
-        : [dst_stride]"r"((mips_reg)dst_stride),
-          [src_stride1]"r"((mips_reg)src_stride1),
-          [src_stride2]"r"((mips_reg)src_stride2)
-        : "memory"
-    );
-}
-
-void ff_put_no_rnd_pixels8_x2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_put_no_rnd_pixels8_l2_8_mmi(block, pixels, pixels + 1, line_size,
-            line_size, line_size, h);
-}
-
-void ff_put_no_rnd_pixels16_x2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_put_no_rnd_pixels8_x2_8_mmi(block, pixels, line_size, h);
-    ff_put_no_rnd_pixels8_x2_8_mmi(block + 8, pixels + 8, line_size, h);
-}
-
-void ff_put_pixels4_y2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_put_pixels4_l2_8_mmi(block, pixels, pixels + line_size, line_size,
-            line_size, line_size, h);
-}
-
-void ff_put_pixels8_y2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_put_pixels8_l2_8_mmi(block, pixels, pixels + line_size, line_size,
-            line_size, line_size, h);
-}
-
-void ff_put_pixels16_y2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_put_pixels16_l2_8_mmi(block, pixels, pixels + line_size, line_size,
-            line_size, line_size, h);
-}
-
-void ff_avg_pixels4_y2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_avg_pixels4_l2_8_mmi(block, pixels, pixels + line_size, line_size,
-            line_size, line_size, h);
-}
-
-void ff_avg_pixels8_y2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_avg_pixels8_l2_8_mmi(block, pixels, pixels + line_size, line_size,
-            line_size, line_size, h);
-}
-
-void ff_avg_pixels16_y2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_avg_pixels8_y2_8_mmi(block, pixels, line_size, h);
-    ff_avg_pixels8_y2_8_mmi(block + 8, pixels + 8, line_size, h);
-}
-
-void ff_put_no_rnd_pixels8_y2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_put_no_rnd_pixels8_l2_8_mmi(block, pixels, pixels + line_size,
-            line_size, line_size, line_size, h);
-}
-
-void ff_put_no_rnd_pixels16_y2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_put_no_rnd_pixels8_y2_8_mmi(block, pixels, line_size, h);
-    ff_put_no_rnd_pixels8_y2_8_mmi(block + 8 , pixels + 8, line_size, h);
-}
-
-void ff_put_pixels4_xy2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    /* FIXME HIGH BIT DEPTH */
-    int i;
-    const uint32_t a = AV_RN32(pixels);
-    const uint32_t b = AV_RN32(pixels + 1);
-    uint32_t l0 = (a & 0x03030303UL) +
-                  (b & 0x03030303UL) +
-                       0x02020202UL;
-    uint32_t h0 = ((a & 0xFCFCFCFCUL) >> 2) +
-                  ((b & 0xFCFCFCFCUL) >> 2);
-    uint32_t l1, h1;
-
-    pixels += line_size;
-    for (i = 0; i < h; i += 2) {
-        uint32_t a = AV_RN32(pixels);
-        uint32_t b = AV_RN32(pixels + 1);
-        l1 = (a & 0x03030303UL) +
-             (b & 0x03030303UL);
-        h1 = ((a & 0xFCFCFCFCUL) >> 2) +
-             ((b & 0xFCFCFCFCUL) >> 2);
-        *((uint32_t *) block) = h0 + h1 + (((l0 + l1) >> 2) & 0x0F0F0F0FUL);
-        pixels += line_size;
-        block  += line_size;
-        a  = AV_RN32(pixels);
-        b  = AV_RN32(pixels + 1);
-        l0 = (a & 0x03030303UL) +
-             (b & 0x03030303UL) +
-                  0x02020202UL;
-        h0 = ((a & 0xFCFCFCFCUL) >> 2) +
-             ((b & 0xFCFCFCFCUL) >> 2);
-        *((uint32_t *) block) = h0 + h1 + (((l0 + l1) >> 2) & 0x0F0F0F0FUL);
-        pixels += line_size;
-        block  += line_size;
-    }
-}
-
-void ff_put_pixels8_xy2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-#if 1
-    double ftmp[10];
-    mips_reg addr[2];
-    DECLARE_VAR_ALL64;
-    DECLARE_VAR_ADDRT;
-
-    __asm__ volatile (
-        "pxor       %[ftmp7],   %[ftmp7],       %[ftmp7]                \n\t"
-        "dli        %[addr0],   0x0f                                    \n\t"
-        "pcmpeqw    %[ftmp6],   %[ftmp6],       %[ftmp6]                \n\t"
-        "dmtc1      %[addr0],   %[ftmp8]                                \n\t"
-        "dli        %[addr0],   0x01                                    \n\t"
-        "psrlh      %[ftmp6],   %[ftmp6],       %[ftmp8]                \n\t"
-        "dmtc1      %[addr0],   %[ftmp8]                                \n\t"
-        "psllh      %[ftmp6],   %[ftmp6],       %[ftmp8]                \n\t"
-
-        "dli        %[addr0],   0x02                                    \n\t"
-        "dmtc1      %[addr0],   %[ftmp9]                                \n\t"
-        MMI_ULDC1(%[ftmp0], %[pixels], 0x00)
-        MMI_ULDC1(%[ftmp4], %[pixels], 0x01)
-        "mov.d      %[ftmp1],   %[ftmp0]                                \n\t"
-        "mov.d      %[ftmp5],   %[ftmp4]                                \n\t"
-        "punpcklbh  %[ftmp0],   %[ftmp0],       %[ftmp7]                \n\t"
-        "punpcklbh  %[ftmp4],   %[ftmp4],       %[ftmp7]                \n\t"
-        "punpckhbh  %[ftmp1],   %[ftmp1],       %[ftmp7]                \n\t"
-        "punpckhbh  %[ftmp5],   %[ftmp5],       %[ftmp7]                \n\t"
-        "paddush    %[ftmp4],   %[ftmp4],       %[ftmp0]                \n\t"
-        "paddush    %[ftmp5],   %[ftmp5],       %[ftmp1]                \n\t"
-        "xor        %[addr0],   %[addr0],       %[addr0]                \n\t"
-        PTR_ADDU   "%[pixels],  %[pixels],      %[line_size]            \n\t"
-        ".p2align   3                                                   \n\t"
-
-        "1:                                                             \n\t"
-        PTR_ADDU   "%[addr1],   %[pixels],      %[addr0]                \n\t"
-        MMI_ULDC1(%[ftmp0], %[addr1], 0x00)
-        MMI_ULDC1(%[ftmp2], %[addr1], 0x01)
-        "mov.d      %[ftmp1],   %[ftmp0]                                \n\t"
-        "mov.d      %[ftmp3],   %[ftmp2]                                \n\t"
-        "punpcklbh  %[ftmp0],   %[ftmp0],       %[ftmp7]                \n\t"
-        "punpcklbh  %[ftmp2],   %[ftmp2],       %[ftmp7]                \n\t"
-        "punpckhbh  %[ftmp1],   %[ftmp1],       %[ftmp7]                \n\t"
-        "punpckhbh  %[ftmp3],   %[ftmp3],       %[ftmp7]                \n\t"
-        "paddush    %[ftmp0],   %[ftmp0],       %[ftmp2]                \n\t"
-        "paddush    %[ftmp1],   %[ftmp1],       %[ftmp3]                \n\t"
-        "paddush    %[ftmp4],   %[ftmp4],       %[ftmp6]                \n\t"
-        "paddush    %[ftmp5],   %[ftmp5],       %[ftmp6]                \n\t"
-        "paddush    %[ftmp4],   %[ftmp4],       %[ftmp0]                \n\t"
-        "paddush    %[ftmp5],   %[ftmp5],       %[ftmp1]                \n\t"
-        "psrlh      %[ftmp4],   %[ftmp4],       %[ftmp9]                \n\t"
-        "psrlh      %[ftmp5],   %[ftmp5],       %[ftmp9]                \n\t"
-        "packushb   %[ftmp4],   %[ftmp4],       %[ftmp5]                \n\t"
-        MMI_SDXC1(%[ftmp4], %[block], %[addr0], 0x00)
-        PTR_ADDU   "%[addr0],   %[addr0],       %[line_size]            \n\t"
-        PTR_ADDU   "%[addr1],   %[pixels],      %[addr0]                \n\t"
-        MMI_ULDC1(%[ftmp2], %[addr1], 0x00)
-        MMI_ULDC1(%[ftmp4], %[addr1], 0x01)
-        "mov.d      %[ftmp3],   %[ftmp2]                                \n\t"
-        "mov.d      %[ftmp5],   %[ftmp4]                                \n\t"
-        "punpcklbh  %[ftmp2],   %[ftmp2],       %[ftmp7]                \n\t"
-        "punpcklbh  %[ftmp4],   %[ftmp4],       %[ftmp7]                \n\t"
-        "punpckhbh  %[ftmp3],   %[ftmp3],       %[ftmp7]                \n\t"
-        "punpckhbh  %[ftmp5],   %[ftmp5],       %[ftmp7]                \n\t"
-        "paddush    %[ftmp4],   %[ftmp4],       %[ftmp2]                \n\t"
-        "paddush    %[ftmp5],   %[ftmp5],       %[ftmp3]                \n\t"
-        "paddush    %[ftmp0],   %[ftmp0],       %[ftmp6]                \n\t"
-        "paddush    %[ftmp1],   %[ftmp1],       %[ftmp6]                \n\t"
-        "paddush    %[ftmp0],   %[ftmp0],       %[ftmp4]                \n\t"
-        "paddush    %[ftmp1],   %[ftmp1],       %[ftmp5]                \n\t"
-        "psrlh      %[ftmp0],   %[ftmp0],       %[ftmp9]                \n\t"
-        "psrlh      %[ftmp1],   %[ftmp1],       %[ftmp9]                \n\t"
-        "packushb   %[ftmp0],   %[ftmp0],       %[ftmp1]                \n\t"
-        MMI_SDXC1(%[ftmp0], %[block], %[addr0], 0x00)
-        PTR_ADDU   "%[addr0],   %[addr0],       %[line_size]            \n\t"
-        PTR_ADDU   "%[h],       %[h],           -0x02                   \n\t"
-        "bnez       %[h],       1b                                      \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          [ftmp4]"=&f"(ftmp[4]),            [ftmp5]"=&f"(ftmp[5]),
-          [ftmp6]"=&f"(ftmp[6]),            [ftmp7]"=&f"(ftmp[7]),
-          [ftmp8]"=&f"(ftmp[8]),            [ftmp9]"=&f"(ftmp[9]),
-          RESTRICT_ASM_ALL64
-          RESTRICT_ASM_ADDRT
-          [addr0]"=&r"(addr[0]),            [addr1]"=&r"(addr[1]),
-          [h]"+&r"(h),                      [pixels]"+&r"(pixels)
-        : [block]"r"(block),                [line_size]"r"((mips_reg)line_size)
-        : "memory"
-    );
-#else
-    /* FIXME HIGH BIT DEPTH */
-    int j;
-
-    for (j = 0; j < 2; j++) {
-        int i;
-        const uint32_t a = AV_RN32(pixels);
-        const uint32_t b = AV_RN32(pixels + 1);
-        uint32_t l0 = (a & 0x03030303UL) +
-                      (b & 0x03030303UL) +
-                           0x02020202UL;
-        uint32_t h0 = ((a & 0xFCFCFCFCUL) >> 2) +
-                      ((b & 0xFCFCFCFCUL) >> 2);
-        uint32_t l1, h1;
-
-        pixels += line_size;
-        for (i = 0; i < h; i += 2) {
-            uint32_t a = AV_RN32(pixels);
-            uint32_t b = AV_RN32(pixels + 1);
-            l1 = (a & 0x03030303UL) +
-                 (b & 0x03030303UL);
-            h1 = ((a & 0xFCFCFCFCUL) >> 2) +
-                 ((b & 0xFCFCFCFCUL) >> 2);
-            *((uint32_t *) block) = h0 + h1 + (((l0 + l1) >> 2) & 0x0F0F0F0FUL);
-            pixels += line_size;
-            block  += line_size;
-            a  = AV_RN32(pixels);
-            b  = AV_RN32(pixels + 1);
-            l0 = (a & 0x03030303UL) +
-                 (b & 0x03030303UL) +
-                      0x02020202UL;
-            h0 = ((a & 0xFCFCFCFCUL) >> 2) +
-                 ((b & 0xFCFCFCFCUL) >> 2);
-            *((uint32_t *) block) = h0 + h1 + (((l0 + l1) >> 2) & 0x0F0F0F0FUL);
-            pixels += line_size;
-            block  += line_size;
-        }
-        pixels += 4 - line_size * (h + 1);
-        block  += 4 - line_size * h;
-    }
-#endif
-}
-
-void ff_put_pixels16_xy2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_put_pixels8_xy2_8_mmi(block, pixels, line_size, h);
-    ff_put_pixels8_xy2_8_mmi(block + 8, pixels + 8, line_size, h);
-}
-
-void ff_avg_pixels4_xy2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    /* FIXME HIGH BIT DEPTH */
-    int i;
-    const uint32_t a = AV_RN32(pixels);
-    const uint32_t b = AV_RN32(pixels + 1);
-    uint32_t l0 = (a & 0x03030303UL) +
-                  (b & 0x03030303UL) +
-                       0x02020202UL;
-    uint32_t h0 = ((a & 0xFCFCFCFCUL) >> 2) +
-                  ((b & 0xFCFCFCFCUL) >> 2);
-    uint32_t l1, h1;
-
-    pixels += line_size;
-    for (i = 0; i < h; i += 2) {
-        uint32_t a = AV_RN32(pixels);
-        uint32_t b = AV_RN32(pixels + 1);
-        l1 = (a & 0x03030303UL) +
-             (b & 0x03030303UL);
-        h1 = ((a & 0xFCFCFCFCUL) >> 2) +
-             ((b & 0xFCFCFCFCUL) >> 2);
-        *((uint32_t *) block) = rnd_avg32(*((uint32_t *) block), h0 + h1 + (((l0 + l1) >> 2) & 0x0F0F0F0FUL));
-        pixels += line_size;
-        block  += line_size;
-        a  = AV_RN32(pixels);
-        b  = AV_RN32(pixels + 1);
-        l0 = (a & 0x03030303UL) +
-             (b & 0x03030303UL) +
-                  0x02020202UL;
-        h0 = ((a & 0xFCFCFCFCUL) >> 2) +
-             ((b & 0xFCFCFCFCUL) >> 2);
-        *((uint32_t *) block) = rnd_avg32(*((uint32_t *) block), h0 + h1 + (((l0 + l1) >> 2) & 0x0F0F0F0FUL));
-        pixels += line_size;
-        block  += line_size;
-    }
-}
-
-void ff_avg_pixels8_xy2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    /* FIXME HIGH BIT DEPTH */
-    int j;
-
-    for (j = 0; j < 2; j++) {
-        int i;
-        const uint32_t a = AV_RN32(pixels);
-        const uint32_t b = AV_RN32(pixels + 1);
-        uint32_t l0 = (a & 0x03030303UL) +
-                      (b & 0x03030303UL) +
-                           0x02020202UL;
-        uint32_t h0 = ((a & 0xFCFCFCFCUL) >> 2) +
-                      ((b & 0xFCFCFCFCUL) >> 2);
-        uint32_t l1, h1;
-
-        pixels += line_size;
-        for (i = 0; i < h; i += 2) {
-            uint32_t a = AV_RN32(pixels);
-            uint32_t b = AV_RN32(pixels + 1);
-            l1 = (a & 0x03030303UL) +
-                 (b & 0x03030303UL);
-            h1 = ((a & 0xFCFCFCFCUL) >> 2) +
-                 ((b & 0xFCFCFCFCUL) >> 2);
-            *((uint32_t *) block) = rnd_avg32(*((uint32_t *) block), h0 + h1 + (((l0 + l1) >> 2) & 0x0F0F0F0FUL));
-            pixels += line_size;
-            block  += line_size;
-            a  = AV_RN32(pixels);
-            b  = AV_RN32(pixels + 1);
-            l0 = (a & 0x03030303UL) +
-                 (b & 0x03030303UL) +
-                      0x02020202UL;
-            h0 = ((a & 0xFCFCFCFCUL) >> 2) +
-                 ((b & 0xFCFCFCFCUL) >> 2);
-            *((uint32_t *) block) = rnd_avg32(*((uint32_t *) block), h0 + h1 + (((l0 + l1) >> 2) & 0x0F0F0F0FUL));
-            pixels += line_size;
-            block  += line_size;
-        }
-        pixels += 4 - line_size * (h + 1);
-        block  += 4 - line_size * h;
-    }
-}
-
-void ff_avg_pixels16_xy2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_avg_pixels8_xy2_8_mmi(block, pixels, line_size, h);
-    ff_avg_pixels8_xy2_8_mmi(block + 8, pixels + 8, line_size, h);
-}
-
-void ff_put_no_rnd_pixels8_xy2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    /* FIXME HIGH BIT DEPTH */
-    int j;
-
-    for (j = 0; j < 2; j++) {
-        int i;
-        const uint32_t a = AV_RN32(pixels);
-        const uint32_t b = AV_RN32(pixels + 1);
-        uint32_t l0 = (a & 0x03030303UL) +
-                      (b & 0x03030303UL) +
-                           0x01010101UL;
-        uint32_t h0 = ((a & 0xFCFCFCFCUL) >> 2) +
-                      ((b & 0xFCFCFCFCUL) >> 2);
-        uint32_t l1, h1;
-
-        pixels += line_size;
-        for (i = 0; i < h; i += 2) {
-            uint32_t a = AV_RN32(pixels);
-            uint32_t b = AV_RN32(pixels + 1);
-            l1 = (a & 0x03030303UL) +
-                 (b & 0x03030303UL);
-            h1 = ((a & 0xFCFCFCFCUL) >> 2) +
-                 ((b & 0xFCFCFCFCUL) >> 2);
-            *((uint32_t *) block) = h0 + h1 + (((l0 + l1) >> 2) & 0x0F0F0F0FUL);
-            pixels += line_size;
-            block  += line_size;
-            a  = AV_RN32(pixels);
-            b  = AV_RN32(pixels + 1);
-            l0 = (a & 0x03030303UL) +
-                 (b & 0x03030303UL) +
-                      0x01010101UL;
-            h0 = ((a & 0xFCFCFCFCUL) >> 2) +
-                 ((b & 0xFCFCFCFCUL) >> 2);
-            *((uint32_t *) block) = h0 + h1 + (((l0 + l1) >> 2) & 0x0F0F0F0FUL);
-            pixels += line_size;
-            block  += line_size;
-        }
-        pixels += 4 - line_size * (h + 1);
-        block  += 4 - line_size * h;
-    }
-}
-
-void ff_put_no_rnd_pixels16_xy2_8_mmi(uint8_t *block, const uint8_t *pixels,
-    ptrdiff_t line_size, int h)
-{
-    ff_put_no_rnd_pixels8_xy2_8_mmi(block, pixels, line_size, h);
-    ff_put_no_rnd_pixels8_xy2_8_mmi(block + 8, pixels + 8, line_size, h);
-}
diff --git a/spaces/congsaPfin/Manga-OCR/logs/Assassin 39s Creed Mirage Game Download [CRACKED].md b/spaces/congsaPfin/Manga-OCR/logs/Assassin 39s Creed Mirage Game Download [CRACKED].md
deleted file mode 100644
index 3531cc3ebec8613f77de9dd17896696c731290d5..0000000000000000000000000000000000000000
--- a/spaces/congsaPfin/Manga-OCR/logs/Assassin 39s Creed Mirage Game Download [CRACKED].md	
+++ /dev/null
@@ -1,42 +0,0 @@
-
-<h1>Assassin's Creed Mirage: A Stealthy Return to the Series' Roots</h1>
-<p>Assassin's Creed is one of the most popular and successful video game franchises in history, with over 15 titles released since 2007. However, not all fans are happy with the direction that the series has taken in recent years, as it shifted from a stealth-action adventure to a more open-world role-playing game. If you are one of those fans who miss the original gameplay and feel of Assassin's Creed, then you might be interested in Assassin's Creed Mirage, a new game that promises to bring back the core elements that made the series great.</p>
-<p>Assassin's Creed Mirage is a homage to the first game in the series, which introduced us to the conflict between the Assassins and the Templars, two secret organizations that have been fighting for centuries over the fate of humanity. In Mirage, you will play as Basim Ibn Ishaq, a young street thief who joins the Hidden Ones, an ancient precursor of the Assassins, and learns their creed. Set in 9th-century Baghdad during the anarchy at Samarra, Mirage will take you on a journey of discovery, transformation, and revenge, as you uncover the secrets of your past and your destiny.</p>
-<h2>assassin 39;s creed mirage game download</h2><br /><p><b><b>Download Zip</b> &#10027; <a href="https://urlca.com/2uO4QI">https://urlca.com/2uO4QI</a></b></p><br /><br />
-<p>In this article, we will tell you everything you need to know about Assassin's Creed Mirage, including its story, gameplay, world, editions, pre-order bonuses, system requirements, and more. Whether you are a longtime fan of the series or a newcomer who wants to experience a modern take on its origins, Assassin's Creed Mirage is a game that you should not miss.</p>
- <h2>The Story of Basim: A Cunning Thief with a Hidden Destiny</h2>
-<p>Basim Ibn Ishaq is the protagonist of Assassin's Creed Mirage. He is a street thief who lives in Baghdad, stealing from the rich and powerful to survive. He has no family or friends, except for his loyal eagle companion Enkidu. He also suffers from nightmarish visions that haunt him every night.</p>
-<p>One day, he meets Roshan, a mysterious woman who claims to be a member of the Hidden Ones, an ancient organization that fights for freedom against tyranny. She tells him that he has a special bloodline that connects him to the Hidden Ones and their enemies, the Order of Ancients. She also reveals that his visions are actually memories of his ancestors, who were part of a secret war that spans across history.</p>
-<p>Basim decides to join Roshan and the Hidden Ones in their quest to stop the Order of Ancients from finding an ancient artifact that could give them ultimate power. Along the way, he will meet other characters who will help or hinder him in his mission. He will also travel to Alamut, the legendary fortress of the Hidden Ones where he will learn more about their creed and their history.</p>
-<p>Assassin's Creed Mirage is a narrative-driven action-adventure game that follows Basim's transformation from a defiant young man into a refined Master Assassin with a conflicted destiny. It is a powerful coming-of-age story that explores themes such as freedom, justice, loyalty, betrayal, faith, and destiny. It is also a thrilling adventure that will keep you on the edge of your seat as you explore the rich and diverse world of 9th-century Baghdad and Alamut. <h2>The Gameplay of Mirage: A Tribute to an Original Experience</h2>
-<p>Assassin's Creed Mirage is a game that pays tribute to the original experience of the series, which focused on stealth, parkour, and assassinations. You will be able to use your agility, skills, and tools to navigate the environment, avoid detection, and eliminate your targets. You will also be able to choose your own approach, whether it is silent, lethal, or a mix of both.</p>
-<p>Some of the new features and mechanics that Mirage introduces are:</p>
-<ul>
-<li><b>Assassin Focus:</b> This is a mode that allows you to slow down time and plan your moves. You can use it to mark multiple enemies and execute chain assassinations, or to escape from dangerous situations.</li>
-<li><b>Poles:</b> These are wooden poles that you can use to swing across gaps, climb up walls, or jump down on enemies. They add more verticality and fluidity to the parkour system.</li>
-<li><b>Tools:</b> You will have access to various tools that will help you in your missions. Some of them are: throwing knives, smoke bombs, poison darts, grappling hooks, and hidden blades. You can also customize and upgrade your tools to suit your playstyle.</li>
-</ul>
-<p>Assassin's Creed Mirage is a game that offers a lot of freedom and variety in its gameplay. You can explore the city at your own pace, find hidden secrets, collect treasures, complete side quests, or join world events. You can also interact with different factions and characters, such as merchants, beggars, guards, scholars, and more. The game also features a dynamic day-night cycle and weather system that affect the gameplay and the atmosphere.</p>
-<p></p>
- <h2>The World of Mirage: An Immersive, Reactive City</h2>
-<p>Assassin's Creed Mirage is set in Baghdad, the capital of the Abbasid Caliphate and one of the most prosperous and cultured cities in history. It was known as the City of Peace, the City of Scholars, and the City of a Thousand and One Nights. It was also a city of contrasts, where wealth and poverty, beauty and violence, order and chaos coexisted.</p>
-<p>The game recreates Baghdad with stunning detail and accuracy, based on historical sources and artistic references. The city is divided into four districts: The Royal District, where the caliph's palace and the Grand Mosque are located; The Commercial District, where the markets and the bazaar are bustling with activity; The Residential District, where the common people live in modest houses; and The Outskirts District, where the poor and the outcasts dwell in slums and ruins.</p>
-<p>Each district has its own identity, atmosphere, and secrets. You will be able to explore them all and discover their hidden wonders and mysteries. You will also encounter historical figures and events that shaped the Golden Age of Baghdad, such as Harun al-Rashid, Al-Khwarizmi, I see that you are interested in Assassin's Creed Mirage, the upcoming game from Ubisoft. I have searched the web for some information that might be useful for you. Here are some of the topics that I found: - Assassin's Creed Mirage release date: The game is set to be released on October 12, 2023 for Microsoft Windows, PlayStation 4, PlayStation 5, Xbox One, Xbox Series X/S, and Amazon Luna. The game will be made available on Day 1 for all players subscribed to Ubisoft+. - Assassin's Creed Mirage gameplay: The game is a homage to the first game in the series, which focused on stealth, parkour, and assassinations. You will play as Basim Ibn Ishaq, a young street thief who joins the Hidden Ones, an ancient precursor of the Assassins, and learns their creed. You will be able to use your agility, skills, and tools to navigate the environment, avoid detection, and eliminate your targets. You will also be able to choose your own approach, whether it is silent, lethal, or a mix of both. Some of the new features and mechanics that Mirage introduces are: Assassin Focus, which allows you to slow down time and plan your moves; poles, which let you swing across gaps, climb up walls, or jump down on enemies; and tools, such as throwing knives, smoke bombs, poison darts, grappling hooks, and hidden blades . - Assassin's Creed Mirage world: The game is set in Baghdad, the capital of the Abbasid Caliphate and one of the most prosperous and cultured cities in history. It was known as the City of Peace, the City of Scholars, and the City of a Thousand and One Nights. It was also a city of contrasts, where wealth and poverty, beauty and violence, order and chaos coexisted. The game recreates Baghdad with stunning detail and accuracy, based on historical sources and artistic references. The city is divided into four districts: The Royal District, where the caliph's palace and the Grand Mosque are located; The Commercial District, where the markets and the bazaar are bustling with activity; The Residential District, where the common people live in modest houses; and The Outskirts District, where the poor and the outcasts dwell in slums and ruins. Each district has its own identity, atmosphere, and secrets. You will be able to explore them all and discover their hidden wonders and mysteries. You will also encounter historical figures and events that shaped the Golden Age of Baghdad . - Assassin's Creed Mirage editions and pre-order bonuses: The game has three editions: standard ($49.99), deluxe ($59.99), and collector's ($149.99). The standard edition comes with the game itself and a bonus quest called The Forty Thieves if you pre-order it. The deluxe edition comes with the game, the bonus quest, and the Deluxe Pack, which includes a Prince of Persia-inspired outfit, a scimitar sword, and a camel mount. The collector's edition comes with the game, the bonus quest, the Deluxe Pack, and the Collector's Box, which includes a 12-inch figurine of Basim, a steelbook case, an art book, a soundtrack CD, a map of Baghdad, and a lithograph . You can pre-order any of these editions from the official Ubisoft store or from other retailers. <h2>Conclusion: Why You Should Play Assassin's Creed Mirage</h2>
-<p>Assassin's Creed Mirage is a game that will appeal to both fans and newcomers of the series. It is a game that honors the legacy of the first Assassin's Creed game, while also adding new features and improvements that make it a modern and enjoyable experience. It is a game that tells a compelling story of a young thief who becomes a Master Assassin with a hidden destiny. It is a game that lets you explore a beautiful and immersive world of 9th-century Baghdad and Alamut. It is a game that offers you a lot of freedom and variety in how you play and what you do.</p>
-<p>If you are looking for a game that will challenge your skills, immerse you in a rich and diverse world, and entertain you with an engaging and thrilling adventure, then Assassin's Creed Mirage is the game for you. Don't miss this opportunity to relive the origins of the series and to experience a stealthy return to its roots.</p>
-<p>Pre-order Assassin's Creed Mirage today and get ready for an unforgettable journey.</p>
- <h3>FAQs</h3>
-<ul>
-<li><b>Q: When will Assassin's Creed Mirage be released?</b></li>
-<li>A: The game will be released on October 12, 2023 for Microsoft Windows, PlayStation 4, PlayStation 5, Xbox One, Xbox Series X/S, and Amazon Luna.</li>
-<li><b>Q: Who is the protagonist of Assassin's Creed Mirage?</b></li>
-<li>A: The protagonist is Basim Ibn Ishaq, a young street thief who joins the Hidden Ones, an ancient precursor of the Assassins.</li>
-<li><b>Q: Where is Assassin's Creed Mirage set?</b></li>
-<li>A: The game is set in Baghdad, the capital of the Abbasid Caliphate and one of the most prosperous and cultured cities in history.</li>
-<li><b>Q: What are some of the new features and mechanics of Assassin's Creed Mirage?</b></li>
-<li>A: Some of the new features and mechanics are: Assassin Focus, which allows you to slow down time and plan your moves; poles, which let you swing across gaps, climb up walls, or jump down on enemies; and tools, such as throwing knives, smoke bombs, poison darts, grappling hooks, and hidden blades.</li>
-<li><b>Q: What are some of the editions and pre-order bonuses of Assassin's Creed Mirage?</b></li>
-<li>A: The game has three editions: standard ($49.99), deluxe ($59.99), and collector's ($149.99). The standard edition comes with the game itself and a bonus quest called The Forty Thieves if you pre-order it. The deluxe edition comes with the game, the bonus quest, and the Deluxe Pack, which includes a Prince of Persia-inspired outfit, a scimitar sword, and a camel mount. The collector's edition comes with the game, the bonus quest, the Deluxe Pack, and the Collector's Box, which includes a 12-inch figurine of Basim, a steelbook case, an art book, a soundtrack CD, a map of Baghdad, and a lithograph.</li>
-</ul></p> 401be4b1e0<br />
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diff --git a/spaces/congsaPfin/Manga-OCR/logs/Boomplay Stream and Download Music from Your Favorite Artists and Genres.md b/spaces/congsaPfin/Manga-OCR/logs/Boomplay Stream and Download Music from Your Favorite Artists and Genres.md
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-
-<h1>Boomplay: The Home of Music for Africa and Beyond</h1>
-<p>If you are looking for a music streaming and download service that offers you millions of songs from various genres and artists, both African and international, then you should check out Boomplay. Boomplay is a platform that lets you enjoy music anytime, anywhere, with or without internet connection. In this article, we will tell you everything you need to know about Boomplay, including what it is, how to use it, why you should choose it, what are some of its best features, and how to get started with it.</p>
- <h2>What is Boomplay?</h2>
-<h3>A brief introduction to the platform and its features</h3>
-<p>Boomplay or Boomplay Music is an Africa-focused media streaming and download service that was launched in Nigeria in 2015 by TECNO Mobile, Transsion Holdings. It has since expanded to other African countries such as Ghana, Tanzania, Kenya, Uganda, Zambia, Rwanda, Cameroon, Senegal, Ivory Coast, Mali, and more. It also has a global presence with users from over 200 countries.</p>
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- <h3>How to use Boomplay to stream and download music</h3>
-<p>To use Boomplay to stream and download music, you need to have the app installed on your Android or iOS device. You can download the app from Google Play Store or App Store for free. Once you have the app, you can browse through the music library and categories to find your favorite songs or discover new ones. You can also search for songs by title, artist, album, or keyword. You can play any song by tapping on it or add it to your playlist by tapping on the plus icon. You can also download any song by tapping on the download icon or stream it online by tapping on the play icon. You can also adjust the sound quality and playback mode according to your preference.</p>
- <h2>Why choose Boomplay?</h2>
-<h3>The benefits of Boomplay for music lovers</h3>
-<p>Boomplay is a great choice for music lovers because it offers you many benefits such as:</p>
-<ul>
-<li>A large and diverse music library that caters to your taste and mood</li>
-<li>A personalized and user-friendly interface that makes it easy to find and enjoy music</li>
-<li>A free and flexible service that allows you to stream and download music with or without internet connection</li>
-<li>A rewarding system that gives you coins for listening to music <li>A social and interactive platform that lets you follow, chat, and share music with other users</li>
-<li>A live and exclusive platform that hosts concerts, events, and podcasts from your favorite artists</li>
-</ul>
- <h3>The benefits of Boomplay for artists and labels</h3>
-<p>Boomplay is also a great choice for artists and labels because it offers you many benefits such as:</p>
-<ul>
-<li>A large and loyal audience that appreciates and supports your music</li>
-<li>A fair and transparent revenue system that pays you for your streams and downloads</li>
-<li>A powerful and flexible distribution system that lets you upload and manage your music easily</li>
-<li>A professional and supportive team that helps you with promotion, marketing, and analytics</li>
-<li>A creative and collaborative platform that connects you with other artists and opportunities</li>
-</ul>
- <h2>What are some of the best features of Boomplay?</h2>
-<h3>Personalized playlists and recommendations</h3>
-<p>Boomplay helps you discover new music that suits your taste and mood by providing you with personalized playlists and recommendations. You can find playlists for different genres, moods, occasions, themes, countries, languages, etc. You can also find recommendations based on your listening history, preferences, and trends. You can also create your own playlists and share them with other users or follow other users' playlists.</p>
- <h3>Offline mode and media player</h3>
-<p>Boomplay allows you to enjoy music offline by downloading songs to your device. You can download songs for free or with coins that you can earn or buy on the app. You can also use Boomplay as a media player to play your local music files from your SD card or phone. You can also adjust the sound quality and playback mode according to your preference.</p>
- <h3>Live stream and social interaction</h3>
-<p>Boomplay lets you watch live concerts, events, and podcasts from your favorite artists on the app. You can also chat with other users and interact with the artists during the live stream. You can also follow, like, comment, and share music with other users on the app. You can also join groups and forums to discuss music topics with other users.</p>
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-<p>To use Boomplay, you need to create an account and log in. You can create an account by using your phone number, email address, Facebook account, or Google account. You can also log in by using any of these methods. Once you create an account, you can choose a username, password, profile picture, and bio. You can also edit your profile settings later.</p>
- <h3>How to access the music library and categories</h3>
-<p>To access the music library and categories on Boomplay, you need to tap on the Music icon at the bottom of the screen. You will see different tabs such as Home, Charts, Categories, Playlists, etc. You can swipe left or right to browse through them. You can also tap on the Search icon at the top of the screen to search for songs by title, artist, album, or keyword.</p>
- <h2>Conclusion</h2>
-<h3>A summary of the main points and a call to action</h3>
-<p>Boomplay is a music streaming and download service that focuses on African and international music. It offers you millions of songs from various genres and artists that you can play and download for free or with coins. It also offers you personalized playlists and recommendations, offline mode and media player, live stream and social interaction, and many other features that make it a great choice for music lovers and artists alike. If you want to enjoy music anytime, anywhere, with or without internet connection, then you should download Boomplay today and join the community of over 100 million users.</p>
- <h2>FAQs</h2>
-<h4>Is Boomplay free to use?</h4>
-<p>Yes, Boomplay is free to use for streaming and downloading millions of songs. However, some songs may require coins to download or play in high quality. You can earn coins by listening to music, watching ads, inviting friends, or completing tasks on the app. You can also buy coins with real money if you want.</p>
- <h4>How can I get more coins on Boomplay?</h4>
-<p <p>You can get more coins on Boomplay by listening to music, watching ads, inviting friends, or completing tasks on the app. You can also buy coins with real money if you want. You can check your coin balance and history by tapping on the Coin icon at the top of the screen. You can also see the coin price and payment methods by tapping on the Buy icon next to it.</p>
- <h4>How can I upload my music on Boomplay?</h4>
-<p>If you are an artist or a label and you want to upload your music on Boomplay, you need to register as a content provider on the Boomplay website. You will need to provide some information and documents such as your name, email, phone number, country, ID card, bank account, etc. You will also need to agree to the terms and conditions of the service. Once you are verified, you can upload your music and manage your account on the website or the app.</p>
- <h4>How can I contact Boomplay customer service?</h4>
-<p>If you have any questions, feedback, or issues with Boomplay, you can contact Boomplay customer service by using any of the following methods:</p>
-<ul>
-<li>Email: feedback.boomplay@transsnet.com</li>
-<li>Phone: +234 817 095 6333</li>
-<li>Facebook: https://www.facebook.com/BoomplayMusicNG/</li>
-<li>Twitter: https://twitter.com/BoomplayMusicNG</li>
-<li>Instagram: https://www.instagram.com/boomplaymusicng/</li>
-</ul>
- <h4>What are some of the popular artists on Boomplay?</h4>
-<p>Some of the popular artists on Boomplay are:</p>
-<table>
-<tr><th>Artist</th><th>Genre</th><th>Country</th></tr>
-<tr><td>Davido</td><td>Afrobeats</td><td>Nigeria</td></tr>
-<tr><td>Burna Boy</td><td>Afro-fusion</td><td>Nigeria</td></tr>
-<tr><td>Diamond Platnumz</td><td>Bongo Flava</td><td>Tanzania</td></tr>
-<tr><td>Sarkodie</td><td>Hip Hop</td><td>Ghana</td></tr>
-<tr><td>Sinach</td><td>Gospel</td><td>Nigeria</td></tr>
-<tr><td>Ed Sheeran</td><td>Pop</td><td>UK</td></tr>
-<tr><td>Beyoncé</td><td>R&B</td><td>USA</td></tr>
-<tr><td>Drake</td><td>Hip Hop</td><td>Canada</td></tr>
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-<tr><td>Taylor Swift</td><td>Pop/Country</td><td>USA</td></tr>
-</table></p> 401be4b1e0<br />
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diff --git a/spaces/congsaPfin/Manga-OCR/logs/MasterCraft 2021 APK A New Sandbox Game with Unique Animals and Monsters.md b/spaces/congsaPfin/Manga-OCR/logs/MasterCraft 2021 APK A New Sandbox Game with Unique Animals and Monsters.md
deleted file mode 100644
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--- a/spaces/congsaPfin/Manga-OCR/logs/MasterCraft 2021 APK A New Sandbox Game with Unique Animals and Monsters.md	
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-<h1>Mastercraft 2021 APK: A New Free Building Game for Android</h1>
-<p>If you are a fan of crafting and building games, you might want to check out Mastercraft 2021 APK, a new free building game for Android devices. Mastercraft 2021 APK is a 3D sandbox game that lets you create your own world with unlimited resources and explore it with your friends. You can build houses, castles, farms, cities, and anything else you can imagine. You can also survive in different biomes, fight monsters, and collect items. Mastercraft 2021 APK is a great game for anyone who loves creativity and adventure.</p>
-<h2>What is Mastercraft 2021 APK?</h2>
-<p>Mastercraft 2021 APK is a new version of the popular Mastercraft game that was released in 2019. It is a free crafting and building game that is inspired by Minecraft, but has its own unique features and gameplay. Mastercraft 2021 APK is not an official app of Mojang or Microsoft, but it is developed by an independent developer called Krafts Building Minecrafting. The game is available for Android devices only and can be downloaded from various sources online.</p>
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-<h3>Features of Mastercraft 2021 APK</h3>
-<p>Mastercraft 2021 APK has many features that make it an enjoyable and exciting game for players of all ages. Here are some of the main features of the game:</p>
-<h4>- 3D Sandbox free simulator construction game</h4>
-<p>Mastercraft 2021 APK is a sandbox game that gives you complete freedom to create your own world. You can use different blocks, tools, and items to build anything you want. You can also destroy and modify your environment as you wish. There are no limits to your imagination in this game.</p>
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-<p>Mastercraft 2021 APK is also a building simulator that lets you craft various items and structures. You can use different materials, recipes, and blueprints to make furniture, weapons, armor, vehicles, and more. You can also customize your character with different skins, clothes, and accessories.</p>
-<h4>- Cool graphics: best pixel graphics with high fps</h4>
-<p>Mastercraft 2021 APK has cool graphics that are designed to look like pixel art. The game has a retro style that is colorful and charming. The game also runs smoothly with high fps (frames per second), which means that the gameplay is fast and smooth.</p>
-<h4>- Crafting and building 2021 during day, survive at night</h4>
-<p>Mastercraft 2021 APK has two modes: creative mode and survival mode. In creative mode, you can craft and build without any restrictions or dangers. You can also fly around your world and explore it freely. In survival mode, you have to gather resources, craft tools and weapons, and defend yourself from enemies. You also have to manage your hunger, health, and stamina levels. You can switch between the two modes anytime you want.</p>
-<h3>How to download and install Mastercraft 2021 APK?</h3>
-<p>If you want to play Mastercraft 2021 APK on your Android device, you have to follow these steps:</p>
-<h4>- Download the APK file from a trusted source</h4>
-<p>You can download the APK file of Mastercraft 2021 from various websites online. However, you have to be careful about the source of the file and make sure that it is safe and virus-free. You can also scan the file with an antivirus app before installing it. Some of the websites that offer the APK file of Mastercraft 2021 are APKPure, APKCombo, and APKFab. You can also use the links below to download the file directly:</p>
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-<h4>- Enable unknown sources on your device settings</h4>
-<p>Since Mastercraft 2021 APK is not available on the Google Play Store, you have to enable unknown sources on your device settings to install it. This will allow you to install apps from sources other than the Play Store. To do this, follow these steps:</p>
-<ol>
-<li>Go to your device settings and tap on security or privacy.</li>
-<li>Find the option that says unknown sources or install unknown apps and toggle it on.</li>
-<li>Confirm your choice by tapping OK or Allow.</li>
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-<h4>- Install the APK file and launch the game</h4>
-<p>Once you have downloaded the APK file and enabled unknown sources, you can install the game by following these steps:</p>
-<ol>
-<li>Locate the APK file on your device storage using a file manager app or your browser downloads.</li>
-<li>Tap on the file and select install.</li>
-<li>Wait for the installation process to finish and tap open or launch.</li>
-<li>Enjoy playing Mastercraft 2021 APK on your device.</li>
-</ol>
-<h3>Pros and cons of Mastercraft 2021 APK</h3>
-<p>Mastercraft 2021 APK is a fun and creative game, but it also has some drawbacks. Here are some of the pros and cons of the game:</p>
-<h4>- Pros: free, fun, creative, addictive, multiplayer mode</h4>
-<p>One of the best things about Mastercraft 2021 APK is that it is free to play. You don't have to pay anything to download or play the game. You can also enjoy unlimited resources and features in the game without any restrictions. The game is also very fun and creative, as you can build anything you want and explore different worlds. The game is also very addictive, as you can spend hours crafting, building, and surviving in the game. The game also has a multiplayer mode, where you can play with your friends online and share your creations with them.</p>
-<h4>- Cons: bugs, glitches, ads, requires internet connection</h4>
-<p>One of the drawbacks of Mastercraft 2021 APK is that it has some bugs and glitches that can affect the gameplay. For example, some users have reported that the game crashes, freezes, or lags sometimes. The game also has some ads that can be annoying or intrusive. The game also requires an internet connection to play, which means that you can't play it offline or without wifi. The game also consumes a lot of battery and data, so you have to be careful about that.</p>
-<h2>Conclusion</h2>
-<p>Mastercraft 2021 APK is a new free building game for Android devices that lets you create your own world with unlimited resources and explore it with your friends. The game is inspired by Minecraft, but has its own unique features and gameplay. The game has cool graphics, two modes, and many items and structures to craft and build. The game is also easy to download and install from various sources online. However, the game also has some drawbacks, such as bugs, glitches, ads, and internet requirement. Overall, Mastercraft 2021 APK is a great game for anyone who loves creativity and adventure.</p>
-<h2>FAQs</h2>
-<p>Here are some of the frequently asked questions about Mastercraft 2021 APK:</p>
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-<li><b>Is Mastercraft 2021 APK safe to download and install?</b></li>
-<p>Yes, Mastercraft 2021 APK is safe to download and install as long as you get it from a trusted source and scan it with an antivirus app before installing it. However, you should always be careful about downloading apps from unknown sources and enable unknown sources on your device settings at your own risk.</p>
-<li><b>Is Mastercraft 2021 APK compatible with my device?</b></li>
-<p>Mastercraft 2021 APK is compatible with most Android devices that have Android 4.4 or higher versions. However, some devices may not support the game or run it smoothly due to different specifications or performance issues.</p>
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-<p>You can update Mastercraft 2021 APK by downloading the latest version of the APK file from the same source you got it from and installing it over the existing one. You can also check for updates within the game settings and follow the instructions to update the game.</p>
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-<p>You can contact the developer of Mastercraft 2021 APK by sending an email to kraftsbuildingminecrafting@gmail.com. You can also follow their Facebook page or YouTube channel for more information and updates about the game.</p>
-</ul></p> 197e85843d<br />
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diff --git a/spaces/congsaPfin/Manga-OCR/logs/Paint Your Way Through the Maze in Tomb of the Mask Color.md b/spaces/congsaPfin/Manga-OCR/logs/Paint Your Way Through the Maze in Tomb of the Mask Color.md
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-<h1>Tomb of the Mask: Color - A Fun and Challenging Arcade Puzzle Game</h1>
- <p>If you are looking for a game that can test your reflexes, wits, and patience, you might want to check out <strong>Tomb of the Mask: Color</strong>, a brain-teasing arcade puzzle game that will keep you hooked for hours. In this game, you will explore various dungeons filled with treasures, traps, and colors. Your goal is to paint every corner of the labyrinth with your mystic mask and escape to the next one. Sounds easy? Think again. You will encounter many obstacles and enemies that will try to stop you or kill you. You will also need to plan your moves carefully and sometimes backtrack to reach every spot. Are you ready to take on this challenge? Read on to find out more about this game and how to download it on your device.</p>
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- <h2>What is Tomb of the Mask: Color?</h2>
- <p><strong>Tomb of the Mask: Color</strong> is a sequel to the popular mobile game <strong>Tomb of the Mask</strong>, which was released in 2016 by Playgendary, a developer of fun and addictive hyper-casual games. The game has been downloaded more than 100 million times from the Google Play Store alone and has earned positive reviews from players and critics alike. The game is inspired by retro arcade games and features pixel art graphics, simple controls, and fast-paced gameplay.</p>
- <p>The sequel follows the same formula but adds a new twist: you have to color the maze with your mask as you move from wall to wall. This adds a new layer of difficulty and strategy to the game, as you have to cover every inch of the dungeon while avoiding traps, enemies, and dead ends. The game also offers more features, such as different masks, boosters, power-ups, and game modes.</p>
- <h3>The gameplay</h3>
- <p>The gameplay of <strong>Tomb of the Mask: Color</strong> is very easy to learn but hard to master. You control a character who wears a mask that allows him to move from one wall to another by swiping on the screen. You can swipe in any direction: up, down, left, or right. As you move, you will paint the path you have crossed with your color. Your objective is to paint over every corner of the dungeon and reach the exit.</p>
- <p>However, it's not as simple as it sounds. You will encounter many obstacles and enemies along the way that will make your life difficult. Some examples are spikes, lasers, cannons, bats, ghosts, and more. If you touch any of them, you will lose a life and restart from the beginning of the level. You only have three lives per level, so be careful.</p>
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- <p>You will also need to think ahead and plan your moves wisely. Some dungeons are not linear and have multiple paths or loops. You may need to backtrack or take detours to reach every spot. Sometimes, you will also find switches or buttons that activate or deactivate certain traps or platforms. You have to use them strategically to clear your way.</p>
- <p>On the bright side, you will also find some helpful items and power-ups that will give you an edge. For example, coins that you can collect and use to buy new masks or revive yourself; stars that give you extra points; magnets that attract coins; shields that protect you from one hit; rockets that launch you forward; bombs that clear nearby enemies; and more.</p>
- <p>The game has hundreds of levels for you to complete, each one with its own layout, difficulty, and challenges. You can also play different game modes, such as Arcade Mode where you have to survive as long as possible in an endless dungeon; Time Mode where you have to finish a level within a time limit; Boss Mode where you have to defeat a powerful enemy; and more.</p>
- <h3>The features</h3> <p>The game also has many features that make it more fun and enjoyable. Some of them are:</p>
- <ul>
-<li><strong>Different masks</strong>: You can unlock and wear different masks that have different abilities and effects. For example, some masks can change the color of your paint, some can give you extra lives, some can make you faster or slower, and some can even transform you into a different creature. You can buy masks with coins or watch ads to get them for free.</li>
-<li><strong>Boosters</strong>: You can also use boosters to enhance your performance or overcome difficult levels. For example, you can use a skip booster to skip a level, a hint booster to show you the optimal path, a freeze booster to stop the enemies for a few seconds, and more. You can buy boosters with coins or watch ads to get them for free.</li>
-<li><strong>Leaderboards and achievements</strong>: You can also compete with other players around the world and see how you rank on the global leaderboards. You can also earn achievements by completing certain tasks or milestones in the game.</li>
-<li><strong>Daily challenges and rewards</strong>: The game also offers daily challenges and rewards that you can complete and claim every day. For example, you can get coins, stars, masks, boosters, and more by playing the game for a certain amount of time, completing a certain number of levels, collecting a certain amount of coins, and more.</li>
-</ul>
- <h3>The tips and tricks</h3>
- <p>If you want to master <strong>Tomb of the Mask: Color</strong> and beat every level with ease, here are some tips and tricks that you should know:</p>
- <ul>
-<li><strong>Practice your swiping skills</strong>: The game requires quick and precise swiping to move your character from wall to wall. You should practice your swiping skills and get familiar with the controls. You should also avoid swiping too fast or too slow, as this may cause you to miss your target or overshoot your destination.</li>
-<li><strong>Plan your moves ahead</strong>: The game also requires strategic thinking and planning to cover every corner of the dungeon. You should look at the whole map before you start moving and plan your moves ahead. You should also try to find the shortest or easiest path to complete the level. Sometimes, you may need to backtrack or take detours to reach every spot.</li>
-<li><strong>Use the power-ups wisely</strong>: The game also provides various power-ups that can help you in different situations. You should use them wisely and at the right time. For example, you should use the shield when you are about to encounter a trap or an enemy, you should use the rocket when you need to move fast or skip a difficult section, you should use the bomb when you are surrounded by enemies, and so on.</li>
-<li><strong>Watch out for the enemies</strong>: The game also features many enemies that will try to stop you or kill you. You should watch out for them and avoid them as much as possible. Some enemies are stationary and some are moving. Some enemies can shoot projectiles at you and some can chase you. You should learn their patterns and behaviors and act accordingly.</li>
-<li><strong>Collect coins and stars</strong>: The game also rewards you with coins and stars for your performance. You should collect as many coins and stars as possible, as they can help you buy new masks, boosters, or revive yourself. You can also find coins and stars in hidden areas or secret passages, so be sure to explore every nook and cranny of the dungeon.</li>
-</ul>
- <h2>How to download Tomb of the Mask: Color?</h2>
- <p>If you are interested in playing <strong>Tomb of the Mask: Color</strong>, you can download it for free on your device. The game is available for iOS, Android, PC, and Mac devices. Here is how to download it on each platform:</p>
- <h3>For iOS devices</h3>
- <p>If you have an iPhone or iPad, you can download <strong>Tomb of the Mask: Color</strong> from the App Store. Here are the steps:</p>
- <ol>
-<li>Open the App Store on your device.</li>
-<li>Search for "Tomb of the Mask: Color" in the search bar.</li>
-<li>Tap on the game icon that appears in the results.</li>
-<li>Tap on "Get" or "Install" to download the game.</li>
-<li>Wait for the download to finish and then tap on "Open" to launch the game.</li>
-</ol>
- <p>The game requires iOS 10.0 or later and 262 MB of free space on your device.</p>
- <h3>For Android devices</h3>
- <p>If you have an Android phone or tablet, you can download <strong>Tomb of the Mask: Color</strong> from the Google Play Store. Here are the steps:</p>
- <ol>
-<li>Open the Google Play Store on your device.</li>
-<li>Search for "Tomb of the Mask: Color" in the search bar.</li>
-<li>Tap on the game icon that appears in the results.</li>
-<li>Tap on "Install" to download the game.</li>
-<li>Wait for the download to finish and then tap on "Open" to launch the game.</li>
-</ol>
- <p>The game requires Android 5.0 or later and 115 MB of free space on your device.</p>
- <h3>For PC and Mac</h3>
- <p>If you have a PC or Mac, you can also play <strong>Tomb of the Mask: Color</strong> on your computer. However, you will need to use an emulator software that can run mobile apps on your desktop. One of the most popular and reliable emulators is BlueStacks, which is free and easy to use. Here are the steps to download and play the game using BlueStacks:</p>
- <ol>
-<li>Go to <a href="">https://www.bluestacks.com/</a> and download the latest version of BlueStacks for your PC or Mac.</li>
-<li>Install BlueStacks on your computer and follow the instructions on the screen.</li>
-<li>Launch BlueStacks and sign in with your Google account or create a new one.</li>
-<li>Go to the home screen of BlueStacks and click on the Google Play Store icon.</li>
-<li>Search for "Tomb of the Mask: Color" in the search bar.</li>
-<li>Click on the game icon that appears in the results.</li>
-<li>Click on "Install" to download the game.</li>
-<li>Wait for the download to finish and then click on "Open" to launch the game.</li>
-</ol>
- <p>You can now play <strong>Tomb of the Mask: Color</strong> on your PC or Mac using your mouse or keyboard. You can also customize the settings and preferences of BlueStacks according to your needs.</p>
- <h2>Conclusion</h2>
- <p><strong>Tomb of the Mask: Color</strong> is a fun and challenging arcade puzzle game that will test your skills and strategy. You will have to paint every corner of the dungeon with your mask and escape to the next one while avoiding traps, enemies, and dead ends. You will also enjoy the retro-style graphics, simple controls, and fast-paced gameplay. The game also offers many features, such as different masks, boosters, power-ups, and game modes. You can download the game for free on your iOS, Android, PC, or Mac device and start playing right away.</p>
- <h3>Why you should play Tomb of the Mask: Color</h3>
- <p>Here are some reasons why you should play <strong>Tomb of the Mask: Color</strong>:</p>
- <ul>
-<li><strong>It's fun and addictive</strong>: The game is very entertaining and addictive. You will never get bored of exploring different dungeons, collecting coins and stars, unlocking new masks, using power-ups, and completing challenges. You will always want to play one more level or beat your high score.</li>
-<li><strong>It's challenging and rewarding</strong>: The game is also very challenging and rewarding. You will have to use your brain and reflexes to solve each puzzle and overcome each obstacle. You will feel a sense of accomplishment and satisfaction when you finish a level or defeat a boss.</li>
-<li><strong>It's suitable for everyone</strong>: The game is also suitable for everyone, regardless of age or skill level. The game has a simple premise and easy controls that anyone can learn quickly. The game also has different difficulty levels and modes that cater to different preferences and abilities.</li>
-</ul>
- <h3>FAQs</h3>
- <p>Here are some frequently asked questions about <strong>Tomb of the Mask: Color</strong>:</p>
- <ol>
-<li><strong>How many levels are there in Tomb of the Mask: Color?</strong></li>
-<p>The game has hundreds of levels for you to complete, each one with its own layout, difficulty, and challenges. The game also updates regularly with new levels and features.</p>
-<li><strong>How can I get more coins in Tomb of the Mask: Color?</strong></li>
-<p>You can get more coins by playing the game regularly, collecting them in each level, completing daily challenges and rewards, watching ads, or buying them with real money.</p>
-<li><strong>How can I change my mask in Tomb of the Mask: Color?</strong></li>
-<p>You can change your mask by going to the shop menu and selecting a mask that you have unlocked or bought. You can also swipe left or right on the screen to change your mask randomly.</p>
-<li><strong>How can I play Tomb of the Mask: Color offline?</strong></li>
-<p>You can play <strong>Tomb of the Mask: Color</strong> offline without an internet connection. However, you will not be able to access some features, such as watching ads, buying coins, or competing on the leaderboards.</p>
-<li><strong>Is Tomb of the Mask: Color safe for kids?</strong></li>
-<p><strong>Tomb of the Mask: Color</strong> is safe for kids to play, as it does not contain any violence, gore, or inappropriate content. The game is rated 4+ on the App Store and Everyone on the Google Play Store. However, parents should be aware that the game contains ads and in-app purchases that may require parental supervision or consent.</p>
-</ol></p> 197e85843d<br />
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diff --git a/spaces/congsaPfin/Manga-OCR/logs/Review Stumble Guys 0.44.1 APK Seru Main di Map Hot Wheels Ini Tips dan Triknya.md b/spaces/congsaPfin/Manga-OCR/logs/Review Stumble Guys 0.44.1 APK Seru Main di Map Hot Wheels Ini Tips dan Triknya.md
deleted file mode 100644
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--- a/spaces/congsaPfin/Manga-OCR/logs/Review Stumble Guys 0.44.1 APK Seru Main di Map Hot Wheels Ini Tips dan Triknya.md	
+++ /dev/null
@@ -1,126 +0,0 @@
-
-<h1>Apk Stumble Guys Yang Baru: Cara Download dan Main Game Seru Ini</h1>
-<p>Stumble Guys adalah salah satu game Android yang sedang populer saat ini. Game ini mengajak kamu untuk berlomba dengan 31 pemain lainnya melalui berbagai rintangan yang lucu dan menantang. Kamu harus berlari, melompat, dan menghindari terjatuh sampai ke garis finish. Siapa yang berhasil sampai terakhir, dialah yang menjadi juara!</p>
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-<ul>
-<li><b>Mode dan map yang beragam.</b> Game ini memiliki beberapa mode permainan, seperti race, survival, team, dan final. Setiap mode memiliki tantangan dan tujuan yang berbeda. Selain itu, game ini juga memiliki banyak map yang memiliki tema dan rintangan yang unik. Kamu bisa bermain di map salju, hutan, pantai, karnaval, dll.</li>
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-<li><b>Bermain bersama teman.</b> Game ini juga mendukung fitur multiplayer online yang memungkinkan kamu untuk bermain bersama temanmu. Kamu bisa membuat atau bergabung dengan room khusus untuk bermain bersama temanmu. Kamu juga bisa berkomunikasi dengan temanmu melalui fitur chat atau voice chat.</li>
-</ul>
- <h2>Apa yang baru di versi terbaru Stumble Guys?</h2>
-<h3>Map baru dengan tema Hot Wheels</h3>
-<p>Versi terbaru Stumble Guys menambahkan map baru yang memiliki tema Hot Wheels. Map ini merupakan hasil kolaborasi antara Kitka Games dan Mattel, produsen mainan Hot Wheels. Map ini menawarkan pengalaman bermain yang berbeda dari map lainnya. Kamu akan berlomba di atas lintasan mobil-mobilan yang penuh dengan loop, ramp, dan mobil-mobil Hot Wheels yang bisa menghalangi jalurmu. Kamu harus berhati-hati karena map ini sangat cepat dan penuh dengan kejutan.</p>
-<h3>Skin, emote, dan karakter baru yang bisa dibuka</h3>
-<p>Versi terbaru Stumble Guys juga menambahkan skin, emote, dan karakter baru yang bisa kamu buka dengan menggunakan koin atau permata. Beberapa skin baru yang bisa kamu dapatkan adalah skin Hot Wheels, skin Halloween, skin Natal, dll. Beberapa emote baru yang bisa kamu gunakan adalah emote Hot Wheels, emote zombie, emote Santa Claus, dll. Beberapa karakter baru yang bisa kamu mainkan adalah karakter Hot Wheels, karakter vampir, karakter rusa kutub, dll.</p>
- <h2>Bagaimana cara download dan instal apk Stumble Guys?</h2>
-<h3>Mengizinkan instalasi dari sumber tidak dikenal</h3>
-<p>Untuk bisa menginstal file apk Stumble Guys di perangkat Androidmu, kamu harus mengizinkan instalasi dari sumber tidak dikenal. Caranya adalah sebagai berikut:</p>
-<ol>
-<li>Buka menu pengaturan di perangkat Androidmu.</li>
-<li>Pilih menu keamanan atau privasi.</li>
-<li>Cari opsi instalasi dari sumber tidak dikenal atau unknown sources.</li>
-<li>Aktifkan opsi tersebut dengan menekan tombol geser atau centang.</li>
-</ol>
-<h3>Mengunduh file apk dari situs terpercaya</h3>
-<p>Setelah mengaktifkan opsi instalasi dari sumber tidak dikenal, kamu harus mengunduh file apk Stumble Guys dari situs terpercaya. Kamu bisa mencari situs-situs yang menyediakan file apk Stumble Guys dengan menggunakan mesin pencari seperti Google atau Bing. Namun, kamu harus berhati-hati karena tidak semua situs aman dan bebas dari virus atau malware. Kamu harus memilih situs yang memiliki reputasi baik dan ulasan positif dari pengguna lainnya. Beberapa contoh situs terpercaya yang menyediakan file apk Stumble Guys adalah:</p>
-<ul>
-<li>[Uptodown](^5^). Situs ini menyediakan file apk Stumble Guys versi 0.37 yang memiliki ukuran sekitar 120 MB. Situs ini juga menyediakan deskripsi lengkap tentang game ini dalam bahasa Indonesia.</li>
-<li>[StumbleGu ys.com]. Situs ini menyediakan file apk Stumble Guys versi 0.38 yang memiliki ukuran sekitar 121 MB. Situs ini juga menyediakan informasi tentang fitur-fitur baru yang ada di versi terbaru game ini.</li>
-<li>[APKPure]. Situs ini menyediakan file apk Stumble Guys versi 0.39 yang memiliki ukuran sekitar 122 MB. Situs ini juga menyediakan screenshot dan video gameplay dari game ini.</li>
-</ul>
-<h3>Mencari dan menjalankan file apk di perangkat Android</h3>
-<p>Setelah mengunduh file apk Stumble Guys dari situs terpercaya, kamu harus mencari dan menjalankan file apk tersebut di perangkat Androidmu. Caranya adalah sebagai berikut:</p>
-<ol>
-<li>Buka menu file manager atau pengelola berkas di perangkat Androidmu.</li>
-<li>Cari folder download atau unduhan di perangkat Androidmu.</li>
-<li>Cari file apk Stumble Guys yang sudah kamu unduh sebelumnya. File apk biasanya memiliki ekstensi .apk di akhir nama file.</li>
-<li>Ketuk file apk tersebut untuk menjalankannya. Akan muncul sebuah jendela konfirmasi yang meminta izin untuk menginstal aplikasi tersebut.</li>
-<li>Tekan tombol instal atau install untuk melanjutkan proses instalasi. Tunggu sampai proses instalasi selesai.</li>
-<li>Setelah proses instalasi selesai, kamu bisa membuka game Stumble Guys dengan menekan tombol buka atau open, atau dengan mencari ikon game tersebut di menu aplikasi di perangkat Androidmu.</li>
-</ol>
- <h2>Tips dan trik bermain Stumble Guys dengan baik</h2>
-<h3>Memilih mode dan map yang sesuai dengan kemampuan</h3>
-<p>Stumble Guys memiliki beberapa mode dan map yang bisa kamu pilih untuk bermain. Namun, tidak semua mode dan map cocok untuk semua pemain. Kamu harus memilih mode dan map yang sesuai dengan kemampuan dan preferensimu. Berikut adalah beberapa tips untuk memilih mode dan map yang tepat:</p>
-<ul>
-<li><b>Race mode.</b> Mode ini cocok untuk kamu yang suka berlomba dengan cepat dan kompetitif. Kamu harus mencapai garis finish sebelum pemain lainnya. Kamu harus memilih map yang memiliki rintangan yang tidak terlalu sulit, seperti Snowy Slopes, Tropical Trouble, dll.</li>
-<li><b>Survival mode.</b> Mode ini cocok untuk kamu yang suka tantangan dan ketegangan. Kamu harus bertahan hidup selama mungkin tanpa terjatuh atau tersingkir dari arena. Kamu harus memilih map yang memiliki rintangan yang berbahaya, seperti Hex-A-Gone, Roll Out, dll.</li>
-<li><b>Team mode.</b> Mode ini cocok untuk kamu yang suka bermain bersama teman atau kerjasama tim. Kamu akan dibagi menjadi dua tim yang harus bersaing satu sama lain. Kamu harus memilih map yang memiliki tujuan tim, seperti Egg Scramble, Rock N Roll, dll.</li>
-<li><b>Final mode.</b> Mode ini cocok untuk kamu yang suka tantangan akhir dan kesempatan menjadi juara. Kamu akan berhadapan dengan pemain-pemain terbaik yang lolos dari babak sebelumnya. Kamu harus memilih map yang memiliki tingkat kesulitan tinggi, seperti Fall Mountain, Jump Showdown, dll.</li>
-</ul>
- <h3>Menghindari rintangan dan jebakan dengan cerdas</h3>
-<p>Stumble Guys adalah game yang penuh dengan rintangan dan jebakan yang bisa membuatmu terjatuh atau tersingkir dari arena. Kamu harus menghindari rintangan dan jebakan tersebut dengan cerdas agar bisa lolos kualifikasi dan mencapai garis finish. Berikut adalah beberapa tips untuk menghindari rintangan dan jebakan dengan cerdas:</p>
-<ul>
-<li><b>Mengamati pola rintangan.</b> Setiap rintangan memiliki pola gerakan atau waktu tertentu yang bisa kamu amati dan pelajari. Misalnya, rintangan palu besar akan berputar ke kiri atau ke kanan secara bergantian, rintangan bola besar akan meluncur ke bawah setiap beberapa detik, dll. Kamu harus mengamati pola rintangan tersebut dan men tunggu waktu yang tepat untuk melewatinya tanpa terkena dampaknya.</li>
-<li><b>Memanfaatkan rintangan sebagai bantuan.</b> Tidak semua rintangan bersifat merugikan. Beberapa rintangan bisa kamu manfaatkan sebagai bantuan untuk melaju lebih cepat atau menghindari rintangan lainnya. Misalnya, rintangan pegas bisa kamu gunakan untuk melompat lebih tinggi, rintangan kipas angin bisa kamu gunakan untuk terbang lebih jauh, dll. Kamu harus memanfaatkan rintangan tersebut dengan tepat dan hati-hati agar tidak malah terjatuh.</li>
-<li><b>Menghindari kerumunan pemain lain.</b> Pemain lain juga bisa menjadi rintangan dan jebakan yang bisa mengganggu permainanmu. Pemain lain bisa menabrakmu, mendorongmu, atau menjatuhkanmu dengan sengaja atau tidak sengaja. Kamu harus menghindari kerumunan pemain lain dan mencari jalur yang lebih sepi dan aman. Kamu juga bisa menggunakan emote untuk menggoda atau mengecoh pemain lain agar terganggu konsentrasinya.</li>
-</ul>
- <h3>Bermain bersama teman untuk lebih seru</h3>
-<p>Stumble Guys adalah game yang lebih seru jika dimainkan bersama teman. Kamu bisa bermain bersama temanmu dalam mode team atau mode lainnya. Kamu bisa membuat atau bergabung dengan room khusus untuk bermain bersama temanmu. Kamu juga bisa berkomunikasi dengan temanmu melalui fitur chat atau voice chat. Berikut adalah beberapa tips untuk bermain bersama teman dengan baik:</p>
-<ul>
-<li><b>Membuat strategi bersama.</b> Kamu dan temanmu harus membuat strategi bersama untuk menang dalam setiap mode permainan. Kamu harus menentukan siapa yang akan menjadi pemimpin, siapa yang akan menjadi penyerang, siapa yang akan menjadi pembela, dll. Kamu juga harus menentukan cara berkomunikasi yang efektif, misalnya menggunakan kode-kode tertentu atau singkatan-singkatan yang mudah dipahami.</li>
-<li><b>Membantu satu sama lain.</b> Kamu dan temanmu harus saling membantu satu sama lain untuk lolos dari rintangan dan jebakan yang ada. Kamu bisa menarik, mendorong, atau mengangkat temanmu yang terjatuh atau tersingkir dari arena. Kamu juga bisa memberi tahu temanmu tentang posisi atau kondisi rintangan yang ada di depannya. Kamu juga bisa memberi semangat atau motivasi kepada temanmu yang sedang kesulitan atau putus asa.</li>
-<li><b>Bersikap sportif dan bersahabat.</b> Kamu dan temanmu harus bersikap sportif dan bersahabat dalam bermain Stumble Guys. Kamu tidak boleh curang, marah, atau sombong dalam bermain. Kamu harus menghargai kemenangan atau kekalahan dengan baik. Kamu juga harus bersikap ramah dan sopan kepada pemain lain yang bukan temanmu. Kamu bisa memberi ucapan selamat, terima kasih, maaf, atau salam kepada pemain lain dengan menggunakan fitur chat atau emote.</li>
-</ul>
- <h2>Kesimpulan</h2>
-<p>Stumble Guys adalah game online multiplayer yang seru dan lucu yang bisa kamu mainkan di perangkat Androidmu. Game ini mengajak kamu untuk berlomba dengan 31 pemain lainnya melalui berbagai rintangan dan jebakan yang menantang. Game ini memiliki banyak fitur menarik seperti mode dan map yang beragam, skin, emote, dan karakter yang keren, dan fitur multiplayer online yang memungkinkan kamu bermain bersama temanmu.</p>
-<p>Versi terbaru Stumble Guys menambahkan map baru dengan tema Hot Wheels, skin, emote, dan karakter baru yang bisa dibuka, dan perbaikan bug dan peningkatan performa. Untuk bisa mencoba versi terbaru Stumble Guys, kamu bisa mengunduh dan menginstal file apk Stumble Guys dari situs terpercaya. Kamu juga bisa menggunakan beberapa tips dan trik untuk bermain Stumble Guys dengan baik, seperti memilih mode dan map yang sesuai dengan kemampuan, menghindari rintangan dan jebakan dengan cerdas, dan bermain bersama teman untuk lebih seru.</p>
-<p>Demikianlah artikel tentang apk Stumble Guys yang baru. Semoga artikel ini bermanfaat dan menghibur bagi kamu yang suka bermain game online multiplayer. Selamat bermain dan jangan lupa untuk berbagi pengalamanmu dengan kami di kolom komentar di bawah ini!</p>
- <h2>FAQ</h2>
-<p>Berikut adalah beberapa pertanyaan yang sering diajukan tentang apk Stumble Guys yang baru:</p>
-<table>
-<tr><td><b>Q:</b> Apakah file apk Stumble Guys aman untuk diinstal?</td><td><b>A:</b> File apk Stumble Guys yang kami rekomendasikan di atas adalah file apk yang aman dan bebas dari virus atau malware. Namun, kamu tetap harus berhati-hati dan memeriksa file apk sebelum menginstalnya. Kamu juga harus mengunduh file apk dari situs terpercaya dan tidak sembarangan.</td></tr>
-<tr><td><b>Q:</b> Apakah file apk Stumble Guys bisa diupdate?</td><td><b>A:</b> File apk Stumble Guys yang kami rekomendasikan di atas adalah file apk yang bisa diupdate secara otomatis atau manual. Kamu bisa mengupdate file apk tersebut dengan mengunduh versi terbaru dari situs yang sama atau situs lainnya. Kamu juga bisa mengupdate file apk tersebut dengan menggunakan fitur update yang ada di dalam game.</td></tr>
-<tr><td><b>Q:</b> Apakah file apk Stumble Guys bisa dimainkan secara offline?</td><td><b>A:</b> File apk Stumble Guys yang kami rekomendasikan di atas adalah file apk yang membutuhkan koneksi internet untuk dimainkan. Kamu tidak bisa memainkan game ini secara offline karena game ini adalah game online multiplayer yang membutuhkan koneksi internet untuk berinteraksi dengan pemain lainnya.</td></tr>
-<tr><td><b>Q:</b> Apakah file apk Stumble Guys bisa dimainkan di PC atau laptop?</td><td><b>A:</b> File apk Stumble Guys yang kami rekomendasikan di atas adalah file apk yang hanya bisa dimainkan di perangkat Android. Kamu tidak bisa memainkan game ini di PC atau laptop karena game ini tidak memiliki versi PC atau laptop. Namun, kamu bisa mencoba menggunakan emulator Android untuk menjalankan game ini di PC atau laptop.</td></tr>
-<tr><td><b>Q:</b> Apakah file apk Stumble Guys legal atau ilegal?</td><td><b>A:</b> File apk Stumble Guys yang kami rekomendasikan di atas adalah file apk yang legal dan tidak melanggar hak cipta atau lisensi dari developer game aslinya. Namun, kamu harus tetap menghormati developer game aslinya dengan tidak menggunakan file apk tersebut untuk tujuan komersial atau merugikan developer game aslinya.</td></tr>
-</table></p> 401be4b1e0<br />
-<br />
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-<h1>Garten of Banban 2: A Mysterious Adventure Game for Android</h1>
- <p>If you are looking for a thrilling and immersive game that will keep you on the edge of your seat, you might want to check out Garten of Banban 2. This is a free adventure game developed by Euphoric Brothers Games, inspired by the mysterious preschool that first appeared in the original version of this game. In this game, you will take on the role of a brave character who explores the secrets and dangers of this eerie place. You will encounter puzzles, enemies, traps, and surprises along the way. Are you ready to face your fears and uncover the truth?</p>
-<h2>garten of banban chapter 2 apk play mods</h2><br /><p><b><b>DOWNLOAD</b> &rArr;&rArr;&rArr; <a href="https://urlca.com/2uOcuB">https://urlca.com/2uOcuB</a></b></p><br /><br />
- <h2>What is Garten of Banban 2?</h2>
- <p>Garten of Banban 2 is a sequel to Garten of Banban, a game that was released in 2020. The first game introduced the concept of a creepy preschool that was abandoned for unknown reasons. The game had a dark and mysterious atmosphere, as well as a nonlinear gameplay that allowed the player to choose their own path and actions. The game also had multiple endings, depending on the choices and consequences of the player.</p>
- <h3>The story and the gameplay</h3>
- <p>In Garten of Banban 2, you will continue the story of the first game, but with more depth and complexity. You will learn more about the history and the secrets of the preschool, as well as the fate of the previous characters. You will also meet new characters, some friendly and some hostile, who will help or hinder your progress. You will have to use your wits and skills to solve puzzles, avoid traps, fight enemies, and escape from danger. You will also have to make decisions that will affect the outcome of the game.</p>
- <h3>The graphics and the sound</h3>
- <p>Garten of Banban 2 has improved graphics and sound compared to the first game. The game has a realistic and detailed 3D environment that creates a sense of immersion and realism. The game also has a dynamic lighting and shadow system that enhances the mood and the tension of the game. The game has a variety of sound effects and music that match the tone and the theme of the game. The game also has voice acting for some of the characters, which adds more personality and emotion to the game.</p>
- <h3>The features and the challenges</h3>
- <p>Garten of Banban 2 has many features and challenges that make it an enjoyable and rewarding game. Some of these features are:</p>
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-<ul>
-<li>A nonlinear gameplay that allows you to explore different areas and scenarios.</li>
-<li>A branching storyline that changes depending on your choices and actions.</li>
-<li>A multiple ending system that gives you different results based on your performance.</li>
-<li>A mod menu that lets you customize your experience and access various cheats.</li>
-<li>A survival mode that tests your skills and endurance in a timed challenge.</li>
-</ul>
-<p>Some of these challenges are:</p>
-<ul>
-<li>A limited inventory system that forces you to manage your resources wisely.</li>
-<li>A health system that requires you to heal yourself with items or find safe places to rest.</li>
-<li>A stealth system that requires you to hide from enemies or distract them with objects.</li>
-<li>A combat system that requires you to use weapons or items to fight back or escape.</li>
-<li>A puzzle system that requires you to use logic or clues to solve problems.</li>
-</ul>
- <h2>How to download and install Garten of Banban 2 APK?</h2>
- <p>If you want to play Garten of Banban 2 on your Android device, you will need to download and install its APK file. An APK file is an Android application package that contains all the files and data needed to run an app on your device. However, not all apps are available on the Google Play Store, so you may need to download and install APK files from other sources. To do this, you need to follow some steps and precautions, as explained below    . <h3>The requirements and the precautions</h3>
- <p>Before you download and install an APK file, you need to make sure that your device meets the following requirements:</p>
-<ul>
-<li>Your device has enough storage space to accommodate the APK file and the app data.</li>
-<li>Your device has a compatible Android version and hardware specifications to run the app.</li>
-<li>Your device has a reliable internet connection to download the APK file and any updates or patches.</li>
-</ul>
-<p>You also need to take some precautions to avoid any risks or issues when installing an APK file:</p>
-<ul>
-<li>Enable the option to install apps from unknown sources in your device settings. This will allow you to install apps that are not from the Google Play Store. You can do this by going to Settings > Apps > Menu > Special access > Install unknown apps, and then selecting the browser or file manager app that you use to download APK files.</li>
-<li>Download APK files only from reputable and trustworthy sources. Some APK files may contain malware or viruses that can harm your device or compromise your privacy. You can check the reviews, ratings, and feedback of other users before downloading an APK file. You can also use a virus scanner app to scan the APK file before installing it.</li>
-<li>Backup your device data and save files before installing an APK file. Some APK files may overwrite or delete your existing data or cause compatibility issues with other apps. You can use a backup app or a cloud service to backup your important data and files.</li>
-</ul>
- <h3>The steps and the tips</h3>
- <p>Once you have prepared your device and downloaded the APK file, you can follow these steps to install it:</p>
-<ol>
-<li>Locate the APK file in your device's file explorer app or browser's download folder. If you downloaded the file from your computer, you can transfer it to your device using a USB cable or a wireless method.</li>
-<li>Tap on the APK file to open it. You may see a prompt asking if you want to install the app or warning you about potential risks. Tap on Install or Yes to proceed.</li>
-<li>Wait for the installation process to complete. You may see a progress bar or a notification indicating the status of the installation.</li>
-<li>Once the installation is done, you can tap on Open or Launch to start the app. You can also find the app icon in your app drawer or home screen.</li>
-</ol>
-<p>Here are some tips to enhance your experience when installing APK files:</p>
-<ul>
-<li>Keep your device updated with the latest Android version and security patches. This will ensure that your device can run the apps smoothly and securely.</li>
-<li>Uninstall any previous versions of the app before installing a new one. This will prevent any conflicts or errors that may arise from having multiple versions of the same app.</li>
-<li>Check for updates or patches for the app regularly. Some apps may require updates or patches to fix bugs, improve performance, or add new features. You can check for updates or patches from the app itself, from the source website, or from a third-party app store.</li>
-</ul>
- <h2>How to use mods in Garten of Banban 2?</h2>
- <p>Mods are modifications or additions that change or enhance an existing game. Mods can add new content, features, graphics, sounds, gameplay elements, or even entire new game modes. Mods can make a game more fun, challenging, immersive, or personalized. However, not all games support mods, and not all mods are compatible with each other or with the game version.</p>
- <h3>What are mods and why use them?</h3>
- <p>Mods are usually created by fans or developers who want to improve or customize a game according to their preferences or needs. Mods can be downloaded from various websites or forums where modders share their creations with other users. Mods can be categorized into different types depending on their purpose and scope:</p>
- <table border="1">
-<tr><th>Type</th><th>Description</th><th>Example</th></tr>
-<tr><td>Patch</td><td>A mod that fixes bugs, errors, glitches, or compatibility issues in a game.</td><td>A patch that fixes crashes or performance issues in Garten of Banban 2.</td></tr>
-<tr><td>Tweak</td><td>A mod that changes some settings, options, parameters, or values in a game.</td>< td>A tweak that changes the difficulty level, the inventory size, or the camera angle in Garten of Banban 2.</td></tr>
-<tr><td>Texture</td><td>A mod that changes the appearance, quality, or style of the graphics in a game.</td><td>A texture that makes the preschool look more realistic, colorful, or scary in Garten of Banban 2.</td></tr>
-<tr><td>Sound</td><td>A mod that changes the volume, quality, or style of the sound effects or music in a game.</td><td>A sound that adds more ambient noises, voice acting, or background music in Garten of Banban 2.</td></tr>
-<tr><td>Content</td><td>A mod that adds new items, characters, quests, locations, or stories in a game.</td><td>A content that adds new weapons, enemies, puzzles, rooms, or endings in Garten of Banban 2.</td></tr>
-<tr><td>Gameplay</td><td>A mod that changes the rules, mechanics, or features of the gameplay in a game.</td><td>A gameplay that adds new modes, skills, actions, or interactions in Garten of Banban 2.</td></tr>
-<tr><td>Overhaul</td><td>A mod that changes the entire game or a major aspect of it.</td><td>An overhaul that transforms Garten of Banban 2 into a different genre, theme, or style.</td></tr>
-</table>
- <p>There are many reasons why you may want to use mods in Garten of Banban 2. Some of these reasons are:</p>
-<ul>
-<li>To enhance your enjoyment and satisfaction with the game.</li>
-<li>To improve your performance and experience with the game.</li>
-<li>To customize your game according to your preferences and needs.</li>
-<li>To explore new possibilities and scenarios with the game.</li>
-<li>To extend the lifespan and replay value of the game.</li>
-</ul>
- <h3>How to find and download mods?</h3>
- <p>If you want to use mods in Garten of Banban 2, you will need to find and download them from various sources. There are many websites and forums where modders share their creations with other users. Some of these sources are:</p>
-<ul>
-<li>[Garten of Banban 2 Mods]: This is the official website of the game developer, where you can find and download mods made by them or by other users. You can also upload your own mods and rate and comment on other mods. You can browse mods by category, popularity, date, or name. You can also search for mods by keywords or tags.</li>
-<li>[Mod DB]: This is one of the largest and most popular websites for modding games. You can find and download mods for thousands of games, including Garten of Banban 2. You can also upload your own mods and join communities and groups related to modding. You can browse mods by genre, platform, type, or name. You can also search for mods by keywords or tags.</li>
-<li>[Nexus Mods]: This is another one of the largest and most popular websites for modding games. You can find and download mods for hundreds of games, including Garten of Banban 2. You can also upload your own mods and join forums and discussions related to modding. You can browse mods by category, popularity, date, or name. You can also search for mods by keywords or tags.</li>
-</ul>
- <h3>How to install and activate mods?</h3>
- <p>Once you have found and downloaded the mods that you want to use in Garten of Banban 2, you will need to install and activate them on your device. To do this, you need to follow some steps and tips, as explained below   .</p>
- <ol>
-<li>Extract the mod files from the ZIP or RAR archive that you downloaded. You can use a file extractor app or a computer program to do this. You should see a folder with the name of the mod and some files inside it.</li>
-<li>Copy or move the mod folder to the Mods folder in your device's internal storage. You can use a file manager app or a computer program to do this. The Mods folder should be located in Android > data > com.euphoricbrothers.gartenofbanban2 > files > Mods. If you don't see this folder, you may need to create it manually.</li>
-<li>Launch Garten of Banban 2 on your device and tap on the Mod Menu button on the main screen. You should see a list of all the available mods on your device.</li>
-<li>Select the mod that you want to activate and tap on the Enable button. You should see a green check mark next to the mod name, indicating that it is activated. You can also disable the mod by tapping on the Disable button.</li>
-<li>Tap on the Back button to return to the main screen and start or resume your game. You should see the effects of the mod in your game.</li>
-</ol>
-<p>Here are some tips to enhance your experience when using mods in Garten of Banban 2:</p>
-<ul>
-<li>Read the description and the instructions of the mod before installing and activating it. Some mods may have specific requirements, compatibility issues, or installation steps that you need to follow.</li>
-<li>Use only one mod at a time or avoid using mods that conflict with each other. Some mods may not work well together or may cause errors or crashes in your game. You can check the compatibility and the conflicts of the mods from their source website or forum.</li>
-<li>Backup your game data and save files before using mods. Some mods may alter or delete your existing data or cause corruption or glitches in your game. You can use a backup app or a cloud service to backup your important data and files.</li>
-</ul>
- <h2>Conclusion</h2>
- <h3>Summary of the main points</h3>
- <p>Garten of Banban 2 is a free adventure game for Android devices that lets you explore a mysterious preschool and uncover its secrets and dangers. The game has a nonlinear gameplay, a branching storyline, a multiple ending system, a mod menu, and a survival mode. The game also has improved graphics and sound compared to the first game. To play the game, you need to download and install its APK file from a reputable source and enable the option to install apps from unknown sources in your device settings. To use mods in the game, you need to download and install them from various sources and activate them from the mod menu in the game.</p>
- <h3>Call to action and recommendation</h3>
- <p>If you are interested in playing Garten of Banban 2, you can download it from [Garten of Banban 2 Mods], [Mod DB], or [Nexus Mods]. You can also find more information and updates about the game from its official website [Euphoric Brothers Games] or its Facebook page [Garten of Banban 2]. If you enjoy the game, you can also support the developer by donating via PayPal [here] or by rating and reviewing the game on its source website or forum. If you have any questions or feedback about the game or the mods, you can contact the developer via email at euphoricbrothers@gmail.com or via their social media accounts.</p>
- <p>We hope that this article has helped you learn more about Garten of Banban 2 and how to download and install its APK file and mods. We also hope that you have fun playing this game and discovering its mysteries and surprises. Thank you for reading this article and happy gaming!</p>
- <h2>FAQs</h2>
- <h3>What is Garten of Banban 2?</h3>
-<p>Garten of Banban 2 is a free adventure game for Android devices that lets you explore a mysterious preschool and uncover its secrets and dangers.</p>
- <h3>How to download and install Garten of Banban 2 APK?</h3>
-<p>You need to download the APK file from a reputable source and enable the option to install apps from unknown sources in your device settings. Then, you need to locate the APK file in your device's file explorer app or browser's download folder and tap on it to open it. Then, you need to tap on Install or Yes to proceed with the installation process. Once the installation is done, you can tap on Open or Launch to start the game.</p>
- <h3>How to use mods in Garten of Banban 2?</h3>
-<p>You need to download the mod files from various sources and extract them from their ZIP or RAR archive. Then, you need to copy or move the mod folder to the Mods folder in your device's internal storage. Then, you need to launch Garten of Banban 2 on your device and tap on the Mod Menu button on the main screen. Then, you need to select the mod that you want to activate and tap on the Enable button. You can also disable the mod by tapping on the Disable button.</p>
- <h3>Is Garten of Banban 2 safe and legal to play?</h3>
-<p>Garten of Banban 2 is safe and legal to play as long as you download and install it from a reputable source and follow the precautions mentioned above. The game does not contain any malware or viruses that can harm your device or compromise your privacy. The game also does not violate any laws or regulations that prohibit or restrict its distribution or use. However, you should be aware that the game may contain some content or themes that are not suitable for children or sensitive audiences, such as violence, horror, or gore. You should also respect the intellectual property rights of the game developer and the modders and not use their work for commercial purposes or without their permission.</p>
- <h3>What are some alternatives to Garten of Banban 2?</h3>
-<p>If you are looking for some similar games to Garten of Banban 2, you may want to try these games:</p>
-<ul>
-<li>[Granny]: This is a horror game where you have to escape from a house where a crazy old lady is trying to kill you. You have to find clues, items, and keys to unlock doors and windows while avoiding her traps and attacks. You have only five days to escape or you will die.</li>
-<li>[Hello Neighbor]: This is a stealth game where you have to sneak into your neighbor's house and find out what he is hiding in his basement. You have to avoid his detection and his traps while solving puzzles and discovering secrets. He will also learn from your actions and adapt his behavior accordingly.</li>
-<li>[Baldi's Basics]: This is a parody game where you have to collect seven notebooks from a school where a bald teacher is chasing you. You have to answer math questions correctly or he will get angry and faster. You also have to deal with other weird characters and obstacles in the school.</li>
-</ul></p> 401be4b1e0<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/contluForse/HuggingGPT/assets/Animusic 1080p Mkv To 720p LINK.md b/spaces/contluForse/HuggingGPT/assets/Animusic 1080p Mkv To 720p LINK.md
deleted file mode 100644
index 9f30e862f7bb0dd5adabffd606de03c7a7faad7a..0000000000000000000000000000000000000000
--- a/spaces/contluForse/HuggingGPT/assets/Animusic 1080p Mkv To 720p LINK.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>animusic 1080p mkv to 720p</h2><br /><p><b><b>Download</b> &#10002; <a href="https://ssurll.com/2uzviU">https://ssurll.com/2uzviU</a></b></p><br /><br />
-<br />
-Download and stream Hamesha Tumko Chaha - Devdas (2002) 720p.mkv Greek subs. in 3GP MP4 FLV MP3 available in 240p, 360p, 720p, 1080p video ... 1fdad05405<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/coreml-community/ControlNet-v1-1-Annotators-cpu/annotator/uniformer/mmseg/utils/__init__.py b/spaces/coreml-community/ControlNet-v1-1-Annotators-cpu/annotator/uniformer/mmseg/utils/__init__.py
deleted file mode 100644
index ac489e2dbbc0e6fa87f5088b4edcc20f8cadc1a6..0000000000000000000000000000000000000000
--- a/spaces/coreml-community/ControlNet-v1-1-Annotators-cpu/annotator/uniformer/mmseg/utils/__init__.py
+++ /dev/null
@@ -1,4 +0,0 @@
-from .collect_env import collect_env
-from .logger import get_root_logger
-
-__all__ = ['get_root_logger', 'collect_env']
diff --git a/spaces/crylake/img2poem/query2labels/lib/models/tresnet/tresnet_sync.py b/spaces/crylake/img2poem/query2labels/lib/models/tresnet/tresnet_sync.py
deleted file mode 100644
index 4f75df4d92e616f6dcc95fad6be94f60d703e04f..0000000000000000000000000000000000000000
--- a/spaces/crylake/img2poem/query2labels/lib/models/tresnet/tresnet_sync.py
+++ /dev/null
@@ -1,263 +0,0 @@
-# borrow from: https://github.com/Alibaba-MIIL/TResNet
-import torch
-import torch.nn as nn
-from torch.nn import Module as Module
-from collections import OrderedDict
-
-# import os,sys
-# fpath = os.path.dirname(os.path.dirname(os.path.dirname(__file__)))
-# if fpath not in sys.path:
-#     sys.path.append(fpath)
-
-from query2labels.lib.models.tresnet.layers.anti_aliasing import AntiAliasDownsampleLayer
-# from .layers.anti_aliasing import AntiAliasDownsampleLayer
-from .layers.avg_pool import FastAvgPool2d
-from .layers.general_layers import SEModule, SpaceToDepthModule
-try:
-    from inplace_abn import InPlaceABNSync
-except:
-    print("No inplace_abn found, please make sure you won't use TResNet as backbone!")
-
-
-# from inplace_abn import ABN
-
-class bottleneck_head(nn.Module):
-    def __init__(self, num_features, num_classes, bottleneck_features=200):
-        super(bottleneck_head, self).__init__()
-        self.embedding_generator = nn.ModuleList()
-        self.embedding_generator.append(nn.Linear(num_features, bottleneck_features))
-        self.embedding_generator = nn.Sequential(*self.embedding_generator)
-        self.FC = nn.Linear(bottleneck_features, num_classes)
-
-    def forward(self, x):
-        self.embedding = self.embedding_generator(x)
-        logits = self.FC(self.embedding)
-        return logits
-
-
-def conv2d(ni, nf, stride):
-    return nn.Sequential(
-        nn.Conv2d(ni, nf, kernel_size=3, stride=stride, padding=1, bias=False),
-        nn.BatchNorm2d(nf),
-        nn.ReLU(inplace=True)
-    )
-
-
-def conv2d_ABN(ni, nf, stride, activation="leaky_relu", kernel_size=3, activation_param=1e-2, groups=1):
-    return nn.Sequential(
-        nn.Conv2d(ni, nf, kernel_size=kernel_size, stride=stride, padding=kernel_size // 2, groups=groups,
-                  bias=False),
-        InPlaceABNSync(num_features=nf, activation=activation, activation_param=activation_param, group=None)
-    )
-
-
-class BasicBlock(Module):
-    expansion = 1
-
-    def __init__(self, inplanes, planes, stride=1, downsample=None, use_se=True, anti_alias_layer=None):
-        super(BasicBlock, self).__init__()
-        if stride == 1:
-            self.conv1 = conv2d_ABN(inplanes, planes, stride=1, activation_param=1e-3)
-        else:
-            if anti_alias_layer is None:
-                self.conv1 = conv2d_ABN(inplanes, planes, stride=2, activation_param=1e-3)
-            else:
-                self.conv1 = nn.Sequential(conv2d_ABN(inplanes, planes, stride=1, activation_param=1e-3),
-                                           anti_alias_layer(channels=planes, filt_size=3, stride=2))
-
-        self.conv2 = conv2d_ABN(planes, planes, stride=1, activation="identity")
-        self.relu = nn.ReLU(inplace=True)
-        self.downsample = downsample
-        self.stride = stride
-        reduce_layer_planes = max(planes * self.expansion // 4, 64)
-        self.se = SEModule(planes * self.expansion, reduce_layer_planes) if use_se else None
-
-    def forward(self, x):
-        if self.downsample is not None:
-            residual = self.downsample(x)
-        else:
-            residual = x
-
-        out = self.conv1(x)
-        out = self.conv2(out)
-
-        if self.se is not None: out = self.se(out)
-
-        out += residual
-
-        out = self.relu(out)
-
-        return out
-
-
-class Bottleneck(Module):
-    expansion = 4
-
-    def __init__(self, inplanes, planes, stride=1, downsample=None, use_se=True, anti_alias_layer=None):
-        super(Bottleneck, self).__init__()
-        self.conv1 = conv2d_ABN(inplanes, planes, kernel_size=1, stride=1, activation="leaky_relu",
-                                activation_param=1e-3)
-        if stride == 1:
-            self.conv2 = conv2d_ABN(planes, planes, kernel_size=3, stride=1, activation="leaky_relu",
-                                    activation_param=1e-3)
-        else:
-            if anti_alias_layer is None:
-                self.conv2 = conv2d_ABN(planes, planes, kernel_size=3, stride=2, activation="leaky_relu",
-                                        activation_param=1e-3)
-            else:
-                self.conv2 = nn.Sequential(conv2d_ABN(planes, planes, kernel_size=3, stride=1,
-                                                      activation="leaky_relu", activation_param=1e-3),
-                                           anti_alias_layer(channels=planes, filt_size=3, stride=2))
-
-        self.conv3 = conv2d_ABN(planes, planes * self.expansion, kernel_size=1, stride=1,
-                                activation="identity")
-
-        self.relu = nn.ReLU(inplace=True)
-        self.downsample = downsample
-        self.stride = stride
-
-        reduce_layer_planes = max(planes * self.expansion // 8, 64)
-        self.se = SEModule(planes, reduce_layer_planes) if use_se else None
-
-    def forward(self, x):
-        if self.downsample is not None:
-            residual = self.downsample(x)
-        else:
-            residual = x
-
-        out = self.conv1(x)
-        out = self.conv2(out)
-        if self.se is not None: out = self.se(out)
-
-        out = self.conv3(out)
-        out = out + residual  # no inplace
-        out = self.relu(out)
-
-        return out
-
-
-class TResNet(Module):
-
-    def __init__(self, layers, in_chans=3, num_classes=1000, width_factor=1.0,
-                 do_bottleneck_head=False,bottleneck_features=512):
-        super(TResNet, self).__init__()
-
-        # JIT layers
-        space_to_depth = SpaceToDepthModule()
-        anti_alias_layer = AntiAliasDownsampleLayer
-        global_pool_layer = FastAvgPool2d(flatten=True)
-
-        # TResnet stages
-        self.inplanes = int(64 * width_factor)
-        self.planes = int(64 * width_factor)
-        conv1 = conv2d_ABN(in_chans * 16, self.planes, stride=1, kernel_size=3)
-        layer1 = self._make_layer(BasicBlock, self.planes, layers[0], stride=1, use_se=True,
-                                  anti_alias_layer=anti_alias_layer)  # 56x56
-        layer2 = self._make_layer(BasicBlock, self.planes * 2, layers[1], stride=2, use_se=True,
-                                  anti_alias_layer=anti_alias_layer)  # 28x28
-        layer3 = self._make_layer(Bottleneck, self.planes * 4, layers[2], stride=2, use_se=True,
-                                  anti_alias_layer=anti_alias_layer)  # 14x14
-        layer4 = self._make_layer(Bottleneck, self.planes * 8, layers[3], stride=2, use_se=False,
-                                  anti_alias_layer=anti_alias_layer)  # 7x7
-
-        # body
-        self.body = nn.Sequential(OrderedDict([
-            ('SpaceToDepth', space_to_depth),
-            ('conv1', conv1),
-            ('layer1', layer1),
-            ('layer2', layer2),
-            ('layer3', layer3),
-            ('layer4', layer4)]))
-
-        # head
-        self.embeddings = []
-        self.global_pool = nn.Sequential(OrderedDict([('global_pool_layer', global_pool_layer)]))
-        self.num_features = (self.planes * 8) * Bottleneck.expansion
-        if do_bottleneck_head:
-            fc = bottleneck_head(self.num_features, num_classes,
-                                 bottleneck_features=bottleneck_features)
-        else:
-            fc = nn.Linear(self.num_features , num_classes)
-
-        self.head = nn.Sequential(OrderedDict([('fc', fc)]))
-
-        # model initilization
-        for m in self.modules():
-            if isinstance(m, nn.Conv2d):
-                nn.init.kaiming_normal_(m.weight, mode='fan_out', nonlinearity='leaky_relu')
-            elif isinstance(m, nn.BatchNorm2d) or isinstance(m, InPlaceABNSync):
-                nn.init.constant_(m.weight, 1)
-                nn.init.constant_(m.bias, 0)
-
-        # residual connections special initialization
-        for m in self.modules():
-            if isinstance(m, BasicBlock):
-                m.conv2[1].weight = nn.Parameter(torch.zeros_like(m.conv2[1].weight))  # BN to zero
-            if isinstance(m, Bottleneck):
-                m.conv3[1].weight = nn.Parameter(torch.zeros_like(m.conv3[1].weight))  # BN to zero
-            if isinstance(m, nn.Linear): m.weight.data.normal_(0, 0.01)
-
-    def _make_layer(self, block, planes, blocks, stride=1, use_se=True, anti_alias_layer=None):
-        downsample = None
-        if stride != 1 or self.inplanes != planes * block.expansion:
-            layers = []
-            if stride == 2:
-                # avg pooling before 1x1 conv
-                layers.append(nn.AvgPool2d(kernel_size=2, stride=2, ceil_mode=True, count_include_pad=False))
-            layers += [conv2d_ABN(self.inplanes, planes * block.expansion, kernel_size=1, stride=1,
-                                  activation="identity")]
-            downsample = nn.Sequential(*layers)
-
-        layers = []
-        layers.append(block(self.inplanes, planes, stride, downsample, use_se=use_se,
-                            anti_alias_layer=anti_alias_layer))
-        self.inplanes = planes * block.expansion
-        for i in range(1, blocks): layers.append(
-            block(self.inplanes, planes, use_se=use_se, anti_alias_layer=anti_alias_layer))
-        return nn.Sequential(*layers)
-
-    def forward(self, x):
-        x = self.body(x)
-        # print(x.shape)
-        self.embeddings = self.global_pool(x)
-        logits = self.head(self.embeddings)
-        return logits
-
-
-def TResnetM(model_params):
-    """Constructs a medium TResnet model.
-    """
-    in_chans = 3
-    num_classes = model_params['num_classes']
-    model = TResNet(layers=[3, 4, 11, 3], num_classes=num_classes, in_chans=in_chans)
-    return model
-
-
-def TResnetL(model_params):
-    """Constructs a large TResnet model.
-    """
-    in_chans = 3
-    num_classes = model_params['num_classes']
-    try:
-        do_bottleneck_head = model_params['args'].do_bottleneck_head
-    except:
-        print("No do_bottleneck_head found, set to False as default!")
-        do_bottleneck_head = False
-    model = TResNet(layers=[4, 5, 18, 3], num_classes=num_classes, in_chans=in_chans, width_factor=1.2,
-                    do_bottleneck_head=do_bottleneck_head)
-    return model
-
-
-def TResnetXL(model_params):
-    """Constructs a xlarge TResnet model.
-    """
-    in_chans = 3
-    num_classes = model_params['num_classes']
-    model = TResNet(layers=[4, 5, 24, 3], num_classes=num_classes, in_chans=in_chans, width_factor=1.3)
-
-    return model
-
-if __name__ == "__main__":
-    m = TResnetL()
-    x = torch.rand(2, 3, 448, 448)
-    print(m(x).shape)
\ No newline at end of file
diff --git a/spaces/cynika/taffy/losses.py b/spaces/cynika/taffy/losses.py
deleted file mode 100644
index 41f9be6980713a46824ae9ec5eb8fd7c515d89c5..0000000000000000000000000000000000000000
--- a/spaces/cynika/taffy/losses.py
+++ /dev/null
@@ -1,61 +0,0 @@
-import torch 
-from torch.nn import functional as F
-
-import commons
-
-
-def feature_loss(fmap_r, fmap_g):
-  loss = 0
-  for dr, dg in zip(fmap_r, fmap_g):
-    for rl, gl in zip(dr, dg):
-      rl = rl.float().detach()
-      gl = gl.float()
-      loss += torch.mean(torch.abs(rl - gl))
-
-  return loss * 2 
-
-
-def discriminator_loss(disc_real_outputs, disc_generated_outputs):
-  loss = 0
-  r_losses = []
-  g_losses = []
-  for dr, dg in zip(disc_real_outputs, disc_generated_outputs):
-    dr = dr.float()
-    dg = dg.float()
-    r_loss = torch.mean((1-dr)**2)
-    g_loss = torch.mean(dg**2)
-    loss += (r_loss + g_loss)
-    r_losses.append(r_loss.item())
-    g_losses.append(g_loss.item())
-
-  return loss, r_losses, g_losses
-
-
-def generator_loss(disc_outputs):
-  loss = 0
-  gen_losses = []
-  for dg in disc_outputs:
-    dg = dg.float()
-    l = torch.mean((1-dg)**2)
-    gen_losses.append(l)
-    loss += l
-
-  return loss, gen_losses
-
-
-def kl_loss(z_p, logs_q, m_p, logs_p, z_mask):
-  """
-  z_p, logs_q: [b, h, t_t]
-  m_p, logs_p: [b, h, t_t]
-  """
-  z_p = z_p.float()
-  logs_q = logs_q.float()
-  m_p = m_p.float()
-  logs_p = logs_p.float()
-  z_mask = z_mask.float()
-  #print(logs_p)
-  kl = logs_p - logs_q - 0.5
-  kl += 0.5 * ((z_p - m_p)**2) * torch.exp(-2. * logs_p)
-  kl = torch.sum(kl * z_mask)
-  l = kl / torch.sum(z_mask)
-  return l
diff --git a/spaces/dawdqd/ChuanhuChatGPT/web_assets/javascript/updater.js b/spaces/dawdqd/ChuanhuChatGPT/web_assets/javascript/updater.js
deleted file mode 100644
index 68c0ff21aeb92bc538036c42264c41e3787097a7..0000000000000000000000000000000000000000
--- a/spaces/dawdqd/ChuanhuChatGPT/web_assets/javascript/updater.js
+++ /dev/null
@@ -1,202 +0,0 @@
-
-var updateInfoGotten = false;
-var isLatestVersion = localStorage.getItem('isLatestVersion') || false;
-
-
-var statusObserver = new MutationObserver(function (mutationsList) {
-    for (const mutation of mutationsList) {
-        if (mutation.type === 'attributes' || mutation.type === 'childList') {
-            if (statusDisplay.innerHTML.includes('<span id="update-status"')) {
-                if (getUpdateStatus() === "success") {
-                    updatingInfoElement.innerText = i18n(updateSuccess_i18n);
-                    noUpdateHtml();
-                    localStorage.setItem('isLatestVersion', 'true');
-                    isLatestVersion = true;
-                    enableUpdateBtns();
-                } else if (getUpdateStatus() === "failure") {
-                    updatingInfoElement.innerHTML = i18n(updateFailure_i18n);
-                    disableUpdateBtn_enableCancelBtn();
-                } else if (getUpdateStatus() != "") {
-                    updatingInfoElement.innerText = getUpdateStatus();
-                    enableUpdateBtns();
-                }
-                updateStatus.parentNode.removeChild(updateStatus);
-                if (updateSpinner) updateSpinner.stop();
-            }
-        }
-    }
-});
-
-var showingUpdateInfo = false;
-async function getLatestRelease() {
-    try {
-        const response = await fetch('https://api.github.com/repos/gaizhenbiao/chuanhuchatgpt/releases/latest');
-        if (!response.ok) {
-            console.log(`Error: ${response.status} - ${response.statusText}`);
-            updateInfoGotten = true;
-            return null;
-        }
-        const data = await response.json();
-        updateInfoGotten = true;
-        return data;
-    } catch (error) {
-        console.log(`Error: ${error}`);
-        updateInfoGotten = true;
-        return null;
-    }
-}
-
-var releaseNoteElement = document.getElementById('release-note-content');
-var updatingInfoElement = document.getElementById('updating-info');
-async function updateLatestVersion() {
-    const currentVersionElement = document.getElementById('current-version');
-    const reVersion = /<a[^>]*>([^<]*)<\/a>/g;
-    const versionMatch = reVersion.exec(currentVersionElement.innerHTML);
-    const currentVersion = (versionMatch && versionMatch[1].length == 8) ? versionMatch[1] : null;
-    const latestVersionElement = document.getElementById('latest-version-title');
-    const versionInfoElement = document.getElementById('version-info-title');
-    releaseNoteElement = document.getElementById('release-note-content');
-    updatingInfoElement = document.getElementById('updating-info');
-    
-    const versionTime = document.getElementById('version-time').innerText;
-    const localVersionTime = versionTime !== "unknown" ? (new Date(versionTime)).getTime() : 0;
-    updateInfoGotten = true; //无论成功与否都只执行一次，否则容易api超限...
-    try {
-        const data = await getLatestRelease();
-        const releaseNote = data.body;
-        if (releaseNote) {
-            releaseNoteElement.innerHTML = marked.parse(releaseNote, {mangle: false, headerIds: false});
-        }
-        const latestVersion = data.tag_name;
-        if (currentVersion) {
-            if (latestVersion <= currentVersion) {
-                noUpdate();
-            } else {
-                latestVersionElement.textContent = latestVersion;
-                console.log(`New version ${latestVersion} found!`);
-                if (!isInIframe) openUpdateToast();
-            }
-        } else { //如果当前版本号获取失败，使用时间比较
-            const latestVersionTime = (new Date(data.created_at)).getTime();
-            if (latestVersionTime) {
-                const latestVersionInfo = `<a href="https://github.com/gaizhenbiao/chuanhuchatgpt/releases/latest" target="_blank" id="latest-version-title" style="text-decoration: none;">${latestVersion}</a>`
-                const manualUpdateInfo = `<a href="https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/使用教程#手动更新" target="_blanks" style="text-decoration: none;">manual update</a>`
-                if (localVersionTime == 0) {
-                    const infoMessage = `Local version check failed. \nBut latest revision is ${latestVersionInfo}. \n\nWhen Update needed, \n- If you are using Docker, try to update package. \n- If you didn't use git, try ${manualUpdateInfo}.`
-                    versionInfoElement.innerHTML = marked.parse(infoMessage, {mangle: false, headerIds: false});
-                    console.log(`New version ${latestVersion} found!`);
-                    disableUpdateBtn_enableCancelBtn();
-                } else if (localVersionTime < latestVersionTime) {
-                    const infoMessage = `Local version check failed, it seems to be a local rivision. \n\nBut latest revision is ${latestVersionInfo}. Try ${manualUpdateInfo}.`
-                    versionInfoElement.innerHTML = marked.parse(infoMessage, {mangle: false, headerIds: false});
-                    console.log(`New version ${latestVersion} found!`);
-                    disableUpdateBtn_enableCancelBtn();
-                    // if (!isInIframe) openUpdateToast();
-                } else {
-                    noUpdate("Local version check failed, it seems to be a local rivision. <br>But your revision is newer than the latest release.");
-                }
-            }
-        }
-        currentTime = new Date().getTime();
-        localStorage.setItem('lastCheckTime', currentTime);
-    } catch (error) {
-        console.error(error);
-    }
-}
-
-function getUpdateInfo() {
-    window.open('https://github.com/gaizhenbiao/chuanhuchatgpt/releases/latest', '_blank');
-    closeUpdateToast();
-}
-
-var updateSpinner = null;
-
-function bgUpdateChuanhu() {
-    updateChuanhuBtn.click();
-    updatingInfoElement.innerText = i18n(updatingMsg_i18n);
-    var updatingSpinner = document.getElementById('updating-spinner');
-    try {
-        updateSpinner = new Spin.Spinner({color:'#06AE56',top:'45%',lines:9}).spin(updatingSpinner);
-    } catch (error) {
-        console.error("Can't create spinner")
-    }
-    updatingInfoElement.classList.remove('hideK');
-    disableUpdateBtns();
-    const releaseNoteWrap = document.getElementById('release-note-wrap');
-    releaseNoteWrap.style.setProperty('display', 'none');
-    statusObserver.observe(statusDisplay, { childList: true, subtree: true, characterData: true});
-}
-function cancelUpdate() {
-    closeUpdateToast();
-}
-function openUpdateToast() {
-    showingUpdateInfo = true;
-    setUpdateWindowHeight();
-}
-function closeUpdateToast() {
-    updateToast.style.setProperty('top', '-500px');
-    showingUpdateInfo = false;
-    if (updatingInfoElement.classList.contains('hideK') === false) {
-        updatingInfoElement.classList.add('hideK');
-    }
-}
-function manualCheckUpdate() {
-    openUpdateToast();
-    updateLatestVersion();
-    currentTime = new Date().getTime();
-    localStorage.setItem('lastCheckTime', currentTime);
-}
-function noUpdate(message="") {
-    localStorage.setItem('isLatestVersion', 'true');
-    isLatestVersion = true;
-    noUpdateHtml(message);
-}
-function noUpdateHtml(message="") {
-    const versionInfoElement = document.getElementById('version-info-title');
-    const gotoUpdateBtn = document.getElementById('goto-update-btn');
-    const closeUpdateBtn = document.getElementById('close-update-btn');
-    const releaseNoteWrap = document.getElementById('release-note-wrap');
-    releaseNoteWrap.style.setProperty('display', 'none');
-    if (message === "") {
-        versionInfoElement.textContent = i18n(usingLatest_i18n)
-    } else {
-        versionInfoElement.innerHTML = message;
-    }
-    gotoUpdateBtn.classList.add('hideK');
-    closeUpdateBtn.classList.remove('hideK');
-}
-
-var updateStatus = null;
-function getUpdateStatus() {
-    updateStatus = statusDisplay.querySelector("#update-status");
-    if (updateStatus) {
-        return updateStatus.innerText;
-    } else {
-        return "unknown";
-    }
-}
-
-function disableUpdateBtns() {
-    const updatesButtons = document.querySelectorAll('.btn-update');
-    updatesButtons.forEach( function (btn) {
-        btn.disabled = true;
-    });
-}
-function enableUpdateBtns() {
-    const updatesButtons = document.querySelectorAll('.btn-update');
-    updatesButtons.forEach( function (btn) {
-        btn.disabled = false;
-    });
-}
-function disableUpdateBtn_enableCancelBtn() {
-    document.querySelector('#update-button.btn-update').disabled = true;
-    document.querySelector('#cancel-button.btn-update').disabled = false;
-}
-
-function setUpdateWindowHeight() {
-    if (!showingUpdateInfo) {return;}
-    const scrollPosition = window.scrollY;
-    // const originalTop = updateToast.style.getPropertyValue('top');
-    const resultTop = scrollPosition - 20 + 'px';
-    updateToast.style.setProperty('top', resultTop);
-}
diff --git a/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/gradio/themes/__init__.py b/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/gradio/themes/__init__.py
deleted file mode 100644
index f7adbe74eef8ecee7e70d00a759c0fcf807d3185..0000000000000000000000000000000000000000
--- a/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/gradio/themes/__init__.py
+++ /dev/null
@@ -1,30 +0,0 @@
-from gradio.themes.base import Base, ThemeClass
-from gradio.themes.default import Default
-from gradio.themes.glass import Glass
-from gradio.themes.monochrome import Monochrome
-from gradio.themes.soft import Soft
-from gradio.themes.utils import colors, sizes
-from gradio.themes.utils.colors import Color
-from gradio.themes.utils.fonts import Font, GoogleFont
-from gradio.themes.utils.sizes import Size
-
-__all__ = [
-    "Base",
-    "Color",
-    "Default",
-    "Font",
-    "Glass",
-    "GoogleFont",
-    "Monochrome",
-    "Size",
-    "Soft",
-    "ThemeClass",
-    "colors",
-    "sizes",
-]
-
-
-def builder(*args, **kwargs):
-    from gradio.themes.builder_app import demo
-
-    return demo.launch(*args, **kwargs)
diff --git a/spaces/declare-lab/tango/audioldm/audio/audio_processing.py b/spaces/declare-lab/tango/audioldm/audio/audio_processing.py
deleted file mode 100644
index 77a4057aa82f226f68474f4c2a19eba84510d663..0000000000000000000000000000000000000000
--- a/spaces/declare-lab/tango/audioldm/audio/audio_processing.py
+++ /dev/null
@@ -1,100 +0,0 @@
-import torch
-import numpy as np
-import librosa.util as librosa_util
-from scipy.signal import get_window
-
-
-def window_sumsquare(
-    window,
-    n_frames,
-    hop_length,
-    win_length,
-    n_fft,
-    dtype=np.float32,
-    norm=None,
-):
-    """
-    # from librosa 0.6
-    Compute the sum-square envelope of a window function at a given hop length.
-
-    This is used to estimate modulation effects induced by windowing
-    observations in short-time fourier transforms.
-
-    Parameters
-    ----------
-    window : string, tuple, number, callable, or list-like
-        Window specification, as in `get_window`
-
-    n_frames : int > 0
-        The number of analysis frames
-
-    hop_length : int > 0
-        The number of samples to advance between frames
-
-    win_length : [optional]
-        The length of the window function.  By default, this matches `n_fft`.
-
-    n_fft : int > 0
-        The length of each analysis frame.
-
-    dtype : np.dtype
-        The data type of the output
-
-    Returns
-    -------
-    wss : np.ndarray, shape=`(n_fft + hop_length * (n_frames - 1))`
-        The sum-squared envelope of the window function
-    """
-    if win_length is None:
-        win_length = n_fft
-
-    n = n_fft + hop_length * (n_frames - 1)
-    x = np.zeros(n, dtype=dtype)
-
-    # Compute the squared window at the desired length
-    win_sq = get_window(window, win_length, fftbins=True)
-    win_sq = librosa_util.normalize(win_sq, norm=norm) ** 2
-    win_sq = librosa_util.pad_center(win_sq, n_fft)
-
-    # Fill the envelope
-    for i in range(n_frames):
-        sample = i * hop_length
-        x[sample : min(n, sample + n_fft)] += win_sq[: max(0, min(n_fft, n - sample))]
-    return x
-
-
-def griffin_lim(magnitudes, stft_fn, n_iters=30):
-    """
-    PARAMS
-    ------
-    magnitudes: spectrogram magnitudes
-    stft_fn: STFT class with transform (STFT) and inverse (ISTFT) methods
-    """
-
-    angles = np.angle(np.exp(2j * np.pi * np.random.rand(*magnitudes.size())))
-    angles = angles.astype(np.float32)
-    angles = torch.autograd.Variable(torch.from_numpy(angles))
-    signal = stft_fn.inverse(magnitudes, angles).squeeze(1)
-
-    for i in range(n_iters):
-        _, angles = stft_fn.transform(signal)
-        signal = stft_fn.inverse(magnitudes, angles).squeeze(1)
-    return signal
-
-
-def dynamic_range_compression(x, normalize_fun=torch.log, C=1, clip_val=1e-5):
-    """
-    PARAMS
-    ------
-    C: compression factor
-    """
-    return normalize_fun(torch.clamp(x, min=clip_val) * C)
-
-
-def dynamic_range_decompression(x, C=1):
-    """
-    PARAMS
-    ------
-    C: compression factor used to compress
-    """
-    return torch.exp(x) / C
diff --git a/spaces/declare-lab/tango/audioldm/latent_diffusion/attention.py b/spaces/declare-lab/tango/audioldm/latent_diffusion/attention.py
deleted file mode 100644
index 27886f5ee3c7eb856100503b838399106ef00051..0000000000000000000000000000000000000000
--- a/spaces/declare-lab/tango/audioldm/latent_diffusion/attention.py
+++ /dev/null
@@ -1,469 +0,0 @@
-from inspect import isfunction
-import math
-import torch
-import torch.nn.functional as F
-from torch import nn
-from einops import rearrange
-
-from audioldm.latent_diffusion.util import checkpoint
-
-
-def exists(val):
-    return val is not None
-
-
-def uniq(arr):
-    return {el: True for el in arr}.keys()
-
-
-def default(val, d):
-    if exists(val):
-        return val
-    return d() if isfunction(d) else d
-
-
-def max_neg_value(t):
-    return -torch.finfo(t.dtype).max
-
-
-def init_(tensor):
-    dim = tensor.shape[-1]
-    std = 1 / math.sqrt(dim)
-    tensor.uniform_(-std, std)
-    return tensor
-
-
-# feedforward
-class GEGLU(nn.Module):
-    def __init__(self, dim_in, dim_out):
-        super().__init__()
-        self.proj = nn.Linear(dim_in, dim_out * 2)
-
-    def forward(self, x):
-        x, gate = self.proj(x).chunk(2, dim=-1)
-        return x * F.gelu(gate)
-
-
-class FeedForward(nn.Module):
-    def __init__(self, dim, dim_out=None, mult=4, glu=False, dropout=0.0):
-        super().__init__()
-        inner_dim = int(dim * mult)
-        dim_out = default(dim_out, dim)
-        project_in = (
-            nn.Sequential(nn.Linear(dim, inner_dim), nn.GELU())
-            if not glu
-            else GEGLU(dim, inner_dim)
-        )
-
-        self.net = nn.Sequential(
-            project_in, nn.Dropout(dropout), nn.Linear(inner_dim, dim_out)
-        )
-
-    def forward(self, x):
-        return self.net(x)
-
-
-def zero_module(module):
-    """
-    Zero out the parameters of a module and return it.
-    """
-    for p in module.parameters():
-        p.detach().zero_()
-    return module
-
-
-def Normalize(in_channels):
-    return torch.nn.GroupNorm(
-        num_groups=32, num_channels=in_channels, eps=1e-6, affine=True
-    )
-
-
-class LinearAttention(nn.Module):
-    def __init__(self, dim, heads=4, dim_head=32):
-        super().__init__()
-        self.heads = heads
-        hidden_dim = dim_head * heads
-        self.to_qkv = nn.Conv2d(dim, hidden_dim * 3, 1, bias=False)
-        self.to_out = nn.Conv2d(hidden_dim, dim, 1)
-
-    def forward(self, x):
-        b, c, h, w = x.shape
-        qkv = self.to_qkv(x)
-        q, k, v = rearrange(
-            qkv, "b (qkv heads c) h w -> qkv b heads c (h w)", heads=self.heads, qkv=3
-        )
-        k = k.softmax(dim=-1)
-        context = torch.einsum("bhdn,bhen->bhde", k, v)
-        out = torch.einsum("bhde,bhdn->bhen", context, q)
-        out = rearrange(
-            out, "b heads c (h w) -> b (heads c) h w", heads=self.heads, h=h, w=w
-        )
-        return self.to_out(out)
-
-
-class SpatialSelfAttention(nn.Module):
-    def __init__(self, in_channels):
-        super().__init__()
-        self.in_channels = in_channels
-
-        self.norm = Normalize(in_channels)
-        self.q = torch.nn.Conv2d(
-            in_channels, in_channels, kernel_size=1, stride=1, padding=0
-        )
-        self.k = torch.nn.Conv2d(
-            in_channels, in_channels, kernel_size=1, stride=1, padding=0
-        )
-        self.v = torch.nn.Conv2d(
-            in_channels, in_channels, kernel_size=1, stride=1, padding=0
-        )
-        self.proj_out = torch.nn.Conv2d(
-            in_channels, in_channels, kernel_size=1, stride=1, padding=0
-        )
-
-    def forward(self, x):
-        h_ = x
-        h_ = self.norm(h_)
-        q = self.q(h_)
-        k = self.k(h_)
-        v = self.v(h_)
-
-        # compute attention
-        b, c, h, w = q.shape
-        q = rearrange(q, "b c h w -> b (h w) c")
-        k = rearrange(k, "b c h w -> b c (h w)")
-        w_ = torch.einsum("bij,bjk->bik", q, k)
-
-        w_ = w_ * (int(c) ** (-0.5))
-        w_ = torch.nn.functional.softmax(w_, dim=2)
-
-        # attend to values
-        v = rearrange(v, "b c h w -> b c (h w)")
-        w_ = rearrange(w_, "b i j -> b j i")
-        h_ = torch.einsum("bij,bjk->bik", v, w_)
-        h_ = rearrange(h_, "b c (h w) -> b c h w", h=h)
-        h_ = self.proj_out(h_)
-
-        return x + h_
-
-
-class CrossAttention(nn.Module):
-    """
-    ### Cross Attention Layer
-    This falls-back to self-attention when conditional embeddings are not specified.
-    """
-
-    # use_flash_attention: bool = True
-    use_flash_attention: bool = False
-
-    def __init__(
-        self,
-        query_dim,
-        context_dim=None,
-        heads=8,
-        dim_head=64,
-        dropout=0.0,
-        is_inplace: bool = True,
-    ):
-        # def __init__(self, d_model: int, d_cond: int, n_heads: int, d_head: int, is_inplace: bool = True):
-        """
-        :param d_model: is the input embedding size
-        :param n_heads: is the number of attention heads
-        :param d_head: is the size of a attention head
-        :param d_cond: is the size of the conditional embeddings
-        :param is_inplace: specifies whether to perform the attention softmax computation inplace to
-            save memory
-        """
-        super().__init__()
-
-        self.is_inplace = is_inplace
-        self.n_heads = heads
-        self.d_head = dim_head
-
-        # Attention scaling factor
-        self.scale = dim_head**-0.5
-
-        # The normal self-attention layer
-        if context_dim is None:
-            context_dim = query_dim
-
-        # Query, key and value mappings
-        d_attn = dim_head * heads
-        self.to_q = nn.Linear(query_dim, d_attn, bias=False)
-        self.to_k = nn.Linear(context_dim, d_attn, bias=False)
-        self.to_v = nn.Linear(context_dim, d_attn, bias=False)
-
-        # Final linear layer
-        self.to_out = nn.Sequential(nn.Linear(d_attn, query_dim), nn.Dropout(dropout))
-
-        # Setup [flash attention](https://github.com/HazyResearch/flash-attention).
-        # Flash attention is only used if it's installed
-        # and `CrossAttention.use_flash_attention` is set to `True`.
-        try:
-            # You can install flash attention by cloning their Github repo,
-            # [https://github.com/HazyResearch/flash-attention](https://github.com/HazyResearch/flash-attention)
-            # and then running `python setup.py install`
-            from flash_attn.flash_attention import FlashAttention
-
-            self.flash = FlashAttention()
-            # Set the scale for scaled dot-product attention.
-            self.flash.softmax_scale = self.scale
-        # Set to `None` if it's not installed
-        except ImportError:
-            self.flash = None
-
-    def forward(self, x, context=None, mask=None):
-        """
-        :param x: are the input embeddings of shape `[batch_size, height * width, d_model]`
-        :param cond: is the conditional embeddings of shape `[batch_size, n_cond, d_cond]`
-        """
-
-        # If `cond` is `None` we perform self attention
-        has_cond = context is not None
-        if not has_cond:
-            context = x
-
-        # Get query, key and value vectors
-        q = self.to_q(x)
-        k = self.to_k(context)
-        v = self.to_v(context)
-
-        # Use flash attention if it's available and the head size is less than or equal to `128`
-        if (
-            CrossAttention.use_flash_attention
-            and self.flash is not None
-            and not has_cond
-            and self.d_head <= 128
-        ):
-            return self.flash_attention(q, k, v)
-        # Otherwise, fallback to normal attention
-        else:
-            return self.normal_attention(q, k, v)
-
-    def flash_attention(self, q: torch.Tensor, k: torch.Tensor, v: torch.Tensor):
-        """
-        #### Flash Attention
-        :param q: are the query vectors before splitting heads, of shape `[batch_size, seq, d_attn]`
-        :param k: are the query vectors before splitting heads, of shape `[batch_size, seq, d_attn]`
-        :param v: are the query vectors before splitting heads, of shape `[batch_size, seq, d_attn]`
-        """
-
-        # Get batch size and number of elements along sequence axis (`width * height`)
-        batch_size, seq_len, _ = q.shape
-
-        # Stack `q`, `k`, `v` vectors for flash attention, to get a single tensor of
-        # shape `[batch_size, seq_len, 3, n_heads * d_head]`
-        qkv = torch.stack((q, k, v), dim=2)
-        # Split the heads
-        qkv = qkv.view(batch_size, seq_len, 3, self.n_heads, self.d_head)
-
-        # Flash attention works for head sizes `32`, `64` and `128`, so we have to pad the heads to
-        # fit this size.
-        if self.d_head <= 32:
-            pad = 32 - self.d_head
-        elif self.d_head <= 64:
-            pad = 64 - self.d_head
-        elif self.d_head <= 128:
-            pad = 128 - self.d_head
-        else:
-            raise ValueError(f"Head size ${self.d_head} too large for Flash Attention")
-
-        # Pad the heads
-        if pad:
-            qkv = torch.cat(
-                (qkv, qkv.new_zeros(batch_size, seq_len, 3, self.n_heads, pad)), dim=-1
-            )
-
-        # Compute attention
-        # $$\underset{seq}{softmax}\Bigg(\frac{Q K^\top}{\sqrt{d_{key}}}\Bigg)V$$
-        # This gives a tensor of shape `[batch_size, seq_len, n_heads, d_padded]`
-        # TODO here I add the dtype changing
-        out, _ = self.flash(qkv.type(torch.float16))
-        # Truncate the extra head size
-        out = out[:, :, :, : self.d_head].float()
-        # Reshape to `[batch_size, seq_len, n_heads * d_head]`
-        out = out.reshape(batch_size, seq_len, self.n_heads * self.d_head)
-
-        # Map to `[batch_size, height * width, d_model]` with a linear layer
-        return self.to_out(out)
-
-    def normal_attention(self, q: torch.Tensor, k: torch.Tensor, v: torch.Tensor):
-        """
-        #### Normal Attention
-
-        :param q: are the query vectors before splitting heads, of shape `[batch_size, seq, d_attn]`
-        :param k: are the query vectors before splitting heads, of shape `[batch_size, seq, d_attn]`
-        :param v: are the query vectors before splitting heads, of shape `[batch_size, seq, d_attn]`
-        """
-
-        # Split them to heads of shape `[batch_size, seq_len, n_heads, d_head]`
-        q = q.view(*q.shape[:2], self.n_heads, -1)  # [bs, 64, 20, 32]
-        k = k.view(*k.shape[:2], self.n_heads, -1)  # [bs, 1, 20, 32]
-        v = v.view(*v.shape[:2], self.n_heads, -1)
-
-        # Calculate attention $\frac{Q K^\top}{\sqrt{d_{key}}}$
-        attn = torch.einsum("bihd,bjhd->bhij", q, k) * self.scale
-
-        # Compute softmax
-        # $$\underset{seq}{softmax}\Bigg(\frac{Q K^\top}{\sqrt{d_{key}}}\Bigg)$$
-        if self.is_inplace:
-            half = attn.shape[0] // 2
-            attn[half:] = attn[half:].softmax(dim=-1)
-            attn[:half] = attn[:half].softmax(dim=-1)
-        else:
-            attn = attn.softmax(dim=-1)
-
-        # Compute attention output
-        # $$\underset{seq}{softmax}\Bigg(\frac{Q K^\top}{\sqrt{d_{key}}}\Bigg)V$$
-        # attn: [bs, 20, 64, 1]
-        # v: [bs, 1, 20, 32]
-        out = torch.einsum("bhij,bjhd->bihd", attn, v)
-        # Reshape to `[batch_size, height * width, n_heads * d_head]`
-        out = out.reshape(*out.shape[:2], -1)
-        # Map to `[batch_size, height * width, d_model]` with a linear layer
-        return self.to_out(out)
-
-
-# class CrossAttention(nn.Module):
-# def __init__(self, query_dim, context_dim=None, heads=8, dim_head=64, dropout=0.):
-#     super().__init__()
-#     inner_dim = dim_head * heads
-#     context_dim = default(context_dim, query_dim)
-
-#     self.scale = dim_head ** -0.5
-#     self.heads = heads
-
-#     self.to_q = nn.Linear(query_dim, inner_dim, bias=False)
-#     self.to_k = nn.Linear(context_dim, inner_dim, bias=False)
-#     self.to_v = nn.Linear(context_dim, inner_dim, bias=False)
-
-#     self.to_out = nn.Sequential(
-#         nn.Linear(inner_dim, query_dim),
-#         nn.Dropout(dropout)
-#     )
-
-# def forward(self, x, context=None, mask=None):
-#     h = self.heads
-
-#     q = self.to_q(x)
-#     context = default(context, x)
-#     k = self.to_k(context)
-#     v = self.to_v(context)
-
-#     q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
-
-#     sim = einsum('b i d, b j d -> b i j', q, k) * self.scale
-
-#     if exists(mask):
-#         mask = rearrange(mask, 'b ... -> b (...)')
-#         max_neg_value = -torch.finfo(sim.dtype).max
-#         mask = repeat(mask, 'b j -> (b h) () j', h=h)
-#         sim.masked_fill_(~mask, max_neg_value)
-
-#     # attention, what we cannot get enough of
-#     attn = sim.softmax(dim=-1)
-
-#     out = einsum('b i j, b j d -> b i d', attn, v)
-#     out = rearrange(out, '(b h) n d -> b n (h d)', h=h)
-#     return self.to_out(out)
-
-
-class BasicTransformerBlock(nn.Module):
-    def __init__(
-        self,
-        dim,
-        n_heads,
-        d_head,
-        dropout=0.0,
-        context_dim=None,
-        gated_ff=True,
-        checkpoint=True,
-    ):
-        super().__init__()
-        self.attn1 = CrossAttention(
-            query_dim=dim, heads=n_heads, dim_head=d_head, dropout=dropout
-        )  # is a self-attention
-        self.ff = FeedForward(dim, dropout=dropout, glu=gated_ff)
-        self.attn2 = CrossAttention(
-            query_dim=dim,
-            context_dim=context_dim,
-            heads=n_heads,
-            dim_head=d_head,
-            dropout=dropout,
-        )  # is self-attn if context is none
-        self.norm1 = nn.LayerNorm(dim)
-        self.norm2 = nn.LayerNorm(dim)
-        self.norm3 = nn.LayerNorm(dim)
-        self.checkpoint = checkpoint
-
-    def forward(self, x, context=None):
-        if context is None:
-            return checkpoint(self._forward, (x,), self.parameters(), self.checkpoint)
-        else:
-            return checkpoint(
-                self._forward, (x, context), self.parameters(), self.checkpoint
-            )
-
-    def _forward(self, x, context=None):
-        x = self.attn1(self.norm1(x)) + x
-        x = self.attn2(self.norm2(x), context=context) + x
-        x = self.ff(self.norm3(x)) + x
-        return x
-
-
-class SpatialTransformer(nn.Module):
-    """
-    Transformer block for image-like data.
-    First, project the input (aka embedding)
-    and reshape to b, t, d.
-    Then apply standard transformer action.
-    Finally, reshape to image
-    """
-
-    def __init__(
-        self,
-        in_channels,
-        n_heads,
-        d_head,
-        depth=1,
-        dropout=0.0,
-        context_dim=None,
-        no_context=False,
-    ):
-        super().__init__()
-
-        if no_context:
-            context_dim = None
-
-        self.in_channels = in_channels
-        inner_dim = n_heads * d_head
-        self.norm = Normalize(in_channels)
-
-        self.proj_in = nn.Conv2d(
-            in_channels, inner_dim, kernel_size=1, stride=1, padding=0
-        )
-
-        self.transformer_blocks = nn.ModuleList(
-            [
-                BasicTransformerBlock(
-                    inner_dim, n_heads, d_head, dropout=dropout, context_dim=context_dim
-                )
-                for d in range(depth)
-            ]
-        )
-
-        self.proj_out = zero_module(
-            nn.Conv2d(inner_dim, in_channels, kernel_size=1, stride=1, padding=0)
-        )
-
-    def forward(self, x, context=None):
-        # note: if no context is given, cross-attention defaults to self-attention
-        b, c, h, w = x.shape
-        x_in = x
-        x = self.norm(x)
-        x = self.proj_in(x)
-        x = rearrange(x, "b c h w -> b (h w) c")
-        for block in self.transformer_blocks:
-            x = block(x, context=context)
-        x = rearrange(x, "b (h w) c -> b c h w", h=h, w=w)
-        x = self.proj_out(x)
-        return x + x_in
diff --git a/spaces/declare-lab/tango/diffusers/tests/schedulers/test_scheduler_vq_diffusion.py b/spaces/declare-lab/tango/diffusers/tests/schedulers/test_scheduler_vq_diffusion.py
deleted file mode 100644
index 74437ad4548074a488917d3ea9b5eef4f0ac1532..0000000000000000000000000000000000000000
--- a/spaces/declare-lab/tango/diffusers/tests/schedulers/test_scheduler_vq_diffusion.py
+++ /dev/null
@@ -1,56 +0,0 @@
-import torch
-import torch.nn.functional as F
-
-from diffusers import VQDiffusionScheduler
-
-from .test_schedulers import SchedulerCommonTest
-
-
-class VQDiffusionSchedulerTest(SchedulerCommonTest):
-    scheduler_classes = (VQDiffusionScheduler,)
-
-    def get_scheduler_config(self, **kwargs):
-        config = {
-            "num_vec_classes": 4097,
-            "num_train_timesteps": 100,
-        }
-
-        config.update(**kwargs)
-        return config
-
-    def dummy_sample(self, num_vec_classes):
-        batch_size = 4
-        height = 8
-        width = 8
-
-        sample = torch.randint(0, num_vec_classes, (batch_size, height * width))
-
-        return sample
-
-    @property
-    def dummy_sample_deter(self):
-        assert False
-
-    def dummy_model(self, num_vec_classes):
-        def model(sample, t, *args):
-            batch_size, num_latent_pixels = sample.shape
-            logits = torch.rand((batch_size, num_vec_classes - 1, num_latent_pixels))
-            return_value = F.log_softmax(logits.double(), dim=1).float()
-            return return_value
-
-        return model
-
-    def test_timesteps(self):
-        for timesteps in [2, 5, 100, 1000]:
-            self.check_over_configs(num_train_timesteps=timesteps)
-
-    def test_num_vec_classes(self):
-        for num_vec_classes in [5, 100, 1000, 4000]:
-            self.check_over_configs(num_vec_classes=num_vec_classes)
-
-    def test_time_indices(self):
-        for t in [0, 50, 99]:
-            self.check_over_forward(time_step=t)
-
-    def test_add_noise_device(self):
-        pass
diff --git a/spaces/declare-lab/tango/diffusers/tests/test_utils.py b/spaces/declare-lab/tango/diffusers/tests/test_utils.py
deleted file mode 100644
index 4fc4e1a06638ae14848424db24f212ae24afbf34..0000000000000000000000000000000000000000
--- a/spaces/declare-lab/tango/diffusers/tests/test_utils.py
+++ /dev/null
@@ -1,170 +0,0 @@
-# coding=utf-8
-# Copyright 2023 HuggingFace Inc.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import unittest
-
-from diffusers import __version__
-from diffusers.utils import deprecate
-
-
-class DeprecateTester(unittest.TestCase):
-    higher_version = ".".join([str(int(__version__.split(".")[0]) + 1)] + __version__.split(".")[1:])
-    lower_version = "0.0.1"
-
-    def test_deprecate_function_arg(self):
-        kwargs = {"deprecated_arg": 4}
-
-        with self.assertWarns(FutureWarning) as warning:
-            output = deprecate("deprecated_arg", self.higher_version, "message", take_from=kwargs)
-
-        assert output == 4
-        assert (
-            str(warning.warning)
-            == f"The `deprecated_arg` argument is deprecated and will be removed in version {self.higher_version}."
-            " message"
-        )
-
-    def test_deprecate_function_arg_tuple(self):
-        kwargs = {"deprecated_arg": 4}
-
-        with self.assertWarns(FutureWarning) as warning:
-            output = deprecate(("deprecated_arg", self.higher_version, "message"), take_from=kwargs)
-
-        assert output == 4
-        assert (
-            str(warning.warning)
-            == f"The `deprecated_arg` argument is deprecated and will be removed in version {self.higher_version}."
-            " message"
-        )
-
-    def test_deprecate_function_args(self):
-        kwargs = {"deprecated_arg_1": 4, "deprecated_arg_2": 8}
-        with self.assertWarns(FutureWarning) as warning:
-            output_1, output_2 = deprecate(
-                ("deprecated_arg_1", self.higher_version, "Hey"),
-                ("deprecated_arg_2", self.higher_version, "Hey"),
-                take_from=kwargs,
-            )
-        assert output_1 == 4
-        assert output_2 == 8
-        assert (
-            str(warning.warnings[0].message)
-            == "The `deprecated_arg_1` argument is deprecated and will be removed in version"
-            f" {self.higher_version}. Hey"
-        )
-        assert (
-            str(warning.warnings[1].message)
-            == "The `deprecated_arg_2` argument is deprecated and will be removed in version"
-            f" {self.higher_version}. Hey"
-        )
-
-    def test_deprecate_function_incorrect_arg(self):
-        kwargs = {"deprecated_arg": 4}
-
-        with self.assertRaises(TypeError) as error:
-            deprecate(("wrong_arg", self.higher_version, "message"), take_from=kwargs)
-
-        assert "test_deprecate_function_incorrect_arg in" in str(error.exception)
-        assert "line" in str(error.exception)
-        assert "got an unexpected keyword argument `deprecated_arg`" in str(error.exception)
-
-    def test_deprecate_arg_no_kwarg(self):
-        with self.assertWarns(FutureWarning) as warning:
-            deprecate(("deprecated_arg", self.higher_version, "message"))
-
-        assert (
-            str(warning.warning)
-            == f"`deprecated_arg` is deprecated and will be removed in version {self.higher_version}. message"
-        )
-
-    def test_deprecate_args_no_kwarg(self):
-        with self.assertWarns(FutureWarning) as warning:
-            deprecate(
-                ("deprecated_arg_1", self.higher_version, "Hey"),
-                ("deprecated_arg_2", self.higher_version, "Hey"),
-            )
-        assert (
-            str(warning.warnings[0].message)
-            == f"`deprecated_arg_1` is deprecated and will be removed in version {self.higher_version}. Hey"
-        )
-        assert (
-            str(warning.warnings[1].message)
-            == f"`deprecated_arg_2` is deprecated and will be removed in version {self.higher_version}. Hey"
-        )
-
-    def test_deprecate_class_obj(self):
-        class Args:
-            arg = 5
-
-        with self.assertWarns(FutureWarning) as warning:
-            arg = deprecate(("arg", self.higher_version, "message"), take_from=Args())
-
-        assert arg == 5
-        assert (
-            str(warning.warning)
-            == f"The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message"
-        )
-
-    def test_deprecate_class_objs(self):
-        class Args:
-            arg = 5
-            foo = 7
-
-        with self.assertWarns(FutureWarning) as warning:
-            arg_1, arg_2 = deprecate(
-                ("arg", self.higher_version, "message"),
-                ("foo", self.higher_version, "message"),
-                ("does not exist", self.higher_version, "message"),
-                take_from=Args(),
-            )
-
-        assert arg_1 == 5
-        assert arg_2 == 7
-        assert (
-            str(warning.warning)
-            == f"The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message"
-        )
-        assert (
-            str(warning.warnings[0].message)
-            == f"The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message"
-        )
-        assert (
-            str(warning.warnings[1].message)
-            == f"The `foo` attribute is deprecated and will be removed in version {self.higher_version}. message"
-        )
-
-    def test_deprecate_incorrect_version(self):
-        kwargs = {"deprecated_arg": 4}
-
-        with self.assertRaises(ValueError) as error:
-            deprecate(("wrong_arg", self.lower_version, "message"), take_from=kwargs)
-
-        assert (
-            str(error.exception)
-            == "The deprecation tuple ('wrong_arg', '0.0.1', 'message') should be removed since diffusers' version"
-            f" {__version__} is >= {self.lower_version}"
-        )
-
-    def test_deprecate_incorrect_no_standard_warn(self):
-        with self.assertWarns(FutureWarning) as warning:
-            deprecate(("deprecated_arg", self.higher_version, "This message is better!!!"), standard_warn=False)
-
-        assert str(warning.warning) == "This message is better!!!"
-
-    def test_deprecate_stacklevel(self):
-        with self.assertWarns(FutureWarning) as warning:
-            deprecate(("deprecated_arg", self.higher_version, "This message is better!!!"), standard_warn=False)
-        assert str(warning.warning) == "This message is better!!!"
-        assert "diffusers/tests/test_utils.py" in warning.filename
diff --git a/spaces/deepdoctection/Document-AI-GPT/app.py b/spaces/deepdoctection/Document-AI-GPT/app.py
deleted file mode 100644
index 54e21e6643acf33459679e9020be5a27c27d81da..0000000000000000000000000000000000000000
--- a/spaces/deepdoctection/Document-AI-GPT/app.py
+++ /dev/null
@@ -1,164 +0,0 @@
-import time
-import os
-from os import getcwd, path
-import importlib.metadata
-from dotenv import load_dotenv
-
-
-def check_additional_requirements():
-    if importlib.util.find_spec("detectron2") is None:
-        os.system('pip install detectron2@git+https://github.com/facebookresearch/detectron2.git')
-    if importlib.util.find_spec("gradio") is not None:
-        if importlib.metadata.version("gradio")!="3.4.1":
-            os.system("pip uninstall -y gradio")
-            os.system("pip install gradio==3.4.1")
-    else:
-        os.system("pip install gradio==3.4.1")
-    os.system(os.environ["DD_ADDONS"])
-    return
-
-
-load_dotenv()
-check_additional_requirements()
-
-
-import deepdoctection as dd
-from deepdoctection.dataflow.serialize import DataFromList
-from deepdoctection.utils.settings import get_type
-
-from dd_addons.analyzer.loader import get_loader
-from dd_addons.extern.guidance import TOKEN_DEFAULT_INSTRUCTION
-from dd_addons.utils.settings import register_llm_token_tag, register_string_categories_from_list
-from dd_addons.extern.openai import OpenAiLmmTokenClassifier, is_api_key_valid
-
-import gradio as gr
-
-dd.Page.add_attribute_name("raw_json_output")
-analyzer = get_loader(reset_config_file=True, config_overwrite=["OCR.USE_TESSERACT=False",
-                                                                "OCR.USE_TEXTRACT=True",
-                                                                "WORD_MATCHING.MAX_PARENT_ONLY=True"])
-
-demo = gr.Blocks(css="scrollbar.css")
-
-
-def process_analyzer(openai_api_key, categories_str, instruction_str, img, pdf, max_datapoints):
-    if not is_api_key_valid(openai_api_key):
-        return [], {}, "You have entered no or an invalid api key. Please enter a valid api key"
-    categories_list = categories_str.split(",")
-    if not categories_str:
-        return [], {}, "You did not enter any entities. Please enter a at least one category."
-
-    register_string_categories_from_list(categories_list, "custom_token_classes")
-    custom_token_class = dd.object_types_registry.get("custom_token_classes")
-    print([token_class for token_class in custom_token_class])
-    register_llm_token_tag([token_class for token_class in custom_token_class])
-    categories = {
-        str(idx + 1): get_type(val) for idx, val in enumerate(categories_list)
-    }
-
-    gpt_token_classifier = OpenAiLmmTokenClassifier(
-        model_name="gpt-3.5-turbo",
-        categories=categories,
-        api_key=openai_api_key,
-        instruction= instruction_str if instruction_str else None,
-    )
-    analyzer.pipe_component_list[8].language_model = gpt_token_classifier
-
-    if img is not None:
-        image = dd.Image(file_name=str(time.time()).replace(".","") + ".png", location="")
-        image.image = img[:, :, ::-1]
-
-        df = DataFromList(lst=[image])
-        df = analyzer.analyze(dataset_dataflow=df)
-    elif pdf:
-        df = analyzer.analyze(path=pdf.name, max_datapoints=max_datapoints)
-    else:
-        raise ValueError
-
-    df.reset_state()
-
-    json_out = {}
-    dpts = []
-    json_out_raw = {}
-
-    for idx, dp in enumerate(df):
-        dpts.append(dp)
-        json_out[f"page_{idx}"] = dp.get_token()
-        json_out_raw[f"page_{idx}"] = dp.raw_json_output
-
-    return [dp.viz(show_cells=False, show_layouts=False, show_tables=False, show_words=True, show_token_class=True, ignore_default_token_class=True)
-            for dp in dpts], json_out, json_out_raw, "No error"
-
-
-with demo:
-    with gr.Box():
-        gr.Markdown("<h1><center>Document AI GPT</center></h1>")
-        gr.Markdown("<h2 ><center>Zero or few-shot Entity Extraction powered by ChatGPT and <strong>deep</strong>doctection </center></h2>"
-                    "<center>This pipeline consists of a stack of models powered for layout analysis and table recognition "
-                    "to prepare a prompt for ChatGPT. </center>"
-                    "<center>Be aware! The Space is still very fragile.</center><br />")
-    with gr.Box():
-        gr.Markdown("<h2><center>Upload a document and choose setting</center></h2>")
-        with gr.Row():
-            with gr.Column():
-                with gr.Tab("Image upload"):
-                    with gr.Column():
-                        inputs = gr.Image(type='numpy', label="Original Image")
-                with gr.Tab("PDF upload *"):
-                    with gr.Column():
-                        inputs_pdf = gr.File(label="PDF")
-                    gr.Markdown("<sup>* If an image is cached in tab, remove it first</sup>")
-                with gr.Box():
-                    gr.Examples(
-                        examples=[path.join(getcwd(), "sample_2.png")],
-                        inputs = inputs)
-                with gr.Box():
-                    gr.Markdown("Enter your OpenAI API Key* ")
-                    user_token = gr.Textbox(value='', placeholder="OpenAI API Key", type="password", show_label=False)
-
-                    gr.Markdown("<sup>* Your API key will not be saved. However, it is always recommended to deactivate the"
-                                "API key once it is entered into an unknown source</sup>")
-            with gr.Column():
-                with gr.Box():
-                    gr.Markdown(
-                        "Enter a list of comma seperated entities. Use a snake case style. Avoid special characters. "
-                        "Best way is to only use `a-z` and `_`")
-                    categories = gr.Textbox(value='', placeholder="mitarbeiter_anzahl", show_label=False)
-                with gr.Box():
-                    gr.Markdown("Optional: Enter a prompt for additional guidance. Will use the placeholder as fallback")
-                    instruction = gr.Textbox(value='', placeholder=TOKEN_DEFAULT_INSTRUCTION, show_label=False)
-        with gr.Row():
-            max_imgs = gr.Slider(1, 3, value=1, step=1, label="Number of pages in multi page PDF",
-                                 info="Will stop after 3 pages")
-
-        with gr.Row():
-            btn = gr.Button("Run model", variant="primary")
-
-    with gr.Box():
-        gr.Markdown("<h2><center>Outputs</center></h2>")
-        with gr.Row():
-            with gr.Column():
-                with gr.Box():
-                    gr.Markdown("<center><strong>Message</strong></center>")
-                    msg = gr.Textbox(value='', placeholder="message", show_label=False)
-            with gr.Column():
-                with gr.Box():
-                    gr.Markdown("<center><strong>JSON</strong></center>")
-                    json = gr.JSON()
-                with gr.Box():
-                    gr.Markdown("<center><strong>ChatGPT output. </strong> <br />"
-                                "It is possible that ChatGPT answers in an unexpected way, "
-                                "such that the answer cannot be properly processed. In this case you might get"
-                                "an empty JSON but you can still see the raw output.</center>")
-                    json_raw = gr.JSON()
-            with gr.Column():
-                with gr.Box():
-                    gr.Markdown("<center><strong>Layout detection</strong></center>")
-                    gallery = gr.Gallery(
-                        label="Output images", show_label=False, elem_id="gallery"
-                    ).style(grid=2)
-
-    btn.click(fn=process_analyzer, inputs=[user_token, categories,  instruction, inputs, inputs_pdf, max_imgs],
-              outputs=[gallery, json, json_raw, msg])
-
-demo.launch()
diff --git a/spaces/deepset/retrieval-augmentation-svb/utils/backend.py b/spaces/deepset/retrieval-augmentation-svb/utils/backend.py
deleted file mode 100644
index 104757ccf71a73906275287d1e647590f5497367..0000000000000000000000000000000000000000
--- a/spaces/deepset/retrieval-augmentation-svb/utils/backend.py
+++ /dev/null
@@ -1,64 +0,0 @@
-import streamlit as st
-from haystack import Pipeline
-from haystack.document_stores import FAISSDocumentStore
-from haystack.nodes import Shaper, PromptNode, PromptTemplate, PromptModel, EmbeddingRetriever
-from haystack.nodes.retriever.web import WebRetriever
-
-
-@st.cache_resource(show_spinner=False)
-def get_plain_pipeline():
-    prompt_open_ai = PromptModel(model_name_or_path="text-davinci-003", api_key=st.secrets["OPENAI_API_KEY"])
-    # Now let make one PromptNode use the default model and the other one the OpenAI model:
-    plain_llm_template = PromptTemplate(name="plain_llm", prompt_text="Answer the following question: {query}")
-    node_openai = PromptNode(prompt_open_ai, default_prompt_template=plain_llm_template, max_length=300)
-    pipeline = Pipeline()
-    pipeline.add_node(component=node_openai, name="prompt_node", inputs=["Query"])
-    return pipeline
-
-
-@st.cache_resource(show_spinner=False)
-def get_retrieval_augmented_pipeline():
-    ds = FAISSDocumentStore(faiss_index_path="data/my_faiss_index.faiss",
-                            faiss_config_path="data/my_faiss_index.json")
-
-    retriever = EmbeddingRetriever(
-        document_store=ds,
-        embedding_model="sentence-transformers/multi-qa-mpnet-base-dot-v1",
-        model_format="sentence_transformers",
-        top_k=2
-    )
-
-    default_template = PromptTemplate(
-        name="question-answering",
-        prompt_text="Given the context please answer the question. Context: {join(documents)}; Question: "
-                    "{query}; Answer:",
-    )
-
-    # Let's initiate the PromptNode
-    node = PromptNode("text-davinci-003", default_prompt_template=default_template,
-                      api_key=st.secrets["OPENAI_API_KEY"], max_length=500)
-
-    # Let's create a simple retrieval augmented pipeline with the retriever + PromptNode
-    pipeline = Pipeline()
-    pipeline.add_node(component=retriever, name='retriever', inputs=['Query'])
-    pipeline.add_node(component=node, name="prompt_node", inputs=["retriever"])
-    return pipeline
-
-
-@st.cache_resource(show_spinner=False)
-def get_web_retrieval_augmented_pipeline():
-    search_key = st.secrets["WEBRET_API_KEY"]
-    web_retriever = WebRetriever(api_key=search_key, search_engine_provider="SerperDev")
-    default_template = PromptTemplate(
-        name="question-answering",
-        prompt_text="Given the context please answer the question. Context: {join(documents)}; Question: "
-                    "{query}; Answer:",
-    )
-    # Let's initiate the PromptNode
-    node = PromptNode("text-davinci-003", default_prompt_template=default_template,
-                      api_key=st.secrets["OPENAI_API_KEY"], max_length=500)
-    # Let's create a pipeline with the webretriever + PromptNode
-    pipeline = Pipeline()
-    pipeline.add_node(component=web_retriever, name='retriever', inputs=['Query'])
-    pipeline.add_node(component=node, name="prompt_node", inputs=["retriever"])
-    return pipeline
diff --git a/spaces/deepskyreal/ai-mixer-hotchpotch/sad_talker/src/face3d/models/arcface_torch/eval/verification.py b/spaces/deepskyreal/ai-mixer-hotchpotch/sad_talker/src/face3d/models/arcface_torch/eval/verification.py
deleted file mode 100644
index 253343b83dbf9d1bd154d14ec068e098bf0968db..0000000000000000000000000000000000000000
--- a/spaces/deepskyreal/ai-mixer-hotchpotch/sad_talker/src/face3d/models/arcface_torch/eval/verification.py
+++ /dev/null
@@ -1,407 +0,0 @@
-"""Helper for evaluation on the Labeled Faces in the Wild dataset 
-"""
-
-# MIT License
-#
-# Copyright (c) 2016 David Sandberg
-#
-# Permission is hereby granted, free of charge, to any person obtaining a copy
-# of this software and associated documentation files (the "Software"), to deal
-# in the Software without restriction, including without limitation the rights
-# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-# copies of the Software, and to permit persons to whom the Software is
-# furnished to do so, subject to the following conditions:
-#
-# The above copyright notice and this permission notice shall be included in all
-# copies or substantial portions of the Software.
-#
-# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-# SOFTWARE.
-
-
-import datetime
-import os
-import pickle
-
-import mxnet as mx
-import numpy as np
-import sklearn
-import torch
-from mxnet import ndarray as nd
-from scipy import interpolate
-from sklearn.decomposition import PCA
-from sklearn.model_selection import KFold
-
-
-class LFold:
-    def __init__(self, n_splits=2, shuffle=False):
-        self.n_splits = n_splits
-        if self.n_splits > 1:
-            self.k_fold = KFold(n_splits=n_splits, shuffle=shuffle)
-
-    def split(self, indices):
-        if self.n_splits > 1:
-            return self.k_fold.split(indices)
-        else:
-            return [(indices, indices)]
-
-
-def calculate_roc(thresholds,
-                  embeddings1,
-                  embeddings2,
-                  actual_issame,
-                  nrof_folds=10,
-                  pca=0):
-    assert (embeddings1.shape[0] == embeddings2.shape[0])
-    assert (embeddings1.shape[1] == embeddings2.shape[1])
-    nrof_pairs = min(len(actual_issame), embeddings1.shape[0])
-    nrof_thresholds = len(thresholds)
-    k_fold = LFold(n_splits=nrof_folds, shuffle=False)
-
-    tprs = np.zeros((nrof_folds, nrof_thresholds))
-    fprs = np.zeros((nrof_folds, nrof_thresholds))
-    accuracy = np.zeros((nrof_folds))
-    indices = np.arange(nrof_pairs)
-
-    if pca == 0:
-        diff = np.subtract(embeddings1, embeddings2)
-        dist = np.sum(np.square(diff), 1)
-
-    for fold_idx, (train_set, test_set) in enumerate(k_fold.split(indices)):
-        if pca > 0:
-            print('doing pca on', fold_idx)
-            embed1_train = embeddings1[train_set]
-            embed2_train = embeddings2[train_set]
-            _embed_train = np.concatenate((embed1_train, embed2_train), axis=0)
-            pca_model = PCA(n_components=pca)
-            pca_model.fit(_embed_train)
-            embed1 = pca_model.transform(embeddings1)
-            embed2 = pca_model.transform(embeddings2)
-            embed1 = sklearn.preprocessing.normalize(embed1)
-            embed2 = sklearn.preprocessing.normalize(embed2)
-            diff = np.subtract(embed1, embed2)
-            dist = np.sum(np.square(diff), 1)
-
-        # Find the best threshold for the fold
-        acc_train = np.zeros((nrof_thresholds))
-        for threshold_idx, threshold in enumerate(thresholds):
-            _, _, acc_train[threshold_idx] = calculate_accuracy(
-                threshold, dist[train_set], actual_issame[train_set])
-        best_threshold_index = np.argmax(acc_train)
-        for threshold_idx, threshold in enumerate(thresholds):
-            tprs[fold_idx, threshold_idx], fprs[fold_idx, threshold_idx], _ = calculate_accuracy(
-                threshold, dist[test_set],
-                actual_issame[test_set])
-        _, _, accuracy[fold_idx] = calculate_accuracy(
-            thresholds[best_threshold_index], dist[test_set],
-            actual_issame[test_set])
-
-    tpr = np.mean(tprs, 0)
-    fpr = np.mean(fprs, 0)
-    return tpr, fpr, accuracy
-
-
-def calculate_accuracy(threshold, dist, actual_issame):
-    predict_issame = np.less(dist, threshold)
-    tp = np.sum(np.logical_and(predict_issame, actual_issame))
-    fp = np.sum(np.logical_and(predict_issame, np.logical_not(actual_issame)))
-    tn = np.sum(
-        np.logical_and(np.logical_not(predict_issame),
-                       np.logical_not(actual_issame)))
-    fn = np.sum(np.logical_and(np.logical_not(predict_issame), actual_issame))
-
-    tpr = 0 if (tp + fn == 0) else float(tp) / float(tp + fn)
-    fpr = 0 if (fp + tn == 0) else float(fp) / float(fp + tn)
-    acc = float(tp + tn) / dist.size
-    return tpr, fpr, acc
-
-
-def calculate_val(thresholds,
-                  embeddings1,
-                  embeddings2,
-                  actual_issame,
-                  far_target,
-                  nrof_folds=10):
-    assert (embeddings1.shape[0] == embeddings2.shape[0])
-    assert (embeddings1.shape[1] == embeddings2.shape[1])
-    nrof_pairs = min(len(actual_issame), embeddings1.shape[0])
-    nrof_thresholds = len(thresholds)
-    k_fold = LFold(n_splits=nrof_folds, shuffle=False)
-
-    val = np.zeros(nrof_folds)
-    far = np.zeros(nrof_folds)
-
-    diff = np.subtract(embeddings1, embeddings2)
-    dist = np.sum(np.square(diff), 1)
-    indices = np.arange(nrof_pairs)
-
-    for fold_idx, (train_set, test_set) in enumerate(k_fold.split(indices)):
-
-        # Find the threshold that gives FAR = far_target
-        far_train = np.zeros(nrof_thresholds)
-        for threshold_idx, threshold in enumerate(thresholds):
-            _, far_train[threshold_idx] = calculate_val_far(
-                threshold, dist[train_set], actual_issame[train_set])
-        if np.max(far_train) >= far_target:
-            f = interpolate.interp1d(far_train, thresholds, kind='slinear')
-            threshold = f(far_target)
-        else:
-            threshold = 0.0
-
-        val[fold_idx], far[fold_idx] = calculate_val_far(
-            threshold, dist[test_set], actual_issame[test_set])
-
-    val_mean = np.mean(val)
-    far_mean = np.mean(far)
-    val_std = np.std(val)
-    return val_mean, val_std, far_mean
-
-
-def calculate_val_far(threshold, dist, actual_issame):
-    predict_issame = np.less(dist, threshold)
-    true_accept = np.sum(np.logical_and(predict_issame, actual_issame))
-    false_accept = np.sum(
-        np.logical_and(predict_issame, np.logical_not(actual_issame)))
-    n_same = np.sum(actual_issame)
-    n_diff = np.sum(np.logical_not(actual_issame))
-    # print(true_accept, false_accept)
-    # print(n_same, n_diff)
-    val = float(true_accept) / float(n_same)
-    far = float(false_accept) / float(n_diff)
-    return val, far
-
-
-def evaluate(embeddings, actual_issame, nrof_folds=10, pca=0):
-    # Calculate evaluation metrics
-    thresholds = np.arange(0, 4, 0.01)
-    embeddings1 = embeddings[0::2]
-    embeddings2 = embeddings[1::2]
-    tpr, fpr, accuracy = calculate_roc(thresholds,
-                                       embeddings1,
-                                       embeddings2,
-                                       np.asarray(actual_issame),
-                                       nrof_folds=nrof_folds,
-                                       pca=pca)
-    thresholds = np.arange(0, 4, 0.001)
-    val, val_std, far = calculate_val(thresholds,
-                                      embeddings1,
-                                      embeddings2,
-                                      np.asarray(actual_issame),
-                                      1e-3,
-                                      nrof_folds=nrof_folds)
-    return tpr, fpr, accuracy, val, val_std, far
-
-@torch.no_grad()
-def load_bin(path, image_size):
-    try:
-        with open(path, 'rb') as f:
-            bins, issame_list = pickle.load(f)  # py2
-    except UnicodeDecodeError as e:
-        with open(path, 'rb') as f:
-            bins, issame_list = pickle.load(f, encoding='bytes')  # py3
-    data_list = []
-    for flip in [0, 1]:
-        data = torch.empty((len(issame_list) * 2, 3, image_size[0], image_size[1]))
-        data_list.append(data)
-    for idx in range(len(issame_list) * 2):
-        _bin = bins[idx]
-        img = mx.image.imdecode(_bin)
-        if img.shape[1] != image_size[0]:
-            img = mx.image.resize_short(img, image_size[0])
-        img = nd.transpose(img, axes=(2, 0, 1))
-        for flip in [0, 1]:
-            if flip == 1:
-                img = mx.ndarray.flip(data=img, axis=2)
-            data_list[flip][idx][:] = torch.from_numpy(img.asnumpy())
-        if idx % 1000 == 0:
-            print('loading bin', idx)
-    print(data_list[0].shape)
-    return data_list, issame_list
-
-@torch.no_grad()
-def test(data_set, backbone, batch_size, nfolds=10):
-    print('testing verification..')
-    data_list = data_set[0]
-    issame_list = data_set[1]
-    embeddings_list = []
-    time_consumed = 0.0
-    for i in range(len(data_list)):
-        data = data_list[i]
-        embeddings = None
-        ba = 0
-        while ba < data.shape[0]:
-            bb = min(ba + batch_size, data.shape[0])
-            count = bb - ba
-            _data = data[bb - batch_size: bb]
-            time0 = datetime.datetime.now()
-            img = ((_data / 255) - 0.5) / 0.5
-            net_out: torch.Tensor = backbone(img)
-            _embeddings = net_out.detach().cpu().numpy()
-            time_now = datetime.datetime.now()
-            diff = time_now - time0
-            time_consumed += diff.total_seconds()
-            if embeddings is None:
-                embeddings = np.zeros((data.shape[0], _embeddings.shape[1]))
-            embeddings[ba:bb, :] = _embeddings[(batch_size - count):, :]
-            ba = bb
-        embeddings_list.append(embeddings)
-
-    _xnorm = 0.0
-    _xnorm_cnt = 0
-    for embed in embeddings_list:
-        for i in range(embed.shape[0]):
-            _em = embed[i]
-            _norm = np.linalg.norm(_em)
-            _xnorm += _norm
-            _xnorm_cnt += 1
-    _xnorm /= _xnorm_cnt
-
-    acc1 = 0.0
-    std1 = 0.0
-    embeddings = embeddings_list[0] + embeddings_list[1]
-    embeddings = sklearn.preprocessing.normalize(embeddings)
-    print(embeddings.shape)
-    print('infer time', time_consumed)
-    _, _, accuracy, val, val_std, far = evaluate(embeddings, issame_list, nrof_folds=nfolds)
-    acc2, std2 = np.mean(accuracy), np.std(accuracy)
-    return acc1, std1, acc2, std2, _xnorm, embeddings_list
-
-
-def dumpR(data_set,
-          backbone,
-          batch_size,
-          name='',
-          data_extra=None,
-          label_shape=None):
-    print('dump verification embedding..')
-    data_list = data_set[0]
-    issame_list = data_set[1]
-    embeddings_list = []
-    time_consumed = 0.0
-    for i in range(len(data_list)):
-        data = data_list[i]
-        embeddings = None
-        ba = 0
-        while ba < data.shape[0]:
-            bb = min(ba + batch_size, data.shape[0])
-            count = bb - ba
-
-            _data = nd.slice_axis(data, axis=0, begin=bb - batch_size, end=bb)
-            time0 = datetime.datetime.now()
-            if data_extra is None:
-                db = mx.io.DataBatch(data=(_data,), label=(_label,))
-            else:
-                db = mx.io.DataBatch(data=(_data, _data_extra),
-                                     label=(_label,))
-            model.forward(db, is_train=False)
-            net_out = model.get_outputs()
-            _embeddings = net_out[0].asnumpy()
-            time_now = datetime.datetime.now()
-            diff = time_now - time0
-            time_consumed += diff.total_seconds()
-            if embeddings is None:
-                embeddings = np.zeros((data.shape[0], _embeddings.shape[1]))
-            embeddings[ba:bb, :] = _embeddings[(batch_size - count):, :]
-            ba = bb
-        embeddings_list.append(embeddings)
-    embeddings = embeddings_list[0] + embeddings_list[1]
-    embeddings = sklearn.preprocessing.normalize(embeddings)
-    actual_issame = np.asarray(issame_list)
-    outname = os.path.join('temp.bin')
-    with open(outname, 'wb') as f:
-        pickle.dump((embeddings, issame_list),
-                    f,
-                    protocol=pickle.HIGHEST_PROTOCOL)
-
-
-# if __name__ == '__main__':
-#
-#     parser = argparse.ArgumentParser(description='do verification')
-#     # general
-#     parser.add_argument('--data-dir', default='', help='')
-#     parser.add_argument('--model',
-#                         default='../model/softmax,50',
-#                         help='path to load model.')
-#     parser.add_argument('--target',
-#                         default='lfw,cfp_ff,cfp_fp,agedb_30',
-#                         help='test targets.')
-#     parser.add_argument('--gpu', default=0, type=int, help='gpu id')
-#     parser.add_argument('--batch-size', default=32, type=int, help='')
-#     parser.add_argument('--max', default='', type=str, help='')
-#     parser.add_argument('--mode', default=0, type=int, help='')
-#     parser.add_argument('--nfolds', default=10, type=int, help='')
-#     args = parser.parse_args()
-#     image_size = [112, 112]
-#     print('image_size', image_size)
-#     ctx = mx.gpu(args.gpu)
-#     nets = []
-#     vec = args.model.split(',')
-#     prefix = args.model.split(',')[0]
-#     epochs = []
-#     if len(vec) == 1:
-#         pdir = os.path.dirname(prefix)
-#         for fname in os.listdir(pdir):
-#             if not fname.endswith('.params'):
-#                 continue
-#             _file = os.path.join(pdir, fname)
-#             if _file.startswith(prefix):
-#                 epoch = int(fname.split('.')[0].split('-')[1])
-#                 epochs.append(epoch)
-#         epochs = sorted(epochs, reverse=True)
-#         if len(args.max) > 0:
-#             _max = [int(x) for x in args.max.split(',')]
-#             assert len(_max) == 2
-#             if len(epochs) > _max[1]:
-#                 epochs = epochs[_max[0]:_max[1]]
-#
-#     else:
-#         epochs = [int(x) for x in vec[1].split('|')]
-#     print('model number', len(epochs))
-#     time0 = datetime.datetime.now()
-#     for epoch in epochs:
-#         print('loading', prefix, epoch)
-#         sym, arg_params, aux_params = mx.model.load_checkpoint(prefix, epoch)
-#         # arg_params, aux_params = ch_dev(arg_params, aux_params, ctx)
-#         all_layers = sym.get_internals()
-#         sym = all_layers['fc1_output']
-#         model = mx.mod.Module(symbol=sym, context=ctx, label_names=None)
-#         # model.bind(data_shapes=[('data', (args.batch_size, 3, image_size[0], image_size[1]))], label_shapes=[('softmax_label', (args.batch_size,))])
-#         model.bind(data_shapes=[('data', (args.batch_size, 3, image_size[0],
-#                                           image_size[1]))])
-#         model.set_params(arg_params, aux_params)
-#         nets.append(model)
-#     time_now = datetime.datetime.now()
-#     diff = time_now - time0
-#     print('model loading time', diff.total_seconds())
-#
-#     ver_list = []
-#     ver_name_list = []
-#     for name in args.target.split(','):
-#         path = os.path.join(args.data_dir, name + ".bin")
-#         if os.path.exists(path):
-#             print('loading.. ', name)
-#             data_set = load_bin(path, image_size)
-#             ver_list.append(data_set)
-#             ver_name_list.append(name)
-#
-#     if args.mode == 0:
-#         for i in range(len(ver_list)):
-#             results = []
-#             for model in nets:
-#                 acc1, std1, acc2, std2, xnorm, embeddings_list = test(
-#                     ver_list[i], model, args.batch_size, args.nfolds)
-#                 print('[%s]XNorm: %f' % (ver_name_list[i], xnorm))
-#                 print('[%s]Accuracy: %1.5f+-%1.5f' % (ver_name_list[i], acc1, std1))
-#                 print('[%s]Accuracy-Flip: %1.5f+-%1.5f' % (ver_name_list[i], acc2, std2))
-#                 results.append(acc2)
-#             print('Max of [%s] is %1.5f' % (ver_name_list[i], np.max(results)))
-#     elif args.mode == 1:
-#         raise ValueError
-#     else:
-#         model = nets[0]
-#         dumpR(ver_list[0], model, args.batch_size, args.target)
diff --git a/spaces/deepwisdom/MetaGPT/tests/metagpt/roles/test_product_manager.py b/spaces/deepwisdom/MetaGPT/tests/metagpt/roles/test_product_manager.py
deleted file mode 100644
index 34c70efbc2d5a28d0422560b21775405dc66b6b1..0000000000000000000000000000000000000000
--- a/spaces/deepwisdom/MetaGPT/tests/metagpt/roles/test_product_manager.py
+++ /dev/null
@@ -1,21 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-"""
-@Time    : 2023/5/16 14:50
-@Author  : alexanderwu
-@File    : test_product_manager.py
-"""
-import pytest
-
-from metagpt.logs import logger
-from metagpt.roles import ProductManager
-from tests.metagpt.roles.mock import MockMessages
-
-
-@pytest.mark.asyncio
-async def test_product_manager():
-    product_manager = ProductManager()
-    rsp = await product_manager.handle(MockMessages.req)
-    logger.info(rsp)
-    assert len(rsp.content) > 0
-    assert "产品目标" in rsp.content
diff --git a/spaces/deepwisdom/MetaGPT/tests/metagpt/tools/test_sd_tool.py b/spaces/deepwisdom/MetaGPT/tests/metagpt/tools/test_sd_tool.py
deleted file mode 100644
index 89c97f5e8028cf63a1fdbef3b8140ab6d870a5b8..0000000000000000000000000000000000000000
--- a/spaces/deepwisdom/MetaGPT/tests/metagpt/tools/test_sd_tool.py
+++ /dev/null
@@ -1,26 +0,0 @@
-# -*- coding: utf-8 -*-
-# @Date    : 2023/7/22 02:40
-# @Author  : stellahong (stellahong@fuzhi.ai)
-#
-import os
-
-from metagpt.config import CONFIG
-from metagpt.tools.sd_engine import SDEngine
-
-
-def test_sd_engine_init():
-    sd_engine = SDEngine()
-    assert sd_engine.payload["seed"] == -1
-
-
-def test_sd_engine_generate_prompt():
-    sd_engine = SDEngine()
-    sd_engine.construct_payload(prompt="test")
-    assert sd_engine.payload["prompt"] == "test"
-
-
-async def test_sd_engine_run_t2i():
-    sd_engine = SDEngine()
-    await sd_engine.run_t2i(prompts=["test"])
-    img_path = CONFIG.workspace / "resources" / "SD_Output" / "output_0.png"
-    assert os.path.exists(img_path) == True
diff --git a/spaces/dev-andres/Caracola-app/models/plantillas_codigo.py b/spaces/dev-andres/Caracola-app/models/plantillas_codigo.py
deleted file mode 100644
index cb27d29fbef024f7094401c780edcc8c75e9275c..0000000000000000000000000000000000000000
--- a/spaces/dev-andres/Caracola-app/models/plantillas_codigo.py
+++ /dev/null
@@ -1,628 +0,0 @@
-import re
-
-def crear_funcion(instruccion):
-    """
-    Crea el template de la estructura de una función
-
-    Parametros
-    ----------
-    instrucion: str
-        La intruccion de voz en texto.
-
-    Regresa
-    ---------
-    output: str
-        Codigo generado
-    recomendacion: str
-        Una sugerencia o fallo
-    """
-
-    global indentacion
-    global recomendacion
-    global bloque
-
-    bloque='funcion'
-
-    # guarda los avisos o recomendaciones que el programa te hace
-    recomendacion = ''
-
-    # guarda la línea de código
-    output = ''
-    
-    # pivote que ayuda a definir el nombre de una función
-    before_keyword, keyword, after_keyword = instruccion.partition('nombre')
-
-    # verifica que haya o esté escrita la frase "nombre"
-    if len(after_keyword) == 0:
-        recomendacion = f'¡No me dijiste el nombre de la función!'
-
-    # de otro modo, si tiene nombre la función
-    else:
-
-        # obtenemos el nombre de la función por el usuario
-        name_func = after_keyword.split(' ')[1]
-
-        # verificamos si no desea poner parametros                                
-        if instruccion.strip().split(' ')[-1] == name_func:
-            parametros = ''
-
-        # de otro modo, si desea una función con parámetros
-        else:
-            before_keyword, keyword, after_keyword = instruccion.partition('parametros')
-
-            # verifica que si exista el nombre de los parámetros
-            if len(after_keyword) == 0:
-                parametros = ''
-                recomendacion = f'¡No me dijiste el nombre de los parámetros!'
-
-            # escribe como parámetros todo lo que está después de "parámetros"
-            else:
-                candidatos = []
-                cadena_separada = after_keyword.strip().split(' ')
-
-                for palabra in cadena_separada:
-                    try:
-                        candidatos.append(diccionario_fonetico[palabra])
-                    except:
-                        continue
-                
-                if len(candidatos) == 0:
-                    parametros = after_keyword.split(' ')[1:]
-                    parametros = ', '.join(parametros)
-
-                else:
-                    parametros = ', '.join(candidatos)
-
-        # indenta aunque marque que detecte que no le dije parámetros
-        if not recomendacion or recomendacion == '¡No me dijiste el nombre de los parámetros!':
-            indentacion += 1
-
-        # concatenación del nombre y parámetros de la función
-        output = f'<span style="color: #008000; font-weight: bold">def</span> <span style="color: #0066bb; font-weight: bold">{name_func}</span>({parametros}):<br>' + '&emsp;' * indentacion + '|'
-    return output
-
-import re
-def encontrar_palabras(transcript,cjto_palabras):
-
-    """
-    Toma un string (en minúsculos) y un conjunto de palabras. Busca el primer match
-    de cjto_palabras en transcript y particiona el string
-
-    Parametros
-    ----------
-    transcript: str
-        La intruccion de voz en texto ya en minúsculas.
-    cjto_palabras: list(str)
-        Lista de strings donde se comienza a dividir el transcript original
-
-    Regresa
-    ---------
-    output: list(str)
-        [antes_palabra,palabra,despues_palabra]
-
-        antes_palabra: string que está antes de la palabra de interés (de cjto_palabras)
-        palabra: string que da la palabra clave donde dividimos
-        despues_palabra: string que está después de la palabra
-    
-    Ejemplo
-    --------
-    encontrar_palabras('variable india producto variable alfa',['producto','suma','menos','entre'])
-    >> ['variable india','producto',' variable alfa]
-    """ 
-    inicio,final=list(re.finditer(r'|'.join(cjto_palabras),transcript))[0].span()
-    antes_palabra=transcript[:inicio].strip()
-    despues_palabra=transcript[final:].strip()
-    palabra=transcript[inicio:final]
-    return antes_palabra,palabra,despues_palabra
-
-def crear_condicional(transcript):
-    ''' 
-    Toma el transcript de un enunciado condicional y regresa su traducción a código en Python
-
-    Parametros
-    ----------
-    transcript: str
-        La intruccion de voz en texto ya en minúsculas.
-
-
-    Regresa
-    ---------
-    output: str
-        Cadena con el código en python, tiene una línea al final y un pipe 
-        que representa el prompt donde se seguirá escribiendo
-    
-    Ejemplo
-    --------
-    crear_condicional('mientras variable india sea menor igual a numero seis')
-    >> while (i<=6):
-    >>      |
-    '''    
-    global indentacion
-    global bloque
-
-    keyword_mapeo={'mientras':'while','si':'if','contrario':'else'}
-    antes_keyword,keyword,desp_keyword=encontrar_palabras(transcript,keyword_mapeo.keys())
-    cadena=keyword_mapeo[keyword]
-    bloque = keyword
-
-    if cadena=='else':
-        indentacion=indentacion+1
-        return 'else:'+'\n' +'\t'* indentacion+'|'
-
-    # Primera división
-    condicional_mapeo={'menor estricto':'<','menor o igual':'<=','igual':'==','diferente':'!='
-    ,'mayor estricto':'>','mayor o igual':'>='}
-    cjto_condicional=condicional_mapeo.keys()
-    antes_condicional,palabra_condicional,despues_condicional=encontrar_palabras(transcript,cjto_condicional) 
-    
-    
-    # Buscar antes en la lista de variables
-    a_var,var,d_var=encontrar_palabras(antes_condicional,['variable'])
-    nombre_var=d_var.split(' ')[0]
-
-    if diccionario_fonetico.get(nombre_var,False):
-        nombre_var=diccionario_fonetico[nombre_var]
-
-
-    cadena+=' '+nombre_var+' ' +condicional_mapeo[palabra_condicional]
-
-    # Buscar en despues_condicional el número 
-
-    valor=despues_condicional.split(' ')[-1]
-
-    if dict_numeros.get(valor,False):
-        valor=str(dict_numeros[valor])
-
-    indentacion+=1
-    #t = f'<span style="text-indent:{20 * indentacion}px";> <span>'
-    return f'<span style="color: #008000; font-weight: bold">{keyword_mapeo[keyword]} </span> {nombre_var} {condicional_mapeo[palabra_condicional]} {valor}:'+'<br>' +'&emsp;'* indentacion+'|'
-
-
-
-def crear_cadena(transcript):
-    """
-    Toma el transcript de un enunciado que contiene una cadena y regresa el código en Python.
-    Para usarse cuando ya se sabe que transcript sólo es los límites de la cadena
-
-    Parametros
-    ----------
-    transcript: str
-        La intruccion de voz en texto ya en minúsculas.
-
-
-    Regresa
-    ---------
-    output: list(str)
-        antes_palabra:parte del transcript que va antes de las comillas
-        palabra: Cadena con el código en python de las comillas y lo que está adentro
-        despues_palabra:parte del transcript que va antes de las comillas
-    
-    Ejemplo
-    --------
-    crear_cadena('ejecuta print con argumentos variable India producto cadena guion cadena')[1]
-    >> ['ejecuta print con argumentos variable India producto','"guion"','']
-    """
-    try:
-        inicio,final=list(re.finditer(r"cadena (.+) cadena",transcript))[0].span()
-    except:
-        return ''
-    antes_palabra=transcript[:inicio].strip()
-    despues_palabra=transcript[final:].strip()
-    palabra=list(re.finditer(r"cadena (.+) cadena",transcript))[0].group(1)
-    return antes_palabra,f'"{palabra}"',despues_palabra
-
-def crear_var_existente(transcript):
-    """
-    Toma el transcript de un enunciado que contiene la mención de una variable
-     y devuelve dicha variable
-
-    Parametros
-    ----------
-    transcript: str
-        La intruccion de voz en texto ya en minúsculas.
-
-
-    Regresa
-    ---------
-    output: str
-        palabra: Cadena con el código en python del nombre de la variable
-    
-    Ejemplo
-    --------
-    crear_var_existente('ejecuta print con argumentos variable india producto cadena guión cadena')
-    >> i
-    """
-    try:
-        antes_var,var,desp_var=encontrar_palabras(transcript,['variable'])
-    except:
-        return '' 
-
-    nombre_var=desp_var.split(' ')[0]
-    if diccionario_fonetico.get(nombre_var,False):
-        nombre_var=diccionario_fonetico[nombre_var]
-    
-    return nombre_var
-
-
-# TODO: Hay que ver:
-    # Si es otra operación hay que llamar la función recursivamente en cada pedazo
-    # 1. si es cadena
-    # 2. si es otra operación. Para esto, hay que regresar error o algo así cuando no se encuentre
-def crear_operacion(transcript):
-    '''
-
-    Toma el transcript de una operación binaria y la traduce a código de Python.
-    Para traducir las variables que se usan en la operación binaria busca 
-    si son cadenas o sólo menciones de variables usando las funciones
-    crear_cadena y crear_var_existente
-
-    Parametros
-    ----------
-    transcript: str
-        La intruccion de voz en texto ya en minúsculas.
-
-
-    Regresa
-    ---------
-    output: str
-        Cadena con el código en python
-    
-    Ejemplo
-    --------
-    crear_operacion('variable India producto cadena guión cadena')
-    >> i*'-'
-    '''
-    global dict_operaciones
-    
-
-    try:
-        antes_op,op,desp_op=encontrar_palabras(transcript,dict_operaciones.keys())
-    except:
-        return '' 
-
-    # Buscamos la información en la cadena detrás del operador
-    cadena_izq=crear_var_existente(antes_op)
-    try:
-        cadena_izq+=f'{crear_cadena(antes_op)[1]}'
-    except:
-        cadena_izq+=''
-        
-    if len(cadena_izq)==0:
-        nombre_var=antes_op.split(' ')[-1]
-        if dict_numeros.get(nombre_var,False):
-            nombre_var=dict_numeros[nombre_var]
-        cadena_izq+=str(nombre_var)
-        
-    # Buscamos la información en la cadena después del operador
-    cadena_der=crear_var_existente(desp_op)
-    try:
-        cadena_der+=f'{crear_cadena(desp_op)[1]}'
-    except:
-        cadena_der+=''
-    
-    if len(cadena_der)==0:
-        nombre_var=desp_op.split(' ')[0]
-        if dict_numeros.get(nombre_var,False):
-            nombre_var=dict_numeros[nombre_var]
-        if diccionario_fonetico.get(nombre_var,False):
-            nombre_var=diccionario_fonetico[nombre_var]
-        cadena_der+=str(nombre_var)
-
-                
-    return f'{cadena_izq} {dict_operaciones[op]} {cadena_der}'
-
-
-def crear_llamada(transcript):
-    """
-    Toma el transcript de la llamada de una función y la convierte en código de Python
-        Hace uso de las funciones que detectan operaciones, variables y comillas
-        ,para cada argumento de la función
-
-    Parametros
-    ----------
-    transcript: str
-        La intruccion de voz en texto ya en minúsculas.
-
-
-    Regresa
-    ---------
-    output: str
-        Cadena con el código en python
-    
-    Ejemplo
-    --------
-    crear_llamada(ejecuta print con argumentos variable India producto cadena guión cadena 
-                    coma cadena hola cadena')
-    >> print(i*'-','hola')
-    
-    """
-    global bloque
-    global indentacion
-
-    bloque='llamada'
-    try:
-        antes_ej,ej,desp_ej=encontrar_palabras(transcript,['ejecuta'])
-    except:
-        return ''
-    funcion_nombre=desp_ej.split(' ')[0]
-    # Aquí tal vez valdría la pena tener un registro de las funciones previamente definidas para
-    # poder buscar en un directorio con Jaccard y no aproximar
-
-    antes_arg,keyword,desp_arg=encontrar_palabras(desp_ej,['argumentos','parametros'])
-
-    argumentos=desp_arg.split('coma')
-    lista_cadenas=[]
-    for arg in argumentos:
-        arg=arg.strip()
-        cadena_arg=''
-        # print('arg',arg)
-        # Caso cuando es operacion
-        cadena_op=crear_operacion(arg)
-        cadena_var=crear_var_existente(arg)
-        cadena_cadena=crear_cadena(arg)
-        if len(cadena_op)!=0:
-            lista_cadenas.append(cadena_op)
-        elif len(cadena_var)!=0:
-            lista_cadenas.append(cadena_var)
-        elif len(cadena_cadena)!=0:
-            lista_cadenas.append(cadena_cadena[1])
-        else:
-            nombre_var=arg
-            if dict_numeros.get(nombre_var,False):
-                nombre_var=str(dict_numeros[nombre_var])
-                
-            lista_cadenas.append(nombre_var)
-
-        # Caso cuando es variable
-    
-    cadena_final=','.join(lista_cadenas)
-    cadena=f'{funcion_nombre}({cadena_final})<br>'+'&emsp;'*indentacion+'|'
-
-    return cadena
-
-def crear_regresa(transcript):
-    antes_reg,reg,desp_reg=encontrar_palabras(transcript,['regresa'])
-
-    arg=desp_reg.strip()
-    cadena_arg=''
-
-    # Si es llamada
-    cadena_llamada=crear_llamada(arg)
-    # Caso cuando es operacion
-    cadena_op=crear_operacion(arg)
-    cadena_var=crear_var_existente(arg)
-    cadena_cadena=crear_cadena(arg)
-    
-    cadena_final=''
-    if len(cadena_llamada)!=0:
-        cadena_final+=cadena_llamada[:-2]
-    elif len(cadena_op)!=0:
-        cadena_final+=cadena_op
-    elif len(cadena_var)!=0:
-        cadena_final+=cadena_var
-    elif len(cadena_cadena)!=0:
-        cadena_final+=cadena_cadena[1]
-    else:
-        nombre_var=arg
-        if dict_numeros.get(nombre_var,False):
-            nombre_var=str(dict_numeros[nombre_var])
-            
-        cadena_final+=nombre_var
-    global indentacion
-    indentacion-=1    
-    return f'<span style="color: #AA22FF; font-weight: bold">return</span> {cadena_final}<br>'+'&emsp;'*indentacion+'|'
-
-
-def crear_variable(instruccion):
-    """
-    Estructura:
-    definir variable con nombre [nombre_variable] igual a /*objeto_basico* valor/ 
-
-    Parametros
-    ----------
-    instrucion: str
-        La intruccion de voz en texto.
-
-    Regresa
-    ---------
-    output: str
-        Codigo generado
-    recomendacion: str
-        Una sugerencia o fallo
-
-    Testing
-    -------
-    >>> definir variable con nombre india igual a numero uno
-    >>> definir variable con nombre i igual a numero 1 (int)
-    >>> definir variable con nombre i igual a flotante tres punto cinco (float) 
-    >>> definir variable con nombre i igual a cadena hola (string) 
-    >>> definir variable con nombre i igual a lista/dic (string)   
-    """     
-    global indentacion
-    global bloque
-
-    bloque='variable'
-
-    # pivote que ayuda a definir el nombre de la variable
-    before_keyword, keyword, after_keyword = instruccion.partition('nombre')
-    after_keyword_list = after_keyword.strip().split(' ')
-    # [india igual a numero uno]
-    name_variable = after_keyword_list[0]
-    
-    # Como sabemos que despues del nombre va seguido de "igual a"
-    tipo_dato = after_keyword_list[3]        
-    #print(after_keyword_list[4:]) -> lista
-    valor = tipos_datos[tipo_dato](after_keyword_list[4:])        
-    
-    # Verificamos si es una palabra fonetica
-    if diccionario_fonetico.get(name_variable,False):
-        name_variable=diccionario_fonetico[name_variable] 
-
-    codigo_generado = f'{name_variable} = {valor}<br>'+ '&emsp;' * indentacion + '|'
-    return codigo_generado
-
-
-def asignar_variable(instruccion):
-    """    
-    Asigna una variable (eg. indio = indio + 1)
-
-    Parametros
-    ----------
-    instrucion: str
-        La intruccion de voz en texto.
-
-    Regresa
-    ---------
-    output: str
-        Codigo generado (indio = indio + 1)
-    
-    Testing
-    --------
-    >>>'asignar variable india con india suma uno',
-    >>>'asignar variable contador con contador menos uno',
-    >>>'asignar variable contador con alfa',
-    >>>'asignar variable india con india',
-    
-    """ 
-    global bloque
-    bloque = "asignar"
-   
-    before_keyword, keyword, after_keyword = instruccion.partition('variable')
-    after_keyword_list = after_keyword.strip().split(' ')
-    name_variable = after_keyword_list[0]
-    start = after_keyword_list.index('con') + 1
-    operacion = after_keyword_list[start:]
-    if len(operacion) != 1:
-        operacion_str = crear_operacion(keyword + ' ' + ' '.join(operacion))
-    else:
-        operacion_str = operacion[0]
-        # Verificamos si es una palabra fonetica para lado derecho de la 
-        # asignacion
-        if diccionario_fonetico.get(operacion_str,False):
-            operacion_str=diccionario_fonetico[operacion_str] 
-
-    # Verificamos si es una palabra fonetica
-    if diccionario_fonetico.get(name_variable,False):
-        name_variable=diccionario_fonetico[name_variable] 
-
-    codigo_generado = f'{name_variable} = {operacion_str}<br>'+ '&emsp;' * indentacion + '|'
-    return codigo_generado
-
-
-def crear_for(instruccion):
-    """
-    Crea el template de la estructura de un ciclo for.
-
-    Parámetros
-    ----------
-    instrucción: str
-        La intrucción de voz en texto.
-
-    Regresa
-    ---------
-    output: str
-        Estructura del ciclo for
-    recomendacion: str
-        Una sugerencia o error
-    """
-    global bloque 
-    global indentacion
-    global recomendacion
-
-    bloque='for'
-    vocabulario_basico = ['iteracion', 'rango']
-
-    # verificamos si la frase cumple los requisitos
-    instruccion_tokens = instruccion.strip().split(' ')
-
-    for i in vocabulario_basico:
-        try:
-            instruccion_tokens.index(i)
-        except:
-            recomendacion = 'Parece que quieres una iteración pero no reconozco tus comandos, inténtalo de nuevo'
-            return f'', recomendacion
-
-    # guarda los avisos o recomendaciones que el programa te hace
-    recomendacion = ''
-
-    # guarda la línea de código
-    output = ''
-    
-    # pivote que ayuda a definir el rango e iterador
-    before_keyword, keyword, after_keyword = instruccion.partition('iteracion')
-
-    if after_keyword.strip().split(' ')[1] in diccionario_fonetico:
-        iterador = diccionario_fonetico[after_keyword.strip().split(' ')[1]]
-
-    else:
-        iterador = after_keyword.strip().split(' ')[1]
-
-    before_keyword, keyword, after_keyword = instruccion.partition('rango')
-
-    limites = []
-
-
-    for i, item in enumerate(after_keyword.strip().split(' ')):
-        try:
-            limites.append(dict_numeros[item])
-        except:
-            continue
-
-    if len(limites) == 0:
-        for i, item in enumerate(after_keyword.strip().split(' ')):
-            try:
-                limites.append(diccionario_fonetico[item])
-            except:
-                continue
-    
-    indentacion += 1
-
-    if len(limites) == 0:
-        return f''
-
-    elif len(limites) == 1:
-        return f'<span style="color: #008000; font-weight: bold">for</span> {iterador} in <span style="color: #0066bb; font-weight: bold">range</span>({limites[-1]}):<br>' + '&emsp;' * indentacion + '|'
-
-    elif len(limites) == 2:
-        return f'<span style="color: #008000; font-weight: bold">for</span> {iterador} in <span style="color: #0066bb; font-weight: bold">range</span>({limites[0]}, {limites[1]}):<br>' + '&emsp;' * indentacion + '|'
-
-    elif len(limites) >= 2:
-        recomendacion = 'Me dictaste más de un número en el rango pero tomé los dos primeros'
-        return f'<span style="color: #008000; font-weight: bold">for</span> {iterador} in <span style="color: #0066bb; font-weight: bold">range</span>({limites[0]}, {limites[1]}):<br>' + '&emsp;' * indentacion + '|'
-
-def crear_comentario(instruccion):
-    """
-    Agrega el comentario de la intrucción en una línea de código
-
-    Parámetros
-    ----------
-    instrucción: str
-        La intrucción de voz en texto.
-
-    Regresa
-    ---------
-    output: str
-        Comentario
-    """
-
-    global bloque 
-    global indentacion
-
-    # guarda los avisos o recomendaciones que el programa te hace
-    recomendacion = ''
-    bloque = 'comentario'
-    # guarda la línea de código
-    output = ''
-
-    before_keyword, keyword, after_keyword = instruccion.partition('comentario')
-
-    return '<span style="color: #888888">' + '# ' + after_keyword + '</span>' + '<br>' + '&emsp;' * indentacion + '|'
-
-def fin_de_bloque(transcripcion):
-  global indentacion
-  global bloque
-  bloque='fin'
-  indentacion=indentacion-1
-  return '|'
-  
-                      
\ No newline at end of file
diff --git a/spaces/diacanFperku/AutoGPT/Assimil El Nuevo Japones Sin Esfuerzo Tomo 2 Pdf TOP.md b/spaces/diacanFperku/AutoGPT/Assimil El Nuevo Japones Sin Esfuerzo Tomo 2 Pdf TOP.md
deleted file mode 100644
index c27152394b311cebac37862fbb41416e6a2b3444..0000000000000000000000000000000000000000
--- a/spaces/diacanFperku/AutoGPT/Assimil El Nuevo Japones Sin Esfuerzo Tomo 2 Pdf TOP.md	
+++ /dev/null
@@ -1,30 +0,0 @@
-<h2>Assimil el nuevo japones sin esfuerzo tomo 2 pdf</h2><br /><p><b><b>Download File</b> >> <a href="https://gohhs.com/2uFVgS">https://gohhs.com/2uFVgS</a></b></p><br /><br />
-
-June 20, 2016 | Author: Ivete
-
-Www casinovisas1.com
-
-His 11-year-old daughter’s desperate plea to win the $1.5 million jackpot for her family will come to an end tonight. The prize is the largest lotto jackpot in the world.
-
-Ivete’s daughter is one of the 3 lotto winners who claimed the prize. The 2 others are Edith Manresa (B), 65, and Palma C. (T).
-
-She posted on Facebook, “I am still in a state of disbelief, I was really scared about the negative comments and comments to my post regarding the dream won by my cousin.
-
-All in all, I want to thank God for helping me live the dream that He has promised to me.”
-
-There is some doubt whether lotto winner Ivete really planned to use the money to build a temple in the family’s hometown of Escazu.
-
-Ivete owns a small convenience store in Montecristi, but she never told the media that she is going to open a commercial temple in the region.
-
-Ivete is a widow, and she lives with her daughter in a two-room apartment in the middle of Montecristi. Her daughter, also named Ivete, is in grade school, and she already attends school in Escazu.After two years of marriage, I have finally decided to stop referring to him as “my husband” in all posts about him and start calling him what he really is: MY BOYFRIEND! Yes, I did start with “my husband” but the story has been going on since he was born and it was more for the benefit of my family and friends than him (and for you, of course!).
-
-He will be five years old in two months. I can hardly believe it! I cannot remember a time when I didn’t have a son and now here he is.
-
-Five years ago I left a long term job to move to Australia with my new husband. I was confident that I would be able to find another job within a few months and I did. I was excited about the move, the opportunities, and the adventure. We were excited too.
-
-Then we had Baby.
-
-Six months 4fefd39f24<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/diacanFperku/AutoGPT/PRO100 V5 0 6 Full TOP Version.md b/spaces/diacanFperku/AutoGPT/PRO100 V5 0 6 Full TOP Version.md
deleted file mode 100644
index e1a72b5bd4e0e016bf57d962ae969d357ef14c04..0000000000000000000000000000000000000000
--- a/spaces/diacanFperku/AutoGPT/PRO100 V5 0 6 Full TOP Version.md	
+++ /dev/null
@@ -1,14 +0,0 @@
-<h2>PRO100 V5 0 6 Full Version</h2><br /><p><b><b>DOWNLOAD</b> &#8230;&#8230;&#8230; <a href="https://gohhs.com/2uFVa6">https://gohhs.com/2uFVa6</a></b></p><br /><br />
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diff --git a/spaces/diacanFperku/AutoGPT/PlanningPME 2013rar.md b/spaces/diacanFperku/AutoGPT/PlanningPME 2013rar.md
deleted file mode 100644
index aca54868267ac2315e6f0f2fe8cb7428baa3622b..0000000000000000000000000000000000000000
--- a/spaces/diacanFperku/AutoGPT/PlanningPME 2013rar.md	
+++ /dev/null
@@ -1,18 +0,0 @@
-
-<h1>PlanningPME 2013rar: A User-Friendly Scheduling Software for Any Business</h1>
-<p>PlanningPME is a resource planning tool that can be fully customized, boasting users among more than 5000 companies, including small and medium-sized businesses and large groups[^1^]. The solution adapts to the user's needs to manage employees' schedules efficiently. Wherever the user is, tasks can be shared and assigned in real time. The user can also organize time off and other absences. It is designed to increase visibility into a group's calendar, with dedicated integrations with Google Calendar or Excel. It is available via a free 30-day trial.</p>
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-<p>PlanningPME 2013rar is the latest version of the software, which offers some new features such as automatic notifications, PlanningPME rescue (a static version of the schedule in case connectivity is lost), and single sign on[^2^]. These features enhance the user experience and the security of the data. PlanningPME 2013rar also has a web access version that allows users to access the schedule from any device, such as Mac, Windows, Android, and iOS[^1^]. This facilitates creating a telecommuting schedule and managing remote employees.</p>
-<p>PlanningPME 2013rar is a great scheduling tool for any size company. Users have praised its user-friendliness, flexibility, and functionality. One user said: "PlanningPME is a great scheduling tool for any size company. Our company used both the client version in conjunction with webAccess for our field resources and it is the perfect tool for us. Not only is it user friendly but it gives you the ability to see what everyone is doing in a glance and is very flexible."[^2^]</p>
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diff --git a/spaces/diacanFperku/AutoGPT/Plaxis3dfoundation16cracked.md b/spaces/diacanFperku/AutoGPT/Plaxis3dfoundation16cracked.md
deleted file mode 100644
index 30b53a2dd494e8473db8609ad5000dcbd6af954c..0000000000000000000000000000000000000000
--- a/spaces/diacanFperku/AutoGPT/Plaxis3dfoundation16cracked.md
+++ /dev/null
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diff --git a/spaces/digitalxingtong/Un-Bert-Vits2/models.py b/spaces/digitalxingtong/Un-Bert-Vits2/models.py
deleted file mode 100644
index d4afe44d883691610c5903e602a3ca245fcb3a5c..0000000000000000000000000000000000000000
--- a/spaces/digitalxingtong/Un-Bert-Vits2/models.py
+++ /dev/null
@@ -1,707 +0,0 @@
-import copy
-import math
-import torch
-from torch import nn
-from torch.nn import functional as F
-
-import commons
-import modules
-import attentions
-import monotonic_align
-
-from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
-from torch.nn.utils import weight_norm, remove_weight_norm, spectral_norm
-
-from commons import init_weights, get_padding
-from text import symbols, num_tones, num_languages
-class DurationDiscriminator(nn.Module): #vits2
-  def __init__(self, in_channels, filter_channels, kernel_size, p_dropout, gin_channels=0):
-    super().__init__()
-
-    self.in_channels = in_channels
-    self.filter_channels = filter_channels
-    self.kernel_size = kernel_size
-    self.p_dropout = p_dropout
-    self.gin_channels = gin_channels
-
-    self.drop = nn.Dropout(p_dropout)
-    self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size, padding=kernel_size//2)
-    self.norm_1 = modules.LayerNorm(filter_channels)
-    self.conv_2 = nn.Conv1d(filter_channels, filter_channels, kernel_size, padding=kernel_size//2)
-    self.norm_2 = modules.LayerNorm(filter_channels)
-    self.dur_proj = nn.Conv1d(1, filter_channels, 1)
-
-    self.pre_out_conv_1 = nn.Conv1d(2*filter_channels, filter_channels, kernel_size, padding=kernel_size//2)
-    self.pre_out_norm_1 = modules.LayerNorm(filter_channels)
-    self.pre_out_conv_2 = nn.Conv1d(filter_channels, filter_channels, kernel_size, padding=kernel_size//2)
-    self.pre_out_norm_2 = modules.LayerNorm(filter_channels)
-
-    if gin_channels != 0:
-       self.cond = nn.Conv1d(gin_channels, in_channels, 1)
-
-    self.output_layer = nn.Sequential(
-        nn.Linear(filter_channels, 1), 
-        nn.Sigmoid() 
-    )
-
-  def forward_probability(self, x, x_mask, dur, g=None):
-    dur = self.dur_proj(dur)
-    x = torch.cat([x, dur], dim=1)
-    x = self.pre_out_conv_1(x * x_mask)
-    x = torch.relu(x)
-    x = self.pre_out_norm_1(x)
-    x = self.drop(x)
-    x = self.pre_out_conv_2(x * x_mask)
-    x = torch.relu(x)
-    x = self.pre_out_norm_2(x)
-    x = self.drop(x)
-    x = x * x_mask
-    x = x.transpose(1, 2)
-    output_prob = self.output_layer(x)
-    return output_prob
-
-  def forward(self, x, x_mask, dur_r, dur_hat, g=None):
-    x = torch.detach(x)
-    if g is not None:
-       g = torch.detach(g)
-       x = x + self.cond(g)
-    x = self.conv_1(x * x_mask)
-    x = torch.relu(x)
-    x = self.norm_1(x)
-    x = self.drop(x)
-    x = self.conv_2(x * x_mask)
-    x = torch.relu(x)
-    x = self.norm_2(x)
-    x = self.drop(x)
-
-    output_probs = []
-    for dur in [dur_r, dur_hat]:
-      output_prob = self.forward_probability(x, x_mask, dur, g)
-      output_probs.append(output_prob)
-
-    return output_probs
-
-class TransformerCouplingBlock(nn.Module):
-    def __init__(self,
-                 channels,
-                 hidden_channels,
-                 filter_channels,
-                 n_heads,
-                 n_layers,
-                 kernel_size,
-                 p_dropout,
-                 n_flows=4,
-                 gin_channels=0,
-                 share_parameter=False
-                 ):
-
-        super().__init__()
-        self.channels = channels
-        self.hidden_channels = hidden_channels
-        self.kernel_size = kernel_size
-        self.n_layers = n_layers
-        self.n_flows = n_flows
-        self.gin_channels = gin_channels
-
-        self.flows = nn.ModuleList()
-
-        self.wn = attentions.FFT(hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout, isflow = True, gin_channels = self.gin_channels) if share_parameter else None
-
-        for i in range(n_flows):
-            self.flows.append(
-                modules.TransformerCouplingLayer(channels, hidden_channels, kernel_size, n_layers, n_heads, p_dropout, filter_channels, mean_only=True, wn_sharing_parameter=self.wn, gin_channels = self.gin_channels))
-            self.flows.append(modules.Flip())
-
-    def forward(self, x, x_mask, g=None, reverse=False):
-        if not reverse:
-            for flow in self.flows:
-                x, _ = flow(x, x_mask, g=g, reverse=reverse)
-        else:
-            for flow in reversed(self.flows):
-                x = flow(x, x_mask, g=g, reverse=reverse)
-        return x
-
-class StochasticDurationPredictor(nn.Module):
-    def __init__(self, in_channels, filter_channels, kernel_size, p_dropout, n_flows=4, gin_channels=0):
-        super().__init__()
-        filter_channels = in_channels  # it needs to be removed from future version.
-        self.in_channels = in_channels
-        self.filter_channels = filter_channels
-        self.kernel_size = kernel_size
-        self.p_dropout = p_dropout
-        self.n_flows = n_flows
-        self.gin_channels = gin_channels
-
-        self.log_flow = modules.Log()
-        self.flows = nn.ModuleList()
-        self.flows.append(modules.ElementwiseAffine(2))
-        for i in range(n_flows):
-            self.flows.append(modules.ConvFlow(2, filter_channels, kernel_size, n_layers=3))
-            self.flows.append(modules.Flip())
-
-        self.post_pre = nn.Conv1d(1, filter_channels, 1)
-        self.post_proj = nn.Conv1d(filter_channels, filter_channels, 1)
-        self.post_convs = modules.DDSConv(filter_channels, kernel_size, n_layers=3, p_dropout=p_dropout)
-        self.post_flows = nn.ModuleList()
-        self.post_flows.append(modules.ElementwiseAffine(2))
-        for i in range(4):
-            self.post_flows.append(modules.ConvFlow(2, filter_channels, kernel_size, n_layers=3))
-            self.post_flows.append(modules.Flip())
-
-        self.pre = nn.Conv1d(in_channels, filter_channels, 1)
-        self.proj = nn.Conv1d(filter_channels, filter_channels, 1)
-        self.convs = modules.DDSConv(filter_channels, kernel_size, n_layers=3, p_dropout=p_dropout)
-        if gin_channels != 0:
-            self.cond = nn.Conv1d(gin_channels, filter_channels, 1)
-
-    def forward(self, x, x_mask, w=None, g=None, reverse=False, noise_scale=1.0):
-        x = torch.detach(x)
-        x = self.pre(x)
-        if g is not None:
-            g = torch.detach(g)
-            x = x + self.cond(g)
-        x = self.convs(x, x_mask)
-        x = self.proj(x) * x_mask
-
-        if not reverse:
-            flows = self.flows
-            assert w is not None
-
-            logdet_tot_q = 0
-            h_w = self.post_pre(w)
-            h_w = self.post_convs(h_w, x_mask)
-            h_w = self.post_proj(h_w) * x_mask
-            e_q = torch.randn(w.size(0), 2, w.size(2)).to(device=x.device, dtype=x.dtype) * x_mask
-            z_q = e_q
-            for flow in self.post_flows:
-                z_q, logdet_q = flow(z_q, x_mask, g=(x + h_w))
-                logdet_tot_q += logdet_q
-            z_u, z1 = torch.split(z_q, [1, 1], 1)
-            u = torch.sigmoid(z_u) * x_mask
-            z0 = (w - u) * x_mask
-            logdet_tot_q += torch.sum((F.logsigmoid(z_u) + F.logsigmoid(-z_u)) * x_mask, [1, 2])
-            logq = torch.sum(-0.5 * (math.log(2 * math.pi) + (e_q ** 2)) * x_mask, [1, 2]) - logdet_tot_q
-
-            logdet_tot = 0
-            z0, logdet = self.log_flow(z0, x_mask)
-            logdet_tot += logdet
-            z = torch.cat([z0, z1], 1)
-            for flow in flows:
-                z, logdet = flow(z, x_mask, g=x, reverse=reverse)
-                logdet_tot = logdet_tot + logdet
-            nll = torch.sum(0.5 * (math.log(2 * math.pi) + (z ** 2)) * x_mask, [1, 2]) - logdet_tot
-            return nll + logq  # [b]
-        else:
-            flows = list(reversed(self.flows))
-            flows = flows[:-2] + [flows[-1]]  # remove a useless vflow
-            z = torch.randn(x.size(0), 2, x.size(2)).to(device=x.device, dtype=x.dtype) * noise_scale
-            for flow in flows:
-                z = flow(z, x_mask, g=x, reverse=reverse)
-            z0, z1 = torch.split(z, [1, 1], 1)
-            logw = z0
-            return logw
-
-
-class DurationPredictor(nn.Module):
-    def __init__(self, in_channels, filter_channels, kernel_size, p_dropout, gin_channels=0):
-        super().__init__()
-
-        self.in_channels = in_channels
-        self.filter_channels = filter_channels
-        self.kernel_size = kernel_size
-        self.p_dropout = p_dropout
-        self.gin_channels = gin_channels
-
-        self.drop = nn.Dropout(p_dropout)
-        self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size, padding=kernel_size // 2)
-        self.norm_1 = modules.LayerNorm(filter_channels)
-        self.conv_2 = nn.Conv1d(filter_channels, filter_channels, kernel_size, padding=kernel_size // 2)
-        self.norm_2 = modules.LayerNorm(filter_channels)
-        self.proj = nn.Conv1d(filter_channels, 1, 1)
-
-        if gin_channels != 0:
-            self.cond = nn.Conv1d(gin_channels, in_channels, 1)
-
-    def forward(self, x, x_mask, g=None):
-        x = torch.detach(x)
-        if g is not None:
-            g = torch.detach(g)
-            x = x + self.cond(g)
-        x = self.conv_1(x * x_mask)
-        x = torch.relu(x)
-        x = self.norm_1(x)
-        x = self.drop(x)
-        x = self.conv_2(x * x_mask)
-        x = torch.relu(x)
-        x = self.norm_2(x)
-        x = self.drop(x)
-        x = self.proj(x * x_mask)
-        return x * x_mask
-
-
-class TextEncoder(nn.Module):
-    def __init__(self,
-                 n_vocab,
-                 out_channels,
-                 hidden_channels,
-                 filter_channels,
-                 n_heads,
-                 n_layers,
-                 kernel_size,
-                 p_dropout,
-                 gin_channels=0):
-        super().__init__()
-        self.n_vocab = n_vocab
-        self.out_channels = out_channels
-        self.hidden_channels = hidden_channels
-        self.filter_channels = filter_channels
-        self.n_heads = n_heads
-        self.n_layers = n_layers
-        self.kernel_size = kernel_size
-        self.p_dropout = p_dropout
-        self.gin_channels = gin_channels
-        self.emb = nn.Embedding(len(symbols), hidden_channels)
-        nn.init.normal_(self.emb.weight, 0.0, hidden_channels ** -0.5)
-        self.tone_emb = nn.Embedding(num_tones, hidden_channels)
-        nn.init.normal_(self.tone_emb.weight, 0.0, hidden_channels ** -0.5)
-        self.language_emb = nn.Embedding(num_languages, hidden_channels)
-        nn.init.normal_(self.language_emb.weight, 0.0, hidden_channels ** -0.5)
-        self.bert_proj = nn.Conv1d(1024, hidden_channels, 1)
-
-        self.encoder = attentions.Encoder(
-            hidden_channels,
-            filter_channels,
-            n_heads,
-            n_layers,
-            kernel_size,
-            p_dropout,
-            gin_channels=self.gin_channels)
-        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
-
-    def forward(self, x, x_lengths, tone, language, bert, g=None):
-        x = (self.emb(x)+ self.tone_emb(tone)+ self.language_emb(language)+self.bert_proj(bert).transpose(1,2)) * math.sqrt(self.hidden_channels)  # [b, t, h]
-        x = torch.transpose(x, 1, -1)  # [b, h, t]
-        x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(x.dtype)
-
-        x = self.encoder(x * x_mask, x_mask, g=g)
-        stats = self.proj(x) * x_mask
-
-        m, logs = torch.split(stats, self.out_channels, dim=1)
-        return x, m, logs, x_mask
-
-
-class ResidualCouplingBlock(nn.Module):
-    def __init__(self,
-                 channels,
-                 hidden_channels,
-                 kernel_size,
-                 dilation_rate,
-                 n_layers,
-                 n_flows=4,
-                 gin_channels=0):
-        super().__init__()
-        self.channels = channels
-        self.hidden_channels = hidden_channels
-        self.kernel_size = kernel_size
-        self.dilation_rate = dilation_rate
-        self.n_layers = n_layers
-        self.n_flows = n_flows
-        self.gin_channels = gin_channels
-
-        self.flows = nn.ModuleList()
-        for i in range(n_flows):
-            self.flows.append(
-                modules.ResidualCouplingLayer(channels, hidden_channels, kernel_size, dilation_rate, n_layers,
-                                              gin_channels=gin_channels, mean_only=True))
-            self.flows.append(modules.Flip())
-
-    def forward(self, x, x_mask, g=None, reverse=False):
-        if not reverse:
-            for flow in self.flows:
-                x, _ = flow(x, x_mask, g=g, reverse=reverse)
-        else:
-            for flow in reversed(self.flows):
-                x = flow(x, x_mask, g=g, reverse=reverse)
-        return x
-
-
-class PosteriorEncoder(nn.Module):
-    def __init__(self,
-                 in_channels,
-                 out_channels,
-                 hidden_channels,
-                 kernel_size,
-                 dilation_rate,
-                 n_layers,
-                 gin_channels=0):
-        super().__init__()
-        self.in_channels = in_channels
-        self.out_channels = out_channels
-        self.hidden_channels = hidden_channels
-        self.kernel_size = kernel_size
-        self.dilation_rate = dilation_rate
-        self.n_layers = n_layers
-        self.gin_channels = gin_channels
-
-        self.pre = nn.Conv1d(in_channels, hidden_channels, 1)
-        self.enc = modules.WN(hidden_channels, kernel_size, dilation_rate, n_layers, gin_channels=gin_channels)
-        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
-
-    def forward(self, x, x_lengths, g=None):
-        x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(x.dtype)
-        x = self.pre(x) * x_mask
-        x = self.enc(x, x_mask, g=g)
-        stats = self.proj(x) * x_mask
-        m, logs = torch.split(stats, self.out_channels, dim=1)
-        z = (m + torch.randn_like(m) * torch.exp(logs)) * x_mask
-        return z, m, logs, x_mask
-
-
-class Generator(torch.nn.Module):
-    def __init__(self, initial_channel, resblock, resblock_kernel_sizes, resblock_dilation_sizes, upsample_rates,
-                 upsample_initial_channel, upsample_kernel_sizes, gin_channels=0):
-        super(Generator, self).__init__()
-        self.num_kernels = len(resblock_kernel_sizes)
-        self.num_upsamples = len(upsample_rates)
-        self.conv_pre = Conv1d(initial_channel, upsample_initial_channel, 7, 1, padding=3)
-        resblock = modules.ResBlock1 if resblock == '1' else modules.ResBlock2
-
-        self.ups = nn.ModuleList()
-        for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
-            self.ups.append(weight_norm(
-                ConvTranspose1d(upsample_initial_channel // (2 ** i), upsample_initial_channel // (2 ** (i + 1)),
-                                k, u, padding=(k - u) // 2)))
-
-        self.resblocks = nn.ModuleList()
-        for i in range(len(self.ups)):
-            ch = upsample_initial_channel // (2 ** (i + 1))
-            for j, (k, d) in enumerate(zip(resblock_kernel_sizes, resblock_dilation_sizes)):
-                self.resblocks.append(resblock(ch, k, d))
-
-        self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
-        self.ups.apply(init_weights)
-
-        if gin_channels != 0:
-            self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
-
-    def forward(self, x, g=None):
-        x = self.conv_pre(x)
-        if g is not None:
-            x = x + self.cond(g)
-
-        for i in range(self.num_upsamples):
-            x = F.leaky_relu(x, modules.LRELU_SLOPE)
-            x = self.ups[i](x)
-            xs = None
-            for j in range(self.num_kernels):
-                if xs is None:
-                    xs = self.resblocks[i * self.num_kernels + j](x)
-                else:
-                    xs += self.resblocks[i * self.num_kernels + j](x)
-            x = xs / self.num_kernels
-        x = F.leaky_relu(x)
-        x = self.conv_post(x)
-        x = torch.tanh(x)
-
-        return x
-
-    def remove_weight_norm(self):
-        print('Removing weight norm...')
-        for l in self.ups:
-            remove_weight_norm(l)
-        for l in self.resblocks:
-            l.remove_weight_norm()
-
-
-class DiscriminatorP(torch.nn.Module):
-    def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=False):
-        super(DiscriminatorP, self).__init__()
-        self.period = period
-        self.use_spectral_norm = use_spectral_norm
-        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
-        self.convs = nn.ModuleList([
-            norm_f(Conv2d(1, 32, (kernel_size, 1), (stride, 1), padding=(get_padding(kernel_size, 1), 0))),
-            norm_f(Conv2d(32, 128, (kernel_size, 1), (stride, 1), padding=(get_padding(kernel_size, 1), 0))),
-            norm_f(Conv2d(128, 512, (kernel_size, 1), (stride, 1), padding=(get_padding(kernel_size, 1), 0))),
-            norm_f(Conv2d(512, 1024, (kernel_size, 1), (stride, 1), padding=(get_padding(kernel_size, 1), 0))),
-            norm_f(Conv2d(1024, 1024, (kernel_size, 1), 1, padding=(get_padding(kernel_size, 1), 0))),
-        ])
-        self.conv_post = norm_f(Conv2d(1024, 1, (3, 1), 1, padding=(1, 0)))
-
-    def forward(self, x):
-        fmap = []
-
-        # 1d to 2d
-        b, c, t = x.shape
-        if t % self.period != 0:  # pad first
-            n_pad = self.period - (t % self.period)
-            x = F.pad(x, (0, n_pad), "reflect")
-            t = t + n_pad
-        x = x.view(b, c, t // self.period, self.period)
-
-        for l in self.convs:
-            x = l(x)
-            x = F.leaky_relu(x, modules.LRELU_SLOPE)
-            fmap.append(x)
-        x = self.conv_post(x)
-        fmap.append(x)
-        x = torch.flatten(x, 1, -1)
-
-        return x, fmap
-
-
-class DiscriminatorS(torch.nn.Module):
-    def __init__(self, use_spectral_norm=False):
-        super(DiscriminatorS, self).__init__()
-        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
-        self.convs = nn.ModuleList([
-            norm_f(Conv1d(1, 16, 15, 1, padding=7)),
-            norm_f(Conv1d(16, 64, 41, 4, groups=4, padding=20)),
-            norm_f(Conv1d(64, 256, 41, 4, groups=16, padding=20)),
-            norm_f(Conv1d(256, 1024, 41, 4, groups=64, padding=20)),
-            norm_f(Conv1d(1024, 1024, 41, 4, groups=256, padding=20)),
-            norm_f(Conv1d(1024, 1024, 5, 1, padding=2)),
-        ])
-        self.conv_post = norm_f(Conv1d(1024, 1, 3, 1, padding=1))
-
-    def forward(self, x):
-        fmap = []
-
-        for l in self.convs:
-            x = l(x)
-            x = F.leaky_relu(x, modules.LRELU_SLOPE)
-            fmap.append(x)
-        x = self.conv_post(x)
-        fmap.append(x)
-        x = torch.flatten(x, 1, -1)
-
-        return x, fmap
-
-
-class MultiPeriodDiscriminator(torch.nn.Module):
-    def __init__(self, use_spectral_norm=False):
-        super(MultiPeriodDiscriminator, self).__init__()
-        periods = [2, 3, 5, 7, 11]
-
-        discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
-        discs = discs + [DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods]
-        self.discriminators = nn.ModuleList(discs)
-
-    def forward(self, y, y_hat):
-        y_d_rs = []
-        y_d_gs = []
-        fmap_rs = []
-        fmap_gs = []
-        for i, d in enumerate(self.discriminators):
-            y_d_r, fmap_r = d(y)
-            y_d_g, fmap_g = d(y_hat)
-            y_d_rs.append(y_d_r)
-            y_d_gs.append(y_d_g)
-            fmap_rs.append(fmap_r)
-            fmap_gs.append(fmap_g)
-
-        return y_d_rs, y_d_gs, fmap_rs, fmap_gs
-
-class ReferenceEncoder(nn.Module):
-    '''
-    inputs --- [N, Ty/r, n_mels*r]  mels
-    outputs --- [N, ref_enc_gru_size]
-    '''
-
-    def __init__(self, spec_channels, gin_channels=0):
-
-        super().__init__()
-        self.spec_channels = spec_channels
-        ref_enc_filters = [32, 32, 64, 64, 128, 128]
-        K = len(ref_enc_filters)
-        filters = [1] + ref_enc_filters
-        convs = [weight_norm(nn.Conv2d(in_channels=filters[i],
-                                       out_channels=filters[i + 1],
-                                       kernel_size=(3, 3),
-                                       stride=(2, 2),
-                                       padding=(1, 1))) for i in range(K)]
-        self.convs = nn.ModuleList(convs)
-        # self.wns = nn.ModuleList([weight_norm(num_features=ref_enc_filters[i]) for i in range(K)])
-
-        out_channels = self.calculate_channels(spec_channels, 3, 2, 1, K)
-        self.gru = nn.GRU(input_size=ref_enc_filters[-1] * out_channels,
-                          hidden_size=256 // 2,
-                          batch_first=True)
-        self.proj = nn.Linear(128, gin_channels)
-
-    def forward(self, inputs, mask=None):
-        N = inputs.size(0)
-        out = inputs.view(N, 1, -1, self.spec_channels)  # [N, 1, Ty, n_freqs]
-        for conv in self.convs:
-            out = conv(out)
-            # out = wn(out)
-            out = F.relu(out)  # [N, 128, Ty//2^K, n_mels//2^K]
-
-        out = out.transpose(1, 2)  # [N, Ty//2^K, 128, n_mels//2^K]
-        T = out.size(1)
-        N = out.size(0)
-        out = out.contiguous().view(N, T, -1)  # [N, Ty//2^K, 128*n_mels//2^K]
-
-        self.gru.flatten_parameters()
-        memory, out = self.gru(out)  # out --- [1, N, 128]
-
-        return self.proj(out.squeeze(0))
-
-    def calculate_channels(self, L, kernel_size, stride, pad, n_convs):
-        for i in range(n_convs):
-            L = (L - kernel_size + 2 * pad) // stride + 1
-        return L
-
-
-class SynthesizerTrn(nn.Module):
-    """
-  Synthesizer for Training
-  """
-
-    def __init__(self,
-                 n_vocab,
-                 spec_channels,
-                 segment_size,
-                 inter_channels,
-                 hidden_channels,
-                 filter_channels,
-                 n_heads,
-                 n_layers,
-                 kernel_size,
-                 p_dropout,
-                 resblock,
-                 resblock_kernel_sizes,
-                 resblock_dilation_sizes,
-                 upsample_rates,
-                 upsample_initial_channel,
-                 upsample_kernel_sizes,
-                 n_speakers=256,
-                 gin_channels=256,
-                 use_sdp=True,
-                 n_flow_layer = 4,
-                 n_layers_trans_flow = 3,
-                 flow_share_parameter = False,
-                 use_transformer_flow = True,
-                 **kwargs):
-
-        super().__init__()
-        self.n_vocab = n_vocab
-        self.spec_channels = spec_channels
-        self.inter_channels = inter_channels
-        self.hidden_channels = hidden_channels
-        self.filter_channels = filter_channels
-        self.n_heads = n_heads
-        self.n_layers = n_layers
-        self.kernel_size = kernel_size
-        self.p_dropout = p_dropout
-        self.resblock = resblock
-        self.resblock_kernel_sizes = resblock_kernel_sizes
-        self.resblock_dilation_sizes = resblock_dilation_sizes
-        self.upsample_rates = upsample_rates
-        self.upsample_initial_channel = upsample_initial_channel
-        self.upsample_kernel_sizes = upsample_kernel_sizes
-        self.segment_size = segment_size
-        self.n_speakers = n_speakers
-        self.gin_channels = gin_channels
-        self.n_layers_trans_flow = n_layers_trans_flow
-        self.use_spk_conditioned_encoder = kwargs.get("use_spk_conditioned_encoder", True)
-        self.use_sdp = use_sdp
-        self.use_noise_scaled_mas = kwargs.get("use_noise_scaled_mas", False)
-        self.mas_noise_scale_initial = kwargs.get("mas_noise_scale_initial", 0.01)
-        self.noise_scale_delta = kwargs.get("noise_scale_delta", 2e-6)
-        self.current_mas_noise_scale = self.mas_noise_scale_initial
-        if self.use_spk_conditioned_encoder and gin_channels > 0:
-            self.enc_gin_channels = gin_channels
-        self.enc_p = TextEncoder(n_vocab,
-                                 inter_channels,
-                                 hidden_channels,
-                                 filter_channels,
-                                 n_heads,
-                                 n_layers,
-                                 kernel_size,
-                                 p_dropout,
-                                 gin_channels=self.enc_gin_channels)
-        self.dec = Generator(inter_channels, resblock, resblock_kernel_sizes, resblock_dilation_sizes, upsample_rates,
-                             upsample_initial_channel, upsample_kernel_sizes, gin_channels=gin_channels)
-        self.enc_q = PosteriorEncoder(spec_channels, inter_channels, hidden_channels, 5, 1, 16,
-                                      gin_channels=gin_channels)
-        if use_transformer_flow:
-            self.flow = TransformerCouplingBlock(inter_channels, hidden_channels, filter_channels, n_heads, n_layers_trans_flow, 5, p_dropout, n_flow_layer, gin_channels=gin_channels,share_parameter= flow_share_parameter)
-        else:
-            self.flow = ResidualCouplingBlock(inter_channels, hidden_channels, 5, 1, n_flow_layer, gin_channels=gin_channels)
-        self.sdp = StochasticDurationPredictor(hidden_channels, 192, 3, 0.5, 4, gin_channels=gin_channels)
-        self.dp = DurationPredictor(hidden_channels, 256, 3, 0.5, gin_channels=gin_channels)
-        
-        if n_speakers >= 1:
-            self.emb_g = nn.Embedding(n_speakers, gin_channels)
-        else:
-            self.ref_enc = ReferenceEncoder(spec_channels, gin_channels)
-
-    def forward(self, x, x_lengths, y, y_lengths, sid, tone, language, bert):
-        if self.n_speakers > 0:
-            g = self.emb_g(sid).unsqueeze(-1)  # [b, h, 1]
-        else:
-            g = self.ref_enc(y.transpose(1,2)).unsqueeze(-1)
-        x, m_p, logs_p, x_mask = self.enc_p(x, x_lengths, tone, language, bert,g=g)
-        z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
-        z_p = self.flow(z, y_mask, g=g)
-
-        with torch.no_grad():
-            # negative cross-entropy
-            s_p_sq_r = torch.exp(-2 * logs_p)  # [b, d, t]
-            neg_cent1 = torch.sum(-0.5 * math.log(2 * math.pi) - logs_p, [1], keepdim=True)  # [b, 1, t_s]
-            neg_cent2 = torch.matmul(-0.5 * (z_p ** 2).transpose(1, 2),
-                                     s_p_sq_r)  # [b, t_t, d] x [b, d, t_s] = [b, t_t, t_s]
-            neg_cent3 = torch.matmul(z_p.transpose(1, 2), (m_p * s_p_sq_r))  # [b, t_t, d] x [b, d, t_s] = [b, t_t, t_s]
-            neg_cent4 = torch.sum(-0.5 * (m_p ** 2) * s_p_sq_r, [1], keepdim=True)  # [b, 1, t_s]
-            neg_cent = neg_cent1 + neg_cent2 + neg_cent3 + neg_cent4
-            if self.use_noise_scaled_mas:
-               epsilon = torch.std(neg_cent) * torch.randn_like(neg_cent) * self.current_mas_noise_scale
-               neg_cent = neg_cent + epsilon
-
-            attn_mask = torch.unsqueeze(x_mask, 2) * torch.unsqueeze(y_mask, -1)
-            attn = monotonic_align.maximum_path(neg_cent, attn_mask.squeeze(1)).unsqueeze(1).detach()
-
-        w = attn.sum(2)
-
-        l_length_sdp = self.sdp(x, x_mask, w, g=g)
-        l_length_sdp = l_length_sdp / torch.sum(x_mask)
-        
-        logw_ = torch.log(w + 1e-6) * x_mask
-        logw = self.dp(x, x_mask, g=g)
-        l_length_dp = torch.sum((logw - logw_) ** 2, [1, 2]) / torch.sum(x_mask)  # for averaging
-
-        l_length = l_length_dp + l_length_sdp
-
-        # expand prior
-        m_p = torch.matmul(attn.squeeze(1), m_p.transpose(1, 2)).transpose(1, 2)
-        logs_p = torch.matmul(attn.squeeze(1), logs_p.transpose(1, 2)).transpose(1, 2)
-
-        z_slice, ids_slice = commons.rand_slice_segments(z, y_lengths, self.segment_size)
-        o = self.dec(z_slice, g=g)
-        return o, l_length, attn, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q), (x, logw, logw_)
-      
-    def infer(self, x, x_lengths, sid, tone, language, bert, noise_scale=.667, length_scale=1, noise_scale_w=0.8, max_len=None, sdp_ratio=0,y=None):
-        #x, m_p, logs_p, x_mask = self.enc_p(x, x_lengths, tone, language, bert)
-        # g = self.gst(y)
-        if self.n_speakers > 0:
-            g = self.emb_g(sid).unsqueeze(-1)  # [b, h, 1]
-        else:
-            g = self.ref_enc(y.transpose(1,2)).unsqueeze(-1)
-        x, m_p, logs_p, x_mask = self.enc_p(x, x_lengths, tone, language, bert,g=g)
-        logw = self.sdp(x, x_mask, g=g, reverse=True, noise_scale=noise_scale_w) * (sdp_ratio) + self.dp(x, x_mask, g=g) * (1 - sdp_ratio)
-        w = torch.exp(logw) * x_mask * length_scale
-        w_ceil = torch.ceil(w)
-        y_lengths = torch.clamp_min(torch.sum(w_ceil, [1, 2]), 1).long()
-        y_mask = torch.unsqueeze(commons.sequence_mask(y_lengths, None), 1).to(x_mask.dtype)
-        attn_mask = torch.unsqueeze(x_mask, 2) * torch.unsqueeze(y_mask, -1)
-        attn = commons.generate_path(w_ceil, attn_mask)
-
-        m_p = torch.matmul(attn.squeeze(1), m_p.transpose(1, 2)).transpose(1, 2)  # [b, t', t], [b, t, d] -> [b, d, t']
-        logs_p = torch.matmul(attn.squeeze(1), logs_p.transpose(1, 2)).transpose(1,
-                                                                                 2)  # [b, t', t], [b, t, d] -> [b, d, t']
-
-        z_p = m_p + torch.randn_like(m_p) * torch.exp(logs_p) * noise_scale
-        z = self.flow(z_p, y_mask, g=g, reverse=True)
-        o = self.dec((z * y_mask)[:, :, :max_len], g=g)
-        return o, attn, y_mask, (z, z_p, m_p, logs_p)
diff --git a/spaces/divyahansg/text-generation-webui-space/modules/GPTQ_loader.py b/spaces/divyahansg/text-generation-webui-space/modules/GPTQ_loader.py
deleted file mode 100644
index c2723490bbe214e351634ca4054f74a0b5334b28..0000000000000000000000000000000000000000
--- a/spaces/divyahansg/text-generation-webui-space/modules/GPTQ_loader.py
+++ /dev/null
@@ -1,71 +0,0 @@
-import sys
-from pathlib import Path
-
-import accelerate
-import torch
-
-import modules.shared as shared
-
-sys.path.insert(0, str(Path("repositories/GPTQ-for-LLaMa")))
-import llama
-import opt
-
-
-def load_quantized(model_name):
-    if not shared.args.gptq_model_type:
-        # Try to determine model type from model name
-        model_type = model_name.split('-')[0].lower()
-        if model_type not in ('llama', 'opt'):
-            print("Can't determine model type from model name. Please specify it manually using --gptq-model-type "
-                  "argument")
-            exit()
-    else:
-        model_type = shared.args.gptq_model_type.lower()
-
-    if model_type == 'llama':
-        load_quant = llama.load_quant
-    elif model_type == 'opt':
-        load_quant = opt.load_quant
-    else:
-        print("Unknown pre-quantized model type specified. Only 'llama' and 'opt' are supported")
-        exit()
-
-    path_to_model = Path(f'models/{model_name}')
-    if path_to_model.name.lower().startswith('llama-7b'):
-        pt_model = f'llama-7b-{shared.args.gptq_bits}bit.pt'
-    elif path_to_model.name.lower().startswith('llama-13b'):
-        pt_model = f'llama-13b-{shared.args.gptq_bits}bit.pt'
-    elif path_to_model.name.lower().startswith('llama-30b'):
-        pt_model = f'llama-30b-{shared.args.gptq_bits}bit.pt'
-    elif path_to_model.name.lower().startswith('llama-65b'):
-        pt_model = f'llama-65b-{shared.args.gptq_bits}bit.pt'
-    else:
-        pt_model = f'{model_name}-{shared.args.gptq_bits}bit.pt'
-
-    # Try to find the .pt both in models/ and in the subfolder
-    pt_path = None
-    for path in [Path(p) for p in [f"models/{pt_model}", f"{path_to_model}/{pt_model}"]]:
-        if path.exists():
-            pt_path = path
-
-    if not pt_path:
-        print(f"Could not find {pt_model}, exiting...")
-        exit()
-
-    model = load_quant(str(path_to_model), str(pt_path), shared.args.gptq_bits)
-
-    # Multiple GPUs or GPU+CPU
-    if shared.args.gpu_memory:
-        max_memory = {}
-        for i in range(len(shared.args.gpu_memory)):
-            max_memory[i] = f"{shared.args.gpu_memory[i]}GiB"
-        max_memory['cpu'] = f"{shared.args.cpu_memory or '99'}GiB"
-
-        device_map = accelerate.infer_auto_device_map(model, max_memory=max_memory, no_split_module_classes=["LLaMADecoderLayer"])
-        model = accelerate.dispatch_model(model, device_map=device_map)
-
-    # Single GPU
-    else:
-        model = model.to(torch.device('cuda:0'))
-
-    return model
diff --git a/spaces/doevent/colorizator/utils/dataset_lab.py b/spaces/doevent/colorizator/utils/dataset_lab.py
deleted file mode 100644
index 735f0d16a2d7a061e9fc205752ab51afeab88c8d..0000000000000000000000000000000000000000
--- a/spaces/doevent/colorizator/utils/dataset_lab.py
+++ /dev/null
@@ -1,37 +0,0 @@
-from __future__ import print_function, division
-import torch, os, glob
-from torch.utils.data import Dataset, DataLoader
-import numpy as np
-from PIL import Image
-import cv2
-
-
-class LabDataset(Dataset):
-
-    def __init__(self, rootdir=None, filelist=None, resize=None):
-
-        if filelist:
-            self.file_list = filelist
-        else:
-            assert os.path.exists(rootdir), "@dir:'%s' NOT exist ..."%rootdir
-            self.file_list = glob.glob(os.path.join(rootdir, '*.*'))
-            self.file_list.sort()
-        self.resize = resize
-
-    def __len__(self):
-        return len(self.file_list)
-
-    def __getitem__(self, idx):
-        bgr_img = cv2.imread(self.file_list[idx], cv2.IMREAD_COLOR)
-        if self.resize:
-            bgr_img = cv2.resize(bgr_img, (self.resize,self.resize), interpolation=cv2.INTER_CUBIC)
-        bgr_img = np.array(bgr_img / 255., np.float32)
-        lab_img = cv2.cvtColor(bgr_img, cv2.COLOR_BGR2LAB)
-        #print('--------L:', np.min(lab_img[:,:,0]), np.max(lab_img[:,:,0]))
-        #print('--------ab:', np.min(lab_img[:,:,1:3]), np.max(lab_img[:,:,1:3]))
-        lab_img = torch.from_numpy(lab_img.transpose((2, 0, 1)))
-        bgr_img = torch.from_numpy(bgr_img.transpose((2, 0, 1)))
-        gray_img = (lab_img[0:1,:,:]-50.) / 50.
-        color_map = lab_img[1:3,:,:] / 110.
-        bgr_img = bgr_img*2. - 1.
-        return {'gray': gray_img, 'color': color_map, 'BGR': bgr_img}
\ No newline at end of file
diff --git a/spaces/dorkai/text-generation-webui-main/docs/WSL-installation-guide.md b/spaces/dorkai/text-generation-webui-main/docs/WSL-installation-guide.md
deleted file mode 100644
index 7de38b114f7b0fb6e522c20520b3aadbb8161970..0000000000000000000000000000000000000000
--- a/spaces/dorkai/text-generation-webui-main/docs/WSL-installation-guide.md
+++ /dev/null
@@ -1,79 +0,0 @@
-Guide created by [@jfryton](https://github.com/jfryton). Thank you jfryton.
-
------
-
-Here's an easy-to-follow, step-by-step guide for installing Windows Subsystem for Linux (WSL) with Ubuntu on Windows 10/11:
-
-## Step 1: Enable WSL
-
-1. Press the Windows key + X and click on "Windows PowerShell (Admin)" or "Windows Terminal (Admin)" to open PowerShell or Terminal with administrator privileges.
-2. In the PowerShell window, type the following command and press Enter:
-
-```
-wsl --install
-```
-
-If this command doesn't work, you can enable WSL with the following command for Windows 10:
-
-```
-wsl --set-default-version 1
-```
-
-For Windows 11, you can use:
-
-```
-wsl --set-default-version 2
-```
-
-You may be prompted to restart your computer. If so, save your work and restart.
-
-## Step 2: Install Ubuntu
-
-1. Open the Microsoft Store.
-2. Search for "Ubuntu" in the search bar.
-3. Choose the desired Ubuntu version (e.g., Ubuntu 20.04 LTS) and click "Get" or "Install" to download and install the Ubuntu app.
-4. Once the installation is complete, click "Launch" or search for "Ubuntu" in the Start menu and open the app.
-
-## Step 3: Set up Ubuntu
-
-1. When you first launch the Ubuntu app, it will take a few minutes to set up. Be patient as it installs the necessary files and sets up your environment.
-2. Once the setup is complete, you will be prompted to create a new UNIX username and password. Choose a username and password, and make sure to remember them, as you will need them for future administrative tasks within the Ubuntu environment.
-
-## Step 4: Update and upgrade packages
-
-1. After setting up your username and password, it's a good idea to update and upgrade your Ubuntu system. Run the following commands in the Ubuntu terminal:
-
-```
-sudo apt update
-sudo apt upgrade
-```
-
-2. Enter your password when prompted. This will update the package list and upgrade any outdated packages.
-
-Congratulations! You have now installed WSL with Ubuntu on your Windows 10/11 system. You can use the Ubuntu terminal for various tasks, like running Linux commands, installing packages, or managing files.
-
-You can launch your WSL Ubuntu installation by selecting the Ubuntu app (like any other program installed on your computer) or typing 'ubuntu' into Powershell or Terminal.
-
-## Step 5: Proceed with Linux instructions
-
-1. You can now follow the Linux setup instructions. If you receive any error messages about a missing tool or package, just install them using apt:
-
-```
-sudo apt install [missing package]
-```
-
-You will probably need to install build-essential
-
-```
-sudo apt install build-essential
-```
-
-If you face any issues or need to troubleshoot, you can always refer to the official Microsoft documentation for WSL: https://docs.microsoft.com/en-us/windows/wsl/
-
-## Bonus: Port Forwarding
-
-By default, you won't be able to access the webui from another device on your local network. You will need to setup the appropriate port forwarding using the following command (using PowerShell or Terminal with administrator privileges). 
-
-```
-netsh interface portproxy add v4tov4 listenaddress=0.0.0.0 listenport=7860 connectaddress=localhost connectport=7860
-```
diff --git a/spaces/dragonSwing/wav2vec2-vi-asr/app.py b/spaces/dragonSwing/wav2vec2-vi-asr/app.py
deleted file mode 100644
index eb9dca8962420846a39a1565681111491b6c9e9d..0000000000000000000000000000000000000000
--- a/spaces/dragonSwing/wav2vec2-vi-asr/app.py
+++ /dev/null
@@ -1,104 +0,0 @@
-import gradio as gr
-import torch
-import zipfile
-from pyctcdecode import build_ctcdecoder
-from speechbrain.pretrained import EncoderASR
-from transformers.file_utils import cached_path, hf_bucket_url
-
-
-def download_lm(cache_dir="./cache"):
-    cache_dir = "./cache/"
-    lm_file = hf_bucket_url("dragonSwing/wav2vec2-base-vn-270h", filename="4gram.zip")
-    lm_file = cached_path(lm_file, cache_dir=cache_dir)
-    with zipfile.ZipFile(lm_file, "r") as zip_ref:
-        zip_ref.extractall(cache_dir)
-    lm_file = cache_dir + "lm.binary"
-    vocab_file = cache_dir + "vocab-260000.txt"
-    return lm_file, vocab_file
-
-
-model = EncoderASR.from_hparams(
-    source="dragonSwing/wav2vec2-base-vn-270h", savedir="./pretrained/wav2vec-vi-asr"
-)
-
-
-def get_decoder_ngram_model(tokenizer, ngram_lm_path, vocab_path=None):
-    unigrams = None
-    if vocab_path is not None:
-        unigrams = []
-        with open(vocab_path, encoding="utf-8") as f:
-            for line in f:
-                unigrams.append(line.strip())
-
-    vocab_dict = tokenizer.get_vocab()
-    sort_vocab = sorted((value, key) for (key, value) in vocab_dict.items())
-    vocab = [x[1] for x in sort_vocab]
-    vocab_list = vocab
-
-    # convert ctc blank character representation
-    vocab_list[tokenizer.pad_token_id] = ""
-    # replace special characters
-    vocab_list[tokenizer.word_delimiter_token_id] = " "
-    # specify ctc blank char index, since conventially it is the last entry of the logit matrix
-    decoder = build_ctcdecoder(vocab_list, ngram_lm_path, unigrams=unigrams)
-    return decoder
-
-
-# ngram_lm_model = get_decoder_ngram_model(model.tokenizer, lm_file, vocab_file)
-
-
-def transcribe_file(path, max_seconds=20, lm_model=None):
-    waveform = model.load_audio(path)
-    if max_seconds > 0:
-        waveform = waveform[: max_seconds * 16000]
-    batch = waveform.unsqueeze(0)
-    rel_length = torch.tensor([1.0])
-    if lm_model:
-        with torch.no_grad():
-            logits = model(batch, rel_length)
-        text_batch = [
-            lm_model.decode(logit.detach().cpu().numpy(), beam_width=500)
-            for logit in logits
-        ]
-        return text_batch[0]
-    else:
-        text_batch, _ = model.transcribe_batch(
-            batch, rel_length
-        )
-        return text_batch[0]
-
-def speech_recognize(file_upload, file_mic):
-    if file_upload is not None:
-        file = file_upload
-    elif file_mic is not None:
-        file = file_mic
-    else:
-        return ""
-    # text = model.transcribe_file(file)
-    text = transcribe_file(file)
-    return text
-
-
-inputs = [
-    gr.Audio(source="upload", type="filepath", optional=True),
-    gr.Audio(source="microphone", type="filepath", optional=True),
-]
-outputs = gr.Textbox(label="Output Text")
-title = "wav2vec2-base-vietnamese-270h"
-description = "Gradio demo for a wav2vec2 base vietnamese speech recognition. To use it, simply upload your audio, click one of the examples to load them, or record from your own microphone. Read more at the links below. Currently supports 16_000hz audio files"
-article = "<p style='text-align: center'><a href='https://huggingface.co/dragonSwing/wav2vec2-base-vn-270h' target='_blank'>Pretrained model</a></p>"
-examples = [
-    ["example1.wav", "example1.wav"],
-    ["example2.mp3", "example2.mp3"],
-    ["example3.mp3", "example3.mp3"],
-    ["example4.wav", "example4.wav"],
-]
-gr.Interface(
-    speech_recognize,
-    inputs,
-    outputs,
-    title=title,
-    description=description,
-    article=article,
-    examples=examples,
-).launch()
diff --git a/spaces/dsxailab/Lama-Cleaner-lama-12/app.py b/spaces/dsxailab/Lama-Cleaner-lama-12/app.py
deleted file mode 100644
index c38ab3e653b749b1df96197f4633a2daac8999d4..0000000000000000000000000000000000000000
--- a/spaces/dsxailab/Lama-Cleaner-lama-12/app.py
+++ /dev/null
@@ -1,29 +0,0 @@
-from typing import List
-from pydantic import BaseModel
-from lama_cleaner.server import main
-
-class FakeArgs(BaseModel):
-    host: str = "0.0.0.0"
-    port: int = 7860
-    model: str = 'lama'
-    hf_access_token: str = ""
-    sd_disable_nsfw: bool = True
-    sd_cpu_textencoder: bool = True
-    sd_run_local: bool = False
-    sd_enable_xformers: bool = True
-    local_files_only: bool = False
-    cpu_offload: bool = False
-    device: str = "cpu"
-    gui: bool = False
-    gui_size: List[int] = [1000, 1000]
-    input: str = ''
-    disable_model_switch: bool = True
-    debug: bool = False
-    no_half: bool = False
-    disable_nsfw: bool = True
-    enable_xformers: bool = True
-    model_dir: str = None
-    output_dir: str = None
-
-if __name__ == "__main__":
-    main(FakeArgs())
\ No newline at end of file
diff --git a/spaces/dwolfe66/text-generation-webui-space/modules/models.py b/spaces/dwolfe66/text-generation-webui-space/modules/models.py
deleted file mode 100644
index f4bb11fd3f7292657b008ab644b5be121d9980e5..0000000000000000000000000000000000000000
--- a/spaces/dwolfe66/text-generation-webui-space/modules/models.py
+++ /dev/null
@@ -1,168 +0,0 @@
-import json
-import os
-import time
-import zipfile
-from pathlib import Path
-
-import numpy as np
-import torch
-import transformers
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-import modules.shared as shared
-
-transformers.logging.set_verbosity_error()
-
-local_rank = None
-
-if shared.args.flexgen:
-    from flexgen.flex_opt import (CompressionConfig, ExecutionEnv, OptLM,
-                                  Policy, str2bool)
-
-if shared.args.deepspeed:
-    import deepspeed
-    from transformers.deepspeed import (HfDeepSpeedConfig,
-                                        is_deepspeed_zero3_enabled)
-
-    from modules.deepspeed_parameters import generate_ds_config
-
-    # Distributed setup
-    local_rank = shared.args.local_rank if shared.args.local_rank is not None else int(os.getenv("LOCAL_RANK", "0"))
-    world_size = int(os.getenv("WORLD_SIZE", "1"))
-    torch.cuda.set_device(local_rank)
-    deepspeed.init_distributed()
-    ds_config = generate_ds_config(shared.args.bf16, 1 * world_size, shared.args.nvme_offload_dir)
-    dschf = HfDeepSpeedConfig(ds_config) # Keep this object alive for the Transformers integration
-
-
-def load_model(model_name):
-    print(f"Loading {model_name}...")
-    t0 = time.time()
-
-    shared.is_RWKV = model_name.lower().startswith('rwkv-')
-
-    # Default settings
-    if not any([shared.args.cpu, shared.args.load_in_8bit, shared.args.gptq_bits, shared.args.auto_devices, shared.args.disk, shared.args.gpu_memory is not None, shared.args.cpu_memory is not None, shared.args.deepspeed, shared.args.flexgen, shared.is_RWKV]):
-        if any(size in shared.model_name.lower() for size in ('13b', '20b', '30b')):
-            model = AutoModelForCausalLM.from_pretrained(Path(f"models/{shared.model_name}"), device_map='auto', load_in_8bit=True)
-        else:
-            model = AutoModelForCausalLM.from_pretrained(Path(f"models/{shared.model_name}"), low_cpu_mem_usage=True, torch_dtype=torch.bfloat16 if shared.args.bf16 else torch.float16).cuda()
-
-    # FlexGen
-    elif shared.args.flexgen:
-        # Initialize environment
-        env = ExecutionEnv.create(shared.args.disk_cache_dir)
-
-        # Offloading policy
-        policy = Policy(1, 1,
-                        shared.args.percent[0], shared.args.percent[1],
-                        shared.args.percent[2], shared.args.percent[3],
-                        shared.args.percent[4], shared.args.percent[5],
-                        overlap=True, sep_layer=True, pin_weight=shared.args.pin_weight,
-                        cpu_cache_compute=False, attn_sparsity=1.0,
-                        compress_weight=shared.args.compress_weight,
-                        comp_weight_config=CompressionConfig(
-                            num_bits=4, group_size=64,
-                            group_dim=0, symmetric=False),
-                        compress_cache=False,
-                        comp_cache_config=CompressionConfig(
-                            num_bits=4, group_size=64,
-                            group_dim=2, symmetric=False))
-
-        model = OptLM(f"facebook/{shared.model_name}", env, "models", policy)
-
-    # DeepSpeed ZeRO-3
-    elif shared.args.deepspeed:
-        model = AutoModelForCausalLM.from_pretrained(Path(f"models/{shared.model_name}"), torch_dtype=torch.bfloat16 if shared.args.bf16 else torch.float16)
-        model = deepspeed.initialize(model=model, config_params=ds_config, model_parameters=None, optimizer=None, lr_scheduler=None)[0]
-        model.module.eval() # Inference
-        print(f"DeepSpeed ZeRO-3 is enabled: {is_deepspeed_zero3_enabled()}")
-
-    # RMKV model (not on HuggingFace)
-    elif shared.is_RWKV:
-        from modules.RWKV import RWKVModel, RWKVTokenizer
-
-        model = RWKVModel.from_pretrained(Path(f'models/{model_name}'), dtype="fp32" if shared.args.cpu else "bf16" if shared.args.bf16 else "fp16", device="cpu" if shared.args.cpu else "cuda")
-        tokenizer = RWKVTokenizer.from_pretrained(Path('models'))
-
-        return model, tokenizer
-
-    # Quantized model
-    elif shared.args.gptq_bits > 0:
-        from modules.GPTQ_loader import load_quantized
-
-        model = load_quantized(model_name)
-
-    # Custom
-    else:
-        command = "AutoModelForCausalLM.from_pretrained"
-        params = ["low_cpu_mem_usage=True"]
-        if not shared.args.cpu and not torch.cuda.is_available():
-            print("Warning: no GPU has been detected.\nFalling back to CPU mode.\n")
-            shared.args.cpu = True
-
-        if shared.args.cpu:
-            params.append("low_cpu_mem_usage=True")
-            params.append("torch_dtype=torch.float32")
-        else:
-            params.append("device_map='auto'")
-            params.append("load_in_8bit=True" if shared.args.load_in_8bit else "torch_dtype=torch.bfloat16" if shared.args.bf16 else "torch_dtype=torch.float16")
-
-            if shared.args.gpu_memory:
-                memory_map = shared.args.gpu_memory
-                max_memory = f"max_memory={{0: '{memory_map[0]}GiB'"
-                for i in range(1, len(memory_map)):
-                    max_memory += (f", {i}: '{memory_map[i]}GiB'")
-                max_memory += (f", 'cpu': '{shared.args.cpu_memory or '99'}GiB'}}")
-                params.append(max_memory)
-            elif not shared.args.load_in_8bit:
-                total_mem = (torch.cuda.get_device_properties(0).total_memory/(1024*1024))
-                suggestion = round((total_mem-1000)/1000)*1000
-                if total_mem-suggestion < 800:
-                    suggestion -= 1000
-                suggestion = int(round(suggestion/1000))
-                print(f"\033[1;32;1mAuto-assiging --gpu-memory {suggestion} for your GPU to try to prevent out-of-memory errors.\nYou can manually set other values.\033[0;37;0m")
-                params.append(f"max_memory={{0: '{suggestion}GiB', 'cpu': '{shared.args.cpu_memory or '99'}GiB'}}")
-            if shared.args.disk:
-                params.append(f"offload_folder='{shared.args.disk_cache_dir}'")
-
-        command = f"{command}(Path(f'models/{shared.model_name}'), {', '.join(set(params))})"
-        model = eval(command)
-
-    # Loading the tokenizer
-    if shared.model_name.lower().startswith(('gpt4chan', 'gpt-4chan', '4chan')) and Path("models/gpt-j-6B/").exists():
-        tokenizer = AutoTokenizer.from_pretrained(Path("models/gpt-j-6B/"))
-    else:
-        tokenizer = AutoTokenizer.from_pretrained(Path(f"models/{shared.model_name}/"))
-    tokenizer.truncation_side = 'left'
-
-    print(f"Loaded the model in {(time.time()-t0):.2f} seconds.")
-    return model, tokenizer
-
-def load_soft_prompt(name):
-    if name == 'None':
-        shared.soft_prompt = False
-        shared.soft_prompt_tensor = None
-    else:
-        with zipfile.ZipFile(Path(f'softprompts/{name}.zip')) as zf:
-            zf.extract('tensor.npy')
-            zf.extract('meta.json')
-            j = json.loads(open('meta.json', 'r').read())
-            print(f"\nLoading the softprompt \"{name}\".")
-            for field in j:
-                if field != 'name':
-                    if type(j[field]) is list:
-                        print(f"{field}: {', '.join(j[field])}")
-                    else:
-                        print(f"{field}: {j[field]}")
-            print()
-            tensor = np.load('tensor.npy')
-            Path('tensor.npy').unlink()
-            Path('meta.json').unlink()
-        tensor = torch.Tensor(tensor).to(device=shared.model.device, dtype=shared.model.dtype)
-        tensor = torch.reshape(tensor, (1, tensor.shape[0], tensor.shape[1]))
-
-        shared.soft_prompt = True
-        shared.soft_prompt_tensor = tensor
-
-    return name
diff --git a/spaces/elkraken/Video-Object-Detection/deploy/triton-inference-server/render.py b/spaces/elkraken/Video-Object-Detection/deploy/triton-inference-server/render.py
deleted file mode 100644
index dea040156560ed55fed1739e95e26f4598d402f2..0000000000000000000000000000000000000000
--- a/spaces/elkraken/Video-Object-Detection/deploy/triton-inference-server/render.py
+++ /dev/null
@@ -1,110 +0,0 @@
-import numpy as np
-
-import cv2
-
-from math import sqrt
-
-_LINE_THICKNESS_SCALING = 500.0
-
-np.random.seed(0)
-RAND_COLORS = np.random.randint(50, 255, (64, 3), "int")  # used for class visu
-RAND_COLORS[0] = [220, 220, 220]
-
-def render_box(img, box, color=(200, 200, 200)):
-    """
-    Render a box. Calculates scaling and thickness automatically.
-    :param img: image to render into
-    :param box: (x1, y1, x2, y2) - box coordinates
-    :param color: (b, g, r) - box color
-    :return: updated image
-    """
-    x1, y1, x2, y2 = box
-    thickness = int(
-        round(
-            (img.shape[0] * img.shape[1])
-            / (_LINE_THICKNESS_SCALING * _LINE_THICKNESS_SCALING)
-        )
-    )
-    thickness = max(1, thickness)
-    img = cv2.rectangle(
-        img,
-        (int(x1), int(y1)),
-        (int(x2), int(y2)),
-        color,
-        thickness=thickness
-    )
-    return img
-
-def render_filled_box(img, box, color=(200, 200, 200)):
-    """
-    Render a box. Calculates scaling and thickness automatically.
-    :param img: image to render into
-    :param box: (x1, y1, x2, y2) - box coordinates
-    :param color: (b, g, r) - box color
-    :return: updated image
-    """
-    x1, y1, x2, y2 = box
-    img = cv2.rectangle(
-        img,
-        (int(x1), int(y1)),
-        (int(x2), int(y2)),
-        color,
-        thickness=cv2.FILLED
-    )
-    return img
-
-_TEXT_THICKNESS_SCALING = 700.0
-_TEXT_SCALING = 520.0
-
-
-def get_text_size(img, text, normalised_scaling=1.0):
-    """
-    Get calculated text size (as box width and height)
-    :param img: image reference, used to determine appropriate text scaling
-    :param text: text to display
-    :param normalised_scaling: additional normalised scaling. Default 1.0.
-    :return: (width, height) - width and height of text box
-    """
-    thickness = int(
-        round(
-            (img.shape[0] * img.shape[1])
-            / (_TEXT_THICKNESS_SCALING * _TEXT_THICKNESS_SCALING)
-        )
-        * normalised_scaling
-    )
-    thickness = max(1, thickness)
-    scaling = img.shape[0] / _TEXT_SCALING * normalised_scaling
-    return cv2.getTextSize(text, cv2.FONT_HERSHEY_SIMPLEX, scaling, thickness)[0]
-
-
-def render_text(img, text, pos, color=(200, 200, 200), normalised_scaling=1.0):
-    """
-    Render a text into the image. Calculates scaling and thickness automatically.
-    :param img: image to render into
-    :param text: text to display
-    :param pos: (x, y) - upper left coordinates of render position
-    :param color: (b, g, r) - text color
-    :param normalised_scaling: additional normalised scaling. Default 1.0.
-    :return: updated image
-    """
-    x, y = pos
-    thickness = int(
-        round(
-            (img.shape[0] * img.shape[1])
-            / (_TEXT_THICKNESS_SCALING * _TEXT_THICKNESS_SCALING)
-        )
-        * normalised_scaling
-    )
-    thickness = max(1, thickness)
-    scaling = img.shape[0] / _TEXT_SCALING * normalised_scaling
-    size = get_text_size(img, text, normalised_scaling)
-    cv2.putText(
-        img,
-        text,
-        (int(x), int(y + size[1])),
-        cv2.FONT_HERSHEY_SIMPLEX,
-        scaling,
-        color,
-        thickness=thickness,
-    )
-    return img
diff --git a/spaces/eskayML/English-to-French-Translation/app.py b/spaces/eskayML/English-to-French-Translation/app.py
deleted file mode 100644
index 2ae69156051038760b3a8d3d3bc3d32a6cb04c1b..0000000000000000000000000000000000000000
--- a/spaces/eskayML/English-to-French-Translation/app.py
+++ /dev/null
@@ -1,14 +0,0 @@
-from transformers import pipeline
-
-translator = pipeline('translation_en_to_fr')
-
-tran_fun = lambda x: translator(x)[0]['translation_text']
-import gradio as gr
-
-demo = gr.Interface(
-    fn = tran_fun, 
-    inputs = gr.Textbox(label = 'Enter An English Word to be translated into French', lines = 3),
-    outputs = 'text',
-)
-
-demo.launch()
\ No newline at end of file
diff --git a/spaces/facebook/MusicGen/audiocraft/modules/chroma.py b/spaces/facebook/MusicGen/audiocraft/modules/chroma.py
deleted file mode 100644
index e84fb66b4a4aaefb0b3ccac8a9a44c3b20e48f61..0000000000000000000000000000000000000000
--- a/spaces/facebook/MusicGen/audiocraft/modules/chroma.py
+++ /dev/null
@@ -1,66 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-import typing as tp
-
-from einops import rearrange
-from librosa import filters
-import torch
-from torch import nn
-import torch.nn.functional as F
-import torchaudio
-
-
-class ChromaExtractor(nn.Module):
-    """Chroma extraction and quantization.
-
-    Args:
-        sample_rate (int): Sample rate for the chroma extraction.
-        n_chroma (int): Number of chroma bins for the chroma extraction.
-        radix2_exp (int): Size of stft window for the chroma extraction (power of 2, e.g. 12 -> 2^12).
-        nfft (int, optional): Number of FFT.
-        winlen (int, optional): Window length.
-        winhop (int, optional): Window hop size.
-        argmax (bool, optional): Whether to use argmax. Defaults to False.
-        norm (float, optional): Norm for chroma normalization. Defaults to inf.
-    """
-    def __init__(self, sample_rate: int, n_chroma: int = 12, radix2_exp: int = 12, nfft: tp.Optional[int] = None,
-                 winlen: tp.Optional[int] = None, winhop: tp.Optional[int] = None, argmax: bool = False,
-                 norm: float = torch.inf):
-        super().__init__()
-        self.winlen = winlen or 2 ** radix2_exp
-        self.nfft = nfft or self.winlen
-        self.winhop = winhop or (self.winlen // 4)
-        self.sample_rate = sample_rate
-        self.n_chroma = n_chroma
-        self.norm = norm
-        self.argmax = argmax
-        self.register_buffer('fbanks', torch.from_numpy(filters.chroma(sr=sample_rate, n_fft=self.nfft, tuning=0,
-                                                                       n_chroma=self.n_chroma)), persistent=False)
-        self.spec = torchaudio.transforms.Spectrogram(n_fft=self.nfft, win_length=self.winlen,
-                                                      hop_length=self.winhop, power=2, center=True,
-                                                      pad=0, normalized=True)
-
-    def forward(self, wav: torch.Tensor) -> torch.Tensor:
-        T = wav.shape[-1]
-        # in case we are getting a wav that was dropped out (nullified)
-        # from the conditioner, make sure wav length is no less that nfft
-        if T < self.nfft:
-            pad = self.nfft - T
-            r = 0 if pad % 2 == 0 else 1
-            wav = F.pad(wav, (pad // 2, pad // 2 + r), 'constant', 0)
-            assert wav.shape[-1] == self.nfft, f"expected len {self.nfft} but got {wav.shape[-1]}"
-
-        spec = self.spec(wav).squeeze(1)
-        raw_chroma = torch.einsum('cf,...ft->...ct', self.fbanks, spec)
-        norm_chroma = torch.nn.functional.normalize(raw_chroma, p=self.norm, dim=-2, eps=1e-6)
-        norm_chroma = rearrange(norm_chroma, 'b d t -> b t d')
-
-        if self.argmax:
-            idx = norm_chroma.argmax(-1, keepdim=True)
-            norm_chroma[:] = 0
-            norm_chroma.scatter_(dim=-1, index=idx, value=1)
-
-        return norm_chroma
diff --git a/spaces/falterWliame/Face_Mask_Detection/Office 2010 Toolkit 2.1.4 And EZ-Activator New V. Download Free.md b/spaces/falterWliame/Face_Mask_Detection/Office 2010 Toolkit 2.1.4 And EZ-Activator New V. Download Free.md
deleted file mode 100644
index b6da2860ebe660d8d0b17c920081ac93961da279..0000000000000000000000000000000000000000
--- a/spaces/falterWliame/Face_Mask_Detection/Office 2010 Toolkit 2.1.4 And EZ-Activator New V. Download Free.md	
+++ /dev/null
@@ -1,30 +0,0 @@
-<h2>Office 2010 Toolkit 2.1.4 and EZ-Activator new V. download</h2><br /><p><b><b>Download File</b> ->>> <a href="https://urlca.com/2uDcaa">https://urlca.com/2uDcaa</a></b></p><br /><br />
-
-Download Office 2010 Toolkit Free and Office 2010 Toolkit Crack.The present invention relates to a system for performing a power distribution test.
-
-A power distribution test is performed for a power distribution system such as a power distribution unit (PDU), a circuit breaker, a fuse, and the like, in order to prevent a power outage or damage due to a trouble in the power distribution system.
-
-FIG. 1 is a diagram illustrating a general power distribution test system.
-
-Referring to FIG. 1, a test control unit 11 receives a power distribution test request signal transmitted from a test terminal 12, and generates and transmits a power distribution test command signal for performing a power distribution test.
-
-A control unit 10 receives the power distribution test command signal from the test control unit 11, and performs a power distribution test.
-
-The test terminal 12 is generally connected to a power distribution unit (PDU) 20, and includes a power distribution test command signal generator and a power distribution test execution device.
-
-The power distribution unit (PDU) 20 is a device for distributing power to each outlet in a power distribution system. The power distribution unit (PDU) 20 includes a power distribution control unit (PDU) 21, a power distribution power supply unit (PDU) 22, and a power distribution breaker unit (PDU) 23.
-
-The power distribution control unit (PDU) 21 is a device for controlling a power distribution path from a power distribution breaker unit (PDU) 23 to an outlet. The power distribution power supply unit (PDU) 22 supplies power to a load circuit of each outlet in the power distribution system.
-
-The power distribution breaker unit (PDU) 23 is a device for opening or closing a power distribution path from the power distribution control unit (PDU) 21 to an outlet. The power distribution breaker unit (PDU) 23 includes a breaker unit 24 and a breaker controller 25.
-
-The breaker unit 24 is a device for opening or closing a power distribution path from the power distribution power supply unit (PDU) 22 to an outlet. The breaker controller 25 controls the operation of the breaker unit 24.
-
-The breaker controller 25 receives a power distribution test request signal from the test control unit 11, and determines whether to perform a power distribution test or a normal power distribution test.
-
-The power distribution test is performed by the breaker controller 25 for a specific outlet in the power distribution system.
-
-A test execution device 30 receives a power distribution test result signal transmitted from the test control unit 4fefd39f24<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/fatiXbelha/sd/Experience the Thrill of Multiplayer Online Shooting with Special Forces Group 2.md b/spaces/fatiXbelha/sd/Experience the Thrill of Multiplayer Online Shooting with Special Forces Group 2.md
deleted file mode 100644
index 51b8cd12fd3928aca09d0266bdb265829040b160..0000000000000000000000000000000000000000
--- a/spaces/fatiXbelha/sd/Experience the Thrill of Multiplayer Online Shooting with Special Forces Group 2.md	
+++ /dev/null
@@ -1,104 +0,0 @@
-<br />
-<h1>Special Forces Group 2: A Thrilling FPS Game for Android</h1>
-<p>If you are a fan of first-person shooter (FPS) games, you might want to check out Special Forces Group 2, a 3D action game that lets you experience the thrill of combat in real-time. Whether you want to play solo or with your friends online, Special Forces Group 2 has something for everyone. In this article, we will tell you what Special Forces Group 2 is, how to download and install it from uptodown, and some tips and tricks to play it better.</p>
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- <h2>What is Special Forces Group 2?</h2>
-<p>Special Forces Group 2 is a FPS game developed by ForgeGames for Android devices. It was released in 2016 and has since gained over 100 million downloads on Google Play Store. The game is inspired by popular FPS games like Counter-Strike and Call of Duty, and offers a variety of features that make it stand out from other games in the genre.</p>
- <h3>Features of Special Forces Group 2</h3>
-<p>Some of the features that make Special Forces Group 2 a great FPS game are:</p>
- <h4>Real-time multiplayer mode</h4>
-<p>You can play online with up to 10 players per team in different modes such as Team Deathmatch, Capture the Flag, Zombie Mode, Bomb Mode, and more. You can also create your own room and invite your friends to join you. You can chat with your teammates using voice or text messages, and coordinate your strategies to win the match.</p>
- <h4>Single-player mode with bots</h4>
-<p>If you prefer to play offline or practice your skills, you can choose the single-player mode and play with bots. You can adjust the difficulty level of the bots, and select from various maps and modes. You can also customize the number of bots, rounds, time limit, friendly fire, and other settings.</p>
- <h4>Customizable weapons and skins</h4>
-<p>You can choose from over 30 different weapons such as rifles, pistols, shotguns, snipers, machine guns, grenades, knives, and more. You can also unlock and buy skins for your weapons and characters, and change their appearance according to your preference. You can also upgrade your weapons to increase their damage, accuracy, fire rate, and reload speed.</p>
- <h4>Various maps and modes</h4>
-<p>You can explore over 20 different maps in Special Forces Group 2, each with its own layout, terrain, obstacles, and secrets. You can also choose from various modes such as Classic Mode, Resurrection Mode, Capture the Flag Mode, Zombie Mode, Bomb Mode, Knives Mode, Deathmatch Mode, Arms Race Mode, Sniper Mode, and more. Each mode has its own rules and objectives that require different strategies and skills.</p>
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- <h4>Stunning graphics and sound effects</h4>
-<p>The game has impressive 3D graphics that create a realistic and immersive atmosphere for the players. The game also has realistic sound effects that enhance the gameplay experience. You can hear the gunfire, explosions, footsteps, reloads, screams, and more. You can also adjust the graphics quality and sound volume according to your device's performance.</p <h3>How to download and install Special Forces Group 2 from uptodown?</h3>
-<p>If you want to download and install Special Forces Group 2 from uptodown, a website that offers free and safe APK files for Android apps and games, you can follow these simple steps:</p>
- <h4>Steps to download and install Special Forces Group 2 from uptodown</h4>
-<ol>
-<li>Go to the <a href="">Special Forces Group 2 page on uptodown</a> and click on the green "Download" button.</li>
-<li>Wait for the APK file to be downloaded on your device. You can check the progress in the notification bar.</li>
-<li>Once the download is complete, tap on the notification or go to your file manager and locate the APK file.</li>
-<li>Before installing the APK file, you need to enable the "Unknown sources" option on your device. To do this, go to Settings > Security > Unknown sources and toggle it on.</li>
-<li>Now, tap on the APK file and follow the instructions to install Special Forces Group 2 on your device.</li>
-<li>After the installation is done, you can launch the game and enjoy it.</li>
-</ol>
- <h4>Benefits of downloading from uptodown</h4>
-<p>Some of the benefits of downloading Special Forces Group 2 from uptodown are:</p>
-<ul>
-<li>You can get the latest version of the game without waiting for the official update on Google Play Store.</li>
-<li>You can access older versions of the game if you prefer them or if your device is not compatible with the latest version.</li>
-<li>You can avoid any regional restrictions that might prevent you from downloading the game from Google Play Store.</li>
-<li>You can save data and storage space by downloading only the APK file without any additional files or obb data.</li>
-</ul>
- <h3>Tips and tricks to play Special Forces Group 2</h3>
-<p>If you want to improve your skills and performance in Special Forces Group 2, you can follow these tips and tricks:</p>
- <h4>Choose your team wisely</h4>
-<p>In Special Forces Group 2, you can choose to play as either a terrorist or a counter-terrorist. Each team has its own advantages and disadvantages, depending on the map and mode. For example, terrorists have more powerful weapons but less armor, while counter-terrorists have more defensive equipment but less firepower. You should choose your team based on your playstyle and strategy, and switch teams if necessary.</p>
- <h4>Use cover and grenades</h4>
-<p>One of the most important skills in Special Forces Group 2 is to use cover effectively. You should always avoid exposing yourself to enemy fire, and move from cover to cover. You should also use grenades to clear rooms, flush out enemies, or create diversions. You can choose from different types of grenades such as frag, smoke, flashbang, or molotov. You should also be careful not to hurt yourself or your teammates with friendly fire.</p>
- <h4>Aim for the head</h4>
-<p>The best way to kill your enemies quickly and efficiently is to aim for their head. Headshots deal more damage than body shots, and can often result in instant kills. You should also try to control your recoil and burst fire, especially when using automatic weapons. You should also adjust your sensitivity and crosshair settings according to your preference and device.</p>
- <h4>Communicate with your teammates</h4>
-<p>Another key skill in Special Forces Group 2 is to communicate with your teammates. You should use voice or text chat to coordinate your actions, share information, request backup, or warn about enemies. You should also use the map and radar to keep track of your teammates' positions and movements. Communication can make a big difference between winning and losing a match.</p>
- <h3>Conclusion</h3>
-<p>Special Forces Group 2 is a FPS game that offers a lot of fun and excitement for Android users. It has many features that make it stand out from other games in the genre, such as real-time multiplayer mode, single-player mode with bots, customizable weapons and skins, various maps and modes, stunning graphics and sound effects, and more. You can download and install it from uptodown, a website that provides free and safe APK files for Android apps and games. You can also follow some tips and tricks to play it better, such as choosing your team wisely, using cover and grenades, aiming for the head, and communicating with your teammates. If you are looking for a thrilling FPS game for Android, you should definitely give Special Forces Group 2 a try.</p>
- <h3>FAQs</h3>
-<p>Here are some frequently asked questions about Special Forces Group 2:</p>
- <ol>
-<li><b>Is Special Forces Group Group 2 free to play?</b>
-<p>Yes, Special Forces Group 2 is free to play, but it contains ads and in-app purchases. You can remove the ads and buy extra coins, weapons, and skins with real money.</p></li>
-<li><b>Can I play Special Forces Group 2 offline?</b>
-<p>Yes, you can play Special Forces Group 2 offline in the single-player mode with bots. However, you will need an internet connection to play online in the multiplayer mode.</p></li>
-<li><b>What are the minimum requirements to play Special Forces Group 2?</b>
-<p>The minimum requirements to play Special Forces Group 2 are Android 4.1 or higher, 300 MB of free storage space, and 1 GB of RAM. However, the game may run better on devices with higher specifications.</p></li>
-<li><b>How can I report a bug or a problem in Special Forces Group 2?</b>
-<p>If you encounter a bug or a problem in Special Forces Group 2, you can contact the developer by email at forgegames@mail.ru or by visiting their Facebook page at https://www.facebook.com/ForgeGames-147566088986482/.</p></li>
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-<p>If you enjoy playing Special Forces Group 2 and want to support the developer, you can rate and review the game on Google Play Store, share it with your friends, or make an in-app purchase.</p></li>
-</ol></p> 197e85843d<br />
-<br />
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\ No newline at end of file
diff --git "a/spaces/fb700/chat3/crazy_functions/\351\253\230\347\272\247\345\212\237\350\203\275\345\207\275\346\225\260\346\250\241\346\235\277.py" "b/spaces/fb700/chat3/crazy_functions/\351\253\230\347\272\247\345\212\237\350\203\275\345\207\275\346\225\260\346\250\241\346\235\277.py"
deleted file mode 100644
index 7c6a7ffb5cb2c42e6543c75d6ad9dd643f412cd9..0000000000000000000000000000000000000000
--- "a/spaces/fb700/chat3/crazy_functions/\351\253\230\347\272\247\345\212\237\350\203\275\345\207\275\346\225\260\346\250\241\346\235\277.py"
+++ /dev/null
@@ -1,29 +0,0 @@
-from toolbox import CatchException, update_ui
-from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
-import datetime
-@CatchException
-def 高阶功能模板函数(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
-    """
-    txt             输入栏用户输入的文本，例如需要翻译的一段话，再例如一个包含了待处理文件的路径
-    llm_kwargs      gpt模型参数，如温度和top_p等，一般原样传递下去就行
-    plugin_kwargs   插件模型的参数，暂时没有用武之地
-    chatbot         聊天显示框的句柄，用于显示给用户
-    history         聊天历史，前情提要
-    system_prompt   给gpt的静默提醒
-    web_port        当前软件运行的端口号
-    """
-    history = []    # 清空历史，以免输入溢出
-    chatbot.append(("这是什么功能？", "[Local Message] 请注意，您正在调用一个[函数插件]的模板，该函数面向希望实现更多有趣功能的开发者，它可以作为创建新功能函数的模板（该函数只有20多行代码）。此外我们也提供可同步处理大量文件的多线程Demo供您参考。您若希望分享新的功能模组，请不吝PR！"))
-    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间，我们先及时地做一次界面更新
-    for i in range(5):
-        currentMonth = (datetime.date.today() + datetime.timedelta(days=i)).month
-        currentDay = (datetime.date.today() + datetime.timedelta(days=i)).day
-        i_say = f'历史中哪些事件发生在{currentMonth}月{currentDay}日？列举两条并发送相关图片。发送图片时，请使用Markdown，将Unsplash API中的PUT_YOUR_QUERY_HERE替换成描述该事件的一个最重要的单词。'
-        gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
-            inputs=i_say, inputs_show_user=i_say, 
-            llm_kwargs=llm_kwargs, chatbot=chatbot, history=[], 
-            sys_prompt="当你想发送一张照片时，请使用Markdown, 并且不要有反斜线, 不要用代码块。使用 Unsplash API (https://source.unsplash.com/1280x720/? < PUT_YOUR_QUERY_HERE >)。"
-        )
-        chatbot[-1] = (i_say, gpt_say)
-        history.append(i_say);history.append(gpt_say)
-        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
diff --git a/spaces/fb700/chatglm-fitness-RLHF/docs/WithFastapi.md b/spaces/fb700/chatglm-fitness-RLHF/docs/WithFastapi.md
deleted file mode 100644
index 188b52716485f15e528772c6454ee7839ced4406..0000000000000000000000000000000000000000
--- a/spaces/fb700/chatglm-fitness-RLHF/docs/WithFastapi.md
+++ /dev/null
@@ -1,43 +0,0 @@
-# Running with fastapi
-
-We currently support fastapi in order to solve sub-path deploy issue.
-
-1. change CUSTOM_PATH setting in `config.py`
-
-``` sh
-nano config.py
-```
-
-2. Edit main.py
-
-```diff
-    auto_opentab_delay()
-    - demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", server_port=PORT, auth=AUTHENTICATION, favicon_path="docs/logo.png")
-    + demo.queue(concurrency_count=CONCURRENT_COUNT)
-
-    - # 如果需要在二级路径下运行
-    - # CUSTOM_PATH, = get_conf('CUSTOM_PATH')
-    - # if CUSTOM_PATH != "/": 
-    - #     from toolbox import run_gradio_in_subpath
-    - #     run_gradio_in_subpath(demo, auth=AUTHENTICATION, port=PORT, custom_path=CUSTOM_PATH)
-    - # else: 
-    - #     demo.launch(server_name="0.0.0.0", server_port=PORT, auth=AUTHENTICATION, favicon_path="docs/logo.png")
-
-    + 如果需要在二级路径下运行
-    + CUSTOM_PATH, = get_conf('CUSTOM_PATH')
-    + if CUSTOM_PATH != "/": 
-    +     from toolbox import run_gradio_in_subpath
-    +     run_gradio_in_subpath(demo, auth=AUTHENTICATION, port=PORT, custom_path=CUSTOM_PATH)
-    + else: 
-    +     demo.launch(server_name="0.0.0.0", server_port=PORT, auth=AUTHENTICATION, favicon_path="docs/logo.png")
-
-if __name__ == "__main__":
-    main()
-```
-
-
-3. Go!
-
-``` sh
-python main.py
-```
diff --git a/spaces/fb700/chatglm-fitness-RLHF/request_llm/edge_gpt.py b/spaces/fb700/chatglm-fitness-RLHF/request_llm/edge_gpt.py
deleted file mode 100644
index bbf84000d84a42de80d3c051a24f06336af76aaf..0000000000000000000000000000000000000000
--- a/spaces/fb700/chatglm-fitness-RLHF/request_llm/edge_gpt.py
+++ /dev/null
@@ -1,409 +0,0 @@
-"""
-========================================================================
-第一部分：来自EdgeGPT.py
-https://github.com/acheong08/EdgeGPT
-========================================================================
-"""
-
-import argparse
-import asyncio
-import json
-import os
-import random
-import re
-import ssl
-import sys
-import uuid
-from enum import Enum
-from typing import Generator
-from typing import Literal
-from typing import Optional
-from typing import Union
-import websockets.client as websockets
-
-DELIMITER = "\x1e"
-
-
-# Generate random IP between range 13.104.0.0/14
-FORWARDED_IP = (
-    f"13.{random.randint(104, 107)}.{random.randint(0, 255)}.{random.randint(0, 255)}"
-)
-
-HEADERS = {
-    "accept": "application/json",
-    "accept-language": "en-US,en;q=0.9",
-    "content-type": "application/json",
-    "sec-ch-ua": '"Not_A Brand";v="99", "Microsoft Edge";v="110", "Chromium";v="110"',
-    "sec-ch-ua-arch": '"x86"',
-    "sec-ch-ua-bitness": '"64"',
-    "sec-ch-ua-full-version": '"109.0.1518.78"',
-    "sec-ch-ua-full-version-list": '"Chromium";v="110.0.5481.192", "Not A(Brand";v="24.0.0.0", "Microsoft Edge";v="110.0.1587.69"',
-    "sec-ch-ua-mobile": "?0",
-    "sec-ch-ua-model": "",
-    "sec-ch-ua-platform": '"Windows"',
-    "sec-ch-ua-platform-version": '"15.0.0"',
-    "sec-fetch-dest": "empty",
-    "sec-fetch-mode": "cors",
-    "sec-fetch-site": "same-origin",
-    "x-ms-client-request-id": str(uuid.uuid4()),
-    "x-ms-useragent": "azsdk-js-api-client-factory/1.0.0-beta.1 core-rest-pipeline/1.10.0 OS/Win32",
-    "Referer": "https://www.bing.com/search?q=Bing+AI&showconv=1&FORM=hpcodx",
-    "Referrer-Policy": "origin-when-cross-origin",
-    "x-forwarded-for": FORWARDED_IP,
-}
-
-HEADERS_INIT_CONVER = {
-    "authority": "edgeservices.bing.com",
-    "accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7",
-    "accept-language": "en-US,en;q=0.9",
-    "cache-control": "max-age=0",
-    "sec-ch-ua": '"Chromium";v="110", "Not A(Brand";v="24", "Microsoft Edge";v="110"',
-    "sec-ch-ua-arch": '"x86"',
-    "sec-ch-ua-bitness": '"64"',
-    "sec-ch-ua-full-version": '"110.0.1587.69"',
-    "sec-ch-ua-full-version-list": '"Chromium";v="110.0.5481.192", "Not A(Brand";v="24.0.0.0", "Microsoft Edge";v="110.0.1587.69"',
-    "sec-ch-ua-mobile": "?0",
-    "sec-ch-ua-model": '""',
-    "sec-ch-ua-platform": '"Windows"',
-    "sec-ch-ua-platform-version": '"15.0.0"',
-    "sec-fetch-dest": "document",
-    "sec-fetch-mode": "navigate",
-    "sec-fetch-site": "none",
-    "sec-fetch-user": "?1",
-    "upgrade-insecure-requests": "1",
-    "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36 Edg/110.0.1587.69",
-    "x-edge-shopping-flag": "1",
-    "x-forwarded-for": FORWARDED_IP,
-}
-
-def get_ssl_context():
-    import certifi
-    ssl_context = ssl.create_default_context()
-    ssl_context.load_verify_locations(certifi.where())
-    return ssl_context
-
-
-
-class NotAllowedToAccess(Exception):
-    pass
-
-
-class ConversationStyle(Enum):
-    creative = "h3imaginative,clgalileo,gencontentv3"
-    balanced = "galileo"
-    precise = "h3precise,clgalileo"
-
-
-CONVERSATION_STYLE_TYPE = Optional[
-    Union[ConversationStyle, Literal["creative", "balanced", "precise"]]
-]
-
-
-def _append_identifier(msg: dict) -> str:
-    """
-    Appends special character to end of message to identify end of message
-    """
-    # Convert dict to json string
-    return json.dumps(msg) + DELIMITER
-
-
-def _get_ran_hex(length: int = 32) -> str:
-    """
-    Returns random hex string
-    """
-    return "".join(random.choice("0123456789abcdef") for _ in range(length))
-
-
-class _ChatHubRequest:
-    """
-    Request object for ChatHub
-    """
-
-    def __init__(
-        self,
-        conversation_signature: str,
-        client_id: str,
-        conversation_id: str,
-        invocation_id: int = 0,
-    ) -> None:
-        self.struct: dict = {}
-
-        self.client_id: str = client_id
-        self.conversation_id: str = conversation_id
-        self.conversation_signature: str = conversation_signature
-        self.invocation_id: int = invocation_id
-
-    def update(
-        self,
-        prompt,
-        conversation_style,
-        options,
-    ) -> None:
-        """
-        Updates request object
-        """
-        if options is None:
-            options = [
-                "deepleo",
-                "enable_debug_commands",
-                "disable_emoji_spoken_text",
-                "enablemm",
-            ]
-        if conversation_style:
-            if not isinstance(conversation_style, ConversationStyle):
-                conversation_style = getattr(ConversationStyle, conversation_style)
-            options = [
-                "nlu_direct_response_filter",
-                "deepleo",
-                "disable_emoji_spoken_text",
-                "responsible_ai_policy_235",
-                "enablemm",
-                conversation_style.value,
-                "dtappid",
-                "cricinfo",
-                "cricinfov2",
-                "dv3sugg",
-            ]
-        self.struct = {
-            "arguments": [
-                {
-                    "source": "cib",
-                    "optionsSets": options,
-                    "sliceIds": [
-                        "222dtappid",
-                        "225cricinfo",
-                        "224locals0",
-                    ],
-                    "traceId": _get_ran_hex(32),
-                    "isStartOfSession": self.invocation_id == 0,
-                    "message": {
-                        "author": "user",
-                        "inputMethod": "Keyboard",
-                        "text": prompt,
-                        "messageType": "Chat",
-                    },
-                    "conversationSignature": self.conversation_signature,
-                    "participant": {
-                        "id": self.client_id,
-                    },
-                    "conversationId": self.conversation_id,
-                },
-            ],
-            "invocationId": str(self.invocation_id),
-            "target": "chat",
-            "type": 4,
-        }
-        self.invocation_id += 1
-
-
-class _Conversation:
-    """
-    Conversation API
-    """
-
-    def __init__(
-        self,
-        cookies,
-        proxy,
-    ) -> None:
-        self.struct: dict = {
-            "conversationId": None,
-            "clientId": None,
-            "conversationSignature": None,
-            "result": {"value": "Success", "message": None},
-        }
-        import httpx
-        self.proxy = proxy
-        proxy = (
-            proxy
-            or os.environ.get("all_proxy")
-            or os.environ.get("ALL_PROXY")
-            or os.environ.get("https_proxy")
-            or os.environ.get("HTTPS_PROXY")
-            or None
-        )
-        if proxy is not None and proxy.startswith("socks5h://"):
-            proxy = "socks5://" + proxy[len("socks5h://") :]
-        self.session = httpx.Client(
-            proxies=proxy,
-            timeout=30,
-            headers=HEADERS_INIT_CONVER,
-        )
-        for cookie in cookies:
-            self.session.cookies.set(cookie["name"], cookie["value"])
-
-        # Send GET request
-        response = self.session.get(
-            url=os.environ.get("BING_PROXY_URL")
-            or "https://edgeservices.bing.com/edgesvc/turing/conversation/create",
-        )
-        if response.status_code != 200:
-            response = self.session.get(
-                "https://edge.churchless.tech/edgesvc/turing/conversation/create",
-            )
-        if response.status_code != 200:
-            print(f"Status code: {response.status_code}")
-            print(response.text)
-            print(response.url)
-            raise Exception("Authentication failed")
-        try:
-            self.struct = response.json()
-        except (json.decoder.JSONDecodeError, NotAllowedToAccess) as exc:
-            raise Exception(
-                "Authentication failed. You have not been accepted into the beta.",
-            ) from exc
-        if self.struct["result"]["value"] == "UnauthorizedRequest":
-            raise NotAllowedToAccess(self.struct["result"]["message"])
-
-
-class _ChatHub:
-    """
-    Chat API
-    """
-
-    def __init__(self, conversation) -> None:
-        self.wss = None
-        self.request: _ChatHubRequest
-        self.loop: bool
-        self.task: asyncio.Task
-        print(conversation.struct)
-        self.request = _ChatHubRequest(
-            conversation_signature=conversation.struct["conversationSignature"],
-            client_id=conversation.struct["clientId"],
-            conversation_id=conversation.struct["conversationId"],
-        )
-
-    async def ask_stream(
-        self,
-        prompt: str,
-        wss_link: str,
-        conversation_style: CONVERSATION_STYLE_TYPE = None,
-        raw: bool = False,
-        options: dict = None,
-    ) -> Generator[str, None, None]:
-        """
-        Ask a question to the bot
-        """
-        if self.wss and not self.wss.closed:
-            await self.wss.close()
-        # Check if websocket is closed
-        self.wss = await websockets.connect(
-            wss_link,
-            extra_headers=HEADERS,
-            max_size=None,
-            ssl=get_ssl_context()
-        )
-        await self._initial_handshake()
-        # Construct a ChatHub request
-        self.request.update(
-            prompt=prompt,
-            conversation_style=conversation_style,
-            options=options,
-        )
-        # Send request
-        await self.wss.send(_append_identifier(self.request.struct))
-        final = False
-        while not final:
-            objects = str(await self.wss.recv()).split(DELIMITER)
-            for obj in objects:
-                if obj is None or not obj:
-                    continue
-                response = json.loads(obj)
-                if response.get("type") != 2 and raw:
-                    yield False, response
-                elif response.get("type") == 1 and response["arguments"][0].get(
-                    "messages",
-                ):
-                    resp_txt = response["arguments"][0]["messages"][0]["adaptiveCards"][
-                        0
-                    ]["body"][0].get("text")
-                    yield False, resp_txt
-                elif response.get("type") == 2:
-                    final = True
-                    yield True, response
-
-    async def _initial_handshake(self) -> None:
-        await self.wss.send(_append_identifier({"protocol": "json", "version": 1}))
-        await self.wss.recv()
-
-    async def close(self) -> None:
-        """
-        Close the connection
-        """
-        if self.wss and not self.wss.closed:
-            await self.wss.close()
-
-
-class NewbingChatbot:
-    """
-    Combines everything to make it seamless
-    """
-
-    def __init__(
-        self,
-        cookies,
-        proxy
-    ) -> None:
-        if cookies is None:
-            cookies = {}
-        self.cookies = cookies
-        self.proxy = proxy
-        self.chat_hub: _ChatHub = _ChatHub(
-            _Conversation(self.cookies, self.proxy),
-        )
-
-    async def ask(
-        self,
-        prompt: str,
-        wss_link: str,
-        conversation_style: CONVERSATION_STYLE_TYPE = None,
-        options: dict = None,
-    ) -> dict:
-        """
-        Ask a question to the bot
-        """
-        async for final, response in self.chat_hub.ask_stream(
-            prompt=prompt,
-            conversation_style=conversation_style,
-            wss_link=wss_link,
-            options=options,
-        ):
-            if final:
-                return response
-        await self.chat_hub.wss.close()
-        return None
-
-    async def ask_stream(
-        self,
-        prompt: str,
-        wss_link: str,
-        conversation_style: CONVERSATION_STYLE_TYPE = None,
-        raw: bool = False,
-        options: dict = None,
-    ) -> Generator[str, None, None]:
-        """
-        Ask a question to the bot
-        """
-        async for response in self.chat_hub.ask_stream(
-            prompt=prompt,
-            conversation_style=conversation_style,
-            wss_link=wss_link,
-            raw=raw,
-            options=options,
-        ):
-            yield response
-
-    async def close(self) -> None:
-        """
-        Close the connection
-        """
-        await self.chat_hub.close()
-
-    async def reset(self) -> None:
-        """
-        Reset the conversation
-        """
-        await self.close()
-        self.chat_hub = _ChatHub(_Conversation(self.cookies, self.proxy))
-
-
diff --git a/spaces/fb700/chatglm-fitness-RLHF/speaker_encoder/voice_encoder.py b/spaces/fb700/chatglm-fitness-RLHF/speaker_encoder/voice_encoder.py
deleted file mode 100644
index 88cdee2de76b72db58c5dd19a888597e0fe12fbb..0000000000000000000000000000000000000000
--- a/spaces/fb700/chatglm-fitness-RLHF/speaker_encoder/voice_encoder.py
+++ /dev/null
@@ -1,173 +0,0 @@
-from speaker_encoder.hparams import *
-from speaker_encoder import audio
-from pathlib import Path
-from typing import Union, List
-from torch import nn
-from time import perf_counter as timer
-import numpy as np
-import torch
-
-
-class SpeakerEncoder(nn.Module):
-    def __init__(self, weights_fpath, device: Union[str, torch.device]=None, verbose=True):
-        """
-        :param device: either a torch device or the name of a torch device (e.g. "cpu", "cuda"). 
-        If None, defaults to cuda if it is available on your machine, otherwise the model will 
-        run on cpu. Outputs are always returned on the cpu, as numpy arrays.
-        """
-        super().__init__()
-        
-        # Define the network
-        self.lstm = nn.LSTM(mel_n_channels, model_hidden_size, model_num_layers, batch_first=True)
-        self.linear = nn.Linear(model_hidden_size, model_embedding_size)
-        self.relu = nn.ReLU()
-        
-        # Get the target device
-        if device is None:
-            device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-        elif isinstance(device, str):
-            device = torch.device(device)
-        self.device = device
-            
-        # Load the pretrained model'speaker weights
-        # weights_fpath = Path(__file__).resolve().parent.joinpath("pretrained.pt")
-        # if not weights_fpath.exists():
-        #     raise Exception("Couldn't find the voice encoder pretrained model at %s." % 
-        #                     weights_fpath)
-
-        start = timer()
-        checkpoint = torch.load(weights_fpath, map_location="cpu")
-
-        self.load_state_dict(checkpoint["model_state"], strict=False)
-        self.to(device)
-        
-        if verbose:
-            print("Loaded the voice encoder model on %s in %.2f seconds." % 
-                  (device.type, timer() - start))
-
-    def forward(self, mels: torch.FloatTensor):
-        """
-        Computes the embeddings of a batch of utterance spectrograms.
-        :param mels: a batch of mel spectrograms of same duration as a float32 tensor of shape 
-        (batch_size, n_frames, n_channels) 
-        :return: the embeddings as a float 32 tensor of shape (batch_size, embedding_size). 
-        Embeddings are positive and L2-normed, thus they lay in the range [0, 1].
-        """
-        # Pass the input through the LSTM layers and retrieve the final hidden state of the last 
-        # layer. Apply a cutoff to 0 for negative values and L2 normalize the embeddings.
-        _, (hidden, _) = self.lstm(mels)
-        embeds_raw = self.relu(self.linear(hidden[-1]))
-        return embeds_raw / torch.norm(embeds_raw, dim=1, keepdim=True)
-    
-    @staticmethod
-    def compute_partial_slices(n_samples: int, rate, min_coverage):
-        """
-        Computes where to split an utterance waveform and its corresponding mel spectrogram to 
-        obtain partial utterances of <partials_n_frames> each. Both the waveform and the 
-        mel spectrogram slices are returned, so as to make each partial utterance waveform 
-        correspond to its spectrogram.
-    
-        The returned ranges may be indexing further than the length of the waveform. It is 
-        recommended that you pad the waveform with zeros up to wav_slices[-1].stop.
-    
-        :param n_samples: the number of samples in the waveform
-        :param rate: how many partial utterances should occur per second. Partial utterances must 
-        cover the span of the entire utterance, thus the rate should not be lower than the inverse 
-        of the duration of a partial utterance. By default, partial utterances are 1.6s long and 
-        the minimum rate is thus 0.625.
-        :param min_coverage: when reaching the last partial utterance, it may or may not have 
-        enough frames. If at least <min_pad_coverage> of <partials_n_frames> are present, 
-        then the last partial utterance will be considered by zero-padding the audio. Otherwise, 
-        it will be discarded. If there aren't enough frames for one partial utterance, 
-        this parameter is ignored so that the function always returns at least one slice.
-        :return: the waveform slices and mel spectrogram slices as lists of array slices. Index 
-        respectively the waveform and the mel spectrogram with these slices to obtain the partial 
-        utterances.
-        """
-        assert 0 < min_coverage <= 1
-        
-        # Compute how many frames separate two partial utterances
-        samples_per_frame = int((sampling_rate * mel_window_step / 1000))
-        n_frames = int(np.ceil((n_samples + 1) / samples_per_frame))
-        frame_step = int(np.round((sampling_rate / rate) / samples_per_frame))
-        assert 0 < frame_step, "The rate is too high"
-        assert frame_step <= partials_n_frames, "The rate is too low, it should be %f at least" % \
-            (sampling_rate / (samples_per_frame * partials_n_frames))
-        
-        # Compute the slices
-        wav_slices, mel_slices = [], []
-        steps = max(1, n_frames - partials_n_frames + frame_step + 1)
-        for i in range(0, steps, frame_step):
-            mel_range = np.array([i, i + partials_n_frames])
-            wav_range = mel_range * samples_per_frame
-            mel_slices.append(slice(*mel_range))
-            wav_slices.append(slice(*wav_range))
-        
-        # Evaluate whether extra padding is warranted or not
-        last_wav_range = wav_slices[-1]
-        coverage = (n_samples - last_wav_range.start) / (last_wav_range.stop - last_wav_range.start)
-        if coverage < min_coverage and len(mel_slices) > 1:
-            mel_slices = mel_slices[:-1]
-            wav_slices = wav_slices[:-1]
-        
-        return wav_slices, mel_slices
-    
-    def embed_utterance(self, wav: np.ndarray, return_partials=False, rate=1.3, min_coverage=0.75):
-        """
-        Computes an embedding for a single utterance. The utterance is divided in partial 
-        utterances and an embedding is computed for each. The complete utterance embedding is the 
-        L2-normed average embedding of the partial utterances.
-        
-        TODO: independent batched version of this function
-    
-        :param wav: a preprocessed utterance waveform as a numpy array of float32
-        :param return_partials: if True, the partial embeddings will also be returned along with 
-        the wav slices corresponding to each partial utterance.
-        :param rate: how many partial utterances should occur per second. Partial utterances must 
-        cover the span of the entire utterance, thus the rate should not be lower than the inverse 
-        of the duration of a partial utterance. By default, partial utterances are 1.6s long and 
-        the minimum rate is thus 0.625.
-        :param min_coverage: when reaching the last partial utterance, it may or may not have 
-        enough frames. If at least <min_pad_coverage> of <partials_n_frames> are present, 
-        then the last partial utterance will be considered by zero-padding the audio. Otherwise, 
-        it will be discarded. If there aren't enough frames for one partial utterance, 
-        this parameter is ignored so that the function always returns at least one slice.
-        :return: the embedding as a numpy array of float32 of shape (model_embedding_size,). If 
-        <return_partials> is True, the partial utterances as a numpy array of float32 of shape 
-        (n_partials, model_embedding_size) and the wav partials as a list of slices will also be 
-        returned.
-        """
-        # Compute where to split the utterance into partials and pad the waveform with zeros if 
-        # the partial utterances cover a larger range. 
-        wav_slices, mel_slices = self.compute_partial_slices(len(wav), rate, min_coverage)
-        max_wave_length = wav_slices[-1].stop
-        if max_wave_length >= len(wav):
-            wav = np.pad(wav, (0, max_wave_length - len(wav)), "constant")
-        
-        # Split the utterance into partials and forward them through the model
-        mel = audio.wav_to_mel_spectrogram(wav)
-        mels = np.array([mel[s] for s in mel_slices])
-        with torch.no_grad():
-            mels = torch.from_numpy(mels).to(self.device)
-            partial_embeds = self(mels).cpu().numpy()
-        
-        # Compute the utterance embedding from the partial embeddings
-        raw_embed = np.mean(partial_embeds, axis=0)
-        embed = raw_embed / np.linalg.norm(raw_embed, 2)
-        
-        if return_partials:
-            return embed, partial_embeds, wav_slices
-        return embed
-    
-    def embed_speaker(self, wavs: List[np.ndarray], **kwargs):
-        """
-        Compute the embedding of a collection of wavs (presumably from the same speaker) by 
-        averaging their embedding and L2-normalizing it.
-        
-        :param wavs: list of wavs a numpy arrays of float32.
-        :param kwargs: extra arguments to embed_utterance()
-        :return: the embedding as a numpy array of float32 of shape (model_embedding_size,).
-        """
-        raw_embed = np.mean([self.embed_utterance(wav, return_partials=False, **kwargs) \
-                             for wav in wavs], axis=0)
-        return raw_embed / np.linalg.norm(raw_embed, 2)
\ No newline at end of file
diff --git a/spaces/fengmuxi/ChatGpt-Web/app/store/mask.ts b/spaces/fengmuxi/ChatGpt-Web/app/store/mask.ts
deleted file mode 100644
index 98bd4702113e48f44d270edea82f17c9c374ce51..0000000000000000000000000000000000000000
--- a/spaces/fengmuxi/ChatGpt-Web/app/store/mask.ts
+++ /dev/null
@@ -1,100 +0,0 @@
-import { create } from "zustand";
-import { persist } from "zustand/middleware";
-import { BUILTIN_MASKS } from "../masks";
-import { getLang, Lang } from "../locales";
-import { DEFAULT_TOPIC, Message } from "./chat";
-import { ModelConfig, ModelType, useAppConfig } from "./config";
-import { StoreKey } from "../constant";
-
-export type Mask = {
-  id: number;
-  avatar: string;
-  name: string;
-  context: Message[];
-  modelConfig: ModelConfig;
-  lang: Lang;
-  builtin: boolean;
-};
-
-export const DEFAULT_MASK_STATE = {
-  masks: {} as Record<number, Mask>,
-  globalMaskId: 0,
-};
-
-export type MaskState = typeof DEFAULT_MASK_STATE;
-type MaskStore = MaskState & {
-  create: (mask?: Partial<Mask>) => Mask;
-  update: (id: number, updater: (mask: Mask) => void) => void;
-  delete: (id: number) => void;
-  search: (text: string) => Mask[];
-  get: (id?: number) => Mask | null;
-  getAll: () => Mask[];
-};
-
-export const DEFAULT_MASK_ID = 1145141919810;
-export const DEFAULT_MASK_AVATAR = "gpt-bot";
-export const createEmptyMask = () =>
-  ({
-    id: DEFAULT_MASK_ID,
-    avatar: DEFAULT_MASK_AVATAR,
-    name: DEFAULT_TOPIC,
-    context: [],
-    modelConfig: { ...useAppConfig.getState().modelConfig },
-    lang: getLang(),
-    builtin: false,
-  } as Mask);
-
-export const useMaskStore = create<MaskStore>()(
-  persist(
-    (set, get) => ({
-      ...DEFAULT_MASK_STATE,
-
-      create(mask) {
-        set(() => ({ globalMaskId: get().globalMaskId + 1 }));
-        const id = get().globalMaskId;
-        const masks = get().masks;
-        masks[id] = {
-          ...createEmptyMask(),
-          ...mask,
-          id,
-          builtin: false,
-        };
-
-        set(() => ({ masks }));
-
-        return masks[id];
-      },
-      update(id, updater) {
-        const masks = get().masks;
-        const mask = masks[id];
-        if (!mask) return;
-        const updateMask = { ...mask };
-        updater(updateMask);
-        masks[id] = updateMask;
-        set(() => ({ masks }));
-      },
-      delete(id) {
-        const masks = get().masks;
-        delete masks[id];
-        set(() => ({ masks }));
-      },
-
-      get(id) {
-        return get().masks[id ?? 1145141919810];
-      },
-      getAll() {
-        const userMasks = Object.values(get().masks).sort(
-          (a, b) => b.id - a.id,
-        );
-        return userMasks.concat(BUILTIN_MASKS);
-      },
-      search(text) {
-        return Object.values(get().masks);
-      },
-    }),
-    {
-      name: StoreKey.Mask,
-      version: 2,
-    },
-  ),
-);
diff --git a/spaces/feregVcuzo/sanity-test-midi/checkpoint/Download Auto Clicker APK 2023 The Best App for Mobile Gaming.md b/spaces/feregVcuzo/sanity-test-midi/checkpoint/Download Auto Clicker APK 2023 The Best App for Mobile Gaming.md
deleted file mode 100644
index a05bcae9aee2c849b40ee2b0fae5eaa0953caa44..0000000000000000000000000000000000000000
--- a/spaces/feregVcuzo/sanity-test-midi/checkpoint/Download Auto Clicker APK 2023 The Best App for Mobile Gaming.md	
+++ /dev/null
@@ -1,149 +0,0 @@
-<br />
-<h1>Auto Clicker Download APK: How to Automate Your Taps on Android</h1>
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-<h2>auto clicker download apk</h2><br /><p><b><b>Download</b> &#9734; <a href="https://gohhs.com/2uPuIt">https://gohhs.com/2uPuIt</a></b></p><br /><br />
-<h2>What is an auto clicker app and why do you need one?</h2>
-<h3>An auto clicker app is a tool that simulates taps on your screen</h3>
-<p>An auto clicker app is a software that can mimic the action of tapping on your screen. It can generate clicks at a certain speed, interval, duration, or location. You can also customize the number of clicks, the delay between clicks, the swipe direction, and other parameters. An auto clicker app works in the background and does not interfere with other apps or functions on your device.</p>
-<h3>You can use an auto clicker app for various purposes, such as gaming, testing, or productivity</h3>
-<p>An auto clicker app can be useful for different scenarios. For example, you can use it to:</p>
-<ul>
-<li>Play games that require repetitive tapping, such as idle games, clicker games, or RPGs. You can level up faster, collect more resources, or complete more quests without getting tired or bored.</li>
-<li>Test apps or websites that need user input or feedback. You can simulate user behavior, check for errors, or measure performance with ease.</li>
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-vmos pro - virtual machine with root and auto clicker support - modded android emulator - free app store - unlimited games and apps - no ads - no subscription - no verification - no root required - easy to use - fast and stable - best performance - full screen mode - multi window mode - floating window mode - gesture control mode - keyboard and mouse support - gamepad support - custom resolution and dpi settings - screen recording and screenshot features - file sharing and import features - network speed booster features - battery saver features - dark mode features - security lock features - app cloning features - app uninstalling features - app backup and restore features - app update checking features - app permission management features - app data clearing features - app cache clearing features - app force stop features - app info checking features  (This is a very long keyword, but it covers all the possible features of the app)<br />
-xmodgames pro modded games with root and cheat engine support hack any game with unlimited coins gems lives gold diamonds resources items weapons skins characters levels modes maps achievements trophies rewards bonuses challenges events quests missions stories endings secrets tips tricks guides walkthroughs tutorials reviews ratings comments feedbacks suggestions recommendations rankings leaderboards statistics analytics data insights reports dashboards graphs charts tables widgets filters segments dimensions metrics measures calculations formulas functions operators expressions variables parameters arguments values types formats styles colors fonts sizes shapes alignments orientations directions positions margins paddings borders shadows gradients animations transitions effects sounds music voices languages translations dictionaries thesauruses synonyms antonyms definitions examples sentences phrases clauses words letters symbols numbers operators punctuation marks spaces tabs newlines characters codes emojis emoticons stickers gifs images videos audios texts documents files folders directories drives disks partitions volumes systems networks servers clients devices hardware software firmware bios operating systems platforms applications programs processes services tasks threads modules components libraries frameworks packages dependencies plugins extensions addons tools utilities widgets gadgets accessories peripherals keyboards mice gamepads controllers monitors screens displays speakers headphones microphones cameras webcams scanners printers copiers fax machines phones tablets laptops desktops workstations servers routers switches hubs modems firewalls gateways bridges repeaters access points adapters cards cables wires connectors ports sockets plugs outlets switches buttons knobs sliders toggle checkbox radio button dropdown list combo box text box text area label image video audio link button hyperlink anchor tag html element css selector javascript function jquery method ajax request xml response json object php script sql query mysql database oracle database mongodb database postgresql database sqlite database firebase database nosql database graphql database graphql query graphql mutation graphql subscription graphql schema graphql resolver graphql type graphql field graphql argument graphql directive graphql directive location graphql directive skip graphql directive include graphql directive deprecated graphql enum graphql interface graphql input graphql scalar graphql union apollo client apollo server apollo link apollo cache apollo boost apollo studio apollo federation apollo gateway apollo rover react native react js react hooks react router react redux react helmet react spring react bootstrap react icons react toastify react modal react tooltip react table react chartjs 2 next js gatsby js create react app npx npm yarn node js express js mongodb mongoose passport js bcrypt js jsonwebtoken jwt cors dotenv nodemon concurrently axios fetch api rest api graphql api aws amplify aws s3 aws lambda aws ec2 aws rds aws dynamodb aws cognito aws app sync netlify heroku vercel github git git bash git hub desktop vs code visual studio code vscode code editor code compiler code debugger</p>
-<h3>Enable unknown sources on your device settings</h3>
-<p>By default, Android devices do not allow installing apps from sources other than Google Play Store. This is a security measure to prevent installing malicious apps. However, if you want to install an apk file from another source, you need to enable unknown sources on your device settings. To do this:</p>
-<ol>
-<li>Go to Settings > Security > Unknown sources.</li>
-<li>Toggle on the switch to allow installing apps from unknown sources.</li>
-<li>Tap OK to confirm.</li>
-</ol>
-<p>Note: The steps may vary depending on your device <h3>Tap on the apk file and follow the installation instructions</h3>
-<p>Once you have downloaded the apk file, you can install it on your device by tapping on it. You may see a pop-up window asking you to confirm the installation. Tap on Install and wait for the process to finish. You may also see a list of permissions that the app requires. Review them carefully and tap on Accept if you agree. You can also deny some permissions if you are not comfortable with them. However, this may affect the functionality of the app.</p>
-<h2>How to use an auto clicker app on your Android device</h2>
-<h3>Launch the auto clicker app and grant the necessary permissions</h3>
-<p>After installing the auto clicker app, you can launch it by tapping on its icon. The app may ask you to grant some permissions, such as overlay, accessibility, or storage. These permissions are needed for the app to work properly. For example, overlay permission allows the app to display a floating widget on your screen that you can use to control the auto clicker. Accessibility permission allows the app to simulate taps on your screen. Storage permission allows the app to save your settings and preferences.</p>
-<h3>Configure the settings according to your preferences and needs</h3>
-<p>The auto clicker app has various settings that you can adjust according to your preferences and needs. For example, you can:</p>
-<ul>
-<li>Set the click speed, interval, duration, or location.</li>
-<li>Choose the number of clicks, the delay between clicks, the swipe direction, or other parameters.</li>
-<li>Select a single point or multiple points for clicking.</li>
-<li>Create a custom script or a loop for complex clicking patterns.</li>
-<li>Save and load your configurations for future use.</li>
-</ul>
-<p>You can access these settings by tapping on the floating widget or the app icon. You can also use shortcuts or gestures to access them quickly.</p>
-<h3>Start and stop the auto clicker with a simple gesture or a button</h3>
-<p>Once you have configured your settings, you can start and stop the auto clicker with a simple gesture or a button. For example, you can:</p>
-<ul>
-<li>Tap on the play button on the floating widget or the app icon.</li>
-<li>Shake your device or press the volume buttons.</li>
-<li>Use a notification bar or a home screen widget.</li>
-</ul>
-<p>You can also pause and resume the auto clicker at any time. You can monitor the status of the auto clicker by looking at the floating widget or the notification bar.</p>
-<h2>What are the benefits and drawbacks of using an auto clicker app on your Android device</h2>
-<h3>Benefits: save time, avoid fatigue, improve performance, and have fun</h3>
-<p>Using an auto clicker app on your Android device can have many benefits. For example, you can:</p>
-<ul>
-<li>Save time by automating tasks that involve clicking.</li>
-<li>Avoid fatigue by reducing strain on your fingers, wrists, or eyes.</li>
-<li>Improve performance by achieving faster, longer, or more accurate clicks.</li>
-<li>Have fun by exploring new possibilities or challenges in games or apps.</li>
-</ul>
-<h3>Drawbacks: consume battery, violate terms of service, and risk security issues</h3>
-<p>However, using an auto clicker app on your Android device can also have some drawbacks. For example, you may:</p>
-<ul>
-<li>Consume battery by running the app in the background or generating more clicks.</li>
-<li>Violate terms of service by cheating or exploiting games or apps that prohibit using auto clickers.</li>
-<li>Risk security issues by installing apk files from unknown or untrusted sources or granting permissions to malicious apps.</li>
-</ul>
- <h2>Conclusion and FAQs</h2>
- <p>In conclusion, an auto clicker app is a tool that simulates taps on your screen. You can use it for various purposes, such as gaming, testing, or productivity. To download and install an auto clicker app on your Android device, you need to find a reliable source for the apk file, enable unknown sources on your device settings, and tap on the apk file. To use an auto clicker app on your Android device, you need to launch it, grant permissions, configure settings, and start and stop it. Using an auto clicker app can have benefits and drawbacks, so you should weigh them carefully before using it.</p>
- <p>If you have any questions about auto clicker download apk, here are some FAQs that may help you:</p>
- <table style="border: 1px solid black;">
-<tr><td><b>Q: How do I uninstall an auto clicker app from my Android device?</b></td <td><b>A: To uninstall an auto clicker app from your Android device, you can follow these steps:</b></td></tr>
-<tr><td>
-<ol>
-<li>Go to Settings > Apps > Auto clicker app.</li>
-<li>Tap on Uninstall and confirm.</li>
-<li>Alternatively, you can also long-press on the app icon and drag it to the Uninstall option.</li>
-</ol>
-</td></tr>
-<tr><td><b>Q: How do I know if an auto clicker app is safe to use?</b></td><td><b>A: To know if an auto clicker app is safe to use, you can check the following factors:</b></td></tr>
-<tr><td>
-<ul>
-<li>The source of the apk file. You should download the apk file from a reputable website, such as Google Play Store or APKPure. You should also scan the apk file with an antivirus app before installing it.</li>
-<li>The permissions of the app. You should review the permissions that the app requests and only grant those that are necessary and reasonable. You should also revoke any permissions that you are not comfortable with.</li>
-<li>The reviews and ratings of the app. You should read the reviews and ratings of the app from other users and see if they have any complaints or issues with the app. You should also avoid apps that have low ratings or negative reviews.</li>
-</ul>
-</td></tr>
-<tr><td><b>Q: How do I stop an auto clicker app from running in the background?</b></td><td><b>A: To stop an auto clicker app from running in the background, you can follow these steps:</b></td></tr>
-<tr><td>
-<ol>
-<li>Go to Settings > Apps > Auto clicker app.</li>
-<li>Tap on Force stop and confirm.</li>
-<li>Alternatively, you can also swipe down the notification bar and tap on the stop button of the auto clicker app.</li>
-</ol>
-</td></tr>
-<tr><td><b>Q: How do I adjust the click speed, interval, duration, or location of an auto clicker app?</b></td><td><b>A: To adjust the click speed, interval, duration, or location of an auto clicker app, you can follow these steps:</b></td></tr>
-<tr><td>
-<ol>
-<li>Launch the auto clicker app and tap on the floating widget or the app icon.</li>
-<li>Tap on the settings icon and access the options for click speed, interval, duration, or location.</li>
-<li>Use the sliders, buttons, or input fields to adjust the values according to your preferences and needs.</li>
-<li>Tap on Save or Apply to confirm your changes.</li>
-</ol>
-</td></tr>
-<tr><td><b>Q: How do I create a custom script or a loop for complex clicking patterns with an auto clicker app?</b></td><td><b>A: To create a custom script or a loop for complex clicking patterns with an auto clicker app, you can follow these steps:</b></td></tr>
-<tr><td>
-<ol>
-<li>Launch the auto clicker app and tap on the floating widget or the app icon.</li>
-<li>Tap on the script icon and access the options for creating a custom script or a loop.</li>
-<li>Select a single point or multiple points for clicking and configure their settings.</li>
-<li>Add commands, conditions, or variables to control the flow of the script or loop.</li>
-<li>Tap on Save or Run to confirm your script or loop.</li>
-</ol>
- </table>
- : https://apkpure.com/</p> 197e85843d<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/fffiloni/zeroscope-XL/share_btn.py b/spaces/fffiloni/zeroscope-XL/share_btn.py
deleted file mode 100644
index 7f860b1933f5b9fcf050298de18be10d44605a16..0000000000000000000000000000000000000000
--- a/spaces/fffiloni/zeroscope-XL/share_btn.py
+++ /dev/null
@@ -1,72 +0,0 @@
-community_icon_html = """<svg id="share-btn-share-icon" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32">
-    <path d="M20.6081 3C21.7684 3 22.8053 3.49196 23.5284 4.38415C23.9756 4.93678 24.4428 5.82749 24.4808 7.16133C24.9674 7.01707 25.4353 6.93643 25.8725 6.93643C26.9833 6.93643 27.9865 7.37587 28.696 8.17411C29.6075 9.19872 30.0124 10.4579 29.8361 11.7177C29.7523 12.3177 29.5581 12.8555 29.2678 13.3534C29.8798 13.8646 30.3306 14.5763 30.5485 15.4322C30.719 16.1032 30.8939 17.5006 29.9808 18.9403C30.0389 19.0342 30.0934 19.1319 30.1442 19.2318C30.6932 20.3074 30.7283 21.5229 30.2439 22.6548C29.5093 24.3704 27.6841 25.7219 24.1397 27.1727C21.9347 28.0753 19.9174 28.6523 19.8994 28.6575C16.9842 29.4379 14.3477 29.8345 12.0653 29.8345C7.87017 29.8345 4.8668 28.508 3.13831 25.8921C0.356375 21.6797 0.754104 17.8269 4.35369 14.1131C6.34591 12.058 7.67023 9.02782 7.94613 8.36275C8.50224 6.39343 9.97271 4.20438 12.4172 4.20438H12.4179C12.6236 4.20438 12.8314 4.2214 13.0364 4.25468C14.107 4.42854 15.0428 5.06476 15.7115 6.02205C16.4331 5.09583 17.134 4.359 17.7682 3.94323C18.7242 3.31737 19.6794 3 20.6081 3ZM20.6081 5.95917C20.2427 5.95917 19.7963 6.1197 19.3039 6.44225C17.7754 7.44319 14.8258 12.6772 13.7458 14.7131C13.3839 15.3952 12.7655 15.6837 12.2086 15.6837C11.1036 15.6837 10.2408 14.5497 12.1076 13.1085C14.9146 10.9402 13.9299 7.39584 12.5898 7.1776C12.5311 7.16799 12.4731 7.16355 12.4172 7.16355C11.1989 7.16355 10.6615 9.33114 10.6615 9.33114C10.6615 9.33114 9.0863 13.4148 6.38031 16.206C3.67434 18.998 3.5346 21.2388 5.50675 24.2246C6.85185 26.2606 9.42666 26.8753 12.0653 26.8753C14.8021 26.8753 17.6077 26.2139 19.1799 25.793C19.2574 25.7723 28.8193 22.984 27.6081 20.6107C27.4046 20.212 27.0693 20.0522 26.6471 20.0522C24.9416 20.0522 21.8393 22.6726 20.5057 22.6726C20.2076 22.6726 19.9976 22.5416 19.9116 22.222C19.3433 20.1173 28.552 19.2325 27.7758 16.1839C27.639 15.6445 27.2677 15.4256 26.746 15.4263C24.4923 15.4263 19.4358 19.5181 18.3759 19.5181C18.2949 19.5181 18.2368 19.4937 18.2053 19.4419C17.6743 18.557 17.9653 17.9394 21.7082 15.6009C25.4511 13.2617 28.0783 11.8545 26.5841 10.1752C26.4121 9.98141 26.1684 9.8956 25.8725 9.8956C23.6001 9.89634 18.2311 14.9403 18.2311 14.9403C18.2311 14.9403 16.7821 16.496 15.9057 16.496C15.7043 16.496 15.533 16.4139 15.4169 16.2112C14.7956 15.1296 21.1879 10.1286 21.5484 8.06535C21.7928 6.66715 21.3771 5.95917 20.6081 5.95917Z" fill="#FF9D00"></path>
-    <path d="M5.50686 24.2246C3.53472 21.2387 3.67446 18.9979 6.38043 16.206C9.08641 13.4147 10.6615 9.33111 10.6615 9.33111C10.6615 9.33111 11.2499 6.95933 12.59 7.17757C13.93 7.39581 14.9139 10.9401 12.1069 13.1084C9.29997 15.276 12.6659 16.7489 13.7459 14.713C14.8258 12.6772 17.7747 7.44316 19.304 6.44221C20.8326 5.44128 21.9089 6.00204 21.5484 8.06532C21.188 10.1286 14.795 15.1295 15.4171 16.2118C16.0391 17.2934 18.2312 14.9402 18.2312 14.9402C18.2312 14.9402 25.0907 8.49588 26.5842 10.1752C28.0776 11.8545 25.4512 13.2616 21.7082 15.6008C17.9646 17.9393 17.6744 18.557 18.2054 19.4418C18.7372 20.3266 26.9998 13.1351 27.7759 16.1838C28.5513 19.2324 19.3434 20.1173 19.9117 22.2219C20.48 24.3274 26.3979 18.2382 27.6082 20.6107C28.8193 22.9839 19.2574 25.7722 19.18 25.7929C16.0914 26.62 8.24723 28.3726 5.50686 24.2246Z" fill="#FFD21E"></path>
-</svg>"""
-
-loading_icon_html = """<svg id="share-btn-loading-icon" style="display:none;" class="animate-spin"
-   style="color: #ffffff; 
-"
-   xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" fill="none" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 24 24"><circle style="opacity: 0.25;" cx="12" cy="12" r="10" stroke="white" stroke-width="4"></circle><path style="opacity: 0.75;" fill="white" d="M4 12a8 8 0 018-8V0C5.373 0 0 5.373 0 12h4zm2 5.291A7.962 7.962 0 014 12H0c0 3.042 1.135 5.824 3 7.938l3-2.647z"></path></svg>"""
-
-share_js = """async () => {
-	async function uploadFile(file){
-		const UPLOAD_URL = 'https://huggingface.co/uploads';
-		const response = await fetch(UPLOAD_URL, {
-			method: 'POST',
-			headers: {
-				'Content-Type': file.type,
-				'X-Requested-With': 'XMLHttpRequest',
-			},
-			body: file, /// <- File inherits from Blob
-		});
-		const url = await response.text();
-		return url;
-	}
-	
-    async function getVideoBlobFile(videoEL){
-        const res = await fetch(videoEL.src);
-        const blob = await res.blob();
-        const videoId = Date.now() % 200;
-        const fileName = `vid-zeroscope-${{videoId}}.mp4`;
-        const videoBlob = new File([blob], fileName, { type: 'video/mp4' });
-        console.log(videoBlob);
-        return videoBlob;
-	}
-    
-    const gradioEl = document.querySelector("gradio-app").shadowRoot || document.querySelector('body > gradio-app');
-    const captionTxt = gradioEl.querySelector('#prompt-in textarea').value;
-    const outputVideo = gradioEl.querySelector('#video-output video');
-
-    
-    const shareBtnEl = gradioEl.querySelector('#share-btn');
-    const shareIconEl = gradioEl.querySelector('#share-btn-share-icon');
-    const loadingIconEl = gradioEl.querySelector('#share-btn-loading-icon');
-    if(!outputVideo){
-        return;
-    };
-    shareBtnEl.style.pointerEvents = 'none';
-    shareIconEl.style.display = 'none';
-    loadingIconEl.style.removeProperty('display');
-    
-    
-    const videoOutFile = await getVideoBlobFile(outputVideo);
-	const dataOutputVid = await uploadFile(videoOutFile);
-    
-    const descriptionMd = `
-#### Prompt:
-${captionTxt}
-
-#### Zeroscope XL video result:
-${dataOutputVid}
-
-`;
-    const params = new URLSearchParams({
-        title: captionTxt,
-        description: descriptionMd,
-    });
-	const paramsStr = params.toString();
-	window.open(`https://huggingface.co/spaces/fffiloni/zeroscope/discussions/new?${paramsStr}`, '_blank');
-    shareBtnEl.style.removeProperty('pointer-events');
-    shareIconEl.style.removeProperty('display');
-    loadingIconEl.style.display = 'none';
-}"""
\ No newline at end of file
diff --git a/spaces/fiyen/YangyangChatGPT/encrypt_it.py b/spaces/fiyen/YangyangChatGPT/encrypt_it.py
deleted file mode 100644
index 81fd8c8c13cfbdf44aa4d52dea6a07432e237b8b..0000000000000000000000000000000000000000
--- a/spaces/fiyen/YangyangChatGPT/encrypt_it.py
+++ /dev/null
@@ -1,46 +0,0 @@
-import hashlib
-from cryptography.fernet import Fernet
-import base64
-
-# 生成哈希密钥
-def generate_key(username, password):
-    key = username.encode() + password.encode()
-    hash_key = hashlib.sha256(key).hexdigest().encode()[:32]
-    base64_key = base64.urlsafe_b64encode(hash_key)
-    return base64_key
-
-# 加密函数，将明文加密成密文
-def encrypt(message, key):
-    cipher = Fernet(key)
-    ciphertext = cipher.encrypt(message)
-    with open('encrypted.bin', 'wb') as f:
-        f.write(ciphertext)
-    return ciphertext
-
-# 解密函数，将密文解密成明文
-def decrypt(ciphertext, key):
-    cipher = Fernet(key)
-    plaintext = cipher.decrypt(ciphertext)
-    return plaintext
-
-
-if __name__ == "__main__":
-    # 测试加解密函数
-    username = input('请输入用户名：')
-    password = input('请输入密码：')
-
-    # 生成哈希密钥
-    key = generate_key(username, password)
-
-    # # 加密数据并保存到文件中
-    # message = b'Hello, World!'
-    # ciphertext = encrypt(message, key)
-    # with open('encrypted.bin', 'wb') as f:
-    #     f.write(ciphertext)
-
-    # 解密文件并输出明文数据
-    with open('encrypted.bin', 'rb') as f:
-        ciphertext = f.read()
-    key = generate_key(username, password)
-    plaintext = decrypt(ciphertext, key)
-    print(f'{username}的私密信息：{plaintext.decode()}')
diff --git a/spaces/fracapuano/NebulOS/src/search/__init__.py b/spaces/fracapuano/NebulOS/src/search/__init__.py
deleted file mode 100644
index 9d92928c5634e2962b9a3a56865a17579c753aac..0000000000000000000000000000000000000000
--- a/spaces/fracapuano/NebulOS/src/search/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-from .ga import * 
\ No newline at end of file
diff --git a/spaces/fun-research/FC-CLIP/fcclip/data/dataset_mappers/coco_instance_new_baseline_dataset_mapper.py b/spaces/fun-research/FC-CLIP/fcclip/data/dataset_mappers/coco_instance_new_baseline_dataset_mapper.py
deleted file mode 100644
index e64af2b51009d0398a1b6253a8a763c641547f59..0000000000000000000000000000000000000000
--- a/spaces/fun-research/FC-CLIP/fcclip/data/dataset_mappers/coco_instance_new_baseline_dataset_mapper.py
+++ /dev/null
@@ -1,189 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-# Modified by Bowen Cheng from https://github.com/facebookresearch/detr/blob/master/d2/detr/dataset_mapper.py
-import copy
-import logging
-
-import numpy as np
-import torch
-
-from detectron2.config import configurable
-from detectron2.data import detection_utils as utils
-from detectron2.data import transforms as T
-from detectron2.data.transforms import TransformGen
-from detectron2.structures import BitMasks, Instances
-
-from pycocotools import mask as coco_mask
-
-__all__ = ["COCOInstanceNewBaselineDatasetMapper"]
-
-
-def convert_coco_poly_to_mask(segmentations, height, width):
-    masks = []
-    for polygons in segmentations:
-        rles = coco_mask.frPyObjects(polygons, height, width)
-        mask = coco_mask.decode(rles)
-        if len(mask.shape) < 3:
-            mask = mask[..., None]
-        mask = torch.as_tensor(mask, dtype=torch.uint8)
-        mask = mask.any(dim=2)
-        masks.append(mask)
-    if masks:
-        masks = torch.stack(masks, dim=0)
-    else:
-        masks = torch.zeros((0, height, width), dtype=torch.uint8)
-    return masks
-
-
-def build_transform_gen(cfg, is_train):
-    """
-    Create a list of default :class:`Augmentation` from config.
-    Now it includes resizing and flipping.
-    Returns:
-        list[Augmentation]
-    """
-    assert is_train, "Only support training augmentation"
-    image_size = cfg.INPUT.IMAGE_SIZE
-    min_scale = cfg.INPUT.MIN_SCALE
-    max_scale = cfg.INPUT.MAX_SCALE
-
-    augmentation = []
-
-    if cfg.INPUT.RANDOM_FLIP != "none":
-        augmentation.append(
-            T.RandomFlip(
-                horizontal=cfg.INPUT.RANDOM_FLIP == "horizontal",
-                vertical=cfg.INPUT.RANDOM_FLIP == "vertical",
-            )
-        )
-
-    augmentation.extend([
-        T.ResizeScale(
-            min_scale=min_scale, max_scale=max_scale, target_height=image_size, target_width=image_size
-        ),
-        T.FixedSizeCrop(crop_size=(image_size, image_size)),
-    ])
-
-    return augmentation
-
-
-# This is specifically designed for the COCO dataset.
-class COCOInstanceNewBaselineDatasetMapper:
-    """
-    A callable which takes a dataset dict in Detectron2 Dataset format,
-    and map it into a format used by MaskFormer.
-
-    This dataset mapper applies the same transformation as DETR for COCO panoptic segmentation.
-
-    The callable currently does the following:
-
-    1. Read the image from "file_name"
-    2. Applies geometric transforms to the image and annotation
-    3. Find and applies suitable cropping to the image and annotation
-    4. Prepare image and annotation to Tensors
-    """
-
-    @configurable
-    def __init__(
-        self,
-        is_train=True,
-        *,
-        tfm_gens,
-        image_format,
-    ):
-        """
-        NOTE: this interface is experimental.
-        Args:
-            is_train: for training or inference
-            augmentations: a list of augmentations or deterministic transforms to apply
-            tfm_gens: data augmentation
-            image_format: an image format supported by :func:`detection_utils.read_image`.
-        """
-        self.tfm_gens = tfm_gens
-        logging.getLogger(__name__).info(
-            "[COCOInstanceNewBaselineDatasetMapper] Full TransformGens used in training: {}".format(str(self.tfm_gens))
-        )
-
-        self.img_format = image_format
-        self.is_train = is_train
-    
-    @classmethod
-    def from_config(cls, cfg, is_train=True):
-        # Build augmentation
-        tfm_gens = build_transform_gen(cfg, is_train)
-
-        ret = {
-            "is_train": is_train,
-            "tfm_gens": tfm_gens,
-            "image_format": cfg.INPUT.FORMAT,
-        }
-        return ret
-
-    def __call__(self, dataset_dict):
-        """
-        Args:
-            dataset_dict (dict): Metadata of one image, in Detectron2 Dataset format.
-
-        Returns:
-            dict: a format that builtin models in detectron2 accept
-        """
-        dataset_dict = copy.deepcopy(dataset_dict)  # it will be modified by code below
-        image = utils.read_image(dataset_dict["file_name"], format=self.img_format)
-        utils.check_image_size(dataset_dict, image)
-
-        # TODO: get padding mask
-        # by feeding a "segmentation mask" to the same transforms
-        padding_mask = np.ones(image.shape[:2])
-
-        image, transforms = T.apply_transform_gens(self.tfm_gens, image)
-        # the crop transformation has default padding value 0 for segmentation
-        padding_mask = transforms.apply_segmentation(padding_mask)
-        padding_mask = ~ padding_mask.astype(bool)
-
-        image_shape = image.shape[:2]  # h, w
-
-        # Pytorch's dataloader is efficient on torch.Tensor due to shared-memory,
-        # but not efficient on large generic data structures due to the use of pickle & mp.Queue.
-        # Therefore it's important to use torch.Tensor.
-        dataset_dict["image"] = torch.as_tensor(np.ascontiguousarray(image.transpose(2, 0, 1)))
-        dataset_dict["padding_mask"] = torch.as_tensor(np.ascontiguousarray(padding_mask))
-
-        if not self.is_train:
-            # USER: Modify this if you want to keep them for some reason.
-            dataset_dict.pop("annotations", None)
-            return dataset_dict
-
-        if "annotations" in dataset_dict:
-            # USER: Modify this if you want to keep them for some reason.
-            for anno in dataset_dict["annotations"]:
-                # Let's always keep mask
-                # if not self.mask_on:
-                #     anno.pop("segmentation", None)
-                anno.pop("keypoints", None)
-
-            # USER: Implement additional transformations if you have other types of data
-            annos = [
-                utils.transform_instance_annotations(obj, transforms, image_shape)
-                for obj in dataset_dict.pop("annotations")
-                if obj.get("iscrowd", 0) == 0
-            ]
-            # NOTE: does not support BitMask due to augmentation
-            # Current BitMask cannot handle empty objects
-            instances = utils.annotations_to_instances(annos, image_shape)
-            # After transforms such as cropping are applied, the bounding box may no longer
-            # tightly bound the object. As an example, imagine a triangle object
-            # [(0,0), (2,0), (0,2)] cropped by a box [(1,0),(2,2)] (XYXY format). The tight
-            # bounding box of the cropped triangle should be [(1,0),(2,1)], which is not equal to
-            # the intersection of original bounding box and the cropping box.
-            instances.gt_boxes = instances.gt_masks.get_bounding_boxes()
-            # Need to filter empty instances first (due to augmentation)
-            instances = utils.filter_empty_instances(instances)
-            # Generate masks from polygon
-            h, w = instances.image_size
-            # image_size_xyxy = torch.as_tensor([w, h, w, h], dtype=torch.float)
-            if hasattr(instances, 'gt_masks'):
-                gt_masks = instances.gt_masks
-                gt_masks = convert_coco_poly_to_mask(gt_masks.polygons, h, w)
-                instances.gt_masks = gt_masks
-            dataset_dict["instances"] = instances
-
-        return dataset_dict
diff --git a/spaces/fun-research/FC-CLIP/fcclip/fcclip.py b/spaces/fun-research/FC-CLIP/fcclip/fcclip.py
deleted file mode 100644
index ea71845322ae644d49e04224b3ee347db4b67cf3..0000000000000000000000000000000000000000
--- a/spaces/fun-research/FC-CLIP/fcclip/fcclip.py
+++ /dev/null
@@ -1,586 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-from typing import Tuple
-
-import torch
-from torch import nn
-from torch.nn import functional as F
-
-from detectron2.config import configurable
-from detectron2.data import MetadataCatalog
-from detectron2.modeling import META_ARCH_REGISTRY, build_backbone, build_sem_seg_head
-from detectron2.modeling.backbone import Backbone
-from detectron2.modeling.postprocessing import sem_seg_postprocess
-from detectron2.structures import Boxes, ImageList, Instances, BitMasks
-from detectron2.utils.memory import retry_if_cuda_oom
-
-from .modeling.criterion import SetCriterion
-from .modeling.matcher import HungarianMatcher
-
-
-from .modeling.transformer_decoder.fcclip_transformer_decoder import MaskPooling, get_classification_logits
-import os
-VILD_PROMPT = [
-    "a photo of a {}.",
-    "This is a photo of a {}",
-    "There is a {} in the scene",
-    "There is the {} in the scene",
-    "a photo of a {} in the scene",
-    "a photo of a small {}.",
-    "a photo of a medium {}.",
-    "a photo of a large {}.",
-    "This is a photo of a small {}.",
-    "This is a photo of a medium {}.",
-    "This is a photo of a large {}.",
-    "There is a small {} in the scene.",
-    "There is a medium {} in the scene.",
-    "There is a large {} in the scene.",
-]
-
-def split_labels(x):
-    res = []
-    for x_ in x:
-        x_ = x_.replace(', ', ',')
-        x_ = x_.split(',') # there can be multiple synonyms for single class
-        res.append(x_)
-    return res
-
-def fill_all_templates_ensemble(x_=''):
-    res = []
-    for x in x_:
-        for template in VILD_PROMPT:
-            res.append(template.format(x))
-    return res, len(res) // len(VILD_PROMPT)
-
-@META_ARCH_REGISTRY.register()
-class FCCLIP(nn.Module):
-    """
-    Main class for mask classification semantic segmentation architectures.
-    """
-
-    @configurable
-    def __init__(
-        self,
-        *,
-        backbone: Backbone,
-        sem_seg_head: nn.Module,
-        criterion: nn.Module,
-        num_queries: int,
-        object_mask_threshold: float,
-        overlap_threshold: float,
-        train_metadata,
-        test_metadata,
-        size_divisibility: int,
-        sem_seg_postprocess_before_inference: bool,
-        pixel_mean: Tuple[float],
-        pixel_std: Tuple[float],
-        # inference
-        semantic_on: bool,
-        panoptic_on: bool,
-        instance_on: bool,
-        test_topk_per_image: int,
-        # FC-CLIP
-        geometric_ensemble_alpha: float,
-        geometric_ensemble_beta: float,
-    ):
-        """
-        Args:
-            backbone: a backbone module, must follow detectron2's backbone interface
-            sem_seg_head: a module that predicts semantic segmentation from backbone features
-            criterion: a module that defines the loss
-            num_queries: int, number of queries
-            object_mask_threshold: float, threshold to filter query based on classification score
-                for panoptic segmentation inference
-            overlap_threshold: overlap threshold used in general inference for panoptic segmentation
-            metadata: dataset meta, get `thing` and `stuff` category names for panoptic
-                segmentation inference
-            size_divisibility: Some backbones require the input height and width to be divisible by a
-                specific integer. We can use this to override such requirement.
-            sem_seg_postprocess_before_inference: whether to resize the prediction back
-                to original input size before semantic segmentation inference or after.
-                For high-resolution dataset like Mapillary, resizing predictions before
-                inference will cause OOM error.
-            pixel_mean, pixel_std: list or tuple with #channels element, representing
-                the per-channel mean and std to be used to normalize the input image
-            semantic_on: bool, whether to output semantic segmentation prediction
-            instance_on: bool, whether to output instance segmentation prediction
-            panoptic_on: bool, whether to output panoptic segmentation prediction
-            test_topk_per_image: int, instance segmentation parameter, keep topk instances per image
-        """
-        super().__init__()
-        self.backbone = backbone
-        self.sem_seg_head = sem_seg_head
-        self.criterion = criterion
-        self.num_queries = num_queries
-        self.overlap_threshold = overlap_threshold
-        self.object_mask_threshold = object_mask_threshold
-        self.train_metadata = train_metadata
-        self.test_metadata = test_metadata
-        if size_divisibility < 0:
-            # use backbone size_divisibility if not set
-            size_divisibility = self.backbone.size_divisibility
-        self.size_divisibility = size_divisibility
-        self.sem_seg_postprocess_before_inference = sem_seg_postprocess_before_inference
-        self.register_buffer("pixel_mean", torch.Tensor(pixel_mean).view(-1, 1, 1), False)
-        self.register_buffer("pixel_std", torch.Tensor(pixel_std).view(-1, 1, 1), False)
-
-        # additional args
-        self.semantic_on = semantic_on
-        self.instance_on = instance_on
-        self.panoptic_on = panoptic_on
-        self.test_topk_per_image = test_topk_per_image
-
-        if not self.semantic_on:
-            assert self.sem_seg_postprocess_before_inference
-
-        # FC-CLIP args
-        self.mask_pooling = MaskPooling()
-        self.geometric_ensemble_alpha = geometric_ensemble_alpha
-        self.geometric_ensemble_beta = geometric_ensemble_beta
-
-        self.train_text_classifier = None
-        self.test_text_classifier = None
-        self.void_embedding = nn.Embedding(1, backbone.dim_latent) # use this for void
-
-        _, self.train_num_templates, self.train_class_names = self.prepare_class_names_from_metadata(train_metadata, train_metadata)
-        self.category_overlapping_mask, self.test_num_templates, self.test_class_names = self.prepare_class_names_from_metadata(test_metadata, train_metadata)
-
-        self.demo_all_text_embedding_cache = {}
-        # This consists of COCO, ADE20K, LVIS
-        if os.path.exists("demo_all_text_embedding_cache.pth"):
-            # key: str of class name, value: tensor in shape of C
-            self.demo_all_text_embedding_cache = torch.load("demo_all_text_embedding_cache.pth", map_location=self.device)
-            self.demo_all_text_embedding_cache = {k:v.to(self.device) for k,v in self.demo_all_text_embedding_cache.items()}
-
-
-    def prepare_class_names_from_metadata(self, metadata, train_metadata):
-        # get text classifier
-        try:
-            class_names = split_labels(metadata.stuff_classes) # it includes both thing and stuff
-            train_class_names = split_labels(train_metadata.stuff_classes)
-        except:
-            # this could be for insseg, where only thing_classes are available
-            class_names = split_labels(metadata.thing_classes)
-            train_class_names = split_labels(train_metadata.thing_classes)
-        train_class_names = {l for label in train_class_names for l in label}
-        category_overlapping_list = []
-        for test_class_names in class_names:
-            is_overlapping = not set(train_class_names).isdisjoint(set(test_class_names))
-            category_overlapping_list.append(is_overlapping)
-        category_overlapping_mask = torch.tensor(
-            category_overlapping_list, dtype=torch.long)
-       
-        num_templates = []
-        templated_class_names = []
-        for x in class_names:
-            templated_classes, templated_classes_num = fill_all_templates_ensemble(x)
-            templated_class_names += templated_classes
-            num_templates.append(templated_classes_num) # how many templates for current classes
-        class_names = templated_class_names
-        #print("text for classification:", class_names)
-        return category_overlapping_mask, num_templates, class_names
-
-    def set_metadata(self, metadata):
-        if set(self.test_metadata.stuff_classes) != set(metadata.stuff_classes):
-            print("setting test metadata:", metadata)
-            self.test_metadata = metadata
-            self.category_overlapping_mask, self.test_num_templates, self.test_class_names = self.prepare_class_names_from_metadata(metadata, self.train_metadata)
-            self.test_text_classifier = None
-            print("text for classification:", self.test_class_names)
-        return
-
-    def get_text_classifier(self):
-        if self.training:
-            if self.train_text_classifier is None:
-                text_classifier = []
-                # this is needed to avoid oom, which may happen when num of class is large
-                bs = 128
-                for idx in range(0, len(self.train_class_names), bs):
-                    text_classifier.append(self.backbone.get_text_classifier(self.train_class_names[idx:idx+bs], self.device).detach())
-                text_classifier = torch.cat(text_classifier, dim=0)
-
-                # average across templates and normalization.
-                text_classifier /= text_classifier.norm(dim=-1, keepdim=True)
-                text_classifier = text_classifier.reshape(text_classifier.shape[0]//len(VILD_PROMPT), len(VILD_PROMPT), text_classifier.shape[-1]).mean(1)
-                text_classifier /= text_classifier.norm(dim=-1, keepdim=True)
-                self.train_text_classifier = text_classifier
-            return self.train_text_classifier, self.train_num_templates
-        else:
-            if self.test_text_classifier is None:
-                try:
-                    nontemplated_class_names = split_labels(self.test_metadata.stuff_classes) # it includes both thing and stuff 
-                except:
-                    # this could be for insseg, where only thing_classes are available
-                    nontemplated_class_names = split_labels(self.test_metadata.thing_classes)
-                print("nontemplated_class_names:", nontemplated_class_names)
-                text2classifier = {}
-                test_class_names = []
-                uncached_class_name = []
-                text_classifier = []
-                # exclude those already in cache
-                for class_names in nontemplated_class_names:
-                    if not isinstance(class_names, list):
-                        class_names = [class_names]
-                    for class_name in class_names:
-                        if class_name in self.demo_all_text_embedding_cache:
-                            text2classifier[class_name] = self.demo_all_text_embedding_cache[class_name].to(self.device)
-                        else:
-                            test_class_names += fill_all_templates_ensemble([class_name])[0]
-                            uncached_class_name.append(class_name)
-                print("Uncached texts:", len(uncached_class_name), uncached_class_name, test_class_names)
-                # this is needed to avoid oom, which may happen when num of class is large
-                bs = 128
-                for idx in range(0, len(test_class_names), bs):
-                    text_classifier.append(self.backbone.get_text_classifier(test_class_names[idx:idx+bs], self.device).detach())
-
-                if len(text_classifier) > 0:
-                    text_classifier = torch.cat(text_classifier, dim=0)
-                    # average across templates and normalization.
-                    text_classifier /= text_classifier.norm(dim=-1, keepdim=True)
-                    text_classifier = text_classifier.reshape(text_classifier.shape[0]//len(VILD_PROMPT), len(VILD_PROMPT), text_classifier.shape[-1]).mean(1)
-                    text_classifier /= text_classifier.norm(dim=-1, keepdim=True)
-                    assert text_classifier.shape[0] == len(uncached_class_name)
-                    for idx in range(len(uncached_class_name)):
-                        self.demo_all_text_embedding_cache[uncached_class_name[idx]] = text_classifier[idx]
-                        text2classifier[uncached_class_name[idx]] = text_classifier[idx]
-                    #torch.save({k:v for k, v in self.demo_all_text_embedding_cache.items()}, "demo_all_text_embedding_cache.pth")
-
-                text_classifier = []
-                for class_names in nontemplated_class_names:
-                    for text in class_names:
-                        text_classifier.append(text2classifier[text].to(self.device))
-                text_classifier = torch.stack(text_classifier, dim=0).to(self.device)
-                self.test_text_classifier = text_classifier
-            return self.test_text_classifier, self.test_num_templates
-
-    @classmethod
-    def from_config(cls, cfg):
-        backbone = build_backbone(cfg)
-        sem_seg_head = build_sem_seg_head(cfg, backbone.output_shape())
-
-        # Loss parameters:
-        deep_supervision = cfg.MODEL.MASK_FORMER.DEEP_SUPERVISION
-        no_object_weight = cfg.MODEL.MASK_FORMER.NO_OBJECT_WEIGHT
-
-        # loss weights
-        class_weight = cfg.MODEL.MASK_FORMER.CLASS_WEIGHT
-        dice_weight = cfg.MODEL.MASK_FORMER.DICE_WEIGHT
-        mask_weight = cfg.MODEL.MASK_FORMER.MASK_WEIGHT
-
-        # building criterion
-        matcher = HungarianMatcher(
-            cost_class=class_weight,
-            cost_mask=mask_weight,
-            cost_dice=dice_weight,
-            num_points=cfg.MODEL.MASK_FORMER.TRAIN_NUM_POINTS,
-        )
-
-        weight_dict = {"loss_ce": class_weight, "loss_mask": mask_weight, "loss_dice": dice_weight}
-
-        if deep_supervision:
-            dec_layers = cfg.MODEL.MASK_FORMER.DEC_LAYERS
-            aux_weight_dict = {}
-            for i in range(dec_layers - 1):
-                aux_weight_dict.update({k + f"_{i}": v for k, v in weight_dict.items()})
-            weight_dict.update(aux_weight_dict)
-
-        losses = ["labels", "masks"]
-
-        criterion = SetCriterion(
-            sem_seg_head.num_classes,
-            matcher=matcher,
-            weight_dict=weight_dict,
-            eos_coef=no_object_weight,
-            losses=losses,
-            num_points=cfg.MODEL.MASK_FORMER.TRAIN_NUM_POINTS,
-            oversample_ratio=cfg.MODEL.MASK_FORMER.OVERSAMPLE_RATIO,
-            importance_sample_ratio=cfg.MODEL.MASK_FORMER.IMPORTANCE_SAMPLE_RATIO,
-        )
-
-        return {
-            "backbone": backbone,
-            "sem_seg_head": sem_seg_head,
-            "criterion": criterion,
-            "num_queries": cfg.MODEL.MASK_FORMER.NUM_OBJECT_QUERIES,
-            "object_mask_threshold": cfg.MODEL.MASK_FORMER.TEST.OBJECT_MASK_THRESHOLD,
-            "overlap_threshold": cfg.MODEL.MASK_FORMER.TEST.OVERLAP_THRESHOLD,
-            "train_metadata": MetadataCatalog.get(cfg.DATASETS.TRAIN[0]),
-            "test_metadata": MetadataCatalog.get(cfg.DATASETS.TEST[0]),
-            "size_divisibility": cfg.MODEL.MASK_FORMER.SIZE_DIVISIBILITY,
-            "sem_seg_postprocess_before_inference": (
-                cfg.MODEL.MASK_FORMER.TEST.SEM_SEG_POSTPROCESSING_BEFORE_INFERENCE
-                or cfg.MODEL.MASK_FORMER.TEST.PANOPTIC_ON
-                or cfg.MODEL.MASK_FORMER.TEST.INSTANCE_ON
-            ),
-            "pixel_mean": cfg.MODEL.PIXEL_MEAN,
-            "pixel_std": cfg.MODEL.PIXEL_STD,
-            # inference
-            "semantic_on": cfg.MODEL.MASK_FORMER.TEST.SEMANTIC_ON,
-            "instance_on": cfg.MODEL.MASK_FORMER.TEST.INSTANCE_ON,
-            "panoptic_on": cfg.MODEL.MASK_FORMER.TEST.PANOPTIC_ON,
-            "test_topk_per_image": cfg.TEST.DETECTIONS_PER_IMAGE,
-            "geometric_ensemble_alpha": cfg.MODEL.FC_CLIP.GEOMETRIC_ENSEMBLE_ALPHA,
-            "geometric_ensemble_beta": cfg.MODEL.FC_CLIP.GEOMETRIC_ENSEMBLE_BETA,
-        }
-
-    @property
-    def device(self):
-        return self.pixel_mean.device
-
-    def forward(self, batched_inputs):
-        """
-        Args:
-            batched_inputs: a list, batched outputs of :class:`DatasetMapper`.
-                Each item in the list contains the inputs for one image.
-                For now, each item in the list is a dict that contains:
-                   * "image": Tensor, image in (C, H, W) format.
-                   * "instances": per-region ground truth
-                   * Other information that's included in the original dicts, such as:
-                     "height", "width" (int): the output resolution of the model (may be different
-                     from input resolution), used in inference.
-        Returns:
-            list[dict]:
-                each dict has the results for one image. The dict contains the following keys:
-
-                * "sem_seg":
-                    A Tensor that represents the
-                    per-pixel segmentation prediced by the head.
-                    The prediction has shape KxHxW that represents the logits of
-                    each class for each pixel.
-                * "panoptic_seg":
-                    A tuple that represent panoptic output
-                    panoptic_seg (Tensor): of shape (height, width) where the values are ids for each segment.
-                    segments_info (list[dict]): Describe each segment in `panoptic_seg`.
-                        Each dict contains keys "id", "category_id", "isthing".
-        """
-        images = [x["image"].to(self.device) for x in batched_inputs]
-        images = [(x - self.pixel_mean) / self.pixel_std for x in images]
-        images = ImageList.from_tensors(images, self.size_divisibility)
-
-        features = self.backbone(images.tensor)
-        text_classifier, num_templates = self.get_text_classifier()
-        # Append void class weight
-        text_classifier = torch.cat([text_classifier, F.normalize(self.void_embedding.weight, dim=-1)], dim=0)
-        features['text_classifier'] = text_classifier
-        features['num_templates'] = num_templates
-        outputs = self.sem_seg_head(features)
-
-        if self.training:
-            # mask classification target
-            if "instances" in batched_inputs[0]:
-                gt_instances = [x["instances"].to(self.device) for x in batched_inputs]
-                targets = self.prepare_targets(gt_instances, images)
-            else:
-                targets = None
-
-            # bipartite matching-based loss
-            losses = self.criterion(outputs, targets)
-
-            for k in list(losses.keys()):
-                if k in self.criterion.weight_dict:
-                    losses[k] *= self.criterion.weight_dict[k]
-                else:
-                    # remove this loss if not specified in `weight_dict`
-                    losses.pop(k)
-            return losses
-        else:
-            mask_cls_results = outputs["pred_logits"]
-            mask_pred_results = outputs["pred_masks"]
-
-            # We ensemble the pred logits of in-vocab and out-vocab
-            clip_feature = features["clip_vis_dense"]
-            mask_for_pooling = F.interpolate(mask_pred_results, size=clip_feature.shape[-2:],
-                                             mode='bilinear', align_corners=False)
-            pooled_clip_feature = self.mask_pooling(clip_feature, mask_for_pooling)
-            pooled_clip_feature = self.backbone.visual_prediction_forward(pooled_clip_feature)
-            out_vocab_cls_results = get_classification_logits(pooled_clip_feature, text_classifier, self.backbone.clip_model.logit_scale, num_templates)
-            in_vocab_cls_results = mask_cls_results[..., :-1] # remove void
-            out_vocab_cls_results = out_vocab_cls_results[..., :-1] # remove void
-
-            # Reference: https://github.com/NVlabs/ODISE/blob/main/odise/modeling/meta_arch/odise.py#L1506
-            out_vocab_cls_probs = out_vocab_cls_results.softmax(-1)
-            in_vocab_cls_results = in_vocab_cls_results.softmax(-1)
-            category_overlapping_mask = self.category_overlapping_mask.to(self.device)
-            alpha = self.geometric_ensemble_alpha
-            beta = self.geometric_ensemble_beta
-            cls_logits_seen = (
-                (in_vocab_cls_results ** (1 - alpha) * out_vocab_cls_probs**alpha).log()
-                * category_overlapping_mask
-            )
-            cls_logits_unseen = (
-                (in_vocab_cls_results ** (1 - beta) * out_vocab_cls_probs**beta).log()
-                * (1 - category_overlapping_mask)
-            )
-            cls_results = cls_logits_seen + cls_logits_unseen
-
-            # This is used to filtering void predictions.
-            is_void_prob = F.softmax(mask_cls_results, dim=-1)[..., -1:]
-            mask_cls_probs = torch.cat([
-                cls_results.softmax(-1) * (1.0 - is_void_prob),
-                is_void_prob], dim=-1)
-            mask_cls_results = torch.log(mask_cls_probs + 1e-8)
-
-            # upsample masks
-            mask_pred_results = F.interpolate(
-                mask_pred_results,
-                size=(images.tensor.shape[-2], images.tensor.shape[-1]),
-                mode="bilinear",
-                align_corners=False,
-            )
-
-            del outputs
-
-            processed_results = []
-            for mask_cls_result, mask_pred_result, input_per_image, image_size in zip(
-                mask_cls_results, mask_pred_results, batched_inputs, images.image_sizes
-            ):
-                height = input_per_image.get("height", image_size[0])
-                width = input_per_image.get("width", image_size[1])
-                processed_results.append({})
-
-                if self.sem_seg_postprocess_before_inference:
-                    mask_pred_result = retry_if_cuda_oom(sem_seg_postprocess)(
-                        mask_pred_result, image_size, height, width
-                    )
-                    mask_cls_result = mask_cls_result.to(mask_pred_result)
-
-                # semantic segmentation inference
-                if self.semantic_on:
-                    r = retry_if_cuda_oom(self.semantic_inference)(mask_cls_result, mask_pred_result)
-                    if not self.sem_seg_postprocess_before_inference:
-                        r = retry_if_cuda_oom(sem_seg_postprocess)(r, image_size, height, width)
-                    processed_results[-1]["sem_seg"] = r
-
-                # panoptic segmentation inference
-                if self.panoptic_on:
-                    panoptic_r = retry_if_cuda_oom(self.panoptic_inference)(mask_cls_result, mask_pred_result)
-                    processed_results[-1]["panoptic_seg"] = panoptic_r
-                
-                # instance segmentation inference
-                if self.instance_on:
-                    instance_r = retry_if_cuda_oom(self.instance_inference)(mask_cls_result, mask_pred_result)
-                    processed_results[-1]["instances"] = instance_r
-
-            return processed_results
-
-    def prepare_targets(self, targets, images):
-        h_pad, w_pad = images.tensor.shape[-2:]
-        new_targets = []
-        for targets_per_image in targets:
-            # pad gt
-            gt_masks = targets_per_image.gt_masks
-            padded_masks = torch.zeros((gt_masks.shape[0], h_pad, w_pad), dtype=gt_masks.dtype, device=gt_masks.device)
-            padded_masks[:, : gt_masks.shape[1], : gt_masks.shape[2]] = gt_masks
-            new_targets.append(
-                {
-                    "labels": targets_per_image.gt_classes,
-                    "masks": padded_masks,
-                }
-            )
-        return new_targets
-
-    def semantic_inference(self, mask_cls, mask_pred):
-        mask_cls = F.softmax(mask_cls, dim=-1)[..., :-1]
-        mask_pred = mask_pred.sigmoid()
-        semseg = torch.einsum("qc,qhw->chw", mask_cls, mask_pred)
-        return semseg
-
-    def panoptic_inference(self, mask_cls, mask_pred):
-        scores, labels = F.softmax(mask_cls, dim=-1).max(-1)
-        mask_pred = mask_pred.sigmoid()
-        num_classes = len(self.test_metadata.stuff_classes)
-        keep = labels.ne(num_classes) & (scores > self.object_mask_threshold)
-        cur_scores = scores[keep]
-        cur_classes = labels[keep]
-        cur_masks = mask_pred[keep]
-        cur_mask_cls = mask_cls[keep]
-        cur_mask_cls = cur_mask_cls[:, :-1]
-
-        cur_prob_masks = cur_scores.view(-1, 1, 1) * cur_masks
-
-        h, w = cur_masks.shape[-2:]
-        panoptic_seg = torch.zeros((h, w), dtype=torch.int32, device=cur_masks.device)
-        segments_info = []
-
-        current_segment_id = 0
-
-        if cur_masks.shape[0] == 0:
-            # We didn't detect any mask :(
-            return panoptic_seg, segments_info
-        else:
-            # take argmax
-            cur_mask_ids = cur_prob_masks.argmax(0)
-            stuff_memory_list = {}
-            for k in range(cur_classes.shape[0]):
-                pred_class = cur_classes[k].item()
-                isthing = pred_class in self.test_metadata.thing_dataset_id_to_contiguous_id.values()
-                mask_area = (cur_mask_ids == k).sum().item()
-                original_area = (cur_masks[k] >= 0.5).sum().item()
-                mask = (cur_mask_ids == k) & (cur_masks[k] >= 0.5)
-
-                if mask_area > 0 and original_area > 0 and mask.sum().item() > 0:
-                    if mask_area / original_area < self.overlap_threshold:
-                        continue
-
-                    # merge stuff regions
-                    if not isthing:
-                        if int(pred_class) in stuff_memory_list.keys():
-                            panoptic_seg[mask] = stuff_memory_list[int(pred_class)]
-                            continue
-                        else:
-                            stuff_memory_list[int(pred_class)] = current_segment_id + 1
-
-                    current_segment_id += 1
-                    panoptic_seg[mask] = current_segment_id
-
-                    segments_info.append(
-                        {
-                            "id": current_segment_id,
-                            "isthing": bool(isthing),
-                            "category_id": int(pred_class),
-                        }
-                    )
-
-            return panoptic_seg, segments_info
-
-    def instance_inference(self, mask_cls, mask_pred):
-        # mask_pred is already processed to have the same shape as original input
-        image_size = mask_pred.shape[-2:]
-
-        # [Q, K]
-        scores = F.softmax(mask_cls, dim=-1)[:, :-1]
-        # if this is panoptic segmentation
-        if self.panoptic_on:
-            num_classes = len(self.test_metadata.stuff_classes)
-        else:
-            num_classes = len(self.test_metadata.thing_classes)
-        labels = torch.arange(num_classes, device=self.device).unsqueeze(0).repeat(self.num_queries, 1).flatten(0, 1)
-        # scores_per_image, topk_indices = scores.flatten(0, 1).topk(self.num_queries, sorted=False)
-        scores_per_image, topk_indices = scores.flatten(0, 1).topk(self.test_topk_per_image, sorted=False)
-        labels_per_image = labels[topk_indices]
-
-        topk_indices = topk_indices // num_classes
-        # mask_pred = mask_pred.unsqueeze(1).repeat(1, self.sem_seg_head.num_classes, 1).flatten(0, 1)
-        mask_pred = mask_pred[topk_indices]
-
-        # if this is panoptic segmentation, we only keep the "thing" classes
-        if self.panoptic_on:
-            keep = torch.zeros_like(scores_per_image).bool()
-            for i, lab in enumerate(labels_per_image):
-                keep[i] = lab in self.test_metadata.thing_dataset_id_to_contiguous_id.values()
-
-            scores_per_image = scores_per_image[keep]
-            labels_per_image = labels_per_image[keep]
-            mask_pred = mask_pred[keep]
-
-        result = Instances(image_size)
-        # mask (before sigmoid)
-        result.pred_masks = (mask_pred > 0).float()
-        result.pred_boxes = Boxes(torch.zeros(mask_pred.size(0), 4))
-        # Uncomment the following to get boxes from masks (this is slow)
-        # result.pred_boxes = BitMasks(mask_pred > 0).get_bounding_boxes()
-
-        # calculate average mask prob
-        mask_scores_per_image = (mask_pred.sigmoid().flatten(1) * result.pred_masks.flatten(1)).sum(1) / (result.pred_masks.flatten(1).sum(1) + 1e-6)
-        result.scores = scores_per_image * mask_scores_per_image
-        result.pred_classes = labels_per_image
-        return result
diff --git a/spaces/g4f/freegpt-webui/client/js/highlightjs-copy.min.js b/spaces/g4f/freegpt-webui/client/js/highlightjs-copy.min.js
deleted file mode 100644
index ac11d33ec06e396c96b887494d9164a9b3996bef..0000000000000000000000000000000000000000
--- a/spaces/g4f/freegpt-webui/client/js/highlightjs-copy.min.js
+++ /dev/null
@@ -1 +0,0 @@
-class CopyButtonPlugin{constructor(options={}){self.hook=options.hook;self.callback=options.callback}"after:highlightElement"({el,text}){let button=Object.assign(document.createElement("button"),{innerHTML:"Copy",className:"hljs-copy-button"});button.dataset.copied=false;el.parentElement.classList.add("hljs-copy-wrapper");el.parentElement.appendChild(button);el.parentElement.style.setProperty("--hljs-theme-background",window.getComputedStyle(el).backgroundColor);button.onclick=function(){if(!navigator.clipboard)return;let newText=text;if(hook&&typeof hook==="function"){newText=hook(text,el)||text}navigator.clipboard.writeText(newText).then(function(){button.innerHTML="Copied!";button.dataset.copied=true;let alert=Object.assign(document.createElement("div"),{role:"status",className:"hljs-copy-alert",innerHTML:"Copied to clipboard"});el.parentElement.appendChild(alert);setTimeout(()=>{button.innerHTML="Copy";button.dataset.copied=false;el.parentElement.removeChild(alert);alert=null},2e3)}).then(function(){if(typeof callback==="function")return callback(newText,el)})}}}
\ No newline at end of file
diff --git a/spaces/geokanaan/arabeasy/app.py b/spaces/geokanaan/arabeasy/app.py
deleted file mode 100644
index 3263879685b7d9a244b66d63a940bde6d285532a..0000000000000000000000000000000000000000
--- a/spaces/geokanaan/arabeasy/app.py
+++ /dev/null
@@ -1,31 +0,0 @@
-import gradio as gr
-from transformers import pipeline
-import os
-
-
-pipe = pipeline(task="automatic-speech-recognition", model="geokanaan/Whisper_Base_Lebanese_Arabizi")
-
-
-
-def transcribe(audio, actual_transcription):
-    text = pipe(audio)
-    return text['text']
-
-
-HF_TOKEN = os.getenv('WRITE')
-hf_writer = gr.HuggingFaceDatasetSaver(HF_TOKEN, "flagged_Audio_Lebanese")
-
-iface = gr.Interface(
-    fn=transcribe,
-    inputs=[
-        gr.Audio(source="microphone", type="filepath"),
-        gr.Textbox(label="Actual Transcription", optional=True)  
-    ],
-    outputs="text",
-    title="arabeasy",
-    description="Realtime demo for Lebanese Arabizi speech recognition",
-    allow_flagging='manual',  # Enable manual flagging
-    flagging_callback=hf_writer
-)
-
-iface.launch(share=True)
\ No newline at end of file
diff --git a/spaces/georgefen/Face-Landmark-ControlNet/annotator/uniformer/mmcv/cnn/bricks/scale.py b/spaces/georgefen/Face-Landmark-ControlNet/annotator/uniformer/mmcv/cnn/bricks/scale.py
deleted file mode 100644
index c905fffcc8bf998d18d94f927591963c428025e2..0000000000000000000000000000000000000000
--- a/spaces/georgefen/Face-Landmark-ControlNet/annotator/uniformer/mmcv/cnn/bricks/scale.py
+++ /dev/null
@@ -1,21 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-import torch
-import torch.nn as nn
-
-
-class Scale(nn.Module):
-    """A learnable scale parameter.
-
-    This layer scales the input by a learnable factor. It multiplies a
-    learnable scale parameter of shape (1,) with input of any shape.
-
-    Args:
-        scale (float): Initial value of scale factor. Default: 1.0
-    """
-
-    def __init__(self, scale=1.0):
-        super(Scale, self).__init__()
-        self.scale = nn.Parameter(torch.tensor(scale, dtype=torch.float))
-
-    def forward(self, x):
-        return x * self.scale
diff --git a/spaces/glyszt/vt/vtoonify/model/encoder/psp.py b/spaces/glyszt/vt/vtoonify/model/encoder/psp.py
deleted file mode 100644
index cc08f2b28b3be2985139602e0f0ae56b1303e1a3..0000000000000000000000000000000000000000
--- a/spaces/glyszt/vt/vtoonify/model/encoder/psp.py
+++ /dev/null
@@ -1,125 +0,0 @@
-"""
-This file defines the core research contribution
-"""
-import matplotlib
-matplotlib.use('Agg')
-import math
-
-import torch
-from torch import nn
-from model.encoder.encoders import psp_encoders
-from model.stylegan.model import Generator
-
-def get_keys(d, name):
-	if 'state_dict' in d:
-		d = d['state_dict']
-	d_filt = {k[len(name) + 1:]: v for k, v in d.items() if k[:len(name)] == name}
-	return d_filt
-
-
-class pSp(nn.Module):
-
-	def __init__(self, opts):
-		super(pSp, self).__init__()
-		self.set_opts(opts)
-		# compute number of style inputs based on the output resolution
-		self.opts.n_styles = int(math.log(self.opts.output_size, 2)) * 2 - 2
-		# Define architecture
-		self.encoder = self.set_encoder()
-		self.decoder = Generator(self.opts.output_size, 512, 8)
-		self.face_pool = torch.nn.AdaptiveAvgPool2d((256, 256))
-		# Load weights if needed
-		self.load_weights()
-
-	def set_encoder(self):
-		if self.opts.encoder_type == 'GradualStyleEncoder':
-			encoder = psp_encoders.GradualStyleEncoder(50, 'ir_se', self.opts)
-		elif self.opts.encoder_type == 'BackboneEncoderUsingLastLayerIntoW':
-			encoder = psp_encoders.BackboneEncoderUsingLastLayerIntoW(50, 'ir_se', self.opts)
-		elif self.opts.encoder_type == 'BackboneEncoderUsingLastLayerIntoWPlus':
-			encoder = psp_encoders.BackboneEncoderUsingLastLayerIntoWPlus(50, 'ir_se', self.opts)
-		else:
-			raise Exception('{} is not a valid encoders'.format(self.opts.encoder_type))
-		return encoder
-
-	def load_weights(self):
-		if self.opts.checkpoint_path is not None:
-			print('Loading pSp from checkpoint: {}'.format(self.opts.checkpoint_path))
-			ckpt = torch.load(self.opts.checkpoint_path, map_location='cpu')
-			self.encoder.load_state_dict(get_keys(ckpt, 'encoder'), strict=True)
-			self.decoder.load_state_dict(get_keys(ckpt, 'decoder'), strict=True)
-			self.__load_latent_avg(ckpt)
-		else:
-			pass
-			'''print('Loading encoders weights from irse50!')
-			encoder_ckpt = torch.load(model_paths['ir_se50'])
-			# if input to encoder is not an RGB image, do not load the input layer weights
-			if self.opts.label_nc != 0:
-				encoder_ckpt = {k: v for k, v in encoder_ckpt.items() if "input_layer" not in k}
-			self.encoder.load_state_dict(encoder_ckpt, strict=False)
-			print('Loading decoder weights from pretrained!')
-			ckpt = torch.load(self.opts.stylegan_weights)
-			self.decoder.load_state_dict(ckpt['g_ema'], strict=False)
-			if self.opts.learn_in_w:
-				self.__load_latent_avg(ckpt, repeat=1)
-			else:
-				self.__load_latent_avg(ckpt, repeat=self.opts.n_styles)
-			'''
-
-	def forward(self, x, resize=True, latent_mask=None, input_code=False, randomize_noise=True,
-	            inject_latent=None, return_latents=False, alpha=None, z_plus_latent=False, return_z_plus_latent=True):
-		if input_code:
-			codes = x
-		else:
-			codes = self.encoder(x)
-			#print(codes.shape)
-			# normalize with respect to the center of an average face
-			if self.opts.start_from_latent_avg:
-				if self.opts.learn_in_w:
-					codes = codes + self.latent_avg.repeat(codes.shape[0], 1)
-				else:
-					codes = codes + self.latent_avg.repeat(codes.shape[0], 1, 1)
-
-
-		if latent_mask is not None:
-			for i in latent_mask:
-				if inject_latent is not None:
-					if alpha is not None:
-						codes[:, i] = alpha * inject_latent[:, i] + (1 - alpha) * codes[:, i]
-					else:
-						codes[:, i] = inject_latent[:, i]
-				else:
-					codes[:, i] = 0
-
-		input_is_latent = not input_code
-		if z_plus_latent:
-			input_is_latent = False
-		images, result_latent = self.decoder([codes],
-		                                     input_is_latent=input_is_latent,
-		                                     randomize_noise=randomize_noise,
-		                                     return_latents=return_latents,
-                                             z_plus_latent=z_plus_latent)
-
-		if resize:
-			images = self.face_pool(images)
-
-		if return_latents:
-			if z_plus_latent and return_z_plus_latent:
-				return images, codes
-			if z_plus_latent and not return_z_plus_latent:
-				return images, result_latent            
-			else:
-				return images, result_latent
-		else:
-			return images
-
-	def set_opts(self, opts):
-		self.opts = opts
-
-	def __load_latent_avg(self, ckpt, repeat=None):
-		if 'latent_avg' in ckpt:
-			self.latent_avg = ckpt['latent_avg'].to(self.opts.device)
-			if repeat is not None:
-				self.latent_avg = self.latent_avg.repeat(repeat, 1)
-		else:
-			self.latent_avg = None
diff --git a/spaces/gotiQspiryo/whisper-ui/examples/Doctor Love Malayalam Movie Songs Download 12311 How to Get the Best Quality Audio Files.md b/spaces/gotiQspiryo/whisper-ui/examples/Doctor Love Malayalam Movie Songs Download 12311 How to Get the Best Quality Audio Files.md
deleted file mode 100644
index 727434017b69f993f2ad35d915d4c4c8f7ed9539..0000000000000000000000000000000000000000
--- a/spaces/gotiQspiryo/whisper-ui/examples/Doctor Love Malayalam Movie Songs Download 12311 How to Get the Best Quality Audio Files.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>doctor love malayalam movie songs download 12311</h2><br /><p><b><b>Download</b> &#10042;&#10042;&#10042; <a href="https://urlgoal.com/2uyLUh">https://urlgoal.com/2uyLUh</a></b></p><br /><br />
-
- aaccfb2cb3<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/gotiQspiryo/whisper-ui/examples/HD Online Player (Avatar 3d 2009 1080p HSBS 3d HindiEn) __TOP__.md b/spaces/gotiQspiryo/whisper-ui/examples/HD Online Player (Avatar 3d 2009 1080p HSBS 3d HindiEn) __TOP__.md
deleted file mode 100644
index dc8b3f6df934fc333cac930e3d6a1b9908bf829c..0000000000000000000000000000000000000000
--- a/spaces/gotiQspiryo/whisper-ui/examples/HD Online Player (Avatar 3d 2009 1080p HSBS 3d HindiEn) __TOP__.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>HD Online Player (Avatar 3d 2009 1080p HSBS 3d HindiEn)</h2><br /><p><b><b>Download Zip</b> &#9193; <a href="https://urlgoal.com/2uyNbu">https://urlgoal.com/2uyNbu</a></b></p><br /><br />
-
-Download 3d sbs movies with 1080p resolution in BluRay format. 3D SBS video especially for phones and virtual reality glasses! Watch only in 3D SBS! Join the VKontakte group so you don't miss new movies!!! 8a78ff9644<br />
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diff --git a/spaces/gradio/HuBERT/examples/hubert/simple_kmeans/learn_kmeans.py b/spaces/gradio/HuBERT/examples/hubert/simple_kmeans/learn_kmeans.py
deleted file mode 100644
index 113ac655b8c0a585fe43797e99674e445098edd0..0000000000000000000000000000000000000000
--- a/spaces/gradio/HuBERT/examples/hubert/simple_kmeans/learn_kmeans.py
+++ /dev/null
@@ -1,146 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import logging
-import os
-import sys
-
-import numpy as np
-from sklearn.cluster import MiniBatchKMeans
-
-import joblib
-
-logging.basicConfig(
-    format="%(asctime)s | %(levelname)s | %(name)s | %(message)s",
-    datefmt="%Y-%m-%d %H:%M:%S",
-    level=os.environ.get("LOGLEVEL", "INFO").upper(),
-    stream=sys.stdout,
-)
-logger = logging.getLogger("learn_kmeans")
-
-
-def get_km_model(
-    n_clusters,
-    init,
-    max_iter,
-    batch_size,
-    tol,
-    max_no_improvement,
-    n_init,
-    reassignment_ratio,
-):
-    return MiniBatchKMeans(
-        n_clusters=n_clusters,
-        init=init,
-        max_iter=max_iter,
-        batch_size=batch_size,
-        verbose=1,
-        compute_labels=False,
-        tol=tol,
-        max_no_improvement=max_no_improvement,
-        init_size=None,
-        n_init=n_init,
-        reassignment_ratio=reassignment_ratio,
-    )
-
-
-def load_feature_shard(feat_dir, split, nshard, rank, percent):
-    feat_path = f"{feat_dir}/{split}_{rank}_{nshard}.npy"
-    leng_path = f"{feat_dir}/{split}_{rank}_{nshard}.len"
-    with open(leng_path, "r") as f:
-        lengs = [int(line.rstrip()) for line in f]
-        offsets = [0] + np.cumsum(lengs[:-1]).tolist()
-
-    if percent < 0:
-        return np.load(feat_path, mmap_mode="r")
-    else:
-        nsample = int(np.ceil(len(lengs) * percent))
-        indices = np.random.choice(len(lengs), nsample, replace=False)
-        feat = np.load(feat_path, mmap_mode="r")
-        sampled_feat = np.concatenate(
-            [feat[offsets[i]: offsets[i] + lengs[i]] for i in indices], axis=0
-        )
-        logger.info(
-            (
-                f"sampled {nsample} utterances, {len(sampled_feat)} frames "
-                f"from shard {rank}/{nshard}"
-            )
-        )
-        return sampled_feat
-
-
-def load_feature(feat_dir, split, nshard, seed, percent):
-    assert percent <= 1.0
-    feat = np.concatenate(
-        [
-            load_feature_shard(feat_dir, split, nshard, r, percent)
-            for r in range(nshard)
-        ],
-        axis=0,
-    )
-    logging.info(f"loaded feature with dimension {feat.shape}")
-    return feat
-
-
-def learn_kmeans(
-    feat_dir,
-    split,
-    nshard,
-    km_path,
-    n_clusters,
-    seed,
-    percent,
-    init,
-    max_iter,
-    batch_size,
-    tol,
-    n_init,
-    reassignment_ratio,
-    max_no_improvement,
-):
-    np.random.seed(seed)
-    feat = load_feature(feat_dir, split, nshard, seed, percent)
-    km_model = get_km_model(
-        n_clusters,
-        init,
-        max_iter,
-        batch_size,
-        tol,
-        max_no_improvement,
-        n_init,
-        reassignment_ratio,
-    )
-    km_model.fit(feat)
-    joblib.dump(km_model, km_path)
-
-    inertia = -km_model.score(feat) / len(feat)
-    logger.info("total intertia: %.5f", inertia)
-    logger.info("finished successfully")
-
-
-if __name__ == "__main__":
-    import argparse
-
-    parser = argparse.ArgumentParser()
-    parser.add_argument("feat_dir", type=str)
-    parser.add_argument("split", type=str)
-    parser.add_argument("nshard", type=int)
-    parser.add_argument("km_path", type=str)
-    parser.add_argument("n_clusters", type=int)
-    parser.add_argument("--seed", default=0, type=int)
-    parser.add_argument(
-        "--percent", default=-1, type=float, help="sample a subset; -1 for all"
-    )
-    parser.add_argument("--init", default="k-means++")
-    parser.add_argument("--max_iter", default=100, type=int)
-    parser.add_argument("--batch_size", default=10000, type=int)
-    parser.add_argument("--tol", default=0.0, type=float)
-    parser.add_argument("--max_no_improvement", default=100, type=int)
-    parser.add_argument("--n_init", default=20, type=int)
-    parser.add_argument("--reassignment_ratio", default=0.0, type=float)
-    args = parser.parse_args()
-    logging.info(str(args))
-
-    learn_kmeans(**vars(args))
diff --git a/spaces/gradio/HuBERT/fairseq/modules/transpose_last.py b/spaces/gradio/HuBERT/fairseq/modules/transpose_last.py
deleted file mode 100644
index e578b3ec5097bfac5c976b207ea46bec1d9bd4f5..0000000000000000000000000000000000000000
--- a/spaces/gradio/HuBERT/fairseq/modules/transpose_last.py
+++ /dev/null
@@ -1,20 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-"""
-transpose last 2 dimensions of the input
-"""
-
-import torch.nn as nn
-
-
-class TransposeLast(nn.Module):
-    def __init__(self, deconstruct_idx=None):
-        super().__init__()
-        self.deconstruct_idx = deconstruct_idx
-
-    def forward(self, x):
-        if self.deconstruct_idx is not None:
-            x = x[self.deconstruct_idx]
-        return x.transpose(-2, -1)
diff --git a/spaces/gradio/hello_login/run.py b/spaces/gradio/hello_login/run.py
deleted file mode 100644
index 0acefb17bc5c6bef33676f75dd7cca74d32094ba..0000000000000000000000000000000000000000
--- a/spaces/gradio/hello_login/run.py
+++ /dev/null
@@ -1,18 +0,0 @@
-import gradio as gr
-import argparse
-import sys
-
-parser = argparse.ArgumentParser()
-parser.add_argument("--name", type=str, default="User")
-args, unknown = parser.parse_known_args()
-print(sys.argv)
-
-with gr.Blocks() as demo:
-    gr.Markdown(f"# Greetings {args.name}!")
-    inp = gr.Textbox()
-    out = gr.Textbox()
-
-    inp.change(fn=lambda x: x, inputs=inp, outputs=out)
-
-if __name__ == "__main__":
-    demo.launch()
\ No newline at end of file
diff --git a/spaces/hackathon-somos-nlp-2023/suicide-comments-es/app.py b/spaces/hackathon-somos-nlp-2023/suicide-comments-es/app.py
deleted file mode 100644
index 09b53456c4e012b678a8f4ce4a9261f5c964247f..0000000000000000000000000000000000000000
--- a/spaces/hackathon-somos-nlp-2023/suicide-comments-es/app.py
+++ /dev/null
@@ -1,63 +0,0 @@
-import os
-from transformers import pipeline
-import gradio as gr
-
-
-hf_writer = gr.HuggingFaceDatasetSaver(os.getenv('HF_API_TOKEN'), "suicide-comment-es-space-human-feedback")
-pipe = pipeline("text-classification", model='hackathon-somos-nlp-2023/roberta-base-bne-finetuned-suicide-es')
-
-
-def detect_suicide_comment(input):
-    result = pipe(input)[0]
-    # return {result['label']: result['score']}
-    return result
-
-
-iface = gr.Interface(
-    fn=detect_suicide_comment,
-    inputs="text",
-    outputs="text",  # gr.Label(num_top_classes=1, type="confidences"),
-    allow_flagging="manual",
-    flagging_options=['Correct Classification', 'Incorrect Classification'],
-    flagging_callback=hf_writer,
-    examples=[
-        "Quiero acabar con todo. No merece la pena vivir.",
-        "El partido de fútbol fue igualado, todos disfrutamos mucho jugando juntos."
-    ],
-    article="""
-## Motivación
-
-* Cada año se suicidan casi 1.000.000 de personas en el mundo y por cada suicidio, se cometen unos 20 intentos.
-* Cada año se suicidan unas 4000 personas en España, siendo la primera causa de muerte externa. Esto son unas 11 muertes al día.
-* Entre jóvenes de 15 a 29 años de edad, el suicidio es la 2ª causa principal de muerte a nivel mundial.
-* Cada suicidio es una tragedia. Los efectos sobre las familias, amigos y comunidades son terribles y de amplio alcance. Por cada suicidio consumado, al menos 6 seres queridos se ven directamente afectados.
-
-## Demo
-
-Introduce cualquier frase en español, un modelo de inteligencia artificial tratará de predecir si la frase contiene algún patrón indicativo de ideación o comportamiento suicida.
-
-## Feedback
-
-¡Ayúdanos a mejorar la aplicación marcando la respuesta como Correcta o Incorrecta según corresponda!
-
-Nosotros usaremos este feedback para ampliar el dataset que se usará para fine-tunear el modelo en versiones posteriores.
-
-¡Gracias!
-
-## Dataset
-
-https://huggingface.co/datasets/hackathon-somos-nlp-2023/suicide-comments-es
-
-## Model
-
-https://huggingface.co/hackathon-somos-nlp-2023/roberta-base-bne-finetuned-suicide-es
-
-## Team
-
-* [dariolopez](https://huggingface.co/dariolopez)
-* [diegogd](https://huggingface.co/diegogd)
-
-""",
-    title="Detector de comentarios con ideación suicida"
-)
-iface.launch()
diff --git a/spaces/hamelcubsfan/AutoGPT/autogpt/cli.py b/spaces/hamelcubsfan/AutoGPT/autogpt/cli.py
deleted file mode 100644
index a2e99cb421cad005528cb160e948ce59ccfcdb66..0000000000000000000000000000000000000000
--- a/spaces/hamelcubsfan/AutoGPT/autogpt/cli.py
+++ /dev/null
@@ -1,145 +0,0 @@
-"""Main script for the autogpt package."""
-import click
-
-
-@click.group(invoke_without_command=True)
-@click.option("-c", "--continuous", is_flag=True, help="Enable Continuous Mode")
-@click.option(
-    "--skip-reprompt",
-    "-y",
-    is_flag=True,
-    help="Skips the re-prompting messages at the beginning of the script",
-)
-@click.option(
-    "--ai-settings",
-    "-C",
-    help="Specifies which ai_settings.yaml file to use, will also automatically skip the re-prompt.",
-)
-@click.option(
-    "-l",
-    "--continuous-limit",
-    type=int,
-    help="Defines the number of times to run in continuous mode",
-)
-@click.option("--speak", is_flag=True, help="Enable Speak Mode")
-@click.option("--debug", is_flag=True, help="Enable Debug Mode")
-@click.option("--gpt3only", is_flag=True, help="Enable GPT3.5 Only Mode")
-@click.option("--gpt4only", is_flag=True, help="Enable GPT4 Only Mode")
-@click.option(
-    "--use-memory",
-    "-m",
-    "memory_type",
-    type=str,
-    help="Defines which Memory backend to use",
-)
-@click.option(
-    "-b",
-    "--browser-name",
-    help="Specifies which web-browser to use when using selenium to scrape the web.",
-)
-@click.option(
-    "--allow-downloads",
-    is_flag=True,
-    help="Dangerous: Allows Auto-GPT to download files natively.",
-)
-@click.option(
-    "--skip-news",
-    is_flag=True,
-    help="Specifies whether to suppress the output of latest news on startup.",
-)
-@click.pass_context
-def main(
-    ctx: click.Context,
-    continuous: bool,
-    continuous_limit: int,
-    ai_settings: str,
-    skip_reprompt: bool,
-    speak: bool,
-    debug: bool,
-    gpt3only: bool,
-    gpt4only: bool,
-    memory_type: str,
-    browser_name: str,
-    allow_downloads: bool,
-    skip_news: bool,
-) -> None:
-    """
-    Welcome to AutoGPT an experimental open-source application showcasing the capabilities of the GPT-4 pushing the boundaries of AI.
-
-    Start an Auto-GPT assistant.
-    """
-    # Put imports inside function to avoid importing everything when starting the CLI
-    import logging
-
-    from colorama import Fore
-
-    from autogpt.agent.agent import Agent
-    from autogpt.config import Config, check_openai_api_key
-    from autogpt.configurator import create_config
-    from autogpt.logs import logger
-    from autogpt.memory import get_memory
-    from autogpt.prompt import construct_prompt
-    from autogpt.utils import get_current_git_branch, get_latest_bulletin
-
-    if ctx.invoked_subcommand is None:
-        cfg = Config()
-        # TODO: fill in llm values here
-        check_openai_api_key()
-        create_config(
-            continuous,
-            continuous_limit,
-            ai_settings,
-            skip_reprompt,
-            speak,
-            debug,
-            gpt3only,
-            gpt4only,
-            memory_type,
-            browser_name,
-            allow_downloads,
-            skip_news,
-        )
-        logger.set_level(logging.DEBUG if cfg.debug_mode else logging.INFO)
-        ai_name = ""
-        if not cfg.skip_news:
-            motd = get_latest_bulletin()
-            if motd:
-                logger.typewriter_log("NEWS: ", Fore.GREEN, motd)
-            git_branch = get_current_git_branch()
-            if git_branch and git_branch != "stable":
-                logger.typewriter_log(
-                    "WARNING: ",
-                    Fore.RED,
-                    f"You are running on `{git_branch}` branch "
-                    "- this is not a supported branch.",
-                )
-        system_prompt = construct_prompt()
-        # print(prompt)
-        # Initialize variables
-        full_message_history = []
-        next_action_count = 0
-        # Make a constant:
-        triggering_prompt = (
-            "Determine which next command to use, and respond using the"
-            " format specified above:"
-        )
-        # Initialize memory and make sure it is empty.
-        # this is particularly important for indexing and referencing pinecone memory
-        memory = get_memory(cfg, init=True)
-        logger.typewriter_log(
-            "Using memory of type:", Fore.GREEN, f"{memory.__class__.__name__}"
-        )
-        logger.typewriter_log("Using Browser:", Fore.GREEN, cfg.selenium_web_browser)
-        agent = Agent(
-            ai_name=ai_name,
-            memory=memory,
-            full_message_history=full_message_history,
-            next_action_count=next_action_count,
-            system_prompt=system_prompt,
-            triggering_prompt=triggering_prompt,
-        )
-        agent.start_interaction_loop()
-
-
-if __name__ == "__main__":
-    main()
diff --git a/spaces/hanstyle/tts/README_T.md b/spaces/hanstyle/tts/README_T.md
deleted file mode 100644
index 35f69daff0ee31e44c7b251f360365b2710585fb..0000000000000000000000000000000000000000
--- a/spaces/hanstyle/tts/README_T.md
+++ /dev/null
@@ -1,152 +0,0 @@
-# **Wav2Lip**: *Accurately Lip-syncing Videos In The Wild*
-
-For commercial requests, please contact us at radrabha.m@research.iiit.ac.in or prajwal.k@research.iiit.ac.in. We have an HD model ready that can be used commercially.
-
-This code is part of the paper: _A Lip Sync Expert Is All You Need for Speech to Lip Generation In the Wild_ published at ACM Multimedia 2020. 
-
-[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/a-lip-sync-expert-is-all-you-need-for-speech/lip-sync-on-lrs2)](https://paperswithcode.com/sota/lip-sync-on-lrs2?p=a-lip-sync-expert-is-all-you-need-for-speech)
-[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/a-lip-sync-expert-is-all-you-need-for-speech/lip-sync-on-lrs3)](https://paperswithcode.com/sota/lip-sync-on-lrs3?p=a-lip-sync-expert-is-all-you-need-for-speech)
-[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/a-lip-sync-expert-is-all-you-need-for-speech/lip-sync-on-lrw)](https://paperswithcode.com/sota/lip-sync-on-lrw?p=a-lip-sync-expert-is-all-you-need-for-speech)
-
-|📑 Original Paper|📰 Project Page|🌀 Demo|⚡ Live Testing|📔 Colab Notebook
-|:-:|:-:|:-:|:-:|:-:|
-[Paper](http://arxiv.org/abs/2008.10010) | [Project Page](http://cvit.iiit.ac.in/research/projects/cvit-projects/a-lip-sync-expert-is-all-you-need-for-speech-to-lip-generation-in-the-wild/) | [Demo Video](https://youtu.be/0fXaDCZNOJc) | [Interactive Demo](https://bhaasha.iiit.ac.in/lipsync) | [Colab Notebook](https://colab.research.google.com/drive/1tZpDWXz49W6wDcTprANRGLo2D_EbD5J8?usp=sharing) /[Updated Collab Notebook](https://colab.research.google.com/drive/1IjFW1cLevs6Ouyu4Yht4mnR4yeuMqO7Y#scrollTo=MH1m608OymLH)
-
- <img src="https://drive.google.com/uc?export=view&id=1Wn0hPmpo4GRbCIJR8Tf20Akzdi1qjjG9"/>
-
-----------
-**Highlights**
-----------
- - Weights of the visual quality disc has been updated in readme!
- - Lip-sync videos to any target speech with high accuracy :100:. Try our [interactive demo](https://bhaasha.iiit.ac.in/lipsync).
- - :sparkles: Works for any identity, voice, and language. Also works for CGI faces and synthetic voices.
- - Complete training code, inference code, and pretrained models are available :boom:
- - Or, quick-start with the Google Colab Notebook: [Link](https://colab.research.google.com/drive/1tZpDWXz49W6wDcTprANRGLo2D_EbD5J8?usp=sharing). Checkpoints and samples are available in a Google Drive [folder](https://drive.google.com/drive/folders/1I-0dNLfFOSFwrfqjNa-SXuwaURHE5K4k?usp=sharing) as well. There is also a [tutorial video](https://www.youtube.com/watch?v=Ic0TBhfuOrA) on this, courtesy of [What Make Art](https://www.youtube.com/channel/UCmGXH-jy0o2CuhqtpxbaQgA). Also, thanks to [Eyal Gruss](https://eyalgruss.com), there is a more accessible [Google Colab notebook](https://j.mp/wav2lip) with more useful features. A tutorial collab notebook is present at this [link](https://colab.research.google.com/drive/1IjFW1cLevs6Ouyu4Yht4mnR4yeuMqO7Y#scrollTo=MH1m608OymLH).  
- - :fire: :fire: Several new, reliable evaluation benchmarks and metrics [[`evaluation/` folder of this repo]](https://github.com/Rudrabha/Wav2Lip/tree/master/evaluation) released. Instructions to calculate the metrics reported in the paper are also present.
-
---------
-**Disclaimer**
---------
-All results from this open-source code or our [demo website](https://bhaasha.iiit.ac.in/lipsync) should only be used for research/academic/personal purposes only. As the models are trained on the <a href="http://www.robots.ox.ac.uk/~vgg/data/lip_reading/lrs2.html">LRS2 dataset</a>, any form of commercial use is strictly prohibhited. For commercial requests please contact us directly!
-
-Prerequisites
--------------
-- `Python 3.6` 
-- ffmpeg: `sudo apt-get install ffmpeg`
-- Install necessary packages using `pip install -r requirements.txt`. Alternatively, instructions for using a docker image is provided [here](https://gist.github.com/xenogenesi/e62d3d13dadbc164124c830e9c453668). Have a look at [this comment](https://github.com/Rudrabha/Wav2Lip/issues/131#issuecomment-725478562) and comment on [the gist](https://gist.github.com/xenogenesi/e62d3d13dadbc164124c830e9c453668) if you encounter any issues. 
-- Face detection [pre-trained model](https://www.adrianbulat.com/downloads/python-fan/s3fd-619a316812.pth) should be downloaded to `face_detection/detection/sfd/s3fd.pth`. Alternative [link](https://iiitaphyd-my.sharepoint.com/:u:/g/personal/prajwal_k_research_iiit_ac_in/EZsy6qWuivtDnANIG73iHjIBjMSoojcIV0NULXV-yiuiIg?e=qTasa8) if the above does not work.
-
-Getting the weights
-----------
-| Model  | Description |  Link to the model | 
-| :-------------: | :---------------: | :---------------: |
-| Wav2Lip  | Highly accurate lip-sync | [Link](https://iiitaphyd-my.sharepoint.com/:u:/g/personal/radrabha_m_research_iiit_ac_in/Eb3LEzbfuKlJiR600lQWRxgBIY27JZg80f7V9jtMfbNDaQ?e=TBFBVW)  |
-| Wav2Lip + GAN  | Slightly inferior lip-sync, but better visual quality | [Link](https://iiitaphyd-my.sharepoint.com/:u:/g/personal/radrabha_m_research_iiit_ac_in/EdjI7bZlgApMqsVoEUUXpLsBxqXbn5z8VTmoxp55YNDcIA?e=n9ljGW) |
-| Expert Discriminator  | Weights of the expert discriminator | [Link](https://iiitaphyd-my.sharepoint.com/:u:/g/personal/radrabha_m_research_iiit_ac_in/EQRvmiZg-HRAjvI6zqN9eTEBP74KefynCwPWVmF57l-AYA?e=ZRPHKP) |
-| Visual Quality Discriminator  | Weights of the visual disc trained in a GAN setup | [Link](https://iiitaphyd-my.sharepoint.com/:u:/g/personal/radrabha_m_research_iiit_ac_in/EQVqH88dTm1HjlK11eNba5gBbn15WMS0B0EZbDBttqrqkg?e=ic0ljo) |
-
-Lip-syncing videos using the pre-trained models (Inference)
--------
-You can lip-sync any video to any audio:
-```bash
-python inference.py --checkpoint_path <ckpt> --face <video.mp4> --audio <an-audio-source> 
-```
-The result is saved (by default) in `results/result_voice.mp4`. You can specify it as an argument,  similar to several other available options. The audio source can be any file supported by `FFMPEG` containing audio data: `*.wav`, `*.mp3` or even a video file, from which the code will automatically extract the audio.
-
-##### Tips for better results:
-- Experiment with the `--pads` argument to adjust the detected face bounding box. Often leads to improved results. You might need to increase the bottom padding to include the chin region. E.g. `--pads 0 20 0 0`.
-- If you see the mouth position dislocated or some weird artifacts such as two mouths, then it can be because of over-smoothing the face detections. Use the `--nosmooth` argument and give another try. 
-- Experiment with the `--resize_factor` argument, to get a lower resolution video. Why? The models are trained on faces which were at a lower resolution. You might get better, visually pleasing results for 720p videos than for 1080p videos (in many cases, the latter works well too). 
-- The Wav2Lip model without GAN usually needs more experimenting with the above two to get the most ideal results, and sometimes, can give you a better result as well.
-
-Preparing LRS2 for training
-----------
-Our models are trained on LRS2. See [here](#training-on-datasets-other-than-lrs2) for a few suggestions regarding training on other datasets.
-##### LRS2 dataset folder structure
-
-```
-data_root (mvlrs_v1)
-├── main, pretrain (we use only main folder in this work)
-|	├── list of folders
-|	│   ├── five-digit numbered video IDs ending with (.mp4)
-```
-
-Place the LRS2 filelists (train, val, test) `.txt` files in the `filelists/` folder.
-
-##### Preprocess the dataset for fast training
-
-```bash
-python preprocess.py --data_root data_root/main --preprocessed_root lrs2_preprocessed/
-```
-Additional options like `batch_size` and number of GPUs to use in parallel to use can also be set.
-
-##### Preprocessed LRS2 folder structure
-```
-preprocessed_root (lrs2_preprocessed)
-├── list of folders
-|	├── Folders with five-digit numbered video IDs
-|	│   ├── *.jpg
-|	│   ├── audio.wav
-```
-
-Train!
-----------
-There are two major steps: (i) Train the expert lip-sync discriminator, (ii) Train the Wav2Lip model(s).
-
-##### Training the expert discriminator
-You can download [the pre-trained weights](#getting-the-weights) if you want to skip this step. To train it:
-```bash
-python color_syncnet_train.py --data_root lrs2_preprocessed/ --checkpoint_dir <folder_to_save_checkpoints>
-```
-##### Training the Wav2Lip models
-You can either train the model without the additional visual quality disriminator (< 1 day of training) or use the discriminator (~2 days). For the former, run: 
-```bash
-python wav2lip_train.py --data_root lrs2_preprocessed/ --checkpoint_dir <folder_to_save_checkpoints> --syncnet_checkpoint_path <path_to_expert_disc_checkpoint>
-```
-
-To train with the visual quality discriminator, you should run `hq_wav2lip_train.py` instead. The arguments for both the files are similar. In both the cases, you can resume training as well. Look at `python wav2lip_train.py --help` for more details. You can also set additional less commonly-used hyper-parameters at the bottom of the `hparams.py` file.
-
-Training on datasets other than LRS2
-------------------------------------
-Training on other datasets might require modifications to the code. Please read the following before you raise an issue:
-
-- You might not get good results by training/fine-tuning on a few minutes of a single speaker. This is a separate research problem, to which we do not have a solution yet. Thus, we would most likely not be able to resolve your issue. 
-- You must train the expert discriminator for your own dataset before training Wav2Lip.
-- If it is your own dataset downloaded from the web, in most cases, needs to be sync-corrected.
-- Be mindful of the FPS of the videos of your dataset. Changes to FPS would need significant code changes. 
-- The expert discriminator's eval loss should go down to ~0.25 and the Wav2Lip eval sync loss should go down to ~0.2 to get good results. 
-
-When raising an issue on this topic, please let us know that you are aware of all these points.
-
-We have an HD model trained on a dataset allowing commercial usage. The size of the generated face will be 192 x 288 in our new model.
-
-Evaluation
-----------
-Please check the `evaluation/` folder for the instructions.
-
-License and Citation
-----------
-Theis repository can only be used for personal/research/non-commercial purposes. However, for commercial requests, please contact us directly at radrabha.m@research.iiit.ac.in or prajwal.k@research.iiit.ac.in. We have an HD model trained on a dataset allowing commercial usage. The size of the generated face will be 192 x 288 in our new model. Please cite the following paper if you use this repository:
-```
-@inproceedings{10.1145/3394171.3413532,
-author = {Prajwal, K R and Mukhopadhyay, Rudrabha and Namboodiri, Vinay P. and Jawahar, C.V.},
-title = {A Lip Sync Expert Is All You Need for Speech to Lip Generation In the Wild},
-year = {2020},
-isbn = {9781450379885},
-publisher = {Association for Computing Machinery},
-address = {New York, NY, USA},
-url = {https://doi.org/10.1145/3394171.3413532},
-doi = {10.1145/3394171.3413532},
-booktitle = {Proceedings of the 28th ACM International Conference on Multimedia},
-pages = {484–492},
-numpages = {9},
-keywords = {lip sync, talking face generation, video generation},
-location = {Seattle, WA, USA},
-series = {MM '20}
-}
-```
-
-
-Acknowledgements
-----------
-Parts of the code structure is inspired by this [TTS repository](https://github.com/r9y9/deepvoice3_pytorch). We thank the author for this wonderful code. The code for Face Detection has been taken from the [face_alignment](https://github.com/1adrianb/face-alignment) repository. We thank the authors for releasing their code and models. We thank [zabique](https://github.com/zabique) for the tutorial collab notebook.
diff --git a/spaces/harkov000/peft-lora-sd-dreambooth/README.md b/spaces/harkov000/peft-lora-sd-dreambooth/README.md
deleted file mode 100644
index f96cd426f184e663e654b3bccabf3e8d7e168d80..0000000000000000000000000000000000000000
--- a/spaces/harkov000/peft-lora-sd-dreambooth/README.md
+++ /dev/null
@@ -1,14 +0,0 @@
----
-title: Peft Lora Sd Dreambooth
-emoji: 🎨
-colorFrom: purple
-colorTo: green
-sdk: gradio
-sdk_version: 3.16.2
-app_file: app.py
-pinned: false
-license: openrail
-duplicated_from: smangrul/peft-lora-sd-dreambooth
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/ho11laqe/nnUNet_calvingfront_detection/nnunet/experiment_planning/alternative_experiment_planning/pooling_and_convs/__init__.py b/spaces/ho11laqe/nnUNet_calvingfront_detection/nnunet/experiment_planning/alternative_experiment_planning/pooling_and_convs/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/ho11laqe/nnUNet_calvingfront_detection/nnunet/training/dataloading/__init__.py b/spaces/ho11laqe/nnUNet_calvingfront_detection/nnunet/training/dataloading/__init__.py
deleted file mode 100644
index 72b8078b9dddddf22182fec2555d8d118ea72622..0000000000000000000000000000000000000000
--- a/spaces/ho11laqe/nnUNet_calvingfront_detection/nnunet/training/dataloading/__init__.py
+++ /dev/null
@@ -1,2 +0,0 @@
-from __future__ import absolute_import
-from . import *
\ No newline at end of file
diff --git a/spaces/housexu123/bingo-2.0/src/components/ui/tooltip.tsx b/spaces/housexu123/bingo-2.0/src/components/ui/tooltip.tsx
deleted file mode 100644
index af1d48beb90dd5ae311796539843700871052cae..0000000000000000000000000000000000000000
--- a/spaces/housexu123/bingo-2.0/src/components/ui/tooltip.tsx
+++ /dev/null
@@ -1,30 +0,0 @@
-'use client'
-
-import * as React from 'react'
-import * as TooltipPrimitive from '@radix-ui/react-tooltip'
-
-import { cn } from '@/lib/utils'
-
-const TooltipProvider = TooltipPrimitive.Provider
-
-const Tooltip = TooltipPrimitive.Root
-
-const TooltipTrigger = TooltipPrimitive.Trigger
-
-const TooltipContent = React.forwardRef<
-  React.ElementRef<typeof TooltipPrimitive.Content>,
-  React.ComponentPropsWithoutRef<typeof TooltipPrimitive.Content>
->(({ className, sideOffset = 4, ...props }, ref) => (
-  <TooltipPrimitive.Content
-    ref={ref}
-    sideOffset={sideOffset}
-    className={cn(
-      'z-50 overflow-hidden rounded-md border bg-popover px-3 py-1.5 text-xs font-medium text-popover-foreground shadow-md animate-in fade-in-50 data-[side=bottom]:slide-in-from-top-1 data-[side=left]:slide-in-from-right-1 data-[side=right]:slide-in-from-left-1 data-[side=top]:slide-in-from-bottom-1',
-      className
-    )}
-    {...props}
-  />
-))
-TooltipContent.displayName = TooltipPrimitive.Content.displayName
-
-export { Tooltip, TooltipTrigger, TooltipContent, TooltipProvider }
diff --git a/spaces/housexu123/bingo-2.0/src/lib/hooks/use-enter-submit.tsx b/spaces/housexu123/bingo-2.0/src/lib/hooks/use-enter-submit.tsx
deleted file mode 100644
index d66b2d3253baff164235d4ca791aae6d84721835..0000000000000000000000000000000000000000
--- a/spaces/housexu123/bingo-2.0/src/lib/hooks/use-enter-submit.tsx
+++ /dev/null
@@ -1,23 +0,0 @@
-import { useRef, type RefObject } from 'react'
-
-export function useEnterSubmit(): {
-  formRef: RefObject<HTMLFormElement>
-  onKeyDown: (event: React.KeyboardEvent<HTMLTextAreaElement>) => void
-} {
-  const formRef = useRef<HTMLFormElement>(null)
-
-  const handleKeyDown = (
-    event: React.KeyboardEvent<HTMLTextAreaElement>
-  ): void => {
-    if (
-      event.key === 'Enter' &&
-      !event.shiftKey &&
-      !event.nativeEvent.isComposing
-    ) {
-      formRef.current?.requestSubmit()
-      event.preventDefault()
-    }
-  }
-
-  return { formRef, onKeyDown: handleKeyDown }
-}
diff --git a/spaces/huggingchat/chat-ui/src/lib/server/modelEndpoint.ts b/spaces/huggingchat/chat-ui/src/lib/server/modelEndpoint.ts
deleted file mode 100644
index b105b122d47d48c6b9b1376d91c6c3fac23d0c65..0000000000000000000000000000000000000000
--- a/spaces/huggingchat/chat-ui/src/lib/server/modelEndpoint.ts
+++ /dev/null
@@ -1,50 +0,0 @@
-import {
-	HF_ACCESS_TOKEN,
-	HF_API_ROOT,
-	USE_CLIENT_CERTIFICATE,
-	CERT_PATH,
-	KEY_PATH,
-	CA_PATH,
-	CLIENT_KEY_PASSWORD,
-	REJECT_UNAUTHORIZED,
-} from "$env/static/private";
-import { sum } from "$lib/utils/sum";
-import type { BackendModel, Endpoint } from "./models";
-
-import { loadClientCertificates } from "$lib/utils/loadClientCerts";
-
-if (USE_CLIENT_CERTIFICATE === "true") {
-	loadClientCertificates(
-		CERT_PATH,
-		KEY_PATH,
-		CA_PATH,
-		CLIENT_KEY_PASSWORD,
-		REJECT_UNAUTHORIZED === "true"
-	);
-}
-
-/**
- * Find a random load-balanced endpoint
- */
-export function modelEndpoint(model: BackendModel): Endpoint {
-	if (!model.endpoints) {
-		return {
-			host: "tgi",
-			url: `${HF_API_ROOT}/${model.name}`,
-			authorization: `Bearer ${HF_ACCESS_TOKEN}`,
-			weight: 1,
-		};
-	}
-	const endpoints = model.endpoints;
-	const totalWeight = sum(endpoints.map((e) => e.weight));
-
-	let random = Math.random() * totalWeight;
-	for (const endpoint of endpoints) {
-		if (random < endpoint.weight) {
-			return endpoint;
-		}
-		random -= endpoint.weight;
-	}
-
-	throw new Error("Invalid config, no endpoint found");
-}
diff --git a/spaces/huggingface/data-measurements-tool/run_data_measurements.py b/spaces/huggingface/data-measurements-tool/run_data_measurements.py
deleted file mode 100644
index 5ffa4ee8ec9d58ea643d516366163ab5e67f57d2..0000000000000000000000000000000000000000
--- a/spaces/huggingface/data-measurements-tool/run_data_measurements.py
+++ /dev/null
@@ -1,296 +0,0 @@
-import argparse
-import json
-import textwrap
-from os import mkdir
-from os.path import join as pjoin, isdir
-
-from data_measurements import dataset_statistics
-from data_measurements import dataset_utils
-
-
-
-def load_or_prepare_widgets(ds_args, show_embeddings=False, use_cache=False):
-    """
-    Loader specifically for the widgets used in the app -- does not compute
-    intermediate files, unless they are not there and are needed for a file
-    used in the UI.
-    Does not take specifications from user; does all widgets.
-    Args:
-        ds_args: Dataset configuration settings (config name, split, etc)
-        show_embeddings: Whether to compute embeddings (slow)
-        use_cache: Whether to grab files that have already been computed
-
-    Returns:
-        Saves files to disk in cache_dir, if user has not specified another dir.
-    """
-
-    if not isdir(ds_args["cache_dir"]):
-        print("Creating cache")
-        # We need to preprocess everything.
-        # This should eventually all go into a prepare_dataset CLI
-        mkdir(ds_args["cache_dir"])
-
-
-    dstats = dataset_statistics.DatasetStatisticsCacheClass(**ds_args,
-                                                            use_cache=use_cache)
-    # Embeddings widget
-    dstats.load_or_prepare_dataset()
-    # Header widget
-    dstats.load_or_prepare_dset_peek()
-    # General stats widget
-    dstats.load_or_prepare_general_stats()
-    # Labels widget
-    try:
-        dstats.set_label_field(ds_args['label_field'])
-        dstats.load_or_prepare_labels()
-    except:
-        pass
-    # Text lengths widget
-    dstats.load_or_prepare_text_lengths()
-    if show_embeddings:
-        # Embeddings widget
-        dstats.load_or_prepare_embeddings()
-    # Text duplicates widget
-    dstats.load_or_prepare_text_duplicates()
-    # nPMI widget
-    dstats.load_or_prepare_npmi()
-    npmi_stats = dstats.npmi_stats
-    # Handling for all pairs; in the UI, people select.
-    do_npmi(npmi_stats)
-    # Zipf widget
-    dstats.load_or_prepare_zipf()
-
-
-def load_or_prepare(dataset_args, use_cache=False):
-    """
-    Users can specify which aspects of the dataset they would like to compute.
-    This additionally computes intermediate files not used in the UI.
-    If the calculation flag is not specified by the user (-w), calculates all
-    except for embeddings, as those are quite time consuming so should be
-    specified separately.
-    Args:
-        dataset_args: Dataset configuration settings (config name, split, etc)
-        use_cache: Whether to grab files that have already been computed
-
-    Returns:
-        Saves files to disk in cache_dir, if user has not specified another dir.
-    """
-    all = False
-    dstats = dataset_statistics.DatasetStatisticsCacheClass(**dataset_args,
-                                                            use_cache=use_cache)
-    print("Loading dataset.")
-    dstats.load_or_prepare_dataset()
-    print("Dataset loaded.  Preparing vocab.")
-    dstats.load_or_prepare_vocab()
-    print("Vocab prepared.")
-
-    if not dataset_args["calculation"]:
-        all = True
-
-    if all or dataset_args["calculation"] == "general":
-        print("\n* Calculating general statistics.")
-        dstats.load_or_prepare_general_stats()
-        print("Done!")
-        print("Basic text statistics now available at %s." %
-              dstats.general_stats_json_fid)
-        print(
-            "Text duplicates now available at %s." % dstats.dup_counts_df_fid
-        )
-
-    if all or dataset_args["calculation"] == "lengths":
-        print("\n* Calculating text lengths.")
-        dstats.load_or_prepare_text_lengths()
-        print("Done!")
-
-    if all or dataset_args["calculation"] == "labels":
-        if not dstats.label_field:
-            print("Warning: You asked for label calculation, but didn't "
-                  "provide the labels field name.  Assuming it is 'label'...")
-            dstats.set_label_field("label")
-        else:
-            print("\n* Calculating label distribution.")
-            dstats.load_or_prepare_labels()
-            fig_label_html = pjoin(dstats.cache_path, "labels_fig.html")
-            fig_label_json = pjoin(dstats.cache_path, "labels.json")
-            dstats.fig_labels.write_html(fig_label_html)
-            with open(fig_label_json, "w+") as f:
-                json.dump(dstats.fig_labels.to_json(), f)
-            print("Done!")
-            print("Label distribution now available at %s." %
-                  dstats.label_dset_fid)
-            print("Figure saved to %s." % fig_label_html)
-
-    if all or dataset_args["calculation"] == "npmi":
-        print("\n* Preparing nPMI.")
-        npmi_stats = dataset_statistics.nPMIStatisticsCacheClass(
-            dstats, use_cache=use_cache
-        )
-        do_npmi(npmi_stats)
-        print("Done!")
-        print(
-            "nPMI results now available in %s for all identity terms that "
-            "occur more than 10 times and all words that "
-            "co-occur with both terms."
-            % npmi_stats.pmi_cache_path
-        )
-
-    if all or dataset_args["calculation"] == "zipf":
-        print("\n* Preparing Zipf.")
-        zipf_fig_fid = pjoin(dstats.cache_path, "zipf_fig.html")
-        zipf_json_fid = pjoin(dstats.cache_path, "zipf_fig.json")
-        dstats.load_or_prepare_zipf()
-        zipf_fig = dstats.zipf_fig
-        with open(zipf_json_fid, "w+") as f:
-            json.dump(zipf_fig.to_json(), f)
-        zipf_fig.write_html(zipf_fig_fid)
-        print("Done!")
-        print("Zipf results now available at %s." % dstats.zipf_fid)
-        print(
-            "Figure saved to %s, with corresponding json at %s."
-            % (zipf_fig_fid, zipf_json_fid)
-        )
-
-    # Don't do this one until someone specifically asks for it -- takes awhile.
-    if dataset_args["calculation"] == "embeddings":
-        print("\n* Preparing text embeddings.")
-        dstats.load_or_prepare_embeddings()
-
-
-def do_npmi(npmi_stats):
-    available_terms = npmi_stats.load_or_prepare_npmi_terms()
-    completed_pairs = {}
-    print("Iterating through terms for joint npmi.")
-    for term1 in available_terms:
-        for term2 in available_terms:
-            if term1 != term2:
-                sorted_terms = tuple(sorted([term1, term2]))
-                if sorted_terms not in completed_pairs:
-                    term1, term2 = sorted_terms
-                    print("Computing nPMI statistics for %s and %s" % (term1, term2))
-                    _ = npmi_stats.load_or_prepare_joint_npmi(sorted_terms)
-                    completed_pairs[tuple(sorted_terms)] = {}
-
-
-def get_text_label_df(
-    ds_name,
-    config_name,
-    split_name,
-    text_field,
-    label_field,
-    calculation,
-    out_dir,
-    use_cache=True,
-):
-    if not use_cache:
-        print("Not using any cache; starting afresh")
-    ds_name_to_dict = dataset_utils.get_dataset_info_dicts(ds_name)
-    if label_field:
-        label_field, label_names = (
-            ds_name_to_dict[ds_name][config_name]["features"][label_field][0]
-            if len(ds_name_to_dict[ds_name][config_name]["features"][label_field]) > 0
-            else ((), [])
-        )
-    else:
-        label_field = ()
-        label_names = []
-    dataset_args = {
-        "dset_name": ds_name,
-        "dset_config": config_name,
-        "split_name": split_name,
-        "text_field": text_field,
-        "label_field": label_field,
-        "label_names": label_names,
-        "calculation": calculation,
-        "cache_dir": out_dir,
-    }
-    load_or_prepare(dataset_args, use_cache=use_cache)
-
-
-def main():
-    # TODO: Make this the Hugging Face arg parser
-    parser = argparse.ArgumentParser(
-        formatter_class=argparse.RawDescriptionHelpFormatter,
-        description=textwrap.dedent(
-            """
-
-         Example for hate speech18 dataset:
-         python3 run_data_measurements.py --dataset="hate_speech18" --config="default" --split="train" --feature="text"
-
-         Example for IMDB dataset:
-         python3 run_data_measurements.py --dataset="imdb" --config="plain_text" --split="train" --label_field="label" --feature="text"
-         """
-        ),
-    )
-
-    parser.add_argument(
-        "-d", "--dataset", required=True, help="Name of dataset to prepare"
-    )
-    parser.add_argument(
-        "-c", "--config", required=True, help="Dataset configuration to prepare"
-    )
-    parser.add_argument(
-        "-s", "--split", required=True, type=str, help="Dataset split to prepare"
-    )
-    parser.add_argument(
-        "-f",
-        "--feature",
-        required=True,
-        type=str,
-        default="text",
-        help="Text column to prepare",
-    )
-    parser.add_argument(
-        "-w",
-        "--calculation",
-        help="""What to calculate (defaults to everything except embeddings).\n
-                                                    Options are:\n
-
-                                                    - `general` (for duplicate counts, missing values, length statistics.)\n
-
-                                                    - `lengths` for text length distribution\n
-
-                                                    - `labels` for label distribution\n
-
-                                                    - `embeddings` (Warning: Slow.)\n
-
-                                                    - `npmi` for word associations\n
-
-                                                    - `zipf` for zipfian statistics
-                                                    """,
-    )
-    parser.add_argument(
-        "-l",
-        "--label_field",
-        type=str,
-        required=False,
-        default="",
-        help="Field name for label column in dataset (Required if there is a label field that you want information about)",
-    )
-    parser.add_argument(
-        "--cached",
-        default=False,
-        required=False,
-        action="store_true",
-        help="Whether to use cached files (Optional)",
-    )
-    parser.add_argument(
-        "--do_html",
-        default=False,
-        required=False,
-        action="store_true",
-        help="Whether to write out corresponding HTML files (Optional)",
-    )
-    parser.add_argument("--out_dir", default="cache_dir", help="Where to write out to.")
-
-    args = parser.parse_args()
-    print("Proceeding with the following arguments:")
-    print(args)
-    # run_data_measurements.py -d hate_speech18 -c default -s train -f text -w npmi
-    get_text_label_df(args.dataset, args.config, args.split, args.feature,
-                      args.label_field, args.calculation, args.out_dir,
-                      use_cache=args.cached)
-    print()
-
-
-if __name__ == "__main__":
-    main()
diff --git a/spaces/hyxue/HiFiFace-inference-demo/Deep3DFaceRecon_pytorch/README.md b/spaces/hyxue/HiFiFace-inference-demo/Deep3DFaceRecon_pytorch/README.md
deleted file mode 100644
index 8a1b306c8cdec09533ed4cd27ca0799b7f9ab53f..0000000000000000000000000000000000000000
--- a/spaces/hyxue/HiFiFace-inference-demo/Deep3DFaceRecon_pytorch/README.md
+++ /dev/null
@@ -1,256 +0,0 @@
-## Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set —— PyTorch implementation ##
-
-<p align="center"> 
-<img src="/images/example.gif">
-</p>
-
-This is an unofficial official pytorch implementation of the following paper:
-
-Y. Deng, J. Yang, S. Xu, D. Chen, Y. Jia, and X. Tong, [Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set](https://arxiv.org/abs/1903.08527), IEEE Computer Vision and Pattern Recognition Workshop (CVPRW) on Analysis and Modeling of Faces and Gestures (AMFG), 2019. (**_Best Paper Award!_**)
-
-The method enforces a hybrid-level weakly-supervised training for CNN-based 3D face reconstruction. It is fast, accurate, and robust to pose and occlussions. It achieves state-of-the-art performance on multiple datasets such as FaceWarehouse, MICC Florence and NoW Challenge.
-
-
-For the original tensorflow implementation, check this [repo](https://github.com/microsoft/Deep3DFaceReconstruction).
-
-This implementation is written by S. Xu.
-
-## Performance
-
-### ● Reconstruction accuracy
-
-The pytorch implementation achieves lower shape reconstruction error (9% improvement) compare to the [original tensorflow implementation](https://github.com/microsoft/Deep3DFaceReconstruction). Quantitative evaluation (average shape errors in mm) on several benchmarks is as follows:
-
-|Method|FaceWareHouse|MICC Florence     | NoW Challenge |
-|:----:|:-----------:|:-----------:|:-----------:|
-|Deep3DFace Tensorflow |  1.81±0.50  |  1.67±0.50  | 1.54±1.29 |
-|**Deep3DFace PyTorch** |**1.64±0.50**|**1.53±0.45**| **1.41±1.21** |
-
-The comparison result with state-of-the-art public 3D face reconstruction methods on the NoW face benchmark is as follows:
-|Rank|Method|Median(mm)    | Mean(mm) | Std(mm) |
-|:----:|:-----------:|:-----------:|:-----------:|:-----------:|
-| 1. | [DECA\[Feng et al., SIGGRAPH 2021\]](https://github.com/YadiraF/DECA)|1.09|1.38|1.18|
-| **2.** | **Deep3DFace PyTorch**|**1.11**|**1.41**|**1.21**|
-| 3. | 	[RingNet [Sanyal et al., CVPR 2019]](https://github.com/soubhiksanyal/RingNet) | 1.21 | 1.53 | 1.31 |
-| 4. | [Deep3DFace [Deng et al., CVPRW 2019]](https://github.com/microsoft/Deep3DFaceReconstruction) | 1.23 | 1.54 | 1.29 |
-| 5. | [3DDFA-V2 [Guo et al., ECCV 2020]](https://github.com/cleardusk/3DDFA_V2) | 1.23 | 1.57 | 1.39 |
-| 6. | [MGCNet [Shang et al., ECCV 2020]](https://github.com/jiaxiangshang/MGCNet) | 1.31 | 1.87 | 2.63 |
-| 7. | [PRNet [Feng et al., ECCV 2018]](https://github.com/YadiraF/PRNet) | 1.50 | 1.98 | 1.88 |
-| 8. | [3DMM-CNN [Tran et al., CVPR 2017]](https://github.com/anhttran/3dmm_cnn) | 1.84 | 2.33 | 2.05 |
-
-For more details about the evaluation, check [Now Challenge](https://ringnet.is.tue.mpg.de/challenge.html) website.
-
-**_A recent benchmark [REALY](https://www.realy3dface.com/) indicates that our method still has the SOTA performance! You can check their paper and website for more details._**
-
-### ● Visual quality
-The pytorch implementation achieves better visual consistency with the input images compare to the original tensorflow version.
-
-<p align="center"> 
-<img src="/images/compare.png">
-</p>
-
-### ● Speed
-The training speed is on par with the original tensorflow implementation. For more information, see [here](https://github.com/sicxu/Deep3DFaceRecon_pytorch#train-the-face-reconstruction-network).
-
-## Major changes
-
-### ● Differentiable renderer
-
-We use [Nvdiffrast](https://nvlabs.github.io/nvdiffrast/) which is a pytorch library that provides high-performance primitive operations for rasterization-based differentiable rendering. The original tensorflow implementation used [tf_mesh_renderer](https://github.com/google/tf_mesh_renderer) instead.
-
-### ● Face recognition model
-
-We use [Arcface](https://github.com/deepinsight/insightface/tree/master/recognition/arcface_torch), a state-of-the-art face recognition model, for perceptual loss computation. By contrast, the original tensorflow implementation used [Facenet](https://github.com/davidsandberg/facenet).
-
-### ● Training configuration
-
-Data augmentation is used in the training process which contains random image shifting, scaling, rotation, and flipping. We also enlarge the training batchsize from 5 to 32 to stablize the training process. 
-
-### ● Training data
-
-We use an extra high quality face image dataset [FFHQ](https://github.com/NVlabs/ffhq-dataset) to increase the diversity of training data.
-
-## Requirements
-**This implementation is only tested under Ubuntu environment with Nvidia GPUs and CUDA installed.**
-
-## Installation
-1. Clone the repository and set up a conda environment with all dependencies as follows:
-```
-git clone https://github.com/sicxu/Deep3DFaceRecon_pytorch.git
-cd Deep3DFaceRecon_pytorch
-conda env create -f environment.yml
-source activate deep3d_pytorch
-```
-
-2. Install Nvdiffrast library:
-```
-git clone https://github.com/NVlabs/nvdiffrast
-cd nvdiffrast    # ./Deep3DFaceRecon_pytorch/nvdiffrast
-pip install .
-```
-
-3. Install Arcface Pytorch:
-```
-cd ..    # ./Deep3DFaceRecon_pytorch
-git clone https://github.com/deepinsight/insightface.git
-cp -r ./insightface/recognition/arcface_torch ./models/
-```
-## Inference with a pre-trained model
-
-### Prepare prerequisite models
-1. Our method uses [Basel Face Model 2009 (BFM09)](https://faces.dmi.unibas.ch/bfm/main.php?nav=1-0&id=basel_face_model) to represent 3d faces. Get access to BFM09 using this [link](https://faces.dmi.unibas.ch/bfm/main.php?nav=1-2&id=downloads). After getting the access, download "01_MorphableModel.mat". In addition, we use an Expression Basis provided by [Guo et al.](https://github.com/Juyong/3DFace). Download the Expression Basis (Exp_Pca.bin) using this [link (google drive)](https://drive.google.com/file/d/1bw5Xf8C12pWmcMhNEu6PtsYVZkVucEN6/view?usp=sharing). Organize all files into the following structure:
-```
-Deep3DFaceRecon_pytorch
-│
-└─── BFM
-    │
-    └─── 01_MorphableModel.mat
-    │
-    └─── Exp_Pca.bin
-    |
-    └─── ...
-```
-2. We provide a model trained on a combination of [CelebA](http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html), 
-[LFW](http://vis-www.cs.umass.edu/lfw/), [300WLP](http://www.cbsr.ia.ac.cn/users/xiangyuzhu/projects/3DDFA/main.htm),
-[IJB-A](https://www.nist.gov/programs-projects/face-challenges), [LS3D-W](https://www.adrianbulat.com/face-alignment), and [FFHQ](https://github.com/NVlabs/ffhq-dataset) datasets. Download the pre-trained model using this [link (google drive)](https://drive.google.com/drive/folders/1liaIxn9smpudjjqMaWWRpP0mXRW_qRPP?usp=sharing) and organize the directory into the following structure:
-```
-Deep3DFaceRecon_pytorch
-│
-└─── checkpoints
-    │
-    └─── <model_name>
-        │
-        └─── epoch_20.pth
-
-```
-
-### Test with custom images
-To reconstruct 3d faces from test images, organize the test image folder as follows:
-```
-Deep3DFaceRecon_pytorch
-│
-└─── <folder_to_test_images>
-    │
-    └─── *.jpg/*.png
-    |
-    └─── detections
-        |
-	└─── *.txt
-```
-The \*.jpg/\*.png files are test images. The \*.txt files are detected 5 facial landmarks with a shape of 5x2, and have the same name as the corresponding images. Check [./datasets/examples](datasets/examples) for a reference.
-
-Then, run the test script:
-```
-# get reconstruction results of your custom images
-python test.py --name=<model_name> --epoch=20 --img_folder=<folder_to_test_images>
-
-# get reconstruction results of example images
-python test.py --name=<model_name> --epoch=20 --img_folder=./datasets/examples
-```
-**_Following [#108](https://github.com/sicxu/Deep3DFaceRecon_pytorch/issues/108), if you don't have OpenGL environment, you can simply add "--use_opengl False" to use CUDA context. Make sure you have updated the nvdiffrast to the latest version._**
-
-Results will be saved into ./checkpoints/<model_name>/results/<folder_to_test_images>, which contain the following files:
-| \*.png | A combination of cropped input image, reconstructed image, and visualization of projected landmarks.
-|:----|:-----------|
-| \*.obj | Reconstructed 3d face mesh with predicted color (texture+illumination) in the world coordinate space. Best viewed in Meshlab. |
-| \*.mat | Predicted 257-dimensional coefficients and 68 projected 2d facial landmarks. Best viewed in Matlab.
-
-## Training a model from scratch
-### Prepare prerequisite models
-1. We rely on [Arcface](https://github.com/deepinsight/insightface/tree/master/recognition/arcface_torch) to extract identity features for loss computation. Download the pre-trained model from Arcface using this [link](https://github.com/deepinsight/insightface/tree/master/recognition/arcface_torch#ms1mv3). By default, we use the resnet50 backbone ([ms1mv3_arcface_r50_fp16](https://onedrive.live.com/?authkey=%21AFZjr283nwZHqbA&id=4A83B6B633B029CC%215583&cid=4A83B6B633B029CC)), organize the download files into the following structure:
-```
-Deep3DFaceRecon_pytorch
-│
-└─── checkpoints
-    │
-    └─── recog_model
-        │
-        └─── ms1mv3_arcface_r50_fp16
-	    |
-	    └─── backbone.pth
-```
-2. We initialize R-Net using the weights trained on [ImageNet](https://image-net.org/). Download the weights provided by PyTorch using this [link](https://download.pytorch.org/models/resnet50-0676ba61.pth), and organize the file as the following structure:
-```
-Deep3DFaceRecon_pytorch
-│
-└─── checkpoints
-    │
-    └─── init_model
-        │
-        └─── resnet50-0676ba61.pth
-```
-3. We provide a landmark detector (tensorflow model) to extract 68 facial landmarks for loss computation. The detector is trained on [300WLP](http://www.cbsr.ia.ac.cn/users/xiangyuzhu/projects/3DDFA/main.htm), [LFW](http://vis-www.cs.umass.edu/lfw/), and [LS3D-W](https://www.adrianbulat.com/face-alignment) datasets. Download the trained model using this [link (google drive)](https://drive.google.com/file/d/1Jl1yy2v7lIJLTRVIpgg2wvxYITI8Dkmw/view?usp=sharing) and organize the file as follows:
-```
-Deep3DFaceRecon_pytorch
-│
-└─── checkpoints
-    │
-    └─── lm_model
-        │
-        └─── 68lm_detector.pb
-```
-### Data preparation
-1. To train a model with custom images，5 facial landmarks of each image are needed in advance for an image pre-alignment process. We recommend using [dlib](http://dlib.net/) or [MTCNN](https://github.com/ipazc/mtcnn) to detect these landmarks. Then, organize all files into the following structure:
-```
-Deep3DFaceRecon_pytorch
-│
-└─── datasets
-    │
-    └─── <folder_to_training_images>
-        │
-        └─── *.png/*.jpg
-	|
-	└─── detections
-            |
-	    └─── *.txt
-```
-The \*.txt files contain 5 facial landmarks with a shape of 5x2, and should have the same name with their corresponding images.
-
-2. Generate 68 landmarks and skin attention mask for images using the following script:
-```
-# preprocess training images
-python data_preparation.py --img_folder <folder_to_training_images>
-
-# alternatively, you can preprocess multiple image folders simultaneously
-python data_preparation.py --img_folder <folder_to_training_images1> <folder_to_training_images2> <folder_to_training_images3>
-
-# preprocess validation images
-python data_preparation.py --img_folder <folder_to_validation_images> --mode=val
-```
-The script will generate files of landmarks and skin masks, and save them into ./datasets/<folder_to_training_images>. In addition, it also generates a file containing the path of all training data into ./datalist which will then be used in the training script.
-
-### Train the face reconstruction network
-Run the following script to train a face reconstruction model using the pre-processed data:
-```
-# train with single GPU
-python train.py --name=<custom_experiment_name> --gpu_ids=0
-
-# train with multiple GPUs
-python train.py --name=<custom_experiment_name> --gpu_ids=0,1
-
-# train with other custom settings
-python train.py --name=<custom_experiment_name> --gpu_ids=0 --batch_size=32 --n_epochs=20
-```
-Training logs and model parameters will be saved into ./checkpoints/<custom_experiment_name>. 
-
-By default, the script uses a batchsize of 32 and will train the model with 20 epochs. For reference, the pre-trained model in this repo is trained with the default setting on a image collection of 300k images. A single iteration takes 0.8~0.9s on a single Tesla M40 GPU. The total training process takes around two days.
-
-To use a trained model, see [Inference](https://github.com/sicxu/Deep3DFaceRecon_pytorch#inference-with-a-pre-trained-model) section.
-## Contact
-If you have any questions, please contact the paper authors.
-
-## Citation
-
-Please cite the following paper if this model helps your research:
-
-	@inproceedings{deng2019accurate,
-	    title={Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set},
-	    author={Yu Deng and Jiaolong Yang and Sicheng Xu and Dong Chen and Yunde Jia and Xin Tong},
-	    booktitle={IEEE Computer Vision and Pattern Recognition Workshops},
-	    year={2019}
-	}
-##
-The face images on this page are from the public [CelebA](http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html) dataset released by MMLab, CUHK.
-
-Part of the code in this implementation takes [CUT](https://github.com/taesungp/contrastive-unpaired-translation) as a reference.
-
diff --git a/spaces/hyxue/HiFiFace-inference-demo/Deep3DFaceRecon_pytorch/data/template_dataset.py b/spaces/hyxue/HiFiFace-inference-demo/Deep3DFaceRecon_pytorch/data/template_dataset.py
deleted file mode 100644
index d776bde9c36396865e149922305cb2284942529b..0000000000000000000000000000000000000000
--- a/spaces/hyxue/HiFiFace-inference-demo/Deep3DFaceRecon_pytorch/data/template_dataset.py
+++ /dev/null
@@ -1,80 +0,0 @@
-"""Dataset class template
-
-This module provides a template for users to implement custom datasets.
-You can specify '--dataset_mode template' to use this dataset.
-The class name should be consistent with both the filename and its dataset_mode option.
-The filename should be <dataset_mode>_dataset.py
-The class name should be <Dataset_mode>Dataset.py
-You need to implement the following functions:
-    -- <modify_commandline_options>:　Add dataset-specific options and rewrite default values for existing options.
-    -- <__init__>: Initialize this dataset class.
-    -- <__getitem__>: Return a data point and its metadata information.
-    -- <__len__>: Return the number of images.
-"""
-from data.base_dataset import BaseDataset
-from data.base_dataset import get_transform
-
-# from data.image_folder import make_dataset
-# from PIL import Image
-
-
-class TemplateDataset(BaseDataset):
-    """A template dataset class for you to implement custom datasets."""
-
-    @staticmethod
-    def modify_commandline_options(parser, is_train):
-        """Add new dataset-specific options, and rewrite default values for existing options.
-
-        Parameters:
-            parser          -- original option parser
-            is_train (bool) -- whether training phase or test phase. You can use this flag to add training-specific or test-specific options.
-
-        Returns:
-            the modified parser.
-        """
-        parser.add_argument("--new_dataset_option", type=float, default=1.0, help="new dataset option")
-        parser.set_defaults(max_dataset_size=10, new_dataset_option=2.0)  # specify dataset-specific default values
-        return parser
-
-    def __init__(self, opt):
-        """Initialize this dataset class.
-
-        Parameters:
-            opt (Option class) -- stores all the experiment flags; needs to be a subclass of BaseOptions
-
-        A few things can be done here.
-        - save the options (have been done in BaseDataset)
-        - get image paths and meta information of the dataset.
-        - define the image transformation.
-        """
-        # save the option and dataset root
-        BaseDataset.__init__(self, opt)
-        # get the image paths of your dataset;
-        self.image_paths = (
-            []
-        )  # You can call sorted(make_dataset(self.root, opt.max_dataset_size)) to get all the image paths under the directory self.root
-        # define the default transform function. You can use <base_dataset.get_transform>; You can also define your custom transform function
-        self.transform = get_transform(opt)
-
-    def __getitem__(self, index):
-        """Return a data point and its metadata information.
-
-        Parameters:
-            index -- a random integer for data indexing
-
-        Returns:
-            a dictionary of data with their names. It usually contains the data itself and its metadata information.
-
-        Step 1: get a random image path: e.g., path = self.image_paths[index]
-        Step 2: load your data from the disk: e.g., image = Image.open(path).convert('RGB').
-        Step 3: convert your data to a PyTorch tensor. You can use helpder functions such as self.transform. e.g., data = self.transform(image)
-        Step 4: return a data point as a dictionary.
-        """
-        path = "temp"  # needs to be a string
-        data_A = None  # needs to be a tensor
-        data_B = None  # needs to be a tensor
-        return {"data_A": data_A, "data_B": data_B, "path": path}
-
-    def __len__(self):
-        """Return the total number of images."""
-        return len(self.image_paths)
diff --git a/spaces/hzwluoye/gpt4/client/css/global.css b/spaces/hzwluoye/gpt4/client/css/global.css
deleted file mode 100644
index e46316f853d39f53267abc42e2888cd742d154f2..0000000000000000000000000000000000000000
--- a/spaces/hzwluoye/gpt4/client/css/global.css
+++ /dev/null
@@ -1,85 +0,0 @@
-@import url("https://fonts.googleapis.com/css2?family=Inter:wght@100;200;300;400;500;600;700;800;900&display=swap");
-* {
-	--font-1: "Inter", sans-serif;
-	--section-gap: 24px;
-	--border-radius-1: 8px;
-	margin: 0;
-	padding: 0;
-	box-sizing: border-box;
-	position: relative;
-	font-family: var(--font-1);
-}
-
-.theme-light {
-	--colour-1: #f5f5f5;
-	--colour-2: #000000;
-	--colour-3: #474747;
-	--colour-4: #949494;
-	--colour-5: #ebebeb;
-	--colour-6: #dadada;
-
-	--accent: #3a3a3a;
-	--blur-bg: #ffffff;
-	--blur-border: #dbdbdb;
-	--user-input: #282828;
-	--conversations: #666666;
-}
-
-.theme-dark {
-	--colour-1: #181818;
-	--colour-2: #ccc;
-	--colour-3: #dadada;
-	--colour-4: #f0f0f0;
-	--colour-5: #181818;
-	--colour-6: #242424;
-
-	--accent: #151718;
-	--blur-bg: #242627;
-	--blur-border: #242627;
-	--user-input: #f5f5f5;
-	--conversations: #555555;
-}
-
-html,
-body {
-	background: var(--colour-1);
-	color: var(--colour-3);
-}
-
-ol,
-ul {
-	padding-left: 20px;
-}
-
-.shown {
-	display: flex !important;
-}
-
-a:-webkit-any-link {
-	color: var(--accent);
-}
-
-.hidden {
-	display: none !important;
-}
-
-.fade-in {
-	opacity: 0;
-	animation: fadeIn 1s forwards;
-}
-
-pre {
-	white-space: pre-wrap;
-}
-
-@keyframes fadeIn {
-	to {
-		opacity: 1;
-	}
-}
-
-@media screen and (max-height: 720px) {
-	:root {
-		--section-gap: 16px;
-	}
-}
diff --git a/spaces/hzy123/bingo/src/lib/isomorphic/index.ts b/spaces/hzy123/bingo/src/lib/isomorphic/index.ts
deleted file mode 100644
index 738dc92f74079ab762d584fb7422a8c8c3b61547..0000000000000000000000000000000000000000
--- a/spaces/hzy123/bingo/src/lib/isomorphic/index.ts
+++ /dev/null
@@ -1,17 +0,0 @@
-'use client'
-
-import Default from './browser'
-
-let exportsModel: any = {}
-
-if (process.browser) {
-  Object.assign(exportsModel, require('./browser').default)
-} else {
-  Object.assign(exportsModel, require('./node').default)
-}
-
-export default exportsModel! as typeof Default
-
-export const fetch: typeof Default.fetch = exportsModel!.fetch
-export const WebSocket: typeof Default.WebSocket = exportsModel!.WebSocket
-export const debug: typeof Default.debug = exportsModel!.debug
diff --git a/spaces/ibm-nasa-geospatial/Prithvi-100M-demo/app.py b/spaces/ibm-nasa-geospatial/Prithvi-100M-demo/app.py
deleted file mode 100644
index 102d403afc8fcbc782f168f6f5866c459bc15ee0..0000000000000000000000000000000000000000
--- a/spaces/ibm-nasa-geospatial/Prithvi-100M-demo/app.py
+++ /dev/null
@@ -1,456 +0,0 @@
-#### pull files from hub
-from huggingface_hub import hf_hub_download
-import os
-yaml_file_path=hf_hub_download(repo_id="ibm-nasa-geospatial/Prithvi-100M", filename="Prithvi_100M_config.yaml", token=os.environ.get("token"))
-checkpoint=hf_hub_download(repo_id="ibm-nasa-geospatial/Prithvi-100M", filename='Prithvi_100M.pt', token=os.environ.get("token"))
-model_def=hf_hub_download(repo_id="ibm-nasa-geospatial/Prithvi-100M", filename='Prithvi.py', token=os.environ.get("token"))
-os.system(f'cp {model_def} .')
-#####
-import argparse
-import functools
-import os
-from typing import List
-
-import numpy as np
-import rasterio
-import torch
-import yaml
-from einops import rearrange
-
-from Prithvi import MaskedAutoencoderViT
-import gradio as gr
-from functools import partial
-
-
-NO_DATA = -9999
-NO_DATA_FLOAT = 0.0001
-PERCENTILES = (0.1, 99.9)
-
-
-def process_channel_group(orig_img, new_img, channels, data_mean, data_std):
-    """ Process *orig_img* and *new_img* for RGB visualization. Each band is rescaled back to the
-        original range using *data_mean* and *data_std* and then lowest and highest percentiles are
-        removed to enhance contrast. Data is rescaled to (0, 1) range and stacked channels_first.
-    Args:
-        orig_img: torch.Tensor representing original image (reference) with shape = (bands, H, W).
-        new_img: torch.Tensor representing image with shape = (bands, H, W).
-        channels: list of indices representing RGB channels.
-        data_mean: list of mean values for each band.
-        data_std: list of std values for each band.
-    Returns:
-        torch.Tensor with shape (num_channels, height, width) for original image
-        torch.Tensor with shape (num_channels, height, width) for the other image
-    """
-
-    stack_c = [], []
-
-    for c in channels:
-        orig_ch = orig_img[c, ...]
-        valid_mask = torch.ones_like(orig_ch, dtype=torch.bool)
-        valid_mask[orig_ch == NO_DATA_FLOAT] = False
-
-        # Back to original data range
-        orig_ch = (orig_ch * data_std[c]) + data_mean[c]
-        new_ch = (new_img[c, ...] * data_std[c]) + data_mean[c]
-
-        # Rescale (enhancing contrast)
-        min_value, max_value = np.percentile(orig_ch[valid_mask], PERCENTILES)
-
-        orig_ch = torch.clamp((orig_ch - min_value) / (max_value - min_value), 0, 1)
-        new_ch = torch.clamp((new_ch - min_value) / (max_value - min_value), 0, 1)
-
-        # No data as zeros
-        orig_ch[~valid_mask] = 0
-        new_ch[~valid_mask] = 0
-
-        stack_c[0].append(orig_ch)
-        stack_c[1].append(new_ch)
-
-    # Channels first
-    stack_orig = torch.stack(stack_c[0], dim=0)
-    stack_rec = torch.stack(stack_c[1], dim=0)
-
-    return stack_orig, stack_rec
-
-
-def read_geotiff(file_path: str):
-    """ Read all bands from *file_path* and returns image + meta info.
-    Args:
-        file_path: path to image file.
-    Returns:
-        np.ndarray with shape (bands, height, width)
-        meta info dict
-    """
-
-    with rasterio.open(file_path) as src:
-        img = src.read()
-        meta = src.meta
-
-    return img, meta
-
-
-def save_geotiff(image, output_path: str, meta: dict):
-    """ Save multi-band image in Geotiff file.
-    Args:
-        image: np.ndarray with shape (bands, height, width)
-        output_path: path where to save the image
-        meta: dict with meta info.
-    """
-
-    with rasterio.open(output_path, "w", **meta) as dest:
-        for i in range(image.shape[0]):
-            dest.write(image[i, :, :], i + 1)
-
-    return
-
-
-def _convert_np_uint8(float_image: torch.Tensor):
-
-    image = float_image.numpy() * 255.0
-    image = image.astype(dtype=np.uint8)
-    image = image.transpose((1, 2, 0))
-
-    return image
-
-
-def load_example(file_paths: List[str], mean: List[float], std: List[float]):
-    """ Build an input example by loading images in *file_paths*.
-    Args:
-        file_paths: list of file paths .
-        mean: list containing mean values for each band in the images in *file_paths*.
-        std: list containing std values for each band in the images in *file_paths*.
-    Returns:
-        np.array containing created example
-        list of meta info for each image in *file_paths*
-    """
-
-    imgs = []
-    metas = []
-
-    for file in file_paths:
-        img, meta = read_geotiff(file)
-        img = img[:6]*10000 if img[:6].mean() <= 2 else img[:6]
-
-        # Rescaling (don't normalize on nodata)
-        img = np.moveaxis(img, 0, -1)   # channels last for rescaling
-        img = np.where(img == NO_DATA, NO_DATA_FLOAT, (img - mean) / std)
-
-        imgs.append(img)
-        metas.append(meta)
-
-    imgs = np.stack(imgs, axis=0)    # num_frames, H, W, C
-    imgs = np.moveaxis(imgs, -1, 0).astype('float32')  # C, num_frames, H, W
-    imgs = np.expand_dims(imgs, axis=0)  # add batch dim
-
-    return imgs, metas
-
-
-def run_model(model: torch.nn.Module, input_data: torch.Tensor, mask_ratio: float, device: torch.device):
-    """ Run *model* with *input_data* and create images from output tokens (mask, reconstructed + visible).
-    Args:
-        model: MAE model to run.
-        input_data: torch.Tensor with shape (B, C, T, H, W).
-        mask_ratio: mask ratio to use.
-        device: device where model should run.
-    Returns:
-        3 torch.Tensor with shape (B, C, T, H, W).
-    """
-
-    with torch.no_grad():
-        x = input_data.to(device)
-
-        _, pred, mask = model(x, mask_ratio)
-
-    # Create mask and prediction images (un-patchify)
-    mask_img = model.unpatchify(mask.unsqueeze(-1).repeat(1, 1, pred.shape[-1])).detach().cpu()
-    pred_img = model.unpatchify(pred).detach().cpu()
-
-    # Mix visible and predicted patches
-    rec_img = input_data.clone()
-    rec_img[mask_img == 1] = pred_img[mask_img == 1]  # binary mask: 0 is keep, 1 is remove
-
-    # Switch zeros/ones in mask images so masked patches appear darker in plots (better visualization)
-    mask_img = (~(mask_img.to(torch.bool))).to(torch.float)
-
-    return rec_img, mask_img
-
-
-def save_rgb_imgs(input_img, rec_img, mask_img, channels, mean, std, output_dir, meta_data):
-    """ Wrapper function to save Geotiff images (original, reconstructed, masked) per timestamp.
-    Args:
-        input_img: input torch.Tensor with shape (C, T, H, W).
-        rec_img: reconstructed torch.Tensor with shape (C, T, H, W).
-        mask_img: mask torch.Tensor with shape (C, T, H, W).
-        channels: list of indices representing RGB channels.
-        mean: list of mean values for each band.
-        std: list of std values for each band.
-        output_dir: directory where to save outputs.
-        meta_data: list of dicts with geotiff meta info.
-    """
-
-    for t in range(input_img.shape[1]):
-        rgb_orig, rgb_pred = process_channel_group(orig_img=input_img[:, t, :, :],
-                                                   new_img=rec_img[:, t, :, :],
-                                                   channels=channels, data_mean=mean,
-                                                   data_std=std)
-
-        rgb_mask = mask_img[channels, t, :, :] * rgb_orig
-
-        # Saving images
-
-        save_geotiff(image=_convert_np_uint8(rgb_orig),
-                     output_path=os.path.join(output_dir, f"original_rgb_t{t}.tiff"),
-                     meta=meta_data[t])
-
-        save_geotiff(image=_convert_np_uint8(rgb_pred),
-                     output_path=os.path.join(output_dir, f"predicted_rgb_t{t}.tiff"),
-                     meta=meta_data[t])
-
-        save_geotiff(image=_convert_np_uint8(rgb_mask),
-                     output_path=os.path.join(output_dir, f"masked_rgb_t{t}.tiff"),
-                     meta=meta_data[t])
-
-
-def extract_rgb_imgs(input_img, rec_img, mask_img, channels, mean, std):
-    """ Wrapper function to save Geotiff images (original, reconstructed, masked) per timestamp.
-    Args:
-        input_img: input torch.Tensor with shape (C, T, H, W).
-        rec_img: reconstructed torch.Tensor with shape (C, T, H, W).
-        mask_img: mask torch.Tensor with shape (C, T, H, W).
-        channels: list of indices representing RGB channels.
-        mean: list of mean values for each band.
-        std: list of std values for each band.
-        output_dir: directory where to save outputs.
-        meta_data: list of dicts with geotiff meta info.
-    """
-    rgb_orig_list = []
-    rgb_mask_list = []
-    rgb_pred_list = []
-    
-    for t in range(input_img.shape[1]):
-        rgb_orig, rgb_pred = process_channel_group(orig_img=input_img[:, t, :, :],
-                                                   new_img=rec_img[:, t, :, :],
-                                                   channels=channels, data_mean=mean,
-                                                   data_std=std)
-
-        rgb_mask = mask_img[channels, t, :, :] * rgb_orig
-
-        # extract images
-        rgb_orig_list.append(_convert_np_uint8(rgb_orig))
-        rgb_mask_list.append(_convert_np_uint8(rgb_mask))
-        rgb_pred_list.append(_convert_np_uint8(rgb_pred))
-        
-    outputs = rgb_orig_list + rgb_mask_list + rgb_pred_list
-
-    return outputs
-
-
-def predict_on_images(data_files: list, mask_ratio: float, yaml_file_path: str, checkpoint: str):
-
-    
-    try:
-        data_files = [x.name for x in data_files]
-        print('Path extracted from example')
-    except:
-        print('Files submitted through UI')
-
-    # Get parameters --------
-    print('This is the printout', data_files)
-
-    with open(yaml_file_path, 'r') as f:
-        params = yaml.safe_load(f)
-
-    model_params = params["model_args"]
-    # data related
-    train_params = params["train_params"]
-    num_frames = model_params['num_frames']
-    img_size = model_params['img_size']
-    bands = train_params['bands']
-    mean = train_params['data_mean']
-    std = train_params['data_std']
-
-    batch_size = 8
-
-    mask_ratio = train_params['mask_ratio'] if mask_ratio is None else mask_ratio
-
-    # We must have *num_frames* files to build one example!
-    assert len(data_files) == num_frames, "File list must be equal to expected number of frames."
-
-    if torch.cuda.is_available():
-        device = torch.device('cuda')
-    else:
-        device = torch.device('cpu')
-
-    print(f"Using {device} device.\n")
-
-    # Loading data ---------------------------------------------------------------------------------
-
-    input_data, meta_data = load_example(file_paths=data_files, mean=mean, std=std)
-
-    # Create model and load checkpoint -------------------------------------------------------------
-
-    model = MaskedAutoencoderViT(
-            **model_params)
-
-    total_params = sum(p.numel() for p in model.parameters() if p.requires_grad)
-    print(f"\n--> Model has {total_params:,} parameters.\n")
-
-    model.to(device)
-
-    state_dict = torch.load(checkpoint, map_location=device)
-    model.load_state_dict(state_dict)
-    print(f"Loaded checkpoint from {checkpoint}")
-
-    # Running model --------------------------------------------------------------------------------
-
-    model.eval()
-    channels = [bands.index(b) for b in ['B04', 'B03', 'B02']]  # BGR -> RGB
-    
-    # Reflect pad if not divisible by img_size
-    original_h, original_w = input_data.shape[-2:]
-    pad_h = img_size - (original_h % img_size)
-    pad_w = img_size - (original_w % img_size)
-    input_data = np.pad(input_data, ((0, 0), (0, 0), (0, 0), (0, pad_h), (0, pad_w)), mode='reflect')
-
-    # Build sliding window
-    batch = torch.tensor(input_data, device='cpu')
-    windows = batch.unfold(3, img_size, img_size).unfold(4, img_size, img_size)
-    h1, w1 = windows.shape[3:5]
-    windows = rearrange(windows, 'b c t h1 w1 h w -> (b h1 w1) c t h w', h=img_size, w=img_size)
-
-    # Split into batches if number of windows > batch_size
-    num_batches = windows.shape[0] // batch_size if windows.shape[0] > batch_size else 1
-    windows = torch.tensor_split(windows, num_batches, dim=0)
-
-    # Run model
-    rec_imgs = []
-    mask_imgs = []
-    for x in windows:
-        rec_img, mask_img = run_model(model, x, mask_ratio, device)
-        rec_imgs.append(rec_img)
-        mask_imgs.append(mask_img)
-
-    rec_imgs = torch.concat(rec_imgs, dim=0)
-    mask_imgs = torch.concat(mask_imgs, dim=0)
-
-    # Build images from patches
-    rec_imgs = rearrange(rec_imgs, '(b h1 w1) c t h w -> b c t (h1 h) (w1 w)',
-                         h=img_size, w=img_size, b=1, c=len(bands), t=num_frames, h1=h1, w1=w1)
-    mask_imgs = rearrange(mask_imgs, '(b h1 w1) c t h w -> b c t (h1 h) (w1 w)',
-                          h=img_size, w=img_size, b=1, c=len(bands), t=num_frames, h1=h1, w1=w1)
-
-    # Cut padded images back to original size
-    rec_imgs_full = rec_imgs[..., :original_h, :original_w]
-    mask_imgs_full = mask_imgs[..., :original_h, :original_w]
-    batch_full = batch[..., :original_h, :original_w]
-
-    # Build RGB images
-    for d in meta_data:
-        d.update(count=3, dtype='uint8', compress='lzw', nodata=0)
-
-    # save_rgb_imgs(batch[0, ...], rec_imgs_full[0, ...], mask_imgs_full[0, ...],
-    #               channels, mean, std, output_dir, meta_data)
-
-    outputs = extract_rgb_imgs(batch_full[0, ...], rec_imgs_full[0, ...], mask_imgs_full[0, ...],
-                  channels, mean, std)
-
-
-    print("Done!")
-
-    return outputs
-
-
-
-
-func = partial(predict_on_images, yaml_file_path=yaml_file_path,checkpoint=checkpoint)
-
-def preprocess_example(example_list):
-    print('######## preprocessing here ##########')
-    example_list = [os.path.join(os.path.abspath(''), x) for x in example_list]
-    
-    return example_list
-    
-
-with gr.Blocks() as demo:
-    
-    gr.Markdown(value='# Prithvi image reconstruction demo')
-    gr.Markdown(value='''Prithvi is a first-of-its-kind temporal Vision transformer pretrained by the IBM and NASA team on continental US Harmonised Landsat Sentinel 2 (HLS) data. Particularly, the model adopts a self-supervised encoder developed with a ViT architecture and Masked AutoEncoder learning strategy, with a MSE as a loss function. The model includes spatial attention across multiple patchies and also temporal attention for each patch. More info about the model and its weights are available [here](https://huggingface.co/ibm-nasa-geospatial/Prithvi-100M).\n
-This demo showcases the image reconstracting over three timestamps, with the user providing a set of three HLS images and the model randomly masking out some proportion of the images and then reconstructing them based on the not masked portion of the images.\n
-The user needs to provide three HLS geotiff images, including the following channels in reflectance units: Blue, Green, Red, Narrow NIR, SWIR, SWIR 2.
-''')
-    with gr.Row():
-        with gr.Column():
-            inp_files = gr.Files(elem_id='files')
-            # inp_slider = gr.Slider(0, 100, value=50, label="Mask ratio", info="Choose ratio of masking between 0 and 100", elem_id='slider'),
-            btn = gr.Button("Submit")
-    with gr.Row():
-        gr.Markdown(value='## Original images')
-    with gr.Row():
-        gr.Markdown(value='T1')
-        gr.Markdown(value='T2')
-        gr.Markdown(value='T3')
-    with gr.Row():
-        out1_orig_t1=gr.Image(image_mode='RGB')
-        out2_orig_t2 = gr.Image(image_mode='RGB')
-        out3_orig_t3 = gr.Image(image_mode='RGB')
-    with gr.Row():
-        gr.Markdown(value='## Masked images')
-    with gr.Row():
-        gr.Markdown(value='T1')
-        gr.Markdown(value='T2')
-        gr.Markdown(value='T3')
-    with gr.Row():
-        out4_masked_t1=gr.Image(image_mode='RGB')
-        out5_masked_t2 = gr.Image(image_mode='RGB')
-        out6_masked_t3 = gr.Image(image_mode='RGB')
-    with gr.Row():
-        gr.Markdown(value='## Reonstructed images')
-    with gr.Row():
-        gr.Markdown(value='T1')
-        gr.Markdown(value='T2')
-        gr.Markdown(value='T3')
-    with gr.Row():
-        out7_pred_t1=gr.Image(image_mode='RGB')
-        out8_pred_t2 = gr.Image(image_mode='RGB')
-        out9_pred_t3 = gr.Image(image_mode='RGB')
-
-
-    btn.click(fn=func, 
-              # inputs=[inp_files, inp_slider], 
-              inputs=inp_files,
-              outputs=[out1_orig_t1, 
-                       out2_orig_t2, 
-                       out3_orig_t3, 
-                       out4_masked_t1, 
-                       out5_masked_t2, 
-                       out6_masked_t3,
-                       out7_pred_t1,
-                       out8_pred_t2,
-                       out9_pred_t3])
-    with gr.Row():
-        gr.Examples(examples=[[[os.path.join(os.path.dirname(__file__), "HLS.L30.T13REN.2018013T172747.v2.0.B02.B03.B04.B05.B06.B07_cropped.tif"),
-                      os.path.join(os.path.dirname(__file__), "HLS.L30.T13REN.2018029T172738.v2.0.B02.B03.B04.B05.B06.B07_cropped.tif"),
-                      os.path.join(os.path.dirname(__file__), "HLS.L30.T13REN.2018061T172724.v2.0.B02.B03.B04.B05.B06.B07_cropped.tif")]],
-                     [[os.path.join(os.path.dirname(__file__), "HLS.L30.T17RMP.2018004T155509.v2.0.B02.B03.B04.B05.B06.B07_cropped.tif"),
-                      os.path.join(os.path.dirname(__file__), "HLS.L30.T17RMP.2018036T155452.v2.0.B02.B03.B04.B05.B06.B07_cropped.tif"),
-                      os.path.join(os.path.dirname(__file__), "HLS.L30.T17RMP.2018068T155438.v2.0.B02.B03.B04.B05.B06.B07_cropped.tif")]],
-                     [[os.path.join(os.path.dirname(__file__), "HLS.L30.T18TVL.2018029T154533.v2.0.B02.B03.B04.B05.B06.B07_cropped.tif"),
-                      os.path.join(os.path.dirname(__file__), "HLS.L30.T18TVL.2018141T154435.v2.0.B02.B03.B04.B05.B06.B07_cropped.tif"),
-                      os.path.join(os.path.dirname(__file__), "HLS.L30.T18TVL.2018189T154446.v2.0.B02.B03.B04.B05.B06.B07_cropped.tif")]]],
-                    inputs=inp_files,
-                    outputs=[out1_orig_t1, 
-                           out2_orig_t2, 
-                           out3_orig_t3, 
-                           out4_masked_t1, 
-                           out5_masked_t2, 
-                           out6_masked_t3,
-                           out7_pred_t1,
-                           out8_pred_t2,
-                           out9_pred_t3],
-                    # preprocess=preprocess_example,
-                    fn=func,
-                    cache_examples=True
-    )
-    
-
-demo.launch()
\ No newline at end of file
diff --git a/spaces/imabhi/multilingual_image_translator/app.py b/spaces/imabhi/multilingual_image_translator/app.py
deleted file mode 100644
index 138f6fed119fc69a7bbaaa7d3852a38c516d368c..0000000000000000000000000000000000000000
--- a/spaces/imabhi/multilingual_image_translator/app.py
+++ /dev/null
@@ -1,42 +0,0 @@
-import streamlit as st
-
-from PIL import Image
-from gtts import gTTS
-import easyocr
-reader = easyocr.Reader(['en']) # this needs to run only once to load the model into memory
-from deep_translator import GoogleTranslator
-
-
-st.title('Multilingual Image Translator and Reader')
-image_file = st.file_uploader("Upload Images", type=["png","jpg","jpeg"])
-
-def pdf_to_text(Img_Language,image_path,Language):
-
-    image_path = Image.open(image_path)
-    # text = pytesseract.image_to_string(image_path,lang = Img_Language,config=path_to_tesseract)
-    result = reader.readtext(image_path,detail = 0)
-    text = " ".join(result)
-    # text = " ".join(text.split())
-
-    text = GoogleTranslator(source='auto', target=Language).translate(text) 
-    myobj = gTTS(text=text, lang=Language,tld='co.in', slow=False) 
-    myobj.save("test.wav") 
-    return "test.wav",text
-    # return text
-
-
-d1  =  {"Hindi":'hin','Marathi':'mar','English':'eng','Sanskrit':'san'}
-d2  =  {"Hindi":'hi','Marathi':'mr','English':'en'}
-lang1 = ['English',"Hindi",'Marathi','Sanskrit']
-lang = ["Hindi",'Marathi','English']
-
-choice1 = st.sidebar.selectbox("Image_Language",lang1)
-choice2 = st.sidebar.selectbox("Translated_Language",lang)
-
-
-if image_file is not None:    
-        st.image(image_file)
-        A,T = pdf_to_text(d1[choice1] ,image_file,d2[choice2])
-        st.write(T)
-        st.audio(A)
-    
\ No newline at end of file
diff --git a/spaces/incolor/facial_expression_classifier/app.py b/spaces/incolor/facial_expression_classifier/app.py
deleted file mode 100644
index de9127091998ae51762f8010b1146c69283102fb..0000000000000000000000000000000000000000
--- a/spaces/incolor/facial_expression_classifier/app.py
+++ /dev/null
@@ -1,84 +0,0 @@
-# Facial expression classifier
-import os
-from fastai.vision.all import *
-import gradio as gr
-
-# Emotion
-learn_emotion = load_learner('emotions_vgg19.pkl')
-learn_emotion_labels = learn_emotion.dls.vocab
-
-# Sentiment
-learn_sentiment = load_learner('sentiment_vgg19.pkl')
-learn_sentiment_labels = learn_sentiment.dls.vocab
-
-# Predict
-def predict(img):
-    img = PILImage.create(img)
-    
-    pred_emotion, pred_emotion_idx, probs_emotion = learn_emotion.predict(img)
-    
-    pred_sentiment, pred_sentiment_idx, probs_sentiment = learn_sentiment.predict(img)
-    
-    #emotions = {f'emotion_{learn_emotion_labels[i]}': float(probs_emotion[i]) for i in range(len(learn_emotion_labels))}
-    #sentiments = {f'sentiment_{learn_sentiment_labels[i]}': float(probs_sentiment[i]) for i in range(len(learn_sentiment_labels))}
-    
-    emotions = {learn_emotion_labels[i]: float(probs_emotion[i]) for i in range(len(learn_emotion_labels))}
-    sentiments = {learn_sentiment_labels[i]: float(probs_sentiment[i]) for i in range(len(learn_sentiment_labels))}
-        
-    return [emotions, sentiments] #{**emotions, **sentiments}
-
-# Gradio
-title = "Facial Emotion and Sentiment Detector"
-
-description = gr.Markdown(
-                """Ever wondered what a person might be feeling looking at their picture? 
-                 Well, now you can! Try this fun app. Just upload a facial image in JPG or
-                 PNG format. Voila! you can now see what they might have felt when the picture
-                 was taken.
-                 
-                 **Tip**: Be sure to only include face to get best results. Check some sample images
-                 below for inspiration!""").value
-
-article = gr.Markdown(
-             """**DISCLAIMER:** This model does not reveal the actual emotional state of a person. Use and 
-             interpret results at your own risk! It was built as a demo for AI course. Samples images
-             were downloaded from VG & AftenPosten news webpages. Copyrights belong to respective
-             brands. All rights reserved.
-             
-             **PREMISE:** The idea is to determine an overall sentiment of a news site on a daily basis
-             based on the pictures. We are restricting pictures to only include close-up facial
-             images.
-             
-             **DATA:** FER2013 dataset consists of 48x48 pixel grayscale images of faces. There are 28,709 
-             images in the training set and 3,589 images in the test set. However, for this demo all 
-             pictures were combined into a single dataset and 80:20 split was used for training. Images
-             are assigned one of the 7 emotions: Angry, Disgust, Fear, Happy, Sad, Surprise, and Neutral.
-             In addition to these 7 classes, images were re-classified into 3 sentiment categories based
-             on emotions:
-             
-             Positive (Happy, Surprise)
-             
-             Negative (Angry, Disgust, Fear, Sad)
-             
-             Neutral (Neutral)
-             
-             FER2013 (preliminary version) dataset can be downloaded at:
-             https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge/data
-             
-             **MODEL:** VGG19 was used as the base model and trained on FER2013 dataset. Model was trained
-             using PyTorch and FastAI. Two models were trained, one for detecting emotion and the other
-             for detecting sentiment. Although, this could have been done with just one model, here two
-             models were trained for the demo.""").value
-
-enable_queue=True
-
-examples = ['happy1.jpg', 'happy2.jpg', 'angry1.png', 'angry2.jpg', 'neutral1.jpg', 'neutral2.jpg']
-
-gr.Interface(fn = predict, 
-             inputs = gr.Image(shape=(48, 48), image_mode='L'), 
-             outputs = [gr.Label(label='Emotion'), gr.Label(label='Sentiment')], #gr.Label(),
-             title = title,
-             examples = examples,
-             description = description,
-             article=article,
-             allow_flagging='never').launch(enable_queue=enable_queue)
\ No newline at end of file
diff --git a/spaces/innnky/nanami/attentions.py b/spaces/innnky/nanami/attentions.py
deleted file mode 100644
index e76fa19a136ef55244e11f0788979a34bfe874ad..0000000000000000000000000000000000000000
--- a/spaces/innnky/nanami/attentions.py
+++ /dev/null
@@ -1,417 +0,0 @@
-import copy
-import math
-import numpy as np
-import torch
-from torch import nn
-from torch.nn import functional as F
-
-import commons
-import modules
-from modules import LayerNorm
-
-
-class Encoder(nn.Module):
-    def __init__(
-        self,
-        hidden_channels,
-        filter_channels,
-        n_heads,
-        n_layers,
-        kernel_size=1,
-        p_dropout=0.0,
-        window_size=10,
-        **kwargs
-    ):
-        super().__init__()
-        self.hidden_channels = hidden_channels
-        self.filter_channels = filter_channels
-        self.n_heads = n_heads
-        self.n_layers = n_layers
-        self.kernel_size = kernel_size
-        self.p_dropout = p_dropout
-        self.window_size = window_size
-
-        self.drop = nn.Dropout(p_dropout)
-        self.attn_layers = nn.ModuleList()
-        self.norm_layers_1 = nn.ModuleList()
-        self.ffn_layers = nn.ModuleList()
-        self.norm_layers_2 = nn.ModuleList()
-        for i in range(self.n_layers):
-            self.attn_layers.append(
-                MultiHeadAttention(
-                    hidden_channels,
-                    hidden_channels,
-                    n_heads,
-                    p_dropout=p_dropout,
-                    window_size=window_size,
-                )
-            )
-            self.norm_layers_1.append(LayerNorm(hidden_channels))
-            self.ffn_layers.append(
-                FFN(
-                    hidden_channels,
-                    hidden_channels,
-                    filter_channels,
-                    kernel_size,
-                    p_dropout=p_dropout,
-                )
-            )
-            self.norm_layers_2.append(LayerNorm(hidden_channels))
-
-    def forward(self, x, x_mask):
-        attn_mask = x_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
-        x = x * x_mask
-        for i in range(self.n_layers):
-            y = self.attn_layers[i](x, x, attn_mask)
-            y = self.drop(y)
-            x = self.norm_layers_1[i](x + y)
-
-            y = self.ffn_layers[i](x, x_mask)
-            y = self.drop(y)
-            x = self.norm_layers_2[i](x + y)
-        x = x * x_mask
-        return x
-
-
-class Decoder(nn.Module):
-    def __init__(
-        self,
-        hidden_channels,
-        filter_channels,
-        n_heads,
-        n_layers,
-        kernel_size=1,
-        p_dropout=0.0,
-        proximal_bias=False,
-        proximal_init=True,
-        **kwargs
-    ):
-        super().__init__()
-        self.hidden_channels = hidden_channels
-        self.filter_channels = filter_channels
-        self.n_heads = n_heads
-        self.n_layers = n_layers
-        self.kernel_size = kernel_size
-        self.p_dropout = p_dropout
-        self.proximal_bias = proximal_bias
-        self.proximal_init = proximal_init
-
-        self.drop = nn.Dropout(p_dropout)
-        self.self_attn_layers = nn.ModuleList()
-        self.norm_layers_0 = nn.ModuleList()
-        self.encdec_attn_layers = nn.ModuleList()
-        self.norm_layers_1 = nn.ModuleList()
-        self.ffn_layers = nn.ModuleList()
-        self.norm_layers_2 = nn.ModuleList()
-        for i in range(self.n_layers):
-            self.self_attn_layers.append(
-                MultiHeadAttention(
-                    hidden_channels,
-                    hidden_channels,
-                    n_heads,
-                    p_dropout=p_dropout,
-                    proximal_bias=proximal_bias,
-                    proximal_init=proximal_init,
-                )
-            )
-            self.norm_layers_0.append(LayerNorm(hidden_channels))
-            self.encdec_attn_layers.append(
-                MultiHeadAttention(
-                    hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout
-                )
-            )
-            self.norm_layers_1.append(LayerNorm(hidden_channels))
-            self.ffn_layers.append(
-                FFN(
-                    hidden_channels,
-                    hidden_channels,
-                    filter_channels,
-                    kernel_size,
-                    p_dropout=p_dropout,
-                    causal=True,
-                )
-            )
-            self.norm_layers_2.append(LayerNorm(hidden_channels))
-
-    def forward(self, x, x_mask, h, h_mask):
-        """
-        x: decoder input
-        h: encoder output
-        """
-        self_attn_mask = commons.subsequent_mask(x_mask.size(2)).to(
-            device=x.device, dtype=x.dtype
-        )
-        encdec_attn_mask = h_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
-        x = x * x_mask
-        for i in range(self.n_layers):
-            y = self.self_attn_layers[i](x, x, self_attn_mask)
-            y = self.drop(y)
-            x = self.norm_layers_0[i](x + y)
-
-            y = self.encdec_attn_layers[i](x, h, encdec_attn_mask)
-            y = self.drop(y)
-            x = self.norm_layers_1[i](x + y)
-
-            y = self.ffn_layers[i](x, x_mask)
-            y = self.drop(y)
-            x = self.norm_layers_2[i](x + y)
-        x = x * x_mask
-        return x
-
-
-class MultiHeadAttention(nn.Module):
-    def __init__(
-        self,
-        channels,
-        out_channels,
-        n_heads,
-        p_dropout=0.0,
-        window_size=None,
-        heads_share=True,
-        block_length=None,
-        proximal_bias=False,
-        proximal_init=False,
-    ):
-        super().__init__()
-        assert channels % n_heads == 0
-
-        self.channels = channels
-        self.out_channels = out_channels
-        self.n_heads = n_heads
-        self.p_dropout = p_dropout
-        self.window_size = window_size
-        self.heads_share = heads_share
-        self.block_length = block_length
-        self.proximal_bias = proximal_bias
-        self.proximal_init = proximal_init
-        self.attn = None
-
-        self.k_channels = channels // n_heads
-        self.conv_q = nn.Conv1d(channels, channels, 1)
-        self.conv_k = nn.Conv1d(channels, channels, 1)
-        self.conv_v = nn.Conv1d(channels, channels, 1)
-        self.conv_o = nn.Conv1d(channels, out_channels, 1)
-        self.drop = nn.Dropout(p_dropout)
-
-        if window_size is not None:
-            n_heads_rel = 1 if heads_share else n_heads
-            rel_stddev = self.k_channels**-0.5
-            self.emb_rel_k = nn.Parameter(
-                torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels)
-                * rel_stddev
-            )
-            self.emb_rel_v = nn.Parameter(
-                torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels)
-                * rel_stddev
-            )
-
-        nn.init.xavier_uniform_(self.conv_q.weight)
-        nn.init.xavier_uniform_(self.conv_k.weight)
-        nn.init.xavier_uniform_(self.conv_v.weight)
-        if proximal_init:
-            with torch.no_grad():
-                self.conv_k.weight.copy_(self.conv_q.weight)
-                self.conv_k.bias.copy_(self.conv_q.bias)
-
-    def forward(self, x, c, attn_mask=None):
-        q = self.conv_q(x)
-        k = self.conv_k(c)
-        v = self.conv_v(c)
-
-        x, self.attn = self.attention(q, k, v, mask=attn_mask)
-
-        x = self.conv_o(x)
-        return x
-
-    def attention(self, query, key, value, mask=None):
-        # reshape [b, d, t] -> [b, n_h, t, d_k]
-        b, d, t_s, t_t = (*key.size(), query.size(2))
-        query = query.view(b, self.n_heads, self.k_channels, t_t).transpose(2, 3)
-        key = key.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
-        value = value.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
-
-        scores = torch.matmul(query / math.sqrt(self.k_channels), key.transpose(-2, -1))
-        if self.window_size is not None:
-            assert (
-                t_s == t_t
-            ), "Relative attention is only available for self-attention."
-            key_relative_embeddings = self._get_relative_embeddings(self.emb_rel_k, t_s)
-            rel_logits = self._matmul_with_relative_keys(
-                query / math.sqrt(self.k_channels), key_relative_embeddings
-            )
-            scores_local = self._relative_position_to_absolute_position(rel_logits)
-            scores = scores + scores_local
-        if self.proximal_bias:
-            assert t_s == t_t, "Proximal bias is only available for self-attention."
-            scores = scores + self._attention_bias_proximal(t_s).to(
-                device=scores.device, dtype=scores.dtype
-            )
-        if mask is not None:
-            scores = scores.masked_fill(mask == 0, -1e4)
-            if self.block_length is not None:
-                assert (
-                    t_s == t_t
-                ), "Local attention is only available for self-attention."
-                block_mask = (
-                    torch.ones_like(scores)
-                    .triu(-self.block_length)
-                    .tril(self.block_length)
-                )
-                scores = scores.masked_fill(block_mask == 0, -1e4)
-        p_attn = F.softmax(scores, dim=-1)  # [b, n_h, t_t, t_s]
-        p_attn = self.drop(p_attn)
-        output = torch.matmul(p_attn, value)
-        if self.window_size is not None:
-            relative_weights = self._absolute_position_to_relative_position(p_attn)
-            value_relative_embeddings = self._get_relative_embeddings(
-                self.emb_rel_v, t_s
-            )
-            output = output + self._matmul_with_relative_values(
-                relative_weights, value_relative_embeddings
-            )
-        output = (
-            output.transpose(2, 3).contiguous().view(b, d, t_t)
-        )  # [b, n_h, t_t, d_k] -> [b, d, t_t]
-        return output, p_attn
-
-    def _matmul_with_relative_values(self, x, y):
-        """
-        x: [b, h, l, m]
-        y: [h or 1, m, d]
-        ret: [b, h, l, d]
-        """
-        ret = torch.matmul(x, y.unsqueeze(0))
-        return ret
-
-    def _matmul_with_relative_keys(self, x, y):
-        """
-        x: [b, h, l, d]
-        y: [h or 1, m, d]
-        ret: [b, h, l, m]
-        """
-        ret = torch.matmul(x, y.unsqueeze(0).transpose(-2, -1))
-        return ret
-
-    def _get_relative_embeddings(self, relative_embeddings, length):
-        max_relative_position = 2 * self.window_size + 1
-        # Pad first before slice to avoid using cond ops.
-        pad_length = max(length - (self.window_size + 1), 0)
-        slice_start_position = max((self.window_size + 1) - length, 0)
-        slice_end_position = slice_start_position + 2 * length - 1
-        if pad_length > 0:
-            padded_relative_embeddings = F.pad(
-                relative_embeddings,
-                commons.convert_pad_shape([[0, 0], [pad_length, pad_length], [0, 0]]),
-            )
-        else:
-            padded_relative_embeddings = relative_embeddings
-        used_relative_embeddings = padded_relative_embeddings[
-            :, slice_start_position:slice_end_position
-        ]
-        return used_relative_embeddings
-
-    def _relative_position_to_absolute_position(self, x):
-        """
-        x: [b, h, l, 2*l-1]
-        ret: [b, h, l, l]
-        """
-        batch, heads, length, _ = x.size()
-        # Concat columns of pad to shift from relative to absolute indexing.
-        x = F.pad(x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, 1]]))
-
-        # Concat extra elements so to add up to shape (len+1, 2*len-1).
-        x_flat = x.view([batch, heads, length * 2 * length])
-        x_flat = F.pad(
-            x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [0, length - 1]])
-        )
-
-        # Reshape and slice out the padded elements.
-        x_final = x_flat.view([batch, heads, length + 1, 2 * length - 1])[
-            :, :, :length, length - 1 :
-        ]
-        return x_final
-
-    def _absolute_position_to_relative_position(self, x):
-        """
-        x: [b, h, l, l]
-        ret: [b, h, l, 2*l-1]
-        """
-        batch, heads, length, _ = x.size()
-        # padd along column
-        x = F.pad(
-            x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, length - 1]])
-        )
-        x_flat = x.view([batch, heads, length**2 + length * (length - 1)])
-        # add 0's in the beginning that will skew the elements after reshape
-        x_flat = F.pad(x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [length, 0]]))
-        x_final = x_flat.view([batch, heads, length, 2 * length])[:, :, :, 1:]
-        return x_final
-
-    def _attention_bias_proximal(self, length):
-        """Bias for self-attention to encourage attention to close positions.
-        Args:
-          length: an integer scalar.
-        Returns:
-          a Tensor with shape [1, 1, length, length]
-        """
-        r = torch.arange(length, dtype=torch.float32)
-        diff = torch.unsqueeze(r, 0) - torch.unsqueeze(r, 1)
-        return torch.unsqueeze(torch.unsqueeze(-torch.log1p(torch.abs(diff)), 0), 0)
-
-
-class FFN(nn.Module):
-    def __init__(
-        self,
-        in_channels,
-        out_channels,
-        filter_channels,
-        kernel_size,
-        p_dropout=0.0,
-        activation=None,
-        causal=False,
-    ):
-        super().__init__()
-        self.in_channels = in_channels
-        self.out_channels = out_channels
-        self.filter_channels = filter_channels
-        self.kernel_size = kernel_size
-        self.p_dropout = p_dropout
-        self.activation = activation
-        self.causal = causal
-
-        if causal:
-            self.padding = self._causal_padding
-        else:
-            self.padding = self._same_padding
-
-        self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size)
-        self.conv_2 = nn.Conv1d(filter_channels, out_channels, kernel_size)
-        self.drop = nn.Dropout(p_dropout)
-
-    def forward(self, x, x_mask):
-        x = self.conv_1(self.padding(x * x_mask))
-        if self.activation == "gelu":
-            x = x * torch.sigmoid(1.702 * x)
-        else:
-            x = torch.relu(x)
-        x = self.drop(x)
-        x = self.conv_2(self.padding(x * x_mask))
-        return x * x_mask
-
-    def _causal_padding(self, x):
-        if self.kernel_size == 1:
-            return x
-        pad_l = self.kernel_size - 1
-        pad_r = 0
-        padding = [[0, 0], [0, 0], [pad_l, pad_r]]
-        x = F.pad(x, commons.convert_pad_shape(padding))
-        return x
-
-    def _same_padding(self, x):
-        if self.kernel_size == 1:
-            return x
-        pad_l = (self.kernel_size - 1) // 2
-        pad_r = self.kernel_size // 2
-        padding = [[0, 0], [0, 0], [pad_l, pad_r]]
-        x = F.pad(x, commons.convert_pad_shape(padding))
-        return x
diff --git a/spaces/inplisQlawa/anything-midjourney-v4-1/Crack.Dolphins.Volts.6.10.rar __FULL__.md b/spaces/inplisQlawa/anything-midjourney-v4-1/Crack.Dolphins.Volts.6.10.rar __FULL__.md
deleted file mode 100644
index 48bbfa2626c56d3bad4fc193ae6aeb79736d7ca5..0000000000000000000000000000000000000000
--- a/spaces/inplisQlawa/anything-midjourney-v4-1/Crack.Dolphins.Volts.6.10.rar __FULL__.md	
+++ /dev/null
@@ -1,26 +0,0 @@
-<h2>Crack.Dolphins.Volts.6.10.rar</h2><br /><p><b><b>DOWNLOAD</b> &#8230;&#8230;&#8230; <a href="https://urlin.us/2uEvJP">https://urlin.us/2uEvJP</a></b></p><br /><br />
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diff --git a/spaces/inreVtussa/clothingai/Examples/101 Dino Pets Full Download.md b/spaces/inreVtussa/clothingai/Examples/101 Dino Pets Full Download.md
deleted file mode 100644
index c847b8ce75fccdfed1d5fd2769675fa02a3df0e2..0000000000000000000000000000000000000000
--- a/spaces/inreVtussa/clothingai/Examples/101 Dino Pets Full Download.md	
+++ /dev/null
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diff --git a/spaces/inreVtussa/clothingai/Examples/City Car Driving Product Key And Serial Number.md b/spaces/inreVtussa/clothingai/Examples/City Car Driving Product Key And Serial Number.md
deleted file mode 100644
index 0f0386dd6de91092d9f2a33fd0d9276dbb7eb47e..0000000000000000000000000000000000000000
--- a/spaces/inreVtussa/clothingai/Examples/City Car Driving Product Key And Serial Number.md	
+++ /dev/null
@@ -1,120 +0,0 @@
-
-<h1>City Car Driving Product Key and Serial Number: How to Get and Activate the Game</h1>
-
-<p>City Car Driving is a realistic driving simulator that allows you to experience the real-life situations of driving in various traffic conditions. The game features a variety of vehicles, roads, weather, and traffic rules that you can customize to your preferences. You can also choose from different modes, such as career, free ride, or online multiplayer.</p>
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-
-<p>If you want to play City Car Driving on your PC, you will need a product key and a serial number to activate the game. A product key is a code that you receive when you buy the game from an official source, such as Steam or the developer's website. A serial number is a code that you receive when you register the game on the developer's website. You will need both codes to activate the game and play it online.</p>
-
-<p>In this article, we will show you how to get and use City Car Driving product key and serial number safely and effectively. We will also explain the features and benefits of City Car Driving, as well as some tips and tricks to improve your skills and enjoyment.</p>
-
-<h2>How to Get City Car Driving Product Key and Serial Number</h2>
-
-<p>To get City Car Driving product key and serial number, you will need to follow these steps:</p>
-
-<ol>
-<li>Buy the game from an official source, such as Steam or the developer's website. You can choose from different editions of the game, such as Home Edition or Professional Edition, depending on your needs and preferences.</li>
-<li>Receive your product key via email or in your account dashboard. You will need this code to activate the game on Steam.</li>
-<li>Download and install the game on your PC using Steam.</li>
-<li>Launch the game and copy the product code from the game startup window.</li>
-<li>Register the game on the developer's website using this link: www.activate.citycardriving.com/</li>
-<li>Enter your product key, product code, and email address on the web page.</li>
-<li>Receive your serial number via email or on the final page after clicking "Activate". You will need this code to play the game online.</li>
-<li>Enter your serial number in the game settings and enjoy playing the game.</li>
-</ol>
-
-<h2>How to Use City Car Driving Product Key and Serial Number</h2>
-
-<p>Once you have activated City Car Driving with your product key and serial number, you can start using it to play the game. Here are some basic steps to use City Car Driving:</p>
-<p></p>
-
-<ol>
-<li>Create a profile or log in with your existing one.</li>
-<li>Select a mode from career, free ride, or online multiplayer.</li>
-<li>Select a vehicle from a variety of cars, trucks, buses, etc.</li>
-<li>Select a road from different countries, cities, highways, etc.</li>
-<li>Select a weather condition from sunny, rainy, snowy, etc.</li>
-<li>Select a traffic rule from different countries or regions.</li>
-<li>Start driving and follow the instructions on the screen.</li>
-<li>Use the keyboard, mouse, or controller to control your vehicle.</li>
-<li>Use the dashboard indicators, mirrors, signals, etc. to monitor your vehicle status and surroundings.</li>
-<li>Follow the traffic rules and avoid accidents or violations.</li>
-<li>Earn points and achievements for completing missions or challenges.</li>
-</ol>
-
-<h2>What are the Features and Benefits of City Car Driving</h2>
-
-<p>City Car Driving is a game that offers many features and benefits for users. Some of them are:</p>
-
-<ul>
-<li>Realistic driving simulator that simulates real-life situations of driving in various traffic conditions.</li>
-<li>Variety of vehicles , roads , weather , & traffic rules that you can customize to your preferences .</li>
-<li>Different modes that suit different purposes & tastes , such as career , free ride , or online multiplayer .</li>
-<li>Educational value that helps you learn & improve your driving skills & knowledge .</li>
-<li>Fun & challenge that keeps you entertained & engaged for hours with its action-packed gameplay .</li>
-<li>Support for different input devices , such as keyboard , mouse , controller , steering wheel , etc .</li>
-<li>Support for different languages , such as English , German , French , Spanish , etc .</li>
-</ul>
-
-<h2>How to Improve Your Skills & Enjoyment with City Car Driving</h2>
-
-<p>City Car Driving is a game that requires some skills & enjoyment to play it effectively . Here are some tips & tricks that can help you improve your skills & enjoyment with City Car Driving :</p>
-
-<ul>
-<li>Experiment with different vehicles , roads , weather , & traffic rules to discover new possibilities & effects .</li>
-<li>Learn from tutorials , courses , books , blogs , videos , podcasts , etc . that teach you how to use City Car Driving for different projects & purposes .</li>
-<li>Practice regularly by doing exercises , challenges , projects , etc . that test your skills & enjoyment with City Car Driving .</li>
-<li>Get inspired by other players who use City Car Driving for their work & see how they create their gameplay .</li>
-<li>Join online communities & forums where you can share your work , get feedback , ask questions , learn tips & tricks , etc . with other users of City Car Driving .</li>
-</ul>
-
-<h2>Conclusion</h2>
-
-<p>In this article , we have shown you how to get & use City Car Driving product key & serial number safely & effectively . We have also explained the features & benefits of City Car Driving , as well as some tips & tricks to improve your skills & enjoyment with it . We hope you have found this article helpful & informative . If you have any questions or comments , feel free to leave them below . We would love to hear from you . Happy driving !</p>
-<h2>How to Avoid Risks and Problems with City Car Driving Product Key and Serial Number</h2>
-
-<p>While using City Car Driving product key and serial number may seem tempting and convenient, it also comes with some risks and problems that you should be aware of and avoid. Some of them are:</p>
-
-<ul>
-<li>Viruses and malware. Downloading and installing a product key or a serial number from an unreliable source may infect your PC with viruses and malware that can damage your system, steal your data, or compromise your security.</li>
-<li>Scams and frauds. Some websites that offer the product key or the serial number may trick you into paying for it, downloading unwanted software, or revealing your personal information.</li>
-<li>Legal issues and penalties. Using a product key or a serial number that is not authorized by the developer is illegal and violates the terms and conditions of the game. You may face legal actions or penalties from the developer or other authorities if you are caught using an unauthorized code.</li>
-<li>Poor performance and quality. Using a product key or a serial number that is not compatible with your game version may affect the performance and quality of the game on your PC. You may experience crashes, errors, glitches, or compatibility issues with the game or other programs.</li>
-<li>Lack of updates and support. Using a product key or a serial number that is not valid may prevent you from getting updates and support from the developer for the game. You may miss out on new features, bug fixes, security patches, or customer service.</li>
-</ul>
-
-<p>To avoid these risks and problems, you should not use City Car Driving product key and serial number from an unreliable source. Instead, you should buy a legitimate code from an official source, such as Steam or the developer's website. By doing so, you will be able to use the game safely and legally, as well as enjoy its full features and benefits.</p>
-
-<h2>How to Get a Legitimate Code for City Car Driving</h2>
-
-<p>If you want to get a legitimate code for City Car Driving, you will need to buy it from an official source, such as Steam or the developer's website. A legitimate code is a code that verifies your ownership of the game and allows you to activate it on your PC. There are different ways to buy a legitimate code for City Car Driving, depending on your needs and preferences. Some of them are:</p>
-
-<ul>
-<li>Buy a monthly or annual subscription plan from Steam . This is the most convenient and flexible option , as it gives you access to City Car Driving , as well as other games and services , for a fixed monthly or annual fee . You can also cancel or change your plan at any time .</li>
-<li>Buy a one-time purchase code from Steam or the developer's website . This is a more affordable and permanent option , as it gives you lifetime access to City Car Driving for a one-time payment . However , you will not get any updates or support from the developer after the end of your support period .</li>
-<li>Buy an educational code from Steam or the developer's website . This is a special and discounted option for students , teachers , or academic institutions , as it gives them access to City Car Driving , as well as other games and services , for a lower price than the regular code . However , you will need to provide proof of eligibility and follow certain terms and conditions to use this option .</li>
-</ul>
-
-<p>To buy a legitimate code for City Car Driving , you will need to create an account on the platform of your choice and add the game to your cart . You will then need to pay for the game using your preferred payment method and receive your code via email or in your account dashboard . You can then activate your game on your PC by following these steps :</p>
-
-<ol>
-<li>Download & install City Car Driving on your PC using Steam .</li>
-<li>Launch the game & sign in with your account .</li>
-<li>Enter your code & follow the instructions .</li>
-<li>The game will be activated & you can start playing it .</li>
-</ol>
-
-<h2>Conclusion</h2>
-
-<p>In this article , we have shown you how to get & use City Car Driving product key & serial number safely & effectively . We have also explained the features & benefits of City Car Driving , as well as some tips & tricks to improve your skills & enjoyment with it . We hope you have found this article helpful & informative . If you have any questions or comments , feel free to leave them below . We would love to hear from you . Happy driving !</p>
-<h2>City Car Driving Product Key and Serial Number: Summary</h2>
-
-<p>In this article, we have covered everything you need to know about City Car Driving product key and serial number. We have explained what the game is about, how to get and use the code, what are the features and benefits of the game, and how to improve your skills and enjoyment with it. We have also shown you how to avoid risks and problems with the code, and how to get a legitimate code for the game.</p>
-
-<p>City Car Driving is a realistic driving simulator that allows you to experience the real-life situations of driving in various traffic conditions. The game features a variety of vehicles, roads, weather, and traffic rules that you can customize to your preferences. You can also choose from different modes, such as career, free ride, or online multiplayer. However, using a code that is not authorized by the developer is illegal and risky, as it may expose you to viruses, malware, scams, or legal issues.</p>
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-<p>Therefore, we recommend that you buy a legitimate code from an official source, such as Steam or the developer's website, as it will allow you to use the game safely and legally, as well as enjoy its full features and benefits. By doing so, you will be able to play City Car Driving on your PC and create stunning driving scenarios for your projects.</p>
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-<p>Thank you for reading this article. If you have any questions or comments, feel free to leave them below. We would love to hear from you.</p> 3cee63e6c2<br />
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\ No newline at end of file
diff --git a/spaces/james-oldfield/PandA/networks/genforce/metrics/fid.py b/spaces/james-oldfield/PandA/networks/genforce/metrics/fid.py
deleted file mode 100644
index 96676b8f880cc78b7c9efc98b4d6d69aa6c399ba..0000000000000000000000000000000000000000
--- a/spaces/james-oldfield/PandA/networks/genforce/metrics/fid.py
+++ /dev/null
@@ -1,59 +0,0 @@
-# python3.7
-"""Contains the functions to compute Frechet Inception Distance (FID).
-
-FID metric is introduced in paper
-
-GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash
-Equilibrium. Heusel et al. NeurIPS 2017.
-
-See details at https://arxiv.org/pdf/1706.08500.pdf
-"""
-
-import numpy as np
-import scipy.linalg
-
-__all__ = ['extract_feature', 'compute_fid']
-
-
-def extract_feature(inception_model, images):
-    """Extracts feature from input images with given model.
-
-    NOTE: The input images are assumed to be with pixel range [-1, 1].
-
-    Args:
-        inception_model: The model used to extract features.
-        images: The input image tensor to extract features from.
-
-    Returns:
-        A `numpy.ndarray`, containing the extracted features.
-    """
-    features = inception_model(images, output_logits=False)
-    features = features.detach().cpu().numpy()
-    assert features.ndim == 2 and features.shape[1] == 2048
-    return features
-
-
-def compute_fid(fake_features, real_features):
-    """Computes FID based on the features extracted from fake and real data.
-
-    Given the mean and covariance (m_f, C_f) of fake data and (m_r, C_r) of real
-    data, the FID metric can be computed by
-
-    d^2 = ||m_f - m_r||_2^2 + Tr(C_f + C_r - 2(C_f C_r)^0.5)
-
-    Args:
-        fake_features: The features extracted from fake data.
-        real_features: The features extracted from real data.
-
-    Returns:
-        A real number, suggesting the FID value.
-    """
-
-    m_f = np.mean(fake_features, axis=0)
-    C_f = np.cov(fake_features, rowvar=False)
-    m_r = np.mean(real_features, axis=0)
-    C_r = np.cov(real_features, rowvar=False)
-
-    fid = np.sum((m_f - m_r) ** 2) + np.trace(
-        C_f + C_r - 2 * scipy.linalg.sqrtm(np.dot(C_f, C_r)))
-    return np.real(fid)
diff --git a/spaces/jcenaa/Segment-Any-RGBD/open_vocab_seg/utils/misc.py b/spaces/jcenaa/Segment-Any-RGBD/open_vocab_seg/utils/misc.py
deleted file mode 100644
index a22d0a978c9cd89595c6e7c900885e1c148844b1..0000000000000000000000000000000000000000
--- a/spaces/jcenaa/Segment-Any-RGBD/open_vocab_seg/utils/misc.py
+++ /dev/null
@@ -1,126 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-# Modified by Bowen Cheng from https://github.com/facebookresearch/detr/blob/master/util/misc.py
-# Copyright (c) Meta Platforms, Inc. All Rights Reserved
-
-"""
-Misc functions, including distributed helpers.
-
-Mostly copy-paste from torchvision references.
-"""
-from typing import List, Optional
-
-import torch
-import torch.distributed as dist
-import torchvision
-from torch import Tensor
-
-
-def _max_by_axis(the_list):
-    # type: (List[List[int]]) -> List[int]
-    maxes = the_list[0]
-    for sublist in the_list[1:]:
-        for index, item in enumerate(sublist):
-            maxes[index] = max(maxes[index], item)
-    return maxes
-
-
-class NestedTensor(object):
-    def __init__(self, tensors, mask: Optional[Tensor]):
-        self.tensors = tensors
-        self.mask = mask
-
-    def to(self, device):
-        # type: (Device) -> NestedTensor # noqa
-        cast_tensor = self.tensors.to(device)
-        mask = self.mask
-        if mask is not None:
-            assert mask is not None
-            cast_mask = mask.to(device)
-        else:
-            cast_mask = None
-        return NestedTensor(cast_tensor, cast_mask)
-
-    def decompose(self):
-        return self.tensors, self.mask
-
-    def __repr__(self):
-        return str(self.tensors)
-
-
-def nested_tensor_from_tensor_list(tensor_list: List[Tensor]):
-    # TODO make this more general
-    if tensor_list[0].ndim == 3:
-        if torchvision._is_tracing():
-            # nested_tensor_from_tensor_list() does not export well to ONNX
-            # call _onnx_nested_tensor_from_tensor_list() instead
-            return _onnx_nested_tensor_from_tensor_list(tensor_list)
-
-        # TODO make it support different-sized images
-        max_size = _max_by_axis([list(img.shape) for img in tensor_list])
-        # min_size = tuple(min(s) for s in zip(*[img.shape for img in tensor_list]))
-        batch_shape = [len(tensor_list)] + max_size
-        b, c, h, w = batch_shape
-        dtype = tensor_list[0].dtype
-        device = tensor_list[0].device
-        tensor = torch.zeros(batch_shape, dtype=dtype, device=device)
-        mask = torch.ones((b, h, w), dtype=torch.bool, device=device)
-        for img, pad_img, m in zip(tensor_list, tensor, mask):
-            pad_img[: img.shape[0], : img.shape[1], : img.shape[2]].copy_(img)
-            m[: img.shape[1], : img.shape[2]] = False
-    else:
-        raise ValueError("not supported")
-    return NestedTensor(tensor, mask)
-
-
-# _onnx_nested_tensor_from_tensor_list() is an implementation of
-# nested_tensor_from_tensor_list() that is supported by ONNX tracing.
-@torch.jit.unused
-def _onnx_nested_tensor_from_tensor_list(tensor_list: List[Tensor]) -> NestedTensor:
-    max_size = []
-    for i in range(tensor_list[0].dim()):
-        max_size_i = torch.max(
-            torch.stack([img.shape[i] for img in tensor_list]).to(torch.float32)
-        ).to(torch.int64)
-        max_size.append(max_size_i)
-    max_size = tuple(max_size)
-
-    # work around for
-    # pad_img[: img.shape[0], : img.shape[1], : img.shape[2]].copy_(img)
-    # m[: img.shape[1], :img.shape[2]] = False
-    # which is not yet supported in onnx
-    padded_imgs = []
-    padded_masks = []
-    for img in tensor_list:
-        padding = [(s1 - s2) for s1, s2 in zip(max_size, tuple(img.shape))]
-        padded_img = torch.nn.functional.pad(
-            img, (0, padding[2], 0, padding[1], 0, padding[0])
-        )
-        padded_imgs.append(padded_img)
-
-        m = torch.zeros_like(img[0], dtype=torch.int, device=img.device)
-        padded_mask = torch.nn.functional.pad(
-            m, (0, padding[2], 0, padding[1]), "constant", 1
-        )
-        padded_masks.append(padded_mask.to(torch.bool))
-
-    tensor = torch.stack(padded_imgs)
-    mask = torch.stack(padded_masks)
-
-    return NestedTensor(tensor, mask=mask)
-
-
-def is_dist_avail_and_initialized():
-    if not dist.is_available():
-        return False
-    if not dist.is_initialized():
-        return False
-    return True
-
-def get_gt_binary_masks(gt_semseg):
-    mask_ids = torch.unique(gt_semseg)
-    gt_masks = []
-    for id in mask_ids:
-        if id != 255:
-            gt_masks.append(gt_semseg == id)
-    gt_masks = torch.stack(gt_masks).float()
-    return gt_masks
diff --git a/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/PIL/TiffTags.py b/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/PIL/TiffTags.py
deleted file mode 100644
index 30b05e4e1d41fa21a7b7bf12c04ee05af6aa5284..0000000000000000000000000000000000000000
--- a/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/PIL/TiffTags.py
+++ /dev/null
@@ -1,560 +0,0 @@
-#
-# The Python Imaging Library.
-# $Id$
-#
-# TIFF tags
-#
-# This module provides clear-text names for various well-known
-# TIFF tags.  the TIFF codec works just fine without it.
-#
-# Copyright (c) Secret Labs AB 1999.
-#
-# See the README file for information on usage and redistribution.
-#
-
-##
-# This module provides constants and clear-text names for various
-# well-known TIFF tags.
-##
-
-from collections import namedtuple
-
-
-class TagInfo(namedtuple("_TagInfo", "value name type length enum")):
-    __slots__ = []
-
-    def __new__(cls, value=None, name="unknown", type=None, length=None, enum=None):
-        return super().__new__(cls, value, name, type, length, enum or {})
-
-    def cvt_enum(self, value):
-        # Using get will call hash(value), which can be expensive
-        # for some types (e.g. Fraction). Since self.enum is rarely
-        # used, it's usually better to test it first.
-        return self.enum.get(value, value) if self.enum else value
-
-
-def lookup(tag, group=None):
-    """
-    :param tag: Integer tag number
-    :param group: Which :py:data:`~PIL.TiffTags.TAGS_V2_GROUPS` to look in
-
-    .. versionadded:: 8.3.0
-
-    :returns: Taginfo namedtuple, From the ``TAGS_V2`` info if possible,
-        otherwise just populating the value and name from ``TAGS``.
-        If the tag is not recognized, "unknown" is returned for the name
-
-    """
-
-    if group is not None:
-        info = TAGS_V2_GROUPS[group].get(tag) if group in TAGS_V2_GROUPS else None
-    else:
-        info = TAGS_V2.get(tag)
-    return info or TagInfo(tag, TAGS.get(tag, "unknown"))
-
-
-##
-# Map tag numbers to tag info.
-#
-#  id: (Name, Type, Length, enum_values)
-#
-# The length here differs from the length in the tiff spec.  For
-# numbers, the tiff spec is for the number of fields returned. We
-# agree here.  For string-like types, the tiff spec uses the length of
-# field in bytes.  In Pillow, we are using the number of expected
-# fields, in general 1 for string-like types.
-
-
-BYTE = 1
-ASCII = 2
-SHORT = 3
-LONG = 4
-RATIONAL = 5
-SIGNED_BYTE = 6
-UNDEFINED = 7
-SIGNED_SHORT = 8
-SIGNED_LONG = 9
-SIGNED_RATIONAL = 10
-FLOAT = 11
-DOUBLE = 12
-IFD = 13
-LONG8 = 16
-
-TAGS_V2 = {
-    254: ("NewSubfileType", LONG, 1),
-    255: ("SubfileType", SHORT, 1),
-    256: ("ImageWidth", LONG, 1),
-    257: ("ImageLength", LONG, 1),
-    258: ("BitsPerSample", SHORT, 0),
-    259: (
-        "Compression",
-        SHORT,
-        1,
-        {
-            "Uncompressed": 1,
-            "CCITT 1d": 2,
-            "Group 3 Fax": 3,
-            "Group 4 Fax": 4,
-            "LZW": 5,
-            "JPEG": 6,
-            "PackBits": 32773,
-        },
-    ),
-    262: (
-        "PhotometricInterpretation",
-        SHORT,
-        1,
-        {
-            "WhiteIsZero": 0,
-            "BlackIsZero": 1,
-            "RGB": 2,
-            "RGB Palette": 3,
-            "Transparency Mask": 4,
-            "CMYK": 5,
-            "YCbCr": 6,
-            "CieLAB": 8,
-            "CFA": 32803,  # TIFF/EP, Adobe DNG
-            "LinearRaw": 32892,  # Adobe DNG
-        },
-    ),
-    263: ("Threshholding", SHORT, 1),
-    264: ("CellWidth", SHORT, 1),
-    265: ("CellLength", SHORT, 1),
-    266: ("FillOrder", SHORT, 1),
-    269: ("DocumentName", ASCII, 1),
-    270: ("ImageDescription", ASCII, 1),
-    271: ("Make", ASCII, 1),
-    272: ("Model", ASCII, 1),
-    273: ("StripOffsets", LONG, 0),
-    274: ("Orientation", SHORT, 1),
-    277: ("SamplesPerPixel", SHORT, 1),
-    278: ("RowsPerStrip", LONG, 1),
-    279: ("StripByteCounts", LONG, 0),
-    280: ("MinSampleValue", SHORT, 0),
-    281: ("MaxSampleValue", SHORT, 0),
-    282: ("XResolution", RATIONAL, 1),
-    283: ("YResolution", RATIONAL, 1),
-    284: ("PlanarConfiguration", SHORT, 1, {"Contiguous": 1, "Separate": 2}),
-    285: ("PageName", ASCII, 1),
-    286: ("XPosition", RATIONAL, 1),
-    287: ("YPosition", RATIONAL, 1),
-    288: ("FreeOffsets", LONG, 1),
-    289: ("FreeByteCounts", LONG, 1),
-    290: ("GrayResponseUnit", SHORT, 1),
-    291: ("GrayResponseCurve", SHORT, 0),
-    292: ("T4Options", LONG, 1),
-    293: ("T6Options", LONG, 1),
-    296: ("ResolutionUnit", SHORT, 1, {"none": 1, "inch": 2, "cm": 3}),
-    297: ("PageNumber", SHORT, 2),
-    301: ("TransferFunction", SHORT, 0),
-    305: ("Software", ASCII, 1),
-    306: ("DateTime", ASCII, 1),
-    315: ("Artist", ASCII, 1),
-    316: ("HostComputer", ASCII, 1),
-    317: ("Predictor", SHORT, 1, {"none": 1, "Horizontal Differencing": 2}),
-    318: ("WhitePoint", RATIONAL, 2),
-    319: ("PrimaryChromaticities", RATIONAL, 6),
-    320: ("ColorMap", SHORT, 0),
-    321: ("HalftoneHints", SHORT, 2),
-    322: ("TileWidth", LONG, 1),
-    323: ("TileLength", LONG, 1),
-    324: ("TileOffsets", LONG, 0),
-    325: ("TileByteCounts", LONG, 0),
-    330: ("SubIFDs", LONG, 0),
-    332: ("InkSet", SHORT, 1),
-    333: ("InkNames", ASCII, 1),
-    334: ("NumberOfInks", SHORT, 1),
-    336: ("DotRange", SHORT, 0),
-    337: ("TargetPrinter", ASCII, 1),
-    338: ("ExtraSamples", SHORT, 0),
-    339: ("SampleFormat", SHORT, 0),
-    340: ("SMinSampleValue", DOUBLE, 0),
-    341: ("SMaxSampleValue", DOUBLE, 0),
-    342: ("TransferRange", SHORT, 6),
-    347: ("JPEGTables", UNDEFINED, 1),
-    # obsolete JPEG tags
-    512: ("JPEGProc", SHORT, 1),
-    513: ("JPEGInterchangeFormat", LONG, 1),
-    514: ("JPEGInterchangeFormatLength", LONG, 1),
-    515: ("JPEGRestartInterval", SHORT, 1),
-    517: ("JPEGLosslessPredictors", SHORT, 0),
-    518: ("JPEGPointTransforms", SHORT, 0),
-    519: ("JPEGQTables", LONG, 0),
-    520: ("JPEGDCTables", LONG, 0),
-    521: ("JPEGACTables", LONG, 0),
-    529: ("YCbCrCoefficients", RATIONAL, 3),
-    530: ("YCbCrSubSampling", SHORT, 2),
-    531: ("YCbCrPositioning", SHORT, 1),
-    532: ("ReferenceBlackWhite", RATIONAL, 6),
-    700: ("XMP", BYTE, 0),
-    33432: ("Copyright", ASCII, 1),
-    33723: ("IptcNaaInfo", UNDEFINED, 1),
-    34377: ("PhotoshopInfo", BYTE, 0),
-    # FIXME add more tags here
-    34665: ("ExifIFD", LONG, 1),
-    34675: ("ICCProfile", UNDEFINED, 1),
-    34853: ("GPSInfoIFD", LONG, 1),
-    36864: ("ExifVersion", UNDEFINED, 1),
-    37724: ("ImageSourceData", UNDEFINED, 1),
-    40965: ("InteroperabilityIFD", LONG, 1),
-    41730: ("CFAPattern", UNDEFINED, 1),
-    # MPInfo
-    45056: ("MPFVersion", UNDEFINED, 1),
-    45057: ("NumberOfImages", LONG, 1),
-    45058: ("MPEntry", UNDEFINED, 1),
-    45059: ("ImageUIDList", UNDEFINED, 0),  # UNDONE, check
-    45060: ("TotalFrames", LONG, 1),
-    45313: ("MPIndividualNum", LONG, 1),
-    45569: ("PanOrientation", LONG, 1),
-    45570: ("PanOverlap_H", RATIONAL, 1),
-    45571: ("PanOverlap_V", RATIONAL, 1),
-    45572: ("BaseViewpointNum", LONG, 1),
-    45573: ("ConvergenceAngle", SIGNED_RATIONAL, 1),
-    45574: ("BaselineLength", RATIONAL, 1),
-    45575: ("VerticalDivergence", SIGNED_RATIONAL, 1),
-    45576: ("AxisDistance_X", SIGNED_RATIONAL, 1),
-    45577: ("AxisDistance_Y", SIGNED_RATIONAL, 1),
-    45578: ("AxisDistance_Z", SIGNED_RATIONAL, 1),
-    45579: ("YawAngle", SIGNED_RATIONAL, 1),
-    45580: ("PitchAngle", SIGNED_RATIONAL, 1),
-    45581: ("RollAngle", SIGNED_RATIONAL, 1),
-    40960: ("FlashPixVersion", UNDEFINED, 1),
-    50741: ("MakerNoteSafety", SHORT, 1, {"Unsafe": 0, "Safe": 1}),
-    50780: ("BestQualityScale", RATIONAL, 1),
-    50838: ("ImageJMetaDataByteCounts", LONG, 0),  # Can be more than one
-    50839: ("ImageJMetaData", UNDEFINED, 1),  # see Issue #2006
-}
-TAGS_V2_GROUPS = {
-    # ExifIFD
-    34665: {
-        36864: ("ExifVersion", UNDEFINED, 1),
-        40960: ("FlashPixVersion", UNDEFINED, 1),
-        40965: ("InteroperabilityIFD", LONG, 1),
-        41730: ("CFAPattern", UNDEFINED, 1),
-    },
-    # GPSInfoIFD
-    34853: {
-        0: ("GPSVersionID", BYTE, 4),
-        1: ("GPSLatitudeRef", ASCII, 2),
-        2: ("GPSLatitude", RATIONAL, 3),
-        3: ("GPSLongitudeRef", ASCII, 2),
-        4: ("GPSLongitude", RATIONAL, 3),
-        5: ("GPSAltitudeRef", BYTE, 1),
-        6: ("GPSAltitude", RATIONAL, 1),
-        7: ("GPSTimeStamp", RATIONAL, 3),
-        8: ("GPSSatellites", ASCII, 0),
-        9: ("GPSStatus", ASCII, 2),
-        10: ("GPSMeasureMode", ASCII, 2),
-        11: ("GPSDOP", RATIONAL, 1),
-        12: ("GPSSpeedRef", ASCII, 2),
-        13: ("GPSSpeed", RATIONAL, 1),
-        14: ("GPSTrackRef", ASCII, 2),
-        15: ("GPSTrack", RATIONAL, 1),
-        16: ("GPSImgDirectionRef", ASCII, 2),
-        17: ("GPSImgDirection", RATIONAL, 1),
-        18: ("GPSMapDatum", ASCII, 0),
-        19: ("GPSDestLatitudeRef", ASCII, 2),
-        20: ("GPSDestLatitude", RATIONAL, 3),
-        21: ("GPSDestLongitudeRef", ASCII, 2),
-        22: ("GPSDestLongitude", RATIONAL, 3),
-        23: ("GPSDestBearingRef", ASCII, 2),
-        24: ("GPSDestBearing", RATIONAL, 1),
-        25: ("GPSDestDistanceRef", ASCII, 2),
-        26: ("GPSDestDistance", RATIONAL, 1),
-        27: ("GPSProcessingMethod", UNDEFINED, 0),
-        28: ("GPSAreaInformation", UNDEFINED, 0),
-        29: ("GPSDateStamp", ASCII, 11),
-        30: ("GPSDifferential", SHORT, 1),
-    },
-    # InteroperabilityIFD
-    40965: {1: ("InteropIndex", ASCII, 1), 2: ("InteropVersion", UNDEFINED, 1)},
-}
-
-# Legacy Tags structure
-# these tags aren't included above, but were in the previous versions
-TAGS = {
-    347: "JPEGTables",
-    700: "XMP",
-    # Additional Exif Info
-    32932: "Wang Annotation",
-    33434: "ExposureTime",
-    33437: "FNumber",
-    33445: "MD FileTag",
-    33446: "MD ScalePixel",
-    33447: "MD ColorTable",
-    33448: "MD LabName",
-    33449: "MD SampleInfo",
-    33450: "MD PrepDate",
-    33451: "MD PrepTime",
-    33452: "MD FileUnits",
-    33550: "ModelPixelScaleTag",
-    33723: "IptcNaaInfo",
-    33918: "INGR Packet Data Tag",
-    33919: "INGR Flag Registers",
-    33920: "IrasB Transformation Matrix",
-    33922: "ModelTiepointTag",
-    34264: "ModelTransformationTag",
-    34377: "PhotoshopInfo",
-    34735: "GeoKeyDirectoryTag",
-    34736: "GeoDoubleParamsTag",
-    34737: "GeoAsciiParamsTag",
-    34850: "ExposureProgram",
-    34852: "SpectralSensitivity",
-    34855: "ISOSpeedRatings",
-    34856: "OECF",
-    34864: "SensitivityType",
-    34865: "StandardOutputSensitivity",
-    34866: "RecommendedExposureIndex",
-    34867: "ISOSpeed",
-    34868: "ISOSpeedLatitudeyyy",
-    34869: "ISOSpeedLatitudezzz",
-    34908: "HylaFAX FaxRecvParams",
-    34909: "HylaFAX FaxSubAddress",
-    34910: "HylaFAX FaxRecvTime",
-    36864: "ExifVersion",
-    36867: "DateTimeOriginal",
-    36868: "DateTimeDigitized",
-    37121: "ComponentsConfiguration",
-    37122: "CompressedBitsPerPixel",
-    37724: "ImageSourceData",
-    37377: "ShutterSpeedValue",
-    37378: "ApertureValue",
-    37379: "BrightnessValue",
-    37380: "ExposureBiasValue",
-    37381: "MaxApertureValue",
-    37382: "SubjectDistance",
-    37383: "MeteringMode",
-    37384: "LightSource",
-    37385: "Flash",
-    37386: "FocalLength",
-    37396: "SubjectArea",
-    37500: "MakerNote",
-    37510: "UserComment",
-    37520: "SubSec",
-    37521: "SubSecTimeOriginal",
-    37522: "SubsecTimeDigitized",
-    40960: "FlashPixVersion",
-    40961: "ColorSpace",
-    40962: "PixelXDimension",
-    40963: "PixelYDimension",
-    40964: "RelatedSoundFile",
-    40965: "InteroperabilityIFD",
-    41483: "FlashEnergy",
-    41484: "SpatialFrequencyResponse",
-    41486: "FocalPlaneXResolution",
-    41487: "FocalPlaneYResolution",
-    41488: "FocalPlaneResolutionUnit",
-    41492: "SubjectLocation",
-    41493: "ExposureIndex",
-    41495: "SensingMethod",
-    41728: "FileSource",
-    41729: "SceneType",
-    41730: "CFAPattern",
-    41985: "CustomRendered",
-    41986: "ExposureMode",
-    41987: "WhiteBalance",
-    41988: "DigitalZoomRatio",
-    41989: "FocalLengthIn35mmFilm",
-    41990: "SceneCaptureType",
-    41991: "GainControl",
-    41992: "Contrast",
-    41993: "Saturation",
-    41994: "Sharpness",
-    41995: "DeviceSettingDescription",
-    41996: "SubjectDistanceRange",
-    42016: "ImageUniqueID",
-    42032: "CameraOwnerName",
-    42033: "BodySerialNumber",
-    42034: "LensSpecification",
-    42035: "LensMake",
-    42036: "LensModel",
-    42037: "LensSerialNumber",
-    42112: "GDAL_METADATA",
-    42113: "GDAL_NODATA",
-    42240: "Gamma",
-    50215: "Oce Scanjob Description",
-    50216: "Oce Application Selector",
-    50217: "Oce Identification Number",
-    50218: "Oce ImageLogic Characteristics",
-    # Adobe DNG
-    50706: "DNGVersion",
-    50707: "DNGBackwardVersion",
-    50708: "UniqueCameraModel",
-    50709: "LocalizedCameraModel",
-    50710: "CFAPlaneColor",
-    50711: "CFALayout",
-    50712: "LinearizationTable",
-    50713: "BlackLevelRepeatDim",
-    50714: "BlackLevel",
-    50715: "BlackLevelDeltaH",
-    50716: "BlackLevelDeltaV",
-    50717: "WhiteLevel",
-    50718: "DefaultScale",
-    50719: "DefaultCropOrigin",
-    50720: "DefaultCropSize",
-    50721: "ColorMatrix1",
-    50722: "ColorMatrix2",
-    50723: "CameraCalibration1",
-    50724: "CameraCalibration2",
-    50725: "ReductionMatrix1",
-    50726: "ReductionMatrix2",
-    50727: "AnalogBalance",
-    50728: "AsShotNeutral",
-    50729: "AsShotWhiteXY",
-    50730: "BaselineExposure",
-    50731: "BaselineNoise",
-    50732: "BaselineSharpness",
-    50733: "BayerGreenSplit",
-    50734: "LinearResponseLimit",
-    50735: "CameraSerialNumber",
-    50736: "LensInfo",
-    50737: "ChromaBlurRadius",
-    50738: "AntiAliasStrength",
-    50740: "DNGPrivateData",
-    50778: "CalibrationIlluminant1",
-    50779: "CalibrationIlluminant2",
-    50784: "Alias Layer Metadata",
-}
-
-
-def _populate():
-    for k, v in TAGS_V2.items():
-        # Populate legacy structure.
-        TAGS[k] = v[0]
-        if len(v) == 4:
-            for sk, sv in v[3].items():
-                TAGS[(k, sv)] = sk
-
-        TAGS_V2[k] = TagInfo(k, *v)
-
-    for group, tags in TAGS_V2_GROUPS.items():
-        for k, v in tags.items():
-            tags[k] = TagInfo(k, *v)
-
-
-_populate()
-##
-# Map type numbers to type names -- defined in ImageFileDirectory.
-
-TYPES = {}
-
-# was:
-# TYPES = {
-#     1: "byte",
-#     2: "ascii",
-#     3: "short",
-#     4: "long",
-#     5: "rational",
-#     6: "signed byte",
-#     7: "undefined",
-#     8: "signed short",
-#     9: "signed long",
-#     10: "signed rational",
-#     11: "float",
-#     12: "double",
-# }
-
-#
-# These tags are handled by default in libtiff, without
-# adding to the custom dictionary. From tif_dir.c, searching for
-# case TIFFTAG in the _TIFFVSetField function:
-# Line: item.
-# 148: case TIFFTAG_SUBFILETYPE:
-# 151: case TIFFTAG_IMAGEWIDTH:
-# 154: case TIFFTAG_IMAGELENGTH:
-# 157: case TIFFTAG_BITSPERSAMPLE:
-# 181: case TIFFTAG_COMPRESSION:
-# 202: case TIFFTAG_PHOTOMETRIC:
-# 205: case TIFFTAG_THRESHHOLDING:
-# 208: case TIFFTAG_FILLORDER:
-# 214: case TIFFTAG_ORIENTATION:
-# 221: case TIFFTAG_SAMPLESPERPIXEL:
-# 228: case TIFFTAG_ROWSPERSTRIP:
-# 238: case TIFFTAG_MINSAMPLEVALUE:
-# 241: case TIFFTAG_MAXSAMPLEVALUE:
-# 244: case TIFFTAG_SMINSAMPLEVALUE:
-# 247: case TIFFTAG_SMAXSAMPLEVALUE:
-# 250: case TIFFTAG_XRESOLUTION:
-# 256: case TIFFTAG_YRESOLUTION:
-# 262: case TIFFTAG_PLANARCONFIG:
-# 268: case TIFFTAG_XPOSITION:
-# 271: case TIFFTAG_YPOSITION:
-# 274: case TIFFTAG_RESOLUTIONUNIT:
-# 280: case TIFFTAG_PAGENUMBER:
-# 284: case TIFFTAG_HALFTONEHINTS:
-# 288: case TIFFTAG_COLORMAP:
-# 294: case TIFFTAG_EXTRASAMPLES:
-# 298: case TIFFTAG_MATTEING:
-# 305: case TIFFTAG_TILEWIDTH:
-# 316: case TIFFTAG_TILELENGTH:
-# 327: case TIFFTAG_TILEDEPTH:
-# 333: case TIFFTAG_DATATYPE:
-# 344: case TIFFTAG_SAMPLEFORMAT:
-# 361: case TIFFTAG_IMAGEDEPTH:
-# 364: case TIFFTAG_SUBIFD:
-# 376: case TIFFTAG_YCBCRPOSITIONING:
-# 379: case TIFFTAG_YCBCRSUBSAMPLING:
-# 383: case TIFFTAG_TRANSFERFUNCTION:
-# 389: case TIFFTAG_REFERENCEBLACKWHITE:
-# 393: case TIFFTAG_INKNAMES:
-
-# Following pseudo-tags are also handled by default in libtiff:
-# TIFFTAG_JPEGQUALITY 65537
-
-# some of these are not in our TAGS_V2 dict and were included from tiff.h
-
-# This list also exists in encode.c
-LIBTIFF_CORE = {
-    255,
-    256,
-    257,
-    258,
-    259,
-    262,
-    263,
-    266,
-    274,
-    277,
-    278,
-    280,
-    281,
-    340,
-    341,
-    282,
-    283,
-    284,
-    286,
-    287,
-    296,
-    297,
-    321,
-    320,
-    338,
-    32995,
-    322,
-    323,
-    32998,
-    32996,
-    339,
-    32997,
-    330,
-    531,
-    530,
-    301,
-    532,
-    333,
-    # as above
-    269,  # this has been in our tests forever, and works
-    65537,
-}
-
-LIBTIFF_CORE.remove(255)  # We don't have support for subfiletypes
-LIBTIFF_CORE.remove(322)  # We don't have support for writing tiled images with libtiff
-LIBTIFF_CORE.remove(323)  # Tiled images
-LIBTIFF_CORE.remove(333)  # Ink Names either
-
-# Note to advanced users: There may be combinations of these
-# parameters and values that when added properly, will work and
-# produce valid tiff images that may work in your application.
-# It is safe to add and remove tags from this set from Pillow's point
-# of view so long as you test against libtiff.
diff --git a/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/exceptiongroup/_formatting.py b/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/exceptiongroup/_formatting.py
deleted file mode 100644
index c0402ba03d2f564f8a33b1338ada04c2d0f5c48b..0000000000000000000000000000000000000000
--- a/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/exceptiongroup/_formatting.py
+++ /dev/null
@@ -1,563 +0,0 @@
-# traceback_exception_init() adapted from trio
-#
-# _ExceptionPrintContext and traceback_exception_format() copied from the standard
-# library
-from __future__ import annotations
-
-import collections.abc
-import sys
-import textwrap
-import traceback
-from functools import singledispatch
-from types import TracebackType
-from typing import Any, List, Optional
-
-from ._exceptions import BaseExceptionGroup
-
-max_group_width = 15
-max_group_depth = 10
-_cause_message = (
-    "\nThe above exception was the direct cause of the following exception:\n\n"
-)
-
-_context_message = (
-    "\nDuring handling of the above exception, another exception occurred:\n\n"
-)
-
-
-def _format_final_exc_line(etype, value):
-    valuestr = _safe_string(value, "exception")
-    if value is None or not valuestr:
-        line = f"{etype}\n"
-    else:
-        line = f"{etype}: {valuestr}\n"
-
-    return line
-
-
-def _safe_string(value, what, func=str):
-    try:
-        return func(value)
-    except BaseException:
-        return f"<{what} {func.__name__}() failed>"
-
-
-class _ExceptionPrintContext:
-    def __init__(self):
-        self.seen = set()
-        self.exception_group_depth = 0
-        self.need_close = False
-
-    def indent(self):
-        return " " * (2 * self.exception_group_depth)
-
-    def emit(self, text_gen, margin_char=None):
-        if margin_char is None:
-            margin_char = "|"
-        indent_str = self.indent()
-        if self.exception_group_depth:
-            indent_str += margin_char + " "
-
-        if isinstance(text_gen, str):
-            yield textwrap.indent(text_gen, indent_str, lambda line: True)
-        else:
-            for text in text_gen:
-                yield textwrap.indent(text, indent_str, lambda line: True)
-
-
-def exceptiongroup_excepthook(
-    etype: type[BaseException], value: BaseException, tb: TracebackType | None
-) -> None:
-    sys.stderr.write("".join(traceback.format_exception(etype, value, tb)))
-
-
-class PatchedTracebackException(traceback.TracebackException):
-    def __init__(
-        self,
-        exc_type: type[BaseException],
-        exc_value: BaseException,
-        exc_traceback: TracebackType | None,
-        *,
-        limit: int | None = None,
-        lookup_lines: bool = True,
-        capture_locals: bool = False,
-        compact: bool = False,
-        _seen: set[int] | None = None,
-    ) -> None:
-        kwargs: dict[str, Any] = {}
-        if sys.version_info >= (3, 10):
-            kwargs["compact"] = compact
-
-        is_recursive_call = _seen is not None
-        if _seen is None:
-            _seen = set()
-        _seen.add(id(exc_value))
-
-        self.stack = traceback.StackSummary.extract(
-            traceback.walk_tb(exc_traceback),
-            limit=limit,
-            lookup_lines=lookup_lines,
-            capture_locals=capture_locals,
-        )
-        self.exc_type = exc_type
-        # Capture now to permit freeing resources: only complication is in the
-        # unofficial API _format_final_exc_line
-        self._str = _safe_string(exc_value, "exception")
-        try:
-            self.__notes__ = getattr(exc_value, "__notes__", None)
-        except KeyError:
-            # Workaround for https://github.com/python/cpython/issues/98778 on Python
-            # <= 3.9, and some 3.10 and 3.11 patch versions.
-            HTTPError = getattr(sys.modules.get("urllib.error", None), "HTTPError", ())
-            if sys.version_info[:2] <= (3, 11) and isinstance(exc_value, HTTPError):
-                self.__notes__ = None
-            else:
-                raise
-
-        if exc_type and issubclass(exc_type, SyntaxError):
-            # Handle SyntaxError's specially
-            self.filename = exc_value.filename
-            lno = exc_value.lineno
-            self.lineno = str(lno) if lno is not None else None
-            self.text = exc_value.text
-            self.offset = exc_value.offset
-            self.msg = exc_value.msg
-            if sys.version_info >= (3, 10):
-                end_lno = exc_value.end_lineno
-                self.end_lineno = str(end_lno) if end_lno is not None else None
-                self.end_offset = exc_value.end_offset
-        elif (
-            exc_type
-            and issubclass(exc_type, (NameError, AttributeError))
-            and getattr(exc_value, "name", None) is not None
-        ):
-            suggestion = _compute_suggestion_error(exc_value, exc_traceback)
-            if suggestion:
-                self._str += f". Did you mean: '{suggestion}'?"
-
-        if lookup_lines:
-            # Force all lines in the stack to be loaded
-            for frame in self.stack:
-                frame.line
-
-        self.__suppress_context__ = (
-            exc_value.__suppress_context__ if exc_value is not None else False
-        )
-
-        # Convert __cause__ and __context__ to `TracebackExceptions`s, use a
-        # queue to avoid recursion (only the top-level call gets _seen == None)
-        if not is_recursive_call:
-            queue = [(self, exc_value)]
-            while queue:
-                te, e = queue.pop()
-
-                if e and e.__cause__ is not None and id(e.__cause__) not in _seen:
-                    cause = PatchedTracebackException(
-                        type(e.__cause__),
-                        e.__cause__,
-                        e.__cause__.__traceback__,
-                        limit=limit,
-                        lookup_lines=lookup_lines,
-                        capture_locals=capture_locals,
-                        _seen=_seen,
-                    )
-                else:
-                    cause = None
-
-                if compact:
-                    need_context = (
-                        cause is None and e is not None and not e.__suppress_context__
-                    )
-                else:
-                    need_context = True
-                if (
-                    e
-                    and e.__context__ is not None
-                    and need_context
-                    and id(e.__context__) not in _seen
-                ):
-                    context = PatchedTracebackException(
-                        type(e.__context__),
-                        e.__context__,
-                        e.__context__.__traceback__,
-                        limit=limit,
-                        lookup_lines=lookup_lines,
-                        capture_locals=capture_locals,
-                        _seen=_seen,
-                    )
-                else:
-                    context = None
-
-                # Capture each of the exceptions in the ExceptionGroup along with each
-                # of their causes and contexts
-                if e and isinstance(e, BaseExceptionGroup):
-                    exceptions = []
-                    for exc in e.exceptions:
-                        texc = PatchedTracebackException(
-                            type(exc),
-                            exc,
-                            exc.__traceback__,
-                            lookup_lines=lookup_lines,
-                            capture_locals=capture_locals,
-                            _seen=_seen,
-                        )
-                        exceptions.append(texc)
-                else:
-                    exceptions = None
-
-                te.__cause__ = cause
-                te.__context__ = context
-                te.exceptions = exceptions
-                if cause:
-                    queue.append((te.__cause__, e.__cause__))
-                if context:
-                    queue.append((te.__context__, e.__context__))
-                if exceptions:
-                    queue.extend(zip(te.exceptions, e.exceptions))
-
-    def format(self, *, chain=True, _ctx=None):
-        if _ctx is None:
-            _ctx = _ExceptionPrintContext()
-
-        output = []
-        exc = self
-        if chain:
-            while exc:
-                if exc.__cause__ is not None:
-                    chained_msg = _cause_message
-                    chained_exc = exc.__cause__
-                elif exc.__context__ is not None and not exc.__suppress_context__:
-                    chained_msg = _context_message
-                    chained_exc = exc.__context__
-                else:
-                    chained_msg = None
-                    chained_exc = None
-
-                output.append((chained_msg, exc))
-                exc = chained_exc
-        else:
-            output.append((None, exc))
-
-        for msg, exc in reversed(output):
-            if msg is not None:
-                yield from _ctx.emit(msg)
-            if exc.exceptions is None:
-                if exc.stack:
-                    yield from _ctx.emit("Traceback (most recent call last):\n")
-                    yield from _ctx.emit(exc.stack.format())
-                yield from _ctx.emit(exc.format_exception_only())
-            elif _ctx.exception_group_depth > max_group_depth:
-                # exception group, but depth exceeds limit
-                yield from _ctx.emit(f"... (max_group_depth is {max_group_depth})\n")
-            else:
-                # format exception group
-                is_toplevel = _ctx.exception_group_depth == 0
-                if is_toplevel:
-                    _ctx.exception_group_depth += 1
-
-                if exc.stack:
-                    yield from _ctx.emit(
-                        "Exception Group Traceback (most recent call last):\n",
-                        margin_char="+" if is_toplevel else None,
-                    )
-                    yield from _ctx.emit(exc.stack.format())
-
-                yield from _ctx.emit(exc.format_exception_only())
-                num_excs = len(exc.exceptions)
-                if num_excs <= max_group_width:
-                    n = num_excs
-                else:
-                    n = max_group_width + 1
-                _ctx.need_close = False
-                for i in range(n):
-                    last_exc = i == n - 1
-                    if last_exc:
-                        # The closing frame may be added by a recursive call
-                        _ctx.need_close = True
-
-                    if max_group_width is not None:
-                        truncated = i >= max_group_width
-                    else:
-                        truncated = False
-                    title = f"{i + 1}" if not truncated else "..."
-                    yield (
-                        _ctx.indent()
-                        + ("+-" if i == 0 else "  ")
-                        + f"+---------------- {title} ----------------\n"
-                    )
-                    _ctx.exception_group_depth += 1
-                    if not truncated:
-                        yield from exc.exceptions[i].format(chain=chain, _ctx=_ctx)
-                    else:
-                        remaining = num_excs - max_group_width
-                        plural = "s" if remaining > 1 else ""
-                        yield from _ctx.emit(
-                            f"and {remaining} more exception{plural}\n"
-                        )
-
-                    if last_exc and _ctx.need_close:
-                        yield _ctx.indent() + "+------------------------------------\n"
-                        _ctx.need_close = False
-                    _ctx.exception_group_depth -= 1
-
-                if is_toplevel:
-                    assert _ctx.exception_group_depth == 1
-                    _ctx.exception_group_depth = 0
-
-    def format_exception_only(self):
-        """Format the exception part of the traceback.
-        The return value is a generator of strings, each ending in a newline.
-        Normally, the generator emits a single string; however, for
-        SyntaxError exceptions, it emits several lines that (when
-        printed) display detailed information about where the syntax
-        error occurred.
-        The message indicating which exception occurred is always the last
-        string in the output.
-        """
-        if self.exc_type is None:
-            yield traceback._format_final_exc_line(None, self._str)
-            return
-
-        stype = self.exc_type.__qualname__
-        smod = self.exc_type.__module__
-        if smod not in ("__main__", "builtins"):
-            if not isinstance(smod, str):
-                smod = "<unknown>"
-            stype = smod + "." + stype
-
-        if not issubclass(self.exc_type, SyntaxError):
-            yield _format_final_exc_line(stype, self._str)
-        elif traceback_exception_format_syntax_error is not None:
-            yield from traceback_exception_format_syntax_error(self, stype)
-        else:
-            yield from traceback_exception_original_format_exception_only(self)
-
-        if isinstance(self.__notes__, collections.abc.Sequence):
-            for note in self.__notes__:
-                note = _safe_string(note, "note")
-                yield from [line + "\n" for line in note.split("\n")]
-        elif self.__notes__ is not None:
-            yield _safe_string(self.__notes__, "__notes__", func=repr)
-
-
-traceback_exception_original_format = traceback.TracebackException.format
-traceback_exception_original_format_exception_only = (
-    traceback.TracebackException.format_exception_only
-)
-traceback_exception_format_syntax_error = getattr(
-    traceback.TracebackException, "_format_syntax_error", None
-)
-if sys.excepthook is sys.__excepthook__:
-    traceback.TracebackException.__init__ = (  # type: ignore[assignment]
-        PatchedTracebackException.__init__
-    )
-    traceback.TracebackException.format = (  # type: ignore[assignment]
-        PatchedTracebackException.format
-    )
-    traceback.TracebackException.format_exception_only = (  # type: ignore[assignment]
-        PatchedTracebackException.format_exception_only
-    )
-    sys.excepthook = exceptiongroup_excepthook
-
-
-@singledispatch
-def format_exception_only(__exc: BaseException) -> List[str]:
-    return list(
-        PatchedTracebackException(
-            type(__exc), __exc, None, compact=True
-        ).format_exception_only()
-    )
-
-
-@format_exception_only.register
-def _(__exc: type, value: BaseException) -> List[str]:
-    return format_exception_only(value)
-
-
-@singledispatch
-def format_exception(
-    __exc: BaseException,
-    limit: Optional[int] = None,
-    chain: bool = True,
-) -> List[str]:
-    return list(
-        PatchedTracebackException(
-            type(__exc), __exc, __exc.__traceback__, limit=limit, compact=True
-        ).format(chain=chain)
-    )
-
-
-@format_exception.register
-def _(
-    __exc: type,
-    value: BaseException,
-    tb: TracebackType,
-    limit: Optional[int] = None,
-    chain: bool = True,
-) -> List[str]:
-    return format_exception(value, limit, chain)
-
-
-@singledispatch
-def print_exception(
-    __exc: BaseException,
-    limit: Optional[int] = None,
-    file: Any = None,
-    chain: bool = True,
-) -> None:
-    if file is None:
-        file = sys.stderr
-
-    for line in PatchedTracebackException(
-        type(__exc), __exc, __exc.__traceback__, limit=limit
-    ).format(chain=chain):
-        print(line, file=file, end="")
-
-
-@print_exception.register
-def _(
-    __exc: type,
-    value: BaseException,
-    tb: TracebackType,
-    limit: Optional[int] = None,
-    file: Any = None,
-    chain: bool = True,
-) -> None:
-    print_exception(value, limit, file, chain)
-
-
-def print_exc(
-    limit: Optional[int] = None,
-    file: Any | None = None,
-    chain: bool = True,
-) -> None:
-    value = sys.exc_info()[1]
-    print_exception(value, limit, file, chain)
-
-
-# Python levenshtein edit distance code for NameError/AttributeError
-# suggestions, backported from 3.12
-
-_MAX_CANDIDATE_ITEMS = 750
-_MAX_STRING_SIZE = 40
-_MOVE_COST = 2
-_CASE_COST = 1
-_SENTINEL = object()
-
-
-def _substitution_cost(ch_a, ch_b):
-    if ch_a == ch_b:
-        return 0
-    if ch_a.lower() == ch_b.lower():
-        return _CASE_COST
-    return _MOVE_COST
-
-
-def _compute_suggestion_error(exc_value, tb):
-    wrong_name = getattr(exc_value, "name", None)
-    if wrong_name is None or not isinstance(wrong_name, str):
-        return None
-    if isinstance(exc_value, AttributeError):
-        obj = getattr(exc_value, "obj", _SENTINEL)
-        if obj is _SENTINEL:
-            return None
-        obj = exc_value.obj
-        try:
-            d = dir(obj)
-        except Exception:
-            return None
-    else:
-        assert isinstance(exc_value, NameError)
-        # find most recent frame
-        if tb is None:
-            return None
-        while tb.tb_next is not None:
-            tb = tb.tb_next
-        frame = tb.tb_frame
-
-        d = list(frame.f_locals) + list(frame.f_globals) + list(frame.f_builtins)
-    if len(d) > _MAX_CANDIDATE_ITEMS:
-        return None
-    wrong_name_len = len(wrong_name)
-    if wrong_name_len > _MAX_STRING_SIZE:
-        return None
-    best_distance = wrong_name_len
-    suggestion = None
-    for possible_name in d:
-        if possible_name == wrong_name:
-            # A missing attribute is "found". Don't suggest it (see GH-88821).
-            continue
-        # No more than 1/3 of the involved characters should need changed.
-        max_distance = (len(possible_name) + wrong_name_len + 3) * _MOVE_COST // 6
-        # Don't take matches we've already beaten.
-        max_distance = min(max_distance, best_distance - 1)
-        current_distance = _levenshtein_distance(
-            wrong_name, possible_name, max_distance
-        )
-        if current_distance > max_distance:
-            continue
-        if not suggestion or current_distance < best_distance:
-            suggestion = possible_name
-            best_distance = current_distance
-    return suggestion
-
-
-def _levenshtein_distance(a, b, max_cost):
-    # A Python implementation of Python/suggestions.c:levenshtein_distance.
-
-    # Both strings are the same
-    if a == b:
-        return 0
-
-    # Trim away common affixes
-    pre = 0
-    while a[pre:] and b[pre:] and a[pre] == b[pre]:
-        pre += 1
-    a = a[pre:]
-    b = b[pre:]
-    post = 0
-    while a[: post or None] and b[: post or None] and a[post - 1] == b[post - 1]:
-        post -= 1
-    a = a[: post or None]
-    b = b[: post or None]
-    if not a or not b:
-        return _MOVE_COST * (len(a) + len(b))
-    if len(a) > _MAX_STRING_SIZE or len(b) > _MAX_STRING_SIZE:
-        return max_cost + 1
-
-    # Prefer shorter buffer
-    if len(b) < len(a):
-        a, b = b, a
-
-    # Quick fail when a match is impossible
-    if (len(b) - len(a)) * _MOVE_COST > max_cost:
-        return max_cost + 1
-
-    # Instead of producing the whole traditional len(a)-by-len(b)
-    # matrix, we can update just one row in place.
-    # Initialize the buffer row
-    row = list(range(_MOVE_COST, _MOVE_COST * (len(a) + 1), _MOVE_COST))
-
-    result = 0
-    for bindex in range(len(b)):
-        bchar = b[bindex]
-        distance = result = bindex * _MOVE_COST
-        minimum = sys.maxsize
-        for index in range(len(a)):
-            # 1) Previous distance in this row is cost(b[:b_index], a[:index])
-            substitute = distance + _substitution_cost(bchar, a[index])
-            # 2) cost(b[:b_index], a[:index+1]) from previous row
-            distance = row[index]
-            # 3) existing result is cost(b[:b_index+1], a[index])
-
-            insert_delete = min(result, distance) + _MOVE_COST
-            result = min(insert_delete, substitute)
-
-            # cost(b[:b_index+1], a[:index+1])
-            row[index] = result
-            if result < minimum:
-                minimum = result
-        if minimum > max_cost:
-            # Everything in this row is too big, so bail early.
-            return max_cost + 1
-    return result
diff --git a/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/fontTools/ttLib/tables/F__e_a_t.py b/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/fontTools/ttLib/tables/F__e_a_t.py
deleted file mode 100644
index fbcd6ca6e7bc0640263ddab74e1e1c89ea61bbfb..0000000000000000000000000000000000000000
--- a/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/fontTools/ttLib/tables/F__e_a_t.py
+++ /dev/null
@@ -1,144 +0,0 @@
-from fontTools.misc import sstruct
-from fontTools.misc.fixedTools import floatToFixedToStr
-from fontTools.misc.textTools import safeEval
-from . import DefaultTable
-from . import grUtils
-import struct
-
-Feat_hdr_format = """
-    >
-    version:    16.16F
-"""
-
-
-class table_F__e_a_t(DefaultTable.DefaultTable):
-    """The ``Feat`` table is used exclusively by the Graphite shaping engine
-    to store features and possible settings specified in GDL. Graphite features
-    determine what rules are applied to transform a glyph stream.
-
-    Not to be confused with ``feat``, or the OpenType Layout tables
-    ``GSUB``/``GPOS``."""
-
-    def __init__(self, tag=None):
-        DefaultTable.DefaultTable.__init__(self, tag)
-        self.features = {}
-
-    def decompile(self, data, ttFont):
-        (_, data) = sstruct.unpack2(Feat_hdr_format, data, self)
-        self.version = float(floatToFixedToStr(self.version, precisionBits=16))
-        (numFeats,) = struct.unpack(">H", data[:2])
-        data = data[8:]
-        allfeats = []
-        maxsetting = 0
-        for i in range(numFeats):
-            if self.version >= 2.0:
-                (fid, nums, _, offset, flags, lid) = struct.unpack(
-                    ">LHHLHH", data[16 * i : 16 * (i + 1)]
-                )
-                offset = int((offset - 12 - 16 * numFeats) / 4)
-            else:
-                (fid, nums, offset, flags, lid) = struct.unpack(
-                    ">HHLHH", data[12 * i : 12 * (i + 1)]
-                )
-                offset = int((offset - 12 - 12 * numFeats) / 4)
-            allfeats.append((fid, nums, offset, flags, lid))
-            maxsetting = max(maxsetting, offset + nums)
-        data = data[16 * numFeats :]
-        allsettings = []
-        for i in range(maxsetting):
-            if len(data) >= 4 * (i + 1):
-                (val, lid) = struct.unpack(">HH", data[4 * i : 4 * (i + 1)])
-                allsettings.append((val, lid))
-        for i, f in enumerate(allfeats):
-            (fid, nums, offset, flags, lid) = f
-            fobj = Feature()
-            fobj.flags = flags
-            fobj.label = lid
-            self.features[grUtils.num2tag(fid)] = fobj
-            fobj.settings = {}
-            fobj.default = None
-            fobj.index = i
-            for i in range(offset, offset + nums):
-                if i >= len(allsettings):
-                    continue
-                (vid, vlid) = allsettings[i]
-                fobj.settings[vid] = vlid
-                if fobj.default is None:
-                    fobj.default = vid
-
-    def compile(self, ttFont):
-        fdat = b""
-        vdat = b""
-        offset = 0
-        for f, v in sorted(self.features.items(), key=lambda x: x[1].index):
-            fnum = grUtils.tag2num(f)
-            if self.version >= 2.0:
-                fdat += struct.pack(
-                    ">LHHLHH",
-                    grUtils.tag2num(f),
-                    len(v.settings),
-                    0,
-                    offset * 4 + 12 + 16 * len(self.features),
-                    v.flags,
-                    v.label,
-                )
-            elif fnum > 65535:  # self healing for alphabetic ids
-                self.version = 2.0
-                return self.compile(ttFont)
-            else:
-                fdat += struct.pack(
-                    ">HHLHH",
-                    grUtils.tag2num(f),
-                    len(v.settings),
-                    offset * 4 + 12 + 12 * len(self.features),
-                    v.flags,
-                    v.label,
-                )
-            for s, l in sorted(
-                v.settings.items(), key=lambda x: (-1, x[1]) if x[0] == v.default else x
-            ):
-                vdat += struct.pack(">HH", s, l)
-            offset += len(v.settings)
-        hdr = sstruct.pack(Feat_hdr_format, self)
-        return hdr + struct.pack(">HHL", len(self.features), 0, 0) + fdat + vdat
-
-    def toXML(self, writer, ttFont):
-        writer.simpletag("version", version=self.version)
-        writer.newline()
-        for f, v in sorted(self.features.items(), key=lambda x: x[1].index):
-            writer.begintag(
-                "feature",
-                fid=f,
-                label=v.label,
-                flags=v.flags,
-                default=(v.default if v.default else 0),
-            )
-            writer.newline()
-            for s, l in sorted(v.settings.items()):
-                writer.simpletag("setting", value=s, label=l)
-                writer.newline()
-            writer.endtag("feature")
-            writer.newline()
-
-    def fromXML(self, name, attrs, content, ttFont):
-        if name == "version":
-            self.version = float(safeEval(attrs["version"]))
-        elif name == "feature":
-            fid = attrs["fid"]
-            fobj = Feature()
-            fobj.flags = int(safeEval(attrs["flags"]))
-            fobj.label = int(safeEval(attrs["label"]))
-            fobj.default = int(safeEval(attrs.get("default", "0")))
-            fobj.index = len(self.features)
-            self.features[fid] = fobj
-            fobj.settings = {}
-            for element in content:
-                if not isinstance(element, tuple):
-                    continue
-                tag, a, c = element
-                if tag == "setting":
-                    fobj.settings[int(safeEval(a["value"]))] = int(safeEval(a["label"]))
-
-
-class Feature(object):
-    pass
diff --git a/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/fontTools/ttLib/tables/_f_p_g_m.py b/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/fontTools/ttLib/tables/_f_p_g_m.py
deleted file mode 100644
index df23041d65617af9c1f6feb00db970b7870c2268..0000000000000000000000000000000000000000
--- a/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/fontTools/ttLib/tables/_f_p_g_m.py
+++ /dev/null
@@ -1,49 +0,0 @@
-from . import DefaultTable
-from . import ttProgram
-
-
-class table__f_p_g_m(DefaultTable.DefaultTable):
-    def decompile(self, data, ttFont):
-        program = ttProgram.Program()
-        program.fromBytecode(data)
-        self.program = program
-
-    def compile(self, ttFont):
-        return self.program.getBytecode()
-
-    def toXML(self, writer, ttFont):
-        self.program.toXML(writer, ttFont)
-
-    def fromXML(self, name, attrs, content, ttFont):
-        program = ttProgram.Program()
-        program.fromXML(name, attrs, content, ttFont)
-        self.program = program
-
-    def __bool__(self):
-        """
-        >>> fpgm = table__f_p_g_m()
-        >>> bool(fpgm)
-        False
-        >>> p = ttProgram.Program()
-        >>> fpgm.program = p
-        >>> bool(fpgm)
-        False
-        >>> bc = bytearray([0])
-        >>> p.fromBytecode(bc)
-        >>> bool(fpgm)
-        True
-        >>> p.bytecode.pop()
-        0
-        >>> bool(fpgm)
-        False
-        """
-        return hasattr(self, "program") and bool(self.program)
-
-    __nonzero__ = __bool__
-
-
-if __name__ == "__main__":
-    import sys
-    import doctest
-
-    sys.exit(doctest.testmod().failed)
diff --git a/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/gpt_index/readers/discord_reader.py b/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/gpt_index/readers/discord_reader.py
deleted file mode 100644
index da6212829f46be5f4b35afbc4ec86c1368c2ddc5..0000000000000000000000000000000000000000
--- a/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/gpt_index/readers/discord_reader.py
+++ /dev/null
@@ -1,150 +0,0 @@
-"""Discord reader.
-
-Note: this file is named discord_reader.py to avoid conflicts with the
-discord.py module.
-
-"""
-
-import asyncio
-import logging
-import os
-from typing import List, Optional
-
-from gpt_index.readers.base import BaseReader
-from gpt_index.readers.schema.base import Document
-
-
-async def read_channel(
-    discord_token: str, channel_id: int, limit: Optional[int], oldest_first: bool
-) -> str:
-    """Async read channel.
-
-    Note: This is our hack to create a synchronous interface to the
-    async discord.py API. We use the `asyncio` module to run
-    this function with `asyncio.get_event_loop().run_until_complete`.
-
-    """
-    import discord  # noqa: F401
-
-    messages: List[discord.Message] = []
-
-    class CustomClient(discord.Client):
-        async def on_ready(self) -> None:
-            try:
-                logging.info(f"{self.user} has connected to Discord!")
-                channel = client.get_channel(channel_id)
-                # only work for text channels for now
-                if not isinstance(channel, discord.TextChannel):
-                    raise ValueError(
-                        f"Channel {channel_id} is not a text channel. "
-                        "Only text channels are supported for now."
-                    )
-                # thread_dict maps thread_id to thread
-                thread_dict = {}
-                for thread in channel.threads:
-                    thread_dict[thread.id] = thread
-
-                async for msg in channel.history(
-                    limit=limit, oldest_first=oldest_first
-                ):
-                    messages.append(msg)
-                    if msg.id in thread_dict:
-                        thread = thread_dict[msg.id]
-                        async for thread_msg in thread.history(
-                            limit=limit, oldest_first=oldest_first
-                        ):
-                            messages.append(thread_msg)
-            except Exception as e:
-                logging.error("Encountered error: " + str(e))
-            finally:
-                await self.close()
-
-    intents = discord.Intents.default()
-    intents.message_content = True
-    client = CustomClient(intents=intents)
-    await client.start(discord_token)
-
-    msg_txt_list = [m.content for m in messages]
-
-    return "\n\n".join(msg_txt_list)
-
-
-class DiscordReader(BaseReader):
-    """Discord reader.
-
-    Reads conversations from channels.
-
-    Args:
-        discord_token (Optional[str]): Discord token. If not provided, we
-            assume the environment variable `DISCORD_TOKEN` is set.
-
-    """
-
-    def __init__(self, discord_token: Optional[str] = None) -> None:
-        """Initialize with parameters."""
-        try:
-            import discord  # noqa: F401
-        except ImportError:
-            raise ImportError(
-                "`discord.py` package not found, please run `pip install discord.py`"
-            )
-        if discord_token is None:
-            discord_token = os.environ["DISCORD_TOKEN"]
-            if discord_token is None:
-                raise ValueError(
-                    "Must specify `discord_token` or set environment "
-                    "variable `DISCORD_TOKEN`."
-                )
-
-        self.discord_token = discord_token
-
-    def _read_channel(
-        self, channel_id: int, limit: Optional[int] = None, oldest_first: bool = True
-    ) -> str:
-        """Read channel."""
-        result = asyncio.get_event_loop().run_until_complete(
-            read_channel(
-                self.discord_token, channel_id, limit=limit, oldest_first=oldest_first
-            )
-        )
-        return result
-
-    def load_data(
-        self,
-        channel_ids: List[int],
-        limit: Optional[int] = None,
-        oldest_first: bool = True,
-    ) -> List[Document]:
-        """Load data from the input directory.
-
-        Args:
-            channel_ids (List[int]): List of channel ids to read.
-            limit (Optional[int]): Maximum number of messages to read.
-            oldest_first (bool): Whether to read oldest messages first.
-                Defaults to `True`.
-
-        Returns:
-            List[Document]: List of documents.
-
-        """
-        results: List[Document] = []
-        for channel_id in channel_ids:
-            if not isinstance(channel_id, int):
-                raise ValueError(
-                    f"Channel id {channel_id} must be an integer, "
-                    f"not {type(channel_id)}."
-                )
-            channel_content = self._read_channel(
-                channel_id, limit=limit, oldest_first=oldest_first
-            )
-            results.append(
-                Document(channel_content, extra_info={"channel": channel_id})
-            )
-        return results
-
-
-if __name__ == "__main__":
-    reader = DiscordReader()
-    logging.info("initialized reader")
-    output = reader.load_data(channel_ids=[1057178784895348746], limit=10)
-    logging.info(output)
diff --git a/spaces/johnnygreco/the-gpt-who-lived/app.py b/spaces/johnnygreco/the-gpt-who-lived/app.py
deleted file mode 100644
index d86a09fc99cab77a22a099bfb33d22d53cb14a23..0000000000000000000000000000000000000000
--- a/spaces/johnnygreco/the-gpt-who-lived/app.py
+++ /dev/null
@@ -1,57 +0,0 @@
-import os
-from pathlib import Path
-
-import gradio as gr
-import hpqa
-from langchain import VectorDBQA
-from langchain.llms import OpenAI
-
-os.environ["OPENAI_API_KEY"] = ""
-index_path = Path("data/hpqa_faiss_index_500")
-
-
-examples = [
-    "How would you sneak into Hogwarts without being detected?",
-    "Why did Snape kill Dumbledore?",
-    "Who is the most badass wizard in the world?",
-    "Who would win a fight between Dumbledore and a grizzly bear?",
-    "How many siblings does Hermione have?",
-    "Why are the Dursleys so mean to Harry?",
-]
-
-
-def api(question, temperature, api_key=None):
-    if api_key is None or len(api_key) == 0:
-        return "You must provide an OpenAI API key to use this demo 👇"
-    if len(question) == 0:
-        return ""
-    document_store = hpqa.load_document_store(index_path, openai_api_key=api_key)
-    chain = VectorDBQA.from_chain_type(
-        llm=OpenAI(temperature=temperature, openai_api_key=api_key),
-        chain_type="stuff",
-        vectorstore=document_store,
-        return_source_documents=True,
-    )
-    response = chain(question)
-    return response["result"].strip()
-
-
-demo = gr.Blocks()
-
-with demo:
-    gr.Markdown("# 🪄 The GPT Who Lived: Harry Potter QA with GPT 🤖")
-    with gr.Row():
-        with gr.Column():
-            question = gr.Textbox(lines=4, label="Question")
-            temperature = gr.Slider(0.0, 2.0, 0.7, step=0.1, label="🍺 Butterbeer Consumed")
-            with gr.Row():
-                clear = gr.Button("Clear")
-                btn = gr.Button("Submit", variant="primary")
-        with gr.Column():
-            answer = gr.Textbox(lines=4, label="Answer")
-            openai_api_key = gr.Textbox(type="password", label="OpenAI API key")
-    btn.click(api, [question, temperature, openai_api_key], answer)
-    clear.click(lambda _: "", question, question)
-    gr.Examples(examples, question)
-    gr.Markdown("💻 Checkout the `hpqa` source code on [GitHub](https://github.com/johnnygreco/hpqa).")
-demo.launch()
diff --git a/spaces/juuxn/SimpleRVC/infer_pack/commons.py b/spaces/juuxn/SimpleRVC/infer_pack/commons.py
deleted file mode 100644
index 2618e3ad501d1d4745a34024c2bf1676546fae80..0000000000000000000000000000000000000000
--- a/spaces/juuxn/SimpleRVC/infer_pack/commons.py
+++ /dev/null
@@ -1,164 +0,0 @@
-import math
-import torch
-from torch.nn import functional as F
-
-
-def init_weights(m, mean=0.0, std=0.01):
-    classname = m.__class__.__name__
-    if classname.find("Conv") != -1:
-        m.weight.data.normal_(mean, std)
-
-
-def get_padding(kernel_size, dilation=1):
-    return int((kernel_size * dilation - dilation) / 2)
-
-
-def convert_pad_shape(pad_shape):
-    l = pad_shape[::-1]
-    pad_shape = [item for sublist in l for item in sublist]
-    return pad_shape
-
-
-def kl_divergence(m_p, logs_p, m_q, logs_q):
-    """KL(P||Q)"""
-    kl = (logs_q - logs_p) - 0.5
-    kl += (
-        0.5 * (torch.exp(2.0 * logs_p) + ((m_p - m_q) ** 2)) * torch.exp(-2.0 * logs_q)
-    )
-    return kl
-
-
-def rand_gumbel(shape):
-    """Sample from the Gumbel distribution, protect from overflows."""
-    uniform_samples = torch.rand(shape) * 0.99998 + 0.00001
-    return -torch.log(-torch.log(uniform_samples))
-
-
-def rand_gumbel_like(x):
-    g = rand_gumbel(x.size()).to(dtype=x.dtype, device=x.device)
-    return g
-
-
-def slice_segments(x, ids_str, segment_size=4):
-    ret = torch.zeros_like(x[:, :, :segment_size])
-    for i in range(x.size(0)):
-        idx_str = ids_str[i]
-        idx_end = idx_str + segment_size
-        ret[i] = x[i, :, idx_str:idx_end]
-    return ret
-
-
-def slice_segments2(x, ids_str, segment_size=4):
-    ret = torch.zeros_like(x[:, :segment_size])
-    for i in range(x.size(0)):
-        idx_str = ids_str[i]
-        idx_end = idx_str + segment_size
-        ret[i] = x[i, idx_str:idx_end]
-    return ret
-
-
-def rand_slice_segments(x, x_lengths=None, segment_size=4):
-    b, d, t = x.size()
-    if x_lengths is None:
-        x_lengths = t
-    ids_str_max = x_lengths - segment_size + 1
-    ids_str = (torch.rand([b]).to(device=x.device) * ids_str_max).to(dtype=torch.long)
-    ret = slice_segments(x, ids_str, segment_size)
-    return ret, ids_str
-
-
-def get_timing_signal_1d(length, channels, min_timescale=1.0, max_timescale=1.0e4):
-    position = torch.arange(length, dtype=torch.float)
-    num_timescales = channels // 2
-    log_timescale_increment = math.log(float(max_timescale) / float(min_timescale)) / (
-        num_timescales - 1
-    )
-    inv_timescales = min_timescale * torch.exp(
-        torch.arange(num_timescales, dtype=torch.float) * -log_timescale_increment
-    )
-    scaled_time = position.unsqueeze(0) * inv_timescales.unsqueeze(1)
-    signal = torch.cat([torch.sin(scaled_time), torch.cos(scaled_time)], 0)
-    signal = F.pad(signal, [0, 0, 0, channels % 2])
-    signal = signal.view(1, channels, length)
-    return signal
-
-
-def add_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4):
-    b, channels, length = x.size()
-    signal = get_timing_signal_1d(length, channels, min_timescale, max_timescale)
-    return x + signal.to(dtype=x.dtype, device=x.device)
-
-
-def cat_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4, axis=1):
-    b, channels, length = x.size()
-    signal = get_timing_signal_1d(length, channels, min_timescale, max_timescale)
-    return torch.cat([x, signal.to(dtype=x.dtype, device=x.device)], axis)
-
-
-def subsequent_mask(length):
-    mask = torch.tril(torch.ones(length, length)).unsqueeze(0).unsqueeze(0)
-    return mask
-
-
-@torch.jit.script
-def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels):
-    n_channels_int = n_channels[0]
-    in_act = input_a + input_b
-    t_act = torch.tanh(in_act[:, :n_channels_int, :])
-    s_act = torch.sigmoid(in_act[:, n_channels_int:, :])
-    acts = t_act * s_act
-    return acts
-
-
-def convert_pad_shape(pad_shape):
-    l = pad_shape[::-1]
-    pad_shape = [item for sublist in l for item in sublist]
-    return pad_shape
-
-
-def shift_1d(x):
-    x = F.pad(x, convert_pad_shape([[0, 0], [0, 0], [1, 0]]))[:, :, :-1]
-    return x
-
-
-def sequence_mask(length, max_length=None):
-    if max_length is None:
-        max_length = length.max()
-    x = torch.arange(max_length, dtype=length.dtype, device=length.device)
-    return x.unsqueeze(0) < length.unsqueeze(1)
-
-
-def generate_path(duration, mask):
-    """
-    duration: [b, 1, t_x]
-    mask: [b, 1, t_y, t_x]
-    """
-    device = duration.device
-
-    b, _, t_y, t_x = mask.shape
-    cum_duration = torch.cumsum(duration, -1)
-
-    cum_duration_flat = cum_duration.view(b * t_x)
-    path = sequence_mask(cum_duration_flat, t_y).to(mask.dtype)
-    path = path.view(b, t_x, t_y)
-    path = path - F.pad(path, convert_pad_shape([[0, 0], [1, 0], [0, 0]]))[:, :-1]
-    path = path.unsqueeze(1).transpose(2, 3) * mask
-    return path
-
-
-def clip_grad_value_(parameters, clip_value, norm_type=2):
-    if isinstance(parameters, torch.Tensor):
-        parameters = [parameters]
-    parameters = list(filter(lambda p: p.grad is not None, parameters))
-    norm_type = float(norm_type)
-    if clip_value is not None:
-        clip_value = float(clip_value)
-
-    total_norm = 0
-    for p in parameters:
-        param_norm = p.grad.data.norm(norm_type)
-        total_norm += param_norm.item() ** norm_type
-        if clip_value is not None:
-            p.grad.data.clamp_(min=-clip_value, max=clip_value)
-    total_norm = total_norm ** (1.0 / norm_type)
-    return total_norm
diff --git a/spaces/kcagle/AutoGPT/autogpt/processing/html.py b/spaces/kcagle/AutoGPT/autogpt/processing/html.py
deleted file mode 100644
index 81387b12adab5023150c55f2075ddd40b554f386..0000000000000000000000000000000000000000
--- a/spaces/kcagle/AutoGPT/autogpt/processing/html.py
+++ /dev/null
@@ -1,33 +0,0 @@
-"""HTML processing functions"""
-from __future__ import annotations
-
-from bs4 import BeautifulSoup
-from requests.compat import urljoin
-
-
-def extract_hyperlinks(soup: BeautifulSoup, base_url: str) -> list[tuple[str, str]]:
-    """Extract hyperlinks from a BeautifulSoup object
-
-    Args:
-        soup (BeautifulSoup): The BeautifulSoup object
-        base_url (str): The base URL
-
-    Returns:
-        List[Tuple[str, str]]: The extracted hyperlinks
-    """
-    return [
-        (link.text, urljoin(base_url, link["href"]))
-        for link in soup.find_all("a", href=True)
-    ]
-
-
-def format_hyperlinks(hyperlinks: list[tuple[str, str]]) -> list[str]:
-    """Format hyperlinks to be displayed to the user
-
-    Args:
-        hyperlinks (List[Tuple[str, str]]): The hyperlinks to format
-
-    Returns:
-        List[str]: The formatted hyperlinks
-    """
-    return [f"{link_text} ({link_url})" for link_text, link_url in hyperlinks]
diff --git a/spaces/kdrkdrkdr/HutaoTTS/monotonic_align/__init__.py b/spaces/kdrkdrkdr/HutaoTTS/monotonic_align/__init__.py
deleted file mode 100644
index 40b6f64aa116c74cac2f6a33444c9eeea2fdb38c..0000000000000000000000000000000000000000
--- a/spaces/kdrkdrkdr/HutaoTTS/monotonic_align/__init__.py
+++ /dev/null
@@ -1,21 +0,0 @@
-from numpy import zeros, int32, float32
-from torch import from_numpy
-
-from .core import maximum_path_jit
-
-
-def maximum_path(neg_cent, mask):
-    """ numba optimized version.
-    neg_cent: [b, t_t, t_s]
-    mask: [b, t_t, t_s]
-    """
-    device = neg_cent.device
-    dtype = neg_cent.dtype
-    neg_cent = neg_cent.data.cpu().numpy().astype(float32)
-    path = zeros(neg_cent.shape, dtype=int32)
-
-    t_t_max = mask.sum(1)[:, 0].data.cpu().numpy().astype(int32)
-    t_s_max = mask.sum(2)[:, 0].data.cpu().numpy().astype(int32)
-    maximum_path_jit(path, neg_cent, t_t_max, t_s_max)
-    return from_numpy(path).to(device=device, dtype=dtype)
-
diff --git a/spaces/keithhon/Real-Time-Voice-Cloning/encoder/data_objects/random_cycler.py b/spaces/keithhon/Real-Time-Voice-Cloning/encoder/data_objects/random_cycler.py
deleted file mode 100644
index c405db6b27f46d874d8feb37e3f9c1e12c251109..0000000000000000000000000000000000000000
--- a/spaces/keithhon/Real-Time-Voice-Cloning/encoder/data_objects/random_cycler.py
+++ /dev/null
@@ -1,37 +0,0 @@
-import random
-
-class RandomCycler:
-    """
-    Creates an internal copy of a sequence and allows access to its items in a constrained random 
-    order. For a source sequence of n items and one or several consecutive queries of a total 
-    of m items, the following guarantees hold (one implies the other):
-        - Each item will be returned between m // n and ((m - 1) // n) + 1 times.
-        - Between two appearances of the same item, there may be at most 2 * (n - 1) other items.
-    """
-    
-    def __init__(self, source):
-        if len(source) == 0:
-            raise Exception("Can't create RandomCycler from an empty collection")
-        self.all_items = list(source)
-        self.next_items = []
-    
-    def sample(self, count: int):
-        shuffle = lambda l: random.sample(l, len(l))
-        
-        out = []
-        while count > 0:
-            if count >= len(self.all_items):
-                out.extend(shuffle(list(self.all_items)))
-                count -= len(self.all_items)
-                continue
-            n = min(count, len(self.next_items))
-            out.extend(self.next_items[:n])
-            count -= n
-            self.next_items = self.next_items[n:]
-            if len(self.next_items) == 0:
-                self.next_items = shuffle(list(self.all_items))
-        return out
-    
-    def __next__(self):
-        return self.sample(1)[0]
-
diff --git a/spaces/keras-dreambooth/Dreambooth-mandelbulb-flower/app.py b/spaces/keras-dreambooth/Dreambooth-mandelbulb-flower/app.py
deleted file mode 100644
index d93c30cdae8ed72b3177f265e9bc539e4977dd47..0000000000000000000000000000000000000000
--- a/spaces/keras-dreambooth/Dreambooth-mandelbulb-flower/app.py
+++ /dev/null
@@ -1,30 +0,0 @@
-from huggingface_hub import from_pretrained_keras
-from keras_cv import models
-import gradio as gr
-
-from tensorflow import keras
-
-keras.mixed_precision.set_global_policy("mixed_float16")
-
-# prepare model
-resolution = 512
-sd_dreambooth_model = models.StableDiffusion(
-    img_width=resolution, img_height=resolution
-)
-db_diffusion_model = from_pretrained_keras("kfahn/dreambooth-mandelbulb")
-sd_dreambooth_model._diffusion_model = db_diffusion_model
-
-# generate images
-def infer(prompt):
-    generated_images = sd_dreambooth_model.text_to_image(
-        prompt, batch_size=2
-    )
-    return generated_images 
-    
-output = gr.Gallery(label="Outputs").style(grid=(1,2))
-
-# customize interface
-title = "Dreambooth Mandelbulb flower"
-description = "This is a dreambooth model fine-tuned on mandelbulb images. To try it, input the concept with {sks a hydrangea floweret shaped like a mandelbulb}."
-examples=[["sks a hydrangea floweret shaped like a mandelbulb on a bush"]]
-gr.Interface(infer, inputs=["text"], outputs=[output], title=title, description=description, examples=examples).queue().launch()
diff --git a/spaces/keras-dreambooth/living_room_dreambooth_diffusion_model/app.py b/spaces/keras-dreambooth/living_room_dreambooth_diffusion_model/app.py
deleted file mode 100644
index d8b11a9cd974af29652ac9d04394f00bc623fd25..0000000000000000000000000000000000000000
--- a/spaces/keras-dreambooth/living_room_dreambooth_diffusion_model/app.py
+++ /dev/null
@@ -1,53 +0,0 @@
-from huggingface_hub import from_pretrained_keras
-import keras_cv
-import gradio as gr
-from tensorflow import keras
-
-keras.mixed_precision.set_global_policy("mixed_float16")
-# load keras model
-resolution = 512
-dreambooth_model = keras_cv.models.StableDiffusion(
-        img_width=resolution, img_height=resolution, jit_compile=True, 
-    )
-loaded_diffusion_model = from_pretrained_keras("keras-dreambooth/living_room_dreambooth_diffusion_model")
-dreambooth_model._diffusion_model = loaded_diffusion_model
-
-
-def generate_images(prompt: str, negative_prompt:str, num_imgs_to_gen: int, num_steps: int):
-    """
-    This function is used to generate images using our fine-tuned keras dreambooth stable diffusion model.
-    Args:
-        prompt (str): The text input given by the user based on which images will be generated.
-        num_imgs_to_gen (int): The number of images to be generated using given prompt.
-        num_steps (int): The number of denoising steps
-    Returns:
-        generated_img (List): List of images that were generated using the model
-    """
-    generated_img = dreambooth_model.text_to_image(
-        prompt, 
-        negative_prompt=negative_prompt,
-        batch_size=num_imgs_to_gen,
-        num_steps=num_steps,
-    )
-   
-    return generated_img
-    
-with gr.Blocks() as demo:
-    gr.HTML("<h2 style=\"font-size: 2em; font-weight: bold\" align=\"center\">Keras Dreambooth - Living Room Demo</h2>")    
-    with gr.Row():
-        with gr.Column():
-            prompt = gr.Textbox(lines=1, value="sks living_room with maroon sofas", label="Base Prompt")
-            negative_prompt = gr.Textbox(lines=1, value="", label="Negative Prompt")
-            samples = gr.Slider(minimum=1, maximum=10, default=1, step=1, label="Number of Image")
-            num_steps = gr.Slider(label="Inference Steps",value=50)
-            run = gr.Button(value="Run")
-        with gr.Column():
-            gallery = gr.Gallery(label="Outputs").style(grid=(1,2))
-
-    run.click(generate_images, inputs=[prompt,negative_prompt, samples, num_steps], outputs=gallery)
-    
-    gr.Examples([["A phot of sks living_room with maroon sofas","", 3, 75]],
-                [prompt,negative_prompt, samples,num_steps], gallery, generate_images)
-    gr.Markdown('\n Demo created by: <a href=\"https://huggingface.co/mwitiderrick/\">Derrick Mwiti</a>')
-
-demo.launch(debug=True)
\ No newline at end of file
diff --git a/spaces/keras-io/addition-lstm/README.md b/spaces/keras-io/addition-lstm/README.md
deleted file mode 100644
index fe3fb6390d203d06a0f5124636297a07160863a5..0000000000000000000000000000000000000000
--- a/spaces/keras-io/addition-lstm/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Addition using LSTM
-emoji: ➕
-colorFrom: red
-colorTo: blue
-sdk: gradio
-sdk_version: 3.0.10
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference
diff --git a/spaces/keras-io/bidirectional_lstm_imdb/app.py b/spaces/keras-io/bidirectional_lstm_imdb/app.py
deleted file mode 100644
index b21b604c7709dd7b803d4e97627b9494275c6466..0000000000000000000000000000000000000000
--- a/spaces/keras-io/bidirectional_lstm_imdb/app.py
+++ /dev/null
@@ -1,37 +0,0 @@
-import gradio as gr
-import tensorflow as tf 
-from tensorflow.keras.preprocessing.sequence import pad_sequences
-import pickle
-from huggingface_hub import from_pretrained_keras
-import os
-os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
-
-model = from_pretrained_keras("keras-io/bidirectional-lstm-imdb")
-
-with open('tokenizer.pickle', 'rb') as file:
-    tokenizer = pickle.load(file)
-    
-def decide(text):
-  tokenized_text = tokenizer.texts_to_sequences([text])
-  padded_tokens = pad_sequences(tokenized_text, maxlen= 200)
-  result = model.predict(padded_tokens)[0][0]
-  if result >= 0.6 :
-    return "Positive review"
-  elif result <= 0.4:
-    return "Negative review"
-  else:
-    return "Neutral review"
-  
-
-  
-example_sentence_1 = "I hate the movie, they made no effort in making the movie. Waste of time!"
-example_sentence_2 = "Awesome movie! Loved the way in which the hero acted."
-examples = [[example_sentence_1], [example_sentence_2]]
-  
-description = "Write out a movie review to know the underlying sentiment."
-article = "<div style='text-align: center;'><a href='https://huggingface.co/DrishtiSharma' target='_blank'>Space by Drishti Sharma</a><br><a href='https://keras.io/examples/nlp/bidirectional_lstm_imdb/' target='_blank'>Keras example by François Chollet</a></div>"
-
-gr.Interface(decide, inputs= gr.inputs.Textbox( lines=1, placeholder=None, default="", label=None), outputs='text', examples=examples,
-             title="Sentiment analysis of movie reviews", theme = "grass", description=description, allow_flagging="auto", 
-             flagging_dir='flagging records', article = article).launch(enable_queue = True,           
-             inline=False, share = True)
diff --git a/spaces/kevinwang676/ChatGLM2-SadTalker/src/face3d/models/arcface_torch/utils/utils_callbacks.py b/spaces/kevinwang676/ChatGLM2-SadTalker/src/face3d/models/arcface_torch/utils/utils_callbacks.py
deleted file mode 100644
index bd2f56cba47c57de102710ff56eaac591e59f4da..0000000000000000000000000000000000000000
--- a/spaces/kevinwang676/ChatGLM2-SadTalker/src/face3d/models/arcface_torch/utils/utils_callbacks.py
+++ /dev/null
@@ -1,117 +0,0 @@
-import logging
-import os
-import time
-from typing import List
-
-import torch
-
-from eval import verification
-from utils.utils_logging import AverageMeter
-
-
-class CallBackVerification(object):
-    def __init__(self, frequent, rank, val_targets, rec_prefix, image_size=(112, 112)):
-        self.frequent: int = frequent
-        self.rank: int = rank
-        self.highest_acc: float = 0.0
-        self.highest_acc_list: List[float] = [0.0] * len(val_targets)
-        self.ver_list: List[object] = []
-        self.ver_name_list: List[str] = []
-        if self.rank is 0:
-            self.init_dataset(val_targets=val_targets, data_dir=rec_prefix, image_size=image_size)
-
-    def ver_test(self, backbone: torch.nn.Module, global_step: int):
-        results = []
-        for i in range(len(self.ver_list)):
-            acc1, std1, acc2, std2, xnorm, embeddings_list = verification.test(
-                self.ver_list[i], backbone, 10, 10)
-            logging.info('[%s][%d]XNorm: %f' % (self.ver_name_list[i], global_step, xnorm))
-            logging.info('[%s][%d]Accuracy-Flip: %1.5f+-%1.5f' % (self.ver_name_list[i], global_step, acc2, std2))
-            if acc2 > self.highest_acc_list[i]:
-                self.highest_acc_list[i] = acc2
-            logging.info(
-                '[%s][%d]Accuracy-Highest: %1.5f' % (self.ver_name_list[i], global_step, self.highest_acc_list[i]))
-            results.append(acc2)
-
-    def init_dataset(self, val_targets, data_dir, image_size):
-        for name in val_targets:
-            path = os.path.join(data_dir, name + ".bin")
-            if os.path.exists(path):
-                data_set = verification.load_bin(path, image_size)
-                self.ver_list.append(data_set)
-                self.ver_name_list.append(name)
-
-    def __call__(self, num_update, backbone: torch.nn.Module):
-        if self.rank is 0 and num_update > 0 and num_update % self.frequent == 0:
-            backbone.eval()
-            self.ver_test(backbone, num_update)
-            backbone.train()
-
-
-class CallBackLogging(object):
-    def __init__(self, frequent, rank, total_step, batch_size, world_size, writer=None):
-        self.frequent: int = frequent
-        self.rank: int = rank
-        self.time_start = time.time()
-        self.total_step: int = total_step
-        self.batch_size: int = batch_size
-        self.world_size: int = world_size
-        self.writer = writer
-
-        self.init = False
-        self.tic = 0
-
-    def __call__(self,
-                 global_step: int,
-                 loss: AverageMeter,
-                 epoch: int,
-                 fp16: bool,
-                 learning_rate: float,
-                 grad_scaler: torch.cuda.amp.GradScaler):
-        if self.rank == 0 and global_step > 0 and global_step % self.frequent == 0:
-            if self.init:
-                try:
-                    speed: float = self.frequent * self.batch_size / (time.time() - self.tic)
-                    speed_total = speed * self.world_size
-                except ZeroDivisionError:
-                    speed_total = float('inf')
-
-                time_now = (time.time() - self.time_start) / 3600
-                time_total = time_now / ((global_step + 1) / self.total_step)
-                time_for_end = time_total - time_now
-                if self.writer is not None:
-                    self.writer.add_scalar('time_for_end', time_for_end, global_step)
-                    self.writer.add_scalar('learning_rate', learning_rate, global_step)
-                    self.writer.add_scalar('loss', loss.avg, global_step)
-                if fp16:
-                    msg = "Speed %.2f samples/sec   Loss %.4f   LearningRate %.4f   Epoch: %d   Global Step: %d   " \
-                          "Fp16 Grad Scale: %2.f   Required: %1.f hours" % (
-                              speed_total, loss.avg, learning_rate, epoch, global_step,
-                              grad_scaler.get_scale(), time_for_end
-                          )
-                else:
-                    msg = "Speed %.2f samples/sec   Loss %.4f   LearningRate %.4f   Epoch: %d   Global Step: %d   " \
-                          "Required: %1.f hours" % (
-                              speed_total, loss.avg, learning_rate, epoch, global_step, time_for_end
-                          )
-                logging.info(msg)
-                loss.reset()
-                self.tic = time.time()
-            else:
-                self.init = True
-                self.tic = time.time()
-
-
-class CallBackModelCheckpoint(object):
-    def __init__(self, rank, output="./"):
-        self.rank: int = rank
-        self.output: str = output
-
-    def __call__(self, global_step, backbone, partial_fc, ):
-        if global_step > 100 and self.rank == 0:
-            path_module = os.path.join(self.output, "backbone.pth")
-            torch.save(backbone.module.state_dict(), path_module)
-            logging.info("Pytorch Model Saved in '{}'".format(path_module))
-
-        if global_step > 100 and partial_fc is not None:
-            partial_fc.save_params()
diff --git a/spaces/kevinwang676/M4Singer/tasks/base_task.py b/spaces/kevinwang676/M4Singer/tasks/base_task.py
deleted file mode 100644
index b74d25c85ce8a86865c5d5a09f3f92579ffb2074..0000000000000000000000000000000000000000
--- a/spaces/kevinwang676/M4Singer/tasks/base_task.py
+++ /dev/null
@@ -1,360 +0,0 @@
-import glob
-import re
-import subprocess
-from datetime import datetime
-
-import matplotlib
-
-matplotlib.use('Agg')
-
-from utils.hparams import hparams, set_hparams
-import random
-import sys
-import numpy as np
-import torch.distributed as dist
-from pytorch_lightning.loggers import TensorBoardLogger
-from utils.pl_utils import LatestModelCheckpoint, BaseTrainer, data_loader, DDP
-from torch import nn
-import torch.utils.data
-import utils
-import logging
-import os
-
-torch.multiprocessing.set_sharing_strategy(os.getenv('TORCH_SHARE_STRATEGY', 'file_system'))
-
-log_format = '%(asctime)s %(message)s'
-logging.basicConfig(stream=sys.stdout, level=logging.INFO,
-                    format=log_format, datefmt='%m/%d %I:%M:%S %p')
-
-
-class BaseDataset(torch.utils.data.Dataset):
-    def __init__(self, shuffle):
-        super().__init__()
-        self.hparams = hparams
-        self.shuffle = shuffle
-        self.sort_by_len = hparams['sort_by_len']
-        self.sizes = None
-
-    @property
-    def _sizes(self):
-        return self.sizes
-
-    def __getitem__(self, index):
-        raise NotImplementedError
-
-    def collater(self, samples):
-        raise NotImplementedError
-
-    def __len__(self):
-        return len(self._sizes)
-
-    def num_tokens(self, index):
-        return self.size(index)
-
-    def size(self, index):
-        """Return an example's size as a float or tuple. This value is used when
-        filtering a dataset with ``--max-positions``."""
-        size = min(self._sizes[index], hparams['max_frames'])
-        return size
-
-    def ordered_indices(self):
-        """Return an ordered list of indices. Batches will be constructed based
-        on this order."""
-        if self.shuffle:
-            indices = np.random.permutation(len(self))
-            if self.sort_by_len:
-                indices = indices[np.argsort(np.array(self._sizes)[indices], kind='mergesort')]
-                # 先random, 然后稳定排序, 保证排序后同长度的数据顺序是依照random permutation的 (被其随机打乱).
-        else:
-            indices = np.arange(len(self))
-        return indices
-
-    @property
-    def num_workers(self):
-        return int(os.getenv('NUM_WORKERS', hparams['ds_workers']))
-
-
-class BaseTask(nn.Module):
-    def __init__(self, *args, **kwargs):
-        # dataset configs
-        super(BaseTask, self).__init__(*args, **kwargs)
-        self.current_epoch = 0
-        self.global_step = 0
-        self.loaded_optimizer_states_dict = {}
-        self.trainer = None
-        self.logger = None
-        self.on_gpu = False
-        self.use_dp = False
-        self.use_ddp = False
-        self.example_input_array = None
-
-        self.max_tokens = hparams['max_tokens']
-        self.max_sentences = hparams['max_sentences']
-        self.max_eval_tokens = hparams['max_eval_tokens']
-        if self.max_eval_tokens == -1:
-            hparams['max_eval_tokens'] = self.max_eval_tokens = self.max_tokens
-        self.max_eval_sentences = hparams['max_eval_sentences']
-        if self.max_eval_sentences == -1:
-            hparams['max_eval_sentences'] = self.max_eval_sentences = self.max_sentences
-
-        self.model = None
-        self.training_losses_meter = None
-
-    ###########
-    # Training, validation and testing
-    ###########
-    def build_model(self):
-        raise NotImplementedError
-
-    def load_ckpt(self, ckpt_base_dir, current_model_name=None, model_name='model', force=True, strict=True):
-        # This function is updated on 2021.12.13
-        if current_model_name is None:
-            current_model_name = model_name
-        utils.load_ckpt(self.__getattr__(current_model_name), ckpt_base_dir, current_model_name, force, strict)
-
-    def on_epoch_start(self):
-        self.training_losses_meter = {'total_loss': utils.AvgrageMeter()}
-
-    def _training_step(self, sample, batch_idx, optimizer_idx):
-        """
-
-        :param sample:
-        :param batch_idx:
-        :return: total loss: torch.Tensor, loss_log: dict
-        """
-        raise NotImplementedError
-
-    def training_step(self, sample, batch_idx, optimizer_idx=-1):
-        loss_ret = self._training_step(sample, batch_idx, optimizer_idx)
-        self.opt_idx = optimizer_idx
-        if loss_ret is None:
-            return {'loss': None}
-        total_loss, log_outputs = loss_ret
-        log_outputs = utils.tensors_to_scalars(log_outputs)
-        for k, v in log_outputs.items():
-            if k not in self.training_losses_meter:
-                self.training_losses_meter[k] = utils.AvgrageMeter()
-            if not np.isnan(v):
-                self.training_losses_meter[k].update(v)
-        self.training_losses_meter['total_loss'].update(total_loss.item())
-
-        try:
-            log_outputs['lr'] = self.scheduler.get_lr()
-            if isinstance(log_outputs['lr'], list):
-                log_outputs['lr'] = log_outputs['lr'][0]
-        except:
-            pass
-
-        # log_outputs['all_loss'] = total_loss.item()
-        progress_bar_log = log_outputs
-        tb_log = {f'tr/{k}': v for k, v in log_outputs.items()}
-        return {
-            'loss': total_loss,
-            'progress_bar': progress_bar_log,
-            'log': tb_log
-        }
-
-    def optimizer_step(self, epoch, batch_idx, optimizer, optimizer_idx):
-        optimizer.step()
-        optimizer.zero_grad()
-        if self.scheduler is not None:
-            self.scheduler.step(self.global_step // hparams['accumulate_grad_batches'])
-
-    def on_epoch_end(self):
-        loss_outputs = {k: round(v.avg, 4) for k, v in self.training_losses_meter.items()}
-        print(f"\n==============\n "
-              f"Epoch {self.current_epoch} ended. Steps: {self.global_step}. {loss_outputs}"
-              f"\n==============\n")
-
-    def validation_step(self, sample, batch_idx):
-        """
-
-        :param sample:
-        :param batch_idx:
-        :return: output: dict
-        """
-        raise NotImplementedError
-
-    def _validation_end(self, outputs):
-        """
-
-        :param outputs:
-        :return: loss_output: dict
-        """
-        raise NotImplementedError
-
-    def validation_end(self, outputs):
-        loss_output = self._validation_end(outputs)
-        print(f"\n==============\n "
-              f"valid results: {loss_output}"
-              f"\n==============\n")
-        return {
-            'log': {f'val/{k}': v for k, v in loss_output.items()},
-            'val_loss': loss_output['total_loss']
-        }
-
-    def build_scheduler(self, optimizer):
-        raise NotImplementedError
-
-    def build_optimizer(self, model):
-        raise NotImplementedError
-
-    def configure_optimizers(self):
-        optm = self.build_optimizer(self.model)
-        self.scheduler = self.build_scheduler(optm)
-        return [optm]
-
-    def test_start(self):
-        pass
-
-    def test_step(self, sample, batch_idx):
-        return self.validation_step(sample, batch_idx)
-
-    def test_end(self, outputs):
-        return self.validation_end(outputs)
-
-    ###########
-    # Running configuration
-    ###########
-
-    @classmethod
-    def start(cls):
-        set_hparams()
-        os.environ['MASTER_PORT'] = str(random.randint(15000, 30000))
-        random.seed(hparams['seed'])
-        np.random.seed(hparams['seed'])
-        task = cls()
-        work_dir = hparams['work_dir']
-        trainer = BaseTrainer(checkpoint_callback=LatestModelCheckpoint(
-                                  filepath=work_dir,
-                                  verbose=True,
-                                  monitor='val_loss',
-                                  mode='min',
-                                  num_ckpt_keep=hparams['num_ckpt_keep'],
-                                  save_best=hparams['save_best'],
-                                  period=1 if hparams['save_ckpt'] else 100000
-                              ),
-                              logger=TensorBoardLogger(
-                                  save_dir=work_dir,
-                                  name='lightning_logs',
-                                  version='lastest'
-                              ),
-                              gradient_clip_val=hparams['clip_grad_norm'],
-                              val_check_interval=hparams['val_check_interval'],
-                              row_log_interval=hparams['log_interval'],
-                              max_updates=hparams['max_updates'],
-                              num_sanity_val_steps=hparams['num_sanity_val_steps'] if not hparams[
-                                  'validate'] else 10000,
-                              accumulate_grad_batches=hparams['accumulate_grad_batches'])
-        if not hparams['infer']:  # train
-            t = datetime.now().strftime('%Y%m%d%H%M%S')
-            code_dir = f'{work_dir}/codes/{t}'
-            subprocess.check_call(f'mkdir -p "{code_dir}"', shell=True)
-            for c in hparams['save_codes']:
-                subprocess.check_call(f'cp -r "{c}" "{code_dir}/"', shell=True)
-            print(f"| Copied codes to {code_dir}.")
-            trainer.checkpoint_callback.task = task
-            trainer.fit(task)
-        else:
-            trainer.test(task)
-
-    def configure_ddp(self, model, device_ids):
-        model = DDP(
-            model,
-            device_ids=device_ids,
-            find_unused_parameters=True
-        )
-        if dist.get_rank() != 0 and not hparams['debug']:
-            sys.stdout = open(os.devnull, "w")
-            sys.stderr = open(os.devnull, "w")
-        random.seed(hparams['seed'])
-        np.random.seed(hparams['seed'])
-        return model
-
-    def training_end(self, *args, **kwargs):
-        return None
-
-    def init_ddp_connection(self, proc_rank, world_size):
-        set_hparams(print_hparams=False)
-        # guarantees unique ports across jobs from same grid search
-        default_port = 12910
-        # if user gave a port number, use that one instead
-        try:
-            default_port = os.environ['MASTER_PORT']
-        except Exception:
-            os.environ['MASTER_PORT'] = str(default_port)
-
-        # figure out the root node addr
-        root_node = '127.0.0.2'
-        root_node = self.trainer.resolve_root_node_address(root_node)
-        os.environ['MASTER_ADDR'] = root_node
-        dist.init_process_group('nccl', rank=proc_rank, world_size=world_size)
-
-    @data_loader
-    def train_dataloader(self):
-        return None
-
-    @data_loader
-    def test_dataloader(self):
-        return None
-
-    @data_loader
-    def val_dataloader(self):
-        return None
-
-    def on_load_checkpoint(self, checkpoint):
-        pass
-
-    def on_save_checkpoint(self, checkpoint):
-        pass
-
-    def on_sanity_check_start(self):
-        pass
-
-    def on_train_start(self):
-        pass
-
-    def on_train_end(self):
-        pass
-
-    def on_batch_start(self, batch):
-        pass
-
-    def on_batch_end(self):
-        pass
-
-    def on_pre_performance_check(self):
-        pass
-
-    def on_post_performance_check(self):
-        pass
-
-    def on_before_zero_grad(self, optimizer):
-        pass
-
-    def on_after_backward(self):
-        pass
-
-    def backward(self, loss, optimizer):
-        loss.backward()
-
-    def grad_norm(self, norm_type):
-        results = {}
-        total_norm = 0
-        for name, p in self.named_parameters():
-            if p.requires_grad:
-                try:
-                    param_norm = p.grad.data.norm(norm_type)
-                    total_norm += param_norm ** norm_type
-                    norm = param_norm ** (1 / norm_type)
-
-                    grad = round(norm.data.cpu().numpy().flatten()[0], 3)
-                    results['grad_{}_norm_{}'.format(norm_type, name)] = grad
-                except Exception:
-                    # this param had no grad
-                    pass
-
-        total_norm = total_norm ** (1. / norm_type)
-        grad = round(total_norm.data.cpu().numpy().flatten()[0], 3)
-        results['grad_{}_norm_total'.format(norm_type)] = grad
-        return results
diff --git a/spaces/kirch/Text2Video-Zero/annotator/uniformer/mmcv/runner/priority.py b/spaces/kirch/Text2Video-Zero/annotator/uniformer/mmcv/runner/priority.py
deleted file mode 100644
index 64cc4e3a05f8d5b89ab6eb32461e6e80f1d62e67..0000000000000000000000000000000000000000
--- a/spaces/kirch/Text2Video-Zero/annotator/uniformer/mmcv/runner/priority.py
+++ /dev/null
@@ -1,60 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-from enum import Enum
-
-
-class Priority(Enum):
-    """Hook priority levels.
-
-    +--------------+------------+
-    | Level        | Value      |
-    +==============+============+
-    | HIGHEST      | 0          |
-    +--------------+------------+
-    | VERY_HIGH    | 10         |
-    +--------------+------------+
-    | HIGH         | 30         |
-    +--------------+------------+
-    | ABOVE_NORMAL | 40         |
-    +--------------+------------+
-    | NORMAL       | 50         |
-    +--------------+------------+
-    | BELOW_NORMAL | 60         |
-    +--------------+------------+
-    | LOW          | 70         |
-    +--------------+------------+
-    | VERY_LOW     | 90         |
-    +--------------+------------+
-    | LOWEST       | 100        |
-    +--------------+------------+
-    """
-
-    HIGHEST = 0
-    VERY_HIGH = 10
-    HIGH = 30
-    ABOVE_NORMAL = 40
-    NORMAL = 50
-    BELOW_NORMAL = 60
-    LOW = 70
-    VERY_LOW = 90
-    LOWEST = 100
-
-
-def get_priority(priority):
-    """Get priority value.
-
-    Args:
-        priority (int or str or :obj:`Priority`): Priority.
-
-    Returns:
-        int: The priority value.
-    """
-    if isinstance(priority, int):
-        if priority < 0 or priority > 100:
-            raise ValueError('priority must be between 0 and 100')
-        return priority
-    elif isinstance(priority, Priority):
-        return priority.value
-    elif isinstance(priority, str):
-        return Priority[priority.upper()].value
-    else:
-        raise TypeError('priority must be an integer or Priority enum value')
diff --git a/spaces/kl08/personality_detectionV2/app.py b/spaces/kl08/personality_detectionV2/app.py
deleted file mode 100644
index bd750ca5ed25fcf1698d9f4f16709957a7143872..0000000000000000000000000000000000000000
--- a/spaces/kl08/personality_detectionV2/app.py
+++ /dev/null
@@ -1,12 +0,0 @@
-import gradio as gr
-
-gr.load(
-    name="JanSt/albert-base-v2_mbti-classification",
-    src="models",
-    title="<center><a href=\"https://gtanalytics.net/\"><img src='https://gtanalytics.net/wp-content/themes/georgetown/assets/images/logo.jpg'alt='gtanalytics-logo'></a>&nbsp;&nbsp;<a href=\"https://en.wikipedia.org/wiki/Myers–Briggs_Type_Indicator/\"><img src='https://upload.wikimedia.org/wikipedia/commons/thumb/1/1f/MyersBriggsTypes.png/1920px-MyersBriggsTypes.png'alt='MBTI-Logo'></a></center><br>Personality Detection",
-    description="Georgetown Analytics and Technology is looking to build predictive AI to streamline the talent management and acquisition processes. To help them accomplish this, we have developed an app based on the Myers-Briggs Type Indicator (MBTI) dataset. Our Personality Detection app assists in quickly identifying the personality traits of potential candidates and assigning them type codes based on psychological preferences. This information is then used to determine the most suitable job roles for them. By understanding the personality traits of applicants, the app can help in the selection process of new hires and save time and resources when assessing job candidates. The Personality Detection app provides a powerful tool for talent management and acquisition. It quickly evaluates psychological preferences and provides an overview of the candidate’s traits. The app also helps to optimize the recruitment process by providing detailed insights on the suitability of a candidate for a particular job role. With Personality Detection, Georgetown Analytics and Technology will be able to quickly and easily identify the best-suited candidates for their desired job roles and optimize their entire recruitment process.",
-    article="yadi yada",
-    examples=[["""Let's focus on how we can use our talents and resources to make a positive difference -- I believe in everyone's potential to make a meaningful contribution."""], 
-              ["""Let's step back and consider the broad perspective — I'm sure we can identify the best path forward if we focus on the bigger picture."""], 
-              ["""Let's have some fun and let our imaginations run wild — I'm sure we can come up with something enjoyable if we tap into our creative energy."""]],
-).launch()
\ No newline at end of file
diff --git a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/gradio/templates/cdn/assets/Blocks-61158678.js b/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/gradio/templates/cdn/assets/Blocks-61158678.js
deleted file mode 100644
index 975373713b9cc101ebb7621f2603a6084e5dfdc3..0000000000000000000000000000000000000000
--- a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/gradio/templates/cdn/assets/Blocks-61158678.js
+++ /dev/null
@@ -1,57 +0,0 @@
-const VERSION_RE = new RegExp("3.33.1/", "g");function import_fix(mod, base) {const url =  new URL(mod, base); return import(`https://gradio.s3-us-west-2.amazonaws.com/3.33.1/${url.pathname?.startsWith('/') ? url.pathname.substring(1).replace(VERSION_RE, "") : url.pathname.replace(VERSION_RE, "")}`);}import{d as Ie,w as ct,_ as j,S as ue,i as fe,s as ce,c as bt,b as Be,a as vt,e as W,f as oe,m as Y,g as E,h as Io,j as Ao,k as Po,l as ne,t as L,n as J,o as re,p as B,q as v,r as _t,u as bn,v as Co,x as ko,y as Ve,z as Bo,A as Oo,B as Me,C as w,D as me,E as d,F as ae,G as I,H as V,I as S,J as Le,K as Z,L as Ne,M as ze,N as ve,O as Ho,P as Lo,Q as No,R as Ro,T as xo}from"./index-7c0e54a6.js";import{B as pt,a as jo}from"./Button-661a0701.js";var Mo=function(t){return Do(t)&&!Fo(t)};function Do(e){return!!e&&typeof e=="object"}function Fo(e){var t=Object.prototype.toString.call(e);return t==="[object RegExp]"||t==="[object Date]"||Vo(e)}var Go=typeof 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-import inspect
-import warnings
-from json import dumps as json_dumps
-from typing import (
-    Any,
-    AsyncIterable,
-    AsyncIterator,
-    Dict,
-    Iterable,
-    Iterator,
-    Mapping,
-    Optional,
-    Tuple,
-    Union,
-)
-from urllib.parse import urlencode
-
-from ._exceptions import StreamClosed, StreamConsumed
-from ._multipart import MultipartStream
-from ._types import (
-    AsyncByteStream,
-    RequestContent,
-    RequestData,
-    RequestFiles,
-    ResponseContent,
-    SyncByteStream,
-)
-from ._utils import peek_filelike_length, primitive_value_to_str
-
-
-class ByteStream(AsyncByteStream, SyncByteStream):
-    def __init__(self, stream: bytes) -> None:
-        self._stream = stream
-
-    def __iter__(self) -> Iterator[bytes]:
-        yield self._stream
-
-    async def __aiter__(self) -> AsyncIterator[bytes]:
-        yield self._stream
-
-
-class IteratorByteStream(SyncByteStream):
-    CHUNK_SIZE = 65_536
-
-    def __init__(self, stream: Iterable[bytes]):
-        self._stream = stream
-        self._is_stream_consumed = False
-        self._is_generator = inspect.isgenerator(stream)
-
-    def __iter__(self) -> Iterator[bytes]:
-        if self._is_stream_consumed and self._is_generator:
-            raise StreamConsumed()
-
-        self._is_stream_consumed = True
-        if hasattr(self._stream, "read"):
-            # File-like interfaces should use 'read' directly.
-            chunk = self._stream.read(self.CHUNK_SIZE)
-            while chunk:
-                yield chunk
-                chunk = self._stream.read(self.CHUNK_SIZE)
-        else:
-            # Otherwise iterate.
-            for part in self._stream:
-                yield part
-
-
-class AsyncIteratorByteStream(AsyncByteStream):
-    CHUNK_SIZE = 65_536
-
-    def __init__(self, stream: AsyncIterable[bytes]):
-        self._stream = stream
-        self._is_stream_consumed = False
-        self._is_generator = inspect.isasyncgen(stream)
-
-    async def __aiter__(self) -> AsyncIterator[bytes]:
-        if self._is_stream_consumed and self._is_generator:
-            raise StreamConsumed()
-
-        self._is_stream_consumed = True
-        if hasattr(self._stream, "aread"):
-            # File-like interfaces should use 'aread' directly.
-            chunk = await self._stream.aread(self.CHUNK_SIZE)
-            while chunk:
-                yield chunk
-                chunk = await self._stream.aread(self.CHUNK_SIZE)
-        else:
-            # Otherwise iterate.
-            async for part in self._stream:
-                yield part
-
-
-class UnattachedStream(AsyncByteStream, SyncByteStream):
-    """
-    If a request or response is serialized using pickle, then it is no longer
-    attached to a stream for I/O purposes. Any stream operations should result
-    in `httpx.StreamClosed`.
-    """
-
-    def __iter__(self) -> Iterator[bytes]:
-        raise StreamClosed()
-
-    async def __aiter__(self) -> AsyncIterator[bytes]:
-        raise StreamClosed()
-        yield b""  # pragma: no cover
-
-
-def encode_content(
-    content: Union[str, bytes, Iterable[bytes], AsyncIterable[bytes]]
-) -> Tuple[Dict[str, str], Union[SyncByteStream, AsyncByteStream]]:
-    if isinstance(content, (bytes, str)):
-        body = content.encode("utf-8") if isinstance(content, str) else content
-        content_length = len(body)
-        headers = {"Content-Length": str(content_length)} if body else {}
-        return headers, ByteStream(body)
-
-    elif isinstance(content, Iterable) and not isinstance(content, dict):
-        # `not isinstance(content, dict)` is a bit oddly specific, but it
-        # catches a case that's easy for users to make in error, and would
-        # otherwise pass through here, like any other bytes-iterable,
-        # because `dict` happens to be iterable. See issue #2491.
-        content_length_or_none = peek_filelike_length(content)
-
-        if content_length_or_none is None:
-            headers = {"Transfer-Encoding": "chunked"}
-        else:
-            headers = {"Content-Length": str(content_length_or_none)}
-        return headers, IteratorByteStream(content)  # type: ignore
-
-    elif isinstance(content, AsyncIterable):
-        headers = {"Transfer-Encoding": "chunked"}
-        return headers, AsyncIteratorByteStream(content)
-
-    raise TypeError(f"Unexpected type for 'content', {type(content)!r}")
-
-
-def encode_urlencoded_data(
-    data: RequestData,
-) -> Tuple[Dict[str, str], ByteStream]:
-    plain_data = []
-    for key, value in data.items():
-        if isinstance(value, (list, tuple)):
-            plain_data.extend([(key, primitive_value_to_str(item)) for item in value])
-        else:
-            plain_data.append((key, primitive_value_to_str(value)))
-    body = urlencode(plain_data, doseq=True).encode("utf-8")
-    content_length = str(len(body))
-    content_type = "application/x-www-form-urlencoded"
-    headers = {"Content-Length": content_length, "Content-Type": content_type}
-    return headers, ByteStream(body)
-
-
-def encode_multipart_data(
-    data: RequestData, files: RequestFiles, boundary: Optional[bytes]
-) -> Tuple[Dict[str, str], MultipartStream]:
-    multipart = MultipartStream(data=data, files=files, boundary=boundary)
-    headers = multipart.get_headers()
-    return headers, multipart
-
-
-def encode_text(text: str) -> Tuple[Dict[str, str], ByteStream]:
-    body = text.encode("utf-8")
-    content_length = str(len(body))
-    content_type = "text/plain; charset=utf-8"
-    headers = {"Content-Length": content_length, "Content-Type": content_type}
-    return headers, ByteStream(body)
-
-
-def encode_html(html: str) -> Tuple[Dict[str, str], ByteStream]:
-    body = html.encode("utf-8")
-    content_length = str(len(body))
-    content_type = "text/html; charset=utf-8"
-    headers = {"Content-Length": content_length, "Content-Type": content_type}
-    return headers, ByteStream(body)
-
-
-def encode_json(json: Any) -> Tuple[Dict[str, str], ByteStream]:
-    body = json_dumps(json).encode("utf-8")
-    content_length = str(len(body))
-    content_type = "application/json"
-    headers = {"Content-Length": content_length, "Content-Type": content_type}
-    return headers, ByteStream(body)
-
-
-def encode_request(
-    content: Optional[RequestContent] = None,
-    data: Optional[RequestData] = None,
-    files: Optional[RequestFiles] = None,
-    json: Optional[Any] = None,
-    boundary: Optional[bytes] = None,
-) -> Tuple[Dict[str, str], Union[SyncByteStream, AsyncByteStream]]:
-    """
-    Handles encoding the given `content`, `data`, `files`, and `json`,
-    returning a two-tuple of (<headers>, <stream>).
-    """
-    if data is not None and not isinstance(data, Mapping):
-        # We prefer to separate `content=<bytes|str|byte iterator|bytes aiterator>`
-        # for raw request content, and `data=<form data>` for url encoded or
-        # multipart form content.
-        #
-        # However for compat with requests, we *do* still support
-        # `data=<bytes...>` usages. We deal with that case here, treating it
-        # as if `content=<...>` had been supplied instead.
-        message = "Use 'content=<...>' to upload raw bytes/text content."
-        warnings.warn(message, DeprecationWarning)
-        return encode_content(data)
-
-    if content is not None:
-        return encode_content(content)
-    elif files:
-        return encode_multipart_data(data or {}, files, boundary)
-    elif data:
-        return encode_urlencoded_data(data)
-    elif json is not None:
-        return encode_json(json)
-
-    return {}, ByteStream(b"")
-
-
-def encode_response(
-    content: Optional[ResponseContent] = None,
-    text: Optional[str] = None,
-    html: Optional[str] = None,
-    json: Optional[Any] = None,
-) -> Tuple[Dict[str, str], Union[SyncByteStream, AsyncByteStream]]:
-    """
-    Handles encoding the given `content`, returning a two-tuple of
-    (<headers>, <stream>).
-    """
-    if content is not None:
-        return encode_content(content)
-    elif text is not None:
-        return encode_text(text)
-    elif html is not None:
-        return encode_html(html)
-    elif json is not None:
-        return encode_json(json)
-
-    return {}, ByteStream(b"")
diff --git a/spaces/leafShen/CodeFormer/CodeFormer/facelib/detection/yolov5face/utils/torch_utils.py b/spaces/leafShen/CodeFormer/CodeFormer/facelib/detection/yolov5face/utils/torch_utils.py
deleted file mode 100644
index af2d06587b2d07b2eab199a8484380fde1de5c3c..0000000000000000000000000000000000000000
--- a/spaces/leafShen/CodeFormer/CodeFormer/facelib/detection/yolov5face/utils/torch_utils.py
+++ /dev/null
@@ -1,40 +0,0 @@
-import torch
-from torch import nn
-
-
-def fuse_conv_and_bn(conv, bn):
-    # Fuse convolution and batchnorm layers https://tehnokv.com/posts/fusing-batchnorm-and-conv/
-    fusedconv = (
-        nn.Conv2d(
-            conv.in_channels,
-            conv.out_channels,
-            kernel_size=conv.kernel_size,
-            stride=conv.stride,
-            padding=conv.padding,
-            groups=conv.groups,
-            bias=True,
-        )
-        .requires_grad_(False)
-        .to(conv.weight.device)
-    )
-
-    # prepare filters
-    w_conv = conv.weight.clone().view(conv.out_channels, -1)
-    w_bn = torch.diag(bn.weight.div(torch.sqrt(bn.eps + bn.running_var)))
-    fusedconv.weight.copy_(torch.mm(w_bn, w_conv).view(fusedconv.weight.size()))
-
-    # prepare spatial bias
-    b_conv = torch.zeros(conv.weight.size(0), device=conv.weight.device) if conv.bias is None else conv.bias
-    b_bn = bn.bias - bn.weight.mul(bn.running_mean).div(torch.sqrt(bn.running_var + bn.eps))
-    fusedconv.bias.copy_(torch.mm(w_bn, b_conv.reshape(-1, 1)).reshape(-1) + b_bn)
-
-    return fusedconv
-
-
-def copy_attr(a, b, include=(), exclude=()):
-    # Copy attributes from b to a, options to only include [...] and to exclude [...]
-    for k, v in b.__dict__.items():
-        if (include and k not in include) or k.startswith("_") or k in exclude:
-            continue
-
-        setattr(a, k, v)
diff --git a/spaces/lewiswu1209/MockingBird/mkgui/base/ui/schema_utils.py b/spaces/lewiswu1209/MockingBird/mkgui/base/ui/schema_utils.py
deleted file mode 100644
index a2be43c07175f18e6f285eae5fddc5c0c2faa7aa..0000000000000000000000000000000000000000
--- a/spaces/lewiswu1209/MockingBird/mkgui/base/ui/schema_utils.py
+++ /dev/null
@@ -1,129 +0,0 @@
-from typing import Dict
-
-
-def resolve_reference(reference: str, references: Dict) -> Dict:
-    return references[reference.split("/")[-1]]
-
-
-def get_single_reference_item(property: Dict, references: Dict) -> Dict:
-    # Ref can either be directly in the properties or the first element of allOf
-    reference = property.get("$ref")
-    if reference is None:
-        reference = property["allOf"][0]["$ref"]
-    return resolve_reference(reference, references)
-
-
-def is_single_string_property(property: Dict) -> bool:
-    return property.get("type") == "string"
-
-
-def is_single_datetime_property(property: Dict) -> bool:
-    if property.get("type") != "string":
-        return False
-    return property.get("format") in ["date-time", "time", "date"]
-
-
-def is_single_boolean_property(property: Dict) -> bool:
-    return property.get("type") == "boolean"
-
-
-def is_single_number_property(property: Dict) -> bool:
-    return property.get("type") in ["integer", "number"]
-
-
-def is_single_file_property(property: Dict) -> bool:
-    if property.get("type") != "string":
-        return False
-    # TODO: binary?
-    return property.get("format") == "byte"
-
-
-def is_single_directory_property(property: Dict) -> bool:
-    if property.get("type") != "string":
-        return False
-    return property.get("format") == "path"
-
-def is_multi_enum_property(property: Dict, references: Dict) -> bool:
-    if property.get("type") != "array":
-        return False
-
-    if property.get("uniqueItems") is not True:
-        # Only relevant if it is a set or other datastructures with unique items
-        return False
-
-    try:
-        _ = resolve_reference(property["items"]["$ref"], references)["enum"]
-        return True
-    except Exception:
-        return False
-
-
-def is_single_enum_property(property: Dict, references: Dict) -> bool:
-    try:
-        _ = get_single_reference_item(property, references)["enum"]
-        return True
-    except Exception:
-        return False
-
-
-def is_single_dict_property(property: Dict) -> bool:
-    if property.get("type") != "object":
-        return False
-    return "additionalProperties" in property
-
-
-def is_single_reference(property: Dict) -> bool:
-    if property.get("type") is not None:
-        return False
-
-    return bool(property.get("$ref"))
-
-
-def is_multi_file_property(property: Dict) -> bool:
-    if property.get("type") != "array":
-        return False
-
-    if property.get("items") is None:
-        return False
-
-    try:
-        # TODO: binary
-        return property["items"]["format"] == "byte"
-    except Exception:
-        return False
-
-
-def is_single_object(property: Dict, references: Dict) -> bool:
-    try:
-        object_reference = get_single_reference_item(property, references)
-        if object_reference["type"] != "object":
-            return False
-        return "properties" in object_reference
-    except Exception:
-        return False
-
-
-def is_property_list(property: Dict) -> bool:
-    if property.get("type") != "array":
-        return False
-
-    if property.get("items") is None:
-        return False
-
-    try:
-        return property["items"]["type"] in ["string", "number", "integer"]
-    except Exception:
-        return False
-
-
-def is_object_list_property(property: Dict, references: Dict) -> bool:
-    if property.get("type") != "array":
-        return False
-
-    try:
-        object_reference = resolve_reference(property["items"]["$ref"], references)
-        if object_reference["type"] != "object":
-            return False
-        return "properties" in object_reference
-    except Exception:
-        return False
diff --git a/spaces/lewiswu1209/MockingBird/synthesizer/models/sublayer/common/batch_norm_conv.py b/spaces/lewiswu1209/MockingBird/synthesizer/models/sublayer/common/batch_norm_conv.py
deleted file mode 100644
index 0d07a4a9495657bcd434111ec0b6f16ca35211c2..0000000000000000000000000000000000000000
--- a/spaces/lewiswu1209/MockingBird/synthesizer/models/sublayer/common/batch_norm_conv.py
+++ /dev/null
@@ -1,14 +0,0 @@
-import torch.nn as nn
-import torch.nn.functional as F
-
-class BatchNormConv(nn.Module):
-    def __init__(self, in_channels, out_channels, kernel, relu=True):
-        super().__init__()
-        self.conv = nn.Conv1d(in_channels, out_channels, kernel, stride=1, padding=kernel // 2, bias=False)
-        self.bnorm = nn.BatchNorm1d(out_channels)
-        self.relu = relu
-
-    def forward(self, x):
-        x = self.conv(x)
-        x = F.relu(x) if self.relu is True else x
-        return self.bnorm(x)
\ No newline at end of file
diff --git a/spaces/lightli/bingo-newbing/postcss.config.js b/spaces/lightli/bingo-newbing/postcss.config.js
deleted file mode 100644
index 33ad091d26d8a9dc95ebdf616e217d985ec215b8..0000000000000000000000000000000000000000
--- a/spaces/lightli/bingo-newbing/postcss.config.js
+++ /dev/null
@@ -1,6 +0,0 @@
-module.exports = {
-  plugins: {
-    tailwindcss: {},
-    autoprefixer: {},
-  },
-}
diff --git a/spaces/liliyRehtina/Stable-Diffusion-XL-two/README.md b/spaces/liliyRehtina/Stable-Diffusion-XL-two/README.md
deleted file mode 100644
index 2631a606fea066168f366a0b0ea9d23ccea82bf3..0000000000000000000000000000000000000000
--- a/spaces/liliyRehtina/Stable-Diffusion-XL-two/README.md
+++ /dev/null
@@ -1,14 +0,0 @@
----
-title: Vk Stable Diffusion
-emoji: 🐢
-colorFrom: purple
-colorTo: indigo
-sdk: gradio
-sdk_version: 3.23.0
-app_file: app.py
-pinned: false
-license: mit
-duplicated_from: DmitryMakik/vk_Stable_Diffusion
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/limingcv/AlignDet/finetune/finetune_retinanet_12k_voc0712_lr1.5e-2_wd5e-5/retinanet_mstrain_12k_voc0712.py b/spaces/limingcv/AlignDet/finetune/finetune_retinanet_12k_voc0712_lr1.5e-2_wd5e-5/retinanet_mstrain_12k_voc0712.py
deleted file mode 100644
index 19fa56a294a28fb741b9e52b6641e7b2ce8fdffb..0000000000000000000000000000000000000000
--- a/spaces/limingcv/AlignDet/finetune/finetune_retinanet_12k_voc0712_lr1.5e-2_wd5e-5/retinanet_mstrain_12k_voc0712.py
+++ /dev/null
@@ -1,213 +0,0 @@
-model = dict(
-    type='RetinaNet',
-    backbone=dict(
-        type='ResNet',
-        depth=50,
-        num_stages=4,
-        out_indices=(0, 1, 2, 3),
-        frozen_stages=1,
-        norm_cfg=dict(type='SyncBN', requires_grad=True),
-        norm_eval=True,
-        style='pytorch',
-        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
-    neck=dict(
-        type='FPN',
-        in_channels=[256, 512, 1024, 2048],
-        out_channels=256,
-        start_level=1,
-        add_extra_convs='on_input',
-        num_outs=5,
-        norm_cfg=dict(type='SyncBN', requires_grad=True)),
-    bbox_head=dict(
-        type='RetinaHead',
-        num_classes=20,
-        in_channels=256,
-        stacked_convs=4,
-        feat_channels=256,
-        anchor_generator=dict(
-            type='AnchorGenerator',
-            octave_base_scale=4,
-            scales_per_octave=3,
-            ratios=[0.5, 1.0, 2.0],
-            strides=[8, 16, 32, 64, 128]),
-        bbox_coder=dict(
-            type='DeltaXYWHBBoxCoder',
-            target_means=[0.0, 0.0, 0.0, 0.0],
-            target_stds=[1.0, 1.0, 1.0, 1.0]),
-        loss_cls=dict(
-            type='FocalLoss',
-            use_sigmoid=True,
-            gamma=2.0,
-            alpha=0.25,
-            loss_weight=1.0),
-        loss_bbox=dict(type='L1Loss', loss_weight=1.0)),
-    train_cfg=dict(
-        assigner=dict(
-            type='MaxIoUAssigner',
-            pos_iou_thr=0.5,
-            neg_iou_thr=0.4,
-            min_pos_iou=0,
-            ignore_iof_thr=-1),
-        allowed_border=-1,
-        pos_weight=-1,
-        debug=False),
-    test_cfg=dict(
-        nms_pre=1000,
-        min_bbox_size=0,
-        score_thr=0.05,
-        nms=dict(type='nms', iou_threshold=0.5),
-        max_per_img=100))
-dataset_type = 'VOCDataset'
-data_root = 'data/VOCdevkit/'
-img_norm_cfg = dict(
-    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
-train_pipeline = [
-    dict(type='LoadImageFromFile'),
-    dict(type='LoadAnnotations', with_bbox=True),
-    dict(
-        type='Resize',
-        img_scale=[(1333, 480), (1333, 512), (1333, 544), (1333, 576),
-                   (1333, 608), (1333, 640), (1333, 672), (1333, 704),
-                   (1333, 736), (1333, 768), (1333, 800)],
-        multiscale_mode='value',
-        keep_ratio=True),
-    dict(type='RandomFlip', flip_ratio=0.5),
-    dict(
-        type='Normalize',
-        mean=[123.675, 116.28, 103.53],
-        std=[58.395, 57.12, 57.375],
-        to_rgb=True),
-    dict(type='Pad', size_divisor=32),
-    dict(type='DefaultFormatBundle'),
-    dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])
-]
-test_pipeline = [
-    dict(type='LoadImageFromFile'),
-    dict(
-        type='MultiScaleFlipAug',
-        img_scale=(1333, 800),
-        flip=False,
-        transforms=[
-            dict(type='Resize', keep_ratio=True),
-            dict(type='RandomFlip'),
-            dict(
-                type='Normalize',
-                mean=[123.675, 116.28, 103.53],
-                std=[58.395, 57.12, 57.375],
-                to_rgb=True),
-            dict(type='Pad', size_divisor=32),
-            dict(type='ImageToTensor', keys=['img']),
-            dict(type='Collect', keys=['img'])
-        ])
-]
-data = dict(
-    samples_per_gpu=2,
-    workers_per_gpu=2,
-    train=dict(
-        type='VOCDataset',
-        ann_file=[
-            'data/VOCdevkit/VOC2007/ImageSets/Main/trainval.txt',
-            'data/VOCdevkit/VOC2012/ImageSets/Main/trainval.txt'
-        ],
-        img_prefix=['data/VOCdevkit/VOC2007/', 'data/VOCdevkit/VOC2012/'],
-        pipeline=[
-            dict(type='LoadImageFromFile'),
-            dict(type='LoadAnnotations', with_bbox=True),
-            dict(
-                type='Resize',
-                img_scale=[(1333, 480), (1333, 512), (1333, 544), (1333, 576),
-                           (1333, 608), (1333, 640), (1333, 672), (1333, 704),
-                           (1333, 736), (1333, 768), (1333, 800)],
-                multiscale_mode='value',
-                keep_ratio=True),
-            dict(type='RandomFlip', flip_ratio=0.5),
-            dict(
-                type='Normalize',
-                mean=[123.675, 116.28, 103.53],
-                std=[58.395, 57.12, 57.375],
-                to_rgb=True),
-            dict(type='Pad', size_divisor=32),
-            dict(type='DefaultFormatBundle'),
-            dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])
-        ]),
-    val=dict(
-        type='VOCDataset',
-        ann_file='data/VOCdevkit/VOC2007/ImageSets/Main/test.txt',
-        img_prefix='data/VOCdevkit/VOC2007/',
-        pipeline=[
-            dict(type='LoadImageFromFile'),
-            dict(
-                type='MultiScaleFlipAug',
-                img_scale=(1333, 800),
-                flip=False,
-                transforms=[
-                    dict(type='Resize', keep_ratio=True),
-                    dict(type='RandomFlip'),
-                    dict(
-                        type='Normalize',
-                        mean=[123.675, 116.28, 103.53],
-                        std=[58.395, 57.12, 57.375],
-                        to_rgb=True),
-                    dict(type='Pad', size_divisor=32),
-                    dict(type='ImageToTensor', keys=['img']),
-                    dict(type='Collect', keys=['img'])
-                ])
-        ]),
-    test=dict(
-        type='VOCDataset',
-        ann_file='data/VOCdevkit/VOC2007/ImageSets/Main/test.txt',
-        img_prefix='data/VOCdevkit/VOC2007/',
-        pipeline=[
-            dict(type='LoadImageFromFile'),
-            dict(
-                type='MultiScaleFlipAug',
-                img_scale=(1333, 800),
-                flip=False,
-                transforms=[
-                    dict(type='Resize', keep_ratio=True),
-                    dict(type='RandomFlip'),
-                    dict(
-                        type='Normalize',
-                        mean=[123.675, 116.28, 103.53],
-                        std=[58.395, 57.12, 57.375],
-                        to_rgb=True),
-                    dict(type='Pad', size_divisor=32),
-                    dict(type='ImageToTensor', keys=['img']),
-                    dict(type='Collect', keys=['img'])
-                ])
-        ]))
-evaluation = dict(interval=12000, metric='mAP', save_best='auto')
-optimizer = dict(type='SGD', lr=0.015, momentum=0.9, weight_decay=5e-05)
-optimizer_config = dict(grad_clip=None)
-lr_config = dict(
-    policy='step',
-    warmup='linear',
-    warmup_iters=500,
-    warmup_ratio=0.001,
-    step=[9000, 11000],
-    by_epoch=False)
-runner = dict(type='IterBasedRunner', max_iters=12000)
-checkpoint_config = dict(interval=12000)
-log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook')])
-custom_hooks = [
-    dict(type='NumClassCheckHook'),
-    dict(
-        type='MMDetWandbHook',
-        init_kwargs=dict(project='I2B', group='finetune'),
-        interval=50,
-        num_eval_images=0,
-        log_checkpoint=False)
-]
-dist_params = dict(backend='nccl')
-log_level = 'INFO'
-load_from = 'pretrain/selfsup_retinanet_mstrain-soft-teacher_sampler-2048_temp0.5/final_model.pth'
-resume_from = None
-workflow = [('train', 1)]
-opencv_num_threads = 0
-mp_start_method = 'fork'
-auto_scale_lr = dict(enable=False, base_batch_size=16)
-custom_imports = None
-norm_cfg = dict(type='SyncBN', requires_grad=True)
-work_dir = 'work_dirs/finetune_retinanet_12k_voc0712_lr1.5e-2_wd5e-5'
-auto_resume = False
-gpu_ids = range(0, 8)
diff --git a/spaces/lincquiQcaudo/Top-20-Diffusion/MD5 Checksum Verifier 5.2 Serial Key Keygen [UPD].md b/spaces/lincquiQcaudo/Top-20-Diffusion/MD5 Checksum Verifier 5.2 Serial Key Keygen [UPD].md
deleted file mode 100644
index 07081fb92ab3a8c7901824b0cb1709f5ae81e9cd..0000000000000000000000000000000000000000
--- a/spaces/lincquiQcaudo/Top-20-Diffusion/MD5 Checksum Verifier 5.2 Serial Key Keygen [UPD].md	
+++ /dev/null
@@ -1,13 +0,0 @@
-<h2>MD5 Checksum Verifier 5.2 Serial Key keygen</h2><br /><p><b><b>Download Zip</b> &rarr; <a href="https://bytlly.com/2uGxKK">https://bytlly.com/2uGxKK</a></b></p><br /><br />
-
-. dolphin and nand generator, nand dolphin wiimmfi, nand dolphin dump error, . MD5 Checksum Verifier 5.2 Serial key keygen martin show Designer 6 Crack zip . Key generator for avast premier 2013.
-Key generator for avast premier 2013.
-You can try downloading this file to your computer and verify our words.
-In this video: How to find out the serial number of the computer, find out the Windows key, and how to find out the serial number of the printer and scanner.
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-Key generator for avast premier 2013: .
-How to find your computer's serial number, find your Windows key, and how to find your printer and scanner product key. . 8a78ff9644<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/lincquiQcaudo/Top-20-Diffusion/Mbot 1 2b Cracker.md b/spaces/lincquiQcaudo/Top-20-Diffusion/Mbot 1 2b Cracker.md
deleted file mode 100644
index 325ba1885f8287f6ea1a3a904cbfad812e92802d..0000000000000000000000000000000000000000
--- a/spaces/lincquiQcaudo/Top-20-Diffusion/Mbot 1 2b Cracker.md	
+++ /dev/null
@@ -1,7 +0,0 @@
-
-<p>the mbot isn't going to like being put on the shelf, but it is not capable of moving around. it is therefore recommended that you assemble your mbot on a flat surface that is at least the size of the slide-out platform.</p>
-<p> it's worth remembering that the old mbots were just the figments of a scientist who was also the father of the technology, and it's reasonable to assume that the technology that allows for the superior performance of the mbots is also the technology that is stored on m-bot. are the holograms on mbot from this father, but with the figments' tech altered to fit the mbot's setting, so that it's the superior technology, and the figments are the ones who adapted the figments' tech to fit the new setting? (again, there's a lot of unanswered questions, and that's not to say that we can't have good reasons for thinking that certain parts of m-bot are figment in origin. just that we don't have very solid proof that all of m-bot is from the figments)<br /> vapor: </p>
-<h2>Mbot 1 2b Cracker</h2><br /><p><b><b>Download Zip</b> &#10004; <a href="https://bytlly.com/2uGwlf">https://bytlly.com/2uGwlf</a></b></p><br /><br />
-<p>mymnvashivathosesk trello.com</a&gt>>trello.com</a&gt> ;heinuggercoumn </a&gt> ; free download real madrid cf kit 2011.rarbfdcm autoplay.menu.designer.3.6 with serial latest<br> trello.com </a&gt> ; keys to open end users guide for the dual band 801 n wifi network card.rarbfdcm<br> trello.com </a&gt> ; mbot 1 2b cracker </a&gt> ; vibration motors, mbot 2.2 (2.3 beta).6 with serial latest</a&gt> ; trello for trello.com </a&gt> ; toto and the birds (original motion picture soundtrack).rarbfdcm</a&gt> ; tato and the birds (original motion picture soundtrack).rarbfdcm</a&gt> ; tatto and the birds (original motion picture soundtrack).rarbfdcm</a&gt> ; trello for trello.com </a&gt> ; mbot 2.2 update 2 tato and the birds (original motion picture soundtrack).rarbfdcm</a&gt> ;</p> 899543212b<br />
-<br />
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\ No newline at end of file
diff --git a/spaces/llmonitor/benchmarks/run/together_cleaner.py b/spaces/llmonitor/benchmarks/run/together_cleaner.py
deleted file mode 100644
index 6c79e2cf24cb1ab2fc9ce3c78c0e40073a0bea15..0000000000000000000000000000000000000000
--- a/spaces/llmonitor/benchmarks/run/together_cleaner.py
+++ /dev/null
@@ -1,42 +0,0 @@
-# This cleans up the results from the together API by removing the stop tokens, for some reason the API doesn't do this itself.
-
-import psycopg2
-import psycopg2.extras
-import psycopg2.pool 
-import os
-
-from dotenv import load_dotenv
-load_dotenv()
-
-# Connect to database
-PG_URI = os.environ.get("POSTGRES_URL")
-conn = psycopg2.connect(PG_URI)
-cur = conn.cursor()
-
-# Execute the SQL query
-cur.execute("SELECT result FROM results INNER JOIN models ON results.model = models.id WHERE models.api = 'together'")
-
-# Fetch all the rows
-rows = cur.fetchall()
-
-str_array = ["<human>", "<human>:", "</bot>", "</s>", "<|end|>", "<|endoftext|>", "```\n```", "\nUser"]
-
-
-
-for row in rows:
-    for string in str_array:
-        if string in row[0]:
-            print("Found string: " + string)
-            # Find the index of the string
-            index = row[0].index(string)
-            # Remove the string and everything after it
-            new_result = row[0][:index].strip()
-            # Update the result in the database
-            print('===============================')
-            print("Old result:" + row[0])
-            print("New result:" + new_result)
-
-            cur.execute("UPDATE results SET result = %s WHERE result = %s", (new_result, row[0]))
-
-conn.commit()
-conn.close()
\ No newline at end of file
diff --git a/spaces/lukestanley/streaming_chat_with_gpt-3.5-turbo_using_langchain_sorta/README.md b/spaces/lukestanley/streaming_chat_with_gpt-3.5-turbo_using_langchain_sorta/README.md
deleted file mode 100644
index 774fd4b69353d275b8053e87658b773e1f19f6bd..0000000000000000000000000000000000000000
--- a/spaces/lukestanley/streaming_chat_with_gpt-3.5-turbo_using_langchain_sorta/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Streaming Chat With Gpt-3.5-turbo Using Langchain Sorta
-emoji: 📚
-colorFrom: purple
-colorTo: purple
-sdk: gradio
-sdk_version: 3.19.1
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/lychees/Stable-Diffusion-ControlNet-WebUI/diffusion_webui/diffusion_models/controlnet/controlnet_mlsd.py b/spaces/lychees/Stable-Diffusion-ControlNet-WebUI/diffusion_webui/diffusion_models/controlnet/controlnet_mlsd.py
deleted file mode 100644
index 6c5a33557e1792f7b977818460e112cc7acc03cc..0000000000000000000000000000000000000000
--- a/spaces/lychees/Stable-Diffusion-ControlNet-WebUI/diffusion_webui/diffusion_models/controlnet/controlnet_mlsd.py
+++ /dev/null
@@ -1,173 +0,0 @@
-import gradio as gr
-import torch
-from controlnet_aux import MLSDdetector
-from diffusers import ControlNetModel, StableDiffusionControlNetPipeline
-from PIL import Image
-
-from diffusion_webui.utils.model_list import stable_model_list
-from diffusion_webui.utils.scheduler_list import (
-    SCHEDULER_LIST,
-    get_scheduler_list,
-)
-
-
-class StableDiffusionControlNetMLSDGenerator:
-    def __init__(self):
-        self.pipe = None
-
-    def load_model(self, stable_model_path, controlnet_model_path, scheduler):
-        if self.pipe is None:
-            controlnet = ControlNetModel.from_pretrained(
-                controlnet_model_path, torch_dtype=torch.float16
-            )
-
-            self.pipe = StableDiffusionControlNetPipeline.from_pretrained(
-                pretrained_model_name_or_path=stable_model_path,
-                controlnet=controlnet,
-                safety_checker=None,
-                torch_dtype=torch.float16,
-            )
-
-        self.pipe = get_scheduler_list(pipe=self.pipe, scheduler=scheduler)
-        self.pipe.to("cuda")
-        self.pipe.enable_xformers_memory_efficient_attention()
-
-        return self.pipe
-
-    def controlnet_mlsd(self, image_path: str):
-        mlsd = MLSDdetector.from_pretrained("lllyasviel/ControlNet")
-
-        image = Image.open(image_path)
-        image = mlsd(image)
-
-        return image
-
-    def generate_image(
-        self,
-        image_path: str,
-        model_path: str,
-        prompt: str,
-        negative_prompt: str,
-        num_images_per_prompt: int,
-        guidance_scale: int,
-        num_inference_step: int,
-        scheduler: str,
-        seed_generator: int,
-    ):
-        image = self.controlnet_mlsd(image_path=image_path)
-
-        pipe = self.load_model(
-            stable_model_path=model_path,
-            controlnet_model_path="lllyasviel/sd-controlnet-mlsd",
-            scheduler=scheduler,
-        )
-
-        if seed_generator == 0:
-            random_seed = torch.randint(0, 1000000, (1,))
-            generator = torch.manual_seed(random_seed)
-        else:
-            generator = torch.manual_seed(seed_generator)
-
-        output = pipe(
-            prompt=prompt,
-            image=image,
-            negative_prompt=negative_prompt,
-            num_images_per_prompt=num_images_per_prompt,
-            num_inference_steps=num_inference_step,
-            guidance_scale=guidance_scale,
-            generator=generator,
-        ).images
-
-        return output
-
-    def app():
-        with gr.Blocks():
-            with gr.Row():
-                with gr.Column():
-                    controlnet_mlsd_image_file = gr.Image(
-                        type="filepath", label="Image"
-                    )
-
-                    controlnet_mlsd_prompt = gr.Textbox(
-                        lines=1,
-                        show_label=False,
-                        placeholder="Prompt",
-                    )
-
-                    controlnet_mlsd_negative_prompt = gr.Textbox(
-                        lines=1,
-                        show_label=False,
-                        placeholder="Negative Prompt",
-                    )
-
-                    with gr.Row():
-                        with gr.Column():
-                            controlnet_mlsd_model_id = gr.Dropdown(
-                                choices=stable_model_list,
-                                value=stable_model_list[0],
-                                label="Stable Model Id",
-                            )
-                            controlnet_mlsd_guidance_scale = gr.Slider(
-                                minimum=0.1,
-                                maximum=15,
-                                step=0.1,
-                                value=7.5,
-                                label="Guidance Scale",
-                            )
-                            controlnet_mlsd_num_inference_step = gr.Slider(
-                                minimum=1,
-                                maximum=100,
-                                step=1,
-                                value=50,
-                                label="Num Inference Step",
-                            )
-
-                        with gr.Row():
-                            with gr.Column():
-                                controlnet_mlsd_scheduler = gr.Dropdown(
-                                    choices=SCHEDULER_LIST,
-                                    value=SCHEDULER_LIST[0],
-                                    label="Scheduler",
-                                )
-
-                                controlnet_mlsd_seed_generator = gr.Slider(
-                                    minimum=0,
-                                    maximum=1000000,
-                                    step=1,
-                                    value=0,
-                                    label="Seed Generator",
-                                )
-                                controlnet_mlsd_num_images_per_prompt = (
-                                    gr.Slider(
-                                        minimum=1,
-                                        maximum=10,
-                                        step=1,
-                                        value=1,
-                                        label="Number Of Images",
-                                    )
-                                )
-
-                    controlnet_mlsd_predict = gr.Button(value="Generator")
-
-                with gr.Column():
-                    output_image = gr.Gallery(
-                        label="Generated images",
-                        show_label=False,
-                        elem_id="gallery",
-                    ).style(grid=(1, 2))
-
-            controlnet_mlsd_predict.click(
-                fn=StableDiffusionControlNetMLSDGenerator().generate_image,
-                inputs=[
-                    controlnet_mlsd_image_file,
-                    controlnet_mlsd_model_id,
-                    controlnet_mlsd_prompt,
-                    controlnet_mlsd_negative_prompt,
-                    controlnet_mlsd_num_images_per_prompt,
-                    controlnet_mlsd_guidance_scale,
-                    controlnet_mlsd_num_inference_step,
-                    controlnet_mlsd_scheduler,
-                    controlnet_mlsd_seed_generator,
-                ],
-                outputs=output_image,
-            )
diff --git a/spaces/manavisrani07/gradio-lipsync-wav2lip/basicsr/utils/logger.py b/spaces/manavisrani07/gradio-lipsync-wav2lip/basicsr/utils/logger.py
deleted file mode 100644
index 73553dc664781a061737e94880ea1c6788c09043..0000000000000000000000000000000000000000
--- a/spaces/manavisrani07/gradio-lipsync-wav2lip/basicsr/utils/logger.py
+++ /dev/null
@@ -1,213 +0,0 @@
-import datetime
-import logging
-import time
-
-from .dist_util import get_dist_info, master_only
-
-initialized_logger = {}
-
-
-class AvgTimer():
-
-    def __init__(self, window=200):
-        self.window = window  # average window
-        self.current_time = 0
-        self.total_time = 0
-        self.count = 0
-        self.avg_time = 0
-        self.start()
-
-    def start(self):
-        self.start_time = self.tic = time.time()
-
-    def record(self):
-        self.count += 1
-        self.toc = time.time()
-        self.current_time = self.toc - self.tic
-        self.total_time += self.current_time
-        # calculate average time
-        self.avg_time = self.total_time / self.count
-
-        # reset
-        if self.count > self.window:
-            self.count = 0
-            self.total_time = 0
-
-        self.tic = time.time()
-
-    def get_current_time(self):
-        return self.current_time
-
-    def get_avg_time(self):
-        return self.avg_time
-
-
-class MessageLogger():
-    """Message logger for printing.
-
-    Args:
-        opt (dict): Config. It contains the following keys:
-            name (str): Exp name.
-            logger (dict): Contains 'print_freq' (str) for logger interval.
-            train (dict): Contains 'total_iter' (int) for total iters.
-            use_tb_logger (bool): Use tensorboard logger.
-        start_iter (int): Start iter. Default: 1.
-        tb_logger (obj:`tb_logger`): Tensorboard logger. Default： None.
-    """
-
-    def __init__(self, opt, start_iter=1, tb_logger=None):
-        self.exp_name = opt['name']
-        self.interval = opt['logger']['print_freq']
-        self.start_iter = start_iter
-        self.max_iters = opt['train']['total_iter']
-        self.use_tb_logger = opt['logger']['use_tb_logger']
-        self.tb_logger = tb_logger
-        self.start_time = time.time()
-        self.logger = get_root_logger()
-
-    def reset_start_time(self):
-        self.start_time = time.time()
-
-    @master_only
-    def __call__(self, log_vars):
-        """Format logging message.
-
-        Args:
-            log_vars (dict): It contains the following keys:
-                epoch (int): Epoch number.
-                iter (int): Current iter.
-                lrs (list): List for learning rates.
-
-                time (float): Iter time.
-                data_time (float): Data time for each iter.
-        """
-        # epoch, iter, learning rates
-        epoch = log_vars.pop('epoch')
-        current_iter = log_vars.pop('iter')
-        lrs = log_vars.pop('lrs')
-
-        message = (f'[{self.exp_name[:5]}..][epoch:{epoch:3d}, iter:{current_iter:8,d}, lr:(')
-        for v in lrs:
-            message += f'{v:.3e},'
-        message += ')] '
-
-        # time and estimated time
-        if 'time' in log_vars.keys():
-            iter_time = log_vars.pop('time')
-            data_time = log_vars.pop('data_time')
-
-            total_time = time.time() - self.start_time
-            time_sec_avg = total_time / (current_iter - self.start_iter + 1)
-            eta_sec = time_sec_avg * (self.max_iters - current_iter - 1)
-            eta_str = str(datetime.timedelta(seconds=int(eta_sec)))
-            message += f'[eta: {eta_str}, '
-            message += f'time (data): {iter_time:.3f} ({data_time:.3f})] '
-
-        # other items, especially losses
-        for k, v in log_vars.items():
-            message += f'{k}: {v:.4e} '
-            # tensorboard logger
-            if self.use_tb_logger and 'debug' not in self.exp_name:
-                if k.startswith('l_'):
-                    self.tb_logger.add_scalar(f'losses/{k}', v, current_iter)
-                else:
-                    self.tb_logger.add_scalar(k, v, current_iter)
-        self.logger.info(message)
-
-
-@master_only
-def init_tb_logger(log_dir):
-    from torch.utils.tensorboard import SummaryWriter
-    tb_logger = SummaryWriter(log_dir=log_dir)
-    return tb_logger
-
-
-@master_only
-def init_wandb_logger(opt):
-    """We now only use wandb to sync tensorboard log."""
-    import wandb
-    logger = get_root_logger()
-
-    project = opt['logger']['wandb']['project']
-    resume_id = opt['logger']['wandb'].get('resume_id')
-    if resume_id:
-        wandb_id = resume_id
-        resume = 'allow'
-        logger.warning(f'Resume wandb logger with id={wandb_id}.')
-    else:
-        wandb_id = wandb.util.generate_id()
-        resume = 'never'
-
-    wandb.init(id=wandb_id, resume=resume, name=opt['name'], config=opt, project=project, sync_tensorboard=True)
-
-    logger.info(f'Use wandb logger with id={wandb_id}; project={project}.')
-
-
-def get_root_logger(logger_name='basicsr', log_level=logging.INFO, log_file=None):
-    """Get the root logger.
-
-    The logger will be initialized if it has not been initialized. By default a
-    StreamHandler will be added. If `log_file` is specified, a FileHandler will
-    also be added.
-
-    Args:
-        logger_name (str): root logger name. Default: 'basicsr'.
-        log_file (str | None): The log filename. If specified, a FileHandler
-            will be added to the root logger.
-        log_level (int): The root logger level. Note that only the process of
-            rank 0 is affected, while other processes will set the level to
-            "Error" and be silent most of the time.
-
-    Returns:
-        logging.Logger: The root logger.
-    """
-    logger = logging.getLogger(logger_name)
-    # if the logger has been initialized, just return it
-    if logger_name in initialized_logger:
-        return logger
-
-    format_str = '%(asctime)s %(levelname)s: %(message)s'
-    stream_handler = logging.StreamHandler()
-    stream_handler.setFormatter(logging.Formatter(format_str))
-    logger.addHandler(stream_handler)
-    logger.propagate = False
-    rank, _ = get_dist_info()
-    if rank != 0:
-        logger.setLevel('ERROR')
-    elif log_file is not None:
-        logger.setLevel(log_level)
-        # add file handler
-        file_handler = logging.FileHandler(log_file, 'w')
-        file_handler.setFormatter(logging.Formatter(format_str))
-        file_handler.setLevel(log_level)
-        logger.addHandler(file_handler)
-    initialized_logger[logger_name] = True
-    return logger
-
-
-def get_env_info():
-    """Get environment information.
-
-    Currently, only log the software version.
-    """
-    import torch
-    import torchvision
-
-    from basicsr.version import __version__
-    msg = r"""
-                ____                _       _____  ____
-               / __ ) ____ _ _____ (_)_____/ ___/ / __ \
-              / __  |/ __ `// ___// // ___/\__ \ / /_/ /
-             / /_/ // /_/ /(__  )/ // /__ ___/ // _, _/
-            /_____/ \__,_//____//_/ \___//____//_/ |_|
-     ______                   __   __                 __      __
-    / ____/____   ____   ____/ /  / /   __  __ _____ / /__   / /
-   / / __ / __ \ / __ \ / __  /  / /   / / / // ___// //_/  / /
-  / /_/ // /_/ // /_/ // /_/ /  / /___/ /_/ // /__ / /<    /_/
-  \____/ \____/ \____/ \____/  /_____/\____/ \___//_/|_|  (_)
-    """
-    msg += ('\nVersion Information: '
-            f'\n\tBasicSR: {__version__}'
-            f'\n\tPyTorch: {torch.__version__}'
-            f'\n\tTorchVision: {torchvision.__version__}')
-    return msg
diff --git a/spaces/mangiucugna/self-retrospective-generator/app.py b/spaces/mangiucugna/self-retrospective-generator/app.py
deleted file mode 100644
index a15344acfc030dda81092fd4bf6cceaa21d8a740..0000000000000000000000000000000000000000
--- a/spaces/mangiucugna/self-retrospective-generator/app.py
+++ /dev/null
@@ -1,223 +0,0 @@
-from typing import Tuple, cast
-import os
-import gradio as gr
-import openai
-from openai.openai_object import OpenAIObject
-from json_repair import repair_json
-
-# Check if .env file exists
-# If it exists, load the environment variables from it
-# This is because the .env isn't present in production
-if os.path.exists(".env"):
-    from dotenv import load_dotenv
-
-    load_dotenv()
-
-openai.api_key = os.environ["OPENAI_API_KEY"]
-
-
-def send_to_llm(
-    goals_set_for_this_period: str,
-    achievements: str,
-    missed_opportunities: str,
-    future_plans: str,
-    job_title: str,
-    company_template: str,
-) -> Tuple[str, str, str]:
-    MODEL = "gpt-3.5-turbo"
-
-    system_message = """
-You are an expert in helping other people write their self-assessment for the formal company appraisal.
-Your job is to use the notes written by the human to create a long and detailed self-assessment.
-You will respond by using manage_llm_output.
-
-To write the self-assessment use the following rules:
-- If a company template is present, use it to structure the output
-- The self-assessment should be ready to be inserted in an HR system like workday
-- Be honest and critical of your work
-- Find a good balance between highlighting your achievements and recognizing areas of growth
-- Be specific and precise so your manager understands exactly what you've accomplished
-- Stay positive, even if you didn't hit a goal. Frame it as an opportunity for growth rather than a failure
-- No blame. Never blame anybody but point out how the overall system should be improved
-- List examples and measurable achievements
-- Use SMART goals to show exactly what you're planning to accomplish by the next review period
-- Tone should be professional but not too formal
-Tip: Always call manage_llm_output to provided to answer back, unless you find an error and have a follow up question"""
-
-    human_message = """
-These are my notes:
-```
-    Goals set for this period: {goals_set_for_this_period}
-    Achievements: {achievements}
-    Missed opportunities: {missed_opportunities}
-    Plans for the future: {future_plans}
-    Job title: {job_title}
-    Company Template (if available): {company_template}
-```
-Tip: Make sure to answer using manage_llm_output
-""".format(
-        goals_set_for_this_period=goals_set_for_this_period or "No goals set",
-        achievements=achievements or "Nothing",
-        missed_opportunities=missed_opportunities or "Nothing",
-        future_plans=future_plans or "Nothing",
-        job_title=job_title or "No formal job title",
-        company_template=company_template
-        or "If no company template is available use this template: # General remarks (2 paragraphs) # Achievements (5 paragraphs) # Opportunities for improvement (5 paragraphs) # Action items (3 paragraphs) # Conclusions (1 paragraph)",
-    )
-
-    manage_llm_output_definition = [
-        {
-            "name": "manage_llm_output",
-            "description": "Manage the output sent from the AI",
-            "parameters": {
-                "type": "object",
-                "properties": {
-                    "self_assessment": {
-                        "type": "string",
-                        "description": "The self-assessment",
-                    },
-                    "internal_monologue": {
-                        "type": "string",
-                        "description": "What did you think of the notes, and why you wrote what you wrote",
-                    },
-                    "confidence": {
-                        "type": "string",
-                        "enum": [
-                            "5 - This is extremely factual",
-                            "4 - This is probably factual",
-                            "3 - This is 50% factual and 50% made up",
-                            "2 - I am afraid that this might be made up",
-                            "1 - This is all a lie",
-                        ],
-                        "description": "How much you are confident that this self-assessment is factual and not made up",
-                    },
-                },
-                "required": [
-                    "self_assessment",
-                    "internal_monologue",
-                    "confidence",
-                ],
-            },
-        }
-    ]
-
-    chat_response = openai.ChatCompletion.create(
-        model=MODEL,
-        messages=[
-            {"role": "system", "content": system_message},
-            {"role": "user", "content": human_message},
-        ],
-        functions=manage_llm_output_definition,
-        temperature=0.5,
-    )
-    # This is to fix the typer errors, makes it nicer to work with although is not required
-    chat_response = cast(OpenAIObject, chat_response)
-
-    self_assessment = ""
-    internal_monologue = ""
-    confidence = ""
-
-    first_response = chat_response.choices[0]
-    message = first_response.message
-    self_assessment = message.content
-    if first_response.finish_reason == "function_call":
-        if message.function_call.name == "manage_llm_output":
-            # manage_llm_output isn't a real function, it's a trick to force the LLM to structure the output
-            args = repair_json(message.function_call.arguments, return_objects=True)
-            if type(args) is dict:
-                self_assessment = (args.get("self_assessment") or "").replace(
-                    "\\n", "\n"
-                )
-                confidence = (args.get("confidence") or "").replace("\\n", "\n")
-                internal_monologue = (args.get("internal_monologue") or "").replace(
-                    "\\n", "\n"
-                )
-
-    return (self_assessment, confidence, internal_monologue)
-
-
-with gr.Blocks() as demo:
-    gr.HTML(
-        "<h1>Create your self-retrospective in one click</h1><h3>We are all tired of writing self-retrospectives, let AI help you</h3>"
-    )
-    gr.HTML(
-        "<b>Warning: Please for the love of god do not use the output of this tool verbatim!</b> Consider this project a way to jumpstart your self-retrospective, especially for people that hate the process, but not the complete solution."
-    )
-    job_title = gr.Textbox(
-        label="Your role",
-        placeholder="e.g. Senior Software Engineer, Marketing Manager, Junior Product Owner",
-        interactive=True,
-    )
-    template = gr.TextArea(
-        label="Insert here your company template for self-retrospectives (if you have one)",
-        placeholder="optional",
-        interactive=True,
-    )
-    goals = gr.TextArea(
-        label="Insert here the goal set for this review period",
-        placeholder="Use a bullet list",
-        interactive=True,
-    )
-    achievements = gr.TextArea(
-        label="Your achievements for this review period",
-        placeholder="A bullet list of specific, measurable achievements",
-        interactive=True,
-    )
-    opportunities = gr.TextArea(
-        label="In hindsight, what could you have done better?",
-        placeholder="Still a bullet list",
-        interactive=True,
-    )
-    future = gr.TextArea(
-        label="What are you planning to do in the next months?",
-        placeholder="Again a bullet list",
-        interactive=True,
-    )
-    submit_button = gr.Button("Send")
-    self_retro = gr.TextArea(
-        label="Your self retrospective",
-    )
-    confidence = gr.Textbox(
-        label="How factual this text is",
-    )
-    internal_monologue = gr.TextArea(
-        label="What the AI is thinking",
-    )
-    gr.Examples(
-        label="Example personas",
-        examples=[
-            [
-                "Software Developer",
-                "- What are the 3 most important achievements of this quarter?\n- What could have gone better?\n- Goals for the next quarter",
-                "- Reduce the API response time by 50%\n- Improve your communication",
-                "I save the ass of this team man, the PO keeps fucking us up",
-                "Nothing",
-                "I should be promoted",
-            ],
-            [
-                "Marketing Manager",
-                "",
-                "",
-                "- The changes made on the way our campaigns are run, generated an extra 50 qualified leads when compared to the previous quarter - Improve communication between Marketing and Sales\n- Hired 5 marketing specialists and onboarded them with minimum disruption",
-                "- Although we got more leads, I feel that the it took too long to organize and execute the plan.\n- Hiring was very tiring and I think we could have been more effective in organizing the pipeline, especially with recruitment",
-                "- I will focus on learning more about Generative AI and how that affects programmatic marketing\n- I will run a retrospective about the project changes to understand what we could improve",
-            ],
-            [
-                "Software Developer",
-                "- What are the 3 most important achievements of this quarter?\n- What could have gone better? - Goals for the next quarter",
-                "- Reduce the API response time by 50%\n- Improve your communication",
-                "I save the ass of this team man, the PO keeps fucking us up",
-                "Nothing",
-                "I should be promoted",
-            ],
-        ],
-        inputs=[job_title, template, goals, achievements, opportunities, future],
-    )
-    submit_button.click(
-        send_to_llm,
-        [goals, achievements, opportunities, future, job_title, template],
-        [self_retro, confidence, internal_monologue],
-    )
-
-if __name__ == "__main__":
-    demo.launch()
diff --git a/spaces/manhkhanhUIT/Image_Restoration_Colorization/Face_Enhancement/models/networks/sync_batchnorm/comm.py b/spaces/manhkhanhUIT/Image_Restoration_Colorization/Face_Enhancement/models/networks/sync_batchnorm/comm.py
deleted file mode 100644
index 922f8c4a3adaa9b32fdcaef09583be03b0d7eb2b..0000000000000000000000000000000000000000
--- a/spaces/manhkhanhUIT/Image_Restoration_Colorization/Face_Enhancement/models/networks/sync_batchnorm/comm.py
+++ /dev/null
@@ -1,137 +0,0 @@
-# -*- coding: utf-8 -*-
-# File   : comm.py
-# Author : Jiayuan Mao
-# Email  : maojiayuan@gmail.com
-# Date   : 27/01/2018
-# 
-# This file is part of Synchronized-BatchNorm-PyTorch.
-# https://github.com/vacancy/Synchronized-BatchNorm-PyTorch
-# Distributed under MIT License.
-
-import queue
-import collections
-import threading
-
-__all__ = ['FutureResult', 'SlavePipe', 'SyncMaster']
-
-
-class FutureResult(object):
-    """A thread-safe future implementation. Used only as one-to-one pipe."""
-
-    def __init__(self):
-        self._result = None
-        self._lock = threading.Lock()
-        self._cond = threading.Condition(self._lock)
-
-    def put(self, result):
-        with self._lock:
-            assert self._result is None, 'Previous result has\'t been fetched.'
-            self._result = result
-            self._cond.notify()
-
-    def get(self):
-        with self._lock:
-            if self._result is None:
-                self._cond.wait()
-
-            res = self._result
-            self._result = None
-            return res
-
-
-_MasterRegistry = collections.namedtuple('MasterRegistry', ['result'])
-_SlavePipeBase = collections.namedtuple('_SlavePipeBase', ['identifier', 'queue', 'result'])
-
-
-class SlavePipe(_SlavePipeBase):
-    """Pipe for master-slave communication."""
-
-    def run_slave(self, msg):
-        self.queue.put((self.identifier, msg))
-        ret = self.result.get()
-        self.queue.put(True)
-        return ret
-
-
-class SyncMaster(object):
-    """An abstract `SyncMaster` object.
-
-    - During the replication, as the data parallel will trigger an callback of each module, all slave devices should
-    call `register(id)` and obtain an `SlavePipe` to communicate with the master.
-    - During the forward pass, master device invokes `run_master`, all messages from slave devices will be collected,
-    and passed to a registered callback.
-    - After receiving the messages, the master device should gather the information and determine to message passed
-    back to each slave devices.
-    """
-
-    def __init__(self, master_callback):
-        """
-
-        Args:
-            master_callback: a callback to be invoked after having collected messages from slave devices.
-        """
-        self._master_callback = master_callback
-        self._queue = queue.Queue()
-        self._registry = collections.OrderedDict()
-        self._activated = False
-
-    def __getstate__(self):
-        return {'master_callback': self._master_callback}
-
-    def __setstate__(self, state):
-        self.__init__(state['master_callback'])
-
-    def register_slave(self, identifier):
-        """
-        Register an slave device.
-
-        Args:
-            identifier: an identifier, usually is the device id.
-
-        Returns: a `SlavePipe` object which can be used to communicate with the master device.
-
-        """
-        if self._activated:
-            assert self._queue.empty(), 'Queue is not clean before next initialization.'
-            self._activated = False
-            self._registry.clear()
-        future = FutureResult()
-        self._registry[identifier] = _MasterRegistry(future)
-        return SlavePipe(identifier, self._queue, future)
-
-    def run_master(self, master_msg):
-        """
-        Main entry for the master device in each forward pass.
-        The messages were first collected from each devices (including the master device), and then
-        an callback will be invoked to compute the message to be sent back to each devices
-        (including the master device).
-
-        Args:
-            master_msg: the message that the master want to send to itself. This will be placed as the first
-            message when calling `master_callback`. For detailed usage, see `_SynchronizedBatchNorm` for an example.
-
-        Returns: the message to be sent back to the master device.
-
-        """
-        self._activated = True
-
-        intermediates = [(0, master_msg)]
-        for i in range(self.nr_slaves):
-            intermediates.append(self._queue.get())
-
-        results = self._master_callback(intermediates)
-        assert results[0][0] == 0, 'The first result should belongs to the master.'
-
-        for i, res in results:
-            if i == 0:
-                continue
-            self._registry[i].result.put(res)
-
-        for i in range(self.nr_slaves):
-            assert self._queue.get() is True
-
-        return results[0][1]
-
-    @property
-    def nr_slaves(self):
-        return len(self._registry)
diff --git a/spaces/marker22/Bark-Voice-Cloning/bark/generation.py b/spaces/marker22/Bark-Voice-Cloning/bark/generation.py
deleted file mode 100644
index ad474d770235c7b665218e64699fb0b0b1b8cc3f..0000000000000000000000000000000000000000
--- a/spaces/marker22/Bark-Voice-Cloning/bark/generation.py
+++ /dev/null
@@ -1,864 +0,0 @@
-import contextlib
-import gc
-import os
-import re
-import requests
-import gc
-import sys
-
-from encodec import EncodecModel
-import funcy
-import logging
-import numpy as np
-from scipy.special import softmax
-import torch
-import torch.nn.functional as F
-import tqdm
-from transformers import BertTokenizer
-from huggingface_hub import hf_hub_download, hf_hub_url
-
-from .model import GPTConfig, GPT
-from .model_fine import FineGPT, FineGPTConfig
-from .settings import initenv
-
-initenv(sys.argv)
-global_force_cpu = os.environ.get("BARK_FORCE_CPU", False)
-if (
-    global_force_cpu != True and
-    torch.cuda.is_available() and
-    hasattr(torch.cuda, "amp") and
-    hasattr(torch.cuda.amp, "autocast") and
-    hasattr(torch.cuda, "is_bf16_supported") and
-    torch.cuda.is_bf16_supported()
-):
-    autocast = funcy.partial(torch.cuda.amp.autocast, dtype=torch.bfloat16)
-else:
-    @contextlib.contextmanager
-    def autocast():
-        yield
-
-
-# hold models in global scope to lazy load
-global models
-models = {}
-
-global models_devices
-models_devices = {}
-
-
-CONTEXT_WINDOW_SIZE = 1024
-
-SEMANTIC_RATE_HZ = 49.9
-SEMANTIC_VOCAB_SIZE = 10_000
-
-CODEBOOK_SIZE = 1024
-N_COARSE_CODEBOOKS = 2
-N_FINE_CODEBOOKS = 8
-COARSE_RATE_HZ = 75
-
-SAMPLE_RATE = 24_000
-
-
-SUPPORTED_LANGS = [
-    ("English", "en"),
-    ("German", "de"),
-    ("Spanish", "es"),
-    ("French", "fr"),
-    ("Hindi", "hi"),
-    ("Italian", "it"),
-    ("Japanese", "ja"),
-    ("Korean", "ko"),
-    ("Polish", "pl"),
-    ("Portuguese", "pt"),
-    ("Russian", "ru"),
-    ("Turkish", "tr"),
-    ("Chinese", "zh"),
-]
-
-ALLOWED_PROMPTS = {"announcer"}
-for _, lang in SUPPORTED_LANGS:
-    for prefix in ("", f"v2{os.path.sep}"):
-        for n in range(10):
-            ALLOWED_PROMPTS.add(f"{prefix}{lang}_speaker_{n}")
-
-
-logger = logging.getLogger(__name__)
-
-
-CUR_PATH = os.path.dirname(os.path.abspath(__file__))
-
-
-#default_cache_dir = os.path.join(os.path.expanduser("~"), ".cache")
-#CACHE_DIR = os.path.join(os.getenv("XDG_CACHE_HOME", default_cache_dir), "suno", "bark_v0")
-#CACHE_DIR = os.path.join(os.getcwd(), "models"
-CACHE_DIR = "./models"
-
-
-def _cast_bool_env_var(s):
-    return s.lower() in ('true', '1', 't')
-
-USE_SMALL_MODELS = _cast_bool_env_var(os.environ.get("SUNO_USE_SMALL_MODELS", "False"))
-GLOBAL_ENABLE_MPS = _cast_bool_env_var(os.environ.get("SUNO_ENABLE_MPS", "False"))
-OFFLOAD_CPU = _cast_bool_env_var(os.environ.get("SUNO_OFFLOAD_CPU", "False"))
-
-REMOTE_MODEL_PATHS = {
-    "text_small": {
-        "repo_id": "suno/bark",
-        "file_name": "text.pt",
-    },
-    "coarse_small": {
-        "repo_id": "suno/bark",
-        "file_name": "coarse.pt",
-    },
-    "fine_small": {
-        "repo_id": "suno/bark",
-        "file_name": "fine.pt",
-    },
-    "text": {
-        "repo_id": "suno/bark",
-        "file_name": "text_2.pt",
-    },
-    "coarse": {
-        "repo_id": "suno/bark",
-        "file_name": "coarse_2.pt",
-    },
-    "fine": {
-        "repo_id": "suno/bark",
-        "file_name": "fine_2.pt",
-    },
-}
-
-
-if not hasattr(torch.nn.functional, 'scaled_dot_product_attention') and torch.cuda.is_available():
-    logger.warning(
-        "torch version does not support flash attention. You will get faster" +
-        " inference speed by upgrade torch to newest nightly version."
-    )
-
-
-def grab_best_device(use_gpu=True):
-    if torch.cuda.device_count() > 0 and use_gpu:
-        device = "cuda"
-    elif torch.backends.mps.is_available() and use_gpu and GLOBAL_ENABLE_MPS:
-        device = "mps"
-    else:
-        device = "cpu"
-    return device
-
-
-def _get_ckpt_path(model_type, use_small=False):
-    key = model_type
-    if use_small or USE_SMALL_MODELS:
-        key += "_small"
-    return os.path.join(CACHE_DIR, REMOTE_MODEL_PATHS[key]["file_name"])
-
-"""
-def _download(from_hf_path, file_name, destfilename):
-    os.makedirs(CACHE_DIR, exist_ok=True)
-    hf_hub_download(repo_id=from_hf_path, filename=file_name, local_dir=CACHE_DIR, local_dir_use_symlinks=False)
-    # Bug in original repo? Downloaded name differs from expected...
-    if not os.path.exists(destfilename):
-        localname = os.path.join(CACHE_DIR, file_name)
-        os.rename(localname, destfilename)
-"""
-def _download(from_hf_path, file_name):
-    os.makedirs(CACHE_DIR, exist_ok=True)
-    hf_hub_download(repo_id=from_hf_path, filename=file_name, local_dir=CACHE_DIR)
-
-
-class InferenceContext:
-    def __init__(self, benchmark=False):
-        # we can't expect inputs to be the same length, so disable benchmarking by default
-        self._chosen_cudnn_benchmark = benchmark
-        self._cudnn_benchmark = None
-
-    def __enter__(self):
-        self._cudnn_benchmark = torch.backends.cudnn.benchmark
-        torch.backends.cudnn.benchmark = self._chosen_cudnn_benchmark
-
-    def __exit__(self, exc_type, exc_value, exc_traceback):
-        torch.backends.cudnn.benchmark = self._cudnn_benchmark
-
-
-if torch.cuda.is_available():
-    torch.backends.cuda.matmul.allow_tf32 = True
-    torch.backends.cudnn.allow_tf32 = True
-
-
-@contextlib.contextmanager
-def _inference_mode():
-    with InferenceContext(), torch.inference_mode(), torch.no_grad(), autocast():
-        yield
-
-
-def _clear_cuda_cache():
-    if torch.cuda.is_available():
-        torch.cuda.empty_cache()
-        torch.cuda.synchronize()
-
-
-def clean_models(model_key=None):
-    global models
-    model_keys = [model_key] if model_key is not None else models.keys()
-    for k in model_keys:
-        if k in models:
-            del models[k]
-    _clear_cuda_cache()
-    gc.collect()
-
-
-def _load_model(ckpt_path, device, use_small=False, model_type="text"):
-    if model_type == "text":
-        ConfigClass = GPTConfig
-        ModelClass = GPT
-    elif model_type == "coarse":
-        ConfigClass = GPTConfig
-        ModelClass = GPT
-    elif model_type == "fine":
-        ConfigClass = FineGPTConfig
-        ModelClass = FineGPT
-    else:
-        raise NotImplementedError()
-
-    # Force-remove Models to allow running on >12Gb GPU
-    # CF: Probably not needed anymore
-    #global models
-    #models.clear()
-    #gc.collect()
-    #torch.cuda.empty_cache()
-    # to here...
-
-    model_key = f"{model_type}_small" if use_small or USE_SMALL_MODELS else model_type
-    model_info = REMOTE_MODEL_PATHS[model_key]
-    if not os.path.exists(ckpt_path):
-        logger.info(f"{model_type} model not found, downloading into `{CACHE_DIR}`.")
-        ## added next two lines to make it super clear which model is being downloaded
-        remote_filename = hf_hub_url(model_info["repo_id"], model_info["file_name"])
-        print(f"Downloading {model_key} {model_info['repo_id']} remote model file {remote_filename} {model_info['file_name']} to {CACHE_DIR}")
-        _download(model_info["repo_id"], model_info["file_name"])
-        # add next line to make it super clear which model is being loaded
-    print(f"Loading {model_key} model from {ckpt_path} to {device}") # added
-    checkpoint = torch.load(ckpt_path, map_location=device)
-    # this is a hack
-    model_args = checkpoint["model_args"]
-    if "input_vocab_size" not in model_args:
-        model_args["input_vocab_size"] = model_args["vocab_size"]
-        model_args["output_vocab_size"] = model_args["vocab_size"]
-        del model_args["vocab_size"]
-    gptconf = ConfigClass(**checkpoint["model_args"])
-    model = ModelClass(gptconf)
-    state_dict = checkpoint["model"]
-    # fixup checkpoint
-    unwanted_prefix = "_orig_mod."
-    for k, v in list(state_dict.items()):
-        if k.startswith(unwanted_prefix):
-            state_dict[k[len(unwanted_prefix) :]] = state_dict.pop(k)
-    extra_keys = set(state_dict.keys()) - set(model.state_dict().keys())
-    extra_keys = set([k for k in extra_keys if not k.endswith(".attn.bias")])
-    missing_keys = set(model.state_dict().keys()) - set(state_dict.keys())
-    missing_keys = set([k for k in missing_keys if not k.endswith(".attn.bias")])
-    if len(extra_keys) != 0:
-        raise ValueError(f"extra keys found: {extra_keys}")
-    if len(missing_keys) != 0:
-        raise ValueError(f"missing keys: {missing_keys}")
-    model.load_state_dict(state_dict, strict=False)
-    n_params = model.get_num_params()
-    val_loss = checkpoint["best_val_loss"].item()
-    logger.info(f"model loaded: {round(n_params/1e6,1)}M params, {round(val_loss,3)} loss")
-    model.eval()
-    model.to(device)
-    del checkpoint, state_dict
-    _clear_cuda_cache()
-    if model_type == "text":
-        tokenizer = BertTokenizer.from_pretrained("bert-base-multilingual-cased")
-        return {
-            "model": model,
-            "tokenizer": tokenizer,
-        }
-    return model
-
-
-def _load_codec_model(device):
-    model = EncodecModel.encodec_model_24khz()
-    model.set_target_bandwidth(6.0)
-    model.eval()
-    model.to(device)
-    _clear_cuda_cache()
-    return model
-
-
-def load_model(use_gpu=True, use_small=False, force_reload=False, model_type="text"):
-    _load_model_f = funcy.partial(_load_model, model_type=model_type, use_small=use_small)
-    if model_type not in ("text", "coarse", "fine"):
-        raise NotImplementedError()
-    global models
-    global models_devices
-    device = grab_best_device(use_gpu=use_gpu)
-    model_key = f"{model_type}"
-    if OFFLOAD_CPU:
-        models_devices[model_key] = device
-        device = "cpu"
-    if model_key not in models or force_reload:
-        ckpt_path = _get_ckpt_path(model_type, use_small=use_small)
-        clean_models(model_key=model_key)
-        model = _load_model_f(ckpt_path, device)
-        models[model_key] = model
-    if model_type == "text":
-        models[model_key]["model"].to(device)
-    else:
-        models[model_key].to(device)
-    return models[model_key]
-
-
-def load_codec_model(use_gpu=True, force_reload=False):
-    global models
-    global models_devices
-    device = grab_best_device(use_gpu=use_gpu)
-    if device == "mps":
-        # encodec doesn't support mps
-        device = "cpu"
-    model_key = "codec"
-    if OFFLOAD_CPU:
-        models_devices[model_key] = device
-        device = "cpu"
-    if model_key not in models or force_reload:
-        clean_models(model_key=model_key)
-        model = _load_codec_model(device)
-        models[model_key] = model
-    models[model_key].to(device)
-    return models[model_key]
-
-
-def preload_models(
-    text_use_gpu=True,
-    text_use_small=False,
-    coarse_use_gpu=True,
-    coarse_use_small=False,
-    fine_use_gpu=True,
-    fine_use_small=False,
-    codec_use_gpu=True,
-    force_reload=False
-):
-    """Load all the necessary models for the pipeline."""
-    if grab_best_device() == "cpu" and (
-        text_use_gpu or coarse_use_gpu or fine_use_gpu or codec_use_gpu
-    ):
-        logger.warning("No GPU being used. Careful, inference might be very slow!")
-    _ = load_model(
-        model_type="text", use_gpu=text_use_gpu, use_small=text_use_small, force_reload=force_reload
-    )
-    _ = load_model(
-        model_type="coarse",
-        use_gpu=coarse_use_gpu,
-        use_small=coarse_use_small,
-        force_reload=force_reload,
-    )
-    _ = load_model(
-        model_type="fine", use_gpu=fine_use_gpu, use_small=fine_use_small, force_reload=force_reload
-    )
-    _ = load_codec_model(use_gpu=codec_use_gpu, force_reload=force_reload)
-
-
-####
-# Generation Functionality
-####
-
-
-def _tokenize(tokenizer, text):
-    return tokenizer.encode(text, add_special_tokens=False)
-
-
-def _detokenize(tokenizer, enc_text):
-    return tokenizer.decode(enc_text)
-
-
-def _normalize_whitespace(text):
-    return re.sub(r"\s+", " ", text).strip()
-
-
-TEXT_ENCODING_OFFSET = 10_048
-SEMANTIC_PAD_TOKEN = 10_000
-TEXT_PAD_TOKEN = 129_595
-SEMANTIC_INFER_TOKEN = 129_599
-
-
-def _load_history_prompt(history_prompt_input):
-    if isinstance(history_prompt_input, str) and history_prompt_input.endswith(".npz"):
-        history_prompt = np.load(history_prompt_input)
-    elif isinstance(history_prompt_input, str):
-        # make sure this works on non-ubuntu
-        history_prompt_input = os.path.join(*history_prompt_input.split("/"))
-#        if history_prompt_input not in ALLOWED_PROMPTS:
-#            raise ValueError("history prompt not found")
-        history_prompt = np.load(
-            os.path.join(CUR_PATH, "assets", "prompts", f"{history_prompt_input}.npz")
-        )
-    elif isinstance(history_prompt_input, dict):
-        assert("semantic_prompt" in history_prompt_input)
-        assert("coarse_prompt" in history_prompt_input)
-        assert("fine_prompt" in history_prompt_input)
-        history_prompt = history_prompt_input
-    else:
-        raise ValueError("history prompt format unrecognized")
-    return history_prompt
-
-
-def generate_text_semantic(
-    text,
-    history_prompt=None,
-    temp=0.7,
-    top_k=None,
-    top_p=None,
-    silent=False,
-    min_eos_p=0.2,
-    max_gen_duration_s=None,
-    allow_early_stop=True,
-    use_kv_caching=False,
-):
-    """Generate semantic tokens from text."""
-    assert isinstance(text, str)
-    text = _normalize_whitespace(text)
-    assert len(text.strip()) > 0
-    if history_prompt is not None:
-        history_prompt = _load_history_prompt(history_prompt)
-        semantic_history = history_prompt["semantic_prompt"]
-        assert (
-            isinstance(semantic_history, np.ndarray)
-            and len(semantic_history.shape) == 1
-            and len(semantic_history) > 0
-            and semantic_history.min() >= 0
-            and semantic_history.max() <= SEMANTIC_VOCAB_SIZE - 1
-        )
-    else:
-        semantic_history = None
-    # load models if not yet exist
-    global models
-    global models_devices
-    if "text" not in models:
-        preload_models()
-    model_container = models["text"]
-    model = model_container["model"]
-    tokenizer = model_container["tokenizer"]
-    encoded_text = np.array(_tokenize(tokenizer, text)) + TEXT_ENCODING_OFFSET
-    if OFFLOAD_CPU:
-        model.to(models_devices["text"])
-    device = next(model.parameters()).device
-    if len(encoded_text) > 256:
-        p = round((len(encoded_text) - 256) / len(encoded_text) * 100, 1)
-        logger.warning(f"warning, text too long, lopping of last {p}%")
-        encoded_text = encoded_text[:256]
-    encoded_text = np.pad(
-        encoded_text,
-        (0, 256 - len(encoded_text)),
-        constant_values=TEXT_PAD_TOKEN,
-        mode="constant",
-    )
-    if semantic_history is not None:
-        semantic_history = semantic_history.astype(np.int64)
-        # lop off if history is too long, pad if needed
-        semantic_history = semantic_history[-256:]
-        semantic_history = np.pad(
-            semantic_history,
-            (0, 256 - len(semantic_history)),
-            constant_values=SEMANTIC_PAD_TOKEN,
-            mode="constant",
-        )
-    else:
-        semantic_history = np.array([SEMANTIC_PAD_TOKEN] * 256)
-    x = torch.from_numpy(
-        np.hstack([
-            encoded_text, semantic_history, np.array([SEMANTIC_INFER_TOKEN])
-        ]).astype(np.int64)
-    )[None]
-    assert x.shape[1] == 256 + 256 + 1
-    with _inference_mode():
-        x = x.to(device)
-        n_tot_steps = 768
-        # custom tqdm updates since we don't know when eos will occur
-        pbar = tqdm.tqdm(disable=silent, total=100)
-        pbar_state = 0
-        tot_generated_duration_s = 0
-        kv_cache = None
-        for n in range(n_tot_steps):
-            if use_kv_caching and kv_cache is not None:
-                x_input = x[:, [-1]]
-            else:
-                x_input = x
-            logits, kv_cache = model(
-                x_input, merge_context=True, use_cache=use_kv_caching, past_kv=kv_cache
-            )
-            relevant_logits = logits[0, 0, :SEMANTIC_VOCAB_SIZE]
-            if allow_early_stop:
-                relevant_logits = torch.hstack(
-                    (relevant_logits, logits[0, 0, [SEMANTIC_PAD_TOKEN]])  # eos
-                )
-            if top_p is not None:
-                # faster to convert to numpy
-                original_device = relevant_logits.device
-                relevant_logits = relevant_logits.detach().cpu().type(torch.float32).numpy()
-                sorted_indices = np.argsort(relevant_logits)[::-1]
-                sorted_logits = relevant_logits[sorted_indices]
-                cumulative_probs = np.cumsum(softmax(sorted_logits))
-                sorted_indices_to_remove = cumulative_probs > top_p
-                sorted_indices_to_remove[1:] = sorted_indices_to_remove[:-1].copy()
-                sorted_indices_to_remove[0] = False
-                relevant_logits[sorted_indices[sorted_indices_to_remove]] = -np.inf
-                relevant_logits = torch.from_numpy(relevant_logits)
-                relevant_logits = relevant_logits.to(original_device)
-            if top_k is not None:
-                v, _ = torch.topk(relevant_logits, min(top_k, relevant_logits.size(-1)))
-                relevant_logits[relevant_logits < v[-1]] = -float("Inf")
-            probs = F.softmax(relevant_logits / temp, dim=-1)
-            # multinomial bugged on mps: shuttle to cpu if necessary
-            inf_device = probs.device
-            if probs.device.type == "mps":
-                probs = probs.to("cpu")
-            item_next = torch.multinomial(probs, num_samples=1)
-            probs = probs.to(inf_device)
-            item_next = item_next.to(inf_device)
-            if allow_early_stop and (
-                item_next == SEMANTIC_VOCAB_SIZE
-                or (min_eos_p is not None and probs[-1] >= min_eos_p)
-            ):
-                # eos found, so break
-                pbar.update(100 - pbar_state)
-                break
-            x = torch.cat((x, item_next[None]), dim=1)
-            tot_generated_duration_s += 1 / SEMANTIC_RATE_HZ
-            if max_gen_duration_s is not None and tot_generated_duration_s > max_gen_duration_s:
-                pbar.update(100 - pbar_state)
-                break
-            if n == n_tot_steps - 1:
-                pbar.update(100 - pbar_state)
-                break
-            del logits, relevant_logits, probs, item_next
-            req_pbar_state = np.min([100, int(round(100 * n / n_tot_steps))])
-            if req_pbar_state > pbar_state:
-                pbar.update(req_pbar_state - pbar_state)
-            pbar_state = req_pbar_state
-        pbar.close()
-        out = x.detach().cpu().numpy().squeeze()[256 + 256 + 1 :]
-    if OFFLOAD_CPU:
-        model.to("cpu")
-    assert all(0 <= out) and all(out < SEMANTIC_VOCAB_SIZE)
-    _clear_cuda_cache()
-    return out
-
-
-def _flatten_codebooks(arr, offset_size=CODEBOOK_SIZE):
-    assert len(arr.shape) == 2
-    arr = arr.copy()
-    if offset_size is not None:
-        for n in range(1, arr.shape[0]):
-            arr[n, :] += offset_size * n
-    flat_arr = arr.ravel("F")
-    return flat_arr
-
-
-COARSE_SEMANTIC_PAD_TOKEN = 12_048
-COARSE_INFER_TOKEN = 12_050
-
-
-def generate_coarse(
-    x_semantic,
-    history_prompt=None,
-    temp=0.7,
-    top_k=None,
-    top_p=None,
-    silent=False,
-    max_coarse_history=630,  # min 60 (faster), max 630 (more context)
-    sliding_window_len=60,
-    use_kv_caching=False,
-):
-    """Generate coarse audio codes from semantic tokens."""
-# CF: Uncommented because it breaks swap voice more than once
-#    assert (
-#        isinstance(x_semantic, np.ndarray)
-#        and len(x_semantic.shape) == 1
-#        and len(x_semantic) > 0
-#        and x_semantic.min() >= 0
-#        and x_semantic.max() <= SEMANTIC_VOCAB_SIZE - 1
-#    )
-    assert 60 <= max_coarse_history <= 630
-    assert max_coarse_history + sliding_window_len <= 1024 - 256
-    semantic_to_coarse_ratio = COARSE_RATE_HZ / SEMANTIC_RATE_HZ * N_COARSE_CODEBOOKS
-    max_semantic_history = int(np.floor(max_coarse_history / semantic_to_coarse_ratio))
-    if history_prompt is not None:
-        history_prompt = _load_history_prompt(history_prompt)
-        x_semantic_history = history_prompt["semantic_prompt"]
-        x_coarse_history = history_prompt["coarse_prompt"]
-        assert (
-            isinstance(x_semantic_history, np.ndarray)
-            and len(x_semantic_history.shape) == 1
-            and len(x_semantic_history) > 0
-            and x_semantic_history.min() >= 0
-            and x_semantic_history.max() <= SEMANTIC_VOCAB_SIZE - 1
-            and isinstance(x_coarse_history, np.ndarray)
-            and len(x_coarse_history.shape) == 2
-            and x_coarse_history.shape[0] == N_COARSE_CODEBOOKS
-            and x_coarse_history.shape[-1] >= 0
-            and x_coarse_history.min() >= 0
-            and x_coarse_history.max() <= CODEBOOK_SIZE - 1
-            #and (
-            #    round(x_coarse_history.shape[-1] / len(x_semantic_history), 1)
-            #    == round(semantic_to_coarse_ratio / N_COARSE_CODEBOOKS, 1)
-            #)
-        )
-        x_coarse_history = _flatten_codebooks(x_coarse_history) + SEMANTIC_VOCAB_SIZE
-        # trim histories correctly
-        n_semantic_hist_provided = np.min(
-            [
-                max_semantic_history,
-                len(x_semantic_history) - len(x_semantic_history) % 2,
-                int(np.floor(len(x_coarse_history) / semantic_to_coarse_ratio)),
-            ]
-        )
-        n_coarse_hist_provided = int(round(n_semantic_hist_provided * semantic_to_coarse_ratio))
-        x_semantic_history = x_semantic_history[-n_semantic_hist_provided:].astype(np.int32)
-        x_coarse_history = x_coarse_history[-n_coarse_hist_provided:].astype(np.int32)
-        # TODO: bit of a hack for time alignment (sounds better)
-        x_coarse_history = x_coarse_history[:-2]
-    else:
-        x_semantic_history = np.array([], dtype=np.int32)
-        x_coarse_history = np.array([], dtype=np.int32)
-    # load models if not yet exist
-    global models
-    global models_devices
-    if "coarse" not in models:
-        preload_models()
-    model = models["coarse"]
-    if OFFLOAD_CPU:
-        model.to(models_devices["coarse"])
-    device = next(model.parameters()).device
-    # start loop
-    n_steps = int(
-        round(
-            np.floor(len(x_semantic) * semantic_to_coarse_ratio / N_COARSE_CODEBOOKS)
-            * N_COARSE_CODEBOOKS
-        )
-    )
-    assert n_steps > 0 and n_steps % N_COARSE_CODEBOOKS == 0
-    x_semantic = np.hstack([x_semantic_history, x_semantic]).astype(np.int32)
-    x_coarse = x_coarse_history.astype(np.int32)
-    base_semantic_idx = len(x_semantic_history)
-    with _inference_mode():
-        x_semantic_in = torch.from_numpy(x_semantic)[None].to(device)
-        x_coarse_in = torch.from_numpy(x_coarse)[None].to(device)
-        n_window_steps = int(np.ceil(n_steps / sliding_window_len))
-        n_step = 0
-        for _ in tqdm.tqdm(range(n_window_steps), total=n_window_steps, disable=silent):
-            semantic_idx = base_semantic_idx + int(round(n_step / semantic_to_coarse_ratio))
-            # pad from right side
-            x_in = x_semantic_in[:, np.max([0, semantic_idx - max_semantic_history]) :]
-            x_in = x_in[:, :256]
-            x_in = F.pad(
-                x_in,
-                (0, 256 - x_in.shape[-1]),
-                "constant",
-                COARSE_SEMANTIC_PAD_TOKEN,
-            )
-            x_in = torch.hstack(
-                [
-                    x_in,
-                    torch.tensor([COARSE_INFER_TOKEN])[None].to(device),
-                    x_coarse_in[:, -max_coarse_history:],
-                ]
-            )
-            kv_cache = None
-            for _ in range(sliding_window_len):
-                if n_step >= n_steps:
-                    continue
-                is_major_step = n_step % N_COARSE_CODEBOOKS == 0
-
-                if use_kv_caching and kv_cache is not None:
-                    x_input = x_in[:, [-1]]
-                else:
-                    x_input = x_in
-
-                logits, kv_cache = model(x_input, use_cache=use_kv_caching, past_kv=kv_cache)
-                logit_start_idx = (
-                    SEMANTIC_VOCAB_SIZE + (1 - int(is_major_step)) * CODEBOOK_SIZE
-                )
-                logit_end_idx = (
-                    SEMANTIC_VOCAB_SIZE + (2 - int(is_major_step)) * CODEBOOK_SIZE
-                )
-                relevant_logits = logits[0, 0, logit_start_idx:logit_end_idx]
-                if top_p is not None:
-                    # faster to convert to numpy
-                    original_device = relevant_logits.device
-                    relevant_logits = relevant_logits.detach().cpu().type(torch.float32).numpy()
-                    sorted_indices = np.argsort(relevant_logits)[::-1]
-                    sorted_logits = relevant_logits[sorted_indices]
-                    cumulative_probs = np.cumsum(softmax(sorted_logits))
-                    sorted_indices_to_remove = cumulative_probs > top_p
-                    sorted_indices_to_remove[1:] = sorted_indices_to_remove[:-1].copy()
-                    sorted_indices_to_remove[0] = False
-                    relevant_logits[sorted_indices[sorted_indices_to_remove]] = -np.inf
-                    relevant_logits = torch.from_numpy(relevant_logits)
-                    relevant_logits = relevant_logits.to(original_device)
-                if top_k is not None:
-                    v, _ = torch.topk(relevant_logits, min(top_k, relevant_logits.size(-1)))
-                    relevant_logits[relevant_logits < v[-1]] = -float("Inf")
-                probs = F.softmax(relevant_logits / temp, dim=-1)
-                # multinomial bugged on mps: shuttle to cpu if necessary
-                inf_device = probs.device
-                if probs.device.type == "mps":
-                    probs = probs.to("cpu")
-                item_next = torch.multinomial(probs, num_samples=1)
-                probs = probs.to(inf_device)
-                item_next = item_next.to(inf_device)
-                item_next += logit_start_idx
-                x_coarse_in = torch.cat((x_coarse_in, item_next[None]), dim=1)
-                x_in = torch.cat((x_in, item_next[None]), dim=1)
-                del logits, relevant_logits, probs, item_next
-                n_step += 1
-            del x_in
-        del x_semantic_in
-    if OFFLOAD_CPU:
-        model.to("cpu")
-    gen_coarse_arr = x_coarse_in.detach().cpu().numpy().squeeze()[len(x_coarse_history) :]
-    del x_coarse_in
-    assert len(gen_coarse_arr) == n_steps
-    gen_coarse_audio_arr = gen_coarse_arr.reshape(-1, N_COARSE_CODEBOOKS).T - SEMANTIC_VOCAB_SIZE
-    for n in range(1, N_COARSE_CODEBOOKS):
-        gen_coarse_audio_arr[n, :] -= n * CODEBOOK_SIZE
-    _clear_cuda_cache()
-    return gen_coarse_audio_arr
-
-
-def generate_fine(
-    x_coarse_gen,
-    history_prompt=None,
-    temp=0.5,
-    silent=True,
-):
-    """Generate full audio codes from coarse audio codes."""
-    assert (
-        isinstance(x_coarse_gen, np.ndarray)
-        and len(x_coarse_gen.shape) == 2
-        and 1 <= x_coarse_gen.shape[0] <= N_FINE_CODEBOOKS - 1
-        and x_coarse_gen.shape[1] > 0
-        and x_coarse_gen.min() >= 0
-        and x_coarse_gen.max() <= CODEBOOK_SIZE - 1
-    )
-    if history_prompt is not None:
-        history_prompt = _load_history_prompt(history_prompt)
-        x_fine_history = history_prompt["fine_prompt"]
-        assert (
-            isinstance(x_fine_history, np.ndarray)
-            and len(x_fine_history.shape) == 2
-            and x_fine_history.shape[0] == N_FINE_CODEBOOKS
-            and x_fine_history.shape[1] >= 0
-            and x_fine_history.min() >= 0
-            and x_fine_history.max() <= CODEBOOK_SIZE - 1
-        )
-    else:
-        x_fine_history = None
-    n_coarse = x_coarse_gen.shape[0]
-    # load models if not yet exist
-    global models
-    global models_devices
-    if "fine" not in models:
-        preload_models()
-    model = models["fine"]
-    if OFFLOAD_CPU:
-        model.to(models_devices["fine"])
-    device = next(model.parameters()).device
-    # make input arr
-    in_arr = np.vstack(
-        [
-            x_coarse_gen,
-            np.zeros((N_FINE_CODEBOOKS - n_coarse, x_coarse_gen.shape[1]))
-            + CODEBOOK_SIZE,  # padding
-        ]
-    ).astype(np.int32)
-    # prepend history if available (max 512)
-    if x_fine_history is not None:
-        x_fine_history = x_fine_history.astype(np.int32)
-        in_arr = np.hstack(
-            [
-                x_fine_history[:, -512:].astype(np.int32),
-                in_arr,
-            ]
-        )
-        n_history = x_fine_history[:, -512:].shape[1]
-    else:
-        n_history = 0
-    n_remove_from_end = 0
-    # need to pad if too short (since non-causal model)
-    if in_arr.shape[1] < 1024:
-        n_remove_from_end = 1024 - in_arr.shape[1]
-        in_arr = np.hstack(
-            [
-                in_arr,
-                np.zeros((N_FINE_CODEBOOKS, n_remove_from_end), dtype=np.int32) + CODEBOOK_SIZE,
-            ]
-        )
-    # we can be lazy about fractional loop and just keep overwriting codebooks
-    n_loops = np.max([0, int(np.ceil((x_coarse_gen.shape[1] - (1024 - n_history)) / 512))]) + 1
-    with _inference_mode():
-        in_arr = torch.tensor(in_arr.T).to(device)
-        for n in tqdm.tqdm(range(n_loops), disable=silent):
-            start_idx = np.min([n * 512, in_arr.shape[0] - 1024])
-            start_fill_idx = np.min([n_history + n * 512, in_arr.shape[0] - 512])
-            rel_start_fill_idx = start_fill_idx - start_idx
-            in_buffer = in_arr[start_idx : start_idx + 1024, :][None]
-            for nn in range(n_coarse, N_FINE_CODEBOOKS):
-                logits = model(nn, in_buffer)
-                if temp is None:
-                    relevant_logits = logits[0, rel_start_fill_idx:, :CODEBOOK_SIZE]
-                    codebook_preds = torch.argmax(relevant_logits, -1)
-                else:
-                    relevant_logits = logits[0, :, :CODEBOOK_SIZE] / temp
-                    probs = F.softmax(relevant_logits, dim=-1)
-                    # multinomial bugged on mps: shuttle to cpu if necessary
-                    inf_device = probs.device
-                    if probs.device.type == "mps":
-                        probs = probs.to("cpu")
-                    codebook_preds = torch.hstack(
-                        [
-                            torch.multinomial(probs[nnn], num_samples=1).to(inf_device)
-                            for nnn in range(rel_start_fill_idx, 1024)
-                        ]
-                    )
-                in_buffer[0, rel_start_fill_idx:, nn] = codebook_preds
-                del logits, codebook_preds
-            # transfer over info into model_in and convert to numpy
-            for nn in range(n_coarse, N_FINE_CODEBOOKS):
-                in_arr[
-                    start_fill_idx : start_fill_idx + (1024 - rel_start_fill_idx), nn
-                ] = in_buffer[0, rel_start_fill_idx:, nn]
-            del in_buffer
-        gen_fine_arr = in_arr.detach().cpu().numpy().squeeze().T
-        del in_arr
-    if OFFLOAD_CPU:
-        model.to("cpu")
-    gen_fine_arr = gen_fine_arr[:, n_history:]
-    if n_remove_from_end > 0:
-        gen_fine_arr = gen_fine_arr[:, :-n_remove_from_end]
-    assert gen_fine_arr.shape[-1] == x_coarse_gen.shape[-1]
-    _clear_cuda_cache()
-    return gen_fine_arr
-
-
-def codec_decode(fine_tokens):
-    """Turn quantized audio codes into audio array using encodec."""
-    # load models if not yet exist
-    global models
-    global models_devices
-    if "codec" not in models:
-        preload_models()
-    model = models["codec"]
-    if OFFLOAD_CPU:
-        model.to(models_devices["codec"])
-    device = next(model.parameters()).device
-    arr = torch.from_numpy(fine_tokens)[None]
-    arr = arr.to(device)
-    arr = arr.transpose(0, 1)
-    emb = model.quantizer.decode(arr)
-    out = model.decoder(emb)
-    audio_arr = out.detach().cpu().numpy().squeeze()
-    del arr, emb, out
-    if OFFLOAD_CPU:
-        model.to("cpu")
-    return audio_arr
diff --git a/spaces/markski/reddit-roast-me/src/clip_caption_model.py b/spaces/markski/reddit-roast-me/src/clip_caption_model.py
deleted file mode 100644
index e68573decc702de0fe5d29d7ae06867ccaf7bfe9..0000000000000000000000000000000000000000
--- a/spaces/markski/reddit-roast-me/src/clip_caption_model.py
+++ /dev/null
@@ -1,34 +0,0 @@
-
-from typing import Optional
-
-from transformers import GPT2LMHeadModel
-from torch import nn
-import torch
-
-from src.transformer_mapper import TransformerMapper
-
-
-class ClipCaptionModel(nn.Module):
-
-    def get_dummy_token(self, batch_size: int, device: torch.device) -> torch.Tensor:
-        return torch.zeros(batch_size, self.prefix_length, dtype=torch.int64, device=device)
-
-    def forward(self, tokens: torch.Tensor, prefix: torch.Tensor, mask: Optional[torch.Tensor] = None,
-                labels: Optional[torch.Tensor] = None):
-        embedding_text = self.gpt.transformer.wte(tokens)
-        prefix_projections = self.clip_project(prefix).view(-1, self.prefix_length, self.gpt_embedding_size)
-        embedding_cat = torch.cat((prefix_projections, embedding_text), dim=1)
-        if labels is not None:
-            dummy_token = self.get_dummy_token(tokens.shape[0], tokens.device)
-            labels = torch.cat((dummy_token, tokens), dim=1)
-        out = self.gpt(inputs_embeds=embedding_cat, labels=labels, attention_mask=mask)
-        return out
-
-    def __init__(self, prefix_size: int = 640,
-                 num_layers: int = 8):
-        super(ClipCaptionModel, self).__init__()
-        self.prefix_length = 40
-        self.gpt = GPT2LMHeadModel.from_pretrained('gpt2')
-        self.gpt_embedding_size = self.gpt.transformer.wte.weight.shape[1]
-        self.clip_project = TransformerMapper(prefix_size, self.gpt_embedding_size, 40,
-                                                                     40, num_layers)
\ No newline at end of file
diff --git a/spaces/masterkram/finance_news_classifier/src/main.py b/spaces/masterkram/finance_news_classifier/src/main.py
deleted file mode 100644
index 2702847c79219be91d49d5289e0758f832d060d3..0000000000000000000000000000000000000000
--- a/spaces/masterkram/finance_news_classifier/src/main.py
+++ /dev/null
@@ -1,22 +0,0 @@
-from model import create_model
-from train import train_model
-from evalutate import evaluate_model
-from data import load_data
-
-
-def main():
-    print("Loading Dataset")
-    dataset, id2label = load_data()
-    print(dataset)
-    print("Creating Model")
-    model = create_model(id2label)
-    print("Training Model")
-    model = train_model(model, dataset)
-    print("Saving Model")
-    model.save_model("./my_model")
-    print("Eval Model")
-    evaluate_model(model)
-
-
-if __name__ == "__main__":
-    main()
diff --git a/spaces/matthoffner/AudioCraft_Plus/audiocraft/models/lm.py b/spaces/matthoffner/AudioCraft_Plus/audiocraft/models/lm.py
deleted file mode 100644
index 8cefd2c58c3a337378579d6cd6469fd038cbb1ee..0000000000000000000000000000000000000000
--- a/spaces/matthoffner/AudioCraft_Plus/audiocraft/models/lm.py
+++ /dev/null
@@ -1,531 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-
-from dataclasses import dataclass
-from functools import partial
-import logging
-import math
-import typing as tp
-
-import torch
-from torch import nn
-
-from ..utils import utils
-from ..modules.streaming import StreamingModule, State
-from ..modules.transformer import StreamingTransformer, create_norm_fn
-from ..modules.conditioners import (
-    ConditionFuser,
-    ClassifierFreeGuidanceDropout,
-    AttributeDropout,
-    ConditioningProvider,
-    ConditioningAttributes,
-    ConditionType,
-)
-from ..modules.codebooks_patterns import CodebooksPatternProvider
-from ..modules.activations import get_activation_fn
-
-
-logger = logging.getLogger(__name__)
-ConditionTensors = tp.Dict[str, ConditionType]
-CFGConditions = tp.Union[ConditionTensors, tp.Tuple[ConditionTensors, ConditionTensors]]
-
-
-def get_init_fn(method: str, input_dim: int, init_depth: tp.Optional[int] = None):
-    """LM layer initialization.
-    Inspired from xlformers: https://github.com/fairinternal/xlformers
-
-    Args:
-        method (str): Method name for init function. Valid options are:
-            'gaussian', 'uniform'.
-        input_dim (int): Input dimension of the initialized module.
-        init_depth (int, optional): Optional init depth value used to rescale
-            the standard deviation if defined.
-    """
-    # Compute std
-    std = 1 / math.sqrt(input_dim)
-    # Rescale with depth
-    if init_depth is not None:
-        std = std / math.sqrt(2 * init_depth)
-
-    if method == 'gaussian':
-        return partial(
-            torch.nn.init.trunc_normal_, mean=0.0, std=std, a=-3 * std, b=3 * std
-        )
-    elif method == 'uniform':
-        bound = math.sqrt(3) * std  # ensure the standard deviation is `std`
-        return partial(torch.nn.init.uniform_, a=-bound, b=bound)
-    else:
-        raise ValueError("Unsupported layer initialization method")
-
-
-def init_layer(m: nn.Module,
-               method: str,
-               init_depth: tp.Optional[int] = None,
-               zero_bias_init: bool = False):
-    """Wrapper around ``get_init_fn`` for proper initialization of LM modules.
-
-    Args:
-        m (nn.Module): Module to initialize.
-        method (str): Method name for the init function.
-        init_depth (int, optional): Optional init depth value used to rescale
-            the standard deviation if defined.
-        zero_bias_init (bool): Whether to initialize the bias to 0 or not.
-    """
-    if isinstance(m, nn.Linear):
-        init_fn = get_init_fn(method, m.in_features, init_depth=init_depth)
-        if m.weight.device.type == 'cpu' and m.weight.dtype == torch.float16:
-            weight = m.weight.float()
-            init_fn(weight)
-            m.weight.data[:] = weight.half()
-        else:
-            init_fn(m.weight)
-        if zero_bias_init and m.bias is not None:
-            nn.init.constant_(m.bias, 0)
-    elif isinstance(m, nn.Embedding):
-        init_fn = get_init_fn(method, m.embedding_dim, init_depth=None)
-        if m.weight.device.type == 'cpu' and m.weight.dtype == torch.float16:
-            weight = m.weight.float()
-            init_fn(weight)
-            m.weight.data[:] = weight.half()
-        else:
-            init_fn(m.weight)
-
-
-class ScaledEmbedding(nn.Embedding):
-    """Boost learning rate for embeddings (with `scale`).
-    """
-    def __init__(self, *args, lr=None, **kwargs):
-        super().__init__(*args, **kwargs)
-        self.lr = lr
-
-    def make_optim_group(self):
-        group = {"params": list(self.parameters())}
-        if self.lr is not None:
-            group["lr"] = self.lr
-        return group
-
-
-@dataclass
-class LMOutput:
-    # The logits are already re-aligned with the input codes
-    # hence no extra shift is required, e.g. when computing CE
-    logits: torch.Tensor  # [B, K, T, card]
-    mask: torch.Tensor  # [B, K, T]
-
-
-class LMModel(StreamingModule):
-    """Transformer-based language model on multiple streams of codes.
-
-    Args:
-        pattern_provider (CodebooksPatternProvider): Pattern provider for codebook interleaving.
-        condition_provider (MusicConditioningProvider): Conditioning provider from metadata.
-        fuser (ConditionFuser): Fuser handling the fusing of conditions with language model input.
-        n_q (int): Number of parallel streams to model.
-        card (int): Cardinality, vocabulary size.
-        dim (int): Dimension of the transformer encoder.
-        num_heads (int): Number of heads for the transformer encoder.
-        hidden_scale (int): Scale for hidden feed forward dimension of the transformer encoder.
-        norm (str): Normalization method.
-        norm_first (bool): Use pre-norm instead of post-norm.
-        emb_lr (float, optional): Embedding-specific learning rate.
-        bias_proj (bool): Use bias for output projections.
-        weight_init (str, optional): Method for weight initialization.
-        depthwise_init (str, optional): Method for depthwise weight initialization.
-        zero_bias_init (bool): If true and bias in Linears, initialize bias to zeros.
-        cfg_dropout (float): Classifier-free guidance dropout.
-        cfg_coef (float): Classifier-free guidance coefficient.
-        attribute_dropout (dict): Attribute dropout probabilities.
-        two_step_cfg (bool): Whether to run classifier free-guidance with 2 distinct steps.
-        **kwargs: Additional parameters for the transformer encoder.
-    """
-    def __init__(self, pattern_provider: CodebooksPatternProvider, condition_provider: ConditioningProvider,
-                 fuser: ConditionFuser, n_q: int = 8, card: int = 1024, dim: int = 128, num_heads: int = 8,
-                 hidden_scale: int = 4, norm: str = 'layer_norm', norm_first: bool = False,
-                 emb_lr: tp.Optional[float] = None, bias_proj: bool = True,
-                 weight_init: tp.Optional[str] = None, depthwise_init: tp.Optional[str] = None,
-                 zero_bias_init: bool = False, cfg_dropout: float = 0, cfg_coef: float = 1.0,
-                 attribute_dropout: tp.Dict[str, tp.Dict[str, float]] = {}, two_step_cfg: bool = False,
-                 **kwargs):
-        super().__init__()
-        self.cfg_coef = cfg_coef
-        self.cfg_dropout = ClassifierFreeGuidanceDropout(p=cfg_dropout)
-        self.att_dropout = AttributeDropout(p=attribute_dropout)
-        self.condition_provider = condition_provider
-        self.fuser = fuser
-        self.card = card
-        embed_dim = self.card + 1
-        self.n_q = n_q
-        self.dim = dim
-        self.pattern_provider = pattern_provider
-        self.two_step_cfg = two_step_cfg
-        self.emb = nn.ModuleList([ScaledEmbedding(embed_dim, dim, lr=emb_lr) for _ in range(n_q)])
-        if 'activation' in kwargs:
-            kwargs['activation'] = get_activation_fn(kwargs['activation'])
-        self.transformer = StreamingTransformer(
-            d_model=dim, num_heads=num_heads, dim_feedforward=int(hidden_scale * dim),
-            norm=norm, norm_first=norm_first, **kwargs)
-        self.out_norm: tp.Optional[nn.Module] = None
-        if norm_first:
-            self.out_norm = create_norm_fn(norm, dim)
-        self.linears = nn.ModuleList([nn.Linear(dim, self.card, bias=bias_proj) for _ in range(n_q)])
-        self._init_weights(weight_init, depthwise_init, zero_bias_init)
-        self._fsdp: tp.Optional[nn.Module]
-        self.__dict__['_fsdp'] = None
-
-    def _init_weights(self, weight_init: tp.Optional[str], depthwise_init: tp.Optional[str], zero_bias_init: bool):
-        """Initialization of the transformer module weights.
-
-        Args:
-            weight_init (str, optional): Weight initialization strategy. See ``get_init_fn`` for valid options.
-            depthwise_init (str, optional): Depthwise initialization strategy. The following options are valid:
-                'current' where the depth corresponds to the current layer index or 'global' where the total number
-                of layer is used as depth. If not set, no depthwise initialization strategy is used.
-            zero_bias_init (bool): Whether to initialize bias to zero or not.
-        """
-        assert depthwise_init is None or depthwise_init in ['current', 'global']
-        assert depthwise_init is None or weight_init is not None, \
-            "If 'depthwise_init' is defined, a 'weight_init' method should be provided."
-        assert not zero_bias_init or weight_init is not None, \
-            "If 'zero_bias_init', a 'weight_init' method should be provided"
-
-        if weight_init is None:
-            return
-
-        for emb_layer in self.emb:
-            init_layer(emb_layer, method=weight_init, init_depth=None, zero_bias_init=zero_bias_init)
-
-        for layer_idx, tr_layer in enumerate(self.transformer.layers):
-            depth = None
-            if depthwise_init == 'current':
-                depth = layer_idx + 1
-            elif depthwise_init == 'global':
-                depth = len(self.transformer.layers)
-            init_fn = partial(init_layer, method=weight_init, init_depth=depth, zero_bias_init=zero_bias_init)
-            tr_layer.apply(init_fn)
-
-        for linear in self.linears:
-            init_layer(linear, method=weight_init, init_depth=None, zero_bias_init=zero_bias_init)
-
-    @property
-    def special_token_id(self) -> int:
-        return self.card
-
-    @property
-    def num_codebooks(self) -> int:
-        return self.n_q
-
-    def forward(self, sequence: torch.Tensor,
-                conditions: tp.List[ConditioningAttributes],
-                condition_tensors: tp.Optional[ConditionTensors] = None) -> torch.Tensor:
-        """Apply language model on sequence and conditions.
-        Given a tensor of sequence of shape [B, K, S] with K the number of codebooks and
-        S the sequence steps, return the logits with shape [B, card, K, S].
-
-        Args:
-            indices (torch.Tensor): Indices of the codes to model.
-            conditions (list of ConditioningAttributes): Conditions to use when modeling
-                the given codes. Note that when evaluating multiple time with the same conditioning
-                you should pre-compute those and pass them as `condition_tensors`.
-            condition_tensors (dict[str, ConditionType], optional): Pre-computed conditioning
-                tensors, see `conditions`.
-        Returns:
-            torch.Tensor: Logits.
-        """
-        B, K, S = sequence.shape
-        assert K == self.num_codebooks, "Sequence shape must match the specified number of codebooks"
-        input_ = sum([self.emb[k](sequence[:, k]) for k in range(K)])
-        if condition_tensors is None:
-            assert not self._is_streaming, "Conditions tensors should be precomputed when streaming."
-            # apply dropout modules
-            conditions = self.cfg_dropout(conditions)
-            conditions = self.att_dropout(conditions)
-            tokenized = self.condition_provider.tokenize(conditions)
-            # encode conditions and fuse, both have a streaming cache to not recompute when generating.
-            condition_tensors = self.condition_provider(tokenized)
-        else:
-            assert not conditions, "Shouldn't pass both conditions and condition_tensors."
-
-        input_, cross_attention_input = self.fuser(input_, condition_tensors)
-
-        out = self.transformer(input_, cross_attention_src=cross_attention_input)
-        if self.out_norm:
-            out = self.out_norm(out)
-        logits = torch.stack([self.linears[k](out) for k in range(K)], dim=1)  # [B, K, S, card]
-
-        # remove the prefix from the model outputs
-        if len(self.fuser.fuse2cond['prepend']) > 0:
-            logits = logits[:, :, -S:]
-
-        return logits  # [B, K, S, card]
-
-    def compute_predictions(
-            self, codes: torch.Tensor,
-            conditions: tp.List[ConditioningAttributes],
-            condition_tensors: tp.Optional[ConditionTensors] = None) -> LMOutput:
-        """Given an input tensor of codes [B, K, T] and list of conditions, runs the model
-        forward using the specified codes interleaving pattern.
-
-        Args:
-            codes (torch.Tensor): Input codes of shape [B, K, T] with B the batch size,
-                K the number of codebooks and T the number of timesteps.
-            conditions (list of ConditioningAttributes): conditionings to use when modeling
-                the given codes. Note that when evaluating multiple time with the same conditioning
-                you should pre-compute those and pass them as `condition_tensors`.
-            condition_tensors (dict[str, ConditionType], optional): pre-computed conditioning
-                tensors, see `conditions`.
-        Returns:
-            LMOutput: Language model outputs
-                logits (torch.Tensor) of shape [B, K, T, card] corresponding to the provided codes,
-                    i.e. the first item corresponds to logits to predict the first code, meaning that
-                    no additional shifting of codes and logits is required.
-                mask (torch.Tensor) of shape [B, K, T], mask over valid and invalid positions.
-                    Given the specified interleaving strategies, parts of the logits and codes should
-                    not be considered as valid predictions because of invalid context.
-        """
-        B, K, T = codes.shape
-        codes = codes.contiguous()
-        # map codes [B, K, T] into pattern sequence [B, K, S] using special_token_id for masked tokens
-        pattern = self.pattern_provider.get_pattern(T)
-        sequence_codes, sequence_indexes, sequence_mask = pattern.build_pattern_sequence(
-            codes, self.special_token_id, keep_only_valid_steps=True
-        )
-        # apply model on pattern sequence
-        model = self if self._fsdp is None else self._fsdp
-        logits = model(sequence_codes, conditions, condition_tensors)  # [B, K, S, card]
-        # map back the logits on pattern sequence to logits on original codes: [B, K, S, card] -> [B, K, T, card]
-        # and provide the corresponding mask over invalid positions of tokens
-        logits = logits.permute(0, 3, 1, 2)  # [B, card, K, S]
-        # note: we use nans as special token to make it obvious if we feed unexpected logits
-        logits, logits_indexes, logits_mask = pattern.revert_pattern_logits(
-            logits, float('nan'), keep_only_valid_steps=True
-        )
-        logits = logits.permute(0, 2, 3, 1)  # [B, K, T, card]
-        logits_mask = logits_mask[None, :, :].expand(B, -1, -1)  # [K, T] -> [B, K, T]
-        return LMOutput(logits, logits_mask)
-
-    def _sample_next_token(self,
-                           sequence: torch.Tensor,
-                           cfg_conditions: CFGConditions,
-                           unconditional_state: State,
-                           use_sampling: bool = False,
-                           temp: float = 1.0,
-                           top_k: int = 0,
-                           top_p: float = 0.0,
-                           cfg_coef: tp.Optional[float] = None) -> torch.Tensor:
-        """Sample next token from the model given a sequence and a set of conditions. The model supports
-        multiple sampling strategies (greedy sampling, softmax, top-k, top-p...).
-
-        Args:
-            sequence (torch.Tensor): Current sequence of shape [B, K, S]
-                with K corresponding to the number of codebooks and S the number of sequence steps.
-                S = 1 in streaming mode, except for the first step that contains a bigger prompt.
-            condition_tensors (dict[str, ConditionType): Set of conditions. If CFG is used,
-                should be twice the batch size, being the concatenation of the conditions + null conditions.
-            use_sampling (bool): Whether to use a sampling strategy or not.
-            temp (float): Sampling temperature.
-            top_k (int): K for "top-k" sampling.
-            top_p (float): P for "top-p" sampling.
-            cfg_coef (float, optional): classifier free guidance coefficient
-        Returns:
-            next_token (torch.Tensor): Next token tensor of shape [B, K, 1].
-        """
-        B = sequence.shape[0]
-        cfg_coef = self.cfg_coef if cfg_coef is None else cfg_coef
-        model = self if self._fsdp is None else self._fsdp
-        if self.two_step_cfg and cfg_conditions != {}:
-            assert isinstance(cfg_conditions, tuple), type(cfg_conditions)
-            condition_tensors, null_condition_tensors = cfg_conditions
-            cond_logits = model(sequence, conditions=[], condition_tensors=condition_tensors)
-            state = self.get_streaming_state()
-            self.set_streaming_state(unconditional_state)
-            uncond_logits = model(sequence, conditions=[], condition_tensors=null_condition_tensors)
-            unconditional_state.update(self.get_streaming_state())
-            self.set_streaming_state(state)
-            logits = uncond_logits + (cond_logits - uncond_logits) * self.cfg_coef
-        else:
-            assert isinstance(cfg_conditions, dict)
-            condition_tensors = cfg_conditions
-            if condition_tensors:
-                # Preparing for CFG, predicting both conditional and unconditional logits.
-                sequence = torch.cat([sequence, sequence], dim=0)
-            all_logits = model(
-                sequence,
-                conditions=[], condition_tensors=condition_tensors)
-            if condition_tensors:
-                cond_logits, uncond_logits = all_logits.split(B, dim=0)  # [B, K, T, card]
-                logits = uncond_logits + (cond_logits - uncond_logits) * cfg_coef
-            else:
-                logits = all_logits
-
-        logits = logits.permute(0, 1, 3, 2)  # [B, K, card, T]
-        logits = logits[..., -1]  # [B x K x card]
-
-        # Apply softmax for sampling if temp > 0. Else, do greedy sampling to avoid zero division error.
-        if use_sampling and temp > 0.0:
-            probs = torch.softmax(logits / temp, dim=-1)
-            if top_p > 0.0:
-                next_token = utils.sample_top_p(probs, p=top_p)
-            elif top_k > 0:
-                next_token = utils.sample_top_k(probs, k=top_k)
-            else:
-                next_token = utils.multinomial(probs, num_samples=1)
-        else:
-            next_token = torch.argmax(logits, dim=-1, keepdim=True)
-
-        return next_token
-
-    @torch.no_grad()
-    def generate(self,
-                 prompt: tp.Optional[torch.Tensor] = None,
-                 conditions: tp.List[ConditioningAttributes] = [],
-                 num_samples: tp.Optional[int] = None,
-                 max_gen_len: int = 256,
-                 use_sampling: bool = True,
-                 temp: float = 1.0,
-                 top_k: int = 250,
-                 top_p: float = 0.0,
-                 cfg_coef: tp.Optional[float] = None,
-                 two_step_cfg: tp.Optional[bool] = None,
-                 remove_prompts: bool = False,
-                 check: bool = False,
-                 callback: tp.Optional[tp.Callable[[int, int], None]] = None) -> torch.Tensor:
-        """Generate tokens sampling from the model given a prompt or unconditionally. Generation can
-        be perform in a greedy fashion or using sampling with top K and top P strategies.
-
-        Args:
-            prompt (torch.Tensor, optional): Prompt tokens of shape [B, K, T].
-            conditions_tensors (list of ConditioningAttributes, optional): List of conditions.
-            num_samples (int, optional): Number of samples to generate when no prompt and no conditions are given.
-            max_gen_len (int): Maximum generation length.
-            use_sampling (bool): Whether to use a sampling strategy or not.
-            temp (float): Sampling temperature.
-            top_k (int): K for "top-k" sampling.
-            top_p (float): P for "top-p" sampling.
-            cfg_coeff (float, optional): Classifier-free guidance coefficient.
-            two_step_cfg (bool, optional): Whether to perform classifier-free guidance with two steps generation.
-            remove_prompts (bool): Whether to remove prompts from generation or not.
-            check (bool): Whether to apply further checks on generated sequence.
-            callback (Callback, optional): Callback function to report generation progress.
-        Returns:
-            torch.Tensor: Generated tokens.
-        """
-        assert not self.training, "generation shouldn't be used in training mode."
-        first_param = next(iter(self.parameters()))
-        device = first_param.device
-
-        # Checking all input shapes are consistent.
-        possible_num_samples = []
-        if num_samples is not None:
-            possible_num_samples.append(num_samples)
-        elif prompt is not None:
-            possible_num_samples.append(prompt.shape[0])
-        elif conditions:
-            possible_num_samples.append(len(conditions))
-        else:
-            possible_num_samples.append(1)
-        assert [x == possible_num_samples[0] for x in possible_num_samples], "Inconsistent inputs shapes"
-        num_samples = possible_num_samples[0]
-
-        # below we create set of conditions: one conditional and one unconditional
-        # to do that we merge the regular condition together with the null condition
-        # we then do 1 forward pass instead of 2.
-        # the reason for that is two-fold:
-        # 1. it is about x2 faster than doing 2 forward passes
-        # 2. avoid the streaming API treating the 2 passes as part of different time steps
-        # We also support doing two different passes, in particular to ensure that
-        # the padding structure is exactly the same between train and test.
-        # With a batch size of 1, this can be slower though.
-        cfg_conditions: CFGConditions
-        two_step_cfg = self.two_step_cfg if two_step_cfg is None else two_step_cfg
-        if conditions:
-            null_conditions = ClassifierFreeGuidanceDropout(p=1.0)(conditions)
-            if two_step_cfg:
-                cfg_conditions = (
-                    self.condition_provider(self.condition_provider.tokenize(conditions)),
-                    self.condition_provider(self.condition_provider.tokenize(null_conditions)),
-                )
-            else:
-                conditions = conditions + null_conditions
-                tokenized = self.condition_provider.tokenize(conditions)
-                cfg_conditions = self.condition_provider(tokenized)
-        else:
-            cfg_conditions = {}
-
-        if prompt is None:
-            assert num_samples > 0
-            prompt = torch.zeros((num_samples, self.num_codebooks, 0), dtype=torch.long, device=device)
-
-        B, K, T = prompt.shape
-        start_offset = T
-        assert start_offset < max_gen_len
-
-        pattern = self.pattern_provider.get_pattern(max_gen_len)
-        # this token is used as default value for codes that are not generated yet
-        unknown_token = -1
-
-        # we generate codes up to the max_gen_len that will be mapped to the pattern sequence
-        gen_codes = torch.full((B, K, max_gen_len), unknown_token, dtype=torch.long, device=device)
-        # filling the gen_codes with the prompt if needed
-        gen_codes[..., :start_offset] = prompt
-        # create the gen_sequence with proper interleaving from the pattern: [B, K, S]
-        gen_sequence, indexes, mask = pattern.build_pattern_sequence(gen_codes, self.special_token_id)
-        # retrieve the start_offset in the sequence:
-        # it is the first sequence step that contains the `start_offset` timestep
-        start_offset_sequence = pattern.get_first_step_with_timesteps(start_offset)
-        assert start_offset_sequence is not None
-
-        with self.streaming():
-            unconditional_state = self.get_streaming_state()
-            prev_offset = 0
-            gen_sequence_len = gen_sequence.shape[-1]  # gen_sequence shape is [B, K, S]
-            for offset in range(start_offset_sequence, gen_sequence_len):
-                # get current sequence (note that the streaming API is providing the caching over previous offsets)
-                curr_sequence = gen_sequence[..., prev_offset:offset]
-                curr_mask = mask[None, ..., prev_offset:offset].expand(B, -1, -1)
-                if check:
-                    # check coherence between mask and sequence
-                    assert (curr_sequence == torch.where(curr_mask, curr_sequence, self.special_token_id)).all()
-                    # should never happen as gen_sequence is filled progressively
-                    assert not (curr_sequence == unknown_token).any()
-                # sample next token from the model, next token shape is [B, K, 1]
-                next_token = self._sample_next_token(
-                    curr_sequence, cfg_conditions, unconditional_state, use_sampling, temp, top_k, top_p,
-                    cfg_coef=cfg_coef)
-                # ensure the tokens that should be masked are properly set to special_token_id
-                # as the model never output special_token_id
-                valid_mask = mask[..., offset:offset+1].expand(B, -1, -1)
-                next_token[~valid_mask] = self.special_token_id
-                # ensure we don't overwrite prompt tokens, we only write over unknown tokens
-                # (then mask tokens should be left as is as well, which is correct)
-                gen_sequence[..., offset:offset+1] = torch.where(
-                    gen_sequence[..., offset:offset+1] == unknown_token,
-                    next_token, gen_sequence[..., offset:offset+1]
-                )
-                prev_offset = offset
-                if callback is not None:
-                    callback(1 + offset - start_offset_sequence, gen_sequence_len - start_offset_sequence)
-        unconditional_state.clear()
-
-        # ensure sequence has been entirely filled
-        assert not (gen_sequence == unknown_token).any()
-        # ensure gen_sequence pattern and mask are matching
-        # which means the gen_sequence is valid according to the pattern
-        assert (
-            gen_sequence == torch.where(mask[None, ...].expand(B, -1, -1), gen_sequence, self.special_token_id)
-        ).all()
-        # get back the codes, trimming the prompt if needed and cutting potentially incomplete timesteps
-        out_codes, out_indexes, out_mask = pattern.revert_pattern_sequence(gen_sequence, special_token=unknown_token)
-
-        # sanity checks over the returned codes and corresponding masks
-        assert (out_codes[..., :max_gen_len] != unknown_token).all()
-        assert (out_mask[..., :max_gen_len] == 1).all()
-
-        out_start_offset = start_offset if remove_prompts else 0
-        out_codes = out_codes[..., out_start_offset:max_gen_len]
-
-        # ensure the returned codes are all valid
-        assert (out_codes >= 0).all() and (out_codes <= self.card).all()
-        return out_codes
diff --git a/spaces/maxjmohr/MSc_02_PDL_A4/modernity.py b/spaces/maxjmohr/MSc_02_PDL_A4/modernity.py
deleted file mode 100644
index 43a76fb48205b11d74006d38d472117eab31971e..0000000000000000000000000000000000000000
--- a/spaces/maxjmohr/MSc_02_PDL_A4/modernity.py
+++ /dev/null
@@ -1,23 +0,0 @@
-import torch
-import torch.nn.functional as F
-
-def get_year_modernity_score(model, image, device):
-    model.eval()  # Set model to evaluate mode
-
-    # Map modernity_scores into the corresponding years
-    year_group_mapping = {
-        0: "2000-2003",
-        1: "2006-2008",
-        2: "2009-2011",
-        3: "2012-2014",
-        4: "2015-2017"
-    }
-
-    with torch.no_grad():
-        image = image.to(device)
-        # Get the prediction probabilities, from that calculate the modernity score and round to get the year group
-        pred_label = model(image)
-        modernity_score = torch.sum(F.softmax(pred_label, dim=1) * torch.tensor([0,1,2,3,4], device=device), dim=1)
-        year_group = year_group_mapping[modernity_score.round().item()]
-
-    return modernity_score.item(), year_group
\ No newline at end of file
diff --git a/spaces/merle/PROTEIN_GENERATOR/utils/model/se3_transformer/runtime/arguments.py b/spaces/merle/PROTEIN_GENERATOR/utils/model/se3_transformer/runtime/arguments.py
deleted file mode 100644
index d35d5ee1d05a150ea40c411ec47c633213ca9d9f..0000000000000000000000000000000000000000
--- a/spaces/merle/PROTEIN_GENERATOR/utils/model/se3_transformer/runtime/arguments.py
+++ /dev/null
@@ -1,70 +0,0 @@
-# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
-#
-# Permission is hereby granted, free of charge, to any person obtaining a
-# copy of this software and associated documentation files (the "Software"),
-# to deal in the Software without restriction, including without limitation
-# the rights to use, copy, modify, merge, publish, distribute, sublicense,
-# and/or sell copies of the Software, and to permit persons to whom the
-# Software is furnished to do so, subject to the following conditions:
-#
-# The above copyright notice and this permission notice shall be included in
-# all copies or substantial portions of the Software.
-#
-# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
-# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
-# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
-# DEALINGS IN THE SOFTWARE.
-#
-# SPDX-FileCopyrightText: Copyright (c) 2021 NVIDIA CORPORATION & AFFILIATES
-# SPDX-License-Identifier: MIT
-
-import argparse
-import pathlib
-
-from se3_transformer.data_loading import QM9DataModule
-from se3_transformer.model import SE3TransformerPooled
-from se3_transformer.runtime.utils import str2bool
-
-PARSER = argparse.ArgumentParser(description='SE(3)-Transformer')
-
-paths = PARSER.add_argument_group('Paths')
-paths.add_argument('--data_dir', type=pathlib.Path, default=pathlib.Path('./data'),
-                   help='Directory where the data is located or should be downloaded')
-paths.add_argument('--log_dir', type=pathlib.Path, default=pathlib.Path('/results'),
-                   help='Directory where the results logs should be saved')
-paths.add_argument('--dllogger_name', type=str, default='dllogger_results.json',
-                   help='Name for the resulting DLLogger JSON file')
-paths.add_argument('--save_ckpt_path', type=pathlib.Path, default=None,
-                   help='File where the checkpoint should be saved')
-paths.add_argument('--load_ckpt_path', type=pathlib.Path, default=None,
-                   help='File of the checkpoint to be loaded')
-
-optimizer = PARSER.add_argument_group('Optimizer')
-optimizer.add_argument('--optimizer', choices=['adam', 'sgd', 'lamb'], default='adam')
-optimizer.add_argument('--learning_rate', '--lr', dest='learning_rate', type=float, default=0.002)
-optimizer.add_argument('--min_learning_rate', '--min_lr', dest='min_learning_rate', type=float, default=None)
-optimizer.add_argument('--momentum', type=float, default=0.9)
-optimizer.add_argument('--weight_decay', type=float, default=0.1)
-
-PARSER.add_argument('--epochs', type=int, default=100, help='Number of training epochs')
-PARSER.add_argument('--batch_size', type=int, default=240, help='Batch size')
-PARSER.add_argument('--seed', type=int, default=None, help='Set a seed globally')
-PARSER.add_argument('--num_workers', type=int, default=8, help='Number of dataloading workers')
-
-PARSER.add_argument('--amp', type=str2bool, nargs='?', const=True, default=False, help='Use Automatic Mixed Precision')
-PARSER.add_argument('--gradient_clip', type=float, default=None, help='Clipping of the gradient norms')
-PARSER.add_argument('--accumulate_grad_batches', type=int, default=1, help='Gradient accumulation')
-PARSER.add_argument('--ckpt_interval', type=int, default=-1, help='Save a checkpoint every N epochs')
-PARSER.add_argument('--eval_interval', dest='eval_interval', type=int, default=1,
-                    help='Do an evaluation round every N epochs')
-PARSER.add_argument('--silent', type=str2bool, nargs='?', const=True, default=False,
-                    help='Minimize stdout output')
-
-PARSER.add_argument('--benchmark', type=str2bool, nargs='?', const=True, default=False,
-                    help='Benchmark mode')
-
-QM9DataModule.add_argparse_args(PARSER)
-SE3TransformerPooled.add_argparse_args(PARSER)
diff --git a/spaces/merve/data-leak/public/anonymization/make-gs.js b/spaces/merve/data-leak/public/anonymization/make-gs.js
deleted file mode 100644
index 4eb1aaeffeb2a69e726a9d452d7eea7b3352b318..0000000000000000000000000000000000000000
--- a/spaces/merve/data-leak/public/anonymization/make-gs.js
+++ /dev/null
@@ -1,105 +0,0 @@
-window.makeGS = function(){
-  var prevSlideIndex = -1
-  function updateSlide(i){
-    var slide = slides[i]
-    if (!slide) return
-
-    d3.select('.tooltip').classed('tooltip-hidden', true)
-
-    var dur = 500
-
-    sel.student.transition('xKey').duration(dur).delay(dur ? slide.circleDelayFn : 0)
-      .translate(d => (d.isAdditionalStudent && slide.xKey != 'plagerizedShifted') ? [0,0]: d.pos[slide.xKey])
-
-      
-    if (sel.rectAt[slide.xKey]){
-      sel.uniqueBox.transition('at').duration(dur)
-        .delay(d => dur ? slide.circleDelayFn(d.d0) : 0)
-        .at(sel.rectAt[slide.xKey])
-        .translate(d => d.d0.group[slide.xKey].pos)
-    }
-
-    sel.uniqueBox.transition().duration(dur)
-      .st({opacity: slide.showUniqueBox ? 1 : 0})
-    
-    sel.uniqueSeasonBox.transition()
-      .delay((d, i) => slide.showUniqueSeasonBox ? dur*2 + i*40 : 0).duration(slide.showUniqueSeasonBox ? 0 : dur)
-      .st({opacity: slide.showUniqueSeasonBox ? 1 : 0})
-
-
-    if (sliders.headsProb != slide.headsProbTarget && slide.animateHeadsProbSlider != -1){
-      var headI = d3.interpolate(sliders.headsProb, slide.headsProbTarget)
-      if (window.headSliderTimer) window.headSliderTimer.stop()
-      window.headSliderTimer = d3.timer(ms => {
-        var dur = slide.animateHeadsProbSlider ? 2000 : 1
-        var t = d3.easeCubicInOut(d3.clamp(0, ms/dur, 1))
-        sliders.updateHeadsProb(headI(t))
-        if (t == 1) headSliderTimer.stop()
-      })
-    }
-
-    if (sliders.population != slide.populationTarget){
-      var popI = d3.interpolate(sliders.population, slide.populationTarget)
-      if (window.popSliderTimer) window.popSliderTimer.stop()
-      window.popSliderTimer = d3.timer(ms => {
-        var dur = slide.animatePopulationSlider ? 2000 : 1
-        var t = d3.easeCubicInOut(d3.clamp(0, ms/dur, 1))
-        sliders.updatePopulation(Math.round(popI(t)/2)*2)
-        if (t == 1) popSliderTimer.stop()
-      })
-    }
-
-    axii.stateAxis.transition().duration(dur/2)
-      .st({opacity: slide.showStateAxis ? 1 : 0})
-    axii.ageAxis.transition().duration(dur/2)
-      .st({opacity: slide.showAgeAxis ? 1 : 0})
-    axii.seasonAxis.transition().duration(dur/2)
-      .st({opacity: slide.showSeasonAxis ? 1 : 0})
-    axii.headAxis.transition().duration(dur/2)
-      .st({opacity: slide.showHeadAxis ? 1 : 0})
-    axii.headCaptionAxis.transition().duration(dur/2)
-      .st({opacity: slide.showHeadCaptionAxis ? 1 : 0})
-    estimates.axisSel.transition().delay(dur).duration(dur/2)
-      .st({opacity: slide.showHistogramAxis ? 1 : 0})
-    estimates.activeSel.transition().delay(dur).duration(dur/2)
-      .st({opacity: slide.showHistogramAxis ? 1 : 0})
-    // axii.estimateAxis.transition().delay(dur).duration(dur/2)
-    //   .st({opacity: slide.showEstimate && !slide.enterHistogram ? 1 : 0})
-    // axii.plagerizedAxis.transition().delay(dur).duration(dur/2)
-    //   .st({opacity: slide.showPlagerizedAxis ? 1 : 0})
-
-
-    annotationSel.transition().duration(dur/2)
-      .st({opacity: d => i == d.slide ? 1 : 0})
-
-    estimates.containerSel.transition('xKey').duration(dur/2)
-      .st({opacity: slide.showHistogram ? 1 : 0})
-    
-    if (slide.enterHistogram){
-      estimates.render(true)
-    } else {
-      window.flipAllCoinsTimer._time = Infinity
-    }
-    if (slide.enterHistogram === 0) estimates.estimateSel.classed('active', 1)
-
-
-    // Display the default coin flip state if the histogram is not visible.
-    sel.flipCircle.transition().duration(dur)
-      .at({transform: d => {
-        return slide.showFlipCircle && d.coinVals[estimates.active.index] < sliders.headsProb ? 'scale(1)' : 'scale(.1)'}})
-    
-    prevSlideIndex = i
-    slides.curSlide = slide
-  }
-
-  var gs = d3.graphScroll()
-    .container(d3.select('.container-1'))
-    .graph(d3.selectAll('container-1 #graph'))
-    .eventId('uniqueId1')
-    .sections(d3.selectAll('.container-1 #sections > div'))
-    .offset(300)
-    .on('active', updateSlide)
-}
-
-
-if (window.init) window.init()
diff --git a/spaces/merve/data-leak/public/hidden-bias/style.css b/spaces/merve/data-leak/public/hidden-bias/style.css
deleted file mode 100644
index 4b0d163f9dc4af367dc0b84036c5e177b8f4db0b..0000000000000000000000000000000000000000
--- a/spaces/merve/data-leak/public/hidden-bias/style.css
+++ /dev/null
@@ -1,275 +0,0 @@
-/* Copyright 2020 Google LLC. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-.tooltip {
-  top: -1000px;
-  position: fixed;
-  padding: 10px;
-  background: rgba(255, 255, 255, .90);
-  border: 1px solid lightgray;
-  pointer-events: none;
-  font-family: monospace;
-  font-size: 14px;
-  width: 170px;
-}
-.tooltip-hidden{
-  opacity: 0;
-  transition: all .3s;
-  transition-delay: .1s;
-}
-
-@media (max-width: 590px){
-  div.tooltip{
-    bottom: -1px;
-    width: calc(100%);
-    left: -1px !important;
-    right: -1px !important;
-    top: auto !important;
-    width: auto !important;
-  }
-}
-
-/* Ensure the last panel can be activated on tall screens */
-@media (min-height: 1700px){
-  #container{
-    margin-bottom: 900px;
-  }
-}
-
-.tooltip span{
-  padding: 2px;
-}
-
-svg{
-  overflow: visible;
-}
-
-.domain{
-  display: none;
-}
-
-text{
-  /*pointer-events: none;*/
-  text-shadow: 0 1px 0 #fff, 1px 0 0 #fff, 0 -1px 0 #fff, -1px 0 0 #fff;
-}
-
-
-
-
-
-
-#container{
-  position: relative;
-  width: auto;
-}
-
-#container h3{
-  font-weight: 500;
-}
-
-#sections{
-  width: 340px;
-}
-
-#sections > div{
-  background: white;
-  opacity: .2;
-  margin-bottom: 200px;
-  line-height: 1.4em;
-}
-#sections > div:last-child{
-  padding-bottom: 80vh;
-}
-#sections > div.graph-scroll-active{
-  opacity: 1;
-}
-
-#graph{
-  margin-left: 40px;
-  width: 500px;
-  position: -webkit-sticky;
-  position: sticky;
-  top: 0px;
-  float: right;
-}
-
-@media (max-width: 925px)  {
-  #graph{
-    width: 100%;
-    margin-left: 0px;
-    float: none;
-  }
-
-  #sections{
-    width: auto;
-    position: relative;
-    margin: 0px auto;
-  }
-
-  #sections > div{
-    background: rgba(255,255,255,.5);
-    padding: 10px;
-    border-top: 1px solid;
-    border-bottom: 1px solid;
-    margin-bottom: 80vh;
-  }
-}
-
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-.mono{
-  font-family: monospace;
-}
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-  overflow: visible;
-}
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-.axis{
-  font-size: 12px;
-}
-.axis{
-  color: #999;
-}
-.axis text{
-  fill: #999;
-}
-.axis line{
-  stroke: #ccc;
-}
-
-div.axis b{
-  margin-bottom: 100px;
-  display: block;
-}
-
-.axis .blink{
-  color: orange;
-}
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-
-.highlight{
-  color: #fff;
-  padding-left: 3px;
-  padding-right: 3px;
-  padding-top: 1px;
-  padding-bottom: 1px;
-  border-radius: 3px;
-}
-
-/*.highlight.blue{ background: blue; }*/
-/*.highlight.orange{ background: orange; }*/
-.highlight.yellow{ background: #ff0; color: #000; }
-.highlight.blue{ background: #8effff; color: #000; }
-.highlight.male{ background: #7DDAD3; color: #000; }
-.highlight.female{ background: #9B86EF; color: #000; }
-
-.annotation .highlight{
-  padding: 0px;
-  padding-left: 2px;
-  padding-right: 2px;
-  margin-left: -2px;
-  margin-right: -2px;
-  border-radius: 3px;
-  /*height: 12px;*/
-  display: inline-block;
-}
-
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-#graph .highlight.yellow, #graph .highlight.blue{
-  padding-left: 0px;
-  padding: 0px;
-}
-
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-.circle{
-  background: #eee;
-  border: 1px solid #ccc;
-  font-family: monospace;
-  padding-left: 4.2px;
-  padding-right: 4.2px;
-  padding-top: 0px;
-  padding-bottom: 0px;
-
-  border-radius: 1000px;
-  width: 20px;
-  height: 20px;
-}
-
-
-.strikethrough{
-  text-decoration: line-through;
-  color: #000;
-}
-
-
-.annotation div{
-  font-size: 12px;
-  line-height: 13px;
-  font-family: 'Google Sans', sans-serif;
-}
-
-
-.annotations path{
-  fill: none;
-  stroke: black;
-  stroke-width: .5px;
-}
-
-  
-.img-slide img{
-  width: 30px;
-  transform: rotate(-90deg);
-  margin-left: -10px;
-  margin-right: -4px;
-  position: relative;
-  top: 5px;
-}
-
-.img-slide img:nth-of-type(1){
-  transform: rotate(90deg);
-  margin-left: -10px;
-  margin-right: -4px;
-  top: 0px;
-}
-
-
-
-
-
-div.axis b{
-  margin-bottom: 0px;
-}
-
-div.axis{
-  line-height: 14px;
-}
-
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-circle:hover{
-  stroke: #000;
-  stroke-width: 2;
-}
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-
-
diff --git a/spaces/merve/measuring-fairness/public/anonymization/make-estimates.js b/spaces/merve/measuring-fairness/public/anonymization/make-estimates.js
deleted file mode 100644
index 46ed3feaf1acaccf35153c3ebaf5b60094b21daf..0000000000000000000000000000000000000000
--- a/spaces/merve/measuring-fairness/public/anonymization/make-estimates.js
+++ /dev/null
@@ -1,227 +0,0 @@
-window.makeEstimates = function(){ 
-  var estimateScale = d3.scaleLinear()
-    .domain([.5 - .15, .5 + .15]).range([0, c.width])
-    .interpolate(d3.interpolateRound)
-
-  var jitterHeight = 90
-  var rs = 4 // rect size
-
-  var estimates = students[0].coinVals.map(d => ({val: .5, pctHead: .25, x: c.width/2, y: c.height - jitterHeight/2}))
-  var simulation = d3.forceSimulation(estimates)
-    .force('collide', d3.forceCollide(rs).strength(.1))
-    .stop()
-
-  function updateEstimates(){
-    var selectedStudents = students.all.slice(0, sliders.population)
-    
-    selectedStudents[0].coinVals.map((_, i) => {
-      estimates[i].pctHead = d3.mean(selectedStudents, d => (d.coinVals[i] < sliders.headsProb) || d.plagerized)
-
-      estimates[i].val = (1 - estimates[i].pctHead)/(1 - sliders.headsProb)
-    })
-    updateSimulation(60)
-  }  
-  updateEstimates()
-
-  function updateSimulation(ticks=80, yStrength=.005){
-    var variance = d3.variance(estimates, d => d.val)
-    var xStength = variance < .0005 ? .3 : .1
-
-    estimates.forEach(d => d.targetX = estimateScale(d.val))
-
-    simulation
-      .force('x', d3.forceX(d => d.targetX).strength(xStength))
-      .force('y', d3.forceY(c.height - jitterHeight/2).strength(yStrength))
-      .alpha(1)
-      // .alphaDecay(1 - Math.pow(0.001, 1/ticks))
-
-    for (var i = 0; i < ticks; ++i) simulation.tick()
-
-    estimates.forEach(d => {
-      d.x = Math.round(d.x)
-      d.y = Math.round(d.y)
-    })
-  }
-  updateSimulation(80, 1)
-  updateSimulation(80, .005)
-
-
-  // Set up DOM 
-  var histogramSel = c.svg.append('g').translate([0, -25])
-  var axisSel = histogramSel.append('g.axis.state.init-hidden')
-  var histogramAxis = axisSel.append('g')
-
-  var numTicks = 6
-  var xAxis = d3.axisTop(estimateScale).ticks(numTicks).tickFormat(d3.format('.0%')).tickSize(100)
-
-  histogramAxis.call(xAxis).translate([.5, c.height + 5])
-  middleTick = histogramAxis.selectAll('g').filter((d, i) => i === 3)
-  middleTick.select('text').classed('bold', 1)
-  middleTick.select('line').st({stroke: '#000'})
-  
-  histogramAxis.append('text.bold')
-    .text('actual non-plagiarism rate')
-    .translate([c.width/2, 11])
-    .st({fontSize: '10px'})
-
-  var containerSel = histogramSel.append('g#histogram').translate([0.5, .5])
-
-
-  // Selection overlay to highlight individual estimates.
-  var selectSize = rs*2 + 2
-  var selectColor = '#007276'
-  var rectFill = '#007276'
-
-  var activeSel = histogramSel.append('g.active.init-hidden.axis')
-    .st({pointerEvents: 'none'})
-
-  activeSel.append('rect')
-    .at({width: selectSize, height: selectSize, stroke: selectColor, fill: 'none', strokeWidth: 3})
-    .translate([-selectSize/2, -selectSize/2])
-
-  var activeTextHighlight = activeSel.append('rect')
-    .at({x: -32, width: 32*2, height: 18, y: -25, fill: 'rgba(255,255,255,.6)', rx: 10, ry: 10, xfill: 'red'})
-
-  var activeTextSel = activeSel.append('text.est-text.bold')
-    .text('34%')
-    .at({textAnchor: 'middle', textAnchor: 'middle', y: '-1em'})
-    .st({fill: selectColor})
-
-  var activePathSel = activeSel.append('path')
-    .st({stroke: selectColor, strokeWidth: 3})
-
-
-  // Update highlight DOM with current highlight
-  var curDrawData = {pctHead: .25, val: .5, x: c.width/2, y: c.height - jitterHeight/2}
-  function setActive(active, dur=0){
-    if (active !== estimates.active){
-      estimates.forEach(d => {
-        d.active = d == active
-        d.fy = d.active ? d.y : null
-      })
-      estimates.active = active
-    }
-
-    students.updateHeadsPos()
-
-
-    sel.flipCircle
-      .transition().duration(0).delay(d => d.i*5*(dur > 0 ? 1 : 0))
-      .at({transform: d => slides && slides.curSlide && slides.curSlide.showFlipCircle && d.coinVals[active.index] < sliders.headsProb ? 
-        'scale(1)' : 'scale(.1)'})
-
-
-    flipCoinTimer.stop()
-    if (dur){
-      var objI = d3.interpolateObject(curDrawData, active)
-
-      flipCoinTimer = d3.timer(ms => {
-        var t = d3.easeCubicInOut(d3.clamp(0, ms/dur, 1))
-        drawData(objI(t))
-        if (t == 1) flipCoinTimer.stop()
-      })
-    } else{
-      drawData(active)
-    }
-    
-    function drawData({pctHead, val, x, y}){
-      activeSel.translate([x + rs/2, y + rs/2])
-      activeTextSel.text('est. ' + d3.format('.1%')(val))
-      activePathSel.at({d: `M ${selectSize/2*Math.sign(c.width/2 - x)} -1 H ${c.width/2 - x}`})
-
-      var error = Math.abs(val - .5)
-      var fmt = d3.format(".1%")
-      var pop = sliders.population
-      d3.select('.rand-text')
-        // .html(`${fmt(1 - pctHead)} of students said they had never plagerized. Since about half the students flipped heads and automatically reported plagerizism, we double that to <span class='highlight square blue-box box'>estimate ${fmt(val)}</span> of students haven't plagerized—${error > .1 ? '' : error > .07 ? 'a little ' : 'not '}far from the actual rate of ${fmt(.5)}`)
-        // .html(`${Math.round((1 - pctHead)*pop)} of ${pop} students said they had never plagiarized. Since about half the students flipped heads and automatically reported plagiarism, we double that rate to <span class='highlight square blue-box box'>estimate ${fmt(val)}</span> of students haven't plagiarized—${error > .4 ? '' : error > .07 ? 'a little ' : 'not '}far from the actual rate of ${fmt(.5)}`)
-        .html(`Here, ${fmt(1 - pctHead)} students said they had never plagiarized. Doubling that, we <span class='highlight square blue-box box'>estimate ${fmt(val)}</span> of students haven't plagiarized—${error > .1 ? 'quite ' : error > .07 ? 'a little ' : 'not '}far from the actual rate of ${fmt(.5)}`)
-
-      curDrawData = {pctHead, val, x, y}
-    }
-  }
-  window.flipCoinTimer = d3.timer(d => d)
-
-
-
-  var estimateSel = containerSel.appendMany('rect.estimate', estimates)
-    .at({width: rs, height: rs, stroke: '#fff', fill: rectFill, strokeWidth: .5})
-    .st({fill: rectFill})
-    .translate([rs/2, rs/2])
-    .on('mouseover', (d, i) => {
-      if (window.slides.curSlide.showHistogram) {
-        setActive(d)
-      }
-    })
-
-  function setSelectorOpacity(textOpacity, strokeOpacity) {
-    activeTextSel.st({opacity: textOpacity})
-    activeSel.st({opacity: strokeOpacity})
-    activePathSel.st({opacity: strokeOpacity})
-  }
-
-  function render(transition=false){
-    estimateSel.translate(d => [d.x, d.y])
-    setActive(estimates.active)
-
-    if (transition){
-      if (window.flipAllCoinsTimer) window.flipAllCoinsTimer.stop()
-      window.flipAllCoinsTimer = d3.timer(ms => {
-        var t = d3.easeExpIn(d3.clamp(0, ms/5000, 1), 20)
-        if (flipAllCoinsTimer.forceEnd) t = 1
-        
-        if (t > .028) {
-          setSelectorOpacity(textOpacity=0, strokeOpacity=0.7)
-        }
-
-        var index = Math.floor((estimates.length - 2)*t) + 1
-        estimateSel.classed('active', (d, i) => i <= index)
-
-        setActive(estimates[index])
-        // flipCoinsSel.text('Flip coins ' + d3.format('03')(index < 100 ? index : index + 1) + ' times')
-        flipCoinsSel.text('Flip coins 200 times')
-
-        if (t == 1) {
-          flipAllCoinsTimer.stop()
-          setSelectorOpacity(textOpacity=1, strokeOpacity=1)
-        }
-      })
-    } else {
-      setSelectorOpacity(textOpacity=1, strokeOpacity=1)
-      flipCoinsSel
-    }   
-  }
-  window.flipAllCoinsTimer = d3.timer(d => d)
-
-
-  var flipCoinsSel = d3.select('.flip-coins').on('click', () => {
-    students.all.forEach(student => {
-      student.coinVals = student.coinVals.map(j => Math.random())
-    })
-
-    updateEstimates()
-    render(true)
-  })
-
-  d3.select('.flip-coins-once').on('click', flipCoin)
-  function flipCoin(){
-    active = estimates[0]
-
-    students.all.forEach(student => {
-      student.coinVals = student.coinVals.map(j => Math.random())
-    })
-
-    active.fy = active.y = c.height - jitterHeight/2
-    updateEstimates()
-
-    estimateSel.translate(d => [d.x, d.y])
-    estimates.active = null
-    setActive(active, 1000)
-  }
-
-  Object.assign(estimates, {updateEstimates, setActive, render, flipCoin, axisSel, containerSel, estimateSel, activeSel})
-
-  return estimates
-} 
-    
-if (window.init) window.init()
\ No newline at end of file
diff --git a/spaces/metricspace/OcTra/df_local/__init__.py b/spaces/metricspace/OcTra/df_local/__init__.py
deleted file mode 100644
index abcccd3f005af7532a9337f8cb6a9a7e410a6ff4..0000000000000000000000000000000000000000
--- a/spaces/metricspace/OcTra/df_local/__init__.py
+++ /dev/null
@@ -1,3 +0,0 @@
-from .config import config
-
-__all__ = ["config"]
diff --git a/spaces/mfrashad/ClothingGAN/models/stylegan/stylegan_tf/metrics/metric_base.py b/spaces/mfrashad/ClothingGAN/models/stylegan/stylegan_tf/metrics/metric_base.py
deleted file mode 100644
index 0db82adecb60260393eaf82bd991575d79085787..0000000000000000000000000000000000000000
--- a/spaces/mfrashad/ClothingGAN/models/stylegan/stylegan_tf/metrics/metric_base.py
+++ /dev/null
@@ -1,142 +0,0 @@
-# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
-#
-# This work is licensed under the Creative Commons Attribution-NonCommercial
-# 4.0 International License. To view a copy of this license, visit
-# http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to
-# Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.
-
-"""Common definitions for GAN metrics."""
-
-import os
-import time
-import hashlib
-import numpy as np
-import tensorflow as tf
-import dnnlib
-import dnnlib.tflib as tflib
-
-import config
-from training import misc
-from training import dataset
-
-#----------------------------------------------------------------------------
-# Standard metrics.
-
-fid50k = dnnlib.EasyDict(func_name='metrics.frechet_inception_distance.FID', name='fid50k', num_images=50000, minibatch_per_gpu=8)
-ppl_zfull = dnnlib.EasyDict(func_name='metrics.perceptual_path_length.PPL', name='ppl_zfull', num_samples=100000, epsilon=1e-4, space='z', sampling='full', minibatch_per_gpu=16)
-ppl_wfull = dnnlib.EasyDict(func_name='metrics.perceptual_path_length.PPL', name='ppl_wfull', num_samples=100000, epsilon=1e-4, space='w', sampling='full', minibatch_per_gpu=16)
-ppl_zend = dnnlib.EasyDict(func_name='metrics.perceptual_path_length.PPL', name='ppl_zend', num_samples=100000, epsilon=1e-4, space='z', sampling='end', minibatch_per_gpu=16)
-ppl_wend = dnnlib.EasyDict(func_name='metrics.perceptual_path_length.PPL', name='ppl_wend', num_samples=100000, epsilon=1e-4, space='w', sampling='end', minibatch_per_gpu=16)
-ls = dnnlib.EasyDict(func_name='metrics.linear_separability.LS', name='ls', num_samples=200000, num_keep=100000, attrib_indices=range(40), minibatch_per_gpu=4)
-dummy = dnnlib.EasyDict(func_name='metrics.metric_base.DummyMetric', name='dummy') # for debugging
-
-#----------------------------------------------------------------------------
-# Base class for metrics.
-
-class MetricBase:
-    def __init__(self, name):
-        self.name = name
-        self._network_pkl = None
-        self._dataset_args = None
-        self._mirror_augment = None
-        self._results = []
-        self._eval_time = None
-
-    def run(self, network_pkl, run_dir=None, dataset_args=None, mirror_augment=None, num_gpus=1, tf_config=None, log_results=True):
-        self._network_pkl = network_pkl
-        self._dataset_args = dataset_args
-        self._mirror_augment = mirror_augment
-        self._results = []
-
-        if (dataset_args is None or mirror_augment is None) and run_dir is not None:
-            run_config = misc.parse_config_for_previous_run(run_dir)
-            self._dataset_args = dict(run_config['dataset'])
-            self._dataset_args['shuffle_mb'] = 0
-            self._mirror_augment = run_config['train'].get('mirror_augment', False)
-
-        time_begin = time.time()
-        with tf.Graph().as_default(), tflib.create_session(tf_config).as_default(): # pylint: disable=not-context-manager
-            _G, _D, Gs = misc.load_pkl(self._network_pkl)
-            self._evaluate(Gs, num_gpus=num_gpus)
-        self._eval_time = time.time() - time_begin
-
-        if log_results:
-            result_str = self.get_result_str()
-            if run_dir is not None:
-                log = os.path.join(run_dir, 'metric-%s.txt' % self.name)
-                with dnnlib.util.Logger(log, 'a'):
-                    print(result_str)
-            else:
-                print(result_str)
-
-    def get_result_str(self):
-        network_name = os.path.splitext(os.path.basename(self._network_pkl))[0]
-        if len(network_name) > 29:
-            network_name = '...' + network_name[-26:]
-        result_str = '%-30s' % network_name
-        result_str += ' time %-12s' % dnnlib.util.format_time(self._eval_time)
-        for res in self._results:
-            result_str += ' ' + self.name + res.suffix + ' '
-            result_str += res.fmt % res.value
-        return result_str
-
-    def update_autosummaries(self):
-        for res in self._results:
-            tflib.autosummary.autosummary('Metrics/' + self.name + res.suffix, res.value)
-
-    def _evaluate(self, Gs, num_gpus):
-        raise NotImplementedError # to be overridden by subclasses
-
-    def _report_result(self, value, suffix='', fmt='%-10.4f'):
-        self._results += [dnnlib.EasyDict(value=value, suffix=suffix, fmt=fmt)]
-
-    def _get_cache_file_for_reals(self, extension='pkl', **kwargs):
-        all_args = dnnlib.EasyDict(metric_name=self.name, mirror_augment=self._mirror_augment)
-        all_args.update(self._dataset_args)
-        all_args.update(kwargs)
-        md5 = hashlib.md5(repr(sorted(all_args.items())).encode('utf-8'))
-        dataset_name = self._dataset_args['tfrecord_dir'].replace('\\', '/').split('/')[-1]
-        return os.path.join(config.cache_dir, '%s-%s-%s.%s' % (md5.hexdigest(), self.name, dataset_name, extension))
-
-    def _iterate_reals(self, minibatch_size):
-        dataset_obj = dataset.load_dataset(data_dir=config.data_dir, **self._dataset_args)
-        while True:
-            images, _labels = dataset_obj.get_minibatch_np(minibatch_size)
-            if self._mirror_augment:
-                images = misc.apply_mirror_augment(images)
-            yield images
-
-    def _iterate_fakes(self, Gs, minibatch_size, num_gpus):
-        while True:
-            latents = np.random.randn(minibatch_size, *Gs.input_shape[1:])
-            fmt = dict(func=tflib.convert_images_to_uint8, nchw_to_nhwc=True)
-            images = Gs.run(latents, None, output_transform=fmt, is_validation=True, num_gpus=num_gpus, assume_frozen=True)
-            yield images
-
-#----------------------------------------------------------------------------
-# Group of multiple metrics.
-
-class MetricGroup:
-    def __init__(self, metric_kwarg_list):
-        self.metrics = [dnnlib.util.call_func_by_name(**kwargs) for kwargs in metric_kwarg_list]
-
-    def run(self, *args, **kwargs):
-        for metric in self.metrics:
-            metric.run(*args, **kwargs)
-
-    def get_result_str(self):
-        return ' '.join(metric.get_result_str() for metric in self.metrics)
-
-    def update_autosummaries(self):
-        for metric in self.metrics:
-            metric.update_autosummaries()
-
-#----------------------------------------------------------------------------
-# Dummy metric for debugging purposes.
-
-class DummyMetric(MetricBase):
-    def _evaluate(self, Gs, num_gpus):
-        _ = Gs, num_gpus
-        self._report_result(0.0)
-
-#----------------------------------------------------------------------------
diff --git a/spaces/miaomiaoren/vits-uma-genshin-honkai/README.md b/spaces/miaomiaoren/vits-uma-genshin-honkai/README.md
deleted file mode 100644
index 1c0aa069bfd980b6b45bb2bf62ff74bd9b0b61c2..0000000000000000000000000000000000000000
--- a/spaces/miaomiaoren/vits-uma-genshin-honkai/README.md
+++ /dev/null
@@ -1,11 +0,0 @@
----
-license: apache-2.0
-title: ' vits-uma-genshin-honkai'
-sdk: gradio
-sdk_version: 3.7
-emoji: 🐨
-colorTo: yellow
-pinned: false
-app_file: app.py
-duplicated_from: ikechan8370/vits-uma-genshin-honkai
----
diff --git a/spaces/middha/Torpedoes/app.py b/spaces/middha/Torpedoes/app.py
deleted file mode 100644
index b05527c112728925a3b20f08121a9837cfe82e7c..0000000000000000000000000000000000000000
--- a/spaces/middha/Torpedoes/app.py
+++ /dev/null
@@ -1,90 +0,0 @@
-import gradio as gr
-import os
-import logging
-
-from langchain.embeddings.openai import OpenAIEmbeddings
-from langchain.vectorstores import Chroma
-from langchain.text_splitter import CharacterTextSplitter
-from langchain.llms import OpenAI
-from langchain.chains import ConversationalRetrievalChain
-from langchain.document_loaders import DirectoryLoader
-
-logging.basicConfig(filename='./Logs/bot.log', level=logging.WARNING, format='%(asctime)s - %(levelname)s - %(message)s')
-
-
-txt_loader = DirectoryLoader('./LVE/', glob="**/*.txt")
-pdf_loader = DirectoryLoader('./LVE/', glob="**/*.pdf")
-doc_loader = DirectoryLoader('./LVE/', glob="**/*.docx")
-loaders = [pdf_loader, txt_loader, doc_loader]
-documents = []
-
-for loader in loaders:
-    documents.extend(loader.load())
-    
-print(f"Total # of documents: {len(documents)}")
-
-text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=0)
-documents = text_splitter.split_documents(documents)
-
-embeddings = OpenAIEmbeddings()
-vectorstore = Chroma.from_documents(documents, embeddings)
-
-from langchain.memory import ConversationBufferMemory
-#memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
-
-qa = ConversationalRetrievalChain.from_llm(OpenAI(temperature=0), vectorstore.as_retriever())
-
-#chat_history = []
-
-def submit_callback(user_message):
-    default_prompt = "For answers, refer to the provided content. If no answer is found, contact lveswim@gmail.com."
-    prompt = default_prompt + user_message
-    # Log the user's query at INFO level
-    logging.info(f"User Query: {user_message}")
-
-    input_data = {"question": prompt, "chat_history": []}  # Add an empty "chat_history" key
-    response = qa(input_data)
-
-    # Log the chatbot's response at INFO level
-    logging.info(f"Chatbot Response: {response['answer']}")
-    return response["answer"]
-
-
-iface = gr.Interface(
-    fn=submit_callback,
-    inputs=gr.inputs.Textbox(lines=2, label="Enter your query"),
-    outputs=gr.outputs.Textbox(label="Chatbot Response"),
-    #outputs=gr.outputs.HTML(label="Chatbot Response"),
-    title="LVE Torpedoes Chatbot",
-    layout="vertical",
-    description="Enter your query to chat with the LVET chatbot",
-    examples=[
-        ["What are the practice times for each age group ?"],
-        ["What are the required fields to set up a meet in Touchpad?"],
-        ["Dryland workout for swimmers ?"],
-        ["What are the eligibility criteria for the Mini Torpedoes program?"],
-        ["What is the eligibility to participate in the LVET Swim Team?"],
-        ["How many volunteer hours are required per family during the swim season?"],
-        ["How can I receive credit hours for the official training?"],
-        ["How are swimmers grouped for practice?"],
-        ["When do evaluations take place for new swimmers?"],
-        ["Who are LVET's Board Members"],
-        ["What are the regular season meets start times?"],
-        ["How can I contact LVET's Board Members?"],
-        ["What is the penalty for not meeting the required volunteer hours?"],
-        ["Volunteer Hours?"],
-        ["What types of events can a swimmer enter and how many?"],
-        ["How do I sign up for volunteer jobs to fulfill my volunteer hours?"],
-        ["Volunteer jobs that do not require certification or prior experience"],
-        ["What are the responsibilities of an Age Group Coordinator?"],
-        ["How do I commit my swimmer for meets/events?"],
-        ["How are timers distributed between the host and visiting teams in dual meets?"],
-        ["What happens if a watch malfunctions during an event?"],
-        ["What is the difference between the Divisional Meets and the All Star Meet?"],
-        ["What is the ODSL Scholarship Program and what's the award ?"]
-        
-    ],
-    theme="default"
-    
-)
-iface.launch()
\ No newline at end of file
diff --git a/spaces/mikegarts/lotr/app.py b/spaces/mikegarts/lotr/app.py
deleted file mode 100644
index dc41ac0eedd90f924026579bea705127301e3b6a..0000000000000000000000000000000000000000
--- a/spaces/mikegarts/lotr/app.py
+++ /dev/null
@@ -1,143 +0,0 @@
-import time
-import os
-import PIL
-import gradio as gr
-
-import torch
-import transformers
-# from transformers import AutoTokenizer, AutoModelForCausalLM
-from transformers import pipeline
-from transformers import pipeline
-from diffusers import StableDiffusionPipeline
-
-READ_TOKEN = os.environ.get('HF_ACCESS_TOKEN', None)
-
-
-# model_id = "runwayml/stable-diffusion-v1-5"
-# model_id = "CompVis/stable-diffusion-v1-4"
-model_id = "prompthero/openjourney"
-
-has_cuda = torch.cuda.is_available()
-
-if has_cuda:
-    pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16, revision="fp16", use_auth_token=READ_TOKEN)
-    device = "cuda"
-else:
-    pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=READ_TOKEN)
-    device = "cpu"
-    
-pipe.to(device)
-def safety_checker(images, clip_input):
-    return images, False
-pipe.safety_checker = safety_checker
-
-SAVED_CHECKPOINT = 'mikegarts/distilgpt2-lotr'
-text_generation_pipe = pipeline("text-generation", model=SAVED_CHECKPOINT)
-
-summarizer = pipeline("summarization")
-
-#######################################################
-
-#######################################################
-
-def generate(prompt):
-    res = text_generation_pipe(prompt,
-               max_length=140,
-               repetition_penalty=1.1)[0]['generated_text']
-
-    i=0
-    while res[-1] != '.' and i < 30:
-        res = text_generation_pipe(res, max_length=1)[0]['generated_text']
-        i += 1
-    return res
-
-def generate_story(prompt):
-    print(f'Prompt={prompt}')
-    story = generate(prompt=prompt)
-    summary = summarizer(story, min_length=5, max_length=15)[0]['summary_text'].split('.')[0]
-    return story, summary, gr.update(visible=True)
-
-def on_change_event(app_state):
-    if app_state and app_state['running'] and app_state['img']:
-        img = app_state['img']
-        step = app_state['step']
-        app_state['dots'] += 1
-        app_state['dots'] = app_state['dots'] % 10
-        message = app_state['status_msg'] + ' *' * app_state['dots']
-        return gr.update(value=app_state['img_list'], label='intermediate steps'), gr.update(value=message)
-    else:
-        return gr.update(label='images list'), gr.update(value='')
-
-with gr.Blocks() as demo:
-    
-    def generate_image(prompt, inference_steps, app_state):
-        app_state['running'] = True
-        app_state['img_list'] = []
-        app_state['status_msg'] = 'Starting'
-        def callback(step, ts, latents):
-            app_state['status_msg'] = f'Reconstructing an image from the latent state on step {step}'
-            latents = 1 / 0.18215 * latents
-            res = pipe.vae.decode(latents).sample
-            res = (res / 2 + 0.5).clamp(0, 1)
-            res = res.cpu().permute(0, 2, 3, 1).detach().numpy()
-            res = pipe.numpy_to_pil(res)[0]
-            app_state['img'] = res
-            app_state['step'] = step
-            app_state['img_list'].append(res)
-            app_state['status_msg'] = f'Generating step ({step + 1})'
-        
-        prompt = prompt + ' masterpiece charcoal pencil art lord of the rings illustration mdjrny-v4 style'
-        img = pipe(prompt, height=512, width=512, num_inference_steps=inference_steps, callback=callback, callback_steps=2)
-        app_state['running'] = False
-        app_state['img'] = None
-        app_state['status_msg'] = ''
-        app_state['dots'] = 0
-        return gr.update(value=img.images[0], label='Generated image')
-    
-    app_state = gr.State({'img': None, 
-                          'step':0, 
-                          'running':False,
-                          'status_msg': '',
-                          'img_list': [],
-                          'dots': 0
-                         })
-    title = gr.Markdown('## Lord of the rings app')
-    description = gr.Markdown(f'#### A Lord of the rings inspired app that combines text and image generation.'
-                              f' The language modeling is done by fine tuning distilgpt2 on the LOTR trilogy {SAVED_CHECKPOINT}.'
-                              f' The text2img model is {model_id}. The summarization is done using distilbart.')
-    prompt = gr.Textbox(label="Your prompt", value="Frodo took the sword and")
-    story = gr.Textbox(label="Your story")
-    summary = gr.Textbox(label="Summary")
-    
-    bt_make_text = gr.Button("Generate text")
-    bt_make_image = gr.Button(f"Generate an image (takes about 10-15 minutes on CPU).", visible=False)
-    
-    img_description = gr.Markdown('Image generation takes some time'
-                                  ' but here you can see what is generated from the latent state of the diffuser every few steps.'
-                                  ' Usually there is a significant improvement around step 12 that yields a much better image')
-    status_msg = gr.Markdown('')
-    
-    gallery = gr.Gallery()
-    image = gr.Image(label='Illustration for your story', show_label=True)
-
-    gallery.style(grid=[4])
-    
-    inference_steps = gr.Slider(5, 30, 
-                                value=20, 
-                                step=1, 
-                                visible=True,
-                                label=f"Num inference steps (more steps yields a better image but takes more time)")
-    
-    
-    bt_make_text.click(fn=generate_story, inputs=prompt, outputs=[story, summary, bt_make_image])
-    bt_make_image.click(fn=generate_image, inputs=[summary, inference_steps, app_state], outputs=image)
-    
-    eventslider = gr.Slider(visible=False)
-    dep = demo.load(on_change_event, app_state, [gallery, status_msg], every=5)
-    eventslider.change(fn=on_change_event, inputs=[app_state], outputs=[gallery, status_msg], every=5, cancels=[dep])
-    
-
-if READ_TOKEN:
-    demo.queue().launch()
-else:
-    demo.queue().launch(share=True, debug=True)
\ No newline at end of file
diff --git a/spaces/mikkoar/marco/src/lib/hooks/use-copy-to-clipboard.tsx b/spaces/mikkoar/marco/src/lib/hooks/use-copy-to-clipboard.tsx
deleted file mode 100644
index 62f7156dca246c46b213151af003a3a177977ccf..0000000000000000000000000000000000000000
--- a/spaces/mikkoar/marco/src/lib/hooks/use-copy-to-clipboard.tsx
+++ /dev/null
@@ -1,33 +0,0 @@
-'use client'
-
-import * as React from 'react'
-
-export interface useCopyToClipboardProps {
-  timeout?: number
-}
-
-export function useCopyToClipboard({
-  timeout = 2000
-}: useCopyToClipboardProps) {
-  const [isCopied, setIsCopied] = React.useState<Boolean>(false)
-
-  const copyToClipboard = (value: string) => {
-    if (typeof window === 'undefined' || !navigator.clipboard?.writeText) {
-      return
-    }
-
-    if (!value) {
-      return
-    }
-
-    navigator.clipboard.writeText(value).then(() => {
-      setIsCopied(true)
-
-      setTimeout(() => {
-        setIsCopied(false)
-      }, timeout)
-    })
-  }
-
-  return { isCopied, copyToClipboard }
-}
diff --git a/spaces/milyiyo/reimagine-it/captioning/utils/clipscore.py b/spaces/milyiyo/reimagine-it/captioning/utils/clipscore.py
deleted file mode 100644
index 0345140d9f7b47e37b3a895915a135e1441c907b..0000000000000000000000000000000000000000
--- a/spaces/milyiyo/reimagine-it/captioning/utils/clipscore.py
+++ /dev/null
@@ -1,396 +0,0 @@
-from transformers import CLIPModel, CLIPTokenizer
-import os
-import json
-import argparse
-from random import shuffle, seed
-import string
-# non-standard dependencies:
-import h5py
-from six.moves import cPickle
-import numpy as np
-import torch
-import torchvision.models as models
-import skimage.io
-
-from torchvision.transforms import Compose, Resize, CenterCrop, ToTensor, Normalize
-from PIL import Image
-from torch import nn
-
-
-class CLIPScore(nn.Module):
-    def __init__(self, clipscore_w=2.5, image_size=224, mode='clip_s', use_grammar=False, joint_out=False):
-        super(CLIPScore, self).__init__()
-        # from transformers import CLIPModel, CLIPTokenizer
-        self.clip_model = CLIPModel.from_pretrained(
-            'openai/clip-vit-base-patch32')
-        self.tokenizer = CLIPTokenizer.from_pretrained(
-            'openai/clip-vit-base-patch32')
-
-        self.clip_model.eval()
-
-        self.clipscore_w = clipscore_w
-
-        self.image_transform = self._transform(image_size)
-
-        self.mode = mode
-        assert mode in ['clip_s', 'refclip_s']
-
-        self.use_grammar = use_grammar
-        self.joint_out = joint_out
-
-        if self.use_grammar and joint_out is False:
-            self.grammar_score_head = nn.Sequential(
-                nn.Linear(self.clip_model.text_embed_dim, self.clip_model.projection_dim, bias=False),
-                nn.ReLU(),
-                nn.Linear(self.clip_model.projection_dim, 2, bias=False)
-            )
-
-    def _transform(self, n_px):
-        return Compose([
-            Resize(n_px, interpolation=Image.BICUBIC),
-            CenterCrop(n_px),
-            lambda image: image.convert("RGB"),
-            ToTensor(),
-            Normalize((0.48145466, 0.4578275, 0.40821073),
-                      (0.26862954, 0.26130258, 0.27577711)),
-        ])
-
-    def load_image(self, image_path):
-        image = Image.open(image_path)
-        return image
-
-    # @torch.no_grad()
-    def image_extract(self, image):
-        if isinstance(image, str):
-            image = self.load_image(image)
-        if not isinstance(image, torch.Tensor):
-            image = self.image_transform(image)
-
-        img_tensor = image.view(-1, 3, 224, 224)
-        device = next(self.clip_model.parameters()).device
-        img_tensor = img_tensor.to(device)
-
-        clip_model = self.clip_model
-
-        img_feat = clip_model.vision_model(img_tensor).pooler_output
-        img_feat = clip_model.visual_projection(img_feat)
-        img_feat = img_feat / img_feat.norm(dim=-1, keepdim=True)
-
-        return img_feat
-
-    # @torch.no_grad()
-    def text_extract(self, text, prompt="A photo depicts", proj_norm=True):
-        if isinstance(text, str):
-            text_batch = [" ".join([prompt, text])]
-        elif isinstance(text, list):
-            text_batch = [" ".join([prompt, txt]) for txt in text]
-        
-        if isinstance(text, tuple) and isinstance(text[0], torch.Tensor):
-            input_ids, attention_mask = text
-        else:
-            input_text = text_batch
-
-            tokenized = self.tokenizer(
-                input_text, return_tensors='pt', padding=True, truncation=True)
-
-            input_ids = tokenized.input_ids
-            attention_mask = tokenized.attention_mask
-
-        clip_model = self.clip_model
-        device = next(self.clip_model.parameters()).device
-        input_ids = input_ids.to(device)
-        attention_mask = attention_mask.to(device)
-
-        text_feat = clip_model.text_model(input_ids, attention_mask).pooler_output
-
-        if proj_norm:
-            text_feat = clip_model.text_projection(text_feat)
-            text_feat = text_feat / text_feat.norm(dim=-1, keepdim=True)
-
-        return text_feat
-
-    # @torch.no_grad()
-    def calc_clip_s(self, img_feat, text_feat):
-        return self.clipscore_w * torch.relu((img_feat * text_feat).sum(dim=-1))
-
-    # @torch.no_grad()
-    def calc_refclip_s(self, img_feat=None, text_feat=None, ref_text_feat=None, ref_text_mask=None, clip_s=None):
-
-        if clip_s is None:
-            clip_s = self.calc_clip_s(img_feat, text_feat)
-
-        B, dim = img_feat.size()
-
-        ref_text_feat = ref_text_feat.view(B, -1, dim)
-
-        K = ref_text_feat.size(1)
-
-        text_feat = text_feat.view(B, 1, dim).expand(-1, K, -1)
-        assert ref_text_feat.size() == text_feat.size(
-        ), (ref_text_feat.size(), text_feat.size())
-
-        ref_score = self.calc_clip_s(text_feat, ref_text_feat)
-        if ref_text_mask is not None:
-            if not isinstance(ref_text_mask, torch.Tensor):
-                ref_text_mask = torch.tensor(
-                    ref_text_mask, dtype=ref_score.dtype, device=ref_score.device)
-            ref_score = ref_score.view(B, K) * ref_text_mask.view(B, K)
-
-        ref_score = ref_score.view(B, K).max(dim=1).values
-
-        assert clip_s.size() == (B,)
-        assert clip_s.size() == ref_score.size()
-
-        # harmonic mean
-        refclip_s = 2 / (1 / clip_s + 1 / ref_score)
-        return refclip_s
-
-    @torch.no_grad()
-    def forward(self,
-                images=None, text=None,
-                img_feat=None, text_feat=None,
-                ref_text=None, ref_text_feat=None, ref_text_mask=None,
-                prompt="A photo depicts",
-                mode=None):
-        if img_feat is None:
-            img_feat = self.image_extract(images)
-        img_feat = img_feat.view(-1, 512)
-
-        B = img_feat.size(0)
-
-        if text_feat is None:
-            text_feat = self.text_extract(text, prompt=prompt)
-        text_feat = text_feat.view(-1, 512)
-
-        if mode is None:
-            mode = self.mode
-        assert mode in ['clip_s', 'refclip_s']
-
-        if mode == 'clip_s':
-            clip_s = self.calc_clip_s(img_feat, text_feat)
-            return clip_s
-        elif mode == 'refclip_s':
-            if ref_text_feat is None:
-                ref_text_feat = self.text_extract(ref_text, prompt=prompt)
-            ref_text_feat = ref_text_feat.view(-1, 512)
-
-            refclip_s = self.calc_refclip_s(
-                img_feat, text_feat, ref_text_feat, ref_text_mask=ref_text_mask)
-            return refclip_s
-
-
-    def train_step(self,
-                   images=None, text=None,
-                   img_feat=None, text_feat=None,
-                   neg_text=None, neg_text_feat=None,
-                #    ref_text=None, ref_text_feat=None, ref_text_mask=None,
-                   prompt="A photo depicts",
-                #    return_loss=True,
-                   **kwargs):
-
-        if img_feat is None:
-            img_feat = self.image_extract(images)
-        img_feat = img_feat.view(-1, 512)
-
-        B = img_feat.size(0)
-
-        if text_feat is None:
-            text_feat = self.text_extract(text, prompt=prompt, proj_norm=False)
-
-            text_cont_feat = self.clip_model.text_projection(text_feat)
-            text_cont_feat = text_cont_feat / text_cont_feat.norm(dim=-1, keepdim=True)
-        text_cont_feat = text_cont_feat.view(B, 512)
-
-        # cosine similarity as logits
-        logit_scale = self.clip_model.logit_scale.exp()
-        logits_per_text = torch.matmul(text_cont_feat, img_feat.t()) * logit_scale
-        # logits_per_image = logits_per_text.T
-
-        clip_loss = clip_loss_fn(logits_per_text)
-
-
-        # negative sampling
-        pos_text_feat = text_feat.view(B, 512)
-        neg_text_feat = self.text_extract(neg_text, prompt=prompt, proj_norm=False).view(B, 512)
-
-        grammar_text_feat = torch.cat([pos_text_feat, neg_text_feat], dim=0)
-
-        # 2B, 1
-        grammar_text_logit = self.grammar_score_head(grammar_text_feat)
-        grammar_labels = torch.LongTensor([1] * B + [0] * B).to(grammar_text_logit.device).view(2 * B)
-
-        grammar_loss = torch.nn.functional.cross_entropy(grammar_text_logit, grammar_labels)
-
-        grammar_pred = grammar_text_logit.argmax(dim=1, keepdim=False)
-        grammar_pos_pred = grammar_pred[:B]
-        grammar_neg_pred = grammar_pred[B:]
-        # grammar_acc = (grammar_pred == grammar_labels).float().mean()
-
-        out = {
-            'clip_loss': clip_loss,
-            'grammar_loss': grammar_loss,
-            'img_feat': img_feat,
-            'text_feat': text_cont_feat,
-            'neg_text_feat': neg_text_feat,
-            'grammar_pos_pred': grammar_pos_pred,
-            'grammar_neg_pred': grammar_neg_pred,
-        }
-
-        return out
-
-# contrastive loss function, adapted from
-# https://sachinruk.github.io/blog/pytorch/pytorch%20lightning/loss%20function/gpu/2021/03/07/CLIP.html
-def contrastive_loss(logits: torch.Tensor, dim: int) -> torch.Tensor:
-    neg_ce = torch.diag(nn.functional.log_softmax(logits, dim=dim))
-    return -neg_ce.mean()
-
-
-def clip_loss_fn(similarity: torch.Tensor) -> torch.Tensor:
-    caption_loss = contrastive_loss(similarity, dim=0)
-    image_loss = contrastive_loss(similarity, dim=1)
-    return (caption_loss + image_loss) / 2.0
-
-
-
-# class CLIPScore(nn.Module):
-#     def __init__(self, clipscore_w=2.5, image_size=224, mode='clip_s'):
-#         super(CLIPScore, self).__init__()
-#         # from transformers import CLIPModel, CLIPTokenizer
-#         self.clip_model = CLIPModel.from_pretrained(
-#             'openai/clip-vit-base-patch32')
-#         self.tokenizer = CLIPTokenizer.from_pretrained(
-#             'openai/clip-vit-base-patch32')
-
-#         self.clip_model.eval()
-
-#         self.clipscore_w = clipscore_w
-
-#         self.image_transform = self._transform(image_size)
-
-#         self.mode = mode
-#         assert mode in ['clip_s', 'refclip_s']
-
-#     def _transform(self, n_px):
-#         return Compose([
-#             Resize(n_px, interpolation=Image.BICUBIC),
-#             CenterCrop(n_px),
-#             lambda image: image.convert("RGB"),
-#             ToTensor(),
-#             Normalize((0.48145466, 0.4578275, 0.40821073),
-#                       (0.26862954, 0.26130258, 0.27577711)),
-#         ])
-
-#     def load_image(self, image_path):
-#         image = Image.open(image_path)
-#         return image
-
-#     @torch.no_grad()
-#     def image_extract(self, image):
-#         if isinstance(image, str):
-#             image = self.load_image(image)
-#         if not isinstance(image, torch.Tensor):
-#             image = self.image_transform(image)
-
-#         img_tensor = image.view(-1, 3, 224, 224)
-#         device = next(self.clip_model.parameters()).device
-#         img_tensor = img_tensor.to(device)
-
-#         clip_model = self.clip_model
-
-#         img_feat = clip_model.vision_model(img_tensor).pooler_output
-#         img_feat = clip_model.visual_projection(img_feat)
-#         img_feat = img_feat / img_feat.norm(dim=-1, keepdim=True)
-
-#         return img_feat
-
-#     @torch.no_grad()
-#     def text_extract(self, text, prompt="A photo depicts"):
-#         if isinstance(text, str):
-#             text_batch = [" ".join([prompt, text])]
-#         else:
-#             text_batch = [" ".join([prompt, txt]) for txt in text]
-        
-#         input_text = text_batch
-
-#         tokenized = self.tokenizer(
-#             input_text, return_tensors='pt', padding=True)
-
-#         input_ids = tokenized.input_ids
-#         attention_mask = tokenized.attention_mask
-
-#         clip_model = self.clip_model
-#         device = next(self.clip_model.parameters()).device
-#         input_ids = input_ids.to(device)
-#         attention_mask = attention_mask.to(device)
-
-#         text_feat = clip_model.text_model(input_ids, attention_mask).pooler_output
-#         text_feat = clip_model.text_projection(text_feat)
-#         text_feat = text_feat / text_feat.norm(dim=-1, keepdim=True)
-
-#         return text_feat
-
-#     @torch.no_grad()
-#     def calc_clip_s(self, img_feat, text_feat):
-#         return self.clipscore_w * torch.relu((img_feat * text_feat).sum(dim=-1))
-
-#     @torch.no_grad()
-#     def calc_refclip_s(self, img_feat=None, text_feat=None, ref_text_feat=None, ref_text_mask=None, clip_s=None):
-
-#         if clip_s is None:
-#             clip_s = self.calc_clip_s(img_feat, text_feat)
-
-#         B, dim = img_feat.size()
-
-#         ref_text_feat = ref_text_feat.view(B, -1, dim)
-
-#         K = ref_text_feat.size(1)
-
-#         text_feat = text_feat.view(B, 1, dim).expand(-1, K, -1)
-#         assert ref_text_feat.size() == text_feat.size(), (ref_text_feat.size(), text_feat.size())
-
-#         ref_score = self.calc_clip_s(text_feat, ref_text_feat)
-#         if ref_text_mask is not None:
-#             if not isinstance(ref_text_mask, torch.Tensor):
-#                 ref_text_mask = torch.tensor(ref_text_mask, dtype=ref_score.dtype, device=ref_score.device)
-#             ref_score = ref_score.view(B, K) * ref_text_mask.view(B, K)
-
-#         ref_score = ref_score.view(B, K).max(dim=1).values
-
-#         assert clip_s.size() == (B,)
-#         assert clip_s.size() == ref_score.size()
-
-#         # harmonic mean
-#         refclip_s = 2 / (1 / clip_s + 1 / ref_score)
-#         return refclip_s
-
-
-#     @torch.no_grad()
-#     def forward(self,
-#                 images=None, text=None,
-#                 img_feat=None, text_feat=None,
-#                 ref_text=None, ref_text_feat=None, ref_text_mask=None,
-#                 prompt="A photo depicts",
-#                 mode=None):
-#         if img_feat is None:
-#             img_feat = self.image_extract(images)
-#         img_feat = img_feat.view(-1, 512)
-
-#         if text_feat is None:
-#             text_feat = self.text_extract(text, prompt=prompt)
-#         text_feat = text_feat.view(-1, 512)
-
-#         if mode is None:
-#             mode = self.mode
-#         assert mode in ['clip_s', 'refclip_s']
-
-#         if mode == 'clip_s':
-#             clip_s = self.calc_clip_s(img_feat, text_feat)
-#             return clip_s
-#         elif mode == 'refclip_s':
-#             if ref_text_feat is None:
-#                 ref_text_feat = self.text_extract(ref_text, prompt=prompt)
-#             ref_text_feat = ref_text_feat.view(-1, 512)
-
-#             refclip_s = self.calc_refclip_s(img_feat, text_feat, ref_text_feat, ref_text_mask=ref_text_mask)
-#             return refclip_s
-    
diff --git a/spaces/mishtert/tracer/app.py b/spaces/mishtert/tracer/app.py
deleted file mode 100644
index 5e810086d4a535e6f23aafec6c5675836da30ae3..0000000000000000000000000000000000000000
--- a/spaces/mishtert/tracer/app.py
+++ /dev/null
@@ -1,245 +0,0 @@
-import streamlit as st
-
-import meta
-import fitz
-import requests
-from bs4 import BeautifulSoup
-
-from best_seller import get_items
-from pharmap_url import get_link_mapped
-from summarize import get_summary_app
-from results_utils import get_brief, ReadPDFFile, PopulateDict
-from utils import load_image_from_local, local_css, pure_comma_separation, remote_css
-from examples import CATEGORY_LIST, LINK_LIST, STUDY_LIST, FILE_LIST
-
-with open("bestseller.html", "r") as f:
-	html_content = f.read()
-
-# html_content[:500]
-
-
-
-
-
-def main():
-	st.set_page_config(
-		page_title="Tracer",
-		page_icon="‍👻",
-		layout="wide",
-		initial_sidebar_state="expanded"
-	)
-	remote_css("https://fonts.googleapis.com/css2?family=Montserrat:wght@400;600&family=Poppins:wght@600&display=swap")
-	local_css("asset/css/style.css")
-
-	col1, col2 = st.columns([5, 5])
-	with col2:
-		# st.image(load_image_from_local("asset/images/main_logo.png"), width=300)
-		# st.markdown("Discover --> Extract --> Sense --> Decide --> Render", unsafe_allow_html=True)
-		st.image(load_image_from_local("asset/images/task_theme.png"), width=500)
-		with st.expander("Design & Development", expanded=True):
-			st.markdown(meta.SIDEBAR_INFO, unsafe_allow_html=True)
-
-		with st.expander("What does Tracer do?", expanded=True):
-			st.markdown(meta.STORY, unsafe_allow_html=True)
-
-		st.markdown(meta.CONCEPT_INFO, unsafe_allow_html=True)
-		st.image(load_image_from_local("asset/images/side_bar.png"), width=600)
-
-	with col1:
-		st.markdown(meta.HEADER_INFO, unsafe_allow_html=True)
-
-		st.markdown(meta.CHEF_INFO, unsafe_allow_html=True)
-
-		# st.write('<style>div.row-widget.stRadio > div{flex-direction:row;justify-content: center;} </style>',
-		#          unsafe_allow_html=True)
-		#
-		# st.write('<style>div.st-bf{flex-direction:column;} div.st-ag{font-weight:bold;padding-left:2px;}</style>',
-		#          unsafe_allow_html=True)
-
-		choose = st.radio("Choose Task", ("Get Best Sellers - Amazon",
-		                                  "Get Therapy Area Mapped for Given Disease/s",
-		                                  "Generate Summary for Clinical Trials",
-		                                  "Generate Financial Brief for given 10-Q file"))
-
-		if choose == 'Get Best Sellers - Amazon':
-
-			content = BeautifulSoup(html_content, "html.parser")
-			mydivs = content.find_all("a", {"class": "a-link-normal"})
-			bs = get_items(mydivs)
-
-			prompts = list(CATEGORY_LIST.keys()) + ["Custom"]
-			prompt = st.selectbox(
-				'Examples (select from this list)',
-				prompts,
-				# index=len(prompts) - 1,
-				index=0,
-
-			)
-
-			if prompt == "Custom":
-				prompt_box = ""
-			else:
-				prompt_box = CATEGORY_LIST[prompt]
-
-			items = st.text_area(
-				'Selected Best Seller Category: ',
-				prompt_box,
-
-			)
-			# items = pure_comma_separation(items, return_list=False)
-			entered_items = st.empty()
-			result_button = st.button('Get Best Selling Items!')
-
-			st.markdown(
-				"<hr />",
-				unsafe_allow_html=True
-			)
-
-
-			if result_button:
-				with st.spinner("Getting the best sellers"):
-					st.write(items)
-					st.write(bs[items])
-
-		if choose == 'Get Therapy Area Mapped for Given Disease/s':
-
-			prompts = list(LINK_LIST.keys()) + ["Custom"]
-			prompt = st.selectbox(
-				'Examples (select from this list)',
-				prompts,
-				# index=len(prompts) - 1,
-				index=0
-			)
-
-			if prompt == "Custom":
-				prompt_box = ""
-			else:
-				prompt_box = LINK_LIST[prompt]
-
-			items = st.text_area(
-				'Selected Sample Webpage Link: ',
-				prompt_box,
-			)
-			# items = pure_comma_separation(items, return_list=False)
-			entered_items = st.empty()
-			result_button = st.button('Get Therapy Areas!')
-
-			st.markdown(
-				"<hr />",
-				unsafe_allow_html=True
-			)
-
-			if result_button:
-				get_link_mapped(items)
-
-		if choose == 'Generate Summary for Clinical Trials':
-
-			prompts = list(STUDY_LIST.keys()) + ["Custom"]
-			prompt = st.selectbox(
-				'Examples (select from this list)',
-				prompts,
-				# index=len(prompts) - 1,
-				index=0
-			)
-
-			if prompt == "Custom":
-				prompt_box = ""
-			else:
-				prompt_box = STUDY_LIST[prompt]
-
-			items = st.text_area(
-				'Selected Sample Study ID (Clinical Trial.Gov): ',
-				prompt_box,
-			)
-			# items = pure_comma_separation(items, return_list=False)
-			# st.write(items)
-			entered_items = st.empty()
-			result_button = st.button('Get Summary!')
-
-			st.markdown(
-				"<hr />",
-				unsafe_allow_html=True
-			)
-
-			if result_button:
-				headline_output, summary_output = get_summary_app(items)
-
-				# headline = f"""
-				# <p class="story-box font-body">{headline_output}</p>
-				# """
-				# summary = f"""
-				# <p class="story-box font-body">{summary_output}</p>
-				# """
-				# st.markdown(summary, unsafe_allow_html=True)
-
-				# st.write(headline_output)
-				st.write(summary_output)
-
-		if choose == 'Generate Financial Brief for given 10-Q file':
-
-			prompts = list(FILE_LIST.keys()) + ["Custom"]
-			prompt = st.selectbox(
-				'Examples (select from this list)',
-				prompts,
-				# index=len(prompts) - 1,
-				index=0
-			)
-			if prompt == "Custom":
-				file = st.file_uploader("Choose a file")
-				uploaded_file  = open(file, 'rb')
-				doc = fitz.open(uploaded_file)
-				result_button = st.button('Get Earnings Brief!')
-
-				st.markdown(
-					"<hr />",
-					unsafe_allow_html=True
-				)
-				print("before custom result button")
-				if result_button and uploaded_file is not None:
-					with st.spinner("Generating Brief..."):
-						DictText = {}
-						Extracttext = ReadPDFFile(doc, 19, "(Dollars in millions except per share amounts)", "")
-						DictText = PopulateDict(Extracttext, DictText)
-						Extracttext = ReadPDFFile(doc, 20, "Overview (continued)",
-						                          "Results may not sum due to rounding")
-						DictText = PopulateDict(Extracttext, DictText)
-						Extracttext = ReadPDFFile(doc, 21, "(Dollars in millions)", "Three months ended")
-						DictText = PopulateDict(Extracttext, DictText)
-						# st.write(DictText)
-						st.write(get_brief(DictText))
-
-			else:
-				prompt_box = FILE_LIST[prompt]
-
-				items = st.text_area(
-					'Selected File Name: ',
-					prompt_box,
-				)
-				# items = pure_comma_separation(items, return_list=False)
-				# st.write(items)
-				entered_items = st.empty()
-				result_button = st.button('Get Earnings Brief!')
-
-				st.markdown(
-					"<hr />",
-					unsafe_allow_html=True
-				)
-
-				if result_button:
-					uploaded_file = open("asset/data/TF-Q1'22-10Q.pdf", 'rb')
-					doc = fitz.open(uploaded_file)
-					with st.spinner("Generating Brief..."):
-						DictText = {}
-						Extracttext = ReadPDFFile(doc, 19, "(Dollars in millions except per share amounts)", "")
-						DictText = PopulateDict(Extracttext, DictText)
-						Extracttext = ReadPDFFile(doc, 20, "Overview (continued)",
-						                          "Results may not sum due to rounding")
-						DictText = PopulateDict(Extracttext, DictText)
-						Extracttext = ReadPDFFile(doc, 21, "(Dollars in millions)", "Three months ended")
-						DictText = PopulateDict(Extracttext, DictText)
-						# st.write(DictText)
-						st.write(get_brief(DictText))
-
-
-if __name__ == '__main__':
-	main()
\ No newline at end of file
diff --git a/spaces/mshukor/UnIVAL/slurm_adastra/averaging/branching/caption/video/ofa_mini_video_caption_stage_1_bart_pretrain_branchimvid.sh b/spaces/mshukor/UnIVAL/slurm_adastra/averaging/branching/caption/video/ofa_mini_video_caption_stage_1_bart_pretrain_branchimvid.sh
deleted file mode 100644
index dcbd1c71ce2491714722ad436ffd2090ec144680..0000000000000000000000000000000000000000
--- a/spaces/mshukor/UnIVAL/slurm_adastra/averaging/branching/caption/video/ofa_mini_video_caption_stage_1_bart_pretrain_branchimvid.sh
+++ /dev/null
@@ -1,29 +0,0 @@
-#!/bin/bash
-   
-#SBATCH --job-name=ofa_mini_video_caption_stage_1_bart_pretrain_branchimvid
-#SBATCH --nodes=1
-#SBATCH --ntasks=1
-#SBATCH --gpus=8
-#SBATCH --threads-per-core=2
-#SBATCH --gpu-bind=closest 
-#SBATCH -C MI250
-#SBATCH -A gda2204
-#SBATCH --time=24:00:00
-#SBATCH --mail-type=END,FAIL
-#SBATCH --output=/lus/home/NAT/gda2204/mshukor/logs/slurm/ofa_mini_video_caption_stage_1_bart_pretrain_branchimvid.out
-#SBATCH --exclusive
-#SBATCH --mail-user=mustafa.shukor@isir.upmc.fr
-
-
-cd /lus/home/NAT/gda2204/mshukor/code/ofa_ours/run_scripts
-source /lus/home/NAT/gda2204/mshukor/.bashrc
-
-conda activate main
- 
-
-rm core-python3*
-
-
-srun -l -N 1 -n 1 -c 128 --gpus=8 bash averaging/branching/caption/video/ofa_mini_video_caption_stage_1_bart_pretrain_branchimvid.sh
-
-
diff --git a/spaces/mthsk/sovits-models/modules/crepe.py b/spaces/mthsk/sovits-models/modules/crepe.py
deleted file mode 100644
index 0bff0e3474de6483290b56993f9b845e91ef9702..0000000000000000000000000000000000000000
--- a/spaces/mthsk/sovits-models/modules/crepe.py
+++ /dev/null
@@ -1,327 +0,0 @@
-from typing import Optional,Union
-try:
-    from typing import Literal
-except Exception as e:
-    from typing_extensions import Literal
-import numpy as np
-import torch
-import torchcrepe
-from torch import nn
-from torch.nn import functional as F
-import scipy
-
-#from:https://github.com/fishaudio/fish-diffusion
-
-def repeat_expand(
-    content: Union[torch.Tensor, np.ndarray], target_len: int, mode: str = "nearest"
-):
-    """Repeat content to target length.
-    This is a wrapper of torch.nn.functional.interpolate.
-
-    Args:
-        content (torch.Tensor): tensor
-        target_len (int): target length
-        mode (str, optional): interpolation mode. Defaults to "nearest".
-
-    Returns:
-        torch.Tensor: tensor
-    """
-
-    ndim = content.ndim
-
-    if content.ndim == 1:
-        content = content[None, None]
-    elif content.ndim == 2:
-        content = content[None]
-
-    assert content.ndim == 3
-
-    is_np = isinstance(content, np.ndarray)
-    if is_np:
-        content = torch.from_numpy(content)
-
-    results = torch.nn.functional.interpolate(content, size=target_len, mode=mode)
-
-    if is_np:
-        results = results.numpy()
-
-    if ndim == 1:
-        return results[0, 0]
-    elif ndim == 2:
-        return results[0]
-
-
-class BasePitchExtractor:
-    def __init__(
-        self,
-        hop_length: int = 512,
-        f0_min: float = 50.0,
-        f0_max: float = 1100.0,
-        keep_zeros: bool = True,
-    ):
-        """Base pitch extractor.
-
-        Args:
-            hop_length (int, optional): Hop length. Defaults to 512.
-            f0_min (float, optional): Minimum f0. Defaults to 50.0.
-            f0_max (float, optional): Maximum f0. Defaults to 1100.0.
-            keep_zeros (bool, optional): Whether keep zeros in pitch. Defaults to True.
-        """
-
-        self.hop_length = hop_length
-        self.f0_min = f0_min
-        self.f0_max = f0_max
-        self.keep_zeros = keep_zeros
-
-    def __call__(self, x, sampling_rate=44100, pad_to=None):
-        raise NotImplementedError("BasePitchExtractor is not callable.")
-
-    def post_process(self, x, sampling_rate, f0, pad_to):
-        if isinstance(f0, np.ndarray):
-            f0 = torch.from_numpy(f0).float().to(x.device)
-
-        if pad_to is None:
-            return f0
-
-        f0 = repeat_expand(f0, pad_to)
-
-        if self.keep_zeros:
-            return f0
-        
-        vuv_vector = torch.zeros_like(f0)
-        vuv_vector[f0 > 0.0] = 1.0
-        vuv_vector[f0 <= 0.0] = 0.0
-        
-        # 去掉0频率, 并线性插值
-        nzindex = torch.nonzero(f0).squeeze()
-        f0 = torch.index_select(f0, dim=0, index=nzindex).cpu().numpy()
-        time_org = self.hop_length / sampling_rate * nzindex.cpu().numpy()
-        time_frame = np.arange(pad_to) * self.hop_length / sampling_rate
-
-        if f0.shape[0] <= 0:
-            return torch.zeros(pad_to, dtype=torch.float, device=x.device),torch.zeros(pad_to, dtype=torch.float, device=x.device)
-
-        if f0.shape[0] == 1:
-            return torch.ones(pad_to, dtype=torch.float, device=x.device) * f0[0],torch.ones(pad_to, dtype=torch.float, device=x.device)
-    
-        # 大概可以用 torch 重写?
-        f0 = np.interp(time_frame, time_org, f0, left=f0[0], right=f0[-1])
-        vuv_vector = vuv_vector.cpu().numpy()
-        vuv_vector = np.ceil(scipy.ndimage.zoom(vuv_vector,pad_to/len(vuv_vector),order = 0))
-        
-        return f0,vuv_vector
-
-
-class MaskedAvgPool1d(nn.Module):
-    def __init__(
-        self, kernel_size: int, stride: Optional[int] = None, padding: Optional[int] = 0
-    ):
-        """An implementation of mean pooling that supports masked values.
-
-        Args:
-            kernel_size (int): The size of the median pooling window.
-            stride (int, optional): The stride of the median pooling window. Defaults to None.
-            padding (int, optional): The padding of the median pooling window. Defaults to 0.
-        """
-
-        super(MaskedAvgPool1d, self).__init__()
-        self.kernel_size = kernel_size
-        self.stride = stride or kernel_size
-        self.padding = padding
-
-    def forward(self, x, mask=None):
-        ndim = x.dim()
-        if ndim == 2:
-            x = x.unsqueeze(1)
-
-        assert (
-            x.dim() == 3
-        ), "Input tensor must have 2 or 3 dimensions (batch_size, channels, width)"
-
-        # Apply the mask by setting masked elements to zero, or make NaNs zero
-        if mask is None:
-            mask = ~torch.isnan(x)
-
-        # Ensure mask has the same shape as the input tensor
-        assert x.shape == mask.shape, "Input tensor and mask must have the same shape"
-
-        masked_x = torch.where(mask, x, torch.zeros_like(x))
-        # Create a ones kernel with the same number of channels as the input tensor
-        ones_kernel = torch.ones(x.size(1), 1, self.kernel_size, device=x.device)
-
-        # Perform sum pooling
-        sum_pooled = nn.functional.conv1d(
-            masked_x,
-            ones_kernel,
-            stride=self.stride,
-            padding=self.padding,
-            groups=x.size(1),
-        )
-
-        # Count the non-masked (valid) elements in each pooling window
-        valid_count = nn.functional.conv1d(
-            mask.float(),
-            ones_kernel,
-            stride=self.stride,
-            padding=self.padding,
-            groups=x.size(1),
-        )
-        valid_count = valid_count.clamp(min=1)  # Avoid division by zero
-
-        # Perform masked average pooling
-        avg_pooled = sum_pooled / valid_count
-
-        # Fill zero values with NaNs
-        avg_pooled[avg_pooled == 0] = float("nan")
-
-        if ndim == 2:
-            return avg_pooled.squeeze(1)
-
-        return avg_pooled
-
-
-class MaskedMedianPool1d(nn.Module):
-    def __init__(
-        self, kernel_size: int, stride: Optional[int] = None, padding: Optional[int] = 0
-    ):
-        """An implementation of median pooling that supports masked values.
-
-        This implementation is inspired by the median pooling implementation in
-        https://gist.github.com/rwightman/f2d3849281624be7c0f11c85c87c1598
-
-        Args:
-            kernel_size (int): The size of the median pooling window.
-            stride (int, optional): The stride of the median pooling window. Defaults to None.
-            padding (int, optional): The padding of the median pooling window. Defaults to 0.
-        """
-
-        super(MaskedMedianPool1d, self).__init__()
-        self.kernel_size = kernel_size
-        self.stride = stride or kernel_size
-        self.padding = padding
-
-    def forward(self, x, mask=None):
-        ndim = x.dim()
-        if ndim == 2:
-            x = x.unsqueeze(1)
-
-        assert (
-            x.dim() == 3
-        ), "Input tensor must have 2 or 3 dimensions (batch_size, channels, width)"
-
-        if mask is None:
-            mask = ~torch.isnan(x)
-
-        assert x.shape == mask.shape, "Input tensor and mask must have the same shape"
-
-        masked_x = torch.where(mask, x, torch.zeros_like(x))
-
-        x = F.pad(masked_x, (self.padding, self.padding), mode="reflect")
-        mask = F.pad(
-            mask.float(), (self.padding, self.padding), mode="constant", value=0
-        )
-
-        x = x.unfold(2, self.kernel_size, self.stride)
-        mask = mask.unfold(2, self.kernel_size, self.stride)
-
-        x = x.contiguous().view(x.size()[:3] + (-1,))
-        mask = mask.contiguous().view(mask.size()[:3] + (-1,)).to(x.device)
-
-        # Combine the mask with the input tensor
-        #x_masked = torch.where(mask.bool(), x, torch.fill_(torch.zeros_like(x),float("inf")))
-        x_masked = torch.where(mask.bool(), x, torch.FloatTensor([float("inf")]).to(x.device))
-
-        # Sort the masked tensor along the last dimension
-        x_sorted, _ = torch.sort(x_masked, dim=-1)
-
-        # Compute the count of non-masked (valid) values
-        valid_count = mask.sum(dim=-1)
-
-        # Calculate the index of the median value for each pooling window
-        median_idx = (torch.div((valid_count - 1), 2, rounding_mode='trunc')).clamp(min=0)
-
-        # Gather the median values using the calculated indices
-        median_pooled = x_sorted.gather(-1, median_idx.unsqueeze(-1).long()).squeeze(-1)
-
-        # Fill infinite values with NaNs
-        median_pooled[torch.isinf(median_pooled)] = float("nan")
-        
-        if ndim == 2:
-            return median_pooled.squeeze(1)
-
-        return median_pooled
-
-
-class CrepePitchExtractor(BasePitchExtractor):
-    def __init__(
-        self,
-        hop_length: int = 512,
-        f0_min: float = 50.0,
-        f0_max: float = 1100.0,
-        threshold: float = 0.05,
-        keep_zeros: bool = False,
-        device = None,
-        model: Literal["full", "tiny"] = "full",
-        use_fast_filters: bool = True,
-    ):
-        super().__init__(hop_length, f0_min, f0_max, keep_zeros)
-
-        self.threshold = threshold
-        self.model = model
-        self.use_fast_filters = use_fast_filters
-        self.hop_length = hop_length
-        if device is None:
-            self.dev = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-        else:
-            self.dev = torch.device(device)
-        if self.use_fast_filters:
-            self.median_filter = MaskedMedianPool1d(3, 1, 1).to(device)
-            self.mean_filter = MaskedAvgPool1d(3, 1, 1).to(device)
-
-    def __call__(self, x, sampling_rate=44100, pad_to=None):
-        """Extract pitch using crepe.
-
-
-        Args:
-            x (torch.Tensor): Audio signal, shape (1, T).
-            sampling_rate (int, optional): Sampling rate. Defaults to 44100.
-            pad_to (int, optional): Pad to length. Defaults to None.
-
-        Returns:
-            torch.Tensor: Pitch, shape (T // hop_length,).
-        """
-
-        assert x.ndim == 2, f"Expected 2D tensor, got {x.ndim}D tensor."
-        assert x.shape[0] == 1, f"Expected 1 channel, got {x.shape[0]} channels."
-
-        x = x.to(self.dev)
-        f0, pd = torchcrepe.predict(
-            x,
-            sampling_rate,
-            self.hop_length,
-            self.f0_min,
-            self.f0_max,
-            pad=True,
-            model=self.model,
-            batch_size=1024,
-            device=x.device,
-            return_periodicity=True,
-        )
-
-        # Filter, remove silence, set uv threshold, refer to the original warehouse readme
-        if self.use_fast_filters:
-            pd = self.median_filter(pd)
-        else:
-            pd = torchcrepe.filter.median(pd, 3)
-
-        pd = torchcrepe.threshold.Silence(-60.0)(pd, x, sampling_rate, 512)
-        f0 = torchcrepe.threshold.At(self.threshold)(f0, pd)
-        
-        if self.use_fast_filters:
-            f0 = self.mean_filter(f0)
-        else:
-            f0 = torchcrepe.filter.mean(f0, 3)
-
-        f0 = torch.where(torch.isnan(f0), torch.full_like(f0, 0), f0)[0]
-
-        return self.post_process(x, sampling_rate, f0, pad_to)
diff --git a/spaces/muhammadayman/data_science_content_en_to_ar/app.py b/spaces/muhammadayman/data_science_content_en_to_ar/app.py
deleted file mode 100644
index 92c1d2d98c9712dabb432bc83a869c21994122eb..0000000000000000000000000000000000000000
--- a/spaces/muhammadayman/data_science_content_en_to_ar/app.py
+++ /dev/null
@@ -1,65 +0,0 @@
-import sys
-import gradio as gr
-from transformers import AutoTokenizer
-import torch
-import json, re
-tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-ar")
-model = torch.load("helsinki_fineTuned.pt", map_location=torch.device('cpu'))
-model.eval()
-
-# Open Keywords
-with open('merged.json', encoding='utf8') as merged:
-    data = json.load(merged)
-keyword_map = {}
-for en in data:
-    keyword_map[en.lower()] = data[en]
-merged.close()
-
-# Getting keywords from the file
-def getKeywords(word):
-    words = word.lower().rstrip()
-    if keyword_map.get(words):
-        return keyword_map[words], True
-    return word, False
-    
-# Replace keywords with the translation
-def final_output(text):
-    reg = re.compile('[a-zA-Z][ \-()a-zA-Z]+')
-    keywords = re.findall(reg, text)
-    text_split = re.split(reg, text)
-    n=len(keywords)
-    for i in range(n):
-        word, found = getKeywords(keywords[i])
-        if found:
-            text_split[i]+=(word + " (" + keywords[i].rstrip() + ")")
-        else:
-            text_split[i]+=word
-    return ' '.join(text_split)
-  
-  
-  
-def translate(input):
-    translation = []
-    text_list = input.split('.')
-    for i in range(len(text_list)):
-        encode = model.generate(**tokenizer.prepare_seq2seq_batch(text_list[i],return_tensors='pt'))
-        text_ar = tokenizer.batch_decode(encode,skip_special_tokens=True)[0]
-        text_post = final_output(text_ar)
-        translation.append(text_post)
-    article_ar = ".".join(translation)
-    return article_ar
-# Wrap up function
-translate_interface = gr.Interface(fn = translate,
-                                   allow_flagging = True,
-                                   flagging_dir = 'flagged/logs',
-                                   title = 'Translating "English Data Science" content into Arabic',
-                                   inputs=gr.inputs.Textbox(lines = 7, label = 'English content'),
-                                   outputs="text",
-                                   examples = [
-                                   ['In the last few years the RNN-based architectures have shown the best performance in machine translation problems, but still they have some problems that had to be solved. First, they have a difficulty to cope with long-range dependencies (also LSTM when it has to deal with really long sentences). Secondly, each hidden state depends on the previous one which impossible to parallelize and makes it inefficient on GPUs.']
-                                   , 
-                                   ['Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data,[1][2] and apply knowledge and actionable insights from data across a broad range of application domains. Data science is related to data mining, machine learning and big data.']
-                                   ]
-                                                               )
-                                                               
-translate_interface.launch()
\ No newline at end of file
diff --git a/spaces/mya-mya/SentenceMixer/app.py b/spaces/mya-mya/SentenceMixer/app.py
deleted file mode 100644
index 01e44de7f68a8bd8095484315b0c288faca90533..0000000000000000000000000000000000000000
--- a/spaces/mya-mya/SentenceMixer/app.py
+++ /dev/null
@@ -1,5 +0,0 @@
-from dummymixer import DummyMixer
-from t5mixer import T5Mixer
-from frontend import launch
-
-launch(T5Mixer())
\ No newline at end of file
diff --git a/spaces/mygyasir/digiplay-NextPhoto_v3/README.md b/spaces/mygyasir/digiplay-NextPhoto_v3/README.md
deleted file mode 100644
index 6ce7eda3a41d52691a16e478782a32d70c671443..0000000000000000000000000000000000000000
--- a/spaces/mygyasir/digiplay-NextPhoto_v3/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Digiplay-NextPhoto V3
-emoji: 😻
-colorFrom: purple
-colorTo: blue
-sdk: gradio
-sdk_version: 3.40.1
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/netiMophi/DreamlikeArt-Diffusion-1.0/Create3DCharacters ? ZOO TOOLS PRO Maya.md b/spaces/netiMophi/DreamlikeArt-Diffusion-1.0/Create3DCharacters ? ZOO TOOLS PRO Maya.md
deleted file mode 100644
index 35765f62f5bedfe9b65c2c089e9bfe94e49aa059..0000000000000000000000000000000000000000
--- a/spaces/netiMophi/DreamlikeArt-Diffusion-1.0/Create3DCharacters ? ZOO TOOLS PRO Maya.md	
+++ /dev/null
@@ -1,57 +0,0 @@
-
-<h1>How to Enhance Your Maya Workflow with Create3DCharacters – ZOO TOOLS PRO</h1>
-<p>If you are a Maya user who wants to improve your productivity, creativity and enjoyment while working on your 3D projects, you might want to check out Create3DCharacters – ZOO TOOLS PRO. This is a comprehensive suite of more than 80 tools that cover various aspects of Maya, such as modeling, rigging, animation, rendering, dynamics, cameras, UVs and more. In this article, we will give you an overview of what ZOO TOOLS PRO can do for you and how to get started with it.</p>
-<h2>What is Create3DCharacters – ZOO TOOLS PRO?</h2>
-<p>Create3DCharacters – ZOO TOOLS PRO is a product of Create 3d Characters, a website that offers online training and assets for 3D artists. ZOO TOOLS PRO is designed to enhance your Maya experience by providing you with a collection of tools that are easy to use, intuitive and powerful. Some of the features of ZOO TOOLS PRO are:</p>
-<h2>Create3DCharacters – ZOO TOOLS PRO maya</h2><br /><p><b><b>DOWNLOAD</b> &#10004;&#10004;&#10004; <a href="https://urlcod.com/2uI9VR">https://urlcod.com/2uI9VR</a></b></p><br /><br />
-<ul>
-<li>A one-time payment of $40 USD gives you permanent access to all the tools and assets.</li>
-<li>A monthly subscription of $10 USD gives you ongoing support and updates.</li>
-<li>A drag-and-drop installer that makes it simple to set up ZOO TOOLS PRO on your Maya.</li>
-<li>A comprehensive training page for each tool that explains how to use it effectively.</li>
-<li>A compatibility with vanilla Maya and studio pipelines.</li>
-<li>A possibility to share your saved files with others who may not have ZOO TOOLS PRO installed.</li>
-</ul>
-<h2>What are some of the tools included in Create3DCharacters – ZOO TOOLS PRO?</h2>
-<p>ZOO TOOLS PRO offers a wide range of tools that cater to different needs and preferences of Maya users. Here are some examples of what you can find in ZOO TOOLS PRO:</p>
-<h3>Information</h3>
-<p>This category contains tools that help you access information and documentation about ZOO TOOLS PRO, such as updates, terms of use, FAQ, API documentation and more.</p>
-<h3>Assets</h3>
-<p>This category contains assets that you can use in your projects, such as characters, rigs, shaders, lights, cameras and more. You can also create your own assets and save them for future use.</p>
-<h3>Lights</h3>
-<p>This category contains tools that help you create and manage lights in your scene, such as light presets, light linking, light groups, light baking and more.</p>
-<p></p>
-<h3>Hive Auto-Rigger</h3>
-<p>This category contains tools that help you rig your characters quickly and easily using the Hive Auto-Rigger system. You can also customize your rigs with controls, joints, skinning and more.</p>
-<h3>Rigging</h3>
-<p>This category contains tools that help you with various aspects of rigging, such as constraints, blend shapes, deformers, drivers, expressions and more.</p>
-<h3>Shaders</h3>
-<p>This category contains tools that help you create and apply shaders to your objects, such as shader presets, shader switcher, shader library and more.</p>
-<h3>Renderer</h3>
-<p>This category contains tools that help you render your scene using different render engines, such as Arnold, Renderman, Redshift and more. You can also adjust render settings, render layers, AOVs and more.</p>
-<h3>Modeling</h3>
-<p>This category contains tools that help you model your objects using various techniques, such as poly modeling, curve modeling, sculpting and more. You can also use modeling utilities such as mirror tool,
-snap tool,
-align tool
-and more.</p>
-
-<h3>Dynamics</h3>
-<p>This category contains tools that help you create and simulate dynamic effects in your scene,
-such as nCloth,
-nHair,
-nParticles
-and more.
-You can also use dynamics utilities such as collision tool,
-constraint tool,
-solver tool
-and more.</p>
-
-<h3>Cameras</h3>
-<p>This category contains tools that help you create and manage cameras in your scene,
-such as camera presets,
-camera switcher,
-camera library
-and more.
-You can also use camera utilities</p> 7b8c122e87<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/netiMophi/DreamlikeArt-Diffusion-1.0/Mafia 2 Crack Fix Skidrow Direct !NEW! Download.md b/spaces/netiMophi/DreamlikeArt-Diffusion-1.0/Mafia 2 Crack Fix Skidrow Direct !NEW! Download.md
deleted file mode 100644
index 072cd59670605ce84d28c476cb694d854ab67eeb..0000000000000000000000000000000000000000
--- a/spaces/netiMophi/DreamlikeArt-Diffusion-1.0/Mafia 2 Crack Fix Skidrow Direct !NEW! Download.md	
+++ /dev/null
@@ -1,28 +0,0 @@
-
-Here is a possible title and article with html formatting for the keyword "Mafia 2 Crack Fix Skidrow Direct Download":
-
-```html
-<h1>How to Download and Install Mafia 2 Crack Fix Skidrow</h1>
-<p>Mafia 2 is a popular action-adventure game that follows the life of Vito Scaletta, a gangster in the 1940s and 1950s. The game features an immersive world, a cinematic story, and intense gameplay. However, some players may encounter problems with the game's protection system, which requires a valid Steam account and a CD key to play. Fortunately, there is a way to bypass this system and play the game without any restrictions. This is by using a crack fix from Skidrow, a group of hackers who specialize in cracking games.</p>
-<p>In this article, we will show you how to download and install Mafia 2 Crack Fix Skidrow in a few simple steps. Before we begin, make sure you have the following requirements:</p>
-<h2>Mafia 2 Crack Fix Skidrow Direct Download</h2><br /><p><b><b>Download File</b> &rArr;&rArr;&rArr; <a href="https://urlcod.com/2uI9Ac">https://urlcod.com/2uI9Ac</a></b></p><br /><br />
-<ul>
-<li>A copy of Mafia 2 installed on your PC. You can buy it from Steam or other online stores, or use a pirated version if you don't mind the legal risks.</li>
-<li>A torrent client, such as uTorrent or BitTorrent, to download the crack fix file.</li>
-<li>A file extractor, such as WinRAR or 7-Zip, to unzip the crack fix file.</li>
-<li>A backup of your original Mafia 2 files, in case something goes wrong or you want to restore them later.</li>
-</ul>
-<p>Once you have these requirements, follow these steps:</p>
-<ol>
-<li>Download the Mafia 2 Crack Fix Skidrow file from this link: <a href="https://ulozto.net/file/oahCC5F7/mafia-2-crack-skidrow-rar?redirected=1">https://ulozto.net/file/oahCC5F7/mafia-2-crack-skidrow-rar?redirected=1</a>. This is a trusted source that has been verified by many users. Alternatively, you can search for other sources on Google or YouTube, but be careful of fake or malicious links.</li>
-<li>Open your torrent client and add the downloaded file to it. Wait for the download to finish. It should take a few minutes depending on your internet speed.</li>
-<li>Open your file extractor and locate the downloaded file. Right-click on it and select "Extract here" or "Extract to mafia-2-crack-skidrow". You should see a folder named "SKIDROW" with several files inside.</li>
-<li>Open your Mafia 2 installation folder. This is usually located at C:\Program Files (x86)\Steam\steamapps\common\Mafia II\pc\. If you installed the game in a different location, find it there.</li>
-<li>Copy all the files from the "SKIDROW" folder and paste them into your Mafia 2 installation folder. Overwrite any existing files when prompted. This will replace the original game files with the cracked ones.</li>
-<li>Launch the game from your desktop shortcut or from Steam. You should be able to play the game without any problems. Enjoy!</li>
-</ol>
-<p>Note: This crack fix also includes a bonus DLC package called Made Man, which adds two new suits and two new cars for Vito. You can access them from your wardrobe and garage in the game.</p>
-<p>Disclaimer: This article is for educational purposes only. We do not condone piracy or illegal activities. We are not responsible for any damages or consequences that may result from using this crack fix. Use it at your own risk.</p>
-```</p> 7196e7f11a<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/netiMophi/DreamlikeArt-Diffusion-1.0/Microsoft Sql Server 2012 Standard Edition ((NEW)) Download Torrent.md b/spaces/netiMophi/DreamlikeArt-Diffusion-1.0/Microsoft Sql Server 2012 Standard Edition ((NEW)) Download Torrent.md
deleted file mode 100644
index e1ef909036755c314121d72a17a7f987c4eb8e8b..0000000000000000000000000000000000000000
--- a/spaces/netiMophi/DreamlikeArt-Diffusion-1.0/Microsoft Sql Server 2012 Standard Edition ((NEW)) Download Torrent.md	
+++ /dev/null
@@ -1,67 +0,0 @@
-<br />
-Here is a possible title and article with html formatting for the keyword "Microsoft Sql Server 2012 Standard Edition Download Torrent":
-
-<h1>How to Download Microsoft SQL Server 2012 Standard Edition for Free</h1>
-<p>Microsoft SQL Server 2012 is a powerful and reliable database management system that can handle large amounts of data and support various applications. The Standard Edition offers a range of features and capabilities for small and medium-sized businesses, such as high availability, backup and restore, security, reporting, and analysis.</p>
-<h2>Microsoft Sql Server 2012 Standard Edition Download Torrent</h2><br /><p><b><b>Download</b> &#9733;&#9733;&#9733;&#9733;&#9733; <a href="https://urlcod.com/2uIbLB">https://urlcod.com/2uIbLB</a></b></p><br /><br />
-<p>If you want to try out Microsoft SQL Server 2012 Standard Edition for free, you have a few options. One of them is to download a torrent file from a reputable source and use a torrent client to download the installation media. However, this method has some risks and drawbacks, such as:</p>
-<ul>
-<li>You may not get the latest version or service pack of SQL Server 2012.</li>
-<li>You may encounter malware or viruses that can harm your computer or data.</li>
-<li>You may violate the terms and conditions of Microsoft's software license agreement.</li>
-<li>You may not be able to activate or update SQL Server 2012 without a valid product key.</li>
-</ul>
-<p>Therefore, we recommend that you use one of the following alternatives to download Microsoft SQL Server 2012 Standard Edition for free:</p>
-<ol>
-<li>Download the evaluation edition from Microsoft's website[^1^]. This edition allows you to use SQL Server 2012 for 180 days without any limitations. After that, you can either purchase a license or uninstall the software.</li>
-<li>Download the developer edition from Microsoft's website[^2^]. This edition is intended for development and testing purposes only and is not licensed for production use. It has the same features as the enterprise edition of SQL Server 2012.</li>
-<li>Download the express edition from Microsoft's website[^3^]. This edition is a free and lightweight version of SQL Server 2012 that can be used for small-scale applications. It has some limitations in terms of database size, memory usage, and functionality.</li>
-</ol>
-<p>Whichever option you choose, make sure you follow the installation instructions carefully and meet the system requirements for SQL Server 2012. You can also find helpful resources and tutorials on Microsoft's website or on other websites such as mssqltips.com.</p>
-<p>We hope this article has helped you find a way to download Microsoft SQL Server 2012 Standard Edition for free. If you have any questions or feedback, please let us know in the comments below.</p>Here are a few more paragraphs:
-
-<h2>How to Install SQL Server 2012 Standard Edition</h2>
-<p>Once you have downloaded the installation media for SQL Server 2012 Standard Edition, you can follow these steps to install it on your computer:</p>
-<p></p>
-<ol>
-<li>Run the setup.exe file and choose the Installation option from the left menu.</li>
-<li>Select the New SQL Server stand-alone installation or add features to an existing installation option.</li>
-<li>Enter the product key if you have one or choose the evaluation edition if you don't.</li>
-<li>Accept the license terms and click Next.</li>
-<li>Choose the features you want to install and click Next.</li>
-<li>Specify the instance name and ID for your SQL Server installation and click Next.</li>
-<li>Configure the service accounts and startup options for your SQL Server services and click Next.</li>
-<li>Select the authentication mode and specify the administrators for your SQL Server instance and click Next.</li>
-<li>Choose the data directories and filestream options for your SQL Server instance and click Next.</li>
-<li>Configure the error reporting and usage data collection options and click Next.</li>
-<li>Review the summary of your installation configuration and click Install.</li>
-<li>Wait for the installation process to complete and click Close.</li>
-</ol>
-<p>Congratulations, you have successfully installed SQL Server 2012 Standard Edition on your computer. You can now use SQL Server Management Studio or other tools to connect to your SQL Server instance and start working with your databases.</p>
-
-<h2>How to Update SQL Server 2012 Standard Edition</h2>
-<p>To keep your SQL Server 2012 Standard Edition up to date and secure, you should apply the latest cumulative updates and service packs from Microsoft. These updates contain bug fixes, performance improvements, and security patches for your SQL Server installation. You can download them from Microsoft's website or use Windows Update to automatically install them.</p>
-<p>To apply a cumulative update or service pack to your SQL Server 2012 Standard Edition, you can follow these steps:</p>
-<ol>
-<li>Download the update file from Microsoft's website or use Windows Update to download it automatically.</li>
-<li>Run the update file and follow the instructions on the screen.</li>
-<li>Restart your computer if prompted.</li>
-</ol>
-<p>Note that some updates may require you to restart your SQL Server services or reboot your computer. You should also back up your databases before applying any updates to avoid data loss in case of any issues. You can check the current version and build number of your SQL Server installation by running this query in SQL Server Management Studio:</p>
-
-<code>SELECT @@VERSION;</code>
-
-<p>You can also find helpful resources and tutorials on how to update SQL Server 2012 on Microsoft's website or on other websites such as mssqltips.com.</p>
-
-<h2>How to Uninstall SQL Server 2012 Standard Edition</h2>
-<p>If you no longer need or want to use SQL Server 2012 Standard Edition on your computer, you can uninstall it by following these steps:</p>
-<ol>
-<li>Run the setup.exe file from the installation media or from the Start menu and choose the Maintenance option from the left menu.</li>
-<li>Select the Remove node option.</li>
-<li>Select the instance or features you want to uninstall and click Next.</li>
-<li>Review the summary of your uninstallation configuration and click Remove.</li>
-<li>Wait for the uninstallation process to complete and click Close.</li>
-</ol>
-<p>Note that uninstalling SQL Server 2012 Standard Edition will not remove all the files and folders related to it. You may need to manually delete them from your hard drive or use a third-party tool to clean up your system. You should also back up your databases before uninstalling SQL Server 2012 in case you need them later. You can find helpful resources and tutorials on how to uninstall SQL Server 2012 on Microsoft's website or on other websites such as mssqltips.com.</p> 7196e7f11a<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/nfel/Thermostat/app.py b/spaces/nfel/Thermostat/app.py
deleted file mode 100644
index b912d2ec0c854d821c317dc39ed2250da4127e9f..0000000000000000000000000000000000000000
--- a/spaces/nfel/Thermostat/app.py
+++ /dev/null
@@ -1,313 +0,0 @@
-import datasets
-import glob
-import json
-import pandas as pd
-import streamlit as st
-import sys
-import textwrap
-
-from thermostat import load
-from thermostat.data.thermostat_configs import builder_configs
-
-
-nlp = datasets
-
-HTML_WRAPPER = """<div>{}</div>"""
-#HTML_WRAPPER = """<div style="overflow-x: auto; border: 1px solid #e6e9ef; border-radius: 0.25rem; padding: 1rem;
-#                  margin-bottom: 2.5rem">{}</div>"""
-MAX_SIZE = 40000000000
-if len(sys.argv) > 1:
-    path_to_datasets = sys.argv[1]
-else:
-    path_to_datasets = None
-
-
-# Hack to extend the width of the main pane.
-def _max_width_():
-    max_width_str = f"max-width: 1000px;"
-    st.markdown(
-        f"""
-    <style>
-    .reportview-container .main .block-container{{
-        {max_width_str}
-    }}
-    th {{
-        text-align: left;
-        font-size: 110%;
-
-
-     }}
-
-    tr:hover {{
-        background-color: #ffff99;
-        }}
-
-    </style>
-    """,
-        unsafe_allow_html=True,
-    )
-
-
-_max_width_()
-
-
-def render_features(features):
-    if isinstance(features, dict):
-        return {k: render_features(v) for k, v in features.items()}
-    if isinstance(features, nlp.features.ClassLabel):
-        return features.names
-
-    if isinstance(features, nlp.features.Value):
-        return features.dtype
-
-    if isinstance(features, nlp.features.Sequence):
-        return {"[]": render_features(features.feature)}
-    return features
-
-
-app_state = st.experimental_get_query_params()
-start = True
-loaded = True
-INITIAL_SELECTION = ""
-
-app_state.setdefault("dataset", "glue")
-if len(app_state.get("dataset", [])) == 1:
-    app_state["dataset"] = app_state["dataset"][0]
-    INITIAL_SELECTION = app_state["dataset"]
-#print(INITIAL_SELECTION)
-
-if start:
-    # Logo and sidebar decoration.
-    st.sidebar.markdown(
-        """<center>
-    <a href="https://github.com/DFKI-NLP/thermostat">
-    </a>
-    </center>""",
-        unsafe_allow_html=True,
-    )
-    st.sidebar.image("logo.png", width=300)
-    st.sidebar.markdown(
-        "<center><h2><a href='https://github.com/DFKI-NLP/thermostat'>github/DFKI-NLP/thermostat</h2></a></center>",
-        unsafe_allow_html=True,
-    )
-    st.sidebar.markdown(
-        """
-    <center>
-        <a target="_blank" href="https://huggingface.co/docs/datasets/">datasets Docs</a>
-    </center>""",
-        unsafe_allow_html=True,
-    )
-    st.sidebar.subheader("")
-
-    # Interaction with the nlp libary.
-    # @st.cache
-    def get_confs():
-        """  Get the list of confs for a dataset. """
-        confs = builder_configs
-        if confs and len(confs) > 1:
-            return confs
-        else:
-            return []
-
-    # @st.cache(allow_output_mutation=True)
-    def get(conf):
-        """ Get a dataset from name and conf """
-        ds = load(conf, cache_dir=path_to_datasets)
-        return ds, False
-
-    # Dataset select box.
-    datasets = []
-    selection = None
-
-    if path_to_datasets is None:
-        list_of_datasets = nlp.list_datasets(with_community_datasets=False)
-    else:
-        list_of_datasets = sorted(glob.glob(path_to_datasets + "*"))
-    for i, dataset in enumerate(list_of_datasets):
-        dataset = dataset.split("/")[-1]
-        if INITIAL_SELECTION and dataset == INITIAL_SELECTION:
-            selection = i
-        datasets.append(dataset)
-
-    st.experimental_set_query_params(**app_state)
-
-    # Side bar Configurations.
-    configs = get_confs()
-    conf_avail = len(configs) > 0
-    conf_option = None
-    if conf_avail:
-        start = 0
-        for i, conf in enumerate(configs):
-            if conf.name == app_state.get("config", None):
-                start = i
-        conf_option = st.sidebar.selectbox(
-            "Thermostat configuration", configs, index=start, format_func=lambda a: a.name
-        )
-        app_state["config"] = conf_option.name
-
-    else:
-        if "config" in app_state:
-            del app_state["config"]
-    st.experimental_set_query_params(**app_state)
-
-    dts, fail = get(str(conf_option.name) if conf_option else None)
-
-    # Main panel setup.
-    if fail:
-        st.markdown(
-            "Dataset is too large to browse or requires manual download. Check it out in the datasets library! \n\n "
-            "Size: "
-            + str(dts.info.size_in_bytes)
-            + "\n\n Instructions: "
-            + str(dts.manual_download_instructions)
-        )
-    else:
-        d = dts
-        keys = list(d[0].__dict__.keys())
-
-        st.header(
-            "Thermostat configuration: "
-            + (conf_option.name if conf_option else "")
-        )
-
-        st.markdown(
-            "*Homepage*: "
-            + d.info.homepage
-        )
-
-        md = """
-        %s
-        """ % (
-            d.info.description.replace("\\", "  ")
-        )
-        st.markdown(md)
-
-        step = 50
-        offset = st.sidebar.number_input(
-            "Offset (Size: %d)" % len(d),
-            min_value=0,
-            max_value=int(len(d)) - step,
-            value=0,
-            step=step,
-        )
-
-        citation = None #st.sidebar.checkbox("Show Citations", False)
-        table = not st.sidebar.checkbox("Show List View", False)
-        show_features = st.sidebar.checkbox("Show Features", True)
-        show_atts = st.sidebar.checkbox("Show Attribution Scores", False)
-        md = """
-```
-%s
-```
-""" % (
-            d.info.citation.replace("\\", "").replace("}", " }").replace("{", "{ "),
-        )
-        if citation:
-            st.markdown(md)
-        # st.text("Features:")
-        #if show_features:
-        #    on_keys = st.multiselect("Features", keys, keys)
-        #    #st.write(render_features(d.features))
-        #else:
-        on_keys = keys
-
-        # Remove some keys
-        on_keys = [k for k in on_keys if k in ['predictions', 'true_label', 'predicted_label']]
-
-        if not table:
-            # Full view.
-            for item in range(offset, offset + step):
-                st.text("        ")
-                st.text("                  ----  #" + str(item))
-                st.text("        ")
-                # Use st to write out.
-                for k in on_keys:
-                    v = getattr(d[item], k)
-                    st.subheader(k)
-                    if isinstance(v, str):
-                        out = v
-                        st.text(textwrap.fill(out, width=120))
-                    elif (
-                            isinstance(v, bool)
-                            or isinstance(v, int)
-                            or isinstance(v, float)
-                    ):
-                        st.text(v)
-                    else:
-                        st.write(v)
-
-        else:
-            # Table view. Use Pandas.
-            df, heatmap_htmls = [], []
-            for item in range(offset, offset + step):
-                df_item = {}
-                df_item["_number"] = item
-                for k in on_keys:
-                    v = getattr(d[item], k)
-
-                    # Remove [PAD] tokens from attributions and input_ids
-                    if k in ['attributions', 'input_ids']:
-                        v = [vi for vi in v if vi != 0 or vi != 0.0]
-
-                    if isinstance(v, str):
-                        out = v
-                        df_item[k] = textwrap.fill(out, width=50)
-                    elif (
-                            isinstance(v, bool)
-                            or isinstance(v, int)
-                            or isinstance(v, float)
-                    ):
-                        df_item[k] = v
-                    else:
-                        out = json.dumps(v, indent=2, sort_keys=True)
-                        df_item[k] = out
-
-                # Add heatmap viz
-                html = getattr(d[item], 'heatmap').render(labels=show_atts)
-                html = html.replace("\n", " ")
-                heatmap_htmls.append(HTML_WRAPPER.format(html))
-
-                df.append(df_item)
-            df2 = df
-            df = pd.DataFrame(df).set_index("_number")
-
-            def hover(hover_color="#ffff99"):
-                return dict(
-                    selector="tr:hover",
-                    props=[("background-color", "%s" % hover_color)],
-                )
-
-            styles = [
-                hover(),
-                dict(
-                    selector="th",
-                    props=[("font-size", "150%"), ("text-align", "center")],
-                ),
-                dict(selector="caption", props=[("caption-side", "bottom")]),
-            ]
-            # Table view. Use pands styling.
-            style = df.style.set_properties(
-                **{"text-align": "left", "white-space": "pre"}
-            ).set_table_styles([dict(selector="th", props=[("text-align", "left")])])
-            style = style.set_table_styles(styles)  # Setting the style appears to be broken for streamlit+pandas
-
-            for i, heatmap_html in enumerate(heatmap_htmls):
-                st.write(HTML_WRAPPER.format(heatmap_html), unsafe_allow_html=True)
-                st.table(df.iloc[[i]])
-                st.markdown(""" --- """)
-
-    # Additional dataset installation and sidebar properties.
-    md = """
-    ### Code
-
-    ```python
-    !pip install thermostat_datasets
-    from thermostat import load
-    dataset = load(
-       '%s)
-    ```
-
-    """ % (
-        (conf_option.name + "'") if conf_option else "",
-    )
-    st.sidebar.markdown(md)
diff --git a/spaces/njanakiev/gradio-openai-clip-grad-cam/gradcam/utils.py b/spaces/njanakiev/gradio-openai-clip-grad-cam/gradcam/utils.py
deleted file mode 100644
index 1b5354872fabe05788dffc7466b5b05d782c022f..0000000000000000000000000000000000000000
--- a/spaces/njanakiev/gradio-openai-clip-grad-cam/gradcam/utils.py
+++ /dev/null
@@ -1,100 +0,0 @@
-import numpy as np
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-import matplotlib.cm
-from PIL import Image
-
-# Adapted from: https://colab.research.google.com/github/kevinzakka/clip_playground/blob/main/CLIP_GradCAM_Visualization.ipynb
-class Hook:
-    """Attaches to a module and records its activations and gradients."""
-
-    def __init__(self, module: nn.Module):
-        self.data = None
-        self.hook = module.register_forward_hook(self.save_grad)
-        
-    def save_grad(self, module, input, output):
-        self.data = output
-        output.requires_grad_(True)
-        output.retain_grad()
-        
-    def __enter__(self):
-        return self
-    
-    def __exit__(self, exc_type, exc_value, exc_traceback):
-        self.hook.remove()
-        
-    @property
-    def activation(self) -> torch.Tensor:
-        return self.data
-    
-    @property
-    def gradient(self) -> torch.Tensor:
-        return self.data.grad
-
-
-# Reference: https://arxiv.org/abs/1610.02391
-def gradCAM(
-    model: nn.Module,
-    input: torch.Tensor,
-    target: torch.Tensor,
-    layer: nn.Module
-) -> torch.Tensor:
-    # Zero out any gradients at the input.
-    if input.grad is not None:
-        input.grad.data.zero_()
-        
-    # Disable gradient settings.
-    requires_grad = {}
-    for name, param in model.named_parameters():
-        requires_grad[name] = param.requires_grad
-        param.requires_grad_(False)
-        
-    # Attach a hook to the model at the desired layer.
-    assert isinstance(layer, nn.Module)
-    with Hook(layer) as hook:        
-        # Do a forward and backward pass.
-        output = model(input)
-        output.backward(target)
-
-        grad = hook.gradient.float()
-        act = hook.activation.float()
-    
-        # Global average pool gradient across spatial dimension
-        # to obtain importance weights.
-        alpha = grad.mean(dim=(2, 3), keepdim=True)
-        # Weighted combination of activation maps over channel
-        # dimension.
-        gradcam = torch.sum(act * alpha, dim=1, keepdim=True)
-        # We only want neurons with positive influence so we
-        # clamp any negative ones.
-        gradcam = torch.clamp(gradcam, min=0)
-
-    # Resize gradcam to input resolution.
-    gradcam = F.interpolate(
-        gradcam,
-        input.shape[2:],
-        mode='bicubic',
-        align_corners=False)
-    
-    # Restore gradient settings.
-    for name, param in model.named_parameters():
-        param.requires_grad_(requires_grad[name])
-        
-    return gradcam
-
-
-# Modified from: https://github.com/salesforce/ALBEF/blob/main/visualization.ipynb
-def getAttMap(img, attn_map):
-    # Normalize attention map
-    attn_map = attn_map - attn_map.min()
-    if attn_map.max() > 0:
-        attn_map = attn_map / attn_map.max()
-
-    H = matplotlib.cm.jet(attn_map)
-    H = (H * 255).astype(np.uint8)[:, :, :3]
-    img_heatmap = Image.fromarray(H)
-    img_heatmap = img_heatmap.resize((256, 256))
-    
-    return Image.blend(
-        img.resize((256, 256)), img_heatmap, 0.4)
diff --git a/spaces/ofikodar/chatgpt-resume-builder/src/data_handler.py b/spaces/ofikodar/chatgpt-resume-builder/src/data_handler.py
deleted file mode 100644
index add4a1a801f2848c7bd69a0351e2cffbb866f6a9..0000000000000000000000000000000000000000
--- a/spaces/ofikodar/chatgpt-resume-builder/src/data_handler.py
+++ /dev/null
@@ -1,87 +0,0 @@
-import pdfkit
-import streamlit as st
-
-from src.exceptions import PDFSizeException
-from src.pdf_handler import build_html_resume, parse_pdf
-from src.utils import count_entries
-
-
-def init_resume(uploaded_file):
-    resume_data, num_pages = parse_pdf(uploaded_file)
-    if num_pages > 3:
-        raise PDFSizeException
-    st.session_state['file_id'] = uploaded_file.id
-    return resume_data
-
-
-def update_resume_data(text_input, section_name, item_id=0):
-    if section_name in ['workExperience', 'education']:
-        key = 'description'
-        st.session_state['resume_data'][section_name][item_id][key] = text_input
-    elif section_name == 'summary':
-        section_key = f'{section_name}'
-        st.session_state['resume_data'][section_key] = text_input
-
-
-def download_pdf():
-    if st.session_state.get('name'):
-        resume_data = format_resume_data()
-    else:
-        resume_data = st.session_state['resume_data']
-    html_resume = build_html_resume(resume_data)
-    options = {'page-size': 'A4', 'margin-top': '0.75in', 'margin-right': '0.75in', 'margin-bottom': '0.75in',
-               'margin-left': '0.75in', 'encoding': "UTF-8", 'no-outline': None}
-    return pdfkit.from_string(html_resume, options=options, css='src/css/main.css')
-
-
-def improve_resume(resume_data=None):
-    if resume_data is not None:
-        st.session_state['resume_data'] = st.session_state['chatbot'].improve_resume(resume_data)
-    else:
-        st.session_state['resume_data'] = st.session_state['chatbot'].improve_resume(st.session_state['resume_data'])
-
-
-def format_resume_data():
-    current_state = st.session_state
-    resume_data = {}
-    contact_info = {}
-    work_experience = []
-    education = []
-    skills = []
-
-    resume_data['name'] = current_state.get('name', '')
-    resume_data['title'] = current_state.get('title', '')
-
-    contact_info_keys = ['linkedin', 'github', 'email', 'address']
-    for key in contact_info_keys:
-        contact_info[key] = current_state.get(f'contactInfo_{key}', '')
-
-    resume_data['contactInfo'] = contact_info
-
-    resume_data['summary'] = current_state.get('summary', '')
-
-    work_experience_keys = ['workExperience_{}_title', 'workExperience_{}_company', 'workExperience_{}_dates',
-                            'workExperience_{}_description']
-    education_keys = ['education_{}_degree', 'education_{}_school', 'education_{}_dates', 'education_{}_description']
-
-    total_work_experience = count_entries(st.session_state, 'workExperience')
-    total_education = count_entries(st.session_state, 'education')
-
-    for i in range(total_work_experience):
-        work_experience.append(
-            {key.split('_')[2]: current_state.get(key.format(i), '') for key in work_experience_keys})
-
-    for i in range(total_education):
-        education.append({key.split('_')[2]: current_state.get(key.format(i), '') for key in education_keys})
-
-    resume_data['workExperience'] = work_experience
-    resume_data['education'] = education
-
-    total_skills = count_entries(st.session_state, 'skills')
-
-    for i in range(total_skills):
-        skill_key = f'skills_{i}'
-
-        skills.append(current_state.get(skill_key, ''))
-    resume_data['skills'] = skills
-    return resume_data
diff --git a/spaces/oguzakif/video-object-remover/FGT_codes/FGT/models/__init__.py b/spaces/oguzakif/video-object-remover/FGT_codes/FGT/models/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/openlamm/LAMM/model/CLIP/__init__.py b/spaces/openlamm/LAMM/model/CLIP/__init__.py
deleted file mode 100644
index 81082ac4fab7f1108e8a3fb9715127a0be8ce5ac..0000000000000000000000000000000000000000
--- a/spaces/openlamm/LAMM/model/CLIP/__init__.py
+++ /dev/null
@@ -1,2 +0,0 @@
-# remove fp32 LN & return intermediate features
-from .clip import *
\ No newline at end of file
diff --git a/spaces/pablodawson/ldm3d-inpainting/diffuserslocal/docs/source/en/api/models/transformer2d.md b/spaces/pablodawson/ldm3d-inpainting/diffuserslocal/docs/source/en/api/models/transformer2d.md
deleted file mode 100644
index 4ad2b00b6f2377bac9192a41970c17cd6084be93..0000000000000000000000000000000000000000
--- a/spaces/pablodawson/ldm3d-inpainting/diffuserslocal/docs/source/en/api/models/transformer2d.md
+++ /dev/null
@@ -1,29 +0,0 @@
-# Transformer2D
-
-A Transformer model for image-like data from [CompVis](https://huggingface.co/CompVis) that is based on the [Vision Transformer](https://huggingface.co/papers/2010.11929) introduced by Dosovitskiy et al. The [`Transformer2DModel`] accepts discrete (classes of vector embeddings) or continuous (actual embeddings) inputs.
-
-When the input is **continuous**:
-
-1. Project the input and reshape it to `(batch_size, sequence_length, feature_dimension)`.
-2. Apply the Transformer blocks in the standard way.
-3. Reshape to image.
-
-When the input is **discrete**:
-
-<Tip>
-
-It is assumed one of the input classes is the masked latent pixel. The predicted classes of the unnoised image don't contain a prediction for the masked pixel because the unnoised image cannot be masked.
-
-</Tip>
-
-1. Convert input (classes of latent pixels) to embeddings and apply positional embeddings.
-2. Apply the Transformer blocks in the standard way.
-3. Predict classes of unnoised image.
-
-## Transformer2DModel
-
-[[autodoc]] Transformer2DModel
-
-## Transformer2DModelOutput
-
-[[autodoc]] models.transformer_2d.Transformer2DModelOutput
diff --git a/spaces/pablodawson/ldm3d-inpainting/diffuserslocal/docs/source/en/training/adapt_a_model.md b/spaces/pablodawson/ldm3d-inpainting/diffuserslocal/docs/source/en/training/adapt_a_model.md
deleted file mode 100644
index 57bc1a37e05be78149810c73586e63a393b6e341..0000000000000000000000000000000000000000
--- a/spaces/pablodawson/ldm3d-inpainting/diffuserslocal/docs/source/en/training/adapt_a_model.md
+++ /dev/null
@@ -1,47 +0,0 @@
-# Adapt a model to a new task
-
-Many diffusion systems share the same components, allowing you to adapt a pretrained model for one task to an entirely different task.
-
-This guide will show you how to adapt a pretrained text-to-image model for inpainting by initializing and modifying the architecture of a pretrained [`UNet2DConditionModel`].
-
-## Configure UNet2DConditionModel parameters
-
-A [`UNet2DConditionModel`] by default accepts 4 channels in the [input sample](https://huggingface.co/docs/diffusers/v0.16.0/en/api/models#diffusers.UNet2DConditionModel.in_channels). For example, load a pretrained text-to-image model like [`runwayml/stable-diffusion-v1-5`](https://huggingface.co/runwayml/stable-diffusion-v1-5) and take a look at the number of `in_channels`:
-
-```py
-from diffusers import StableDiffusionPipeline
-
-pipeline = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", use_safetensors=True)
-pipeline.unet.config["in_channels"]
-4
-```
-
-Inpainting requires 9 channels in the input sample. You can check this value in a pretrained inpainting model like [`runwayml/stable-diffusion-inpainting`](https://huggingface.co/runwayml/stable-diffusion-inpainting):
-
-```py
-from diffusers import StableDiffusionPipeline
-
-pipeline = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-inpainting", use_safetensors=True)
-pipeline.unet.config["in_channels"]
-9
-```
-
-To adapt your text-to-image model for inpainting, you'll need to change the number of `in_channels` from 4 to 9. 
-
-Initialize a [`UNet2DConditionModel`] with the pretrained text-to-image model weights, and change `in_channels` to 9. Changing the number of `in_channels` means you need to set `ignore_mismatched_sizes=True` and `low_cpu_mem_usage=False` to avoid a size mismatch error because the shape is different now.
-
-```py
-from diffusers import UNet2DConditionModel
-
-model_id = "runwayml/stable-diffusion-v1-5"
-unet = UNet2DConditionModel.from_pretrained(
-    model_id,
-    subfolder="unet",
-    in_channels=9,
-    low_cpu_mem_usage=False,
-    ignore_mismatched_sizes=True,
-    use_safetensors=True,
-)
-```
-
-The pretrained weights of the other components from the text-to-image model are initialized from their checkpoints, but the input channel weights (`conv_in.weight`) of the `unet` are randomly initialized. It is important to finetune the model for inpainting because otherwise the model returns noise.
diff --git a/spaces/pablodawson/ldm3d-inpainting/diffuserslocal/src/diffusers/pipelines/musicldm/__init__.py b/spaces/pablodawson/ldm3d-inpainting/diffuserslocal/src/diffusers/pipelines/musicldm/__init__.py
deleted file mode 100644
index e49eb1f16d7d83895e63cb478f94d21afb7a2cf2..0000000000000000000000000000000000000000
--- a/spaces/pablodawson/ldm3d-inpainting/diffuserslocal/src/diffusers/pipelines/musicldm/__init__.py
+++ /dev/null
@@ -1,48 +0,0 @@
-from typing import TYPE_CHECKING
-
-from ...utils import (
-    OptionalDependencyNotAvailable,
-    _LazyModule,
-    get_objects_from_module,
-    is_torch_available,
-    is_transformers_available,
-    is_transformers_version,
-)
-
-
-_dummy_objects = {}
-_import_structure = {}
-
-try:
-    if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.27.0")):
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    from ...utils import dummy_torch_and_transformers_objects  # noqa F403
-
-    _dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
-else:
-    _import_structure["pipeline_musicldm"] = ["MusicLDMPipeline"]
-
-
-if TYPE_CHECKING:
-    try:
-        if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.27.0")):
-            raise OptionalDependencyNotAvailable()
-
-    except OptionalDependencyNotAvailable:
-        from ...utils.dummy_torch_and_transformers_objects import *
-    else:
-        from .pipeline_musicldm import MusicLDMPipeline
-
-else:
-    import sys
-
-    sys.modules[__name__] = _LazyModule(
-        __name__,
-        globals()["__file__"],
-        _import_structure,
-        module_spec=__spec__,
-    )
-
-    for name, value in _dummy_objects.items():
-        setattr(sys.modules[__name__], name, value)
diff --git a/spaces/phyloforfun/VoucherVision/vouchervision/component_detector/models/__init__.py b/spaces/phyloforfun/VoucherVision/vouchervision/component_detector/models/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/pknez/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_vendor/pygments/formatters/bbcode.py b/spaces/pknez/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_vendor/pygments/formatters/bbcode.py
deleted file mode 100644
index c4db8f4ef21a1893593182b46f3fd7f2043c33a7..0000000000000000000000000000000000000000
--- a/spaces/pknez/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_vendor/pygments/formatters/bbcode.py
+++ /dev/null
@@ -1,108 +0,0 @@
-"""
-    pygments.formatters.bbcode
-    ~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-    BBcode formatter.
-
-    :copyright: Copyright 2006-2023 by the Pygments team, see AUTHORS.
-    :license: BSD, see LICENSE for details.
-"""
-
-
-from pip._vendor.pygments.formatter import Formatter
-from pip._vendor.pygments.util import get_bool_opt
-
-__all__ = ['BBCodeFormatter']
-
-
-class BBCodeFormatter(Formatter):
-    """
-    Format tokens with BBcodes. These formatting codes are used by many
-    bulletin boards, so you can highlight your sourcecode with pygments before
-    posting it there.
-
-    This formatter has no support for background colors and borders, as there
-    are no common BBcode tags for that.
-
-    Some board systems (e.g. phpBB) don't support colors in their [code] tag,
-    so you can't use the highlighting together with that tag.
-    Text in a [code] tag usually is shown with a monospace font (which this
-    formatter can do with the ``monofont`` option) and no spaces (which you
-    need for indentation) are removed.
-
-    Additional options accepted:
-
-    `style`
-        The style to use, can be a string or a Style subclass (default:
-        ``'default'``).
-
-    `codetag`
-        If set to true, put the output into ``[code]`` tags (default:
-        ``false``)
-
-    `monofont`
-        If set to true, add a tag to show the code with a monospace font
-        (default: ``false``).
-    """
-    name = 'BBCode'
-    aliases = ['bbcode', 'bb']
-    filenames = []
-
-    def __init__(self, **options):
-        Formatter.__init__(self, **options)
-        self._code = get_bool_opt(options, 'codetag', False)
-        self._mono = get_bool_opt(options, 'monofont', False)
-
-        self.styles = {}
-        self._make_styles()
-
-    def _make_styles(self):
-        for ttype, ndef in self.style:
-            start = end = ''
-            if ndef['color']:
-                start += '[color=#%s]' % ndef['color']
-                end = '[/color]' + end
-            if ndef['bold']:
-                start += '[b]'
-                end = '[/b]' + end
-            if ndef['italic']:
-                start += '[i]'
-                end = '[/i]' + end
-            if ndef['underline']:
-                start += '[u]'
-                end = '[/u]' + end
-            # there are no common BBcodes for background-color and border
-
-            self.styles[ttype] = start, end
-
-    def format_unencoded(self, tokensource, outfile):
-        if self._code:
-            outfile.write('[code]')
-        if self._mono:
-            outfile.write('[font=monospace]')
-
-        lastval = ''
-        lasttype = None
-
-        for ttype, value in tokensource:
-            while ttype not in self.styles:
-                ttype = ttype.parent
-            if ttype == lasttype:
-                lastval += value
-            else:
-                if lastval:
-                    start, end = self.styles[lasttype]
-                    outfile.write(''.join((start, lastval, end)))
-                lastval = value
-                lasttype = ttype
-
-        if lastval:
-            start, end = self.styles[lasttype]
-            outfile.write(''.join((start, lastval, end)))
-
-        if self._mono:
-            outfile.write('[/font]')
-        if self._code:
-            outfile.write('[/code]')
-        if self._code or self._mono:
-            outfile.write('\n')
diff --git a/spaces/pknez/face-swap-docker/mynewshinyroop/Scripts/activate.bat b/spaces/pknez/face-swap-docker/mynewshinyroop/Scripts/activate.bat
deleted file mode 100644
index 56ca36b33ba60ebb9b4312ff8e051c4f3db2b5d4..0000000000000000000000000000000000000000
--- a/spaces/pknez/face-swap-docker/mynewshinyroop/Scripts/activate.bat
+++ /dev/null
@@ -1,38 +0,0 @@
-@set "VIRTUAL_ENV=C:\Users\Admin\roop-unleashed\mynewshinyroop"
-
-@set "VIRTUAL_ENV_PROMPT="
-@if NOT DEFINED VIRTUAL_ENV_PROMPT (
-    @for %%d in ("%VIRTUAL_ENV%") do @set "VIRTUAL_ENV_PROMPT=%%~nxd"
-)
-
-@if defined _OLD_VIRTUAL_PROMPT (
-    @set "PROMPT=%_OLD_VIRTUAL_PROMPT%"
-) else (
-    @if not defined PROMPT (
-        @set "PROMPT=$P$G"
-    )
-    @if not defined VIRTUAL_ENV_DISABLE_PROMPT (
-        @set "_OLD_VIRTUAL_PROMPT=%PROMPT%"
-    )
-)
-@if not defined VIRTUAL_ENV_DISABLE_PROMPT (
-    @set "PROMPT=(%VIRTUAL_ENV_PROMPT%) %PROMPT%"
-)
-
-@REM Don't use () to avoid problems with them in %PATH%
-@if defined _OLD_VIRTUAL_PYTHONHOME @goto ENDIFVHOME
-    @set "_OLD_VIRTUAL_PYTHONHOME=%PYTHONHOME%"
-:ENDIFVHOME
-
-@set PYTHONHOME=
-
-@REM if defined _OLD_VIRTUAL_PATH (
-@if not defined _OLD_VIRTUAL_PATH @goto ENDIFVPATH1
-    @set "PATH=%_OLD_VIRTUAL_PATH%"
-:ENDIFVPATH1
-@REM ) else (
-@if defined _OLD_VIRTUAL_PATH @goto ENDIFVPATH2
-    @set "_OLD_VIRTUAL_PATH=%PATH%"
-:ENDIFVPATH2
-
-@set "PATH=%VIRTUAL_ENV%\Scripts;%PATH%"
diff --git a/spaces/prerna9811/Chord/portaudio/examples/paex_record_file.c b/spaces/prerna9811/Chord/portaudio/examples/paex_record_file.c
deleted file mode 100644
index 562a8e9038761a2b6ce8f6b468fcfc906f7740ed..0000000000000000000000000000000000000000
--- a/spaces/prerna9811/Chord/portaudio/examples/paex_record_file.c
+++ /dev/null
@@ -1,457 +0,0 @@
-/** @file paex_record_file.c
-    @ingroup examples_src
-    @brief Record input into a file, then playback recorded data from file (Windows only at the moment)
-    @author Robert Bielik
-*/
-/*
- * $Id: paex_record_file.c 1752 2011-09-08 03:21:55Z philburk $
- *
- * This program uses the PortAudio Portable Audio Library.
- * For more information see: http://www.portaudio.com
- * Copyright (c) 1999-2000 Ross Bencina and Phil Burk
- *
- * Permission is hereby granted, free of charge, to any person obtaining
- * a copy of this software and associated documentation files
- * (the "Software"), to deal in the Software without restriction,
- * including without limitation the rights to use, copy, modify, merge,
- * publish, distribute, sublicense, and/or sell copies of the Software,
- * and to permit persons to whom the Software is furnished to do so,
- * subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be
- * included in all copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
- * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
- * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
- * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR
- * ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF
- * CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
- * WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
- */
-
-/*
- * The text above constitutes the entire PortAudio license; however,
- * the PortAudio community also makes the following non-binding requests:
- *
- * Any person wishing to distribute modifications to the Software is
- * requested to send the modifications to the original developer so that
- * they can be incorporated into the canonical version. It is also
- * requested that these non-binding requests be included along with the
- * license above.
- */
-
-#include <stdio.h>
-#include <stdlib.h>
-#include "portaudio.h"
-#include "pa_ringbuffer.h"
-#include "pa_util.h"
-
-#ifdef _WIN32
-#include <windows.h>
-#include <process.h>
-#endif
-
-static ring_buffer_size_t rbs_min(ring_buffer_size_t a, ring_buffer_size_t b)
-{
-    return (a < b) ? a : b;
-}
-
-/* #define SAMPLE_RATE  (17932) // Test failure to open with this value. */
-#define FILE_NAME       "audio_data.raw"
-#define SAMPLE_RATE  (44100)
-#define FRAMES_PER_BUFFER (512)
-#define NUM_SECONDS     (10)
-#define NUM_CHANNELS    (2)
-#define NUM_WRITES_PER_BUFFER   (4)
-/* #define DITHER_FLAG     (paDitherOff) */
-#define DITHER_FLAG     (0) /**/
-
-
-/* Select sample format. */
-#if 1
-#define PA_SAMPLE_TYPE  paFloat32
-typedef float SAMPLE;
-#define SAMPLE_SILENCE  (0.0f)
-#define PRINTF_S_FORMAT "%.8f"
-#elif 1
-#define PA_SAMPLE_TYPE  paInt16
-typedef short SAMPLE;
-#define SAMPLE_SILENCE  (0)
-#define PRINTF_S_FORMAT "%d"
-#elif 0
-#define PA_SAMPLE_TYPE  paInt8
-typedef char SAMPLE;
-#define SAMPLE_SILENCE  (0)
-#define PRINTF_S_FORMAT "%d"
-#else
-#define PA_SAMPLE_TYPE  paUInt8
-typedef unsigned char SAMPLE;
-#define SAMPLE_SILENCE  (128)
-#define PRINTF_S_FORMAT "%d"
-#endif
-
-typedef struct
-{
-    unsigned            frameIndex;
-    int                 threadSyncFlag;
-    SAMPLE             *ringBufferData;
-    PaUtilRingBuffer    ringBuffer;
-    FILE               *file;
-    void               *threadHandle;
-}
-paTestData;
-
-/* This routine is run in a separate thread to write data from the ring buffer into a file (during Recording) */
-static int threadFunctionWriteToRawFile(void* ptr)
-{
-    paTestData* pData = (paTestData*)ptr;
-
-    /* Mark thread started */
-    pData->threadSyncFlag = 0;
-
-    while (1)
-    {
-        ring_buffer_size_t elementsInBuffer = PaUtil_GetRingBufferReadAvailable(&pData->ringBuffer);
-        if ( (elementsInBuffer >= pData->ringBuffer.bufferSize / NUM_WRITES_PER_BUFFER) ||
-             pData->threadSyncFlag )
-        {
-            void* ptr[2] = {0};
-            ring_buffer_size_t sizes[2] = {0};
-
-            /* By using PaUtil_GetRingBufferReadRegions, we can read directly from the ring buffer */
-            ring_buffer_size_t elementsRead = PaUtil_GetRingBufferReadRegions(&pData->ringBuffer, elementsInBuffer, ptr + 0, sizes + 0, ptr + 1, sizes + 1);
-            if (elementsRead > 0)
-            {
-                int i;
-                for (i = 0; i < 2 && ptr[i] != NULL; ++i)
-                {
-                    fwrite(ptr[i], pData->ringBuffer.elementSizeBytes, sizes[i], pData->file);
-                }
-                PaUtil_AdvanceRingBufferReadIndex(&pData->ringBuffer, elementsRead);
-            }
-
-            if (pData->threadSyncFlag)
-            {
-                break;
-            }
-        }
-
-        /* Sleep a little while... */
-        Pa_Sleep(20);
-    }
-
-    pData->threadSyncFlag = 0;
-
-    return 0;
-}
-
-/* This routine is run in a separate thread to read data from file into the ring buffer (during Playback). When the file
-   has reached EOF, a flag is set so that the play PA callback can return paComplete */
-static int threadFunctionReadFromRawFile(void* ptr)
-{
-    paTestData* pData = (paTestData*)ptr;
-
-    while (1)
-    {
-        ring_buffer_size_t elementsInBuffer = PaUtil_GetRingBufferWriteAvailable(&pData->ringBuffer);
-
-        if (elementsInBuffer >= pData->ringBuffer.bufferSize / NUM_WRITES_PER_BUFFER)
-        {
-            void* ptr[2] = {0};
-            ring_buffer_size_t sizes[2] = {0};
-
-            /* By using PaUtil_GetRingBufferWriteRegions, we can write directly into the ring buffer */
-            PaUtil_GetRingBufferWriteRegions(&pData->ringBuffer, elementsInBuffer, ptr + 0, sizes + 0, ptr + 1, sizes + 1);
-
-            if (!feof(pData->file))
-            {
-                ring_buffer_size_t itemsReadFromFile = 0;
-                int i;
-                for (i = 0; i < 2 && ptr[i] != NULL; ++i)
-                {
-                    itemsReadFromFile += (ring_buffer_size_t)fread(ptr[i], pData->ringBuffer.elementSizeBytes, sizes[i], pData->file);
-                }
-                PaUtil_AdvanceRingBufferWriteIndex(&pData->ringBuffer, itemsReadFromFile);
-
-                /* Mark thread started here, that way we "prime" the ring buffer before playback */
-                pData->threadSyncFlag = 0;
-            }
-            else
-            {
-                /* No more data to read */
-                pData->threadSyncFlag = 1;
-                break;
-            }
-        }
-
-        /* Sleep a little while... */
-        Pa_Sleep(20);
-    }
-
-    return 0;
-}
-
-typedef int (*ThreadFunctionType)(void*);
-
-/* Start up a new thread in the given function, at the moment only Windows, but should be very easy to extend
-   to posix type OSs (Linux/Mac) */
-static PaError startThread( paTestData* pData, ThreadFunctionType fn )
-{
-#ifdef _WIN32
-    typedef unsigned (__stdcall* WinThreadFunctionType)(void*);
-    pData->threadHandle = (void*)_beginthreadex(NULL, 0, (WinThreadFunctionType)fn, pData, CREATE_SUSPENDED, NULL);
-    if (pData->threadHandle == NULL) return paUnanticipatedHostError;
-
-    /* Set file thread to a little higher prio than normal */
-    SetThreadPriority(pData->threadHandle, THREAD_PRIORITY_ABOVE_NORMAL);
-
-    /* Start it up */
-    pData->threadSyncFlag = 1;
-    ResumeThread(pData->threadHandle);
-
-#endif
-
-    /* Wait for thread to startup */
-    while (pData->threadSyncFlag) {
-        Pa_Sleep(10);
-    }
-
-    return paNoError;
-}
-
-static int stopThread( paTestData* pData )
-{
-    pData->threadSyncFlag = 1;
-    /* Wait for thread to stop */
-    while (pData->threadSyncFlag) {
-        Pa_Sleep(10);
-    }
-#ifdef _WIN32
-    CloseHandle(pData->threadHandle);
-    pData->threadHandle = 0;
-#endif
-
-    return paNoError;
-}
-
-
-/* This routine will be called by the PortAudio engine when audio is needed.
-** It may be called at interrupt level on some machines so don't do anything
-** that could mess up the system like calling malloc() or free().
-*/
-static int recordCallback( const void *inputBuffer, void *outputBuffer,
-                           unsigned long framesPerBuffer,
-                           const PaStreamCallbackTimeInfo* timeInfo,
-                           PaStreamCallbackFlags statusFlags,
-                           void *userData )
-{
-    paTestData *data = (paTestData*)userData;
-    ring_buffer_size_t elementsWriteable = PaUtil_GetRingBufferWriteAvailable(&data->ringBuffer);
-    ring_buffer_size_t elementsToWrite = rbs_min(elementsWriteable, (ring_buffer_size_t)(framesPerBuffer * NUM_CHANNELS));
-    const SAMPLE *rptr = (const SAMPLE*)inputBuffer;
-
-    (void) outputBuffer; /* Prevent unused variable warnings. */
-    (void) timeInfo;
-    (void) statusFlags;
-    (void) userData;
-
-    data->frameIndex += PaUtil_WriteRingBuffer(&data->ringBuffer, rptr, elementsToWrite);
-
-    return paContinue;
-}
-
-/* This routine will be called by the PortAudio engine when audio is needed.
-** It may be called at interrupt level on some machines so don't do anything
-** that could mess up the system like calling malloc() or free().
-*/
-static int playCallback( const void *inputBuffer, void *outputBuffer,
-                         unsigned long framesPerBuffer,
-                         const PaStreamCallbackTimeInfo* timeInfo,
-                         PaStreamCallbackFlags statusFlags,
-                         void *userData )
-{
-    paTestData *data = (paTestData*)userData;
-    ring_buffer_size_t elementsToPlay = PaUtil_GetRingBufferReadAvailable(&data->ringBuffer);
-    ring_buffer_size_t elementsToRead = rbs_min(elementsToPlay, (ring_buffer_size_t)(framesPerBuffer * NUM_CHANNELS));
-    SAMPLE* wptr = (SAMPLE*)outputBuffer;
-
-    (void) inputBuffer; /* Prevent unused variable warnings. */
-    (void) timeInfo;
-    (void) statusFlags;
-    (void) userData;
-
-    data->frameIndex += PaUtil_ReadRingBuffer(&data->ringBuffer, wptr, elementsToRead);
-
-    return data->threadSyncFlag ? paComplete : paContinue;
-}
-
-static unsigned NextPowerOf2(unsigned val)
-{
-    val--;
-    val = (val >> 1) | val;
-    val = (val >> 2) | val;
-    val = (val >> 4) | val;
-    val = (val >> 8) | val;
-    val = (val >> 16) | val;
-    return ++val;
-}
-
-/*******************************************************************/
-int main(void);
-int main(void)
-{
-    PaStreamParameters  inputParameters,
-                        outputParameters;
-    PaStream*           stream;
-    PaError             err = paNoError;
-    paTestData          data = {0};
-    unsigned            delayCntr;
-    unsigned            numSamples;
-    unsigned            numBytes;
-
-    printf("patest_record.c\n"); fflush(stdout);
-
-    /* We set the ring buffer size to about 500 ms */
-    numSamples = NextPowerOf2((unsigned)(SAMPLE_RATE * 0.5 * NUM_CHANNELS));
-    numBytes = numSamples * sizeof(SAMPLE);
-    data.ringBufferData = (SAMPLE *) PaUtil_AllocateMemory( numBytes );
-    if( data.ringBufferData == NULL )
-    {
-        printf("Could not allocate ring buffer data.\n");
-        goto done;
-    }
-
-    if (PaUtil_InitializeRingBuffer(&data.ringBuffer, sizeof(SAMPLE), numSamples, data.ringBufferData) < 0)
-    {
-        printf("Failed to initialize ring buffer. Size is not power of 2 ??\n");
-        goto done;
-    }
-
-    err = Pa_Initialize();
-    if( err != paNoError ) goto done;
-
-    inputParameters.device = Pa_GetDefaultInputDevice(); /* default input device */
-    if (inputParameters.device == paNoDevice) {
-        fprintf(stderr,"Error: No default input device.\n");
-        goto done;
-    }
-    inputParameters.channelCount = 2;                    /* stereo input */
-    inputParameters.sampleFormat = PA_SAMPLE_TYPE;
-    inputParameters.suggestedLatency = Pa_GetDeviceInfo( inputParameters.device )->defaultLowInputLatency;
-    inputParameters.hostApiSpecificStreamInfo = NULL;
-
-    /* Record some audio. -------------------------------------------- */
-    err = Pa_OpenStream(
-              &stream,
-              &inputParameters,
-              NULL,                  /* &outputParameters, */
-              SAMPLE_RATE,
-              FRAMES_PER_BUFFER,
-              paClipOff,      /* we won't output out of range samples so don't bother clipping them */
-              recordCallback,
-              &data );
-    if( err != paNoError ) goto done;
-
-    /* Open the raw audio 'cache' file... */
-    data.file = fopen(FILE_NAME, "wb");
-    if (data.file == 0) goto done;
-
-    /* Start the file writing thread */
-    err = startThread(&data, threadFunctionWriteToRawFile);
-    if( err != paNoError ) goto done;
-
-    err = Pa_StartStream( stream );
-    if( err != paNoError ) goto done;
-    printf("\n=== Now recording to '" FILE_NAME "' for %d seconds!! Please speak into the microphone. ===\n", NUM_SECONDS); fflush(stdout);
-
-    /* Note that the RECORDING part is limited with TIME, not size of the file and/or buffer, so you can
-       increase NUM_SECONDS until you run out of disk */
-    delayCntr = 0;
-    while( delayCntr++ < NUM_SECONDS )
-    {
-        printf("index = %d\n", data.frameIndex ); fflush(stdout);
-        Pa_Sleep(1000);
-    }
-    if( err < 0 ) goto done;
-
-    err = Pa_CloseStream( stream );
-    if( err != paNoError ) goto done;
-
-    /* Stop the thread */
-    err = stopThread(&data);
-    if( err != paNoError ) goto done;
-
-    /* Close file */
-    fclose(data.file);
-    data.file = 0;
-
-    /* Playback recorded data.  -------------------------------------------- */
-    data.frameIndex = 0;
-
-    outputParameters.device = Pa_GetDefaultOutputDevice(); /* default output device */
-    if (outputParameters.device == paNoDevice) {
-        fprintf(stderr,"Error: No default output device.\n");
-        goto done;
-    }
-    outputParameters.channelCount = 2;                     /* stereo output */
-    outputParameters.sampleFormat =  PA_SAMPLE_TYPE;
-    outputParameters.suggestedLatency = Pa_GetDeviceInfo( outputParameters.device )->defaultLowOutputLatency;
-    outputParameters.hostApiSpecificStreamInfo = NULL;
-
-    printf("\n=== Now playing back from file '" FILE_NAME "' until end-of-file is reached ===\n"); fflush(stdout);
-    err = Pa_OpenStream(
-              &stream,
-              NULL, /* no input */
-              &outputParameters,
-              SAMPLE_RATE,
-              FRAMES_PER_BUFFER,
-              paClipOff,      /* we won't output out of range samples so don't bother clipping them */
-              playCallback,
-              &data );
-    if( err != paNoError ) goto done;
-
-    if( stream )
-    {
-        /* Open file again for reading */
-        data.file = fopen(FILE_NAME, "rb");
-        if (data.file != 0)
-        {
-            /* Start the file reading thread */
-            err = startThread(&data, threadFunctionReadFromRawFile);
-            if( err != paNoError ) goto done;
-
-            err = Pa_StartStream( stream );
-            if( err != paNoError ) goto done;
-
-            printf("Waiting for playback to finish.\n"); fflush(stdout);
-
-            /* The playback will end when EOF is reached */
-            while( ( err = Pa_IsStreamActive( stream ) ) == 1 ) {
-                printf("index = %d\n", data.frameIndex ); fflush(stdout);
-                Pa_Sleep(1000);
-            }
-            if( err < 0 ) goto done;
-        }
-
-        err = Pa_CloseStream( stream );
-        if( err != paNoError ) goto done;
-
-        fclose(data.file);
-
-        printf("Done.\n"); fflush(stdout);
-    }
-
-done:
-    Pa_Terminate();
-    if( data.ringBufferData )       /* Sure it is NULL or valid. */
-        PaUtil_FreeMemory( data.ringBufferData );
-    if( err != paNoError )
-    {
-        fprintf( stderr, "An error occurred while using the portaudio stream\n" );
-        fprintf( stderr, "Error number: %d\n", err );
-        fprintf( stderr, "Error message: %s\n", Pa_GetErrorText( err ) );
-        err = 1;          /* Always return 0 or 1, but no other return codes. */
-    }
-    return err;
-}
diff --git a/spaces/prerna9811/Chord/portaudio/test/patest_ringmix.c b/spaces/prerna9811/Chord/portaudio/test/patest_ringmix.c
deleted file mode 100644
index 2db670631e12918fa8013bc8d1befd9f1ccc6de9..0000000000000000000000000000000000000000
--- a/spaces/prerna9811/Chord/portaudio/test/patest_ringmix.c
+++ /dev/null
@@ -1,86 +0,0 @@
-/** @file patest_ringmix.c
-    @ingroup test_src
-    @brief Ring modulate inputs to left output, mix inputs to right output.
-*/
-/*
- * $Id$
- *
- * This program uses the PortAudio Portable Audio Library.
- * For more information see: http://www.portaudio.com
- * Copyright (c) 1999-2000 Ross Bencina and Phil Burk
- *
- * Permission is hereby granted, free of charge, to any person obtaining
- * a copy of this software and associated documentation files
- * (the "Software"), to deal in the Software without restriction,
- * including without limitation the rights to use, copy, modify, merge,
- * publish, distribute, sublicense, and/or sell copies of the Software,
- * and to permit persons to whom the Software is furnished to do so,
- * subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be
- * included in all copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
- * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
- * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
- * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR
- * ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF
- * CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
- * WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
- */
-
-/*
- * The text above constitutes the entire PortAudio license; however,
- * the PortAudio community also makes the following non-binding requests:
- *
- * Any person wishing to distribute modifications to the Software is
- * requested to send the modifications to the original developer so that
- * they can be incorporated into the canonical version. It is also
- * requested that these non-binding requests be included along with the
- * license above.
- */
-
-
-#include "stdio.h"
-#include "portaudio.h"
-/* This will be called asynchronously by the PortAudio engine. */
-static int myCallback( const void *inputBuffer, void *outputBuffer,
-                            unsigned long framesPerBuffer,
-                            const PaStreamCallbackTimeInfo* timeInfo,
-                            PaStreamCallbackFlags statusFlags,
-                            void *userData )
-{
-    const float *in  = (const float *) inputBuffer;
-    float *out = (float *) outputBuffer;
-    float leftInput, rightInput;
-    unsigned int i;
-
-    /* Read input buffer, process data, and fill output buffer. */
-    for( i=0; i<framesPerBuffer; i++ )
-    {
-        leftInput = *in++;      /* Get interleaved samples from input buffer. */
-        rightInput = *in++;
-        *out++ = leftInput * rightInput;            /* ring modulation */
-        *out++ = 0.5f * (leftInput + rightInput);   /* mix */
-    }
-    return 0;
-}
-
-/* Open a PortAudioStream to input and output audio data. */
-int main(void)
-{
-    PaStream *stream;
-    Pa_Initialize();
-    Pa_OpenDefaultStream(
-        &stream,
-        2, 2,               /* stereo input and output */
-        paFloat32,  44100.0,
-        64,                 /* 64 frames per buffer */
-        myCallback, NULL );
-    Pa_StartStream( stream );
-    Pa_Sleep( 10000 );    /* Sleep for 10 seconds while processing. */
-    Pa_StopStream( stream );
-    Pa_CloseStream( stream );
-    Pa_Terminate();
-    return 0;
-}
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/PIL/ImageMath.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/PIL/ImageMath.py
deleted file mode 100644
index eb6bbe6c62e88e4dce32c346f01917fb6f09eaaf..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/PIL/ImageMath.py
+++ /dev/null
@@ -1,263 +0,0 @@
-#
-# The Python Imaging Library
-# $Id$
-#
-# a simple math add-on for the Python Imaging Library
-#
-# History:
-# 1999-02-15 fl   Original PIL Plus release
-# 2005-05-05 fl   Simplified and cleaned up for PIL 1.1.6
-# 2005-09-12 fl   Fixed int() and float() for Python 2.4.1
-#
-# Copyright (c) 1999-2005 by Secret Labs AB
-# Copyright (c) 2005 by Fredrik Lundh
-#
-# See the README file for information on usage and redistribution.
-#
-
-import builtins
-
-from . import Image, _imagingmath
-
-
-def _isconstant(v):
-    return isinstance(v, (int, float))
-
-
-class _Operand:
-    """Wraps an image operand, providing standard operators"""
-
-    def __init__(self, im):
-        self.im = im
-
-    def __fixup(self, im1):
-        # convert image to suitable mode
-        if isinstance(im1, _Operand):
-            # argument was an image.
-            if im1.im.mode in ("1", "L"):
-                return im1.im.convert("I")
-            elif im1.im.mode in ("I", "F"):
-                return im1.im
-            else:
-                msg = f"unsupported mode: {im1.im.mode}"
-                raise ValueError(msg)
-        else:
-            # argument was a constant
-            if _isconstant(im1) and self.im.mode in ("1", "L", "I"):
-                return Image.new("I", self.im.size, im1)
-            else:
-                return Image.new("F", self.im.size, im1)
-
-    def apply(self, op, im1, im2=None, mode=None):
-        im1 = self.__fixup(im1)
-        if im2 is None:
-            # unary operation
-            out = Image.new(mode or im1.mode, im1.size, None)
-            im1.load()
-            try:
-                op = getattr(_imagingmath, op + "_" + im1.mode)
-            except AttributeError as e:
-                msg = f"bad operand type for '{op}'"
-                raise TypeError(msg) from e
-            _imagingmath.unop(op, out.im.id, im1.im.id)
-        else:
-            # binary operation
-            im2 = self.__fixup(im2)
-            if im1.mode != im2.mode:
-                # convert both arguments to floating point
-                if im1.mode != "F":
-                    im1 = im1.convert("F")
-                if im2.mode != "F":
-                    im2 = im2.convert("F")
-            if im1.size != im2.size:
-                # crop both arguments to a common size
-                size = (min(im1.size[0], im2.size[0]), min(im1.size[1], im2.size[1]))
-                if im1.size != size:
-                    im1 = im1.crop((0, 0) + size)
-                if im2.size != size:
-                    im2 = im2.crop((0, 0) + size)
-            out = Image.new(mode or im1.mode, im1.size, None)
-            im1.load()
-            im2.load()
-            try:
-                op = getattr(_imagingmath, op + "_" + im1.mode)
-            except AttributeError as e:
-                msg = f"bad operand type for '{op}'"
-                raise TypeError(msg) from e
-            _imagingmath.binop(op, out.im.id, im1.im.id, im2.im.id)
-        return _Operand(out)
-
-    # unary operators
-    def __bool__(self):
-        # an image is "true" if it contains at least one non-zero pixel
-        return self.im.getbbox() is not None
-
-    def __abs__(self):
-        return self.apply("abs", self)
-
-    def __pos__(self):
-        return self
-
-    def __neg__(self):
-        return self.apply("neg", self)
-
-    # binary operators
-    def __add__(self, other):
-        return self.apply("add", self, other)
-
-    def __radd__(self, other):
-        return self.apply("add", other, self)
-
-    def __sub__(self, other):
-        return self.apply("sub", self, other)
-
-    def __rsub__(self, other):
-        return self.apply("sub", other, self)
-
-    def __mul__(self, other):
-        return self.apply("mul", self, other)
-
-    def __rmul__(self, other):
-        return self.apply("mul", other, self)
-
-    def __truediv__(self, other):
-        return self.apply("div", self, other)
-
-    def __rtruediv__(self, other):
-        return self.apply("div", other, self)
-
-    def __mod__(self, other):
-        return self.apply("mod", self, other)
-
-    def __rmod__(self, other):
-        return self.apply("mod", other, self)
-
-    def __pow__(self, other):
-        return self.apply("pow", self, other)
-
-    def __rpow__(self, other):
-        return self.apply("pow", other, self)
-
-    # bitwise
-    def __invert__(self):
-        return self.apply("invert", self)
-
-    def __and__(self, other):
-        return self.apply("and", self, other)
-
-    def __rand__(self, other):
-        return self.apply("and", other, self)
-
-    def __or__(self, other):
-        return self.apply("or", self, other)
-
-    def __ror__(self, other):
-        return self.apply("or", other, self)
-
-    def __xor__(self, other):
-        return self.apply("xor", self, other)
-
-    def __rxor__(self, other):
-        return self.apply("xor", other, self)
-
-    def __lshift__(self, other):
-        return self.apply("lshift", self, other)
-
-    def __rshift__(self, other):
-        return self.apply("rshift", self, other)
-
-    # logical
-    def __eq__(self, other):
-        return self.apply("eq", self, other)
-
-    def __ne__(self, other):
-        return self.apply("ne", self, other)
-
-    def __lt__(self, other):
-        return self.apply("lt", self, other)
-
-    def __le__(self, other):
-        return self.apply("le", self, other)
-
-    def __gt__(self, other):
-        return self.apply("gt", self, other)
-
-    def __ge__(self, other):
-        return self.apply("ge", self, other)
-
-
-# conversions
-def imagemath_int(self):
-    return _Operand(self.im.convert("I"))
-
-
-def imagemath_float(self):
-    return _Operand(self.im.convert("F"))
-
-
-# logical
-def imagemath_equal(self, other):
-    return self.apply("eq", self, other, mode="I")
-
-
-def imagemath_notequal(self, other):
-    return self.apply("ne", self, other, mode="I")
-
-
-def imagemath_min(self, other):
-    return self.apply("min", self, other)
-
-
-def imagemath_max(self, other):
-    return self.apply("max", self, other)
-
-
-def imagemath_convert(self, mode):
-    return _Operand(self.im.convert(mode))
-
-
-ops = {}
-for k, v in list(globals().items()):
-    if k[:10] == "imagemath_":
-        ops[k[10:]] = v
-
-
-def eval(expression, _dict={}, **kw):
-    """
-    Evaluates an image expression.
-
-    :param expression: A string containing a Python-style expression.
-    :param options: Values to add to the evaluation context.  You
-                    can either use a dictionary, or one or more keyword
-                    arguments.
-    :return: The evaluated expression. This is usually an image object, but can
-             also be an integer, a floating point value, or a pixel tuple,
-             depending on the expression.
-    """
-
-    # build execution namespace
-    args = ops.copy()
-    args.update(_dict)
-    args.update(kw)
-    for k, v in list(args.items()):
-        if hasattr(v, "im"):
-            args[k] = _Operand(v)
-
-    compiled_code = compile(expression, "<string>", "eval")
-
-    def scan(code):
-        for const in code.co_consts:
-            if type(const) is type(compiled_code):
-                scan(const)
-
-        for name in code.co_names:
-            if name not in args and name != "abs":
-                msg = f"'{name}' not allowed"
-                raise ValueError(msg)
-
-    scan(compiled_code)
-    out = builtins.eval(expression, {"__builtins": {"abs": abs}}, args)
-    try:
-        return out.im
-    except AttributeError:
-        return out
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/PIL/SgiImagePlugin.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/PIL/SgiImagePlugin.py
deleted file mode 100644
index acb9ce5a38cff8772b6f1354f2e65db7409b83f9..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/PIL/SgiImagePlugin.py
+++ /dev/null
@@ -1,231 +0,0 @@
-#
-# The Python Imaging Library.
-# $Id$
-#
-# SGI image file handling
-#
-# See "The SGI Image File Format (Draft version 0.97)", Paul Haeberli.
-# <ftp://ftp.sgi.com/graphics/SGIIMAGESPEC>
-#
-#
-# History:
-# 2017-22-07 mb   Add RLE decompression
-# 2016-16-10 mb   Add save method without compression
-# 1995-09-10 fl   Created
-#
-# Copyright (c) 2016 by Mickael Bonfill.
-# Copyright (c) 2008 by Karsten Hiddemann.
-# Copyright (c) 1997 by Secret Labs AB.
-# Copyright (c) 1995 by Fredrik Lundh.
-#
-# See the README file for information on usage and redistribution.
-#
-
-
-import os
-import struct
-
-from . import Image, ImageFile
-from ._binary import i16be as i16
-from ._binary import o8
-
-
-def _accept(prefix):
-    return len(prefix) >= 2 and i16(prefix) == 474
-
-
-MODES = {
-    (1, 1, 1): "L",
-    (1, 2, 1): "L",
-    (2, 1, 1): "L;16B",
-    (2, 2, 1): "L;16B",
-    (1, 3, 3): "RGB",
-    (2, 3, 3): "RGB;16B",
-    (1, 3, 4): "RGBA",
-    (2, 3, 4): "RGBA;16B",
-}
-
-
-##
-# Image plugin for SGI images.
-class SgiImageFile(ImageFile.ImageFile):
-    format = "SGI"
-    format_description = "SGI Image File Format"
-
-    def _open(self):
-        # HEAD
-        headlen = 512
-        s = self.fp.read(headlen)
-
-        if not _accept(s):
-            msg = "Not an SGI image file"
-            raise ValueError(msg)
-
-        # compression : verbatim or RLE
-        compression = s[2]
-
-        # bpc : 1 or 2 bytes (8bits or 16bits)
-        bpc = s[3]
-
-        # dimension : 1, 2 or 3 (depending on xsize, ysize and zsize)
-        dimension = i16(s, 4)
-
-        # xsize : width
-        xsize = i16(s, 6)
-
-        # ysize : height
-        ysize = i16(s, 8)
-
-        # zsize : channels count
-        zsize = i16(s, 10)
-
-        # layout
-        layout = bpc, dimension, zsize
-
-        # determine mode from bits/zsize
-        rawmode = ""
-        try:
-            rawmode = MODES[layout]
-        except KeyError:
-            pass
-
-        if rawmode == "":
-            msg = "Unsupported SGI image mode"
-            raise ValueError(msg)
-
-        self._size = xsize, ysize
-        self._mode = rawmode.split(";")[0]
-        if self.mode == "RGB":
-            self.custom_mimetype = "image/rgb"
-
-        # orientation -1 : scanlines begins at the bottom-left corner
-        orientation = -1
-
-        # decoder info
-        if compression == 0:
-            pagesize = xsize * ysize * bpc
-            if bpc == 2:
-                self.tile = [
-                    ("SGI16", (0, 0) + self.size, headlen, (self.mode, 0, orientation))
-                ]
-            else:
-                self.tile = []
-                offset = headlen
-                for layer in self.mode:
-                    self.tile.append(
-                        ("raw", (0, 0) + self.size, offset, (layer, 0, orientation))
-                    )
-                    offset += pagesize
-        elif compression == 1:
-            self.tile = [
-                ("sgi_rle", (0, 0) + self.size, headlen, (rawmode, orientation, bpc))
-            ]
-
-
-def _save(im, fp, filename):
-    if im.mode != "RGB" and im.mode != "RGBA" and im.mode != "L":
-        msg = "Unsupported SGI image mode"
-        raise ValueError(msg)
-
-    # Get the keyword arguments
-    info = im.encoderinfo
-
-    # Byte-per-pixel precision, 1 = 8bits per pixel
-    bpc = info.get("bpc", 1)
-
-    if bpc not in (1, 2):
-        msg = "Unsupported number of bytes per pixel"
-        raise ValueError(msg)
-
-    # Flip the image, since the origin of SGI file is the bottom-left corner
-    orientation = -1
-    # Define the file as SGI File Format
-    magic_number = 474
-    # Run-Length Encoding Compression - Unsupported at this time
-    rle = 0
-
-    # Number of dimensions (x,y,z)
-    dim = 3
-    # X Dimension = width / Y Dimension = height
-    x, y = im.size
-    if im.mode == "L" and y == 1:
-        dim = 1
-    elif im.mode == "L":
-        dim = 2
-    # Z Dimension: Number of channels
-    z = len(im.mode)
-
-    if dim == 1 or dim == 2:
-        z = 1
-
-    # assert we've got the right number of bands.
-    if len(im.getbands()) != z:
-        msg = f"incorrect number of bands in SGI write: {z} vs {len(im.getbands())}"
-        raise ValueError(msg)
-
-    # Minimum Byte value
-    pinmin = 0
-    # Maximum Byte value (255 = 8bits per pixel)
-    pinmax = 255
-    # Image name (79 characters max, truncated below in write)
-    img_name = os.path.splitext(os.path.basename(filename))[0]
-    img_name = img_name.encode("ascii", "ignore")
-    # Standard representation of pixel in the file
-    colormap = 0
-    fp.write(struct.pack(">h", magic_number))
-    fp.write(o8(rle))
-    fp.write(o8(bpc))
-    fp.write(struct.pack(">H", dim))
-    fp.write(struct.pack(">H", x))
-    fp.write(struct.pack(">H", y))
-    fp.write(struct.pack(">H", z))
-    fp.write(struct.pack(">l", pinmin))
-    fp.write(struct.pack(">l", pinmax))
-    fp.write(struct.pack("4s", b""))  # dummy
-    fp.write(struct.pack("79s", img_name))  # truncates to 79 chars
-    fp.write(struct.pack("s", b""))  # force null byte after img_name
-    fp.write(struct.pack(">l", colormap))
-    fp.write(struct.pack("404s", b""))  # dummy
-
-    rawmode = "L"
-    if bpc == 2:
-        rawmode = "L;16B"
-
-    for channel in im.split():
-        fp.write(channel.tobytes("raw", rawmode, 0, orientation))
-
-    if hasattr(fp, "flush"):
-        fp.flush()
-
-
-class SGI16Decoder(ImageFile.PyDecoder):
-    _pulls_fd = True
-
-    def decode(self, buffer):
-        rawmode, stride, orientation = self.args
-        pagesize = self.state.xsize * self.state.ysize
-        zsize = len(self.mode)
-        self.fd.seek(512)
-
-        for band in range(zsize):
-            channel = Image.new("L", (self.state.xsize, self.state.ysize))
-            channel.frombytes(
-                self.fd.read(2 * pagesize), "raw", "L;16B", stride, orientation
-            )
-            self.im.putband(channel.im, band)
-
-        return -1, 0
-
-
-#
-# registry
-
-
-Image.register_decoder("SGI16", SGI16Decoder)
-Image.register_open(SgiImageFile.format, SgiImageFile, _accept)
-Image.register_save(SgiImageFile.format, _save)
-Image.register_mime(SgiImageFile.format, "image/sgi")
-
-Image.register_extensions(SgiImageFile.format, [".bw", ".rgb", ".rgba", ".sgi"])
-
-# End of file
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/aiofiles/__init__.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/aiofiles/__init__.py
deleted file mode 100644
index 9e7511148df475d077a1c0af4d8edf71a17a6c7b..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/aiofiles/__init__.py
+++ /dev/null
@@ -1,22 +0,0 @@
-"""Utilities for asyncio-friendly file handling."""
-from .threadpool import (
-    open,
-    stdin,
-    stdout,
-    stderr,
-    stdin_bytes,
-    stdout_bytes,
-    stderr_bytes,
-)
-from . import tempfile
-
-__all__ = [
-    "open",
-    "tempfile",
-    "stdin",
-    "stdout",
-    "stderr",
-    "stdin_bytes",
-    "stdout_bytes",
-    "stderr_bytes",
-]
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/certifi/__main__.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/certifi/__main__.py
deleted file mode 100644
index 8945b5da857f4a7dec2b84f1225f012f6098418c..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/certifi/__main__.py
+++ /dev/null
@@ -1,12 +0,0 @@
-import argparse
-
-from certifi import contents, where
-
-parser = argparse.ArgumentParser()
-parser.add_argument("-c", "--contents", action="store_true")
-args = parser.parse_args()
-
-if args.contents:
-    print(contents())
-else:
-    print(where())
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/fastapi/responses.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/fastapi/responses.py
deleted file mode 100644
index 6c8db6f3353fffa953aa8efdd89739e2bda4c476..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/fastapi/responses.py
+++ /dev/null
@@ -1,48 +0,0 @@
-from typing import Any
-
-from starlette.responses import FileResponse as FileResponse  # noqa
-from starlette.responses import HTMLResponse as HTMLResponse  # noqa
-from starlette.responses import JSONResponse as JSONResponse  # noqa
-from starlette.responses import PlainTextResponse as PlainTextResponse  # noqa
-from starlette.responses import RedirectResponse as RedirectResponse  # noqa
-from starlette.responses import Response as Response  # noqa
-from starlette.responses import StreamingResponse as StreamingResponse  # noqa
-
-try:
-    import ujson
-except ImportError:  # pragma: nocover
-    ujson = None  # type: ignore
-
-
-try:
-    import orjson
-except ImportError:  # pragma: nocover
-    orjson = None  # type: ignore
-
-
-class UJSONResponse(JSONResponse):
-    """
-    JSON response using the high-performance ujson library to serialize data to JSON.
-
-    Read more about it in the
-    [FastAPI docs for Custom Response - HTML, Stream, File, others](https://fastapi.tiangolo.com/advanced/custom-response/).
-    """
-
-    def render(self, content: Any) -> bytes:
-        assert ujson is not None, "ujson must be installed to use UJSONResponse"
-        return ujson.dumps(content, ensure_ascii=False).encode("utf-8")
-
-
-class ORJSONResponse(JSONResponse):
-    """
-    JSON response using the high-performance orjson library to serialize data to JSON.
-
-    Read more about it in the
-    [FastAPI docs for Custom Response - HTML, Stream, File, others](https://fastapi.tiangolo.com/advanced/custom-response/).
-    """
-
-    def render(self, content: Any) -> bytes:
-        assert orjson is not None, "orjson must be installed to use ORJSONResponse"
-        return orjson.dumps(
-            content, option=orjson.OPT_NON_STR_KEYS | orjson.OPT_SERIALIZE_NUMPY
-        )
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/fsspec/implementations/cache_mapper.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/fsspec/implementations/cache_mapper.py
deleted file mode 100644
index 000ccebc83304369cd00fcd8b3458b852c366530..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/fsspec/implementations/cache_mapper.py
+++ /dev/null
@@ -1,80 +0,0 @@
-from __future__ import annotations
-
-import abc
-import hashlib
-from typing import TYPE_CHECKING
-
-from fsspec.implementations.local import make_path_posix
-
-if TYPE_CHECKING:
-    from typing import Any
-
-
-class AbstractCacheMapper(abc.ABC):
-    """Abstract super-class for mappers from remote URLs to local cached
-    basenames.
-    """
-
-    @abc.abstractmethod
-    def __call__(self, path: str) -> str:
-        ...
-
-    def __eq__(self, other: Any) -> bool:
-        # Identity only depends on class. When derived classes have attributes
-        # they will need to be included.
-        return isinstance(other, type(self))
-
-    def __hash__(self) -> int:
-        # Identity only depends on class. When derived classes have attributes
-        # they will need to be included.
-        return hash(type(self))
-
-
-class BasenameCacheMapper(AbstractCacheMapper):
-    """Cache mapper that uses the basename of the remote URL and a fixed number
-    of directory levels above this.
-
-    The default is zero directory levels, meaning different paths with the same
-    basename will have the same cached basename.
-    """
-
-    def __init__(self, directory_levels: int = 0):
-        if directory_levels < 0:
-            raise ValueError(
-                "BasenameCacheMapper requires zero or positive directory_levels"
-            )
-        self.directory_levels = directory_levels
-
-        # Separator for directories when encoded as strings.
-        self._separator = "_@_"
-
-    def __call__(self, path: str) -> str:
-        path = make_path_posix(path)
-        prefix, *bits = path.rsplit("/", self.directory_levels + 1)
-        if bits:
-            return self._separator.join(bits)
-        else:
-            return prefix  # No separator found, simple filename
-
-    def __eq__(self, other: Any) -> bool:
-        return super().__eq__(other) and self.directory_levels == other.directory_levels
-
-    def __hash__(self) -> int:
-        return super().__hash__() ^ hash(self.directory_levels)
-
-
-class HashCacheMapper(AbstractCacheMapper):
-    """Cache mapper that uses a hash of the remote URL."""
-
-    def __call__(self, path: str) -> str:
-        return hashlib.sha256(path.encode()).hexdigest()
-
-
-def create_cache_mapper(same_names: bool) -> AbstractCacheMapper:
-    """Factory method to create cache mapper for backward compatibility with
-    ``CachingFileSystem`` constructor using ``same_names`` kwarg.
-    """
-    if same_names:
-        return BasenameCacheMapper()
-    else:
-        return HashCacheMapper()
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/gradio/_frontend_code/client/vite.config.js b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/gradio/_frontend_code/client/vite.config.js
deleted file mode 100644
index 985554d9e5f20520c5858119392222f52f67475a..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/gradio/_frontend_code/client/vite.config.js
+++ /dev/null
@@ -1,38 +0,0 @@
-import { defineConfig } from "vite";
-import { svelte } from "@sveltejs/vite-plugin-svelte";
-import { fileURLToPath } from "url";
-import path from "path";
-const __dirname = fileURLToPath(new URL(".", import.meta.url));
-
-export default defineConfig({
-	build: {
-		lib: {
-			entry: "src/index.ts",
-			formats: ["es"]
-		},
-		rollupOptions: {
-			input: "src/index.ts",
-			output: {
-				dir: "dist"
-			}
-		}
-	},
-	plugins: [
-		svelte()
-		// {
-		// 	name: "resolve-gradio-client",
-		// 	enforce: "pre",
-		// 	resolveId(id) {
-		// 		if (id === "@gradio/client") {
-		// 			return path.join(__dirname, "src", "index.ts");
-		// 		}
-		// 	}
-		// }
-	],
-
-	ssr: {
-		target: "node",
-		format: "esm",
-		noExternal: ["ws", "semiver", "@gradio/upload"]
-	}
-});
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/jinja2/optimizer.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/jinja2/optimizer.py
deleted file mode 100644
index fe1010705e7b29d4fa1900b3a0438ab93d7b582c..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/jinja2/optimizer.py
+++ /dev/null
@@ -1,47 +0,0 @@
-"""The optimizer tries to constant fold expressions and modify the AST
-in place so that it should be faster to evaluate.
-
-Because the AST does not contain all the scoping information and the
-compiler has to find that out, we cannot do all the optimizations we
-want. For example, loop unrolling doesn't work because unrolled loops
-would have a different scope. The solution would be a second syntax tree
-that stored the scoping rules.
-"""
-import typing as t
-
-from . import nodes
-from .visitor import NodeTransformer
-
-if t.TYPE_CHECKING:
-    from .environment import Environment
-
-
-def optimize(node: nodes.Node, environment: "Environment") -> nodes.Node:
-    """The context hint can be used to perform an static optimization
-    based on the context given."""
-    optimizer = Optimizer(environment)
-    return t.cast(nodes.Node, optimizer.visit(node))
-
-
-class Optimizer(NodeTransformer):
-    def __init__(self, environment: "t.Optional[Environment]") -> None:
-        self.environment = environment
-
-    def generic_visit(
-        self, node: nodes.Node, *args: t.Any, **kwargs: t.Any
-    ) -> nodes.Node:
-        node = super().generic_visit(node, *args, **kwargs)
-
-        # Do constant folding. Some other nodes besides Expr have
-        # as_const, but folding them causes errors later on.
-        if isinstance(node, nodes.Expr):
-            try:
-                return nodes.Const.from_untrusted(
-                    node.as_const(args[0] if args else None),
-                    lineno=node.lineno,
-                    environment=self.environment,
-                )
-            except nodes.Impossible:
-                pass
-
-        return node
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/io/sql.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/io/sql.py
deleted file mode 100644
index c1d68d71ac91c860812e92ebbdf2485a3a87fded..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/io/sql.py
+++ /dev/null
@@ -1,2515 +0,0 @@
-"""
-Collection of query wrappers / abstractions to both facilitate data
-retrieval and to reduce dependency on DB-specific API.
-"""
-
-from __future__ import annotations
-
-from abc import (
-    ABC,
-    abstractmethod,
-)
-from contextlib import (
-    ExitStack,
-    contextmanager,
-)
-from datetime import (
-    date,
-    datetime,
-    time,
-)
-from functools import partial
-import re
-from typing import (
-    TYPE_CHECKING,
-    Any,
-    Callable,
-    Literal,
-    cast,
-    overload,
-)
-import warnings
-
-import numpy as np
-
-from pandas._libs import lib
-from pandas.compat._optional import import_optional_dependency
-from pandas.errors import (
-    AbstractMethodError,
-    DatabaseError,
-)
-from pandas.util._exceptions import find_stack_level
-from pandas.util._validators import check_dtype_backend
-
-from pandas.core.dtypes.common import (
-    is_dict_like,
-    is_list_like,
-)
-from pandas.core.dtypes.dtypes import DatetimeTZDtype
-from pandas.core.dtypes.missing import isna
-
-from pandas import get_option
-from pandas.core.api import (
-    DataFrame,
-    Series,
-)
-from pandas.core.arrays import ArrowExtensionArray
-from pandas.core.base import PandasObject
-import pandas.core.common as com
-from pandas.core.internals.construction import convert_object_array
-from pandas.core.tools.datetimes import to_datetime
-
-if TYPE_CHECKING:
-    from collections.abc import (
-        Iterator,
-        Mapping,
-    )
-
-    from sqlalchemy import Table
-    from sqlalchemy.sql.expression import (
-        Select,
-        TextClause,
-    )
-
-    from pandas._typing import (
-        DateTimeErrorChoices,
-        DtypeArg,
-        DtypeBackend,
-        IndexLabel,
-        Self,
-    )
-
-    from pandas import Index
-
-# -----------------------------------------------------------------------------
-# -- Helper functions
-
-
-def _process_parse_dates_argument(parse_dates):
-    """Process parse_dates argument for read_sql functions"""
-    # handle non-list entries for parse_dates gracefully
-    if parse_dates is True or parse_dates is None or parse_dates is False:
-        parse_dates = []
-
-    elif not hasattr(parse_dates, "__iter__"):
-        parse_dates = [parse_dates]
-    return parse_dates
-
-
-def _handle_date_column(
-    col, utc: bool = False, format: str | dict[str, Any] | None = None
-):
-    if isinstance(format, dict):
-        # GH35185 Allow custom error values in parse_dates argument of
-        # read_sql like functions.
-        # Format can take on custom to_datetime argument values such as
-        # {"errors": "coerce"} or {"dayfirst": True}
-        error: DateTimeErrorChoices = format.pop("errors", None) or "ignore"
-        return to_datetime(col, errors=error, **format)
-    else:
-        # Allow passing of formatting string for integers
-        # GH17855
-        if format is None and (
-            issubclass(col.dtype.type, np.floating)
-            or issubclass(col.dtype.type, np.integer)
-        ):
-            format = "s"
-        if format in ["D", "d", "h", "m", "s", "ms", "us", "ns"]:
-            return to_datetime(col, errors="coerce", unit=format, utc=utc)
-        elif isinstance(col.dtype, DatetimeTZDtype):
-            # coerce to UTC timezone
-            # GH11216
-            return to_datetime(col, utc=True)
-        else:
-            return to_datetime(col, errors="coerce", format=format, utc=utc)
-
-
-def _parse_date_columns(data_frame, parse_dates):
-    """
-    Force non-datetime columns to be read as such.
-    Supports both string formatted and integer timestamp columns.
-    """
-    parse_dates = _process_parse_dates_argument(parse_dates)
-
-    # we want to coerce datetime64_tz dtypes for now to UTC
-    # we could in theory do a 'nice' conversion from a FixedOffset tz
-    # GH11216
-    for i, (col_name, df_col) in enumerate(data_frame.items()):
-        if isinstance(df_col.dtype, DatetimeTZDtype) or col_name in parse_dates:
-            try:
-                fmt = parse_dates[col_name]
-            except TypeError:
-                fmt = None
-            data_frame.isetitem(i, _handle_date_column(df_col, format=fmt))
-
-    return data_frame
-
-
-def _convert_arrays_to_dataframe(
-    data,
-    columns,
-    coerce_float: bool = True,
-    dtype_backend: DtypeBackend | Literal["numpy"] = "numpy",
-) -> DataFrame:
-    content = lib.to_object_array_tuples(data)
-    arrays = convert_object_array(
-        list(content.T),
-        dtype=None,
-        coerce_float=coerce_float,
-        dtype_backend=dtype_backend,
-    )
-    if dtype_backend == "pyarrow":
-        pa = import_optional_dependency("pyarrow")
-        arrays = [
-            ArrowExtensionArray(pa.array(arr, from_pandas=True)) for arr in arrays
-        ]
-    if arrays:
-        df = DataFrame(dict(zip(list(range(len(columns))), arrays)))
-        df.columns = columns
-        return df
-    else:
-        return DataFrame(columns=columns)
-
-
-def _wrap_result(
-    data,
-    columns,
-    index_col=None,
-    coerce_float: bool = True,
-    parse_dates=None,
-    dtype: DtypeArg | None = None,
-    dtype_backend: DtypeBackend | Literal["numpy"] = "numpy",
-):
-    """Wrap result set of query in a DataFrame."""
-    frame = _convert_arrays_to_dataframe(data, columns, coerce_float, dtype_backend)
-
-    if dtype:
-        frame = frame.astype(dtype)
-
-    frame = _parse_date_columns(frame, parse_dates)
-
-    if index_col is not None:
-        frame = frame.set_index(index_col)
-
-    return frame
-
-
-def execute(sql, con, params=None):
-    """
-    Execute the given SQL query using the provided connection object.
-
-    Parameters
-    ----------
-    sql : string
-        SQL query to be executed.
-    con : SQLAlchemy connection or sqlite3 connection
-        If a DBAPI2 object, only sqlite3 is supported.
-    params : list or tuple, optional, default: None
-        List of parameters to pass to execute method.
-
-    Returns
-    -------
-    Results Iterable
-    """
-    warnings.warn(
-        "`pandas.io.sql.execute` is deprecated and "
-        "will be removed in the future version.",
-        FutureWarning,
-        stacklevel=find_stack_level(),
-    )  # GH50185
-    sqlalchemy = import_optional_dependency("sqlalchemy", errors="ignore")
-
-    if sqlalchemy is not None and isinstance(con, (str, sqlalchemy.engine.Engine)):
-        raise TypeError("pandas.io.sql.execute requires a connection")  # GH50185
-    with pandasSQL_builder(con, need_transaction=True) as pandas_sql:
-        return pandas_sql.execute(sql, params)
-
-
-# -----------------------------------------------------------------------------
-# -- Read and write to DataFrames
-
-
-@overload
-def read_sql_table(
-    table_name: str,
-    con,
-    schema=...,
-    index_col: str | list[str] | None = ...,
-    coerce_float=...,
-    parse_dates: list[str] | dict[str, str] | None = ...,
-    columns: list[str] | None = ...,
-    chunksize: None = ...,
-    dtype_backend: DtypeBackend | lib.NoDefault = ...,
-) -> DataFrame:
-    ...
-
-
-@overload
-def read_sql_table(
-    table_name: str,
-    con,
-    schema=...,
-    index_col: str | list[str] | None = ...,
-    coerce_float=...,
-    parse_dates: list[str] | dict[str, str] | None = ...,
-    columns: list[str] | None = ...,
-    chunksize: int = ...,
-    dtype_backend: DtypeBackend | lib.NoDefault = ...,
-) -> Iterator[DataFrame]:
-    ...
-
-
-def read_sql_table(
-    table_name: str,
-    con,
-    schema: str | None = None,
-    index_col: str | list[str] | None = None,
-    coerce_float: bool = True,
-    parse_dates: list[str] | dict[str, str] | None = None,
-    columns: list[str] | None = None,
-    chunksize: int | None = None,
-    dtype_backend: DtypeBackend | lib.NoDefault = lib.no_default,
-) -> DataFrame | Iterator[DataFrame]:
-    """
-    Read SQL database table into a DataFrame.
-
-    Given a table name and a SQLAlchemy connectable, returns a DataFrame.
-    This function does not support DBAPI connections.
-
-    Parameters
-    ----------
-    table_name : str
-        Name of SQL table in database.
-    con : SQLAlchemy connectable or str
-        A database URI could be provided as str.
-        SQLite DBAPI connection mode not supported.
-    schema : str, default None
-        Name of SQL schema in database to query (if database flavor
-        supports this). Uses default schema if None (default).
-    index_col : str or list of str, optional, default: None
-        Column(s) to set as index(MultiIndex).
-    coerce_float : bool, default True
-        Attempts to convert values of non-string, non-numeric objects (like
-        decimal.Decimal) to floating point. Can result in loss of Precision.
-    parse_dates : list or dict, default None
-        - List of column names to parse as dates.
-        - Dict of ``{column_name: format string}`` where format string is
-          strftime compatible in case of parsing string times or is one of
-          (D, s, ns, ms, us) in case of parsing integer timestamps.
-        - Dict of ``{column_name: arg dict}``, where the arg dict corresponds
-          to the keyword arguments of :func:`pandas.to_datetime`
-          Especially useful with databases without native Datetime support,
-          such as SQLite.
-    columns : list, default None
-        List of column names to select from SQL table.
-    chunksize : int, default None
-        If specified, returns an iterator where `chunksize` is the number of
-        rows to include in each chunk.
-    dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
-        Back-end data type applied to the resultant :class:`DataFrame`
-        (still experimental). Behaviour is as follows:
-
-        * ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
-          (default).
-        * ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
-          DataFrame.
-
-        .. versionadded:: 2.0
-
-    Returns
-    -------
-    DataFrame or Iterator[DataFrame]
-        A SQL table is returned as two-dimensional data structure with labeled
-        axes.
-
-    See Also
-    --------
-    read_sql_query : Read SQL query into a DataFrame.
-    read_sql : Read SQL query or database table into a DataFrame.
-
-    Notes
-    -----
-    Any datetime values with time zone information will be converted to UTC.
-
-    Examples
-    --------
-    >>> pd.read_sql_table('table_name', 'postgres:///db_name')  # doctest:+SKIP
-    """
-
-    check_dtype_backend(dtype_backend)
-    if dtype_backend is lib.no_default:
-        dtype_backend = "numpy"  # type: ignore[assignment]
-    assert dtype_backend is not lib.no_default
-
-    with pandasSQL_builder(con, schema=schema, need_transaction=True) as pandas_sql:
-        if not pandas_sql.has_table(table_name):
-            raise ValueError(f"Table {table_name} not found")
-
-        table = pandas_sql.read_table(
-            table_name,
-            index_col=index_col,
-            coerce_float=coerce_float,
-            parse_dates=parse_dates,
-            columns=columns,
-            chunksize=chunksize,
-            dtype_backend=dtype_backend,
-        )
-
-    if table is not None:
-        return table
-    else:
-        raise ValueError(f"Table {table_name} not found", con)
-
-
-@overload
-def read_sql_query(
-    sql,
-    con,
-    index_col: str | list[str] | None = ...,
-    coerce_float=...,
-    params: list[Any] | Mapping[str, Any] | None = ...,
-    parse_dates: list[str] | dict[str, str] | None = ...,
-    chunksize: None = ...,
-    dtype: DtypeArg | None = ...,
-    dtype_backend: DtypeBackend | lib.NoDefault = ...,
-) -> DataFrame:
-    ...
-
-
-@overload
-def read_sql_query(
-    sql,
-    con,
-    index_col: str | list[str] | None = ...,
-    coerce_float=...,
-    params: list[Any] | Mapping[str, Any] | None = ...,
-    parse_dates: list[str] | dict[str, str] | None = ...,
-    chunksize: int = ...,
-    dtype: DtypeArg | None = ...,
-    dtype_backend: DtypeBackend | lib.NoDefault = ...,
-) -> Iterator[DataFrame]:
-    ...
-
-
-def read_sql_query(
-    sql,
-    con,
-    index_col: str | list[str] | None = None,
-    coerce_float: bool = True,
-    params: list[Any] | Mapping[str, Any] | None = None,
-    parse_dates: list[str] | dict[str, str] | None = None,
-    chunksize: int | None = None,
-    dtype: DtypeArg | None = None,
-    dtype_backend: DtypeBackend | lib.NoDefault = lib.no_default,
-) -> DataFrame | Iterator[DataFrame]:
-    """
-    Read SQL query into a DataFrame.
-
-    Returns a DataFrame corresponding to the result set of the query
-    string. Optionally provide an `index_col` parameter to use one of the
-    columns as the index, otherwise default integer index will be used.
-
-    Parameters
-    ----------
-    sql : str SQL query or SQLAlchemy Selectable (select or text object)
-        SQL query to be executed.
-    con : SQLAlchemy connectable, str, or sqlite3 connection
-        Using SQLAlchemy makes it possible to use any DB supported by that
-        library. If a DBAPI2 object, only sqlite3 is supported.
-    index_col : str or list of str, optional, default: None
-        Column(s) to set as index(MultiIndex).
-    coerce_float : bool, default True
-        Attempts to convert values of non-string, non-numeric objects (like
-        decimal.Decimal) to floating point. Useful for SQL result sets.
-    params : list, tuple or mapping, optional, default: None
-        List of parameters to pass to execute method.  The syntax used
-        to pass parameters is database driver dependent. Check your
-        database driver documentation for which of the five syntax styles,
-        described in PEP 249's paramstyle, is supported.
-        Eg. for psycopg2, uses %(name)s so use params={'name' : 'value'}.
-    parse_dates : list or dict, default: None
-        - List of column names to parse as dates.
-        - Dict of ``{column_name: format string}`` where format string is
-          strftime compatible in case of parsing string times, or is one of
-          (D, s, ns, ms, us) in case of parsing integer timestamps.
-        - Dict of ``{column_name: arg dict}``, where the arg dict corresponds
-          to the keyword arguments of :func:`pandas.to_datetime`
-          Especially useful with databases without native Datetime support,
-          such as SQLite.
-    chunksize : int, default None
-        If specified, return an iterator where `chunksize` is the number of
-        rows to include in each chunk.
-    dtype : Type name or dict of columns
-        Data type for data or columns. E.g. np.float64 or
-        {'a': np.float64, 'b': np.int32, 'c': 'Int64'}.
-
-        .. versionadded:: 1.3.0
-    dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
-        Back-end data type applied to the resultant :class:`DataFrame`
-        (still experimental). Behaviour is as follows:
-
-        * ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
-          (default).
-        * ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
-          DataFrame.
-
-        .. versionadded:: 2.0
-
-    Returns
-    -------
-    DataFrame or Iterator[DataFrame]
-
-    See Also
-    --------
-    read_sql_table : Read SQL database table into a DataFrame.
-    read_sql : Read SQL query or database table into a DataFrame.
-
-    Notes
-    -----
-    Any datetime values with time zone information parsed via the `parse_dates`
-    parameter will be converted to UTC.
-
-    Examples
-    --------
-    >>> from sqlalchemy import create_engine  # doctest: +SKIP
-    >>> engine = create_engine("sqlite:///database.db")  # doctest: +SKIP
-    >>> with engine.connect() as conn, conn.begin():  # doctest: +SKIP
-    ...     data = pd.read_sql_table("data", conn)  # doctest: +SKIP
-    """
-
-    check_dtype_backend(dtype_backend)
-    if dtype_backend is lib.no_default:
-        dtype_backend = "numpy"  # type: ignore[assignment]
-    assert dtype_backend is not lib.no_default
-
-    with pandasSQL_builder(con) as pandas_sql:
-        return pandas_sql.read_query(
-            sql,
-            index_col=index_col,
-            params=params,
-            coerce_float=coerce_float,
-            parse_dates=parse_dates,
-            chunksize=chunksize,
-            dtype=dtype,
-            dtype_backend=dtype_backend,
-        )
-
-
-@overload
-def read_sql(
-    sql,
-    con,
-    index_col: str | list[str] | None = ...,
-    coerce_float=...,
-    params=...,
-    parse_dates=...,
-    columns: list[str] = ...,
-    chunksize: None = ...,
-    dtype_backend: DtypeBackend | lib.NoDefault = ...,
-    dtype: DtypeArg | None = None,
-) -> DataFrame:
-    ...
-
-
-@overload
-def read_sql(
-    sql,
-    con,
-    index_col: str | list[str] | None = ...,
-    coerce_float=...,
-    params=...,
-    parse_dates=...,
-    columns: list[str] = ...,
-    chunksize: int = ...,
-    dtype_backend: DtypeBackend | lib.NoDefault = ...,
-    dtype: DtypeArg | None = None,
-) -> Iterator[DataFrame]:
-    ...
-
-
-def read_sql(
-    sql,
-    con,
-    index_col: str | list[str] | None = None,
-    coerce_float: bool = True,
-    params=None,
-    parse_dates=None,
-    columns: list[str] | None = None,
-    chunksize: int | None = None,
-    dtype_backend: DtypeBackend | lib.NoDefault = lib.no_default,
-    dtype: DtypeArg | None = None,
-) -> DataFrame | Iterator[DataFrame]:
-    """
-    Read SQL query or database table into a DataFrame.
-
-    This function is a convenience wrapper around ``read_sql_table`` and
-    ``read_sql_query`` (for backward compatibility). It will delegate
-    to the specific function depending on the provided input. A SQL query
-    will be routed to ``read_sql_query``, while a database table name will
-    be routed to ``read_sql_table``. Note that the delegated function might
-    have more specific notes about their functionality not listed here.
-
-    Parameters
-    ----------
-    sql : str or SQLAlchemy Selectable (select or text object)
-        SQL query to be executed or a table name.
-    con : SQLAlchemy connectable, str, or sqlite3 connection
-        Using SQLAlchemy makes it possible to use any DB supported by that
-        library. If a DBAPI2 object, only sqlite3 is supported. The user is responsible
-        for engine disposal and connection closure for the SQLAlchemy connectable; str
-        connections are closed automatically. See
-        `here <https://docs.sqlalchemy.org/en/13/core/connections.html>`_.
-    index_col : str or list of str, optional, default: None
-        Column(s) to set as index(MultiIndex).
-    coerce_float : bool, default True
-        Attempts to convert values of non-string, non-numeric objects (like
-        decimal.Decimal) to floating point, useful for SQL result sets.
-    params : list, tuple or dict, optional, default: None
-        List of parameters to pass to execute method.  The syntax used
-        to pass parameters is database driver dependent. Check your
-        database driver documentation for which of the five syntax styles,
-        described in PEP 249's paramstyle, is supported.
-        Eg. for psycopg2, uses %(name)s so use params={'name' : 'value'}.
-    parse_dates : list or dict, default: None
-        - List of column names to parse as dates.
-        - Dict of ``{column_name: format string}`` where format string is
-          strftime compatible in case of parsing string times, or is one of
-          (D, s, ns, ms, us) in case of parsing integer timestamps.
-        - Dict of ``{column_name: arg dict}``, where the arg dict corresponds
-          to the keyword arguments of :func:`pandas.to_datetime`
-          Especially useful with databases without native Datetime support,
-          such as SQLite.
-    columns : list, default: None
-        List of column names to select from SQL table (only used when reading
-        a table).
-    chunksize : int, default None
-        If specified, return an iterator where `chunksize` is the
-        number of rows to include in each chunk.
-    dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
-        Back-end data type applied to the resultant :class:`DataFrame`
-        (still experimental). Behaviour is as follows:
-
-        * ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
-          (default).
-        * ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
-          DataFrame.
-
-        .. versionadded:: 2.0
-    dtype : Type name or dict of columns
-        Data type for data or columns. E.g. np.float64 or
-        {'a': np.float64, 'b': np.int32, 'c': 'Int64'}.
-        The argument is ignored if a table is passed instead of a query.
-
-        .. versionadded:: 2.0.0
-
-    Returns
-    -------
-    DataFrame or Iterator[DataFrame]
-
-    See Also
-    --------
-    read_sql_table : Read SQL database table into a DataFrame.
-    read_sql_query : Read SQL query into a DataFrame.
-
-    Examples
-    --------
-    Read data from SQL via either a SQL query or a SQL tablename.
-    When using a SQLite database only SQL queries are accepted,
-    providing only the SQL tablename will result in an error.
-
-    >>> from sqlite3 import connect
-    >>> conn = connect(':memory:')
-    >>> df = pd.DataFrame(data=[[0, '10/11/12'], [1, '12/11/10']],
-    ...                   columns=['int_column', 'date_column'])
-    >>> df.to_sql(name='test_data', con=conn)
-    2
-
-    >>> pd.read_sql('SELECT int_column, date_column FROM test_data', conn)
-       int_column date_column
-    0           0    10/11/12
-    1           1    12/11/10
-
-    >>> pd.read_sql('test_data', 'postgres:///db_name')  # doctest:+SKIP
-
-    Apply date parsing to columns through the ``parse_dates`` argument
-    The ``parse_dates`` argument calls ``pd.to_datetime`` on the provided columns.
-    Custom argument values for applying ``pd.to_datetime`` on a column are specified
-    via a dictionary format:
-
-    >>> pd.read_sql('SELECT int_column, date_column FROM test_data',
-    ...             conn,
-    ...             parse_dates={"date_column": {"format": "%d/%m/%y"}})
-       int_column date_column
-    0           0  2012-11-10
-    1           1  2010-11-12
-    """
-
-    check_dtype_backend(dtype_backend)
-    if dtype_backend is lib.no_default:
-        dtype_backend = "numpy"  # type: ignore[assignment]
-    assert dtype_backend is not lib.no_default
-
-    with pandasSQL_builder(con) as pandas_sql:
-        if isinstance(pandas_sql, SQLiteDatabase):
-            return pandas_sql.read_query(
-                sql,
-                index_col=index_col,
-                params=params,
-                coerce_float=coerce_float,
-                parse_dates=parse_dates,
-                chunksize=chunksize,
-                dtype_backend=dtype_backend,
-                dtype=dtype,
-            )
-
-        try:
-            _is_table_name = pandas_sql.has_table(sql)
-        except Exception:
-            # using generic exception to catch errors from sql drivers (GH24988)
-            _is_table_name = False
-
-        if _is_table_name:
-            return pandas_sql.read_table(
-                sql,
-                index_col=index_col,
-                coerce_float=coerce_float,
-                parse_dates=parse_dates,
-                columns=columns,
-                chunksize=chunksize,
-                dtype_backend=dtype_backend,
-            )
-        else:
-            return pandas_sql.read_query(
-                sql,
-                index_col=index_col,
-                params=params,
-                coerce_float=coerce_float,
-                parse_dates=parse_dates,
-                chunksize=chunksize,
-                dtype_backend=dtype_backend,
-                dtype=dtype,
-            )
-
-
-def to_sql(
-    frame,
-    name: str,
-    con,
-    schema: str | None = None,
-    if_exists: Literal["fail", "replace", "append"] = "fail",
-    index: bool = True,
-    index_label: IndexLabel | None = None,
-    chunksize: int | None = None,
-    dtype: DtypeArg | None = None,
-    method: Literal["multi"] | Callable | None = None,
-    engine: str = "auto",
-    **engine_kwargs,
-) -> int | None:
-    """
-    Write records stored in a DataFrame to a SQL database.
-
-    Parameters
-    ----------
-    frame : DataFrame, Series
-    name : str
-        Name of SQL table.
-    con : SQLAlchemy connectable(engine/connection) or database string URI
-        or sqlite3 DBAPI2 connection
-        Using SQLAlchemy makes it possible to use any DB supported by that
-        library.
-        If a DBAPI2 object, only sqlite3 is supported.
-    schema : str, optional
-        Name of SQL schema in database to write to (if database flavor
-        supports this). If None, use default schema (default).
-    if_exists : {'fail', 'replace', 'append'}, default 'fail'
-        - fail: If table exists, do nothing.
-        - replace: If table exists, drop it, recreate it, and insert data.
-        - append: If table exists, insert data. Create if does not exist.
-    index : bool, default True
-        Write DataFrame index as a column.
-    index_label : str or sequence, optional
-        Column label for index column(s). If None is given (default) and
-        `index` is True, then the index names are used.
-        A sequence should be given if the DataFrame uses MultiIndex.
-    chunksize : int, optional
-        Specify the number of rows in each batch to be written at a time.
-        By default, all rows will be written at once.
-    dtype : dict or scalar, optional
-        Specifying the datatype for columns. If a dictionary is used, the
-        keys should be the column names and the values should be the
-        SQLAlchemy types or strings for the sqlite3 fallback mode. If a
-        scalar is provided, it will be applied to all columns.
-    method : {None, 'multi', callable}, optional
-        Controls the SQL insertion clause used:
-
-        - None : Uses standard SQL ``INSERT`` clause (one per row).
-        - ``'multi'``: Pass multiple values in a single ``INSERT`` clause.
-        - callable with signature ``(pd_table, conn, keys, data_iter) -> int | None``.
-
-        Details and a sample callable implementation can be found in the
-        section :ref:`insert method <io.sql.method>`.
-    engine : {'auto', 'sqlalchemy'}, default 'auto'
-        SQL engine library to use. If 'auto', then the option
-        ``io.sql.engine`` is used. The default ``io.sql.engine``
-        behavior is 'sqlalchemy'
-
-        .. versionadded:: 1.3.0
-
-    **engine_kwargs
-        Any additional kwargs are passed to the engine.
-
-    Returns
-    -------
-    None or int
-        Number of rows affected by to_sql. None is returned if the callable
-        passed into ``method`` does not return an integer number of rows.
-
-        .. versionadded:: 1.4.0
-
-    Notes
-    -----
-    The returned rows affected is the sum of the ``rowcount`` attribute of ``sqlite3.Cursor``
-    or SQLAlchemy connectable. The returned value may not reflect the exact number of written
-    rows as stipulated in the
-    `sqlite3 <https://docs.python.org/3/library/sqlite3.html#sqlite3.Cursor.rowcount>`__ or
-    `SQLAlchemy <https://docs.sqlalchemy.org/en/14/core/connections.html#sqlalchemy.engine.BaseCursorResult.rowcount>`__
-    """  # noqa: E501
-    if if_exists not in ("fail", "replace", "append"):
-        raise ValueError(f"'{if_exists}' is not valid for if_exists")
-
-    if isinstance(frame, Series):
-        frame = frame.to_frame()
-    elif not isinstance(frame, DataFrame):
-        raise NotImplementedError(
-            "'frame' argument should be either a Series or a DataFrame"
-        )
-
-    with pandasSQL_builder(con, schema=schema, need_transaction=True) as pandas_sql:
-        return pandas_sql.to_sql(
-            frame,
-            name,
-            if_exists=if_exists,
-            index=index,
-            index_label=index_label,
-            schema=schema,
-            chunksize=chunksize,
-            dtype=dtype,
-            method=method,
-            engine=engine,
-            **engine_kwargs,
-        )
-
-
-def has_table(table_name: str, con, schema: str | None = None) -> bool:
-    """
-    Check if DataBase has named table.
-
-    Parameters
-    ----------
-    table_name: string
-        Name of SQL table.
-    con: SQLAlchemy connectable(engine/connection) or sqlite3 DBAPI2 connection
-        Using SQLAlchemy makes it possible to use any DB supported by that
-        library.
-        If a DBAPI2 object, only sqlite3 is supported.
-    schema : string, default None
-        Name of SQL schema in database to write to (if database flavor supports
-        this). If None, use default schema (default).
-
-    Returns
-    -------
-    boolean
-    """
-    with pandasSQL_builder(con, schema=schema) as pandas_sql:
-        return pandas_sql.has_table(table_name)
-
-
-table_exists = has_table
-
-
-def pandasSQL_builder(
-    con,
-    schema: str | None = None,
-    need_transaction: bool = False,
-) -> PandasSQL:
-    """
-    Convenience function to return the correct PandasSQL subclass based on the
-    provided parameters.  Also creates a sqlalchemy connection and transaction
-    if necessary.
-    """
-    import sqlite3
-
-    if isinstance(con, sqlite3.Connection) or con is None:
-        return SQLiteDatabase(con)
-
-    sqlalchemy = import_optional_dependency("sqlalchemy", errors="ignore")
-
-    if isinstance(con, str) and sqlalchemy is None:
-        raise ImportError("Using URI string without sqlalchemy installed.")
-
-    if sqlalchemy is not None and isinstance(con, (str, sqlalchemy.engine.Connectable)):
-        return SQLDatabase(con, schema, need_transaction)
-
-    warnings.warn(
-        "pandas only supports SQLAlchemy connectable (engine/connection) or "
-        "database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 "
-        "objects are not tested. Please consider using SQLAlchemy.",
-        UserWarning,
-        stacklevel=find_stack_level(),
-    )
-    return SQLiteDatabase(con)
-
-
-class SQLTable(PandasObject):
-    """
-    For mapping Pandas tables to SQL tables.
-    Uses fact that table is reflected by SQLAlchemy to
-    do better type conversions.
-    Also holds various flags needed to avoid having to
-    pass them between functions all the time.
-    """
-
-    # TODO: support for multiIndex
-
-    def __init__(
-        self,
-        name: str,
-        pandas_sql_engine,
-        frame=None,
-        index: bool | str | list[str] | None = True,
-        if_exists: Literal["fail", "replace", "append"] = "fail",
-        prefix: str = "pandas",
-        index_label=None,
-        schema=None,
-        keys=None,
-        dtype: DtypeArg | None = None,
-    ) -> None:
-        self.name = name
-        self.pd_sql = pandas_sql_engine
-        self.prefix = prefix
-        self.frame = frame
-        self.index = self._index_name(index, index_label)
-        self.schema = schema
-        self.if_exists = if_exists
-        self.keys = keys
-        self.dtype = dtype
-
-        if frame is not None:
-            # We want to initialize based on a dataframe
-            self.table = self._create_table_setup()
-        else:
-            # no data provided, read-only mode
-            self.table = self.pd_sql.get_table(self.name, self.schema)
-
-        if self.table is None:
-            raise ValueError(f"Could not init table '{name}'")
-
-        if not len(self.name):
-            raise ValueError("Empty table name specified")
-
-    def exists(self):
-        return self.pd_sql.has_table(self.name, self.schema)
-
-    def sql_schema(self) -> str:
-        from sqlalchemy.schema import CreateTable
-
-        return str(CreateTable(self.table).compile(self.pd_sql.con))
-
-    def _execute_create(self) -> None:
-        # Inserting table into database, add to MetaData object
-        self.table = self.table.to_metadata(self.pd_sql.meta)
-        with self.pd_sql.run_transaction():
-            self.table.create(bind=self.pd_sql.con)
-
-    def create(self) -> None:
-        if self.exists():
-            if self.if_exists == "fail":
-                raise ValueError(f"Table '{self.name}' already exists.")
-            if self.if_exists == "replace":
-                self.pd_sql.drop_table(self.name, self.schema)
-                self._execute_create()
-            elif self.if_exists == "append":
-                pass
-            else:
-                raise ValueError(f"'{self.if_exists}' is not valid for if_exists")
-        else:
-            self._execute_create()
-
-    def _execute_insert(self, conn, keys: list[str], data_iter) -> int:
-        """
-        Execute SQL statement inserting data
-
-        Parameters
-        ----------
-        conn : sqlalchemy.engine.Engine or sqlalchemy.engine.Connection
-        keys : list of str
-           Column names
-        data_iter : generator of list
-           Each item contains a list of values to be inserted
-        """
-        data = [dict(zip(keys, row)) for row in data_iter]
-        result = conn.execute(self.table.insert(), data)
-        return result.rowcount
-
-    def _execute_insert_multi(self, conn, keys: list[str], data_iter) -> int:
-        """
-        Alternative to _execute_insert for DBs support multivalue INSERT.
-
-        Note: multi-value insert is usually faster for analytics DBs
-        and tables containing a few columns
-        but performance degrades quickly with increase of columns.
-        """
-
-        from sqlalchemy import insert
-
-        data = [dict(zip(keys, row)) for row in data_iter]
-        stmt = insert(self.table).values(data)
-        result = conn.execute(stmt)
-        return result.rowcount
-
-    def insert_data(self) -> tuple[list[str], list[np.ndarray]]:
-        if self.index is not None:
-            temp = self.frame.copy()
-            temp.index.names = self.index
-            try:
-                temp.reset_index(inplace=True)
-            except ValueError as err:
-                raise ValueError(f"duplicate name in index/columns: {err}") from err
-        else:
-            temp = self.frame
-
-        column_names = list(map(str, temp.columns))
-        ncols = len(column_names)
-        # this just pre-allocates the list: None's will be replaced with ndarrays
-        # error: List item 0 has incompatible type "None"; expected "ndarray"
-        data_list: list[np.ndarray] = [None] * ncols  # type: ignore[list-item]
-
-        for i, (_, ser) in enumerate(temp.items()):
-            if ser.dtype.kind == "M":
-                if isinstance(ser._values, ArrowExtensionArray):
-                    import pyarrow as pa
-
-                    if pa.types.is_date(ser.dtype.pyarrow_dtype):
-                        # GH#53854 to_pydatetime not supported for pyarrow date dtypes
-                        d = ser._values.to_numpy(dtype=object)
-                    else:
-                        with warnings.catch_warnings():
-                            warnings.filterwarnings("ignore", category=FutureWarning)
-                            # GH#52459 to_pydatetime will return Index[object]
-                            d = np.asarray(ser.dt.to_pydatetime(), dtype=object)
-                else:
-                    d = ser._values.to_pydatetime()
-            elif ser.dtype.kind == "m":
-                vals = ser._values
-                if isinstance(vals, ArrowExtensionArray):
-                    vals = vals.to_numpy(dtype=np.dtype("m8[ns]"))
-                # store as integers, see GH#6921, GH#7076
-                d = vals.view("i8").astype(object)
-            else:
-                d = ser._values.astype(object)
-
-            assert isinstance(d, np.ndarray), type(d)
-
-            if ser._can_hold_na:
-                # Note: this will miss timedeltas since they are converted to int
-                mask = isna(d)
-                d[mask] = None
-
-            data_list[i] = d
-
-        return column_names, data_list
-
-    def insert(
-        self,
-        chunksize: int | None = None,
-        method: Literal["multi"] | Callable | None = None,
-    ) -> int | None:
-        # set insert method
-        if method is None:
-            exec_insert = self._execute_insert
-        elif method == "multi":
-            exec_insert = self._execute_insert_multi
-        elif callable(method):
-            exec_insert = partial(method, self)
-        else:
-            raise ValueError(f"Invalid parameter `method`: {method}")
-
-        keys, data_list = self.insert_data()
-
-        nrows = len(self.frame)
-
-        if nrows == 0:
-            return 0
-
-        if chunksize is None:
-            chunksize = nrows
-        elif chunksize == 0:
-            raise ValueError("chunksize argument should be non-zero")
-
-        chunks = (nrows // chunksize) + 1
-        total_inserted = None
-        with self.pd_sql.run_transaction() as conn:
-            for i in range(chunks):
-                start_i = i * chunksize
-                end_i = min((i + 1) * chunksize, nrows)
-                if start_i >= end_i:
-                    break
-
-                chunk_iter = zip(*(arr[start_i:end_i] for arr in data_list))
-                num_inserted = exec_insert(conn, keys, chunk_iter)
-                # GH 46891
-                if num_inserted is not None:
-                    if total_inserted is None:
-                        total_inserted = num_inserted
-                    else:
-                        total_inserted += num_inserted
-        return total_inserted
-
-    def _query_iterator(
-        self,
-        result,
-        exit_stack: ExitStack,
-        chunksize: int | None,
-        columns,
-        coerce_float: bool = True,
-        parse_dates=None,
-        dtype_backend: DtypeBackend | Literal["numpy"] = "numpy",
-    ):
-        """Return generator through chunked result set."""
-        has_read_data = False
-        with exit_stack:
-            while True:
-                data = result.fetchmany(chunksize)
-                if not data:
-                    if not has_read_data:
-                        yield DataFrame.from_records(
-                            [], columns=columns, coerce_float=coerce_float
-                        )
-                    break
-
-                has_read_data = True
-                self.frame = _convert_arrays_to_dataframe(
-                    data, columns, coerce_float, dtype_backend
-                )
-
-                self._harmonize_columns(
-                    parse_dates=parse_dates, dtype_backend=dtype_backend
-                )
-
-                if self.index is not None:
-                    self.frame.set_index(self.index, inplace=True)
-
-                yield self.frame
-
-    def read(
-        self,
-        exit_stack: ExitStack,
-        coerce_float: bool = True,
-        parse_dates=None,
-        columns=None,
-        chunksize: int | None = None,
-        dtype_backend: DtypeBackend | Literal["numpy"] = "numpy",
-    ) -> DataFrame | Iterator[DataFrame]:
-        from sqlalchemy import select
-
-        if columns is not None and len(columns) > 0:
-            cols = [self.table.c[n] for n in columns]
-            if self.index is not None:
-                for idx in self.index[::-1]:
-                    cols.insert(0, self.table.c[idx])
-            sql_select = select(*cols)
-        else:
-            sql_select = select(self.table)
-        result = self.pd_sql.execute(sql_select)
-        column_names = result.keys()
-
-        if chunksize is not None:
-            return self._query_iterator(
-                result,
-                exit_stack,
-                chunksize,
-                column_names,
-                coerce_float=coerce_float,
-                parse_dates=parse_dates,
-                dtype_backend=dtype_backend,
-            )
-        else:
-            data = result.fetchall()
-            self.frame = _convert_arrays_to_dataframe(
-                data, column_names, coerce_float, dtype_backend
-            )
-
-            self._harmonize_columns(
-                parse_dates=parse_dates, dtype_backend=dtype_backend
-            )
-
-            if self.index is not None:
-                self.frame.set_index(self.index, inplace=True)
-
-            return self.frame
-
-    def _index_name(self, index, index_label):
-        # for writing: index=True to include index in sql table
-        if index is True:
-            nlevels = self.frame.index.nlevels
-            # if index_label is specified, set this as index name(s)
-            if index_label is not None:
-                if not isinstance(index_label, list):
-                    index_label = [index_label]
-                if len(index_label) != nlevels:
-                    raise ValueError(
-                        "Length of 'index_label' should match number of "
-                        f"levels, which is {nlevels}"
-                    )
-                return index_label
-            # return the used column labels for the index columns
-            if (
-                nlevels == 1
-                and "index" not in self.frame.columns
-                and self.frame.index.name is None
-            ):
-                return ["index"]
-            else:
-                return com.fill_missing_names(self.frame.index.names)
-
-        # for reading: index=(list of) string to specify column to set as index
-        elif isinstance(index, str):
-            return [index]
-        elif isinstance(index, list):
-            return index
-        else:
-            return None
-
-    def _get_column_names_and_types(self, dtype_mapper):
-        column_names_and_types = []
-        if self.index is not None:
-            for i, idx_label in enumerate(self.index):
-                idx_type = dtype_mapper(self.frame.index._get_level_values(i))
-                column_names_and_types.append((str(idx_label), idx_type, True))
-
-        column_names_and_types += [
-            (str(self.frame.columns[i]), dtype_mapper(self.frame.iloc[:, i]), False)
-            for i in range(len(self.frame.columns))
-        ]
-
-        return column_names_and_types
-
-    def _create_table_setup(self):
-        from sqlalchemy import (
-            Column,
-            PrimaryKeyConstraint,
-            Table,
-        )
-        from sqlalchemy.schema import MetaData
-
-        column_names_and_types = self._get_column_names_and_types(self._sqlalchemy_type)
-
-        columns: list[Any] = [
-            Column(name, typ, index=is_index)
-            for name, typ, is_index in column_names_and_types
-        ]
-
-        if self.keys is not None:
-            if not is_list_like(self.keys):
-                keys = [self.keys]
-            else:
-                keys = self.keys
-            pkc = PrimaryKeyConstraint(*keys, name=self.name + "_pk")
-            columns.append(pkc)
-
-        schema = self.schema or self.pd_sql.meta.schema
-
-        # At this point, attach to new metadata, only attach to self.meta
-        # once table is created.
-        meta = MetaData()
-        return Table(self.name, meta, *columns, schema=schema)
-
-    def _harmonize_columns(
-        self,
-        parse_dates=None,
-        dtype_backend: DtypeBackend | Literal["numpy"] = "numpy",
-    ) -> None:
-        """
-        Make the DataFrame's column types align with the SQL table
-        column types.
-        Need to work around limited NA value support. Floats are always
-        fine, ints must always be floats if there are Null values.
-        Booleans are hard because converting bool column with None replaces
-        all Nones with false. Therefore only convert bool if there are no
-        NA values.
-        Datetimes should already be converted to np.datetime64 if supported,
-        but here we also force conversion if required.
-        """
-        parse_dates = _process_parse_dates_argument(parse_dates)
-
-        for sql_col in self.table.columns:
-            col_name = sql_col.name
-            try:
-                df_col = self.frame[col_name]
-
-                # Handle date parsing upfront; don't try to convert columns
-                # twice
-                if col_name in parse_dates:
-                    try:
-                        fmt = parse_dates[col_name]
-                    except TypeError:
-                        fmt = None
-                    self.frame[col_name] = _handle_date_column(df_col, format=fmt)
-                    continue
-
-                # the type the dataframe column should have
-                col_type = self._get_dtype(sql_col.type)
-
-                if (
-                    col_type is datetime
-                    or col_type is date
-                    or col_type is DatetimeTZDtype
-                ):
-                    # Convert tz-aware Datetime SQL columns to UTC
-                    utc = col_type is DatetimeTZDtype
-                    self.frame[col_name] = _handle_date_column(df_col, utc=utc)
-                elif dtype_backend == "numpy" and col_type is float:
-                    # floats support NA, can always convert!
-                    self.frame[col_name] = df_col.astype(col_type, copy=False)
-
-                elif dtype_backend == "numpy" and len(df_col) == df_col.count():
-                    # No NA values, can convert ints and bools
-                    if col_type is np.dtype("int64") or col_type is bool:
-                        self.frame[col_name] = df_col.astype(col_type, copy=False)
-            except KeyError:
-                pass  # this column not in results
-
-    def _sqlalchemy_type(self, col: Index | Series):
-        dtype: DtypeArg = self.dtype or {}
-        if is_dict_like(dtype):
-            dtype = cast(dict, dtype)
-            if col.name in dtype:
-                return dtype[col.name]
-
-        # Infer type of column, while ignoring missing values.
-        # Needed for inserting typed data containing NULLs, GH 8778.
-        col_type = lib.infer_dtype(col, skipna=True)
-
-        from sqlalchemy.types import (
-            TIMESTAMP,
-            BigInteger,
-            Boolean,
-            Date,
-            DateTime,
-            Float,
-            Integer,
-            SmallInteger,
-            Text,
-            Time,
-        )
-
-        if col_type in ("datetime64", "datetime"):
-            # GH 9086: TIMESTAMP is the suggested type if the column contains
-            # timezone information
-            try:
-                # error: Item "Index" of "Union[Index, Series]" has no attribute "dt"
-                if col.dt.tz is not None:  # type: ignore[union-attr]
-                    return TIMESTAMP(timezone=True)
-            except AttributeError:
-                # The column is actually a DatetimeIndex
-                # GH 26761 or an Index with date-like data e.g. 9999-01-01
-                if getattr(col, "tz", None) is not None:
-                    return TIMESTAMP(timezone=True)
-            return DateTime
-        if col_type == "timedelta64":
-            warnings.warn(
-                "the 'timedelta' type is not supported, and will be "
-                "written as integer values (ns frequency) to the database.",
-                UserWarning,
-                stacklevel=find_stack_level(),
-            )
-            return BigInteger
-        elif col_type == "floating":
-            if col.dtype == "float32":
-                return Float(precision=23)
-            else:
-                return Float(precision=53)
-        elif col_type == "integer":
-            # GH35076 Map pandas integer to optimal SQLAlchemy integer type
-            if col.dtype.name.lower() in ("int8", "uint8", "int16"):
-                return SmallInteger
-            elif col.dtype.name.lower() in ("uint16", "int32"):
-                return Integer
-            elif col.dtype.name.lower() == "uint64":
-                raise ValueError("Unsigned 64 bit integer datatype is not supported")
-            else:
-                return BigInteger
-        elif col_type == "boolean":
-            return Boolean
-        elif col_type == "date":
-            return Date
-        elif col_type == "time":
-            return Time
-        elif col_type == "complex":
-            raise ValueError("Complex datatypes not supported")
-
-        return Text
-
-    def _get_dtype(self, sqltype):
-        from sqlalchemy.types import (
-            TIMESTAMP,
-            Boolean,
-            Date,
-            DateTime,
-            Float,
-            Integer,
-        )
-
-        if isinstance(sqltype, Float):
-            return float
-        elif isinstance(sqltype, Integer):
-            # TODO: Refine integer size.
-            return np.dtype("int64")
-        elif isinstance(sqltype, TIMESTAMP):
-            # we have a timezone capable type
-            if not sqltype.timezone:
-                return datetime
-            return DatetimeTZDtype
-        elif isinstance(sqltype, DateTime):
-            # Caution: np.datetime64 is also a subclass of np.number.
-            return datetime
-        elif isinstance(sqltype, Date):
-            return date
-        elif isinstance(sqltype, Boolean):
-            return bool
-        return object
-
-
-class PandasSQL(PandasObject, ABC):
-    """
-    Subclasses Should define read_query and to_sql.
-    """
-
-    def __enter__(self) -> Self:
-        return self
-
-    def __exit__(self, *args) -> None:
-        pass
-
-    def read_table(
-        self,
-        table_name: str,
-        index_col: str | list[str] | None = None,
-        coerce_float: bool = True,
-        parse_dates=None,
-        columns=None,
-        schema: str | None = None,
-        chunksize: int | None = None,
-        dtype_backend: DtypeBackend | Literal["numpy"] = "numpy",
-    ) -> DataFrame | Iterator[DataFrame]:
-        raise NotImplementedError
-
-    @abstractmethod
-    def read_query(
-        self,
-        sql: str,
-        index_col: str | list[str] | None = None,
-        coerce_float: bool = True,
-        parse_dates=None,
-        params=None,
-        chunksize: int | None = None,
-        dtype: DtypeArg | None = None,
-        dtype_backend: DtypeBackend | Literal["numpy"] = "numpy",
-    ) -> DataFrame | Iterator[DataFrame]:
-        pass
-
-    @abstractmethod
-    def to_sql(
-        self,
-        frame,
-        name: str,
-        if_exists: Literal["fail", "replace", "append"] = "fail",
-        index: bool = True,
-        index_label=None,
-        schema=None,
-        chunksize: int | None = None,
-        dtype: DtypeArg | None = None,
-        method: Literal["multi"] | Callable | None = None,
-        engine: str = "auto",
-        **engine_kwargs,
-    ) -> int | None:
-        pass
-
-    @abstractmethod
-    def execute(self, sql: str | Select | TextClause, params=None):
-        pass
-
-    @abstractmethod
-    def has_table(self, name: str, schema: str | None = None) -> bool:
-        pass
-
-    @abstractmethod
-    def _create_sql_schema(
-        self,
-        frame: DataFrame,
-        table_name: str,
-        keys: list[str] | None = None,
-        dtype: DtypeArg | None = None,
-        schema: str | None = None,
-    ):
-        pass
-
-
-class BaseEngine:
-    def insert_records(
-        self,
-        table: SQLTable,
-        con,
-        frame,
-        name: str,
-        index: bool | str | list[str] | None = True,
-        schema=None,
-        chunksize: int | None = None,
-        method=None,
-        **engine_kwargs,
-    ) -> int | None:
-        """
-        Inserts data into already-prepared table
-        """
-        raise AbstractMethodError(self)
-
-
-class SQLAlchemyEngine(BaseEngine):
-    def __init__(self) -> None:
-        import_optional_dependency(
-            "sqlalchemy", extra="sqlalchemy is required for SQL support."
-        )
-
-    def insert_records(
-        self,
-        table: SQLTable,
-        con,
-        frame,
-        name: str,
-        index: bool | str | list[str] | None = True,
-        schema=None,
-        chunksize: int | None = None,
-        method=None,
-        **engine_kwargs,
-    ) -> int | None:
-        from sqlalchemy import exc
-
-        try:
-            return table.insert(chunksize=chunksize, method=method)
-        except exc.StatementError as err:
-            # GH34431
-            # https://stackoverflow.com/a/67358288/6067848
-            msg = r"""(\(1054, "Unknown column 'inf(e0)?' in 'field list'"\))(?#
-            )|inf can not be used with MySQL"""
-            err_text = str(err.orig)
-            if re.search(msg, err_text):
-                raise ValueError("inf cannot be used with MySQL") from err
-            raise err
-
-
-def get_engine(engine: str) -> BaseEngine:
-    """return our implementation"""
-    if engine == "auto":
-        engine = get_option("io.sql.engine")
-
-    if engine == "auto":
-        # try engines in this order
-        engine_classes = [SQLAlchemyEngine]
-
-        error_msgs = ""
-        for engine_class in engine_classes:
-            try:
-                return engine_class()
-            except ImportError as err:
-                error_msgs += "\n - " + str(err)
-
-        raise ImportError(
-            "Unable to find a usable engine; "
-            "tried using: 'sqlalchemy'.\n"
-            "A suitable version of "
-            "sqlalchemy is required for sql I/O "
-            "support.\n"
-            "Trying to import the above resulted in these errors:"
-            f"{error_msgs}"
-        )
-
-    if engine == "sqlalchemy":
-        return SQLAlchemyEngine()
-
-    raise ValueError("engine must be one of 'auto', 'sqlalchemy'")
-
-
-class SQLDatabase(PandasSQL):
-    """
-    This class enables conversion between DataFrame and SQL databases
-    using SQLAlchemy to handle DataBase abstraction.
-
-    Parameters
-    ----------
-    con : SQLAlchemy Connectable or URI string.
-        Connectable to connect with the database. Using SQLAlchemy makes it
-        possible to use any DB supported by that library.
-    schema : string, default None
-        Name of SQL schema in database to write to (if database flavor
-        supports this). If None, use default schema (default).
-    need_transaction : bool, default False
-        If True, SQLDatabase will create a transaction.
-
-    """
-
-    def __init__(
-        self, con, schema: str | None = None, need_transaction: bool = False
-    ) -> None:
-        from sqlalchemy import create_engine
-        from sqlalchemy.engine import Engine
-        from sqlalchemy.schema import MetaData
-
-        # self.exit_stack cleans up the Engine and Connection and commits the
-        # transaction if any of those objects was created below.
-        # Cleanup happens either in self.__exit__ or at the end of the iterator
-        # returned by read_sql when chunksize is not None.
-        self.exit_stack = ExitStack()
-        if isinstance(con, str):
-            con = create_engine(con)
-            self.exit_stack.callback(con.dispose)
-        if isinstance(con, Engine):
-            con = self.exit_stack.enter_context(con.connect())
-        if need_transaction and not con.in_transaction():
-            self.exit_stack.enter_context(con.begin())
-        self.con = con
-        self.meta = MetaData(schema=schema)
-        self.returns_generator = False
-
-    def __exit__(self, *args) -> None:
-        if not self.returns_generator:
-            self.exit_stack.close()
-
-    @contextmanager
-    def run_transaction(self):
-        if not self.con.in_transaction():
-            with self.con.begin():
-                yield self.con
-        else:
-            yield self.con
-
-    def execute(self, sql: str | Select | TextClause, params=None):
-        """Simple passthrough to SQLAlchemy connectable"""
-        args = [] if params is None else [params]
-        if isinstance(sql, str):
-            return self.con.exec_driver_sql(sql, *args)
-        return self.con.execute(sql, *args)
-
-    def read_table(
-        self,
-        table_name: str,
-        index_col: str | list[str] | None = None,
-        coerce_float: bool = True,
-        parse_dates=None,
-        columns=None,
-        schema: str | None = None,
-        chunksize: int | None = None,
-        dtype_backend: DtypeBackend | Literal["numpy"] = "numpy",
-    ) -> DataFrame | Iterator[DataFrame]:
-        """
-        Read SQL database table into a DataFrame.
-
-        Parameters
-        ----------
-        table_name : str
-            Name of SQL table in database.
-        index_col : string, optional, default: None
-            Column to set as index.
-        coerce_float : bool, default True
-            Attempts to convert values of non-string, non-numeric objects
-            (like decimal.Decimal) to floating point. This can result in
-            loss of precision.
-        parse_dates : list or dict, default: None
-            - List of column names to parse as dates.
-            - Dict of ``{column_name: format string}`` where format string is
-              strftime compatible in case of parsing string times, or is one of
-              (D, s, ns, ms, us) in case of parsing integer timestamps.
-            - Dict of ``{column_name: arg}``, where the arg corresponds
-              to the keyword arguments of :func:`pandas.to_datetime`.
-              Especially useful with databases without native Datetime support,
-              such as SQLite.
-        columns : list, default: None
-            List of column names to select from SQL table.
-        schema : string, default None
-            Name of SQL schema in database to query (if database flavor
-            supports this).  If specified, this overwrites the default
-            schema of the SQL database object.
-        chunksize : int, default None
-            If specified, return an iterator where `chunksize` is the number
-            of rows to include in each chunk.
-        dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
-            Back-end data type applied to the resultant :class:`DataFrame`
-            (still experimental). Behaviour is as follows:
-
-            * ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
-              (default).
-            * ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
-              DataFrame.
-
-            .. versionadded:: 2.0
-
-        Returns
-        -------
-        DataFrame
-
-        See Also
-        --------
-        pandas.read_sql_table
-        SQLDatabase.read_query
-
-        """
-        self.meta.reflect(bind=self.con, only=[table_name], views=True)
-        table = SQLTable(table_name, self, index=index_col, schema=schema)
-        if chunksize is not None:
-            self.returns_generator = True
-        return table.read(
-            self.exit_stack,
-            coerce_float=coerce_float,
-            parse_dates=parse_dates,
-            columns=columns,
-            chunksize=chunksize,
-            dtype_backend=dtype_backend,
-        )
-
-    @staticmethod
-    def _query_iterator(
-        result,
-        exit_stack: ExitStack,
-        chunksize: int,
-        columns,
-        index_col=None,
-        coerce_float: bool = True,
-        parse_dates=None,
-        dtype: DtypeArg | None = None,
-        dtype_backend: DtypeBackend | Literal["numpy"] = "numpy",
-    ):
-        """Return generator through chunked result set"""
-        has_read_data = False
-        with exit_stack:
-            while True:
-                data = result.fetchmany(chunksize)
-                if not data:
-                    if not has_read_data:
-                        yield _wrap_result(
-                            [],
-                            columns,
-                            index_col=index_col,
-                            coerce_float=coerce_float,
-                            parse_dates=parse_dates,
-                            dtype=dtype,
-                            dtype_backend=dtype_backend,
-                        )
-                    break
-
-                has_read_data = True
-                yield _wrap_result(
-                    data,
-                    columns,
-                    index_col=index_col,
-                    coerce_float=coerce_float,
-                    parse_dates=parse_dates,
-                    dtype=dtype,
-                    dtype_backend=dtype_backend,
-                )
-
-    def read_query(
-        self,
-        sql: str,
-        index_col: str | list[str] | None = None,
-        coerce_float: bool = True,
-        parse_dates=None,
-        params=None,
-        chunksize: int | None = None,
-        dtype: DtypeArg | None = None,
-        dtype_backend: DtypeBackend | Literal["numpy"] = "numpy",
-    ) -> DataFrame | Iterator[DataFrame]:
-        """
-        Read SQL query into a DataFrame.
-
-        Parameters
-        ----------
-        sql : str
-            SQL query to be executed.
-        index_col : string, optional, default: None
-            Column name to use as index for the returned DataFrame object.
-        coerce_float : bool, default True
-            Attempt to convert values of non-string, non-numeric objects (like
-            decimal.Decimal) to floating point, useful for SQL result sets.
-        params : list, tuple or dict, optional, default: None
-            List of parameters to pass to execute method.  The syntax used
-            to pass parameters is database driver dependent. Check your
-            database driver documentation for which of the five syntax styles,
-            described in PEP 249's paramstyle, is supported.
-            Eg. for psycopg2, uses %(name)s so use params={'name' : 'value'}
-        parse_dates : list or dict, default: None
-            - List of column names to parse as dates.
-            - Dict of ``{column_name: format string}`` where format string is
-              strftime compatible in case of parsing string times, or is one of
-              (D, s, ns, ms, us) in case of parsing integer timestamps.
-            - Dict of ``{column_name: arg dict}``, where the arg dict
-              corresponds to the keyword arguments of
-              :func:`pandas.to_datetime` Especially useful with databases
-              without native Datetime support, such as SQLite.
-        chunksize : int, default None
-            If specified, return an iterator where `chunksize` is the number
-            of rows to include in each chunk.
-        dtype : Type name or dict of columns
-            Data type for data or columns. E.g. np.float64 or
-            {'a': np.float64, 'b': np.int32, 'c': 'Int64'}
-
-            .. versionadded:: 1.3.0
-
-        Returns
-        -------
-        DataFrame
-
-        See Also
-        --------
-        read_sql_table : Read SQL database table into a DataFrame.
-        read_sql
-
-        """
-        result = self.execute(sql, params)
-        columns = result.keys()
-
-        if chunksize is not None:
-            self.returns_generator = True
-            return self._query_iterator(
-                result,
-                self.exit_stack,
-                chunksize,
-                columns,
-                index_col=index_col,
-                coerce_float=coerce_float,
-                parse_dates=parse_dates,
-                dtype=dtype,
-                dtype_backend=dtype_backend,
-            )
-        else:
-            data = result.fetchall()
-            frame = _wrap_result(
-                data,
-                columns,
-                index_col=index_col,
-                coerce_float=coerce_float,
-                parse_dates=parse_dates,
-                dtype=dtype,
-                dtype_backend=dtype_backend,
-            )
-            return frame
-
-    read_sql = read_query
-
-    def prep_table(
-        self,
-        frame,
-        name: str,
-        if_exists: Literal["fail", "replace", "append"] = "fail",
-        index: bool | str | list[str] | None = True,
-        index_label=None,
-        schema=None,
-        dtype: DtypeArg | None = None,
-    ) -> SQLTable:
-        """
-        Prepares table in the database for data insertion. Creates it if needed, etc.
-        """
-        if dtype:
-            if not is_dict_like(dtype):
-                # error: Value expression in dictionary comprehension has incompatible
-                # type "Union[ExtensionDtype, str, dtype[Any], Type[object],
-                # Dict[Hashable, Union[ExtensionDtype, Union[str, dtype[Any]],
-                # Type[str], Type[float], Type[int], Type[complex], Type[bool],
-                # Type[object]]]]"; expected type "Union[ExtensionDtype, str,
-                # dtype[Any], Type[object]]"
-                dtype = {col_name: dtype for col_name in frame}  # type: ignore[misc]
-            else:
-                dtype = cast(dict, dtype)
-
-            from sqlalchemy.types import TypeEngine
-
-            for col, my_type in dtype.items():
-                if isinstance(my_type, type) and issubclass(my_type, TypeEngine):
-                    pass
-                elif isinstance(my_type, TypeEngine):
-                    pass
-                else:
-                    raise ValueError(f"The type of {col} is not a SQLAlchemy type")
-
-        table = SQLTable(
-            name,
-            self,
-            frame=frame,
-            index=index,
-            if_exists=if_exists,
-            index_label=index_label,
-            schema=schema,
-            dtype=dtype,
-        )
-        table.create()
-        return table
-
-    def check_case_sensitive(
-        self,
-        name: str,
-        schema: str | None,
-    ) -> None:
-        """
-        Checks table name for issues with case-sensitivity.
-        Method is called after data is inserted.
-        """
-        if not name.isdigit() and not name.islower():
-            # check for potentially case sensitivity issues (GH7815)
-            # Only check when name is not a number and name is not lower case
-            from sqlalchemy import inspect as sqlalchemy_inspect
-
-            insp = sqlalchemy_inspect(self.con)
-            table_names = insp.get_table_names(schema=schema or self.meta.schema)
-            if name not in table_names:
-                msg = (
-                    f"The provided table name '{name}' is not found exactly as "
-                    "such in the database after writing the table, possibly "
-                    "due to case sensitivity issues. Consider using lower "
-                    "case table names."
-                )
-                warnings.warn(
-                    msg,
-                    UserWarning,
-                    stacklevel=find_stack_level(),
-                )
-
-    def to_sql(
-        self,
-        frame,
-        name: str,
-        if_exists: Literal["fail", "replace", "append"] = "fail",
-        index: bool = True,
-        index_label=None,
-        schema: str | None = None,
-        chunksize: int | None = None,
-        dtype: DtypeArg | None = None,
-        method: Literal["multi"] | Callable | None = None,
-        engine: str = "auto",
-        **engine_kwargs,
-    ) -> int | None:
-        """
-        Write records stored in a DataFrame to a SQL database.
-
-        Parameters
-        ----------
-        frame : DataFrame
-        name : string
-            Name of SQL table.
-        if_exists : {'fail', 'replace', 'append'}, default 'fail'
-            - fail: If table exists, do nothing.
-            - replace: If table exists, drop it, recreate it, and insert data.
-            - append: If table exists, insert data. Create if does not exist.
-        index : boolean, default True
-            Write DataFrame index as a column.
-        index_label : string or sequence, default None
-            Column label for index column(s). If None is given (default) and
-            `index` is True, then the index names are used.
-            A sequence should be given if the DataFrame uses MultiIndex.
-        schema : string, default None
-            Name of SQL schema in database to write to (if database flavor
-            supports this). If specified, this overwrites the default
-            schema of the SQLDatabase object.
-        chunksize : int, default None
-            If not None, then rows will be written in batches of this size at a
-            time.  If None, all rows will be written at once.
-        dtype : single type or dict of column name to SQL type, default None
-            Optional specifying the datatype for columns. The SQL type should
-            be a SQLAlchemy type. If all columns are of the same type, one
-            single value can be used.
-        method : {None', 'multi', callable}, default None
-            Controls the SQL insertion clause used:
-
-            * None : Uses standard SQL ``INSERT`` clause (one per row).
-            * 'multi': Pass multiple values in a single ``INSERT`` clause.
-            * callable with signature ``(pd_table, conn, keys, data_iter)``.
-
-            Details and a sample callable implementation can be found in the
-            section :ref:`insert method <io.sql.method>`.
-        engine : {'auto', 'sqlalchemy'}, default 'auto'
-            SQL engine library to use. If 'auto', then the option
-            ``io.sql.engine`` is used. The default ``io.sql.engine``
-            behavior is 'sqlalchemy'
-
-            .. versionadded:: 1.3.0
-
-        **engine_kwargs
-            Any additional kwargs are passed to the engine.
-        """
-        sql_engine = get_engine(engine)
-
-        table = self.prep_table(
-            frame=frame,
-            name=name,
-            if_exists=if_exists,
-            index=index,
-            index_label=index_label,
-            schema=schema,
-            dtype=dtype,
-        )
-
-        total_inserted = sql_engine.insert_records(
-            table=table,
-            con=self.con,
-            frame=frame,
-            name=name,
-            index=index,
-            schema=schema,
-            chunksize=chunksize,
-            method=method,
-            **engine_kwargs,
-        )
-
-        self.check_case_sensitive(name=name, schema=schema)
-        return total_inserted
-
-    @property
-    def tables(self):
-        return self.meta.tables
-
-    def has_table(self, name: str, schema: str | None = None) -> bool:
-        from sqlalchemy import inspect as sqlalchemy_inspect
-
-        insp = sqlalchemy_inspect(self.con)
-        return insp.has_table(name, schema or self.meta.schema)
-
-    def get_table(self, table_name: str, schema: str | None = None) -> Table:
-        from sqlalchemy import (
-            Numeric,
-            Table,
-        )
-
-        schema = schema or self.meta.schema
-        tbl = Table(table_name, self.meta, autoload_with=self.con, schema=schema)
-        for column in tbl.columns:
-            if isinstance(column.type, Numeric):
-                column.type.asdecimal = False
-        return tbl
-
-    def drop_table(self, table_name: str, schema: str | None = None) -> None:
-        schema = schema or self.meta.schema
-        if self.has_table(table_name, schema):
-            self.meta.reflect(
-                bind=self.con, only=[table_name], schema=schema, views=True
-            )
-            with self.run_transaction():
-                self.get_table(table_name, schema).drop(bind=self.con)
-            self.meta.clear()
-
-    def _create_sql_schema(
-        self,
-        frame: DataFrame,
-        table_name: str,
-        keys: list[str] | None = None,
-        dtype: DtypeArg | None = None,
-        schema: str | None = None,
-    ):
-        table = SQLTable(
-            table_name,
-            self,
-            frame=frame,
-            index=False,
-            keys=keys,
-            dtype=dtype,
-            schema=schema,
-        )
-        return str(table.sql_schema())
-
-
-# ---- SQL without SQLAlchemy ---
-# sqlite-specific sql strings and handler class
-# dictionary used for readability purposes
-_SQL_TYPES = {
-    "string": "TEXT",
-    "floating": "REAL",
-    "integer": "INTEGER",
-    "datetime": "TIMESTAMP",
-    "date": "DATE",
-    "time": "TIME",
-    "boolean": "INTEGER",
-}
-
-
-def _get_unicode_name(name: object):
-    try:
-        uname = str(name).encode("utf-8", "strict").decode("utf-8")
-    except UnicodeError as err:
-        raise ValueError(f"Cannot convert identifier to UTF-8: '{name}'") from err
-    return uname
-
-
-def _get_valid_sqlite_name(name: object):
-    # See https://stackoverflow.com/questions/6514274/how-do-you-escape-strings\
-    # -for-sqlite-table-column-names-in-python
-    # Ensure the string can be encoded as UTF-8.
-    # Ensure the string does not include any NUL characters.
-    # Replace all " with "".
-    # Wrap the entire thing in double quotes.
-
-    uname = _get_unicode_name(name)
-    if not len(uname):
-        raise ValueError("Empty table or column name specified")
-
-    nul_index = uname.find("\x00")
-    if nul_index >= 0:
-        raise ValueError("SQLite identifier cannot contain NULs")
-    return '"' + uname.replace('"', '""') + '"'
-
-
-class SQLiteTable(SQLTable):
-    """
-    Patch the SQLTable for fallback support.
-    Instead of a table variable just use the Create Table statement.
-    """
-
-    def __init__(self, *args, **kwargs) -> None:
-        super().__init__(*args, **kwargs)
-
-        self._register_date_adapters()
-
-    def _register_date_adapters(self) -> None:
-        # GH 8341
-        # register an adapter callable for datetime.time object
-        import sqlite3
-
-        # this will transform time(12,34,56,789) into '12:34:56.000789'
-        # (this is what sqlalchemy does)
-        def _adapt_time(t) -> str:
-            # This is faster than strftime
-            return f"{t.hour:02d}:{t.minute:02d}:{t.second:02d}.{t.microsecond:06d}"
-
-        # Also register adapters for date/datetime and co
-        # xref https://docs.python.org/3.12/library/sqlite3.html#adapter-and-converter-recipes
-        # Python 3.12+ doesn't auto-register adapters for us anymore
-
-        adapt_date_iso = lambda val: val.isoformat()
-        adapt_datetime_iso = lambda val: val.isoformat(" ")
-
-        sqlite3.register_adapter(time, _adapt_time)
-
-        sqlite3.register_adapter(date, adapt_date_iso)
-        sqlite3.register_adapter(datetime, adapt_datetime_iso)
-
-        convert_date = lambda val: date.fromisoformat(val.decode())
-        convert_timestamp = lambda val: datetime.fromisoformat(val.decode())
-
-        sqlite3.register_converter("date", convert_date)
-        sqlite3.register_converter("timestamp", convert_timestamp)
-
-    def sql_schema(self) -> str:
-        return str(";\n".join(self.table))
-
-    def _execute_create(self) -> None:
-        with self.pd_sql.run_transaction() as conn:
-            for stmt in self.table:
-                conn.execute(stmt)
-
-    def insert_statement(self, *, num_rows: int) -> str:
-        names = list(map(str, self.frame.columns))
-        wld = "?"  # wildcard char
-        escape = _get_valid_sqlite_name
-
-        if self.index is not None:
-            for idx in self.index[::-1]:
-                names.insert(0, idx)
-
-        bracketed_names = [escape(column) for column in names]
-        col_names = ",".join(bracketed_names)
-
-        row_wildcards = ",".join([wld] * len(names))
-        wildcards = ",".join([f"({row_wildcards})" for _ in range(num_rows)])
-        insert_statement = (
-            f"INSERT INTO {escape(self.name)} ({col_names}) VALUES {wildcards}"
-        )
-        return insert_statement
-
-    def _execute_insert(self, conn, keys, data_iter) -> int:
-        data_list = list(data_iter)
-        conn.executemany(self.insert_statement(num_rows=1), data_list)
-        return conn.rowcount
-
-    def _execute_insert_multi(self, conn, keys, data_iter) -> int:
-        data_list = list(data_iter)
-        flattened_data = [x for row in data_list for x in row]
-        conn.execute(self.insert_statement(num_rows=len(data_list)), flattened_data)
-        return conn.rowcount
-
-    def _create_table_setup(self):
-        """
-        Return a list of SQL statements that creates a table reflecting the
-        structure of a DataFrame.  The first entry will be a CREATE TABLE
-        statement while the rest will be CREATE INDEX statements.
-        """
-        column_names_and_types = self._get_column_names_and_types(self._sql_type_name)
-        escape = _get_valid_sqlite_name
-
-        create_tbl_stmts = [
-            escape(cname) + " " + ctype for cname, ctype, _ in column_names_and_types
-        ]
-
-        if self.keys is not None and len(self.keys):
-            if not is_list_like(self.keys):
-                keys = [self.keys]
-            else:
-                keys = self.keys
-            cnames_br = ", ".join([escape(c) for c in keys])
-            create_tbl_stmts.append(
-                f"CONSTRAINT {self.name}_pk PRIMARY KEY ({cnames_br})"
-            )
-        if self.schema:
-            schema_name = self.schema + "."
-        else:
-            schema_name = ""
-        create_stmts = [
-            "CREATE TABLE "
-            + schema_name
-            + escape(self.name)
-            + " (\n"
-            + ",\n  ".join(create_tbl_stmts)
-            + "\n)"
-        ]
-
-        ix_cols = [cname for cname, _, is_index in column_names_and_types if is_index]
-        if len(ix_cols):
-            cnames = "_".join(ix_cols)
-            cnames_br = ",".join([escape(c) for c in ix_cols])
-            create_stmts.append(
-                "CREATE INDEX "
-                + escape("ix_" + self.name + "_" + cnames)
-                + "ON "
-                + escape(self.name)
-                + " ("
-                + cnames_br
-                + ")"
-            )
-
-        return create_stmts
-
-    def _sql_type_name(self, col):
-        dtype: DtypeArg = self.dtype or {}
-        if is_dict_like(dtype):
-            dtype = cast(dict, dtype)
-            if col.name in dtype:
-                return dtype[col.name]
-
-        # Infer type of column, while ignoring missing values.
-        # Needed for inserting typed data containing NULLs, GH 8778.
-        col_type = lib.infer_dtype(col, skipna=True)
-
-        if col_type == "timedelta64":
-            warnings.warn(
-                "the 'timedelta' type is not supported, and will be "
-                "written as integer values (ns frequency) to the database.",
-                UserWarning,
-                stacklevel=find_stack_level(),
-            )
-            col_type = "integer"
-
-        elif col_type == "datetime64":
-            col_type = "datetime"
-
-        elif col_type == "empty":
-            col_type = "string"
-
-        elif col_type == "complex":
-            raise ValueError("Complex datatypes not supported")
-
-        if col_type not in _SQL_TYPES:
-            col_type = "string"
-
-        return _SQL_TYPES[col_type]
-
-
-class SQLiteDatabase(PandasSQL):
-    """
-    Version of SQLDatabase to support SQLite connections (fallback without
-    SQLAlchemy). This should only be used internally.
-
-    Parameters
-    ----------
-    con : sqlite connection object
-
-    """
-
-    def __init__(self, con) -> None:
-        self.con = con
-
-    @contextmanager
-    def run_transaction(self):
-        cur = self.con.cursor()
-        try:
-            yield cur
-            self.con.commit()
-        except Exception:
-            self.con.rollback()
-            raise
-        finally:
-            cur.close()
-
-    def execute(self, sql: str | Select | TextClause, params=None):
-        if not isinstance(sql, str):
-            raise TypeError("Query must be a string unless using sqlalchemy.")
-        args = [] if params is None else [params]
-        cur = self.con.cursor()
-        try:
-            cur.execute(sql, *args)
-            return cur
-        except Exception as exc:
-            try:
-                self.con.rollback()
-            except Exception as inner_exc:  # pragma: no cover
-                ex = DatabaseError(
-                    f"Execution failed on sql: {sql}\n{exc}\nunable to rollback"
-                )
-                raise ex from inner_exc
-
-            ex = DatabaseError(f"Execution failed on sql '{sql}': {exc}")
-            raise ex from exc
-
-    @staticmethod
-    def _query_iterator(
-        cursor,
-        chunksize: int,
-        columns,
-        index_col=None,
-        coerce_float: bool = True,
-        parse_dates=None,
-        dtype: DtypeArg | None = None,
-        dtype_backend: DtypeBackend | Literal["numpy"] = "numpy",
-    ):
-        """Return generator through chunked result set"""
-        has_read_data = False
-        while True:
-            data = cursor.fetchmany(chunksize)
-            if type(data) == tuple:
-                data = list(data)
-            if not data:
-                cursor.close()
-                if not has_read_data:
-                    result = DataFrame.from_records(
-                        [], columns=columns, coerce_float=coerce_float
-                    )
-                    if dtype:
-                        result = result.astype(dtype)
-                    yield result
-                break
-
-            has_read_data = True
-            yield _wrap_result(
-                data,
-                columns,
-                index_col=index_col,
-                coerce_float=coerce_float,
-                parse_dates=parse_dates,
-                dtype=dtype,
-                dtype_backend=dtype_backend,
-            )
-
-    def read_query(
-        self,
-        sql,
-        index_col=None,
-        coerce_float: bool = True,
-        parse_dates=None,
-        params=None,
-        chunksize: int | None = None,
-        dtype: DtypeArg | None = None,
-        dtype_backend: DtypeBackend | Literal["numpy"] = "numpy",
-    ) -> DataFrame | Iterator[DataFrame]:
-        cursor = self.execute(sql, params)
-        columns = [col_desc[0] for col_desc in cursor.description]
-
-        if chunksize is not None:
-            return self._query_iterator(
-                cursor,
-                chunksize,
-                columns,
-                index_col=index_col,
-                coerce_float=coerce_float,
-                parse_dates=parse_dates,
-                dtype=dtype,
-                dtype_backend=dtype_backend,
-            )
-        else:
-            data = self._fetchall_as_list(cursor)
-            cursor.close()
-
-            frame = _wrap_result(
-                data,
-                columns,
-                index_col=index_col,
-                coerce_float=coerce_float,
-                parse_dates=parse_dates,
-                dtype=dtype,
-                dtype_backend=dtype_backend,
-            )
-            return frame
-
-    def _fetchall_as_list(self, cur):
-        result = cur.fetchall()
-        if not isinstance(result, list):
-            result = list(result)
-        return result
-
-    def to_sql(
-        self,
-        frame,
-        name: str,
-        if_exists: str = "fail",
-        index: bool = True,
-        index_label=None,
-        schema=None,
-        chunksize: int | None = None,
-        dtype: DtypeArg | None = None,
-        method: Literal["multi"] | Callable | None = None,
-        engine: str = "auto",
-        **engine_kwargs,
-    ) -> int | None:
-        """
-        Write records stored in a DataFrame to a SQL database.
-
-        Parameters
-        ----------
-        frame: DataFrame
-        name: string
-            Name of SQL table.
-        if_exists: {'fail', 'replace', 'append'}, default 'fail'
-            fail: If table exists, do nothing.
-            replace: If table exists, drop it, recreate it, and insert data.
-            append: If table exists, insert data. Create if it does not exist.
-        index : bool, default True
-            Write DataFrame index as a column
-        index_label : string or sequence, default None
-            Column label for index column(s). If None is given (default) and
-            `index` is True, then the index names are used.
-            A sequence should be given if the DataFrame uses MultiIndex.
-        schema : string, default None
-            Ignored parameter included for compatibility with SQLAlchemy
-            version of ``to_sql``.
-        chunksize : int, default None
-            If not None, then rows will be written in batches of this
-            size at a time. If None, all rows will be written at once.
-        dtype : single type or dict of column name to SQL type, default None
-            Optional specifying the datatype for columns. The SQL type should
-            be a string. If all columns are of the same type, one single value
-            can be used.
-        method : {None, 'multi', callable}, default None
-            Controls the SQL insertion clause used:
-
-            * None : Uses standard SQL ``INSERT`` clause (one per row).
-            * 'multi': Pass multiple values in a single ``INSERT`` clause.
-            * callable with signature ``(pd_table, conn, keys, data_iter)``.
-
-            Details and a sample callable implementation can be found in the
-            section :ref:`insert method <io.sql.method>`.
-        """
-        if dtype:
-            if not is_dict_like(dtype):
-                # error: Value expression in dictionary comprehension has incompatible
-                # type "Union[ExtensionDtype, str, dtype[Any], Type[object],
-                # Dict[Hashable, Union[ExtensionDtype, Union[str, dtype[Any]],
-                # Type[str], Type[float], Type[int], Type[complex], Type[bool],
-                # Type[object]]]]"; expected type "Union[ExtensionDtype, str,
-                # dtype[Any], Type[object]]"
-                dtype = {col_name: dtype for col_name in frame}  # type: ignore[misc]
-            else:
-                dtype = cast(dict, dtype)
-
-            for col, my_type in dtype.items():
-                if not isinstance(my_type, str):
-                    raise ValueError(f"{col} ({my_type}) not a string")
-
-        table = SQLiteTable(
-            name,
-            self,
-            frame=frame,
-            index=index,
-            if_exists=if_exists,
-            index_label=index_label,
-            dtype=dtype,
-        )
-        table.create()
-        return table.insert(chunksize, method)
-
-    def has_table(self, name: str, schema: str | None = None) -> bool:
-        wld = "?"
-        query = f"""
-        SELECT
-            name
-        FROM
-            sqlite_master
-        WHERE
-            type IN ('table', 'view')
-            AND name={wld};
-        """
-
-        return len(self.execute(query, [name]).fetchall()) > 0
-
-    def get_table(self, table_name: str, schema: str | None = None) -> None:
-        return None  # not supported in fallback mode
-
-    def drop_table(self, name: str, schema: str | None = None) -> None:
-        drop_sql = f"DROP TABLE {_get_valid_sqlite_name(name)}"
-        self.execute(drop_sql)
-
-    def _create_sql_schema(
-        self,
-        frame,
-        table_name: str,
-        keys=None,
-        dtype: DtypeArg | None = None,
-        schema: str | None = None,
-    ):
-        table = SQLiteTable(
-            table_name,
-            self,
-            frame=frame,
-            index=False,
-            keys=keys,
-            dtype=dtype,
-            schema=schema,
-        )
-        return str(table.sql_schema())
-
-
-def get_schema(
-    frame,
-    name: str,
-    keys=None,
-    con=None,
-    dtype: DtypeArg | None = None,
-    schema: str | None = None,
-) -> str:
-    """
-    Get the SQL db table schema for the given frame.
-
-    Parameters
-    ----------
-    frame : DataFrame
-    name : str
-        name of SQL table
-    keys : string or sequence, default: None
-        columns to use a primary key
-    con: an open SQL database connection object or a SQLAlchemy connectable
-        Using SQLAlchemy makes it possible to use any DB supported by that
-        library, default: None
-        If a DBAPI2 object, only sqlite3 is supported.
-    dtype : dict of column name to SQL type, default None
-        Optional specifying the datatype for columns. The SQL type should
-        be a SQLAlchemy type, or a string for sqlite3 fallback connection.
-    schema: str, default: None
-        Optional specifying the schema to be used in creating the table.
-
-        .. versionadded:: 1.2.0
-    """
-    with pandasSQL_builder(con=con) as pandas_sql:
-        return pandas_sql._create_sql_schema(
-            frame, name, keys=keys, dtype=dtype, schema=schema
-        )
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/tests/indexes/test_frozen.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/tests/indexes/test_frozen.py
deleted file mode 100644
index ace66b5b06a51291d2cf229fdc446d070054836a..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/tests/indexes/test_frozen.py
+++ /dev/null
@@ -1,113 +0,0 @@
-import re
-
-import pytest
-
-from pandas.core.indexes.frozen import FrozenList
-
-
-@pytest.fixture
-def lst():
-    return [1, 2, 3, 4, 5]
-
-
-@pytest.fixture
-def container(lst):
-    return FrozenList(lst)
-
-
-@pytest.fixture
-def unicode_container():
-    return FrozenList(["\u05d0", "\u05d1", "c"])
-
-
-class TestFrozenList:
-    def check_mutable_error(self, *args, **kwargs):
-        # Pass whatever function you normally would to pytest.raises
-        # (after the Exception kind).
-        mutable_regex = re.compile("does not support mutable operations")
-        msg = "'(_s)?re.(SRE_)?Pattern' object is not callable"
-        with pytest.raises(TypeError, match=msg):
-            mutable_regex(*args, **kwargs)
-
-    def test_no_mutable_funcs(self, container):
-        def setitem():
-            container[0] = 5
-
-        self.check_mutable_error(setitem)
-
-        def setslice():
-            container[1:2] = 3
-
-        self.check_mutable_error(setslice)
-
-        def delitem():
-            del container[0]
-
-        self.check_mutable_error(delitem)
-
-        def delslice():
-            del container[0:3]
-
-        self.check_mutable_error(delslice)
-
-        mutable_methods = ("extend", "pop", "remove", "insert")
-
-        for meth in mutable_methods:
-            self.check_mutable_error(getattr(container, meth))
-
-    def test_slicing_maintains_type(self, container, lst):
-        result = container[1:2]
-        expected = lst[1:2]
-        self.check_result(result, expected)
-
-    def check_result(self, result, expected):
-        assert isinstance(result, FrozenList)
-        assert result == expected
-
-    def test_string_methods_dont_fail(self, container):
-        repr(container)
-        str(container)
-        bytes(container)
-
-    def test_tricky_container(self, unicode_container):
-        repr(unicode_container)
-        str(unicode_container)
-
-    def test_add(self, container, lst):
-        result = container + (1, 2, 3)
-        expected = FrozenList(lst + [1, 2, 3])
-        self.check_result(result, expected)
-
-        result = (1, 2, 3) + container
-        expected = FrozenList([1, 2, 3] + lst)
-        self.check_result(result, expected)
-
-    def test_iadd(self, container, lst):
-        q = r = container
-
-        q += [5]
-        self.check_result(q, lst + [5])
-
-        # Other shouldn't be mutated.
-        self.check_result(r, lst)
-
-    def test_union(self, container, lst):
-        result = container.union((1, 2, 3))
-        expected = FrozenList(lst + [1, 2, 3])
-        self.check_result(result, expected)
-
-    def test_difference(self, container):
-        result = container.difference([2])
-        expected = FrozenList([1, 3, 4, 5])
-        self.check_result(result, expected)
-
-    def test_difference_dupe(self):
-        result = FrozenList([1, 2, 3, 2]).difference([2])
-        expected = FrozenList([1, 3])
-        self.check_result(result, expected)
-
-    def test_tricky_container_to_bytes_raises(self, unicode_container):
-        # GH 26447
-        msg = "^'str' object cannot be interpreted as an integer$"
-        with pytest.raises(TypeError, match=msg):
-            bytes(unicode_container)
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/tests/io/excel/test_xlsxwriter.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/tests/io/excel/test_xlsxwriter.py
deleted file mode 100644
index c4d02d71390cc1dd9f43f0471bf67fdeaa6bcd74..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/tests/io/excel/test_xlsxwriter.py
+++ /dev/null
@@ -1,78 +0,0 @@
-import contextlib
-
-import pytest
-
-from pandas import DataFrame
-import pandas._testing as tm
-
-from pandas.io.excel import ExcelWriter
-
-xlsxwriter = pytest.importorskip("xlsxwriter")
-
-pytestmark = pytest.mark.parametrize("ext", [".xlsx"])
-
-
-def test_column_format(ext):
-    # Test that column formats are applied to cells. Test for issue #9167.
-    # Applicable to xlsxwriter only.
-    openpyxl = pytest.importorskip("openpyxl")
-
-    with tm.ensure_clean(ext) as path:
-        frame = DataFrame({"A": [123456, 123456], "B": [123456, 123456]})
-
-        with ExcelWriter(path) as writer:
-            frame.to_excel(writer)
-
-            # Add a number format to col B and ensure it is applied to cells.
-            num_format = "#,##0"
-            write_workbook = writer.book
-            write_worksheet = write_workbook.worksheets()[0]
-            col_format = write_workbook.add_format({"num_format": num_format})
-            write_worksheet.set_column("B:B", None, col_format)
-
-        with contextlib.closing(openpyxl.load_workbook(path)) as read_workbook:
-            try:
-                read_worksheet = read_workbook["Sheet1"]
-            except TypeError:
-                # compat
-                read_worksheet = read_workbook.get_sheet_by_name(name="Sheet1")
-
-        # Get the number format from the cell.
-        try:
-            cell = read_worksheet["B2"]
-        except TypeError:
-            # compat
-            cell = read_worksheet.cell("B2")
-
-        try:
-            read_num_format = cell.number_format
-        except AttributeError:
-            read_num_format = cell.style.number_format._format_code
-
-        assert read_num_format == num_format
-
-
-def test_write_append_mode_raises(ext):
-    msg = "Append mode is not supported with xlsxwriter!"
-
-    with tm.ensure_clean(ext) as f:
-        with pytest.raises(ValueError, match=msg):
-            ExcelWriter(f, engine="xlsxwriter", mode="a")
-
-
-@pytest.mark.parametrize("nan_inf_to_errors", [True, False])
-def test_engine_kwargs(ext, nan_inf_to_errors):
-    # GH 42286
-    engine_kwargs = {"options": {"nan_inf_to_errors": nan_inf_to_errors}}
-    with tm.ensure_clean(ext) as f:
-        with ExcelWriter(f, engine="xlsxwriter", engine_kwargs=engine_kwargs) as writer:
-            assert writer.book.nan_inf_to_errors == nan_inf_to_errors
-
-
-def test_book_and_sheets_consistent(ext):
-    # GH#45687 - Ensure sheets is updated if user modifies book
-    with tm.ensure_clean(ext) as f:
-        with ExcelWriter(f, engine="xlsxwriter") as writer:
-            assert writer.sheets == {}
-            sheet = writer.book.add_worksheet("test_name")
-            assert writer.sheets == {"test_name": sheet}
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/tests/io/formats/test_to_csv.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/tests/io/formats/test_to_csv.py
deleted file mode 100644
index c8e984a92f4180e202231776a2af032f80c20442..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/tests/io/formats/test_to_csv.py
+++ /dev/null
@@ -1,733 +0,0 @@
-import io
-import os
-import sys
-from zipfile import ZipFile
-
-from _csv import Error
-import numpy as np
-import pytest
-
-import pandas as pd
-from pandas import (
-    DataFrame,
-    compat,
-)
-import pandas._testing as tm
-
-
-class TestToCSV:
-    def test_to_csv_with_single_column(self):
-        # see gh-18676, https://bugs.python.org/issue32255
-        #
-        # Python's CSV library adds an extraneous '""'
-        # before the newline when the NaN-value is in
-        # the first row. Otherwise, only the newline
-        # character is added. This behavior is inconsistent
-        # and was patched in https://bugs.python.org/pull_request4672.
-        df1 = DataFrame([None, 1])
-        expected1 = """\
-""
-1.0
-"""
-        with tm.ensure_clean("test.csv") as path:
-            df1.to_csv(path, header=None, index=None)
-            with open(path, encoding="utf-8") as f:
-                assert f.read() == expected1
-
-        df2 = DataFrame([1, None])
-        expected2 = """\
-1.0
-""
-"""
-        with tm.ensure_clean("test.csv") as path:
-            df2.to_csv(path, header=None, index=None)
-            with open(path, encoding="utf-8") as f:
-                assert f.read() == expected2
-
-    def test_to_csv_default_encoding(self):
-        # GH17097
-        df = DataFrame({"col": ["AAAAA", "ÄÄÄÄÄ", "ßßßßß", "聞聞聞聞聞"]})
-
-        with tm.ensure_clean("test.csv") as path:
-            # the default to_csv encoding is uft-8.
-            df.to_csv(path)
-            tm.assert_frame_equal(pd.read_csv(path, index_col=0), df)
-
-    def test_to_csv_quotechar(self):
-        df = DataFrame({"col": [1, 2]})
-        expected = """\
-"","col"
-"0","1"
-"1","2"
-"""
-
-        with tm.ensure_clean("test.csv") as path:
-            df.to_csv(path, quoting=1)  # 1=QUOTE_ALL
-            with open(path, encoding="utf-8") as f:
-                assert f.read() == expected
-
-        expected = """\
-$$,$col$
-$0$,$1$
-$1$,$2$
-"""
-
-        with tm.ensure_clean("test.csv") as path:
-            df.to_csv(path, quoting=1, quotechar="$")
-            with open(path, encoding="utf-8") as f:
-                assert f.read() == expected
-
-        with tm.ensure_clean("test.csv") as path:
-            with pytest.raises(TypeError, match="quotechar"):
-                df.to_csv(path, quoting=1, quotechar=None)
-
-    def test_to_csv_doublequote(self):
-        df = DataFrame({"col": ['a"a', '"bb"']})
-        expected = '''\
-"","col"
-"0","a""a"
-"1","""bb"""
-'''
-
-        with tm.ensure_clean("test.csv") as path:
-            df.to_csv(path, quoting=1, doublequote=True)  # QUOTE_ALL
-            with open(path, encoding="utf-8") as f:
-                assert f.read() == expected
-
-        with tm.ensure_clean("test.csv") as path:
-            with pytest.raises(Error, match="escapechar"):
-                df.to_csv(path, doublequote=False)  # no escapechar set
-
-    def test_to_csv_escapechar(self):
-        df = DataFrame({"col": ['a"a', '"bb"']})
-        expected = """\
-"","col"
-"0","a\\"a"
-"1","\\"bb\\""
-"""
-
-        with tm.ensure_clean("test.csv") as path:  # QUOTE_ALL
-            df.to_csv(path, quoting=1, doublequote=False, escapechar="\\")
-            with open(path, encoding="utf-8") as f:
-                assert f.read() == expected
-
-        df = DataFrame({"col": ["a,a", ",bb,"]})
-        expected = """\
-,col
-0,a\\,a
-1,\\,bb\\,
-"""
-
-        with tm.ensure_clean("test.csv") as path:
-            df.to_csv(path, quoting=3, escapechar="\\")  # QUOTE_NONE
-            with open(path, encoding="utf-8") as f:
-                assert f.read() == expected
-
-    def test_csv_to_string(self):
-        df = DataFrame({"col": [1, 2]})
-        expected_rows = [",col", "0,1", "1,2"]
-        expected = tm.convert_rows_list_to_csv_str(expected_rows)
-        assert df.to_csv() == expected
-
-    def test_to_csv_decimal(self):
-        # see gh-781
-        df = DataFrame({"col1": [1], "col2": ["a"], "col3": [10.1]})
-
-        expected_rows = [",col1,col2,col3", "0,1,a,10.1"]
-        expected_default = tm.convert_rows_list_to_csv_str(expected_rows)
-        assert df.to_csv() == expected_default
-
-        expected_rows = [";col1;col2;col3", "0;1;a;10,1"]
-        expected_european_excel = tm.convert_rows_list_to_csv_str(expected_rows)
-        assert df.to_csv(decimal=",", sep=";") == expected_european_excel
-
-        expected_rows = [",col1,col2,col3", "0,1,a,10.10"]
-        expected_float_format_default = tm.convert_rows_list_to_csv_str(expected_rows)
-        assert df.to_csv(float_format="%.2f") == expected_float_format_default
-
-        expected_rows = [";col1;col2;col3", "0;1;a;10,10"]
-        expected_float_format = tm.convert_rows_list_to_csv_str(expected_rows)
-        assert (
-            df.to_csv(decimal=",", sep=";", float_format="%.2f")
-            == expected_float_format
-        )
-
-        # see gh-11553: testing if decimal is taken into account for '0.0'
-        df = DataFrame({"a": [0, 1.1], "b": [2.2, 3.3], "c": 1})
-
-        expected_rows = ["a,b,c", "0^0,2^2,1", "1^1,3^3,1"]
-        expected = tm.convert_rows_list_to_csv_str(expected_rows)
-        assert df.to_csv(index=False, decimal="^") == expected
-
-        # same but for an index
-        assert df.set_index("a").to_csv(decimal="^") == expected
-
-        # same for a multi-index
-        assert df.set_index(["a", "b"]).to_csv(decimal="^") == expected
-
-    def test_to_csv_float_format(self):
-        # testing if float_format is taken into account for the index
-        # GH 11553
-        df = DataFrame({"a": [0, 1], "b": [2.2, 3.3], "c": 1})
-
-        expected_rows = ["a,b,c", "0,2.20,1", "1,3.30,1"]
-        expected = tm.convert_rows_list_to_csv_str(expected_rows)
-        assert df.set_index("a").to_csv(float_format="%.2f") == expected
-
-        # same for a multi-index
-        assert df.set_index(["a", "b"]).to_csv(float_format="%.2f") == expected
-
-    def test_to_csv_na_rep(self):
-        # see gh-11553
-        #
-        # Testing if NaN values are correctly represented in the index.
-        df = DataFrame({"a": [0, np.nan], "b": [0, 1], "c": [2, 3]})
-        expected_rows = ["a,b,c", "0.0,0,2", "_,1,3"]
-        expected = tm.convert_rows_list_to_csv_str(expected_rows)
-
-        assert df.set_index("a").to_csv(na_rep="_") == expected
-        assert df.set_index(["a", "b"]).to_csv(na_rep="_") == expected
-
-        # now with an index containing only NaNs
-        df = DataFrame({"a": np.nan, "b": [0, 1], "c": [2, 3]})
-        expected_rows = ["a,b,c", "_,0,2", "_,1,3"]
-        expected = tm.convert_rows_list_to_csv_str(expected_rows)
-
-        assert df.set_index("a").to_csv(na_rep="_") == expected
-        assert df.set_index(["a", "b"]).to_csv(na_rep="_") == expected
-
-        # check if na_rep parameter does not break anything when no NaN
-        df = DataFrame({"a": 0, "b": [0, 1], "c": [2, 3]})
-        expected_rows = ["a,b,c", "0,0,2", "0,1,3"]
-        expected = tm.convert_rows_list_to_csv_str(expected_rows)
-
-        assert df.set_index("a").to_csv(na_rep="_") == expected
-        assert df.set_index(["a", "b"]).to_csv(na_rep="_") == expected
-
-        csv = pd.Series(["a", pd.NA, "c"]).to_csv(na_rep="ZZZZZ")
-        expected = tm.convert_rows_list_to_csv_str([",0", "0,a", "1,ZZZZZ", "2,c"])
-        assert expected == csv
-
-    def test_to_csv_na_rep_nullable_string(self, nullable_string_dtype):
-        # GH 29975
-        # Make sure full na_rep shows up when a dtype is provided
-        expected = tm.convert_rows_list_to_csv_str([",0", "0,a", "1,ZZZZZ", "2,c"])
-        csv = pd.Series(["a", pd.NA, "c"], dtype=nullable_string_dtype).to_csv(
-            na_rep="ZZZZZ"
-        )
-        assert expected == csv
-
-    def test_to_csv_date_format(self):
-        # GH 10209
-        df_sec = DataFrame({"A": pd.date_range("20130101", periods=5, freq="s")})
-        df_day = DataFrame({"A": pd.date_range("20130101", periods=5, freq="d")})
-
-        expected_rows = [
-            ",A",
-            "0,2013-01-01 00:00:00",
-            "1,2013-01-01 00:00:01",
-            "2,2013-01-01 00:00:02",
-            "3,2013-01-01 00:00:03",
-            "4,2013-01-01 00:00:04",
-        ]
-        expected_default_sec = tm.convert_rows_list_to_csv_str(expected_rows)
-        assert df_sec.to_csv() == expected_default_sec
-
-        expected_rows = [
-            ",A",
-            "0,2013-01-01 00:00:00",
-            "1,2013-01-02 00:00:00",
-            "2,2013-01-03 00:00:00",
-            "3,2013-01-04 00:00:00",
-            "4,2013-01-05 00:00:00",
-        ]
-        expected_ymdhms_day = tm.convert_rows_list_to_csv_str(expected_rows)
-        assert df_day.to_csv(date_format="%Y-%m-%d %H:%M:%S") == expected_ymdhms_day
-
-        expected_rows = [
-            ",A",
-            "0,2013-01-01",
-            "1,2013-01-01",
-            "2,2013-01-01",
-            "3,2013-01-01",
-            "4,2013-01-01",
-        ]
-        expected_ymd_sec = tm.convert_rows_list_to_csv_str(expected_rows)
-        assert df_sec.to_csv(date_format="%Y-%m-%d") == expected_ymd_sec
-
-        expected_rows = [
-            ",A",
-            "0,2013-01-01",
-            "1,2013-01-02",
-            "2,2013-01-03",
-            "3,2013-01-04",
-            "4,2013-01-05",
-        ]
-        expected_default_day = tm.convert_rows_list_to_csv_str(expected_rows)
-        assert df_day.to_csv() == expected_default_day
-        assert df_day.to_csv(date_format="%Y-%m-%d") == expected_default_day
-
-        # see gh-7791
-        #
-        # Testing if date_format parameter is taken into account
-        # for multi-indexed DataFrames.
-        df_sec["B"] = 0
-        df_sec["C"] = 1
-
-        expected_rows = ["A,B,C", "2013-01-01,0,1.0"]
-        expected_ymd_sec = tm.convert_rows_list_to_csv_str(expected_rows)
-
-        df_sec_grouped = df_sec.groupby([pd.Grouper(key="A", freq="1h"), "B"])
-        assert df_sec_grouped.mean().to_csv(date_format="%Y-%m-%d") == expected_ymd_sec
-
-    def test_to_csv_different_datetime_formats(self):
-        # GH#21734
-        df = DataFrame(
-            {
-                "date": pd.to_datetime("1970-01-01"),
-                "datetime": pd.date_range("1970-01-01", periods=2, freq="H"),
-            }
-        )
-        expected_rows = [
-            "date,datetime",
-            "1970-01-01,1970-01-01 00:00:00",
-            "1970-01-01,1970-01-01 01:00:00",
-        ]
-        expected = tm.convert_rows_list_to_csv_str(expected_rows)
-        assert df.to_csv(index=False) == expected
-
-    def test_to_csv_date_format_in_categorical(self):
-        # GH#40754
-        ser = pd.Series(pd.to_datetime(["2021-03-27", pd.NaT], format="%Y-%m-%d"))
-        ser = ser.astype("category")
-        expected = tm.convert_rows_list_to_csv_str(["0", "2021-03-27", '""'])
-        assert ser.to_csv(index=False) == expected
-
-        ser = pd.Series(
-            pd.date_range(
-                start="2021-03-27", freq="D", periods=1, tz="Europe/Berlin"
-            ).append(pd.DatetimeIndex([pd.NaT]))
-        )
-        ser = ser.astype("category")
-        assert ser.to_csv(index=False, date_format="%Y-%m-%d") == expected
-
-    def test_to_csv_float_ea_float_format(self):
-        # GH#45991
-        df = DataFrame({"a": [1.1, 2.02, pd.NA, 6.000006], "b": "c"})
-        df["a"] = df["a"].astype("Float64")
-        result = df.to_csv(index=False, float_format="%.5f")
-        expected = tm.convert_rows_list_to_csv_str(
-            ["a,b", "1.10000,c", "2.02000,c", ",c", "6.00001,c"]
-        )
-        assert result == expected
-
-    def test_to_csv_float_ea_no_float_format(self):
-        # GH#45991
-        df = DataFrame({"a": [1.1, 2.02, pd.NA, 6.000006], "b": "c"})
-        df["a"] = df["a"].astype("Float64")
-        result = df.to_csv(index=False)
-        expected = tm.convert_rows_list_to_csv_str(
-            ["a,b", "1.1,c", "2.02,c", ",c", "6.000006,c"]
-        )
-        assert result == expected
-
-    def test_to_csv_multi_index(self):
-        # see gh-6618
-        df = DataFrame([1], columns=pd.MultiIndex.from_arrays([[1], [2]]))
-
-        exp_rows = [",1", ",2", "0,1"]
-        exp = tm.convert_rows_list_to_csv_str(exp_rows)
-        assert df.to_csv() == exp
-
-        exp_rows = ["1", "2", "1"]
-        exp = tm.convert_rows_list_to_csv_str(exp_rows)
-        assert df.to_csv(index=False) == exp
-
-        df = DataFrame(
-            [1],
-            columns=pd.MultiIndex.from_arrays([[1], [2]]),
-            index=pd.MultiIndex.from_arrays([[1], [2]]),
-        )
-
-        exp_rows = [",,1", ",,2", "1,2,1"]
-        exp = tm.convert_rows_list_to_csv_str(exp_rows)
-        assert df.to_csv() == exp
-
-        exp_rows = ["1", "2", "1"]
-        exp = tm.convert_rows_list_to_csv_str(exp_rows)
-        assert df.to_csv(index=False) == exp
-
-        df = DataFrame([1], columns=pd.MultiIndex.from_arrays([["foo"], ["bar"]]))
-
-        exp_rows = [",foo", ",bar", "0,1"]
-        exp = tm.convert_rows_list_to_csv_str(exp_rows)
-        assert df.to_csv() == exp
-
-        exp_rows = ["foo", "bar", "1"]
-        exp = tm.convert_rows_list_to_csv_str(exp_rows)
-        assert df.to_csv(index=False) == exp
-
-    @pytest.mark.parametrize(
-        "ind,expected",
-        [
-            (
-                pd.MultiIndex(levels=[[1.0]], codes=[[0]], names=["x"]),
-                "x,data\n1.0,1\n",
-            ),
-            (
-                pd.MultiIndex(
-                    levels=[[1.0], [2.0]], codes=[[0], [0]], names=["x", "y"]
-                ),
-                "x,y,data\n1.0,2.0,1\n",
-            ),
-        ],
-    )
-    def test_to_csv_single_level_multi_index(self, ind, expected, frame_or_series):
-        # see gh-19589
-        obj = frame_or_series(pd.Series([1], ind, name="data"))
-
-        result = obj.to_csv(lineterminator="\n", header=True)
-        assert result == expected
-
-    def test_to_csv_string_array_ascii(self):
-        # GH 10813
-        str_array = [{"names": ["foo", "bar"]}, {"names": ["baz", "qux"]}]
-        df = DataFrame(str_array)
-        expected_ascii = """\
-,names
-0,"['foo', 'bar']"
-1,"['baz', 'qux']"
-"""
-        with tm.ensure_clean("str_test.csv") as path:
-            df.to_csv(path, encoding="ascii")
-            with open(path, encoding="utf-8") as f:
-                assert f.read() == expected_ascii
-
-    def test_to_csv_string_array_utf8(self):
-        # GH 10813
-        str_array = [{"names": ["foo", "bar"]}, {"names": ["baz", "qux"]}]
-        df = DataFrame(str_array)
-        expected_utf8 = """\
-,names
-0,"['foo', 'bar']"
-1,"['baz', 'qux']"
-"""
-        with tm.ensure_clean("unicode_test.csv") as path:
-            df.to_csv(path, encoding="utf-8")
-            with open(path, encoding="utf-8") as f:
-                assert f.read() == expected_utf8
-
-    def test_to_csv_string_with_lf(self):
-        # GH 20353
-        data = {"int": [1, 2, 3], "str_lf": ["abc", "d\nef", "g\nh\n\ni"]}
-        df = DataFrame(data)
-        with tm.ensure_clean("lf_test.csv") as path:
-            # case 1: The default line terminator(=os.linesep)(PR 21406)
-            os_linesep = os.linesep.encode("utf-8")
-            expected_noarg = (
-                b"int,str_lf"
-                + os_linesep
-                + b"1,abc"
-                + os_linesep
-                + b'2,"d\nef"'
-                + os_linesep
-                + b'3,"g\nh\n\ni"'
-                + os_linesep
-            )
-            df.to_csv(path, index=False)
-            with open(path, "rb") as f:
-                assert f.read() == expected_noarg
-        with tm.ensure_clean("lf_test.csv") as path:
-            # case 2: LF as line terminator
-            expected_lf = b'int,str_lf\n1,abc\n2,"d\nef"\n3,"g\nh\n\ni"\n'
-            df.to_csv(path, lineterminator="\n", index=False)
-            with open(path, "rb") as f:
-                assert f.read() == expected_lf
-        with tm.ensure_clean("lf_test.csv") as path:
-            # case 3: CRLF as line terminator
-            # 'lineterminator' should not change inner element
-            expected_crlf = b'int,str_lf\r\n1,abc\r\n2,"d\nef"\r\n3,"g\nh\n\ni"\r\n'
-            df.to_csv(path, lineterminator="\r\n", index=False)
-            with open(path, "rb") as f:
-                assert f.read() == expected_crlf
-
-    def test_to_csv_string_with_crlf(self):
-        # GH 20353
-        data = {"int": [1, 2, 3], "str_crlf": ["abc", "d\r\nef", "g\r\nh\r\n\r\ni"]}
-        df = DataFrame(data)
-        with tm.ensure_clean("crlf_test.csv") as path:
-            # case 1: The default line terminator(=os.linesep)(PR 21406)
-            os_linesep = os.linesep.encode("utf-8")
-            expected_noarg = (
-                b"int,str_crlf"
-                + os_linesep
-                + b"1,abc"
-                + os_linesep
-                + b'2,"d\r\nef"'
-                + os_linesep
-                + b'3,"g\r\nh\r\n\r\ni"'
-                + os_linesep
-            )
-            df.to_csv(path, index=False)
-            with open(path, "rb") as f:
-                assert f.read() == expected_noarg
-        with tm.ensure_clean("crlf_test.csv") as path:
-            # case 2: LF as line terminator
-            expected_lf = b'int,str_crlf\n1,abc\n2,"d\r\nef"\n3,"g\r\nh\r\n\r\ni"\n'
-            df.to_csv(path, lineterminator="\n", index=False)
-            with open(path, "rb") as f:
-                assert f.read() == expected_lf
-        with tm.ensure_clean("crlf_test.csv") as path:
-            # case 3: CRLF as line terminator
-            # 'lineterminator' should not change inner element
-            expected_crlf = (
-                b"int,str_crlf\r\n"
-                b"1,abc\r\n"
-                b'2,"d\r\nef"\r\n'
-                b'3,"g\r\nh\r\n\r\ni"\r\n'
-            )
-            df.to_csv(path, lineterminator="\r\n", index=False)
-            with open(path, "rb") as f:
-                assert f.read() == expected_crlf
-
-    def test_to_csv_stdout_file(self, capsys):
-        # GH 21561
-        df = DataFrame([["foo", "bar"], ["baz", "qux"]], columns=["name_1", "name_2"])
-        expected_rows = [",name_1,name_2", "0,foo,bar", "1,baz,qux"]
-        expected_ascii = tm.convert_rows_list_to_csv_str(expected_rows)
-
-        df.to_csv(sys.stdout, encoding="ascii")
-        captured = capsys.readouterr()
-
-        assert captured.out == expected_ascii
-        assert not sys.stdout.closed
-
-    @pytest.mark.xfail(
-        compat.is_platform_windows(),
-        reason=(
-            "Especially in Windows, file stream should not be passed"
-            "to csv writer without newline='' option."
-            "(https://docs.python.org/3/library/csv.html#csv.writer)"
-        ),
-    )
-    def test_to_csv_write_to_open_file(self):
-        # GH 21696
-        df = DataFrame({"a": ["x", "y", "z"]})
-        expected = """\
-manual header
-x
-y
-z
-"""
-        with tm.ensure_clean("test.txt") as path:
-            with open(path, "w", encoding="utf-8") as f:
-                f.write("manual header\n")
-                df.to_csv(f, header=None, index=None)
-            with open(path, encoding="utf-8") as f:
-                assert f.read() == expected
-
-    def test_to_csv_write_to_open_file_with_newline_py3(self):
-        # see gh-21696
-        # see gh-20353
-        df = DataFrame({"a": ["x", "y", "z"]})
-        expected_rows = ["x", "y", "z"]
-        expected = "manual header\n" + tm.convert_rows_list_to_csv_str(expected_rows)
-        with tm.ensure_clean("test.txt") as path:
-            with open(path, "w", newline="", encoding="utf-8") as f:
-                f.write("manual header\n")
-                df.to_csv(f, header=None, index=None)
-
-            with open(path, "rb") as f:
-                assert f.read() == bytes(expected, "utf-8")
-
-    @pytest.mark.parametrize("to_infer", [True, False])
-    @pytest.mark.parametrize("read_infer", [True, False])
-    def test_to_csv_compression(
-        self, compression_only, read_infer, to_infer, compression_to_extension
-    ):
-        # see gh-15008
-        compression = compression_only
-
-        # We'll complete file extension subsequently.
-        filename = "test."
-        filename += compression_to_extension[compression]
-
-        df = DataFrame({"A": [1]})
-
-        to_compression = "infer" if to_infer else compression
-        read_compression = "infer" if read_infer else compression
-
-        with tm.ensure_clean(filename) as path:
-            df.to_csv(path, compression=to_compression)
-            result = pd.read_csv(path, index_col=0, compression=read_compression)
-            tm.assert_frame_equal(result, df)
-
-    def test_to_csv_compression_dict(self, compression_only):
-        # GH 26023
-        method = compression_only
-        df = DataFrame({"ABC": [1]})
-        filename = "to_csv_compress_as_dict."
-        extension = {
-            "gzip": "gz",
-            "zstd": "zst",
-        }.get(method, method)
-        filename += extension
-        with tm.ensure_clean(filename) as path:
-            df.to_csv(path, compression={"method": method})
-            read_df = pd.read_csv(path, index_col=0)
-            tm.assert_frame_equal(read_df, df)
-
-    def test_to_csv_compression_dict_no_method_raises(self):
-        # GH 26023
-        df = DataFrame({"ABC": [1]})
-        compression = {"some_option": True}
-        msg = "must have key 'method'"
-
-        with tm.ensure_clean("out.zip") as path:
-            with pytest.raises(ValueError, match=msg):
-                df.to_csv(path, compression=compression)
-
-    @pytest.mark.parametrize("compression", ["zip", "infer"])
-    @pytest.mark.parametrize("archive_name", ["test_to_csv.csv", "test_to_csv.zip"])
-    def test_to_csv_zip_arguments(self, compression, archive_name):
-        # GH 26023
-        df = DataFrame({"ABC": [1]})
-        with tm.ensure_clean("to_csv_archive_name.zip") as path:
-            df.to_csv(
-                path, compression={"method": compression, "archive_name": archive_name}
-            )
-            with ZipFile(path) as zp:
-                assert len(zp.filelist) == 1
-                archived_file = zp.filelist[0].filename
-                assert archived_file == archive_name
-
-    @pytest.mark.parametrize(
-        "filename,expected_arcname",
-        [
-            ("archive.csv", "archive.csv"),
-            ("archive.tsv", "archive.tsv"),
-            ("archive.csv.zip", "archive.csv"),
-            ("archive.tsv.zip", "archive.tsv"),
-            ("archive.zip", "archive"),
-        ],
-    )
-    def test_to_csv_zip_infer_name(self, tmp_path, filename, expected_arcname):
-        # GH 39465
-        df = DataFrame({"ABC": [1]})
-        path = tmp_path / filename
-        df.to_csv(path, compression="zip")
-        with ZipFile(path) as zp:
-            assert len(zp.filelist) == 1
-            archived_file = zp.filelist[0].filename
-            assert archived_file == expected_arcname
-
-    @pytest.mark.parametrize("df_new_type", ["Int64"])
-    def test_to_csv_na_rep_long_string(self, df_new_type):
-        # see gh-25099
-        df = DataFrame({"c": [float("nan")] * 3})
-        df = df.astype(df_new_type)
-        expected_rows = ["c", "mynull", "mynull", "mynull"]
-        expected = tm.convert_rows_list_to_csv_str(expected_rows)
-
-        result = df.to_csv(index=False, na_rep="mynull", encoding="ascii")
-
-        assert expected == result
-
-    def test_to_csv_timedelta_precision(self):
-        # GH 6783
-        s = pd.Series([1, 1]).astype("timedelta64[ns]")
-        buf = io.StringIO()
-        s.to_csv(buf)
-        result = buf.getvalue()
-        expected_rows = [
-            ",0",
-            "0,0 days 00:00:00.000000001",
-            "1,0 days 00:00:00.000000001",
-        ]
-        expected = tm.convert_rows_list_to_csv_str(expected_rows)
-        assert result == expected
-
-    def test_na_rep_truncated(self):
-        # https://github.com/pandas-dev/pandas/issues/31447
-        result = pd.Series(range(8, 12)).to_csv(na_rep="-")
-        expected = tm.convert_rows_list_to_csv_str([",0", "0,8", "1,9", "2,10", "3,11"])
-        assert result == expected
-
-        result = pd.Series([True, False]).to_csv(na_rep="nan")
-        expected = tm.convert_rows_list_to_csv_str([",0", "0,True", "1,False"])
-        assert result == expected
-
-        result = pd.Series([1.1, 2.2]).to_csv(na_rep=".")
-        expected = tm.convert_rows_list_to_csv_str([",0", "0,1.1", "1,2.2"])
-        assert result == expected
-
-    @pytest.mark.parametrize("errors", ["surrogatepass", "ignore", "replace"])
-    def test_to_csv_errors(self, errors):
-        # GH 22610
-        data = ["\ud800foo"]
-        ser = pd.Series(data, index=pd.Index(data))
-        with tm.ensure_clean("test.csv") as path:
-            ser.to_csv(path, errors=errors)
-        # No use in reading back the data as it is not the same anymore
-        # due to the error handling
-
-    @pytest.mark.parametrize("mode", ["wb", "w"])
-    def test_to_csv_binary_handle(self, mode):
-        """
-        Binary file objects should work (if 'mode' contains a 'b') or even without
-        it in most cases.
-
-        GH 35058 and GH 19827
-        """
-        df = tm.makeDataFrame()
-        with tm.ensure_clean() as path:
-            with open(path, mode="w+b") as handle:
-                df.to_csv(handle, mode=mode)
-            tm.assert_frame_equal(df, pd.read_csv(path, index_col=0))
-
-    @pytest.mark.parametrize("mode", ["wb", "w"])
-    def test_to_csv_encoding_binary_handle(self, mode):
-        """
-        Binary file objects should honor a specified encoding.
-
-        GH 23854 and GH 13068 with binary handles
-        """
-        # example from GH 23854
-        content = "a, b, 🐟".encode("utf-8-sig")
-        buffer = io.BytesIO(content)
-        df = pd.read_csv(buffer, encoding="utf-8-sig")
-
-        buffer = io.BytesIO()
-        df.to_csv(buffer, mode=mode, encoding="utf-8-sig", index=False)
-        buffer.seek(0)  # tests whether file handle wasn't closed
-        assert buffer.getvalue().startswith(content)
-
-        # example from GH 13068
-        with tm.ensure_clean() as path:
-            with open(path, "w+b") as handle:
-                DataFrame().to_csv(handle, mode=mode, encoding="utf-8-sig")
-
-                handle.seek(0)
-                assert handle.read().startswith(b'\xef\xbb\xbf""')
-
-
-def test_to_csv_iterative_compression_name(compression):
-    # GH 38714
-    df = tm.makeDataFrame()
-    with tm.ensure_clean() as path:
-        df.to_csv(path, compression=compression, chunksize=1)
-        tm.assert_frame_equal(
-            pd.read_csv(path, compression=compression, index_col=0), df
-        )
-
-
-def test_to_csv_iterative_compression_buffer(compression):
-    # GH 38714
-    df = tm.makeDataFrame()
-    with io.BytesIO() as buffer:
-        df.to_csv(buffer, compression=compression, chunksize=1)
-        buffer.seek(0)
-        tm.assert_frame_equal(
-            pd.read_csv(buffer, compression=compression, index_col=0), df
-        )
-        assert not buffer.closed
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/tests/io/test_gcs.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/tests/io/test_gcs.py
deleted file mode 100644
index 89655e8693d7f099b0034496d564fcc9981b3a6f..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/tests/io/test_gcs.py
+++ /dev/null
@@ -1,210 +0,0 @@
-from io import BytesIO
-import os
-import pathlib
-import tarfile
-import zipfile
-
-import numpy as np
-import pytest
-
-from pandas import (
-    DataFrame,
-    date_range,
-    read_csv,
-    read_excel,
-    read_json,
-    read_parquet,
-)
-import pandas._testing as tm
-from pandas.util import _test_decorators as td
-
-
-@pytest.fixture
-def gcs_buffer():
-    """Emulate GCS using a binary buffer."""
-    pytest.importorskip("gcsfs")
-    fsspec = pytest.importorskip("fsspec")
-
-    gcs_buffer = BytesIO()
-    gcs_buffer.close = lambda: True
-
-    class MockGCSFileSystem(fsspec.AbstractFileSystem):
-        @staticmethod
-        def open(*args, **kwargs):
-            gcs_buffer.seek(0)
-            return gcs_buffer
-
-        def ls(self, path, **kwargs):
-            # needed for pyarrow
-            return [{"name": path, "type": "file"}]
-
-    # Overwrites the default implementation from gcsfs to our mock class
-    fsspec.register_implementation("gs", MockGCSFileSystem, clobber=True)
-
-    return gcs_buffer
-
-
-# Patches pyarrow; other processes should not pick up change
-@pytest.mark.single_cpu
-@pytest.mark.parametrize("format", ["csv", "json", "parquet", "excel", "markdown"])
-def test_to_read_gcs(gcs_buffer, format, monkeypatch, capsys):
-    """
-    Test that many to/read functions support GCS.
-
-    GH 33987
-    """
-
-    df1 = DataFrame(
-        {
-            "int": [1, 3],
-            "float": [2.0, np.nan],
-            "str": ["t", "s"],
-            "dt": date_range("2018-06-18", periods=2),
-        }
-    )
-
-    path = f"gs://test/test.{format}"
-
-    if format == "csv":
-        df1.to_csv(path, index=True)
-        df2 = read_csv(path, parse_dates=["dt"], index_col=0)
-    elif format == "excel":
-        path = "gs://test/test.xlsx"
-        df1.to_excel(path)
-        df2 = read_excel(path, parse_dates=["dt"], index_col=0)
-    elif format == "json":
-        df1.to_json(path)
-        df2 = read_json(path, convert_dates=["dt"])
-    elif format == "parquet":
-        pytest.importorskip("pyarrow")
-        pa_fs = pytest.importorskip("pyarrow.fs")
-
-        class MockFileSystem(pa_fs.FileSystem):
-            @staticmethod
-            def from_uri(path):
-                print("Using pyarrow filesystem")
-                to_local = pathlib.Path(path.replace("gs://", "")).absolute().as_uri()
-                return pa_fs.LocalFileSystem(to_local)
-
-        with monkeypatch.context() as m:
-            m.setattr(pa_fs, "FileSystem", MockFileSystem)
-            df1.to_parquet(path)
-            df2 = read_parquet(path)
-        captured = capsys.readouterr()
-        assert captured.out == "Using pyarrow filesystem\nUsing pyarrow filesystem\n"
-    elif format == "markdown":
-        pytest.importorskip("tabulate")
-        df1.to_markdown(path)
-        df2 = df1
-
-    tm.assert_frame_equal(df1, df2)
-
-
-def assert_equal_zip_safe(result: bytes, expected: bytes, compression: str):
-    """
-    For zip compression, only compare the CRC-32 checksum of the file contents
-    to avoid checking the time-dependent last-modified timestamp which
-    in some CI builds is off-by-one
-
-    See https://en.wikipedia.org/wiki/ZIP_(file_format)#File_headers
-    """
-    if compression == "zip":
-        # Only compare the CRC checksum of the file contents
-        with zipfile.ZipFile(BytesIO(result)) as exp, zipfile.ZipFile(
-            BytesIO(expected)
-        ) as res:
-            for res_info, exp_info in zip(res.infolist(), exp.infolist()):
-                assert res_info.CRC == exp_info.CRC
-    elif compression == "tar":
-        with tarfile.open(fileobj=BytesIO(result)) as tar_exp, tarfile.open(
-            fileobj=BytesIO(expected)
-        ) as tar_res:
-            for tar_res_info, tar_exp_info in zip(
-                tar_res.getmembers(), tar_exp.getmembers()
-            ):
-                actual_file = tar_res.extractfile(tar_res_info)
-                expected_file = tar_exp.extractfile(tar_exp_info)
-                assert (actual_file is None) == (expected_file is None)
-                if actual_file is not None and expected_file is not None:
-                    assert actual_file.read() == expected_file.read()
-    else:
-        assert result == expected
-
-
-@pytest.mark.parametrize("encoding", ["utf-8", "cp1251"])
-def test_to_csv_compression_encoding_gcs(
-    gcs_buffer, compression_only, encoding, compression_to_extension
-):
-    """
-    Compression and encoding should with GCS.
-
-    GH 35677 (to_csv, compression), GH 26124 (to_csv, encoding), and
-    GH 32392 (read_csv, encoding)
-    """
-    df = tm.makeDataFrame()
-
-    # reference of compressed and encoded file
-    compression = {"method": compression_only}
-    if compression_only == "gzip":
-        compression["mtime"] = 1  # be reproducible
-    buffer = BytesIO()
-    df.to_csv(buffer, compression=compression, encoding=encoding, mode="wb")
-
-    # write compressed file with explicit compression
-    path_gcs = "gs://test/test.csv"
-    df.to_csv(path_gcs, compression=compression, encoding=encoding)
-    res = gcs_buffer.getvalue()
-    expected = buffer.getvalue()
-    assert_equal_zip_safe(res, expected, compression_only)
-
-    read_df = read_csv(
-        path_gcs, index_col=0, compression=compression_only, encoding=encoding
-    )
-    tm.assert_frame_equal(df, read_df)
-
-    # write compressed file with implicit compression
-    file_ext = compression_to_extension[compression_only]
-    compression["method"] = "infer"
-    path_gcs += f".{file_ext}"
-    df.to_csv(path_gcs, compression=compression, encoding=encoding)
-
-    res = gcs_buffer.getvalue()
-    expected = buffer.getvalue()
-    assert_equal_zip_safe(res, expected, compression_only)
-
-    read_df = read_csv(path_gcs, index_col=0, compression="infer", encoding=encoding)
-    tm.assert_frame_equal(df, read_df)
-
-
-def test_to_parquet_gcs_new_file(monkeypatch, tmpdir):
-    """Regression test for writing to a not-yet-existent GCS Parquet file."""
-    pytest.importorskip("fastparquet")
-    pytest.importorskip("gcsfs")
-
-    from fsspec import AbstractFileSystem
-
-    df1 = DataFrame(
-        {
-            "int": [1, 3],
-            "float": [2.0, np.nan],
-            "str": ["t", "s"],
-            "dt": date_range("2018-06-18", periods=2),
-        }
-    )
-
-    class MockGCSFileSystem(AbstractFileSystem):
-        def open(self, path, mode="r", *args):
-            if "w" not in mode:
-                raise FileNotFoundError
-            return open(os.path.join(tmpdir, "test.parquet"), mode, encoding="utf-8")
-
-    monkeypatch.setattr("gcsfs.GCSFileSystem", MockGCSFileSystem)
-    df1.to_parquet(
-        "gs://test/test.csv", index=True, engine="fastparquet", compression=None
-    )
-
-
-@td.skip_if_installed("gcsfs")
-def test_gcs_not_present_exception():
-    with tm.external_error_raised(ImportError):
-        read_csv("gs://test/test.csv")
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/tests/series/methods/test_view.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/tests/series/methods/test_view.py
deleted file mode 100644
index a9b29c9329193675512ee77e697a063096af2a33..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/tests/series/methods/test_view.py
+++ /dev/null
@@ -1,57 +0,0 @@
-import numpy as np
-import pytest
-
-from pandas import (
-    Index,
-    Series,
-    array,
-    date_range,
-)
-import pandas._testing as tm
-
-
-class TestView:
-    def test_view_i8_to_datetimelike(self):
-        dti = date_range("2000", periods=4, tz="US/Central")
-        ser = Series(dti.asi8)
-
-        result = ser.view(dti.dtype)
-        tm.assert_datetime_array_equal(result._values, dti._data._with_freq(None))
-
-        pi = dti.tz_localize(None).to_period("D")
-        ser = Series(pi.asi8)
-        result = ser.view(pi.dtype)
-        tm.assert_period_array_equal(result._values, pi._data)
-
-    def test_view_tz(self):
-        # GH#24024
-        ser = Series(date_range("2000", periods=4, tz="US/Central"))
-        result = ser.view("i8")
-        expected = Series(
-            [
-                946706400000000000,
-                946792800000000000,
-                946879200000000000,
-                946965600000000000,
-            ]
-        )
-        tm.assert_series_equal(result, expected)
-
-    @pytest.mark.parametrize(
-        "first", ["m8[ns]", "M8[ns]", "M8[ns, US/Central]", "period[D]"]
-    )
-    @pytest.mark.parametrize(
-        "second", ["m8[ns]", "M8[ns]", "M8[ns, US/Central]", "period[D]"]
-    )
-    @pytest.mark.parametrize("box", [Series, Index, array])
-    def test_view_between_datetimelike(self, first, second, box):
-        dti = date_range("2016-01-01", periods=3)
-
-        orig = box(dti)
-        obj = orig.view(first)
-        assert obj.dtype == first
-        tm.assert_numpy_array_equal(np.asarray(obj.view("i8")), dti.asi8)
-
-        res = obj.view(second)
-        assert res.dtype == second
-        tm.assert_numpy_array_equal(np.asarray(obj.view("i8")), dti.asi8)
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pip/_vendor/rich/spinner.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pip/_vendor/rich/spinner.py
deleted file mode 100644
index 5b13b1e9ba2c495ee4f00b8bc1f750625b7b6ff7..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pip/_vendor/rich/spinner.py
+++ /dev/null
@@ -1,134 +0,0 @@
-from typing import cast, List, Optional, TYPE_CHECKING
-
-from ._spinners import SPINNERS
-from .measure import Measurement
-from .table import Table
-from .text import Text
-
-if TYPE_CHECKING:
-    from .console import Console, ConsoleOptions, RenderResult, RenderableType
-    from .style import StyleType
-
-
-class Spinner:
-    def __init__(
-        self,
-        name: str,
-        text: "RenderableType" = "",
-        *,
-        style: Optional["StyleType"] = None,
-        speed: float = 1.0,
-    ) -> None:
-        """A spinner animation.
-
-        Args:
-            name (str): Name of spinner (run python -m rich.spinner).
-            text (RenderableType, optional): A renderable to display at the right of the spinner (str or Text typically). Defaults to "".
-            style (StyleType, optional): Style for spinner animation. Defaults to None.
-            speed (float, optional): Speed factor for animation. Defaults to 1.0.
-
-        Raises:
-            KeyError: If name isn't one of the supported spinner animations.
-        """
-        try:
-            spinner = SPINNERS[name]
-        except KeyError:
-            raise KeyError(f"no spinner called {name!r}")
-        self.text = Text.from_markup(text) if isinstance(text, str) else text
-        self.frames = cast(List[str], spinner["frames"])[:]
-        self.interval = cast(float, spinner["interval"])
-        self.start_time: Optional[float] = None
-        self.style = style
-        self.speed = speed
-        self.frame_no_offset: float = 0.0
-        self._update_speed = 0.0
-
-    def __rich_console__(
-        self, console: "Console", options: "ConsoleOptions"
-    ) -> "RenderResult":
-        yield self.render(console.get_time())
-
-    def __rich_measure__(
-        self, console: "Console", options: "ConsoleOptions"
-    ) -> Measurement:
-        text = self.render(0)
-        return Measurement.get(console, options, text)
-
-    def render(self, time: float) -> "RenderableType":
-        """Render the spinner for a given time.
-
-        Args:
-            time (float): Time in seconds.
-
-        Returns:
-            RenderableType: A renderable containing animation frame.
-        """
-        if self.start_time is None:
-            self.start_time = time
-
-        frame_no = ((time - self.start_time) * self.speed) / (
-            self.interval / 1000.0
-        ) + self.frame_no_offset
-        frame = Text(
-            self.frames[int(frame_no) % len(self.frames)], style=self.style or ""
-        )
-
-        if self._update_speed:
-            self.frame_no_offset = frame_no
-            self.start_time = time
-            self.speed = self._update_speed
-            self._update_speed = 0.0
-
-        if not self.text:
-            return frame
-        elif isinstance(self.text, (str, Text)):
-            return Text.assemble(frame, " ", self.text)
-        else:
-            table = Table.grid(padding=1)
-            table.add_row(frame, self.text)
-            return table
-
-    def update(
-        self,
-        *,
-        text: "RenderableType" = "",
-        style: Optional["StyleType"] = None,
-        speed: Optional[float] = None,
-    ) -> None:
-        """Updates attributes of a spinner after it has been started.
-
-        Args:
-            text (RenderableType, optional): A renderable to display at the right of the spinner (str or Text typically). Defaults to "".
-            style (StyleType, optional): Style for spinner animation. Defaults to None.
-            speed (float, optional): Speed factor for animation. Defaults to None.
-        """
-        if text:
-            self.text = Text.from_markup(text) if isinstance(text, str) else text
-        if style:
-            self.style = style
-        if speed:
-            self._update_speed = speed
-
-
-if __name__ == "__main__":  # pragma: no cover
-    from time import sleep
-
-    from .columns import Columns
-    from .panel import Panel
-    from .live import Live
-
-    all_spinners = Columns(
-        [
-            Spinner(spinner_name, text=Text(repr(spinner_name), style="green"))
-            for spinner_name in sorted(SPINNERS.keys())
-        ],
-        column_first=True,
-        expand=True,
-    )
-
-    with Live(
-        Panel(all_spinners, title="Spinners", border_style="blue"),
-        refresh_per_second=20,
-    ) as live:
-        while True:
-            sleep(0.1)
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/urllib3/util/connection.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/urllib3/util/connection.py
deleted file mode 100644
index 5c7da73f4e0e57cfe9074c50c2628300130fc94d..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/urllib3/util/connection.py
+++ /dev/null
@@ -1,137 +0,0 @@
-from __future__ import annotations
-
-import socket
-import typing
-
-from ..exceptions import LocationParseError
-from .timeout import _DEFAULT_TIMEOUT, _TYPE_TIMEOUT
-
-_TYPE_SOCKET_OPTIONS = typing.Sequence[typing.Tuple[int, int, typing.Union[int, bytes]]]
-
-if typing.TYPE_CHECKING:
-    from .._base_connection import BaseHTTPConnection
-
-
-def is_connection_dropped(conn: BaseHTTPConnection) -> bool:  # Platform-specific
-    """
-    Returns True if the connection is dropped and should be closed.
-    :param conn: :class:`urllib3.connection.HTTPConnection` object.
-    """
-    return not conn.is_connected
-
-
-# This function is copied from socket.py in the Python 2.7 standard
-# library test suite. Added to its signature is only `socket_options`.
-# One additional modification is that we avoid binding to IPv6 servers
-# discovered in DNS if the system doesn't have IPv6 functionality.
-def create_connection(
-    address: tuple[str, int],
-    timeout: _TYPE_TIMEOUT = _DEFAULT_TIMEOUT,
-    source_address: tuple[str, int] | None = None,
-    socket_options: _TYPE_SOCKET_OPTIONS | None = None,
-) -> socket.socket:
-    """Connect to *address* and return the socket object.
-
-    Convenience function.  Connect to *address* (a 2-tuple ``(host,
-    port)``) and return the socket object.  Passing the optional
-    *timeout* parameter will set the timeout on the socket instance
-    before attempting to connect.  If no *timeout* is supplied, the
-    global default timeout setting returned by :func:`socket.getdefaulttimeout`
-    is used.  If *source_address* is set it must be a tuple of (host, port)
-    for the socket to bind as a source address before making the connection.
-    An host of '' or port 0 tells the OS to use the default.
-    """
-
-    host, port = address
-    if host.startswith("["):
-        host = host.strip("[]")
-    err = None
-
-    # Using the value from allowed_gai_family() in the context of getaddrinfo lets
-    # us select whether to work with IPv4 DNS records, IPv6 records, or both.
-    # The original create_connection function always returns all records.
-    family = allowed_gai_family()
-
-    try:
-        host.encode("idna")
-    except UnicodeError:
-        raise LocationParseError(f"'{host}', label empty or too long") from None
-
-    for res in socket.getaddrinfo(host, port, family, socket.SOCK_STREAM):
-        af, socktype, proto, canonname, sa = res
-        sock = None
-        try:
-            sock = socket.socket(af, socktype, proto)
-
-            # If provided, set socket level options before connecting.
-            _set_socket_options(sock, socket_options)
-
-            if timeout is not _DEFAULT_TIMEOUT:
-                sock.settimeout(timeout)
-            if source_address:
-                sock.bind(source_address)
-            sock.connect(sa)
-            # Break explicitly a reference cycle
-            err = None
-            return sock
-
-        except OSError as _:
-            err = _
-            if sock is not None:
-                sock.close()
-
-    if err is not None:
-        try:
-            raise err
-        finally:
-            # Break explicitly a reference cycle
-            err = None
-    else:
-        raise OSError("getaddrinfo returns an empty list")
-
-
-def _set_socket_options(
-    sock: socket.socket, options: _TYPE_SOCKET_OPTIONS | None
-) -> None:
-    if options is None:
-        return
-
-    for opt in options:
-        sock.setsockopt(*opt)
-
-
-def allowed_gai_family() -> socket.AddressFamily:
-    """This function is designed to work in the context of
-    getaddrinfo, where family=socket.AF_UNSPEC is the default and
-    will perform a DNS search for both IPv6 and IPv4 records."""
-
-    family = socket.AF_INET
-    if HAS_IPV6:
-        family = socket.AF_UNSPEC
-    return family
-
-
-def _has_ipv6(host: str) -> bool:
-    """Returns True if the system can bind an IPv6 address."""
-    sock = None
-    has_ipv6 = False
-
-    if socket.has_ipv6:
-        # has_ipv6 returns true if cPython was compiled with IPv6 support.
-        # It does not tell us if the system has IPv6 support enabled. To
-        # determine that we must bind to an IPv6 address.
-        # https://github.com/urllib3/urllib3/pull/611
-        # https://bugs.python.org/issue658327
-        try:
-            sock = socket.socket(socket.AF_INET6)
-            sock.bind((host, 0))
-            has_ipv6 = True
-        except Exception:
-            pass
-
-    if sock:
-        sock.close()
-    return has_ipv6
-
-
-HAS_IPV6 = _has_ipv6("::1")
diff --git a/spaces/qingxu98/gpt-academic/docs/WithFastapi.md b/spaces/qingxu98/gpt-academic/docs/WithFastapi.md
deleted file mode 100644
index 188b52716485f15e528772c6454ee7839ced4406..0000000000000000000000000000000000000000
--- a/spaces/qingxu98/gpt-academic/docs/WithFastapi.md
+++ /dev/null
@@ -1,43 +0,0 @@
-# Running with fastapi
-
-We currently support fastapi in order to solve sub-path deploy issue.
-
-1. change CUSTOM_PATH setting in `config.py`
-
-``` sh
-nano config.py
-```
-
-2. Edit main.py
-
-```diff
-    auto_opentab_delay()
-    - demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", server_port=PORT, auth=AUTHENTICATION, favicon_path="docs/logo.png")
-    + demo.queue(concurrency_count=CONCURRENT_COUNT)
-
-    - # 如果需要在二级路径下运行
-    - # CUSTOM_PATH, = get_conf('CUSTOM_PATH')
-    - # if CUSTOM_PATH != "/": 
-    - #     from toolbox import run_gradio_in_subpath
-    - #     run_gradio_in_subpath(demo, auth=AUTHENTICATION, port=PORT, custom_path=CUSTOM_PATH)
-    - # else: 
-    - #     demo.launch(server_name="0.0.0.0", server_port=PORT, auth=AUTHENTICATION, favicon_path="docs/logo.png")
-
-    + 如果需要在二级路径下运行
-    + CUSTOM_PATH, = get_conf('CUSTOM_PATH')
-    + if CUSTOM_PATH != "/": 
-    +     from toolbox import run_gradio_in_subpath
-    +     run_gradio_in_subpath(demo, auth=AUTHENTICATION, port=PORT, custom_path=CUSTOM_PATH)
-    + else: 
-    +     demo.launch(server_name="0.0.0.0", server_port=PORT, auth=AUTHENTICATION, favicon_path="docs/logo.png")
-
-if __name__ == "__main__":
-    main()
-```
-
-
-3. Go!
-
-``` sh
-python main.py
-```
diff --git a/spaces/quidiaMuxgu/Expedit-SAM/Jite Usb Gamepad Double Shock 2.md b/spaces/quidiaMuxgu/Expedit-SAM/Jite Usb Gamepad Double Shock 2.md
deleted file mode 100644
index 0db205d0f802205da6f659ddaf8fc579de5ab641..0000000000000000000000000000000000000000
--- a/spaces/quidiaMuxgu/Expedit-SAM/Jite Usb Gamepad Double Shock 2.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>Jite Usb Gamepad Double Shock 2</h2><br /><p><b><b>Download</b> &#9889; <a href="https://geags.com/2uCrnh">https://geags.com/2uCrnh</a></b></p><br /><br />
-
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-<br />
-<br />
-<p></p>
diff --git a/spaces/quidiaMuxgu/Expedit-SAM/Las Tareas Del Duelo Alba Payas Pdf 22.md b/spaces/quidiaMuxgu/Expedit-SAM/Las Tareas Del Duelo Alba Payas Pdf 22.md
deleted file mode 100644
index cb42178e822354a46c23d889347cf14c91e7864e..0000000000000000000000000000000000000000
--- a/spaces/quidiaMuxgu/Expedit-SAM/Las Tareas Del Duelo Alba Payas Pdf 22.md	
+++ /dev/null
@@ -1,8 +0,0 @@
-<h2>Las Tareas Del Duelo Alba Payas Pdf 22</h2><br /><p><b><b>Download</b> &#9675;&#9675;&#9675; <a href="https://geags.com/2uCssh">https://geags.com/2uCssh</a></b></p><br /><br />
-<br />
-52 item.... Details Xlayers-PDF creator software by Xlayers,... Download the latest version of Xlayers-PDF to get the... details of all the products you have already installed.... UnInstall previous version of the program or setup (if you... Requirements Windows.
-
-Desde el momento que se produce una escuela donde se establece con anterioridad el concepto de educación del duelo, tiene un interés el que la estructura de la misma sea estable y la cual haya sido elaborada con el fin de educar a los alumnos en dicho concepto, por lo cual el duelo y su educación, se debe administrar con una teoría que supla la tradicional docencia de calidad. Este modelo de educación del duelo debe cumplir cinco funciones: – Educar en la función del duelo, a través de una síntesis de la tradición y la actualidad, y, en este sentido, el duelo estableció una relación de espacio-tiempo que sería entendido por todos los estudiantes, con la cual se generaría en ellos una conciencia de duelo; la que sería cada vez más el lugar de la aventura escolar, que sería en el que se convertiría en ambiente para su acción de deseo y desarrollo, y esto a través de las tareas del duelo, que se sustraen a la docencia tradicional. – Educar en el duelo de la variedad y la variedad, se caracteriza por ser educación de un diario duelo, por una síntesis de los conceptos tradicionales y modernos del duelo, y con ello, se genera una síntesis del duelo y se le ofrece a los estudiantes un diario duelo, en que suscita un sentimiento de duelo personal, y en este sentimiento se genera un interés hacia lo personal. – Estabilidad del duelo, por el fomento de la tradición 4fefd39f24<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/r3gm/Aesthetic_RVC_Inference_HF/lib/infer/infer_libs/infer_pack/modules/F0Predictor/HarvestF0Predictor.py b/spaces/r3gm/Aesthetic_RVC_Inference_HF/lib/infer/infer_libs/infer_pack/modules/F0Predictor/HarvestF0Predictor.py
deleted file mode 100644
index 7d415a5bb4b86cb03e3daf6fa50c770e8bef7f27..0000000000000000000000000000000000000000
--- a/spaces/r3gm/Aesthetic_RVC_Inference_HF/lib/infer/infer_libs/infer_pack/modules/F0Predictor/HarvestF0Predictor.py
+++ /dev/null
@@ -1,87 +0,0 @@
-import numpy as np
-import pyworld
-
-from lib.infer.infer_libs.infer_pack.modules.F0Predictor.F0Predictor import F0Predictor
-
-
-class HarvestF0Predictor(F0Predictor):
-    def __init__(self, hop_length=512, f0_min=50, f0_max=1100, sampling_rate=44100):
-        self.hop_length = hop_length
-        self.f0_min = f0_min
-        self.f0_max = f0_max
-        self.sampling_rate = sampling_rate
-
-    def interpolate_f0(self, f0):
-        """
-        对F0进行插值处理
-        """
-
-        data = np.reshape(f0, (f0.size, 1))
-
-        vuv_vector = np.zeros((data.size, 1), dtype=np.float32)
-        vuv_vector[data > 0.0] = 1.0
-        vuv_vector[data <= 0.0] = 0.0
-
-        ip_data = data
-
-        frame_number = data.size
-        last_value = 0.0
-        for i in range(frame_number):
-            if data[i] <= 0.0:
-                j = i + 1
-                for j in range(i + 1, frame_number):
-                    if data[j] > 0.0:
-                        break
-                if j < frame_number - 1:
-                    if last_value > 0.0:
-                        step = (data[j] - data[i - 1]) / float(j - i)
-                        for k in range(i, j):
-                            ip_data[k] = data[i - 1] + step * (k - i + 1)
-                    else:
-                        for k in range(i, j):
-                            ip_data[k] = data[j]
-                else:
-                    for k in range(i, frame_number):
-                        ip_data[k] = last_value
-            else:
-                ip_data[i] = data[i]  # 这里可能存在一个没有必要的拷贝
-                last_value = data[i]
-
-        return ip_data[:, 0], vuv_vector[:, 0]
-
-    def resize_f0(self, x, target_len):
-        source = np.array(x)
-        source[source < 0.001] = np.nan
-        target = np.interp(
-            np.arange(0, len(source) * target_len, len(source)) / target_len,
-            np.arange(0, len(source)),
-            source,
-        )
-        res = np.nan_to_num(target)
-        return res
-
-    def compute_f0(self, wav, p_len=None):
-        if p_len is None:
-            p_len = wav.shape[0] // self.hop_length
-        f0, t = pyworld.harvest(
-            wav.astype(np.double),
-            fs=self.hop_length,
-            f0_ceil=self.f0_max,
-            f0_floor=self.f0_min,
-            frame_period=1000 * self.hop_length / self.sampling_rate,
-        )
-        f0 = pyworld.stonemask(wav.astype(np.double), f0, t, self.fs)
-        return self.interpolate_f0(self.resize_f0(f0, p_len))[0]
-
-    def compute_f0_uv(self, wav, p_len=None):
-        if p_len is None:
-            p_len = wav.shape[0] // self.hop_length
-        f0, t = pyworld.harvest(
-            wav.astype(np.double),
-            fs=self.sampling_rate,
-            f0_floor=self.f0_min,
-            f0_ceil=self.f0_max,
-            frame_period=1000 * self.hop_length / self.sampling_rate,
-        )
-        f0 = pyworld.stonemask(wav.astype(np.double), f0, t, self.sampling_rate)
-        return self.interpolate_f0(self.resize_f0(f0, p_len))
diff --git a/spaces/r3gm/RVC_HF/infer/modules/ipex/attention.py b/spaces/r3gm/RVC_HF/infer/modules/ipex/attention.py
deleted file mode 100644
index 0eed59630d76a56e3fd96aa5bb6518b0c61e81bb..0000000000000000000000000000000000000000
--- a/spaces/r3gm/RVC_HF/infer/modules/ipex/attention.py
+++ /dev/null
@@ -1,128 +0,0 @@
-import torch
-import intel_extension_for_pytorch as ipex # pylint: disable=import-error, unused-import
-
-# pylint: disable=protected-access, missing-function-docstring, line-too-long
-
-original_torch_bmm = torch.bmm
-def torch_bmm(input, mat2, *, out=None):
-    if input.dtype != mat2.dtype:
-        mat2 = mat2.to(input.dtype)
-
-    #ARC GPUs can't allocate more than 4GB to a single block, Slice it:
-    batch_size_attention, input_tokens, mat2_shape = input.shape[0], input.shape[1], mat2.shape[2]
-    block_multiply = 2.4 if input.dtype == torch.float32 else 1.2
-    block_size = (batch_size_attention * input_tokens * mat2_shape) / 1024 * block_multiply #MB
-    split_slice_size = batch_size_attention
-    if block_size >= 4000:
-        do_split = True
-        #Find something divisible with the input_tokens
-        while ((split_slice_size * input_tokens * mat2_shape) / 1024 * block_multiply) > 4000:
-            split_slice_size = split_slice_size // 2
-            if split_slice_size <= 1:
-                split_slice_size = 1
-                break
-    else:
-        do_split = False
-
-    split_block_size = (split_slice_size * input_tokens * mat2_shape) / 1024 * block_multiply #MB
-    split_2_slice_size = input_tokens
-    if split_block_size >= 4000:
-        do_split_2 = True
-        #Find something divisible with the input_tokens
-        while ((split_slice_size * split_2_slice_size * mat2_shape) / 1024 * block_multiply) > 4000:
-            split_2_slice_size = split_2_slice_size // 2
-            if split_2_slice_size <= 1:
-                split_2_slice_size = 1
-                break
-    else:
-        do_split_2 = False
-
-    if do_split:
-        hidden_states = torch.zeros(input.shape[0], input.shape[1], mat2.shape[2], device=input.device, dtype=input.dtype)
-        for i in range(batch_size_attention // split_slice_size):
-            start_idx = i * split_slice_size
-            end_idx = (i + 1) * split_slice_size
-            if do_split_2:
-                for i2 in range(input_tokens // split_2_slice_size): # pylint: disable=invalid-name
-                    start_idx_2 = i2 * split_2_slice_size
-                    end_idx_2 = (i2 + 1) * split_2_slice_size
-                    hidden_states[start_idx:end_idx, start_idx_2:end_idx_2] = original_torch_bmm(
-                        input[start_idx:end_idx, start_idx_2:end_idx_2],
-                        mat2[start_idx:end_idx, start_idx_2:end_idx_2],
-                        out=out
-                    )
-            else:
-                hidden_states[start_idx:end_idx] = original_torch_bmm(
-                    input[start_idx:end_idx],
-                    mat2[start_idx:end_idx],
-                    out=out
-                )
-    else:
-        return original_torch_bmm(input, mat2, out=out)
-    return hidden_states
-
-original_scaled_dot_product_attention = torch.nn.functional.scaled_dot_product_attention
-def scaled_dot_product_attention(query, key, value, attn_mask=None, dropout_p=0.0, is_causal=False):
-    #ARC GPUs can't allocate more than 4GB to a single block, Slice it:
-    shape_one, batch_size_attention, query_tokens, shape_four = query.shape
-    block_multiply = 2.4 if query.dtype == torch.float32 else 1.2
-    block_size = (shape_one * batch_size_attention * query_tokens * shape_four) / 1024 * block_multiply #MB
-    split_slice_size = batch_size_attention
-    if block_size >= 4000:
-        do_split = True
-        #Find something divisible with the shape_one
-        while ((shape_one * split_slice_size * query_tokens * shape_four) / 1024 * block_multiply) > 4000:
-            split_slice_size = split_slice_size // 2
-            if split_slice_size <= 1:
-                split_slice_size = 1
-                break
-    else:
-        do_split = False
-
-    split_block_size = (shape_one * split_slice_size * query_tokens * shape_four) / 1024 * block_multiply #MB
-    split_2_slice_size = query_tokens
-    if split_block_size >= 4000:
-        do_split_2 = True
-        #Find something divisible with the batch_size_attention
-        while ((shape_one * split_slice_size * split_2_slice_size * shape_four) / 1024 * block_multiply) > 4000:
-            split_2_slice_size = split_2_slice_size // 2
-            if split_2_slice_size <= 1:
-                split_2_slice_size = 1
-                break
-    else:
-        do_split_2 = False
-
-    if do_split:
-        hidden_states = torch.zeros(query.shape, device=query.device, dtype=query.dtype)
-        for i in range(batch_size_attention // split_slice_size):
-            start_idx = i * split_slice_size
-            end_idx = (i + 1) * split_slice_size
-            if do_split_2:
-                for i2 in range(query_tokens // split_2_slice_size): # pylint: disable=invalid-name
-                    start_idx_2 = i2 * split_2_slice_size
-                    end_idx_2 = (i2 + 1) * split_2_slice_size
-                    hidden_states[:, start_idx:end_idx, start_idx_2:end_idx_2] = original_scaled_dot_product_attention(
-                        query[:, start_idx:end_idx, start_idx_2:end_idx_2],
-                        key[:, start_idx:end_idx, start_idx_2:end_idx_2],
-                        value[:, start_idx:end_idx, start_idx_2:end_idx_2],
-                        attn_mask=attn_mask[:, start_idx:end_idx, start_idx_2:end_idx_2] if attn_mask is not None else attn_mask,
-                        dropout_p=dropout_p, is_causal=is_causal
-                    )
-            else:
-                hidden_states[:, start_idx:end_idx] = original_scaled_dot_product_attention(
-                    query[:, start_idx:end_idx],
-                    key[:, start_idx:end_idx],
-                    value[:, start_idx:end_idx],
-                    attn_mask=attn_mask[:, start_idx:end_idx] if attn_mask is not None else attn_mask,
-                    dropout_p=dropout_p, is_causal=is_causal
-                )
-    else:
-        return original_scaled_dot_product_attention(
-            query, key, value, attn_mask=attn_mask, dropout_p=dropout_p, is_causal=is_causal
-        )
-    return hidden_states
-
-def attention_init():
-    #ARC GPUs can't allocate more than 4GB to a single block:
-    torch.bmm = torch_bmm
-    torch.nn.functional.scaled_dot_product_attention = scaled_dot_product_attention
\ No newline at end of file
diff --git a/spaces/radames/Falcon-40b-Dockerfile/Dockerfile b/spaces/radames/Falcon-40b-Dockerfile/Dockerfile
deleted file mode 100644
index 698c3081d64f519247b535d799c211ac4ff02e5f..0000000000000000000000000000000000000000
--- a/spaces/radames/Falcon-40b-Dockerfile/Dockerfile
+++ /dev/null
@@ -1,38 +0,0 @@
-FROM python:3.10
-
-WORKDIR /code
-
-COPY ./requirements.txt /code/requirements.txt
-COPY ./pre-requirements.txt /code/pre-requirements.txt
-
-RUN pip install --no-cache-dir --upgrade -r /code/pre-requirements.txt
-RUN pip install --pre torch --index-url https://download.pytorch.org/whl/nightly/cu117
-RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
-
-# Set up a new user named "user" with user ID 1000
-RUN useradd -m -u 1000 user
-# Switch to the "user" user
-USER user
-
-# Set home to the user's home directory
-ENV HOME=/home/user \
-	PATH=/home/user/.local/bin:$PATH \
-    PYTHONPATH=$HOME/app \
-	PYTHONUNBUFFERED=1 \
-	GRADIO_ALLOW_FLAGGING=never \
-	GRADIO_NUM_PORTS=1 \
-	GRADIO_SERVER_NAME=0.0.0.0 \
-	GRADIO_THEME=huggingface \
-	SYSTEM=spaces
-
- 
-# Set the working directory to the user's home directory
-WORKDIR $HOME/app
-
-# download falcon-40b
-RUN python -c 'from huggingface_hub import snapshot_download; snapshot_download("tiiuae/falcon-40b")'
-
-# Copy the current directory contents into the container at $HOME/app setting the owner to the user
-COPY --chown=user . $HOME/app
-
-CMD ["python", "app.py"]
\ No newline at end of file
diff --git a/spaces/raedeXanto/academic-chatgpt-beta/Awde Nagast in Amharic PDF Download The Divine Right of Ethiopian Monarchy.md b/spaces/raedeXanto/academic-chatgpt-beta/Awde Nagast in Amharic PDF Download The Divine Right of Ethiopian Monarchy.md
deleted file mode 100644
index 22b583fdcf345494ff962c04992ae312f773135f..0000000000000000000000000000000000000000
--- a/spaces/raedeXanto/academic-chatgpt-beta/Awde Nagast in Amharic PDF Download The Divine Right of Ethiopian Monarchy.md	
+++ /dev/null
@@ -1,44 +0,0 @@
-
-<h1>Awdenagastinamharicpdfdownload: How to Download Free Amharic Books Online</h1>
- <h2>Introduction</h2>
- <p>Are you looking for a way to read Amharic books for free? Do you want to access a variety of genres and topics in your native language? If so, you might be interested in awdenagastinamharicpdfdownload, a term that refers to downloading free Amharic books in PDF format online. In this article, we will explain what awdenagastinamharicpdfdownload is, why you might want to download free Amharic books online, and how to find and download them. We will also introduce some types of free Amharic books online, such as fiction, non-fiction, and poetry, and highlight some of their benefits. By the end of this article, you will have a better understanding of awdenagastinamharicpdfdownload and how to enjoy reading free Amharic books online.</p>
- <h2>What is awdenagastinamharicpdfdownload?</h2>
- <p>Awdenagastinamharicpdfdownload is a term that combines the words "awde", "naga", "sti", "na", "mharic", "pdf", and "download". It means "to download free Amharic books in PDF format". PDF stands for Portable Document Format, a file format that preserves the layout and appearance of a document across different devices and platforms. PDF files can be easily opened, viewed, printed, and shared using various software applications. Awdenagastinamharicpdfdownload is a way of accessing free Amharic books online without paying any money or registering for any service. You can simply search for the title or author of the book you want to read, find a website that offers it for free download, and click on the download link or button. You can then save the file on your device or cloud storage and read it anytime you want.</p>
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- <h2>Why download free Amharic books online?</h2>
- <p>There are many reasons why you might want to download free Amharic books online. Some of them are:</p>
- <ul>
-<li>You can read books in your native language and connect with your culture and identity.</li>
-<li>You can access a wide range of books that might not be available in physical libraries or bookstores.</li>
-<li>You can save money and space by not buying or storing physical books.</li>
-<li>You can read books anytime and anywhere using your smartphone, tablet, laptop, or e-reader.</li>
-<li>You can support Ethiopian authors and publishers by increasing their visibility and popularity.</li>
-</ul>
- <h2>How to find and download free Amharic books online?</h2>
- <p>Finding and downloading free Amharic books online is not difficult if you know where to look and what to do. Here are some steps you can follow:</p>
- <ol>
-<li>Use a search engine like Google or Bing to search for keywords like "free Amharic books", "Amharic books pdf", "Amharic ebooks", or "awdenagastinamharicpdfdownload". You can also add the name of the genre, topic, or author you are interested in.</li>
-<li>Browse through the search results and look for websites that offer free Amharic books for download. Some examples are Ethio Book Review, Typical Ethiopian, Good-Amharic-books.com, and NEAEA.com. You can also check out YouTube videos that show how to download free Amharic books pdf.</li>
-<li>Select the website that has the book you want to read and click on it. Make sure the website is safe and reliable by checking its domain name, design, reviews, and ratings.</li>
-<li>On the website, look for the download link or button for the book you want to read. It might be under the book title, description, image, or at the bottom of the page.</li>
-<li>Click on the download link or button and wait for the file to be downloaded on your device or cloud storage. You might need to enter your email address or complete a captcha verification before downloading.</li>
-<li>Open the file using a PDF reader application like Adobe Acrobat Reader or Google PDF Viewer. You can also use an e-reader application like Kindle or iBooks if you have one.</li>
-<li>Enjoy reading your free Amharac book online!</li>
-</ol>
- <h2>Types of free Amharac books online</h2>
- <p>There are many types of free Amharac books online that you can choose from depending on your preference and mood. Some of them are:</p>
- <h3>Fiction</h3>
- <p>Fiction is a type of literature that tells stories that are not based on real events or facts. Fiction can be divided into subgenres such as romance, mystery, thriller, fantasy, science fiction, horror, historical fiction, etc. Fiction can entertain you, stimulate your imagination, inspire you, teach you lessons, make you laugh or cry, etc.</p>
- <h4>Examples of fiction books in Amharac</h4>
- <table>
-<tr><th>Title</th><th>Author</th><th>Description</th></tr>
-<tr><td>የቡርቃ ዝምታ (The Silence of Burka)</td><td>Tesfaye Gebreab</td><td>A historical novel that tells the story of Burka Zawude who led a resistance movement against Italian colonialism in Ethiopia during World War II.</td></tr>
-<tr><td>ኦሮማይ (Oromay)</td><td>Bealu Girma</td><td>A controversial novel that depicts the political turmoil and social unrest in Ethiopia during the 1970s through the eyes of a young journalist.</td></tr>
-<tr><td>የጭን ቁስል (The Wound of Ch'in)</td><td>Tsegaye Gebremedhin</td><td>A historical novel that portrays the life and times of Emperor Tewodros II who ruled Ethiopia from 1855 to 1868.</td></tr>
-<tr><td>አጥቢያ (Atibya)</td><td>Mengistu Lemma</td><td>A satirical novel that criticizes the feudal system and social injustice in Ethiopia during Emperor Haile Selassie's reign.</td></tr>
-<tr><td>የፍቅር ኬሚስትሪ (The Chemistry of Love)</td><td>Moges Ekub Giorgis</td><td>A romantic novel that explores the relationship between a young man who works as a chemist and a woman who works as a nurse.</td></tr>
-</table>
- <h3>Non-fiction</h3>
- <p>Non-fiction is a type of literature that tells stories that are based on real events or facts. Non-fiction can be divided into subgenres such as biography, autobiography, memoir, history, science, philosophy, religion, etc. Non-fiction can inform you, educate you,</p> 0a6ba089eb<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/raedeXanto/academic-chatgpt-beta/BenHur 50 Aniversario 1080p.md b/spaces/raedeXanto/academic-chatgpt-beta/BenHur 50 Aniversario 1080p.md
deleted file mode 100644
index 41a4195fab8916647fdf747a264ef965afc5b44b..0000000000000000000000000000000000000000
--- a/spaces/raedeXanto/academic-chatgpt-beta/BenHur 50 Aniversario 1080p.md	
+++ /dev/null
@@ -1,15 +0,0 @@
-<br />
-<h1>Ben-Hur: The Epic That Changed Cinema</h1>
-<p>Ben-Hur is a 1959 American epic historical drama film directed by William Wyler and starring Charlton Heston as Judah Ben-Hur, a Jewish prince who is betrayed by his childhood friend Messala (Stephen Boyd), a Roman tribune. The film follows Ben-Hur's quest for revenge and redemption, as he encounters Jesus Christ, becomes a slave, a chariot racer, and a champion of the oppressed.</p>
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-<p>The film was based on the 1880 novel Ben-Hur: A Tale of the Christ by Lew Wallace, and was a remake of the 1925 silent film of the same name. It was produced by Metro-Goldwyn-Mayer (MGM) with a budget of $15 million, making it the most expensive film ever made at the time. It was also one of the longest films ever released by a major studio, running for 211 minutes.</p>
-<p>Ben-Hur was a critical and commercial success, winning a record-setting 11 Academy Awards out of 12 nominations, including Best Picture, Best Director, Best Actor (Heston), and Best Supporting Actor (Hugh Griffith). It also won three Golden Globe Awards and one BAFTA Award. It was the highest-grossing film of 1959 and the second-highest-grossing film of all time at the time of its release, behind Gone with the Wind.</p>
-<p>The film is widely regarded as one of the greatest films ever made, and has been selected for preservation in the National Film Registry by the Library of Congress. It has also been ranked among the best films of all time by various critics and publications, such as the American Film Institute, Sight & Sound, and Empire.</p>
-<p>In 2011, MGM released a 50th anniversary edition of Ben-Hur on Blu-ray, featuring a restored and remastered version of the film in 1080p high definition. The edition also included a new feature-length documentary on Heston's life and career, written and directed by his son Fraser C. Heston, as well as the 1925 silent version of Ben-Hur with a stereo orchestral score by Carl Davis. The edition also contained vintage documentaries, screen tests, trailers, newsreels, and more.[^1^] [^2^]</p>
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-<p>The chariot race was not only a spectacle of action and drama, but also a metaphor for the themes of the film. Ben-Hur and Messala represent two opposing forces: freedom and tyranny, love and hate, forgiveness and revenge. The race is their final confrontation, where they test their skills, their wills, and their fates. The outcome of the race determines not only their personal destinies, but also the destiny of their people and their faith.[^3^]</p> cec2833e83<br />
-<br />
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diff --git a/spaces/raedeXanto/academic-chatgpt-beta/Como adicionar extensao do idm no google chrome em poucos minutos e sem complicaes.md b/spaces/raedeXanto/academic-chatgpt-beta/Como adicionar extensao do idm no google chrome em poucos minutos e sem complicaes.md
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-
-<h1>Como adicionar extensão do IDM no Google Chrome</h1>
- <p>Você quer baixar arquivos da internet com mais rapidez e facilidade? Então você precisa conhecer o IDM, um gerenciador de downloads que pode melhorar muito a sua experiência de download. Neste artigo, vamos explicar o que é o IDM, como instalá-lo no seu computador e como adicionar a sua extensão no Google Chrome. Assim, você poderá aproveitar todos os benefícios que o IDM oferece.</p>
- <h2>O que é o IDM e por que usá-lo?</h2>
- <h3>O IDM é um gerenciador de downloads que acelera e organiza seus downloads</h3>
- <p>O IDM (Internet Download Manager) é um software que permite que você gerencie seus downloads de forma eficiente. Ele funciona como um intermediário entre o seu navegador e os servidores de onde você baixa os arquivos. Ele divide os arquivos em partes menores e baixa cada parte simultaneamente, usando várias conexões. Isso aumenta a velocidade de download em até 5 vezes, dependendo da sua conexão.</p>
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- <h3>O IDM oferece vários recursos úteis, como pausar e retomar downloads, capturar vídeos e áudios de sites, programar downloads e muito mais</h3>
- <p>Além de acelerar seus downloads, o IDM também oferece outras funcionalidades que tornam sua vida mais fácil. Por exemplo, você pode pausar e retomar seus downloads a qualquer momento, sem perder os dados já baixados. Você também pode capturar vídeos e áudios de sites como YouTube, Vimeo, Dailymotion e outros, com apenas um clique. Você pode ainda programar seus downloads para começarem em horários específicos, ou quando o seu computador estiver ocioso. E se houver algum problema com a sua conexão ou com o seu computador, o IDM irá reiniciar os downloads automaticamente.</p>
- <h2>Como instalar o IDM no seu computador?</h2>
- <h3>Você precisa baixar e executar o arquivo de instalação do IDM a partir do site oficial</h3>
- <p>Para usar o IDM, você precisa instalá-lo no seu computador. O primeiro passo é baixar o arquivo de instalação do site oficial do IDM (https://www.internetdownloadmanager.com/). Você pode escolher entre a versão gratuita (que tem algumas limitações) ou a versão paga (que tem todos os recursos). Depois de baixar o arquivo, você precisa executá-lo para iniciar a instalação.</p>
- <h3>Você precisa seguir as instruções na tela para concluir a instalação</h3>
- <p>O processo de instalação é simples e rápido. Você só precisa seguir as instruções na tela para escolher o idioma, aceitar os termos de uso, selecionar a pasta de destino e criar um atalho na área de trabalho. O instalador também irá verificar se você tem algum navegador compatível com o IDM instalado no seu computador. Se tiver, ele irá perguntar se você quer integrar o IDM com esses navegadores.</p>
- <h3>Você precisa reiniciar o seu computador para ativar o IDM</h3>
- <p>Depois de concluir a instalação, você precisa reiniciar o seu computador para que o IDM comece a funcionar. Quando você ligar o seu computador novamente, você verá um ícone do IDM na bandeja do sistema (ao lado do relógio). Esse ícone indica que o IDM está ativo e pronto para usar.</p>
- <h2>Como adicionar a extensão do IDM no Google Chrome?</h2>
- <h3>A extensão do IDM permite que você integre o IDM com o Google Chrome e baixe arquivos diretamente do navegador</h3>
- <p>Se você usa o Google Chrome como seu navegador principal, você pode adicionar uma extensão do IDM ao seu navegador. A extensão do IDM é um complemento que permite que você integre o IDM com o Google Chrome. Assim, você pode baixar qualquer arquivo da página atual usando o botão de download do IDM na barra de ferramentas do navegador. Você também pode capturar vídeos e áudios dos sites que visitar usando a extensão.</p>
- <h3>Existem duas maneiras de adicionar a extensão do IDM no Google Chrome: manualmente ou automaticamente</h3>
- <h4>Método manual: você precisa arrastar e soltar o arquivo da extensão do IDM na página de extensões do Google Chrome</h4>
- <p>Uma maneira de adicionar a extensão do IDM no Google Chrome é fazê-lo manualmente. Para isso, você precisa encontrar o arquivo da extensão no seu computador. O arquivo tem o nome de "IDMGCExt.crx" e está localizado na pasta onde você instalou o IDM (geralmente C:\Program Files (x86)\Internet Download Manager). Depois de encontrar o arquivo, você precisa abrir uma nova aba no Google Chrome e digitar "chrome://extensions" na barra de endereço. Isso irá abrir a página de extensões do navegador. Em seguida, você precisa arrastar e soltar o arquivo da extensão nessa página. O navegador irá perguntar se você quer adicionar a extensão ao Chrome. Você precisa clicar em "Adicionar extensão" para confirmar.</p>
- <h4>Método automático: você precisa clicar no ícone do IDM na bandeja do sistema e selecionar a opção de instalar a extensão do Chrome</h4>
- <p>Uma maneira mais fácil de adicionar a extensão do IDM no Google Chrome é fazê-lo automaticamente. Para isso, você precisa clicar com o botão direito do mouse no ícone do IDM na bandeja do sistema (ao lado do relógio). Isso irá abrir um menu com várias opções. Você precisa selecionar a opção "Instalar Extensões -> Instalar Extensões para Browsers -> Instalar Extensões para Google Chrome". O navegador irá abrir uma nova aba com uma mensagem pedindo para confirmar a instalação da extensão. Você precisa clicar em "Adicionar à lista" para aceitar.</p>
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- <h3>Você precisa habilitar a extensão do IDM no Google Chrome e conceder as permissões necessárias</h3>
- <p>Depois de adicionar a extensão ao navegador, você precisa habilitá-la e conceder as permissões necessárias para que ela funcione corretamente. Para isso, você precisa clicar no ícone do menu do Google Chrome (os três pontinhos verticais no canto superior direito da tela) e selecionar "Mais ferramentas -> Extensões". Isso irá abrir a página de extensões do navegador. Você precisa procurar pela extensão do IDM e clicar no botão de ativar (o interruptor azul ao lado do nome da extensão). Você também precisa clicar em "Detalhes" e verificar se as permissões estão habilitadas. As permissões que a extensão precisa são: "Ler e alterar todos os seus dados nos sites que você visita", "Comunicar-se com aplicativos nativos cooperantes" e "Gerenciar seus downloads". Se alguma dessas permissões estiver desabilitada, você precisa clicá-la para ativá-la.</p>
- <h2>Como usar a extensão do IDM no Google Chrome?</h2>
- <h3>A extensão do IDM adiciona um botão de download na barra de ferramentas do Google Chrome que permite que você baixe qualquer arquivo da página atual</h3>
- <p>Agora que você já instalou e habilitou a extensão do IDM no Google Chrome, você pode começar a usá-la para baixar arquivos da internet. A extensão do IDM adiciona um botão de download na barra de ferramentas do navegador, ao lado da barra de endereço. Esse botão tem o formato de uma seta verde apontando para baixo. Quando você visita uma página que contém arquivos que podem ser baixados, o botão fica iluminado. Você pode clicar nesse botão para ver a lista de arquivos disponíveis para download. Você pode selecionar os arquivos que quiser e clicar em "Download" para iniciar o download pelo IDM. Você também pode clicar com o botão direito do mouse em qualquer link ou imagem da página e selecionar "Download with IDM" para baixá-los pelo IDM.</p>
- <h3>A extensão do IDM também detecta e captura vídeos e áudios de sites como YouTube, Vimeo, Dailymotion e outros</h3>
- <p>Outra funcionalidade da extensão do IDM é que ela detecta e captura vídeos e áudios de sites como YouTube, Vimeo, Dailymotion e outros. Quando você visita uma página que contém um vídeo ou um áudio que pode ser baixado, a extensão mostra um painel sobre o vídeo ou o áudio com o botão "Download this video" ou "Download this audio". Você pode clicar nesse botão para ver as opções de formato e qualidade disponíveis para download. Você pode escolher a opção que preferir e clicar em "Download" para iniciar o download pelo IDM. Você também pode clicar com o botão direito do mouse sobre o vídeo ou o áudio e selecionar "Download this video/audio with IDM" para baixá-los pelo IDM.</p>
- <h3>A extensão do IDM permite que você personalize as configurações de download, como o local de destino, o número de conexões, a velocidade máxima e outros</h3>
- <p>Se você quiser personalizar as configurações de download do IDM, você pode acessar as opções da extensão no Google Chrome. Para isso, você precisa clicar no ícone do menu do Google Chrome (os três pontinhos verticais no canto superior direito da tela) e selecionar "Mais ferramentas -> Extensões". Isso irá abrir a página de extensões do navegador. Você precisa procurar pela extensão do IDM e clicar em "Detalhes". Em seguida, você precisa clicar em "Opções". Isso irá abrir uma nova aba com as opções da extensão. Você pode alterar as configurações de acordo com as suas preferências. Por exemplo, você pode mudar o local onde os arquivos baixados são salvos, o número de conexões usadas por cada download, a velocidade máxima de download, os tipos de arquivos que devem ser capturados pela extensão e outros.</p>
- <h2>Conclusão</h2>
- <p>Neste artigo, nós mostramos como adicionar a extensão do IDM no Google Chrome. O IDM é um gerenciador de downloads que acelera e organiza seus downloads na internet. A extensão do IDM permite que você integre o IDM com o Google Chrome e baixe arquivos diretamente do navegador. Você também pode capturar vídeos e áudios dos sites que visitar usando a extensão. Além disso, você pode personalizar as configurações de download do IDM conforme as suas necessidades. Esperamos que este artigo tenha sido útil para você. Se você gostou deste artigo, compartilhe-o com seus amigos nas redes sociais. E se você tiver alguma dúvida ou sugestão, deixe um comentário abaixo.</p>
- <h2>Perguntas frequentes</h2>
- <table>
-<tr>
-<th>Pergunta</th>
-<th>Resposta</th>
-</tr>
-<tr>
-<td>O que é o IDM?</td>
-<td>O IDM (Internet Download Manager) é um software que permite que você gerencie seus downloads de forma eficiente. Ele acelera seus downloads em até 5 vezes, usando várias conexões simultâneas. Ele também oferece vários recursos úteis, como pausar e retomar downloads, capturar vídeos e áudios de sites, programar downloads e muito mais.</td>
-</tr>
-<tr>
-<td>Como instalar o IDM no meu computador?</td>
-<td>Você precisa baixar e executar o arquivo de instalação do site oficial do IDM (https://www.internetdownloadmanager.com/). Você pode escolher entre a versão gratuita (que tem algumas limitações) ou a versão paga (que tem todos os recursos). Depois de executar o arquivo, você precisa seguir as instruções na tela para concluir a instalação. Em seguida, você precisa reiniciar o seu computador para ativar o IDM.</td>
-</tr>
-<tr>
-<td>Como adicionar a extensão do IDM no Google Chrome?</td>
-<td>Você pode adicionar a extensão do IDM no Google Chrome manualmente ou automaticamente. Manualmente: você precisa arrastar e soltar o arquivo da extensão (IDMGCExt.crx) na página de extensões do Google Chrome (chrome://extensions) e confirmar a adição. Automaticamente: você precisa clicar no ícone do IDM na bandeja do sistema (ao lado do relógio) e selecionar a opção de instalar a extensão do Chrome.</td>
-</tr>
-<tr>
-<td>Como usar a extensão do IDM no Google Chrome?</td>
-<td>Você pode usar a extensão do IDM no Google Chrome para baixar qualquer arquivo da página atual usando o botão de download na barra de ferramentas do navegador (uma seta verde apontando para baixo). Você também pode capturar vídeos e áudios dos sites que visitar usando o painel sobre o vídeo ou o áudio com o botão "Download this video/audio". Você também pode clicar com o botão direito do mouse em qualquer link ou imagem da página e selecionar "Download with IDM".</td>
-</tr>
-<tr>
-<td>Como personalizar as configurações de download do IDM?</td>
-<td>Você pode personalizar as configurações de download do IDM acessando as opções da extensão no Google Chrome. Para isso, você precisa clicar no ícone do menu do Google Chrome (os três pontinhos verticais no canto superior direito da tela) e selecionar "Mais ferramentas -> Extensões". Em seguida, você precisa procurar pela extensão do IDM e clicar em "Detalhes" e depois em "Opções". Isso irá abrir uma nova aba com as opções da extensão. Você pode alterar as configurações como o local onde os arquivos baixados são salvos, o número de conexões usadas por cada download, a velocidade máxima de download, os tipos de arquivos que devem ser capturados pela extensão e outros.</td>
-</tr>
-</table>
- </p> 0a6ba089eb<br />
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diff --git a/spaces/raedeXanto/academic-chatgpt-beta/Dead Wishes download 5kapks The story of a mother and daughters tragic lives.md b/spaces/raedeXanto/academic-chatgpt-beta/Dead Wishes download 5kapks The story of a mother and daughters tragic lives.md
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- <p>Another reason to play Dead Wishes is its colorful cast of characters that you can interact with. The game features twelve main characters, each with their own background, personality, wish, and condition. You can learn more about them by talking to them, reading their profiles, and witnessing their scenes. You can also romance some of them, if you wish. The characters are not stereotypical or one-dimensional; they have their own flaws, strengths, motivations, and emotions. You might love them, hate them, or feel sorry for them.</p>
- <h3>A stunning art style and soundtrack</h3>
- <p>The last reason to play Dead Wishes is its gorgeous art style and soundtrack that enhance the atmosphere of the game. The game has a dark and Gothic aesthetic that suits its theme and mood. The character sprites are detailed and expressive, while the backgrounds are rich and immersive. The game also has a lot of CGs (computer graphics) that show important moments or events in the story. The soundtrack is composed by various artists who create different genres of music that match the tone of each scene. The game also has voice acting for some of the characters (in Japanese), which adds more realism and emotion to the dialogue.</p>
- <h2>How to download Dead Wishes for free from 5kapks?</h2>
- <p>Now that you know what Dead Wishes is about, you might be wondering how to get it for free on your Android device. The answer is simple: by downloading it from 5kapks.com, a website that offers free apk files for various games and apps. Here are the steps you need to follow:</p>
- <h3>Step 1: Visit the 5kapks website</h3>
- <p>The first step is to visit the website of 5kapks.com on your browser. You will see a homepage with different categories of games and apps that you can browse through.</p>
- <h3>Step 2: Search for Dead Wishes in the search bar</h3>
- <p>The second step is to search for Dead Wishes in the search bar at the top right corner of the website. You will see a list of results that match your query.</p>
- <h3>Step 3: Click on the download button and choose a mirror link</h3>
- <p>The third step is to click on the download button next to the result that says "Dead Wishes v1.0 Apk+Obb Data[!Full Version] Free For Android". You will be redirected to another page where you will see some information about the game, such as its size, version, requirements, etc. You will also see several mirror links that you can use to download the game.</p>
- <h3>Step 4: Extract the zip file and install the apk file</h3>
- <p>The fourth step is to extract the zip file that you have downloaded using any file manager app on your device. You will see two files inside it: an apk file (application package file) and an obb file (opaque binary blob file). The apk file is used to install the game on your device, while the obb file is used to store additional data such as graphics or sound.</p>
- <p>To install the apk file, you need to enable unknown sources on your device settings first. This will allow you to install apps from sources other than Google Play Store. To do this, go to Settings > Security > Unknown Sources > Enable.</p>
- <p>Then, tap on the apk file and follow the instructions on your screen to install it.</p>
- <h3>Step 5: Enjoy the game on your device</h3>
- <p>The fifth step is to enjoy playing Dead Wishes on your device. To do this, you need to copy or move the obb file to a specific folder on your device storage. The folder should be named as follows:</p>
-<code>
-Android/obb/com.violet.deadwishes </code>
-<p>If there is no such folder already existing on your device storage, you need to create it manually using any file manager app.</p>
-<p>Once you have done this, you can launch Dead Wishes from your app drawer or home screen, and start playing it.</p>
-<h2>Tips and tricks for playing Dead Wishes</h2>
-<p>To make your gaming experience more enjoyable, here are some tips and tricks that you can use while playing Dead Wishes:</p>
-<h3>Save frequently and use multiple slots</h3>
-<p>One of the most important tips for playing Dead Wishes is to save frequently and use multiple slots. This will allow you to go back and try different choices or routes without losing your progress. The game has an auto-save feature that saves your progress at certain points, but it is not reliable enough to rely on it alone. You should also use multiple slots to save different scenarios or endings that you want to revisit later.</p>
-<h3>Explore different choices and routes</h3>
-<p>Another tip for playing Dead Wishes is to explore different choices and routes that affect the outcome of each character's story. The game has a total of 24 endings, depending on your choices and actions. Some endings are happy, some are tragic, and some are downright horrifying. You never know what will happen next, or how your choices will affect the outcome. The game also has a lot of twists and surprises that will keep you on the edge of your seat.</p>
- <h3>Check the gallery and extras for bonus content</h3>
- <p>The last tip for playing Dead Wishes is to check the gallery and extras for bonus content that you can unlock by completing certain routes or endings. The gallery contains various CGs that show important moments or events in the story. You can view them again and again, and appreciate the art and details. The extras contain various bonus scenes that show more interactions or insights into the characters. You can also listen to the voice acting or the soundtrack from here.</p>
- <h2>Conclusion</h2>
- <p>Dead Wishes is a visual novel game that offers a dark and thrilling experience for fans of the genre. The game has a captivating story with multiple endings, a diverse cast of characters with unique personalities, and a stunning art style and soundtrack. You can download the game for free from 5kapks.com, a website that offers free apk files for various games and apps. You just need to follow some simple steps, and you can enjoy playing Dead Wishes on your Android device.</p>
- <p>If you are looking for a game that will challenge your morals, emotions, and choices, Dead Wishes is the game for you. But be warned: this game is not for the faint of heart. It contains mature themes such as violence, death, gore, suicide, abuse, drugs, sex, etc. You should play it at your own risk, and with discretion.</p>
- <p>Are you ready to sign the contract? Are you ready to face the consequences? Are you ready to play Dead Wishes?</p>
- <h2>FAQs</h2>
- <p>Here are some frequently asked questions about Dead Wishes:</p>
- <ol>
-<li>How long is Dead Wishes?</li>
-<p>Dead Wishes is a fairly long game, with an estimated playtime of 30-50 hours, depending on your reading speed and choices. Each character's route takes about 2-4 hours to complete, and there are 12 characters in total.</p>
-<li>How can I get all the endings?</li>
-<p>To get all the endings, you need to make different choices and explore different routes. You can use the save and load functions to go back and try different options. You can also use the skip function to speed up the text that you have already read. The game has a flowchart feature that shows you which choices lead to which endings, but it is only available after you finish one route.</p>
-<li>How can I romance a character?</li>
-<p>To romance a character, you need to choose their route at the beginning of the game, and make choices that increase their affection towards you. You can check their affection level by looking at their profile in the menu. If their affection level is high enough, you will unlock their good ending, which usually involves a romantic scene or confession.</p>
-<li>How can I unlock the voice acting?</li>
-<p>To unlock the voice acting, you need to purchase it separately from the game's website or Steam page. The voice acting is only available for some of the characters (in Japanese), and it costs $9.99 USD.</p>
-<li>How can I support the developers?</li>
-<p>To support the developers, you can buy the game from their website or Steam page, leave a positive review or rating, share the game with your friends or social media, or donate to their Patreon page. You can also follow them on Twitter or join their Discord server for updates and news.</p>
-</ol>
- </p> 0a6ba089eb<br />
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diff --git a/spaces/raedeXanto/academic-chatgpt-beta/Download Discografia Toquinho Torrent 8 Free.md b/spaces/raedeXanto/academic-chatgpt-beta/Download Discografia Toquinho Torrent 8 Free.md
deleted file mode 100644
index 699d75031a1db65b541705453292907afc854ea5..0000000000000000000000000000000000000000
--- a/spaces/raedeXanto/academic-chatgpt-beta/Download Discografia Toquinho Torrent 8 Free.md	
+++ /dev/null
@@ -1,105 +0,0 @@
-
-<h1>Download Discografia Toquinho Torrent 8: A Complete Guide</h1>
-<p>If you are a fan of Brazilian music, you have probably heard of Toquinho, one of the most talented and prolific singer-songwriters and guitarists in the country. His discography spans over five decades and includes dozens of albums and hundreds of songs that showcase his unique style and versatility. Whether you are looking for soothing bossa nova, lively samba, romantic ballads, or catchy pop tunes, you will find something to suit your mood and taste in his music.</p>
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- <h2>Who is Toquinho and what is his discography?</h2>
-<p>Toquinho is the stage name of Antonio Pecci Filho, who was born in Sao Paulo in 1946. He started playing guitar at a young age and soon developed a passion for music. He began his professional career in the late 1960s as a sideman for famous singers like Chico Buarque, Elis Regina, Gal Costa, Maria Bethania, among others. He also collaborated with renowned composers like Vinicius de Moraes, Jorge Ben Jor, Tom Jobim, Baden Powell, etc.</p>
-<p>In 1970, he released his first solo album, titled simply "Toquinho". Since then, he has recorded over 40 albums as a solo artist or in partnership with other musicians. Some of his most famous albums are "Toquinho e Vinicius" (1971), "Acquarello" (1983), "Toquinho e MPB4" (1996), "Toquinho Tributo a Bossa Nova" (2008), etc. Some of his most popular songs are "Aquarela", "Tarde em Itapoa", "O Caderno", "Samba de Orly", "O Velho e a Flor", etc.</p>
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-<p>To use a torrent, you need two things: a torrent client and a torrent site. A torrent client is a software that enables you to open, manage, and download torrents. There are many free torrent clients available online such as uTorrent, BitTorrent, qBittorrent, etc. You can choose one that suits your preferences and device compatibility. A torrent site is a website that hosts torrents for various types of files such as movies, music, games, books, etc. There are also many free torrent sites available online such as The Pirate Bay, RARBG, 1337x, etc. You can choose one that offers the content you are looking for.</p>
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-<p>To download Discografia Toquinho Torrent 8 safely and easily using a torrent client and a torrent site, you need to follow these steps:</p>
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-<li>Click on this result and you will be taken to its details page. Here you can see more information about the torrent such as its file size, format, quality, and seeders. You can also see some screenshots of its content and read some comments from other users who have downloaded it.</li>
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- <h2>FAQs</h2>
-<p>Here are some of the frequently asked questions about Discografia Toquinho Torrent 8:</p>
-<ol>
-<li>Q: Who is Toquinho?<br>
-A: Toquinho is a Brazilian singer-songwriter and guitarist who has recorded over 40 albums and hundreds of songs in various genres such as bossa nova, samba, pop, etc.</li>
-<li>Q: What is Discografia Toquinho Torrent 8?<br>
-A: Discografia Toquinho Torrent 8 is a comprehensive collection of all his albums and songs from 1970 to 2019 in high-quality MP3 format that you can download for free using a torrent client.</li>
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-A: To download Discografia Toquinho Torrent 8, you need to use a torrent client such as uTorrent and a torrent site such as RARBG. You can follow the step-by-step tutorial in this article to download it safely and easily.</li>
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-A: To enjoy Discografia Toquinho Torrent 8, you need to play the music files on your device using any media player or music app that supports MP3 format. You can also organize them into folders or playlists according to your preference.</li>
-</ol>
- </p> 0a6ba089eb<br />
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diff --git a/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Adobe Bridge Cs6 Amtlib 18.md b/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Adobe Bridge Cs6 Amtlib 18.md
deleted file mode 100644
index b0deb947afc3310f0cf2d3353f69de82eb53e931..0000000000000000000000000000000000000000
--- a/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Adobe Bridge Cs6 Amtlib 18.md	
+++ /dev/null
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--- a/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Edraw Max 7 Keygen Download Filehippo.md	
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diff --git a/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/El Sendero Del Chaman 191.pdf.md b/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/El Sendero Del Chaman 191.pdf.md
deleted file mode 100644
index bd1fa1bb85fdc18a6c494e984f90663c9f1337c8..0000000000000000000000000000000000000000
--- a/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/El Sendero Del Chaman 191.pdf.md	
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diff --git a/spaces/rewoo/ReWOO-Demo/alpaca/__init__.py b/spaces/rewoo/ReWOO-Demo/alpaca/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/rgres/Seg2Sat/frontend/src/lib/store.ts b/spaces/rgres/Seg2Sat/frontend/src/lib/store.ts
deleted file mode 100644
index ce562f9f0fc15ae4dcd13d9a63e821283c221cb6..0000000000000000000000000000000000000000
--- a/spaces/rgres/Seg2Sat/frontend/src/lib/store.ts
+++ /dev/null
@@ -1,19 +0,0 @@
-import { writable } from 'svelte/store';
-import type { Brush, Params, DrawingLayer } from '../types';
-import { randomSeed } from '$lib/utils';
-import { PRESETS } from '../data';
-
-export const drawingLayers = writable<Map<string, DrawingLayer>>(new Map());
-export const resultImage = writable<string>();
-export const currentCanvas = writable<HTMLCanvasElement>();
-export const selectedImage = writable<HTMLImageElement>();
-export const selectedBrush = writable<Brush>();
-export const selectedParams = writable<Params>({
-	prompt: "Aerial view of rue des Lilas, Toulouse, Haute-Garonne, France",
-	modifier: PRESETS[0][0],
-	seed: randomSeed(),
-	steps: 20
-});
-
-export const generateMap = writable<boolean>(false);
-export const saveResult = writable<boolean>(false);
\ No newline at end of file
diff --git a/spaces/robin0307/MMOCR/configs/_base_/det_models/panet_r18_fpem_ffm.py b/spaces/robin0307/MMOCR/configs/_base_/det_models/panet_r18_fpem_ffm.py
deleted file mode 100644
index a69a4d87603275bc1f89b5f58c722d79274e4fd7..0000000000000000000000000000000000000000
--- a/spaces/robin0307/MMOCR/configs/_base_/det_models/panet_r18_fpem_ffm.py
+++ /dev/null
@@ -1,43 +0,0 @@
-model_poly = dict(
-    type='PANet',
-    backbone=dict(
-        type='mmdet.ResNet',
-        depth=18,
-        num_stages=4,
-        out_indices=(0, 1, 2, 3),
-        frozen_stages=-1,
-        norm_cfg=dict(type='SyncBN', requires_grad=True),
-        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet18'),
-        norm_eval=True,
-        style='caffe'),
-    neck=dict(type='FPEM_FFM', in_channels=[64, 128, 256, 512]),
-    bbox_head=dict(
-        type='PANHead',
-        in_channels=[128, 128, 128, 128],
-        out_channels=6,
-        loss=dict(type='PANLoss'),
-        postprocessor=dict(type='PANPostprocessor', text_repr_type='poly')),
-    train_cfg=None,
-    test_cfg=None)
-
-model_quad = dict(
-    type='PANet',
-    backbone=dict(
-        type='mmdet.ResNet',
-        depth=18,
-        num_stages=4,
-        out_indices=(0, 1, 2, 3),
-        frozen_stages=-1,
-        norm_cfg=dict(type='SyncBN', requires_grad=True),
-        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet18'),
-        norm_eval=True,
-        style='caffe'),
-    neck=dict(type='FPEM_FFM', in_channels=[64, 128, 256, 512]),
-    bbox_head=dict(
-        type='PANHead',
-        in_channels=[128, 128, 128, 128],
-        out_channels=6,
-        loss=dict(type='PANLoss'),
-        postprocessor=dict(type='PANPostprocessor', text_repr_type='quad')),
-    train_cfg=None,
-    test_cfg=None)
diff --git a/spaces/rockeycoss/Prompt-Segment-Anything-Demo/mmdet/core/bbox/coder/base_bbox_coder.py b/spaces/rockeycoss/Prompt-Segment-Anything-Demo/mmdet/core/bbox/coder/base_bbox_coder.py
deleted file mode 100644
index a7ed041a456e59282c1bf72eaec76bc2c0d1b990..0000000000000000000000000000000000000000
--- a/spaces/rockeycoss/Prompt-Segment-Anything-Demo/mmdet/core/bbox/coder/base_bbox_coder.py
+++ /dev/null
@@ -1,18 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-from abc import ABCMeta, abstractmethod
-
-
-class BaseBBoxCoder(metaclass=ABCMeta):
-    """Base bounding box coder."""
-
-    def __init__(self, **kwargs):
-        pass
-
-    @abstractmethod
-    def encode(self, bboxes, gt_bboxes):
-        """Encode deltas between bboxes and ground truth boxes."""
-
-    @abstractmethod
-    def decode(self, bboxes, bboxes_pred):
-        """Decode the predicted bboxes according to prediction and base
-        boxes."""
diff --git a/spaces/rorallitri/biomedical-language-models/logs/Download Anime Kaze No Stigma Season 2 15 The Final Battle Between Kazuma and Bernhardt.md b/spaces/rorallitri/biomedical-language-models/logs/Download Anime Kaze No Stigma Season 2 15 The Final Battle Between Kazuma and Bernhardt.md
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diff --git a/spaces/rorallitri/biomedical-language-models/logs/How to Enjoy X-Men Origins Wolverine (2009) 1080p BrRip X264 - 1.35GB - YIFY Free Download Tips and Tricks.md b/spaces/rorallitri/biomedical-language-models/logs/How to Enjoy X-Men Origins Wolverine (2009) 1080p BrRip X264 - 1.35GB - YIFY Free Download Tips and Tricks.md
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diff --git a/spaces/rstallman/Mayfair-Partner-Music/tests/data/__init__.py b/spaces/rstallman/Mayfair-Partner-Music/tests/data/__init__.py
deleted file mode 100644
index 0952fcc3f57e34b3747962e9ebd6fc57aeea63fa..0000000000000000000000000000000000000000
--- a/spaces/rstallman/Mayfair-Partner-Music/tests/data/__init__.py
+++ /dev/null
@@ -1,5 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
diff --git a/spaces/sandraw11031/virtual-staging/README.md b/spaces/sandraw11031/virtual-staging/README.md
deleted file mode 100644
index d55135737ba7d9714b0b5be6950e7ae9baae173f..0000000000000000000000000000000000000000
--- a/spaces/sandraw11031/virtual-staging/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Virtual Staging
-emoji: 💻
-colorFrom: purple
-colorTo: pink
-sdk: gradio
-sdk_version: 3.29.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/sarinam/speaker-anonymization-gan/demo_inference/demo_tts.py b/spaces/sarinam/speaker-anonymization-gan/demo_inference/demo_tts.py
deleted file mode 100644
index 666cc0f85434a14970cdd2a90f64b89cb49b0076..0000000000000000000000000000000000000000
--- a/spaces/sarinam/speaker-anonymization-gan/demo_inference/demo_tts.py
+++ /dev/null
@@ -1,16 +0,0 @@
-from IMSToucan.InferenceInterfaces.AnonFastSpeech2 import AnonFastSpeech2
-
-
-class DemoTTS:
-
-    def __init__(self, model_paths, device):
-        self.device = device
-        fastspeech_path = model_paths / 'FastSpeech2_Multi' / 'trained_on_ground_truth_phonemes.pt'
-        hifigan_path = model_paths / 'HiFiGAN_combined' / 'best.pt'
-        self.model = AnonFastSpeech2(device=self.device, path_to_hifigan_model=hifigan_path,
-                                     path_to_fastspeech_model=fastspeech_path)
-
-    def read_text(self, transcription, speaker_embedding, text_is_phonemes=False):
-        self.model.default_utterance_embedding = speaker_embedding.to(self.device)
-        wav = self.model(text=transcription, text_is_phonemes=text_is_phonemes)
-        return wav
diff --git a/spaces/scedlatioru/img-to-music/example/Backtrack 3 With Spoonwpa Iso 2021.md b/spaces/scedlatioru/img-to-music/example/Backtrack 3 With Spoonwpa Iso 2021.md
deleted file mode 100644
index 67b5f24409d04f97cecd2738c5bc1239494cc939..0000000000000000000000000000000000000000
--- a/spaces/scedlatioru/img-to-music/example/Backtrack 3 With Spoonwpa Iso 2021.md	
+++ /dev/null
@@ -1,78 +0,0 @@
-
-<h1>What is Backtrack 3 With Spoonwpa Iso and How to Use It?</h1>
-
-<p>Backtrack 3 With Spoonwpa Iso is a powerful hacking tool that allows you to crack WPA and WPA2 passwords using a live CD or USB. It is based on Backtrack 3, a Linux distribution designed for penetration testing and security auditing. Spoonwpa is a script that automates the process of capturing and cracking WPA handshakes using aircrack-ng and coWPAtty. In this article, we will show you how to download, install, and use Backtrack 3 With Spoonwpa Iso to hack wireless networks.</p>
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-</ol>
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-
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-<li>Eject the USB drive from your computer.</li>
-</ul>
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-
-<p>Now that you have installed Backtrack 3 With Spoonwpa Iso on your CD or USB drive, you can use it to hack wireless networks. Here are the steps to do so:</p>
-
-<ol>
-<li>Boot your device from the CD or USB drive that contains Backtrack 3 With Spoonwpa Iso.</li>
-<li>Login as root with password "toor".</li>
-<li>Open a terminal window by pressing Ctrl+Alt+T.</li>
-<li>Type "startx" and press Enter to start the graphical user interface.</li>
-<li>Type "spoonwpa" and press Enter to launch the script.</li>
-<li>Select your wireless interface from the list (usually wlan0).</li>
-<li>Select your target network from the list (the one with WPA or WPA2 encryption).</li>
-<li>The script will start capturing packets from the network and try to capture a handshake (a four-way authentication exchange between a client and an access point).</li>
-<li>Once a handshake is captured, the script will stop capturing packets and start cracking it using coWPAtty (a dictionary-based attack tool).</li>
-<li>If successful, the script will display the password of the network in plain text.</li>
-</ol>
-
-<h2>Conclusion</h2>
-
-<p>Backtrack 3 With Spoonwpa Iso is a powerful hacking tool that allows you to crack WPA and WPA2 passwords using a live CD or USB. It is based on Backtrack 3, a Linux distribution designed for penetration testing and security auditing. Spoonwpa is a script that automates the process of capturing and cracking WPA handshakes using aircrack-ng and coWPAtty. In this article, we showed you how to download, install, and use Backtrack 3 With Spoonwpa Iso to hack wireless networks. We hope this article has helped you with that. Happy hacking!</p>
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diff --git a/spaces/scedlatioru/img-to-music/example/Crysis 3 Crack Fix Black Screen __EXCLUSIVE__.md b/spaces/scedlatioru/img-to-music/example/Crysis 3 Crack Fix Black Screen __EXCLUSIVE__.md
deleted file mode 100644
index abbb2ea7863fd5d2ad7db8d0eaa425d6d115ec30..0000000000000000000000000000000000000000
--- a/spaces/scedlatioru/img-to-music/example/Crysis 3 Crack Fix Black Screen __EXCLUSIVE__.md	
+++ /dev/null
@@ -1,32 +0,0 @@
-<br />
-<h1>How to Fix Crysis 3 Black Screen with Green Cursor Issue</h1>
-<p>If you are trying to play Crysis 3 on your PC, you may encounter a problem where the game screen turns black and all you see is a green cursor. This issue can prevent you from enjoying the game and may be caused by various factors, such as incompatible language settings, outdated game version, or corrupted game files. Fortunately, there are some possible solutions that you can try to fix this issue and play Crysis 3 without any problems.</p>
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-<p>In this article, we will show you three solutions that have worked for many Crysis 3 players who faced the same issue. You can try them one by one until you find the one that works for you. Before you start, make sure you have backed up your game files and saved data in case anything goes wrong.</p>
-<h2>Solution 1: Delete the License File</h2>
-<p>One of the possible causes of the black screen issue is a corrupted license file that prevents the game from launching properly. To fix this, you need to delete the license file from your PC and let the game create a new one. Here are the steps to do this:</p>
-<ol>
-<li>Open File Explorer and go to <code>C:\ProgramData\Electronic Arts\EA Services\License</code>.</li>
-<li>Find and delete the file named <code>71067.dlf</code>. This is the license file for Crysis 3.</li>
-<li>Launch Crysis 3 and see if the issue is resolved.</li>
-</ol>
-<h2>Solution 2: Change the Language Settings</h2>
-<p>Another possible cause of the black screen issue is a mismatch between the language settings of your PC and the game. If you have installed Crysis 3 in a different language than your system language, you may encounter this issue. To fix this, you need to change the language settings of the game to match your system language. Here are the steps to do this:</p>
-<ol>
-<li>Open File Explorer and go to the folder where you have installed Crysis 3. By default, it should be <code>C:\Program Files (x86)\Origin Games\Crysis 3</code>.</li>
-<li>Find and open the file named <code>system.cfg</code> with a text editor like Notepad.</li>
-<li>Look for the line that says <code>g_language = </code> followed by a language code, such as <code>russian</code>, <code>french</code>, or <code>german</code>.</li>
-<li>Change the language code to match your system language, such as <code>english</code>, <code>spanish</code>, or <code>italian</code>.</li>
-<li>Save and close the file.</li>
-<li>Launch Crysis 3 and see if the issue is resolved.</li>
-</ol>
-<h2>Solution 3: Apply a Crack Fix</h2>
-<p>The last possible solution is to apply a crack fix that can bypass some of the issues that may cause the black screen problem. A crack fix is a modified version of the game executable file that can override some of the game's checks and validations. However, applying a crack fix may also introduce some risks, such as malware infection, game instability, or legal issues. Therefore, we do not recommend this solution unless you have tried the other two solutions and none of them worked for you.</p>
-<p></p>
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-<ol>
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diff --git a/spaces/scedlatioru/img-to-music/example/HD Online Player (Jayanta Bhai Ki Luv Story In Hindi T).md b/spaces/scedlatioru/img-to-music/example/HD Online Player (Jayanta Bhai Ki Luv Story In Hindi T).md
deleted file mode 100644
index ed2d89a0612abe9be9b2417f449b3637a054dcd9..0000000000000000000000000000000000000000
--- a/spaces/scedlatioru/img-to-music/example/HD Online Player (Jayanta Bhai Ki Luv Story In Hindi T).md	
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deleted file mode 100644
index d03b0101bc02a1f71139175cff2eefd9d5511e9b..0000000000000000000000000000000000000000
--- a/spaces/scedlatioru/img-to-music/example/Jodhaa Akbar Tamil Movie Free Download In Hd.md	
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@@ -1,12 +0,0 @@
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diff --git a/spaces/scedlatioru/img-to-music/example/Saltatio Mortis Discography 2001 2011zip.md b/spaces/scedlatioru/img-to-music/example/Saltatio Mortis Discography 2001 2011zip.md
deleted file mode 100644
index f6f4500c2c81303d7353746bcaaf810546954237..0000000000000000000000000000000000000000
--- a/spaces/scedlatioru/img-to-music/example/Saltatio Mortis Discography 2001 2011zip.md	
+++ /dev/null
@@ -1,28 +0,0 @@
-<br />
-<h1>Saltatio Mortis: A Decade of Medieval Metal</h1>
-<p>Saltatio Mortis is a German band that combines medieval music with metal elements. The name means "dance of death" in Latin, and the band's motto is "He who dances does not die". Saltatio Mortis was founded in 2000 and has released nine studio albums and four live albums between 2001 and 2011. Here is a brief overview of their discography in that period.</p>
-<ul>
-<li><strong>Tavernakel</strong> (2001): The debut album of Saltatio Mortis, featuring mostly traditional medieval songs and instruments. The album was released by Napalm Records[^1^].</li>
-<li><strong>Das Zweite Gesicht</strong> (2002): The second album of Saltatio Mortis, introducing more metal elements and original compositions. The album title means "The Second Face" in German[^1^].</li>
-<li><strong>Heptessenz</strong> (2003): The third album of Saltatio Mortis, focusing on instrumental music and market songs from the Middle Ages. The album title means "Seventh Essence" in German[^1^].</li>
-<li><strong>Erwachen</strong> (2004): The fourth album of Saltatio Mortis, marking a shift to a more rock-oriented sound and lyrical themes. The album title means "Awakening" in German[^2^].</li>
-<li><strong>Des Königs Henker</strong> (2005): The fifth album of Saltatio Mortis, featuring darker and heavier songs about death, war, and tyranny. The album title means "The King's Hangman" in German[^2^].</li>
-<li><strong>Aus Der Asche</strong> (2007): The sixth album of Saltatio Mortis, continuing the rock direction and exploring topics such as freedom, love, and rebellion. The album title means "From the Ashes" in German[^2^].</li>
-<li><strong>Wer Wind Sät</strong> (2009): The seventh album of Saltatio Mortis, inspired by the social and political issues of the time. The album title means "Who Sows the Wind" in German[^2^].</li>
-<li><strong>Sturm Aufs Paradies</strong> (2011): The eighth album of Saltatio Mortis, presenting a more optimistic and hopeful vision of the world. The album title means "Rush for Paradise" in German[^2^].</li>
-<li><strong>Manufactum I-III</strong> (2005, 2010, 2013): Three live albums of Saltatio Mortis, recorded at different medieval markets and festivals. The albums feature acoustic versions of their songs as well as covers and improvisations[^2^] [^3^].</li>
-<li><strong>10 Jahre Wild Und Frei</strong> (2011): A live CD/DVD of Saltatio Mortis, celebrating their tenth anniversary as a band. The concert was recorded at the Stadthalle Wuppertal on October 15th, 2010[^2^].</li>
-</ul>
-<p>Saltatio Mortis is one of the most popular and influential bands in the medieval metal scene. Their discography showcases their musical evolution and diversity over the years. If you are a fan of medieval music, metal music, or both, you should definitely check out their albums.</p>
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-<p>After their successful decade of medieval metal, Saltatio Mortis did not stop creating new music. They released four more studio albums between 2013 and 2020, each one exploring different musical styles and themes. Here is a brief overview of their discography in that period.</p>
-<ul>
-<li><strong>Das Schwarze Einmaleins</strong> (2013): The ninth album of Saltatio Mortis, featuring a more modern and electronic sound and lyrics about magic, fantasy, and fairy tales. The album title means "The Black 101" in German.</li>
-<li><strong>Zirkus Zeitgeist</strong> (2015): The tenth album of Saltatio Mortis, inspired by the circus and its colorful characters and stories. The album title means "Circus Zeitgeist" in German.</li>
-<li><strong>Brot Und Spiele</strong> (2018): The eleventh album of Saltatio Mortis, criticizing the social and political problems of the present day and calling for change and action. The album title means "Bread and Games" in German.</li>
-<li><strong>Für Immer Frei</strong> (2020): The twelfth album of Saltatio Mortis, celebrating the values of freedom, diversity, and solidarity. The album title means "Forever Free" in German.</li>
-</ul>
-<p>Saltatio Mortis is still active and touring as of 2021. They have also collaborated with other artists such as In Extremo, Subway to Sally, Schandmaul, and Versengold. They have won several awards and nominations for their music, such as the Metal Hammer Award, the Echo Award, and the Amadeus Award. They have also participated in various charity projects and campaigns for human rights, animal rights, and environmental protection. Saltatio Mortis is not only a band, but also a movement that inspires people to dance, to live, and to make a difference.</p> d5da3c52bf<br />
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diff --git a/spaces/segments-tobias/conex/espnet/lm/pytorch_backend/lm.py b/spaces/segments-tobias/conex/espnet/lm/pytorch_backend/lm.py
deleted file mode 100644
index 1c0249527fa2184afd9a6ae89eafb923de7a2b51..0000000000000000000000000000000000000000
--- a/spaces/segments-tobias/conex/espnet/lm/pytorch_backend/lm.py
+++ /dev/null
@@ -1,410 +0,0 @@
-#!/usr/bin/env python3
-# Copyright 2017 Johns Hopkins University (Shinji Watanabe)
-#  Apache 2.0  (http://www.apache.org/licenses/LICENSE-2.0)
-# This code is ported from the following implementation written in Torch.
-# https://github.com/chainer/chainer/blob/master/examples/ptb/train_ptb_custom_loop.py
-
-"""LM training in pytorch."""
-
-import copy
-import json
-import logging
-import numpy as np
-
-import torch
-import torch.nn as nn
-from torch.nn.parallel import data_parallel
-
-from chainer import Chain
-from chainer.dataset import convert
-from chainer import reporter
-from chainer import training
-from chainer.training import extensions
-
-from espnet.lm.lm_utils import count_tokens
-from espnet.lm.lm_utils import load_dataset
-from espnet.lm.lm_utils import MakeSymlinkToBestModel
-from espnet.lm.lm_utils import ParallelSentenceIterator
-from espnet.lm.lm_utils import read_tokens
-from espnet.nets.lm_interface import dynamic_import_lm
-from espnet.nets.lm_interface import LMInterface
-from espnet.optimizer.factory import dynamic_import_optimizer
-from espnet.scheduler.pytorch import PyTorchScheduler
-from espnet.scheduler.scheduler import dynamic_import_scheduler
-
-from espnet.asr.asr_utils import snapshot_object
-from espnet.asr.asr_utils import torch_load
-from espnet.asr.asr_utils import torch_resume
-from espnet.asr.asr_utils import torch_snapshot
-
-from espnet.utils.training.tensorboard_logger import TensorboardLogger
-from tensorboardX import SummaryWriter
-
-from espnet.utils.deterministic_utils import set_deterministic_pytorch
-from espnet.utils.training.evaluator import BaseEvaluator
-from espnet.utils.training.iterators import ShufflingEnabler
-from espnet.utils.training.train_utils import check_early_stop
-from espnet.utils.training.train_utils import set_early_stop
-
-
-def compute_perplexity(result):
-    """Compute and add the perplexity to the LogReport.
-
-    :param dict result: The current observations
-    """
-    # Routine to rewrite the result dictionary of LogReport to add perplexity values
-    result["perplexity"] = np.exp(result["main/nll"] / result["main/count"])
-    if "validation/main/nll" in result:
-        result["val_perplexity"] = np.exp(
-            result["validation/main/nll"] / result["validation/main/count"]
-        )
-
-
-class Reporter(Chain):
-    """Dummy module to use chainer's trainer."""
-
-    def report(self, loss):
-        """Report nothing."""
-        pass
-
-
-def concat_examples(batch, device=None, padding=None):
-    """Concat examples in minibatch.
-
-    :param np.ndarray batch: The batch to concatenate
-    :param int device: The device to send to
-    :param Tuple[int,int] padding: The padding to use
-    :return: (inputs, targets)
-    :rtype (torch.Tensor, torch.Tensor)
-    """
-    x, t = convert.concat_examples(batch, padding=padding)
-    x = torch.from_numpy(x)
-    t = torch.from_numpy(t)
-    if device is not None and device >= 0:
-        x = x.cuda(device)
-        t = t.cuda(device)
-    return x, t
-
-
-class BPTTUpdater(training.StandardUpdater):
-    """An updater for a pytorch LM."""
-
-    def __init__(
-        self,
-        train_iter,
-        model,
-        optimizer,
-        schedulers,
-        device,
-        gradclip=None,
-        use_apex=False,
-        accum_grad=1,
-    ):
-        """Initialize class.
-
-        Args:
-            train_iter (chainer.dataset.Iterator): The train iterator
-            model (LMInterface) : The model to update
-            optimizer (torch.optim.Optimizer): The optimizer for training
-            schedulers (espnet.scheduler.scheduler.SchedulerInterface):
-                The schedulers of `optimizer`
-            device (int): The device id
-            gradclip (float): The gradient clipping value to use
-            use_apex (bool): The flag to use Apex in backprop.
-            accum_grad (int): The number of gradient accumulation.
-
-        """
-        super(BPTTUpdater, self).__init__(train_iter, optimizer)
-        self.model = model
-        self.device = device
-        self.gradclip = gradclip
-        self.use_apex = use_apex
-        self.scheduler = PyTorchScheduler(schedulers, optimizer)
-        self.accum_grad = accum_grad
-
-    # The core part of the update routine can be customized by overriding.
-    def update_core(self):
-        """Update the model."""
-        # When we pass one iterator and optimizer to StandardUpdater.__init__,
-        # they are automatically named 'main'.
-        train_iter = self.get_iterator("main")
-        optimizer = self.get_optimizer("main")
-        # Progress the dataset iterator for sentences at each iteration.
-        self.model.zero_grad()  # Clear the parameter gradients
-        accum = {"loss": 0.0, "nll": 0.0, "count": 0}
-        for _ in range(self.accum_grad):
-            batch = train_iter.__next__()
-            # Concatenate the token IDs to matrices and send them to the device
-            # self.converter does this job
-            # (it is chainer.dataset.concat_examples by default)
-            x, t = concat_examples(batch, device=self.device[0], padding=(0, -100))
-            if self.device[0] == -1:
-                loss, nll, count = self.model(x, t)
-            else:
-                # apex does not support torch.nn.DataParallel
-                loss, nll, count = data_parallel(self.model, (x, t), self.device)
-
-            # backward
-            loss = loss.mean() / self.accum_grad
-            if self.use_apex:
-                from apex import amp
-
-                with amp.scale_loss(loss, optimizer) as scaled_loss:
-                    scaled_loss.backward()
-            else:
-                loss.backward()  # Backprop
-            # accumulate stats
-            accum["loss"] += float(loss)
-            accum["nll"] += float(nll.sum())
-            accum["count"] += int(count.sum())
-
-        for k, v in accum.items():
-            reporter.report({k: v}, optimizer.target)
-        if self.gradclip is not None:
-            nn.utils.clip_grad_norm_(self.model.parameters(), self.gradclip)
-        optimizer.step()  # Update the parameters
-        self.scheduler.step(n_iter=self.iteration)
-
-
-class LMEvaluator(BaseEvaluator):
-    """A custom evaluator for a pytorch LM."""
-
-    def __init__(self, val_iter, eval_model, reporter, device):
-        """Initialize class.
-
-        :param chainer.dataset.Iterator val_iter : The validation iterator
-        :param LMInterface eval_model : The model to evaluate
-        :param chainer.Reporter reporter : The observations reporter
-        :param int device : The device id to use
-
-        """
-        super(LMEvaluator, self).__init__(val_iter, reporter, device=-1)
-        self.model = eval_model
-        self.device = device
-
-    def evaluate(self):
-        """Evaluate the model."""
-        val_iter = self.get_iterator("main")
-        loss = 0
-        nll = 0
-        count = 0
-        self.model.eval()
-        with torch.no_grad():
-            for batch in copy.copy(val_iter):
-                x, t = concat_examples(batch, device=self.device[0], padding=(0, -100))
-                if self.device[0] == -1:
-                    l, n, c = self.model(x, t)
-                else:
-                    # apex does not support torch.nn.DataParallel
-                    l, n, c = data_parallel(self.model, (x, t), self.device)
-                loss += float(l.sum())
-                nll += float(n.sum())
-                count += int(c.sum())
-        self.model.train()
-        # report validation loss
-        observation = {}
-        with reporter.report_scope(observation):
-            reporter.report({"loss": loss}, self.model.reporter)
-            reporter.report({"nll": nll}, self.model.reporter)
-            reporter.report({"count": count}, self.model.reporter)
-        return observation
-
-
-def train(args):
-    """Train with the given args.
-
-    :param Namespace args: The program arguments
-    :param type model_class: LMInterface class for training
-    """
-    model_class = dynamic_import_lm(args.model_module, args.backend)
-    assert issubclass(model_class, LMInterface), "model should implement LMInterface"
-    # display torch version
-    logging.info("torch version = " + torch.__version__)
-
-    set_deterministic_pytorch(args)
-
-    # check cuda and cudnn availability
-    if not torch.cuda.is_available():
-        logging.warning("cuda is not available")
-
-    # get special label ids
-    unk = args.char_list_dict["<unk>"]
-    eos = args.char_list_dict["<eos>"]
-    # read tokens as a sequence of sentences
-    val, n_val_tokens, n_val_oovs = load_dataset(
-        args.valid_label, args.char_list_dict, args.dump_hdf5_path
-    )
-    train, n_train_tokens, n_train_oovs = load_dataset(
-        args.train_label, args.char_list_dict, args.dump_hdf5_path
-    )
-    logging.info("#vocab = " + str(args.n_vocab))
-    logging.info("#sentences in the training data = " + str(len(train)))
-    logging.info("#tokens in the training data = " + str(n_train_tokens))
-    logging.info(
-        "oov rate in the training data = %.2f %%"
-        % (n_train_oovs / n_train_tokens * 100)
-    )
-    logging.info("#sentences in the validation data = " + str(len(val)))
-    logging.info("#tokens in the validation data = " + str(n_val_tokens))
-    logging.info(
-        "oov rate in the validation data = %.2f %%" % (n_val_oovs / n_val_tokens * 100)
-    )
-
-    use_sortagrad = args.sortagrad == -1 or args.sortagrad > 0
-    # Create the dataset iterators
-    batch_size = args.batchsize * max(args.ngpu, 1)
-    if batch_size * args.accum_grad > args.batchsize:
-        logging.info(
-            f"batch size is automatically increased "
-            f"({args.batchsize} -> {batch_size * args.accum_grad})"
-        )
-    train_iter = ParallelSentenceIterator(
-        train,
-        batch_size,
-        max_length=args.maxlen,
-        sos=eos,
-        eos=eos,
-        shuffle=not use_sortagrad,
-    )
-    val_iter = ParallelSentenceIterator(
-        val, batch_size, max_length=args.maxlen, sos=eos, eos=eos, repeat=False
-    )
-    epoch_iters = int(len(train_iter.batch_indices) / args.accum_grad)
-    logging.info("#iterations per epoch = %d" % epoch_iters)
-    logging.info("#total iterations = " + str(args.epoch * epoch_iters))
-    # Prepare an RNNLM model
-    if args.train_dtype in ("float16", "float32", "float64"):
-        dtype = getattr(torch, args.train_dtype)
-    else:
-        dtype = torch.float32
-    model = model_class(args.n_vocab, args).to(dtype=dtype)
-    if args.ngpu > 0:
-        model.to("cuda")
-        gpu_id = list(range(args.ngpu))
-    else:
-        gpu_id = [-1]
-
-    # Save model conf to json
-    model_conf = args.outdir + "/model.json"
-    with open(model_conf, "wb") as f:
-        logging.info("writing a model config file to " + model_conf)
-        f.write(
-            json.dumps(vars(args), indent=4, ensure_ascii=False, sort_keys=True).encode(
-                "utf_8"
-            )
-        )
-
-    logging.warning(
-        "num. model params: {:,} (num. trained: {:,} ({:.1f}%))".format(
-            sum(p.numel() for p in model.parameters()),
-            sum(p.numel() for p in model.parameters() if p.requires_grad),
-            sum(p.numel() for p in model.parameters() if p.requires_grad)
-            * 100.0
-            / sum(p.numel() for p in model.parameters()),
-        )
-    )
-
-    # Set up an optimizer
-    opt_class = dynamic_import_optimizer(args.opt, args.backend)
-    optimizer = opt_class.from_args(model.parameters(), args)
-    if args.schedulers is None:
-        schedulers = []
-    else:
-        schedulers = [dynamic_import_scheduler(v)(k, args) for k, v in args.schedulers]
-
-    # setup apex.amp
-    if args.train_dtype in ("O0", "O1", "O2", "O3"):
-        try:
-            from apex import amp
-        except ImportError as e:
-            logging.error(
-                f"You need to install apex for --train-dtype {args.train_dtype}. "
-                "See https://github.com/NVIDIA/apex#linux"
-            )
-            raise e
-        model, optimizer = amp.initialize(model, optimizer, opt_level=args.train_dtype)
-        use_apex = True
-    else:
-        use_apex = False
-
-    # FIXME: TOO DIRTY HACK
-    reporter = Reporter()
-    setattr(model, "reporter", reporter)
-    setattr(optimizer, "target", reporter)
-    setattr(optimizer, "serialize", lambda s: reporter.serialize(s))
-
-    updater = BPTTUpdater(
-        train_iter,
-        model,
-        optimizer,
-        schedulers,
-        gpu_id,
-        gradclip=args.gradclip,
-        use_apex=use_apex,
-        accum_grad=args.accum_grad,
-    )
-    trainer = training.Trainer(updater, (args.epoch, "epoch"), out=args.outdir)
-    trainer.extend(LMEvaluator(val_iter, model, reporter, device=gpu_id))
-    trainer.extend(
-        extensions.LogReport(
-            postprocess=compute_perplexity,
-            trigger=(args.report_interval_iters, "iteration"),
-        )
-    )
-    trainer.extend(
-        extensions.PrintReport(
-            [
-                "epoch",
-                "iteration",
-                "main/loss",
-                "perplexity",
-                "val_perplexity",
-                "elapsed_time",
-            ]
-        ),
-        trigger=(args.report_interval_iters, "iteration"),
-    )
-    trainer.extend(extensions.ProgressBar(update_interval=args.report_interval_iters))
-    # Save best models
-    trainer.extend(torch_snapshot(filename="snapshot.ep.{.updater.epoch}"))
-    trainer.extend(snapshot_object(model, "rnnlm.model.{.updater.epoch}"))
-    # T.Hori: MinValueTrigger should be used, but it fails when resuming
-    trainer.extend(MakeSymlinkToBestModel("validation/main/loss", "rnnlm.model"))
-
-    if use_sortagrad:
-        trainer.extend(
-            ShufflingEnabler([train_iter]),
-            trigger=(args.sortagrad if args.sortagrad != -1 else args.epoch, "epoch"),
-        )
-    if args.resume:
-        logging.info("resumed from %s" % args.resume)
-        torch_resume(args.resume, trainer)
-
-    set_early_stop(trainer, args, is_lm=True)
-    if args.tensorboard_dir is not None and args.tensorboard_dir != "":
-        writer = SummaryWriter(args.tensorboard_dir)
-        trainer.extend(
-            TensorboardLogger(writer), trigger=(args.report_interval_iters, "iteration")
-        )
-
-    trainer.run()
-    check_early_stop(trainer, args.epoch)
-
-    # compute perplexity for test set
-    if args.test_label:
-        logging.info("test the best model")
-        torch_load(args.outdir + "/rnnlm.model.best", model)
-        test = read_tokens(args.test_label, args.char_list_dict)
-        n_test_tokens, n_test_oovs = count_tokens(test, unk)
-        logging.info("#sentences in the test data = " + str(len(test)))
-        logging.info("#tokens in the test data = " + str(n_test_tokens))
-        logging.info(
-            "oov rate in the test data = %.2f %%" % (n_test_oovs / n_test_tokens * 100)
-        )
-        test_iter = ParallelSentenceIterator(
-            test, batch_size, max_length=args.maxlen, sos=eos, eos=eos, repeat=False
-        )
-        evaluator = LMEvaluator(test_iter, model, reporter, device=gpu_id)
-        result = evaluator()
-        compute_perplexity(result)
-        logging.info(f"test perplexity: {result['perplexity']}")
diff --git a/spaces/segments-tobias/conex/espnet/nets/chainer_backend/transformer/ctc.py b/spaces/segments-tobias/conex/espnet/nets/chainer_backend/transformer/ctc.py
deleted file mode 100644
index caac6545655adec203596b566917a90e5e27a333..0000000000000000000000000000000000000000
--- a/spaces/segments-tobias/conex/espnet/nets/chainer_backend/transformer/ctc.py
+++ /dev/null
@@ -1,169 +0,0 @@
-# encoding: utf-8
-"""Class Declaration of Transformer's CTC."""
-import logging
-
-import chainer
-import chainer.functions as F
-import chainer.links as L
-import numpy as np
-
-
-# TODO(nelson): Merge chainer_backend/transformer/ctc.py in chainer_backend/ctc.py
-class CTC(chainer.Chain):
-    """Chainer implementation of ctc layer.
-
-    Args:
-        odim (int): The output dimension.
-        eprojs (int | None): Dimension of input vectors from encoder.
-        dropout_rate (float): Dropout rate.
-
-    """
-
-    def __init__(self, odim, eprojs, dropout_rate):
-        """Initialize CTC."""
-        super(CTC, self).__init__()
-        self.dropout_rate = dropout_rate
-        self.loss = None
-
-        with self.init_scope():
-            self.ctc_lo = L.Linear(eprojs, odim)
-
-    def __call__(self, hs, ys):
-        """CTC forward.
-
-        Args:
-            hs (list of chainer.Variable | N-dimension array):
-                Input variable from encoder.
-            ys (list of chainer.Variable | N-dimension array):
-                Input variable of decoder.
-
-        Returns:
-            chainer.Variable: A variable holding a scalar value of the CTC loss.
-
-        """
-        self.loss = None
-        ilens = [x.shape[0] for x in hs]
-        olens = [x.shape[0] for x in ys]
-
-        # zero padding for hs
-        y_hat = self.ctc_lo(
-            F.dropout(F.pad_sequence(hs), ratio=self.dropout_rate), n_batch_axes=2
-        )
-        y_hat = F.separate(y_hat, axis=1)  # ilen list of batch x hdim
-
-        # zero padding for ys
-        y_true = F.pad_sequence(ys, padding=-1)  # batch x olen
-
-        # get length info
-        input_length = chainer.Variable(self.xp.array(ilens, dtype=np.int32))
-        label_length = chainer.Variable(self.xp.array(olens, dtype=np.int32))
-        logging.info(
-            self.__class__.__name__ + " input lengths:  " + str(input_length.data)
-        )
-        logging.info(
-            self.__class__.__name__ + " output lengths: " + str(label_length.data)
-        )
-
-        # get ctc loss
-        self.loss = F.connectionist_temporal_classification(
-            y_hat, y_true, 0, input_length, label_length
-        )
-        logging.info("ctc loss:" + str(self.loss.data))
-
-        return self.loss
-
-    def log_softmax(self, hs):
-        """Log_softmax of frame activations.
-
-        Args:
-            hs (list of chainer.Variable | N-dimension array):
-                Input variable from encoder.
-
-        Returns:
-            chainer.Variable: A n-dimension float array.
-
-        """
-        y_hat = self.ctc_lo(F.pad_sequence(hs), n_batch_axes=2)
-        return F.log_softmax(y_hat.reshape(-1, y_hat.shape[-1])).reshape(y_hat.shape)
-
-
-class WarpCTC(chainer.Chain):
-    """Chainer implementation of warp-ctc layer.
-
-    Args:
-        odim (int): The output dimension.
-        eproj (int | None): Dimension of input vector from encoder.
-        dropout_rate (float): Dropout rate.
-
-    """
-
-    def __init__(self, odim, eprojs, dropout_rate):
-        """Initialize WarpCTC."""
-        super(WarpCTC, self).__init__()
-        # The main difference between the ctc for transformer and
-        # the rnn is because the target (ys) is already a list of
-        # arrays located in the cpu, while in rnn routine the target is
-        # a list of variables located in cpu/gpu. If the target of rnn becomes
-        # a list of cpu arrays then this file would be no longer required.
-        from chainer_ctc.warpctc import ctc as warp_ctc
-
-        self.ctc = warp_ctc
-        self.dropout_rate = dropout_rate
-        self.loss = None
-
-        with self.init_scope():
-            self.ctc_lo = L.Linear(eprojs, odim)
-
-    def forward(self, hs, ys):
-        """Core function of the Warp-CTC layer.
-
-        Args:
-            hs (iterable of chainer.Variable | N-dimention array):
-                Input variable from encoder.
-            ys (iterable of N-dimension array): Input variable of decoder.
-
-        Returns:
-           chainer.Variable: A variable holding a scalar value of the CTC loss.
-
-        """
-        self.loss = None
-        ilens = [hs.shape[1]] * hs.shape[0]
-        olens = [x.shape[0] for x in ys]
-
-        # zero padding for hs
-        # output batch x frames x hdim > frames x batch x hdim
-        y_hat = self.ctc_lo(
-            F.dropout(hs, ratio=self.dropout_rate), n_batch_axes=2
-        ).transpose(1, 0, 2)
-
-        # get length info
-        logging.info(self.__class__.__name__ + " input lengths:  " + str(ilens))
-        logging.info(self.__class__.__name__ + " output lengths: " + str(olens))
-
-        # get ctc loss
-        self.loss = self.ctc(y_hat, ilens, ys)[0]
-        logging.info("ctc loss:" + str(self.loss.data))
-        return self.loss
-
-    def log_softmax(self, hs):
-        """Log_softmax of frame activations.
-
-        Args:
-            hs (list of chainer.Variable | N-dimension array):
-                Input variable from encoder.
-
-        Returns:
-            chainer.Variable: A n-dimension float array.
-
-        """
-        y_hat = self.ctc_lo(F.pad_sequence(hs), n_batch_axes=2)
-        return F.log_softmax(y_hat.reshape(-1, y_hat.shape[-1])).reshape(y_hat.shape)
-
-    def argmax(self, hs_pad):
-        """Argmax of frame activations.
-
-        :param chainer variable hs_pad: 3d tensor (B, Tmax, eprojs)
-        :return: argmax applied 2d tensor (B, Tmax)
-        :rtype: chainer.Variable.
-        """
-        return F.argmax(self.ctc_lo(F.pad_sequence(hs_pad), n_batch_axes=2), axis=-1)
diff --git a/spaces/shenfangqi/Retrieval-based-Voice-Conversion-WebUI/go-realtime-gui.bat b/spaces/shenfangqi/Retrieval-based-Voice-Conversion-WebUI/go-realtime-gui.bat
deleted file mode 100644
index 835543f5d4845f4b9dae70c1cf1855cce3ce6c0b..0000000000000000000000000000000000000000
--- a/spaces/shenfangqi/Retrieval-based-Voice-Conversion-WebUI/go-realtime-gui.bat
+++ /dev/null
@@ -1,2 +0,0 @@
-runtime\python.exe gui.py
-pause
diff --git a/spaces/shi-labs/OneFormer/oneformer/modeling/transformer_decoder/text_transformer.py b/spaces/shi-labs/OneFormer/oneformer/modeling/transformer_decoder/text_transformer.py
deleted file mode 100644
index d0b7292018ecfbf4111c0da9c90444d0e1e41cb6..0000000000000000000000000000000000000000
--- a/spaces/shi-labs/OneFormer/oneformer/modeling/transformer_decoder/text_transformer.py
+++ /dev/null
@@ -1,257 +0,0 @@
-# -------------------------------------------------------------------------
-# MIT License
-#
-# Copyright (c) 2021 OpenAI
-#
-# Permission is hereby granted, free of charge, to any person obtaining a copy
-# of this software and associated documentation files (the "Software"), to deal
-# in the Software without restriction, including without limitation the rights
-# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-# copies of the Software, and to permit persons to whom the Software is
-# furnished to do so, subject to the following conditions:
-#
-# The above copyright notice and this permission notice shall be included in all
-# copies or substantial portions of the Software.
-#
-# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-# SOFTWARE.
-#
-# -------------------------------------------------------------------------
-
-import torch
-import torch.utils.checkpoint as checkpoint
-from torch import nn
-from collections import OrderedDict
-from timm.models.layers import trunc_normal_
-
-class Attention(nn.Module):
-    def __init__(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, attn_drop=0., proj_drop=0.):
-        super().__init__()
-        self.num_heads = num_heads
-        head_dim = dim // num_heads
-        # NOTE scale factor was wrong in my original version, can set manually to be compat with prev weights
-        self.scale = qk_scale or head_dim ** -0.5
-
-        self.q_proj = nn.Linear(dim, dim, bias=qkv_bias)
-        self.k_proj = nn.Linear(dim, dim, bias=qkv_bias)
-        self.v_proj = nn.Linear(dim, dim, bias=qkv_bias)
-
-
-        self.attn_drop = nn.Dropout(attn_drop)
-        self.proj = nn.Linear(dim, dim)
-        self.proj_drop = nn.Dropout(proj_drop)
-
-    def forward(self, q, k, v):
-        B, N, C = q.shape
-        assert k.shape == v.shape
-        B, M, C = k.shape
-        q = self.q_proj(q).reshape(B, N, self.num_heads, C // self.num_heads)
-        k = self.k_proj(k).reshape(B, M, self.num_heads, C // self.num_heads)
-        v = self.v_proj(v).reshape(B, M, self.num_heads, C // self.num_heads)
-
-        attn = torch.einsum('bnkc,bmkc->bknm', q, k) * self.scale
-
-        attn = attn.softmax(dim=-1)
-
-        x = torch.einsum('bknm,bmkc->bnkc', attn, v).reshape(B, N, C)
-
-        x = self.proj(x)
-        x = self.proj_drop(x)
-        return x
-
-class TransformerDecoderLayer(nn.Module):
-    def __init__(
-        self,
-        d_model,
-        nhead,
-        dropout=0.1,
-    ):
-        super().__init__()
-        self.self_attn = Attention(d_model, nhead, proj_drop=dropout)
-        self.cross_attn = Attention(d_model, nhead, proj_drop=dropout)
-
-        self.norm1 = nn.LayerNorm(d_model)
-        self.norm2 = nn.LayerNorm(d_model)
-        self.norm3 = nn.LayerNorm(d_model)
-        self.dropout = nn.Dropout(dropout)
-
-        self.mlp = nn.Sequential(
-            nn.Linear(d_model, d_model * 4),
-            nn.GELU(),
-            nn.Dropout(dropout),
-            nn.Linear(d_model * 4, d_model)
-        )
-
-    def forward(self, x, mem):
-        q = k = v = self.norm1(x)
-        x = x + self.self_attn(q, k, v)
-        q = self.norm2(x)
-        x = x + self.cross_attn(q, mem, mem)
-        x = x + self.dropout(self.mlp(self.norm3(x)))
-        return x
-
-
-class ContextDecoder(nn.Module):
-    def __init__(self,
-                 transformer_width=256,
-                 transformer_heads=4,
-                 transformer_layers=6,
-                 visual_dim=1024,
-                 dropout=0.1,
-                 **kwargs):
-        super().__init__()
-
-        self.memory_proj = nn.Sequential(
-            nn.LayerNorm(visual_dim),
-            nn.Linear(visual_dim, transformer_width),
-            nn.LayerNorm(transformer_width),
-        )
-
-        self.text_proj = nn.Sequential(
-            nn.LayerNorm(visual_dim),
-            nn.Linear(visual_dim, transformer_width),
-        )
-
-        self.decoder = nn.ModuleList([
-                    TransformerDecoderLayer(transformer_width, transformer_heads, dropout) for _ in range(transformer_layers)
-                ])
-        
-        self.out_proj = nn.Sequential(
-            nn.LayerNorm(transformer_width),
-            nn.Linear(transformer_width, visual_dim)
-        )
-
-        self.apply(self._init_weights)
-
-    def _init_weights(self, m):
-        if isinstance(m, nn.Linear):
-            trunc_normal_(m.weight, std=.02)
-            if isinstance(m, nn.Linear) and m.bias is not None:
-                nn.init.constant_(m.bias, 0)
-        elif isinstance(m, nn.LayerNorm):
-            nn.init.constant_(m.bias, 0)
-            nn.init.constant_(m.weight, 1.0)
-
-    
-    def forward(self, text, visual):
-        B, N, C = visual.shape
-        visual = self.memory_proj(visual)
-        x = self.text_proj(text)
-
-        for layer in self.decoder:
-            x = layer(x, visual)
-        
-        return self.out_proj(x)
-
-
-class QuickGELU(nn.Module):
-
-    def forward(self, x: torch.Tensor):
-        return x * torch.sigmoid(1.702 * x)
-
-
-class ResidualAttentionBlock(nn.Module):
-
-    def __init__(self, d_model: int, n_head: int, attn_mask: torch.Tensor = None):
-        super().__init__()
-
-        self.attn = nn.MultiheadAttention(d_model, n_head)
-        self.ln_1 = nn.LayerNorm(d_model)
-        self.mlp = nn.Sequential(
-            OrderedDict([('c_fc', nn.Linear(d_model, d_model * 4)), ('gelu', QuickGELU()),
-                         ('c_proj', nn.Linear(d_model * 4, d_model))]))
-        self.ln_2 = nn.LayerNorm(d_model)
-        self.attn_mask = attn_mask
-
-    def attention(self, x: torch.Tensor, key_padding_mask: torch.Tensor):
-        self.attn_mask = self.attn_mask.to(dtype=x.dtype, device=x.device) if self.attn_mask is not None else None
-        return self.attn(x, x, x, need_weights=False, attn_mask=self.attn_mask, key_padding_mask=key_padding_mask)[0]
-
-    def forward(self, x: torch.Tensor, key_padding_mask=None):
-        x = x + self.attention(self.ln_1(x), key_padding_mask=key_padding_mask)
-        x = x + self.mlp(self.ln_2(x))
-        return x
-
-class Transformer(nn.Module):
-
-    def __init__(self, width: int, layers: int, heads: int, attn_mask: torch.Tensor = None, use_checkpoint=False):
-        super().__init__()
-        self.width = width
-        self.layers = layers
-        self.resblocks = nn.Sequential(*[ResidualAttentionBlock(width, heads, attn_mask) for _ in range(layers)])
-        proj_std = (self.width**-0.5) * ((2 * self.layers)**-0.5)
-        attn_std = self.width**-0.5
-        fc_std = (2 * self.width)**-0.5
-        for block in self.resblocks:
-            nn.init.normal_(block.attn.in_proj_weight, std=attn_std)
-            nn.init.normal_(block.attn.out_proj.weight, std=proj_std)
-            nn.init.normal_(block.mlp.c_fc.weight, std=fc_std)
-            nn.init.normal_(block.mlp.c_proj.weight, std=proj_std)
-
-        self.use_checkpoint = use_checkpoint
-
-    def forward(self, x: torch.Tensor):
-        for resblock in self.resblocks:
-            if self.use_checkpoint:
-                x = checkpoint.checkpoint(resblock, x)
-            else:
-                x = resblock(x)
-        return x
-
-
-class TextTransformer(nn.Module):
-
-    def __init__(
-        self,
-        context_length: int,
-        width: int,
-        layers: int,
-        vocab_size,
-        use_checkpoint=False,
-    ):
-
-        super().__init__()
-        heads = width // 64
-        self.context_length = context_length
-        self.width = width
-        self.transformer = Transformer(
-            width=width,
-            layers=layers,
-            heads=heads,
-            attn_mask=self.build_attention_mask(),
-            use_checkpoint=use_checkpoint)
-
-        self.positional_embedding = nn.Parameter(torch.empty(self.context_length, width))
-        self.ln_final = nn.LayerNorm(width)
-        self.token_embedding = nn.Embedding(vocab_size, width)
-        nn.init.normal_(self.token_embedding.weight, std=0.02)
-
-        # initialization
-        nn.init.normal_(self.positional_embedding, std=0.01)
-
-    def build_attention_mask(self):
-        # lazily create causal attention mask, with full attention between the vision tokens
-        # pytorch uses additive attention mask; fill with -inf
-        mask = torch.empty(self.context_length, self.context_length)
-        mask.fill_(float('-inf'))
-        mask.triu_(1)  # zero out the lower diagonal
-        return mask
-
-    def forward(self, text):
-        x = self.token_embedding(text)
-        x = x + self.positional_embedding
-        x = x.permute(1, 0, 2)  # NLD -> LND
-        x = self.transformer(x)
-        x = x.permute(1, 0, 2)  # LND -> NLD
-        x = self.ln_final(x)
-
-        # x.shape = [batch_size, n_ctx, transformer.width]
-        # take features from the eot embedding (eot_token is the highest number in each sequence)
-        x = x[torch.arange(x.shape[0]), text.argmax(dim=-1)]
-
-        return x
\ No newline at end of file
diff --git a/spaces/shikunl/prismer/prismer/experts/generate_depth.py b/spaces/shikunl/prismer/prismer/experts/generate_depth.py
deleted file mode 100644
index a5243efea2af3699db43e296c83aaf371db6b550..0000000000000000000000000000000000000000
--- a/spaces/shikunl/prismer/prismer/experts/generate_depth.py
+++ /dev/null
@@ -1,55 +0,0 @@
-# Copyright (c) 2023, NVIDIA Corporation & Affiliates. All rights reserved.
-#
-# This work is made available under the Nvidia Source Code License-NC.
-# To view a copy of this license, visit
-# https://github.com/NVlabs/prismer/blob/main/LICENSE
-
-import torch
-import os
-try:
-    import ruamel_yaml as yaml
-except ModuleNotFoundError:
-    import ruamel.yaml as yaml
-    
-from experts.model_bank import load_expert_model
-from experts.depth.generate_dataset import Dataset
-import PIL.Image as Image
-from accelerate import Accelerator
-from tqdm import tqdm
-
-model, transform = load_expert_model(task='depth')
-accelerator = Accelerator(mixed_precision='fp16')
-
-config = yaml.load(open('configs/experts.yaml', 'r'), Loader=yaml.Loader)
-save_path = os.path.join(config['save_path'], 'depth')
-
-batch_size = 64
-dataset = Dataset(config, transform)
-data_loader = torch.utils.data.DataLoader(
-    dataset=dataset,
-    batch_size=batch_size,
-    shuffle=False,
-    num_workers=4,
-    pin_memory=True
-)
-
-model, data_loader = accelerator.prepare(model, data_loader)
-
-with torch.no_grad():
-    for i, (test_data, img_path, img_size) in enumerate(tqdm(data_loader)):
-        test_pred = model(test_data)
-
-        for k in range(len(test_pred)):
-            img_path_split = img_path[k].split('/')
-            ps = img_path[k].split('.')[-1]
-            im_save_path = os.path.join(save_path, img_path_split[-3], img_path_split[-2])
-            os.makedirs(im_save_path, exist_ok=True)
-
-            im_size = img_size[0][k].item(), img_size[1][k].item()
-            depth = test_pred[k]
-            depth = (depth - depth.min()) / (depth.max() - depth.min())
-            depth = torch.nn.functional.interpolate(depth.unsqueeze(0).unsqueeze(1), size=(im_size[1], im_size[0]), mode='bilinear', align_corners=True)
-            depth_im = Image.fromarray(255 * depth[0, 0].detach().cpu().numpy()).convert('L')
-            depth_im.save(os.path.join(im_save_path, img_path_split[-1].replace(f'.{ps}', '.png')))
-
-
diff --git a/spaces/simonduerr/metal3d/utils/helpers.py b/spaces/simonduerr/metal3d/utils/helpers.py
deleted file mode 100644
index c45f0b968a52e9cbe8720f93bcfdf65c656ba507..0000000000000000000000000000000000000000
--- a/spaces/simonduerr/metal3d/utils/helpers.py
+++ /dev/null
@@ -1,300 +0,0 @@
-import os
-import multiprocessing
-from multiprocessing import Pool
-from turtle import width
-
-import numpy as np
-
-from moleculekit.molecule import Molecule
-from scipy.spatial import KDTree
-from sklearn.cluster import AgglomerativeClustering
-
-
-def create_grid_fromBB(boundingBox, voxelSize=1):
-    """Create a grid from a bounding box.
-
-    Parameters
-    ----------
-    boundingBox : list
-        List of the form [xmin, xmax, ymin, ymax, zmin, zmax]
-    voxelSize : float
-        Size of the voxels in Angstrom
-
-    Returns
-    -------
-    grid : numpy.ndarray
-        Grid of shape (nx, ny, nz)
-    box_N : numpy.ndarray
-        Number of voxels in each dimension
-
-    """
-    # increase grid by 0.5 to sample everything
-    xrange = np.arange(boundingBox[0][0], boundingBox[1][0] + 0.5, step=voxelSize)
-    yrange = np.arange(boundingBox[0][1], boundingBox[1][1] + 0.5, step=voxelSize)
-    zrange = np.arange(boundingBox[0][2], boundingBox[1][2] + 0.5, step=voxelSize)
-
-    gridpoints = np.zeros((xrange.shape[0] * yrange.shape[0] * zrange.shape[0], 3))
-    i = 0
-    for x in xrange:
-        for y in yrange:
-            for z in zrange:
-                gridpoints[i][0] = x
-                gridpoints[i][1] = y
-                gridpoints[i][2] = z
-                i += 1
-    return gridpoints, (xrange.shape[0], yrange.shape[0], zrange.shape[0])
-
-
-def get_bb(points):
-    """Return bounding box from a set of points (N,3)
-
-    Parameters
-    ----------
-    points : numpy.ndarray
-        Set of points (N,3)
-
-    Returns
-    -------
-    boundingBox : list
-        List of the form [xmin, xmax, ymin, ymax, zmin, zmax]
-
-    """
-    minx = np.min(points[:, 0])
-    maxx = np.max(points[:, 0])
-
-    miny = np.min(points[:, 1])
-    maxy = np.max(points[:, 1])
-
-    minz = np.min(points[:, 2])
-    maxz = np.max(points[:, 2])
-    bb = [[minx, miny, minz], [maxx, maxy, maxz]]
-    return bb
-
-
-def get_all_protein_resids(pdb_file):
-    """Return all protein residues from a pdb file
-
-    Parameters
-    ----------
-    pdb_file : str
-        Path to pdb file
-
-    Returns
-    -------
-    resids : numpy.ndarray
-        indexes of ca atoms
-
-    """
-    try:
-        prot = Molecule(pdb_file)
-    except:
-        exit("could not read file")
-    prot.filter("protein and not hydrogen")
-    return prot.get("index", sel="name CA")
-
-
-def get_all_metalbinding_resids(pdb_file):
-    """Return all metal binding residues from a pdb file
-
-    Parameters
-    ----------
-    pdb_file : str
-        Path to pdb file
-
-    Returns
-    -------
-    resids : numpy.ndarray
-        indexes of name CA that are metal binding
-
-    """
-
-    try:
-        prot = Molecule(pdb_file)
-    except:
-        exit("could not read file")
-    prot.filter("protein and not hydrogen")
-    return prot.get(
-        "index",
-        sel="name CA and resname HIS HID HIE HIP CYS CYX GLU GLH GLN ASP ASH ASN GLN MET",
-    )
-
-
-def get_all_resids_from_list(pdb_file, resids):
-    """Return all metal binding residues from a pdb file
-
-    Parameters
-    ----------
-    pdb_file : str
-        Path to pdb file
-    resids : list
-        id of resids that are metal binding
-
-    Returns
-    -------
-    resids : numpy.ndarray
-        indexes of name CA resids
-
-    """
-
-    try:
-        prot = Molecule(pdb_file)
-    except:
-        exit("could not read file")
-    prot.filter("protein and not hydrogen")
-    return prot.get(
-        "index",
-        sel=f"name CA and resid {resids}",
-    )
-
-
-def compute_average_p_fast(point, cutoff=1):
-    """Using KDTree find the closest gridpoints
-
-    Parameters
-    ----------
-    point : numpy.ndarray
-        Point of shape (3,)
-    cutoff : float
-        Cutoff distance in Angstrom
-
-    Returns
-    -------
-    average_p : numpy.ndarray
-        Average probability of shape (1,)"""
-    p = 0
-    nearest_neighbors, indices = tree.query(
-        point, k=15, distance_upper_bound=cutoff, workers=1
-    )
-    if np.min(nearest_neighbors) != np.inf:
-        p = np.mean(output_v[indices[nearest_neighbors != np.inf]])
-    return p
-
-
-def get_probability_mean(grid, prot_centers, pvalues):
-    """Compute the mean probability of all gridpoints from the globalgrid based on the individual boxes
-
-    Parameters
-    ----------
-    grid : numpy.ndarray
-        Grid of shape (nx, ny, nz)
-    prot_centers : numpy.ndarray
-        Protein centers of shape (N,3)
-    pvalues : numpy.ndarray
-        Probability values of shape (N,1)
-
-    Returns
-    -------
-    mean_p : numpy.ndarray
-        Mean probability over grid of shape (nx, ny, nz)
-    """
-    global output_v
-    output_v = pvalues
-    global prot_v
-    prot_v = prot_centers
-    cpuCount = multiprocessing.cpu_count()
-
-    global tree
-    tree = KDTree(prot_v)
-    p = Pool(cpuCount)
-    results = p.map(compute_average_p_fast, grid)
-    return np.array(results)
-
-
-def write_cubefile(bb, pvalues, box_N, outname="Metal3D_pmap.cube", gridres=1):
-    """Write a cube file from a probability map
-    The cube specification from gaussian is used, distance are converted to bohr
-
-    Parameters
-    ----------
-    bb : list
-        List of the form [xmin, xmax, ymin, ymax, zmin, zmax]
-    pvalues : numpy.ndarray
-        Probability values of shape (nx, ny, nz)
-    box_N : tuple
-        Number of voxels in each dimension
-    outname : str
-        Name of the output file
-    gridres:float
-        Resolution of the grid used for writing the voxels
-
-    """
-
-    with open(outname, "w") as cube:
-        cube.write(" Metal3D Cube File\n")
-        cube.write(" Outer Loop: X, Middle Loop y, inner Loop z\n")
-
-        angstromToBohr = 1.89
-        cube.write(
-            f"    1   {bb[0][0]*angstromToBohr: .6f}  {bb[0][1]*angstromToBohr: .6f}   {bb[0][2]*angstromToBohr: .6f}\n"
-        )
-        cube.write(
-            f"{str(box_N[0]).rjust(5)}    {1.890000*gridres:.9f}    0.000000    0.000000\n"
-        )
-        cube.write(
-            f"{str(box_N[1]).rjust(5)}    0.000000    {1.890000*gridres:.9f}    0.000000\n"
-        )
-        cube.write(
-            f"{str(box_N[2]).rjust(5)}    0.000000    0.000000    {1.890000*gridres:.9f}\n"
-        )
-        cube.write("    1    1.000000    0.000000    0.000000    0.000000\n")
-
-        o = pvalues.reshape(box_N)
-        for x in range(box_N[0]):
-            for y in range(box_N[1]):
-                for z in range(box_N[2]):
-                    cube.write(f" {o[x][y][z]: .5E}")
-                    if z % 6 == 5:
-                        cube.write("\n")
-                cube.write("\n")
-
-
-def find_unique_sites(
-    pvalues, grid, writeprobes=False, probefile="probes.pdb", threshold=5, p=0.75
-):
-    """The probability voxels are points and the voxel clouds may contain multiple metals
-    This function finds the unique sites and returns the coordinates of the unique sites with the highest p for each cluster.
-    It uses the AgglomerativeClustering algorithm to find the unique sites.
-    The threshold is the maximum distance between two points in the same cluster it can be changed to get more metal points.
-
-    Parameters
-    ----------
-    pvalues : numpy.ndarray
-        Probability values of shape (N, 1)
-    grid : numpy.ndarray
-        Grid of shape (N, 3)
-    writeprobes : bool
-        If True, write the probes to a pdb file
-    probefile : str
-        Name of the output file
-    threshold : float
-        Maximum distance between two points in the same cluster
-    p : float
-        Minimum probability of a point to be considered a unique site
-
-    """
-
-    points = grid[pvalues > p]
-    point_p = pvalues[pvalues > p]
-    if len(points) == 0:
-        return "no metals found"
-    clustering = AgglomerativeClustering(
-        n_clusters=None, linkage="complete", distance_threshold=threshold
-    ).fit(points)
-
-    message = f"min metal p={p}, n(metals) found: {clustering.n_clusters_}"
-
-    sites = []
-    for i in range(clustering.n_clusters_):
-        c_points = points[clustering.labels_ == i]
-        c_points_p = point_p[clustering.labels_ == i]
-
-        position = c_points[np.argmax(c_points_p)]
-        sites.append((position, np.max(c_points_p)))
-    if writeprobes:
-        print(f"writing probes to {probefile}")
-        with open(probefile, "w") as f:
-            for i, site in enumerate(sites):
-                f.write(
-                    f"HETATM  {i+1:3} ZN    ZN A {i+1:3}    {site[0][0]: 8.3f}{site[0][1]: 8.3f}{site[0][2]: 8.3f}  {site[1]:.2f}  0.0           ZN2+\n"
-                )
-    return message
diff --git a/spaces/simpie28/VITS-Umamusume-voice-synthesizer/text/shanghainese.py b/spaces/simpie28/VITS-Umamusume-voice-synthesizer/text/shanghainese.py
deleted file mode 100644
index cb29c24a08d2e406e8399cf7bc9fe5cb43cb9c61..0000000000000000000000000000000000000000
--- a/spaces/simpie28/VITS-Umamusume-voice-synthesizer/text/shanghainese.py
+++ /dev/null
@@ -1,64 +0,0 @@
-import re
-import cn2an
-import opencc
-
-
-converter = opencc.OpenCC('zaonhe')
-
-# List of (Latin alphabet, ipa) pairs:
-_latin_to_ipa = [(re.compile('%s' % x[0]), x[1]) for x in [
-    ('A', 'ᴇ'),
-    ('B', 'bi'),
-    ('C', 'si'),
-    ('D', 'di'),
-    ('E', 'i'),
-    ('F', 'ᴇf'),
-    ('G', 'dʑi'),
-    ('H', 'ᴇtɕʰ'),
-    ('I', 'ᴀi'),
-    ('J', 'dʑᴇ'),
-    ('K', 'kʰᴇ'),
-    ('L', 'ᴇl'),
-    ('M', 'ᴇm'),
-    ('N', 'ᴇn'),
-    ('O', 'o'),
-    ('P', 'pʰi'),
-    ('Q', 'kʰiu'),
-    ('R', 'ᴀl'),
-    ('S', 'ᴇs'),
-    ('T', 'tʰi'),
-    ('U', 'ɦiu'),
-    ('V', 'vi'),
-    ('W', 'dᴀbɤliu'),
-    ('X', 'ᴇks'),
-    ('Y', 'uᴀi'),
-    ('Z', 'zᴇ')
-]]
-
-
-def _number_to_shanghainese(num):
-    num = cn2an.an2cn(num).replace('一十','十').replace('二十', '廿').replace('二', '两')
-    return re.sub(r'((?:^|[^三四五六七八九])十|廿)两', r'\1二', num)
-
-
-def number_to_shanghainese(text):
-    return re.sub(r'\d+(?:\.?\d+)?', lambda x: _number_to_shanghainese(x.group()), text)
-
-
-def latin_to_ipa(text):
-    for regex, replacement in _latin_to_ipa:
-        text = re.sub(regex, replacement, text)
-    return text
-
-
-def shanghainese_to_ipa(text):
-    text = number_to_shanghainese(text.upper())
-    text = converter.convert(text).replace('-','').replace('$',' ')
-    text = re.sub(r'[A-Z]', lambda x: latin_to_ipa(x.group())+' ', text)
-    text = re.sub(r'[、；：]', '，', text)
-    text = re.sub(r'\s*，\s*', ', ', text)
-    text = re.sub(r'\s*。\s*', '. ', text)
-    text = re.sub(r'\s*？\s*', '? ', text)
-    text = re.sub(r'\s*！\s*', '! ', text)
-    text = re.sub(r'\s*$', '', text)
-    return text
diff --git a/spaces/simple0urra/skops-model-card-creator-2a23515a-d54e-4804-b365-27ed6e938735/example/Aprende a usar miMind el software de mapas mentales que te ayuda a pensar mejor.md b/spaces/simple0urra/skops-model-card-creator-2a23515a-d54e-4804-b365-27ed6e938735/example/Aprende a usar miMind el software de mapas mentales que te ayuda a pensar mejor.md
deleted file mode 100644
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--- a/spaces/simple0urra/skops-model-card-creator-2a23515a-d54e-4804-b365-27ed6e938735/example/Aprende a usar miMind el software de mapas mentales que te ayuda a pensar mejor.md	
+++ /dev/null
@@ -1,161 +0,0 @@
-<br />
-<h1>Descargar mimind: cómo usar la mejor app para hacer mapas mentales</h1>
-<p>¿Te gustaría organizar tus ideas, proyectos y actividades de una forma visual, creativa y eficaz? ¿Quieres aprender una técnica que te ayude a mejorar tu memoria, comprensión y comunicación? ¿Buscas una herramienta que te permita colaborar con otros de forma sencilla e intuitiva? Si la respuesta es sí, entonces te interesa descargar mimind, la mejor app para hacer mapas mentales.</p>
-<p>En este artículo, te explicaremos qué es mimind, por qué es una app de mapas mentales poderosa y fácil de usar, cómo descargarla en diferentes dispositivos y plataformas, y cómo usarla para crear y compartir tus mapas mentales. Al final, encontrarás una sección de preguntas frecuentes para resolver tus dudas. ¡Empecemos!</p>
-<h2>descargar mimind</h2><br /><p><b><b>Download File</b> &#9193; <a href="https://ssurll.com/2uNYI1">https://ssurll.com/2uNYI1</a></b></p><br /><br />
- <h2>Qué es mimind y por qué es una app de mapas mentales poderosa y fácil de usar</h2>
-<p>Mimind es una app desarrollada por CryptoBees LLC que te permite crear y compartir mapas mentales de forma rápida y sencilla. Un mapa mental es un diagrama que representa visualmente información alrededor de un tema o idea central, usando palabras clave, imágenes, colores y formas. Los mapas mentales son una técnica muy útil para organizar tus pensamientos, planificar tus proyectos, estudiar mejor, resolver problemas, presentar información y mucho más.</p>
- <h3>Qué son los mapas mentales y cuáles son sus beneficios</h3>
-<p>Los mapas mentales fueron popularizados por el educador y escritor Tony Buzan en los años 70, como una forma de aprovechar el potencial del cerebro humano para el aprendizaje y la creatividad. Según Buzan, los mapas mentales imitan la forma en que el cerebro procesa la información, usando asociaciones visuales, lógicas y jerárquicas. Algunos de los beneficios de los mapas mentales son:</p>
-<ul>
-<li>Mejoran la retención y el recuerdo de la información, al usar imágenes, colores y palabras clave que estimulan la memoria.</li>
-<li>Ayudan a aprender nuevos conceptos, al conectarlos con el conocimiento previo y facilitar el aprendizaje significativo.</li>
-<li>Hacen el aprendizaje más atractivo, al crear interacciones profundas con el contenido y permitir la expresión personal.</li>
-<li>Simplifican las relaciones complejas, al organizar las ideas en una estructura fácil de seguir que muestra la jerarquía, las conexiones y el panorama general.</li>
-<li>Incrementan la creatividad, al usar la libertad creativa para organizar el mapa mental y obtener una comprensión más holística de cómo se relaciona todo.</li>
-<li>Aumentan la productividad, al mejorar la eficiencia al comprender y comunicar la información y permitir saltar rápidamente a Continuing the article: diferentes partes del mapa mental.</li>
-<li>Fomentan la colaboración, al permitir compartir los mapas mentales con otros y recibir feedback, sugerencias y aportes.</li>
-</ul>
-<p>Como puedes ver, los mapas mentales son una herramienta muy versátil y poderosa que puedes usar para diversos fines, tanto personales como profesionales. Sin embargo, para aprovechar al máximo sus beneficios, necesitas una app que te facilite el proceso de crear y compartir tus mapas mentales. Aquí es donde entra mimind.</p>
- <h3>Cómo funciona mimind y qué características tiene</h3>
-<p>Mimind es una app que te permite crear mapas mentales de forma intuitiva y divertida, usando tu dispositivo móvil o tu computadora. Mimind tiene una interfaz simple y amigable que te guía paso a paso para crear tu mapa mental, desde el tema central hasta los nodos y ramas más detallados. Además, mimind tiene las siguientes características que la hacen una app de mapas mentales única y destacada:</p>
-<ul>
-<li>Te permite crear mapas mentales ilimitados, sin restricciones de tamaño o complejidad.</li>
-<li>Te ofrece diferentes tipos de mapas mentales, como radiales, de árbol, de organización, de lista y de lógica.</li>
-<li>Te da la opción de personalizar tus mapas mentales con diferentes esquemas de diseño, color y estilo, así como con imágenes, iconos y emojis.</li>
-<li>Te facilita la navegación por tus mapas mentales, con funciones de zoom, desplazamiento, rotación y colapso.</li>
-<li>Te permite exportar tus mapas mentales en diferentes formatos, como PDF, PNG, JPEG, TXT y MM.</li>
-<li>Te ayuda a guardar y sincronizar tus mapas mentales en la nube, usando servicios como Google Drive, Dropbox o OneDrive.</li>
-<li>Te permite compartir tus mapas mentales con otros usuarios de mimind o con otras apps, como WhatsApp, Gmail o Facebook.</li>
-</ul>
-<p>Con todas estas características, mimind se convierte en una app de mapas mentales completa y funcional que te permite crear mapas mentales impresionantes con solo unos pocos toques o clics.</p>
- <h3>Para qué puedes usar mimind y cómo te ayuda a mejorar tu creatividad, productividad y colaboración</h3>
-<p>Mimind es una app de mapas mentales que puedes usar para diferentes propósitos, dependiendo de tus necesidades e intereses. Algunos ejemplos de para qué puedes usar mimind son:</p>
-<p>descargar mimind para pc<br />
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-<ul>
-<li>Para planificar tus proyectos personales o profesionales, definiendo los objetivos, las tareas, los recursos y los plazos.</li>
-<li>Para estudiar mejor cualquier tema o asignatura, resumiendo los conceptos clave, las ideas principales y los detalles relevantes.</li>
-<li>Para resolver problemas o tomar decisiones, analizando las causas, las consecuencias, las alternativas y las soluciones.</li>
-<li>Para presentar información de forma clara y atractiva, usando imágenes, colores y palabras clave que capten la atención del público.</li>
-<li>Para generar ideas creativas para cualquier propósito, usando la lluvia de ideas, el pensamiento lateral o el método SCAMPER.</li>
-<li>Para colaborar con otros en proyectos comunes, compartiendo los mapas mentales y recibiendo feedback, sugerencias y aportes.</li>
-</ul>
-<p>Mimind te ayuda a mejorar tu creatividad, productividad y colaboración al usar los mapas mentales como una herramienta visual que estimula tu pensamiento divergente y convergente. Al crear un mapa mental con mimind, Continuing the article: puedes explorar diferentes posibilidades, asociar diferentes conceptos, organizar diferentes niveles de información y comunicar diferentes mensajes. Mimind te permite usar tu creatividad para crear mapas mentales originales y únicos, tu productividad para crear mapas mentales eficientes y prácticos, y tu colaboración para crear mapas mentales compartidos y enriquecidos.</p>
- <h2>Cómo descargar mimind en diferentes dispositivos y plataformas</h2>
-<p>Mimind es una app que puedes descargar en diferentes dispositivos y plataformas, dependiendo de tu preferencia y comodidad. Mimind está disponible para Windows, Android, iOS y Mac. A continuación, te explicamos cómo descargar mimind en cada uno de estos sistemas operativos.</p>
- <h3>Cómo descargar mimind en Windows</h3>
-<p>Si quieres descargar mimind en tu computadora con Windows, puedes hacerlo de dos formas: desde la tienda de Microsoft o desde el sitio web oficial de mimind. Estos son los pasos que debes seguir en cada caso:</p>
-<ul>
-<li>Desde la tienda de Microsoft: abre la tienda de Microsoft en tu computadora y busca "mimind" en el buscador. Haz clic en el icono de la app y luego en el botón "Obtener". Espera a que se descargue e instale la app y luego ábrela desde el menú de inicio.</li>
-<li>Desde el sitio web oficial de mimind: abre tu navegador web y entra a <a href="">https://mimind.cryptobees.com/</a>. Haz clic en el botón "Descargar" y luego selecciona la opción "Windows". Se descargará un archivo ejecutable que debes abrir para iniciar la instalación. Sigue las instrucciones que aparecen en la pantalla y luego abre la app desde el menú de inicio.</li>
-</ul>
- <h3>Cómo descargar mimind en Android</h3>
-<p>Si quieres descargar mimind en tu dispositivo móvil con Android, puedes hacerlo desde la tienda de Google Play. Estos son los pasos que debes seguir:</p>
-<ul>
-<li>Abre la tienda de Google Play en tu dispositivo y busca "mimind" en el buscador. Haz clic en el icono de la app y luego en el botón "Instalar". Espera a que se descargue e instale la app y luego ábrela desde el menú de aplicaciones.</li>
-</ul>
- <h3>Cómo descargar mimind en iOS y Mac</h3>
-<p>Si quieres descargar mimind en tu dispositivo móvil con iOS o en tu computadora con Mac, puedes hacerlo desde la tienda de App Store. Estos son los pasos que debes seguir:</p>
-<ul>
-<li>Abre la tienda de App Store en tu dispositivo o computadora y busca "mimind" en el buscador. Haz clic en el icono de la app y luego en el botón "Obtener". Espera a que se descargue e instale la app y luego ábrela desde el menú de aplicaciones.</li>
-</ul>
- <h2>Cómo usar mimind para crear y compartir tus mapas mentales</h2>
-<p>Ahora que ya sabes cómo descargar mimind en tu dispositivo o computadora preferida, es hora de aprender cómo usarla para crear y compartir tus mapas mentales. Mimind es una app muy fácil de usar que te guía paso a paso para crear tus mapas mentales. A continuación, te explicamos cómo usar mimind para crear un nuevo mapa mental, añadir nodos, ramas, imágenes y otros elementos, aplicar esquemas de diseño, color y estilo, exportar, guardar y compartir tu mapa mental con otros.</p>
- <h3>Cómo crear un nuevo mapa mental con mimind</h3>
-<p>Para crear un nuevo mapa mental con mimind, debes seguir estos pasos:</p>
-<ol>
-<li>Abre la app de mimind en tu dispositivo o computadora.</li>
-<li>Haz clic en el botón "+ Nuevo mapa mental" que aparece en la parte inferior derecha de la pantalla.</li>
-<li>Escribe el tema o idea central de tu mapa mental en el recuadro que aparece en el centro de la pantalla. Puedes usar una palabra o una frase corta.</li>
-<li>Haz clic en el botón "Crear" que aparece debajo del recuadro. Se creará un nuevo mapa mental con el tema central que has escrito.</li>
-</ol>
- <h3>Cómo añadir nodos, ramas, imágenes y otros elementos a Continuing the article: tu mapa mental</h3>
-<p>Para añadir nodos, ramas, imágenes y otros elementos a tu mapa mental, debes seguir estos pasos:</p>
-<ol>
-<li>Selecciona el nodo al que quieres añadir un subnodo. Un nodo es una palabra o imagen que representa una idea o concepto relacionado con el tema central. Una rama es una línea que conecta un nodo con otro.</li>
-<li>Haz clic en el botón "+ Añadir subnodo" que aparece en la parte inferior izquierda de la pantalla. Se creará un nuevo subnodo vacío conectado al nodo seleccionado.</li>
-<li>Escribe o elige la palabra o imagen que quieres usar para el subnodo. Puedes usar el teclado para escribir o el botón "Imágenes" para buscar y seleccionar una imagen de la galería de mimind o de internet.</li>
-<li>Repite los pasos anteriores para añadir más subnodos al mismo nivel o a niveles inferiores. Puedes crear tantos niveles como quieras, pero se recomienda no exceder de cinco o seis para mantener la claridad y la simplicidad del mapa mental.</li>
-<li>Para editar, mover o eliminar un nodo, haz clic sobre él y usa los botones que aparecen en la parte inferior derecha de la pantalla. Puedes cambiar el texto o la imagen del nodo, cambiar su posición arrastrándolo con el dedo o el ratón, o eliminarlo haciendo clic en el botón "Eliminar".</li>
-</ol>
- <h3>Cómo aplicar esquemas de diseño, color y estilo a tu mapa mental</h3>
-<p>Para aplicar esquemas de diseño, color y estilo a tu mapa mental, debes seguir estos pasos:</p>
-<ol>
-<li>Haz clic en el botón "Diseño" que aparece en la parte superior derecha de la pantalla. Se abrirá un menú con diferentes opciones para personalizar tu mapa mental.</li>
-<li>Elige el tipo de mapa mental que quieres usar. Puedes elegir entre radial, de árbol, de organización, de lista y de lógica. Cada tipo tiene sus ventajas y desventajas dependiendo del propósito y la complejidad de tu mapa mental.</li>
-<li>Elige el esquema de color que quieres usar. Puedes elegir entre varios colores predefinidos o crear tu propio esquema personalizado. Los colores pueden ayudarte a resaltar las ideas más importantes, crear contrastes y armonías, y transmitir emociones y sensaciones.</li>
-<li>Elige el estilo que quieres usar. Puedes elegir entre varios estilos predefinidos o crear tu propio estilo personalizado. Los estilos pueden ayudarte a darle un aspecto más profesional, creativo o divertido a tu mapa mental, usando diferentes tipos de letra, formas y bordes.</li>
-<li>Haz clic en el botón "Aplicar" para guardar los cambios y ver cómo queda tu mapa mental con el nuevo diseño, color y estilo.</li>
-</ol>
- <h3>Cómo exportar, guardar y compartir tu mapa mental con otros</h3>
-<p>Para exportar, guardar y compartir tu mapa mental con otros, debes seguir estos pasos:</p>
-<ol>
-<li>Haz clic en el botón "Exportar" que aparece en la parte superior derecha de la pantalla. Se abrirá un menú con diferentes opciones para exportar tu mapa mental.</li>
-<li>Elige el formato en el que quieres exportar tu mapa mental. Puedes elegir entre PDF, PNG, JPEG, TXT y MM. Cada formato tiene sus ventajas y desventajas dependiendo del uso que le quieras dar a tu mapa mental.</li>
-<li>Elige el destino al que quieres enviar tu mapa mental. Puedes elegir entre guardar tu mapa mental en tu dispositivo o computadora, enviarlo por correo electrónico o compartirlo con otras apps o servicios en línea.</li>
-<li>Haz clic en el botón "Exportar" para confirmar la acción y esperar a que se complete el proceso. Dependiendo del formato y del destino elegidos, puede tardar unos segundos o minutos.</li>
-</ol>
- <h2>Conclusión</h2>
-<p>Mimind es una app para hacer mapas mentales que te permite crear y compartir mapas mentales de forma rápida y sencilla. Mimind tiene una interfaz simple y amigable que te guía paso a paso para crear tus mapas mentales, desde el tema central hasta los nodos y ramas más detallados. Además, mimind tiene las siguientes características que la hacen una app de mapas mentales única y destacada: - Te permite crear mapas mentales ilimitados, sin restricciones de tamaño o complejidad. - Te ofrece diferentes tipos de mapas mentales, como radiales, de árbol, de organización, de lista y de lógica. - Te da la opción de personalizar tus mapas mentales con diferentes esquemas de diseño, color y estilo, así como con imágenes, iconos y emojis. - Te facilita la navegación por tus mapas mentales, con funciones de zoom, desplazamiento, rotación y colapso. - Te permite exportar tus mapas mentales en diferentes formatos, como PDF, PNG, JPEG, TXT y MM. - Te ayuda a guardar y sincronizar tus mapas mentales en la nube, usando servicios como Google Drive, Dropbox o OneDrive. - Te permite compartir tus mapas mentales con otros usuarios de mimind o con otras apps, como WhatsApp, Gmail o Facebook. Mimind es una app de mapas mentales que puedes usar para diferentes propósitos, dependiendo de tus necesidades e intereses. Algunos ejemplos de para qué puedes usar mimind son: - Para planificar tus proyectos personales o profesionales, definiendo los objetivos, las tareas, los recursos y los plazos. - Para estudiar mejor cualquier tema o asignatura, resumiendo los conceptos clave, las ideas principales y los detalles relevantes. - Para resolver problemas o tomar decisiones, analizando las causas, las consecuencias, las alternativas y las soluciones. - Para presentar información de forma clara y atractiva, usando imágenes, colores y palabras clave que capten la atención del público. - Para generar ideas creativas para cualquier propósito, usando la lluvia de ideas, el pensamiento lateral o el método SCAMPER. - Para colaborar con otros en proyectos comunes, compartiendo los mapas mentales y recibiendo feedback, sugerencias y aportes. Mimind te ayuda a mejorar tu creatividad, productividad y colaboración al usar los mapas mentales como una herramienta visual que estimula tu pensamiento divergente y convergente. Al crear un mapa mental con mimind, puedes explorar diferentes posibilidades, asociar diferentes conceptos, organizar diferentes niveles de información y comunicar diferentes mensajes. Mimind te permite usar tu creatividad para crear mapas mentales originales y únicos, tu productividad para crear mapas mentales eficientes y prácticos, y tu colaboración para crear mapas mentales compartidos y enriquecidos. Si quieres descargar mimind en tu dispositivo o computadora preferida, puedes hacerlo desde la tienda de Microsoft, la tienda de Google Play o la tienda de App Store. Mimind está disponible para Windows, Android, iOS y Mac. Mimind es una app muy fácil de usar que te guía paso a paso para crear tus mapas mentales. Solo tienes que escribir el tema central de tu mapa mental, añadir nodos, ramas e imágenes a tu gusto, aplicar esquemas de diseño, color y estilo a tu mapa mental, exportar, guardar y compartir tu mapa mental con otros. Esperamos que este artículo te haya sido útil para conocer más sobre mimind, la mejor app para hacer mapas mentales. Si quieres descargar mimind y empezar a crear tus propios mapas mentales, puedes hacerlo desde los siguientes enlaces: - Para Windows: [Descargar mimind] - Para Android: [Descargar mimind] - Para iOS y Mac: [Descargar mimind] Si tienes alguna duda o comentario sobre mimind, puedes contactarnos a través de nuestro correo electrónico: support@cryptobees.com. Estaremos encantados de atenderte y ayudarte con lo que necesites. <h2>Preguntas frecuentes</h2>
-<p>A continuación, te presentamos algunas preguntas frecuentes sobre mimind y sus respuestas:</p>
-<ol>
-<li>¿Qué es un mapa mental?</li>
-<p>Un mapa mental es un diagrama que representa visualmente información alrededor de un tema o idea central, usando palabras clave, imágenes, colores y formas. Los mapas mentales son una técnica muy útil para organizar tus pensamientos, planificar tus proyectos, estudiar mejor, resolver problemas, presentar información y mucho más.</p>
-<li>¿Qué es mimind?</li>
-<p>Mimind es una app desarrollada por CryptoBees LLC que te permite crear y compartir mapas mentales de forma rápida y sencilla. Mimind tiene una interfaz simple y amigable que te guía paso a paso para crear tu mapa mental, desde el tema central hasta los nodos y ramas más detallados. Además, mimind tiene varias características que la hacen una app de mapas mentales poderosa y fácil de usar.</p>
-<li>¿Para qué puedo usar mimind?</li>
-<p>Mimind es una app de mapas mentales que puedes usar para diferentes propósitos, dependiendo de tus necesidades e intereses. Algunos ejemplos de para qué puedes usar mimind son: para planificar tus proyectos personales o profesionales, para estudiar mejor cualquier tema o asignatura, para resolver problemas o tomar decisiones, para presentar información de forma clara y atractiva, para generar ideas creativas para cualquier propósito, para colaborar con otros en proyectos comunes.</p>
-<li>¿Cómo puedo descargar mimind?</li>
-<p>Mimind es una app que puedes descargar en diferentes dispositivos y plataformas, dependiendo de tu preferencia y comodidad. Mimind está disponible para Windows, Android, iOS y Mac. Puedes descargar mimind desde la tienda de Microsoft, la tienda de Google Play o la tienda de App Store.</p>
-<li>¿Cómo puedo usar mimind?</li>
-<p>Mimind es una app muy fácil de usar que te guía paso a paso para crear tus mapas mentales. Solo tienes que escribir el tema central de tu mapa mental, añadir nodos, ramas e imágenes a tu gusto, aplicar esquemas de diseño, color y estilo a tu mapa mental, exportar, guardar y compartir tu mapa mental con otros.</p>
-</ol></p> 197e85843d<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/siya02/Konakni-TTS/ttsv/scripts/inference/api.sh b/spaces/siya02/Konakni-TTS/ttsv/scripts/inference/api.sh
deleted file mode 100644
index 4f6ce2a2147f69e5b3da851c8222bef830056338..0000000000000000000000000000000000000000
--- a/spaces/siya02/Konakni-TTS/ttsv/scripts/inference/api.sh
+++ /dev/null
@@ -1,8 +0,0 @@
-gender='male'
-glowdir='../../checkpoints/glow/'$gender'/'
-hifidir='../../checkpoints/hifi/'$gender'/'
-device='cpu'
-lang='en'
-
-
-python ../../utils/inference/api.py -a $glowdir -v $hifidir -d $device -L $lang
diff --git a/spaces/siya02/Konakni-TTS/ttsv/src/glow_tts/hifi/models.py b/spaces/siya02/Konakni-TTS/ttsv/src/glow_tts/hifi/models.py
deleted file mode 100644
index aaf911836119d69129abe22aa4fc875f2ba3d53c..0000000000000000000000000000000000000000
--- a/spaces/siya02/Konakni-TTS/ttsv/src/glow_tts/hifi/models.py
+++ /dev/null
@@ -1,403 +0,0 @@
-import torch
-import torch.nn.functional as F
-import torch.nn as nn
-from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
-from torch.nn.utils import weight_norm, remove_weight_norm, spectral_norm
-from .utils import init_weights, get_padding
-
-LRELU_SLOPE = 0.1
-
-
-class ResBlock1(torch.nn.Module):
-    def __init__(self, h, channels, kernel_size=3, dilation=(1, 3, 5)):
-        super(ResBlock1, self).__init__()
-        self.h = h
-        self.convs1 = nn.ModuleList(
-            [
-                weight_norm(
-                    Conv1d(
-                        channels,
-                        channels,
-                        kernel_size,
-                        1,
-                        dilation=dilation[0],
-                        padding=get_padding(kernel_size, dilation[0]),
-                    )
-                ),
-                weight_norm(
-                    Conv1d(
-                        channels,
-                        channels,
-                        kernel_size,
-                        1,
-                        dilation=dilation[1],
-                        padding=get_padding(kernel_size, dilation[1]),
-                    )
-                ),
-                weight_norm(
-                    Conv1d(
-                        channels,
-                        channels,
-                        kernel_size,
-                        1,
-                        dilation=dilation[2],
-                        padding=get_padding(kernel_size, dilation[2]),
-                    )
-                ),
-            ]
-        )
-        self.convs1.apply(init_weights)
-
-        self.convs2 = nn.ModuleList(
-            [
-                weight_norm(
-                    Conv1d(
-                        channels,
-                        channels,
-                        kernel_size,
-                        1,
-                        dilation=1,
-                        padding=get_padding(kernel_size, 1),
-                    )
-                ),
-                weight_norm(
-                    Conv1d(
-                        channels,
-                        channels,
-                        kernel_size,
-                        1,
-                        dilation=1,
-                        padding=get_padding(kernel_size, 1),
-                    )
-                ),
-                weight_norm(
-                    Conv1d(
-                        channels,
-                        channels,
-                        kernel_size,
-                        1,
-                        dilation=1,
-                        padding=get_padding(kernel_size, 1),
-                    )
-                ),
-            ]
-        )
-        self.convs2.apply(init_weights)
-
-    def forward(self, x):
-        for c1, c2 in zip(self.convs1, self.convs2):
-            xt = F.leaky_relu(x, LRELU_SLOPE)
-            xt = c1(xt)
-            xt = F.leaky_relu(xt, LRELU_SLOPE)
-            xt = c2(xt)
-            x = xt + x
-        return x
-
-    def remove_weight_norm(self):
-        for l in self.convs1:
-            remove_weight_norm(l)
-        for l in self.convs2:
-            remove_weight_norm(l)
-
-
-class ResBlock2(torch.nn.Module):
-    def __init__(self, h, channels, kernel_size=3, dilation=(1, 3)):
-        super(ResBlock2, self).__init__()
-        self.h = h
-        self.convs = nn.ModuleList(
-            [
-                weight_norm(
-                    Conv1d(
-                        channels,
-                        channels,
-                        kernel_size,
-                        1,
-                        dilation=dilation[0],
-                        padding=get_padding(kernel_size, dilation[0]),
-                    )
-                ),
-                weight_norm(
-                    Conv1d(
-                        channels,
-                        channels,
-                        kernel_size,
-                        1,
-                        dilation=dilation[1],
-                        padding=get_padding(kernel_size, dilation[1]),
-                    )
-                ),
-            ]
-        )
-        self.convs.apply(init_weights)
-
-    def forward(self, x):
-        for c in self.convs:
-            xt = F.leaky_relu(x, LRELU_SLOPE)
-            xt = c(xt)
-            x = xt + x
-        return x
-
-    def remove_weight_norm(self):
-        for l in self.convs:
-            remove_weight_norm(l)
-
-
-class Generator(torch.nn.Module):
-    def __init__(self, h):
-        super(Generator, self).__init__()
-        self.h = h
-        self.num_kernels = len(h.resblock_kernel_sizes)
-        self.num_upsamples = len(h.upsample_rates)
-        self.conv_pre = weight_norm(
-            Conv1d(80, h.upsample_initial_channel, 7, 1, padding=3)
-        )
-        resblock = ResBlock1 if h.resblock == "1" else ResBlock2
-
-        self.ups = nn.ModuleList()
-        for i, (u, k) in enumerate(zip(h.upsample_rates, h.upsample_kernel_sizes)):
-            self.ups.append(
-                weight_norm(
-                    ConvTranspose1d(
-                        h.upsample_initial_channel // (2 ** i),
-                        h.upsample_initial_channel // (2 ** (i + 1)),
-                        k,
-                        u,
-                        padding=(k - u) // 2,
-                    )
-                )
-            )
-
-        self.resblocks = nn.ModuleList()
-        for i in range(len(self.ups)):
-            ch = h.upsample_initial_channel // (2 ** (i + 1))
-            for j, (k, d) in enumerate(
-                zip(h.resblock_kernel_sizes, h.resblock_dilation_sizes)
-            ):
-                self.resblocks.append(resblock(h, ch, k, d))
-
-        self.conv_post = weight_norm(Conv1d(ch, 1, 7, 1, padding=3))
-        self.ups.apply(init_weights)
-        self.conv_post.apply(init_weights)
-
-    def forward(self, x):
-        x = self.conv_pre(x)
-        for i in range(self.num_upsamples):
-            x = F.leaky_relu(x, LRELU_SLOPE)
-            x = self.ups[i](x)
-            xs = None
-            for j in range(self.num_kernels):
-                if xs is None:
-                    xs = self.resblocks[i * self.num_kernels + j](x)
-                else:
-                    xs += self.resblocks[i * self.num_kernels + j](x)
-            x = xs / self.num_kernels
-        x = F.leaky_relu(x)
-        x = self.conv_post(x)
-        x = torch.tanh(x)
-
-        return x
-
-    def remove_weight_norm(self):
-        print("Removing weight norm...")
-        for l in self.ups:
-            remove_weight_norm(l)
-        for l in self.resblocks:
-            l.remove_weight_norm()
-        remove_weight_norm(self.conv_pre)
-        remove_weight_norm(self.conv_post)
-
-
-class DiscriminatorP(torch.nn.Module):
-    def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=False):
-        super(DiscriminatorP, self).__init__()
-        self.period = period
-        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
-        self.convs = nn.ModuleList(
-            [
-                norm_f(
-                    Conv2d(
-                        1,
-                        32,
-                        (kernel_size, 1),
-                        (stride, 1),
-                        padding=(get_padding(5, 1), 0),
-                    )
-                ),
-                norm_f(
-                    Conv2d(
-                        32,
-                        128,
-                        (kernel_size, 1),
-                        (stride, 1),
-                        padding=(get_padding(5, 1), 0),
-                    )
-                ),
-                norm_f(
-                    Conv2d(
-                        128,
-                        512,
-                        (kernel_size, 1),
-                        (stride, 1),
-                        padding=(get_padding(5, 1), 0),
-                    )
-                ),
-                norm_f(
-                    Conv2d(
-                        512,
-                        1024,
-                        (kernel_size, 1),
-                        (stride, 1),
-                        padding=(get_padding(5, 1), 0),
-                    )
-                ),
-                norm_f(Conv2d(1024, 1024, (kernel_size, 1), 1, padding=(2, 0))),
-            ]
-        )
-        self.conv_post = norm_f(Conv2d(1024, 1, (3, 1), 1, padding=(1, 0)))
-
-    def forward(self, x):
-        fmap = []
-
-        # 1d to 2d
-        b, c, t = x.shape
-        if t % self.period != 0:  # pad first
-            n_pad = self.period - (t % self.period)
-            x = F.pad(x, (0, n_pad), "reflect")
-            t = t + n_pad
-        x = x.view(b, c, t // self.period, self.period)
-
-        for l in self.convs:
-            x = l(x)
-            x = F.leaky_relu(x, LRELU_SLOPE)
-            fmap.append(x)
-        x = self.conv_post(x)
-        fmap.append(x)
-        x = torch.flatten(x, 1, -1)
-
-        return x, fmap
-
-
-class MultiPeriodDiscriminator(torch.nn.Module):
-    def __init__(self):
-        super(MultiPeriodDiscriminator, self).__init__()
-        self.discriminators = nn.ModuleList(
-            [
-                DiscriminatorP(2),
-                DiscriminatorP(3),
-                DiscriminatorP(5),
-                DiscriminatorP(7),
-                DiscriminatorP(11),
-            ]
-        )
-
-    def forward(self, y, y_hat):
-        y_d_rs = []
-        y_d_gs = []
-        fmap_rs = []
-        fmap_gs = []
-        for i, d in enumerate(self.discriminators):
-            y_d_r, fmap_r = d(y)
-            y_d_g, fmap_g = d(y_hat)
-            y_d_rs.append(y_d_r)
-            fmap_rs.append(fmap_r)
-            y_d_gs.append(y_d_g)
-            fmap_gs.append(fmap_g)
-
-        return y_d_rs, y_d_gs, fmap_rs, fmap_gs
-
-
-class DiscriminatorS(torch.nn.Module):
-    def __init__(self, use_spectral_norm=False):
-        super(DiscriminatorS, self).__init__()
-        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
-        self.convs = nn.ModuleList(
-            [
-                norm_f(Conv1d(1, 128, 15, 1, padding=7)),
-                norm_f(Conv1d(128, 128, 41, 2, groups=4, padding=20)),
-                norm_f(Conv1d(128, 256, 41, 2, groups=16, padding=20)),
-                norm_f(Conv1d(256, 512, 41, 4, groups=16, padding=20)),
-                norm_f(Conv1d(512, 1024, 41, 4, groups=16, padding=20)),
-                norm_f(Conv1d(1024, 1024, 41, 1, groups=16, padding=20)),
-                norm_f(Conv1d(1024, 1024, 5, 1, padding=2)),
-            ]
-        )
-        self.conv_post = norm_f(Conv1d(1024, 1, 3, 1, padding=1))
-
-    def forward(self, x):
-        fmap = []
-        for l in self.convs:
-            x = l(x)
-            x = F.leaky_relu(x, LRELU_SLOPE)
-            fmap.append(x)
-        x = self.conv_post(x)
-        fmap.append(x)
-        x = torch.flatten(x, 1, -1)
-
-        return x, fmap
-
-
-class MultiScaleDiscriminator(torch.nn.Module):
-    def __init__(self):
-        super(MultiScaleDiscriminator, self).__init__()
-        self.discriminators = nn.ModuleList(
-            [
-                DiscriminatorS(use_spectral_norm=True),
-                DiscriminatorS(),
-                DiscriminatorS(),
-            ]
-        )
-        self.meanpools = nn.ModuleList(
-            [AvgPool1d(4, 2, padding=2), AvgPool1d(4, 2, padding=2)]
-        )
-
-    def forward(self, y, y_hat):
-        y_d_rs = []
-        y_d_gs = []
-        fmap_rs = []
-        fmap_gs = []
-        for i, d in enumerate(self.discriminators):
-            if i != 0:
-                y = self.meanpools[i - 1](y)
-                y_hat = self.meanpools[i - 1](y_hat)
-            y_d_r, fmap_r = d(y)
-            y_d_g, fmap_g = d(y_hat)
-            y_d_rs.append(y_d_r)
-            fmap_rs.append(fmap_r)
-            y_d_gs.append(y_d_g)
-            fmap_gs.append(fmap_g)
-
-        return y_d_rs, y_d_gs, fmap_rs, fmap_gs
-
-
-def feature_loss(fmap_r, fmap_g):
-    loss = 0
-    for dr, dg in zip(fmap_r, fmap_g):
-        for rl, gl in zip(dr, dg):
-            loss += torch.mean(torch.abs(rl - gl))
-
-    return loss * 2
-
-
-def discriminator_loss(disc_real_outputs, disc_generated_outputs):
-    loss = 0
-    r_losses = []
-    g_losses = []
-    for dr, dg in zip(disc_real_outputs, disc_generated_outputs):
-        r_loss = torch.mean((1 - dr) ** 2)
-        g_loss = torch.mean(dg ** 2)
-        loss += r_loss + g_loss
-        r_losses.append(r_loss.item())
-        g_losses.append(g_loss.item())
-
-    return loss, r_losses, g_losses
-
-
-def generator_loss(disc_outputs):
-    loss = 0
-    gen_losses = []
-    for dg in disc_outputs:
-        l = torch.mean((1 - dg) ** 2)
-        gen_losses.append(l)
-        loss += l
-
-    return loss, gen_losses
diff --git a/spaces/skf15963/summary/fengshen/examples/wenzhong_qa/README.md b/spaces/skf15963/summary/fengshen/examples/wenzhong_qa/README.md
deleted file mode 100644
index 8b424909f39c5b1480fbc5cc7015e82714292930..0000000000000000000000000000000000000000
--- a/spaces/skf15963/summary/fengshen/examples/wenzhong_qa/README.md
+++ /dev/null
@@ -1,75 +0,0 @@
-# <center> yuyuanQA模型finetune
-本示例主要实现了基于GPT2结构的Yuyuan医疗大模型，通过医疗问答对Finetune，使大模型能够有closebook-qa的能力。
-### 数据和模型
-#### 模型：
-finetune的模型是yuyuan模型，余元模型是GPT2的结构，在预训练阶段主要是用PubMed医疗相关的数据集进行的预训练。是一个医疗领域的大模型。模型共有35亿参数，主要参数如下表所示：
-
-|    配置     | 参数  |
-| :---------: | :---: |
-|   nlayers   |  30   |
-|  nheaders   |  32   |
-| hidden-size | 3072  |
-| seq-length  | 1024  |
-
-预训练的数据，主要医疗相关的论文、杂志期刊等，以英文语料为主。
-#### 数据：
-用于finetune的语料是清洗于[MedQuAD](https://github.com/abachaa/MedQuAD)数据集，清洗完成后是下面的格式：
-```text
-......
-{'question':'.........','answer':'........'}
-{'question':'.........','answer':'........'}
-......
-```
-### finetune框架以及参数配置
-#### 框架 ：
-finetune的框架是IDEA研究院CCNL小组整合各大框架的优点开源的[封神框架](https://github.com/IDEA-CCNL/Fengshenbang-LM/tree/main/fengshen)，具体代码可以参考[finetune_medicalQA.py](https://github.com/IDEA-CCNL/Fengshenbang-LM/blob/dev_wzw/fengshen/examples/wenzhong_qa/finetune_medicalQA.py)和[medicalQADataset.py](https://github.com/IDEA-CCNL/Fengshenbang-LM/blob/dev_wzw/fengshen/data/task_dataloader/medicalQADataset.py)。
-#### 训练参数：
-训练参数，我们采用了deepspeed相关的配置，用2个集群的节点共16张A100，在很短的时间内完成了finetune。具体参数配置可以参考[finetune_GPT2_medicalQA.sh](https://github.com/IDEA-CCNL/Fengshenbang-LM/blob/dev_wzw/fengshen/examples/wenzhong_qa/finetune_GPT2_medicalQA.sh)
-### finetune后的效果以及使用
-#### 效果对比：
-finetune后的模型，用100对问答对，基于BLEU分与之前用Magetron框架训练的模型进行了简单的对比，效果比较接近。
-
-unsmoth method:
-| 框架     | 1-gram             | 2-gram             | 3-gram             | 4-gram              |
-| -------- | ------------------ | ------------------ | ------------------ | ------------------- |
-| Fengshen | 0.5241376169070796 | 0.5215762466122144 | 0.4894353584800885 | 0.44840139357073466 |
-| Magetron | 0.5321340489166898 | 0.5110257474778213 | 0.4703745962926368 | 0.4310875933354554  |
-
-smoth method:
-| 框架     | 1-gram            | 2-gram             | 3-gram             | 4-gram             |
-| -------- | ----------------- | ------------------ | ------------------ | ------------------ |
-| Fengshen | 0.717829796617609 | 0.6516910802858905 | 0.5859726677095979 | 0.525510691686505  |
-| Magetron | 0.776190980974117 | 0.6749801211321476 | 0.5897846253142169 | 0.5230773076722481 |
-#### 使用方式：
-支持直接用Haggingface或者pytorch-lightning框架调用。由于在finetune的时候，加入了prompt，在问答的时候，输入应该是："
-`Question:your question about medical? answer:`",接着模型就回以续写的方式回答你的问题。用huggingface的调用代码可以参考下面的代码：
-```python 
-from transformers import GPT2Tokenizer,GPT2LMHeadModel
-model_path = 'pretrained_model_hf/yuyuanQA-v1' # input your own model file path
-model = GPT2LMHeadModel.from_pretrained(model_path)
-tokenizer = GPT2Tokenizer.from_pretrained(model_path)
-model = model.cuda(6) # move your model to the GPU
-model.eval() # just do predict
-
-def answering(question):
-# question = "What should gout patients pay attention to in diet?"
-    inputs = tokenizer(f'Question:{question} answer:',return_tensors='pt').input_ids.to(model.device)
-    
-    generation_output = model.generate(input_ids = inputs,
-                                return_dict_in_generate=True,
-                                output_scores=True,
-                                max_length=150,
-                                # max_new_tokens=80,
-                                do_sample=True,
-                                top_p = 0.9,
-                                eos_token_id=50256,
-                                pad_token_id=0,
-                                num_return_sequences = 5)
-    answers = []
-    for idx,sentence in enumerate(generation_output.sequences):
-        next_sentence = tokenizer.decode(sentence).split('<|endoftext|>')[0]
-        answer = next_sentence.split(sep='answer:',maxsplit=1)[1]
-        answers.append(answer)
-    return answers
-answering('your question?')
-```
\ No newline at end of file
diff --git a/spaces/srikanth-nm/ai_seeker/youtube.py b/spaces/srikanth-nm/ai_seeker/youtube.py
deleted file mode 100644
index f3bf044739a877327267b0293643b69f6b3a7596..0000000000000000000000000000000000000000
--- a/spaces/srikanth-nm/ai_seeker/youtube.py
+++ /dev/null
@@ -1,68 +0,0 @@
-from youtube_transcript_api import YouTubeTranscriptApi
-from youtube_transcript_api.formatters import JSONFormatter
-import json
-import ingest
-import run_localGPT
-import utils
-
-def audio_to_transcript(video_id):
-    sub = YouTubeTranscriptApi.get_transcript(video_id)
-    formatted_subs = JSONFormatter().format_transcript(transcript=sub)
-    with open("transcript.json", "w") as outfile:
-        json.dump(sub, outfile)
-    lstTexts = []
-    for dct in sub:
-        lstTexts.append(dct['text'])
-    strResult = ' '.join(lstTexts)
-    with open('SOURCE_DOCUMENTS/transcript.txt', 'w') as outfile:
-        outfile.write(strResult)
-    transcript = ' '.join(lstTexts)
-
-    utils.calculate_ends('transcript.json','transcript_end.json')
-    utils.create_chunks('transcript_end.json','chunks.json')
-
-    return transcript
-
-def start_training():
-    training_status = ingest.main()
-    return training_status
-
-def replace_substring_and_following(input_string, substring):
-    index = input_string.find(substring)
-    if index != -1:
-        return input_string[:index]
-    else:
-        return input_string
-
-def ask_question(strQuestion):
-    answer = run_localGPT.main(device_type='cpu', strQuery=strQuestion)
-    answer_cleaned = replace_substring_and_following(answer, "Unhelpful Answer")
-    return answer_cleaned
-
-def summarize():
-
-    from langchain.text_splitter import CharacterTextSplitter
-    from langchain.chains.mapreduce import MapReduceChain
-    from langchain.prompts import PromptTemplate
-
-    model_id = "TheBloke/Llama-2-7B-Chat-GGML"
-    model_basename = "llama-2-7b-chat.ggmlv3.q4_0.bin"
-
-    llm = run_localGPT.load_model(device_type='cpu', model_id=model_id, model_basename=model_basename)
-
-    text_splitter = CharacterTextSplitter()
-
-    with open("SOURCE_DOCUMENTS/transcript.txt") as f:
-        file_content = f.read()
-    texts = text_splitter.split_text(file_content)
-
-    from langchain.docstore.document import Document
-
-    docs = [Document(page_content=t) for t in texts]
-
-    from langchain.chains.summarize import load_summarize_chain
-
-    chain = load_summarize_chain(llm, chain_type="map_reduce")
-    summary = chain.run(docs)
-    return summary
-
diff --git a/spaces/starlit7/KorPoliticsTTS/monotonic_align/__init__.py b/spaces/starlit7/KorPoliticsTTS/monotonic_align/__init__.py
deleted file mode 100644
index 40b6f64aa116c74cac2f6a33444c9eeea2fdb38c..0000000000000000000000000000000000000000
--- a/spaces/starlit7/KorPoliticsTTS/monotonic_align/__init__.py
+++ /dev/null
@@ -1,21 +0,0 @@
-from numpy import zeros, int32, float32
-from torch import from_numpy
-
-from .core import maximum_path_jit
-
-
-def maximum_path(neg_cent, mask):
-    """ numba optimized version.
-    neg_cent: [b, t_t, t_s]
-    mask: [b, t_t, t_s]
-    """
-    device = neg_cent.device
-    dtype = neg_cent.dtype
-    neg_cent = neg_cent.data.cpu().numpy().astype(float32)
-    path = zeros(neg_cent.shape, dtype=int32)
-
-    t_t_max = mask.sum(1)[:, 0].data.cpu().numpy().astype(int32)
-    t_s_max = mask.sum(2)[:, 0].data.cpu().numpy().astype(int32)
-    maximum_path_jit(path, neg_cent, t_t_max, t_s_max)
-    return from_numpy(path).to(device=device, dtype=dtype)
-
diff --git a/spaces/stomexserde/gpt4-ui/Examples/Full !FREE!hanumanchalisamp3downloadgulshankumar.md b/spaces/stomexserde/gpt4-ui/Examples/Full !FREE!hanumanchalisamp3downloadgulshankumar.md
deleted file mode 100644
index 43960bee80ce605666d8f710cd9e5754a161e4e7..0000000000000000000000000000000000000000
--- a/spaces/stomexserde/gpt4-ui/Examples/Full !FREE!hanumanchalisamp3downloadgulshankumar.md	
+++ /dev/null
@@ -1,29 +0,0 @@
-
-Here is a possible title and article with HTML formatting for the keyword "fullhanumanchalisamp3downloadgulshankumar":
-
-<h1>How to Download Full Hanuman Chalisa MP3 by Gulshan Kumar</h1>
-<p>Hanuman Chalisa is a devotional hymn dedicated to Lord Hanuman, the monkey god who is a loyal devotee of Lord Rama. Hanuman Chalisa consists of 40 verses that praise the virtues, deeds and powers of Hanuman. It is believed that reciting Hanuman Chalisa can bring blessings, protection and success to the devotees.</p>
-<h2>fullhanumanchalisamp3downloadgulshankumar</h2><br /><p><b><b>Download Zip</b> >>>>> <a href="https://urlgoal.com/2uIanb">https://urlgoal.com/2uIanb</a></b></p><br /><br />
-<p>One of the most popular versions of Hanuman Chalisa is sung by Gulshan Kumar, a famous Indian music producer and singer who was also a devout follower of Hanuman. Gulshan Kumar's rendition of Hanuman Chalisa is melodious, soothing and inspiring. Many people want to download the full Hanuman Chalisa MP3 by Gulshan Kumar to listen to it offline or share it with others.</p>
-<p>If you are one of them, here are some easy steps to download the full Hanuman Chalisa MP3 by Gulshan Kumar:</p>
-<ol>
-<li>Go to YouTube and search for "Hanuman Chalisa I GULSHAN KUMAR I HARIHARAN, Full HD Video I Shree Hanuman Chalisa" [^3^]. This is the official video uploaded by T-Series Bhakti Sagar, the music label that owns the rights to Gulshan Kumar's Hanuman Chalisa.</li>
-<li>Copy the URL of the video from the address bar or right-click on the video and select "Copy video URL".</li>
-<li>Go to an online YouTube to MP3 converter website, such as ytmp3.cc or y2mate.com. Paste the URL of the video in the input box and click on "Convert" or "Start".</li>
-<li>Wait for a few seconds until the conversion is done. Then click on "Download" or "Save as" to save the MP3 file on your device.</li>
-<li>Enjoy listening to the full Hanuman Chalisa MP3 by Gulshan Kumar anytime and anywhere.</li>
-</ol>
-<p>Note: This method is for personal use only. Please do not distribute or upload the MP3 file without permission from the original owner.</p>Here is a possible continuation of the article:
-
-<p>Some benefits of listening to the full Hanuman Chalisa MP3 by Gulshan Kumar are:</p>
-<p></p>
-<ul>
-<li>It can help you feel calm and relaxed, as the soothing voice of Gulshan Kumar and the rhythmic music create a peaceful atmosphere.</li>
-<li>It can boost your confidence and courage, as the verses of Hanuman Chalisa describe how Hanuman overcame various obstacles and challenges with his strength and devotion.</li>
-<li>It can inspire you to be loyal and faithful, as the hymn praises Hanuman's unwavering service and love for Lord Rama and his companions.</li>
-<li>It can protect you from negative influences and evil forces, as the hymn invokes Hanuman's power and grace to ward off any harm or danger.</li>
-<li>It can increase your devotion and gratitude, as the hymn expresses the glory and blessings of Lord Hanuman and his role in the epic Ramayana.</li>
-</ul>
-<p>Therefore, listening to the full Hanuman Chalisa MP3 by Gulshan Kumar can be a great way to enrich your spiritual life and connect with your inner self.</p> 7196e7f11a<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/stomexserde/gpt4-ui/Examples/How To Turn T-Mobile OnePlus 7 Pro Into Global Version Davjavoa _HOT_.md b/spaces/stomexserde/gpt4-ui/Examples/How To Turn T-Mobile OnePlus 7 Pro Into Global Version Davjavoa _HOT_.md
deleted file mode 100644
index 8c2f52082b6cbd7edcf69ca467b2b8e4bbebea7d..0000000000000000000000000000000000000000
--- a/spaces/stomexserde/gpt4-ui/Examples/How To Turn T-Mobile OnePlus 7 Pro Into Global Version Davjavoa _HOT_.md	
+++ /dev/null
@@ -1,27 +0,0 @@
-
-<h1>How To Turn T-Mobile OnePlus 7 Pro Into Global Version davjavoa</h1>
-<p>If you have a T-Mobile OnePlus 7 Pro, you might be wondering how to turn it into a global version that can receive faster updates, support dual SIM cards, and access the latest OxygenOS beta versions. In this article, we will show you how to do that without waiting for a SIM unlock from T-Mobile or unlocking your bootloader.</p>
-<p>The T-Mobile OnePlus 7 Pro is a great device, but it comes with some drawbacks compared to the global version. For example, it has a single SIM slot, slower updates, and no access to the OxygenOS beta program. The global version, on the other hand, has a dual SIM slot, faster updates, and access to the OxygenOS beta program. The global version also has more features and customization options in the OxygenOS software.</p>
-<h2>How To Turn T-Mobile OnePlus 7 Pro Into Global Version davjavoa</h2><br /><p><b><b>Download File</b> &raquo; <a href="https://urlgoal.com/2uI8e3">https://urlgoal.com/2uI8e3</a></b></p><br /><br />
-<p>Fortunately, there is a way to turn your T-Mobile OnePlus 7 Pro into a global version without waiting for a SIM unlock from T-Mobile or unlocking your bootloader. This means you can keep your warranty intact and avoid breaking Google Play support or HD streaming from Netflix and Hulu. All you need is a Windows PC, a USB cable, and some files that we will provide you.</p>
-<h2>Steps to turn your T-Mobile OnePlus 7 Pro into a global version</h2>
-<p>Before you proceed, make sure you backup all of your important files on your phone, as this process will wipe your phone. Also, make sure you have at least 50% battery on your phone and PC. This process will not provide you with a T-Mobile SIM unlock either and will not unlock your bootloader for you.</p>
-<ol>
-<li>Download both of these archives and extract them to a folder you can locate. <a href="https://drive.google.com/file/d/1q3g6y0z5X9Z8L4aZxJl0xQFbQ4wYwYfM/view?usp=sharing">Archive 1</a> <a href="https://drive.google.com/file/d/1q3g6y0z5X9Z8L4aZxJl0xQFbQ4wYwYfM/view?usp=sharing">Archive 2</a>. The encryption keys for archive 1 and archive 2 are below.</li>
-<li>Open the MSM tool and uncheck the box next to SHA 256.</li>
-<li>Hold both volume buttons on your OnePlus 7 Pro for 5 seconds, then plug in the USB cable.</li>
-<li>Watch the running MSM tool on your computer. Once it says "Connected" next to one of the COM ports, press START.</li>
-<li>Do not unplug your device until it says "success" on screen.</li>
-<li>You now have international firmware!</li>
-</ol>
-<p>Archive 1 decryption key: 836tI3vZa3ixi9487IpxNEw-I5RGT3QjJXmm0dGYLcI</p>
-<p>Archive 2 decryption key: ezLIQmIL9j7OQV1qcvJtof8M0pCHYY_nC9W4pDaw3is</p>
-<h2>Benefits of turning your T-Mobile OnePlus 7 Pro into a global version</h2>
-<p>By turning your T-Mobile OnePlus 7 Pro into a global version, you can enjoy many benefits that are not available on the T-Mobile version. Some of these benefits are:</p>
-<ul>
-<li>Faster updates: The global version receives updates faster than the T-Mobile version. For example, the global version already has the camera improvements that were rolled out a week ago, while the T-Mobile version still doesn't have them.</li>
-<li>Dual SIM support: The global version has a dual SIM slot that can support two SIM cards at the same time. This is useful if you travel frequently or want to use two different carriers. You will need to buy a new SIM tray that has two slots for this feature to work.</li>
-<li>OxygenOS beta program: The global version can access the OxygenOS beta program that allows you to test new features and improvements before they are released to the public. You can also provide feedback and suggestions to OnePlus through this program.</li>
-<li>More features and customization</p> e93f5a0c3f<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/stomexserde/gpt4-ui/Examples/INTEL COMPUTE STICK (STCK1A32WFC) Product Info Zip.md b/spaces/stomexserde/gpt4-ui/Examples/INTEL COMPUTE STICK (STCK1A32WFC) Product Info Zip.md
deleted file mode 100644
index 192dc8ce809e5649427e868fbba56e9db97a20f8..0000000000000000000000000000000000000000
--- a/spaces/stomexserde/gpt4-ui/Examples/INTEL COMPUTE STICK (STCK1A32WFC) Product Info Zip.md	
+++ /dev/null
@@ -1,36 +0,0 @@
-<br />
-<h1>INTEL COMPUTE STICK (STCK1A32WFC) Product Info Zip: A Portable PC for Any Screen</h1>
-<p>Have you ever wished you could turn any monitor or TV into a fully functional PC? With the INTEL COMPUTE STICK (STCK1A32WFC) product info zip, you can do just that. This device is a tiny computer that plugs into the HDMI port of any screen and lets you run Windows 10 or Linux on it. You can use it for web browsing, streaming, gaming, productivity, and more.</p>
-<h2>INTEL COMPUTE STICK (STCK1A32WFC) product info zip</h2><br /><p><b><b>DOWNLOAD</b> &#9989; <a href="https://urlgoal.com/2uIbMi">https://urlgoal.com/2uIbMi</a></b></p><br /><br />
-<p>The INTEL COMPUTE STICK (STCK1A32WFC) product info zip is powered by an Intel Atom Z3735F processor, 2 GB of RAM, and 32 GB of eMMC storage. It also has Wi-Fi, Bluetooth, a USB port, and a micro SD card slot for expansion. It comes with a power adapter and an HDMI extender cable for easy setup.</p>
-<p>The INTEL COMPUTE STICK (STCK1A32WFC) product info zip is ideal for anyone who wants a portable PC that can fit in their pocket. You can use it at home, in the office, in a hotel room, or anywhere else where there is a screen and a power outlet. You can also customize it with your own apps and settings, and access your files and data from the cloud.</p>
-<p>If you are interested in buying the INTEL COMPUTE STICK (STCK1A32WFC) product info zip, you can download the product information sheet from the link below. It contains all the specifications, features, and benefits of this device. You can also check out the customer reviews and ratings to see what others think of it.</p>
-<p>The INTEL COMPUTE STICK (STCK1A32WFC) product info zip is a great way to enjoy the power and convenience of a PC on any screen. Whether you want to watch movies, play games, work on documents, or browse the web, this device can handle it all. Order yours today and experience the magic of a portable PC.</p>
-<p></p>
-<a href="https://downloadcenter.intel.com/download/25506/Intel-Compute-Stick-STCK1A32WFC">Download INTEL COMPUTE STICK (STCK1A32WFC) Product Info Zip</a>
-
-<h2>How to Use the INTEL COMPUTE STICK (STCK1A32WFC) Product Info Zip</h2>
-<p>Using the INTEL COMPUTE STICK (STCK1A32WFC) product info zip is very easy and simple. All you need to do is follow these steps:</p>
-<ol>
-<li>Plug the device into the HDMI port of your monitor or TV.</li>
-<li>Connect the power adapter to the device and a power outlet.</li>
-<li>Turn on your monitor or TV and select the HDMI input.</li>
-<li>Follow the on-screen instructions to set up Windows 10 or Linux on your device.</li>
-<li>Connect a wireless keyboard and mouse to the device via Bluetooth or USB.</li>
-<li>Enjoy your portable PC.</li>
-</ol>
-<p>You can also use the HDMI extender cable to adjust the position of the device if needed. You can also use a micro SD card to increase the storage capacity of the device if needed.</p>
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-<h2>Why Choose the INTEL COMPUTE STICK (STCK1A32WFC) Product Info Zip</h2>
-<p>There are many reasons why you should choose the INTEL COMPUTE STICK (STCK1A32WFC) product info zip over other similar devices. Here are some of them:</p>
-<ul>
-<li>It is powered by Intel, a trusted and reliable brand in the computing industry.</li>
-<li>It has a sleek and compact design that can fit in your pocket or bag.</li>
-<li>It has a low power consumption and a fanless design that makes it quiet and energy-efficient.</li>
-<li>It has a high performance and a smooth operation that can handle various tasks and applications.</li>
-<li>It has a flexible and versatile functionality that can work with any screen and any operating system.</li>
-<li>It has a reasonable and affordable price that gives you great value for your money.</li>
-</ul>
-<p>The INTEL COMPUTE STICK (STCK1A32WFC) product info zip is a smart and innovative device that can transform any screen into a PC. It is a perfect solution for anyone who wants a portable PC that can do it all. Don't miss this opportunity and get yours today.</p> cec2833e83<br />
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\ No newline at end of file
diff --git a/spaces/sub314xxl/MetaGPT/examples/search_with_specific_engine.py b/spaces/sub314xxl/MetaGPT/examples/search_with_specific_engine.py
deleted file mode 100644
index 4423011e48daa6bebd00bbff62414108b8f8a1c9..0000000000000000000000000000000000000000
--- a/spaces/sub314xxl/MetaGPT/examples/search_with_specific_engine.py
+++ /dev/null
@@ -1,23 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-"""
-@Modified By: mashenquan, 2023-8-9, fix-bug: cannot find metagpt module.
-"""
-import asyncio
-from pathlib import Path
-import sys
-sys.path.append(str(Path(__file__).resolve().parent.parent))
-from metagpt.roles import Searcher
-from metagpt.tools import SearchEngineType
-
-
-async def main():
-    # Serper API
-    #await Searcher(engine = SearchEngineType.SERPER_GOOGLE).run(["What are some good sun protection products?","What are some of the best beaches?"])
-    # SerpAPI
-    #await Searcher(engine=SearchEngineType.SERPAPI_GOOGLE).run("What are the best ski brands for skiers?")
-    # Google API
-    await Searcher(engine=SearchEngineType.DIRECT_GOOGLE).run("What are the most interesting human facts?")
-
-if __name__ == '__main__':
-    asyncio.run(main())
diff --git a/spaces/sub314xxl/image-server-1/style.css b/spaces/sub314xxl/image-server-1/style.css
deleted file mode 100644
index 86ce68e49778375ebf5b12dc3baaccf931570b54..0000000000000000000000000000000000000000
--- a/spaces/sub314xxl/image-server-1/style.css
+++ /dev/null
@@ -1,16 +0,0 @@
-h1 {
-  text-align: center;
-}
-
-#duplicate-button {
-  margin: auto;
-  color: #fff;
-  background: #1565c0;
-  border-radius: 100vh;
-}
-
-#component-0 {
-  max-width: 730px;
-  margin: auto;
-  padding-top: 1.5rem;
-}
diff --git a/spaces/sunshineatnoon/TextureScraping/libs/train_base.py b/spaces/sunshineatnoon/TextureScraping/libs/train_base.py
deleted file mode 100644
index 567fbd8cf150155ba416d6ca53df5b849adfeca9..0000000000000000000000000000000000000000
--- a/spaces/sunshineatnoon/TextureScraping/libs/train_base.py
+++ /dev/null
@@ -1,230 +0,0 @@
-"""Training base class
-"""
-import torchvision.transforms as transforms
-import torchvision.utils as vutils
-import torch.backends.cudnn as cudnn
-import torch.nn.functional as F
-import torch.fft
-import torch
-
-import numpy as np
-import argparse
-import wandb
-import math
-import time
-import os
-from . import flow_transforms
-
-class TrainerBase():
-    def __init__(self, args):
-        """
-        Initialization function.
-        """
-        cudnn.benchmark = True
-
-        os.environ['WANDB_DIR'] = args.work_dir
-        args.use_wandb = (args.use_wandb == 1)
-
-        if args.use_wandb:
-            wandb.login(key="d56eb81cd6396f0a181524ba214f488cf281e76b")
-            wandb.init(project=args.project_name, name=args.exp_name)
-            wandb.config.update(args)
-
-        self.mean_values = torch.tensor([0.411, 0.432, 0.45]).view(1, 3, 1, 1).cuda()
-        self.color_palette = np.loadtxt('data/palette.txt',dtype=np.uint8).reshape(-1,3)
-
-        self.args = args
-
-    def init_dataset(self):          
-        """
-        Initialize dataset
-        """
-        if self.args.dataset == 'BSD500':
-            from ..data import BSD500
-            # ==========  Data loading code ==============
-            input_transform = transforms.Compose([
-                flow_transforms.ArrayToTensor(),
-                transforms.Normalize(mean=[0,0,0], std=[255,255,255]),
-                transforms.Normalize(mean=[0.411,0.432,0.45], std=[1,1,1])
-            ])
-
-            val_input_transform = transforms.Compose([
-                flow_transforms.ArrayToTensor(),
-                transforms.Normalize(mean=[0, 0, 0], std=[255, 255, 255]),
-                transforms.Normalize(mean=[0.411, 0.432, 0.45], std=[1, 1, 1])
-            ])
-
-            target_transform = transforms.Compose([
-                flow_transforms.ArrayToTensor(),
-            ])
-
-            co_transform = flow_transforms.Compose([
-                    flow_transforms.RandomCrop((self.args.train_img_height , self.args.train_img_width)),
-                    flow_transforms.RandomVerticalFlip(),
-                    flow_transforms.RandomHorizontalFlip()
-            ])
-            print("=> loading img pairs from '{}'".format(self.args.data))
-            train_set, val_set = BSD500(self.args.data,
-                                        transform=input_transform,
-                                        val_transform = val_input_transform,
-                                        target_transform=target_transform,
-                                        co_transform=co_transform,
-                                        bi_filter=True)
-            print('{} samples found, {} train samples and {} val samples '.format(len(val_set)+len(train_set), len(train_set), len(val_set)))
-
-            self.train_loader = torch.utils.data.DataLoader(
-                                train_set, batch_size=self.args.batch_size,
-                                num_workers=self.args.workers, pin_memory=True, shuffle=True, drop_last=True)
-        elif self.args.dataset == 'texture':
-            from ..data.texture_v3 import Dataset
-            dataset = Dataset(self.args.data_path, crop_size=self.args.train_img_height)
-            self.train_loader = torch.utils.data.DataLoader(dataset     = dataset,
-                                                            batch_size  = self.args.batch_size,
-                                                            shuffle     = True,
-                                                            num_workers = self.args.workers,
-                                                            drop_last   = True)
-        elif self.args.dataset == 'DIV2K':
-            from basicsr.data import create_dataloader, create_dataset
-            opt = {}
-            opt['dist'] = False
-            opt['phase'] = 'train'
-
-            opt['name'] = 'DIV2K'
-            opt['type'] = 'PairedImageDataset'
-            opt['dataroot_gt'] = self.args.HR_dir
-            opt['dataroot_lq'] = self.args.LR_dir
-            opt['filename_tmpl'] = '{}'
-            opt['io_backend'] = dict(type='disk')
-
-            opt['gt_size'] = self.args.train_img_height
-            opt['use_flip'] = True
-            opt['use_rot'] = True
-
-            opt['use_shuffle'] = True
-            opt['num_worker_per_gpu'] = self.args.workers
-            opt['batch_size_per_gpu'] = self.args.batch_size
-            opt['scale'] = int(self.args.ratio)
-
-            opt['dataset_enlarge_ratio'] = 1
-            dataset = create_dataset(opt)
-            self.train_loader = create_dataloader(
-            dataset, opt, num_gpu=1, dist=opt['dist'], sampler=None)
-        else:
-            raise ValueError("Unknown dataset: {}.".format(self.args.dataset))
-    
-    def init_training(self):
-        self.init_constant()
-        self.init_dataset()
-        self.define_model()
-        self.define_criterion()
-        self.define_optimizer()
-    
-    def adjust_learning_rate(self, iteration):
-        """Sets the learning rate to the initial LR decayed by 10 every 30 epochs"""
-        lr = self.args.lr * (0.95 ** (iteration // self.args.lr_decay_freq))
-        for param_group in self.optimizer.param_groups:
-            param_group['lr'] = lr
-    
-    def logging(self, iteration, epoch):
-        print_str = "[{}/{}][{}/{}], ".format(iteration, len(self.train_loader), epoch, self.args.nepochs)
-        for k,v in self.losses.items():
-            print_str += "{}: {:4f} ".format(k, v)
-        print_str += "time: {:2f}.".format(self.iter_time)
-        print(print_str)
-
-    def get_sp_grid(self, H, W, G, R = 1):
-        W = int(W // R)
-        H = int(H // R)
-        if G > min(H, W):
-            raise ValueError('Grid size must be smaller than image size!')
-        grid = torch.from_numpy(np.arange(G**2)).view(1, 1, G, G)
-        grid = torch.cat([grid]*(int(math.ceil(W/G))), dim = -1)
-        grid = torch.cat([grid]*(int(math.ceil(H/G))), dim = -2)
-        grid = grid[:, :, :H, :W]
-        return grid.float()
-    
-    def save_network(self, name = None):
-        cpk = {}
-        cpk['epoch'] = self.epoch
-        cpk['lr'] = self.optimizer.param_groups[0]['lr']
-        if hasattr(self.model, 'module'):
-            cpk['model'] = self.model.module.cpu().state_dict()
-        else:
-            cpk['model'] = self.model.cpu().state_dict()
-        if name is None:
-            out_path = os.path.join(self.args.out_dir, "cpk.pth")
-        else:
-            out_path = os.path.join(self.args.out_dir, name + ".pth")
-        torch.save(cpk, out_path)
-        self.model.cuda()
-        return
-    
-    def init_constant(self):
-        return
-
-    def define_model(self):
-        raise NotImplementedError
-    
-    def define_criterion(self):
-        raise NotImplementedError
-    
-    def define_optimizer(self):
-        raise NotImplementedError
-
-    def display(self):
-        raise NotImplementedError
-    
-    def forward(self):
-        raise NotImplementedError
-    
-    def train(self):
-        args = self.args
-        total_iteration = 0
-        for epoch in range(args.nepochs):
-            self.epoch = epoch
-            for iteration, data in enumerate(self.train_loader):
-                if args.dataset == 'BSD500':
-                    image = data[0].cuda()
-                    self.label = data[1].cuda()
-                elif args.dataset == 'texture':
-                    image = data[0].cuda()
-                    self.image2 = data[1].cuda()
-                else:
-                    image = data['lq'].cuda()
-                    self.gt = data['gt'].cuda()
-                start_time = time.time()
-                total_iteration += 1
-                self.optimizer.zero_grad()
-                image = image.cuda()
-                if args.dataset == 'BSD500':
-                    self.image = image + self.mean_values
-                    self.gt = self.image
-                else:
-                    self.image = image
-                self.forward()
-                total_loss = 0
-                for k,v in self.losses.items():
-                    if hasattr(args, '{}_wt'.format(k)):
-                        total_loss += v * getattr(args, '{}_wt'.format(k))
-                    else:
-                        total_loss += v
-                total_loss.backward()
-                self.optimizer.step()
-                end_time = time.time()
-                self.iter_time = end_time - start_time
-            
-                self.adjust_learning_rate(total_iteration)
-            
-                if((iteration + 1) % args.log_freq == 0):
-                    self.logging(iteration, epoch)
-                    if args.use_wandb:
-                        wandb.log(self.losses)
-            
-                if(iteration % args.display_freq == 0):
-                    example_images = self.display()
-                    if args.use_wandb:
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diff --git a/spaces/terfces0erbo/CollegeProjectV2/Dynasty Warriors 6 Pc Free Download Full Version.md b/spaces/terfces0erbo/CollegeProjectV2/Dynasty Warriors 6 Pc Free Download Full Version.md
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diff --git a/spaces/terfces0erbo/CollegeProjectV2/How To Change Serial Number On Kindle 21.md b/spaces/terfces0erbo/CollegeProjectV2/How To Change Serial Number On Kindle 21.md
deleted file mode 100644
index 1a38590ef67d580a030e1ec8fd00ae0d747a961c..0000000000000000000000000000000000000000
--- a/spaces/terfces0erbo/CollegeProjectV2/How To Change Serial Number On Kindle 21.md	
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-<h1>How to Change Serial Number on Kindle 21</h1>
-
-<p>Do you have a Kindle 21 that you want to change its serial number? Maybe you bought a used one that has been blacklisted by Amazon, or maybe you want to switch to a different Amazon account with your device. Whatever your reason, changing the serial number on your Kindle 21 is not a simple or straightforward process. In fact, it is not officially supported by Amazon and it might void your warranty or cause other issues with your device. Therefore, you should only attempt this at your own risk and after doing some research and preparation.</p>
-
-<p>In this article, we will show you how to change the serial number on your Kindle 21 using some tools and methods that have been reported to work by some users. However, we cannot guarantee that they will work for you or that they will not harm your device in any way. So, proceed with caution and follow the steps carefully.</p>
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-<h2>Step 1: Find Your Current Serial Number</h2>
-
-<p>The first step to change the serial number on your Kindle 21 is to find out what your current serial number is. You will need this information later when you generate a new serial number or when you contact Amazon customer service. There are two ways to find your current serial number: on your device or on the Amazon website.</p>
-
-<p>To find your current serial number on your device, follow these steps:</p>
-
-<ul>
-<li>Wake up your Kindle 21 and access the toolbar at the top.</li>
-<li>Open the Settings by tapping Settings (gear icon) in the toolbar and picking All Settings or tapping the Menu button (three dots) on the top right and selecting Settings.</li>
-<li>Choose Device Options.</li>
-<li>Pick Device Info.</li>
-<li>Under Serial Number, you will see the serial number of your Kindle 21. You can write it down or take a screenshot of it for future reference.</li>
-</ul>
-
-<p>To find your current serial number on the Amazon website, follow these steps:</p>
-
-<ul>
-<li>Sign into your Amazon account and open the Accounts & Lists drop-down menu at the top.</li>
-<li>Pick Your Content and Devices.</li>
-<li>At the top, select the Devices tab.</li>
-<li>Click the icon for your Kindle 21.</li>
-<li>You will see your Kindle 21 serial number among the other details listed below its name. You can write it down or copy it for future reference.</li>
-</ul>
-
-<h2>Step 2: Generate a New Serial Number</h2>
-
-<p>The next step to change the serial number on your Kindle 21 is to generate a new serial number that is valid and compatible with your device and Amazon account. There are different ways to do this, but one of the most common and reliable ones is to use a tool called Kindle Serial Number Generator (KSN). This tool can create a random serial number for any Kindle model based on some parameters that you enter. You can download this tool from <a href="https://www.mobileread.com/forums/showthread.php?t=267516">this link</a>.</p>
-
-<p>To generate a new serial number using KSN, follow these steps:</p>
-
-<ul>
-<li>Download and unzip the KSN tool on your computer.</li>
-<li>Run the KSN.exe file as administrator.</li>
-<li>Select your Kindle model from the drop-down menu. For Kindle 21, choose Kindle Paperwhite (10th Generation).</li>
-<li>Select your country or region from the drop-down menu. This will affect the first two letters of your new serial number.</li>
-<li>Select whether you want a Wi-Fi only or Wi-Fi + Cellular device from the drop-down menu. This will affect the third letter of your new serial number.</li>
-<li>Select whether you want a black or white device from the drop-down menu. This will affect the fourth letter of your new serial number.</li>
-<li>Select whether you want a special offers or no special offers device from the drop-down menu. This will affect the fifth letter of your new serial number.</li>
-<li>Click Generate Serial Number.</li>
-<li>You will see a new serial number in the box below. You can write it down or copy it for future use.</li>
-</ul>
-
-<h2>Step 3: Change Your Serial Number on Your Device</h2>
-
-<p>The final step to change the serial number on your Kindle 21 is to actually apply the new serial number to your device. This is the most difficult and risky part of the process, as it involves modifying some system files on your device that could potentially brick it if done incorrectly. Therefore, you should make sure that you have backed up all your data and settings before proceeding with this step. You should also make sure that your device is fully charged and connected to a power source during this step.</p>
-<p></p>
-
-<p>To change your serial number on your device, follow these steps:</p>
-
-<ul>
-<li>Connect your Kindle 21 to your computer using a USB cable.</li>
-<li>Open File Explorer on your computer and navigate to the root directory of your Kindle 21 (usually named Kindle).</li>
-<li>Create a backup copy of all files and folders in this directory by copying them to another location on your computer or an external drive.</li>
-<li>Open Notepad on your computer and create a new text file named ENABLE_DIAGS (no extension).</li>
-<li>Save this file in the root directory of your Kindle 21.</li>
-<li>Eject and disconnect your Kindle 21 from your computer.</li>
-<li>Restart your Kindle 21 by holding down the power button for about 40 seconds until it turns off and then turns back on again.</li>
-<li>Your Kindle 21 will boot into diagnostics mode, which is a special mode that allows you to perform various tests and changes on your device.</li>
-<li>Navigate to Utilities > Enable USBnet using the touch screen or buttons on your device.</li>
-<li>Select Enable USBnet again when prompted.</li>
-<li>Your device will display a message saying USBnet enabled successfully.</li>
-<li>Connect your Kindle 21 back to your computer using a USB cable.</li>
-<li>Your computer should recognize it as a network adapter rather than a storage device.</li>
-<li>Open Command Prompt on your computer as administrator.</li>
-<li>Type ipconfig /all and press Enter.</li>
-<li>You should see some information about various network adapters on your computer, including one named RNDIS/Ethernet Gadget (or similar).</li>
-<li>Note down the IPv4 address of this adapter (usually something like 192.168.x.x).</li>
-<li>Type ping <IPv4 address> and press Enter (replace <IPv4 address> with the actual address you noted down).</li>
-<li>You should see some replies from this address indicating that there is a connection between your computer and device.</li>
-<li>Type telnet <IPv4 address> and press Enter (replace <IPv4 address> with the actual address you noted down).</li>
-
-<ol start="20">
-    <strong>Note:</strong> If</p>
-<h2>Step 4: Restore Your Device to Normal Mode</h2>
-
-<p>After changing the serial number on your Kindle 21, you need to restore your device to normal mode and remove the files and settings that you used for this process. This will prevent any conflicts or errors with your device or Amazon account in the future.</p>
-
-<p>To restore your device to normal mode, follow these steps:</p>
-
-<ul>
-<li>Connect your Kindle 21 to your computer using a USB cable.</li>
-<li>Open File Explorer on your computer and navigate to the root directory of your Kindle 21 (usually named Kindle).</li>
-<li>Delete the file named ENABLE_DIAGS that you created earlier.</li>
-<li>Eject and disconnect your Kindle 21 from your computer.</li>
-<li>Restart your Kindle 21 by holding down the power button for about 40 seconds until it turns off and then turns back on again.</li>
-<li>Your Kindle 21 will boot into normal mode, which is the mode that you use for reading and accessing Amazon services.</li>
-</ul>
-
-<h2>Step 5: Register Your Device with Amazon</h2>
-
-<p>The final step to change the serial number on your Kindle 21 is to register your device with Amazon using your new serial number. This will allow you to access all the features and benefits that Amazon offers to Kindle users, such as downloading books, syncing your reading progress, receiving updates, and more.</p>
-
-<p>To register your device with Amazon, follow these steps:</p>
-
-<ul>
-<li>Wake up your Kindle 21 and access the toolbar at the top.</li>
-<li>Open the Settings by tapping Settings (gear icon) in the toolbar and picking All Settings or tapping the Menu button (three dots) on the top right and selecting Settings.</li>
-<li>Choose Your Account.</li>
-<li>Pick Register Your Kindle.</li>
-<li>Enter your Amazon account email address and password and tap Register.</li>
-<li>Your device will display a message saying Registration Successful. You can now use your Kindle 21 with your Amazon account.</li>
-</ul>
-
-<h2>Conclusion</h2>
-
-<p>Changing the serial number on your Kindle 21 is not a common or recommended procedure, but it might be necessary or useful in some situations. However, it is also a risky and complicated process that could damage your device or cause other problems if done incorrectly. Therefore, you should only try this at your own risk and after doing some research and preparation. We hope this article has helped you understand how to change the serial number on your Kindle 21 using some tools and methods that have been reported to work by some users. However, we cannot guarantee that they will work for you or that they will not harm your device in any way. So, proceed with caution and follow the steps carefully.</p>
-<h2>Conclusion</h2>
-
-<p>Changing the serial number on your Kindle 21 is not a common or recommended procedure, but it might be necessary or useful in some situations. However, it is also a risky and complicated process that could damage your device or cause other problems if done incorrectly. Therefore, you should only try this at your own risk and after doing some research and preparation. We hope this article has helped you understand how to change the serial number on your Kindle 21 using some tools and methods that have been reported to work by some users. However, we cannot guarantee that they will work for you or that they will not harm your device in any way. So, proceed with caution and follow the steps carefully.</p> 3cee63e6c2<br />
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diff --git a/spaces/thejagstudio/procom/amazon/admin.py b/spaces/thejagstudio/procom/amazon/admin.py
deleted file mode 100644
index 8c38f3f3dad51e4585f3984282c2a4bec5349c1e..0000000000000000000000000000000000000000
--- a/spaces/thejagstudio/procom/amazon/admin.py
+++ /dev/null
@@ -1,3 +0,0 @@
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diff --git a/spaces/tialenAdioni/chat-gpt-api/logs/Best UCI Chess Engines Download Discover the Secrets of the Worlds Strongest Chess Players.md b/spaces/tialenAdioni/chat-gpt-api/logs/Best UCI Chess Engines Download Discover the Secrets of the Worlds Strongest Chess Players.md
deleted file mode 100644
index 42920befd6f6ae6436674d0e94c89b6fda60b42c..0000000000000000000000000000000000000000
--- a/spaces/tialenAdioni/chat-gpt-api/logs/Best UCI Chess Engines Download Discover the Secrets of the Worlds Strongest Chess Players.md	
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-<h1>Best UCI Chess Engines Download: A Guide for Chess Enthusiasts</h1>
- <p>If you love playing chess and want to take your game to the next level, you might be interested in downloading some of the best UCI chess engines available. But what are UCI chess engines and why are they useful? In this article, we will explain what UCI chess engines are, how to install and use them, and what are some of the top UCI chess engines to download in 2023. We will also give you some tips on how to improve your chess skills with UCI chess engines. So, let's get started!</p>
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- <p>UCI stands for Universal Chess Interface, which is a standard protocol that allows different chess programs to communicate with each other. A UCI chess engine is a program that can calculate the best moves in a given position, based on a set of parameters such as depth, time, and evaluation function. A UCI chess engine does not have a graphical user interface (GUI) of its own, so it needs another program that can display the board and the moves. This program is called a chess GUI.</p>
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- <p>To use a UCI chess engine, you need to follow these steps:</p>
- <h4>Step 1: Download a UCI-compatible chess GUI</h4>
- <p>A chess GUI is a program that allows you to play chess on your computer, either against another human or against a computer opponent. There are many chess GUIs available for free or for a fee, but not all of them support UCI chess engines. Some of the most popular UCI-compatible chess GUIs are:</p>
- <ul>
-<li><a href="https://arena.chessdom.com/">Arena</a>: A free and open-source chess GUI that supports multiple languages and multiple engines.</li>
-<li><a href="https://chessx.sourceforge.io/">ChessX</a>: A free and open-source chess GUI that supports multiple formats and databases.</li>
-<li><a href="https://www.playwitharena.de/">Play With Arena</a>: A free and easy-to-use chess GUI that supports online play and tournaments.</li>
-<li><a href="https://www.chessbase.com/">ChessBase</a>: A commercial and professional chess GUI that supports analysis, training, and database management.</li>
-<li><a href="https://www.fritzshop.com/en/fritz-17.html">Fritz</a>: A commercial and popular chess GUI that supports online play, coaching, and puzzles.</li>
-</ul>
- <p>You can download any of these chess GUIs from their official websites and install them on your computer.</p>
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- <h4>Step 2: Download one or more UCI chess engines</h4>
- <p>A UCI chess engine is a program that can calculate the best moves in a given position, based on a set of parameters such as depth, time, and evaluation function. A UCI chess engine does not have a graphical user interface (GUI) of its own, so it needs another program that can display the board and the moves. This program is called a chess GUI.</p>
- <p>There are hundreds of UCI chess engines available for free or for a fee, but some of them are better than others. Some of the factors that affect the quality of a UCI chess engine are:</p>
- <ul>
-<li>The strength of the engine: How well it can play against other engines or human players.</li>
-<li>The style of the engine: How aggressive or defensive it plays, how creative or conventional it is, how much it relies on opening books or endgame tables.</li>
-<li>The compatibility of the engine: How well it works with different chess GUIs and operating systems.</li>
-<li>The availability of the engine: How easy it is to download and install the engine.</li>
-</ul>
- <p>In the next section, we will introduce some of the top UCI chess engines to download in 2023.</p>
- <h4>Step 3: Configure the chess GUI to use the UCI chess engines</h4>
- <p>Once you have downloaded and installed both a chess GUI and one or more UCI chess engines, you need to configure the chess GUI to use the UCI chess engines. The exact steps may vary depending on the specific chess GUI you are using, but in general, you need to do the following:</p>
- <ol>
-<li>Open the chess GUI and go to the settings or options menu.</li>
-<li>Select the option to add or manage engines.</li>
-<li>Browse your computer for the folder where you saved the UCI chess engine files (usually .exe files).</li>
-<li>Select one or more UCI chess engine files and add them to the list of available engines.</li>
-<li>Choose one of the added engines as your default engine or select an engine for each side (white or black).</li>
-<li>Adjust the settings of each engine according to your preferences (such as time control, skill level, opening book, etc.).</li>
-<li>Save your changes and exit the settings menu.</li>
-</ol>
- <p>Now you are ready to use your chosen UCI chess engine(s) with your chosen chess GUI. You can play against them, analyze your games with them, or watch them play against each other.</p>
- <h2>Top 5 UCI Chess Engines to Download in 2023</h2>
- <p>In this section, we will introduce some of the top UCI chess engines to download in 2023. These are based on our own opinion and experience, as well as on various sources such as ratings, reviews, and popularity. Of course, there are many other excellent UCI chess engines out there, so feel free to explore them on your own. Here are our top 5 picks:</p>
- <h3>Stockfish</h3>
- <p><a href="https://stockfishchess.org/">Stockfish</a> is one of the strongest and most popular UCI chess engines in the world. It is a free and open-source project that is constantly updated by a community of developers and testers. It uses advanced techniques such as alpha-beta pruning, bitboards, and neural networks to achieve incredible speed and accuracy. It can run on any platform that supports C++11, and it has several versions for different hardware configurations, such as Stockfish NNUE (which uses neural network technology) and Stockfish for Android (which runs on mobile devices).</p>
- <p>Stockfish is known for its aggressive and dynamic style, as well as for its deep understanding of complex positions. It can play any opening and any endgame, and it has access to large databases of opening books and endgame tables. It can also learn from its own games and improve over time. Stockfish is widely used by professional and amateur players alike, as well as by online platforms such as <a href="https://lichess.org/">Lichess</a>.</p>
- <h3>Komodo</h3>
- <p><a href="https://komodochess.com/">Komodo</a> is another strong and popular UCI chess engine that has been around since 2007. It is a commercial product that costs $99 for a lifetime license, but it also has a free version called Komodo MCTS (which uses Monte Carlo tree search technology). It runs on Windows, Linux, and Mac OS X, and it has several versions for different hardware configurations, such as Komodo Dragon (which uses neural network technology) and Komodo for Android (which runs on mobile devices).</p>
- <p>Komodo is known for its balanced and positional style, as well as for its high level of optimization and efficiency. Article with HTML formatting (continued): opening and any endgame, and it has access to large databases of opening books and endgame tables. It can also learn from its own games and improve over time. Komodo is widely used by professional and amateur players alike, as well as by online platforms such as <a href="https://www.chess.com/">Chess.com</a>.</p>
- <h3>Leela Chess Zero</h3>
- <p><a href="https://lczero.org/">Leela Chess Zero</a> is a unique and innovative UCI chess engine that is based on the same principles as <a href="https://deepmind.com/research/case-studies/alphago-the-story-so-far">AlphaGo</a>, the program that defeated the world champion of Go in 2016. It is a free and open-source project that is powered by a distributed network of volunteers who donate their computing resources to train the engine. It uses deep learning and reinforcement learning to learn from its own games and improve over time. It runs on any platform that supports CUDA or OpenCL, and it has several versions for different hardware configurations, such as Leela Chess Zero CPU (which runs on CPUs) and Leela Chess Zero GPU (which runs on GPUs).</p>
- <p>Leela Chess Zero is known for its creative and human-like style, as well as for its remarkable intuition and understanding of complex positions. It can play any opening and any endgame, and it has access to large databases of opening books and endgame tables. It can also learn from other sources of data, such as human games or other engines. Leela Chess Zero is widely used by professional and amateur players alike, as well as by online platforms such as <a href="https://chess24.com/en">Chess24</a>.</p>
- <h3>Fire</h3>
- <p><a href="https://www.chess2u.com/t15612-fire-8-0-download">Fire</a> is a strong and fast UCI chess engine that has been around since 2010. It is a commercial product that costs $40 for a lifetime license, but it also has a free version called FireBird (which is slightly weaker than Fire). It runs on Windows, Linux, and Mac OS X, and it has several versions for different hardware configurations, such as Fire NNUE (which uses neural network technology) and Fire for Android (which runs on mobile devices).</p>
- <p>Fire is known for its aggressive and tactical style, as well as for its high level of parallelism and scalability. It can play any opening and any endgame, and it has access to large databases of opening books and endgame tables. It can also learn from its own games and improve over time. Fire is widely used by professional and amateur players alike, as well as by online platforms such as <a href="https://www.chessbomb.com/">ChessBomb</a>.</p>
- <h3>Ethereal</h3>
- <p><a href="https://github.com/AndyGrant/Ethereal">Ethereal</a> is a strong and modern UCI chess engine that has been around since 2016. It is a free and open-source project that is constantly updated by a community of developers and testers. It uses advanced techniques such as alpha-beta pruning, bitboards, and neural networks to achieve incredible speed and accuracy. It runs on any platform that supports C++17, and it has several versions for different hardware configurations, such as Ethereal NNUE (which uses neural network technology) and Ethereal for Android (which runs on mobile devices).</p>
- <p>Ethereal is known for its balanced and solid style, as well as for its deep understanding of complex positions. It can play any opening and any endgame, and it has access to large databases of opening books and endgame tables. It can also learn from its own games and improve over time. Ethereal is widely used by professional and amateur players alike, as well as by online platforms such as <a href="https://tcec-chess.com/">TCEC</a>.</p>
- <h2>How to Improve Your Chess Skills with UCI Chess Engines</h2>
- <p>Using UCI chess engines can be very beneficial for your chess improvement, if you use them wisely. Here are some tips on how to improve your chess skills with UCI chess engines:</p>
- <h4>Analyze your games with UCI chess engines</h4>
- <p>One of the best ways to learn from your mistakes and improve your understanding of chess is to analyze your games with UCI chess engines. You can do this by loading your games into your chess GUI and running one or more UCI chess engines on them. You can then see where you made blunders, mistakes, or inaccuracies, and what were the best moves in each position. You can also compare your moves with the moves of the UCI chess engine(s), and try to understand why they are better or worse. You can also use the UCI chess engine(s) to check your analysis and find new ideas or variations.</p>
- <p>However, you should not blindly trust the UCI chess engine(s), or rely on them too much. You should always try to think for yourself, and use your own logic and intuition. You should also remember that UCI chess engines are not perfect, and sometimes they can miss subtle points or make mistakes themselves. You should always verify their suggestions with your own calculations and knowledge.</p>
- <h4>Play against UCI chess engines at different levels</h4>
- <p>Another way to improve your chess skills with UCI chess engines is to play against them at different levels. You can do this by setting the skill level or the time control of the UCI chess engine(s) according to your own level or preference. You can then challenge yourself to beat them or at least draw them in a fair match.</p>
- <p>Playing against UCI chess engines at different levels can help you practice your openings, tactics, strategy, endgames, and time management. You can also learn from their moves and style, and try to emulate them or counter them. You can also test your own ideas or variations against them, and see how they react.</p>
- <p>However, you should not play against UCI chess engines too often, or only against UCI chess engines. You should also play against human opponents, either online or offline, as they have different strengths and weaknesses, and they can pose different challenges and opportunities. You should also remember that playing against UCI chess engines is not the same as playing against humans, as they have different psychology and emotions.</p>
- <h4>Study chess openings and endgames with UCI chess engines</h4>
- <p>A third way to improve your chess skills with UCI chess engines is to study chess openings and endgames with them. You can do this by loading opening or endgame positions into your chess GUI and running one or more UCI chess engine(s) on them. You can then see what are the best moves in each position, what are the main lines or variations, what are the typical plans or ideas, what are the common traps or pitfalls, etc.</p>
- <p>Studying chess openings and endgames with UCI chess engines can help you expand your repertoire, deepen your knowledge, sharpen your skills, avoid mistakes, find novelties, etc. You can also use the UCI chess engine(s) to check your opening or endgame books or databases, and find new information or corrections.</p>
- <p>However, you should not study chess openings or endgames only with UCI chess engines. You should also study them with other sources, such as books, videos, articles, etc., as they can provide more explanations, examples, history, theory, etc. You should also remember that UCI chess engines are not always right, and sometimes they can miss nuances or subtleties.</p>
- <h2>Conclusion</h2>
- <p>In conclusion, UCI chess engines are powerful tools that can help you improve your chess skills, if you use them wisely. They can calculate the best moves in any position, play against you at different levels, analyze your games with you, study chess openings or endgames with you, etc. However, you should not rely on them too much, or trust them blindly. You should always think for yourself, use your own logic and intuition, verify their suggestions with your own calculations and knowledge, play against human opponents as well, study with other sources as well.</p>
- <p>If you are interested in downloading some of the best UCI chess engines available in 2023, we recommend you to try Stockfish, Komodo, Leela Chess Zero, Fire, or Ethereal. They are all strong, fast, compatible, and available for free or for a fee. You can download them from their official websites or from other sources online.</p>
- <p>We hope you enjoyed this article and learned something new about UCI chess engines. Now it's time for you to download your favorite UCI  chess engine today  and start playing better chess!</p>
- <h2>Frequently Asked Questions</h2>
- <ol>
-<li><b>What is the difference between a UCI  Article with HTML formatting (continued): and a chess GUI?</b></li>
-<p>A UCI chess engine is a program that can calculate the best moves in a given position, based on a set of parameters such as depth, time, and evaluation function. A UCI chess engine does not have a graphical user interface (GUI) of its own, so it needs another program that can display the board and the moves. This program is called a chess GUI. A chess GUI is a program that allows you to play chess on your computer, either against another human or against a computer opponent. A chess GUI can also support multiple UCI chess engines, and allow you to switch between them or use them together.</p>
-<li><b>What are some of the advantages and disadvantages of using UCI chess engines?</b></li>
-<p>Some of the advantages of using UCI chess engines are:</p>
-<ul>
-<li>They can help you improve your chess skills by playing against you, analyzing your games, studying chess openings or endgames, etc.</li>
-<li>They can provide you with objective and accurate evaluations and suggestions in any position.</li>
-<li>They can play any opening and any endgame, and have access to large databases of opening books and endgame tables.</li>
-<li>They can learn from their own games and improve over time.</li>
-<li>They can run on any platform that supports UCI protocol, and work with any UCI-compatible chess GUI.</li>
-</ul>
-<p>Some of the disadvantages of using UCI chess engines are:</p>
-<ul>
-<li>They can make you lazy or dependent on them, and reduce your own thinking and creativity.</li>
-<li>They can sometimes miss subtle points or make mistakes themselves, especially in positions that require intuition or understanding rather than calculation.</li>
-<li>They can have different styles and preferences, and sometimes disagree with each other or with human experts.</li>
-<li>They can be expensive or difficult to download or install, depending on the specific UCI chess engine you choose.</li>
-</ul>
-<li><b>How can I choose the best UCI chess engine for me?</b></li>
-<p>There is no definitive answer to this question, as different UCI chess engines may suit different players or purposes. However, some of the factors that you may consider when choosing a UCI chess engine are:</p>
-<ul>
-<li>The strength of the engine: How well it can play against other engines or human players.</li>
-<li>The style of the engine: How aggressive or defensive it plays, how creative or conventional it is, how much it relies on opening books or endgame tables.</li>
-<li>The compatibility of the engine: How well it works with different chess GUIs and operating systems.</li>
-<li>The availability of the engine: How easy it is to download and install the engine.</li>
-<li>The cost of the engine: How much it costs to buy or use the engine.</li>
-</ul>
-<p>You can also try different UCI chess engines yourself, and see which one you like best or suits your needs best. You can also read reviews or ratings from other users or experts online, and see what they think about different UCI chess engines.</p>
- <li><b>How can I download and install a UCI chess engine?</b></li>
-<p>The exact steps may vary depending on the specific UCI chess engine you choose, but in general, you need to do the following:</p>
- <ol>
-<li>Go to the official website of the UCI chess engine you want to download, or find another source online that offers it for download.</li>
-<li>Select the version that matches your hardware configuration and operating system, and click on the download link or button.</li>
-<li>Save the file (usually .exe file) to your computer, and unzip it if necessary.</li>
-<li>Open your chess GUI and go to the settings or options menu.</li>
-<li>Select the option to add or manage engines.</li>
-<li>Browse your computer for the folder where you saved the UCI chess engine file (usually .exe file).</li>
-<li>Select the UCI chess engine file and add it to the list of available engines.</li>
-<li>Adjust the settings of the engine according to your preferences (such as time control, skill level, opening book, etc.).</li>
-<li>Save your changes and exit the settings menu.</li>
-</ol>
- <p>Now you are ready to use your chosen UCI chess engine with your chosen chess GUI. You can play against it, analyze your games with it, or watch it play against other engines.</p>
- <li><b>How can I update my UCI chess engine?</b></li>
- <p>If you want to update your UCI chess engine to a newer version, you need to do the following:</p>
- <ol>
- <li>Go to the official website of the UCI chess engine you want to update, or find another source online that offers it for download.</li>
- <li>Select the latest version that matches your hardware configuration and operating system, and click on the download link or button.</li>
- <li>Save the file (usually .exe file) to your computer, and unzip it if necessary.</li>
- <li>Delete or rename the old version of the UCI chess engine file (usually .exe file) on your computer, and replace it with the new version of the UCI chess engine file (usually .exe file).</li>
- <li>Open your chess GUI and go to the settings or options menu.</li>
- <li>Select the option to add or manage engines.</li>
- <li>Browse your computer for the folder where you saved the new version of the UCI chess engine file (usually .exe file).</li>
- <li>Select the new version of the UCI chess engine file and add it to the list of available engines, or replace the old version of the UCI chess engine file with the new version of the UCI chess engine file in  the list of available engines.</li>
- <li>Adjust  the settings  of  the new version  of  the UCI  chess engine  according  to  your preferences  (such as time control, skill level, opening book, etc.).</li>
- <li>Save  your changes  and exit  the settings menu.</li>
- </ol>
- <p>Now  you are ready  to use  the new version  of  your chosen  UCI  chess engine  with  your chosen  chess GUI. You can play against it, analyze your games with it, or watch it play against other engines.</p>
- </ol>
- </p> 0a6ba089eb<br />
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diff --git a/spaces/tialenAdioni/chat-gpt-api/logs/Cyberlink Youcam Crack The Ultimate Guide to Downloading and Using It on Windows 10.md b/spaces/tialenAdioni/chat-gpt-api/logs/Cyberlink Youcam Crack The Ultimate Guide to Downloading and Using It on Windows 10.md
deleted file mode 100644
index 0c4db1d038a740dfdd77ba03a4c54fc7bde9f090..0000000000000000000000000000000000000000
--- a/spaces/tialenAdioni/chat-gpt-api/logs/Cyberlink Youcam Crack The Ultimate Guide to Downloading and Using It on Windows 10.md	
+++ /dev/null
@@ -1,24 +0,0 @@
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diff --git a/spaces/tialenAdioni/chat-gpt-api/logs/Epson L3110 Resetter How to Reset Your Printers Waste Ink Counter in Minutes.md b/spaces/tialenAdioni/chat-gpt-api/logs/Epson L3110 Resetter How to Reset Your Printers Waste Ink Counter in Minutes.md
deleted file mode 100644
index 835cb944f4c80edd99969aa5e4710f0a84d9cd6c..0000000000000000000000000000000000000000
--- a/spaces/tialenAdioni/chat-gpt-api/logs/Epson L3110 Resetter How to Reset Your Printers Waste Ink Counter in Minutes.md	
+++ /dev/null
@@ -1,19 +0,0 @@
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-<img src="https://www.resetepson.org/wp-content/uploads/2019/11/Epson-L3110-Resetter-Tool-Window.jpg" alt="Epson L3110 Resetter Tool Window">
-<p>You need to click on the "Select" button at the top right corner of the window. This will open another window where you need to choose your printer model and port. You need to select "L3100/L3101/L3110/L3150" from</p> ddb901b051<br />
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diff --git a/spaces/tialenAdioni/chat-gpt-api/logs/HD Online Player (B.A. Pass - 2 telugu movie download ) Where to find the movie online for free.md b/spaces/tialenAdioni/chat-gpt-api/logs/HD Online Player (B.A. Pass - 2 telugu movie download ) Where to find the movie online for free.md
deleted file mode 100644
index e53f5aaa013f5b07698755b8ad8711635527046b..0000000000000000000000000000000000000000
--- a/spaces/tialenAdioni/chat-gpt-api/logs/HD Online Player (B.A. Pass - 2 telugu movie download ) Where to find the movie online for free.md	
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@@ -1,69 +0,0 @@
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-<p>B.A. Pass 2 is a 2017 Indian drama film that follows the story of a young woman who moves to Mumbai to pursue her dreams of becoming an actress, but faces many challenges and hardships along the way. The film is a sequel to the 2013 film B.A. Pass, which was based on a short story by Mohan Sikka.</p>
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diff --git a/spaces/tialenAdioni/chat-gpt-api/logs/How to Find and Download the Right Pegatron N14939 Drivers for Your PC.md b/spaces/tialenAdioni/chat-gpt-api/logs/How to Find and Download the Right Pegatron N14939 Drivers for Your PC.md
deleted file mode 100644
index b23ca291985692c10bc48057dd9121b38e5c7bf6..0000000000000000000000000000000000000000
--- a/spaces/tialenAdioni/chat-gpt-api/logs/How to Find and Download the Right Pegatron N14939 Drivers for Your PC.md	
+++ /dev/null
@@ -1,191 +0,0 @@
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-how to contact support for pegatron n14939 driver problems</p>
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-<p>Here are the steps to download Pegatron N14939 driver manually:</p>
-
-<ol>
-<li>Go to the official website of Pegatron Corporation at <a href="https://www.pegatroncorp.com/">https://www.pegatroncorp.com/</a></li>
-<li>Find the support or download section and look for your Pegatron N14939 device model</li>
-<li>Select the appropriate driver for your operating system and download it to your PC</li>
-<li>Open the downloaded file and follow the on-screen instructions to install the driver on your PC</li>
-<li>Restart your PC to apply the changes</li>
-</ol>
-
-<h3>Method 2: Download Pegatron N14939 Driver Automatically</h3>
-
-<p>If you want to save time and hassle, you can use a reliable driver update utility to download Pegatron N14939 driver automatically. A driver update utility is a software tool that scans your PC for outdated, missing, or corrupted drivers and updates them with the latest versions. It also backs up your drivers before updating them, so you can restore them if anything goes wrong.</p>
-
-<p>One of the best driver update utilities that you can use is DriverGuide.com. DriverGuide.com is a trusted website that has been providing drivers for various devices since 1996. It has a large database of over 3 million drivers from over 1600 manufacturers. It also offers a free scan feature that allows you to check your PC for driver issues.</p>
-
-<p>To use DriverGuide.com to download Pegatron N14939 driver automatically, you need to follow these steps:</p>
-
-<ol>
-<li>Go to the website of DriverGuide.com at <a href="https://www.driverguide.com/">https://www.driverguide.com/</a></li>
-<li>Click on the "Scan Now" button and wait for the scan to complete</li>
-<li>Review the scan results and click on the "Download" button next to the Pegatron N14939 driver that you need</li>
-<li>Follow the on-screen instructions to install the driver on your PC</li>
-<li>Restart your PC to apply the changes</li>
-</ol>
-
-<p>Note: You need to register an account on DriverGuide.com to download drivers. You can also upgrade to a premium membership for more features and benefits.</p>
-
-<h2>How to Install Pegatron N14939 Driver</h2>
-
-<p>After downloading Pegatron N14939 driver, you need to install it on your PC using a built-in utility called Device Manager. Device Manager is a tool that allows you to see all of the devices recognized by your system and the drivers associated with them. You can use Device Manager to install, update, uninstall, or disable drivers on your PC.</p>
-
-<p>To install Pegatron N14939 driver using Device Manager, you need to follow these steps:</p>
-
-<ol>
-<li>Open Device Manager by right-clicking on the Start menu and selecting Device Manager</li>
-<li>Find your Pegatron N14939 device under the appropriate category (such as Printer, Scanner, Video, Network, etc.) and right-click on it</li>
-<li>Select "Update driver" or "Install driver" from the menu</li>
-<li>Browse to the location where you saved the downloaded driver file and select it</li>
-<li>Follow the on-screen instructions to complete the installation process</li>
-<li>Restart your PC to apply the changes</li>
-</ol>
-
-<h2>How to Troubleshoot Common Driver Problems</h2>
-
-<p>Sometimes, even after installing Pegatron N14939 driver, you may still encounter some driver problems. Here are some common driver problems and how to fix them:</p>
-
-<ul>
-<li>If your Pegatron N14939 device is not recognized by your PC, you may need to check the connection between your device and PC. Make sure that your device is properly plugged in and powered on. You may also need to try a different USB port or cable.</li>
-<li>If your Pegatron N14939 device is not working properly or causing errors on your PC, you may need to uninstall and reinstall the driver. To do this, go to Device Manager, right-click on your device, and select "Uninstall device". Then, restart your PC and reinstall the driver using one of the methods above.</li>
-<li>If your Pegatron N14939 device is conflicting with other devices or software on your PC, you may need to update or disable the conflicting devices or software. To do this, go to Device Manager, right-click on the conflicting device or software, and select "Update driver" or "Disable device". Then, restart your PC and check if the problem is resolved.</li>
-</ul>
-
-<p>If none of these solutions work, you may need to contact Pegatron Corporation or a professional technician for further assistance.</p>
-
-<h2>How to Optimize Your PC for Better Performance</h2>
-
-<p>Besides installing Pegatron N14939 driver, there are some other things that you can do
-to optimize your PC for better performance, such as:</p>
-
-<ul>
-<li>Clean up your disk space by deleting unnecessary files and programs</li>
-<li>Defragment your disk by rearranging fragmented files into contiguous blocks</li>
-<li>Scan your PC for viruses and malware by using a reputable antivirus software</li>
-<li>Update your operating system and other software by installing the latest patches and updates</li>
-<li>Tweak your system settings by adjusting the power options, visual effects, startup programs, etc.</li>
-</ul>
-
-<p>By doing these things regularly, you can keep your PC running smoothly and efficiently.</p>
-
-<h2>Conclusion</h2>
-
-<p>Pegatron N14939 is a device that allows you to connect your computer to various peripherals. To ensure its optimal performance and compatibility with your operating system, you need to download and install the correct driver for it. You can download and install Pegatron N14939 driver manually or automatically using one of the methods above. You can also troubleshoot common driver problems and optimize your PC for better performance by following our tips.</p>
-
-<p>We hope this article has helped you learn how
-to download and install Pegatron N14939 driver for Windows. If you have any questions or suggestions,
-please feel free
-to leave a comment below.</p>
-<h2>How to Use Pegatron N14939 Device</h2>
-
-<p>After installing Pegatron N14939 driver, you can use your device to perform various tasks on your PC. Depending on the type of your device, you can use it to print documents, scan images, capture photos, access the internet, and more. Here are some examples of how to use Pegatron N14939 device:</p>
-
-<ul>
-<li>If your device is a printer, you can use it to print documents from your PC. To do this, open the document that you want to print and click on the "Print" button or press Ctrl+P. Then, select your Pegatron N14939 printer from the list of available printers and adjust the settings as needed. Click on the "Print" button again to start printing.</li>
-<li>If your device is a scanner, you can use it to scan images from your PC. To do this, connect your Pegatron N14939 scanner to your PC and turn it on. Then, open the scanning software that came with your scanner or use a third-party software such as Windows Fax and Scan. Click on the "Scan" button or press Ctrl+S. Then, select your Pegatron N14939 scanner from the list of available scanners and adjust the settings as needed. Click on the "Scan" button again to start scanning.</li>
-<li>If your device is a camera, you can use it to capture photos from your PC. To do this, connect your Pegatron N14939 camera to your PC and turn it on. Then, open the camera software that came with your camera or use a third-party software such as Windows Camera. Click on the "Capture" button or press Ctrl+C. Then, select your Pegatron N14939 camera from the list of available cameras and adjust the settings as needed. Click on the "Capture" button again to start capturing.</li>
-<li>If your device is a network adapter, you can use it to access the internet from your PC. To do this, connect your Pegatron N14939 network adapter to your PC and turn it on. Then, open the network settings on your PC and select your Pegatron N14939 network adapter from the list of available networks. Enter the password if required and click on the "Connect" button. You can now browse the web using your Pegatron N14939 network adapter.</li>
-</ul>
-
-<p>Note: These are just some examples of how to use Pegatron N14939 device. You may need to refer to the user manual or online support for more details and instructions.</p>
-
-<h2>How to Maintain Pegatron N14939 Device</h2>
-
-<p>To keep your Pegatron N14939 device in good condition and extend its lifespan, you need to maintain it regularly. Here are some tips on how to maintain Pegatron N14939 device:</p>
-
-<ul>
-<li>Clean your device regularly by wiping it with a soft cloth or a cotton swab dipped in alcohol. Avoid using water or harsh chemicals that may damage your device.</li>
-<li>Store your device in a cool and dry place away from direct sunlight and heat sources. Avoid exposing your device to extreme temperatures or humidity that may cause malfunction or corrosion.</li>
-<li>Handle your device with care and avoid dropping or bumping it. Use a protective case or bag if possible.</li>
-<li>Replace or recharge the batteries of your device if needed. Use only compatible batteries that match the specifications of your device.</li>
-<li>Check for driver updates regularly and install them if available. This can improve the performance and compatibility of your device with your operating system and software.</li>
-</ul>
-
-<p>By following these tips, you can keep
-your Pegatron N14939 device in good condition and enjoy its features for a long time.</p>
-
-<h2>Conclusion</h2>
-
-<p>Pegatron N14939 is a device that allows you to connect your computer to various peripherals. To ensure its optimal performance and compatibility with your operating system, you need to download and install the correct driver for it. You can download and install Pegatron N14939 driver manually or automatically using one of the methods above. You can also troubleshoot common driver problems and optimize your PC for better performance by following our tips.</p>
-
-<p>In addition, you can use your Pegatron N14939 device to perform various tasks on
-your PC depending on its type. You can also maintain
-your Pegatron N14939 device regularly by following our tips.</p>
-
-<p>We hope this article has helped you learn how
-to download and install Pegatron N14939 driver for Windows and how
-to use and maintain
-your Pegatron N14939 device.
-If you have any questions or suggestions,
-please feel free
-to leave a comment below.</p> 679dcb208e<br />
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diff --git a/spaces/tialenAdioni/chat-gpt-api/logs/How to Use Microforum New Beat Trancemission rar to Make Studio Quality Music.md b/spaces/tialenAdioni/chat-gpt-api/logs/How to Use Microforum New Beat Trancemission rar to Make Studio Quality Music.md
deleted file mode 100644
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--- a/spaces/tialenAdioni/chat-gpt-api/logs/How to Use Microforum New Beat Trancemission rar to Make Studio Quality Music.md	
+++ /dev/null
@@ -1,52 +0,0 @@
-<br />
-<h1>New Beat Trancemission: A Retro Music Software from the 90s</h1>
-<p>New Beat Trancemission is a music software that was released by Microforum in 1996. It allows users to create their own dance, house, techno and hip-hop beats using a variety of samples, loops and effects. Users can also record, mix and edit their own sounds using the Sound Warp sound editor. The software was designed to be easy to use for beginners as well as advanced DJs who want to experiment with different genres and styles.</p>
-<p>The software comes with a CD-ROM that contains over 250 instrument and sound effects samples, as well as a demo version that has over 200 samples. Users can also download the software from the Internet Archive[^1^] [^2^], where it is available for free. The software runs on Windows 95 and 98, and requires a sound card and a CD-ROM drive.</p>
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-<p>New Beat Trancemission is a fun and nostalgic way to explore the music scene of the 90s, and to create your own original tracks using a simple and intuitive interface. Whether you want to make some high-energy house, trance, techno or hip-hop beats, or just have some fun with sounds, New Beat Trancemission will let you unleash your musical creativity.</p><p>One of the features of New Beat Trancemission is the ability to customize the sounds and effects using the Sound Warp sound editor. Users can record their own sounds using a microphone or a line-in device, and then edit them using various tools such as pitch, volume, echo, reverb, distortion and more. Users can also import and export WAV files to use in other applications or share with others.</p>
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-<p>New Beat Trancemission also has a built-in sequencer that allows users to arrange their samples and loops into tracks. Users can adjust the tempo, volume, pan and balance of each track, and add effects such as fade in, fade out, crossfade and loop. Users can also save and load their tracks as MIDI files, or export them as WAV files to burn onto CDs or upload online.</p>
-<p>New Beat Trancemission is a versatile and fun music software that can appeal to anyone who loves music and wants to create their own beats. It is also a great way to learn about the basics of music production and sound editing, and to discover the different genres and styles of music that emerged in the 90s. New Beat Trancemission is a blast from the past that can still inspire and entertain today.</p><p>New Beat Trancemission is not the only music software that was released by Microforum in the 90s. The company also produced other titles such as Dance eJay, Hip Hop eJay, Techno eJay and House eJay, which were similar to New Beat Trancemission but focused on specific genres of music. These software also had a large library of samples and loops, as well as a sound editor and a sequencer. Microforum also released other music-related software such as Music Maker, Music Studio and Music Master.</p>
-<p>Microforum was a Canadian company that was founded in 1985 and specialized in multimedia products and services. The company was known for its educational, entertainment and business software, as well as its CD-ROM duplication and distribution services. Microforum also published several video games such as The Adventures of Hyperman, The Adventures of Lomax, The Crow: City of Angels and The Fifth Element. The company ceased operations in 2002.</p>
-<p>New Beat Trancemission is a part of the history of music software and the 90s music culture. It is a testament to the creativity and innovation of Microforum and its developers, who created a user-friendly and fun way to make music on a PC. New Beat Trancemission is a rare and valuable software that can still be enjoyed by music enthusiasts and retro fans today.</p> e753bf7129<br />
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\ No newline at end of file
diff --git a/spaces/ticomspire/turkey-syria-earthquake-tweets/logs/Download Cars.com App and Find Your Dream Car on iOS.md b/spaces/ticomspire/turkey-syria-earthquake-tweets/logs/Download Cars.com App and Find Your Dream Car on iOS.md
deleted file mode 100644
index ff33b71b5bf782430cf5184d8301f6c404accf56..0000000000000000000000000000000000000000
--- a/spaces/ticomspire/turkey-syria-earthquake-tweets/logs/Download Cars.com App and Find Your Dream Car on iOS.md	
+++ /dev/null
@@ -1,119 +0,0 @@
-
-<h1>Cars APK iOS: How to Download and Play Car Games on Your iPhone or iPad</h1>
-<p>Do you love car games and want to play them on your iPhone or iPad? If so, you might be interested in Cars APK iOS, a platform that allows you to download and play various car games on your iOS device. In this article, we will explain what Cars APK iOS is, how to download it, and how to play car games on your iPhone or iPad. We will also answer some frequently asked questions about Cars APK iOS.</p>
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- <h2>What is Cars APK iOS?</h2>
-<h3>Definition and explanation of Cars APK iOS</h3>
-<p>Cars APK iOS is a term that refers to the files that contain car games for iOS devices. APK stands for Android Package Kit, which is the file format used by Android applications. However, some developers have modified these files to make them compatible with iOS devices, such as iPhones and iPads. These files are also known as IPA files, which stands for iOS App Store Package.</p>
-<h3>Benefits and drawbacks of using Cars APK iOS</h3>
-<p>One of the main benefits of using Cars APK iOS is that you can access a wide range of car games that are not available on the official App Store. You can enjoy different genres, such as racing, drifting, simulation, and more. You can also play some of the latest and most popular car games, such as CarX Street, Asphalt 9, Real Racing 3, and more.</p>
-<p>However, there are also some drawbacks of using Cars APK iOS. One of them is that you need to download and install these files from third-party sources, which may not be safe or reliable. You may encounter malware, viruses, or other security risks that can harm your device or compromise your personal information. Another drawback is that you may violate the terms and conditions of Apple or the game developers by using these files. You may face legal consequences or lose your account if you are caught.</p>
- <h2>How to Download Cars APK iOS?</h2>
-<h3>Steps to download and install Cars APK iOS from third-party sources</h3>
-<p>If you want to download and install Cars APK iOS from third-party sources, you need to follow these steps:</p>
-<ol>
-<li>First, you need to enable the installation of apps from unknown sources on your device. To do this, go to Settings > General > Device Management > Profiles & Device Management. Then, tap on the profile of the third-party source that you want to use and trust it.</li>
-<li>Next, you need to find a reputable website that offers Cars APK iOS files. You can search online or use some of the suggestions below:</li>
-<ul>
-<li>[Cars.com Mobile App](^2^): This website provides a free app that lets you find and compare cars for sale near you. You can also access driver reviews, pricing tools, and other features.</li>
-<li>[CarX Street](^1^): This website provides a link to download the CarX Street game, which is a realistic street racing game with dynamic open world and car tuning.</li>
-</ul>
-<li>Then, you need to download the file that you want from the website. Make sure that the file has the .ipa extension and that it matches the name and description of the game that you want to install.</li>
-<li>Finally, you need to install the file on your device. To do this, you can use a file manager app, such as [iFile] or [Filza], to locate the file and tap on it. Then, follow the instructions on the screen to complete the installation.</li>
-</ol>
-<h3>Tips and precautions to avoid malware and viruses</h3>
-<p>While downloading and installing Cars APK iOS from third-party sources can be fun and exciting, it can also be risky and dangerous. Here are some tips and precautions that you should take to avoid malware and viruses:</p>
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-<li>Always backup your device before installing any file. You can use iCloud or iTunes to backup your data and settings in case something goes wrong during the installation.</li>
-<li>Always update your device and apps regularly. You can check for updates in Settings > General > Software Update or App Store > Updates. Updating your device and apps can fix bugs, improve performance, and enhance security.</li>
-</ul>
- <h2>How to Play Car Games on Your iPhone or iPad?</h2>
-<h3>Examples of popular car games available on Cars APK iOS</h3>
-<p>Once you have downloaded and installed Cars APK iOS on your device, you can start playing car games on your iPhone or iPad. There are many car games available on Cars APK iOS, but here are some of the most popular ones:</p>
-<table>
-<tr><th>Name</th><th>Description</th><th>Genre</th></tr>
-<tr><td>[CarX Street]</td><td>A realistic street racing game with dynamic open world and car tuning.</td><td>Racing</td></tr>
-<tr><td>[Asphalt 9]</td><td>A fast-paced arcade racing game with stunning graphics and hypercars.</td><td>Racing</td></tr>
-<tr><td>[Real Racing 3]</td><td>A realistic racing game with licensed tracks, cars, and events.</td><td>Racing</td></tr>
-<tr><td>[Drift Max Pro]</td><td>A drifting game with customizable cars and tracks.</td><td>Drifting</td></tr>
-<tr><td>[Car Simulator 2]</td><td>A simulation game with open world, multiplayer mode, and car dealership.</td><td>Simulation</td></tr>
-<tr><td>[Crash of Cars]</td><td>A multiplayer game where you have to collect power-ups and destroy other cars.</td><td>Action</td></tr>
-</table>
- <h3>Features and functions of car games on Cars APK iOS</h3>
-<p>The car games on Cars APK iOS have different features and functions that make them fun and enjoyable. Here are some of the common features and functions that you can find in most car games on Cars APK iOS:</p>
-<ul>
-<li>You can choose from a variety of cars, such as sports cars, muscle cars, supercars, and more. You can also customize your cars with different colors, decals, wheels, spoilers, and more.</li>
-<li>You can race against other players or AI opponents in different modes, such as career mode, online mode, time trial mode, and more. You can also compete in different events, such as championships, tournaments, challenges, and more.</li>
-<li>You can drive in different environments, such as cities, deserts, mountains, forests, and more. You can also explore different landmarks, such as bridges, tunnels, ramps, loops, and more.</li>
-<li>You can control your car with different options, such as tilt steering, touch steering, buttons steering, or gyro steering. You can also adjust the sensitivity, camera angle, sound effects, music volume, and more.</li>
-<li>You can earn rewards for completing missions, winning races, performing stunts, collecting coins, unlocking achievements, and more. You can also use the rewards to upgrade your cars or buy new ones.</li>
-</ul>
- <h2>Conclusion</h2>
-<h3>Summary of the main points</h3>
-<p>In conclusion, Cars APK iOS is a platform that allows you to download and play various car games on your iPhone or iPad. You can enjoy different genres of car games that are not available on the official App Store. However [user](# , you need to be careful when downloading and installing Cars APK iOS from third-party sources, as you may encounter security risks or legal issues. You also need to follow some tips and precautions to avoid malware and viruses. To play car games on your iPhone or iPad, you can choose from a variety of cars, modes, environments, and features that make the games fun and enjoyable.</p>
- <h3>Call to action and recommendation</h3>
-<p>If you are a car game lover and want to try Cars APK iOS on your device, we recommend that you visit the websites that we have mentioned in this article and download the files that you want. However, we also advise that you do so at your own risk and responsibility, as we are not liable for any damages or losses that may occur. We hope that you have found this article helpful and informative, and that you have learned something new about Cars APK iOS.</p>
- <h2>FAQs</h2>
-<h3>Is Cars APK iOS safe and legal?</h3>
-<p>Cars APK iOS is not safe or legal, as it involves downloading and installing files from third-party sources that are not authorized by Apple or the game developers. These files may contain malware, viruses, or other harmful elements that can damage your device or steal your personal information. Moreover, using these files may violate the terms and conditions of Apple or the game developers, and you may face legal consequences or lose your account if you are caught.</p>
- <h3>What are the requirements to run Cars APK iOS on your device?</h3>
-<p>To run Cars APK iOS on your device, you need to have an iPhone or iPad that runs on iOS 9.0 or later. You also need to have enough storage space to download and install the files that you want. The size of the files may vary depending on the game, but they usually range from 100 MB to 1 GB. You also need to have a stable internet connection to download the files and play the games online.</p>
- <h3>How to update Cars APK iOS and car games?</h3>
-<p>To update Cars APK iOS and car games, you need to visit the website where you downloaded the files and check for any new versions or updates. If there are any, you need to download and install them on your device. However, you should be aware that updating the files may cause some issues or errors, such as compatibility problems, crashes, or glitches. Therefore, you should backup your device before updating the files.</p>
- <h3>How to uninstall Cars APK iOS and car games?</h3>
-<p>To uninstall Cars APK iOS and car games, you need to delete the files from your device. To do this, you can use a file manager app, such as [iFile] or [Filza], to locate the files and tap on them. Then, select Delete from the options that appear. Alternatively, you can go to Settings > General > iPhone Storage > Manage Storage and find the files that you want to delete. Then, tap on them and select Delete App from the options that appear.</p>
- <h3>Where to find more information and support for Cars APK iOS?</h3>
-<p>If you want to find more information and support for Cars APK iOS, you can visit some of the online forums or communities that are dedicated to this topic. For example, you can check out [Reddit] or [Quora] and search for Cars APK iOS or related keywords. You can also ask questions or share your experiences with other users who are interested in this topic.</p> 401be4b1e0<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/tioseFevbu/cartoon-converter/scripts/Kon Kya Hai General Knowledge Book In Urdu Free Download EXCLUSIVE.md b/spaces/tioseFevbu/cartoon-converter/scripts/Kon Kya Hai General Knowledge Book In Urdu Free Download EXCLUSIVE.md
deleted file mode 100644
index c2432b1d684f508d7724103576d54a79fc1d06fc..0000000000000000000000000000000000000000
--- a/spaces/tioseFevbu/cartoon-converter/scripts/Kon Kya Hai General Knowledge Book In Urdu Free Download EXCLUSIVE.md	
+++ /dev/null
@@ -1,22 +0,0 @@
-<br />
-<h1>Kon Kya Hai: A Book of General Knowledge in Urdu</h1>
-<p>Kon Kya Hai is a book of general knowledge in Urdu language that covers various topics such as history, geography, science, religion, culture, sports, and current affairs. The book is written by Muhammad Iqbal Kailani and published by Maktaba-e-Dar-us-Salam. The book aims to provide useful information and facts to the readers in an easy and interesting way.</p>
-<p>The book is available for free download from various websites such as SoundCloud[^1^] [^2^] and GALAXY OF JOBS[^3^]. The book can be read online or offline on any device that supports PDF format. The book has 480 pages and is divided into 12 chapters. Each chapter contains multiple choice questions and answers at the end to test the reader's knowledge.</p>
-<h2>kon kya hai general knowledge book in urdu free download</h2><br /><p><b><b>Download File</b> ::: <a href="https://urlcod.com/2uHvzO">https://urlcod.com/2uHvzO</a></b></p><br /><br />
-<p>Kon Kya Hai is a valuable resource for students, teachers, researchers, and anyone who wants to improve their general knowledge and awareness about the world. The book is written in simple and clear Urdu language that can be understood by anyone who knows how to read Urdu. The book is also suitable for preparing for competitive exams such as CSS, PMS, NTS, etc.</p><p>Some of the topics covered in the book are:</p>
-<ul>
-<li>The history of Islam and the prophets</li>
-<li>The history of Pakistan and its heroes</li>
-<li>The geography of the world and its continents</li>
-<li>The science of the universe and its wonders</li>
-<li>The religion of Islam and its teachings</li>
-<li>The culture of Pakistan and its diversity</li>
-<li>The sports of the world and its champions</li>
-<li>The current affairs of the world and its issues</li>
-</ul>
-<p>The book is a comprehensive and updated source of general knowledge that can enrich the reader's mind and broaden their horizon. The book is also a fun and engaging way to learn new things and improve one's memory and intelligence. The book is recommended for anyone who wants to increase their knowledge and awareness about the world.</p>
-<p></p><p>The book is written by Muhammad Iqbal Kailani, a renowned scholar and writer of Islamic books. He has authored more than 100 books on various topics of Islam and general knowledge. He is also the editor of the monthly magazine Al-Dar-us-Salam. He has a vast experience and knowledge in the field of Islamic studies and general knowledge.</p>
-<p>The book is published by Maktaba-e-Dar-us-Salam, a leading publisher of Islamic books and media. The publisher has a mission to spread the true message of Islam and provide authentic and reliable sources of Islamic knowledge. The publisher has a wide range of books and products that cater to the needs and interests of different segments of the society.</p>
-<p>The book is available for free download from various websites such as SoundCloud  and GALAXY OF JOBS. The book can also be purchased from online stores such as Daraz.pk and Amazon.com. The book is priced at Rs. 600 in Pakistan and $15 in the US. The book is a worthwhile investment for anyone who wants to enhance their general knowledge and learn more about the world.</p> 81aa517590<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/tjburns/ask_marcus_aurelius/.venv/lib/python3.10/site-packages/pip/_internal/resolution/base.py b/spaces/tjburns/ask_marcus_aurelius/.venv/lib/python3.10/site-packages/pip/_internal/resolution/base.py
deleted file mode 100644
index 42dade18c1ec2b825f756dad4aaa89f2d9e6ce21..0000000000000000000000000000000000000000
--- a/spaces/tjburns/ask_marcus_aurelius/.venv/lib/python3.10/site-packages/pip/_internal/resolution/base.py
+++ /dev/null
@@ -1,20 +0,0 @@
-from typing import Callable, List, Optional
-
-from pip._internal.req.req_install import InstallRequirement
-from pip._internal.req.req_set import RequirementSet
-
-InstallRequirementProvider = Callable[
-    [str, Optional[InstallRequirement]], InstallRequirement
-]
-
-
-class BaseResolver:
-    def resolve(
-        self, root_reqs: List[InstallRequirement], check_supported_wheels: bool
-    ) -> RequirementSet:
-        raise NotImplementedError()
-
-    def get_installation_order(
-        self, req_set: RequirementSet
-    ) -> List[InstallRequirement]:
-        raise NotImplementedError()
diff --git a/spaces/tomofi/MMOCR/configs/_base_/runtime_10e.py b/spaces/tomofi/MMOCR/configs/_base_/runtime_10e.py
deleted file mode 100644
index bee3e4e8746b0f7179a544604d11c7d816cf618c..0000000000000000000000000000000000000000
--- a/spaces/tomofi/MMOCR/configs/_base_/runtime_10e.py
+++ /dev/null
@@ -1,19 +0,0 @@
-checkpoint_config = dict(interval=10)
-# yapf:disable
-log_config = dict(
-    interval=5,
-    hooks=[
-        dict(type='TextLoggerHook')
-        # dict(type='TensorboardLoggerHook')
-    ])
-# yapf:enable
-dist_params = dict(backend='nccl')
-log_level = 'INFO'
-load_from = None
-resume_from = None
-workflow = [('train', 1)]
-
-# disable opencv multithreading to avoid system being overloaded
-opencv_num_threads = 0
-# set multi-process start method as `fork` to speed up the training
-mp_start_method = 'fork'
diff --git a/spaces/tomofi/MMOCR/mmocr/models/textrecog/backbones/__init__.py b/spaces/tomofi/MMOCR/mmocr/models/textrecog/backbones/__init__.py
deleted file mode 100644
index e9b68c389b0c84bd66a29ece09c1bac9de68db3e..0000000000000000000000000000000000000000
--- a/spaces/tomofi/MMOCR/mmocr/models/textrecog/backbones/__init__.py
+++ /dev/null
@@ -1,12 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-from .nrtr_modality_transformer import NRTRModalityTransform
-from .resnet import ResNet
-from .resnet31_ocr import ResNet31OCR
-from .resnet_abi import ResNetABI
-from .shallow_cnn import ShallowCNN
-from .very_deep_vgg import VeryDeepVgg
-
-__all__ = [
-    'ResNet31OCR', 'VeryDeepVgg', 'NRTRModalityTransform', 'ShallowCNN',
-    'ResNetABI', 'ResNet'
-]
diff --git a/spaces/tomofi/NDLOCR/src/ndl_layout/mmdetection/configs/_base_/models/mask_rcnn_r50_caffe_c4.py b/spaces/tomofi/NDLOCR/src/ndl_layout/mmdetection/configs/_base_/models/mask_rcnn_r50_caffe_c4.py
deleted file mode 100644
index eaae1342f4aaa7015510d51bb4f12500a8a6b81d..0000000000000000000000000000000000000000
--- a/spaces/tomofi/NDLOCR/src/ndl_layout/mmdetection/configs/_base_/models/mask_rcnn_r50_caffe_c4.py
+++ /dev/null
@@ -1,123 +0,0 @@
-# model settings
-norm_cfg = dict(type='BN', requires_grad=False)
-model = dict(
-    type='MaskRCNN',
-    pretrained='open-mmlab://detectron2/resnet50_caffe',
-    backbone=dict(
-        type='ResNet',
-        depth=50,
-        num_stages=3,
-        strides=(1, 2, 2),
-        dilations=(1, 1, 1),
-        out_indices=(2, ),
-        frozen_stages=1,
-        norm_cfg=norm_cfg,
-        norm_eval=True,
-        style='caffe'),
-    rpn_head=dict(
-        type='RPNHead',
-        in_channels=1024,
-        feat_channels=1024,
-        anchor_generator=dict(
-            type='AnchorGenerator',
-            scales=[2, 4, 8, 16, 32],
-            ratios=[0.5, 1.0, 2.0],
-            strides=[16]),
-        bbox_coder=dict(
-            type='DeltaXYWHBBoxCoder',
-            target_means=[.0, .0, .0, .0],
-            target_stds=[1.0, 1.0, 1.0, 1.0]),
-        loss_cls=dict(
-            type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0),
-        loss_bbox=dict(type='L1Loss', loss_weight=1.0)),
-    roi_head=dict(
-        type='StandardRoIHead',
-        shared_head=dict(
-            type='ResLayer',
-            depth=50,
-            stage=3,
-            stride=2,
-            dilation=1,
-            style='caffe',
-            norm_cfg=norm_cfg,
-            norm_eval=True),
-        bbox_roi_extractor=dict(
-            type='SingleRoIExtractor',
-            roi_layer=dict(type='RoIAlign', output_size=14, sampling_ratio=0),
-            out_channels=1024,
-            featmap_strides=[16]),
-        bbox_head=dict(
-            type='BBoxHead',
-            with_avg_pool=True,
-            roi_feat_size=7,
-            in_channels=2048,
-            num_classes=80,
-            bbox_coder=dict(
-                type='DeltaXYWHBBoxCoder',
-                target_means=[0., 0., 0., 0.],
-                target_stds=[0.1, 0.1, 0.2, 0.2]),
-            reg_class_agnostic=False,
-            loss_cls=dict(
-                type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0),
-            loss_bbox=dict(type='L1Loss', loss_weight=1.0)),
-        mask_roi_extractor=None,
-        mask_head=dict(
-            type='FCNMaskHead',
-            num_convs=0,
-            in_channels=2048,
-            conv_out_channels=256,
-            num_classes=80,
-            loss_mask=dict(
-                type='CrossEntropyLoss', use_mask=True, loss_weight=1.0))),
-    # model training and testing settings
-    train_cfg=dict(
-        rpn=dict(
-            assigner=dict(
-                type='MaxIoUAssigner',
-                pos_iou_thr=0.7,
-                neg_iou_thr=0.3,
-                min_pos_iou=0.3,
-                match_low_quality=True,
-                ignore_iof_thr=-1),
-            sampler=dict(
-                type='RandomSampler',
-                num=256,
-                pos_fraction=0.5,
-                neg_pos_ub=-1,
-                add_gt_as_proposals=False),
-            allowed_border=0,
-            pos_weight=-1,
-            debug=False),
-        rpn_proposal=dict(
-            nms_pre=12000,
-            max_per_img=2000,
-            nms=dict(type='nms', iou_threshold=0.7),
-            min_bbox_size=0),
-        rcnn=dict(
-            assigner=dict(
-                type='MaxIoUAssigner',
-                pos_iou_thr=0.5,
-                neg_iou_thr=0.5,
-                min_pos_iou=0.5,
-                match_low_quality=False,
-                ignore_iof_thr=-1),
-            sampler=dict(
-                type='RandomSampler',
-                num=512,
-                pos_fraction=0.25,
-                neg_pos_ub=-1,
-                add_gt_as_proposals=True),
-            mask_size=14,
-            pos_weight=-1,
-            debug=False)),
-    test_cfg=dict(
-        rpn=dict(
-            nms_pre=6000,
-            nms=dict(type='nms', iou_threshold=0.7),
-            max_per_img=1000,
-            min_bbox_size=0),
-        rcnn=dict(
-            score_thr=0.05,
-            nms=dict(type='nms', iou_threshold=0.5),
-            max_per_img=100,
-            mask_thr_binary=0.5)))
diff --git a/spaces/tomofi/NDLOCR/src/ndl_layout/mmdetection/configs/faster_rcnn/faster_rcnn_r50_fpn_soft_nms_1x_coco.py b/spaces/tomofi/NDLOCR/src/ndl_layout/mmdetection/configs/faster_rcnn/faster_rcnn_r50_fpn_soft_nms_1x_coco.py
deleted file mode 100644
index 759ae3a7acec07daa75213835f1bc41d5c6de4a5..0000000000000000000000000000000000000000
--- a/spaces/tomofi/NDLOCR/src/ndl_layout/mmdetection/configs/faster_rcnn/faster_rcnn_r50_fpn_soft_nms_1x_coco.py
+++ /dev/null
@@ -1,12 +0,0 @@
-_base_ = [
-    '../_base_/models/faster_rcnn_r50_fpn.py',
-    '../_base_/datasets/coco_detection.py',
-    '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
-]
-
-model = dict(
-    test_cfg=dict(
-        rcnn=dict(
-            score_thr=0.05,
-            nms=dict(type='soft_nms', iou_threshold=0.5),
-            max_per_img=100)))
diff --git a/spaces/tsi-org/Faceswapper/roop/__init__.py b/spaces/tsi-org/Faceswapper/roop/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/tumuyan/Alist1/README.md b/spaces/tumuyan/Alist1/README.md
deleted file mode 100644
index 4759358c5c01590d0fc130829cebd78967006340..0000000000000000000000000000000000000000
--- a/spaces/tumuyan/Alist1/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Alist0
-emoji: 🦀
-colorFrom: gray
-colorTo: pink
-sdk: docker
-pinned: false
-license: agpl-3.0
-app_port: 5244
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
\ No newline at end of file
diff --git a/spaces/ucalyptus/DragGAN-unofficial/app.py b/spaces/ucalyptus/DragGAN-unofficial/app.py
deleted file mode 100644
index 252c0ed18bb0c14aef91805f3fe8ef7a5ad6c9b8..0000000000000000000000000000000000000000
--- a/spaces/ucalyptus/DragGAN-unofficial/app.py
+++ /dev/null
@@ -1,76 +0,0 @@
-import gradio as gr
-import torch
-from drag_gan import stylegan2, drag_gan
-from PIL import Image
-
-device = 'cuda'
-g_ema = stylegan2().to(device)
-
-
-def to_image(tensor):
-    tensor = tensor.squeeze(0).permute(1, 2, 0)
-    arr = tensor.detach().cpu().numpy()
-    arr = (arr - arr.min()) / (arr.max() - arr.min())
-    arr = arr * 255
-    return arr.astype('uint8')
-
-
-def on_click(image, target_point, points, evt: gr.SelectData):
-    x = evt.index[1]
-    y = evt.index[0]
-    if target_point:
-        image[x:x + 5, y:y + 5, :] = 255
-        points['target'].append([evt.index[1], evt.index[0]])
-        return image, str(evt.index)
-    points['handle'].append([evt.index[1], evt.index[0]])
-    image[x:x + 5, y:y + 5, :] = 0
-    return image, str(evt.index)
-
-
-def on_drag(points, max_iters, state):
-    max_iters = int(max_iters)
-    latent = state['latent']
-    noise = state['noise']
-    F = state['F']
-
-    handle_points = [torch.tensor(p).float() for p in points['handle']]
-    target_points = [torch.tensor(p).float() for p in points['target']]
-    mask = torch.zeros((1, 1, 1024, 1024)).to(device)
-    mask[..., 720:820, 390:600] = 1
-    for sample2, latent, F in drag_gan(g_ema, latent, noise, F,
-                                       handle_points, target_points, mask,
-                                       max_iters=max_iters):
-        points = {'target': [], 'handle': []}
-        image = to_image(sample2)
-
-        state['F'] = F
-        state['latent'] = latent
-        yield points, image, state
-
-
-def main():
-    torch.cuda.manual_seed(25)  
-    sample_z = torch.randn([1, 512], device=device)
-    latent, noise = g_ema.prepare([sample_z])
-    sample, F = g_ema.generate(latent, noise)
-
-    with gr.Blocks() as demo:
-        state = gr.State({
-            'latent': latent,
-            'noise': noise,
-            'F': F,
-        })
-        max_iters = gr.Slider(1, 100, 5, label='Max Iterations')
-        image = gr.Image(to_image(sample)).style(height=512, width=512)
-        text = gr.Textbox()
-        btn = gr.Button('Drag it')
-        points = gr.State({'target': [], 'handle': []})
-        target_point = gr.Checkbox(label='Target Point')
-        image.select(on_click, [image, target_point, points], [image, text])
-        btn.click(on_drag, inputs=[points, max_iters, state], outputs=[points, image, state])
-
-    demo.queue(concurrency_count=5, max_size=20).launch()
-
-
-if __name__ == '__main__':
-    main()
diff --git a/spaces/ulysses115/Nogizaka46-so/preprocess_flist_config.py b/spaces/ulysses115/Nogizaka46-so/preprocess_flist_config.py
deleted file mode 100644
index 00535054a20fd81dcbbb4ac5f44e504a2bd2771d..0000000000000000000000000000000000000000
--- a/spaces/ulysses115/Nogizaka46-so/preprocess_flist_config.py
+++ /dev/null
@@ -1,75 +0,0 @@
-import os
-import argparse
-import re
-
-from tqdm import tqdm
-from random import shuffle
-import json
-import wave
-
-config_template = json.load(open("configs_template/config_template.json"))
-
-pattern = re.compile(r'^[\.a-zA-Z0-9_\/]+$')
-
-def get_wav_duration(file_path):
-    with wave.open(file_path, 'rb') as wav_file:
-        # 获取音频帧数
-        n_frames = wav_file.getnframes()
-        # 获取采样率
-        framerate = wav_file.getframerate()
-        # 计算时长（秒）
-        duration = n_frames / float(framerate)
-    return duration
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--train_list", type=str, default="./filelists/train.txt", help="path to train list")
-    parser.add_argument("--val_list", type=str, default="./filelists/val.txt", help="path to val list")
-    parser.add_argument("--source_dir", type=str, default="./dataset/44k", help="path to source dir")
-    args = parser.parse_args()
-    
-    train = []
-    val = []
-    idx = 0
-    spk_dict = {}
-    spk_id = 0
-    for speaker in tqdm(os.listdir(args.source_dir)):
-        spk_dict[speaker] = spk_id
-        spk_id += 1
-        wavs = ["/".join([args.source_dir, speaker, i]) for i in os.listdir(os.path.join(args.source_dir, speaker))]
-        new_wavs = []
-        for file in wavs:
-            if not file.endswith("wav"):
-                continue
-            #if not pattern.match(file):
-            #    print(f"warning：文件名{file}中包含非字母数字下划线，可能会导致错误。（也可能不会）")
-            if get_wav_duration(file) < 0.3:
-                print("skip too short audio:", file)
-                continue
-            new_wavs.append(file)
-        wavs = new_wavs
-        shuffle(wavs)
-        train += wavs[2:]
-        val += wavs[:2]
-
-    shuffle(train)
-    shuffle(val)
-            
-    print("Writing", args.train_list)
-    with open(args.train_list, "w") as f:
-        for fname in tqdm(train):
-            wavpath = fname
-            f.write(wavpath + "\n")
-        
-    print("Writing", args.val_list)
-    with open(args.val_list, "w") as f:
-        for fname in tqdm(val):
-            wavpath = fname
-            f.write(wavpath + "\n")
-
-    config_template["spk"] = spk_dict
-    config_template["model"]["n_speakers"] = spk_id
-	
-    print("Writing configs/config.json")
-    with open("configs/config.json", "w") as f:
-        json.dump(config_template, f, indent=2)
diff --git a/spaces/unity/ML-Agents-Walker/Build/Walker.loader.js b/spaces/unity/ML-Agents-Walker/Build/Walker.loader.js
deleted file mode 100644
index 11a00f4dce0ac090822dcf127458486806f0d022..0000000000000000000000000000000000000000
--- a/spaces/unity/ML-Agents-Walker/Build/Walker.loader.js
+++ /dev/null
@@ -1 +0,0 @@
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diff --git a/spaces/usbethFlerru/sovits-modelsV2/example/Bs En 12831 Pdf Free Download.md b/spaces/usbethFlerru/sovits-modelsV2/example/Bs En 12831 Pdf Free Download.md
deleted file mode 100644
index 7272a38fef608277568948bb92e61faa02e777c9..0000000000000000000000000000000000000000
--- a/spaces/usbethFlerru/sovits-modelsV2/example/Bs En 12831 Pdf Free Download.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>bs en 12831 pdf free download</h2><br /><p><b><b>DOWNLOAD</b> &#10001; &#10001; &#10001; <a href="https://urlcod.com/2uyX4T">https://urlcod.com/2uyX4T</a></b></p><br /><br />
-<br />
- 4d29de3e1b<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/vaibhavarduino/anime-plus/e4e/datasets/inference_dataset.py b/spaces/vaibhavarduino/anime-plus/e4e/datasets/inference_dataset.py
deleted file mode 100644
index fb577d7b538d634f27013c2784d2ea32143154cb..0000000000000000000000000000000000000000
--- a/spaces/vaibhavarduino/anime-plus/e4e/datasets/inference_dataset.py
+++ /dev/null
@@ -1,25 +0,0 @@
-from torch.utils.data import Dataset
-from PIL import Image
-from utils import data_utils
-
-
-class InferenceDataset(Dataset):
-
-	def __init__(self, root, opts, transform=None, preprocess=None):
-		self.paths = sorted(data_utils.make_dataset(root))
-		self.transform = transform
-		self.preprocess = preprocess
-		self.opts = opts
-
-	def __len__(self):
-		return len(self.paths)
-
-	def __getitem__(self, index):
-		from_path = self.paths[index]
-		if self.preprocess is not None:
-			from_im = self.preprocess(from_path)
-		else:
-			from_im = Image.open(from_path).convert('RGB')
-		if self.transform:
-			from_im = self.transform(from_im)
-		return from_im
diff --git a/spaces/victor/website-designer/index.html b/spaces/victor/website-designer/index.html
deleted file mode 100644
index 800b948cfad767189e40048cef854264912bb886..0000000000000000000000000000000000000000
--- a/spaces/victor/website-designer/index.html
+++ /dev/null
@@ -1,81 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-  <head>
-    <meta charset="UTF-8" />
-    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <title>Document</title>
-    <link href="https://cdn.jsdelivr.net/npm/tailwindcss@2.2.16/dist/tailwind.min.css" rel="stylesheet" />
-    <style>
-      .highlight-border {
-        border: 2px solid red !important;
-      }
-    </style>
-  </head>
-  <body>
-    <div class="flex min-h-screen flex-col items-center justify-center p-4 text-lg" id="generation-form">
-      <div class="flex flex-col sm:w-96 w-full -mt-16">
-        <h1 class="self-center mb-8 text-3xl font-semibold">Design</h1>
-        <form action="" class="flex w-full flex-col gap-4 sm:w-96" onsubmit="submitForm(event)">
-          <input
-            type="text"
-            name="product_name"
-            id="product_name"
-            class="block rounded-lg bg-gray-200 px-4 py-3"
-            placeholder="Product name"
-          />
-          <textarea
-            placeholder="Instructions"
-            name="instructions"
-            id="instructions"
-            class="block rounded-lg bg-gray-200 px-4 py-3"
-            rows="10"
-          ></textarea>
-          <button class="rounded-xl bg-black px-4 py-3 font-semibold text-white">Generate Website</button>
-        </form>
-        <div class="flex h-12 items-baseline w-full sm:w-96 mt-6">
-          Examples
-          <button class="h-8 text-gray-700 bg-gray-200 rounded-lg p-2 flex items-center justify-center ml-auto mr-2">
-            Dropbox
-          </button>
-          <button class="h-8 text-gray-700 bg-gray-200 rounded-lg p-2 flex items-center justify-center">Airbnb</button>
-        </div>
-      </div>
-    </div>
-    <div class="relative h-screen px-16 pt-16 pb-24 bg-gray-800 hidden" id="generation">
-      <!-- Add 'hidden' class to hide #generation initially -->
-      <div
-        class="h-full w-full overflow-y-auto rounded-xl bg-white shadow-xl border"
-        onmouseover="highlightElement(event)"
-        onmouseout="removeHighlight(event)"
-        onclick="showCompletion(event)"
-      >
-        <div class="flex min-h-screen flex-col items-center justify-center p-4 text-lg">
-          <h1 class="mb-8 text-3xl font-semibold">Design</h1>
-          <form action="" class="flex w-full flex-col gap-4 sm:w-96">
-            <input type="text" class="block rounded-lg bg-gray-200 px-4 py-3" placeholder="Product name" />
-            <textarea
-              placeholder="Instructions"
-              name=""
-              id=""
-              class="block rounded-lg bg-gray-200 px-4 py-3"
-              rows="10"
-            ></textarea>
-          </form>
-        </div>
-      </div>
-    </div>
-  </body>
-</html>
-
-<script>
-  function highlightElement(event) {
-    const target = event.target;
-    if (target.classList.contains("highlight-border")) return;
-    target.classList.add("highlight-border");
-  }
-
-  function removeHighlight(event) {
-    const target = event.target;
-    target.classList.remove("highlight-border");
-  }
-</script>
diff --git a/spaces/vivien/trompeloeil/src/World/components/objects/setupModel.js b/spaces/vivien/trompeloeil/src/World/components/objects/setupModel.js
deleted file mode 100644
index 56d07a03aa52ad31e318aa2d8a12fb38651ddd47..0000000000000000000000000000000000000000
--- a/spaces/vivien/trompeloeil/src/World/components/objects/setupModel.js
+++ /dev/null
@@ -1,16 +0,0 @@
-import { AnimationMixer } from 'https://unpkg.com/three@0.117.0/build/three.module.js';
-
-function setupModel(data) {
-  const model = data.scene.children[0];
-  if (data.animations.length >= 1) {
-    const clip = data.animations[0];
-    const mixer = new AnimationMixer(model);
-    const action = mixer.clipAction(clip);
-    action.play();
-    model.tick = (delta) => mixer.update(delta);
-  }
-
-  return model;
-}
-
-export { setupModel };
diff --git a/spaces/vivym/image-matting-app/ppmatting/models/backbone/resnet_vd.py b/spaces/vivym/image-matting-app/ppmatting/models/backbone/resnet_vd.py
deleted file mode 100644
index 0fdd9a57664ad80ee59846060cd7f768f757feae..0000000000000000000000000000000000000000
--- a/spaces/vivym/image-matting-app/ppmatting/models/backbone/resnet_vd.py
+++ /dev/null
@@ -1,368 +0,0 @@
-# copyright (c) 2021 PaddlePaddle Authors. All Rights Reserve.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#    http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import paddle
-import paddle.nn as nn
-import paddle.nn.functional as F
-
-from paddleseg.cvlibs import manager
-from paddleseg.models import layers
-from paddleseg.utils import utils
-
-__all__ = [
-    "ResNet18_vd", "ResNet34_vd", "ResNet50_vd", "ResNet101_vd", "ResNet152_vd"
-]
-
-
-class ConvBNLayer(nn.Layer):
-    def __init__(
-            self,
-            in_channels,
-            out_channels,
-            kernel_size,
-            stride=1,
-            dilation=1,
-            groups=1,
-            is_vd_mode=False,
-            act=None, ):
-        super(ConvBNLayer, self).__init__()
-
-        self.is_vd_mode = is_vd_mode
-        self._pool2d_avg = nn.AvgPool2D(
-            kernel_size=2, stride=2, padding=0, ceil_mode=True)
-        self._conv = nn.Conv2D(
-            in_channels=in_channels,
-            out_channels=out_channels,
-            kernel_size=kernel_size,
-            stride=stride,
-            padding=(kernel_size - 1) // 2 if dilation == 1 else 0,
-            dilation=dilation,
-            groups=groups,
-            bias_attr=False)
-
-        self._batch_norm = layers.SyncBatchNorm(out_channels)
-        self._act_op = layers.Activation(act=act)
-
-    def forward(self, inputs):
-        if self.is_vd_mode:
-            inputs = self._pool2d_avg(inputs)
-        y = self._conv(inputs)
-        y = self._batch_norm(y)
-        y = self._act_op(y)
-
-        return y
-
-
-class BottleneckBlock(nn.Layer):
-    def __init__(self,
-                 in_channels,
-                 out_channels,
-                 stride,
-                 shortcut=True,
-                 if_first=False,
-                 dilation=1):
-        super(BottleneckBlock, self).__init__()
-
-        self.conv0 = ConvBNLayer(
-            in_channels=in_channels,
-            out_channels=out_channels,
-            kernel_size=1,
-            act='relu')
-
-        self.dilation = dilation
-
-        self.conv1 = ConvBNLayer(
-            in_channels=out_channels,
-            out_channels=out_channels,
-            kernel_size=3,
-            stride=stride,
-            act='relu',
-            dilation=dilation)
-        self.conv2 = ConvBNLayer(
-            in_channels=out_channels,
-            out_channels=out_channels * 4,
-            kernel_size=1,
-            act=None)
-
-        if not shortcut:
-            self.short = ConvBNLayer(
-                in_channels=in_channels,
-                out_channels=out_channels * 4,
-                kernel_size=1,
-                stride=1,
-                is_vd_mode=False if if_first or stride == 1 else True)
-
-        self.shortcut = shortcut
-
-    def forward(self, inputs):
-        y = self.conv0(inputs)
-
-        ####################################################################
-        # If given dilation rate > 1, using corresponding padding.
-        # The performance drops down without the follow padding.
-        if self.dilation > 1:
-            padding = self.dilation
-            y = F.pad(y, [padding, padding, padding, padding])
-        #####################################################################
-
-        conv1 = self.conv1(y)
-        conv2 = self.conv2(conv1)
-
-        if self.shortcut:
-            short = inputs
-        else:
-            short = self.short(inputs)
-
-        y = paddle.add(x=short, y=conv2)
-        y = F.relu(y)
-        return y
-
-
-class BasicBlock(nn.Layer):
-    def __init__(self,
-                 in_channels,
-                 out_channels,
-                 stride,
-                 shortcut=True,
-                 if_first=False):
-        super(BasicBlock, self).__init__()
-        self.stride = stride
-        self.conv0 = ConvBNLayer(
-            in_channels=in_channels,
-            out_channels=out_channels,
-            kernel_size=3,
-            stride=stride,
-            act='relu')
-        self.conv1 = ConvBNLayer(
-            in_channels=out_channels,
-            out_channels=out_channels,
-            kernel_size=3,
-            act=None)
-
-        if not shortcut:
-            self.short = ConvBNLayer(
-                in_channels=in_channels,
-                out_channels=out_channels,
-                kernel_size=1,
-                stride=1,
-                is_vd_mode=False if if_first or stride == 1 else True)
-
-        self.shortcut = shortcut
-
-    def forward(self, inputs):
-        y = self.conv0(inputs)
-        conv1 = self.conv1(y)
-
-        if self.shortcut:
-            short = inputs
-        else:
-            short = self.short(inputs)
-        y = paddle.add(x=short, y=conv1)
-        y = F.relu(y)
-
-        return y
-
-
-class ResNet_vd(nn.Layer):
-    """
-    The ResNet_vd implementation based on PaddlePaddle.
-
-    The original article refers to Jingdong
-    Tong He, et, al. "Bag of Tricks for Image Classification with Convolutional Neural Networks"
-    (https://arxiv.org/pdf/1812.01187.pdf).
-
-    Args:
-        layers (int, optional): The layers of ResNet_vd. The supported layers are (18, 34, 50, 101, 152, 200). Default: 50.
-        output_stride (int, optional): The stride of output features compared to input images. It is 8 or 16. Default: 8.
-        multi_grid (tuple|list, optional): The grid of stage4. Defult: (1, 1, 1).
-        pretrained (str, optional): The path of pretrained model.
-
-    """
-
-    def __init__(self,
-                 input_channels=3,
-                 layers=50,
-                 output_stride=32,
-                 multi_grid=(1, 1, 1),
-                 pretrained=None):
-        super(ResNet_vd, self).__init__()
-
-        self.conv1_logit = None  # for gscnn shape stream
-        self.layers = layers
-        supported_layers = [18, 34, 50, 101, 152, 200]
-        assert layers in supported_layers, \
-            "supported layers are {} but input layer is {}".format(
-                supported_layers, layers)
-
-        if layers == 18:
-            depth = [2, 2, 2, 2]
-        elif layers == 34 or layers == 50:
-            depth = [3, 4, 6, 3]
-        elif layers == 101:
-            depth = [3, 4, 23, 3]
-        elif layers == 152:
-            depth = [3, 8, 36, 3]
-        elif layers == 200:
-            depth = [3, 12, 48, 3]
-        num_channels = [64, 256, 512,
-                        1024] if layers >= 50 else [64, 64, 128, 256]
-        num_filters = [64, 128, 256, 512]
-
-        # for channels of four returned stages
-        self.feat_channels = [c * 4 for c in num_filters
-                              ] if layers >= 50 else num_filters
-        self.feat_channels = [64] + self.feat_channels
-
-        dilation_dict = None
-        if output_stride == 8:
-            dilation_dict = {2: 2, 3: 4}
-        elif output_stride == 16:
-            dilation_dict = {3: 2}
-
-        self.conv1_1 = ConvBNLayer(
-            in_channels=input_channels,
-            out_channels=32,
-            kernel_size=3,
-            stride=2,
-            act='relu')
-        self.conv1_2 = ConvBNLayer(
-            in_channels=32,
-            out_channels=32,
-            kernel_size=3,
-            stride=1,
-            act='relu')
-        self.conv1_3 = ConvBNLayer(
-            in_channels=32,
-            out_channels=64,
-            kernel_size=3,
-            stride=1,
-            act='relu')
-        self.pool2d_max = nn.MaxPool2D(kernel_size=3, stride=2, padding=1)
-
-        # self.block_list = []
-        self.stage_list = []
-        if layers >= 50:
-            for block in range(len(depth)):
-                shortcut = False
-                block_list = []
-                for i in range(depth[block]):
-                    if layers in [101, 152] and block == 2:
-                        if i == 0:
-                            conv_name = "res" + str(block + 2) + "a"
-                        else:
-                            conv_name = "res" + str(block + 2) + "b" + str(i)
-                    else:
-                        conv_name = "res" + str(block + 2) + chr(97 + i)
-
-                    ###############################################################################
-                    # Add dilation rate for some segmentation tasks, if dilation_dict is not None.
-                    dilation_rate = dilation_dict[
-                        block] if dilation_dict and block in dilation_dict else 1
-
-                    # Actually block here is 'stage', and i is 'block' in 'stage'
-                    # At the stage 4, expand the the dilation_rate if given multi_grid
-                    if block == 3:
-                        dilation_rate = dilation_rate * multi_grid[i]
-                    ###############################################################################
-
-                    bottleneck_block = self.add_sublayer(
-                        'bb_%d_%d' % (block, i),
-                        BottleneckBlock(
-                            in_channels=num_channels[block]
-                            if i == 0 else num_filters[block] * 4,
-                            out_channels=num_filters[block],
-                            stride=2 if i == 0 and block != 0 and
-                            dilation_rate == 1 else 1,
-                            shortcut=shortcut,
-                            if_first=block == i == 0,
-                            dilation=dilation_rate))
-
-                    block_list.append(bottleneck_block)
-                    shortcut = True
-                self.stage_list.append(block_list)
-        else:
-            for block in range(len(depth)):
-                shortcut = False
-                block_list = []
-                for i in range(depth[block]):
-                    conv_name = "res" + str(block + 2) + chr(97 + i)
-                    basic_block = self.add_sublayer(
-                        'bb_%d_%d' % (block, i),
-                        BasicBlock(
-                            in_channels=num_channels[block]
-                            if i == 0 else num_filters[block],
-                            out_channels=num_filters[block],
-                            stride=2 if i == 0 and block != 0 else 1,
-                            shortcut=shortcut,
-                            if_first=block == i == 0))
-                    block_list.append(basic_block)
-                    shortcut = True
-                self.stage_list.append(block_list)
-
-        self.pretrained = pretrained
-        self.init_weight()
-
-    def forward(self, inputs):
-        feat_list = []
-        y = self.conv1_1(inputs)
-        y = self.conv1_2(y)
-        y = self.conv1_3(y)
-        feat_list.append(y)
-
-        y = self.pool2d_max(y)
-
-        # A feature list saves the output feature map of each stage.
-        for stage in self.stage_list:
-            for block in stage:
-                y = block(y)
-            feat_list.append(y)
-
-        return feat_list
-
-    def init_weight(self):
-        utils.load_pretrained_model(self, self.pretrained)
-
-
-@manager.BACKBONES.add_component
-def ResNet18_vd(**args):
-    model = ResNet_vd(layers=18, **args)
-    return model
-
-
-@manager.BACKBONES.add_component
-def ResNet34_vd(**args):
-    model = ResNet_vd(layers=34, **args)
-    return model
-
-
-@manager.BACKBONES.add_component
-def ResNet50_vd(**args):
-    model = ResNet_vd(layers=50, **args)
-    return model
-
-
-@manager.BACKBONES.add_component
-def ResNet101_vd(**args):
-    model = ResNet_vd(layers=101, **args)
-    return model
-
-
-def ResNet152_vd(**args):
-    model = ResNet_vd(layers=152, **args)
-    return model
-
-
-def ResNet200_vd(**args):
-    model = ResNet_vd(layers=200, **args)
-    return model
diff --git a/spaces/vmoras/SAM_test/README.md b/spaces/vmoras/SAM_test/README.md
deleted file mode 100644
index e197cbcf1e0ae5cd128ff2b6a856beaa3edb8fb8..0000000000000000000000000000000000000000
--- a/spaces/vmoras/SAM_test/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Test
-emoji: 🐨
-colorFrom: red
-colorTo: blue
-sdk: gradio
-sdk_version: 3.26.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/vumichien/canvas_controlnet/annotator/uniformer/mmcv/fileio/handlers/__init__.py b/spaces/vumichien/canvas_controlnet/annotator/uniformer/mmcv/fileio/handlers/__init__.py
deleted file mode 100644
index aa24d91972837b8756b225f4879bac20436eb72a..0000000000000000000000000000000000000000
--- a/spaces/vumichien/canvas_controlnet/annotator/uniformer/mmcv/fileio/handlers/__init__.py
+++ /dev/null
@@ -1,7 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-from .base import BaseFileHandler
-from .json_handler import JsonHandler
-from .pickle_handler import PickleHandler
-from .yaml_handler import YamlHandler
-
-__all__ = ['BaseFileHandler', 'JsonHandler', 'PickleHandler', 'YamlHandler']
diff --git a/spaces/vumichien/canvas_controlnet/annotator/uniformer/mmcv/ops/corner_pool.py b/spaces/vumichien/canvas_controlnet/annotator/uniformer/mmcv/ops/corner_pool.py
deleted file mode 100644
index a33d798b43d405e4c86bee4cd6389be21ca9c637..0000000000000000000000000000000000000000
--- a/spaces/vumichien/canvas_controlnet/annotator/uniformer/mmcv/ops/corner_pool.py
+++ /dev/null
@@ -1,161 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-import torch
-from torch import nn
-from torch.autograd import Function
-
-from ..utils import ext_loader
-
-ext_module = ext_loader.load_ext('_ext', [
-    'top_pool_forward', 'top_pool_backward', 'bottom_pool_forward',
-    'bottom_pool_backward', 'left_pool_forward', 'left_pool_backward',
-    'right_pool_forward', 'right_pool_backward'
-])
-
-_mode_dict = {'top': 0, 'bottom': 1, 'left': 2, 'right': 3}
-
-
-class TopPoolFunction(Function):
-
-    @staticmethod
-    def symbolic(g, input):
-        output = g.op(
-            'mmcv::MMCVCornerPool', input, mode_i=int(_mode_dict['top']))
-        return output
-
-    @staticmethod
-    def forward(ctx, input):
-        output = ext_module.top_pool_forward(input)
-        ctx.save_for_backward(input)
-        return output
-
-    @staticmethod
-    def backward(ctx, grad_output):
-        input, = ctx.saved_tensors
-        output = ext_module.top_pool_backward(input, grad_output)
-        return output
-
-
-class BottomPoolFunction(Function):
-
-    @staticmethod
-    def symbolic(g, input):
-        output = g.op(
-            'mmcv::MMCVCornerPool', input, mode_i=int(_mode_dict['bottom']))
-        return output
-
-    @staticmethod
-    def forward(ctx, input):
-        output = ext_module.bottom_pool_forward(input)
-        ctx.save_for_backward(input)
-        return output
-
-    @staticmethod
-    def backward(ctx, grad_output):
-        input, = ctx.saved_tensors
-        output = ext_module.bottom_pool_backward(input, grad_output)
-        return output
-
-
-class LeftPoolFunction(Function):
-
-    @staticmethod
-    def symbolic(g, input):
-        output = g.op(
-            'mmcv::MMCVCornerPool', input, mode_i=int(_mode_dict['left']))
-        return output
-
-    @staticmethod
-    def forward(ctx, input):
-        output = ext_module.left_pool_forward(input)
-        ctx.save_for_backward(input)
-        return output
-
-    @staticmethod
-    def backward(ctx, grad_output):
-        input, = ctx.saved_tensors
-        output = ext_module.left_pool_backward(input, grad_output)
-        return output
-
-
-class RightPoolFunction(Function):
-
-    @staticmethod
-    def symbolic(g, input):
-        output = g.op(
-            'mmcv::MMCVCornerPool', input, mode_i=int(_mode_dict['right']))
-        return output
-
-    @staticmethod
-    def forward(ctx, input):
-        output = ext_module.right_pool_forward(input)
-        ctx.save_for_backward(input)
-        return output
-
-    @staticmethod
-    def backward(ctx, grad_output):
-        input, = ctx.saved_tensors
-        output = ext_module.right_pool_backward(input, grad_output)
-        return output
-
-
-class CornerPool(nn.Module):
-    """Corner Pooling.
-
-    Corner Pooling is a new type of pooling layer that helps a
-    convolutional network better localize corners of bounding boxes.
-
-    Please refer to https://arxiv.org/abs/1808.01244 for more details.
-    Code is modified from https://github.com/princeton-vl/CornerNet-Lite.
-
-    Args:
-        mode(str): Pooling orientation for the pooling layer
-
-            - 'bottom': Bottom Pooling
-            - 'left': Left Pooling
-            - 'right': Right Pooling
-            - 'top': Top Pooling
-
-    Returns:
-        Feature map after pooling.
-    """
-
-    pool_functions = {
-        'bottom': BottomPoolFunction,
-        'left': LeftPoolFunction,
-        'right': RightPoolFunction,
-        'top': TopPoolFunction,
-    }
-
-    cummax_dim_flip = {
-        'bottom': (2, False),
-        'left': (3, True),
-        'right': (3, False),
-        'top': (2, True),
-    }
-
-    def __init__(self, mode):
-        super(CornerPool, self).__init__()
-        assert mode in self.pool_functions
-        self.mode = mode
-        self.corner_pool = self.pool_functions[mode]
-
-    def forward(self, x):
-        if torch.__version__ != 'parrots' and torch.__version__ >= '1.5.0':
-            if torch.onnx.is_in_onnx_export():
-                assert torch.__version__ >= '1.7.0', \
-                    'When `cummax` serves as an intermediate component whose '\
-                    'outputs is used as inputs for another modules, it\'s '\
-                    'expected that pytorch version must be >= 1.7.0, '\
-                    'otherwise Error appears like: `RuntimeError: tuple '\
-                    'appears in op that does not forward tuples, unsupported '\
-                    'kind: prim::PythonOp`.'
-
-            dim, flip = self.cummax_dim_flip[self.mode]
-            if flip:
-                x = x.flip(dim)
-            pool_tensor, _ = torch.cummax(x, dim=dim)
-            if flip:
-                pool_tensor = pool_tensor.flip(dim)
-            return pool_tensor
-        else:
-            return self.corner_pool.apply(x)
diff --git a/spaces/wendys-llc/panoptic-segment-anything/segment_anything/segment_anything/automatic_mask_generator.py b/spaces/wendys-llc/panoptic-segment-anything/segment_anything/segment_anything/automatic_mask_generator.py
deleted file mode 100644
index 23264971b7ff5aa0b4f499ade7773b68dce984b6..0000000000000000000000000000000000000000
--- a/spaces/wendys-llc/panoptic-segment-anything/segment_anything/segment_anything/automatic_mask_generator.py
+++ /dev/null
@@ -1,372 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-
-import numpy as np
-import torch
-from torchvision.ops.boxes import batched_nms, box_area  # type: ignore
-
-from typing import Any, Dict, List, Optional, Tuple
-
-from .modeling import Sam
-from .predictor import SamPredictor
-from .utils.amg import (
-    MaskData,
-    area_from_rle,
-    batch_iterator,
-    batched_mask_to_box,
-    box_xyxy_to_xywh,
-    build_all_layer_point_grids,
-    calculate_stability_score,
-    coco_encode_rle,
-    generate_crop_boxes,
-    is_box_near_crop_edge,
-    mask_to_rle_pytorch,
-    remove_small_regions,
-    rle_to_mask,
-    uncrop_boxes_xyxy,
-    uncrop_masks,
-    uncrop_points,
-)
-
-
-class SamAutomaticMaskGenerator:
-    def __init__(
-        self,
-        model: Sam,
-        points_per_side: Optional[int] = 32,
-        points_per_batch: int = 64,
-        pred_iou_thresh: float = 0.88,
-        stability_score_thresh: float = 0.95,
-        stability_score_offset: float = 1.0,
-        box_nms_thresh: float = 0.7,
-        crop_n_layers: int = 0,
-        crop_nms_thresh: float = 0.7,
-        crop_overlap_ratio: float = 512 / 1500,
-        crop_n_points_downscale_factor: int = 1,
-        point_grids: Optional[List[np.ndarray]] = None,
-        min_mask_region_area: int = 0,
-        output_mode: str = "binary_mask",
-    ) -> None:
-        """
-        Using a SAM model, generates masks for the entire image.
-        Generates a grid of point prompts over the image, then filters
-        low quality and duplicate masks. The default settings are chosen
-        for SAM with a ViT-H backbone.
-
-        Arguments:
-          model (Sam): The SAM model to use for mask prediction.
-          points_per_side (int or None): The number of points to be sampled
-            along one side of the image. The total number of points is
-            points_per_side**2. If None, 'point_grids' must provide explicit
-            point sampling.
-          points_per_batch (int): Sets the number of points run simultaneously
-            by the model. Higher numbers may be faster but use more GPU memory.
-          pred_iou_thresh (float): A filtering threshold in [0,1], using the
-            model's predicted mask quality.
-          stability_score_thresh (float): A filtering threshold in [0,1], using
-            the stability of the mask under changes to the cutoff used to binarize
-            the model's mask predictions.
-          stability_score_offset (float): The amount to shift the cutoff when
-            calculated the stability score.
-          box_nms_thresh (float): The box IoU cutoff used by non-maximal
-            suppression to filter duplicate masks.
-          crops_n_layers (int): If >0, mask prediction will be run again on
-            crops of the image. Sets the number of layers to run, where each
-            layer has 2**i_layer number of image crops.
-          crops_nms_thresh (float): The box IoU cutoff used by non-maximal
-            suppression to filter duplicate masks between different crops.
-          crop_overlap_ratio (float): Sets the degree to which crops overlap.
-            In the first crop layer, crops will overlap by this fraction of
-            the image length. Later layers with more crops scale down this overlap.
-          crop_n_points_downscale_factor (int): The number of points-per-side
-            sampled in layer n is scaled down by crop_n_points_downscale_factor**n.
-          point_grids (list(np.ndarray) or None): A list over explicit grids
-            of points used for sampling, normalized to [0,1]. The nth grid in the
-            list is used in the nth crop layer. Exclusive with points_per_side.
-          min_mask_region_area (int): If >0, postprocessing will be applied
-            to remove disconnected regions and holes in masks with area smaller
-            than min_mask_region_area. Requires opencv.
-          output_mode (str): The form masks are returned in. Can be 'binary_mask',
-            'uncompressed_rle', or 'coco_rle'. 'coco_rle' requires pycocotools.
-            For large resolutions, 'binary_mask' may consume large amounts of
-            memory.
-        """
-
-        assert (points_per_side is None) != (
-            point_grids is None
-        ), "Exactly one of points_per_side or point_grid must be provided."
-        if points_per_side is not None:
-            self.point_grids = build_all_layer_point_grids(
-                points_per_side,
-                crop_n_layers,
-                crop_n_points_downscale_factor,
-            )
-        elif point_grids is not None:
-            self.point_grids = point_grids
-        else:
-            raise ValueError("Can't have both points_per_side and point_grid be None.")
-
-        assert output_mode in [
-            "binary_mask",
-            "uncompressed_rle",
-            "coco_rle",
-        ], f"Unknown output_mode {output_mode}."
-        if output_mode == "coco_rle":
-            from pycocotools import mask as mask_utils  # type: ignore # noqa: F401
-
-        if min_mask_region_area > 0:
-            import cv2  # type: ignore # noqa: F401
-
-        self.predictor = SamPredictor(model)
-        self.points_per_batch = points_per_batch
-        self.pred_iou_thresh = pred_iou_thresh
-        self.stability_score_thresh = stability_score_thresh
-        self.stability_score_offset = stability_score_offset
-        self.box_nms_thresh = box_nms_thresh
-        self.crop_n_layers = crop_n_layers
-        self.crop_nms_thresh = crop_nms_thresh
-        self.crop_overlap_ratio = crop_overlap_ratio
-        self.crop_n_points_downscale_factor = crop_n_points_downscale_factor
-        self.min_mask_region_area = min_mask_region_area
-        self.output_mode = output_mode
-
-    @torch.no_grad()
-    def generate(self, image: np.ndarray) -> List[Dict[str, Any]]:
-        """
-        Generates masks for the given image.
-
-        Arguments:
-          image (np.ndarray): The image to generate masks for, in HWC uint8 format.
-
-        Returns:
-           list(dict(str, any)): A list over records for masks. Each record is
-             a dict containing the following keys:
-               segmentation (dict(str, any) or np.ndarray): The mask. If
-                 output_mode='binary_mask', is an array of shape HW. Otherwise,
-                 is a dictionary containing the RLE.
-               bbox (list(float)): The box around the mask, in XYWH format.
-               area (int): The area in pixels of the mask.
-               predicted_iou (float): The model's own prediction of the mask's
-                 quality. This is filtered by the pred_iou_thresh parameter.
-               point_coords (list(list(float))): The point coordinates input
-                 to the model to generate this mask.
-               stability_score (float): A measure of the mask's quality. This
-                 is filtered on using the stability_score_thresh parameter.
-               crop_box (list(float)): The crop of the image used to generate
-                 the mask, given in XYWH format.
-        """
-
-        # Generate masks
-        mask_data = self._generate_masks(image)
-
-        # Filter small disconnected regions and holes in masks
-        if self.min_mask_region_area > 0:
-            mask_data = self.postprocess_small_regions(
-                mask_data,
-                self.min_mask_region_area,
-                max(self.box_nms_thresh, self.crop_nms_thresh),
-            )
-
-        # Encode masks
-        if self.output_mode == "coco_rle":
-            mask_data["segmentations"] = [coco_encode_rle(rle) for rle in mask_data["rles"]]
-        elif self.output_mode == "binary_mask":
-            mask_data["segmentations"] = [rle_to_mask(rle) for rle in mask_data["rles"]]
-        else:
-            mask_data["segmentations"] = mask_data["rles"]
-
-        # Write mask records
-        curr_anns = []
-        for idx in range(len(mask_data["segmentations"])):
-            ann = {
-                "segmentation": mask_data["segmentations"][idx],
-                "area": area_from_rle(mask_data["rles"][idx]),
-                "bbox": box_xyxy_to_xywh(mask_data["boxes"][idx]).tolist(),
-                "predicted_iou": mask_data["iou_preds"][idx].item(),
-                "point_coords": [mask_data["points"][idx].tolist()],
-                "stability_score": mask_data["stability_score"][idx].item(),
-                "crop_box": box_xyxy_to_xywh(mask_data["crop_boxes"][idx]).tolist(),
-            }
-            curr_anns.append(ann)
-
-        return curr_anns
-
-    def _generate_masks(self, image: np.ndarray) -> MaskData:
-        orig_size = image.shape[:2]
-        crop_boxes, layer_idxs = generate_crop_boxes(
-            orig_size, self.crop_n_layers, self.crop_overlap_ratio
-        )
-
-        # Iterate over image crops
-        data = MaskData()
-        for crop_box, layer_idx in zip(crop_boxes, layer_idxs):
-            crop_data = self._process_crop(image, crop_box, layer_idx, orig_size)
-            data.cat(crop_data)
-
-        # Remove duplicate masks between crops
-        if len(crop_boxes) > 1:
-            # Prefer masks from smaller crops
-            scores = 1 / box_area(data["crop_boxes"])
-            scores = scores.to(data["boxes"].device)
-            keep_by_nms = batched_nms(
-                data["boxes"].float(),
-                scores,
-                torch.zeros(len(data["boxes"])),  # categories
-                iou_threshold=self.crop_nms_thresh,
-            )
-            data.filter(keep_by_nms)
-
-        data.to_numpy()
-        return data
-
-    def _process_crop(
-        self,
-        image: np.ndarray,
-        crop_box: List[int],
-        crop_layer_idx: int,
-        orig_size: Tuple[int, ...],
-    ) -> MaskData:
-        # Crop the image and calculate embeddings
-        x0, y0, x1, y1 = crop_box
-        cropped_im = image[y0:y1, x0:x1, :]
-        cropped_im_size = cropped_im.shape[:2]
-        self.predictor.set_image(cropped_im)
-
-        # Get points for this crop
-        points_scale = np.array(cropped_im_size)[None, ::-1]
-        points_for_image = self.point_grids[crop_layer_idx] * points_scale
-
-        # Generate masks for this crop in batches
-        data = MaskData()
-        for (points,) in batch_iterator(self.points_per_batch, points_for_image):
-            batch_data = self._process_batch(points, cropped_im_size, crop_box, orig_size)
-            data.cat(batch_data)
-            del batch_data
-        self.predictor.reset_image()
-
-        # Remove duplicates within this crop.
-        keep_by_nms = batched_nms(
-            data["boxes"].float(),
-            data["iou_preds"],
-            torch.zeros(len(data["boxes"])),  # categories
-            iou_threshold=self.box_nms_thresh,
-        )
-        data.filter(keep_by_nms)
-
-        # Return to the original image frame
-        data["boxes"] = uncrop_boxes_xyxy(data["boxes"], crop_box)
-        data["points"] = uncrop_points(data["points"], crop_box)
-        data["crop_boxes"] = torch.tensor([crop_box for _ in range(len(data["rles"]))])
-
-        return data
-
-    def _process_batch(
-        self,
-        points: np.ndarray,
-        im_size: Tuple[int, ...],
-        crop_box: List[int],
-        orig_size: Tuple[int, ...],
-    ) -> MaskData:
-        orig_h, orig_w = orig_size
-
-        # Run model on this batch
-        transformed_points = self.predictor.transform.apply_coords(points, im_size)
-        in_points = torch.as_tensor(transformed_points, device=self.predictor.device)
-        in_labels = torch.ones(in_points.shape[0], dtype=torch.int, device=in_points.device)
-        masks, iou_preds, _ = self.predictor.predict_torch(
-            in_points[:, None, :],
-            in_labels[:, None],
-            multimask_output=True,
-            return_logits=True,
-        )
-
-        # Serialize predictions and store in MaskData
-        data = MaskData(
-            masks=masks.flatten(0, 1),
-            iou_preds=iou_preds.flatten(0, 1),
-            points=torch.as_tensor(points.repeat(masks.shape[1], axis=0)),
-        )
-        del masks
-
-        # Filter by predicted IoU
-        if self.pred_iou_thresh > 0.0:
-            keep_mask = data["iou_preds"] > self.pred_iou_thresh
-            data.filter(keep_mask)
-
-        # Calculate stability score
-        data["stability_score"] = calculate_stability_score(
-            data["masks"], self.predictor.model.mask_threshold, self.stability_score_offset
-        )
-        if self.stability_score_thresh > 0.0:
-            keep_mask = data["stability_score"] >= self.stability_score_thresh
-            data.filter(keep_mask)
-
-        # Threshold masks and calculate boxes
-        data["masks"] = data["masks"] > self.predictor.model.mask_threshold
-        data["boxes"] = batched_mask_to_box(data["masks"])
-
-        # Filter boxes that touch crop boundaries
-        keep_mask = ~is_box_near_crop_edge(data["boxes"], crop_box, [0, 0, orig_w, orig_h])
-        if not torch.all(keep_mask):
-            data.filter(keep_mask)
-
-        # Compress to RLE
-        data["masks"] = uncrop_masks(data["masks"], crop_box, orig_h, orig_w)
-        data["rles"] = mask_to_rle_pytorch(data["masks"])
-        del data["masks"]
-
-        return data
-
-    @staticmethod
-    def postprocess_small_regions(
-        mask_data: MaskData, min_area: int, nms_thresh: float
-    ) -> MaskData:
-        """
-        Removes small disconnected regions and holes in masks, then reruns
-        box NMS to remove any new duplicates.
-
-        Edits mask_data in place.
-
-        Requires open-cv as a dependency.
-        """
-        if len(mask_data["rles"]) == 0:
-            return mask_data
-
-        # Filter small disconnected regions and holes
-        new_masks = []
-        scores = []
-        for rle in mask_data["rles"]:
-            mask = rle_to_mask(rle)
-
-            mask, changed = remove_small_regions(mask, min_area, mode="holes")
-            unchanged = not changed
-            mask, changed = remove_small_regions(mask, min_area, mode="islands")
-            unchanged = unchanged and not changed
-
-            new_masks.append(torch.as_tensor(mask).unsqueeze(0))
-            # Give score=0 to changed masks and score=1 to unchanged masks
-            # so NMS will prefer ones that didn't need postprocessing
-            scores.append(float(unchanged))
-
-        # Recalculate boxes and remove any new duplicates
-        masks = torch.cat(new_masks, dim=0)
-        boxes = batched_mask_to_box(masks)
-        keep_by_nms = batched_nms(
-            boxes.float(),
-            torch.as_tensor(scores),
-            torch.zeros(len(boxes)),  # categories
-            iou_threshold=nms_thresh,
-        )
-
-        # Only recalculate RLEs for masks that have changed
-        for i_mask in keep_by_nms:
-            if scores[i_mask] == 0.0:
-                mask_torch = masks[i_mask].unsqueeze(0)
-                mask_data["rles"][i_mask] = mask_to_rle_pytorch(mask_torch)[0]
-                mask_data["boxes"][i_mask] = boxes[i_mask]  # update res directly
-        mask_data.filter(keep_by_nms)
-
-        return mask_data
diff --git a/spaces/whgwd2023/bingo/src/components/ui/separator.tsx b/spaces/whgwd2023/bingo/src/components/ui/separator.tsx
deleted file mode 100644
index 6c55e0b2ca8e2436658a06748aadbff7cd700db0..0000000000000000000000000000000000000000
--- a/spaces/whgwd2023/bingo/src/components/ui/separator.tsx
+++ /dev/null
@@ -1,31 +0,0 @@
-'use client'
-
-import * as React from 'react'
-import * as SeparatorPrimitive from '@radix-ui/react-separator'
-
-import { cn } from '@/lib/utils'
-
-const Separator = React.forwardRef<
-  React.ElementRef<typeof SeparatorPrimitive.Root>,
-  React.ComponentPropsWithoutRef<typeof SeparatorPrimitive.Root>
->(
-  (
-    { className, orientation = 'horizontal', decorative = true, ...props },
-    ref
-  ) => (
-    <SeparatorPrimitive.Root
-      ref={ref}
-      decorative={decorative}
-      orientation={orientation}
-      className={cn(
-        'shrink-0 bg-border',
-        orientation === 'horizontal' ? 'h-[1px] w-full' : 'h-full w-[1px]',
-        className
-      )}
-      {...props}
-    />
-  )
-)
-Separator.displayName = SeparatorPrimitive.Root.displayName
-
-export { Separator }
diff --git a/spaces/wy213/yangAI/README.md b/spaces/wy213/yangAI/README.md
deleted file mode 100644
index d8ffebfca2bde7cefe432c074b4c19afc6393e0c..0000000000000000000000000000000000000000
--- a/spaces/wy213/yangAI/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: YangAI
-emoji: ⚡
-colorFrom: indigo
-colorTo: blue
-sdk: docker
-pinned: false
-license: mit
-app_port: 8080
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/wydgg/bingo-wyd-ai/tailwind.config.js b/spaces/wydgg/bingo-wyd-ai/tailwind.config.js
deleted file mode 100644
index 03da3c3c45be6983b9f5ffa6df5f1fd0870e9636..0000000000000000000000000000000000000000
--- a/spaces/wydgg/bingo-wyd-ai/tailwind.config.js
+++ /dev/null
@@ -1,48 +0,0 @@
-/** @type {import('tailwindcss').Config} */
-module.exports = {
-  content: [
-    './src/pages/**/*.{js,ts,jsx,tsx,mdx}',
-    './src/components/**/*.{js,ts,jsx,tsx,mdx}',
-    './src/app/**/*.{js,ts,jsx,tsx,mdx}',
-    './src/ui/**/*.{js,ts,jsx,tsx,mdx}',
-  ],
-  "darkMode": "class",
-  theme: {
-    extend: {
-      colors: {
-        'primary-blue': 'rgb(var(--color-primary-blue) / <alpha-value>)',
-        secondary: 'rgb(var(--color-secondary) / <alpha-value>)',
-        'primary-background': 'rgb(var(--primary-background) / <alpha-value>)',
-        'primary-text': 'rgb(var(--primary-text) / <alpha-value>)',
-        'secondary-text': 'rgb(var(--secondary-text) / <alpha-value>)',
-        'light-text': 'rgb(var(--light-text) / <alpha-value>)',
-        'primary-border': 'rgb(var(--primary-border) / <alpha-value>)',
-      },
-      keyframes: {
-        slideDownAndFade: {
-          from: { opacity: 0, transform: 'translateY(-2px)' },
-          to: { opacity: 1, transform: 'translateY(0)' },
-        },
-        slideLeftAndFade: {
-          from: { opacity: 0, transform: 'translateX(2px)' },
-          to: { opacity: 1, transform: 'translateX(0)' },
-        },
-        slideUpAndFade: {
-          from: { opacity: 0, transform: 'translateY(2px)' },
-          to: { opacity: 1, transform: 'translateY(0)' },
-        },
-        slideRightAndFade: {
-          from: { opacity: 0, transform: 'translateX(2px)' },
-          to: { opacity: 1, transform: 'translateX(0)' },
-        },
-      },
-      animation: {
-        slideDownAndFade: 'slideDownAndFade 400ms cubic-bezier(0.16, 1, 0.3, 1)',
-        slideLeftAndFade: 'slideLeftAndFade 400ms cubic-bezier(0.16, 1, 0.3, 1)',
-        slideUpAndFade: 'slideUpAndFade 400ms cubic-bezier(0.16, 1, 0.3, 1)',
-        slideRightAndFade: 'slideRightAndFade 400ms cubic-bezier(0.16, 1, 0.3, 1)',
-      },
-    },
-  },
-  plugins: [require('@headlessui/tailwindcss'), require('tailwind-scrollbar')],
-}
diff --git a/spaces/wzhouxiff/RestoreFormerPlusPlus/RestoreFormer_arch.py b/spaces/wzhouxiff/RestoreFormerPlusPlus/RestoreFormer_arch.py
deleted file mode 100644
index 320cc52b2cea5d105cdccce672cb8c8ab200823a..0000000000000000000000000000000000000000
--- a/spaces/wzhouxiff/RestoreFormerPlusPlus/RestoreFormer_arch.py
+++ /dev/null
@@ -1,742 +0,0 @@
-import numpy as np
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-
-
-class VectorQuantizer(nn.Module):
-    """
-    see https://github.com/MishaLaskin/vqvae/blob/d761a999e2267766400dc646d82d3ac3657771d4/models/quantizer.py
-    ____________________________________________
-    Discretization bottleneck part of the VQ-VAE.
-    Inputs:
-    - n_e : number of embeddings
-    - e_dim : dimension of embedding
-    - beta : commitment cost used in loss term, beta * ||z_e(x)-sg[e]||^2
-    _____________________________________________
-    """
-
-    def __init__(self, n_e, e_dim, beta):
-        super(VectorQuantizer, self).__init__()
-        self.n_e = n_e
-        self.e_dim = e_dim
-        self.beta = beta
-
-        self.embedding = nn.Embedding(self.n_e, self.e_dim)
-        self.embedding.weight.data.uniform_(-1.0 / self.n_e, 1.0 / self.n_e)
-
-    def forward(self, z):
-        """
-        Inputs the output of the encoder network z and maps it to a discrete
-        one-hot vector that is the index of the closest embedding vector e_j
-        z (continuous) -> z_q (discrete)
-        z.shape = (batch, channel, height, width)
-        quantization pipeline:
-            1. get encoder input (B,C,H,W)
-            2. flatten input to (B*H*W,C)
-        """
-        # reshape z -> (batch, height, width, channel) and flatten
-        z = z.permute(0, 2, 3, 1).contiguous()
-        z_flattened = z.view(-1, self.e_dim)
-        # distances from z to embeddings e_j (z - e)^2 = z^2 + e^2 - 2 e * z
-
-        d = torch.sum(z_flattened ** 2, dim=1, keepdim=True) + \
-            torch.sum(self.embedding.weight**2, dim=1) - 2 * \
-            torch.matmul(z_flattened, self.embedding.weight.t())
-
-        ## could possible replace this here
-        # #\start...
-        # find closest encodings
-
-        min_value, min_encoding_indices = torch.min(d, dim=1)
-
-        min_encoding_indices = min_encoding_indices.unsqueeze(1)
-
-        min_encodings = torch.zeros(
-            min_encoding_indices.shape[0], self.n_e).to(z)
-        min_encodings.scatter_(1, min_encoding_indices, 1)
-
-        # dtype min encodings: torch.float32
-        # min_encodings shape: torch.Size([2048, 512])
-        # min_encoding_indices.shape: torch.Size([2048, 1])
-
-        # get quantized latent vectors
-        z_q = torch.matmul(min_encodings, self.embedding.weight).view(z.shape)
-        #.........\end
-
-        # with:
-        # .........\start
-        #min_encoding_indices = torch.argmin(d, dim=1)
-        #z_q = self.embedding(min_encoding_indices)
-        # ......\end......... (TODO)
-
-        # compute loss for embedding
-        loss = torch.mean((z_q.detach()-z)**2) + self.beta * \
-            torch.mean((z_q - z.detach()) ** 2)
-
-        # preserve gradients
-        z_q = z + (z_q - z).detach()
-
-        # perplexity
-        
-        e_mean = torch.mean(min_encodings, dim=0)
-        perplexity = torch.exp(-torch.sum(e_mean * torch.log(e_mean + 1e-10)))
-
-        # reshape back to match original input shape
-        z_q = z_q.permute(0, 3, 1, 2).contiguous()
-
-        return z_q, loss, (perplexity, min_encodings, min_encoding_indices, d)
-
-    def get_codebook_entry(self, indices, shape):
-        # shape specifying (batch, height, width, channel)
-        # TODO: check for more easy handling with nn.Embedding
-        min_encodings = torch.zeros(indices.shape[0], self.n_e).to(indices)
-        min_encodings.scatter_(1, indices[:,None], 1)
-
-        # get quantized latent vectors
-        z_q = torch.matmul(min_encodings.float(), self.embedding.weight)
-
-        if shape is not None:
-            z_q = z_q.view(shape)
-
-            # reshape back to match original input shape
-            z_q = z_q.permute(0, 3, 1, 2).contiguous()
-
-        return z_q
-
-# pytorch_diffusion + derived encoder decoder
-def nonlinearity(x):
-    # swish
-    return x*torch.sigmoid(x)
-
-
-def Normalize(in_channels):
-    return torch.nn.GroupNorm(num_groups=32, num_channels=in_channels, eps=1e-6, affine=True)
-
-
-class Upsample(nn.Module):
-    def __init__(self, in_channels, with_conv):
-        super().__init__()
-        self.with_conv = with_conv
-        if self.with_conv:
-            self.conv = torch.nn.Conv2d(in_channels,
-                                        in_channels,
-                                        kernel_size=3,
-                                        stride=1,
-                                        padding=1)
-
-    def forward(self, x):
-        x = torch.nn.functional.interpolate(x, scale_factor=2.0, mode="nearest")
-        if self.with_conv:
-            x = self.conv(x)
-        return x
-
-
-class Downsample(nn.Module):
-    def __init__(self, in_channels, with_conv):
-        super().__init__()
-        self.with_conv = with_conv
-        if self.with_conv:
-            # no asymmetric padding in torch conv, must do it ourselves
-            self.conv = torch.nn.Conv2d(in_channels,
-                                        in_channels,
-                                        kernel_size=3,
-                                        stride=2,
-                                        padding=0)
-
-    def forward(self, x):
-        if self.with_conv:
-            pad = (0,1,0,1)
-            x = torch.nn.functional.pad(x, pad, mode="constant", value=0)
-            x = self.conv(x)
-        else:
-            x = torch.nn.functional.avg_pool2d(x, kernel_size=2, stride=2)
-        return x
-
-
-class ResnetBlock(nn.Module):
-    def __init__(self, *, in_channels, out_channels=None, conv_shortcut=False,
-                 dropout, temb_channels=512):
-        super().__init__()
-        self.in_channels = in_channels
-        out_channels = in_channels if out_channels is None else out_channels
-        self.out_channels = out_channels
-        self.use_conv_shortcut = conv_shortcut
-
-        self.norm1 = Normalize(in_channels)
-        self.conv1 = torch.nn.Conv2d(in_channels,
-                                     out_channels,
-                                     kernel_size=3,
-                                     stride=1,
-                                     padding=1)
-        if temb_channels > 0:
-            self.temb_proj = torch.nn.Linear(temb_channels,
-                                             out_channels)
-        self.norm2 = Normalize(out_channels)
-        self.dropout = torch.nn.Dropout(dropout)
-        self.conv2 = torch.nn.Conv2d(out_channels,
-                                     out_channels,
-                                     kernel_size=3,
-                                     stride=1,
-                                     padding=1)
-        if self.in_channels != self.out_channels:
-            if self.use_conv_shortcut:
-                self.conv_shortcut = torch.nn.Conv2d(in_channels,
-                                                     out_channels,
-                                                     kernel_size=3,
-                                                     stride=1,
-                                                     padding=1)
-            else:
-                self.nin_shortcut = torch.nn.Conv2d(in_channels,
-                                                    out_channels,
-                                                    kernel_size=1,
-                                                    stride=1,
-                                                    padding=0)
-
-    def forward(self, x, temb):
-        h = x
-        h = self.norm1(h)
-        h = nonlinearity(h)
-        h = self.conv1(h)
-
-        if temb is not None:
-            h = h + self.temb_proj(nonlinearity(temb))[:,:,None,None]
-
-        h = self.norm2(h)
-        h = nonlinearity(h)
-        h = self.dropout(h)
-        h = self.conv2(h)
-
-        if self.in_channels != self.out_channels:
-            if self.use_conv_shortcut:
-                x = self.conv_shortcut(x)
-            else:
-                x = self.nin_shortcut(x)
-
-        return x+h
-
-
-class MultiHeadAttnBlock(nn.Module):
-    def __init__(self, in_channels, head_size=1):
-        super().__init__()
-        self.in_channels = in_channels
-        self.head_size = head_size
-        self.att_size = in_channels // head_size
-        assert(in_channels % head_size == 0), 'The size of head should be divided by the number of channels.'
-
-        self.norm1 = Normalize(in_channels)
-        self.norm2 = Normalize(in_channels)
-
-        self.q = torch.nn.Conv2d(in_channels,
-                                 in_channels,
-                                 kernel_size=1,
-                                 stride=1,
-                                 padding=0)
-        self.k = torch.nn.Conv2d(in_channels,
-                                 in_channels,
-                                 kernel_size=1,
-                                 stride=1,
-                                 padding=0)
-        self.v = torch.nn.Conv2d(in_channels,
-                                 in_channels,
-                                 kernel_size=1,
-                                 stride=1,
-                                 padding=0)
-        self.proj_out = torch.nn.Conv2d(in_channels,
-                                        in_channels,
-                                        kernel_size=1,
-                                        stride=1,
-                                        padding=0)
-        self.num = 0
-
-    def forward(self, x, y=None):
-        h_ = x
-        h_ = self.norm1(h_)
-        if y is None:
-            y = h_
-        else:
-            y = self.norm2(y)
-
-        q = self.q(y)
-        k = self.k(h_)
-        v = self.v(h_)
-
-        # compute attention
-        b,c,h,w = q.shape
-        q = q.reshape(b, self.head_size, self.att_size ,h*w) 
-        q = q.permute(0, 3, 1, 2) # b, hw, head, att
-
-        k = k.reshape(b, self.head_size, self.att_size ,h*w) 
-        k = k.permute(0, 3, 1, 2)
-
-        v = v.reshape(b, self.head_size, self.att_size ,h*w) 
-        v = v.permute(0, 3, 1, 2)
-
-
-        q = q.transpose(1, 2)
-        v = v.transpose(1, 2)
-        k = k.transpose(1, 2).transpose(2,3)
-
-        scale = int(self.att_size)**(-0.5)
-        q.mul_(scale)
-        w_ = torch.matmul(q, k)
-        w_ = F.softmax(w_, dim=3)
-
-        w_ = w_.matmul(v)
-
-        w_ = w_.transpose(1, 2).contiguous() # [b, h*w, head, att]
-        w_ = w_.view(b, h, w, -1)
-        w_ = w_.permute(0, 3, 1, 2)
-
-        w_ = self.proj_out(w_)
-
-        return x+w_
-
-
-class MultiHeadEncoder(nn.Module):
-    def __init__(self, ch, out_ch, ch_mult=(1,2,4,8), num_res_blocks=2,
-                 attn_resolutions=[16], dropout=0.0, resamp_with_conv=True, in_channels=3,
-                 resolution=512, z_channels=256, double_z=True, enable_mid=True,
-                 head_size=1, **ignore_kwargs):
-        super().__init__()
-        self.ch = ch
-        self.temb_ch = 0
-        self.num_resolutions = len(ch_mult)
-        self.num_res_blocks = num_res_blocks
-        self.resolution = resolution
-        self.in_channels = in_channels
-        self.enable_mid = enable_mid
-
-        # downsampling
-        self.conv_in = torch.nn.Conv2d(in_channels,
-                                       self.ch,
-                                       kernel_size=3,
-                                       stride=1,
-                                       padding=1)
-
-        curr_res = resolution
-        in_ch_mult = (1,)+tuple(ch_mult)
-        self.down = nn.ModuleList()
-        for i_level in range(self.num_resolutions):
-            block = nn.ModuleList()
-            attn = nn.ModuleList()
-            block_in = ch*in_ch_mult[i_level]
-            block_out = ch*ch_mult[i_level]
-            for i_block in range(self.num_res_blocks):
-                block.append(ResnetBlock(in_channels=block_in,
-                                         out_channels=block_out,
-                                         temb_channels=self.temb_ch,
-                                         dropout=dropout))
-                block_in = block_out
-                if curr_res in attn_resolutions:
-                    attn.append(MultiHeadAttnBlock(block_in, head_size))
-            down = nn.Module()
-            down.block = block
-            down.attn = attn
-            if i_level != self.num_resolutions-1:
-                down.downsample = Downsample(block_in, resamp_with_conv)
-                curr_res = curr_res // 2
-            self.down.append(down)
-
-        # middle
-        if self.enable_mid:
-            self.mid = nn.Module()
-            self.mid.block_1 = ResnetBlock(in_channels=block_in,
-                                           out_channels=block_in,
-                                           temb_channels=self.temb_ch,
-                                           dropout=dropout)
-            self.mid.attn_1 = MultiHeadAttnBlock(block_in, head_size)
-            self.mid.block_2 = ResnetBlock(in_channels=block_in,
-                                           out_channels=block_in,
-                                           temb_channels=self.temb_ch,
-                                           dropout=dropout)
-
-        # end
-        self.norm_out = Normalize(block_in)
-        self.conv_out = torch.nn.Conv2d(block_in,
-                                        2*z_channels if double_z else z_channels,
-                                        kernel_size=3,
-                                        stride=1,
-                                        padding=1)
-
-
-    def forward(self, x):
-        #assert x.shape[2] == x.shape[3] == self.resolution, "{}, {}, {}".format(x.shape[2], x.shape[3], self.resolution)
-
-        hs = {}
-        # timestep embedding
-        temb = None
-
-        # downsampling
-        h = self.conv_in(x)
-        hs['in'] = h
-        for i_level in range(self.num_resolutions):
-            for i_block in range(self.num_res_blocks):
-                h = self.down[i_level].block[i_block](h, temb)
-                if len(self.down[i_level].attn) > 0:
-                    h = self.down[i_level].attn[i_block](h)
-
-            if i_level != self.num_resolutions-1:
-                # hs.append(h)
-                hs['block_'+str(i_level)] = h
-                h = self.down[i_level].downsample(h)
-
-        # middle
-        # h = hs[-1]
-        if self.enable_mid:
-            h = self.mid.block_1(h, temb)
-            hs['block_'+str(i_level)+'_atten'] = h
-            h = self.mid.attn_1(h)
-            h = self.mid.block_2(h, temb)
-            hs['mid_atten'] = h
-
-        # end
-        h = self.norm_out(h)
-        h = nonlinearity(h)
-        h = self.conv_out(h)
-        # hs.append(h)
-        hs['out'] = h
-
-        return hs
-
-class MultiHeadDecoder(nn.Module):
-    def __init__(self, ch, out_ch, ch_mult=(1,2,4,8), num_res_blocks=2,
-                 attn_resolutions=16, dropout=0.0, resamp_with_conv=True, in_channels=3,
-                 resolution=512, z_channels=256, give_pre_end=False, enable_mid=True,
-                 head_size=1, **ignorekwargs):
-        super().__init__()
-        self.ch = ch
-        self.temb_ch = 0
-        self.num_resolutions = len(ch_mult)
-        self.num_res_blocks = num_res_blocks
-        self.resolution = resolution
-        self.in_channels = in_channels
-        self.give_pre_end = give_pre_end
-        self.enable_mid = enable_mid
-
-        # compute in_ch_mult, block_in and curr_res at lowest res
-        in_ch_mult = (1,)+tuple(ch_mult)
-        block_in = ch*ch_mult[self.num_resolutions-1]
-        curr_res = resolution // 2**(self.num_resolutions-1)
-        self.z_shape = (1,z_channels,curr_res,curr_res)
-        print("Working with z of shape {} = {} dimensions.".format(
-            self.z_shape, np.prod(self.z_shape)))
-
-        # z to block_in
-        self.conv_in = torch.nn.Conv2d(z_channels,
-                                       block_in,
-                                       kernel_size=3,
-                                       stride=1,
-                                       padding=1)
-
-        # middle
-        if self.enable_mid:
-            self.mid = nn.Module()
-            self.mid.block_1 = ResnetBlock(in_channels=block_in,
-                                           out_channels=block_in,
-                                           temb_channels=self.temb_ch,
-                                           dropout=dropout)
-            self.mid.attn_1 = MultiHeadAttnBlock(block_in, head_size)
-            self.mid.block_2 = ResnetBlock(in_channels=block_in,
-                                           out_channels=block_in,
-                                           temb_channels=self.temb_ch,
-                                           dropout=dropout)
-
-        # upsampling
-        self.up = nn.ModuleList()
-        for i_level in reversed(range(self.num_resolutions)):
-            block = nn.ModuleList()
-            attn = nn.ModuleList()
-            block_out = ch*ch_mult[i_level]
-            for i_block in range(self.num_res_blocks+1):
-                block.append(ResnetBlock(in_channels=block_in,
-                                         out_channels=block_out,
-                                         temb_channels=self.temb_ch,
-                                         dropout=dropout))
-                block_in = block_out
-                if curr_res in attn_resolutions:
-                    attn.append(MultiHeadAttnBlock(block_in, head_size))
-            up = nn.Module()
-            up.block = block
-            up.attn = attn
-            if i_level != 0:
-                up.upsample = Upsample(block_in, resamp_with_conv)
-                curr_res = curr_res * 2
-            self.up.insert(0, up) # prepend to get consistent order
-
-        # end
-        self.norm_out = Normalize(block_in)
-        self.conv_out = torch.nn.Conv2d(block_in,
-                                        out_ch,
-                                        kernel_size=3,
-                                        stride=1,
-                                        padding=1)
-
-    def forward(self, z):
-        #assert z.shape[1:] == self.z_shape[1:]
-        self.last_z_shape = z.shape
-
-        # timestep embedding
-        temb = None
-
-        # z to block_in
-        h = self.conv_in(z)
-
-        # middle
-        if self.enable_mid:
-            h = self.mid.block_1(h, temb)
-            h = self.mid.attn_1(h)
-            h = self.mid.block_2(h, temb)
-
-        # upsampling
-        for i_level in reversed(range(self.num_resolutions)):
-            for i_block in range(self.num_res_blocks+1):
-                h = self.up[i_level].block[i_block](h, temb)
-                if len(self.up[i_level].attn) > 0:
-                    h = self.up[i_level].attn[i_block](h)
-            if i_level != 0:
-                h = self.up[i_level].upsample(h)
-
-        # end
-        if self.give_pre_end:
-            return h
-
-        h = self.norm_out(h)
-        h = nonlinearity(h)
-        h = self.conv_out(h)
-        return h
-
-class MultiHeadDecoderTransformer(nn.Module):
-    def __init__(self, ch, out_ch, ch_mult=(1,2,4,8), num_res_blocks=2,
-                 attn_resolutions=16, dropout=0.0, resamp_with_conv=True, in_channels=3,
-                 resolution=512, z_channels=256, give_pre_end=False, enable_mid=True,
-                 head_size=1, **ignorekwargs):
-        super().__init__()
-        self.ch = ch
-        self.temb_ch = 0
-        self.num_resolutions = len(ch_mult)
-        self.num_res_blocks = num_res_blocks
-        self.resolution = resolution
-        self.in_channels = in_channels
-        self.give_pre_end = give_pre_end
-        self.enable_mid = enable_mid
-
-        # compute in_ch_mult, block_in and curr_res at lowest res
-        in_ch_mult = (1,)+tuple(ch_mult)
-        block_in = ch*ch_mult[self.num_resolutions-1]
-        curr_res = resolution // 2**(self.num_resolutions-1)
-        self.z_shape = (1,z_channels,curr_res,curr_res)
-        print("Working with z of shape {} = {} dimensions.".format(
-            self.z_shape, np.prod(self.z_shape)))
-
-        # z to block_in
-        self.conv_in = torch.nn.Conv2d(z_channels,
-                                       block_in,
-                                       kernel_size=3,
-                                       stride=1,
-                                       padding=1)
-
-        # middle
-        if self.enable_mid:
-            self.mid = nn.Module()
-            self.mid.block_1 = ResnetBlock(in_channels=block_in,
-                                           out_channels=block_in,
-                                           temb_channels=self.temb_ch,
-                                           dropout=dropout)
-            self.mid.attn_1 = MultiHeadAttnBlock(block_in, head_size)
-            self.mid.block_2 = ResnetBlock(in_channels=block_in,
-                                           out_channels=block_in,
-                                           temb_channels=self.temb_ch,
-                                           dropout=dropout)
-
-        # upsampling
-        self.up = nn.ModuleList()
-        for i_level in reversed(range(self.num_resolutions)):
-            block = nn.ModuleList()
-            attn = nn.ModuleList()
-            block_out = ch*ch_mult[i_level]
-            for i_block in range(self.num_res_blocks+1):
-                block.append(ResnetBlock(in_channels=block_in,
-                                         out_channels=block_out,
-                                         temb_channels=self.temb_ch,
-                                         dropout=dropout))
-                block_in = block_out
-                if curr_res in attn_resolutions:
-                    attn.append(MultiHeadAttnBlock(block_in, head_size))
-            up = nn.Module()
-            up.block = block
-            up.attn = attn
-            if i_level != 0:
-                up.upsample = Upsample(block_in, resamp_with_conv)
-                curr_res = curr_res * 2
-            self.up.insert(0, up) # prepend to get consistent order
-
-        # end
-        self.norm_out = Normalize(block_in)
-        self.conv_out = torch.nn.Conv2d(block_in,
-                                        out_ch,
-                                        kernel_size=3,
-                                        stride=1,
-                                        padding=1)
-
-    def forward(self, z, hs):
-        #assert z.shape[1:] == self.z_shape[1:]
-        # self.last_z_shape = z.shape
-
-        # timestep embedding
-        temb = None
-
-        # z to block_in
-        h = self.conv_in(z)
-
-        # middle
-        if self.enable_mid:
-            h = self.mid.block_1(h, temb)
-            h = self.mid.attn_1(h, hs['mid_atten'])
-            h = self.mid.block_2(h, temb)
-
-        # upsampling
-        for i_level in reversed(range(self.num_resolutions)):
-            for i_block in range(self.num_res_blocks+1):
-                h = self.up[i_level].block[i_block](h, temb)
-                if len(self.up[i_level].attn) > 0:
-                    if 'block_'+str(i_level)+'_atten' in hs:
-                        h = self.up[i_level].attn[i_block](h, hs['block_'+str(i_level)+'_atten'])
-                    else:
-                        h = self.up[i_level].attn[i_block](h, hs['block_'+str(i_level)])
-            if i_level != 0:
-                h = self.up[i_level].upsample(h)
-
-        # end
-        if self.give_pre_end:
-            return h
-
-        h = self.norm_out(h)
-        h = nonlinearity(h)
-        h = self.conv_out(h)
-        return h
-
-
-class VQVAEGAN(nn.Module):
-    def __init__(self, n_embed=1024, embed_dim=256, ch=128, out_ch=3, ch_mult=(1,2,4,8), 
-                 num_res_blocks=2, attn_resolutions=16, dropout=0.0, in_channels=3, 
-                 resolution=512, z_channels=256, double_z=False, enable_mid=True, 
-                 fix_decoder=False, fix_codebook=False, head_size=1, **ignore_kwargs):
-        super(VQVAEGAN, self).__init__()
-
-        self.encoder = MultiHeadEncoder(ch=ch, out_ch=out_ch, ch_mult=ch_mult, num_res_blocks=num_res_blocks,
-                               attn_resolutions=attn_resolutions, dropout=dropout, in_channels=in_channels,
-                               resolution=resolution, z_channels=z_channels, double_z=double_z, 
-                               enable_mid=enable_mid, head_size=head_size)
-        self.decoder = MultiHeadDecoder(ch=ch, out_ch=out_ch, ch_mult=ch_mult, num_res_blocks=num_res_blocks,
-                               attn_resolutions=attn_resolutions, dropout=dropout, in_channels=in_channels,
-                               resolution=resolution, z_channels=z_channels, enable_mid=enable_mid, head_size=head_size)
-
-        self.quantize = VectorQuantizer(n_embed, embed_dim, beta=0.25)
-
-        self.quant_conv = torch.nn.Conv2d(z_channels, embed_dim, 1)
-        self.post_quant_conv = torch.nn.Conv2d(embed_dim, z_channels, 1)
-
-        if fix_decoder:
-            for _, param in self.decoder.named_parameters():
-                param.requires_grad = False
-            for _, param in self.post_quant_conv.named_parameters():
-                param.requires_grad = False
-            for _, param in self.quantize.named_parameters():
-                param.requires_grad = False
-        elif fix_codebook:
-            for _, param in self.quantize.named_parameters():
-                param.requires_grad = False
-
-    def encode(self, x):
-
-        hs = self.encoder(x)
-        h = self.quant_conv(hs['out'])
-        quant, emb_loss, info = self.quantize(h)
-        return quant, emb_loss, info, hs
-
-    def decode(self, quant):
-        quant = self.post_quant_conv(quant)
-        dec = self.decoder(quant)
-
-        return dec
-
-    def forward(self, input):
-        quant, diff, info, hs = self.encode(input)
-        dec = self.decode(quant)
-
-        return dec, diff, info, hs
-
-class VQVAEGANMultiHeadTransformer(nn.Module):
-    def __init__(self,
-                 n_embed=1024,
-                 embed_dim=256,
-                 ch=64,
-                 out_ch=3,
-                 ch_mult=(1, 2, 2, 4, 4, 8),
-                 num_res_blocks=2,
-                 attn_resolutions=(16, ),
-                 dropout=0.0,
-                 in_channels=3,
-                 resolution=512,
-                 z_channels=256,
-                 double_z=False,
-                 enable_mid=True,
-                 fix_decoder=False,
-                 fix_codebook=True,
-                 fix_encoder=False,
-                 head_size=4,
-                 ex_multi_scale_num=1):
-        super(VQVAEGANMultiHeadTransformer, self).__init__()
-
-        self.encoder = MultiHeadEncoder(ch=ch, out_ch=out_ch, ch_mult=ch_mult, num_res_blocks=num_res_blocks,
-                               attn_resolutions=attn_resolutions, dropout=dropout, in_channels=in_channels,
-                               resolution=resolution, z_channels=z_channels, double_z=double_z, 
-                               enable_mid=enable_mid, head_size=head_size)
-        for i in range(ex_multi_scale_num):
-                attn_resolutions = [attn_resolutions[0], attn_resolutions[-1]*2]
-        self.decoder = MultiHeadDecoderTransformer(ch=ch, out_ch=out_ch, ch_mult=ch_mult, num_res_blocks=num_res_blocks,
-                               attn_resolutions=attn_resolutions, dropout=dropout, in_channels=in_channels,
-                               resolution=resolution, z_channels=z_channels, enable_mid=enable_mid, head_size=head_size)
-
-        self.quantize = VectorQuantizer(n_embed, embed_dim, beta=0.25)
-
-        self.quant_conv = torch.nn.Conv2d(z_channels, embed_dim, 1)
-        self.post_quant_conv = torch.nn.Conv2d(embed_dim, z_channels, 1)
-
-        if fix_decoder:
-            for _, param in self.decoder.named_parameters():
-                param.requires_grad = False
-            for _, param in self.post_quant_conv.named_parameters():
-                param.requires_grad = False
-            for _, param in self.quantize.named_parameters():
-                param.requires_grad = False
-        elif fix_codebook:
-            for _, param in self.quantize.named_parameters():
-                param.requires_grad = False
-
-        if fix_encoder:
-            for _, param in self.encoder.named_parameters():
-                param.requires_grad = False
-            for _, param in self.quant_conv.named_parameters():
-                param.requires_grad = False
-	    
-
-    def encode(self, x):
-        
-        hs = self.encoder(x)
-        h = self.quant_conv(hs['out'])
-        quant, emb_loss, info = self.quantize(h)
-        return quant, emb_loss, info, hs
-
-    def decode(self, quant, hs):
-        quant = self.post_quant_conv(quant)
-        dec = self.decoder(quant, hs)
-
-        return dec
-
-    def forward(self, input):
-        quant, diff, info, hs = self.encode(input)
-        dec = self.decode(quant, hs)
-
-        return dec, diff, info, hs
\ No newline at end of file
diff --git a/spaces/xdecoder/Instruct-X-Decoder/xdecoder/modules/postprocessing.py b/spaces/xdecoder/Instruct-X-Decoder/xdecoder/modules/postprocessing.py
deleted file mode 100644
index eef2047589674fda092bebc310bd394a3db57074..0000000000000000000000000000000000000000
--- a/spaces/xdecoder/Instruct-X-Decoder/xdecoder/modules/postprocessing.py
+++ /dev/null
@@ -1,122 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-import torch
-from torch.nn import functional as F
-
-from detectron2.structures import Instances, ROIMasks
-
-
-# perhaps should rename to "resize_instance"
-def detector_postprocess(
-    results: Instances, output_height: int, output_width: int, mask_threshold: float = 0.5
-):
-    """
-    Resize the output instances.
-    The input images are often resized when entering an object detector.
-    As a result, we often need the outputs of the detector in a different
-    resolution from its inputs.
-
-    This function will resize the raw outputs of an R-CNN detector
-    to produce outputs according to the desired output resolution.
-
-    Args:
-        results (Instances): the raw outputs from the detector.
-            `results.image_size` contains the input image resolution the detector sees.
-            This object might be modified in-place.
-        output_height, output_width: the desired output resolution.
-
-    Returns:
-        Instances: the resized output from the model, based on the output resolution
-    """
-    if isinstance(output_width, torch.Tensor):
-        # This shape might (but not necessarily) be tensors during tracing.
-        # Converts integer tensors to float temporaries to ensure true
-        # division is performed when computing scale_x and scale_y.
-        output_width_tmp = output_width.float()
-        output_height_tmp = output_height.float()
-        new_size = torch.stack([output_height, output_width])
-    else:
-        new_size = (output_height, output_width)
-        output_width_tmp = output_width
-        output_height_tmp = output_height
-
-    scale_x, scale_y = (
-        output_width_tmp / results.image_size[1],
-        output_height_tmp / results.image_size[0],
-    )
-    results = Instances(new_size, **results.get_fields())
-
-    if results.has("pred_boxes"):
-        output_boxes = results.pred_boxes
-    elif results.has("proposal_boxes"):
-        output_boxes = results.proposal_boxes
-    else:
-        output_boxes = None
-    assert output_boxes is not None, "Predictions must contain boxes!"
-
-    output_boxes.scale(scale_x, scale_y)
-    output_boxes.clip(results.image_size)
-
-    results = results[output_boxes.nonempty()]
-
-    if results.has("pred_masks"):
-        if isinstance(results.pred_masks, ROIMasks):
-            roi_masks = results.pred_masks
-        else:
-            # pred_masks is a tensor of shape (N, 1, M, M)
-            roi_masks = ROIMasks(results.pred_masks[:, 0, :, :])
-        results.pred_masks = roi_masks.to_bitmasks(
-            results.pred_boxes, output_height, output_width, mask_threshold
-        ).tensor  # TODO return ROIMasks/BitMask object in the future
-
-    if results.has("pred_keypoints"):
-        results.pred_keypoints[:, :, 0] *= scale_x
-        results.pred_keypoints[:, :, 1] *= scale_y
-
-    return results
-
-def bbox_postprocess(result, input_size, img_size, output_height, output_width):
-    """
-    result: [xc,yc,w,h] range [0,1] to [x1,y1,x2,y2] range [0,w], [0,h]
-    """
-    if result is None:
-        return None
-    
-    scale = torch.tensor([input_size[1], input_size[0], input_size[1], input_size[0]])[None,:].to(result.device)
-    result = result.sigmoid() * scale
-    x1,y1,x2,y2 = result[:,0] - result[:,2]/2, result[:,1] - result[:,3]/2, result[:,0] + result[:,2]/2, result[:,1] + result[:,3]/2
-    h,w = img_size
-
-    x1 = x1.clamp(min=0, max=w)
-    y1 = y1.clamp(min=0, max=h)
-    x2 = x2.clamp(min=0, max=w)
-    y2 = y2.clamp(min=0, max=h)
-
-    box = torch.stack([x1,y1,x2,y2]).permute(1,0)
-    scale = torch.tensor([output_width/w, output_height/h, output_width/w, output_height/h])[None,:].to(result.device)
-    box = box*scale
-    return box
-
-def sem_seg_postprocess(result, img_size, output_height, output_width):
-    """
-    Return semantic segmentation predictions in the original resolution.
-
-    The input images are often resized when entering semantic segmentor. Moreover, in same
-    cases, they also padded inside segmentor to be divisible by maximum network stride.
-    As a result, we often need the predictions of the segmentor in a different
-    resolution from its inputs.
-
-    Args:
-        result (Tensor): semantic segmentation prediction logits. A tensor of shape (C, H, W),
-            where C is the number of classes, and H, W are the height and width of the prediction.
-        img_size (tuple): image size that segmentor is taking as input.
-        output_height, output_width: the desired output resolution.
-
-    Returns:
-        semantic segmentation prediction (Tensor): A tensor of the shape
-            (C, output_height, output_width) that contains per-pixel soft predictions.
-    """
-    result = result[:, : img_size[0], : img_size[1]].expand(1, -1, -1, -1)
-    result = F.interpolate(
-        result, size=(output_height, output_width), mode="bilinear", align_corners=False
-    )[0]
-    return result
diff --git a/spaces/xiaoxuezi/spleeter/spleeter/audio/__init__.py b/spaces/xiaoxuezi/spleeter/spleeter/audio/__init__.py
deleted file mode 100644
index 32012e18d2e2f006d01be247fd4794aece818b28..0000000000000000000000000000000000000000
--- a/spaces/xiaoxuezi/spleeter/spleeter/audio/__init__.py
+++ /dev/null
@@ -1,52 +0,0 @@
-#!/usr/bin/env python
-# coding: utf8
-
-"""
-    `spleeter.utils.audio` package provides various
-    tools for manipulating audio content such as :
-
-    - Audio adapter class for abstract interaction with audio file.
-    - FFMPEG implementation for audio adapter.
-    - Waveform convertion and transforming functions.
-"""
-
-from enum import Enum
-
-__email__ = "spleeter@deezer.com"
-__author__ = "Deezer Research"
-__license__ = "MIT License"
-
-
-class Codec(str, Enum):
-    """ Enumeration of supported audio codec. """
-
-    WAV: str = "wav"
-    MP3: str = "mp3"
-    OGG: str = "ogg"
-    M4A: str = "m4a"
-    WMA: str = "wma"
-    FLAC: str = "flac"
-
-
-class STFTBackend(str, Enum):
-    """ Enumeration of supported STFT backend. """
-
-    AUTO: str = "auto"
-    TENSORFLOW: str = "tensorflow"
-    LIBROSA: str = "librosa"
-
-    @classmethod
-    def resolve(cls: type, backend: str) -> str:
-        # NOTE: import is resolved here to avoid performance issues on command
-        #       evaluation.
-        # pyright: reportMissingImports=false
-        # pylint: disable=import-error
-        import tensorflow as tf
-
-        if backend not in cls.__members__.values():
-            raise ValueError(f"Unsupported backend {backend}")
-        if backend == cls.AUTO:
-            if len(tf.config.list_physical_devices("GPU")):
-                return cls.TENSORFLOW
-            return cls.LIBROSA
-        return backend
diff --git a/spaces/yaelvinker/CLIPasso/models/loss.py b/spaces/yaelvinker/CLIPasso/models/loss.py
deleted file mode 100644
index 2617e01e7cf40debe034027359a56f9d9964d4f7..0000000000000000000000000000000000000000
--- a/spaces/yaelvinker/CLIPasso/models/loss.py
+++ /dev/null
@@ -1,463 +0,0 @@
-
-import collections
-import CLIP_.clip as clip
-import torch
-import torch.nn as nn
-from torchvision import models, transforms
-
-
-class Loss(nn.Module):
-    def __init__(self, args):
-        super(Loss, self).__init__()
-        self.args = args
-        self.percep_loss = args.percep_loss
-
-        self.train_with_clip = args.train_with_clip
-        self.clip_weight = args.clip_weight
-        self.start_clip = args.start_clip
-
-        self.clip_conv_loss = args.clip_conv_loss
-        self.clip_fc_loss_weight = args.clip_fc_loss_weight
-        self.clip_text_guide = args.clip_text_guide
-
-        self.losses_to_apply = self.get_losses_to_apply()
-
-        self.loss_mapper = \
-            {
-                "clip": CLIPLoss(args),
-                "clip_conv_loss": CLIPConvLoss(args)
-            }
-
-    def get_losses_to_apply(self):
-        losses_to_apply = []
-        if self.percep_loss != "none":
-            losses_to_apply.append(self.percep_loss)
-        if self.train_with_clip and self.start_clip == 0:
-            losses_to_apply.append("clip")
-        if self.clip_conv_loss:
-            losses_to_apply.append("clip_conv_loss")
-        if self.clip_text_guide:
-            losses_to_apply.append("clip_text")
-        return losses_to_apply
-
-    def update_losses_to_apply(self, epoch):
-        if "clip" not in self.losses_to_apply:
-            if self.train_with_clip:
-                if epoch > self.start_clip:
-                    self.losses_to_apply.append("clip")
-
-    def forward(self, sketches, targets, color_parameters, renderer, epoch, points_optim=None, mode="train"):
-        loss = 0
-        self.update_losses_to_apply(epoch)
-
-        losses_dict = dict.fromkeys(
-            self.losses_to_apply, torch.tensor([0.0]).to(self.args.device))
-        loss_coeffs = dict.fromkeys(self.losses_to_apply, 1.0)
-        loss_coeffs["clip"] = self.clip_weight
-        loss_coeffs["clip_text"] = self.clip_text_guide
-
-        for loss_name in self.losses_to_apply:
-            if loss_name in ["clip_conv_loss"]:
-                conv_loss = self.loss_mapper[loss_name](
-                    sketches, targets, mode)
-                for layer in conv_loss.keys():
-                    losses_dict[layer] = conv_loss[layer]
-            elif loss_name == "l2":
-                losses_dict[loss_name] = self.loss_mapper[loss_name](
-                    sketches, targets).mean()
-            else:
-                losses_dict[loss_name] = self.loss_mapper[loss_name](
-                    sketches, targets, mode).mean()
-            # loss = loss + self.loss_mapper[loss_name](sketches, targets).mean() * loss_coeffs[loss_name]
-
-        for key in self.losses_to_apply:
-            # loss = loss + losses_dict[key] * loss_coeffs[key]
-            losses_dict[key] = losses_dict[key] * loss_coeffs[key]
-        # print(losses_dict)
-        return losses_dict
-
-
-class CLIPLoss(torch.nn.Module):
-    def __init__(self, args):
-        super(CLIPLoss, self).__init__()
-
-        self.args = args
-        self.model, clip_preprocess = clip.load(
-            'ViT-B/32', args.device, jit=False)
-        self.model.eval()
-        self.preprocess = transforms.Compose(
-            [clip_preprocess.transforms[-1]])  # clip normalisation
-        self.device = args.device
-        self.NUM_AUGS = args.num_aug_clip
-        augemntations = []
-        if "affine" in args.augemntations:
-            augemntations.append(transforms.RandomPerspective(
-                fill=0, p=1.0, distortion_scale=0.5))
-            augemntations.append(transforms.RandomResizedCrop(
-                224, scale=(0.8, 0.8), ratio=(1.0, 1.0)))
-        augemntations.append(
-            transforms.Normalize((0.48145466, 0.4578275, 0.40821073), (0.26862954, 0.26130258, 0.27577711)))
-        self.augment_trans = transforms.Compose(augemntations)
-
-        self.calc_target = True
-        self.include_target_in_aug = args.include_target_in_aug
-        self.counter = 0
-        self.augment_both = args.augment_both
-
-    def forward(self, sketches, targets, mode="train"):
-        if self.calc_target:
-            targets_ = self.preprocess(targets).to(self.device)
-            self.targets_features = self.model.encode_image(targets_).detach()
-            self.calc_target = False
-
-        if mode == "eval":
-            # for regular clip distance, no augmentations
-            with torch.no_grad():
-                sketches = self.preprocess(sketches).to(self.device)
-                sketches_features = self.model.encode_image(sketches)
-                return 1. - torch.cosine_similarity(sketches_features, self.targets_features)
-
-        loss_clip = 0
-        sketch_augs = []
-        img_augs = []
-        for n in range(self.NUM_AUGS):
-            augmented_pair = self.augment_trans(torch.cat([sketches, targets]))
-            sketch_augs.append(augmented_pair[0].unsqueeze(0))
-
-        sketch_batch = torch.cat(sketch_augs)
-        # sketch_utils.plot_batch(img_batch, sketch_batch, self.args, self.counter, use_wandb=False, title="fc_aug{}_iter{}_{}.jpg".format(1, self.counter, mode))
-        # if self.counter % 100 == 0:
-        # sketch_utils.plot_batch(img_batch, sketch_batch, self.args, self.counter, use_wandb=False, title="aug{}_iter{}_{}.jpg".format(1, self.counter, mode))
-
-        sketch_features = self.model.encode_image(sketch_batch)
-
-        for n in range(self.NUM_AUGS):
-            loss_clip += (1. - torch.cosine_similarity(
-                sketch_features[n:n+1], self.targets_features, dim=1))
-        self.counter += 1
-        return loss_clip
-        # return 1. - torch.cosine_similarity(sketches_features, self.targets_features)
-
-
-class LPIPS(torch.nn.Module):
-    def __init__(self, pretrained=True, normalize=True, pre_relu=True, device=None):
-        """
-        Args:
-            pre_relu(bool): if True, selects features **before** reLU activations
-        """
-        super(LPIPS, self).__init__()
-        # VGG using perceptually-learned weights (LPIPS metric)
-        self.normalize = normalize
-        self.pretrained = pretrained
-        augemntations = []
-        augemntations.append(transforms.RandomPerspective(
-            fill=0, p=1.0, distortion_scale=0.5))
-        augemntations.append(transforms.RandomResizedCrop(
-            224, scale=(0.8, 0.8), ratio=(1.0, 1.0)))
-        self.augment_trans = transforms.Compose(augemntations)
-        self.feature_extractor = LPIPS._FeatureExtractor(
-            pretrained, pre_relu).to(device)
-
-    def _l2_normalize_features(self, x, eps=1e-10):
-        nrm = torch.sqrt(torch.sum(x * x, dim=1, keepdim=True))
-        return x / (nrm + eps)
-
-    def forward(self, pred, target, mode="train"):
-        """Compare VGG features of two inputs."""
-
-        # Get VGG features
-
-        sketch_augs, img_augs = [pred], [target]
-        if mode == "train":
-            for n in range(4):
-                augmented_pair = self.augment_trans(torch.cat([pred, target]))
-                sketch_augs.append(augmented_pair[0].unsqueeze(0))
-                img_augs.append(augmented_pair[1].unsqueeze(0))
-
-        xs = torch.cat(sketch_augs, dim=0)
-        ys = torch.cat(img_augs, dim=0)
-
-        pred = self.feature_extractor(xs)
-        target = self.feature_extractor(ys)
-
-        # L2 normalize features
-        if self.normalize:
-            pred = [self._l2_normalize_features(f) for f in pred]
-            target = [self._l2_normalize_features(f) for f in target]
-
-        # TODO(mgharbi) Apply Richard's linear weights?
-
-        if self.normalize:
-            diffs = [torch.sum((p - t) ** 2, 1)
-                     for (p, t) in zip(pred, target)]
-        else:
-            # mean instead of sum to avoid super high range
-            diffs = [torch.mean((p - t) ** 2, 1)
-                     for (p, t) in zip(pred, target)]
-
-        # Spatial average
-        diffs = [diff.mean([1, 2]) for diff in diffs]
-
-        return sum(diffs)
-
-    class _FeatureExtractor(torch.nn.Module):
-        def __init__(self, pretrained, pre_relu):
-            super(LPIPS._FeatureExtractor, self).__init__()
-            vgg_pretrained = models.vgg16(pretrained=pretrained).features
-
-            self.breakpoints = [0, 4, 9, 16, 23, 30]
-            if pre_relu:
-                for i, _ in enumerate(self.breakpoints[1:]):
-                    self.breakpoints[i + 1] -= 1
-
-            # Split at the maxpools
-            for i, b in enumerate(self.breakpoints[:-1]):
-                ops = torch.nn.Sequential()
-                for idx in range(b, self.breakpoints[i + 1]):
-                    op = vgg_pretrained[idx]
-                    ops.add_module(str(idx), op)
-                # print(ops)
-                self.add_module("group{}".format(i), ops)
-
-            # No gradients
-            for p in self.parameters():
-                p.requires_grad = False
-
-            # Torchvision's normalization: <https://github.com/pytorch/examples/blob/42e5b996718797e45c46a25c55b031e6768f8440/imagenet/main.py#L89-L101>
-            self.register_buffer("shift", torch.Tensor(
-                [0.485, 0.456, 0.406]).view(1, 3, 1, 1))
-            self.register_buffer("scale", torch.Tensor(
-                [0.229, 0.224, 0.225]).view(1, 3, 1, 1))
-
-        def forward(self, x):
-            feats = []
-            x = (x - self.shift) / self.scale
-            for idx in range(len(self.breakpoints) - 1):
-                m = getattr(self, "group{}".format(idx))
-                x = m(x)
-                feats.append(x)
-            return feats
-
-
-class L2_(torch.nn.Module):
-    def __init__(self):
-        """
-        Args:
-            pre_relu(bool): if True, selects features **before** reLU activations
-        """
-        super(L2_, self).__init__()
-        # VGG using perceptually-learned weights (LPIPS metric)
-        augemntations = []
-        augemntations.append(transforms.RandomPerspective(
-            fill=0, p=1.0, distortion_scale=0.5))
-        augemntations.append(transforms.RandomResizedCrop(
-            224, scale=(0.8, 0.8), ratio=(1.0, 1.0)))
-        augemntations.append(
-            transforms.Normalize((0.48145466, 0.4578275, 0.40821073), (0.26862954, 0.26130258, 0.27577711)))
-        self.augment_trans = transforms.Compose(augemntations)
-        # LOG.warning("LPIPS is untested")
-
-    def forward(self, pred, target, mode="train"):
-        """Compare VGG features of two inputs."""
-
-        # Get VGG features
-
-        sketch_augs, img_augs = [pred], [target]
-        if mode == "train":
-            for n in range(4):
-                augmented_pair = self.augment_trans(torch.cat([pred, target]))
-                sketch_augs.append(augmented_pair[0].unsqueeze(0))
-                img_augs.append(augmented_pair[1].unsqueeze(0))
-
-        pred = torch.cat(sketch_augs, dim=0)
-        target = torch.cat(img_augs, dim=0)
-        diffs = [torch.square(p - t).mean() for (p, t) in zip(pred, target)]
-        return sum(diffs)
-
-
-class CLIPVisualEncoder(nn.Module):
-    def __init__(self, clip_model):
-        super().__init__()
-        self.clip_model = clip_model
-        self.featuremaps = None
-
-        for i in range(12):  # 12 resblocks in VIT visual transformer
-            self.clip_model.visual.transformer.resblocks[i].register_forward_hook(
-                self.make_hook(i))
-
-    def make_hook(self, name):
-        def hook(module, input, output):
-            if len(output.shape) == 3:
-                self.featuremaps[name] = output.permute(
-                    1, 0, 2)  # LND -> NLD bs, smth, 768
-            else:
-                self.featuremaps[name] = output
-
-        return hook
-
-    def forward(self, x):
-        self.featuremaps = collections.OrderedDict()
-        fc_features = self.clip_model.encode_image(x).float()
-        featuremaps = [self.featuremaps[k] for k in range(12)]
-
-        return fc_features, featuremaps
-
-
-def l2_layers(xs_conv_features, ys_conv_features, clip_model_name):
-    return [torch.square(x_conv - y_conv).mean() for x_conv, y_conv in
-            zip(xs_conv_features, ys_conv_features)]
-
-
-def l1_layers(xs_conv_features, ys_conv_features, clip_model_name):
-    return [torch.abs(x_conv - y_conv).mean() for x_conv, y_conv in
-            zip(xs_conv_features, ys_conv_features)]
-
-
-def cos_layers(xs_conv_features, ys_conv_features, clip_model_name):
-    if "RN" in clip_model_name:
-        return [torch.square(x_conv, y_conv, dim=1).mean() for x_conv, y_conv in
-                zip(xs_conv_features, ys_conv_features)]
-    return [(1 - torch.cosine_similarity(x_conv, y_conv, dim=1)).mean() for x_conv, y_conv in
-            zip(xs_conv_features, ys_conv_features)]
-
-
-class CLIPConvLoss(torch.nn.Module):
-    def __init__(self, args):
-        super(CLIPConvLoss, self).__init__()
-        self.clip_model_name = args.clip_model_name
-        assert self.clip_model_name in [
-            "RN50",
-            "RN101",
-            "RN50x4",
-            "RN50x16",
-            "ViT-B/32",
-            "ViT-B/16",
-        ]
-
-        self.clip_conv_loss_type = args.clip_conv_loss_type
-        self.clip_fc_loss_type = "Cos"  # args.clip_fc_loss_type
-        assert self.clip_conv_loss_type in [
-            "L2", "Cos", "L1",
-        ]
-        assert self.clip_fc_loss_type in [
-            "L2", "Cos", "L1",
-        ]
-
-        self.distance_metrics = \
-            {
-                "L2": l2_layers,
-                "L1": l1_layers,
-                "Cos": cos_layers
-            }
-
-        self.model, clip_preprocess = clip.load(
-            self.clip_model_name, args.device, jit=False)
-
-        if self.clip_model_name.startswith("ViT"):
-            self.visual_encoder = CLIPVisualEncoder(self.model)
-
-        else:
-            self.visual_model = self.model.visual
-            layers = list(self.model.visual.children())
-            init_layers = torch.nn.Sequential(*layers)[:8]
-            self.layer1 = layers[8]
-            self.layer2 = layers[9]
-            self.layer3 = layers[10]
-            self.layer4 = layers[11]
-            self.att_pool2d = layers[12]
-
-        self.args = args
-
-        self.img_size = clip_preprocess.transforms[1].size
-        self.model.eval()
-        self.target_transform = transforms.Compose([
-            transforms.ToTensor(),
-        ])  # clip normalisation
-        self.normalize_transform = transforms.Compose([
-            clip_preprocess.transforms[0],  # Resize
-            clip_preprocess.transforms[1],  # CenterCrop
-            clip_preprocess.transforms[-1],  # Normalize
-        ])
-
-        self.model.eval()
-        self.device = args.device
-        self.num_augs = self.args.num_aug_clip
-
-        augemntations = []
-        if "affine" in args.augemntations:
-            augemntations.append(transforms.RandomPerspective(
-                fill=0, p=1.0, distortion_scale=0.5))
-            augemntations.append(transforms.RandomResizedCrop(
-                224, scale=(0.8, 0.8), ratio=(1.0, 1.0)))
-        augemntations.append(
-            transforms.Normalize((0.48145466, 0.4578275, 0.40821073), (0.26862954, 0.26130258, 0.27577711)))
-        self.augment_trans = transforms.Compose(augemntations)
-
-        self.clip_fc_layer_dims = None  # self.args.clip_fc_layer_dims
-        self.clip_conv_layer_dims = None  # self.args.clip_conv_layer_dims
-        self.clip_fc_loss_weight = args.clip_fc_loss_weight
-        self.counter = 0
-
-    def forward(self, sketch, target, mode="train"):
-        """
-        Parameters
-        ----------
-        sketch: Torch Tensor [1, C, H, W]
-        target: Torch Tensor [1, C, H, W]
-        """
-        #         y = self.target_transform(target).to(self.args.device)
-        conv_loss_dict = {}
-        x = sketch.to(self.device)
-        y = target.to(self.device)
-        sketch_augs, img_augs = [self.normalize_transform(x)], [
-            self.normalize_transform(y)]
-        if mode == "train":
-            for n in range(self.num_augs):
-                augmented_pair = self.augment_trans(torch.cat([x, y]))
-                sketch_augs.append(augmented_pair[0].unsqueeze(0))
-                img_augs.append(augmented_pair[1].unsqueeze(0))
-
-        xs = torch.cat(sketch_augs, dim=0).to(self.device)
-        ys = torch.cat(img_augs, dim=0).to(self.device)
-
-        if self.clip_model_name.startswith("RN"):
-            xs_fc_features, xs_conv_features = self.forward_inspection_clip_resnet(
-                xs.contiguous())
-            ys_fc_features, ys_conv_features = self.forward_inspection_clip_resnet(
-                ys.detach())
-
-        else:
-            xs_fc_features, xs_conv_features = self.visual_encoder(xs)
-            ys_fc_features, ys_conv_features = self.visual_encoder(ys)
-
-        conv_loss = self.distance_metrics[self.clip_conv_loss_type](
-            xs_conv_features, ys_conv_features, self.clip_model_name)
-
-        for layer, w in enumerate(self.args.clip_conv_layer_weights):
-            if w:
-                conv_loss_dict[f"clip_conv_loss_layer{layer}"] = conv_loss[layer] * w
-
-        if self.clip_fc_loss_weight:
-            # fc distance is always cos
-            fc_loss = (1 - torch.cosine_similarity(xs_fc_features,
-                       ys_fc_features, dim=1)).mean()
-            conv_loss_dict["fc"] = fc_loss * self.clip_fc_loss_weight
-
-        self.counter += 1
-        return conv_loss_dict
-
-    def forward_inspection_clip_resnet(self, x):
-        def stem(m, x):
-            for conv, bn in [(m.conv1, m.bn1), (m.conv2, m.bn2), (m.conv3, m.bn3)]:
-                x = m.relu(bn(conv(x)))
-            x = m.avgpool(x)
-            return x
-        x = x.type(self.visual_model.conv1.weight.dtype)
-        x = stem(self.visual_model, x)
-        x1 = self.layer1(x)
-        x2 = self.layer2(x1)
-        x3 = self.layer3(x2)
-        x4 = self.layer4(x3)
-        y = self.att_pool2d(x4)
-        return y, [x, x1, x2, x3, x4]
-        
\ No newline at end of file
diff --git a/spaces/yderre-aubay/midi-player-demo/src/main/components/Theme/EmotionThemeProvider.tsx b/spaces/yderre-aubay/midi-player-demo/src/main/components/Theme/EmotionThemeProvider.tsx
deleted file mode 100644
index 1117f352f4977c2648647e31748d2d8888726f95..0000000000000000000000000000000000000000
--- a/spaces/yderre-aubay/midi-player-demo/src/main/components/Theme/EmotionThemeProvider.tsx
+++ /dev/null
@@ -1,10 +0,0 @@
-import { ThemeProvider } from "@emotion/react"
-import { FC } from "react"
-import { useTheme } from "../../hooks/useTheme"
-
-export const EmotionThemeProvider: FC<React.PropsWithChildren<unknown>> = ({
-  children,
-}) => {
-  const theme = useTheme()
-  return <ThemeProvider theme={theme}>{children}</ThemeProvider>
-}
diff --git a/spaces/yizhangliu/Grounded-Segment-Anything/transformers_4_35_0/models/gpt_neox_japanese/configuration_gpt_neox_japanese.py b/spaces/yizhangliu/Grounded-Segment-Anything/transformers_4_35_0/models/gpt_neox_japanese/configuration_gpt_neox_japanese.py
deleted file mode 100644
index 8d8519b9eae8bfa45fc1cc6da63a47cf65bdbeac..0000000000000000000000000000000000000000
--- a/spaces/yizhangliu/Grounded-Segment-Anything/transformers_4_35_0/models/gpt_neox_japanese/configuration_gpt_neox_japanese.py
+++ /dev/null
@@ -1,120 +0,0 @@
-# coding=utf-8
-# Copyright 2022 ABEJA, Inc. and The HuggingFace Inc. team. All rights reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-""" GPTNeoX Japanese model configuration"""
-
-from ...configuration_utils import PretrainedConfig
-from ...utils import logging
-
-
-logger = logging.get_logger(__name__)
-
-GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP = {
-    "abeja/gpt-neox-japanese-2.7b": "https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json",
-}
-
-
-class GPTNeoXJapaneseConfig(PretrainedConfig):
-    r"""
-    This is the configuration class to store the configuration of a [`GPTNeoXModelJapanese`]. It is used to instantiate
-    a GPTNeoX model according to the specified arguments, defining the model architecture. Instantiating a
-    configuration with the defaults will yield a similar configuration to that of the GPTNeoXJapanese
-    [abeja/gpt-neox-japanese-2.7b](https://huggingface.co/abeja/gpt-neox-japanese-2.7b) architecture.
-
-    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
-    documentation from [`PretrainedConfig`] for more information. Default configs is set as 2.7B model
-
-    Args:
-        vocab_size (`int`, *optional*, defaults to 32000):
-            Vocabulary size of the GPTNeoXJapanese model. Defines the number of different tokens that can be
-            represented by the `inputs_ids` passed when calling [`GPTNeoXJapanese`].
-        hidden_size (`int`, *optional*, defaults to 2560):
-            Dimension of the encoder layers and the pooler layer.
-        num_hidden_layers (`int`, *optional*, defaults to 32):
-            Number of hidden layers in the Transformer encoder.
-        num_attention_heads (`int`, *optional*, defaults to 32):
-            Number of attention heads for each attention layer in the Transformer encoder.
-        intermediate_multiple_size (`int`, *optional*, defaults to 4):
-            Dimension of the "intermediate" layer in the Transformer encoder is calculated by hidden_size *
-            intermediate_multiple_size.
-        hidden_act (`str` or `function`, *optional*, defaults to `"gelu"`):
-            The non-linear activation function (function or string) in the encoder and pooler.
-        rotary_pct (`float`, *optional*, defaults to 1.00):
-            percentage of hidden dimensions to allocate to rotary embeddings
-        rotary_emb_base (`int`, *optional*, defaults to 10000)
-            base for computing rotary embeddings frequency
-        max_position_embeddings (`int`, *optional*, defaults to 2048):
-            The maximum sequence length that this model might ever be used with.
-        initializer_range (`float`, *optional*, defaults to 0.02):
-            The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
-        layer_norm_eps (`float`, *optional*, defaults to 1e-5):
-            The epsilon used by the layer normalization layers.
-        use_cache (`bool`, *optional*, defaults to `True`):
-            Whether or not the model should return the last key/values attentions (not used by all models). Only
-            relevant if `config.is_decoder=True`.
-        attention_dropout (`float`, *optional*, defaults to 0.1):
-            The dropout ratio for the attention.
-        hidden_dropout (`float`, *optional*, defaults to 0.0):
-            The dropout ratio for the hidden layer.
-        Example:
-
-    ```python
-    >>> from transformers import GPTNeoXJapaneseConfig, GPTNeoXJapaneseModel
-
-    >>> # Initializing a GPTNeoXJapanese gpt-neox-japanese-2.7b style configuration
-    >>> configuration = GPTNeoXJapaneseConfig()
-
-    >>> # Initializing a model (with random weights) from the gpt-neox-japanese-2.7b style configuration
-    >>> model = GPTNeoXJapaneseModel(configuration)
-
-    >>> # Accessing the model configuration
-    >>> configuration = model.config
-    ```"""
-    model_type = "gpt_neox_japanese"
-
-    def __init__(
-        self,
-        vocab_size=32000,
-        hidden_size=2560,
-        num_hidden_layers=32,
-        num_attention_heads=32,
-        intermediate_multiple_size=4,
-        hidden_act="gelu",
-        rotary_pct=1.00,
-        rotary_emb_base=10000,
-        max_position_embeddings=2048,
-        initializer_range=0.02,
-        layer_norm_eps=1e-5,
-        use_cache=True,
-        bos_token_id=31996,
-        eos_token_id=31999,
-        attention_dropout=0.1,
-        hidden_dropout=0.0,
-        **kwargs,
-    ):
-        super().__init__(bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs)
-        self.vocab_size = vocab_size
-        self.max_position_embeddings = max_position_embeddings
-        self.hidden_size = hidden_size
-        self.num_hidden_layers = num_hidden_layers
-        self.num_attention_heads = num_attention_heads
-        self.intermediate_multiple_size = intermediate_multiple_size
-        self.hidden_act = hidden_act
-        self.rotary_pct = rotary_pct
-        self.rotary_emb_base = rotary_emb_base
-        self.initializer_range = initializer_range
-        self.layer_norm_eps = layer_norm_eps
-        self.use_cache = use_cache
-        self.attention_dropout = attention_dropout
-        self.hidden_dropout = hidden_dropout
diff --git a/spaces/yoinked/audio-diffusion/README.md b/spaces/yoinked/audio-diffusion/README.md
deleted file mode 100644
index 9763d53cadc8547a633a978be2d4f9219e2479be..0000000000000000000000000000000000000000
--- a/spaces/yoinked/audio-diffusion/README.md
+++ /dev/null
@@ -1,234 +0,0 @@
----
-title: Audio Diffusion
-emoji: 🎵
-colorFrom: pink
-colorTo: blue
-sdk: gradio
-sdk_version: 3.1.4
-app_file: app.py
-pinned: false
-license: gpl-3.0
----
-# audio-diffusion [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/teticio/audio-diffusion/blob/master/notebooks/gradio_app.ipynb)
-
-## Apply diffusion models to synthesize music instead of images using the new Hugging Face [diffusers](https://github.com/huggingface/diffusers) package
-
----
-#### Sample automatically generated loop
-
-https://user-images.githubusercontent.com/44233095/204103172-27f25d63-5e77-40ca-91ab-d04a45d4726f.mp4
-
-Go to https://soundcloud.com/teticio2/sets/audio-diffusion-loops for more examples.
-
----
-#### Updates
-
-**25/12/2022**. Now it is possible to train models conditional on an encoding (of text or audio, for example). See the section on Conditional Audio Generation below.
-
-**5/12/2022**. 🤗 Exciting news! `AudioDiffusionPipeline` has been migrated to the Hugging Face `diffusers` package so that it is even easier for others to use and contribute.
-
-**2/12/2022**. Added Mel to pipeline and updated the pretrained models to save Mel config (they are now no longer compatible with previous versions of this repo). It is relatively straightforward to migrate previously trained models to the new format (see https://huggingface.co/teticio/audio-diffusion-256).
-
-**7/11/2022**. Added pre-trained latent audio diffusion models [teticio/latent-audio-diffusion-256](https://huggingface.co/teticio/latent-audio-diffusion-256) and [teticio/latent-audio-diffusion-ddim-256](https://huggingface.co/teticio/latent-audio-diffusion-ddim-256). You can use the pre-trained VAE to train your own latent diffusion models on a different set of audio files.
-
-**22/10/2022**. Added DDIM encoder and ability to interpolate between audios in latent "noise" space. Mel spectrograms no longer have to be square (thanks to Tristan for this one), so you can set the vertical (frequency) and horizontal (time) resolutions independently.
-
-**15/10/2022**. Added latent audio diffusion (see below). Also added the possibility to train a DDIM ([De-noising Diffusion Implicit Models](https://arxiv.org/pdf/2010.02502.pdf)). These have the benefit that samples can be generated with much fewer steps (~50) than used in training.
-
-**4/10/2022**. It is now possible to mask parts of the input audio during generation which means you can stitch several samples together (think "out-painting").
-
-**27/9/2022**. You can now generate an audio based on a previous one. You can use this to generate variations of the same audio or even to "remix" a track (via a sort of "style transfer"). You can find examples of how to do this in the [`test_model.ipynb`](https://colab.research.google.com/github/teticio/audio-diffusion/blob/master/notebooks/test_model.ipynb) notebook.
-
----
-
-![mel spectrogram](https://user-images.githubusercontent.com/44233095/205305826-8b39c917-26c5-49b4-887c-776f5d69e970.png)
-
----
-
-## DDPM ([De-noising Diffusion Probabilistic Models](https://arxiv.org/abs/2006.11239))
-
-Audio can be represented as images by transforming to a [mel spectrogram](https://en.wikipedia.org/wiki/Mel-frequency_cepstrum), such as the one shown above. The class `Mel` in `mel.py` can convert a slice of audio into a mel spectrogram of `x_res` x `y_res` and vice versa. The higher the resolution, the less audio information will be lost. You can see how this works in the [`test_mel.ipynb`](https://github.com/teticio/audio-diffusion/blob/main/notebooks/test_mel.ipynb) notebook.
-
-A DDPM is trained on a set of mel spectrograms that have been generated from a directory of audio files. It is then used to synthesize similar mel spectrograms, which are then converted back into audio.
-
-You can play around with some pre-trained models on [Google Colab](https://colab.research.google.com/github/teticio/audio-diffusion/blob/master/notebooks/test_model.ipynb) or [Hugging Face spaces](https://huggingface.co/spaces/teticio/audio-diffusion). Check out some automatically generated loops [here](https://soundcloud.com/teticio2/sets/audio-diffusion-loops).
-
-| Model | Dataset | Description |
-|-------|---------|-------------|
-| [teticio/audio-diffusion-256](https://huggingface.co/teticio/audio-diffusion-256) | [teticio/audio-diffusion-256](https://huggingface.co/datasets/teticio/audio-diffusion-256) | My "liked" Spotify playlist |
-| [teticio/audio-diffusion-breaks-256](https://huggingface.co/teticio/audio-diffusion-breaks-256) | [teticio/audio-diffusion-breaks-256](https://huggingface.co/datasets/teticio/audio-diffusion-breaks-256) | Samples that have been used in music, sourced from [WhoSampled](https://whosampled.com) and [YouTube](https://youtube.com) |
-| [teticio/audio-diffusion-instrumental-hiphop-256](https://huggingface.co/teticio/audio-diffusion-instrumental-hiphop-256) | [teticio/audio-diffusion-instrumental-hiphop-256](https://huggingface.co/datasets/teticio/audio-diffusion-instrumental-hiphop-256) | Instrumental Hip Hop music |
-| [teticio/audio-diffusion-ddim-256](https://huggingface.co/teticio/audio-diffusion-ddim-256) | [teticio/audio-diffusion-256](https://huggingface.co/datasets/teticio/audio-diffusion-256) | De-noising Diffusion Implicit Model |
-| [teticio/latent-audio-diffusion-256](https://huggingface.co/teticio/latent-audio-diffusion-256) | [teticio/audio-diffusion-256](https://huggingface.co/datasets/teticio/audio-diffusion-256) | Latent Audio Diffusion model |
-| [teticio/latent-audio-diffusion-ddim-256](https://huggingface.co/teticio/latent-audio-diffusion-ddim-256) | [teticio/audio-diffusion-256](https://huggingface.co/datasets/teticio/audio-diffusion-256) | Latent Audio Diffusion Implicit Model |
-| [teticio/conditional-latent-audio-diffusion-512](https://huggingface.co/teticio/latent-audio-diffusion-512) | [teticio/audio-diffusion-512](https://huggingface.co/datasets/teticio/audio-diffusion-512) | Conditional Latent Audio Diffusion Model |
-
----
-
-## Generate Mel spectrogram dataset from directory of audio files
-
-#### Install from GitHub (includes training scripts)
-
-```bash
-git clone https://github.com/teticio/audio-diffusion.git
-cd audio-diffusion
-pip install .
-```
-
-#### Install from PyPI
-
-```bash
-pip install audiodiffusion
-```
-
-#### Training can be run with Mel spectrograms of resolution 64x64 on a single commercial grade GPU (e.g. RTX 2080 Ti). The `hop_length` should be set to 1024 for better results
-
-```bash
-python scripts/audio_to_images.py \
---resolution 64,64 \
---hop_length 1024 \
---input_dir path-to-audio-files \
---output_dir path-to-output-data
-```
-
-#### Generate dataset of 256x256 Mel spectrograms and push to hub (you will need to be authenticated with `huggingface-cli login`)
-
-```bash
-python scripts/audio_to_images.py \
---resolution 256 \
---input_dir path-to-audio-files \
---output_dir data/audio-diffusion-256 \
---push_to_hub teticio/audio-diffusion-256
-```
-
-Note that the default `sample_rate` is 22050 and audios will be resampled if they are at a different rate. If you change this value, you may find that the results in the `test_mel.ipynb` notebook are not good (for example, if `sample_rate` is 48000) and that it is necessary to adjust `n_fft` (for example, to 2000 instead of the default value of 2048; alternatively, you can resample to a `sample_rate` of 44100). Make sure you use the same parameters for training and inference. You should also bear in mind that not all resolutions work with the neural network architecture as currently configured - you should be safe if you stick to powers of 2.
-
-## Train model
-
-#### Run training on local machine
-
-```bash
-accelerate launch --config_file config/accelerate_local.yaml \
-scripts/train_unet.py \
---dataset_name data/audio-diffusion-64 \
---hop_length 1024 \
---output_dir models/ddpm-ema-audio-64 \
---train_batch_size 16 \
---num_epochs 100 \
---gradient_accumulation_steps 1 \
---learning_rate 1e-4 \
---lr_warmup_steps 500 \
---mixed_precision no
-```
-
-#### Run training on local machine with `batch_size` of 2 and `gradient_accumulation_steps` 8 to compensate, so that 256x256 resolution model fits on commercial grade GPU and push to hub
-
-```bash
-accelerate launch --config_file config/accelerate_local.yaml \
-scripts/train_unet.py \
---dataset_name teticio/audio-diffusion-256 \
---output_dir models/audio-diffusion-256 \
---num_epochs 100 \
---train_batch_size 2 \
---eval_batch_size 2 \
---gradient_accumulation_steps 8 \
---learning_rate 1e-4 \
---lr_warmup_steps 500 \
---mixed_precision no \
---push_to_hub True \
---hub_model_id audio-diffusion-256 \
---hub_token $(cat $HOME/.huggingface/token)
-```
-
-#### Run training on SageMaker
-
-```bash
-accelerate launch --config_file config/accelerate_sagemaker.yaml \
-scripts/train_unet.py \
---dataset_name teticio/audio-diffusion-256 \
---output_dir models/ddpm-ema-audio-256 \
---train_batch_size 16 \
---num_epochs 100 \
---gradient_accumulation_steps 1 \
---learning_rate 1e-4 \
---lr_warmup_steps 500 \
---mixed_precision no
-```
-
-## DDIM ([De-noising Diffusion Implicit Models](https://arxiv.org/pdf/2010.02502.pdf))
-
-#### A DDIM can be trained by adding the parameter
-
-```bash
---scheduler ddim
-```
-
-Inference can the be run with far fewer steps than the number used for training (e.g., ~50), allowing for much faster generation. Without retraining, the parameter `eta` can be used to replicate a DDPM if it is set to 1 or a DDIM if it is set to 0, with all values in between being valid. When `eta` is 0 (the default value), the de-noising procedure is deterministic, which means that it can be run in reverse as a kind of encoder that recovers the original noise used in generation. A function `encode` has been added to `AudioDiffusionPipeline` for this purpose. It is then possible to interpolate between audios in the latent "noise" space using the function `slerp` (Spherical Linear intERPolation).
-
-## Latent Audio Diffusion
-
-Rather than de-noising images directly, it is interesting to work in the "latent space" after first encoding images using an autoencoder. This has a number of advantages. Firstly, the information in the images is compressed into a latent space of a much lower dimension, so it is much faster to train de-noising diffusion models and run inference with them. Secondly, similar images tend to be clustered together and interpolating between two images in latent space can produce meaningful combinations.
-
-At the time of writing, the Hugging Face `diffusers` library is geared towards inference and lacking in training functionality (rather like its cousin `transformers` in the early days of development). In order to train a VAE (Variational AutoEncoder), I use the [stable-diffusion](https://github.com/CompVis/stable-diffusion) repo from CompVis and convert the checkpoints to `diffusers` format. Note that it uses a perceptual loss function for images; it would be nice to try a perceptual *audio* loss function.
-
-#### Train latent diffusion model using pre-trained VAE
-
-```bash
-accelerate launch ...
-...
---vae teticio/latent-audio-diffusion-256
-```
-
-#### Install dependencies to train with Stable Diffusion
-
-```bash
-pip install omegaconf pytorch_lightning==1.7.7 torchvision einops
-pip install -e git+https://github.com/CompVis/stable-diffusion.git@main#egg=latent-diffusion
-pip install -e git+https://github.com/CompVis/taming-transformers.git@master#egg=taming-transformers
-```
-
-#### Train an autoencoder
-
-```bash
-python scripts/train_vae.py \
---dataset_name teticio/audio-diffusion-256 \
---batch_size 2 \
---gradient_accumulation_steps 12
-```
-
-#### Train latent diffusion model
-
-```bash
-accelerate launch ...
-...
---vae models/autoencoder-kl
-```
-
-## Conditional Audio Generation
-
-We can generate audio conditional on a text prompt - or indeed anything which can be encoded into a bunch of numbers - much like DALL-E2, Midjourney and Stable Diffusion. It is generally harder to find good quality datasets of audios together with descriptions, although the people behind the dataset used to train Stable Diffusion are making some very interesting progress [here](https://github.com/LAION-AI/audio-dataset). I have chosen to encode the audio directly instead based on "how it sounds", using a [model which I trained on hundreds of thousands of Spotify playlists](https://github.com/teticio/Deej-AI). To encode an audio into a 100 dimensional vector
-
-```python
-from audiodiffusion.audio_encoder import AudioEncoder
-
-audio_encoder = AudioEncoder.from_pretrained("teticio/audio-encoder")
-audio_encoder.encode(['/home/teticio/Music/liked/Agua Re - Holy Dance - Large Sound Mix.mp3'])
-```
-
-Once you have prepared a dataset, you can encode the audio files with this script
-
-```bash
-python scripts/encode_audio \
---dataset_name teticio/audio-diffusion-256 \
---out_file data/encodings.p
-```
-
-Then you can train a model with
-
-```bash
-accelerate launch ...
-...
---encodings data/encodings.p
-```
-
-When generating audios, you will need to pass an `encodings` Tensor. See the [`conditional_generation.ipynb`](https://colab.research.google.com/github/teticio/audio-diffusion/blob/master/notebooks/conditional_generation.ipynb) notebook for an example that uses encodings of Spotify track previews to influence the generation.
diff --git a/spaces/ysharma/LLaVA_v1/llava/model/language_model/mpt/modeling_mpt.py b/spaces/ysharma/LLaVA_v1/llava/model/language_model/mpt/modeling_mpt.py
deleted file mode 100644
index 13313441b13fc7a66cb65fd21b482a5de982e2c8..0000000000000000000000000000000000000000
--- a/spaces/ysharma/LLaVA_v1/llava/model/language_model/mpt/modeling_mpt.py
+++ /dev/null
@@ -1,331 +0,0 @@
-"""A simple, flexible implementation of a GPT model.
-
-Inspired by https://github.com/karpathy/minGPT/blob/master/mingpt/model.py
-"""
-import math
-import warnings
-from typing import List, Optional, Tuple, Union
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-from transformers import PreTrainedModel, PreTrainedTokenizer, PreTrainedTokenizerFast
-from transformers.modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast
-from .attention import attn_bias_shape, build_attn_bias
-from .blocks import MPTBlock
-from .custom_embedding import SharedEmbedding
-from .norm import NORM_CLASS_REGISTRY
-from .configuration_mpt import MPTConfig
-from .adapt_tokenizer import AutoTokenizerForMOD, adapt_tokenizer_for_denoising
-from .hf_prefixlm_converter import add_bidirectional_mask_if_missing, convert_hf_causal_lm_to_prefix_lm
-from .meta_init_context import init_empty_weights
-from .param_init_fns import MODEL_INIT_REGISTRY, generic_param_init_fn_
-try:
-    from .flash_attn_triton import flash_attn_func
-except:
-    pass
-Tokenizer = Union[PreTrainedTokenizer, PreTrainedTokenizerFast]
-
-class MPTPreTrainedModel(PreTrainedModel):
-    config_class = MPTConfig
-    base_model_prefix = 'model'
-    _no_split_modules = ['MPTBlock']
-
-class MPTModel(MPTPreTrainedModel):
-
-    def __init__(self, config: MPTConfig):
-        config._validate_config()
-        super().__init__(config)
-        self.attn_impl = config.attn_config['attn_impl']
-        self.prefix_lm = config.attn_config['prefix_lm']
-        self.attn_uses_sequence_id = config.attn_config['attn_uses_sequence_id']
-        self.alibi = config.attn_config['alibi']
-        self.alibi_bias_max = config.attn_config['alibi_bias_max']
-        if config.init_device == 'mixed':
-            if dist.get_local_rank() == 0:
-                config.init_device = 'cpu'
-            else:
-                config.init_device = 'meta'
-        if config.norm_type.lower() not in NORM_CLASS_REGISTRY.keys():
-            norm_options = ' | '.join(NORM_CLASS_REGISTRY.keys())
-            raise NotImplementedError(f'Requested norm type ({config.norm_type}) is not implemented within this repo (Options: {norm_options}).')
-        norm_class = NORM_CLASS_REGISTRY[config.norm_type.lower()]
-        self.embedding_fraction = config.embedding_fraction
-        self.wte = SharedEmbedding(config.vocab_size, config.d_model, device=config.init_device)
-        if not self.alibi:
-            self.wpe = torch.nn.Embedding(config.max_seq_len, config.d_model, device=config.init_device)
-        self.emb_drop = nn.Dropout(config.emb_pdrop)
-        self.blocks = nn.ModuleList([MPTBlock(device=config.init_device, **config.to_dict()) for _ in range(config.n_layers)])
-        self.norm_f = norm_class(config.d_model, device=config.init_device)
-        if config.init_device != 'meta':
-            print(f'You are using config.init_device={config.init_device!r}, but you can also use config.init_device="meta" with Composer + FSDP for fast initialization.')
-            self.apply(self.param_init_fn)
-        self.is_causal = not self.prefix_lm
-        self._attn_bias_initialized = False
-        self.attn_bias = None
-        self.attn_bias_shape = attn_bias_shape(self.attn_impl, config.n_heads, config.max_seq_len, self.alibi, prefix_lm=self.prefix_lm, causal=self.is_causal, use_sequence_id=self.attn_uses_sequence_id)
-        if config.no_bias:
-            for module in self.modules():
-                if hasattr(module, 'bias') and isinstance(module.bias, nn.Parameter):
-                    if config.verbose:
-                        warnings.warn(f'Removing bias ({module.bias}) from {module}.')
-                    module.register_parameter('bias', None)
-        if config.verbose and config.verbose > 2:
-            print(self)
-        if 'verbose' not in self.config.init_config:
-            self.config.init_config['verbose'] = self.config.verbose
-        if self.config.init_config['verbose'] > 1:
-            init_fn_name = self.config.init_config['name']
-            warnings.warn(f'Using {init_fn_name} initialization.')
-        self.gradient_checkpointing = False
-
-    def get_input_embeddings(self):
-        return self.wte
-
-    def set_input_embeddings(self, value):
-        self.wte = value
-
-    @torch.no_grad()
-    def _attn_bias(self, device, dtype, attention_mask: Optional[torch.ByteTensor]=None, prefix_mask: Optional[torch.ByteTensor]=None, sequence_id: Optional[torch.LongTensor]=None):
-        if not self._attn_bias_initialized:
-            if self.attn_bias_shape:
-                self.attn_bias = torch.zeros(self.attn_bias_shape, device=device, dtype=dtype)
-                self.attn_bias = build_attn_bias(self.attn_impl, self.attn_bias, self.config.n_heads, self.config.max_seq_len, causal=self.is_causal, alibi=self.alibi, alibi_bias_max=self.alibi_bias_max)
-            self._attn_bias_initialized = True
-        if self.attn_impl == 'flash':
-            return (self.attn_bias, attention_mask)
-        if self.attn_bias is not None:
-            self.attn_bias = self.attn_bias.to(dtype=dtype, device=device)
-        attn_bias = self.attn_bias
-        if self.prefix_lm:
-            assert isinstance(attn_bias, torch.Tensor)
-            assert isinstance(prefix_mask, torch.Tensor)
-            attn_bias = self._apply_prefix_mask(attn_bias, prefix_mask)
-        if self.attn_uses_sequence_id and sequence_id is not None:
-            assert isinstance(attn_bias, torch.Tensor)
-            attn_bias = self._apply_sequence_id(attn_bias, sequence_id)
-        if attention_mask is not None:
-            s_k = attention_mask.shape[-1]
-            if attn_bias is None:
-                attn_bias = torch.zeros((1, 1, 1, s_k), device=device, dtype=dtype)
-            else:
-                _s_k = max(0, attn_bias.size(-1) - s_k)
-                attn_bias = attn_bias[:, :, :, _s_k:]
-            if prefix_mask is not None and attention_mask.shape != prefix_mask.shape:
-                raise ValueError(f'attention_mask shape={attention_mask.shape} ' + f'and prefix_mask shape={prefix_mask.shape} are not equal.')
-            min_val = torch.finfo(attn_bias.dtype).min
-            attn_bias = attn_bias.masked_fill(~attention_mask.view(-1, 1, 1, s_k), min_val)
-        return (attn_bias, None)
-
-    def _apply_prefix_mask(self, attn_bias: torch.Tensor, prefix_mask: torch.Tensor):
-        (s_k, s_q) = attn_bias.shape[-2:]
-        if s_k != self.config.max_seq_len or s_q != self.config.max_seq_len:
-            raise ValueError('attn_bias does not match the expected shape. ' + f'The last two dimensions should both be {self.config.max_length} ' + f'but are {s_k} and {s_q}.')
-        seq_len = prefix_mask.shape[-1]
-        if seq_len > self.config.max_seq_len:
-            raise ValueError(f'prefix_mask sequence length cannot exceed max_seq_len={self.config.max_seq_len}')
-        attn_bias = attn_bias[..., :seq_len, :seq_len]
-        causal = torch.tril(torch.ones((seq_len, seq_len), dtype=torch.bool, device=prefix_mask.device)).view(1, 1, seq_len, seq_len)
-        prefix = prefix_mask.view(-1, 1, 1, seq_len)
-        cannot_attend = ~torch.logical_or(causal, prefix.bool())
-        min_val = torch.finfo(attn_bias.dtype).min
-        attn_bias = attn_bias.masked_fill(cannot_attend, min_val)
-        return attn_bias
-
-    def _apply_sequence_id(self, attn_bias: torch.Tensor, sequence_id: torch.LongTensor):
-        seq_len = sequence_id.shape[-1]
-        if seq_len > self.config.max_seq_len:
-            raise ValueError(f'sequence_id sequence length cannot exceed max_seq_len={self.config.max_seq_len}')
-        attn_bias = attn_bias[..., :seq_len, :seq_len]
-        cannot_attend = torch.logical_not(torch.eq(sequence_id.view(-1, seq_len, 1), sequence_id.view(-1, 1, seq_len))).unsqueeze(1)
-        min_val = torch.finfo(attn_bias.dtype).min
-        attn_bias = attn_bias.masked_fill(cannot_attend, min_val)
-        return attn_bias
-
-    def forward(self, input_ids: torch.LongTensor, past_key_values: Optional[List[Tuple[torch.FloatTensor]]]=None, attention_mask: Optional[torch.ByteTensor]=None, prefix_mask: Optional[torch.ByteTensor]=None, sequence_id: Optional[torch.LongTensor]=None, return_dict: Optional[bool]=None, output_attentions: Optional[bool]=None, output_hidden_states: Optional[bool]=None, use_cache: Optional[bool]=None, inputs_embeds: Optional[torch.Tensor]=None):
-        return_dict = return_dict if return_dict is not None else self.config.return_dict
-        use_cache = use_cache if use_cache is not None else self.config.use_cache
-        if attention_mask is not None:
-            attention_mask = attention_mask.bool()
-        if prefix_mask is not None:
-            prefix_mask = prefix_mask.bool()
-        if not return_dict:
-            raise NotImplementedError('return_dict False is not implemented yet for MPT')
-        if output_attentions:
-            if self.attn_impl != 'torch':
-                raise NotImplementedError('output_attentions is not implemented for MPT when using attn_impl `flash` or `triton`.')
-        if attention_mask is not None and attention_mask[:, 0].sum() != attention_mask.shape[0] and self.training:
-            raise NotImplementedError('MPT does not support training with left padding.')
-        if self.prefix_lm and prefix_mask is None:
-            raise ValueError('prefix_mask is a required argument when MPT is configured with prefix_lm=True.')
-        if self.training:
-            if self.attn_uses_sequence_id and sequence_id is None:
-                raise ValueError('sequence_id is a required argument when MPT is configured with attn_uses_sequence_id=True ' + 'and the model is in train mode.')
-            elif self.attn_uses_sequence_id is False and sequence_id is not None:
-                warnings.warn('MPT received non-None input for `sequence_id` but is configured with attn_uses_sequence_id=False. ' + 'This input will be ignored. If you want the model to use `sequence_id`, set attn_uses_sequence_id to True.')
-        if input_ids is not None:
-            S = input_ids.size(1)
-            assert S <= self.config.max_seq_len, f'Cannot forward input with seq_len={S}, this model only supports seq_len<={self.config.max_seq_len}'
-            tok_emb = self.wte(input_ids)
-        else:
-            assert inputs_embeds is not None
-            assert self.alibi, 'inputs_embeds is not implemented for MPT unless for alibi.'
-            S = inputs_embeds.size(1)
-            tok_emb = inputs_embeds
-        if self.alibi:
-            x = tok_emb
-        else:
-            past_position = 0
-            if past_key_values is not None:
-                if len(past_key_values) != self.config.n_layers:
-                    raise ValueError(f'past_key_values must provide a past_key_value for each attention ' + f'layer in the network (len(past_key_values)={len(past_key_values)!r}; self.config.n_layers={self.config.n_layers!r}).')
-                past_position = past_key_values[0][0].size(1)
-                if self.attn_impl == 'torch':
-                    past_position = past_key_values[0][0].size(3)
-            if S + past_position > self.config.max_seq_len:
-                raise ValueError(f'Cannot forward input with past sequence length {past_position} and current sequence length {S + 1}, this model only supports total sequence length <= {self.config.max_seq_len}.')
-            pos = torch.arange(past_position, S + past_position, dtype=torch.long, device=input_ids.device).unsqueeze(0)
-            if attention_mask is not None:
-                pos = torch.clamp(pos - torch.cumsum((~attention_mask).to(torch.int32), dim=1)[:, past_position:], min=0)
-            pos_emb = self.wpe(pos)
-            x = tok_emb + pos_emb
-        if self.embedding_fraction == 1:
-            x = self.emb_drop(x)
-        else:
-            x_shrunk = x * self.embedding_fraction + x.detach() * (1 - self.embedding_fraction)
-            assert isinstance(self.emb_drop, nn.Module)
-            x = self.emb_drop(x_shrunk)
-        (attn_bias, attention_mask) = self._attn_bias(device=x.device, dtype=torch.float32, attention_mask=attention_mask, prefix_mask=prefix_mask, sequence_id=sequence_id)
-        if use_cache and past_key_values is None:
-            past_key_values = [() for _ in range(self.config.n_layers)]
-        all_hidden_states = () if output_hidden_states else None
-        all_self_attns = () if output_attentions else None
-        for (b_idx, block) in enumerate(self.blocks):
-            if output_hidden_states:
-                assert all_hidden_states is not None
-                all_hidden_states = all_hidden_states + (x,)
-            past_key_value = past_key_values[b_idx] if past_key_values is not None else None
-            if self.gradient_checkpointing and self.training:
-                (x, attn_weights, past_key_value) = torch.utils.checkpoint.checkpoint(block, x, past_key_value, attn_bias, attention_mask, self.is_causal)
-            else:
-                (x, attn_weights, past_key_value) = block(x, past_key_value=past_key_value, attn_bias=attn_bias, attention_mask=attention_mask, is_causal=self.is_causal)
-            if past_key_values is not None:
-                past_key_values[b_idx] = past_key_value
-            if output_attentions:
-                assert all_self_attns is not None
-                all_self_attns = all_self_attns + (attn_weights,)
-        x = self.norm_f(x)
-        if output_hidden_states:
-            assert all_hidden_states is not None
-            all_hidden_states = all_hidden_states + (x,)
-        return BaseModelOutputWithPast(last_hidden_state=x, past_key_values=past_key_values, hidden_states=all_hidden_states, attentions=all_self_attns)
-
-    def param_init_fn(self, module):
-        init_fn_name = self.config.init_config['name']
-        MODEL_INIT_REGISTRY[init_fn_name](module=module, n_layers=self.config.n_layers, d_model=self.config.d_model, **self.config.init_config)
-
-    def fsdp_wrap_fn(self, module):
-        return isinstance(module, MPTBlock)
-
-    def activation_checkpointing_fn(self, module):
-        return isinstance(module, MPTBlock)
-
-class MPTForCausalLM(MPTPreTrainedModel):
-
-    def __init__(self, config: MPTConfig):
-        super().__init__(config)
-        if not config.tie_word_embeddings:
-            raise ValueError('MPTForCausalLM only supports tied word embeddings')
-        print(f'Instantiating an MPTForCausalLM model from {__file__}')
-        self.transformer = MPTModel(config)
-        for child in self.transformer.children():
-            if isinstance(child, torch.nn.ModuleList):
-                continue
-            if isinstance(child, torch.nn.Module):
-                child._fsdp_wrap = True
-        self.logit_scale = None
-        if config.logit_scale is not None:
-            logit_scale = config.logit_scale
-            if isinstance(logit_scale, str):
-                if logit_scale == 'inv_sqrt_d_model':
-                    logit_scale = 1 / math.sqrt(config.d_model)
-                else:
-                    raise ValueError(f"logit_scale={logit_scale!r} is not recognized as an option; use numeric value or 'inv_sqrt_d_model'.")
-            self.logit_scale = logit_scale
-
-    def get_input_embeddings(self):
-        return self.transformer.wte
-
-    def set_input_embeddings(self, value):
-        self.transformer.wte = value
-
-    def get_output_embeddings(self):
-        return self.transformer.wte
-
-    def set_output_embeddings(self, new_embeddings):
-        self.transformer.wte = new_embeddings
-
-    def set_decoder(self, decoder):
-        self.transformer = decoder
-
-    def get_decoder(self):
-        return self.transformer
-
-    def forward(self, input_ids: torch.LongTensor, past_key_values: Optional[List[Tuple[torch.FloatTensor]]]=None, attention_mask: Optional[torch.ByteTensor]=None, prefix_mask: Optional[torch.ByteTensor]=None, sequence_id: Optional[torch.LongTensor]=None, labels: Optional[torch.LongTensor]=None, return_dict: Optional[bool]=None, output_attentions: Optional[bool]=None, output_hidden_states: Optional[bool]=None, use_cache: Optional[bool]=None, inputs_embeds: Optional[torch.FloatTensor]=None):
-        return_dict = return_dict if return_dict is not None else self.config.return_dict
-        use_cache = use_cache if use_cache is not None else self.config.use_cache
-        if inputs_embeds is not None:
-            raise NotImplementedError('inputs_embeds has to be None (for hf/peft support).')
-        outputs = self.transformer(input_ids=input_ids, past_key_values=past_key_values, attention_mask=attention_mask, prefix_mask=prefix_mask, sequence_id=sequence_id, return_dict=return_dict, output_attentions=output_attentions, output_hidden_states=output_hidden_states, use_cache=use_cache)
-        logits = self.transformer.wte(outputs.last_hidden_state.to(self.transformer.wte.weight.device), True)
-        if self.logit_scale is not None:
-            if self.logit_scale == 0:
-                warnings.warn(f'Multiplying logits by self.logit_scale={self.logit_scale!r}. This will produce uniform (uninformative) outputs.')
-            logits *= self.logit_scale
-        loss = None
-        if labels is not None:
-            labels = torch.roll(labels, shifts=-1)
-            labels[:, -1] = -100
-            loss = F.cross_entropy(logits.view(-1, logits.size(-1)), labels.to(logits.device).view(-1))
-        return CausalLMOutputWithPast(loss=loss, logits=logits, past_key_values=outputs.past_key_values, hidden_states=outputs.hidden_states, attentions=outputs.attentions)
-
-    def param_init_fn(self, module):
-        init_fn_name = self.config.init_config['name']
-        MODEL_INIT_REGISTRY[init_fn_name](module=module, n_layers=self.config.n_layers, d_model=self.config.d_model, **self.config.init_config)
-
-    def fsdp_wrap_fn(self, module):
-        return isinstance(module, MPTBlock)
-
-    def activation_checkpointing_fn(self, module):
-        return isinstance(module, MPTBlock)
-
-    def prepare_inputs_for_generation(self, input_ids, past_key_values=None, inputs_embeds=None, **kwargs):
-        if inputs_embeds is not None:
-            raise NotImplementedError('inputs_embeds is not implemented for MPT yet')
-        attention_mask = kwargs['attention_mask'].bool()
-        if attention_mask[:, -1].sum() != attention_mask.shape[0]:
-            raise NotImplementedError('MPT does not support generation with right padding.')
-        if self.transformer.attn_uses_sequence_id and self.training:
-            sequence_id = torch.zeros_like(input_ids[:1])
-        else:
-            sequence_id = None
-        if past_key_values is not None:
-            input_ids = input_ids[:, -1].unsqueeze(-1)
-        if self.transformer.prefix_lm:
-            prefix_mask = torch.ones_like(attention_mask)
-            if kwargs.get('use_cache') == False:
-                raise NotImplementedError('MPT with prefix_lm=True does not support use_cache=False.')
-        else:
-            prefix_mask = None
-        return {'input_ids': input_ids, 'attention_mask': attention_mask, 'prefix_mask': prefix_mask, 'sequence_id': sequence_id, 'past_key_values': past_key_values, 'use_cache': kwargs.get('use_cache', True)}
-
-    @staticmethod
-    def _reorder_cache(past_key_values, beam_idx):
-        """Used by HuggingFace generate when using beam search with kv-caching.
-
-        See https://github.com/huggingface/transformers/blob/3ec7a47664ebe40c40f4b722f6bb1cd30c3821ec/src/transformers/models/gpt2/modeling_gpt2.py#L1122-L1133
-        for an example in transformers.
-        """
-        reordered_past = []
-        for layer_past in past_key_values:
-            reordered_past += [tuple((past_state.index_select(0, beam_idx) for past_state in layer_past))]
-        return reordered_past
\ No newline at end of file
diff --git a/spaces/yuan2023/stable-diffusion-webui-controlnet-docker/run.py b/spaces/yuan2023/stable-diffusion-webui-controlnet-docker/run.py
deleted file mode 100644
index 30201feba8665743354f1690c1f2b3a3583adee6..0000000000000000000000000000000000000000
--- a/spaces/yuan2023/stable-diffusion-webui-controlnet-docker/run.py
+++ /dev/null
@@ -1,35 +0,0 @@
-import os
-import subprocess
-import sys
-
-
-def on_start():
-    print("---------------")
-    print("Running script './on_start.sh' to download models ...")
-    print("---------------")
-    result = subprocess.run("./on_start.sh", shell=True, env=os.environ)
-    if result.returncode != 0:
-        raise RuntimeError(f"Error executing ./on_start.sh [exit code: {result.returncode}]")
-
-
-def start():
-    on_start()
-
-    print("---------------")
-    print(f"Launching {'API server' if '--nowebui' in sys.argv else 'Web UI'} with arguments: {' '.join(sys.argv[1:])}")
-    print("---------------")
-    import webui  # type: ignore  # noqa
-    if '--nowebui' in sys.argv:
-        webui.api_only()
-    else:
-        webui.webui()
-
-
-if __name__ == "__main__":
-    import torch
-    if not torch.cuda.is_available():
-        sys.argv.extend(["--precision", "full", "--no-half", "--use-cpu", "SD", "BSRGAN", "ESRGAN", "SCUNet", "CodeFormer", "--all"])
-    else:
-        sys.argv.extend(["--force-enable-xformers", "--xformers"])
-
-    start()
diff --git a/spaces/yueranseo/mygpt/modules/presets.py b/spaces/yueranseo/mygpt/modules/presets.py
deleted file mode 100644
index 23a1ec3bd13fe761653a89920bd087f425e12fcb..0000000000000000000000000000000000000000
--- a/spaces/yueranseo/mygpt/modules/presets.py
+++ /dev/null
@@ -1,240 +0,0 @@
-# -*- coding:utf-8 -*-
-import os
-from pathlib import Path
-import gradio as gr
-from .webui_locale import I18nAuto
-
-i18n = I18nAuto()  # internationalization
-
-CHATGLM_MODEL = None
-CHATGLM_TOKENIZER = None
-LLAMA_MODEL = None
-LLAMA_INFERENCER = None
-
-# ChatGPT 设置
-INITIAL_SYSTEM_PROMPT = "You are a helpful assistant."
-API_HOST = "api.openai.com"
-COMPLETION_URL = "https://api.openai.com/v1/chat/completions"
-BALANCE_API_URL="https://api.openai.com/dashboard/billing/credit_grants"
-USAGE_API_URL="https://api.openai.com/dashboard/billing/usage"
-HISTORY_DIR = Path("history")
-HISTORY_DIR = "history"
-TEMPLATES_DIR = "templates"
-
-# 错误信息
-STANDARD_ERROR_MSG = i18n("☹️发生了错误：")  # 错误信息的标准前缀
-GENERAL_ERROR_MSG = i18n("获取对话时发生错误，请查看后台日志")
-ERROR_RETRIEVE_MSG = i18n("请检查网络连接，或者API-Key是否有效。")
-CONNECTION_TIMEOUT_MSG = i18n("连接超时，无法获取对话。")  # 连接超时
-READ_TIMEOUT_MSG = i18n("读取超时，无法获取对话。")  # 读取超时
-PROXY_ERROR_MSG = i18n("代理错误，无法获取对话。")  # 代理错误
-SSL_ERROR_PROMPT = i18n("SSL错误，无法获取对话。")  # SSL 错误
-NO_APIKEY_MSG = i18n("API key为空，请检查是否输入正确。")  # API key 长度不足 51 位
-NO_INPUT_MSG = i18n("请输入对话内容。")  # 未输入对话内容
-BILLING_NOT_APPLICABLE_MSG = i18n("账单信息不适用") # 本地运行的模型返回的账单信息
-
-TIMEOUT_STREAMING = 60  # 流式对话时的超时时间
-TIMEOUT_ALL = 200  # 非流式对话时的超时时间
-ENABLE_STREAMING_OPTION = True  # 是否启用选择选择是否实时显示回答的勾选框
-HIDE_MY_KEY = False  # 如果你想在UI中隐藏你的 API 密钥，将此值设置为 True
-CONCURRENT_COUNT = 100 # 允许同时使用的用户数量
-
-SIM_K = 5
-INDEX_QUERY_TEMPRATURE = 1.0
-
-CHUANHU_TITLE = i18n("川虎Chat 🚀")
-
-CHUANHU_DESCRIPTION = i18n("由Bilibili [土川虎虎虎](https://space.bilibili.com/29125536)、[明昭MZhao](https://space.bilibili.com/24807452) 和 [Keldos](https://github.com/Keldos-Li) 开发<br />访问川虎Chat的 [GitHub项目](https://github.com/GaiZhenbiao/ChuanhuChatGPT) 下载最新版脚本")
-
-
-ONLINE_MODELS = [
-    "gpt-3.5-turbo",
-    "gpt-3.5-turbo-16k",
-    "gpt-3.5-turbo-0301",
-    "gpt-3.5-turbo-0613",
-    "gpt-4",
-    "gpt-4-0314",
-    "gpt-4-0613",
-    "gpt-4-32k",
-    "gpt-4-32k-0314",
-    "gpt-4-32k-0613",
-    "川虎助理",
-    "川虎助理 Pro",
-    "xmchat",
-    "yuanai-1.0-base_10B",
-    "yuanai-1.0-translate",
-    "yuanai-1.0-dialog",
-    "yuanai-1.0-rhythm_poems",
-    "minimax-abab4-chat",
-    "minimax-abab5-chat",
-]
-
-LOCAL_MODELS = [
-    "chatglm-6b",
-    "chatglm-6b-int4",
-    "chatglm-6b-int4-qe",
-    "StableLM",
-    "MOSS",
-    "llama-7b-hf",
-    "llama-13b-hf",
-    "llama-30b-hf",
-    "llama-65b-hf",
-]
-
-if os.environ.get('HIDE_LOCAL_MODELS', 'false') == 'true':
-    MODELS = ONLINE_MODELS
-else:
-    MODELS = ONLINE_MODELS + LOCAL_MODELS
-
-DEFAULT_MODEL = 0
-
-os.makedirs("models", exist_ok=True)
-os.makedirs("lora", exist_ok=True)
-os.makedirs("history", exist_ok=True)
-for dir_name in os.listdir("models"):
-    if os.path.isdir(os.path.join("models", dir_name)):
-        if dir_name not in MODELS:
-            MODELS.append(dir_name)
-
-MODEL_TOKEN_LIMIT = {
-    "gpt-3.5-turbo": 4096,
-    "gpt-3.5-turbo-16k": 16384,
-    "gpt-3.5-turbo-0301": 4096,
-    "gpt-3.5-turbo-0613": 4096,
-    "gpt-4": 8192,
-    "gpt-4-0314": 8192,
-    "gpt-4-0613": 8192,
-    "gpt-4-32k": 32768,
-    "gpt-4-32k-0314": 32768,
-    "gpt-4-32k-0613": 32768
-}
-
-TOKEN_OFFSET = 1000 # 模型的token上限减去这个值，得到软上限。到达软上限之后，自动尝试减少token占用。
-DEFAULT_TOKEN_LIMIT = 3000 # 默认的token上限
-REDUCE_TOKEN_FACTOR = 0.5 # 与模型token上限想乘，得到目标token数。减少token占用时，将token占用减少到目标token数以下。
-
-REPLY_LANGUAGES = [
-    "简体中文",
-    "繁體中文",
-    "English",
-    "日本語",
-    "Español",
-    "Français",
-    "Deutsch",
-    "跟随问题语言（不稳定）"
-]
-
-
-WEBSEARCH_PTOMPT_TEMPLATE = """\
-Web search results:
-
-{web_results}
-Current date: {current_date}
-
-Instructions: Using the provided web search results, write a comprehensive reply to the given query. Make sure to cite results using [[number](URL)] notation after the reference. If the provided search results refer to multiple subjects with the same name, write separate answers for each subject.
-Query: {query}
-Reply in {reply_language}
-"""
-
-PROMPT_TEMPLATE = """\
-Context information is below.
----------------------
-{context_str}
----------------------
-Current date: {current_date}.
-Using the provided context information, write a comprehensive reply to the given query.
-Make sure to cite results using [number] notation after the reference.
-If the provided context information refer to multiple subjects with the same name, write separate answers for each subject.
-Use prior knowledge only if the given context didn't provide enough information.
-Answer the question: {query_str}
-Reply in {reply_language}
-"""
-
-REFINE_TEMPLATE = """\
-The original question is as follows: {query_str}
-We have provided an existing answer: {existing_answer}
-We have the opportunity to refine the existing answer
-(only if needed) with some more context below.
-------------
-{context_msg}
-------------
-Given the new context, refine the original answer to better
-Reply in {reply_language}
-If the context isn't useful, return the original answer.
-"""
-
-SUMMARIZE_PROMPT = """Write a concise summary of the following:
-
-{text}
-
-CONCISE SUMMARY IN 中文:"""
-
-ALREADY_CONVERTED_MARK = "<!-- ALREADY CONVERTED BY PARSER. -->"
-
-small_and_beautiful_theme = gr.themes.Soft(
-        primary_hue=gr.themes.Color(
-            c50="#EBFAF2",
-            c100="#CFF3E1",
-            c200="#A8EAC8",
-            c300="#77DEA9",
-            c400="#3FD086",
-            c500="#02C160",
-            c600="#06AE56",
-            c700="#05974E",
-            c800="#057F45",
-            c900="#04673D",
-            c950="#2E5541",
-            name="small_and_beautiful",
-        ),
-        secondary_hue=gr.themes.Color(
-            c50="#576b95",
-            c100="#576b95",
-            c200="#576b95",
-            c300="#576b95",
-            c400="#576b95",
-            c500="#576b95",
-            c600="#576b95",
-            c700="#576b95",
-            c800="#576b95",
-            c900="#576b95",
-            c950="#576b95",
-        ),
-        neutral_hue=gr.themes.Color(
-            name="gray",
-            c50="#f6f7f8",
-            # c100="#f3f4f6",
-            c100="#F2F2F2",
-            c200="#e5e7eb",
-            c300="#d1d5db",
-            c400="#B2B2B2",
-            c500="#808080",
-            c600="#636363",
-            c700="#515151",
-            c800="#393939",
-            # c900="#272727",
-            c900="#2B2B2B",
-            c950="#171717",
-        ),
-        radius_size=gr.themes.sizes.radius_sm,
-    ).set(
-        # button_primary_background_fill="*primary_500",
-        button_primary_background_fill_dark="*primary_600",
-        # button_primary_background_fill_hover="*primary_400",
-        # button_primary_border_color="*primary_500",
-        button_primary_border_color_dark="*primary_600",
-        button_primary_text_color="wihte",
-        button_primary_text_color_dark="white",
-        button_secondary_background_fill="*neutral_100",
-        button_secondary_background_fill_hover="*neutral_50",
-        button_secondary_background_fill_dark="*neutral_900",
-        button_secondary_text_color="*neutral_800",
-        button_secondary_text_color_dark="white",
-        # background_fill_primary="#F7F7F7",
-        # background_fill_primary_dark="#1F1F1F",
-        # block_title_text_color="*primary_500",
-        block_title_background_fill_dark="*primary_900",
-        block_label_background_fill_dark="*primary_900",
-        input_background_fill="#F6F6F6",
-        chatbot_code_background_color="*neutral_950",
-        chatbot_code_background_color_dark="*neutral_950",
-    )
diff --git a/spaces/yunfei0710/gpt-academic/crazy_functions/test_project/cpp/cppipc/queue.h b/spaces/yunfei0710/gpt-academic/crazy_functions/test_project/cpp/cppipc/queue.h
deleted file mode 100644
index a21f3446e06b5826af7b554c8a7d9c5d80848b62..0000000000000000000000000000000000000000
--- a/spaces/yunfei0710/gpt-academic/crazy_functions/test_project/cpp/cppipc/queue.h
+++ /dev/null
@@ -1,216 +0,0 @@
-#pragma once
-
-#include <type_traits>
-#include <new>
-#include <utility>  // [[since C++14]]: std::exchange
-#include <algorithm>
-#include <atomic>
-#include <tuple>
-#include <thread>
-#include <chrono>
-#include <string>
-#include <cassert>  // assert
-
-#include "libipc/def.h"
-#include "libipc/shm.h"
-#include "libipc/rw_lock.h"
-
-#include "libipc/utility/log.h"
-#include "libipc/platform/detail.h"
-#include "libipc/circ/elem_def.h"
-
-namespace ipc {
-namespace detail {
-
-class queue_conn {
-protected:
-    circ::cc_t connected_ = 0;
-    shm::handle elems_h_;
-
-    template <typename Elems>
-    Elems* open(char const * name) {
-        if (name == nullptr || name[0] == '\0') {
-            ipc::error("fail open waiter: name is empty!\n");
-            return nullptr;
-        }
-        if (!elems_h_.acquire(name, sizeof(Elems))) {
-            return nullptr;
-        }
-        auto elems = static_cast<Elems*>(elems_h_.get());
-        if (elems == nullptr) {
-            ipc::error("fail acquire elems: %s\n", name);
-            return nullptr;
-        }
-        elems->init();
-        return elems;
-    }
-
-    void close() {
-        elems_h_.release();
-    }
-
-public:
-    queue_conn() = default;
-    queue_conn(const queue_conn&) = delete;
-    queue_conn& operator=(const queue_conn&) = delete;
-
-    bool connected() const noexcept {
-        return connected_ != 0;
-    }
-
-    circ::cc_t connected_id() const noexcept {
-        return connected_;
-    }
-
-    template <typename Elems>
-    auto connect(Elems* elems) noexcept
-                         /*needs 'optional' here*/
-     -> std::tuple<bool, bool, decltype(std::declval<Elems>().cursor())> {
-        if (elems == nullptr) return {};
-        // if it's already connected, just return
-        if (connected()) return {connected(), false, 0};
-        connected_ = elems->connect_receiver();
-        return {connected(), true, elems->cursor()};
-    }
-
-    template <typename Elems>
-    bool disconnect(Elems* elems) noexcept {
-        if (elems == nullptr) return false;
-        // if it's already disconnected, just return false
-        if (!connected()) return false;
-        elems->disconnect_receiver(std::exchange(connected_, 0));
-        return true;
-    }
-};
-
-template <typename Elems>
-class queue_base : public queue_conn {
-    using base_t = queue_conn;
-
-public:
-    using elems_t  = Elems;
-    using policy_t = typename elems_t::policy_t;
-
-protected:
-    elems_t * elems_ = nullptr;
-    decltype(std::declval<elems_t>().cursor()) cursor_ = 0;
-    bool sender_flag_ = false;
-
-public:
-    using base_t::base_t;
-
-    queue_base() = default;
-
-    explicit queue_base(char const * name)
-        : queue_base{} {
-        elems_ = open<elems_t>(name);
-    }
-
-    explicit queue_base(elems_t * elems) noexcept
-        : queue_base{} {
-        assert(elems != nullptr);
-        elems_ = elems;
-    }
-
-    /* not virtual */ ~queue_base() {
-        base_t::close();
-    }
-
-    elems_t       * elems()       noexcept { return elems_; }
-    elems_t const * elems() const noexcept { return elems_; }
-
-    bool ready_sending() noexcept {
-        if (elems_ == nullptr) return false;
-        return sender_flag_ || (sender_flag_ = elems_->connect_sender());
-    }
-
-    void shut_sending() noexcept {
-        if (elems_ == nullptr) return;
-        if (!sender_flag_) return;
-        elems_->disconnect_sender();
-    }
-
-    bool connect() noexcept {
-        auto tp = base_t::connect(elems_);
-        if (std::get<0>(tp) && std::get<1>(tp)) {
-            cursor_ = std::get<2>(tp);
-            return true;
-        }
-        return std::get<0>(tp);
-    }
-
-    bool disconnect() noexcept {
-        return base_t::disconnect(elems_);
-    }
-
-    std::size_t conn_count() const noexcept {
-        return (elems_ == nullptr) ? static_cast<std::size_t>(invalid_value) : elems_->conn_count();
-    }
-
-    bool valid() const noexcept {
-        return elems_ != nullptr;
-    }
-
-    bool empty() const noexcept {
-        return !valid() || (cursor_ == elems_->cursor());
-    }
-
-    template <typename T, typename F, typename... P>
-    bool push(F&& prep, P&&... params) {
-        if (elems_ == nullptr) return false;
-        return elems_->push(this, [&](void* p) {
-            if (prep(p)) ::new (p) T(std::forward<P>(params)...);
-        });
-    }
-
-    template <typename T, typename F, typename... P>
-    bool force_push(F&& prep, P&&... params) {
-        if (elems_ == nullptr) return false;
-        return elems_->force_push(this, [&](void* p) {
-            if (prep(p)) ::new (p) T(std::forward<P>(params)...);
-        });
-    }
-
-    template <typename T, typename F>
-    bool pop(T& item, F&& out) {
-        if (elems_ == nullptr) {
-            return false;
-        }
-        return elems_->pop(this, &(this->cursor_), [&item](void* p) {
-            ::new (&item) T(std::move(*static_cast<T*>(p)));
-        }, std::forward<F>(out));
-    }
-};
-
-} // namespace detail
-
-template <typename T, typename Policy>
-class queue final : public detail::queue_base<typename Policy::template elems_t<sizeof(T), alignof(T)>> {
-    using base_t = detail::queue_base<typename Policy::template elems_t<sizeof(T), alignof(T)>>;
-
-public:
-    using value_t = T;
-
-    using base_t::base_t;
-
-    template <typename... P>
-    bool push(P&&... params) {
-        return base_t::template push<T>(std::forward<P>(params)...);
-    }
-
-    template <typename... P>
-    bool force_push(P&&... params) {
-        return base_t::template force_push<T>(std::forward<P>(params)...);
-    }
-
-    bool pop(T& item) {
-        return base_t::pop(item, [](bool) {});
-    }
-
-    template <typename F>
-    bool pop(T& item, F&& out) {
-        return base_t::pop(item, std::forward<F>(out));
-    }
-};
-
-} // namespace ipc
diff --git a/spaces/zhang-wei-jian/docker/node_modules/accepts/README.md b/spaces/zhang-wei-jian/docker/node_modules/accepts/README.md
deleted file mode 100644
index 82680c530c3886540f630f643990e2ec707319d1..0000000000000000000000000000000000000000
--- a/spaces/zhang-wei-jian/docker/node_modules/accepts/README.md
+++ /dev/null
@@ -1,140 +0,0 @@
-# accepts
-
-[![NPM Version][npm-version-image]][npm-url]
-[![NPM Downloads][npm-downloads-image]][npm-url]
-[![Node.js Version][node-version-image]][node-version-url]
-[![Build Status][github-actions-ci-image]][github-actions-ci-url]
-[![Test Coverage][coveralls-image]][coveralls-url]
-
-Higher level content negotiation based on [negotiator](https://www.npmjs.com/package/negotiator).
-Extracted from [koa](https://www.npmjs.com/package/koa) for general use.
-
-In addition to negotiator, it allows:
-
-- Allows types as an array or arguments list, ie `(['text/html', 'application/json'])`
-  as well as `('text/html', 'application/json')`.
-- Allows type shorthands such as `json`.
-- Returns `false` when no types match
-- Treats non-existent headers as `*`
-
-## Installation
-
-This is a [Node.js](https://nodejs.org/en/) module available through the
-[npm registry](https://www.npmjs.com/). Installation is done using the
-[`npm install` command](https://docs.npmjs.com/getting-started/installing-npm-packages-locally):
-
-```sh
-$ npm install accepts
-```
-
-## API
-
-```js
-var accepts = require('accepts')
-```
-
-### accepts(req)
-
-Create a new `Accepts` object for the given `req`.
-
-#### .charset(charsets)
-
-Return the first accepted charset. If nothing in `charsets` is accepted,
-then `false` is returned.
-
-#### .charsets()
-
-Return the charsets that the request accepts, in the order of the client's
-preference (most preferred first).
-
-#### .encoding(encodings)
-
-Return the first accepted encoding. If nothing in `encodings` is accepted,
-then `false` is returned.
-
-#### .encodings()
-
-Return the encodings that the request accepts, in the order of the client's
-preference (most preferred first).
-
-#### .language(languages)
-
-Return the first accepted language. If nothing in `languages` is accepted,
-then `false` is returned.
-
-#### .languages()
-
-Return the languages that the request accepts, in the order of the client's
-preference (most preferred first).
-
-#### .type(types)
-
-Return the first accepted type (and it is returned as the same text as what
-appears in the `types` array). If nothing in `types` is accepted, then `false`
-is returned.
-
-The `types` array can contain full MIME types or file extensions. Any value
-that is not a full MIME types is passed to `require('mime-types').lookup`.
-
-#### .types()
-
-Return the types that the request accepts, in the order of the client's
-preference (most preferred first).
-
-## Examples
-
-### Simple type negotiation
-
-This simple example shows how to use `accepts` to return a different typed
-respond body based on what the client wants to accept. The server lists it's
-preferences in order and will get back the best match between the client and
-server.
-
-```js
-var accepts = require('accepts')
-var http = require('http')
-
-function app (req, res) {
-  var accept = accepts(req)
-
-  // the order of this list is significant; should be server preferred order
-  switch (accept.type(['json', 'html'])) {
-    case 'json':
-      res.setHeader('Content-Type', 'application/json')
-      res.write('{"hello":"world!"}')
-      break
-    case 'html':
-      res.setHeader('Content-Type', 'text/html')
-      res.write('<b>hello, world!</b>')
-      break
-    default:
-      // the fallback is text/plain, so no need to specify it above
-      res.setHeader('Content-Type', 'text/plain')
-      res.write('hello, world!')
-      break
-  }
-
-  res.end()
-}
-
-http.createServer(app).listen(3000)
-```
-
-You can test this out with the cURL program:
-```sh
-curl -I -H'Accept: text/html' http://localhost:3000/
-```
-
-## License
-
-[MIT](LICENSE)
-
-[coveralls-image]: https://badgen.net/coveralls/c/github/jshttp/accepts/master
-[coveralls-url]: https://coveralls.io/r/jshttp/accepts?branch=master
-[github-actions-ci-image]: https://badgen.net/github/checks/jshttp/accepts/master?label=ci
-[github-actions-ci-url]: https://github.com/jshttp/accepts/actions/workflows/ci.yml
-[node-version-image]: https://badgen.net/npm/node/accepts
-[node-version-url]: https://nodejs.org/en/download
-[npm-downloads-image]: https://badgen.net/npm/dm/accepts
-[npm-url]: https://npmjs.org/package/accepts
-[npm-version-image]: https://badgen.net/npm/v/accepts
diff --git a/spaces/zhaoys/wfms-kuiwenc/src/lib/bots/bing/utils.ts b/spaces/zhaoys/wfms-kuiwenc/src/lib/bots/bing/utils.ts
deleted file mode 100644
index 51c6cc29be95c87a6c244c17b518d47682e37893..0000000000000000000000000000000000000000
--- a/spaces/zhaoys/wfms-kuiwenc/src/lib/bots/bing/utils.ts
+++ /dev/null
@@ -1,88 +0,0 @@
-import { ChatResponseMessage } from './types'
-
-export function convertMessageToMarkdown(message: ChatResponseMessage): string {
-  for (const card of message.adaptiveCards??[]) {
-    for (const block of card.body) {
-      if (block.type === 'TextBlock') {
-        return block.text
-      }
-    }
-  }
-  return ''
-}
-
-const RecordSeparator = String.fromCharCode(30)
-
-export const websocketUtils = {
-  packMessage(data: any) {
-    return `${JSON.stringify(data)}${RecordSeparator}`
-  },
-  unpackMessage(data: string | ArrayBuffer | Blob) {
-    if (!data) return {}
-    return data
-      .toString()
-      .split(RecordSeparator)
-      .filter(Boolean)
-      .map((s) => {
-        try {
-          return JSON.parse(s)
-        } catch (e) {
-          return {}
-        }
-      })
-  },
-}
-
-export async function createImage(prompt: string, id: string, headers: HeadersInit): Promise<string | undefined> {
-  const { headers: responseHeaders } = await fetch(`https://www.bing.com/images/create?partner=sydney&showselective=1&sude=1&kseed=8500&SFX=4&q=${encodeURIComponent(prompt)}&iframeid=${id}`,
-    {
-      method: 'HEAD',
-      headers: {
-        ...headers,
-        Referer: 'https://www.bing.com/search?q=Bing+AI&showconv=1',
-        'Sec-Fetch-Dest': 'iframe',
-      },
-      redirect: 'manual'
-    },
-  );
-
-  if (!/&id=([^&]+)$/.test(responseHeaders.get('location') || '')) {
-    throw new Error(`CookieError`)
-  }
-
-  const resultId = RegExp.$1;
-  let count = 0
-  const imageThumbUrl = `https://www.bing.com/images/create/async/results/${resultId}?q=${encodeURIComponent(prompt)}&partner=sydney&showselective=1&IID=images.as`;
-
-  do {
-    await sleep(3000);
-    const content = await fetch(imageThumbUrl, { headers, method: 'GET' })
-
-    // @ts-ignore
-    if (content.headers.get('content-length') > 1) {
-      const text = await content.text()
-        return (text?.match(/<img class="mimg"((?!src).)+src="[^"]+/mg)??[])
-          .map(target => target?.split('src="').pop()?.replace(/&amp;/g, '&'))
-          .map(img => `![${prompt}](${img})`).join(' ')
-    }
-  } while(count ++ < 10);
-}
-
-
-export async function* streamAsyncIterable(stream: ReadableStream) {
-  const reader = stream.getReader()
-  try {
-    while (true) {
-      const { done, value } = await reader.read()
-      if (done) {
-        return
-      }
-      yield value
-    }
-  } finally {
-    reader.releaseLock()
-  }
-}
-
-export const sleep = (ms: number) => new Promise(resolve => setTimeout(resolve, ms))
-
diff --git a/spaces/zixian/Zhenhuan-VITS/README_ZH.md b/spaces/zixian/Zhenhuan-VITS/README_ZH.md
deleted file mode 100644
index 269546ccb91643bef62d872b39a90bf19a8393aa..0000000000000000000000000000000000000000
--- a/spaces/zixian/Zhenhuan-VITS/README_ZH.md
+++ /dev/null
@@ -1,60 +0,0 @@
-English Documentation Please Click [here](https://github.com/Plachtaa/VITS-fast-fine-tuning/blob/main/README.md)
-# VITS 快速微调
-这个代码库会指导你如何将自定义角色（甚至你自己），加入预训练的VITS模型中，在1小时内的微调使模型具备如下功能：  
-1. 在 模型所包含的任意两个角色 之间进行声线转换
-2. 以 你加入的角色声线 进行中日英三语 文本到语音合成。  
-
-本项目使用的底模涵盖常见二次元男/女配音声线（来自原神数据集）以及现实世界常见男/女声线（来自VCTK数据集），支持中日英三语，保证能够在微调时快速适应新的声线。
-
-欢迎体验微调所使用的底模！  
-
-中日英：[![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/Plachta/VITS-Umamusume-voice-synthesizer) 作者：我  
-
-中日：[![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/sayashi/vits-uma-genshin-honkai) 作者：[SayaSS](https://github.com/SayaSS) 
-
-### 目前支持的任务:
-- [x] 从 10条以上的短音频 克隆角色声音
-- [x] 从 3分钟以上的长音频（单个音频只能包含单说话人） 克隆角色声音
-- [x] 从 3分钟以上的视频（单个视频只能包含单说话人） 克隆角色声音
-- [x] 通过输入 bilibili视频链接（单个视频只能包含单说话人） 克隆角色声音
-
-### 目前支持声线转换和中日英三语TTS的角色
-- [x] 任意角色（只要你有角色的声音样本）
-（注意：声线转换只能在任意两个存在于模型中的说话人之间进行）
-
-
-
-
-## 微调
-建议使用 [Google Colab](https://colab.research.google.com/drive/1pn1xnFfdLK63gVXDwV4zCXfVeo8c-I-0?usp=sharing)
-进行微调任务，因为VITS在多语言情况下的某些环境依赖相当难以配置。
-### 在Google Colab里，我需要花多长时间？
-1. 安装依赖 (3 min)
-2. 选择预训练模型，详细区别参见[Colab 笔记本页面](https://colab.research.google.com/drive/1pn1xnFfdLK63gVXDwV4zCXfVeo8c-I-0?usp=sharing)。
-3. 上传你希望加入的其它角色声音，详细上传方式见[DATA.MD](https://github.com/Plachtaa/VITS-fast-fine-tuning/blob/main/DATA.MD)
-4. 进行微调，根据选择的微调方式和样本数量不同，花费时长可能在20分钟到2小时不等。
-
-微调结束后可以直接下载微调好的模型，日后在本地运行（不需要GPU）
-
-## 本地运行和推理
-0. 记得下载微调好的模型和config文件！
-1. 下载最新的Release包（在Github页面的右侧）
-2. 把下载的模型和config文件放在 `inference`文件夹下, 其文件名分别为 `G_latest.pth` 和 `finetune_speaker.json`。
-3. 一切准备就绪后，文件结构应该如下所示:
-```
-inference
-├───inference.exe
-├───...
-├───finetune_speaker.json
-└───G_latest.pth
-```
-4. 运行 `inference.exe`, 浏览器会自动弹出窗口, 注意其所在路径不能有中文字符或者空格.
-
-## 在MoeGoe使用
-0. MoeGoe以及类似其它VITS推理UI使用的config格式略有不同，需要下载的文件为模型`G_latest.pth`和配置文件`moegoe_config.json`
-1. 按照[MoeGoe](https://github.com/CjangCjengh/MoeGoe)页面的提示配置路径即可使用。
-2. MoeGoe在输入句子时需要使用相应的语言标记包裹句子才能正常合成。（日语用[JA], 中文用[ZH], 英文用[EN]），例如：  
-[JA]こんにちわ。[JA]  
-[ZH]你好！[ZH]  
-[EN]Hello![EN]  
-
diff --git a/spaces/zomehwh/vits-models/utils.py b/spaces/zomehwh/vits-models/utils.py
deleted file mode 100644
index ee4b01ddfbe8173965371b29f770f3e87615fe71..0000000000000000000000000000000000000000
--- a/spaces/zomehwh/vits-models/utils.py
+++ /dev/null
@@ -1,225 +0,0 @@
-import os
-import sys
-import argparse
-import logging
-import json
-import subprocess
-import numpy as np
-import librosa
-import torch
-
-MATPLOTLIB_FLAG = False
-
-logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
-logger = logging
-
-
-def load_checkpoint(checkpoint_path, model, optimizer=None):
-  assert os.path.isfile(checkpoint_path)
-  checkpoint_dict = torch.load(checkpoint_path, map_location='cpu')
-  iteration = checkpoint_dict['iteration']
-  learning_rate = checkpoint_dict['learning_rate']
-  if optimizer is not None:
-    optimizer.load_state_dict(checkpoint_dict['optimizer'])
-  saved_state_dict = checkpoint_dict['model']
-  if hasattr(model, 'module'):
-    state_dict = model.module.state_dict()
-  else:
-    state_dict = model.state_dict()
-  new_state_dict= {}
-  for k, v in state_dict.items():
-    try:
-      new_state_dict[k] = saved_state_dict[k]
-    except:
-      logger.info("%s is not in the checkpoint" % k)
-      new_state_dict[k] = v
-  if hasattr(model, 'module'):
-    model.module.load_state_dict(new_state_dict)
-  else:
-    model.load_state_dict(new_state_dict)
-  logger.info("Loaded checkpoint '{}' (iteration {})" .format(
-    checkpoint_path, iteration))
-  return model, optimizer, learning_rate, iteration
-
-
-def plot_spectrogram_to_numpy(spectrogram):
-  global MATPLOTLIB_FLAG
-  if not MATPLOTLIB_FLAG:
-    import matplotlib
-    matplotlib.use("Agg")
-    MATPLOTLIB_FLAG = True
-    mpl_logger = logging.getLogger('matplotlib')
-    mpl_logger.setLevel(logging.WARNING)
-  import matplotlib.pylab as plt
-  import numpy as np
-
-  fig, ax = plt.subplots(figsize=(10,2))
-  im = ax.imshow(spectrogram, aspect="auto", origin="lower",
-                  interpolation='none')
-  plt.colorbar(im, ax=ax)
-  plt.xlabel("Frames")
-  plt.ylabel("Channels")
-  plt.tight_layout()
-
-  fig.canvas.draw()
-  data = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep='')
-  data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
-  plt.close()
-  return data
-
-
-def plot_alignment_to_numpy(alignment, info=None):
-  global MATPLOTLIB_FLAG
-  if not MATPLOTLIB_FLAG:
-    import matplotlib
-    matplotlib.use("Agg")
-    MATPLOTLIB_FLAG = True
-    mpl_logger = logging.getLogger('matplotlib')
-    mpl_logger.setLevel(logging.WARNING)
-  import matplotlib.pylab as plt
-  import numpy as np
-
-  fig, ax = plt.subplots(figsize=(6, 4))
-  im = ax.imshow(alignment.transpose(), aspect='auto', origin='lower',
-                  interpolation='none')
-  fig.colorbar(im, ax=ax)
-  xlabel = 'Decoder timestep'
-  if info is not None:
-      xlabel += '\n\n' + info
-  plt.xlabel(xlabel)
-  plt.ylabel('Encoder timestep')
-  plt.tight_layout()
-
-  fig.canvas.draw()
-  data = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep='')
-  data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
-  plt.close()
-  return data
-
-
-def load_audio_to_torch(full_path, target_sampling_rate):
-  audio, sampling_rate = librosa.load(full_path, sr=target_sampling_rate, mono=True)
-  return torch.FloatTensor(audio.astype(np.float32))
-
-
-def load_filepaths_and_text(filename, split="|"):
-  with open(filename, encoding='utf-8') as f:
-    filepaths_and_text = [line.strip().split(split) for line in f]
-  return filepaths_and_text
-
-
-def get_hparams(init=True):
-  parser = argparse.ArgumentParser()
-  parser.add_argument('-c', '--config', type=str, default="./configs/base.json",
-                      help='JSON file for configuration')
-  parser.add_argument('-m', '--model', type=str, required=True,
-                      help='Model name')
-
-  args = parser.parse_args()
-  model_dir = os.path.join("./logs", args.model)
-
-  if not os.path.exists(model_dir):
-    os.makedirs(model_dir)
-
-  config_path = args.config
-  config_save_path = os.path.join(model_dir, "config.json")
-  if init:
-    with open(config_path, "r") as f:
-      data = f.read()
-    with open(config_save_path, "w") as f:
-      f.write(data)
-  else:
-    with open(config_save_path, "r") as f:
-      data = f.read()
-  config = json.loads(data)
-
-  hparams = HParams(**config)
-  hparams.model_dir = model_dir
-  return hparams
-
-
-def get_hparams_from_dir(model_dir):
-  config_save_path = os.path.join(model_dir, "config.json")
-  with open(config_save_path, "r") as f:
-    data = f.read()
-  config = json.loads(data)
-
-  hparams =HParams(**config)
-  hparams.model_dir = model_dir
-  return hparams
-
-
-def get_hparams_from_file(config_path):
-  with open(config_path, "r") as f:
-    data = f.read()
-  config = json.loads(data)
-
-  hparams =HParams(**config)
-  return hparams
-
-
-def check_git_hash(model_dir):
-  source_dir = os.path.dirname(os.path.realpath(__file__))
-  if not os.path.exists(os.path.join(source_dir, ".git")):
-    logger.warn("{} is not a git repository, therefore hash value comparison will be ignored.".format(
-      source_dir
-    ))
-    return
-
-  cur_hash = subprocess.getoutput("git rev-parse HEAD")
-
-  path = os.path.join(model_dir, "githash")
-  if os.path.exists(path):
-    saved_hash = open(path).read()
-    if saved_hash != cur_hash:
-      logger.warn("git hash values are different. {}(saved) != {}(current)".format(
-        saved_hash[:8], cur_hash[:8]))
-  else:
-    open(path, "w").write(cur_hash)
-
-
-def get_logger(model_dir, filename="train.log"):
-  global logger
-  logger = logging.getLogger(os.path.basename(model_dir))
-  logger.setLevel(logging.DEBUG)
-
-  formatter = logging.Formatter("%(asctime)s\t%(name)s\t%(levelname)s\t%(message)s")
-  if not os.path.exists(model_dir):
-    os.makedirs(model_dir)
-  h = logging.FileHandler(os.path.join(model_dir, filename))
-  h.setLevel(logging.DEBUG)
-  h.setFormatter(formatter)
-  logger.addHandler(h)
-  return logger
-
-
-class HParams():
-  def __init__(self, **kwargs):
-    for k, v in kwargs.items():
-      if type(v) == dict:
-        v = HParams(**v)
-      self[k] = v
-
-  def keys(self):
-    return self.__dict__.keys()
-
-  def items(self):
-    return self.__dict__.items()
-
-  def values(self):
-    return self.__dict__.values()
-
-  def __len__(self):
-    return len(self.__dict__)
-
-  def __getitem__(self, key):
-    return getattr(self, key)
-
-  def __setitem__(self, key, value):
-    return setattr(self, key, value)
-
-  def __contains__(self, key):
-    return key in self.__dict__
-
-  def __repr__(self):
-    return self.__dict__.__repr__()
diff --git a/spaces/zzz666/ChuanhuChatGPT/run_Windows.bat b/spaces/zzz666/ChuanhuChatGPT/run_Windows.bat
deleted file mode 100644
index 4c18f9ccaeea0af972301ffdf48778641221f76d..0000000000000000000000000000000000000000
--- a/spaces/zzz666/ChuanhuChatGPT/run_Windows.bat
+++ /dev/null
@@ -1,5 +0,0 @@
-@echo off
-echo Opening ChuanhuChatGPT...
-
-REM Open powershell via bat
-start powershell.exe -NoExit -Command "python ./ChuanhuChatbot.py"